Cartcopy中pcolormesh的问题

Question

我试图将环形南极立体图的Cartopy example plot改编为北极并向其添加数据。我有几个问题。

首先，在示例代码中，陆地特征在海洋特征之前被添加。当我这样做时，我得到了一张只有海洋的地图。我在下面的代码中颠倒了电话的顺序，并获得了陆地和海洋的地图。为什么其他订单与南极例子一起工作？

其次，更重要的是，我无法弄清楚为什么我的pcolormesh调用没有任何效果。

我使用Python 2.7.7，matplotlib 1.5.1和Cartopy 0.15.1。

import matplotlib.path as mpath 
import matplotlib.pyplot as plt 
import numpy as np 

import cartopy.crs as ccrs 
import cartopy.feature 

lats = np.linspace(60,90,30) 
lons = np.linspace(0,360,200) 
X,Y = np.meshgrid(lons,lats) 
Z = np.random.normal(size = X.shape) 

def main(): 
    fig = plt.figure(figsize=[10, 5]) 
    ax = plt.subplot(1, 1, 1, projection=ccrs.NorthPolarStereo()) 
    fig.subplots_adjust(bottom=0.05, top=0.95, 
         left=0.04, right=0.95, wspace=0.02) 

    # Limit the map to -60 degrees latitude and below. 
    ax.set_extent([-180, 180, 60, 60], ccrs.PlateCarree()) 

    ax.gridlines() 

    ax.add_feature(cartopy.feature.OCEAN) 
    ax.add_feature(cartopy.feature.LAND) 

    # Compute a circle in axes coordinates, which we can use as a boundary 
    # for the map. We can pan/zoom as much as we like - the boundary will be 
    # permanently circular. 
    theta = np.linspace(0, 2*np.pi, 100) 
    center, radius = [0.5, 0.5], 0.5 
    verts = np.vstack([np.sin(theta), np.cos(theta)]).T 
    circle = mpath.Path(verts * radius + center) 

    ax.set_boundary(circle, transform=ax.transAxes) 
    ax.pcolormesh(X,Y,Z,transform=ccrs.PlateCarree()) 


    plt.show() 


if __name__ == '__main__': 
    main() 

Answer 1

你的代码留下cartopy支配地图上的功能地块的顺序，因此，有些功能可以在没有线索被隐藏。可以明确指定图的顺序。

特征图的顺序由zorder控制，可以在大多数绘图语句中用zorder=integer指定。这是一个修改后的代码，可以产生更好的情节。

# your data 
lats = np.linspace(60, 90, 30) 
lons = np.linspace(0, 360, 160) 
X,Y = np.meshgrid(lons, lats) 
Z = np.random.normal(size = X.shape) 

# new data for pcolormesh plot 
latz = np.linspace(75, 90, 15) 
lonz = np.linspace(0, 360, 160) 
X1,Y1 = np.meshgrid(lonz, latz) 
Z1 = np.random.normal(size = X1.shape) 

def main(): 
    fig = plt.figure(figsize=[10, 10]) 
    ax = plt.subplot(1, 1, 1, projection=ccrs.NorthPolarStereo()) 
    fig.subplots_adjust(bottom=0.05, top=0.95, 
         left=0.04, right=0.95, wspace=0.02) 

    # Limit the map to -60 degrees latitude and below. 
    ax.set_extent([-180, 180, 60, 60], ccrs.PlateCarree()) 

    ax.gridlines() 

    # zorder can be used to arrange what is on top 
    ax.add_feature(cartopy.feature.LAND, zorder=4) # land is specified to plot above ... 
    ax.add_feature(cartopy.feature.OCEAN, zorder=1) # ... the ocean 

    # Compute a circle in axes coordinates, which we can use as a boundary 
    # for the map. We can pan/zoom as much as we like - the boundary will be 
    # permanently circular. 
    theta = np.linspace(0, 2*np.pi, 100) 
    center, radius = [0.5, 0.5], 0.5 
    verts = np.vstack([np.sin(theta), np.cos(theta)]).T 
    circle = mpath.Path(verts * radius + center) 

    ax.set_boundary(circle, transform=ax.transAxes) 
    # pcolormesh is specified to plot on top of the ocean but below land 
    ax.pcolormesh(X1, Y1, Z1, transform=ccrs.PlateCarree(), zorder=3) 

    plt.show() 

if __name__ == '__main__': 
    main()