def test_simple_fit_runs(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path(
'multimodal/simple_fit_test_XRF.nxs')
options = tu.set_options(data_file, process_file=process_file)
self.datapath = options['out_path']
run_protected_plugin_runner(options)
def test_i08_REGRESSION(self):
data_file = tu.get_test_big_data_path(
'pymca_live_processing_test/i08-10471.nxs')
process_file = tu.get_test_process_path('i08_pymca_process.nxs')
outdir = tempfile.mkdtemp(prefix="pymca_i08_test")
if os.path.exists(outdir):
shutil.rmtree(outdir)
os.makedirs(outdir, stat.S_IRWXO | stat.S_IRWXU)
options = tu.set_options(data_file,
process_file=process_file,
out_path=outdir)
run_protected_plugin_runner(options)
change_permissions_recursive(
options['out_path'], stat.S_IRWXO | stat.S_IRWXU | stat.S_IRWXG)
output_filename = ("%(out_path)s" + os.sep +
"%(out_folder)s_processed.nxs") % options
f_test = h5.File(output_filename, 'r') # the result of this test
test_path = tu.get_test_big_data_path(
'pymca_live_processing_test/savu_test_result/test_processed.nxs')
f_known = h5.File(test_path,
'r') # a known good result from the same data
# first we just do a direct comparison of the data. This should be equal exactly.
data = '/entry/final_result_fluo/data'
elements = 'entry/final_result_fluo/PeakElements'
self.assertTrue((f_test[data][...] == f_known[data][...]).any())
self.assertListEqual(list(f_test[elements][...]),
list(f_known[elements][...]))
def test_i08_REGRESSION(self):
data_file = tu.get_test_big_data_path('pymca_live_processing_test/i08-10471.nxs')
process_file = tu.get_test_process_path('i08_pymca_process.nxs')
outdir = tempfile.mkdtemp(prefix="pymca_i08_test")
if os.path.exists(outdir):
shutil.rmtree(outdir)
os.makedirs(outdir, stat.S_IRWXO | stat.S_IRWXU)
options = tu.set_options(data_file, process_file=process_file, out_path=outdir)
run_protected_plugin_runner(options)
change_permissions_recursive(options['out_path'],
stat.S_IRWXO | stat.S_IRWXU | stat.S_IRWXG)
output_filename = ("%(out_path)s"+os.sep+"%(out_folder)s_processed.nxs") % options
f_test = h5.File(output_filename, 'r') # the result of this test
test_path = tu.get_test_big_data_path('pymca_live_processing_test/savu_test_result/test_processed.nxs')
f_known = h5.File(test_path, 'r') # a known good result from the same data
# first we just do a direct comparison of the data. This should be equal exactly.
data = '/entry/final_result_fluo/data'
elements = 'entry/final_result_fluo/PeakElements'
self.assertTrue((f_test[data][...] == f_known[data][...]).any())
self.assertListEqual(list(f_test[elements][...]),
list(f_known[elements][...]))
def test_1D_data(self):
A = 11
X = 10
Y = 13
expected_output_shape = (A, X, Y)
expected_top_corners = np.arange(A, dtype=np.float32)
self.create_N_tiffs(A, frame_size=(X, Y))
# create a data file with the axis information
self.data_file['entry/A'] = np.arange(A)
self.data_file.close()
# edit and save the yaml
self.yaml['xrd']['data']['shape'] = '$(len(A_vals),)'
self.yaml['xrd']['params'].update({
'idx_A': 0,
'idx_detx': 1,
'idx_dety': 2,
'A_vals': "$dfile['entry/A'].value",
'dims': "$range(0, 3)"
})
# add some axis labels
self.yaml['xrd']['axis_labels'] = {
0: {
'dim': '$idx_A',
'name': 'A',
'value': '$A_vals',
'units': 'pixels'
},
1: self.detX_axis_label,
2: self.detY_axis_label
}
self.save_yaml_and_change_process_list()
run_protected_plugin_runner(
tu.set_options(self.data_file_path,
process_file=self.process_list_path,
out_path=self.test_folder))
# now check the result
result = h5.File(os.path.join(self.test_folder, 'test_processed.nxs'),
'r')['entry/final_result_xrd/data']
np.testing.assert_array_equal(
result.shape,
expected_output_shape,
err_msg='The output shape is not as expected.')
result_corners = result[..., -1, -1]
np.testing.assert_equal(
result_corners.dtype,
expected_top_corners.dtype,
err_msg='The array does not output the correct type.')
np.testing.assert_array_equal(
result_corners,
expected_top_corners,
err_msg="The output values are not as expected")
def test_i18_stxm(self):
# data_file = '/dls/i18/data/2016/sp12601-1/processing/Savu_Test_Data/70214_Cat2_RT_1.nxs'
data_file = tu.get_test_data_path('i18_test_data.nxs')
process_file = tu.get_test_process_path('basic_stxm_process_i18.nxs')
# process_file = tu.get_process_list_path('stxm_tomo_i18.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_stxm_tomo_astra(self):
print "Hi2"
data_file = tu.get_test_data_path('mm.nxs')
process_file = \
tu.get_test_process_path('simple_stxm_tomo_test_astra.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_diffraction_correction(self):
data_file = tu.get_test_data_path('i18_test_data.nxs')
# data_file = '/dls/i18/data/2016/sp13939-1/Experiment_1/nexus/75996_alphanitrateRT_1.nxs'
process_file = tu.get_test_process_path('diffraction_absorption_correction_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_simple_fit_runs(self):
# data_file = '/dls/i13-1/data/2016/mt14190-1/raw/91318.nxs'#
data_file = tu.get_test_data_path('i18_test_data.nxs')
process_file = tu.get_test_process_path('pymca_test.nxs')
# process_file = '/dls/i13-1/data/2016/mt14190-1/processing/savu/process_lists/pymca_process.nxs'
options = tu.set_options(data_file, process_file=process_file)
self.datapath = options['out_path']
run_protected_plugin_runner(options)
def test_pyfai(self):
data_file = tu.get_test_data_path(
'i18_test_data.nxs'
) #'/dls/i18/data/2016/sp12601-1/processing/Savu_Test_Data/70214_Cat2_RT_1.nxs'#
process_file = tu.get_test_process_path(
'PyFAI_azimuth_new_calib_i18_test.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_simple_fit_runs(self):
# data_file = '/dls/i13-1/data/2016/mt14190-1/raw/91318.nxs'#
data_file = tu.get_test_data_path('i18_test_data.nxs')
process_file = tu.get_test_process_path('pymca_test.nxs')
# process_file = '/dls/i13-1/data/2016/mt14190-1/processing/savu/process_lists/pymca_process.nxs'
options = tu.set_options(data_file, process_file=process_file)
self.datapath = options['out_path']
run_protected_plugin_runner(options)
def test_reload(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('savu_nexus_loader_test1.nxs')
exp = run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
data_file = exp.meta_data.get('nxs_filename')
process_file = tu.get_test_process_path('savu_nexus_loader_test2.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_tomobar3d_fast(self):
process_list = 'reconstruction/tomobar/tomobar3d_gpu_recon.nxs'
options1 = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options1)
#read the output file using SavuNexusLoader
data_file2 = options1['out_path'] + 'test_processed.nxs'
options2 = tu.initialise_options(data_file2, 'load_data', 'loaders/savu_nexus_loader_test4.nxs')
run_protected_plugin_runner(options2)
tu.cleanup(options1)
tu.cleanup(options2)
def test_reload(self):
process_list = 'loaders/savu_nexus_loader_test1.nxs'
options1 = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options1)
#read the output file using SavuNexusLoader
data_file2 = options1['out_path'] + 'test_processed.nxs'
options2 = tu.initialise_options(
data_file2, 'load_data', 'loaders/savu_nexus_loader_test2.nxs')
run_protected_plugin_runner(options2)
tu.cleanup(options1)
tu.cleanup(options2)
def test_3D_data(self):
A = 3
B = 4
C = 5
X = 10
Y = 13
expected_output_shape = (A, B, C, X, Y)
expected_top_corners = np.arange(A*B*C, dtype=np.float32).reshape((A, B, C))
self.create_N_tiffs(A*B*C, frame_size=(X, Y))
# create a data file with the axis information
self.data_file['entry/A'] = np.arange(A)
self.data_file['entry/B'] = np.arange(B)
self.data_file['entry/C'] = np.arange(C)
self.data_file.close()
# edit and save the yaml
self.yaml['xrd']['data']['shape'] = '$(len(A_vals), len(B_vals), len(C_vals))'
self.yaml['xrd']['params'].update({'idx_A': 0,
'idx_B': 1,
'idx_C': 2,
'idx_detx': 3,
'idx_dety': 4,
'A_vals': "$dfile['entry/A'].value",
'B_vals': "$dfile['entry/B'].value",
'C_vals': "$dfile['entry/C'].value",
'dims': "$range(0, 4)"})
self.yaml['xrd']['axis_labels'] = {0: {'dim': '$idx_A', 'name': 'A', 'value': '$A_vals', 'units': 'pixels'},
1: {'dim': '$idx_B', 'name': 'B', 'value': '$B_vals', 'units': 'pixels'},
2: {'dim': '$idx_C', 'name': 'C', 'value': '$C_vals', 'units': 'pixels'},
3: self.detX_axis_label,
4: self.detY_axis_label}
self.save_yaml_and_change_process_list()
run_protected_plugin_runner(tu.set_options(self.data_file_path,
process_file=self.process_list_path,
out_path=self.test_folder))
result = h5.File(os.path.join(self.test_folder, 'test_processed.nxs'), 'r')['entry/final_result_xrd/data']
np.testing.assert_array_equal(result.shape, expected_output_shape,
err_msg='The output shape is not as expected.')
result_corners = result[..., -1, -1]
np.testing.assert_equal(result_corners.dtype, expected_top_corners.dtype,
err_msg='The array does not output the correct type.')
np.testing.assert_array_equal(result_corners, expected_top_corners,
err_msg="The output values are not as expected")
def test_reload(self):
process_list = 'loaders/savu_nexus_loader_test1.nxs'
options1 = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options1)
#read the output file using SavuNexusLoader
path_to_rec = options1['out_path'] + 'test_processed.nxs'
self.test_folder2 = tempfile.mkdtemp(suffix='my_test2/')
options2 = tu.set_experiment('tomo')
options2['data_file'] = path_to_rec
options2['out_path'] = os.path.join(self.test_folder2)
options2['process_file'] = tu.get_test_process_path(
'loaders/savu_nexus_loader_test2.nxs')
run_protected_plugin_runner(options2)
tu.cleanup(options1)
tu.cleanup(options2)
def test_i08_REGRESSION(self):
data_file = tu.get_test_big_data_path('pymca_live_processing_test/i08-10471.nxs')
process_file = tu.get_test_process_path('i08_pymca_process.nxs')
outdir = '/tmp/pymca_i08_test'+strftime("%Y%m%d%H%M%S", gmtime())+'/'
if os.path.exists(outdir):
shutil.rmtree(outdir)
os.makedirs(outdir, stat.S_IRWXO | stat.S_IRWXU)
options = tu.set_options(data_file,process_file=process_file,out_path=outdir)
run_protected_plugin_runner(options)
change_permissions_recursive(options['out_path'], stat.S_IRWXO | stat.S_IRWXU | stat.S_IRWXG)
f_test = h5.File(options['out_path']+os.sep+options['out_folder']+'_processed.nxs','r') # the result of this test
f_known = h5.File(tu.get_test_big_data_path('pymca_live_processing_test/savu_test_result/test_processed.nxs'),'r')# a known good result from the same data
# first we just do a direct comparison of the data. This should be equal exactly.
data = '/entry/final_result_fluo/data'
elements = 'entry/final_result_fluo/PeakElements'
# test=np.around(f_test[data][...], decimals=-1)
# known=np.around(f_known[data][...], decimals=-1)
# self.assertEqual(test, known)
self.assertTrue((f_test[data][...]==f_known[data][...]).any())
# np.testing.assert_array_almost_equal(f_test[data][...], f_known[data][...], 0) # this needs to be -1
self.assertListEqual(list(f_test[elements][...]), list(f_known[elements][...]))
def test_process(self):
data_file = tu.get_test_data_path('fluo_single_sino.nxs')
process_file = tu.get_test_process_path('simple_fit_test_XRF_tomo.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_binary_quantisation_filter(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('threshold_filter_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_nx_ptycho(self):
data_file = tu.get_test_data_path('NXptycho.nxs')
process_file = tu.get_test_process_path('basic_ptycho_process.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_pyfai(self):
data_file = tu.get_test_data_path('i18_test_data.nxs')#'/dls/i18/data/2016/sp12601-1/processing/Savu_Test_Data/70214_Cat2_RT_1.nxs'#
process_file = tu.get_test_process_path('PyFAI_azimuth_new_calib_i18_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_process(self):
data_file = tu.get_test_big_data_path('xrd_tomo_p3_astra_recon_cpu.h5')
process_file = tu.get_test_process_path('pca_test.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_i14_software(self):
data_file = tu.get_test_big_data_path('i14-5195.nxs')
process_file = tu.get_test_process_path('i14_pymca_process.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_gmm(self):
process_list = 'segmentation/gmm/gmm_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_process_preview(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = \
tu.get_test_process_path('tomo_pipeline_preview_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_tomobar_recon(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('tomobar2d_recon.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_correction(self):
process_list = 'corrections/camera_rot_corr_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_simple_fit_XRD(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('findpeakstest.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_tomopy_gridrec(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('tomopy_test.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_sinogram_alignment(self):
process_list = 'sino_alignment_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_chunking(self):
data_file = tu.get_test_data_path('xrd_single_sino.nxs')
process_file = tu.get_test_process_path(
'pyfai_tomo_chunking_single_sino_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_distortion_correction(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = \
tu.get_test_process_path('distortion_correction_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_process(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('spectrum_crop_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_nx_xrd(self):
data_file = '/dls/i18/data/2016/sp12601-1/processing/Savu_Test_Data/70214_Cat2_RT_1.nxs'
process_file = tu.get_test_process_path('basic_xrd_process_i18.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_cgls_recon(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('ccpi_cgls_recon_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def tiff_test_stitch_dim(self):
data_file = tu.get_test_data_path('image_test/tiffs')
process_file = tu.get_test_process_path(
'tiff_loader_test_change_stitching_dim.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_process(self):
data_file = tu.get_test_big_data_path('xrd_tomo_p3_astra_recon_cpu.h5')
process_file = tu.get_test_process_path('ica_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_multi_params_tomo(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path(
'basic_tomo_process_preview_params_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_ptycho(self):
data_file = '/dls/mx-scratch/savu_test_data/NXptychoflipped.nxs'
process_file = tu.get_test_process_path('ptycho_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_stage_motion(self):
data_file = tu.get_test_data_path('kinematics_data.nxs')
process_file = tu.get_test_process_path('kinematic_parser_test.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_mm(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('multiple_mm_inputs_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_median_gpu_filter(self):
process_list = 'filters/denoise/median_filter_gpu_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_pyfai_filtered(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('PyFAI_azimuth_test_bragg.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_fbp(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('raven_filter_test.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_ccpi_regul_cpu(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('CcpiRegulToolkitCpu_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_process(self):
data_file = tu.get_test_data_path('/i12_test_data/i12_test_data.nxs')
process_file = tu.get_test_process_path('i12_tomo_pipeline_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_process(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path(
'I18_pipeline_just_xrd_from_raw_filtered_adp_mod2.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_stxm_tomo_scikit(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = \
tu.get_test_process_path('simple_stxm_tomo_test_scikit.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
def test_dezinger_sinogram(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('dezinger_sinogram_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_nx_stxm(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('basic_stxm_process.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_stage_motion(self):
data_file = tu.get_test_data_path('kinematics_data.nxs')
process_file = tu.get_test_process_path('kinematic_parser_test.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_i18_mm(self):
process_list = 'loaders/MM_i18_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_subpixel_shift(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = \
tu.get_test_process_path('subpixel_shift.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_nx_tomo(self):
process_list = 'loaders/basic_tomo_process.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_process(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = tu.get_test_process_path('mm_template_processing.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
def test_dezinger_sinogram(self):
process_list = 'filters/dezinger/dezinger_sinogram_test.nxs'
options = tu.initialise_options(data_file, experiment, process_list)
run_protected_plugin_runner(options)
tu.cleanup(options)
def test_process(self):
data_file = tu.get_test_data_path('mm.nxs')
process_file = \
tu.get_test_process_path('simple_stxm_tomo_test_astra.nxs')
run_protected_plugin_runner(tu.set_options(data_file,
process_file=process_file))
