Mercurial > hg > plosone_underreview
annotate tests/test_classification.py @ 105:edd82eb89b4b branch-tests tip
Merge
author | Maria Panteli |
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date | Sun, 15 Oct 2017 13:36:59 +0100 |
parents | f9513664fe42 |
children |
rev | line source |
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m@30 | 1 # -*- coding: utf-8 -*- |
m@30 | 2 """ |
m@30 | 3 Created on Fri Sep 1 19:11:52 2017 |
m@30 | 4 |
m@30 | 5 @author: mariapanteli |
m@30 | 6 """ |
m@30 | 7 |
m@30 | 8 import pytest |
m@30 | 9 |
m@30 | 10 import numpy as np |
m@30 | 11 from sklearn.model_selection import train_test_split |
m@30 | 12 |
m@30 | 13 import scripts.classification as classification |
m@30 | 14 |
m@30 | 15 |
m@30 | 16 def test_confusion_matrix(): |
m@30 | 17 X = np.random.randn(100, 3) |
m@30 | 18 # create 2 classes by shifting the entries of half the samples |
m@30 | 19 X[-50:, :] = X[-50:, :] + 10 |
m@30 | 20 Y = np.concatenate([np.repeat('a', 50), np.repeat('b', 50)]) |
m@30 | 21 X_train, X_test, Y_train, Y_test = train_test_split(X, Y, train_size=0.6, random_state=1, stratify=Y) |
m@93 | 22 accuracy, _, _ = classification.confusion_matrix(X_train, Y_train, X_test, Y_test) |
m@30 | 23 # expect perfect accuracy for this 'easy' dataset |
m@30 | 24 assert accuracy == 1.0 |
m@30 | 25 |