openag_sim

Simulating

Prerequisites

• A Windows machine with Scilab and GreenScilab installed.
  • Setting up a Windows VM is sufficient.
  • Inside Windows, run scilab-4.1.exe (in the repository’s Software folder).
  • Place Software/GreenScilabV0.9 folder inside now-installed Scilab’s ‘contrib’ folder.

Obtaining input weather data

This is the procedure to follow if you want to re-download and re-process data from the EPW website. Otherwise, the relevant .dat weather files are available in Data/station_dat_files, and you should feel free to copy them.

• ‘Data’ folder in repository is relevant. Contains epw_reader.py, epw_retriever.py, and ew_weather_data.csv.
• ‘epw’ refers to EnergyPlus aggregated weather data set: https://energyplus.net/weather
• To download weather data from epw website, in standard format
  • In terminal: ‘python epw_retriever.py’ with input argument ‘epw_data.csv’
• To convert the .epw files to .dat files:
  • In terminal: ‘python epw_reader.py’ with input argument ‘EPW’
  • (Run this command from the same directory as the epw_retriever.py command)
• Afterwards, you should have created an ‘EPW’ file in your directory that contains subfolders for every country and weather station. You should also have a directory EPW/dat/ that contains a .dat file for every weather station.

Simulating on weather station .dat files

• Open Scilab. Run command ‘exec(“path to the ‘loader’ file inside Greenlab”)’
• Run command ‘exec(“fun1.sci”)’ to have access to the prewritten simulator function.
• Run command ‘fun1(“path to parameter file”, “path to folder with batch of desired .dat files/*.dat”, “path to desired output directory”)’
  • The parameter file for five stages of cotton growth is included in this repository as Software/GreenScilabV0.9/parafiles/cotton_5stages.sci
• You should have output files that look like this (five from each simulation):

Visualizing simulator output

Converting simulation output to visualization input

Known issue: this process only creates 1690 (coordinate, value, weather station) tuples, rather than the ~2500 that were simulated and are listed in referenceFile.txt. This is probably due to the prefix-removal section of the code.

• run create_viz_input.py with the following command line arguments:
  • ‘—-dir’, default = ‘EPW’: point the script to the original directory with scraped EPW data (it looks here to get weather station names)
  • ‘—-referencefile’, default = ‘../Data/output/referenceFile.txt’: location of referenceFile.txt that was output from the simulations
  • ‘output’, default='latLongValData.json’: specify target file for writing formatted data.

Generating visualization

• Name the resultant .json ‘latLongValData.json’ and place it in a directory with the visualization files. Reload visualization. Done!
• [Integration with OpenAg repository TBD—currently the visualization is in Elena’s personal github.]
  • Code
  • View (taking about 30 seconds to load is normal)