import os from graphpype.nodes.correl_mat import (ExtractTS, IntersectMask, ExtractMeanTS, RegressCovar, ComputeConfCorMat) from graphpype.utils import _make_tmp_dir from graphpype.utils_tests import load_test_data data_path = load_test_data("data_nii") img_file = os.path.join(data_path, "wrsub-01_task-rest_bold.nii") gm_mask_file = os.path.join(data_path, "rwc1sub-01_T1w.nii") wm_mask_file = os.path.join(data_path, "rwc2sub-01_T1w.nii") csf_mask_file = os.path.join(data_path, "rwc3sub-01_T1w.nii") indexed_mask_file = os.path.join(data_path, "ROI_HCP", "indexed_mask-ROI_HCP.nii") def test_neuropycon_data(): """test if neuropycon_data is installed""" assert os.path.exists(data_path) assert os.path.exists(img_file) assert os.path.exists(gm_mask_file) assert os.path.exists(wm_mask_file) assert os.path.exists(csf_mask_file) assert os.path.exists(indexed_mask_file) def test_extract_ts(): """ test ExtractTS""" _make_tmp_dir()
import os import shutil import numpy as np from graphpype.utils_net import (return_net_list, read_Pajek_corres_nodes, read_Pajek_corres_nodes_and_sparse_matrix, export_Louvain_net_from_list) from graphpype.utils_tests import load_test_data data_path = load_test_data("data_con") conmat_file = os.path.join(data_path, "Z_cor_mat_resid_ts.npy") coords_file = os.path.join(data_path, "ROI_MNI_coords-Atlas.txt") Z_list_file = os.path.join(data_path, "data_graph", "Z_List.txt") Pajek_net_file = os.path.join(data_path, "data_graph", "Z_List.net") def test_data(): """test if test_data is accessible""" assert os.path.exists(data_path) assert os.path.exists(conmat_file) assert os.path.exists(coords_file) assert os.path.exists(Z_list_file) assert os.path.exists(Pajek_net_file) tmp_dir = "/tmp/test_graphpype" if os.path.exists(tmp_dir): shutil.rmtree(tmp_dir) os.makedirs(tmp_dir)
import nipype.pipeline.engine as pe from nipype.interfaces.utility import IdentityInterface import nipype.interfaces.io as nio import json # noqa import pprint # noqa ############################################################################### # Check if data are available from graphpype.utils_tests import load_test_data data_path = load_test_data("data_nii") data_path_mask = load_test_data("data_nii_HCP") ROI_mask_file = op.join(data_path_mask, "indexed_mask-ROI_HCP.nii") ROI_coords_file = op.join(data_path_mask, "ROI_coords-ROI_HCP.txt") ROI_MNI_coords_file = op.join(data_path_mask, "ROI_MNI_coords-ROI_HCP.txt") ROI_labels_file = op.join(data_path_mask, "ROI_labels-ROI_HCP.txt") ############################################################################### # Then, we create our workflow and specify the `base_dir` which tells # nipype the directory in which to store the outputs. # workflow directory within the `base_dir` conmat_analysis_name = 'nii_to_dyn_graph'
# Authors: David Meunier <*****@*****.**> # License: BSD (3-clause) # sphinx_gallery_thumbnail_number = 2 import os.path as op import nipype.pipeline.engine as pe import nipype.interfaces.io as nio from ephypype.nodes import create_iterator from ephypype.nodes import get_frequency_band ############################################################################### # Check if data are available from graphpype.utils_tests import load_test_data data_path = load_test_data("data_inv_ts") ############################################################################### # First, we create our workflow and specify the `base_dir` which tells # nipype the directory in which to store the outputs. # workflow directory within the `base_dir` graph_analysis_name = 'inv_ts_to_graph_analysis' main_workflow = pe.Workflow(name=graph_analysis_name) main_workflow.base_dir = data_path ############################################################################### # We now use a json file for describing the connectivity parameters, loaded # from a json as a dictionnary
def test_load_test_data(): """Test load_test_data""" data_path = load_test_data("data_nii") assert os.path.exists(data_path)
# Authors: David Meunier <*****@*****.**> # License: BSD (3-clause) # sphinx_gallery_thumbnail_number = 2 import os.path as op import nipype.pipeline.engine as pe from nipype.interfaces.utility import IdentityInterface import nipype.interfaces.io as nio ############################################################################### # Check if data are available from graphpype.utils_tests import load_test_data data_path = load_test_data("data_con_meg") ############################################################################### # This will be what we will loop on freq_band_names = ['alpha', 'beta'] ############################################################################### # Then, we create our workflow and specify the `base_dir` which tells # nipype the directory in which to store the outputs. # workflow directory within the `base_dir` graph_analysis_name = 'graph_analysis' main_workflow = pe.Workflow(name=graph_analysis_name) main_workflow.base_dir = data_path
import os # import numpy as np # import nibabel as nib # from graphpype.utils_img import (return_data_img_from_roi_mask) from graphpype.utils_tests import load_test_data data_path = load_test_data("data_nii_HCP") indexed_mask_file = os.path.join(data_path, "indexed_mask-ROI_HCP.nii") def test_data(): """test if test_data is accessible""" assert os.path.exists(data_path) # assert os.path.exists(indexed_mask_file) # def test_return_data_img_from_roi_mask(): # """test_return_data_img_from_roi_mask""" # data_img = nib.load(indexed_mask_file).get_data() # test_vect = np.random.rand(len(np.unique(data_img))-1) # data_img_vect = return_data_img_from_roi_mask(indexed_mask_file, # test_vect) # data_img_vect_vals = np.unique(data_img_vect.get_data())[1:] # assert all(data_img_vect_vals == np.unique(test_vect))
from graphpype.labeled_mask import (segment_mask_in_ROI) import os import shutil from graphpype.utils_tests import load_test_data data_path = load_test_data("data_nii_mask") mask_file = os.path.join(data_path, "rwc1sub-01_T1w.nii") def test_data(): """test if test_data is accessible""" assert os.path.exists(data_path) assert os.path.exists(mask_file) nb_ROIs = 10 tmp_dir = "/tmp/test_graphpype" if os.path.exists(tmp_dir): shutil.rmtree(tmp_dir) os.makedirs(tmp_dir) def test_segment_mask_in_ROI(): """test_segment_mask_in_ROI""" # with cube (default) indexed_mask_rois_file, _, _ = segment_mask_in_ROI(mask_file,
import os import string import numpy as np import nibabel as nib from graphpype.utils_cor import ( mean_select_mask_data, mean_select_indexed_mask_data, regress_parameters, return_conf_cor_mat, filter_data, normalize_data, return_corres_correl_mat, where_in_labels, return_corres_correl_mat_labels, spearmanr_by_hand) from graphpype.utils_tests import load_test_data data_path = load_test_data("data_nii_min") img_file = os.path.join(data_path, "wrsub-01_task-rest_bold.nii") mask_file = os.path.join(data_path, "rwc1sub-01_T1w.nii") data_path_HCP = load_test_data("data_nii_HCP") indexed_mask_file = os.path.join(data_path_HCP, "indexed_mask-ROI_HCP.nii") def test_data(): """test if test_data is accessible""" assert os.path.exists(data_path) assert os.path.exists(img_file) assert os.path.exists(mask_file) assert os.path.exists(data_path_HCP) assert os.path.exists(indexed_mask_file)