swctools
========

Jupyter-first toolbox for SWC parsing, modeling, analysis, geometry, and 3D visualization (NetworkX, NumPy, Plotly).

- Parse SWC into directed ``SWCModel``
- Visualize skeletons (centroid) with ``plot_model``
- Build volumetric frusta meshes with ``FrustaSet``, or use the master ``plot_model``

.. toctree::
   :maxdepth: 2
   :caption: Contents:

   installation
   examples
   api

Quick start
-----------

.. code-block:: python

   from swctools import parse_swc, SWCModel, FrustaSet, PointSet, plot_model, set_config

   # Optional: global viz settings (equal axes enforced by default)
   set_config(width=800, height=600)

   swc = """
   # CYCLE_BREAK reconnect 2 3
   1 1 0 0 0 1 -1
   2 3 2 0 0 0.5 1
   3 3 2 0 0 0.5 1
   4 3 3 0 0 0.4 2
   """.strip()

   swc_model = SWCModel.from_swc_file(swc, strict=True, validate_reconnections=True)
   fr = FrustaSet.from_swc_model(swc_model, sides=16, end_caps=False)

   # Optional overlay points (as small spheres)
   ps = PointSet.from_points([(0,0,0), (3,0,0)], base_radius=0.05)

   # One-call visualization
   fig = plot_model(swc_model=swc_model, frusta=fr, show_centroid=True, point_set=ps, radius_scale=0.8)
   fig.show()

   # Interactive radius slider (0..1)
   fig_slider = plot_model(swc_model=swc_model, frusta=fr, slider=True, min_scale=0.0, max_scale=1.0, steps=21)
   fig_slider.show()

See the :doc:`examples` and :doc:`api` pages for details.