metric module

metric.M_q_func(coords)[source]
class metric.Metric(psd_xml, coord_func, duration=4, flow=30.0, fhigh=512.0, approximant='TaylorF2')[source]

Bases: object

distancesq(metric_tensor, x, y)[source]

Compute the distance squared between to points inside the cube using the metric tensor, but assuming it is constant

explicit_match(c1, c2)[source]
match_minus_1(w1, w2, t_factor=1.0)[source]
metric_match(metric_tensor, c1, c2)[source]
pseudo_match(metric_tensor, c1, c2)[source]
volume_element(metric_tensor)[source]
waveform(coords)[source]
metric.add_quadrature_phase(fseries, n)[source]

From the Fourier transform of a real-valued function of time, compute and return the Fourier transform of the complex-valued function of time whose real component is the original time series and whose imaginary component is the quadrature phase of the real part. fseries is a LAL COMPLEX16FrequencySeries and n is the number of samples in the original time series.

metric.ceil_pow_2(x)[source]
metric.m1_from_mc_m2(mc, m2)[source]
metric.m1_from_x_y_z_zn(x, y, z, zn)[source]
metric.m1_m2_func(coords)[source]
metric.m1_m2_s1z_s2z_func(coords)[source]
metric.m1_m2_s2z_func(coords)[source]
metric.m2_from_x_y_z_zn(x, y, z, zn)[source]
metric.mc_from_m1_m2(m1, m2)[source]
metric.s1_from_x_y_z_zn(x, y, z, zn)[source]
metric.s2_from_x_y_z_zn(x, y, z, zn)[source]
metric.x_from_m1_m2_s1_s2(m1, m2, s1, s2)[source]
metric.x_y_z_zn_func(coords)[source]
metric.y_from_m1_m2_s1_s2(m1, m2, s1, s2)[source]
metric.z_from_m1_m2_s1_s2(m1, m2, s1, s2)[source]
metric.zn_from_m1_m2_s1_s2(m1, m2, s1, s2)[source]