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matplotlib & pandas
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Python/matplotlab/gallery/style_sheets/style_sheets_reference.md
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Python/matplotlab/gallery/style_sheets/style_sheets_reference.md
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# 样式表参考
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此脚本演示了一组常见示例图上的不同可用样式表：散点图，图像，条形图，面片，线图和直方图，
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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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# Fixing random state for reproducibility
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np.random.seed(19680801)
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def plot_scatter(ax, prng, nb_samples=100):
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"""Scatter plot.
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"""
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for mu, sigma, marker in [(-.5, 0.75, 'o'), (0.75, 1., 's')]:
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x, y = prng.normal(loc=mu, scale=sigma, size=(2, nb_samples))
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ax.plot(x, y, ls='none', marker=marker)
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ax.set_xlabel('X-label')
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return ax
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def plot_colored_sinusoidal_lines(ax):
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"""Plot sinusoidal lines with colors following the style color cycle.
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"""
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L = 2 * np.pi
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x = np.linspace(0, L)
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nb_colors = len(plt.rcParams['axes.prop_cycle'])
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shift = np.linspace(0, L, nb_colors, endpoint=False)
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for s in shift:
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ax.plot(x, np.sin(x + s), '-')
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ax.set_xlim([x[0], x[-1]])
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return ax
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def plot_bar_graphs(ax, prng, min_value=5, max_value=25, nb_samples=5):
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"""Plot two bar graphs side by side, with letters as x-tick labels.
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"""
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x = np.arange(nb_samples)
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ya, yb = prng.randint(min_value, max_value, size=(2, nb_samples))
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width = 0.25
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ax.bar(x, ya, width)
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ax.bar(x + width, yb, width, color='C2')
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ax.set_xticks(x + width)
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ax.set_xticklabels(['a', 'b', 'c', 'd', 'e'])
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return ax
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def plot_colored_circles(ax, prng, nb_samples=15):
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"""Plot circle patches.
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NB: draws a fixed amount of samples, rather than using the length of
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the color cycle, because different styles may have different numbers
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of colors.
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"""
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for sty_dict, j in zip(plt.rcParams['axes.prop_cycle'], range(nb_samples)):
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ax.add_patch(plt.Circle(prng.normal(scale=3, size=2),
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radius=1.0, color=sty_dict['color']))
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# Force the limits to be the same across the styles (because different
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# styles may have different numbers of available colors).
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ax.set_xlim([-4, 8])
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ax.set_ylim([-5, 6])
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ax.set_aspect('equal', adjustable='box') # to plot circles as circles
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return ax
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def plot_image_and_patch(ax, prng, size=(20, 20)):
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"""Plot an image with random values and superimpose a circular patch.
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"""
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values = prng.random_sample(size=size)
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ax.imshow(values, interpolation='none')
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c = plt.Circle((5, 5), radius=5, label='patch')
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ax.add_patch(c)
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# Remove ticks
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ax.set_xticks([])
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ax.set_yticks([])
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def plot_histograms(ax, prng, nb_samples=10000):
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"""Plot 4 histograms and a text annotation.
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"""
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params = ((10, 10), (4, 12), (50, 12), (6, 55))
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for a, b in params:
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values = prng.beta(a, b, size=nb_samples)
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ax.hist(values, histtype="stepfilled", bins=30,
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alpha=0.8, density=True)
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# Add a small annotation.
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ax.annotate('Annotation', xy=(0.25, 4.25), xycoords='data',
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xytext=(0.9, 0.9), textcoords='axes fraction',
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va="top", ha="right",
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bbox=dict(boxstyle="round", alpha=0.2),
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arrowprops=dict(
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arrowstyle="->",
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connectionstyle="angle,angleA=-95,angleB=35,rad=10"),
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)
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return ax
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def plot_figure(style_label=""):
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"""Setup and plot the demonstration figure with a given style.
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"""
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# Use a dedicated RandomState instance to draw the same "random" values
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# across the different figures.
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prng = np.random.RandomState(96917002)
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# Tweak the figure size to be better suited for a row of numerous plots:
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# double the width and halve the height. NB: use relative changes because
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# some styles may have a figure size different from the default one.
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(fig_width, fig_height) = plt.rcParams['figure.figsize']
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fig_size = [fig_width * 2, fig_height / 2]
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fig, axes = plt.subplots(ncols=6, nrows=1, num=style_label,
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figsize=fig_size, squeeze=True)
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axes[0].set_ylabel(style_label)
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plot_scatter(axes[0], prng)
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plot_image_and_patch(axes[1], prng)
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plot_bar_graphs(axes[2], prng)
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plot_colored_circles(axes[3], prng)
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plot_colored_sinusoidal_lines(axes[4])
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plot_histograms(axes[5], prng)
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fig.tight_layout()
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return fig
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if __name__ == "__main__":
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# Setup a list of all available styles, in alphabetical order but
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# the `default` and `classic` ones, which will be forced resp. in
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# first and second position.
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style_list = ['default', 'classic'] + sorted(
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style for style in plt.style.available if style != 'classic')
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# Plot a demonstration figure for every available style sheet.
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for style_label in style_list:
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with plt.style.context(style_label):
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fig = plot_figure(style_label=style_label)
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plt.show()
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```
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脚本的总运行时间：（0分5.216秒）
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## 下载这个示例
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- [下载python源码: style_sheets_reference.py](https://matplotlib.org/_downloads/style_sheets_reference.py)
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- [下载Jupyter notebook: style_sheets_reference.ipynb](https://matplotlib.org/_downloads/style_sheets_reference.ipynb)
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