public static void Main(string[] args)
{
ToolArguments parsedArgs = new ToolArguments(args, "None", new MainClass());
PorterStemmer stemmer = new PorterStemmer();
if (parsedArgs["stem"] != null)
{
Console.WriteLine(parsedArgs["stem"] + " => " + stemmer.stemTerm(parsedArgs["stem"]));
}
if (parsedArgs["freqrows"] != null)
{
DataReader reader = new DataReader(parsedArgs["f"]);
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
TwoTuple <int, int> counts = FrequencyTools.WordCount(parsedArgs["freqrows"], row[1]);
Console.WriteLine(counts.one + "," + counts.two + ",\"" + row[2] + "\"");
}
}
if (parsedArgs["emotion"] != null)
{
ANEWEmotionSensor sensor = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
double[] emotions = sensor.EstimateEmotions(parsedArgs["emotion"]);
for (int ii = 0; ii < (int)ANEWEmotionSensor.Emotions.COUNT; ii++)
{
Console.WriteLine(((ANEWEmotionSensor.Emotions)ii).ToString() + ": " + emotions[ii]);
}
}
if (parsedArgs["emorows"] != null)
{
int rows = 0, valids = 0;
ANEWEmotionSensor sensor = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
DataReader reader = new DataReader(parsedArgs["f"]);
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
rows++;
double[] emotions = sensor.EstimateEmotions(row[1]);
Console.WriteLine("\"" + row[0] + "\"," + emotions[0] + "," + emotions[1] + "," + emotions[2] + "," + emotions[3] + "," + emotions[4] + "," + emotions[5] + "," + emotions[6] + "," + emotions[7] + ",\"" + row[2] + "\"");
if (!double.IsNaN(emotions[0]))
{
valids++;
}
}
}
}
public static void Main(string[] args)
{
ToolArguments parsedArgs = new ToolArguments(args, "None", new MainClass());
PorterStemmer stemmer = new PorterStemmer();
if (parsedArgs["stem"] != null)
{
Console.WriteLine(parsedArgs["stem"] + " => " + stemmer.stemTerm(parsedArgs["stem"]));
}
/*ANEWEmotionSensor sensor2 = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
* for (int rr = 0; rr < sensor2.positiveMatrix.GetLength(0); rr++) {
* for (int cc = 0; cc < sensor2.positiveMatrix.GetLength(1); cc++)
* Console.Write(sensor2.positiveMatrix[rr, cc] + ", ");
* Console.WriteLine(" - ");
* }
* for (int rr = 0; rr < sensor2.negativeMatrix.GetLength(0); rr++) {
* for (int cc = 0; cc < sensor2.negativeMatrix.GetLength(1); cc++)
* Console.Write(sensor2.negativeMatrix[rr, cc] + ", ");
* Console.WriteLine(" - ");
* }
* return;*/
if (parsedArgs["freqrows"] != null)
{
DataReader reader = new DataReader(parsedArgs["f"]);
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
TwoTuple <int, int> counts = FrequencyTools.WordCount(parsedArgs["freqrows"], row[1]);
Console.WriteLine(counts.one + "," + counts.two + ",\"" + row[2] + "\"");
}
}
if (parsedArgs["emotion"] != null)
{
ANEWEmotionSensor sensor = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
double[] emotions = sensor.EstimateEmotions(parsedArgs["emotion"]);
for (int ii = 0; ii < (int)ANEWEmotionSensor.Emotions.COUNT; ii++)
{
Console.WriteLine(((ANEWEmotionSensor.Emotions)ii).ToString() + ": " + emotions[ii]);
}
}
if (parsedArgs["emorows"] != null)
{
int rows = 0, valids = 0;
ANEWEmotionSensor sensor = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
DataReader reader = new DataReader(parsedArgs["f"]);
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
rows++;
double[] emotions = sensor.EstimateEmotions(row[1]);
Console.WriteLine("\"" + row[0] + "\"," + emotions[0] + "," + emotions[1] + "," + emotions[2] + "," + emotions[3] + "," + emotions[4] + "," + emotions[5] + "," + emotions[6] + "," + emotions[7] + ",\"" + row[2] + "\"");
if (!double.IsNaN(emotions[0]))
{
valids++;
}
}
}
if (parsedArgs["eimpute"] != null)
{
ANEWEmotionSensor sensor = new ANEWEmotionSensor("/Users/jrising/projects/virsona/github/data");
// DIAGNOSTIC
/*List<List<string>> rows = new List<List<string>>();
* rows.Add(TwitterUtilities.SplitWords("happy aaaa cccc"));
* rows.Add(TwitterUtilities.SplitWords("sad bbbb cccc"));
*
* IDataSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> inputed = sensor.ImputeEmotionalContent(rows, 1000);
* foreach (KeyValuePair<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> kvp in inputed)
* Console.WriteLine(kvp.Key + ": " + kvp.Value.one.Mean + ", " + kvp.Value.two.Mean + ", " + kvp.Value.three.Mean);*/
bool smallFile = false;
if (smallFile)
{
DataReader reader = new DataReader(parsedArgs["f"]);
List <List <string> > rows = new List <List <string> >();
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
Console.WriteLine(row);
rows.Add(TwitterUtilities.SplitWords(row[10].ToLower()));
}
reader.Close();
/*IDataSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> inputed = sensor.ImputeEmotionalContent(rows, 10);
* double minv = 1, maxv = 0;
* foreach (KeyValuePair<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> kvp in inputed) {
* minv = Math.Min(minv, kvp.Value.one.Mean);
* maxv = Math.Max(maxv, kvp.Value.one.Mean);
* Console.WriteLine(kvp.Key + ": " + kvp.Value.one.Mean + " x " + kvp.Value.one.Variance + ", " + kvp.Value.two.Mean + ", " + kvp.Value.three.Mean);
* }
*
* Console.WriteLine("Min: " + minv + ", Max: " + maxv);*/
sensor.ImputeEmotionalContent(rows, 10, parsedArgs["f"] + "imputed");
}
else
{
sensor.ImputeEmotionalContentFromFile(parsedArgs["f"], 11, 0, parsedArgs["f"].Substring(0, parsedArgs["f"].Length - 4) + "imputed.csv");
}
uint jj = 0;
using (var stream = File.CreateText(parsedArgs["f"] + "result")) {
jj++;
if (jj % 1000 == 0)
{
Console.WriteLine("#" + jj);
}
DataReader reader = new DataReader(parsedArgs["f"]);
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
double[] emotions = sensor.EstimateEmotions(row[11]);
for (int ii = 0; ii < 11; ii++)
{
stream.Write(row[ii] + ",");
}
stream.WriteLine(emotions[0] + "," + emotions[1] + "," + emotions[2] + "," + emotions[3] + "," + emotions[4] + "," + emotions[5] + "," + emotions[6] + "," + emotions[7]);
}
}
}
}