diff options
Diffstat (limited to 'lib/parameters.py')
| -rw-r--r-- | lib/parameters.py | 25 |
1 files changed, 22 insertions, 3 deletions
diff --git a/lib/parameters.py b/lib/parameters.py index 2a614a3..740647e 100644 --- a/lib/parameters.py +++ b/lib/parameters.py @@ -8,7 +8,7 @@ from copy import deepcopy from multiprocessing import Pool import dfatool.functions as df from .paramfit import ParamFit -from .utils import remove_index_from_tuple, is_numeric +from .utils import remove_indexes_from_tuple, is_numeric from .utils import filter_aggregate_by_param, partition_by_param from .utils import param_to_ndarray @@ -69,10 +69,29 @@ def _mean_std_by_param(n_by_param, all_param_values, param_index): this function returns the mean of the standard deviations of (a=1, b=*, c=1), (a=1, b=*, c=2), and so on. """ + return _mean_std_by_params(n_by_param, all_param_values, [param_index]) + + +def _mean_std_by_params(n_by_param, all_param_values, param_indexes): + """ + Calculate the mean standard deviation for a static model where all parameters but `param_indexes` are constant. + + :param n_by_param: measurements of a specific model attribute partitioned by parameter values. + Example: `{(0, 2): [2], (0, 4): [4], (0, 6): [6]}` + :param all_param_values: distinct values of each parameter. + E.g. for two parameters, the first being None, FOO, or BAR, and the second being 1, 2, 3, or 4, the argument is + `[[None, 'FOO', 'BAR'], [1, 2, 3, 4]]`. + :param param_indexes: indexes of variable parameters + :returns: mean stddev + *mean stddev* is the mean standard deviation of all measurements where parameters `param_indexes` are dynamic and all other parameters are fixed. + E.g., if parameters are a, b, c ∈ {1,2,3} and 'indexes' corresponds to b and c, then + this function returns the mean of the standard deviations of (a=1, b=*, c=*), + (a=2, b=*, c=*), and so on. + """ partition_by_tuple = dict() for k, v in n_by_param.items(): - tuple_key = (*k[:param_index], *k[param_index + 1 :]) + tuple_key = remove_indexes_from_tuple(k, param_indexes) if not tuple_key in partition_by_tuple: partition_by_tuple[tuple_key] = list() partition_by_tuple[tuple_key].extend(v) @@ -1218,7 +1237,7 @@ class ModelAttribute: continue if ignore_irrelevant_parameters: - std_by_param = _mean_std_by_param( + std_by_param = _mean_std_by_params( by_param, distinct_values_by_param_index, list(self.ignore_param.keys()) + [param_index], |