partially implemented using new data structure in point lookup

I spoke with Dr. Gorrell about first trying to call the nearest-neighbor routine, releasing the trapped exception where the matrix ends up being singular, and trapping it in the grid object's run_baker, where I could then call the connectivity-based lookup routine. Those are my next steps, as well as starting to think about pushing the 3D front ahead this week.

lib/grid.py

@@ -111,6 +111,13 @@ class grid(object):
     """
       this returns two grid objects: R and S.
 
+      this function differes from the get_simplex_and_nearest_points
+      function in that it builds up the extra points based on
+      connectivity information, not just nearest-neighbor.
+      in theory, this will work much better for situations like
+      points near a short edge in a boundary layer cell where the
+      nearest points would all be colinear
+
       R is a grid object that is the (a) containing simplex around point X
       S is a connectivity-based nearest-neighbor lookup, limited to 3 extra points
     """
@@ -128,7 +135,7 @@ class grid(object):
 
     if not simplex:
       raise AssertionError('no containing simplex found')
-    simplex_set = set(simplex.verts)
+
     R = self.create_mesh(simplex.verts)
 
 
@@ -139,8 +146,12 @@ class grid(object):
 
     return R, S
 
-  def run_baker(self, X):
-    (R, S) = self.get_simplex_and_nearest_points(X)
+  def run_baker(self, X, connectivity_based = False):
+    print >>sys.stderr, "suxor"
+    if connectivity_based:
+      (R, S) = self.get_points_conn(X)
+    else:
+      (R, S) = self.get_simplex_and_nearest_points(X)
     return run_baker(X, R, S)
 
   def construct_connectivity(self):