core.py 46.3 KB
Newer Older
Gregory Ashton's avatar
Gregory Ashton committed
1
2
3
4
5
6
7
""" The core tools used in pyfstat """
import os
import logging
import copy
import glob

import numpy as np
8
9
10
11
12
13
14
15
16
17
18

# workaround for matplotlib on X-less remote logins
if os.environ.has_key('DISPLAY'):
    import matplotlib.pyplot as plt
else:
    logging.info('No $DISPLAY environment variable found, \
                  so importing matplotlib.pyplot with non-interactive "Agg" backend.')
    import matplotlib
    matplotlib.use('Agg')
    import matplotlib.pyplot as plt

Gregory Ashton's avatar
Gregory Ashton committed
19
20
21
22
23
24
25
import scipy.special
import scipy.optimize
import lal
import lalpulsar

import helper_functions
helper_functions.set_up_matplotlib_defaults()
26
args, tqdm = helper_functions.set_up_command_line_arguments()
Gregory Ashton's avatar
Gregory Ashton committed
27
earth_ephem, sun_ephem = helper_functions.set_up_ephemeris_configuration()
28
detector_colors = {'h1': 'C0', 'l1': 'C1'}
Gregory Ashton's avatar
Gregory Ashton committed
29
30


31
32
33
34
35
36
37
38
39
def read_par(label=None, outdir=None, filename=None, suffix='par'):
    """ Read in a .par file, returns a dictionary of the values

    Note, can also read in .loudest files
    """
    if filename is None:
        filename = '{}/{}.{}'.format(outdir, label, suffix)
    if os.path.isfile(filename) is False:
        raise ValueError("No file ({}) found".format(filename))
Gregory Ashton's avatar
Gregory Ashton committed
40
41
    d = {}
    with open(filename, 'r') as f:
42
        d = get_dictionary_from_lines(f)
Gregory Ashton's avatar
Gregory Ashton committed
43
44
45
    return d


46
47
48
49
50
51
52
53
54
55
56
57
58
59
def get_dictionary_from_lines(lines):
    d = {}
    for line in lines:
        if line[0] not in ['%', '#'] and len(line.split('=')) == 2:
            try:
                key, val = line.rstrip('\n').split('=')
                key = key.strip()
                d[key] = np.float64(eval(val.rstrip('; ')))
            except SyntaxError:
                pass
    return d


def predict_fstat(h0, cosi, psi, Alpha, Delta, Freq, sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
60
61
                  minStartTime, maxStartTime, IFO=None, assumeSqrtSX=None,
                  **kwargs):
62
    """ Wrapper to lalapps_PredictFstat """
63
64
65
66
67
68
69
70
71
72
    cl_pfs = []
    cl_pfs.append("lalapps_PredictFstat")
    cl_pfs.append("--h0={}".format(h0))
    cl_pfs.append("--cosi={}".format(cosi))
    cl_pfs.append("--psi={}".format(psi))
    cl_pfs.append("--Alpha={}".format(Alpha))
    cl_pfs.append("--Delta={}".format(Delta))
    cl_pfs.append("--Freq={}".format(Freq))

    cl_pfs.append("--DataFiles='{}'".format(sftfilepattern))
73
    if assumeSqrtSX:
74
        cl_pfs.append("--assumeSqrtSX={}".format(assumeSqrtSX))
75
    if IFO:
76
        cl_pfs.append("--IFO={}".format(IFO))
77

78
79
80
    cl_pfs.append("--minStartTime={}".format(int(minStartTime)))
    cl_pfs.append("--maxStartTime={}".format(int(maxStartTime)))
    cl_pfs.append("--outputFstat=/tmp/fs")
81

82
83
    cl_pfs = " ".join(cl_pfs)
    helper_functions.run_commandline(cl_pfs)
84
85
86
87
    d = read_par(filename='/tmp/fs')
    return float(d['twoF_expected']), float(d['twoF_sigma'])


Gregory Ashton's avatar
Gregory Ashton committed
88
89
90
91
92
93
class BaseSearchClass(object):
    """ The base search class, provides general functions """

    earth_ephem_default = earth_ephem
    sun_ephem_default = sun_ephem

94
    def _add_log_file(self):
Gregory Ashton's avatar
Gregory Ashton committed
95
96
97
98
99
100
101
102
103
        """ Log output to a file, requires class to have outdir and label """
        logfilename = '{}/{}.log'.format(self.outdir, self.label)
        fh = logging.FileHandler(logfilename)
        fh.setLevel(logging.INFO)
        fh.setFormatter(logging.Formatter(
            '%(asctime)s %(levelname)-8s: %(message)s',
            datefmt='%y-%m-%d %H:%M'))
        logging.getLogger().addHandler(fh)

104
    def _shift_matrix(self, n, dT):
Gregory Ashton's avatar
Gregory Ashton committed
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
        """ Generate the shift matrix

        Parameters
        ----------
        n: int
            The dimension of the shift-matrix to generate
        dT: float
            The time delta of the shift matrix

        Returns
        -------
        m: array (n, n)
            The shift matrix
        """

        m = np.zeros((n, n))
        factorial = np.math.factorial
        for i in range(n):
            for j in range(n):
                if i == j:
                    m[i, j] = 1.0
                elif i > j:
                    m[i, j] = 0.0
                else:
                    if i == 0:
                        m[i, j] = 2*np.pi*float(dT)**(j-i) / factorial(j-i)
                    else:
                        m[i, j] = float(dT)**(j-i) / factorial(j-i)
        return m

135
    def _shift_coefficients(self, theta, dT):
Gregory Ashton's avatar
Gregory Ashton committed
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
        """ Shift a set of coefficients by dT

        Parameters
        ----------
        theta: array-like, shape (n,)
            vector of the expansion coefficients to transform starting from the
            lowest degree e.g [phi, F0, F1,...].
        dT: float
            difference between the two reference times as tref_new - tref_old.

        Returns
        -------
        theta_new: array-like shape (n,)
            vector of the coefficients as evaluate as the new reference time.
        """

        n = len(theta)
153
        m = self._shift_matrix(n, dT)
Gregory Ashton's avatar
Gregory Ashton committed
154
155
        return np.dot(m, theta)

156
    def _calculate_thetas(self, theta, delta_thetas, tbounds, theta0_idx=0):
Gregory Ashton's avatar
Gregory Ashton committed
157
158
159
160
        """ Calculates the set of coefficients for the post-glitch signal """
        thetas = [theta]
        for i, dt in enumerate(delta_thetas):
            if i < theta0_idx:
161
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
162
163
                    thetas[0], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch - dt
164
                thetas.insert(0, self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
165
166
167
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))

            elif i >= theta0_idx:
168
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
169
170
                    thetas[i], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch + dt
171
                thetas.append(self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
172
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))
173
        self.thetas_at_tref = thetas
Gregory Ashton's avatar
Gregory Ashton committed
174
175
        return thetas

176
    def _get_list_of_matching_sfts(self):
177
178
179
180
        # first make sure we have a list of paths, to avoid
        # list comprehension trying to glob each single character
        sftfilepathlist = np.atleast_1d(self.sftfilepath)
        matches = [glob.glob(p) for p in sftfilepathlist]
181
        matches = [item for sublist in matches for item in sublist]
182
183
184
185
186
187
        if len(matches) > 0:
            return matches
        else:
            raise IOError('No sfts found matching {}'.format(
                self.sftfilepath))

Gregory Ashton's avatar
Gregory Ashton committed
188
189
190
191
192
193
194
195
196
197

class ComputeFstat(object):
    """ Base class providing interface to `lalpulsar.ComputeFstat` """

    earth_ephem_default = earth_ephem
    sun_ephem_default = sun_ephem

    @helper_functions.initializer
    def __init__(self, tref, sftfilepath=None, minStartTime=None,
                 maxStartTime=None, binary=False, transient=True, BSGL=False,
198
                 detectors=None, minCoverFreq=None, maxCoverFreq=None,
199
                 earth_ephem=None, sun_ephem=None, injectSources=None,
200
                 injectSqrtSX=None, assumeSqrtSX=None, SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
        """
        Parameters
        ----------
        tref: int
            GPS seconds of the reference time.
        sftfilepath: str
            File patern to match SFTs
        minStartTime, maxStartTime: float GPStime
            Only use SFTs with timestemps starting from (including, excluding)
            this epoch
        binary: bool
            If true, search of binary parameters.
        transient: bool
            If true, allow for the Fstat to be computed over a transient range.
        BSGL: bool
            If true, compute the BSGL rather than the twoF value.
217
        detectors: str
Gregory Ashton's avatar
Gregory Ashton committed
218
            Two character reference to the data to use, specify None for no
219
            contraint. If multiple-separate by comma.
Gregory Ashton's avatar
Gregory Ashton committed
220
221
222
223
224
225
226
227
        minCoverFreq, maxCoverFreq: float
            The min and max cover frequency passed to CreateFstatInput, if
            either is None the range of frequencies in the SFT less 1Hz is
            used.
        earth_ephem, sun_ephem: str
            Paths of the two files containing positions of Earth and Sun,
            respectively at evenly spaced times, as passed to CreateFstatInput.
            If None defaults defined in BaseSearchClass will be used.
228
229
230
231
232
        injectSources: dict or str
            Either a dictionary of the values to inject, or a string pointing
            to the .cff file to inject
        injectSqrtSX:
            Not yet implemented
233
234
235
236
        assumeSqrtSX: float
            Don't estimate noise-floors but assume (stationary) per-IFO
            sqrt{SX} (if single value: use for all IFOs). If signal only,
            set sqrtSX=1
237
238
239
        SSBprec: int
            Flag to set the SSB calculation: 0=Newtonian, 1=relativistic,
            2=relativisitic optimised, 3=DMoff, 4=NO_SPIN
Gregory Ashton's avatar
Gregory Ashton committed
240
241
242
243
244
245
246
247
248
249
250
251
252

        """

        if earth_ephem is None:
            self.earth_ephem = self.earth_ephem_default
        if sun_ephem is None:
            self.sun_ephem = self.sun_ephem_default

        self.init_computefstatistic_single_point()

    def get_SFTCatalog(self):
        if hasattr(self, 'SFTCatalog'):
            return
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
        if self.sftfilepath is None:
            for k in ['minStartTime', 'maxStartTime', 'detectors']:
                if getattr(self, k) is None:
                    raise ValueError('You must provide "{}" to injectSources'
                                     .format(k))
            C1 = getattr(self, 'injectSources', None) is None
            C2 = getattr(self, 'injectSqrtSX', None) is None
            if C1 and C2:
                raise ValueError('You must specify either one of injectSources'
                                 ' or injectSqrtSX')
            SFTCatalog = lalpulsar.SFTCatalog()
            Tsft = 1800
            Toverlap = 0
            Tspan = self.maxStartTime - self.minStartTime
            detNames = lal.CreateStringVector(
                *[d for d in self.detectors.split(',')])
            multiTimestamps = lalpulsar.MakeMultiTimestamps(
                self.minStartTime, Tspan, Tsft, Toverlap, detNames.length)
            SFTCatalog = lalpulsar.MultiAddToFakeSFTCatalog(
                SFTCatalog, detNames, multiTimestamps)
            return SFTCatalog

Gregory Ashton's avatar
Gregory Ashton committed
275
276
        logging.info('Initialising SFTCatalog')
        constraints = lalpulsar.SFTConstraints()
277
        if self.detectors:
278
279
280
281
            if ',' in self.detectors:
                logging.info('Using all detector data')
            else:
                constraints.detector = self.detectors
Gregory Ashton's avatar
Gregory Ashton committed
282
283
284
285
286
287
288
289
290
291
292
        if self.minStartTime:
            constraints.minStartTime = lal.LIGOTimeGPS(self.minStartTime)
        if self.maxStartTime:
            constraints.maxStartTime = lal.LIGOTimeGPS(self.maxStartTime)

        logging.info('Loading data matching pattern {}'.format(
                     self.sftfilepath))
        SFTCatalog = lalpulsar.SFTdataFind(self.sftfilepath, constraints)
        detector_names = list(set([d.header.name for d in SFTCatalog.data]))
        self.detector_names = detector_names
        SFT_timestamps = [d.header.epoch for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
293
        self.SFT_timestamps = [float(s) for s in SFT_timestamps]
294
295
        if len(SFT_timestamps) == 0:
            raise ValueError('Failed to load any data')
Gregory Ashton's avatar
Gregory Ashton committed
296
297
298
299
300
        if args.quite is False and args.no_interactive is False:
            try:
                from bashplotlib.histogram import plot_hist
                print('Data timestamps histogram:')
                plot_hist(SFT_timestamps, height=5, bincount=50)
Gregory Ashton's avatar
Gregory Ashton committed
301
            except ImportError:
Gregory Ashton's avatar
Gregory Ashton committed
302
303
304
305
306
                pass
        if len(detector_names) == 0:
            raise ValueError('No data loaded.')
        logging.info('Loaded {} data files from detectors {}'.format(
            len(SFT_timestamps), detector_names))
307
308
309
310
311
312
        cl_tconv1 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[0]))
        output    = helper_functions.run_commandline(cl_tconv1)
        tconvert1 = output.rstrip('\n')
        cl_tconv2 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[-1]))
        output    = helper_functions.run_commandline(cl_tconv2)
        tconvert2 = output.rstrip('\n')
Gregory Ashton's avatar
Gregory Ashton committed
313
314
        logging.info('Data spans from {} ({}) to {} ({})'.format(
            int(SFT_timestamps[0]),
315
            tconvert1,
Gregory Ashton's avatar
Gregory Ashton committed
316
            int(SFT_timestamps[-1]),
317
            tconvert2))
318
        return SFTCatalog
Gregory Ashton's avatar
Gregory Ashton committed
319
320
321
322

    def init_computefstatistic_single_point(self):
        """ Initilisation step of run_computefstatistic for a single point """

323
        SFTCatalog = self.get_SFTCatalog()
Gregory Ashton's avatar
Gregory Ashton committed
324
325
326
327
328
329
330
331
332
333
334
335
336

        logging.info('Initialising ephems')
        ephems = lalpulsar.InitBarycenter(self.earth_ephem, self.sun_ephem)

        logging.info('Initialising FstatInput')
        dFreq = 0
        if self.transient:
            self.whatToCompute = lalpulsar.FSTATQ_ATOMS_PER_DET
        else:
            self.whatToCompute = lalpulsar.FSTATQ_2F

        FstatOAs = lalpulsar.FstatOptionalArgs()
        FstatOAs.randSeed = lalpulsar.FstatOptionalArgsDefaults.randSeed
337
338
339
340
341
        if self.SSBprec:
            logging.info('Using SSBprec={}'.format(self.SSBprec))
            FstatOAs.SSBprec = self.SSBprec
        else:
            FstatOAs.SSBprec = lalpulsar.FstatOptionalArgsDefaults.SSBprec
Gregory Ashton's avatar
Gregory Ashton committed
342
343
344
        FstatOAs.Dterms = lalpulsar.FstatOptionalArgsDefaults.Dterms
        FstatOAs.runningMedianWindow = lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow
        FstatOAs.FstatMethod = lalpulsar.FstatOptionalArgsDefaults.FstatMethod
345
346
347
348
349
350
351
352
        if self.assumeSqrtSX is None:
            FstatOAs.assumeSqrtSX = lalpulsar.FstatOptionalArgsDefaults.assumeSqrtSX
        else:
            mnf = lalpulsar.MultiNoiseFloor()
            assumeSqrtSX = np.atleast_1d(self.assumeSqrtSX)
            mnf.sqrtSn[:len(assumeSqrtSX)] = assumeSqrtSX
            mnf.length = len(assumeSqrtSX)
            FstatOAs.assumeSqrtSX = mnf
Gregory Ashton's avatar
Gregory Ashton committed
353
354
355
        FstatOAs.prevInput = lalpulsar.FstatOptionalArgsDefaults.prevInput
        FstatOAs.collectTiming = lalpulsar.FstatOptionalArgsDefaults.collectTiming

Gregory Ashton's avatar
Gregory Ashton committed
356
        if hasattr(self, 'injectSources') and type(self.injectSources) == dict:
Gregory Ashton's avatar
Gregory Ashton committed
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
            logging.info('Injecting source with params: {}'.format(
                self.injectSources))
            PPV = lalpulsar.CreatePulsarParamsVector(1)
            PP = PPV.data[0]
            PP.Amp.h0 = self.injectSources['h0']
            PP.Amp.cosi = self.injectSources['cosi']
            PP.Amp.phi0 = self.injectSources['phi0']
            PP.Amp.psi = self.injectSources['psi']
            PP.Doppler.Alpha = self.injectSources['Alpha']
            PP.Doppler.Delta = self.injectSources['Delta']
            PP.Doppler.fkdot = np.array(self.injectSources['fkdot'])
            PP.Doppler.refTime = self.tref
            if 't0' not in self.injectSources:
                PP.Transient.type = lalpulsar.TRANSIENT_NONE
            FstatOAs.injectSources = PPV
Gregory Ashton's avatar
Gregory Ashton committed
372
        elif hasattr(self, 'injectSources') and type(self.injectSources) == str:
373
374
375
376
            logging.info('Injecting source from param file: {}'.format(
                self.injectSources))
            PPV = lalpulsar.PulsarParamsFromFile(self.injectSources, self.tref)
            FstatOAs.injectSources = PPV
Gregory Ashton's avatar
Gregory Ashton committed
377
378
        else:
            FstatOAs.injectSources = lalpulsar.FstatOptionalArgsDefaults.injectSources
379
380
381
382
        if hasattr(self, 'injectSqrtSX') and self.injectSqrtSX is not None:
            raise ValueError('injectSqrtSX not implemented')
        else:
            FstatOAs.InjectSqrtSX = lalpulsar.FstatOptionalArgsDefaults.injectSqrtSX
Gregory Ashton's avatar
Gregory Ashton committed
383
        if self.minCoverFreq is None or self.maxCoverFreq is None:
384
            fAs = [d.header.f0 for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
385
            fBs = [d.header.f0 + (d.numBins-1)*d.header.deltaF
386
                   for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
387
388
389
390
391
392
            self.minCoverFreq = np.min(fAs) + 0.5
            self.maxCoverFreq = np.max(fBs) - 0.5
            logging.info('Min/max cover freqs not provided, using '
                         '{} and {}, est. from SFTs'.format(
                             self.minCoverFreq, self.maxCoverFreq))

393
        self.FstatInput = lalpulsar.CreateFstatInput(SFTCatalog,
Gregory Ashton's avatar
Gregory Ashton committed
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
                                                     self.minCoverFreq,
                                                     self.maxCoverFreq,
                                                     dFreq,
                                                     ephems,
                                                     FstatOAs
                                                     )

        logging.info('Initialising PulsarDoplerParams')
        PulsarDopplerParams = lalpulsar.PulsarDopplerParams()
        PulsarDopplerParams.refTime = self.tref
        PulsarDopplerParams.Alpha = 1
        PulsarDopplerParams.Delta = 1
        PulsarDopplerParams.fkdot = np.array([0, 0, 0, 0, 0, 0, 0])
        self.PulsarDopplerParams = PulsarDopplerParams

        logging.info('Initialising FstatResults')
        self.FstatResults = lalpulsar.FstatResults()

        if self.BSGL:
            if len(self.detector_names) < 2:
414
                raise ValueError("Can't use BSGL with single detectors data")
Gregory Ashton's avatar
Gregory Ashton committed
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
            else:
                logging.info('Initialising BSGL')

            # Tuning parameters - to be reviewed
            numDetectors = 2
            if hasattr(self, 'nsegs'):
                p_val_threshold = 1e-6
                Fstar0s = np.linspace(0, 1000, 10000)
                p_vals = scipy.special.gammaincc(2*self.nsegs, Fstar0s)
                Fstar0 = Fstar0s[np.argmin(np.abs(p_vals - p_val_threshold))]
                if Fstar0 == Fstar0s[-1]:
                    raise ValueError('Max Fstar0 exceeded')
            else:
                Fstar0 = 15.
            logging.info('Using Fstar0 of {:1.2f}'.format(Fstar0))
            oLGX = np.zeros(10)
            oLGX[:numDetectors] = 1./numDetectors
            self.BSGLSetup = lalpulsar.CreateBSGLSetup(numDetectors,
                                                       Fstar0,
                                                       oLGX,
                                                       True,
                                                       1)
            self.twoFX = np.zeros(10)
            self.whatToCompute = (self.whatToCompute +
                                  lalpulsar.FSTATQ_2F_PER_DET)

        if self.transient:
            logging.info('Initialising transient parameters')
            self.windowRange = lalpulsar.transientWindowRange_t()
            self.windowRange.type = lalpulsar.TRANSIENT_RECTANGULAR
            self.windowRange.t0Band = 0
            self.windowRange.dt0 = 1
            self.windowRange.tauBand = 0
            self.windowRange.dtau = 1

    def compute_fullycoherent_det_stat_single_point(
            self, F0, F1, F2, Alpha, Delta, asini=None, period=None, ecc=None,
            tp=None, argp=None):
        """ Compute the fully-coherent det. statistic at a single point """

        return self.run_computefstatistic_single_point(
            self.minStartTime, self.maxStartTime, F0, F1, F2, Alpha, Delta,
            asini, period, ecc, tp, argp)

    def run_computefstatistic_single_point(self, tstart, tend, F0, F1,
                                           F2, Alpha, Delta, asini=None,
                                           period=None, ecc=None, tp=None,
                                           argp=None):
        """ Returns twoF or ln(BSGL) fully-coherently at a single point """

        self.PulsarDopplerParams.fkdot = np.array([F0, F1, F2, 0, 0, 0, 0])
        self.PulsarDopplerParams.Alpha = Alpha
        self.PulsarDopplerParams.Delta = Delta
        if self.binary:
            self.PulsarDopplerParams.asini = asini
            self.PulsarDopplerParams.period = period
            self.PulsarDopplerParams.ecc = ecc
            self.PulsarDopplerParams.tp = tp
            self.PulsarDopplerParams.argp = argp

        lalpulsar.ComputeFstat(self.FstatResults,
                               self.FstatInput,
                               self.PulsarDopplerParams,
                               1,
                               self.whatToCompute
                               )

        if self.transient is False:
            if self.BSGL is False:
                return self.FstatResults.twoF[0]

            twoF = np.float(self.FstatResults.twoF[0])
            self.twoFX[0] = self.FstatResults.twoFPerDet(0)
            self.twoFX[1] = self.FstatResults.twoFPerDet(1)
            log10_BSGL = lalpulsar.ComputeBSGL(twoF, self.twoFX,
                                               self.BSGLSetup)
            return log10_BSGL/np.log10(np.exp(1))

        self.windowRange.t0 = int(tstart)  # TYPE UINT4
        self.windowRange.tau = int(tend - tstart)  # TYPE UINT4

        FS = lalpulsar.ComputeTransientFstatMap(
            self.FstatResults.multiFatoms[0], self.windowRange, False)

        if self.BSGL is False:
500
501
502
503
504
            twoF = 2*FS.F_mn.data[0][0]
            if np.isnan(twoF):
                return 0
            else:
                return twoF
Gregory Ashton's avatar
Gregory Ashton committed
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524

        FstatResults_single = copy.copy(self.FstatResults)
        FstatResults_single.lenth = 1
        FstatResults_single.data = self.FstatResults.multiFatoms[0].data[0]
        FS0 = lalpulsar.ComputeTransientFstatMap(
            FstatResults_single.multiFatoms[0], self.windowRange, False)
        FstatResults_single.data = self.FstatResults.multiFatoms[0].data[1]
        FS1 = lalpulsar.ComputeTransientFstatMap(
            FstatResults_single.multiFatoms[0], self.windowRange, False)

        self.twoFX[0] = 2*FS0.F_mn.data[0][0]
        self.twoFX[1] = 2*FS1.F_mn.data[0][0]
        log10_BSGL = lalpulsar.ComputeBSGL(
                2*FS.F_mn.data[0][0], self.twoFX, self.BSGLSetup)

        return log10_BSGL/np.log10(np.exp(1))

    def calculate_twoF_cumulative(self, F0, F1, F2, Alpha, Delta, asini=None,
                                  period=None, ecc=None, tp=None, argp=None,
                                  tstart=None, tend=None, npoints=1000,
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
                                  ):
        """ Calculate the cumulative twoF along the obseration span
        Params
        ------
        F0, F1, F2, Alpha, Delta: float
            Parameters at which to compute the cumulative twoF
        asini, period, ecc, tp, argp: float
            Binary parameters at which to compute the cumulative twoF (default
            to None)
        tstart, tend: int
            GPS times to restrict the range of data used - automatically
            truncated to the span of data available
        npoints: int
            Number of points to compute twoF along the span

        Note: the minimum cumulatibe twoF is hard-coded to be computed over
        the first 6 hours from either the first timestampe in the data (if
        tstart is smaller than it) or tstart.

        """
        SFTminStartTime = self.SFT_timestamps[0]
        SFTmaxStartTime = self.SFT_timestamps[-1]
Gregory Ashton's avatar
Gregory Ashton committed
547
        tstart = np.max([SFTminStartTime, tstart])
548
549
550
        min_tau = np.max([SFTminStartTime - tstart, 0]) + 3600*6
        max_tau = SFTmaxStartTime - tstart
        taus = np.linspace(min_tau, max_tau, npoints)
Gregory Ashton's avatar
Gregory Ashton committed
551
552
553
554
555
556
557
558
559
560
561
562
        twoFs = []
        if self.transient is False:
            self.transient = True
            self.init_computefstatistic_single_point()
        for tau in taus:
            twoFs.append(self.run_computefstatistic_single_point(
                tstart=tstart, tend=tstart+tau, F0=F0, F1=F1, F2=F2,
                Alpha=Alpha, Delta=Delta, asini=asini, period=period, ecc=ecc,
                tp=tp, argp=argp))

        return taus, np.array(twoFs)

Gregory Ashton's avatar
Gregory Ashton committed
563
564
565
566
567
568
569
570
571
    def calculate_pfs(self, label, outdir, N=15, IFO=None, pfs_input=None):

        if pfs_input is None:
            if os.path.isfile('{}/{}.loudest'.format(outdir, label)) is False:
                raise ValueError(
                    'Need a loudest file to add the predicted Fstat')
            loudest = read_par(label, outdir, suffix='loudest')
            pfs_input = {key: loudest[key] for key in
                         ['h0', 'cosi', 'psi', 'Alpha', 'Delta', 'Freq']}
572
573
574
575
576
577
578
579
        times = np.linspace(self.minStartTime, self.maxStartTime, N+1)[1:]
        times = np.insert(times, 0, self.minStartTime + 86400/2.)
        out = [predict_fstat(minStartTime=self.minStartTime, maxStartTime=t,
                             sftfilepattern=self.sftfilepath, IFO=IFO,
                             **pfs_input) for t in times]
        pfs, pfs_sigma = np.array(out).T
        return times, pfs, pfs_sigma

Gregory Ashton's avatar
Gregory Ashton committed
580
    def plot_twoF_cumulative(self, label, outdir, ax=None, c='k', savefig=True,
Gregory Ashton's avatar
Gregory Ashton committed
581
582
                             title=None, add_pfs=False, N=15,
                             injectSources=None, **kwargs):
Gregory Ashton's avatar
Gregory Ashton committed
583
584
        if ax is None:
            fig, ax = plt.subplots()
Gregory Ashton's avatar
Gregory Ashton committed
585
586
587
588
589
590
591
        if injectSources:
            pfs_input = dict(
                h0=injectSources['h0'], cosi=injectSources['cosi'],
                psi=injectSources['psi'], Alpha=injectSources['Alpha'],
                Delta=injectSources['Delta'], Freq=injectSources['fkdot'][0])
        else:
            pfs_input = None
592
593
594
595

        taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
        ax.plot(taus/86400., twoFs, label='All detectors', color=c)
        if len(self.detector_names) > 1:
596
597
            detector_names = self.detector_names
            detectors = self.detectors
598
599
600
601
            for d in self.detector_names:
                self.detectors = d
                self.init_computefstatistic_single_point()
                taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
602
603
604
605
606
607
                ax.plot(taus/86400., twoFs, label='{}'.format(d),
                        color=detector_colors[d.lower()])
            self.detectors = detectors
            self.detector_names = detector_names

        if add_pfs:
Gregory Ashton's avatar
Gregory Ashton committed
608
609
            times, pfs, pfs_sigma = self.calculate_pfs(
                label, outdir, N=N, pfs_input=pfs_input)
610
611
            ax.fill_between(
                (times-self.minStartTime)/86400., pfs-pfs_sigma, pfs+pfs_sigma,
Gregory Ashton's avatar
Gregory Ashton committed
612
613
                color=c,
                label=r'Predicted $\langle 2\mathcal{F} \rangle\pm $ 1-$\sigma$ band',
614
615
616
                zorder=-10, alpha=0.2)
            if len(self.detector_names) > 1:
                for d in self.detector_names:
Gregory Ashton's avatar
Gregory Ashton committed
617
                    times, pfs, pfs_sigma = self.calculate_pfs(
Gregory Ashton's avatar
Gregory Ashton committed
618
                        label, outdir, IFO=d.upper(), N=N, pfs_input=pfs_input)
619
620
621
622
623
624
625
626
                    ax.fill_between(
                        (times-self.minStartTime)/86400., pfs-pfs_sigma,
                        pfs+pfs_sigma, color=detector_colors[d.lower()],
                        alpha=0.5,
                        label=(
                            'Predicted $2\mathcal{{F}}$ 1-$\sigma$ band ({})'
                            .format(d.upper())),
                        zorder=-10)
627

Gregory Ashton's avatar
Gregory Ashton committed
628
629
630
631
632
633
634
        ax.set_xlabel(r'Days from $t_{{\rm start}}={:.0f}$'.format(
            kwargs['tstart']))
        if self.BSGL:
            ax.set_ylabel(r'$\log_{10}(\mathrm{BSGL})_{\rm cumulative}$')
        else:
            ax.set_ylabel(r'$\widetilde{2\mathcal{F}}_{\rm cumulative}$')
        ax.set_xlim(0, taus[-1]/86400)
Gregory Ashton's avatar
Gregory Ashton committed
635
        ax.legend(frameon=False, loc=2, fontsize=6)
Gregory Ashton's avatar
Gregory Ashton committed
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
        if title:
            ax.set_title(title)
        if savefig:
            plt.tight_layout()
            plt.savefig('{}/{}_twoFcumulative.png'.format(outdir, label))
            return taus, twoFs
        else:
            return ax


class SemiCoherentSearch(BaseSearchClass, ComputeFstat):
    """ A semi-coherent search """

    @helper_functions.initializer
    def __init__(self, label, outdir, tref, nsegs=None, sftfilepath=None,
                 binary=False, BSGL=False, minStartTime=None,
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
653
                 detectors=None, earth_ephem=None, sun_ephem=None,
654
                 injectSources=None, assumeSqrtSX=None, SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to.
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, and start and end of the data.
        nsegs: int
            The (fixed) number of segments
        sftfilepath: str
            File patern to match SFTs

        For all other parameters, see pyfstat.ComputeFStat.
        """

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
        if self.earth_ephem is None:
            self.earth_ephem = self.earth_ephem_default
        if self.sun_ephem is None:
            self.sun_ephem = self.sun_ephem_default
        self.transient = True
        self.init_computefstatistic_single_point()
        self.init_semicoherent_parameters()

    def init_semicoherent_parameters(self):
        logging.info(('Initialising semicoherent parameters from {} to {} in'
                      ' {} segments').format(
            self.minStartTime, self.maxStartTime, self.nsegs))
        self.transient = True
        self.whatToCompute = lalpulsar.FSTATQ_2F+lalpulsar.FSTATQ_ATOMS_PER_DET
        self.tboundaries = np.linspace(self.minStartTime, self.maxStartTime,
                                       self.nsegs+1)

    def run_semi_coherent_computefstatistic_single_point(
            self, F0, F1, F2, Alpha, Delta, asini=None,
690
691
            period=None, ecc=None, tp=None, argp=None,
            record_segments=False):
Gregory Ashton's avatar
Gregory Ashton committed
692
693
        """ Returns twoF or ln(BSGL) semi-coherently at a single point """

694
695
696
697
698
699
700
701
702
        if hasattr(self, 'SFT_timestamps'):
            if self.tboundaries[0] < self.SFT_timestamps[0]:
                logging.debug(
                    'Semi-coherent start time {} before first SFT timestamp {}'
                    .format(self.tboundaries[0], self.SFT_timestamps[0]))
            if self.tboundaries[-1] > self.SFT_timestamps[-1]:
                logging.debug(
                    'Semi-coherent end time {} after last SFT timestamp {}'
                    .format(self.tboundaries[-1], self.SFT_timestamps[-1]))
Gregory Ashton's avatar
Gregory Ashton committed
703

Gregory Ashton's avatar
Gregory Ashton committed
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
        self.PulsarDopplerParams.fkdot = np.array([F0, F1, F2, 0, 0, 0, 0])
        self.PulsarDopplerParams.Alpha = Alpha
        self.PulsarDopplerParams.Delta = Delta
        if self.binary:
            self.PulsarDopplerParams.asini = asini
            self.PulsarDopplerParams.period = period
            self.PulsarDopplerParams.ecc = ecc
            self.PulsarDopplerParams.tp = tp
            self.PulsarDopplerParams.argp = argp

        lalpulsar.ComputeFstat(self.FstatResults,
                               self.FstatInput,
                               self.PulsarDopplerParams,
                               1,
                               self.whatToCompute
                               )

721
722
723
724
725
726
727
728
729
        #if self.transient is False:
        #    if self.BSGL is False:
        #        return self.FstatResults.twoF[0]
        #    twoF = np.float(self.FstatResults.twoF[0])
        #    self.twoFX[0] = self.FstatResults.twoFPerDet(0)
        #    self.twoFX[1] = self.FstatResults.twoFPerDet(1)
        #    log10_BSGL = lalpulsar.ComputeBSGL(twoF, self.twoFX,
        #                                       self.BSGLSetup)
        #    return log10_BSGL/np.log10(np.exp(1))
Gregory Ashton's avatar
Gregory Ashton committed
730
731

        detStat = 0
732
733
        if record_segments:
            self.detStat_per_segment = []
Gregory Ashton's avatar
Gregory Ashton committed
734
735
736
737
738
739
740
741
        for tstart, tend in zip(self.tboundaries[:-1], self.tboundaries[1:]):
            self.windowRange.t0 = int(tstart)  # TYPE UINT4
            self.windowRange.tau = int(tend - tstart)  # TYPE UINT4

            FS = lalpulsar.ComputeTransientFstatMap(
                self.FstatResults.multiFatoms[0], self.windowRange, False)

            if self.BSGL is False:
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
                d_detStat = 2*FS.F_mn.data[0][0]
            else:
                FstatResults_single = copy.copy(self.FstatResults)
                FstatResults_single.lenth = 1
                FstatResults_single.data = self.FstatResults.multiFatoms[0].data[0]
                FS0 = lalpulsar.ComputeTransientFstatMap(
                    FstatResults_single.multiFatoms[0], self.windowRange, False)
                FstatResults_single.data = self.FstatResults.multiFatoms[0].data[1]
                FS1 = lalpulsar.ComputeTransientFstatMap(
                    FstatResults_single.multiFatoms[0], self.windowRange, False)

                self.twoFX[0] = 2*FS0.F_mn.data[0][0]
                self.twoFX[1] = 2*FS1.F_mn.data[0][0]
                log10_BSGL = lalpulsar.ComputeBSGL(
                        2*FS.F_mn.data[0][0], self.twoFX, self.BSGLSetup)
                d_detStat = log10_BSGL/np.log10(np.exp(1))
Gregory Ashton's avatar
Gregory Ashton committed
758
759
760
            if np.isnan(d_detStat):
                logging.debug('NaNs in semi-coherent twoF treated as zero')
                d_detStat = 0
761
762
763
            detStat += d_detStat
            if record_segments:
                self.detStat_per_segment.append(d_detStat)
Gregory Ashton's avatar
Gregory Ashton committed
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779

        return detStat


class SemiCoherentGlitchSearch(BaseSearchClass, ComputeFstat):
    """ A semi-coherent glitch search

    This implements a basic `semi-coherent glitch F-stat in which the data
    is divided into segments either side of the proposed glitches and the
    fully-coherent F-stat in each segment is summed to give the semi-coherent
    F-stat
    """

    @helper_functions.initializer
    def __init__(self, label, outdir, tref, minStartTime, maxStartTime,
                 nglitch=0, sftfilepath=None, theta0_idx=0, BSGL=False,
780
                 minCoverFreq=None, maxCoverFreq=None, assumeSqrtSX=None,
781
                 detectors=None, earth_ephem=None, sun_ephem=None,
Gregory Ashton's avatar
Gregory Ashton committed
782
                 SSBprec=None, injectSources=None):
Gregory Ashton's avatar
Gregory Ashton committed
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
        """
        Parameters
        ----------
        label, outdir: str
            A label and directory to read/write data from/to.
        tref, minStartTime, maxStartTime: int
            GPS seconds of the reference time, and start and end of the data.
        nglitch: int
            The (fixed) number of glitches; this can zero, but occasionally
            this causes issue (in which case just use ComputeFstat).
        sftfilepath: str
            File patern to match SFTs
        theta0_idx, int
            Index (zero-based) of which segment the theta refers to - uyseful
            if providing a tight prior on theta to allow the signal to jump
            too theta (and not just from)

        For all other parameters, see pyfstat.ComputeFStat.
        """

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
        if self.earth_ephem is None:
            self.earth_ephem = self.earth_ephem_default
        if self.sun_ephem is None:
            self.sun_ephem = self.sun_ephem_default
        self.transient = True
        self.binary = False
        self.init_computefstatistic_single_point()

    def compute_nglitch_fstat(self, F0, F1, F2, Alpha, Delta, *args):
        """ Returns the semi-coherent glitch summed twoF """

        args = list(args)
        tboundaries = ([self.minStartTime] + args[-self.nglitch:]
                       + [self.maxStartTime])
        delta_F0s = args[-3*self.nglitch:-2*self.nglitch]
        delta_F1s = args[-2*self.nglitch:-self.nglitch]
        delta_F2 = np.zeros(len(delta_F0s))
        delta_phi = np.zeros(len(delta_F0s))
        theta = [0, F0, F1, F2]
        delta_thetas = np.atleast_2d(
                np.array([delta_phi, delta_F0s, delta_F1s, delta_F2]).T)

826
        thetas = self._calculate_thetas(theta, delta_thetas, tboundaries,
Gregory Ashton's avatar
Gregory Ashton committed
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
                                       theta0_idx=self.theta0_idx)

        twoFSum = 0
        for i, theta_i_at_tref in enumerate(thetas):
            ts, te = tboundaries[i], tboundaries[i+1]

            twoFVal = self.run_computefstatistic_single_point(
                ts, te, theta_i_at_tref[1], theta_i_at_tref[2],
                theta_i_at_tref[3], Alpha, Delta)
            twoFSum += twoFVal

        if np.isfinite(twoFSum):
            return twoFSum
        else:
            return -np.inf

    def compute_glitch_fstat_single(self, F0, F1, F2, Alpha, Delta, delta_F0,
                                    delta_F1, tglitch):
        """ Returns the semi-coherent glitch summed twoF for nglitch=1

        Note: OBSOLETE, used only for testing
        """

        theta = [F0, F1, F2]
        delta_theta = [delta_F0, delta_F1, 0]
        tref = self.tref

854
        theta_at_glitch = self._shift_coefficients(theta, tglitch - tref)
Gregory Ashton's avatar
Gregory Ashton committed
855
        theta_post_glitch_at_glitch = theta_at_glitch + delta_theta
856
        theta_post_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
            theta_post_glitch_at_glitch, tref - tglitch)

        twoFsegA = self.run_computefstatistic_single_point(
            self.minStartTime, tglitch, theta[0], theta[1], theta[2], Alpha,
            Delta)

        if tglitch == self.maxStartTime:
            return twoFsegA

        twoFsegB = self.run_computefstatistic_single_point(
            tglitch, self.maxStartTime, theta_post_glitch[0],
            theta_post_glitch[1], theta_post_glitch[2], Alpha,
            Delta)

        return twoFsegA + twoFsegB


class Writer(BaseSearchClass):
    """ Instance object for generating SFTs containing glitch signals """
    @helper_functions.initializer
    def __init__(self, label='Test', tstart=700000000, duration=100*86400,
                 dtglitch=None, delta_phi=0, delta_F0=0, delta_F1=0,
                 delta_F2=0, tref=None, F0=30, F1=1e-10, F2=0, Alpha=5e-3,
                 Delta=6e-2, h0=0.1, cosi=0.0, psi=0.0, phi=0, Tsft=1800,
881
                 outdir=".", sqrtSX=1, Band=4, detectors='H1',
882
                 minStartTime=None, maxStartTime=None, add_noise=True):
Gregory Ashton's avatar
Gregory Ashton committed
883
884
885
886
887
888
889
890
891
        """
        Parameters
        ----------
        label: string
            a human-readable label to be used in naming the output files
        tstart, tend : float
            start and end times (in gps seconds) of the total observation span
        dtglitch: float
            time (in gps seconds) of the glitch after tstart. To create data
892
            without a glitch, set dtglitch=None
Gregory Ashton's avatar
Gregory Ashton committed
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
        delta_phi, delta_F0, delta_F1: float
            instanteneous glitch magnitudes in rad, Hz, and Hz/s respectively
        tref: float or None
            reference time (default is None, which sets the reference time to
            tstart)
        F0, F1, F2, Alpha, Delta, h0, cosi, psi, phi: float
            frequency, sky-position, and amplitude parameters
        Tsft: float
            the sft duration
        minStartTime, maxStartTime: float
            if not None, the total span of data, this can be used to generate
            transient signals

        see `lalapps_Makefakedata_v5 --help` for help with the other paramaters
        """

        for d in self.delta_phi, self.delta_F0, self.delta_F1, self.delta_F2:
            if np.size(d) == 1:
911
                d = np.atleast_1d(d)
Gregory Ashton's avatar
Gregory Ashton committed
912
913
914
915
916
        self.tend = self.tstart + self.duration
        if self.minStartTime is None:
            self.minStartTime = self.tstart
        if self.maxStartTime is None:
            self.maxStartTime = self.tend
917
        if self.dtglitch is None:
Gregory Ashton's avatar
Gregory Ashton committed
918
919
            self.tbounds = [self.tstart, self.tend]
        else:
920
            self.dtglitch = np.atleast_1d(self.dtglitch)
921
922
923
            self.tglitch = self.tstart + self.dtglitch
            self.tbounds = np.concatenate((
                [self.tstart], self.tglitch, [self.tend]))
924
        logging.info('Using segment boundaries {}'.format(self.tbounds))
925
926

        self.check_inputs()
Gregory Ashton's avatar
Gregory Ashton committed
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942

        if os.path.isdir(self.outdir) is False:
            os.makedirs(self.outdir)
        if self.tref is None:
            self.tref = self.tstart
        self.tend = self.tstart + self.duration
        tbs = np.array(self.tbounds)
        self.durations_days = (tbs[1:] - tbs[:-1]) / 86400
        self.config_file_name = "{}/{}.cff".format(outdir, label)

        self.theta = np.array([phi, F0, F1, F2])
        self.delta_thetas = np.atleast_2d(
                np.array([delta_phi, delta_F0, delta_F1, delta_F2]).T)

        self.data_duration = self.maxStartTime - self.minStartTime
        numSFTs = int(float(self.data_duration) / self.Tsft)
943
944
945
946
947
948
949
        self.sftfilenames = [
            lalpulsar.OfficialSFTFilename(
                dets[0], dets[1], numSFTs, self.Tsft, self.minStartTime,
                self.data_duration, self.label)
            for dets in self.detectors.split(',')]
        self.sftfilepath = ';'.join([
            '{}/{}'.format(self.outdir, fn) for fn in self.sftfilenames])
Gregory Ashton's avatar
Gregory Ashton committed
950
951
        self.calculate_fmin_Band()

952
953
954
955
956
957
958
959
960
961
    def check_inputs(self):
        self.minStartTime = int(self.minStartTime)
        self.maxStartTime = int(self.maxStartTime)
        shapes = np.array([np.shape(x) for x in [self.delta_phi, self.delta_F0,
                                                 self.delta_F1, self.delta_F2]]
                          )
        if not np.all(shapes == shapes[0]):
            raise ValueError('all delta_* must be the same shape: {}'.format(
                shapes))

Gregory Ashton's avatar
Gregory Ashton committed
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
    def make_data(self):
        ''' A convienience wrapper to generate a cff file then sfts '''
        self.make_cff()
        self.run_makefakedata()

    def get_single_config_line(self, i, Alpha, Delta, h0, cosi, psi, phi, F0,
                               F1, F2, tref, tstart, duration_days):
        template = (
"""[TS{}]
Alpha = {:1.18e}
Delta = {:1.18e}
h0 = {:1.18e}
cosi = {:1.18e}
psi = {:1.18e}
phi0 = {:1.18e}
Freq = {:1.18e}
f1dot = {:1.18e}
f2dot = {:1.18e}
refTime = {:10.6f}
transientWindowType=rect
transientStartTime={:10.3f}
transientTauDays={:1.3f}\n""")
        return template.format(i, Alpha, Delta, h0, cosi, psi, phi, F0, F1,
                               F2, tref, tstart, duration_days)

    def make_cff(self):
        """
        Generates an .cff file for a 'glitching' signal

        """

993
        thetas = self._calculate_thetas(self.theta, self.delta_thetas,
Gregory Ashton's avatar
Gregory Ashton committed
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
                                       self.tbounds)

        content = ''
        for i, (t, d, ts) in enumerate(zip(thetas, self.durations_days,
                                           self.tbounds[:-1])):
            line = self.get_single_config_line(
                i, self.Alpha, self.Delta, self.h0, self.cosi, self.psi,
                t[0], t[1], t[2], t[3], self.tref, ts, d)

            content += line

        if self.check_if_cff_file_needs_rewritting(content):
            config_file = open(self.config_file_name, "w+")
            config_file.write(content)
            config_file.close()

    def calculate_fmin_Band(self):
        self.fmin = self.F0 - .5 * self.Band

1013
    def check_cached_data_okay_to_use(self, cl_mfd):
Gregory Ashton's avatar
Gregory Ashton committed
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
        """ Check if cached data exists and, if it does, if it can be used """

        getmtime = os.path.getmtime

        if os.path.isfile(self.sftfilepath) is False:
            logging.info('No SFT file matching {} found'.format(
                self.sftfilepath))
            return False
        else:
            logging.info('Matching SFT file found')

        if getmtime(self.sftfilepath) < getmtime(self.config_file_name):
            logging.info(
                ('The config file {} has been modified since the sft file {} '
                 + 'was created').format(
                    self.config_file_name, self.sftfilepath))
            return False

        logging.info(
            'The config file {} is older than the sft file {}'.format(
                self.config_file_name, self.sftfilepath))
        logging.info('Checking contents of cff file')
1036
1037
1038
        cl_dump = 'lalapps_SFTdumpheader {} | head -n 20'.format(self.sftfilepath)
        output  = helper_functions.run_commandline(cl_dump)
        calls   = [line for line in output.split('\n') if line[:3] == 'lal']
1039
        if calls[0] == cl_mfd:
Gregory Ashton's avatar
Gregory Ashton committed
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
            logging.info('Contents matched, use old sft file')
            return True
        else:
            logging.info('Contents unmatched, create new sft file')
            return False

    def check_if_cff_file_needs_rewritting(self, content):
        """ Check if the .cff file has changed

        Returns True if the file should be overwritten - where possible avoid
        overwriting to allow cached data to be used
        """
        if os.path.isfile(self.config_file_name) is False:
            logging.info('No config file {} found'.format(
                self.config_file_name))
            return True
        else:
            logging.info('Config file {} already exists'.format(
                self.config_file_name))

        with open(self.config_file_name, 'r') as f:
            file_content = f.read()
            if file_content == content:
                logging.info(
                    'File contents match, no update of {} required'.format(
                        self.config_file_name))
                return False
            else:
                logging.info(
                    'File contents unmatched, updating {}'.format(
                        self.config_file_name))
                return True

    def run_makefakedata(self):
        """ Generate the sft data from the configuration file """

        # Remove old data:
        try:
            os.unlink("{}/*{}*.sft".format(self.outdir, self.label))
        except OSError:
            pass

1082
1083
1084
1085
1086
1087
        cl_mfd = []
        cl_mfd.append('lalapps_Makefakedata_v5')
        cl_mfd.append('--outSingleSFT=TRUE')
        cl_mfd.append('--outSFTdir="{}"'.format(self.outdir))
        cl_mfd.append('--outLabel="{}"'.format(self.label))
        cl_mfd.append('--IFOs={}'.format(
1088
            ",".join(['"{}"'.format(d) for d in self.detectors.split(",")])))
1089
        if self.add_noise:
1090
            cl_mfd.append('--sqrtSX="{}"'.format(self.sqrtSX))
Gregory Ashton's avatar
Gregory Ashton committed
1091
        if self.minStartTime is None:
1092
            cl_mfd.append('--startTime={:0.0f}'.format(float(self.tstart)))
Gregory Ashton's avatar
Gregory Ashton committed
1093
        else:
1094
            cl_mfd.append('--startTime={:0.0f}'.format(float(self.minStartTime)))
Gregory Ashton's avatar
Gregory Ashton committed
1095
        if self.maxStartTime is None:
1096
            cl_mfd.append('--duration={}'.format(int(self.duration)))
Gregory Ashton's avatar
Gregory Ashton committed
1097
1098
        else:
            data_duration = self.maxStartTime - self.minStartTime
1099
            cl_mfd.append('--duration={}'.format(int(data_duration)))
Gregory Ashton's avatar
Gregory Ashton committed
1100
1101
        cl_mfd.append('--fmin={:.16g}'.format(self.fmin))
        cl_mfd.append('--Band={:.16g}'.format(self.Band))
1102
        cl_mfd.append('--Tsft={}'.format(self.Tsft))
Gregory Ashton's avatar
Gregory Ashton committed
1103
        if self.h0 != 0:
1104
            cl_mfd.append('--injectionSources="{}"'.format(self.config_file_name))
Gregory Ashton's avatar
Gregory Ashton committed
1105

1106
        cl_mfd = " ".join(cl_mfd)
Gregory Ashton's avatar
Gregory Ashton committed
1107

1108
1109
        if self.check_cached_data_okay_to_use(cl_mfd) is False:
            helper_functions.run_commandline(cl_mfd)
Gregory Ashton's avatar
Gregory Ashton committed
1110
1111
1112

    def predict_fstat(self):
        """ Wrapper to lalapps_PredictFstat """
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
        cl_pfs = []
        cl_pfs.append("lalapps_PredictFstat")
        cl_pfs.append("--h0={}".format(self.h0))
        cl_pfs.append("--cosi={}".format(self.cosi))
        cl_pfs.append("--psi={}".format(self.psi))
        cl_pfs.append("--Alpha={}".format(self.Alpha))
        cl_pfs.append("--Delta={}".format(self.Delta))
        cl_pfs.append("--Freq={}".format(self.F0))

        cl_pfs.append("--DataFiles='{}'".format(
Gregory Ashton's avatar
Gregory Ashton committed
1123
            self.outdir+"/*SFT_"+self.label+"*sft"))
1124
        cl_pfs.append("--assumeSqrtSX={}".format(self.sqrtSX))
Gregory Ashton's avatar
Gregory Ashton committed
1125

1126
1127
        cl_pfs.append("--minStartTime={}".format(int(self.minStartTime)))
        cl_pfs.append("--maxStartTime={}".format(int(self.maxStartTime)))
Gregory Ashton's avatar
Gregory Ashton committed
1128

1129
1130
        cl_pfs = " ".join(cl_pfs)
        output = helper_functions.run_commandline(cl_pfs)
Gregory Ashton's avatar
Gregory Ashton committed
1131
1132
        twoF = float(output.split('\n')[-2])
        return float(twoF)