User Guide

Scientific user guides for each coco-pipe module. Every guide covers the concepts, the workflow, and the catalog of what the module offers. For the programmatic interface, see the API Reference.

📦 Data & IO

Loading (tabular, BIDS, embeddings), the DataContainer, quality control, and persistence.

Data & IO

🌊 Descriptors

Signal feature extraction — spectral band, parametric, and complexity families — emitted as a DataContainer.

Descriptors

🧠 Decoding — Classical ML

Leakage-safe classification/regression with scikit-learn estimators: cross-validation, feature selection, tuning, and statistical inference.

Decoding

🤖 Decoding — Foundation Models

Pretrained backbones (frozen, fine-tuned, LoRA/QLoRA). Lives in the decoding module but has a wholly separate design.

Foundation Models

🌀 Dimensionality Reduction

Reducers, preservation metrics, interpretation, and post-hoc method comparison.

Dimensionality Reduction

📈 Trajectory Analysis

Kinematics and time-resolved group separation over native 3D (trajectory, time, dim) embedding tensors.

Trajectory Analysis

📊 Visualization

Theme, primitives, and the static/interactive plot catalog.

Visualization

📄 Reports

Building reports, section builders, elements, and advanced templating.

Reports