Notebook
The Python notebook feature in GRID is the central element in the development experience. It provides an interactive environment where you can write and execute Python code that directly interacts with the simulation and AI models. This feature is intended to be used for programming robotic behaviors, invoking machine learning models, and visualizing results in real-time.
Key features of the Python notebook in GRID include:
Interactive Coding: Write and run Python code in real-time, with immediate feedback and results displayed within the notebook.
Simulation Integration: Directly interact with the simulation environment, allowing you to test and refine your code on the fly.
Data Visualization: Utilize built-in tools to visualize data outputs, making it easier to analyze and understand the results of your simulations.
Machine Learning: Integrate and run machine learning models within the notebook, leveraging the power of GRID's extensive ML libraries.
Skill Development: Export your code as skills that can be reused and shared across different sessions and scenarios.
To get started with the Python notebook, simply launch a session and observe the Notebook Panel. The notebook will be pre-populated with initial cells that you should run first. From there, you can add new cells, write your own code, and interact with the simulation in a seamless and intuitive manner.
Remember to make use of the various controls available in the notebook interface, such as adding new cells, running code, exporting skills, and downloading your notebook as a .ipynb file. These tools are designed to streamline your workflow and enhance your productivity within the GRID environment.
Notebook Controls
Add Cell: Add a new cell to the notebook.
Collapse Button: Minimize a cell.
Play Button: Run the code in the current cell.
Interrupt: Interrupt a running cell. (only enabled when a cell is actively running)
Download: Download the notebook as a .ipynb file.
Load sample notebooks: Load a sample notebook to get started.