def matrix_to_timeseries( image, matrix, mask=None ):
    """
    converts a matrix to a ND image.

    ANTsR function: `matrix2timeseries`

    Arguments
    ---------

    image: reference ND image

    matrix: matrix to convert to image

    mask: mask image defining voxels of interest


    Returns
    -------
    ANTsImage

    Example
    -------
    >>> import ants
    >>> img = ants.make_image( (10,10,10,5 ) )
    >>> mask = ants.ndimage_to_list( img )[0] * 0
    >>> mask[ 4:8, 4:8, 4:8 ] = 1
    >>> mat = ants.timeseries_to_matrix( img, mask = mask )
    >>> img2 = ants.matrix_to_timeseries( img,  mat, mask)
    """

    if mask is None:
        mask = temp[0]*0 + 1
    temp = matrix_to_images( matrix, mask )
    newImage = utils.list_to_ndimage( image, temp)
    iio.copy_image_info( image, newImage)
    return(newImage)
def matrix_to_timeseries ( image , matrix , mask = None ) : if mask is None : mask = temp [ 0 ] * 0 + 1 temp = matrix_to_images ( matrix , mask ) newImage = utils . list_to_ndimage ( image , temp ) iio . copy_image_info ( image , newImage ) return ( newImage )
converts a matrix to a ND image.

    ANTsR function: `matrix2timeseries`

    Arguments
    ---------

    image: reference ND image

    matrix: matrix to convert to image

    mask: mask image defining voxels of interest


    Returns
    -------
    ANTsImage

    Example
    -------
    >>> import ants
    >>> img = ants.make_image( (10,10,10,5 ) )
    >>> mask = ants.ndimage_to_list( img )[0] * 0
    >>> mask[ 4:8, 4:8, 4:8 ] = 1
    >>> mat = ants.timeseries_to_matrix( img, mask = mask )
    >>> img2 = ants.matrix_to_timeseries( img,  mat, mask)