def initial_dist_from_config(cp, variable_params):
r"""Loads a distribution for the sampler start from the given config file.
A distribution will only be loaded if the config file has a [initial-\*]
section(s).
Parameters
----------
cp : Config parser
The config parser to try to load from.
variable_params : list of str
The variable parameters for the distribution.
Returns
-------
JointDistribution or None :
The initial distribution. If no [initial-\*] section found in the
config file, will just return None.
"""
if len(cp.get_subsections("initial")):
logging.info("Using a different distribution for the starting points "
"than the prior.")
initial_dists = distributions.read_distributions_from_config(
cp, section="initial")
constraints = distributions.read_constraints_from_config(
cp, constraint_section="initial_constraint")
init_dist = distributions.JointDistribution(
variable_params, *initial_dists, **{"constraints": constraints})
else:
init_dist = None
return init_dist
def draw_samples_from_config(path, num=1, seed=150914):
r""" Generate sampling points from a standalone .ini file.
Parameters
----------
path : str
The path to the .ini file.
num : int
The number of samples.
seed: int
The random seed for sampling.
Returns
--------
samples : pycbc.io.record.FieldArray
The parameter values and names of sample(s).
Examples
--------
Draw a sample from the distribution defined in the .ini file:
>>> import numpy as np
>>> from pycbc.distributions.utils import draw_samples_from_config
>>> # A path to the .ini file.
>>> CONFIG_PATH = "./pycbc_bbh_prior.ini"
>>> random_seed = np.random.randint(low=0, high=2**32-1)
>>> sample = draw_samples_from_config(
>>> path=CONFIG_PATH, num=1, seed=random_seed)
>>> # Print all parameters.
>>> print(sample.fieldnames)
>>> print(sample)
>>> # Print a certain parameter, for example 'mass1'.
>>> print(sample[0]['mass1'])
"""
np.random.seed(seed)
# Initialise InterpolatingConfigParser class.
config_parser = InterpolatingConfigParser()
# Read the file
file = open(path, 'r')
config_parser.read_file(file)
file.close()
# Get the vairable arguments from the .ini file.
variable_args, _ = distributions.read_params_from_config(
config_parser, prior_section='prior', vargs_section='variable_params')
constraints = distributions.read_constraints_from_config(config_parser)
if any(config_parser.get_subsections('waveform_transforms')):
waveform_transforms = transforms.read_transforms_from_config(
config_parser, 'waveform_transforms')
else:
waveform_transforms = None
# Get prior distribution for each variable parameter.
dists = distributions.read_distributions_from_config(config_parser)
# Construct class that will draw the samples.
randomsampler = distributions.JointDistribution(
variable_args, *dists, **{"constraints": constraints})
# Draw samples from prior distribution.
samples = randomsampler.rvs(size=int(num))
# Apply parameter transformation.
if waveform_transforms is not None:
samples = transforms.apply_transforms(samples, waveform_transforms)
else:
pass
return samples
