FilesDSSAT

This was an exercise I made to extract data from an excel/csv file and organize it into a .CST file (DSSAT specific format). It can also extract data from a .CST file to a pandas dataframe.

Overview

The source file contains field data from cassava experiments.

The .CST is where we inform real data for DSSAT. With a .CST we are able to compare this results against simulations. That is used for model calibration and validation purposes.

How to use

From excel/csv to .CST

from main import sourceFile, targetFile

# Create the source instance
source = sourceFile('excelFileDirectory')

# Choose the variables to extract and the cultivar name
source.choose_variables(var_list = ["MASSA SECA DE RAÍZ", 
                                    "MASSA SECA DE FOLHAS", 
                                    "MASSA SECA DE CAULE", 
                                    "MASSA SECA TOTAL", 
                                    "IAF"],
                        cultivar = "EUCALIPTO")

# Create the target instance
target = targetFile(filename = "EBCZ1802.CST")  # the filename can be of a nonexistent one

# Set the var list with the same sequence as the 'source' above 
target.set_variables(var_list = ["HWAD", "LWAD", "SWAD", "TWAD", "LAID"])

# and Go!
source.write_file(target)

Of course, the source file must follow the same structure as the exampleSource.xlsx.

From .CST to pd.DataFrame

# That time, must be an existent one
target = targetFile("yourFile.CST")

# and Go!
df = target.read_file()

Further Reading

Working with dynamic crop models

The DSSAT crop modeling ecosystem