matplotlib 中的半小提琴图
Half violin plot in matplotlib
最近 matplotlib 添加了对 violin plot. What I want to do is half-violin plot as here 的原生支持。我想可以通过更改函数返回的 body
来完成。您知道如何使用 matplotlib 中的新函数绘制示例中的半小提琴图吗?
data1 = (np.random.normal(0, 1, size=10000), np.random.normal(0, 2, size=10000))
data2 = (np.random.normal(1, 1, size=10000), np.random.normal(1, 2, size=10000))
fig, ax = plt.subplots(figsize=(18, 7))
v1 = ax.violinplot(data1, points=100, positions=np.arange(0, len(data1)),
showmeans=False, showextrema=False, showmedians=False)
for b in v1['bodies']:
# get the center
m = np.mean(b.get_paths()[0].vertices[:, 0])
# modify the paths to not go further right than the center
b.get_paths()[0].vertices[:, 0] = np.clip(b.get_paths()[0].vertices[:, 0], -np.inf, m)
b.set_color('r')
v2 = ax.violinplot(data2, points=100, positions=np.arange(0, len(data2)),
showmeans=False, showextrema=False, showmedians=False)
for b in v2['bodies']:
# get the center
m = np.mean(b.get_paths()[0].vertices[:, 0])
# modify the paths to not go further left than the center
b.get_paths()[0].vertices[:, 0] = np.clip(b.get_paths()[0].vertices[:, 0], m, np.inf)
b.set_color('b')
ax.legend([v1['bodies'][0],v2['bodies'][0]],['data1', 'data2'])
最近 matplotlib 添加了对 violin plot. What I want to do is half-violin plot as here 的原生支持。我想可以通过更改函数返回的 body
来完成。您知道如何使用 matplotlib 中的新函数绘制示例中的半小提琴图吗?
data1 = (np.random.normal(0, 1, size=10000), np.random.normal(0, 2, size=10000))
data2 = (np.random.normal(1, 1, size=10000), np.random.normal(1, 2, size=10000))
fig, ax = plt.subplots(figsize=(18, 7))
v1 = ax.violinplot(data1, points=100, positions=np.arange(0, len(data1)),
showmeans=False, showextrema=False, showmedians=False)
for b in v1['bodies']:
# get the center
m = np.mean(b.get_paths()[0].vertices[:, 0])
# modify the paths to not go further right than the center
b.get_paths()[0].vertices[:, 0] = np.clip(b.get_paths()[0].vertices[:, 0], -np.inf, m)
b.set_color('r')
v2 = ax.violinplot(data2, points=100, positions=np.arange(0, len(data2)),
showmeans=False, showextrema=False, showmedians=False)
for b in v2['bodies']:
# get the center
m = np.mean(b.get_paths()[0].vertices[:, 0])
# modify the paths to not go further left than the center
b.get_paths()[0].vertices[:, 0] = np.clip(b.get_paths()[0].vertices[:, 0], m, np.inf)
b.set_color('b')
ax.legend([v1['bodies'][0],v2['bodies'][0]],['data1', 'data2'])