/// <summary>
/// Gets a network based on the given path
/// </summary>
/// <param name="path"></param>
/// <returns></returns>
public Bayesian LoadExistingNetwork(string path)
{
Bayesian bn = new Bayesian();
//gets the object in its text format from the file
string bnJsonString = File.ReadAllText(path);
//converts the text back to the object
bn = JsonConvert.DeserializeObject <Bayesian>(bnJsonString);
return(bn);
}
/// <summary>
/// saves the given network to a txt file
/// </summary>
/// <param name="bn">the network to be saved</param>
/// <returns></returns>
public bool SaveNetworkKnowledge(Bayesian bn)
{
string path;
bool fileSaved = false;
//checks if the file type is included
if (!bn.FileName.EndsWith(".txt"))
{
path = _trainedFilePath + "/" + bn.FileName + ".txt";
}
else
{
path = _trainedFilePath + "/" + bn.FileName;
}
try
{
if (!File.Exists(path))
{
//converts the object to be placed into a file
string bnJsonString = JsonConvert.SerializeObject(bn);
//creates the file
FileStream s = File.Create(path);
s.Close();
//saves the bayesian network to the file
StreamWriter sw = File.AppendText(path);
sw.WriteLine(bnJsonString);
sw.Close();
fileSaved = true;
}
}
catch (Exception e)
{
Debug.WriteLine("Error : " + e);
}
return(fileSaved);
}
/// <summary>
/// The main menu for the program
/// </summary>
public void DisplayMenu()
{
bool displayMenu = true;
string uInput;
do
{
Console.WriteLine("Please Select an Option or press q to quit");
Console.WriteLine("1. Train");
Console.WriteLine("2. Generate A haiku");
Console.WriteLine("q. quit");
uInput = Console.ReadLine();
switch (uInput.ToLower())
{
case "1":
_bn.Train(_frw.LoadTrainingData());
if (_bn.Words == null || _bn.Words.Count == 0)
{
Console.Clear();
Console.WriteLine("\nERROR: No training Data Provided");
Console.ReadKey();
}
SaveNetwork();
break;
case "2":
Console.Clear();
string[] availableNetworks = _frw.TrainedBayesianNetworkNames();
int networkNum = -100;
if (availableNetworks.Count() != 0)
{
//list the already saved networks
Console.WriteLine("Select the Network you'd like to use");
for (int i = 1; i <= availableNetworks.Count(); i++)
{
Console.WriteLine(i + ". " + availableNetworks[i - 1]);
}
bool outOfBounds = true;
//validate the userinput
do
{
uInput = Console.ReadLine();
int.TryParse(uInput, out networkNum);
if ((networkNum > 0) && (networkNum <= availableNetworks.Count()))
{
outOfBounds = false;
}
else
{
Console.WriteLine("invalid input");
}
} while(outOfBounds);
Console.Clear();
Console.WriteLine("Press any key to exit. You're haiku is:");
//TEMP
//for (int i = 0; i < 30; i++)
//{
//setting the network
_bn = _frw.LoadExistingNetwork(availableNetworks[networkNum - 1]);
List <string[]> haiku = _bn.CreateHaiku();
Console.WriteLine();
foreach (string[] line in haiku)
{
Console.WriteLine();
foreach (string word in line)
{
Console.Write(word + " ");
}
}
//}
//TEMP
Console.ReadKey();
}
else
{
Console.WriteLine("ERROR: No trained networks available.");
Console.ReadKey();
}
break;
case "q":
displayMenu = false;
break;
default:
Console.WriteLine("Invalid menu option");
break;
}
Console.Clear();
} while (displayMenu);
}
/// <summary>
/// Instanciates the member variables and allows
/// </summary>
public Menu()
{
_frw = new FileReadWrite();
_bn = new Bayesian();
}
