def __init__(
self,
mask_img=None,
sessions=None,
smoothing_fwhm=None,
standardize=False,
detrend=False,
low_pass=None,
high_pass=None,
t_r=None,
target_affine=None,
target_shape=None,
mask_strategy="background",
mask_args=None,
sample_mask=None,
memory_level=1,
memory=Memory(cachedir=None),
verbose=0,
hemisphere="L",
):
if hemisphere.lower() in ["l", "left"]:
self.hemi = "l"
elif hemisphere.lower() in ["r", "right"]:
self.hemi = "r"
else:
raise ValueError("Hemisphere must be left or right; " "got value %s" % self.hemi)
mask_img = mask_img or nib.load(fetch_grey_matter_mask())
target_affine = mask_img.affine
target_shape = mask_img.shape
super(HemisphereMasker, self).__init__(
mask_img=mask_img,
sessions=sessions,
smoothing_fwhm=smoothing_fwhm,
standardize=standardize,
detrend=detrend,
low_pass=low_pass,
high_pass=high_pass,
t_r=t_r,
target_affine=target_affine,
target_shape=target_shape,
mask_strategy=mask_strategy,
mask_args=mask_args,
sample_mask=sample_mask,
memory_level=memory_level,
memory=memory,
verbose=verbose,
)
def __init__(
self,
sessions=None,
smoothing_fwhm=None,
standardize=False,
detrend=False,
low_pass=None,
high_pass=None,
t_r=None,
target_affine=None,
target_shape=None,
mask_strategy="background",
mask_args=None,
sample_mask=None,
memory_level=1,
memory=Memory(cachedir=None),
verbose=0,
):
# Use grey matter mask computed for Neurovault analysis
# ('https://github.com/NeuroVault/neurovault_analysis/')
target_img = nib.load(fetch_grey_matter_mask())
grey_voxels = (target_img.get_data() > 0).astype(int)
mask_img = new_img_like(target_img, grey_voxels, copy_header=True)
super(GreyMatterNiftiMasker, self).__init__(
mask_img=mask_img,
target_affine=mask_img.affine,
target_shape=mask_img.shape,
sessions=sessions,
smoothing_fwhm=smoothing_fwhm,
standardize=standardize,
detrend=detrend,
low_pass=low_pass,
high_pass=high_pass,
t_r=t_r,
mask_strategy=mask_strategy,
mask_args=mask_args,
sample_mask=sample_mask,
memory_level=memory_level,
memory=memory,
verbose=verbose,
)
