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@@ 333-340 (lines=8) @@
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@pytest.mark.parametrize('pressure, variable, heights, bottom, depth, interp, expected', [ |
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(layer_test_data()[0], layer_test_data()[1], None, None, 150 * units.hPa, True, |
| 332 |
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(np.array([1000, 900, 850]) * units.hPa, |
| 333 |
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np.array([25.0, 16.666666, 12.62262]) * units.degC)), |
| 334 |
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(layer_test_data()[0], layer_test_data()[1], None, None, 150 * units.hPa, False, |
| 335 |
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(np.array([1000, 900]) * units.hPa, np.array([25.0, 16.666666]) * units.degC)), |
| 336 |
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(layer_test_data()[0], layer_test_data()[1], None, 2 * units.km, 3 * units.km, True, |
| 337 |
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(np.array([794.85264282, 700., 600., 540.01696548]) * units.hPa, |
| 338 |
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np.array([7.93049516, 0., -8.33333333, -13.14758845]) * units.degC)) |
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]) |
| 340 |
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def test_get_layer(pressure, variable, heights, bottom, depth, interp, expected): |
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"""Tests get_layer functionality.""" |
| 342 |
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p_layer, y_layer = get_layer(pressure, variable, heights=heights, bottom=bottom, |
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depth=depth, interpolate=interp) |
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@@ 323-330 (lines=8) @@
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@pytest.fixture |
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def layer_test_data(): |
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"""Provide test data for testing of layer bounds.""" |
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pressure = np.arange(1000, 10, -100) * units.hPa |
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temperature = np.linspace(25, -50, len(pressure)) * units.degC |
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return pressure, temperature |
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| 329 |
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| 330 |
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@pytest.mark.parametrize('pressure, variable, heights, bottom, depth, interp, expected', [ |
| 331 |
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(layer_test_data()[0], layer_test_data()[1], None, None, 150 * units.hPa, True, |
| 332 |
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(np.array([1000, 900, 850]) * units.hPa, |
| 333 |
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np.array([25.0, 16.666666, 12.62262]) * units.degC)), |
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@@ 343-352 (lines=10) @@
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| 340 |
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def test_get_layer(pressure, variable, heights, bottom, depth, interp, expected): |
| 341 |
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"""Tests get_layer functionality.""" |
| 342 |
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p_layer, y_layer = get_layer(pressure, variable, heights=heights, bottom=bottom, |
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depth=depth, interpolate=interp) |
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assert_array_almost_equal(p_layer, expected[0], 5) |
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assert_array_almost_equal(y_layer, expected[1], 5) |
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|
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def test_log_interp_2d(): |
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"""Test interpolating with log x-scale in 2 dimensions.""" |
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x_log = np.array([[1e3, 1e4, 1e5, 1e6], [1e3, 1e4, 1e5, 1e6]]) |
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y_log = np.log(x_log) * 2 + 3 |
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x_interp = np.array([5e3, 5e4, 5e5]) |
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y_interp_truth = np.array([20.0343863828, 24.6395565688, 29.2447267548]) |
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y_interp = log_interp(x_interp, x_log, y_log, axis=1) |
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assert_array_almost_equal(y_interp[1], y_interp_truth, 7) |
Unidata /
MetPy
