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_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_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_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 setUp(self):
self.test_folder = tempfile.mkdtemp(suffix='template_test/')
self.tif_folder = os.path.join(self.test_folder, 'tiffs/')
os.mkdir(self.tif_folder)
# copy across the process list to the working directory
self.process_list_path = os.path.join(self.test_folder, 'xrd_template_test.nxs')
shutil.copyfile(tu.get_test_process_path('xrd_template_test.nxs'),
self.process_list_path)
utils.populate_plugins()
self.process_list = Content()
self.process_list.fopen(self.process_list_path, update=False)
for idx in self.process_list.get_positions():
self.process_list.refresh(idx)
self.detX_axis_label = {'dim': '$idx_detx', 'name': 'detector_x', 'value': None, 'units': 'pixels'}
self.detY_axis_label = {'dim': '$idx_dety', 'name': 'detector_y', 'value': None, 'units': 'pixels'}
self.yaml = OrderedDict()
# now make some standard modifications
self.yaml['inherit'] = [tu.get_test_data_path(os.path.join('i18_templates', 'xrd_calibration.yml'))]
self.yaml['xrd'] = OrderedDict()
self.yaml['xrd']['params'] = {}
self.yaml['xrd']['data'] = {}
self.yaml['xrd']['data']['folder'] = self.tif_folder
self.yaml['xrd']['params']['cfile'] = \
"$h5py.File('%s', 'r')" % tu.get_test_data_path('LaB6_calibration_new.nxs')
self.yaml['xrd']['patterns'] = {}
self.yaml['xrd']['patterns']['DIFFRACTION'] = {'core_dims': '$(idx_detx, idx_dety)',
'slice_dims': '$tuple([d for d in dims if d not in [idx_detx, idx_dety]])'}
self.yaml['xrd']['axis_labels'] = {}
self.yaml['xrd']['metadata'] = {}
self.data_file_path = 'test_data.nxs'
self.data_file = h5.File(self.data_file_path, 'w') # this will have the axes in.
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_monitor_correction(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('mm.nxs'),
"process_file": tu.get_test_process_path('monitor_correction_test.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_process(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('mm.nxs'),
"process_file": tu.get_test_process_path('basic_stxm_process.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def "r6"(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path("r7"),
"process_file": tu.get_test_process_path("r8"),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_fbp(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('24737.nxs'),
"process_file": tu.get_test_process_path('miro_test.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_cgls_astra(self):
process = 'basic_tomo_iterative_process.nxs'
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('24737.nxs'),
"process_file": tu.get_test_process_path(process),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_multi_params_tomo(self):
process = 'basic_tomo_process_preview_params_test.nxs'
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('24737.nxs'),
"process_file": tu.get_test_process_path(process),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_mm(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('mm.nxs'),
"process_file": tu.get_test_process_path(
'multiple_mm_inputs_test.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_multi_params_i12tomo(self):
process = 'i12_tomo_pipeline_test.nxs'
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path(
'i12_test_data/i12_test_data.nxs'),
"process_file": tu.get_test_process_path(process),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def setUp(self):
self.test_folder = tempfile.mkdtemp(suffix='template_test/')
self.tif_folder = os.path.join(self.test_folder, 'tiffs/')
os.mkdir(self.tif_folder)
# copy across the process list to the working directory
self.process_list_path = os.path.join(self.test_folder,
'xrd_template_test.nxs')
shutil.copyfile(tu.get_test_process_path('xrd_template_test.nxs'),
self.process_list_path)
utils.populate_plugins()
self.process_list = Content()
self.process_list.fopen(self.process_list_path, update=False)
for idx in self.process_list.get_positions():
self.process_list.refresh(idx)
self.detX_axis_label = {
'dim': '$idx_detx',
'name': 'detector_x',
'value': None,
'units': 'pixels'
}
self.detY_axis_label = {
'dim': '$idx_dety',
'name': 'detector_y',
'value': None,
'units': 'pixels'
}
self.yaml = OrderedDict()
# now make some standard modifications
self.yaml['inherit'] = [
tu.get_test_data_path(
os.path.join('i18_templates', 'xrd_calibration.yml'))
]
self.yaml['xrd'] = OrderedDict()
self.yaml['xrd']['params'] = {}
self.yaml['xrd']['data'] = {}
self.yaml['xrd']['data']['folder'] = self.tif_folder
self.yaml['xrd']['params']['cfile'] = \
"$h5py.File('%s', 'r')" % tu.get_test_data_path('LaB6_calibration_new.nxs')
self.yaml['xrd']['patterns'] = {}
self.yaml['xrd']['patterns']['DIFFRACTION'] = {
'core_dims':
'$(idx_detx, idx_dety)',
'slice_dims':
'$tuple([d for d in dims if d not in [idx_detx, idx_dety]])'
}
self.yaml['xrd']['axis_labels'] = {}
self.yaml['xrd']['metadata'] = {}
self.data_file_path = 'test_data.nxs'
self.data_file = h5.File(self.data_file_path,
'w') # this will have the axes in.
def test_process(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path('mm.nxs'),
# "process_file": tu.get_test_process_path('simplefitreconstest.nxs'),
"process_file": tu.get_test_process_path(
'testing_mm_sart_recon.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def test_process_preview(self):
options = {
"transport": "hdf5",
"process_names": "CPU0",
"data_file": tu.get_test_data_path(
'/i12_test_data/i12_test_data.nxs'),
"process_file": tu.get_test_process_path(
'i12_tomo_pipeline_preview_test.nxs'),
"out_path": tempfile.mkdtemp()
}
run_protected_plugin_runner(options)
def create_chunking_instance(self, current_list, nnext_list, nProcs):
current = self.create_pattern('a', current_list)
nnext = self.create_pattern('b', nnext_list)
options = tu.set_experiment('tomoRaw')
options['processes'] = range(nProcs)
# set a dummy process list
options['process_file'] = \
tu.get_test_process_path('basic_tomo_process.nxs')
exp = Experiment(options)
test_dict = {'current': current, 'next': nnext}
chunking = Chunking(exp, test_dict)
return chunking
def create_chunking_instance(self, current_list, nnext_list, nProcs):
current = self.create_pattern('a', current_list)
nnext = self.create_pattern('b', nnext_list)
options = tu.set_experiment('tomoRaw')
options['processes'] = range(nProcs)
# set a dummy process list
options['process_file'] = \
tu.get_test_process_path('basic_tomo_process.nxs')
exp = Experiment(options)
test_dict = {'current': current, 'next': nnext}
chunking = Chunking(exp, test_dict)
return chunking
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_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 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_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_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_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_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_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_astra_recon_init_vol(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('astra_init_vol_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_basic_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_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_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_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))
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_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_hilbert(self):
data_file = tu.get_test_data_path('24737.nxs')
process_file = tu.get_test_process_path('hilbert_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_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_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_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_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_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_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_i13_speckle_tracking(self):
data_file = tu.get_test_big_data_path('speckle_tracking.h5')
process_file = tu.get_test_process_path('to_revise/i13_speckle_loader_process.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_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_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_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_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_i13_fluo(self):
data_file = tu.get_test_data_path('i13_fluo_data.nxs')
process_file = tu.get_test_process_path('basic_fluo_process_i13.nxs')
run_protected_plugin_runner(
tu.set_options(data_file, process_file=process_file))
