Update README

README.md

@@ -96,6 +96,13 @@ It will return a dense array X.
 Refer to the pardiso documentation for detailed description of options.
 Consider this wrapper to be experimental.
 
+#### SciPy Classes
+
+`csr_array`, `csr_matrix`, `csc_array`, `csc_matrix`, `bsr_array`, `bsr_matrix`
+
+Scipy sparse classes where `__matmul__` and `__rmatmul__` have been replaced to use MKL
+for matrix math
+
 #### Service Functions
 
 Several service functions are available and can be imported from the base `sparse_dot_mkl` package.

sparse_dot_mkl/tests/test_scipy_classes.py

@@ -1,5 +1,6 @@
 import unittest
 import numpy.testing as npt
+import scipy as sp
 import scipy.sparse as sps
 from types import MethodType
 
@@ -77,28 +78,34 @@ def test_matmul_fail(self):
         with self.assertRaises(ValueError):
             b @ a
 
-        m1 = MATRIX_1.copy()
-        m2 = MATRIX_2.copy()
-
-        install_wire(m1)
-        install_wire(m2)
-        install_wire(a)
-        install_wire(b)
+        # Following tests dont work with old scipy
+        if (
+            (int(sp.__version__.split('.')[1]) > 1) or
+            (int(sp.__version__.split('.')[1]) > 13)
+        ):
+
+            m1 = MATRIX_1.copy()
+            m2 = MATRIX_2.copy()
+
+            install_wire(m1)
+            install_wire(m2)
+            install_wire(a)
+            install_wire(b)
+            # SCIPY
+            with self.assertRaises(TripError):
+                m1 @ m2
 
-        # SCIPY
-        with self.assertRaises(TripError):
-            m1 @ m2
+            # SCIPY CSR_MATRIX USES RMATMUL DUNNO WHY
+            if self.arr != csr_matrix:
+                with self.assertRaises(TripError):
+                    m1 @ b
 
-        # SCIPY CSR_MATRIX USES RMATMUL DUNNO WHY
-        if self.arr != csr_matrix:
-            with self.assertRaises(TripError):
-                m1 @ b
+            # MKL
+            a @ m2 
 
-        # MKL
-        a @ m2 
+            # MKL
+            a @ b 
 
-        # MKL
-        a @ b 
 
 class TestCSRMat(TestCSR):
     arr = csr_matrix