Installation & Setup

Requirements

Julia 1.10 or newer.
A CUDA-capable GPU is recommended. The fitting step uses GaussMLE, which is GPU-accelerated via CUDA; see the GaussMLE documentation for GPU/CPU options.
Start Julia with multiple threads — several steps (drift correction, frame connection) are threaded:
```
julia -t auto --project=.
```

Installing

using Pkg
Pkg.add("SMLMAnalysis")

using SMLMAnalysis

using SMLMAnalysis re-exports the key ecosystem types and verbs (cameras, emitter types, the step configs, cluster, render, run_bagol, frameconnect, …), so for most work no further imports are needed.

Development install (from source)

Clone the repository and instantiate its environment:

git clone https://github.com/JuliaSMLM/SMLMAnalysis.jl
cd SMLMAnalysis.jl
julia -t auto --project=. -e 'using Pkg; Pkg.instantiate()'

Then using SMLMAnalysis as above.

Verifying the install

A quick end-to-end check on simulated data (the simulation verbs come from SMLMSim, which you'll need to add separately — it's a dependency of SMLMAnalysis, but Julia environments don't inherit dependencies, so it must also be a direct dependency of yours to using it):

using Pkg
Pkg.add("SMLMSim")

using SMLMAnalysis
using SMLMSim

# Simulate a small 8-mer sample and synthesize its camera frames
cam = IdealCamera(64, 64, 0.1)                          # 64×64 px, 100 nm pixels
sim = StaticSMLMConfig(density = 2.0, σ_psf = 0.13, nframes = 200, ndatasets = 1)
(_, si) = simulate(sim; pattern  = Nmer2D(n = 8, d = 0.05),
                        molecule = GenericFluor(photons = 5.0e4, k_off = 20.0, k_on = 0.05),
                        camera   = cam)
(images, _) = gen_images(si.smld_model, SMLMAnalysis.MicroscopePSFs.GaussianPSF(0.13);
                         dataset = 1, bg = 20.0, poisson_noise = true)

# Run a minimal pipeline on it
config = AnalysisConfig(
    camera = cam,
    steps = [
        DetectFitConfig(boxer = BoxerConfig(boxsize = 7, psf_sigma = 0.13)),
        RenderConfig(zoom = 10),
    ],
)
(result, info) = analyze(images, config)
@show length(result.smld.emitters)

examples/loading_data.jl in the repository is the runnable version of this check.

See Getting Started for a full simulated walkthrough, and Running a Pipeline for the config-driven and step-by-step styles.

Building the documentation

The documentation builds from a checkout of the repository. The docs/ environment sources SMLMAnalysis from that checkout itself (the [sources] entry in docs/Project.toml, honoured on Julia ≥ 1.11), so no Pkg.develop step is needed — and running one would rewrite the tracked docs/Project.toml with an absolute path:

julia --project=docs -e 'using Pkg; Pkg.instantiate()'
julia --project=docs docs/make.jl