def add_benchmark(self, parameter_values, benchmark_name=None, verbose=True):
"""
Manually adds an individual benchmark, that is, a parameter point that will be evaluated by MadGraph.
If this command is called before
Parameters
----------
parameter_values : dict
The keys of this dict should be the parameter names and the values the corresponding parameter values.
benchmark_name : str or None, optional
Name of benchmark. If None, a default name is used. Default value: None.
verbose : bool, optional
If True, prints output about each benchmark. Default value: True.
Returns
-------
None
Raises
------
RuntimeError
If a benchmark with the same name already exists, if parameter_values is not a dict, or if a key of
parameter_values does not correspond to a defined parameter.
"""
# Default names
if benchmark_name is None:
benchmark_name = "benchmark_" + str(len(self.benchmarks))
# Check input
if not isinstance(parameter_values, dict):
raise RuntimeError("Parameter values are not a dict: {}".format(parameter_values))
for key, value in six.iteritems(parameter_values):
if key not in self.parameters:
raise RuntimeError("Unknown parameter: {0}".format(key))
if benchmark_name in self.benchmarks:
raise RuntimeError("Benchmark name {} exists already".format(benchmark_name))
# Add benchmark
self.benchmarks[benchmark_name] = parameter_values
# If first benchmark, this will be the default for sampling
if len(self.benchmarks) == 1:
self.default_benchmark = benchmark_name
if verbose:
logger.info("Added benchmark %s: %s)", benchmark_name, format_benchmark(parameter_values))
else:
logger.debug("Added benchmark %s: %s)", benchmark_name, format_benchmark(parameter_values))
def _report_setup(self):
logger.info("Found %s parameters", self.n_parameters)
for key, values in six.iteritems(self.parameters):
logger.debug(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
if self.nuisance_parameters is not None:
logger.info("Found %s nuisance parameters",
self.n_nuisance_parameters)
for key, values in six.iteritems(self.nuisance_parameters):
logger.debug(" %s (%s)", key, values)
else:
logger.info("Did not find nuisance parameters")
self.include_nuisance_parameters = False
logger.info("Found %s benchmarks, of which %s physical",
self.n_benchmarks, self.n_benchmarks_phys)
for (key, values), is_nuisance in zip(six.iteritems(self.benchmarks),
self.benchmark_is_nuisance):
if is_nuisance:
logger.debug(" %s: systematics", key)
else:
logger.debug(" %s: %s", key, format_benchmark(values))
logger.info("Found %s observables", self.n_observables)
if self.observables is not None:
for i, obs in enumerate(self.observables):
logger.debug(" %2.2s %s", i, obs)
logger.info("Found %s events", self.n_samples)
if self.n_events_generated_per_benchmark is not None:
for events, name in zip(self.n_events_generated_per_benchmark,
six.iterkeys(self.benchmarks)):
if events > 0:
logger.info(" %s signal events sampled from benchmark %s",
events, name)
if self.n_events_backgrounds is not None and self.n_events_backgrounds > 0:
logger.info(" %s background events",
self.n_events_backgrounds)
else:
logger.debug(" Did not find sample summary information")
if self.morpher is not None:
logger.info("Found morphing setup with %s components",
len(self.morphing_components))
else:
logger.info("Did not find morphing setup.")
if self.nuisance_morpher is not None:
logger.info("Found nuisance morphing setup")
else:
logger.info("Did not find nuisance morphing setup")
def load(self, filename, disable_morphing=False):
"""
Loads MadMiner setup from a file. All parameters, benchmarks, and morphing settings are overwritten. See `save`
for more details.
Parameters
----------
filename : str
Path to the MadMiner file.
disable_morphing : bool, optional
If True, the morphing setup is not loaded from the file. Default value: False.
Returns
-------
None
"""
# Load data
(self.parameters, self.benchmarks, morphing_components,
morphing_matrix, _, _) = load_madminer_settings(filename)
logging.info("Found %s parameters:", len(self.parameters))
for key, values in six.iteritems(self.parameters):
logging.info(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
logging.info("Found %s benchmarks:", len(self.benchmarks))
for key, values in six.iteritems(self.benchmarks):
logging.info(" %s: %s", key, format_benchmark(values))
if self.default_benchmark is None:
self.default_benchmark = key
# Morphing
self.morpher = None
self.export_morphing = False
if morphing_matrix is not None and morphing_components is not None and not disable_morphing:
self.morpher = Morpher(self.parameters)
self.morpher.set_components(morphing_components)
self.morpher.set_basis(self.benchmarks,
morphing_matrix=morphing_matrix)
self.export_morphing = True
logging.info("Found morphing setup with %s components",
len(morphing_components))
else:
logging.info("Did not find morphing setup.")
def _report_setup(self):
logger.info(f"Found {self.n_parameters} parameters")
for i, (key, values) in enumerate(self.parameters.items()):
values_str = " / ".join(str(x) for x in values)
logger.info(f" {i}: {key} ({values_str})")
if self.nuisance_parameters is not None:
logger.info(f"Found {self.n_nuisance_parameters} nuisance parameters")
for i, (key, values) in enumerate(self.systematics.items()):
values_str = " / ".join(str(x) for x in values)
logger.info(f" {i}: {key} ({values_str})")
else:
logger.info("Did not find nuisance parameters")
self.include_nuisance_parameters = False
logger.info(f"Found {self.n_benchmarks} benchmarks")
for (key, values), is_nuisance in zip(self.benchmarks.items(), self.benchmark_is_nuisance):
if is_nuisance:
logger.debug(" %s: systematics", key)
else:
logger.debug(" %s: %s", key, format_benchmark(values))
logger.info(f"Found {self.n_observables} observables")
if self.observables is not None:
for i, obs in enumerate(self.observables):
logger.debug(" %2.2s %s", i, obs)
logger.info(f"Found {self.n_samples} events")
if self.n_events_generated_per_benchmark is not None:
for events, name in zip(self.n_events_generated_per_benchmark, self.benchmarks.keys()):
if events > 0:
logger.info(" %s signal events sampled from benchmark %s", events, name)
if self.n_events_backgrounds is not None and self.n_events_backgrounds > 0:
logger.info(" %s background events", self.n_events_backgrounds)
else:
logger.debug(" Did not find sample summary information")
if self.morpher is not None:
logger.info("Found morphing setup with %s components", len(self.morphing_components))
else:
logger.info("Did not find morphing setup.")
if self.nuisance_morpher is not None:
logger.info("Found nuisance morphing setup")
else:
logger.info("Did not find nuisance morphing setup")
def __init__(self,
filename,
disable_morphing=False,
include_nuisance_parameters=True):
# Save setup
self.include_nuisance_parameters = include_nuisance_parameters
self.madminer_filename = filename
logger.info("Loading data from %s", filename)
# Load data
(
self.parameters,
self.benchmarks,
self.benchmark_is_nuisance,
self.morphing_components,
self.morphing_matrix,
self.observables,
self.n_samples,
_,
self.reference_benchmark,
self.nuisance_parameters,
) = load_madminer_settings(
filename, include_nuisance_benchmarks=include_nuisance_parameters)
self.n_parameters = len(self.parameters)
self.n_benchmarks = len(self.benchmarks)
self.n_benchmarks_phys = np.sum(
np.logical_not(self.benchmark_is_nuisance))
self.n_observables = len(self.observables)
self.n_nuisance_parameters = 0
if self.nuisance_parameters is not None and include_nuisance_parameters:
self.n_nuisance_parameters = len(self.nuisance_parameters)
else:
self.nuisance_parameters = None
logger.info("Found %s parameters", self.n_parameters)
for key, values in six.iteritems(self.parameters):
logger.debug(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
if self.nuisance_parameters is not None:
logger.info("Found %s nuisance parameters",
self.n_nuisance_parameters)
for key, values in six.iteritems(self.nuisance_parameters):
logger.debug(" %s (%s)", key, values)
else:
logger.info("Did not find nuisance parameters")
logger.info("Found %s benchmarks, of which %s physical",
self.n_benchmarks, self.n_benchmarks_phys)
for (key, values), is_nuisance in zip(six.iteritems(self.benchmarks),
self.benchmark_is_nuisance):
if is_nuisance:
logger.debug(" %s: systematics", key)
else:
logger.debug(" %s: %s", key, format_benchmark(values))
logger.info("Found %s observables", len(self.observables))
for i, obs in enumerate(self.observables):
logger.debug(" %2.2s %s", i, obs)
logger.info("Found %s events", self.n_samples)
# Morphing
self.morpher = None
if self.morphing_matrix is not None and self.morphing_components is not None and not disable_morphing:
self.morpher = PhysicsMorpher(self.parameters)
self.morpher.set_components(self.morphing_components)
self.morpher.set_basis(self.benchmarks,
morphing_matrix=self.morphing_matrix)
logger.info("Found morphing setup with %s components",
len(self.morphing_components))
else:
logger.info("Did not find morphing setup.")
# Nuisance morphing
self.nuisance_morpher = None
if self.nuisance_parameters is not None:
self.nuisance_morpher = NuisanceMorpher(
self.nuisance_parameters, list(self.benchmarks.keys()),
self.reference_benchmark)
logger.info("Found nuisance morphing setup")
def load(self, filename, disable_morphing=False):
"""
Loads MadMiner setup from a file. All parameters, benchmarks, and morphing settings are overwritten. See `save`
for more details.
Parameters
----------
filename : str
Path to the MadMiner file.
disable_morphing : bool, optional
If True, the morphing setup is not loaded from the file. Default value: False.
Returns
-------
None
"""
# Load data
(
self.parameters,
self.benchmarks,
_,
morphing_components,
morphing_matrix,
_,
_,
self.systematics,
_,
_,
_,
_,
self.finite_difference_benchmarks,
self.finite_difference_epsilon,
) = load_madminer_settings(filename, include_nuisance_benchmarks=False)
logger.info("Found %s parameters:", len(self.parameters))
for key, values in self.parameters.items():
logger.info(
" %s (LHA: %s %s, maximal power in squared ME: %s, range: %s)",
key,
values[0],
values[1],
values[2],
values[3],
)
logger.info("Found %s benchmarks:", len(self.benchmarks))
for key, values in self.benchmarks.items():
logger.info(" %s: %s", key, format_benchmark(values))
if self.default_benchmark is None:
self.default_benchmark = key
# Morphing
self.morpher = None
self.export_morphing = False
if morphing_matrix is not None and morphing_components is not None and not disable_morphing:
self.morpher = PhysicsMorpher(self.parameters)
self.morpher.set_components(morphing_components)
self.morpher.set_basis(self.benchmarks, morphing_matrix=morphing_matrix)
self.export_morphing = True
logger.info("Found morphing setup with %s components", len(morphing_components))
else:
logger.info("Did not find morphing setup.")
# Systematics setup
if len(self.systematics) == 0:
logger.info("Did not find systematics setup.")
else:
logger.info("Found systematics setup with %s nuisance parameter groups", len(self.systematics))
for key, value in self.systematics.items():
logger.debug(" %s: %s", key, " / ".join(str(x) for x in value))
