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# (C) British Crown Copyright 2014 - 2018, Met Office
#
# This file is part of cartopy.
#
# cartopy is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# cartopy is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with cartopy. If not, see <https://www.gnu.org/licenses/>.
"""
This module contains utilities that are useful in conjunction with
cartopy.
"""
from __future__ import (absolute_import, division, print_function)
import numpy as np
import numpy.ma as ma
def add_cyclic_point(data, coord=None, axis=-1):
"""
Add a cyclic point to an array and optionally a corresponding
coordinate.
Parameters
----------
data
An n-dimensional array of data to add a cyclic point to.
coord: optional
A 1-dimensional array which specifies the coordinate values for
the dimension the cyclic point is to be added to. The coordinate
values must be regularly spaced. Defaults to None.
axis: optional
Specifies the axis of the data array to add the cyclic point to.
Defaults to the right-most axis.
Returns
-------
cyclic_data
The data array with a cyclic point added.
cyclic_coord
The coordinate with a cyclic point, only returned if the coord
keyword was supplied.
Examples
--------
Adding a cyclic point to a data array, where the cyclic dimension is
the right-most dimension
.. testsetup::
>>> from distutils.version import LooseVersion
>>> import numpy as np
>>> if LooseVersion(np.__version__) >= '1.14.0':
... # To provide consistent doctests.
... np.set_printoptions(legacy='1.13')
>>> import numpy as np
>>> data = np.ones([5, 6]) * np.arange(6)
>>> cyclic_data = add_cyclic_point(data)
>>> print(cyclic_data) # doctest: +NORMALIZE_WHITESPACE
[[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]]
Adding a cyclic point to a data array and an associated coordinate
>>> lons = np.arange(0, 360, 60)
>>> cyclic_data, cyclic_lons = add_cyclic_point(data, coord=lons)
>>> print(cyclic_data) # doctest: +NORMALIZE_WHITESPACE
[[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]
[ 0. 1. 2. 3. 4. 5. 0.]]
>>> print(cyclic_lons)
[ 0 60 120 180 240 300 360]
"""
if coord is not None:
if coord.ndim != 1:
raise ValueError('The coordinate must be 1-dimensional.')
if len(coord) != data.shape[axis]:
raise ValueError('The length of the coordinate does not match '
'the size of the corresponding dimension of '
'the data array: len(coord) = {}, '
'data.shape[{}] = {}.'.format(
len(coord), axis, data.shape[axis]))
delta_coord = np.diff(coord)
if not np.allclose(delta_coord, delta_coord[0]):
raise ValueError('The coordinate must be equally spaced.')
new_coord = ma.concatenate((coord, coord[-1:] + delta_coord[0]))
slicer = [slice(None)] * data.ndim
try:
slicer[axis] = slice(0, 1)
except IndexError:
raise ValueError('The specified axis does not correspond to an '
'array dimension.')
new_data = ma.concatenate((data, data[tuple(slicer)]), axis=axis)
if coord is None:
return_value = new_data
else:
return_value = new_data, new_coord
return return_value
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