lets_plot.sampling_vertex_dp

lets_plot.sampling_vertex_dp(n)

Simplify a polyline using the Douglas-Peucker algorithm.

Parameters

n (int) – Number of items to return.

Returns

Vertices sample specification.

Return type

FeatureSpec

Note

Vertex sampling is designed for polygon simplification.

Examples

 1import numpy as np
 2from scipy.stats import multivariate_normal
 3from lets_plot import *
 4LetsPlot.setup_html()
 5np.random.seed(42)
 6n = 300
 7x = np.linspace(-1, 1, n)
 8y = np.linspace(-1, 1, n)
 9X, Y = np.meshgrid(x, y)
10mean = np.zeros(2)
11cov = [[1, .5],
12       [.5, 1]]
13rv = multivariate_normal(mean, cov)
14Z = rv.pdf(np.dstack((X, Y)))
15data = {'x': X.flatten(), 'y': Y.flatten(), 'z': Z.flatten()}
16ggplot(data, aes(x='x', y='y', z='z')) + \
17    geom_contour(sampling=sampling_vertex_dp(100))