如何动画散点图 [英] How to animate a scatter plot
问题描述
我正在尝试制作散点图的动画,其中点的颜色和大小在动画的不同阶段会发生变化.对于数据,我有两个带有 x 值和 y 值的 numpy ndarray:
I'm trying to do an animation of a scatter plot where colors and size of the points changes at different stage of the animation. For data I have two numpy ndarray with an x value and y value:
data.shape = (ntime, npoint)
x.shape = (npoint)
y.shape = (npoint)
现在我想绘制一个散点图
Now I want to plot a scatter plot of the type
pylab.scatter(x,y,c=data[i,:])
并在索引 i
上创建动画.我该怎么做?
and create an animation over the index i
. How do I do this?
推荐答案
假设你有一个散点图,scat = ax.scatter(...)
,那么你可以
Suppose you have a scatter plot, scat = ax.scatter(...)
, then you can
改变位置
scat.set_offsets(array)
其中 array
是一个 N x 2
形状的 x 和 y 坐标数组.
where array
is a N x 2
shaped array of x and y coordinates.
改变尺寸
scat.set_sizes(array)
其中 array
是以点为单位的一维数组.
where array
is a 1D array of sizes in points.
改变颜色
scat.set_array(array)
其中 array
是将被颜色映射的值的一维数组.
where array
is a 1D array of values which will be colormapped.
这是一个使用动画模块的简单示例.
它比实际需要的稍微复杂一些,但这应该为您提供一个框架来做更有趣的事情.
Here's a quick example using the animation module.
It's slightly more complex than it has to be, but this should give you a framework to do fancier things.
(代码于 2019 年 4 月编辑以与当前版本兼容.对于旧代码,请参阅修订历史)
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
class AnimatedScatter(object):
"""An animated scatter plot using matplotlib.animations.FuncAnimation."""
def __init__(self, numpoints=50):
self.numpoints = numpoints
self.stream = self.data_stream()
# Setup the figure and axes...
self.fig, self.ax = plt.subplots()
# Then setup FuncAnimation.
self.ani = animation.FuncAnimation(self.fig, self.update, interval=5,
init_func=self.setup_plot, blit=True)
def setup_plot(self):
"""Initial drawing of the scatter plot."""
x, y, s, c = next(self.stream).T
self.scat = self.ax.scatter(x, y, c=c, s=s, vmin=0, vmax=1,
cmap="jet", edgecolor="k")
self.ax.axis([-10, 10, -10, 10])
# For FuncAnimation's sake, we need to return the artist we'll be using
# Note that it expects a sequence of artists, thus the trailing comma.
return self.scat,
def data_stream(self):
"""Generate a random walk (brownian motion). Data is scaled to produce
a soft "flickering" effect."""
xy = (np.random.random((self.numpoints, 2))-0.5)*10
s, c = np.random.random((self.numpoints, 2)).T
while True:
xy += 0.03 * (np.random.random((self.numpoints, 2)) - 0.5)
s += 0.05 * (np.random.random(self.numpoints) - 0.5)
c += 0.02 * (np.random.random(self.numpoints) - 0.5)
yield np.c_[xy[:,0], xy[:,1], s, c]
def update(self, i):
"""Update the scatter plot."""
data = next(self.stream)
# Set x and y data...
self.scat.set_offsets(data[:, :2])
# Set sizes...
self.scat.set_sizes(300 * abs(data[:, 2])**1.5 + 100)
# Set colors..
self.scat.set_array(data[:, 3])
# We need to return the updated artist for FuncAnimation to draw..
# Note that it expects a sequence of artists, thus the trailing comma.
return self.scat,
if __name__ == '__main__':
a = AnimatedScatter()
plt.show()
如果您使用的是 OSX 并使用 OSX 后端,则需要将 FuncAnimation
中的 blit=True
更改为 blit=False
代码> 初始化如下.OSX 后端不完全支持块传输.性能会受到影响,但该示例应该可以在禁用 blitting 的 OSX 上正确运行.
If you're on OSX and using the OSX backend, you'll need to change blit=True
to blit=False
in the FuncAnimation
initialization below. The OSX backend doesn't fully support blitting. The performance will suffer, but the example should run correctly on OSX with blitting disabled.
对于一个简单的例子,它只是更新颜色,看看以下内容:
For a simpler example, which just updates the colors, have a look at the following:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
def main():
numframes = 100
numpoints = 10
color_data = np.random.random((numframes, numpoints))
x, y, c = np.random.random((3, numpoints))
fig = plt.figure()
scat = plt.scatter(x, y, c=c, s=100)
ani = animation.FuncAnimation(fig, update_plot, frames=range(numframes),
fargs=(color_data, scat))
plt.show()
def update_plot(i, data, scat):
scat.set_array(data[i])
return scat,
main()
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