File I/O

SMLMData provides functionality for importing and exporting localization data in various formats. This page documents the currently supported formats and related functions.

SMITE Format

SMITE is a MATLAB-based format commonly used in single molecule localization microscopy. SMLMData provides types and functions for interfacing with this format.

Types

# Helper type for loading SMITE .mat files
struct SmiteSMD 
    filepath::String    # Path to the directory containing the .mat file
    filename::String    # Name of the .mat file
    varname::String     # Variable name in the .mat file (default: "SMD")
end

# Constructor with default variable name
SmiteSMD(filepath::String, filename::String) = SmiteSMD(filepath, filename, "SMD")

# SMLD type compatible with SMITE format
struct SmiteSMLD{T,E<:AbstractEmitter} <: SMLD
    emitters::Vector{E}
    camera::AbstractCamera
    n_frames::Int
    n_datasets::Int
    metadata::Dict{String,Any}
end

Loading SMITE Data

SMLMData provides separate functions for loading 2D and 3D data from SMITE format:

# Load 2D data
smd = SmiteSMD("path/to/data", "localizations.mat")
smld_2d = load_smite_2d(smd)

# Load 3D data
smld_3d = load_smite_3d(smd)

Both functions handle:

• Conversion of coordinates to microns
• Creation of appropriate camera model
• Preservation of metadata

Example:

# Load SMITE data
smd = SmiteSMD("/data/microscopy", "cell1_localizations.mat")
smld = load_smite_2d(smd)

# Inspect metadata
println("Loaded $(length(smld.emitters)) emitters")
println("Image size: $(smld.metadata["data_size"])")
println("Pixel size: $(smld.metadata["pixel_size"]) μm")

Saving SMITE Data

You can save any SMLD object back to SMITE format:

# Save to SMITE format
save_smite(smld, "output/directory", "processed_results.mat")

The save_smite function:

• Converts SMLMData structures to SMITE's structure
• Preserves all metadata fields
• Saves in MATLAB v7.3 format

Example workflow:

# Load data
smd = SmiteSMD("raw_data", "experiment1.mat")
smld = load_smite_2d(smd)

# Process data
bright = @filter(smld, photons > 1000)
roi = filter_roi(bright, 10.0:20.0, 10.0:20.0)

# Add analysis info to metadata
roi.metadata["analysis_date"] = Dates.now()
roi.metadata["selection_criteria"] = "photons > 1000, ROI (10-20,10-20)"

# Save processed data
save_smite(roi, "processed_data", "experiment1_processed.mat")

Future File Formats

SMLMData is designed to be extended with additional file formats. Future versions may include support for:

• CSV formats
• HDF5
• ThunderSTORM
• Picasso

When new formats are added, they will be documented in this section.