A Python package for general minimization, where derivatives are not available, using random subspaces. For a description of this algorithm, see this paper.
For lower-dimensional problems, consider using the more actively maintained Py-BOBYQA.
Citation
If you use RSDFO-Q in an academic work, please cite the following paper:
C. Cartis and L. Roberts, Randomized Subspace Derivative-Free Optimization with Quadratic Models and Second-Order Convergence. Optimization Methods and Software, to appear.
A preprint version of this paper can be found on arXiv.
Installation
You can install RSDFO-Q by cloning this repository and installing with pip:
$ git clone https://github.com/lindonroberts/rsdfoq.git
$ cd rsdfoq
$ ls <-- check for pyproject.toml
$ pip install -e .RSDFO-Q requires NumPy, SciPy and pandas, but these will be installed automatically if they are not already available.
Usage
Examples for how to use RSDFO-Q may be found in the examples directory.
1 maintainer
Metadata
1 maintainer
Release files for rsdfoq 1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rsdfoq-1.0.tar.gz | 39.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rsdfoq-1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 84.2 kB
Release files / rsdfoq-1.0.tar.gz
| Download URL | rsdfoq-1.0.tar.gz |
|---|---|
| Size | 39.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8e5b098ffbee7647000aeb7d375782b639e472eb019bfb7aef77a92cbfd6eb2f
|
|
BLAKE2b-256 checksum How to use checksums |
251082a150a0f1d0665fc95f301aeab3bd7549b1a8c1800a99e0fbc7e0a735db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 15, 2025.
Transparency logRelease files / rsdfoq-1.0-py3-none-any.whl
| Download URL | rsdfoq-1.0-py3-none-any.whl |
|---|---|
| Size | 45.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
27692fc74afb11d7140f58b943bf65f01c27185f465c6578e9698ae5f144832f
|
|
BLAKE2b-256 checksum How to use checksums |
066f46951cba172948f355ac7b7a26c818a538cfa9e2a2c6ee57f71706d309fa
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 15, 2025.
Transparency log
