Skip to content

D
dlib
Commit af1af6d2 authored by Davis King's avatar Davis King
Browse files
Options

Fixed the decayed running stats objects so they use unbiased estimators.

parent 18489b11
Hide whitespace changes
Inline Side-by-side
Showing with 90 additions and 28 deletions
dlib/statistics/statistics.h
View file @ af1af6d2
......@@ -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
View file @ af1af6d2
......@@ -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
View file @ af1af6d2
......@@ -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 +801,68 @@ 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();
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;
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 +901,8 @@ namespace
test_average_precision();
test_lda();
test_event_corr();
test_running_stats_decayed();
test_running_scalar_covariance_decayed();
}
} a;
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment