psevencore 2026.3.19

pSeven Core is an integrated toolkit for design space exploration, optimization, and predictive modeling.

pSeven Core is an integrated toolkit for predictive modeling, data analysis and optimization. It provides a variety of proprietary and classical algorithms for local and global optimization, approximation, dimension reduction, design of experiments, and sensitivity analysis. See the homepage and documentation for full details.

• Homepage: https://www.pseven.io/product/pseven-core/
• Documentation: https://www.pseven.io/product/pseven-core/manual/
• Support: https://www.pseven.io/support.html
• Contacts: https://www.pseven.io/contacts/

Requirements

• Python 3.6 or newer.
  • pSeven Core also maintains compatibility with the final Python 2.7 version.
• NumPy 1.16 or newer.
  • pSeven Core v2024.06 and older versions are not compatible with NumPy 2. pSeven Core v2024.07 and newer are up to date with NumPy 2.

Additionally recommended:

• pandas, any up to date version.
• SciPy, any up to date version.
• Matplotlib 1.1 or newer.

While the above are not required, they are widely used in pSeven Core examples and guides.

Optional:

• SHAP - implements a game theoretic approach to explain model output.

SHAP is required only by some pSeven Core approximation models and only if you are going to use the SHAP evaluation feature for that certain kind of models.

Windows requirements

pSeven Core is tested on Windows 10, 64-bit desktop editions. Newer versions and corresponding server editions are also supported but not regularly tested.

Linux requirements

pSeven Core works on any Linux x86_64 with:

• Linux kernel 2.6.18 or newer.
• GNU C Library (glibc) 2.5 or newer.