Changeset 4048 for trunk/yat/normalizer/Zscore.h

Timestamp:

Mar 3, 2021, 1:39:31 PM (2 years ago)

Author:

Peter

Message:

add parameter allowing scaling to other than unity variance.

File:

• trunk/yat/normalizer/Zscore.h (modified) (5 diffs)

trunk/yat/normalizer/Zscore.h

@@ -42 +42 @@
 
      Shift and scale the values in a range as: \f$ y_i =
-     \frac{x_i-m}{s} \f$ where \a m is the mean and \a s is the
-     standard deviation. After normalization, the range will have zero
-     mean and unity variance.
+     \frac{x_i-m}{k*s} \f$ where \a m is the mean, \a s is the
+     standard deviation, and \a k is set in constructor (default:
+     1.0). After normalization, the range will have zero mean and
+     variance = \f$ 1/k^2 \f$.
 
        Type Requirements:
@@ -57 +58 @@
   {
   public:
+    /**
+       \param k In the scaling step elements are divided by \c k times
+       the standard deviation
+
+       \since New in yat 0.19
+     */
+    Zscore(double k=1.0);
+
+    /**
+       \return the k-factor set in constructor
+
+       \since new in yat 0.19
+     */
+    double k(void) const;
+
     /**
        The element in range [result, result + (last-first)) is
@@ -80 +96 @@
 
   private:
+    double k_;
+
+
     template<class ForwardIterator, class OutputIterator>
     void normalize(ForwardIterator first, ForwardIterator last,
@@ -95 +114 @@
       add(a, first, last);
       double m = a.mean();
-      double std = a.std();
+      double factor = 1.0 / (a.std() * k_);
       while (first!=last) {
-        *result = (*first - m) / std;
+        *result = (*first - m) * factor;
         ++first;
         ++result;
@@ -120 +139 @@
       add(a, first, last);
       double m = a.mean();
-      double std = a.std();
+      double factor = 1.0 / (a.std() * k_);
       utility::iterator_traits<ForwardIterator> in_trait;
       utility::iterator_traits<OutputIterator> out_trait;
       while (first!=last) {
-        out_trait.data(result) = (in_trait.data(first) - m) / std;
+        out_trait.data(result) = (in_trait.data(first) - m) * factor;
         ++first;
         ++result;