diff options
Diffstat (limited to 'lib/functions.py')
| -rw-r--r-- | lib/functions.py | 30 |
1 files changed, 12 insertions, 18 deletions
diff --git a/lib/functions.py b/lib/functions.py index 6d8daa4..359c8d7 100644 --- a/lib/functions.py +++ b/lib/functions.py @@ -5,12 +5,14 @@ This module provides classes and helper functions useful for least-squares regression and general handling of model functions. """ from itertools import chain, combinations +import logging import numpy as np import re from scipy import optimize -from .utils import is_numeric, vprint +from .utils import is_numeric arg_support_enabled = True +logger = logging.getLogger(__name__) def powerset(iterable): @@ -118,9 +120,7 @@ class AnalyticFunction: packet length. """ - def __init__( - self, function_str, parameters, num_args, verbose=True, regression_args=None - ): + def __init__(self, function_str, parameters, num_args, regression_args=None): """ Create a new AnalyticFunction object from a function string. @@ -135,7 +135,6 @@ class AnalyticFunction: :param num_args: number of local function arguments, if any. Set to 0 if the model attribute does not belong to a function or if function arguments are not included in the model. - :param verbose: complain about odd events :param regression_args: Initial regression variable values, both for function usage and least squares optimization. If unset, defaults to [1, 1, 1, ...] @@ -146,7 +145,6 @@ class AnalyticFunction: rawfunction = function_str self._dependson = [False] * (len(parameters) + num_args) self.fit_success = False - self.verbose = verbose if type(function_str) == str: num_vars_re = re.compile(r"regression_arg\(([0-9]+)\)") @@ -231,9 +229,8 @@ class AnalyticFunction: else: X[i].extend([np.nan] * len(val[model_attribute])) elif key[0] == state_or_tran and len(key[1]) != dimension: - vprint( - self.verbose, - "[W] Invalid parameter key length while gathering fit data for {}/{}. is {}, want {}.".format( + logging.warning( + "Invalid parameter key length while gathering fit data for {}/{}. is {}, want {}.".format( state_or_tran, model_attribute, len(key[1]), dimension ), ) @@ -266,9 +263,8 @@ class AnalyticFunction: error_function, self._regression_args, args=(X, Y), xtol=2e-15 ) except ValueError as err: - vprint( - self.verbose, - "[W] Fit failed for {}/{}: {} (function: {})".format( + logging.warning( + "Fit failed for {}/{}: {} (function: {})".format( state_or_tran, model_attribute, err, self._model_str ), ) @@ -277,16 +273,14 @@ class AnalyticFunction: self._regression_args = res.x self.fit_success = True else: - vprint( - self.verbose, - "[W] Fit failed for {}/{}: {} (function: {})".format( + logging.warning( + "Fit failed for {}/{}: {} (function: {})".format( state_or_tran, model_attribute, res.message, self._model_str ), ) else: - vprint( - self.verbose, - "[W] Insufficient amount of valid parameter keys, cannot fit {}/{}".format( + logging.warning( + "Insufficient amount of valid parameter keys, cannot fit {}/{}".format( state_or_tran, model_attribute ), ) |