update generator used for sparse matrix vector product (#450)

mpmath/matrices/calculus.py

@@ -84,8 +84,8 @@ class MatrixCalculusMethods:
             [ 2.26812870852145  2.44114713886289   1.42699786729125]
             [0.841130841230196  1.42699786729125    1.6000162976327]
             >>> expm([[1+j, 0], [1+j,1]])
-            [(1.46869393991589 + 2.28735528717884j)                        0.0]
-            [  (1.03776739863568 + 3.536943175722j)  (2.71828182845905 + 0.0j)]
+            [(1.46869393991589 + 2.28735528717884j)               0.0]
+            [  (1.03776739863568 + 3.536943175722j)  2.71828182845905]
 
         Matrices with large entries are allowed::
 

mpmath/matrices/matrices.py

@@ -573,14 +573,10 @@ class _matrix:
             if self.__cols != other.__rows:
                 raise ValueError('dimensions not compatible for multiplication')
             new = self.ctx.matrix(self.__rows, other.__cols)
-            self_zero = self.ctx.zero
-            self_get = self.__data.get
-            other_zero = other.ctx.zero
-            other_get = other.__data.get
             for i in range(self.__rows):
                 for j in range(other.__cols):
-                    new[i, j] = self.ctx.fdot((self_get((i,k), self_zero), other_get((k,j), other_zero))
-                                     for k in range(other.__rows))
+                    new[i, j] = self.ctx.fdot((self.__data[i,k], other.__data[k,j])
+                                              for k in range(other.__rows) if (i,k) in self.__data and (k,j) in other.__data)
             return new
         else:
             # try scalar multiplication