Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

Code Block
breakoutModewide
library(ForestForesight)# this will load the FF library and the variables in the config.yml file
# Make sure you have DATA_FOLDER in config.yml in your working directory
download_folder <- Sys.getenv("DATA_FOLDER")

print(download_folder)
#if the previous line returns empty it means your system environment variables were not set. You can then create a folder
#somewhere in your file explorer and use  the following line to select that folder:
download_folder <- dir.choose() 

# Choose an identifier (country code, tile ID, or SpatVector). 
# ONLY RUN 1 OF THE FOLLOWING TWO LINES
identifier <- "LAO" # Example: Laos
identifier <- vect(file.choose()) # Make sure this is a valid SpatVector object.  

# Part 1: Download only predictions
ff_sync(
    ff_folder = download_folder,
    identifier = identifier,
    download_data = FALSE,          # Don't download input data
    download_groundtruth = FALSE,   # Don't download ground truth
    download_predictions = TRUE,     # Only download predictions
    date_start_date = "2023-01-01"       # Only download data since 2023
)

# Part 2: Download complete dataset
ff_sync(
    ff_folder = download_folder,
    identifier = identifier,
    features = "Model",             # Download model-related features
    download_data = TRUE,          # Download input data
    download_groundtruth = TRUE,   # Download ground truth
    download_predictions = FALSE,   # Download predictions
    download_model = TRUE,        # Download the model
    date_start_date = "2023-01-01"       # Only download data since 2023
)

# check all the other available options of ff_sync
?ff_sync

...