/********************************************
* individual mate
* given the parents, creates a new child chromosome
* by taking parts from the parents at random
* then returns the child
********************************************/
public individual mate(individual parent2, uint[,,] source, uint[,,] stock, int stockSize)
{
int total = (int)Pow(Globals.SIZE, 2);
Random rnd = new Random();
Random mutated = new Random();
int[] child_chrom = new int[total];
for (int i = 0; i < total; i++)
{
double p = rnd.Next(0, 100) / 100.0;
// if probability is less than 0.45
// insert gene from parent 1
if (p < 0.45)
{
child_chrom[i] = chromosome[i];
}
// if probability is less than 0.90
// insert gene from parent 2
else if (p < 0.90)
{
child_chrom[i] = parent2.chromosome[i];
}
// otherwise add a new random gene
else
{
child_chrom[i] = mutated.Next(0, stockSize);
}
}
individual child = new individual(child_chrom, source, stock);
return(child);
}
public object GetData()
{
if (null == savedRecord)
{
savedRecord = new individual();
}
savedRecord.firstname = FirstName;
savedRecord.lastname = LastName;
savedRecord.sunshineid = ID;
savedRecord.phone = Phone;
savedRecord.phonenumbers_individual.Clear();
foreach (var item in flpPhoneNumbers.Controls)
{
if (item is PhoneAdd)
{
savedRecord.phonenumbers_individual.Add(new phonenumbers_individual()
{
ownerID = savedRecord.id,
phonenumber = (item as PhoneAdd).GetText()
});
}
}
savedRecord.social_media_individual.Clear();
foreach (var item in flpSocial.Controls)
{
if (item is SocialMediaLink)
{
savedRecord.social_media_individual.Add(new social_media_individual()
{
sm_ind_id = savedRecord.id,
sm_title = (item as SocialMediaLink).LinkTitle,
sm_link = Encoding.ASCII.GetBytes((item as SocialMediaLink).LinkURL),
sm_type = (item as SocialMediaLink).SMType
});
}
}
savedRecord.addresses_individual.Clear();
if (null != GetPrimaryAddress())
{
savedRecord.addresses_individual.Add(GetPrimaryAddress());
}
if (null != GetSecondaryAddress())
{
savedRecord.addresses_individual.Add(GetSecondaryAddress());
}
savedRecord.actions_individual.Clear();
foreach (var item in actions)
{
savedRecord.actions_individual.Add(item);
}
savedRecord.financialsupport = GetFinancialSupport();
return(savedRecord);
}
static void FindBestIndividual(ref individual[] population, ref individual bestindividual, ref individual currentbest, int generation, ref int[] TempCitySet, ref int[] WorkSet, ref int[] CitySet, int PopSiz_e, double[,] temp)
{
int i;
bestindividual = population[0];
for (i = 1; i < PopSiz_e; i++)
{
if (population[i].fitness > bestindividual.fitness)
{
bestindividual = population[i];
}
}
if (generation == 0)
{
currentbest = bestindividual;
}
else
{
if (bestindividual.fitness > currentbest.fitness)
{
currentbest = bestindividual;
OutputTextReport(ref currentbest, ref generation, ref TempCitySet, ref WorkSet, ref CitySet, (int)Math.Sqrt(PopSiz_e), temp);
}
}
}
//Генетический оператор - арифметический кроссинговер
public void crossingover(individual p1, individual p2, individual c1, individual c2)
{
//лямбда-переменная для кроссинговера
double ß = random.NextDouble();
for (int i = 0; i < p1.Genes.Count(); i++)
{
c1.Genes[i] = Convert.ToInt32(ß * p1.Genes[i] + (1 - ß) * p2.Genes[i]);
c2.Genes[i] = Convert.ToInt32(ß * p2.Genes[i] + (1 - ß) * p1.Genes[i]);
}
}
public double absolutlifitnessPersent(individual ind, individual model)
{
double rgbFitness = 0;
for (int i = 0; i < ind.Genes.Count(); i++)
{
rgbFitness += Math.Pow(ind.Genes[i] - model.Genes[i], 2);
}
rgbFitness = Math.Sqrt(rgbFitness);
return(rgbFitness);
}
private string test_self()
{
individual self = new individual("Self");
gedcomer gc = new gedcomer();
gc.root(self);
string gedcom = gc.ToString();
return(gedcom);
}
// Test father
private string test_father()
{
individual self = new individual("Self");
individual father = new individual("Father");
self.relate(kinship.FATHER, father);
gedcomer gc = new gedcomer();
gc.root(self);
string gedcom = gc.ToString();
return(gedcom);
}
// @todo Spousal relationship should be drawn
// Create FAM record
private string test_spouse()
{
individual self = new individual("Self");
individual spouse = new individual("Spouse");
self.relate(kinship.SPOUSE, spouse);
gedcomer gc = new gedcomer();
gc.root(self);
string gedcom = gc.ToString();
return(gedcom);
}
public static void m3_Main(double[,] temp, int size)
{
int POPSIZE = (int)Math.Pow(size, 2) + size;
int CITYCOUNT = size;
int CHROMLENGTH = CITYCOUNT;
int PopSiz_e = (int)Math.Pow(size, 2);
int MaxGeneration = POPSIZE;
individual bestindividual = new individual();
individual currentbest = new individual();
individual[] population = new individual[POPSIZE];
individual[] newpopulation = new individual[POPSIZE];
bestindividual.chrom = new int[CHROMLENGTH];
currentbest.chrom = new int[CHROMLENGTH];
for (int i = 0; i < POPSIZE; i++)
{
population[i].chrom = new int[CHROMLENGTH];
newpopulation[i].chrom = new int[CHROMLENGTH];
}
int[] CitySet = new int[CITYCOUNT];
int[] WorkSet = new int[CITYCOUNT];
int[] TempCitySet = new int[CITYCOUNT];
double[,] CityDistance = new double[CITYCOUNT, CITYCOUNT];
CityDistance = temp;
int generation = 0;
GenerateInitialPopulation(ref CitySet, ref population, PopSiz_e);
CalculateFitness(ref population, ref TempCitySet, ref CityDistance, ref WorkSet, ref CitySet, PopSiz_e, CITYCOUNT);
FindBestIndividual(ref population, ref bestindividual, ref currentbest, generation, ref TempCitySet, ref WorkSet, ref CitySet, PopSiz_e, temp);
OutputTextReport(ref currentbest, ref generation, ref TempCitySet, ref WorkSet, ref CitySet, CHROMLENGTH, temp);
while (generation < MaxGeneration)
{
generation++;
GenerateNextPopulation(ref population, ref newpopulation, PopSiz_e, POPSIZE);
CalculateFitness(ref population, ref TempCitySet, ref CityDistance, ref WorkSet, ref CitySet, PopSiz_e, CITYCOUNT);
FindBestIndividual(ref population, ref bestindividual, ref currentbest, generation, ref TempCitySet, ref WorkSet, ref CitySet, PopSiz_e, temp);
}
}
//отбор при помощи турнинрой селекции с турниром (размер турнира в переменной)
public void choice(population parent, population selectionparent)
{
Random rand = new Random();
population parentForSelection = new population();
for (int i = 0; i < numberOfIndividuals / 2; i++)
{
int theBest = 0;
double theBestresult = 50000;
for (int j = 0; j < sizeTourney; j++)
{
int in1 = rand.Next(0, numberOfIndividuals);
if (absolutlifitnessPersent(parent.Population[in1], model) < theBestresult)
{
theBestresult = absolutlifitnessPersent(parent.Population[in1], model);
theBest = in1;
}
}
parentForSelection.Population.Add(parent.Population[theBest]);
selectionparent.Population.Add(parent.Population[theBest]);
}
parent.Population.Clear();
individual child1;
individual child2;
while (parent.Population.Count < numberOfIndividuals)
{
int i = rand.Next(0, numberOfIndividuals / 2);
int j = rand.Next(0, numberOfIndividuals / 2);
if (p > rand.NextDouble())
{
crossingover(parentForSelection.Population[i], parentForSelection.Population[j], child1 = new individual(), child2 = new individual());
}
else
{
child1 = new individual();
child2 = new individual();
child1.Genes = parentForSelection.Population[i].Genes;
child2.Genes = parentForSelection.Population[j].Genes;
}
parent.Population.Add(child1);
parent.Population.Add(child2);
}
}
static void OutputTextReport(ref individual currentbest, ref int generation, ref int[] TempCitySet, ref int[] WorkSet, ref int[] CitySet, int CHROMLENGTH, double[,] temp)
{
int i, j;
TextWriter str = Console.Out;
StreamWriter fileOut = new StreamWriter(new FileStream("graph_opt.txt",
FileMode.Create,
FileAccess.Write));
Console.SetOut(fileOut);
for (i = 0; i < CHROMLENGTH; i++)
{
for (j = 0; j < CHROMLENGTH; j++)
{
Console.Write("{0:N} ", temp[i, j]);
}
Console.WriteLine();
}
Console.SetOut(str);
DecodeChromosome(ref currentbest.chrom, ref TempCitySet, ref WorkSet, ref CitySet, CHROMLENGTH);
Console.SetOut(fileOut);
Console.Write("\nНайкраще значення = {0:N} при шляху ==>> ", currentbest.value);
for (i = 0; i < CHROMLENGTH; i++)
{
Console.Write("<{0}>", TempCitySet[i]);
}
Console.WriteLine("\n");
fileOut.Close();
Console.SetOut(str);
}
public void NewIndividual()
{
if (Repository.HasChanges())
{
var result = MessageBox.Show($"You have unsaved changes, save first?", $"Save?", MessageBoxButton.YesNoCancel, MessageBoxImage.Warning);
switch (result)
{
case MessageBoxResult.Cancel:
return;
case MessageBoxResult.Yes:
Save();
break;
case MessageBoxResult.No:
Repository.CancelChanges();
break;
default:
break;
}
}
ReportsVM = null;
NewIndividualVisibility = Visibility.Collapsed;
NewOrganizationVisibility = Visibility.Collapsed;
ContentView = _container.GetInstance <IndividualDetailViewModel>();
individual i = new individual();
(ContentView as IndividualDetailViewModel).Entity = new ModelLibrary.Models.ReturnedEntity()
{
Entity = i
};
var ida = _container.GetInstance <IndividualDataAccess>();
ida.Add(i);
ActivateItem(ContentView);
}
/********************************************
* individual - copy constructor
* copys a given individual
********************************************/
public individual(individual copy)
{
int total = (int)Pow(Globals.SIZE, 2);
chromosome = new int[total];
uint[,,] temp = new uint[total, 5, 3];
fitness = new uint[total, 5];
wholeIMGscore = new double[total];
for (int i = 0; i < total; i++)
{
chromosome[i] = copy.chromosome[i];
wholeIMGscore[i] = copy.wholeIMGscore[i];
}
chromscore = copy.chromscore;
for (int i = 0; i < total; i++)
{
for (int k = 0; k < 5; k++)
{
fitness[i, k] = copy.fitness[i, k];
}
}
}
private void button_win_Click(object sender, EventArgs e)
{
//данные с формы
numberOfIndividuals = Convert.ToInt32(PopulationNumber.Text);
sizeTourney = Convert.ToInt32(textBox_sizeTourney.Text);
//храним родителей, родителей для селекции и потомство
parents = new population();
parentsForSelection = new population();
children = new population();
Random rnd = new Random();
//Эталонная особь
model.Genes = new int[] { 96, 96, 159 };
//Генерация начальной популяции
population FirstPopulation = new population();
for (int i = 0; i < numberOfIndividuals; i++)
{
individual curentIndividuals = new individual();
curentIndividuals.Genes = new int[] { rnd.Next(0, 256), rnd.Next(0, 256), rnd.Next(0, 256) };
FirstPopulation.Population.Add(curentIndividuals);
}
bool individualIsfind = false;
int iter = 0;
listBox_number.Items.Clear();
while (!individualIsfind)
{
double theBestreslt = 50000;
for (int i = 0; i < FirstPopulation.Population.Count; i++)
{
double rez = absolutlifitnessPersent(FirstPopulation.Population[i], model);
if (rez < theBestreslt)
{
theBestreslt = rez;
}
if (absolutlifitnessPersent(FirstPopulation.Population[i], model) == 0)
{
individualIsfind = true;
int number = i;
break;
}
}
rezult.Add(theBestreslt);
if (!individualIsfind)
{
iter++;
foreach (var item in FirstPopulation.Population)
{
parents.Population.Add(item);
}
listBox_number.Items.Add(iter);
choice(FirstPopulation, parentsForSelection);
foreach (var item in FirstPopulation.Population)
{
children.Population.Add(item);
}
Mutation(FirstPopulation);
}
}
Form2 graph = new Form2(rezult, iter);
graph.Show();
}
public Generation NextGen(CNF_Instance cnf)
{
Generation newGen = new Generation(this.variable_count);
newGen.gen_count = this.gen_count + 1;
newGen.total_flips = this.total_flips;
this.Get_fitness(cnf);
this.population.Sort((x, y) => y.fitness.CompareTo(x.fitness));
List <individual> selected = new List <individual>(10);
Random r = new Random();
//add elites
for (int i = 0; i < 2; i++)
{
newGen.population.Add(this.population[i]);
selected.Add(this.population[i]);
}
//select 8
double[] cdf = new double[10];
for (int i = 0; i < 10; i++)
{
cdf[i] = this.population[i].prob;
if (i != 0)
{
cdf[i] += cdf[i - 1];
}
}
for (int i = 0; i < 8; i++)
{
double selector = r.NextDouble();
int j = 0;
for (j = 0; j < 10; j++)
{
if (selector <= cdf[j])
{
break;
}
}
selected.Add(this.population[j]);
}
//crossover
for (int i = 2; i < 10; i += 2)
{
string father = selected[i].bits;
string mother = selected[i + 1].bits;
individual son = new individual();
individual daughter = new individual();
for (int j = 0; j < variable_count; j++)
{
if (r.NextDouble() < 0.5)
{
son.bits = string.Concat(son.bits, father[j]);
daughter.bits = string.Concat(son.bits, mother[j]);
}
else
{
daughter.bits = string.Concat(son.bits, father[j]);
son.bits = string.Concat(son.bits, mother[j]);
}
}
newGen.population.Add(son);
newGen.population.Add(daughter);
}
//mutation
for (int i = 2; i < 10; i++)
{
string cur = newGen.population[i].bits;
char[] tmp = cur.ToCharArray();
if (r.NextDouble() < 0.9)
{
for (int j = 0; j < this.variable_count; j++)
{
if (r.NextDouble() < 0.5)
{
tmp[j] = Flip(tmp[j]);
newGen.total_flips++;
}
}
newGen.population[i].bits = new string(tmp);
}
}
//flip heuristic
for (int i = 2; i < 10; i++)
{
string cur = newGen.population[i].bits;
char[] tmp = cur.ToArray();
int[] flip_order = RandomSequence(variable_count);
double old_fitness = 0, new_fitness = 0;
do
{
for (int j = 0; j < variable_count; j++)
{
old_fitness = Get_single_fitness(new string(tmp), cnf);
int index = flip_order[j];
tmp[index] = Flip(tmp[index]);
newGen.total_flips++;
new_fitness = Get_single_fitness(new string(tmp), cnf);
if (new_fitness < old_fitness)
{
tmp[index] = Flip(tmp[index]);
newGen.total_flips--;
}
}
if (new_fitness == 1)
{
break;
}
} while (old_fitness < new_fitness);
newGen.population[i].bits = new string(tmp);
}
return(newGen);
}
//Save button
private void toolStripButton2_Click(object sender, EventArgs e)
{
if (tabControl.SelectedTab is RecordViewTabPage)
{
byte saveID = (tabControl.SelectedTab as RecordViewTabPage).ID;
object r = (tabControl.SelectedTab as RecordViewTabPage).GetContactFromData();
if (r is individual)
{
//Replace with UpdateIndividualRecord
individual c = (individual)r;
try
{
individual record = Entities.individuals.First(a => a.id == c.id);
record.firstname = c.firstname;
record.lastname = c.lastname;
record.addresses_individual = c.addresses_individual;
record.phone = c.phone;
record.phonenumbers_individual = c.phonenumbers_individual;
record.financialsupport = c.financialsupport;
record.actions_individual = c.actions_individual;
record.social_media_individual = c.social_media_individual;
record.sunshineid = c.sunshineid;
record.source = c.source;
}
catch (InvalidOperationException)
{
Entities.individuals.Add(c);
}
finally
{
Entities.SaveChanges();
tsslMainForm.Text = $"{c.ToString()} has been saved.";
}
}
else
{
//Replace with UpdateOrgRecord
organization o = (organization)r;
try
{
organization record = Entities.organizations.First(a => a.orgid == o.orgid);
record.name = o.name;
record.addresses_organization = o.addresses_organization;
record.phonenumbers_organization = o.phonenumbers_organization;
record.phone = o.phone;
record.financialsupport = o.financialsupport;
record.actions_organization = o.actions_organization;
record.social_media_organization = o.social_media_organization;
record.orgsunshineid = o.orgsunshineid;
}
catch (InvalidOperationException)
{
Entities.organizations.Add(o);
}
finally
{
Entities.SaveChanges();
tsslMainForm.Text = $"{o.name} has been saved.";
}
}
}
}
public void SetData()
{
workingRecord = JsonConvert.DeserializeObject <individual>(JsonConvert.SerializeObject(savedRecord,
new JsonSerializerSettings {
ReferenceLoopHandling = ReferenceLoopHandling.Ignore
}));
if (this.InvokeRequired)
{
this.Invoke(new EventHandler(delegate { SetData(); }));
}
else
{
FirstName = savedRecord.firstname;
LastName = savedRecord.lastname;
Phone = savedRecord.phone;
ID = savedRecord.sunshineid;
if (null != savedRecord.phonenumbers_individual)
{
foreach (var item in savedRecord.phonenumbers_individual)
{
PhoneAdd pa = new PhoneAdd();
pa.SetText(item.phonenumber);
flpPhoneNumbers.Controls.Add(pa);
}
}
SetFinancialSupport(savedRecord.financialsupport);
if (null != savedRecord.actions_individual)
{
ICollection <actions_individual> items = new List <actions_individual>();
foreach (var item in savedRecord.actions_individual)
{
//items.Add(item);
}
InitializeActionList(items);
}
foreach (var x in savedRecord.addresses_individual)
{
if ((bool)x.primary)
{
StreetPrimary = x.streetAddress;
CityPrimary = x.city;
cmbState.SelectedIndex = cmbState.FindStringExact(x.state);
cmbState.SelectedItem = cmbState.SelectedIndex;
ZipPrimary = x.zip;
}
else
{
StreetSecondary = x.streetAddress;
CitySecondary = x.city;
cmbState2.SelectedIndex = cmbState2.FindStringExact(x.state);
ZipSecondary = x.zip;
}
}
foreach (var item in savedRecord.social_media_individual)
{
flpSocial.Controls.Add(
new SocialMediaLink(item.sm_title, Encoding.ASCII.GetString(item.sm_link))
{
SMType = item.sm_type
});
}
}
}
private string test_family()
{
individual self = new individual("Self You");
individual grandfather = new individual("Grand Father");
individual grandmother = new individual("Grand Mother");
individual gotra = new individual("Gotra");
individual father = new individual("Father");
individual mother = new individual("Mother");
individual spouse = new individual("Spouse");
individual child1 = new individual("Son #1");
individual child2 = new individual("Daughter");
individual child3 = new individual("Unmarried");
individual daughterinlaw = new individual("Daugher In-Law");
individual grandson = new individual("Grand Son");
self.birth("1980");
father.birth("1955");
mother.birth("1960");
spouse.birth("1984");
child1.birth("1987");
child2.birth("1990");
grandfather.marry(grandmother); // or the revese way should be too possible.
grandfather.death("2004");
grandmother.death("2006");
// generation #2
daughterinlaw.birth("1995");
child1.marry(daughterinlaw);
// generation #3
grandson.birth("1999");
self.male();
child1.male();
child2.female();
self.alias("Alias 2");
mother.marry(father);
father.note("Seniorly respected");
father.note("Social worker");
father.register_event("2010", "Migrate", "City 1");
father.register_event("2011", "Teaching", "City 2");
mother.birth("1960");
mother.death("2001");
father.relate(kinship.FATHER, grandfather);
father.relate(kinship.CHILD, self);
grandfather.relate(kinship.FATHER, gotra);
child1.relate(kinship.CHILD, grandson);
// just: values change
self.relate(kinship.SELF, self);
// assignment of a new individual defined separately
//self.relate(kinship.FATHER, father);
self.relate(kinship.MOTHER, mother);
//self.relate(kinship.SPOUSE, spouse);
self.marry(spouse);
self.relate(kinship.CHILD, child1);
self.relate(kinship.CHILD, child2);
self.relate(kinship.CHILD, child3);
gedcomer gc = new gedcomer();
gc.root(self);
// self // case 1
// grandfather // case 2
// grandson // case 3
// mother // case 4
string gedcom = gc.ToString();
return(gedcom);
}
/********************************************
* generate
* inputs - source, stock, sourceVal, stockVal
* outputs - new image to showmosaic picture box
* This function uses the genetic algorithm try and piece
* together the source image with all the stock photos.
* The best generation is brought to the top with
* a simple bubble sort.
********************************************/
public void generate(Bitmap[] source, Bitmap[] stock, uint[,,] sourceVal, uint[,,] stockVal)
{
// MessageBox.Show("In Generate");
int mySize = Globals.SIZE; // amount of source images per row
int totalimages = (int)Pow(mySize, 2); // amount of source images
int popSize = Globals.population; // population size
int TotalGens = Globals.Generations; // total amount of generations
int stockSize = stock.Length; // stock images size
progressBar1.Minimum = 0;
progressBar1.Maximum = TotalGens;
Bitmap[] BestInGen = new Bitmap[totalimages]; // gets the best person in population
int[,] populationLoc = new int[popSize, totalimages]; // holds the values of stock
Random rnd = new Random();
int currentGen = 0;
int[] sourcegnome = new int[totalimages];
for (int i = 0; i < totalimages; i++)
{
sourcegnome[i] = i;
}
individual mySource = new individual(sourceVal);
// initializes the population array with random stock images
for (int i = 0; i < popSize; i++)
{
for (int j = 0; j < totalimages; j++)
{
int myNum = rnd.Next(0, stockSize);
populationLoc[i, j] = myNum;
}
}
// SourceDom(domCol); // gets the dominant color on source images
// List<individual> myPop = new List<individual>();
individual[] myPop = new individual[popSize];
bool found = false;
int[] gnome = new int[totalimages];
for (int i = 0; i < popSize; i++)
{
for (int k = 0; k < totalimages; k++)
{
gnome[k] = populationLoc[i, k];
}
myPop[i] = (new individual(gnome, sourceVal, stockVal));
}
int elite = Globals.elitism;
int weak = 100 - elite;
while (!found && currentGen < TotalGens)
{
// sort
sort();
if (Globals.Generations <= 500)
{
if (currentGen % 10 == 0)
{
for (int i = 0; i < totalimages; i++)
{
BestInGen[i] = stock[myPop[0].chromosome[i]];
}
DisplayIMG(BestInGen);
}
}
else
{
if (currentGen % 100 == 0)
{
for (int i = 0; i < totalimages; i++)
{
BestInGen[i] = stock[myPop[0].chromosome[i]];
}
DisplayIMG(BestInGen);
}
}
progressBar1.Value = currentGen;
progressBar1.Refresh();
if (myPop[0].chromscore <= 100)
{
progressBar1.Value = TotalGens;
found = true;
break;
}
List <individual> nextGen = new List <individual>();
// elitism, variable of user choice of population goes to the next generation
int s = (elite * popSize) / 100;
for (int i = 0; i < s; i++)
{
nextGen.Add(new individual(myPop[i]));
}
// rest of the population will mate
// produces offspring from the best 20
// For those 20 are the fittest, the rest "die"
s = (weak * popSize) / 100;
for (int i = 0; i < s; i++)
{
int r = rnd.Next(0, 20);
individual parent1 = new individual(myPop[r]);
r = rnd.Next(0, 20);
individual parent2 = new individual(myPop[r]);
individual child = parent1.mate(parent2, sourceVal, stockVal, stockSize);
nextGen.Add(new individual(child));
}
//nextGen.CopyTo(myPop,totalimages);
nextGen.CopyTo(myPop);
currentGen++;
}
progressBar1.Value = TotalGens;
progressBar1.Refresh();
// Bubble sort
void sort()
{
for (int i = 0; i < popSize - 1; i++)
{
for (int j = 0; j < popSize - i - 1; j++)
{
if (myPop[j].chromscore > myPop[j + 1].chromscore)
{
swap(j, j + 1);
}
}
}
return;
}
// swaps two individuals
void swap(int who, int what)
{
individual temp = new individual(myPop[who]);
myPop[who] = myPop[what];
myPop[what] = temp;
}
}
public string generateIdebJson(DbConnection conn, string resultid, int dbTimeout)
{
string result = "";
DataTable dtheader = conn.GetDataTable("select * from slik_ideb where resultid = @1", new object[] { resultid }, dbTimeout);
DataTable dtpokok = conn.GetDataTable("select * from slik_ideb_datapokokdebitur where resultid = @1", new object[] { resultid }, dbTimeout);
DataTable dtkredit = conn.GetDataTable("select * from slik_ideb_kredit where resultid = @1", new object[] { resultid }, dbTimeout);
if (dtheader.Rows.Count > 0)
{
if (dtheader.Rows[0]["isCompany"].ToString() == "0")
{
header header = BindData <header>(dtheader, 0);
individual individu = BindData <individual>(dtheader, 0);
parameterPencarian searchParam = BindData <parameterPencarian>(dtheader, 0);
ringkasanFasilitas ringkasanfasilitas = BindData <ringkasanFasilitas>(dtheader, 0);
//datapokok
List <dataPokokDebitur> datapokoks = new List <dataPokokDebitur>();
for (int i = 0; i < dtpokok.Rows.Count; i++)
{
dataPokokDebitur datapokok = BindData <dataPokokDebitur>(dtpokok, i);
datapokoks.Add(datapokok);
}
//kredit
List <kreditPembiayan> kredits = new List <kreditPembiayan>();
for (int i = 0; i < dtkredit.Rows.Count; i++)
{
kreditPembiayan kredit = BindData <kreditPembiayan>(dtkredit, i);
string fasilitasid = dtkredit.Rows[i]["fasilitasid"].ToString();
DataTable dtagunan = conn.GetDataTable("select * from slik_ideb_agunan where resultid = @1 and fasilitasid = @2", new object[] { resultid, fasilitasid }, dbTimeout);
//agunan
List <agunan> agunans = new List <agunan>();
for (int x = 0; x < dtagunan.Rows.Count; x++)
{
agunan agunan = BindData <agunan>(dtagunan, x);
agunans.Add(agunan);
}
kredit.agunan = agunans.ToArray();
List <penjamin> penjamins = new List <penjamin>();
kredit.penjamin = penjamins.ToArray();
kredits.Add(kredit);
}
individu.dataPokokDebitur = datapokoks.ToArray();
individu.parameterPencarian = searchParam;
individu.ringkasanFasilitas = ringkasanfasilitas;
fasilitas fasilitas = new fasilitas();
fasilitas.kreditPembiayan = kredits.ToArray();
individu.fasilitas = fasilitas;
idebIndividu ideb = new idebIndividu();
ideb.header = header;
ideb.individual = individu;
result = JsonConvert.SerializeObject(ideb);
}
else
{
header header = BindData <header>(dtheader, 0);
perusahaan perusahaan = BindData <perusahaan>(dtheader, 0);
parameterPencarianPerusahaan searchParam = BindData <parameterPencarianPerusahaan>(dtheader, 0);
ringkasanFasilitas ringkasanfasilitas = BindData <ringkasanFasilitas>(dtheader, 0);
//datapokok
List <dataPokokDebiturPerusahaan> datapokoks = new List <dataPokokDebiturPerusahaan>();
for (int i = 0; i < dtpokok.Rows.Count; i++)
{
dataPokokDebiturPerusahaan datapokok = BindData <dataPokokDebiturPerusahaan>(dtpokok, i);
datapokoks.Add(datapokok);
}
//kredit
List <kreditPembiayan> kredits = new List <kreditPembiayan>();
for (int i = 0; i < dtkredit.Rows.Count; i++)
{
kreditPembiayan kredit = BindData <kreditPembiayan>(dtkredit, i);
string fasilitasid = dtkredit.Rows[i]["fasilitasid"].ToString();
DataTable dtagunan = conn.GetDataTable("select * from slik_ideb_agunan where resultid = @1 and fasilitasid = @2", new object[] { resultid, fasilitasid }, dbTimeout);
//agunan
List <agunan> agunans = new List <agunan>();
for (int x = 0; x < dtagunan.Rows.Count; x++)
{
agunan agunan = BindData <agunan>(dtagunan, x);
agunans.Add(agunan);
}
kredit.agunan = agunans.ToArray();
List <penjamin> penjamins = new List <penjamin>();
kredit.penjamin = penjamins.ToArray();
kredits.Add(kredit);
}
perusahaan.dataPokokDebitur = datapokoks.ToArray();
perusahaan.parameterPencarian = searchParam;
perusahaan.ringkasanFasilitas = ringkasanfasilitas;
fasilitas fasilitas = new fasilitas();
fasilitas.kreditPembiayan = kredits.ToArray();
perusahaan.fasilitas = fasilitas;
idebPerusahaan ideb = new idebPerusahaan();
ideb.header = header;
ideb.perusahaan = perusahaan;
result = JsonConvert.SerializeObject(ideb);
}
}
return(result);
}
public void Add(individual individual)
{
da.Add <individual>(individual);
}
