neurosynth/base/imageutils.py
def load_imgs(filenames, masker, nan_to_num=True):
    """ Load multiple images from file into an ndarray.

    Args:
      filenames: A single filename or list of filenames pointing to valid
        images.
      masker: A Masker instance.
      nan_to_num: Optional boolean indicating whether to convert NaNs to zero.

    Returns:
      An m x n 2D numpy array, where m = number of voxels in mask and
      n = number of images passed.
    """
    if isinstance(filenames, string_types):
        filenames = [filenames]
    data = np.zeros((masker.n_vox_in_mask, len(filenames)))
    for i, f in enumerate(filenames):
        data[:, i] = masker.mask(f, nan_to_num)
    return data
def load_imgs(filenames, masker, nan_to_num=True):
    """ Load multiple images from file into an ndarray.

    Args:
      filenames: A single filename or list of filenames pointing to valid
        images.
      masker: A Masker instance.
      nan_to_num: Optional boolean indicating whether to convert NaNs to zero.

    Returns:
      An m x n 2D numpy array, where m = number of voxels in mask and
      n = number of images passed.
    """
    if isinstance(filenames, string_types):
        filenames = [filenames]
    data = np.zeros((masker.n_vox_in_mask, len(filenames)))
    for i, f in enumerate(filenames):
        data[:, i] = masker.mask(f, nan_to_num)
    return data
Load multiple images from file into an ndarray.

    Args:
      filenames: A single filename or list of filenames pointing to valid
        images.
      masker: A Masker instance.
      nan_to_num: Optional boolean indicating whether to convert NaNs to zero.

    Returns:
      An m x n 2D numpy array, where m = number of voxels in mask and
      n = number of images passed.