random gen update

Author: behnamasadi

CMakeLists.txt

@@ -410,6 +410,10 @@ target_link_libraries(default-initialized)
 add_executable(scope_resolution_operator src/scope_resolution_operator.cpp)
 target_link_libraries(scope_resolution_operator)
 
+add_executable(random_number_generation src/random_number_generation.cpp)
+target_link_libraries(random_number_generation)
+
+
 
 #set(CMAKE_CXX_FLAGS "-Wall -Wextra")
 #set(CMAKE_CXX_FLAGS_DEBUG "-g")

docs/random_number.md

@@ -1,6 +1,6 @@
 # Pseudo-random number generation
 
-`int std::rand();`: Returns a pseudo-random integral value between `0` and `RAND_MAX` (both numbers included). 
+`int std::rand()`: returns a pseudo-random integral value between `0` and `RAND_MAX` (both numbers included). 
 `RAND_MAX` (macro constant) is the maximum possible value generated by `std::rand` 
 
 `std::srand()` seeds the  `rand()`. If `rand()` is used before any calls to `std::srand( unsigned seed)`, `rand()` behaves as if it was seeded with `std::srand(1)` and each time `rand()` is seeded with `std::srand()`, it must produce the same sequence of values on successive calls. to generate random number between 0 and your upperbound just use `rand() % upperbound`.
@@ -20,16 +20,11 @@ std::cout<<(rand() % upperbound) <<std::endl;
 ```
 
 
-# Ranndom Generator From Specific Distribution
+# Random Generator From Specific Distribution
 
 ```cpp
-
-#include <random>
-#include <map>
-
-
 int rangeFrom=0;
-int rangeTo=1
+int rangeTo=1;
 
 std::random_device rand_dev;
 std::mt19937 generator(rand_dev());
@@ -68,142 +63,6 @@ weibull_distribution;
 
 # Histogram of Distribution 
 
-```cpp
-#include <random>
-#include <map>
-#include <iomanip>
-
-template < typename T>
-void calculatePrintHistogram(T d, std::mt19937 gen, int number_of_samples = 1000000, int histogram_bin_size = 4000)
-{
-	std::map<int, int> hist{};
-	
-
-	for (int n = 0; n < number_of_samples; ++n)
-	{
-		++hist[std::round(d(gen))];
-	}
-	for (auto p : hist)
-	{
-		std::cout << std::setw(2) << p.first << ' ' << std::string(p.second / histogram_bin_size, '*') << '\n';
-	}
-
-}
-
-int main() 
-{
-
-	enum Distributions
-	{
-		bernoulli_distribution,
-		exponential_distribution,
-		gamma_distribution,
-		normal_distribution,
-		poisson_distribution,
-		uniform_real_distribution
-	};
-
-
-	int number_of_samples = 1000000;
-	int histogram_bin_size = 2500;
-
-
-	std::random_device rd{};
-	std::mt19937 gen{ rd() };
-
-	/*parameters for normal_distribution*/
-	double mean = 5;
-	double sigma = 3;
-	
-
-	/*parameters for uniform_real_distribution*/
-	double rangeFrom = 0;
-	double rangeTo = 20;
-
-	/*parameters for bernoulli_distribution
-	give "true" 1/4 of the time, give "false" 3/4 of the time*/
-	double chance_of_wining = 0.25;
-	
-
-	/*parameters for poisson_distribution
-	if an event occurs 4 times a minute on average
-	how often is it that it occurs n times in one minute?*/
-	int frequency_of_occurance_in_a_minute_on_average = 4;
-	
-
-	/* parameters for exponential_distribution
-	if particles decay once per second on average,
-	how much time, in seconds, until the next one?*/
-	int decay_once_per_second_on_average = 1;
-
-
-	/* 
-	A gamma distribution with alpha = 1, and beta = 2
-	approximates an exponential distribution.
-	*/
-	int alpha = 1;
-	int  beta = 2;
-
-
-	
-	for (int it = bernoulli_distribution; it != uniform_real_distribution; it++)
-	{
-		Distributions distribution = static_cast<Distributions>(it);
-
-		switch (distribution)
-		{
-		case bernoulli_distribution: 
-		{
-			std::bernoulli_distribution d(chance_of_wining);
-			std::cout<<"------------------------bernoulli distribution------------------------" <<std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-		case exponential_distribution:
-		{
-			std::exponential_distribution<> d(decay_once_per_second_on_average);
-			std::cout << "------------------------exponential distribution------------------------" << std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-		case gamma_distribution: 
-		{
-			std::gamma_distribution<> d(alpha, beta);
-			std::cout << "------------------------gamma distribution------------------------" << std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-		case normal_distribution: 
-		{
-			std::normal_distribution<> d{ mean, sigma };
-			std::cout << "------------------------normal distribution------------------------" << std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-
-		case poisson_distribution: 
-		{
-			std::poisson_distribution<> d(frequency_of_occurance_in_a_minute_on_average);
-			std::cout << "------------------------poisson distribution------------------------" << std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-
-		case uniform_real_distribution: 
-		{
-			std::uniform_real_distribution<double> d(rangeFrom, rangeTo);
-			std::cout << "------------------------uniform real distribution------------------------" << std::endl;
-			calculatePrintHistogram(d, gen);
-		}
-			break;
-
-		default:
-			break;
-		}
-	}
-```
-output is:
-
 ```
 ------------------------bernoulli distribution------------------------
  0 *******************************************************************************************************************************************************************************************
@@ -216,13 +75,6 @@ output is:
  4 ****
  5 *
  6
- 7
- 8
- 9
-10
-11
-12
-13
 14
 ------------------------gamma distribution------------------------
  0 *******************************************************
@@ -237,22 +89,6 @@ output is:
  9 *
 10
 11
-12
-13
-14
-15
-16
-17
-18
-19
-20
-21
-22
-23
-24
-25
-26
-27
 ------------------------normal distribution------------------------
 -10
 -9
@@ -300,11 +136,8 @@ output is:
 11
 12
 13
-14
-15
-16
-17
 
-```
 
+```
+[code](../src/random_number_generation.cpp)