Merge branch 'main' into fix/bbl_x2d

* Use GTK sink for Wayland liveview

Keep native Wayland sessions on the GTK backend and use a GTK widget based GStreamer sink for Bambu liveview instead of the Wayland video overlay path, which can render black on NVIDIA/Hyprland.

Keep the existing wxMediaCtrl path for X11 and continue preferring software H.264 decoding while demoting GL and hardware decoder paths that caused liveview crashes.

* Narrow Linux liveview fix to native Wayland

* Tighten native Wayland liveview setup

* Tighten Wayland liveview teardown and rank setup

* Package GStreamer gtksink for Wayland liveview

---------

Co-authored-by: SoftFever <softfeverever@gmail.com>

.clang-format

@@ -5,7 +5,7 @@ Language:        Cpp
 AccessModifierOffset: -4
 AlignAfterOpenBracket: Align
 AlignConsecutiveAssignments: true
-AlignConsecutiveDeclarations: true
+AlignConsecutiveDeclarations: false
 AlignEscapedNewlines: DontAlign
 AlignOperands:   true
 AlignTrailingComments: true

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -11,6 +11,15 @@ body:
         For this, please use the [Feature request](https://github.com/OrcaSlicer/OrcaSlicer/issues/new?assignees=&labels=&projects=&template=feature_request.yml) issue type or you can discuss your idea on our [Discord server](https://discord.gg/P4VE9UY9gJ) with others.
         
         Before filing, please check if the issue already exists (either open or closed) by using the search bar on the issues page. If it does, comment there. Even if it's closed, we can reopen it based on your comment.
+  - type: checkboxes
+    attributes:
+      label: Is this issue reproducible in the latest nightly build?
+      description: >
+        Please verify this issue still happens in the latest nightly build first. It may already be fixed there:
+        [Nightly builds](https://github.com/OrcaSlicer/OrcaSlicer/releases/tag/nightly-builds).
+      options:
+        - label: I have checked the latest nightly build and the issue is still reproducible
+          required: true
   - type: checkboxes
     attributes:
       label: Is there an existing issue for this problem?

.github/pull_request_template.md

@@ -19,3 +19,9 @@
 <!--
 > Please describe the tests that you have conducted to verify the changes made in this PR.
 -->
+
+<!--
+> A guide for users on how to download the artifacts from this PR.
+-->
+
+[How to Download Pull Requests Artifacts for Testing](https://www.orcaslicer.com/wiki/how_to_download_pr_artifacts)

.github/workflows/build_all.yml

@@ -110,7 +110,7 @@ jobs:
         if: ${{ !vars.SELF_HOSTED }}
         uses: ./.github/actions/apt-install-deps
       - name: Restore Test Artifact
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: ${{ github.sha }}-tests
       - uses: lukka/get-cmake@latest
@@ -124,7 +124,7 @@ jobs:
           tar -xvf build_tests.tar
           scripts/run_unit_tests.sh
       - name: Upload Test Logs
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         if: ${{ failure() }}
         with:
           name: unit-test-logs
@@ -136,7 +136,7 @@ jobs:
           files: "ctest_results.xml"
       - name: Delete Test Artifact
         if: success()
-        uses: geekyeggo/delete-artifact@v5
+        uses: geekyeggo/delete-artifact@v6
         with:
           name: ${{ github.sha }}-tests
   flatpak:
@@ -160,6 +160,7 @@ jobs:
             runner: ubuntu-24.04-arm
     # Don't run scheduled builds on forks; skip entirely on self-hosted runners
     if: ${{ !cancelled() && !vars.SELF_HOSTED && (github.event_name != 'schedule' || github.repository == 'OrcaSlicer/OrcaSlicer') }}
+
     runs-on: ${{ matrix.variant.runner }}
     env:
       date:
@@ -188,14 +189,14 @@ jobs:
     # Manage flatpak-builder cache externally so PRs restore but never upload
     - name: Restore flatpak-builder cache
       if: github.event_name == 'pull_request'
-      uses: actions/cache/restore@v4
+      uses: actions/cache/restore@v5
       with:
         path: .flatpak-builder
         key: flatpak-builder-${{ matrix.variant.arch }}-${{ github.event.pull_request.base.sha }}
         restore-keys: flatpak-builder-${{ matrix.variant.arch }}-
     - name: Save/restore flatpak-builder cache
       if: github.event_name != 'pull_request'
-      uses: actions/cache@v4
+      uses: actions/cache@v5
       with:
         path: .flatpak-builder
         key: flatpak-builder-${{ matrix.variant.arch }}-${{ github.sha }}
@@ -218,7 +219,7 @@ jobs:
         arch: ${{ matrix.variant.arch }}
         upload-artifact: false
     - name: Upload artifacts Flatpak
-      uses: actions/upload-artifact@v6
+      uses: actions/upload-artifact@v7
       with:
         name: OrcaSlicer-Linux-flatpak_${{ env.ver }}_${{ matrix.variant.arch }}.flatpak
         path: '/__w/OrcaSlicer/OrcaSlicer/OrcaSlicer-Linux-flatpak_${{ env.ver }}_${{ matrix.variant.arch }}.flatpak'

.github/workflows/build_check_cache.yml

@@ -28,7 +28,7 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v6
         with:
-          lfs: 'true'
+          lfs: 'false'
         
       - name: set outputs
         id: set_outputs

.github/workflows/build_deps.yml

@@ -36,7 +36,7 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v6
         with:
-          lfs: 'true'
+          lfs: 'false'
 
       - name: load cached deps
         uses: actions/cache@v5
@@ -52,7 +52,7 @@ jobs:
 
       - name: setup dev on Windows
         if: runner.os == 'Windows'
-        uses: microsoft/setup-msbuild@v2
+        uses: microsoft/setup-msbuild@v3
 
       - name: Get the date on Ubuntu and macOS
         if: runner.os != 'Windows'

.github/workflows/build_orca.yml

@@ -34,7 +34,7 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v6
         with:
-          lfs: 'true'
+          lfs: 'false'
 
       - name: load cached deps
         if: ${{ !(runner.os == 'macOS' && inputs.macos-combine-only) }}
@@ -125,14 +125,14 @@ jobs:
 
       - name: Upload macOS app bundle ${{ inputs.arch }}
         if: runner.os == 'macOS' && !inputs.macos-combine-only
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_Mac_bundle_${{ inputs.arch }}_${{ github.sha }}
           path: ${{ github.workspace }}/OrcaSlicer_Mac_bundle_${{ inputs.arch }}_${{ github.sha }}.tar.gz
 
       - name: Download macOS app bundles
         if: runner.os == 'macOS' && inputs.macos-combine-only
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           pattern: OrcaSlicer_Mac_bundle_*_${{ github.sha }}
           path: ${{ github.workspace }}/mac_bundles
@@ -155,7 +155,7 @@ jobs:
 
       - name: Delete intermediate per-arch artifacts
         if: runner.os == 'macOS' && inputs.macos-combine-only
-        uses: geekyeggo/delete-artifact@v5
+        uses: geekyeggo/delete-artifact@v6
         with:
           name: |
             OrcaSlicer_Mac_bundle_arm64_${{ github.sha }}
@@ -237,14 +237,14 @@ jobs:
 
       - name: Upload artifacts mac
         if: runner.os == 'macOS' && inputs.macos-combine-only
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_Mac_universal_${{ env.ver }}
           path: ${{ github.workspace }}/OrcaSlicer_Mac_universal_${{ env.ver }}.dmg
 
       - name: Upload OrcaSlicer_profile_validator DMG mac
         if: runner.os == 'macOS' && inputs.macos-combine-only && !vars.SELF_HOSTED
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_profile_validator_Mac_universal_DMG_${{ env.ver }}
           path: ${{ github.workspace }}/OrcaSlicer_profile_validator_Mac_universal_${{ env.ver }}.dmg
@@ -275,7 +275,7 @@ jobs:
 # Windows
       - name: setup MSVC
         if: runner.os == 'Windows'
-        uses: microsoft/setup-msbuild@v2
+        uses: microsoft/setup-msbuild@v3
 
       - name: Install nsis
         if: runner.os == 'Windows' && !vars.SELF_HOSTED
@@ -286,9 +286,10 @@ jobs:
       - name: Build slicer Win
         if: runner.os == 'Windows'
         working-directory: ${{ github.workspace }}
-        env:
-          WindowsSdkDir: 'C:\Program Files (x86)\Windows Kits\10\'
-          WindowsSDKVersion: '10.0.26100.0\'
+        # Orca: Removed Netfabb STL fixing service support in favor of CGAL.
+        # env:
+        #   WindowsSdkDir: 'C:\Program Files (x86)\Windows Kits\10\'
+        #   WindowsSDKVersion: '10.0.26100.0\'
         run: .\build_release_vs.bat slicer
 
       - name: Create installer Win
@@ -311,28 +312,28 @@ jobs:
 
       - name: Upload artifacts Win zip
         if: runner.os == 'Windows'
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_Windows_${{ env.ver }}_portable
           path: ${{ github.workspace }}/build/OrcaSlicer
 
       - name: Upload artifacts Win installer
         if: runner.os == 'Windows' && !vars.SELF_HOSTED
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_Windows_${{ env.ver }}
           path: ${{ github.workspace }}/build/OrcaSlicer*.exe
 
       - name: Upload artifacts Win PDB
         if: runner.os == 'Windows' && !vars.SELF_HOSTED
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: PDB
           path: ${{ github.workspace }}/build/src/Release/Debug_PDB_${{ env.ver }}_for_developers_only.7z
 
       - name: Upload OrcaSlicer_profile_validator Win
         if: runner.os == 'Windows' && !vars.SELF_HOSTED
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_profile_validator_Windows_${{ env.ver }}
           path: ${{ github.workspace }}/build/src/Release/OrcaSlicer_profile_validator.exe
@@ -382,6 +383,7 @@ jobs:
         shell: bash
         run: |
           ./build_linux.sh -istrlL
+          ./scripts/check_appimage_libs.sh ./build/package ./build/package/bin/orca-slicer
           mv -n ./build/OrcaSlicer_Linux_V${{ env.ver_pure }}.AppImage ./build/OrcaSlicer_Linux_AppImage${{ env.ubuntu-ver-str }}_${{ env.ver }}.AppImage
           chmod +x ./build/OrcaSlicer_Linux_AppImage${{ env.ubuntu-ver-str }}_${{ env.ver }}.AppImage
           tar -cvpf build_tests.tar build/tests
@@ -390,7 +392,7 @@ jobs:
         # and doesn't preserve file permissions
       - name: Upload Test Artifact
         if: runner.os == 'Linux'
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: ${{ github.sha }}-tests
           overwrite: true
@@ -398,6 +400,16 @@ jobs:
           retention-days: 5
           if-no-files-found: error
 
+      - name: Run external slicer regression tests
+        if: runner.os == 'Linux'
+        timeout-minutes: 20
+        shell: bash
+        run: |
+          test_repo_dir="${{ runner.temp }}/orca-test-repo"
+          rm -rf "$test_repo_dir"
+          git clone --depth 1 https://github.com/OrcaSlicer/orca-test-repo.git "$test_repo_dir"
+          python3 "$test_repo_dir/run_test.py" "${{ github.workspace }}/build/package/bin/orca-slicer"
+
       - name: Build orca_custom_preset_tests
         if: github.ref == 'refs/heads/main' && runner.os == 'Linux' && !vars.SELF_HOSTED
         working-directory: ${{ github.workspace }}/build/src/Release
@@ -409,14 +421,14 @@ jobs:
 
       - name: Upload artifacts Ubuntu
         if: ${{ ! env.ACT && runner.os == 'Linux' }}
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_Linux_ubuntu_${{ env.ubuntu-ver }}_${{ env.ver }}
           path: './build/OrcaSlicer_Linux_AppImage${{ env.ubuntu-ver-str }}_${{ env.ver }}.AppImage'
 
       - name: Upload OrcaSlicer_profile_validator Ubuntu
         if: ${{ ! env.ACT && runner.os == 'Linux' && !vars.SELF_HOSTED }}
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: OrcaSlicer_profile_validator_Linux_ubuntu_${{ env.ubuntu-ver }}_${{ env.ver }}
           path: './build/src/Release/OrcaSlicer_profile_validator'

.github/workflows/check_profiles.yml

@@ -34,6 +34,46 @@ jobs:
           python3 ./scripts/orca_extra_profile_check.py 2>&1 | tee ${{ runner.temp }}/extra_json_check.log
           exit ${PIPESTATUS[0]}
 
+      - name: Check profile indentation
+        id: indentation_check
+        continue-on-error: true
+        run: |
+          set +e
+          python3 - <<'PY' 2>&1 | tee ${{ runner.temp }}/indentation_check.log
+          import re
+          from pathlib import Path
+          import sys
+
+          profiles_root = Path("resources/profiles")
+          invalid_files = []
+
+          for file_path in sorted(profiles_root.rglob("*.json")):
+            try:
+              for line_number, line in enumerate(file_path.read_text(encoding="utf-8").splitlines(), start=1):
+                if not line.strip():
+                  continue
+                leading_ws = re.match(r"^[ \t]*", line).group(0)
+                if " " in leading_ws:
+                  invalid_files.append((file_path, line_number))
+                  break
+            except Exception as exc:
+              print(f"[ERROR] Unable to read {file_path}: {exc}")
+              invalid_files.append((file_path, 0))
+
+          if invalid_files:
+            for path, line in invalid_files:
+              if line > 0:
+                print(f"[ERROR] Space indentation found in {path}:{line}")
+              else:
+                print(f"[ERROR] Could not validate indentation in {path}")
+            print("Use tab indentation in profile JSON files (1 tab per indentation level).")
+            print("Tip: run python3 ./scripts/orca_filament_lib.py --fix --force to normalize formatting.")
+            sys.exit(1)
+
+          print("All profile JSON files use tab-only indentation.")
+          PY
+          exit ${PIPESTATUS[0]}
+
       # download
       - name: Download
         working-directory: ${{ github.workspace }}
@@ -62,7 +102,7 @@ jobs:
           exit ${PIPESTATUS[0]}
 
       - name: Prepare comment artifact
-        if: ${{ always() && github.event_name == 'pull_request' && (steps.extra_json_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
+        if: ${{ always() && github.event_name == 'pull_request' && (steps.extra_json_check.outcome == 'failure' || steps.indentation_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
         run: |
           mkdir -p ${{ runner.temp }}/profile-check-results
 
@@ -79,6 +119,15 @@ jobs:
               echo ""
             fi
 
+            if [ "${{ steps.indentation_check.outcome }}" = "failure" ]; then
+              echo "### Indentation Check Failed"
+              echo ""
+              echo '```'
+              head -c 30000 ${{ runner.temp }}/indentation_check.log || echo "No output captured"
+              echo '```'
+              echo ""
+            fi
+
             if [ "${{ steps.validate_system.outcome }}" = "failure" ]; then
               echo "### System Profile Validation Failed"
               echo ""
@@ -104,15 +153,15 @@ jobs:
           echo "${{ github.event.pull_request.number }}" > ${{ runner.temp }}/profile-check-results/pr_number.txt
 
       - name: Upload comment artifact
-        if: ${{ always() && github.event_name == 'pull_request' && (steps.extra_json_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
-        uses: actions/upload-artifact@v4
+        if: ${{ always() && github.event_name == 'pull_request' && (steps.extra_json_check.outcome == 'failure' || steps.indentation_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
+        uses: actions/upload-artifact@v7
         with:
           name: profile-check-results
           path: ${{ runner.temp }}/profile-check-results/
           retention-days: 1
 
       - name: Fail if any check failed
-        if: ${{ always() && (steps.extra_json_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
+        if: ${{ always() && (steps.extra_json_check.outcome == 'failure' || steps.indentation_check.outcome == 'failure' || steps.validate_system.outcome == 'failure' || steps.validate_custom.outcome == 'failure') }}
         run: |
           echo "One or more profile checks failed. See above for details."
           exit 1

.github/workflows/check_profiles_comment.yml

@@ -19,7 +19,7 @@ jobs:
     steps:
       - name: Download artifact
         id: download
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         continue-on-error: true
         with:
           name: profile-check-results

.github/workflows/pr-label-bot.yml

@@ -0,0 +1,275 @@
+name: PR Label Bot
+
+on:
+  pull_request_target:
+    types:
+      - opened
+      - reopened
+  issue_comment:
+    types:
+      - created
+
+permissions:
+  contents: read
+  pull-requests: write
+  issues: write
+
+jobs:
+  request-label:
+    if: github.event_name == 'pull_request_target' && github.event.pull_request.author_association != 'COLLABORATOR' && github.event.pull_request.author_association != 'OWNER' && github.event.pull_request.author_association != 'MEMBER'
+    permissions:
+      contents: read
+      pull-requests: write
+      issues: write
+    runs-on: ubuntu-latest
+    steps:
+      - name: Ask PR author for label
+        uses: actions/github-script@v7
+        with:
+          script: |
+            function isPermissionDenied(error) {
+              return error && error.status === 403 && /Resource not accessible by integration/i.test(error.message || '');
+            }
+
+            const allowedLabels = [
+              'bug-fix',
+              'enhancement',
+              'Localization',
+              'profile',
+              'QoL',
+              'UI/UX',
+              'dependencies'
+            ];
+            const pr = context.payload.pull_request;
+            const labelsList = `${allowedLabels
+              .slice(0, -1)
+              .map((label) => `\`${label}\``)
+              .join(', ')} and \`${allowedLabels[allowedLabels.length - 1]}\`.`;
+            const examplesText = [
+              '```',
+              '/bot add-label bug-fix',
+              '```',
+              '```',
+              '/bot add-label bug-fix, UI/UX',
+              '```',
+              '```',
+              '/bot remove-label bug-fix, UI/UX',
+              '```'
+            ].join('\n');
+
+            try {
+              await github.rest.issues.createComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: pr.number,
+                body:
+                  `Hi @${pr.user.login}, you can manage the labels for this PR by \`/bot add-label\` and \`/bot remove-label\`\n\n` +
+                  `Allowed labels are:\n${labelsList}\n\n` +
+                  `Examples:\n${examplesText}`
+              });
+            } catch (error) {
+              if (isPermissionDenied(error)) {
+                core.warning(
+                  'Skipping PR comment because token cannot write. Enable Actions write permissions, ' +
+                  'or run with a token that has issues:write and pull_requests:write.'
+                );
+                return;
+              }
+
+              throw error;
+            }
+
+  apply-label:
+    if: github.event_name == 'issue_comment'
+    permissions:
+      contents: read
+      pull-requests: write
+      issues: write
+    runs-on: ubuntu-latest
+    steps:
+      - name: Apply label command from PR author
+        uses: actions/github-script@v7
+        with:
+          script: |
+            function isPermissionDenied(error) {
+              return error && error.status === 403 && /Resource not accessible by integration/i.test(error.message || '');
+            }
+
+            const allowedLabels = [
+              'bug-fix',
+              'enhancement',
+              'Localization',
+              'profile',
+              'QoL',
+              'UI/UX',
+              'dependencies'
+            ];
+
+            const issue = context.payload.issue;
+            if (!issue.pull_request) {
+              core.info('Ignoring comment that is not on a pull request.');
+              return;
+            }
+
+            const body = (context.payload.comment.body || '').trim();
+            const commandLine = body
+              .split('\n')
+              .map((line) => line.trim())
+              .find((line) => /^\/bot\s+(add-label|remove-label)(?:\s*:\s*|\s+)/i.test(line));
+
+            if (!commandLine) {
+              core.info('No /bot add-label or /bot remove-label command found.');
+              return;
+            }
+
+            const commandMatch = commandLine.match(/^\/bot\s+(add-label|remove-label)(?:\s*:\s*|\s+)(.+)\s*$/i);
+            if (!commandMatch) {
+              core.info('Label command format is invalid.');
+              return;
+            }
+
+            const action = commandMatch[1].toLowerCase() === 'add-label' ? 'add' : 'remove';
+            let labelsExpr = (commandMatch[2] || '').trim();
+            if (!labelsExpr) {
+              core.info('Label command is missing label name.');
+              return;
+            }
+
+            if (labelsExpr.startsWith('[') && labelsExpr.endsWith(']')) {
+              labelsExpr = labelsExpr.slice(1, -1).trim();
+            }
+
+            const requestedRawLabels = labelsExpr
+              .split(',')
+              .map((part) => part.trim())
+              .filter(Boolean);
+
+            if (!requestedRawLabels.length) {
+              core.info('No labels were provided in the command.');
+              return;
+            }
+
+            const { data: pr } = await github.rest.pulls.get({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              pull_number: issue.number
+            });
+
+            const commenter = context.payload.comment.user.login;
+            if (commenter !== pr.user.login) {
+              core.info('Ignoring command because commenter is not the PR author.');
+              return;
+            }
+
+            const labelsByLower = new Map(
+              allowedLabels.map((label) => [label.toLowerCase(), label])
+            );
+
+            const resolvedLabels = [];
+            const invalidLabels = [];
+
+            for (const rawLabel of requestedRawLabels) {
+              const resolved = labelsByLower.get(rawLabel.toLowerCase());
+              if (resolved) {
+                resolvedLabels.push(resolved);
+              } else {
+                invalidLabels.push(rawLabel);
+              }
+            }
+            const uniqueRequestedLabels = [...new Set(resolvedLabels)];
+
+            if (action === 'add' && uniqueRequestedLabels.length) {
+              try {
+                await github.rest.issues.addLabels({
+                  owner: context.repo.owner,
+                  repo: context.repo.repo,
+                  issue_number: issue.number,
+                  labels: uniqueRequestedLabels
+                });
+              } catch (error) {
+                if (isPermissionDenied(error)) {
+                  core.warning(
+                    'Cannot add labels because token cannot write. Enable Actions write permissions, ' +
+                    'or run with a token that has issues:write and pull_requests:write.'
+                  );
+                  return;
+                }
+
+                throw error;
+              }
+
+              core.info(`Added labels: ${uniqueRequestedLabels.join(', ')}`);
+            }
+
+            if (action === 'remove' && uniqueRequestedLabels.length) {
+              let removedCount = 0;
+              try {
+                for (const label of uniqueRequestedLabels) {
+                  try {
+                    await github.rest.issues.removeLabel({
+                      owner: context.repo.owner,
+                      repo: context.repo.repo,
+                      issue_number: issue.number,
+                      name: label
+                    });
+                    removedCount += 1;
+                  } catch (error) {
+                    if (isPermissionDenied(error)) {
+                      core.warning(
+                        'Cannot remove labels because token cannot write. Enable Actions write permissions, ' +
+                        'or run with a token that has issues:write and pull_requests:write.'
+                      );
+                      return;
+                    }
+
+                    if (error.status === 404) {
+                      core.info(`Label is not currently applied: ${label}`);
+                      continue;
+                    }
+
+                    throw error;
+                  }
+                }
+
+                core.info(`Removed labels count: ${removedCount}`);
+              } catch (error) {
+                throw error;
+              }
+            }
+
+            if (!uniqueRequestedLabels.length) {
+              core.info('No valid labels were provided in the command.');
+            }
+
+            if (invalidLabels.length) {
+              const allowedText = allowedLabels.map((label) => `\`${label}\``).join(', ');
+              const invalidText = invalidLabels.map((label) => `\`${label}\``).join(', ');
+              const validText = uniqueRequestedLabels.length
+                ? `\n\nProcessed valid label(s): ${uniqueRequestedLabels.map((label) => `\`${label}\``).join(', ')}`
+                : '';
+
+              try {
+                await github.rest.issues.createComment({
+                  owner: context.repo.owner,
+                  repo: context.repo.repo,
+                  issue_number: issue.number,
+                  body:
+                    `@${commenter} invalid label(s): ${invalidText}.${validText}\n\n` +
+                    `Allowed labels: ${allowedText}\n\n` +
+                    `Use:\n` +
+                    `- \`/bot add-label label\`\n` +
+                    `- \`/bot remove-label label\`\n` +
+                    `- \`/bot add-label label1, label2\``
+                });
+              } catch (error) {
+                if (isPermissionDenied(error)) {
+                  core.warning('Cannot post invalid-label feedback because token cannot write comments.');
+                  return;
+                }
+
+                throw error;
+              }
+            }
+
+            const processedLabelsText = uniqueRequestedLabels.length ? uniqueRequestedLabels.join(', ') : '(none)';
+            core.info(`Processed label command: ${action} ${processedLabelsText}`);

AGENTS.md

@@ -1,23 +1,48 @@
-# Repository Guidelines
+# CLAUDE.md
 
-## Project Structure & Module Organization
-OrcaSlicer’s C++17 sources live in `src/`, split by feature modules and platform adapters. User assets, icons, and printer presets are in `resources/`; translations stay in `localization/`. Tests sit in `tests/`, grouped by domain (`libslic3r/`, `sla_print/`, etc.) with fixtures under `tests/data/`. CMake helpers reside in `cmake/`, and longer references in `doc/` and `SoftFever_doc/`. Automation scripts belong in `scripts/` and `tools/`. Treat everything in `deps/` and `deps_src/` as vendored snapshots—do not modify without mirroring upstream tags.
+OrcaSlicer — open-source C++17 3D slicer. wxWidgets GUI, CMake build system.
 
-## Build, Test, and Development Commands
-Use out-of-source builds:
-- `cmake -S . -B build -DCMAKE_BUILD_TYPE=Release` configures dependencies and generates build files.
-- `cmake --build build --target OrcaSlicer --config Release` compiles the app; add `--parallel` to speed up.
-- `cmake --build build --target tests` then `ctest --test-dir build --output-on-failure` runs automated suites.
-Platform helpers such as `build_linux.sh`, `build_release_macos.sh`, and `build_release_vs2022.bat` wrap the same flow with toolchain flags. Use `build_release_macos.sh -sx` when reproducing macOS build issues, and `scripts/DockerBuild.sh` for reproducible container builds.
+## Build Commands
 
-## Coding Style & Naming Conventions
-`.clang-format` enforces 4-space indents, a 140-column limit, aligned initializers, and brace wrapping for classes and functions. Run `clang-format -i <file>` before committing; the CMake `clang-format` target is available when LLVM tools are on your PATH. Prefer `CamelCase` for classes, `snake_case` for functions and locals, and `SCREAMING_CASE` for constants, matching conventions in `src/`. Keep headers self-contained and align include order with the IWYU pragmas.
+```bash
+# macOS
+cmake --build build/arm64 --config RelWithDebInfo --target all --
 
-## Testing Guidelines
-Unit tests rely on Catch2 (`tests/catch2/`). Name specs after the component under test—for example `tests/libslic3r/TestPlanarHole.cpp`—and tag long-running cases so `ctest -L fast` remains useful. Cover new algorithms with deterministic fixtures or sample G-code stored in `tests/data/`. Document manual printer validation or regression slicer checks in your PR when automated coverage is insufficient.
+# Linux
+cmake --build build --config RelWithDebInfo --target all --
 
-## Commit & Pull Request Guidelines
-The history favors concise, sentence-style subject lines with optional issue references, e.g., `Fix grid lines origin for multiple plates (#10724)`. Squash fixups locally before opening a PR. Complete `.github/pull_request_template.md`, include reproduction steps or screenshots for UI changes, and mention impacted presets or translations. Link issues via `Closes #NNNN` when applicable, and call out dependency bumps or profile migrations for maintainer review.
+# Windows (replace %build_type% with Debug/Release/RelWithDebInfo)
+cmake --build . --config %build_type% --target ALL_BUILD -- -m
+```
 
-## Security & Configuration Tips
-Follow `SECURITY.md` for vulnerability reporting. Keep API tokens and printer credentials out of tracked configs; use `sandboxes/` for experimental settings. When touching third-party code in `deps_src/`, record the upstream commit or release in your PR description and run the relevant platform build script to confirm integration.
+## Testing
+
+Catch2 framework. Tests in `tests/` directory.
+
+```bash
+cd build && ctest --output-on-failure           # all tests
+ctest --test-dir ./tests/libslic3r              # individual suite
+ctest --test-dir ./tests/fff_print
+```
+
+## Code Style
+
+- C++17, selective C++20. PascalCase classes, snake_case functions/variables
+- `#pragma once` for headers. Smart pointers and RAII preferred
+- Parallelization via TBB — be mindful of shared state
+
+## Key Entry Points
+
+- App startup: `src/OrcaSlicer.cpp`
+- Slicing pipeline: `src/libslic3r/Print.cpp`
+- All print/printer/material settings: `src/libslic3r/PrintConfig.cpp`
+- GUI: `src/slic3r/GUI/`
+- Core algorithms: `src/libslic3r/` (GCode/, Fill/, Support/, Geometry/, Format/, Arachne/)
+- Printer profiles: `resources/profiles/[manufacturer].json`
+
+## Critical Constraints
+
+- **Backward compatibility required** for .3mf project files and printer profiles
+- **Cross-platform** — all changes must work on Windows, macOS, and Linux
+- Profile/format changes need version migration handling
+- Dependencies built separately in `deps/build/`, then linked to main app

CLAUDE.md

@@ -1,234 +1 @@
-# CLAUDE.md
-
-This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
-
-## Overview
-
-OrcaSlicer is an open-source 3D slicer application forked from Bambu Studio, built using C++ with wxWidgets for the GUI and CMake as the build system. The project uses a modular architecture with separate libraries for core slicing functionality, GUI components, and platform-specific code.
-
-## Build Commands
-
-### Building on Windows
-**Always use this command to build the project when testing build issues on Windows.**
-```bash
-cmake --build . --config %build_type% --target ALL_BUILD -- -m
-```
-
-### Building on macOS
-**Always use this command to build the project when testing build issues on macOS.**
-```bash
-cmake --build build/arm64 --config RelWithDebInfo --target all --
-```
-
-### Building on Linux
- **Always use this command to build the project when testing build issues on Linux.**
-```bash
-cmake --build build/arm64 --config RelWithDebInfo --target all --
-
-```
-### Build test:
-
-**Always use this command to build the project when testing build issues on Windows.**
-```bash
-cmake --build . --config %build_type% --target ALL_BUILD -- -m
-```
-
-### Building on macOS
-**Always use this command to build the project when testing build issues on macOS.**
-```bash
-cmake --build build/arm64 --config RelWithDebInfo --target all --
-```
-
-### Building on Linux
- **Always use this command to build the project when testing build issues on Linux.**
-```bash
-cmake --build build --config RelWithDebInfo --target all --
-
-```
-
-
-### Build System
-- Uses CMake with minimum version 3.13 (maximum 3.31.x on Windows)
-- Primary build directory: `build/`
-- Dependencies are built in `deps/build/`
-- The build process is split into dependency building and main application building
-- Windows builds use Visual Studio generators
-- macOS builds use Xcode by default, Ninja with -x flag
-- Linux builds use Ninja generator
-
-### Testing
-Tests are located in the `tests/` directory and use the Catch2 testing framework. Test structure:
-- `tests/libslic3r/` - Core library tests (21 test files)
-  - Geometry processing, algorithms, file formats (STL, 3MF, AMF)
-  - Polygon operations, clipper utilities, Voronoi diagrams
-- `tests/fff_print/` - Fused Filament Fabrication tests (12 test files)
-  - Slicing algorithms, G-code generation, print mechanics
-  - Fill patterns, extrusion, support material
-- `tests/sla_print/` - Stereolithography tests (4 test files)
-  - SLA-specific printing algorithms, support generation
-- `tests/libnest2d/` - 2D nesting algorithm tests
-- `tests/slic3rutils/` - Utility function tests
-- `tests/sandboxes/` - Experimental/sandbox test code
-
-Run all tests after building:
-```bash
-cd build && ctest
-```
-
-Run tests with verbose output:
-```bash
-cd build && ctest --output-on-failure
-```
-
-Run individual test suites:
-```bash
-# From build directory
-ctest --test-dir ./tests/libslic3r/libslic3r_tests
-ctest --test-dir ./tests/fff_print/fff_print_tests
-ctest --test-dir ./tests/sla_print/sla_print_tests
-# and so on
-```
-
-## Architecture
-
-### Core Libraries
-- **libslic3r/**: Core slicing engine and algorithms (platform-independent)
-  - Main slicing logic, geometry processing, G-code generation
-  - Key classes: Print, PrintObject, Layer, GCode, Config
-  - Modular design with specialized subdirectories:
-    - `GCode/` - G-code generation, cooling, pressure equalization, thumbnails
-    - `Fill/` - Infill pattern implementations (gyroid, honeycomb, lightning, etc.)
-    - `Support/` - Tree supports and traditional support generation
-    - `Geometry/` - Advanced geometry operations, Voronoi diagrams, medial axis
-    - `Format/` - File I/O for 3MF, AMF, STL, OBJ, STEP formats
-    - `SLA/` - SLA-specific print processing and support generation
-    - `Arachne/` - Advanced wall generation using skeletal trapezoidation
-
-- **src/slic3r/**: Main application framework and GUI
-  - GUI application built with wxWidgets
-  - Integration between libslic3r core and user interface
-  - Located in `src/slic3r/GUI/` (not shown in this directory but exists)
-
-### Key Algorithmic Components
-- **Arachne Wall Generation**: Variable-width perimeter generation using skeletal trapezoidation
-- **Tree Supports**: Organic support generation algorithm  
-- **Lightning Infill**: Sparse infill optimization for internal structures
-- **Adaptive Slicing**: Variable layer height based on geometry
-- **Multi-material**: Multi-extruder and soluble support processing
-- **G-code Post-processing**: Cooling, fan control, pressure advance, conflict checking
-
-### File Format Support
-- **3MF/BBS_3MF**: Native format with extensions for multi-material and metadata
-- **STL**: Standard tessellation language for 3D models
-- **AMF**: Additive Manufacturing Format with color/material support  
-- **OBJ**: Wavefront OBJ with material definitions
-- **STEP**: CAD format support for precise geometry
-- **G-code**: Output format with extensive post-processing capabilities
-
-### External Dependencies
-- **Clipper2**: Advanced 2D polygon clipping and offsetting
-- **libigl**: Computational geometry library for mesh operations
-- **TBB**: Intel Threading Building Blocks for parallelization
-- **wxWidgets**: Cross-platform GUI framework
-- **OpenGL**: 3D graphics rendering and visualization
-- **CGAL**: Computational Geometry Algorithms Library (selective use)
-- **OpenVDB**: Volumetric data structures for advanced operations
-- **Eigen**: Linear algebra library for mathematical operations
-
-## File Organization
-
-### Resources and Configuration
-- `resources/profiles/` - Printer and material profiles organized by manufacturer
-- `resources/printers/` - Printer-specific configurations and G-code templates  
-- `resources/images/` - UI icons, logos, calibration images
-- `resources/calib/` - Calibration test patterns and data
-- `resources/handy_models/` - Built-in test models (benchy, calibration cubes)
-
-### Internationalization and Localization  
-- `localization/i18n/` - Source translation files (.pot, .po)
-- `resources/i18n/` - Runtime language resources
-- Translation managed via `scripts/run_gettext.sh` / `scripts/run_gettext.bat`
-
-### Platform-Specific Code
-- `src/libslic3r/Platform.cpp` - Platform abstractions and utilities
-- `src/libslic3r/MacUtils.mm` - macOS-specific utilities (Objective-C++)
-- Windows-specific build scripts and configurations
-- Linux distribution support scripts in `scripts/linux.d/`
-
-### Build and Development Tools
-- `cmake/modules/` - Custom CMake find modules and utilities
-- `scripts/` - Python utilities for profile generation and validation  
-- `tools/` - Windows build tools (gettext utilities)
-- `deps/` - External dependency build configurations
-
-## Development Workflow
-
-### Code Style and Standards
-- **C++17 standard** with selective C++20 features
-- **Naming conventions**: PascalCase for classes, snake_case for functions/variables
-- **Header guards**: Use `#pragma once` 
-- **Memory management**: Prefer smart pointers, RAII patterns
-- **Thread safety**: Use TBB for parallelization, be mindful of shared state
-
-### Common Development Tasks
-
-#### Adding New Print Settings
-1. Define setting in `PrintConfig.cpp` with proper bounds and defaults
-2. Add UI controls in appropriate GUI components  
-3. Update serialization in config save/load
-4. Add tooltips and help text for user guidance
-5. Test with different printer profiles
-
-#### Modifying Slicing Algorithms  
-1. Core algorithms live in `libslic3r/` subdirectories
-2. Performance-critical code should be profiled and optimized
-3. Consider multi-threading implications (TBB integration)
-4. Validate changes don't break existing profiles
-5. Add regression tests where appropriate
-
-#### GUI Development
-1. GUI code resides in `src/slic3r/GUI/` (not visible in current tree)
-2. Use existing wxWidgets patterns and custom controls
-3. Support both light and dark themes
-4. Consider DPI scaling on high-resolution displays
-5. Maintain cross-platform compatibility
-
-#### Adding Printer Support
-1. Create JSON profile in `resources/profiles/[manufacturer].json`
-2. Add printer-specific start/end G-code templates
-3. Configure build volume, capabilities, and material compatibility
-4. Test thoroughly with actual hardware when possible
-5. Follow existing profile structure and naming conventions
-
-### Dependencies and Build System
-- **CMake-based** with separate dependency building phase
-- **Dependencies** built once in `deps/build/`, then linked to main application  
-- **Cross-platform** considerations important for all changes
-- **Resource files** embedded at build time, platform-specific handling
-
-### Performance Considerations
-- **Slicing algorithms** are CPU-intensive, profile before optimizing
-- **Memory usage** can be substantial with complex models
-- **Multi-threading** extensively used via TBB
-- **File I/O** optimized for large 3MF files with embedded textures
-- **Real-time preview** requires efficient mesh processing
-
-## Important Development Notes
-
-### Codebase Navigation
-- Use search tools extensively - codebase has 500k+ lines
-- Key entry points: `src/OrcaSlicer.cpp` for application startup
-- Core slicing: `libslic3r/Print.cpp` orchestrates the slicing pipeline
-- Configuration: `PrintConfig.cpp` defines all print/printer/material settings
-
-### Compatibility and Stability
-- **Backward compatibility** maintained for project files and profiles
-- **Cross-platform** support essential (Windows/macOS/Linux)  
-- **File format** changes require careful version handling
-- **Profile migrations** needed when settings change significantly
-
-### Quality and Testing
-- **Regression testing** important due to algorithm complexity
-- **Performance benchmarks** help catch performance regressions
-- **Memory leak** detection important for long-running GUI application
-- **Cross-platform** testing required before releases
+@AGENTS.md

CMakeLists.txt

@@ -1,13 +1,9 @@
 if(${CMAKE_VERSION} VERSION_GREATER_EQUAL "4.0")
-    set(CMAKE_POLICY_VERSION_MINIMUM 3.5 CACHE STRING "" FORCE)
+    set(CMAKE_POLICY_VERSION_MINIMUM 3.13 CACHE STRING "" FORCE)
 endif()
 
 cmake_minimum_required(VERSION 3.13)
 
-# Verify that your CMake version is exactly 3.5 series or higher on windows
-if ( (MSVC OR WIN32) AND (${CMAKE_VERSION} VERSION_LESS "3.5") )
-    message(FATAL_ERROR "CMake current version ${CMAKE_VERSION} is too old. Minimum required is 3.5.")
-endif()
 
 # The following line used to be in tests/CMakeLists.txt
 # Having it there causes rebuilds of all targets on any CMakeLists.txt change under tests/
@@ -121,11 +117,10 @@ else()
     set(SLIC3R_STATIC_INITIAL 1)
 endif()
 
-option(SLIC3R_STATIC 			"Compile OrcaSlicer with static libraries (Boost, TBB, glew)" ${SLIC3R_STATIC_INITIAL})
-option(SLIC3R_GUI    			"Compile OrcaSlicer with GUI components (OpenGL, wxWidgets)" 1)
+option(SLIC3R_STATIC            "Compile OrcaSlicer with static libraries (Boost, TBB)" ${SLIC3R_STATIC_INITIAL})
+option(SLIC3R_GUI               "Compile OrcaSlicer with GUI components (OpenGL, wxWidgets)" 1)
 option(SLIC3R_FHS               "Assume OrcaSlicer is to be installed in a FHS directory structure" 0)
-option(SLIC3R_WX_STABLE         "Build against wxWidgets stable (3.0) as oppsed to dev (3.1) on Linux" 0)
-option(SLIC3R_PROFILE 			"Compile OrcaSlicer with an invasive Shiny profiler" 0)
+option(SLIC3R_PROFILE           "Compile OrcaSlicer with an invasive Shiny profiler" 0)
 option(SLIC3R_PCH               "Use precompiled headers" 1)
 option(SLIC3R_MSVC_COMPILE_PARALLEL "Compile on Visual Studio in parallel" 1)
 option(SLIC3R_MSVC_PDB          "Generate PDB files on MSVC in Release mode" 1)
@@ -328,43 +323,44 @@ set(CMAKE_POSITION_INDEPENDENT_CODE ON)
 
 # WIN10SDK_PATH is used to point CMake to the WIN10 SDK installation directory.
 # We pick it from environment if it is not defined in another way
-if(WIN32)
-    if(NOT DEFINED WIN10SDK_PATH)
-        if(DEFINED ENV{WIN10SDK_PATH})
-                set(WIN10SDK_PATH "$ENV{WIN10SDK_PATH}")
-        endif()
-    endif()
-    if(DEFINED WIN10SDK_PATH)
-        #BBS: modify win10sdk_path
-        if (EXISTS "${WIN10SDK_PATH}/winrt/windows.graphics.printing3d.h")
-            set(WIN10SDK_INCLUDE_PATH "${WIN10SDK_PATH}")
-        else()
-            message("WIN10SDK_PATH is invalid: ${WIN10SDK_PATH}")
-            message("${WIN10SDK_PATH}/winrt/windows.graphics.printing3d.h was not found")
-            message("STL fixing by the Netfabb service will not be compiled")
-            unset(WIN10SDK_PATH)
-        endif()
-    else()
-        # Try to use the default Windows 10 SDK path.
-        if (DEFINED ENV{WindowsSdkDir} AND DEFINED ENV{WindowsSDKVersion})
-            set(WIN10SDK_INCLUDE_PATH "$ENV{WindowsSdkDir}/Include/$ENV{WindowsSDKVersion}")
-        else ()
-            set(WIN10SDK_INCLUDE_PATH "C:/Program Files (x86)/Windows Kits/10/Include/10.0.26100.0")
-        endif ()
-        if (NOT EXISTS "${WIN10SDK_INCLUDE_PATH}/winrt/windows.graphics.printing3d.h")
-            message("${WIN10SDK_INCLUDE_PATH}/winrt/windows.graphics.printing3d.h was not found")
-            message("STL fixing by the Netfabb service will not be compiled")
-            unset(WIN10SDK_INCLUDE_PATH)
-        endif()
-    endif()
-    if(WIN10SDK_INCLUDE_PATH)
-        message("Building with Win10 Netfabb STL fixing service support")
-        add_definitions(-DHAS_WIN10SDK)
-        include_directories(SYSTEM "${WIN10SDK_INCLUDE_PATH}")
-    else()
-        message("Building without Win10 Netfabb STL fixing service support")
-    endif()
-endif()
+# ORCA: Removed Netfabb STL fixing service support in favor of CGAL.
+# if(WIN32)
+#     if(NOT DEFINED WIN10SDK_PATH)
+#         if(DEFINED ENV{WIN10SDK_PATH})
+#                 set(WIN10SDK_PATH "$ENV{WIN10SDK_PATH}")
+#         endif()
+#     endif()
+#     if(DEFINED WIN10SDK_PATH)
+#         #BBS: modify win10sdk_path
+#         if (EXISTS "${WIN10SDK_PATH}/winrt/windows.graphics.printing3d.h")
+#             set(WIN10SDK_INCLUDE_PATH "${WIN10SDK_PATH}")
+#         else()
+#             message("WIN10SDK_PATH is invalid: ${WIN10SDK_PATH}")
+#             message("${WIN10SDK_PATH}/winrt/windows.graphics.printing3d.h was not found")
+#             message("STL fixing by the Netfabb service will not be compiled")
+#             unset(WIN10SDK_PATH)
+#         endif()
+#     else()
+#         # Try to use the default Windows 10 SDK path.
+#         if (DEFINED ENV{WindowsSdkDir} AND DEFINED ENV{WindowsSDKVersion})
+#             set(WIN10SDK_INCLUDE_PATH "$ENV{WindowsSdkDir}/Include/$ENV{WindowsSDKVersion}")
+#         else ()
+#             set(WIN10SDK_INCLUDE_PATH "C:/Program Files (x86)/Windows Kits/10/Include/10.0.26100.0")
+#         endif ()
+#         if (NOT EXISTS "${WIN10SDK_INCLUDE_PATH}/winrt/windows.graphics.printing3d.h")
+#             message("${WIN10SDK_INCLUDE_PATH}/winrt/windows.graphics.printing3d.h was not found")
+#             message("STL fixing by the Netfabb service will not be compiled")
+#             unset(WIN10SDK_INCLUDE_PATH)
+#         endif()
+#     endif()
+#     if(WIN10SDK_INCLUDE_PATH)
+#         message("Building with Win10 Netfabb STL fixing service support")
+#         add_definitions(-DHAS_WIN10SDK)
+#         include_directories(SYSTEM "${WIN10SDK_INCLUDE_PATH}")
+#     else()
+#         message("Building without Win10 Netfabb STL fixing service support")
+#     endif()
+# endif()
 
 if (APPLE)
     message("OS X SDK Path: ${CMAKE_OSX_SYSROOT}")
@@ -378,11 +374,6 @@ endif ()
 if (CMAKE_SYSTEM_NAME STREQUAL "Linux")
     find_package(PkgConfig REQUIRED)
 
-    if (CMAKE_VERSION VERSION_LESS "3.1")
-        # Workaround for an old CMake, which does not understand CMAKE_CXX_STANDARD.
-        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
-    endif()
-
     # Boost on Raspberry-Pi does not link to pthreads.
     set(THREADS_PREFER_PTHREAD_FLAG ON)
     find_package(Threads REQUIRED)
@@ -585,6 +576,9 @@ endif()
 set(Boost_NO_SYSTEM_PATHS TRUE)
 find_package(Boost 1.83.0 REQUIRED COMPONENTS system filesystem thread log log_setup locale regex chrono atomic date_time iostreams program_options nowide)
 
+# Find and configure Eigen3
+find_package(Eigen3 5.0.1 REQUIRED)
+
 add_library(boost_libs INTERFACE)
 add_library(boost_headeronly INTERFACE)
 
@@ -669,16 +663,6 @@ endif()
 
 ## OPTIONAL packages
 
-# Find eigen3 or use bundled version
-if (NOT SLIC3R_STATIC)
-    find_package(Eigen3 3.3)
-endif ()
-if (NOT EIGEN3_FOUND)
-    set(EIGEN3_FOUND 1)
-    set(EIGEN3_INCLUDE_DIR ${LIBDIR}/eigen/)
-endif ()
-include_directories(BEFORE SYSTEM ${EIGEN3_INCLUDE_DIR})
-
 # Find expat or use bundled version
 # Always use the system libexpat on Linux.
 
@@ -704,16 +688,6 @@ if(APPLE AND CMAKE_VERSION VERSION_GREATER_EQUAL "4.0")
     set(OPENGL_LIBRARIES "-framework OpenGL" CACHE STRING "OpenGL framework" FORCE)
 endif()
 
-set(GLEW_ROOT "${CMAKE_PREFIX_PATH}")
-message("GLEW_ROOT: ${GLEW_ROOT}")
-# Find glew or use bundled version
-if (SLIC3R_STATIC AND NOT SLIC3R_STATIC_EXCLUDE_GLEW)
-    set(GLEW_USE_STATIC_LIBS ON)
-    set(GLEW_VERBOSE ON)
-endif()
-
-find_package(GLEW REQUIRED)
-
 find_package(glfw3 REQUIRED)
 
 # Find the Cereal serialization library
@@ -732,7 +706,7 @@ add_custom_target(gettext_make_pot
     COMMAND xgettext --keyword=L --keyword=_L --keyword=_u8L --keyword=L_CONTEXT:1,2c --keyword=_L_PLURAL:1,2 --add-comments=TRN --from-code=UTF-8 --no-location --debug --boost
         -f "${BBL_L18N_DIR}/list.txt"
         -o "${BBL_L18N_DIR}/OrcaSlicer.pot"
-	COMMAND hintsToPot ${SLIC3R_RESOURCES_DIR} ${BBL_L18N_DIR}
+    COMMAND hintsToPot ${SLIC3R_RESOURCES_DIR} ${BBL_L18N_DIR}
     WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}
     COMMENT "Generate pot file from strings in the source tree"
 )
@@ -804,8 +778,10 @@ function(orcaslicer_copy_dlls target config postfix output_dlls)
         set(_arch "x64")
     elseif ("${CMAKE_SYSTEM_PROCESSOR}" STREQUAL "X86")
         set(_arch "x86")
+    elseif ("${CMAKE_SYSTEM_PROCESSOR}" STREQUAL "ARM64")
+        set(_arch "arm64")
     else ()
-        message(FATAL_ERROR "Unable to detect architecture")
+        message(FATAL_ERROR "Unable to detect architecture: ${CMAKE_SYSTEM_PROCESSOR}")
     endif ()
 
     get_property(_is_multi GLOBAL PROPERTY GENERATOR_IS_MULTI_CONFIG)
@@ -929,7 +905,7 @@ elseif (SLIC3R_FHS)
     install(DIRECTORY ${SLIC3R_RESOURCES_DIR}/ DESTINATION ${SLIC3R_FHS_RESOURCES}
         PATTERN "*/udev" EXCLUDE
     )
-    install(FILES src/dev-utils/platform/unix/OrcaSlicer.desktop DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/applications)
+    install(FILES src/dev-utils/platform/unix/com.orcaslicer.OrcaSlicer.desktop DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/applications)
     foreach(SIZE 32 128 192)
         install(FILES ${SLIC3R_RESOURCES_DIR}/images/OrcaSlicer_${SIZE}px.png
             DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/icons/hicolor/${SIZE}x${SIZE}/apps RENAME OrcaSlicer.png
@@ -938,7 +914,7 @@ elseif (SLIC3R_FHS)
 elseif (CMAKE_MACOSX_BUNDLE)
     # install(DIRECTORY "${SLIC3R_RESOURCES_DIR}/" DESTINATION "${CMAKE_INSTALL_PREFIX}/OrcaSlicer.app/Contents/resources")
 else ()
-    install(FILES src/dev-utils/platform/unix/OrcaSlicer.desktop DESTINATION ${CMAKE_INSTALL_PREFIX}/resources/applications)
+    install(FILES src/dev-utils/platform/unix/com.orcaslicer.OrcaSlicer.desktop DESTINATION ${CMAKE_INSTALL_PREFIX}/resources/applications)
     install(DIRECTORY "${SLIC3R_RESOURCES_DIR}/" DESTINATION "${CMAKE_INSTALL_PREFIX}/resources")
 endif ()
 

README.md

@@ -44,7 +44,7 @@ If you come across any of these in search results, please <b>report them</b> as
 
 # Main features
 
-- **[Advanced Calibration Tools](https://www.orcaslicer.com/wiki/Calibration)**  
+- **[Advanced Calibration Tools](https://www.orcaslicer.com/wiki/calibration_guide)**  
   Comprehensive suite: temperature towers, flow rate, retraction & more for optimal performance.
 - **[Precise Wall](https://www.orcaslicer.com/wiki/quality_settings_precision#precise-wall) and [Seam Control](https://www.orcaslicer.com/wiki/quality_settings_seam)**  
   Adjust outer wall spacing and apply scarf seams to enhance print accuracy.
@@ -71,7 +71,7 @@ If you come across any of these in search results, please <b>report them</b> as
 The [wiki](https://www.orcaslicer.com/wiki) aims to provide a detailed explanation of the slicer settings, including how to maximize their use and how to calibrate and set up your printer.
 
 - **[Access the wiki here](https://www.orcaslicer.com/wiki)**
-- **[Contribute to the wiki](https://www.orcaslicer.com/wiki/How-to-wiki)**
+- **[Contribute to the wiki](https://www.orcaslicer.com/wiki/how_to_wiki)**
 
 # Download
 
@@ -137,14 +137,32 @@ winget install --id=SoftFever.OrcaSlicer -e
             ![mac_security_setting](./SoftFever_doc/mac_security_setting.png)
     </details>
 
-## Linux (Ubuntu)
+## Linux         
 
- 1. If you run into trouble executing it, try this command in the terminal:
+### Flathub (Recommended)
+OrcaSlicer is available through FlatHub:
+
+<a href='https://flathub.org/apps/com.orcaslicer.OrcaSlicer'><img width='240' alt='Download on Flathub' src='https://dl.flathub.org/assets/badges/flathub-badge-en.png'/></a>
+
+Install from the command line:
+
+```shell
+flatpak install flathub com.orcaslicer.OrcaSlicer
+flatpak run com.orcaslicer.OrcaSlicer
+```
+
+It can also be installed through graphical software managers (KDE Discover, GNOME Software, etc.) when Flathub is enabled. Search for **OrcaSlicer** in your software center.
+
+### AppImage
+ 1. Download App image from the [releases page](https://github.com/OrcaSlicer/OrcaSlicer/releases).
+ 2. Double click the downloaded file to run it.
+
+ 3. If you run into trouble executing it, try this command in the terminal:
     `chmod +x /path_to_appimage/OrcaSlicer_Linux.AppImage`
 
 # How to Compile
 
-All updated build instructions for Windows, macOS, and Linux are now available on the official [OrcaSlicer Wiki - How to build](https://www.orcaslicer.com/wiki/How-to-build) page.
+All updated build instructions for Windows, macOS, and Linux are now available on the official [OrcaSlicer Wiki - How to build](https://www.orcaslicer.com/wiki/how_to_build) page.
 
 Please refer to the wiki to ensure you're following the latest and most accurate steps for your platform.
 

build_linux.sh

@@ -8,7 +8,7 @@ SCRIPT_PATH=$(dirname "$(readlink -f "${0}")")
 pushd "${SCRIPT_PATH}" > /dev/null
 
 function usage() {
-    echo "Usage: ./${SCRIPT_NAME} [-1][-b][-c][-d][-D][-e][-h][-i][-j N][-p][-r][-s][-t][-u][-l][-L]"
+    echo "Usage: ./${SCRIPT_NAME} [-1][-b][-c][-d][-D][-e][-F][-g][-h][-i][-j N][-p][-r][-s][-t][-u][-l][-L]"
     echo "   -1: limit builds to one core (where possible)"
     echo "   -j N: limit builds to N cores (where possible)"
     echo "   -b: build in Debug mode"
@@ -17,6 +17,8 @@ function usage() {
     echo "   -d: download and build dependencies in ./deps/ (build prerequisite)"
     echo "   -D: dry run"
     echo "   -e: build in RelWithDebInfo mode"
+    echo "   -F: rebuild the cached Docker/Podman runner image from scratch when used with -g"
+    echo "   -g: run the requested build steps inside a Docker/Podman Ubuntu 24.04 container similar to the GitHub Actions Linux runner"
     echo "   -h: prints this help text"
     echo "   -i: build the Orca Slicer AppImage (optional)"
     echo "   -p: boost ccache hit rate by disabling precompiled headers (default: ON)"
@@ -28,6 +30,9 @@ function usage() {
     echo "   -L: use ld.lld as linker (if available)"
     echo "For a first use, you want to './${SCRIPT_NAME} -u'"
     echo "   and then './${SCRIPT_NAME} -dsi'"
+    echo "For a GitHub Actions-like Linux build locally, use './${SCRIPT_NAME} -g -istrlL'"
+    echo "Use './${SCRIPT_NAME} -gF -istrlL' to rebuild the cached runner image first."
+    echo "Set ORCA_CONTAINER_CLI, ORCA_DOCKER_IMAGE, ORCA_DOCKER_BASE_IMAGE, or ORCA_DOCKER_CMAKE_VERSION to override the container runtime, cached image tag, base image, or CMake version."
 }
 
 SLIC3R_PRECOMPILED_HEADERS="ON"
@@ -35,60 +40,83 @@ SLIC3R_PRECOMPILED_HEADERS="ON"
 unset name
 BUILD_DIR=build
 BUILD_CONFIG=Release
-while getopts ":1j:bcCdDehiprstulL" opt ; do
+FORWARDED_ARGS=()
+while getopts ":1j:bcCdDeFghiprstulL" opt ; do
   case ${opt} in
     1 )
         export CMAKE_BUILD_PARALLEL_LEVEL=1
+        FORWARDED_ARGS+=("-1")
         ;;
     j )
         export CMAKE_BUILD_PARALLEL_LEVEL=$OPTARG
+        FORWARDED_ARGS+=("-j" "$OPTARG")
         ;;
     b )
         BUILD_DIR=build-dbg
         BUILD_CONFIG=Debug
+        FORWARDED_ARGS+=("-b")
         ;;
     c )
         CLEAN_BUILD=1
+        FORWARDED_ARGS+=("-c")
         ;;
     C )
         COLORED_OUTPUT="-DCOLORED_OUTPUT=ON"
+        FORWARDED_ARGS+=("-C")
         ;;
     d )
         BUILD_DEPS="1"
+        FORWARDED_ARGS+=("-d")
         ;;
     D )
         DRY_RUN="1"
+        FORWARDED_ARGS+=("-D")
         ;;
     e )
         BUILD_DIR=build-dbginfo
         BUILD_CONFIG=RelWithDebInfo
+        FORWARDED_ARGS+=("-e")
+        ;;
+    F )
+        CLEAN_DOCKER_IMAGE="1"
+        ;;
+    g )
+        USE_DOCKER="1"
         ;;
     h ) usage
         exit 1
         ;;
     i )
         BUILD_IMAGE="1"
+        FORWARDED_ARGS+=("-i")
         ;;
     p )
         SLIC3R_PRECOMPILED_HEADERS="OFF"
+        FORWARDED_ARGS+=("-p")
         ;;
     r )
         SKIP_RAM_CHECK="1"
+        FORWARDED_ARGS+=("-r")
         ;;
     s )
         BUILD_ORCA="1"
+        FORWARDED_ARGS+=("-s")
         ;;
     t )
         BUILD_TESTS="1"
+        FORWARDED_ARGS+=("-t")
         ;;
     u )
         export UPDATE_LIB="1"
+        FORWARDED_ARGS+=("-u")
         ;;
     l )
         USE_CLANG="1"
+        FORWARDED_ARGS+=("-l")
         ;;
     L )
         USE_LLD="1"
+        FORWARDED_ARGS+=("-L")
         ;;
     * )
 	echo "Unknown argument '${opt}', aborting."
@@ -102,6 +130,11 @@ if [ ${OPTIND} -eq 1 ] ; then
     exit 1
 fi
 
+if [[ -n "${CLEAN_DOCKER_IMAGE}" ]] && [[ -z "${USE_DOCKER}" ]] ; then
+    echo "Error: -F requires -g."
+    exit 1
+fi
+
 function check_available_memory_and_disk() {
     FREE_MEM_GB=$(free --gibi --total | grep 'Mem' | rev | cut --delimiter=" " --fields=1 | rev)
     MIN_MEM_GB=10
@@ -139,6 +172,275 @@ function print_and_run() {
     fi
 }
 
+function resolve_container_cli() {
+    if [[ -n "${ORCA_CONTAINER_CLI}" ]] ; then
+        if ! command -v "${ORCA_CONTAINER_CLI}" >/dev/null 2>&1 ; then
+            echo "Error: container runtime '${ORCA_CONTAINER_CLI}' was not found." >&2
+            exit 1
+        fi
+
+        echo "${ORCA_CONTAINER_CLI}"
+        return
+    fi
+
+    if command -v docker >/dev/null 2>&1 ; then
+        echo "docker"
+        return
+    fi
+
+    if command -v podman >/dev/null 2>&1 ; then
+        echo "podman"
+        return
+    fi
+
+    echo "Error: neither docker nor podman is available. Install one of them or set ORCA_CONTAINER_CLI." >&2
+    exit 1
+}
+
+function get_docker_runner_image() {
+    local base_image
+    local docker_cmake_version
+    local recipe_hash
+    local sanitized_base_image
+    local sanitized_cmake_version
+
+    if [[ -n "${ORCA_DOCKER_IMAGE}" ]] ; then
+        echo "${ORCA_DOCKER_IMAGE}"
+        return
+    fi
+
+    base_image="${ORCA_DOCKER_BASE_IMAGE:-ubuntu:24.04}"
+    docker_cmake_version="${ORCA_DOCKER_CMAKE_VERSION-4.3.0}"
+    recipe_hash=$(find "${SCRIPT_PATH}/build_linux.sh" "${SCRIPT_PATH}/scripts/linux.d" -type f -print0 | sort -z | xargs -0 cat | sha256sum | cut -c1-12)
+    sanitized_base_image=$(echo "${base_image}" | tr '/:@' '---' | tr -cs 'A-Za-z0-9_.-' '-')
+    sanitized_cmake_version=$(echo "${docker_cmake_version:-system}" | tr -cs 'A-Za-z0-9_.-' '-')
+    echo "orcaslicer-linux-builder:${sanitized_base_image}-cmake-${sanitized_cmake_version}-${recipe_hash}"
+}
+
+function docker_runner_dockerfile() {
+    cat <<'EOF'
+ARG BASE_IMAGE=ubuntu:24.04
+FROM ${BASE_IMAGE}
+
+ARG CMAKE_VERSION=4.3.0
+
+ENV DEBIAN_FRONTEND=noninteractive
+SHELL ["/bin/bash", "-c"]
+
+RUN apt-get update && apt-get install -y sudo ca-certificates curl tar
+
+COPY build_linux.sh /tmp/orcaslicer/build_linux.sh
+COPY scripts/linux.d /tmp/orcaslicer/scripts/linux.d
+
+WORKDIR /tmp/orcaslicer
+
+RUN chmod +x ./build_linux.sh
+RUN ./build_linux.sh -ur
+RUN if [[ -n "${CMAKE_VERSION}" ]] ; then \
+        case "$(uname -m)" in \
+            x86_64|amd64) cmake_arch="x86_64" ;; \
+            aarch64|arm64) cmake_arch="aarch64" ;; \
+            *) cmake_arch="" ;; \
+        esac ; \
+        if [[ -n "${cmake_arch}" ]] ; then \
+            cmake_root="/opt/cmake-${CMAKE_VERSION}-linux-${cmake_arch}" ; \
+            if ! curl -fsSL "https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-linux-${cmake_arch}.tar.gz" | tar -xz -C /opt ; then \
+                echo "Warning: failed to install CMake ${CMAKE_VERSION}; falling back to the distro cmake package." ; \
+            elif [[ -d "${cmake_root}" ]] ; then \
+                ln -sf "${cmake_root}/bin/"* /usr/local/bin/ ; \
+            fi ; \
+        else \
+            echo "Skipping GitHub Actions CMake install for unsupported architecture $(uname -m)." ; \
+        fi ; \
+    fi
+RUN rm -rf /var/lib/apt/lists/* /tmp/orcaslicer
+EOF
+}
+
+function ensure_docker_runner_image() {
+    local container_cli
+    local base_image
+    local runner_image
+    local docker_cmake_version
+    local image_exists="0"
+    local force_rebuild="0"
+    local -a build_cmd
+
+    container_cli="$1"
+    runner_image="$2"
+    base_image="${ORCA_DOCKER_BASE_IMAGE:-ubuntu:24.04}"
+    docker_cmake_version="${ORCA_DOCKER_CMAKE_VERSION-4.3.0}"
+
+    if "${container_cli}" image inspect "${runner_image}" >/dev/null 2>&1 ; then
+        image_exists="1"
+    fi
+
+    if [[ -n "${CLEAN_DOCKER_IMAGE}" ]] ; then
+        force_rebuild="1"
+        if [[ "${image_exists}" == "1" ]] ; then
+            echo "Removing cached container image ${runner_image} ..."
+            if [[ -z "${DRY_RUN}" ]] ; then
+                "${container_cli}" image rm -f "${runner_image}" >/dev/null
+            else
+                printf '%q ' "${container_cli}" image rm -f "${runner_image}"
+                echo
+            fi
+            image_exists="0"
+        fi
+    fi
+
+    if [[ "${image_exists}" == "1" ]] ; then
+        echo "Using cached container image ${runner_image}"
+        return
+    fi
+
+    build_cmd=(
+        "${container_cli}" build --pull
+        -t "${runner_image}"
+        --build-arg "BASE_IMAGE=${base_image}"
+        --build-arg "CMAKE_VERSION=${docker_cmake_version}"
+    )
+    if [[ "${force_rebuild}" == "1" ]] ; then
+        build_cmd+=(--no-cache)
+    fi
+    build_cmd+=(-f - "${SCRIPT_PATH}")
+
+    printf '%q ' "${build_cmd[@]}"
+    echo
+    if [[ -n "${DRY_RUN}" ]] ; then
+        return
+    fi
+
+    docker_runner_dockerfile | "${build_cmd[@]}"
+}
+
+function run_in_docker() {
+    local container_cli
+    local runner_image
+    local container_workspace
+    local host_uid
+    local host_gid
+    local host_user
+    local -a build_args
+    local -a container_env
+
+    container_cli=$(resolve_container_cli)
+    runner_image=$(get_docker_runner_image)
+    host_uid=$(id -u)
+    host_gid=$(id -g)
+    host_user="${USER:-orca}"
+    container_workspace="/__w/OrcaSlicer/OrcaSlicer"
+    build_args=()
+    for item in "${FORWARDED_ARGS[@]}" ; do
+        if [[ "${item}" == "-u" ]] || [[ "${item}" == "-D" ]] ; then
+            continue
+        fi
+
+        build_args+=("${item}")
+    done
+
+    container_env=(
+        -e "CI=true"
+        -e "GITHUB_ACTIONS=true"
+        -e "GITHUB_WORKSPACE=${container_workspace}"
+        -e "RUNNER_OS=Linux"
+        -e "RUNNER_TEMP=/tmp"
+        -e "HOST_UID=${host_uid}"
+        -e "HOST_GID=${host_gid}"
+        -e "HOST_USER=${host_user}"
+    )
+    if [[ -n "${CMAKE_BUILD_PARALLEL_LEVEL}" ]] ; then
+        container_env+=( -e "CMAKE_BUILD_PARALLEL_LEVEL=${CMAKE_BUILD_PARALLEL_LEVEL}" )
+    fi
+    if [[ -n "${ORCA_UPDATER_SIG_KEY}" ]] ; then
+        container_env+=( -e "ORCA_UPDATER_SIG_KEY=${ORCA_UPDATER_SIG_KEY}" )
+    fi
+
+    ensure_docker_runner_image "${container_cli}" "${runner_image}"
+
+    printf '%q ' "${container_cli}" run --rm -i \
+        -v "${SCRIPT_PATH}:${container_workspace}" \
+        -w "${container_workspace}" \
+        "${container_env[@]}" \
+        "${runner_image}" \
+        bash -s -- "${build_args[@]}"
+    echo
+    if [[ -n "${DRY_RUN}" ]] ; then
+        return
+    fi
+
+    "${container_cli}" run --rm -i \
+        -v "${SCRIPT_PATH}:${container_workspace}" \
+        -w "${container_workspace}" \
+        "${container_env[@]}" \
+        "${runner_image}" \
+        bash -s -- "${build_args[@]}" <<'EOF'
+set -e
+
+function create_builder_user() {
+    if [[ "${HOST_UID}" == "0" ]] ; then
+        HOST_USER=root
+        return
+    fi
+
+    if getent group "${HOST_GID}" >/dev/null 2>&1 ; then
+        HOST_GROUP=$(getent group "${HOST_GID}" | cut -d: -f1)
+    else
+        HOST_GROUP="orca-builder"
+        if getent group "${HOST_GROUP}" >/dev/null 2>&1 ; then
+            HOST_GROUP="orca-builder-${HOST_GID}"
+        fi
+        groupadd -g "${HOST_GID}" "${HOST_GROUP}"
+    fi
+
+    if getent passwd "${HOST_UID}" >/dev/null 2>&1 ; then
+        HOST_USER=$(getent passwd "${HOST_UID}" | cut -d: -f1)
+        usermod -g "${HOST_GROUP}" "${HOST_USER}"
+    elif id -u "${HOST_USER}" >/dev/null 2>&1 ; then
+        usermod -u "${HOST_UID}" -g "${HOST_GROUP}" "${HOST_USER}"
+    else
+        useradd -m -u "${HOST_UID}" -g "${HOST_GROUP}" -s /bin/bash "${HOST_USER}"
+    fi
+
+    echo "${HOST_USER} ALL=(ALL) NOPASSWD:ALL" >/etc/sudoers.d/orcaslicer-builder
+    chmod 0440 /etc/sudoers.d/orcaslicer-builder
+}
+
+create_builder_user
+mkdir -p "${GITHUB_WORKSPACE}/deps/build/destdir"
+chown -R "${HOST_UID}:${HOST_GID}" "${GITHUB_WORKSPACE}/deps/build"
+if [[ -d "${GITHUB_WORKSPACE}/build" ]] ; then
+    chown -R "${HOST_UID}:${HOST_GID}" "${GITHUB_WORKSPACE}/build"
+fi
+if [[ -d "${GITHUB_WORKSPACE}/build-dbg" ]] ; then
+    chown -R "${HOST_UID}:${HOST_GID}" "${GITHUB_WORKSPACE}/build-dbg"
+fi
+if [[ -d "${GITHUB_WORKSPACE}/build-dbginfo" ]] ; then
+    chown -R "${HOST_UID}:${HOST_GID}" "${GITHUB_WORKSPACE}/build-dbginfo"
+fi
+
+sudo -H -u "${HOST_USER}" env \
+    CMAKE_BUILD_PARALLEL_LEVEL="${CMAKE_BUILD_PARALLEL_LEVEL-}" \
+    GITHUB_WORKSPACE="${GITHUB_WORKSPACE}" \
+    ORCA_UPDATER_SIG_KEY="${ORCA_UPDATER_SIG_KEY-}" \
+    bash -c '
+        set -e
+        cd "${GITHUB_WORKSPACE}"
+        if [[ "$#" -gt 0 ]] ; then
+            ./build_linux.sh "$@"
+        else
+            echo "No build steps were requested after container setup."
+        fi
+    ' bash "$@"
+EOF
+}
+
+if [[ -n "${USE_DOCKER}" ]] ; then
+    run_in_docker
+    popd > /dev/null # ${SCRIPT_PATH}
+    exit 0
+fi
+
 # cmake 4.x compatibility workaround
 export CMAKE_POLICY_VERSION_MINIMUM=3.5
 
@@ -152,6 +454,8 @@ elif [[ "${DISTRIBUTION_LIKE}" == *"debian"* ]] || [[ "${DISTRIBUTION_LIKE}" ==
     DISTRIBUTION="debian"
 elif [[ "${DISTRIBUTION_LIKE}" == *"arch"* ]] ; then
     DISTRIBUTION="arch"
+elif [[ "${DISTRIBUTION_LIKE}" == *"suse"* ]] ; then
+    DISTRIBUTION="suse"
 fi
 
 if [ ! -f "./scripts/linux.d/${DISTRIBUTION}" ] ; then
@@ -200,6 +504,15 @@ if [[ -n "${USE_LLD}" ]] ; then
     fi
 fi
 
+# Auto-detect ccache for faster rebuilds
+export CMAKE_CCACHE_ARGS=()
+if command -v ccache >/dev/null 2>&1 ; then
+    echo "ccache found at $(command -v ccache), enabling compiler caching..."
+    export CMAKE_CCACHE_ARGS=(-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache)
+else
+    echo "Note: ccache not found. Install ccache for faster rebuilds."
+fi
+
 if [[ -n "${BUILD_DEPS}" ]] ; then
     echo "Configuring dependencies..."
     read -r -a BUILD_ARGS <<< "${DEPS_EXTRA_BUILD_ARGS}"
@@ -213,7 +526,7 @@ if [[ -n "${BUILD_DEPS}" ]] ; then
     fi
 
     print_and_run cmake -S deps -B deps/$BUILD_DIR "${CMAKE_C_CXX_COMPILER_CLANG[@]}" "${CMAKE_LLD_LINKER_ARGS[@]}" -G Ninja "${COLORED_OUTPUT}" "${BUILD_ARGS[@]}"
-    print_and_run cmake --build deps/$BUILD_DIR
+    print_and_run cmake --build deps/$BUILD_DIR -j1
 fi
 
 if [[ -n "${BUILD_ORCA}" ]] || [[ -n "${BUILD_TESTS}" ]] ; then
@@ -232,7 +545,7 @@ if [[ -n "${BUILD_ORCA}" ]] || [[ -n "${BUILD_TESTS}" ]] ; then
         BUILD_ARGS+=(-DORCA_UPDATER_SIG_KEY="${ORCA_UPDATER_SIG_KEY}")
     fi
 
-    print_and_run cmake -S . -B $BUILD_DIR "${CMAKE_C_CXX_COMPILER_CLANG[@]}" "${CMAKE_LLD_LINKER_ARGS[@]}" -G "Ninja Multi-Config" \
+    print_and_run cmake -S . -B $BUILD_DIR "${CMAKE_C_CXX_COMPILER_CLANG[@]}" "${CMAKE_LLD_LINKER_ARGS[@]}" "${CMAKE_CCACHE_ARGS[@]}" -G "Ninja Multi-Config" \
 -DSLIC3R_PCH=${SLIC3R_PRECOMPILED_HEADERS} \
 -DORCA_TOOLS=ON \
 "${COLORED_OUTPUT}" \

cmake/modules/FindEigen3.cmake

@@ -1,86 +0,0 @@
-# - Try to find Eigen3 lib
-#
-# This module supports requiring a minimum version, e.g. you can do
-#   find_package(Eigen3 3.1.2)
-# to require version 3.1.2 or newer of Eigen3.
-#
-# Once done this will define
-#
-#  EIGEN3_FOUND - system has eigen lib with correct version
-#  EIGEN3_INCLUDE_DIR - the eigen include directory
-#  EIGEN3_VERSION - eigen version
-
-# Copyright (c) 2006, 2007 Montel Laurent, <montel@kde.org>
-# Copyright (c) 2008, 2009 Gael Guennebaud, <g.gael@free.fr>
-# Copyright (c) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-# Redistribution and use is allowed according to the terms of the 2-clause BSD license.
-
-if(NOT Eigen3_FIND_VERSION)
-  if(NOT Eigen3_FIND_VERSION_MAJOR)
-    set(Eigen3_FIND_VERSION_MAJOR 2)
-  endif(NOT Eigen3_FIND_VERSION_MAJOR)
-  if(NOT Eigen3_FIND_VERSION_MINOR)
-    set(Eigen3_FIND_VERSION_MINOR 91)
-  endif(NOT Eigen3_FIND_VERSION_MINOR)
-  if(NOT Eigen3_FIND_VERSION_PATCH)
-    set(Eigen3_FIND_VERSION_PATCH 0)
-  endif(NOT Eigen3_FIND_VERSION_PATCH)
-
-  set(Eigen3_FIND_VERSION "${Eigen3_FIND_VERSION_MAJOR}.${Eigen3_FIND_VERSION_MINOR}.${Eigen3_FIND_VERSION_PATCH}")
-endif(NOT Eigen3_FIND_VERSION)
-
-macro(_eigen3_check_version)
-  file(READ "${EIGEN3_INCLUDE_DIR}/Eigen/src/Core/util/Macros.h" _eigen3_version_header)
-
-  string(REGEX MATCH "define[ \t]+EIGEN_WORLD_VERSION[ \t]+([0-9]+)" _eigen3_world_version_match "${_eigen3_version_header}")
-  set(EIGEN3_WORLD_VERSION "${CMAKE_MATCH_1}")
-  string(REGEX MATCH "define[ \t]+EIGEN_MAJOR_VERSION[ \t]+([0-9]+)" _eigen3_major_version_match "${_eigen3_version_header}")
-  set(EIGEN3_MAJOR_VERSION "${CMAKE_MATCH_1}")
-  string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen3_minor_version_match "${_eigen3_version_header}")
-  set(EIGEN3_MINOR_VERSION "${CMAKE_MATCH_1}")
-
-  set(EIGEN3_VERSION ${EIGEN3_WORLD_VERSION}.${EIGEN3_MAJOR_VERSION}.${EIGEN3_MINOR_VERSION})
-  if(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
-    set(EIGEN3_VERSION_OK FALSE)
-  else(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
-    set(EIGEN3_VERSION_OK TRUE)
-  endif(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
-
-  if(NOT EIGEN3_VERSION_OK)
-
-    message(STATUS "Eigen3 version ${EIGEN3_VERSION} found in ${EIGEN3_INCLUDE_DIR}, "
-                   "but at least version ${Eigen3_FIND_VERSION} is required")
-  endif(NOT EIGEN3_VERSION_OK)
-endmacro(_eigen3_check_version)
-
-if (EIGEN3_INCLUDE_DIR)
-
-  # in cache already
-  _eigen3_check_version()
-  set(EIGEN3_FOUND ${EIGEN3_VERSION_OK})
-
-else (EIGEN3_INCLUDE_DIR)
-
-  # specific additional paths for some OS
-  if (WIN32)
-    set(EIGEN_ADDITIONAL_SEARCH_PATHS ${EIGEN_ADDITIONAL_SEARCH_PATHS} "C:/Program Files/Eigen/include" "C:/Program Files (x86)/Eigen/include")
-  endif(WIN32)
-
-  find_path(EIGEN3_INCLUDE_DIR NAMES signature_of_eigen3_matrix_library
-      PATHS
-      ${CMAKE_INSTALL_PREFIX}/include
-      ${EIGEN_ADDITIONAL_SEARCH_PATHS}
-      ${KDE4_INCLUDE_DIR}
-      PATH_SUFFIXES eigen3 eigen
-    )
-
-  if(EIGEN3_INCLUDE_DIR)
-    _eigen3_check_version()
-  endif(EIGEN3_INCLUDE_DIR)
-
-  include(FindPackageHandleStandardArgs)
-  find_package_handle_standard_args(Eigen3 DEFAULT_MSG EIGEN3_INCLUDE_DIR EIGEN3_VERSION_OK)
-
-  mark_as_advanced(EIGEN3_INCLUDE_DIR)
-
-endif(EIGEN3_INCLUDE_DIR)

deps/Boost/Boost.cmake

@@ -18,6 +18,7 @@ orcaslicer_add_cmake_project(Boost
         -DBOOST_EXCLUDE_LIBRARIES:STRING=contract|fiber|numpy|stacktrace|wave|test
         -DBOOST_LOCALE_ENABLE_ICU:BOOL=OFF # do not link to libicu, breaks compatibility between distros
         -DBUILD_TESTING:BOOL=OFF
+        -DBOOST_IOSTREAMS_ENABLE_BZIP2:BOOL=OFF # avoid libbz2 soname differences in AppImage builds
         -DBOOST_IOSTREAMS_ENABLE_ZSTD:BOOL=OFF
         "${_context_abi_line}"
         "${_context_arch_line}"

deps/CGAL/CGAL.cmake

@@ -9,7 +9,7 @@ orcaslicer_add_cmake_project(
     # For whatever reason, this keeps downloading forever (repeats downloads if finished)
     URL      https://github.com/CGAL/cgal/releases/download/v5.6.3/CGAL-5.6.3.zip
     URL_HASH SHA256=5d577acb4a9918ccb960491482da7a3838f8d363aff47e14d703f19fd84733d4
-    DEPENDS dep_Boost dep_GMP dep_MPFR
+    DEPENDS dep_Boost dep_Eigen dep_GMP dep_MPFR
 )
 
 include(GNUInstallDirs)

deps/CMakeLists.txt

@@ -134,7 +134,7 @@ if (APPLE)
 endif ()
 
 
-# On developer machines, it can be enabled to speed up compilation and suppress warnings coming from IGL. 
+# On developer machines, it can be enabled to speed up compilation and suppress warnings coming from IGL.
 # FIXME:
 # Enabling this option is not safe. IGL will compile itself with its own version of Eigen while
 # Slic3r compiles with a different version which will cause runtime errors.
@@ -146,7 +146,7 @@ message(STATUS "OrcaSlicer deps debug build: ${DEP_DEBUG}")
 
 find_package(Git REQUIRED)
 
-# The default command line for patching. Only works for newer 
+# The default command line for patching. Only works for newer
 set(PATCH_CMD ${GIT_EXECUTABLE} apply --verbose --ignore-space-change --whitespace=fix)
 
 if (NOT _is_multi AND NOT CMAKE_BUILD_TYPE)
@@ -166,11 +166,18 @@ function(orcaslicer_add_cmake_project projectname)
         endif ()
     endif ()
 
-    set(_gen "")
-    set(_build_j "-j${NPROC}")
     if (MSVC)
-        set(_gen CMAKE_GENERATOR "${DEP_MSVC_GEN}" CMAKE_GENERATOR_PLATFORM "${DEP_PLATFORM}")
-        set(_build_j "/m")
+      set(_gen CMAKE_GENERATOR "${DEP_MSVC_GEN}" CMAKE_GENERATOR_PLATFORM "${DEP_PLATFORM}")
+    else()
+      set(_gen "")
+    endif()
+
+    if ($ENV{CMAKE_BUILD_PARALLEL_LEVEL})
+      set(_build_j "")  # assume environment will control --build parallel setting
+    elseif(MSVC)
+      set(_build_j "/m")
+    else()
+      set(_build_j "-j${NPROC}")
     endif ()
 
 if (NOT IS_CROSS_COMPILE OR NOT APPLE)
@@ -241,7 +248,7 @@ else()
             ${P_ARGS_CMAKE_ARGS}
        ${P_ARGS_UNPARSED_ARGUMENTS}
        BUILD_COMMAND ${CMAKE_COMMAND} --build . --config Release -- ${_build_j}
-       INSTALL_COMMAND ${CMAKE_COMMAND} --build . --target install --config Release 
+       INSTALL_COMMAND ${CMAKE_COMMAND} --build . --target install --config Release
     )
 
 endif()
@@ -258,8 +265,12 @@ if (MSVC)
         message(STATUS "\nDetected X86 compiler => building X86 deps bundle\n")
         set(DEPS_ARCH "x86")
         include("deps-windows.cmake")
+    elseif ("${CMAKE_SYSTEM_PROCESSOR}" STREQUAL "ARM64")
+        message(STATUS "\nDetected ARM64 compiler => building ARM64 deps bundle\n")
+        set(DEPS_ARCH "arm64")
+        include("deps-windows.cmake")
     else ()
-        message(FATAL_ERROR "Unable to detect architecture")
+        message(FATAL_ERROR "Unable to detect architecture: ${CMAKE_SYSTEM_PROCESSOR}")
     endif ()
 elseif (APPLE)
     message("OS X SDK Path: ${CMAKE_OSX_SYSROOT}")
@@ -301,26 +312,26 @@ if(FLATPAK)
 endif()
 
 set(ZLIB_PKG "")
-if (NOT ZLIB_FOUND) 
+if (NOT ZLIB_FOUND)
     include(ZLIB/ZLIB.cmake)
     set(ZLIB_PKG dep_ZLIB)
 endif ()
 set(PNG_PKG "")
-if (NOT PNG_FOUND) 
+if (NOT PNG_FOUND)
     include(PNG/PNG.cmake)
     set(PNG_PKG dep_PNG)
 endif ()
 set(EXPAT_PKG "")
 find_package(EXPAT)
-if (NOT EXPAT_FOUND) 
+if (NOT EXPAT_FOUND)
     include(EXPAT/EXPAT.cmake)
     set(EXPAT_PKG dep_EXPAT)
 endif ()
 
+# The order of includes respects the dependencies between libraries
 set(DEP_Boost_COMPONENTS system iostreams filesystem thread log locale regex date_time)
 include(Boost/Boost.cmake)
 
-# The order of includes respects the dependencies between libraries
 include(Cereal/Cereal.cmake)
 include(Qhull/Qhull.cmake)
 include(GLEW/GLEW.cmake)
@@ -336,6 +347,7 @@ include(OpenVDB/OpenVDB.cmake)
 
 include(GMP/GMP.cmake)
 include(MPFR/MPFR.cmake)
+include(Eigen/Eigen.cmake)
 include(CGAL/CGAL.cmake)
 
 include(NLopt/NLopt.cmake)
@@ -347,7 +359,7 @@ include(Draco/Draco.cmake)
 # I *think* 1.1 is used for *just* md5 hashing?
 # 3.1 has everything in the right place, but the md5 funcs used are deprecated
 # a grep across the repo shows it is used for other things
-# TODO: update openssl and everything that uses <openssl/md5.h> 
+# TODO: update openssl and everything that uses <openssl/md5.h>
 set(OPENSSL_PKG "")
 if(NOT OPENSSL_FOUND)
     include(OpenSSL/OpenSSL.cmake)
@@ -355,7 +367,7 @@ if(NOT OPENSSL_FOUND)
 endif()
 
 # we don't want to load a "wrong" openssl when loading curl
-# so, just don't even bother 
+# so, just don't even bother
 # ...i think this is how it works? change if wrong
 set(CURL_PKG "")
 if (NOT OPENSSL_FOUND OR NOT CURL_FOUND)
@@ -379,7 +391,7 @@ endif()
 set(FREETYPE_PKG "")
 if(NOT FREETYPE_FOUND)
     include(FREETYPE/FREETYPE.cmake)
-    set(FREETYPE_PKG "dep_FREETYPE") 
+    set(FREETYPE_PKG "dep_FREETYPE")
 endif()
 
 execute_process(
@@ -411,6 +423,7 @@ set(_dep_list
     dep_OpenVDB
     dep_OpenCSG
     dep_OpenCV
+    dep_Eigen
     dep_CGAL
     dep_GLFW
     dep_OCCT

deps/Eigen/Eigen.cmake

@@ -0,0 +1,5 @@
+orcaslicer_add_cmake_project(Eigen
+    URL https://gitlab.com/libeigen/eigen/-/archive/5.0.1/eigen-5.0.1.zip
+    URL_HASH SHA256=0dbb1f9e3aaad66f352c03227d8c983f6f0b49e0b07e71a7300f4abcc01aee12
+    DEPENDS dep_Boost dep_GMP dep_MPFR
+)

deps/GLFW/GLFW.cmake

@@ -6,22 +6,20 @@ else()
     set(_build_static ON)
 endif()
 
+set(_glfw_platform_args "")
 if(CMAKE_SYSTEM_NAME STREQUAL "Linux")
-    set(_glfw_use_wayland "-DGLFW_USE_WAYLAND=ON")
-else()
-    set(_glfw_use_wayland "-DGLFW_USE_WAYLAND=FF")
+    set(_glfw_platform_args -DGLFW_BUILD_WAYLAND=ON -DGLFW_BUILD_X11=ON)
 endif()
 
 orcaslicer_add_cmake_project(GLFW
-    URL https://github.com/glfw/glfw/archive/refs/tags/3.3.7.zip
-    URL_HASH SHA256=e02d956935e5b9fb4abf90e2c2e07c9a0526d7eacae8ee5353484c69a2a76cd0
-    #DEPENDS dep_Boost
+    URL https://github.com/glfw/glfw/archive/refs/tags/3.4.zip
+    URL_HASH SHA256=a133ddc3d3c66143eba9035621db8e0bcf34dba1ee9514a9e23e96afd39fd57a
     CMAKE_ARGS
-        -DBUILD_SHARED_LIBS=${_build_shared} 
+        -DBUILD_SHARED_LIBS=${_build_shared}
         -DGLFW_BUILD_DOCS=OFF
         -DGLFW_BUILD_EXAMPLES=OFF
-	-DGLFW_BUILD_TESTS=OFF
-	${_glfw_use_wayland}
+        -DGLFW_BUILD_TESTS=OFF
+        ${_glfw_platform_args}
 )
 
 if (MSVC)

deps/OpenCV/OpenCV.cmake

@@ -55,6 +55,8 @@ orcaslicer_add_cmake_project(OpenCV
        -DWITH_VTK=OFF
        -DWITH_JPEG=OFF
        -DWITH_WEBP=OFF
+       -DWITH_TIFF=OFF
+       -DBUILD_TIFF=OFF
        -DENABLE_PRECOMPILED_HEADERS=OFF
        -DINSTALL_TESTS=OFF
        -DINSTALL_C_EXAMPLES=OFF

deps/deps-windows.cmake

@@ -36,8 +36,10 @@ if ("${DEPS_ARCH}" STREQUAL "x86")
     set(DEP_PLATFORM "Win32")
 elseif ("${DEPS_ARCH}" STREQUAL "x64")
     set(DEP_PLATFORM "x64")
+elseif ("${DEPS_ARCH}" STREQUAL "arm64")
+    set(DEP_PLATFORM "ARM64")
 else ()
-    message(FATAL_ERROR "Unsupported OS architecture")
+    message(FATAL_ERROR "Unsupported OS architecture: ${DEPS_ARCH}")
 endif ()
 
 if (${DEP_DEBUG})
@@ -64,8 +66,11 @@ if ("${DEPS_ARCH}" STREQUAL "x86")
 elseif ("${DEPS_ARCH}" STREQUAL "x64")
     set(DEP_WXWIDGETS_TARGET "TARGET_CPU=X64")
     set(DEP_WXWIDGETS_LIBDIR "vc_x64_lib")
+elseif ("${DEPS_ARCH}" STREQUAL "arm64")
+    set(DEP_WXWIDGETS_TARGET "TARGET_CPU=ARM64")
+    set(DEP_WXWIDGETS_LIBDIR "vc_arm64_lib")
 else ()
-    message(FATAL_ERROR "Unsupported OS architecture")
+    message(FATAL_ERROR "Unsupported OS architecture: ${DEPS_ARCH}")
 endif ()
 
 find_package(Git REQUIRED)

deps/wxWidgets/wxWidgets.cmake

@@ -21,21 +21,13 @@ else ()
     set(_wx_edge "-DwxUSE_WEBVIEW_EDGE=OFF")
 endif ()
 
-set(_wx_opengl_override "")
-if(APPLE AND CMAKE_VERSION VERSION_GREATER_EQUAL "4.0")
-    set(_wx_opengl_override
-        -DOPENGL_gl_LIBRARY="-framework OpenGL"
-        -DOPENGL_glu_LIBRARY="-framework OpenGL"
-    )
-endif()
-
 orcaslicer_add_cmake_project(
     wxWidgets
     GIT_REPOSITORY "https://github.com/SoftFever/Orca-deps-wxWidgets"
+    GIT_TAG v3.3.2
     GIT_SHALLOW ON
     DEPENDS ${PNG_PKG} ${ZLIB_PKG} ${EXPAT_PKG} ${JPEG_PKG}
     CMAKE_ARGS
-        ${_wx_opengl_override}
         -DwxBUILD_PRECOMP=ON
         ${_wx_toolkit}
         "-DCMAKE_DEBUG_POSTFIX:STRING=${_wx_debug_postfix}"
@@ -44,10 +36,9 @@ orcaslicer_add_cmake_project(
         ${_wx_shared}
         -DwxUSE_MEDIACTRL=ON
         -DwxUSE_DETECT_SM=OFF
-        -DwxUSE_UNICODE=ON
         -DwxUSE_PRIVATE_FONTS=ON
         -DwxUSE_OPENGL=ON
-        -DwxUSE_GLCANVAS_EGL=OFF
+        -DwxUSE_GLCANVAS_EGL=ON
         -DwxUSE_WEBREQUEST=ON
         -DwxUSE_WEBVIEW=ON
         ${_wx_edge}
@@ -61,7 +52,31 @@ orcaslicer_add_cmake_project(
         -DwxUSE_ZLIB=sys
         -DwxUSE_LIBJPEG=sys
         -DwxUSE_LIBTIFF=OFF
+        -DwxUSE_LIBWEBP=builtin
         -DwxUSE_EXPAT=sys
+        -DwxUSE_NANOSVG=OFF
+)
+
+# wxWidgets 3.3 cmake install doesn't include private headers.
+# OrcaSlicer uses some of the private headers (for accessibility support).
+# Copy the private headers directory after install.
+if(MSVC)
+    set(_wx_inc_dest ${DESTDIR}/include/wx)
+else()
+    set(_wx_inc_dest ${DESTDIR}/include/wx-3.3/wx)
+endif()
+ExternalProject_Add_Step(dep_wxWidgets copy_private_headers
+    DEPENDEES install
+    COMMENT "Copying wxWidgets private headers"
+    COMMAND ${CMAKE_COMMAND} -E copy_directory
+        <SOURCE_DIR>/include/wx/private
+        ${_wx_inc_dest}/private
+    COMMAND ${CMAKE_COMMAND} -E copy_directory
+        <SOURCE_DIR>/include/wx/generic/private
+        ${_wx_inc_dest}/generic/private
+    COMMAND ${CMAKE_COMMAND} -E copy_directory
+        <SOURCE_DIR>/include/wx/gtk/private
+        ${_wx_inc_dest}/gtk/private
 )
 
 if (MSVC)

deps_src/CMakeLists.txt

@@ -32,6 +32,3 @@ add_subdirectory(minilzo)
 add_subdirectory(qhull)
 add_subdirectory(qoi)
 add_subdirectory(semver)      # Semver static library
-
-# Eigen header-only library
-add_subdirectory(eigen)

deps_src/admesh/CMakeLists.txt

@@ -18,6 +18,6 @@ target_include_directories(admesh SYSTEM
 )
 
 target_link_libraries(admesh 
+    PUBLIC Eigen3::Eigen
     PRIVATE boost_headeronly
-    PUBLIC eigen
 )

deps_src/clipper/CMakeLists.txt

@@ -15,6 +15,6 @@ target_include_directories(clipper SYSTEM
 )
 
 target_link_libraries(clipper 
-    PUBLIC eigen
+    PUBLIC Eigen3::Eigen
     PRIVATE TBB::tbb TBB::tbbmalloc
 )

deps_src/eigen/CMakeLists.txt

@@ -1,12 +0,0 @@
-cmake_minimum_required(VERSION 3.13)
-project(eigen)
-
-add_library(eigen INTERFACE)
-
-target_include_directories(eigen SYSTEM
-    INTERFACE
-        ${CMAKE_CURRENT_SOURCE_DIR}
-)
-
-# Eigen is header-only, so we only need to specify the include directory
-# The headers are in the Eigen/ subdirectory structure

deps_src/eigen/COPYING.README

@@ -1,18 +0,0 @@
-Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
-  http://www.mozilla.org/MPL/2.0/
-  http://www.mozilla.org/MPL/2.0/FAQ.html
-
-Some files contain third-party code under BSD or LGPL licenses, whence the other
-COPYING.* files here.
-
-All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
-For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
-
-If you want to guarantee that the Eigen code that you are #including is licensed
-under the MPL2 and possibly more permissive licenses (like BSD), #define this
-preprocessor symbol:
-  EIGEN_MPL2_ONLY
-For example, with most compilers, you could add this to your project CXXFLAGS:
-  -DEIGEN_MPL2_ONLY
-This will cause a compilation error to be generated if you #include any code that is
-LGPL licensed.

deps_src/eigen/Eigen/CMakeLists.txt

@@ -1,19 +0,0 @@
-include(RegexUtils)
-test_escape_string_as_regex()
-
-file(GLOB Eigen_directory_files "*")
-
-escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
-
-foreach(f ${Eigen_directory_files})
-  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/src")
-    list(APPEND Eigen_directory_files_to_install ${f})
-  endif()
-endforeach(f ${Eigen_directory_files})
-
-install(FILES
-  ${Eigen_directory_files_to_install}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel
-  )
-
-install(DIRECTORY src DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel FILES_MATCHING PATTERN "*.h")

deps_src/eigen/Eigen/Cholesky

@@ -1,46 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CHOLESKY_MODULE_H
-#define EIGEN_CHOLESKY_MODULE_H
-
-#include "Core"
-#include "Jacobi"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup Cholesky_Module Cholesky module
-  *
-  *
-  *
-  * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
-  * Those decompositions are also accessible via the following methods:
-  *  - MatrixBase::llt()
-  *  - MatrixBase::ldlt()
-  *  - SelfAdjointView::llt()
-  *  - SelfAdjointView::ldlt()
-  *
-  * \code
-  * #include <Eigen/Cholesky>
-  * \endcode
-  */
-
-#include "src/Cholesky/LLT.h"
-#include "src/Cholesky/LDLT.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/Cholesky/LLT_LAPACKE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_CHOLESKY_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/CholmodSupport

@@ -1,48 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
-#define EIGEN_CHOLMODSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-  #include <cholmod.h>
-}
-
-/** \ingroup Support_modules
-  * \defgroup CholmodSupport_Module CholmodSupport module
-  *
-  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
-  * It provides the two following main factorization classes:
-  * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
-  * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
-  *
-  * For the sake of completeness, this module also propose the two following classes:
-  * - class CholmodSimplicialLLT
-  * - class CholmodSimplicialLDLT
-  * Note that these classes does not bring any particular advantage compared to the built-in
-  * SimplicialLLT and SimplicialLDLT factorization classes.
-  *
-  * \code
-  * #include <Eigen/CholmodSupport>
-  * \endcode
-  *
-  * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
-  * The dependencies depend on how cholmod has been compiled.
-  * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
-  *
-  */
-
-#include "src/CholmodSupport/CholmodSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
-

deps_src/eigen/Eigen/Core

@@ -1,537 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2007-2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CORE_H
-#define EIGEN_CORE_H
-
-// first thing Eigen does: stop the compiler from committing suicide
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#if defined(__CUDACC__) && !defined(EIGEN_NO_CUDA)
-  #define EIGEN_CUDACC __CUDACC__
-#endif
-
-#if defined(__CUDA_ARCH__) && !defined(EIGEN_NO_CUDA)
-  #define EIGEN_CUDA_ARCH __CUDA_ARCH__
-#endif
-
-#if defined(__CUDACC_VER_MAJOR__) && (__CUDACC_VER_MAJOR__ >= 9)
-#define EIGEN_CUDACC_VER  ((__CUDACC_VER_MAJOR__ * 10000) + (__CUDACC_VER_MINOR__ * 100))
-#elif defined(__CUDACC_VER__)
-#define EIGEN_CUDACC_VER __CUDACC_VER__
-#else
-#define EIGEN_CUDACC_VER 0
-#endif
-
-// Handle NVCC/CUDA/SYCL
-#if defined(__CUDACC__) || defined(__SYCL_DEVICE_ONLY__)
-  // Do not try asserts on CUDA and SYCL!
-  #ifndef EIGEN_NO_DEBUG
-  #define EIGEN_NO_DEBUG
-  #endif
-
-  #ifdef EIGEN_INTERNAL_DEBUGGING
-  #undef EIGEN_INTERNAL_DEBUGGING
-  #endif
-
-  #ifdef EIGEN_EXCEPTIONS
-  #undef EIGEN_EXCEPTIONS
-  #endif
-
-  // All functions callable from CUDA code must be qualified with __device__
-  #ifdef __CUDACC__
-    // Do not try to vectorize on CUDA and SYCL!
-    #ifndef EIGEN_DONT_VECTORIZE
-    #define EIGEN_DONT_VECTORIZE
-    #endif
-
-    #define EIGEN_DEVICE_FUNC __host__ __device__
-    // We need cuda_runtime.h to ensure that that EIGEN_USING_STD_MATH macro
-    // works properly on the device side
-    #include <cuda_runtime.h>
-  #else
-    #define EIGEN_DEVICE_FUNC
-  #endif
-
-#else
-  #define EIGEN_DEVICE_FUNC
-
-#endif
-
-// When compiling CUDA device code with NVCC, pull in math functions from the
-// global namespace.  In host mode, and when device doee with clang, use the
-// std versions.
-#if defined(__CUDA_ARCH__) && defined(__NVCC__)
-  #define EIGEN_USING_STD_MATH(FUNC) using ::FUNC;
-#else
-  #define EIGEN_USING_STD_MATH(FUNC) using std::FUNC;
-#endif
-
-#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(EIGEN_EXCEPTIONS) && !defined(EIGEN_USE_SYCL)
-  #define EIGEN_EXCEPTIONS
-#endif
-
-#ifdef EIGEN_EXCEPTIONS
-  #include <new>
-#endif
-
-// then include this file where all our macros are defined. It's really important to do it first because
-// it's where we do all the alignment settings (platform detection and honoring the user's will if he
-// defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
-#include "src/Core/util/Macros.h"
-
-// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
-// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
-#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6)
-  #pragma GCC optimize ("-fno-ipa-cp-clone")
-#endif
-
-#include <complex>
-
-// this include file manages BLAS and MKL related macros
-// and inclusion of their respective header files
-#include "src/Core/util/MKL_support.h"
-
-// if alignment is disabled, then disable vectorization. Note: EIGEN_MAX_ALIGN_BYTES is the proper check, it takes into
-// account both the user's will (EIGEN_MAX_ALIGN_BYTES,EIGEN_DONT_ALIGN) and our own platform checks
-#if EIGEN_MAX_ALIGN_BYTES==0
-  #ifndef EIGEN_DONT_VECTORIZE
-    #define EIGEN_DONT_VECTORIZE
-  #endif
-#endif
-
-#if EIGEN_COMP_MSVC
-  #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
-  #if (EIGEN_COMP_MSVC >= 1500) // 2008 or later
-    // Remember that usage of defined() in a #define is undefined by the standard.
-    // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
-    #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || EIGEN_ARCH_x86_64
-      #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
-    #endif
-  #endif
-#else
-  // Remember that usage of defined() in a #define is undefined by the standard
-  #if (defined __SSE2__) && ( (!EIGEN_COMP_GNUC) || EIGEN_COMP_ICC || EIGEN_GNUC_AT_LEAST(4,2) )
-    #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
-  #endif
-#endif
-
-#ifndef EIGEN_DONT_VECTORIZE
-
-  #if defined (EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER)
-
-    // Defines symbols for compile-time detection of which instructions are
-    // used.
-    // EIGEN_VECTORIZE_YY is defined if and only if the instruction set YY is used
-    #define EIGEN_VECTORIZE
-    #define EIGEN_VECTORIZE_SSE
-    #define EIGEN_VECTORIZE_SSE2
-
-    // Detect sse3/ssse3/sse4:
-    // gcc and icc defines __SSE3__, ...
-    // there is no way to know about this on msvc. You can define EIGEN_VECTORIZE_SSE* if you
-    // want to force the use of those instructions with msvc.
-    #ifdef __SSE3__
-      #define EIGEN_VECTORIZE_SSE3
-    #endif
-    #ifdef __SSSE3__
-      #define EIGEN_VECTORIZE_SSSE3
-    #endif
-    #ifdef __SSE4_1__
-      #define EIGEN_VECTORIZE_SSE4_1
-    #endif
-    #ifdef __SSE4_2__
-      #define EIGEN_VECTORIZE_SSE4_2
-    #endif
-    #ifdef __AVX__
-      #define EIGEN_VECTORIZE_AVX
-      #define EIGEN_VECTORIZE_SSE3
-      #define EIGEN_VECTORIZE_SSSE3
-      #define EIGEN_VECTORIZE_SSE4_1
-      #define EIGEN_VECTORIZE_SSE4_2
-    #endif
-    #ifdef __AVX2__
-      #define EIGEN_VECTORIZE_AVX2
-    #endif
-    #ifdef __FMA__
-      #define EIGEN_VECTORIZE_FMA
-    #endif
-    #if defined(__AVX512F__) && defined(EIGEN_ENABLE_AVX512)
-      #define EIGEN_VECTORIZE_AVX512
-      #define EIGEN_VECTORIZE_AVX2
-      #define EIGEN_VECTORIZE_AVX
-      #define EIGEN_VECTORIZE_FMA
-      #ifdef __AVX512DQ__
-        #define EIGEN_VECTORIZE_AVX512DQ
-      #endif
-      #ifdef __AVX512ER__
-        #define EIGEN_VECTORIZE_AVX512ER
-      #endif
-    #endif
-
-    // include files
-
-    // This extern "C" works around a MINGW-w64 compilation issue
-    // https://sourceforge.net/tracker/index.php?func=detail&aid=3018394&group_id=202880&atid=983354
-    // In essence, intrin.h is included by windows.h and also declares intrinsics (just as emmintrin.h etc. below do).
-    // However, intrin.h uses an extern "C" declaration, and g++ thus complains of duplicate declarations
-    // with conflicting linkage.  The linkage for intrinsics doesn't matter, but at that stage the compiler doesn't know;
-    // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
-    // notice that since these are C headers, the extern "C" is theoretically needed anyways.
-    extern "C" {
-      // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
-      // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
-      #if EIGEN_COMP_ICC >= 1110
-        #include <immintrin.h>
-      #else
-        #include <mmintrin.h>
-        #include <emmintrin.h>
-        #include <xmmintrin.h>
-        #ifdef  EIGEN_VECTORIZE_SSE3
-        #include <pmmintrin.h>
-        #endif
-        #ifdef EIGEN_VECTORIZE_SSSE3
-        #include <tmmintrin.h>
-        #endif
-        #ifdef EIGEN_VECTORIZE_SSE4_1
-        #include <smmintrin.h>
-        #endif
-        #ifdef EIGEN_VECTORIZE_SSE4_2
-        #include <nmmintrin.h>
-        #endif
-        #if defined(EIGEN_VECTORIZE_AVX) || defined(EIGEN_VECTORIZE_AVX512)
-        #include <immintrin.h>
-        #endif
-      #endif
-    } // end extern "C"
-  #elif defined __VSX__
-    #define EIGEN_VECTORIZE
-    #define EIGEN_VECTORIZE_VSX
-    #include <altivec.h>
-    // We need to #undef all these ugly tokens defined in <altivec.h>
-    // => use __vector instead of vector
-    #undef bool
-    #undef vector
-    #undef pixel
-  #elif defined __ALTIVEC__
-    #define EIGEN_VECTORIZE
-    #define EIGEN_VECTORIZE_ALTIVEC
-    #include <altivec.h>
-    // We need to #undef all these ugly tokens defined in <altivec.h>
-    // => use __vector instead of vector
-    #undef bool
-    #undef vector
-    #undef pixel
-  #elif (defined  __ARM_NEON) || (defined __ARM_NEON__)
-    #define EIGEN_VECTORIZE
-    #define EIGEN_VECTORIZE_NEON
-    #include <arm_neon.h>
-  #elif (defined __s390x__ && defined __VEC__)
-    #define EIGEN_VECTORIZE
-    #define EIGEN_VECTORIZE_ZVECTOR
-    #include <vecintrin.h>
-  #endif
-#endif
-
-#if defined(__F16C__) && !defined(EIGEN_COMP_CLANG)
-  // We can use the optimized fp16 to float and float to fp16 conversion routines
-  #define EIGEN_HAS_FP16_C
-#endif
-
-#if defined __CUDACC__
-  #define EIGEN_VECTORIZE_CUDA
-  #include <vector_types.h>
-  #if EIGEN_CUDACC_VER >= 70500
-    #define EIGEN_HAS_CUDA_FP16
-  #endif
-#endif
-
-#if defined EIGEN_HAS_CUDA_FP16
-  #include <host_defines.h>
-  #include <cuda_fp16.h>
-#endif
-
-#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
-  #define EIGEN_HAS_OPENMP
-#endif
-
-#ifdef EIGEN_HAS_OPENMP
-#include <omp.h>
-#endif
-
-// MSVC for windows mobile does not have the errno.h file
-#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
-#define EIGEN_HAS_ERRNO
-#endif
-
-#ifdef EIGEN_HAS_ERRNO
-#include <cerrno>
-#endif
-#include <cstddef>
-#include <cstdlib>
-#include <cmath>
-#include <cassert>
-#include <functional>
-#include <iosfwd>
-#include <cstring>
-#include <string>
-#include <limits>
-#include <climits> // for CHAR_BIT
-// for min/max:
-#include <algorithm>
-
-// for std::is_nothrow_move_assignable
-#ifdef EIGEN_INCLUDE_TYPE_TRAITS
-#include <type_traits>
-#endif
-
-// for outputting debug info
-#ifdef EIGEN_DEBUG_ASSIGN
-#include <iostream>
-#endif
-
-// required for __cpuid, needs to be included after cmath
-#if EIGEN_COMP_MSVC && EIGEN_ARCH_i386_OR_x86_64 && !EIGEN_OS_WINCE
-  #include <intrin.h>
-#endif
-
-/** \brief Namespace containing all symbols from the %Eigen library. */
-namespace Eigen {
-
-inline static const char *SimdInstructionSetsInUse(void) {
-#if defined(EIGEN_VECTORIZE_AVX512)
-  return "AVX512, FMA, AVX2, AVX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
-#elif defined(EIGEN_VECTORIZE_AVX)
-  return "AVX SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
-#elif defined(EIGEN_VECTORIZE_SSE4_2)
-  return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
-#elif defined(EIGEN_VECTORIZE_SSE4_1)
-  return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
-#elif defined(EIGEN_VECTORIZE_SSSE3)
-  return "SSE, SSE2, SSE3, SSSE3";
-#elif defined(EIGEN_VECTORIZE_SSE3)
-  return "SSE, SSE2, SSE3";
-#elif defined(EIGEN_VECTORIZE_SSE2)
-  return "SSE, SSE2";
-#elif defined(EIGEN_VECTORIZE_ALTIVEC)
-  return "AltiVec";
-#elif defined(EIGEN_VECTORIZE_VSX)
-  return "VSX";
-#elif defined(EIGEN_VECTORIZE_NEON)
-  return "ARM NEON";
-#elif defined(EIGEN_VECTORIZE_ZVECTOR)
-  return "S390X ZVECTOR";
-#else
-  return "None";
-#endif
-}
-
-} // end namespace Eigen
-
-#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API || defined EIGEN2_SUPPORT
-// This will generate an error message:
-#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
-#endif
-
-namespace Eigen {
-
-// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
-// ensure QNX/QCC support
-using std::size_t;
-// gcc 4.6.0 wants std:: for ptrdiff_t
-using std::ptrdiff_t;
-
-}
-
-/** \defgroup Core_Module Core module
-  * This is the main module of Eigen providing dense matrix and vector support
-  * (both fixed and dynamic size) with all the features corresponding to a BLAS library
-  * and much more...
-  *
-  * \code
-  * #include <Eigen/Core>
-  * \endcode
-  */
-
-#include "src/Core/util/Constants.h"
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/ForwardDeclarations.h"
-#include "src/Core/util/StaticAssert.h"
-#include "src/Core/util/XprHelper.h"
-#include "src/Core/util/Memory.h"
-
-#include "src/Core/NumTraits.h"
-#include "src/Core/MathFunctions.h"
-#include "src/Core/GenericPacketMath.h"
-#include "src/Core/MathFunctionsImpl.h"
-#include "src/Core/arch/Default/ConjHelper.h"
-
-#if defined EIGEN_VECTORIZE_AVX512
-  #include "src/Core/arch/SSE/PacketMath.h"
-  #include "src/Core/arch/AVX/PacketMath.h"
-  #include "src/Core/arch/AVX512/PacketMath.h"
-  #include "src/Core/arch/AVX512/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_AVX
-  // Use AVX for floats and doubles, SSE for integers
-  #include "src/Core/arch/SSE/PacketMath.h"
-  #include "src/Core/arch/SSE/Complex.h"
-  #include "src/Core/arch/SSE/MathFunctions.h"
-  #include "src/Core/arch/AVX/PacketMath.h"
-  #include "src/Core/arch/AVX/MathFunctions.h"
-  #include "src/Core/arch/AVX/Complex.h"
-  #include "src/Core/arch/AVX/TypeCasting.h"
-  #include "src/Core/arch/SSE/TypeCasting.h"
-#elif defined EIGEN_VECTORIZE_SSE
-  #include "src/Core/arch/SSE/PacketMath.h"
-  #include "src/Core/arch/SSE/MathFunctions.h"
-  #include "src/Core/arch/SSE/Complex.h"
-  #include "src/Core/arch/SSE/TypeCasting.h"
-#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
-  #include "src/Core/arch/AltiVec/PacketMath.h"
-  #include "src/Core/arch/AltiVec/MathFunctions.h"
-  #include "src/Core/arch/AltiVec/Complex.h"
-#elif defined EIGEN_VECTORIZE_NEON
-  #include "src/Core/arch/NEON/PacketMath.h"
-  #include "src/Core/arch/NEON/MathFunctions.h"
-  #include "src/Core/arch/NEON/Complex.h"
-#elif defined EIGEN_VECTORIZE_ZVECTOR
-  #include "src/Core/arch/ZVector/PacketMath.h"
-  #include "src/Core/arch/ZVector/MathFunctions.h"
-  #include "src/Core/arch/ZVector/Complex.h"
-#endif
-
-// Half float support
-#include "src/Core/arch/CUDA/Half.h"
-#include "src/Core/arch/CUDA/PacketMathHalf.h"
-#include "src/Core/arch/CUDA/TypeCasting.h"
-
-#if defined EIGEN_VECTORIZE_CUDA
-  #include "src/Core/arch/CUDA/PacketMath.h"
-  #include "src/Core/arch/CUDA/MathFunctions.h"
-#endif
-
-#include "src/Core/arch/Default/Settings.h"
-
-#include "src/Core/functors/TernaryFunctors.h"
-#include "src/Core/functors/BinaryFunctors.h"
-#include "src/Core/functors/UnaryFunctors.h"
-#include "src/Core/functors/NullaryFunctors.h"
-#include "src/Core/functors/StlFunctors.h"
-#include "src/Core/functors/AssignmentFunctors.h"
-
-// Specialized functors to enable the processing of complex numbers
-// on CUDA devices
-#include "src/Core/arch/CUDA/Complex.h"
-
-#include "src/Core/IO.h"
-#include "src/Core/DenseCoeffsBase.h"
-#include "src/Core/DenseBase.h"
-#include "src/Core/MatrixBase.h"
-#include "src/Core/EigenBase.h"
-
-#include "src/Core/Product.h"
-#include "src/Core/CoreEvaluators.h"
-#include "src/Core/AssignEvaluator.h"
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
-                                // at least confirmed with Doxygen 1.5.5 and 1.5.6
-  #include "src/Core/Assign.h"
-#endif
-
-#include "src/Core/ArrayBase.h"
-#include "src/Core/util/BlasUtil.h"
-#include "src/Core/DenseStorage.h"
-#include "src/Core/NestByValue.h"
-
-// #include "src/Core/ForceAlignedAccess.h"
-
-#include "src/Core/ReturnByValue.h"
-#include "src/Core/NoAlias.h"
-#include "src/Core/PlainObjectBase.h"
-#include "src/Core/Matrix.h"
-#include "src/Core/Array.h"
-#include "src/Core/CwiseTernaryOp.h"
-#include "src/Core/CwiseBinaryOp.h"
-#include "src/Core/CwiseUnaryOp.h"
-#include "src/Core/CwiseNullaryOp.h"
-#include "src/Core/CwiseUnaryView.h"
-#include "src/Core/SelfCwiseBinaryOp.h"
-#include "src/Core/Dot.h"
-#include "src/Core/StableNorm.h"
-#include "src/Core/Stride.h"
-#include "src/Core/MapBase.h"
-#include "src/Core/Map.h"
-#include "src/Core/Ref.h"
-#include "src/Core/Block.h"
-#include "src/Core/VectorBlock.h"
-#include "src/Core/Transpose.h"
-#include "src/Core/DiagonalMatrix.h"
-#include "src/Core/Diagonal.h"
-#include "src/Core/DiagonalProduct.h"
-#include "src/Core/Redux.h"
-#include "src/Core/Visitor.h"
-#include "src/Core/Fuzzy.h"
-#include "src/Core/Swap.h"
-#include "src/Core/CommaInitializer.h"
-#include "src/Core/GeneralProduct.h"
-#include "src/Core/Solve.h"
-#include "src/Core/Inverse.h"
-#include "src/Core/SolverBase.h"
-#include "src/Core/PermutationMatrix.h"
-#include "src/Core/Transpositions.h"
-#include "src/Core/TriangularMatrix.h"
-#include "src/Core/SelfAdjointView.h"
-#include "src/Core/products/GeneralBlockPanelKernel.h"
-#include "src/Core/products/Parallelizer.h"
-#include "src/Core/ProductEvaluators.h"
-#include "src/Core/products/GeneralMatrixVector.h"
-#include "src/Core/products/GeneralMatrixMatrix.h"
-#include "src/Core/SolveTriangular.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular.h"
-#include "src/Core/products/SelfadjointMatrixVector.h"
-#include "src/Core/products/SelfadjointMatrixMatrix.h"
-#include "src/Core/products/SelfadjointProduct.h"
-#include "src/Core/products/SelfadjointRank2Update.h"
-#include "src/Core/products/TriangularMatrixVector.h"
-#include "src/Core/products/TriangularMatrixMatrix.h"
-#include "src/Core/products/TriangularSolverMatrix.h"
-#include "src/Core/products/TriangularSolverVector.h"
-#include "src/Core/BandMatrix.h"
-#include "src/Core/CoreIterators.h"
-#include "src/Core/ConditionEstimator.h"
-
-#include "src/Core/BooleanRedux.h"
-#include "src/Core/Select.h"
-#include "src/Core/VectorwiseOp.h"
-#include "src/Core/Random.h"
-#include "src/Core/Replicate.h"
-#include "src/Core/Reverse.h"
-#include "src/Core/ArrayWrapper.h"
-
-#ifdef EIGEN_USE_BLAS
-#include "src/Core/products/GeneralMatrixMatrix_BLAS.h"
-#include "src/Core/products/GeneralMatrixVector_BLAS.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixMatrix_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularMatrixMatrix_BLAS.h"
-#include "src/Core/products/TriangularMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularSolverMatrix_BLAS.h"
-#endif // EIGEN_USE_BLAS
-
-#ifdef EIGEN_USE_MKL_VML
-#include "src/Core/Assign_MKL.h"
-#endif
-
-#include "src/Core/GlobalFunctions.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_CORE_H

deps_src/eigen/Eigen/Dense

@@ -1,7 +0,0 @@
-#include "Core"
-#include "LU"
-#include "Cholesky"
-#include "QR"
-#include "SVD"
-#include "Geometry"
-#include "Eigenvalues"

deps_src/eigen/Eigen/Eigen

@@ -1,2 +0,0 @@
-#include "Dense"
-#include "Sparse"

deps_src/eigen/Eigen/Eigenvalues

@@ -1,61 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_EIGENVALUES_MODULE_H
-#define EIGEN_EIGENVALUES_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "Cholesky"
-#include "Jacobi"
-#include "Householder"
-#include "LU"
-#include "Geometry"
-
-/** \defgroup Eigenvalues_Module Eigenvalues module
-  *
-  *
-  *
-  * This module mainly provides various eigenvalue solvers.
-  * This module also provides some MatrixBase methods, including:
-  *  - MatrixBase::eigenvalues(),
-  *  - MatrixBase::operatorNorm()
-  *
-  * \code
-  * #include <Eigen/Eigenvalues>
-  * \endcode
-  */
-
-#include "src/misc/RealSvd2x2.h"
-#include "src/Eigenvalues/Tridiagonalization.h"
-#include "src/Eigenvalues/RealSchur.h"
-#include "src/Eigenvalues/EigenSolver.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver.h"
-#include "src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h"
-#include "src/Eigenvalues/HessenbergDecomposition.h"
-#include "src/Eigenvalues/ComplexSchur.h"
-#include "src/Eigenvalues/ComplexEigenSolver.h"
-#include "src/Eigenvalues/RealQZ.h"
-#include "src/Eigenvalues/GeneralizedEigenSolver.h"
-#include "src/Eigenvalues/MatrixBaseEigenvalues.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/Eigenvalues/RealSchur_LAPACKE.h"
-#include "src/Eigenvalues/ComplexSchur_LAPACKE.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_EIGENVALUES_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/Geometry

@@ -1,62 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GEOMETRY_MODULE_H
-#define EIGEN_GEOMETRY_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "SVD"
-#include "LU"
-#include <limits>
-
-/** \defgroup Geometry_Module Geometry module
-  *
-  * This module provides support for:
-  *  - fixed-size homogeneous transformations
-  *  - translation, scaling, 2D and 3D rotations
-  *  - \link Quaternion quaternions \endlink
-  *  - cross products (\ref MatrixBase::cross, \ref MatrixBase::cross3)
-  *  - orthognal vector generation (\ref MatrixBase::unitOrthogonal)
-  *  - some linear components: \link ParametrizedLine parametrized-lines \endlink and \link Hyperplane hyperplanes \endlink
-  *  - \link AlignedBox axis aligned bounding boxes \endlink
-  *  - \link umeyama least-square transformation fitting \endlink
-  *
-  * \code
-  * #include <Eigen/Geometry>
-  * \endcode
-  */
-
-#include "src/Geometry/OrthoMethods.h"
-#include "src/Geometry/EulerAngles.h"
-
-#include "src/Geometry/Homogeneous.h"
-#include "src/Geometry/RotationBase.h"
-#include "src/Geometry/Rotation2D.h"
-#include "src/Geometry/Quaternion.h"
-#include "src/Geometry/AngleAxis.h"
-#include "src/Geometry/Transform.h"
-#include "src/Geometry/Translation.h"
-#include "src/Geometry/Scaling.h"
-#include "src/Geometry/Hyperplane.h"
-#include "src/Geometry/ParametrizedLine.h"
-#include "src/Geometry/AlignedBox.h"
-#include "src/Geometry/Umeyama.h"
-
-// Use the SSE optimized version whenever possible. At the moment the
-// SSE version doesn't compile when AVX is enabled
-#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
-#include "src/Geometry/arch/Geometry_SSE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_GEOMETRY_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */
-

deps_src/eigen/Eigen/Householder

@@ -1,30 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_HOUSEHOLDER_MODULE_H
-#define EIGEN_HOUSEHOLDER_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup Householder_Module Householder module
-  * This module provides Householder transformations.
-  *
-  * \code
-  * #include <Eigen/Householder>
-  * \endcode
-  */
-
-#include "src/Householder/Householder.h"
-#include "src/Householder/HouseholderSequence.h"
-#include "src/Householder/BlockHouseholder.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_HOUSEHOLDER_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/IterativeLinearSolvers

@@ -1,48 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
-#define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
-
-#include "SparseCore"
-#include "OrderingMethods"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** 
-  * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
-  *
-  * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
-  * Those solvers are accessible via the following classes:
-  *  - ConjugateGradient for selfadjoint (hermitian) matrices,
-  *  - LeastSquaresConjugateGradient for rectangular least-square problems,
-  *  - BiCGSTAB for general square matrices.
-  *
-  * These iterative solvers are associated with some preconditioners:
-  *  - IdentityPreconditioner - not really useful
-  *  - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
-  *  - IncompleteLUT - incomplete LU factorization with dual thresholding
-  *
-  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
-  *
-    \code
-    #include <Eigen/IterativeLinearSolvers>
-    \endcode
-  */
-
-#include "src/IterativeLinearSolvers/SolveWithGuess.h"
-#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
-#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
-#include "src/IterativeLinearSolvers/ConjugateGradient.h"
-#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
-#include "src/IterativeLinearSolvers/BiCGSTAB.h"
-#include "src/IterativeLinearSolvers/IncompleteLUT.h"
-#include "src/IterativeLinearSolvers/IncompleteCholesky.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

deps_src/eigen/Eigen/Jacobi

@@ -1,33 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_JACOBI_MODULE_H
-#define EIGEN_JACOBI_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup Jacobi_Module Jacobi module
-  * This module provides Jacobi and Givens rotations.
-  *
-  * \code
-  * #include <Eigen/Jacobi>
-  * \endcode
-  *
-  * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation:
-  *  - MatrixBase::applyOnTheLeft()
-  *  - MatrixBase::applyOnTheRight().
-  */
-
-#include "src/Jacobi/Jacobi.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_JACOBI_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */
-

deps_src/eigen/Eigen/LU

@@ -1,50 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_LU_MODULE_H
-#define EIGEN_LU_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup LU_Module LU module
-  * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
-  * This module defines the following MatrixBase methods:
-  *  - MatrixBase::inverse()
-  *  - MatrixBase::determinant()
-  *
-  * \code
-  * #include <Eigen/LU>
-  * \endcode
-  */
-
-#include "src/misc/Kernel.h"
-#include "src/misc/Image.h"
-#include "src/LU/FullPivLU.h"
-#include "src/LU/PartialPivLU.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/LU/PartialPivLU_LAPACKE.h"
-#endif
-#include "src/LU/Determinant.h"
-#include "src/LU/InverseImpl.h"
-
-// Use the SSE optimized version whenever possible. At the moment the
-// SSE version doesn't compile when AVX is enabled
-#if defined EIGEN_VECTORIZE_SSE && !defined EIGEN_VECTORIZE_AVX
-  #include "src/LU/arch/Inverse_SSE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_LU_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/MetisSupport

@@ -1,35 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_METISSUPPORT_MODULE_H
-#define EIGEN_METISSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <metis.h>
-}
-
-
-/** \ingroup Support_modules
-  * \defgroup MetisSupport_Module MetisSupport module
-  *
-  * \code
-  * #include <Eigen/MetisSupport>
-  * \endcode
-  * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis). 
-  * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
-  */
-
-
-#include "src/MetisSupport/MetisSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_METISSUPPORT_MODULE_H

deps_src/eigen/Eigen/OrderingMethods

@@ -1,73 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ORDERINGMETHODS_MODULE_H
-#define EIGEN_ORDERINGMETHODS_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** 
-  * \defgroup OrderingMethods_Module OrderingMethods module
-  *
-  * This module is currently for internal use only
-  * 
-  * It defines various built-in and external ordering methods for sparse matrices. 
-  * They are typically used to reduce the number of elements during 
-  * the sparse matrix decomposition (LLT, LU, QR).
-  * Precisely, in a preprocessing step, a permutation matrix P is computed using 
-  * those ordering methods and applied to the columns of the matrix. 
-  * Using for instance the sparse Cholesky decomposition, it is expected that 
-  * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
-  * 
-  * 
-  * Usage : 
-  * \code
-  * #include <Eigen/OrderingMethods>
-  * \endcode
-  * 
-  * A simple usage is as a template parameter in the sparse decomposition classes : 
-  * 
-  * \code 
-  * SparseLU<MatrixType, COLAMDOrdering<int> > solver;
-  * \endcode 
-  * 
-  * \code 
-  * SparseQR<MatrixType, COLAMDOrdering<int> > solver;
-  * \endcode
-  * 
-  * It is possible as well to call directly a particular ordering method for your own purpose, 
-  * \code 
-  * AMDOrdering<int> ordering;
-  * PermutationMatrix<Dynamic, Dynamic, int> perm;
-  * SparseMatrix<double> A; 
-  * //Fill the matrix ...
-  * 
-  * ordering(A, perm); // Call AMD
-  * \endcode
-  * 
-  * \note Some of these methods (like AMD or METIS), need the sparsity pattern 
-  * of the input matrix to be symmetric. When the matrix is structurally unsymmetric, 
-  * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method.
-  * If your matrix is already symmetric (at leat in structure), you can avoid that
-  * by calling the method with a SelfAdjointView type.
-  * 
-  * \code
-  *  // Call the ordering on the pattern of the lower triangular matrix A
-  * ordering(A.selfadjointView<Lower>(), perm);
-  * \endcode
-  */
-
-#ifndef EIGEN_MPL2_ONLY
-#include "src/OrderingMethods/Amd.h"
-#endif
-
-#include "src/OrderingMethods/Ordering.h"
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_ORDERINGMETHODS_MODULE_H

deps_src/eigen/Eigen/PaStiXSupport

@@ -1,48 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_PASTIXSUPPORT_MODULE_H
-#define EIGEN_PASTIXSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <pastix_nompi.h>
-#include <pastix.h>
-}
-
-#ifdef complex
-#undef complex
-#endif
-
-/** \ingroup Support_modules
-  * \defgroup PaStiXSupport_Module PaStiXSupport module
-  * 
-  * This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
-  * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
-  * It provides the two following main factorization classes:
-  * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
-  * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
-  * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
-  * 
-  * \code
-  * #include <Eigen/PaStiXSupport>
-  * \endcode
-  *
-  * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies.
-  * The dependencies depend on how PaSTiX has been compiled.
-  * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
-  *
-  */
-
-#include "src/PaStiXSupport/PaStiXSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_PASTIXSUPPORT_MODULE_H

deps_src/eigen/Eigen/PardisoSupport

@@ -1,35 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_PARDISOSUPPORT_MODULE_H
-#define EIGEN_PARDISOSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <mkl_pardiso.h>
-
-/** \ingroup Support_modules
-  * \defgroup PardisoSupport_Module PardisoSupport module
-  *
-  * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
-  *
-  * \code
-  * #include <Eigen/PardisoSupport>
-  * \endcode
-  *
-  * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies.
-  * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration.
-  * 
-  */
-
-#include "src/PardisoSupport/PardisoSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_PARDISOSUPPORT_MODULE_H

deps_src/eigen/Eigen/QR

@@ -1,51 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_QR_MODULE_H
-#define EIGEN_QR_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "Cholesky"
-#include "Jacobi"
-#include "Householder"
-
-/** \defgroup QR_Module QR module
-  *
-  *
-  *
-  * This module provides various QR decompositions
-  * This module also provides some MatrixBase methods, including:
-  *  - MatrixBase::householderQr()
-  *  - MatrixBase::colPivHouseholderQr()
-  *  - MatrixBase::fullPivHouseholderQr()
-  *
-  * \code
-  * #include <Eigen/QR>
-  * \endcode
-  */
-
-#include "src/QR/HouseholderQR.h"
-#include "src/QR/FullPivHouseholderQR.h"
-#include "src/QR/ColPivHouseholderQR.h"
-#include "src/QR/CompleteOrthogonalDecomposition.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/QR/HouseholderQR_LAPACKE.h"
-#include "src/QR/ColPivHouseholderQR_LAPACKE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_QR_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/QtAlignedMalloc

@@ -1,40 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_QTMALLOC_MODULE_H
-#define EIGEN_QTMALLOC_MODULE_H
-
-#include "Core"
-
-#if (!EIGEN_MALLOC_ALREADY_ALIGNED)
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-void *qMalloc(std::size_t size)
-{
-  return Eigen::internal::aligned_malloc(size);
-}
-
-void qFree(void *ptr)
-{
-  Eigen::internal::aligned_free(ptr);
-}
-
-void *qRealloc(void *ptr, std::size_t size)
-{
-  void* newPtr = Eigen::internal::aligned_malloc(size);
-  std::memcpy(newPtr, ptr, size);
-  Eigen::internal::aligned_free(ptr);
-  return newPtr;
-}
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif
-
-#endif // EIGEN_QTMALLOC_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/SPQRSupport

@@ -1,34 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPQRSUPPORT_MODULE_H
-#define EIGEN_SPQRSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "SuiteSparseQR.hpp"
-
-/** \ingroup Support_modules
-  * \defgroup SPQRSupport_Module SuiteSparseQR module
-  * 
-  * This module provides an interface to the SPQR library, which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
-  *
-  * \code
-  * #include <Eigen/SPQRSupport>
-  * \endcode
-  *
-  * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...).
-  * For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules
-  *
-  */
-
-#include "src/CholmodSupport/CholmodSupport.h"
-#include "src/SPQRSupport/SuiteSparseQRSupport.h"
-
-#endif

deps_src/eigen/Eigen/SVD

@@ -1,51 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SVD_MODULE_H
-#define EIGEN_SVD_MODULE_H
-
-#include "QR"
-#include "Householder"
-#include "Jacobi"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup SVD_Module SVD module
-  *
-  *
-  *
-  * This module provides SVD decomposition for matrices (both real and complex).
-  * Two decomposition algorithms are provided:
-  *  - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very slow for larger ones.
-  *  - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast for large problems.
-  * These decompositions are accessible via the respective classes and following MatrixBase methods:
-  *  - MatrixBase::jacobiSvd()
-  *  - MatrixBase::bdcSvd()
-  *
-  * \code
-  * #include <Eigen/SVD>
-  * \endcode
-  */
-
-#include "src/misc/RealSvd2x2.h"
-#include "src/SVD/UpperBidiagonalization.h"
-#include "src/SVD/SVDBase.h"
-#include "src/SVD/JacobiSVD.h"
-#include "src/SVD/BDCSVD.h"
-#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/SVD/JacobiSVD_LAPACKE.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SVD_MODULE_H
-/* vim: set filetype=cpp et sw=2 ts=2 ai: */

deps_src/eigen/Eigen/Sparse

@@ -1,36 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSE_MODULE_H
-#define EIGEN_SPARSE_MODULE_H
-
-/** \defgroup Sparse_Module Sparse meta-module
-  *
-  * Meta-module including all related modules:
-  * - \ref SparseCore_Module
-  * - \ref OrderingMethods_Module
-  * - \ref SparseCholesky_Module
-  * - \ref SparseLU_Module
-  * - \ref SparseQR_Module
-  * - \ref IterativeLinearSolvers_Module
-  *
-    \code
-    #include <Eigen/Sparse>
-    \endcode
-  */
-
-#include "SparseCore"
-#include "OrderingMethods"
-#ifndef EIGEN_MPL2_ONLY
-#include "SparseCholesky"
-#endif
-#include "SparseLU"
-#include "SparseQR"
-#include "IterativeLinearSolvers"
-
-#endif // EIGEN_SPARSE_MODULE_H
-

deps_src/eigen/Eigen/SparseCholesky

@@ -1,45 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2013 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSECHOLESKY_MODULE_H
-#define EIGEN_SPARSECHOLESKY_MODULE_H
-
-#include "SparseCore"
-#include "OrderingMethods"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** 
-  * \defgroup SparseCholesky_Module SparseCholesky module
-  *
-  * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices.
-  * Those decompositions are accessible via the following classes:
-  *  - SimplicialLLt,
-  *  - SimplicialLDLt
-  *
-  * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
-  *
-  * \code
-  * #include <Eigen/SparseCholesky>
-  * \endcode
-  */
-
-#ifdef EIGEN_MPL2_ONLY
-#error The SparseCholesky module has nothing to offer in MPL2 only mode
-#endif
-
-#include "src/SparseCholesky/SimplicialCholesky.h"
-
-#ifndef EIGEN_MPL2_ONLY
-#include "src/SparseCholesky/SimplicialCholesky_impl.h"
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SPARSECHOLESKY_MODULE_H

deps_src/eigen/Eigen/SparseCore

@@ -1,69 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSECORE_MODULE_H
-#define EIGEN_SPARSECORE_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <vector>
-#include <map>
-#include <cstdlib>
-#include <cstring>
-#include <algorithm>
-
-/** 
-  * \defgroup SparseCore_Module SparseCore module
-  *
-  * This module provides a sparse matrix representation, and basic associated matrix manipulations
-  * and operations.
-  *
-  * See the \ref TutorialSparse "Sparse tutorial"
-  *
-  * \code
-  * #include <Eigen/SparseCore>
-  * \endcode
-  *
-  * This module depends on: Core.
-  */
-
-#include "src/SparseCore/SparseUtil.h"
-#include "src/SparseCore/SparseMatrixBase.h"
-#include "src/SparseCore/SparseAssign.h"
-#include "src/SparseCore/CompressedStorage.h"
-#include "src/SparseCore/AmbiVector.h"
-#include "src/SparseCore/SparseCompressedBase.h"
-#include "src/SparseCore/SparseMatrix.h"
-#include "src/SparseCore/SparseMap.h"
-#include "src/SparseCore/MappedSparseMatrix.h"
-#include "src/SparseCore/SparseVector.h"
-#include "src/SparseCore/SparseRef.h"
-#include "src/SparseCore/SparseCwiseUnaryOp.h"
-#include "src/SparseCore/SparseCwiseBinaryOp.h"
-#include "src/SparseCore/SparseTranspose.h"
-#include "src/SparseCore/SparseBlock.h"
-#include "src/SparseCore/SparseDot.h"
-#include "src/SparseCore/SparseRedux.h"
-#include "src/SparseCore/SparseView.h"
-#include "src/SparseCore/SparseDiagonalProduct.h"
-#include "src/SparseCore/ConservativeSparseSparseProduct.h"
-#include "src/SparseCore/SparseSparseProductWithPruning.h"
-#include "src/SparseCore/SparseProduct.h"
-#include "src/SparseCore/SparseDenseProduct.h"
-#include "src/SparseCore/SparseSelfAdjointView.h"
-#include "src/SparseCore/SparseTriangularView.h"
-#include "src/SparseCore/TriangularSolver.h"
-#include "src/SparseCore/SparsePermutation.h"
-#include "src/SparseCore/SparseFuzzy.h"
-#include "src/SparseCore/SparseSolverBase.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SPARSECORE_MODULE_H
-

deps_src/eigen/Eigen/SparseLU

@@ -1,46 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
-// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSELU_MODULE_H
-#define EIGEN_SPARSELU_MODULE_H
-
-#include "SparseCore"
-
-/** 
-  * \defgroup SparseLU_Module SparseLU module
-  * This module defines a supernodal factorization of general sparse matrices.
-  * The code is fully optimized for supernode-panel updates with specialized kernels.
-  * Please, see the documentation of the SparseLU class for more details.
-  */
-
-// Ordering interface
-#include "OrderingMethods"
-
-#include "src/SparseLU/SparseLU_gemm_kernel.h"
-
-#include "src/SparseLU/SparseLU_Structs.h"
-#include "src/SparseLU/SparseLU_SupernodalMatrix.h"
-#include "src/SparseLU/SparseLUImpl.h"
-#include "src/SparseCore/SparseColEtree.h"
-#include "src/SparseLU/SparseLU_Memory.h"
-#include "src/SparseLU/SparseLU_heap_relax_snode.h"
-#include "src/SparseLU/SparseLU_relax_snode.h"
-#include "src/SparseLU/SparseLU_pivotL.h"
-#include "src/SparseLU/SparseLU_panel_dfs.h"
-#include "src/SparseLU/SparseLU_kernel_bmod.h"
-#include "src/SparseLU/SparseLU_panel_bmod.h"
-#include "src/SparseLU/SparseLU_column_dfs.h"
-#include "src/SparseLU/SparseLU_column_bmod.h"
-#include "src/SparseLU/SparseLU_copy_to_ucol.h"
-#include "src/SparseLU/SparseLU_pruneL.h"
-#include "src/SparseLU/SparseLU_Utils.h"
-#include "src/SparseLU/SparseLU.h"
-
-#endif // EIGEN_SPARSELU_MODULE_H

deps_src/eigen/Eigen/SparseQR

@@ -1,37 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSEQR_MODULE_H
-#define EIGEN_SPARSEQR_MODULE_H
-
-#include "SparseCore"
-#include "OrderingMethods"
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup SparseQR_Module SparseQR module
-  * \brief Provides QR decomposition for sparse matrices
-  * 
-  * This module provides a simplicial version of the left-looking Sparse QR decomposition. 
-  * The columns of the input matrix should be reordered to limit the fill-in during the 
-  * decomposition. Built-in methods (COLAMD, AMD) or external  methods (METIS) can be used to this end.
-  * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list 
-  * of built-in and external ordering methods.
-  * 
-  * \code
-  * #include <Eigen/SparseQR>
-  * \endcode
-  * 
-  * 
-  */
-
-#include "OrderingMethods"
-#include "src/SparseCore/SparseColEtree.h"
-#include "src/SparseQR/SparseQR.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif

deps_src/eigen/Eigen/StdDeque

@@ -1,27 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_STDDEQUE_MODULE_H
-#define EIGEN_STDDEQUE_MODULE_H
-
-#include "Core"
-#include <deque>
-
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
-
-#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
-
-#else
-
-#include "src/StlSupport/StdDeque.h"
-
-#endif
-
-#endif // EIGEN_STDDEQUE_MODULE_H

deps_src/eigen/Eigen/StdList

@@ -1,26 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_STDLIST_MODULE_H
-#define EIGEN_STDLIST_MODULE_H
-
-#include "Core"
-#include <list>
-
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
-
-#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
-
-#else
-
-#include "src/StlSupport/StdList.h"
-
-#endif
-
-#endif // EIGEN_STDLIST_MODULE_H

deps_src/eigen/Eigen/StdVector

@@ -1,27 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_STDVECTOR_MODULE_H
-#define EIGEN_STDVECTOR_MODULE_H
-
-#include "Core"
-#include <vector>
-
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && (EIGEN_MAX_STATIC_ALIGN_BYTES<=16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
-
-#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
-
-#else
-
-#include "src/StlSupport/StdVector.h"
-
-#endif
-
-#endif // EIGEN_STDVECTOR_MODULE_H

deps_src/eigen/Eigen/SuperLUSupport

@@ -1,64 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
-#define EIGEN_SUPERLUSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#ifdef EMPTY
-#define EIGEN_EMPTY_WAS_ALREADY_DEFINED
-#endif
-
-typedef int int_t;
-#include <slu_Cnames.h>
-#include <supermatrix.h>
-#include <slu_util.h>
-
-// slu_util.h defines a preprocessor token named EMPTY which is really polluting,
-// so we remove it in favor of a SUPERLU_EMPTY token.
-// If EMPTY was already defined then we don't undef it.
-
-#if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED)
-# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
-#elif defined(EMPTY)
-# undef EMPTY
-#endif
-
-#define SUPERLU_EMPTY (-1)
-
-namespace Eigen { struct SluMatrix; }
-
-/** \ingroup Support_modules
-  * \defgroup SuperLUSupport_Module SuperLUSupport module
-  *
-  * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
-  * It provides the following factorization class:
-  * - class SuperLU: a supernodal sequential LU factorization.
-  * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
-  *
-  * \warning This wrapper requires at least versions 4.0 of SuperLU. The 3.x versions are not supported.
-  *
-  * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
-  *
-  * \code
-  * #include <Eigen/SuperLUSupport>
-  * \endcode
-  *
-  * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies.
-  * The dependencies depend on how superlu has been compiled.
-  * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
-  *
-  */
-
-#include "src/SuperLUSupport/SuperLUSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

deps_src/eigen/Eigen/UmfPackSupport

@@ -1,40 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
-#define EIGEN_UMFPACKSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <umfpack.h>
-}
-
-/** \ingroup Support_modules
-  * \defgroup UmfPackSupport_Module UmfPackSupport module
-  *
-  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
-  * It provides the following factorization class:
-  * - class UmfPackLU: a multifrontal sequential LU factorization.
-  *
-  * \code
-  * #include <Eigen/UmfPackSupport>
-  * \endcode
-  *
-  * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
-  * The dependencies depend on how umfpack has been compiled.
-  * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
-  *
-  */
-
-#include "src/UmfPackSupport/UmfPackSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

deps_src/eigen/Eigen/src/Cholesky/LDLT.h

@@ -1,673 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2009 Keir Mierle <mierle@gmail.com>
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2011 Timothy E. Holy <tim.holy@gmail.com >
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_LDLT_H
-#define EIGEN_LDLT_H
-
-namespace Eigen {
-
-namespace internal {
-  template<typename MatrixType, int UpLo> struct LDLT_Traits;
-
-  // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef
-  enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite };
-}
-
-/** \ingroup Cholesky_Module
-  *
-  * \class LDLT
-  *
-  * \brief Robust Cholesky decomposition of a matrix with pivoting
-  *
-  * \tparam _MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
-  * \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
-  *             The other triangular part won't be read.
-  *
-  * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite
-  * matrix \f$ A \f$ such that \f$ A =  P^TLDL^*P \f$, where P is a permutation matrix, L
-  * is lower triangular with a unit diagonal and D is a diagonal matrix.
-  *
-  * The decomposition uses pivoting to ensure stability, so that L will have
-  * zeros in the bottom right rank(A) - n submatrix. Avoiding the square root
-  * on D also stabilizes the computation.
-  *
-  * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky
-  * decomposition to determine whether a system of equations has a solution.
-  *
-  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
-  * 
-  * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT
-  */
-template<typename _MatrixType, int _UpLo> class LDLT
-{
-  public:
-    typedef _MatrixType MatrixType;
-    enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-      UpLo = _UpLo
-    };
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
-    typedef typename MatrixType::StorageIndex StorageIndex;
-    typedef Matrix<Scalar, RowsAtCompileTime, 1, 0, MaxRowsAtCompileTime, 1> TmpMatrixType;
-
-    typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
-    typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationType;
-
-    typedef internal::LDLT_Traits<MatrixType,UpLo> Traits;
-
-    /** \brief Default Constructor.
-      *
-      * The default constructor is useful in cases in which the user intends to
-      * perform decompositions via LDLT::compute(const MatrixType&).
-      */
-    LDLT()
-      : m_matrix(),
-        m_transpositions(),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false)
-    {}
-
-    /** \brief Default Constructor with memory preallocation
-      *
-      * Like the default constructor but with preallocation of the internal data
-      * according to the specified problem \a size.
-      * \sa LDLT()
-      */
-    explicit LDLT(Index size)
-      : m_matrix(size, size),
-        m_transpositions(size),
-        m_temporary(size),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false)
-    {}
-
-    /** \brief Constructor with decomposition
-      *
-      * This calculates the decomposition for the input \a matrix.
-      *
-      * \sa LDLT(Index size)
-      */
-    template<typename InputType>
-    explicit LDLT(const EigenBase<InputType>& matrix)
-      : m_matrix(matrix.rows(), matrix.cols()),
-        m_transpositions(matrix.rows()),
-        m_temporary(matrix.rows()),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false)
-    {
-      compute(matrix.derived());
-    }
-
-    /** \brief Constructs a LDLT factorization from a given matrix
-      *
-      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c MatrixType is a Eigen::Ref.
-      *
-      * \sa LDLT(const EigenBase&)
-      */
-    template<typename InputType>
-    explicit LDLT(EigenBase<InputType>& matrix)
-      : m_matrix(matrix.derived()),
-        m_transpositions(matrix.rows()),
-        m_temporary(matrix.rows()),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false)
-    {
-      compute(matrix.derived());
-    }
-
-    /** Clear any existing decomposition
-     * \sa rankUpdate(w,sigma)
-     */
-    void setZero()
-    {
-      m_isInitialized = false;
-    }
-
-    /** \returns a view of the upper triangular matrix U */
-    inline typename Traits::MatrixU matrixU() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return Traits::getU(m_matrix);
-    }
-
-    /** \returns a view of the lower triangular matrix L */
-    inline typename Traits::MatrixL matrixL() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return Traits::getL(m_matrix);
-    }
-
-    /** \returns the permutation matrix P as a transposition sequence.
-      */
-    inline const TranspositionType& transpositionsP() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_transpositions;
-    }
-
-    /** \returns the coefficients of the diagonal matrix D */
-    inline Diagonal<const MatrixType> vectorD() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_matrix.diagonal();
-    }
-
-    /** \returns true if the matrix is positive (semidefinite) */
-    inline bool isPositive() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign;
-    }
-
-    /** \returns true if the matrix is negative (semidefinite) */
-    inline bool isNegative(void) const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign;
-    }
-
-    /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * This function also supports in-place solves using the syntax <tt>x = decompositionObject.solve(x)</tt> .
-      *
-      * \note_about_checking_solutions
-      *
-      * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$
-      * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$,
-      * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then
-      * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the
-      * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function
-      * computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular.
-      *
-      * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt()
-      */
-    template<typename Rhs>
-    inline const Solve<LDLT, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      eigen_assert(m_matrix.rows()==b.rows()
-                && "LDLT::solve(): invalid number of rows of the right hand side matrix b");
-      return Solve<LDLT, Rhs>(*this, b.derived());
-    }
-
-    template<typename Derived>
-    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
-
-    template<typename InputType>
-    LDLT& compute(const EigenBase<InputType>& matrix);
-
-    /** \returns an estimate of the reciprocal condition number of the matrix of
-     *  which \c *this is the LDLT decomposition.
-     */
-    RealScalar rcond() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return internal::rcond_estimate_helper(m_l1_norm, *this);
-    }
-
-    template <typename Derived>
-    LDLT& rankUpdate(const MatrixBase<Derived>& w, const RealScalar& alpha=1);
-
-    /** \returns the internal LDLT decomposition matrix
-      *
-      * TODO: document the storage layout
-      */
-    inline const MatrixType& matrixLDLT() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_matrix;
-    }
-
-    MatrixType reconstructedMatrix() const;
-
-    /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix is self-adjoint.
-      *
-      * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
-      * \code x = decomposition.adjoint().solve(b) \endcode
-      */
-    const LDLT& adjoint() const { return *this; };
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the factorization failed because of a zero pivot.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return m_info;
-    }
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename RhsType, typename DstType>
-    EIGEN_DEVICE_FUNC
-    void _solve_impl(const RhsType &rhs, DstType &dst) const;
-    #endif
-
-  protected:
-
-    static void check_template_parameters()
-    {
-      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
-    }
-
-    /** \internal
-      * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
-      * The strict upper part is used during the decomposition, the strict lower
-      * part correspond to the coefficients of L (its diagonal is equal to 1 and
-      * is not stored), and the diagonal entries correspond to D.
-      */
-    MatrixType m_matrix;
-    RealScalar m_l1_norm;
-    TranspositionType m_transpositions;
-    TmpMatrixType m_temporary;
-    internal::SignMatrix m_sign;
-    bool m_isInitialized;
-    ComputationInfo m_info;
-};
-
-namespace internal {
-
-template<int UpLo> struct ldlt_inplace;
-
-template<> struct ldlt_inplace<Lower>
-{
-  template<typename MatrixType, typename TranspositionType, typename Workspace>
-  static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
-  {
-    using std::abs;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename TranspositionType::StorageIndex IndexType;
-    eigen_assert(mat.rows()==mat.cols());
-    const Index size = mat.rows();
-    bool found_zero_pivot = false;
-    bool ret = true;
-
-    if (size <= 1)
-    {
-      transpositions.setIdentity();
-      if(size==0) sign = ZeroSign;
-      else if (numext::real(mat.coeff(0,0)) > static_cast<RealScalar>(0) ) sign = PositiveSemiDef;
-      else if (numext::real(mat.coeff(0,0)) < static_cast<RealScalar>(0)) sign = NegativeSemiDef;
-      else sign = ZeroSign;
-      return true;
-    }
-
-    for (Index k = 0; k < size; ++k)
-    {
-      // Find largest diagonal element
-      Index index_of_biggest_in_corner;
-      mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
-      index_of_biggest_in_corner += k;
-
-      transpositions.coeffRef(k) = IndexType(index_of_biggest_in_corner);
-      if(k != index_of_biggest_in_corner)
-      {
-        // apply the transposition while taking care to consider only
-        // the lower triangular part
-        Index s = size-index_of_biggest_in_corner-1; // trailing size after the biggest element
-        mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k));
-        mat.col(k).tail(s).swap(mat.col(index_of_biggest_in_corner).tail(s));
-        std::swap(mat.coeffRef(k,k),mat.coeffRef(index_of_biggest_in_corner,index_of_biggest_in_corner));
-        for(Index i=k+1;i<index_of_biggest_in_corner;++i)
-        {
-          Scalar tmp = mat.coeffRef(i,k);
-          mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i));
-          mat.coeffRef(index_of_biggest_in_corner,i) = numext::conj(tmp);
-        }
-        if(NumTraits<Scalar>::IsComplex)
-          mat.coeffRef(index_of_biggest_in_corner,k) = numext::conj(mat.coeff(index_of_biggest_in_corner,k));
-      }
-
-      // partition the matrix:
-      //       A00 |  -  |  -
-      // lu  = A10 | A11 |  -
-      //       A20 | A21 | A22
-      Index rs = size - k - 1;
-      Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
-      Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
-      Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
-
-      if(k>0)
-      {
-        temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
-        mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
-        if(rs>0)
-          A21.noalias() -= A20 * temp.head(k);
-      }
-
-      // In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot
-      // was smaller than the cutoff value. However, since LDLT is not rank-revealing
-      // we should only make sure that we do not introduce INF or NaN values.
-      // Remark that LAPACK also uses 0 as the cutoff value.
-      RealScalar realAkk = numext::real(mat.coeffRef(k,k));
-      bool pivot_is_valid = (abs(realAkk) > RealScalar(0));
-
-      if(k==0 && !pivot_is_valid)
-      {
-        // The entire diagonal is zero, there is nothing more to do
-        // except filling the transpositions, and checking whether the matrix is zero.
-        sign = ZeroSign;
-        for(Index j = 0; j<size; ++j)
-        {
-          transpositions.coeffRef(j) = IndexType(j);
-          ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all();
-        }
-        return ret;
-      }
-
-      if((rs>0) && pivot_is_valid)
-        A21 /= realAkk;
-      else if(rs>0)
-        ret = ret && (A21.array()==Scalar(0)).all();
-
-      if(found_zero_pivot && pivot_is_valid) ret = false; // factorization failed
-      else if(!pivot_is_valid) found_zero_pivot = true;
-
-      if (sign == PositiveSemiDef) {
-        if (realAkk < static_cast<RealScalar>(0)) sign = Indefinite;
-      } else if (sign == NegativeSemiDef) {
-        if (realAkk > static_cast<RealScalar>(0)) sign = Indefinite;
-      } else if (sign == ZeroSign) {
-        if (realAkk > static_cast<RealScalar>(0)) sign = PositiveSemiDef;
-        else if (realAkk < static_cast<RealScalar>(0)) sign = NegativeSemiDef;
-      }
-    }
-
-    return ret;
-  }
-
-  // Reference for the algorithm: Davis and Hager, "Multiple Rank
-  // Modifications of a Sparse Cholesky Factorization" (Algorithm 1)
-  // Trivial rearrangements of their computations (Timothy E. Holy)
-  // allow their algorithm to work for rank-1 updates even if the
-  // original matrix is not of full rank.
-  // Here only rank-1 updates are implemented, to reduce the
-  // requirement for intermediate storage and improve accuracy
-  template<typename MatrixType, typename WDerived>
-  static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, const typename MatrixType::RealScalar& sigma=1)
-  {
-    using numext::isfinite;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-
-    const Index size = mat.rows();
-    eigen_assert(mat.cols() == size && w.size()==size);
-
-    RealScalar alpha = 1;
-
-    // Apply the update
-    for (Index j = 0; j < size; j++)
-    {
-      // Check for termination due to an original decomposition of low-rank
-      if (!(isfinite)(alpha))
-        break;
-
-      // Update the diagonal terms
-      RealScalar dj = numext::real(mat.coeff(j,j));
-      Scalar wj = w.coeff(j);
-      RealScalar swj2 = sigma*numext::abs2(wj);
-      RealScalar gamma = dj*alpha + swj2;
-
-      mat.coeffRef(j,j) += swj2/alpha;
-      alpha += swj2/dj;
-
-
-      // Update the terms of L
-      Index rs = size-j-1;
-      w.tail(rs) -= wj * mat.col(j).tail(rs);
-      if(gamma != 0)
-        mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs);
-    }
-    return true;
-  }
-
-  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
-  static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, const typename MatrixType::RealScalar& sigma=1)
-  {
-    // Apply the permutation to the input w
-    tmp = transpositions * w;
-
-    return ldlt_inplace<Lower>::updateInPlace(mat,tmp,sigma);
-  }
-};
-
-template<> struct ldlt_inplace<Upper>
-{
-  template<typename MatrixType, typename TranspositionType, typename Workspace>
-  static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
-  {
-    Transpose<MatrixType> matt(mat);
-    return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign);
-  }
-
-  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
-  static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, const typename MatrixType::RealScalar& sigma=1)
-  {
-    Transpose<MatrixType> matt(mat);
-    return ldlt_inplace<Lower>::update(matt, transpositions, tmp, w.conjugate(), sigma);
-  }
-};
-
-template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
-{
-  typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
-};
-
-template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
-{
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
-  typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
-};
-
-} // end namespace internal
-
-/** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix
-  */
-template<typename MatrixType, int _UpLo>
-template<typename InputType>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
-{
-  check_template_parameters();
-
-  eigen_assert(a.rows()==a.cols());
-  const Index size = a.rows();
-
-  m_matrix = a.derived();
-
-  // Compute matrix L1 norm = max abs column sum.
-  m_l1_norm = RealScalar(0);
-  // TODO move this code to SelfAdjointView
-  for (Index col = 0; col < size; ++col) {
-    RealScalar abs_col_sum;
-    if (_UpLo == Lower)
-      abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
-    else
-      abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
-    if (abs_col_sum > m_l1_norm)
-      m_l1_norm = abs_col_sum;
-  }
-
-  m_transpositions.resize(size);
-  m_isInitialized = false;
-  m_temporary.resize(size);
-  m_sign = internal::ZeroSign;
-
-  m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue;
-
-  m_isInitialized = true;
-  return *this;
-}
-
-/** Update the LDLT decomposition:  given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T.
- * \param w a vector to be incorporated into the decomposition.
- * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1.
- * \sa setZero()
-  */
-template<typename MatrixType, int _UpLo>
-template<typename Derived>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
-{
-  typedef typename TranspositionType::StorageIndex IndexType;
-  const Index size = w.rows();
-  if (m_isInitialized)
-  {
-    eigen_assert(m_matrix.rows()==size);
-  }
-  else
-  {
-    m_matrix.resize(size,size);
-    m_matrix.setZero();
-    m_transpositions.resize(size);
-    for (Index i = 0; i < size; i++)
-      m_transpositions.coeffRef(i) = IndexType(i);
-    m_temporary.resize(size);
-    m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
-    m_isInitialized = true;
-  }
-
-  internal::ldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, w, sigma);
-
-  return *this;
-}
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template<typename _MatrixType, int _UpLo>
-template<typename RhsType, typename DstType>
-void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
-{
-  eigen_assert(rhs.rows() == rows());
-  // dst = P b
-  dst = m_transpositions * rhs;
-
-  // dst = L^-1 (P b)
-  matrixL().solveInPlace(dst);
-
-  // dst = D^-1 (L^-1 P b)
-  // more precisely, use pseudo-inverse of D (see bug 241)
-  using std::abs;
-  const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
-  // In some previous versions, tolerance was set to the max of 1/highest (or rather numeric_limits::min())
-  // and the maximal diagonal entry * epsilon as motivated by LAPACK's xGELSS:
-  // RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
-  // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
-  // diagonal element is not well justified and leads to numerical issues in some cases.
-  // Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
-  // Using numeric_limits::min() gives us more robustness to denormals.
-  RealScalar tolerance = (std::numeric_limits<RealScalar>::min)();
-
-  for (Index i = 0; i < vecD.size(); ++i)
-  {
-    if(abs(vecD(i)) > tolerance)
-      dst.row(i) /= vecD(i);
-    else
-      dst.row(i).setZero();
-  }
-
-  // dst = L^-T (D^-1 L^-1 P b)
-  matrixU().solveInPlace(dst);
-
-  // dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
-  dst = m_transpositions.transpose() * dst;
-}
-#endif
-
-/** \internal use x = ldlt_object.solve(x);
-  *
-  * This is the \em in-place version of solve().
-  *
-  * \param bAndX represents both the right-hand side matrix b and result x.
-  *
-  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
-  *
-  * This version avoids a copy when the right hand side matrix b is not
-  * needed anymore.
-  *
-  * \sa LDLT::solve(), MatrixBase::ldlt()
-  */
-template<typename MatrixType,int _UpLo>
-template<typename Derived>
-bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
-{
-  eigen_assert(m_isInitialized && "LDLT is not initialized.");
-  eigen_assert(m_matrix.rows() == bAndX.rows());
-
-  bAndX = this->solve(bAndX);
-
-  return true;
-}
-
-/** \returns the matrix represented by the decomposition,
- * i.e., it returns the product: P^T L D L^* P.
- * This function is provided for debug purpose. */
-template<typename MatrixType, int _UpLo>
-MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
-{
-  eigen_assert(m_isInitialized && "LDLT is not initialized.");
-  const Index size = m_matrix.rows();
-  MatrixType res(size,size);
-
-  // P
-  res.setIdentity();
-  res = transpositionsP() * res;
-  // L^* P
-  res = matrixU() * res;
-  // D(L^*P)
-  res = vectorD().real().asDiagonal() * res;
-  // L(DL^*P)
-  res = matrixL() * res;
-  // P^T (LDL^*P)
-  res = transpositionsP().transpose() * res;
-
-  return res;
-}
-
-/** \cholesky_module
-  * \returns the Cholesky decomposition with full pivoting without square root of \c *this
-  * \sa MatrixBase::ldlt()
-  */
-template<typename MatrixType, unsigned int UpLo>
-inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
-SelfAdjointView<MatrixType, UpLo>::ldlt() const
-{
-  return LDLT<PlainObject,UpLo>(m_matrix);
-}
-
-/** \cholesky_module
-  * \returns the Cholesky decomposition with full pivoting without square root of \c *this
-  * \sa SelfAdjointView::ldlt()
-  */
-template<typename Derived>
-inline const LDLT<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::ldlt() const
-{
-  return LDLT<PlainObject>(derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_LDLT_H

deps_src/eigen/Eigen/src/Cholesky/LLT.h

@@ -1,542 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_LLT_H
-#define EIGEN_LLT_H
-
-namespace Eigen {
-
-namespace internal{
-template<typename MatrixType, int UpLo> struct LLT_Traits;
-}
-
-/** \ingroup Cholesky_Module
-  *
-  * \class LLT
-  *
-  * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
-  *
-  * \tparam _MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
-  * \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
-  *               The other triangular part won't be read.
-  *
-  * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
-  * matrix A such that A = LL^* = U^*U, where L is lower triangular.
-  *
-  * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like  D^*D x = b,
-  * for that purpose, we recommend the Cholesky decomposition without square root which is more stable
-  * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
-  * situations like generalised eigen problems with hermitian matrices.
-  *
-  * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive definite matrices,
-  * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
-  * has a solution.
-  *
-  * Example: \include LLT_example.cpp
-  * Output: \verbinclude LLT_example.out
-  *
-  * \b Performance: for best performance, it is recommended to use a column-major storage format
-  * with the Lower triangular part (the default), or, equivalently, a row-major storage format
-  * with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization
-  * step, and rank-updates can be up to 3 times slower.
-  *
-  * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
-  *
-  * Note that during the decomposition, only the lower (or upper, as defined by _UpLo) triangular part of A is considered.
-  * Therefore, the strict lower part does not have to store correct values.
-  *
-  * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
-  */
-template<typename _MatrixType, int _UpLo> class LLT
-{
-  public:
-    typedef _MatrixType MatrixType;
-    enum {
-      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
-    };
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
-    typedef typename MatrixType::StorageIndex StorageIndex;
-
-    enum {
-      PacketSize = internal::packet_traits<Scalar>::size,
-      AlignmentMask = int(PacketSize)-1,
-      UpLo = _UpLo
-    };
-
-    typedef internal::LLT_Traits<MatrixType,UpLo> Traits;
-
-    /**
-      * \brief Default Constructor.
-      *
-      * The default constructor is useful in cases in which the user intends to
-      * perform decompositions via LLT::compute(const MatrixType&).
-      */
-    LLT() : m_matrix(), m_isInitialized(false) {}
-
-    /** \brief Default Constructor with memory preallocation
-      *
-      * Like the default constructor but with preallocation of the internal data
-      * according to the specified problem \a size.
-      * \sa LLT()
-      */
-    explicit LLT(Index size) : m_matrix(size, size),
-                    m_isInitialized(false) {}
-
-    template<typename InputType>
-    explicit LLT(const EigenBase<InputType>& matrix)
-      : m_matrix(matrix.rows(), matrix.cols()),
-        m_isInitialized(false)
-    {
-      compute(matrix.derived());
-    }
-
-    /** \brief Constructs a LDLT factorization from a given matrix
-      *
-      * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
-      * \c MatrixType is a Eigen::Ref.
-      *
-      * \sa LLT(const EigenBase&)
-      */
-    template<typename InputType>
-    explicit LLT(EigenBase<InputType>& matrix)
-      : m_matrix(matrix.derived()),
-        m_isInitialized(false)
-    {
-      compute(matrix.derived());
-    }
-
-    /** \returns a view of the upper triangular matrix U */
-    inline typename Traits::MatrixU matrixU() const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      return Traits::getU(m_matrix);
-    }
-
-    /** \returns a view of the lower triangular matrix L */
-    inline typename Traits::MatrixL matrixL() const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      return Traits::getL(m_matrix);
-    }
-
-    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * Since this LLT class assumes anyway that the matrix A is invertible, the solution
-      * theoretically exists and is unique regardless of b.
-      *
-      * Example: \include LLT_solve.cpp
-      * Output: \verbinclude LLT_solve.out
-      *
-      * \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt()
-      */
-    template<typename Rhs>
-    inline const Solve<LLT, Rhs>
-    solve(const MatrixBase<Rhs>& b) const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      eigen_assert(m_matrix.rows()==b.rows()
-                && "LLT::solve(): invalid number of rows of the right hand side matrix b");
-      return Solve<LLT, Rhs>(*this, b.derived());
-    }
-
-    template<typename Derived>
-    void solveInPlace(const MatrixBase<Derived> &bAndX) const;
-
-    template<typename InputType>
-    LLT& compute(const EigenBase<InputType>& matrix);
-
-    /** \returns an estimate of the reciprocal condition number of the matrix of
-      *  which \c *this is the Cholesky decomposition.
-      */
-    RealScalar rcond() const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      eigen_assert(m_info == Success && "LLT failed because matrix appears to be negative");
-      return internal::rcond_estimate_helper(m_l1_norm, *this);
-    }
-
-    /** \returns the LLT decomposition matrix
-      *
-      * TODO: document the storage layout
-      */
-    inline const MatrixType& matrixLLT() const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      return m_matrix;
-    }
-
-    MatrixType reconstructedMatrix() const;
-
-
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the matrix.appears not to be positive definite.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "LLT is not initialized.");
-      return m_info;
-    }
-
-    /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix is self-adjoint.
-      *
-      * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
-      * \code x = decomposition.adjoint().solve(b) \endcode
-      */
-    const LLT& adjoint() const { return *this; };
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-
-    template<typename VectorType>
-    LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename RhsType, typename DstType>
-    EIGEN_DEVICE_FUNC
-    void _solve_impl(const RhsType &rhs, DstType &dst) const;
-    #endif
-
-  protected:
-
-    static void check_template_parameters()
-    {
-      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
-    }
-
-    /** \internal
-      * Used to compute and store L
-      * The strict upper part is not used and even not initialized.
-      */
-    MatrixType m_matrix;
-    RealScalar m_l1_norm;
-    bool m_isInitialized;
-    ComputationInfo m_info;
-};
-
-namespace internal {
-
-template<typename Scalar, int UpLo> struct llt_inplace;
-
-template<typename MatrixType, typename VectorType>
-static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
-{
-  using std::sqrt;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::ColXpr ColXpr;
-  typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
-  typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
-  typedef Matrix<Scalar,Dynamic,1> TempVectorType;
-  typedef typename TempVectorType::SegmentReturnType TempVecSegment;
-
-  Index n = mat.cols();
-  eigen_assert(mat.rows()==n && vec.size()==n);
-
-  TempVectorType temp;
-
-  if(sigma>0)
-  {
-    // This version is based on Givens rotations.
-    // It is faster than the other one below, but only works for updates,
-    // i.e., for sigma > 0
-    temp = sqrt(sigma) * vec;
-
-    for(Index i=0; i<n; ++i)
-    {
-      JacobiRotation<Scalar> g;
-      g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
-
-      Index rs = n-i-1;
-      if(rs>0)
-      {
-        ColXprSegment x(mat.col(i).tail(rs));
-        TempVecSegment y(temp.tail(rs));
-        apply_rotation_in_the_plane(x, y, g);
-      }
-    }
-  }
-  else
-  {
-    temp = vec;
-    RealScalar beta = 1;
-    for(Index j=0; j<n; ++j)
-    {
-      RealScalar Ljj = numext::real(mat.coeff(j,j));
-      RealScalar dj = numext::abs2(Ljj);
-      Scalar wj = temp.coeff(j);
-      RealScalar swj2 = sigma*numext::abs2(wj);
-      RealScalar gamma = dj*beta + swj2;
-
-      RealScalar x = dj + swj2/beta;
-      if (x<=RealScalar(0))
-        return j;
-      RealScalar nLjj = sqrt(x);
-      mat.coeffRef(j,j) = nLjj;
-      beta += swj2/dj;
-
-      // Update the terms of L
-      Index rs = n-j-1;
-      if(rs)
-      {
-        temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
-        if(gamma != 0)
-          mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*numext::conj(wj)/gamma)*temp.tail(rs);
-      }
-    }
-  }
-  return -1;
-}
-
-template<typename Scalar> struct llt_inplace<Scalar, Lower>
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  template<typename MatrixType>
-  static Index unblocked(MatrixType& mat)
-  {
-    using std::sqrt;
-
-    eigen_assert(mat.rows()==mat.cols());
-    const Index size = mat.rows();
-    for(Index k = 0; k < size; ++k)
-    {
-      Index rs = size-k-1; // remaining size
-
-      Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
-      Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
-      Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
-
-      RealScalar x = numext::real(mat.coeff(k,k));
-      if (k>0) x -= A10.squaredNorm();
-      if (x<=RealScalar(0))
-        return k;
-      mat.coeffRef(k,k) = x = sqrt(x);
-      if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
-      if (rs>0) A21 /= x;
-    }
-    return -1;
-  }
-
-  template<typename MatrixType>
-  static Index blocked(MatrixType& m)
-  {
-    eigen_assert(m.rows()==m.cols());
-    Index size = m.rows();
-    if(size<32)
-      return unblocked(m);
-
-    Index blockSize = size/8;
-    blockSize = (blockSize/16)*16;
-    blockSize = (std::min)((std::max)(blockSize,Index(8)), Index(128));
-
-    for (Index k=0; k<size; k+=blockSize)
-    {
-      // partition the matrix:
-      //       A00 |  -  |  -
-      // lu  = A10 | A11 |  -
-      //       A20 | A21 | A22
-      Index bs = (std::min)(blockSize, size-k);
-      Index rs = size - k - bs;
-      Block<MatrixType,Dynamic,Dynamic> A11(m,k,   k,   bs,bs);
-      Block<MatrixType,Dynamic,Dynamic> A21(m,k+bs,k,   rs,bs);
-      Block<MatrixType,Dynamic,Dynamic> A22(m,k+bs,k+bs,rs,rs);
-
-      Index ret;
-      if((ret=unblocked(A11))>=0) return k+ret;
-      if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
-      if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,typename NumTraits<RealScalar>::Literal(-1)); // bottleneck
-    }
-    return -1;
-  }
-
-  template<typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
-  {
-    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-  }
-};
-
-template<typename Scalar> struct llt_inplace<Scalar, Upper>
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  template<typename MatrixType>
-  static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat)
-  {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::unblocked(matt);
-  }
-  template<typename MatrixType>
-  static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat)
-  {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::blocked(matt);
-  }
-  template<typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
-  {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
-  }
-};
-
-template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
-{
-  typedef const TriangularView<const MatrixType, Lower> MatrixL;
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
-  static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
-};
-
-template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
-{
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
-  typedef const TriangularView<const MatrixType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
-  static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
-};
-
-} // end namespace internal
-
-/** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
-  *
-  * \returns a reference to *this
-  *
-  * Example: \include TutorialLinAlgComputeTwice.cpp
-  * Output: \verbinclude TutorialLinAlgComputeTwice.out
-  */
-template<typename MatrixType, int _UpLo>
-template<typename InputType>
-LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
-{
-  check_template_parameters();
-
-  eigen_assert(a.rows()==a.cols());
-  const Index size = a.rows();
-  m_matrix.resize(size, size);
-  if (!internal::is_same_dense(m_matrix, a.derived()))
-    m_matrix = a.derived();
-
-  // Compute matrix L1 norm = max abs column sum.
-  m_l1_norm = RealScalar(0);
-  // TODO move this code to SelfAdjointView
-  for (Index col = 0; col < size; ++col) {
-    RealScalar abs_col_sum;
-    if (_UpLo == Lower)
-      abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
-    else
-      abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
-    if (abs_col_sum > m_l1_norm)
-      m_l1_norm = abs_col_sum;
-  }
-
-  m_isInitialized = true;
-  bool ok = Traits::inplace_decomposition(m_matrix);
-  m_info = ok ? Success : NumericalIssue;
-
-  return *this;
-}
-
-/** Performs a rank one update (or dowdate) of the current decomposition.
-  * If A = LL^* before the rank one update,
-  * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector
-  * of same dimension.
-  */
-template<typename _MatrixType, int _UpLo>
-template<typename VectorType>
-LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType);
-  eigen_assert(v.size()==m_matrix.cols());
-  eigen_assert(m_isInitialized);
-  if(internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix,v,sigma)>=0)
-    m_info = NumericalIssue;
-  else
-    m_info = Success;
-
-  return *this;
-}
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template<typename _MatrixType,int _UpLo>
-template<typename RhsType, typename DstType>
-void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
-{
-  dst = rhs;
-  solveInPlace(dst);
-}
-#endif
-
-/** \internal use x = llt_object.solve(x);
-  *
-  * This is the \em in-place version of solve().
-  *
-  * \param bAndX represents both the right-hand side matrix b and result x.
-  *
-  * This version avoids a copy when the right hand side matrix b is not needed anymore.
-  *
-  * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
-  * This function will const_cast it, so constness isn't honored here.
-  *
-  * \sa LLT::solve(), MatrixBase::llt()
-  */
-template<typename MatrixType, int _UpLo>
-template<typename Derived>
-void LLT<MatrixType,_UpLo>::solveInPlace(const MatrixBase<Derived> &bAndX) const
-{
-  eigen_assert(m_isInitialized && "LLT is not initialized.");
-  eigen_assert(m_matrix.rows()==bAndX.rows());
-  matrixL().solveInPlace(bAndX);
-  matrixU().solveInPlace(bAndX);
-}
-
-/** \returns the matrix represented by the decomposition,
- * i.e., it returns the product: L L^*.
- * This function is provided for debug purpose. */
-template<typename MatrixType, int _UpLo>
-MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
-{
-  eigen_assert(m_isInitialized && "LLT is not initialized.");
-  return matrixL() * matrixL().adjoint().toDenseMatrix();
-}
-
-/** \cholesky_module
-  * \returns the LLT decomposition of \c *this
-  * \sa SelfAdjointView::llt()
-  */
-template<typename Derived>
-inline const LLT<typename MatrixBase<Derived>::PlainObject>
-MatrixBase<Derived>::llt() const
-{
-  return LLT<PlainObject>(derived());
-}
-
-/** \cholesky_module
-  * \returns the LLT decomposition of \c *this
-  * \sa SelfAdjointView::llt()
-  */
-template<typename MatrixType, unsigned int UpLo>
-inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
-SelfAdjointView<MatrixType, UpLo>::llt() const
-{
-  return LLT<PlainObject,UpLo>(m_matrix);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_LLT_H

deps_src/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h

@@ -1,99 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to LAPACKe
- *     LLt decomposition based on LAPACKE_?potrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_LLT_LAPACKE_H
-#define EIGEN_LLT_LAPACKE_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Scalar> struct lapacke_llt;
-
-#define EIGEN_LAPACKE_LLT(EIGTYPE, BLASTYPE, LAPACKE_PREFIX) \
-template<> struct lapacke_llt<EIGTYPE> \
-{ \
-  template<typename MatrixType> \
-  static inline Index potrf(MatrixType& m, char uplo) \
-  { \
-    lapack_int matrix_order; \
-    lapack_int size, lda, info, StorageOrder; \
-    EIGTYPE* a; \
-    eigen_assert(m.rows()==m.cols()); \
-    /* Set up parameters for ?potrf */ \
-    size = convert_index<lapack_int>(m.rows()); \
-    StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
-    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
-    a = &(m.coeffRef(0,0)); \
-    lda = convert_index<lapack_int>(m.outerStride()); \
-\
-    info = LAPACKE_##LAPACKE_PREFIX##potrf( matrix_order, uplo, size, (BLASTYPE*)a, lda ); \
-    info = (info==0) ? -1 : info>0 ? info-1 : size; \
-    return info; \
-  } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Lower> \
-{ \
-  template<typename MatrixType> \
-  static Index blocked(MatrixType& m) \
-  { \
-    return lapacke_llt<EIGTYPE>::potrf(m, 'L'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Upper> \
-{ \
-  template<typename MatrixType> \
-  static Index blocked(MatrixType& m) \
-  { \
-    return lapacke_llt<EIGTYPE>::potrf(m, 'U'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { \
-    Transpose<MatrixType> matt(mat); \
-    return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
-  } \
-};
-
-EIGEN_LAPACKE_LLT(double, double, d)
-EIGEN_LAPACKE_LLT(float, float, s)
-EIGEN_LAPACKE_LLT(dcomplex, lapack_complex_double, z)
-EIGEN_LAPACKE_LLT(scomplex, lapack_complex_float, c)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_LLT_LAPACKE_H

deps_src/eigen/Eigen/src/CholmodSupport/CholmodSupport.h

@@ -1,639 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CHOLMODSUPPORT_H
-#define EIGEN_CHOLMODSUPPORT_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Scalar> struct cholmod_configure_matrix;
-
-template<> struct cholmod_configure_matrix<double> {
-  template<typename CholmodType>
-  static void run(CholmodType& mat) {
-    mat.xtype = CHOLMOD_REAL;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-};
-
-template<> struct cholmod_configure_matrix<std::complex<double> > {
-  template<typename CholmodType>
-  static void run(CholmodType& mat) {
-    mat.xtype = CHOLMOD_COMPLEX;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-};
-
-// Other scalar types are not yet suppotred by Cholmod
-// template<> struct cholmod_configure_matrix<float> {
-//   template<typename CholmodType>
-//   static void run(CholmodType& mat) {
-//     mat.xtype = CHOLMOD_REAL;
-//     mat.dtype = CHOLMOD_SINGLE;
-//   }
-// };
-//
-// template<> struct cholmod_configure_matrix<std::complex<float> > {
-//   template<typename CholmodType>
-//   static void run(CholmodType& mat) {
-//     mat.xtype = CHOLMOD_COMPLEX;
-//     mat.dtype = CHOLMOD_SINGLE;
-//   }
-// };
-
-} // namespace internal
-
-/** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
-  * Note that the data are shared.
-  */
-template<typename _Scalar, int _Options, typename _StorageIndex>
-cholmod_sparse viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_StorageIndex> > mat)
-{
-  cholmod_sparse res;
-  res.nzmax   = mat.nonZeros();
-  res.nrow    = mat.rows();
-  res.ncol    = mat.cols();
-  res.p       = mat.outerIndexPtr();
-  res.i       = mat.innerIndexPtr();
-  res.x       = mat.valuePtr();
-  res.z       = 0;
-  res.sorted  = 1;
-  if(mat.isCompressed())
-  {
-    res.packed  = 1;
-    res.nz = 0;
-  }
-  else
-  {
-    res.packed  = 0;
-    res.nz = mat.innerNonZeroPtr();
-  }
-
-  res.dtype   = 0;
-  res.stype   = -1;
-  
-  if (internal::is_same<_StorageIndex,int>::value)
-  {
-    res.itype = CHOLMOD_INT;
-  }
-  else if (internal::is_same<_StorageIndex,long>::value)
-  {
-    res.itype = CHOLMOD_LONG;
-  }
-  else
-  {
-    eigen_assert(false && "Index type not supported yet");
-  }
-
-  // setup res.xtype
-  internal::cholmod_configure_matrix<_Scalar>::run(res);
-  
-  res.stype = 0;
-  
-  return res;
-}
-
-template<typename _Scalar, int _Options, typename _Index>
-const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
-{
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
-  return res;
-}
-
-template<typename _Scalar, int _Options, typename _Index>
-const cholmod_sparse viewAsCholmod(const SparseVector<_Scalar,_Options,_Index>& mat)
-{
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
-  return res;
-}
-
-/** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
-  * The data are not copied but shared. */
-template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
-cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<const SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
-{
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.matrix().const_cast_derived()));
-  
-  if(UpLo==Upper) res.stype =  1;
-  if(UpLo==Lower) res.stype = -1;
-
-  return res;
-}
-
-/** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
-  * The data are not copied but shared. */
-template<typename Derived>
-cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
-{
-  EIGEN_STATIC_ASSERT((internal::traits<Derived>::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-  typedef typename Derived::Scalar Scalar;
-
-  cholmod_dense res;
-  res.nrow   = mat.rows();
-  res.ncol   = mat.cols();
-  res.nzmax  = res.nrow * res.ncol;
-  res.d      = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
-  res.x      = (void*)(mat.derived().data());
-  res.z      = 0;
-
-  internal::cholmod_configure_matrix<Scalar>::run(res);
-
-  return res;
-}
-
-/** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
-  * The data are not copied but shared. */
-template<typename Scalar, int Flags, typename StorageIndex>
-MappedSparseMatrix<Scalar,Flags,StorageIndex> viewAsEigen(cholmod_sparse& cm)
-{
-  return MappedSparseMatrix<Scalar,Flags,StorageIndex>
-         (cm.nrow, cm.ncol, static_cast<StorageIndex*>(cm.p)[cm.ncol],
-          static_cast<StorageIndex*>(cm.p), static_cast<StorageIndex*>(cm.i),static_cast<Scalar*>(cm.x) );
-}
-
-enum CholmodMode {
-  CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt
-};
-
-
-/** \ingroup CholmodSupport_Module
-  * \class CholmodBase
-  * \brief The base class for the direct Cholesky factorization of Cholmod
-  * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
-  */
-template<typename _MatrixType, int _UpLo, typename Derived>
-class CholmodBase : public SparseSolverBase<Derived>
-{
-  protected:
-    typedef SparseSolverBase<Derived> Base;
-    using Base::derived;
-    using Base::m_isInitialized;
-  public:
-    typedef _MatrixType MatrixType;
-    enum { UpLo = _UpLo };
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef MatrixType CholMatrixType;
-    typedef typename MatrixType::StorageIndex StorageIndex;
-    enum {
-      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
-    };
-
-  public:
-
-    CholmodBase()
-      : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<double,RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
-      m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
-      cholmod_start(&m_cholmod);
-    }
-
-    explicit CholmodBase(const MatrixType& matrix)
-      : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<double,RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
-      m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
-      cholmod_start(&m_cholmod);
-      compute(matrix);
-    }
-
-    ~CholmodBase()
-    {
-      if(m_cholmodFactor)
-        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
-      cholmod_finish(&m_cholmod);
-    }
-    
-    inline StorageIndex cols() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
-    inline StorageIndex rows() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
-    
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the matrix.appears to be negative.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
-      return m_info;
-    }
-
-    /** Computes the sparse Cholesky decomposition of \a matrix */
-    Derived& compute(const MatrixType& matrix)
-    {
-      analyzePattern(matrix);
-      factorize(matrix);
-      return derived();
-    }
-    
-    /** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
-      *
-      * This function is particularly useful when solving for several problems having the same structure.
-      * 
-      * \sa factorize()
-      */
-    void analyzePattern(const MatrixType& matrix)
-    {
-      if(m_cholmodFactor)
-      {
-        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
-        m_cholmodFactor = 0;
-      }
-      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
-      m_cholmodFactor = cholmod_analyze(&A, &m_cholmod);
-      
-      this->m_isInitialized = true;
-      this->m_info = Success;
-      m_analysisIsOk = true;
-      m_factorizationIsOk = false;
-    }
-    
-    /** Performs a numeric decomposition of \a matrix
-      *
-      * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.
-      *
-      * \sa analyzePattern()
-      */
-    void factorize(const MatrixType& matrix)
-    {
-      eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
-      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
-      cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
-
-      // If the factorization failed, minor is the column at which it did. On success minor == n.
-      this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
-      m_factorizationIsOk = true;
-    }
-    
-    /** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations.
-     *  See the Cholmod user guide for details. */
-    cholmod_common& cholmod() { return m_cholmod; }
-    
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** \internal */
-    template<typename Rhs,typename Dest>
-    void _solve_impl(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
-    {
-      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
-      const Index size = m_cholmodFactor->n;
-      EIGEN_UNUSED_VARIABLE(size);
-      eigen_assert(size==b.rows());
-      
-      // Cholmod needs column-major stoarge without inner-stride, which corresponds to the default behavior of Ref.
-      Ref<const Matrix<typename Rhs::Scalar,Dynamic,Dynamic,ColMajor> > b_ref(b.derived());
-
-      cholmod_dense b_cd = viewAsCholmod(b_ref);
-      cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod);
-      if(!x_cd)
-      {
-        this->m_info = NumericalIssue;
-        return;
-      }
-      // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
-      dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
-      cholmod_free_dense(&x_cd, &m_cholmod);
-    }
-    
-    /** \internal */
-    template<typename RhsDerived, typename DestDerived>
-    void _solve_impl(const SparseMatrixBase<RhsDerived> &b, SparseMatrixBase<DestDerived> &dest) const
-    {
-      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
-      const Index size = m_cholmodFactor->n;
-      EIGEN_UNUSED_VARIABLE(size);
-      eigen_assert(size==b.rows());
-
-      // note: cs stands for Cholmod Sparse
-      Ref<SparseMatrix<typename RhsDerived::Scalar,ColMajor,typename RhsDerived::StorageIndex> > b_ref(b.const_cast_derived());
-      cholmod_sparse b_cs = viewAsCholmod(b_ref);
-      cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod);
-      if(!x_cs)
-      {
-        this->m_info = NumericalIssue;
-        return;
-      }
-      // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
-      dest.derived() = viewAsEigen<typename DestDerived::Scalar,ColMajor,typename DestDerived::StorageIndex>(*x_cs);
-      cholmod_free_sparse(&x_cs, &m_cholmod);
-    }
-    #endif // EIGEN_PARSED_BY_DOXYGEN
-    
-    
-    /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
-      *
-      * During the numerical factorization, an offset term is added to the diagonal coefficients:\n
-      * \c d_ii = \a offset + \c d_ii
-      *
-      * The default is \a offset=0.
-      *
-      * \returns a reference to \c *this.
-      */
-    Derived& setShift(const RealScalar& offset)
-    {
-      m_shiftOffset[0] = double(offset);
-      return derived();
-    }
-    
-    /** \returns the determinant of the underlying matrix from the current factorization */
-    Scalar determinant() const
-    {
-      using std::exp;
-      return exp(logDeterminant());
-    }
-
-    /** \returns the log determinant of the underlying matrix from the current factorization */
-    Scalar logDeterminant() const
-    {
-      using std::log;
-      using numext::real;
-      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
-
-      RealScalar logDet = 0;
-      Scalar *x = static_cast<Scalar*>(m_cholmodFactor->x);
-      if (m_cholmodFactor->is_super)
-      {
-        // Supernodal factorization stored as a packed list of dense column-major blocs,
-        // as described by the following structure:
-
-        // super[k] == index of the first column of the j-th super node
-        StorageIndex *super = static_cast<StorageIndex*>(m_cholmodFactor->super);
-        // pi[k] == offset to the description of row indices
-        StorageIndex *pi = static_cast<StorageIndex*>(m_cholmodFactor->pi);
-        // px[k] == offset to the respective dense block
-        StorageIndex *px = static_cast<StorageIndex*>(m_cholmodFactor->px);
-
-        Index nb_super_nodes = m_cholmodFactor->nsuper;
-        for (Index k=0; k < nb_super_nodes; ++k)
-        {
-          StorageIndex ncols = super[k + 1] - super[k];
-          StorageIndex nrows = pi[k + 1] - pi[k];
-
-          Map<const Array<Scalar,1,Dynamic>, 0, InnerStride<> > sk(x + px[k], ncols, InnerStride<>(nrows+1));
-          logDet += sk.real().log().sum();
-        }
-      }
-      else
-      {
-        // Simplicial factorization stored as standard CSC matrix.
-        StorageIndex *p = static_cast<StorageIndex*>(m_cholmodFactor->p);
-        Index size = m_cholmodFactor->n;
-        for (Index k=0; k<size; ++k)
-          logDet += log(real( x[p[k]] ));
-      }
-      if (m_cholmodFactor->is_ll)
-        logDet *= 2.0;
-      return logDet;
-    };
-
-    template<typename Stream>
-    void dumpMemory(Stream& /*s*/)
-    {}
-    
-  protected:
-    mutable cholmod_common m_cholmod;
-    cholmod_factor* m_cholmodFactor;
-    double m_shiftOffset[2];
-    mutable ComputationInfo m_info;
-    int m_factorizationIsOk;
-    int m_analysisIsOk;
-};
-
-/** \ingroup CholmodSupport_Module
-  * \class CholmodSimplicialLLT
-  * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod
-  *
-  * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization
-  * using the Cholmod library.
-  * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical interest.
-  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
-  * X and B can be either dense or sparse.
-  *
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
-  *
-  * \implsparsesolverconcept
-  *
-  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
-  *
-  * \warning Only double precision real and complex scalar types are supported by Cholmod.
-  *
-  * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLLT
-  */
-template<typename _MatrixType, int _UpLo = Lower>
-class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
-{
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
-    using Base::m_cholmod;
-    
-  public:
-    
-    typedef _MatrixType MatrixType;
-    
-    CholmodSimplicialLLT() : Base() { init(); }
-
-    CholmodSimplicialLLT(const MatrixType& matrix) : Base()
-    {
-      init();
-      this->compute(matrix);
-    }
-
-    ~CholmodSimplicialLLT() {}
-  protected:
-    void init()
-    {
-      m_cholmod.final_asis = 0;
-      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
-      m_cholmod.final_ll = 1;
-    }
-};
-
-
-/** \ingroup CholmodSupport_Module
-  * \class CholmodSimplicialLDLT
-  * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod
-  *
-  * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization
-  * using the Cholmod library.
-  * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Therefore, it has little practical interest.
-  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
-  * X and B can be either dense or sparse.
-  *
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
-  *
-  * \implsparsesolverconcept
-  *
-  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
-  *
-  * \warning Only double precision real and complex scalar types are supported by Cholmod.
-  *
-  * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLDLT
-  */
-template<typename _MatrixType, int _UpLo = Lower>
-class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
-{
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
-    using Base::m_cholmod;
-    
-  public:
-    
-    typedef _MatrixType MatrixType;
-    
-    CholmodSimplicialLDLT() : Base() { init(); }
-
-    CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
-    {
-      init();
-      this->compute(matrix);
-    }
-
-    ~CholmodSimplicialLDLT() {}
-  protected:
-    void init()
-    {
-      m_cholmod.final_asis = 1;
-      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
-    }
-};
-
-/** \ingroup CholmodSupport_Module
-  * \class CholmodSupernodalLLT
-  * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod
-  *
-  * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization
-  * using the Cholmod library.
-  * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM.
-  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
-  * X and B can be either dense or sparse.
-  *
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
-  *
-  * \implsparsesolverconcept
-  *
-  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
-  *
-  * \warning Only double precision real and complex scalar types are supported by Cholmod.
-  *
-  * \sa \ref TutorialSparseSolverConcept
-  */
-template<typename _MatrixType, int _UpLo = Lower>
-class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
-{
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
-    using Base::m_cholmod;
-    
-  public:
-    
-    typedef _MatrixType MatrixType;
-    
-    CholmodSupernodalLLT() : Base() { init(); }
-
-    CholmodSupernodalLLT(const MatrixType& matrix) : Base()
-    {
-      init();
-      this->compute(matrix);
-    }
-
-    ~CholmodSupernodalLLT() {}
-  protected:
-    void init()
-    {
-      m_cholmod.final_asis = 1;
-      m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
-    }
-};
-
-/** \ingroup CholmodSupport_Module
-  * \class CholmodDecomposition
-  * \brief A general Cholesky factorization and solver based on Cholmod
-  *
-  * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization
-  * using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
-  * X and B can be either dense or sparse.
-  *
-  * This variant permits to change the underlying Cholesky method at runtime.
-  * On the other hand, it does not provide access to the result of the factorization.
-  * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization.
-  *
-  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
-  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
-  *               or Upper. Default is Lower.
-  *
-  * \implsparsesolverconcept
-  *
-  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
-  *
-  * \warning Only double precision real and complex scalar types are supported by Cholmod.
-  *
-  * \sa \ref TutorialSparseSolverConcept
-  */
-template<typename _MatrixType, int _UpLo = Lower>
-class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
-{
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
-    using Base::m_cholmod;
-    
-  public:
-    
-    typedef _MatrixType MatrixType;
-    
-    CholmodDecomposition() : Base() { init(); }
-
-    CholmodDecomposition(const MatrixType& matrix) : Base()
-    {
-      init();
-      this->compute(matrix);
-    }
-
-    ~CholmodDecomposition() {}
-    
-    void setMode(CholmodMode mode)
-    {
-      switch(mode)
-      {
-        case CholmodAuto:
-          m_cholmod.final_asis = 1;
-          m_cholmod.supernodal = CHOLMOD_AUTO;
-          break;
-        case CholmodSimplicialLLt:
-          m_cholmod.final_asis = 0;
-          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
-          m_cholmod.final_ll = 1;
-          break;
-        case CholmodSupernodalLLt:
-          m_cholmod.final_asis = 1;
-          m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
-          break;
-        case CholmodLDLt:
-          m_cholmod.final_asis = 1;
-          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
-          break;
-        default:
-          break;
-      }
-    }
-  protected:
-    void init()
-    {
-      m_cholmod.final_asis = 1;
-      m_cholmod.supernodal = CHOLMOD_AUTO;
-    }
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_CHOLMODSUPPORT_H

deps_src/eigen/Eigen/src/Core/Array.h

@@ -1,329 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ARRAY_H
-#define EIGEN_ARRAY_H
-
-namespace Eigen {
-
-namespace internal {
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  typedef ArrayXpr XprKind;
-  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
-};
-}
-
-/** \class Array
-  * \ingroup Core_Module
-  *
-  * \brief General-purpose arrays with easy API for coefficient-wise operations
-  *
-  * The %Array class is very similar to the Matrix class. It provides
-  * general-purpose one- and two-dimensional arrays. The difference between the
-  * %Array and the %Matrix class is primarily in the API: the API for the
-  * %Array class provides easy access to coefficient-wise operations, while the
-  * API for the %Matrix class provides easy access to linear-algebra
-  * operations.
-  *
-  * See documentation of class Matrix for detailed information on the template parameters
-  * storage layout.
-  *
-  * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
-  *
-  * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-class Array
-  : public PlainObjectBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  public:
-
-    typedef PlainObjectBase<Array> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Array)
-
-    enum { Options = _Options };
-    typedef typename Base::PlainObject PlainObject;
-
-  protected:
-    template <typename Derived, typename OtherDerived, bool IsVector>
-    friend struct internal::conservative_resize_like_impl;
-
-    using Base::m_storage;
-
-  public:
-
-    using Base::base;
-    using Base::coeff;
-    using Base::coeffRef;
-
-    /**
-      * The usage of
-      *   using Base::operator=;
-      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
-      * the usage of 'using'. This should be done only for operator=.
-      */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
-    {
-      return Base::operator=(other);
-    }
-
-    /** Set all the entries to \a value.
-      * \sa DenseBase::setConstant(), DenseBase::fill()
-      */
-    /* This overload is needed because the usage of
-      *   using Base::operator=;
-      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
-      * the usage of 'using'. This should be done only for operator=.
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array& operator=(const Scalar &value)
-    {
-      Base::setConstant(value);
-      return *this;
-    }
-
-    /** Copies the value of the expression \a other into \c *this with automatic resizing.
-      *
-      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
-      * it will be initialized.
-      *
-      * Note that copying a row-vector into a vector (and conversely) is allowed.
-      * The resizing, if any, is then done in the appropriate way so that row-vectors
-      * remain row-vectors and vectors remain vectors.
-      */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other)
-    {
-      return Base::_set(other);
-    }
-
-    /** This is a special case of the templated operator=. Its purpose is to
-      * prevent a default operator= from hiding the templated operator=.
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array& operator=(const Array& other)
-    {
-      return Base::_set(other);
-    }
-    
-    /** Default constructor.
-      *
-      * For fixed-size matrices, does nothing.
-      *
-      * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
-      * is called a null matrix. This constructor is the unique way to create null matrices: resizing
-      * a matrix to 0 is not supported.
-      *
-      * \sa resize(Index,Index)
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array() : Base()
-    {
-      Base::_check_template_params();
-      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
-    }
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    // FIXME is it still needed ??
-    /** \internal */
-    EIGEN_DEVICE_FUNC
-    Array(internal::constructor_without_unaligned_array_assert)
-      : Base(internal::constructor_without_unaligned_array_assert())
-    {
-      Base::_check_template_params();
-      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
-    }
-#endif
-
-#if EIGEN_HAS_RVALUE_REFERENCES
-    EIGEN_DEVICE_FUNC
-    Array(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_constructible<Scalar>::value)
-      : Base(std::move(other))
-    {
-      Base::_check_template_params();
-    }
-    EIGEN_DEVICE_FUNC
-    Array& operator=(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
-    {
-      other.swap(*this);
-      return *this;
-    }
-#endif
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename T>
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE explicit Array(const T& x)
-    {
-      Base::_check_template_params();
-      Base::template _init1<T>(x);
-    }
-
-    template<typename T0, typename T1>
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
-    {
-      Base::_check_template_params();
-      this->template _init2<T0,T1>(val0, val1);
-    }
-    #else
-    /** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */
-    EIGEN_DEVICE_FUNC explicit Array(const Scalar *data);
-    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
-      *
-      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
-      * it is redundant to pass the dimension here, so it makes more sense to use the default
-      * constructor Array() instead.
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE explicit Array(Index dim);
-    /** constructs an initialized 1x1 Array with the given coefficient */
-    Array(const Scalar& value);
-    /** constructs an uninitialized array with \a rows rows and \a cols columns.
-      *
-      * This is useful for dynamic-size arrays. For fixed-size arrays,
-      * it is redundant to pass these parameters, so one should use the default constructor
-      * Array() instead. */
-    Array(Index rows, Index cols);
-    /** constructs an initialized 2D vector with given coefficients */
-    Array(const Scalar& val0, const Scalar& val1);
-    #endif
-
-    /** constructs an initialized 3D vector with given coefficients */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
-    {
-      Base::_check_template_params();
-      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
-      m_storage.data()[0] = val0;
-      m_storage.data()[1] = val1;
-      m_storage.data()[2] = val2;
-    }
-    /** constructs an initialized 4D vector with given coefficients */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
-    {
-      Base::_check_template_params();
-      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
-      m_storage.data()[0] = val0;
-      m_storage.data()[1] = val1;
-      m_storage.data()[2] = val2;
-      m_storage.data()[3] = val3;
-    }
-
-    /** Copy constructor */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array(const Array& other)
-            : Base(other)
-    { }
-
-  private:
-    struct PrivateType {};
-  public:
-
-    /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other,
-                              typename internal::enable_if<internal::is_convertible<typename OtherDerived::Scalar,Scalar>::value,
-                                                           PrivateType>::type = PrivateType())
-      : Base(other.derived())
-    { }
-
-    EIGEN_DEVICE_FUNC inline Index innerStride() const { return 1; }
-    EIGEN_DEVICE_FUNC inline Index outerStride() const { return this->innerSize(); }
-
-    #ifdef EIGEN_ARRAY_PLUGIN
-    #include EIGEN_ARRAY_PLUGIN
-    #endif
-
-  private:
-
-    template<typename MatrixType, typename OtherDerived, bool SwapPointers>
-    friend struct internal::matrix_swap_impl;
-};
-
-/** \defgroup arraytypedefs Global array typedefs
-  * \ingroup Core_Module
-  *
-  * Eigen defines several typedef shortcuts for most common 1D and 2D array types.
-  *
-  * The general patterns are the following:
-  *
-  * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size,
-  * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd
-  * for complex double.
-  *
-  * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of floats.
-  *
-  * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is
-  * a fixed-size 1D array of 4 complex floats.
-  *
-  * \sa class Array
-  */
-
-#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)   \
-/** \ingroup arraytypedefs */                                    \
-typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix;  \
-/** \ingroup arraytypedefs */                                    \
-typedef Array<Type, Size, 1>    Array##SizeSuffix##TypeSuffix;
-
-#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size)         \
-/** \ingroup arraytypedefs */                                    \
-typedef Array<Type, Size, Dynamic> Array##Size##X##TypeSuffix;  \
-/** \ingroup arraytypedefs */                                    \
-typedef Array<Type, Dynamic, Size> Array##X##Size##TypeSuffix;
-
-#define EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
-EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \
-EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \
-EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \
-EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
-
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int,                  i)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float,                f)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double,               d)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<float>,  cf)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
-
-#undef EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES
-#undef EIGEN_MAKE_ARRAY_TYPEDEFS
-
-#undef EIGEN_MAKE_ARRAY_TYPEDEFS_LARGE
-
-#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
-using Eigen::Matrix##SizeSuffix##TypeSuffix; \
-using Eigen::Vector##SizeSuffix##TypeSuffix; \
-using Eigen::RowVector##SizeSuffix##TypeSuffix;
-
-#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
-
-#define EIGEN_USING_ARRAY_TYPEDEFS \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
-EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
-
-} // end namespace Eigen
-
-#endif // EIGEN_ARRAY_H

deps_src/eigen/Eigen/src/Core/ArrayBase.h

@@ -1,226 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ARRAYBASE_H
-#define EIGEN_ARRAYBASE_H
-
-namespace Eigen { 
-
-template<typename ExpressionType> class MatrixWrapper;
-
-/** \class ArrayBase
-  * \ingroup Core_Module
-  *
-  * \brief Base class for all 1D and 2D array, and related expressions
-  *
-  * An array is similar to a dense vector or matrix. While matrices are mathematical
-  * objects with well defined linear algebra operators, an array is just a collection
-  * of scalar values arranged in a one or two dimensionnal fashion. As the main consequence,
-  * all operations applied to an array are performed coefficient wise. Furthermore,
-  * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient
-  * constructors allowing to easily write generic code working for both scalar values
-  * and arrays.
-  *
-  * This class is the base that is inherited by all array expression types.
-  *
-  * \tparam Derived is the derived type, e.g., an array or an expression type.
-  *
-  * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
-  *
-  * \sa class MatrixBase, \ref TopicClassHierarchy
-  */
-template<typename Derived> class ArrayBase
-  : public DenseBase<Derived>
-{
-  public:
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** The base class for a given storage type. */
-    typedef ArrayBase StorageBaseType;
-
-    typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
-
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
-    typedef DenseBase<Derived> Base;
-    using Base::RowsAtCompileTime;
-    using Base::ColsAtCompileTime;
-    using Base::SizeAtCompileTime;
-    using Base::MaxRowsAtCompileTime;
-    using Base::MaxColsAtCompileTime;
-    using Base::MaxSizeAtCompileTime;
-    using Base::IsVectorAtCompileTime;
-    using Base::Flags;
-    
-    using Base::derived;
-    using Base::const_cast_derived;
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::coeff;
-    using Base::coeffRef;
-    using Base::lazyAssign;
-    using Base::operator=;
-    using Base::operator+=;
-    using Base::operator-=;
-    using Base::operator*=;
-    using Base::operator/=;
-
-    typedef typename Base::CoeffReturnType CoeffReturnType;
-
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    typedef typename Base::PlainObject PlainObject;
-
-    /** \internal Represents a matrix with all coefficients equal to one another*/
-    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
-#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
-#define EIGEN_DOC_UNARY_ADDONS(X,Y)
-#   include "../plugins/CommonCwiseUnaryOps.h"
-#   include "../plugins/MatrixCwiseUnaryOps.h"
-#   include "../plugins/ArrayCwiseUnaryOps.h"
-#   include "../plugins/CommonCwiseBinaryOps.h"
-#   include "../plugins/MatrixCwiseBinaryOps.h"
-#   include "../plugins/ArrayCwiseBinaryOps.h"
-#   ifdef EIGEN_ARRAYBASE_PLUGIN
-#     include EIGEN_ARRAYBASE_PLUGIN
-#   endif
-#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_DOC_UNARY_ADDONS
-
-    /** Special case of the template operator=, in order to prevent the compiler
-      * from generating a default operator= (issue hit with g++ 4.1)
-      */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator=(const ArrayBase& other)
-    {
-      internal::call_assignment(derived(), other.derived());
-      return derived();
-    }
-    
-    /** Set all the entries to \a value.
-      * \sa DenseBase::setConstant(), DenseBase::fill() */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator=(const Scalar &value)
-    { Base::setConstant(value); return derived(); }
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator+=(const Scalar& scalar);
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator-=(const Scalar& scalar);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator+=(const ArrayBase<OtherDerived>& other);
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator-=(const ArrayBase<OtherDerived>& other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator*=(const ArrayBase<OtherDerived>& other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator/=(const ArrayBase<OtherDerived>& other);
-
-  public:
-    EIGEN_DEVICE_FUNC
-    ArrayBase<Derived>& array() { return *this; }
-    EIGEN_DEVICE_FUNC
-    const ArrayBase<Derived>& array() const { return *this; }
-
-    /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
-      * \sa MatrixBase::array() */
-    EIGEN_DEVICE_FUNC
-    MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
-    EIGEN_DEVICE_FUNC
-    const MatrixWrapper<const Derived> matrix() const { return MatrixWrapper<const Derived>(derived()); }
-
-//     template<typename Dest>
-//     inline void evalTo(Dest& dst) const { dst = matrix(); }
-
-  protected:
-    EIGEN_DEVICE_FUNC
-    ArrayBase() : Base() {}
-
-  private:
-    explicit ArrayBase(Index);
-    ArrayBase(Index,Index);
-    template<typename OtherDerived> explicit ArrayBase(const ArrayBase<OtherDerived>&);
-  protected:
-    // mixing arrays and matrices is not legal
-    template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
-    // mixing arrays and matrices is not legal
-    template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
-};
-
-/** replaces \c *this by \c *this - \a other.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
-ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
-{
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-/** replaces \c *this by \c *this + \a other.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
-ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
-{
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-/** replaces \c *this by \c *this * \a other coefficient wise.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
-ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
-{
-  call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-/** replaces \c *this by \c *this / \a other coefficient wise.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
-ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
-{
-  call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_ARRAYBASE_H

deps_src/eigen/Eigen/src/Core/ArrayWrapper.h

@@ -1,209 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ARRAYWRAPPER_H
-#define EIGEN_ARRAYWRAPPER_H
-
-namespace Eigen { 
-
-/** \class ArrayWrapper
-  * \ingroup Core_Module
-  *
-  * \brief Expression of a mathematical vector or matrix as an array object
-  *
-  * This class is the return type of MatrixBase::array(), and most of the time
-  * this is the only way it is use.
-  *
-  * \sa MatrixBase::array(), class MatrixWrapper
-  */
-
-namespace internal {
-template<typename ExpressionType>
-struct traits<ArrayWrapper<ExpressionType> >
-  : public traits<typename remove_all<typename ExpressionType::Nested>::type >
-{
-  typedef ArrayXpr XprKind;
-  // Let's remove NestByRefBit
-  enum {
-    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
-  };
-};
-}
-
-template<typename ExpressionType>
-class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
-{
-  public:
-    typedef ArrayBase<ArrayWrapper> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
-    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
-
-    typedef typename internal::conditional<
-                       internal::is_lvalue<ExpressionType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-
-    typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
-
-    using Base::coeffRef;
-
-    EIGEN_DEVICE_FUNC
-    explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
-
-    EIGEN_DEVICE_FUNC
-    inline Index rows() const { return m_expression.rows(); }
-    EIGEN_DEVICE_FUNC
-    inline Index cols() const { return m_expression.cols(); }
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const { return m_expression.innerStride(); }
-
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-    EIGEN_DEVICE_FUNC
-    inline const Scalar* data() const { return m_expression.data(); }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return m_expression.coeffRef(rowId, colId);
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_expression.coeffRef(index);
-    }
-
-    template<typename Dest>
-    EIGEN_DEVICE_FUNC
-    inline void evalTo(Dest& dst) const { dst = m_expression; }
-
-    const typename internal::remove_all<NestedExpressionType>::type& 
-    EIGEN_DEVICE_FUNC
-    nestedExpression() const 
-    {
-      return m_expression;
-    }
-
-    /** Forwards the resizing request to the nested expression
-      * \sa DenseBase::resize(Index)  */
-    EIGEN_DEVICE_FUNC
-    void resize(Index newSize) { m_expression.resize(newSize); }
-    /** Forwards the resizing request to the nested expression
-      * \sa DenseBase::resize(Index,Index)*/
-    EIGEN_DEVICE_FUNC
-    void resize(Index rows, Index cols) { m_expression.resize(rows,cols); }
-
-  protected:
-    NestedExpressionType m_expression;
-};
-
-/** \class MatrixWrapper
-  * \ingroup Core_Module
-  *
-  * \brief Expression of an array as a mathematical vector or matrix
-  *
-  * This class is the return type of ArrayBase::matrix(), and most of the time
-  * this is the only way it is use.
-  *
-  * \sa MatrixBase::matrix(), class ArrayWrapper
-  */
-
-namespace internal {
-template<typename ExpressionType>
-struct traits<MatrixWrapper<ExpressionType> >
- : public traits<typename remove_all<typename ExpressionType::Nested>::type >
-{
-  typedef MatrixXpr XprKind;
-  // Let's remove NestByRefBit
-  enum {
-    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
-  };
-};
-}
-
-template<typename ExpressionType>
-class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
-{
-  public:
-    typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
-    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
-
-    typedef typename internal::conditional<
-                       internal::is_lvalue<ExpressionType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-
-    typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
-
-    using Base::coeffRef;
-
-    EIGEN_DEVICE_FUNC
-    explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
-
-    EIGEN_DEVICE_FUNC
-    inline Index rows() const { return m_expression.rows(); }
-    EIGEN_DEVICE_FUNC
-    inline Index cols() const { return m_expression.cols(); }
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const { return m_expression.outerStride(); }
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const { return m_expression.innerStride(); }
-
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-    EIGEN_DEVICE_FUNC
-    inline const Scalar* data() const { return m_expression.data(); }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return m_expression.derived().coeffRef(rowId, colId);
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_expression.coeffRef(index);
-    }
-
-    EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<NestedExpressionType>::type& 
-    nestedExpression() const 
-    {
-      return m_expression;
-    }
-
-    /** Forwards the resizing request to the nested expression
-      * \sa DenseBase::resize(Index)  */
-    EIGEN_DEVICE_FUNC
-    void resize(Index newSize) { m_expression.resize(newSize); }
-    /** Forwards the resizing request to the nested expression
-      * \sa DenseBase::resize(Index,Index)*/
-    EIGEN_DEVICE_FUNC
-    void resize(Index rows, Index cols) { m_expression.resize(rows,cols); }
-
-  protected:
-    NestedExpressionType m_expression;
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_ARRAYWRAPPER_H

deps_src/eigen/Eigen/src/Core/Assign.h

@@ -1,90 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2007 Michael Olbrich <michael.olbrich@gmx.net>
-// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ASSIGN_H
-#define EIGEN_ASSIGN_H
-
-namespace Eigen {
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
-  ::lazyAssign(const DenseBase<OtherDerived>& other)
-{
-  enum{
-    SameType = internal::is_same<typename Derived::Scalar,typename OtherDerived::Scalar>::value
-  };
-
-  EIGEN_STATIC_ASSERT_LVALUE(Derived)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-  eigen_assert(rows() == other.rows() && cols() == other.cols());
-  internal::call_assignment_no_alias(derived(),other.derived());
-  
-  return derived();
-}
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
-{
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
-{
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
-{
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
-{
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
-{
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
-{
-  other.derived().evalTo(derived());
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_ASSIGN_H

deps_src/eigen/Eigen/src/Core/AssignEvaluator.h

@@ -1,935 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ASSIGN_EVALUATOR_H
-#define EIGEN_ASSIGN_EVALUATOR_H
-
-namespace Eigen {
-
-// This implementation is based on Assign.h
-
-namespace internal {
-  
-/***************************************************************************
-* Part 1 : the logic deciding a strategy for traversal and unrolling       *
-***************************************************************************/
-
-// copy_using_evaluator_traits is based on assign_traits
-
-template <typename DstEvaluator, typename SrcEvaluator, typename AssignFunc>
-struct copy_using_evaluator_traits
-{
-  typedef typename DstEvaluator::XprType Dst;
-  typedef typename Dst::Scalar DstScalar;
-  
-  enum {
-    DstFlags = DstEvaluator::Flags,
-    SrcFlags = SrcEvaluator::Flags
-  };
-  
-public:
-  enum {
-    DstAlignment = DstEvaluator::Alignment,
-    SrcAlignment = SrcEvaluator::Alignment,
-    DstHasDirectAccess = (DstFlags & DirectAccessBit) == DirectAccessBit,
-    JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
-  };
-
-private:
-  enum {
-    InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
-              : int(DstFlags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
-              : int(Dst::RowsAtCompileTime),
-    InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
-              : int(DstFlags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
-              : int(Dst::MaxRowsAtCompileTime),
-    OuterStride = int(outer_stride_at_compile_time<Dst>::ret),
-    MaxSizeAtCompileTime = Dst::SizeAtCompileTime
-  };
-
-  // TODO distinguish between linear traversal and inner-traversals
-  typedef typename find_best_packet<DstScalar,Dst::SizeAtCompileTime>::type LinearPacketType;
-  typedef typename find_best_packet<DstScalar,InnerSize>::type InnerPacketType;
-
-  enum {
-    LinearPacketSize = unpacket_traits<LinearPacketType>::size,
-    InnerPacketSize = unpacket_traits<InnerPacketType>::size
-  };
-
-public:
-  enum {
-    LinearRequiredAlignment = unpacket_traits<LinearPacketType>::alignment,
-    InnerRequiredAlignment = unpacket_traits<InnerPacketType>::alignment
-  };
-
-private:
-  enum {
-    DstIsRowMajor = DstFlags&RowMajorBit,
-    SrcIsRowMajor = SrcFlags&RowMajorBit,
-    StorageOrdersAgree = (int(DstIsRowMajor) == int(SrcIsRowMajor)),
-    MightVectorize = bool(StorageOrdersAgree)
-                  && (int(DstFlags) & int(SrcFlags) & ActualPacketAccessBit)
-                  && bool(functor_traits<AssignFunc>::PacketAccess),
-    MayInnerVectorize  = MightVectorize
-                       && int(InnerSize)!=Dynamic && int(InnerSize)%int(InnerPacketSize)==0
-                       && int(OuterStride)!=Dynamic && int(OuterStride)%int(InnerPacketSize)==0
-                       && (EIGEN_UNALIGNED_VECTORIZE  || int(JointAlignment)>=int(InnerRequiredAlignment)),
-    MayLinearize = bool(StorageOrdersAgree) && (int(DstFlags) & int(SrcFlags) & LinearAccessBit),
-    MayLinearVectorize = bool(MightVectorize) && bool(MayLinearize) && bool(DstHasDirectAccess)
-                       && (EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)) || MaxSizeAtCompileTime == Dynamic),
-      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
-         so it's only good for large enough sizes. */
-    MaySliceVectorize  = bool(MightVectorize) && bool(DstHasDirectAccess)
-                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=(EIGEN_UNALIGNED_VECTORIZE?InnerPacketSize:(3*InnerPacketSize)))
-      /* slice vectorization can be slow, so we only want it if the slices are big, which is
-         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
-         in a fixed-size matrix
-         However, with EIGEN_UNALIGNED_VECTORIZE and unrolling, slice vectorization is still worth it */
-  };
-
-public:
-  enum {
-    Traversal = int(MayLinearVectorize) && (LinearPacketSize>InnerPacketSize) ? int(LinearVectorizedTraversal)
-              : int(MayInnerVectorize)   ? int(InnerVectorizedTraversal)
-              : int(MayLinearVectorize)  ? int(LinearVectorizedTraversal)
-              : int(MaySliceVectorize)   ? int(SliceVectorizedTraversal)
-              : int(MayLinearize)        ? int(LinearTraversal)
-                                         : int(DefaultTraversal),
-    Vectorized = int(Traversal) == InnerVectorizedTraversal
-              || int(Traversal) == LinearVectorizedTraversal
-              || int(Traversal) == SliceVectorizedTraversal
-  };
-
-  typedef typename conditional<int(Traversal)==LinearVectorizedTraversal, LinearPacketType, InnerPacketType>::type PacketType;
-
-private:
-  enum {
-    ActualPacketSize    = int(Traversal)==LinearVectorizedTraversal ? LinearPacketSize
-                        : Vectorized ? InnerPacketSize
-                        : 1,
-    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * ActualPacketSize,
-    MayUnrollCompletely = int(Dst::SizeAtCompileTime) != Dynamic
-                       && int(Dst::SizeAtCompileTime) * (int(DstEvaluator::CoeffReadCost)+int(SrcEvaluator::CoeffReadCost)) <= int(UnrollingLimit),
-    MayUnrollInner      = int(InnerSize) != Dynamic
-                       && int(InnerSize) * (int(DstEvaluator::CoeffReadCost)+int(SrcEvaluator::CoeffReadCost)) <= int(UnrollingLimit)
-  };
-
-public:
-  enum {
-    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
-                ? (
-                    int(MayUnrollCompletely) ? int(CompleteUnrolling)
-                  : int(MayUnrollInner)      ? int(InnerUnrolling)
-                                             : int(NoUnrolling)
-                  )
-              : int(Traversal) == int(LinearVectorizedTraversal)
-                ? ( bool(MayUnrollCompletely) && ( EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)))
-                          ? int(CompleteUnrolling)
-                          : int(NoUnrolling) )
-              : int(Traversal) == int(LinearTraversal)
-                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) 
-                                              : int(NoUnrolling) )
-#if EIGEN_UNALIGNED_VECTORIZE
-              : int(Traversal) == int(SliceVectorizedTraversal)
-                ? ( bool(MayUnrollInner) ? int(InnerUnrolling)
-                                         : int(NoUnrolling) )
-#endif
-              : int(NoUnrolling)
-  };
-
-#ifdef EIGEN_DEBUG_ASSIGN
-  static void debug()
-  {
-    std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl;
-    std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl;
-    std::cerr.setf(std::ios::hex, std::ios::basefield);
-    std::cerr << "DstFlags" << " = " << DstFlags << " (" << demangle_flags(DstFlags) << " )" << std::endl;
-    std::cerr << "SrcFlags" << " = " << SrcFlags << " (" << demangle_flags(SrcFlags) << " )" << std::endl;
-    std::cerr.unsetf(std::ios::hex);
-    EIGEN_DEBUG_VAR(DstAlignment)
-    EIGEN_DEBUG_VAR(SrcAlignment)
-    EIGEN_DEBUG_VAR(LinearRequiredAlignment)
-    EIGEN_DEBUG_VAR(InnerRequiredAlignment)
-    EIGEN_DEBUG_VAR(JointAlignment)
-    EIGEN_DEBUG_VAR(InnerSize)
-    EIGEN_DEBUG_VAR(InnerMaxSize)
-    EIGEN_DEBUG_VAR(LinearPacketSize)
-    EIGEN_DEBUG_VAR(InnerPacketSize)
-    EIGEN_DEBUG_VAR(ActualPacketSize)
-    EIGEN_DEBUG_VAR(StorageOrdersAgree)
-    EIGEN_DEBUG_VAR(MightVectorize)
-    EIGEN_DEBUG_VAR(MayLinearize)
-    EIGEN_DEBUG_VAR(MayInnerVectorize)
-    EIGEN_DEBUG_VAR(MayLinearVectorize)
-    EIGEN_DEBUG_VAR(MaySliceVectorize)
-    std::cerr << "Traversal" << " = " << Traversal << " (" << demangle_traversal(Traversal) << ")" << std::endl;
-    EIGEN_DEBUG_VAR(SrcEvaluator::CoeffReadCost)
-    EIGEN_DEBUG_VAR(UnrollingLimit)
-    EIGEN_DEBUG_VAR(MayUnrollCompletely)
-    EIGEN_DEBUG_VAR(MayUnrollInner)
-    std::cerr << "Unrolling" << " = " << Unrolling << " (" << demangle_unrolling(Unrolling) << ")" << std::endl;
-    std::cerr << std::endl;
-  }
-#endif
-};
-
-/***************************************************************************
-* Part 2 : meta-unrollers
-***************************************************************************/
-
-/************************
-*** Default traversal ***
-************************/
-
-template<typename Kernel, int Index, int Stop>
-struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
-{
-  // FIXME: this is not very clean, perhaps this information should be provided by the kernel?
-  typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
-  typedef typename DstEvaluatorType::XprType DstXprType;
-  
-  enum {
-    outer = Index / DstXprType::InnerSizeAtCompileTime,
-    inner = Index % DstXprType::InnerSizeAtCompileTime
-  };
-
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    kernel.assignCoeffByOuterInner(outer, inner);
-    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
-  }
-};
-
-template<typename Kernel, int Stop>
-struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
-};
-
-template<typename Kernel, int Index_, int Stop>
-struct copy_using_evaluator_DefaultTraversal_InnerUnrolling
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
-  {
-    kernel.assignCoeffByOuterInner(outer, Index_);
-    copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index_+1, Stop>::run(kernel, outer);
-  }
-};
-
-template<typename Kernel, int Stop>
-struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index) { }
-};
-
-/***********************
-*** Linear traversal ***
-***********************/
-
-template<typename Kernel, int Index, int Stop>
-struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel)
-  {
-    kernel.assignCoeff(Index);
-    copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index+1, Stop>::run(kernel);
-  }
-};
-
-template<typename Kernel, int Stop>
-struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
-};
-
-/**************************
-*** Inner vectorization ***
-**************************/
-
-template<typename Kernel, int Index, int Stop>
-struct copy_using_evaluator_innervec_CompleteUnrolling
-{
-  // FIXME: this is not very clean, perhaps this information should be provided by the kernel?
-  typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
-  typedef typename DstEvaluatorType::XprType DstXprType;
-  typedef typename Kernel::PacketType PacketType;
-  
-  enum {
-    outer = Index / DstXprType::InnerSizeAtCompileTime,
-    inner = Index % DstXprType::InnerSizeAtCompileTime,
-    SrcAlignment = Kernel::AssignmentTraits::SrcAlignment,
-    DstAlignment = Kernel::AssignmentTraits::DstAlignment
-  };
-
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, inner);
-    enum { NextIndex = Index + unpacket_traits<PacketType>::size };
-    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
-  }
-};
-
-template<typename Kernel, int Stop>
-struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
-};
-
-template<typename Kernel, int Index_, int Stop, int SrcAlignment, int DstAlignment>
-struct copy_using_evaluator_innervec_InnerUnrolling
-{
-  typedef typename Kernel::PacketType PacketType;
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel, Index outer)
-  {
-    kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, Index_);
-    enum { NextIndex = Index_ + unpacket_traits<PacketType>::size };
-    copy_using_evaluator_innervec_InnerUnrolling<Kernel, NextIndex, Stop, SrcAlignment, DstAlignment>::run(kernel, outer);
-  }
-};
-
-template<typename Kernel, int Stop, int SrcAlignment, int DstAlignment>
-struct copy_using_evaluator_innervec_InnerUnrolling<Kernel, Stop, Stop, SrcAlignment, DstAlignment>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &, Index) { }
-};
-
-/***************************************************************************
-* Part 3 : implementation of all cases
-***************************************************************************/
-
-// dense_assignment_loop is based on assign_impl
-
-template<typename Kernel,
-         int Traversal = Kernel::AssignmentTraits::Traversal,
-         int Unrolling = Kernel::AssignmentTraits::Unrolling>
-struct dense_assignment_loop;
-
-/************************
-*** Default traversal ***
-************************/
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, DefaultTraversal, NoUnrolling>
-{
-  EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE run(Kernel &kernel)
-  {
-    for(Index outer = 0; outer < kernel.outerSize(); ++outer) {
-      for(Index inner = 0; inner < kernel.innerSize(); ++inner) {
-        kernel.assignCoeffByOuterInner(outer, inner);
-      }
-    }
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, DefaultTraversal, CompleteUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, DefaultTraversal, InnerUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-
-    const Index outerSize = kernel.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer)
-      copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime>::run(kernel, outer);
-  }
-};
-
-/***************************
-*** Linear vectorization ***
-***************************/
-
-
-// The goal of unaligned_dense_assignment_loop is simply to factorize the handling
-// of the non vectorizable beginning and ending parts
-
-template <bool IsAligned = false>
-struct unaligned_dense_assignment_loop
-{
-  // if IsAligned = true, then do nothing
-  template <typename Kernel>
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index, Index) {}
-};
-
-template <>
-struct unaligned_dense_assignment_loop<false>
-{
-  // MSVC must not inline this functions. If it does, it fails to optimize the
-  // packet access path.
-  // FIXME check which version exhibits this issue
-#if EIGEN_COMP_MSVC
-  template <typename Kernel>
-  static EIGEN_DONT_INLINE void run(Kernel &kernel,
-                                    Index start,
-                                    Index end)
-#else
-  template <typename Kernel>
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel,
-                                      Index start,
-                                      Index end)
-#endif
-  {
-    for (Index index = start; index < end; ++index)
-      kernel.assignCoeff(index);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    const Index size = kernel.size();
-    typedef typename Kernel::Scalar Scalar;
-    typedef typename Kernel::PacketType PacketType;
-    enum {
-      requestedAlignment = Kernel::AssignmentTraits::LinearRequiredAlignment,
-      packetSize = unpacket_traits<PacketType>::size,
-      dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
-      dstAlignment = packet_traits<Scalar>::AlignedOnScalar ? int(requestedAlignment)
-                                                            : int(Kernel::AssignmentTraits::DstAlignment),
-      srcAlignment = Kernel::AssignmentTraits::JointAlignment
-    };
-    const Index alignedStart = dstIsAligned ? 0 : internal::first_aligned<requestedAlignment>(kernel.dstDataPtr(), size);
-    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
-
-    unaligned_dense_assignment_loop<dstIsAligned!=0>::run(kernel, 0, alignedStart);
-
-    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
-      kernel.template assignPacket<dstAlignment, srcAlignment, PacketType>(index);
-
-    unaligned_dense_assignment_loop<>::run(kernel, alignedEnd, size);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    typedef typename Kernel::PacketType PacketType;
-    
-    enum { size = DstXprType::SizeAtCompileTime,
-           packetSize =unpacket_traits<PacketType>::size,
-           alignedSize = (size/packetSize)*packetSize };
-
-    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, alignedSize>::run(kernel);
-    copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, alignedSize, size>::run(kernel);
-  }
-};
-
-/**************************
-*** Inner vectorization ***
-**************************/
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, NoUnrolling>
-{
-  typedef typename Kernel::PacketType PacketType;
-  enum {
-    SrcAlignment = Kernel::AssignmentTraits::SrcAlignment,
-    DstAlignment = Kernel::AssignmentTraits::DstAlignment
-  };
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    const Index innerSize = kernel.innerSize();
-    const Index outerSize = kernel.outerSize();
-    const Index packetSize = unpacket_traits<PacketType>::size;
-    for(Index outer = 0; outer < outerSize; ++outer)
-      for(Index inner = 0; inner < innerSize; inner+=packetSize)
-        kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, inner);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, CompleteUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    typedef typename Kernel::AssignmentTraits Traits;
-    const Index outerSize = kernel.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer)
-      copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, DstXprType::InnerSizeAtCompileTime,
-                                                   Traits::SrcAlignment, Traits::DstAlignment>::run(kernel, outer);
-  }
-};
-
-/***********************
-*** Linear traversal ***
-***********************/
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    const Index size = kernel.size();
-    for(Index i = 0; i < size; ++i)
-      kernel.assignCoeff(i);
-  }
-};
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
-  }
-};
-
-/**************************
-*** Slice vectorization ***
-***************************/
-
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::Scalar Scalar;
-    typedef typename Kernel::PacketType PacketType;
-    enum {
-      packetSize = unpacket_traits<PacketType>::size,
-      requestedAlignment = int(Kernel::AssignmentTraits::InnerRequiredAlignment),
-      alignable = packet_traits<Scalar>::AlignedOnScalar || int(Kernel::AssignmentTraits::DstAlignment)>=sizeof(Scalar),
-      dstIsAligned = int(Kernel::AssignmentTraits::DstAlignment)>=int(requestedAlignment),
-      dstAlignment = alignable ? int(requestedAlignment)
-                               : int(Kernel::AssignmentTraits::DstAlignment)
-    };
-    const Scalar *dst_ptr = kernel.dstDataPtr();
-    if((!bool(dstIsAligned)) && (UIntPtr(dst_ptr) % sizeof(Scalar))>0)
-    {
-      // the pointer is not aligend-on scalar, so alignment is not possible
-      return dense_assignment_loop<Kernel,DefaultTraversal,NoUnrolling>::run(kernel);
-    }
-    const Index packetAlignedMask = packetSize - 1;
-    const Index innerSize = kernel.innerSize();
-    const Index outerSize = kernel.outerSize();
-    const Index alignedStep = alignable ? (packetSize - kernel.outerStride() % packetSize) & packetAlignedMask : 0;
-    Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned<requestedAlignment>(dst_ptr, innerSize);
-
-    for(Index outer = 0; outer < outerSize; ++outer)
-    {
-      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
-      // do the non-vectorizable part of the assignment
-      for(Index inner = 0; inner<alignedStart ; ++inner)
-        kernel.assignCoeffByOuterInner(outer, inner);
-
-      // do the vectorizable part of the assignment
-      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
-        kernel.template assignPacketByOuterInner<dstAlignment, Unaligned, PacketType>(outer, inner);
-
-      // do the non-vectorizable part of the assignment
-      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
-        kernel.assignCoeffByOuterInner(outer, inner);
-
-      alignedStart = numext::mini((alignedStart+alignedStep)%packetSize, innerSize);
-    }
-  }
-};
-
-#if EIGEN_UNALIGNED_VECTORIZE
-template<typename Kernel>
-struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, InnerUnrolling>
-{
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
-  {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
-    typedef typename Kernel::PacketType PacketType;
-
-    enum { size = DstXprType::InnerSizeAtCompileTime,
-           packetSize =unpacket_traits<PacketType>::size,
-           vectorizableSize = (size/packetSize)*packetSize };
-
-    for(Index outer = 0; outer < kernel.outerSize(); ++outer)
-    {
-      copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, vectorizableSize, 0, 0>::run(kernel, outer);
-      copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, vectorizableSize, size>::run(kernel, outer);
-    }
-  }
-};
-#endif
-
-
-/***************************************************************************
-* Part 4 : Generic dense assignment kernel
-***************************************************************************/
-
-// This class generalize the assignment of a coefficient (or packet) from one dense evaluator
-// to another dense writable evaluator.
-// It is parametrized by the two evaluators, and the actual assignment functor.
-// This abstraction level permits to keep the evaluation loops as simple and as generic as possible.
-// One can customize the assignment using this generic dense_assignment_kernel with different
-// functors, or by completely overloading it, by-passing a functor.
-template<typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
-class generic_dense_assignment_kernel
-{
-protected:
-  typedef typename DstEvaluatorTypeT::XprType DstXprType;
-  typedef typename SrcEvaluatorTypeT::XprType SrcXprType;
-public:
-  
-  typedef DstEvaluatorTypeT DstEvaluatorType;
-  typedef SrcEvaluatorTypeT SrcEvaluatorType;
-  typedef typename DstEvaluatorType::Scalar Scalar;
-  typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
-  typedef typename AssignmentTraits::PacketType PacketType;
-  
-  
-  EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
-    : m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr)
-  {
-    #ifdef EIGEN_DEBUG_ASSIGN
-    AssignmentTraits::debug();
-    #endif
-  }
-  
-  EIGEN_DEVICE_FUNC Index size() const        { return m_dstExpr.size(); }
-  EIGEN_DEVICE_FUNC Index innerSize() const   { return m_dstExpr.innerSize(); }
-  EIGEN_DEVICE_FUNC Index outerSize() const   { return m_dstExpr.outerSize(); }
-  EIGEN_DEVICE_FUNC Index rows() const        { return m_dstExpr.rows(); }
-  EIGEN_DEVICE_FUNC Index cols() const        { return m_dstExpr.cols(); }
-  EIGEN_DEVICE_FUNC Index outerStride() const { return m_dstExpr.outerStride(); }
-  
-  EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() { return m_dst; }
-  EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const { return m_src; }
-  
-  /// Assign src(row,col) to dst(row,col) through the assignment functor.
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index row, Index col)
-  {
-    m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
-  }
-  
-  /// \sa assignCoeff(Index,Index)
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index index)
-  {
-    m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
-  }
-  
-  /// \sa assignCoeff(Index,Index)
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeffByOuterInner(Index outer, Index inner)
-  {
-    Index row = rowIndexByOuterInner(outer, inner); 
-    Index col = colIndexByOuterInner(outer, inner); 
-    assignCoeff(row, col);
-  }
-  
-  
-  template<int StoreMode, int LoadMode, typename PacketType>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index row, Index col)
-  {
-    m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode,PacketType>(row,col));
-  }
-  
-  template<int StoreMode, int LoadMode, typename PacketType>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index index)
-  {
-    m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
-  }
-  
-  template<int StoreMode, int LoadMode, typename PacketType>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketByOuterInner(Index outer, Index inner)
-  {
-    Index row = rowIndexByOuterInner(outer, inner); 
-    Index col = colIndexByOuterInner(outer, inner);
-    assignPacket<StoreMode,LoadMode,PacketType>(row, col);
-  }
-  
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner)
-  {
-    typedef typename DstEvaluatorType::ExpressionTraits Traits;
-    return int(Traits::RowsAtCompileTime) == 1 ? 0
-      : int(Traits::ColsAtCompileTime) == 1 ? inner
-      : int(DstEvaluatorType::Flags)&RowMajorBit ? outer
-      : inner;
-  }
-
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner)
-  {
-    typedef typename DstEvaluatorType::ExpressionTraits Traits;
-    return int(Traits::ColsAtCompileTime) == 1 ? 0
-      : int(Traits::RowsAtCompileTime) == 1 ? inner
-      : int(DstEvaluatorType::Flags)&RowMajorBit ? inner
-      : outer;
-  }
-
-  EIGEN_DEVICE_FUNC const Scalar* dstDataPtr() const
-  {
-    return m_dstExpr.data();
-  }
-  
-protected:
-  DstEvaluatorType& m_dst;
-  const SrcEvaluatorType& m_src;
-  const Functor &m_functor;
-  // TODO find a way to avoid the needs of the original expression
-  DstXprType& m_dstExpr;
-};
-
-/***************************************************************************
-* Part 5 : Entry point for dense rectangular assignment
-***************************************************************************/
-
-template<typename DstXprType,typename SrcXprType, typename Functor>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const Functor &/*func*/)
-{
-  EIGEN_ONLY_USED_FOR_DEBUG(dst);
-  EIGEN_ONLY_USED_FOR_DEBUG(src);
-  eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
-}
-
-template<typename DstXprType,typename SrcXprType, typename T1, typename T2>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const internal::assign_op<T1,T2> &/*func*/)
-{
-  Index dstRows = src.rows();
-  Index dstCols = src.cols();
-  if(((dst.rows()!=dstRows) || (dst.cols()!=dstCols)))
-    dst.resize(dstRows, dstCols);
-  eigen_assert(dst.rows() == dstRows && dst.cols() == dstCols);
-}
-
-template<typename DstXprType, typename SrcXprType, typename Functor>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
-{
-  typedef evaluator<DstXprType> DstEvaluatorType;
-  typedef evaluator<SrcXprType> SrcEvaluatorType;
-
-  SrcEvaluatorType srcEvaluator(src);
-
-  // NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
-  // we need to resize the destination after the source evaluator has been created.
-  resize_if_allowed(dst, src, func);
-
-  DstEvaluatorType dstEvaluator(dst);
-    
-  typedef generic_dense_assignment_kernel<DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
-  Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
-
-  dense_assignment_loop<Kernel>::run(kernel);
-}
-
-template<typename DstXprType, typename SrcXprType>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src)
-{
-  call_dense_assignment_loop(dst, src, internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar>());
-}
-
-/***************************************************************************
-* Part 6 : Generic assignment
-***************************************************************************/
-
-// Based on the respective shapes of the destination and source,
-// the class AssignmentKind determine the kind of assignment mechanism.
-// AssignmentKind must define a Kind typedef.
-template<typename DstShape, typename SrcShape> struct AssignmentKind;
-
-// Assignement kind defined in this file:
-struct Dense2Dense {};
-struct EigenBase2EigenBase {};
-
-template<typename,typename> struct AssignmentKind { typedef EigenBase2EigenBase Kind; };
-template<> struct AssignmentKind<DenseShape,DenseShape> { typedef Dense2Dense Kind; };
-    
-// This is the main assignment class
-template< typename DstXprType, typename SrcXprType, typename Functor,
-          typename Kind = typename AssignmentKind< typename evaluator_traits<DstXprType>::Shape , typename evaluator_traits<SrcXprType>::Shape >::Kind,
-          typename EnableIf = void>
-struct Assignment;
-
-
-// The only purpose of this call_assignment() function is to deal with noalias() / "assume-aliasing" and automatic transposition.
-// Indeed, I (Gael) think that this concept of "assume-aliasing" was a mistake, and it makes thing quite complicated.
-// So this intermediate function removes everything related to "assume-aliasing" such that Assignment
-// does not has to bother about these annoying details.
-
-template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(Dst& dst, const Src& src)
-{
-  call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
-}
-template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(const Dst& dst, const Src& src)
-{
-  call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
-}
-                     
-// Deal with "assume-aliasing"
-template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if< evaluator_assume_aliasing<Src>::value, void*>::type = 0)
-{
-  typename plain_matrix_type<Src>::type tmp(src);
-  call_assignment_no_alias(dst, tmp, func);
-}
-
-template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<!evaluator_assume_aliasing<Src>::value, void*>::type = 0)
-{
-  call_assignment_no_alias(dst, src, func);
-}
-
-// by-pass "assume-aliasing"
-// When there is no aliasing, we require that 'dst' has been properly resized
-template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
-{
-  call_assignment_no_alias(dst.expression(), src, func);
-}
-
-
-template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
-{
-  enum {
-    NeedToTranspose = (    (int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1)
-                        || (int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)
-                      ) && int(Dst::SizeAtCompileTime) != 1
-  };
-
-  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
-  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
-  ActualDstType actualDst(dst);
-  
-  // TODO check whether this is the right place to perform these checks:
-  EIGEN_STATIC_ASSERT_LVALUE(Dst)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned,Src)
-  EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename ActualDstTypeCleaned::Scalar,typename Src::Scalar);
-  
-  Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
-}
-template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment_no_alias(Dst& dst, const Src& src)
-{
-  call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
-}
-
-template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func& func)
-{
-  // TODO check whether this is the right place to perform these checks:
-  EIGEN_STATIC_ASSERT_LVALUE(Dst)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst,Src)
-  EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename Dst::Scalar,typename Src::Scalar);
-
-  Assignment<Dst,Src,Func>::run(dst, src, func);
-}
-template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src)
-{
-  call_assignment_no_alias_no_transpose(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
-}
-
-// forward declaration
-template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, const Src &src);
-
-// Generic Dense to Dense assignment
-// Note that the last template argument "Weak" is needed to make it possible to perform
-// both partial specialization+SFINAE without ambiguous specialization
-template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
-struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Weak>
-{
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
-  {
-#ifndef EIGEN_NO_DEBUG
-    internal::check_for_aliasing(dst, src);
-#endif
-    
-    call_dense_assignment_loop(dst, src, func);
-  }
-};
-
-// Generic assignment through evalTo.
-// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism.
-// Note that the last template argument "Weak" is needed to make it possible to perform
-// both partial specialization+SFINAE without ambiguous specialization
-template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
-struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Weak>
-{
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
-  {
-    Index dstRows = src.rows();
-    Index dstCols = src.cols();
-    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
-      dst.resize(dstRows, dstCols);
-
-    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
-    src.evalTo(dst);
-  }
-
-  // NOTE The following two functions are templated to avoid their instanciation if not needed
-  //      This is needed because some expressions supports evalTo only and/or have 'void' as scalar type.
-  template<typename SrcScalarType>
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
-  {
-    Index dstRows = src.rows();
-    Index dstCols = src.cols();
-    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
-      dst.resize(dstRows, dstCols);
-
-    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
-    src.addTo(dst);
-  }
-
-  template<typename SrcScalarType>
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,SrcScalarType> &/*func*/)
-  {
-    Index dstRows = src.rows();
-    Index dstCols = src.cols();
-    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
-      dst.resize(dstRows, dstCols);
-
-    eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
-    src.subTo(dst);
-  }
-};
-
-} // namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_ASSIGN_EVALUATOR_H

deps_src/eigen/Eigen/src/Core/Assign_MKL.h

@@ -1,178 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
- Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
- 
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
- ********************************************************************************
-*/
-
-#ifndef EIGEN_ASSIGN_VML_H
-#define EIGEN_ASSIGN_VML_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Dst, typename Src>
-class vml_assign_traits
-{
-  private:
-    enum {
-      DstHasDirectAccess = Dst::Flags & DirectAccessBit,
-      SrcHasDirectAccess = Src::Flags & DirectAccessBit,
-      StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
-      InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
-                : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
-                : int(Dst::RowsAtCompileTime),
-      InnerMaxSize  = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
-                    : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
-                    : int(Dst::MaxRowsAtCompileTime),
-      MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
-
-      MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
-      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
-      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
-      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD
-    };
-  public:
-    enum {
-      EnableVml = MightEnableVml && LargeEnough,
-      Traversal = MightLinearize ? LinearTraversal : DefaultTraversal
-    };
-};
-
-#define EIGEN_PP_EXPAND(ARG) ARG
-#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
-#define EIGEN_VMLMODE_EXPAND_LA , VML_HA
-#else
-#define EIGEN_VMLMODE_EXPAND_LA , VML_LA
-#endif
-
-#define EIGEN_VMLMODE_EXPAND__ 
-
-#define EIGEN_VMLMODE_PREFIX_LA vm
-#define EIGEN_VMLMODE_PREFIX__  v
-#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_,VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                                           \
-  template< typename DstXprType, typename SrcXprNested>                                                                         \
-  struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>,   \
-                   Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {              \
-    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType;                                            \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) {                       \
-      resize_if_allowed(dst, src, func);                                                                                        \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                                       \
-      if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) {                                              \
-        VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(),                                                        \
-              (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) );                                           \
-      } else {                                                                                                                  \
-        const Index outerSize = dst.outerSize();                                                                                \
-        for(Index outer = 0; outer < outerSize; ++outer) {                                                                      \
-          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) :                             \
-                                                      &(src.nestedExpression().coeffRef(0, outer));                             \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));                           \
-          VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr,                                                                      \
-                (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE));                                             \
-        }                                                                                                                       \
-      }                                                                                                                         \
-    }                                                                                                                           \
-  };                                                                                                                            \
-
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE)           \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)                                                         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE)
-  
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE)                                                              \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                               \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
-
-  
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin,   Sin,   LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin,  Asin,  LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh,  Sinh,  LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos,   Cos,   LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos,  Acos,  LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh,  Cosh,  LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan,   Tan,   LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan,  Atan,  LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh,  Tanh,  LA)
-// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,   Abs,    _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp,   Exp,   LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log,   Ln,    LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt,  Sqrt,  _)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr,   _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg,      _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round,  _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor,  _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil,  Ceil,   _)
-
-#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                                           \
-  template< typename DstXprType, typename SrcXprNested, typename Plain>                                                       \
-  struct Assignment<DstXprType, CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested,                       \
-                    const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> >, assign_op<EIGENTYPE,EIGENTYPE>,    \
-                   Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {            \
-    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested,                                           \
-                    const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType;                         \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) {                     \
-      resize_if_allowed(dst, src, func);                                                                                      \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                                     \
-      VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other);                                       \
-      if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal)                                              \
-      {                                                                                                                       \
-        VMLOP( dst.size(), (const VMLTYPE*)src.lhs().data(), exponent,                                                        \
-              (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE) );                                         \
-      } else {                                                                                                                \
-        const Index outerSize = dst.outerSize();                                                                              \
-        for(Index outer = 0; outer < outerSize; ++outer) {                                                                    \
-          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.lhs().coeffRef(outer,0)) :                                        \
-                                                      &(src.lhs().coeffRef(0, outer));                                        \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));                         \
-          VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent,                                                          \
-                 (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_##VMLMODE));                                          \
-        }                                                                                                                     \
-      }                                                                                                                       \
-    }                                                                                                                         \
-  };
-  
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float,    float,         LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double,   double,        LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8,  LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_ASSIGN_VML_H

deps_src/eigen/Eigen/src/Core/BandMatrix.h

@@ -1,353 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_BANDMATRIX_H
-#define EIGEN_BANDMATRIX_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Derived>
-class BandMatrixBase : public EigenBase<Derived>
-{
-  public:
-
-    enum {
-      Flags = internal::traits<Derived>::Flags,
-      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
-      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
-      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
-      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
-      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
-      Supers = internal::traits<Derived>::Supers,
-      Subs   = internal::traits<Derived>::Subs,
-      Options = internal::traits<Derived>::Options
-    };
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
-    typedef typename DenseMatrixType::StorageIndex StorageIndex;
-    typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
-    typedef EigenBase<Derived> Base;
-
-  protected:
-    enum {
-      DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic))
-                            ? 1 + Supers + Subs
-                            : Dynamic,
-      SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime)
-    };
-
-  public:
-    
-    using Base::derived;
-    using Base::rows;
-    using Base::cols;
-
-    /** \returns the number of super diagonals */
-    inline Index supers() const { return derived().supers(); }
-
-    /** \returns the number of sub diagonals */
-    inline Index subs() const { return derived().subs(); }
-    
-    /** \returns an expression of the underlying coefficient matrix */
-    inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
-    
-    /** \returns an expression of the underlying coefficient matrix */
-    inline CoefficientsType& coeffs() { return derived().coeffs(); }
-
-    /** \returns a vector expression of the \a i -th column,
-      * only the meaningful part is returned.
-      * \warning the internal storage must be column major. */
-    inline Block<CoefficientsType,Dynamic,1> col(Index i)
-    {
-      EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-      Index start = 0;
-      Index len = coeffs().rows();
-      if (i<=supers())
-      {
-        start = supers()-i;
-        len = (std::min)(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
-      }
-      else if (i>=rows()-subs())
-        len = std::max<Index>(0,coeffs().rows() - (i + 1 - rows() + subs()));
-      return Block<CoefficientsType,Dynamic,1>(coeffs(), start, i, len, 1);
-    }
-
-    /** \returns a vector expression of the main diagonal */
-    inline Block<CoefficientsType,1,SizeAtCompileTime> diagonal()
-    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
-
-    /** \returns a vector expression of the main diagonal (const version) */
-    inline const Block<const CoefficientsType,1,SizeAtCompileTime> diagonal() const
-    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
-
-    template<int Index> struct DiagonalIntReturnType {
-      enum {
-        ReturnOpposite = (Options&SelfAdjoint) && (((Index)>0 && Supers==0) || ((Index)<0 && Subs==0)),
-        Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
-        ActualIndex = ReturnOpposite ? -Index : Index,
-        DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic)
-                     ? Dynamic
-                     : (ActualIndex<0
-                     ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
-                     : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
-      };
-      typedef Block<CoefficientsType,1, DiagonalSize> BuildType;
-      typedef typename internal::conditional<Conjugate,
-                 CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,BuildType >,
-                 BuildType>::type Type;
-    };
-
-    /** \returns a vector expression of the \a N -th sub or super diagonal */
-    template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
-    {
-      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
-    }
-
-    /** \returns a vector expression of the \a N -th sub or super diagonal */
-    template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
-    {
-      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
-    }
-
-    /** \returns a vector expression of the \a i -th sub or super diagonal */
-    inline Block<CoefficientsType,1,Dynamic> diagonal(Index i)
-    {
-      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
-      return Block<CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
-    }
-
-    /** \returns a vector expression of the \a i -th sub or super diagonal */
-    inline const Block<const CoefficientsType,1,Dynamic> diagonal(Index i) const
-    {
-      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
-      return Block<const CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
-    }
-    
-    template<typename Dest> inline void evalTo(Dest& dst) const
-    {
-      dst.resize(rows(),cols());
-      dst.setZero();
-      dst.diagonal() = diagonal();
-      for (Index i=1; i<=supers();++i)
-        dst.diagonal(i) = diagonal(i);
-      for (Index i=1; i<=subs();++i)
-        dst.diagonal(-i) = diagonal(-i);
-    }
-
-    DenseMatrixType toDenseMatrix() const
-    {
-      DenseMatrixType res(rows(),cols());
-      evalTo(res);
-      return res;
-    }
-
-  protected:
-
-    inline Index diagonalLength(Index i) const
-    { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); }
-};
-
-/**
-  * \class BandMatrix
-  * \ingroup Core_Module
-  *
-  * \brief Represents a rectangular matrix with a banded storage
-  *
-  * \tparam _Scalar Numeric type, i.e. float, double, int
-  * \tparam _Rows Number of rows, or \b Dynamic
-  * \tparam _Cols Number of columns, or \b Dynamic
-  * \tparam _Supers Number of super diagonal
-  * \tparam _Subs Number of sub diagonal
-  * \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
-  *                  The former controls \ref TopicStorageOrders "storage order", and defaults to
-  *                  column-major. The latter controls whether the matrix represents a selfadjoint
-  *                  matrix in which case either Supers of Subs have to be null.
-  *
-  * \sa class TridiagonalMatrix
-  */
-
-template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
-struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
-{
-  typedef _Scalar Scalar;
-  typedef Dense StorageKind;
-  typedef Eigen::Index StorageIndex;
-  enum {
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    RowsAtCompileTime = _Rows,
-    ColsAtCompileTime = _Cols,
-    MaxRowsAtCompileTime = _Rows,
-    MaxColsAtCompileTime = _Cols,
-    Flags = LvalueBit,
-    Supers = _Supers,
-    Subs = _Subs,
-    Options = _Options,
-    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
-  };
-  typedef Matrix<Scalar,DataRowsAtCompileTime,ColsAtCompileTime,Options&RowMajor?RowMajor:ColMajor> CoefficientsType;
-};
-
-template<typename _Scalar, int Rows, int Cols, int Supers, int Subs, int Options>
-class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
-{
-  public:
-
-    typedef typename internal::traits<BandMatrix>::Scalar Scalar;
-    typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
-    typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
-
-    explicit inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
-      : m_coeffs(1+supers+subs,cols),
-        m_rows(rows), m_supers(supers), m_subs(subs)
-    {
-    }
-
-    /** \returns the number of columns */
-    inline Index rows() const { return m_rows.value(); }
-
-    /** \returns the number of rows */
-    inline Index cols() const { return m_coeffs.cols(); }
-
-    /** \returns the number of super diagonals */
-    inline Index supers() const { return m_supers.value(); }
-
-    /** \returns the number of sub diagonals */
-    inline Index subs() const { return m_subs.value(); }
-
-    inline const CoefficientsType& coeffs() const { return m_coeffs; }
-    inline CoefficientsType& coeffs() { return m_coeffs; }
-
-  protected:
-
-    CoefficientsType m_coeffs;
-    internal::variable_if_dynamic<Index, Rows>   m_rows;
-    internal::variable_if_dynamic<Index, Supers> m_supers;
-    internal::variable_if_dynamic<Index, Subs>   m_subs;
-};
-
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
-class BandMatrixWrapper;
-
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
-struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
-{
-  typedef typename _CoefficientsType::Scalar Scalar;
-  typedef typename _CoefficientsType::StorageKind StorageKind;
-  typedef typename _CoefficientsType::StorageIndex StorageIndex;
-  enum {
-    CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
-    RowsAtCompileTime = _Rows,
-    ColsAtCompileTime = _Cols,
-    MaxRowsAtCompileTime = _Rows,
-    MaxColsAtCompileTime = _Cols,
-    Flags = LvalueBit,
-    Supers = _Supers,
-    Subs = _Subs,
-    Options = _Options,
-    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
-  };
-  typedef _CoefficientsType CoefficientsType;
-};
-
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
-class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
-{
-  public:
-
-    typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
-    typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
-    typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
-
-    explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
-      : m_coeffs(coeffs),
-        m_rows(rows), m_supers(supers), m_subs(subs)
-    {
-      EIGEN_UNUSED_VARIABLE(cols);
-      //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
-    }
-
-    /** \returns the number of columns */
-    inline Index rows() const { return m_rows.value(); }
-
-    /** \returns the number of rows */
-    inline Index cols() const { return m_coeffs.cols(); }
-
-    /** \returns the number of super diagonals */
-    inline Index supers() const { return m_supers.value(); }
-
-    /** \returns the number of sub diagonals */
-    inline Index subs() const { return m_subs.value(); }
-
-    inline const CoefficientsType& coeffs() const { return m_coeffs; }
-
-  protected:
-
-    const CoefficientsType& m_coeffs;
-    internal::variable_if_dynamic<Index, _Rows>   m_rows;
-    internal::variable_if_dynamic<Index, _Supers> m_supers;
-    internal::variable_if_dynamic<Index, _Subs>   m_subs;
-};
-
-/**
-  * \class TridiagonalMatrix
-  * \ingroup Core_Module
-  *
-  * \brief Represents a tridiagonal matrix with a compact banded storage
-  *
-  * \tparam Scalar Numeric type, i.e. float, double, int
-  * \tparam Size Number of rows and cols, or \b Dynamic
-  * \tparam Options Can be 0 or \b SelfAdjoint
-  *
-  * \sa class BandMatrix
-  */
-template<typename Scalar, int Size, int Options>
-class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
-{
-    typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
-    typedef typename Base::StorageIndex StorageIndex;
-  public:
-    explicit TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
-
-    inline typename Base::template DiagonalIntReturnType<1>::Type super()
-    { return Base::template diagonal<1>(); }
-    inline const typename Base::template DiagonalIntReturnType<1>::Type super() const
-    { return Base::template diagonal<1>(); }
-    inline typename Base::template DiagonalIntReturnType<-1>::Type sub()
-    { return Base::template diagonal<-1>(); }
-    inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const
-    { return Base::template diagonal<-1>(); }
-  protected:
-};
-
-
-struct BandShape {};
-
-template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
-struct evaluator_traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
-  : public evaluator_traits_base<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
-{
-  typedef BandShape Shape;
-};
-
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
-struct evaluator_traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
-  : public evaluator_traits_base<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
-{
-  typedef BandShape Shape;
-};
-
-template<> struct AssignmentKind<DenseShape,BandShape> { typedef EigenBase2EigenBase Kind; };
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_BANDMATRIX_H

deps_src/eigen/Eigen/src/Core/Block.h

@@ -1,452 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_BLOCK_H
-#define EIGEN_BLOCK_H
-
-namespace Eigen { 
-
-namespace internal {
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprType>
-{
-  typedef typename traits<XprType>::Scalar Scalar;
-  typedef typename traits<XprType>::StorageKind StorageKind;
-  typedef typename traits<XprType>::XprKind XprKind;
-  typedef typename ref_selector<XprType>::type XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
-  enum{
-    MatrixRows = traits<XprType>::RowsAtCompileTime,
-    MatrixCols = traits<XprType>::ColsAtCompileTime,
-    RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows,
-    ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols,
-    MaxRowsAtCompileTime = BlockRows==0 ? 0
-                         : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
-                         : int(traits<XprType>::MaxRowsAtCompileTime),
-    MaxColsAtCompileTime = BlockCols==0 ? 0
-                         : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
-                         : int(traits<XprType>::MaxColsAtCompileTime),
-
-    XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
-    IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
-               : (MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
-               : XprTypeIsRowMajor,
-    HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
-    InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
-    InnerStrideAtCompileTime = HasSameStorageOrderAsXprType
-                             ? int(inner_stride_at_compile_time<XprType>::ret)
-                             : int(outer_stride_at_compile_time<XprType>::ret),
-    OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
-                             ? int(outer_stride_at_compile_time<XprType>::ret)
-                             : int(inner_stride_at_compile_time<XprType>::ret),
-
-    // FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
-    FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
-    FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
-    Flags = (traits<XprType>::Flags & (DirectAccessBit | (InnerPanel?CompressedAccessBit:0))) | FlagsLvalueBit | FlagsRowMajorBit,
-    // FIXME DirectAccessBit should not be handled by expressions
-    // 
-    // Alignment is needed by MapBase's assertions
-    // We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the respective evaluator
-    Alignment = 0
-  };
-};
-
-template<typename XprType, int BlockRows=Dynamic, int BlockCols=Dynamic, bool InnerPanel = false,
-         bool HasDirectAccess = internal::has_direct_access<XprType>::ret> class BlockImpl_dense;
-         
-} // end namespace internal
-
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind> class BlockImpl;
-
-/** \class Block
-  * \ingroup Core_Module
-  *
-  * \brief Expression of a fixed-size or dynamic-size block
-  *
-  * \tparam XprType the type of the expression in which we are taking a block
-  * \tparam BlockRows the number of rows of the block we are taking at compile time (optional)
-  * \tparam BlockCols the number of columns of the block we are taking at compile time (optional)
-  * \tparam InnerPanel is true, if the block maps to a set of rows of a row major matrix or
-  *         to set of columns of a column major matrix (optional). The parameter allows to determine
-  *         at compile time whether aligned access is possible on the block expression.
-  *
-  * This class represents an expression of either a fixed-size or dynamic-size block. It is the return
-  * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
-  * most of the time this is the only way it is used.
-  *
-  * However, if you want to directly maniputate block expressions,
-  * for instance if you want to write a function returning such an expression, you
-  * will need to use this class.
-  *
-  * Here is an example illustrating the dynamic case:
-  * \include class_Block.cpp
-  * Output: \verbinclude class_Block.out
-  *
-  * \note Even though this expression has dynamic size, in the case where \a XprType
-  * has fixed size, this expression inherits a fixed maximal size which means that evaluating
-  * it does not cause a dynamic memory allocation.
-  *
-  * Here is an example illustrating the fixed-size case:
-  * \include class_FixedBlock.cpp
-  * Output: \verbinclude class_FixedBlock.out
-  *
-  * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
-  */
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
-  : public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind>
-{
-    typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
-  public:
-    //typedef typename Impl::Base Base;
-    typedef Impl Base;
-    EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
-    
-    typedef typename internal::remove_all<XprType>::type NestedExpression;
-  
-    /** Column or Row constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline Block(XprType& xpr, Index i) : Impl(xpr,i)
-    {
-      eigen_assert( (i>=0) && (
-          ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
-        ||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
-    }
-
-    /** Fixed-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline Block(XprType& xpr, Index startRow, Index startCol)
-      : Impl(xpr, startRow, startCol)
-    {
-      EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
-      eigen_assert(startRow >= 0 && BlockRows >= 0 && startRow + BlockRows <= xpr.rows()
-             && startCol >= 0 && BlockCols >= 0 && startCol + BlockCols <= xpr.cols());
-    }
-
-    /** Dynamic-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline Block(XprType& xpr,
-          Index startRow, Index startCol,
-          Index blockRows, Index blockCols)
-      : Impl(xpr, startRow, startCol, blockRows, blockCols)
-    {
-      eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
-          && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
-      eigen_assert(startRow >= 0 && blockRows >= 0 && startRow  <= xpr.rows() - blockRows
-          && startCol >= 0 && blockCols >= 0 && startCol <= xpr.cols() - blockCols);
-    }
-};
-         
-// The generic default implementation for dense block simplu forward to the internal::BlockImpl_dense
-// that must be specialized for direct and non-direct access...
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
-  : public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel>
-{
-    typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
-    typedef typename XprType::StorageIndex StorageIndex;
-  public:
-    typedef Impl Base;
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
-    EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
-    EIGEN_DEVICE_FUNC inline BlockImpl(XprType& xpr, Index startRow, Index startCol) : Impl(xpr, startRow, startCol) {}
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, Index blockCols)
-      : Impl(xpr, startRow, startCol, blockRows, blockCols) {}
-};
-
-namespace internal {
-
-/** \internal Internal implementation of dense Blocks in the general case. */
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
-  : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel> >::type
-{
-    typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
-    typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
-  public:
-
-    typedef typename internal::dense_xpr_base<BlockType>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
-
-    // class InnerIterator; // FIXME apparently never used
-
-    /** Column or Row constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr, Index i)
-      : m_xpr(xpr),
-        // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
-        // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
-        // all other cases are invalid.
-        // The case a 1x1 matrix seems ambiguous, but the result is the same anyway.
-        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
-        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
-        m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
-        m_blockCols(BlockCols==1 ? 1 : xpr.cols())
-    {}
-
-    /** Fixed-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
-                    m_blockRows(BlockRows), m_blockCols(BlockCols)
-    {}
-
-    /** Dynamic-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr,
-          Index startRow, Index startCol,
-          Index blockRows, Index blockCols)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
-                    m_blockRows(blockRows), m_blockCols(blockCols)
-    {}
-
-    EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
-    EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
-
-    EIGEN_DEVICE_FUNC
-    inline Scalar& coeffRef(Index rowId, Index colId)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(XprType)
-      return m_xpr.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return m_xpr.derived().coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
-    {
-      return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Scalar& coeffRef(Index index)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(XprType)
-      return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index index) const
-    {
-      return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const CoeffReturnType coeff(Index index) const
-    {
-      return m_xpr.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                         m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-
-    template<int LoadMode>
-    inline PacketScalar packet(Index rowId, Index colId) const
-    {
-      return m_xpr.template packet<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value());
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
-    {
-      m_xpr.template writePacket<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value(), val);
-    }
-
-    template<int LoadMode>
-    inline PacketScalar packet(Index index) const
-    {
-      return m_xpr.template packet<Unaligned>
-              (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-               m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& val)
-    {
-      m_xpr.template writePacket<Unaligned>
-         (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
-    }
-
-    #ifdef EIGEN_PARSED_BY_DOXYGEN
-    /** \sa MapBase::data() */
-    EIGEN_DEVICE_FUNC inline const Scalar* data() const;
-    EIGEN_DEVICE_FUNC inline Index innerStride() const;
-    EIGEN_DEVICE_FUNC inline Index outerStride() const;
-    #endif
-
-    EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
-    { 
-      return m_xpr; 
-    }
-
-    EIGEN_DEVICE_FUNC
-    XprType& nestedExpression() { return m_xpr; }
-      
-    EIGEN_DEVICE_FUNC
-    StorageIndex startRow() const
-    { 
-      return m_startRow.value(); 
-    }
-      
-    EIGEN_DEVICE_FUNC
-    StorageIndex startCol() const
-    { 
-      return m_startCol.value(); 
-    }
-
-  protected:
-
-    XprTypeNested m_xpr;
-    const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
-    const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
-    const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
-    const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
-};
-
-/** \internal Internal implementation of dense Blocks in the direct access case.*/
-template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
-  : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> >
-{
-    typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
-    typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
-    enum {
-      XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0
-    };
-  public:
-
-    typedef MapBase<BlockType> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
-
-    /** Column or Row constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr, Index i)
-      : Base(xpr.data() + i * (    ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) 
-                                || ((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && ( XprTypeIsRowMajor)) ? xpr.innerStride() : xpr.outerStride()),
-             BlockRows==1 ? 1 : xpr.rows(),
-             BlockCols==1 ? 1 : xpr.cols()),
-        m_xpr(xpr),
-        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
-        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)
-    {
-      init();
-    }
-
-    /** Fixed-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
-      : Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol)),
-        m_xpr(xpr), m_startRow(startRow), m_startCol(startCol)
-    {
-      init();
-    }
-
-    /** Dynamic-size constructor
-      */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr,
-          Index startRow, Index startCol,
-          Index blockRows, Index blockCols)
-      : Base(xpr.data()+xpr.innerStride()*(XprTypeIsRowMajor?startCol:startRow) + xpr.outerStride()*(XprTypeIsRowMajor?startRow:startCol), blockRows, blockCols),
-        m_xpr(xpr), m_startRow(startRow), m_startCol(startCol)
-    {
-      init();
-    }
-
-    EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
-    { 
-      return m_xpr; 
-    }
-
-    EIGEN_DEVICE_FUNC
-    XprType& nestedExpression() { return m_xpr; }
-      
-    /** \sa MapBase::innerStride() */
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const
-    {
-      return internal::traits<BlockType>::HasSameStorageOrderAsXprType
-             ? m_xpr.innerStride()
-             : m_xpr.outerStride();
-    }
-
-    /** \sa MapBase::outerStride() */
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const
-    {
-      return m_outerStride;
-    }
-
-    EIGEN_DEVICE_FUNC
-    StorageIndex startRow() const
-    {
-      return m_startRow.value();
-    }
-
-    EIGEN_DEVICE_FUNC
-    StorageIndex startCol() const
-    {
-      return m_startCol.value();
-    }
-
-  #ifndef __SUNPRO_CC
-  // FIXME sunstudio is not friendly with the above friend...
-  // META-FIXME there is no 'friend' keyword around here. Is this obsolete?
-  protected:
-  #endif
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** \internal used by allowAligned() */
-    EIGEN_DEVICE_FUNC
-    inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
-      : Base(data, blockRows, blockCols), m_xpr(xpr)
-    {
-      init();
-    }
-    #endif
-
-  protected:
-    EIGEN_DEVICE_FUNC
-    void init()
-    {
-      m_outerStride = internal::traits<BlockType>::HasSameStorageOrderAsXprType
-                    ? m_xpr.outerStride()
-                    : m_xpr.innerStride();
-    }
-
-    XprTypeNested m_xpr;
-    const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow;
-    const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol;
-    Index m_outerStride;
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_BLOCK_H

deps_src/eigen/Eigen/src/Core/BooleanRedux.h

@@ -1,164 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ALLANDANY_H
-#define EIGEN_ALLANDANY_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Derived, int UnrollCount>
-struct all_unroller
-{
-  typedef typename Derived::ExpressionTraits Traits;
-  enum {
-    col = (UnrollCount-1) / Traits::RowsAtCompileTime,
-    row = (UnrollCount-1) % Traits::RowsAtCompileTime
-  };
-
-  static inline bool run(const Derived &mat)
-  {
-    return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
-  }
-};
-
-template<typename Derived>
-struct all_unroller<Derived, 0>
-{
-  static inline bool run(const Derived &/*mat*/) { return true; }
-};
-
-template<typename Derived>
-struct all_unroller<Derived, Dynamic>
-{
-  static inline bool run(const Derived &) { return false; }
-};
-
-template<typename Derived, int UnrollCount>
-struct any_unroller
-{
-  typedef typename Derived::ExpressionTraits Traits;
-  enum {
-    col = (UnrollCount-1) / Traits::RowsAtCompileTime,
-    row = (UnrollCount-1) % Traits::RowsAtCompileTime
-  };
-  
-  static inline bool run(const Derived &mat)
-  {
-    return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
-  }
-};
-
-template<typename Derived>
-struct any_unroller<Derived, 0>
-{
-  static inline bool run(const Derived & /*mat*/) { return false; }
-};
-
-template<typename Derived>
-struct any_unroller<Derived, Dynamic>
-{
-  static inline bool run(const Derived &) { return false; }
-};
-
-} // end namespace internal
-
-/** \returns true if all coefficients are true
-  *
-  * Example: \include MatrixBase_all.cpp
-  * Output: \verbinclude MatrixBase_all.out
-  *
-  * \sa any(), Cwise::operator<()
-  */
-template<typename Derived>
-inline bool DenseBase<Derived>::all() const
-{
-  typedef internal::evaluator<Derived> Evaluator;
-  enum {
-    unroll = SizeAtCompileTime != Dynamic
-          && SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
-  };
-  Evaluator evaluator(derived());
-  if(unroll)
-    return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
-  else
-  {
-    for(Index j = 0; j < cols(); ++j)
-      for(Index i = 0; i < rows(); ++i)
-        if (!evaluator.coeff(i, j)) return false;
-    return true;
-  }
-}
-
-/** \returns true if at least one coefficient is true
-  *
-  * \sa all()
-  */
-template<typename Derived>
-inline bool DenseBase<Derived>::any() const
-{
-  typedef internal::evaluator<Derived> Evaluator;
-  enum {
-    unroll = SizeAtCompileTime != Dynamic
-          && SizeAtCompileTime * (Evaluator::CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
-  };
-  Evaluator evaluator(derived());
-  if(unroll)
-    return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic>::run(evaluator);
-  else
-  {
-    for(Index j = 0; j < cols(); ++j)
-      for(Index i = 0; i < rows(); ++i)
-        if (evaluator.coeff(i, j)) return true;
-    return false;
-  }
-}
-
-/** \returns the number of coefficients which evaluate to true
-  *
-  * \sa all(), any()
-  */
-template<typename Derived>
-inline Eigen::Index DenseBase<Derived>::count() const
-{
-  return derived().template cast<bool>().template cast<Index>().sum();
-}
-
-/** \returns true is \c *this contains at least one Not A Number (NaN).
-  *
-  * \sa allFinite()
-  */
-template<typename Derived>
-inline bool DenseBase<Derived>::hasNaN() const
-{
-#if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
-  return derived().array().isNaN().any();
-#else
-  return !((derived().array()==derived().array()).all());
-#endif
-}
-
-/** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values.
-  *
-  * \sa hasNaN()
-  */
-template<typename Derived>
-inline bool DenseBase<Derived>::allFinite() const
-{
-#if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
-  return derived().array().isFinite().all();
-#else
-  return !((derived()-derived()).hasNaN());
-#endif
-}
-    
-} // end namespace Eigen
-
-#endif // EIGEN_ALLANDANY_H

deps_src/eigen/Eigen/src/Core/CommaInitializer.h

@@ -1,160 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_COMMAINITIALIZER_H
-#define EIGEN_COMMAINITIALIZER_H
-
-namespace Eigen { 
-
-/** \class CommaInitializer
-  * \ingroup Core_Module
-  *
-  * \brief Helper class used by the comma initializer operator
-  *
-  * This class is internally used to implement the comma initializer feature. It is
-  * the return type of MatrixBase::operator<<, and most of the time this is the only
-  * way it is used.
-  *
-  * \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
-  */
-template<typename XprType>
-struct CommaInitializer
-{
-  typedef typename XprType::Scalar Scalar;
-
-  EIGEN_DEVICE_FUNC
-  inline CommaInitializer(XprType& xpr, const Scalar& s)
-    : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
-  {
-    m_xpr.coeffRef(0,0) = s;
-  }
-
-  template<typename OtherDerived>
-  EIGEN_DEVICE_FUNC
-  inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
-    : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
-  {
-    m_xpr.block(0, 0, other.rows(), other.cols()) = other;
-  }
-
-  /* Copy/Move constructor which transfers ownership. This is crucial in 
-   * absence of return value optimization to avoid assertions during destruction. */
-  // FIXME in C++11 mode this could be replaced by a proper RValue constructor
-  EIGEN_DEVICE_FUNC
-  inline CommaInitializer(const CommaInitializer& o)
-  : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
-    // Mark original object as finished. In absence of R-value references we need to const_cast:
-    const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
-    const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
-    const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
-  }
-
-  /* inserts a scalar value in the target matrix */
-  EIGEN_DEVICE_FUNC
-  CommaInitializer& operator,(const Scalar& s)
-  {
-    if (m_col==m_xpr.cols())
-    {
-      m_row+=m_currentBlockRows;
-      m_col = 0;
-      m_currentBlockRows = 1;
-      eigen_assert(m_row<m_xpr.rows()
-        && "Too many rows passed to comma initializer (operator<<)");
-    }
-    eigen_assert(m_col<m_xpr.cols()
-      && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows==1);
-    m_xpr.coeffRef(m_row, m_col++) = s;
-    return *this;
-  }
-
-  /* inserts a matrix expression in the target matrix */
-  template<typename OtherDerived>
-  EIGEN_DEVICE_FUNC
-  CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
-  {
-    if (m_col==m_xpr.cols() && (other.cols()!=0 || other.rows()!=m_currentBlockRows))
-    {
-      m_row+=m_currentBlockRows;
-      m_col = 0;
-      m_currentBlockRows = other.rows();
-      eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows()
-        && "Too many rows passed to comma initializer (operator<<)");
-    }
-    eigen_assert((m_col + other.cols() <= m_xpr.cols())
-      && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows==other.rows());
-    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>
-                    (m_row, m_col, other.rows(), other.cols()) = other;
-    m_col += other.cols();
-    return *this;
-  }
-
-  EIGEN_DEVICE_FUNC
-  inline ~CommaInitializer()
-#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
-  EIGEN_EXCEPTION_SPEC(Eigen::eigen_assert_exception)
-#endif
-  {
-      finished();
-  }
-
-  /** \returns the built matrix once all its coefficients have been set.
-    * Calling finished is 100% optional. Its purpose is to write expressions
-    * like this:
-    * \code
-    * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
-    * \endcode
-    */
-  EIGEN_DEVICE_FUNC
-  inline XprType& finished() {
-      eigen_assert(((m_row+m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0)
-           && m_col == m_xpr.cols()
-           && "Too few coefficients passed to comma initializer (operator<<)");
-      return m_xpr;
-  }
-
-  XprType& m_xpr;           // target expression
-  Index m_row;              // current row id
-  Index m_col;              // current col id
-  Index m_currentBlockRows; // current block height
-};
-
-/** \anchor MatrixBaseCommaInitRef
-  * Convenient operator to set the coefficients of a matrix.
-  *
-  * The coefficients must be provided in a row major order and exactly match
-  * the size of the matrix. Otherwise an assertion is raised.
-  *
-  * Example: \include MatrixBase_set.cpp
-  * Output: \verbinclude MatrixBase_set.out
-  * 
-  * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
-  *
-  * \sa CommaInitializer::finished(), class CommaInitializer
-  */
-template<typename Derived>
-inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
-{
-  return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
-}
-
-/** \sa operator<<(const Scalar&) */
-template<typename Derived>
-template<typename OtherDerived>
-inline CommaInitializer<Derived>
-DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
-{
-  return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_COMMAINITIALIZER_H

deps_src/eigen/Eigen/src/Core/ConditionEstimator.h

@@ -1,175 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.com)
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CONDITIONESTIMATOR_H
-#define EIGEN_CONDITIONESTIMATOR_H
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Vector, typename RealVector, bool IsComplex>
-struct rcond_compute_sign {
-  static inline Vector run(const Vector& v) {
-    const RealVector v_abs = v.cwiseAbs();
-    return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
-            .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
-  }
-};
-
-// Partial specialization to avoid elementwise division for real vectors.
-template <typename Vector>
-struct rcond_compute_sign<Vector, Vector, false> {
-  static inline Vector run(const Vector& v) {
-    return (v.array() < static_cast<typename Vector::RealScalar>(0))
-           .select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
-  }
-};
-
-/**
-  * \returns an estimate of ||inv(matrix)||_1 given a decomposition of
-  * \a matrix that implements .solve() and .adjoint().solve() methods.
-  *
-  * This function implements Algorithms 4.1 and 5.1 from
-  *   http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf
-  * which also forms the basis for the condition number estimators in
-  * LAPACK. Since at most 10 calls to the solve method of dec are
-  * performed, the total cost is O(dims^2), as opposed to O(dims^3)
-  * needed to compute the inverse matrix explicitly.
-  *
-  * The most common usage is in estimating the condition number
-  * ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be
-  * computed directly in O(n^2) operations.
-  *
-  * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and
-  * LLT.
-  *
-  * \sa FullPivLU, PartialPivLU, LDLT, LLT.
-  */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec)
-{
-  typedef typename Decomposition::MatrixType MatrixType;
-  typedef typename Decomposition::Scalar Scalar;
-  typedef typename Decomposition::RealScalar RealScalar;
-  typedef typename internal::plain_col_type<MatrixType>::type Vector;
-  typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
-  const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
-
-  eigen_assert(dec.rows() == dec.cols());
-  const Index n = dec.rows();
-  if (n == 0)
-    return 0;
-
-  // Disable Index to float conversion warning
-#ifdef __INTEL_COMPILER
-  #pragma warning push
-  #pragma warning ( disable : 2259 )
-#endif
-  Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
-#ifdef __INTEL_COMPILER
-  #pragma warning pop
-#endif
-
-  // lower_bound is a lower bound on
-  //   ||inv(matrix)||_1  = sup_v ||inv(matrix) v||_1 / ||v||_1
-  // and is the objective maximized by the ("super-") gradient ascent
-  // algorithm below.
-  RealScalar lower_bound = v.template lpNorm<1>();
-  if (n == 1)
-    return lower_bound;
-
-  // Gradient ascent algorithm follows: We know that the optimum is achieved at
-  // one of the simplices v = e_i, so in each iteration we follow a
-  // super-gradient to move towards the optimal one.
-  RealScalar old_lower_bound = lower_bound;
-  Vector sign_vector(n);
-  Vector old_sign_vector;
-  Index v_max_abs_index = -1;
-  Index old_v_max_abs_index = v_max_abs_index;
-  for (int k = 0; k < 4; ++k)
-  {
-    sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
-    if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )|
-    v = dec.adjoint().solve(sign_vector);
-    v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
-    if (v_max_abs_index == old_v_max_abs_index) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // Move to the new simplex e_j, where j = v_max_abs_index.
-    v = dec.solve(Vector::Unit(n, v_max_abs_index));  // v = inv(matrix) * e_j.
-    lower_bound = v.template lpNorm<1>();
-    if (lower_bound <= old_lower_bound) {
-      // Break if the gradient step did not increase the lower_bound.
-      break;
-    }
-    if (!is_complex) {
-      old_sign_vector = sign_vector;
-    }
-    old_v_max_abs_index = v_max_abs_index;
-    old_lower_bound = lower_bound;
-  }
-  // The following calculates an independent estimate of ||matrix||_1 by
-  // multiplying matrix by a vector with entries of slowly increasing
-  // magnitude and alternating sign:
-  //   v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1.
-  // This improvement to Hager's algorithm above is due to Higham. It was
-  // added to make the algorithm more robust in certain corner cases where
-  // large elements in the matrix might otherwise escape detection due to
-  // exact cancellation (especially when op and op_adjoint correspond to a
-  // sequence of backsubstitutions and permutations), which could cause
-  // Hager's algorithm to vastly underestimate ||matrix||_1.
-  Scalar alternating_sign(RealScalar(1));
-  for (Index i = 0; i < n; ++i) {
-    // The static_cast is needed when Scalar is a complex and RealScalar implements expression templates
-    v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
-    alternating_sign = -alternating_sign;
-  }
-  v = dec.solve(v);
-  const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n));
-  return numext::maxi(lower_bound, alternate_lower_bound);
-}
-
-/** \brief Reciprocal condition number estimator.
-  *
-  * Computing a decomposition of a dense matrix takes O(n^3) operations, while
-  * this method estimates the condition number quickly and reliably in O(n^2)
-  * operations.
-  *
-  * \returns an estimate of the reciprocal condition number
-  * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
-  * its decomposition. Supports the following decompositions: FullPivLU,
-  * PartialPivLU, LDLT, and LLT.
-  *
-  * \sa FullPivLU, PartialPivLU, LDLT, LLT.
-  */
-template <typename Decomposition>
-typename Decomposition::RealScalar
-rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm, const Decomposition& dec)
-{
-  typedef typename Decomposition::RealScalar RealScalar;
-  eigen_assert(dec.rows() == dec.cols());
-  if (dec.rows() == 0)              return NumTraits<RealScalar>::infinity();
-  if (matrix_norm == RealScalar(0)) return RealScalar(0);
-  if (dec.rows() == 1)              return RealScalar(1);
-  const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
-  return (inverse_matrix_norm == RealScalar(0) ? RealScalar(0)
-                                               : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
-}
-
-}  // namespace internal
-
-}  // namespace Eigen
-
-#endif

deps_src/eigen/Eigen/src/Core/CoreIterators.h

@@ -1,127 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_COREITERATORS_H
-#define EIGEN_COREITERATORS_H
-
-namespace Eigen { 
-
-/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
- */
-
-namespace internal {
-
-template<typename XprType, typename EvaluatorKind>
-class inner_iterator_selector;
-
-}
-
-/** \class InnerIterator
-  * \brief An InnerIterator allows to loop over the element of any matrix expression.
-  * 
-  * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is constructed.
-  * 
-  * TODO: add a usage example
-  */
-template<typename XprType>
-class InnerIterator
-{
-protected:
-  typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
-  typedef internal::evaluator<XprType> EvaluatorType;
-  typedef typename internal::traits<XprType>::Scalar Scalar;
-public:
-  /** Construct an iterator over the \a outerId -th row or column of \a xpr */
-  InnerIterator(const XprType &xpr, const Index &outerId)
-    : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize())
-  {}
-  
-  /// \returns the value of the current coefficient.
-  EIGEN_STRONG_INLINE Scalar value() const          { return m_iter.value(); }
-  /** Increment the iterator \c *this to the next non-zero coefficient.
-    * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
-    */
-  EIGEN_STRONG_INLINE InnerIterator& operator++()   { m_iter.operator++(); return *this; }
-  /// \returns the column or row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index index() const           { return m_iter.index(); }
-  /// \returns the row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index row() const             { return m_iter.row(); }
-  /// \returns the column index of the current coefficient.
-  EIGEN_STRONG_INLINE Index col() const             { return m_iter.col(); }
-  /// \returns \c true if the iterator \c *this still references a valid coefficient.
-  EIGEN_STRONG_INLINE operator bool() const         { return m_iter; }
-  
-protected:
-  EvaluatorType m_eval;
-  IteratorType m_iter;
-private:
-  // If you get here, then you're not using the right InnerIterator type, e.g.:
-  //   SparseMatrix<double,RowMajor> A;
-  //   SparseMatrix<double>::InnerIterator it(A,0);
-  template<typename T> InnerIterator(const EigenBase<T>&,Index outer);
-};
-
-namespace internal {
-
-// Generic inner iterator implementation for dense objects
-template<typename XprType>
-class inner_iterator_selector<XprType, IndexBased>
-{
-protected:
-  typedef evaluator<XprType> EvaluatorType;
-  typedef typename traits<XprType>::Scalar Scalar;
-  enum { IsRowMajor = (XprType::Flags&RowMajorBit)==RowMajorBit };
-  
-public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
-    : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize)
-  {}
-
-  EIGEN_STRONG_INLINE Scalar value() const
-  {
-    return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner)
-                        : m_eval.coeff(m_inner, m_outer);
-  }
-
-  EIGEN_STRONG_INLINE inner_iterator_selector& operator++() { m_inner++; return *this; }
-
-  EIGEN_STRONG_INLINE Index index() const { return m_inner; }
-  inline Index row() const { return IsRowMajor ? m_outer : index(); }
-  inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-  EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
-
-protected:
-  const EvaluatorType& m_eval;
-  Index m_inner;
-  const Index m_outer;
-  const Index m_end;
-};
-
-// For iterator-based evaluator, inner-iterator is already implemented as
-// evaluator<>::InnerIterator
-template<typename XprType>
-class inner_iterator_selector<XprType, IteratorBased>
- : public evaluator<XprType>::InnerIterator
-{
-protected:
-  typedef typename evaluator<XprType>::InnerIterator Base;
-  typedef evaluator<XprType> EvaluatorType;
-  
-public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &/*innerSize*/)
-    : Base(eval, outerId)
-  {}  
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_COREITERATORS_H

deps_src/eigen/Eigen/src/Core/CwiseBinaryOp.h

@@ -1,184 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_BINARY_OP_H
-#define EIGEN_CWISE_BINARY_OP_H
-
-namespace Eigen {
-
-namespace internal {
-template<typename BinaryOp, typename Lhs, typename Rhs>
-struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
-{
-  // we must not inherit from traits<Lhs> since it has
-  // the potential to cause problems with MSVC
-  typedef typename remove_all<Lhs>::type Ancestor;
-  typedef typename traits<Ancestor>::XprKind XprKind;
-  enum {
-    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
-    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
-  };
-
-  // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor),
-  // we still want to handle the case when the result type is different.
-  typedef typename result_of<
-                     BinaryOp(
-                       const typename Lhs::Scalar&,
-                       const typename Rhs::Scalar&
-                     )
-                   >::type Scalar;
-  typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind,
-                                              typename traits<Rhs>::StorageKind,
-                                              BinaryOp>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<Lhs>::StorageIndex,
-                                      typename traits<Rhs>::StorageIndex>::type StorageIndex;
-  typedef typename Lhs::Nested LhsNested;
-  typedef typename Rhs::Nested RhsNested;
-  typedef typename remove_reference<LhsNested>::type _LhsNested;
-  typedef typename remove_reference<RhsNested>::type _RhsNested;
-  enum {
-    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind,typename traits<Rhs>::StorageKind,_LhsNested::Flags & RowMajorBit,_RhsNested::Flags & RowMajorBit>::value
-  };
-};
-} // end namespace internal
-
-template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
-class CwiseBinaryOpImpl;
-
-/** \class CwiseBinaryOp
-  * \ingroup Core_Module
-  *
-  * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
-  *
-  * \tparam BinaryOp template functor implementing the operator
-  * \tparam LhsType the type of the left-hand side
-  * \tparam RhsType the type of the right-hand side
-  *
-  * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
-  * It is the return type of binary operators, by which we mean only those binary operators where
-  * both the left-hand side and the right-hand side are Eigen expressions.
-  * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
-  *
-  * Most of the time, this is the only way that it is used, so you typically don't have to name
-  * CwiseBinaryOp types explicitly.
-  *
-  * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
-  */
-template<typename BinaryOp, typename LhsType, typename RhsType>
-class CwiseBinaryOp : 
-  public CwiseBinaryOpImpl<
-          BinaryOp, LhsType, RhsType,
-          typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
-                                                        typename internal::traits<RhsType>::StorageKind,
-                                                        BinaryOp>::ret>,
-  internal::no_assignment_operator
-{
-  public:
-    
-    typedef typename internal::remove_all<BinaryOp>::type Functor;
-    typedef typename internal::remove_all<LhsType>::type Lhs;
-    typedef typename internal::remove_all<RhsType>::type Rhs;
-
-    typedef typename CwiseBinaryOpImpl<
-        BinaryOp, LhsType, RhsType,
-        typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
-                                                      typename internal::traits<Rhs>::StorageKind,
-                                                      BinaryOp>::ret>::Base Base;
-    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
-
-    typedef typename internal::ref_selector<LhsType>::type LhsNested;
-    typedef typename internal::ref_selector<RhsType>::type RhsNested;
-    typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
-    typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
-      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
-    {
-      EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
-      // require the sizes to match
-      EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
-      eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index rows() const {
-      // return the fixed size type if available to enable compile time optimizations
-      if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
-        return m_rhs.rows();
-      else
-        return m_lhs.rows();
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index cols() const {
-      // return the fixed size type if available to enable compile time optimizations
-      if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
-        return m_rhs.cols();
-      else
-        return m_lhs.cols();
-    }
-
-    /** \returns the left hand side nested expression */
-    EIGEN_DEVICE_FUNC
-    const _LhsNested& lhs() const { return m_lhs; }
-    /** \returns the right hand side nested expression */
-    EIGEN_DEVICE_FUNC
-    const _RhsNested& rhs() const { return m_rhs; }
-    /** \returns the functor representing the binary operation */
-    EIGEN_DEVICE_FUNC
-    const BinaryOp& functor() const { return m_functor; }
-
-  protected:
-    LhsNested m_lhs;
-    RhsNested m_rhs;
-    const BinaryOp m_functor;
-};
-
-// Generic API dispatcher
-template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
-class CwiseBinaryOpImpl
-  : public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
-{
-public:
-  typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
-};
-
-/** replaces \c *this by \c *this - \a other.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
-MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
-{
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-/** replaces \c *this by \c *this + \a other.
-  *
-  * \returns a reference to \c *this
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived &
-MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
-{
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_CWISE_BINARY_OP_H
-

deps_src/eigen/Eigen/src/Core/CwiseNullaryOp.h

@@ -1,866 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_NULLARY_OP_H
-#define EIGEN_CWISE_NULLARY_OP_H
-
-namespace Eigen {
-
-namespace internal {
-template<typename NullaryOp, typename PlainObjectType>
-struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
-{
-  enum {
-    Flags = traits<PlainObjectType>::Flags & RowMajorBit
-  };
-};
-
-} // namespace internal
-
-/** \class CwiseNullaryOp
-  * \ingroup Core_Module
-  *
-  * \brief Generic expression of a matrix where all coefficients are defined by a functor
-  *
-  * \tparam NullaryOp template functor implementing the operator
-  * \tparam PlainObjectType the underlying plain matrix/array type
-  *
-  * This class represents an expression of a generic nullary operator.
-  * It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() methods,
-  * and most of the time this is the only way it is used.
-  *
-  * However, if you want to write a function returning such an expression, you
-  * will need to use this class.
-  *
-  * The functor NullaryOp must expose one of the following method:
-    <table class="manual">
-    <tr            ><td>\c operator()() </td><td>if the procedural generation does not depend on the coefficient entries (e.g., random numbers)</td></tr>
-    <tr class="alt"><td>\c operator()(Index i)</td><td>if the procedural generation makes sense for vectors only and that it depends on the coefficient index \c i (e.g., linspace) </td></tr>
-    <tr            ><td>\c operator()(Index i,Index j)</td><td>if the procedural generation depends on the matrix coordinates \c i, \c j (e.g., to generate a checkerboard with 0 and 1)</td></tr>
-    </table>
-  * It is also possible to expose the last two operators if the generation makes sense for matrices but can be optimized for vectors.
-  *
-  * See DenseBase::NullaryExpr(Index,const CustomNullaryOp&) for an example binding
-  * C++11 random number generators.
-  *
-  * A nullary expression can also be used to implement custom sophisticated matrix manipulations
-  * that cannot be covered by the existing set of natively supported matrix manipulations.
-  * See this \ref TopicCustomizing_NullaryExpr "page" for some examples and additional explanations
-  * on the behavior of CwiseNullaryOp.
-  *
-  * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr
-  */
-template<typename NullaryOp, typename PlainObjectType>
-class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
-{
-  public:
-
-    typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
-
-    EIGEN_DEVICE_FUNC
-    CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
-      : m_rows(rows), m_cols(cols), m_functor(func)
-    {
-      eigen_assert(rows >= 0
-            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-            &&  cols >= 0
-            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
-
-    /** \returns the functor representing the nullary operation */
-    EIGEN_DEVICE_FUNC
-    const NullaryOp& functor() const { return m_functor; }
-
-  protected:
-    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
-    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
-    const NullaryOp m_functor;
-};
-
-
-/** \returns an expression of a matrix defined by a custom functor \a func
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
-  * instead.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-template<typename CustomNullaryOp>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
-DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
-{
-  return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func);
-}
-
-/** \returns an expression of a matrix defined by a custom functor \a func
-  *
-  * The parameter \a size is the size of the returned vector.
-  * Must be compatible with this MatrixBase type.
-  *
-  * \only_for_vectors
-  *
-  * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
-  * it is redundant to pass \a size as argument, so Zero() should be used
-  * instead.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * Here is an example with C++11 random generators: \include random_cpp11.cpp
-  * Output: \verbinclude random_cpp11.out
-  * 
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-template<typename CustomNullaryOp>
-EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
-DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, PlainObject>(1, size, func);
-  else return CwiseNullaryOp<CustomNullaryOp, PlainObject>(size, 1, func);
-}
-
-/** \returns an expression of a matrix defined by a custom functor \a func
-  *
-  * This variant is only for fixed-size DenseBase types. For dynamic-size types, you
-  * need to use the variants taking size arguments.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-template<typename CustomNullaryOp>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
-DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
-{
-  return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func);
-}
-
-/** \returns an expression of a constant matrix of value \a value
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this DenseBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
-  * instead.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
-{
-  return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_constant_op<Scalar>(value));
-}
-
-/** \returns an expression of a constant matrix of value \a value
-  *
-  * The parameter \a size is the size of the returned vector.
-  * Must be compatible with this DenseBase type.
-  *
-  * \only_for_vectors
-  *
-  * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
-  * it is redundant to pass \a size as argument, so Zero() should be used
-  * instead.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(Index size, const Scalar& value)
-{
-  return DenseBase<Derived>::NullaryExpr(size, internal::scalar_constant_op<Scalar>(value));
-}
-
-/** \returns an expression of a constant matrix of value \a value
-  *
-  * This variant is only for fixed-size DenseBase types. For dynamic-size types, you
-  * need to use the variants taking size arguments.
-  *
-  * The template parameter \a CustomNullaryOp is the type of the functor.
-  *
-  * \sa class CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(const Scalar& value)
-{
-  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return DenseBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_constant_op<Scalar>(value));
-}
-
-/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(Index,const Scalar&,const Scalar&)
-  *
-  * \sa LinSpaced(Index,Scalar,Scalar), setLinSpaced(Index,const Scalar&,const Scalar&)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar>(low,high,size));
-}
-
-/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(const Scalar&,const Scalar&)
-  *
-  * \sa LinSpaced(Scalar,Scalar)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar>(low,high,Derived::SizeAtCompileTime));
-}
-
-/**
-  * \brief Sets a linearly spaced vector.
-  *
-  * The function generates 'size' equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include DenseBase_LinSpaced.cpp
-  * Output: \verbinclude DenseBase_LinSpaced.out
-  *
-  * For integer scalar types, an even spacing is possible if and only if the length of the range,
-  * i.e., \c high-low is a scalar multiple of \c size-1, or if \c size is a scalar multiple of the
-  * number of values \c high-low+1 (meaning each value can be repeated the same number of time).
-  * If one of these two considions is not satisfied, then \c high is lowered to the largest value
-  * satisfying one of this constraint.
-  * Here are some examples:
-  *
-  * Example: \include DenseBase_LinSpacedInt.cpp
-  * Output: \verbinclude DenseBase_LinSpacedInt.out
-  *
-  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,PacketScalar>(low,high,size));
-}
-
-/**
-  * \copydoc DenseBase::LinSpaced(Index, const Scalar&, const Scalar&)
-  * Special version for fixed size types which does not require the size parameter.
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,PacketScalar>(low,high,Derived::SizeAtCompileTime));
-}
-
-/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
-template<typename Derived>
-EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApproxToConstant
-(const Scalar& val, const RealScalar& prec) const
-{
-  typename internal::nested_eval<Derived,1>::type self(derived());
-  for(Index j = 0; j < cols(); ++j)
-    for(Index i = 0; i < rows(); ++i)
-      if(!internal::isApprox(self.coeff(i, j), val, prec))
-        return false;
-  return true;
-}
-
-/** This is just an alias for isApproxToConstant().
-  *
-  * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
-template<typename Derived>
-EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isConstant
-(const Scalar& val, const RealScalar& prec) const
-{
-  return isApproxToConstant(val, prec);
-}
-
-/** Alias for setConstant(): sets all coefficients in this expression to \a val.
-  *
-  * \sa setConstant(), Constant(), class CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
-{
-  setConstant(val);
-}
-
-/** Sets all coefficients in this expression to value \a val.
-  *
-  * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
-{
-  return derived() = Constant(rows(), cols(), val);
-}
-
-/** Resizes to the given \a size, and sets all coefficients in this expression to the given value \a val.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include Matrix_setConstant_int.cpp
-  * Output: \verbinclude Matrix_setConstant_int.out
-  *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
-{
-  resize(size);
-  return setConstant(val);
-}
-
-/** Resizes to the given size, and sets all coefficients in this expression to the given value \a val.
-  *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
-  * \param val the value to which all coefficients are set
-  *
-  * Example: \include Matrix_setConstant_int_int.cpp
-  * Output: \verbinclude Matrix_setConstant_int_int.out
-  *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& val)
-{
-  resize(rows, cols);
-  return setConstant(val);
-}
-
-/**
-  * \brief Sets a linearly spaced vector.
-  *
-  * The function generates 'size' equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include DenseBase_setLinSpaced.cpp
-  * Output: \verbinclude DenseBase_setLinSpaced.out
-  *
-  * For integer scalar types, do not miss the explanations on the definition
-  * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
-  *
-  * \sa LinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,PacketScalar>(low,high,newSize));
-}
-
-/**
-  * \brief Sets a linearly spaced vector.
-  *
-  * The function fills \c *this with equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
-  * \only_for_vectors
-  *
-  * For integer scalar types, do not miss the explanations on the definition
-  * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
-  *
-  * \sa LinSpaced(Index,const Scalar&,const Scalar&), setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return setLinSpaced(size(), low, high);
-}
-
-// zero:
-
-/** \returns an expression of a zero matrix.
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_zero_int_int.cpp
-  * Output: \verbinclude MatrixBase_zero_int_int.out
-  *
-  * \sa Zero(), Zero(Index)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(Index rows, Index cols)
-{
-  return Constant(rows, cols, Scalar(0));
-}
-
-/** \returns an expression of a zero vector.
-  *
-  * The parameter \a size is the size of the returned vector.
-  * Must be compatible with this MatrixBase type.
-  *
-  * \only_for_vectors
-  *
-  * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
-  * it is redundant to pass \a size as argument, so Zero() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_zero_int.cpp
-  * Output: \verbinclude MatrixBase_zero_int.out
-  *
-  * \sa Zero(), Zero(Index,Index)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(Index size)
-{
-  return Constant(size, Scalar(0));
-}
-
-/** \returns an expression of a fixed-size zero matrix or vector.
-  *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
-  * need to use the variants taking size arguments.
-  *
-  * Example: \include MatrixBase_zero.cpp
-  * Output: \verbinclude MatrixBase_zero.out
-  *
-  * \sa Zero(Index), Zero(Index,Index)
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero()
-{
-  return Constant(Scalar(0));
-}
-
-/** \returns true if *this is approximately equal to the zero matrix,
-  *          within the precision given by \a prec.
-  *
-  * Example: \include MatrixBase_isZero.cpp
-  * Output: \verbinclude MatrixBase_isZero.out
-  *
-  * \sa class CwiseNullaryOp, Zero()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isZero(const RealScalar& prec) const
-{
-  typename internal::nested_eval<Derived,1>::type self(derived());
-  for(Index j = 0; j < cols(); ++j)
-    for(Index i = 0; i < rows(); ++i)
-      if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<Scalar>(1), prec))
-        return false;
-  return true;
-}
-
-/** Sets all coefficients in this expression to zero.
-  *
-  * Example: \include MatrixBase_setZero.cpp
-  * Output: \verbinclude MatrixBase_setZero.out
-  *
-  * \sa class CwiseNullaryOp, Zero()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
-{
-  return setConstant(Scalar(0));
-}
-
-/** Resizes to the given \a size, and sets all coefficients in this expression to zero.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include Matrix_setZero_int.cpp
-  * Output: \verbinclude Matrix_setZero_int.out
-  *
-  * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index newSize)
-{
-  resize(newSize);
-  return setConstant(Scalar(0));
-}
-
-/** Resizes to the given size, and sets all coefficients in this expression to zero.
-  *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
-  *
-  * Example: \include Matrix_setZero_int_int.cpp
-  * Output: \verbinclude Matrix_setZero_int_int.out
-  *
-  * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index rows, Index cols)
-{
-  resize(rows, cols);
-  return setConstant(Scalar(0));
-}
-
-// ones:
-
-/** \returns an expression of a matrix where all coefficients equal one.
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_ones_int_int.cpp
-  * Output: \verbinclude MatrixBase_ones_int_int.out
-  *
-  * \sa Ones(), Ones(Index), isOnes(), class Ones
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index rows, Index cols)
-{
-  return Constant(rows, cols, Scalar(1));
-}
-
-/** \returns an expression of a vector where all coefficients equal one.
-  *
-  * The parameter \a newSize is the size of the returned vector.
-  * Must be compatible with this MatrixBase type.
-  *
-  * \only_for_vectors
-  *
-  * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
-  * it is redundant to pass \a size as argument, so Ones() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_ones_int.cpp
-  * Output: \verbinclude MatrixBase_ones_int.out
-  *
-  * \sa Ones(), Ones(Index,Index), isOnes(), class Ones
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index newSize)
-{
-  return Constant(newSize, Scalar(1));
-}
-
-/** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
-  *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
-  * need to use the variants taking size arguments.
-  *
-  * Example: \include MatrixBase_ones.cpp
-  * Output: \verbinclude MatrixBase_ones.out
-  *
-  * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones()
-{
-  return Constant(Scalar(1));
-}
-
-/** \returns true if *this is approximately equal to the matrix where all coefficients
-  *          are equal to 1, within the precision given by \a prec.
-  *
-  * Example: \include MatrixBase_isOnes.cpp
-  * Output: \verbinclude MatrixBase_isOnes.out
-  *
-  * \sa class CwiseNullaryOp, Ones()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isOnes
-(const RealScalar& prec) const
-{
-  return isApproxToConstant(Scalar(1), prec);
-}
-
-/** Sets all coefficients in this expression to one.
-  *
-  * Example: \include MatrixBase_setOnes.cpp
-  * Output: \verbinclude MatrixBase_setOnes.out
-  *
-  * \sa class CwiseNullaryOp, Ones()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
-{
-  return setConstant(Scalar(1));
-}
-
-/** Resizes to the given \a newSize, and sets all coefficients in this expression to one.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include Matrix_setOnes_int.cpp
-  * Output: \verbinclude Matrix_setOnes_int.out
-  *
-  * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index newSize)
-{
-  resize(newSize);
-  return setConstant(Scalar(1));
-}
-
-/** Resizes to the given size, and sets all coefficients in this expression to one.
-  *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
-  *
-  * Example: \include Matrix_setOnes_int_int.cpp
-  * Output: \verbinclude Matrix_setOnes_int_int.out
-  *
-  * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
-{
-  resize(rows, cols);
-  return setConstant(Scalar(1));
-}
-
-// Identity:
-
-/** \returns an expression of the identity matrix (not necessarily square).
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_identity_int_int.cpp
-  * Output: \verbinclude MatrixBase_identity_int_int.out
-  *
-  * \sa Identity(), setIdentity(), isIdentity()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(Index rows, Index cols)
-{
-  return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
-}
-
-/** \returns an expression of the identity matrix (not necessarily square).
-  *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
-  * need to use the variant taking size arguments.
-  *
-  * Example: \include MatrixBase_identity.cpp
-  * Output: \verbinclude MatrixBase_identity.out
-  *
-  * \sa Identity(Index,Index), setIdentity(), isIdentity()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity()
-{
-  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return MatrixBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_identity_op<Scalar>());
-}
-
-/** \returns true if *this is approximately equal to the identity matrix
-  *          (not necessarily square),
-  *          within the precision given by \a prec.
-  *
-  * Example: \include MatrixBase_isIdentity.cpp
-  * Output: \verbinclude MatrixBase_isIdentity.out
-  *
-  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity()
-  */
-template<typename Derived>
-bool MatrixBase<Derived>::isIdentity
-(const RealScalar& prec) const
-{
-  typename internal::nested_eval<Derived,1>::type self(derived());
-  for(Index j = 0; j < cols(); ++j)
-  {
-    for(Index i = 0; i < rows(); ++i)
-    {
-      if(i == j)
-      {
-        if(!internal::isApprox(self.coeff(i, j), static_cast<Scalar>(1), prec))
-          return false;
-      }
-      else
-      {
-        if(!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<RealScalar>(1), prec))
-          return false;
-      }
-    }
-  }
-  return true;
-}
-
-namespace internal {
-
-template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)>
-struct setIdentity_impl
-{
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE Derived& run(Derived& m)
-  {
-    return m = Derived::Identity(m.rows(), m.cols());
-  }
-};
-
-template<typename Derived>
-struct setIdentity_impl<Derived, true>
-{
-  EIGEN_DEVICE_FUNC
-  static EIGEN_STRONG_INLINE Derived& run(Derived& m)
-  {
-    m.setZero();
-    const Index size = numext::mini(m.rows(), m.cols());
-    for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
-    return m;
-  }
-};
-
-} // end namespace internal
-
-/** Writes the identity expression (not necessarily square) into *this.
-  *
-  * Example: \include MatrixBase_setIdentity.cpp
-  * Output: \verbinclude MatrixBase_setIdentity.out
-  *
-  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
-{
-  return internal::setIdentity_impl<Derived>::run(derived());
-}
-
-/** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
-  *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
-  *
-  * Example: \include Matrix_setIdentity_int_int.cpp
-  * Output: \verbinclude Matrix_setIdentity_int_int.out
-  *
-  * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
-{
-  derived().resize(rows, cols);
-  return setIdentity();
-}
-
-/** \returns an expression of the i-th unit (basis) vector.
-  *
-  * \only_for_vectors
-  *
-  * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
-}
-
-/** \returns an expression of the i-th unit (basis) vector.
-  *
-  * \only_for_vectors
-  *
-  * This variant is for fixed-size vector only.
-  *
-  * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return BasisReturnType(SquareMatrixType::Identity(),i);
-}
-
-/** \returns an expression of the X axis unit vector (1{,0}^*)
-  *
-  * \only_for_vectors
-  *
-  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
-{ return Derived::Unit(0); }
-
-/** \returns an expression of the Y axis unit vector (0,1{,0}^*)
-  *
-  * \only_for_vectors
-  *
-  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
-{ return Derived::Unit(1); }
-
-/** \returns an expression of the Z axis unit vector (0,0,1{,0}^*)
-  *
-  * \only_for_vectors
-  *
-  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
-{ return Derived::Unit(2); }
-
-/** \returns an expression of the W axis unit vector (0,0,0,1)
-  *
-  * \only_for_vectors
-  *
-  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
-  */
-template<typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
-{ return Derived::Unit(3); }
-
-} // end namespace Eigen
-
-#endif // EIGEN_CWISE_NULLARY_OP_H

deps_src/eigen/Eigen/src/Core/CwiseTernaryOp.h

@@ -1,197 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_TERNARY_OP_H
-#define EIGEN_CWISE_TERNARY_OP_H
-
-namespace Eigen {
-
-namespace internal {
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
-struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> > {
-  // we must not inherit from traits<Arg1> since it has
-  // the potential to cause problems with MSVC
-  typedef typename remove_all<Arg1>::type Ancestor;
-  typedef typename traits<Ancestor>::XprKind XprKind;
-  enum {
-    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
-    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
-  };
-
-  // even though we require Arg1, Arg2, and Arg3 to have the same scalar type
-  // (see CwiseTernaryOp constructor),
-  // we still want to handle the case when the result type is different.
-  typedef typename result_of<TernaryOp(
-      const typename Arg1::Scalar&, const typename Arg2::Scalar&,
-      const typename Arg3::Scalar&)>::type Scalar;
-
-  typedef typename internal::traits<Arg1>::StorageKind StorageKind;
-  typedef typename internal::traits<Arg1>::StorageIndex StorageIndex;
-
-  typedef typename Arg1::Nested Arg1Nested;
-  typedef typename Arg2::Nested Arg2Nested;
-  typedef typename Arg3::Nested Arg3Nested;
-  typedef typename remove_reference<Arg1Nested>::type _Arg1Nested;
-  typedef typename remove_reference<Arg2Nested>::type _Arg2Nested;
-  typedef typename remove_reference<Arg3Nested>::type _Arg3Nested;
-  enum { Flags = _Arg1Nested::Flags & RowMajorBit };
-};
-}  // end namespace internal
-
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3,
-          typename StorageKind>
-class CwiseTernaryOpImpl;
-
-/** \class CwiseTernaryOp
-  * \ingroup Core_Module
-  *
-  * \brief Generic expression where a coefficient-wise ternary operator is
- * applied to two expressions
-  *
-  * \tparam TernaryOp template functor implementing the operator
-  * \tparam Arg1Type the type of the first argument
-  * \tparam Arg2Type the type of the second argument
-  * \tparam Arg3Type the type of the third argument
-  *
-  * This class represents an expression where a coefficient-wise ternary
- * operator is applied to three expressions.
-  * It is the return type of ternary operators, by which we mean only those
- * ternary operators where
-  * all three arguments are Eigen expressions.
-  * For example, the return type of betainc(matrix1, matrix2, matrix3) is a
- * CwiseTernaryOp.
-  *
-  * Most of the time, this is the only way that it is used, so you typically
- * don't have to name
-  * CwiseTernaryOp types explicitly.
-  *
-  * \sa MatrixBase::ternaryExpr(const MatrixBase<Argument2> &, const
- * MatrixBase<Argument3> &, const CustomTernaryOp &) const, class CwiseBinaryOp,
- * class CwiseUnaryOp, class CwiseNullaryOp
-  */
-template <typename TernaryOp, typename Arg1Type, typename Arg2Type,
-          typename Arg3Type>
-class CwiseTernaryOp : public CwiseTernaryOpImpl<
-                           TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-                           typename internal::traits<Arg1Type>::StorageKind>,
-                       internal::no_assignment_operator
-{
- public:
-  typedef typename internal::remove_all<Arg1Type>::type Arg1;
-  typedef typename internal::remove_all<Arg2Type>::type Arg2;
-  typedef typename internal::remove_all<Arg3Type>::type Arg3;
-
-  typedef typename CwiseTernaryOpImpl<
-      TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-      typename internal::traits<Arg1Type>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp)
-
-  typedef typename internal::ref_selector<Arg1Type>::type Arg1Nested;
-  typedef typename internal::ref_selector<Arg2Type>::type Arg2Nested;
-  typedef typename internal::ref_selector<Arg3Type>::type Arg3Nested;
-  typedef typename internal::remove_reference<Arg1Nested>::type _Arg1Nested;
-  typedef typename internal::remove_reference<Arg2Nested>::type _Arg2Nested;
-  typedef typename internal::remove_reference<Arg3Nested>::type _Arg3Nested;
-
-  EIGEN_DEVICE_FUNC
-  EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2,
-                                     const Arg3& a3,
-                                     const TernaryOp& func = TernaryOp())
-      : m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) {
-    // require the sizes to match
-    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
-    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
-
-    // The index types should match
-    EIGEN_STATIC_ASSERT((internal::is_same<
-                         typename internal::traits<Arg1Type>::StorageKind,
-                         typename internal::traits<Arg2Type>::StorageKind>::value),
-                        STORAGE_KIND_MUST_MATCH)
-    EIGEN_STATIC_ASSERT((internal::is_same<
-                         typename internal::traits<Arg1Type>::StorageKind,
-                         typename internal::traits<Arg3Type>::StorageKind>::value),
-                        STORAGE_KIND_MUST_MATCH)
-
-    eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() &&
-                 a1.rows() == a3.rows() && a1.cols() == a3.cols());
-  }
-
-  EIGEN_DEVICE_FUNC
-  EIGEN_STRONG_INLINE Index rows() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
-                RowsAtCompileTime == Dynamic &&
-        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
-                RowsAtCompileTime == Dynamic)
-      return m_arg3.rows();
-    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
-                     RowsAtCompileTime == Dynamic &&
-             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
-                     RowsAtCompileTime == Dynamic)
-      return m_arg2.rows();
-    else
-      return m_arg1.rows();
-  }
-  EIGEN_DEVICE_FUNC
-  EIGEN_STRONG_INLINE Index cols() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
-                ColsAtCompileTime == Dynamic &&
-        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
-                ColsAtCompileTime == Dynamic)
-      return m_arg3.cols();
-    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
-                     ColsAtCompileTime == Dynamic &&
-             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
-                     ColsAtCompileTime == Dynamic)
-      return m_arg2.cols();
-    else
-      return m_arg1.cols();
-  }
-
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC
-  const _Arg1Nested& arg1() const { return m_arg1; }
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC
-  const _Arg2Nested& arg2() const { return m_arg2; }
-  /** \returns the third argument nested expression */
-  EIGEN_DEVICE_FUNC
-  const _Arg3Nested& arg3() const { return m_arg3; }
-  /** \returns the functor representing the ternary operation */
-  EIGEN_DEVICE_FUNC
-  const TernaryOp& functor() const { return m_functor; }
-
- protected:
-  Arg1Nested m_arg1;
-  Arg2Nested m_arg2;
-  Arg3Nested m_arg3;
-  const TernaryOp m_functor;
-};
-
-// Generic API dispatcher
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3,
-          typename StorageKind>
-class CwiseTernaryOpImpl
-    : public internal::generic_xpr_base<
-          CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >::type {
- public:
-  typedef typename internal::generic_xpr_base<
-      CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> >::type Base;
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_CWISE_TERNARY_OP_H

deps_src/eigen/Eigen/src/Core/CwiseUnaryOp.h

@@ -1,103 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_UNARY_OP_H
-#define EIGEN_CWISE_UNARY_OP_H
-
-namespace Eigen { 
-
-namespace internal {
-template<typename UnaryOp, typename XprType>
-struct traits<CwiseUnaryOp<UnaryOp, XprType> >
- : traits<XprType>
-{
-  typedef typename result_of<
-                     UnaryOp(const typename XprType::Scalar&)
-                   >::type Scalar;
-  typedef typename XprType::Nested XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
-  enum {
-    Flags = _XprTypeNested::Flags & RowMajorBit 
-  };
-};
-}
-
-template<typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl;
-
-/** \class CwiseUnaryOp
-  * \ingroup Core_Module
-  *
-  * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
-  *
-  * \tparam UnaryOp template functor implementing the operator
-  * \tparam XprType the type of the expression to which we are applying the unary operator
-  *
-  * This class represents an expression where a unary operator is applied to an expression.
-  * It is the return type of all operations taking exactly 1 input expression, regardless of the
-  * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
-  * is considered unary, because only the right-hand side is an expression, and its
-  * return type is a specialization of CwiseUnaryOp.
-  *
-  * Most of the time, this is the only way that it is used, so you typically don't have to name
-  * CwiseUnaryOp types explicitly.
-  *
-  * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
-  */
-template<typename UnaryOp, typename XprType>
-class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
-{
-  public:
-
-    typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
-    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
-    typedef typename internal::ref_selector<XprType>::type XprTypeNested;
-    typedef typename internal::remove_all<XprType>::type NestedExpression;
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
-      : m_xpr(xpr), m_functor(func) {}
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Index rows() const { return m_xpr.rows(); }
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Index cols() const { return m_xpr.cols(); }
-
-    /** \returns the functor representing the unary operation */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const UnaryOp& functor() const { return m_functor; }
-
-    /** \returns the nested expression */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const typename internal::remove_all<XprTypeNested>::type&
-    nestedExpression() const { return m_xpr; }
-
-    /** \returns the nested expression */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    typename internal::remove_all<XprTypeNested>::type&
-    nestedExpression() { return m_xpr; }
-
-  protected:
-    XprTypeNested m_xpr;
-    const UnaryOp m_functor;
-};
-
-// Generic API dispatcher
-template<typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl
-  : public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
-{
-public:
-  typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_CWISE_UNARY_OP_H

deps_src/eigen/Eigen/src/Core/CwiseUnaryView.h

@@ -1,128 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_UNARY_VIEW_H
-#define EIGEN_CWISE_UNARY_VIEW_H
-
-namespace Eigen {
-
-namespace internal {
-template<typename ViewOp, typename MatrixType>
-struct traits<CwiseUnaryView<ViewOp, MatrixType> >
- : traits<MatrixType>
-{
-  typedef typename result_of<
-                     ViewOp(const typename traits<MatrixType>::Scalar&)
-                   >::type Scalar;
-  typedef typename MatrixType::Nested MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
-  enum {
-    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags = traits<_MatrixTypeNested>::Flags & (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions
-    MatrixTypeInnerStride =  inner_stride_at_compile_time<MatrixType>::ret,
-    // need to cast the sizeof's from size_t to int explicitly, otherwise:
-    // "error: no integral type can represent all of the enumerator values
-    InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
-                             ? int(Dynamic)
-                             : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
-    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic
-                             ? int(Dynamic)
-                             : outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar))
-  };
-};
-}
-
-template<typename ViewOp, typename MatrixType, typename StorageKind>
-class CwiseUnaryViewImpl;
-
-/** \class CwiseUnaryView
-  * \ingroup Core_Module
-  *
-  * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
-  *
-  * \tparam ViewOp template functor implementing the view
-  * \tparam MatrixType the type of the matrix we are applying the unary operator
-  *
-  * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
-  * It is the return type of real() and imag(), and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
-  */
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
-{
-  public:
-
-    typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
-    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
-    typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
-    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
-
-    explicit inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
-      : m_matrix(mat), m_functor(func) {}
-
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
-
-    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
-
-    /** \returns the functor representing unary operation */
-    const ViewOp& functor() const { return m_functor; }
-
-    /** \returns the nested expression */
-    const typename internal::remove_all<MatrixTypeNested>::type&
-    nestedExpression() const { return m_matrix; }
-
-    /** \returns the nested expression */
-    typename internal::remove_reference<MatrixTypeNested>::type&
-    nestedExpression() { return m_matrix.const_cast_derived(); }
-
-  protected:
-    MatrixTypeNested m_matrix;
-    ViewOp m_functor;
-};
-
-// Generic API dispatcher
-template<typename ViewOp, typename XprType, typename StorageKind>
-class CwiseUnaryViewImpl
-  : public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type
-{
-public:
-  typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type Base;
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
-  : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
-{
-  public:
-
-    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
-    typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
-
-    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
-    
-    EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
-    EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeff(0)); }
-
-    EIGEN_DEVICE_FUNC inline Index innerStride() const
-    {
-      return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
-    }
-
-    EIGEN_DEVICE_FUNC inline Index outerStride() const
-    {
-      return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
-    }
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_CWISE_UNARY_VIEW_H

deps_src/eigen/Eigen/src/Core/DenseBase.h

@@ -1,611 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DENSEBASE_H
-#define EIGEN_DENSEBASE_H
-
-namespace Eigen {
-
-namespace internal {
-  
-// The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
-// This dummy function simply aims at checking that at compile time.
-static inline void check_DenseIndex_is_signed() {
-  EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); 
-}
-
-} // end namespace internal
-  
-/** \class DenseBase
-  * \ingroup Core_Module
-  *
-  * \brief Base class for all dense matrices, vectors, and arrays
-  *
-  * This class is the base that is inherited by all dense objects (matrix, vector, arrays,
-  * and related expression types). The common Eigen API for dense objects is contained in this class.
-  *
-  * \tparam Derived is the derived type, e.g., a matrix type or an expression.
-  *
-  * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
-  *
-  * \sa \blank \ref TopicClassHierarchy
-  */
-template<typename Derived> class DenseBase
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  : public DenseCoeffsBase<Derived>
-#else
-  : public DenseCoeffsBase<Derived,DirectWriteAccessors>
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-{
-  public:
-
-    /** Inner iterator type to iterate over the coefficients of a row or column.
-      * \sa class InnerIterator
-      */
-    typedef Eigen::InnerIterator<Derived> InnerIterator;
-
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-
-    /**
-      * \brief The type used to store indices
-      * \details This typedef is relevant for types that store multiple indices such as
-      *          PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
-      * \sa \blank \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
-     */
-    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
-
-    /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    
-    /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
-      *
-      * It is an alias for the Scalar type */
-    typedef Scalar value_type;
-    
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef DenseCoeffsBase<Derived> Base;
-
-    using Base::derived;
-    using Base::const_cast_derived;
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::rowIndexByOuterInner;
-    using Base::colIndexByOuterInner;
-    using Base::coeff;
-    using Base::coeffByOuterInner;
-    using Base::operator();
-    using Base::operator[];
-    using Base::x;
-    using Base::y;
-    using Base::z;
-    using Base::w;
-    using Base::stride;
-    using Base::innerStride;
-    using Base::outerStride;
-    using Base::rowStride;
-    using Base::colStride;
-    typedef typename Base::CoeffReturnType CoeffReturnType;
-
-    enum {
-
-      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
-        /**< The number of rows at compile-time. This is just a copy of the value provided
-          * by the \a Derived type. If a value is not known at compile-time,
-          * it is set to the \a Dynamic constant.
-          * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */
-
-      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
-        /**< The number of columns at compile-time. This is just a copy of the value provided
-          * by the \a Derived type. If a value is not known at compile-time,
-          * it is set to the \a Dynamic constant.
-          * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
-
-
-      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
-                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
-        /**< This is equal to the number of coefficients, i.e. the number of
-          * rows times the number of columns, or to \a Dynamic if this is not
-          * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
-
-      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
-        /**< This value is equal to the maximum possible number of rows that this expression
-          * might have. If this expression might have an arbitrarily high number of rows,
-          * this value is set to \a Dynamic.
-          *
-          * This value is useful to know when evaluating an expression, in order to determine
-          * whether it is possible to avoid doing a dynamic memory allocation.
-          *
-          * \sa RowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime
-          */
-
-      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
-        /**< This value is equal to the maximum possible number of columns that this expression
-          * might have. If this expression might have an arbitrarily high number of columns,
-          * this value is set to \a Dynamic.
-          *
-          * This value is useful to know when evaluating an expression, in order to determine
-          * whether it is possible to avoid doing a dynamic memory allocation.
-          *
-          * \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime
-          */
-
-      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
-                                                      internal::traits<Derived>::MaxColsAtCompileTime>::ret),
-        /**< This value is equal to the maximum possible number of coefficients that this expression
-          * might have. If this expression might have an arbitrarily high number of coefficients,
-          * this value is set to \a Dynamic.
-          *
-          * This value is useful to know when evaluating an expression, in order to determine
-          * whether it is possible to avoid doing a dynamic memory allocation.
-          *
-          * \sa SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime
-          */
-
-      IsVectorAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime == 1
-                           || internal::traits<Derived>::MaxColsAtCompileTime == 1,
-        /**< This is set to true if either the number of rows or the number of
-          * columns is known at compile-time to be equal to 1. Indeed, in that case,
-          * we are dealing with a column-vector (if there is only one column) or with
-          * a row-vector (if there is only one row). */
-
-      Flags = internal::traits<Derived>::Flags,
-        /**< This stores expression \ref flags flags which may or may not be inherited by new expressions
-          * constructed from this one. See the \ref flags "list of flags".
-          */
-
-      IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
-
-      InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
-                             : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
-
-      InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
-      OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
-    };
-    
-    typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
-
-    enum { IsPlainObjectBase = 0 };
-    
-    /** The plain matrix type corresponding to this expression.
-      * \sa PlainObject */
-    typedef Matrix<typename internal::traits<Derived>::Scalar,
-                internal::traits<Derived>::RowsAtCompileTime,
-                internal::traits<Derived>::ColsAtCompileTime,
-                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
-                internal::traits<Derived>::MaxRowsAtCompileTime,
-                internal::traits<Derived>::MaxColsAtCompileTime
-          > PlainMatrix;
-    
-    /** The plain array type corresponding to this expression.
-      * \sa PlainObject */
-    typedef Array<typename internal::traits<Derived>::Scalar,
-                internal::traits<Derived>::RowsAtCompileTime,
-                internal::traits<Derived>::ColsAtCompileTime,
-                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
-                internal::traits<Derived>::MaxRowsAtCompileTime,
-                internal::traits<Derived>::MaxColsAtCompileTime
-          > PlainArray;
-
-    /** \brief The plain matrix or array type corresponding to this expression.
-      *
-      * This is not necessarily exactly the return type of eval(). In the case of plain matrices,
-      * the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
-      * that the return type of eval() is either PlainObject or const PlainObject&.
-      */
-    typedef typename internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
-                                 PlainMatrix, PlainArray>::type PlainObject;
-
-    /** \returns the number of nonzero coefficients which is in practice the number
-      * of stored coefficients. */
-    EIGEN_DEVICE_FUNC
-    inline Index nonZeros() const { return size(); }
-
-    /** \returns the outer size.
-      *
-      * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
-      * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a
-      * column-major matrix, and the number of rows for a row-major matrix. */
-    EIGEN_DEVICE_FUNC
-    Index outerSize() const
-    {
-      return IsVectorAtCompileTime ? 1
-           : int(IsRowMajor) ? this->rows() : this->cols();
-    }
-
-    /** \returns the inner size.
-      *
-      * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
-      * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a 
-      * column-major matrix, and the number of columns for a row-major matrix. */
-    EIGEN_DEVICE_FUNC
-    Index innerSize() const
-    {
-      return IsVectorAtCompileTime ? this->size()
-           : int(IsRowMajor) ? this->cols() : this->rows();
-    }
-
-    /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
-      * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
-      * nothing else.
-      */
-    EIGEN_DEVICE_FUNC
-    void resize(Index newSize)
-    {
-      EIGEN_ONLY_USED_FOR_DEBUG(newSize);
-      eigen_assert(newSize == this->size()
-                && "DenseBase::resize() does not actually allow to resize.");
-    }
-    /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
-      * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
-      * nothing else.
-      */
-    EIGEN_DEVICE_FUNC
-    void resize(Index rows, Index cols)
-    {
-      EIGEN_ONLY_USED_FOR_DEBUG(rows);
-      EIGEN_ONLY_USED_FOR_DEBUG(cols);
-      eigen_assert(rows == this->rows() && cols == this->cols()
-                && "DenseBase::resize() does not actually allow to resize.");
-    }
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** \internal Represents a matrix with all coefficients equal to one another*/
-    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
-    /** \internal \deprecated Represents a vector with linearly spaced coefficients that allows sequential access only. */
-    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar>,PlainObject> SequentialLinSpacedReturnType;
-    /** \internal Represents a vector with linearly spaced coefficients that allows random access. */
-    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,PacketScalar>,PlainObject> RandomAccessLinSpacedReturnType;
-    /** \internal the return type of MatrixBase::eigenvalues() */
-    typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType;
-
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
-    /** Copies \a other into *this. \returns a reference to *this. */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator=(const DenseBase<OtherDerived>& other);
-
-    /** Special case of the template operator=, in order to prevent the compiler
-      * from generating a default operator= (issue hit with g++ 4.1)
-      */
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator=(const DenseBase& other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    Derived& operator=(const EigenBase<OtherDerived> &other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    Derived& operator+=(const EigenBase<OtherDerived> &other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    Derived& operator-=(const EigenBase<OtherDerived> &other);
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    Derived& operator=(const ReturnByValue<OtherDerived>& func);
-
-    /** \internal
-      * Copies \a other into *this without evaluating other. \returns a reference to *this.
-      * \deprecated */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    Derived& lazyAssign(const DenseBase<OtherDerived>& other);
-
-    EIGEN_DEVICE_FUNC
-    CommaInitializer<Derived> operator<< (const Scalar& s);
-
-    /** \deprecated it now returns \c *this */
-    template<unsigned int Added,unsigned int Removed>
-    EIGEN_DEPRECATED
-    const Derived& flagged() const
-    { return derived(); }
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
-
-    typedef Transpose<Derived> TransposeReturnType;
-    EIGEN_DEVICE_FUNC
-    TransposeReturnType transpose();
-    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
-    EIGEN_DEVICE_FUNC
-    ConstTransposeReturnType transpose() const;
-    EIGEN_DEVICE_FUNC
-    void transposeInPlace();
-
-    EIGEN_DEVICE_FUNC static const ConstantReturnType
-    Constant(Index rows, Index cols, const Scalar& value);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType
-    Constant(Index size, const Scalar& value);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType
-    Constant(const Scalar& value);
-
-    EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
-    LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high);
-    EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
-    LinSpaced(Index size, const Scalar& low, const Scalar& high);
-    EIGEN_DEVICE_FUNC static const SequentialLinSpacedReturnType
-    LinSpaced(Sequential_t, const Scalar& low, const Scalar& high);
-    EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType
-    LinSpaced(const Scalar& low, const Scalar& high);
-
-    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
-    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
-    NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
-    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
-    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
-    NullaryExpr(Index size, const CustomNullaryOp& func);
-    template<typename CustomNullaryOp> EIGEN_DEVICE_FUNC
-    static const CwiseNullaryOp<CustomNullaryOp, PlainObject>
-    NullaryExpr(const CustomNullaryOp& func);
-
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index rows, Index cols);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero(Index size);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Zero();
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size);
-    EIGEN_DEVICE_FUNC static const ConstantReturnType Ones();
-
-    EIGEN_DEVICE_FUNC void fill(const Scalar& value);
-    EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value);
-    EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
-    EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high);
-    EIGEN_DEVICE_FUNC Derived& setZero();
-    EIGEN_DEVICE_FUNC Derived& setOnes();
-    EIGEN_DEVICE_FUNC Derived& setRandom();
-
-    template<typename OtherDerived> EIGEN_DEVICE_FUNC
-    bool isApprox(const DenseBase<OtherDerived>& other,
-                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    EIGEN_DEVICE_FUNC 
-    bool isMuchSmallerThan(const RealScalar& other,
-                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    template<typename OtherDerived> EIGEN_DEVICE_FUNC
-    bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
-                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-
-    EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-    
-    inline bool hasNaN() const;
-    inline bool allFinite() const;
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator*=(const Scalar& other);
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Derived& operator/=(const Scalar& other);
-
-    typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
-    /** \returns the matrix or vector obtained by evaluating this expression.
-      *
-      * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
-      * a const reference, in order to avoid a useless copy.
-      * 
-      * \warning Be carefull with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page \endlink.
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE EvalReturnType eval() const
-    {
-      // Even though MSVC does not honor strong inlining when the return type
-      // is a dynamic matrix, we desperately need strong inlining for fixed
-      // size types on MSVC.
-      return typename internal::eval<Derived>::type(derived());
-    }
-    
-    /** swaps *this with the expression \a other.
-      *
-      */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    void swap(const DenseBase<OtherDerived>& other)
-    {
-      EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase,THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
-      eigen_assert(rows()==other.rows() && cols()==other.cols());
-      call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
-    }
-
-    /** swaps *this with the matrix or array \a other.
-      *
-      */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    void swap(PlainObjectBase<OtherDerived>& other)
-    {
-      eigen_assert(rows()==other.rows() && cols()==other.cols());
-      call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
-    }
-
-    EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
-    EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
-    EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
-    template<bool Enable> EIGEN_DEVICE_FUNC
-    inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
-    template<bool Enable> EIGEN_DEVICE_FUNC
-    inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
-
-    EIGEN_DEVICE_FUNC Scalar sum() const;
-    EIGEN_DEVICE_FUNC Scalar mean() const;
-    EIGEN_DEVICE_FUNC Scalar trace() const;
-
-    EIGEN_DEVICE_FUNC Scalar prod() const;
-
-    EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff() const;
-    EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() const;
-
-    template<typename IndexType> EIGEN_DEVICE_FUNC
-    typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
-    template<typename IndexType> EIGEN_DEVICE_FUNC
-    typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
-    template<typename IndexType> EIGEN_DEVICE_FUNC
-    typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
-    template<typename IndexType> EIGEN_DEVICE_FUNC
-    typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
-
-    template<typename BinaryOp>
-    EIGEN_DEVICE_FUNC
-    Scalar redux(const BinaryOp& func) const;
-
-    template<typename Visitor>
-    EIGEN_DEVICE_FUNC
-    void visit(Visitor& func) const;
-
-    /** \returns a WithFormat proxy object allowing to print a matrix the with given
-      * format \a fmt.
-      *
-      * See class IOFormat for some examples.
-      *
-      * \sa class IOFormat, class WithFormat
-      */
-    inline const WithFormat<Derived> format(const IOFormat& fmt) const
-    {
-      return WithFormat<Derived>(derived(), fmt);
-    }
-
-    /** \returns the unique coefficient of a 1x1 expression */
-    EIGEN_DEVICE_FUNC
-    CoeffReturnType value() const
-    {
-      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
-      eigen_assert(this->rows() == 1 && this->cols() == 1);
-      return derived().coeff(0,0);
-    }
-
-    EIGEN_DEVICE_FUNC bool all() const;
-    EIGEN_DEVICE_FUNC bool any() const;
-    EIGEN_DEVICE_FUNC Index count() const;
-
-    typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
-    typedef const VectorwiseOp<const Derived, Horizontal> ConstRowwiseReturnType;
-    typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
-    typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
-
-    /** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
-    *
-    * Example: \include MatrixBase_rowwise.cpp
-    * Output: \verbinclude MatrixBase_rowwise.out
-    *
-    * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-    */
-    //Code moved here due to a CUDA compiler bug
-    EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const {
-      return ConstRowwiseReturnType(derived());
-    }
-    EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
-
-    /** \returns a VectorwiseOp wrapper of *this providing additional partial reduction operations
-    *
-    * Example: \include MatrixBase_colwise.cpp
-    * Output: \verbinclude MatrixBase_colwise.out
-    *
-    * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-    */
-    EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const {
-      return ConstColwiseReturnType(derived());
-    }
-    EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
-
-    typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>,PlainObject> RandomReturnType;
-    static const RandomReturnType Random(Index rows, Index cols);
-    static const RandomReturnType Random(Index size);
-    static const RandomReturnType Random();
-
-    template<typename ThenDerived,typename ElseDerived>
-    const Select<Derived,ThenDerived,ElseDerived>
-    select(const DenseBase<ThenDerived>& thenMatrix,
-           const DenseBase<ElseDerived>& elseMatrix) const;
-
-    template<typename ThenDerived>
-    inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType>
-    select(const DenseBase<ThenDerived>& thenMatrix, const typename ThenDerived::Scalar& elseScalar) const;
-
-    template<typename ElseDerived>
-    inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived >
-    select(const typename ElseDerived::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
-
-    template<int p> RealScalar lpNorm() const;
-
-    template<int RowFactor, int ColFactor>
-    EIGEN_DEVICE_FUNC
-    const Replicate<Derived,RowFactor,ColFactor> replicate() const;
-    /**
-    * \return an expression of the replication of \c *this
-    *
-    * Example: \include MatrixBase_replicate_int_int.cpp
-    * Output: \verbinclude MatrixBase_replicate_int_int.out
-    *
-    * \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
-    */
-    //Code moved here due to a CUDA compiler bug
-    EIGEN_DEVICE_FUNC
-    const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const
-    {
-      return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
-    }
-
-    typedef Reverse<Derived, BothDirections> ReverseReturnType;
-    typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
-    EIGEN_DEVICE_FUNC ReverseReturnType reverse();
-    /** This is the const version of reverse(). */
-    //Code moved here due to a CUDA compiler bug
-    EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const
-    {
-      return ConstReverseReturnType(derived());
-    }
-    EIGEN_DEVICE_FUNC void reverseInPlace();
-
-#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
-#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
-#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
-#   include "../plugins/BlockMethods.h"
-#   ifdef EIGEN_DENSEBASE_PLUGIN
-#     include EIGEN_DENSEBASE_PLUGIN
-#   endif
-#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
-#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
-
-    // disable the use of evalTo for dense objects with a nice compilation error
-    template<typename Dest>
-    EIGEN_DEVICE_FUNC
-    inline void evalTo(Dest& ) const
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<Dest,void>::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
-    }
-
-  protected:
-    /** Default constructor. Do nothing. */
-    EIGEN_DEVICE_FUNC DenseBase()
-    {
-      /* Just checks for self-consistency of the flags.
-       * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
-       */
-#ifdef EIGEN_INTERNAL_DEBUGGING
-      EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, int(IsRowMajor))
-                        && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, int(!IsRowMajor))),
-                          INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
-#endif
-    }
-
-  private:
-    EIGEN_DEVICE_FUNC explicit DenseBase(int);
-    EIGEN_DEVICE_FUNC DenseBase(int,int);
-    template<typename OtherDerived> EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&);
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_DENSEBASE_H

deps_src/eigen/Eigen/src/Core/DenseCoeffsBase.h

@@ -1,681 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DENSECOEFFSBASE_H
-#define EIGEN_DENSECOEFFSBASE_H
-
-namespace Eigen {
-
-namespace internal {
-template<typename T> struct add_const_on_value_type_if_arithmetic
-{
-  typedef typename conditional<is_arithmetic<T>::value, T, typename add_const_on_value_type<T>::type>::type type;
-};
-}
-
-/** \brief Base class providing read-only coefficient access to matrices and arrays.
-  * \ingroup Core_Module
-  * \tparam Derived Type of the derived class
-  * \tparam #ReadOnlyAccessors Constant indicating read-only access
-  *
-  * This class defines the \c operator() \c const function and friends, which can be used to read specific
-  * entries of a matrix or array.
-  * 
-  * \sa DenseCoeffsBase<Derived, WriteAccessors>, DenseCoeffsBase<Derived, DirectAccessors>,
-  *     \ref TopicClassHierarchy
-  */
-template<typename Derived>
-class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
-{
-  public:
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
-
-    // Explanation for this CoeffReturnType typedef.
-    // - This is the return type of the coeff() method.
-    // - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references
-    // to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value).
-    // - The is_artihmetic check is required since "const int", "const double", etc. will cause warnings on some systems
-    // while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is
-    // not possible, since the underlying expressions might not offer a valid address the reference could be referring to.
-    typedef typename internal::conditional<bool(internal::traits<Derived>::Flags&LvalueBit),
-                         const Scalar&,
-                         typename internal::conditional<internal::is_arithmetic<Scalar>::value, Scalar, const Scalar>::type
-                     >::type CoeffReturnType;
-
-    typedef typename internal::add_const_on_value_type_if_arithmetic<
-                         typename internal::packet_traits<Scalar>::type
-                     >::type PacketReturnType;
-
-    typedef EigenBase<Derived> Base;
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::derived;
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
-    {
-      return int(Derived::RowsAtCompileTime) == 1 ? 0
-          : int(Derived::ColsAtCompileTime) == 1 ? inner
-          : int(Derived::Flags)&RowMajorBit ? outer
-          : inner;
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
-    {
-      return int(Derived::ColsAtCompileTime) == 1 ? 0
-          : int(Derived::RowsAtCompileTime) == 1 ? inner
-          : int(Derived::Flags)&RowMajorBit ? inner
-          : outer;
-    }
-
-    /** Short version: don't use this function, use
-      * \link operator()(Index,Index) const \endlink instead.
-      *
-      * Long version: this function is similar to
-      * \link operator()(Index,Index) const \endlink, but without the assertion.
-      * Use this for limiting the performance cost of debugging code when doing
-      * repeated coefficient access. Only use this when it is guaranteed that the
-      * parameters \a row and \a col are in range.
-      *
-      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator()(Index,Index) const \endlink.
-      *
-      * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
-    {
-      eigen_internal_assert(row >= 0 && row < rows()
-                         && col >= 0 && col < cols());
-      return internal::evaluator<Derived>(derived()).coeff(row,col);
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
-    {
-      return coeff(rowIndexByOuterInner(outer, inner),
-                   colIndexByOuterInner(outer, inner));
-    }
-
-    /** \returns the coefficient at given the given row and column.
-      *
-      * \sa operator()(Index,Index), operator[](Index)
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const
-    {
-      eigen_assert(row >= 0 && row < rows()
-          && col >= 0 && col < cols());
-      return coeff(row, col);
-    }
-
-    /** Short version: don't use this function, use
-      * \link operator[](Index) const \endlink instead.
-      *
-      * Long version: this function is similar to
-      * \link operator[](Index) const \endlink, but without the assertion.
-      * Use this for limiting the performance cost of debugging code when doing
-      * repeated coefficient access. Only use this when it is guaranteed that the
-      * parameter \a index is in range.
-      *
-      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator[](Index) const \endlink.
-      *
-      * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    coeff(Index index) const
-    {
-      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
-                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
-      eigen_internal_assert(index >= 0 && index < size());
-      return internal::evaluator<Derived>(derived()).coeff(index);
-    }
-
-
-    /** \returns the coefficient at given index.
-      *
-      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-      *
-      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
-      * z() const, w() const
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    operator[](Index index) const
-    {
-      EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
-                          THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
-      eigen_assert(index >= 0 && index < size());
-      return coeff(index);
-    }
-
-    /** \returns the coefficient at given index.
-      *
-      * This is synonymous to operator[](Index) const.
-      *
-      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-      *
-      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
-      * z() const, w() const
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    operator()(Index index) const
-    {
-      eigen_assert(index >= 0 && index < size());
-      return coeff(index);
-    }
-
-    /** equivalent to operator[](0).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    x() const { return (*this)[0]; }
-
-    /** equivalent to operator[](1).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    y() const
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=2, OUT_OF_RANGE_ACCESS);
-      return (*this)[1];
-    }
-
-    /** equivalent to operator[](2).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    z() const
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=3, OUT_OF_RANGE_ACCESS);
-      return (*this)[2];
-    }
-
-    /** equivalent to operator[](3).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE CoeffReturnType
-    w() const
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=4, OUT_OF_RANGE_ACCESS);
-      return (*this)[3];
-    }
-
-    /** \internal
-      * \returns the packet of coefficients starting at the given row and column. It is your responsibility
-      * to ensure that a packet really starts there. This method is only available on expressions having the
-      * PacketAccessBit.
-      *
-      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
-      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-      * starting at an address which is a multiple of the packet size.
-      */
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
-    {
-      typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
-      eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
-      return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(row,col);
-    }
-
-
-    /** \internal */
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketReturnType packetByOuterInner(Index outer, Index inner) const
-    {
-      return packet<LoadMode>(rowIndexByOuterInner(outer, inner),
-                              colIndexByOuterInner(outer, inner));
-    }
-
-    /** \internal
-      * \returns the packet of coefficients starting at the given index. It is your responsibility
-      * to ensure that a packet really starts there. This method is only available on expressions having the
-      * PacketAccessBit and the LinearAccessBit.
-      *
-      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
-      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-      * starting at an address which is a multiple of the packet size.
-      */
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
-    {
-      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
-                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
-      typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
-      eigen_internal_assert(index >= 0 && index < size());
-      return internal::evaluator<Derived>(derived()).template packet<LoadMode,DefaultPacketType>(index);
-    }
-
-  protected:
-    // explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase.
-    // But some methods are only available in the DirectAccess case.
-    // So we add dummy methods here with these names, so that "using... " doesn't fail.
-    // It's not private so that the child class DenseBase can access them, and it's not public
-    // either since it's an implementation detail, so has to be protected.
-    void coeffRef();
-    void coeffRefByOuterInner();
-    void writePacket();
-    void writePacketByOuterInner();
-    void copyCoeff();
-    void copyCoeffByOuterInner();
-    void copyPacket();
-    void copyPacketByOuterInner();
-    void stride();
-    void innerStride();
-    void outerStride();
-    void rowStride();
-    void colStride();
-};
-
-/** \brief Base class providing read/write coefficient access to matrices and arrays.
-  * \ingroup Core_Module
-  * \tparam Derived Type of the derived class
-  * \tparam #WriteAccessors Constant indicating read/write access
-  *
-  * This class defines the non-const \c operator() function and friends, which can be used to write specific
-  * entries of a matrix or array. This class inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which
-  * defines the const variant for reading specific entries.
-  * 
-  * \sa DenseCoeffsBase<Derived, DirectAccessors>, \ref TopicClassHierarchy
-  */
-template<typename Derived>
-class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
-{
-  public:
-
-    typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
-
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
-    using Base::coeff;
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::derived;
-    using Base::rowIndexByOuterInner;
-    using Base::colIndexByOuterInner;
-    using Base::operator[];
-    using Base::operator();
-    using Base::x;
-    using Base::y;
-    using Base::z;
-    using Base::w;
-
-    /** Short version: don't use this function, use
-      * \link operator()(Index,Index) \endlink instead.
-      *
-      * Long version: this function is similar to
-      * \link operator()(Index,Index) \endlink, but without the assertion.
-      * Use this for limiting the performance cost of debugging code when doing
-      * repeated coefficient access. Only use this when it is guaranteed that the
-      * parameters \a row and \a col are in range.
-      *
-      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator()(Index,Index) \endlink.
-      *
-      * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
-      */
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
-    {
-      eigen_internal_assert(row >= 0 && row < rows()
-                         && col >= 0 && col < cols());
-      return internal::evaluator<Derived>(derived()).coeffRef(row,col);
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    coeffRefByOuterInner(Index outer, Index inner)
-    {
-      return coeffRef(rowIndexByOuterInner(outer, inner),
-                      colIndexByOuterInner(outer, inner));
-    }
-
-    /** \returns a reference to the coefficient at given the given row and column.
-      *
-      * \sa operator[](Index)
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    operator()(Index row, Index col)
-    {
-      eigen_assert(row >= 0 && row < rows()
-          && col >= 0 && col < cols());
-      return coeffRef(row, col);
-    }
-
-
-    /** Short version: don't use this function, use
-      * \link operator[](Index) \endlink instead.
-      *
-      * Long version: this function is similar to
-      * \link operator[](Index) \endlink, but without the assertion.
-      * Use this for limiting the performance cost of debugging code when doing
-      * repeated coefficient access. Only use this when it is guaranteed that the
-      * parameters \a row and \a col are in range.
-      *
-      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator[](Index) \endlink.
-      *
-      * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    coeffRef(Index index)
-    {
-      EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
-                          THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
-      eigen_internal_assert(index >= 0 && index < size());
-      return internal::evaluator<Derived>(derived()).coeffRef(index);
-    }
-
-    /** \returns a reference to the coefficient at given index.
-      *
-      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-      *
-      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    operator[](Index index)
-    {
-      EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
-                          THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
-      eigen_assert(index >= 0 && index < size());
-      return coeffRef(index);
-    }
-
-    /** \returns a reference to the coefficient at given index.
-      *
-      * This is synonymous to operator[](Index).
-      *
-      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-      *
-      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
-      */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    operator()(Index index)
-    {
-      eigen_assert(index >= 0 && index < size());
-      return coeffRef(index);
-    }
-
-    /** equivalent to operator[](0).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    x() { return (*this)[0]; }
-
-    /** equivalent to operator[](1).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    y()
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=2, OUT_OF_RANGE_ACCESS);
-      return (*this)[1];
-    }
-
-    /** equivalent to operator[](2).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    z()
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=3, OUT_OF_RANGE_ACCESS);
-      return (*this)[2];
-    }
-
-    /** equivalent to operator[](3).  */
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar&
-    w()
-    {
-      EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime==-1 || Derived::SizeAtCompileTime>=4, OUT_OF_RANGE_ACCESS);
-      return (*this)[3];
-    }
-};
-
-/** \brief Base class providing direct read-only coefficient access to matrices and arrays.
-  * \ingroup Core_Module
-  * \tparam Derived Type of the derived class
-  * \tparam #DirectAccessors Constant indicating direct access
-  *
-  * This class defines functions to work with strides which can be used to access entries directly. This class
-  * inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which defines functions to access entries read-only using
-  * \c operator() .
-  *
-  * \sa \blank \ref TopicClassHierarchy
-  */
-template<typename Derived>
-class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
-{
-  public:
-
-    typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::derived;
-
-    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
-      *
-      * \sa outerStride(), rowStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const
-    {
-      return derived().innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
-      *          in a column-major matrix).
-      *
-      * \sa innerStride(), rowStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const
-    {
-      return derived().outerStride();
-    }
-
-    // FIXME shall we remove it ?
-    inline Index stride() const
-    {
-      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive rows.
-      *
-      * \sa innerStride(), outerStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index rowStride() const
-    {
-      return Derived::IsRowMajor ? outerStride() : innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive columns.
-      *
-      * \sa innerStride(), outerStride(), rowStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index colStride() const
-    {
-      return Derived::IsRowMajor ? innerStride() : outerStride();
-    }
-};
-
-/** \brief Base class providing direct read/write coefficient access to matrices and arrays.
-  * \ingroup Core_Module
-  * \tparam Derived Type of the derived class
-  * \tparam #DirectWriteAccessors Constant indicating direct access
-  *
-  * This class defines functions to work with strides which can be used to access entries directly. This class
-  * inherits DenseCoeffsBase<Derived, WriteAccessors> which defines functions to access entries read/write using
-  * \c operator().
-  *
-  * \sa \blank \ref TopicClassHierarchy
-  */
-template<typename Derived>
-class DenseCoeffsBase<Derived, DirectWriteAccessors>
-  : public DenseCoeffsBase<Derived, WriteAccessors>
-{
-  public:
-
-    typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::derived;
-
-    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
-      *
-      * \sa outerStride(), rowStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const
-    {
-      return derived().innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
-      *          in a column-major matrix).
-      *
-      * \sa innerStride(), rowStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const
-    {
-      return derived().outerStride();
-    }
-
-    // FIXME shall we remove it ?
-    inline Index stride() const
-    {
-      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive rows.
-      *
-      * \sa innerStride(), outerStride(), colStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index rowStride() const
-    {
-      return Derived::IsRowMajor ? outerStride() : innerStride();
-    }
-
-    /** \returns the pointer increment between two consecutive columns.
-      *
-      * \sa innerStride(), outerStride(), rowStride()
-      */
-    EIGEN_DEVICE_FUNC
-    inline Index colStride() const
-    {
-      return Derived::IsRowMajor ? innerStride() : outerStride();
-    }
-};
-
-namespace internal {
-
-template<int Alignment, typename Derived, bool JustReturnZero>
-struct first_aligned_impl
-{
-  static inline Index run(const Derived&)
-  { return 0; }
-};
-
-template<int Alignment, typename Derived>
-struct first_aligned_impl<Alignment, Derived, false>
-{
-  static inline Index run(const Derived& m)
-  {
-    return internal::first_aligned<Alignment>(m.data(), m.size());
-  }
-};
-
-/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect to \a Alignment for vectorization.
-  *
-  * \tparam Alignment requested alignment in Bytes.
-  *
-  * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
-  * documentation.
-  */
-template<int Alignment, typename Derived>
-static inline Index first_aligned(const DenseBase<Derived>& m)
-{
-  enum { ReturnZero = (int(evaluator<Derived>::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) };
-  return first_aligned_impl<Alignment, Derived, ReturnZero>::run(m.derived());
-}
-
-template<typename Derived>
-static inline Index first_default_aligned(const DenseBase<Derived>& m)
-{
-  typedef typename Derived::Scalar Scalar;
-  typedef typename packet_traits<Scalar>::type DefaultPacketType;
-  return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
-}
-
-template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
-struct inner_stride_at_compile_time
-{
-  enum { ret = traits<Derived>::InnerStrideAtCompileTime };
-};
-
-template<typename Derived>
-struct inner_stride_at_compile_time<Derived, false>
-{
-  enum { ret = 0 };
-};
-
-template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
-struct outer_stride_at_compile_time
-{
-  enum { ret = traits<Derived>::OuterStrideAtCompileTime };
-};
-
-template<typename Derived>
-struct outer_stride_at_compile_time<Derived, false>
-{
-  enum { ret = 0 };
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_DENSECOEFFSBASE_H

deps_src/eigen/Eigen/src/Core/DenseStorage.h

@@ -1,570 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2010-2013 Hauke Heibel <hauke.heibel@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MATRIXSTORAGE_H
-#define EIGEN_MATRIXSTORAGE_H
-
-#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) X; EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
-#else
-  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
-#endif
-
-namespace Eigen {
-
-namespace internal {
-
-struct constructor_without_unaligned_array_assert {};
-
-template<typename T, int Size>
-EIGEN_DEVICE_FUNC
-void check_static_allocation_size()
-{
-  // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
-  #if EIGEN_STACK_ALLOCATION_LIMIT
-  EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
-  #endif
-}
-
-/** \internal
-  * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
-  * to 16 bytes boundary if the total size is a multiple of 16 bytes.
-  */
-template <typename T, int Size, int MatrixOrArrayOptions,
-          int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
-                        : compute_default_alignment<T,Size>::value >
-struct plain_array
-{
-  T array[Size];
-
-  EIGEN_DEVICE_FUNC
-  plain_array()
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-
-  EIGEN_DEVICE_FUNC
-  plain_array(constructor_without_unaligned_array_assert)
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-};
-
-#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
-  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
-#elif EIGEN_GNUC_AT_LEAST(4,7) 
-  // GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned.
-  // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
-  // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
-  template<typename PtrType>
-  EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
-  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((internal::UIntPtr(eigen_unaligned_array_assert_workaround_gcc47(array)) & (sizemask)) == 0 \
-              && "this assertion is explained here: " \
-              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
-              " **** READ THIS WEB PAGE !!! ****");
-#else
-  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((internal::UIntPtr(array) & (sizemask)) == 0 \
-              && "this assertion is explained here: " \
-              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
-              " **** READ THIS WEB PAGE !!! ****");
-#endif
-
-template <typename T, int Size, int MatrixOrArrayOptions>
-struct plain_array<T, Size, MatrixOrArrayOptions, 8>
-{
-  EIGEN_ALIGN_TO_BOUNDARY(8) T array[Size];
-
-  EIGEN_DEVICE_FUNC
-  plain_array() 
-  {
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(7);
-    check_static_allocation_size<T,Size>();
-  }
-
-  EIGEN_DEVICE_FUNC
-  plain_array(constructor_without_unaligned_array_assert) 
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-};
-
-template <typename T, int Size, int MatrixOrArrayOptions>
-struct plain_array<T, Size, MatrixOrArrayOptions, 16>
-{
-  EIGEN_ALIGN_TO_BOUNDARY(16) T array[Size];
-
-  EIGEN_DEVICE_FUNC
-  plain_array() 
-  { 
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(15);
-    check_static_allocation_size<T,Size>();
-  }
-
-  EIGEN_DEVICE_FUNC
-  plain_array(constructor_without_unaligned_array_assert) 
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-};
-
-template <typename T, int Size, int MatrixOrArrayOptions>
-struct plain_array<T, Size, MatrixOrArrayOptions, 32>
-{
-  EIGEN_ALIGN_TO_BOUNDARY(32) T array[Size];
-
-  EIGEN_DEVICE_FUNC
-  plain_array() 
-  {
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(31);
-    check_static_allocation_size<T,Size>();
-  }
-
-  EIGEN_DEVICE_FUNC
-  plain_array(constructor_without_unaligned_array_assert) 
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-};
-
-template <typename T, int Size, int MatrixOrArrayOptions>
-struct plain_array<T, Size, MatrixOrArrayOptions, 64>
-{
-  EIGEN_ALIGN_TO_BOUNDARY(64) T array[Size];
-
-  EIGEN_DEVICE_FUNC
-  plain_array() 
-  { 
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(63);
-    check_static_allocation_size<T,Size>();
-  }
-
-  EIGEN_DEVICE_FUNC
-  plain_array(constructor_without_unaligned_array_assert) 
-  { 
-    check_static_allocation_size<T,Size>();
-  }
-};
-
-template <typename T, int MatrixOrArrayOptions, int Alignment>
-struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
-{
-  T array[1];
-  EIGEN_DEVICE_FUNC plain_array() {}
-  EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
-};
-
-} // end namespace internal
-
-/** \internal
-  *
-  * \class DenseStorage
-  * \ingroup Core_Module
-  *
-  * \brief Stores the data of a matrix
-  *
-  * This class stores the data of fixed-size, dynamic-size or mixed matrices
-  * in a way as compact as possible.
-  *
-  * \sa Matrix
-  */
-template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage;
-
-// purely fixed-size matrix
-template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage
-{
-    internal::plain_array<T,Size,_Options> m_data;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
-    }
-    EIGEN_DEVICE_FUNC
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
-      : m_data(internal::constructor_without_unaligned_array_assert()) {}
-    EIGEN_DEVICE_FUNC 
-    DenseStorage(const DenseStorage& other) : m_data(other.m_data) {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
-    }
-    EIGEN_DEVICE_FUNC 
-    DenseStorage& operator=(const DenseStorage& other)
-    { 
-      if (this != &other) m_data = other.m_data;
-      return *this; 
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
-      EIGEN_UNUSED_VARIABLE(size);
-      EIGEN_UNUSED_VARIABLE(rows);
-      EIGEN_UNUSED_VARIABLE(cols);
-    }
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
-    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
-    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
-};
-
-// null matrix
-template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
-{
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {}
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; }
-    EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {}
-    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
-    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC const T *data() const { return 0; }
-    EIGEN_DEVICE_FUNC T *data() { return 0; }
-};
-
-// more specializations for null matrices; these are necessary to resolve ambiguities
-template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-// dynamic-size matrix with fixed-size storage
-template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
-{
-    internal::plain_array<T,Size,_Options> m_data;
-    Index m_rows;
-    Index m_cols;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 
-    { 
-      if (this != &other)
-      {
-        m_data = other.m_data;
-        m_rows = other.m_rows;
-        m_cols = other.m_cols;
-      }
-      return *this; 
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
-    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    EIGEN_DEVICE_FUNC Index rows() const {return m_rows;}
-    EIGEN_DEVICE_FUNC Index cols() const {return m_cols;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
-    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
-};
-
-// dynamic-size matrix with fixed-size storage and fixed width
-template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
-{
-    internal::plain_array<T,Size,_Options> m_data;
-    Index m_rows;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) 
-    {
-      if (this != &other)
-      {
-        m_data = other.m_data;
-        m_rows = other.m_rows;
-      }
-      return *this; 
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
-    EIGEN_DEVICE_FUNC Index cols(void) const {return _Cols;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
-    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) { m_rows = rows; }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
-};
-
-// dynamic-size matrix with fixed-size storage and fixed height
-template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
-{
-    internal::plain_array<T,Size,_Options> m_data;
-    Index m_cols;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
-    {
-      if (this != &other)
-      {
-        m_data = other.m_data;
-        m_cols = other.m_cols;
-      }
-      return *this;
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {}
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    EIGEN_DEVICE_FUNC Index rows(void) const {return _Rows;}
-    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
-    void conservativeResize(Index, Index, Index cols) { m_cols = cols; }
-    void resize(Index, Index, Index cols) { m_cols = cols; }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
-};
-
-// purely dynamic matrix.
-template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
-{
-    T *m_data;
-    Index m_rows;
-    Index m_cols;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
-       : m_data(0), m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*other.m_cols))
-      , m_rows(other.m_rows)
-      , m_cols(other.m_cols)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*m_cols)
-      internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
-    {
-      if (this != &other)
-      {
-        DenseStorage tmp(other);
-        this->swap(tmp);
-      }
-      return *this;
-    }
-#if EIGEN_HAS_RVALUE_REFERENCES
-    EIGEN_DEVICE_FUNC
-    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
-      : m_data(std::move(other.m_data))
-      , m_rows(std::move(other.m_rows))
-      , m_cols(std::move(other.m_cols))
-    {
-      other.m_data = nullptr;
-      other.m_rows = 0;
-      other.m_cols = 0;
-    }
-    EIGEN_DEVICE_FUNC
-    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
-    {
-      using std::swap;
-      swap(m_data, other.m_data);
-      swap(m_rows, other.m_rows);
-      swap(m_cols, other.m_cols);
-      return *this;
-    }
-#endif
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
-    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
-    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
-    void conservativeResize(Index size, Index rows, Index cols)
-    {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
-      m_rows = rows;
-      m_cols = cols;
-    }
-    EIGEN_DEVICE_FUNC void resize(Index size, Index rows, Index cols)
-    {
-      if(size != m_rows*m_cols)
-      {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols);
-        if (size)
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
-        else
-          m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      }
-      m_rows = rows;
-      m_cols = cols;
-    }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data; }
-};
-
-// matrix with dynamic width and fixed height (so that matrix has dynamic size).
-template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
-{
-    T *m_data;
-    Index m_cols;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {}
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0);
-      EIGEN_UNUSED_VARIABLE(rows);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
-      , m_cols(other.m_cols)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows)
-      internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
-    {
-      if (this != &other)
-      {
-        DenseStorage tmp(other);
-        this->swap(tmp);
-      }
-      return *this;
-    }    
-#if EIGEN_HAS_RVALUE_REFERENCES
-    EIGEN_DEVICE_FUNC
-    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
-      : m_data(std::move(other.m_data))
-      , m_cols(std::move(other.m_cols))
-    {
-      other.m_data = nullptr;
-      other.m_cols = 0;
-    }
-    EIGEN_DEVICE_FUNC
-    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
-    {
-      using std::swap;
-      swap(m_data, other.m_data);
-      swap(m_cols, other.m_cols);
-      return *this;
-    }
-#endif
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    EIGEN_DEVICE_FUNC static Index rows(void) {return _Rows;}
-    EIGEN_DEVICE_FUNC Index cols(void) const {return m_cols;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index size, Index, Index cols)
-    {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
-      m_cols = cols;
-    }
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index, Index cols)
-    {
-      if(size != _Rows*m_cols)
-      {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols);
-        if (size)
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
-        else
-          m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      }
-      m_cols = cols;
-    }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data; }
-};
-
-// matrix with dynamic height and fixed width (so that matrix has dynamic size).
-template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
-{
-    T *m_data;
-    Index m_rows;
-  public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {}
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols);
-      EIGEN_UNUSED_VARIABLE(cols);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
-      , m_rows(other.m_rows)
-    {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols)
-      internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
-    }
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
-    {
-      if (this != &other)
-      {
-        DenseStorage tmp(other);
-        this->swap(tmp);
-      }
-      return *this;
-    }    
-#if EIGEN_HAS_RVALUE_REFERENCES
-    EIGEN_DEVICE_FUNC
-    DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
-      : m_data(std::move(other.m_data))
-      , m_rows(std::move(other.m_rows))
-    {
-      other.m_data = nullptr;
-      other.m_rows = 0;
-    }
-    EIGEN_DEVICE_FUNC
-    DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
-    {
-      using std::swap;
-      swap(m_data, other.m_data);
-      swap(m_rows, other.m_rows);
-      return *this;
-    }
-#endif
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    EIGEN_DEVICE_FUNC Index rows(void) const {return m_rows;}
-    EIGEN_DEVICE_FUNC static Index cols(void) {return _Cols;}
-    void conservativeResize(Index size, Index rows, Index)
-    {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
-      m_rows = rows;
-    }
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index rows, Index)
-    {
-      if(size != m_rows*_Cols)
-      {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows);
-        if (size)
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
-        else
-          m_data = 0;
-        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      }
-      m_rows = rows;
-    }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data; }
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_MATRIX_H

deps_src/eigen/Eigen/src/Core/Diagonal.h

@@ -1,260 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DIAGONAL_H
-#define EIGEN_DIAGONAL_H
-
-namespace Eigen { 
-
-/** \class Diagonal
-  * \ingroup Core_Module
-  *
-  * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
-  *
-  * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
-  * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
-  *              A positive value means a superdiagonal, a negative value means a subdiagonal.
-  *              You can also use DynamicIndex so the index can be set at runtime.
-  *
-  * The matrix is not required to be square.
-  *
-  * This class represents an expression of the main diagonal, or any sub/super diagonal
-  * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
-  * time this is the only way it is used.
-  *
-  * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
-  */
-
-namespace internal {
-template<typename MatrixType, int DiagIndex>
-struct traits<Diagonal<MatrixType,DiagIndex> >
- : traits<MatrixType>
-{
-  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
-  typedef typename MatrixType::StorageKind StorageKind;
-  enum {
-    RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
-                      : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
-                                              MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
-    ColsAtCompileTime = 1,
-    MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-                         : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
-                                                                              MatrixType::MaxColsAtCompileTime)
-                         : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
-                                                 MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
-    MaxColsAtCompileTime = 1,
-    MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags = (unsigned int)_MatrixTypeNested::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
-    MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
-    InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
-    OuterStrideAtCompileTime = 0
-  };
-};
-}
-
-template<typename MatrixType, int _DiagIndex> class Diagonal
-   : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
-{
-  public:
-
-    enum { DiagIndex = _DiagIndex };
-    typedef typename internal::dense_xpr_base<Diagonal>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
-
-    EIGEN_DEVICE_FUNC
-    explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index)
-    {
-      eigen_assert( a_index <= m_matrix.cols() && -a_index <= m_matrix.rows() );
-    }
-
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
-
-    EIGEN_DEVICE_FUNC
-    inline Index rows() const
-    {
-      return m_index.value()<0 ? numext::mini<Index>(m_matrix.cols(),m_matrix.rows()+m_index.value())
-                               : numext::mini<Index>(m_matrix.rows(),m_matrix.cols()-m_index.value());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Index cols() const { return 1; }
-
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const
-    {
-      return m_matrix.outerStride() + 1;
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const
-    {
-      return 0;
-    }
-
-    typedef typename internal::conditional<
-                       internal::is_lvalue<MatrixType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
-    EIGEN_DEVICE_FUNC
-    inline const Scalar* data() const { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
-
-    EIGEN_DEVICE_FUNC
-    inline Scalar& coeffRef(Index row, Index)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.coeffRef(row+rowOffset(), row+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index row, Index) const
-    {
-      return m_matrix.coeffRef(row+rowOffset(), row+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline CoeffReturnType coeff(Index row, Index) const
-    {
-      return m_matrix.coeff(row+rowOffset(), row+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Scalar& coeffRef(Index idx)
-    {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.coeffRef(idx+rowOffset(), idx+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index idx) const
-    {
-      return m_matrix.coeffRef(idx+rowOffset(), idx+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline CoeffReturnType coeff(Index idx) const
-    {
-      return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline const typename internal::remove_all<typename MatrixType::Nested>::type& 
-    nestedExpression() const 
-    {
-      return m_matrix;
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Index index() const
-    {
-      return m_index.value();
-    }
-
-  protected:
-    typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
-    const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
-
-  private:
-    // some compilers may fail to optimize std::max etc in case of compile-time constants...
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
-    // trigger a compile-time error if someone try to call packet
-    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
-    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
-};
-
-/** \returns an expression of the main diagonal of the matrix \c *this
-  *
-  * \c *this is not required to be square.
-  *
-  * Example: \include MatrixBase_diagonal.cpp
-  * Output: \verbinclude MatrixBase_diagonal.out
-  *
-  * \sa class Diagonal */
-template<typename Derived>
-inline typename MatrixBase<Derived>::DiagonalReturnType
-MatrixBase<Derived>::diagonal()
-{
-  return DiagonalReturnType(derived());
-}
-
-/** This is the const version of diagonal(). */
-template<typename Derived>
-inline typename MatrixBase<Derived>::ConstDiagonalReturnType
-MatrixBase<Derived>::diagonal() const
-{
-  return ConstDiagonalReturnType(derived());
-}
-
-/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
-  *
-  * \c *this is not required to be square.
-  *
-  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
-  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
-  *
-  * Example: \include MatrixBase_diagonal_int.cpp
-  * Output: \verbinclude MatrixBase_diagonal_int.out
-  *
-  * \sa MatrixBase::diagonal(), class Diagonal */
-template<typename Derived>
-inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
-MatrixBase<Derived>::diagonal(Index index)
-{
-  return DiagonalDynamicIndexReturnType(derived(), index);
-}
-
-/** This is the const version of diagonal(Index). */
-template<typename Derived>
-inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
-MatrixBase<Derived>::diagonal(Index index) const
-{
-  return ConstDiagonalDynamicIndexReturnType(derived(), index);
-}
-
-/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
-  *
-  * \c *this is not required to be square.
-  *
-  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
-  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
-  *
-  * Example: \include MatrixBase_diagonal_template_int.cpp
-  * Output: \verbinclude MatrixBase_diagonal_template_int.out
-  *
-  * \sa MatrixBase::diagonal(), class Diagonal */
-template<typename Derived>
-template<int Index_>
-inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
-MatrixBase<Derived>::diagonal()
-{
-  return typename DiagonalIndexReturnType<Index_>::Type(derived());
-}
-
-/** This is the const version of diagonal<int>(). */
-template<typename Derived>
-template<int Index_>
-inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
-MatrixBase<Derived>::diagonal() const
-{
-  return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_DIAGONAL_H

deps_src/eigen/Eigen/src/Core/DiagonalMatrix.h

@@ -1,343 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DIAGONALMATRIX_H
-#define EIGEN_DIAGONALMATRIX_H
-
-namespace Eigen { 
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template<typename Derived>
-class DiagonalBase : public EigenBase<Derived>
-{
-  public:
-    typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
-    typedef typename DiagonalVectorType::Scalar Scalar;
-    typedef typename DiagonalVectorType::RealScalar RealScalar;
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
-
-    enum {
-      RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-      ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-      MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-      MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-      IsVectorAtCompileTime = 0,
-      Flags = NoPreferredStorageOrderBit
-    };
-
-    typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
-    typedef DenseMatrixType DenseType;
-    typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
-
-    EIGEN_DEVICE_FUNC
-    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
-    EIGEN_DEVICE_FUNC
-    inline Derived& derived() { return *static_cast<Derived*>(this); }
-
-    EIGEN_DEVICE_FUNC
-    DenseMatrixType toDenseMatrix() const { return derived(); }
-    
-    EIGEN_DEVICE_FUNC
-    inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
-    EIGEN_DEVICE_FUNC
-    inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
-
-    EIGEN_DEVICE_FUNC
-    inline Index rows() const { return diagonal().size(); }
-    EIGEN_DEVICE_FUNC
-    inline Index cols() const { return diagonal().size(); }
-
-    template<typename MatrixDerived>
-    EIGEN_DEVICE_FUNC
-    const Product<Derived,MatrixDerived,LazyProduct>
-    operator*(const MatrixBase<MatrixDerived> &matrix) const
-    {
-      return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
-    }
-
-    typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType;
-    EIGEN_DEVICE_FUNC
-    inline const InverseReturnType
-    inverse() const
-    {
-      return InverseReturnType(diagonal().cwiseInverse());
-    }
-    
-    EIGEN_DEVICE_FUNC
-    inline const DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >
-    operator*(const Scalar& scalar) const
-    {
-      return DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >(diagonal() * scalar);
-    }
-    EIGEN_DEVICE_FUNC
-    friend inline const DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >
-    operator*(const Scalar& scalar, const DiagonalBase& other)
-    {
-      return DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >(scalar * other.diagonal());
-    }
-};
-
-#endif
-
-/** \class DiagonalMatrix
-  * \ingroup Core_Module
-  *
-  * \brief Represents a diagonal matrix with its storage
-  *
-  * \param _Scalar the type of coefficients
-  * \param SizeAtCompileTime the dimension of the matrix, or Dynamic
-  * \param MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults
-  *        to SizeAtCompileTime. Most of the time, you do not need to specify it.
-  *
-  * \sa class DiagonalWrapper
-  */
-
-namespace internal {
-template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
-struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
- : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
-{
-  typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
-  typedef DiagonalShape StorageKind;
-  enum {
-    Flags = LvalueBit | NoPreferredStorageOrderBit
-  };
-};
-}
-template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
-class DiagonalMatrix
-  : public DiagonalBase<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
-{
-  public:
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
-    typedef const DiagonalMatrix& Nested;
-    typedef _Scalar Scalar;
-    typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
-    typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
-    #endif
-
-  protected:
-
-    DiagonalVectorType m_diagonal;
-
-  public:
-
-    /** const version of diagonal(). */
-    EIGEN_DEVICE_FUNC
-    inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
-    /** \returns a reference to the stored vector of diagonal coefficients. */
-    EIGEN_DEVICE_FUNC
-    inline DiagonalVectorType& diagonal() { return m_diagonal; }
-
-    /** Default constructor without initialization */
-    EIGEN_DEVICE_FUNC
-    inline DiagonalMatrix() {}
-
-    /** Constructs a diagonal matrix with given dimension  */
-    EIGEN_DEVICE_FUNC
-    explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
-
-    /** 2D constructor. */
-    EIGEN_DEVICE_FUNC
-    inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
-
-    /** 3D constructor. */
-    EIGEN_DEVICE_FUNC
-    inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
-
-    /** Copy constructor. */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
-    inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {}
-    #endif
-
-    /** generic constructor from expression of the diagonal coefficients */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
-    {}
-
-    /** Copy operator. */
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC
-    DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
-    {
-      m_diagonal = other.diagonal();
-      return *this;
-    }
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** This is a special case of the templated operator=. Its purpose is to
-      * prevent a default operator= from hiding the templated operator=.
-      */
-    EIGEN_DEVICE_FUNC
-    DiagonalMatrix& operator=(const DiagonalMatrix& other)
-    {
-      m_diagonal = other.diagonal();
-      return *this;
-    }
-    #endif
-
-    /** Resizes to given size. */
-    EIGEN_DEVICE_FUNC
-    inline void resize(Index size) { m_diagonal.resize(size); }
-    /** Sets all coefficients to zero. */
-    EIGEN_DEVICE_FUNC
-    inline void setZero() { m_diagonal.setZero(); }
-    /** Resizes and sets all coefficients to zero. */
-    EIGEN_DEVICE_FUNC
-    inline void setZero(Index size) { m_diagonal.setZero(size); }
-    /** Sets this matrix to be the identity matrix of the current size. */
-    EIGEN_DEVICE_FUNC
-    inline void setIdentity() { m_diagonal.setOnes(); }
-    /** Sets this matrix to be the identity matrix of the given size. */
-    EIGEN_DEVICE_FUNC
-    inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
-};
-
-/** \class DiagonalWrapper
-  * \ingroup Core_Module
-  *
-  * \brief Expression of a diagonal matrix
-  *
-  * \param _DiagonalVectorType the type of the vector of diagonal coefficients
-  *
-  * This class is an expression of a diagonal matrix, but not storing its own vector of diagonal coefficients,
-  * instead wrapping an existing vector expression. It is the return type of MatrixBase::asDiagonal()
-  * and most of the time this is the only way that it is used.
-  *
-  * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal()
-  */
-
-namespace internal {
-template<typename _DiagonalVectorType>
-struct traits<DiagonalWrapper<_DiagonalVectorType> >
-{
-  typedef _DiagonalVectorType DiagonalVectorType;
-  typedef typename DiagonalVectorType::Scalar Scalar;
-  typedef typename DiagonalVectorType::StorageIndex StorageIndex;
-  typedef DiagonalShape StorageKind;
-  typedef typename traits<DiagonalVectorType>::XprKind XprKind;
-  enum {
-    RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    Flags =  (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
-  };
-};
-}
-
-template<typename _DiagonalVectorType>
-class DiagonalWrapper
-  : public DiagonalBase<DiagonalWrapper<_DiagonalVectorType> >, internal::no_assignment_operator
-{
-  public:
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    typedef _DiagonalVectorType DiagonalVectorType;
-    typedef DiagonalWrapper Nested;
-    #endif
-
-    /** Constructor from expression of diagonal coefficients to wrap. */
-    EIGEN_DEVICE_FUNC
-    explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
-
-    /** \returns a const reference to the wrapped expression of diagonal coefficients. */
-    EIGEN_DEVICE_FUNC
-    const DiagonalVectorType& diagonal() const { return m_diagonal; }
-
-  protected:
-    typename DiagonalVectorType::Nested m_diagonal;
-};
-
-/** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
-  *
-  * \only_for_vectors
-  *
-  * Example: \include MatrixBase_asDiagonal.cpp
-  * Output: \verbinclude MatrixBase_asDiagonal.out
-  *
-  * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()
-  **/
-template<typename Derived>
-inline const DiagonalWrapper<const Derived>
-MatrixBase<Derived>::asDiagonal() const
-{
-  return DiagonalWrapper<const Derived>(derived());
-}
-
-/** \returns true if *this is approximately equal to a diagonal matrix,
-  *          within the precision given by \a prec.
-  *
-  * Example: \include MatrixBase_isDiagonal.cpp
-  * Output: \verbinclude MatrixBase_isDiagonal.out
-  *
-  * \sa asDiagonal()
-  */
-template<typename Derived>
-bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
-{
-  if(cols() != rows()) return false;
-  RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
-  for(Index j = 0; j < cols(); ++j)
-  {
-    RealScalar absOnDiagonal = numext::abs(coeff(j,j));
-    if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
-  }
-  for(Index j = 0; j < cols(); ++j)
-    for(Index i = 0; i < j; ++i)
-    {
-      if(!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
-      if(!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
-    }
-  return true;
-}
-
-namespace internal {
-
-template<> struct storage_kind_to_shape<DiagonalShape> { typedef DiagonalShape Shape; };
-
-struct Diagonal2Dense {};
-
-template<> struct AssignmentKind<DenseShape,DiagonalShape> { typedef Diagonal2Dense Kind; };
-
-// Diagonal matrix to Dense assignment
-template< typename DstXprType, typename SrcXprType, typename Functor>
-struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense>
-{
-  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
-  {
-    Index dstRows = src.rows();
-    Index dstCols = src.cols();
-    if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
-      dst.resize(dstRows, dstCols);
-    
-    dst.setZero();
-    dst.diagonal() = src.diagonal();
-  }
-  
-  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
-  { dst.diagonal() += src.diagonal(); }
-  
-  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
-  { dst.diagonal() -= src.diagonal(); }
-};
-
-} // namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_DIAGONALMATRIX_H

deps_src/eigen/Eigen/src/Core/DiagonalProduct.h

@@ -1,28 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DIAGONALPRODUCT_H
-#define EIGEN_DIAGONALPRODUCT_H
-
-namespace Eigen { 
-
-/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
-  */
-template<typename Derived>
-template<typename DiagonalDerived>
-inline const Product<Derived, DiagonalDerived, LazyProduct>
-MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
-{
-  return Product<Derived, DiagonalDerived, LazyProduct>(derived(),a_diagonal.derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_DIAGONALPRODUCT_H

deps_src/eigen/Eigen/src/Core/Dot.h

@@ -1,318 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008, 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DOT_H
-#define EIGEN_DOT_H
-
-namespace Eigen { 
-
-namespace internal {
-
-// helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot
-// with mismatched types, the compiler emits errors about failing to instantiate cwiseProduct BEFORE
-// looking at the static assertions. Thus this is a trick to get better compile errors.
-template<typename T, typename U,
-// the NeedToTranspose condition here is taken straight from Assign.h
-         bool NeedToTranspose = T::IsVectorAtCompileTime
-                && U::IsVectorAtCompileTime
-                && ((int(T::RowsAtCompileTime) == 1 && int(U::ColsAtCompileTime) == 1)
-                      |  // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
-                         // revert to || as soon as not needed anymore.
-                    (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))
->
-struct dot_nocheck
-{
-  typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
-  typedef typename conj_prod::result_type ResScalar;
-  EIGEN_DEVICE_FUNC
-  EIGEN_STRONG_INLINE
-  static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
-  {
-    return a.template binaryExpr<conj_prod>(b).sum();
-  }
-};
-
-template<typename T, typename U>
-struct dot_nocheck<T, U, true>
-{
-  typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
-  typedef typename conj_prod::result_type ResScalar;
-  EIGEN_DEVICE_FUNC
-  EIGEN_STRONG_INLINE
-  static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
-  {
-    return a.transpose().template binaryExpr<conj_prod>(b).sum();
-  }
-};
-
-} // end namespace internal
-
-/** \fn MatrixBase::dot
-  * \returns the dot product of *this with other.
-  *
-  * \only_for_vectors
-  *
-  * \note If the scalar type is complex numbers, then this function returns the hermitian
-  * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the
-  * second variable.
-  *
-  * \sa squaredNorm(), norm()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-EIGEN_STRONG_INLINE
-typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
-MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
-#if !(defined(EIGEN_NO_STATIC_ASSERT) && defined(EIGEN_NO_DEBUG))
-  typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
-  EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
-#endif
-  
-  eigen_assert(size() == other.size());
-
-  return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
-}
-
-//---------- implementation of L2 norm and related functions ----------
-
-/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
-  * In both cases, it consists in the sum of the square of all the matrix entries.
-  * For vectors, this is also equals to the dot product of \c *this with itself.
-  *
-  * \sa dot(), norm(), lpNorm()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
-{
-  return numext::real((*this).cwiseAbs2().sum());
-}
-
-/** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
-  * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
-  * For vectors, this is also equals to the square root of the dot product of \c *this with itself.
-  *
-  * \sa lpNorm(), dot(), squaredNorm()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
-{
-  return numext::sqrt(squaredNorm());
-}
-
-/** \returns an expression of the quotient of \c *this by its own norm.
-  *
-  * \warning If the input vector is too small (i.e., this->norm()==0),
-  *          then this function returns a copy of the input.
-  *
-  * \only_for_vectors
-  *
-  * \sa norm(), normalize()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
-MatrixBase<Derived>::normalized() const
-{
-  typedef typename internal::nested_eval<Derived,2>::type _Nested;
-  _Nested n(derived());
-  RealScalar z = n.squaredNorm();
-  // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
-  if(z>RealScalar(0))
-    return n / numext::sqrt(z);
-  else
-    return n;
-}
-
-/** Normalizes the vector, i.e. divides it by its own norm.
-  *
-  * \only_for_vectors
-  *
-  * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
-  *
-  * \sa norm(), normalized()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
-{
-  RealScalar z = squaredNorm();
-  // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
-  if(z>RealScalar(0))
-    derived() /= numext::sqrt(z);
-}
-
-/** \returns an expression of the quotient of \c *this by its own norm while avoiding underflow and overflow.
-  *
-  * \only_for_vectors
-  *
-  * This method is analogue to the normalized() method, but it reduces the risk of
-  * underflow and overflow when computing the norm.
-  *
-  * \warning If the input vector is too small (i.e., this->norm()==0),
-  *          then this function returns a copy of the input.
-  *
-  * \sa stableNorm(), stableNormalize(), normalized()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
-MatrixBase<Derived>::stableNormalized() const
-{
-  typedef typename internal::nested_eval<Derived,3>::type _Nested;
-  _Nested n(derived());
-  RealScalar w = n.cwiseAbs().maxCoeff();
-  RealScalar z = (n/w).squaredNorm();
-  if(z>RealScalar(0))
-    return n / (numext::sqrt(z)*w);
-  else
-    return n;
-}
-
-/** Normalizes the vector while avoid underflow and overflow
-  *
-  * \only_for_vectors
-  *
-  * This method is analogue to the normalize() method, but it reduces the risk of
-  * underflow and overflow when computing the norm.
-  *
-  * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
-  *
-  * \sa stableNorm(), stableNormalized(), normalize()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize()
-{
-  RealScalar w = cwiseAbs().maxCoeff();
-  RealScalar z = (derived()/w).squaredNorm();
-  if(z>RealScalar(0))
-    derived() /= numext::sqrt(z)*w;
-}
-
-//---------- implementation of other norms ----------
-
-namespace internal {
-
-template<typename Derived, int p>
-struct lpNorm_selector
-{
-  typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  EIGEN_DEVICE_FUNC
-  static inline RealScalar run(const MatrixBase<Derived>& m)
-  {
-    EIGEN_USING_STD_MATH(pow)
-    return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
-  }
-};
-
-template<typename Derived>
-struct lpNorm_selector<Derived, 1>
-{
-  EIGEN_DEVICE_FUNC
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
-  {
-    return m.cwiseAbs().sum();
-  }
-};
-
-template<typename Derived>
-struct lpNorm_selector<Derived, 2>
-{
-  EIGEN_DEVICE_FUNC
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
-  {
-    return m.norm();
-  }
-};
-
-template<typename Derived>
-struct lpNorm_selector<Derived, Infinity>
-{
-  typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  EIGEN_DEVICE_FUNC
-  static inline RealScalar run(const MatrixBase<Derived>& m)
-  {
-    if(Derived::SizeAtCompileTime==0 || (Derived::SizeAtCompileTime==Dynamic && m.size()==0))
-      return RealScalar(0);
-    return m.cwiseAbs().maxCoeff();
-  }
-};
-
-} // end namespace internal
-
-/** \returns the \b coefficient-wise \f$ \ell^p \f$ norm of \c *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
-  *          of the coefficients of \c *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$
-  *          norm, that is the maximum of the absolute values of the coefficients of \c *this.
-  *
-  * In all cases, if \c *this is empty, then the value 0 is returned.
-  *
-  * \note For matrices, this function does not compute the <a href="https://en.wikipedia.org/wiki/Operator_norm">operator-norm</a>. That is, if \c *this is a matrix, then its coefficients are interpreted as a 1D vector. Nonetheless, you can easily compute the 1-norm and \f$\infty\f$-norm matrix operator norms using \link TutorialReductionsVisitorsBroadcastingReductionsNorm partial reductions \endlink.
-  *
-  * \sa norm()
-  */
-template<typename Derived>
-template<int p>
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
-#else
-MatrixBase<Derived>::RealScalar
-#endif
-MatrixBase<Derived>::lpNorm() const
-{
-  return internal::lpNorm_selector<Derived, p>::run(*this);
-}
-
-//---------- implementation of isOrthogonal / isUnitary ----------
-
-/** \returns true if *this is approximately orthogonal to \a other,
-  *          within the precision given by \a prec.
-  *
-  * Example: \include MatrixBase_isOrthogonal.cpp
-  * Output: \verbinclude MatrixBase_isOrthogonal.out
-  */
-template<typename Derived>
-template<typename OtherDerived>
-bool MatrixBase<Derived>::isOrthogonal
-(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
-{
-  typename internal::nested_eval<Derived,2>::type nested(derived());
-  typename internal::nested_eval<OtherDerived,2>::type otherNested(other.derived());
-  return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
-}
-
-/** \returns true if *this is approximately an unitary matrix,
-  *          within the precision given by \a prec. In the case where the \a Scalar
-  *          type is real numbers, a unitary matrix is an orthogonal matrix, whence the name.
-  *
-  * \note This can be used to check whether a family of vectors forms an orthonormal basis.
-  *       Indeed, \c m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an
-  *       orthonormal basis.
-  *
-  * Example: \include MatrixBase_isUnitary.cpp
-  * Output: \verbinclude MatrixBase_isUnitary.out
-  */
-template<typename Derived>
-bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
-{
-  typename internal::nested_eval<Derived,1>::type self(derived());
-  for(Index i = 0; i < cols(); ++i)
-  {
-    if(!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
-      return false;
-    for(Index j = 0; j < i; ++j)
-      if(!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast<Scalar>(1), prec))
-        return false;
-  }
-  return true;
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_DOT_H

deps_src/eigen/Eigen/src/Core/EigenBase.h

@@ -1,159 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_EIGENBASE_H
-#define EIGEN_EIGENBASE_H
-
-namespace Eigen {
-
-/** \class EigenBase
-  * \ingroup Core_Module
-  * 
-  * Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
-  *
-  * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
-  *
-  * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc.
-  *
-  * Notice that this class is trivial, it is only used to disambiguate overloaded functions.
-  *
-  * \sa \blank \ref TopicClassHierarchy
-  */
-template<typename Derived> struct EigenBase
-{
-//   typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
-  
-  /** \brief The interface type of indices
-    * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
-    * \deprecated Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead.
-    * \sa StorageIndex, \ref TopicPreprocessorDirectives.
-    */
-  typedef Eigen::Index Index;
-
-  // FIXME is it needed?
-  typedef typename internal::traits<Derived>::StorageKind StorageKind;
-
-  /** \returns a reference to the derived object */
-  EIGEN_DEVICE_FUNC
-  Derived& derived() { return *static_cast<Derived*>(this); }
-  /** \returns a const reference to the derived object */
-  EIGEN_DEVICE_FUNC
-  const Derived& derived() const { return *static_cast<const Derived*>(this); }
-
-  EIGEN_DEVICE_FUNC
-  inline Derived& const_cast_derived() const
-  { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
-  EIGEN_DEVICE_FUNC
-  inline const Derived& const_derived() const
-  { return *static_cast<const Derived*>(this); }
-
-  /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
-  EIGEN_DEVICE_FUNC
-  inline Index rows() const { return derived().rows(); }
-  /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
-  EIGEN_DEVICE_FUNC
-  inline Index cols() const { return derived().cols(); }
-  /** \returns the number of coefficients, which is rows()*cols().
-    * \sa rows(), cols(), SizeAtCompileTime. */
-  EIGEN_DEVICE_FUNC
-  inline Index size() const { return rows() * cols(); }
-
-  /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
-  template<typename Dest>
-  EIGEN_DEVICE_FUNC
-  inline void evalTo(Dest& dst) const
-  { derived().evalTo(dst); }
-
-  /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
-  template<typename Dest>
-  EIGEN_DEVICE_FUNC
-  inline void addTo(Dest& dst) const
-  {
-    // This is the default implementation,
-    // derived class can reimplement it in a more optimized way.
-    typename Dest::PlainObject res(rows(),cols());
-    evalTo(res);
-    dst += res;
-  }
-
-  /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
-  template<typename Dest>
-  EIGEN_DEVICE_FUNC
-  inline void subTo(Dest& dst) const
-  {
-    // This is the default implementation,
-    // derived class can reimplement it in a more optimized way.
-    typename Dest::PlainObject res(rows(),cols());
-    evalTo(res);
-    dst -= res;
-  }
-
-  /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
-  template<typename Dest>
-  EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const
-  {
-    // This is the default implementation,
-    // derived class can reimplement it in a more optimized way.
-    dst = dst * this->derived();
-  }
-
-  /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
-  template<typename Dest>
-  EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const
-  {
-    // This is the default implementation,
-    // derived class can reimplement it in a more optimized way.
-    dst = this->derived() * dst;
-  }
-
-};
-
-/***************************************************************************
-* Implementation of matrix base methods
-***************************************************************************/
-
-/** \brief Copies the generic expression \a other into *this.
-  *
-  * \details The expression must provide a (templated) evalTo(Derived& dst) const
-  * function which does the actual job. In practice, this allows any user to write
-  * its own special matrix without having to modify MatrixBase
-  *
-  * \returns a reference to *this.
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
-{
-  call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
-{
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_DEVICE_FUNC
-Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
-{
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
-  return derived();
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_EIGENBASE_H

deps_src/eigen/Eigen/src/Core/ForceAlignedAccess.h

@@ -1,146 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_FORCEALIGNEDACCESS_H
-#define EIGEN_FORCEALIGNEDACCESS_H
-
-namespace Eigen {
-
-/** \class ForceAlignedAccess
-  * \ingroup Core_Module
-  *
-  * \brief Enforce aligned packet loads and stores regardless of what is requested
-  *
-  * \param ExpressionType the type of the object of which we are forcing aligned packet access
-  *
-  * This class is the return type of MatrixBase::forceAlignedAccess()
-  * and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::forceAlignedAccess()
-  */
-
-namespace internal {
-template<typename ExpressionType>
-struct traits<ForceAlignedAccess<ExpressionType> > : public traits<ExpressionType>
-{};
-}
-
-template<typename ExpressionType> class ForceAlignedAccess
-  : public internal::dense_xpr_base< ForceAlignedAccess<ExpressionType> >::type
-{
-  public:
-
-    typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess)
-
-    EIGEN_DEVICE_FUNC explicit inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
-
-    EIGEN_DEVICE_FUNC inline Index rows() const { return m_expression.rows(); }
-    EIGEN_DEVICE_FUNC inline Index cols() const { return m_expression.cols(); }
-    EIGEN_DEVICE_FUNC inline Index outerStride() const { return m_expression.outerStride(); }
-    EIGEN_DEVICE_FUNC inline Index innerStride() const { return m_expression.innerStride(); }
-
-    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const
-    {
-      return m_expression.coeff(row, col);
-    }
-
-    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col)
-    {
-      return m_expression.const_cast_derived().coeffRef(row, col);
-    }
-
-    EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const
-    {
-      return m_expression.coeff(index);
-    }
-
-    EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index)
-    {
-      return m_expression.const_cast_derived().coeffRef(index);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
-    {
-      return m_expression.template packet<Aligned>(row, col);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
-    {
-      m_expression.const_cast_derived().template writePacket<Aligned>(row, col, x);
-    }
-
-    template<int LoadMode>
-    inline const PacketScalar packet(Index index) const
-    {
-      return m_expression.template packet<Aligned>(index);
-    }
-
-    template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
-    {
-      m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
-    }
-
-    EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; }
-
-  protected:
-    const ExpressionType& m_expression;
-
-  private:
-    ForceAlignedAccess& operator=(const ForceAlignedAccess&);
-};
-
-/** \returns an expression of *this with forced aligned access
-  * \sa forceAlignedAccessIf(),class ForceAlignedAccess
-  */
-template<typename Derived>
-inline const ForceAlignedAccess<Derived>
-MatrixBase<Derived>::forceAlignedAccess() const
-{
-  return ForceAlignedAccess<Derived>(derived());
-}
-
-/** \returns an expression of *this with forced aligned access
-  * \sa forceAlignedAccessIf(), class ForceAlignedAccess
-  */
-template<typename Derived>
-inline ForceAlignedAccess<Derived>
-MatrixBase<Derived>::forceAlignedAccess()
-{
-  return ForceAlignedAccess<Derived>(derived());
-}
-
-/** \returns an expression of *this with forced aligned access if \a Enable is true.
-  * \sa forceAlignedAccess(), class ForceAlignedAccess
-  */
-template<typename Derived>
-template<bool Enable>
-inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
-MatrixBase<Derived>::forceAlignedAccessIf() const
-{
-  return derived();  // FIXME This should not work but apparently is never used
-}
-
-/** \returns an expression of *this with forced aligned access if \a Enable is true.
-  * \sa forceAlignedAccess(), class ForceAlignedAccess
-  */
-template<typename Derived>
-template<bool Enable>
-inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
-MatrixBase<Derived>::forceAlignedAccessIf()
-{
-  return derived();  // FIXME This should not work but apparently is never used
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_FORCEALIGNEDACCESS_H

deps_src/eigen/Eigen/src/Core/Fuzzy.h

@@ -1,155 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_FUZZY_H
-#define EIGEN_FUZZY_H
-
-namespace Eigen { 
-
-namespace internal
-{
-
-template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
-struct isApprox_selector
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
-  {
-    typename internal::nested_eval<Derived,2>::type nested(x);
-    typename internal::nested_eval<OtherDerived,2>::type otherNested(y);
-    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
-  }
-};
-
-template<typename Derived, typename OtherDerived>
-struct isApprox_selector<Derived, OtherDerived, true>
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
-  {
-    return x.matrix() == y.matrix();
-  }
-};
-
-template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
-struct isMuchSmallerThan_object_selector
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
-  {
-    return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum();
-  }
-};
-
-template<typename Derived, typename OtherDerived>
-struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
-  {
-    return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
-  }
-};
-
-template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
-struct isMuchSmallerThan_scalar_selector
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
-  {
-    return x.cwiseAbs2().sum() <= numext::abs2(prec * y);
-  }
-};
-
-template<typename Derived>
-struct isMuchSmallerThan_scalar_selector<Derived, true>
-{
-  EIGEN_DEVICE_FUNC
-  static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
-  {
-    return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
-  }
-};
-
-} // end namespace internal
-
-
-/** \returns \c true if \c *this is approximately equal to \a other, within the precision
-  * determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$
-  * are considered to be approximately equal within precision \f$ p \f$ if
-  * \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f]
-  * For matrices, the comparison is done using the Hilbert-Schmidt norm (aka Frobenius norm
-  * L2 norm).
-  *
-  * \note Because of the multiplicativeness of this comparison, one can't use this function
-  * to check whether \c *this is approximately equal to the zero matrix or vector.
-  * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix
-  * or vector. If you want to test whether \c *this is zero, use internal::isMuchSmallerThan(const
-  * RealScalar&, RealScalar) instead.
-  *
-  * \sa internal::isMuchSmallerThan(const RealScalar&, RealScalar) const
-  */
-template<typename Derived>
-template<typename OtherDerived>
-bool DenseBase<Derived>::isApprox(
-  const DenseBase<OtherDerived>& other,
-  const RealScalar& prec
-) const
-{
-  return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
-}
-
-/** \returns \c true if the norm of \c *this is much smaller than \a other,
-  * within the precision determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
-  * considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if
-  * \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f]
-  *
-  * For matrices, the comparison is done using the Hilbert-Schmidt norm. For this reason,
-  * the value of the reference scalar \a other should come from the Hilbert-Schmidt norm
-  * of a reference matrix of same dimensions.
-  *
-  * \sa isApprox(), isMuchSmallerThan(const DenseBase<OtherDerived>&, RealScalar) const
-  */
-template<typename Derived>
-bool DenseBase<Derived>::isMuchSmallerThan(
-  const typename NumTraits<Scalar>::Real& other,
-  const RealScalar& prec
-) const
-{
-  return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec);
-}
-
-/** \returns \c true if the norm of \c *this is much smaller than the norm of \a other,
-  * within the precision determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
-  * considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if
-  * \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f]
-  * For matrices, the comparison is done using the Hilbert-Schmidt norm.
-  *
-  * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const
-  */
-template<typename Derived>
-template<typename OtherDerived>
-bool DenseBase<Derived>::isMuchSmallerThan(
-  const DenseBase<OtherDerived>& other,
-  const RealScalar& prec
-) const
-{
-  return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_FUZZY_H

deps_src/eigen/Eigen/src/Core/GeneralProduct.h

@@ -1,455 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GENERAL_PRODUCT_H
-#define EIGEN_GENERAL_PRODUCT_H
-
-namespace Eigen {
-
-enum {
-  Large = 2,
-  Small = 3
-};
-
-namespace internal {
-
-template<int Rows, int Cols, int Depth> struct product_type_selector;
-
-template<int Size, int MaxSize> struct product_size_category
-{
-  enum {
-    #ifndef EIGEN_CUDA_ARCH
-    is_large = MaxSize == Dynamic ||
-               Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD ||
-               (Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD),
-    #else
-    is_large = 0,
-    #endif
-    value = is_large  ? Large
-          : Size == 1 ? 1
-                      : Small
-  };
-};
-
-template<typename Lhs, typename Rhs> struct product_type
-{
-  typedef typename remove_all<Lhs>::type _Lhs;
-  typedef typename remove_all<Rhs>::type _Rhs;
-  enum {
-    MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
-    Rows    = traits<_Lhs>::RowsAtCompileTime,
-    MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
-    Cols    = traits<_Rhs>::ColsAtCompileTime,
-    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime,
-                                           traits<_Rhs>::MaxRowsAtCompileTime),
-    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime,
-                                        traits<_Rhs>::RowsAtCompileTime)
-  };
-
-  // the splitting into different lines of code here, introducing the _select enums and the typedef below,
-  // is to work around an internal compiler error with gcc 4.1 and 4.2.
-private:
-  enum {
-    rows_select = product_size_category<Rows,MaxRows>::value,
-    cols_select = product_size_category<Cols,MaxCols>::value,
-    depth_select = product_size_category<Depth,MaxDepth>::value
-  };
-  typedef product_type_selector<rows_select, cols_select, depth_select> selector;
-
-public:
-  enum {
-    value = selector::ret,
-    ret = selector::ret
-  };
-#ifdef EIGEN_DEBUG_PRODUCT
-  static void debug()
-  {
-      EIGEN_DEBUG_VAR(Rows);
-      EIGEN_DEBUG_VAR(Cols);
-      EIGEN_DEBUG_VAR(Depth);
-      EIGEN_DEBUG_VAR(rows_select);
-      EIGEN_DEBUG_VAR(cols_select);
-      EIGEN_DEBUG_VAR(depth_select);
-      EIGEN_DEBUG_VAR(value);
-  }
-#endif
-};
-
-/* The following allows to select the kind of product at compile time
- * based on the three dimensions of the product.
- * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
-// FIXME I'm not sure the current mapping is the ideal one.
-template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
-template<int M>         struct product_type_selector<M, 1, 1>            { enum { ret = LazyCoeffBasedProductMode }; };
-template<int N>         struct product_type_selector<1, N, 1>            { enum { ret = LazyCoeffBasedProductMode }; };
-template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
-template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
-template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small, Large, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Large,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Large,Large>  { enum { ret = GemvProduct }; };
-template<>              struct product_type_selector<1,    Small,Large>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large,1,    Large>  { enum { ret = GemvProduct }; };
-template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
-
-} // end namespace internal
-
-/***********************************************************************
-*  Implementation of Inner Vector Vector Product
-***********************************************************************/
-
-// FIXME : maybe the "inner product" could return a Scalar
-// instead of a 1x1 matrix ??
-// Pro: more natural for the user
-// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
-// product ends up to a row-vector times col-vector product... To tackle this use
-// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
-
-/***********************************************************************
-*  Implementation of Outer Vector Vector Product
-***********************************************************************/
-
-/***********************************************************************
-*  Implementation of General Matrix Vector Product
-***********************************************************************/
-
-/*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
- *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
- *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
- *   3 - all other cases are handled using a simple loop along the outer-storage direction.
- *  Therefore we need a lower level meta selector.
- *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
- */
-namespace internal {
-
-template<int Side, int StorageOrder, bool BlasCompatible>
-struct gemv_dense_selector;
-
-} // end namespace internal
-
-namespace internal {
-
-template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
-
-template<typename Scalar,int Size,int MaxSize>
-struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
-{
-  EIGEN_STRONG_INLINE  Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
-};
-
-template<typename Scalar,int Size>
-struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
-{
-  EIGEN_STRONG_INLINE Scalar* data() { return 0; }
-};
-
-template<typename Scalar,int Size,int MaxSize>
-struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
-{
-  enum {
-    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
-    PacketSize      = internal::packet_traits<Scalar>::size
-  };
-  #if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0,EIGEN_PLAIN_ENUM_MIN(AlignedMax,PacketSize)> m_data;
-  EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
-  #else
-  // Some architectures cannot align on the stack,
-  // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0),0> m_data;
-  EIGEN_STRONG_INLINE Scalar* data() {
-    return ForceAlignment
-            ? reinterpret_cast<Scalar*>((internal::UIntPtr(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES)
-            : m_data.array;
-  }
-  #endif
-};
-
-// The vector is on the left => transposition
-template<int StorageOrder, bool BlasCompatible>
-struct gemv_dense_selector<OnTheLeft,StorageOrder,BlasCompatible>
-{
-  template<typename Lhs, typename Rhs, typename Dest>
-  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
-  {
-    Transpose<Dest> destT(dest);
-    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
-    gemv_dense_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
-      ::run(rhs.transpose(), lhs.transpose(), destT, alpha);
-  }
-};
-
-template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
-{
-  template<typename Lhs, typename Rhs, typename Dest>
-  static inline void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
-  {
-    typedef typename Lhs::Scalar   LhsScalar;
-    typedef typename Rhs::Scalar   RhsScalar;
-    typedef typename Dest::Scalar  ResScalar;
-    typedef typename Dest::RealScalar  RealScalar;
-    
-    typedef internal::blas_traits<Lhs> LhsBlasTraits;
-    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
-    typedef internal::blas_traits<Rhs> RhsBlasTraits;
-    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
-  
-    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
-
-    ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
-    ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
-                                  * RhsBlasTraits::extractScalarFactor(rhs);
-
-    // make sure Dest is a compile-time vector type (bug 1166)
-    typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest;
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime==1),
-      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
-      MightCannotUseDest = (!EvalToDestAtCompileTime) || ComplexByReal
-    };
-
-    typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper;
-    typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper;
-    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
-
-    if(!MightCannotUseDest)
-    {
-      // shortcut if we are sure to be able to use dest directly,
-      // this ease the compiler to generate cleaner and more optimzized code for most common cases
-      general_matrix_vector_product
-          <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
-          actualLhs.rows(), actualLhs.cols(),
-          LhsMapper(actualLhs.data(), actualLhs.outerStride()),
-          RhsMapper(actualRhs.data(), actualRhs.innerStride()),
-          dest.data(), 1,
-          compatibleAlpha);
-    }
-    else
-    {
-      gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
-
-      const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
-      const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
-
-      ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
-                                                    evalToDest ? dest.data() : static_dest.data());
-
-      if(!evalToDest)
-      {
-        #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-        Index size = dest.size();
-        EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-        #endif
-        if(!alphaIsCompatible)
-        {
-          MappedDest(actualDestPtr, dest.size()).setZero();
-          compatibleAlpha = RhsScalar(1);
-        }
-        else
-          MappedDest(actualDestPtr, dest.size()) = dest;
-      }
-
-      general_matrix_vector_product
-          <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
-          actualLhs.rows(), actualLhs.cols(),
-          LhsMapper(actualLhs.data(), actualLhs.outerStride()),
-          RhsMapper(actualRhs.data(), actualRhs.innerStride()),
-          actualDestPtr, 1,
-          compatibleAlpha);
-
-      if (!evalToDest)
-      {
-        if(!alphaIsCompatible)
-          dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size());
-        else
-          dest = MappedDest(actualDestPtr, dest.size());
-      }
-    }
-  }
-};
-
-template<> struct gemv_dense_selector<OnTheRight,RowMajor,true>
-{
-  template<typename Lhs, typename Rhs, typename Dest>
-  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
-  {
-    typedef typename Lhs::Scalar   LhsScalar;
-    typedef typename Rhs::Scalar   RhsScalar;
-    typedef typename Dest::Scalar  ResScalar;
-    
-    typedef internal::blas_traits<Lhs> LhsBlasTraits;
-    typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
-    typedef internal::blas_traits<Rhs> RhsBlasTraits;
-    typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
-    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
-
-    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
-    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs)
-                                  * RhsBlasTraits::extractScalarFactor(rhs);
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1
-    };
-
-    gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
-
-    ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
-        DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
-
-    if(!DirectlyUseRhs)
-    {
-      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      Index size = actualRhs.size();
-      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      #endif
-      Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
-    }
-
-    typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper;
-    typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper;
-    general_matrix_vector_product
-        <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run(
-        actualLhs.rows(), actualLhs.cols(),
-        LhsMapper(actualLhs.data(), actualLhs.outerStride()),
-        RhsMapper(actualRhsPtr, 1),
-        dest.data(), dest.col(0).innerStride(), //NOTE  if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
-        actualAlpha);
-  }
-};
-
-template<> struct gemv_dense_selector<OnTheRight,ColMajor,false>
-{
-  template<typename Lhs, typename Rhs, typename Dest>
-  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
-  {
-    EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
-    // TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, otherwise use a temp
-    typename nested_eval<Rhs,1>::type actual_rhs(rhs);
-    const Index size = rhs.rows();
-    for(Index k=0; k<size; ++k)
-      dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k);
-  }
-};
-
-template<> struct gemv_dense_selector<OnTheRight,RowMajor,false>
-{
-  template<typename Lhs, typename Rhs, typename Dest>
-  static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha)
-  {
-    EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
-    typename nested_eval<Rhs,Lhs::RowsAtCompileTime>::type actual_rhs(rhs);
-    const Index rows = dest.rows();
-    for(Index i=0; i<rows; ++i)
-      dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
-  }
-};
-
-} // end namespace internal
-
-/***************************************************************************
-* Implementation of matrix base methods
-***************************************************************************/
-
-/** \returns the matrix product of \c *this and \a other.
-  *
-  * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
-  *
-  * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-inline const Product<Derived, OtherDerived>
-MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
-{
-  // A note regarding the function declaration: In MSVC, this function will sometimes
-  // not be inlined since DenseStorage is an unwindable object for dynamic
-  // matrices and product types are holding a member to store the result.
-  // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
-  enum {
-    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
-                   || OtherDerived::RowsAtCompileTime==Dynamic
-                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
-    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
-    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  };
-  // note to the lost user:
-  //    * for a dot product use: v1.dot(v2)
-  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
-    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
-    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
-  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
-#ifdef EIGEN_DEBUG_PRODUCT
-  internal::product_type<Derived,OtherDerived>::debug();
-#endif
-
-  return Product<Derived, OtherDerived>(derived(), other.derived());
-}
-
-/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
-  *
-  * The returned product will behave like any other expressions: the coefficients of the product will be
-  * computed once at a time as requested. This might be useful in some extremely rare cases when only
-  * a small and no coherent fraction of the result's coefficients have to be computed.
-  *
-  * \warning This version of the matrix product can be much much slower. So use it only if you know
-  * what you are doing and that you measured a true speed improvement.
-  *
-  * \sa operator*(const MatrixBase&)
-  */
-template<typename Derived>
-template<typename OtherDerived>
-const Product<Derived,OtherDerived,LazyProduct>
-MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
-{
-  enum {
-    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
-                   || OtherDerived::RowsAtCompileTime==Dynamic
-                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
-    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
-    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  };
-  // note to the lost user:
-  //    * for a dot product use: v1.dot(v2)
-  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
-    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
-    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
-  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
-
-  return Product<Derived,OtherDerived,LazyProduct>(derived(), other.derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_PRODUCT_H

deps_src/eigen/Eigen/src/Core/GenericPacketMath.h

@@ -1,593 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GENERIC_PACKET_MATH_H
-#define EIGEN_GENERIC_PACKET_MATH_H
-
-namespace Eigen {
-
-namespace internal {
-
-/** \internal
-  * \file GenericPacketMath.h
-  *
-  * Default implementation for types not supported by the vectorization.
-  * In practice these functions are provided to make easier the writing
-  * of generic vectorized code.
-  */
-
-#ifndef EIGEN_DEBUG_ALIGNED_LOAD
-#define EIGEN_DEBUG_ALIGNED_LOAD
-#endif
-
-#ifndef EIGEN_DEBUG_UNALIGNED_LOAD
-#define EIGEN_DEBUG_UNALIGNED_LOAD
-#endif
-
-#ifndef EIGEN_DEBUG_ALIGNED_STORE
-#define EIGEN_DEBUG_ALIGNED_STORE
-#endif
-
-#ifndef EIGEN_DEBUG_UNALIGNED_STORE
-#define EIGEN_DEBUG_UNALIGNED_STORE
-#endif
-
-struct default_packet_traits
-{
-  enum {
-    HasHalfPacket = 0,
-
-    HasAdd    = 1,
-    HasSub    = 1,
-    HasMul    = 1,
-    HasNegate = 1,
-    HasAbs    = 1,
-    HasArg    = 0,
-    HasAbs2   = 1,
-    HasMin    = 1,
-    HasMax    = 1,
-    HasConj   = 1,
-    HasSetLinear = 1,
-    HasBlend  = 0,
-
-    HasDiv    = 0,
-    HasSqrt   = 0,
-    HasRsqrt  = 0,
-    HasExp    = 0,
-    HasLog    = 0,
-    HasLog1p  = 0,
-    HasLog10  = 0,
-    HasPow    = 0,
-
-    HasSin    = 0,
-    HasCos    = 0,
-    HasTan    = 0,
-    HasASin   = 0,
-    HasACos   = 0,
-    HasATan   = 0,
-    HasSinh   = 0,
-    HasCosh   = 0,
-    HasTanh   = 0,
-    HasLGamma = 0,
-    HasDiGamma = 0,
-    HasZeta = 0,
-    HasPolygamma = 0,
-    HasErf = 0,
-    HasErfc = 0,
-    HasIGamma = 0,
-    HasIGammac = 0,
-    HasBetaInc = 0,
-
-    HasRound  = 0,
-    HasFloor  = 0,
-    HasCeil   = 0,
-
-    HasSign   = 0
-  };
-};
-
-template<typename T> struct packet_traits : default_packet_traits
-{
-  typedef T type;
-  typedef T half;
-  enum {
-    Vectorizable = 0,
-    size = 1,
-    AlignedOnScalar = 0,
-    HasHalfPacket = 0
-  };
-  enum {
-    HasAdd    = 0,
-    HasSub    = 0,
-    HasMul    = 0,
-    HasNegate = 0,
-    HasAbs    = 0,
-    HasAbs2   = 0,
-    HasMin    = 0,
-    HasMax    = 0,
-    HasConj   = 0,
-    HasSetLinear = 0
-  };
-};
-
-template<typename T> struct packet_traits<const T> : packet_traits<T> { };
-
-template <typename Src, typename Tgt> struct type_casting_traits {
-  enum {
-    VectorizedCast = 0,
-    SrcCoeffRatio = 1,
-    TgtCoeffRatio = 1
-  };
-};
-
-
-/** \internal \returns static_cast<TgtType>(a) (coeff-wise) */
-template <typename SrcPacket, typename TgtPacket>
-EIGEN_DEVICE_FUNC inline TgtPacket
-pcast(const SrcPacket& a) {
-  return static_cast<TgtPacket>(a);
-}
-template <typename SrcPacket, typename TgtPacket>
-EIGEN_DEVICE_FUNC inline TgtPacket
-pcast(const SrcPacket& a, const SrcPacket& /*b*/) {
-  return static_cast<TgtPacket>(a);
-}
-
-template <typename SrcPacket, typename TgtPacket>
-EIGEN_DEVICE_FUNC inline TgtPacket
-pcast(const SrcPacket& a, const SrcPacket& /*b*/, const SrcPacket& /*c*/, const SrcPacket& /*d*/) {
-  return static_cast<TgtPacket>(a);
-}
-
-/** \internal \returns a + b (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-padd(const Packet& a,
-        const Packet& b) { return a+b; }
-
-/** \internal \returns a - b (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-psub(const Packet& a,
-        const Packet& b) { return a-b; }
-
-/** \internal \returns -a (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pnegate(const Packet& a) { return -a; }
-
-/** \internal \returns conj(a) (coeff-wise) */
-
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pconj(const Packet& a) { return numext::conj(a); }
-
-/** \internal \returns a * b (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pmul(const Packet& a,
-        const Packet& b) { return a*b; }
-
-/** \internal \returns a / b (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pdiv(const Packet& a,
-        const Packet& b) { return a/b; }
-
-/** \internal \returns the min of \a a and \a b  (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pmin(const Packet& a,
-        const Packet& b) { return numext::mini(a, b); }
-
-/** \internal \returns the max of \a a and \a b  (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pmax(const Packet& a,
-        const Packet& b) { return numext::maxi(a, b); }
-
-/** \internal \returns the absolute value of \a a */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pabs(const Packet& a) { using std::abs; return abs(a); }
-
-/** \internal \returns the phase angle of \a a */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-parg(const Packet& a) { using numext::arg; return arg(a); }
-
-/** \internal \returns the bitwise and of \a a and \a b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pand(const Packet& a, const Packet& b) { return a & b; }
-
-/** \internal \returns the bitwise or of \a a and \a b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-por(const Packet& a, const Packet& b) { return a | b; }
-
-/** \internal \returns the bitwise xor of \a a and \a b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pxor(const Packet& a, const Packet& b) { return a ^ b; }
-
-/** \internal \returns the bitwise andnot of \a a and \a b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pandnot(const Packet& a, const Packet& b) { return a & (!b); }
-
-/** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
-
-/** \internal \returns a packet version of \a *from, (un-aligned load) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-ploadu(const typename unpacket_traits<Packet>::type* from) { return *from; }
-
-/** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
-
-/** \internal \returns a packet with constant coefficients \a a[0], e.g.: (a[0],a[0],a[0],a[0]) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pload1(const typename unpacket_traits<Packet>::type  *a) { return pset1<Packet>(*a); }
-
-/** \internal \returns a packet with elements of \a *from duplicated.
-  * For instance, for a packet of 8 elements, 4 scalars will be read from \a *from and
-  * duplicated to form: {from[0],from[0],from[1],from[1],from[2],from[2],from[3],from[3]}
-  * Currently, this function is only used for scalar * complex products.
-  */
-template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
-ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
-
-/** \internal \returns a packet with elements of \a *from quadrupled.
-  * For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and
-  * replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]}
-  * Currently, this function is only used in matrix products.
-  * For packet-size smaller or equal to 4, this function is equivalent to pload1 
-  */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-ploadquad(const typename unpacket_traits<Packet>::type* from)
-{ return pload1<Packet>(from); }
-
-/** \internal equivalent to
-  * \code
-  * a0 = pload1(a+0);
-  * a1 = pload1(a+1);
-  * a2 = pload1(a+2);
-  * a3 = pload1(a+3);
-  * \endcode
-  * \sa pset1, pload1, ploaddup, pbroadcast2
-  */
-template<typename Packet> EIGEN_DEVICE_FUNC
-inline void pbroadcast4(const typename unpacket_traits<Packet>::type *a,
-                        Packet& a0, Packet& a1, Packet& a2, Packet& a3)
-{
-  a0 = pload1<Packet>(a+0);
-  a1 = pload1<Packet>(a+1);
-  a2 = pload1<Packet>(a+2);
-  a3 = pload1<Packet>(a+3);
-}
-
-/** \internal equivalent to
-  * \code
-  * a0 = pload1(a+0);
-  * a1 = pload1(a+1);
-  * \endcode
-  * \sa pset1, pload1, ploaddup, pbroadcast4
-  */
-template<typename Packet> EIGEN_DEVICE_FUNC
-inline void pbroadcast2(const typename unpacket_traits<Packet>::type *a,
-                        Packet& a0, Packet& a1)
-{
-  a0 = pload1<Packet>(a+0);
-  a1 = pload1<Packet>(a+1);
-}
-
-/** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
-template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet
-plset(const typename unpacket_traits<Packet>::type& a) { return a; }
-
-/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
-template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from)
-{ (*to) = from; }
-
-/** \internal copy the packet \a from to \a *to, (un-aligned store) */
-template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
-{  (*to) = from; }
-
- template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/)
- { return ploadu<Packet>(from); }
-
- template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/)
- { pstore(to, from); }
-
-/** \internal tries to do cache prefetching of \a addr */
-template<typename Scalar> EIGEN_DEVICE_FUNC inline void prefetch(const Scalar* addr)
-{
-#ifdef __CUDA_ARCH__
-#if defined(__LP64__)
-  // 64-bit pointer operand constraint for inlined asm
-  asm(" prefetch.L1 [ %1 ];" : "=l"(addr) : "l"(addr));
-#else
-  // 32-bit pointer operand constraint for inlined asm
-  asm(" prefetch.L1 [ %1 ];" : "=r"(addr) : "r"(addr));
-#endif
-#elif (!EIGEN_COMP_MSVC) && (EIGEN_COMP_GNUC || EIGEN_COMP_CLANG || EIGEN_COMP_ICC)
-  __builtin_prefetch(addr);
-#endif
-}
-
-/** \internal \returns the first element of a packet */
-template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
-{ return a; }
-
-/** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-preduxp(const Packet* vecs) { return vecs[0]; }
-
-/** \internal \returns the sum of the elements of \a a*/
-template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux(const Packet& a)
-{ return a; }
-
-/** \internal \returns the sum of the elements of \a a by block of 4 elements.
-  * For a packet {a0, a1, a2, a3, a4, a5, a6, a7}, it returns a half packet {a0+a4, a1+a5, a2+a6, a3+a7}
-  * For packet-size smaller or equal to 4, this boils down to a noop.
-  */
-template<typename Packet> EIGEN_DEVICE_FUNC inline
-typename conditional<(unpacket_traits<Packet>::size%8)==0,typename unpacket_traits<Packet>::half,Packet>::type
-predux_downto4(const Packet& a)
-{ return a; }
-
-/** \internal \returns the product of the elements of \a a*/
-template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
-{ return a; }
-
-/** \internal \returns the min of the elements of \a a*/
-template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
-{ return a; }
-
-/** \internal \returns the max of the elements of \a a*/
-template<typename Packet> EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
-{ return a; }
-
-/** \internal \returns the reversed elements of \a a*/
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet preverse(const Packet& a)
-{ return a; }
-
-/** \internal \returns \a a with real and imaginary part flipped (for complex type only) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet& a)
-{
-  // FIXME: uncomment the following in case we drop the internal imag and real functions.
-//   using std::imag;
-//   using std::real;
-  return Packet(imag(a),real(a));
-}
-
-/**************************
-* Special math functions
-***************************/
-
-/** \internal \returns the sine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet psin(const Packet& a) { using std::sin; return sin(a); }
-
-/** \internal \returns the cosine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pcos(const Packet& a) { using std::cos; return cos(a); }
-
-/** \internal \returns the tan of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet ptan(const Packet& a) { using std::tan; return tan(a); }
-
-/** \internal \returns the arc sine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pasin(const Packet& a) { using std::asin; return asin(a); }
-
-/** \internal \returns the arc cosine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pacos(const Packet& a) { using std::acos; return acos(a); }
-
-/** \internal \returns the arc tangent of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet patan(const Packet& a) { using std::atan; return atan(a); }
-
-/** \internal \returns the hyperbolic sine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet psinh(const Packet& a) { using std::sinh; return sinh(a); }
-
-/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pcosh(const Packet& a) { using std::cosh; return cosh(a); }
-
-/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet ptanh(const Packet& a) { using std::tanh; return tanh(a); }
-
-/** \internal \returns the exp of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pexp(const Packet& a) { using std::exp; return exp(a); }
-
-/** \internal \returns the log of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet plog(const Packet& a) { using std::log; return log(a); }
-
-/** \internal \returns the log1p of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet plog1p(const Packet& a) { return numext::log1p(a); }
-
-/** \internal \returns the log10 of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet plog10(const Packet& a) { using std::log10; return log10(a); }
-
-/** \internal \returns the square-root of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); }
-
-/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet prsqrt(const Packet& a) {
-  return pdiv(pset1<Packet>(1), psqrt(a));
-}
-
-/** \internal \returns the rounded value of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pround(const Packet& a) { using numext::round; return round(a); }
-
-/** \internal \returns the floor of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pfloor(const Packet& a) { using numext::floor; return floor(a); }
-
-/** \internal \returns the ceil of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
-
-/***************************************************************************
-* The following functions might not have to be overwritten for vectorized types
-***************************************************************************/
-
-/** \internal copy a packet with constant coeficient \a a (e.g., [a,a,a,a]) to \a *to. \a to must be 16 bytes aligned */
-// NOTE: this function must really be templated on the packet type (think about different packet types for the same scalar type)
-template<typename Packet>
-inline void pstore1(typename unpacket_traits<Packet>::type* to, const typename unpacket_traits<Packet>::type& a)
-{
-  pstore(to, pset1<Packet>(a));
-}
-
-/** \internal \returns a * b + c (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pmadd(const Packet&  a,
-         const Packet&  b,
-         const Packet&  c)
-{ return padd(pmul(a, b),c); }
-
-/** \internal \returns a packet version of \a *from.
-  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
-template<typename Packet, int Alignment>
-EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_traits<Packet>::type* from)
-{
-  if(Alignment >= unpacket_traits<Packet>::alignment)
-    return pload<Packet>(from);
-  else
-    return ploadu<Packet>(from);
-}
-
-/** \internal copy the packet \a from to \a *to.
-  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
-template<typename Scalar, typename Packet, int Alignment>
-EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& from)
-{
-  if(Alignment >= unpacket_traits<Packet>::alignment)
-    pstore(to, from);
-  else
-    pstoreu(to, from);
-}
-
-/** \internal \returns a packet version of \a *from.
-  * Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the
-  * hardware if available to speedup the loading of data that won't be modified
-  * by the current computation.
-  */
-template<typename Packet, int LoadMode>
-EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_ro(const typename unpacket_traits<Packet>::type* from)
-{
-  return ploadt<Packet, LoadMode>(from);
-}
-
-/** \internal default implementation of palign() allowing partial specialization */
-template<int Offset,typename PacketType>
-struct palign_impl
-{
-  // by default data are aligned, so there is nothing to be done :)
-  static inline void run(PacketType&, const PacketType&) {}
-};
-
-/** \internal update \a first using the concatenation of the packet_size minus \a Offset last elements
-  * of \a first and \a Offset first elements of \a second.
-  * 
-  * This function is currently only used to optimize matrix-vector products on unligned matrices.
-  * It takes 2 packets that represent a contiguous memory array, and returns a packet starting
-  * at the position \a Offset. For instance, for packets of 4 elements, we have:
-  *  Input:
-  *  - first = {f0,f1,f2,f3}
-  *  - second = {s0,s1,s2,s3}
-  * Output: 
-  *   - if Offset==0 then {f0,f1,f2,f3}
-  *   - if Offset==1 then {f1,f2,f3,s0}
-  *   - if Offset==2 then {f2,f3,s0,s1}
-  *   - if Offset==3 then {f3,s0,s1,s3}
-  */
-template<int Offset,typename PacketType>
-inline void palign(PacketType& first, const PacketType& second)
-{
-  palign_impl<Offset,PacketType>::run(first,second);
-}
-
-/***************************************************************************
-* Fast complex products (GCC generates a function call which is very slow)
-***************************************************************************/
-
-// Eigen+CUDA does not support complexes.
-#ifndef __CUDACC__
-
-template<> inline std::complex<float> pmul(const std::complex<float>& a, const std::complex<float>& b)
-{ return std::complex<float>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
-
-template<> inline std::complex<double> pmul(const std::complex<double>& a, const std::complex<double>& b)
-{ return std::complex<double>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
-
-#endif
-
-
-/***************************************************************************
- * PacketBlock, that is a collection of N packets where the number of words
- * in the packet is a multiple of N.
-***************************************************************************/
-template <typename Packet,int N=unpacket_traits<Packet>::size> struct PacketBlock {
-  Packet packet[N];
-};
-
-template<typename Packet> EIGEN_DEVICE_FUNC inline void
-ptranspose(PacketBlock<Packet,1>& /*kernel*/) {
-  // Nothing to do in the scalar case, i.e. a 1x1 matrix.
-}
-
-/***************************************************************************
- * Selector, i.e. vector of N boolean values used to select (i.e. blend)
- * words from 2 packets.
-***************************************************************************/
-template <size_t N> struct Selector {
-  bool select[N];
-};
-
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pblend(const Selector<unpacket_traits<Packet>::size>& ifPacket, const Packet& thenPacket, const Packet& elsePacket) {
-  return ifPacket.select[0] ? thenPacket : elsePacket;
-}
-
-/** \internal \returns \a a with the first coefficient replaced by the scalar b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pinsertfirst(const Packet& a, typename unpacket_traits<Packet>::type b)
-{
-  // Default implementation based on pblend.
-  // It must be specialized for higher performance.
-  Selector<unpacket_traits<Packet>::size> mask;
-  mask.select[0] = true;
-  // This for loop should be optimized away by the compiler.
-  for(Index i=1; i<unpacket_traits<Packet>::size; ++i)
-    mask.select[i] = false;
-  return pblend(mask, pset1<Packet>(b), a);
-}
-
-/** \internal \returns \a a with the last coefficient replaced by the scalar b */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pinsertlast(const Packet& a, typename unpacket_traits<Packet>::type b)
-{
-  // Default implementation based on pblend.
-  // It must be specialized for higher performance.
-  Selector<unpacket_traits<Packet>::size> mask;
-  // This for loop should be optimized away by the compiler.
-  for(Index i=0; i<unpacket_traits<Packet>::size-1; ++i)
-    mask.select[i] = false;
-  mask.select[unpacket_traits<Packet>::size-1] = true;
-  return pblend(mask, pset1<Packet>(b), a);
-}
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_GENERIC_PACKET_MATH_H

deps_src/eigen/Eigen/src/Core/GlobalFunctions.h

@@ -1,187 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GLOBAL_FUNCTIONS_H
-#define EIGEN_GLOBAL_FUNCTIONS_H
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-
-#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR,DOC_OP,DOC_DETAILS) \
-  /** \returns an expression of the coefficient-wise DOC_OP of \a x
-
-    DOC_DETAILS
-
-    \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_##NAME">Math functions</a>, class CwiseUnaryOp
-    */ \
-  template<typename Derived> \
-  inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
-  NAME(const Eigen::ArrayBase<Derived>& x);
-
-#else
-
-#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR,DOC_OP,DOC_DETAILS) \
-  template<typename Derived> \
-  inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
-  (NAME)(const Eigen::ArrayBase<Derived>& x) { \
-    return Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived>(x.derived()); \
-  }
-
-#endif // EIGEN_PARSED_BY_DOXYGEN
-
-#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
-  \
-  template<typename Derived> \
-  struct NAME##_retval<ArrayBase<Derived> > \
-  { \
-    typedef const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> type; \
-  }; \
-  template<typename Derived> \
-  struct NAME##_impl<ArrayBase<Derived> > \
-  { \
-    static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \
-    { \
-      return typename NAME##_retval<ArrayBase<Derived> >::type(x.derived()); \
-    } \
-  };
-
-namespace Eigen
-{
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op,real part,\sa ArrayBase::real)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op,imaginary part,\sa ArrayBase::imag)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op,complex conjugate,\sa ArrayBase::conjugate)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(inverse,scalar_inverse_op,inverse,\sa ArrayBase::inverse)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op,sine,\sa ArrayBase::sin)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op,cosine,\sa ArrayBase::cos)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op,tangent,\sa ArrayBase::tan)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan,scalar_atan_op,arc-tangent,\sa ArrayBase::atan)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op,arc-sine,\sa ArrayBase::asin)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op,arc-consine,\sa ArrayBase::acos)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh,scalar_sinh_op,hyperbolic sine,\sa ArrayBase::sinh)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh,scalar_cosh_op,hyperbolic cosine,\sa ArrayBase::cosh)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh,scalar_tanh_op,hyperbolic tangent,\sa ArrayBase::tanh)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(lgamma,scalar_lgamma_op,natural logarithm of the gamma function,\sa ArrayBase::lgamma)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(digamma,scalar_digamma_op,derivative of lgamma,\sa ArrayBase::digamma)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erf,scalar_erf_op,error function,\sa ArrayBase::erf)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erfc,scalar_erfc_op,complement error function,\sa ArrayBase::erfc)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op,exponential,\sa ArrayBase::exp)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op,natural logarithm,\sa Eigen::log10 DOXCOMMA ArrayBase::log)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log1p,scalar_log1p_op,natural logarithm of 1 plus the value,\sa ArrayBase::log1p)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log10,scalar_log10_op,base 10 logarithm,\sa Eigen::log DOXCOMMA ArrayBase::log)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op,absolute value,\sa ArrayBase::abs DOXCOMMA MatrixBase::cwiseAbs)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs2,scalar_abs2_op,squared absolute value,\sa ArrayBase::abs2 DOXCOMMA MatrixBase::cwiseAbs2)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(arg,scalar_arg_op,complex argument,\sa ArrayBase::arg)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op,square root,\sa ArrayBase::sqrt DOXCOMMA MatrixBase::cwiseSqrt)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(rsqrt,scalar_rsqrt_op,reciprocal square root,\sa ArrayBase::rsqrt)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(square,scalar_square_op,square (power 2),\sa Eigen::abs2 DOXCOMMA Eigen::pow DOXCOMMA ArrayBase::square)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cube,scalar_cube_op,cube (power 3),\sa Eigen::pow DOXCOMMA ArrayBase::cube)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(round,scalar_round_op,nearest integer,\sa Eigen::floor DOXCOMMA Eigen::ceil DOXCOMMA ArrayBase::round)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(floor,scalar_floor_op,nearest integer not greater than the giben value,\sa Eigen::ceil DOXCOMMA ArrayBase::floor)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(ceil,scalar_ceil_op,nearest integer not less than the giben value,\sa Eigen::floor DOXCOMMA ArrayBase::ceil)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isnan,scalar_isnan_op,not-a-number test,\sa Eigen::isinf DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isnan)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isinf,scalar_isinf_op,infinite value test,\sa Eigen::isnan DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isinf)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite,scalar_isfinite_op,finite value test,\sa Eigen::isinf DOXCOMMA Eigen::isnan DOXCOMMA ArrayBase::isfinite)
-  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sign,scalar_sign_op,sign (or 0),\sa ArrayBase::sign)
-  
-  /** \returns an expression of the coefficient-wise power of \a x to the given constant \a exponent.
-    *
-    * \tparam ScalarExponent is the scalar type of \a exponent. It must be compatible with the scalar type of the given expression (\c Derived::Scalar).
-    *
-    * \sa ArrayBase::pow()
-    *
-    * \relates ArrayBase
-    */
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  template<typename Derived,typename ScalarExponent>
-  inline const CwiseBinaryOp<internal::scalar_pow_op<Derived::Scalar,ScalarExponent>,Derived,Constant<ScalarExponent> >
-  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent);
-#else
-  template<typename Derived,typename ScalarExponent>
-  inline typename internal::enable_if<   !(internal::is_same<typename Derived::Scalar,ScalarExponent>::value) && EIGEN_SCALAR_BINARY_SUPPORTED(pow,typename Derived::Scalar,ScalarExponent),
-          const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,ScalarExponent,pow) >::type
-  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent) {
-    return x.derived().pow(exponent);
-  }
-
-  template<typename Derived>
-  inline const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,typename Derived::Scalar,pow)
-  pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) {
-    return x.derived().pow(exponent);
-  }
-#endif
-
-  /** \returns an expression of the coefficient-wise power of \a x to the given array of \a exponents.
-    *
-    * This function computes the coefficient-wise power.
-    *
-    * Example: \include Cwise_array_power_array.cpp
-    * Output: \verbinclude Cwise_array_power_array.out
-    * 
-    * \sa ArrayBase::pow()
-    *
-    * \relates ArrayBase
-    */
-  template<typename Derived,typename ExponentDerived>
-  inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>
-  pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<ExponentDerived>& exponents) 
-  {
-    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar, typename ExponentDerived::Scalar>, const Derived, const ExponentDerived>(
-      x.derived(),
-      exponents.derived()
-    );
-  }
-  
-  /** \returns an expression of the coefficient-wise power of the scalar \a x to the given array of \a exponents.
-    *
-    * This function computes the coefficient-wise power between a scalar and an array of exponents.
-    *
-    * \tparam Scalar is the scalar type of \a x. It must be compatible with the scalar type of the given array expression (\c Derived::Scalar).
-    *
-    * Example: \include Cwise_scalar_power_array.cpp
-    * Output: \verbinclude Cwise_scalar_power_array.out
-    * 
-    * \sa ArrayBase::pow()
-    *
-    * \relates ArrayBase
-    */
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  template<typename Scalar,typename Derived>
-  inline const CwiseBinaryOp<internal::scalar_pow_op<Scalar,Derived::Scalar>,Constant<Scalar>,Derived>
-  pow(const Scalar& x,const Eigen::ArrayBase<Derived>& x);
-#else
-  template<typename Scalar, typename Derived>
-  inline typename internal::enable_if<   !(internal::is_same<typename Derived::Scalar,Scalar>::value) && EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar),
-          const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,Derived,pow) >::type
-  pow(const Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
-  {
-    return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,Derived,pow)(
-            typename internal::plain_constant_type<Derived,Scalar>::type(exponents.rows(), exponents.cols(), x), exponents.derived() );
-  }
-
-  template<typename Derived>
-  inline const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename Derived::Scalar,Derived,pow)
-  pow(const typename Derived::Scalar& x, const Eigen::ArrayBase<Derived>& exponents)
-  {
-    return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename Derived::Scalar,Derived,pow)(
-      typename internal::plain_constant_type<Derived,typename Derived::Scalar>::type(exponents.rows(), exponents.cols(), x), exponents.derived() );
-  }
-#endif
-
-
-  namespace internal
-  {
-    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op)
-    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op)
-    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2,scalar_abs2_op)
-  }
-}
-
-// TODO: cleanly disable those functions that are not supported on Array (numext::real_ref, internal::random, internal::isApprox...)
-
-#endif // EIGEN_GLOBAL_FUNCTIONS_H

deps_src/eigen/Eigen/src/Core/IO.h

@@ -1,225 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_IO_H
-#define EIGEN_IO_H
-
-namespace Eigen { 
-
-enum { DontAlignCols = 1 };
-enum { StreamPrecision = -1,
-       FullPrecision = -2 };
-
-namespace internal {
-template<typename Derived>
-std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt);
-}
-
-/** \class IOFormat
-  * \ingroup Core_Module
-  *
-  * \brief Stores a set of parameters controlling the way matrices are printed
-  *
-  * List of available parameters:
-  *  - \b precision number of digits for floating point values, or one of the special constants \c StreamPrecision and \c FullPrecision.
-  *                 The default is the special value \c StreamPrecision which means to use the
-  *                 stream's own precision setting, as set for instance using \c cout.precision(3). The other special value
-  *                 \c FullPrecision means that the number of digits will be computed to match the full precision of each floating-point
-  *                 type.
-  *  - \b flags an OR-ed combination of flags, the default value is 0, the only currently available flag is \c DontAlignCols which
-  *             allows to disable the alignment of columns, resulting in faster code.
-  *  - \b coeffSeparator string printed between two coefficients of the same row
-  *  - \b rowSeparator string printed between two rows
-  *  - \b rowPrefix string printed at the beginning of each row
-  *  - \b rowSuffix string printed at the end of each row
-  *  - \b matPrefix string printed at the beginning of the matrix
-  *  - \b matSuffix string printed at the end of the matrix
-  *
-  * Example: \include IOFormat.cpp
-  * Output: \verbinclude IOFormat.out
-  *
-  * \sa DenseBase::format(), class WithFormat
-  */
-struct IOFormat
-{
-  /** Default constructor, see class IOFormat for the meaning of the parameters */
-  IOFormat(int _precision = StreamPrecision, int _flags = 0,
-    const std::string& _coeffSeparator = " ",
-    const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="",
-    const std::string& _matPrefix="", const std::string& _matSuffix="")
-  : matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator),
-    rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
-  {
-    // TODO check if rowPrefix, rowSuffix or rowSeparator contains a newline
-    // don't add rowSpacer if columns are not to be aligned
-    if((flags & DontAlignCols))
-      return;
-    int i = int(matSuffix.length())-1;
-    while (i>=0 && matSuffix[i]!='\n')
-    {
-      rowSpacer += ' ';
-      i--;
-    }
-  }
-  std::string matPrefix, matSuffix;
-  std::string rowPrefix, rowSuffix, rowSeparator, rowSpacer;
-  std::string coeffSeparator;
-  int precision;
-  int flags;
-};
-
-/** \class WithFormat
-  * \ingroup Core_Module
-  *
-  * \brief Pseudo expression providing matrix output with given format
-  *
-  * \tparam ExpressionType the type of the object on which IO stream operations are performed
-  *
-  * This class represents an expression with stream operators controlled by a given IOFormat.
-  * It is the return type of DenseBase::format()
-  * and most of the time this is the only way it is used.
-  *
-  * See class IOFormat for some examples.
-  *
-  * \sa DenseBase::format(), class IOFormat
-  */
-template<typename ExpressionType>
-class WithFormat
-{
-  public:
-
-    WithFormat(const ExpressionType& matrix, const IOFormat& format)
-      : m_matrix(matrix), m_format(format)
-    {}
-
-    friend std::ostream & operator << (std::ostream & s, const WithFormat& wf)
-    {
-      return internal::print_matrix(s, wf.m_matrix.eval(), wf.m_format);
-    }
-
-  protected:
-    typename ExpressionType::Nested m_matrix;
-    IOFormat m_format;
-};
-
-namespace internal {
-
-// NOTE: This helper is kept for backward compatibility with previous code specializing
-//       this internal::significant_decimals_impl structure. In the future we should directly
-//       call digits10() which has been introduced in July 2016 in 3.3.
-template<typename Scalar>
-struct significant_decimals_impl
-{
-  static inline int run()
-  {
-    return NumTraits<Scalar>::digits10();
-  }
-};
-
-/** \internal
-  * print the matrix \a _m to the output stream \a s using the output format \a fmt */
-template<typename Derived>
-std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt)
-{
-  if(_m.size() == 0)
-  {
-    s << fmt.matPrefix << fmt.matSuffix;
-    return s;
-  }
-  
-  typename Derived::Nested m = _m;
-  typedef typename Derived::Scalar Scalar;
-
-  Index width = 0;
-
-  std::streamsize explicit_precision;
-  if(fmt.precision == StreamPrecision)
-  {
-    explicit_precision = 0;
-  }
-  else if(fmt.precision == FullPrecision)
-  {
-    if (NumTraits<Scalar>::IsInteger)
-    {
-      explicit_precision = 0;
-    }
-    else
-    {
-      explicit_precision = significant_decimals_impl<Scalar>::run();
-    }
-  }
-  else
-  {
-    explicit_precision = fmt.precision;
-  }
-
-  std::streamsize old_precision = 0;
-  if(explicit_precision) old_precision = s.precision(explicit_precision);
-
-  bool align_cols = !(fmt.flags & DontAlignCols);
-  if(align_cols)
-  {
-    // compute the largest width
-    for(Index j = 0; j < m.cols(); ++j)
-      for(Index i = 0; i < m.rows(); ++i)
-      {
-        std::stringstream sstr;
-        sstr.copyfmt(s);
-        sstr << m.coeff(i,j);
-        width = std::max<Index>(width, Index(sstr.str().length()));
-      }
-  }
-  s << fmt.matPrefix;
-  for(Index i = 0; i < m.rows(); ++i)
-  {
-    if (i)
-      s << fmt.rowSpacer;
-    s << fmt.rowPrefix;
-    if(width) s.width(width);
-    s << m.coeff(i, 0);
-    for(Index j = 1; j < m.cols(); ++j)
-    {
-      s << fmt.coeffSeparator;
-      if (width) s.width(width);
-      s << m.coeff(i, j);
-    }
-    s << fmt.rowSuffix;
-    if( i < m.rows() - 1)
-      s << fmt.rowSeparator;
-  }
-  s << fmt.matSuffix;
-  if(explicit_precision) s.precision(old_precision);
-  return s;
-}
-
-} // end namespace internal
-
-/** \relates DenseBase
-  *
-  * Outputs the matrix, to the given stream.
-  *
-  * If you wish to print the matrix with a format different than the default, use DenseBase::format().
-  *
-  * It is also possible to change the default format by defining EIGEN_DEFAULT_IO_FORMAT before including Eigen headers.
-  * If not defined, this will automatically be defined to Eigen::IOFormat(), that is the Eigen::IOFormat with default parameters.
-  *
-  * \sa DenseBase::format()
-  */
-template<typename Derived>
-std::ostream & operator <<
-(std::ostream & s,
- const DenseBase<Derived> & m)
-{
-  return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_IO_H

deps_src/eigen/Eigen/src/Core/Inverse.h

@@ -1,118 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_INVERSE_H
-#define EIGEN_INVERSE_H
-
-namespace Eigen { 
-
-template<typename XprType,typename StorageKind> class InverseImpl;
-
-namespace internal {
-
-template<typename XprType>
-struct traits<Inverse<XprType> >
-  : traits<typename XprType::PlainObject>
-{
-  typedef typename XprType::PlainObject PlainObject;
-  typedef traits<PlainObject> BaseTraits;
-  enum {
-    Flags = BaseTraits::Flags & RowMajorBit
-  };
-};
-
-} // end namespace internal
-
-/** \class Inverse
-  *
-  * \brief Expression of the inverse of another expression
-  *
-  * \tparam XprType the type of the expression we are taking the inverse
-  *
-  * This class represents an abstract expression of A.inverse()
-  * and most of the time this is the only way it is used.
-  *
-  */
-template<typename XprType>
-class Inverse : public InverseImpl<XprType,typename internal::traits<XprType>::StorageKind>
-{
-public:
-  typedef typename XprType::StorageIndex StorageIndex;
-  typedef typename XprType::PlainObject                       PlainObject;
-  typedef typename XprType::Scalar                            Scalar;
-  typedef typename internal::ref_selector<XprType>::type      XprTypeNested;
-  typedef typename internal::remove_all<XprTypeNested>::type  XprTypeNestedCleaned;
-  typedef typename internal::ref_selector<Inverse>::type Nested;
-  typedef typename internal::remove_all<XprType>::type NestedExpression;
-  
-  explicit EIGEN_DEVICE_FUNC Inverse(const XprType &xpr)
-    : m_xpr(xpr)
-  {}
-
-  EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
-  EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
-
-  EIGEN_DEVICE_FUNC const XprTypeNestedCleaned& nestedExpression() const { return m_xpr; }
-
-protected:
-  XprTypeNested m_xpr;
-};
-
-// Generic API dispatcher
-template<typename XprType, typename StorageKind>
-class InverseImpl
-  : public internal::generic_xpr_base<Inverse<XprType> >::type
-{
-public:
-  typedef typename internal::generic_xpr_base<Inverse<XprType> >::type Base;
-  typedef typename XprType::Scalar Scalar;
-private:
-
-  Scalar coeff(Index row, Index col) const;
-  Scalar coeff(Index i) const;
-};
-
-namespace internal {
-
-/** \internal
-  * \brief Default evaluator for Inverse expression.
-  * 
-  * This default evaluator for Inverse expression simply evaluate the inverse into a temporary
-  * by a call to internal::call_assignment_no_alias.
-  * Therefore, inverse implementers only have to specialize Assignment<Dst,Inverse<...>, ...> for
-  * there own nested expression.
-  *
-  * \sa class Inverse
-  */
-template<typename ArgType>
-struct unary_evaluator<Inverse<ArgType> >
-  : public evaluator<typename Inverse<ArgType>::PlainObject>
-{
-  typedef Inverse<ArgType> InverseType;
-  typedef typename InverseType::PlainObject PlainObject;
-  typedef evaluator<PlainObject> Base;
-  
-  enum { Flags = Base::Flags | EvalBeforeNestingBit };
-
-  unary_evaluator(const InverseType& inv_xpr)
-    : m_result(inv_xpr.rows(), inv_xpr.cols())
-  {
-    ::new (static_cast<Base*>(this)) Base(m_result);
-    internal::call_assignment_no_alias(m_result, inv_xpr);
-  }
-  
-protected:
-  PlainObject m_result;
-};
-  
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_INVERSE_H

deps_src/eigen/Eigen/src/Core/Map.h

@@ -1,171 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MAP_H
-#define EIGEN_MAP_H
-
-namespace Eigen { 
-
-namespace internal {
-template<typename PlainObjectType, int MapOptions, typename StrideType>
-struct traits<Map<PlainObjectType, MapOptions, StrideType> >
-  : public traits<PlainObjectType>
-{
-  typedef traits<PlainObjectType> TraitsBase;
-  enum {
-    PlainObjectTypeInnerSize = ((traits<PlainObjectType>::Flags&RowMajorBit)==RowMajorBit)
-                             ? PlainObjectType::ColsAtCompileTime
-                             : PlainObjectType::RowsAtCompileTime,
-
-    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
-                             ? int(PlainObjectType::InnerStrideAtCompileTime)
-                             : int(StrideType::InnerStrideAtCompileTime),
-    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
-                             ? (InnerStrideAtCompileTime==Dynamic || PlainObjectTypeInnerSize==Dynamic
-                                ? Dynamic
-                                : int(InnerStrideAtCompileTime) * int(PlainObjectTypeInnerSize))
-                             : int(StrideType::OuterStrideAtCompileTime),
-    Alignment = int(MapOptions)&int(AlignedMask),
-    Flags0 = TraitsBase::Flags & (~NestByRefBit),
-    Flags = is_lvalue<PlainObjectType>::value ? int(Flags0) : (int(Flags0) & ~LvalueBit)
-  };
-private:
-  enum { Options }; // Expressions don't have Options
-};
-}
-
-/** \class Map
-  * \ingroup Core_Module
-  *
-  * \brief A matrix or vector expression mapping an existing array of data.
-  *
-  * \tparam PlainObjectType the equivalent matrix type of the mapped data
-  * \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, \c #Aligned16, \c #Aligned8 or \c #Unaligned.
-  *                The default is \c #Unaligned.
-  * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
-  *                   of an ordinary, contiguous array. This can be overridden by specifying strides.
-  *                   The type passed here must be a specialization of the Stride template, see examples below.
-  *
-  * This class represents a matrix or vector expression mapping an existing array of data.
-  * It can be used to let Eigen interface without any overhead with non-Eigen data structures,
-  * such as plain C arrays or structures from other libraries. By default, it assumes that the
-  * data is laid out contiguously in memory. You can however override this by explicitly specifying
-  * inner and outer strides.
-  *
-  * Here's an example of simply mapping a contiguous array as a \ref TopicStorageOrders "column-major" matrix:
-  * \include Map_simple.cpp
-  * Output: \verbinclude Map_simple.out
-  *
-  * If you need to map non-contiguous arrays, you can do so by specifying strides:
-  *
-  * Here's an example of mapping an array as a vector, specifying an inner stride, that is, the pointer
-  * increment between two consecutive coefficients. Here, we're specifying the inner stride as a compile-time
-  * fixed value.
-  * \include Map_inner_stride.cpp
-  * Output: \verbinclude Map_inner_stride.out
-  *
-  * Here's an example of mapping an array while specifying an outer stride. Here, since we're mapping
-  * as a column-major matrix, 'outer stride' means the pointer increment between two consecutive columns.
-  * Here, we're specifying the outer stride as a runtime parameter. Note that here \c OuterStride<> is
-  * a short version of \c OuterStride<Dynamic> because the default template parameter of OuterStride
-  * is  \c Dynamic
-  * \include Map_outer_stride.cpp
-  * Output: \verbinclude Map_outer_stride.out
-  *
-  * For more details and for an example of specifying both an inner and an outer stride, see class Stride.
-  *
-  * \b Tip: to change the array of data mapped by a Map object, you can use the C++
-  * placement new syntax:
-  *
-  * Example: \include Map_placement_new.cpp
-  * Output: \verbinclude Map_placement_new.out
-  *
-  * This class is the return type of PlainObjectBase::Map() but can also be used directly.
-  *
-  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
-  */
-template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
-  : public MapBase<Map<PlainObjectType, MapOptions, StrideType> >
-{
-  public:
-
-    typedef MapBase<Map> Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Map)
-
-    typedef typename Base::PointerType PointerType;
-    typedef PointerType PointerArgType;
-    EIGEN_DEVICE_FUNC
-    inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; }
-
-    EIGEN_DEVICE_FUNC
-    inline Index innerStride() const
-    {
-      return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline Index outerStride() const
-    {
-      return int(StrideType::OuterStrideAtCompileTime) != 0 ? m_stride.outer()
-           : int(internal::traits<Map>::OuterStrideAtCompileTime) != Dynamic ? Index(internal::traits<Map>::OuterStrideAtCompileTime)
-           : IsVectorAtCompileTime ? (this->size() * innerStride())
-           : (int(Flags)&RowMajorBit) ? (this->cols() * innerStride())
-           : (this->rows() * innerStride());
-    }
-
-    /** Constructor in the fixed-size case.
-      *
-      * \param dataPtr pointer to the array to map
-      * \param stride optional Stride object, passing the strides.
-      */
-    EIGEN_DEVICE_FUNC
-    explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr)), m_stride(stride)
-    {
-      PlainObjectType::Base::_check_template_params();
-    }
-
-    /** Constructor in the dynamic-size vector case.
-      *
-      * \param dataPtr pointer to the array to map
-      * \param size the size of the vector expression
-      * \param stride optional Stride object, passing the strides.
-      */
-    EIGEN_DEVICE_FUNC
-    inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr), size), m_stride(stride)
-    {
-      PlainObjectType::Base::_check_template_params();
-    }
-
-    /** Constructor in the dynamic-size matrix case.
-      *
-      * \param dataPtr pointer to the array to map
-      * \param rows the number of rows of the matrix expression
-      * \param cols the number of columns of the matrix expression
-      * \param stride optional Stride object, passing the strides.
-      */
-    EIGEN_DEVICE_FUNC
-    inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType())
-      : Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride)
-    {
-      PlainObjectType::Base::_check_template_params();
-    }
-
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
-
-  protected:
-    StrideType m_stride;
-};
-
-
-} // end namespace Eigen
-
-#endif // EIGEN_MAP_H

deps_src/eigen/Eigen/src/Core/MapBase.h

@@ -1,303 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MAPBASE_H
-#define EIGEN_MAPBASE_H
-
-#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \
-      EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
-                          YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
-
-namespace Eigen { 
-
-/** \ingroup Core_Module
-  *
-  * \brief Base class for dense Map and Block expression with direct access
-  *
-  * This base class provides the const low-level accessors (e.g. coeff, coeffRef) of dense
-  * Map and Block objects with direct access.
-  * Typical users do not have to directly deal with this class.
-  *
-  * This class can be extended by through the macro plugin \c EIGEN_MAPBASE_PLUGIN.
-  * See \link TopicCustomizing_Plugins customizing Eigen \endlink for details.
-  *
-  * The \c Derived class has to provide the following two methods describing the memory layout:
-  *  \code Index innerStride() const; \endcode
-  *  \code Index outerStride() const; \endcode
-  *
-  * \sa class Map, class Block
-  */
-template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
-  : public internal::dense_xpr_base<Derived>::type
-{
-  public:
-
-    typedef typename internal::dense_xpr_base<Derived>::type Base;
-    enum {
-      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
-      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
-      InnerStrideAtCompileTime = internal::traits<Derived>::InnerStrideAtCompileTime,
-      SizeAtCompileTime = Base::SizeAtCompileTime
-    };
-
-    typedef typename internal::traits<Derived>::StorageKind StorageKind;
-    typedef typename internal::traits<Derived>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename internal::conditional<
-                         bool(internal::is_lvalue<Derived>::value),
-                         Scalar *,
-                         const Scalar *>::type
-                     PointerType;
-
-    using Base::derived;
-//    using Base::RowsAtCompileTime;
-//    using Base::ColsAtCompileTime;
-//    using Base::SizeAtCompileTime;
-    using Base::MaxRowsAtCompileTime;
-    using Base::MaxColsAtCompileTime;
-    using Base::MaxSizeAtCompileTime;
-    using Base::IsVectorAtCompileTime;
-    using Base::Flags;
-    using Base::IsRowMajor;
-
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::coeff;
-    using Base::coeffRef;
-    using Base::lazyAssign;
-    using Base::eval;
-
-    using Base::innerStride;
-    using Base::outerStride;
-    using Base::rowStride;
-    using Base::colStride;
-
-    // bug 217 - compile error on ICC 11.1
-    using Base::operator=;
-
-    typedef typename Base::CoeffReturnType CoeffReturnType;
-
-    /** \copydoc DenseBase::rows() */
-    EIGEN_DEVICE_FUNC inline Index rows() const { return m_rows.value(); }
-    /** \copydoc DenseBase::cols() */
-    EIGEN_DEVICE_FUNC inline Index cols() const { return m_cols.value(); }
-
-    /** Returns a pointer to the first coefficient of the matrix or vector.
-      *
-      * \note When addressing this data, make sure to honor the strides returned by innerStride() and outerStride().
-      *
-      * \sa innerStride(), outerStride()
-      */
-    EIGEN_DEVICE_FUNC inline const Scalar* data() const { return m_data; }
-
-    /** \copydoc PlainObjectBase::coeff(Index,Index) const */
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeff(Index rowId, Index colId) const
-    {
-      return m_data[colId * colStride() + rowId * rowStride()];
-    }
-
-    /** \copydoc PlainObjectBase::coeff(Index) const */
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeff(Index index) const
-    {
-      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
-      return m_data[index * innerStride()];
-    }
-
-    /** \copydoc PlainObjectBase::coeffRef(Index,Index) const */
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index rowId, Index colId) const
-    {
-      return this->m_data[colId * colStride() + rowId * rowStride()];
-    }
-
-    /** \copydoc PlainObjectBase::coeffRef(Index) const */
-    EIGEN_DEVICE_FUNC
-    inline const Scalar& coeffRef(Index index) const
-    {
-      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
-      return this->m_data[index * innerStride()];
-    }
-
-    /** \internal */
-    template<int LoadMode>
-    inline PacketScalar packet(Index rowId, Index colId) const
-    {
-      return internal::ploadt<PacketScalar, LoadMode>
-               (m_data + (colId * colStride() + rowId * rowStride()));
-    }
-
-    /** \internal */
-    template<int LoadMode>
-    inline PacketScalar packet(Index index) const
-    {
-      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
-      return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
-    }
-
-    /** \internal Constructor for fixed size matrices or vectors */
-    EIGEN_DEVICE_FUNC
-    explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
-    {
-      EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-      checkSanity<Derived>();
-    }
-
-    /** \internal Constructor for dynamically sized vectors */
-    EIGEN_DEVICE_FUNC
-    inline MapBase(PointerType dataPtr, Index vecSize)
-            : m_data(dataPtr),
-              m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
-              m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-      eigen_assert(vecSize >= 0);
-      eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize);
-      checkSanity<Derived>();
-    }
-
-    /** \internal Constructor for dynamically sized matrices */
-    EIGEN_DEVICE_FUNC
-    inline MapBase(PointerType dataPtr, Index rows, Index cols)
-            : m_data(dataPtr), m_rows(rows), m_cols(cols)
-    {
-      eigen_assert( (dataPtr == 0)
-              || (   rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-                  && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
-      checkSanity<Derived>();
-    }
-
-    #ifdef EIGEN_MAPBASE_PLUGIN
-    #include EIGEN_MAPBASE_PLUGIN
-    #endif
-
-  protected:
-
-    template<typename T>
-    EIGEN_DEVICE_FUNC
-    void checkSanity(typename internal::enable_if<(internal::traits<T>::Alignment>0),void*>::type = 0) const
-    {
-#if EIGEN_MAX_ALIGN_BYTES>0
-      // innerStride() is not set yet when this function is called, so we optimistically assume the lowest plausible value:
-      const Index minInnerStride = InnerStrideAtCompileTime == Dynamic ? 1 : Index(InnerStrideAtCompileTime);
-      EIGEN_ONLY_USED_FOR_DEBUG(minInnerStride);
-      eigen_assert((   ((internal::UIntPtr(m_data) % internal::traits<Derived>::Alignment) == 0)
-                    || (cols() * rows() * minInnerStride * sizeof(Scalar)) < internal::traits<Derived>::Alignment ) && "data is not aligned");
-#endif
-    }
-
-    template<typename T>
-    EIGEN_DEVICE_FUNC
-    void checkSanity(typename internal::enable_if<internal::traits<T>::Alignment==0,void*>::type = 0) const
-    {}
-
-    PointerType m_data;
-    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
-    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
-};
-
-/** \ingroup Core_Module
-  *
-  * \brief Base class for non-const dense Map and Block expression with direct access
-  *
-  * This base class provides the non-const low-level accessors (e.g. coeff and coeffRef) of
-  * dense Map and Block objects with direct access.
-  * It inherits MapBase<Derived, ReadOnlyAccessors> which defines the const variant for reading specific entries.
-  *
-  * \sa class Map, class Block
-  */
-template<typename Derived> class MapBase<Derived, WriteAccessors>
-  : public MapBase<Derived, ReadOnlyAccessors>
-{
-    typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
-  public:
-
-    typedef MapBase<Derived, ReadOnlyAccessors> Base;
-
-    typedef typename Base::Scalar Scalar;
-    typedef typename Base::PacketScalar PacketScalar;
-    typedef typename Base::StorageIndex StorageIndex;
-    typedef typename Base::PointerType PointerType;
-
-    using Base::derived;
-    using Base::rows;
-    using Base::cols;
-    using Base::size;
-    using Base::coeff;
-    using Base::coeffRef;
-
-    using Base::innerStride;
-    using Base::outerStride;
-    using Base::rowStride;
-    using Base::colStride;
-
-    typedef typename internal::conditional<
-                    internal::is_lvalue<Derived>::value,
-                    Scalar,
-                    const Scalar
-                  >::type ScalarWithConstIfNotLvalue;
-
-    EIGEN_DEVICE_FUNC
-    inline const Scalar* data() const { return this->m_data; }
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue* data() { return this->m_data; } // no const-cast here so non-const-correct code will give a compile error
-
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
-    {
-      return this->m_data[col * colStride() + row * rowStride()];
-    }
-
-    EIGEN_DEVICE_FUNC
-    inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
-    {
-      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
-      return this->m_data[index * innerStride()];
-    }
-
-    template<int StoreMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& val)
-    {
-      internal::pstoret<Scalar, PacketScalar, StoreMode>
-               (this->m_data + (col * colStride() + row * rowStride()), val);
-    }
-
-    template<int StoreMode>
-    inline void writePacket(Index index, const PacketScalar& val)
-    {
-      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
-      internal::pstoret<Scalar, PacketScalar, StoreMode>
-                (this->m_data + index * innerStride(), val);
-    }
-
-    EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
-    EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
-    EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) : Base(dataPtr, rows, cols) {}
-
-    EIGEN_DEVICE_FUNC
-    Derived& operator=(const MapBase& other)
-    {
-      ReadOnlyMapBase::Base::operator=(other);
-      return derived();
-    }
-
-    // In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base,
-    // see bugs 821 and 920.
-    using ReadOnlyMapBase::Base::operator=;
-};
-
-#undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS
-
-} // end namespace Eigen
-
-#endif // EIGEN_MAPBASE_H

deps_src/eigen/Eigen/src/Core/MathFunctionsImpl.h

@@ -1,101 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com)
-// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_MATHFUNCTIONSIMPL_H
-#define EIGEN_MATHFUNCTIONSIMPL_H
-
-namespace Eigen {
-
-namespace internal {
-
-/** \internal \returns the hyperbolic tan of \a a (coeff-wise)
-    Doesn't do anything fancy, just a 13/6-degree rational interpolant which
-    is accurate up to a couple of ulp in the range [-9, 9], outside of which
-    the tanh(x) = +/-1.
-
-    This implementation works on both scalars and packets.
-*/
-template<typename T>
-T generic_fast_tanh_float(const T& a_x)
-{
-  // Clamp the inputs to the range [-9, 9] since anything outside
-  // this range is +/-1.0f in single-precision.
-  const T plus_9 = pset1<T>(9.f);
-  const T minus_9 = pset1<T>(-9.f);
-  // NOTE GCC prior to 6.3 might improperly optimize this max/min
-  //      step such that if a_x is nan, x will be either 9 or -9,
-  //      and tanh will return 1 or -1 instead of nan.
-  //      This is supposed to be fixed in gcc6.3,
-  //      see: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=72867
-  const T x = pmax(minus_9,pmin(plus_9,a_x));
-  // The monomial coefficients of the numerator polynomial (odd).
-  const T alpha_1 = pset1<T>(4.89352455891786e-03f);
-  const T alpha_3 = pset1<T>(6.37261928875436e-04f);
-  const T alpha_5 = pset1<T>(1.48572235717979e-05f);
-  const T alpha_7 = pset1<T>(5.12229709037114e-08f);
-  const T alpha_9 = pset1<T>(-8.60467152213735e-11f);
-  const T alpha_11 = pset1<T>(2.00018790482477e-13f);
-  const T alpha_13 = pset1<T>(-2.76076847742355e-16f);
-
-  // The monomial coefficients of the denominator polynomial (even).
-  const T beta_0 = pset1<T>(4.89352518554385e-03f);
-  const T beta_2 = pset1<T>(2.26843463243900e-03f);
-  const T beta_4 = pset1<T>(1.18534705686654e-04f);
-  const T beta_6 = pset1<T>(1.19825839466702e-06f);
-
-  // Since the polynomials are odd/even, we need x^2.
-  const T x2 = pmul(x, x);
-
-  // Evaluate the numerator polynomial p.
-  T p = pmadd(x2, alpha_13, alpha_11);
-  p = pmadd(x2, p, alpha_9);
-  p = pmadd(x2, p, alpha_7);
-  p = pmadd(x2, p, alpha_5);
-  p = pmadd(x2, p, alpha_3);
-  p = pmadd(x2, p, alpha_1);
-  p = pmul(x, p);
-
-  // Evaluate the denominator polynomial p.
-  T q = pmadd(x2, beta_6, beta_4);
-  q = pmadd(x2, q, beta_2);
-  q = pmadd(x2, q, beta_0);
-
-  // Divide the numerator by the denominator.
-  return pdiv(p, q);
-}
-
-template<typename RealScalar>
-EIGEN_STRONG_INLINE
-RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y)
-{
-  EIGEN_USING_STD_MATH(sqrt);
-  RealScalar p, qp;
-  p = numext::maxi(x,y);
-  if(p==RealScalar(0)) return RealScalar(0);
-  qp = numext::mini(y,x) / p;    
-  return p * sqrt(RealScalar(1) + qp*qp);
-}
-
-template<typename Scalar>
-struct hypot_impl
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  static inline RealScalar run(const Scalar& x, const Scalar& y)
-  {
-    EIGEN_USING_STD_MATH(abs);
-    return positive_real_hypot<RealScalar>(abs(x), abs(y));
-  }
-};
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_MATHFUNCTIONSIMPL_H