예제 #1
0
def HAR_Regularizer(ls_graph, ls_lb_tr, str_file, ls_lb_tl):

    ls_lb_nu = src.copy_list(ls_lb_tr)
    ls_lb_tlnu = src.copy_list(ls_lb_tl)
    src.configureLabels(ls_lb_nu, 0, -1)
    src.configureLabels(ls_lb_tlnu, 0, -1)

    #raw_input("--pausa-- ");

    flo_timestart = time()
    mtx_lb_pr = src.HarmonicRegularizer(ls_graph, ls_lb_nu)
    flo_timefinal = time() - flo_timestart

    # Getting Results

    ls_lb_pr = src.convert_to_list(mtx_lb_pr)
    ls_lb_prflo = src.float_list_normalization(ls_lb_pr)
    ls_temp_lb = ls_lb_prflo

    np.savetxt("Pr" + str_file, (tuple(ls_temp_lb) + tuple(ls_lb_tlnu)))

    ls_lb_alpha = src.generalizeAlphaCut(np.array(ls_lb_pr), 0, -1, 1)
    ls_lb_alphaint = src.int_list_normalization(ls_lb_alpha)

    flo_acc = src.accuracyTest(ls_lb_alphaint, ls_lb_tlnu)
    flo_TP, flo_TN, flo_FP, flo_FN = src.confussionMatrix(
        ls_lb_alphaint, ls_lb_tlnu)

    np.savetxt("Rs" + str_file,
               (flo_TP, flo_TN, flo_FP, flo_FN, flo_acc, flo_timefinal))

    print str_file + " done!"
    return ls_lb_pr
예제 #2
0
    #----- (begin) K GRAPH CONSTRUCTION (begin) -----#
    str_graph_type = "K"
    floint_graph_hyper = 2
    timestart = time()
    Gr_K = src.buildKGraph(data_proc, 2)
    # ----> Construction Method
    timefinal_gc = time() - timestart
    #----- (end) FULL GRAPH CONSTRUCTION (end) -----#

    #----- (begin) HARMONIC REGULARIZATION (begin) -----#
    print "< < Harmonic > >"
    # Checking Regularization
    str_reg_type = "Har"

    timestart = time()
    respH = src.HarmonicRegularizer(Gr_K, label_proc)
    # --------------------> Regulating
    timefinal_gr = time() - timestart

    respH = src.convert_to_list(respH)
    # Converting to list, the result of the regulation

    dataH = src.float_list_normalization(respH)
    # Mapping results as floats
    temp_respH = dataH
    string_nome_data_temp = string_nome_data + str_graph_type + str(
        floint_graph_hyper) + str_reg_type + "L" + str(int_per) + "%.txt"
    # Saving results of data
    np.savetxt(string_nome_data_temp, (temp_respH))

    repH = src.generalizeAlphaCut(np.array(respH), 0.5, 0, 1)