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, )