|
| 1 | +import numpy as np |
| 2 | +import pytest |
| 3 | +from sklearn.linear_model import RidgeCV |
| 4 | +from sklearn.svm import SVR |
| 5 | + |
| 6 | +from hidimstat.statistical_tools.lasso_test import ( |
| 7 | + preconfigure_LassoCV, |
| 8 | + lasso_statistic_with_sampling, |
| 9 | + lasso_statistic, |
| 10 | +) |
| 11 | + |
| 12 | + |
| 13 | +def test_preconfigure_LassoCV(): |
| 14 | + """Test type errors""" |
| 15 | + with pytest.raises( |
| 16 | + TypeError, match="You should not use this function to configure the estimator" |
| 17 | + ): |
| 18 | + preconfigure_LassoCV( |
| 19 | + estimator=RidgeCV(), |
| 20 | + X=np.random.rand(10, 10), |
| 21 | + y=np.random.rand(10), |
| 22 | + X_tilde=np.random.rand(10, 10), |
| 23 | + ) |
| 24 | + |
| 25 | + |
| 26 | +def test_error_lasso_statistic_with_sampling_with_bad_config(): |
| 27 | + """Test error lasso statistic""" |
| 28 | + with pytest.raises( |
| 29 | + TypeError, match="You should not use this function to configure the estimator" |
| 30 | + ): |
| 31 | + lasso_statistic_with_sampling( |
| 32 | + X=np.random.rand(10, 10), |
| 33 | + X_tilde=np.random.rand(10, 10), |
| 34 | + y=np.random.rand(10), |
| 35 | + lasso=SVR(), |
| 36 | + ) |
| 37 | + |
| 38 | + |
| 39 | +def test_error_lasso_statistic_with_sampling(): |
| 40 | + """Test error lasso statistic""" |
| 41 | + with pytest.raises(TypeError, match="estimator should be linear"): |
| 42 | + lasso_statistic_with_sampling( |
| 43 | + X=np.random.rand(10, 10), |
| 44 | + X_tilde=np.random.rand(10, 10), |
| 45 | + y=np.random.rand(10), |
| 46 | + lasso=SVR(), |
| 47 | + preconfigure_lasso=None, |
| 48 | + ) |
| 49 | + |
| 50 | + |
| 51 | +def test_error_lasso_statistic(): |
| 52 | + """Test error lasso statistic""" |
| 53 | + with pytest.raises(TypeError, match="estimator should be linear"): |
| 54 | + lasso_statistic(X=np.random.rand(10, 10), y=np.random.rand(10), lasso=SVR()) |
0 commit comments