如何统计Python matplotlib网格中包含x,y坐标点的网格数量及占比

实现方案 #

核心逻辑 #

你提到的示例总网格数48对应x轴[-960,960]划分为8段、y轴[-540,540]划分为6段的配置，我们先显式定义网格划分参数，避免matplotlib自动调整刻度导致的网格计数偏差，再通过坐标映射找到散点所属的网格，最后填充并统计即可。

完整可运行代码 #

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle

# -------------------------- 配置参数 --------------------------
# 坐标范围
X_MIN, X_MAX = -960, 960
Y_MIN, Y_MAX = -540, 540
# 网格划分数量（对应示例48总网格：8*6=48，可按需修改）
X_GRID_NUM = 8
Y_GRID_NUM = 6
# 计算每个网格的宽高
grid_width = (X_MAX - X_MIN) / X_GRID_NUM
grid_height = (Y_MAX - Y_MIN) / Y_GRID_NUM
# 散点数量
POINT_NUM = 15
# 底图路径，替换为你自己的本地路径
scene_folder = "your_image_path.png"

# -------------------------- 生成随机点+识别含点网格 --------------------------
# 固定随机种子可复现结果，不需要可以删除下一行
np.random.seed(42)
x = np.random.randint(X_MIN, X_MAX, POINT_NUM)
y = np.random.randint(Y_MIN, Y_MAX, POINT_NUM)

# 计算每个点所属的网格索引，去重得到所有含点的网格
grid_set = set()
for px, py in zip(x, y):
    # 计算x方向网格索引（从左到右0到X_GRID_NUM-1）
    x_idx = int((px - X_MIN) // grid_width)
    # 边界处理：刚好落在X_MAX的点归到最后一个网格
    x_idx = min(x_idx, X_GRID_NUM - 1)
    # 计算y方向网格索引（从下到上0到Y_GRID_NUM-1）
    y_idx = int((py - Y_MIN) // grid_height)
    y_idx = min(y_idx, Y_GRID_NUM - 1)
    grid_set.add((x_idx, y_idx))

# -------------------------- 绘图 --------------------------
fig, ax = plt.subplots(figsize=(20, 11))
# 先画底图
img = plt.imread(scene_folder)
ax.imshow(img, extent = [X_MIN, X_MAX, Y_MIN, Y_MAX], aspect='auto')

# 填充所有含点的网格为白色，透明度可按需调整
for (x_idx, y_idx) in grid_set:
    # 计算网格左下角坐标
    grid_x0 = X_MIN + x_idx * grid_width
    grid_y0 = Y_MIN + y_idx * grid_height
    # 添加白色矩形
    ax.add_patch(Rectangle((grid_x0, grid_y0), grid_width, grid_height, color='white', alpha=0.7))

# 画网格、散点
ax.grid(color='white', linestyle='--', linewidth=1)
# zorder参数保证散点在最上层，不会被白色填充盖住
ax.scatter(x, y, marker='o', color='red', alpha=0.8, zorder=10)

# 显式设置刻度，保证网格和我们定义的划分完全一致
ax.set_xticks(np.arange(X_MIN, X_MAX+1, grid_width))
ax.set_yticks(np.arange(Y_MIN, Y_MAX+1, grid_height))

plt.show()
plt.close()

# -------------------------- 统计计算 --------------------------
total_grid = X_GRID_NUM * Y_GRID_NUM
has_point_grid = len(grid_set)
ratio = has_point_grid / total_grid * 100
print(f"总网格数：{total_grid}")
print(f"含散点的网格数：{has_point_grid}")
print(f"占比：{ratio:.1f}%")

补充说明 #

• 如果需要调整网格划分数量，直接修改X_GRID_NUM和Y_GRID_NUM即可，代码会自动适配
• 白色填充的透明度可以修改Rectangle的alpha参数调整，0为完全透明，1为完全不透明

内容的提问来源于stack exchange，提问作者Phoenix