From 981a026a9aa99c3628e342f9909d1f94f9609e1b Mon Sep 17 00:00:00 2001
From: David Rotermund <54365609+davrot@users.noreply.github.com>
Date: Tue, 19 Dec 2023 12:05:56 +0100
Subject: [PATCH] Update README.md

Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
---
 numpy/mesh_grid/README.md | 40 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)

diff --git a/numpy/mesh_grid/README.md b/numpy/mesh_grid/README.md
index 6024a8d..bf3de26 100644
--- a/numpy/mesh_grid/README.md
+++ b/numpy/mesh_grid/README.md
@@ -47,3 +47,43 @@ plt.show()
 ![image0](image0.png)
 
 ![image1](image1.png)
+
+An example:
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+x = np.linspace(0, 1, 100)
+y = np.linspace(0, 1, 100)
+
+xv, yv = np.meshgrid(x, y)
+
+a = np.sin(xv * 2 * np.pi) * np.sin(yv * 8 * np.pi)
+
+plt.imshow(a, cmap="hot")
+plt.xlabel("x axis")
+plt.ylabel("y axis")
+plt.show()
+```
+
+![image2](image2.png)
+
+**The question is if you really need a mesh or if just using broadcasting can do the job too.** I guess this depends on your need.
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+x = np.linspace(0, 1, 100)[np.newaxis, :]
+y = np.linspace(0, 1, 100)[:, np.newaxis]
+
+a = np.sin(x * 2 * np.pi) * np.sin(y * 8 * np.pi)
+
+plt.imshow(a, cmap="hot")
+plt.xlabel("x axis")
+plt.ylabel("y axis")
+plt.show()
+```
+
+![image3](image3.png)