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# -*- coding: utf-8 -*-
# Copyright (c) Vispy Development Team. All Rights Reserved.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
"""
Plot clusters of data points and a graph of connections
"""
from vispy import app, scene, color
import numpy as np
# Initialize arrays for position, color, edges, and types for each point in
# the graph.
npts = 400
nedges = 900
ngroups = 7
np.random.seed(127396)
pos = np.empty((npts, 2), dtype='float32')
colors = np.empty((npts, 3), dtype='float32')
edges = np.empty((nedges, 2), dtype='uint32')
types = np.empty(npts, dtype=int)
# Assign random starting positions
pos[:] = np.random.normal(size=pos.shape, scale=4.)
# Assign each point to a group
grpsize = npts // ngroups
ptr = 0
typ = 0
while ptr < npts:
size = np.random.random() * grpsize + grpsize // 2
types[int(ptr):int(ptr+size)] = typ
typ += 1
ptr = ptr + size
# Randomly select connections, with higher connection probability between
# points in the same group
conn = []
connset = set()
while len(conn) < nedges:
i, j = np.random.randint(npts, size=2)
if i == j:
continue
p = 0.7 if types[i] == types[j] else 0.01
if np.random.random() < p:
if (i, j) in connset:
continue
connset.add((i, j))
connset.add((j, i))
conn.append([i, j])
edges[:] = conn
# Assign colors to each point based on its type
cmap = color.get_colormap('cubehelix')
typ_colors = np.array([cmap.map(x)[0, :3] for x in np.linspace(0.2, 0.8, typ)])
colors[:] = typ_colors[types]
# Add some RGB noise and clip
colors *= 1.1 ** np.random.normal(size=colors.shape)
colors = np.clip(colors, 0, 1)
# Display the data
canvas = scene.SceneCanvas(keys='interactive', show=True)
view = canvas.central_widget.add_view()
view.camera = 'panzoom'
view.camera.aspect = 1
lines = scene.Line(pos=pos, connect=edges, antialias=False, method='gl',
color=(1, 1, 1, 0.2), parent=view.scene)
markers = scene.Markers(pos=pos, face_color=colors, symbol='o',
parent=view.scene)
view.camera.set_range()
i = 1
def update(ev):
global pos, edges, lines, markers, view, force, dist, i
dx = np.empty((npts, npts, 2), dtype='float32')
dx[:] = pos[:, np.newaxis, :]
dx -= pos[np.newaxis, :, :]
dist = (dx**2).sum(axis=2)**0.5
dist[dist == 0] = 1.
ndx = dx / dist[..., np.newaxis]
force = np.zeros((npts, npts, 2), dtype='float32')
# all points push away from each other
force -= 0.1 * ndx / dist[..., np.newaxis]**2
# connected points pull toward each other
# pulsed force helps to settle faster:
s = 0.1
# s = 0.05 * 5 ** (np.sin(i/20.) / (i/100.))
# s = 0.05 + 1 * 0.99 ** i
mask = np.zeros((npts, npts, 1), dtype='float32')
mask[edges[:, 0], edges[:, 1]] = s
mask[edges[:, 1], edges[:, 0]] = s
force += dx * dist[..., np.newaxis] * mask
# points do not exert force on themselves
force[np.arange(npts), np.arange(npts)] = 0
force = force.sum(axis=0)
pos += np.clip(force, -3, 3) * 0.09
lines.set_data(pos=pos)
markers.set_data(pos=pos, face_color=colors)
i += 1
timer = app.Timer(interval=0, connect=update, start=True)
if __name__ == '__main__':
app.run()
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