Matplotlib/CartoPy等高线图下方的实心填充 [英] Matplotlib/CartoPy Solid Fill Underneath Contour Plot

问题描述

我希望在我的轮廓数据(Matplotlib 中的轮廓)下方添加一个实体填充.具体来说，我希望将实体填充限制为特定的 shapefile，在这种情况下，美国大陆的各个州.

I am looking to add a solid fill underneath my contoured data (contourf in Matplotlib). Specifically, I would like the solid fill to be constrained to specific shapefiles, in this case individual states in the continental United States.

我当前的情节

我当前的代码

请注意，我已经包括绘制轮廓和shapefile的关键内部工作，我已经排除了无关的代码(例如城市地块)来帮助那些致力于解决此问题的人.

Please note that I've included the key inner workings to plot the contours and shapefiles, I've excluded extraneous code (like the city plots) to help those working on a solution to this question.

import os, sys, re, ast, tifffile
import matplotlib.pyplot as plt
import matplotlib.colors as clr
import matplotlib.figure as fig
import matplotlib as mpl
import cartopy.crs as crs
import cartopy.feature as cfeature
from matplotlib.offsetbox import AnnotationBbox, OffsetImage
from cartopy.io.shapereader import Reader
from cartopy.feature import ShapelyFeature

states = '/filepath/gis/st_us.shp'
counties = '/filepath/gis/cnt_us.shp'
lakes_hires = '/filepath/gis/lk_us.shp'
states_feature = ShapelyFeature(Reader(states).geometries(), crs.LambertConformal(), facecolor='none', edgecolor='black')
states_fill = ShapelyFeature(Reader(states).geometries(), crs.LambertConformal(), facecolor='#C7C6C1', edgecolor='none')
counties_feature = ShapelyFeature(Reader(counties).geometries(), crs.LambertConformal(), facecolor='none', edgecolor='lightgray')
lakeshi_feature = ShapelyFeature(Reader(lakes_hires).geometries(), crs.LambertConformal(), facecolor='none', edgecolor='navy')

file = '/filepath/gis/globalpop_conus_1km.tif'
tiffimage = tifffile.imread(file)
lat0 = 52.817021799999999
lon0 = -130.122944799999999 
dlat = 0.008332904595765
dlon = 0.008332442558080
tiffimage[tiffimage<-1e100]=np.nan
tiffimage[tiffimage>1e100]=np.nan
tiflats = np.linspace(lat0,(lat0 - (tiffimage.shape[0]*dlat)),num=tiffimage.shape[0])
tiflons = np.linspace(lon0,(lon0 + (tiffimage.shape[1]*dlon)),num=tiffimage.shape[1])
tiffgrid = np.meshgrid(tiflats,tiflons)
tiffimage = tiffimage.transpose()
xtif,ytif = tiffgrid[1],tiffgrid[0]

fig = plt.figure(figsize=(14,8))
ax = plt.axes([0.25, 0.05, 0.95, 0.9],projection=crs.LambertConformal())
ax.set_adjustable('datalim')
ax.set_extent(lit_domain, crs=crs.LambertConformal())

ax.add_feature(counties_feature, linewidth=0.75)
ax.add_feature(states_feature, linewidth=1.75)

vals=[1, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000]
cmap = clr.LinearSegmentedColormap.from_list('Population',[(0, '#1e6eeb'), (0.15, '#e1ffff'),(0.25, '#0fa00f'),(0.255, '#fffaaa'),(0.40, '#e11400'),(0.55, '#78000c'),(0.79, '#e96f58'),(0.80, '#643c32'),(1, '#f0dcd2')], N=256)
bounds=[1, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000]

norm = mpl.colors.BoundaryNorm(bounds, cmap.N)

im = plt.contourf(xtif, ytif, tiffimage, levels=vals, cmap=cmap, norm=norm, alpha=0.85, transform=crs.LambertConformal())

plt.colorbar(im, pad=0.01, boundaries=[1, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000], ticks=[1, 10, 20, 30, 40, 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 6000, 7000, 8000, 9000, 10000, 15000, 20000, 25000, 30000, 35000, 40000, 45000, 50000], spacing='uniform', aspect=40)

我的初步方法

我最初的方法是执行以下代码行(由于未产生期望的结果，因此未在上面显示)

My initial approach was to execute the following lines of code (not shown above since it did not produce the desired result)

states_fill = ShapelyFeature(Reader(states).geometries(), crs.LambertConformal(), facecolor='#C7C6C1', edgecolor='none')
ax.add_feature(states_fill, linewidth=1.75)
im = plt.contourf(xtif, ytif, tiffimage, levels=vals, cmap=cmap, norm=norm, alpha=0.85, transform=crs.LambertConformal())

ax.add_feature(states_fill，linewidth = 1.75)的添加和放置绘制了所有美国州的灰色填充shapefile，这是预期的和期望的.但是，即使我在执行 plt.contourf 之前正确地定了顺序，它还是将这个shapefile放置在轮廓图上.

The addition and placement of ax.add_feature(states_fill, linewidth=1.75) plotted a gray filled shapefile of all U.S states, which was expected and desired. However, it placed this shapefile over the contoured plot, even though I had ordered this correctly before the execution of plt.contourf.

在等高线图下方放置填充等高线的最佳方法是什么?任何帮助是极大的赞赏！

What is the best approach to place a filled contour underneath the contoured plot? Any help is greatly appreciated!

推荐答案

这是一个棘手的问题，但是有一个非常简单的附加功能可以在轮廓图像下方绘制 shapefile:

This was a tricky, sneaky issue, however there is a very simple addition to plot shapefiles underneath a contoured image:

ax.add_feature(states_fill, linewidth=0.45, zorder=0)

注意添加了 zorder=0.这样可以确保绘制在图的最低/最低层上的shapefile相应地绘制.

Note the addition of zorder=0. This will ensure shapefiles that are required to be on the lowest/bottom layer of the plot, are plotted accordingly.

这篇关于Matplotlib/CartoPy等高线图下方的实心填充的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！