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.
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.
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.
# That time, must be an existent one
target = targetFile("yourFile.CST")
# and Go!
df = target.read_file()
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