From a16885fc2b9957cc9ebc4ae27c5669b2f0a855c2 Mon Sep 17 00:00:00 2001
From: David Rotermund <54365609+davrot@users.noreply.github.com>
Date: Tue, 19 Dec 2023 12:13:04 +0100
Subject: [PATCH] Update README.md

Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
---
 numpy/mesh_grid/README.md | 97 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 97 insertions(+)

diff --git a/numpy/mesh_grid/README.md b/numpy/mesh_grid/README.md
index bf3de26..1b0d3f7 100644
--- a/numpy/mesh_grid/README.md
+++ b/numpy/mesh_grid/README.md
@@ -87,3 +87,100 @@ plt.show()
 ```
 
 ![image3](image3.png)
+
+## [numpy.mgrid](https://numpy.org/doc/stable/reference/generated/numpy.mgrid.html) (dense meshgrid)
+
+{: .topic-optional}
+This is an optional topic!
+
+```python
+numpy.mgrid = <numpy.lib.index_tricks.MGridClass object>
+```
+
+> An instance which returns a dense multi-dimensional “meshgrid”.
+> 
+> An instance which returns a dense (or fleshed out) mesh-grid when indexed, so that each returned argument has the same shape. The dimensions and number of the output arrays are equal to the number of indexing dimensions. If the step length is not a complex number, then the stop is not inclusive.
+> 
+> However, if the step length is a complex number (e.g. 5j), then the integer part of its magnitude is interpreted as specifying the number of points to create between the start and stop values, where the stop value is inclusive.
+
+```python
+import numpy as np
+
+xv, yv = np.mgrid[0:5, 0:5]
+
+print(xv)
+print()
+print(yv)
+```
+
+Output: 
+
+```python
+[[0 0 0 0 0]
+ [1 1 1 1 1]
+ [2 2 2 2 2]
+ [3 3 3 3 3]
+ [4 4 4 4 4]]
+
+[[0 1 2 3 4]
+ [0 1 2 3 4]
+ [0 1 2 3 4]
+ [0 1 2 3 4]
+ [0 1 2 3 4]]
+```
+
+```python
+import numpy as np
+
+xv, yv = np.mgrid[0:5:0.25, 0:5:0.5]
+
+print(xv)
+print()
+print(yv)
+```
+
+Output:
+
+```python
+[[0.   0.   0.   0.   0.   0.   0.   0.   0.   0.  ]
+ [0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25]
+ [0.5  0.5  0.5  0.5  0.5  0.5  0.5  0.5  0.5  0.5 ]
+ [0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75]
+ [1.   1.   1.   1.   1.   1.   1.   1.   1.   1.  ]
+ [1.25 1.25 1.25 1.25 1.25 1.25 1.25 1.25 1.25 1.25]
+ [1.5  1.5  1.5  1.5  1.5  1.5  1.5  1.5  1.5  1.5 ]
+ [1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75]
+ [2.   2.   2.   2.   2.   2.   2.   2.   2.   2.  ]
+ [2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25 2.25]
+ [2.5  2.5  2.5  2.5  2.5  2.5  2.5  2.5  2.5  2.5 ]
+ [2.75 2.75 2.75 2.75 2.75 2.75 2.75 2.75 2.75 2.75]
+ [3.   3.   3.   3.   3.   3.   3.   3.   3.   3.  ]
+ [3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25 3.25]
+ [3.5  3.5  3.5  3.5  3.5  3.5  3.5  3.5  3.5  3.5 ]
+ [3.75 3.75 3.75 3.75 3.75 3.75 3.75 3.75 3.75 3.75]
+ [4.   4.   4.   4.   4.   4.   4.   4.   4.   4.  ]
+ [4.25 4.25 4.25 4.25 4.25 4.25 4.25 4.25 4.25 4.25]
+ [4.5  4.5  4.5  4.5  4.5  4.5  4.5  4.5  4.5  4.5 ]
+ [4.75 4.75 4.75 4.75 4.75 4.75 4.75 4.75 4.75 4.75]]
+
+[[0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]
+ [0.  0.5 1.  1.5 2.  2.5 3.  3.5 4.  4.5]]
+```