Add tuple-pattern return format for simulate and gen_images#31
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Add tuple-pattern return format for simulate and gen_images#31
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Introduces AbstractLabeling type hierarchy to separate labeling statistics from molecule photophysics: - FixedLabeling: deterministic n fluorophores per site - PoissonLabeling: Poisson-distributed fluorophores per site - BinomialLabeling: binomial-distributed (n trials, p probability) All types include labeling_efficiency parameter for probability that a site gets labeled at all. Key design decisions: - Labeling is orthogonal to Molecule (photophysics) - enables composition - Default FixedLabeling(n=1, efficiency=1.0) preserves backward compatibility - apply_labeling() dispatches on labeling type for coordinate expansion - Metadata tracks labeling_type and labeling_params Usage: simulate(params; pattern=Nmer2D(), labeling=PoissonLabeling(1.5), molecule=fluor) Co-Authored-By: Claude Opus 4.5 <[email protected]>
- Update emitter constructors in simulation.jl, photophysics.jl, and coordinate_noise.jl to set σ_xy=0.0 (correct for symmetric PSFs) - Update test files to use new Emitter2DFit keyword constructor format - Require SMLMData >= 0.5.1 for σ_xy field support Co-Authored-By: Claude Opus 4.5 <[email protected]>
- Add burn_in parameter to intensity_trace() and kinetic_model() for simulating pre-illumination before recording (photobleaching models) - Add state1 parameter to simulate() for explicit initial state control - Fix CTMC warnings for absorbing states (Q[i,i]=0 is valid) - Update api_overview.md with labeling types documentation - Update CLAUDE.md with simulation pipeline documentation burn_in is useful for 3-state photobleaching models where you want to simulate the experimental protocol of high laser power for several seconds before data collection begins. Co-Authored-By: Claude Opus 4.5 <[email protected]>
- uniform2D/uniform3D now return pattern_ids indicating pattern membership - apply_labeling preserves pattern_ids through expansion (with backward-compat overloads) - Emitters now carry pattern id through simulation pipeline - Update SMLMData compat to "0.5, 0.6" - Update documentation for new return signatures Co-Authored-By: Claude Opus 4.5 <[email protected]>
BREAKING CHANGE: All simulation and image generation functions now return (output, info) tuples instead of single values or 3-tuples. Changes: - simulate(::StaticSMLMParams) returns (smld_noisy, SimInfo) - SimInfo contains smld_true, smld_model, timing, and counts - simulate(::DiffusionSMLMParams) returns (smld, SimInfo) - gen_images() returns (images, ImageInfo) - gen_image() returns (image, ImageInfo) New types: - SimInfo: elapsed_ns, backend, device_id, seed, smld_true, smld_model, n_patterns, n_emitters, n_localizations, n_frames - ImageInfo: elapsed_ns, backend, device_id, frames_generated, n_photons_total, output_size Bump version to 0.5.0 Co-Authored-By: Claude Opus 4.5 <[email protected]>
- SimInfo.elapsed_s::Float64 (was elapsed_ns::UInt64) - ImageInfo.elapsed_s::Float64 (was elapsed_ns::UInt64) - Time now stored directly in seconds for convenience Co-Authored-By: Claude Opus 4.5 <[email protected]>
Breaking change: Renamed simulation config types for consistency: - StaticSMLMParams -> StaticSMLMConfig - DiffusionSMLMParams -> DiffusionSMLMConfig Updated all source files, tests, and documentation. Co-Authored-By: Claude Opus 4.5 <[email protected]>
Breaking changes in this release: - simulate() returns (output, info) tuple instead of 3-tuple or single value - gen_images()/gen_image() return (images, ImageInfo) tuple - StaticSMLMParams renamed to StaticSMLMConfig - DiffusionSMLMParams renamed to DiffusionSMLMConfig Co-Authored-By: Claude Opus 4.5 <[email protected]>
SMLMSimParams <: AbstractSMLMConfig, SimInfo <: AbstractSMLMInfo, ImageInfo <: AbstractSMLMInfo. Remove unused AbstractSim type. Co-Authored-By: Claude Opus 4.6 <[email protected]>
Requires SMLMData v0.7.0 which provides AbstractSMLMConfig and AbstractSMLMInfo abstract types for the tuple pattern. Co-Authored-By: Claude Opus 4.6 <[email protected]>
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Summary
(output, info)tuplessimulate(::StaticSMLMParams)returns(smld_noisy, SimInfo)with intermediate results in infosimulate(::DiffusionSMLMParams)returns(smld, SimInfo)gen_images()andgen_image()return(images/image, ImageInfo)SimInfoandImageInfotypes provide timing, counts, and metadataTest plan
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