def test_table_output(tmpdir):
# create mock data
stat_img_name = os.path.basename(STAT_IMG)[:-7]
# temporary output
output_dir = tmpdir.mkdir('mni_test')
atlasreader.create_output(STAT_IMG, cluster_extent=20,
voxel_thresh=4, atlas='default',
outdir=output_dir)
# test if output tables contain expected output
df = pd.read_csv(output_dir.join('{}_clusters.csv'.format(stat_img_name)))
assert np.allclose(df[df.keys()[1:6]].values, EXPECTED_TABLES['cluster'])
df = pd.read_csv(output_dir.join('{}_peaks.csv'.format(stat_img_name)))
assert np.allclose(df[df.keys()[1:6]].values, EXPECTED_TABLES['peak'])
def main():
"""
The primary entrypoint for calling atlas reader via the command line
All parameters are read via argparse, so this should only be called from
the command line!
"""
opts = _get_parser()
create_output(opts.filename,
atlas=check_atlases(opts.atlas),
voxel_thresh=opts.voxel_thresh,
cluster_extent=opts.cluster_extent,
prob_thresh=opts.prob_thresh,
outdir=opts.outdir)
def test_create_output(tmpdir):
# create mock data
stat_img_name = os.path.basename(STAT_IMG)[:-7]
# temporary output
output_dir = tmpdir.mkdir('mni_test')
atlasreader.create_output(STAT_IMG, cluster_extent=20,
atlas=['Harvard_Oxford'],
outdir=output_dir)
# test if output exists and if the key .csv and .png files were created
assert output_dir.exists()
assert len(output_dir.listdir()) > 0
assert output_dir.join('{}_clusters.csv'.format(stat_img_name)).isfile()
assert output_dir.join('{}_peaks.csv'.format(stat_img_name)).isfile()
assert output_dir.join('{}.png'.format(stat_img_name)).isfile()
def test_plotting(tmpdir):
"""Test functionality of kwarg implementation"""
# temporary output
output_dir = tmpdir.mkdir('mni_test')
# overwrite some default params
atlasreader.create_output(STAT_IMG, cluster_extent=20,
atlas=['Harvard_Oxford'],
outdir=output_dir,
glass_plot_kws={'display_mode': 'ortho'},
stat_plot_kws={'black_bg': False})
# add new parameter not already set by default
atlasreader.create_output(STAT_IMG, cluster_extent=20,
atlas=['Harvard_Oxford'],
outdir=output_dir,
glass_plot_kws={'alpha': .4})
def test_table_output(tmpdir):
# create mock data
stat_img_name = os.path.basename(STAT_IMG)[:-7]
# temporary output
output_dir = tmpdir.mkdir('mni_test')
atlasreader.create_output(STAT_IMG, cluster_extent=20,
atlas=['AAL', 'desikan_killiany',
'Harvard_Oxford'],
outdir=output_dir)
# test if output tables contain expected output
cluster_checksum = hashlib.md5(open(output_dir.join(
'{}_clusters.csv'.format(stat_img_name)), 'rb').read()).hexdigest()
peak_checksum = hashlib.md5(open(output_dir.join(
'{}_peaks.csv'.format(stat_img_name)), 'rb').read()).hexdigest()
assert cluster_checksum == 'b03705caeaad17b3cbc9f9b6042bdd72'
assert peak_checksum == '061b505b6a505053e4e8e4e25d051b1a'
def test_create_output(tmpdir):
# create mock data
motor_images = fetch_neurovault_motor_task()
stat_img = motor_images.images[0]
stat_img_name = os.path.basename(stat_img)[:-7]
# temporary output
output_dir = tmpdir.mkdir('mni_test')
atlasreader.create_output(stat_img,
atlas=['Harvard_Oxford'],
outdir=output_dir)
# test if output exists and if the key .csv and .png files were created
assert os.path.exists(output_dir)
assert len(os.listdir(output_dir)) > 0
assert os.path.isfile(
os.path.join(output_dir, '{}_clusters.csv'.format(stat_img_name)))
assert os.path.isfile(
os.path.join(output_dir, '{}_peaks.csv'.format(stat_img_name)))
assert os.path.isfile(
os.path.join(output_dir, '{}.png'.format(stat_img_name)))
