shadowmsatmhmmcreator.java

马尔科夫模型的c语言实现

	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in13_s");


	modelmaker.setTransition("in14", "in15");
	modelmaker.setTransition("in14", "in25");
	modelmaker.setTransition("in14", "in26");
	modelmaker.setTransition("in14", "in14_s");
	modelmaker.setTransition("in14", "e");
	//tot = setChiSquareDistrib("in14", 9, 10, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in14");

	modelmaker.setTransition("in14_s", "in15");
	modelmaker.setTransition("in14_s", "in25");
	modelmaker.setTransition("in14_s", "in26");
	modelmaker.setTransition("in14_s", "e");
	m1 = modelmaker.getModule("in14_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in14_s");
	
	
	modelmaker.setTransition("in15", "in16");
	modelmaker.setTransition("in15", "in24");
	modelmaker.setTransition("in15", "in25");
	modelmaker.setTransition("in15", "in15_s");
	modelmaker.setTransition("in15", "e");
	//tot = setChiSquareDistrib("in15", 11, 12, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in15");
	
	modelmaker.setTransition("in15_s", "in16");
	modelmaker.setTransition("in15_s", "in24");
	modelmaker.setTransition("in15_s", "in25");
	modelmaker.setTransition("in15_s", "e");
	m1 = modelmaker.getModule("in15_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in15_s");
	

	modelmaker.setTransition("in16", "in17");
	modelmaker.setTransition("in16", "in23");
	modelmaker.setTransition("in16", "in24");
	modelmaker.setTransition("in16", "in16_s");
	modelmaker.setTransition("in16", "e");
	//tot = setChiSquareDistrib("in16", 13, 14, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in16");

	modelmaker.setTransition("in16_s", "in17");
	modelmaker.setTransition("in16_s", "in23");
	modelmaker.setTransition("in16_s", "in24");
	modelmaker.setTransition("in16_s", "e");
	m1 = modelmaker.getModule("in16_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in16_s");


	modelmaker.setTransition("in17", "in18");
	modelmaker.setTransition("in17", "in22");
	modelmaker.setTransition("in17", "in23");
	modelmaker.setTransition("in17", "in17_s");
	modelmaker.setTransition("in17", "e");
	//tot = setChiSquareDistrib("in17", 15, 16, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in17");

	modelmaker.setTransition("in17_s", "in18");
	modelmaker.setTransition("in17_s", "in22");
	modelmaker.setTransition("in17_s", "in23");
	modelmaker.setTransition("in17_s", "e");
	m1 = modelmaker.getModule("in17_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in17_s");


	modelmaker.setTransition("in18", "in19");
	modelmaker.setTransition("in18", "in21");
	modelmaker.setTransition("in18", "in22");
	modelmaker.setTransition("in18", "in18_s");
	modelmaker.setTransition("in18", "e");
	//tot = setChiSquareDistrib("in18", 17, 18, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in18");
	
	modelmaker.setTransition("in18_s", "in19");
	modelmaker.setTransition("in18_s", "in21");
	modelmaker.setTransition("in18_s", "in22");
	modelmaker.setTransition("in18_s", "e");
	m1 = modelmaker.getModule("in18_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in18_s");


	modelmaker.setTransition("in19", "in20");
	modelmaker.setTransition("in19", "in21");
	modelmaker.setTransition("in19", "inglob1");
	modelmaker.setTransition("in19", "in19_s");
	modelmaker.setTransition("in19", "e");
	//tot = setChiSquareDistrib("in19", 19, 20, f_i, q_i, distribSum, tot);
	modelmaker.initializeTransitionProbabilities("in19");
	
	modelmaker.setTransition("in19_s", "in20");
	modelmaker.setTransition("in19_s", "in21");
	modelmaker.setTransition("in19_s", "inglob1");
	modelmaker.setTransition("in19_s", "e");
	m1 = modelmaker.getModule("in19_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in19_s");


	modelmaker.setTransition("in20", "in21");
	modelmaker.setTransition("in20", "in20_s");
	modelmaker.setTransition("in20", "e");
	modelmaker.initializeTransitionProbabilities("in20");

	modelmaker.setTransition("in20_s", "in21");
	modelmaker.setTransition("in20_s", "e");
	m1 = modelmaker.getModule("in20_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in20_s");


	modelmaker.setTransition("in21", "in22");
	modelmaker.setTransition("in21", "in21_s");
	modelmaker.setTransition("in21", "e");
	modelmaker.initializeTransitionProbabilities("in21");
	
	modelmaker.setTransition("in21_s", "in22");
	modelmaker.setTransition("in21_s", "e");
	m1 = modelmaker.getModule("in21_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in21_s");


	modelmaker.setTransition("in22", "in23");
	modelmaker.setTransition("in22", "e");
	modelmaker.setTransition("in22", "in22_s");
	modelmaker.initializeTransitionProbabilities("in22");

	modelmaker.setTransition("in22_s", "in23");
	modelmaker.setTransition("in22_s", "e");
	m1 = modelmaker.getModule("in22_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in22_s");


	modelmaker.setTransition("in23", "in24");
	modelmaker.setTransition("in23", "in23_s");
	modelmaker.setTransition("in23", "e");
	modelmaker.initializeTransitionProbabilities("in23");
	
	modelmaker.setTransition("in23_s", "in24");
	modelmaker.setTransition("in23_s", "e");
	m1 = modelmaker.getModule("in23_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in23_s");

	modelmaker.setTransition("in24", "in25");
	modelmaker.setTransition("in24", "in24_s");
	modelmaker.setTransition("in24", "e");
	modelmaker.initializeTransitionProbabilities("in24");

	modelmaker.setTransition("in24_s", "in25");
	modelmaker.setTransition("in24_s", "e");
	m1 = modelmaker.getModule("in24_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in24_s");


	modelmaker.setTransition("in25", "in26");
	modelmaker.setTransition("in25", "in25_s");
	modelmaker.setTransition("in25", "e");
	modelmaker.initializeTransitionProbabilities("in25");

	modelmaker.setTransition("in25_s", "in26");
	modelmaker.setTransition("in25_s", "e");
	m1 = modelmaker.getModule("in25_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in25_s");


	modelmaker.setTransition("in26", "in27");
	modelmaker.setTransition("in26", "in26_s");
	modelmaker.setTransition("in26", "e");
	modelmaker.initializeTransitionProbabilities("in26");

	modelmaker.setTransition("in26_s", "in27");
	modelmaker.setTransition("in26_s", "e");
	m1 = modelmaker.getModule("in26_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in26_s");


	modelmaker.setTransition("in27", "in28");
	modelmaker.setTransition("in27", "in27_s");
	modelmaker.setTransition("in27", "e");
	modelmaker.initializeTransitionProbabilities("in27");

	modelmaker.setTransition("in27_s", "in28");
	modelmaker.setTransition("in27_s", "e");
	m1 = modelmaker.getModule("in27_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in27_s");


	modelmaker.setTransition("in28", "in29");
	modelmaker.setTransition("in28", "in28_s");
	modelmaker.setTransition("in28", "e");
	modelmaker.initializeTransitionProbabilities("in28");

	modelmaker.setTransition("in28_s", "in29");
	modelmaker.setTransition("in28_s", "e");
	m1 = modelmaker.getModule("in28_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in28_s");
	

	modelmaker.setTransition("in29", "ohelixi1");
	modelmaker.setTransition("in29", "in29_s");
	modelmaker.setTransition("in29", "e");
	modelmaker.initializeTransitionProbabilities("in29");

	modelmaker.setTransition("in29_s", "ohelixi1");
	modelmaker.setTransition("in29_s", "e");
	m1 = modelmaker.getModule("in29_s");
	l = m1.getVertices();
	v = ((Vertex)l.get(0));
	v.setTransitionProbability(v.getNumber(), gapLenProb);
	modelmaker.initializeTransitionProbabilities("in29_s");
	/////l鋑g in s