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koala_test.py
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koala_test.py
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import os
import platform
import numpy as np
import pandas as pd
import koala
import unittest
if (platform.uname())[0] == "Windows":
FOLDER = os.environ['USERPROFILE']
else:
FOLDER = os.environ.get("HOME")
FILE = 'test.dat'
PATH = os.path.join(FOLDER, FILE)
DATASET = pd.read_csv('data/iris.csv')
class KoalaTest(unittest.TestCase):
def testKoalaInstantiation(self):
try:
k = koala.Koala()
except Exception as e:
self.fail(str(e))
def testKoalaSetData(self):
try:
k = koala.Koala()
k.set_data(DATASET)
self.assertEqual(k.data.frame, DATASET)
except Exception as e:
self.fail(str(e))
def testKoalaSaveAndLoad(self):
try:
k = koala.Koala()
k.set_data(DATASET)
k.set_target(4)
k.train(test_size=0.05)
k.save(PATH)
l = koala.Koala()
l.load(PATH)
self.assertEqual(k.data, l.data)
self.assertEqual(k._mc, l._mc)
except Exception as e:
self.fail(str(e))
else:
os.remove(PATH)
def testKoalaClassification(self):
try:
X_test = np.array([[5,3,1,0],[8,3,6,2]])
k = koala.Koala(data=DATASET,target='species')
k.train(test_size=0.4)
predictions = k.predict(X_test)
self.assertEqual(predictions[0].lower(), 'iris-setosa')
self.assertEqual(predictions[1].lower(), 'iris-virginica')
except Exception as e:
self.fail(str(e))
def testKoalaClassiferFeatures(self):
try:
k = koala.Koala(data=DATASET, target='species')
k.train()
fs = k.feature_importance()
fr = k.feature_reduction_scores()
except Exception as e:
self.fail(str(e))
if __name__ == "__main__":
unittest.main()