电子说
前几期,有朋友让我用python将cp的测试数据转化为map
但是,他又想把特定的测量数据转化为map图后,进行上色,即不同的测试数据能够呈现不同的颜色,以便于直观的观察其趋势。
数据样式:
左边列是序号,中间列是XY,X-0016Y0079表示的是(X,Y)坐标为(16,79),最右行是测试数据。序号最大值为13278,即这个wafer有13278粒完成测试,得到了cp的测试数据。
我的思路:
1,将现有数据按照坐标,转化为map图,并将测试数值一一对应填入map图中。
2,有时测试标准是不一样的,所以可以手动设置标准值,这个在运行程序时能够弹出对话框,让使用者能够随意更改标准。低于标准值的测量值单元格呈现浅红色到红色的渐变,高于标准值的测量值呈现浅绿到紫色的渐变。
做出的效果:
1,双击“map上色.exe”运行程序
2,选择要上色的测试数据文件
3,手动设置标准值
4,设置文件名
5,在原文件地址下输出包含map图的文件
6,打开文件
这样就很直观地看出测量值的分布图来了。
原代码如下,欢迎参考:
import pandas as pd import numpy as np import matplotlib.pyplot as plt from openpyxl import Workbook from openpyxl.utils.dataframe import dataframe_to_rows from openpyxl.styles import PatternFill from tkinter.simpledialog import askfloat from tkinter import Tk from tkinter import filedialog import colorsys from tkinter.simpledialog import askstring def get_threshold(threshold_type): print(f"Getting threshold for {threshold_type}...") root = Tk() root.withdraw() if threshold_type == "IL": threshold = askfloat(f"Input {threshold_type} Threshold", f"Enter the {threshold_type} threshold:") return threshold elif threshold_type == "FC": threshold_range_str = askstring(f"Input {threshold_type} Threshold Range", f"Enter the {threshold_type} threshold range (e.g., 'min,max'):") print(f"User input for FC threshold: {threshold_range_str}") try: min_threshold, max_threshold = map(float, threshold_range_str.split(',')) return min_threshold, max_threshold except ValueError: print("Invalid input. Please enter two numbers separated by a comma.") return None root.destroy() def color_map(value, threshold, data_min, data_max): # 正常化值到 [threshold, data_max] 区间,从极淡绿(144,238,144)到紫(128,0,128) if threshold <= value <= data_max: normed_value = (value - threshold) / (data_max - threshold) r = int(144 * (1 - normed_value) + 128 * normed_value) g = int(238 * (1 - normed_value) + 0 * normed_value) b = int(144 * (1 - normed_value) + 128 * normed_value) # 正常化值到 [data_min, threshold] 区间,从红(255,0,0)到黄(255,255,0) elif -10 <= value < threshold: normed_value = (value + 10) / (threshold + 10) # 正则化到 [0, 1] 区间 r = int(222 + (241 - 222) * normed_value) # 从 222 渐变到 241 g = int(28 + (147 - 28) * normed_value) # 从 28 渐变到 147 b = int(49 + (156 - 49) * normed_value) # 从 49 渐变到 156 elif data_min <= value < -10: r, g, b = 139, 0, 0 else: r, g, b = 255, 255, 255 # 默认为白色 hex_color = 'FF' + '{:02X}{:02X}{:02X}'.format(r, g, b) return hex_color def fc_color_map(value, min_threshold, max_threshold, data_min, data_max): if min_threshold <= value <= max_threshold: normed_value = (value - min_threshold) / (max_threshold - min_threshold) hue = normed_value * 360 r, g, b = colorsys.hsv_to_rgb(hue / 360.0, 1, 1) # Here saturation and value are both set to 1 r, g, b = int(r * 255), int(g * 255), int(b * 255) hex_color = 'FF' + '{:02X}{:02X}{:02X}'.format(r, g, b) # For values outside the specified range elif value > max_threshold or value < min_threshold: r, g, b = 139, 0, 0 hex_color = 'FF' + '{:02X}{:02X}{:02X}'.format(r, g, b) else: r, g, b = 255, 255, 255 # default to white hex_color = 'FF' + '{:02X}{:02X}{:02X}'.format(r, g, b) return hex_color def save_to_excel(df, threshold, output_path, color_function): wb = Workbook() ws = wb.active data_min = df.min().min() # 获取整个 dataframe 中的最小值 data_max = df.max().max() # 获取整个 dataframe 中的最大值 for i in range(df.shape[0]): for j in range(df.shape[1]): value = df.iloc[i, j] if not pd.isna(value): cell = ws.cell(row=i + 2, column=j + 2) cell.value = value # 选择正确的颜色映射函数和参数 if color_function == color_map: fill_color = color_function(value, threshold, data_min, data_max) elif color_function == fc_color_map: min_threshold, max_threshold = threshold # 从元组中解包 fill_color = color_function(value, min_threshold, max_threshold, data_min, data_max) cell.fill = PatternFill(start_color=fill_color, end_color=fill_color, fill_type="solid") wb.save(output_path) def rgb_to_hex(rgb): return '{:02X}{:02X}{:02X}'.format(rgb[0], rgb[1], rgb[2]) def main(): print("Starting main function...") input_file = filedialog.askopenfilename(title="Select the CSV file") print(f"Selected file: {input_file}") if "il" in input_file.lower(): threshold_type = "IL" color_function = color_map threshold = get_threshold(threshold_type) else: threshold_type = "FC" color_function = fc_color_map threshold = get_threshold(threshold_type) if threshold is None: print("Invalid threshold. Exiting program.") return output_file = filedialog.asksaveasfilename(title="Save the visualization as", defaultextension=".xlsx", filetypes=[("Excel files", "*.xlsx")]) print(f"Output file: {output_file}") df = pd.read_csv(input_file) save_to_excel(df, threshold, output_file, color_function) if __name__ == "__main__":
main()
审核编辑:刘清
全部0条评论
快来发表一下你的评论吧 !