# 7.3. Creating Delaunay Lines¶

On this example we show how to create AequilibraE’s famous Delaunay Lines, but in Python

For more on this topic, the firs publication is here: https://xl-optim.com/delaunay/

We use the Sioux-Falls example once again.

```import pandas as pd
from uuid import uuid4
from os.path import join
import sqlite3
from tempfile import gettempdir
import matplotlib.pyplot as plt
import shapely.wkb

from aequilibrae.utils.create_example import create_example
from aequilibrae.utils.create_delaunay_network import DelaunayAnalysis
```

We create an empty project on an arbitrary folder

```fldr = join(gettempdir(), uuid4().hex)

project = create_example(fldr)
```

Get the Delaunay Lines generation class

```da = DelaunayAnalysis()

# Let's create the triangulation based on the zones, but we could create based on the network (centroids) too
da.create_network('zones')
```

Now we get the matrix we want and create the Delaunay Lines

```demand = project.matrices.get_matrix("demand_omx")
demand.computational_view(["matrix"])

# And we will call it 'delaunay_test'./ It will also be saved in the results_database.sqlite
da.assign_matrix(demand, 'delaunay_test')
```

we retrieve the results

```conn = sqlite3.connect(join(fldr, 'results_database.sqlite'))
```

Now we get the matrix we want and create the Delaunay Lines

```links = pd.read_sql('Select link_id, st_asBinary(geometry) geometry from delaunay_network', project.conn)

max_vol = df.matrix_tot.max()

for idx, lnk in df.iterrows():
geo = lnk.geometry
plt.plot(*geo.xy, color='blue', linewidth=4 * lnk.matrix_tot / max_vol)
plt.show()
```

Close the project

```project.close()
```

Total running time of the script: ( 0 minutes 1.407 seconds)

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