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conftest.py
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conftest.py
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# Copyright (c) 2016,2019 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Configure pytest for metpy."""
import os
import matplotlib
import matplotlib.pyplot
import numpy
import pandas
import pooch
import pyproj
import pytest
import scipy
import traitlets
import xarray
import metpy.calc
import metpy.units
# Need to disable fallback before importing pint
os.environ['PINT_ARRAY_PROTOCOL_FALLBACK'] = '0'
import pint # noqa: I100, E402
try:
pooch_version = pooch.__version__
except AttributeError:
pooch_version = pooch.version.full_version
def pytest_report_header(config, startdir):
"""Add dependency information to pytest output."""
return (f'Dep Versions: Matplotlib {matplotlib.__version__}, '
f'NumPy {numpy.__version__}, Pandas {pandas.__version__}, '
f'Pint {pint.__version__}, Pooch {pooch_version}\n'
f'\tPyProj {pyproj.__version__}, SciPy {scipy.__version__}, '
f'Traitlets {traitlets.__version__}, Xarray {xarray.__version__}')
@pytest.fixture(autouse=True)
def doctest_available_modules(doctest_namespace):
"""Make modules available automatically to doctests."""
doctest_namespace['metpy'] = metpy
doctest_namespace['metpy.calc'] = metpy.calc
doctest_namespace['np'] = numpy
doctest_namespace['plt'] = matplotlib.pyplot
doctest_namespace['units'] = metpy.units.units
@pytest.fixture()
def ccrs():
"""Provide access to the ``cartopy.crs`` module through a global fixture.
Any testing function/fixture that needs access to ``cartopy.crs`` can simply add this to
their parameter list.
"""
return pytest.importorskip('cartopy.crs')
@pytest.fixture
def cfeature():
"""Provide access to the ``cartopy.feature`` module through a global fixture.
Any testing function/fixture that needs access to ``cartopy.feature`` can simply add this
to their parameter list.
"""
return pytest.importorskip('cartopy.feature')
@pytest.fixture()
def test_da_lonlat():
"""Return a DataArray with a lon/lat grid and no time coordinate for use in tests."""
data = numpy.linspace(300, 250, 3 * 4 * 4).reshape((3, 4, 4))
ds = xarray.Dataset(
{'temperature': (['isobaric', 'lat', 'lon'], data)},
coords={
'isobaric': xarray.DataArray(
numpy.array([850., 700., 500.]),
name='isobaric',
dims=['isobaric'],
attrs={'units': 'hPa'}
),
'lat': xarray.DataArray(
numpy.linspace(30, 40, 4),
name='lat',
dims=['lat'],
attrs={'units': 'degrees_north'}
),
'lon': xarray.DataArray(
numpy.linspace(260, 270, 4),
name='lon',
dims=['lon'],
attrs={'units': 'degrees_east'}
)
}
)
ds['temperature'].attrs['units'] = 'kelvin'
return ds.metpy.parse_cf('temperature')
@pytest.fixture()
def test_da_xy():
"""Return a DataArray with a x/y grid and a time coordinate for use in tests."""
data = numpy.linspace(300, 250, 3 * 3 * 4 * 4).reshape((3, 3, 4, 4))
ds = xarray.Dataset(
{'temperature': (['time', 'isobaric', 'y', 'x'], data),
'lambert_conformal': ([], '')},
coords={
'time': xarray.DataArray(
numpy.array([numpy.datetime64('2018-07-01T00:00'),
numpy.datetime64('2018-07-01T06:00'),
numpy.datetime64('2018-07-01T12:00')]),
name='time',
dims=['time']
),
'isobaric': xarray.DataArray(
numpy.array([850., 700., 500.]),
name='isobaric',
dims=['isobaric'],
attrs={'units': 'hPa'}
),
'y': xarray.DataArray(
numpy.linspace(-1000, 500, 4),
name='y',
dims=['y'],
attrs={'units': 'km'}
),
'x': xarray.DataArray(
numpy.linspace(0, 1500, 4),
name='x',
dims=['x'],
attrs={'units': 'km'}
)
}
)
ds['temperature'].attrs = {
'units': 'kelvin',
'grid_mapping': 'lambert_conformal'
}
ds['lambert_conformal'].attrs = {
'grid_mapping_name': 'lambert_conformal_conic',
'standard_parallel': 50.0,
'longitude_of_central_meridian': -107.0,
'latitude_of_projection_origin': 50.0,
'earth_shape': 'spherical',
'earth_radius': 6367470.21484375
}
return ds.metpy.parse_cf('temperature')
@pytest.fixture()
def set_agg_backend():
"""Fixture to ensure the Agg backend is active."""
prev_backend = matplotlib.pyplot.get_backend()
try:
matplotlib.pyplot.switch_backend('agg')
yield
finally:
matplotlib.pyplot.switch_backend(prev_backend)
@pytest.fixture(params=['dask', 'xarray', 'masked', 'numpy'])
def array_type(request):
"""Return an array type for testing calc functions."""
quantity = metpy.units.units.Quantity
if request.param == 'dask':
dask_array = pytest.importorskip('dask.array', reason='dask.array is not available')
marker = request.node.get_closest_marker('xfail_dask')
if marker is not None:
request.applymarker(pytest.mark.xfail(reason=marker.args[0]))
return lambda d, u, *, mask=None: quantity(dask_array.array(d), u)
elif request.param == 'xarray':
return lambda d, u, *, mask=None: xarray.DataArray(d, attrs={'units': u})
elif request.param == 'masked':
return lambda d, u, *, mask=None: quantity(numpy.ma.array(d, mask=mask), u)
elif request.param == 'numpy':
return lambda d, u, *, mask=None: quantity(numpy.array(d), u)
else:
raise ValueError(f'Unsupported array_type option {request.param}')