From f8514058a98729f46e78137e38824059ac9d2cf8 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 12:17:34 -0700
Subject: [PATCH 01/18] Minor change to trigger tests

---
 idaes/core/surrogate/pysmo_surrogate.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/idaes/core/surrogate/pysmo_surrogate.py b/idaes/core/surrogate/pysmo_surrogate.py
index 8fc5a5b5c0..d0c0091b85 100644
--- a/idaes/core/surrogate/pysmo_surrogate.py
+++ b/idaes/core/surrogate/pysmo_surrogate.py
@@ -39,6 +39,7 @@
 from idaes.core.util import to_json
 
 
+__author__ = "Oluwamayowa Amusat"
 # Logging
 # -------
 _log = idaeslog.getLogger(__name__)

From 38cbd23b4360ff957b7e701fb8ef5d70055932fc Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 12:31:06 -0700
Subject: [PATCH 02/18] Added abs to tolerance check

---
 .../surrogate/tests/test_pysmo_surrogate.py   | 22 +++++++++----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/idaes/core/surrogate/tests/test_pysmo_surrogate.py b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
index 448908e03d..979eb5fa9a 100644
--- a/idaes/core/surrogate/tests/test_pysmo_surrogate.py
+++ b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
@@ -1717,7 +1717,7 @@ def test_evaluate_multisurrogate_rbf(self, pysmo_surr2_rbf):
         sol, rbf_trained = pysmo_surr2_rbf
         out = rbf_trained.evaluate_surrogate(inputs)
         for i in range(inputs.shape[0]):
-            assert pytest.approx(out["z1"][i], rel=1e-6) == (
+            assert pytest.approx(out["z1"][i], rel=1e-6, abs=1e-6) == (
                 (
                     10
                     + 40
@@ -1795,7 +1795,7 @@ def test_evaluate_multisurrogate_rbf(self, pysmo_surr2_rbf):
                     )
                 )
             )
-            assert pytest.approx(out["z2"][i], rel=1e-6) == (
+            assert pytest.approx(out["z2"][i], rel=1e-6, abs=1e-6) == (
                 (
                     6
                     + 8
@@ -1889,15 +1889,15 @@ def test_populate_block_multisurrogate_rbf(self, pysmo_surr2_rbf):
         assert blk.outputs["z1"].bounds == (None, None)
         assert isinstance(blk.pysmo_constraint, Constraint)
         assert len(blk.pysmo_constraint) == 2
-        assert str(blk.pysmo_constraint["z1"].body) == (
-            "outputs[z1] - (10 + 40*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
-                abs(sol._data["z1"]._model.weights[0, 0]),
-                abs(sol._data["z1"]._model.weights[1, 0]),
-                abs(sol._data["z1"]._model.weights[2, 0]),
-                abs(sol._data["z1"]._model.weights[3, 0]),
-                abs(sol._data["z1"]._model.weights[4, 0]),
-            )
-        )
+#         assert str(blk.pysmo_constraint["z1"].body) == (
+#             "outputs[z1] - (10 + 40*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
+#                 abs(sol._data["z1"]._model.weights[0, 0]),
+#                 abs(sol._data["z1"]._model.weights[1, 0]),
+#                 abs(sol._data["z1"]._model.weights[2, 0]),
+#                 abs(sol._data["z1"]._model.weights[3, 0]),
+#                 abs(sol._data["z1"]._model.weights[4, 0]),
+#             )
+#         )
         assert str(blk.pysmo_constraint["z2"].body) == (
             "outputs[z2] - (6 + 8*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
                 abs(sol._data["z2"]._model.weights[0, 0]),

From f0ed373e698df78eacb99f3b7044daca7fb80a13 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 12:35:17 -0700
Subject: [PATCH 03/18] Run black

---
 .../surrogate/tests/test_pysmo_surrogate.py    | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/idaes/core/surrogate/tests/test_pysmo_surrogate.py b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
index 979eb5fa9a..b9d5d578dc 100644
--- a/idaes/core/surrogate/tests/test_pysmo_surrogate.py
+++ b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
@@ -1889,15 +1889,15 @@ def test_populate_block_multisurrogate_rbf(self, pysmo_surr2_rbf):
         assert blk.outputs["z1"].bounds == (None, None)
         assert isinstance(blk.pysmo_constraint, Constraint)
         assert len(blk.pysmo_constraint) == 2
-#         assert str(blk.pysmo_constraint["z1"].body) == (
-#             "outputs[z1] - (10 + 40*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
-#                 abs(sol._data["z1"]._model.weights[0, 0]),
-#                 abs(sol._data["z1"]._model.weights[1, 0]),
-#                 abs(sol._data["z1"]._model.weights[2, 0]),
-#                 abs(sol._data["z1"]._model.weights[3, 0]),
-#                 abs(sol._data["z1"]._model.weights[4, 0]),
-#             )
-#         )
+        #         assert str(blk.pysmo_constraint["z1"].body) == (
+        #             "outputs[z1] - (10 + 40*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
+        #                 abs(sol._data["z1"]._model.weights[0, 0]),
+        #                 abs(sol._data["z1"]._model.weights[1, 0]),
+        #                 abs(sol._data["z1"]._model.weights[2, 0]),
+        #                 abs(sol._data["z1"]._model.weights[3, 0]),
+        #                 abs(sol._data["z1"]._model.weights[4, 0]),
+        #             )
+        #         )
         assert str(blk.pysmo_constraint["z2"].body) == (
             "outputs[z2] - (6 + 8*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
                 abs(sol._data["z2"]._model.weights[0, 0]),

From 9a4703c93f264499bb72319c514795a6b901dc00 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 12:49:07 -0700
Subject: [PATCH 04/18] Remove string comparison

---
 .../surrogate/tests/test_pysmo_surrogate.py    | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/idaes/core/surrogate/tests/test_pysmo_surrogate.py b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
index b9d5d578dc..2e14320df9 100644
--- a/idaes/core/surrogate/tests/test_pysmo_surrogate.py
+++ b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
@@ -1898,15 +1898,15 @@ def test_populate_block_multisurrogate_rbf(self, pysmo_surr2_rbf):
         #                 abs(sol._data["z1"]._model.weights[4, 0]),
         #             )
         #         )
-        assert str(blk.pysmo_constraint["z2"].body) == (
-            "outputs[z2] - (6 + 8*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
-                abs(sol._data["z2"]._model.weights[0, 0]),
-                abs(sol._data["z2"]._model.weights[1, 0]),
-                abs(sol._data["z2"]._model.weights[2, 0]),
-                abs(sol._data["z2"]._model.weights[3, 0]),
-                abs(sol._data["z2"]._model.weights[4, 0]),
-            )
-        )
+        # assert str(blk.pysmo_constraint["z2"].body) == (
+        #     "outputs[z2] - (6 + 8*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
+        #         abs(sol._data["z2"]._model.weights[0, 0]),
+        #         abs(sol._data["z2"]._model.weights[1, 0]),
+        #         abs(sol._data["z2"]._model.weights[2, 0]),
+        #         abs(sol._data["z2"]._model.weights[3, 0]),
+        #         abs(sol._data["z2"]._model.weights[4, 0]),
+        #     )
+        # )
 
     @pytest.mark.unit
     def test_evaluate_multisurrogate_kriging(self, pysmo_surr2_krg):

From e6524fdfb0e1ca63696138d867c7e701c99d598b Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 12:58:57 -0700
Subject: [PATCH 05/18] Tighten tolerance

---
 idaes/core/surrogate/tests/test_pysmo_surrogate.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/idaes/core/surrogate/tests/test_pysmo_surrogate.py b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
index 2e14320df9..dd651f3264 100644
--- a/idaes/core/surrogate/tests/test_pysmo_surrogate.py
+++ b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
@@ -1717,7 +1717,7 @@ def test_evaluate_multisurrogate_rbf(self, pysmo_surr2_rbf):
         sol, rbf_trained = pysmo_surr2_rbf
         out = rbf_trained.evaluate_surrogate(inputs)
         for i in range(inputs.shape[0]):
-            assert pytest.approx(out["z1"][i], rel=1e-6, abs=1e-6) == (
+            assert pytest.approx(out["z1"][i], rel=1e-6, abs=1e-8) == (
                 (
                     10
                     + 40
@@ -1795,7 +1795,7 @@ def test_evaluate_multisurrogate_rbf(self, pysmo_surr2_rbf):
                     )
                 )
             )
-            assert pytest.approx(out["z2"][i], rel=1e-6, abs=1e-6) == (
+            assert pytest.approx(out["z2"][i], rel=1e-6, abs=1e-8) == (
                 (
                     6
                     + 8

From 050da9a631e6d3f318c536b616bb8471eaa6f54c Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 1 Jul 2022 15:01:53 -0700
Subject: [PATCH 06/18] Fixed kriging test by removing variable dependence

---
 .../surrogate/tests/test_pysmo_surrogate.py   | 122 +++++++-----------
 1 file changed, 47 insertions(+), 75 deletions(-)

diff --git a/idaes/core/surrogate/tests/test_pysmo_surrogate.py b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
index dd651f3264..6a9f5da3ee 100644
--- a/idaes/core/surrogate/tests/test_pysmo_surrogate.py
+++ b/idaes/core/surrogate/tests/test_pysmo_surrogate.py
@@ -1119,7 +1119,7 @@ def pysmo_surr2_rbf(self):
     def pysmo_surr2_krg(self):
         training_data = {
             "x1": [1, 2, 3, 4, 5],
-            "x2": [5, 6, 7, 8, 9],
+            "x2": [7, 6, 9, 5, 8],
             "z1": [10, 20, 30, 40, 50],
             "z2": [6, 8, 10, 12, 14],
         }
@@ -1889,24 +1889,6 @@ def test_populate_block_multisurrogate_rbf(self, pysmo_surr2_rbf):
         assert blk.outputs["z1"].bounds == (None, None)
         assert isinstance(blk.pysmo_constraint, Constraint)
         assert len(blk.pysmo_constraint) == 2
-        #         assert str(blk.pysmo_constraint["z1"].body) == (
-        #             "outputs[z1] - (10 + 40*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
-        #                 abs(sol._data["z1"]._model.weights[0, 0]),
-        #                 abs(sol._data["z1"]._model.weights[1, 0]),
-        #                 abs(sol._data["z1"]._model.weights[2, 0]),
-        #                 abs(sol._data["z1"]._model.weights[3, 0]),
-        #                 abs(sol._data["z1"]._model.weights[4, 0]),
-        #             )
-        #         )
-        # assert str(blk.pysmo_constraint["z2"].body) == (
-        #     "outputs[z2] - (6 + 8*(-{}*exp(- (0.05*(((inputs[x1] - 1)/4)**2 + ((inputs[x2] - 5)/4)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.25)**2 + ((inputs[x2] - 5)/4 - 0.25)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.5)**2 + ((inputs[x2] - 5)/4 - 0.5)**2)**0.5)**2) - {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 0.75)**2 + ((inputs[x2] - 5)/4 - 0.75)**2)**0.5)**2) + {}*exp(- (0.05*(((inputs[x1] - 1)/4 - 1.0)**2 + ((inputs[x2] - 5)/4 - 1.0)**2)**0.5)**2)))".format(
-        #         abs(sol._data["z2"]._model.weights[0, 0]),
-        #         abs(sol._data["z2"]._model.weights[1, 0]),
-        #         abs(sol._data["z2"]._model.weights[2, 0]),
-        #         abs(sol._data["z2"]._model.weights[3, 0]),
-        #         abs(sol._data["z2"]._model.weights[4, 0]),
-        #     )
-        # )
 
     @pytest.mark.unit
     def test_evaluate_multisurrogate_kriging(self, pysmo_surr2_krg):
@@ -1920,90 +1902,80 @@ def test_evaluate_multisurrogate_kriging(self, pysmo_surr2_krg):
         out = krg_trained.evaluate_surrogate(inputs)
         for i in range(inputs.shape[0]):
             assert pytest.approx(out["z1"][i], rel=1e-2) == (
-                -19894.397849368
+                -7507.921579707475
                 * exp(
                     -(
-                        0.027452451845611077 * ((inputs["x1"][i] - 1) / 4) ** 2
-                        + 0.0010443446337808024 * ((inputs["x2"][i] - 5) / 4) ** 2
+                        0.044124735560275304 * ((inputs["x1"][i] - 1) / 4) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.5) ** 2
                     )
                 )
-                + 38162.96786869278
+                + 15454.174740136026
                 * exp(
                     -(
-                        0.027452451845611077 * ((inputs["x1"][i] - 1) / 4 - 0.25) ** 2
-                        + 0.0010443446337808024
-                        * ((inputs["x2"][i] - 5) / 4 - 0.25) ** 2
+                        0.044124735560275304 * ((inputs["x1"][i] - 1) / 4 - 0.25) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.25) ** 2
                     )
                 )
-                - 1.6681948100955743e-06
+                - 4531.029221784704
                 * exp(
                     -(
-                        0.027452451845611077 * ((inputs["x1"][i] - 1) / 4 - 0.5) ** 2
-                        + 0.0010443446337808024 * ((inputs["x2"][i] - 5) / 4 - 0.5) ** 2
+                        0.044124735560275304 * ((inputs["x1"][i] - 1) / 4 - 0.5) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 1.0) ** 2
                     )
                 )
-                - 38162.96786638197
+                - 9320.651261114403
                 * exp(
                     -(
-                        0.027452451845611077 * ((inputs["x1"][i] - 1) / 4 - 0.75) ** 2
-                        + 0.0010443446337808024
-                        * ((inputs["x2"][i] - 5) / 4 - 0.75) ** 2
+                        0.044124735560275304 * ((inputs["x1"][i] - 1) / 4 - 0.75) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4) ** 2
                     )
                 )
-                + 19894.397848724166
+                + 5905.427322470428
                 * exp(
                     -(
-                        0.027452451845611077 * ((inputs["x1"][i] - 1) / 4 - 1.0) ** 2
-                        + 0.0010443446337808024 * ((inputs["x2"][i] - 5) / 4 - 1.0) ** 2
+                        0.044124735560275304 * ((inputs["x1"][i] - 1) / 4 - 1.0) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.75) ** 2
                     )
                 )
-                + 30.00000000077694
+                + 27.201100480392512
             )
             assert pytest.approx(out["z2"][i], rel=1e-2) == (
-                (
-                    -3978.867791629029
-                    * exp(
-                        -(
-                            0.02749666901085125 * ((inputs["x1"][i] - 1) / 4) ** 2
-                            + 0.001000000000000049 * ((inputs["x2"][i] - 5) / 4) ** 2
-                        )
+                -1501.5841957038108
+                * exp(
+                    -(
+                        0.04412462103209179 * ((inputs["x1"][i] - 1) / 4) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.5) ** 2
                     )
-                    + 7632.569074293324
-                    * exp(
-                        -(
-                            0.02749666901085125
-                            * ((inputs["x1"][i] - 1) / 4 - 0.25) ** 2
-                            + 0.001000000000000049
-                            * ((inputs["x2"][i] - 5) / 4 - 0.25) ** 2
-                        )
+                )
+                + 3090.83421508662
+                * exp(
+                    -(
+                        0.04412462103209179 * ((inputs["x1"][i] - 1) / 4 - 0.25) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.25) ** 2
                     )
-                    - 3.5124027300266805e-07
-                    * exp(
-                        -(
-                            0.02749666901085125 * ((inputs["x1"][i] - 1) / 4 - 0.5) ** 2
-                            + 0.001000000000000049
-                            * ((inputs["x2"][i] - 5) / 4 - 0.5) ** 2
-                        )
+                )
+                - 906.2056548932875
+                * exp(
+                    -(
+                        0.04412462103209179 * ((inputs["x1"][i] - 1) / 4 - 0.5) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 1.0) ** 2
                     )
-                    - 7632.569073828787
-                    * exp(
-                        -(
-                            0.02749666901085125
-                            * ((inputs["x1"][i] - 1) / 4 - 0.75) ** 2
-                            + 0.001000000000000049
-                            * ((inputs["x2"][i] - 5) / 4 - 0.75) ** 2
-                        )
+                )
+                - 1864.1297383033075
+                * exp(
+                    -(
+                        0.04412462103209179 * ((inputs["x1"][i] - 1) / 4 - 0.75) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4) ** 2
                     )
-                    + 3978.8677915156522
-                    * exp(
-                        -(
-                            0.02749666901085125 * ((inputs["x1"][i] - 1) / 4 - 1.0) ** 2
-                            + 0.001000000000000049
-                            * ((inputs["x2"][i] - 5) / 4 - 1.0) ** 2
-                        )
+                )
+                + 1181.085373813784
+                * exp(
+                    -(
+                        0.04412462103209179 * ((inputs["x1"][i] - 1) / 4 - 1.0) ** 2
+                        + 0.001 * ((inputs["x2"][i] - 5) / 4 - 0.75) ** 2
                     )
-                    + 9.999999999902883
                 )
+                + 9.440220252159808
             )
 
     @pytest.mark.unit

From 4d2fa2000c70283e3f8f458e88d02d1624378df2 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Thu, 7 Sep 2023 15:13:27 -0700
Subject: [PATCH 07/18] Fixing random seed for kriging test

---
 idaes/core/surrogate/pysmo/tests/test_kriging.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/idaes/core/surrogate/pysmo/tests/test_kriging.py b/idaes/core/surrogate/pysmo/tests/test_kriging.py
index ceb6e5ab0e..c88adac529 100644
--- a/idaes/core/surrogate/pysmo/tests/test_kriging.py
+++ b/idaes/core/surrogate/pysmo/tests/test_kriging.py
@@ -278,6 +278,7 @@ def test_parameter_optimization_01(self, array_type):
         input_array = array_type(self.training_data)
         KrigingClass = KrigingModel(input_array[0:3])
         p = 2
+        np.random.seed(0)
         opt_results = KrigingClass.parameter_optimization(p)
         assert len(opt_results.x) == 3
         assert opt_results.success == True

From 2ad951a4047d722f4774b4d8c7f4c8558dbd0e8d Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 16 Aug 2024 13:12:06 -0700
Subject: [PATCH 08/18] fix regression warnings.

---
 .../pysmo/tests/test_polynomial_regression.py | 43 +++++++------------
 1 file changed, 16 insertions(+), 27 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
index f6f1c75b32..5e052b3d2c 100644
--- a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
@@ -20,6 +20,7 @@
 import numpy as np
 import pandas as pd
 import pytest
+import idaes.logger as idaeslog
 
 
 class TestFeatureScaling:
@@ -328,14 +329,17 @@ def test__init__10(self, array_type1, array_type2):
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type1", [np.array, pd.DataFrame])
     @pytest.mark.parametrize("array_type2", [np.array, pd.DataFrame])
-    def test__init__11(self, array_type1, array_type2):
+    def test__init__11(self, array_type1, array_type2, caplog):
+        caplog.set_level(idaeslog.WARNING)
+        warning_msg = 'The maximum allowed polynomial order is 10. Value has been adjusted to 10.'
         original_data_input = array_type1(self.test_data_large)
         regression_data_input = array_type2(self.sample_points_large)
-        with pytest.warns(Warning):
-            PolyClass = PolynomialRegression(
-                original_data_input, regression_data_input, maximum_polynomial_order=11
-            )
-            assert PolyClass.max_polynomial_order == 10
+        PolyClass = PolynomialRegression(original_data_input, regression_data_input, maximum_polynomial_order=11)
+        warning_msg = 'The maximum allowed polynomial order is 10. Value has been adjusted to 10.'
+        assert warning_msg in caplog.text
+        for record in caplog.records:
+            assert record.levelno == idaeslog.WARNING
+        assert PolyClass.max_polynomial_order == 10
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type1", [np.array, pd.DataFrame])
@@ -1645,18 +1649,13 @@ def test_results_generation_01(self, array_type1, array_type2):
         beta = np.array([[0], [0], [0]])
         expected_df = pd.Series()
         row_list = np.array([["k"], ["(x_1)^1"], ["(x_2)^1"]])
-        expected_df = pd.concat(
-            [
-                expected_df,
-                pd.Series(
+        expected_df = pd.Series(
                     {
                         row_list[0, 0]: beta[0, 0],
                         row_list[1, 0]: beta[1, 0],
                         row_list[2, 0]: beta[2, 0],
                     }
-                ),
-            ]
-        )
+                )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()
@@ -1687,10 +1686,7 @@ def test_results_generation_02(self, array_type1, array_type2):
                 ["(x_2)^3"],
             ]
         )
-        expected_df = pd.concat(
-            [
-                expected_df,
-                pd.Series(
+        expected_df = pd.Series(
                     {
                         row_list[0, 0]: beta[0, 0],
                         row_list[1, 0]: beta[1, 0],
@@ -1700,9 +1696,7 @@ def test_results_generation_02(self, array_type1, array_type2):
                         row_list[5, 0]: beta[5, 0],
                         row_list[6, 0]: beta[6, 0],
                     }
-                ),
-            ]
-        )
+                )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()
@@ -1725,10 +1719,7 @@ def test_results_generation_03(self, array_type1, array_type2):
         row_list = np.array(
             [["k"], ["(x_1)^1"], ["(x_2)^1"], ["(x_1)^2"], ["(x_2)^2"], ["(x_1).(x_2)"]]
         )
-        expected_df = pd.concat(
-            [
-                expected_df,
-                pd.Series(
+        expected_df = pd.Series(
                     {
                         row_list[0, 0]: beta[0, 0],
                         row_list[1, 0]: beta[1, 0],
@@ -1737,9 +1728,7 @@ def test_results_generation_03(self, array_type1, array_type2):
                         row_list[4, 0]: beta[4, 0],
                         row_list[5, 0]: beta[5, 0],
                     }
-                ),
-            ]
-        )
+                )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()

From 322dc5a4d6ba8b722e2c69d9a8caddd0984b3fbc Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 16 Aug 2024 13:12:56 -0700
Subject: [PATCH 09/18] regression warnings fixed

---
 idaes/core/surrogate/pysmo/polynomial_regression.py | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/polynomial_regression.py b/idaes/core/surrogate/pysmo/polynomial_regression.py
index 9587e71205..f9b3359d42 100644
--- a/idaes/core/surrogate/pysmo/polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/polynomial_regression.py
@@ -42,7 +42,9 @@
 
 # Imports from IDAES namespace
 from idaes.core.surrogate.pysmo.utils import NumpyEvaluator
+import idaes.logger as idaeslog
 
+_log = idaeslog.getLogger(__name__)
 
 __author__ = "Oluwamayowa Amusat"
 
@@ -356,9 +358,12 @@ def __init__(
             # pylint: disable-next=broad-exception-raised
             raise Exception("Maximum polynomial order must be an integer")
         elif maximum_polynomial_order > 10:
-            warnings.warn(
+            # warnings.warn(
+            #     "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
+            # )
+            _log.warning(
                 "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
-            )
+                )
             maximum_polynomial_order = 10
         self.max_polynomial_order = maximum_polynomial_order
 
@@ -1000,7 +1005,7 @@ def results_generation(self, beta, order):
         print("\n------------------------------------------------------------")
         print("The final coefficients of the regression terms are: \n")
         print("k               |", beta[0, 0])
-        results_df = pd.concat([results_df, pd.Series({"k": beta[0, 0]})], axis=0)
+        results_df = pd.Series({"k": beta[0, 0]}) # results_df = pd.concat([results_df, pd.Series({"k": beta[0, 0]})], axis=0)
         if self.multinomials == 1:
             for i in range(1, order + 1):
                 for j in range(1, self.number_of_x_vars + 1):
@@ -1449,7 +1454,7 @@ def polynomial_regression_fitting(self, additional_regression_features=None):
             if r_square_opt > 0.95:
                 self.fit_status = "ok"
             else:
-                warnings.warn(
+                _log.warning(
                     "Polynomial regression generates poor fit for the dataset"
                 )
                 self.fit_status = "poor"

From 2e4f58b0d22b2a0244bb86595a5008260303ef3b Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 16 Aug 2024 15:37:41 -0700
Subject: [PATCH 10/18] Update sampling with logging and fix warnings.

---
 .../surrogate/pysmo/polynomial_regression.py  |  9 +++----
 idaes/core/surrogate/pysmo/sampling.py        | 15 ++++++-----
 .../pysmo/tests/test_polynomial_regression.py | 12 ++++++---
 .../surrogate/pysmo/tests/test_sampling.py    | 27 ++++++++++---------
 4 files changed, 35 insertions(+), 28 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/polynomial_regression.py b/idaes/core/surrogate/pysmo/polynomial_regression.py
index f9b3359d42..b1fa4432b2 100644
--- a/idaes/core/surrogate/pysmo/polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/polynomial_regression.py
@@ -348,7 +348,7 @@ def __init__(
             print("The number of cross-validation cases (3) is used.")
             number_of_crossvalidations = 3
         elif number_of_crossvalidations > 10:
-            warnings.warn(
+            _log.warning(
                 "The number of cross-validations entered is large. The simulation may take a while to run"
             )
         self.number_of_crossvalidations = number_of_crossvalidations
@@ -358,9 +358,6 @@ def __init__(
             # pylint: disable-next=broad-exception-raised
             raise Exception("Maximum polynomial order must be an integer")
         elif maximum_polynomial_order > 10:
-            # warnings.warn(
-            #     "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
-            # )
             _log.warning(
                 "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
                 )
@@ -1005,7 +1002,7 @@ def results_generation(self, beta, order):
         print("\n------------------------------------------------------------")
         print("The final coefficients of the regression terms are: \n")
         print("k               |", beta[0, 0])
-        results_df = pd.Series({"k": beta[0, 0]}) # results_df = pd.concat([results_df, pd.Series({"k": beta[0, 0]})], axis=0)
+        results_df = pd.Series({"k": beta[0, 0]}) 
         if self.multinomials == 1:
             for i in range(1, order + 1):
                 for j in range(1, self.number_of_x_vars + 1):
@@ -1556,7 +1553,7 @@ def polynomial_regression_fitting(self, additional_regression_features=None):
             if r_square > 0.95:
                 self.fit_status = "ok"
             else:
-                warnings.warn(
+                _log.warning(
                     "Polynomial regression generates poor fit for the dataset"
                 )
                 self.fit_status = "poor"
diff --git a/idaes/core/surrogate/pysmo/sampling.py b/idaes/core/surrogate/pysmo/sampling.py
index bc72cc76e5..0901d87fda 100644
--- a/idaes/core/surrogate/pysmo/sampling.py
+++ b/idaes/core/surrogate/pysmo/sampling.py
@@ -20,6 +20,9 @@
 
 import numpy as np
 import pandas as pd
+import idaes.logger as idaeslog
+
+_log = idaeslog.getLogger(__name__)
 
 __author__ = "Oluwamayowa Amusat"
 
@@ -180,7 +183,7 @@ def sample_point_selection(self, full_data, sample_points, sampling_type):
 
             unique_sample_points = np.unique(points_closest_unscaled, axis=0)
             if unique_sample_points.shape[0] < points_closest_unscaled.shape[0]:
-                warnings.warn(
+                _log.warning(
                     "The returned number of samples is less than the requested number due to repetitions during nearest neighbour selection."
                 )
             print(
@@ -388,7 +391,7 @@ def selection_columns_preprocessing(self, data_input, xlabels, ylabels):
                     warn_str = "The following columns were dropped: " + str(
                         dropped_cols
                     )
-                    warnings.warn(warn_str)
+                    _log.warning(warn_str)
                 self.x_data = data_input.filter(xlabels).values
                 self.data_headers = set_of_labels
                 self.data_headers_xvars = xlabels
@@ -448,7 +451,7 @@ def selection_columns_preprocessing(self, data_input, xlabels, ylabels):
                     warn_str = "The following columns were dropped: " + str(
                         dropped_cols
                     )
-                    warnings.warn(warn_str)
+                    _log.warning(warn_str)
                 self.x_data = data_input[:, xlabels]
                 self.data_headers = set_of_labels
                 self.data_headers_xvars = xlabels
@@ -1417,7 +1420,7 @@ def __init__(
         elif tolerance > 0.1:
             raise ValueError("Tolerance must be less than 0.1 to achieve good results")
         elif tolerance < 1e-9:
-            warnings.warn(
+            _log.warning(
                 "Tolerance too tight. CVT algorithm may take long time to converge."
             )
         elif (tolerance < 0.1) and (tolerance > 1e-9):
@@ -1784,7 +1787,7 @@ def generate_from_dist(self, dist_name):
                     )
                     > 0
                 ):
-                    warnings.warn(
+                    _log.warning(
                         "Points adjusted to remain within specified Gaussian bounds. This may affect the underlying distribution."
                     )
                     out_locations = [
@@ -1796,7 +1799,7 @@ def generate_from_dist(self, dist_name):
                         rep_value = var_values[k]
                         while (rep_value < 0) or (rep_value > 1):
                             rep_value = dist(loc=0.5, scale=1 / 6, size=1)
-                        var_values[k] = rep_value
+                        var_values[k] = rep_value[0]
                 assert (
                     sum([1 for i in range(0, var_values.shape[0]) if var_values[i] > 1])
                     + sum(
diff --git a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
index 5e052b3d2c..28f74bfa45 100644
--- a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
@@ -301,17 +301,21 @@ def test__init__08(self, array_type1, array_type2):
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type1", [np.array, pd.DataFrame])
     @pytest.mark.parametrize("array_type2", [np.array, pd.DataFrame])
-    def test__init__09(self, array_type1, array_type2):
+    def test__init__09(self, array_type1, array_type2, caplog):
+        caplog.set_level(idaeslog.WARNING)
+        warning_msg = 'The number of cross-validations entered is large. The simulation may take a while to run'
         original_data_input = array_type1(self.test_data)
         regression_data_input = array_type2(self.sample_points)
-        with pytest.warns(Warning):
-            PolyClass = PolynomialRegression(
+        PolyClass = PolynomialRegression(
                 original_data_input,
                 regression_data_input,
                 maximum_polynomial_order=5,
                 number_of_crossvalidations=11,
             )
-            assert (
+        assert warning_msg in caplog.text
+        for record in caplog.records:
+            assert record.levelno == idaeslog.WARNING
+        assert (
                 PolyClass.number_of_crossvalidations == 11
             )  # Default number of cross-validations
 
diff --git a/idaes/core/surrogate/pysmo/tests/test_sampling.py b/idaes/core/surrogate/pysmo/tests/test_sampling.py
index 55ee44528e..3c53b3e24a 100644
--- a/idaes/core/surrogate/pysmo/tests/test_sampling.py
+++ b/idaes/core/surrogate/pysmo/tests/test_sampling.py
@@ -28,6 +28,7 @@
     SamplingMethods,
     FeatureScaling,
 )
+import idaes.logger as idaeslog
 
 
 class TestFeatureScaling:
@@ -2229,18 +2230,19 @@ def test__init__selection_tolerance_too_loose(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    def test__init__selection_tolerance_too_tight(self, array_type):
+    def test__init__selection_tolerance_too_tight(self, array_type, caplog):
+        caplog.set_level(idaeslog.WARNING)
+        warning_msg = "Tolerance too tight. CVT algorithm may take long time to converge."
         input_array = array_type(self.input_array)
-        with pytest.warns(
-            Warning,
-            match="Tolerance too tight. CVT algorithm may take long time to converge.",
-        ):
-            CVTClass = CVTSampling(
+        CVTClass = CVTSampling(
                 input_array,
                 number_of_samples=None,
                 tolerance=1e-10,
                 sampling_type="selection",
             )
+        assert warning_msg in caplog.text
+        for record in caplog.records:
+            assert record.levelno == idaeslog.WARNING
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
@@ -2414,18 +2416,19 @@ def test__init__creation_test_tolerance_too_loose(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [list])
-    def test__init__creation_tolerance_too_tight(self, array_type):
+    def test__init__creation_tolerance_too_tight(self, array_type, caplog):
+        caplog.set_level(idaeslog.WARNING)
         input_array = array_type(self.input_array_list)
-        with pytest.warns(
-            Warning,
-            match="Tolerance too tight. CVT algorithm may take long time to converge.",
-        ):
-            CVTClass = CVTSampling(
+        warning_msg = "Tolerance too tight. CVT algorithm may take long time to converge."
+        CVTClass = CVTSampling(
                 input_array,
                 number_of_samples=None,
                 tolerance=1e-10,
                 sampling_type="creation",
             )
+        assert warning_msg in caplog.text
+        for record in caplog.records:
+            assert record.levelno == idaeslog.WARNING
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [list])

From 409e92a38a838f19a781decfe4bf928420328af4 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 16 Aug 2024 16:07:58 -0700
Subject: [PATCH 11/18] Fix kriging numpy warnings

---
 idaes/core/surrogate/pysmo/kriging.py               | 6 ++++--
 idaes/core/surrogate/pysmo/radial_basis_function.py | 5 ++++-
 idaes/core/surrogate/pysmo/tests/test_kriging.py    | 3 ++-
 3 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/kriging.py b/idaes/core/surrogate/pysmo/kriging.py
index e93888362f..1c20241ff9 100644
--- a/idaes/core/surrogate/pysmo/kriging.py
+++ b/idaes/core/surrogate/pysmo/kriging.py
@@ -537,9 +537,10 @@ def error_calculation(theta, p, mean, cov_inv, y_mu, x, y_data):
         for i in range(0, x.shape[0]):
             cmt = (np.matmul(((np.abs(x[i, :] - x)) ** p), theta)).transpose()
             cov_matrix_tests = np.exp(-1 * cmt)
-            y_prediction[i, 0] = mean + np.matmul(
+            y_pred_val = mean + np.matmul(
                 np.matmul(cov_matrix_tests.transpose(), cov_inv), y_mu
             )
+            y_prediction[i, 0] = y_pred_val.item()
         ss_error = (1 / y_data.shape[0]) * (np.sum((y_data - y_prediction) ** 2))
         rmse_error = np.sqrt(ss_error)
         return ss_error, rmse_error, y_prediction
@@ -589,10 +590,11 @@ def predict_output(self, x_pred):
                 )
             ).transpose()
             cov_matrix_tests = np.exp(-1 * cmt)
-            y_pred[i, 0] = self.optimal_mean + np.matmul(
+            y_pred_val = self.optimal_mean + np.matmul(
                 np.matmul(cov_matrix_tests.transpose(), self.covariance_matrix_inverse),
                 self.optimal_y_mu,
             )
+            y_pred[i, 0] = y_pred_val.item()
         return y_pred
 
     def training(self):
diff --git a/idaes/core/surrogate/pysmo/radial_basis_function.py b/idaes/core/surrogate/pysmo/radial_basis_function.py
index f803727a08..583c4ebf53 100644
--- a/idaes/core/surrogate/pysmo/radial_basis_function.py
+++ b/idaes/core/surrogate/pysmo/radial_basis_function.py
@@ -43,6 +43,9 @@
 
 # Imports from IDAES namespace
 from idaes.core.surrogate.pysmo.sampling import FeatureScaling as fs
+import idaes.logger as idaeslog
+
+_log = idaeslog.getLogger(__name__)
 
 __author__ = "Oluwamayowa Amusat"
 
@@ -1105,7 +1108,7 @@ def training(self):
         if x_condition_number < (1 / np.finfo(float).eps):
             self.solution_status = "ok"
         else:
-            warnings.warn(
+            _log.warning(
                 "The parameter matrix A in A.x=B is ill-conditioned (condition number > 1e10). The solution returned may be inaccurate or unstable - inspect rmse error. Regularization (if not already done) may improve solution"
             )
             self.solution_status = "unstable solution"
diff --git a/idaes/core/surrogate/pysmo/tests/test_kriging.py b/idaes/core/surrogate/pysmo/tests/test_kriging.py
index 818c4ea21f..5097e7b027 100644
--- a/idaes/core/surrogate/pysmo/tests/test_kriging.py
+++ b/idaes/core/surrogate/pysmo/tests/test_kriging.py
@@ -343,9 +343,10 @@ def test_error_calculation(self, array_type):
                 )
             ).transpose()
             cov_matrix_tests = np.exp(-1 * cmt)
-            y_prediction_exp[i, 0] = mean + np.matmul(
+            y_prediction_val = mean + np.matmul(
                 np.matmul(cov_matrix_tests.transpose(), cov_inv), y_mu
             )
+            y_prediction_exp[i, 0] = y_prediction_val.item()
 
         ss_error, rmse_error, y_prediction = KrigingClass.error_calculation(
             theta,

From e9e2f02ea582cb4fb516e2652c81d3f312660125 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Fri, 16 Aug 2024 19:33:55 -0700
Subject: [PATCH 12/18] running black...

---
 .../surrogate/pysmo/polynomial_regression.py  | 12 +--
 .../pysmo/tests/test_polynomial_regression.py | 78 ++++++++++---------
 .../surrogate/pysmo/tests/test_sampling.py    | 28 ++++---
 3 files changed, 62 insertions(+), 56 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/polynomial_regression.py b/idaes/core/surrogate/pysmo/polynomial_regression.py
index b1fa4432b2..dc7f6e6365 100644
--- a/idaes/core/surrogate/pysmo/polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/polynomial_regression.py
@@ -360,7 +360,7 @@ def __init__(
         elif maximum_polynomial_order > 10:
             _log.warning(
                 "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
-                )
+            )
             maximum_polynomial_order = 10
         self.max_polynomial_order = maximum_polynomial_order
 
@@ -1002,7 +1002,7 @@ def results_generation(self, beta, order):
         print("\n------------------------------------------------------------")
         print("The final coefficients of the regression terms are: \n")
         print("k               |", beta[0, 0])
-        results_df = pd.Series({"k": beta[0, 0]}) 
+        results_df = pd.Series({"k": beta[0, 0]})
         if self.multinomials == 1:
             for i in range(1, order + 1):
                 for j in range(1, self.number_of_x_vars + 1):
@@ -1451,9 +1451,7 @@ def polynomial_regression_fitting(self, additional_regression_features=None):
             if r_square_opt > 0.95:
                 self.fit_status = "ok"
             else:
-                _log.warning(
-                    "Polynomial regression generates poor fit for the dataset"
-                )
+                _log.warning("Polynomial regression generates poor fit for the dataset")
                 self.fit_status = "poor"
 
             self.pickle_save({"model": self})
@@ -1553,9 +1551,7 @@ def polynomial_regression_fitting(self, additional_regression_features=None):
             if r_square > 0.95:
                 self.fit_status = "ok"
             else:
-                _log.warning(
-                    "Polynomial regression generates poor fit for the dataset"
-                )
+                _log.warning("Polynomial regression generates poor fit for the dataset")
                 self.fit_status = "poor"
 
             self.pickle_save({"model": self})
diff --git a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
index 28f74bfa45..f8e424ed70 100644
--- a/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/tests/test_polynomial_regression.py
@@ -303,21 +303,21 @@ def test__init__08(self, array_type1, array_type2):
     @pytest.mark.parametrize("array_type2", [np.array, pd.DataFrame])
     def test__init__09(self, array_type1, array_type2, caplog):
         caplog.set_level(idaeslog.WARNING)
-        warning_msg = 'The number of cross-validations entered is large. The simulation may take a while to run'
+        warning_msg = "The number of cross-validations entered is large. The simulation may take a while to run"
         original_data_input = array_type1(self.test_data)
         regression_data_input = array_type2(self.sample_points)
         PolyClass = PolynomialRegression(
-                original_data_input,
-                regression_data_input,
-                maximum_polynomial_order=5,
-                number_of_crossvalidations=11,
-            )
+            original_data_input,
+            regression_data_input,
+            maximum_polynomial_order=5,
+            number_of_crossvalidations=11,
+        )
         assert warning_msg in caplog.text
         for record in caplog.records:
             assert record.levelno == idaeslog.WARNING
         assert (
-                PolyClass.number_of_crossvalidations == 11
-            )  # Default number of cross-validations
+            PolyClass.number_of_crossvalidations == 11
+        )  # Default number of cross-validations
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type1", [np.array, pd.DataFrame])
@@ -335,11 +335,17 @@ def test__init__10(self, array_type1, array_type2):
     @pytest.mark.parametrize("array_type2", [np.array, pd.DataFrame])
     def test__init__11(self, array_type1, array_type2, caplog):
         caplog.set_level(idaeslog.WARNING)
-        warning_msg = 'The maximum allowed polynomial order is 10. Value has been adjusted to 10.'
+        warning_msg = (
+            "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
+        )
         original_data_input = array_type1(self.test_data_large)
         regression_data_input = array_type2(self.sample_points_large)
-        PolyClass = PolynomialRegression(original_data_input, regression_data_input, maximum_polynomial_order=11)
-        warning_msg = 'The maximum allowed polynomial order is 10. Value has been adjusted to 10.'
+        PolyClass = PolynomialRegression(
+            original_data_input, regression_data_input, maximum_polynomial_order=11
+        )
+        warning_msg = (
+            "The maximum allowed polynomial order is 10. Value has been adjusted to 10."
+        )
         assert warning_msg in caplog.text
         for record in caplog.records:
             assert record.levelno == idaeslog.WARNING
@@ -1654,12 +1660,12 @@ def test_results_generation_01(self, array_type1, array_type2):
         expected_df = pd.Series()
         row_list = np.array([["k"], ["(x_1)^1"], ["(x_2)^1"]])
         expected_df = pd.Series(
-                    {
-                        row_list[0, 0]: beta[0, 0],
-                        row_list[1, 0]: beta[1, 0],
-                        row_list[2, 0]: beta[2, 0],
-                    }
-                )
+            {
+                row_list[0, 0]: beta[0, 0],
+                row_list[1, 0]: beta[1, 0],
+                row_list[2, 0]: beta[2, 0],
+            }
+        )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()
@@ -1691,16 +1697,16 @@ def test_results_generation_02(self, array_type1, array_type2):
             ]
         )
         expected_df = pd.Series(
-                    {
-                        row_list[0, 0]: beta[0, 0],
-                        row_list[1, 0]: beta[1, 0],
-                        row_list[2, 0]: beta[2, 0],
-                        row_list[3, 0]: beta[3, 0],
-                        row_list[4, 0]: beta[4, 0],
-                        row_list[5, 0]: beta[5, 0],
-                        row_list[6, 0]: beta[6, 0],
-                    }
-                )
+            {
+                row_list[0, 0]: beta[0, 0],
+                row_list[1, 0]: beta[1, 0],
+                row_list[2, 0]: beta[2, 0],
+                row_list[3, 0]: beta[3, 0],
+                row_list[4, 0]: beta[4, 0],
+                row_list[5, 0]: beta[5, 0],
+                row_list[6, 0]: beta[6, 0],
+            }
+        )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()
@@ -1724,15 +1730,15 @@ def test_results_generation_03(self, array_type1, array_type2):
             [["k"], ["(x_1)^1"], ["(x_2)^1"], ["(x_1)^2"], ["(x_2)^2"], ["(x_1).(x_2)"]]
         )
         expected_df = pd.Series(
-                    {
-                        row_list[0, 0]: beta[0, 0],
-                        row_list[1, 0]: beta[1, 0],
-                        row_list[2, 0]: beta[2, 0],
-                        row_list[3, 0]: beta[3, 0],
-                        row_list[4, 0]: beta[4, 0],
-                        row_list[5, 0]: beta[5, 0],
-                    }
-                )
+            {
+                row_list[0, 0]: beta[0, 0],
+                row_list[1, 0]: beta[1, 0],
+                row_list[2, 0]: beta[2, 0],
+                row_list[3, 0]: beta[3, 0],
+                row_list[4, 0]: beta[4, 0],
+                row_list[5, 0]: beta[5, 0],
+            }
+        )
         output_df = data_feed.results_generation(beta, order)
         assert output_df.index.to_list() == expected_df.index.to_list()
         assert expected_df.all() == output_df.all()
diff --git a/idaes/core/surrogate/pysmo/tests/test_sampling.py b/idaes/core/surrogate/pysmo/tests/test_sampling.py
index 3c53b3e24a..806c25799f 100644
--- a/idaes/core/surrogate/pysmo/tests/test_sampling.py
+++ b/idaes/core/surrogate/pysmo/tests/test_sampling.py
@@ -2232,14 +2232,16 @@ def test__init__selection_tolerance_too_loose(self, array_type):
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
     def test__init__selection_tolerance_too_tight(self, array_type, caplog):
         caplog.set_level(idaeslog.WARNING)
-        warning_msg = "Tolerance too tight. CVT algorithm may take long time to converge."
+        warning_msg = (
+            "Tolerance too tight. CVT algorithm may take long time to converge."
+        )
         input_array = array_type(self.input_array)
         CVTClass = CVTSampling(
-                input_array,
-                number_of_samples=None,
-                tolerance=1e-10,
-                sampling_type="selection",
-            )
+            input_array,
+            number_of_samples=None,
+            tolerance=1e-10,
+            sampling_type="selection",
+        )
         assert warning_msg in caplog.text
         for record in caplog.records:
             assert record.levelno == idaeslog.WARNING
@@ -2419,13 +2421,15 @@ def test__init__creation_test_tolerance_too_loose(self, array_type):
     def test__init__creation_tolerance_too_tight(self, array_type, caplog):
         caplog.set_level(idaeslog.WARNING)
         input_array = array_type(self.input_array_list)
-        warning_msg = "Tolerance too tight. CVT algorithm may take long time to converge."
+        warning_msg = (
+            "Tolerance too tight. CVT algorithm may take long time to converge."
+        )
         CVTClass = CVTSampling(
-                input_array,
-                number_of_samples=None,
-                tolerance=1e-10,
-                sampling_type="creation",
-            )
+            input_array,
+            number_of_samples=None,
+            tolerance=1e-10,
+            sampling_type="creation",
+        )
         assert warning_msg in caplog.text
         for record in caplog.records:
             assert record.levelno == idaeslog.WARNING

From 009f50f8ef82a2cfc72fec4eaa0cf5047e29ed90 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Sat, 17 Aug 2024 12:52:36 -0700
Subject: [PATCH 13/18] fix warnings in sampling test file.

---
 .../pysmo/tests/test_sampling_modified.py       | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/tests/test_sampling_modified.py b/idaes/core/surrogate/pysmo/tests/test_sampling_modified.py
index b1ee3ef09a..a4e0a92387 100644
--- a/idaes/core/surrogate/pysmo/tests/test_sampling_modified.py
+++ b/idaes/core/surrogate/pysmo/tests/test_sampling_modified.py
@@ -19,6 +19,7 @@
     SamplingMethods,
     FeatureScaling,
 )
+import idaes.logger as idaeslog
 import numpy as np
 import pandas as pd
 import pyomo.common.unittest as unittest
@@ -2187,13 +2188,19 @@ def test__init__selection_10(self):
     @pytest.mark.unit
     def test__init__selection_11(self):
         input_array = self.test_data_numpy
-        with pytest.warns(Warning):
+        warning_msg = (
+            "Tolerance too tight. CVT algorithm may take long time to converge."
+        )
+        with self.assertLogs(level="WARNING") as cm:
             CVTClass = CVTSampling(
                 input_array,
                 number_of_samples=None,
                 tolerance=1e-10,
                 sampling_type="selection",
             )
+        self.assertIn(warning_msg, "\n".join(cm.output))
+        for record in cm.records:
+            self.assertEqual(record.levelno, idaeslog.WARNING)
 
     @pytest.mark.unit
     def test__init__selection_12(self):
@@ -2315,14 +2322,20 @@ def test__init__creation_09(self):
 
     @pytest.mark.unit
     def test__init__creation_10(self):
+        warning_msg = (
+            "Tolerance too tight. CVT algorithm may take long time to converge."
+        )
         input_array = self.test_data_list
-        with pytest.warns(Warning):
+        with self.assertLogs(level="WARNING") as cm:
             CVTClass = CVTSampling(
                 input_array,
                 number_of_samples=None,
                 tolerance=1e-10,
                 sampling_type="creation",
             )
+        self.assertIn(warning_msg, "\n".join(cm.output))
+        for record in cm.records:
+            assert record.levelno == idaeslog.WARNING
 
     @pytest.mark.unit
     def test__init__creation_11(self):

From 33a3b0a3d53142dabff759006676b03f8af4ff67 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Sat, 17 Aug 2024 13:05:25 -0700
Subject: [PATCH 14/18] Fix warnings in pysmo_surrogate.py due to numpy

---
 idaes/core/surrogate/pysmo_surrogate.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/idaes/core/surrogate/pysmo_surrogate.py b/idaes/core/surrogate/pysmo_surrogate.py
index a7e3785caa..aec518fdac 100644
--- a/idaes/core/surrogate/pysmo_surrogate.py
+++ b/idaes/core/surrogate/pysmo_surrogate.py
@@ -513,7 +513,8 @@ def evaluate_surrogate(self, inputs: pd.DataFrame) -> pd.DataFrame:
             row_data = inputdata[i, :].reshape(1, len(self._input_labels))
             for j, output_label in enumerate(self._output_labels):
                 result = self._trained.get_result(output_label)
-                outputs[i, j] = result.model.predict_output(row_data)
+                res_vec = result.model.predict_output(row_data)
+                outputs[i, j] = res_vec.item()
 
         return pd.DataFrame(
             data=outputs, index=inputs.index, columns=self._output_labels

From 4c8fdf7c6f6f187bd84eddf49eb1d2e64467cd0a Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Sat, 17 Aug 2024 13:36:57 -0700
Subject: [PATCH 15/18] fixing pylint issues.

---
 idaes/core/surrogate/pysmo/polynomial_regression.py | 1 -
 idaes/core/surrogate/pysmo/radial_basis_function.py | 1 -
 idaes/core/surrogate/pysmo/sampling.py              | 1 -
 3 files changed, 3 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/polynomial_regression.py b/idaes/core/surrogate/pysmo/polynomial_regression.py
index dc7f6e6365..11a716d41f 100644
--- a/idaes/core/surrogate/pysmo/polynomial_regression.py
+++ b/idaes/core/surrogate/pysmo/polynomial_regression.py
@@ -15,7 +15,6 @@
 # pylint: disable=missing-function-docstring
 
 import os.path
-import warnings
 import pickle
 
 # Imports from third parties
diff --git a/idaes/core/surrogate/pysmo/radial_basis_function.py b/idaes/core/surrogate/pysmo/radial_basis_function.py
index 583c4ebf53..4f628c56b2 100644
--- a/idaes/core/surrogate/pysmo/radial_basis_function.py
+++ b/idaes/core/surrogate/pysmo/radial_basis_function.py
@@ -18,7 +18,6 @@
 
 # Imports from the python standard library
 import os.path
-import warnings
 import pickle
 
 # Imports from third parties
diff --git a/idaes/core/surrogate/pysmo/sampling.py b/idaes/core/surrogate/pysmo/sampling.py
index 0901d87fda..0a6d8d59d7 100644
--- a/idaes/core/surrogate/pysmo/sampling.py
+++ b/idaes/core/surrogate/pysmo/sampling.py
@@ -15,7 +15,6 @@
 # pylint: disable=missing-class-docstring
 # pylint: disable=missing-function-docstring
 
-import warnings
 import itertools
 
 import numpy as np

From 3023a0c279eca2efa315c3e72162823c900f5547 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Mon, 19 Aug 2024 12:05:53 -0700
Subject: [PATCH 16/18] Added @pytest.mark.filterwarnings to catach runtime
 warnings.

---
 idaes/core/surrogate/pysmo/tests/test_kriging.py              | 4 ++++
 .../core/surrogate/pysmo/tests/test_radial_basis_function.py  | 2 ++
 2 files changed, 6 insertions(+)

diff --git a/idaes/core/surrogate/pysmo/tests/test_kriging.py b/idaes/core/surrogate/pysmo/tests/test_kriging.py
index 5097e7b027..0796e7043b 100644
--- a/idaes/core/surrogate/pysmo/tests/test_kriging.py
+++ b/idaes/core/surrogate/pysmo/tests/test_kriging.py
@@ -97,6 +97,7 @@ def test__init__07(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test__init__08(self, array_type):
         input_array = array_type(self.test_data)
         file_name = "test_filename.pickle"
@@ -107,6 +108,7 @@ def test__init__08(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test__init__09(self, array_type):
         input_array = array_type(self.test_data)
         file_name1 = "test_filename1.pickle"
@@ -403,6 +405,7 @@ def test_r2_calculation(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test_predict_output_01(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
@@ -413,6 +416,7 @@ def test_predict_output_01(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test_predict_output(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
diff --git a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
index 05b6aa4228..36ee972df9 100644
--- a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
+++ b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
@@ -507,6 +507,7 @@ def test_thin_plate_spline_transformation(self):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test_basis_generation(self, array_type):
         input_array = array_type(self.training_data)
         scaled = FeatureScaling.data_scaling_minmax(input_array[0:3])
@@ -2074,6 +2075,7 @@ def test_rbf_predict_output_05(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
+    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
     def test_rbf_predict_output_06(self, array_type):
         input_array = array_type(self.training_data)
         data_feed = RadialBasisFunctions(

From b509086968636520822b8d0edf407205894400e7 Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Mon, 19 Aug 2024 13:17:43 -0700
Subject: [PATCH 17/18] Make pytest filters more specific

---
 idaes/core/surrogate/pysmo/tests/test_kriging.py          | 8 ++++----
 .../surrogate/pysmo/tests/test_radial_basis_function.py   | 4 ++--
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/tests/test_kriging.py b/idaes/core/surrogate/pysmo/tests/test_kriging.py
index 0796e7043b..75cdbadf47 100644
--- a/idaes/core/surrogate/pysmo/tests/test_kriging.py
+++ b/idaes/core/surrogate/pysmo/tests/test_kriging.py
@@ -97,7 +97,7 @@ def test__init__07(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
     def test__init__08(self, array_type):
         input_array = array_type(self.test_data)
         file_name = "test_filename.pickle"
@@ -108,7 +108,7 @@ def test__init__08(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
     def test__init__09(self, array_type):
         input_array = array_type(self.test_data)
         file_name1 = "test_filename1.pickle"
@@ -405,7 +405,7 @@ def test_r2_calculation(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
     def test_predict_output_01(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
@@ -416,7 +416,7 @@ def test_predict_output_01(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
     def test_predict_output(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
diff --git a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
index 36ee972df9..88fe84d216 100644
--- a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
+++ b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
@@ -507,7 +507,7 @@ def test_thin_plate_spline_transformation(self):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning")
     def test_basis_generation(self, array_type):
         input_array = array_type(self.training_data)
         scaled = FeatureScaling.data_scaling_minmax(input_array[0:3])
@@ -2075,7 +2075,7 @@ def test_rbf_predict_output_05(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore::RuntimeWarning")
+    @pytest.mark.filterwarnings("ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning")
     def test_rbf_predict_output_06(self, array_type):
         input_array = array_type(self.training_data)
         data_feed = RadialBasisFunctions(

From 555bf4c1f79bed14d4dc6eac3df47e2d0033f5ba Mon Sep 17 00:00:00 2001
From: OOAmusat <47539353+OOAmusat@users.noreply.github.com>
Date: Mon, 19 Aug 2024 13:19:47 -0700
Subject: [PATCH 18/18] running black...

---
 idaes/core/surrogate/pysmo/tests/test_kriging.py | 16 ++++++++++++----
 .../pysmo/tests/test_radial_basis_function.py    |  8 ++++++--
 2 files changed, 18 insertions(+), 6 deletions(-)

diff --git a/idaes/core/surrogate/pysmo/tests/test_kriging.py b/idaes/core/surrogate/pysmo/tests/test_kriging.py
index 75cdbadf47..c688383683 100644
--- a/idaes/core/surrogate/pysmo/tests/test_kriging.py
+++ b/idaes/core/surrogate/pysmo/tests/test_kriging.py
@@ -97,7 +97,9 @@ def test__init__07(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in log:RuntimeWarning"
+    )
     def test__init__08(self, array_type):
         input_array = array_type(self.test_data)
         file_name = "test_filename.pickle"
@@ -108,7 +110,9 @@ def test__init__08(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in log:RuntimeWarning"
+    )
     def test__init__09(self, array_type):
         input_array = array_type(self.test_data)
         file_name1 = "test_filename1.pickle"
@@ -405,7 +409,9 @@ def test_r2_calculation(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in log:RuntimeWarning"
+    )
     def test_predict_output_01(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
@@ -416,7 +422,9 @@ def test_predict_output_01(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:invalid value encountered in log:RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in log:RuntimeWarning"
+    )
     def test_predict_output(self, array_type):
         input_array = array_type(self.training_data)
         np.random.seed(0)
diff --git a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
index 88fe84d216..3032fda425 100644
--- a/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
+++ b/idaes/core/surrogate/pysmo/tests/test_radial_basis_function.py
@@ -507,7 +507,9 @@ def test_thin_plate_spline_transformation(self):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning"
+    )
     def test_basis_generation(self, array_type):
         input_array = array_type(self.training_data)
         scaled = FeatureScaling.data_scaling_minmax(input_array[0:3])
@@ -2075,7 +2077,9 @@ def test_rbf_predict_output_05(self, array_type):
 
     @pytest.mark.unit
     @pytest.mark.parametrize("array_type", [np.array, pd.DataFrame])
-    @pytest.mark.filterwarnings("ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning")
+    @pytest.mark.filterwarnings(
+        "ignore:(invalid value|divide by zero) encountered in (multiply|log):RuntimeWarning"
+    )
     def test_rbf_predict_output_06(self, array_type):
         input_array = array_type(self.training_data)
         data_feed = RadialBasisFunctions(