static void Main(string[] args)
{
DataTable meta_table = createMetaTable();
DataTable distractors_video_table = createDistractorVideoTable();
DataTable distractors_game_table = createDistractorGameTable();
DataTable deaths_table = createDeathsTable();
var QuestionnaireScores = new List <double>();
var video_sound_distractor_percentages = new List <double>();
var video_image_distractor_percentages = new List <double>();
var sound_distractor_percentages = new List <double>();
var image_distractor_percentages = new List <double>();
var avgdistractors = new List <double>();
var aps = new List <double>();
var summs = new List <double>();
var exptype = new List <double>();
var skill_lvl = new List <double>();
var death_remembered_percentages = new List <double>();
var underskill_scores = new List <double>();
var overskill_scores = new List <double>();
var matched_scores = new List <double>();
var focused_scores = new List <double>();
var average_scores = new List <double>();
var detached_scores = new List <double>();
var bronze_scores = new List <double>();
var goldplus_scores = new List <double>();
var bps = new List <double[]>();
int participantID = 0;
foreach (String uname in usernames)
{
participantID++;
Experiment exp1 = new Experiment(uname);
Console.Out.WriteLine("User: "******"Skill Level: " + exp1.skill_level);
Console.Out.WriteLine("Play Style: " + exp1.style);
Console.Out.WriteLine("Experiment Type: " + exp1.exp_type);
Console.Out.WriteLine("Questionnaire Score: " + exp1.questionnaire_score);
Console.Out.WriteLine("number of distractors: ");
Console.Out.WriteLine(exp1.video_image_distractor_no + " " + exp1.video_sound_distractor_no + " " + exp1.game_sound_distractor_no + " " + exp1.game_image_distractor_no);
Console.Out.WriteLine("distractor remembering percentages:");
Console.Out.WriteLine("video sound distractors: " + exp1.video_sound_distractor_proc);
Console.Out.WriteLine("video image distractors: " + exp1.video_image_distractor_proc);
Console.Out.WriteLine("game sound distractors: " + exp1.game_sound_distractor_proc);
Console.Out.WriteLine("game image distractors: " + exp1.game_image_distractor_proc);
Console.Out.WriteLine("");
Console.Out.WriteLine("");
QuestionnaireScores.Add(exp1.questionnaire_score);
video_sound_distractor_percentages.Add(exp1.video_sound_distractor_proc);
video_image_distractor_percentages.Add(exp1.video_image_distractor_proc);
sound_distractor_percentages.Add(exp1.game_sound_distractor_proc);
image_distractor_percentages.Add(exp1.game_image_distractor_proc);
death_remembered_percentages.Add(exp1.death_remember_proc);
double video_avg_proc = (exp1.video_sound_distractor_proc + exp1.video_image_distractor_proc) / 2;
double avg_proc = (exp1.game_sound_distractor_proc + exp1.game_image_distractor_proc) / 2;
avgdistractors.Add(avg_proc);
aps.Add(exp1.moves_per_sec);
summs.Add(exp1.summ_no);
exptype.Add((int)exp1.exp_type);
skill_lvl.Add((int)exp1.skill_level);
if (exp1.exp_type == Experiment_Types.UnderSkill)
{
underskill_scores.Add(exp1.questionnaire_score);
}
else if (exp1.exp_type == Experiment_Types.Matched)
{
matched_scores.Add(exp1.questionnaire_score);
}
else if (exp1.exp_type == Experiment_Types.OverSkill)
{
overskill_scores.Add(exp1.questionnaire_score);
}
if (exp1.style == PlayStyle.Focused)
{
focused_scores.Add(exp1.questionnaire_score);
}
else if (exp1.style == PlayStyle.Average)
{
average_scores.Add(exp1.questionnaire_score);
}
else if (exp1.style == PlayStyle.Detached)
{
detached_scores.Add(exp1.questionnaire_score);
}
if (exp1.skill_level == Ranks.Bronze)
{
bronze_scores.Add(exp1.questionnaire_score);
}
else
{
goldplus_scores.Add(exp1.questionnaire_score);
}
foreach (var item in exp1.game_bandpower)
{
bps.Add(item);
}
foreach (var item in exp1.video_bandpower)
{
bps.Add(item);
}
// KMeans tr = new KMeans(4);
// tr.Learn(exp1.game_bandpower);
// Console.Write(tr.ToString());
// Console.ReadKey();
meta_table.Rows.Add(participantID, exp1.skill_level, exp1.style, exp1.exp_type, exp1.questionnaire_score);
deaths_table.Rows.Add(participantID, exp1.death_no, exp1.actual_death_no, exp1.death_remember_proc);
distractors_video_table.Rows.Add(participantID, exp1.video_sound_distractor_proc, exp1.video_image_distractor_proc, video_avg_proc);
distractors_game_table.Rows.Add(participantID, exp1.game_sound_distractor_proc, exp1.game_image_distractor_proc, avg_proc);
}
var test = new PearsonCorrelation();
test.Similarity(QuestionnaireScores.ToArray(), sound_distractor_percentages.ToArray());
Console.Out.WriteLine("accord.net similarity value: ");
Console.Out.WriteLine(test.Similarity(QuestionnaireScores.ToArray(), sound_distractor_percentages.ToArray()));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - sound distractor rememberabce");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, sound_distractor_percentages));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - image distractor rememberabce");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, image_distractor_percentages));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - overall distractor rememberabce");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, avgdistractors));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - moves per second");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, aps));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - number of summ spells");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, summs));
Console.Out.WriteLine("");
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - skill");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, skill_lvl));
Console.Out.WriteLine("");
Console.Out.WriteLine("correlation questionnaire - death rememberabce");
Console.Out.WriteLine(Correlation.Pearson(QuestionnaireScores, death_remembered_percentages));
Console.Out.WriteLine("");
var scatter_values = new List <double>();
scatter_values.AddRange(video_sound_distractor_percentages);
scatter_values.AddRange(sound_distractor_percentages);
double[][] samples = { underskill_scores.ToArray(),
matched_scores.ToArray(),
overskill_scores.ToArray() };
OneWayAnova anova = new OneWayAnova(samples);
// DataGridBox.Show(anova.Table);
//Console.ReadKey();
double[][] style_samples = { focused_scores.ToArray(),
detached_scores.ToArray(),
average_scores.ToArray() };
OneWayAnova style_anova = new OneWayAnova(style_samples);
// DataGridBox.Show(style_anova.Table);
// Console.ReadKey();
double[][] skill_samples = { bronze_scores.ToArray(),
goldplus_scores.ToArray() };
OneWayAnova skill_anova = new OneWayAnova(skill_samples);
//DataGridBox.Show(skill_anova.Table);
//Console.ReadKey();
String meta_table_file = "D:\\Projects\\Conference Paper\\Tables\\meta_table.xml";
String distractors_video_table_file = "D:\\Projects\\Conference Paper\\Tables\\distractors_video_table.xml";
String distractors_game_table_file = "D:\\Projects\\Conference Paper\\Tables\\distractors_game_table.xml";
String deaths_table_file = "D:\\Projects\\Conference Paper\\Tables\\deaths_table.xml";
StreamWriter metaStreamWriter = new StreamWriter(meta_table_file);
StreamWriter distractorsVideoStreamWriter = new StreamWriter(distractors_video_table_file);
StreamWriter distractorsGameStreamWriter = new StreamWriter(distractors_game_table_file);
StreamWriter deathsStreamWriter = new StreamWriter(deaths_table_file);
meta_table.WriteXml(metaStreamWriter);
distractors_video_table.WriteXml(distractorsVideoStreamWriter);
distractors_game_table.WriteXml(distractorsGameStreamWriter);
deaths_table.WriteXml(deathsStreamWriter);
Console.ReadKey();
}
private void Ok_Click(object sender, RoutedEventArgs e)
{
var format = new NumberFormatInfo();
format.NegativeSign = "-";
var valuesCol1 = (from row in mainWindow.gridData.AsEnumerable()
select Convert.ToDouble(ConvertString(row.Field <string>(mainWindow.gridData.Columns[comboBoxCol1.SelectedItem.ToString()].ColumnName)), format)).ToArray();
var valuesCol2 = (from row in mainWindow.gridData.AsEnumerable()
select Convert.ToDouble(ConvertString(row.Field <string>(mainWindow.gridData.Columns[comboBoxCol2.SelectedItem.ToString()].ColumnName)), format)).ToArray();
if (similarityMeasures.SelectedItem.ToString() == "Jaccard")
{
var jaccard = new Jaccard();
textBlock.Text += "\nPodobieństwo miary Jaccard pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + jaccard.Similarity(valuesCol1, valuesCol2).ToString();
}
else if (similarityMeasures.SelectedItem.ToString() == "Korelacja Pearsona")
{
var pearsonCorrelation = new PearsonCorrelation();
textBlock.Text += "\nPodobieństwo miary Korelacja Pearsona pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + pearsonCorrelation.Similarity(valuesCol1, valuesCol2).ToString();
}
else if (similarityMeasures.SelectedItem.ToString() == "Cosinus")
{
var cosine = new Cosine();
textBlock.Text += "\nPodobieństwo miary Cosinus pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + cosine.Similarity(valuesCol1, valuesCol2).ToString();
}
}