DICE Launch

Introduction:

We are excited to announce the first official release of DICE (Diffusion Insight Computation Engine), v1.0.0 - "DICE Launch". DICE is an open-source tool designed for researchers in time-resolved microscopy and related fields. It evaluates the precision and accuracy of diffusion coefficient estimates derived from optical measures of excited state transport, offering a robust method for assessing experimental accuracy and precision by simulating parameters that mirror your experimental setup.

Key Features:

• Simulation of time-series profiles: DICE simulates a population of excited states as a Gaussian distribution profile undergoing decay and diffusion.
• Noise addition and Gaussian fit: Incorporates white noise into profiles and fits the time-evolved noisy profiles with Gaussian functions.
• Linear fit and diffusion coefficient estimation: Uses a weighted least squares method to fit Mean Squared Displacement (MSD) values to a linear function, estimating the diffusion coefficient.
• Statistical analysis and presentation: Provides a statistical view of the precision and accuracy of diffusion estimates and a customizable plotting function for result presentation.

Getting Started:

• Installation: Ensure you have Python installed, then run pip install numpy pandas matplotlib scipy statsmodels joblib to install the necessary packages.
• Basic usage: Modify the parameters.txt file to align with your experimental parameters, then run the simulation using the run_dice.py script.

Documentation:

For detailed instructions and information, please refer to our README.