Graph ML in one call: node/edge/temporal + MLP/GCN/SAGE (optional) + useful plots.
Project description
softgraph (one-call API) — v0.3.0
One call to generate data → extract features → train a model → evaluate and plot.
Install (editable dev)
pip install -e .
Optional deep:
pip install "softgraph[deep]"
# Then install torch-geometric from wheels if you want GCN/SAGE.
Usage
import softgraph
run = softgraph.softgraph(
task="node_classification",
dataset="sbm",
n=800, k=4, p_in=0.10, p_out=0.02,
features="spectral:16",
model="mlp",
plot=True, # confusion matrix
curves=True # learning curve
)
print(run["metrics"])
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