如何使用Cartopy和Matplotlib掩盖海洋中出现的数据

Question

根本不确定我做错了什么，除了我绘制海洋的顺序外，我正在尝试获得海洋功能来掩盖海洋中的数据。我试图使数据不出现在海洋中，而是要获得AX.ADD_FEATURE（CFEATURE.OCEAN），以置于我绘制的温度数据的顶部，因此我看到了海洋，没有数据。类似于大湖区正在看到湖泊而没有温度数据的大湖区发生的事情。

proj_map = ccrs.Mercator(central_longitude=cLon)
proj_data = ccrs.PlateCarree()

fig = plt.figure(figsize=(30,20))
ax = fig.add_subplot(1,1,1, projection=proj_map)
ax.set_extent([-84,-66,37,47.5])

CT = ax.contourf(Tlat, Tlon, tempF, transform=temp.metpy.cartopy_crs, levels=clevs, 
cmap=cmap)

ax.add_feature(cfeature.COASTLINE.with_scale('10m'), linewidth=0.5)
ax.add_feature(cfeature.OCEAN)
ax.add_feature(cfeature.LAKES)
ax.add_feature(cfeature.BORDERS, linewidth=0.5)
ax.add_feature(cfeature.STATES.with_scale('10m'), linewidth=0.5)
ax.add_feature(USCOUNTIES.with_scale('20m'), linewidth=0.25)

cbar = fig.colorbar(CT, orientation='horizontal', shrink=0.5, pad=0.05)
cbar.ax.tick_params(labelsize=14)
cbar.set_ticks([-50, -40, -30, -20, -10, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 
110, 120])
cbar.ax.set_xlabel("Temp ($^\circ$F)",fontsize=20)

这是图像的样子

Answer 1

您需要使用Zorder选项来指定地图上图的正确订单。具有Zorder的大量值的特征将绘制在具有较低值的基础上。就您而言，您需要大于填充的海洋的Zorder。

这是可运行的演示代码及其示例图。在代码中阅读评论以进行解释。

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

fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(projection=ccrs.PlateCarree()))
extent = [-84, -66, 37, 47.5]

# generate (x, y), centered at the middle of the `extent`
mean = [(extent[0]+extent[1])/2, (extent[2]+extent[3])/2] #mean
cov = [[7, 3.5], [3.5, 6]]  #co-variance matrix
x, y = np.random.multivariate_normal(mean, cov, 4000).T

# make a 2D histogram
# set the edges of the bins in x and y directions
bin_size = 40
lonrange = np.linspace(extent[0], extent[1], bin_size)
latrange = np.linspace(extent[2], extent[3], bin_size)

# the cell sizes of the bins:
dx = (lonrange[1]- lonrange[0])/2
dy = (latrange[3]- latrange[2])/2

# compute array of center points of the bins' grid
# the dimensions of mesh-grid < the edges by 1
lonrange2 = np.linspace(extent[0]+dx, extent[1]-dx, bin_size-1)
latrange2 = np.linspace(extent[2]+dy, extent[3]-dy, bin_size-1)
x2d, y2d = np.meshgrid(lonrange2, latrange2)

# create 2d-histogram
# zorder is set = 10
h = ax.hist2d(x, y, bins=[lonrange, latrange], zorder=10, alpha=0.75)
#h: (counts, xedges, yedges, image)

ax.add_feature(cfeature.OCEAN, zorder=12)  #zorder > 10
ax.add_feature(cfeature.BORDERS, linewidth=0.5)

ax.gridlines(draw_labels=True, xlocs=list(range(-85, -60, 5)), ylocs=list(range(35, 50, 5)), 
             linewidth=1.8, color='gray', linestyle='--', alpha=0.8, zorder=20)


# plot colorbar, using image from hist2d's result
plt.colorbar(h[3], ax=ax, shrink=0.45)
# finally, show the plot.
plt.show()

输出图：

如果未指定Zorder选项：

ax.add_feature(cfeature.OCEAN)

绘图将为：

https://i.sstatic.net/b7kax.png“ alt =“ second-plot”>