8000 FIX: new plot · matplotlib/matplotlib@d29f0d5 · GitHub
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FIX: new plot
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doc/users/index.rst

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@@ -13,26 +13,38 @@ User guide
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.. plot::
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x = np.linspace(0, 2, 100) # Sample data.
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rng = np.random.default_rng(seed=19680808)
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x = np.linspace(0, 4, 1000) # Sample data.
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y = rng.normal(size=len(x)) * 1.5 + x**2 + np.cumsum(rng.normal(size=len(x))) / 6
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x = x[::10]
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y = y[::10]
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fig, ax = plt.subplots(figsize=(5, 2.7), layout='constrained')
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ax.scatter(x, np.random.randn(len(x)) + x**2,
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s=13 * np.random.rand(len(x)), c=np.random.randn(len(x)),
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label='noisy data')
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ax.plot(x, x, label='linear') # Plot some data on the axes.
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ax.plot(x, x**2, label='quadratic') # Plot more data on the axes...
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ax.plot(x, x**3, label='cubic') # ... and some more.
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ax.set_xlabel('x label') # Add an x-label to the axes.
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ax.set_ylabel('y label') # Add a y-label to the axes.
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ax.set_title("Simple plot") # Add a title to the axes.
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ax.legend() # Add a legend.
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ax.plot(x, x**2, label='underlying data', linewidth=4, alpha=0.6, color='k')
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ax.scatter(x, y, s=13 * rng.random(size=len(x)), c=rng.normal(size=len(x)),
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label='noisy data')
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# p = np.polyfit(x, y, deg=1)
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# print(p)
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p = np.array([ 3.81283983, -2.00111268])
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out = np.polyval(p, x)
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ax.plot(x, out, label='linear fit') # Plot some data on the axes.
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# p = np.polyfit(x, y, deg=2)
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# print(p)
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p = np.array([ 1.18076933, -0.86768725, 1.05989268])
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out = np.polyval(p, x)
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ax.plot(x, out, label='quadratic fit')
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ax.set_xlabel('x label')
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ax.set_ylabel('y label')
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ax.set_title("Simple plot")
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ax.legend()
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.. toctree::
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:maxdepth: 1
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getting_started/index.rst
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installing/index.rst
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faq/index.rst
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FAQ: How-to and troubleshooting <faq/index.rst>
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.. grid-item-card:: Users guide
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:padding: 2

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