125282dfbe865c9cc47611443cf0ae23080d9233,examples/02_decoding/plot_haxby_grid_search.py,,,#,40

Before Change

print("Functional nifti image (4D) are located at: %s" % haxby_dataset.func[0])

// Load the behavioral data
y, session = np.loadtxt(haxby_dataset.session_target[0]).astype("int").T
conditions = np.recfromtxt(haxby_dataset.conditions_target[0])["f0"]

// Keep only data corresponding to shoes or bottles
condition_mask = np.logical_or(conditions == b"shoe", conditions == b"bottle")
y = y[condition_mask]

After Change

print("Functional nifti image (4D) are located at: %s" % haxby_dataset.func[0])

// Load the behavioral data
labels = np.recfromcsv(haxby_dataset.session_target[0], delimiter=" ")
conditions = labels["labels"]
categories = np.unique(conditions)
y = np.zeros_like(conditions)
for c, category in enumerate(categories):
    y[conditions == category] = c
session = labels["chunks"]

// Keep only data corresponding to shoes or bottles
condition_mask = np.logical_or(conditions == b"shoe", conditions == b"bottle")
y = y[condition_mask]

Instances