PESTools – A Python toolkit for processing PEST-related information

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Abstract

PESTools is an open-source Python package for processing and visualizing information associated with the parameter estimation software PEST and PEST++. While PEST output can be reformatted for post- processing in spreadsheets or other menu-driven software packages, that approach can be error-prone and time-consuming. Managing information from highly parameterized models with thousands of parameters and observations presents additional challenges. PESTools consists of a set of Python object classes to facilitate efficient processing and visualization of PEST-related information. Processing and visualization of observation residuals, objective function contributions, parameter and observation sensitivities, parameter correlation and identifiability, and other common PEST outputs have been implemented. PESTools is integrated with the pyemu software package for linear-based computer model uncertainty analyses, allowing for efficient computations using the Jacobian Matrix without any external utilities or files. The use of dataframe objects (pandas Python package) facilitates rapid subsetting and querying of large datasets, as well as the incorporation of ancillary information such as observation locations, times, measurement types, and other associated information. PESTools’ object methods can be easily scripted with concise code, or alternatively, the use of IPython notebooks allows for live interaction with the information. PESTools is designed to streamline workflows and provide deeper insight into model behavior, enhance troubleshooting, and improve transparency in the calibration process.

Additional publication details

Publication type Conference Paper
Publication Subtype Conference Paper
Title PESTools – A Python toolkit for processing PEST-related information
Year Published 2015
Language English
Publisher MODFLOW and More 2015 Conference
Contributing office(s) Wisconsin Water Science Center
Description 5 p.
Larger Work Type Book
Larger Work Subtype Conference publication
Larger Work Title MODFLOW and More 2015 Proceedings
First page 393
Last page 397