将 Basemap 转换为 Cartopy，是否有 Basemap 的 shiftgrid() 等等效函数？
Converting Basemap to Cartopy, are there quivalent functions such as Basemap's shiftgrid()?
我正在将一个使用 matplotlib 工具包 Basemap 的应用程序转换为使用 Cartopy，以准备从 Python 2 迁移到 Python 3。
我在 Cartopy 中为底图的 'addcyclic()' 和 'maskoceans()' 找到了类似的功能，
但是，对于底图的 shiftgrid() 函数，我在 numpy 或 Cartopy 中找不到类似的东西。
这是使用底图的代码：
'''
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np
from mpl_toolkits.basemap import shiftgrid
bmap = Basemap(projection='ortho', lat_0=0, lon_0=0)
lons = np.arange(30, 410, 30)
lons[1] = 70
lats = np.arange(0, 100, 10)
data = np.indices((lats.shape[0], lons.shape[0]))
data = data[0] + data[1]
data, lons = shiftgrid(180., data, lons, start=False)
llons, llats = np.meshgrid(lons, lats)
x, y = bmap(llons, llats)
bmap.contourf(x, y, data)
bmap.drawcoastlines()
'''
初始数据：
数据
'''
[[ 0 1 2 3 4 5 6 7 8 9 10 11 12]
[ 1 2 3 4 5 6 7 8 9 10 11 12 13]
[ 2 3 4 5 6 7 8 9 10 11 12 13 14]
[ 3 4 5 6 7 8 9 10 11 12 13 14 15]
[ 4 5 6 7 8 9 10 11 12 13 14 15 16]
[ 5 6 7 8 9 10 11 12 13 14 15 16 17]
[ 6 7 8 9 10 11 12 13 14 15 16 17 18]
[ 7 8 9 10 11 12 13 14 15 16 17 18 19]
[ 8 9 10 11 12 13 14 15 16 17 18 19 20]
[ 9 10 11 12 13 14 15 16 17 18 19 20 21]]
lons
[ 30 70 90 120 150 180 210 240 270 300 330 360 390]
After the 'data, lons = shiftgrid(180., data, lons, start=False)':
data
[[ 5 6 7 8 9 10 11 12 1 2 3 4 5]
[ 6 7 8 9 10 11 12 13 2 3 4 5 6]
[ 7 8 9 10 11 12 13 14 3 4 5 6 7]
[ 8 9 10 11 12 13 14 15 4 5 6 7 8]
[ 9 10 11 12 13 14 15 16 5 6 7 8 9]
[10 11 12 13 14 15 16 17 6 7 8 9 10]
[11 12 13 14 15 16 17 18 7 8 9 10 11]
[12 13 14 15 16 17 18 19 8 9 10 11 12]
[13 14 15 16 17 18 19 20 9 10 11 12 13]
[14 15 16 17 18 19 20 21 10 11 12 13 14]]
lons
[-180 -150 -120 -90 -60 -30 0 30 70 90 120 150 180]
'''
我尝试了以下 cartopy 代码来重新创建 Basemap shiftgrid 所做的事情。
这是 Cartopy 代码，有些东西在我一次尝试时被注释掉了：
'''
DATA_CRS = ccrs.PlateCarree()
lons = np.arange(30, 410, 30)
lons[1] = 70
lats = np.arange(0, 100, 10)
data = np.indices((lats.shape[0], lons.shape[0]))
data = data[0] + data[1]
# data2 = np.roll(data, -5)
# lons2 = np.mod(lons2 - 180.0, 360.0) - 180.0
cm_lon = 0
#llons, llats = np.meshgrid(lons2, lats)
llons, llats = np.meshgrid(lons, lats)
PROJECTION = ccrs.Orthographic(central_longitude=cm_lon)
fig1 = plt.figure(num=1, figsize=(11, 8.5), dpi=150)
ax = plt.axes(projection=PROJECTION)
ax.add_feature(cfeature.COASTLINE, linewidths=0.7)
ax.add_feature(cfeature.BORDERS, edgecolor='black', linewidths=0.7)
ax.contourf(llons, llats, data, transform=ccrs.PlateCarree())
'''
原始数据和经度，我只是在投影中使用了 'central_longitude'。
Basemap 图像显示整个地球，但 Cartopy 图像仅显示赤道以上。
除了最右侧外，数据的颜色看起来很相似，所以我担心数据在 Cartopy 中的映射与在 Basemap 中的映射不一样。
所以，问题是...是否有任何与 Basemap 的 shiftgrid() 等效的东西，或者我是否需要找出类似于 Basemap 的 shiftgrid() 的东西，或者只在投影中使用 'central_longitude'？
我似乎无法粘贴 .png 文件。
非常感谢任何帮助。
我在网上搜索了等效函数，但没有找到适用于 shiftgrid() 的函数。
谢谢。
我不知道有任何 shiftgrid 等效项。在请求此类功能的 CartoPy issue tracker 上开一个问题可能是值得的。提及一个可靠的用例来帮助推动功能将有助于这样做。
找到basemap的shiftgrid函数
here
您可以将它作为一个单独的函数与 cartopy 一起调用。
import numpy as np
import numpy.ma as ma
def shiftgrid(lon0,datain,lonsin,start=True,cyclic=360.0):
"""
Shift global lat/lon grid east or west.
.. tabularcolumns:: |l|L|
============== ====================================================
Arguments Description
============== ====================================================
lon0 starting longitude for shifted grid
(ending longitude if start=False). lon0 must be on
input grid (within the range of lonsin).
datain original data with longitude the right-most
dimension.
lonsin original longitudes.
============== ====================================================
.. tabularcolumns:: |l|L|
============== ====================================================
Keywords Description
============== ====================================================
start if True, lon0 represents the starting longitude
of the new grid. if False, lon0 is the ending
longitude. Default True.
cyclic width of periodic domain (default 360)
============== ====================================================
returns ``dataout,lonsout`` (data and longitudes on shifted grid).
"""
if np.fabs(lonsin[-1]-lonsin[0]-cyclic) > 1.e-4:
# Use all data instead of raise ValueError, 'cyclic point not included'
start_idx = 0
else:
# If cyclic, remove the duplicate point
start_idx = 1
if lon0 < lonsin[0] or lon0 > lonsin[-1]:
raise ValueError('lon0 outside of range of lonsin')
i0 = np.argmin(np.fabs(lonsin-lon0))
i0_shift = len(lonsin)-i0
if ma.isMA(datain):
dataout = ma.zeros(datain.shape,datain.dtype)
else:
dataout = np.zeros(datain.shape,datain.dtype)
if ma.isMA(lonsin):
lonsout = ma.zeros(lonsin.shape,lonsin.dtype)
else:
lonsout = np.zeros(lonsin.shape,lonsin.dtype)
if start:
lonsout[0:i0_shift] = lonsin[i0:]
else:
lonsout[0:i0_shift] = lonsin[i0:]-cyclic
dataout[...,0:i0_shift] = datain[...,i0:]
if start:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]+cyclic
else:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]
dataout[...,i0_shift:] = datain[...,start_idx:i0+start_idx]
return dataout,lonsout
这一定是最不优雅的解决方案，但我一直在为 Basemap 的几个有用功能做的（还没有？）在 cartopy 中，只是从 Basemap 的源代码中复制函数定义。它工作正常。例如，shiftgrid:
def shiftgrid(lon0,datain,lonsin,start=True,cyclic=360.0):
"""
Shift global lat/lon grid east or west.
.. tabularcolumns:: |l|L|
============== ====================================================
Arguments Description
============== ====================================================
lon0 starting longitude for shifted grid
(ending longitude if start=False). lon0 must be on
input grid (within the range of lonsin).
datain original data with longitude the right-most
dimension.
lonsin original longitudes.
============== ====================================================
.. tabularcolumns:: |l|L|
============== ====================================================
Keywords Description
============== ====================================================
start if True, lon0 represents the starting longitude
of the new grid. if False, lon0 is the ending
longitude. Default True.
cyclic width of periodic domain (default 360)
============== ====================================================
returns ``dataout,lonsout`` (data and longitudes on shifted grid).
"""
if np.fabs(lonsin[-1]-lonsin[0]-cyclic) > 1.e-4:
# Use all data instead of raise ValueError, 'cyclic point not included'
start_idx = 0
else:
# If cyclic, remove the duplicate point
start_idx = 1
if lon0 < lonsin[0] or lon0 > lonsin[-1]:
raise ValueError('lon0 outside of range of lonsin')
i0 = np.argmin(np.fabs(lonsin-lon0))
i0_shift = len(lonsin)-i0
if ma.isMA(datain):
dataout = ma.zeros(datain.shape,datain.dtype)
else:
dataout = np.zeros(datain.shape,datain.dtype)
if ma.isMA(lonsin):
lonsout = ma.zeros(lonsin.shape,lonsin.dtype)
else:
lonsout = np.zeros(lonsin.shape,lonsin.dtype)
if start:
lonsout[0:i0_shift] = lonsin[i0:]
else:
lonsout[0:i0_shift] = lonsin[i0:]-cyclic
dataout[...,0:i0_shift] = datain[...,i0:]
if start:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]+cyclic
else:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]
dataout[...,i0_shift:] = datain[...,start_idx:i0+start_idx]
return dataout,lonsout
我正在将一个使用 matplotlib 工具包 Basemap 的应用程序转换为使用 Cartopy，以准备从 Python 2 迁移到 Python 3。 我在 Cartopy 中为底图的 'addcyclic()' 和 'maskoceans()' 找到了类似的功能， 但是，对于底图的 shiftgrid() 函数，我在 numpy 或 Cartopy 中找不到类似的东西。
这是使用底图的代码： '''
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np
from mpl_toolkits.basemap import shiftgrid
bmap = Basemap(projection='ortho', lat_0=0, lon_0=0)
lons = np.arange(30, 410, 30)
lons[1] = 70
lats = np.arange(0, 100, 10)
data = np.indices((lats.shape[0], lons.shape[0]))
data = data[0] + data[1]
data, lons = shiftgrid(180., data, lons, start=False)
llons, llats = np.meshgrid(lons, lats)
x, y = bmap(llons, llats)
bmap.contourf(x, y, data)
bmap.drawcoastlines()
'''
初始数据： 数据 '''
[[ 0 1 2 3 4 5 6 7 8 9 10 11 12]
[ 1 2 3 4 5 6 7 8 9 10 11 12 13]
[ 2 3 4 5 6 7 8 9 10 11 12 13 14]
[ 3 4 5 6 7 8 9 10 11 12 13 14 15]
[ 4 5 6 7 8 9 10 11 12 13 14 15 16]
[ 5 6 7 8 9 10 11 12 13 14 15 16 17]
[ 6 7 8 9 10 11 12 13 14 15 16 17 18]
[ 7 8 9 10 11 12 13 14 15 16 17 18 19]
[ 8 9 10 11 12 13 14 15 16 17 18 19 20]
[ 9 10 11 12 13 14 15 16 17 18 19 20 21]]
lons
[ 30 70 90 120 150 180 210 240 270 300 330 360 390]
After the 'data, lons = shiftgrid(180., data, lons, start=False)':
data
[[ 5 6 7 8 9 10 11 12 1 2 3 4 5]
[ 6 7 8 9 10 11 12 13 2 3 4 5 6]
[ 7 8 9 10 11 12 13 14 3 4 5 6 7]
[ 8 9 10 11 12 13 14 15 4 5 6 7 8]
[ 9 10 11 12 13 14 15 16 5 6 7 8 9]
[10 11 12 13 14 15 16 17 6 7 8 9 10]
[11 12 13 14 15 16 17 18 7 8 9 10 11]
[12 13 14 15 16 17 18 19 8 9 10 11 12]
[13 14 15 16 17 18 19 20 9 10 11 12 13]
[14 15 16 17 18 19 20 21 10 11 12 13 14]]
lons
[-180 -150 -120 -90 -60 -30 0 30 70 90 120 150 180]
''' 我尝试了以下 cartopy 代码来重新创建 Basemap shiftgrid 所做的事情。 这是 Cartopy 代码，有些东西在我一次尝试时被注释掉了： '''
DATA_CRS = ccrs.PlateCarree()
lons = np.arange(30, 410, 30)
lons[1] = 70
lats = np.arange(0, 100, 10)
data = np.indices((lats.shape[0], lons.shape[0]))
data = data[0] + data[1]
# data2 = np.roll(data, -5)
# lons2 = np.mod(lons2 - 180.0, 360.0) - 180.0
cm_lon = 0
#llons, llats = np.meshgrid(lons2, lats)
llons, llats = np.meshgrid(lons, lats)
PROJECTION = ccrs.Orthographic(central_longitude=cm_lon)
fig1 = plt.figure(num=1, figsize=(11, 8.5), dpi=150)
ax = plt.axes(projection=PROJECTION)
ax.add_feature(cfeature.COASTLINE, linewidths=0.7)
ax.add_feature(cfeature.BORDERS, edgecolor='black', linewidths=0.7)
ax.contourf(llons, llats, data, transform=ccrs.PlateCarree())
'''
原始数据和经度，我只是在投影中使用了 'central_longitude'。 Basemap 图像显示整个地球，但 Cartopy 图像仅显示赤道以上。 除了最右侧外，数据的颜色看起来很相似，所以我担心数据在 Cartopy 中的映射与在 Basemap 中的映射不一样。
所以，问题是...是否有任何与 Basemap 的 shiftgrid() 等效的东西，或者我是否需要找出类似于 Basemap 的 shiftgrid() 的东西，或者只在投影中使用 'central_longitude'？ 我似乎无法粘贴 .png 文件。 非常感谢任何帮助。 我在网上搜索了等效函数，但没有找到适用于 shiftgrid() 的函数。 谢谢。
我不知道有任何 shiftgrid 等效项。在请求此类功能的 CartoPy issue tracker 上开一个问题可能是值得的。提及一个可靠的用例来帮助推动功能将有助于这样做。
找到basemap的shiftgrid函数 here 您可以将它作为一个单独的函数与 cartopy 一起调用。
import numpy as np
import numpy.ma as ma
def shiftgrid(lon0,datain,lonsin,start=True,cyclic=360.0):
"""
Shift global lat/lon grid east or west.
.. tabularcolumns:: |l|L|
============== ====================================================
Arguments Description
============== ====================================================
lon0 starting longitude for shifted grid
(ending longitude if start=False). lon0 must be on
input grid (within the range of lonsin).
datain original data with longitude the right-most
dimension.
lonsin original longitudes.
============== ====================================================
.. tabularcolumns:: |l|L|
============== ====================================================
Keywords Description
============== ====================================================
start if True, lon0 represents the starting longitude
of the new grid. if False, lon0 is the ending
longitude. Default True.
cyclic width of periodic domain (default 360)
============== ====================================================
returns ``dataout,lonsout`` (data and longitudes on shifted grid).
"""
if np.fabs(lonsin[-1]-lonsin[0]-cyclic) > 1.e-4:
# Use all data instead of raise ValueError, 'cyclic point not included'
start_idx = 0
else:
# If cyclic, remove the duplicate point
start_idx = 1
if lon0 < lonsin[0] or lon0 > lonsin[-1]:
raise ValueError('lon0 outside of range of lonsin')
i0 = np.argmin(np.fabs(lonsin-lon0))
i0_shift = len(lonsin)-i0
if ma.isMA(datain):
dataout = ma.zeros(datain.shape,datain.dtype)
else:
dataout = np.zeros(datain.shape,datain.dtype)
if ma.isMA(lonsin):
lonsout = ma.zeros(lonsin.shape,lonsin.dtype)
else:
lonsout = np.zeros(lonsin.shape,lonsin.dtype)
if start:
lonsout[0:i0_shift] = lonsin[i0:]
else:
lonsout[0:i0_shift] = lonsin[i0:]-cyclic
dataout[...,0:i0_shift] = datain[...,i0:]
if start:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]+cyclic
else:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]
dataout[...,i0_shift:] = datain[...,start_idx:i0+start_idx]
return dataout,lonsout
这一定是最不优雅的解决方案，但我一直在为 Basemap 的几个有用功能做的（还没有？）在 cartopy 中，只是从 Basemap 的源代码中复制函数定义。它工作正常。例如，shiftgrid:
def shiftgrid(lon0,datain,lonsin,start=True,cyclic=360.0):
"""
Shift global lat/lon grid east or west.
.. tabularcolumns:: |l|L|
============== ====================================================
Arguments Description
============== ====================================================
lon0 starting longitude for shifted grid
(ending longitude if start=False). lon0 must be on
input grid (within the range of lonsin).
datain original data with longitude the right-most
dimension.
lonsin original longitudes.
============== ====================================================
.. tabularcolumns:: |l|L|
============== ====================================================
Keywords Description
============== ====================================================
start if True, lon0 represents the starting longitude
of the new grid. if False, lon0 is the ending
longitude. Default True.
cyclic width of periodic domain (default 360)
============== ====================================================
returns ``dataout,lonsout`` (data and longitudes on shifted grid).
"""
if np.fabs(lonsin[-1]-lonsin[0]-cyclic) > 1.e-4:
# Use all data instead of raise ValueError, 'cyclic point not included'
start_idx = 0
else:
# If cyclic, remove the duplicate point
start_idx = 1
if lon0 < lonsin[0] or lon0 > lonsin[-1]:
raise ValueError('lon0 outside of range of lonsin')
i0 = np.argmin(np.fabs(lonsin-lon0))
i0_shift = len(lonsin)-i0
if ma.isMA(datain):
dataout = ma.zeros(datain.shape,datain.dtype)
else:
dataout = np.zeros(datain.shape,datain.dtype)
if ma.isMA(lonsin):
lonsout = ma.zeros(lonsin.shape,lonsin.dtype)
else:
lonsout = np.zeros(lonsin.shape,lonsin.dtype)
if start:
lonsout[0:i0_shift] = lonsin[i0:]
else:
lonsout[0:i0_shift] = lonsin[i0:]-cyclic
dataout[...,0:i0_shift] = datain[...,i0:]
if start:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]+cyclic
else:
lonsout[i0_shift:] = lonsin[start_idx:i0+start_idx]
dataout[...,i0_shift:] = datain[...,start_idx:i0+start_idx]
return dataout,lonsout