I would like help to plot a counterf only within the region bounded by the blue area in the image, not in the whole graph. I am trying to use matplotlib mpath and mpatches but I am getting several errors.
How could I plot the difference in levels (contorf) only within the area delimited by the blue markings?
Here is my code and the picture
#import base modules
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.interpolate import LinearNDInterpolator
from matplotlib.collections import PatchCollection
import matplotlib.path as mpath
import matplotlib.patches as mpatches
from mpl_toolkits.axes_grid1 import make_axes_locatable
#Loading the images
img1953 = plt.imread('O1953_9960_A3_1m.tif')
img1999 = plt.imread('O1999_9523_A3_1m.tif')
img2004 = plt.imread('O2004_2385c_A3_1m.tif')
#extract data from surfer files with pandas and name the columns as x and y, first line omited
area = pd.read_csv('diff_analyse_grd.bln', names=['x1', 'y1'], skiprows=1)
slope = pd.read_csv("Abbruchkante.bln", names=['x2', 'y2'], skiprows=1)
crack = pd.read_csv("Anrisskante.bln", names=['x3', 'y3'], skiprows=1)
xmin, xmax = -1100, -200 #set the maximum and miniumum values for the axIs:
ymin, ymax = 1500, 2100
#Read csv from grid/countour file, 1999
grid = np.loadtxt('kr_99_A3_o25.dat', delimiter = ' ', skiprows = 1, usecols = [1,2,3])
x99 = grid[:,0]
y99 = grid[:,1]
z99 = grid[:,2]
#linear space with 600x900 values between min and max graphic values
xi = np.linspace(xmin, xmax, 900)
yi = np.linspace(ymin, ymax, 600)
X, Y = np.meshgrid(xi, yi)
#Using LinearNDInterpolation, year 1999
interpolation99 = LinearNDInterpolator(list(zip(x99, y99)), z99)#https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.LinearNDInterpolator.html
zi99 = interpolation99(X, Y)
#Read csv from grid/countour file, year 1953
grid = np.loadtxt('kr_53_A3_o25.dat', delimiter = ' ', skiprows = 1, usecols = [1,2,3])
x53 = grid[:,0]
y53 = grid[:,1]
z53 = grid[:,2]
#Using LinearNDInterpolation, year 1953
interpolation53 = LinearNDInterpolator(list(zip(x53,y53)), z53)
zi53 = interpolation53(X,Y)
#Calculation of the hight variation:
dh5399 = zi53 - zi99
#Plot graph 1953 - 1999
plt.title('Hangrutschung im Blaubachgraben \n \n Differenz der Geländeoberflachen \n 1953 - 1999')
plt.imshow(img1953,cmap='gray', extent=(xmin, xmax, ymin, ymax))
plt.plot(area.x1,area.y1,'b-', label ='Studienbereich', linewidth = 2)
plt.plot(slope.x2,slope.y2,'r-', label = 'Abbruchkante')
plt.plot(crack.x3,crack.y3,'r--', label = 'Anrisskante')
cs = plt.contour(X,Y,zi99,levels=10, colors='#333')
plt.clabel(cs,inline=True, colors = 'k')
plt.legend(loc='upper right')
plt.xlabel('North [m]')
plt.ylabel('East [m]')
plt.xlim(xmin,xmax)
plt.ylim(ymin,ymax)
cs = plt.contourf(X, Y, dh5399, cmap='rainbow', vmin=-5, vmax=17)
#Setting colorbar right the axis
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes('right',size='3%',pad=0.1)
cbar = plt.colorbar(cs, cax=cax)
cbar.set_label('\u0394H [m]', rotation = 360, loc = 'top')
plt.tight_layout()
plt.savefig('Dif1.png',dpi=400)
plt.show()
