Matplotlib重绘文本变换效果及庞尼特方图坐标轴标签旋转问题

transData接口说明 #

Axes.transData是Matplotlib官方公开的坐标变换对象，核心功能是实现数据坐标到画布显示坐标的映射，配套的transform()方法可以将输入的数据坐标点转换为对应的画布像素坐标，相关说明可以在Matplotlib官方文档的变换教程章节查询。

需求实现代码 #

你需要实现的-90度旋转轴标签、侧边展示性别标签、底部标签在右侧重复展示的需求，调整原有代码的文本位置和变换参数即可，完整可运行代码如下：

import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
from matplotlib.patches import Rectangle

plt.close("all")
fig, ax0 = plt.subplots(1, 1, figsize=(8, 8))

dim = 1000
tl_margin = 75
br_margin = 50
tau = 0.90
rho = 0.60

# 矩形区域配置
rect_positions = {
    "ffv": {
        "anchor": (0., 0.),
        "height": rho * tau * dim,
        "width": rho * tau * dim,
        "color": "#ff00ff",
        "alpha": 0.6
    },
    "ffh": {
        "anchor": (rho * tau * dim, rho * tau * dim),
        "height": rho * (1 - tau) * dim,
        "width": rho * (1 - tau) * dim,
        "color": "#ffff00",
        "alpha": 0.6
    },
    "mmh": {
        "anchor": (rho * dim + (1 - rho) * tau * dim, rho * dim + (1 - rho) * tau * dim),
        "width": (1 - rho) * (1 - tau) * dim,
        "height": (1 - rho) * (1 - tau) * dim,
        "color": "#0000ff",
        "alpha": 0.6
    }
}

# 标签位置配置
label_positions = {
    "female": {
        "sex": {"pos": rho * dim / 2, "symbol": "female"},
        "transmission": {
            "vertical": {"pos": rho * tau * dim / 2, "symbol": "v"},
            "horizontal": {"pos": rho * tau * dim + rho * (1 - tau) * dim / 2, "symbol": "h"}
        }
    },
    "male": {
        "sex": {"pos": rho * dim + (1 - rho) * dim / 2, "symbol": "male"},
        "transmission": {
            "vertical": {"pos": rho * dim + (1 - rho) * tau * dim / 2, "symbol": "v"},
            "horizontal": {"pos": rho * dim + (1 - rho) * tau * dim + (1 - tau) * (1 - rho) * dim / 2, "symbol": "h"}
        }
    }
}

# 坐标轴配置
ax0.set_xlim(-tl_margin, dim + br_margin)
ax0.set_ylim(-br_margin, dim + tl_margin)
ax0.set_aspect(1)
ax0.set_xticks(())
ax0.set_yticks(())

# 绘制边框
ax0.hlines((0, dim), 0, dim)
ax0.vlines((0, dim), 0, dim)

# 绘制功能区块
for value in rect_positions.values():
    ax0.add_patch(Rectangle(
        value["anchor"], value["height"], value["width"],
        color=value["color"], alpha=value["alpha"]
    ))

# 绘制性别比例分割线
ax0.hlines(rho * dim, -tl_margin, dim + br_margin, color="black", linestyle="--")
ax0.vlines(rho * dim, -br_margin, dim + tl_margin, color="black", linestyle="--")

# 绘制传播模式分割线
ax0.hlines(
    (tau * rho * dim, rho * dim + tau * (1 - rho) * dim),
    0, dim + br_margin, color="black"
)
ax0.vlines(
    (tau * rho * dim, rho * dim + tau * (1 - rho) * dim),
    -br_margin, dim, color="black"
)

label_offset = 25
# 顶部性别标签（水平）
for sex_label in label_positions.values():
    ax0.text(
        sex_label["sex"]["pos"], dim + label_offset, sex_label["sex"]["symbol"],
        va="center", ha="center", color="black"
    )

# 左侧性别标签（-90度旋转）
left_rotate = ax0.transData + Affine2D().rotate_deg(-90)
for sex_label in label_positions.values():
    ax0.text(
        -label_offset, sex_label["sex"]["pos"], sex_label["sex"]["symbol"],
        va="center", ha="center", color="black", transform=left_rotate
    )

# 底部传播模式标签（水平）
for sex_label in label_positions.values():
    for symbol in sex_label["transmission"].values():
        ax0.text(
            symbol["pos"], -label_offset, symbol["symbol"],
            va="center", ha="center", color="black"
        )

# 右侧传播模式标签（-90度旋转）
right_rotate = ax0.transData + Affine2D().rotate_deg(-90)
for sex_label in label_positions.values():
    for symbol in sex_label["transmission"].values():
        ax0.text(
            dim + label_offset, symbol["pos"], symbol["symbol"],
            va="center", ha="center", color="black", transform=right_rotate
        )

plt.show()

运行后得到的效果如下：

内容的提问来源于stack exchange，提问作者mnosefish