Changeset 1471 for trunk/yat/statistics

Timestamp:

Sep 2, 2008, 8:24:20 PM (15 years ago)

Author:

Peter

Message:

fixes #20

Location:

trunk/yat/statistics

Files:

• WilcoxonFoldChange.cc (modified) (2 diffs)
• WilcoxonFoldChange.h (modified) (1 diff)

trunk/yat/statistics/WilcoxonFoldChange.cc

@@ -27 +27 @@
 #include "utility.h"
 #include "yat/classifier/Target.h"
+#include "yat/utility/DataWeight.h"
 
 #include <cmath>
@@ -61 +62 @@
 
 
-  double WilcoxonFoldChange::score
-  (const classifier::Target& target, 
-   const classifier::DataLookupWeighted1D& value) const
-  {
-    std::cerr << " WilcoxonFoldChange::score  not implemented" << std::endl;
-    return 0;
-  }
-
-
   double WilcoxonFoldChange::score(const classifier::Target& target, 
                                    const utility::VectorBase& value,
                                    const utility::VectorBase& weight) const
   {
-    std::cerr << " WilcoxonFoldChange::score  not implemented" << std::endl;
+    std::vector<utility::DataWeight> distance;
+    //Peter, should reserve the vector to avoid reallocations   
+    for (size_t i=0; i<target.size(); i++) {
+      if (target.binary(i)) continue;
+      for (size_t j=0; j<target.size(); j++) {
+        if (!target.binary(j))
+          distance.push_back(utility::DataWeight(value(i)-value(j),
+                                                 weight(i)*weight(j)));
+      }
+    }
+    if (absolute_)
+      return fabs(median(distance.begin(), distance.end()));
+    return median(distance.begin(), distance.end());
+    
+
     return 0;
   }

trunk/yat/statistics/WilcoxonFoldChange.h

@@ -63 +63 @@
  
     /// 
-    /// @return difference of the weighted means of the two classes
-    ///
-    /// @param target defining the two groups (Target.binary() )
-    /// @param value vector of the values (with weights)
-    ///
-    /// @note not implemented
-    ///
-    double score(const classifier::Target& target, 
-                 const classifier::DataLookupWeighted1D& value) const; 
- 
+    /// @return weighted median of all pairwise differences
     /// 
-    /// @return difference of the weighted means of the two classes
+    /// For each pair a DataWeight is created with value = value(i) -
+    /// value(j) and weight = weight(i)*weight(j) where sample i and
+    /// sample j come from different groups.
     ///
     /// @param target defining the two groups