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This is the v.1.5.0 release of PyFstat, a python package for gravitational wave analysis with the F-statistic, dated 30/07/2020. This release requires at least python 3.6. From the changelog since the previous version (v1.4.2): new default coverage band behaviour for all search classes: estimate from search ranges (GridSearch) or prior (MCMCSearch) unless minCoverFreq, maxCoverFreq set negative values can be used to reproduce old default of setting from SFT width explicit option estimate_covering_band deprecated semicoherent searches: sped up by only calling ComputeTransientFstatMap once per point BSGL now computed from summed F-stats, not for each segment per-segment results now stored in attribute twoF_per_segment instead of det_stat_per_segment MCMC searches: save twoF for each sample to .dat file Writer: options minStartTime, maxStartTime deprecated always use tstart, duration for actual data range and use transientStartTime, transientTau for transients transient-on-GPU output file writing fix examples: all output now goes to a directory "PyFstat_example_data" added mcmc_vs_grid_simple_example
See record https://doi.org/10.5281/zenodo.1243930 for previous versions of PyFstat up to v1.4.1.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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