private void button1_Click(object sender, EventArgs e)
{
listBox1.Items.Clear();
var itm = new _song_profile("", "");
itm.MakeSnaps((int)nUD2.Value, (int)nUD.Value, @"mp3\\diskord.mp3", (int)nUD3.Value);
itm.CalcInternalCorrels();
var itm2 = new _song_profile("", "");
itm2.MakeSnaps((int)nUD2.Value, (int)nUD.Value, @"mp3\\diskord2.mp3", (int)nUD3.Value);
itm2.CalcInternalCorrels();
itm.snap_log10_energy = Normalize(itm.snap_log10_energy);
itm2.snap_log10_energy = Normalize(itm2.snap_log10_energy);
listBox1.Items.Add("convoluted histogram value = " + HistogramConv(itm, itm2, 0.001));
}
private void button3_Click(object sender, EventArgs e)
{
if (MessageBox.Show("Are you sure want to (re)create the database?", "Question", MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.No)
return;
listBox1.Items.Clear();
var fll = MakeFilesList(@textBox1.Text);
var fl = fll.OrderBy(t => Path.GetFileName(t).Length.ToString()).ToList();
listBox1.Items.Add("Found files: " + fl.Count);
var db = new SQLiteConnection();
var cmd = db.CreateCommand();
try
{
db.ConnectionString = "Data Source=test.db;";
db.Open();
//cmd.CommandText = "DROP TABLE IF EXISTS MAIN;"; cmd.ExecuteNonQuery();
//cmd.CommandText = "DROP TABLE IF EXISTS STATS;"; cmd.ExecuteNonQuery();
cmd.CommandText = "CREATE TABLE MAIN (id int, name string, path string);"; cmd.ExecuteNonQuery();
cmd.CommandText = "CREATE TABLE STATS (id int, statname string, statparam1 int, statparam2 int, statvalue float);"; cmd.ExecuteNonQuery();
}
catch
{
MessageBox.Show("Something has gone wrong with the database");
}
SQLiteParameter myparam1 = new SQLiteParameter();
SQLiteParameter myparam2 = new SQLiteParameter();
SQLiteParameter myparam3 = new SQLiteParameter();
SQLiteParameter myparam2_1 = new SQLiteParameter();
SQLiteParameter myparam2_2 = new SQLiteParameter();
SQLiteParameter myparam2_3 = new SQLiteParameter();
SQLiteParameter myparam2_4 = new SQLiteParameter();
SQLiteParameter myparam2_5 = new SQLiteParameter();
List<_song_profile> splist = new List<_song_profile>();
int s_count = 0;
PB1.Maximum = fl.Count;
PB1.Minimum = 0;
foreach (var f in fl)
{
//var transaction = db.BeginTransaction();
try
{
if (s_count % 50 == 0)
{
listBox1.Items.Clear();
listBox1.Items.Add("Items done: " + s_count + " of " + fl.Count);
}
var itm = new _song_profile(Path.GetFileName(f), f);
if (!itm.MakeSnaps((int)nUD2.Value, (int)nUD.Value, f, (int)nUD3.Value))
{
listBox1.Items.Add("![" + s_count + "]! Cannot make snapshots for " + itm.path);
s_count++;
continue;
}
//itm.CalcInternalCorrels();
itm.MakeDownscaledSnaps((int)nUD4.Value);
//itm.MakeDownscaledSnaps2((int)nUD4.Value);
var d = CalcAllStats(itm);
listBox1.Items.Add("[" + s_count + "] " + Path.GetFileName(itm.path));
cmd.CommandText = "BEGIN TRANSACTION;";
cmd.ExecuteNonQuery();
foreach (var di in d)
{
cmd.CommandText = "INSERT INTO STATS VALUES (@id, @statname, @statparam1, @statparam2, @statvalue);";
myparam2_1.ParameterName = "@id";
myparam2_2.ParameterName = "@statname";
myparam2_3.ParameterName = "@statparam1";
myparam2_4.ParameterName = "@statparam2";
myparam2_5.ParameterName = "@statvalue";
myparam2_1.Value = s_count;
myparam2_2.Value = di.Key;
myparam2_3.Value = 0;
myparam2_4.Value = 0;
myparam2_5.Value = di.Value;
cmd.Parameters.Add(myparam2_1); cmd.Parameters.Add(myparam2_2); cmd.Parameters.Add(myparam2_3);
cmd.Parameters.Add(myparam2_4); cmd.Parameters.Add(myparam2_5);
cmd.ExecuteNonQuery();
}
//splist.Add(itm);
cmd.CommandText = "INSERT INTO MAIN VALUES (@id, @name, @path);";
myparam1.ParameterName = "@id";
myparam2.ParameterName = "@name";
myparam3.ParameterName = "@path";
myparam1.Value = s_count;
myparam2.Value = itm.name;
myparam3.Value = itm.path;
cmd.Parameters.Add(myparam1);
cmd.Parameters.Add(myparam2);
cmd.Parameters.Add(myparam3);
cmd.ExecuteNonQuery();
PB1.Value = s_count;
Application.DoEvents();
//transaction.Commit();
cmd.CommandText = "COMMIT;";
cmd.ExecuteNonQuery();
s_count++;
}
catch
{
continue;
}
}
db.Close();
DBPostProcess("test.db");
/*
var dct = new Dictionary<string, double>();
for (int i = 0; i < splist.Count; i++)
{
dct.Add(splist[i].path, VecDiff(splist[0].scalar_stats.Values.ToList(), splist[i].scalar_stats.Values.ToList()));
}
dct.OrderBy(t => t.Value);
dct.ToList().OrderBy(t => t.Value).ToList().ForEach(t => listBox1.Items.Add(t.Key + " ---> [" + t.Value + "]"));
*/
/*************************************************************************
k-means++ clusterization
INPUT PARAMETERS:
XY - dataset, array [0..NPoints-1,0..NVars-1].
NPoints - dataset size, NPoints>=K
NVars - number of variables, NVars>=1
K - desired number of clusters, K>=1
Restarts - number of restarts, Restarts>=1
OUTPUT PARAMETERS:
Info - return code:
* -3, if task is degenerate (number of distinct points is
less than K)
* -1, if incorrect NPoints/NFeatures/K/Restarts was passed
* 1, if subroutine finished successfully
C - array[0..NVars-1,0..K-1].matrix whose columns store
cluster's centers
XYC - array[NPoints], which contains cluster indexes
*************************************************************************/
/*
int NPoints = splist.Count;
int NVars = splist[0].scalar_stats.Count;
int K = (int)Math.Sqrt(NPoints);
int Restarts = 5;
int Info = 0;
var C = new double[NVars, K];
var XYC = new int[NPoints];
var XY = new double[NPoints, NVars];
var _XY = splist[0].scalar_stats.Values.ToArray();
for (int i = 0; i < NPoints; i++)
for (int j = 0; j < NVars; j++)
XY[i, j] = splist[i].scalar_stats.Values.ToArray()[j];
alglib.kmeansgenerate(
XY,
NPoints,
NVars,
K,
Restarts,
out Info,
out C,
out XYC);
Info++;
Application.DoEvents();
for (int i = 0; i < splist.Count; i++)
{
listBox1.Items.Add(Path.GetFileName(splist[i].path) + " -> cluster # " + XYC[i]);
}
*/
/*foreach (var itm in splist)
{
var s1 = new List<double>();
var s2 = new List<double>();
var s3 = new List<double>();
foreach (var itm2 in splist)
{
/*listBox1.Items.Add(Path.GetFileName(itm.path) + " vs " + Path.GetFileName(itm2.path) +
"cross_energy_correl = " + Correl(itm.snap_log10_energy, itm2.snap_log10_energy, itm.snap_log10_energy.Average(), itm2.snap_log10_energy.Average()) + " " +
"cross_energy_diff = " + VecDiff(itm.snap_log10_energy, itm2.snap_log10_energy) + " " +
"convoluted histogram value = " + HistogramConv(itm, itm2, 0.001)
);*/
//s1.Add(Correl(itm.snap_log10_energy, itm2.snap_log10_energy, itm.snap_log10_energy.Average(), itm2.snap_log10_energy.Average()));
//s2.Add(1 / Math.Log10(VecDiff(itm.snap_log10_energy, itm2.snap_log10_energy)));
//s3.Add(HistogramConv(itm, itm2, 0.001));
/*s1.Add(0);
s2.Add(0);
s3.Add(0);
}
sp_CED.Add(s1);
sp_CEC.Add(s2);
sp_CHV.Add(s3);
}*/
/*List<double> likelihood = new List<double>();
for (int i = 0; i < splist.Count; i++)
{
double lh = 0;
//listBox1.Items.Add(Path.GetFileName(splist[i].path) + ": " + (int)(100*sp_ASC[i]) + " " + (int)(100*sp_ASSC[i]) + " " + (int)(10*sp_ED[i]));
for (int j = 0; j < splist.Count; j++)
{
lh =
sp_ASC[i] * sp_ASC[j] +
sp_ASSC[i] * sp_ASSC[j] +
sp_ED[i] * sp_ED[j] +
sp_CED[i][j] + sp_CEC[i][j] + sp_CHV[i][j]
;
likelihood.Add(lh);
listBox1.Items.Add((int)(100*lh) + " : " + Path.GetFileName(splist[i].path) + " " + Path.GetFileName(splist[j].path));
}
//listBox1.Items.Add("----->" + (int)(100*sp_CED[i][j]) + " " + (int)(100*sp_CEC[i][j]) + " " + (int)(100*sp_CHV[i][j]) + "; " + Path.GetFileName(splist[j].path));
}*/
}
private void button1_Click(object sender, EventArgs e)
{
listBox1.Items.Clear();
var itm = new _song_profile("", "");
itm.MakeSnaps((int)nUD2.Value, (int)nUD.Value, @"mp3\\diskord.mp3", (int)nUD3.Value);
itm.CalcInternalCorrels();
var itm2 = new _song_profile("", "");
itm2.MakeSnaps((int)nUD2.Value, (int)nUD.Value, @"mp3\\diskord2.mp3", (int)nUD3.Value);
itm2.CalcInternalCorrels();
itm.snap_log10_energy = Normalize(itm.snap_log10_energy);
itm2.snap_log10_energy = Normalize(itm2.snap_log10_energy);
listBox1.Items.Add("convoluted histogram value = " + HistogramConv(itm, itm2, 0.001));
}
private void button3_Click(object sender, EventArgs e)
{
if (MessageBox.Show("Are you sure want to (re)create the database?", "Question", MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.No)
{
return;
}
listBox1.Items.Clear();
var fll = MakeFilesList(@textBox1.Text);
var fl = fll.OrderBy(t => Path.GetFileName(t).Length.ToString()).ToList();
listBox1.Items.Add("Found files: " + fl.Count);
var db = new SQLiteConnection();
var cmd = db.CreateCommand();
try
{
db.ConnectionString = "Data Source=test.db;";
db.Open();
//cmd.CommandText = "DROP TABLE IF EXISTS MAIN;"; cmd.ExecuteNonQuery();
//cmd.CommandText = "DROP TABLE IF EXISTS STATS;"; cmd.ExecuteNonQuery();
cmd.CommandText = "CREATE TABLE MAIN (id int, name string, path string);"; cmd.ExecuteNonQuery();
cmd.CommandText = "CREATE TABLE STATS (id int, statname string, statparam1 int, statparam2 int, statvalue float);"; cmd.ExecuteNonQuery();
}
catch
{
MessageBox.Show("Something has gone wrong with the database");
}
SQLiteParameter myparam1 = new SQLiteParameter();
SQLiteParameter myparam2 = new SQLiteParameter();
SQLiteParameter myparam3 = new SQLiteParameter();
SQLiteParameter myparam2_1 = new SQLiteParameter();
SQLiteParameter myparam2_2 = new SQLiteParameter();
SQLiteParameter myparam2_3 = new SQLiteParameter();
SQLiteParameter myparam2_4 = new SQLiteParameter();
SQLiteParameter myparam2_5 = new SQLiteParameter();
List <_song_profile> splist = new List <_song_profile>();
int s_count = 0;
PB1.Maximum = fl.Count;
PB1.Minimum = 0;
foreach (var f in fl)
{
//var transaction = db.BeginTransaction();
try
{
if (s_count % 50 == 0)
{
listBox1.Items.Clear();
listBox1.Items.Add("Items done: " + s_count + " of " + fl.Count);
}
var itm = new _song_profile(Path.GetFileName(f), f);
if (!itm.MakeSnaps((int)nUD2.Value, (int)nUD.Value, f, (int)nUD3.Value))
{
listBox1.Items.Add("![" + s_count + "]! Cannot make snapshots for " + itm.path);
s_count++;
continue;
}
//itm.CalcInternalCorrels();
itm.MakeDownscaledSnaps((int)nUD4.Value);
//itm.MakeDownscaledSnaps2((int)nUD4.Value);
var d = CalcAllStats(itm);
listBox1.Items.Add("[" + s_count + "] " + Path.GetFileName(itm.path));
cmd.CommandText = "BEGIN TRANSACTION;";
cmd.ExecuteNonQuery();
foreach (var di in d)
{
cmd.CommandText = "INSERT INTO STATS VALUES (@id, @statname, @statparam1, @statparam2, @statvalue);";
myparam2_1.ParameterName = "@id";
myparam2_2.ParameterName = "@statname";
myparam2_3.ParameterName = "@statparam1";
myparam2_4.ParameterName = "@statparam2";
myparam2_5.ParameterName = "@statvalue";
myparam2_1.Value = s_count;
myparam2_2.Value = di.Key;
myparam2_3.Value = 0;
myparam2_4.Value = 0;
myparam2_5.Value = di.Value;
cmd.Parameters.Add(myparam2_1); cmd.Parameters.Add(myparam2_2); cmd.Parameters.Add(myparam2_3);
cmd.Parameters.Add(myparam2_4); cmd.Parameters.Add(myparam2_5);
cmd.ExecuteNonQuery();
}
//splist.Add(itm);
cmd.CommandText = "INSERT INTO MAIN VALUES (@id, @name, @path);";
myparam1.ParameterName = "@id";
myparam2.ParameterName = "@name";
myparam3.ParameterName = "@path";
myparam1.Value = s_count;
myparam2.Value = itm.name;
myparam3.Value = itm.path;
cmd.Parameters.Add(myparam1);
cmd.Parameters.Add(myparam2);
cmd.Parameters.Add(myparam3);
cmd.ExecuteNonQuery();
PB1.Value = s_count;
Application.DoEvents();
//transaction.Commit();
cmd.CommandText = "COMMIT;";
cmd.ExecuteNonQuery();
s_count++;
}
catch
{
continue;
}
}
db.Close();
DBPostProcess("test.db");
/*
* var dct = new Dictionary<string, double>();
*
* for (int i = 0; i < splist.Count; i++)
* {
* dct.Add(splist[i].path, VecDiff(splist[0].scalar_stats.Values.ToList(), splist[i].scalar_stats.Values.ToList()));
* }
*
* dct.OrderBy(t => t.Value);
*
* dct.ToList().OrderBy(t => t.Value).ToList().ForEach(t => listBox1.Items.Add(t.Key + " ---> [" + t.Value + "]"));
*/
/*************************************************************************
* k-means++ clusterization
* INPUT PARAMETERS:
* XY - dataset, array [0..NPoints-1,0..NVars-1].
* NPoints - dataset size, NPoints>=K
* NVars - number of variables, NVars>=1
* K - desired number of clusters, K>=1
* Restarts - number of restarts, Restarts>=1
*
* OUTPUT PARAMETERS:
* Info - return code:
* -3, if task is degenerate (number of distinct points is
* less than K)
* -1, if incorrect NPoints/NFeatures/K/Restarts was passed
* 1, if subroutine finished successfully
* C - array[0..NVars-1,0..K-1].matrix whose columns store
* cluster's centers
* XYC - array[NPoints], which contains cluster indexes
*************************************************************************/
/*
* int NPoints = splist.Count;
* int NVars = splist[0].scalar_stats.Count;
* int K = (int)Math.Sqrt(NPoints);
* int Restarts = 5;
* int Info = 0;
*
* var C = new double[NVars, K];
* var XYC = new int[NPoints];
* var XY = new double[NPoints, NVars];
*
* var _XY = splist[0].scalar_stats.Values.ToArray();
* for (int i = 0; i < NPoints; i++)
* for (int j = 0; j < NVars; j++)
* XY[i, j] = splist[i].scalar_stats.Values.ToArray()[j];
*
* alglib.kmeansgenerate(
* XY,
* NPoints,
* NVars,
* K,
* Restarts,
* out Info,
* out C,
* out XYC);
*
* Info++;
*
* Application.DoEvents();
*
* for (int i = 0; i < splist.Count; i++)
* {
* listBox1.Items.Add(Path.GetFileName(splist[i].path) + " -> cluster # " + XYC[i]);
* }
*/
/*foreach (var itm in splist)
* {
* var s1 = new List<double>();
* var s2 = new List<double>();
* var s3 = new List<double>();
*
* foreach (var itm2 in splist)
* {
* /*listBox1.Items.Add(Path.GetFileName(itm.path) + " vs " + Path.GetFileName(itm2.path) +
* "cross_energy_correl = " + Correl(itm.snap_log10_energy, itm2.snap_log10_energy, itm.snap_log10_energy.Average(), itm2.snap_log10_energy.Average()) + " " +
* "cross_energy_diff = " + VecDiff(itm.snap_log10_energy, itm2.snap_log10_energy) + " " +
* "convoluted histogram value = " + HistogramConv(itm, itm2, 0.001)
* );*/
//s1.Add(Correl(itm.snap_log10_energy, itm2.snap_log10_energy, itm.snap_log10_energy.Average(), itm2.snap_log10_energy.Average()));
//s2.Add(1 / Math.Log10(VecDiff(itm.snap_log10_energy, itm2.snap_log10_energy)));
//s3.Add(HistogramConv(itm, itm2, 0.001));
/*s1.Add(0);
* s2.Add(0);
* s3.Add(0);
* }
*
* sp_CED.Add(s1);
* sp_CEC.Add(s2);
* sp_CHV.Add(s3);
* }*/
/*List<double> likelihood = new List<double>();
*
* for (int i = 0; i < splist.Count; i++)
* {
* double lh = 0;
* //listBox1.Items.Add(Path.GetFileName(splist[i].path) + ": " + (int)(100*sp_ASC[i]) + " " + (int)(100*sp_ASSC[i]) + " " + (int)(10*sp_ED[i]));
* for (int j = 0; j < splist.Count; j++)
* {
* lh =
* sp_ASC[i] * sp_ASC[j] +
* sp_ASSC[i] * sp_ASSC[j] +
* sp_ED[i] * sp_ED[j] +
* sp_CED[i][j] + sp_CEC[i][j] + sp_CHV[i][j]
* ;
* likelihood.Add(lh);
* listBox1.Items.Add((int)(100*lh) + " : " + Path.GetFileName(splist[i].path) + " " + Path.GetFileName(splist[j].path));
* }
* //listBox1.Items.Add("----->" + (int)(100*sp_CED[i][j]) + " " + (int)(100*sp_CEC[i][j]) + " " + (int)(100*sp_CHV[i][j]) + "; " + Path.GetFileName(splist[j].path));
*
* }*/
}
