pypsa-meets-earth/pypsa-earth

Replace centroid by polylabel

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#191 opened on Dec 20, 2021

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good first issuehelp wantedimprovement

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Description

So I tried this out by starting from the cluster_network.py script. In 28f8500, I introduced a function that maps the network buses to their correct gadm regions (could easily be changed to nuts or any other subdivisions). The end product is correctly mapped clustered nodes, but many open sub issues and bugs remain:

* [ ]  Decide where to place the shape-representing node, as of now it is located to the mean long & mean lat of all the buses of the shape. Alternatively could be placed at the centroid of the shape? (will probably need modifying PyPSA scripts, namely `networkclustering.py`)

Hi @Hazem-IEG , I just realise that the centroid is sometimes outside of the original shape. This is because the centroid (red) is not equal to the visual centre (green). The probably best way to find the visual centre of shapes is to use the iterative "get_furthest_point_from_edges" algorithm. This is implemented by the Polylabel in shapely. https://stackoverflow.com/questions/1203135/what-is-the-fastest-way-to-find-the-visual-center-of-an-irregularly-shaped-pol

image

Originally posted by @pz-max in https://github.com/pypsa-meets-africa/pypsa-africa/issues/107#issuecomment-997711362

Contributor guide

Research direction
Implement polylabel from shapely to replace centroid for shape representing node placement in clustering algorithm. Ensure that the polylabel method is used in the clustering module where centroid is currently computed.
Tech stack
python
Domain
backend
Issue type
Refactor
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
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Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Pythonshapely
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
65