test_metaswap.py 文件源码

def plot_swap_subject_cm(swappy,title,name):

    from sklearn.metrics import confusion_matrix
    import numpy as np


    subs = swappy.exportSubjectData()
    labs = getLabelReal(subs)

    # Compute confusion matrix
    cnf_matrix = confusion_matrix(labs['actual'], labs['predicted'])
    np.set_printoptions(precision=2)
    plt.figure()
    plot_confusion_matrix(cnf_matrix, classes=['Bogus','Real'],
                          normalize=False,
                          title=title)

    plt.savefig(name)
    plt.show()


    #import pandas as pd
    #ps = pd.Series([(labs['actual'][x],labs['predicted'][x]) for x in range(0, len(labs['actual']))])
    #counts = ps.value_counts()
    #counts