factcircuit
FactCircuit: an auditable claim-and-evidence verification loop with immutable provenance, staged checks, bounded retrieval, and reproducible evaluation.
High-performance functional data analysis for Python, powered by Rust
Translation pending
DataPython · RustGitHub @sipemuOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
Python bindings for fdars-core – Functional Data Analysis in Rust
Translation pending
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
fdars – Functional Data Analysis for Python
High-performance Functional Data Analysis for Python, powered by a Rust backend (fdars-core).
The central object in fdars is Fdata — a functional data container that bundles
observation data, evaluation grid, identifiers, and metadata into a single object
(mirroring the R package's fdata class).
You can still call low-level functions directly with raw NumPy arrays:Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
fdars – Functional Data Analysis for Python
High-performance Functional Data Analysis for Python, powered by a Rust backend (fdars-core).
The central object in fdars is Fdata — a functional data container that bundles
observation data, evaluation grid, identifiers, and metadata into a single object
(mirroring the R package's fdata class).
You can still call low-level functions directly with raw NumPy arrays:Read the full README ↗