Changeset 5902 for anuga_core/source_numpy_conversion/anuga/utilities/sparse.py

Timestamp:

Nov 6, 2008, 3:32:23 PM (16 years ago)

Author:

rwilson

Message:

NumPy? conversion.

File:

• anuga_core/source_numpy_conversion/anuga/utilities/sparse.py (modified) (14 diffs)

anuga_core/source_numpy_conversion/anuga/utilities/sparse.py

@@ -3 +3 @@
 """
 
+import numpy
 
 class Sparse:
@@ -18 +19 @@
             
         if len(args) == 1:
-            from numpy import array
             try:
-                A = array(args[0])
+                A = numpy.array(args[0])
             except:
                 raise 'Input must be convertable to a Numeric array'
@@ -93 +93 @@
 
     def todense(self):
-        from numpy import zeros, float
-
-        D = zeros( (self.M, self.N), float)
+        D = numpy.zeros( (self.M, self.N), numpy.float)
         
         for i in range(self.M):
@@ -110 +108 @@
         """
 
-        from numpy import array, zeros, float
-        
         try:
-            B = array(other)
+            B = numpy.array(other)
         except:
             msg = 'FIXME: Only Numeric types implemented so far'
@@ -131 +127 @@
             assert B.shape[0] == self.N, msg
 
-            R = zeros(self.M, float) #Result
+            R = numpy.zeros(self.M, numpy.float) #Result
             
             # Multiply nonzero elements
@@ -141 +137 @@
         
             
-            R = zeros((self.M, B.shape[1]), float) #Result matrix
+            R = numpy.zeros((self.M, B.shape[1]), numpy.float) #Result matrix
 
             # Multiply nonzero elements
@@ -197 +193 @@
         """
 
-        from numpy import array, zeros, float
-        
         try:
-            B = array(other)
+            B = numpy.array(other)
         except:
             print 'FIXME: Only Numeric types implemented so far'
@@ -211 +205 @@
             assert B.shape[0] == self.M, 'Mismatching dimensions'
 
-            R = zeros((self.N,), float) #Result
+            R = numpy.zeros((self.N,), numpy.float) #Result
 
             #Multiply nonzero elements
@@ -248 +242 @@
         """
 
-        from numpy import zeros, float, int
-
         if isinstance(A,Sparse):
 
@@ -255 +247 @@
             keys.sort()
             nnz = len(keys)
-            data    = zeros ( (nnz,), float)
-            colind  = zeros ( (nnz,), int)
-            row_ptr = zeros ( (A.M+1,), int)
+            data    = numpy.zeros ( (nnz,), numpy.float)
+            colind  = numpy.zeros ( (nnz,), numpy.int)
+            row_ptr = numpy.zeros ( (A.M+1,), numpy.int)
             current_row = -1
             k = 0
@@ -295 +287 @@
 
     def todense(self):
-        from numpy.oldnumeric import zeros, Float
-
-        D = zeros( (self.M, self.N), Float)
+
+        D = numpy.zeros( (self.M, self.N), numpy.float)
         
         for i in range(self.M):
@@ -310 +301 @@
         """
 
-        from numpy.oldnumeric import array, zeros, Float
-        
         try:
-            B = array(other)
+            B = numpy.array(other)
         except:
             print 'FIXME: Only Numeric types implemented so far'
@@ -329 +318 @@
 if __name__ == '__main__':
     # A little selftest
-    
-    from numpy.oldnumeric import allclose, array, Float 
-    
     A = Sparse(3,3)
 
@@ -362 +348 @@
     u = A*v
     print u
-    assert allclose(u, [6,14,4])
+    assert numpy.allclose(u, [6,14,4])
 
     u = A.trans_mult(v)
     print u
-    assert allclose(u, [6,6,10])
+    assert numpy.allclose(u, [6,6,10])
 
     #Right hand side column
-    v = array([[2,4],[3,4],[4,4]])
+    v = numpy.array([[2,4],[3,4],[4,4]])
 
     u = A*v[:,0]
-    assert allclose(u, [6,14,4])
+    assert numpy.allclose(u, [6,14,4])
 
     #u = A*v[:,1]