public static void Main() {
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
bool use_sign = false;
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(EAlphabet.DNA);
charfeat.set_features(fm_train_dna);
StringUlongFeatures feats_train = new StringUlongFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortUlongString preproc = new SortUlongString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
charfeat_test.set_features(fm_test_dna);
StringUlongFeatures feats_test = new StringUlongFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommUlongStringKernel kernel = new CommUlongStringKernel(feats_train, feats_train, use_sign);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
bool use_sign = false;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
double[] fm_test_real = Load.load_labels("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(EAlphabet.DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
HammingWordDistance distance = new HammingWordDistance(feats_train, feats_train, use_sign);
double[,] dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
double[,] dm_test = distance.get_distance_matrix();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
DoubleMatrix fm_test_real = Load.load_numbers("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order-1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
ManhattanWordDistance distance = new ManhattanWordDistance(feats_train, feats_train);
DoubleMatrix dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
DoubleMatrix dm_test = distance.get_distance_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 0;
bool reverse = false;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
String[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
double[,] fm_test_real = Load.load_numbers("../data/fm_test_real.dat");
StringCharFeatures charfeat = new StringCharFeatures(EAlphabet.DNA);
charfeat.set_features(fm_train_dna);
StringWordFeatures feats_train = new StringWordFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order - 1, order, gap, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
StringCharFeatures charfeat_test = new StringCharFeatures(EAlphabet.DNA);
charfeat_test.set_features(fm_test_dna);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat_test, order - 1, order, gap, reverse);
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
ManhattanWordDistance distance = new ManhattanWordDistance(feats_train, feats_train);
double[,] dm_train = distance.get_distance_matrix();
distance.init(feats_train, feats_test);
double[,] dm_test = distance.get_distance_matrix();
foreach (double item in dm_train)
{
Console.Write(item);
}
foreach (double item in dm_test)
{
Console.Write(item);
}
modshogun.exit_shogun();
}
public static void Main() {
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
double[] histogram = histo.get_histogram();
foreach(double item in histogram) {
Console.Write(item);
}
//int num_examples = feats.get_num_vectors();
//int num_param = histo.get_num_model_parameters();
//double[,] out_likelihood = histo.get_log_likelihood();
//double out_sample = histo.get_log_likelihood_sample();
modshogun.exit_shogun();
}
public static void Main() {
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
LinearHMM hmm = new LinearHMM(feats);
hmm.train();
hmm.get_transition_probs();
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
for(int j = 0; j < num_param; j++) {
hmm.get_log_derivative(j, i);
}
double[] out_likelihood = hmm.get_log_likelihood();
double out_sample = hmm.get_log_likelihood_sample();
}
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, reverse);
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, reverse);
SortWordString preproc = new SortWordString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommWordStringKernel kernel = new CommWordStringKernel(feats_train, feats_train, false);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
int degree = 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 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);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
bool reverse = false;
int order = 3;
int gap = 0;
int degree = 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 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);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test=kernel.get_kernel_matrix();
}
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);
BinaryLabels labels = new BinaryLabels(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);
BinaryLabels.obtain_from_generic(pie.apply()).get_labels();
double[,] km_test=kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
histo.get_histogram();
int num_examples = feats.get_num_vectors();
int num_param = histo.get_num_model_parameters();
DoubleMatrix out_likelihood = histo.get_log_likelihood();
double out_sample = histo.get_log_likelihood_sample();
ArrayList result = new ArrayList();
result.Add(histo);
result.Add(out_sample);
result.Add(out_likelihood);
modshogun.exit_shogun();
return result;
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
int degree = (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 charfeat = new StringCharFeatures(fm_train_dna, 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, DNA);
StringWordFeatures feats_test = new StringWordFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, false);
PolyMatchWordStringKernel kernel = new PolyMatchWordStringKernel(feats_train, feats_train, degree, true);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
public static void Main()
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = 3;
int gap = 4;
String[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order - 1, order, gap, reverse);
Histogram histo = new Histogram(feats);
histo.train();
double[] histogram = histo.get_histogram();
foreach (double item in histogram)
{
Console.Write(item);
}
//int num_examples = feats.get_num_vectors();
//int num_param = histo.get_num_model_parameters();
//double[,] out_likelihood = histo.get_log_likelihood();
//double out_sample = histo.get_log_likelihood_sample();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = (int)((int?)para[0]);
int M = (int)((int?)para[1]);
double pseudo = (double)((double?)para[2]);
int order = (int)((int?)para[3]);
int gap = (int)((int?)para[4]);
string[] fm_train_dna = Load.load_cubes("../data/fm_train_cube.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, CUBE);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
HMM hmm = new HMM(feats, N, M, pseudo);
hmm.train();
hmm.baum_welch_viterbi_train(BW_NORMAL);
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
{
for(int j = 0; j < num_param; j++)
{
hmm.get_log_derivative(j, i);
}
}
int best_path = 0;
int best_path_state = 0;
for(int i = 0; i < num_examples; i++)
{
best_path += hmm.best_path(i);
for(int j = 0; j < N; j++)
{
best_path_state += hmm.get_best_path_state(i, j);
}
}
DoubleMatrix lik_example = hmm.get_log_likelihood();
double lik_sample = hmm.get_log_likelihood_sample();
ArrayList result = new ArrayList();
result.Add(lik_example);
result.Add(lik_sample);
result.Add(hmm);
modshogun.exit_shogun();
return result;
}
public static void Main()
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = 1;
int M = 512;
double pseudo = 1e-5;
int order = 3;
int gap = 0;
string[] fm_train_dna = Load.load_cubes("../data/fm_train_cube.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.CUBE);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order - 1, order, gap, reverse);
HMM hmm = new HMM(feats, N, M, pseudo);
hmm.train();
hmm.baum_welch_viterbi_train(BaumWelchViterbiType.BW_NORMAL);
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
{
for (int j = 0; j < num_param; j++)
{
hmm.get_log_derivative(j, i);
}
}
int best_path = 0;
int best_path_state = 0;
for (int i = 0; i < num_examples; i++)
{
best_path += (int)hmm.best_path(i);
for (int j = 0; j < N; j++)
{
best_path_state += hmm.get_best_path_state(i, j);
}
}
double[] lik_example = hmm.get_log_likelihood();
double lik_sample = hmm.get_log_likelihood_sample();
modshogun.exit_shogun();
}
public static void Main()
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = 1;
int M = 512;
double pseudo = 1e-5;
int order = 3;
int gap = 0;
string[] fm_train_dna = Load.load_cubes("../data/fm_train_cube.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, EAlphabet.CUBE);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
HMM hmm = new HMM(feats, N, M, pseudo);
hmm.train();
hmm.baum_welch_viterbi_train(BaumWelchViterbiType.BW_NORMAL);
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
for(int j = 0; j < num_param; j++) {
hmm.get_log_derivative(j, i);
}
int best_path = 0;
int best_path_state = 0;
for(int i = 0; i < num_examples; i++){
best_path += (int)hmm.best_path(i);
for(int j = 0; j < N; j++)
best_path_state += hmm.get_best_path_state(i, j);
}
double[] lik_example = hmm.get_log_likelihood();
double lik_sample = hmm.get_log_likelihood_sample();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
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, 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, 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);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
pie.set_features(feats_test);
pie.apply().get_labels();
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
internal static void run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
PositionalPWM ppwm = new PositionalPWM();
ppwm.set_sigma(5.0);
ppwm.set_mean(10.0);
DoubleMatrix pwm = new DoubleMatrix(new double[][] {{0.0, 0.5, 0.1, 1.0}, {0.0, 0.5, 0.5, 0.0}, {1.0, 0.0, 0.4, 0.0}, {0.0, 0.0, 0.0, 0.0}});
//ppwm.set_pwm(DoubleMatrix.log(pwm));
ppwm.compute_w(20);
DoubleMatrix w = ppwm.get_w();
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);
BinaryLabels labels = new BinaryLabels(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);
BinaryLabels.obtain_from_generic(pie.apply()).get_labels();
double[,] km_test = kernel.get_kernel_matrix();
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
StringCharFeatures charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures feats = new StringWordFeatures(charfeat.get_alphabet());
feats.obtain_from_char(charfeat, order-1, order, gap, reverse);
LinearHMM hmm = new LinearHMM(feats);
hmm.train();
hmm.get_transition_probs();
int num_examples = feats.get_num_vectors();
int num_param = hmm.get_num_model_parameters();
for (int i = 0; i < num_examples; i++)
{
for(int j = 0; j < num_param; j++)
{
hmm.get_log_derivative(j, i);
}
}
DoubleMatrix out_likelihood = hmm.get_log_likelihood();
double out_sample = hmm.get_log_likelihood_sample();
ArrayList result = new ArrayList();
result.Add(hmm);
result.Add(out_sample);
result.Add(out_likelihood);
modshogun.exit_shogun();
return result;
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int order = (int)((int?)para[0]);
int gap = (int)((int?)para[1]);
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, DNA);
StringUlongFeatures feats_train = new StringUlongFeatures(charfeat.get_alphabet());
feats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
charfeat = new StringCharFeatures(fm_test_dna, DNA);
StringUlongFeatures feats_test = new StringUlongFeatures(charfeat.get_alphabet());
feats_test.obtain_from_char(charfeat, order-1, order, gap, reverse);
SortUlongString preproc = new SortUlongString();
preproc.init(feats_train);
feats_train.add_preprocessor(preproc);
feats_train.apply_preprocessor();
feats_test.add_preprocessor(preproc);
feats_test.apply_preprocessor();
CommUlongStringKernel kernel = new CommUlongStringKernel(feats_train, feats_train, false);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int num = 10;
int order = 7;
int gap = 0;
bool reverse = false;
string[] POS = new string[141];
for (int i = 0; i < 60; i++)
{
POS[i] = repeat("ACGT", 10);
}
for (int i = 61; i < 82; i++)
{
POS[i] = repeat("TTGT", 10);
}
for (int i = 83; i < 141; i++)
{
POS[i] = repeat("ACGT", 10);
}
string[] NEG = new string[141];
for (int i = 0; i < 60; i++)
{
NEG[i] = repeat("ACGT", 10);
}
for (int i = 61; i < 82; i++)
{
NEG[i] = repeat("TTGT", 10);
}
for (int i = 83; i < 141; i++)
{
NEG[i] = repeat("ACGT", 10);
}
string[] POSNEG = new string[282];
for (int i = 0; i < 141; i++)
{
POSNEG[i] = POS[i];
POSNEG[i + 141] = NEG[i];
}
for(int i = 0; i < 10; i++)
{
Alphabet alpha = new Alphabet(DNA);
StringCharFeatures traindat = new StringCharFeatures(alpha);
traindat.set_features(POSNEG);
StringWordFeatures trainudat = new StringWordFeatures(traindat.get_alphabet());
trainudat.obtain_from_char(traindat, order-1, order, gap, reverse);
SortWordString pre = new SortWordString();
pre.init(trainudat);
trainudat.add_preprocessor(pre);
trainudat.apply_preprocessor();
CommWordStringKernel spec = new CommWordStringKernel(10, false);
spec.set_normalizer(new IdentityKernelNormalizer());
spec.init(trainudat, trainudat);
DoubleMatrix K = spec.get_kernel_matrix();
}
modshogun.exit_shogun();
}
internal static ArrayList run(IList para)
{
bool reverse = false;
modshogun.init_shogun_with_defaults();
int N = (int)((int?)para[0]);
int M = (int)((int?)para[1]);
double pseudo = (double)((double?)para[2]);
int order = (int)((int?)para[3]);
int gap = (int)((int?)para[4]);
string[] fm_train_dna = Load.load_dna("../data/fm_train_dna.dat");
string[] fm_test_dna = Load.load_dna("../data/fm_test_dna.dat");
DoubleMatrix label_train_dna = Load.load_labels("../data/label_train_dna.dat");
ArrayList fm_hmm_pos_builder = new ArrayList();
ArrayList fm_hmm_neg_builder = new ArrayList();
for(int i = 0; i < label_train_dna.Columns; i++)
{
if (label_train_dna.get(i) == 1)
{
fm_hmm_pos_builder.Add(fm_train_dna[i]);
}
else
{
fm_hmm_neg_builder.Add(fm_train_dna[i]);
}
}
int pos_size = fm_hmm_pos_builder.Count;
int neg_size = fm_hmm_neg_builder.Count;
string[] fm_hmm_pos = new string[pos_size];
string[] fm_hmm_neg = new string[neg_size];
for (int i = 0; i < pos_size; i++)
{
fm_hmm_pos[i] = (string)fm_hmm_pos_builder[i];
}
for (int i = 0; i < neg_size; i++)
{
fm_hmm_pos[i] = (string)fm_hmm_neg_builder[i];
}
StringCharFeatures charfeat = new StringCharFeatures(fm_hmm_pos, DNA);
StringWordFeatures hmm_pos_train = new StringWordFeatures(charfeat.get_alphabet());
hmm_pos_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
HMM pos = new HMM(hmm_pos_train, N, M, pseudo);
pos.baum_welch_viterbi_train(BW_NORMAL);
charfeat = new StringCharFeatures(fm_hmm_neg, DNA);
StringWordFeatures hmm_neg_train = new StringWordFeatures(charfeat.get_alphabet());
hmm_neg_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
HMM neg = new HMM(hmm_neg_train, N, M, pseudo);
neg.baum_welch_viterbi_train(BW_NORMAL);
charfeat = new StringCharFeatures(fm_train_dna, DNA);
StringWordFeatures wordfeats_train = new StringWordFeatures(charfeat.get_alphabet());
wordfeats_train.obtain_from_char(charfeat, order-1, order, gap, reverse);
charfeat = new StringCharFeatures(fm_test_dna, DNA);
StringWordFeatures wordfeats_test = new StringWordFeatures(charfeat.get_alphabet());
wordfeats_test.obtain_from_char(charfeat, order-1, order, gap, reverse);
pos.set_observations(wordfeats_train);
neg.set_observations(wordfeats_train);
FKFeatures feats_train = new FKFeatures(10, pos, neg);
feats_train.set_opt_a(-1);
PolyKernel kernel = new PolyKernel(feats_train, feats_train, 1, true);
DoubleMatrix km_train = kernel.get_kernel_matrix();
HMM pos_clone = new HMM(pos);
HMM neg_clone = new HMM(neg);
pos_clone.set_observations(wordfeats_test);
neg_clone.set_observations(wordfeats_test);
FKFeatures feats_test = new FKFeatures(10, pos_clone, neg_clone);
feats_test.set_a(feats_train.get_a());
kernel.init(feats_train, feats_test);
DoubleMatrix km_test =kernel.get_kernel_matrix();
ArrayList result = new ArrayList();
result.Add(km_train);
result.Add(km_test);
result.Add(kernel);
modshogun.exit_shogun();
return result;
}
