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82 lines
2.1 KiB
Markdown
82 lines
2.1 KiB
Markdown
# Pyplot 比例尺(Scales)
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在不同的比例上创建图。这里显示了线性，对数，对称对数和对数标度。有关更多示例，请参阅库的[“缩放”](https://matplotlib.org/gallery/index.html#scales-examples)部分。
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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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from matplotlib.ticker import NullFormatter # useful for `logit` scale
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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# make up some data in the interval ]0, 1[
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y = np.random.normal(loc=0.5, scale=0.4, size=1000)
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y = y[(y > 0) & (y < 1)]
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y.sort()
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x = np.arange(len(y))
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# plot with various axes scales
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plt.figure(1)
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# linear
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plt.subplot(221)
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plt.plot(x, y)
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plt.yscale('linear')
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plt.title('linear')
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plt.grid(True)
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# log
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plt.subplot(222)
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plt.plot(x, y)
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plt.yscale('log')
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plt.title('log')
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plt.grid(True)
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# symmetric log
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plt.subplot(223)
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plt.plot(x, y - y.mean())
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plt.yscale('symlog', linthreshy=0.01)
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plt.title('symlog')
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plt.grid(True)
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# logit
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plt.subplot(224)
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plt.plot(x, y)
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plt.yscale('logit')
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plt.title('logit')
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plt.grid(True)
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# Format the minor tick labels of the y-axis into empty strings with
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# `NullFormatter`, to avoid cumbering the axis with too many labels.
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plt.gca().yaxis.set_minor_formatter(NullFormatter())
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# Adjust the subplot layout, because the logit one may take more space
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# than usual, due to y-tick labels like "1 - 10^{-3}"
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plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25,
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wspace=0.35)
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plt.show()
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```
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## 参考
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此示例中显示了以下函数，方法，类和模块的使用：
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```python
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import matplotlib
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matplotlib.pyplot.subplot
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matplotlib.pyplot.subplots_adjust
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matplotlib.pyplot.gca
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matplotlib.pyplot.yscale
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matplotlib.ticker.NullFormatter
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matplotlib.axis.Axis.set_minor_formatter
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```
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## 下载这个示例
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- [下载python源码: pyplot_scales.py](https://matplotlib.org/_downloads/pyplot_scales.py)
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- [下载Jupyter notebook: pyplot_scales.ipynb](https://matplotlib.org/_downloads/pyplot_scales.ipynb) |