protected void PlaceAnovaTable(OneWayAnova anova, string dv, string iv, int numdigits)
{
var t = anova.Table;
ASPxGridView gv = new ASPxGridView();
gv.SettingsText.Title = String.Format("ANOVA: <b>{0}</b> by {1}", dv, iv);
gv.Settings.ShowTitlePanel = true;
gv.DataSource = anova.Table;
gv.DataBind();
List <string> keepAsInt = new List <string> {
"DegreesOfFreedom"
};
foreach (GridViewDataColumn col in gv.Columns)
{
string name = col.FieldName;
if (keepAsInt.Contains(name))
{
col.PropertiesEdit.DisplayFormatString = String.Format("F0");
}
else
{
col.PropertiesEdit.DisplayFormatString = String.Format("F{0}", numdigits);
}
string caption = name;
if (name == "DegreesOfFreedom")
{
caption = "DF";
}
else if (name == "SumOfSquares")
{
caption = "SS";
}
else if (name == "MeanSquares")
{
caption = "MS";
}
else if (name == "Significance")
{
caption = "p-value";
}
else if (name == "Statistic")
{
caption = "F";
}
col.Caption = caption;
}
//panel.Controls.Add(gv);
}
protected override void EndProcessing()
{
var groups = _data.GroupBy(CategoryName);
var test = new OneWayAnova(groups.ToDoubleJaggedArrayOf(ValueName));
test.FTest.Size = Size;
WriteObject(test.Table);
}
public void OneWayAnovaConstructorTest2()
{
// Test for unequal sample sizes
double[][] samples =
{
new double[] { 6, 8, 4, 5 },
new double[] { 8, 12, 9,11, 6, 8 },
new double[] { 13, 9, 11,8, 12 },
};
double mean1 = samples[0].Mean();
double dev1 = samples[0].StandardDeviation();
double mean2 = samples[1].Mean();
double dev2 = samples[1].StandardDeviation();
double mean3 = samples[2].Mean();
double dev3 = samples[2].StandardDeviation();
OneWayAnova anova = new OneWayAnova(samples);
Assert.AreEqual(anova.Table.Count, 3);
Assert.AreEqual("Between-Groups", anova.Table[0].Source);
Assert.AreEqual(53.383333333333326, anova.Table[0].SumOfSquares); // Sb
Assert.AreEqual(2, anova.Table[0].DegreesOfFreedom); // df
Assert.AreEqual(26.691666666666663, anova.Table[0].MeanSquares); // MSb
Assert.AreEqual(6.4124124124124107, anova.Table[0].Statistic);
Assert.AreEqual(0.012757639347451104, anova.Table[0].Significance.PValue);
Assert.IsFalse(double.IsNaN(anova.Table[0].Significance.PValue));
Assert.AreEqual("Within-Groups", anova.Table[1].Source);
Assert.AreEqual(49.95000000000001, anova.Table[1].SumOfSquares); // Sw
Assert.AreEqual(12, anova.Table[1].DegreesOfFreedom); // df
Assert.AreEqual(4.1625000000000005, anova.Table[1].MeanSquares); // MSw
Assert.IsNull(anova.Table[1].Statistic);
Assert.IsNull(anova.Table[1].Significance);
Assert.AreEqual("Total", anova.Table[2].Source);
Assert.AreEqual(103.33333333333334, anova.Table[2].SumOfSquares); // Sw
Assert.AreEqual(14, anova.Table[2].DegreesOfFreedom); // df
Assert.IsNull(anova.Table[2].Statistic);
Assert.IsNull(anova.Table[2].Significance);
}
public void OneWayAnovaConstructorTest()
{
// Example from http://en.wikipedia.org/wiki/F_test
double[][] samples =
{
new double[] { 6, 8, 4, 5, 3, 4 },
new double[] { 8, 12, 9, 11, 6, 8 },
new double[] { 13, 9, 11, 8, 7, 12 },
};
OneWayAnova target = new OneWayAnova(samples);
Assert.AreEqual(target.Table.Count, 3);
Assert.AreEqual("Between-Groups", target.Table[0].Source);
Assert.AreEqual(84, target.Table[0].SumOfSquares); // Sb
Assert.AreEqual(2, target.Table[0].DegreesOfFreedom); // df
Assert.AreEqual(42, target.Table[0].MeanSquares); // MSb
Assert.AreEqual(9.264705882352942, target.Table[0].Statistic);
Assert.AreEqual(0.0023987773293928649, target.Table[0].Significance.PValue);
Assert.AreEqual("Within-Groups", target.Table[1].Source);
Assert.AreEqual(68, target.Table[1].SumOfSquares); // Sw
Assert.AreEqual(15, target.Table[1].DegreesOfFreedom); // df
Assert.AreEqual(4.5333333333333332, target.Table[1].MeanSquares); // MSw
Assert.IsNull(target.Table[1].Statistic);
Assert.IsNull(target.Table[1].Significance);
Assert.AreEqual("Total", target.Table[2].Source);
Assert.AreEqual(152, target.Table[2].SumOfSquares); // Sw
Assert.AreEqual(53, target.Table[2].DegreesOfFreedom); // df
// Assert.IsNull(target.Table[2].MeanSquares); // MSw
Assert.IsNull(target.Table[2].Statistic);
Assert.IsNull(target.Table[2].Significance);
}
public void OneWayAnovaConstructorTest()
{
// The following is the same example given in Wikipedia's page for the
// F-Test [1]. Suppose one would like to test the effect of three levels
// of a fertilizer on plant growth.
// To achieve this goal, an experimenter has divided a set of 18 plants on
// three groups, 6 plants each. Each group has received different levels of
// the fertilizer under question.
// After some months, the experimenter registers the growth for each plant.
double[][] samples =
{
new double[] { 6, 8, 4, 5, 3, 4 }, // records for the first group
new double[] { 8, 12, 9, 11, 6, 8 }, // records for the second group
new double[] { 13, 9, 11, 8, 7, 12 }, // records for the third group
};
// Now, he would like to test whether the different fertilizer levels has
// indeed caused any effect in plant growth. In other words, he would like
// to test if the three groups are indeed significantly different.
// To do it, he runs an ANOVA test:
OneWayAnova anova = new OneWayAnova(samples);
// After the Anova object has been created, one can display its findings
// in the form of a standard ANOVA table by binding anova.Table to a
// DataGridView or any other display object supporting data binding. To
// illustrate, we could use Accord.NET's DataGridBox to inspect the
// table's contents.
// Accord.Controls.DataGridBox.Show(anova.Table);
// The p-level for the analysis is about 0.002, meaning the test is
// significant at the 5% significance level. The experimenter would
// thus reject the null hypothesis, concluding there is a strong
// evidence that the three groups are indeed different. Assuming the
// experiment was correctly controlled, this would be an indication
// that the fertilizer does indeed affect plant growth.
// [1] http://en.wikipedia.org/wiki/F_test
Assert.AreEqual(anova.Table.Count, 3);
Assert.AreEqual("Between-Groups", anova.Table[0].Source);
Assert.AreEqual(84, anova.Table[0].SumOfSquares); // Sb
Assert.AreEqual(2, anova.Table[0].DegreesOfFreedom); // df
Assert.AreEqual(42, anova.Table[0].MeanSquares); // MSb
Assert.AreEqual(9.264705882352942, anova.Table[0].Statistic);
Assert.AreEqual(0.0023987773293928649, anova.Table[0].Significance.PValue, 1e-16);
Assert.IsFalse(double.IsNaN(anova.Table[0].Significance.PValue));
Assert.AreEqual("Within-Groups", anova.Table[1].Source);
Assert.AreEqual(68, anova.Table[1].SumOfSquares); // Sw
Assert.AreEqual(15, anova.Table[1].DegreesOfFreedom); // df
Assert.AreEqual(4.5333333333333332, anova.Table[1].MeanSquares); // MSw
Assert.IsNull(anova.Table[1].Statistic);
Assert.IsNull(anova.Table[1].Significance);
Assert.AreEqual("Total", anova.Table[2].Source);
Assert.AreEqual(152, anova.Table[2].SumOfSquares); // Sw
Assert.AreEqual(17, anova.Table[2].DegreesOfFreedom); // df
Assert.IsNull(anova.Table[2].Statistic);
Assert.IsNull(anova.Table[2].Significance);
}
protected void PlaceAnovaTable(OneWayAnova anova, string dv, string iv)
{
PlaceAnovaTable(anova, dv, iv, 4);
}
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();
}
