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28 | 28 | def times():
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29 | 29 | # must include night values
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30 | 30 | return pd.date_range(start='20140624', freq='6h', periods=4,
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31 |
| - tz='utc').tz_convert('US/Arizona') |
| 31 | + tz='US/Arizona') |
32 | 32 |
|
33 | 33 |
|
34 | 34 | @pytest.fixture
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@@ -112,7 +112,7 @@ def test_get_extra_radiation_nrel_numba(times):
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112 | 112 | # and reset to no-numba state
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113 | 113 | irradiance.get_extra_radiation(times, method='nrel')
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114 | 114 | assert_allclose(result,
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115 |
| - [1322.375560, 1322.338415, 1322.302221, 1322.266984]) |
| 115 | + [1322.332316, 1322.296282, 1322.261205, 1322.227091]) |
116 | 116 |
|
117 | 117 |
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118 | 118 | def test_get_extra_radiation_invalid():
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@@ -602,17 +602,17 @@ def test_poa_components(irrad_data, ephem_data, dni_et, relative_airmass):
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602 | 602 |
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603 | 603 | @pytest.mark.parametrize('pressure,expected', [
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604 | 604 | (93193, [[830.46567, 0.79742, 0.93505],
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605 |
| - [676.09497, 0.63776, 3.02102]]), |
| 605 | + [676.18340, 0.63782, 3.02102]]), |
606 | 606 | (None, [[868.72425, 0.79742, 1.01664],
|
607 |
| - [680.66679, 0.63776, 3.28463]]), |
| 607 | + [680.73800, 0.63782, 3.28463]]), |
608 | 608 | (101325, [[868.72425, 0.79742, 1.01664],
|
609 |
| - [680.66679, 0.63776, 3.28463]]) |
| 609 | + [680.73800, 0.63782, 3.28463]]) |
610 | 610 | ])
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611 | 611 | def test_disc_value(pressure, expected):
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612 | 612 | # see GH 449 for pressure=None vs. 101325.
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613 | 613 | columns = ['dni', 'kt', 'airmass']
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614 | 614 | times = pd.DatetimeIndex(['2014-06-24T1200', '2014-06-24T1800'],
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615 |
| - tz='utc').tz_convert('America/Phoenix') |
| 615 | + tz='America/Phoenix') |
616 | 616 | ghi = pd.Series([1038.62, 254.53], index=times)
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617 | 617 | zenith = pd.Series([10.567, 72.469], index=times)
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618 | 618 | out = irradiance.disc(ghi, zenith, times, pressure=pressure)
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@@ -1079,7 +1079,7 @@ def test_dirindex(times):
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1079 | 1079 | pressure=pressure,
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1080 | 1080 | use_delta_kt_prime=True,
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1081 | 1081 | temp_dew=tdew).values
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1082 |
| - expected_out = np.array([np.nan, 0., 748.31562753, 630.72592644]) |
| 1082 | + expected_out = np.array([np.nan, 0., 748.31562800, 630.73752100]) |
1083 | 1083 |
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1084 | 1084 | tolerance = 1e-8
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1085 | 1085 | assert np.allclose(out, expected_out, rtol=tolerance, atol=0,
|
|
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