Calibration Python Packages

betacal

Beta calibration

pyxcp

ASAM XCP in Python

avica

Automated VLBI calibration pipeline in CASA (AVICA) is a batch processing and calibration pipeline with minimal input configuration.

stochastic-rs

High-performance quantitative finance in Rust and Python — 130+ stochastic processes, option pricing, calibration, fixed income, risk & copulas, with SIMD/GPU acceleration.

calibrax

JAX benchmarking, profiling and evaluation metrics for Flax NNX: a registry of pure-function metrics (regression, classification, calibration, uncertainty, forecasting, generative, image, text, audio, graph, fairness), XLA FLOP counting, roofline analysis, GPU and energy monitoring, regression detection, publication exports, W&B and MLflow.

uncertainty-calibration

Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).

probmetrics

Post-hoc calibration methods and metrics for classification

decisio

A serving layer for decisions: typed questions in, a probability for every option out, one forward pass each. Three bases: Qwen3.6-35B-A3B, Gemma 4 12B, Gemma 4 31B.

uncertainty-toolbox

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

opendecider

Open, calibrated System 1 decision models: typed choice / score / yes-no answers with a probability for every option. 400M to 80B; CPU, NVIDIA, Apple Silicon, LM Studio, Ollama and vLLM.

mcgrad

MCGrad is a scalable and easy-to-use tool for multicalibration. It ensures your ML model predictions are well-calibrated not just globally (across all data), but also across virtually any segment defined by your features

decision-circuits

Decision circuits: typed questions to a System One model, calibrated probabilities back, gates in code. Zero-dependency Python SDK with LangChain, OpenAI Agents, and Claude Agent SDK integrations.

cje-eval

Causal Judge Evaluation: calibrate LLM-as-judge scores against oracle labels with valid uncertainty.

anyjev

Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating, welcome any issue and PR request)

calibrated-explanations

Calibrated Explanations is an explanation method for uncertainty-aware explanations of classification and regression models.

endoxa

Governed beliefs for LLM agents: an append-only ledger, SMT-checked consistency, defeasible revision, and calibration instruments.

avow

Turns measurements on different scales into one score that shows its math — for developers who must explain a score.

rosettax

Interactive flow cytometry calibration software for fluorescence and scattering workflows, with FCS loading, peak finding, fitting, profiles, and reusable calibration exports.

pygac

A python package to read and calibrate NOAA and Metop AVHRR GAC and LAC data

laya-mcp

MCP server for Laya typed decisions (noul / choice / score): warm model sidecar, token-budget preflight, persisted calibration, honest confidence.

jev-style

Small, calibrated decision models on your own machine: systemone-compatible local server, 6 agent skills, Claude Code guard, MCP tools. Weights on Hugging Face.

typecastlm

Use TypeCastLM decision models: ask questions about your material, get calibrated probabilities — locally, via llama.cpp, or as a Jev-API server. pip install typecastlm

acstools

Tools for HST/ACS

jevassert

Record/replay regression tests for Jev (TypeSafe System One) question packs — accuracy, calibration and cost gates in CI