这里有一种方法，基于matplotlib文档中的"Composing Custom Legends"：

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from matplotlib.lines import Line2D

# -- DATA
t = np.linspace(-5, 5, 40)

# Analytical
a1 = np.tanh(t)
a2 = -np.tanh(t) + 1

# Numerical
n1 = a1 + np.random.randn(*a1.shape) / 50
n2 = a2 + np.random.randn(*a2.shape) / 50

# -- PLOTS
fig, ax = plt.subplots()

# Colors
clr1 = "C0"
clr2 = "C1"

# Analytical solution
ax.plot(t, a1, color=clr1)
ax.plot(t, a2, color=clr2)

# Numerical solution
ax.scatter(t, n1, color=clr1)
ax.scatter(t, n2, color=clr2)

# Custom legend
# https://matplotlib.org/stable/gallery/text_labels_and_annotations/custom_legends.html

legend_elements = [
    Patch(color=clr1, label="Exp. 1"),
    Patch(color=clr2, label="Exp. 2"),
    Line2D(
        [0],
        [0],
        marker="o",
        color="k",
        lw=0,
        label="Numerical",
    ),
    Line2D(
        [0],
        [0],
        color="k",
        label="Analytical",
    ),
]
ax.legend(handles=legend_elements, ncols=2)

plt.show()