diff options
Diffstat (limited to 'lib')
| -rw-r--r-- | lib/functions.py | 8 | ||||
| -rw-r--r-- | lib/paramfit.py | 8 |
2 files changed, 14 insertions, 2 deletions
diff --git a/lib/functions.py b/lib/functions.py index 35b04ef..b76814b 100644 --- a/lib/functions.py +++ b/lib/functions.py @@ -27,6 +27,7 @@ dfatool_rmt_relevance_threshold = float( os.getenv("DFATOOL_RMT_RELEVANCE_THRESHOLD", "0.5") ) +dfatool_uls_loss_fun = os.getenv("DFATOOL_ULS_LOSS_FUNCTION", "linear") dfatool_uls_min_bound = float(os.getenv("DFATOOL_ULS_MIN_BOUND", -np.inf)) if dfatool_preproc_relevance_method == "mi": @@ -1692,7 +1693,11 @@ class FOLFunction(SKLearnRegressionFunction): self.model_args = list(np.ones((num_vars))) try: res = optimize.least_squares( - error_function, self.model_args, args=(fit_parameters, data), xtol=2e-15 + error_function, + self.model_args, + args=(fit_parameters, data), + xtol=2e-15, + loss=dfatool_uls_loss_fun, ) except ValueError as err: logger.warning(f"Fit failed: {err} (function: {self.model_function})") @@ -1955,6 +1960,7 @@ class AnalyticFunction(ModelFunction): self.model_args, args=(X, Y), xtol=2e-15, + loss=dfatool_uls_loss_fun, bounds=(lower_bounds, upper_bounds), ) except ValueError as err: diff --git a/lib/paramfit.py b/lib/paramfit.py index 000aa9c..84eba2b 100644 --- a/lib/paramfit.py +++ b/lib/paramfit.py @@ -16,9 +16,14 @@ from .utils import ( ) logger = logging.getLogger(__name__) -best_fit_metric = os.getenv("DFATOOL_ULS_ERROR_METRIC", "ssr") +dfatool_uls_loss_fun = os.getenv("DFATOOL_ULS_LOSS_FUNCTION", "linear") dfatool_uls_min_bound = float(os.getenv("DFATOOL_ULS_MIN_BOUND", -np.inf)) +if dfatool_uls_loss_fun == "linear": + best_fit_metric = os.getenv("DFATOOL_ULS_ERROR_METRIC", "ssr") +else: + best_fit_metric = os.getenv("DFATOOL_ULS_ERROR_METRIC", "mae") + class ParamFit: """ @@ -222,6 +227,7 @@ def _try_fits( ini, args=(X, Y), xtol=2e-15, + loss=dfatool_uls_loss_fun, bounds=param_function.bounds, ) except FloatingPointError as e: |