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# Test methods with long descriptive names can omit docstrings
# pylint: disable=missing-docstring
import unittest
import numpy as np
from Orange.preprocess import Continuize, Randomize
from Orange.projection import LDA
from Orange.data import Table
class TestLDA(unittest.TestCase):
def test_lda(self):
iris = Table('iris')
n_components = 2
lda = LDA(solver="eigen", n_components=n_components)
model = lda(iris)
transformed = model(iris)
self.assertEqual(transformed.X.shape, (len(iris), n_components))
self.assertEqual(transformed.Y.shape, (len(iris),))
def test_transform_changed_domain(self):
"""
1. Open data, apply some preprocessor, splits the data into two parts,
use LDA on the first part, and then transform the second part.
2. Open data, split into two parts, apply the same preprocessor and
LDA only on the first part, and then transform the second part.
The transformed second part in (1) and (2) has to be the same.
"""
data = Table("iris")
data = Randomize()(data)
preprocessor = Continuize()
lda = LDA()
# normalize all
ndata = preprocessor(data)
model = lda(ndata[:75])
result_1 = model(ndata[75:])
# normalize only the "training" part
ndata = preprocessor(data[:75])
model = lda(ndata)
result_2 = model(data[75:])
np.testing.assert_almost_equal(result_1.X, result_2.X)
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