src/main/python/tests/algorithms/test_l2svm.py

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import unittest

import numpy as np
from systemds.context import SystemDSContext
from systemds.operator.algorithm import l2svm


class TestL2svm(unittest.TestCase):

    sds: SystemDSContext = None

    @classmethod
    def setUpClass(cls):
        cls.sds = SystemDSContext(capture_stdout=True, logging_level=50)

    @classmethod
    def tearDownClass(cls):
        cls.sds.close()

    def test_10x10(self):
        features, labels = self.generate_matrices_for_l2svm(10, seed=1304)
        model = l2svm(features, labels).compute()
        # TODO make better verification.
        self.assertTrue(
            np.allclose(
                model,
                np.array(
                    [
                        [-0.03277166],
                        [-0.00820981],
                        [0.00657115],
                        [0.03228764],
                        [-0.01685067],
                        [0.00892918],
                        [0.00945636],
                        [0.01514383],
                        [0.0713272],
                        [-0.05113976],
                    ]
                ),
            )
        )

    def generate_matrices_for_l2svm(self, dims: int, seed: int = 1234):
        np.random.seed(seed)
        m1 = np.array(np.random.randint(100, size=dims * dims) + 1.01, dtype=np.double)
        m1.shape = (dims, dims)
        m2 = np.zeros((dims, 1))
        for i in range(dims):
            if np.random.random() > 0.5:
                m2[i][0] = 1
        return self.sds.from_numpy(m1), self.sds.from_numpy(m2)


if __name__ == "__main__":
    unittest.main(exit=False)