# The new approach I was hoping would work, but got unexpected results from

import matplotlib.pyplot as plt
import numpy as np

# invent some numbers, turning the x and y arrays into simple
# 2d arrays, which make combining them together easier.
x = np.linspace(-3, 5, 150).reshape(1, -1)
y = np.linspace(-3, 5, 120).reshape(-1, 1)
z = np.cos(x) + np.sin(y)

# we no longer need x and y to be 2 dimensional, so flatten them.
x, y = x.flatten(), y.flatten()

fig1, ax1 = plt.subplots()
cs = ax1.contourf(x, y, z, hatches=['-', '/', '\\', '//'],
                  cmap='gray', extend='both', alpha=0.5)

cs.set_edgecolors(["blue","grey","yellow","red"])
fig1.colorbar(cs)



# The older approach that now fails with Matplotlib 3.10

import matplotlib.pyplot as plt
import numpy as np

# invent some numbers, turning the x and y arrays into simple
# 2d arrays, which make combining them together easier.
x = np.linspace(-3, 5, 150).reshape(1, -1)
y = np.linspace(-3, 5, 120).reshape(-1, 1)
z = np.cos(x) + np.sin(y)

# we no longer need x and y to be 2 dimensional, so flatten them.
x, y = x.flatten(), y.flatten()

fig1, ax1 = plt.subplots()
cs = ax1.contourf(x, y, z, hatches=['-', '/', '\\', '//'],
                  cmap='gray', extend='both', alpha=0.5)

colors = ["blue","grey","yellow","red"]
for i, collection in enumerate(cs.collections):
    collection.set_edgecolor(colors[i % len(colors)])
fig1.colorbar(cs)