README.md

Sequencer

This module aims to assign a priority or order to the components of a network for planning purpose. This is done by converting the inputs into a directed acyclic graph and ordering the nodes by the cumulative "downstream" values defined by the input parameters.

See NetworkPlanner.R for similar work, but in R.

Development Setup

Clone this repository and cd into the directory

Setup a virtual environment (example here uses anaconda)

conda create -n sequencer --file requirements.txt python=2.7
source activate sequencer

The repo contains a sample dataset in the data folder.
You can run a test against it via the command line

./run_sequencer.py --metrics_path data/sumaila/input/metrics-local.csv --network_path data/sumaila/input/networks-proposed.shp --demand_field "Demand...Projected.nodal.demand.per.year" --prioritize_field "Population" --output_path output

Take a look at run_sequencer.py for an example of how to use the modules from Python

Output

The main output is a table with the original metrics csv data (i.e. the nodes) plus "Sequence" fields as shown below

Out[12]:

	Sequence..Decision.metric	Sequence..Downstream.demand.sum.kwh	Sequence..Downstream.distance.sum.m	Sequence..Root.vertex.id	Sequence..Upstream.id	Sequence..Upstream.segment.distance.m	Sequence..Vertex.id
Sequence..Far.sighted.sequence
1	2780868.271316	28013000	10.073472	27	27	10.073472	25
2	7010.936648	44720000	6378.605633	505	505	16.171168	391
3	960.761193	1217000	1266.703952	392	392	537.213092	342
4	452.370301	330000	729.490860	392	342	155.021075	304
5	464.776402	267000	574.469785	392	304	574.469785	212
...	...	...	...	...	...	...	...
519	15.164609	165000	10880.596829	424	210	6113.945502	228
520	21.818252	104000	4766.651327	424	228	4766.651327	421
521	13.653252	219000	16040.134490	424	210	3982.017803	486
522	12.025095	145000	12058.116687	424	486	6212.158996	325
523	11.460911	67000	5845.957691	424	325	5845.957691	42

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