How to use build_test_case method in Testify

Best Python code snippet using Testify_python

test_functional_preproc.py

Source:test_functional_preproc.py

...83    wf_inputs_string = wf_inputs_string.replace(base_dir, \84                           "BASE_DIRECTORY_HERE")85    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE", 1)86    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")87    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)88        89    assert flag == 2, err90def test_workflow_func_motion_correct_slice_time():91    import os92    import pkg_resources as p93    from qap.functional_preproc import run_func_motion_correct94    from qap.workflow_utils import build_test_case95   96    func_scan = p.resource_filename("qap", os.path.join(test_sub_dir, \97                                    "rest_1", \98                                    "functional_scan", \99                                    "rest.nii.gz"))100    ref_graph = p.resource_filename("qap", os.path.join("test_data", \101                                    "workflow_reference", \102                                    "func_motion_correct_slice_time", \103                                    "graph_func_motion_correct" \104                                    "_slice_time.dot"))105                                    106    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \107                                     "workflow_reference", \108                                     "func_motion_correct_slice_time", \109                                     "wf_inputs.txt"))    110                                   111    # build the workflow112    wf, base_dir = run_func_motion_correct(func_scan, 0, "End", True, False)113         114    115    # get the workflow inputs of the workflow being tested116    wf_inputs_string = str(wf.inputs).replace("\n","")117    118    wf_inputs_string = wf_inputs_string.replace(base_dir, \119                           "BASE_DIRECTORY_HERE")120    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE",\121                                                1)122    wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")123    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)124        125    assert flag == 2, err126 127    128def test_workflow_functional_brain_mask_3dautomask():129    import os130    import pkg_resources as p131    from qap.functional_preproc import run_functional_brain_mask132    from qap.workflow_utils import build_test_case133   134    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \135                                      "rest_1", \136                                      "func_motion_correct", \137                                      "rest_calc_tshift_resample_" \138                                      "volreg.nii.gz"))139    ref_graph = p.resource_filename("qap", os.path.join("test_data", \140                                    "workflow_reference", \141                                    "functional_brain_mask_3dautomask", \142                                    "graph_functional_brain_mask" \143                                    "_3dautomask.dot"))144                                    145    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \146                                    "workflow_reference", \147                                    "functional_brain_mask_3dautomask", \148                                    "wf_inputs.txt"))149                   150    # build the workflow151    wf, base_dir = run_functional_brain_mask(func_motion, use_bet=False, \152                                             run=False)153    154    # get the workflow inputs of the workflow being tested155    wf_inputs_string = str(wf.inputs).replace("\n","")156    157    wf_inputs_string = wf_inputs_string.replace(base_dir, \158                           "BASE_DIRECTORY_HERE")159    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")160            161    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)162        163    assert flag == 2, err164 165    166    167def test_workflow_functional_brain_mask_BET():168    import os169 170    import pkg_resources as p171    from qap.functional_preproc import run_functional_brain_mask172    from qap.workflow_utils import build_test_case173   174    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \175                                      "rest_1", \176                                      "func_motion_correct", \177                                      "rest_calc_tshift_resample_" \178                                      "volreg.nii.gz"))179                                                                        180    ref_graph = p.resource_filename("qap", os.path.join("test_data", \181                                    "workflow_reference", \182                                    "functional_brain_mask_BET", \183                                    "graph_functional_brain_mask_BET.dot"))184                                    185    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \186                                     "workflow_reference", \187                                     "functional_brain_mask_BET", \188                                     "wf_inputs.txt"))189                                   190    # build the workflow191    wf, base_dir = run_functional_brain_mask(func_motion, use_bet=True, \192                                             run=False)193    # get the workflow inputs of the workflow being tested194    wf_inputs_string = str(wf.inputs).replace("\n","")195    196    wf_inputs_string = wf_inputs_string.replace(base_dir, \197                           "BASE_DIRECTORY_HERE")198    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")199    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)200        201    assert flag == 2, err202def test_workflow_mean_functional():203    import os204    import pkg_resources as p205    from qap.functional_preproc import run_mean_functional206    from qap.workflow_utils import build_test_case207    208    func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \209                                      "rest_1", \210                                      "func_motion_correct", \211                                      "rest_calc_tshift_resample_" \212                                      "volreg.nii.gz"))213                                    214    ref_graph = p.resource_filename("qap", os.path.join("test_data", \215                                    "workflow_reference", \216                                    "mean_functional", \217                                    "graph_mean_functional.dot"))218                                    219    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \220                                     "workflow_reference", \221                                     "mean_functional", \222                                     "wf_inputs.txt"))223                                   224    # build the workflow225    wf, base_dir = run_mean_functional(func_motion, False)226    # get the workflow inputs of the workflow being tested227    wf_inputs_string = str(wf.inputs).replace("\n","")228    229    wf_inputs_string = wf_inputs_string.replace(base_dir, \230                           "BASE_DIRECTORY_HERE")231    wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")232    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)233        234    assert flag == 2, err235def run_all_tests_functional_preproc():236    test_get_idx_whole_timeseries()237    test_get_idx_partial_timeseries()238    test_get_idx_partial_timeseries_overshoot()239    test_workflow_func_motion_correct_no_slice_time()240    test_workflow_func_motion_correct_slice_time()241    test_workflow_functional_brain_mask_3dautomask()242    test_workflow_functional_brain_mask_BET()243    test_workflow_mean_functional()   244    245    246

test_anatomical_preproc.py

Source:test_anatomical_preproc.py

...27    28    wf_inputs_string = wf_inputs_string.replace(base_dir, \29                           "BASE_DIRECTORY_HERE")30    wf_inputs_string = wf_inputs_string.replace(anat_scan, "IN_FILE_HERE")31    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)32        33    assert flag == 2, err34  35    36def test_workflow_anatomical_skullstrip():37    ''' unit test for the anatomical skullstrip workflow BUILDER '''38    import os39    import commands40    41    import pkg_resources as p42    from qap.anatomical_preproc import run_anatomical_skullstrip43    from qap.workflow_utils import build_test_case44    anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \45                                        "anat_1", \46                                        "anatomical_reorient", \47                                        "mprage_resample.nii.gz"))48    ref_graph = p.resource_filename("qap", os.path.join("test_data", \49                                    "workflow_reference", \50                                    "anatomical_skullstrip", \51                                    "graph_anatomical_skullstrip.dot"))52                                    53    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \54                                     "workflow_reference", \55                                     "anatomical_skullstrip", \56                                     "wf_inputs.txt"))57    # build the workflow and return it58    wf, base_dir = run_anatomical_skullstrip(anat_reorient, False)59    # get the workflow inputs of the workflow being tested60    wf_inputs_string = str(wf.inputs).replace("\n","")61    62    wf_inputs_string = wf_inputs_string.replace(base_dir, \63                           "base_directory_here")64    wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_here", 1)65    wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_a_here")66    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)67        68    assert flag == 2, err69def test_workflow_flirt_anatomical_linear_registration():70    ''' unit test for the anatomical reorient workflow BUILDER '''71    import os72    import pkg_resources as p73    from qap.anatomical_preproc import run_flirt_anatomical_linear_registration74    from qap.workflow_utils import build_test_case75    anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \76                                     "anat_1", \77                                     "anatomical_brain", \78                                     "mprage_resample_calc.nii.gz"))79    template_brain = p.resource_filename("qap", os.path.join("test_data", \80                                         "MNI152_T1_2mm_brain.nii.gz"))81    ref_graph = p.resource_filename("qap", os.path.join("test_data", \82                                    "workflow_reference", \83                                    "flirt_anatomical_linear_registration", \84                                    "graph_flirt_anatomical_linear" \85                                    "_registration.dot"))86                                    87    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \88                                     "workflow_reference", \89                                     "flirt_anatomical_linear_registration", \90                                     "wf_inputs.txt"))91    # build the workflow and return it92    wf, base_dir = run_flirt_anatomical_linear_registration(anat_brain, \93                                                            template_brain, \94                                                            False)95    # get the workflow inputs of the workflow being tested96    wf_inputs_string = str(wf.inputs).replace("\n","")97    98    wf_inputs_string = wf_inputs_string.replace(base_dir, \99                           "base_directory_here")100    wf_inputs_string = wf_inputs_string.replace(anat_brain, "in_file_here")101    wf_inputs_string = wf_inputs_string.replace(template_brain, \102                                                    "reference_here")103    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)104        105    assert flag == 2, err106       107    108def test_workflow_segmentation():109    ''' unit test for the segmentation workflow BUILDER '''110    import os111    import commands112    113    import pkg_resources as p114    from qap.anatomical_preproc import run_segmentation_workflow115    from qap.workflow_utils import build_test_case116    anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \117                                     "anat_1", \118                                     "anatomical_brain", \119                                     "mprage_resample_calc.nii.gz"))120    ref_graph = p.resource_filename("qap", os.path.join("test_data", \121                                    "workflow_reference", \122                                    "segmentation", \123                                    "graph_segmentation.dot"))124    ref_inputs = p.resource_filename("qap", os.path.join("test_data", \125                                     "workflow_reference", \126                                     "segmentation", \127                                     "wf_inputs.txt"))128    # build the workflow and return it129    wf, base_dir = run_segmentation_workflow(anat_brain, False)130    # get the workflow inputs of the workflow being tested131    wf_inputs_string = str(wf.inputs).replace("\n","")132    133    wf_inputs_string = wf_inputs_string.replace(base_dir, \134                           "base_directory_here")135    list_input = "['" + anat_brain + "']"136    wf_inputs_string = wf_inputs_string.replace(list_input, "in_files_here")137    flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)138        139    assert flag == 2, err140def run_all_tests_anatomical_preproc():141    test_workflow_anatomical_reorient()142    test_workflow_anatomical_skullstrip()143    test_workflow_flirt_anatomical_linear_registration()...

json.py

Source:json.py

...62    """Check to see if specified test at endpoint should be auto run"""63    with open(directory) as stream:64        data = json.load(stream)65        test_data = data[endpoint]66        auto_run = parse.build_test_case(test_data, test_name)["auto_run"]67        return auto_run68def endpoint_load_all_tests(directory, endpoint):69    """Load list of all test cases from an endpoint"""70    with open(directory) as stream:71        data = json.load(stream)72        test_dict = data[endpoint]73        LOG.debug("Loaded test data : %s", test_dict)74        return test_dict75def endpoint_load_test_case(directory, endpoint, test_name):76    """Load test description, payload, and expected results at index"""77    with open(directory) as stream:78        data = json.load(stream)79        test_data = data[endpoint]80        return parse.build_test_case(test_data, test_name)81def endpoint_load_base_path(directory, endpoint):82    """Load base path from endpoint"""83    return endpoint_load_test_path(directory, endpoint, BASE)84def endpoint_load_test_path(directory, endpoint, test_name):85    """Load expected path for specified endpoint and test"""86    with open(directory) as stream:87        data = json.load(stream)88        test_data = data[endpoint]89        path = parse.build_test_case(test_data, test_name)["path"]90        return path91def endpoint_load_base_parameters(directory, endpoint):92    """Load base parameters from endpoint"""93    return endpoint_load_test_parameters(directory, endpoint, BASE)94def endpoint_load_test_parameters(directory, endpoint, test_name):95    """Load expected parameters for specified endpoint and test"""96    with open(directory) as stream:97        data = json.load(stream)98        test_data = data[endpoint]99        parameters = parse.build_test_case(test_data, test_name)["parameters"]100        return parameters101def endpoint_load_base_payload(directory, endpoint):102    """Load base payload from endpoint"""103    return endpoint_load_test_payload(directory, endpoint, BASE)104def endpoint_load_test_payload(directory, endpoint, test_name):105    """Load expected payload for specified endpoint and test"""106    with open(directory) as stream:107        data = json.load(stream)108        test_data = data[endpoint]109        payload = parse.build_test_case(test_data, test_name)["payload"]110        return payload111def endpoint_load_base_status_codes(directory, endpoint):112    """Load base status_code from endpoint"""113    return endpoint_load_test_status_codes(directory, endpoint, BASE)114def endpoint_load_test_status_codes(directory, endpoint, test_name):115    """Load expected status code for specified endpoint and test"""116    with open(directory) as stream:117        data = json.load(stream)118        test_data = data[endpoint]119        status_codes = parse.build_test_case(test_data, test_name)["status_code"]120        return status_codes121def endpoint_load_base_response(directory, endpoint):122    """Load base response from endpoint"""123    return endpoint_load_test_response(directory, endpoint, BASE)124def endpoint_load_test_response(directory, endpoint, test_name):125    """Load expected response for specified endpoint and test"""126    with open(directory) as stream:127        data = json.load(stream)128        test_data = data[endpoint]129        response = parse.build_test_case(test_data, test_name)["response"]130        return response131###################################################################################################132# JSON Utilites133###################################################################################################134def load_response_data(response):135    """Return the data of the response body"""136    try:137        response_data = json.loads(response.text)138    except json.decoder.JSONDecodeError:139        response_data = {}...

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