From d7f207f2f7e7e29f8807a09ec0b2809eeb24c1f5 Mon Sep 17 00:00:00 2001
From: Davis King <davis@dlib.net>
Date: Fri, 23 May 2014 18:35:49 -0400
Subject: [PATCH] Added unit tests for the svm_multiclass_linear with sparse
 priors

---
 dlib/test/svm_multiclass_linear.cpp | 58 +++++++++++++++++++++++++++++
 1 file changed, 58 insertions(+)

diff --git a/dlib/test/svm_multiclass_linear.cpp b/dlib/test/svm_multiclass_linear.cpp
index a5cb699c5..e01d48892 100644
--- a/dlib/test/svm_multiclass_linear.cpp
+++ b/dlib/test/svm_multiclass_linear.cpp
@@ -6,6 +6,7 @@
 #include <dlib/data_io.h>
 #include "create_iris_datafile.h"
 #include <vector>
+#include <map>
 #include <sstream>
 
 namespace  
@@ -92,6 +93,62 @@ namespace
             DLIB_TEST((unsigned int)sum(diag(res))==samples.size());
         }
 
+        void test_prior_sparse ()
+        {
+            print_spinner();
+            typedef std::map<unsigned long,double> sample_type;
+            typedef sparse_linear_kernel<sample_type> kernel_type;
+
+            std::vector<sample_type> samples;
+            std::vector<int> labels;
+
+            for (int i = 0; i < 4; ++i)
+            {
+                if (i==2)
+                    ++i;
+                for (int iter = 0; iter < 5; ++iter)
+                {
+                    sample_type samp;
+                    samp[i] = 1;
+                    samples.push_back(samp);
+                    labels.push_back(i);
+                }
+            }
+
+
+            svm_multiclass_linear_trainer<kernel_type,int> trainer;
+
+            multiclass_linear_decision_function<kernel_type,int> df = trainer.train(samples, labels);
+
+            //cout << "test: \n" << test_multiclass_decision_function(df, samples, labels) << endl;
+            //cout << df.weights << endl;
+            //cout << df.b << endl;
+
+            std::vector<sample_type> samples2;
+            std::vector<int> labels2;
+            int i = 2;
+            for (int iter = 0; iter < 5; ++iter)
+            {
+                sample_type samp;
+                samp[i] = 1;
+                samp[i+10] = 1;
+                samples2.push_back(samp);
+                labels2.push_back(i);
+                samples.push_back(samp);
+                labels.push_back(i);
+            }
+
+            trainer.set_prior(df);
+            trainer.set_c(0.1);
+            df = trainer.train(samples2, labels2);
+
+            matrix<double> res = test_multiclass_decision_function(df, samples, labels);
+            dlog << LINFO << "test: \n" << res;
+            dlog << LINFO << df.weights;
+            dlog << LINFO << df.b;
+            DLIB_TEST((unsigned int)sum(diag(res))==samples.size());
+        }
+
         template <typename sample_type>
         void run_test()
         {
@@ -158,6 +215,7 @@ namespace
             run_test<std::vector<std::pair<unsigned long, double> > >();
 
             test_prior();
+            test_prior_sparse();
         }
     };