- lal-python --> python-lal
- lalinspiral-python --> python-lalinspiral

gstlal_inspiral_pipe: fixed error that prevented coincidence threshold from being passed to gstlal_inspiral_create_prior_diststats

Change cov matrix calculation to use actual waveform amplitude/parameters instead of stationary phase approx

this fix removes the "wait time" where O(10^2s) of data was dumped until the whitener settled.

gstlal_inspiral_create_dt_dphi_snr_ratio_pdfs_dag: Add flow and fhigh arguments to covariance matrix calculation.

Allow for cov matrix computations over arbitrary frequency bands. Necessary for early warning. Defaults to 10-1024 Hz band.

feature_extractor.py: remove unused imports, utils.py: switch feature dtype from double to single precision float

same as commit for segment file input, just with invert_output reversed in mksegmentsrcgate

currently making it the same procedure as when the buffer is non-gap but not enough samples (< autocorrelation_length), like itac

dump number of events in the coinc_events table.

gstlal_inspiral_dag: rework analysis if starting at post-processing step, add parallelization to calc_likelihood_by_bin jobs, remove unused func

feature_extraction: change block_stride for whitening, high pass from 1s to 0.25s, allow for a minimum downsampling rate to improve latency at expensive of computational cost

gstlal_feature_monitor: reduce number of missing channels messages, remove close connection line causing crashes upon shutdown

this enables to do multi-detector trigger generator & coincidence analysis
by inputs of channel-name, data, template, and PSDs from multiple IFOs.
In short, this is lalapps_StringSearch + ligolw_add + lalapps_burca of old pipeline.

like the old burca

__lt__() and friends