Changeset 731

Timestamp:

Jan 6, 2007, 5:06:19 PM (15 years ago)

Author:

Peter

Message:

added test for multidimensional weighted and straight version

Location:

trunk

Files:

• test/regression_test.cc (modified) (4 diffs)
• yat/regression/MultiDimensional.cc (modified) (3 diffs)
• yat/regression/MultiDimensional.h (modified) (1 diff)
• yat/regression/MultiDimensionalWeighted.cc (modified) (3 diffs)
• yat/regression/MultiDimensionalWeighted.h (modified) (1 diff)
• yat/regression/PolynomialWeighted.cc (modified) (1 diff)

trunk/test/regression_test.cc

@@ -43 +43 @@
 bool equal(regression::OneDimensional&, regression::OneDimensionalWeighted&, 
            std::ostream*); 
+
+bool multidim(std::ostream* error);
 
 bool unity_weights(regression::OneDimensional&, 
@@ -185 +187 @@
   *error << "  testing regression::PolynomialWeighted" << std::endl;
   regression::PolynomialWeighted pol_weighted(2);
+  // ok = equal(polynomial, pol_weighted, error) && ok;
+
+  ok = multidim(error) && ok;
 
   if (error!=&std::cerr)
@@ -220 +225 @@
   if (r.predict(2000) != rw.predict(2000)){
     ok = false;
-    *error << "Error: predict not equal" << std::endl;
+    *error << "Error: predict not equal\n" 
+           << "   weighted: " << rw.predict(2000) << "\n"
+           << "   non-weighted: " << r.predict(2000)
+           << std::endl;
   }
   if (fabs(r.prediction_error2(2000)-rw.prediction_error2(2000))>10e-7){
@@ -340 +348 @@
 
 
+bool multidim(std::ostream* error)
+{
+  bool ok = true;
+  *error << "  testing regression::MultiDimensionalWeighted" << std::endl;
+  utility::vector x(5); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; x(4)=2010;
+  utility::vector y(5); y(0)=12;   y(1)=11;   y(2)=14;   y(3)=13;   y(4)=15;
+  utility::vector w(5,1.0);
+  
+  utility::matrix data(5,3);
+  for (size_t i=0; i<data.rows(); ++i){
+    data(i,0)=1;
+    data(i,1)=x(i);
+    data(i,2)=x(i)*x(i);
+  }
+  regression::MultiDimensional md;
+  md.fit(data,y);
+  regression::MultiDimensionalWeighted mdw;
+  mdw.fit(data,y,w);
+  utility::vector z(3,1);
+  z(1)=2000;
+  z(2)=2000*2000;
+  if (md.predict(z) != mdw.predict(z)){
+    ok = false;
+    *error << "Error: predict not equal\n" 
+           << "   weighted: " << mdw.predict(1) << "\n"
+           << "   non-weighted: " << md.predict(1)
+           << std::endl;
+  }
+  /*
+  if (md.standard_error2(z) != mdw.standard_error2(z)){
+    ok = false;
+    *error << "Error: standard_error2 not equal\n" 
+           << "   weighted: " << mdw.standard_error2(z) << "\n"
+           << "   non-weighted: " << md.standard_error2(z)
+           << std::endl;
+  }
+  */
+  return ok;
+}
+
+
 bool Local_test(regression::OneDimensionalWeighted& r, 
                 regression::Kernel& k)

trunk/yat/regression/MultiDimensional.cc

@@ -26 +26 @@
 #include "yat/utility/vector.h"
 
+#include <cassert>
+
 namespace theplu {
 namespace yat {
@@ -52 +54 @@
   void MultiDimensional::fit(const utility::matrix& x, const utility::vector& y)
   {
+    assert(x.rows()==y.size());
     covariance_=utility::matrix(x.columns(),x.columns());
     fit_parameters_=utility::vector(x.columns());
@@ -76 +79 @@
   double MultiDimensional::predict(const utility::vector& x) const 
   {
+    assert(x.size()==fit_parameters_.size());
     return fit_parameters_ * x;
   }

trunk/yat/regression/MultiDimensional.h

@@ -68 +68 @@
 
     /**
-       @brief Mean Squared Error
+       @brief Summed Squared Error
      */
     double chisq(void) const;

trunk/yat/regression/MultiDimensionalWeighted.cc

@@ -62 +62 @@
   double MultiDimensionalWeighted::predict(const utility::vector& x) const
   {
+    assert(x.size()==fit_parameters_.size());
     return fit_parameters_ * x;
   }
@@ -78 +79 @@
 
 
-  double MultiDimensionalWeighted::standard_error(const utility::vector& x) const
+  double 
+  MultiDimensionalWeighted::standard_error2(const utility::vector& x) const
   {
     double s2 = 0;
@@ -86 +88 @@
         s2 += 2*covariance_(i,j)*x(i)*x(j);
     }
-    return sqrt(s2);
+    return s2;
   }
 

trunk/yat/regression/MultiDimensionalWeighted.h

@@ -70 +70 @@
     /// @return error of model value in @a x
     ///
-    double standard_error(const utility::vector& x) const;
+    double standard_error2(const utility::vector& x) const;
 
     ///

trunk/yat/regression/PolynomialWeighted.cc

@@ -81 +81 @@
     for (size_t i=1; i<=power_; ++i)
       vec(i) = vec(i-1)*x;
-    return md_.standard_error(vec);
+    return md_.standard_error2(vec);
   }