def analyze(self, methods=['GRs']):
self.log.info('Analyzing %d files.' % self.background.nsets)
self.log.debug('Producing search template.')
search = {
m: templates.Signal(self.detector, self.psr, m, 0, self.t)
for m in methods
}
self.log.debug('Setting up results') # NEEDS CORRECTION!
self.results = Results(self.detector,
self.psr,
methods=methods,
hinj=self.hinj,
kind=self.injkind,
pdif=self.pdif)
self.log.debug('Looping over files')
for n in range(self.background.nsets):
self.log.debug('File %i.' % n)
try:
back_file = pd.HDFStore(self.background.path + str(n), 'r')
data = back_file[self.psr]
finally:
back_file.close()
self.log.debug('Looping over instantiations.')
for inst in data.columns:
inst_number = int(n * self.background.filesize + inst)
self.log.info('%i/%i ' % (inst_number, len(self.hinj) - 1))
self.log.debug('Selecting psi, iota, phi0.')
psi = random.uniform(self.pol_range[0], self.pol_range[1])
iota = random.uniform(self.inc_range[0], self.inc_range[1])
psi_inj = random.uniform(self.pol_range[0], self.pol_range[1])
iota_inj = random.uniform(self.inc_range[0], self.inc_range[1])
phi0 = random.uniform(self.phi0_range[0], self.phi0_range[1])
self.log.debug('Search with POL: %f, INC: %f' % (psi, iota))
self.log.debug('Loop over search methods.')
# note: important that this follows inst loop to get same psi and iota
for m in methods:
d = data[inst]
# inject if necessary
h = self.hinj[inst_number]
self.log.debug('I! %(psi_inj)f %(iota_inj)f %(phi0)f' %
locals())
d += h * self.injection.simulate(
psi_inj, iota_inj, phase=phi0)
self.log.debug('Get design matrix.')
designMatrix = search[m].design_matrix(psi, iota)
A = designMatrix.div(self.sg, axis=0)
b = d / self.sg
self.log.debug('SVD decomposition.')
svd = np.linalg.svd(A, full_matrices=False)
U = pd.DataFrame(svd[0], columns=A.columns, index=A.index)
W = pd.DataFrame(np.diag(1. / svd[1]),
index=A.columns,
columns=A.columns)
V = pd.DataFrame(svd[2],
index=A.columns,
columns=A.columns)
cov = V.T.dot(W**2).dot(V) # covariance matrix
VtW = V.T.dot(W)
# need to make U complex before dotting with b
Utb = (U + 0j).mul(b, axis=0).sum(axis=0)
a = VtW.dot(Utb.T) # results
# NEEDS MODIFYICATION FROM HERE ON:
self.log.debug('Average h0')
self.results.h[m][inst_number] = (abs(a).sum()) / len(a)
self.log.debug('Significance')
self.results.s[m][inst_number] = abs(
np.dot(a.conj(), np.linalg.solve(cov, a)))
## Save
self.results.save()
def __init__(self,
nh0,
nhs,
detector='H1',
psr='J0534+2200',
pdif='p',
pdif_s='p',
frange=[1.0e-7, 1.0e-5],
hinjrange=[1.0E-27, 1.0E-23],
range=[],
filesize=100):
# system info
self.detector = detector
self.psr = psr
self.log = logging.getLogger('Frequentist')
self.log.debug('Initializing frequentist ST sensitivity analysis.')
# data info
self.freq = np.linspace(frange[0], frange[1], nh0)
self.background = Background(detector, psr, self.freq, filesize)
self.background.get()
self.log.debug('Obtaining time.')
self.t = self.background.seed.finehet.index
self.log.debug('Obtaining sigma.')
sigma = Sigma(self.detector, self.psr, self.background.seed.finehet)
self.sg = sigma.std
self.log.debug('Preparing injections.')
inj = np.linspace(hinjrange[0], hinjrange[1], ninj)
self.pdif = pdif
self.pdif_s = pdif_s
self.injkind = 'GRs'
self.injection = templates.Signal(
detector,
psr,
self.t,
pdif=pdif,
pdif_s=pdif_s,
kind=injkind,
)
self.log.debug('Preparing parameter ranges.')
src = self.injection.response.src
if 'psi' in rangeparam or rangeparam == 'all':
self.pol_range = [
src.param['POL'] - src.param['POL error'],
src.param['POL'] + src.param['POL error']
]
else:
self.pol_range = [src.param['POL'], src.param['POL']]
if 'iota' in rangeparam or rangeparam == 'all':
self.inc_range = [
src.param['INC'] - src.param['INC error'],
src.param['INC'] + src.param['INC error']
]
else:
self.inc_range = [src.param['INC'], src.param['INC']]
if 'phi0' in rangeparam or rangeparam == 'all':
self.phi0_range = [0., np.pi / 2]
else:
self.phi0_range = [0., 0.]
def __init__(self,
detector,
psr,
nfreq,
injkind,
pdif,
ninj,
rangeparam=[],
frange=[1.0e-7, 1.0e-5],
hinjrange=[1.0E-27, 1.0E-23],
filesize=100):
# system info
self.detector = detector
self.psr = psr
self.log = logging.getLogger('Frequentist')
self.log.debug('Initializing frequentist sensitivity analysis.')
# data info
self.freq = np.linspace(frange[0], frange[1], nfreq)
self.background = Background(detector, psr, self.freq, filesize)
self.background.get()
self.log.debug('Obtaining time.')
self.t = self.background.seed.finehet.index
self.log.debug('Obtaining sigma.')
sigma = Sigma(self.detector, self.psr, self.background.seed.finehet)
self.sg = sigma.std
self.log.debug('Preparing injection strengths.')
inj = np.linspace(hinjrange[0], hinjrange[1], ninj)
injLocations = [
int(x) for x in np.linspace(0, nfreq, ninj, endpoint=False)
]
self.hinj = np.zeros(nfreq)
self.hinj[injLocations] = inj
self.pdif = pdif
self.injkind = injkind
self.injection = templates.Signal(detector, psr, injkind, pdif, self.t)
src = self.injection.response.src
self.log.debug('Preparing parameter ranges.')
if 'psi' in rangeparam or rangeparam == 'all':
self.pol_range = [
src.param['POL'] - src.param['POL error'],
src.param['POL'] + src.param['POL error']
]
else:
self.pol_range = [src.param['POL'], src.param['POL']]
if 'iota' in rangeparam or rangeparam == 'all':
self.inc_range = [
src.param['INC'] - src.param['INC error'],
src.param['INC'] + src.param['INC error']
]
else:
self.inc_range = [src.param['INC'], src.param['INC']]
if 'phi0' in rangeparam or rangeparam == 'all':
self.phi0_range = [0., np.pi / 2]
else:
self.phi0_range = [0., 0.]
def analyze(self, methods):
print 'Analyzing %d files.' % self.background.nsets
# search info
search = {
m: templates.Signal(self.detector, self.psr, m, 0, self.t)
for m in methods
}
# results
self.results = Results(self.detector,
self.psr,
methods=methods,
hinj=self.hinj,
kind=self.injkind,
pdif=self.pdif)
# loop over files
for n in range(self.background.nsets):
try:
back_file = pd.HDFStore(self.background.path + str(n), 'r')
data = back_file[self.psr]
finally:
back_file.close()
# loop over instantiations
for inst in data.columns:
inst_number = int(n * self.background.filesize + inst)
print '%i/%i ' % (inst_number, len(self.hinj) - 1),
# select psi, iota and phi0
psi = random.uniform(self.pol_range[0], self.pol_range[1])
iota = random.uniform(self.inc_range[0], self.inc_range[1])
psi_inj = random.uniform(self.pol_range[0], self.pol_range[1])
iota_inj = random.uniform(self.inc_range[0], self.inc_range[1])
phi0 = random.uniform(self.phi0_range[0], self.phi0_range[1])
print psi, iota, phi0
# loop over search methods
# note: important that this follows inst loop to get same psi and iota
for m in methods:
d = data[inst]
# inject if necessary
h = self.hinj[inst_number]
if h != 0:
print self.injection.kind + str(self.injection.pdif),
print 'I! %(psi_inj)f %(iota_inj)f %(phi0)f' % locals()
d += h * self.injection.simulate(
psi_inj, iota_inj, phase=phi0)
# get design matrix
designMatrix = search[m].design_matrix(psi, iota)
A = designMatrix.div(self.sg, axis=0)
b = d / self.sg
# SVD DECOMPOSITION
svd = np.linalg.svd(A, full_matrices=False)
U = pd.DataFrame(svd[0], columns=A.columns, index=A.index)
W = pd.DataFrame(np.diag(1. / svd[1]),
index=A.columns,
columns=A.columns)
V = pd.DataFrame(svd[2],
index=A.columns,
columns=A.columns)
cov = V.T.dot(W**2).dot(V) # covariance matrix
VtW = V.T.dot(W)
# need to make U complex before dotting with b
Utb = (U + 0j).mul(b, axis=0).sum(axis=0)
a = VtW.dot(Utb.T) # results
# average h0
self.results.h[m][inst_number] = (abs(a).sum()) / len(a)
# significance
self.results.s[m][inst_number] = abs(
np.dot(a.conj(), np.linalg.solve(cov, a)))
## Save
self.results.save()
def __init__(self,
detector,
psr,
nfreq,
injkind,
pdif,
ninj,
rangeparam=[],
frange=[1.0e-7, 1.0e-5],
hinjrange=[1.0E-27, 1.0E-23],
filesize=100):
# system info
self.detector = detector
self.psr = psr
# data info
self.freq = np.linspace(frange[0], frange[1], nfreq)
print 'Getting background.'
self.background = Background(detector, psr, self.freq, filesize)
self.background.get()
self.t = self.background.seed.finehet.index
sigma = Sigma(self.detector, self.psr, self.background.seed.finehet)
self.sg = 2 * sigma.std
# injection info
inj = np.linspace(hinjrange[0], hinjrange[1], ninj)
injLocations = [
int(x) for x in np.linspace(0, nfreq, ninj, endpoint=False)
]
self.hinj = np.zeros(nfreq)
self.hinj[injLocations] = inj
self.pdif = pdif
self.injkind = injkind
self.injection = templates.Signal(detector, psr, injkind, pdif, self.t)
src = self.injection.response.src
# range info
if 'psi' in rangeparam or rangeparam == 'all':
self.pol_range = [
src.param['POL'] - src.param['POL error'],
src.param['POL'] + src.param['POL error']
]
else:
self.pol_range = [src.param['POL'], src.param['POL']]
if 'iota' in rangeparam or rangeparam == 'all':
self.inc_range = [
src.param['INC'] - src.param['INC error'],
src.param['INC'] + src.param['INC error']
]
else:
self.inc_range = [src.param['INC'], src.param['INC']]
if 'phi0' in rangeparam or rangeparam == 'all':
self.phi0_range = [0., np.pi / 2]
else:
self.phi0_range = [0., 0.]
days = 1
t = np.array([x + 630720013 for x in range(0, int(days * sd.ss), 60)])
det = 'H1'
kind = 'GR'
pdifs = ['0', 'p', 'm']
phi0 = 5.
plt.figure()
for p in pdifs:
sig = templates.Signal('H1', 'J0534+2200', 'GR', p, t)
s = sig.simulate(sig.response.src.param['POL'],
sig.response.src.param['INC'],
phase=phi0)
s.real.plot(label=p)
plt.title('Crab LHO GR signal (Re) $\phi_0=$' + str(phi0))
plt.legend(numpoints=1, loc=4)
plt.figure()
for p in pdifs:
sig = templates.Signal('H1', 'J0534+2200', 'GR', p, t)