public TOPFeatures(TOPFeatures orig) : this(modshogunPINVOKE.new_TOPFeatures__SWIG_2(TOPFeatures.getCPtr(orig)), true) { if (modshogunPINVOKE.SWIGPendingException.Pending) { throw modshogunPINVOKE.SWIGPendingException.Retrieve(); } }
public TOPFeatures(TOPFeatures orig) : this(modshogunPINVOKE.new_TOPFeatures__SWIG_2(TOPFeatures.getCPtr(orig)), true) { if (modshogunPINVOKE.SWIGPendingException.Pending) throw modshogunPINVOKE.SWIGPendingException.Retrieve(); }
internal static HandleRef getCPtr(TOPFeatures obj) { return (obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr; }
internal static HandleRef getCPtr(TOPFeatures obj) { return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr); }
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); TOPFeatures feats_train = new TOPFeatures(10, pos, neg, false, false); 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); TOPFeatures feats_test = new TOPFeatures(10, pos_clone, neg_clone, false, false); 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; }