File size: 6,721 Bytes
c5f0b3c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 |
import numpy as np
from numpy.testing import (assert_equal,
assert_array_equal, assert_array_almost_equal, assert_array_less, assert_,)
import pytest
import scipy.signal._wavelets as wavelets
class TestWavelets:
def test_qmf(self):
with pytest.deprecated_call():
assert_array_equal(wavelets.qmf([1, 1]), [1, -1])
def test_daub(self):
with pytest.deprecated_call():
for i in range(1, 15):
assert_equal(len(wavelets.daub(i)), i * 2)
def test_cascade(self):
with pytest.deprecated_call():
for J in range(1, 7):
for i in range(1, 5):
lpcoef = wavelets.daub(i)
k = len(lpcoef)
x, phi, psi = wavelets.cascade(lpcoef, J)
assert_(len(x) == len(phi) == len(psi))
assert_equal(len(x), (k - 1) * 2 ** J)
def test_morlet(self):
with pytest.deprecated_call():
x = wavelets.morlet(50, 4.1, complete=True)
y = wavelets.morlet(50, 4.1, complete=False)
# Test if complete and incomplete wavelet have same lengths:
assert_equal(len(x), len(y))
# Test if complete wavelet is less than incomplete wavelet:
assert_array_less(x, y)
x = wavelets.morlet(10, 50, complete=False)
y = wavelets.morlet(10, 50, complete=True)
# For large widths complete and incomplete wavelets should be
# identical within numerical precision:
assert_equal(x, y)
# miscellaneous tests:
x = np.array([1.73752399e-09 + 9.84327394e-25j,
6.49471756e-01 + 0.00000000e+00j,
1.73752399e-09 - 9.84327394e-25j])
y = wavelets.morlet(3, w=2, complete=True)
assert_array_almost_equal(x, y)
x = np.array([2.00947715e-09 + 9.84327394e-25j,
7.51125544e-01 + 0.00000000e+00j,
2.00947715e-09 - 9.84327394e-25j])
y = wavelets.morlet(3, w=2, complete=False)
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, s=4, complete=True)
y = wavelets.morlet(20000, s=8, complete=True)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, s=4, complete=False)
assert_array_almost_equal(y, x, decimal=2)
y = wavelets.morlet(20000, s=8, complete=False)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, w=3, s=5, complete=True)
y = wavelets.morlet(20000, w=3, s=10, complete=True)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, w=3, s=5, complete=False)
assert_array_almost_equal(y, x, decimal=2)
y = wavelets.morlet(20000, w=3, s=10, complete=False)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, w=7, s=10, complete=True)
y = wavelets.morlet(20000, w=7, s=20, complete=True)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
x = wavelets.morlet(10000, w=7, s=10, complete=False)
assert_array_almost_equal(x, y, decimal=2)
y = wavelets.morlet(20000, w=7, s=20, complete=False)[5000:15000]
assert_array_almost_equal(x, y, decimal=2)
def test_morlet2(self):
with pytest.deprecated_call():
w = wavelets.morlet2(1.0, 0.5)
expected = (np.pi**(-0.25) * np.sqrt(1/0.5)).astype(complex)
assert_array_equal(w, expected)
lengths = [5, 11, 15, 51, 101]
for length in lengths:
w = wavelets.morlet2(length, 1.0)
assert_(len(w) == length)
max_loc = np.argmax(w)
assert_(max_loc == (length // 2))
points = 100
w = abs(wavelets.morlet2(points, 2.0))
half_vec = np.arange(0, points // 2)
assert_array_almost_equal(w[half_vec], w[-(half_vec + 1)])
x = np.array([5.03701224e-09 + 2.46742437e-24j,
1.88279253e+00 + 0.00000000e+00j,
5.03701224e-09 - 2.46742437e-24j])
y = wavelets.morlet2(3, s=1/(2*np.pi), w=2)
assert_array_almost_equal(x, y)
def test_ricker(self):
with pytest.deprecated_call():
w = wavelets.ricker(1.0, 1)
expected = 2 / (np.sqrt(3 * 1.0) * (np.pi ** 0.25))
assert_array_equal(w, expected)
lengths = [5, 11, 15, 51, 101]
for length in lengths:
w = wavelets.ricker(length, 1.0)
assert_(len(w) == length)
max_loc = np.argmax(w)
assert_(max_loc == (length // 2))
points = 100
w = wavelets.ricker(points, 2.0)
half_vec = np.arange(0, points // 2)
#Wavelet should be symmetric
assert_array_almost_equal(w[half_vec], w[-(half_vec + 1)])
#Check zeros
aas = [5, 10, 15, 20, 30]
points = 99
for a in aas:
w = wavelets.ricker(points, a)
vec = np.arange(0, points) - (points - 1.0) / 2
exp_zero1 = np.argmin(np.abs(vec - a))
exp_zero2 = np.argmin(np.abs(vec + a))
assert_array_almost_equal(w[exp_zero1], 0)
assert_array_almost_equal(w[exp_zero2], 0)
def test_cwt(self):
with pytest.deprecated_call():
widths = [1.0]
def delta_wavelet(s, t):
return np.array([1])
len_data = 100
test_data = np.sin(np.pi * np.arange(0, len_data) / 10.0)
#Test delta function input gives same data as output
cwt_dat = wavelets.cwt(test_data, delta_wavelet, widths)
assert_(cwt_dat.shape == (len(widths), len_data))
assert_array_almost_equal(test_data, cwt_dat.flatten())
#Check proper shape on output
widths = [1, 3, 4, 5, 10]
cwt_dat = wavelets.cwt(test_data, wavelets.ricker, widths)
assert_(cwt_dat.shape == (len(widths), len_data))
widths = [len_data * 10]
#Note: this wavelet isn't defined quite right, but is fine for this test
def flat_wavelet(l, w):
return np.full(w, 1 / w)
cwt_dat = wavelets.cwt(test_data, flat_wavelet, widths)
assert_array_almost_equal(cwt_dat, np.mean(test_data))
|