if opts.verbose:
print "generating white noise (in the freq domain)"
(freqs, wFreqDom), (times, wTimeDom) = waveforms.whiteNoise( opts.duration, opts.sampling_rate )
# if opts.verbose:
# print "generating white noise (in the time domain)"
# timesT, wTimeDomT = waveforms.whiteNoiseT( opts.duration, opts.sampling_rate )
# wFreqDomT = np.fft.fftshift( np.fft.fft( wTimeDomT ) )/opts.sampling_rate
#-------------------------------------------------
to = max(opts.duration-3*opts.tau, opts.duration/2)
if opts.verbose:
print "generating injection with to=%.3f"%(to)
hTimeDom = waveforms.chirpSineGaussianT( times, 1.0, opts.freq, opts.freqDot, opts.tau, to )
hFreqDom = waveforms.chirpSineGaussianF( freqs, 1.0, opts.freq, opts.freqDot, opts.tau, to )
#-------------------------------------------------
if opts.verbose:
print "computing optimal SNR and scaling injection"
### for white-gaussian noise with unit-variance in the frequency domain
snr = ( 2 * np.sum( hFreqDom.real**2 + hFreqDom.imag**2 ) / opts.duration )**0.5
scaling = opts.SNR/snr
hTimeDom *= scaling
hFreqDom *= scaling
#-------------------------------------------------
#-------------------------------------------------
if opts.verbose:
print "generating white noise (in the freq domain)"
(freqs, wFreqDom1), (times, wTimeDom1) = waveforms.whiteNoise( opts.duration, opts.sampling_rate )
(freqs, wFreqDom2), (times, wTimeDom2) = waveforms.whiteNoise( opts.duration, opts.sampling_rate )
#-------------------------------------------------
dt = opts.D_over_c * np.cos( opts.theta*np.pi/180 )
to = opts.duration/2
if opts.verbose:
print "generating injection with to=%.3f"%(to)
hTimeDom1 = waveforms.chirpSineGaussianT( times, 1.0, opts.freq, opts.freqDot, opts.tau, to+dt/2 )
hFreqDom1 = waveforms.chirpSineGaussianF( freqs, 1.0, opts.freq, opts.freqDot, opts.tau, to+dt/2 )
hTimeDom2 = waveforms.chirpSineGaussianT( times, 1.0, opts.freq, opts.freqDot, opts.tau, to-dt/2 )
hFreqDom2 = waveforms.chirpSineGaussianF( freqs, 1.0, opts.freq, opts.freqDot, opts.tau, to-dt/2 )
#-------------------------------------------------
if opts.verbose:
print "computing optimal SNR and scaling injection"
### for white-gaussian noise with unit-variance in the frequency domain
snr = ( 2 * np.sum( hFreqDom1.real**2 + hFreqDom1.imag**2 + hFreqDom2.real**2 + hFreqDom2.imag**2 ) / opts.duration )**0.5
scaling = opts.SNR/snr
hTimeDom1 *= scaling
hFreqDom1 *= scaling
print "generating white noise (in the freq domain)"
(freqs, wFreqDom), (times,
wTimeDom) = waveforms.whiteNoise(opts.duration,
opts.sampling_rate)
# if opts.verbose:
# print "generating white noise (in the time domain)"
# timesT, wTimeDomT = waveforms.whiteNoiseT( opts.duration, opts.sampling_rate )
# wFreqDomT = np.fft.fftshift( np.fft.fft( wTimeDomT ) )/opts.sampling_rate
#-------------------------------------------------
to = max(opts.duration - 3 * opts.tau, opts.duration / 2)
if opts.verbose:
print "generating injection with to=%.3f" % (to)
hTimeDom = waveforms.chirpSineGaussianT(times, 1.0, opts.freq, opts.freqDot,
opts.tau, to)
hFreqDom = waveforms.chirpSineGaussianF(freqs, 1.0, opts.freq, opts.freqDot,
opts.tau, to)
#-------------------------------------------------
if opts.verbose:
print "computing optimal SNR and scaling injection"
### for white-gaussian noise with unit-variance in the frequency domain
snr = (2 * np.sum(hFreqDom.real**2 + hFreqDom.imag**2) / opts.duration)**0.5
scaling = opts.SNR / snr
hTimeDom *= scaling
hFreqDom *= scaling
#-------------------------------------------------
print "generating white noise (in the freq domain)"
(freqs, wFreqDom1), (times,
wTimeDom1) = waveforms.whiteNoise(opts.duration,
opts.sampling_rate)
(freqs, wFreqDom2), (times,
wTimeDom2) = waveforms.whiteNoise(opts.duration,
opts.sampling_rate)
#-------------------------------------------------
dt = opts.D_over_c * np.cos(opts.theta * np.pi / 180)
to = opts.duration / 2
if opts.verbose:
print "generating injection with to=%.3f" % (to)
hTimeDom1 = waveforms.chirpSineGaussianT(times, 1.0, opts.freq, opts.freqDot,
opts.tau, to + dt / 2)
hFreqDom1 = waveforms.chirpSineGaussianF(freqs, 1.0, opts.freq, opts.freqDot,
opts.tau, to + dt / 2)
hTimeDom2 = waveforms.chirpSineGaussianT(times, 1.0, opts.freq, opts.freqDot,
opts.tau, to - dt / 2)
hFreqDom2 = waveforms.chirpSineGaussianF(freqs, 1.0, opts.freq, opts.freqDot,
opts.tau, to - dt / 2)
#-------------------------------------------------
if opts.verbose:
print "computing optimal SNR and scaling injection"
### for white-gaussian noise with unit-variance in the frequency domain
snr = (2 * np.sum(hFreqDom1.real**2 + hFreqDom1.imag**2 + hFreqDom2.real**2 +
hFreqDom2.imag**2) / opts.duration)**0.5
