core.py 48.7 KB
Newer Older
Gregory Ashton's avatar
Gregory Ashton committed
1
""" The core tools used in pyfstat """
2
3
from __future__ import division, absolute_import, print_function

Gregory Ashton's avatar
Gregory Ashton committed
4
5
6
7
import os
import logging
import copy

8
import glob
Gregory Ashton's avatar
Gregory Ashton committed
9
import numpy as np
10
11
12
13
14
import scipy.special
import scipy.optimize

import lal
import lalpulsar
15
import pyfstat.helper_functions as helper_functions
16
import pyfstat.tcw_fstat_map_funcs as tcw
17
18

# workaround for matplotlib on X-less remote logins
19
if 'DISPLAY' in os.environ:
20
21
    import matplotlib.pyplot as plt
else:
22
23
    logging.info('No $DISPLAY environment variable found, so importing \
                  matplotlib.pyplot with non-interactive "Agg" backend.')
24
25
26
27
    import matplotlib
    matplotlib.use('Agg')
    import matplotlib.pyplot as plt

Gregory Ashton's avatar
Gregory Ashton committed
28
helper_functions.set_up_matplotlib_defaults()
29
args, tqdm = helper_functions.set_up_command_line_arguments()
30
detector_colors = {'h1': 'C0', 'l1': 'C1'}
Gregory Ashton's avatar
Gregory Ashton committed
31
32


Gregory Ashton's avatar
Gregory Ashton committed
33
class Bunch(object):
34
35
    """ Turns dictionary into object with attribute-style access

36
37
    Parameters
    ----------
38
39
40
41
42
43
44
45
46
47
48
49
50
51
    dict
        Input dictionary

    Examples
    --------
    >>> data = Bunch(dict(x=1, y=[1, 2, 3], z=True))
    >>> print(data.x)
    1
    >>> print(data.y)
    [1, 2, 3]
    >>> print(data.z)
    True

    """
Gregory Ashton's avatar
Gregory Ashton committed
52
53
54
55
56
    def __init__(self, dictionary):
        self.__dict__.update(dictionary)


def read_par(filename=None, label=None, outdir=None, suffix='par',
57
58
             return_type='dict', comments=['%', '#'], raise_error=False):
    """ Read in a .par or .loudest file, returns a dict or Bunch of the data
59

Gregory Ashton's avatar
Gregory Ashton committed
60
61
    Parameters
    ----------
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
    filename : str
        Filename (path) containing rows of `key=val` data to read in.
    label, outdir, suffix : str, optional
        If filename is None, form the file to read as `outdir/label.suffix`.
    return_type : {'dict', 'bunch'}, optional
        If `dict`, return a dictionary, if 'bunch' return a Bunch
    comments : str or list of strings, optional
        Characters denoting that a row is a comment.
    raise_error : bool, optional
        If True, raise an error for lines which are not comments, but cannot
        be read.

    Notes
    -----
    This can also be used to read in .loudest files, or any file which has
    rows of `key=val` data (in which the val can be understood using eval(val)
Gregory Ashton's avatar
Gregory Ashton committed
78
79
80
81
82

    Returns
    -------
    d: Bunch or dict
        The par values as either a `Bunch` or dict type
83

84
85
86
87
    """
    if filename is None:
        filename = '{}/{}.{}'.format(outdir, label, suffix)
    if os.path.isfile(filename) is False:
88
        raise ValueError("No file {} found".format(filename))
Gregory Ashton's avatar
Gregory Ashton committed
89
90
    d = {}
    with open(filename, 'r') as f:
91
        d = _get_dictionary_from_lines(f, comments, raise_error)
Gregory Ashton's avatar
Gregory Ashton committed
92
93
94
95
96
97
    if return_type in ['bunch', 'Bunch']:
        return Bunch(d)
    elif return_type in ['dict', 'dictionary']:
        return d
    else:
        raise ValueError('return_type {} not understood'.format(return_type))
Gregory Ashton's avatar
Gregory Ashton committed
98
99


100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
def _get_dictionary_from_lines(lines, comments, raise_error):
    """ Return dictionary of key=val pairs for each line in lines

    Parameters
    ----------
    comments : str or list of strings
        Characters denoting that a row is a comment.
    raise_error : bool
        If True, raise an error for lines which are not comments, but cannot
        be read.

    Returns
    -------
    d: Bunch or dict
        The par values as either a `Bunch` or dict type

    """
117
118
    d = {}
    for line in lines:
119
        if line[0] not in comments and len(line.split('=')) == 2:
120
121
122
            try:
                key, val = line.rstrip('\n').split('=')
                key = key.strip()
123
124
125
126
127
128
129
130
                val = val.strip()
                if (val[0] in ["'", '"']) and (val[-1] in ["'", '"']):
                    d[key] = val.lstrip('"').lstrip("'").rstrip('"').rstrip("'")
                else:
                    try:
                        d[key] = np.float64(eval(val.rstrip('; ')))
                    except NameError:
                        d[key] = val.rstrip('; ')
131
            except SyntaxError:
132
133
                if raise_error:
                    raise IOError('Line {} not understood'.format(line))
134
135
136
137
138
                pass
    return d


def predict_fstat(h0, cosi, psi, Alpha, Delta, Freq, sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
139
                  minStartTime, maxStartTime, IFO=None, assumeSqrtSX=None,
140
                  tempory_filename='fs.tmp', **kwargs):
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
    """ Wrapper to lalapps_PredictFstat

    Parameters
    ----------
    h0, cosi, psi, Alpha, Delta, Freq : float
        Signal properties, see `lalapps_PredictFstat --help` for more info.
    sftfilepattern : str
        Pattern matching the sftfiles to use.
    minStartTime, maxStartTime : int
    IFO : str
        See `lalapps_PredictFstat --help`
    assumeSqrtSX : float or None
        See `lalapps_PredictFstat --help`, if None this option is not used

    Returns
    -------
    twoF_expected, twoF_sigma : float
        The expectation and standard deviation of 2F

    """
161

162
163
164
165
166
167
168
169
170
171
    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))
172
    if assumeSqrtSX:
173
        cl_pfs.append("--assumeSqrtSX={}".format(assumeSqrtSX))
174
    if IFO:
175
176
177
178
179
        if ',' in IFO:
            logging.warning('Multiple detector selection not available, using'
                            ' all available data')
        else:
            cl_pfs.append("--IFO={}".format(IFO))
180

181
182
    cl_pfs.append("--minStartTime={}".format(int(minStartTime)))
    cl_pfs.append("--maxStartTime={}".format(int(maxStartTime)))
183
    cl_pfs.append("--outputFstat={}".format(tempory_filename))
184

185
186
    cl_pfs = " ".join(cl_pfs)
    helper_functions.run_commandline(cl_pfs)
187
188
    d = read_par(filename=tempory_filename)
    os.remove(tempory_filename)
189
190
191
    return float(d['twoF_expected']), float(d['twoF_sigma'])


Gregory Ashton's avatar
Gregory Ashton committed
192
class BaseSearchClass(object):
193
    """ The base search class providing parent methods to other searches """
Gregory Ashton's avatar
Gregory Ashton committed
194

195
    def _add_log_file(self):
Gregory Ashton's avatar
Gregory Ashton committed
196
197
198
199
200
201
202
203
204
        """ 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)

205
    def _shift_matrix(self, n, dT):
Gregory Ashton's avatar
Gregory Ashton committed
206
207
208
209
        """ Generate the shift matrix

        Parameters
        ----------
210
        n : int
Gregory Ashton's avatar
Gregory Ashton committed
211
            The dimension of the shift-matrix to generate
212
        dT : float
Gregory Ashton's avatar
Gregory Ashton committed
213
214
215
216
            The time delta of the shift matrix

        Returns
        -------
217
218
        m : ndarray, shape (n,)
            The shift matrix.
Gregory Ashton's avatar
Gregory Ashton committed
219

220
        """
Gregory Ashton's avatar
Gregory Ashton committed
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
        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

236
    def _shift_coefficients(self, theta, dT):
Gregory Ashton's avatar
Gregory Ashton committed
237
238
239
240
        """ Shift a set of coefficients by dT

        Parameters
        ----------
241
242
        theta : array-like, shape (n,)
            Vector of the expansion coefficients to transform starting from the
Gregory Ashton's avatar
Gregory Ashton committed
243
            lowest degree e.g [phi, F0, F1,...].
244
245
        dT : float
            Difference between the two reference times as tref_new - tref_old.
Gregory Ashton's avatar
Gregory Ashton committed
246
247
248

        Returns
        -------
249
250
        theta_new : ndarray, shape (n,)
            Vector of the coefficients as evaluated as the new reference time.
Gregory Ashton's avatar
Gregory Ashton committed
251
252
        """
        n = len(theta)
253
        m = self._shift_matrix(n, dT)
Gregory Ashton's avatar
Gregory Ashton committed
254
255
        return np.dot(m, theta)

256
    def _calculate_thetas(self, theta, delta_thetas, tbounds, theta0_idx=0):
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
        """ Calculates the set of thetas given delta_thetas, the jumps

        This is used when generating data containing glitches or timing noise.
        Specifically, the source parameters of the signal are not constant in
        time, but jump by `delta_theta` at `tbounds`.

        Parameters
        ----------
        theta : array_like
            The source parameters of size (n,).
        delta_thetas : array_like
            The jumps in the source parameters of size (m, n) where m is the
            number of jumps.
        tbounds : array_like
            Time boundaries of the jumps of size (m+2,).
        theta0_idx : int
            Index of the segment for which the theta are defined.

        Returns
        -------
        ndarray
            The set of thetas, shape (m+1, n).

        """
Gregory Ashton's avatar
Gregory Ashton committed
281
282
283
        thetas = [theta]
        for i, dt in enumerate(delta_thetas):
            if i < theta0_idx:
284
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
285
286
                    thetas[0], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch - dt
287
                thetas.insert(0, self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
288
289
290
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))

            elif i >= theta0_idx:
291
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
292
293
                    thetas[i], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch + dt
294
                thetas.append(self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
295
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))
296
        self.thetas_at_tref = thetas
Gregory Ashton's avatar
Gregory Ashton committed
297
298
        return thetas

299
    def _get_list_of_matching_sfts(self):
300
        """ Returns a list of sfts matching the attribute sftfilepattern """
301
302
        sftfilepatternlist = np.atleast_1d(self.sftfilepattern.split(';'))
        matches = [glob.glob(p) for p in sftfilepatternlist]
303
        matches = [item for sublist in matches for item in sublist]
304
305
306
307
        if len(matches) > 0:
            return matches
        else:
            raise IOError('No sfts found matching {}'.format(
308
                self.sftfilepattern))
309

310
311
    def set_ephemeris_files(self, earth_ephem=None, sun_ephem=None):
        """ Set the ephemeris files to use for the Earth and Sun
Gregory Ashton's avatar
Gregory Ashton committed
312

313
314
315
316
317
        Parameters
        ----------
        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
Gregory Ashton's avatar
Gregory Ashton committed
318

319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
        Note: If not manually set, default values in ~/.pyfstat are used

        """

        earth_ephem_default, sun_ephem_default = (
                helper_functions.get_ephemeris_files())

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


class ComputeFstat(BaseSearchClass):
    """ Base class providing interface to `lalpulsar.ComputeFstat` """
Gregory Ashton's avatar
Gregory Ashton committed
334
335

    @helper_functions.initializer
336
    def __init__(self, tref, sftfilepattern=None, minStartTime=None,
David Keitel's avatar
David Keitel committed
337
338
                 maxStartTime=None, binary=False, BSGL=False,
                 transientWindowType=None, t0Band=None, tauBand=None,
339
                 tauMin=None,
340
                 dt0=None, dtau=None,
341
                 detectors=None, minCoverFreq=None, maxCoverFreq=None,
342
                 injectSources=None, injectSqrtSX=None, assumeSqrtSX=None,
343
                 SSBprec=None,
344
                 tCWFstatMapVersion='lal', cudaDeviceName=None):
Gregory Ashton's avatar
Gregory Ashton committed
345
346
347
        """
        Parameters
        ----------
348
        tref : int
Gregory Ashton's avatar
Gregory Ashton committed
349
            GPS seconds of the reference time.
350
        sftfilepattern : str
351
352
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
353
        minStartTime, maxStartTime : float GPStime
Gregory Ashton's avatar
Gregory Ashton committed
354
355
            Only use SFTs with timestemps starting from (including, excluding)
            this epoch
356
        binary : bool
Gregory Ashton's avatar
Gregory Ashton committed
357
            If true, search of binary parameters.
358
        BSGL : bool
Gregory Ashton's avatar
Gregory Ashton committed
359
            If true, compute the BSGL rather than the twoF value.
David Keitel's avatar
David Keitel committed
360
361
362
        transientWindowType: str
            If 'rect' or 'exp',
            allow for the Fstat to be computed over a transient range.
Gregory Ashton's avatar
Gregory Ashton committed
363
364
            ('none' instead of None explicitly calls the transient-window
            function, but with the full range, for debugging)
365
366
        t0Band, tauBand: int
            if >0, search t0 in (minStartTime,minStartTime+t0Band)
367
                   and tau in (tauMin,2*Tsft+tauBand).
368
369
            if =0, only compute CW Fstat with t0=minStartTime,
                   tau=maxStartTime-minStartTime.
370
371
        tauMin: int
            defaults to 2*Tsft
372
373
374
        dt0, dtau: int
            grid resolutions in transient start-time and duration,
            both default to Tsft
375
        detectors : str
Gregory Ashton's avatar
Gregory Ashton committed
376
            Two character reference to the data to use, specify None for no
377
            contraint. If multiple-separate by comma.
378
        minCoverFreq, maxCoverFreq : float
Gregory Ashton's avatar
Gregory Ashton committed
379
380
381
            The min and max cover frequency passed to CreateFstatInput, if
            either is None the range of frequencies in the SFT less 1Hz is
            used.
382
        injectSources : dict or str
383
384
            Either a dictionary of the values to inject, or a string pointing
            to the .cff file to inject
385
        injectSqrtSX :
386
            Not yet implemented
387
        assumeSqrtSX : float
388
389
390
            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
391
        SSBprec : int
392
393
            Flag to set the SSB calculation: 0=Newtonian, 1=relativistic,
            2=relativisitic optimised, 3=DMoff, 4=NO_SPIN
394
395
396
        tCWFstatMapVersion: str
            Choose between standard 'lal' implementation,
            'pycuda' for gpu, and some others for devel/debug.
397
398
        cudaDeviceName: str
            GPU name to be matched against drv.Device output.
Gregory Ashton's avatar
Gregory Ashton committed
399
400
401

        """

402
        self.set_ephemeris_files()
Gregory Ashton's avatar
Gregory Ashton committed
403
404
        self.init_computefstatistic_single_point()

405
406
407
408
409
410
411
412
413
414
415
    def _get_SFTCatalog(self):
        """ Load the SFTCatalog

        If sftfilepattern is specified, load the data. If not, attempt to
        create data on the fly.

        Returns
        -------
        SFTCatalog: lalpulsar.SFTCatalog

        """
Gregory Ashton's avatar
Gregory Ashton committed
416
417
        if hasattr(self, 'SFTCatalog'):
            return
418
        if self.sftfilepattern is None:
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
            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
440
441
        logging.info('Initialising SFTCatalog')
        constraints = lalpulsar.SFTConstraints()
442
        if self.detectors:
443
            if ',' in self.detectors:
444
445
                logging.warning('Multiple detector selection not available,'
                                ' using all available data')
446
447
            else:
                constraints.detector = self.detectors
Gregory Ashton's avatar
Gregory Ashton committed
448
449
450
451
452
        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(
453
454
                     self.sftfilepattern))
        SFTCatalog = lalpulsar.SFTdataFind(self.sftfilepattern, constraints)
455

Gregory Ashton's avatar
Gregory Ashton committed
456
        SFT_timestamps = [d.header.epoch for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
457
        self.SFT_timestamps = [float(s) for s in SFT_timestamps]
458
459
        if len(SFT_timestamps) == 0:
            raise ValueError('Failed to load any data')
Gregory Ashton's avatar
Gregory Ashton committed
460
461
462
463
464
        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
465
            except ImportError:
Gregory Ashton's avatar
Gregory Ashton committed
466
                pass
467

468
        cl_tconv1 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[0]))
469
470
        output = helper_functions.run_commandline(cl_tconv1,
                                                  log_level=logging.DEBUG)
471
472
        tconvert1 = output.rstrip('\n')
        cl_tconv2 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[-1]))
473
474
        output = helper_functions.run_commandline(cl_tconv2,
                                                  log_level=logging.DEBUG)
475
        tconvert2 = output.rstrip('\n')
Gregory Ashton's avatar
Gregory Ashton committed
476
477
        logging.info('Data spans from {} ({}) to {} ({})'.format(
            int(SFT_timestamps[0]),
478
            tconvert1,
Gregory Ashton's avatar
Gregory Ashton committed
479
            int(SFT_timestamps[-1]),
480
            tconvert2))
481
482
483
484
485
486
487
488
489
490
491
492
493

        if self.minStartTime is None:
            self.minStartTime = int(SFT_timestamps[0])
        if self.maxStartTime is None:
            self.maxStartTime = int(SFT_timestamps[-1])

        detector_names = list(set([d.header.name for d in SFTCatalog.data]))
        self.detector_names = detector_names
        if len(detector_names) == 0:
            raise ValueError('No data loaded.')
        logging.info('Loaded {} data files from detectors {}'.format(
            len(SFT_timestamps), detector_names))

494
        return SFTCatalog
Gregory Ashton's avatar
Gregory Ashton committed
495
496
497
498

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

499
        SFTCatalog = self._get_SFTCatalog()
Gregory Ashton's avatar
Gregory Ashton committed
500
501
502
503
504
505

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

        logging.info('Initialising FstatInput')
        dFreq = 0
David Keitel's avatar
David Keitel committed
506
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
507
508
509
510
511
512
            self.whatToCompute = lalpulsar.FSTATQ_ATOMS_PER_DET
        else:
            self.whatToCompute = lalpulsar.FSTATQ_2F

        FstatOAs = lalpulsar.FstatOptionalArgs()
        FstatOAs.randSeed = lalpulsar.FstatOptionalArgsDefaults.randSeed
513
514
515
516
517
        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
518
519
520
        FstatOAs.Dterms = lalpulsar.FstatOptionalArgsDefaults.Dterms
        FstatOAs.runningMedianWindow = lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow
        FstatOAs.FstatMethod = lalpulsar.FstatOptionalArgsDefaults.FstatMethod
521
522
523
524
525
526
527
528
        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
529
530
531
        FstatOAs.prevInput = lalpulsar.FstatOptionalArgsDefaults.prevInput
        FstatOAs.collectTiming = lalpulsar.FstatOptionalArgsDefaults.collectTiming

Gregory Ashton's avatar
Gregory Ashton committed
532
        if hasattr(self, 'injectSources') and type(self.injectSources) == dict:
Gregory Ashton's avatar
Gregory Ashton committed
533
534
535
536
537
538
539
540
541
542
            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']
Gregory Ashton's avatar
Gregory Ashton committed
543
544
545
546
547
548
            if 'fkdot' in self.injectSources:
                PP.Doppler.fkdot = np.array(self.injectSources['fkdot'])
            else:
                PP.Doppler.fkdot = np.zeros(lalpulsar.PULSAR_MAX_SPINS)
                for i, key in enumerate(['F0', 'F1', 'F2']):
                    PP.Doppler.fkdot[i] = self.injectSources[key]
Gregory Ashton's avatar
Gregory Ashton committed
549
550
551
552
            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
553
        elif hasattr(self, 'injectSources') and type(self.injectSources) == str:
554
555
556
557
            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
558
559
        else:
            FstatOAs.injectSources = lalpulsar.FstatOptionalArgsDefaults.injectSources
560
561
562
563
        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
564
        if self.minCoverFreq is None or self.maxCoverFreq is None:
565
            fAs = [d.header.f0 for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
566
            fBs = [d.header.f0 + (d.numBins-1)*d.header.deltaF
567
                   for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
568
569
570
571
572
573
            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))

574
        self.FstatInput = lalpulsar.CreateFstatInput(SFTCatalog,
Gregory Ashton's avatar
Gregory Ashton committed
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
                                                     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:
595
                raise ValueError("Can't use BSGL with single detectors data")
Gregory Ashton's avatar
Gregory Ashton committed
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
            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)

David Keitel's avatar
David Keitel committed
622
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
623
624
            logging.info('Initialising transient parameters')
            self.windowRange = lalpulsar.transientWindowRange_t()
David Keitel's avatar
David Keitel committed
625
626
627
628
629
630
            transientWindowTypes = {'none': lalpulsar.TRANSIENT_NONE,
                                    'rect': lalpulsar.TRANSIENT_RECTANGULAR,
                                    'exp':  lalpulsar.TRANSIENT_EXPONENTIAL}
            if self.transientWindowType in transientWindowTypes:
                self.windowRange.type = transientWindowTypes[self.transientWindowType]
            else:
Gregory Ashton's avatar
Gregory Ashton committed
631
632
633
634
                raise ValueError(
                    'Unknown window-type ({}) passed as input, [{}] allows.'
                    .format(self.transientWindowType,
                            ', '.join(transientWindowTypes)))
David Keitel's avatar
David Keitel committed
635

636
            # default spacing
David Keitel's avatar
David Keitel committed
637
            self.Tsft = int(1.0/SFTCatalog.data[0].header.deltaF)
638
639
640
            self.windowRange.dt0 = self.Tsft
            self.windowRange.dtau = self.Tsft

David Keitel's avatar
David Keitel committed
641
642
            # special treatment of window_type = none
            # ==> replace by rectangular window spanning all the data
643
644
            if self.windowRange.type == lalpulsar.TRANSIENT_NONE:
                self.windowRange.t0 = int(self.minStartTime)
Gregory Ashton's avatar
Gregory Ashton committed
645
                self.windowRange.t0Band = 0
646
                self.windowRange.tau = int(self.maxStartTime-self.minStartTime)
David Keitel's avatar
David Keitel committed
647
                self.windowRange.tauBand = 0
Gregory Ashton's avatar
Gregory Ashton committed
648
            else:  # user-set bands and spacings
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
                if self.t0Band is None:
                    self.windowRange.t0Band = 0
                else:
                    if not isinstance(self.t0Band, int):
                        logging.warn('Casting non-integer t0Band={} to int...'
                                     .format(self.t0Band))
                        self.t0Band = int(self.t0Band)
                    self.windowRange.t0Band = self.t0Band
                    if self.dt0:
                        self.windowRange.dt0 = self.dt0
                if self.tauBand is None:
                    self.windowRange.tauBand = 0
                else:
                    if not isinstance(self.tauBand, int):
                        logging.warn('Casting non-integer tauBand={} to int...'
                                     .format(self.tauBand))
                        self.tauBand = int(self.tauBand)
                    self.windowRange.tauBand = self.tauBand
                    if self.dtau:
                        self.windowRange.dtau = self.dtau
669
670
671
672
673
674
675
676
                    if self.tauMin is None:
                        self.windowRange.tau = int(2*self.Tsft)
                    else:
                        if not isinstance(self.tauMin, int):
                            logging.warn('Casting non-integer tauMin={} to int...'
                                         .format(self.tauMin))
                            self.tauMin = int(self.tauMin)
                        self.windowRange.tau = self.tauMin
Gregory Ashton's avatar
Gregory Ashton committed
677

David Keitel's avatar
David Keitel committed
678
            logging.info('Initialising transient FstatMap features...')
Gregory Ashton's avatar
Gregory Ashton committed
679
680
681
            self.tCWFstatMapFeatures, self.gpu_context = (
                tcw.init_transient_fstat_map_features(
                    self.tCWFstatMapVersion == 'pycuda', self.cudaDeviceName))
682

683
684
685
    def get_fullycoherent_twoF(self, tstart, tend, F0, F1, F2, Alpha, Delta,
                               asini=None, period=None, ecc=None, tp=None,
                               argp=None):
Gregory Ashton's avatar
Gregory Ashton committed
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
        """ 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
                               )

David Keitel's avatar
David Keitel committed
704
        if not self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
705
706
707
708
709
710
711
712
713
714
715
            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
David Keitel's avatar
David Keitel committed
716
717
718
719
        if self.windowRange.tauBand == 0:
            # true single-template search also in transient params:
            # actual (t0,tau) window was set with tstart, tend before
            self.windowRange.tau = int(tend - tstart)  # TYPE UINT4
Gregory Ashton's avatar
Gregory Ashton committed
720

Gregory Ashton's avatar
Gregory Ashton committed
721
722
723
        self.FstatMap = tcw.call_compute_transient_fstat_map(
            self.tCWFstatMapVersion, self.tCWFstatMapFeatures,
            self.FstatResults.multiFatoms[0], self.windowRange)
724
725
726
727
        if self.tCWFstatMapVersion == 'lal':
            F_mn = self.FstatMap.F_mn.data
        else:
            F_mn = self.FstatMap.F_mn
Gregory Ashton's avatar
Gregory Ashton committed
728

729
        twoF = 2*np.max(F_mn)
Gregory Ashton's avatar
Gregory Ashton committed
730
        if self.BSGL is False:
731
732
733
734
            if np.isnan(twoF):
                return 0
            else:
                return twoF
Gregory Ashton's avatar
Gregory Ashton committed
735
736
737
738
739
740
741
742
743
744

        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)

745
746
747
748
749
        # for now, use the Doppler parameter with
        # multi-detector F maximised over t0,tau
        # to return BSGL
        # FIXME: should we instead compute BSGL over the whole F_mn
        # and return the maximum of that?
750
        idx_maxTwoF = np.argmax(F_mn)
751
752
753

        self.twoFX[0] = 2*FS0.F_mn.data[idx_maxTwoF]
        self.twoFX[1] = 2*FS1.F_mn.data[idx_maxTwoF]
Gregory Ashton's avatar
Gregory Ashton committed
754
        log10_BSGL = lalpulsar.ComputeBSGL(
755
                twoF, self.twoFX, self.BSGLSetup)
Gregory Ashton's avatar
Gregory Ashton committed
756
757
758
759
760
761

        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,
762
763
                                  ):
        """ Calculate the cumulative twoF along the obseration span
764
765
766

        Parameters
        ----------
767
768
        F0, F1, F2, Alpha, Delta: float
            Parameters at which to compute the cumulative twoF
769
770
        asini, period, ecc, tp, argp: float, optional
            Binary parameters at which to compute the cumulative 2F
771
772
773
774
775
776
        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

777
778
779
        Notes
        -----
        The minimum cumulatibe twoF is hard-coded to be computed over
780
781
782
783
784
785
        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
786
        tstart = np.max([SFTminStartTime, tstart])
787
788
789
        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
790
        twoFs = []
David Keitel's avatar
David Keitel committed
791
792
793
        if not self.transientWindowType:
            # still call the transient-Fstat-map function, but using the full range
            self.transientWindowType = 'none'
Gregory Ashton's avatar
Gregory Ashton committed
794
795
            self.init_computefstatistic_single_point()
        for tau in taus:
796
            detstat = self.get_fullycoherent_twoF(
Gregory Ashton's avatar
Gregory Ashton committed
797
798
                tstart=tstart, tend=tstart+tau, F0=F0, F1=F1, F2=F2,
                Alpha=Alpha, Delta=Delta, asini=asini, period=period, ecc=ecc,
799
800
                tp=tp, argp=argp)
            twoFs.append(detstat)
Gregory Ashton's avatar
Gregory Ashton committed
801
802
803

        return taus, np.array(twoFs)

804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
    def _calculate_predict_fstat_cumulative(self, N, label=None, outdir=None,
                                            IFO=None, pfs_input=None):
        """ Calculates the predicted 2F and standard deviation cumulatively

        Parameters
        ----------
        N : int
            Number of timesteps to use between minStartTime and maxStartTime.
        label, outdir : str, optional
            The label and directory to read in the .loudest file from
        IFO : str
        pfs_input : dict, optional
            Input kwargs to predict_fstat (alternative to giving label and
            outdir).

        Returns
        -------
        times, pfs, pfs_sigma : ndarray, size (N,)

        """
Gregory Ashton's avatar
Gregory Ashton committed
824
825
826
827
828

        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')
829
            loudest = read_par(label=label, outdir=outdir, suffix='loudest')
Gregory Ashton's avatar
Gregory Ashton committed
830
831
            pfs_input = {key: loudest[key] for key in
                         ['h0', 'cosi', 'psi', 'Alpha', 'Delta', 'Freq']}
832
833
834
        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,
835
                             sftfilepattern=self.sftfilepattern, IFO=IFO,
836
837
838
839
                             **pfs_input) for t in times]
        pfs, pfs_sigma = np.array(out).T
        return times, pfs, pfs_sigma

840
841
    def plot_twoF_cumulative(self, label, outdir, add_pfs=False, N=15,
                             injectSources=None, ax=None, c='k', savefig=True,
842
                             title=None, plt_label=None, **kwargs):
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
        """ Plot the twoF value cumulatively

        Parameters
        ----------
        label, outdir : str
        add_pfs : bool
            If true, plot the predicted 2F and standard deviation
        N : int
            Number of points to use
        injectSources : dict
            See `ComputeFstat`
        ax : matplotlib.axes._subplots_AxesSubplot, optional
            Axis to add the plot to.
        c : str
            Colour
        savefig : bool
            If true, save the figure in outdir
860
861
        title, plt_label: str
            Figure title and label
862
863
864
865
866
867
868
869
870

        Returns
        -------
        tauS, tauF : ndarray shape (N,)
            If savefig, the times and twoF (cumulative) values
        ax : matplotlib.axes._subplots_AxesSubplot, optional
            If savefig is False

        """
Gregory Ashton's avatar
Gregory Ashton committed
871
872
        if ax is None:
            fig, ax = plt.subplots()
Gregory Ashton's avatar
Gregory Ashton committed
873
874
875
876
877
878
879
        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
880
881

        taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
882
        ax.plot(taus/86400., twoFs, label=plt_label, color=c)
883
        if len(self.detector_names) > 1:
884
885
            detector_names = self.detector_names
            detectors = self.detectors
886
887
888
889
            for d in self.detector_names:
                self.detectors = d
                self.init_computefstatistic_single_point()
                taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
890
891
892
893
894
895
                ax.plot(taus/86400., twoFs, label='{}'.format(d),
                        color=detector_colors[d.lower()])
            self.detectors = detectors
            self.detector_names = detector_names

        if add_pfs:
896
897
            times, pfs, pfs_sigma = self._calculate_predict_fstat_cumulative(
                N=N, label=label, outdir=outdir, pfs_input=pfs_input)
898
899
            ax.fill_between(
                (times-self.minStartTime)/86400., pfs-pfs_sigma, pfs+pfs_sigma,
Gregory Ashton's avatar
Gregory Ashton committed
900
                color=c,
901
902
                label=(r'Predicted $\langle 2\mathcal{F} '
                       r'\rangle\pm $ 1-$\sigma$ band'),
903
904
905
                zorder=-10, alpha=0.2)
            if len(self.detector_names) > 1:
                for d in self.detector_names:
906
907
908
909
                    out = self._calculate_predict_fstat_cumulative(
                        N=N, label=label, outdir=outdir, IFO=d.upper(),
                        pfs_input=pfs_input)
                    times, pfs, pfs_sigma = out
910
911
912
913
914
915
916
917
                    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)
918

Gregory Ashton's avatar
Gregory Ashton committed
919
920
921
922
923
924
925
        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)
926
927
        if plt_label:
            ax.legend(frameon=False, loc=2, fontsize=6)
Gregory Ashton's avatar
Gregory Ashton committed
928
929
930
931
932
933
934
935
936
        if title:
            ax.set_title(title)
        if savefig:
            plt.tight_layout()
            plt.savefig('{}/{}_twoFcumulative.png'.format(outdir, label))
            return taus, twoFs
        else:
            return ax

937
938
939
940
941
942
943
944
945
946
947
948
    def get_full_CFSv2_output(self, tstart, tend, F0, F1, F2, Alpha, Delta,
                              tref):
        """ Basic wrapper around CFSv2 to get the full (h0..) output """
        cl_CFSv2 = "lalapps_ComputeFstatistic_v2 --minStartTime={} --maxStartTime={} --Freq={} --f1dot={} --f2dot={} --Alpha={} --Delta={} --refTime={} --DataFiles='{}' --outputLoudest='{}' --ephemEarth={} --ephemSun={}"
        LoudestFile = "loudest.temp"
        helper_functions.run_commandline(cl_CFSv2.format(
            tstart, tend, F0, F1, F2, Alpha, Delta, tref, self.sftfilepattern,
            LoudestFile, self.earth_ephem, self.sun_ephem))
        loudest = read_par(LoudestFile, return_type='dict')
        os.remove(LoudestFile)
        return loudest

949
950
951
952
953
954
955
956
957
958
959
960
    def write_atoms_to_file(self, fnamebase=''):
        multiFatoms = getattr(self.FstatResults, 'multiFatoms', None)
        if multiFatoms and multiFatoms[0]:
            dopplerName = lalpulsar.PulsarDopplerParams2String ( self.PulsarDopplerParams )
            #fnameAtoms = os.path.join(self.outdir,'Fstatatoms_%s.dat' % dopplerName)
            fnameAtoms = fnamebase + '_Fstatatoms_%s.dat' % dopplerName
            fo = lal.FileOpen(fnameAtoms, 'w')
            lalpulsar.write_MultiFstatAtoms_to_fp ( fo, multiFatoms[0] )
            del fo # instead of lal.FileClose() which is not SWIG-exported
        else:
            raise RuntimeError('Cannot print atoms vector to file: no FstatResults.multiFatoms, or it is None!')

Gregory Ashton's avatar
Gregory Ashton committed
961

962
963
964
965
966
967
968
969
970
    def __del__(self):
        """
        In pyCuda case without autoinit,
        we need to make sure the context is removed at the end
        """
        if hasattr(self,'gpu_context') and self.gpu_context:
            self.gpu_context.detach()


971
class SemiCoherentSearch(ComputeFstat):
Gregory Ashton's avatar
Gregory Ashton committed
972
973
974
    """ A semi-coherent search """

    @helper_functions.initializer
975
    def __init__(self, label, outdir, tref, nsegs=None, sftfilepattern=None,
Gregory Ashton's avatar
Gregory Ashton committed
976
977
                 binary=False, BSGL=False, minStartTime=None,
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
978
979
                 detectors=None, injectSources=None, assumeSqrtSX=None,
                 SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
980
981
982
983
984
985
986
987
988
        """
        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
989
990
991
        sftfilepattern: str
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
Gregory Ashton's avatar
Gregory Ashton committed
992
993
994
995
996

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

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
997
        self.set_ephemeris_files()
David Keitel's avatar
David Keitel committed
998
999
1000
        self.transientWindowType = 'rect'
        self.t0Band  = None
        self.tauBand = None