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Merge pull request #382 from DoubleML/sk-update-sklearn-1.8
Update dependencies and tests for slearn 1.8.0
2 parents dcb31b8 + 4343f3e commit 0e758cf

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doubleml/plm/tests/test_lplr_exceptions.py

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Original file line numberDiff line numberDiff line change
@@ -241,7 +241,7 @@ def test_lplr_exception_learner():
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def test_lplr_exception_and_warning_learner():
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# invalid ml_M (must be a classifier with predict_proba)
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with pytest.raises(TypeError):
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_ = DoubleMLLPLR(dml_data, _DummyNoClassifier(), ml_t, ml_m)
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_ = DoubleMLLPLR(dml_data, Lasso(), ml_t, ml_m)
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msg = "Invalid learner provided for ml_M: " + r"Lasso\(\) has no method .predict_proba\(\)."
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with pytest.raises(TypeError, match=msg):
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_ = DoubleMLLPLR(dml_data, Lasso(), ml_t, ml_m)

doubleml/tests/test_optuna_multi_wrappers.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -23,7 +23,7 @@ def _build_apos_object():
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dml_data = dml.DoubleMLData(df, "y", "d")
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ml_g = LinearRegression()
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ml_m = LogisticRegression(max_iter=200, multi_class="auto")
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ml_m = LogisticRegression(max_iter=200)
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return dml.DoubleMLAPOS(
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dml_data,
@@ -38,7 +38,7 @@ def _build_apos_object():
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def _build_qte_object():
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np.random.seed(3141)
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dml_data = make_irm_data(n_obs=80, dim_x=5)
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ml = LogisticRegression(max_iter=200, multi_class="auto")
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ml = LogisticRegression(max_iter=200)
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return dml.DoubleMLQTE(
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dml_data,
@@ -57,7 +57,7 @@ def _build_did_multi_object():
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dml_panel = DoubleMLPanelData(df, y_col="y", d_cols="d", t_col="t", id_col="id", x_cols=x_cols)
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ml_g = LinearRegression()
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ml_m = LogisticRegression(max_iter=200, multi_class="auto")
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ml_m = LogisticRegression(max_iter=200)
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return dml.did.DoubleMLDIDMulti(
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obj_dml_data=dml_panel,

pyproject.toml

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@@ -46,7 +46,7 @@ dev = [
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"pytest>=8.3.0",
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"pytest-cov>=6.0.0",
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"xgboost>=2.1.0",
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"lightgbm>=4.5.0",
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"lightgbm>=4.6.0",
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"black>=25.1.0",
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"ruff>=0.11.1",
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"pre-commit>=4.2.0",

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