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test_omni.test_mask_missing()   A

Complexity

Conditions 3

Size

Total Lines 10
Code Lines 8

Duplication

Lines 0
Ratio 0 %

Importance

Changes 0
Metric Value
cc 3
eloc 8
nop 0
dl 0
loc 10
rs 10
c 0
b 0
f 0
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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) 2022 Stefan Bender
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#
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# This module is part of pyspaceweather.
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# pyspaceweather 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 COPYING.GPLv2 file or http://www.gnu.org/licenses/gpl-2.0.html.
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"""OMNI data read tests
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"""
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import os
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import requests
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import numpy as np
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import pandas as pd
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import pytest
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from spaceweather import cache_omnie, omnie_hourly, omnie_mask_missing, sw_daily
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from spaceweather.omni import OMNI_URL_BASE, OMNI_PREFIX, OMNI_EXT
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_TEST_YEAR = 2012
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_TEST_FILE = "{0}_{1:04d}.{2}".format(OMNI_PREFIX, _TEST_YEAR, OMNI_EXT)
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_TEST_URL = os.path.join(OMNI_URL_BASE, _TEST_FILE)
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_TEST_PATH = os.path.join(".", "tests")
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def test_cache(mocker, tmpdir):
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	mocker.patch("requests.get")
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	tmpdir = str(tmpdir)
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	# Check non-existent file
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	cache_omnie(year=_TEST_YEAR, local_path=tmpdir)
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	requests.get.assert_called_once_with(_TEST_URL, stream=True)
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	# Check non-existent (sub)dir
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	tmppath = os.path.join(tmpdir, "data")
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	cache_omnie(year=_TEST_YEAR, local_path=tmppath)
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	requests.get.assert_called_with(_TEST_URL, stream=True)
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def test_auto_update(mocker, tmpdir):
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	# test with non-existent file
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	mocker.patch("requests.get")
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	tmpdir = str(tmpdir)
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	with pytest.raises(IOError):
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		with pytest.warns(UserWarning):
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			omnie_hourly(year=_TEST_YEAR, cache=True, local_path=tmpdir)
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	requests.get.assert_called_once_with(_TEST_URL, stream=True)
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def test_not_avail(mocker, tmpdir):
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	# test with non-existent file
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	tmpdir = str(tmpdir)
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	with pytest.raises(IOError):
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		with pytest.warns(UserWarning):
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			omnie_hourly(year=_TEST_YEAR, cache=False, local_path=tmpdir)
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@pytest.mark.parametrize("hour", range(0, 24, 3))
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@pytest.mark.parametrize("index", ["Ap", "Kp"])
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def test_hourly(hour, index):
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	df1 = omnie_hourly(2000, local_path=_TEST_PATH, prefix="omni2t")
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	# The last row is for the missing value test.
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	df1 = df1.iloc[:-1]
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	df2 = sw_daily()
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	ind_name = "{0}{1}".format(index, hour)
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	df1_ind = df1[df1["hour"] == hour][index]
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	df2_ind = df2[ind_name].loc[df1_ind.index.date].rename(index)
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	df2_ind.index = df1_ind.index
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	pd.testing.assert_series_equal(df1_ind, df2_ind)
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@pytest.mark.parametrize(
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	"name, result",
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	[
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		("Ap", np.array([56, 39, 27, 18, 32, 15, 32, 22])),
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		("Kp", np.array([5.3, 4.7, 4.0, 3.3, 4.3, 3.0, 4.3, 3.7])),
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	]
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)
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def test_3hourly_index(name, result):
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	df = omnie_hourly(2000, local_path=_TEST_PATH, prefix="omni2t")
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	np.testing.assert_allclose(
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		df.loc[
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			pd.date_range(
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				"2000-01-01 00:00", "2000-01-01 23:00", freq="3h"
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			)
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		][name].values,
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		result,
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		rtol=1e-12,
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	)
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def test_mask_missing():
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	df = omnie_hourly(2000, local_path=_TEST_PATH, prefix="omni2t")
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	dfp = omnie_mask_missing(df)
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	# The last row should contain all NaNs.
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	dfp = dfp.iloc[-1]
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	for v in filter(
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		lambda n: n not in ["year", "doy", "hour"],
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		dfp.index,
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	):
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		assert np.isnan(dfp[v])
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