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authorBirte Kristina Friesel <birte.friesel@uos.de>2025-07-01 11:31:35 +0200
committerBirte Kristina Friesel <birte.friesel@uos.de>2025-07-01 11:31:35 +0200
commitd95c23431cfac423a19f7827155ae836cbbe558a (patch)
treeecbde25a8c7f49406e1deab7717c9f4046a6c7b2 /lib/functions.py
parentc9b2559aca435d65ab33a7bfaaa0ee0f9620596e (diff)
Add DFATOOL_ULS_LOSS_FUNCTION variablemain
Diffstat (limited to 'lib/functions.py')
-rw-r--r--lib/functions.py8
1 files changed, 7 insertions, 1 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: