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Make Data objects compatible with Path objects
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,137 @@ | ||
| import pytest | ||
| import itertools | ||
|
|
||
| from pysd.py_backend.data import Columns | ||
|
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|
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| class TestColumns: | ||
| @pytest.fixture(scope="class") | ||
| def out_teacup(self, _root): | ||
| return _root.joinpath("data/out_teacup.csv") | ||
|
|
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| @pytest.fixture(scope="class") | ||
| def out_teacup_transposed(self, _root): | ||
| return _root.joinpath("data/out_teacup_transposed.csv") | ||
|
|
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| def test_clean_columns(self, out_teacup): | ||
| # test the singleton works well for laizy loading | ||
| Columns.clean() | ||
| assert Columns._files == {} | ||
| Columns.read(out_teacup) | ||
| assert Columns._files != {} | ||
| assert out_teacup in Columns._files | ||
| Columns.clean() | ||
| assert Columns._files == {} | ||
|
|
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| def test_transposed_frame(self, out_teacup, out_teacup_transposed): | ||
| # test loading transposed frames | ||
| cols1, trans1 = Columns.get_columns(out_teacup) | ||
| cols2, trans2 = Columns.get_columns(out_teacup_transposed) | ||
| Columns.clean() | ||
|
|
||
| assert cols1 == cols2 | ||
| assert not trans1 | ||
| assert trans2 | ||
|
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| def test_get_columns(self, out_teacup, out_teacup_transposed): | ||
| # test getting specific columns by name | ||
| cols0, trans0 = Columns.get_columns(out_teacup) | ||
|
|
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| cols1, trans1 = Columns.get_columns( | ||
| out_teacup, | ||
| vars=["Room Temperature", "Teacup Temperature"]) | ||
|
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| cols2, trans2 = Columns.get_columns( | ||
| out_teacup_transposed, | ||
| vars=["Heat Loss to Room"]) | ||
|
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| cols3 = Columns.get_columns( | ||
| out_teacup_transposed, | ||
| vars=["No column"])[0] | ||
|
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| Columns.clean() | ||
|
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| assert cols1.issubset(cols0) | ||
| assert cols1 == set(["Room Temperature", "Teacup Temperature"]) | ||
|
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| assert cols2.issubset(cols0) | ||
| assert cols2 == set(["Heat Loss to Room"]) | ||
|
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| assert cols3 == set() | ||
|
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| assert not trans0 | ||
| assert not trans1 | ||
| assert trans2 | ||
|
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| def test_get_columns_subscripted(self, _root): | ||
| # test get subscripted columns | ||
| data_file = _root.joinpath( | ||
| "test-models/tests/subscript_3d_arrays_widthwise/output.tab" | ||
| ) | ||
|
|
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| data_file2 = _root.joinpath( | ||
| "test-models/tests/subscript_2d_arrays/output.tab" | ||
| ) | ||
|
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| subsd = { | ||
| "d3": ["Depth 1", "Depth 2"], | ||
| "d2": ["Column 1", "Column 2"], | ||
| "d1": ["Entry 1", "Entry 2", "Entry 3"] | ||
| } | ||
|
|
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| cols1 = Columns.get_columns( | ||
| data_file, | ||
| vars=["Three Dimensional Constant"])[0] | ||
|
|
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| expected = { | ||
| "Three Dimensional Constant[" + ",".join(el) + "]" | ||
| for el in itertools.product(subsd["d1"], subsd["d2"], subsd["d3"]) | ||
| } | ||
|
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| assert cols1 == expected | ||
|
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| cols2 = Columns.get_columns( | ||
| data_file2, | ||
| vars=["Rate A", "Stock A"])[0] | ||
|
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| subs = list(itertools.product(subsd["d1"], subsd["d2"])) | ||
| expected = { | ||
| "Rate A[" + ",".join(el) + "]" | ||
| for el in subs | ||
| } | ||
|
|
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| expected.update({ | ||
| "Stock A[" + ",".join(el) + "]" | ||
| for el in subs | ||
| }) | ||
|
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| assert cols2 == expected | ||
|
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|
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| @pytest.mark.parametrize( | ||
| "file,raise_type,error_message", | ||
| [ | ||
| ( # invalid_file_type | ||
| "more-tests/not_vensim/test_not_vensim.txt", | ||
| ValueError, | ||
| "Not able to read '%s'" | ||
| ), | ||
| ( # invalid_file_format | ||
| "data/out_teacup_no_head.csv", | ||
| ValueError, | ||
| "Invalid file format '%s'... varible names should appear" | ||
| + " in the first row or in the first column..." | ||
| ) | ||
| ], | ||
| ids=["invalid_file_type", "invalid_file_format"] | ||
| ) | ||
| class TestColumnsErrors: | ||
| # Test errors associated with Columns class | ||
|
|
||
| @pytest.fixture | ||
| def file_path(self, _root, file): | ||
| return _root.joinpath(file) | ||
|
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| def test_columns_errors(self, file_path, raise_type, error_message): | ||
| with pytest.raises(raise_type, match=error_message % str(file_path)): | ||
| Columns.read_file(file_path) |
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