I'm trying to produce a graph of a specific area on the world. To have a convenient figure, I tried the following answers: cartopy figures edge with parallel
It produces the pitcures on the first image. On this figure, all the labels are displayed. I used to hide the labels using some options of cartopy gridlines as mention in the following code. However, when I ask the code to hide the labels on the right and top, I get the second image. In my idea, I only want the label to be displayed on the left and bottom of the figure.
from matplotlib.gridspec import GridSpec
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import cartopy.crs as ccrs
from matplotlib.ticker import MultipleLocator, MaxNLocator
import matplotlib.ticker as mticker
n = 20
lon = np.linspace(-80, 0, n)
lat = np.linspace(10, 60, n)
ano = np.random.uniform(-4, 4, size=(n, n))
proj = ccrs.LambertConformal(central_longitude=-40, central_latitude=35.0)
gs = GridSpec(2, 1, height_ratios=[1, 0.05])
matplotlib.rcParams.update({'font.size': 18})
fig = plt.figure(figsize=(6, 6), facecolor="w")
ax = fig.add_subplot(gs[0, 0], projection=proj)
aoi = mpath.Path(list(zip(np.linspace(-80, 0, n), np.full(n, 60))) + \
list(zip(np.full(n, 0), np.linspace(60, 10, n))) + \
list(zip(np.linspace(0, -80, n), np.full(n, 10))) + \
list(zip(np.full(n, -80), np.linspace(10, 60, n))))
ax.set_boundary(aoi, transform=ccrs.PlateCarree())
ax.set_extent((-80, 0, 10, 60))
gl = ax.gridlines(draw_labels=True,linewidth=0.5, alpha=0.5,linestyle='--',rotate_labels=False,x_inline=False, y_inline=False)
gl.right_labels = False
gl.top_labels = False
cmap = plt.get_cmap('RdYlBu_r', np.nanmax(ano) - np.nanmin(ano) + 1)
s1 = ax.pcolormesh(lon, lat, ano, vmin=-4, vmax=4, cmap=cmap, transform=ccrs.PlateCarree())
ax.coastlines('50m')
cax = fig.add_subplot(gs[1, 0])
cbar1 = plt.colorbar(s1, cax=cax, shrink=0.5, orientation="horizontal", format="$%.2f$", extend='both', pad=0.1)
cax.xaxis.set_major_locator(MaxNLocator(nbins=5, prune='both'))
cax.xaxis.set_major_formatter(mticker.FormatStrFormatter('%0.1f'))
plt.show()
