neurosynth/base/imageutils.py
def create_grid(image, scale=4, apply_mask=True, save_file=None):
    """ Creates an image containing labeled cells in a 3D grid.
    Args:
        image: String or nibabel image. The image used to define the grid
            dimensions. Also used to define the mask to apply to the grid.
            Only voxels with non-zero values in the mask will be retained; all
            other voxels will be zeroed out in the returned image.
        scale: The scaling factor which controls the grid size. Value reflects
            diameter of cube in voxels.
        apply_mask: Boolean indicating whether or not to zero out voxels not in
            image.
        save_file: Optional string giving the path to save image to. Image
            written out is a standard Nifti image. If save_file is None, no
            image is written.
    Returns:
        A nibabel image with the same dimensions as the input image. All voxels
        in each cell in the 3D grid are assigned the same non-zero label.
    """
    if isinstance(image, string_types):
        image = nb.load(image)

    # create a list of cluster centers
    centers = []
    x_length, y_length, z_length = image.shape
    for x in range(0, x_length, scale):
        for y in range(0, y_length, scale):
            for z in range(0, z_length, scale):
                centers.append((x, y, z))

    # create a box around each center with the diameter equal to the scaling
    # factor
    grid = np.zeros(image.shape)
    for (i, (x, y, z)) in enumerate(centers):
        for mov_x in range((-scale + 1) // 2, (scale + 1) // 2):
            for mov_y in range((-scale + 1) // 2, (scale + 1) // 2):
                for mov_z in range((-scale + 1) // 2, (scale + 1) // 2):
                    try:  # Ignore voxels outside bounds of image
                        grid[x + mov_x, y + mov_y, z + mov_z] = i + 1
                    except:
                        pass

    if apply_mask:
        mask = image
        if isinstance(mask, string_types):
            mask = nb.load(mask)
        if type(mask).__module__ != np.__name__:
            mask = mask.get_data()
        grid[~mask.astype(bool)] = 0.0

    grid = nb.Nifti1Image(grid, image.get_affine(), image.get_header())

    if save_file is not None:
        nb.save(grid, save_file)

    return grid
def create_grid(image, scale=4, apply_mask=True, save_file=None):
    """ Creates an image containing labeled cells in a 3D grid.
    Args:
        image: String or nibabel image. The image used to define the grid
            dimensions. Also used to define the mask to apply to the grid.
            Only voxels with non-zero values in the mask will be retained; all
            other voxels will be zeroed out in the returned image.
        scale: The scaling factor which controls the grid size. Value reflects
            diameter of cube in voxels.
        apply_mask: Boolean indicating whether or not to zero out voxels not in
            image.
        save_file: Optional string giving the path to save image to. Image
            written out is a standard Nifti image. If save_file is None, no
            image is written.
    Returns:
        A nibabel image with the same dimensions as the input image. All voxels
        in each cell in the 3D grid are assigned the same non-zero label.
    """
    if isinstance(image, string_types):
        image = nb.load(image)

    # create a list of cluster centers
    centers = []
    x_length, y_length, z_length = image.shape
    for x in range(0, x_length, scale):
        for y in range(0, y_length, scale):
            for z in range(0, z_length, scale):
                centers.append((x, y, z))

    # create a box around each center with the diameter equal to the scaling
    # factor
    grid = np.zeros(image.shape)
    for (i, (x, y, z)) in enumerate(centers):
        for mov_x in range((-scale + 1) // 2, (scale + 1) // 2):
            for mov_y in range((-scale + 1) // 2, (scale + 1) // 2):
                for mov_z in range((-scale + 1) // 2, (scale + 1) // 2):
                    try:  # Ignore voxels outside bounds of image
                        grid[x + mov_x, y + mov_y, z + mov_z] = i + 1
                    except:
                        pass

    if apply_mask:
        mask = image
        if isinstance(mask, string_types):
            mask = nb.load(mask)
        if type(mask).__module__ != np.__name__:
            mask = mask.get_data()
        grid[~mask.astype(bool)] = 0.0

    grid = nb.Nifti1Image(grid, image.get_affine(), image.get_header())

    if save_file is not None:
        nb.save(grid, save_file)

    return grid
def create_grid ( image , scale = 4 , apply_mask = True , save_file = None ) : if isinstance ( image , string_types ) : image = nb . load ( image ) # create a list of cluster centers centers = [ ] x_length , y_length , z_length = image . shape for x in range ( 0 , x_length , scale ) : for y in range ( 0 , y_length , scale ) : for z in range ( 0 , z_length , scale ) : centers . append ( ( x , y , z ) ) # create a box around each center with the diameter equal to the scaling # factor grid = np . zeros ( image . shape ) for ( i , ( x , y , z ) ) in enumerate ( centers ) : for mov_x in range ( ( - scale + 1 ) // 2 , ( scale + 1 ) // 2 ) : for mov_y in range ( ( - scale + 1 ) // 2 , ( scale + 1 ) // 2 ) : for mov_z in range ( ( - scale + 1 ) // 2 , ( scale + 1 ) // 2 ) : try : # Ignore voxels outside bounds of image grid [ x + mov_x , y + mov_y , z + mov_z ] = i + 1 except : pass if apply_mask : mask = image if isinstance ( mask , string_types ) : mask = nb . load ( mask ) if type ( mask ) . __module__ != np . __name__ : mask = mask . get_data ( ) grid [ ~ mask . astype ( bool ) ] = 0.0 grid = nb . Nifti1Image ( grid , image . get_affine ( ) , image . get_header ( ) ) if save_file is not None : nb . save ( grid , save_file ) return grid
Creates an image containing labeled cells in a 3D grid.
    Args:
        image: String or nibabel image. The image used to define the grid
            dimensions. Also used to define the mask to apply to the grid.
            Only voxels with non-zero values in the mask will be retained; all
            other voxels will be zeroed out in the returned image.
        scale: The scaling factor which controls the grid size. Value reflects
            diameter of cube in voxels.
        apply_mask: Boolean indicating whether or not to zero out voxels not in
            image.
        save_file: Optional string giving the path to save image to. Image
            written out is a standard Nifti image. If save_file is None, no
            image is written.
    Returns:
        A nibabel image with the same dimensions as the input image. All voxels
        in each cell in the 3D grid are assigned the same non-zero label.
Creates an image containing labeled cells in a 3D grid . Args : image : String or nibabel image . The image used to define the grid dimensions . Also used to define the mask to apply to the grid . Only voxels with non - zero values in the mask will be retained ; all other voxels will be zeroed out in the returned image . scale : The scaling factor which controls the grid size . Value reflects diameter of cube in voxels . apply_mask : Boolean indicating whether or not to zero out voxels not in image . save_file : Optional string giving the path to save image to . Image written out is a standard Nifti image . If save_file is None no image is written . Returns : A nibabel image with the same dimensions as the input image . All voxels in each cell in the 3D grid are assigned the same non - zero label .