A Python toolkit for simulating intermittent search and Levy walk.
Project description
IntLevPy: Intermittent Lévy Processes Package
IntLevPy is a Python package for simulating and analyzing intermittent and Lévy processes. It provides tools for process simulation, moments calculation, optimization, and classification methods, making it ideal for researchers and practitioners in fields like statistical physics and complex systems.
Overview
- Simulation: Generate synthetic intermittent and Lévy flight trajectories.
- Moments Calculation: Compute theoretical and empirical moments of trajectories.
- Optimization: Fit model parameters to empirical data using optimization techniques.
- Classification: Differentiate between intermittent and Lévy processes using statistical methods.
For detailed documentation and examples, visit the IntLevPy Documentation.
Installation
Install IntLevPy directly from PyPI:
pip install IntLevPy
Usage
To use IntLevPy, import the relevant modules and functions in your Python script or notebook. The package provides functions for simulating processes, computing moments, performing optimizations, and classifying trajectories.
Applying to emperical Data
IntLevPy can be applied to real-life datasets, such as eye-tracking data or financial time series, for classification and analysis using the provided statistical methods.
An example notebook demonstrating the usage of an eye-tracking dataset can be found in the Example Notebook.
Model
Figure: Schematic representation of how the IntLevPy package.
Contact
For questions or inquiries:
Shailendra Bhandari
PyPI Package: IntLevPy on PyPI
Documentation: IntLevPy Documentation
License: This package is licensed under the MIT License.
Contributors: For a detailed list of contributors, visit the Contributors Page.
For a detailed list of contributors, visit: Contributors Page.
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