Stationary
- class legwork.source.Stationary(m_1, m_2, ecc, dist, n_proc=1, f_orb=None, a=None, position=None, polarisation=None, inclination=None, weights=None, gw_lum_tol=0.05, stat_tol=0.01, interpolate_g=True, interpolate_sc=True, sc_params={})[source]
Bases:
Source
Subclass for sources that are stationary
Methods Summary
get_snr
([t_obs, instrument, custom_psd, verbose])Computes the SNR for a generic binary.
Methods Documentation
- get_snr(t_obs=None, instrument=None, custom_psd=None, verbose=False)[source]
Computes the SNR for a generic binary. Also records the harmonic with maximum SNR for each binary in
self.max_snr_harmonic
.- Parameters
- t_obsarray
Observation duration (default: value from sc_params)
- instrument{{ ‘LISA’, ‘TianQin’, ‘custom’ }}
Instrument to observe with. If ‘custom’ then
custom_psd
must be supplied. (default: value from sc_params)- custom_psdfunction
Custom function for computing the PSD. Must take the same arguments as
legwork.psd.lisa_psd()
even if it ignores some. (default: function from sc_params)- Lfloat
LISA arm length in metres
- approximate_Rboolean
Whether to approximate the response function (default: no)
- confusion_noisevarious
Galactic confusion noise. Acceptable inputs are either one of the values listed in
legwork.psd.get_confusion_noise()
, “auto” (automatically selects confusion noise based on instrument - ‘robson19’ if LISA and ‘huang20’ if TianQin), or a custom function that gives the confusion noise at each frequency for a given mission length where it would be called by running noise(f, t_obs) and return a value with units of inverse Hertz- n_stepint
Number of time steps during observation duration
- verboseboolean
Whether to print additional information to user
- re_interpolate_scboolean
Whether to re-interpolate the sensitivity curve if the observation time or instrument changes. If False, warning will instead be given
- which_sourcesboolean/array
Mask of which sources to calculate the SNR for. If None then calculate SNR for all sources.
- Returns
- SNRarray
The signal-to-noise ratio