| """ |
| ========================= |
| Violin plot customization |
| ========================= |
| |
| This example demonstrates how to fully customize violin plots. The first plot |
| shows the default style by providing only the data. The second plot first |
| limits what Matplotlib draws with additional keyword arguments. Then a |
| simplified representation of a box plot is drawn on top. Lastly, the styles of |
| the artists of the violins are modified. |
| |
| For more information on violin plots, the scikit-learn docs have a great |
| section: https://scikit-learn.org/stable/modules/density.html |
| """ |
|
|
| import matplotlib.pyplot as plt |
| import numpy as np |
|
|
|
|
| def adjacent_values(vals, q1, q3): |
| upper_adjacent_value = q3 + (q3 - q1) * 1.5 |
| upper_adjacent_value = np.clip(upper_adjacent_value, q3, vals[-1]) |
|
|
| lower_adjacent_value = q1 - (q3 - q1) * 1.5 |
| lower_adjacent_value = np.clip(lower_adjacent_value, vals[0], q1) |
| return lower_adjacent_value, upper_adjacent_value |
|
|
|
|
| def set_axis_style(ax, labels): |
| ax.set_xticks(np.arange(1, len(labels) + 1), labels=labels) |
| ax.set_xlim(0.25, len(labels) + 0.75) |
| ax.set_xlabel('Sample name') |
|
|
|
|
| |
| np.random.seed(19680801) |
| data = [sorted(np.random.normal(0, std, 100)) for std in range(1, 5)] |
|
|
| fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4), sharey=True) |
|
|
| ax1.set_title('Default violin plot') |
| ax1.set_ylabel('Observed values') |
| ax1.violinplot(data) |
|
|
| ax2.set_title('Customized violin plot') |
| parts = ax2.violinplot( |
| data, showmeans=False, showmedians=False, |
| showextrema=False) |
|
|
| for pc in parts['bodies']: |
| pc.set_facecolor('#D43F3A') |
| pc.set_edgecolor('black') |
| pc.set_alpha(1) |
|
|
| quartile1, medians, quartile3 = np.percentile(data, [25, 50, 75], axis=1) |
| whiskers = np.array([ |
| adjacent_values(sorted_array, q1, q3) |
| for sorted_array, q1, q3 in zip(data, quartile1, quartile3)]) |
| whiskers_min, whiskers_max = whiskers[:, 0], whiskers[:, 1] |
|
|
| inds = np.arange(1, len(medians) + 1) |
| ax2.scatter(inds, medians, marker='o', color='white', s=30, zorder=3) |
| ax2.vlines(inds, quartile1, quartile3, color='k', linestyle='-', lw=5) |
| ax2.vlines(inds, whiskers_min, whiskers_max, color='k', linestyle='-', lw=1) |
|
|
| |
| labels = ['A', 'B', 'C', 'D'] |
| for ax in [ax1, ax2]: |
| set_axis_style(ax, labels) |
|
|
| plt.subplots_adjust(bottom=0.15, wspace=0.05) |
| plt.show() |
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