[Scipy-svn] r3436 - in trunk/scipy/sparse: . tests

[scipy-svn@scip...]

Author: wnbell
Date: 2007-10-15 14:23:07 -0500 (Mon, 15 Oct 2007)
New Revision: 3436

Modified:
   trunk/scipy/sparse/sparse.py
   trunk/scipy/sparse/tests/test_sparse.py
Log:
fix sparse matvec result dimensions
check matvec input dimensions
resolves ticket #514


Modified: trunk/scipy/sparse/sparse.py
===================================================================
--- trunk/scipy/sparse/sparse.py	2007-10-13 18:33:22 UTC (rev 3435)
+++ trunk/scipy/sparse/sparse.py	2007-10-15 19:23:07 UTC (rev 3436)
@@ -673,23 +673,25 @@
 
     def _matvec(self, other, fn):
         if isdense(other):
-            # This check is too harsh -- it prevents a column vector from
-            # being created on-the-fly like dense matrix objects can.
-            #if len(other) != self.shape[1]:
-            #    raise ValueError, "dimension mismatch"
-            oth = numpy.ravel(other)
+            if other.size != self.shape[1] or \
+                    (other.ndim == 2 and self.shape[1] != other.shape[0]):
+                raise ValueError, "dimension mismatch"
+            
             y = fn(self.shape[0], self.shape[1], \
-                   self.indptr, self.indices, self.data, oth)
+                   self.indptr, self.indices, self.data, numpy.ravel(other))
+
             if isinstance(other, matrix):
                 y = asmatrix(y)
+
             if other.ndim == 2 and other.shape[1] == 1:
-                # If 'other' was an (nx1) column vector, transpose the result
-                # to obtain an (mx1) column vector.
-                y = y.T
+                # If 'other' was an (nx1) column vector, reshape the result
+                y = y.reshape(-1,1)
+            
             return y
 
         elif isspmatrix(other):
             raise TypeError, "use matmat() for sparse * sparse"
+
         else:
             raise TypeError, "need a dense vector"
 

Modified: trunk/scipy/sparse/tests/test_sparse.py
===================================================================
--- trunk/scipy/sparse/tests/test_sparse.py	2007-10-13 18:33:22 UTC (rev 3435)
+++ trunk/scipy/sparse/tests/test_sparse.py	2007-10-15 19:23:07 UTC (rev 3436)
@@ -176,7 +176,23 @@
         M = self.spmatrix(matrix([[3,0,0],[0,1,0],[2,0,3.0],[2,3,0]]))
         col = matrix([1,2,3]).T
         assert_array_almost_equal(M * col, M.todense() * col)
+        
+        #check result dimensions (ticket #514) 
+        assert_equal((M * array([1,2,3])).shape,(4,)) 
+        assert_equal((M * array([[1],[2],[3]])).shape,(4,1)) 
+        assert_equal((M * matrix([[1],[2],[3]])).shape,(4,1)) 
 
+        #ensure exception is raised for improper dimensions
+        bad_vecs = [array([1,2]), array([1,2,3,4]), array([[1],[2]]), 
+                    matrix([1,2,3]), matrix([[1],[2]])]
+        caught = 0
+        for x in bad_vecs:
+            try:
+                y = M * x
+            except ValueError:
+                caught += 1
+        assert_equal(caught,len(bad_vecs))
+
         # Should this be supported or not?!
         #flat = array([1,2,3])
         #assert_array_almost_equal(M*flat, M.todense()*flat)