Split test_spectrum.py

docs/sphinx/source/whatsnew/v0.11.1.rst

@@ -19,7 +19,7 @@ Enhancements
 * Restructured the pvlib/spectrum folder by breaking up the contents of
   pvlib/spectrum/mismatch.py into pvlib/spectrum/mismatch.py,
   pvlib/spectrum/irradiance.py, and
-  pvlib/spectrum/response.py. (:issue:`2125`, :pull:`2136`)
+  pvlib/spectrum/response.py. (:issue:`2125`, :pull:`2136`, :pull:`2151`)
 * Added function for calculating wind speed at different heights,
   :py:func:`pvlib.atmosphere.windspeed_powerlaw`.
   (:issue:`2118`, :pull:`2124`)

pvlib/tests/spectrum/test_irradiance.py

@@ -0,0 +1,74 @@
+import pytest
+from numpy.testing import assert_allclose, assert_approx_equal, assert_equal
+import pandas as pd
+import numpy as np
+from pvlib import spectrum
+from pvlib._deprecation import pvlibDeprecationWarning
+
+from ..conftest import assert_series_equal, fail_on_pvlib_version
+
+
+@fail_on_pvlib_version('0.12')
+def test_get_am15g():
+    # test that the reference spectrum is read and interpolated correctly
+    with pytest.warns(pvlibDeprecationWarning,
+                      match="get_reference_spectra instead"):
+        e = spectrum.get_am15g()
+    assert_equal(len(e), 2002)
+    assert_equal(np.sum(e.index), 2761442)
+    assert_approx_equal(np.sum(e), 1002.88, significant=6)
+
+    wavelength = [270, 850, 950, 1200, 1201.25, 4001]
+    expected = [0.0, 0.893720, 0.147260, 0.448250, 0.4371025, 0.0]
+
+    with pytest.warns(pvlibDeprecationWarning,
+                      match="get_reference_spectra instead"):
+        e = spectrum.get_am15g(wavelength)
+    assert_equal(len(e), len(wavelength))
+    assert_allclose(e, expected, rtol=1e-6)
+
+
+@pytest.mark.parametrize(
+    "reference_identifier,expected_sums",
+    [
+        (
+            "ASTM G173-03",  # reference_identifier
+            {  # expected_sums
+                "extraterrestrial": 1356.15,
+                "global": 1002.88,
+                "direct": 887.65,
+            },
+        ),
+    ],
+)
+def test_get_reference_spectra(reference_identifier, expected_sums):
+    # test reading of a standard spectrum
+    standard = spectrum.get_reference_spectra(standard=reference_identifier)
+    assert set(standard.columns) == expected_sums.keys()
+    assert standard.index.name == "wavelength"
+    assert standard.index.is_monotonic_increasing is True
+    expected_sums = pd.Series(expected_sums)  # convert prior to comparison
+    assert_series_equal(np.sum(standard, axis=0), expected_sums, atol=1e-2)
+
+
+def test_get_reference_spectra_custom_wavelengths():
+    # test that the spectrum is interpolated correctly when custom wavelengths
+    # are specified
+    # only checked for ASTM G173-03 reference spectrum
+    wavelength = [270, 850, 951.634, 1200, 4001]
+    expected_sums = pd.Series(
+        {"extraterrestrial": 2.23266, "global": 1.68952, "direct": 1.58480}
+    )  # for given ``wavelength``
+    standard = spectrum.get_reference_spectra(
+        wavelength, standard="ASTM G173-03"
+    )
+    assert_equal(len(standard), len(wavelength))
+    # check no NaN values were returned
+    assert not standard.isna().any().any()  # double any to return one value
+    assert_series_equal(np.sum(standard, axis=0), expected_sums, atol=1e-4)
+
+
+def test_get_reference_spectra_invalid_reference():
+    # test that an invalid reference identifier raises a ValueError
+    with pytest.raises(ValueError, match="Invalid standard identifier"):
+        spectrum.get_reference_spectra(standard="invalid")

pvlib/tests/test_spectrum.py → pvlib/tests/spectrum/test_mismatch.py

@@ -1,11 +1,10 @@
 import pytest
-from numpy.testing import assert_allclose, assert_approx_equal, assert_equal
+from numpy.testing import assert_allclose, assert_approx_equal
 import pandas as pd
 import numpy as np
 from pvlib import spectrum
-from pvlib._deprecation import pvlibDeprecationWarning
 
-from .conftest import DATA_DIR, assert_series_equal, fail_on_pvlib_version
+from ..conftest import DATA_DIR, assert_series_equal
 
 SPECTRL2_TEST_DATA = DATA_DIR / 'spectrl2_example_spectra.csv'
 
@@ -43,154 +42,6 @@ def spectrl2_data():
     return kwargs, df
 
 
-def test_spectrl2(spectrl2_data):
-    # compare against output from solar_utils wrapper around NREL spectrl2_2.c
-    kwargs, expected = spectrl2_data
-    actual = spectrum.spectrl2(**kwargs)
-    assert_allclose(expected['wavelength'].values, actual['wavelength'])
-    assert_allclose(expected['specdif'].values, actual['dhi'].ravel(),
-                    atol=7e-5)
-    assert_allclose(expected['specdir'].values, actual['dni'].ravel(),
-                    atol=1.5e-4)
-    assert_allclose(expected['specetr'], actual['dni_extra'].ravel(),
-                    atol=2e-4)
-    assert_allclose(expected['specglo'], actual['poa_global'].ravel(),
-                    atol=1e-4)
-
-
-def test_spectrl2_array(spectrl2_data):
-    # test that supplying arrays instead of scalars works
-    kwargs, expected = spectrl2_data
-    kwargs = {k: np.array([v, v, v]) for k, v in kwargs.items()}
-    actual = spectrum.spectrl2(**kwargs)
-
-    assert actual['wavelength'].shape == (122,)
-
-    keys = ['dni_extra', 'dhi', 'dni', 'poa_sky_diffuse', 'poa_ground_diffuse',
-            'poa_direct', 'poa_global']
-    for key in keys:
-        assert actual[key].shape == (122, 3)
-
-
-def test_spectrl2_series(spectrl2_data):
-    # test that supplying Series instead of scalars works
-    kwargs, expected = spectrl2_data
-    kwargs.pop('dayofyear')
-    index = pd.to_datetime(['2020-03-15 10:45:59']*3)
-    kwargs = {k: pd.Series([v, v, v], index=index) for k, v in kwargs.items()}
-    actual = spectrum.spectrl2(**kwargs)
-
-    assert actual['wavelength'].shape == (122,)
-
-    keys = ['dni_extra', 'dhi', 'dni', 'poa_sky_diffuse', 'poa_ground_diffuse',
-            'poa_direct', 'poa_global']
-    for key in keys:
-        assert actual[key].shape == (122, 3)
-
-
-def test_dayofyear_missing(spectrl2_data):
-    # test that not specifying dayofyear with non-pandas inputs raises error
-    kwargs, expected = spectrl2_data
-    kwargs.pop('dayofyear')
-    with pytest.raises(ValueError, match='dayofyear must be specified'):
-        _ = spectrum.spectrl2(**kwargs)
-
-
-def test_aoi_gt_90(spectrl2_data):
-    # test that returned irradiance values are non-negative when aoi > 90
-    # see GH #1348
-    kwargs, _ = spectrl2_data
-    kwargs['apparent_zenith'] = 70
-    kwargs['aoi'] = 130
-    kwargs['surface_tilt'] = 60
-
-    spectra = spectrum.spectrl2(**kwargs)
-    for key in ['poa_direct', 'poa_global']:
-        message = f'{key} contains negative values for aoi>90'
-        assert np.all(spectra[key] >= 0), message
-
-
-def test_get_example_spectral_response():
-    # test that the sample sr is read and interpolated correctly
-    sr = spectrum.get_example_spectral_response()
-    assert_equal(len(sr), 185)
-    assert_equal(np.sum(sr.index), 136900)
-    assert_approx_equal(np.sum(sr), 107.6116)
-
-    wavelength = [270, 850, 950, 1200, 4001]
-    expected = [0.0, 0.92778, 1.0, 0.0, 0.0]
-
-    sr = spectrum.get_example_spectral_response(wavelength)
-    assert_equal(len(sr), len(wavelength))
-    assert_allclose(sr, expected, rtol=1e-5)
-
-
-@fail_on_pvlib_version('0.12')
-def test_get_am15g():
-    # test that the reference spectrum is read and interpolated correctly
-    with pytest.warns(pvlibDeprecationWarning,
-                      match="get_reference_spectra instead"):
-        e = spectrum.get_am15g()
-    assert_equal(len(e), 2002)
-    assert_equal(np.sum(e.index), 2761442)
-    assert_approx_equal(np.sum(e), 1002.88, significant=6)
-
-    wavelength = [270, 850, 950, 1200, 1201.25, 4001]
-    expected = [0.0, 0.893720, 0.147260, 0.448250, 0.4371025, 0.0]
-
-    with pytest.warns(pvlibDeprecationWarning,
-                      match="get_reference_spectra instead"):
-        e = spectrum.get_am15g(wavelength)
-    assert_equal(len(e), len(wavelength))
-    assert_allclose(e, expected, rtol=1e-6)
-
-
-@pytest.mark.parametrize(
-    "reference_identifier,expected_sums",
-    [
-        (
-            "ASTM G173-03",  # reference_identifier
-            {  # expected_sums
-                "extraterrestrial": 1356.15,
-                "global": 1002.88,
-                "direct": 887.65,
-            },
-        ),
-    ],
-)
-def test_get_reference_spectra(reference_identifier, expected_sums):
-    # test reading of a standard spectrum
-    standard = spectrum.get_reference_spectra(standard=reference_identifier)
-    assert set(standard.columns) == expected_sums.keys()
-    assert standard.index.name == "wavelength"
-    assert standard.index.is_monotonic_increasing is True
-    expected_sums = pd.Series(expected_sums)  # convert prior to comparison
-    assert_series_equal(np.sum(standard, axis=0), expected_sums, atol=1e-2)
-
-
-def test_get_reference_spectra_custom_wavelengths():
-    # test that the spectrum is interpolated correctly when custom wavelengths
-    # are specified
-    # only checked for ASTM G173-03 reference spectrum
-    wavelength = [270, 850, 951.634, 1200, 4001]
-    expected_sums = pd.Series(
-        {"extraterrestrial": 2.23266, "global": 1.68952, "direct": 1.58480}
-    )  # for given ``wavelength``
-    standard = spectrum.get_reference_spectra(
-        wavelength, standard="ASTM G173-03"
-    )
-    assert_equal(len(standard), len(wavelength))
-    # check no NaN values were returned
-    assert not standard.isna().any().any()  # double any to return one value
-    assert_series_equal(np.sum(standard, axis=0), expected_sums, atol=1e-4)
-
-
-def test_get_reference_spectra_invalid_reference():
-    # test that an invalid reference identifier raises a ValueError
-    with pytest.raises(ValueError, match="Invalid standard identifier"):
-        spectrum.get_reference_spectra(standard="invalid")
-
-
 def test_calc_spectral_mismatch_field(spectrl2_data):
     # test that the mismatch is calculated correctly with
     # - default and custom reference spectrum
@@ -486,107 +337,3 @@ def test_spectral_factor_jrc_supplied_ambiguous():
     with pytest.raises(ValueError, match='No valid input provided'):
         spectrum.spectral_factor_jrc(1.0, 0.8, module_type=None,
                                      coefficients=None)
-
-
-@pytest.fixture
-def sr_and_eqe_fixture():
-    # Just some arbitrary data for testing the conversion functions
-    df = pd.DataFrame(
-        columns=("wavelength", "quantum_efficiency", "spectral_response"),
-        data=[
-            # nm, [0,1], A/W
-            [300, 0.85, 0.205671370402405],
-            [350, 0.86, 0.242772872514211],
-            [400, 0.87, 0.280680929019753],
-            [450, 0.88, 0.319395539919029],
-            [500, 0.89, 0.358916705212040],
-            [550, 0.90, 0.399244424898786],
-            [600, 0.91, 0.440378698979267],
-            [650, 0.92, 0.482319527453483],
-            [700, 0.93, 0.525066910321434],
-            [750, 0.94, 0.568620847583119],
-            [800, 0.95, 0.612981339238540],
-            [850, 0.90, 0.617014111207215],
-            [900, 0.80, 0.580719163489143],
-            [950, 0.70, 0.536358671833723],
-            [1000, 0.6, 0.483932636240953],
-            [1050, 0.4, 0.338752845368667],
-        ],
-    )
-    df.set_index("wavelength", inplace=True)
-    return df
-
-
-def test_sr_to_qe(sr_and_eqe_fixture):
-    # vector type
-    qe = spectrum.sr_to_qe(
-        sr_and_eqe_fixture["spectral_response"].values,
-        sr_and_eqe_fixture.index.values,  # wavelength, nm
-    )
-    assert_allclose(qe, sr_and_eqe_fixture["quantum_efficiency"])
-    # pandas series type
-    # note: output Series' name should match the input
-    qe = spectrum.sr_to_qe(
-        sr_and_eqe_fixture["spectral_response"]
-    )
-    pd.testing.assert_series_equal(
-        qe, sr_and_eqe_fixture["quantum_efficiency"],
-        check_names=False
-    )
-    assert qe.name == "spectral_response"
-    # series normalization
-    qe = spectrum.sr_to_qe(
-        sr_and_eqe_fixture["spectral_response"] * 10, normalize=True
-    )
-    pd.testing.assert_series_equal(
-        qe,
-        sr_and_eqe_fixture["quantum_efficiency"]
-        / max(sr_and_eqe_fixture["quantum_efficiency"]),
-        check_names=False,
-    )
-    # error on lack of wavelength parameter if no pandas object is provided
-    with pytest.raises(TypeError, match="must have an '.index' attribute"):
-        _ = spectrum.sr_to_qe(sr_and_eqe_fixture["spectral_response"].values)
-
-
-def test_qe_to_sr(sr_and_eqe_fixture):
-    # vector type
-    sr = spectrum.qe_to_sr(
-        sr_and_eqe_fixture["quantum_efficiency"].values,
-        sr_and_eqe_fixture.index.values,  # wavelength, nm
-    )
-    assert_allclose(sr, sr_and_eqe_fixture["spectral_response"])
-    # pandas series type
-    # note: output Series' name should match the input
-    sr = spectrum.qe_to_sr(
-        sr_and_eqe_fixture["quantum_efficiency"]
-    )
-    pd.testing.assert_series_equal(
-        sr, sr_and_eqe_fixture["spectral_response"],
-        check_names=False
-    )
-    assert sr.name == "quantum_efficiency"
-    # series normalization
-    sr = spectrum.qe_to_sr(
-        sr_and_eqe_fixture["quantum_efficiency"] * 10, normalize=True
-    )
-    pd.testing.assert_series_equal(
-        sr,
-        sr_and_eqe_fixture["spectral_response"]
-        / max(sr_and_eqe_fixture["spectral_response"]),
-        check_names=False,
-    )
-    # error on lack of wavelength parameter if no pandas object is provided
-    with pytest.raises(TypeError, match="must have an '.index' attribute"):
-        _ = spectrum.qe_to_sr(
-            sr_and_eqe_fixture["quantum_efficiency"].values
-        )
-
-
-def test_qe_and_sr_reciprocal_conversion(sr_and_eqe_fixture):
-    # test that the conversion functions are reciprocal
-    qe = spectrum.sr_to_qe(sr_and_eqe_fixture["spectral_response"])
-    sr = spectrum.qe_to_sr(qe)
-    assert_allclose(sr, sr_and_eqe_fixture["spectral_response"])
-    qe = spectrum.sr_to_qe(sr)
-    assert_allclose(qe, sr_and_eqe_fixture["quantum_efficiency"])