在错误位置的 cartopy 中 LambertConformal 的轴标签

如何解决在错误位置的 cartopy 中 LambertConformal 的轴标签

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，根本没有绘制 x 标签。使用 y 标签，我不会遇到这个问题；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）获取 x 标签？

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

解决方法

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

如果您想将所有经纬度标签移动到外边缘，请尝试使用此代码。比上面的简洁多了。

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs

bounds_lon = [-45,65]

inc = 0.5
lon = np.arange(bounds_lon[0],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),\
                                   cutoff=bounds_lat[0]
                                  )

# init plot
plt.figure(figsize=(15,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]
                              )

使它成为

projection = ccrs.LambertConformal(central_longitude=np.mean(bounds_lon),central_latitude=np.mean(bounds_lat))

你会得到这样的情节：-