From 0bb1113d0d1c50e2a0b37e05c92bd49d8d0be00e Mon Sep 17 00:00:00 2001
From: Moritz Huebner <moritz.huebner@ligo.org>
Date: Tue, 28 Apr 2020 01:14:46 -0500
Subject: [PATCH] Reduce redundant code
---
bilby/core/grid.py | 32 ++-------
bilby/core/prior/base.py | 14 ++--
bilby/core/prior/joint.py | 8 +--
bilby/core/result.py | 23 +------
bilby/core/sampler/dynamic_dynesty.py | 16 +----
bilby/core/sampler/dynesty.py | 19 +++---
bilby/core/sampler/emcee.py | 18 +++--
bilby/core/sampler/kombine.py | 18 ++---
bilby/core/sampler/pymc3.py | 95 +++++++++++----------------
bilby/core/utils.py | 44 +++++++++++++
bilby/gw/likelihood.py | 29 ++++----
bilby/gw/utils.py | 38 ++++-------
12 files changed, 148 insertions(+), 206 deletions(-)
diff --git a/bilby/core/grid.py b/bilby/core/grid.py
index ee09e2fec..42fb58dd0 100644
--- a/bilby/core/grid.py
+++ b/bilby/core/grid.py
@@ -8,7 +8,7 @@ from collections import OrderedDict
from .prior import Prior, PriorDict
from .utils import (logtrapzexp, check_directory_exists_and_if_not_mkdir,
logger)
-from .utils import BilbyJsonEncoder, decode_bilby_json
+from .utils import BilbyJsonEncoder, load_json, move_old_file
from .result import FileMovedError
@@ -397,18 +397,7 @@ class Grid(object):
filename = grid_file_name(outdir, self.label, gzip)
- if os.path.isfile(filename):
- if overwrite:
- logger.debug('Removing existing file {}'.format(filename))
- os.remove(filename)
- else:
- logger.debug(
- 'Renaming existing file {} to {}.old'.format(filename,
- filename))
- os.rename(filename, filename + '.old')
-
- logger.debug("Saving result to {}".format(filename))
-
+ move_old_file(filename, overwrite)
dictionary = self._get_save_data_dictionary()
try:
@@ -452,23 +441,14 @@ class Grid(object):
"""
- if filename is not None:
- fname = filename
- else:
+ if filename is None:
if (outdir is None) and (label is None):
raise ValueError("No information given to load file")
else:
- fname = grid_file_name(outdir, label, gzip)
+ filename = grid_file_name(outdir, label, gzip)
- if os.path.isfile(fname):
- if gzip or os.path.splitext(fname)[1].lstrip('.') == 'gz':
- import gzip
- with gzip.GzipFile(fname, 'r') as file:
- json_str = file.read().decode('utf-8')
- dictionary = json.loads(json_str, object_hook=decode_bilby_json)
- else:
- with open(fname, 'r') as file:
- dictionary = json.load(file, object_hook=decode_bilby_json)
+ if os.path.isfile(filename):
+ dictionary = load_json(filename, gzip)
try:
grid = cls(likelihood=None, priors=dictionary['priors'],
grid_size=dictionary['sample_points'],
diff --git a/bilby/core/prior/base.py b/bilby/core/prior/base.py
index 29efe925d..db5880da1 100644
--- a/bilby/core/prior/base.py
+++ b/bilby/core/prior/base.py
@@ -8,7 +8,8 @@ import scipy.stats
from scipy.integrate import cumtrapz
from scipy.interpolate import interp1d
-from bilby.core.utils import infer_args_from_method, BilbyJsonEncoder, decode_bilby_json, logger
+from bilby.core.utils import infer_args_from_method, BilbyJsonEncoder, decode_bilby_json, logger, \
+ get_dict_with_properties
class Prior(object):
@@ -280,15 +281,8 @@ class Prior(object):
def get_instantiation_dict(self):
subclass_args = infer_args_from_method(self.__init__)
- property_names = [p for p in dir(self.__class__)
- if isinstance(getattr(self.__class__, p), property)]
- dict_with_properties = self.__dict__.copy()
- for key in property_names:
- dict_with_properties[key] = getattr(self, key)
- instantiation_dict = dict()
- for key in subclass_args:
- instantiation_dict[key] = dict_with_properties[key]
- return instantiation_dict
+ dict_with_properties = get_dict_with_properties(self)
+ return {key: dict_with_properties[key] for key in subclass_args}
@property
def boundary(self):
diff --git a/bilby/core/prior/joint.py b/bilby/core/prior/joint.py
index 613183f87..bac8fceb5 100644
--- a/bilby/core/prior/joint.py
+++ b/bilby/core/prior/joint.py
@@ -3,7 +3,7 @@ import scipy.stats
from scipy.special import erfinv
from .base import Prior, PriorException
-from bilby.core.utils import logger, infer_args_from_method
+from bilby.core.utils import logger, infer_args_from_method, get_dict_with_properties
class BaseJointPriorDist(object):
@@ -105,11 +105,7 @@ class BaseJointPriorDist(object):
def get_instantiation_dict(self):
subclass_args = infer_args_from_method(self.__init__)
- property_names = [p for p in dir(self.__class__)
- if isinstance(getattr(self.__class__, p), property)]
- dict_with_properties = self.__dict__.copy()
- for key in property_names:
- dict_with_properties[key] = getattr(self, key)
+ dict_with_properties = get_dict_with_properties(self)
instantiation_dict = dict()
for key in subclass_args:
if isinstance(dict_with_properties[key], list):
diff --git a/bilby/core/result.py b/bilby/core/result.py
index 5bc278e58..8236f24b8 100644
--- a/bilby/core/result.py
+++ b/bilby/core/result.py
@@ -22,7 +22,7 @@ from .utils import (
check_directory_exists_and_if_not_mkdir,
latex_plot_format, safe_save_figure,
)
-from .utils import BilbyJsonEncoder, decode_bilby_json
+from .utils import BilbyJsonEncoder, load_json, move_old_file
from .prior import Prior, PriorDict, DeltaFunction
@@ -259,14 +259,7 @@ class Result(object):
filename = _determine_file_name(filename, outdir, label, 'json', gzip)
if os.path.isfile(filename):
- if gzip or os.path.splitext(filename)[1].lstrip('.') == 'gz':
- import gzip
- with gzip.GzipFile(filename, 'r') as file:
- json_str = file.read().decode('utf-8')
- dictionary = json.loads(json_str, object_hook=decode_bilby_json)
- else:
- with open(filename, 'r') as file:
- dictionary = json.load(file, object_hook=decode_bilby_json)
+ dictionary = load_json(filename, gzip)
try:
return cls(**dictionary)
except TypeError as e:
@@ -468,17 +461,7 @@ class Result(object):
if filename is None:
filename = result_file_name(outdir, self.label, extension, gzip)
- if os.path.isfile(filename):
- if overwrite:
- logger.debug('Removing existing file {}'.format(filename))
- os.remove(filename)
- else:
- logger.debug(
- 'Renaming existing file {} to {}.old'.format(filename,
- filename))
- os.rename(filename, filename + '.old')
-
- logger.debug("Saving result to {}".format(filename))
+ move_old_file(filename, overwrite)
# Convert the prior to a string representation for saving on disk
dictionary = self._get_save_data_dictionary()
diff --git a/bilby/core/sampler/dynamic_dynesty.py b/bilby/core/sampler/dynamic_dynesty.py
index 4e7e1f56d..48d726e4a 100644
--- a/bilby/core/sampler/dynamic_dynesty.py
+++ b/bilby/core/sampler/dynamic_dynesty.py
@@ -5,7 +5,6 @@ import dill as pickle
import signal
import numpy as np
-from pandas import DataFrame
from ..utils import logger, check_directory_exists_and_if_not_mkdir
from .base_sampler import Sampler
@@ -139,20 +138,7 @@ class DynamicDynesty(Dynesty):
print("")
# self.result.sampler_output = out
- weights = np.exp(out['logwt'] - out['logz'][-1])
- nested_samples = DataFrame(
- out.samples, columns=self.search_parameter_keys)
- nested_samples['weights'] = weights
- nested_samples['log_likelihood'] = out.logl
-
- self.result.samples = dynesty.utils.resample_equal(out.samples, weights)
- self.result.nested_samples = nested_samples
- self.result.log_likelihood_evaluations = self.reorder_loglikelihoods(
- unsorted_loglikelihoods=out.logl, unsorted_samples=out.samples,
- sorted_samples=self.result.samples)
- self.result.log_evidence = out.logz[-1]
- self.result.log_evidence_err = out.logzerr[-1]
-
+ self._generate_result(out)
if self.plot:
self.generate_trace_plots(out)
diff --git a/bilby/core/sampler/dynesty.py b/bilby/core/sampler/dynesty.py
index 688efc417..9c2c6683c 100644
--- a/bilby/core/sampler/dynesty.py
+++ b/bilby/core/sampler/dynesty.py
@@ -357,26 +357,29 @@ class Dynesty(NestedSampler):
with open(dynesty_result, 'wb') as file:
pickle.dump(out, file)
+ self._generate_result(out)
+ self.calc_likelihood_count()
+ self.result.sampling_time = self.sampling_time
+
+ if self.plot:
+ self.generate_trace_plots(out)
+
+ return self.result
+
+ def _generate_result(self, out):
+ import dynesty
weights = np.exp(out['logwt'] - out['logz'][-1])
nested_samples = DataFrame(
out.samples, columns=self.search_parameter_keys)
nested_samples['weights'] = weights
nested_samples['log_likelihood'] = out.logl
-
self.result.samples = dynesty.utils.resample_equal(out.samples, weights)
self.result.nested_samples = nested_samples
self.result.log_likelihood_evaluations = self.reorder_loglikelihoods(
unsorted_loglikelihoods=out.logl, unsorted_samples=out.samples,
sorted_samples=self.result.samples)
- self.calc_likelihood_count()
self.result.log_evidence = out.logz[-1]
self.result.log_evidence_err = out.logzerr[-1]
- self.result.sampling_time = self.sampling_time
-
- if self.plot:
- self.generate_trace_plots(out)
-
- return self.result
def _run_nested_wrapper(self, kwargs):
""" Wrapper function to run_nested
diff --git a/bilby/core/sampler/emcee.py b/bilby/core/sampler/emcee.py
index 144bede6d..33f21fcf9 100644
--- a/bilby/core/sampler/emcee.py
+++ b/bilby/core/sampler/emcee.py
@@ -373,20 +373,26 @@ class Emcee(MCMCSampler):
self.calculate_autocorrelation(
self.sampler.chain.reshape((-1, self.ndim)))
self.print_nburn_logging_info()
- self.calc_likelihood_count()
+
+ self._generate_result()
+
+ self.result.samples = self.sampler.chain[:, self.nburn:, :].reshape(
+ (-1, self.ndim))
+ self.result.walkers = self.sampler.chain
+ return self.result
+
+ def _generate_result(self):
self.result.nburn = self.nburn
+ self.calc_likelihood_count()
if self.result.nburn > self.nsteps:
raise SamplerError(
"The run has finished, but the chain is not burned in: "
- "`nburn < nsteps`. Try increasing the number of steps.")
- self.result.samples = self.sampler.chain[:, self.nburn:, :].reshape(
- (-1, self.ndim))
+ "`nburn < nsteps` ({} < {}). Try increasing the "
+ "number of steps.".format(self.result.nburn, self.nsteps))
blobs = np.array(self.sampler.blobs)
blobs_trimmed = blobs[self.nburn:, :, :].reshape((-1, 2))
log_likelihoods, log_priors = blobs_trimmed.T
self.result.log_likelihood_evaluations = log_likelihoods
self.result.log_prior_evaluations = log_priors
- self.result.walkers = self.sampler.chain
self.result.log_evidence = np.nan
self.result.log_evidence_err = np.nan
- return self.result
diff --git a/bilby/core/sampler/kombine.py b/bilby/core/sampler/kombine.py
index 48e85342a..f7c7768ec 100644
--- a/bilby/core/sampler/kombine.py
+++ b/bilby/core/sampler/kombine.py
@@ -3,7 +3,6 @@ from ..utils import logger, get_progress_bar
import numpy as np
import os
from .emcee import Emcee
-from .base_sampler import SamplerError
class Kombine(Emcee):
@@ -157,20 +156,11 @@ class Kombine(Emcee):
tmp_chain = self.sampler.chain.copy()
self.calculate_autocorrelation(tmp_chain.reshape((-1, self.ndim)))
self.print_nburn_logging_info()
- self.result.nburn = self.nburn
- if self.result.nburn > self.nsteps:
- raise SamplerError(
- "The run has finished, but the chain is not burned in: `nburn < nsteps` ({} < {}). Try increasing the "
- "number of steps.".format(self.result.nburn, self.nsteps))
+
+ self._generate_result()
+ self.result.log_evidence_err = np.nan
+
tmp_chain = self.sampler.chain[self.nburn:, :, :].copy()
self.result.samples = tmp_chain.reshape((-1, self.ndim))
- blobs = np.array(self.sampler.blobs)
- blobs_trimmed = blobs[self.nburn:, :, :].reshape((-1, 2))
- self.calc_likelihood_count()
- log_likelihoods, log_priors = blobs_trimmed.T
- self.result.log_likelihood_evaluations = log_likelihoods
- self.result.log_prior_evaluations = log_priors
self.result.walkers = self.sampler.chain.reshape((self.nwalkers, self.nsteps, self.ndim))
- self.result.log_evidence = np.nan
- self.result.log_evidence_err = np.nan
return self.result
diff --git a/bilby/core/sampler/pymc3.py b/bilby/core/sampler/pymc3.py
index 7a8745c8f..824f294ce 100644
--- a/bilby/core/sampler/pymc3.py
+++ b/bilby/core/sampler/pymc3.py
@@ -469,43 +469,13 @@ class Pymc3(MCMCSampler):
for sms in self.step_method[key]:
curmethod = sms.lower()
methodslist.append(curmethod)
- args = {}
- if curmethod == 'nuts':
- if nuts_kwargs is not None:
- args = nuts_kwargs
- elif step_kwargs is not None:
- args = step_kwargs.pop('nuts', {})
- # add values into nuts_kwargs
- nuts_kwargs = args
- else:
- args = {}
- else:
- if step_kwargs is not None:
- args = step_kwargs.get(curmethod, {})
- else:
- args = {}
- self.kwargs['step'].append(
- pymc3.__dict__[step_methods[curmethod]](vars=[self.pymc3_priors[key]], **args))
+ nuts_kwargs = self._create_nuts_kwargs(curmethod, key, nuts_kwargs, pymc3, step_kwargs,
+ step_methods)
else:
curmethod = self.step_method[key].lower()
methodslist.append(curmethod)
- args = {}
- if curmethod == 'nuts':
- if nuts_kwargs is not None:
- args = nuts_kwargs
- elif step_kwargs is not None:
- args = step_kwargs.pop('nuts', {})
- # add values into nuts_kwargs
- nuts_kwargs = args
- else:
- args = {}
- else:
- if step_kwargs is not None:
- args = step_kwargs.get(curmethod, {})
- else:
- args = {}
- self.kwargs['step'].append(
- pymc3.__dict__[step_methods[curmethod]](vars=[self.pymc3_priors[key]], **args))
+ nuts_kwargs = self._create_nuts_kwargs(curmethod, key, nuts_kwargs, pymc3, step_kwargs,
+ step_methods)
else:
with self.pymc3_model:
# check for a compound step list
@@ -514,18 +484,7 @@ class Pymc3(MCMCSampler):
for sms in self.step_method:
curmethod = sms.lower()
methodslist.append(curmethod)
- args = {}
- if curmethod == 'nuts':
- if nuts_kwargs is not None:
- args = nuts_kwargs
- elif step_kwargs is not None:
- args = step_kwargs.pop('nuts', {})
- # add values into nuts_kwargs
- nuts_kwargs = args
- else:
- args = {}
- else:
- args = step_kwargs.get(curmethod, {})
+ args, nuts_kwargs = self._create_args_and_nuts_kwargs(curmethod, nuts_kwargs, step_kwargs)
compound.append(pymc3.__dict__[step_methods[curmethod]](**args))
self.kwargs['step'] = compound
else:
@@ -533,18 +492,7 @@ class Pymc3(MCMCSampler):
if self.step_method is not None:
curmethod = self.step_method.lower()
methodslist.append(curmethod)
- args = {}
- if curmethod == 'nuts':
- if nuts_kwargs is not None:
- args = nuts_kwargs
- elif step_kwargs is not None:
- args = step_kwargs.pop('nuts', {})
- # add values into nuts_kwargs
- nuts_kwargs = args
- else:
- args = {}
- else:
- args = step_kwargs.get(curmethod, {})
+ args, nuts_kwargs = self._create_args_and_nuts_kwargs(curmethod, nuts_kwargs, step_kwargs)
self.kwargs['step'] = pymc3.__dict__[step_methods[curmethod]](**args)
else:
# re-add step_kwargs if no step methods are set
@@ -582,6 +530,37 @@ class Pymc3(MCMCSampler):
self.calc_likelihood_count()
return self.result
+ def _create_args_and_nuts_kwargs(self, curmethod, nuts_kwargs, step_kwargs):
+ if curmethod == 'nuts':
+ args, nuts_kwargs = self._get_nuts_args(nuts_kwargs, step_kwargs)
+ else:
+ args = step_kwargs.get(curmethod, {})
+ return args, nuts_kwargs
+
+ def _create_nuts_kwargs(self, curmethod, key, nuts_kwargs, pymc3, step_kwargs, step_methods):
+ if curmethod == 'nuts':
+ args, nuts_kwargs = self._get_nuts_args(nuts_kwargs, step_kwargs)
+ else:
+ if step_kwargs is not None:
+ args = step_kwargs.get(curmethod, {})
+ else:
+ args = {}
+ self.kwargs['step'].append(
+ pymc3.__dict__[step_methods[curmethod]](vars=[self.pymc3_priors[key]], **args))
+ return nuts_kwargs
+
+ @staticmethod
+ def _get_nuts_args(nuts_kwargs, step_kwargs):
+ if nuts_kwargs is not None:
+ args = nuts_kwargs
+ elif step_kwargs is not None:
+ args = step_kwargs.pop('nuts', {})
+ # add values into nuts_kwargs
+ nuts_kwargs = args
+ else:
+ args = {}
+ return args, nuts_kwargs
+
def set_prior(self):
"""
Set the PyMC3 prior distributions.
diff --git a/bilby/core/utils.py b/bilby/core/utils.py
index 71b0b5028..01bd97dca 100644
--- a/bilby/core/utils.py
+++ b/bilby/core/utils.py
@@ -131,6 +131,15 @@ def _infer_args_from_function_except_for_first_arg(func):
return infer_args_from_function_except_n_args(func=func, n=1)
+def get_dict_with_properties(obj):
+ property_names = [p for p in dir(obj.__class__)
+ if isinstance(getattr(obj.__class__, p), property)]
+ dict_with_properties = obj.__dict__.copy()
+ for key in property_names:
+ dict_with_properties[key] = getattr(obj, key)
+ return dict_with_properties
+
+
def get_sampling_frequency(time_array):
"""
Calculate sampling frequency from a time series
@@ -1022,6 +1031,41 @@ def encode_astropy_quantity(dct):
return dct
+def move_old_file(filename, overwrite=False):
+ """ Moves or removes an old file.
+
+ Parameters
+ ----------
+ filename: str
+ Name of the file to be move
+ overwrite: bool, optional
+ Whether or not to remove the file or to change the name
+ to filename + '.old'
+ """
+ if os.path.isfile(filename):
+ if overwrite:
+ logger.debug('Removing existing file {}'.format(filename))
+ os.remove(filename)
+ else:
+ logger.debug(
+ 'Renaming existing file {} to {}.old'.format(filename,
+ filename))
+ os.rename(filename, filename + '.old')
+ logger.debug("Saving result to {}".format(filename))
+
+
+def load_json(filename, gzip):
+ if gzip or os.path.splitext(filename)[1].lstrip('.') == 'gz':
+ import gzip
+ with gzip.GzipFile(filename, 'r') as file:
+ json_str = file.read().decode('utf-8')
+ dictionary = json.loads(json_str, object_hook=decode_bilby_json)
+ else:
+ with open(filename, 'r') as file:
+ dictionary = json.load(file, object_hook=decode_bilby_json)
+ return dictionary
+
+
def decode_bilby_json(dct):
if dct.get("__prior_dict__", False):
cls = getattr(import_module(dct['__module__']), dct['__name__'])
diff --git a/bilby/gw/likelihood.py b/bilby/gw/likelihood.py
index 786262481..bdfb8de54 100644
--- a/bilby/gw/likelihood.py
+++ b/bilby/gw/likelihood.py
@@ -439,14 +439,7 @@ class GravitationalWaveTransient(Likelihood):
if signal_polarizations is None:
signal_polarizations = \
self.waveform_generator.frequency_domain_strain(self.parameters)
- d_inner_h = 0
- h_inner_h = 0
- for interferometer in self.interferometers:
- per_detector_snr = self.calculate_snrs(
- signal_polarizations, interferometer)
-
- d_inner_h += per_detector_snr.d_inner_h
- h_inner_h += per_detector_snr.optimal_snr_squared
+ d_inner_h, h_inner_h = self._calculate_inner_products(signal_polarizations)
d_inner_h_dist = (
d_inner_h * self.parameters['luminosity_distance'] /
@@ -472,6 +465,17 @@ class GravitationalWaveTransient(Likelihood):
self._rescale_signal(signal_polarizations, new_distance)
return new_distance
+ def _calculate_inner_products(self, signal_polarizations):
+ d_inner_h = 0
+ h_inner_h = 0
+ for interferometer in self.interferometers:
+ per_detector_snr = self.calculate_snrs(
+ signal_polarizations, interferometer)
+
+ d_inner_h += per_detector_snr.d_inner_h
+ h_inner_h += per_detector_snr.optimal_snr_squared
+ return d_inner_h, h_inner_h
+
def generate_phase_sample_from_marginalized_likelihood(
self, signal_polarizations=None):
"""
@@ -497,14 +501,7 @@ class GravitationalWaveTransient(Likelihood):
if signal_polarizations is None:
signal_polarizations = \
self.waveform_generator.frequency_domain_strain(self.parameters)
- d_inner_h = 0
- h_inner_h = 0
- for interferometer in self.interferometers:
- per_detector_snr = self.calculate_snrs(
- signal_polarizations, interferometer)
-
- d_inner_h += per_detector_snr.d_inner_h
- h_inner_h += per_detector_snr.optimal_snr_squared
+ d_inner_h, h_inner_h = self._calculate_inner_products(signal_polarizations)
phases = np.linspace(0, 2 * np.pi, 101)
phasor = np.exp(-2j * phases)
diff --git a/bilby/gw/utils.py b/bilby/gw/utils.py
index 5feb3d51d..dc5ea7964 100644
--- a/bilby/gw/utils.py
+++ b/bilby/gw/utils.py
@@ -717,28 +717,15 @@ def lalsim_SimInspiralFD(
approximant: int, str
"""
- [mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
- luminosity_distance, iota, phase, longitude_ascending_nodes,
- eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
- maximum_frequency, reference_frequency] = convert_args_list_to_float(
+ args = convert_args_list_to_float(
mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
luminosity_distance, iota, phase, longitude_ascending_nodes,
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
maximum_frequency, reference_frequency)
- if isinstance(approximant, int):
- pass
- elif isinstance(approximant, str):
- approximant = lalsim_GetApproximantFromString(approximant)
- else:
- raise ValueError("approximant not an int")
+ approximant = _get_lalsim_approximant(approximant)
- return lalsim.SimInspiralFD(
- mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y,
- spin_2z, luminosity_distance, iota, phase,
- longitude_ascending_nodes, eccentricity, mean_per_ano, delta_frequency,
- minimum_frequency, maximum_frequency, reference_frequency,
- waveform_dictionary, approximant)
+ return lalsim.SimInspiralFD(*args, waveform_dictionary, approximant)
def lalsim_SimInspiralChooseFDWaveform(
@@ -774,28 +761,25 @@ def lalsim_SimInspiralChooseFDWaveform(
approximant: int, str
"""
- [mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
- luminosity_distance, iota, phase, longitude_ascending_nodes,
- eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
- maximum_frequency, reference_frequency] = convert_args_list_to_float(
+ args = convert_args_list_to_float(
mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
luminosity_distance, iota, phase, longitude_ascending_nodes,
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
maximum_frequency, reference_frequency)
+ approximant = _get_lalsim_approximant(approximant)
+
+ return lalsim.SimInspiralChooseFDWaveform(*args, waveform_dictionary, approximant)
+
+
+def _get_lalsim_approximant(approximant):
if isinstance(approximant, int):
pass
elif isinstance(approximant, str):
approximant = lalsim_GetApproximantFromString(approximant)
else:
raise ValueError("approximant not an int")
-
- return lalsim.SimInspiralChooseFDWaveform(
- mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y,
- spin_2z, luminosity_distance, iota, phase,
- longitude_ascending_nodes, eccentricity, mean_per_ano, delta_frequency,
- minimum_frequency, maximum_frequency, reference_frequency,
- waveform_dictionary, approximant)
+ return approximant
def lalsim_SimInspiralChooseFDWaveformSequence(
--
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