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from numpy import arange, convolve, random, sin, pi, exp, array, zeros, float64
from cogent.util.unit_test import TestCase, main
from cogent.maths.period import ipdft, dft, auto_corr, hybrid, goertzel
# because we'll be comparing python and pyrexed implementations of the same
# algorithms I'm separating out those imports to make it clear
from cogent.maths.period import _ipdft_inner2 as py_ipdft_inner, \
_goertzel_inner as py_goertzel_inner, _autocorr_inner2 as py_autocorr_inner
try:
from cogent.maths._period import ipdft_inner as pyx_ipdft_inner, \
goertzel_inner as pyx_goertzel_inner, \
autocorr_inner as pyx_autocorr_inner
pyrex_available = True
except ImportError:
pyrex_available = False
__author__ = "Hua Ying, Julien Epps and Gavin Huttley"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["Julien Epps", "Hua Ying", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.5.3"
__maintainer__ = "Gavin Huttley"
__email__ = "Gavin.Huttley@anu.edu.au"
__status__ = "Production"
class TestPeriod(TestCase):
def setUp(self):
t = arange(0, 10, 0.1)
n = random.randn(len(t))
nse = convolve(n, exp(-t/0.05))*0.1
nse = nse[:len(t)]
self.sig = sin(2*pi*t) + nse
self.p = 10
def test_inner_funcs(self):
"""python and pyrexed implementation should be the same"""
if pyrex_available is not True:
return
x = array([0.04874203, 0.56831373, 0.94267804, 0.95664485, 0.60719478,
-0.09037356, -0.69897319, -1.11239811, -0.84127485, -0.56281126,
0.02301213, 0.56250284, 1.0258557 , 1.03906527, 0.69885916,
0.10103556, -0.43248024, -1.03160503, -0.84901545, -0.84934356,
0.00323728, 0.44344594, 0.97736748, 1.01635433, 0.38538423,
0.09869918, -0.60441861, -0.90175391, -1.00166887, -0.66303249,
-0.02070569, 0.76520328, 0.93462426, 0.97011673, 0.63199999,
0.0764678 , -0.55680168, -0.92028808, -0.98481451, -0.57600588,
0.0482667 , 0.57572519, 1.02077883, 0.93271663, 0.41581696,
-0.07639671, -0.71426286, -0.97730119, -1.0370596 , -0.67919572,
0.03779302, 0.60408759, 0.87826068, 0.79126442, 0.69769622,
0.01419442, -0.42917556, -1.00100485, -0.83945546, -0.55746313,
0.12730859, 0.60057659, 0.98059721, 0.83275501, 0.69031804,
0.02277554, -0.63982729, -1.23680355, -0.79477887, -0.67773375,
-0.05204714, 0.51765381, 0.77691955, 0.8996709 , 0.5153137 ,
0.01840839, -0.65124866, -1.13269058, -0.92342177, -0.45673709,
0.11212881, 0.50153941, 1.09329507, 0.96457193, 0.80271578,
-0.0041043 , -0.81750772, -0.99259986, -0.92343788, -0.57694955,
0.13982059, 0.56653375, 0.82217563, 0.85162513, 0.3984116 ,
-0.18937514, -0.65304629, -1.0067146 , -1.0037422 , -0.68011283])
N = 100
period = 10
self.assertFloatEqual(py_goertzel_inner(x, N, period),
pyx_goertzel_inner(x, N, period))
ulim = 8
N = 8
x = array([ 0., 1., 0., -1., 0., 1., 0., -1.])
X = zeros(8, dtype='complex128')
W = array([1.00000000e+00 +2.44929360e-16j,
-1.00000000e+00 -1.22464680e-16j,
-5.00000000e-01 -8.66025404e-01j,
6.12323400e-17 -1.00000000e+00j,
3.09016994e-01 -9.51056516e-01j,
5.00000000e-01 -8.66025404e-01j,
6.23489802e-01 -7.81831482e-01j,
7.07106781e-01 -7.07106781e-01j])
py_result = py_ipdft_inner(x, X, W, ulim, N)
pyx_result = pyx_ipdft_inner(x, X, W, ulim, N)
for i, j in zip(py_result, pyx_result):
self.assertFloatEqual(abs(i), abs(j))
x = array([-0.07827614, 0.56637551, 1.01320526, 1.01536245, 0.63548361,
0.08560101, -0.46094955, -0.78065656, -0.8893556 , -0.56514145,
0.02325272, 0.63660719, 0.86291302, 0.82953598, 0.5706848 ,
0.11655242, -0.6472655 , -0.86178218, -0.96495057, -0.76098445,
-0.18911517, 0.59280646, 1.00248693, 0.89241423, 0.52475111,
-0.01620599, -0.60199278, -0.98279829, -1.12469771, -0.61355799,
0.04321191, 0.52784788, 0.68508784, 0.86015123, 0.66825756,
-0.0802846 , -0.63626753, -0.93023345, -0.99129547, -0.46891033,
0.04145813, 0.71226518, 1.01499246, 0.94726778, 0.63598143,
-0.21920589, -0.48071702, -0.86041579, -0.9046141 , -0.55714746,
-0.10052384, 0.69708969, 1.02575789, 1.16524031, 0.49895282,
-0.13068573, -0.45770419, -0.86155787, -0.9230734 , -0.6590525 ,
-0.05072955, 0.52380317, 1.02674335, 0.87778499, 0.4303284 ,
-0.01855665, -0.62858193, -0.93954774, -0.94257301, -0.49692951,
0.00699347, 0.69049074, 0.93906549, 1.06339809, 0.69337543,
0.00252569, -0.57825881, -0.88460603, -0.99259672, -0.73535697,
0.12064751, 0.91159174, 0.88966993, 1.02159917, 0.43479926,
-0.06159005, -0.61782651, -0.95284676, -0.8218889 , -0.52166419,
0.021961 , 0.52268762, 0.79428288, 1.01642697, 0.49060377,
-0.02183994, -0.52743836, -0.99363909, -1.02963821, -0.64249996])
py_xc = zeros(2*len(x)-1, dtype=float64)
pyx_xc = py_xc.copy()
N = 100
py_autocorr_inner(x, py_xc, N)
pyx_autocorr_inner(x, pyx_xc, N)
for i, j in zip(py_xc, pyx_xc):
self.assertFloatEqual(i, j)
def test_autocorr(self):
"""correctly compute autocorrelation"""
s = [1,1,1,1]
X, periods = auto_corr(s, llim=-3, ulim=None)
exp_X = array([1,2,3,4,3,2,1], dtype=float)
self.assertEqual(X, exp_X)
auto_x, auto_periods = auto_corr(self.sig, llim=2, ulim=50)
max_idx = list(auto_x).index(max(auto_x))
auto_p = auto_periods[max_idx]
self.assertEqual(auto_p, self.p)
def test_dft(self):
"""correctly compute discrete fourier transform"""
dft_x, dft_periods = dft(self.sig)
dft_x = abs(dft_x)
max_idx = list(dft_x).index(max(dft_x))
dft_p = dft_periods[max_idx]
self.assertEqual(int(dft_p), self.p)
def test_ipdft(self):
"""correctly compute integer discrete fourier transform"""
s = [0, 1, 0, -1, 0, 1, 0, -1]
X, periods = ipdft(s, llim=1, ulim=len(s))
exp_X = abs(array([0, 0, -1.5+0.866j, -4j, 2.927-0.951j, 1.5+0.866j,
0.302+0.627j, 0]))
X = abs(X)
self.assertFloatEqual(X, exp_X, eps=1e-3)
ipdft_x, ipdft_periods = ipdft(self.sig, llim=2, ulim=50)
ipdft_x = abs(ipdft_x)
max_idx = list(ipdft_x).index(max(ipdft_x))
ipdft_p = ipdft_periods[max_idx]
self.assertEqual(ipdft_p, self.p)
def test_goertzel(self):
"""goertzel and ipdft should be the same"""
ipdft_pwr, ipdft_prd = ipdft(self.sig, llim=10, ulim=10)
self.assertFloatEqual(goertzel(self.sig, 10), ipdft_pwr)
def test_hybrid(self):
"""correctly compute hybrid statistic"""
hybrid_x, hybrid_periods = hybrid(self.sig, llim=None, ulim=50)
hybrid_x = abs(hybrid_x)
max_idx = list(hybrid_x).index(max(hybrid_x))
hybrid_p = hybrid_periods[max_idx]
self.assertEqual(hybrid_p, self.p)
def test_hybrid_returns_all(self):
"""correctly returns hybrid, ipdft and autocorr statistics"""
ipdft_pwr, ipdft_prd = ipdft(self.sig, llim=2, ulim=50)
auto_x, auto_periods = auto_corr(self.sig, llim=2, ulim=50)
hybrid_x, hybrid_periods = hybrid(self.sig, llim=None, ulim=50)
hybrid_ipdft_autocorr_stats, hybrid_periods = hybrid(self.sig,
llim=None, ulim=50, return_all=True)
self.assertEqual(hybrid_ipdft_autocorr_stats[0], hybrid_x)
self.assertEqual(hybrid_ipdft_autocorr_stats[1], ipdft_pwr)
self.assertEqual(hybrid_ipdft_autocorr_stats[2], auto_x)
ipdft_pwr, ipdft_prd = ipdft(self.sig, llim=10, ulim=10)
auto_x, auto_periods = auto_corr(self.sig, llim=10, ulim=10)
hybrid_x, hybrid_periods = hybrid(self.sig, llim=10, ulim=10)
hybrid_ipdft_autocorr_stats, hybrid_periods = hybrid(self.sig,
llim=10, ulim=10, return_all=True)
self.assertEqual(hybrid_ipdft_autocorr_stats[0], hybrid_x)
self.assertEqual(hybrid_ipdft_autocorr_stats[1], ipdft_pwr)
self.assertEqual(hybrid_ipdft_autocorr_stats[2], auto_x)
if __name__ == '__main__':
main()
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