# Add options for individual detectors
for detector in lal.CachedDetectors:
name = detector.frDetector.name
prefix = detector.frDetector.prefix
detectors.append(prefix)
parser.add_option('--' + prefix, choices=psd_names, metavar='func',
help='PSD function for {0} detector [optional]'.format(name))
# Parse command line.
opts, args = parser.parse_args()
if args:
parser.error('Did not expect any positional command line arguments')
psds = {}
n = int(opts.f_max // opts.df)
f = np.arange(n) * opts.df
for detector in detectors:
psd_name = getattr(opts, detector)
if psd_name is None:
continue
psd_func = getattr(lalsimulation, psd_name_prefix + psd_name)
series = lal.CreateREAL8FrequencySeries(None, 0, 0, opts.df, lal.SecondUnit, n)
series.data.data = vectorize_swig_psd_func(psd_func)(f)
psds[detector] = series
glue.ligolw.utils.write_filename(
lal.series.make_psd_xmldoc(psds), opts.output,
gz=(os.path.splitext(opts.output)[-1]==".gz"))
psds = {}
n = int(opts.f_max // opts.df)
f = np.arange(n) * opts.df
for detector in detectors:
psd_name = getattr(opts, detector)
scale = 1 / np.square(getattr(opts, detector + '_scale'))
if psd_name is None:
continue
func = getattr(lalsimulation, psd_name_prefix + psd_name)
series = lal.CreateREAL8FrequencySeries(
psd_name, 0, 0, opts.df, lal.SecondUnit, n)
if '(double f) -> double' in func.__doc__:
series.data.data = vectorize_swig_psd_func(
psd_name_prefix + psd_name)(f)
else:
func(series, 0.0)
# Find indices of first and last nonzero samples.
nonzero = np.flatnonzero(series.data.data)
# FIXME: int cast seems to be needed on old versions of Numpy
first_nonzero = int(nonzero[0])
last_nonzero = int(nonzero[-1])
# Truncate
series = lal.CutREAL8FrequencySeries(
series, first_nonzero, last_nonzero - first_nonzero + 1)
series.f0 = first_nonzero * series.deltaF
series.name = psd_name
psds = {}
n = int(opts.f_max // opts.df)
f = np.arange(n) * opts.df
for detector in detectors:
psd_name = getattr(opts, detector)
scale = 1 / np.square(getattr(opts, detector + '_scale'))
if psd_name is None:
continue
func = getattr(lalsimulation, psd_name_prefix + psd_name)
series = lal.CreateREAL8FrequencySeries(psd_name, 0, 0, opts.df,
lal.SecondUnit, n)
if '(double f) -> double' in func.__doc__:
series.data.data = vectorize_swig_psd_func(psd_name_prefix +
psd_name)(f)
else:
func(series, 0.0)
# Find indices of first and last nonzero samples.
nonzero = np.flatnonzero(series.data.data)
# FIXME: int cast seems to be needed on old versions of Numpy
first_nonzero = int(nonzero[0])
last_nonzero = int(nonzero[-1])
# Truncate
series = lal.CutREAL8FrequencySeries(series, first_nonzero,
last_nonzero - first_nonzero + 1)
series.f0 = first_nonzero * series.deltaF
series.name = psd_name
