fixes to compilation and output

Author: petergjoel

CMakeLists.txt

@@ -6,9 +6,15 @@ project(libprlearn VERSION 1.0.0 LANGUAGES CXX)
 if(NOT CMAKE_BUILD_TYPE)
     set(CMAKE_BUILD_TYPE Release)
 endif(NOT CMAKE_BUILD_TYPE)
-set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -Wall -Wpedantic")
-set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -O3 -DNDEBUG -Wall -Wpedantic")
+set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -Wall -Wpedantic -static-libgcc -static-libstdc++")
+set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -O3 -DNDEBUG -Wall -Wpedantic -static-libgcc -static-libstdc++")
+
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
 set(CMAKE_CXX_STANDARD 17)
 
+set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
+
 #actual library
 add_subdirectory(src)

src/CMakeLists.txt

@@ -4,8 +4,13 @@ set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
 
-add_library(prlearn ${HEADER_FILES} MLearning.cpp SimpleMLearning.cpp RefinementTree.cpp structs.cpp)
+add_library(prlearn SHARED ${HEADER_FILES} MLearning.cpp SimpleMLearning.cpp RefinementTree.cpp structs.cpp)
+add_library(prlearnStatic STATIC ${HEADER_FILES} MLearning.cpp SimpleMLearning.cpp RefinementTree.cpp structs.cpp)
+
 target_include_directories (prlearn PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
+target_include_directories (prlearnStatic PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
+set_target_properties(prlearnStatic PROPERTIES OUTPUT_NAME prlearn)
+
 
 install(TARGETS prlearn 
 	LIBRARY DESTINATION lib 

src/MLearning.cpp

@@ -29,6 +29,7 @@
 #include <memory>
 #include <algorithm>
 #include <iostream>
+#include <iomanip>
 
 namespace prlearn {
 
@@ -176,6 +177,7 @@ namespace prlearn {
     }
 
     void MLearning::print(std::ostream& s, size_t tabs, std::map<size_t, size_t>& edge_map, const std::vector<MLearning>& clouds) const {
+        s << std::setprecision (std::numeric_limits<double>::digits10 + 1);
         for (size_t i = 0; i < tabs; ++i) s << "\t";
         s << "{";
         bool first = true;
@@ -210,7 +212,16 @@ namespace prlearn {
             s << "}";
         } else {
             for (size_t i = 0; i < tabs; ++i) s << "\t";
-            s << _q.avg();
+            if(_q.cnt() > 0)
+            {
+                auto v = _q.avg();
+                if(!std::isinf(v) && !std::isnan(v))
+                    s << v;
+                else
+                    s << "\"inf\"";
+            }
+            else
+                s << "\"inf\"";
         }
     }
 

src/MLearning.h

@@ -32,7 +32,7 @@
 #include <map>
 #include <limits>
 
-namespace prlearn {
+namespace prlearn { 
 
     class MLearning {
     public:

src/RefinementTree.cpp

@@ -25,12 +25,15 @@
 
 #include "RefinementTree.h"
 #include <limits>
+#include <iomanip>
+
 namespace prlearn {
 
     RefinementTree::RefinementTree() {
     }
 
     void RefinementTree::print(std::ostream& s, size_t tabs, std::map<size_t, size_t>& edge_map) const {
+        s << std::setprecision (std::numeric_limits<double>::digits10 + 1);
         for (size_t i = 0; i < tabs; ++i) s << "\t";
         s << "{";
         bool first = true;
@@ -121,7 +124,11 @@ namespace prlearn {
             for (size_t i = 0; i < tabs; ++i) s << "\t";
             s << "}";
         } else {
-            s << _predictor._q.avg();
+            auto v = _predictor._q.avg();
+            if(!std::isinf(v) && !std::isnan(v))
+                s << _predictor._q.avg();
+            else
+                s << "\"inf\"";
         }
     }
 

src/SimpleMLearning.cpp

@@ -24,6 +24,7 @@
  */
 
 #include "SimpleMLearning.h"
+#include <iomanip>
 
 namespace prlearn {
     SimpleMLearning::~SimpleMLearning() {
@@ -58,6 +59,7 @@ namespace prlearn {
     }
 
     void SimpleMLearning::print(std::ostream& s, size_t tabs, std::map<size_t, size_t>& label_map, const std::vector<SimpleMLearning>& other) const {
+        s << std::setprecision (std::numeric_limits<double>::digits10 + 1);
         for (size_t i = 0; i < tabs; ++i) s << "\t";
         s << "{\"id\":" << (this - other.data()) << ",";
         bool first = true;
@@ -69,7 +71,13 @@ namespace prlearn {
             for (size_t i = 0; i < tabs + 1; ++i) s << "\t";
             s << "\"";
             s << label_map[el._label];
-            s << "\":{\"val\":" << el._q.avg() << ",\"succs\":[";
+            s << "\":{\"val\":";
+            auto v = el._q.avg();
+            if(!std::isinf(v) && !std::isnan(v))
+                s << v;
+            else
+                s << "\"inf\"";
+            s << ",\"succs\":[";
             bool f = true;
             for(auto& e : el._succssors)
             {

src/SimpleRegressor.h

@@ -25,12 +25,13 @@
 #ifndef SIMPLEREGRESSOR_H
 #define SIMPLEREGRESSOR_H
 
+#include "propts.h"
+#include "structs.h"
+
 #include <limits>
 #include <vector>
 #include <map>
-
-#include "propts.h"
-#include "structs.h"
+#include <iomanip>
 
 namespace prlearn {
 
@@ -73,10 +74,11 @@ namespace prlearn {
             res->_value.cnt() = std::min<size_t>(res->_cnt, options._q_learn_rate);
             res->_cnt += 1;
             res->_value += nval;
-            assert(res->_value._avg >= 0);
+            assert(res->_value.avg() >= 0);
         }
 
         void print(std::ostream& s, size_t tabs, std::map<size_t, size_t>& label_map) const {
+            s << std::setprecision (std::numeric_limits<double>::digits10 + 1);
             for (size_t i = 0; i < tabs; ++i) s << "\t";
             s << "{";
             bool first = true;
@@ -85,7 +87,12 @@ namespace prlearn {
                 first = false;
                 s << "\n";
                 for (size_t t = 0; t < tabs; ++t) s << "\t";
-                s << "\"" << label_map[w._label] << "\" : " << w._value.avg();
+                s << "\"" << label_map[w._label] << "\" : ";
+                auto v = w._value.avg();
+                if(!std::isinf(v) && !std::isnan(v))
+                    s << v;
+                else
+                    s << "\"inf\"";
             }
             s << "\n";
             for (size_t i = 0; i < tabs; ++i) s << "\t";