core.py 44.7 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
17

# workaround for matplotlib on X-less remote logins
18
if 'DISPLAY' in os.environ:
19
20
    import matplotlib.pyplot as plt
else:
21
22
    logging.info('No $DISPLAY environment variable found, so importing \
                  matplotlib.pyplot with non-interactive "Agg" backend.')
23
24
25
26
    import matplotlib
    matplotlib.use('Agg')
    import matplotlib.pyplot as plt

Gregory Ashton's avatar
Gregory Ashton committed
27
helper_functions.set_up_matplotlib_defaults()
28
args, tqdm = helper_functions.set_up_command_line_arguments()
29
detector_colors = {'h1': 'C0', 'l1': 'C1'}
Gregory Ashton's avatar
Gregory Ashton committed
30
31


Gregory Ashton's avatar
Gregory Ashton committed
32
class Bunch(object):
33
34
    """ Turns dictionary into object with attribute-style access

35
36
    Parameters
    ----------
37
38
39
40
41
42
43
44
45
46
47
48
49
50
    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
51
52
53
54
55
    def __init__(self, dictionary):
        self.__dict__.update(dictionary)


def read_par(filename=None, label=None, outdir=None, suffix='par',
56
57
             return_type='dict', comments=['%', '#'], raise_error=False):
    """ Read in a .par or .loudest file, returns a dict or Bunch of the data
58

Gregory Ashton's avatar
Gregory Ashton committed
59
60
    Parameters
    ----------
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
    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
77
78
79
80
81

    Returns
    -------
    d: Bunch or dict
        The par values as either a `Bunch` or dict type
82

83
84
85
86
    """
    if filename is None:
        filename = '{}/{}.{}'.format(outdir, label, suffix)
    if os.path.isfile(filename) is False:
87
        raise ValueError("No file {} found".format(filename))
Gregory Ashton's avatar
Gregory Ashton committed
88
89
    d = {}
    with open(filename, 'r') as f:
90
        d = _get_dictionary_from_lines(f, comments, raise_error)
Gregory Ashton's avatar
Gregory Ashton committed
91
92
93
94
95
96
    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
97
98


99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
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

    """
116
117
    d = {}
    for line in lines:
118
        if line[0] not in comments and len(line.split('=')) == 2:
119
120
121
            try:
                key, val = line.rstrip('\n').split('=')
                key = key.strip()
Gregory Ashton's avatar
Gregory Ashton committed
122
123
124
125
                try:
                    d[key] = np.float64(eval(val.rstrip('; ')))
                except NameError:
                    d[key] = val.rstrip('; ')
126
            except SyntaxError:
127
128
                if raise_error:
                    raise IOError('Line {} not understood'.format(line))
129
130
131
132
133
                pass
    return d


def predict_fstat(h0, cosi, psi, Alpha, Delta, Freq, sftfilepattern,
Gregory Ashton's avatar
Gregory Ashton committed
134
                  minStartTime, maxStartTime, IFO=None, assumeSqrtSX=None,
135
                  tempory_filename='fs.tmp', **kwargs):
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
    """ 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

    """
156

157
158
159
160
161
162
163
164
165
166
    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))
167
    if assumeSqrtSX:
168
        cl_pfs.append("--assumeSqrtSX={}".format(assumeSqrtSX))
169
    if IFO:
170
171
172
173
174
        if ',' in IFO:
            logging.warning('Multiple detector selection not available, using'
                            ' all available data')
        else:
            cl_pfs.append("--IFO={}".format(IFO))
175

176
177
    cl_pfs.append("--minStartTime={}".format(int(minStartTime)))
    cl_pfs.append("--maxStartTime={}".format(int(maxStartTime)))
178
    cl_pfs.append("--outputFstat={}".format(tempory_filename))
179

180
181
    cl_pfs = " ".join(cl_pfs)
    helper_functions.run_commandline(cl_pfs)
182
183
    d = read_par(filename=tempory_filename)
    os.remove(tempory_filename)
184
185
186
    return float(d['twoF_expected']), float(d['twoF_sigma'])


Gregory Ashton's avatar
Gregory Ashton committed
187
class BaseSearchClass(object):
188
    """ The base search class providing parent methods to other searches """
Gregory Ashton's avatar
Gregory Ashton committed
189

190
    def _add_log_file(self):
Gregory Ashton's avatar
Gregory Ashton committed
191
192
193
194
195
196
197
198
199
        """ 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)

200
    def _shift_matrix(self, n, dT):
Gregory Ashton's avatar
Gregory Ashton committed
201
202
203
204
        """ Generate the shift matrix

        Parameters
        ----------
205
        n : int
Gregory Ashton's avatar
Gregory Ashton committed
206
            The dimension of the shift-matrix to generate
207
        dT : float
Gregory Ashton's avatar
Gregory Ashton committed
208
209
210
211
            The time delta of the shift matrix

        Returns
        -------
212
213
        m : ndarray, shape (n,)
            The shift matrix.
Gregory Ashton's avatar
Gregory Ashton committed
214

215
        """
Gregory Ashton's avatar
Gregory Ashton committed
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
        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

231
    def _shift_coefficients(self, theta, dT):
Gregory Ashton's avatar
Gregory Ashton committed
232
233
234
235
        """ Shift a set of coefficients by dT

        Parameters
        ----------
236
237
        theta : array-like, shape (n,)
            Vector of the expansion coefficients to transform starting from the
Gregory Ashton's avatar
Gregory Ashton committed
238
            lowest degree e.g [phi, F0, F1,...].
239
240
        dT : float
            Difference between the two reference times as tref_new - tref_old.
Gregory Ashton's avatar
Gregory Ashton committed
241
242
243

        Returns
        -------
244
245
        theta_new : ndarray, shape (n,)
            Vector of the coefficients as evaluated as the new reference time.
Gregory Ashton's avatar
Gregory Ashton committed
246
247
        """
        n = len(theta)
248
        m = self._shift_matrix(n, dT)
Gregory Ashton's avatar
Gregory Ashton committed
249
250
        return np.dot(m, theta)

251
    def _calculate_thetas(self, theta, delta_thetas, tbounds, theta0_idx=0):
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
        """ 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
276
277
278
        thetas = [theta]
        for i, dt in enumerate(delta_thetas):
            if i < theta0_idx:
279
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
280
281
                    thetas[0], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch - dt
282
                thetas.insert(0, self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
283
284
285
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))

            elif i >= theta0_idx:
286
                pre_theta_at_ith_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
287
288
                    thetas[i], tbounds[i+1] - self.tref)
                post_theta_at_ith_glitch = pre_theta_at_ith_glitch + dt
289
                thetas.append(self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
290
                    post_theta_at_ith_glitch, self.tref - tbounds[i+1]))
291
        self.thetas_at_tref = thetas
Gregory Ashton's avatar
Gregory Ashton committed
292
293
        return thetas

294
    def _get_list_of_matching_sfts(self):
295
        """ Returns a list of sfts matching the attribute sftfilepattern """
296
297
        sftfilepatternlist = np.atleast_1d(self.sftfilepattern.split(';'))
        matches = [glob.glob(p) for p in sftfilepatternlist]
298
        matches = [item for sublist in matches for item in sublist]
299
300
301
302
        if len(matches) > 0:
            return matches
        else:
            raise IOError('No sfts found matching {}'.format(
303
                self.sftfilepattern))
304

305
306
    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
307

308
309
310
311
312
        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
313

314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
        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
329
330

    @helper_functions.initializer
331
    def __init__(self, tref, sftfilepattern=None, minStartTime=None,
David Keitel's avatar
David Keitel committed
332
333
                 maxStartTime=None, binary=False, BSGL=False,
                 transientWindowType=None, t0Band=None, tauBand=None,
334
                 detectors=None, minCoverFreq=None, maxCoverFreq=None,
335
336
                 injectSources=None, injectSqrtSX=None, assumeSqrtSX=None,
                 SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
337
338
339
        """
        Parameters
        ----------
340
        tref : int
Gregory Ashton's avatar
Gregory Ashton committed
341
            GPS seconds of the reference time.
342
        sftfilepattern : str
343
344
            Pattern to match SFTs using wildcards (*?) and ranges [0-9];
            mutiple patterns can be given separated by colons.
345
        minStartTime, maxStartTime : float GPStime
Gregory Ashton's avatar
Gregory Ashton committed
346
347
            Only use SFTs with timestemps starting from (including, excluding)
            this epoch
348
        binary : bool
Gregory Ashton's avatar
Gregory Ashton committed
349
            If true, search of binary parameters.
Gregory Ashton's avatar
Gregory Ashton committed
350
351
        BSGL : bool
            If true, compute the BSGL rather than the twoF value.
David Keitel's avatar
David Keitel committed
352
353
354
        transientWindowType: str
            If 'rect' or 'exp',
            allow for the Fstat to be computed over a transient range.
Gregory Ashton's avatar
Gregory Ashton committed
355
356
            ('none' instead of None explicitly calls the transient-window
            function, but with the full range, for debugging)
357
358
359
360
361
        t0Band, tauBand: int
            if >0, search t0 in (minStartTime,minStartTime+t0Band)
                   and tau in (2*Tsft,2*Tsft+tauBand).
            if =0, only compute CW Fstat with t0=minStartTime,
                   tau=maxStartTime-minStartTime.
362
        detectors : str
Gregory Ashton's avatar
Gregory Ashton committed
363
            Two character reference to the data to use, specify None for no
364
            contraint. If multiple-separate by comma.
365
        minCoverFreq, maxCoverFreq : float
Gregory Ashton's avatar
Gregory Ashton committed
366
367
368
            The min and max cover frequency passed to CreateFstatInput, if
            either is None the range of frequencies in the SFT less 1Hz is
            used.
369
        injectSources : dict or str
370
371
            Either a dictionary of the values to inject, or a string pointing
            to the .cff file to inject
372
        injectSqrtSX :
373
            Not yet implemented
374
        assumeSqrtSX : float
375
376
377
            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
378
        SSBprec : int
379
380
            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
381
382
383

        """

384
        self.set_ephemeris_files()
Gregory Ashton's avatar
Gregory Ashton committed
385
386
        self.init_computefstatistic_single_point()

387
388
389
390
391
392
393
394
395
396
397
    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
398
399
        if hasattr(self, 'SFTCatalog'):
            return
400
        if self.sftfilepattern is None:
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
            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
422
423
        logging.info('Initialising SFTCatalog')
        constraints = lalpulsar.SFTConstraints()
424
        if self.detectors:
425
            if ',' in self.detectors:
426
427
                logging.warning('Multiple detector selection not available,'
                                ' using all available data')
428
429
            else:
                constraints.detector = self.detectors
Gregory Ashton's avatar
Gregory Ashton committed
430
431
432
433
434
        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(
435
436
                     self.sftfilepattern))
        SFTCatalog = lalpulsar.SFTdataFind(self.sftfilepattern, constraints)
437

Gregory Ashton's avatar
Gregory Ashton committed
438
        SFT_timestamps = [d.header.epoch for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
439
        self.SFT_timestamps = [float(s) for s in SFT_timestamps]
440
441
        if len(SFT_timestamps) == 0:
            raise ValueError('Failed to load any data')
Gregory Ashton's avatar
Gregory Ashton committed
442
443
444
445
446
        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
447
            except ImportError:
Gregory Ashton's avatar
Gregory Ashton committed
448
                pass
449

450
        cl_tconv1 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[0]))
451
452
        output = helper_functions.run_commandline(cl_tconv1,
                                                  log_level=logging.DEBUG)
453
454
        tconvert1 = output.rstrip('\n')
        cl_tconv2 = 'lalapps_tconvert {}'.format(int(SFT_timestamps[-1]))
455
456
        output = helper_functions.run_commandline(cl_tconv2,
                                                  log_level=logging.DEBUG)
457
        tconvert2 = output.rstrip('\n')
Gregory Ashton's avatar
Gregory Ashton committed
458
459
        logging.info('Data spans from {} ({}) to {} ({})'.format(
            int(SFT_timestamps[0]),
460
            tconvert1,
Gregory Ashton's avatar
Gregory Ashton committed
461
            int(SFT_timestamps[-1]),
462
            tconvert2))
463
464
465
466
467
468
469
470
471
472
473
474
475

        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))

476
        return SFTCatalog
Gregory Ashton's avatar
Gregory Ashton committed
477
478
479
480

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

481
        SFTCatalog = self._get_SFTCatalog()
Gregory Ashton's avatar
Gregory Ashton committed
482
483
484
485
486
487

        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
488
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
489
490
491
492
493
494
            self.whatToCompute = lalpulsar.FSTATQ_ATOMS_PER_DET
        else:
            self.whatToCompute = lalpulsar.FSTATQ_2F

        FstatOAs = lalpulsar.FstatOptionalArgs()
        FstatOAs.randSeed = lalpulsar.FstatOptionalArgsDefaults.randSeed
495
496
497
498
499
        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
500
501
502
        FstatOAs.Dterms = lalpulsar.FstatOptionalArgsDefaults.Dterms
        FstatOAs.runningMedianWindow = lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow
        FstatOAs.FstatMethod = lalpulsar.FstatOptionalArgsDefaults.FstatMethod
503
504
505
506
507
508
509
510
        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
511
512
513
        FstatOAs.prevInput = lalpulsar.FstatOptionalArgsDefaults.prevInput
        FstatOAs.collectTiming = lalpulsar.FstatOptionalArgsDefaults.collectTiming

Gregory Ashton's avatar
Gregory Ashton committed
514
        if hasattr(self, 'injectSources') and type(self.injectSources) == dict:
Gregory Ashton's avatar
Gregory Ashton committed
515
516
517
518
519
520
521
522
523
524
            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
525
526
527
528
529
530
            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
531
532
533
534
            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
535
        elif hasattr(self, 'injectSources') and type(self.injectSources) == str:
536
537
538
539
            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
540
541
        else:
            FstatOAs.injectSources = lalpulsar.FstatOptionalArgsDefaults.injectSources
542
543
544
545
        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
546
        if self.minCoverFreq is None or self.maxCoverFreq is None:
547
            fAs = [d.header.f0 for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
548
            fBs = [d.header.f0 + (d.numBins-1)*d.header.deltaF
549
                   for d in SFTCatalog.data]
Gregory Ashton's avatar
Gregory Ashton committed
550
551
552
553
554
555
            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))

556
        self.FstatInput = lalpulsar.CreateFstatInput(SFTCatalog,
Gregory Ashton's avatar
Gregory Ashton committed
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
                                                     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:
577
                raise ValueError("Can't use BSGL with single detectors data")
Gregory Ashton's avatar
Gregory Ashton committed
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
            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
604
        if self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
605
606
            logging.info('Initialising transient parameters')
            self.windowRange = lalpulsar.transientWindowRange_t()
David Keitel's avatar
David Keitel committed
607
608
609
610
611
612
            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
613
614
615
616
                raise ValueError(
                    'Unknown window-type ({}) passed as input, [{}] allows.'
                    .format(self.transientWindowType,
                            ', '.join(transientWindowTypes)))
David Keitel's avatar
David Keitel committed
617
618
619

            self.Tsft = int(1.0/SFTCatalog.data[0].header.deltaF)
            if self.t0Band is None:
Gregory Ashton's avatar
Gregory Ashton committed
620
621
                self.windowRange.t0Band = 0
                self.windowRange.dt0 = 1
David Keitel's avatar
David Keitel committed
622
            else:
Gregory Ashton's avatar
Gregory Ashton committed
623
624
625
                if not isinstance(self.t0Band, int):
                    logging.warn('Casting non-integer t0Band={} to int...'
                                 .format(self.t0Band))
David Keitel's avatar
David Keitel committed
626
                    self.t0Band = int(self.t0Band)
Gregory Ashton's avatar
Gregory Ashton committed
627
628
                self.windowRange.t0Band = self.t0Band
                self.windowRange.dt0 = self.Tsft
David Keitel's avatar
David Keitel committed
629
630
            if self.tauBand is None:
                self.windowRange.tauBand = 0
Gregory Ashton's avatar
Gregory Ashton committed
631
                self.windowRange.dtau = 1
David Keitel's avatar
David Keitel committed
632
            else:
Gregory Ashton's avatar
Gregory Ashton committed
633
634
635
                if not isinstance(self.tauBand, int):
                    logging.warn('Casting non-integer tauBand={} to int...'
                                 .format(self.tauBand))
David Keitel's avatar
David Keitel committed
636
637
                    self.tauBand = int(self.tauBand)
                self.windowRange.tauBand = self.tauBand
Gregory Ashton's avatar
Gregory Ashton committed
638
                self.windowRange.dtau = self.Tsft
Gregory Ashton's avatar
Gregory Ashton committed
639

640
641
642
    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
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
        """ 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
661
        if not self.transientWindowType:
Gregory Ashton's avatar
Gregory Ashton committed
662
663
664
665
666
667
668
669
670
671
672
            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
673
674
675
676
677
        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
        else:
Gregory Ashton's avatar
Gregory Ashton committed
678
679
            # grid search: start at minimum tau required for nondegenerate
            # F-stat computation
David Keitel's avatar
David Keitel committed
680
            self.windowRange.tau = int(2*self.Tsft)
Gregory Ashton's avatar
Gregory Ashton committed
681

682
        self.FstatMap = lalpulsar.ComputeTransientFstatMap(
Gregory Ashton's avatar
Gregory Ashton committed
683
            self.FstatResults.multiFatoms[0], self.windowRange, False)
684
        F_mn = self.FstatMap.F_mn.data
Gregory Ashton's avatar
Gregory Ashton committed
685

686
        twoF = 2*np.max(F_mn)
Gregory Ashton's avatar
Gregory Ashton committed
687
        if self.BSGL is False:
688
689
690
691
            if np.isnan(twoF):
                return 0
            else:
                return twoF
Gregory Ashton's avatar
Gregory Ashton committed
692
693
694
695
696
697
698
699
700
701

        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)

702
703
704
705
706
        # 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?
707
        idx_maxTwoF = np.argmax(F_mn)
708
709
710

        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
711
        log10_BSGL = lalpulsar.ComputeBSGL(
712
                twoF, self.twoFX, self.BSGLSetup)
Gregory Ashton's avatar
Gregory Ashton committed
713
714
715
716
717
718

        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,
719
720
                                  ):
        """ Calculate the cumulative twoF along the obseration span
721
722
723

        Parameters
        ----------
724
725
        F0, F1, F2, Alpha, Delta: float
            Parameters at which to compute the cumulative twoF
726
727
        asini, period, ecc, tp, argp: float, optional
            Binary parameters at which to compute the cumulative 2F
728
729
730
731
732
733
        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

734
735
736
        Notes
        -----
        The minimum cumulatibe twoF is hard-coded to be computed over
737
738
739
740
741
742
        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
743
        tstart = np.max([SFTminStartTime, tstart])
744
745
746
        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
747
        twoFs = []
David Keitel's avatar
David Keitel committed
748
749
750
        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
751
752
            self.init_computefstatistic_single_point()
        for tau in taus:
753
            detstat = self.get_fullycoherent_twoF(
Gregory Ashton's avatar
Gregory Ashton committed
754
755
                tstart=tstart, tend=tstart+tau, F0=F0, F1=F1, F2=F2,
                Alpha=Alpha, Delta=Delta, asini=asini, period=period, ecc=ecc,
756
757
                tp=tp, argp=argp)
            twoFs.append(detstat)
Gregory Ashton's avatar
Gregory Ashton committed
758
759
760

        return taus, np.array(twoFs)

761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
    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
781
782
783
784
785

        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')
786
            loudest = read_par(label=label, outdir=outdir, suffix='loudest')
Gregory Ashton's avatar
Gregory Ashton committed
787
788
            pfs_input = {key: loudest[key] for key in
                         ['h0', 'cosi', 'psi', 'Alpha', 'Delta', 'Freq']}
789
790
791
        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,
792
                             sftfilepattern=self.sftfilepattern, IFO=IFO,
793
794
795
796
                             **pfs_input) for t in times]
        pfs, pfs_sigma = np.array(out).T
        return times, pfs, pfs_sigma

797
798
    def plot_twoF_cumulative(self, label, outdir, add_pfs=False, N=15,
                             injectSources=None, ax=None, c='k', savefig=True,
799
                             title=None, plt_label=None, **kwargs):
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
        """ 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
817
818
        title, plt_label: str
            Figure title and label
819
820
821
822
823
824
825
826
827

        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
828
829
        if ax is None:
            fig, ax = plt.subplots()
Gregory Ashton's avatar
Gregory Ashton committed
830
831
832
833
834
835
836
        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
837
838

        taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
839
        ax.plot(taus/86400., twoFs, label=plt_label, color=c)
840
        if len(self.detector_names) > 1:
841
842
            detector_names = self.detector_names
            detectors = self.detectors
843
844
845
846
            for d in self.detector_names:
                self.detectors = d
                self.init_computefstatistic_single_point()
                taus, twoFs = self.calculate_twoF_cumulative(**kwargs)
847
848
849
850
851
852
                ax.plot(taus/86400., twoFs, label='{}'.format(d),
                        color=detector_colors[d.lower()])
            self.detectors = detectors
            self.detector_names = detector_names

        if add_pfs:
853
854
            times, pfs, pfs_sigma = self._calculate_predict_fstat_cumulative(
                N=N, label=label, outdir=outdir, pfs_input=pfs_input)
855
856
            ax.fill_between(
                (times-self.minStartTime)/86400., pfs-pfs_sigma, pfs+pfs_sigma,
Gregory Ashton's avatar
Gregory Ashton committed
857
                color=c,
858
859
                label=(r'Predicted $\langle 2\mathcal{F} '
                       r'\rangle\pm $ 1-$\sigma$ band'),
860
861
862
                zorder=-10, alpha=0.2)
            if len(self.detector_names) > 1:
                for d in self.detector_names:
863
864
865
866
                    out = self._calculate_predict_fstat_cumulative(
                        N=N, label=label, outdir=outdir, IFO=d.upper(),
                        pfs_input=pfs_input)
                    times, pfs, pfs_sigma = out
867
868
869
870
871
872
873
874
                    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)
875

Gregory Ashton's avatar
Gregory Ashton committed
876
877
878
879
880
881
882
        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)
883
884
        if plt_label:
            ax.legend(frameon=False, loc=2, fontsize=6)
Gregory Ashton's avatar
Gregory Ashton committed
885
886
887
888
889
890
891
892
893
894
        if title:
            ax.set_title(title)
        if savefig:
            plt.tight_layout()
            plt.savefig('{}/{}_twoFcumulative.png'.format(outdir, label))
            return taus, twoFs
        else:
            return ax


895
class SemiCoherentSearch(ComputeFstat):
Gregory Ashton's avatar
Gregory Ashton committed
896
897
898
    """ A semi-coherent search """

    @helper_functions.initializer
899
    def __init__(self, label, outdir, tref, nsegs=None, sftfilepattern=None,
Gregory Ashton's avatar
Gregory Ashton committed
900
901
                 binary=False, BSGL=False, minStartTime=None,
                 maxStartTime=None, minCoverFreq=None, maxCoverFreq=None,
902
903
                 detectors=None, injectSources=None, assumeSqrtSX=None,
                 SSBprec=None):
Gregory Ashton's avatar
Gregory Ashton committed
904
905
906
907
908
909
910
911
912
        """
        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
913
914
915
        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
916
917
918
919
920

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

        self.fs_file_name = "{}/{}_FS.dat".format(self.outdir, self.label)
921
        self.set_ephemeris_files()
David Keitel's avatar
David Keitel committed
922
923
924
        self.transientWindowType = 'rect'
        self.t0Band  = None
        self.tauBand = None
Gregory Ashton's avatar
Gregory Ashton committed
925
926
927
928
929
930
931
        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))
David Keitel's avatar
David Keitel committed
932
        self.transientWindowType = 'rect'
Gregory Ashton's avatar
Gregory Ashton committed
933
934
935
        self.whatToCompute = lalpulsar.FSTATQ_2F+lalpulsar.FSTATQ_ATOMS_PER_DET
        self.tboundaries = np.linspace(self.minStartTime, self.maxStartTime,
                                       self.nsegs+1)
936
        self.Tcoh = self.tboundaries[1] - self.tboundaries[0]
Gregory Ashton's avatar
Gregory Ashton committed
937

938
939
940
941
942
943
944
945
946
        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
947

948
    def get_semicoherent_twoF(
949
950
951
952
953
            self, F0, F1, F2, Alpha, Delta, asini=None,
            period=None, ecc=None, tp=None, argp=None,
            record_segments=False):
        """ Returns twoF or ln(BSGL) semi-coherently at a single point """

Gregory Ashton's avatar
Gregory Ashton committed
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
        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
971
        #if not self.transientWindowType:
972
973
974
975
976
977
978
979
        #    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
980
981

        detStat = 0
982
983
        if record_segments:
            self.detStat_per_segment = []
Gregory Ashton's avatar
Gregory Ashton committed
984

985
986
987
        self.windowRange.tau = int(self.Tcoh)  # TYPE UINT4
        for tstart in self.tboundaries[:-1]:
            d_detStat = self._get_per_segment_det_stat(tstart)
988
989
990
            detStat += d_detStat
            if record_segments:
                self.detStat_per_segment.append(d_detStat)
Gregory Ashton's avatar
Gregory Ashton committed
991
992
993

        return detStat

994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
    def _get_per_segment_det_stat(self, tstart):
        self.windowRange.t0 = int(tstart)  # TYPE UINT4

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

        if self.BSGL is False:
            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))
        if np.isnan(d_detStat):
            logging.debug('NaNs in semi-coherent twoF treated as zero')
            d_detStat = 0

        return d_detStat

Gregory Ashton's avatar
Gregory Ashton committed
1023

1024
class SemiCoherentGlitchSearch(ComputeFstat):
Gregory Ashton's avatar
Gregory Ashton committed
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
    """ 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,
1035
                 nglitch=1, sftfilepattern=None, theta0_idx=0, BSGL=False,
1036
                 minCoverFreq=None, maxCoverFreq=None, assumeSqrtSX=None,
1037
                 detectors=None, SSBprec=None, injectSources=None):
Gregory Ashton's avatar
Gregory Ashton committed
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
        """
        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).
1048
1049
1050
        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
1051
1052
1053
1054
1055
1056
1057
1058
1059
        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)
1060
        self.set_ephemeris_files()
David Keitel's avatar
David Keitel committed
1061
1062
1063
1064
        self.transientWindowType = 'rect'
        self.t0Band  = None
        self.tauBand = None
        self.binary  = False
Gregory Ashton's avatar
Gregory Ashton committed
1065
1066
        self.init_computefstatistic_single_point()

1067
    def get_semicoherent_nglitch_twoF(self, F0, F1, F2, Alpha, Delta, *args):
Gregory Ashton's avatar
Gregory Ashton committed
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
        """ 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)

1081
        thetas = self._calculate_thetas(theta, delta_thetas, tboundaries,
1082
                                        theta0_idx=self.theta0_idx)
Gregory Ashton's avatar
Gregory Ashton committed
1083
1084
1085
1086

        twoFSum = 0
        for i, theta_i_at_tref in enumerate(thetas):
            ts, te = tboundaries[i], tboundaries[i+1]
1087
            if te - ts > 1800:
1088
1089
1090
1091
                twoFVal = self.get_fullycoherent_twoF(
                    ts, te, theta_i_at_tref[1], theta_i_at_tref[2],
                    theta_i_at_tref[3], Alpha, Delta)
                twoFSum += twoFVal
Gregory Ashton's avatar
Gregory Ashton committed
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108

        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

1109
        theta_at_glitch = self._shift_coefficients(theta, tglitch - tref)
Gregory Ashton's avatar
Gregory Ashton committed
1110
        theta_post_glitch_at_glitch = theta_at_glitch + delta_theta
1111
        theta_post_glitch = self._shift_coefficients(
Gregory Ashton's avatar
Gregory Ashton committed
1112
1113
            theta_post_glitch_at_glitch, tref - tglitch)

1114
        twoFsegA = self.get_fullycoherent_twoF(
Gregory Ashton's avatar
Gregory Ashton committed
1115
1116
1117
1118
1119
1120
            self.minStartTime, tglitch, theta[0], theta[1], theta[2], Alpha,
            Delta)

        if tglitch == self.maxStartTime:
            return twoFsegA

1121
        twoFsegB = self.get_fullycoherent_twoF(
Gregory Ashton's avatar
Gregory Ashton committed
1122
1123
1124
1125
1126
            tglitch, self.maxStartTime, theta_post_glitch[0],
            theta_post_glitch[1], theta_post_glitch[2], Alpha,
            Delta)

        return twoFsegA + twoFsegB