[pull] master from graphistry:master#133
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…831) * test(layout): add CPU/GPU tests for circle_layout with partition_by - Add test_circle_layout_with_partition_pd for pandas (CPU) testing - Add test_circle_layout_with_partition_cudf for cuDF (GPU) testing - Tests specifically exercise the code path fixed in #830 (circle.py:248-254) - Would have caught the original transform('size') NotImplementedError - Validates that partition-based circle layouts generate valid x/y coordinates - All 4 tests in test_gib.py now pass (2 existing + 2 new) Follow-up to #829 and #830 to prevent regressions. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * test(layout): add gib integration tests with multiple communities - Add test_gib_pd_with_partitions for pandas (CPU) full integration - Add test_gib_cudf_with_partitions for cuDF (GPU) full integration - Tests exercise complete group_in_a_box_layout workflow with partitioning - Creates graphs with multiple communities to trigger partition-based layouts - Complements circle_layout direct tests with full end-to-end user workflow - Ensures the fixed code path (circle.py:248-254) is tested via the high-level API Now have comprehensive coverage: - Low-level: circle_layout with partition_by (direct test) - High-level: group_in_a_box_layout with communities (integration test) - Both: CPU (pandas) and GPU (cuDF) engines All 3 pandas tests pass locally, 3 GPU tests will validate in CI. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * ci(gpu): switch to T4 runner for faster GPU CI - Change from 'group: GPU Runners - Public' to 't4-runner' label - Uses dedicated T4 runner with 16GB VRAM - Should have better availability and faster start times 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * ci(gpu): use gpu_public runner label - Change to gpu_public label (Tesla T4, 16GB VRAM) - Note: Runner restricted to master and gpu-public branches only - Tests validated locally in GPU container (all 6 pass) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix(ci): revert to working GPU runner group configuration - Revert from 'runs-on: gpu_public' back to 'runs-on: group: GPU Runners - Public' - This was the working configuration before commits 555b390 and da472d9 - Last successful GPU CI run (July 17) used the runner group syntax - Direct runner labels (t4-runner, gpu_public) not being picked up 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix(ci): use gpu_public label as per runner UI instructions The runner UI explicitly states: "Add runs-on: gpu_public to your workflow's YAML to send jobs to this runner." Reverting from group syntax back to label syntax. Runner details from UI: - Name: gpu_public - Runner group: GPU Runners - Public - Status: Ready - Hardware: 1x NVIDIA Tesla T4, 16GB VRAM - Usage: 0/8 active jobs 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs(changelog): add test coverage for circle/gib layouts Added entry for comprehensive test coverage of circle_layout() and group_in_a_box_layout() with partition support across CPU/GPU engines. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
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