test.py 文件源码

def testHMMs(inp_file="test_input.txt"):
    inp_vals = map(float, open("test_input.txt","r").read().strip().split(','))
    HMMs = pickle.load(open("trained_HMMs_saved.pkl","rb"))
    codebooks = pickle.load(open("all_codebooks.pkl","rb"))
    vs = pickle.load(open("size_mapping.pkl","rb"))

    results = {}

    for size in vs.keys():
        # organize input data into vectors of particular size
        c = 0
        vecs = []
        for i in range(len(inp_vals)/int(size)):
            vecs.append(inp_vals[c:c+size])
            c += size
        #print vecs
        # Vector Quantizing
        n = len(vecs)
        vq_seq = map(str,sp.vq(np.reshape(vecs,(n,size)), codebooks[size])[0])
        if len(vq_seq) > 0:
            diseases = vs[size]
            for disease in diseases:
                HMM_obj = HMM("initial.json")
                HMM_obj.A = HMMs[disease]["A"]
                HMM_obj.B = HMMs[disease]["B"]
                HMM_obj.pi = HMMs[disease]["pi"]
                prob = HMM_obj.forward_scaled(vq_seq)
                results[disease] = math.exp(prob)

    for i in HMMs.keys():
        if not results.has_key(i):
            results[i] = "Not Enough Data to Predict"

    print "RESULTS:"        
    for dis in results.keys():
        print dis.capitalize()+": "+str(results[dis])