如何用python對(duì)生成的map圖進(jìn)行上色呢？

前幾期，有朋友讓我用python將cp的測(cè)試數(shù)據(jù)轉(zhuǎn)化為map

但是，他又想把特定的測(cè)量數(shù)據(jù)轉(zhuǎn)化為map圖后，進(jìn)行上色，即不同的測(cè)試數(shù)據(jù)能夠呈現(xiàn)不同的顏色，以便于直觀的觀察其趨勢(shì)。

數(shù)據(jù)樣式：

左邊列是序號(hào)，中間列是XY,X-0016Y0079表示的是（X,Y）坐標(biāo)為（16，79），最右行是測(cè)試數(shù)據(jù)。序號(hào)最大值為13278，即這個(gè)wafer有13278粒完成測(cè)試，得到了cp的測(cè)試數(shù)據(jù)。

我的思路：

1，將現(xiàn)有數(shù)據(jù)按照坐標(biāo)，轉(zhuǎn)化為map圖，并將測(cè)試數(shù)值一一對(duì)應(yīng)填入map圖中。

2，有時(shí)測(cè)試標(biāo)準(zhǔn)是不一樣的，所以可以手動(dòng)設(shè)置標(biāo)準(zhǔn)值，這個(gè)在運(yùn)行程序時(shí)能夠彈出對(duì)話框，讓使用者能夠隨意更改標(biāo)準(zhǔn)。低于標(biāo)準(zhǔn)值的測(cè)量值單元格呈現(xiàn)淺紅色到紅色的漸變，高于標(biāo)準(zhǔn)值的測(cè)量值呈現(xiàn)淺綠到紫色的漸變。

做出的效果：

1，雙擊“map上色.exe”運(yùn)行程序

2，選擇要上色的測(cè)試數(shù)據(jù)文件

3，手動(dòng)設(shè)置標(biāo)準(zhǔn)值

4，設(shè)置文件名

5，在原文件地址下輸出包含map圖的文件

6，打開文件

這樣就很直觀地看出測(cè)量值的分布圖來了。

原代碼如下，歡迎參考：

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] 區(qū)間，從極淡綠（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] 區(qū)間，從紅（255,0,0）到黃（255,255,0）
    elif -10 <= value < threshold:
        normed_value = (value + 10) / (threshold + 10)  # 正則化到 [0, 1] 區(qū)間
        r = int(222 + (241 - 222) * normed_value)  # 從 222 漸變到 241
        g = int(28 + (147 - 28) * normed_value)  # 從 28 漸變到 147
        b = int(49 + (156 - 49) * normed_value)  # 從 49 漸變到 156

    elif data_min <= value < -10:
        r, g, b = 139, 0, 0

    else:
        r, g, b = 255, 255, 255  # 默認(rèn)為白色

    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()  # 獲取整個(gè) dataframe 中的最小值
    data_max = df.max().max()  # 獲取整個(gè) 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
                # 選擇正確的顏色映射函數(shù)和參數(shù)
                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  # 從元組中解包
                    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()

審核編輯：劉清