cbc_template_fir module¶
The python module to implement SVD decomposed FIR filtering
Review Status
STATUS: reviewed with actions
Names |
Hash |
Date |
|---|---|---|
Florent, Sathya, Duncan Me, Jolien, Kipp, Chad |
7536db9d496be9a014559f4e273e1e856047bf71 |
2014-04-30 |
Florent, Surabhi, Tjonnie, Kent, Jolien, Kipp, Chad |
d84a8446a056ce92625b042148c2d9ef9cd8bb0d |
2015-05-12 |
Action items
Consider changing the order of interpolation and smoothing the PSD
move sigma squared calculation somewhere and get them updated dynamically
possibly use ROM stuff, possibly use low-order polynomial approx computed on the fly from the template as it’s generated
remove lefttukeywindow()
use template_bank_row.coa_phase == 0. in SimInspiralFD() call, make sure itac adjusts the phase it assigns to triggers from the template coa_phase
change “assumes fhigh” to “asserts fhigh”
move assert epoch_time into condition_imr_waveform(), should be assert -len(data) <= epoch_time * sample_rate < 0
- cbc_template_fir.compute_autocorrelation_mask(autocorrelation)[source]¶
Given an autocorrelation time series, estimate the optimal autocorrelation length to use and return a matrix which masks out the unwanted elements. FIXME TODO for now just returns ones
- cbc_template_fir.condition_ear_warn_template(approximant, data, epoch_time, sample_rate_max, max_shift_time)[source]¶
- cbc_template_fir.condition_imr_template(approximant, data, epoch_time, sample_rate_max, max_ringtime)[source]¶
- cbc_template_fir.generate_template(template_bank_row, approximant, sample_rate, duration, f_low, f_high, amporder=0, order=7, fwdplan=None, fworkspace=None)[source]¶
Generate a single frequency-domain template, which 1. is band-limited between f_low and f_high, 2. has an IFFT which is duration seconds long and 3. has an IFFT which is sampled at sample_rate Hz
- cbc_template_fir.generate_templates(template_table, approximant, psd, f_low, time_slices, autocorrelation_length=None, fhigh=None, time_reverse=False, verbose=False)[source]¶