Changeset 488 for inundation/ga/storm_surge/pyvolution/least_squares.py

Timestamp:

Nov 5, 2004, 4:42:19 PM (20 years ago)

Author:

ole

Message:

Played with regridding of Cornell data

File:

• inundation/ga/storm_surge/pyvolution/least_squares.py (modified) (6 diffs)

inundation/ga/storm_surge/pyvolution/least_squares.py

@@ -3 +3 @@
    Implements a penalised least-squares fit and associated interpolations.
 
-   The panalty term (or smoothing term) is controlled by the smoothing
+   The penalty term (or smoothing term) is controlled by the smoothing
    parameter alpha.
    With a value of alpha=0, the fit function will attempt
@@ -20 +20 @@
 
 #FIXME (Ole): Currently datapoints outside the triangular mesh are ignored.
-#             Is there a clean way of inlcuding them?
+#             Is there a clean way of including them?
 
 
@@ -152 +152 @@
         Inputs:
         
-          vertex_coordinates: List of coordinate pairs [xi, eta] of points
-          constituting mesh (or a an m x 2 Numeric array)
+          vertex_coordinates: List of coordinate pairs [xi, eta] of 
+          points constituting mesh (or a an m x 2 Numeric array)
         
           triangles: List of 3-tuples (or a Numeric array) of
           integers representing indices of all vertices in the mesh.
 
-          point_coordinates: List of coordinate pairs [x, y] of data points
-          (or an nx2 Numeric array)
+          point_coordinates: List of coordinate pairs [x, y] of 
+          data points (or an nx2 Numeric array)
+          If point_coordinates is absent, only smoothing matrix will 
+          be built 
 
           alpha: Smoothing parameter
@@ -504 +506 @@
     def fit_points(self, z):
         """Like fit, but more robust when each point has two or more attributes
-        FIXME(Ole): The name fit_points doesn't carry any meaning for me.
-        How about something like fit_multiple or fit_columns?
+        FIXME (Ole): The name fit_points doesn't carry any meaning 
+        for me. How about something like fit_multiple or fit_columns?
         """
         
@@ -529 +531 @@
         
     def interpolate(self, f):
-        """Compute predicted values at data points implied in self.A. 
+        """Evaluate smooth surface f at data points implied in self.A. 
 
         The mesh values representing a smooth surface are
@@ -546 +548 @@
         
             
-     
-    #FIXME: We will need a method 'evaluate(self):' that will interpolate
-    #a computed surface living on the mesh onto a collection of
-    #arbitrary data points
-    #
-    #Precondition: self.fit(z) has stored its result in self.f.
-    #
-    #Input: data_points
-    #Algorithm:
-    #  1 Build a new temporary A matrix based on mesh and new data points
-    #  2 Apply it to self.f (return A*self.f)
-    #
-    # ON
-
-
-
 #-------------------------------------------------------------
 if __name__ == "__main__":