moved teh grid code into the grid class

by next friday i need to have implemented a way to select between normal kdtree point lookups, and nearest-neighbor lookups. Hopefully i'll have that done tonight.

bin/driver.py

@@ -4,9 +4,7 @@ import sys
 from optparse import OptionParser
 
 import numpy as np
-import scipy.spatial
 
-import baker
 from tools import rms, exact_func
 import grid
 
@@ -72,36 +70,21 @@ if __name__ == '__main__':
                     help = "verbosity")
 
   (options, args) = parser.parse_args()
-  print >> sys.stderr, "options: %s, args: %s" % (options, args)
 
 
+  (mesh_source, mesh_dest) = get_mesh(options.source_total, options.destination_total, options.structured)
 
-
-  (mesh_source, mesh_dest) = get_mesh(options.source_total, options.destination_total, options.structured) 
-
-  tree = scipy.spatial.KDTree(mesh_source.points)
   open(options.output, 'w').write(mesh_source.for_qhull())
-  print >> sys.stderr, "wrote source mesh output to %s" % options.output
+  if options.verbose:
+    print >> sys.stderr, "options: %s, args: %s" % (options, args)
+    print >> sys.stderr, "wrote source mesh output to %s" % options.output
 
   errors = []
   success = 0
 
   for X in mesh_dest.points:
 
-    (dist, indicies) = tree.query(X, 3 + options.extra)
+    answer = mesh_source.run_baker(X)
-
-
-    # get the containing simplex
-    R  = [mesh_source.points[i] for i in indicies[:3] ]
-    Rq = [mesh_source.q[i]      for i in indicies[:3] ]
-    r_mesh = grid.grid(R, Rq)
-
-    # and some extra points
-    S  = [mesh_source.points[i] for i in indicies[3:] ]
-    Sq = [mesh_source.q[i]      for i in indicies[3:] ]
-    s_mesh = grid.grid(S, Sq)
-
-    answer = baker.run_baker(X, r_mesh, s_mesh, options.verbose)
 
     if answer['a'] == None:
       errors.append(0)
@@ -114,9 +97,9 @@ if __name__ == '__main__':
     if options.verbose:
       print "current point : %s"    % X
       print "exact         : %0.4f" % exact
-      print "qlin          : %0.4f" % answer['lin']
+      print "qlin          : %0.4f" % answer['qlin']
       print "q_final       : %0.4f" % answer['final']
-      print "qlinerr       : %1.4f" % (exact - anser['lin'],)
+      print "qlinerr       : %1.4f" % (exact - answer['qlin'],)
       print "q_final_err   : %0.4f" % (exact - answer['final'],)
     cur_error = np.abs(answer['final'] - exact)
     errors.append(cur_error)

lib/baker.py

@@ -1,4 +1,3 @@
-from grid import exact_func
 import numpy as np
 import sys
 
@@ -93,16 +92,16 @@ def qlinear_3D(X, R, q):
   qlin = sum([q_i * phi_i for q_i, phi_i in zip(q, phis)])
   return qlin
 
-def run_baker(X, R, S, verbose = False):
+def run_baker(X, R, S):
   """
-    This is the main function to call to get an interpolation to X from the tree
+    This is the main function to call to get an interpolation to X from the input meshes
 
     X -- the destination point (2D)
          X = [0,0]
 
-    g -- the grid object
+    R = Simplex
 
-    tree -- the kdtree search object (built from the g mesh)
+    S = extra points
 
   """
 

lib/grid.py

@@ -7,6 +7,7 @@ from collections import defaultdict
 import numpy as np
 import scipy.spatial
 
+from baker import run_baker
 from tools import exact_func
 from smcqdelaunay import *
 
@@ -58,9 +59,36 @@ class grid(object):
 
     self.points           = np.array(points)
     self.q                = np.array(q)
+    self.tree             = scipy.spatial.KDTree(self.points)
     self.faces            = {}
     self.facets_for_point = defaultdict(list)
 
+  def get_simplex_and_nearest_points(self, X, extra_points = 3, simplex_size = 3):
+    """
+      this returns two grid objects: R and S.
+
+      R is a grid object that is the (a) containing simplex around point X
+      S is S_j from baker's paper : some points from all point that are not the simplex
+    """
+    (dist, indicies) = self.tree.query(X, 3 + extra_points)
+
+
+    # get the containing simplex
+    R  = [self.points[i] for i in indicies[:simplex_size] ]
+    Rq = [self.q[i]      for i in indicies[:simplex_size] ]
+    r_mesh = grid(R, Rq)
+
+    # and some extra points
+    S  = [self.points[i] for i in indicies[simplex_size:] ]
+    Sq = [self.q[i]      for i in indicies[simplex_size:] ]
+    s_mesh = grid(S, Sq)
+
+    return (r_mesh, s_mesh)
+
+  def run_baker(self, X):
+    (R, S) = self.get_simplex_and_nearest_points(X)
+    return run_baker(X, R, S)
+
   def construct_connectivity(self):
     """
       a call to this method prepares the internal connectivity structure.