ENH add parameter dataset in get_data_home

Author: TomDLT

tutorials/movies/00_download_vim5.py

@@ -30,9 +30,8 @@
 # --------
 
 # path of the data directory
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################

tutorials/movies/01_plot_explainable_variance.py

@@ -40,9 +40,8 @@
 ###############################################################################
 # Path of the data directory
 # --------------------------
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
@@ -59,6 +58,7 @@
 ###############################################################################
 # First, we load the fMRI responses on the test set, which contains brain
 # responses to ten (10) repeats of the same stimulus.
+import os
 file_name = os.path.join(directory, 'responses', f'{subject}_responses.hdf')
 Y_test = load_hdf5_array(file_name, key="Y_test")
 print("(n_repeats, n_samples_test, n_voxels) =", Y_test.shape)

tutorials/movies/02_plot_wordnet_model.py

@@ -32,9 +32,8 @@
 ###############################################################################
 # Path of the data directory
 # --------------------------
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
@@ -53,6 +52,7 @@
 # to estimate the generalization performance of the selected model. The
 # test set contains multiple repetitions of the same experiment to estimate
 # an upper bound of the model prediction accuracy (cf. previous example).
+import os
 import numpy as np
 from voxelwise_tutorials.io import load_hdf5_array
 

tutorials/movies/03_plot_hemodynamic_response.py

@@ -28,9 +28,8 @@
 ###############################################################################
 # Path of the data directory
 # --------------------------
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
@@ -43,6 +42,7 @@
 # -------------
 #
 # We first load the fMRI responses.
+import os
 import numpy as np
 from voxelwise_tutorials.io import load_hdf5_array
 

tutorials/movies/04_plot_motion_energy_model.py

@@ -29,9 +29,8 @@
 ###############################################################################
 # Path of the data directory
 # --------------------------
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
@@ -44,8 +43,8 @@
 # -------------
 #
 # We first load the fMRI responses.
+import os
 import numpy as np
-
 from voxelwise_tutorials.io import load_hdf5_array
 
 file_name = os.path.join(directory, "responses", f"{subject}_responses.hdf")

tutorials/movies/05_plot_banded_ridge_model.py

@@ -21,9 +21,8 @@
 ###############################################################################
 # Path of the data directory
 # --------------------------
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
@@ -37,8 +36,8 @@
 #
 # As in the previous examples, we first load the fMRI responses, which are our
 # regression targets.
+import os
 import numpy as np
-
 from voxelwise_tutorials.io import load_hdf5_array
 
 file_name = os.path.join(directory, "responses", f"{subject}_responses.hdf")

tutorials/movies/06_extract_motion_energy.py

@@ -28,17 +28,16 @@
 ###############################################################################
 
 # path of the data directory
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-5")
+directory = get_data_home(dataset="vim-5")
 print(directory)
 
 ###############################################################################
 # Load the stimuli images
 # -----------------------
 #
 # Here the data is not loaded in memory, we only take a peek at the data shape.
-
+import os
 import h5py
 
 first_file_name = os.path.join(directory, 'stimuli', 'train_00.hdf')

tutorials/movies_deprecated/00_download_vim2.py

@@ -20,9 +20,8 @@
 # --------
 
 # path of the data directory
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-2")
+directory = get_data_home(dataset="vim-2")
 print(directory)
 
 ###############################################################################

tutorials/movies_deprecated/01_extract_motion_energy.py

@@ -27,16 +27,14 @@
 # (We downloaded the files in the previous script.)
 
 # path of the data directory
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-2")
+directory = get_data_home(dataset="vim-2")
 print(directory)
 
 ###############################################################################
 # Here the data is not loaded in memory, we only take a peak at the data shape.
-
-import h5py
 import os
+import h5py
 
 with h5py.File(os.path.join(directory, 'Stimuli.mat'), 'r') as f:
     print(f.keys())  # Show all variables

tutorials/movies_deprecated/02_plot_ridge_model.py

@@ -32,20 +32,20 @@
 # -------------
 
 # path of the data directory
-import os
 from voxelwise_tutorials.io import get_data_home
-directory = os.path.join(get_data_home(), "vim-2")
+directory = get_data_home(dataset="vim-2")
 print(directory)
 
 # modify to use another subject
 subject = "subject1"
 
 ###############################################################################
 # Here the data is not loaded in memory, we only take a peek at the data shape.
+import os
 import h5py
-import os.path as op
 
-with h5py.File(op.join(directory, f'VoxelResponses_{subject}.mat'), 'r') as f:
+file_name = os.path.join(directory, f'VoxelResponses_{subject}.mat')
+with h5py.File(file_name, 'r') as f:
     print(f.keys())  # Show all variables
     for key in f.keys():
         print(f[key])
@@ -57,7 +57,7 @@
 
 from voxelwise_tutorials.io import load_hdf5_array
 
-file_name = op.join(directory, f'VoxelResponses_{subject}.mat')
+file_name = os.path.join(directory, f'VoxelResponses_{subject}.mat')
 Y_train = load_hdf5_array(file_name, key='rt')
 Y_test_repeats = load_hdf5_array(file_name, key='rva')
 
@@ -90,7 +90,7 @@
 # Here we load the motion-energy features, that are going to be used for the
 # linear regression model.
 
-file_name = op.join(directory, "features", "motion_energy.hdf")
+file_name = os.path.join(directory, "features", "motion_energy.hdf")
 X_train = load_hdf5_array(file_name, key='X_train')
 X_test = load_hdf5_array(file_name, key='X_test')