9bf2004b29aa393400bd904bdf788390f5c0404a,niftynet/layer/binary_masking.py,BinaryMaskingLayer,layer_op,#BinaryMaskingLayer#Any#,62

Before Change

                    new_mask = np.zeros(image.shape[0:3], dtype=np.bool)
                    for mod in mod_to_mask:
                        new_mask = np.logical_or(new_mask, mask[..., mod, t])
                    mask[..., t] = np.tile(np.expand_dims(new_mask, axis=-1),
                                           [1, mask.shape[3]])

            if self.multimod_fusion == "and":
                for t in range(0, image.shape[4]):
                    new_mask = np.ones(image.shape[0:3], dtype=np.bool)
                    for mod in mod_to_mask:
                        new_mask = np.logical_and(new_mask, mask[..., mod, t])
                    mask[..., t] = np.tile(np.expand_dims(new_mask, axis=-1),
                                           [1, mask.shape[3]])
            return mask
        raise ValueError("unknown input format")

After Change

                    for mod in mod_to_mask:
                        new_mask = np.logical_or(new_mask, mask[..., t, mod])
                    for mod in mod_to_mask:
                        mask[..., t, mod] = new_mask

            if self.multimod_fusion == "and":
                for t in range(0, image.shape[3]):
                    new_mask = np.ones(image.shape[0:3], dtype=np.bool)
                    for mod in mod_to_mask:
                        new_mask = np.logical_and(new_mask, mask[..., t, mod])
                    for mod in mod_to_mask:
                        mask[..., t, mod] = new_mask
            return mask
        raise ValueError("unknown input format")

Instances