Merge pull request #147 from ndem0/bugfix

Bugfix
mathLab · Apr 7, 2021 · 5a708a7 · 5a708a7
2 parents 281bfaf + 4a3a3e6
commit 5a708a7
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Showing 5 changed files with 35 additions and 15 deletions.
diff --git a/ezyrb/pod.py b/ezyrb/pod.py
@@ -87,7 +87,7 @@ def _truncation(self, X, s):
         :return: the number of modes
         :rtype: int
         """
-        if self.rank is 0:
+        if self.rank == 0:
             omega = lambda x: 0.56 * x**3 - 0.95 * x**2 + 1.82 * x + 1.43
             beta = np.divide(*sorted(X.shape))
             tau = np.median(s) * omega(beta)

diff --git a/ezyrb/reducedordermodel.py b/ezyrb/reducedordermodel.py
@@ -3,6 +3,7 @@
 """
 import numpy as np
 import math
+import copy
 from scipy.spatial import Delaunay
 
 
@@ -74,8 +75,8 @@ def loo_error(self, norm=np.linalg.norm):
             remaining_index = db_range[:]
             remaining_index.remove(j)
             new_db = self.database[remaining_index]
-            rom = type(self)(new_db, self.reduction,
-                    self.approximation).fit()
+            rom = type(self)(new_db, copy.deepcopy(self.reduction),
+                    copy.deepcopy(self.approximation)).fit()
 
             error[j] = norm(self.database.snapshots[j] -
                             rom.predict(self.database.parameters[j]))

diff --git a/tests/test_k_neighbors_regressor.py b/tests/test_k_neighbors_regressor.py
@@ -1,4 +1,5 @@
 import numpy as np
+import warnings
 
 from unittest import TestCase
 from ezyrb import KNeighborsRegressor, Database, POD, ReducedOrderModel
@@ -58,12 +59,16 @@ def test_with_db_predict(self):
 
     def test_wrong1(self):
         # wrong number of params
-        with self.assertRaises(Exception):
-            reg = KNeighborsRegressor()
-            reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning) 
+            with self.assertRaises(Exception):
+                reg = KNeighborsRegressor()
+                reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
 
     def test_wrong2(self):
         # wrong number of values
-        with self.assertRaises(Exception):
-            reg = KNeighborsRegressor()
-            reg.fit([[1, 2], [6,], [8, 9]], [[20, 5], [8, 6]])
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning) 
+            with self.assertRaises(Exception):
+                reg = KNeighborsRegressor()
+                reg.fit([[1, 2], [6,], [8, 9]], [[20, 5], [8, 6]])
diff --git a/tests/test_radius_neighbors_regressor.py b/tests/test_radius_neighbors_regressor.py
@@ -1,4 +1,5 @@
 import numpy as np
+import warnings
 
 from unittest import TestCase
 from ezyrb import RadiusNeighborsRegressor, POD, Database, ReducedOrderModel
@@ -58,12 +59,16 @@ def test_with_db_predict(self):
 
     def test_wrong1(self):
         # wrong number of params
-        with self.assertRaises(Exception):
-            reg = RadiusNeighborsRegressor()
-            reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning) 
+            with self.assertRaises(Exception):
+                reg = RadiusNeighborsRegressor()
+                reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
 
     def test_wrong2(self):
         # wrong number of values
-        with self.assertRaises(Exception):
-            reg = RadiusNeighborsRegressor()
-            reg.fit([[1, 2], [6,], [8, 9]], [[20, 5], [8, 6]])
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning) 
+            with self.assertRaises(Exception):
+                reg = RadiusNeighborsRegressor()
+                reg.fit([[1, 2], [6,], [8, 9]], [[20, 5], [8, 6]])
diff --git a/tests/test_reducedordermodel.py b/tests/test_reducedordermodel.py
@@ -56,6 +56,15 @@ def test_loo_error(self):
             np.array([421.299091, 344.571787,  48.711501, 300.490491]),
             rtol=1e-4)
 
+    def test_loo_error_singular_values(self):
+        pod = POD()
+        rbf = RBF()
+        db = Database(param, snapshots.T)
+        rom = ROM(db, pod, rbf).fit()
+        valid_svalues = rom.reduction.singular_values
+        rom.loo_error()
+        np.testing.assert_allclose(valid_svalues, rom.reduction.singular_values)
+
     def test_optimal_mu(self):
         pod = POD()
         rbf = RBF()