lets_plot.sampling_vertex_vw

lets_plot.sampling_vertex_vw(n)

Simplify a polyline using the Visvalingam-Whyatt algorithm.

Parameters

nint

Number of items to return.

Returns

FeatureSpec

Vertices sample specification.

Notes

Vertex sampling is designed for polygon simplification.

Examples

import numpy as np
from scipy.stats import multivariate_normal
from lets_plot import *
LetsPlot.setup_html()
np.random.seed(42)
n = 300
x = np.linspace(-1, 1, n)
y = np.linspace(-1, 1, n)
X, Y = np.meshgrid(x, y)
mean = np.zeros(2)
cov = [[1, .5],
       [.5, 1]]
rv = multivariate_normal(mean, cov)
Z = rv.pdf(np.dstack((X, Y)))
data = {'x': X.flatten(), 'y': Y.flatten(), 'z': Z.flatten()}
ggplot(data, aes(x='x', y='y', z='z')) + \
    geom_contour(sampling=sampling_vertex_vw(150))