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Xarray + CF + CartoPy Projection Handling #786

Merged
merged 10 commits into from May 15, 2018
3 changes: 3 additions & 0 deletions .codeclimate.yml
Expand Up @@ -9,6 +9,9 @@ checks:
argument-count:
config:
threshold: 10
method-complexity:
config:
threshold: 15

plugins:
sonar-python:
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4 changes: 3 additions & 1 deletion .codecov.yml
Expand Up @@ -22,7 +22,9 @@ coverage:

tests:
target: 100%
paths: "metpy/.*/tests/.*"
paths:
- "metpy/.*/tests/.*"
- "metpy/tests/.*"

notify:
gitter:
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2 changes: 1 addition & 1 deletion .travis.yml
Expand Up @@ -48,7 +48,7 @@ matrix:
include:
- python: 2.7
env:
- VERSIONS="numpy==1.10.0 matplotlib==1.4.0 scipy==0.14.0 pint==0.8"
- VERSIONS="numpy==1.10.0 matplotlib==1.4.0 scipy==0.14.0 pint==0.8 xarray==0.9.0"
- TASK="coverage"
- TEST_OUTPUT_CONTROL=""
- python: 3.4
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35 changes: 35 additions & 0 deletions examples/XArray_Projections.py
@@ -0,0 +1,35 @@
# Copyright (c) 2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
XArray Projection Handling
==========================

Use MetPy's XArray accessors to simplify opening a data file and plotting
data on a map using CartoPy.
"""
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import xarray as xr

# Ensure xarray accessors are available
import metpy.io # noqa: F401
from metpy.testing import get_test_data

ds = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
data_var = ds.metpy.parse_cf('Temperature')

x = data_var.x
y = data_var.y
im_data = data_var.isel(time=0).sel(isobaric=1000.)

fig = plt.figure(figsize=(14, 14))
ax = fig.add_subplot(1, 1, 1, projection=data_var.metpy.cartopy_crs)

ax.imshow(im_data, extent=(x.min(), x.max(), y.min(), y.max()),
cmap='RdBu', origin='lower' if y[0] < y[-1] else 'upper')
ax.coastlines(color='tab:green', resolution='10m')
ax.add_feature(cfeature.LAKES.with_scale('10m'), facecolor='none', edgecolor='tab:blue')
ax.add_feature(cfeature.RIVERS.with_scale('10m'), edgecolor='tab:blue')

plt.show()
27 changes: 7 additions & 20 deletions examples/formats/GINI_Water_Vapor.py
Expand Up @@ -8,7 +8,6 @@
Use MetPy's support for GINI files to read in a water vapor satellite image and plot the
data using CartoPy.
"""
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import xarray as xr
Expand All @@ -24,33 +23,21 @@
print(f)

###########################################

# Get a Dataset view of the data (essentially a NetCDF-like interface to the
# underlying data). Pull out the data, (x, y) coordinates, and the projection
# information.
# underlying data). Pull out the data and (x, y) coordinates. We use `metpy.parse_cf` to
# handle parsing some netCDF Climate and Forecasting (CF) metadata to simplify working with
# projections.
ds = xr.open_dataset(f)
x = ds.variables['x'][:]
y = ds.variables['y'][:]
dat = ds.variables['WV']
proj_var = ds.variables[dat.attrs['grid_mapping']]
print(proj_var)
dat = ds.metpy.parse_cf('WV')

###########################################

# Create CartoPy projection information for the file
globe = ccrs.Globe(ellipse='sphere', semimajor_axis=proj_var.attrs['earth_radius'],
semiminor_axis=proj_var.attrs['earth_radius'])
proj = ccrs.LambertConformal(central_longitude=proj_var.attrs['longitude_of_central_meridian'],
central_latitude=proj_var.attrs['latitude_of_projection_origin'],
standard_parallels=[proj_var.attrs['standard_parallel']],
globe=globe)

###########################################

# Plot the image
# Plot the image. We use MetPy's xarray/cartopy integration to automatically handle parsing
# the projection information.
fig = plt.figure(figsize=(10, 12))
add_metpy_logo(fig, 125, 145)
ax = fig.add_subplot(1, 1, 1, projection=proj)
ax = fig.add_subplot(1, 1, 1, projection=dat.metpy.cartopy_crs)
wv_norm, wv_cmap = colortables.get_with_range('WVCIMSS', 100, 260)
wv_cmap.set_under('k')
im = ax.imshow(dat[:], cmap=wv_cmap, norm=wv_norm,
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3 changes: 2 additions & 1 deletion metpy/calc/kinematics.py
Expand Up @@ -8,7 +8,6 @@
import warnings

import numpy as np
from pyproj import Geod

from ..calc import coriolis_parameter
from ..calc.tools import first_derivative, get_layer_heights, gradient
Expand Down Expand Up @@ -698,6 +697,8 @@ def lat_lon_grid_deltas(longitude, latitude, **kwargs):
Assumes [Y, X] for 2D arrays

"""
from pyproj import Geod

# Inputs must be the same number of dimensions
if latitude.ndim != longitude.ndim:
raise ValueError('Latitude and longitude must have the same number of dimensions.')
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39 changes: 37 additions & 2 deletions metpy/cbook.py
@@ -1,4 +1,4 @@
# Copyright (c) 2008,2015 MetPy Developers.
# Copyright (c) 2008,2015,2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Collection of generally useful utility code from the cookbook."""
Expand Down Expand Up @@ -39,4 +39,39 @@ def get_test_data(fname, as_file_obj=True):
return path


__all__ = ('get_test_data', 'is_string_like', 'iterable')
class Registry(object):
"""Provide a generic function registry.

This provides a class to instantiate, which then has a `register` method that can
be used as a decorator on functions to register them under a particular name.
"""

def __init__(self):
"""Initialize an empty registry."""
self._registry = {}

def register(self, name):
"""Register a callable with the registry under a particular name.

Parameters
----------
name : str
The name under which to register a function

Returns
-------
dec : callable
A decorator that takes a function and will register it under the name.

"""
def dec(func):
self._registry[name] = func
return func
return dec

def __getitem__(self, name):
"""Return any callable registered under name."""
return self._registry[name]


__all__ = ('Registry', 'get_test_data', 'is_string_like', 'iterable')
4 changes: 3 additions & 1 deletion metpy/io/__init__.py
@@ -1,4 +1,4 @@
# Copyright (c) 2015,2016 MetPy Developers.
# Copyright (c) 2015,2016,2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""MetPy's IO module contains classes for reading files. These classes are written
Expand All @@ -9,6 +9,8 @@

from .gini import * # noqa: F403
from .nexrad import * # noqa: F403
from .xarray import * # noqa: F403

__all__ = gini.__all__[:] # pylint: disable=undefined-variable
__all__.extend(nexrad.__all__) # pylint: disable=undefined-variable
__all__.extend(xarray.__all__) # pylint: disable=undefined-variable
1 change: 1 addition & 0 deletions metpy/io/gini.py
Expand Up @@ -2,6 +2,7 @@
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Tools to process GINI-formatted products."""
from __future__ import absolute_import

import contextlib
from datetime import datetime
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108 changes: 108 additions & 0 deletions metpy/io/tests/test_xarray.py
@@ -0,0 +1,108 @@
# Copyright (c) 2018 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Test the operation of MetPy's XArray accessors."""

import cartopy.crs as ccrs
import numpy as np
import pytest
import xarray as xr

# Get activate the xarray accessors
import metpy.io # noqa: F401
from metpy.testing import assert_almost_equal, get_test_data
from metpy.units import units


@pytest.fixture
def test_ds():
"""Provide an xarray dataset for testing."""
return xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))


@pytest.fixture
def test_var():
"""Provide a standard, parsed, variable for testing."""
ds = test_ds()
return ds.metpy.parse_cf('Temperature')


def test_projection(test_var):
"""Test getting the proper projection out of the variable."""
crs = test_var.metpy.crs
assert crs['grid_mapping_name'] == 'lambert_conformal_conic'

assert isinstance(test_var.metpy.cartopy_crs, ccrs.LambertConformal)


def test_no_projection(test_ds):
"""Test getting the crs attribute when not available produces a sensible error."""
var = test_ds.lat
with pytest.raises(AttributeError) as exc:
var.metpy.crs

assert 'not available' in str(exc.value)


def test_units(test_var):
"""Test unit handling through the accessor."""
arr = test_var.metpy.unit_array
assert isinstance(arr, units.Quantity)
assert arr.units == units.kelvin


def test_convert_units(test_var):
"""Test in-place conversion of units."""
test_var.metpy.convert_units('degC')

# Check that variable metadata is updated
assert test_var.attrs['units'] == 'degC'

# Make sure we now get an array back with properly converted values
assert test_var.metpy.unit_array.units == units.degC
assert_almost_equal(test_var[0, 0, 0, 0], 18.44 * units.degC, 2)


def test_radian_projection_coords():
"""Test fallback code for radian units in projection coordinate variables."""
proj = xr.DataArray(0, attrs={'grid_mapping_name': 'geostationary',
'perspective_point_height': 3})
x = xr.DataArray(np.arange(3),
attrs={'standard_name': 'projection_x_coordinate', 'units': 'radians'})
y = xr.DataArray(np.arange(2),
attrs={'standard_name': 'projection_y_coordinate', 'units': 'radians'})
data = xr.DataArray(np.arange(6).reshape(2, 3), coords=(y, x), dims=('y', 'x'),
attrs={'grid_mapping': 'fixedgrid_projection'})
ds = xr.Dataset({'data': data, 'fixedgrid_projection': proj})

# Check that the coordinates in this case are properly converted
data_var = ds.metpy.parse_cf('data')
assert data_var.coords['x'].metpy.unit_array[1] == 3 * units.meter
assert data_var.coords['y'].metpy.unit_array[1] == 3 * units.meter


def test_missing_grid_mapping():
"""Test falling back to implicit lat/lon projection."""
lon = xr.DataArray(-np.arange(3),
attrs={'standard_name': 'longitude', 'units': 'degrees_east'})
lat = xr.DataArray(np.arange(2),
attrs={'standard_name': 'latitude', 'units': 'degrees_north'})
data = xr.DataArray(np.arange(6).reshape(2, 3), coords=(lat, lon), dims=('y', 'x'))
ds = xr.Dataset({'data': data})

data_var = ds.metpy.parse_cf('data')
assert 'crs' in data_var.coords


def test_missing_grid_mapping_var():
"""Test behavior when we can't find the variable pointed to by grid_mapping."""
x = xr.DataArray(np.arange(3),
attrs={'standard_name': 'projection_x_coordinate', 'units': 'radians'})
y = xr.DataArray(np.arange(2),
attrs={'standard_name': 'projection_y_coordinate', 'units': 'radians'})
data = xr.DataArray(np.arange(6).reshape(2, 3), coords=(y, x), dims=('y', 'x'),
attrs={'grid_mapping': 'fixedgrid_projection'})
ds = xr.Dataset({'data': data})

with pytest.warns(UserWarning, match='Could not find'):
ds.metpy.parse_cf('data')