tensor-network-visualization 1.1.0

Minimal Matplotlib visualizations for TensorKrowch tensor networks.

Tensor-Network-Visualization

Minimal Matplotlib visualizations for TensorKrowch tensor networks.

Repository: https://github.com/DOKOS-TAYOS/Tensor-Network-Visualization

Features

• 2D and 3D plotting for TensorKrowch tensor networks
• Tensors rendered as nodes
• Contractions rendered as edges between tensors
• Dangling indices rendered as labeled stubs
• Self-contractions rendered as loops
• No UI; uses Matplotlib for rendering and NetworkX for graph layouts

Installation

As a dependency

Add to your project's pyproject.toml:

[project]
dependencies = ["tensor-network-visualization>=0.1.0"]

Or install with pip:

pip install tensor-network-visualization

Local development

Inside the project virtual environment:

.\.venv\Scripts\python -m pip install -e ".[dev]"

For runtime-only (editable install without dev tools):

.\.venv\Scripts\python -m pip install -e .

Usage

Input formats

You can pass either:

• TensorNetwork — object with nodes or leaf_nodes (iterable or dict)
• List or tuple of nodes — e.g. [node1, node2, ...] for a subset or nodes from different networks

Each node must have edges, axes_names, and name. Each edge must have node1, node2, and name.

When passing a subset of nodes, edges to nodes outside the list are drawn as dangling legs. Disconnected components (e.g. nodes from different networks) are supported.

from tensor_network_viz import PlotConfig, show_tensor_network

config = PlotConfig(figsize=(8, 6))

# From a TensorNetwork
fig, ax = show_tensor_network(network, engine="tensorkrowch", view="2d", config=config)

# From a list of nodes (subset, or nodes without a TensorNetwork)
fig, ax = show_tensor_network([node1, node2, node3], engine="tensorkrowch", view="2d", config=config)

You can also use the TensorKrowch-specific helpers directly:

from tensor_network_viz.tensorkrowch import plot_tensorkrowch_network_2d, plot_tensorkrowch_network_3d

plot_tensorkrowch_network_2d(network)   # or plot_tensorkrowch_network_2d([node1, node2, ...])
plot_tensorkrowch_network_3d(network)

Project layout

• examples/ — Demo scripts. Run python examples/tensor_network_demo.py mps 2d from the project root. Use --from-list to pass nodes as a list instead of the TensorNetwork.
• scripts/ — Utility scripts (e.g. clean.py to remove caches and build artifacts).

Development

.\.venv\Scripts\python -m ruff check .
.\.venv\Scripts\python -m pyright
.\.venv\Scripts\python -m pytest