pystlogic

This package is a forked version of anand-bala's signal-temporal-logic.

This package provides an interface to define offline monitoring for Signal Temporal Logic (STL) specifications. The library is written in C++ (and can be used with CMake) and has been wrapped for Python usage using pybind11.

The library is inspired by the following projects:

• py-metric-temporal-logic is a tool written in pure Python, and provides an elegant interface for evaluating discrete time signals using Metric Temporal Logic (MTL).
• Breach and S-TaLiRo are Matlab toolboxes designed for falsification and simulation-based testing of cyber-physical systems with STL and MTL specifications, respectively. One of their various features includes the ability to evaluate the robustness of signals against STL/MTL.

The signal-temporal-logic library aims to be different from the above in the following ways:

• Written for speed and targets Python.
  • While py-metric-temporal-logic is written in Python, it doesn't perform computations efficiently and quickly.
• Support for multiple quantitative semantics.
  • All the above tools have their own way of computing the quantitative semantics for STL/MTL specifications.
  • This tool will try to support common ways of computing the robustness, but will also have support for other quantitative semantics of STL.

List of Quantitative Semantics

• Classic Robustness
  • A. Donzé and O. Maler, "Robust Satisfaction of Temporal Logic over Real-Valued Signals," in Formal Modeling and Analysis of Timed Systems, Berlin, Heidelberg, 2010, pp. 92–106.
• Temporal Logic as Filtering
  • A. Rodionova, E. Bartocci, D. Nickovic, and R. Grosu, "Temporal Logic As Filtering," in Proceedings of the 19th International Conference on Hybrid Systems: Computation and Control, New York, NY, USA, 2016, pp. 11–20.
• Smooth Cumulative Semantics
  • I. Haghighi, N. Mehdipour, E. Bartocci, and C. Belta, "Control from Signal Temporal Logic Specifications with Smooth Cumulative Quantitative Semantics," arXiv:1904.11611 [cs], Apr. 2019.

Installing Python package

Using pip

$ python3 -m pip install pystlogic

Build from source

Requirements: cmake >= 3.5, git and a C++ compiler that supports C++17.

First clone the repository:

$ git clone https://github.com/davidhjp01/pystlogic

Then install using pip, install the package:

$ python3 -m pip install -U .

Usage

See the examples/ directory for some usage examples in C++ and Python.