def test_detection_full(tmpdir):
tmpdir = str(tmpdir)
cellfinder_args = [
"cellfinder",
"-s",
signal_data,
"-b",
background_data,
"-o",
tmpdir,
"-v",
z_pix,
y_pix,
x_pix,
"--orientation",
"psl",
"--n-free-cpus",
"0",
"--no-register",
"--save-planes",
]
sys.argv = cellfinder_args
cellfinder_run()
cells_test_xml = os.path.join(tmpdir, "points", "cell_classification.xml")
cells_validation = cell_io.get_cells(cells_validation_xml)
cells_test = cell_io.get_cells(cells_test_xml)
num_non_cells_validation = sum(
[cell.type == 1 for cell in cells_validation]
)
num_cells_validation = sum([cell.type == 2 for cell in cells_validation])
num_non_cells_test = sum([cell.type == 1 for cell in cells_test])
num_cells_test = sum([cell.type == 2 for cell in cells_test])
assert isclose(
num_non_cells_validation,
num_non_cells_test,
abs_tol=DETECTION_TOLERANCE,
)
assert isclose(
num_cells_validation, num_cells_test, abs_tol=DETECTION_TOLERANCE
)
def test_register(tmpdir, test_config_path):
output_directory = os.path.join(str(tmpdir), "output")
cellfinder_args = [
"cellfinder",
"-s",
data_dir,
"-b",
data_dir,
"-o",
output_directory,
"-x",
x_pix,
"-y",
y_pix,
"-z",
z_pix,
"--n-free-cpus",
"0",
"--registration-config",
test_config_path,
"--register",
"--no-detection",
"--no-classification",
]
sys.argv = cellfinder_args
cellfinder_run()
output_directory = os.path.join(output_directory, "registration")
# a hack because testing on linux on travis is 100% identical to local,
# but windows is not
if platform.system() == "Linux":
image_list = [
"annotations.nii",
"boundaries.nii",
"brain_filtered.nii",
"control_point_file.nii",
"downsampled.nii",
"hemispheres.nii",
"inverse_control_point_file.nii",
"registered_atlas.nii",
"registered_hemispheres.nii",
"downsampled_channel_0.nii",
]
else:
image_list = [
"annotations.nii",
# "boundaries.nii",
"brain_filtered.nii",
"control_point_file.nii",
"downsampled.nii",
"hemispheres.nii",
"inverse_control_point_file.nii",
# "registered_atlas.nii",
"registered_hemispheres.nii",
"downsampled_channel_0.nii",
]
for image in image_list:
are_images_equal(image, output_directory, test_output_dir)
assert get_text_lines(os.path.join(
output_directory, "affine_matrix.txt")) == get_text_lines(
os.path.join(test_output_dir, "affine_matrix.txt"))
assert get_text_lines(
os.path.join(output_directory,
"invert_affine_matrix.txt")) == get_text_lines(
os.path.join(test_output_dir,
"invert_affine_matrix.txt"))
pd.testing.assert_frame_equal(
pd.read_csv(os.path.join(output_directory, "volumes.csv")),
pd.read_csv(os.path.join(test_output_dir, "volumes.csv")),
check_exact=False,
check_less_precise=check_less_precise_pd,
)
def test_registration_niftyreg(tmpdir):
output_directory = os.path.join(str(tmpdir), "output")
cellfinder_args = [
"cellfinder",
"-s",
data_dir,
"-b",
data_dir,
"-o",
output_directory,
"-v",
z_pix,
y_pix,
x_pix,
"--orientation",
"psl",
"--n-free-cpus",
"0",
"--atlas",
"allen_mouse_100um",
"--no-detection",
"--no-classification",
"--no-analyse",
"--no-figures",
]
sys.argv = cellfinder_args
cellfinder_run()
# none of this testing is ideal, as results seem to vary between systems
if platform.system() == "Linux":
image_list = [
"boundaries.tiff",
"deformation_field_0.tiff",
"deformation_field_1.tiff",
"deformation_field_2.tiff",
"downsampled.tiff",
"downsampled_channel_0.tiff",
"downsampled_standard.tiff",
"downsampled_standard_channel_0.tiff",
"registered_atlas.tiff",
"registered_hemispheres.tiff",
]
else:
image_list = [
"boundaries.tiff",
"deformation_field_0.tiff",
"deformation_field_1.tiff",
"deformation_field_2.tiff",
"downsampled.tiff",
"downsampled_channel_0.tiff",
# "downsampled_standard.tiff",
# "downsampled_standard_channel_0.tiff",
# "registered_atlas.tiff",
# "registered_hemispheres.tiff",
]
output_directory = os.path.join(output_directory, "registration")
for image in image_list:
are_images_equal(image, output_directory, test_niftyreg_output)
if platform.system() == "Linux":
pd.testing.assert_frame_equal(
pd.read_csv(os.path.join(output_directory, "volumes.csv")),
pd.read_csv(os.path.join(test_niftyreg_output, "volumes.csv")),
)