I have a figure with 3 subplots, two of which share a colorbar and the third has has it's own colorbar.
I would like the colorbars to align with the vertical limits of their respective plots, and for the top two plots to have the same vertical limits.
Googling, I have found ways to do this with a single plot, but am stuck trying to make it work for my fig. My figure currently looks like this:
The code for which is as follows:
import cartopy.io.shapereader as shpreader
import cartopy.crs as ccrs
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
shpfilename = shpreader.natural_earth(resolution='50m',
category='cultural',
name='admin_0_countries')
reader = shpreader.Reader(shpfilename)
countries = reader.records()
projection = ccrs.PlateCarree()
fig = plt.figure()
axs = [plt.subplot(2, 2, x + 1, projection = projection) for x in range(2)]\
+ [plt.subplot(2, 2, (3, 4), projection = projection)]
def cmap_seg(cmap, value, k):
cmaplist = [cmap(i) for i in range(cmap.N)]
cmap = mpl.colors.LinearSegmentedColormap.from_list(
'Custom cmap', cmaplist, cmap.N)
bounds = np.linspace(0, k, k + 1)
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
color = cmap(norm(value))
return color, cmap
for country in countries:
c_name = country.attributes["SOVEREIGNT"]
country_dat = df.loc[c_name]
cmap = matplotlib.cm.get_cmap("plasma")
cmap_blues = matplotlib.cm.get_cmap("Blues")
ax_extent = [-170, 180, -65, 85]
alpha = 1.0
edgecolor = "k"
linewidth = 0.5
ax = axs[0]
value = country_dat.loc["wgi_bin"]
ax.add_geometries([country.geometry],
projection,
facecolor = cmap_seg(cmap, value, 5)[0],
alpha = alpha,
edgecolor = edgecolor,
linewidth = linewidth)
ax.set_xlabel("WGI group")
ax.set_extent(ax_extent)
ax = axs[1]
value = country_dat.loc["epi_bin"]
ax.add_geometries([country.geometry],
projection,
facecolor = cmap_seg(cmap, value, 5)[0],
alpha = alpha,
edgecolor = edgecolor,
linewidth = linewidth)
ax.set_xlabel("EPI group")
ax.set_extent(ax_extent)
ax = axs[2]
value = country_dat.loc["diff"]
ax.add_geometries([country.geometry],
projection,
facecolor = cmap_seg(cmap_blues, value, 4)[0],
alpha = alpha,
edgecolor = edgecolor,
linewidth = linewidth)
ax.set_xlabel("difference")
ax.set_extent(ax_extent)
subplot_labels = ["WGI group", "EPI group", "Metric difference"]
for i, ax in enumerate(axs):
ax.text(0.5, -0.07, subplot_labels[i], va='bottom', ha='center',
rotation='horizontal', rotation_mode='anchor',
transform=ax.transAxes)
sm = plt.cm.ScalarMappable(cmap=cmap_seg(cmap, 5, 5)[1], norm = plt.Normalize(0, 5))
sm._A = []
cb = plt.colorbar(sm, ax = axs[1], values = [1,2,3,4, 5], ticks = [1,2,3,4,5])
sm2 = plt.cm.ScalarMappable(cmap=cmap_seg(cmap_blues, 5, 4)[1], norm = plt.Normalize(0, 4))
sm2._A = []
cb2 = plt.colorbar(sm2, ax = axs[2], values = [0,1,2,3], ticks = [0,1,2,3])
Try this:
# update your code for this specific line (added shrink option)
cb = plt.colorbar(sm, ax=axs[1], values=[1,2,3,4,5], ticks=[1,2,3,4,5], shrink=0.6)
And add these lines of code towards the end:
p00 = axs[0].get_position()
p01 = axs[1].get_position()
p00_new = [p00.x0, p01.y0, p00.width, p01.height]
axs[0].set_position(p00_new)
The plot should be similar to this: