Source code for gammapy.maps.image_utils

# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Image utility functions."""
import logging
import numpy as np
import scipy.ndimage
import scipy.signal
from astropy.convolution import Gaussian2DKernel

__all__ = ["scale_cube"]

log = logging.getLogger(__name__)

def _fftconvolve_wrap(kernel, data):
    # wrap gaussian filter as a special case, because the gain in
    # performance is factor ~100
    if isinstance(kernel, Gaussian2DKernel):
        width = kernel.model.x_stddev.value
        norm = kernel.array.sum()
        return norm * scipy.ndimage.gaussian_filter(data, width)
        return scipy.signal.fftconvolve(data, kernel.array, mode="same")

[docs]def scale_cube(data, kernels): """ Compute scale space cube. Compute scale space cube by convolving the data with a set of kernels and stack the resulting images along the third axis. Parameters ---------- data : `~numpy.ndarray` Input data. kernels: list of `~astropy.convolution.Kernel` List of convolution kernels. Returns ------- cube : `~numpy.ndarray` Array of the shape (len(kernels), data.shape) """ return np.dstack(_fftconvolve_wrap(kernel, data) for kernel in kernels)