wish helps you I figured it out on my own, so here's an explanation for anyone future person who is confused by this.

As an example, let's use the simple lattice of points that I was working with in my code, which I generate as follows

code :

```
import numpy as np
import itertools as it
from matplotlib import pyplot as plt
import scipy as sp
inputs = list(it.product([0,1,2],[0,1,2]))
i = 0
lattice = range(0,len(inputs))
for pair in inputs:
lattice[i] = mksite(pair[0], pair[1])
i = i +1
```

```
plt.plot(*np.transpose(lattice), marker = 'o', ls = '')
axes().set_aspect('equal')
```

```
dela = sp.spatial.Delaunay
triang = dela(lattice)
```

```
triang.points
```

```
array([[ 0. , 0. ],
[ 0.5 , 0.8660254 ],
[ 1. , 1.73205081],
[ 1. , 0. ],
[ 1.5 , 0.8660254 ],
[ 2. , 1.73205081],
[ 2. , 0. ],
[ 2.5 , 0.8660254 ],
[ 3. , 1.73205081]])
```

```
triang.vertices
```

```
array([[4, 3, 6],
[5, 4, 2],
[1, 3, 0],
[1, 4, 2],
[1, 4, 3],
[7, 4, 6],
[7, 5, 8],
[7, 5, 4]], dtype=int32)
```

```
[ 1.5 , 0.8660254 ]
[ 1. , 0. ]
[ 2. , 0. ]
```

```
def find_neighbors(pindex, triang):
neighbors = list()
for simplex in triang.vertices:
if pindex in simplex:
neighbors.extend([simplex[i] for i in range(len(simplex)) if simplex[i] != pindex])
'''
this is a one liner for if a simplex contains the point we`re interested in,
extend the neighbors list by appending all the *other* point indices in the simplex
'''
#now we just have to strip out all the dulicate indices and return the neighbors list:
return list(set(neighbors))
```