80 lines
2.4 KiB
Python
80 lines
2.4 KiB
Python
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import pandas as pd
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import matplotlib.pyplot as plt
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from matplotlib.patches import Rectangle
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def col(char):
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return ord(char) - ord('A') + 0
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# 读取Excel文件，指定表格路径
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file_path = '预埋件位置.xlsx'
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# 使用pandas读取Excel
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df = pd.read_excel(file_path, sheet_name='测量结果') # 根据你的Excel表格来设置sheet_name
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# 打印列名
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print("DataFrame 列名:", df.columns)
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# 创建一个图形和坐标轴
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fig, ax = plt.subplots()
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# 初始化边界变量
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x_min, x_max = float('inf'), float('-inf')
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y_min, y_max = float('inf'), float('-inf')
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x_max_original = 0
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for index, row in df.iloc[2:30].iterrows():
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original_x = row[col('K')] - row[col('D')] / 2
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if(original_x > x_max_original):
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x_max_original = original_x
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for index, row in df.iloc[2:30].iterrows():
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# 打印B列和C列的值
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print(f"行 {index+2} -> A列-编号: {row[col('A')]}, D列-测量宽度: {row[col('D')]}, E列-测量高度: {row[col('E')]}，K列-测量中心x: {row[col('K')]}, L列-测量中心y: {row[col('L')]}")
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# 转换x坐标
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x_original = row[col('K')]
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x = x_max_original - x_original - row[col('D')] / 2
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y = row[col('L')] - row[col('E')] / 2
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# 更新边界
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x_min = min(x_min, x)
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x_max = max(x_max, x + row[col('D')])
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y_min = min(y_min, y)
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y_max = max(y_max, y + row[col('E')])
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# 绘制矩形
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rect = Rectangle((x, y), row[col('D')], row[col('E')], linewidth=1, edgecolor='r', facecolor='none')
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ax.add_patch(rect)
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# 在矩形中心绘制编号（A列）
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ax.text(
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x + row[col('D')] / 2, y + row[col('E')] / 2, str(row[col('A')]),
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ha='center', va='center',
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fontsize=12, color='blue' # 编号字体大小为12，颜色为蓝色
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)
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# 在矩形上边绘制宽度（D列）
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ax.text(
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x + row[col('D')] / 2, y + row[col('E')], str(row[col('D')]),
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ha='center', va='bottom',
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fontsize=6, color='green' # 宽度字体大小为10，颜色为绿色
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)
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# 在矩形右边绘制高度（E列）
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ax.text(
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x + row[col('D')], y + row[col('E')] / 2, str(row[col('E')]),
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ha='left', va='center',
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fontsize=6, color='red' # 高度字体大小为10，颜色为红色
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)
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# 设置坐标轴的范围，外扩100左右
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ax.set_xlim(x_min, x_max ) # 留出一些边距
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ax.set_ylim(y_min, y_max ) # 留出一些边距
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# 设置坐标轴的比例
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ax.set_aspect('equal')
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# 显示图形
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plt.show()
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