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73 lines
2.2 KiB
Markdown
73 lines
2.2 KiB
Markdown
# 重采样数据
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下采样会降低信号的采样率或采样大小。在本教程中，当通过拖动和缩放调整打印时，将对信号进行缩减采样。
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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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# A class that will downsample the data and recompute when zoomed.
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class DataDisplayDownsampler(object):
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def __init__(self, xdata, ydata):
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self.origYData = ydata
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self.origXData = xdata
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self.max_points = 50
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self.delta = xdata[-1] - xdata[0]
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def downsample(self, xstart, xend):
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# get the points in the view range
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mask = (self.origXData > xstart) & (self.origXData < xend)
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# dilate the mask by one to catch the points just outside
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# of the view range to not truncate the line
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mask = np.convolve([1, 1], mask, mode='same').astype(bool)
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# sort out how many points to drop
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ratio = max(np.sum(mask) // self.max_points, 1)
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# mask data
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xdata = self.origXData[mask]
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ydata = self.origYData[mask]
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# downsample data
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xdata = xdata[::ratio]
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ydata = ydata[::ratio]
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print("using {} of {} visible points".format(
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len(ydata), np.sum(mask)))
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return xdata, ydata
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def update(self, ax):
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# Update the line
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lims = ax.viewLim
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if np.abs(lims.width - self.delta) > 1e-8:
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self.delta = lims.width
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xstart, xend = lims.intervalx
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self.line.set_data(*self.downsample(xstart, xend))
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ax.figure.canvas.draw_idle()
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# Create a signal
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xdata = np.linspace(16, 365, (365-16)*4)
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ydata = np.sin(2*np.pi*xdata/153) + np.cos(2*np.pi*xdata/127)
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d = DataDisplayDownsampler(xdata, ydata)
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fig, ax = plt.subplots()
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# Hook up the line
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d.line, = ax.plot(xdata, ydata, 'o-')
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ax.set_autoscale_on(False) # Otherwise, infinite loop
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# Connect for changing the view limits
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ax.callbacks.connect('xlim_changed', d.update)
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ax.set_xlim(16, 365)
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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: resample.py](https://matplotlib.org/_downloads/resample.py)
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- [下载Jupyter notebook: resample.ipynb](https://matplotlib.org/_downloads/resample.ipynb) |