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"""Unit tests for Lomb Scargle routines.
"""
import numpy as np
from numpy.testing import dec, assert_raises, assert_equal, \
assert_almost_equal, assert_array_equal, \
assert_array_almost_equal, assert_approx_equal, \
assert_, run_module_suite
from scipy.signal.spectral import lombscargle
class TestLombscargle:
def test_frequency(self):
"""Test if frequency location of peak corresponds to frequency of
generated input signal.
"""
# Input parameters
ampl = 2.
w = 1.
phi = 0.5 * np.pi
nin = 100
nout = 1000
p = 0.7 # Fraction of points to select
# Randomly select a fraction of an array with timesteps
np.random.seed(2353425)
r = np.random.rand(nin)
t = np.linspace(0.01*np.pi, 10.*np.pi, nin)[r >= p]
# Plot a sine wave for the selected times
x = ampl * np.sin(w*t + phi)
# Define the array of frequencies for which to compute the periodogram
f = np.linspace(0.01, 10., nout)
# Calculate Lomb-Scargle periodogram
P = lombscargle(t, x, f)
# Check if difference between found frequency maximum and input
# frequency is less than accuracy
delta = f[1] - f[0]
assert_(w - f[np.argmax(P)] < (delta/2.))
def test_amplitude(self):
"""Test if height of peak in normalized Lomb-Scargle periodogram
corresponds to amplitude of the generated input signal.
"""
# Input parameters
ampl = 2.
w = 1.
phi = 0.5 * np.pi
nin = 100
nout = 1000
p = 0.7 # Fraction of points to select
# Randomly select a fraction of an array with timesteps
np.random.seed(2353425)
r = np.random.rand(nin)
t = np.linspace(0.01*np.pi, 10.*np.pi, nin)[r >= p]
# Plot a sine wave for the selected times
x = ampl * np.sin(w*t + phi)
# Define the array of frequencies for which to compute the periodogram
f = np.linspace(0.01, 10., nout)
# Calculate Lomb-Scargle periodogram
pgram = lombscargle(t, x, f)
# Normalize
pgram = np.sqrt(4 * pgram / t.shape[0])
# Check if difference between found frequency maximum and input
# frequency is less than accuracy
assert_approx_equal(np.max(pgram), ampl, significant=2)
def test_wrong_shape(self):
t = np.linspace(0, 1, 1)
x = np.linspace(0, 1, 2)
f = np.linspace(0, 1, 3)
assert_raises(ValueError, lombscargle, t, x, f)
def test_zero_division(self):
t = np.zeros(1)
x = np.zeros(1)
f = np.zeros(1)
assert_raises(ZeroDivisionError, lombscargle, t, x, f)
if __name__ == "__main__":
run_module_suite()
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