cbb3b9847457068969371c9b2da36a74e14e8bc5,examples/funcalign/srm_image_prediction_example.py,,,#,65

Before Change

image_data = scipy.io.loadmat("data/image_data.mat")
// Convert data to a list of arrays matching SRM input.
// Each element is a matrix of voxels by TRs.
image_data = list(image_data["image_data_lh"])

assert image_data[0].shape[0] == movie_data[0].shape[0], "Number of voxels in movie data and image data do not match!"

// Z-score the image data

After Change

// Load the input data that contains the image stimuli and its labels for training a classifier
image_file = scipy.io.loadmat("data/image_data.mat")
image_data_left = image_file["image_data_lh"]
image_data_right = image_file["image_data_rh"]

// Convert data to a list of arrays matching SRM input.
// Each element is a matrix of voxels by TRs.
// Also, concatenate data from both hemispheres in the brain.
image_data = []
for s in range(subjects):
    image_data.append(np.concatenate([image_data_left[:, :, s], image_data_right[:, :, s]], axis=0))

assert image_data[0].shape[0] == movie_data[0].shape[0], "Number of voxels in movie data and image data do not match!"

// Z-score the image data
for subject in range(subjects):

Instances