Changeset 5905 for anuga_core/source_numpy_conversion/anuga/fit_interpolate/interpolate.py

Timestamp:

Nov 6, 2008, 3:41:41 PM (16 years ago)

Author:

rwilson

Message:

NumPy? conversion.

File:

• anuga_core/source_numpy_conversion/anuga/fit_interpolate/interpolate.py (modified) (21 diffs)

anuga_core/source_numpy_conversion/anuga/fit_interpolate/interpolate.py

@@ -24 +24 @@
 from csv import writer, DictWriter
 
-from Numeric import zeros, array, Float, Int, dot, transpose, concatenate, \
-     ArrayType, allclose, take, NewAxis, arange
+import numpy
 
 from anuga.caching.caching import cache
@@ -116 +115 @@
 
     # Create interpolation object with matrix
-    args = (ensure_numeric(vertex_coordinates, Float), 
+    args = (ensure_numeric(vertex_coordinates, numpy.float), 
             ensure_numeric(triangles))
     kwargs = {'mesh_origin': mesh_origin,
@@ -224 +223 @@
  
         from utilities.polygon import point_on_line
-        from Numeric import ones
-        z=ones(len(point_coordinates),Float)
+        z=numpy.ones(len(point_coordinates),numpy.float)
 
         msg='point coordinates are not given (interpolate.py)'
@@ -343 +341 @@
                 # creating a dummy array to concatenate to.
                 
-                f = ensure_numeric(f, Float)
+                f = ensure_numeric(f, numpy.float)
                 #print "f.shape",f.shape 
                 if len(f.shape) > 1:
-                    z = zeros((0,f.shape[1]))
+                    z = numpy.zeros((0,f.shape[1]), numpy.float)
                 else:
-                    z = zeros((0,))
+                    z = numpy.zeros((0,), numpy.float)
                     
                 for end in range(start_blocking_len,
@@ -358 +356 @@
                     #print "t", t
                     #print "z", z 
-                    z = concatenate((z,t))
+                    z = numpy.concatenate((z,t))
                     start = end
                     
@@ -364 +362 @@
                 t = self.interpolate_block(f, point_coordinates[start:end],
                                            verbose=verbose)
-                z = concatenate((z,t))
+                z = numpy.concatenate((z,t))
         return z
     
@@ -389 +387 @@
 
         # Convert lists to Numeric arrays if necessary
-        point_coordinates = ensure_numeric(point_coordinates, Float)
-        f = ensure_numeric(f, Float)                
+        point_coordinates = ensure_numeric(point_coordinates, numpy.float)
+        f = ensure_numeric(f, numpy.float)                
 
         from anuga.caching import myhash
-        from Numeric import alltrue
         import sys
         if use_cache is True:
@@ -412 +409 @@
                 if self.interpolation_matrices.has_key(key):
                     X, stored_points = self.interpolation_matrices[key] 
-                    if alltrue(stored_points == point_coordinates):
+                    if numpy.alltrue(stored_points == point_coordinates):
                         reuse_A = True # Reuse interpolation matrix
                 
@@ -487 +484 @@
 
         # Convert point_coordinates to Numeric arrays, in case it was a list.
-        point_coordinates = ensure_numeric(point_coordinates, Float)
+        point_coordinates = ensure_numeric(point_coordinates, numpy.float)
         
         
@@ -752 +749 @@
         """
 
-        from Numeric import array, zeros, Float, alltrue, concatenate,\
-             reshape, ArrayType
-
-
         from anuga.config import time_format
         import types
-
 
         # Check temporal info
@@ -764 +756 @@
         msg = 'Time must be a monotonuosly '
         msg += 'increasing sequence %s' %time
-        assert alltrue(time[1:] - time[:-1] >= 0 ), msg
+        assert numpy.alltrue(time[1:] - time[:-1] >= 0 ), msg
 
 
@@ -795 +787 @@
         # Thin timesteps if needed
         # Note array() is used to make the thinned arrays contiguous in memory
-        self.time = array(time[::time_thinning])          
+        self.time = numpy.array(time[::time_thinning])          
         for name in quantity_names:
             if len(quantities[name].shape) == 2:
-                quantities[name] = array(quantities[name][::time_thinning,:])
+                quantities[name] = numpy.array(quantities[name][::time_thinning,:])
              
         # Save for use with statistics
         self.quantities_range = {}
         for name in quantity_names:
-            q = quantities[name][:].flat
+##            q = quantities[name][:].ravel()
+            q = numpy.ravel(quantities[name][:])
             self.quantities_range[name] = [min(q), max(q)]
         
@@ -863 +856 @@
                         if sys.platform == 'win32': # FIXME (Ole): Why only Windoze?
                             from anuga.utilities.polygon import plot_polygons
-                            #out_interp_pts = take(interpolation_points,[indices])
+                            #out_interp_pts = numpy.take(interpolation_points,[indices], axis=0)
                             title = 'Interpolation points fall outside specified mesh'
                             plot_polygons([mesh_boundary_polygon,
@@ -905 +898 @@
             
             for name in quantity_names:
-                self.precomputed_values[name] = zeros((p, m), Float)
+                self.precomputed_values[name] = numpy.zeros((p, m), numpy.float)
 
             # Build interpolator
@@ -995 +988 @@
 
         from math import pi, cos, sin, sqrt
-        from Numeric import zeros, Float
         from anuga.abstract_2d_finite_volumes.util import mean        
 
@@ -1031 +1023 @@
 
         # Compute interpolated values
-        q = zeros(len(self.quantity_names), Float)
+        q = numpy.zeros(len(self.quantity_names), numpy.float)
         # print "self.precomputed_values", self.precomputed_values
         for i, name in enumerate(self.quantity_names):
@@ -1086 +1078 @@
                     return q
                 else:
-                    from Numeric import ones, Float
                     # x is a vector - Create one constant column for each value
                     N = len(x)
@@ -1092 +1083 @@
                     res = []
                     for col in q:
-                        res.append(col*ones(N, Float))
+                        res.append(col*numpy.ones(N, numpy.float))
                         
                 return res
@@ -1129 +1120 @@
             minq, maxq = self.quantities_range[name]
             str += '    %s in [%f, %f]\n' %(name, minq, maxq)            
-            #q = quantities[name][:].flat
+            #q = quantities[name][:].ravel()
             #str += '    %s in [%f, %f]\n' %(name, min(q), max(q))
 
@@ -1142 +1133 @@
         
             for name in quantity_names:
-                q = precomputed_values[name][:].flat
+##NumPy                q = precomputed_values[name][:].ravel()
+                q = numpy.ravel(precomputed_values[name][:])
                 str += '    %s at interpolation points in [%f, %f]\n'\
                        %(name, min(q), max(q))
@@ -1165 +1157 @@
 
     #Add the x and y together
-    vertex_coordinates = concatenate((x[:,NewAxis], y[:,NewAxis]),axis=1)
+    vertex_coordinates = numpy.concatenate((x[:,numpy.newaxis], y[:,numpy.newaxis]),axis=1)
 
     #Will return the quantity values at the specified times and locations