import numpy as np
import matplotlib.pyplot as plt

matrix = np.random.rand(5, 5)

fig, ax = plt.subplots()
cax = ax.matshow(matrix)

# 设置行标签
ax.set_xticks(range(5))
ax.set_xticklabels(['A', 'B', 'C', 'D', 'E'])

# 设置列标签
ax.set_yticks(range(5))
ax.set_yticklabels(['1', '2', '3', '4', '5'])

plt.show()

# 旋转x轴标签45度
ax.set_xticklabels(['A', 'B', 'C', 'D', 'E'], rotation=45)

# 旋转y轴标签
ax.set_yticklabels(['1', '2', '3', '4', '5'], rotation=90)

cbar = fig.colorbar(cax)
cbar.set_label('Value Scale')

plt.figure(figsize=(10, 8))  # 增大图形尺寸
ax.set_xticklabels(labels, rotation=45, fontsize=8)  # 旋转并减小字体

ax.set_xticks(np.arange(matrix.shape[1]))  # 明确设置x刻度位置
ax.set_yticks(np.arange(matrix.shape[0]))  # 明确设置y刻度位置

ax.grid(False)  # 关闭网格线
# 或
ax.grid(True, linestyle='--', alpha=0.5)  # 设置虚线并降低透明度

import numpy as np
import matplotlib.pyplot as plt

# 创建数据
data = np.random.rand(10, 12)
row_labels = [f'Row {i}' for i in range(1, 11)]
col_labels = [f'Col {chr(65+i)}' for i in range(12)]

# 创建图形
fig, ax = plt.subplots(figsize=(12, 8))

# 绘制矩阵
cax = ax.matshow(data, cmap='viridis')

# 设置标签
ax.set_xticks(np.arange(data.shape[1]), labels=col_labels)
ax.set_yticks(np.arange(data.shape[0]), labels=row_labels)

# 旋转x标签
plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")

# 添加颜色条
cbar = fig.colorbar(cax)
cbar.set_label('Value')

# 添加标题
ax.set_title('Matrix Visualization with Labels')

# 显示网格
ax.grid(True, linestyle=':', alpha=0.3)

plt.tight_layout()
plt.show()