autofit.UniformPrior#
- class UniformPrior[source]#
Bases:
Prior
A prior with a uniform distribution, defined between a lower limit and upper limit.
The conversion of an input unit value,
u
, to a physical value,p
, via the prior is as follows:\[\]For example for
prior = UniformPrior(lower_limit=0.0, upper_limit=2.0)
, an inputprior.value_for(unit=0.5)
is equal to 1.0.[Rich describe how this is done via message]
- Parameters:
Examples
prior = af.UniformPrior(lower_limit=0.0, upper_limit=2.0)
physical_value = prior.value_for(unit=0.2)
Methods
assert_within_limits
dict
A dictionary representation of this prior
for_class_and_attribute_name
from_dict
Returns a prior from a JSON representation.
gaussian_prior_model_for_arguments
has
Does this instance have an attribute which is of type cls?
instance_for_arguments
Returns the log prior of a physical value, so the log likelihood of a model evaluation can be converted to a posterior as log_prior + log_likelihood.
logpdf
make_indexes
name_of_class
A string name for the class, with the prior suffix removed.
new
Returns a copy of this prior with a new id assigned making it distinct
next_id
project
random
A random value sampled from this prior
replacing_for_path
Create a new model replacing the value for a given path with a new value
tree_flatten
tree_unflatten
Create a prior from a flattened PyTree
unit_value_for
Compute the unit value between 0 and 1 for the physical value.
Returns a physical value from an input unit value according to the limits of the uniform prior.
Create a new instance of the same prior class with the passed limits.
with_message
Attributes
component_number
factor
A callable PDF used as a factor in factor graphs
identifier
label
limits
lower_unit_limit
The lower limit for this prior in unit vector space
ndim
How many dimensions does this variable have?
parameter_string
upper_unit_limit
The upper limit for this prior in unit vector space
width
- with_limits(lower_limit, upper_limit)[source]#
Create a new instance of the same prior class with the passed limits.
- Return type:
Prior
- value_for(unit, ignore_prior_limits=False)[source]#
Returns a physical value from an input unit value according to the limits of the uniform prior.
- Parameters:
unit (
float
) – A unit value between 0 and 1.- Returns:
The unit value mapped to a physical value according to the prior.
- Return type:
value
Examples
prior = af.UniformPrior(lower_limit=0.0, upper_limit=2.0)
physical_value = prior.value_for(unit=0.2)
- log_prior_from_value(value)[source]#
Returns the log prior of a physical value, so the log likelihood of a model evaluation can be converted to a posterior as log_prior + log_likelihood.
This is used by certain non-linear searches (e.g. Emcee) in the log likelihood function evaluation.
For a UniformPrior this is always zero, provided the value is between the lower and upper limit.