Testing

Test Environment

To create a test environment (called “test” in command below)

conda create --name test python=2

To switch to “test” environment:

conda activate test

To reset “test” environment to initial install:

conda install --name test --revision 0

Savu Training Examples

Training examples are documented here: trainingexamples

Simple

This can be run if in the TrainingExample root directory as follows:

savu data/24737.nxs process_lists/simple_tomo_pipeline_cpu.nxs .

Data files have to be opened and saved by savu_config to avoid import error for a module nxtomo_loader; pending a future formal fix to Savu.

Parallel

This can be run if in the TrainingExample root directory as follows assuming a writeable “/tmp2” folder exists:

savu_mpijob_local.sh data/24737.nxs process_lists/simple_tomo_pipeline.nxs . -d /tmp2

This currently fails, but is not a priority as savu-lite was not intended to run in parallel.

Current Error is:

Global Name ‘mpi4py’ is not defined

Existing Savu Tests

These can be run successfully from a conda installed savu-lite.

  • savu_quick_tests
  • savu_full_test

savu_quick_tests

This is run as part of the build. scikit-image is a pre-requisite for it to run and has therefore been included in savu-lite build.

savu_full_test

This can be run after savu-lite has been installed, success is indicated by it completing with no errors reported at its conclusion. Pre-requisites for this to run are: tifffile, pyfai, peakutils, fabio, tomopy, pymca

Savu Issues

Refresh.py is awaiting a fix that will be introduced in next release.

Training Example Errors

The Savu 2.4 training examples are out-of-date: trainingexamples

Refresh.py is awaiting a fix that will be introduced in next release. python process_lists/refresh.py

In the meantime this can be resolved by opening data files with savu_config and then re-saving them. Thus avoiding import error for a module nxtomo_loader.