动画在matplotlib中的3d散点图

时间:2012-07-07 16:50:33

标签: python matplotlib

我正在尝试在matplotlib中获取一个散点图的三维动画,基于贴出的{2}散点图动画和here发布的三维线图。

问题来自于set_dataset_offsets无法在3D中工作,因此您应该使用set_3d_properties来处理z信息。玩它通常会窒息,但下面张贴的代码会运行。然而,透明度增加到足以使点在几帧后逐渐消失。我在这做错了什么?我希望这些点在盒子的边界内跳一段时间。即使将步长调整到非常小的尺寸也不会降低透明度。

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

FLOOR = -10
CEILING = 10

class AnimatedScatter(object):
    def __init__(self, numpoints=5):
        self.numpoints = numpoints
        self.stream = self.data_stream()
        self.angle = 0

        self.fig = plt.figure()
        self.ax = self.fig.add_subplot(111,projection = '3d')
        self.ani = animation.FuncAnimation(self.fig, self.update, interval=100, 
                                           init_func=self.setup_plot, blit=True)

    def change_angle(self):
        self.angle = (self.angle + 1)%360

    def setup_plot(self):
        x, y, z = next(self.stream)
        c = ['b', 'r', 'g', 'y', 'm']
        self.scat = self.ax.scatter(x, y, z,c=c, s=200, animated=True)

        self.ax.set_xlim3d(FLOOR, CEILING)
        self.ax.set_ylim3d(FLOOR, CEILING)
        self.ax.set_zlim3d(FLOOR, CEILING)

        return self.scat,

    def data_stream(self):
        data = np.zeros((3, self.numpoints))
        xyz = data[:3, :]
        while True:
            xyz += 2 * (np.random.random((3, self.numpoints)) - 0.5)
            yield data

    def update(self, i):
        data = next(self.stream)
        data = np.transpose(data)

        self.scat.set_offsets(data[:,:2])
        #self.scat.set_3d_properties(data)
        self.scat.set_3d_properties(data[:,2:],'z')

        self.change_angle()
        self.ax.view_init(30,self.angle)
        plt.draw()
        return self.scat,

    def show(self):
        plt.show()

if __name__ == '__main__':
    a = AnimatedScatter()
    a.show()

2 个答案:

答案 0 :(得分:6)

最后找到解决方案,这里是如何更新没有触摸颜色的点:

from mpl_toolkits.mplot3d.art3d import juggle_axes
scat._offsets3d = juggle_axes(xs, ys, zs, 'z')

这是由set_3d_properties内部完成以及重新初始化颜色

答案 1 :(得分:3)

我发现了这个更通用的解决方案: 在将数据插入集合之前,请先添加np.ma.ravel( x_data ) ...

但散点图似乎并不适用于动画;它太慢了。

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

FLOOR = -10
CEILING = 10

class AnimatedScatter(object):
    def __init__(self, numpoints=5):
        self.numpoints = numpoints
        self.stream = self.data_stream()
        self.angle = 0

        self.fig = plt.figure()
        self.ax = self.fig.add_subplot(111,projection = '3d')
        self.ani = animation.FuncAnimation(self.fig, self.update, interval=100, 
                                           init_func=self.setup_plot, blit=True)

    def change_angle(self):
        self.angle = (self.angle + 1)%360

    def setup_plot(self):
        X = next(self.stream)
        c = ['b', 'r', 'g', 'y', 'm']
        self.scat = self.ax.scatter(X[:,0], X[:,1], X[:,2] , c=c, s=200, animated=True)

        self.ax.set_xlim3d(FLOOR, CEILING)
        self.ax.set_ylim3d(FLOOR, CEILING)
        self.ax.set_zlim3d(FLOOR, CEILING)

        return self.scat,

    def data_stream(self):
        data = np.zeros(( self.numpoints , 3 ))
        xyz = data[:,:3]
        while True:
            xyz += 2 * (np.random.random(( self.numpoints,3)) - 0.5)
            yield data

    def update(self, i):
        data = next(self.stream)
        data = np.transpose(data)

        self.scat._offsets3d = ( np.ma.ravel(data[:,0]) , np.ma.ravel(data[:,0]) , np.ma.ravel(data[:,0]) )

        self.change_angle()
        self.ax.view_init(30,self.angle)
        plt.draw()
        return self.scat,

    def show(self):
        plt.show()

if __name__ == '__main__':
    a = AnimatedScatter()
    a.show()
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