It turns out that strongly typing the axs
variable is not straightforward at all and requires to understant well how to type np.ndarray
.
See this question and this question for more details.
The simplest and most powerful solution is to wrap numpy.ndarray
with '
characters, in order to avoid the infamous TypeError: 'numpy._DTypeMeta' object is not subscriptable when Python tries to interpret the [] in the expression.
An example:
import matplotlib.pyplot as plt
import numpy as np
import numpy.typing as npt
import seaborn as sns
from typing import cast, Type, Sequence
import typing
sns.set()
# Some example data to display
x = np.linspace(0, 2 * np.pi, 400)
y = np.sin(x ** 2)
fig, axs = plt.subplots(
2, 2,
figsize=(12, 10) # set graph size
)
# typechecking operation
NDArrayOfAxes: typing.TypeAlias = 'np.ndarray[Sequence[Sequence[plt.Axes]], np.dtype[np.object_]]'
axs = cast(np.ndarray, axs)
axs[0, 0].plot(x, y)
axs[0, 0].set_title("main")
axs[1, 0].plot(x, y**2)
axs[1, 0].set_title("shares x with main")
axs[1, 0].sharex(axs[0, 0])
axs[0, 1].plot(x + 1, y + 1)
axs[0, 1].set_title("unrelated")
axs[1, 1].plot(x + 2, y + 2)
axs[1, 1].set_title("also unrelated")
fig.tight_layout()
Which is well detected by Pylance and runs correctly:
