abs - relaxing the minimum beta restriction

bsaakash · bsaakash · commit 53714baca05e · 2025-07-18T01:59:40.000-07:00
diff --git a/modules/performUQ/UCSD_UQ/tmcmcFunctions.py b/modules/performUQ/UCSD_UQ/tmcmcFunctions.py
@@ -371,10 +371,10 @@ def compute_beta_evidence(beta, log_likelihoods, logFile, threshold=1.0):  # noq
         #     if ((cov_weights > (threshold+0.00000005)) or  (std_weights == 0)):
         #         dBeta = dBeta*0.99999999
 
-        if dBeta < 1e-3:  # noqa: PLR2004
-            dBeta = 1e-3  # noqa: N806
-            weights, cov_weights, std_weights = get_weights(dBeta, log_likelihoods)
-            break
+        # if dBeta < 1e-3:
+        #     dBeta = 1e-3
+        #     weights, cov_weights, std_weights = get_weights(dBeta, log_likelihoods)
+        #     break
         weights, cov_weights, std_weights = get_weights(dBeta, log_likelihoods)
 
     beta = beta + dBeta
diff --git a/modules/performUQ/common/adaptive_doe.py b/modules/performUQ/common/adaptive_doe.py
@@ -152,7 +152,7 @@ def select_training_points(
             scaled_candidates = self._scale(candidate_pool)
             scaled_mci_samples = self._scale(mci_samples)
 
-            # 3. Fit GP with dummy outputs
+            # 3. Set GP inputs
             self.gp_model_for_doe.set_XY(
                 scaled_x_train, np.zeros((scaled_x_train.shape[0], 1))
             )

Original file line number	Diff line number	Diff line change
`@@ -152,7 +152,7 @@ def select_training_points(`
`152`	`152`	`scaled_candidates = self._scale(candidate_pool)`
`153`	`153`	`scaled_mci_samples = self._scale(mci_samples)`
`154`	`154`
`155`		`- # 3. Fit GP with dummy outputs`
	`155`	`+ # 3. Set GP inputs`
`156`	`156`	`self.gp_model_for_doe.set_XY(`
`157`	`157`	`scaled_x_train, np.zeros((scaled_x_train.shape[0], 1))`
`158`	`158`	`)`