Changeset 4658

Timestamp:

Aug 6, 2007, 5:00:03 PM (17 years ago)

Author:

duncan

Message:

minor optimising changes - minimal speed up to fitting

Location:

anuga_core/source/anuga/fit_interpolate

Files:

• benchmark_least_squares.py (modified) (2 diffs)
• search_functions.py (modified) (3 diffs)

anuga_core/source/anuga/fit_interpolate/benchmark_least_squares.py

@@ -136 +136 @@
                 pfile = open(profile_file, "w")
                 sys.stdout = pfile
-                s = S.sort_stats('cumulative').print_stats(30)
+                s = S.sort_stats('cumulative').print_stats(60)
                 sys.stdout = saveout 
                 pfile.close()
@@ -164 +164 @@
                 pfile = open(profile_file, "w")
                 sys.stdout = pfile
-                s = S.sort_stats('cumulative').print_stats(30)
+                s = S.sort_stats('cumulative').print_stats(60)
                 sys.stdout = saveout 
                 pfile.close()

anuga_core/source/anuga/fit_interpolate/search_functions.py

@@ -71 +71 @@
     fit and interpolate.
     """
-    
+
+    # these statments are needed if triangles is empty
     #Find triangle containing x:
     element_found = False
@@ -111 +112 @@
     epsilon = 1.0e-6
     
-    xmax = max(xi0[0], xi1[0], xi2[0])
-    xmin = min(xi0[0], xi1[0], xi2[0])
-    ymax = max(xi0[1], xi1[1], xi2[1])
-    ymin = min(xi0[1], xi1[1], xi2[1])
-
-    
-    if  x[0] > xmax + epsilon:
+    if  x[0] > max(xi0[0], xi1[0], xi2[0]) + epsilon:
         return False,0,0,0
-    if  x[0] < xmin - epsilon:
+    if  x[0] < min(xi0[0], xi1[0], xi2[0]) - epsilon:
         return False,0,0,0
-    if  x[1] > ymax + epsilon:
+    if  x[1] > max(xi0[1], xi1[1], xi2[1]) + epsilon:
         return False,0,0,0
-    if  x[1] < ymin - epsilon:
+    if  x[1] < min(xi0[1], xi1[1], xi2[1]) - epsilon:
         return False,0,0,0
     
-    # Get the three normals 
-    #n0 = norms[0]  
-    #n1 = norms[1]
-    #n2 = norms[2]
-        
-    # Compute interpolation
+    # machine precision on some machines (e.g. nautilus)
+    epsilon = get_machine_precision() * 2
+    
+    # Compute interpolation - return as soon as possible
+    
+    sigma0 = dot((x-xi1), n0)/dot((xi0-xi1), n0)
+    if sigma0 < -epsilon:
+        return False,0,0,0
+    sigma1 = dot((x-xi2), n1)/dot((xi1-xi2), n1)
+    if sigma1 < -epsilon:
+        return False,0,0,0
     sigma2 = dot((x-xi0), n2)/dot((xi2-xi0), n2)
-    sigma0 = dot((x-xi1), n0)/dot((xi0-xi1), n0)
-    sigma1 = dot((x-xi2), n1)/dot((xi1-xi2), n1)
-
-    delta = abs(sigma0+sigma1+sigma2-1.0) # Should be close to zero
-    msg = 'abs(sigma0+sigma1+sigma2-1) = %.15e, eps = %.15e'\
-          %(delta, epsilon)
-    assert delta < epsilon, msg
+    if sigma2 < -epsilon:
+        return False,0,0,0
+    
+    # epsilon = 1.0e-6
+    # we want to speed this up, so don't do assertions
+    #delta = abs(sigma0+sigma1+sigma2-1.0) # Should be close to zero
+    #msg = 'abs(sigma0+sigma1+sigma2-1) = %.15e, eps = %.15e'\
+    #      %(delta, epsilon)
+    #assert delta < epsilon, msg
 
 
@@ -145 +147 @@
     # Sigmas are allowed to get negative within
     # machine precision on some machines (e.g. nautilus)
-    epsilon = get_machine_precision() * 2
-    if sigma0 >= -epsilon and sigma1 >= -epsilon and sigma2 >= -epsilon:
-        element_found = True
-    else:
-        element_found = False 
-    return element_found, sigma0, sigma1, sigma2
+    #if sigma0 >= -epsilon and sigma1 >= -epsilon and sigma2 >= -epsilon:
+    #    element_found = True
+    #else:
+    #    element_found = False 
+    return True, sigma0, sigma1, sigma2