interface histogram : public screen 
  {
    histogram(char* p,char* options = "");
    histogram(widget* w,char* p,char* options = "");
    virtual ~histogram();   
  
    void sample(double x,double y = 1);     // adds a sample.
  
    ofstream* file(char* fn);     // write samples made to file fn
    void closefile();             // close file fn
   
    void reset();                 // resets internals.
  
    double mean();                // return mean.
    double variance();            // return variance.
    double standarddeviation();   // return standard deviation.
    double sumfrequencies();      // return sum of frequencies
    double minimum();             // return minimum value
    double maximum();             // return maximum value
            
    void postscript(char* fn);    // generate postscript.
  
    friend ostream& operator<<(ostream& os,histogram& h);
  };
  

A histogram can be used when gathering and printing the results of the simulation. The histogram can be printed as a frequency graph, as a cumulative frequency graph and as a table. You can also print the statistics. The printing can be specified in the options parameter by adding the form option (default graph). The constructor takes the path of the widget. The options take the start value (default 0), the width of a column (default 1), the number of columns (default 10), type of histogram (default frequency), output form (default graph), the title (default histogram), the foreground color (default black), the background color (default grey), the width and height (default dependent on the form ((cumulative) frequency graph, table or statistics). Sample takes two double and adjusts the internal data accordingly. X resembles the sample, y the frequency (default 1). If the histogram is of type FREQUENCY the y value is added to the column that x falls in. The y value becomes y times the time since the last entry if the histogram is of type WEIGHTED. In a time series the x value represents time so it is ignored and the y value is added to all columns between the column representing the last entry and the column representing the current time. The method file creates a file fn and writes every sample made in the histogram to this file (the x value on the first new line and the y value on the second new line). It returns the file pointer of the created file. Reset resets the histogram (and its window), as if no samples were recorded. The method postscript writes the window of the histogram object (if created) in postscript format to the specified file. The histogram can be printed to standard output or on a window (if the library runs in HUSH mode) with the cout operator.

    -start <double = 0>
    -columnwidth <double = 1>
    -columns <int = 10>
    -type <frequency,weighted,series>   // default frequency
    -form <graph,cumulative,table,statistics>   // default graph
    -title <string = histogram>
    -foreground <color = black>
    -background <color = grey>
    -width <coord = 100+40*(columns+2), 600, 400> 
    -height <coord = 360, (columns+7)*20, 100> 
           // pre : width/default == height/default
  

  int application::main(kit* tk,int argc,char* argv[])
  {
    simulation* sim = new simulation();
    histogram* h1 = new histogram(".h1","-columnwidth 10 -form graph -title graph");
    histogram* h2 = new histogram(".h2","-columnwidth 10 -form cumulative -title cumulative");
    histogram* h3 = new histogram(".h3","-columnwidth 10 -form table -title table");
    histogram* h4 = new histogram(".h4","-columnwidth 10 -form statistics -title statistics");
    generator* g = new generator(2,1,9000);
    for (int i=0;i<1000;i++)
    {
      double smp = g -> exponential(10);
      h1 -> sample(smp);
      h2 -> sample(smp);
      h3 -> sample(smp);
      h4 -> sample(smp);
    }
    cout << (*h1);
    cout << (*h2);
    cout << (*h3);
    cout << (*h4);
    delete sim;
    delete h1;
    delete h2;
    delete h3;
    delete h4;
    return 0;
  }
  

Four frequency graphs are created and filled with 1000 samples from the exponential distribution. The couts results in a frequency graph, a cumulative frequency graph, a table and a summary.