substrate

Generates a model predicting substrate class (rock, mixed, sand, or mud) using random forest and a stack of environmental predictors. Model is tested against withheld testing observations. Model can be run using a 1-step or 2-step approach. The 2-step approach generates a binary rock/not-rock layer and a mixed/sand/mud layer and the two are combined. This approach was created to reduce the prevalence of predicted rock in the output raster. Substrate index layers (densities per class) can also be produced.

Asylum Node implementation

a guide in transition for node operators and validators

Sensio Network explorer of blocks, rules, proofs and other things

CLI to calculate the proposal hash of a given wasm runtime. This CLI is used by srtool.

Example Substrate runtime module modeling arranging of workshops.