Correct boundry type test

sparse_dot_mkl/_mkl_interface.py

@@ -1107,7 +1107,16 @@ def _is_double(arr):
 
 
 def _is_allowed_sparse_format(matrix):
-    return _spsparse.isspmatrix_csr(matrix) or _spsparse.isspmatrix_csc(matrix) or _spsparse.isspmatrix_bsr(matrix)
+    """
+    Return True if the matrix is dense or a sparse format we can turn into an MKL object. False otherwise.
+    :param matrix:
+    :return:
+    :rtype: bool
+    """
+    if _spsparse.isspmatrix(matrix):
+        return _spsparse.isspmatrix_csr(matrix) or _spsparse.isspmatrix_csc(matrix) or _spsparse.isspmatrix_bsr(matrix)
+    else:
+        return True
 
 
 def _empty_output_check(matrix_a, matrix_b):

sparse_dot_mkl/_sparse_vector.py

@@ -1,6 +1,6 @@
 from sparse_dot_mkl._mkl_interface import (MKL, _sanity_check, _empty_output_check, _type_check, _create_mkl_sparse,
                                            _destroy_mkl_handle, matrix_descr, RETURN_CODES, _is_dense_vector,
-                                           _out_matrix, _check_return_value)
+                                           _out_matrix, _check_return_value, _is_allowed_sparse_format)
 
 import numpy as np
 import ctypes as _ctypes
@@ -86,7 +86,9 @@ def _sparse_dot_vector(mv_a, mv_b, cast=False, scalar=1., out=None, out_scalar=N
     _sanity_check(mv_a, mv_b, allow_vector=True)
     mv_a, mv_b = _type_check(mv_a, mv_b, cast=cast)
 
-    if _is_dense_vector(mv_b):
+    if not _is_allowed_sparse_format(mv_a) or not _is_allowed_sparse_format(mv_b):
+        raise ValueError("Only CSR, CSC, and BSR-type sparse matrices are supported")
+    elif _is_dense_vector(mv_b):
         return _sparse_dense_vector_mult(mv_a, mv_b, scalar=scalar, out=out, out_scalar=out_scalar)
     elif _is_dense_vector(mv_a) and out is None:
         return _sparse_dense_vector_mult(mv_b, mv_a.T, scalar=scalar, transpose=True).T

sparse_dot_mkl/tests/test_sparse_vector.py

@@ -135,6 +135,26 @@ def setUp(self):
         self.mat2_d = VECTOR.copy()
 
 
+class TestSparseVectorMultiplicationCOO(unittest.TestCase):
+
+    def setUp(self):
+        self.mat1 = _spsparse.coo_matrix(MATRIX_1).copy()
+        self.mat2 = VECTOR.copy()
+
+        self.mat1_d = np.asarray(MATRIX_1.A, order="C")
+        self.mat2_d = VECTOR.copy()
+
+    def make_2d(self, arr):
+        return arr.reshape(-1, 1) if arr.ndim == 1 else arr
+
+    def test_fails(self):
+        with self.assertRaises(ValueError):
+            dot_product_mkl(self.mat1, self.make_2d(self.mat2), cast=True)
+
+        with self.assertRaises(ValueError):
+            dot_product_mkl(self.make_2d(self.mat2), self.mat1.T, cast=True)
+
+
 class TestVectorSparseMultiplication(TestSparseVectorMultiplication):
 
     sparse_func = _spsparse.csr_matrix