merged

dlib/CMakeLists.txt

@@ -816,10 +816,10 @@ if (MSVC)
    # what happens since, at the very least, the filenames will indicate what
    # visual studio runtime they go with.
    math(EXPR numbits ${CMAKE_SIZEOF_VOID_P}*8)
-   set_target_properties(dlib PROPERTIES DEBUG_POSTFIX "_debug_${numbits}bit_msvc${MSVC_VERSION}")
-   set_target_properties(dlib PROPERTIES RELEASE_POSTFIX "_release_${numbits}bit_msvc${MSVC_VERSION}")
-   set_target_properties(dlib PROPERTIES MINSIZEREL_POSTFIX "_minsizerel_${numbits}bit_msvc${MSVC_VERSION}")
-   set_target_properties(dlib PROPERTIES RELWITHDEBINFO_POSTFIX "_relwithdebinfo_${numbits}bit_msvc${MSVC_VERSION}")
+   set_target_properties(dlib PROPERTIES DEBUG_POSTFIX "${VERSION}_debug_${numbits}bit_msvc${MSVC_VERSION}")
+   set_target_properties(dlib PROPERTIES RELEASE_POSTFIX "${VERSION}_release_${numbits}bit_msvc${MSVC_VERSION}")
+   set_target_properties(dlib PROPERTIES MINSIZEREL_POSTFIX "${VERSION}_minsizerel_${numbits}bit_msvc${MSVC_VERSION}")
+   set_target_properties(dlib PROPERTIES RELWITHDEBINFO_POSTFIX "${VERSION}_relwithdebinfo_${numbits}bit_msvc${MSVC_VERSION}")
 endif()
 
 add_library(dlib::dlib ALIAS dlib)

dlib/image_processing/object_detector_abstract.h

@@ -185,7 +185,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - idx < num_detectors
+                - idx < num_detectors()
             ensures
                 - returns the idx-th weight vector loaded into this object.  All the weight vectors
                   have the same dimension and logically each represents a different detector.

dlib/statistics/statistics.h

@@ -499,7 +499,7 @@ namespace dlib
             sum_x  = sum_x*forget + x;
             sum_y  = sum_y*forget + y;
 
-            n = n*forget + forget;
+            n = n*forget + 1;
         }
 
         T current_n (
@@ -530,20 +530,20 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::covariance()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
                 );
 
-            return 1/n * (sum_xy - sum_y*sum_x/n);
+            return 1/(n-1) * (sum_xy - sum_y*sum_x/n);
         }
 
         T correlation (
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::correlation()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
@@ -560,13 +560,13 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::variance_x()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
                 );
 
-            T temp = 1/n * (sum_xx - sum_x*sum_x/n);
+            T temp = 1/(n-1) * (sum_xx - sum_x*sum_x/n);
             // make sure the variance is never negative.  This might
             // happen due to numerical errors.
             if (temp >= 0)
@@ -579,13 +579,13 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::variance_y()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
                 );
 
-            T temp = 1/n * (sum_yy - sum_y*sum_y/n);
+            T temp = 1/(n-1) * (sum_yy - sum_y*sum_y/n);
             // make sure the variance is never negative.  This might
             // happen due to numerical errors.
             if (temp >= 0)
@@ -598,7 +598,7 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::stddev_x()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
@@ -611,7 +611,7 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_scalar_covariance_decayed::stddev_y()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
@@ -673,7 +673,7 @@ namespace dlib
 
             sum_x  = sum_x*forget + x;
 
-            n = n*forget + forget;
+            n = n*forget + 1;
         }
 
         T current_n (
@@ -695,13 +695,13 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_stats_decayed::variance()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this
                 );
 
-            T temp = 1/n * (sum_xx - sum_x*sum_x/n);
+            T temp = 1/(n-1) * (sum_xx - sum_x*sum_x/n);
             // make sure the variance is never negative.  This might
             // happen due to numerical errors.
             if (temp >= 0)
@@ -714,7 +714,7 @@ namespace dlib
         ) const
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(current_n() > 0,
+            DLIB_ASSERT(current_n() > 1,
                 "\tT running_stats_decayed::stddev()"
                 << "\n\tyou have to add some numbers to this object first"
                 << "\n\tthis: " << this

dlib/statistics/statistics_abstract.h

@@ -570,7 +570,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the covariance between all the x and y samples presented
                   to this object via add()
@@ -580,7 +580,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the correlation coefficient between all the x and y samples 
                   presented to this object via add()
@@ -590,7 +590,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample variance value of all x samples presented 
                   to this object via add().
@@ -600,7 +600,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample variance value of all y samples presented 
                   to this object via add().
@@ -610,7 +610,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample standard deviation of all x samples
                   presented to this object via add().
@@ -620,7 +620,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample standard deviation of all y samples
                   presented to this object via add().
@@ -703,7 +703,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample variance value of all x samples presented to this
                   object via add().
@@ -713,7 +713,7 @@ namespace dlib
         ) const;
         /*!
             requires
-                - current_n() > 0
+                - current_n() > 1
             ensures
                 - returns the sample standard deviation of all x samples presented to this
                   object via add().

dlib/test/statistics.cpp

@@ -340,14 +340,12 @@ namespace
             DLIB_TEST(std::abs(rsc2.correlation() - 0) < 1e-10);
 
 
-            const double s = 99/100.0;
-            const double ss = std::sqrt(s);;
             DLIB_TEST_MSG(std::abs(rs.mean() - rscd1.mean_x()) < 1e-2, std::abs(rs.mean() - rscd1.mean_x()) << " " << rscd1.mean_x());
             DLIB_TEST(std::abs(rs.mean() - rscd1.mean_y()) < 1e-2);
-            DLIB_TEST_MSG(std::abs(ss*rs.stddev() - rscd1.stddev_x()) < 1e-2, std::abs(ss*rs.stddev() - rscd1.stddev_x()));
-            DLIB_TEST(std::abs(ss*rs.stddev() - rscd1.stddev_y()) < 1e-2);
-            DLIB_TEST_MSG(std::abs(s*rs.variance() - rscd1.variance_x()) < 1e-2, std::abs(s*rs.variance() - rscd1.variance_x()));
-            DLIB_TEST(std::abs(s*rs.variance() - rscd1.variance_y()) < 1e-2);
+            DLIB_TEST_MSG(std::abs(rs.stddev() - rscd1.stddev_x()) < 1e-2, std::abs(rs.stddev() - rscd1.stddev_x()));
+            DLIB_TEST(std::abs(rs.stddev() - rscd1.stddev_y()) < 1e-2);
+            DLIB_TEST_MSG(std::abs(rs.variance() - rscd1.variance_x()) < 1e-2, std::abs(rs.variance() - rscd1.variance_x()));
+            DLIB_TEST(std::abs(rs.variance() - rscd1.variance_y()) < 1e-2);
             DLIB_TEST(std::abs(rscd1.correlation() - 1) < 1e-2);
             DLIB_TEST(std::abs(rscd2.correlation() - 0) < 1e-2);
 
@@ -803,6 +801,72 @@ namespace
             DLIB_TEST(equal_error_rate(vals2, vals1).first == 1);
         }
 
+        void test_running_stats_decayed()
+        {
+            print_spinner();
+            std::vector<double> tmp(300);
+            std::vector<double> tmp_var(tmp.size());
+            dlib::rand rnd;
+            const int num_rounds = 100000;
+            for (int rounds = 0; rounds < num_rounds; ++rounds)
+            {
+                running_stats_decayed<double> rs(100);
+
+                for (size_t i = 0; i < tmp.size(); ++i)
+                {
+                    rs.add(rnd.get_random_gaussian() + 1);
+                    tmp[i] += rs.mean();
+                    if (i > 0)
+                        tmp_var[i] += rs.variance();
+                }
+            }
+
+            // should print all 1s basically since the mean and variance should always be 1.
+            for (size_t i = 0; i < tmp.size(); ++i)
+            {
+                DLIB_TEST(std::abs(1-tmp[i]/num_rounds) < 0.001);
+                if (i > 1)
+                    DLIB_TEST(std::abs(1-tmp_var[i]/num_rounds) < 0.01);
+            }
+        }
+
+        void test_running_scalar_covariance_decayed()
+        {
+            print_spinner();
+            std::vector<double> tmp(300);
+            std::vector<double> tmp_var(tmp.size());
+            std::vector<double> tmp_covar(tmp.size());
+            dlib::rand rnd;
+            const int num_rounds = 500000;
+            for (int rounds = 0; rounds < num_rounds; ++rounds)
+            {
+                running_scalar_covariance_decayed<double> rs(100);
+
+                for (size_t i = 0; i < tmp.size(); ++i)
+                {
+                    rs.add(rnd.get_random_gaussian() + 1, rnd.get_random_gaussian() + 1);
+                    tmp[i] += (rs.mean_y()+rs.mean_x())/2;
+                    if (i > 0)
+                    {
+                        tmp_var[i] += (rs.variance_y()+rs.variance_x())/2;
+                        tmp_covar[i] += rs.covariance();
+                    }
+                }
+            }
+
+            // should print all 1s basically since the mean and variance should always be 1.
+            for (size_t i = 0; i < tmp.size(); ++i)
+            {
+                DLIB_TEST(std::abs(1-tmp[i]/num_rounds) < 0.001);
+                if (i > 1)
+                {
+                    DLIB_TEST(std::abs(1-tmp_var[i]/num_rounds) < 0.01);
+                    DLIB_TEST(std::abs(tmp_covar[i]/num_rounds) < 0.001);
+                }
+            }
+        }
+
+
         void test_event_corr()
         {
             print_spinner();
@@ -841,6 +905,8 @@ namespace
             test_average_precision();
             test_lda();
             test_event_corr();
+            test_running_stats_decayed();
+            test_running_scalar_covariance_decayed();
         }
     } a;
 

docs/docs/howto_contribute.xml

@@ -13,17 +13,10 @@
 
         <!--   ****************************   EASY CONTRIBUTIONS  ****************************    -->
 
-         There are some simple ways to contribute to dlib:
+        <h2>Contributing Money</h2>
 
-         <ul>
-            <li> Find confusing or incorrect documentation </li>
-            <li> Help make the web page prettier </li>
-            <li> Link to dlib from your web page </li>
-            <li> Add yourself or your project to the list of 
-            <a href="http://sourceforge.net/p/dclib/wiki/Known_users/">dlib users</a> </li>
-            <li> Try to run the dlib regression test suite on any platforms you
-            have access to </li>
-         </ul>
+         The simplest way to contribute is to donate money via Zelle or PayPal
+         to davis@dlib.net. Any amount is appreciated :)
 
         <!--   ****************************   CODE CONTRIBUTIONS  ****************************    -->
         <h2>Contributing Code</h2>

setup.py

@@ -185,7 +185,7 @@ class PyTest(TestCommand):
 
     def initialize_options(self):
         TestCommand.initialize_options(self)
-        self.pytest_args = ''
+        self.pytest_args = '--ignore docs --ignore dlib'
 
     def run_tests(self):
         import shlex