static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
LaRank svm = new LaRank(C, kernel, labels);
svm.set_batch_mode(false);
svm.set_epsilon(epsilon);
svm.train();
DoubleMatrix out_labels = svm.apply(feats_train).get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, false);
charfeat = new StringCharFeatures(fm_test_dna, EAlphabet.DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, false);
Labels labels = new Labels(Load.load_labels("../data/label_train_dna.dat"));
PluginEstimate pie = new PluginEstimate();
pie.set_labels(labels);
pie.set_features(feats_train);
pie.train();
SalzbergWordStringKernel kernel = new SalzbergWordStringKernel(feats_train, feats_train, pie, labels);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
pie.set_features(feats_test);
pie.apply().get_labels();
double[,] km_test=kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public virtual Serializable run(IList para)
{
modshogun.init_shogun_with_defaults();
double learn_rate = (double)((double?)para[0]);
int max_iter = (int)((int?)para[1]);
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
AveragedPerceptron perceptron = new AveragedPerceptron(feats_train, labels);
perceptron.set_learn_rate(learn_rate);
perceptron.set_max_iter(max_iter);
perceptron.train();
perceptron.set_features(feats_test);
DoubleMatrix out_labels = perceptron.apply().get_labels();
ArrayList result = new ArrayList();
result.Add(perceptron);
result.Add(out_labels);
modshogun.exit_shogun();
return result;
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double learn_rate = 1.0;
int max_iter = 1000;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
AveragedPerceptron perceptron = new AveragedPerceptron(feats_train, labels);
perceptron.set_learn_rate(learn_rate);
perceptron.set_max_iter(max_iter);
perceptron.train();
perceptron.set_features(feats_test);
double[] out_labels = perceptron.apply().get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
LibSVMMultiClass svm = new LibSVMMultiClass(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();
kernel.init(feats_train, feats_test);
double[] out_labels = svm.apply().get_labels();
foreach (double item in out_labels)
Console.Write(item);
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
double width = 0.8;
int C = 1;
double epsilon = 1e-5;
double tube_epsilon = 1e-2;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel= new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
LibSVR svr = new LibSVR(C, epsilon, kernel, labels);
svr.set_tube_epsilon(tube_epsilon);
svr.train();
kernel.init(feats_train, feats_test);
double[] out_labels = svr.apply().get_labels();
foreach (double item in out_labels)
Console.Write(out_labels);
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int degree = 3;
int C = 1;
string[] fm_train_dna = {"CGCACGTACGTAGCTCGAT", "CGACGTAGTCGTAGTCGTA", "CGACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGACCACAGTTATATAGTA", "CGACGTAGTCGTAGTCGTA", "CGACGTAGTTTTTTTCGTA", "CGACGTAGTCGTAGCCCCA", "CAAAAAAAAAAAAAAAATA", "CGACGGGGGGGGGGGCGTA"};
string[] fm_test_dna = {"AGCACGTACGTAGCTCGAT", "AGACGTAGTCGTAGTCGTA", "CAACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGAACACAGTTATATAGTA", "CGACCTAGTCGTAGTCGTA", "CGACGTGGGGTTTTTCGTA", "CGACGTAGTCCCAGCCCCA", "CAAAAAAAAAAAACCAATA", "CGACGGCCGGGGGGGCGTA"};
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double[][] label_train_dna = { new double[] { -1, -1, -1, -1, -1, 1, 1, 1, 1, 1 } };
Labels labels = new Labels(new DoubleMatrix(label_train_dna));
SVMLight svm = new SVMLight(C, kernel, labels);
svm.train();
DomainAdaptationSVM dasvm = new DomainAdaptationSVM(C, kernel, labels, svm, 1.0);
dasvm.train();
DoubleMatrix @out = dasvm.apply(feats_test).get_labels();
modshogun.exit_shogun();
}
internal static DoubleMatrix run(IList para)
{
int degree = 20;
modshogun.init_shogun_with_defaults();
double C = (double)((double?)para[0]);
double epsilon = (double)((double?)para[1]);
int num_threads = (int)((int?)para[2]);
string[] fm_train_dna = {"CGCACGTACGTAGCTCGAT", "CGACGTAGTCGTAGTCGTA", "CGACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGACCACAGTTATATAGTA", "CGACGTAGTCGTAGTCGTA", "CGACGTAGTTTTTTTCGTA", "CGACGTAGTCGTAGCCCCA", "CAAAAAAAAAAAAAAAATA", "CGACGGGGGGGGGGGCGTA"};
string[] fm_test_dna = {"AGCACGTACGTAGCTCGAT", "AGACGTAGTCGTAGTCGTA", "CAACGGGGGGGGGGTCGTA", "CGACCTAGTCGTAGTCGTA", "CGAACACAGTTATATAGTA", "CGACCTAGTCGTAGTCGTA", "CGACGTGGGGTTTTTCGTA", "CGACGTAGTCCCAGCCCCA", "CAAAAAAAAAAAACCAATA", "CGACGGCCGGGGGGGCGTA"};
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
double[][] label_train_dna = { new double[] { -1, -1, -1, -1, -1, 1, 1, 1, 1, 1 } };
Labels labels = new Labels(new DoubleMatrix(label_train_dna));
SVMLight svm = new SVMLight(C, kernel, labels);
svm.set_qpsize(3);
svm.set_linear_term(new DoubleMatrix(new double[][] {{-1,-2,-3,-4,-5,-6,-7,-8,-7,-6}}));
svm.set_epsilon(epsilon);
//svm.parallel.set_num_threads(num_threads);
svm.train();
kernel.init(feats_train, feats_test);
DoubleMatrix @out = svm.apply().get_labels();
modshogun.exit_shogun();
return @out;
}
public static void Main() {
modshogun.init_shogun_with_defaults();
int k = 3;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_multiclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train);
Labels labels = new Labels(trainlab);
KNN knn = new KNN(k, distance, labels);
knn.train();
double[] out_labels = knn.apply(feats_test).get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int num = 1000;
double dist = 1.0;
double width = 2.1;
double C = 1.0;
DoubleMatrix offs =ones(2, num).mmul(dist);
DoubleMatrix x = randn(2, num).sub(offs);
DoubleMatrix y = randn(2, num).add(offs);
DoubleMatrix traindata_real = concatHorizontally(x, y);
DoubleMatrix o = ones(1,num);
DoubleMatrix trainlab = concatHorizontally(o.neg(), o);
DoubleMatrix testlab = concatHorizontally(o.neg(), o);
RealFeatures feats = new RealFeatures(traindata_real);
GaussianKernel kernel = new GaussianKernel(feats, feats, width);
Labels labels = new Labels(trainlab);
GMNPSVM svm = new GMNPSVM(C, kernel, labels);
feats.add_preprocessor(new NormOne());
feats.add_preprocessor(new LogPlusOne());
feats.set_preprocessed(1);
svm.train(feats);
SerializableAsciiFile fstream = new SerializableAsciiFile("blaah.asc", 'w');
//svm.save_serializable(fstream);
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double C = 0.9;
double epsilon = 1e-3;
org.shogun.Math.init_random(17);
DoubleMatrix traindata_real = Load.load_numbers(".../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/toy/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
LibLinear svm = new LibLinear(C, feats_train, labels);
svm.set_liblinear_solver_type(L2R_L2LOSS_SVC_DUAL);
svm.set_epsilon(epsilon);
svm.set_bias_enabled(true);
svm.train();
svm.set_features(feats_test);
DoubleMatrix out_labels = svm.apply().get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double width = 0.8;
double tau = 1e-6;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
KRR krr = new KRR(tau, kernel, labels);
krr.train(feats_train);
kernel.init(feats_train, feats_test);
DoubleMatrix out_labels = krr.apply().get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int num = 1000;
double dist = 1.0;
double width = 2.1;
double C = 1.0;
DoubleMatrix offs =ones(2, num).mmul(dist);
DoubleMatrix x = randn(2, num).sub(offs);
DoubleMatrix y = randn(2, num).add(offs);
DoubleMatrix traindata_real = concatHorizontally(x, y);
DoubleMatrix m = randn(2, num).sub(offs);
DoubleMatrix n = randn(2, num).add(offs);
DoubleMatrix testdata_real = concatHorizontally(m, n);
DoubleMatrix o = ones(1,num);
DoubleMatrix trainlab = concatHorizontally(o.neg(), o);
DoubleMatrix testlab = concatHorizontally(o.neg(), o);
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
LibSVM svm = new LibSVM(C, kernel, labels);
svm.train();
DoubleMatrix @out = svm.apply(feats_test).get_labels();
Console.WriteLine("Mean Error = " + signum(@out).ne(testlab).mean());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double learn_rate = 1.0;
int max_iter = 1000;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
Perceptron perceptron = new Perceptron(feats_train, labels);
perceptron.set_learn_rate(learn_rate);
perceptron.set_max_iter(max_iter);
perceptron.train();
perceptron.set_features(feats_test);
DoubleMatrix out_labels = perceptron.apply().get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double width = 0.8;
double tau = 1e-6;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel= new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
KRR krr = new KRR(tau, kernel, labels);
krr.train(feats_train);
kernel.init(feats_train, feats_test);
double[] out_labels = krr.apply().get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
GaussianNaiveBayes gnb = new GaussianNaiveBayes(feats_train, labels);
gnb.train();
double[] out_labels = gnb.apply(feats_test).get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
double width = 1.6;
double[,] train_real = Load.load_numbers("../data/fm_train_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(train_real);
GaussianKernel subkernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
AUCKernel kernel = new AUCKernel(0, subkernel);
kernel.setup_auc_maximization(labels);
double[,] km_train = kernel.get_kernel_matrix();
int numRows = km_train.GetLength(0);
int numCols = km_train.GetLength(1);
Console.Write("km_train:\n");
for(int i = 0; i < numRows; i++){
for(int j = 0; j < numCols; j++){
Console.Write(km_train[i,j] +" ");
}
Console.Write("\n");
}
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int gamma = 3;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
LDA lda = new LDA(gamma, feats_train, labels);
lda.train();
Console.WriteLine(lda.get_bias());
Console.WriteLine(lda.get_w().ToString());
lda.set_features(feats_test);
DoubleMatrix out_labels = lda.apply().get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
int degree = 20;
modshogun.init_shogun_with_defaults();
double C = (double)((double?)para[0]);
double epsilon = (double)((double?)para[1]);
int num_threads = (int)((int?)para[2]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
StringCharFeatures feats_train = new StringCharFeatures(fm_train_dna, DNA);
StringCharFeatures feats_test = new StringCharFeatures(fm_test_dna, DNA);
Labels labels = new Labels(Load.load_labels("../data/label_train_dna.dat"));
WeightedDegreeStringKernel kernel = new WeightedDegreeStringKernel(feats_train, feats_train, degree);
SVMLight svm = new SVMLight(C, kernel, labels);
svm.set_epsilon(epsilon);
//svm.parallel.set_num_threads(num_threads);
svm.train();
kernel.init(feats_train, feats_test);
svm.apply().get_labels();
ArrayList result = new ArrayList();
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
public static void Main() {
modshogun.init_shogun_with_defaults();
double C = 0.9;
double epsilon = 1e-3;
Math.init_random(17);
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
Labels labels = new Labels(trainlab);
LibLinear svm = new LibLinear(C, feats_train, labels);
svm.set_liblinear_solver_type(LIBLINEAR_SOLVER_TYPE.L2R_L2LOSS_SVC_DUAL);
svm.set_epsilon(epsilon);
svm.set_bias_enabled(true);
svm.train();
svm.set_features(feats_test);
double[] out_labels = svm.apply().get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
int mkl_norm = 2;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_multiclass.dat");
CombinedKernel kernel = new CombinedKernel();
CombinedFeatures feats_train = new CombinedFeatures();
CombinedFeatures feats_test = new CombinedFeatures();
RealFeatures subkfeats1_train = new RealFeatures(traindata_real);
RealFeatures subkfeats1_test = new RealFeatures(testdata_real);
GaussianKernel subkernel = new GaussianKernel(10, width);
feats_train.append_feature_obj(subkfeats1_train);
feats_test.append_feature_obj(subkfeats1_test);
kernel.append_kernel(subkernel);
RealFeatures subkfeats2_train = new RealFeatures(traindata_real);
RealFeatures subkfeats2_test = new RealFeatures(testdata_real);
LinearKernel subkernel2 = new LinearKernel();
feats_train.append_feature_obj(subkfeats2_train);
feats_test.append_feature_obj(subkfeats2_test);
kernel.append_kernel(subkernel2);
RealFeatures subkfeats3_train = new RealFeatures(traindata_real);
RealFeatures subkfeats3_test = new RealFeatures(testdata_real);
PolyKernel subkernel3 = new PolyKernel(10, 2);
feats_train.append_feature_obj(subkfeats3_train);
feats_test.append_feature_obj(subkfeats3_test);
kernel.append_kernel(subkernel3);
kernel.init(feats_train, feats_train);
Labels labels = new Labels(trainlab);
MKLMultiClass mkl = new MKLMultiClass(C, kernel, labels);
mkl.set_epsilon(epsilon);
mkl.set_mkl_epsilon(epsilon);
mkl.set_mkl_norm(mkl_norm);
mkl.train();
kernel.init(feats_train, feats_test);
double[] outMatrix = mkl.apply().get_labels();
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
CombinedKernel kernel = new CombinedKernel();
CombinedFeatures feats_train = new CombinedFeatures();
RealFeatures tfeats = new RealFeatures(traindata_real);
PolyKernel tkernel = new PolyKernel(10,3);
tkernel.init(tfeats, tfeats);
DoubleMatrix K = tkernel.get_kernel_matrix();
kernel.append_kernel(new CustomKernel(K));
RealFeatures subkfeats_train = new RealFeatures(traindata_real);
feats_train.append_feature_obj(subkfeats_train);
PolyKernel subkernel = new PolyKernel(10,2);
kernel.append_kernel(subkernel);
kernel.init(feats_train, feats_train);
Labels labels = new Labels(trainlab);
LibSVM svm = new LibSVM(C, kernel, labels);
svm.train();
CombinedKernel kernel_pred = new CombinedKernel();
CombinedFeatures feats_pred = new CombinedFeatures();
RealFeatures pfeats = new RealFeatures(testdata_real);
PolyKernel tkernel_pred = new PolyKernel(10,3);
tkernel_pred.init(tfeats, pfeats);
DoubleMatrix KK = tkernel.get_kernel_matrix();
kernel_pred.append_kernel(new CustomKernel(KK));
RealFeatures subkfeats_test = new RealFeatures(testdata_real);
feats_pred.append_feature_obj(subkfeats_train);
PolyKernel subkernel_pred = new PolyKernel(10,2);
kernel_pred.append_kernel(subkernel_pred);
kernel_pred.init(feats_train, feats_pred);
svm.set_kernel(kernel_pred);
svm.apply();
DoubleMatrix km_train =kernel.get_kernel_matrix();
Console.WriteLine(km_train.ToString());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double[][] y = { new double[] { 1, 2, 3, 4 } };
DoubleMatrix A = new DoubleMatrix(y);
Labels x = new Labels(A);
DoubleMatrix B = x.get_labels();
Console.WriteLine(B.ToString());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
int mkl_norm = 2;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures tfeats = new RealFeatures(traindata_real);
PolyKernel tkernel = new PolyKernel(10,3);
tkernel.init(tfeats, tfeats);
DoubleMatrix K_train = tkernel.get_kernel_matrix();
RealFeatures pfeats = new RealFeatures(testdata_real);
tkernel.init(tfeats, pfeats);
DoubleMatrix K_test = tkernel.get_kernel_matrix();
CombinedFeatures feats_train = new CombinedFeatures();
feats_train.append_feature_obj(new RealFeatures(traindata_real));
CombinedKernel kernel = new CombinedKernel();
kernel.append_kernel(new CustomKernel(K_train));
kernel.append_kernel(new PolyKernel(10,2));
kernel.init(feats_train, feats_train);
Labels labels = new Labels(trainlab);
MKLClassification mkl = new MKLClassification();
mkl.set_mkl_norm(1);
mkl.set_kernel(kernel);
mkl.set_labels(labels);
mkl.train();
CombinedFeatures feats_pred = new CombinedFeatures();
feats_pred.append_feature_obj(new RealFeatures(testdata_real));
CombinedKernel kernel2 = new CombinedKernel();
kernel2.append_kernel(new CustomKernel(K_test));
kernel2.append_kernel(new PolyKernel(10, 2));
kernel2.init(feats_train, feats_pred);
mkl.set_kernel(kernel2);
mkl.apply();
modshogun.exit_shogun();
}
public static void Main(string[] args)
{
modshogun.init_shogun_with_defaults();
double[] y = new double[4] {1, 2, 3, 4,};
Labels x = new Labels(y);
double[] r = x.get_labels();
for (int i = 0; i < 4; i++) {
Console.WriteLine(r[i]);
}
modshogun.exit_shogun();
}
public static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double[] ground_truth = Load.load_labels("../data/label_train_twoclass.dat");
Random RandomNumber = new Random();
double[] predicted = new double[ground_truth.Length];
for (int i = 0; i < ground_truth.Length; i++) {
predicted[i] = RandomNumber.NextDouble();
}
Labels ground_truth_labels = new Labels(ground_truth);
Labels predicted_labels = new Labels(predicted);
ContingencyTableEvaluation base_evaluator = new ContingencyTableEvaluation();
base_evaluator.evaluate(predicted_labels,ground_truth_labels);
AccuracyMeasure evaluator1 = new AccuracyMeasure();
double accuracy = evaluator1.evaluate(predicted_labels,ground_truth_labels);
ErrorRateMeasure evaluator2 = new ErrorRateMeasure();
double errorrate = evaluator2.evaluate(predicted_labels,ground_truth_labels);
BALMeasure evaluator3 = new BALMeasure();
double bal = evaluator3.evaluate(predicted_labels,ground_truth_labels);
WRACCMeasure evaluator4 = new WRACCMeasure();
double wracc = evaluator4.evaluate(predicted_labels,ground_truth_labels);
F1Measure evaluator5 = new F1Measure();
double f1 = evaluator5.evaluate(predicted_labels,ground_truth_labels);
CrossCorrelationMeasure evaluator6 = new CrossCorrelationMeasure();
double crosscorrelation = evaluator6.evaluate(predicted_labels,ground_truth_labels);
RecallMeasure evaluator7 = new RecallMeasure();
double recall = evaluator7.evaluate(predicted_labels,ground_truth_labels);
PrecisionMeasure evaluator8 = new PrecisionMeasure();
double precision = evaluator8.evaluate(predicted_labels,ground_truth_labels);
SpecificityMeasure evaluator9 = new SpecificityMeasure();
double specificity = evaluator9.evaluate(predicted_labels,ground_truth_labels);
Console.Write("{0}, {1}, {2}, {3}, {4}, {5}, {6}, {7}, {8}\n", accuracy, errorrate, bal, wracc, f1, crosscorrelation, recall, precision, specificity);
modshogun.exit_shogun();
}
public GitHubApi(IHttpClient client)
{
this.client = client;
client.BeforeRequest += ClientOnBeforeRequest;
client.AfterRequest += ClientOnAfterRequest;
Repositories = new Repositories(client);
Gists = new Gists(client);
Issues = new Issues(client);
Milestones = new Milestones(client);
Labels = new Labels(client);
Users = new Users(client);
Authorizations = new Authorizations(client);
Keys = new Keys(client);
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
DoubleMatrix ground_truth = Load.load_labels("../data/label_train_twoclass.dat");
DoubleMatrix predicted = randn(1, ground_truth.Length);
Labels ground_truth_labels = new Labels(ground_truth);
Labels predicted_labels = new Labels(predicted);
ROCEvaluation evaluator = new ROCEvaluation();
evaluator.evaluate(predicted_labels, ground_truth_labels);
Console.WriteLine(evaluator.get_ROC());
Console.WriteLine(evaluator.get_auROC());
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int N = 100;
DoubleMatrix ground_truth = randn(1, N);
DoubleMatrix predicted = randn(1, N);
Labels ground_truth_labels = new Labels(ground_truth);
Labels predicted_labels = new Labels(predicted);
MeanSquaredError evaluator = new MeanSquaredError();
double mse = evaluator.evaluate(predicted_labels, ground_truth_labels);
Console.WriteLine(mse);
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double mul = 2.0;
DoubleMatrix ground_truth = Load.load_labels("../data/label_train_multiclass.dat");
DoubleMatrix predicted = Load.load_labels("../data/label_train_multiclass.dat").mmul(mul);
Labels ground_truth_labels = new Labels(ground_truth);
Labels predicted_labels = new Labels(predicted);
MulticlassAccuracy evaluator = new MulticlassAccuracy();
double accuracy = evaluator.evaluate(predicted_labels, ground_truth_labels);
Console.WriteLine(accuracy);
modshogun.exit_shogun();
}
protected override void Update(TimeSpan gameTime)
{
var gameScene = this.Owner.Scene as GameScene;
if (gameScene == null)
{
return;
}
switch (this.PlayerState)
{
case PlayerState.Prepared:
var anchorEntity = gameScene.SlingshotAnchorEntity;
var anchorTransform = anchorEntity.FindComponent <Transform2D>();
var anchorPosition = anchorTransform.Position;
var impulse = anchorPosition - this.transform.Position;
Labels.Add("Impulse", impulse);
var showElasticBands = true;
if (impulse.X == 0)
{
impulse = Vector2.Zero;
showElasticBands = false;
}
gameScene.PreviewTrajectory(impulse);
gameScene.PreviewElasticBands(showElasticBands, this.transform);
break;
case PlayerState.InTheAir:
gameScene.PreviewElasticBands(false, this.transform);
// Dead condition: body slept or out of game area
if (this.rigidBody.Awake == false ||
this.rigidBody.LinearVelocity.LengthSquared() <= this.MinimumVelocityToDeclareDead)
{
this.PlayerState = PlayerState.Dead;
}
var position = this.transform.Position;
if (gamePlayManager.CheckBounds(position))
{
this.PlayerState = PlayerState.Dead;
}
break;
case PlayerState.Stamped:
break;
case PlayerState.Dead:
this.timeToDismiss -= gameTime;
if (this.timeToDismiss <= TimeSpan.Zero)
{
this.gamePlayManager.BoulderDead(this.Owner);
}
break;
default:
break;
}
}
public override IReadOnlyList <string> MergedQualifiers()
{
var parameters = new List <string>();
if (Type != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "type:{0}",
Type.ToParameter()));
}
if (In != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "in:{0}",
string.Join(",", In.Select(i => i.ToParameter()))));
}
if (Author.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "author:{0}", Author));
}
if (Assignee.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "assignee:{0}", Assignee));
}
if (Mentions.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "mentions:{0}", Mentions));
}
if (Commenter.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "commenter:{0}", Commenter));
}
if (Involves.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "involves:{0}", Involves));
}
if (Team.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "team:{0}", Team));
}
if (State.HasValue)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "state:{0}", State.Value.ToParameter()));
}
if (Labels != null)
{
parameters.AddRange(Labels.Select(label => string.Format(CultureInfo.InvariantCulture, "label:\"{0}\"", label)));
}
if (No.HasValue)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "no:{0}", No.Value.ToParameter()));
}
if (Language != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "language:\"{0}\"", Language.ToParameter()));
}
if (Is != null)
{
parameters.AddRange(Is.Select(x => string.Format(CultureInfo.InvariantCulture, "is:{0}", x.ToParameter())));
}
if (Created != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "created:{0}", Created));
}
if (Updated != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "updated:{0}", Updated));
}
if (Merged != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "merged:{0}", Merged));
}
if (Status.HasValue)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "status:{0}", Status.Value.ToParameter()));
}
if (Head.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "head:{0}", Head));
}
if (Base.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "base:{0}", Base));
}
if (Closed != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "closed:{0}", Closed));
}
if (Comments != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "comments:{0}", Comments));
}
if (User.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "user:{0}", User));
}
if (Repos.Any())
{
var invalidFormatRepos = Repos.Where(x => !x.IsNameWithOwnerFormat());
if (invalidFormatRepos.Any())
{
throw new RepositoryFormatException(invalidFormatRepos);
}
parameters.AddRange(Repos.Select(x => string.Format(CultureInfo.InvariantCulture, "repo:{0}", x)));
}
if (Milestone.IsNotBlank())
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "milestone:\"{0}\"", Milestone.EscapeDoubleQuotes()));
}
if (Archived != null)
{
parameters.Add(string.Format(CultureInfo.InvariantCulture, "archived:{0}", Archived.ToString().ToLower()));
}
// Add any exclusion parameters
if (Exclusions != null)
{
parameters.AddRange(Exclusions.MergedQualifiers());
}
return(new ReadOnlyCollection <string>(parameters));
}
private async Task FillSelectedSamples()
{
try
{
if (mainForm.TabsPane[0, 0].SelectedCells.Count <= 0)
{
mainForm.TabsPane[0, 1].DataSource = null;
return;
}
mainForm.TabsPane[0, 1].DataSource = null;
_chosenSamples.Clear();
_chosenSamples.Capacity = 199;
var country = mainForm.TabsPane[0, 0].SelectedCells[0].Value as string;
var client = mainForm.TabsPane[0, 0].SelectedCells[1].Value as string;
var year = mainForm.TabsPane[0, 0].SelectedCells[2].Value as string;
var set = mainForm.TabsPane[0, 0].SelectedCells[3].Value as string;
var set_index = mainForm.TabsPane[0, 0].SelectedCells[4].Value as string;
using (var r = new RegataContext())
{
var query = r.Samples.AsNoTracking()
.Where(s => s.CountryCode == country &&
s.ClientNumber == client &&
s.Year == year &&
s.SetNumber == set &&
s.SetIndex == set_index
);
Sample[] _tmpList = null;
#if NETFRAMEWORK
switch (_irrType)
{
case IrradiationType.sli:
_tmpList = await query.OrderBy(s => s.SampleNumber).ToArrayAsync();
break;
default:
_tmpList = await query.OrderBy(s => s.SampleNumber).ToArrayAsync();
break;
}
;
#else
_tmpList = _irrType switch
{
IrradiationType.sli => await query.OrderBy(s => s.SampleNumber).ToArrayAsync(),
_ => await query.OrderBy(s => s.SampleNumber).ToArrayAsync()
};
#endif
_chosenSamples.AddRange(_tmpList);
}
_chosenSamples.TrimExcess();
if (_displaySetsParam.Checked)
{
foreach (var ir in mainForm.MainRDGV.CurrentDbSet.Local)
{
var c = _chosenSamples.Where(cs => ir.CountryCode == cs.CountryCode &&
ir.ClientNumber == cs.ClientNumber &&
ir.Year == cs.Year &&
ir.SetNumber == cs.SetNumber &&
ir.SetIndex == cs.SetIndex &&
ir.SampleNumber == cs.SampleNumber).FirstOrDefault();
if (c != null)
{
_chosenSamples.Remove(c);
}
}
}
mainForm.TabsPane[0, 1].DataSource = _chosenSamples;
HideAllColumns(mainForm.TabsPane[0, 1]);
// "CountryCode", "ClientNumber", "Year", "SetNumber", "SetIndex",
ShowColumns(mainForm.TabsPane[0, 1], new string[] { "SampleNumber", "LLIWeight", "SLIWeight" });
Labels.SetControlsLabels(mainForm);
}
catch (Exception ex)
{
Report.Notify(new RCM.Message(Codes.ERR_UI_WF_FILL_SEL_SMP_UNREG)
{
DetailedText = ex.ToString()
});
}
}
public void AddLabel(string name)
{
Labels.Add(name);
}
public override int GetHashCode()
{
int hash = 1;
if (modelMetadataCase_ == ModelMetadataOneofCase.TranslationModelMetadata)
{
hash ^= TranslationModelMetadata.GetHashCode();
}
if (modelMetadataCase_ == ModelMetadataOneofCase.ImageClassificationModelMetadata)
{
hash ^= ImageClassificationModelMetadata.GetHashCode();
}
if (modelMetadataCase_ == ModelMetadataOneofCase.TextClassificationModelMetadata)
{
hash ^= TextClassificationModelMetadata.GetHashCode();
}
if (modelMetadataCase_ == ModelMetadataOneofCase.ImageObjectDetectionModelMetadata)
{
hash ^= ImageObjectDetectionModelMetadata.GetHashCode();
}
if (modelMetadataCase_ == ModelMetadataOneofCase.TextExtractionModelMetadata)
{
hash ^= TextExtractionModelMetadata.GetHashCode();
}
if (modelMetadataCase_ == ModelMetadataOneofCase.TextSentimentModelMetadata)
{
hash ^= TextSentimentModelMetadata.GetHashCode();
}
if (Name.Length != 0)
{
hash ^= Name.GetHashCode();
}
if (DisplayName.Length != 0)
{
hash ^= DisplayName.GetHashCode();
}
if (DatasetId.Length != 0)
{
hash ^= DatasetId.GetHashCode();
}
if (createTime_ != null)
{
hash ^= CreateTime.GetHashCode();
}
if (updateTime_ != null)
{
hash ^= UpdateTime.GetHashCode();
}
if (DeploymentState != 0)
{
hash ^= DeploymentState.GetHashCode();
}
if (Etag.Length != 0)
{
hash ^= Etag.GetHashCode();
}
hash ^= Labels.GetHashCode();
hash ^= (int)modelMetadataCase_;
if (_unknownFields != null)
{
hash ^= _unknownFields.GetHashCode();
}
return(hash);
}
internal void EnsureValid()
{
Labels.EnsureValid();
}
private IEnumerable <Label> MapLabels(Labels currentLabelPage)
{
return(currentLabelPage.Edges.Select(edge => edge.Node).Select(node => new Label(node.Name, node.Description, node.Color)).ToList());
}
public override string ToString()
{
return(Labels.Any()
? $"[{string.Join("][", Labels)}] {Name}"
: Name.ToString());
}
public void DrawStatusPanel(Graphics eGraphics, PanelStyle style, int unitPanelHeight)
{
var activeTile = _unit.CurrentLocation;
Draw.Text(eGraphics, Labels.For(LabelIndex.MovingUnits), style.Font, Colors.White, new Point(119, 10), true, true, Colors.Black,
1, 0);
// Show active unit info
var activeUnit = _game.ActiveUnit;
Draw.Unit(eGraphics, activeUnit, false, 1, new Point(7, 27));
// Show move points correctly
var commonMultiplier = _game.Rules.Cosmic.MovementMultiplier;
var remainingFullPoints = activeUnit.MovePoints / commonMultiplier;
var fractionalMove = activeUnit.MovePoints % commonMultiplier;
string moveText;
if (fractionalMove > 0)
{
var gcf = Utils.GreatestCommonFactor(fractionalMove, commonMultiplier);
moveText =
$"{Labels.For(LabelIndex.Moves)}: {(remainingFullPoints > 0 ? remainingFullPoints : "")} {fractionalMove / gcf}/{commonMultiplier / gcf}";
}
else
{
moveText = $"{Labels.For(LabelIndex.Moves)}: {remainingFullPoints}";
}
Draw.Text(eGraphics, moveText, style.Font, style.FrontColor, new Point(79, 25), false, false,
style.BackColor, 1, 1);
// Show other unit info
var cityName = (activeUnit.HomeCity == null) ? Labels.For(LabelIndex.NONE) : activeUnit.HomeCity.Name;
Draw.Text(eGraphics, cityName, style.Font, style.FrontColor, new Point(79, 43), false, false,
style.BackColor, 1, 1);
Draw.Text(eGraphics, _game.GetActiveCiv.Adjective, style.Font, style.FrontColor, new Point(79, 61), false,
false, style.BackColor, 1, 1);
var column = 83;
Draw.Text(eGraphics, activeUnit.Veteran ? $"{activeUnit.Name} ({Labels.For(LabelIndex.Veteran)})" :activeUnit.Name, style.Font, style.FrontColor, new Point(5, column), false,
false, style.BackColor, 1, 1);
column += 18;
if (activeTile != null)
{
Draw.Text(eGraphics, $"({activeTile.Name})", style.Font, style.FrontColor, new Point(5, column),
false,
false, style.BackColor, 1, 1);
// If road/railroad/irrigation/farmland/mine present
var improvements = activeTile.Improvements.Select(c => new
{ Imp = _game.TerrainImprovements[c.Improvement], Const = c }).ToList();
var improvementText = string.Join(", ",
improvements.Where(i => i.Imp.ExclusiveGroup != ImprovementTypes.DefenceGroup && !i.Imp.Negative)
.Select(i => i.Imp.Levels[i.Const.Level].Name));
if (!string.IsNullOrWhiteSpace(improvementText))
{
column += 18;
Draw.Text(eGraphics, $"({improvementText})", style.Font, style.FrontColor,
new Point(5, column), false,
false, style.BackColor, 1, 1);
}
// If airbase/fortress present
if (improvements.Any(i => i.Imp.ExclusiveGroup == ImprovementTypes.DefenceGroup))
{
column += 18;
var airbaseText = string.Join(", ",
improvements.Where(i => i.Imp.ExclusiveGroup == ImprovementTypes.DefenceGroup)
.Select(i => i.Imp.Levels[i.Const.Level].Name));
Draw.Text(eGraphics, $"({airbaseText})", style.Font, style.FrontColor, new Point(5, column),
false,
false, style.BackColor, 1, 1);
}
// If pollution present
var pollutionText = string.Join(", ",
improvements.Where(i => i.Imp.Negative)
.Select(i => i.Imp.Levels[i.Const.Level].Name));
if (!string.IsNullOrWhiteSpace(pollutionText))
{
column += 18;
Draw.Text(eGraphics, $"({pollutionText})", style.Font, style.FrontColor, new Point(5, column), false,
false,
style.BackColor, 1, 1);
}
column += 5;
// Show info for other units on the tile
int drawCount = 0;
foreach (var unit in activeTile.UnitsHere.Where(u => u != activeUnit))
{
// First check if there is vertical space still left for drawing in panel
if (column + 69 > unitPanelHeight)
{
break;
}
// Draw unit
Draw.Unit(eGraphics, unit, false, 1, new Point(7, column + 27));
// Show other unit info
column += 20;
cityName = (unit.HomeCity == null) ? Labels.For(LabelIndex.NONE) : unit.HomeCity.Name;
Draw.Text(eGraphics, cityName, style.Font, style.FrontColor, new Point(80, column), false,
false,
style.BackColor, 1, 1);
column += 18;
Draw.Text(eGraphics, _game.Order2string(unit.Order), style.Font, style.FrontColor,
new Point(80, column),
false, false, style.BackColor, 1, 1);
column += 18;
Draw.Text(eGraphics, unit.Veteran ? $"{unit.Name} ({Labels.For(LabelIndex.Veteran)})" : unit.Name, style.Font, style.FrontColor, new Point(80, column), false,
false,
style.BackColor, 1, 1);
//System.Diagnostics.Debug.WriteLine($"{unit.Name} drawn");
drawCount++;
}
// If not all units were drawn print a message
if (activeTile.UnitsHere.Count - 1 != drawCount) // -1 because you must not count in active unit
{
column += 22;
moveText = activeTile.UnitsHere.Count - 1 - drawCount == 1 ? "Unit" : "Units";
Draw.Text(eGraphics, $"({activeTile.UnitsHere.Count - 1 - drawCount} More {moveText})",
style.Font,
style.FrontColor, new Point(9, column), false, false, style.BackColor, 1, 1);
}
}
}
/// <summary>
/// Allows this instance to execute custom logic during its <c>Update</c>.
/// </summary>
/// <param name="gameTime">The game time.</param>
/// <remarks>
/// This method will not be executed if the <see cref="T:WaveEngine.Framework.Component" />, or the <see cref="T:WaveEngine.Framework.Entity" />
/// owning it are not <c>Active</c>.
/// </remarks>
protected override void Update(TimeSpan gameTime)
{
var virtualScreenHeight = WaveServices.ViewportManager.BottomEdge - WaveServices.ViewportManager.TopEdge;
foreach (RocksBlock block in this.visibleBlocks.ToList())
{
block.Transform2D.Y += scrollVelocity * (float)gameTime.TotalMilliseconds;
if (block.CheckStarCollision(this.squidCollider))
{
this.soundManager.PlaySound(SoundManager.SOUNDS.Star);
this.scene.CurrentScore++;
}
bool gameOverDetected = false;
if (block.CheckRockCollision(this.squidCollider))
{
this.soundManager.PlaySound(SoundManager.SOUNDS.RockCrash);
gameOverDetected = true;
}
else if (block.CheckJellyCollision(this.squidCollider))
{
this.soundManager.PlaySound(SoundManager.SOUNDS.JellyCrash);
gameOverDetected = true;
}
if (gameOverDetected)
{
this.scene.OpenGameOver();
}
var diff = block.Transform2D.Y - WaveServices.ViewportManager.BottomEdge;
if (diff > 0)
{
// Remove this block
block.Reset();
this.visibleBlocks.Remove(block);
block.Entity.Enabled = false;
// Add a new block instead
var selectedBlock = this.avaibleBlocks[WaveServices.Random.Next(this.avaibleBlocks.Count)];
selectedBlock.Transform2D.Y = diff - virtualScreenHeight;
this.avaibleBlocks.Remove(selectedBlock);
this.visibleBlocks.Add(selectedBlock);
selectedBlock.Entity.Enabled = true;
// Set removed block as avaible again
this.avaibleBlocks.Add(block);
}
}
// Decrease scroll velocity
if (this.scrollVelocity > this.MIN_SCROLL_VELOCITY)
{
this.scrollVelocity -= 0.01f * (float)gameTime.TotalSeconds * 60;
}
#if DEBUG
var blockTypesStr = string.Join(", ", this.visibleBlocks.Select(vb => vb.BlockType.ToString()));
Labels.Add("Block types", blockTypesStr);
#endif
}
internal ScriptLocalScopeBinder(Labels labels, Binder next) : base(next)
{
_labels = labels;
}
public override int GetHashCode()
{
int hash = 1;
if (Id.Length != 0)
{
hash ^= Id.GetHashCode();
}
if (FolderId.Length != 0)
{
hash ^= FolderId.GetHashCode();
}
if (createdAt_ != null)
{
hash ^= CreatedAt.GetHashCode();
}
if (Name.Length != 0)
{
hash ^= Name.GetHashCode();
}
if (Description.Length != 0)
{
hash ^= Description.GetHashCode();
}
hash ^= Labels.GetHashCode();
if (TypeId.Length != 0)
{
hash ^= TypeId.GetHashCode();
}
if (ZoneId.Length != 0)
{
hash ^= ZoneId.GetHashCode();
}
if (Size != 0L)
{
hash ^= Size.GetHashCode();
}
if (BlockSize != 0L)
{
hash ^= BlockSize.GetHashCode();
}
hash ^= productIds_.GetHashCode();
if (Status != global::Yandex.Cloud.Compute.V1.Disk.Types.Status.Unspecified)
{
hash ^= Status.GetHashCode();
}
if (sourceCase_ == SourceOneofCase.SourceImageId)
{
hash ^= SourceImageId.GetHashCode();
}
if (sourceCase_ == SourceOneofCase.SourceSnapshotId)
{
hash ^= SourceSnapshotId.GetHashCode();
}
hash ^= instanceIds_.GetHashCode();
if (diskPlacementPolicy_ != null)
{
hash ^= DiskPlacementPolicy.GetHashCode();
}
hash ^= (int)sourceCase_;
if (_unknownFields != null)
{
hash ^= _unknownFields.GetHashCode();
}
return(hash);
}
public bool Equals(Disk other)
{
if (ReferenceEquals(other, null))
{
return(false);
}
if (ReferenceEquals(other, this))
{
return(true);
}
if (Id != other.Id)
{
return(false);
}
if (FolderId != other.FolderId)
{
return(false);
}
if (!object.Equals(CreatedAt, other.CreatedAt))
{
return(false);
}
if (Name != other.Name)
{
return(false);
}
if (Description != other.Description)
{
return(false);
}
if (!Labels.Equals(other.Labels))
{
return(false);
}
if (TypeId != other.TypeId)
{
return(false);
}
if (ZoneId != other.ZoneId)
{
return(false);
}
if (Size != other.Size)
{
return(false);
}
if (BlockSize != other.BlockSize)
{
return(false);
}
if (!productIds_.Equals(other.productIds_))
{
return(false);
}
if (Status != other.Status)
{
return(false);
}
if (SourceImageId != other.SourceImageId)
{
return(false);
}
if (SourceSnapshotId != other.SourceSnapshotId)
{
return(false);
}
if (!instanceIds_.Equals(other.instanceIds_))
{
return(false);
}
if (!object.Equals(DiskPlacementPolicy, other.DiskPlacementPolicy))
{
return(false);
}
if (SourceCase != other.SourceCase)
{
return(false);
}
return(Equals(_unknownFields, other._unknownFields));
}
public Perceptron(DotFeatures traindat, Labels trainlab) : this(modshogunPINVOKE.new_Perceptron__SWIG_1(DotFeatures.getCPtr(traindat), Labels.getCPtr(trainlab)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
internal static HandleRef getCPtr(Labels obj)
{
return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr);
}
public SubGradientSVM(double C, DotFeatures traindat, Labels trainlab) : this(modshogunPINVOKE.new_SubGradientSVM__SWIG_1(C, DotFeatures.getCPtr(traindat), Labels.getCPtr(trainlab)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public void ImmediateValidationForAdd()
{
var labels = new Labels();
labels.AddLabel("test-1").AddLabel("test.2");
}
/// <inheritdoc />
public bool Equals([AllowNull] Sunburst other)
{
if (other == null)
{
return(false);
}
if (ReferenceEquals(this, other))
{
return(true);
}
return
((
Type == other.Type ||
Type != null &&
Type.Equals(other.Type)
) &&
(
Visible == other.Visible ||
Visible != null &&
Visible.Equals(other.Visible)
) &&
(
Opacity == other.Opacity ||
Opacity != null &&
Opacity.Equals(other.Opacity)
) &&
(
Name == other.Name ||
Name != null &&
Name.Equals(other.Name)
) &&
(
UId == other.UId ||
UId != null &&
UId.Equals(other.UId)
) &&
(
Equals(Ids, other.Ids) ||
Ids != null && other.Ids != null &&
Ids.SequenceEqual(other.Ids)
) &&
(
Equals(CustomData, other.CustomData) ||
CustomData != null && other.CustomData != null &&
CustomData.SequenceEqual(other.CustomData)
) &&
(
Meta == other.Meta ||
Meta != null &&
Meta.Equals(other.Meta)
) &&
(
Equals(MetaArray, other.MetaArray) ||
MetaArray != null && other.MetaArray != null &&
MetaArray.SequenceEqual(other.MetaArray)
) &&
(
HoverLabel == other.HoverLabel ||
HoverLabel != null &&
HoverLabel.Equals(other.HoverLabel)
) &&
(
Stream == other.Stream ||
Stream != null &&
Stream.Equals(other.Stream)
) &&
(
Equals(Transforms, other.Transforms) ||
Transforms != null && other.Transforms != null &&
Transforms.SequenceEqual(other.Transforms)
) &&
(
UiRevision == other.UiRevision ||
UiRevision != null &&
UiRevision.Equals(other.UiRevision)
) &&
(
Equals(Labels, other.Labels) ||
Labels != null && other.Labels != null &&
Labels.SequenceEqual(other.Labels)
) &&
(
Equals(Parents, other.Parents) ||
Parents != null && other.Parents != null &&
Parents.SequenceEqual(other.Parents)
) &&
(
Equals(Values, other.Values) ||
Values != null && other.Values != null &&
Values.SequenceEqual(other.Values)
) &&
(
BranchValues == other.BranchValues ||
BranchValues != null &&
BranchValues.Equals(other.BranchValues)
) &&
(
Count == other.Count ||
Count != null &&
Count.Equals(other.Count)
) &&
(
Level == other.Level ||
Level != null &&
Level.Equals(other.Level)
) &&
(
MaxDepth == other.MaxDepth ||
MaxDepth != null &&
MaxDepth.Equals(other.MaxDepth)
) &&
(
Marker == other.Marker ||
Marker != null &&
Marker.Equals(other.Marker)
) &&
(
Leaf == other.Leaf ||
Leaf != null &&
Leaf.Equals(other.Leaf)
) &&
(
Equals(Text, other.Text) ||
Text != null && other.Text != null &&
Text.SequenceEqual(other.Text)
) &&
(
TextInfo == other.TextInfo ||
TextInfo != null &&
TextInfo.Equals(other.TextInfo)
) &&
(
TextTemplate == other.TextTemplate ||
TextTemplate != null &&
TextTemplate.Equals(other.TextTemplate)
) &&
(
Equals(TextTemplateArray, other.TextTemplateArray) ||
TextTemplateArray != null && other.TextTemplateArray != null &&
TextTemplateArray.SequenceEqual(other.TextTemplateArray)
) &&
(
HoverText == other.HoverText ||
HoverText != null &&
HoverText.Equals(other.HoverText)
) &&
(
Equals(HoverTextArray, other.HoverTextArray) ||
HoverTextArray != null && other.HoverTextArray != null &&
HoverTextArray.SequenceEqual(other.HoverTextArray)
) &&
(
HoverInfo == other.HoverInfo ||
HoverInfo != null &&
HoverInfo.Equals(other.HoverInfo)
) &&
(
Equals(HoverInfoArray, other.HoverInfoArray) ||
HoverInfoArray != null && other.HoverInfoArray != null &&
HoverInfoArray.SequenceEqual(other.HoverInfoArray)
) &&
(
HoverTemplate == other.HoverTemplate ||
HoverTemplate != null &&
HoverTemplate.Equals(other.HoverTemplate)
) &&
(
Equals(HoverTemplateArray, other.HoverTemplateArray) ||
HoverTemplateArray != null && other.HoverTemplateArray != null &&
HoverTemplateArray.SequenceEqual(other.HoverTemplateArray)
) &&
(
TextFont == other.TextFont ||
TextFont != null &&
TextFont.Equals(other.TextFont)
) &&
(
InsideTextOrientation == other.InsideTextOrientation ||
InsideTextOrientation != null &&
InsideTextOrientation.Equals(other.InsideTextOrientation)
) &&
(
InsideTextFont == other.InsideTextFont ||
InsideTextFont != null &&
InsideTextFont.Equals(other.InsideTextFont)
) &&
(
OutsideTextFont == other.OutsideTextFont ||
OutsideTextFont != null &&
OutsideTextFont.Equals(other.OutsideTextFont)
) &&
(
Domain == other.Domain ||
Domain != null &&
Domain.Equals(other.Domain)
) &&
(
IdsSrc == other.IdsSrc ||
IdsSrc != null &&
IdsSrc.Equals(other.IdsSrc)
) &&
(
CustomDataSrc == other.CustomDataSrc ||
CustomDataSrc != null &&
CustomDataSrc.Equals(other.CustomDataSrc)
) &&
(
MetaSrc == other.MetaSrc ||
MetaSrc != null &&
MetaSrc.Equals(other.MetaSrc)
) &&
(
LabelsSrc == other.LabelsSrc ||
LabelsSrc != null &&
LabelsSrc.Equals(other.LabelsSrc)
) &&
(
ParentsSrc == other.ParentsSrc ||
ParentsSrc != null &&
ParentsSrc.Equals(other.ParentsSrc)
) &&
(
ValuesSrc == other.ValuesSrc ||
ValuesSrc != null &&
ValuesSrc.Equals(other.ValuesSrc)
) &&
(
TextSrc == other.TextSrc ||
TextSrc != null &&
TextSrc.Equals(other.TextSrc)
) &&
(
TextTemplateSrc == other.TextTemplateSrc ||
TextTemplateSrc != null &&
TextTemplateSrc.Equals(other.TextTemplateSrc)
) &&
(
HoverTextSrc == other.HoverTextSrc ||
HoverTextSrc != null &&
HoverTextSrc.Equals(other.HoverTextSrc)
) &&
(
HoverInfoSrc == other.HoverInfoSrc ||
HoverInfoSrc != null &&
HoverInfoSrc.Equals(other.HoverInfoSrc)
) &&
(
HoverTemplateSrc == other.HoverTemplateSrc ||
HoverTemplateSrc != null &&
HoverTemplateSrc.Equals(other.HoverTemplateSrc)
));
}
static void Main(string[] args)
{
var rate = new RateV40()
{
ShipDate = DateTime.Today.AddDays(5),
From = new Address()
{
State = "CA",
ZIPCode = "92128"
},
To = new Address()
{
State = "CA",
ZIPCode = "90245"
},
WeightLb = 1,
};
var returnedRates = Rates.Get(rate);
foreach (var returnedRate in returnedRates)
{
Console.WriteLine($"Service: {returnedRate.ServiceDescription} = ${returnedRate.Amount}");
}
var labelRate = new RateV40()
{
ShipDate = DateTime.Today.AddDays(5),
From = new Address()
{
FirstName = "Wade",
LastName = "Wilson",
Address1 = "3420 Ocean Park Bl",
Address2 = "Ste 1000",
City = "Santa Monica",
State = "CA",
ZIPCode = "92128"
},
To = new Address()
{
FirstName = "Charles",
LastName = "Xavier",
Address1 = "1900 E Grand Ave",
City = "El Segundo",
State = "CA",
ZIPCode = "90245"
},
Amount = 5,
WeightLb = 2,
WeightOz = 0,
PackageType = PackageTypeV11.Package,
Length = 5,
Width = 5,
Height = 5,
ServiceType = ServiceType.USPM,
};
var labelResponse = Labels.Create(labelRate, Guid.NewGuid().ToString(), "99999");
Console.WriteLine($"Label URL: {labelResponse.URL}");
}
public WDSVMOcas(double C, int d, int from_d, StringByteFeatures traindat, Labels trainlab) : this(modshogunPINVOKE.new_WDSVMOcas__SWIG_2(C, d, from_d, StringByteFeatures.getCPtr(traindat), Labels.getCPtr(trainlab)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
protected bool TryGetLabel(int label, out int position)
{
return(Labels.TryGetValue(label, out position));
}
public bool IsLabel(string s)
{
return(Labels.ContainsKey(s));
}
//imported constructor
public NPCKHeader(BinaryReader br, SupportedGames Mode, string fileName)
{
mode = Mode;
string labelPath = Directory.GetCurrentDirectory() + "/" + mode.ToString() + "/PCK/" + fileName + ".lbl";
if (File.Exists(labelPath))
{
MessageBoxResult labelRead = MessageBox.Show("Label file found. Read labels?", "Labels", MessageBoxButton.YesNo);
if (labelRead == MessageBoxResult.Yes)
{
labels = new Labels(XmlReader.Create(labelPath));
}
}
char[] magicBytes = br.ReadChars(4);
uint headerLen = br.ReadUInt32();
unkn2 = br.ReadUInt32();
languageLength = br.ReadUInt32();
bnkTableLength = br.ReadUInt32();
wemTableLength = br.ReadUInt32();
unknStructLength = br.ReadUInt32();
long stringHeaderStart = br.BaseStream.Position;
uint stringCount = br.ReadUInt32();
for (int i = 0; i < stringCount; i++)
{
PCKString stringData = new PCKString(br, Mode, stringHeaderStart);
pckStrings.Add(stringData);
}
br.BaseStream.Seek(stringHeaderStart + languageLength, SeekOrigin.Begin);
for (int i = 0; i < bnkTableLength / 4; i++)
{
br.ReadUInt32();
}
//this is 4-aligned at least in RE Engine games
uint wemACount = br.ReadUInt32();
for (int i = 0; i < wemACount; i++)
{
uint id = br.ReadUInt32();
uint one = br.ReadUInt32();
uint length = br.ReadUInt32();
uint offset = br.ReadUInt32();
uint languageEnum = br.ReadUInt32();
int workingOffset = (int)br.BaseStream.Position;
br.BaseStream.Seek(offset, SeekOrigin.Begin);
byte[] file = br.ReadBytes((int)length);
br.BaseStream.Seek(workingOffset, SeekOrigin.Begin);
string name;
if (labels.wemLabels.ContainsKey(id))
{
name = labels.wemLabels[id];
}
else
{
name = "Imported Wem " + i;
}
Wem newWem = new Wem(name, id, file, languageEnum);
WemList.Add(newWem);
}
//the unknStruct uint is right here, but we've already read what we need
}
public void ImportData(AwesomeReader ar)
{
// 280 bytes
Indentifier = ar.ReadInt64();
SongType = ar.ReadInt32();
ar.ReadInt32(); // Should be zero.
Title = ar.ReadInt64();
Artist = ar.ReadInt64();
Album = ar.ReadInt64();
Description = ar.ReadInt64();
LegendTag = ar.ReadInt64();
SongLength = ar.ReadSingle();
GuitarIntensity = ar.ReadSingle();
BassIntensity = ar.ReadSingle();
VoxIntensity = ar.ReadSingle();
EraTag = ar.ReadInt64();
Year = ar.ReadInt32();
ar.ReadInt32(); // Should be zero
#region Vox Tuning
VoxTuningName = ar.ReadInt64();
// Reads 1st string info.
ar.ReadInt16();
VoxRealTuning1 = ar.ReadByte();
VoxOffsetTuning1 = ar.ReadByte();
// Reads 2nd string info.
ar.ReadInt16();
VoxRealTuning2 = ar.ReadByte();
VoxOffsetTuning2 = ar.ReadByte();
// Reads 3rd string info.
ar.ReadInt16();
VoxRealTuning3 = ar.ReadByte();
VoxOffsetTuning3 = ar.ReadByte();
// Reads 4th string info.
ar.ReadInt16();
VoxRealTuning4 = ar.ReadByte();
VoxOffsetTuning4 = ar.ReadByte();
// Reads 5th string info.
ar.ReadInt16();
VoxRealTuning5 = ar.ReadByte();
VoxOffsetTuning5 = ar.ReadByte();
// Reads 6th string info.
ar.ReadInt16();
VoxRealTuning6 = ar.ReadByte();
VoxOffsetTuning6 = ar.ReadByte();
ar.ReadInt64(); // Should be zero'd
#endregion
#region Guitar Tuning
GuitarTuningName = ar.ReadInt64();
// Reads 1st string info.
ar.ReadInt16();
GuitarRealTuning1 = ar.ReadByte();
GuitarOffsetTuning1 = ar.ReadByte();
// Reads 2nd string info.
ar.ReadInt16();
GuitarRealTuning2 = ar.ReadByte();
GuitarOffsetTuning2 = ar.ReadByte();
// Reads 3rd string info.
ar.ReadInt16();
GuitarRealTuning3 = ar.ReadByte();
GuitarOffsetTuning3 = ar.ReadByte();
// Reads 4th string info.
ar.ReadInt16();
GuitarRealTuning4 = ar.ReadByte();
GuitarOffsetTuning4 = ar.ReadByte();
// Reads 5th string info.
ar.ReadInt16();
GuitarRealTuning5 = ar.ReadByte();
GuitarOffsetTuning5 = ar.ReadByte();
// Reads 6th string info.
ar.ReadInt16();
GuitarRealTuning6 = ar.ReadByte();
GuitarOffsetTuning6 = ar.ReadByte();
ar.ReadInt64(); // Should be zero'd
#endregion
#region Bass Tuning
BassTuningName = ar.ReadInt64();
// Reads 1st string info.
ar.ReadInt16();
BassRealTuning1 = ar.ReadByte();
BassOffsetTuning1 = ar.ReadByte();
// Reads 2nd string info.
ar.ReadInt16();
BassRealTuning2 = ar.ReadByte();
BassOffsetTuning2 = ar.ReadByte();
// Reads 3rd string info.
ar.ReadInt16();
BassRealTuning3 = ar.ReadByte();
BassOffsetTuning3 = ar.ReadByte();
// Reads 4th string info.
ar.ReadInt16();
BassRealTuning4 = ar.ReadByte();
BassOffsetTuning4 = ar.ReadByte();
// Reads 5th string info.
ar.ReadInt16();
BassRealTuning5 = ar.ReadByte();
BassOffsetTuning5 = ar.ReadByte();
// Reads 6th string info.
ar.ReadInt16();
BassRealTuning6 = ar.ReadByte();
BassOffsetTuning6 = ar.ReadByte();
ar.ReadInt64(); // Should be zero'd
#endregion
// Reads labels.
int count = ar.ReadInt32();
int offset = ar.ReadInt32();
long previousPosition = ar.BaseStream.Position;
ar.BaseStream.Position += offset - 4;
for (int i = 0; i < count; i++)
{
Labels.Add(ar.ReadInt64());
}
ar.BaseStream.Position = previousPosition;
LickPath = ar.ReadInt64();
TexturePath = ar.ReadInt64();
PreviewPath = ar.ReadInt64();
// Reads technique tags.
count = ar.ReadInt32();
offset = ar.ReadInt32();
previousPosition = ar.BaseStream.Position;
ar.BaseStream.Position += offset - 4;
for (int i = 0; i < count; i++)
{
TechniqueTags.Add(ar.ReadInt64());
}
ar.BaseStream.Position = previousPosition;
// Reads genre tags.
count = ar.ReadInt32();
offset = ar.ReadInt32();
previousPosition = ar.BaseStream.Position;
ar.BaseStream.Position += offset - 4;
for (int i = 0; i < count; i++)
{
GenreTags.Add(ar.ReadInt64());
}
ar.BaseStream.Position = previousPosition;
ar.BaseStream.Position += 24;
}
public bool Equals(Model other)
{
if (ReferenceEquals(other, null))
{
return(false);
}
if (ReferenceEquals(other, this))
{
return(true);
}
if (!object.Equals(TranslationModelMetadata, other.TranslationModelMetadata))
{
return(false);
}
if (!object.Equals(ImageClassificationModelMetadata, other.ImageClassificationModelMetadata))
{
return(false);
}
if (!object.Equals(TextClassificationModelMetadata, other.TextClassificationModelMetadata))
{
return(false);
}
if (!object.Equals(ImageObjectDetectionModelMetadata, other.ImageObjectDetectionModelMetadata))
{
return(false);
}
if (!object.Equals(TextExtractionModelMetadata, other.TextExtractionModelMetadata))
{
return(false);
}
if (!object.Equals(TextSentimentModelMetadata, other.TextSentimentModelMetadata))
{
return(false);
}
if (Name != other.Name)
{
return(false);
}
if (DisplayName != other.DisplayName)
{
return(false);
}
if (DatasetId != other.DatasetId)
{
return(false);
}
if (!object.Equals(CreateTime, other.CreateTime))
{
return(false);
}
if (!object.Equals(UpdateTime, other.UpdateTime))
{
return(false);
}
if (DeploymentState != other.DeploymentState)
{
return(false);
}
if (Etag != other.Etag)
{
return(false);
}
if (!Labels.Equals(other.Labels))
{
return(false);
}
if (ModelMetadataCase != other.ModelMetadataCase)
{
return(false);
}
return(Equals(_unknownFields, other._unknownFields));
}
public GremlinStoreVariable(GremlinToSqlContext projectContext, string sideEffectKey)
{
ProjectContext = projectContext;
SideEffectKey = sideEffectKey;
Labels.Add(sideEffectKey);
}
protected override string InnerTranslate()
{
return($@"{Labels.Translate()}
{Statements.Translate()}");
}
/// <inheritdoc />
public override int GetHashCode()
{
unchecked // Overflow is fine, just wrap
{
var hashCode = 41;
if (Type != null)
{
hashCode = hashCode * 59 + Type.GetHashCode();
}
if (Visible != null)
{
hashCode = hashCode * 59 + Visible.GetHashCode();
}
if (Opacity != null)
{
hashCode = hashCode * 59 + Opacity.GetHashCode();
}
if (Name != null)
{
hashCode = hashCode * 59 + Name.GetHashCode();
}
if (UId != null)
{
hashCode = hashCode * 59 + UId.GetHashCode();
}
if (Ids != null)
{
hashCode = hashCode * 59 + Ids.GetHashCode();
}
if (CustomData != null)
{
hashCode = hashCode * 59 + CustomData.GetHashCode();
}
if (Meta != null)
{
hashCode = hashCode * 59 + Meta.GetHashCode();
}
if (MetaArray != null)
{
hashCode = hashCode * 59 + MetaArray.GetHashCode();
}
if (HoverLabel != null)
{
hashCode = hashCode * 59 + HoverLabel.GetHashCode();
}
if (Stream != null)
{
hashCode = hashCode * 59 + Stream.GetHashCode();
}
if (Transforms != null)
{
hashCode = hashCode * 59 + Transforms.GetHashCode();
}
if (UiRevision != null)
{
hashCode = hashCode * 59 + UiRevision.GetHashCode();
}
if (Labels != null)
{
hashCode = hashCode * 59 + Labels.GetHashCode();
}
if (Parents != null)
{
hashCode = hashCode * 59 + Parents.GetHashCode();
}
if (Values != null)
{
hashCode = hashCode * 59 + Values.GetHashCode();
}
if (BranchValues != null)
{
hashCode = hashCode * 59 + BranchValues.GetHashCode();
}
if (Count != null)
{
hashCode = hashCode * 59 + Count.GetHashCode();
}
if (Level != null)
{
hashCode = hashCode * 59 + Level.GetHashCode();
}
if (MaxDepth != null)
{
hashCode = hashCode * 59 + MaxDepth.GetHashCode();
}
if (Marker != null)
{
hashCode = hashCode * 59 + Marker.GetHashCode();
}
if (Leaf != null)
{
hashCode = hashCode * 59 + Leaf.GetHashCode();
}
if (Text != null)
{
hashCode = hashCode * 59 + Text.GetHashCode();
}
if (TextInfo != null)
{
hashCode = hashCode * 59 + TextInfo.GetHashCode();
}
if (TextTemplate != null)
{
hashCode = hashCode * 59 + TextTemplate.GetHashCode();
}
if (TextTemplateArray != null)
{
hashCode = hashCode * 59 + TextTemplateArray.GetHashCode();
}
if (HoverText != null)
{
hashCode = hashCode * 59 + HoverText.GetHashCode();
}
if (HoverTextArray != null)
{
hashCode = hashCode * 59 + HoverTextArray.GetHashCode();
}
if (HoverInfo != null)
{
hashCode = hashCode * 59 + HoverInfo.GetHashCode();
}
if (HoverInfoArray != null)
{
hashCode = hashCode * 59 + HoverInfoArray.GetHashCode();
}
if (HoverTemplate != null)
{
hashCode = hashCode * 59 + HoverTemplate.GetHashCode();
}
if (HoverTemplateArray != null)
{
hashCode = hashCode * 59 + HoverTemplateArray.GetHashCode();
}
if (TextFont != null)
{
hashCode = hashCode * 59 + TextFont.GetHashCode();
}
if (InsideTextOrientation != null)
{
hashCode = hashCode * 59 + InsideTextOrientation.GetHashCode();
}
if (InsideTextFont != null)
{
hashCode = hashCode * 59 + InsideTextFont.GetHashCode();
}
if (OutsideTextFont != null)
{
hashCode = hashCode * 59 + OutsideTextFont.GetHashCode();
}
if (Domain != null)
{
hashCode = hashCode * 59 + Domain.GetHashCode();
}
if (IdsSrc != null)
{
hashCode = hashCode * 59 + IdsSrc.GetHashCode();
}
if (CustomDataSrc != null)
{
hashCode = hashCode * 59 + CustomDataSrc.GetHashCode();
}
if (MetaSrc != null)
{
hashCode = hashCode * 59 + MetaSrc.GetHashCode();
}
if (LabelsSrc != null)
{
hashCode = hashCode * 59 + LabelsSrc.GetHashCode();
}
if (ParentsSrc != null)
{
hashCode = hashCode * 59 + ParentsSrc.GetHashCode();
}
if (ValuesSrc != null)
{
hashCode = hashCode * 59 + ValuesSrc.GetHashCode();
}
if (TextSrc != null)
{
hashCode = hashCode * 59 + TextSrc.GetHashCode();
}
if (TextTemplateSrc != null)
{
hashCode = hashCode * 59 + TextTemplateSrc.GetHashCode();
}
if (HoverTextSrc != null)
{
hashCode = hashCode * 59 + HoverTextSrc.GetHashCode();
}
if (HoverInfoSrc != null)
{
hashCode = hashCode * 59 + HoverInfoSrc.GetHashCode();
}
if (HoverTemplateSrc != null)
{
hashCode = hashCode * 59 + HoverTemplateSrc.GetHashCode();
}
return(hashCode);
}
}
public Task Load(bool forceDataRefresh)
{
return(Labels.SimpleCollectionLoad(Application.Client.Users[Username].Repositories[Repository].GetLabels(), forceDataRefresh));
}
public ApplicationResources()
{
current = this; // 自动绑定最后一个创建的对象.
lables = new Labels();
}
