def set_minimizer(self, minimizer):
"""
Set the minimizer to be used, among those available.
:param minimizer: the name of the new minimizer or an instance of a LocalMinimization or a GlobalMinimization
class. Using the latter two classes allows for more choices and a better control of the details of the
minimization, like the choice of algorithms (if supported by the used minimizer)
:return: (none)
"""
if isinstance(minimizer, minimization._Minimization):
self._minimizer_type = minimizer
else:
assert minimizer.upper() in minimization._minimizers, (
"Minimizer %s is not available on this system. "
"Available minimizers: %s" %
(minimizer, ",".join(list(minimization._minimizers.keys()))))
# The string can only specify a local minimization. This will return an error if that is not the case.
# In order to setup global optimization the user needs to use the GlobalMinimization factory directly
self._minimizer_type = minimization.LocalMinimization(minimizer)
def __init__(self,
likelihood_model,
data_list,
verbose=False,
record=True):
"""
Implement a joint likelihood analysis.
:param likelihood_model: the model for the likelihood analysis
:param data_list: the list of data sets (plugin instances) to be used in this analysis
:param verbose: (True or False) print every step in the -log likelihood minimization
:param record: it records every call to the log likelihood function during minimization. The recorded values
can be retrieved as a pandas DataFrame using the .fit_trace property
:return:
"""
self._analysis_type = "mle"
# Process optional keyword parameters
self.verbose = verbose
self._likelihood_model = likelihood_model # type: astromodels.core.model.Model
self._data_list = data_list
self._assign_model_to_data(self._likelihood_model)
# This is to keep track of the number of calls to the likelihood
# function
self._record = bool(record)
self._ncalls = 0
self._record_calls = {}
# Pre-defined minimizer
default_minimizer = minimization.LocalMinimization(
threeML_config["mle"]["default minimizer"])
if threeML_config["mle"]["default minimizer algorithm"] is not None:
default_minimizer.set_algorithm(
threeML_config["mle"]["default minimizer algorithm"])
self.set_minimizer(default_minimizer)
# Initial set of free parameters
self._free_parameters = self._likelihood_model.free_parameters
# Initially set the value of _current_minimum to None, it will be change by the fit() method
self._current_minimum = None
# Null setup for minimizer
self._minimizer = None
self._minimizer_callback = None
self._analysis_results = None