NAN initialize results.

Author: crmauceri

tests/Distortion Correlation Impact.ipynb renamed to example/Distortion Correlation Impact.ipynb

@@ -1,5 +1,21 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d236b7d9-0991-4e00-b27d-f60671cbaefc",
+   "metadata": {},
+   "source": [
+    "# Distortion Impact\n",
+    "\n",
+    "Recreate the analysis from \n",
+    "\n",
+    "Cecilia Mauceri, Yang Cheng, Yumi Iwashita and Adnan Ansar. \"A Validation Pipeline for Lunar Digital Elevation Models,\" AIAA 2025-2072. AIAA SCITECH 2025 Forum. January 2025. [link](https://arc.aiaa.org/doi/abs/10.2514/6.2025-2072)\n",
+    "\n",
+    "This script artificially distorts DEMs to create map distortion with known parameters and then demonstrates how the correlator can detect this distortion.\n",
+    "\n",
+    "## Setup"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -45,6 +61,14 @@
     "plt.rcParams['figure.figsize'] = [10, 3]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "09cbfc1c-cb87-4d87-8eed-95db43566dff",
+   "metadata": {},
+   "source": [
+    "## Render DEM for visual comparison"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -231,7 +255,7 @@
    "source": [
     "## Self-compare\n",
     "\n",
-    "Landmark compared to itself should have near zero deltas"
+    "Landmark compared to itself without distortion should have near zero deltas"
    ]
   },
   {

example/EarthDemo.ipynb

@@ -21,6 +21,7 @@
  *  limitations under the License.
  */
 
+#include <math.h> // for NAN
 #include <stdlib.h>  // for malloc, free
 #include <stdbool.h> // for bool, false
 #include "landmark_tools/feature_tracking/correlation_results.h"
@@ -39,12 +40,12 @@ bool allocate_correlation_results(CorrelationResults* corr_struct, size_t num_pi
         return false;
     }
 
-    // Initialize all values to 0
+    // Initialize all values to NAN
     for (size_t i = 0; i < num_pixels; ++i) {
-        corr_struct->delta_x[i] = 0.0f;
-        corr_struct->delta_y[i] = 0.0f;
-        corr_struct->delta_z[i] = 0.0f;
-        corr_struct->correlation[i] = 0.0f;
+        corr_struct->delta_x[i] = NAN;
+        corr_struct->delta_y[i] = NAN;
+        corr_struct->delta_z[i] = NAN;
+        corr_struct->correlation[i] = NAN;
     }
 
     return true;
@@ -67,4 +68,4 @@ void destroy_correlation_results(CorrelationResults* corr_struct) {
         free(corr_struct->correlation);
         corr_struct->correlation = NULL;
     }
-} 
+} 

example/MoonDemo.ipynb

@@ -324,11 +324,18 @@ bool process_matched_feature(
 
                 // Update maps with weighted contributions
                 int32_t index = m * num_cols + n;
-                results->delta_x[index] += (float)(delta_map[0] * weight);
-                results->delta_y[index] += (float)(delta_map[1] * weight);
-                results->delta_z[index] += (float)(delta_map[2] * weight);
-                results->correlation[index] += (float)(covariance * weight);
 
+                if(isnan(results->delta_x[index])){
+                    results->delta_x[index] = (float)(delta_map[0] * weight);
+                    results->delta_y[index] = (float)(delta_map[1] * weight);
+                    results->delta_z[index] = (float)(delta_map[2] * weight);
+                    results->correlation[index] = (float)(covariance * weight);
+                }else{
+                    results->delta_x[index] += (float)(delta_map[0] * weight);
+                    results->delta_y[index] += (float)(delta_map[1] * weight);
+                    results->delta_z[index] += (float)(delta_map[2] * weight);
+                    results->correlation[index] += (float)(covariance * weight);
+                }
                 // Update weights
                 if (isnan(weights[index])) {
                     weights[index] = weight;
@@ -414,6 +421,7 @@ bool MatchFeaturesWithLocalDistortion(
             }
 
             double covariances[num_points];
+            memset(covariances, 0, sizeof(double)*num_points);
             int32_t num_matched_features = MatchFeaturesWithNaNHandling(
                 parameters,
                 child_landmark->srm,

example/Rendering.ipynb

@@ -102,16 +102,20 @@ bool process_matched_feature_2d(
 
                 // Update correlation results with weighted contributions
                 int32_t index = m * num_cols + n;
-                results->delta_x[index] += (float)(p_delta_map[0] * weight);
-                results->delta_y[index] += (float)(p_delta_map[1] * weight);
-                results->delta_z[index] += (float)(p_delta_map[2] * weight);
-                results->correlation[index] += (float)(correlation * weight);
-
+                
                 // Update weight matrix for later normalization
                 if (isnan(weights[index])) {
                     weights[index] = weight;  // First contribution to this point
+                    results->delta_x[index] = (float)(p_delta_map[0] * weight);
+                    results->delta_y[index] = (float)(p_delta_map[1] * weight);
+                    results->delta_z[index] = (float)(p_delta_map[2] * weight);
+                    results->correlation[index] = (float)(correlation * weight);
                 } else {
                     weights[index] += weight; // Accumulate weights for multiple features
+                    results->delta_x[index] += (float)(p_delta_map[0] * weight);
+                    results->delta_y[index] += (float)(p_delta_map[1] * weight);
+                    results->delta_z[index] += (float)(p_delta_map[2] * weight);
+                    results->correlation[index] += (float)(correlation * weight);
                 }
             }
         }
@@ -372,4 +376,4 @@ bool MatchFeatures_local_distortion_2d(
     free(weights);
 
     return true;
-} 
+}