Loading minke/noise.py +26 −0 Original line number Diff line number Diff line Loading @@ -24,6 +24,32 @@ class PSD(): lalsimulation.SimNoisePSDFromFile(self.psd, fmin, filename) def SNR(self, waveform, detectors): """ Calculate the SNR for a given waveform compared to this SNR. Parameters ========== waveform : minke source object The waveform which should have its snr measured detectors : list A list of detector names in the format "L1" for the Livingston 4km detector, etc. Returns ======= network snr : float The SNR over the whole network described by the detector list SNRs : list A list of SNRs for each detector """ snrs = [] for detector in detectors: snrs.append(lalsimulation.MeasureSNR(waveform._generate_for_detector([detector]), self.psd)) snrs_r = np.array(snrs) snrs_r = snrs_r**2 return np.sqrt(snrs_r.sum()), snrs def plot(self): """ Loading Loading
minke/noise.py +26 −0 Original line number Diff line number Diff line Loading @@ -24,6 +24,32 @@ class PSD(): lalsimulation.SimNoisePSDFromFile(self.psd, fmin, filename) def SNR(self, waveform, detectors): """ Calculate the SNR for a given waveform compared to this SNR. Parameters ========== waveform : minke source object The waveform which should have its snr measured detectors : list A list of detector names in the format "L1" for the Livingston 4km detector, etc. Returns ======= network snr : float The SNR over the whole network described by the detector list SNRs : list A list of SNRs for each detector """ snrs = [] for detector in detectors: snrs.append(lalsimulation.MeasureSNR(waveform._generate_for_detector([detector]), self.psd)) snrs_r = np.array(snrs) snrs_r = snrs_r**2 return np.sqrt(snrs_r.sum()), snrs def plot(self): """ Loading