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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 contextlib
import importlib
import textwrap
import matplotlib.pyplot
import numpy
import pyproj
import pytest
import xarray
import metpy.calc
import metpy.units
def pytest_report_header():
"""Add dependency information to pytest output."""
lines = []
for modname in ('cartopy', 'dask', 'matplotlib', 'numpy', 'pandas', 'pint', 'pooch',
'pyproj', 'scipy', 'shapely', 'traitlets', 'xarray'):
with contextlib.suppress(ImportError):
mod = importlib.import_module(modname)
lines.append(f'{modname.title()}:{mod.__version__}')
# textwrap.wrap will split on the space in 'mod: version', so add space afterwards
lines = textwrap.wrap('Dep Versions:' + ', '.join(lines), width=80, subsequent_indent='\t')
return [line.replace(':', ': ') for line in lines]
@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(['2018-07-01T00:00', '2018-07-01T06:00', '2018-07-01T12:00'],
dtype='datetime64[ns]'),
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(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}')
@pytest.fixture
def geog_data(request):
"""Create data to use for testing calculations on geographic coordinates."""
# Generate a field of u and v on a lat/lon grid
crs = pyproj.CRS(request.param)
proj = pyproj.Proj(crs)
a = numpy.arange(4)[None, :]
arr = numpy.r_[a, a, a] * metpy.units.units('m/s')
lons = numpy.array([-100, -90, -80, -70]) * metpy.units.units.degree
lats = numpy.array([45, 55, 65]) * metpy.units.units.degree
lon_arr, lat_arr = numpy.meshgrid(lons.m_as('degree'), lats.m_as('degree'))
factors = proj.get_factors(lon_arr, lat_arr)
return (crs, lons, lats, arr, arr, factors.parallel_scale, factors.meridional_scale,
metpy.calc.lat_lon_grid_deltas(lons.m, numpy.zeros_like(lons.m),
geod=crs.get_geod())[0][0],
metpy.calc.lat_lon_grid_deltas(numpy.zeros_like(lats.m), lats.m,
geod=crs.get_geod())[1][:, 0])
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