Write test for independent columns in generate

tests/mst/test_generate.py

@@ -233,3 +233,61 @@ def test_generate(nrows, params):
     data.repartition.assert_called_once_with("100MB")
 
     assert synthetic is data
+
+
+@given(
+    st.integers(1, 100),
+    st.lists(st.text(), min_size=2, max_size=10, unique=True),
+)
+def test_generate_with_extra_independents(nrows, params):
+    """Test generation executes with multiple independent columns."""
+
+    column, *order = params
+
+    prng = da.random.default_rng(0)
+
+    data = mock.MagicMock()
+    data.repartition.return_value = data
+
+    model = mock.MagicMock()
+    marginal = mock.MagicMock()
+    model.project.return_value.datavector.return_value = marginal
+
+    with mock.patch("centhesus.mst.MST._setup_generate") as setup, mock.patch(
+        "centhesus.mst.MST._synthesise_first_column"
+    ) as first, mock.patch(
+        "centhesus.mst.MST._find_prerequisite_columns"
+    ) as find, mock.patch(
+        "centhesus.mst.MST._synthesise_column"
+    ) as synth:
+        setup.return_value = (nrows, prng, "cliques", column, order)
+        first.return_value = data
+        find.return_value = ()
+        synth.return_value = "independent"
+
+        synthetic = MST.generate(model, nrows)
+
+    setup.assert_called_once_with(model, nrows, None)
+    first.assert_called_once_with(model, column, nrows, prng)
+
+    num_subsequent_columns = len(order)
+    assert model.project.call_count == num_subsequent_columns
+    for call, col in zip(model.project.call_args_list, order):
+        assert call.args == ((col,),)
+
+    assert (
+        model.project.return_value.datavector.call_count
+        == num_subsequent_columns
+    )
+    for call in model.project.return_value.datavector.call_args_list:
+        assert call.args == ()
+        assert call.kwargs == {"flatten": False}
+
+    assert synth.call_count == num_subsequent_columns
+    for call, col in zip(synth.call_args_list, order):
+        assert call.args == (marginal, nrows, prng)
+        assert hasattr(data, col)
+
+    data.repartition.assert_called_once_with("100MB")
+
+    assert synthetic is data