streamthinca module¶
- class streamthinca.StreamThinca(xmldoc, process_id, delta_t, min_instruments=2, sngls_snr_threshold=None, background_collector_type='normal', latency_tolerance=0.0)[source]¶
Bases:
object- pull(rankingstat, fapfar=None, zerolag_rankingstatpdf=None, coinc_sieve=None, flush=False, cluster=False, cap_singles=False, FAR_trialsfactor=1.0, template_id_time_map=None)[source]¶
- push(instrument, events, t_complete)[source]¶
Push new triggers into the coinc engine. Returns True if the coinc engine’s internal state has changed in a way that might enable new candidates to be constructed, False if not. If latency_tolerance is not 0, then triggers are allowed to accumulate in the internal queues until the oldest is latency_tolerance older than t_complete before this method reports that candidates can be extracted from the graph. This concentrates the time spent in the Python coincidence code into smaller intervals, which allows the gstreamer code to achieve greater parallelism, which achieves more efficient CPU use at the expense of longer latencies.