test: increasing test rate

src/ansys/math/core/math.py

@@ -1710,7 +1710,11 @@ def sym(self) -> bool:
 
                 elif info.objtype == 3:  # SMAT
                     mat = self.asarray()
-                    sym = bool(np.all(np.abs(mat.data - (mat.T).data) < 1e-16))
+                    matT = mat.T
+                    sym = (
+                        bool(np.allclose(mat.data, matT.data))
+                        and bool(np.allclose(mat.indices, matT.indices))
+                    ) and bool(np.allclose(mat.indptr, matT.indptr))
 
         else:
             warn("``sym`` requires MAPDL version 2022R2 or later. The default value is False.")

tests/conftest.py

@@ -1,7 +1,9 @@
 import os
 from pathlib import Path
 
+import numpy as np
 import pytest
+from scipy import sparse
 
 # import time
 
@@ -152,3 +154,23 @@ def cube_solve(cleared, mapdl):
 
     # solve first 10 non-trivial modes
     out = mapdl.modal_analysis(nmode=10, freqb=1)
+
+
+@pytest.fixture
+def sparse_asym_mat():
+    return sparse.random(5000, 5000, density=0.05, format="csr")
+
+
+@pytest.fixture
+def sparse_sym_mat(sparse_asym_mat):
+    return sparse_asym_mat + sparse_asym_mat.T
+
+
+@pytest.fixture
+def dense_asym_mat():
+    return np.random.rand(1000, 1000)
+
+
+@pytest.fixture
+def dense_sym_mat(dense_asym_mat):
+    return dense_asym_mat + dense_asym_mat.T

tests/test_math.py

@@ -182,19 +182,31 @@ def test_shape(mm):
     assert m1.shape == shape
 
 
-def test_matrix(mm):
-    sz = 5000
-    mat = sparse.random(sz, sz, density=0.05, format="csr")
-    assert mat.data.nbytes // 1024**2 > 4, "Must test over gRPC message limit"
+@pytest.mark.parametrize("sparse_mat", ["sparse_asym_mat", "sparse_sym_mat"])
+def test_matrix(mm, sparse_mat, request):
+    sparse_mat = request.getfixturevalue(sparse_mat)
+    assert sparse_mat.data.nbytes // 1024**2 > 4, "Must test over gRPC message limit"
+
+    name = "TMP_MATRIX"
+    ans_mat = mm.matrix(sparse_mat, name)
+    assert ans_mat.id == name
+
+    mat_back = ans_mat.asarray()
+    assert np.allclose(sparse_mat.data, mat_back.data)
+    assert np.allclose(sparse_mat.indices, mat_back.indices)
+    assert np.allclose(sparse_mat.indptr, mat_back.indptr)
+
+
+@pytest.mark.parametrize("dense_mat", ["dense_asym_mat", "dense_sym_mat"])
+def test_dense_matrix(mm, dense_mat, request):
+    dense_mat = request.getfixturevalue(dense_mat)
 
     name = "TMP_MATRIX"
-    ans_mat = mm.matrix(mat, name)
+    ans_mat = mm.matrix(dense_mat, name)
     assert ans_mat.id == name
 
     mat_back = ans_mat.asarray()
-    assert np.allclose(mat.data, mat_back.data)
-    assert np.allclose(mat.indices, mat_back.indices)
-    assert np.allclose(mat.indptr, mat_back.indptr)
+    assert np.allclose(dense_mat, mat_back)
 
 
 def test_matrix_fail(mm):