def test_rebin_small_df(self):
segment_size = 3
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
with pytest.raises(ValueError):
dps.rebin_frequency(df_new=dps.df/2.0)
def test_rebin_frequency_average_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array(
[5.01000198, 15.01000198, 25.01000198, 35.01000198, 45.01000198])
rebin_dps = np.array([[1.15296690e-08], [1.41532979e-07],
[1.24993989e-02], [1.15516968e-07],
[3.53906336e-08]])
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
dps.rebin_frequency(df_new=df_new, method="average")
assert np.allclose(dps.freq, rebin_freq)
assert np.allclose(dps.dyn_ps, rebin_dps)
assert np.isclose(dps.df, df_new)
def test_rebin_frequency_default_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array(
[5.01000198, 15.01000198, 25.01000198, 35.01000198, 45.01000198])
rebin_dps = np.array([[5.76369293e-06], [7.07524761e-05],
[6.24846189e+00], [5.77470465e-05],
[1.76918128e-05]])
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
dps.rebin_frequency(df_new=df_new)
assert np.allclose(dps.freq, rebin_freq)
assert np.allclose(dps.dyn_ps, rebin_dps)
assert np.isclose(dps.df, df_new)
def test_rebin_frequency_average_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array([5.01000198, 15.01000198, 25.01000198,
35.01000198, 45.01000198])
rebin_dps = np.array([[1.15296690e-08],
[1.41532979e-07],
[1.24993989e-02],
[1.15516968e-07],
[3.53906336e-08]])
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
dps.rebin_frequency(df_new=df_new, method="average")
assert np.allclose(dps.freq, rebin_freq)
assert np.allclose(dps.dyn_ps, rebin_dps)
assert np.isclose(dps.df, df_new)
def test_rebin_frequency_default_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array([5.01000198, 15.01000198, 25.01000198,
35.01000198, 45.01000198])
rebin_dps = np.array([[5.76369293e-06],
[7.07524761e-05],
[6.24846189e+00],
[5.77470465e-05],
[1.76918128e-05]])
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
dps.rebin_frequency(df_new=df_new)
assert np.allclose(dps.freq, rebin_freq)
assert np.allclose(dps.dyn_ps, rebin_dps)
assert np.isclose(dps.df, df_new)
def test_rebin_frequency_average_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array(
[5.01000198, 15.01000198, 25.01000198, 35.01000198, 45.01000198])
rebin_dps = np.array([[1.15296690e-08], [1.41532979e-07],
[1.24993989e-02], [1.15516968e-07],
[3.53906336e-08]])
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
new_dps = dps.rebin_frequency(df_new=df_new, method="average")
assert np.allclose(new_dps.freq, rebin_freq)
assert np.allclose(new_dps.dyn_ps, rebin_dps)
assert np.isclose(new_dps.df, df_new)
def test_rebin_frequency_default_method(self):
segment_size = 50
df_new = 10.0
rebin_freq = np.array(
[5.01000198, 15.01000198, 25.01000198, 35.01000198, 45.01000198])
rebin_dps = np.array([[5.76369293e-06], [7.07524761e-05],
[6.24846189e+00], [5.77470465e-05],
[1.76918128e-05]])
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
new_dps = dps.rebin_frequency(df_new=df_new)
assert np.allclose(new_dps.freq, rebin_freq)
assert np.allclose(new_dps.dyn_ps, rebin_dps)
assert np.isclose(new_dps.df, df_new)
def test_rebin_small_df(self):
segment_size = 3
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
with pytest.raises(ValueError):
dps.rebin_frequency(df_new=dps.df / 2.0)
def test_rebin_small_df(self):
segment_size = 3
dps = DynamicalPowerspectrum(self.lc, segment_size=segment_size)
with pytest.raises(ValueError):
dps.rebin_frequency(df_new=dps.df/2.0)
