Python - Contingency tables using sparse coordinate matrices(general confusion matrix)

Elegant Scipy

開発環境

• OS X El Capitan - Apple (OS)
• Emacs (Text Editor)
• Python 3.5 (プログラミング言語)

Elegant Scipy (Juan Nunez-iglesias (著)、Stéfan Van Der Walt (著)、Harriet Dashnow (著)、 O'Reilly Media)のChapter 5.(Contingency tables using sparse coordinate matrices)、Generic filters の Exercise(No. 3006) を取り組んでみる。

Exercise(No. 3006)

コード(Emacs)

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import numpy as np


def confusion_matrix1(pred, gt):
    cont = np.zeros((2, 2))
    for i, j in zip(pred, gt):
        cont[i, j] += 1
    return cont

if __name__ == '__main__':
    pred = np.array([0, 1, 0, 0, 1, 1, 1, 0, 1, 1])
    gt = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1])
    print(confusion_matrix1(pred, gt))

入出力結果(Terminal, IPython)

$ ./sample1.py
[[ 3.  1.]
 [ 2.  4.]]
$