fix some false positive warnings emitted by msvc

boostorg · Apr 25, 2024 · 44fa5eb · 44fa5eb
1 parent 90867e2
commit 44fa5eb
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Showing 7 changed files with 52 additions and 49 deletions.
diff --git a/Jamfile b/Jamfile
@@ -17,7 +17,7 @@ project
     : requirements
     <implicit-dependency>/boost//headers
     <include>$(BOOST_ROOT)
-    <toolset>clang:<cxxflags>"-pedantic -Wextra -Wsign-compare -Wstrict-aliasing -fstrict-aliasing -Wvexing-parse -Wfloat-conversion -fvisibility=hidden -fvisibility-inlines-hidden"
+    <toolset>clang:<cxxflags>"-pedantic -Wextra -Wsign-compare -Wstrict-aliasing -fstrict-aliasing -Wvexing-parse -Wfloat-conversion -Wimplicit-float-conversion -fvisibility=hidden -fvisibility-inlines-hidden"
     <toolset>darwin:<cxxflags>"-pedantic -Wextra -Wsign-compare -Wstrict-aliasing -fstrict-aliasing -Wvexing-parse -Wfloat-conversion -fvisibility=hidden -fvisibility-inlines-hidden"
     <toolset>gcc:<cxxflags>"-pedantic -Wextra -Wsign-compare -Wstrict-aliasing -fstrict-aliasing -Wfloat-conversion -fvisibility=hidden -fvisibility-inlines-hidden"
     <toolset>msvc:<cxxflags>"/bigobj"

diff --git a/include/boost/histogram/utility/clopper_pearson_interval.hpp b/include/boost/histogram/utility/clopper_pearson_interval.hpp
@@ -54,21 +54,21 @@ class clopper_pearson_interval : public binomial_proportion_interval<ValueType>
     @param successes Number of successful trials.
     @param failures Number of failed trials.
   */
-  interval_type operator()(value_type successes, value_type failures) const noexcept {
+  interval_type operator()(value_type successes, value_type failures) const noexcept override {
     // analytical solution when successes or failures are zero
     // T. Mans (2014), Electronic Journal of Statistics. 8 (1): 817-840.
     // arXiv:1303.1288. doi:10.1214/14-EJS909.
-    const value_type total = successes + failures;
-    if (successes == 0) return {0, 1 - std::pow(alpha_half_, 1 / total)};
-    if (failures == 0) return {std::pow(alpha_half_, 1 / total), 1};
+    const value_type one{1.0}, zero{0.0}, total{successes + failures};
+    if (successes == 0) return {zero, one - std::pow(alpha_half_, one / total)};
+    if (failures == 0) return {std::pow(alpha_half_, one / total), one};
 
     // Source:
     // https://en.wikipedia.org/wiki/
     //   Binomial_proportion_confidence_interval#Clopper%E2%80%93Pearson_interval
     math::beta_distribution<value_type> beta_a(successes, failures + 1);
     const value_type a = math::quantile(beta_a, alpha_half_);
     math::beta_distribution<value_type> beta_b(successes + 1, failures);
-    const value_type b = math::quantile(beta_b, 1 - alpha_half_);
+    const value_type b = math::quantile(beta_b, one - alpha_half_);
     return {a, b};
   }
 

diff --git a/include/boost/histogram/utility/jeffreys_interval.hpp b/include/boost/histogram/utility/jeffreys_interval.hpp
@@ -51,19 +51,20 @@ class jeffreys_interval : public binomial_proportion_interval<ValueType> {
     @param successes Number of successful trials.
     @param failures Number of failed trials.
   */
-  interval_type operator()(value_type successes, value_type failures) const noexcept {
+  interval_type operator()(value_type successes,
+                           value_type failures) const noexcept override {
     // See L.D. Brown, T.T. Cai, A. DasGupta, Statistical Science 16 (2001) 101-133,
     // doi:10.1214/ss/1009213286, section 4.1.2.
-    const value_type half{0.5};
+    const value_type half{0.5}, one{1.0}, zero{0.0};
     const value_type total = successes + failures;
 
     // if successes or failures are 0, modified interval is equal to Clopper-Pearson
-    if (successes == 0) return {0, 1 - std::pow(alpha_half_, 1 / total)};
-    if (failures == 0) return {std::pow(alpha_half_, 1 / total), 1};
+    if (successes == 0) return {zero, one - std::pow(alpha_half_, one / total)};
+    if (failures == 0) return {std::pow(alpha_half_, one / total), one};
 
     math::beta_distribution<value_type> beta(successes + half, failures + half);
-    const value_type a = successes == 1 ? 0 : math::quantile(beta, alpha_half_);
-    const value_type b = failures == 1 ? 1 : math::quantile(beta, 1 - alpha_half_);
+    const value_type a = successes == 1 ? zero : math::quantile(beta, alpha_half_);
+    const value_type b = failures == 1 ? one : math::quantile(beta, one - alpha_half_);
     return {a, b};
   }
 

diff --git a/include/boost/histogram/utility/wald_interval.hpp b/include/boost/histogram/utility/wald_interval.hpp
@@ -59,7 +59,8 @@ class wald_interval : public binomial_proportion_interval<ValueType> {
     @param successes Number of successful trials.
     @param failures Number of failed trials.
   */
-  interval_type operator()(value_type successes, value_type failures) const noexcept {
+  interval_type operator()(value_type successes,
+                           value_type failures) const noexcept override {
     // See https://en.wikipedia.org/wiki/
     //   Binomial_proportion_confidence_interval
     //   #Normal_approximation_interval_or_Wald_interval

diff --git a/include/boost/histogram/utility/wilson_interval.hpp b/include/boost/histogram/utility/wilson_interval.hpp
@@ -58,7 +58,8 @@ class wilson_interval : public binomial_proportion_interval<ValueType> {
     @param successes Number of successful trials.
     @param failures Number of failed trials.
   */
-  interval_type operator()(value_type successes, value_type failures) const noexcept {
+  interval_type operator()(value_type successes,
+                           value_type failures) const noexcept override {
     // See https://en.wikipedia.org/wiki/
     //   Binomial_proportion_confidence_interval
     //   #Wilson_score_interval

diff --git a/test/utility_clopper_pearson_interval_test.cpp b/test/utility_clopper_pearson_interval_test.cpp
@@ -18,7 +18,7 @@ template <class T>
 void test() {
   const T atol = 0.001;
 
-  clopper_pearson_interval<T> iv(deviation{1.f});
+  clopper_pearson_interval<T> iv(deviation{1});
 
   {
     const auto x = iv(0.f, 1.f);

diff --git a/test/utility_jeffreys_interval_test.cpp b/test/utility_jeffreys_interval_test.cpp
@@ -25,78 +25,78 @@ void test() {
   jeffreys_interval<T> iv(confidence_level{0.95});
 
   {
-    auto p = iv(0, 7);
-    BOOST_TEST_IS_CLOSE(p.first, 0, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.41, atol);
+    auto p = iv(0.f, 7.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.41f, atol);
   }
 
   {
-    auto p = iv(1, 6);
-    BOOST_TEST_IS_CLOSE(p.first, 0, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.501, atol);
+    auto p = iv(1.f, 6.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.501f, atol);
   }
 
   {
-    auto p = iv(2, 5);
-    BOOST_TEST_IS_CLOSE(p.first, 0.065, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.648, atol);
+    auto p = iv(2.f, 5.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.065f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.648f, atol);
   }
 
   {
-    auto p = iv(3, 4);
-    BOOST_TEST_IS_CLOSE(p.first, 0.139, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.766, atol);
+    auto p = iv(3.f, 4.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.139f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.766f, atol);
   }
 
   {
-    auto p = iv(4, 7 - 4);
-    BOOST_TEST_IS_CLOSE(p.first, 0.234, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.861, atol);
+    auto p = iv(4.f, 7.f - 4.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.234f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.861f, atol);
   }
 
   // extrapolated from table
   {
-    auto p = iv(5, 2);
-    BOOST_TEST_IS_CLOSE(p.first, 1 - 0.648, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 1 - 0.065, atol);
+    auto p = iv(5.f, 2.f);
+    BOOST_TEST_IS_CLOSE(p.first, 1.f - 0.648f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 1.f - 0.065f, atol);
   }
 
   // extrapolated from table
   {
-    auto p = iv(6, 1);
-    BOOST_TEST_IS_CLOSE(p.first, 1 - 0.501, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 1, atol);
+    auto p = iv(6.f, 1.f);
+    BOOST_TEST_IS_CLOSE(p.first, 1.f - 0.501f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 1.f, atol);
   }
 
   // extrapolated from table
   {
-    auto p = iv(7, 0);
-    BOOST_TEST_IS_CLOSE(p.first, 1 - 0.41, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 1, atol);
+    auto p = iv(7.f, 0.f);
+    BOOST_TEST_IS_CLOSE(p.first, 1.f - 0.41f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 1.f, atol);
   }
 
   // not in table
   {
-    auto p = iv(0, 1);
-    BOOST_TEST_IS_CLOSE(p.first, 0, atol);
-    BOOST_TEST_IS_CLOSE(p.second, 0.975, atol);
+    auto p = iv(0.f, 1.f);
+    BOOST_TEST_IS_CLOSE(p.first, 0.f, atol);
+    BOOST_TEST_IS_CLOSE(p.second, 0.975f, atol);
 
-    fraction<T> f(0, 1);
+    fraction<T> f(0.f, 1.f);
     const auto y = iv(f);
-    BOOST_TEST_IS_CLOSE(y.first, 0.0, atol);
-    BOOST_TEST_IS_CLOSE(y.second, 0.975, atol);
+    BOOST_TEST_IS_CLOSE(y.first, 0.f, atol);
+    BOOST_TEST_IS_CLOSE(y.second, 0.975f, atol);
   }
 
   // not in table
   {
-    auto p = iv(1, 0);
+    auto p = iv(1.f, 0.f);
     BOOST_TEST_IS_CLOSE(p.first, 0.025, atol);
     BOOST_TEST_IS_CLOSE(p.second, 1, atol);
 
-    fraction<T> f(1, 0);
+    fraction<T> f(1.f, 0.f);
     const auto y = iv(f);
-    BOOST_TEST_IS_CLOSE(y.first, 0.025, atol);
-    BOOST_TEST_IS_CLOSE(y.second, 1, atol);
+    BOOST_TEST_IS_CLOSE(y.first, 0.025f, atol);
+    BOOST_TEST_IS_CLOSE(y.second, 1.f, atol);
   }
 }