def test_fetch_localizer_calculation_task(): local_url = "file://" + get_datadir() ids = np.asarray(['S%2d' % i for i in range(94)]) ids = ids.view(dtype=[('subject_id', 'S3')]) get_file_mock().add_csv('cubicwebexport.csv', ids) get_file_mock().add_csv('cubicwebexport2.csv', ids) # Disabled: cannot be tested without actually fetching covariates CSV file # All subjects dataset = datasets.fetch_localizer_calculation_task(data_dir=get_tmpdir(), url=local_url, verbose=0) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.cmaps), 94) # 20 subjects dataset = datasets.fetch_localizer_calculation_task(n_subjects=20, data_dir=get_tmpdir(), url=local_url, verbose=0) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 20) assert_equal(len(dataset.cmaps), 20)
def test_fetch_oasis_vbm(): local_url = "file://" + get_datadir() ids = np.asarray(['OAS1_%4d' % i for i in range(457)]) ids = ids.view(dtype=[('ID', 'S9')]) get_file_mock().add_csv('oasis_cross-sectional.csv', ids) # Disabled: cannot be tested without actually fetching covariates CSV file dataset = datasets.fetch_oasis_vbm(data_dir=get_tmpdir(), url=local_url, verbose=0) assert_equal(len(dataset.gray_matter_maps), 403) assert_equal(len(dataset.white_matter_maps), 403) assert_true(isinstance(dataset.gray_matter_maps[0], _basestring)) assert_true(isinstance(dataset.white_matter_maps[0], _basestring)) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.data_usage_agreement, _basestring)) assert_equal(len(get_url_request().urls), 3) dataset = datasets.fetch_oasis_vbm(data_dir=get_tmpdir(), url=local_url, dartel_version=False, verbose=0) assert_equal(len(dataset.gray_matter_maps), 415) assert_equal(len(dataset.white_matter_maps), 415) assert_true(isinstance(dataset.gray_matter_maps[0], _basestring)) assert_true(isinstance(dataset.white_matter_maps[0], _basestring)) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.data_usage_agreement, _basestring)) assert_equal(len(get_url_request().urls), 4)
def test_fetch_localizer_contrasts(): local_url = "file://" + get_datadir() ids = np.asarray([('S%2d' % i).encode() for i in range(94)]) ids = ids.view(dtype=[('subject_id', 'S3')]) get_file_mock().add_csv('cubicwebexport.csv', ids) get_file_mock().add_csv('cubicwebexport2.csv', ids) # Disabled: cannot be tested without actually fetching covariates CSV file # All subjects dataset = datasets.fetch_localizer_contrasts(["checkerboard"], data_dir=get_tmpdir(), url=local_url, verbose=0) assert_true(dataset.anats is None) assert_true(dataset.tmaps is None) assert_true(dataset.masks is None) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.cmaps), 94) # 20 subjects dataset = datasets.fetch_localizer_contrasts(["checkerboard"], n_subjects=20, data_dir=get_tmpdir(), url=local_url, verbose=0) assert_true(dataset.anats is None) assert_true(dataset.tmaps is None) assert_true(dataset.masks is None) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_equal(len(dataset.cmaps), 20) assert_equal(dataset.ext_vars.size, 20) # Multiple contrasts dataset = datasets.fetch_localizer_contrasts( ["checkerboard", "horizontal checkerboard"], n_subjects=20, data_dir=get_tmpdir(), verbose=0) assert_true(dataset.anats is None) assert_true(dataset.tmaps is None) assert_true(dataset.masks is None) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_equal(len(dataset.cmaps), 20 * 2) # two contrasts are fetched assert_equal(dataset.ext_vars.size, 20) # get_anats=True dataset = datasets.fetch_localizer_contrasts(["checkerboard"], data_dir=get_tmpdir(), url=local_url, get_anats=True, verbose=0) assert_true(dataset.masks is None) assert_true(dataset.tmaps is None) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.anats[0], _basestring)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.anats), 94) assert_equal(len(dataset.cmaps), 94) # get_masks=True dataset = datasets.fetch_localizer_contrasts(["checkerboard"], data_dir=get_tmpdir(), url=local_url, get_masks=True, verbose=0) assert_true(dataset.anats is None) assert_true(dataset.tmaps is None) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_true(isinstance(dataset.masks[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.cmaps), 94) assert_equal(len(dataset.masks), 94) # get_tmaps=True dataset = datasets.fetch_localizer_contrasts(["checkerboard"], data_dir=get_tmpdir(), url=local_url, get_tmaps=True, verbose=0) assert_true(dataset.anats is None) assert_true(dataset.masks is None) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_true(isinstance(dataset.tmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.cmaps), 94) assert_equal(len(dataset.tmaps), 94) # all get_*=True dataset = datasets.fetch_localizer_contrasts(["checkerboard"], data_dir=get_tmpdir(), url=local_url, get_anats=True, get_masks=True, get_tmaps=True, verbose=0) assert_true(isinstance(dataset.ext_vars, np.recarray)) assert_true(isinstance(dataset.anats[0], _basestring)) assert_true(isinstance(dataset.cmaps[0], _basestring)) assert_true(isinstance(dataset.masks[0], _basestring)) assert_true(isinstance(dataset.tmaps[0], _basestring)) assert_equal(dataset.ext_vars.size, 94) assert_equal(len(dataset.anats), 94) assert_equal(len(dataset.cmaps), 94) assert_equal(len(dataset.masks), 94) assert_equal(len(dataset.tmaps), 94)