Update test_PCA equivalence test to use svd_solver='full'

bnpm/tests/test_PCA.py

@@ -12,7 +12,7 @@
 
 def test_fit_transform_equivalence():
     n_components = 5
-    pca_sklearn = sklearnPCA(n_components=n_components).fit(X_np)
+    pca_sklearn = sklearnPCA(n_components=n_components, svd_solver='full').fit(X_np)
     pca_torch = PCA(n_components=n_components).fit(X_torch)
 
     # Compare the principal components directly
@@ -179,4 +179,4 @@ def test_n_components_effect():
         pca_n.fit(X_torch)
 
         assert pca_n.components_.shape[0] == n, f"PCA with n_components={n} did not produce the correct number of components."
-        assert pca_n.explained_variance_.shape[0] == n, f"PCA with n_components={n} did not produce the correct number of explained variances."
+        assert pca_n.explained_variance_.shape[0] == n, f"PCA with n_components={n} did not produce the correct number of explained variances."