def test_confidence_interval(self):
        """
        Test if given two timeseries and a desired confidence interval,
        regression gives us the correct over and underestimation.
        """
        data_x = zip(range(100), range(100))
        overestimations  = [[90, 90 - 1], [91, 91 - 3], [92, 1 - 92], [93, 93 - 40], [94, 94 - 1]]
        underestimations = [[95, 95 + 5], [96, 96 + 1 ], [97,97 + 4], [98, 98 + 3], [99, 99 + 1]]
        data_y = data_x[:90] + overestimations + underestimations

        ts_x = TimeSeries.from_twodim_list(data_x)
        ts_y = TimeSeries.from_twodim_list(data_y)

        #Mock the random.sample method so that we can use our outliers as samples
        with patch('pycast.common.timeseries.random.sample') as sample_mock:
            sample_mock.return_value = underestimations+overestimations

            reg = Regression()
            n, m, error = reg.calculate_parameters_with_confidence(ts_x, ts_y, .6)

            #Since all values are the same the params should be n=0, m=1
            self.assertEquals(0,n)
            self.assertEquals(1,m)

            #assert under/overestimation
            self.assertEquals(error[0], -1)
            self.assertEquals(error[1], 3)
dataset/ETHPy150Open T-002/pycast/pycast/tests/regressiontest.py/RegressionTest.test_confidence_interval/swapped operands of `-`