From b0424e38b39e17246955817254798d1254bee1eb Mon Sep 17 00:00:00 2001
From: Gregory Ashton <gregory.ashton@ligo.org>
Date: Fri, 22 Dec 2017 15:24:47 +0100
Subject: [PATCH] Create TransientGridSearch to provide transient grid searches
Previously, this functionality was part of GridSearch, this splits this
into a separate subclass to ease future development.
---
.../short_transient_search_gridded.py | 4 +-
pyfstat/__init__.py | 2 +-
pyfstat/grid_based_searches.py | 134 ++++++++++++++----
3 files changed, 107 insertions(+), 33 deletions(-)
diff --git a/examples/transient_examples/short_transient_search_gridded.py b/examples/transient_examples/short_transient_search_gridded.py
index 64e6423..8fc801f 100644
--- a/examples/transient_examples/short_transient_search_gridded.py
+++ b/examples/transient_examples/short_transient_search_gridded.py
@@ -30,7 +30,7 @@ Alphas = [Alpha]
Deltas = [Delta]
print('Standard CW search:')
-search1 = pyfstat.GridSearch(
+search1 = pyfstat.TransientGridSearch(
label='CW', outdir=datadir,
sftfilepattern=os.path.join(datadir,'*simulated_transient_signal*sft'),
F0s=F0s, F1s=F1s, F2s=F2s, Alphas=Alphas, Deltas=Deltas, tref=tref,
@@ -44,7 +44,7 @@ search1.plot_1D(xkey='F0',
xlabel='freq [Hz]', ylabel='$2\mathcal{F}$')
print('with t0,tau bands:')
-search2 = pyfstat.GridSearch(
+search2 = pyfstat.TransientGridSearch(
label='tCW', outdir=datadir,
sftfilepattern=os.path.join(datadir,'*simulated_transient_signal*sft'),
F0s=F0s, F1s=F1s, F2s=F2s, Alphas=Alphas, Deltas=Deltas, tref=tref,
diff --git a/pyfstat/__init__.py b/pyfstat/__init__.py
index 5c44708..3516c4a 100644
--- a/pyfstat/__init__.py
+++ b/pyfstat/__init__.py
@@ -3,4 +3,4 @@ from __future__ import division as _division
from .core import BaseSearchClass, ComputeFstat, SemiCoherentSearch, SemiCoherentGlitchSearch
from .make_sfts import Writer, GlitchWriter, FrequencyModulatedArtifactWriter, FrequencyAmplitudeModulatedArtifactWriter
from .mcmc_based_searches import MCMCSearch, MCMCGlitchSearch, MCMCSemiCoherentSearch, MCMCFollowUpSearch, MCMCTransientSearch
-from .grid_based_searches import GridSearch, GridUniformPriorSearch, GridGlitchSearch, FrequencySlidingWindow, DMoff_NO_SPIN, SliceGridSearch
+from .grid_based_searches import GridSearch, GridUniformPriorSearch, GridGlitchSearch, FrequencySlidingWindow, DMoff_NO_SPIN, SliceGridSearch, TransientGridSearch
diff --git a/pyfstat/grid_based_searches.py b/pyfstat/grid_based_searches.py
index f9e2699..233c60c 100644
--- a/pyfstat/grid_based_searches.py
+++ b/pyfstat/grid_based_searches.py
@@ -34,9 +34,7 @@ class GridSearch(BaseSearchClass):
Deltas, tref=None, minStartTime=None, maxStartTime=None,
nsegs=1, BSGL=False, minCoverFreq=None, maxCoverFreq=None,
detectors=None, SSBprec=None, injectSources=None,
- input_arrays=False, assumeSqrtSX=None,
- transientWindowType=None, t0Band=None, tauBand=None,
- outputTransientFstatMap=False):
+ input_arrays=False, assumeSqrtSX=None):
"""
Parameters
----------
@@ -53,19 +51,6 @@ class GridSearch(BaseSearchClass):
GPS seconds of the reference time, start time and end time
input_arrays: bool
if true, use the F0s, F1s, etc as is
- transientWindowType: str
- If 'rect' or 'exp', compute atoms so that a transient (t0,tau) map
- can later be computed. ('none' instead of None explicitly calls
- the transient-window function, but with the full range, for
- debugging). Currently only supported for nsegs=1.
- t0Band, tauBand: int
- if >0, search t0 in (minStartTime,minStartTime+t0Band)
- and tau in (2*Tsft,2*Tsft+tauBand).
- if =0, only compute CW Fstat with t0=minStartTime,
- tau=maxStartTime-minStartTime.
- outputTransientFstatMap: bool
- if true, write output files for (t0,tau) Fstat maps
- (one file for each doppler grid point!)
For all other parameters, see `pyfstat.ComputeFStat` for details
"""
@@ -85,8 +70,6 @@ class GridSearch(BaseSearchClass):
tref=self.tref, sftfilepattern=self.sftfilepattern,
minCoverFreq=self.minCoverFreq, maxCoverFreq=self.maxCoverFreq,
detectors=self.detectors,
- transientWindowType=self.transientWindowType,
- t0Band=self.t0Band, tauBand=self.tauBand,
minStartTime=self.minStartTime, maxStartTime=self.maxStartTime,
BSGL=self.BSGL, SSBprec=self.SSBprec,
injectSources=self.injectSources,
@@ -170,19 +153,7 @@ class GridSearch(BaseSearchClass):
data = []
for vals in tqdm(self.input_data):
detstat = self.search.get_det_stat(*vals)
- windowRange = getattr(self.search, 'windowRange', None)
- FstatMap = getattr(self.search, 'FstatMap', None)
thisCand = list(vals) + [detstat]
- if getattr(self, 'transientWindowType', None):
- if self.outputTransientFstatMap:
- tCWfile = os.path.splitext(self.out_file)[0]+'_tCW_%.16f_%.16f_%.16f_%.16g_%.16g.dat' % (vals[2],vals[5],vals[6],vals[3],vals[4]) # freq alpha delta f1dot f2dot
- fo = lal.FileOpen(tCWfile, 'w')
- lalpulsar.write_transientFstatMap_to_fp ( fo, FstatMap, windowRange, None )
- del fo # instead of lal.FileClose() which is not SWIG-exported
- Fmn = FstatMap.F_mn.data
- maxidx = np.unravel_index(Fmn.argmax(), Fmn.shape)
- thisCand += [windowRange.t0+maxidx[0]*windowRange.dt0,
- windowRange.tau+maxidx[1]*windowRange.dtau]
data.append(thisCand)
data = np.array(data, dtype=np.float)
@@ -372,6 +343,109 @@ class GridSearch(BaseSearchClass):
self.outdir, self.label, dets, type(self).__name__)
+class TransientGridSearch(GridSearch):
+ """ Gridded transient-continous search using ComputeFstat """
+
+ @helper_functions.initializer
+ def __init__(self, label, outdir, sftfilepattern, F0s, F1s, F2s, Alphas,
+ Deltas, tref=None, minStartTime=None, maxStartTime=None,
+ BSGL=False, minCoverFreq=None, maxCoverFreq=None,
+ detectors=None, SSBprec=None, injectSources=None,
+ input_arrays=False, assumeSqrtSX=None,
+ transientWindowType=None, t0Band=None, tauBand=None,
+ outputTransientFstatMap=False):
+ """
+ Parameters
+ ----------
+ label, outdir: str
+ A label and directory to read/write data from/to
+ sftfilepattern: str
+ Pattern to match SFTs using wildcards (*?) and ranges [0-9];
+ mutiple patterns can be given separated by colons.
+ F0s, F1s, F2s, delta_F0s, delta_F1s, tglitchs, Alphas, Deltas: tuple
+ Length 3 tuple describing the grid for each parameter, e.g
+ [F0min, F0max, dF0], for a fixed value simply give [F0]. Unless
+ input_arrays == True, then these are the values to search at.
+ tref, minStartTime, maxStartTime: int
+ GPS seconds of the reference time, start time and end time
+ input_arrays: bool
+ if true, use the F0s, F1s, etc as is
+ transientWindowType: str
+ If 'rect' or 'exp', compute atoms so that a transient (t0,tau) map
+ can later be computed. ('none' instead of None explicitly calls
+ the transient-window function, but with the full range, for
+ debugging). Currently only supported for nsegs=1.
+ t0Band, tauBand: int
+ if >0, search t0 in (minStartTime,minStartTime+t0Band)
+ and tau in (2*Tsft,2*Tsft+tauBand).
+ if =0, only compute CW Fstat with t0=minStartTime,
+ tau=maxStartTime-minStartTime.
+ outputTransientFstatMap: bool
+ if true, write output files for (t0,tau) Fstat maps
+ (one file for each doppler grid point!)
+
+ For all other parameters, see `pyfstat.ComputeFStat` for details
+ """
+
+ self.nsegs = 1
+ if os.path.isdir(outdir) is False:
+ os.mkdir(outdir)
+ self.set_out_file()
+ self.keys = ['_', '_', 'F0', 'F1', 'F2', 'Alpha', 'Delta']
+ self.search_keys = [x+'s' for x in self.keys[2:]]
+ for k in self.search_keys:
+ setattr(self, k, np.atleast_1d(getattr(self, k)))
+
+ def inititate_search_object(self):
+ logging.info('Setting up search object')
+ self.search = ComputeFstat(
+ tref=self.tref, sftfilepattern=self.sftfilepattern,
+ minCoverFreq=self.minCoverFreq, maxCoverFreq=self.maxCoverFreq,
+ detectors=self.detectors,
+ transientWindowType=self.transientWindowType,
+ t0Band=self.t0Band, tauBand=self.tauBand,
+ minStartTime=self.minStartTime, maxStartTime=self.maxStartTime,
+ BSGL=self.BSGL, SSBprec=self.SSBprec,
+ injectSources=self.injectSources,
+ assumeSqrtSX=self.assumeSqrtSX)
+ self.search.get_det_stat = self.search.get_fullycoherent_twoF
+
+ def run(self, return_data=False):
+ self.get_input_data_array()
+ old_data = self.check_old_data_is_okay_to_use()
+ if old_data is not False:
+ self.data = old_data
+ return
+
+ if hasattr(self, 'search') is False:
+ self.inititate_search_object()
+
+ data = []
+ for vals in tqdm(self.input_data):
+ detstat = self.search.get_det_stat(*vals)
+ windowRange = getattr(self.search, 'windowRange', None)
+ FstatMap = getattr(self.search, 'FstatMap', None)
+ thisCand = list(vals) + [detstat]
+ if getattr(self, 'transientWindowType', None):
+ if self.outputTransientFstatMap:
+ tCWfile = os.path.splitext(self.out_file)[0]+'_tCW_%.16f_%.16f_%.16f_%.16g_%.16g.dat' % (vals[2],vals[5],vals[6],vals[3],vals[4]) # freq alpha delta f1dot f2dot
+ fo = lal.FileOpen(tCWfile, 'w')
+ lalpulsar.write_transientFstatMap_to_fp ( fo, FstatMap, windowRange, None )
+ del fo # instead of lal.FileClose() which is not SWIG-exported
+ Fmn = FstatMap.F_mn.data
+ maxidx = np.unravel_index(Fmn.argmax(), Fmn.shape)
+ thisCand += [windowRange.t0+maxidx[0]*windowRange.dt0,
+ windowRange.tau+maxidx[1]*windowRange.dtau]
+ data.append(thisCand)
+
+ data = np.array(data, dtype=np.float)
+ if return_data:
+ return data
+ else:
+ self.save_array_to_disk(data)
+ self.data = data
+
+
class SliceGridSearch(GridSearch):
""" Slice gridded search using ComputeFstat """
@helper_functions.initializer
--
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