#!/usr/bin/env python

"""Spatial filtering of image arrays with the FFT."""


import functools
import numpy
from numpy import fft

from . import map


def _low_pass_filter(shape, radius):
    m, n = shape
    a, b = m // 2, n // 2
    i = numpy.indices((m, n), dtype=numpy.float32)
    rows, columns = i[0, :], i[1, :]
    d = (rows - a) ** 2 + (columns - b) ** 2
    d[d <= radius ** 2] = 1.0
    d[d > radius ** 2] = 0.0
    return d


def _high_pass_filter(shape, radius):
    return 1.0 - _low_pass_filter(shape, radius)


def _filter(filter, array):
    X = fft.rfft2(array)
    X = fft.fftshift(X)
    numpy.multiply(X, filter, out=X)
    X = fft.ifftshift(X)
    x = fft.irfft2(X, s=array.shape)
    return x


def _rshape(shape):
    m, n = shape
    if n % 2 == 0:
        return (m, (n // 2) + 1)
    else:
        return (m, (n + 1) // 2)


def _lowpass(radius, array):
    rfilter = _low_pass_filter(_rshape(array.shape), radius)
    return _filter(rfilter, array)


def lowpass(img, radius):
    """Apply a 2D low-pass filter to an image array."""
    return map.map_to_channels(
        functools.partial(_lowpass, radius),
        img,
    )


def _highpass(radius, array):
    rfilter = _high_pass_filter(_rshape(array.shape), radius)
    return _filter(rfilter, array)


def highpass(img, radius):
    """Apply a 2D high-pass filter to an image array."""
    return map.map_to_channels(
        functools.partial(_highpass, radius),
        lambda shape: shape,
        img,
    )


if __name__ == '__main__':
    pass

#!/usr/bin/env python

"""Spatial filtering of image arrays with the FFT."""


import functools
import numpy
from numpy import fft

from . import map


def _low_pass_filter(shape, radius):
    m, n = shape
    a, b = m // 2, n // 2
    i = numpy.indices((m, n), dtype=numpy.float32)
    rows, columns = i[0, :], i[1, :]
    d = (rows - a) ** 2 + (columns - b) ** 2
    d[d <= radius ** 2] = 1.0
    d[d > radius ** 2] = 0.0
    return d


def _high_pass_filter(shape, radius):
    return 1.0 - _low_pass_filter(shape, radius)


def _filter(filter, array):
    X = fft.rfft2(array)
    X = fft.fftshift(X)
    numpy.multiply(X, filter, out=X)
    X = fft.ifftshift(X)
    x = fft.irfft2(X, s=array.shape)
    return x


def _rshape(shape):
    m, n = shape
    if n % 2 == 0:
        return (m, (n // 2) + 1)
    else:
        return (m, (n + 1) // 2)


def _lowpass(radius, array):
    rfilter = _low_pass_filter(_rshape(array.shape), radius)
    return _filter(rfilter, array)


def lowpass(img, radius):
    """Apply a 2D low-pass filter to an image array."""
    return map.map_to_channels(
        functools.partial(_lowpass, radius),
        img,
    )


def _highpass(radius, array):
    rfilter = _high_pass_filter(_rshape(array.shape), radius)
    return _filter(rfilter, array)


def highpass(img, radius):
    """Apply a 2D high-pass filter to an image array."""
    return map.map_to_channels(
        functools.partial(_highpass, radius),
        img,
    )


if __name__ == '__main__':
    pass

Use the new mapping function.