GaussMLE.GaussSim

GaussSim

Methods for creating simulated data for testing and benchmarking.

poissonnoise!(stack)

Add Poisson noise to a 3D stack of images.

• stack::Array{T}: The 3D stack to which Poisson noise will be added.

The function modifies stack in-place and returns nothing.

genstack(boxsize, stackdepth, modelsymbol; T=Float32, poissonnoise=false)

Generate a 3D stack of images based on a pre-defined Gaussian model identified by modelsymbol.

Default values will be used for the model paramters.

Arguments

• boxsize::Int: The size of each side of the square 2D ROI.
• stackdepth::Int: The number of slices in the 3D stack.
• modelsymbol::Symbol: A symbol identifying the Gaussian model to use.
• T::Type{<:Real} (optional): The type of real numbers to use (default is Float32).
• poissonnoise::Bool (optional): Whether to add Poisson noise to the stack (default is false).

Returns

• A tuple containing the generated 3D stack, the vector of model parameters for each slice, and the model-specific arguments.

genstack(boxsize, stackdepth, θ, args; poissonnoise=false)

Generate a 3D stack of images based on the given Gaussian model parameters θ and additional arguments args.

Each slice in the stack is a 2D ROI generated by the model.

Arguments

• boxsize::Int: The size of each side of the square 2D ROI.
• stackdepth::Int: The number of slices in the 3D stack.
• θ::Vector{<:GaussMLEParams{T}}: A vector of instances of types that inherit from GaussMLEParams containing the model parameters for each slice.
• args::GaussMLEArgs{T}: An instance of a type that inherits from GaussMLEArgs containing model-specific arguments.
• poissonnoise::Bool (optional): Whether to add Poisson noise to the stack (default is false).

Returns

• The generated 3D stack.

poissonnoise!(stack)

Add Poisson noise to a 3D stack of images.

Arguments

• stack::Array{T}: The 3D stack to which Poisson noise will be added.

Returns

• Modifies stack in-place and returns nothing.