Add Matlab-parity methods and rewrite paper examples#49
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iahncajigas merged 6 commits intomainfrom Mar 10, 2026
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Port missing SignalObj methods from Matlab nSTAT toolbox: - Time manipulation: shift, shiftMe, alignTime - Arithmetic: power, sqrt - Cross-covariance: xcov (mean-removed xcorr) - Spectral: periodogram, MTMspectrum (DPSS multi-taper), spectrogram Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Port missing FitResSummary methods from Matlab nSTAT toolbox: - plotAllCoeffs: errorbar plot of GLM coefficients across neurons/fits - plot3dCoeffSummary: 3D bar plot of binned significant coefficients - plot2dCoeffSummary: stacked ridge-plot of coefficient distributions - plotKSSummary: subplot grid of KS goodness-of-fit plots per neuron Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major additions ported from Matlab nSTAT toolbox: SSGLM (State-Space GLM) EM algorithm in decoding_algorithms.py: - PPSS_EStep/PPSS_MStep: E-step (Kalman smoothing) and M-step (Newton) - PPSS_EM/PPSS_EMFB: Full EM with forward-backward smoothing - estimateInfoMat: Fisher information for coefficient CIs - prepareEMResults: Package EM output as FitResult objects - _ComputeStimulusCIs_MC: Monte Carlo stimulus confidence intervals Unscented Kalman Filter (UKF) in decoding_algorithms.py: - ukf_sigmas: Sigma point generation via Cholesky decomposition - ukf_ut: Unscented transformation - ukf: Full UKF one-step update SpikeTrainCollection methods in trial.py: - ssglm(): Run SSGLM EM on spike train collection - ssglmFB(): Run SSGLM EM with forward-backward smoothing Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace thin wrappers (calling main_for) with self-contained scripts matching the Matlab example structure: - example01: Full nSTAT class API usage (nspikeTrain, Trial, Analysis) for mEPSC Poisson modeling under constant and washout Mg2+ - example02: Whisker stimulus GLM with lag/history selection - example03: PSTH comparison and SSGLM dynamics (two-part) - example04: Place-cell receptive fields (Gaussian vs Zernike) - example05: PPAF and hybrid filter decoding (three-part) Each script has: detailed docstrings, workflow comments matching Matlab, CLI args (--repo-root, --export-figures, --export-dir, --output-json), and proper result merging for multi-section examples. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add overview paragraph describing toolbox capabilities, lab website links, license note (GPL v2), Figshare dataset DOI, PMID, and cross-reference to the Matlab repo. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Port findPeaks, findMaxima, findMinima, findGlobalPeak from Matlab SignalObj. Fixes two Matlab bugs: - findPeaks 'minima' branch now negates data before peak detection (Matlab original calls findpeaks on raw data, finding maxima instead) - findGlobalPeak minima branch uses correct variable name (Matlab has typo 'sOBj' instead of 'sObj') Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
core.py): Portshift,shiftMe,alignTime,power,sqrt,xcov,periodogram,MTMspectrum,spectrogramfrom Matlabfit.py): PortplotAllCoeffs,plot3dCoeffSummary,plot2dCoeffSummary,plotKSSummarydecoding_algorithms.py): FullPPSS_EMFBimplementation (~700 lines) with E-step (Kalman), M-step (Newton), Fisher information, and Monte Carlo CIsdecoding_algorithms.py): Portukf,ukf_ut,ukf_sigmastrial.py): Convenience methods for running SSGLM on spike train collectionsTest plan
pytest tests/ -v)test_paper_example_scripts.py)🤖 Generated with Claude Code