Systemic Tau and Discrete Extramental Clock (RECD) implementation
Project description
Systemic Tau & Discrete Extramental Clock (RECD)
systemictau is a Python package implementing the mathematical and ontological framework of the Systemic Tau paradigm and the Discrete Extramental Clock (RECD), developed by Dr. Johel Padilla-Villanueva.
This package offers a novel, non-reductive approach for time series analysis in complex systems, shifting from classical variance-based early-warning signals to purely ordinal observables. It proves that time is not a homogeneous container (Chronos) but an emergent, generated metric dependent on the system's own structural reorganization (Kairos).
Core Concepts
The package operationalizes the three-layer ontological framework detailed in the Magna Synthesis:
- Capa 1 (Local Intensification): Measures local persistence through hyper-persistence of ordinal states and structural trapping (RQA).
- Capa 2 (Relational Coherence): Identifies Joint Episodes (relational kairoi) by measuring the anti-synchronization across modules.
- Capa 3 (Ontological Ascent): Detects the exact moment of global structural reorganization through Kolmogorov-Smirnov contrasts and Frobenius norm shifts, indicating the emergence of a new law of temporal discreteness.
Installation & Execution
The easiest way to install and run the Systemic Tau Mathematical Desktop Application is via the provided Makefile. This ensures all dependencies (including customtkinter, scipy, etc.) are installed perfectly.
# 1. Install the app and all its dependencies
make install
# 2. Run the desktop application
make run
If you prefer to install it manually using uv or pip:
uv pip install -e ".[full]"
systemictau-gui
Quickstart
import numpy as np
import systemictau as st
# 1. Provide your multivariate time series data
# X = np.array([...]) # Shape: (T_steps, N_components)
np.random.seed(42)
X = np.random.randn(500, 4)
# 2. Compute the Systemic Tau over sliding windows
taus_global, taus_per_module = st.compute_taus(X, window_size=13)
# 3. Accumulate the Discrete Extramental Time (RECD)
T_series, dtk_series, gate_series, depths = st.accumulate_time(taus_global)
# 4. Extract Relational Windows (Joint Episodes)
hp_z, core_hyper = st.hyper_persistence(taus_global)
lam, tt = st.rolling_rqa(taus_global)
M_series = st.critical_mass_metric(hp_z, lam, tt)
A_series = st.compute_antisynchronization(taus_per_module)
episodes = st.extract_joint_episodes(A_series, M_series)
# 5. Detect Capa 3 Reorganization (Ontological Ascent)
t_frob, max_dist = st.detect_reorganization_frob(taus_per_module)
t_ks, max_ks = st.detect_reorganization_ks(dtk_series)
t_star = st.consensus_transition(t_frob, t_ks)
print(f"Capa 3 Transition detected at t* = {t_star}")
Systemic Tau Studio (Web Application)
For interactive multi-ontological analysis with publication-quality visualizations:
# Install with the studio extra (recommended)
pip install "systemictau[studio]"
# Or from source
cd /path/to/systemictau_v4
uv pip install --python .venv/bin/python ".[studio]"
# Run the app
# Note: file watcher is disabled by default via .streamlit/config.toml
# to avoid reentrant stdout / watcher errors on macOS + large projects.
PYTHONPATH=src streamlit run src/systemictau/studio/app.py
# If you want to force-disable watcher explicitly:
# PYTHONPATH=src streamlit run src/systemictau/studio/app.py --server.fileWatcherType none
# or (after proper install)
systemictau-studio
Key features:
- Upload CSV or XLSX (panel or wide format)
- Automatic or manual ontological partitioning (Local / Medium / Global)
- Systemic Tau + RECD computed consistently across scales
- High-quality plots ready for papers (PNG/SVG/PDF)
- Built-in interpretation following the Principle of Ontological Ascent
- What-if simulation of different clusterings
Note on Excel files: The app requires openpyxl. If you see an import error, run:
uv pip install --python .venv/bin/python openpyxl
Citation
If you use this package in your research, please cite the foundational work:
Padilla-Villanueva, Johel. (2026). Síntesis Magna del Tau Sistémico. Version v6. Zenodo. DOI: 10.5281/zenodo.20576241
For a full list of references and mathematical proofs, consult the Zenodo Archive.
License
This project is licensed under the MIT License - see the LICENSE file for details. The underlying theoretical corpus is published under CC-BY 4.0.
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