Moja global Chile data pre-processing project setup
The following section describes how to set up the project on your local machine. The following are minimum requirements:
Setting up the project
The following instructions describe how to install all the required tools to do live data pre-processing on a Windows 10 system.
After installing, R Studio and R programming language, start the R Studio IDE and follow these steps:
Click on
File
and selectNew Project
.Click on
Version Control
to checkout a project from a version control repository.Click on
Git
to clone the project from our GitHub repository.Add the repository URL:
https://github.com/moja-global/GCBM.Chile.Data_Preprocessing
. Select the subdirectory as per your needs and click onCreate Project
.After the repository is cloned and a workspace is initialized, download the Input data required for the data pre-processing. You can download it from the GitHub releases:
Visit the GitHub releases on the GCBM Chile Data Preprocessing repository and check out the latest release.
Scroll down to find the
Input_Files.rar
which contains the dataset used by the pre-processing algorithm.Click on
Input_Files.rar
and download it on your local machine. Extract theInput_Files
directory on the root of the cloned GCBM Chile Data Preprocessing repository.Optional: You can download the
Output_Files.rar
as well for reproducibility and checking the results of the pre-processing algorithm.
Ensure the following directory structure for the project:
├── Input_Files
│ ├── Growth # Excel spreadsheet with growth data
│ ├── LUC # Trazabilidad (Land use) data
│ ├── SOC # Soil Organic carbon data
| └── Temperature # Temperature raw data (NetCDF)
├── Output_Files
│ ├── input_database
│ └── layers
│ └── raw
├── disturbances
│ ├── environment
| └── inventory
├── Processing_codes
├── README.md
├── docs/
├── run_all.R
└── ...
Running the project
With the initial setup complete, you are now ready to run the pre-processing algorithm code.
From the R Studio IDE, select the
run_all.R
file and click onRun
to run all the pre-processing code.Optionally, choose the individual files in the
Preprocessing_Codes
to run them singularly. Make sure to install the R packages as suggested by the R Studio.
With the repository and tools set up on your workstation, you can now either edit existing code or prepare local datasets for a GCBM run using R.