def from_config(cls, cp, section, variable_args):
"""Returns a distribution based on a configuration file.
The parameters for the distribution are retrieved from the section
titled "[`section`-`variable_args`]" in the config file. By default,
only the name of the distribution (`uniform_angle`) needs to be
specified. This will results in a uniform prior on `[0, 2pi)`. To
make the domain cyclic, add `cyclic_domain =`. To specify boundaries
that are not `[0, 2pi)`, add `(min|max)-var` arguments, where `var`
is the name of the variable.
For example, this will initialize a variable called `theta` with a
uniform distribution on `[0, 2pi)` without cyclic boundaries:
.. code-block:: ini
[{section}-theta]
name = uniform_angle
This will make the domain cyclic on `[0, 2pi)`:
.. code-block:: ini
[{section}-theta]
name = uniform_angle
cyclic_domain =
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
``VARARGS_DELIM``. These must appear in the "tag" part
of the section header.
Returns
-------
UniformAngle
A distribution instance from the pycbc.inference.prior module.
"""
# we'll retrieve the setting for cyclic_domain directly
additional_opts = {
'cyclic_domain':
cp.has_option_tag(section, 'cyclic_domain', variable_args)
}
return bounded.bounded_from_config(cls,
cp,
section,
variable_args,
bounds_required=False,
additional_opts=additional_opts)
def from_config(cls, cp, section, variable_args):
"""Returns a distribution based on a configuration file.
The parameters for the distribution are retrieved from the section
titled "[`section`-`variable_args`]" in the config file. By default,
only the name of the distribution (`uniform_angle`) needs to be
specified. This will results in a uniform prior on `[0, 2pi)`. To
make the domain cyclic, add `cyclic_domain =`. To specify boundaries
that are not `[0, 2pi)`, add `(min|max)-var` arguments, where `var`
is the name of the variable.
For example, this will initialize a variable called `theta` with a
uniform distribution on `[0, 2pi)` without cyclic boundaries:
.. code-block:: ini
[{section}-theta]
name = uniform_angle
This will make the domain cyclic on `[0, 2pi)`:
.. code-block:: ini
[{section}-theta]
name = uniform_angle
cyclic_domain =
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
``VARARGS_DELIM``. These must appear in the "tag" part
of the section header.
Returns
-------
UniformAngle
A distribution instance from the pycbc.inference.prior module.
"""
# we'll retrieve the setting for cyclic_domain directly
additional_opts = {'cyclic_domain': cp.has_option_tag(section,
'cyclic_domain', variable_args)}
return bounded.bounded_from_config(cls, cp, section, variable_args,
bounds_required=False,
additional_opts=additional_opts)
def from_config(cls, cp, section, variable_args):
"""Returns a Gaussian distribution based on a configuration file. The
parameters for the distribution are retrieved from the section titled
"[`section`-`variable_args`]" in the config file.
Boundary arguments should be provided in the same way as described in
`get_param_bounds_from_config`. In addition, the mean and variance of
each parameter can be specified by setting `{param}_mean` and
`{param}_var`, respectively. For example, the following would create a
truncated Gaussian distribution between 0 and 6.28 for a parameter
called `phi` with mean 3.14 and variance 0.5 that is cyclic:
.. code-block:: ini
[{section}-{tag}]
min-phi = 0
max-phi = 6.28
phi_mean = 3.14
phi_var = 0.5
cyclic =
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
`prior.VARARGS_DELIM`. These must appear in the "tag" part
of the section header.
Returns
-------
Gaussain
A distribution instance from the pycbc.inference.prior module.
"""
return bounded.bounded_from_config(cls,
cp,
section,
variable_args,
bounds_required=False)
def from_config(cls, cp, section, variable_args):
"""Returns a distribution based on a configuration file.
The parameters
for the distribution are retrieved from the section titled
"[`section`-`variable_args`]" in the config file.
The file to construct the distribution from must be provided by setting
`filename`. Boundary arguments can be provided in the same way as
described in `get_param_bounds_from_config`.
.. code-block:: ini
[{section}-{tag}]
name = fromfile
filename = ra_prior.hdf
min-ra = 0
max-ra = 6.28
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
`prior.VARARGS_DELIM`. These must appear in the "tag" part
of the section header.
Returns
-------
BoundedDist
A distribution instance from the pycbc.inference.prior module.
"""
return bounded.bounded_from_config(cls,
cp,
section,
variable_args,
bounds_required=False)
def from_config(cls, cp, section, variable_args):
"""Returns a Gaussian distribution based on a configuration file. The
parameters for the distribution are retrieved from the section titled
"[`section`-`variable_args`]" in the config file.
Boundary arguments should be provided in the same way as described in
`get_param_bounds_from_config`. In addition, the mean and variance of
each parameter can be specified by setting `{param}_mean` and
`{param}_var`, respectively. For example, the following would create a
truncated Gaussian distribution between 0 and 6.28 for a parameter
called `phi` with mean 3.14 and variance 0.5 that is cyclic:
.. code-block:: ini
[{section}-{tag}]
min-phi = 0
max-phi = 6.28
phi_mean = 3.14
phi_var = 0.5
cyclic =
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
`prior.VARARGS_DELIM`. These must appear in the "tag" part
of the section header.
Returns
-------
Gaussain
A distribution instance from the pycbc.inference.prior module.
"""
return bounded.bounded_from_config(cls, cp, section, variable_args,
bounds_required=False)
def from_config(cls, cp, section, variable_args):
"""Returns a distribution based on a configuration file.
The parameters
for the distribution are retrieved from the section titled
"[`section`-`variable_args`]" in the config file.
The file to construct the distribution from must be provided by setting
`filename`. Boundary arguments can be provided in the same way as
described in `get_param_bounds_from_config`.
.. code-block:: ini
[{section}-{tag}]
name = fromfile
filename = ra_prior.hdf
min-ra = 0
max-ra = 6.28
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
`prior.VARARGS_DELIM`. These must appear in the "tag" part
of the section header.
Returns
-------
BoundedDist
A distribution instance from the pycbc.inference.prior module.
"""
return bounded.bounded_from_config(cls, cp, section, variable_args,
bounds_required=False)
def from_config(cls, cp, section, variable_args):
"""Returns a distribution based on a configuration file. The parameters
for the distribution are retrieved from the section titled
"[`section`-`variable_args`]" in the config file.
Parameters
----------
cp : pycbc.workflow.WorkflowConfigParser
A parsed configuration file that contains the distribution
options.
section : str
Name of the section in the configuration file.
variable_args : str
The names of the parameters for this distribution, separated by
`prior.VARARGS_DELIM`. These must appear in the "tag" part
of the section header.
Returns
-------
UniformAngle
A distribution instance from the pycbc.inference.prior module.
"""
return bounded.bounded_from_config(cls, cp, section, variable_args,
bounds_required=False)