\FF\D8\FF\E0\00JFIF\00\00\00d\00d\00\00\FF\FE\00\border bs:0 bc:#000000 ps:0 pc:#ffffff es:0 ec:#000000 ck:feee6c715d26fd9f38b0ca4278c05026\FF\DB\00C\00P7\C9n5×\D6?\BDê\9Ds\EBp\9F[`8m\B7)o\B5\E8\E6I\99\FE3]]A2\BA\8Cw\D6E\93\\DEv\C8\009\F2\F1NI?uc\\F5\EA\96k\xN<~buv\EA\C8\D7 \8B\84\CEcxI\BBg\AE\9E=\D6+n\EC\80\C8A\8C\AE\EB\CF\D5\DA\E9"2\A4\B9j5\EB\F3W\B63\96\B30Yu\DA\FC8\ED\DF\E7Ms\FB\F1\8E\B3\FA\EA\E8\E6(\883zs\F2_\8DFk\8Bh \00\8C\DCw\D3R\B5+6X\BA\B2\C4j\AB0\B4\FCMw\C2I\8E\9B\E3\A9~9u\FA\D3l\80\C8%p\EE\FDn2€ \00 $\FEj\C4e\A9\DB\~\95\A7\A5\80EK\BB\8DDsP\00@@AD'k\CF\E8\DB\D2(\80\9AK\D3\85\D6lb\F2\BA\8C*\80\00)\95 59\A3R:\F3\CE"\B6\80\88\00\00i1u4ê\E9\F2á\A6\A2\FACM\93WMb*\E0*\00\00\00\00\00(\A8\80\00\00\80\00\00\00\00\00\00\00\00\00\FF\D9 C/// """Test functions for fftpack.helper module Copied from fftpack.helper by Pearu Peterson, October 2005 """ import numpy as np from numpy.testing import assert_array_almost_equal from numpy import fft, pi class TestFFTShift: def test_definition(self): x = [0, 1, 2, 3, 4, -4, -3, -2, -1] y = [-4, -3, -2, -1, 0, 1, 2, 3, 4] assert_array_almost_equal(fft.fftshift(x), y) assert_array_almost_equal(fft.ifftshift(y), x) x = [0, 1, 2, 3, 4, -5, -4, -3, -2, -1] y = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4] assert_array_almost_equal(fft.fftshift(x), y) assert_array_almost_equal(fft.ifftshift(y), x) def test_inverse(self): for n in [1, 4, 9, 100, 211]: x = np.random.random((n,)) assert_array_almost_equal(fft.ifftshift(fft.fftshift(x)), x) def test_axes_keyword(self): freqs = [[0, 1, 2], [3, 4, -4], [-3, -2, -1]] shifted = [[-1, -3, -2], [2, 0, 1], [-4, 3, 4]] assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shifted) assert_array_almost_equal(fft.fftshift(freqs, axes=0), fft.fftshift(freqs, axes=(0,))) assert_array_almost_equal(fft.ifftshift(shifted, axes=(0, 1)), freqs) assert_array_almost_equal(fft.ifftshift(shifted, axes=0), fft.ifftshift(shifted, axes=(0,))) assert_array_almost_equal(fft.fftshift(freqs), shifted) assert_array_almost_equal(fft.ifftshift(shifted), freqs) def test_uneven_dims(self): """ Test 2D input, which has uneven dimension sizes """ freqs = [ [0, 1], [2, 3], [4, 5] ] # shift in dimension 0 shift_dim0 = [ [4, 5], [0, 1], [2, 3] ] assert_array_almost_equal(fft.fftshift(freqs, axes=0), shift_dim0) assert_array_almost_equal(fft.ifftshift(shift_dim0, axes=0), freqs) assert_array_almost_equal(fft.fftshift(freqs, axes=(0,)), shift_dim0) assert_array_almost_equal(fft.ifftshift(shift_dim0, axes=[0]), freqs) # shift in dimension 1 shift_dim1 = [ [1, 0], [3, 2], [5, 4] ] assert_array_almost_equal(fft.fftshift(freqs, axes=1), shift_dim1) assert_array_almost_equal(fft.ifftshift(shift_dim1, axes=1), freqs) # shift in both dimensions shift_dim_both = [ [5, 4], [1, 0], [3, 2] ] assert_array_almost_equal(fft.fftshift(freqs, axes=(0, 1)), shift_dim_both) assert_array_almost_equal(fft.ifftshift(shift_dim_both, axes=(0, 1)), freqs) assert_array_almost_equal(fft.fftshift(freqs, axes=[0, 1]), shift_dim_both) assert_array_almost_equal(fft.ifftshift(shift_dim_both, axes=[0, 1]), freqs) # axes=None (default) shift in all dimensions assert_array_almost_equal(fft.fftshift(freqs, axes=None), shift_dim_both) assert_array_almost_equal(fft.ifftshift(shift_dim_both, axes=None), freqs) assert_array_almost_equal(fft.fftshift(freqs), shift_dim_both) assert_array_almost_equal(fft.ifftshift(shift_dim_both), freqs) def test_equal_to_original(self): """ Test that the new (>=v1.15) implementation (see #10073) is equal to the original (<=v1.14) """ from numpy.core import asarray, concatenate, arange, take def original_fftshift(x, axes=None): """ How fftshift was implemented in v1.14""" tmp = asarray(x) ndim = tmp.ndim if axes is None: axes = list(range(ndim)) elif isinstance(axes, int): axes = (axes,) y = tmp for k in axes: n = tmp.shape[k] p2 = (n + 1) // 2 mylist = concatenate((arange(p2, n), arange(p2))) y = take(y, mylist, k) return y def original_ifftshift(x, axes=None): """ How ifftshift was implemented in v1.14 """ tmp = asarray(x) ndim = tmp.ndim if axes is None: axes = list(range(ndim)) elif isinstance(axes, int): axes = (axes,) y = tmp for k in axes: n = tmp.shap