gridai 1.0.0

Python package for building graph dataset from GDM system.

Welcome to Graph Dataset Repo

Installation

Use following commands to install

pip install gridai

Available commands

Use following command to see available commands.

gridai --help

You will see something like this.

Usage: gridai [OPTIONS] COMMAND [ARGS]...

  Entry point

Options:
  --help  Show this message and exit.

Commands:
  generate-dataset  Command line function to generate geojsons from...
  generate-stats    Function to dump stats around the dataset.

How to create a dataset ?

The command generate-dataset can convert all opendss models available in the parent folder by recursively searching for all valid opendss models.

gridai generate-dataset -j <system-json-path>

This will create a sqlite db file stroing all training data in pytorch.data.Data format.

How to use the dataset ?

>>> from torch_geometric.data import SQLiteDatabase
>>> db = SQLiteDatabase(path="dataset.sqlite",name="data_table")
>>> len(db)
51
>>> db[0]
Data(x=[22, 21], edge_index=[2, 21], edge_attr=[21, 4])

Getting NodeObject and EdgeObject

You can use following snippet to convert node attributes back to an instance of DistNodeAttrs and edge attributes back to an DistEdgeAttrs.

>>> from torch_geometric.data import SQLiteDatabase
>>> from gridai.interfaces import DistNodeAttrs, DistEdgeAttrs
>>> from rich import print
>>> db = SQLiteDatabase(path="dataset.sqlite",name="data_table")
>>> print(DistNodeAttrs.from_array(db[0].x[0]))
DistNodeAttrs(
   node_type=<NodeType.LOAD: 2>,
   active_demand_kw=5.726587772369385,
   reactive_demand_kw=1.691259503364563,
   active_generation_kw=0.0,
   reactive_generation_kw=0.0,
   phase_type=<PhaseType.NS1S2: 11>,
   kv_level=0.1200888529419899
)
>>> print(DistEdgeAttrs.from_array(db[0].edge_attr[0]))
DistEdgeAttrs(
   capacity_kva=25.0,
   edge_type=<DistEdgeType.TRANSFORMER: 1>,
   length_miles=0.0
)

Plotting the dataset

You can use following command to plot the dataset.

>>> from gridai.plot_dataset import plot_dataset
>>> from torch_geometric.data import SQLiteDatabase
>>> db = SQLiteDatabase(path="dataset.sqlite",name="data_table")
>>> plot_dataset(db[0])