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matplotlib & pandas
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Python/matplotlab/gallery/animation/random_walk.md
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Python/matplotlab/gallery/animation/random_walk.md
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# 动画3D随机游走
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```python
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import numpy as np
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import matplotlib.pyplot as plt
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import mpl_toolkits.mplot3d.axes3d as p3
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import matplotlib.animation as animation
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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def Gen_RandLine(length, dims=2):
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"""
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Create a line using a random walk algorithm
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length is the number of points for the line.
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dims is the number of dimensions the line has.
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"""
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lineData = np.empty((dims, length))
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lineData[:, 0] = np.random.rand(dims)
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for index in range(1, length):
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# scaling the random numbers by 0.1 so
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# movement is small compared to position.
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# subtraction by 0.5 is to change the range to [-0.5, 0.5]
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# to allow a line to move backwards.
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step = ((np.random.rand(dims) - 0.5) * 0.1)
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lineData[:, index] = lineData[:, index - 1] + step
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return lineData
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def update_lines(num, dataLines, lines):
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for line, data in zip(lines, dataLines):
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# NOTE: there is no .set_data() for 3 dim data...
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line.set_data(data[0:2, :num])
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line.set_3d_properties(data[2, :num])
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return lines
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# Attaching 3D axis to the figure
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fig = plt.figure()
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ax = p3.Axes3D(fig)
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# Fifty lines of random 3-D lines
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data = [Gen_RandLine(25, 3) for index in range(50)]
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# Creating fifty line objects.
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# NOTE: Can't pass empty arrays into 3d version of plot()
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lines = [ax.plot(dat[0, 0:1], dat[1, 0:1], dat[2, 0:1])[0] for dat in data]
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# Setting the axes properties
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ax.set_xlim3d([0.0, 1.0])
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ax.set_xlabel('X')
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ax.set_ylim3d([0.0, 1.0])
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ax.set_ylabel('Y')
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ax.set_zlim3d([0.0, 1.0])
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ax.set_zlabel('Z')
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ax.set_title('3D Test')
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# Creating the Animation object
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line_ani = animation.FuncAnimation(fig, update_lines, 25, fargs=(data, lines),
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interval=50, blit=False)
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plt.show()
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```
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## 下载这个示例
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- [下载python源码: random_walk.py](https://matplotlib.org/_downloads/random_walk.py)
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- [下载Jupyter notebook: random_walk.ipynb](https://matplotlib.org/_downloads/random_walk.ipynb)
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