neurosynth/base/mask.py
def get_image(self, image, output='vector'):
        """ A flexible method for transforming between different
        representations of image data.
        Args:
            image: The input image. Can be a string (filename of image),
                NiBabel image, N-dimensional array (must have same shape as
                self.volume), or vectorized image data (must have same length
                as current conjunction mask).
            output: The format of the returned image representation. Must be
                one of:
                    'vector': A 1D vectorized array
                    'array': An N-dimensional array, with
                        shape = self.volume.shape
                    'image': A NiBabel image
        Returns: An object containing image data; see output options above.
        """
        if isinstance(image, string_types):
            image = nb.load(image)

        if type(image).__module__.startswith('nibabel'):
            if output == 'image':
                return image
            image = image.get_data()

        if not type(image).__module__.startswith('numpy'):
            raise ValueError("Input image must be a string, a NiBabel image, "
                             "or a numpy array.")

        if image.shape[:3] == self.volume.shape:
            if output == 'image':
                return nb.nifti1.Nifti1Image(image, None, self.get_header())
            elif output == 'array':
                return image
            else:
                image = image.ravel()

        if output == 'vector':
            return image.ravel()

        image = np.reshape(image, self.volume.shape)

        if output == 'array':
            return image

        return nb.nifti1.Nifti1Image(image, None, self.get_header())
def get_image(self, image, output='vector'):
        """ A flexible method for transforming between different
        representations of image data.
        Args:
            image: The input image. Can be a string (filename of image),
                NiBabel image, N-dimensional array (must have same shape as
                self.volume), or vectorized image data (must have same length
                as current conjunction mask).
            output: The format of the returned image representation. Must be
                one of:
                    'vector': A 1D vectorized array
                    'array': An N-dimensional array, with
                        shape = self.volume.shape
                    'image': A NiBabel image
        Returns: An object containing image data; see output options above.
        """
        if isinstance(image, string_types):
            image = nb.load(image)

        if type(image).__module__.startswith('nibabel'):
            if output == 'image':
                return image
            image = image.get_data()

        if not type(image).__module__.startswith('numpy'):
            raise ValueError("Input image must be a string, a NiBabel image, "
                             "or a numpy array.")

        if image.shape[:3] == self.volume.shape:
            if output == 'image':
                return nb.nifti1.Nifti1Image(image, None, self.get_header())
            elif output == 'array':
                return image
            else:
                image = image.ravel()

        if output == 'vector':
            return image.ravel()

        image = np.reshape(image, self.volume.shape)

        if output == 'array':
            return image

        return nb.nifti1.Nifti1Image(image, None, self.get_header())
A flexible method for transforming between different
        representations of image data.
        Args:
            image: The input image. Can be a string (filename of image),
                NiBabel image, N-dimensional array (must have same shape as
                self.volume), or vectorized image data (must have same length
                as current conjunction mask).
            output: The format of the returned image representation. Must be
                one of:
                    'vector': A 1D vectorized array
                    'array': An N-dimensional array, with
                        shape = self.volume.shape
                    'image': A NiBabel image
        Returns: An object containing image data; see output options above.