import unittest
from linear_regression import *
from make_test_datasets import *
import numpy

class test_linear_regression(unittest.TestCase):

    def test1(self):
        trainset,testset,theta=make_artificial_datasets_from_function(n_inputs=3,
                                                                      n_targets=2,
                                                                      n_examples=100,
                                                                      f=linear_predictor)
        
        assert trainset.fields()['input'].shape==(50,3)
        assert testset.fields()['target'].shape==(50,2)
        regressor = LinearRegression(L2_regularizer=0.1)
        predictor = regressor(trainset)
        test_data = testset.fields()
        mse = predictor.compute_mse(test_data['input'],test_data['target'])
        print 'mse = ',mse
        
if __name__ == '__main__':
    unittest.main()