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_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_i08_notaux(self): cu.populate_plugins() data_file = tu.get_test_big_data_path('pymca_live_processing_test/i08-10471.nxs') data = h5.File(data_file,'r')['/entry/xmapMca/data'] inputs = {} inputs['data'] = data[0,0,0,:] inputs['dataset_name'] = '' inputs['xaxis_title'] = None metaOnly = False self.persistence = {} self.persistence['sys_path_0_lock'] = threading.Lock() self.persistence['sys_path_0_set'] = False self.persistence['plugin_object'] = None self.persistence['axis_labels'] = None self.persistence['axis_values'] = None self.persistence['string_key'] = None self.persistence['parameters'] = None self.persistence['aux'] = {} params={} params['config']={} params['config']['value'] = tu.get_test_big_data_path('pymca_live_processing_test/10471.cfg') path2plugin = pu.dawn_plugins['Pymca']['path2plugin']# set by dawn-side code self.runSavu(path2plugin, params, metaOnly, inputs)
def test_i08_REGRESSION(self): cu.populate_plugins() data_file = h5.File(tu.get_test_big_data_path('pymca_live_processing_test/dawn_test_result/result.nxs'),'r') data = data_file['/raw_entry/xmapMca/data'] inputs = {} inputs['dataset_name'] = '' inputs['xaxis_title'] = None metaOnly = True self.persistence = {} self.persistence['sys_path_0_lock'] = threading.Lock() self.persistence['sys_path_0_set'] = False self.persistence['plugin_object'] = None self.persistence['axis_labels'] = None self.persistence['axis_values'] = None self.persistence['string_key'] = None self.persistence['parameters'] = None self.persistence['aux'] = {} params={} params['config']={} params['config']['value'] = tu.get_test_big_data_path('pymca_live_processing_test/10471.cfg') path2plugin = pu.dawn_plugins['Pymca']['path2plugin']# set by dawn-side code pts = [(39,51), (45,25), (18,29), (37,96), (8,110)] # just do 5 points for now, is full regression necessary? for y,x in pts: inputs['data'] = data[x,y,0,:] out = self.runSavu(path2plugin, params, metaOnly, inputs) aux = out['auxiliary'] entry = 'entry/auxiliary/0-Python Script - Savu/' for key in aux.keys(): print(key,x,y) foo=data_file[entry+key+'/data'][x,y] self.assertAlmostEqual(aux[key],foo,delta=0.5)
def test_image_interpolation(self): data_file = tu.get_test_big_data_path('speckle_tracking.h5') process_file = tu.get_test_process_path('to_revise/umpa_test.nxs') run_protected_plugin_runner( tu.set_options(data_file, process_file=process_file))
def test_edf(self): data_file = tu.get_test_big_data_path( 'pymca_live_processing_test/savu_test_result/test_processed.nxs') process_file = tu.get_test_process_path("i08_edf_saver_process.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_i13_ptycho(self): data_file = tu.get_test_big_data_path('68862.nxs') process_file = tu.get_test_process_path('basic_ptycho_process_i13.nxs') run_protected_plugin_runner(tu.set_options(data_file, process_file=process_file))
def test_image_interpolation(self): data_file = tu.get_test_big_data_path('speckle_tracking.h5') process_file = tu.get_test_process_path('umpa_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_nx_ptycho(self): data_file = tu.get_test_big_data_path('NXptychoflipped.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_big_data_path('i13_xrf_tomo_92713.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))
def test_i13_speckle_tracking(self): data_file = tu.get_test_big_data_path('speckle_tracking.h5') process_file = tu.get_test_process_path('i13_speckle_loader_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_big_data_path('i13_xrf_tomo_92713.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))
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_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_edf(self): data_file = tu.get_test_big_data_path('pymca_live_processing_test/savu_test_result/test_processed.nxs') process_file = tu.get_test_process_path("i08_edf_saver_process.nxs") run_protected_plugin_runner(tu.set_options(data_file, process_file=process_file))
def test_nx_ptycho(self): data_file = tu.get_test_big_data_path('NXptychoflipped.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_i08_regression(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_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_i08(self): data_file = tu.get_test_big_data_path( 'pymca_live_processing_test/i08-10471.nxs') process_file = tu.get_test_process_path("i08_basic_process.nxs") run_protected_plugin_runner( tu.set_options(data_file, process_file=process_file))