|
| 1 | +"""Tests for input_stream default behavior.""" |
| 2 | + |
| 3 | +import unittest |
| 4 | +from unittest import mock |
| 5 | + |
| 6 | +import numpy as np |
| 7 | + |
| 8 | +from pysr import PySRRegressor |
| 9 | +from pysr.sr import ALREADY_RAN |
| 10 | + |
| 11 | + |
| 12 | +class TestInputStream(unittest.TestCase): |
| 13 | + """Verify input_stream defaults and backend passthrough.""" |
| 14 | + |
| 15 | + def test_default_is_none(self): |
| 16 | + """By default, input_stream should be None so the Julia backend picks the stream.""" |
| 17 | + model = PySRRegressor() |
| 18 | + self.assertIsNone(model.input_stream) |
| 19 | + |
| 20 | + def test_explicit_stdin(self): |
| 21 | + model = PySRRegressor(input_stream="stdin") |
| 22 | + self.assertEqual(model.input_stream, "stdin") |
| 23 | + |
| 24 | + def test_explicit_devnull(self): |
| 25 | + model = PySRRegressor(input_stream="devnull") |
| 26 | + self.assertEqual(model.input_stream, "devnull") |
| 27 | + |
| 28 | + def _make_mock_jl(self): |
| 29 | + """Return a MagicMock that satisfies the Julia calls made before Options().""" |
| 30 | + m = mock.MagicMock() |
| 31 | + m.seval.return_value = mock.MagicMock() |
| 32 | + m.Dict.return_value = mock.MagicMock() |
| 33 | + m.Pair.return_value = mock.MagicMock() |
| 34 | + m.Symbol.return_value = mock.MagicMock() |
| 35 | + m.NamedTuple.return_value = mock.MagicMock() |
| 36 | + return m |
| 37 | + |
| 38 | + def _mocked_fit(self, model, X, y, *, capture_options): |
| 39 | + """Run model.fit with enough Julia infrastructure mocked to reach Options().""" |
| 40 | + mock_jl = self._make_mock_jl() |
| 41 | + sr = mock.MagicMock() |
| 42 | + sr.MutationWeights.return_value = mock.MagicMock() |
| 43 | + sr.Options.side_effect = capture_options |
| 44 | + sr.equation_search.return_value = (mock.MagicMock(), b"mock") |
| 45 | + sr.SearchUtilsModule.generate_run_id.return_value = "test-run-id" |
| 46 | + |
| 47 | + # Reset global so _run doesn't skip its first-run block. |
| 48 | + import pysr.sr as sr_module |
| 49 | + |
| 50 | + old_already_ran = sr_module.ALREADY_RAN |
| 51 | + sr_module.ALREADY_RAN = False |
| 52 | + |
| 53 | + try: |
| 54 | + with mock.patch("pysr.sr.jl", mock_jl): |
| 55 | + with mock.patch("pysr.sr.SymbolicRegression", sr): |
| 56 | + with mock.patch("pysr.sr.jl_array", return_value=mock.MagicMock()): |
| 57 | + with mock.patch("pysr.sr.jl_is_function", return_value=True): |
| 58 | + with mock.patch( |
| 59 | + "pysr.sr.jl_serialize", return_value=b"mock" |
| 60 | + ): |
| 61 | + with mock.patch("pysr.sr.load_required_packages"): |
| 62 | + with mock.patch("pysr.sr._load_cluster_manager"): |
| 63 | + model.fit(X, y) |
| 64 | + finally: |
| 65 | + sr_module.ALREADY_RAN = old_already_ran |
| 66 | + |
| 67 | + def test_default_omits_input_stream_from_options(self): |
| 68 | + """When input_stream is None, Options should not receive the kwarg.""" |
| 69 | + captured_kwargs = {} |
| 70 | + |
| 71 | + def capture_options(**kwargs): |
| 72 | + captured_kwargs.update(kwargs) |
| 73 | + raise RuntimeError("stop_after_options") |
| 74 | + |
| 75 | + X = np.array([[1.0, 2.0], [3.0, 4.0]]) |
| 76 | + y = np.array([1.0, 2.0]) |
| 77 | + |
| 78 | + model = PySRRegressor( |
| 79 | + niterations=0, |
| 80 | + max_evals=0, |
| 81 | + populations=1, |
| 82 | + ncycles_per_iteration=0, |
| 83 | + progress=False, |
| 84 | + verbosity=0, |
| 85 | + temp_equation_file=True, |
| 86 | + parallelism="serial", |
| 87 | + ) |
| 88 | + |
| 89 | + with self.assertRaises(RuntimeError) as cm: |
| 90 | + self._mocked_fit(model, X, y, capture_options=capture_options) |
| 91 | + self.assertEqual(str(cm.exception), "stop_after_options") |
| 92 | + self.assertNotIn("input_stream", captured_kwargs) |
| 93 | + |
| 94 | + def test_explicit_stdin_passes_input_stream(self): |
| 95 | + """When input_stream is 'stdin', Options should receive the kwarg.""" |
| 96 | + captured_kwargs = {} |
| 97 | + |
| 98 | + def capture_options(**kwargs): |
| 99 | + captured_kwargs.update(kwargs) |
| 100 | + raise RuntimeError("stop_after_options") |
| 101 | + |
| 102 | + X = np.array([[1.0, 2.0], [3.0, 4.0]]) |
| 103 | + y = np.array([1.0, 2.0]) |
| 104 | + |
| 105 | + model = PySRRegressor( |
| 106 | + input_stream="stdin", |
| 107 | + niterations=0, |
| 108 | + max_evals=0, |
| 109 | + populations=1, |
| 110 | + ncycles_per_iteration=0, |
| 111 | + progress=False, |
| 112 | + verbosity=0, |
| 113 | + temp_equation_file=True, |
| 114 | + parallelism="serial", |
| 115 | + ) |
| 116 | + |
| 117 | + with self.assertRaises(RuntimeError) as cm: |
| 118 | + self._mocked_fit(model, X, y, capture_options=capture_options) |
| 119 | + self.assertEqual(str(cm.exception), "stop_after_options") |
| 120 | + self.assertIn("input_stream", captured_kwargs) |
| 121 | + |
| 122 | + def test_explicit_devnull_passes_input_stream(self): |
| 123 | + """When input_stream is 'devnull', Options should receive the kwarg.""" |
| 124 | + captured_kwargs = {} |
| 125 | + |
| 126 | + def capture_options(**kwargs): |
| 127 | + captured_kwargs.update(kwargs) |
| 128 | + raise RuntimeError("stop_after_options") |
| 129 | + |
| 130 | + X = np.array([[1.0, 2.0], [3.0, 4.0]]) |
| 131 | + y = np.array([1.0, 2.0]) |
| 132 | + |
| 133 | + model = PySRRegressor( |
| 134 | + input_stream="devnull", |
| 135 | + niterations=0, |
| 136 | + max_evals=0, |
| 137 | + populations=1, |
| 138 | + ncycles_per_iteration=0, |
| 139 | + progress=False, |
| 140 | + verbosity=0, |
| 141 | + temp_equation_file=True, |
| 142 | + parallelism="serial", |
| 143 | + ) |
| 144 | + |
| 145 | + with self.assertRaises(RuntimeError) as cm: |
| 146 | + self._mocked_fit(model, X, y, capture_options=capture_options) |
| 147 | + self.assertEqual(str(cm.exception), "stop_after_options") |
| 148 | + self.assertIn("input_stream", captured_kwargs) |
| 149 | + |
| 150 | + |
| 151 | +def runtests(just_tests=False): |
| 152 | + tests = [TestInputStream] |
| 153 | + if just_tests: |
| 154 | + return tests |
| 155 | + suite = unittest.TestSuite() |
| 156 | + loader = unittest.TestLoader() |
| 157 | + for test in tests: |
| 158 | + suite.addTests(loader.loadTestsFromTestCase(test)) |
| 159 | + runner = unittest.TextTestRunner() |
| 160 | + return runner.run(suite) |
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