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README.md
README.md
 
 
run.py
run.py
 
 
validate.py
validate.py
 
 

README.md

This directory contains two Python scripts, run.py and validate.py, used for validating all ttk-data state files with new TTK releases.

The first script, run.py, generates PNG screenshots for every state files. Just call python3 run.py or python3 tests/run.py to generate a PNG per view of every state file. These PNGs will be stored by default under tests/output_screenshots. To generate screenshots for only one state file, use python3 tests/run.py -i states/file (from the root ttk-data directory, which contains the pipeline inputs).

The second script, validation.py, compares generated screenshots from tests/output_screenshots to a refererence stored in tests/reference_screenshots. By default, it will also run the run.py script to generate the current screenshots to be compared. Use python3 validate.py -c to skip the screenshots generation and only compare previoulsy generated screenshots.

To generate a new reference, use python3 validate.py -r. Please note that the reference is dependent on the following factors:

  • to be independent of the display resolution, an offscreen ParaView renderer (OSMesa on Linux) is recommended.
  • macOS'offscreen renderer has some inconsistencies with Linux'.
  • Windows segfaults during offscreen rendering.
  • the TTKDimensionReduction filter ouput depends on the version of the Scikit-learn Python package. Please use a recent Scikit-learn (use pip on Ubuntu, the system package on ArchLinux).
  • the HarmonicSkeleton state file depends on the Eigen::ConjugateGradient iterative solver, which is non-deterministic. The image comparison threshold has been increased for this state file accordingly.
  • some filters, such as FTMTree, may have a non-deterministic output when used in a highly parallel context. Reducing the parallelism by setting UseAllCores to false in the affected state files might be necessary to ensure a deterministic output.

As a consequence, to reproduce the current reference, the following is required:

  • a Linux OS
  • an OSMesa installation of ParaView (configured with -DPARAVIEW_USE_QT=OFF -DVTK_USE_X=OFF -DVTK_OPENGL_HAS_OSMESA=ON)
  • a pip-installed Scikit-Learn
  • see the automatic test yml script for installation examples.