def test_rebin_small_dt(self): segment_size = 3 with warnings.catch_warnings(): warnings.simplefilter("ignore", category=UserWarning) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) with pytest.raises(ValueError): dps.rebin_time(dt_new=2.0)
def test_rebin_time_average_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([2., 6., 10.]) rebin_dps = np.array([[0.59722222, 0.87301587, 0.21428571]]) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) dps.rebin_time(dt_new=dt_new, method='average') assert np.allclose(dps.time, rebin_time) assert np.allclose(dps.dyn_ps, rebin_dps) assert np.isclose(dps.dt, dt_new)
def test_rebin_time_default_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([2., 6., 10.]) rebin_dps = np.array([[0.7962963, 1.16402116, 0.28571429]]) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) dps.rebin_time(dt_new=dt_new) assert np.allclose(dps.time, rebin_time) assert np.allclose(dps.dyn_ps, rebin_dps) assert np.isclose(dps.dt, dt_new)
def test_rebin_time_average_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([ 2., 6., 10.]) rebin_dps = np.array([[0.59722222, 0.87301587, 0.21428571]]) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) dps.rebin_time(dt_new=dt_new, method='average') assert np.allclose(dps.time, rebin_time) assert np.allclose(dps.dyn_ps, rebin_dps) assert np.isclose(dps.dt, dt_new)
def test_rebin_time_default_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([ 2., 6., 10.]) rebin_dps = np.array([[0.7962963 , 1.16402116, 0.28571429]]) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) dps.rebin_time(dt_new=dt_new) assert np.allclose(dps.time, rebin_time) assert np.allclose(dps.dyn_ps, rebin_dps) assert np.isclose(dps.dt, dt_new)
def test_rebin_time_mean_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([1.5, 5.5, 9.5, 13.5]) rebin_dps = np.array([[0.59722222, 0.87301587, 0.21428571, 0.4921875]]) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) dps.rebin_time(dt_new=dt_new, method='mean') assert np.allclose(dps.time, rebin_time) assert np.allclose(dps.dyn_ps, rebin_dps) assert np.isclose(dps.dt, dt_new)
def test_rebin_time_mean_method(self): segment_size = 3 dt_new = 4.0 rebin_time = np.array([ 2., 6., 10.]) rebin_dps = np.array([[0.59722222, 0.87301587, 0.21428571]]) with warnings.catch_warnings(): warnings.simplefilter("ignore", category=UserWarning) dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) new_dps = dps.rebin_time(dt_new=dt_new, method='mean') assert np.allclose(new_dps.time, rebin_time) assert np.allclose(new_dps.dyn_ps, rebin_dps) assert np.isclose(new_dps.dt, dt_new)
def test_rebin_small_dt(self): segment_size = 3 dps = DynamicalPowerspectrum(self.lc_test, segment_size=segment_size) with pytest.raises(ValueError): dps.rebin_time(dt_new=2.0)