total_deformation() - Code Metrics - Inspection of "MNT: Refactor `lcl` to use `scipy.optimize`" - Unidata/MetPy - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Pull Request — master (#439)

by Ryan

created 2017-05-31 17:14 UTC

total_deformation() B

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loc	36
rs	8.8571
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# Copyright (c) 2008-2015 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Contains calculation of kinematic parameters (e.g. divergence or vorticity)."""
from __future__ import division

import functools
import warnings

import numpy as np

from ..cbook import is_string_like, iterable
from ..constants import g
from ..package_tools import Exporter
from ..units import atleast_2d, concatenate, units

exporter = Exporter(globals())


def _gradient(f, *args, **kwargs):
    """Wrap :func:`numpy.gradient` to handle units."""
    if len(args) < f.ndim:
        args = list(args)
        args.extend([units.Quantity(1., 'dimensionless')] * (f.ndim - len(args)))
    grad = np.gradient(f, *(a.magnitude for a in args), **kwargs)
    if f.ndim == 1:
        return units.Quantity(grad, f.units / args[0].units)
    return [units.Quantity(g, f.units / dx.units) for dx, g in zip(args, grad)]


def _stack(arrs):
    return concatenate([a[np.newaxis] for a in arrs], axis=0)


def _get_gradients(u, v, dx, dy):
    """Return derivatives for components to simplify calculating convergence and vorticity."""
    dudy, dudx = _gradient(u, dy, dx)
    dvdy, dvdx = _gradient(v, dy, dx)
    return dudx, dudy, dvdx, dvdy


def _is_x_first_dim(dim_order):
    """Determine whether x is the first dimension based on the value of dim_order."""
    if dim_order is None:
        warnings.warn('dim_order is using the default setting (currently "xy"). This will '
                      'change to "yx" in the next version. It is recommended that you '
                      'specify the appropriate ordering ("xy", "yx") for your data by '
                      'passing the `dim_order` argument to the calculation.', FutureWarning)
        dim_order = 'xy'
    return dim_order == 'xy'


def _check_and_flip(arr):
    """Transpose array or list of arrays if they are 2D."""
    if hasattr(arr, 'ndim'):
        if arr.ndim >= 2:
            return arr.T
        else:
            return arr
    elif not is_string_like(arr) and iterable(arr):
        return tuple(_check_and_flip(a) for a in arr)
    else:
        return arr


def ensure_yx_order(func):
    """Wrap a function to ensure all array arguments are y, x ordered, based on kwarg."""
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        # Check what order we're given
        dim_order = kwargs.pop('dim_order', None)
        x_first = _is_x_first_dim(dim_order)

        # If x is the first dimension, flip (transpose) every array within the function args.
        if x_first:
            args = tuple(_check_and_flip(arr) for arr in args)
            for k, v in kwargs:
                kwargs[k] = _check_and_flip(v)

        ret = func(*args, **kwargs)

        # If we flipped on the way in, need to flip on the way out so that output array(s)
        # match the dimension order of the original input.
        if x_first:
            return _check_and_flip(ret)
        else:
            return ret

    # Inject a docstring for the dim_order argument into the function's docstring.
    dim_order_doc = """
    dim_order : str or ``None``, optional
        The ordering of dimensions in passed in arrays. Can be one of ``None``, ``'xy'``,
        or ``'yx'``. ``'xy'`` indicates that the dimension corresponding to x is the leading
        dimension, followed by y. ``'yx'`` indicates that x is the last dimension, preceded
        by y. ``None`` indicates that the default ordering should be assumed,
        which will change in version 0.6 from 'xy' to 'yx'. Can only be passed as a keyword
        argument, i.e. func(..., dim_order='xy')."""

    # Find the first blank line after the start of the parameters section
    params = wrapper.__doc__.find('Parameters')
    blank = wrapper.__doc__.find('\n\n', params)
    wrapper.__doc__ = wrapper.__doc__[:blank] + dim_order_doc + wrapper.__doc__[blank:]

    return wrapper


@exporter.export
@ensure_yx_order
def v_vorticity(u, v, dx, dy):
    r"""Calculate the vertical vorticity of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    (M, N) ndarray
        vertical vorticity

    See Also
    --------
    h_convergence, convergence_vorticity

    """
    _, dudy, dvdx, _ = _get_gradients(u, v, dx, dy)
    return dvdx - dudy


@exporter.export
@ensure_yx_order
def h_convergence(u, v, dx, dy):
    r"""Calculate the horizontal convergence of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    (M, N) ndarray
        The horizontal convergence

    See Also
    --------
    v_vorticity, convergence_vorticity

    """
    dudx, _, _, dvdy = _get_gradients(u, v, dx, dy)
    return dudx + dvdy


@exporter.export
@ensure_yx_order
def convergence_vorticity(u, v, dx, dy):
    r"""Calculate the horizontal convergence and vertical vorticity of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    convergence, vorticity : tuple of (M, N) ndarrays
        The horizontal convergence and vertical vorticity, respectively

    See Also
    --------
    v_vorticity, h_convergence

    Notes
    -----
    This is a convenience function that will do less work than calculating
    the horizontal convergence and vertical vorticity separately.

    """
    dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
    return dudx + dvdy, dvdx - dudy


@exporter.export
@ensure_yx_order
def shearing_deformation(u, v, dx, dy):
    r"""Calculate the shearing deformation of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    (M, N) ndarray
        Shearing Deformation

    See Also
    --------
    stretching_convergence, shearing_stretching_deformation

    """
    _, dudy, dvdx, _ = _get_gradients(u, v, dx, dy)
    return dvdx + dudy


@exporter.export
@ensure_yx_order
def stretching_deformation(u, v, dx, dy):
    r"""Calculate the stretching deformation of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    (M, N) ndarray
        Stretching Deformation

    See Also
    --------
    shearing_deformation, shearing_stretching_deformation

    """
    dudx, _, _, dvdy = _get_gradients(u, v, dx, dy)
    return dudx - dvdy


@exporter.export
@ensure_yx_order
def shearing_stretching_deformation(u, v, dx, dy):
    r"""Calculate the horizontal shearing and stretching deformation of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    shearing, strectching : tuple of (M, N) ndarrays
        The horizontal shearing and stretching deformation, respectively

    See Also
    --------
    shearing_deformation, stretching_deformation

    Notes
    -----
    This is a convenience function that will do less work than calculating
    the shearing and streching deformation terms separately.

    """
    dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
    return dvdx + dudy, dudx - dvdy


@exporter.export
@ensure_yx_order
def total_deformation(u, v, dx, dy):
    r"""Calculate the horizontal total deformation of the horizontal wind.

    The grid must have a constant spacing in each direction.

    Parameters
    ----------
    u : (M, N) ndarray
        x component of the wind
    v : (M, N) ndarray
        y component of the wind
    dx : float
        The grid spacing in the x-direction
    dy : float
        The grid spacing in the y-direction

    Returns
    -------
    (M, N) ndarray
        Total Deformation

    See Also
    --------
    shearing_deformation, stretching_deformation, shearing_stretching_deformation

    Notes
    -----
    This is a convenience function that will do less work than calculating
    the shearing and streching deformation terms separately and calculating the
    total deformation "by hand".

    """
    dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
    return np.sqrt((dvdx + dudy)**2 + (dudx - dvdy)**2)


@exporter.export
@ensure_yx_order
def advection(scalar, wind, deltas):
    r"""Calculate the advection of a scalar field by the wind.

    The order of the dimensions of the arrays must match the order in which
    the wind components are given.  For example, if the winds are given [u, v],
    then the scalar and wind arrays must be indexed as x,y (which puts x as the
    rows, not columns).

    Parameters
    ----------
    scalar : N-dimensional array
        Array (with N-dimensions) with the quantity to be advected.
    wind : sequence of arrays
        Length N sequence of N-dimensional arrays.  Represents the flow,
        with a component of the wind in each dimension.  For example, for
        horizontal advection, this could be a list: [u, v], where u and v
        are each a 2-dimensional array.
    deltas : sequence
        A (length N) sequence containing the grid spacing in each dimension.

    Returns
    -------
    N-dimensional array
        An N-dimensional array containing the advection at all grid points.

    """
    # This allows passing in a list of wind components or an array.
    wind = _stack(wind)

    # If we have more than one component, we need to reverse the order along the first
    # dimension so that the wind components line up with the
    # order of the gradients from the ..., y, x ordered array.
    if wind.ndim > scalar.ndim:
        wind = wind[::-1]

    # Gradient returns a list of derivatives along each dimension. We convert
    # this to an array with dimension as the first index. Reverse the deltas to line up
    # with the order of the dimensions.
    grad = _stack(_gradient(scalar, *deltas[::-1]))

    # Make them be at least 2D (handling the 1D case) so that we can do the
    # multiply and sum below
    grad, wind = atleast_2d(grad, wind)

    return (-grad * wind).sum(axis=0)


@exporter.export
@ensure_yx_order
def geostrophic_wind(heights, f, dx, dy):
    r"""Calculate the geostrophic wind given from the heights or geopotential.

    Parameters
    ----------
    heights : (M, N) ndarray
        The height field, with either leading dimensions of (x, y) or trailing dimensions
        of (y, x), depending on the value of ``dim_order``.
    f : array_like
        The coriolis parameter.  This can be a scalar to be applied
        everywhere or an array of values.
    dx : scalar
        The grid spacing in the x-direction
    dy : scalar
        The grid spacing in the y-direction

    Returns
    -------
    A 2-item tuple of arrays
        A tuple of the u-component and v-component of the geostrophic wind.

    """
    if heights.dimensionality['[length]'] == 2.0:
        norm_factor = 1. / f
    else:
        norm_factor = g / f

    # If heights has more than 2 dimensions, we need to pass in some dummy
    # grid deltas so that we can still use np.gradient. It may be better to
    # to loop in this case, but that remains to be done.
    deltas = [dy, dx]
    if heights.ndim > 2:
        deltas = [units.Quantity(1., units.m)] * (heights.ndim - 2) + deltas

    grad = _gradient(heights, *deltas)
    dy, dx = grad[-2:]  # Throw away unused gradient components
    return -norm_factor * dy, norm_factor * dx


1			# Copyright (c) 2008-2015 MetPy Developers.
2			# Distributed under the terms of the BSD 3-Clause License.
3			# SPDX-License-Identifier: BSD-3-Clause
4			"""Contains calculation of kinematic parameters (e.g. divergence or vorticity)."""
5			from __future__ import division
6
7			import functools
8			import warnings
9
10			import numpy as np
11
12			from ..cbook import is_string_like, iterable
13			from ..constants import g
14			from ..package_tools import Exporter
15			from ..units import atleast_2d, concatenate, units
16
17			exporter = Exporter(globals())
18
19
20			def _gradient(f, args, *kwargs):
21			"""Wrap :func:`numpy.gradient` to handle units."""
22			if len(args) < f.ndim:
23			args = list(args)
24			args.extend([units.Quantity(1., 'dimensionless')] * (f.ndim - len(args)))
25			grad = np.gradient(f, (a.magnitude for a in args), *kwargs)
26			if f.ndim == 1:
27			return units.Quantity(grad, f.units / args[0].units)
28			return [units.Quantity(g, f.units / dx.units) for dx, g in zip(args, grad)]
29
30
31			def _stack(arrs):
32			return concatenate([a[np.newaxis] for a in arrs], axis=0)
33
34
35			def _get_gradients(u, v, dx, dy):
36			"""Return derivatives for components to simplify calculating convergence and vorticity."""
37			dudy, dudx = _gradient(u, dy, dx)
38			dvdy, dvdx = _gradient(v, dy, dx)
39			return dudx, dudy, dvdx, dvdy
40
41
42			def _is_x_first_dim(dim_order):
43			"""Determine whether x is the first dimension based on the value of dim_order."""
44			if dim_order is None:
45			warnings.warn('dim_order is using the default setting (currently "xy"). This will '
46			'change to "yx" in the next version. It is recommended that you '
47			'specify the appropriate ordering ("xy", "yx") for your data by '
48			'passing the `dim_order` argument to the calculation.', FutureWarning)
49			dim_order = 'xy'
50			return dim_order == 'xy'
51
52
53			def _check_and_flip(arr):
54			"""Transpose array or list of arrays if they are 2D."""
55			if hasattr(arr, 'ndim'):
56			if arr.ndim >= 2:
57			return arr.T
58			else:
59			return arr
60			elif not is_string_like(arr) and iterable(arr):
61			return tuple(_check_and_flip(a) for a in arr)
62			else:
63			return arr
64
65
66			def ensure_yx_order(func):
67			"""Wrap a function to ensure all array arguments are y, x ordered, based on kwarg."""
68			@functools.wraps(func)
69			def wrapper(args, *kwargs):
70			# Check what order we're given
71			dim_order = kwargs.pop('dim_order', None)
72			x_first = _is_x_first_dim(dim_order)
73
74			# If x is the first dimension, flip (transpose) every array within the function args.
75			if x_first:
76			args = tuple(_check_and_flip(arr) for arr in args)
77			for k, v in kwargs:
78			kwargs[k] = _check_and_flip(v)
79
80			ret = func(args, *kwargs)
81
82			# If we flipped on the way in, need to flip on the way out so that output array(s)
83			# match the dimension order of the original input.
84			if x_first:
85			return _check_and_flip(ret)
86			else:
87			return ret
88
89			# Inject a docstring for the dim_order argument into the function's docstring.
90			dim_order_doc = """
91			dim_order : str or ``None``, optional
92			The ordering of dimensions in passed in arrays. Can be one of ``None``, ``'xy'``,
93			or ``'yx'``. ``'xy'`` indicates that the dimension corresponding to x is the leading
94			dimension, followed by y. ``'yx'`` indicates that x is the last dimension, preceded
95			by y. ``None`` indicates that the default ordering should be assumed,
96			which will change in version 0.6 from 'xy' to 'yx'. Can only be passed as a keyword
97			argument, i.e. func(..., dim_order='xy')."""
98
99			# Find the first blank line after the start of the parameters section
100			params = wrapper.__doc__.find('Parameters')
101			blank = wrapper.__doc__.find('\n\n', params)
102			wrapper.__doc__ = wrapper.__doc__[:blank] + dim_order_doc + wrapper.__doc__[blank:]
103
104			return wrapper
105
106
107			@exporter.export
108			@ensure_yx_order
109			def v_vorticity(u, v, dx, dy):
110			r"""Calculate the vertical vorticity of the horizontal wind.
111
112			The grid must have a constant spacing in each direction.
113
114			Parameters
115			----------
116			u : (M, N) ndarray
117			x component of the wind
118			v : (M, N) ndarray
119			y component of the wind
120			dx : float
121			The grid spacing in the x-direction
122			dy : float
123			The grid spacing in the y-direction
124
125			Returns
126			-------
127			(M, N) ndarray
128			vertical vorticity
129
130			See Also
131			--------
132			h_convergence, convergence_vorticity
133
134			"""
135			_, dudy, dvdx, _ = _get_gradients(u, v, dx, dy)
136			return dvdx - dudy
137
138
139			@exporter.export
140			@ensure_yx_order
141			def h_convergence(u, v, dx, dy):
142			r"""Calculate the horizontal convergence of the horizontal wind.
143
144			The grid must have a constant spacing in each direction.
145
146			Parameters
147			----------
148			u : (M, N) ndarray
149			x component of the wind
150			v : (M, N) ndarray
151			y component of the wind
152			dx : float
153			The grid spacing in the x-direction
154			dy : float
155			The grid spacing in the y-direction
156
157			Returns
158			-------
159			(M, N) ndarray
160			The horizontal convergence
161
162			See Also
163			--------
164			v_vorticity, convergence_vorticity
165
166			"""
167			dudx, _, _, dvdy = _get_gradients(u, v, dx, dy)
168			return dudx + dvdy
169
170
171			@exporter.export
172			@ensure_yx_order
173			def convergence_vorticity(u, v, dx, dy):
174			r"""Calculate the horizontal convergence and vertical vorticity of the horizontal wind.
175
176			The grid must have a constant spacing in each direction.
177
178			Parameters
179			----------
180			u : (M, N) ndarray
181			x component of the wind
182			v : (M, N) ndarray
183			y component of the wind
184			dx : float
185			The grid spacing in the x-direction
186			dy : float
187			The grid spacing in the y-direction
188
189			Returns
190			-------
191			convergence, vorticity : tuple of (M, N) ndarrays
192			The horizontal convergence and vertical vorticity, respectively
193
194			See Also
195			--------
196			v_vorticity, h_convergence
197
198			Notes
199			-----
200			This is a convenience function that will do less work than calculating
201			the horizontal convergence and vertical vorticity separately.
202
203			"""
204			dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
205			return dudx + dvdy, dvdx - dudy
206
207
208			@exporter.export
209			@ensure_yx_order
210			def shearing_deformation(u, v, dx, dy):
211			r"""Calculate the shearing deformation of the horizontal wind.
212
213			The grid must have a constant spacing in each direction.
214
215			Parameters
216			----------
217			u : (M, N) ndarray
218			x component of the wind
219			v : (M, N) ndarray
220			y component of the wind
221			dx : float
222			The grid spacing in the x-direction
223			dy : float
224			The grid spacing in the y-direction
225
226			Returns
227			-------
228			(M, N) ndarray
229			Shearing Deformation
230
231			See Also
232			--------
233			stretching_convergence, shearing_stretching_deformation
234
235			"""
236			_, dudy, dvdx, _ = _get_gradients(u, v, dx, dy)
237			return dvdx + dudy
238
239
240			@exporter.export
241			@ensure_yx_order
242			def stretching_deformation(u, v, dx, dy):
243			r"""Calculate the stretching deformation of the horizontal wind.
244
245			The grid must have a constant spacing in each direction.
246
247			Parameters
248			----------
249			u : (M, N) ndarray
250			x component of the wind
251			v : (M, N) ndarray
252			y component of the wind
253			dx : float
254			The grid spacing in the x-direction
255			dy : float
256			The grid spacing in the y-direction
257
258			Returns
259			-------
260			(M, N) ndarray
261			Stretching Deformation
262
263			See Also
264			--------
265			shearing_deformation, shearing_stretching_deformation
266
267			"""
268			dudx, _, _, dvdy = _get_gradients(u, v, dx, dy)
269			return dudx - dvdy
270
271
272			@exporter.export
273			@ensure_yx_order
274			def shearing_stretching_deformation(u, v, dx, dy):
275			r"""Calculate the horizontal shearing and stretching deformation of the horizontal wind.
276
277			The grid must have a constant spacing in each direction.
278
279			Parameters
280			----------
281			u : (M, N) ndarray
282			x component of the wind
283			v : (M, N) ndarray
284			y component of the wind
285			dx : float
286			The grid spacing in the x-direction
287			dy : float
288			The grid spacing in the y-direction
289
290			Returns
291			-------
292			shearing, strectching : tuple of (M, N) ndarrays
293			The horizontal shearing and stretching deformation, respectively
294
295			See Also
296			--------
297			shearing_deformation, stretching_deformation
298
299			Notes
300			-----
301			This is a convenience function that will do less work than calculating
302			the shearing and streching deformation terms separately.
303
304			"""
305			dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
306			return dvdx + dudy, dudx - dvdy
307
308
309			@exporter.export
310			@ensure_yx_order
311			def total_deformation(u, v, dx, dy):
312			r"""Calculate the horizontal total deformation of the horizontal wind.
313
314			The grid must have a constant spacing in each direction.
315
316			Parameters
317			----------
318			u : (M, N) ndarray
319			x component of the wind
320			v : (M, N) ndarray
321			y component of the wind
322			dx : float
323			The grid spacing in the x-direction
324			dy : float
325			The grid spacing in the y-direction
326
327			Returns
328			-------
329			(M, N) ndarray
330			Total Deformation
331
332			See Also
333			--------
334			shearing_deformation, stretching_deformation, shearing_stretching_deformation
335
336			Notes
337			-----
338			This is a convenience function that will do less work than calculating
339			the shearing and streching deformation terms separately and calculating the
340			total deformation "by hand".
341
342			"""
343			dudx, dudy, dvdx, dvdy = _get_gradients(u, v, dx, dy)
344			return np.sqrt((dvdx + dudy)2 + (dudx - dvdy)2)
345
346
347			@exporter.export
348			@ensure_yx_order
349			def advection(scalar, wind, deltas):
350			r"""Calculate the advection of a scalar field by the wind.
351
352			The order of the dimensions of the arrays must match the order in which
353			the wind components are given. For example, if the winds are given [u, v],
354			then the scalar and wind arrays must be indexed as x,y (which puts x as the
355			rows, not columns).
356
357			Parameters
358			----------
359			scalar : N-dimensional array
360			Array (with N-dimensions) with the quantity to be advected.
361			wind : sequence of arrays
362			Length N sequence of N-dimensional arrays. Represents the flow,
363			with a component of the wind in each dimension. For example, for
364			horizontal advection, this could be a list: [u, v], where u and v
365			are each a 2-dimensional array.
366			deltas : sequence
367			A (length N) sequence containing the grid spacing in each dimension.
368
369			Returns
370			-------
371			N-dimensional array
372			An N-dimensional array containing the advection at all grid points.
373
374			"""
375			# This allows passing in a list of wind components or an array.
376			wind = _stack(wind)
377
378			# If we have more than one component, we need to reverse the order along the first
379			# dimension so that the wind components line up with the
380			# order of the gradients from the ..., y, x ordered array.
381			if wind.ndim > scalar.ndim:
382			wind = wind[::-1]
383
384			# Gradient returns a list of derivatives along each dimension. We convert
385			# this to an array with dimension as the first index. Reverse the deltas to line up
386			# with the order of the dimensions.
387			grad = _stack(_gradient(scalar, *deltas[::-1]))
388
389			# Make them be at least 2D (handling the 1D case) so that we can do the
390			# multiply and sum below
391			grad, wind = atleast_2d(grad, wind)
392
393			return (-grad * wind).sum(axis=0)
394
395
396			@exporter.export
397			@ensure_yx_order
398			def geostrophic_wind(heights, f, dx, dy):
399			r"""Calculate the geostrophic wind given from the heights or geopotential.
400
401			Parameters
402			----------
403			heights : (M, N) ndarray
404			The height field, with either leading dimensions of (x, y) or trailing dimensions
405			of (y, x), depending on the value of ``dim_order``.
406			f : array_like
407			The coriolis parameter. This can be a scalar to be applied
408			everywhere or an array of values.
409			dx : scalar
410			The grid spacing in the x-direction
411			dy : scalar
412			The grid spacing in the y-direction
413
414			Returns
415			-------
416			A 2-item tuple of arrays
417			A tuple of the u-component and v-component of the geostrophic wind.
418
419			"""
420			if heights.dimensionality['[length]'] == 2.0:
421			norm_factor = 1. / f
422			else:
423			norm_factor = g / f
424
425			# If heights has more than 2 dimensions, we need to pass in some dummy
426			# grid deltas so that we can still use np.gradient. It may be better to
427			# to loop in this case, but that remains to be done.
428			deltas = [dy, dx]
429			if heights.ndim > 2:
430			deltas = [units.Quantity(1., units.m)] * (heights.ndim - 2) + deltas
431
432			grad = _gradient(heights, *deltas)
433			dy, dx = grad[-2:] # Throw away unused gradient components
434			return -norm_factor * dy, norm_factor * dx
435

Unidata / MetPy

Pull Request — master (#439)

total_deformation() B

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