您可以跟踪查看过的标签:
import pylab as plt
xs = [1, 2, 1, 4, 3, 2]
ys = [1, 3, 2, 2, 3, 1]
labels = [1, 1, 0, 2, 1, 3]
label_dict = {0: 'r', 1: 'k', 2: 'b', 3: 'g'}
legend_dict = {0: 'foo', 1: 'bar', 2: 'baz', 3: 'biff'}
seen = set()
for x, y, label in zip(xs, ys, labels):
if label not in seen:
plt.scatter(x, y, c=label_dict.get(label), label=legend_dict.get(label))
else:
plt.scatter(x, y, c=label_dict.get(label))
seen.add(label)
plt.legend()
plt.show()
如果您愿意,可以将 if/else 子句压缩为 1 行:
seen = set()
for x, y, label in zip(xs, ys, labels):
plt.scatter(x, y, c=label_dict.get(label), label=legend_dict.get(label) if label not in seen else None)
seen.add(label)
我认为我个人更愿意将数据分组。换句话说,我可能会将具有相同标签的所有数据存储在一起,然后您只需为plot
每种标签类型发出一个命令:
import numpy as np
import pylab as plt
xs = [1, 2, 1, 4, 3, 2]
ys = [1, 3, 2, 2, 3, 1]
labels = [1, 1, 0, 2, 1, 3]
xs = np.array(xs)
ys = np.array(ys)
labels = np.array(labels)
labels_masks =( (x,(labels == x)) for x in set(labels))
data_dict = dict( (lbl,(xs[mask],ys[mask])) for lbl,mask in labels_masks )
label_dict = {0: 'r', 1: 'k', 2: 'b', 3: 'g'}
legend_dict = {0: 'foo', 1: 'bar', 2: 'baz', 3: 'biff'}
for label,data in data_dict.items():
x,y = data
plt.scatter(x,y,c=label_dict.get(label),label=legend_dict.get(label))
plt.legend()
plt.show()