AMS-BP 0.3.1

Advanced Microscopy Simulations developed for the Weber Lab by Baljyot Singh Parmar

AMS-BP

Advanced Fluorescence Microscopy Simulation Tool

AMS-BP is a powerful simulation tool for advanced fluorescence microscopy experiments. This guide covers both command-line usage and library integration.

Overview of Simulation Workflow

A ground truth is created, a, with $f_{n}$ fluorophore types of $N_{f_{n}}$ molecules each. If applicable, the motion of these molecules is modelled using a 3D bounded FBM with fluctuating generalized diffusion coefficients and Hurst parameters. Variations are modelled as a Markov Chain and require rate constants as parameters. Different fluorophores can have different motion models. The resolution of the motion models is $\Delta t$ and cannot be smaller than 1 ms (for computational efficiency). Given the microscope parameters specific to the experimental procedure to simulate, at every time $t_{j}$, the excitation intensity for each channel (b) is calculated at each fluorophore's location, c. For $t_{j} \rightarrow t_{j+\Delta t}$, the photophysical state trajectory of the fluorophore is simulated using the light intensity at the molecule's location as input for any light-dependent transition rates, d. For the duration that the shutter is open and light is emitted from the sample, emission filters for each channel are applied before the convolution with PSF models, e. The incident photons on the detector are then converted to photoelectrons and finally to digital units using the detector models provided, f.

API Reference and Docs

Find detailed API references for the library at: joemans3/github.io/AMS_BP

A more detailed example is provided in the jupyter notebook in the examples. For starters refer to the VisualizingIndividualModules. Then head over to the laser modulation module which will show how to change the laser power over time in the simulations. Then view an example of a complex experiment setup for FRAP which is possible by the use of compositions of modules in this simulation library.

Examples (Click on the image buttons to be taken to the Jupyter notebooks):

!!ATTENTION!! - Please note that you NEED to install the developmental dependencies to run the examples in full. This is mainly for installing the Jupyter notebook extensions, matplotlib and other visualization packages.

Table of Contents

• Installation
• Command Line Interface
• Configuration File
• Running Experiments
• Advanced Usage

Installation

Installing the CLI tool using UV

1. Install UV.
2. Run the command:

uv tool install AMS_BP

3. You will have access to two CLI commands (using the uv interface):
   • run_AMS_BP runsim : This is the main entry point for the simulation. (see run_AMS_BP runsim --help for more details)
   • run_AMS_BP config : This is a helper tool to generate a template config file for the simulation. (see run_AMS_BP config --help for more details)
   • Note: using run_AMS_BP --help will show you all the available commands.
4. You can now use these tools (they are isolated in their own env created by uv, which is cool).

PyPi

1. Run:

pip install AMS_BP

Command Line Interface

AMS-BP provides a command-line interface with two main commands:

# Generate a default configuration file
run_AMS_BP config [OPTIONS]

# Run a simulation using a configuration file
run_AMS_BP runsim CONFIG_FILE

Config Command Options

• -o, --output_path PATH: Specify the output directory for the configuration file
• -r, --recursive_o: Create output directory if it doesn't exist

Configuration File

The configuration file (sim_config.toml) is divided into several key sections:

For a detailed description of the configuration file, refer to the Configuration File Reference.

Basic Units

version = "0.1"
length_unit = "um"        # micrometers
time_unit = "ms"          # milliseconds
diffusion_unit = "um^2/s" # diffusion coefficient units

Key Configuration Sections

1. Cell Parameters

   • Define cell space dimensions

2. Molecule Parameters

   • Number of molecules per type
   • Tracking types (constant/fbm)
   • Diffusion coefficients
   • State transition probabilities

3. Global Parameters

   • Sample plane dimensions
   • Cycle count -> Exposure time + Interval time
   • Exposure and interval times

4. Fluorophore Configuration

   • Any number of fluorophores
   • Any number of States per fluorophore
   • Fluorophore StateType: (bright, dark, bleached) -> All States must be one of these.
   • Transition parameters
   • Spectral properties

5. Optical Configuration

   • PSF parameters
   • Laser settings
   • Channel configuration
   • Camera settings

Running Experiments

AMS-BP's CLI currently supports two types of experiments:

(however this can be extended when used as a library)

1. Time Series

[experiment]
experiment_type = "time-series"
z_position = 0.0
laser_names_active = ["red", "blue"]
laser_powers_active = [0.5, 0.05]
laser_positions_active = [[5, 5, 0], [5, 5, 0]]

2. Z-Stack

[experiment]
experiment_type = "z-stack"
z_position = [-0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5]
laser_names_active = ["red", "blue"]
laser_powers_active = [0.5, 0.05]
laser_positions_active = [[5, 5, 0], [5, 5, 0]]

To run the default configuration:

1. Make sure you followed the uv tool installation.
2. Make a copy of the default configuration file using the command:

run_AMS_BP config

3. Run the sim:

run_AMS_BP runsim sim_config.toml

4. View the results in the newly created folder, whose name is defined in the config file.

Advanced Usage

Using AMS-BP as a Library

For programmatic control, you can import and use AMS-BP as a Python library:

from AMS_BP.configio.convertconfig import ConfigLoader

# Configuration loader intialization
config_loader = ConfigLoader(config_path="path/to/config.toml")

# Setup microscope
setup_config = config_loader.setup_microscope()
microscope = setup_config["microscope"]
config_exp = setup_config["experiment_config"]
function_exp = setup_config["experiment_func"]

# Run simulation
frames, metadata = function_exp(microscope=microscope, config=config_exp)

# Save results
from AMS_BP.configio.saving import save_config_frames
save_config_frames(metadata, frames, setup_config["base_config"].OutputParameters)

NOTE: Please note that this application DOES NOT currently model the process of stimulated emission, and as such is not suitable for simulating stimulated emission microscopy (STED)-type experiments. Work in this area is ongoing.

High Priority Features

1. Irregular cell shapes with motion models (supported with release of v0.2.0) 2. Stimulated Emission models 3. STORM workflow examples 4. CTRW motion models 5. Simpler configurations