Installation
Before starting the setup, ensure you have conda
installed. Follow the links for corresponding installation guides.
Automatic Installation Using Script (Recommended)
-
Download the setup script: Download the
epic_setup.bat
script to your local machine. -
Run the setup script: Execute the downloaded script using the following command:
This script will automate the installation process for you.
Setting up GeoEPIC manually
-
Create a virtual environment in conda: To keep your dependencies isolated and avoid conflicts, it is recommended to create a virtual environment. Run the following command to create a new environment named
epic_env
with Python 3.11: -
Activate the environment: Once the environment is created, activate it using the following command:
-
Install the GeoEPIC Toolkit: You have two options to install the GeoEPIC Toolkit:
-
Option 1: Install Directly from GitHub: This method is straightforward and installs the latest version of the toolkit directly from the GitHub repository. Use the following command:
-
Option 2: Install locally (for developers): If you are a developer and plan to make changes to the toolkit, you can clone the repository and install it locally. Follow these steps:
This will clone the repository to your local machine, navigate into the cloned directory, and install the toolkit from the local files.
-
Verify installation
Additional Notes
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Updating GeoEPIC Toolkit: To update the toolkit to the latest version, use the following command:
-
Uninstalling GeoEPIC Toolkit: If you need to uninstall the toolkit, you can do so with:
-
Troubleshooting: If you encounter any issues during installation or setup, refer to the GeoEPIC Toolkit documentation or seek help from the community.
Example Usage
After setting up the GeoEPIC Toolkit, you can start using it in your projects. Here is a simple example to get you started:
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Initialize a new GeoEPIC project:
-
Navigate to your project directory:
-
Run a sample analysis:
This will create a new project directory with the necessary files and run a sample analysis on the provided data.
Happy coding!