def test_workflow_func_motion_correct_no_slice_time():
import os
import nibabel as nb
import pkg_resources as p
from qap.functional_preproc import run_func_motion_correct
from qap.workflow_utils import build_test_case
func_scan = p.resource_filename("qap", os.path.join(test_sub_dir, "rest_1", "functional_scan", "rest.nii.gz"))
ref_graph = p.resource_filename(
"qap", os.path.join("test_data", "workflow_reference", "func_motion_correct", "graph_func_motion_correct.dot")
)
ref_inputs = p.resource_filename(
"qap", os.path.join("test_data", "workflow_reference", "func_motion_correct", "wf_inputs.txt")
)
# build the workflow
wf, base_dir = run_func_motion_correct(func_scan, 0, "End", False, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, "BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE", 1)
wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_mean_functional():
import os
import pkg_resources as p
from qap.functional_preproc import run_mean_functional
from qap.workflow_utils import build_test_case
func_motion = p.resource_filename(
"qap", os.path.join(test_sub_dir, "rest_1", "func_motion_correct", "rest_calc_tshift_resample_" "volreg.nii.gz")
)
ref_graph = p.resource_filename(
"qap", os.path.join("test_data", "workflow_reference", "mean_functional", "graph_mean_functional.dot")
)
ref_inputs = p.resource_filename(
"qap", os.path.join("test_data", "workflow_reference", "mean_functional", "wf_inputs.txt")
)
# build the workflow
wf, base_dir = run_mean_functional(func_motion, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, "BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_mask():
''' unit test for the QAP head mask workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_qap_mask
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
flirt_affine_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"flirt_affine_xfm", \
"flirt_affine_xfm.mat"))
template_skull = p.resource_filename("qap", os.path.join("test_data", \
"MNI152_T1_2mm.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_head_mask", \
"graph_qap_head_mask.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_head_mask", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_qap_mask(anat_reorient, flirt_affine_xfm, \
template_skull, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"input_skull_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"infile_here", 1)
wf_inputs_string = wf_inputs_string.replace(template_skull, \
"standard_here", 1)
wf_inputs_string = wf_inputs_string.replace(flirt_affine_xfm, \
"transform_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"in_file_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_flirt_anatomical_linear_registration():
''' unit test for the anatomical reorient workflow BUILDER '''
import os
import pkg_resources as p
from qap.anatomical_preproc import run_flirt_anatomical_linear_registration
from qap.workflow_utils import build_test_case
anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_brain", \
"mprage_resample_calc.nii.gz"))
template_brain = p.resource_filename("qap", os.path.join("test_data", \
"MNI152_T1_2mm_brain.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"flirt_anatomical_linear_registration", \
"graph_flirt_anatomical_linear" \
"_registration.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"flirt_anatomical_linear_registration", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_flirt_anatomical_linear_registration(anat_brain, \
template_brain, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
wf_inputs_string = wf_inputs_string.replace(anat_brain, "in_file_here")
wf_inputs_string = wf_inputs_string.replace(template_brain, \
"reference_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_segmentation():
''' unit test for the segmentation workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_segmentation_workflow
from qap.workflow_utils import build_test_case
anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_brain", \
"mprage_resample_calc.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"segmentation", \
"graph_segmentation.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"segmentation", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_segmentation_workflow(anat_brain, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
list_input = "['" + anat_brain + "']"
wf_inputs_string = wf_inputs_string.replace(list_input, "in_files_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_anatomical_skullstrip():
''' unit test for the anatomical skullstrip workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_anatomical_skullstrip
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_skullstrip", \
"graph_anatomical_skullstrip.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_skullstrip", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_anatomical_skullstrip(anat_reorient, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_a_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_flirt_anatomical_linear_registration():
''' unit test for the anatomical reorient workflow BUILDER '''
import os
import pkg_resources as p
from qap.anatomical_preproc import run_flirt_anatomical_linear_registration
from qap.workflow_utils import build_test_case
anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_brain", \
"mprage_resample_calc.nii.gz"))
template_brain = p.resource_filename("qap", os.path.join("test_data", \
"MNI152_T1_2mm_brain.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"flirt_anatomical_linear_registration", \
"graph_flirt_anatomical_linear" \
"_registration.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"flirt_anatomical_linear_registration", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_flirt_anatomical_linear_registration(anat_brain, \
template_brain, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
wf_inputs_string = wf_inputs_string.replace(anat_brain, "in_file_here")
wf_inputs_string = wf_inputs_string.replace(template_brain, \
"reference_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_anatomical_reorient():
''' unit test for the anatomical reorient workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_anatomical_reorient
from qap.workflow_utils import build_test_case
anat_scan = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_scan", \
"mprage.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_reorient", \
"graph_anatomical_reorient.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_reorient", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_anatomical_reorient(anat_scan, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(anat_scan, "IN_FILE_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_anatomical_skullstrip():
''' unit test for the anatomical skullstrip workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_anatomical_skullstrip
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_skullstrip", \
"graph_anatomical_skullstrip.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_skullstrip", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_anatomical_skullstrip(anat_reorient, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
wf_inputs_string = wf_inputs_string.replace(anat_reorient, "in_file_here",
1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient,
"in_file_a_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_segmentation():
''' unit test for the segmentation workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_segmentation_workflow
from qap.workflow_utils import build_test_case
anat_brain = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_brain", \
"mprage_resample_calc.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"segmentation", \
"graph_segmentation.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"segmentation", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_segmentation_workflow(anat_brain, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here")
list_input = "['" + anat_brain + "']"
wf_inputs_string = wf_inputs_string.replace(list_input, "in_files_here")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_functional_brain_mask_3dautomask():
import os
import pkg_resources as p
from qap.functional_preproc import run_functional_brain_mask
from qap.workflow_utils import build_test_case
func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"func_motion_correct", \
"rest_calc_tshift_resample_" \
"volreg.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"functional_brain_mask_3dautomask", \
"graph_functional_brain_mask" \
"_3dautomask.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"functional_brain_mask_3dautomask", \
"wf_inputs.txt"))
# build the workflow
wf, base_dir = run_functional_brain_mask(func_motion, use_bet=False, \
run=False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(func_motion, "IN_FILE_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_func_motion_correct_slice_time():
import os
import pkg_resources as p
from qap.functional_preproc import run_func_motion_correct
from qap.workflow_utils import build_test_case
func_scan = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_scan", \
"rest.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"func_motion_correct_slice_time", \
"graph_func_motion_correct" \
"_slice_time.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"func_motion_correct_slice_time", \
"wf_inputs.txt"))
# build the workflow
wf, base_dir = run_func_motion_correct(func_scan, 0, "End", True, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILE_A_HERE",\
1)
wf_inputs_string = wf_inputs_string.replace(func_scan, "IN_FILES_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_anatomical_reorient():
''' unit test for the anatomical reorient workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.anatomical_preproc import run_anatomical_reorient
from qap.workflow_utils import build_test_case
anat_scan = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_scan", \
"mprage.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_reorient", \
"graph_anatomical_reorient.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"anatomical_reorient", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_anatomical_reorient(anat_scan, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"BASE_DIRECTORY_HERE")
wf_inputs_string = wf_inputs_string.replace(anat_scan, "IN_FILE_HERE")
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_anatomical_spatial():
''' unit test for the QAP anatomical spatial workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_anatomical_spatial
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
qap_head_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"qap_head_mask", \
"mprage_resample_thresh_maths_maths" \
"_maths.nii.gz"))
anat_csf_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_csf_mask", \
"segment_seg_0.nii.gz"))
anat_gm_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_gm_mask", \
"segment_seg_1.nii.gz"))
anat_wm_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_wm_mask", \
"segment_seg_2.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_anatomical_spatial", \
"graph_qap_anatomical_spatial.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_anatomical_spatial", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "anat_1"
site_name = "site_1"
# build the workflow and return it
wf, base_dir = run_single_qap_anatomical_spatial(anat_reorient, \
qap_head_mask, \
anat_csf_mask, \
anat_gm_mask, \
anat_wm_mask, \
subject_id, session_id, \
scan_id, site_name, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_csf_mask, \
"anatomical_csf_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_gm_mask, \
"anatomical_gm_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"anatomical_reorient_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_wm_mask, \
"anatomical_wm_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(qap_head_mask, \
"head_mask_path_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_functional_temporal():
''' unit test for the QAP functional temporal workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_functional_temporal
from qap.workflow_utils import build_test_case
func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"func_motion_correct", \
"rest_calc_tshift_resample_volreg" \
".nii.gz"))
func_brain_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg" \
"_mask.nii.gz"))
coord_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"coordinate_transformation", \
"rest_calc_tshift_resample.aff12.1D"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_temporal", \
"graph_qap_functional_temporal.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_temporal", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "rest_1"
site_name = "site_1"
# build the workflow and return it
wf, base_dir = run_single_qap_functional_temporal(func_motion, \
func_brain_mask, \
subject_id, session_id,\
scan_id, site_name, \
coordinate_transformation=coord_xfm, \
run=False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(coord_xfm, \
"coord_xfm_matrix_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_brain_mask, \
"func_brain_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_motion, \
"func_motion_correct_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_functional_spatial():
''' unit test for the QAP functional spatial workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_functional_spatial
from qap.workflow_utils import build_test_case
mean_func = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"mean_functional", \
"rest_calc_tshift_resample_volreg" \
"_tstat.nii.gz"))
func_brain_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg" \
"_mask.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_spatial", \
"graph_qap_functional_spatial.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_spatial", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "rest_1"
site_name = "site_1"
ghost_direction = "x"
# build the workflow and return it
wf, base_dir = run_single_qap_functional_spatial(mean_func, \
func_brain_mask, \
subject_id, session_id, \
scan_id, site_name, \
ghost_direction, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n", "")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_brain_mask, \
"func_brain_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(mean_func, \
"mean_epi_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_anatomical_spatial():
''' unit test for the QAP anatomical spatial workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_anatomical_spatial
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
qap_head_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"qap_head_mask", \
"mprage_resample_thresh_maths_maths" \
"_maths.nii.gz"))
anat_csf_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_csf_mask", \
"segment_seg_0.nii.gz"))
anat_gm_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_gm_mask", \
"segment_seg_1.nii.gz"))
anat_wm_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_wm_mask", \
"segment_seg_2.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_anatomical_spatial", \
"graph_qap_anatomical_spatial.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_anatomical_spatial", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "anat_1"
site_name = "site_1"
# build the workflow and return it
wf, base_dir = run_single_qap_anatomical_spatial(anat_reorient, \
qap_head_mask, \
anat_csf_mask, \
anat_gm_mask, \
anat_wm_mask, \
subject_id, session_id, \
scan_id, site_name, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_csf_mask, \
"anatomical_csf_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_gm_mask, \
"anatomical_gm_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"anatomical_reorient_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_wm_mask, \
"anatomical_wm_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(qap_head_mask, \
"head_mask_path_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_mask():
''' unit test for the QAP head mask workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_qap_mask
from qap.workflow_utils import build_test_case
anat_reorient = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"anatomical_reorient", \
"mprage_resample.nii.gz"))
flirt_affine_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"anat_1", \
"flirt_affine_xfm", \
"flirt_affine_xfm.mat"))
template_skull = p.resource_filename("qap", os.path.join("test_data", \
"MNI152_T1_2mm.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_head_mask", \
"graph_qap_head_mask.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_head_mask", \
"wf_inputs.txt"))
# build the workflow and return it
wf, base_dir = run_qap_mask(anat_reorient, flirt_affine_xfm, \
template_skull, False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"input_skull_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"infile_here", 1)
wf_inputs_string = wf_inputs_string.replace(template_skull, \
"standard_here", 1)
wf_inputs_string = wf_inputs_string.replace(flirt_affine_xfm, \
"transform_here", 1)
wf_inputs_string = wf_inputs_string.replace(anat_reorient, \
"in_file_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_functional_temporal():
''' unit test for the QAP functional temporal workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_functional_temporal
from qap.workflow_utils import build_test_case
func_motion = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"func_motion_correct", \
"rest_calc_tshift_resample_volreg" \
".nii.gz"))
func_brain_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg" \
"_mask.nii.gz"))
coord_xfm = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"coordinate_transformation", \
"rest_calc_tshift_resample.aff12.1D"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_temporal", \
"graph_qap_functional_temporal.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_temporal", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "rest_1"
site_name = "site_1"
# build the workflow and return it
wf, base_dir = run_single_qap_functional_temporal(func_motion, \
func_brain_mask, \
subject_id, session_id,\
scan_id, site_name, \
coordinate_transformation=coord_xfm, \
run=False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(coord_xfm, \
"coord_xfm_matrix_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_brain_mask, \
"func_brain_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_motion, \
"func_motion_correct_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
def test_workflow_qap_functional_spatial():
''' unit test for the QAP functional spatial workflow BUILDER '''
import os
import commands
import pkg_resources as p
from qap.qap_workflows import run_single_qap_functional_spatial
from qap.workflow_utils import build_test_case
mean_func = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"mean_functional", \
"rest_calc_tshift_resample_volreg" \
"_tstat.nii.gz"))
func_brain_mask = p.resource_filename("qap", os.path.join(test_sub_dir, \
"rest_1", \
"functional_brain_mask", \
"rest_calc_tshift_resample_volreg" \
"_mask.nii.gz"))
ref_graph = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_spatial", \
"graph_qap_functional_spatial.dot"))
ref_inputs = p.resource_filename("qap", os.path.join("test_data", \
"workflow_reference", \
"qap_functional_spatial", \
"wf_inputs.txt"))
subject_id = "1019436"
session_id = "session_1"
scan_id = "rest_1"
site_name = "site_1"
ghost_direction = "x"
# build the workflow and return it
wf, base_dir = run_single_qap_functional_spatial(mean_func, \
func_brain_mask, \
subject_id, session_id, \
scan_id, site_name, \
ghost_direction, \
False)
# get the workflow inputs of the workflow being tested
wf_inputs_string = str(wf.inputs).replace("\n","")
wf_inputs_string = wf_inputs_string.replace(base_dir, \
"base_directory_here", 1)
wf_inputs_string = wf_inputs_string.replace(func_brain_mask, \
"func_brain_mask_here", 1)
wf_inputs_string = wf_inputs_string.replace(mean_func, \
"mean_epi_here", 1)
flag, err = build_test_case(wf, ref_inputs, ref_graph, wf_inputs_string)
assert flag == 2, err
