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# -*- coding: utf-8 -*- |
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# vim:fileencoding=utf-8 |
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# |
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# Copyright (c) 2018 Stefan Bender |
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# |
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# This module is part of sciapy. |
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# sciapy is free software: you can redistribute it or modify |
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# it under the terms of the GNU General Public License as published |
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# by the Free Software Foundation, version 2. |
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# See accompanying LICENSE file or http://www.gnu.org/licenses/gpl-2.0.html. |
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"""SCIAMACHY regression module data loading tests |
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""" |
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from datetime import datetime |
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from pkg_resources import resource_filename |
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from astropy.time import Time |
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import numpy as np |
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from pytest import mark, raises |
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try: |
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import netCDF4 |
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NC_EXT = ".nc" |
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except ImportError: |
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NC_EXT = ".nc3" |
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import sciapy.regress |
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DZM_FILE = resource_filename(__name__, "sciaNO_20100203_v6.2.1_geogra30" + NC_EXT) |
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AEdata = [ |
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("2000-01-01", "jyear", 1999.9986311, 507.208333), |
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("2000-01-01", "jd", 2451544.5, 507.208333), |
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("2000-01-01", "mjd", 51544.0, 507.208333), |
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("2007-07-01", "jyear", 2007.4948665, 83.208333), |
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("2007-07-01", "jd", 2454282.5, 83.208333), |
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("2007-07-01", "mjd", 54282.0, 83.208333), |
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] |
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Lyadata = [ |
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("2000-01-01", "jyear", 1999.9986311, 4.59), |
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("2000-01-01", "jd", 2451544.5, 4.59), |
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("2000-01-01", "mjd", 51544.0, 4.59), |
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("2007-07-01", "jyear", 2007.4948665, 3.74), |
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("2007-07-01", "jd", 2454282.5, 3.74), |
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("2007-07-01", "mjd", 54282.0, 3.74), |
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] |
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def test_load_proxyAEfiles(): |
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AEfile = resource_filename("sciapy", |
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"data/indices/AE_Kyoto_1980-2018_daily2_shift12h.dat") |
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pAEt, pAEv = sciapy.regress.load_solar_gm_table(AEfile, |
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cols=[0, 1], names=["time", "AE"], tfmt="jyear") |
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pAEt2, pAEv2 = sciapy.regress.load_data.load_dailymeanAE() |
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np.testing.assert_allclose(pAEt, pAEt2) |
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def test_load_proxyLyafiles(): |
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Lyafile = resource_filename("sciapy", |
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"data/indices/lisird_lya3_1980-2021.dat") |
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pLyat, pLyav = sciapy.regress.load_solar_gm_table(Lyafile, |
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cols=[0, 1], names=["time", "Lya"], tfmt="jyear") |
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pLyat2, pLyav2 = sciapy.regress.load_data.load_dailymeanLya() |
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np.testing.assert_allclose(pLyat, pLyat2) |
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@mark.parametrize("date, tfmt, texp, vexp", AEdata) |
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def test_load_proxyAEvalues(date, tfmt, texp, vexp): |
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pAEt, pAEv = sciapy.regress.load_data.load_dailymeanAE(tfmt=tfmt) |
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idx = list(Time(pAEt, format=tfmt).iso).index(date + " 00:00:00.000") |
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np.testing.assert_allclose(pAEt[idx], texp) |
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np.testing.assert_allclose(pAEv["AE"][idx], vexp) |
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@mark.parametrize("date, tfmt, texp, vexp", Lyadata) |
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def test_load_proxyLyavalues(date, tfmt, texp, vexp): |
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pLyat, pLyav = sciapy.regress.load_data.load_dailymeanLya(tfmt=tfmt) |
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idx = list(Time(pLyat, format=tfmt).iso).index(date + " 00:00:00.000") |
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np.testing.assert_allclose(pLyat[idx], texp) |
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np.testing.assert_allclose(pLyav["Lya"][idx], vexp) |
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def test_load_dzm_normal(): |
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data = sciapy.regress.load_scia_dzm(DZM_FILE, 70., -75.) |
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np.testing.assert_allclose(data[0], np.array([2010.09184335])) |
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np.testing.assert_allclose(data[1], np.array([25992364.81988303])) |
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np.testing.assert_allclose(data[2], np.array([2722294.10593951])) |
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np.testing.assert_allclose(data[3], np.array([65.5642548])) |
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def test_load_dzm_center(): |
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data = sciapy.regress.load_scia_dzm(DZM_FILE, 70., -45., center=True) |
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np.testing.assert_allclose(data[0], np.array([2010.09184335])) |
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np.testing.assert_allclose(data[1], np.array([-9293324.84946741])) |
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np.testing.assert_allclose(data[2], np.array([2337592.1464543])) |
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np.testing.assert_allclose(data[3], np.array([46.02054338])) |
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def test_load_dzm_spe(): |
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data = sciapy.regress.load_scia_dzm(DZM_FILE, 70., 15., SPEs=True) |
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np.testing.assert_allclose(data[0], np.array([2010.09184335])) |
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np.testing.assert_allclose(data[1], np.array([10184144.7669378])) |
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np.testing.assert_allclose(data[2], np.array([2633165.7502271])) |
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np.testing.assert_allclose(data[3], np.array([45.41338086])) |
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def test_load_dzm_summerSH(): |
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data = sciapy.regress.load_scia_dzm(DZM_FILE, 70., 45., season="summerSH") |
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np.testing.assert_allclose(data[0], np.array([2010.09184335])) |
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np.testing.assert_allclose(data[1], np.array([24484783.29918655])) |
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np.testing.assert_allclose(data[2], np.array([2814284.4588219])) |
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np.testing.assert_allclose(data[3], np.array([65.04123748])) |
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def test_load_dzm_summerNH(): |
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data = sciapy.regress.load_scia_dzm(DZM_FILE, 70., 75., season="summerNH") |
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np.testing.assert_equal(data[0], np.array([])) |
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np.testing.assert_equal(data[1], np.array([])) |
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np.testing.assert_equal(data[2], np.array([])) |
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np.testing.assert_equal(data[3], np.array([])) |
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st-bender /
sciapy
