Cartopy中的pcolormesh问题

Question

我正在尝试将Cartopy 样例图应用于南极的圆形极地立体图，并将数据添加到北极。我有几个问题要问。

首先，在示例代码中，在海洋特征之前添加土地特征。当我这么做的时候，我得到了一张只有海洋的地图。我在下面的代码中颠倒了调用的顺序，得到了一张有陆地和海洋的地图。为什么另一个命令与南极地的例子有效呢？

其次，也是更重要的是，我不明白为什么我的pcolormesh电话没有任何效果。

我正在使用Python2.7.7、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

您的代码将cartopy留给在地图上指定特征图的顺序，因此，一些特性可以被隐藏起来，没有任何线索。可以明确地规定情节的顺序。

特征图的顺序由zorder控制，可以在大多数绘图语句中使用zorder=integer指定。下面是一个经过修改的代码，可以生成更好的绘图。

# 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()

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