From 9593e8ccbc2407358d2fb4afeead14f27f0f6ae8 Mon Sep 17 00:00:00 2001 From: Alex Date: Thu, 17 Sep 2020 22:26:12 +0200 Subject: [PATCH 01/21] class for parsing derivatives subdirectory in BIDS format --- pyrsa/data/__init__.py | 1 + pyrsa/data/pooling.py | 82 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 83 insertions(+) create mode 100755 pyrsa/data/pooling.py diff --git a/pyrsa/data/__init__.py b/pyrsa/data/__init__.py index 425705be..ed797b4a 100644 --- a/pyrsa/data/__init__.py +++ b/pyrsa/data/__init__.py @@ -1,3 +1,4 @@ +from .pooling import BidsDerivatives from .dataset import Dataset from .dataset import load_dataset from .dataset import dataset_from_dict diff --git a/pyrsa/data/pooling.py b/pyrsa/data/pooling.py new file mode 100755 index 00000000..3d8f51a9 --- /dev/null +++ b/pyrsa/data/pooling.py @@ -0,0 +1,82 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Data preparation functions +""" + +import os +import glob +import numpy as np + +class BidsDerivatives: + def __init__(self, fmri_dir, subject_list = None, sessions = None, + run_dirs = None): + assert os.path.exists(fmri_dir), "Specified directory does not exist." + self.fmri_dir = fmri_dir + + # Level 1: Subjects + sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") + if isinstance(subject_list, list): + self.subject_list = subject_list + else: + self.subject_list = [os.path.basename(sub) for sub in sub_dirs] + self.subject_list.sort() + self.n_subs = len(self.subject_list) + + # Level 2: Sessions + session_dirs = [glob.glob(sub_dir + os.sep + "ses*") + for sub_dir in sub_dirs] + session_dirs_flat = [item for sublist in session_dirs + for item in sublist] + bases = [os.path.basename(sess_dir) for sess_dir in session_dirs_flat] + if isinstance(sessions, list): + self.sessions = sessions + else: + self.sessions = np.unique( + [''.join([i for i in base if not i.isdigit()]) for base in bases]) + + # Level 3: Runs + if isinstance(run_dirs, list): + self.run_dirs = run_dirs + else: + run_dirs = [glob.glob(ses_dir + os.sep + "run*") + for ses_dir in session_dirs_flat] + self.run_dirs = [item for sublist in run_dirs + for item in sublist] + self.run_dirs.sort() + + + def __repr__(self): + """ + defines string which is printed for the object + """ + return (f'pyrsa.data.{self.__class__.__name__}(\n\n' + f'fMRI directory = \n{self.fmri_dir}\n\n' + f'Number of subjects = {self.n_subs}\n\n' + f'Session types = {self.sessions}\n\n' + ) + + def subset_subject(self, sub): + assert isinstance(sub, int), "Subject number must be integer." + sub_name = "sub-"+str(sub).zfill(2) + assert sub_name in self.subject_list, \ + "Subject with this ID does not exist" + run_dirs_subset = [run for run in self.run_dirs if sub_name in run] + subset = BidsDerivatives(self.fmri_dir, + subject_list = [sub_name], + sessions = self.sessions, + run_dirs = run_dirs_subset) + return subset + + def subset_session_type(self, session_type): + assert session_type in self.sessions, \ + "Session type does not exist" + run_dirs_subset = [run for run in self.run_dirs if session_type in run] + subset = BidsDerivatives(self.fmri_dir, + subject_list = self.subject_list, + sessions = [session_type], + run_dirs = run_dirs_subset) + return subset + + + From e76ae33cca2ece821333595cff1b3da08dfb2477 Mon Sep 17 00:00:00 2001 From: Alex Date: Thu, 17 Sep 2020 22:56:49 +0200 Subject: [PATCH 02/21] added / refined subsetting methods; added function to flatten lists; better __repr__ method --- pyrsa/data/pooling.py | 64 +++++++++++++++++++++++++++++++------------ 1 file changed, 46 insertions(+), 18 deletions(-) diff --git a/pyrsa/data/pooling.py b/pyrsa/data/pooling.py index 3d8f51a9..b8726e1e 100755 --- a/pyrsa/data/pooling.py +++ b/pyrsa/data/pooling.py @@ -8,6 +8,11 @@ import glob import numpy as np +def flatten_list(lst): + assert isinstance(lst, list) + lst_flattened = [item for sublist in lst for item in sublist] + return lst_flattened + class BidsDerivatives: def __init__(self, fmri_dir, subject_list = None, sessions = None, run_dirs = None): @@ -15,35 +20,39 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, self.fmri_dir = fmri_dir # Level 1: Subjects - sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") if isinstance(subject_list, list): self.subject_list = subject_list + sub_dirs = flatten_list([glob.glob(self.fmri_dir + os.sep + sub) + for sub in subject_list]) + else: + sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") self.subject_list = [os.path.basename(sub) for sub in sub_dirs] self.subject_list.sort() self.n_subs = len(self.subject_list) # Level 2: Sessions - session_dirs = [glob.glob(sub_dir + os.sep + "ses*") - for sub_dir in sub_dirs] - session_dirs_flat = [item for sublist in session_dirs - for item in sublist] - bases = [os.path.basename(sess_dir) for sess_dir in session_dirs_flat] if isinstance(sessions, list): self.sessions = sessions else: - self.sessions = np.unique( - [''.join([i for i in base if not i.isdigit()]) for base in bases]) + session_dirs = flatten_list([glob.glob(sub_dir + os.sep + "ses*") + for sub_dir in sub_dirs]) + bases = [os.path.basename(sess_dir) for sess_dir + in session_dirs] + self.sessions = np.unique(bases) + + self.session_types = np.unique( + [''.join([i for i in base if not i.isdigit()]) + for base in self.sessions]) # Level 3: Runs if isinstance(run_dirs, list): self.run_dirs = run_dirs else: - run_dirs = [glob.glob(ses_dir + os.sep + "run*") - for ses_dir in session_dirs_flat] - self.run_dirs = [item for sublist in run_dirs - for item in sublist] + self.run_dirs = flatten_list([glob.glob(ses_dir + os.sep + "run*") + for ses_dir in session_dirs]) self.run_dirs.sort() + self.runs_total = len(self.run_dirs) def __repr__(self): @@ -52,19 +61,29 @@ def __repr__(self): """ return (f'pyrsa.data.{self.__class__.__name__}(\n\n' f'fMRI directory = \n{self.fmri_dir}\n\n' + f'Subject list = {self.subject_list}\n\n' f'Number of subjects = {self.n_subs}\n\n' - f'Session types = {self.sessions}\n\n' + f'Sessions = {self.sessions}\n\n' + f'Session types = {self.session_types}\n\n' + f'Total number of runs = {self.runs_total}\n' ) def subset_subject(self, sub): - assert isinstance(sub, int), "Subject number must be integer." - sub_name = "sub-"+str(sub).zfill(2) - assert sub_name in self.subject_list, \ - "Subject with this ID does not exist" + + + assert isinstance(sub, int) or sub in self.subject_list, \ + "Subject number must be integer or a string for an existing \ + subject ID" + if isinstance(sub, int): + sub_name = "sub-"+str(sub).zfill(2) + assert sub_name in self.subject_list, \ + "Subject with this ID does not exist" + else: + sub_name = sub + run_dirs_subset = [run for run in self.run_dirs if sub_name in run] subset = BidsDerivatives(self.fmri_dir, subject_list = [sub_name], - sessions = self.sessions, run_dirs = run_dirs_subset) return subset @@ -77,6 +96,15 @@ def subset_session_type(self, session_type): sessions = [session_type], run_dirs = run_dirs_subset) return subset + + def get_subjects(self): + return self.subject_list.copy() + + def get_sessions(self): + return self.sessions.copy() + + def get_runs(self): + return self.run_dirs.copy() From de9fd8e83c996490849b0b046b266174a577861f Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 00:11:53 +0200 Subject: [PATCH 03/21] added docstrings and function to load SPM beta coefficients optionally using dictionary to subset beta coefficients --- pyrsa/data/pooling.py | 107 ++++++++++++++++++++++++++++++++++++++---- 1 file changed, 97 insertions(+), 10 deletions(-) diff --git a/pyrsa/data/pooling.py b/pyrsa/data/pooling.py index b8726e1e..a17df031 100755 --- a/pyrsa/data/pooling.py +++ b/pyrsa/data/pooling.py @@ -7,15 +7,32 @@ import os import glob import numpy as np +from nibabel import nifti1 + -def flatten_list(lst): - assert isinstance(lst, list) - lst_flattened = [item for sublist in lst for item in sublist] - return lst_flattened class BidsDerivatives: + """ + BidsDerivatives class. + Parses a specified subdirectory in the derivatives folder + of a dataset in BIDS format. + + Args: + fmri_dir (str): path to derivatives subdirectory + subject_list (list): names of contained subject folders + sessions (list): names of unique sessions + run_dirs (list): paths to all run folders containing e.g. GLM results + + Returns: + BidsDerivatives object + """ + def __init__(self, fmri_dir, subject_list = None, sessions = None, run_dirs = None): + """ + Parses BIDS structured data in fmri_dir + or inherits said info after subsetting + """ assert os.path.exists(fmri_dir), "Specified directory does not exist." self.fmri_dir = fmri_dir @@ -40,7 +57,6 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, bases = [os.path.basename(sess_dir) for sess_dir in session_dirs] self.sessions = np.unique(bases) - self.session_types = np.unique( [''.join([i for i in base if not i.isdigit()]) for base in self.sessions]) @@ -57,7 +73,7 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, def __repr__(self): """ - defines string which is printed for the object + Defines string which is printed for the object """ return (f'pyrsa.data.{self.__class__.__name__}(\n\n' f'fMRI directory = \n{self.fmri_dir}\n\n' @@ -69,8 +85,16 @@ def __repr__(self): ) def subset_subject(self, sub): + """ + Creates a smaller BidsDerivatives object for specified subject + Args: + sub (int or str): subject id (e.g. 1 or 'sub-01') + + Returns: + Subsetted BidsDerivatives object + """ assert isinstance(sub, int) or sub in self.subject_list, \ "Subject number must be integer or a string for an existing \ subject ID" @@ -88,8 +112,19 @@ def subset_subject(self, sub): return subset def subset_session_type(self, session_type): - assert session_type in self.sessions, \ - "Session type does not exist" + """ + Creates a smaller BidsDerivatives object for specified session + + Args: + sub (int or str): subject id (e.g. 1 or 'sub-01') + + Returns: + Subsetted BidsDerivatives object + + """ + assert session_type in self.sessions \ + or session_type in self.session_types, \ + "Session (type) does not exist" run_dirs_subset = [run for run in self.run_dirs if session_type in run] subset = BidsDerivatives(self.fmri_dir, subject_list = self.subject_list, @@ -105,6 +140,58 @@ def get_sessions(self): def get_runs(self): return self.run_dirs.copy() - - + + +def flatten_list(lst): + """ + Flattens list of lists to single list + + Args: + lst (list) + + Returns: + lst_flattened (list): the flattened version of lst + """ + assert isinstance(lst, list) + lst_flattened = [item for sublist in lst for item in sublist] + return lst_flattened + + +def load_SPM_beta_images(run_dirs, stim_ids_dict): + """ + Collects 3d images of prespecified beta coefficients + (typical SPM GLM results) and corresponding metadata + (condition + run info) into respective lists + + Args: + run_dirs (list of str): + paths to directories containing beta NIfTi files + stim_ids_dict (dict): {condition : beta coefficient number} + e.g. {'face': 1, 'house': 2} + + Returns: + beta_array_superset (list of 3d numpy arrays): + all beta 3d arrays for the keys in stim_ids_dict found in each + run directory + dim4_descriptors (list of str): + corresponding descriptors + e.g. ['cond_face_run_05', 'cond_house_run_30'] + """ + beta_array_superset = [] + dim4_descriptors = [] + run_counter = 0 + for glm_dir in run_dirs: + run_counter += 1 + for condition in stim_ids_dict.keys(): + num = stim_ids_dict[condition] + beta_image_path = os.path.join(glm_dir, "beta_" + + str(num).zfill(4)) + beta_image = nifti1.load(beta_image_path) + beta_array_superset.append(beta_image.get_fdata()) + dim4_descriptors.append("cond_" + condition + "_run_" + + str(run_counter).zfill(2)) + return beta_array_superset, dim4_descriptors + + + From 468197052814feb0fea200fc18fdc7e502fd2274 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 00:19:54 +0200 Subject: [PATCH 04/21] added option to not provide a dictionary for load_SPM_beta_images() --- pyrsa/data/pooling.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/pyrsa/data/pooling.py b/pyrsa/data/pooling.py index a17df031..237bade9 100755 --- a/pyrsa/data/pooling.py +++ b/pyrsa/data/pooling.py @@ -157,7 +157,7 @@ def flatten_list(lst): return lst_flattened -def load_SPM_beta_images(run_dirs, stim_ids_dict): +def load_SPM_beta_images(run_dirs, stim_ids_dict = None): """ Collects 3d images of prespecified beta coefficients (typical SPM GLM results) and corresponding metadata @@ -177,6 +177,13 @@ def load_SPM_beta_images(run_dirs, stim_ids_dict): corresponding descriptors e.g. ['cond_face_run_05', 'cond_house_run_30'] """ + + if stim_ids_dict == None: + n_conds = len(glob.glob(run_dirs[0] + os.sep + "beta*")) + keys = ["beta_" + str(cond_num).zfill(4) for cond_num in range(1, n_conds+1)] + values = [cond_num for cond_num in range(1, n_conds+1)] + stim_ids_dict = dict(zip(keys, values)) + beta_array_superset = [] dim4_descriptors = [] run_counter = 0 From 2787d8e32636457e179e8651658687fff270d4af Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 09:50:49 +0200 Subject: [PATCH 05/21] np.stack for list of 3d images to 4d array --- pyrsa/data/pooling.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/pyrsa/data/pooling.py b/pyrsa/data/pooling.py index 237bade9..bf40dd6f 100755 --- a/pyrsa/data/pooling.py +++ b/pyrsa/data/pooling.py @@ -197,7 +197,9 @@ def load_SPM_beta_images(run_dirs, stim_ids_dict = None): beta_array_superset.append(beta_image.get_fdata()) dim4_descriptors.append("cond_" + condition + "_run_" + str(run_counter).zfill(2)) - return beta_array_superset, dim4_descriptors + + pooled_beta_array = np.stack(beta_array_superset, axis=3) + return pooled_beta_array, dim4_descriptors From ba435b9d653f42248a31f4b1bb9093ca75b367fe Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 11:41:15 +0200 Subject: [PATCH 06/21] renamed pooling.py to fmri.py --- pyrsa/data/{pooling.py => fmri.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename pyrsa/data/{pooling.py => fmri.py} (100%) diff --git a/pyrsa/data/pooling.py b/pyrsa/data/fmri.py similarity index 100% rename from pyrsa/data/pooling.py rename to pyrsa/data/fmri.py From f2585cb2e6d5dbac6e66850030d1cc24e572f1a6 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 16:57:06 +0200 Subject: [PATCH 07/21] inherited class for parsed data of only one subject; methods for loading betas / residuals from SPM output; methods for pooling and saving data as NIfTi and CSV files --- pyrsa/data/__init__.py | 3 +- pyrsa/data/fmri.py | 349 +++++++++++++++++++++++++++++++++-------- 2 files changed, 287 insertions(+), 65 deletions(-) diff --git a/pyrsa/data/__init__.py b/pyrsa/data/__init__.py index ed797b4a..2cde14ee 100644 --- a/pyrsa/data/__init__.py +++ b/pyrsa/data/__init__.py @@ -1,4 +1,3 @@ -from .pooling import BidsDerivatives from .dataset import Dataset from .dataset import load_dataset from .dataset import dataset_from_dict @@ -6,3 +5,5 @@ from .computations import average_dataset_by from .noise import cov_from_residuals from .noise import prec_from_residuals +from .fmri import BidsDerivatives +from .fmri import SubjectData diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index bf40dd6f..a315d877 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -1,12 +1,13 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ -Data preparation functions +Parsing and importing of fMRI data on BIDS format """ import os import glob import numpy as np +import pandas as pd from nibabel import nifti1 @@ -39,12 +40,14 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, # Level 1: Subjects if isinstance(subject_list, list): self.subject_list = subject_list - sub_dirs = flatten_list([glob.glob(self.fmri_dir + os.sep + sub) - for sub in subject_list]) + self.sub_dirs = flatten_list( + [glob.glob(self.fmri_dir + os.sep + sub) + for sub in subject_list]) else: - sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") - self.subject_list = [os.path.basename(sub) for sub in sub_dirs] + self.sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") + self.subject_list = [os.path.basename(sub) + for sub in self.sub_dirs] self.subject_list.sort() self.n_subs = len(self.subject_list) @@ -53,7 +56,7 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, self.sessions = sessions else: session_dirs = flatten_list([glob.glob(sub_dir + os.sep + "ses*") - for sub_dir in sub_dirs]) + for sub_dir in self.sub_dirs]) bases = [os.path.basename(sess_dir) for sess_dir in session_dirs] self.sessions = np.unique(bases) @@ -79,9 +82,8 @@ def __repr__(self): f'fMRI directory = \n{self.fmri_dir}\n\n' f'Subject list = {self.subject_list}\n\n' f'Number of subjects = {self.n_subs}\n\n' - f'Sessions = {self.sessions}\n\n' f'Session types = {self.session_types}\n\n' - f'Total number of runs = {self.runs_total}\n' + f'Total number of runs = {self.runs_total}\n\n\n\n' ) def subset_subject(self, sub): @@ -106,9 +108,9 @@ def subset_subject(self, sub): sub_name = sub run_dirs_subset = [run for run in self.run_dirs if sub_name in run] - subset = BidsDerivatives(self.fmri_dir, - subject_list = [sub_name], - run_dirs = run_dirs_subset) + subset = SubjectData(self.fmri_dir, + subject_list = [sub_name], + run_dirs = run_dirs_subset) return subset def subset_session_type(self, session_type): @@ -122,16 +124,56 @@ def subset_session_type(self, session_type): Subsetted BidsDerivatives object """ - assert session_type in self.sessions \ - or session_type in self.session_types, \ - "Session (type) does not exist" - run_dirs_subset = [run for run in self.run_dirs if session_type in run] - subset = BidsDerivatives(self.fmri_dir, - subject_list = self.subject_list, - sessions = [session_type], - run_dirs = run_dirs_subset) - return subset + raise NotImplementedError( + "subset_session_type method not implemented in used class, \ + you must first subset to one subject!") + def load_betas_SPM(self, stim_ids_dict = None): + """ + Collects 3d images of prespecified beta coefficients + (typical SPM GLM results) and corresponding metadata + (condition + run info) into respective lists + + Args: + run_dirs (list of str): + paths to directories containing beta NIfTi files + stim_ids_dict (dict): {condition : beta coefficient number} + e.g. {'face': 1, 'house': 2} + + Returns: + beta_array_superset (list of 3d numpy arrays): + all beta 3d arrays for the keys in stim_ids_dict found in each + run directory + dim4_descriptors (list of str): + corresponding descriptors + e.g. ['cond_face_run_05', 'cond_house_run_30'] + """ + raise NotImplementedError( + "load_betas_SPM method not implemented in used class, \ + you must first subset to one subject!") + + def load_residuals_SPM(self, res_range = None): + """ + Collects 3d images of a range of GLM residuals + (typical SPM GLM results) and corresponding metadata + (scan number + run info) into respective lists + + Args: + run_dirs (list of str): + paths to directories containing beta NIfTi files + res_range (range): range of to be saved residual images per run + + + Returns: + residual_array_superset (list of 3d numpy arrays): + all residual 3d arrays for scans in res_range + dim4_descriptors (list of str): + corresponding descriptors + e.g. ['res_0001_run_01', 'res_0002_run_01'] + """ + raise NotImplementedError( + "load_residuals_SPM method not implemented in used class, \ + you must first subset to one subject!") def get_subjects(self): return self.subject_list.copy() @@ -141,6 +183,229 @@ def get_sessions(self): def get_runs(self): return self.run_dirs.copy() + +class SubjectData(BidsDerivatives): + """ + SubjectData class is a standard version of BidsDerivative. + It contains data for only one subject + """ + + def __repr__(self): + """ + Defines string which is printed for the object + """ + return (f'pyrsa.data.{self.__class__.__name__}(\n\n' + f'Subject ID = {self.subject_list[0]}\n\n' + f'Subject directory = \n{self.sub_dirs[0]}\n\n' + f'Session types = {self.session_types}\n\n' + f'Sessions = {self.sessions}\n\n' + f'Total number of runs = {self.runs_total}\n\n\n\n' + ) + + def subset_session_type(self, session_type): + """ + Creates a smaller BidsDerivatives object for specified session + + Args: + sub (int or str): subject id (e.g. 1 or 'sub-01') + + Returns: + Subsetted BidsDerivatives object + + """ + assert session_type in self.sessions \ + or session_type in self.session_types, \ + "Session (type) does not exist" + run_dirs_subset = [run for run in self.run_dirs if session_type in run] + subset = SubjectData(self.fmri_dir, + subject_list = self.subject_list, + sessions = [session_type], + run_dirs = run_dirs_subset) + return subset + + def load_betas_SPM(self, stim_ids_dict = None): + """ + Collects 3d images of prespecified beta coefficients + (typical SPM GLM results) and corresponding metadata + (condition + run info) into respective lists + + Args: + run_dirs (list of str): + paths to directories containing beta NIfTi files + stim_ids_dict (dict): {condition : beta coefficient number} + e.g. {'face': 1, 'house': 2} + + Returns: + pooled_beta_array (4d numpy array): + all beta 3d arrays for the keys in stim_ids_dict found in each + run directory stacked along the fourth dimension + dim4_descriptors (list of str): + corresponding descriptors + e.g. ['cond_face_run_05', 'cond_house_run_30'] + """ + assert len(self.session_types) == 1, \ + "You first need to subset to one type of sessions" + + if stim_ids_dict == None: + n_conds = len(glob.glob(self.run_dirs[0] + os.sep + "beta*")) + keys = [str(cond_num).zfill(4) for cond_num in range(1, n_conds+1)] + values = [cond_num for cond_num in range(1, n_conds+1)] + stim_ids_dict = dict(zip(keys, values)) + + beta_array_superset = [] + dim4_descriptors = [] + run_counter = 0 + for glm_dir in self.run_dirs: + run_counter += 1 + for condition in stim_ids_dict.keys(): + num = stim_ids_dict[condition] + beta_image_path = os.path.join(glm_dir, "beta_" + + str(num).zfill(4)) + beta_image = nifti1.load(beta_image_path) + beta_array_superset.append(beta_image.get_fdata()) + dim4_descriptors.append("cond_" + condition + "_run_" + + str(run_counter).zfill(2)) + # Get affine matrix + self.subject_affine = beta_image.affine.copy() + pooled_beta_array = np.stack(beta_array_superset, axis = 3) + return pooled_beta_array, dim4_descriptors + + def load_residuals_SPM(self, res_range = None): + """ + Collects 3d images of a range of GLM residuals + (typical SPM GLM results) and corresponding metadata + (scan number + run info) into respective lists + + Args: + run_dirs (list of str): + paths to directories containing beta NIfTi files + res_range (range): range of to be saved residual images per run + + + Returns: + residual_array_superset (list of 3d numpy arrays): + all residual 3d arrays for scans in res_range + dim4_descriptors (list of str): + corresponding descriptors + e.g. ['res_0001_run_01', 'res_0002_run_01'] + """ + assert len(self.session_types) == 1, \ + "You first need to subset to one type of sessions" + + residual_array_superset = [] + dim4_descriptors = [] + self.n_res = len(glob.glob(os.path.join(self.run_dirs[0], "Res_*"))) + if isinstance(res_range, range): + assert self.n_res >= max(res_range), \ + "res_range outside of existing residuals" + else: + res_range = range(1, self.n_res+1) + + run_counter = 0 + for glm_dir in self.run_dirs: + run_counter += 1 + for res in res_range: + res_image_path = os.path.join(glm_dir, "Res_" + + str(res).zfill(4)) + res_image = nifti1.load(res_image_path) + residual_array_superset.append(res_image.get_fdata()) + dim4_descriptors.append("res_" + str(res).zfill(4)+ "_run_" + + str(run_counter)) + # Get affine matrix + self.subject_affine = res_image.affine.copy() + pooled_residual_array = np.stack(residual_array_superset, axis = 3) + return pooled_residual_array, dim4_descriptors + + def save2nifti(self, pooled_data_array, output_dir = None, + data_type = "signal"): + """ + Converts 4d array to subject-specific 4d NIfTi image + of beta coeffients or residuals and saves it to your OS + + Args: + pooled_data_array (4d numpy array): + all 3d arrays stacked along the fourth dimension + output_dir (str): + path to which you want to save your data + data_type (str): + part of the naming scheme for the saved data + + """ + assert len(self.session_types) == 1, \ + "You first need to subset to one type of sessions" + assert isinstance(data_type, str), "specified data type must be \ + a string object" + assert isinstance(pooled_data_array, np.ndarray) \ + and len(pooled_data_array.shape) == 4, "Wrong type of data provided" + + if output_dir == None: + self.output_dir = self.sub_dirs[0] + else: + assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ + "specified output dir object must be a string \ + to an existing path" + self.output_dir = output_dir + + print("Saving", data_type, "to 4d-NIfTi file in", + self.output_dir, "...") + pooled_data = nifti1.Nifti1Image(pooled_data_array, + self.subject_affine) + self.nifti_filename = os.path.join( + self.output_dir, self.subject_list[0] + "_" + + self.session_types[0] + "_" + data_type + ".nii.gz") + nifti1.save(pooled_data, self.nifti_filename) + print("Saved as", self.nifti_filename) + return + + def save2csv(self, descriptors, output_dir = None, + data_type = "signal"): + """ + Saves subject-specific 4d NIfTi image descriptors to a csv file + + Args: + descriptors (list of str): + descriptors of fourth a NIfTi file's 4th dimension + output_dir (str): + path to which you want to save your data + data_type (str): + part of the naming scheme for the saved data + """ + assert len(self.session_types) == 1, \ + "You first need to subset to one type of sessions" + assert isinstance(data_type, str), "specified data type must be \ + a string object" + assert isinstance(descriptors, list) \ + and isinstance(descriptors[0], str), "Wrong type of data provided" + + if output_dir == None: + self.output_dir = self.sub_dirs[0] + else: + assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ + "specified output dir object must be a string \ + to an existing path" + self.output_dir = output_dir + + + self.csv_filename = os.path.join( + self.output_dir, self.subject_list[0] + "_" + + self.session_types[0] + "_" + data_type + ".csv") + + df = pd.DataFrame({'descriptor': descriptors}) + df.to_csv(self.csv_filename, header=False) + print("Saved", data_type, "descriptors csv to", self.csv_filename) + return + + def save2combo(self, pooled_data_array, descriptors, output_dir = None, + data_type = "signal"): + """ + Combined saving of fmri data and descriptors + """ + self.save2nifti(pooled_data_array, output_dir = output_dir, + data_type = data_type) + self.save2csv(descriptors, output_dir = output_dir, + data_type = data_type) + return + def flatten_list(lst): """ @@ -157,50 +422,6 @@ def flatten_list(lst): return lst_flattened -def load_SPM_beta_images(run_dirs, stim_ids_dict = None): - """ - Collects 3d images of prespecified beta coefficients - (typical SPM GLM results) and corresponding metadata - (condition + run info) into respective lists - - Args: - run_dirs (list of str): - paths to directories containing beta NIfTi files - stim_ids_dict (dict): {condition : beta coefficient number} - e.g. {'face': 1, 'house': 2} - - Returns: - beta_array_superset (list of 3d numpy arrays): - all beta 3d arrays for the keys in stim_ids_dict found in each - run directory - dim4_descriptors (list of str): - corresponding descriptors - e.g. ['cond_face_run_05', 'cond_house_run_30'] - """ - - if stim_ids_dict == None: - n_conds = len(glob.glob(run_dirs[0] + os.sep + "beta*")) - keys = ["beta_" + str(cond_num).zfill(4) for cond_num in range(1, n_conds+1)] - values = [cond_num for cond_num in range(1, n_conds+1)] - stim_ids_dict = dict(zip(keys, values)) - - beta_array_superset = [] - dim4_descriptors = [] - run_counter = 0 - for glm_dir in run_dirs: - run_counter += 1 - for condition in stim_ids_dict.keys(): - num = stim_ids_dict[condition] - beta_image_path = os.path.join(glm_dir, "beta_" + - str(num).zfill(4)) - beta_image = nifti1.load(beta_image_path) - beta_array_superset.append(beta_image.get_fdata()) - dim4_descriptors.append("cond_" + condition + "_run_" + - str(run_counter).zfill(2)) - - pooled_beta_array = np.stack(beta_array_superset, axis=3) - return pooled_beta_array, dim4_descriptors - From f3f49ac9707a642195e9ee731858e55bcacbd29a Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 17:07:34 +0200 Subject: [PATCH 08/21] started coding unit tests --- pyrsa/__init__.py | 2 +- tests/test_fmri.py | 10 ++++++++++ 2 files changed, 11 insertions(+), 1 deletion(-) create mode 100755 tests/test_fmri.py diff --git a/pyrsa/__init__.py b/pyrsa/__init__.py index 74d044c5..8ca2eeb4 100644 --- a/pyrsa/__init__.py +++ b/pyrsa/__init__.py @@ -2,8 +2,8 @@ # -*- coding: utf-8 -*- """ Top level package: Only imports and organisation """ - from . import data +from . import fmri from . import inference from . import model from . import rdm diff --git a/tests/test_fmri.py b/tests/test_fmri.py new file mode 100755 index 00000000..0ebf4f4f --- /dev/null +++ b/tests/test_fmri.py @@ -0,0 +1,10 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Tests for BidsDerivatives class and subclasses + +""" + +import unittest +import pyrsa.fmri as fmri +import numpy as np From d0f8f63acb6865d949dd88ad83418c96de1d0f54 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 18:11:59 +0200 Subject: [PATCH 09/21] fixed __init__ bugs, first parsing unit tests --- pyrsa/__init__.py | 1 - pyrsa/data/__init__.py | 2 +- pyrsa/data/fmri.py | 22 ++++++++------ tests/test_fmri.py | 66 +++++++++++++++++++++++++++++++++++++++++- 4 files changed, 79 insertions(+), 12 deletions(-) diff --git a/pyrsa/__init__.py b/pyrsa/__init__.py index 8ca2eeb4..7e2d3d90 100644 --- a/pyrsa/__init__.py +++ b/pyrsa/__init__.py @@ -3,7 +3,6 @@ """ Top level package: Only imports and organisation """ from . import data -from . import fmri from . import inference from . import model from . import rdm diff --git a/pyrsa/data/__init__.py b/pyrsa/data/__init__.py index 2cde14ee..b419bc67 100644 --- a/pyrsa/data/__init__.py +++ b/pyrsa/data/__init__.py @@ -6,4 +6,4 @@ from .noise import cov_from_residuals from .noise import prec_from_residuals from .fmri import BidsDerivatives -from .fmri import SubjectData +from .fmri import BidsDerivativesSubject diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index a315d877..13036ef6 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -108,9 +108,9 @@ def subset_subject(self, sub): sub_name = sub run_dirs_subset = [run for run in self.run_dirs if sub_name in run] - subset = SubjectData(self.fmri_dir, - subject_list = [sub_name], - run_dirs = run_dirs_subset) + subset = BidsDerivativesSubject(self.fmri_dir, + subject_list = [sub_name], + run_dirs = run_dirs_subset) return subset def subset_session_type(self, session_type): @@ -180,11 +180,14 @@ def get_subjects(self): def get_sessions(self): return self.sessions.copy() + def get_session_types(self): + return self.session_types.copy() + def get_runs(self): return self.run_dirs.copy() -class SubjectData(BidsDerivatives): +class BidsDerivativesSubject(BidsDerivatives): """ SubjectData class is a standard version of BidsDerivative. It contains data for only one subject @@ -216,11 +219,12 @@ def subset_session_type(self, session_type): assert session_type in self.sessions \ or session_type in self.session_types, \ "Session (type) does not exist" - run_dirs_subset = [run for run in self.run_dirs if session_type in run] - subset = SubjectData(self.fmri_dir, - subject_list = self.subject_list, - sessions = [session_type], - run_dirs = run_dirs_subset) + run_dirs_subset = [run for run in self.get_runs() if session_type in run] + ses_subset = [ses for ses in self.get_sessions() if session_type in ses] + subset = BidsDerivativesSubject(self.fmri_dir, + subject_list = self.subject_list, + sessions = ses_subset, + run_dirs = run_dirs_subset) return subset def load_betas_SPM(self, stim_ids_dict = None): diff --git a/tests/test_fmri.py b/tests/test_fmri.py index 0ebf4f4f..b5a819b7 100755 --- a/tests/test_fmri.py +++ b/tests/test_fmri.py @@ -6,5 +6,69 @@ """ import unittest -import pyrsa.fmri as fmri +import os +import pyrsa.data.fmri as fmri import numpy as np + +def get_fmri_data(): + fmri_dir = os.path.join( + os.getcwd(), "data", "BIDS_example", "derivatives", "SPM_example") + fmri_data = fmri.BidsDerivatives(fmri_dir) + return fmri_data + +def get_subject_data(): + fmri_data = get_fmri_data() + subjects = fmri_data.get_subjects() + subject_data = fmri_data.subset_subject(subjects[0]) + return subject_data + +def get_subject_session_data(): + subject_data = get_subject_data() + session_types = subject_data.get_session_types() + subject_data_s = subject_data.subset_session_type(session_types[0]) + return subject_data_s + +class TestParsing(unittest.TestCase): + + def test_full_parsing(self): + fmri_data = get_fmri_data() + np.testing.assert_array_equal( + fmri_data.get_subjects(), + ['sub-01', 'sub-02']) + np.testing.assert_array_equal( + fmri_data.get_session_types(), + ['ses-perceptionTest', 'ses-perceptionTraining']) + np.testing.assert_array_equal( + fmri_data.runs_total, 14) + + def test_sub_parsing(self): + subject_data = get_subject_data() + np.testing.assert_array_equal( + subject_data.get_subjects(), + ['sub-01']) + np.testing.assert_array_equal( + subject_data.get_sessions(), + ['ses-perceptionTest01', 'ses-perceptionTest02', + 'ses-perceptionTraining01']) + np.testing.assert_array_equal( + subject_data.runs_total, 6) + np.testing.assert_array_equal( + [os.path.isdir(run_dir) + for run_dir in subject_data.get_runs()], + [True, True, True, True, True, True]) + + def test_session_parsing(self): + subject_data = get_subject_session_data() + np.testing.assert_array_equal( + subject_data.get_sessions(), + ['ses-perceptionTest01', 'ses-perceptionTest02']) + np.testing.assert_array_equal( + subject_data.runs_total, 4) + np.testing.assert_array_equal( + [os.path.isdir(run_dir) + for run_dir in subject_data.get_runs()], + [True, True, True, True]) + + +if __name__ == '__main__': + unittest.main() \ No newline at end of file From 31166908ce472abfaf894fc11ac4b1d23a1ac023 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 18:56:52 +0200 Subject: [PATCH 10/21] example dataset --- .../ses-perceptionTest01/run-01/Res_0001.nii | Bin 0 -> 1346752 bytes .../ses-perceptionTest01/run-01/beta_0001.nii | Bin 0 -> 673552 bytes .../ses-perceptionTest01/run-01/beta_0002.nii | Bin 0 -> 673552 bytes 3 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/ses-perceptionTest01/run-01/Res_0001.nii create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/ses-perceptionTest01/run-01/beta_0001.nii create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/ses-perceptionTest01/run-01/beta_0002.nii diff --git a/tests/data/BIDS_example/derivatives/SPM_example/sub-01/ses-perceptionTest01/run-01/Res_0001.nii b/tests/data/BIDS_example/derivatives/SPM_example/sub-01/ses-perceptionTest01/run-01/Res_0001.nii new file mode 100644 index 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zal~+0K1V`Y)Rs{A65Hb8ouRCQGxXg)5AV|zFvsN{_tfz%rs$Z|%h;Nf%;N2irX;zR3!Ef2p} zdFD6qylJFhcWMhJnVpBgXNPF_mNsJZOLHMAY-{=h%O%j53#mJr)aAu|Mch_gNUG_hFKCWDncs1M%FK^4k#BB)}YxCPY9O~hSw{A8O zZ-4Z|t`;YSCo{J}@0Po%RA1#UZSl_@zdr1D?3_LnO`CwP`nD4XYX0`j<(s<(;+nx1 zgiRKsQC-iI4lhY0!IsKDMVmxsJTdcfFbo34-K`%V9X~sv|W^C=xtN5cb z{@rzw9j|<6u5`jMeqoOnTsw=<@7Dj_oMAguaNTu693zCWA&+QtStY|cZ4jj zEU(M}Gr$Zm1Iz$3zzi@0%m6dM3@`)C05iZ0Fayj0Gr$Zm1Iz$3zzi@0%m6dM3@`)C z05iZ0{P!C$Om^c7e{Emy#<>3f+OyI)fCWpEafZZw^iE%H=Xv%^AMw_7f3dXnzTdUxzto=G^SbcE*y~$e zeOn%GL@~H1_~I{)BgK&IAMoS#G``{Hgx{^7vW-)Ini#dl-iL?zCKxvPAil|(#@}k3 z1h4O&`C)8#U3|ba>^K?J(dc*U_}jeIhu3;n#=^V^Ykqyd=isl?NE}kp>ASMK8x`Tn z$?`BoJ%}p4m%sxTP$0t}xSR&UMIV^C#F~84cm2+tO=dfB?boj*EuU2pej=_yXB2*an%tRJU6Y zKL7c5{mVabTy~8A{?CxCj#(Wu1Iz$3zzi@0%m6dM3@`)C05iZ0Fayj0Gr$Zm1Iz$3 zzzi@0%m6dM3@`)C05iZ0Fayj0Gr$Zm1Iz$3zzqDX2J{m>f6B40e Date: Fri, 18 Sep 2020 18:57:59 +0200 Subject: [PATCH 11/21] minor bug fixes and full unit tests for all things pooling --- pyrsa/data/fmri.py | 2 +- tests/test_fmri.py | 99 ++++++++++++++++++++++++++++++++++++---------- 2 files changed, 80 insertions(+), 21 deletions(-) diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index 13036ef6..9b601732 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -314,7 +314,7 @@ def load_residuals_SPM(self, res_range = None): res_image = nifti1.load(res_image_path) residual_array_superset.append(res_image.get_fdata()) dim4_descriptors.append("res_" + str(res).zfill(4)+ "_run_" + - str(run_counter)) + str(run_counter).zfill(2)) # Get affine matrix self.subject_affine = res_image.affine.copy() pooled_residual_array = np.stack(residual_array_superset, axis = 3) diff --git a/tests/test_fmri.py b/tests/test_fmri.py index b5a819b7..5b9e9776 100755 --- a/tests/test_fmri.py +++ b/tests/test_fmri.py @@ -33,42 +33,101 @@ class TestParsing(unittest.TestCase): def test_full_parsing(self): fmri_data = get_fmri_data() np.testing.assert_array_equal( - fmri_data.get_subjects(), - ['sub-01', 'sub-02']) + fmri_data.get_subjects(), + ['sub-01', 'sub-02']) np.testing.assert_array_equal( - fmri_data.get_session_types(), - ['ses-perceptionTest', 'ses-perceptionTraining']) + fmri_data.get_session_types(), + ['ses-perceptionTest', 'ses-perceptionTraining']) np.testing.assert_array_equal( - fmri_data.runs_total, 14) + fmri_data.runs_total, 13) def test_sub_parsing(self): subject_data = get_subject_data() np.testing.assert_array_equal( - subject_data.get_subjects(), - ['sub-01']) + subject_data.get_subjects(), + ['sub-01']) np.testing.assert_array_equal( - subject_data.get_sessions(), - ['ses-perceptionTest01', 'ses-perceptionTest02', - 'ses-perceptionTraining01']) + subject_data.get_sessions(), + ['ses-perceptionTest01', 'ses-perceptionTraining01', + 'ses-perceptionTraining02']) np.testing.assert_array_equal( - subject_data.runs_total, 6) + subject_data.runs_total, 5) np.testing.assert_array_equal( - [os.path.isdir(run_dir) - for run_dir in subject_data.get_runs()], - [True, True, True, True, True, True]) + [os.path.isdir(run_dir) + for run_dir in subject_data.get_runs()], + [True, True, True, True, True]) def test_session_parsing(self): subject_data = get_subject_session_data() np.testing.assert_array_equal( - subject_data.get_sessions(), - ['ses-perceptionTest01', 'ses-perceptionTest02']) + subject_data.get_sessions(), + ['ses-perceptionTest01']) np.testing.assert_array_equal( - subject_data.runs_total, 4) + subject_data.runs_total, 1) np.testing.assert_array_equal( - [os.path.isdir(run_dir) - for run_dir in subject_data.get_runs()], - [True, True, True, True]) + [os.path.isdir(run_dir) + for run_dir in subject_data.get_runs()], + [True]) + +class TestPoolingSPM(unittest.TestCase): + + def test_beta_pooling(self): + subject_data = get_subject_session_data() + beta_array, beta_descriptors = subject_data.load_betas_SPM() + np.testing.assert_array_equal( + beta_array.shape, (55, 60, 51, 2)) + np.testing.assert_array_equal( + beta_array.shape[3], len(beta_descriptors)) + beta_descriptors.sort() + np.testing.assert_array_equal( + np.unique(beta_descriptors), + beta_descriptors) + + def test_beta_pooling_w_dict(self): + stim_ids_dict = {"Face": 1, "House": 2} + subject_data = get_subject_session_data() + beta_array, beta_descriptors = subject_data.load_betas_SPM( + stim_ids_dict = stim_ids_dict) + np.testing.assert_array_equal( + beta_array.shape, (55, 60, 51, 2)) + np.testing.assert_array_equal( + beta_array.shape[3], len(beta_descriptors)) + beta_descriptors.sort() + np.testing.assert_array_equal( + np.unique(beta_descriptors), + beta_descriptors) + + def test_res_pooling(self): + subject_data = get_subject_session_data() + res_array, res_descriptors = subject_data.load_residuals_SPM() + np.testing.assert_array_equal( + res_array.shape, (55, 60, 51, 1)) + np.testing.assert_array_equal( + res_array.shape[3], len(res_descriptors)) + res_descriptors.sort() + np.testing.assert_array_equal( + np.unique(res_descriptors), + res_descriptors) +class TestSaving(unittest.TestCase): + + def test_saving_combo_signal(self): + stim_ids_dict = {"Face": 1, "House": 2} + subject_data = get_subject_session_data() + beta_array, beta_descriptors = subject_data.load_betas_SPM( + stim_ids_dict = stim_ids_dict) + subject_data.save2combo( + beta_array, beta_descriptors, data_type = "signal") + assert os.path.isfile(subject_data.nifti_filename) + assert os.path.isfile(subject_data.csv_filename) + + def test_saving_combo_noise(self): + subject_data = get_subject_session_data() + res_array, res_descriptors = subject_data.load_residuals_SPM() + subject_data.save2combo( + res_array, res_descriptors, data_type = "noise") + assert os.path.isfile(subject_data.nifti_filename) + assert os.path.isfile(subject_data.csv_filename) if __name__ == '__main__': unittest.main() \ No newline at end of file From 003c342795bdc53c11c70f91c50acd04961ea3c1 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 19:10:13 +0200 Subject: [PATCH 12/21] CodeFactor fixes --- pyrsa/data/fmri.py | 13 +++---------- 1 file changed, 3 insertions(+), 10 deletions(-) diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index 9b601732..b7fee6d5 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -250,7 +250,7 @@ def load_betas_SPM(self, stim_ids_dict = None): assert len(self.session_types) == 1, \ "You first need to subset to one type of sessions" - if stim_ids_dict == None: + if stim_ids_dict is None: n_conds = len(glob.glob(self.run_dirs[0] + os.sep + "beta*")) keys = [str(cond_num).zfill(4) for cond_num in range(1, n_conds+1)] values = [cond_num for cond_num in range(1, n_conds+1)] @@ -342,7 +342,7 @@ def save2nifti(self, pooled_data_array, output_dir = None, assert isinstance(pooled_data_array, np.ndarray) \ and len(pooled_data_array.shape) == 4, "Wrong type of data provided" - if output_dir == None: + if output_dir is None: self.output_dir = self.sub_dirs[0] else: assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ @@ -359,7 +359,6 @@ def save2nifti(self, pooled_data_array, output_dir = None, self.session_types[0] + "_" + data_type + ".nii.gz") nifti1.save(pooled_data, self.nifti_filename) print("Saved as", self.nifti_filename) - return def save2csv(self, descriptors, output_dir = None, data_type = "signal"): @@ -381,7 +380,7 @@ def save2csv(self, descriptors, output_dir = None, assert isinstance(descriptors, list) \ and isinstance(descriptors[0], str), "Wrong type of data provided" - if output_dir == None: + if output_dir is None: self.output_dir = self.sub_dirs[0] else: assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ @@ -408,7 +407,6 @@ def save2combo(self, pooled_data_array, descriptors, output_dir = None, data_type = data_type) self.save2csv(descriptors, output_dir = output_dir, data_type = data_type) - return def flatten_list(lst): @@ -424,8 +422,3 @@ def flatten_list(lst): assert isinstance(lst, list) lst_flattened = [item for sublist in lst for item in sublist] return lst_flattened - - - - - From 56b495c39a57d18abd799038f882ace91704b610 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 19:11:43 +0200 Subject: [PATCH 13/21] CodeFactor fixes --- pyrsa/data/fmri.py | 1 - 1 file changed, 1 deletion(-) diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index b7fee6d5..678aead8 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -396,7 +396,6 @@ def save2csv(self, descriptors, output_dir = None, df = pd.DataFrame({'descriptor': descriptors}) df.to_csv(self.csv_filename, header=False) print("Saved", data_type, "descriptors csv to", self.csv_filename) - return def save2combo(self, pooled_data_array, descriptors, output_dir = None, data_type = "signal"): From 38932dc01809f64466ea289057d64a3b1a561f50 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 18 Sep 2020 20:05:26 +0200 Subject: [PATCH 14/21] starterd coding class to read in 4d nifti files --- pyrsa/data/fmri.py | 59 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 59 insertions(+) diff --git a/pyrsa/data/fmri.py b/pyrsa/data/fmri.py index 678aead8..efd823c9 100755 --- a/pyrsa/data/fmri.py +++ b/pyrsa/data/fmri.py @@ -407,6 +407,65 @@ def save2combo(self, pooled_data_array, descriptors, output_dir = None, self.save2csv(descriptors, output_dir = output_dir, data_type = data_type) +class Nifti2Dataset: + def __init__(self, bids_dir, derivative, subject_list = None): + """ + Parses BIDS structured data in fmri_dir + """ + self.bids_dir = bids_dir + assert os.path.exists(self.bids_dir), \ + "Specified dataset directory does not exist." + self.fmri_dir = os.path.join( + self.bids_dir, "derivatives", derivative) + assert os.path.exists(self.fmri_dir), \ + "Specified derivatives directory does not exist." + + if isinstance(subject_list, list): + self.subject_list = subject_list + self.sub_dirs = flatten_list( + [glob.glob(self.fmri_dir + os.sep + sub) + for sub in subject_list]) + + else: + self.sub_dirs = glob.glob(self.fmri_dir + os.sep + "sub*") + self.subject_list = [os.path.basename(sub) + for sub in self.sub_dirs] + self.subject_list.sort() + self.n_subs = len(self.subject_list) + self.niftis = flatten_list( + [glob.glob(sub_dir + os.sep + "*.nii.gz") + for sub_dir in self.sub_dirs]) + self.n_niftis = len(self.niftis) + self.csvs = flatten_list( + [glob.glob(sub_dir + os.sep + "*.csv") + for sub_dir in self.sub_dirs]) + + def __repr__(self): + """ + Defines string which is printed for the object + """ + return (f'pyrsa.data.{self.__class__.__name__}(\n\n' + f'fMRI directory = \n{self.fmri_dir}\n\n' + f'Number of subjects = {self.n_subs}\n\n' + f'Subject list = {self.subject_list}\n\n' + f'Number of NIfTi files = {self.n_niftis}\n\n\n' + ) + + def set_output_dirs(self): + self.ds_output_dirs = [os.path.join( + self.bids_dir, "derivatives", "PyRSA", "datasets", sub) + for sub in self.subject_list] + for output_dir in self.ds_output_dirs: + if not os.path.isdir(output_dir): + os.makedirs(output_dir) + self.res_output_dirs = [os.path.join( + self.bids_dir, "derivatives", "PyRSA", "noise", sub) + for sub in self.subject_list] + for output_dir in self.res_output_dirs: + if not os.path.isdir(output_dir): + os.makedirs(output_dir) + + def flatten_list(lst): """ From db58eb8fbd118b9ea4b7b64a32c252cd1e773f4d Mon Sep 17 00:00:00 2001 From: Alex Date: Sat, 19 Sep 2020 11:45:22 +0200 Subject: [PATCH 15/21] added nibabel and pandas to requirements.txt --- requirements.txt | 2 ++ 1 file changed, 2 insertions(+) diff --git a/requirements.txt b/requirements.txt index 9a977129..f6223ad2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,3 +7,5 @@ tqdm h5py matplotlib joblib +nibabel +pandas From 626eb00ab996777d2f8ac98a00f47e895066e9a0 Mon Sep 17 00:00:00 2001 From: Heiko Schuett Date: Wed, 23 Jun 2021 11:34:50 -0400 Subject: [PATCH 16/21] updated fmri-tests to folder structure --- tests/test_fmri.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/test_fmri.py b/tests/test_fmri.py index 5b9e9776..ef03af4b 100755 --- a/tests/test_fmri.py +++ b/tests/test_fmri.py @@ -7,12 +7,12 @@ import unittest import os -import pyrsa.data.fmri as fmri +import rsatoolbox.data.fmri as fmri import numpy as np def get_fmri_data(): fmri_dir = os.path.join( - os.getcwd(), "data", "BIDS_example", "derivatives", "SPM_example") + os.path.dirname(__file__), "data", "BIDS_example", "derivatives", "SPM_example") fmri_data = fmri.BidsDerivatives(fmri_dir) return fmri_data @@ -130,4 +130,4 @@ def test_saving_combo_noise(self): assert os.path.isfile(subject_data.csv_filename) if __name__ == '__main__': - unittest.main() \ No newline at end of file + unittest.main() From 95a01462f2931fc084117c9a73944c7307679336 Mon Sep 17 00:00:00 2001 From: Alex Date: Sun, 27 Jun 2021 15:05:12 +0200 Subject: [PATCH 17/21] fix example data for test_fmri.py --- .../sub-01_ses-perceptionTest_noise.csv | 1 + .../sub-01_ses-perceptionTest_noise.nii.gz | Bin 0 -> 415013 bytes .../sub-01_ses-perceptionTest_signal.csv | 2 ++ .../sub-01_ses-perceptionTest_signal.nii.gz | Bin 0 -> 556204 bytes .../run-01/Res_0001.nii | Bin 0 -> 1165152 bytes .../run-01/beta_0001.nii | Bin 0 -> 582752 bytes .../run-01/beta_0002.nii | Bin 0 -> 582752 bytes tests/test_fmri.py | 16 ++++++++-------- 8 files changed, 11 insertions(+), 8 deletions(-) create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/sub-01_ses-perceptionTest_noise.csv create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/sub-01_ses-perceptionTest_noise.nii.gz create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/sub-01_ses-perceptionTest_signal.csv create mode 100644 tests/data/BIDS_example/derivatives/SPM_example/sub-01/sub-01_ses-perceptionTest_signal.nii.gz create mode 100755 tests/data/BIDS_example/derivatives/SPM_example/sub-02/ses-perceptionTraining01/run-01/Res_0001.nii create mode 100755 tests/data/BIDS_example/derivatives/SPM_example/sub-02/ses-perceptionTraining01/run-01/beta_0001.nii 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zf&b42nvDgS2O7)1nRj$=fG%@l-0g3U^KxAYripWXIBwkJJ*A|xoC+UyK=95uC_fWL zbRDI*IZ;2(oUyf`4p8u5AuO)0>B@s=YCJfkokY3Xwxno`7$Z^;*A;7L%)Giio;{4@ zJE)UN`yljr8Ha~w!G{CYuu(#}E6&f)^YVUUwa7PfLl2h76U#FXaQ@-kFXH6oIR2_^ zH@COp$s3bF`eD)!W9{>Jt^}R~{GjNIIq++ey Date: Fri, 17 Dec 2021 21:14:46 -0500 Subject: [PATCH 18/21] stylefix fmri --- rsatoolbox/data/fmri.py | 198 ++++++++++++++++++++-------------------- 1 file changed, 98 insertions(+), 100 deletions(-) diff --git a/rsatoolbox/data/fmri.py b/rsatoolbox/data/fmri.py index efd823c9..696047fd 100755 --- a/rsatoolbox/data/fmri.py +++ b/rsatoolbox/data/fmri.py @@ -11,7 +11,6 @@ from nibabel import nifti1 - class BidsDerivatives: """ BidsDerivatives class. @@ -20,23 +19,23 @@ class BidsDerivatives: Args: fmri_dir (str): path to derivatives subdirectory - subject_list (list): names of contained subject folders + subject_list (list): names of contained subject folders sessions (list): names of unique sessions run_dirs (list): paths to all run folders containing e.g. GLM results Returns: BidsDerivatives object """ - - def __init__(self, fmri_dir, subject_list = None, sessions = None, - run_dirs = None): + + def __init__(self, fmri_dir, subject_list=None, sessions=None, + run_dirs=None): """ Parses BIDS structured data in fmri_dir or inherits said info after subsetting """ assert os.path.exists(fmri_dir), "Specified directory does not exist." self.fmri_dir = fmri_dir - + # Level 1: Subjects if isinstance(subject_list, list): self.subject_list = subject_list @@ -50,7 +49,7 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, for sub in self.sub_dirs] self.subject_list.sort() self.n_subs = len(self.subject_list) - + # Level 2: Sessions if isinstance(sessions, list): self.sessions = sessions @@ -63,7 +62,7 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, self.session_types = np.unique( [''.join([i for i in base if not i.isdigit()]) for base in self.sessions]) - + # Level 3: Runs if isinstance(run_dirs, list): self.run_dirs = run_dirs @@ -72,8 +71,7 @@ def __init__(self, fmri_dir, subject_list = None, sessions = None, for ses_dir in session_dirs]) self.run_dirs.sort() self.runs_total = len(self.run_dirs) - - + def __repr__(self): """ Defines string which is printed for the object @@ -85,17 +83,17 @@ def __repr__(self): f'Session types = {self.session_types}\n\n' f'Total number of runs = {self.runs_total}\n\n\n\n' ) - + def subset_subject(self, sub): """ Creates a smaller BidsDerivatives object for specified subject - + Args: sub (int or str): subject id (e.g. 1 or 'sub-01') Returns: Subsetted BidsDerivatives object - + """ assert isinstance(sub, int) or sub in self.subject_list, \ "Subject number must be integer or a string for an existing \ @@ -106,40 +104,40 @@ def subset_subject(self, sub): "Subject with this ID does not exist" else: sub_name = sub - + run_dirs_subset = [run for run in self.run_dirs if sub_name in run] subset = BidsDerivativesSubject(self.fmri_dir, - subject_list = [sub_name], - run_dirs = run_dirs_subset) + subject_list=[sub_name], + run_dirs=run_dirs_subset) return subset - + def subset_session_type(self, session_type): """ Creates a smaller BidsDerivatives object for specified session - + Args: sub (int or str): subject id (e.g. 1 or 'sub-01') Returns: Subsetted BidsDerivatives object - + """ raise NotImplementedError( "subset_session_type method not implemented in used class, \ you must first subset to one subject!") - - def load_betas_SPM(self, stim_ids_dict = None): + + def load_betas_SPM(self, stim_ids_dict=None): """ Collects 3d images of prespecified beta coefficients (typical SPM GLM results) and corresponding metadata (condition + run info) into respective lists - + Args: run_dirs (list of str): paths to directories containing beta NIfTi files stim_ids_dict (dict): {condition : beta coefficient number} e.g. {'face': 1, 'house': 2} - + Returns: beta_array_superset (list of 3d numpy arrays): all beta 3d arrays for the keys in stim_ids_dict found in each @@ -151,19 +149,18 @@ def load_betas_SPM(self, stim_ids_dict = None): raise NotImplementedError( "load_betas_SPM method not implemented in used class, \ you must first subset to one subject!") - - def load_residuals_SPM(self, res_range = None): + + def load_residuals_SPM(self, res_range=None): """ - Collects 3d images of a range of GLM residuals + Collects 3d images of a range of GLM residuals (typical SPM GLM results) and corresponding metadata (scan number + run info) into respective lists - + Args: run_dirs (list of str): paths to directories containing beta NIfTi files res_range (range): range of to be saved residual images per run - - + Returns: residual_array_superset (list of 3d numpy arrays): all residual 3d arrays for scans in res_range @@ -174,25 +171,26 @@ def load_residuals_SPM(self, res_range = None): raise NotImplementedError( "load_residuals_SPM method not implemented in used class, \ you must first subset to one subject!") + def get_subjects(self): return self.subject_list.copy() - + def get_sessions(self): return self.sessions.copy() - + def get_session_types(self): return self.session_types.copy() - + def get_runs(self): - return self.run_dirs.copy() + return self.run_dirs.copy() + - class BidsDerivativesSubject(BidsDerivatives): """ SubjectData class is a standard version of BidsDerivative. It contains data for only one subject """ - + def __repr__(self): """ Defines string which is printed for the object @@ -204,41 +202,43 @@ def __repr__(self): f'Sessions = {self.sessions}\n\n' f'Total number of runs = {self.runs_total}\n\n\n\n' ) - + def subset_session_type(self, session_type): """ Creates a smaller BidsDerivatives object for specified session - + Args: sub (int or str): subject id (e.g. 1 or 'sub-01') Returns: Subsetted BidsDerivatives object - + """ assert session_type in self.sessions \ or session_type in self.session_types, \ "Session (type) does not exist" - run_dirs_subset = [run for run in self.get_runs() if session_type in run] - ses_subset = [ses for ses in self.get_sessions() if session_type in ses] + run_dirs_subset = [run for run in self.get_runs() + if session_type in run] + ses_subset = [ses for ses in self.get_sessions() + if session_type in ses] subset = BidsDerivativesSubject(self.fmri_dir, - subject_list = self.subject_list, - sessions = ses_subset, - run_dirs = run_dirs_subset) + subject_list=self.subject_list, + sessions=ses_subset, + run_dirs=run_dirs_subset) return subset - - def load_betas_SPM(self, stim_ids_dict = None): + + def load_betas_SPM(self, stim_ids_dict=None): """ Collects 3d images of prespecified beta coefficients (typical SPM GLM results) and corresponding metadata (condition + run info) into respective lists - + Args: run_dirs (list of str): paths to directories containing beta NIfTi files stim_ids_dict (dict): {condition : beta coefficient number} e.g. {'face': 1, 'house': 2} - + Returns: pooled_beta_array (4d numpy array): all beta 3d arrays for the keys in stim_ids_dict found in each @@ -249,13 +249,13 @@ def load_betas_SPM(self, stim_ids_dict = None): """ assert len(self.session_types) == 1, \ "You first need to subset to one type of sessions" - + if stim_ids_dict is None: n_conds = len(glob.glob(self.run_dirs[0] + os.sep + "beta*")) keys = [str(cond_num).zfill(4) for cond_num in range(1, n_conds+1)] values = [cond_num for cond_num in range(1, n_conds+1)] stim_ids_dict = dict(zip(keys, values)) - + beta_array_superset = [] dim4_descriptors = [] run_counter = 0 @@ -271,21 +271,20 @@ def load_betas_SPM(self, stim_ids_dict = None): str(run_counter).zfill(2)) # Get affine matrix self.subject_affine = beta_image.affine.copy() - pooled_beta_array = np.stack(beta_array_superset, axis = 3) + pooled_beta_array = np.stack(beta_array_superset, axis=3) return pooled_beta_array, dim4_descriptors - - def load_residuals_SPM(self, res_range = None): + + def load_residuals_SPM(self, res_range=None): """ - Collects 3d images of a range of GLM residuals + Collects 3d images of a range of GLM residuals (typical SPM GLM results) and corresponding metadata (scan number + run info) into respective lists - + Args: run_dirs (list of str): paths to directories containing beta NIfTi files res_range (range): range of to be saved residual images per run - - + Returns: residual_array_superset (list of 3d numpy arrays): all residual 3d arrays for scans in res_range @@ -295,7 +294,7 @@ def load_residuals_SPM(self, res_range = None): """ assert len(self.session_types) == 1, \ "You first need to subset to one type of sessions" - + residual_array_superset = [] dim4_descriptors = [] self.n_res = len(glob.glob(os.path.join(self.run_dirs[0], "Res_*"))) @@ -304,28 +303,28 @@ def load_residuals_SPM(self, res_range = None): "res_range outside of existing residuals" else: res_range = range(1, self.n_res+1) - + run_counter = 0 for glm_dir in self.run_dirs: run_counter += 1 for res in res_range: res_image_path = os.path.join(glm_dir, "Res_" + - str(res).zfill(4)) + str(res).zfill(4)) res_image = nifti1.load(res_image_path) residual_array_superset.append(res_image.get_fdata()) - dim4_descriptors.append("res_" + str(res).zfill(4)+ "_run_" + - str(run_counter).zfill(2)) + dim4_descriptors.append("res_" + str(res).zfill(4) + "_run_" + + str(run_counter).zfill(2)) # Get affine matrix self.subject_affine = res_image.affine.copy() - pooled_residual_array = np.stack(residual_array_superset, axis = 3) + pooled_residual_array = np.stack(residual_array_superset, axis=3) return pooled_residual_array, dim4_descriptors - - def save2nifti(self, pooled_data_array, output_dir = None, - data_type = "signal"): + + def save2nifti(self, pooled_data_array, output_dir=None, + data_type="signal"): """ Converts 4d array to subject-specific 4d NIfTi image of beta coeffients or residuals and saves it to your OS - + Args: pooled_data_array (4d numpy array): all 3d arrays stacked along the fourth dimension @@ -333,7 +332,7 @@ def save2nifti(self, pooled_data_array, output_dir = None, path to which you want to save your data data_type (str): part of the naming scheme for the saved data - + """ assert len(self.session_types) == 1, \ "You first need to subset to one type of sessions" @@ -341,74 +340,74 @@ def save2nifti(self, pooled_data_array, output_dir = None, a string object" assert isinstance(pooled_data_array, np.ndarray) \ and len(pooled_data_array.shape) == 4, "Wrong type of data provided" - + if output_dir is None: - self.output_dir = self.sub_dirs[0] + self.output_dir = self.sub_dirs[0] else: - assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ + assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ "specified output dir object must be a string \ to an existing path" - self.output_dir = output_dir - + self.output_dir = output_dir + print("Saving", data_type, "to 4d-NIfTi file in", self.output_dir, "...") pooled_data = nifti1.Nifti1Image(pooled_data_array, - self.subject_affine) + self.subject_affine) self.nifti_filename = os.path.join( self.output_dir, self.subject_list[0] + "_" + self.session_types[0] + "_" + data_type + ".nii.gz") nifti1.save(pooled_data, self.nifti_filename) print("Saved as", self.nifti_filename) - - def save2csv(self, descriptors, output_dir = None, - data_type = "signal"): + + def save2csv(self, descriptors, output_dir=None, + data_type="signal"): """ Saves subject-specific 4d NIfTi image descriptors to a csv file - + Args: descriptors (list of str): - descriptors of fourth a NIfTi file's 4th dimension + descriptors of fourth a NIfTi file's 4th dimension output_dir (str): path to which you want to save your data data_type (str): - part of the naming scheme for the saved data + part of the naming scheme for the saved data """ assert len(self.session_types) == 1, \ "You first need to subset to one type of sessions" assert isinstance(data_type, str), "specified data type must be \ a string object" assert isinstance(descriptors, list) \ - and isinstance(descriptors[0], str), "Wrong type of data provided" - + and isinstance(descriptors[0], str), "Wrong type of data provided" + if output_dir is None: - self.output_dir = self.sub_dirs[0] + self.output_dir = self.sub_dirs[0] else: - assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ - "specified output dir object must be a string \ - to an existing path" - self.output_dir = output_dir - + assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ + "specified output dir object must be a string \ + to an existing path" + self.output_dir = output_dir self.csv_filename = os.path.join( self.output_dir, self.subject_list[0] + "_" + self.session_types[0] + "_" + data_type + ".csv") - + df = pd.DataFrame({'descriptor': descriptors}) df.to_csv(self.csv_filename, header=False) print("Saved", data_type, "descriptors csv to", self.csv_filename) - - def save2combo(self, pooled_data_array, descriptors, output_dir = None, - data_type = "signal"): + + def save2combo(self, pooled_data_array, descriptors, output_dir=None, + data_type="signal"): """ Combined saving of fmri data and descriptors """ - self.save2nifti(pooled_data_array, output_dir = output_dir, - data_type = data_type) - self.save2csv(descriptors, output_dir = output_dir, - data_type = data_type) + self.save2nifti(pooled_data_array, output_dir=output_dir, + data_type=data_type) + self.save2csv(descriptors, output_dir=output_dir, + data_type=data_type) + class Nifti2Dataset: - def __init__(self, bids_dir, derivative, subject_list = None): + def __init__(self, bids_dir, derivative, subject_list=None): """ Parses BIDS structured data in fmri_dir """ @@ -419,7 +418,7 @@ def __init__(self, bids_dir, derivative, subject_list = None): self.bids_dir, "derivatives", derivative) assert os.path.exists(self.fmri_dir), \ "Specified derivatives directory does not exist." - + if isinstance(subject_list, list): self.subject_list = subject_list self.sub_dirs = flatten_list( @@ -439,7 +438,7 @@ def __init__(self, bids_dir, derivative, subject_list = None): self.csvs = flatten_list( [glob.glob(sub_dir + os.sep + "*.csv") for sub_dir in self.sub_dirs]) - + def __repr__(self): """ Defines string which is printed for the object @@ -450,7 +449,7 @@ def __repr__(self): f'Subject list = {self.subject_list}\n\n' f'Number of NIfTi files = {self.n_niftis}\n\n\n' ) - + def set_output_dirs(self): self.ds_output_dirs = [os.path.join( self.bids_dir, "derivatives", "PyRSA", "datasets", sub) @@ -465,7 +464,6 @@ def set_output_dirs(self): if not os.path.isdir(output_dir): os.makedirs(output_dir) - def flatten_list(lst): """ From 6207a97b0b52365582e148b23e075ed4e98c4afa Mon Sep 17 00:00:00 2001 From: Heiko Schuett Date: Fri, 17 Dec 2021 21:27:39 -0500 Subject: [PATCH 19/21] moved fmri to io --- rsatoolbox/data/__init__.py | 4 +--- rsatoolbox/{data => io}/fmri.py | 0 tests/test_fmri.py | 2 +- 3 files changed, 2 insertions(+), 4 deletions(-) rename rsatoolbox/{data => io}/fmri.py (100%) diff --git a/rsatoolbox/data/__init__.py b/rsatoolbox/data/__init__.py index 80e23328..58fbe448 100644 --- a/rsatoolbox/data/__init__.py +++ b/rsatoolbox/data/__init__.py @@ -7,9 +7,7 @@ from .computations import average_dataset_by from .noise import cov_from_residuals from .noise import prec_from_residuals -from .fmri import BidsDerivatives -from .fmri import BidsDerivativesSubject from .noise import cov_from_measurements from .noise import prec_from_measurements from .noise import cov_from_unbalanced -from .noise import prec_from_unbalanced \ No newline at end of file +from .noise import prec_from_unbalanced diff --git a/rsatoolbox/data/fmri.py b/rsatoolbox/io/fmri.py similarity index 100% rename from rsatoolbox/data/fmri.py rename to rsatoolbox/io/fmri.py diff --git a/tests/test_fmri.py b/tests/test_fmri.py index 9662d6b8..7b4740a6 100755 --- a/tests/test_fmri.py +++ b/tests/test_fmri.py @@ -7,7 +7,7 @@ import unittest import os -import rsatoolbox.data.fmri as fmri +import rsatoolbox.io.fmri as fmri import numpy as np def get_fmri_data(): From 79696296884a23c4e7b9698763afa22ee72870cf Mon Sep 17 00:00:00 2001 From: Heiko Schuett Date: Fri, 17 Dec 2021 21:46:35 -0500 Subject: [PATCH 20/21] added init to nifti_filenames --- rsatoolbox/io/fmri.py | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/rsatoolbox/io/fmri.py b/rsatoolbox/io/fmri.py index 696047fd..329994d9 100755 --- a/rsatoolbox/io/fmri.py +++ b/rsatoolbox/io/fmri.py @@ -191,6 +191,11 @@ class BidsDerivativesSubject(BidsDerivatives): It contains data for only one subject """ + def __init__(self, *args, **kwargs): + self.nifti_filename = None + self.csv_filename = None + super().__init__(*args, **kwargs) + def __repr__(self): """ Defines string which is printed for the object @@ -342,19 +347,19 @@ def save2nifti(self, pooled_data_array, output_dir=None, and len(pooled_data_array.shape) == 4, "Wrong type of data provided" if output_dir is None: - self.output_dir = self.sub_dirs[0] + output_dir = self.sub_dirs[0] else: assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ "specified output dir object must be a string \ to an existing path" - self.output_dir = output_dir + output_dir = output_dir print("Saving", data_type, "to 4d-NIfTi file in", - self.output_dir, "...") + output_dir, "...") pooled_data = nifti1.Nifti1Image(pooled_data_array, self.subject_affine) self.nifti_filename = os.path.join( - self.output_dir, self.subject_list[0] + "_" + + output_dir, self.subject_list[0] + "_" + self.session_types[0] + "_" + data_type + ".nii.gz") nifti1.save(pooled_data, self.nifti_filename) print("Saved as", self.nifti_filename) @@ -380,15 +385,15 @@ def save2csv(self, descriptors, output_dir=None, and isinstance(descriptors[0], str), "Wrong type of data provided" if output_dir is None: - self.output_dir = self.sub_dirs[0] + output_dir = self.sub_dirs[0] else: assert isinstance(output_dir, str) and os.path.isdir(output_dir), \ "specified output dir object must be a string \ to an existing path" - self.output_dir = output_dir + output_dir = output_dir self.csv_filename = os.path.join( - self.output_dir, self.subject_list[0] + "_" + + output_dir, self.subject_list[0] + "_" + self.session_types[0] + "_" + data_type + ".csv") df = pd.DataFrame({'descriptor': descriptors}) From ea525435fbd05c59e24eba8feffa0f563dfd5288 Mon Sep 17 00:00:00 2001 From: Heiko Schuett Date: Fri, 17 Dec 2021 21:48:04 -0500 Subject: [PATCH 21/21] style fmri_test --- tests/test_fmri.py | 37 ++++++++++++++++++++++--------------- 1 file changed, 22 insertions(+), 15 deletions(-) diff --git a/tests/test_fmri.py b/tests/test_fmri.py index 7b4740a6..8499d1c9 100755 --- a/tests/test_fmri.py +++ b/tests/test_fmri.py @@ -10,6 +10,7 @@ import rsatoolbox.io.fmri as fmri import numpy as np + def get_fmri_data(): fmri_dir = os.path.join( os.path.dirname(__file__), "data", "BIDS_example", "derivatives", @@ -17,20 +18,23 @@ def get_fmri_data(): fmri_data = fmri.BidsDerivatives(fmri_dir) return fmri_data + def get_subject_data(): fmri_data = get_fmri_data() subjects = fmri_data.get_subjects() subject_data = fmri_data.subset_subject(subjects[0]) # subset data for first subject return subject_data + def get_subject_session_data(): subject_data = get_subject_data() session_types = subject_data.get_session_types() subject_data_s = subject_data.subset_session_type(session_types[0]) # further subset data for first session type return subject_data_s + class TestParsing(unittest.TestCase): - + def test_full_parsing(self): fmri_data = get_fmri_data() np.testing.assert_array_equal( @@ -41,7 +45,7 @@ def test_full_parsing(self): ['ses-perceptionTest', 'ses-perceptionTraining']) np.testing.assert_array_equal( fmri_data.runs_total, 2) - + def test_sub_parsing(self): subject_data = get_subject_data() np.testing.assert_array_equal( @@ -56,7 +60,7 @@ def test_sub_parsing(self): [os.path.isdir(run_dir) for run_dir in subject_data.get_runs()], [True]) - + def test_session_parsing(self): subject_data = get_subject_session_data() np.testing.assert_array_equal( @@ -67,10 +71,11 @@ def test_session_parsing(self): np.testing.assert_array_equal( [os.path.isdir(run_dir) for run_dir in subject_data.get_runs()], - [True]) + [True]) + class TestPoolingSPM(unittest.TestCase): - + def test_beta_pooling(self): subject_data = get_subject_session_data() beta_array, beta_descriptors = subject_data.load_betas_SPM() @@ -82,12 +87,12 @@ def test_beta_pooling(self): np.testing.assert_array_equal( np.unique(beta_descriptors), beta_descriptors) - + def test_beta_pooling_w_dict(self): stim_ids_dict = {"Face": 1, "House": 2} subject_data = get_subject_session_data() beta_array, beta_descriptors = subject_data.load_betas_SPM( - stim_ids_dict = stim_ids_dict) + stim_ids_dict=stim_ids_dict) np.testing.assert_array_equal( beta_array.shape, (55, 60, 51, 2)) np.testing.assert_array_equal( @@ -96,7 +101,7 @@ def test_beta_pooling_w_dict(self): np.testing.assert_array_equal( np.unique(beta_descriptors), beta_descriptors) - + def test_res_pooling(self): subject_data = get_subject_session_data() res_array, res_descriptors = subject_data.load_residuals_SPM() @@ -108,26 +113,28 @@ def test_res_pooling(self): np.testing.assert_array_equal( np.unique(res_descriptors), res_descriptors) - + + class TestSaving(unittest.TestCase): - + def test_saving_combo_signal(self): stim_ids_dict = {"Face": 1, "House": 2} subject_data = get_subject_session_data() beta_array, beta_descriptors = subject_data.load_betas_SPM( - stim_ids_dict = stim_ids_dict) + stim_ids_dict=stim_ids_dict) subject_data.save2combo( - beta_array, beta_descriptors, data_type = "signal") + beta_array, beta_descriptors, data_type="signal") assert os.path.isfile(subject_data.nifti_filename) assert os.path.isfile(subject_data.csv_filename) - + def test_saving_combo_noise(self): subject_data = get_subject_session_data() res_array, res_descriptors = subject_data.load_residuals_SPM() subject_data.save2combo( - res_array, res_descriptors, data_type = "noise") + res_array, res_descriptors, data_type="noise") assert os.path.isfile(subject_data.nifti_filename) assert os.path.isfile(subject_data.csv_filename) - + + if __name__ == '__main__': unittest.main()