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Python

"""Tests for spline filtering."""
from __future__ import division, print_function, absolute_import
import numpy as np
import pytest
from numpy.testing import assert_almost_equal
from scipy import ndimage
def get_spline_knot_values(order):
"""Knot values to the right of a B-spline's center."""
knot_values = {0: [1],
1: [1],
2: [6, 1],
3: [4, 1],
4: [230, 76, 1],
5: [66, 26, 1]}
return knot_values[order]
def make_spline_knot_matrix(n, order, mode='mirror'):
"""Matrix to invert to find the spline coefficients."""
knot_values = get_spline_knot_values(order)
matrix = np.zeros((n, n))
for diag, knot_value in enumerate(knot_values):
indices = np.arange(diag, n)
if diag == 0:
matrix[indices, indices] = knot_value
else:
matrix[indices, indices - diag] = knot_value
matrix[indices - diag, indices] = knot_value
knot_values_sum = knot_values[0] + 2 * sum(knot_values[1:])
if mode == 'mirror':
start, step = 1, 1
elif mode == 'reflect':
start, step = 0, 1
elif mode == 'wrap':
start, step = -1, -1
else:
raise ValueError('unsupported mode {}'.format(mode))
for row in range(len(knot_values) - 1):
for idx, knot_value in enumerate(knot_values[row + 1:]):
matrix[row, start + step*idx] += knot_value
matrix[-row - 1, -start - 1 - step*idx] += knot_value
return matrix / knot_values_sum
@pytest.mark.parametrize('order', [0, 1, 2, 3, 4, 5])
@pytest.mark.parametrize('mode', ['mirror', 'wrap', 'reflect'])
def test_spline_filter_vs_matrix_solution(order, mode):
n = 100
eye = np.eye(n, dtype=float)
spline_filter_axis_0 = ndimage.spline_filter1d(eye, axis=0, order=order,
mode=mode)
spline_filter_axis_1 = ndimage.spline_filter1d(eye, axis=1, order=order,
mode=mode)
matrix = make_spline_knot_matrix(n, order, mode=mode)
assert_almost_equal(eye, np.dot(spline_filter_axis_0, matrix))
assert_almost_equal(eye, np.dot(spline_filter_axis_1, matrix.T))