Esempio n. 1
0
for i in range(1, 5):

    ind_seq = 'Seq' + repr(i)

    print(ind_seq)

    for j in range(0, n_of_seq):

        print(j)

        seq = input_data[ind_seq][j][0][0]

        EXP_Param = trainGD_EXP(seq, eps)

        PWL_Param = trainGD_PWL(seq, eps)

        QEXP_Param = trainGD_QEXP(seq, eps)

        RAY_Param = trainGD_RAY(seq, eps)

        llh_GD_EXP = np.append(llh_GD_EXP, EXP_Param['final_llh'])
        llh_GD_PWL = np.append(llh_GD_PWL, PWL_Param['final_llh'])
        llh_GD_QEXP = np.append(llh_GD_QEXP, QEXP_Param['final_llh'])
        llh_GD_RAY = np.append(llh_GD_RAY, RAY_Param['final_llh'])

        llh_GD_EXP_Renorm_alpha = np.append(llh_GD_EXP_Renorm_alpha,
                                            EXP_Param['llh_renorm_alpha'])
        llh_GD_PWL_Renorm_K = np.append(llh_GD_PWL_Renorm_K,
                                        PWL_Param['llh_renorm_K'])
        llh_GD_QEXP_Renorm_a = np.append(llh_GD_QEXP_Renorm_a,
Esempio n. 2
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llh_GD_PWL_Renorm_Kp = np.array([])

for kernel in kernel_list:

	print(kernel)

	for j in range(n_of_seq):

		print(j)

		seq = simulated_sequences[kernel + "_" + str(i)]

		EXP_Param = trainGD_EXP(seq,eps,M, method, train_method, train_frac, T)

		PWL_Param = trainGD_PWL(seq,eps,M,method, train_method, train_frac, T)

		QEXP_Param = trainGD_QEXP(seq,eps,M,method, train_method, train_frac, T)

		RAY_Param = trainGD_RAY(seq,eps,M,method, train_method, train_frac, T)

		GSS_Param = trainGD_GSS(seq,eps,M,method, train_method, train_frac, T)

		llh_GD_EXP = np.append(llh_GD_EXP,EXP_Param['final_llh'])
		llh_GD_PWL = np.append(llh_GD_PWL,PWL_Param['final_llh'])
		llh_GD_QEXP = np.append(llh_GD_QEXP,QEXP_Param['final_llh'])
		llh_GD_RAY = np.append(llh_GD_RAY,RAY_Param['final_llh'])
		llh_GD_GSS = np.append(llh_GD_GSS, GSS_Param['final_llh'])

		llh_GD_EXP_Renorm_alpha = np.append(llh_GD_EXP_Renorm_alpha,EXP_Param['llh_renorm_alpha'])
		llh_GD_PWL_Renorm_K = np.append(llh_GD_PWL_Renorm_K,PWL_Param['llh_renorm_K'])