# -*- coding: utf-8 -*-
"""
=============================
Surfaces around point clouds
=============================

The `surface` kwarg overlays a smooth, lit surface over each dataset's
convex hull: a filled outline for 2D data, or a shaded, Taubin-smoothed
3D "blob" for 3D data (GH #109). Pass `surface=True` for sensible
defaults, or a dict to customize the alpha, color, lighting, and amount
of smoothing.
"""

# Code source: Contextual Dynamics Laboratory
# License: MIT

import numpy as np

import hypertools as hyp

rng = np.random.default_rng(0)

# two blobby 3D point clouds
blob_a = rng.standard_normal((300, 3)) * [1.0, 0.6, 0.8]
blob_b = rng.standard_normal((300, 3)) * [0.7, 1.0, 0.6] + [3.5, 0, 0]

# default surfaces: hyp.plot infers sensible alpha/lighting/smoothing
hyp.plot([blob_a, blob_b], '.', surface=True)

###############################################################################
# The dict API gives per-call control over the surface's look: `alpha`
# (transparency), `color` (overrides the dataset's own drawn color),
# `lighting` (a dict of Blinn-Phong shading terms), and `smoothing`
# (rounds of Taubin mesh smoothing -- higher looks glossier but is
# slower to compute).

custom_surface = {
    'alpha': 0.5,
    'color': '#2E86AB',
    'lighting': {'ambient': 0.6, 'diffuse': 0.5, 'specular': 0.4},
    'smoothing': 2,
}

hyp.plot([blob_a, blob_b], '.', surface=custom_surface)