neuroweave-tools 0.1.0

A modular scientific modeling framework for temporal neural encoding models.

NeuroWeave

NeuroWeave is a modular Python framework for temporal neural encoding models, including TRF-style models and planned extensions for connectivity, state-dependent, representational, and simulation workflows.

Installation

Install the package in editable mode:

pip install -e .

Install with optional extras as needed:

pip install -e ".[dev]"
pip install -e ".[docs,viz]"

Building the documentation

Install the documentation dependencies and build the HTML site:

pip install -e ".[docs]"
cd docs
make html

The build uses Sphinx, Sphinx-Gallery, and autosummary to generate the tutorial gallery, user guide, and API reference.

Development

The project uses a src layout and mirrored tests:

• src/neuroweave/: package source code
• tests/neuroweave/: test modules mirroring the package hierarchy
• pyproject.toml: package metadata and tool configuration

Architecture Overview

The package is organized into focused modules for:

• core: shared abstractions and registry primitives
• models: TRF and higher-level model families
• estimators: fitting backends and estimator adapters
• design, evaluation, stats, viz: analysis utilities and workflows
• simulation: synthetic data generation and benchmark datasets
• api, backends, utils: user-facing entry points and integrations

The repository includes a Sphinx documentation skeleton under docs/, using pydata-sphinx-theme and autosummary-generated API reference pages.