import numpy as np
from typing import Iterable
[docs]class McmcPtResult(dict):
"""The result of a sampler run using Markov-chain Monte Carlo, and
optionally parallel tempering.
Can be used like a dict.
Parameters
----------
trace_x: [n_chain, n_iter, n_par]
Parameters.
trace_neglogpost: [n_chain, n_iter]
Negative log posterior values.
trace_neglogprior: [n_chain, n_iter]
Negative log prior values.
betas: [n_chain]
The associated inverse temperatures.
burn_in: [n_chain]
The burn in index.
time: [n_chain]
The computation time.
auto_correlation: [n_chain]
The estimated chain autcorrelation.
effective_sample_size: [n_chain]
The estimated effective sample size.
message: str
Textual comment on the profile result.
Here, `n_chain` denotes the number of chains, `n_iter` the number of
iterations (i.e., the chain length), and `n_par` the number of parameters.
"""
[docs] def __init__(self,
trace_x: np.ndarray,
trace_neglogpost: np.ndarray,
trace_neglogprior: np.ndarray,
betas: Iterable[float],
burn_in: int = None,
time: float = 0.,
auto_correlation: float = None,
effective_sample_size: float = None,
message: str = None):
super().__init__()
self.trace_x = trace_x
self.trace_neglogpost = trace_neglogpost
self.trace_neglogprior = trace_neglogprior
self.betas = betas
self.burn_in = burn_in
self.time = time
self.auto_correlation = auto_correlation
self.effective_sample_size = effective_sample_size
self.message = message
if trace_x.ndim != 3:
raise ValueError(f"trace_x.ndim not as expected: {trace_x.ndim}")
if trace_neglogpost.ndim != 2:
raise ValueError("trace_neglogpost.ndim not as expected: "
f"{trace_neglogpost.ndim}")
if trace_neglogprior.ndim != 2:
raise ValueError("trace_neglogprior.ndim not as expected: "
f"{trace_neglogprior.ndim}")
if trace_x.shape[0] != trace_neglogpost.shape[0] \
or trace_x.shape[1] != trace_neglogpost.shape[1]:
raise ValueError("Trace dimensions do not match:"
f"trace_x.shape={trace_x.shape},"
f"trace_neglogpost.shape={trace_neglogpost.shape}") # noqa
if trace_x.shape[0] != trace_neglogprior.shape[0] \
or trace_x.shape[1] != trace_neglogprior.shape[1]:
raise ValueError("Trace dimensions do not match:"
f"trace_x.shape={trace_x.shape},"
f"trace_neglogprior.shape={trace_neglogprior.shape}") # noqa
if trace_neglogpost.shape[0] != trace_neglogprior.shape[0] \
or trace_neglogpost.shape[1] != trace_neglogprior.shape[1]:
raise ValueError("Trace dimensions do not match:"
f"trace_neglogpost.shape={trace_neglogpost.shape}," # noqa
f"trace_neglogprior.shape={trace_neglogprior.shape}") # noqa
def __getattr__(self, key):
try:
return self[key]
except KeyError:
raise AttributeError(key)
__setattr__ = dict.__setitem__
__delattr__ = dict.__delitem__