dpest

A Python package for automating PEST (Parameter Estimation) file creation for DSSAT crop model calibration using time series data.

What is dpest?

dpest is a Python package designed to automate the creation of PEST (Parameter Estimation and Uncertainty Analysis) control files for calibrating DSSAT (Decision Support System for Agrotechnology Transfer) crop models. Currently, dpest is capable of calibrating DSSAT wheat models only. It generates template files for cultivar and ecotype parameters, instruction files for OVERVIEW.OUT and PlantGro.OUT, and the main PEST control file. A utility module is also included to extend PlantGro.OUT files for complete time series compatibility.

Key Features

• Automated generation of PEST control files (.PST).

• Compatibility with DSSAT wheat models.

• Creation of PEST template files (.TPL) for cultivar and ecotype parameters.

• Generation of PEST instruction files (.INS) for key DSSAT output files.

• Utility module to extend PlantGro.OUT files for complete time series.

Installation

dpest can be installed via pip from PyPI.

pip install dpest

Prerequisites

1. DSSAT Software: DSSAT (version 4.8) must be installed on your system.

2. DSSAT Experiment Data: You’ll need a DSSAT experiment to work with. The example below uses the SWSW7501WH N RESPONSE wheat experiment.

3. PEST Software: You’ll need to have PEST (version 18) installed.

How to Use dpest?

Jupyter notebook example

We provide a Jupyter notebook example (usage_example.ipynb) that demonstrates all package functions in a practical workflow and includes steps for using PEST’s “check” functions to validate the generated input files.

Read the Docs

For a detailed, step-by-step example, please refer to the official documentation: Complete Example on Read the Docs

Basic Usage

The following steps provide a brief overview of how to use dpest.

1. Locate DSSAT Genotype Files: The cultivar (.CUL) and ecotype (.ECO) files are typically included with the DSSAT installation. These are usually found in the C:\DSSAT48\Genotype\ directory.

2. Run a DSSAT Simulation: Execute a DSSAT simulation for your chosen wheat experiment using the CERES model. This will generate the necessary output files (OVERVIEW.OUT and PlantGro.OUT), typically found in the C:\DSSAT48\Wheat\ directory.

   2.1. Launch DSSAT. 2.2. Click “Selector”. 2.3. Expand “Crops” and select “Wheat”. 2.4. In the “Data” panel select the “SWSW7501.WHX” experiment. 2.5. Click “Run” button in the toolbar. 2.6. In the “Simulation” popup window, choose “CERES” as the crop model. 2.7. Click “Run Model” and wait for the simulation to finish.

3. Import the ``dpest`` Package:

   To import the entire dpest package:

   import dpest
   

   To import specific modules:

   from dpest import cul, eco, overview, ts, pst, uts
   
   # Now you can use the functions directly:
   cul(...)
   eco(...)
   overview(...)
   ts(...)
   pst(...)
   uts(...)
   

4. Use the Modules

   • cul(): This module creates PEST template files (.TPL) for CERES-Wheat cultivar parameters. Use it to generate template files for cultivar calibration.

   • eco(): This module creates PEST template files (.TPL) for CERES-Wheat ecotype parameters. Use it to generate template files for ecotype calibration.

   • overview(): This module creates PEST instruction files (.INS) for reading observed (measured) values of key end-of-season crop performance metrics and key phenological observations from the OVERVIEW.OUT file. The instruction file tells PEST how to extract model-generated observations from the OVERVIEW.OUT file, compare them with the observations from the DSSAT A file, and adjust model parameters accordingly.

   • plantgro(): This module creates PEST instruction files (.INS) for reading observed (measured) values of plant growth dynamics from the time-series output .OUT files . The instruction file tells PEST how to extract time-series data from the .OUT file, compare that data with the time-series data provided in the DSSAT T file, and adjust model parameters accordingly.

   • pst(): This module creates the main PEST control file (.PST).

   • uplantgro(): This module extends time-series output .OUT files by adding rows when the plant maturity simulation date occurs before a measured observation date.

5. Create Template Files and Instruction Files: Use the dpest modules to generate PEST template files (.TPL) for cultivar and ecotype parameters, and PEST instruction files (.INS) for the OVERVIEW.OUT and time-series output .OUT files.

   import dpest
   
   # 1. Create CULTIVAR parameters TPL file
   cultivar_parameters, cultivar_tpl_path = dpest.cul(
       P = 'P1D, P5', # How the user should enter the parameters
       G = 'G1, G2, G3',
       PHINT = 'PHINT',
       cultivar = 'MANITOU',
       cul_file_path = 'C:/DSSAT48/Genotype/WHCER048.CUL'
   )
   
   # 2. Create OVERVIEW observations INS file
   overview_observations,  overview_ins_path = dpest.overview(
       treatment = '164.0 KG N/HA IRRIG', #Treatment Name
       overview_file_path = 'C:/DSSAT48/Wheat/OVERVIEW.OUT' #Path to the OVERVIEW.OUT file
   )
   # 3. Create PlantGro observations INS file
   plantgro_observations, plantgro_ins_path = dpest.ts(
       treatment = '164.0 KG N/HA IRRIG', #Treatment Name
       variables = ['LAID', 'CWAD', 'T#AD'], #Variables to calibrate
       ts_file_path = 'C:/DSSAT48/Wheat/PlantGro.OUT', #Path to the PlantGro.OUT file
   )
   

6. Create the PEST Control File: Use the dpest.pst() module to generate the main PEST control file (.PST).

   # 4. Create the PST file
   dpest.pst(
       cultivar_parameters = cultivar_parameters,
       dataframe_observations = [overview_observations, plantgro_observations],
       model_comand_line = r'py "C:\pest18\run_dssat.py"', #Command line to run the model
       input_output_file_pairs = [
           (cultivar_tpl_path, 'C://DSSAT48/Genotype/WHCER048.CUL'), #Template file and the file to be modified
           (overview_ins_path , 'C://DSSAT48/Wheat/OVERVIEW.OUT'), #Instruction file and the file to be modified
           (plantgro_ins_path , 'C://DSSAT48/Wheat/PlantGro.OUT') #Instruction file and the file to be modified
       ]
   )
   

7. Run PEST: Calibrate the model using PEST.

Utilities for Editing PEST Control Files

In addition to automating the creation of PEST control and template files for DSSAT CERES-Wheat model calibration, dpest includes a growing set of utility functions under dpest.utils for directly modifying existing .pst (PEST control) files.

Why use dpest.utils?

Unlike libraries such as pyEMU, which parse .pst files into Python objects and rewrite the entire file when saving any change, dpest.utils performs lightweight, line-by-line edits to preserve the original structure and untouched content.

These utilities:

• Edit existing .pst files in place, without reconstructing or redefining unrelated fields.

• Are model-agnostic: they work with any .pst file, not just DSSAT-related ones.

• Only modify model-independent control parameters (e.g., optimization settings), leaving parameter and data blocks untouched.

This makes them ideal for quickly tuning optimization settings or cleaning up ``.pst`` files generated by dpest or other tools.

Example Usage

# Load the dpest.utils
from dpest.utils import noptmax, rmv_splitcols

# Path to the .pst file
pst_file_path = './ENTRY1/PEST_CONTROL.pst'

# Increase the number of optimization iterations (NOPTMAX) in a .pst file
noptmax(pst_file_path, new_value=50)

# Remove SPLITTHRESH/SPLITRELDIFF/SPLITACTION columns from a .pst file parameter groups section
rmv_splitcols("PEST_CONTROL.pst")