TAMC-PLANTS: Reproducible multiband residual-analysis pipeline for plant electrophysiology recordings

This Zenodo record contains the reproducible TAMC-PLANTAS v3 pipeline release, distributed as: TAMC-PLANTAS_v3_2026-06-07.zip TAMC-PLANTAS is a reproducible Python pipeline for multiband residual and Wavelet/PLV phase-synchronization analysis of plant electrophysiology recordings. It transforms public plant bioelectrical WAV recordings into auditable residual metrics, species-level multiband descriptors, distance-based similarity maps, phylogenome-style visualizations, electrical alignment summaries, cross-species residual-coupling reports, and dataset-wide phase-synchronization summaries. This release includes the Python source code, the updated non-interactive launcher, documentation, requirements file, src-level README, and all scripts needed to rerun the complete analysis workflow. The complete non-interactive workflow is executed with: python run_plantasfull.py The expected input dataset path is: data/raw_plants/ This software release is designed to be used with the companion dataset prepared by the author: TAMC-PLANTAS derived dataset: pipeline-ready plant electrophysiology recordings for reproducible multiband bioelectrical analysishttps://doi.org/10.5281/zenodo.20577639 That dataset was created specifically to support reproducible execution of TAMC-PLANTAS. It reorganizes the original public plant electrophysiology recordings into a deterministic data/raw_plants/ folder structure and includes provenance metadata, source attribution, SHA-256 checksums and file manifests. After extracting the companion dataset, the folder data/raw_plants/ should be copied or linked into the TAMC-PLANTAS project root before running the pipeline. The current v3 release includes two complementary Wavelet/PLV layers. First, the dataset-wide batch module: tamc_wavelet_sync_batch.py This module computes compact PLV and phase-delay summary statistics across all valid WAV recordings and generates: results/tamc_wavelet_sync_batch_summary.csvresults/tamc_wavelet_sync_batch_report.pdfresults/figures/tamc_wavelet_sync_batch/ In the reference run used for the manuscript, this module processed 360 out of 361 recordings, with one recording skipped because its processed length was insufficient for Hilbert-phase analysis. Second, the representative single-record visualization module: tamc_wavelet_sync.py This module illustrates within-recording phase dynamics and PLV structure for one selected Araucaria recording. It is intended as a visual diagnostic example, while dataset-wide phase-synchronization conclusions should be based on the batch module. The original plant electrophysiology recordings used to build the derived dataset are credited to Madariaga et al. and are associated with the original source article and public source-data release: Madariaga et al. (2024), A library of electrophysiological responses in plants: A model of transversal education and open science.https://doi.org/10.1080/15592324.2024.2310977 Original source :https://figshare.com/s/65447c618656565467e6 This release does not claim authorship over the original plant recordings. Its contribution is the TAMC-PLANTAS computational framework, reproducible folder structure, Python implementation, analysis scripts, derived metrics, reporting workflow and documentation for independent reruns and audit-oriented verification. The study is methodological and exploratory. The generated species-level fingerprints, electrical genome-like matrices and phylogenome-style maps should be interpreted as computational descriptors of the analysed recordings, not as definitive species traits, taxonomic classifications or evidence of a literal biological electrical genome. Biological interpretation requires future controlled validation with balanced sampling, multiple individuals per species, standardized electrode placement, environmental metadata, robustness checks and sensitivity analyses over frequency-band definitions. This version is intended to support reproducible research, independent inspection, extension by other users, and future controlled studies of plant bioelectrical dynamics.