No. 100 of 106 ·Statistical Analysis Software

Black-it

Linux

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Freedom report

One barScore 4.9

Free tierNo free tier on record
Open codeNo open-source code on record
Runs widely1 of 6 device platforms
DocumentedPlans, terms and facts published

Black-it is ranked #100 of 106 in statistical analysis software on Freedom251. It runs on Linux.

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The record

Purpose: Black-it is a black-box calibration kit for estimating parameters in agent-based models and simulations.
General use: The package can also optimize built-in or custom models when several search techniques need to be combined.
Calibration process: It samples parameter sets, simulates the model for each set, and evaluates a loss function against real data until convergence or the iteration limit.
Built-in losses: Documented loss functions include MinkowskiLoss, MethodOfMomentsLoss, GslDivLoss, and FourierLoss.
Search methods: Documented samplers include uniform and low-discrepancy methods, plus methods based on prior results such as Gaussian process, XGBoost, random forest, and particle swarm samplers.
Customization: Users can implement custom models, loss functions, and samplers by extending the package’s interfaces.
External simulators: A Python wrapper can connect an external simulator, including models written in low-level languages or using Mesa, through a language-agnostic interface.
Parallel execution: Model simulation is parallelized by default across the computer’s CPU cores, and the process count can be set with n_jobs.
Checkpointing: When a saving folder is configured, calibration checkpoints are saved after each batch and can be restored to resume an interrupted run.
Requirements: The project requires Python 3.9 or later; the documentation also lists Poetry as a requirement.
Distribution: The package can be installed from PyPI with pip install black-it or directly from its GitHub repository.
License: Black-it is released under the GNU Affero General Public License v3 or later (AGPLv3+).
Support: The project directs users needing support, bug reports, or feature requests to its GitHub Issues page and says other feedback can be sent to an author by email.
Intended users: The project describes use across economics, epidemiology, biology, logistics, and other agent-based modeling or simulation research.

Where it ranks on Freedom251

Best Statistical Analysis Software in 2026#100 of 106

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Sources

bancaditalia.github.io/black-it/· checked 4 Oct 2026
bancaditalia.github.io/black-it/description/· checked 4 Oct 2026
bancaditalia.github.io/black-it/simulator_interface/· checked 4 Oct 2026
bancaditalia.github.io/black-it/checkpointing_parallelisation/· checked 4 Oct 2026
github.com/bancaditalia/black-it· checked 4 Oct 2026
bancaditalia.github.io/black-it/contributing/· checked 4 Oct 2026