LambertConformal 在错误位置的 cartopy 轴标签
Axis labels for LambertConformal in cartopy at wrong location
我想在 LambertConformal 投影中绘制一些数据并向轴添加标签。请参阅下面的示例代码。但是,现在 x 标签出现了两次,并且两次都出现在图的中间,而不是底部。相反,当我设置 gl.xlabels_bottom = False
和 gl.xlabels_top = True
时,根本不会绘制任何 x 标签。使用 y 标签,我没有遇到这个问题;它们只是沿着图的左边界或右边界很好地绘制。
如何在正确的位置(在图的底部)获得 x-labels?
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
lon = np.arange(bounds_lon[0],bounds_lon[1]+0.1,0.1)
lat = np.arange(bounds_lat[0],bounds_lat[1]+0.1,0.1)
Lon, Lat = np.meshgrid(lon,lat)
data = np.ones(np.shape(Lon))
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon),central_latitude=np.mean(bounds_lat),cutoff=bounds_lat[0])
plt.figure(figsize=(4,4))
ax = plt.axes(projection=projection)
ax.coastlines()
ax.contourf(Lon, Lat, data, transform=data_crs)
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='gray', alpha=0.5, linestyle='--')
gl.xlabels_bottom = True
需要手动重新定位刻度标签。要成功做到这一点,需要对绘图设置进行一些其他调整。这是您可以尝试的代码。
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
# make-up data to plot on the map
inc = 0.5
lon = np.arange(bounds_lon[0],bounds_lon[1]+inc, inc)
lat = np.arange(bounds_lat[0],bounds_lat[1]+inc, inc)
Lon, Lat = np.meshgrid(lon,lat)
#data = np.ones(np.shape(Lon)) # original `boring` data
data = np.sin(Lon)+np.cos(Lat) # better data to use instead
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
#cutoff=bounds_lat[0]
)
# Note: `cutoff` causes horizontal cut at lower edge
# init plot figure
plt.figure(figsize=(15,9))
ax = plt.axes(projection=projection)
ax.coastlines(lw=0.2)
ax.contourf(Lon, Lat, data, transform=data_crs, alpha=0.5)
# set gridlines specs
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='gray', alpha=0.5, linestyle='--')
gl.top_labels=True
gl.bottom_labels=True
gl.left_labels=True
gl.right_labels=True
plt.draw() #enable access to lables' positions
xs_ys = ax.get_extent() #(x0,x1, y0,y1)
#dx = xs_ys[1]-xs_ys[0]
dy = xs_ys[3]-xs_ys[2]
# The extent of `ax` must be adjusted
# Extents' below and above are increased
new_ext = [xs_ys[0], xs_ys[1], xs_ys[2]-dy/15., xs_ys[3]+dy/12.]
ax.set_extent(new_ext, crs=projection)
# find locations of the labels and reposition them as needed
xs, ys = [], []
for ix,ea in enumerate(gl.label_artists):
xy = ea[2].get_position()
xs.append(xy[0])
ys.append(xy[1])
# Targeted labels to manipulate has "W" in them
if "W" in ea[2].get_text():
x_y = ea[2].get_position()
# to check which are above/below mid latitude of the plot
# use 60 (valid only this special case)
if x_y[1]<60:
# labels at lower latitudes
curpos = ea[2].get_position()
newpos = (curpos[0], 54.7) # <- from inspection: 54.7
ea[2].set_position(newpos)
else:
curpos = ea[2].get_position()
newpos = (curpos[0], 65.3) # <- from inspection: 65.3
ea[2].set_position(newpos)
plt.show()
编辑1
如果您想将所有 lat/long 标签移动到外边缘,请尝试此代码。比上面简洁多了。
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
inc = 0.5
lon = np.arange(bounds_lon[0],bounds_lon[1]+inc, inc)
lat = np.arange(bounds_lat[0],bounds_lat[1]+inc, inc)
Lon, Lat = np.meshgrid(lon,lat)
#data = np.ones(np.shape(Lon)) # boring data
data = np.sin(Lon)+np.cos(Lat) # more interesting
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
cutoff=bounds_lat[0]
)
# init plot
plt.figure(figsize=(15,9))
ax = plt.axes(projection=projection)
ax.coastlines(lw=0.2)
ax.contourf(Lon, Lat, data, transform=data_crs, alpha=0.3)
gl = ax.gridlines(draw_labels=True, x_inline=False, y_inline=False,
color='k', linestyle='dashed', linewidth=0.5)
gl.top_labels=True
gl.bottom_labels=True
gl.left_labels=True
gl.right_labels=True
plt.show()
如果你想得到一条直线的底部边缘,你可以通过从这行代码中删除选项 cutoff=bounds_lat[0]
来实现:-
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
cutoff=bounds_lat[0]
)
这样就变成了
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon),
central_latitude=np.mean(bounds_lat))
你会得到这样的情节:-
我想在 LambertConformal 投影中绘制一些数据并向轴添加标签。请参阅下面的示例代码。但是,现在 x 标签出现了两次,并且两次都出现在图的中间,而不是底部。相反,当我设置 gl.xlabels_bottom = False
和 gl.xlabels_top = True
时,根本不会绘制任何 x 标签。使用 y 标签,我没有遇到这个问题;它们只是沿着图的左边界或右边界很好地绘制。
如何在正确的位置(在图的底部)获得 x-labels?
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
lon = np.arange(bounds_lon[0],bounds_lon[1]+0.1,0.1)
lat = np.arange(bounds_lat[0],bounds_lat[1]+0.1,0.1)
Lon, Lat = np.meshgrid(lon,lat)
data = np.ones(np.shape(Lon))
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon),central_latitude=np.mean(bounds_lat),cutoff=bounds_lat[0])
plt.figure(figsize=(4,4))
ax = plt.axes(projection=projection)
ax.coastlines()
ax.contourf(Lon, Lat, data, transform=data_crs)
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='gray', alpha=0.5, linestyle='--')
gl.xlabels_bottom = True
需要手动重新定位刻度标签。要成功做到这一点,需要对绘图设置进行一些其他调整。这是您可以尝试的代码。
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
# make-up data to plot on the map
inc = 0.5
lon = np.arange(bounds_lon[0],bounds_lon[1]+inc, inc)
lat = np.arange(bounds_lat[0],bounds_lat[1]+inc, inc)
Lon, Lat = np.meshgrid(lon,lat)
#data = np.ones(np.shape(Lon)) # original `boring` data
data = np.sin(Lon)+np.cos(Lat) # better data to use instead
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
#cutoff=bounds_lat[0]
)
# Note: `cutoff` causes horizontal cut at lower edge
# init plot figure
plt.figure(figsize=(15,9))
ax = plt.axes(projection=projection)
ax.coastlines(lw=0.2)
ax.contourf(Lon, Lat, data, transform=data_crs, alpha=0.5)
# set gridlines specs
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='gray', alpha=0.5, linestyle='--')
gl.top_labels=True
gl.bottom_labels=True
gl.left_labels=True
gl.right_labels=True
plt.draw() #enable access to lables' positions
xs_ys = ax.get_extent() #(x0,x1, y0,y1)
#dx = xs_ys[1]-xs_ys[0]
dy = xs_ys[3]-xs_ys[2]
# The extent of `ax` must be adjusted
# Extents' below and above are increased
new_ext = [xs_ys[0], xs_ys[1], xs_ys[2]-dy/15., xs_ys[3]+dy/12.]
ax.set_extent(new_ext, crs=projection)
# find locations of the labels and reposition them as needed
xs, ys = [], []
for ix,ea in enumerate(gl.label_artists):
xy = ea[2].get_position()
xs.append(xy[0])
ys.append(xy[1])
# Targeted labels to manipulate has "W" in them
if "W" in ea[2].get_text():
x_y = ea[2].get_position()
# to check which are above/below mid latitude of the plot
# use 60 (valid only this special case)
if x_y[1]<60:
# labels at lower latitudes
curpos = ea[2].get_position()
newpos = (curpos[0], 54.7) # <- from inspection: 54.7
ea[2].set_position(newpos)
else:
curpos = ea[2].get_position()
newpos = (curpos[0], 65.3) # <- from inspection: 65.3
ea[2].set_position(newpos)
plt.show()
编辑1
如果您想将所有 lat/long 标签移动到外边缘,请尝试此代码。比上面简洁多了。
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
bounds_lon = [-45,-25]
bounds_lat = [55,65]
inc = 0.5
lon = np.arange(bounds_lon[0],bounds_lon[1]+inc, inc)
lat = np.arange(bounds_lat[0],bounds_lat[1]+inc, inc)
Lon, Lat = np.meshgrid(lon,lat)
#data = np.ones(np.shape(Lon)) # boring data
data = np.sin(Lon)+np.cos(Lat) # more interesting
data_crs = ccrs.PlateCarree()
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
cutoff=bounds_lat[0]
)
# init plot
plt.figure(figsize=(15,9))
ax = plt.axes(projection=projection)
ax.coastlines(lw=0.2)
ax.contourf(Lon, Lat, data, transform=data_crs, alpha=0.3)
gl = ax.gridlines(draw_labels=True, x_inline=False, y_inline=False,
color='k', linestyle='dashed', linewidth=0.5)
gl.top_labels=True
gl.bottom_labels=True
gl.left_labels=True
gl.right_labels=True
plt.show()
如果你想得到一条直线的底部边缘,你可以通过从这行代码中删除选项 cutoff=bounds_lat[0]
来实现:-
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon), \
central_latitude=np.mean(bounds_lat), \
cutoff=bounds_lat[0]
)
这样就变成了
projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon),
central_latitude=np.mean(bounds_lat))
你会得到这样的情节:-