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2.6 cw-line-veto

Function File: Fveto = computeFveto ( inFstats )

compute "F+veto" stat from input vector with columns [2F, 2F_1, 2F_2, ...] vetoed candidates are set to Fveto=-1, otherwise Fveto>=0

F+veto is defined as F+veto = { 2F if 2F > max(2F_1, 2F_2,...); -1 otherwise }

Examples

assert(computeFveto([10, 6, 5]), 10, 1e-3)

assert(computeFveto([10, 10, 5]), 10, 1e-3)

assert(computeFveto([10, 6, 11]), -1, 1e-3)
Function File: LRstat = ComputeLineRobustStat ( twoF_multi, twoF_single, Fstar0, oLGX, useAllTerms )

function to calculate line-robust statistic for multiple detectors

this is actually the log-Bayes-factor:

LRstat = log10(B_{SGL}) = log10(O_{SGL})-log10(o_{SGL})

see Eq. (36) of Keitel, Prix, Papa, Leaci, Siddiqi, PR D 89, 064023 (2014) and Eq. (55) for the semicoherent case

Notes

  1. input should be 2F, NOT F! Summed, not averaged, over segments!
  2. Fstar0 is therefore reinterpreted as "semicoherent rho", Nseg exponent must already be included from caller (compare Eq. (57), Fstar0^=ln(cstar^Nseg) )
  3. pure line-veto statistic log10(BSL) is obtained in the limit Fstar0 -> -Inf

Original formula

log10(B_SGL) = log10(e) * ( F_multi - log( (1-pL)*exp(Fstar0) + pL*<rX*exp(FX)> ) ) = log10(e) * ( F_multi - log( (1-pL)*exp(Fstar0) + (pL/Ndet)*sum(rX*exp(FX)) ) )

with

implementation here is optimized to avoid underflows ("log-sum-exp formula") should be compatible with current implementation in lalpulsar/src/LineRobustStats.c

Examples

assert(ComputeLineRobustStat(10, [6, 5], 0.1, [0.5, 0.5], false), 1.4706, 1e-3)
Function File: SFTpower_fA = ComputeSFTPowerFAFromThreshold ( SFTpower_thresh, num_SFTs )

Compute SFT power false alarm rate from a SFT power threshold.

Examples

assert(ComputeSFTPowerFAFromThreshold(1.2326, 100), 0.01, 1e-3)
Function File: SFTpower_thresh = ComputeSFTPowerThresholdFromFA ( SFTpower_fA, num_SFTs )

Compute SFT power threshold from a SFT power false alarm rate.

Examples

assert(ComputeSFTPowerThresholdFromFA(0.01, 100), 1.2326, 1e-3)
Function File: outvalue = ConvertLRStransitionScaleParams ( outname, inname, invalue, Nseg )

function to convert between various parametrisations of the line-robust statistic transition scale reference: Keitel, Prix, Papa, Leaci, Siddiq, PRD 89(6):064023 (2014)

outname/inname can be any of: "Fstar0" as defined in Eq. (38), not to be confused with the semicoherent Fstar0hat "Fstar0hat" as defined in Eq. (57) "pFAstar0" as defined in Eq. (67) "cstar" as defined in Eq. (11) "LVrho" (deprecated) as defined in footnote 1 (p4)

Nseg is optional and will be assumed 1 by default

Examples

assert(ConvertLRStransitionScaleParams("Fstar0", "LVrho", 1.23), -3.4204, 1e-3)
Function File: [ num_outliers, max_outlier, freqbins ] = CountSFTPowerOutliers ( params_psd, thresh, lalpath, debug )

function to compute the number of outliers of the SFT power statistic

Function File: [ minCoverFreq, maxCoverFreq ] = CWSignalCoveringBand ( fkdot_starttime, fkdotband_starttime, fkdot_endtime, fkdotband_endtime )

based on XLALCWSignalCoveringBand() by K. Wette, R. Prix Determines a frequency band which covers the frequency evolution of a band of CW signals between two GPS times. The calculation accounts for the spin evolution of the signals, and the maximum possible Dopper modulation due to detector motion. binary orbital motion, which is supported by XLALCWSignalCoveringBand(), is dropped here. contrary to XLALCWSignalCoveringBand, fkdot and fkdotband must be pre-extrapolated to starttime, endtime

Examples

[minCoverFreq, maxCoverFreq] = CWSignalCoveringBand([100, -1e-8], [1e-2, 1e-11], [99, -1e-8], [1e-2, 1e-11]);
assert([minCoverFreq, maxCoverFreq], [98.990, 100.02], 1e-2)
Function File: ret = EstimateLinePriors ( varargin )

Script to estimate oLGX priors from some SFTs based on compute_lX_from_SFTs from LineVetoBstat repository, but with simpler SFTs and timestamps handling this is different from TuneAdaptiveLVPriors which is more EatH-centric, assuming a given run setup command-line parameters can be taken from parseOptions call below example call: octapps_run EstimateLinePriors –SFTs=h1*

Function File: [ lX, freqmin, freqmax, freqbins, num_outliers, max_outlier ] = EstimateLinePriorsFromNormSFT ( psdfiles, thresh, LVlmin, LVlmax )

function to estimate line priors from normalized SFT power values in files computed by lalapps_ComputePSD psdfiles must be a cell array of existing files of length numDet thresh must be a numDet*T matrix, where T is an arbitrary number of thresh values per IFO, so that lX will be returned as a numDet*T matrix also

Function File: [ fkdot_epoch1, fkdotband_epoch1 ] = ExtrapolatePulsarSpinRange ( epoch0, epoch1, fkdot_epoch0, fkdotband_epoch0, numSpins )

function to translate spin-values \f$\f^{(l)}\f$ and bands from epoch0 to epoch1 based on LALSuite programs/functions HierarchSearchGCT and LALExtrapolatePulsarSpinRange

Note

different index conventions between lalapps and octave - (k) here corresponds to [k-1] in LALExtrapolatePulsarSpinRange, i.e. fkdot(1)=fkdot[0]=freq, fkdot(2)=fkdot(1)=f1dot, ...

Examples

assert(ExtrapolatePulsarSpinRange(800000000, 900000000, [100, -1e-8], [1e-2, 1e-8], 1), [99, 1e-8], 1e-3)
Function File: ret = GetNormSFTPowerFiles ( varargin )

function to produce files of normalized SFT power over a large set of frequency bands (input sft files) for a single IFO

command-line parameters can be taken from parseOptions call below

Example

octapps_run GetNormSFTPowerFiles --sftdir=sfts --sft_filenamebit=S6GC1 --IFO=h1 --freqmin=50.5
Function File: num_SFTs = GetNumSFTsFromFile ( sftfile )

safety measure to work around lalapps_dumpSFT bug: check if sftfile is a pattern matching several files, and if it is, just use the first one.

Function File: [ sfts, firstsft, sfts_cell ] = get_EatH_sft_paths ( sftdir, filenamebit, sft_width, sftstartfreq, num_sfts_to_load, IFO )

function to get the full SFT paths (assuming Atlas-like directory structure) and cat them into argument strings for, e.g., lalapps_ComputePSD and also return first single SFT file path and a cell array of all SFT paths

Function File: [ gct_freq_min, gct_freq_band, gct_phys_freq_min, gct_phys_freq_band ] = PredictGCTFreqband ( freq, freqband, dFreq, f1dot, f1dotband, df1dot, f2dot, f2dotband, df2dot, starttime, duration, reftime, Tsft, blocksRngMed, Dterms )

function to predict the frequency band required by a HSGCT search based on code snippets from LALSuite program HierarchSearchGCT and on XLALCreateFstatInput() from lalpulsar for older freqband convention (e.g. S6Bucket, S6LV1 runs), see PredictGCTFreqbandLegacy.m

Note

this is for laldemod only, resampling is somewhat different

Examples

[gct_freq_min, gct_freq_band, gct_phys_freq_min, gct_phys_freq_band] = PredictGCTFreqband(100, 0.1, 1e-7, -1e-8, 1e-8, 1e-11, 0, 0, 0, 800000000, 23*3600, 800000000, 1800, 101, 8);
assert([gct_freq_min, gct_freq_band, gct_phys_freq_min, gct_phys_freq_band], [99.956, 0.18897, 99.984, 0.13175], 1e-2)
Function File: ret = TuneAdaptiveLVPriors ( varargin )

function to count outliers in SFT power statistic over a large set of frequency bands (input sft files) and derive LV priors from that command-line parameters can be taken from parseOptions call below

Example

octapps_run TuneAdaptiveLVPriors --sftdir=sfts --sft_filenamebit=S6GC1 --freqmin=50 --freqmax=50.5

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