Colour match SDL

Description

Colour matching and SDL (Self-Driving Laboratory) simulation utilities for IvoryOS demos. This repository provides a simulated platform to run Bayesian Optimization for color matching, interfacing with simulated instruments.

Installation

First, ensure you have Python >= 3.10. Create a new virtual environment, then you can install the package and its dependencies:

# Install core dependencies
pip install -e .

# Or install with full dependencies (recommended for running all demos)
pip install -e .[full]

Alternatively, if installing purely from the requirements file:

pip install -r requirements.txt

The versions in requirements.txt are frozen reference versions for this repository.

Usage

Order to go through the scripts

In the scripts folder

1. instruments.py
2. multiposition_vici_valve.py
3. demo_prepare_stock_solution_complete.py
4. demo_prepare_stock_solution_with_analyze.py
5. demo_data_visualization_matplotlib.py
6. demo_data_visualization_plotly.py
7. demo_bayesian_optimization.py
8. demo_bayesian_optimization_matplotlib.py
9. demo_bayesian_optimization_plotly.py

In the colour match folder

1. bayesian_optimization_colour_match.py

In the ivoryOS demo basic sdl folder

1. ivoryos_basic_sdl/sdl.py
   • Explore the workflow designer then load and run
     • create_stock_solution_and_analyze.json

In the ivoryOS colour match sdl folder

1. ivorysos_colour_match_sdl/sdl.py
   • Explore the workflow designer then load and run
     • colour_match_ryb_sunset_orange.json
     • colour_match_ryb_grey_blue.json
     • colour_match_rybgp_grey_blue.json

In the examples folder

• Module 1 & 2: sdl_sim_app.py
• Module 3 & 4: color_match_app.py

Authors and acknowledgment

Rebekah Greenwood, Veronica Lai, Wenyu Zhang, Erin Lindenberg, and Jason E. Hein