3103 lines
2.6 MiB
Plaintext
3103 lines
2.6 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "ad8424f1-4fd8-4f68-9557-f560d5a28e4b",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import sys\n",
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"import os\n",
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"sys.path.append('..')\n",
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"from QX8800SP_DA import *\n",
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"plt.rcParams['font.family'] = ['SimHei'] # 用来正常显示中文标签\n",
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"plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号\n",
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"pd.set_option('display.max_columns', None) #显示所有列，把行显示设置成最大\n",
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"pd.set_option('display.max_rows', None) #显示所有行，把列显示设置成最大\n",
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"#交互式绘图\n",
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"%matplotlib widget"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "ccb60f92-e657-4732-a679-6ca67bfcf201",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"MCX (96, 18)\n",
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"MCY (96, 18)\n",
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"Angle13 (96, 18)\n",
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"M1X (96, 18)\n",
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"M1Y (96, 18)\n",
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"M3X (96, 18)\n",
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"M3Y (96, 18)\n",
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"Note (7, 1)\n"
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]
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}
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],
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"source": [
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"#写入TotalData\n",
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"TotalData = pd.read_excel('../Die1AllData.xlsx',sheet_name=None,header=0,index_col = 0)\n",
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"for i in TotalData:\n",
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" print(i,TotalData[i].shape)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8f9078d7",
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"metadata": {},
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"source": [
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"## 对位Mark"
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]
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},
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{
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"cell_type": "markdown",
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"id": "31b36a67",
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"metadata": {},
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"source": [
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"### 对位MarkX"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "6de0e187",
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"metadata": {},
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"outputs": [],
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"source": [
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"AlignMarkX = TotalData['M3X'].dropna(subset='QX8800SP_Index').set_index('QX8800SP_Index').iloc[:,-4:]\n",
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"# AlignMarkX"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "3380eb98",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>10.9.1-Die1</th>\n",
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" <th>10.10.1-Die1</th>\n",
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" <th>10.10.2-Die1</th>\n",
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" <th>10.11.1-Die1</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>72.000000</td>\n",
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" <td>70.000000</td>\n",
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" <td>74.000000</td>\n",
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" <td>75.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>-2.760417</td>\n",
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" <td>-2.452600</td>\n",
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" <td>-2.748135</td>\n",
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" <td>-2.491933</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>0.283306</td>\n",
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" <td>0.309353</td>\n",
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" <td>0.290616</td>\n",
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" <td>0.299251</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>-3.609000</td>\n",
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" <td>-2.994000</td>\n",
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" <td>-3.531000</td>\n",
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" <td>-3.530000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>-2.923250</td>\n",
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" <td>-2.702000</td>\n",
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" <td>-2.937250</td>\n",
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" <td>-2.642500</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>-2.719500</td>\n",
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" <td>-2.431000</td>\n",
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" <td>-2.745500</td>\n",
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" <td>-2.442000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>-2.593750</td>\n",
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" <td>-2.274000</td>\n",
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" <td>-2.520000</td>\n",
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" <td>-2.297000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>-2.241000</td>\n",
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" <td>-1.706000</td>\n",
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" <td>-2.178000</td>\n",
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" <td>-1.904000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>range</th>\n",
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" <td>1.368000</td>\n",
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" <td>1.288000</td>\n",
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" <td>1.353000</td>\n",
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" <td>1.626000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3sigma</th>\n",
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" <td>0.849917</td>\n",
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" <td>0.928060</td>\n",
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" <td>0.871849</td>\n",
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" <td>0.897752</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" 10.9.1-Die1 10.10.1-Die1 10.10.2-Die1 10.11.1-Die1\n",
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"count 72.000000 70.000000 74.000000 75.000000\n",
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"mean -2.760417 -2.452600 -2.748135 -2.491933\n",
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"std 0.283306 0.309353 0.290616 0.299251\n",
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"min -3.609000 -2.994000 -3.531000 -3.530000\n",
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"25% -2.923250 -2.702000 -2.937250 -2.642500\n",
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"50% -2.719500 -2.431000 -2.745500 -2.442000\n",
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"75% -2.593750 -2.274000 -2.520000 -2.297000\n",
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"max -2.241000 -1.706000 -2.178000 -1.904000\n",
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"range 1.368000 1.288000 1.353000 1.626000\n",
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"3sigma 0.849917 0.928060 0.871849 0.897752"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"AXdescibe = describe_3s(AlignMarkX)\n",
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"AXdescibe"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "5355743f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "179b886277fc49639426590de1529db3",
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"version_major": 2,
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"version_minor": 0
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},
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" </div>\n",
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" "
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],
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
|
|||
|
|
},
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"metadata": {},
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"output_type": "display_data"
|
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|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"fig, ax = plt.subplots(2,1)\n",
|
|||
|
|
"ax[0].plot([i+1 for i in range(len(AlignMarkX.columns))],AXdescibe.loc['mean'],linestyle = '-.',marker = 'o',color='w')\n",
|
|||
|
|
"AlignMarkX.boxplot(ax=ax[0])\n",
|
|||
|
|
"ax[0].axhline(0,c='orange',ls='-.',label=r'Mean_X:$0um\\pm0.10um$')\n",
|
|||
|
|
"for i in range(len(AlignMarkX.columns)):\n",
|
|||
|
|
" ax[0].annotate(round(AXdescibe.loc['mean'][i],3), \n",
|
|||
|
|
" xy=(i+1,AXdescibe.loc['mean'][i]),\n",
|
|||
|
|
" xytext=(i+0.95,AXdescibe.loc['mean'][i]+0.05),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[0].legend()\n",
|
|||
|
|
"ax[0].set_title('mean_X/Day')\n",
|
|||
|
|
"ax[1].plot([i for i in AlignMarkX.columns],AXdescibe.loc['3sigma'],marker = 'o')\n",
|
|||
|
|
"ax[1].axhline(0.8,c='orange',ls='-.',label=r'3sigma_X:$<0.800um$')\n",
|
|||
|
|
"ax[1].axhline(0.57,c='green',ls='-.',label=r'3sigma_X:$<0.570um$')\n",
|
|||
|
|
"for i in range(len(AlignMarkX.columns)):\n",
|
|||
|
|
" ax[1].annotate(round(AXdescibe.loc['3sigma'][i],3), \n",
|
|||
|
|
" xy=(i,AXdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" xytext=(i,AXdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[1].legend() \n",
|
|||
|
|
"ax[1].set_title('3sigam_X/Day')\n",
|
|||
|
|
"# ax[2].plot([i for i in AlignMarkX.columns],AXdescibe.loc['range'],marker = 'o')\n",
|
|||
|
|
"# for i in range(len(AlignMarkX.columns)):\n",
|
|||
|
|
"# ax[2].annotate(round(AXdescibe.loc['range'][i],3), \n",
|
|||
|
|
"# xy=(i,AXdescibe.loc['range'][i]),\n",
|
|||
|
|
"# xytext=(i,AXdescibe.loc['range'][i]),\n",
|
|||
|
|
"# color=\"r\")\n",
|
|||
|
|
"# ax[2].set_title('Range_X/Day')\n",
|
|||
|
|
"plt.suptitle('Die1 对位Mark：X')\n",
|
|||
|
|
"fig.tight_layout()\n",
|
|||
|
|
"plt.savefig('Die1/Die1对位MarkX.jpg',dpi=200)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "64f88c9a",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"### 对位MarkY"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"id": "9e294f7b-3ea3-4a33-99b5-92e22bd1a827",
|
|||
|
|
"metadata": {
|
|||
|
|
"tags": []
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
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"\n",
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" }\n",
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"</style>\n",
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" <th></th>\n",
|
|||
|
|
" <th>10.9.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.2-Die1</th>\n",
|
|||
|
|
" <th>10.11.1-Die1</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>count</th>\n",
|
|||
|
|
" <td>72.000000</td>\n",
|
|||
|
|
" <td>70.000000</td>\n",
|
|||
|
|
" <td>74.000000</td>\n",
|
|||
|
|
" <td>75.000000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>mean</th>\n",
|
|||
|
|
" <td>-1.835278</td>\n",
|
|||
|
|
" <td>-2.167943</td>\n",
|
|||
|
|
" <td>-2.189946</td>\n",
|
|||
|
|
" <td>-1.754587</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>std</th>\n",
|
|||
|
|
" <td>0.257746</td>\n",
|
|||
|
|
" <td>0.281506</td>\n",
|
|||
|
|
" <td>0.339576</td>\n",
|
|||
|
|
" <td>0.226120</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>min</th>\n",
|
|||
|
|
" <td>-2.620000</td>\n",
|
|||
|
|
" <td>-2.822000</td>\n",
|
|||
|
|
" <td>-3.065000</td>\n",
|
|||
|
|
" <td>-2.488000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25%</th>\n",
|
|||
|
|
" <td>-1.987750</td>\n",
|
|||
|
|
" <td>-2.331250</td>\n",
|
|||
|
|
" <td>-2.413000</td>\n",
|
|||
|
|
" <td>-1.872500</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50%</th>\n",
|
|||
|
|
" <td>-1.811500</td>\n",
|
|||
|
|
" <td>-2.194000</td>\n",
|
|||
|
|
" <td>-2.195000</td>\n",
|
|||
|
|
" <td>-1.776000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75%</th>\n",
|
|||
|
|
" <td>-1.671250</td>\n",
|
|||
|
|
" <td>-1.995250</td>\n",
|
|||
|
|
" <td>-2.016000</td>\n",
|
|||
|
|
" <td>-1.632000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>max</th>\n",
|
|||
|
|
" <td>-1.252000</td>\n",
|
|||
|
|
" <td>-1.570000</td>\n",
|
|||
|
|
" <td>-1.012000</td>\n",
|
|||
|
|
" <td>-1.079000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>range</th>\n",
|
|||
|
|
" <td>1.368000</td>\n",
|
|||
|
|
" <td>1.252000</td>\n",
|
|||
|
|
" <td>2.053000</td>\n",
|
|||
|
|
" <td>1.409000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>3sigma</th>\n",
|
|||
|
|
" <td>0.773239</td>\n",
|
|||
|
|
" <td>0.844518</td>\n",
|
|||
|
|
" <td>1.018729</td>\n",
|
|||
|
|
" <td>0.678360</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 10.9.1-Die1 10.10.1-Die1 10.10.2-Die1 10.11.1-Die1\n",
|
|||
|
|
"count 72.000000 70.000000 74.000000 75.000000\n",
|
|||
|
|
"mean -1.835278 -2.167943 -2.189946 -1.754587\n",
|
|||
|
|
"std 0.257746 0.281506 0.339576 0.226120\n",
|
|||
|
|
"min -2.620000 -2.822000 -3.065000 -2.488000\n",
|
|||
|
|
"25% -1.987750 -2.331250 -2.413000 -1.872500\n",
|
|||
|
|
"50% -1.811500 -2.194000 -2.195000 -1.776000\n",
|
|||
|
|
"75% -1.671250 -1.995250 -2.016000 -1.632000\n",
|
|||
|
|
"max -1.252000 -1.570000 -1.012000 -1.079000\n",
|
|||
|
|
"range 1.368000 1.252000 2.053000 1.409000\n",
|
|||
|
|
"3sigma 0.773239 0.844518 1.018729 0.678360"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"AlignMarkY = TotalData['M3Y'].dropna(subset='QX8800SP_Index').set_index('QX8800SP_Index').iloc[:,-4:]\n",
|
|||
|
|
"AYdescibe = describe_3s(AlignMarkY)\n",
|
|||
|
|
"AYdescibe"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 10,
|
|||
|
|
"id": "81162e4f-1ed2-4365-9e55-2a0177174f18",
|
|||
|
|
"metadata": {
|
|||
|
|
"tags": []
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "504d610964064527aa33de7c09d08993",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
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|||
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|
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|
"\n",
|
|||
|
|
" <div style=\"display: inline-block;\">\n",
|
|||
|
|
" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
|
|||
|
|
" Figure\n",
|
|||
|
|
" </div>\n",
|
|||
|
|
" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"fig, ax = plt.subplots(2,1)\n",
|
|||
|
|
"ax[0].plot([i+1 for i in range(len(AlignMarkY.columns))],AYdescibe.loc['mean'],linestyle = '-.',marker = 'o',color='w')\n",
|
|||
|
|
"AlignMarkY.boxplot(ax=ax[0])\n",
|
|||
|
|
"ax[0].axhline(0,c='orange',ls='-.',label=r'Mean_Y:$0um\\pm0.10um$')\n",
|
|||
|
|
"for i in range(len(AlignMarkY.columns)):\n",
|
|||
|
|
" ax[0].annotate(round(AYdescibe.loc['mean'][i],2), \n",
|
|||
|
|
" xy=(i+1,AYdescibe.loc['mean'][i]),\n",
|
|||
|
|
" xytext=(i+0.95,AYdescibe.loc['mean'][i]+0.05),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[0].legend()\n",
|
|||
|
|
"ax[0].set_title('mean_Y/Day')\n",
|
|||
|
|
"ax[1].plot([i for i in AlignMarkY.columns],AYdescibe.loc['3sigma'],marker = 'o')\n",
|
|||
|
|
"ax[1].axhline(0.8,c='orange',ls='-.',label=r'3sigma_Y:$<0.800um$')\n",
|
|||
|
|
"ax[1].axhline(0.57,c='green',ls='-.',label=r'3sigma_Y:$<0.570um$')\n",
|
|||
|
|
"for i in range(len(AlignMarkY.columns)):\n",
|
|||
|
|
" ax[1].annotate(round(AYdescibe.loc['3sigma'][i],3), \n",
|
|||
|
|
" xy=(i,AYdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" xytext=(i,AYdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[1].legend() \n",
|
|||
|
|
"ax[1].set_title('3sigam_Y/Day')\n",
|
|||
|
|
"# ax[2].plot([i for i in AlignMarkY.columns],AYdescibe.loc['range'],marker = 'o')\n",
|
|||
|
|
"# for i in range(len(AlignMarkY.columns)):\n",
|
|||
|
|
"# ax[2].annotate(round(AYdescibe.loc['range'][i],3), \n",
|
|||
|
|
"# xy=(i,AYdescibe.loc['range'][i]),\n",
|
|||
|
|
"# xytext=(i,AYdescibe.loc['range'][i]),\n",
|
|||
|
|
"# color=\"r\")\n",
|
|||
|
|
"# ax[2].set_title('Range_Y/Day')\n",
|
|||
|
|
"plt.suptitle('Die1 对位Mark：Y')\n",
|
|||
|
|
"fig.tight_layout()\n",
|
|||
|
|
"plt.savefig('Die1/Die1对位MarkY.jpg',dpi=200)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "6ace8d23",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## 角度Mark"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "c70c8ca9",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"### 角度MarkX"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 12,
|
|||
|
|
"id": "87ad2953",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/html": [
|
|||
|
|
"<div>\n",
|
|||
|
|
"<style scoped>\n",
|
|||
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|||
|
|
" vertical-align: middle;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe tbody tr th {\n",
|
|||
|
|
" vertical-align: top;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe thead th {\n",
|
|||
|
|
" text-align: right;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"</style>\n",
|
|||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|||
|
|
" <thead>\n",
|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>10.9.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.2-Die1</th>\n",
|
|||
|
|
" <th>10.11.1-Die1</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>count</th>\n",
|
|||
|
|
" <td>72.000000</td>\n",
|
|||
|
|
" <td>70.000000</td>\n",
|
|||
|
|
" <td>74.000000</td>\n",
|
|||
|
|
" <td>75.000000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>mean</th>\n",
|
|||
|
|
" <td>-3.491917</td>\n",
|
|||
|
|
" <td>-3.463871</td>\n",
|
|||
|
|
" <td>-3.685568</td>\n",
|
|||
|
|
" <td>-3.396920</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>std</th>\n",
|
|||
|
|
" <td>0.300497</td>\n",
|
|||
|
|
" <td>0.311372</td>\n",
|
|||
|
|
" <td>0.295496</td>\n",
|
|||
|
|
" <td>0.306453</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>min</th>\n",
|
|||
|
|
" <td>-4.376000</td>\n",
|
|||
|
|
" <td>-4.065000</td>\n",
|
|||
|
|
" <td>-4.318000</td>\n",
|
|||
|
|
" <td>-4.468000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25%</th>\n",
|
|||
|
|
" <td>-3.656250</td>\n",
|
|||
|
|
" <td>-3.717750</td>\n",
|
|||
|
|
" <td>-3.879750</td>\n",
|
|||
|
|
" <td>-3.595000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50%</th>\n",
|
|||
|
|
" <td>-3.449000</td>\n",
|
|||
|
|
" <td>-3.416000</td>\n",
|
|||
|
|
" <td>-3.691000</td>\n",
|
|||
|
|
" <td>-3.367000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75%</th>\n",
|
|||
|
|
" <td>-3.311500</td>\n",
|
|||
|
|
" <td>-3.321250</td>\n",
|
|||
|
|
" <td>-3.461000</td>\n",
|
|||
|
|
" <td>-3.211500</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>max</th>\n",
|
|||
|
|
" <td>-3.000000</td>\n",
|
|||
|
|
" <td>-2.496000</td>\n",
|
|||
|
|
" <td>-3.052000</td>\n",
|
|||
|
|
" <td>-2.681000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>range</th>\n",
|
|||
|
|
" <td>1.376000</td>\n",
|
|||
|
|
" <td>1.569000</td>\n",
|
|||
|
|
" <td>1.266000</td>\n",
|
|||
|
|
" <td>1.787000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>3sigma</th>\n",
|
|||
|
|
" <td>0.901491</td>\n",
|
|||
|
|
" <td>0.934116</td>\n",
|
|||
|
|
" <td>0.886488</td>\n",
|
|||
|
|
" <td>0.919359</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 10.9.1-Die1 10.10.1-Die1 10.10.2-Die1 10.11.1-Die1\n",
|
|||
|
|
"count 72.000000 70.000000 74.000000 75.000000\n",
|
|||
|
|
"mean -3.491917 -3.463871 -3.685568 -3.396920\n",
|
|||
|
|
"std 0.300497 0.311372 0.295496 0.306453\n",
|
|||
|
|
"min -4.376000 -4.065000 -4.318000 -4.468000\n",
|
|||
|
|
"25% -3.656250 -3.717750 -3.879750 -3.595000\n",
|
|||
|
|
"50% -3.449000 -3.416000 -3.691000 -3.367000\n",
|
|||
|
|
"75% -3.311500 -3.321250 -3.461000 -3.211500\n",
|
|||
|
|
"max -3.000000 -2.496000 -3.052000 -2.681000\n",
|
|||
|
|
"range 1.376000 1.569000 1.266000 1.787000\n",
|
|||
|
|
"3sigma 0.901491 0.934116 0.886488 0.919359"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 12,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"AngleMarkX = TotalData['M1X'].dropna(subset='QX8800SP_Index').set_index('QX8800SP_Index').iloc[:,-4:]\n",
|
|||
|
|
"RXdescibe = describe_3s(AngleMarkX)\n",
|
|||
|
|
"RXdescibe"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 13,
|
|||
|
|
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|||
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|||
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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}
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],
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|||
|
|
"source": [
|
|||
|
|
"fig, ax = plt.subplots(3,1)\n",
|
|||
|
|
"ax[0].plot([i+1 for i in range(len(AngleMarkX.columns))],RXdescibe.loc['mean'],linestyle = '-.',marker = 'o',color='w')\n",
|
|||
|
|
"AngleMarkX.boxplot(ax=ax[0])\n",
|
|||
|
|
"ax[0].axhline(0,c='orange',ls='-.',label=r'Mean_X:$0um\\pm0.10um$')\n",
|
|||
|
|
"for i in range(len(AngleMarkX.columns)):\n",
|
|||
|
|
" ax[0].annotate(round(RXdescibe.loc['mean'][i],2), \n",
|
|||
|
|
" xy=(i+1,RXdescibe.loc['mean'][i]),\n",
|
|||
|
|
" xytext=(i+0.95,RXdescibe.loc['mean'][i]+0.05),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[0].legend()\n",
|
|||
|
|
"ax[0].set_title('mean_X/Day')\n",
|
|||
|
|
"ax[1].plot([i for i in AngleMarkX.columns],RXdescibe.loc['3sigma'],marker = 'o')\n",
|
|||
|
|
"ax[1].axhline(0.8,c='orange',ls='-.',label=r'3sigma_X:$<0.800um$')\n",
|
|||
|
|
"for i in range(len(AngleMarkX.columns)):\n",
|
|||
|
|
" ax[1].annotate(round(RXdescibe.loc['3sigma'][i],3), \n",
|
|||
|
|
" xy=(i,RXdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" xytext=(i,RXdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[1].legend() \n",
|
|||
|
|
"ax[1].set_title('3sigam_X/Day')\n",
|
|||
|
|
"ax[2].plot([i for i in AngleMarkX.columns],RXdescibe.loc['range'],marker = 'o')\n",
|
|||
|
|
"for i in range(len(AngleMarkX.columns)):\n",
|
|||
|
|
" ax[2].annotate(round(RXdescibe.loc['range'][i],3), \n",
|
|||
|
|
" xy=(i,RXdescibe.loc['range'][i]),\n",
|
|||
|
|
" xytext=(i,RXdescibe.loc['range'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[2].set_title('Range_X/Day')\n",
|
|||
|
|
"plt.suptitle('Die1 角度Mark：X')\n",
|
|||
|
|
"fig.tight_layout()\n",
|
|||
|
|
"plt.savefig('Die1/Die1角度MarkX.jpg',dpi=200)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
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},
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{
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"id": "fca6defb",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"### 角度MarkY"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
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"cell_type": "code",
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"execution_count": 14,
|
|||
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"id": "389557c5",
|
|||
|
|
"metadata": {},
|
|||
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"outputs": [
|
|||
|
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{
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" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe thead th {\n",
|
|||
|
|
" text-align: right;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"</style>\n",
|
|||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|||
|
|
" <thead>\n",
|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>10.9.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.2-Die1</th>\n",
|
|||
|
|
" <th>10.11.1-Die1</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>count</th>\n",
|
|||
|
|
" <td>72.000000</td>\n",
|
|||
|
|
" <td>70.000000</td>\n",
|
|||
|
|
" <td>74.000000</td>\n",
|
|||
|
|
" <td>75.000000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>mean</th>\n",
|
|||
|
|
" <td>-1.151528</td>\n",
|
|||
|
|
" <td>-3.249543</td>\n",
|
|||
|
|
" <td>-2.846649</td>\n",
|
|||
|
|
" <td>-1.147520</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>std</th>\n",
|
|||
|
|
" <td>0.419282</td>\n",
|
|||
|
|
" <td>0.710503</td>\n",
|
|||
|
|
" <td>0.496586</td>\n",
|
|||
|
|
" <td>0.889048</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>min</th>\n",
|
|||
|
|
" <td>-2.650000</td>\n",
|
|||
|
|
" <td>-4.354000</td>\n",
|
|||
|
|
" <td>-3.686000</td>\n",
|
|||
|
|
" <td>-2.350000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25%</th>\n",
|
|||
|
|
" <td>-1.395750</td>\n",
|
|||
|
|
" <td>-3.796500</td>\n",
|
|||
|
|
" <td>-3.263000</td>\n",
|
|||
|
|
" <td>-1.570500</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50%</th>\n",
|
|||
|
|
" <td>-1.132500</td>\n",
|
|||
|
|
" <td>-3.477000</td>\n",
|
|||
|
|
" <td>-2.911000</td>\n",
|
|||
|
|
" <td>-1.315000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75%</th>\n",
|
|||
|
|
" <td>-0.870750</td>\n",
|
|||
|
|
" <td>-2.731000</td>\n",
|
|||
|
|
" <td>-2.436250</td>\n",
|
|||
|
|
" <td>-0.937000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>max</th>\n",
|
|||
|
|
" <td>-0.330000</td>\n",
|
|||
|
|
" <td>-1.446000</td>\n",
|
|||
|
|
" <td>-1.644000</td>\n",
|
|||
|
|
" <td>4.678000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>range</th>\n",
|
|||
|
|
" <td>2.320000</td>\n",
|
|||
|
|
" <td>2.908000</td>\n",
|
|||
|
|
" <td>2.042000</td>\n",
|
|||
|
|
" <td>7.028000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>3sigma</th>\n",
|
|||
|
|
" <td>1.257846</td>\n",
|
|||
|
|
" <td>2.131509</td>\n",
|
|||
|
|
" <td>1.489758</td>\n",
|
|||
|
|
" <td>2.667143</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 10.9.1-Die1 10.10.1-Die1 10.10.2-Die1 10.11.1-Die1\n",
|
|||
|
|
"count 72.000000 70.000000 74.000000 75.000000\n",
|
|||
|
|
"mean -1.151528 -3.249543 -2.846649 -1.147520\n",
|
|||
|
|
"std 0.419282 0.710503 0.496586 0.889048\n",
|
|||
|
|
"min -2.650000 -4.354000 -3.686000 -2.350000\n",
|
|||
|
|
"25% -1.395750 -3.796500 -3.263000 -1.570500\n",
|
|||
|
|
"50% -1.132500 -3.477000 -2.911000 -1.315000\n",
|
|||
|
|
"75% -0.870750 -2.731000 -2.436250 -0.937000\n",
|
|||
|
|
"max -0.330000 -1.446000 -1.644000 4.678000\n",
|
|||
|
|
"range 2.320000 2.908000 2.042000 7.028000\n",
|
|||
|
|
"3sigma 1.257846 2.131509 1.489758 2.667143"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 14,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"AngleMarkY = TotalData['M1Y'].dropna(subset='QX8800SP_Index').set_index('QX8800SP_Index').iloc[:,-4:]\n",
|
|||
|
|
"RYdescibe = describe_3s(AngleMarkY)\n",
|
|||
|
|
"RYdescibe"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 15,
|
|||
|
|
"id": "c7a1606f-4530-4fa6-89ce-892a57c06493",
|
|||
|
|
"metadata": {
|
|||
|
|
"tags": []
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "b59e58f6784145909a0445419c445a56",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
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|||
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|
"text/html": [
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"\n",
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" <div style=\"display: inline-block;\">\n",
|
|||
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|
" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
|
|||
|
|
" Figure\n",
|
|||
|
|
" </div>\n",
|
|||
|
|
" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"fig, ax = plt.subplots(3,1)\n",
|
|||
|
|
"ax[0].plot([i+1 for i in range(len(AngleMarkY.columns))],RYdescibe.loc['mean'],linestyle = '-.',marker = 'o',color='w')\n",
|
|||
|
|
"AngleMarkY.boxplot(ax=ax[0])\n",
|
|||
|
|
"ax[0].axhline(0,c='orange',ls='-.',label=r'Mean_Y:$0um\\pm0.10um$')\n",
|
|||
|
|
"for i in range(len(AngleMarkY.columns)):\n",
|
|||
|
|
" ax[0].annotate(round(RYdescibe.loc['mean'][i],2), \n",
|
|||
|
|
" xy=(i+1,RYdescibe.loc['mean'][i]),\n",
|
|||
|
|
" xytext=(i+0.95,RYdescibe.loc['mean'][i]+0.05),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[0].legend()\n",
|
|||
|
|
"ax[0].set_title('mean_Y/Day')\n",
|
|||
|
|
"ax[1].plot([i for i in AngleMarkY.columns],RYdescibe.loc['3sigma'],marker = 'o')\n",
|
|||
|
|
"ax[1].axhline(0.8,c='orange',ls='-.',label=r'3sigma_Y:$<0.800um$')\n",
|
|||
|
|
"for i in range(len(AngleMarkY.columns)):\n",
|
|||
|
|
" ax[1].annotate(round(RYdescibe.loc['3sigma'][i],3), \n",
|
|||
|
|
" xy=(i,RYdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" xytext=(i,RYdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[1].legend() \n",
|
|||
|
|
"ax[1].set_title('3sigam_Y/Day')\n",
|
|||
|
|
"ax[2].plot([i for i in AngleMarkY.columns],RYdescibe.loc['range'],marker = 'o')\n",
|
|||
|
|
"for i in range(len(AngleMarkY.columns)):\n",
|
|||
|
|
" ax[2].annotate(round(RYdescibe.loc['range'][i],3), \n",
|
|||
|
|
" xy=(i,RYdescibe.loc['range'][i]),\n",
|
|||
|
|
" xytext=(i,RYdescibe.loc['range'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[2].set_title('Range_Y/Day')\n",
|
|||
|
|
"plt.suptitle('Die1 角度Mark：Y')\n",
|
|||
|
|
"fig.tight_layout()\n",
|
|||
|
|
"plt.savefig('Die1/Die1角度MarkY.jpg',dpi=200)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "57aab54c-ca77-46e9-bdfa-becc3323ab8f",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## 角度"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 16,
|
|||
|
|
"id": "3b9aba3d-417d-4292-ac07-8c9d25d260b8",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/html": [
|
|||
|
|
"<div>\n",
|
|||
|
|
"<style scoped>\n",
|
|||
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|||
|
|
" vertical-align: middle;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe tbody tr th {\n",
|
|||
|
|
" vertical-align: top;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe thead th {\n",
|
|||
|
|
" text-align: right;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"</style>\n",
|
|||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|||
|
|
" <thead>\n",
|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>10.9.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.1-Die1</th>\n",
|
|||
|
|
" <th>10.10.2-Die1</th>\n",
|
|||
|
|
" <th>10.11.1-Die1</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>count</th>\n",
|
|||
|
|
" <td>72.000000</td>\n",
|
|||
|
|
" <td>70.000000</td>\n",
|
|||
|
|
" <td>74.000000</td>\n",
|
|||
|
|
" <td>75.000000</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>mean</th>\n",
|
|||
|
|
" <td>-0.003060</td>\n",
|
|||
|
|
" <td>0.005293</td>\n",
|
|||
|
|
" <td>0.003281</td>\n",
|
|||
|
|
" <td>-0.002664</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>std</th>\n",
|
|||
|
|
" <td>0.001829</td>\n",
|
|||
|
|
" <td>0.003321</td>\n",
|
|||
|
|
" <td>0.002353</td>\n",
|
|||
|
|
" <td>0.004332</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>min</th>\n",
|
|||
|
|
" <td>-0.008847</td>\n",
|
|||
|
|
" <td>-0.002692</td>\n",
|
|||
|
|
" <td>-0.003765</td>\n",
|
|||
|
|
" <td>-0.030935</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25%</th>\n",
|
|||
|
|
" <td>-0.004100</td>\n",
|
|||
|
|
" <td>0.002516</td>\n",
|
|||
|
|
" <td>0.001854</td>\n",
|
|||
|
|
" <td>-0.003680</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50%</th>\n",
|
|||
|
|
" <td>-0.003255</td>\n",
|
|||
|
|
" <td>0.006528</td>\n",
|
|||
|
|
" <td>0.003540</td>\n",
|
|||
|
|
" <td>-0.001873</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75%</th>\n",
|
|||
|
|
" <td>-0.002056</td>\n",
|
|||
|
|
" <td>0.007783</td>\n",
|
|||
|
|
" <td>0.004918</td>\n",
|
|||
|
|
" <td>-0.000754</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>max</th>\n",
|
|||
|
|
" <td>0.003344</td>\n",
|
|||
|
|
" <td>0.010516</td>\n",
|
|||
|
|
" <td>0.009001</td>\n",
|
|||
|
|
" <td>0.002542</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>range</th>\n",
|
|||
|
|
" <td>0.012192</td>\n",
|
|||
|
|
" <td>0.013209</td>\n",
|
|||
|
|
" <td>0.012766</td>\n",
|
|||
|
|
" <td>0.033477</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>3sigma</th>\n",
|
|||
|
|
" <td>0.005486</td>\n",
|
|||
|
|
" <td>0.009964</td>\n",
|
|||
|
|
" <td>0.007059</td>\n",
|
|||
|
|
" <td>0.012997</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 10.9.1-Die1 10.10.1-Die1 10.10.2-Die1 10.11.1-Die1\n",
|
|||
|
|
"count 72.000000 70.000000 74.000000 75.000000\n",
|
|||
|
|
"mean -0.003060 0.005293 0.003281 -0.002664\n",
|
|||
|
|
"std 0.001829 0.003321 0.002353 0.004332\n",
|
|||
|
|
"min -0.008847 -0.002692 -0.003765 -0.030935\n",
|
|||
|
|
"25% -0.004100 0.002516 0.001854 -0.003680\n",
|
|||
|
|
"50% -0.003255 0.006528 0.003540 -0.001873\n",
|
|||
|
|
"75% -0.002056 0.007783 0.004918 -0.000754\n",
|
|||
|
|
"max 0.003344 0.010516 0.009001 0.002542\n",
|
|||
|
|
"range 0.012192 0.013209 0.012766 0.033477\n",
|
|||
|
|
"3sigma 0.005486 0.009964 0.007059 0.012997"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 16,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"Angle = TotalData['Angle13'].dropna(subset='QX8800SP_Index').set_index('QX8800SP_Index').iloc[:,-4:]\n",
|
|||
|
|
"Angdescibe = describe_3s(Angle)\n",
|
|||
|
|
"Angdescibe"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 17,
|
|||
|
|
"id": "5ce2eec7-a959-4716-92a0-4aaad88b96b3",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "854e3fc819b94859a75791c550882ab7",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAyAAAAImCAYAAACrXu7BAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAADS+ElEQVR4nOzdd3QU1d/H8ffsbnoPhNA7Ih2B0MSGiICIWLB3FCkqCAqCKE1FRMCKiKKIoqKIiGLhZ3lURLpSlBoh9AgkpLctzx9LNlnS24bA53VOTjJz5965s5ls9ju3GQ6Hw4GIiIiIiIgHmCq7AiIiIiIicv5QACIiIiIiIh6jAERERERERDxGAYiIiIiIiHiMAhAREREREfEYBSAiIiIiIuIxCkBERERERMRjFICIiIiIiIjHKAARERERERGPUQAiIiIiIiIeowBEROQ8Nm/ePF5//fVyKWvq1Kl8/PHH5VJWbikpKWRmZpZ7uadOnSr3MkVEpGgKQEREzlN79+5l7ty5NGrUqFzKS09P57333nPbl5WVRXJycqnLTEhI4N577+Wjjz7Kk/bnn38ye/Zsfvnll1KV/cQTTzB16lQcDkep6yciIiVnOPTOKyJSJuvWrePuu+8GwN/fnyZNmnDLLbcwaNCgAo/dtWtXqc/32WefsWLFCj744INSl5GcnMxtt93G7t27801v1aoVS5YswcvLK0/aW2+9xezZs0t0vq1bt+Lj41OiPBkZGdx66620atWKyZMnY7FYXGl79uxh+vTpjBs3jg8//JDbbruNli1blqj8EydOMGTIEDp06MDEiRNLlFdERErPUvQhIiJSHC+99BKhoaEsX76ciRMncuzYMR555BG3Y1q1asXSpUtLfY6NGzcybdo02rVrV+oyUlJSePjhhwkMDGTjxo14e3u70n744QfGjRvHCy+8kG/wAWCxWGjevDmfffYZAJs3b2b58uVMnTrVdcw777yD1Wpl8ODBZGZmljj4AHjuueeoVasWzz77bJ60PXv2cO2119K8eXN69uzJ/v37SxyAVK9enQULFnD99dcTFRXF1VdfXeI6iohIySkAEREpJ02bNqVFixZccsklZGRk8NZbb3H77bdTrVo11zGBgYG0adOmVOX//PPPjB49miZNmpS6jv/++y+PPfYYGRkZLFy4EJPJhNVqBSAzM5NZs2bxwAMPUKdOHVJSUgDw8/PDZMrpsWsymTCbzRiGgWEYJCYm8vPPP7sFGYcOHSIrKwt/f38sFgsOhwPDMIpdz927d/O///2P7777Lt/0qKgoRo8eTUZGBqtWreKFF14ozctBWFgYL7zwAuPGjePKK690a2UREZGKoXdaEZEKcMstt/C///2P3377jYEDB5ZLmevXr+fll19m69atrF+/vsT5k5OTGTJkCDVq1GD37t1cdtll+R735ptv8uabb7q2V65cSdOmTd2OMQyDF154gY8++giz2YzVanULrGw2Gw6Hg2+//Rar1crq1auJiIgodl0/+ugjrr/+ekJCQvJNj4iIcL0WM2bMKFHZZ+ratSthYWH8/PPPXHXVVaUuR0REikeD0EVEKsCFF14IQHR0tNv+devW0bx583zz7Nixg7vvvpu2bdty5ZVXsnDhQrf0J554osCgoTgCAwNZsGABCxcuxGw2M2/ePDZs2MCGDRt4++23AVzbGzZsYOXKlQBuXbQA7HY7FouF8ePHs2PHDubMmUNoaCjbtm1zfV1//fVcd911/P333/z9999Ur169RHXdunVrkddarVo1rrjiijIFH9kuu+wytmzZUuZyRESkaGoBERGpANlP7hMSEop1fHx8PPfeey9dunThnXfeYffu3Tz//PMEBAS4BrPn7gZVWg0aNACcQUR2Vyogz/fcP5953vT0dLy8vFxjRGw2G4Cry1b2PrvdDlCqbk1HjhwhMjKyxPlKq0aNGmzevNlj5xMROZ8pABERqQAlGe8A8OGHH2IymZg1axZeXl507tyZdevW8eWXX+Y7m1ZZZGZmYrPZGDJkSJ60Dh06FJk/IyOD4OBg13Z6ejqnTp3Kk7dv376lrqOXl5dbQFPRUlJSChx0LyIi5UsBiIhIBUhMTAQocAzDmXbv3k1cXBytW7d2218e3YvOlL0A37fffkvjxo0B5+xad9xxh9v0wMeOHcu3G1RSUhIRERFkZWWRmJjIlVdeWWDrQUZGRqlmwGrYsCG7d++mVatWJc5bGrt376ZZs2YeOZeIyPlOAYiISAXIXl/jzMHbhWnbtq3bVLbg3iWqvOzbtw9wb2XIyMgA3LtRpaWl5Zv/2LFjtGrViujoaAYNGoRhGNjtdgICAlzHZGVlkZKSwrRp07j55ptLXMfLL7+cpUuXcv3115c4b0klJCTwww8/8MADD1T4uURERAGIiEiF+PTTT/Hx8Sn2oPFmzZrx559/0qRJE9eg72+++YaNGzfyzDPPlGvdtm7dCkCvXr3ypBWnC1ZMTAw9e/bkwgsvZNu2bURHR3PrrbeycOFCWrRogd1u58EHH8RkMpW6+9iNN97IW2+9xapVq+jdu3epyiiu2bNn0759e9fEASIiUrE0C5aISDnZu3cvv//+O2PHjuWbb77hiSeeIDQ0tFh577zzTjIzM3nsscf4448/+Prrr5kyZUq5DDzPzeFwsGLFCq644gp27drl+lq8eDGA275ffvklT/7jx48THR1N27ZtXfuaNGnCI488wrBhw4iOjmbKlCkcOXKEmTNnlngsTLbQ0FAmTJjAhAkTClytvTwsXbqUr776ikmTJlXYOURExJ1aQEREysnjjz+On58fLVq04I033si3haEg4eHhLFy4kBdeeIGHHnqIkJAQbrrpJkaOHFmudfzoo4/YvXs3Tz31lNv+9PR0ALcFA0+cOAG4dwNbtWoV1apV44ILLnDLf/fdd/Pnn39y3XXX4efnx7Jly4odfBVk4MCBHDhwgNtvv50333yTqKioMpV3pnfffZdXX32VN954g0aNGpVr2SIiUjDD4XA4KrsSIiJS8eLi4rj22mu58sor84w1+fbbbxk1ahR//fUX3t7e9O/fn3///Zc2bdrw2WefucZ59OnThyuuuIKHH36YY8eOsX//frZs2cKvv/7KyZMnueyyy9i8eTOxsbG0b9+eJk2aEBYWRs2aNbnhhhtK1SLy2Wef0aFDhzKtAJ+fb7/9ljp16ri15oiISMVTACIich45fvw4oaGhRU45e/DgQQzDoG7duq59DoeDVatWccEFF2Aymbjtttto3Lgxbdq0oUePHnTt2tXVWrJnzx7Wrl3Ltm3b2LNnD5dccgmjR4+u0GsTEZGqQQGIiIiIiIh4jAahi4iIiIiIxygAERERERERj1EAIiIiIiIiHqMAREREREREPEYBiIiIiIiIeIwCEBERERER8RgFICIiIiIi4jEKQERERERExGMUgIiIiIiIiMcoABEREREREY9RACIiIiIiIh6jAERERERERDxGAYiIiIiIiHiMAhAREREREfEYBSAiIiIiIuIxCkBERERERMRjFICIiIiIiIjHKAARERERERGPUQAiIiLntWXLluFwOCq7GiIi5w0FICIiUi4SEhJo0aIFr7zySoWep2fPnixbtqxcytqyZQu//fYbhmHw5JNP0rx5cy688EK6devGI488wq5du8rlPCIikkMBiIiIlIs//vgDu93O77//XtlVKbaXX36ZUaNGubYbNmzIp59+ypNPPsnu3bu59dZbFYSIiJQzBSAiIlIufv/9d7y9vdm+fTuJiYmVXZ0i/fzzzzRu3JgGDRq49vn6+tK2bVuuu+46Fi1aBDiDFBERKT8KQEREpFz8/vvv3HnnnYCzNeRsZrfbeeuttxgxYkSBx0RGRnLFFVfw22+/kZWV5cHaiYic2xSAiIicxe666y4mTZrErbfeSocOHfjmm28YPnw47du3Z86cOQB888039O/fn7Zt2zJw4MA8H/63bdvGHXfcwUUXXcQll1zCSy+95Bp0fejQIZo3b86uXbsYO3YsHTp04NJLL+WLL74oUT1jYmI4fPgwPXv2pEWLFm7dsIp7jsW
|
|||
|
|
"text/html": [
|
|||
|
|
"\n",
|
|||
|
|
" <div style=\"display: inline-block;\">\n",
|
|||
|
|
" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
|
|||
|
|
" Figure\n",
|
|||
|
|
" </div>\n",
|
|||
|
|
" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"fig, ax = plt.subplots(2,1)\n",
|
|||
|
|
"ax[0].plot([i+1 for i in range(len(Angle.columns))],Angdescibe.loc['mean'],linestyle = '-.',marker = 'o',color='w')\n",
|
|||
|
|
"Angle.boxplot(ax=ax[0])\n",
|
|||
|
|
"ax[0].axhline(0,c='orange',ls='-.',label=r'Mean_Angle:$0°\\pm0.0005°$')\n",
|
|||
|
|
"for i in range(len(Angle.columns)):\n",
|
|||
|
|
" ax[0].annotate(round(Angdescibe.loc['mean'][i],5), \n",
|
|||
|
|
" xy=(i+1,Angdescibe.loc['mean'][i]),\n",
|
|||
|
|
" xytext=(i+0.95,Angdescibe.loc['mean'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[0].legend()\n",
|
|||
|
|
"ax[0].set_title('mean_Angle/Day')\n",
|
|||
|
|
"ax[1].plot([i for i in Angle.columns],Angdescibe.loc['3sigma'],marker = 'o')\n",
|
|||
|
|
"ax[1].axhline(0.001,c='orange',ls='-.',label=r'3sigma_Angle:$<0.001°$')\n",
|
|||
|
|
"for i in range(len(Angle.columns)):\n",
|
|||
|
|
" ax[1].annotate(round(Angdescibe.loc['3sigma'][i],5), \n",
|
|||
|
|
" xy=(i,Angdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" xytext=(i,Angdescibe.loc['3sigma'][i]),\n",
|
|||
|
|
" color=\"r\")\n",
|
|||
|
|
"ax[1].legend() \n",
|
|||
|
|
"ax[1].set_title('3sigam_Angle/Day')\n",
|
|||
|
|
"# ax[2].plot([i for i in Angle.columns],Angdescibe.loc['range'],marker = 'o')\n",
|
|||
|
|
"# for i in range(len(Angle.columns)):\n",
|
|||
|
|
"# ax[2].annotate(round(Angdescibe.loc['range'][i],3), \n",
|
|||
|
|
"# xy=(i,Angdescibe.loc['range'][i]),\n",
|
|||
|
|
"# xytext=(i,Angdescibe.loc['range'][i]),\n",
|
|||
|
|
"# color=\"r\")\n",
|
|||
|
|
"# ax[2].set_title('Range_Angle/Day')\n",
|
|||
|
|
"plt.suptitle('Die1 角度（°）')\n",
|
|||
|
|
"fig.tight_layout()\n",
|
|||
|
|
"plt.savefig('Die1/Die1角度.jpg',dpi=200)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "f6b3c183-c253-46fb-80aa-45bb98f0eaad",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"### 按wafer数据存储"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"id": "374d2fb2-b795-4f8e-81cb-f1796226bd7a",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "639173af",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"### 补偿值计算"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 19,
|
|||
|
|
"id": "d0e8f6b1-0b58-4eab-8412-7b7c9f23a932",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Text(0.5, 1.0, 'Die1对位MarkX局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 19,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
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|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"BC_X = pd.concat([AlignMarkX[i]-AlignMarkX[i].mean() for i in AlignMarkX.columns[-4:]],axis=1)\n",
|
|||
|
|
"BC_X.plot(marker='o')\n",
|
|||
|
|
"plt.title('Die1对位MarkX局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 22,
|
|||
|
|
"id": "c8f85626-8763-49b3-a9ee-61d8d0fa4f9d",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Text(0.5, 1.0, 'Die1对位MarkX局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 22,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "49898e87da8f4625a47455908abae5d7",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
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"text/html": [
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"BC_X = BC_X.where(abs(BC_X)<1, np.nan)\n",
|
|||
|
|
"BC_X.plot(marker='o')\n",
|
|||
|
|
"plt.title('Die1对位MarkX局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"id": "61ce5e50-3b7b-4b70-8917-cc6bac2a1ced",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Text(0.5, 1.0, 'Die1对位MarkY（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "4ab09376ef2f414f9ed7c5457ac331eb",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
"image/png": "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"text/html": [
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"\n",
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" <div style=\"display: inline-block;\">\n",
|
|||
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
|
|||
|
|
" Figure\n",
|
|||
|
|
" </div>\n",
|
|||
|
|
" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"BC_Y = pd.concat([AlignMarkY[i]-AlignMarkY[i].mean() for i in AlignMarkY.columns[-4:]],axis=1)\n",
|
|||
|
|
"BC_Y.plot(marker='o')\n",
|
|||
|
|
"plt.title('Die1对位MarkY（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 23,
|
|||
|
|
"id": "ac86dfdd-f506-4ac7-9590-c563900d70df",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Text(0.5, 1.0, 'Die1对位MarkY局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 23,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "ca77619fb9984fdbb286338e78b1ec9a",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
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"text/html": [
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"\n",
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" <div style=\"display: inline-block;\">\n",
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" <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
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" Figure\n",
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" </div>\n",
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" <img src='data:image/png;base64,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
|
|||
|
|
" </div>\n",
|
|||
|
|
" "
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"BC_Y = BC_Y.where(abs(BC_Y)<1, np.nan)\n",
|
|||
|
|
"BC_Y.plot(marker='o')\n",
|
|||
|
|
"plt.title('Die1对位MarkY局部补偿（um）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 25,
|
|||
|
|
"id": "a94845fc-49f0-41a1-99a0-b5f5cdff1a69",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Text(0.5, 1.0, 'Die1角度（°）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 25,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"application/vnd.jupyter.widget-view+json": {
|
|||
|
|
"model_id": "bad88ad20d564793843212f3d51e7ae0",
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
},
|
|||
|
|
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|||
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|
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|||
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" "
|
|||
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],
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|
"text/plain": [
|
|||
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|
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"Angle.iloc[:,-4:].plot(marker='o')\n",
|
|||
|
|
"plt.title('Die1角度（°）')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 26,
|
|||
|
|
"id": "b62b7df1",
|
|||
|
|
"metadata": {
|
|||
|
|
"scrolled": true
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
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"text/html": [
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|||
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|
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|
|||
|
|
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|
|||
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|
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|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>对位MarkX</th>\n",
|
|||
|
|
" <th>对位MarkY</th>\n",
|
|||
|
|
" <th>Angle</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
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|
|||
|
|
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|
|||
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|
" <th></th>\n",
|
|||
|
|
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|
|||
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|
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|
|||
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|
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|
|||
|
|
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|
|||
|
|
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|
|||
|
|
" <th>1</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
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|
|||
|
|
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|
|||
|
|
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|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
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|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
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|
|||
|
|
" <th>4</th>\n",
|
|||
|
|
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|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
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|
|||
|
|
" <tr>\n",
|
|||
|
|
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|
|||
|
|
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|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
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|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>6</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>7</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>8</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>9</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>10</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>11</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>12</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>13</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>14</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>15</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>16</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>17</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>18</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>19</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>20</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>21</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>22</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>23</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>24</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>26</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>27</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>28</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>29</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>30</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>31</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>32</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>33</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>34</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>35</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>36</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>37</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>38</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>39</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>40</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>41</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>42</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>43</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>44</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>45</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>46</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>47</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>48</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>49</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>51</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>52</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>53</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>54</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>55</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>56</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>57</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>58</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>59</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>60</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>61</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>62</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>63</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>64</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>65</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>66</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>67</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>68</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>69</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>70</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>71</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>72</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>73</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>74</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>76</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>77</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>78</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>79</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>80</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>81</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>82</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>83</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>84</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>85</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>86</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>87</th>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 对位MarkX 对位MarkY Angle\n",
|
|||
|
|
"Index \n",
|
|||
|
|
"1 NaN NaN NaN\n",
|
|||
|
|
"2 NaN NaN NaN\n",
|
|||
|
|
"3 NaN NaN NaN\n",
|
|||
|
|
"4 NaN NaN NaN\n",
|
|||
|
|
"5 NaN NaN NaN\n",
|
|||
|
|
"6 NaN NaN NaN\n",
|
|||
|
|
"7 NaN NaN NaN\n",
|
|||
|
|
"8 NaN NaN NaN\n",
|
|||
|
|
"9 NaN NaN NaN\n",
|
|||
|
|
"10 NaN NaN NaN\n",
|
|||
|
|
"11 NaN NaN NaN\n",
|
|||
|
|
"12 NaN NaN NaN\n",
|
|||
|
|
"13 NaN NaN NaN\n",
|
|||
|
|
"14 NaN NaN NaN\n",
|
|||
|
|
"15 NaN NaN NaN\n",
|
|||
|
|
"16 NaN NaN NaN\n",
|
|||
|
|
"17 NaN NaN NaN\n",
|
|||
|
|
"18 NaN NaN NaN\n",
|
|||
|
|
"19 NaN NaN NaN\n",
|
|||
|
|
"20 NaN NaN NaN\n",
|
|||
|
|
"21 NaN NaN NaN\n",
|
|||
|
|
"22 NaN NaN NaN\n",
|
|||
|
|
"23 NaN NaN NaN\n",
|
|||
|
|
"24 NaN NaN NaN\n",
|
|||
|
|
"25 NaN NaN NaN\n",
|
|||
|
|
"26 NaN NaN NaN\n",
|
|||
|
|
"27 NaN NaN NaN\n",
|
|||
|
|
"28 NaN NaN NaN\n",
|
|||
|
|
"29 NaN NaN NaN\n",
|
|||
|
|
"30 NaN NaN NaN\n",
|
|||
|
|
"31 NaN NaN NaN\n",
|
|||
|
|
"32 NaN NaN NaN\n",
|
|||
|
|
"33 NaN NaN NaN\n",
|
|||
|
|
"34 NaN NaN NaN\n",
|
|||
|
|
"35 NaN NaN NaN\n",
|
|||
|
|
"36 NaN NaN NaN\n",
|
|||
|
|
"37 NaN NaN NaN\n",
|
|||
|
|
"38 NaN NaN NaN\n",
|
|||
|
|
"39 NaN NaN NaN\n",
|
|||
|
|
"40 NaN NaN NaN\n",
|
|||
|
|
"41 NaN NaN NaN\n",
|
|||
|
|
"42 NaN NaN NaN\n",
|
|||
|
|
"43 NaN NaN NaN\n",
|
|||
|
|
"44 NaN NaN NaN\n",
|
|||
|
|
"45 NaN NaN NaN\n",
|
|||
|
|
"46 NaN NaN NaN\n",
|
|||
|
|
"47 NaN NaN NaN\n",
|
|||
|
|
"48 NaN NaN NaN\n",
|
|||
|
|
"49 NaN NaN NaN\n",
|
|||
|
|
"50 NaN NaN NaN\n",
|
|||
|
|
"51 NaN NaN NaN\n",
|
|||
|
|
"52 NaN NaN NaN\n",
|
|||
|
|
"53 NaN NaN NaN\n",
|
|||
|
|
"54 NaN NaN NaN\n",
|
|||
|
|
"55 NaN NaN NaN\n",
|
|||
|
|
"56 NaN NaN NaN\n",
|
|||
|
|
"57 NaN NaN NaN\n",
|
|||
|
|
"58 NaN NaN NaN\n",
|
|||
|
|
"59 NaN NaN NaN\n",
|
|||
|
|
"60 NaN NaN NaN\n",
|
|||
|
|
"61 NaN NaN NaN\n",
|
|||
|
|
"62 NaN NaN NaN\n",
|
|||
|
|
"63 NaN NaN NaN\n",
|
|||
|
|
"64 NaN NaN NaN\n",
|
|||
|
|
"65 NaN NaN NaN\n",
|
|||
|
|
"66 NaN NaN NaN\n",
|
|||
|
|
"67 NaN NaN NaN\n",
|
|||
|
|
"68 NaN NaN NaN\n",
|
|||
|
|
"69 NaN NaN NaN\n",
|
|||
|
|
"70 NaN NaN NaN\n",
|
|||
|
|
"71 NaN NaN NaN\n",
|
|||
|
|
"72 NaN NaN NaN\n",
|
|||
|
|
"73 NaN NaN NaN\n",
|
|||
|
|
"74 NaN NaN NaN\n",
|
|||
|
|
"75 NaN NaN NaN\n",
|
|||
|
|
"76 NaN NaN NaN\n",
|
|||
|
|
"77 NaN NaN NaN\n",
|
|||
|
|
"78 NaN NaN NaN\n",
|
|||
|
|
"79 NaN NaN NaN\n",
|
|||
|
|
"80 NaN NaN NaN\n",
|
|||
|
|
"81 NaN NaN NaN\n",
|
|||
|
|
"82 NaN NaN NaN\n",
|
|||
|
|
"83 NaN NaN NaN\n",
|
|||
|
|
"84 NaN NaN NaN\n",
|
|||
|
|
"85 NaN NaN NaN\n",
|
|||
|
|
"86 NaN NaN NaN\n",
|
|||
|
|
"87 NaN NaN NaN"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 26,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"DieBC = pd.read_excel('SP-Die补偿模版.xlsx',index_col=0,header=0)\n",
|
|||
|
|
"DieBC"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 27,
|
|||
|
|
"id": "f2ae7ed6-c025-4390-8bd1-4e3b82783c36",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/html": [
|
|||
|
|
"<div>\n",
|
|||
|
|
"<style scoped>\n",
|
|||
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|||
|
|
" vertical-align: middle;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe tbody tr th {\n",
|
|||
|
|
" vertical-align: top;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"\n",
|
|||
|
|
" .dataframe thead th {\n",
|
|||
|
|
" text-align: right;\n",
|
|||
|
|
" }\n",
|
|||
|
|
"</style>\n",
|
|||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|||
|
|
" <thead>\n",
|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>对位MarkX</th>\n",
|
|||
|
|
" <th>对位MarkY</th>\n",
|
|||
|
|
" <th>Angle</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>Index</th>\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>1</th>\n",
|
|||
|
|
" <td>-0.152350</td>\n",
|
|||
|
|
" <td>0.081269</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>2</th>\n",
|
|||
|
|
" <td>-0.304979</td>\n",
|
|||
|
|
" <td>-0.025812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>3</th>\n",
|
|||
|
|
" <td>-0.193479</td>\n",
|
|||
|
|
" <td>0.192938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>4</th>\n",
|
|||
|
|
" <td>-0.223229</td>\n",
|
|||
|
|
" <td>-0.100562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>5</th>\n",
|
|||
|
|
" <td>-0.201229</td>\n",
|
|||
|
|
" <td>-0.215562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>6</th>\n",
|
|||
|
|
" <td>-0.408229</td>\n",
|
|||
|
|
" <td>0.018938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>7</th>\n",
|
|||
|
|
" <td>-0.184229</td>\n",
|
|||
|
|
" <td>0.241438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>8</th>\n",
|
|||
|
|
" <td>-0.495229</td>\n",
|
|||
|
|
" <td>0.374688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>9</th>\n",
|
|||
|
|
" <td>-0.062729</td>\n",
|
|||
|
|
" <td>-0.065312</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>10</th>\n",
|
|||
|
|
" <td>0.007521</td>\n",
|
|||
|
|
" <td>0.148188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>11</th>\n",
|
|||
|
|
" <td>-0.009729</td>\n",
|
|||
|
|
" <td>-0.290812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>12</th>\n",
|
|||
|
|
" <td>-0.094479</td>\n",
|
|||
|
|
" <td>-0.114812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>13</th>\n",
|
|||
|
|
" <td>0.010771</td>\n",
|
|||
|
|
" <td>0.078938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>14</th>\n",
|
|||
|
|
" <td>-0.017479</td>\n",
|
|||
|
|
" <td>-0.233562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>15</th>\n",
|
|||
|
|
" <td>-0.133604</td>\n",
|
|||
|
|
" <td>-0.083937</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>16</th>\n",
|
|||
|
|
" <td>-0.249729</td>\n",
|
|||
|
|
" <td>0.065688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>17</th>\n",
|
|||
|
|
" <td>-0.323729</td>\n",
|
|||
|
|
" <td>-0.177562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>18</th>\n",
|
|||
|
|
" <td>-0.173729</td>\n",
|
|||
|
|
" <td>0.117938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>19</th>\n",
|
|||
|
|
" <td>-0.230229</td>\n",
|
|||
|
|
" <td>-0.018312</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>20</th>\n",
|
|||
|
|
" <td>-0.208979</td>\n",
|
|||
|
|
" <td>-0.043812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>21</th>\n",
|
|||
|
|
" <td>-0.164729</td>\n",
|
|||
|
|
" <td>-0.042562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>22</th>\n",
|
|||
|
|
" <td>-0.108979</td>\n",
|
|||
|
|
" <td>0.027438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>23</th>\n",
|
|||
|
|
" <td>-0.039479</td>\n",
|
|||
|
|
" <td>-0.216562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>24</th>\n",
|
|||
|
|
" <td>-0.294479</td>\n",
|
|||
|
|
" <td>-0.471562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>25</th>\n",
|
|||
|
|
" <td>-0.074979</td>\n",
|
|||
|
|
" <td>0.122438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>26</th>\n",
|
|||
|
|
" <td>-0.319479</td>\n",
|
|||
|
|
" <td>-0.004562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>27</th>\n",
|
|||
|
|
" <td>-0.237479</td>\n",
|
|||
|
|
" <td>0.135938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>28</th>\n",
|
|||
|
|
" <td>0.019021</td>\n",
|
|||
|
|
" <td>0.390188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>29</th>\n",
|
|||
|
|
" <td>0.028771</td>\n",
|
|||
|
|
" <td>0.334438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>30</th>\n",
|
|||
|
|
" <td>0.038521</td>\n",
|
|||
|
|
" <td>0.278688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>31</th>\n",
|
|||
|
|
" <td>0.048271</td>\n",
|
|||
|
|
" <td>0.222938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>32</th>\n",
|
|||
|
|
" <td>0.058021</td>\n",
|
|||
|
|
" <td>0.167188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>33</th>\n",
|
|||
|
|
" <td>0.096771</td>\n",
|
|||
|
|
" <td>-0.165562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>34</th>\n",
|
|||
|
|
" <td>0.119021</td>\n",
|
|||
|
|
" <td>0.010688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>35</th>\n",
|
|||
|
|
" <td>0.166021</td>\n",
|
|||
|
|
" <td>-0.203562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>36</th>\n",
|
|||
|
|
" <td>-0.510283</td>\n",
|
|||
|
|
" <td>0.419602</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>37</th>\n",
|
|||
|
|
" <td>-0.399479</td>\n",
|
|||
|
|
" <td>0.175188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>38</th>\n",
|
|||
|
|
" <td>-0.036979</td>\n",
|
|||
|
|
" <td>0.190688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>39</th>\n",
|
|||
|
|
" <td>-0.017479</td>\n",
|
|||
|
|
" <td>0.310188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>40</th>\n",
|
|||
|
|
" <td>-0.003479</td>\n",
|
|||
|
|
" <td>0.138688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>41</th>\n",
|
|||
|
|
" <td>0.072521</td>\n",
|
|||
|
|
" <td>-0.108062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>42</th>\n",
|
|||
|
|
" <td>0.013021</td>\n",
|
|||
|
|
" <td>0.123688</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>43</th>\n",
|
|||
|
|
" <td>0.341021</td>\n",
|
|||
|
|
" <td>0.055188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>44</th>\n",
|
|||
|
|
" <td>0.417271</td>\n",
|
|||
|
|
" <td>0.034188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>45</th>\n",
|
|||
|
|
" <td>0.196771</td>\n",
|
|||
|
|
" <td>0.288938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>46</th>\n",
|
|||
|
|
" <td>0.159021</td>\n",
|
|||
|
|
" <td>-0.086562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>47</th>\n",
|
|||
|
|
" <td>-0.068979</td>\n",
|
|||
|
|
" <td>0.086188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>48</th>\n",
|
|||
|
|
" <td>0.081271</td>\n",
|
|||
|
|
" <td>0.196938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>49</th>\n",
|
|||
|
|
" <td>0.210521</td>\n",
|
|||
|
|
" <td>0.259438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>50</th>\n",
|
|||
|
|
" <td>0.339271</td>\n",
|
|||
|
|
" <td>0.198438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>51</th>\n",
|
|||
|
|
" <td>0.103271</td>\n",
|
|||
|
|
" <td>0.188354</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>52</th>\n",
|
|||
|
|
" <td>-0.132729</td>\n",
|
|||
|
|
" <td>0.178269</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>53</th>\n",
|
|||
|
|
" <td>-0.006791</td>\n",
|
|||
|
|
" <td>0.154936</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>54</th>\n",
|
|||
|
|
" <td>0.119146</td>\n",
|
|||
|
|
" <td>0.131604</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>55</th>\n",
|
|||
|
|
" <td>0.245084</td>\n",
|
|||
|
|
" <td>0.108271</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>56</th>\n",
|
|||
|
|
" <td>0.371021</td>\n",
|
|||
|
|
" <td>0.084938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>57</th>\n",
|
|||
|
|
" <td>0.225021</td>\n",
|
|||
|
|
" <td>-0.106312</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>58</th>\n",
|
|||
|
|
" <td>0.142271</td>\n",
|
|||
|
|
" <td>0.051938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>59</th>\n",
|
|||
|
|
" <td>-0.038479</td>\n",
|
|||
|
|
" <td>0.202938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>60</th>\n",
|
|||
|
|
" <td>0.010771</td>\n",
|
|||
|
|
" <td>0.093938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>61</th>\n",
|
|||
|
|
" <td>0.060021</td>\n",
|
|||
|
|
" <td>-0.015062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>62</th>\n",
|
|||
|
|
" <td>0.109271</td>\n",
|
|||
|
|
" <td>-0.124062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>63</th>\n",
|
|||
|
|
" <td>0.549271</td>\n",
|
|||
|
|
" <td>-0.173562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>64</th>\n",
|
|||
|
|
" <td>0.017771</td>\n",
|
|||
|
|
" <td>-0.152812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>65</th>\n",
|
|||
|
|
" <td>0.288271</td>\n",
|
|||
|
|
" <td>0.026188</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>66</th>\n",
|
|||
|
|
" <td>0.321271</td>\n",
|
|||
|
|
" <td>-0.122062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>67</th>\n",
|
|||
|
|
" <td>0.242855</td>\n",
|
|||
|
|
" <td>-0.019728</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>68</th>\n",
|
|||
|
|
" <td>0.164438</td>\n",
|
|||
|
|
" <td>0.082605</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>69</th>\n",
|
|||
|
|
" <td>0.086021</td>\n",
|
|||
|
|
" <td>0.184938</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>70</th>\n",
|
|||
|
|
" <td>0.289521</td>\n",
|
|||
|
|
" <td>-0.075812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>71</th>\n",
|
|||
|
|
" <td>0.162521</td>\n",
|
|||
|
|
" <td>0.039438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>72</th>\n",
|
|||
|
|
" <td>0.399271</td>\n",
|
|||
|
|
" <td>-0.192562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>73</th>\n",
|
|||
|
|
" <td>-0.012229</td>\n",
|
|||
|
|
" <td>-0.130562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>74</th>\n",
|
|||
|
|
" <td>0.116271</td>\n",
|
|||
|
|
" <td>-0.067062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>75</th>\n",
|
|||
|
|
" <td>0.149021</td>\n",
|
|||
|
|
" <td>-0.199812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>76</th>\n",
|
|||
|
|
" <td>0.061521</td>\n",
|
|||
|
|
" <td>0.012438</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>77</th>\n",
|
|||
|
|
" <td>-0.231229</td>\n",
|
|||
|
|
" <td>-0.134062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>78</th>\n",
|
|||
|
|
" <td>0.143495</td>\n",
|
|||
|
|
" <td>-0.170730</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>79</th>\n",
|
|||
|
|
" <td>0.171521</td>\n",
|
|||
|
|
" <td>-0.310562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>80</th>\n",
|
|||
|
|
" <td>0.277271</td>\n",
|
|||
|
|
" <td>-0.266812</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>81</th>\n",
|
|||
|
|
" <td>-0.035729</td>\n",
|
|||
|
|
" <td>-0.146562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>82</th>\n",
|
|||
|
|
" <td>0.077521</td>\n",
|
|||
|
|
" <td>-0.050562</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>83</th>\n",
|
|||
|
|
" <td>-0.275979</td>\n",
|
|||
|
|
" <td>-0.139062</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>84</th>\n",
|
|||
|
|
" <td>0.299495</td>\n",
|
|||
|
|
" <td>-0.467397</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>85</th>\n",
|
|||
|
|
" <td>0.173034</td>\n",
|
|||
|
|
" <td>-0.289234</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>86</th>\n",
|
|||
|
|
" <td>-0.056966</td>\n",
|
|||
|
|
" <td>-0.114734</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>87</th>\n",
|
|||
|
|
" <td>0.235034</td>\n",
|
|||
|
|
" <td>-0.349734</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" 对位MarkX 对位MarkY Angle\n",
|
|||
|
|
"Index \n",
|
|||
|
|
"1 -0.152350 0.081269 0\n",
|
|||
|
|
"2 -0.304979 -0.025812 0\n",
|
|||
|
|
"3 -0.193479 0.192938 0\n",
|
|||
|
|
"4 -0.223229 -0.100562 0\n",
|
|||
|
|
"5 -0.201229 -0.215562 0\n",
|
|||
|
|
"6 -0.408229 0.018938 0\n",
|
|||
|
|
"7 -0.184229 0.241438 0\n",
|
|||
|
|
"8 -0.495229 0.374688 0\n",
|
|||
|
|
"9 -0.062729 -0.065312 0\n",
|
|||
|
|
"10 0.007521 0.148188 0\n",
|
|||
|
|
"11 -0.009729 -0.290812 0\n",
|
|||
|
|
"12 -0.094479 -0.114812 0\n",
|
|||
|
|
"13 0.010771 0.078938 0\n",
|
|||
|
|
"14 -0.017479 -0.233562 0\n",
|
|||
|
|
"15 -0.133604 -0.083937 0\n",
|
|||
|
|
"16 -0.249729 0.065688 0\n",
|
|||
|
|
"17 -0.323729 -0.177562 0\n",
|
|||
|
|
"18 -0.173729 0.117938 0\n",
|
|||
|
|
"19 -0.230229 -0.018312 0\n",
|
|||
|
|
"20 -0.208979 -0.043812 0\n",
|
|||
|
|
"21 -0.164729 -0.042562 0\n",
|
|||
|
|
"22 -0.108979 0.027438 0\n",
|
|||
|
|
"23 -0.039479 -0.216562 0\n",
|
|||
|
|
"24 -0.294479 -0.471562 0\n",
|
|||
|
|
"25 -0.074979 0.122438 0\n",
|
|||
|
|
"26 -0.319479 -0.004562 0\n",
|
|||
|
|
"27 -0.237479 0.135938 0\n",
|
|||
|
|
"28 0.019021 0.390188 0\n",
|
|||
|
|
"29 0.028771 0.334438 0\n",
|
|||
|
|
"30 0.038521 0.278688 0\n",
|
|||
|
|
"31 0.048271 0.222938 0\n",
|
|||
|
|
"32 0.058021 0.167188 0\n",
|
|||
|
|
"33 0.096771 -0.165562 0\n",
|
|||
|
|
"34 0.119021 0.010688 0\n",
|
|||
|
|
"35 0.166021 -0.203562 0\n",
|
|||
|
|
"36 -0.510283 0.419602 0\n",
|
|||
|
|
"37 -0.399479 0.175188 0\n",
|
|||
|
|
"38 -0.036979 0.190688 0\n",
|
|||
|
|
"39 -0.017479 0.310188 0\n",
|
|||
|
|
"40 -0.003479 0.138688 0\n",
|
|||
|
|
"41 0.072521 -0.108062 0\n",
|
|||
|
|
"42 0.013021 0.123688 0\n",
|
|||
|
|
"43 0.341021 0.055188 0\n",
|
|||
|
|
"44 0.417271 0.034188 0\n",
|
|||
|
|
"45 0.196771 0.288938 0\n",
|
|||
|
|
"46 0.159021 -0.086562 0\n",
|
|||
|
|
"47 -0.068979 0.086188 0\n",
|
|||
|
|
"48 0.081271 0.196938 0\n",
|
|||
|
|
"49 0.210521 0.259438 0\n",
|
|||
|
|
"50 0.339271 0.198438 0\n",
|
|||
|
|
"51 0.103271 0.188354 0\n",
|
|||
|
|
"52 -0.132729 0.178269 0\n",
|
|||
|
|
"53 -0.006791 0.154936 0\n",
|
|||
|
|
"54 0.119146 0.131604 0\n",
|
|||
|
|
"55 0.245084 0.108271 0\n",
|
|||
|
|
"56 0.371021 0.084938 0\n",
|
|||
|
|
"57 0.225021 -0.106312 0\n",
|
|||
|
|
"58 0.142271 0.051938 0\n",
|
|||
|
|
"59 -0.038479 0.202938 0\n",
|
|||
|
|
"60 0.010771 0.093938 0\n",
|
|||
|
|
"61 0.060021 -0.015062 0\n",
|
|||
|
|
"62 0.109271 -0.124062 0\n",
|
|||
|
|
"63 0.549271 -0.173562 0\n",
|
|||
|
|
"64 0.017771 -0.152812 0\n",
|
|||
|
|
"65 0.288271 0.026188 0\n",
|
|||
|
|
"66 0.321271 -0.122062 0\n",
|
|||
|
|
"67 0.242855 -0.019728 0\n",
|
|||
|
|
"68 0.164438 0.082605 0\n",
|
|||
|
|
"69 0.086021 0.184938 0\n",
|
|||
|
|
"70 0.289521 -0.075812 0\n",
|
|||
|
|
"71 0.162521 0.039438 0\n",
|
|||
|
|
"72 0.399271 -0.192562 0\n",
|
|||
|
|
"73 -0.012229 -0.130562 0\n",
|
|||
|
|
"74 0.116271 -0.067062 0\n",
|
|||
|
|
"75 0.149021 -0.199812 0\n",
|
|||
|
|
"76 0.061521 0.012438 0\n",
|
|||
|
|
"77 -0.231229 -0.134062 0\n",
|
|||
|
|
"78 0.143495 -0.170730 0\n",
|
|||
|
|
"79 0.171521 -0.310562 0\n",
|
|||
|
|
"80 0.277271 -0.266812 0\n",
|
|||
|
|
"81 -0.035729 -0.146562 0\n",
|
|||
|
|
"82 0.077521 -0.050562 0\n",
|
|||
|
|
"83 -0.275979 -0.139062 0\n",
|
|||
|
|
"84 0.299495 -0.467397 0\n",
|
|||
|
|
"85 0.173034 -0.289234 0\n",
|
|||
|
|
"86 -0.056966 -0.114734 0\n",
|
|||
|
|
"87 0.235034 -0.349734 0"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 27,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"BC_X = BC_X.mean(axis=1)\n",
|
|||
|
|
"DieBC['对位MarkX'] = BC_X.fillna(BC_X.interpolate()).values\n",
|
|||
|
|
"BC_Y = BC_Y.mean(axis=1)\n",
|
|||
|
|
"DieBC['对位MarkY'] = BC_Y.fillna(BC_Y.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"DieBC['Angle'] = 0\n",
|
|||
|
|
"DieBC"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 28,
|
|||
|
|
"id": "2dddf61b-818e-4592-8b46-765bfa119856",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# DieBC.to_excel(f'Die1/Die1局部补偿10-12.xlsx')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 17,
|
|||
|
|
"id": "fb698448-6d4d-4477-8afd-35430692c8df",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# DieBC['Top Mark1 X'] = AlX981\n",
|
|||
|
|
"# DieBC['Top Mark1 Y'] = AlY981\n",
|
|||
|
|
"# DieBC['Top Mark2 X'] = AnX981\n",
|
|||
|
|
"# DieBC['Top Mark2 Y'] = AnY981\n",
|
|||
|
|
"# DieBC.to_excel(f'Die1/Die1设备方向偏差9-8-2.xlsx')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 18,
|
|||
|
|
"id": "94ecaf78-98bb-45a4-b66f-d36519a42cd5",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# num = -1\n",
|
|||
|
|
"# AlX982 = AlignMarkX.iloc[:,num]-AlignMarkX.iloc[:,num].mean()\n",
|
|||
|
|
"# AlX982 = AlX982.fillna(AlX982.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"# AlY982 = AlignMarkY.iloc[:,num]-AlignMarkY.iloc[:,num].mean()\n",
|
|||
|
|
"# AlY982 = AlY982.fillna(AlY982.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"# AnX982 = AngleMarkX.iloc[:,num]-AngleMarkX.iloc[:,num].mean()\n",
|
|||
|
|
"# AnX982 = AnX982.fillna(AnX982.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"# AnY982 = AngleMarkY.iloc[:,num]-AngleMarkY.iloc[:,num].mean()\n",
|
|||
|
|
"# AnY982 = AnY982.fillna(AnY982.interpolate()).values"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 19,
|
|||
|
|
"id": "21da49b6-3576-4468-8c86-070e51ac0bce",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# DieBC['Top Mark1 X'] = AlX982\n",
|
|||
|
|
"# DieBC['Top Mark1 Y'] = AlY982\n",
|
|||
|
|
"# DieBC['Top Mark2 X'] = AnX982\n",
|
|||
|
|
"# DieBC['Top Mark2 Y'] = AnY982\n",
|
|||
|
|
"# DieBC.to_excel(f'Die1/Die1设备方向偏差9-9-1.xlsx')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 10,
|
|||
|
|
"id": "1858da30",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# num = -1\n",
|
|||
|
|
"# Die3BC['Top Mark1 X'] = AlignMarkX.iloc[:,num].fillna(AlignMarkX.iloc[:,num].interpolate()).values\n",
|
|||
|
|
"# Die3BC['Top Mark1 Y'] = AlignMarkY.iloc[:,num].fillna(AlignMarkY.iloc[:,num].interpolate()).values\n",
|
|||
|
|
"# Die3BC['Top Mark2 X'] = AngleMarkX.iloc[:,num].fillna(AngleMarkX.iloc[:,num].interpolate()).values\n",
|
|||
|
|
"# Die3BC['Top Mark2 Y'] = AngleMarkY.iloc[:,num].fillna(AngleMarkY.iloc[:,num].interpolate()).values"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 11,
|
|||
|
|
"id": "30ccc3df-e5ad-430c-8ac8-0dd074d7f682",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# Die3BC.to_excel(f'Die1/Die1补偿值9-8.xlsx')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"id": "6d74cea0",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"# num = -2\n",
|
|||
|
|
"# AlX915 = AlignMarkX.iloc[:,num]-AlignMarkX.iloc[:,num].mean()\n",
|
|||
|
|
"# AlX915 = AlX915.fillna(AlX981.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"# AlY915 = AlignMarkY.iloc[:,num]-AlignMarkY.iloc[:,num].mean()\n",
|
|||
|
|
"# AlY915 = AlY915.fillna(AlY981.interpolate()).values\n",
|
|||
|
|
"\n",
|
|||
|
|
"# Ang915 = Angle.iloc[:,num] - Angle.iloc[:,num],mean()"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"metadata": {
|
|||
|
|
"kernelspec": {
|
|||
|
|
"display_name": "Python 3 (ipykernel)",
|
|||
|
|
"language": "python",
|
|||
|
|
"name": "python3"
|
|||
|
|
},
|
|||
|
|
"language_info": {
|
|||
|
|
"codemirror_mode": {
|
|||
|
|
"name": "ipython",
|
|||
|
|
"version": 3
|
|||
|
|
},
|
|||
|
|
"file_extension": ".py",
|
|||
|
|
"mimetype": "text/x-python",
|
|||
|
|
"name": "python",
|
|||
|
|
"nbconvert_exporter": "python",
|
|||
|
|
"pygments_lexer": "ipython3",
|
|||
|
|
"version": "3.10.9"
|
|||
|
|
},
|
|||
|
|
"widgets": {
|
|||
|
|
"application/vnd.jupyter.widget-state+json": {
|
|||
|
|
"state": {
|
|||
|
|
"21d8b0ba77b54fbfabcdf5f52b80df1a": {
|
|||
|
|
"model_module": "@jupyter-widgets/base",
|
|||
|
|
"model_module_version": "2.0.0",
|
|||
|
|
"model_name": "LayoutModel",
|
|||
|
|
"state": {}
|
|||
|
|
},
|
|||
|
|
"2a0670114f11457b80a6ef3ef22a34fc": {
|
|||
|
|
"model_module": "jupyter-matplotlib",
|
|||
|
|
"model_module_version": "^0.11",
|
|||
|
|
"model_name": "ToolbarModel",
|
|||
|
|
"state": {
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"collapsed": true,
|
|||
|
|
"layout": "IPY_MODEL_f7658ea254754f89ae1eaaca3822afd1",
|
|||
|
|
"orientation": "vertical",
|
|||
|
|
"toolitems": [
|
|||
|
|
[
|
|||
|
|
"Home",
|
|||
|
|
"Reset original view",
|
|||
|
|
"home",
|
|||
|
|
"home"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Back",
|
|||
|
|
"Back to previous view",
|
|||
|
|
"arrow-left",
|
|||
|
|
"back"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Forward",
|
|||
|
|
"Forward to next view",
|
|||
|
|
"arrow-right",
|
|||
|
|
"forward"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Pan",
|
|||
|
|
"Left button pans, Right button zooms\nx/y fixes axis, CTRL fixes aspect",
|
|||
|
|
"arrows",
|
|||
|
|
"pan"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Zoom",
|
|||
|
|
"Zoom to rectangle\nx/y fixes axis",
|
|||
|
|
"square-o",
|
|||
|
|
"zoom"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Download",
|
|||
|
|
"Download plot",
|
|||
|
|
"floppy-o",
|
|||
|
|
"save_figure"
|
|||
|
|
]
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"2d1533973ff749659dd783abe0db740f": {
|
|||
|
|
"model_module": "jupyter-matplotlib",
|
|||
|
|
"model_module_version": "^0.11",
|
|||
|
|
"model_name": "ToolbarModel",
|
|||
|
|
"state": {
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"collapsed": true,
|
|||
|
|
"layout": "IPY_MODEL_b8d4c7781ff5497da21ab97b922bac2f",
|
|||
|
|
"orientation": "vertical",
|
|||
|
|
"toolitems": [
|
|||
|
|
[
|
|||
|
|
"Home",
|
|||
|
|
"Reset original view",
|
|||
|
|
"home",
|
|||
|
|
"home"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Back",
|
|||
|
|
"Back to previous view",
|
|||
|
|
"arrow-left",
|
|||
|
|
"back"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Forward",
|
|||
|
|
"Forward to next view",
|
|||
|
|
"arrow-right",
|
|||
|
|
"forward"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Pan",
|
|||
|
|
"Left button pans, Right button zooms\nx/y fixes axis, CTRL fixes aspect",
|
|||
|
|
"arrows",
|
|||
|
|
"pan"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Zoom",
|
|||
|
|
"Zoom to rectangle\nx/y fixes axis",
|
|||
|
|
"square-o",
|
|||
|
|
"zoom"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Download",
|
|||
|
|
"Download plot",
|
|||
|
|
"floppy-o",
|
|||
|
|
"save_figure"
|
|||
|
|
]
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"30e39652821f45d4b6a059be76bf8b9b": {
|
|||
|
|
"model_module": "@jupyter-widgets/base",
|
|||
|
|
"model_module_version": "2.0.0",
|
|||
|
|
"model_name": "LayoutModel",
|
|||
|
|
"state": {}
|
|||
|
|
},
|
|||
|
|
"403a3e58c30643c69e94e76f12bc0587": {
|
|||
|
|
"model_module": "jupyter-matplotlib",
|
|||
|
|
"model_module_version": "^0.11",
|
|||
|
|
"model_name": "MPLCanvasModel",
|
|||
|
|
"state": {
|
|||
|
|
"_data_url": "data:image/png;base64,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
|
|||
|
|
"_figure_label": "Figure 2",
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_size": [
|
|||
|
|
800,
|
|||
|
|
550
|
|||
|
|
],
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"layout": "IPY_MODEL_6bd4aa27ce3d4da78e5e37533a8df70a",
|
|||
|
|
"toolbar": "IPY_MODEL_8a5b8401a4764aa19048fef48718488b",
|
|||
|
|
"toolbar_position": "left"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"6bd4aa27ce3d4da78e5e37533a8df70a": {
|
|||
|
|
"model_module": "@jupyter-widgets/base",
|
|||
|
|
"model_module_version": "2.0.0",
|
|||
|
|
"model_name": "LayoutModel",
|
|||
|
|
"state": {}
|
|||
|
|
},
|
|||
|
|
"8a5b8401a4764aa19048fef48718488b": {
|
|||
|
|
"model_module": "jupyter-matplotlib",
|
|||
|
|
"model_module_version": "^0.11",
|
|||
|
|
"model_name": "ToolbarModel",
|
|||
|
|
"state": {
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"collapsed": true,
|
|||
|
|
"layout": "IPY_MODEL_30e39652821f45d4b6a059be76bf8b9b",
|
|||
|
|
"orientation": "vertical",
|
|||
|
|
"toolitems": [
|
|||
|
|
[
|
|||
|
|
"Home",
|
|||
|
|
"Reset original view",
|
|||
|
|
"home",
|
|||
|
|
"home"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Back",
|
|||
|
|
"Back to previous view",
|
|||
|
|
"arrow-left",
|
|||
|
|
"back"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Forward",
|
|||
|
|
"Forward to next view",
|
|||
|
|
"arrow-right",
|
|||
|
|
"forward"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Pan",
|
|||
|
|
"Left button pans, Right button zooms\nx/y fixes axis, CTRL fixes aspect",
|
|||
|
|
"arrows",
|
|||
|
|
"pan"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Zoom",
|
|||
|
|
"Zoom to rectangle\nx/y fixes axis",
|
|||
|
|
"square-o",
|
|||
|
|
"zoom"
|
|||
|
|
],
|
|||
|
|
[
|
|||
|
|
"Download",
|
|||
|
|
"Download plot",
|
|||
|
|
"floppy-o",
|
|||
|
|
"save_figure"
|
|||
|
|
]
|
|||
|
|
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|
|||
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|
}
|
|||
|
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},
|
|||
|
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|
|||
|
|
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|
|||
|
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|
|||
|
|
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|
|||
|
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|||
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|
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|
|||
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|
|||
|
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|||
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|||
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|
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|
|||
|
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|
|||
|
|
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|
|||
|
|
"model_name": "MPLCanvasModel",
|
|||
|
|
"state": {
|
|||
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|
"_data_url": "data:image/png;base64,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
|
|||
|
|
"_figure_label": "Figure 3",
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_size": [
|
|||
|
|
800,
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|
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|
|
],
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"layout": "IPY_MODEL_8de2ee2a201f4e78b83bb73202597800",
|
|||
|
|
"toolbar": "IPY_MODEL_2d1533973ff749659dd783abe0db740f",
|
|||
|
|
"toolbar_position": "left"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"ee97a7eebb9a425eb0ade6e31817aa89": {
|
|||
|
|
"model_module": "jupyter-matplotlib",
|
|||
|
|
"model_module_version": "^0.11",
|
|||
|
|
"model_name": "MPLCanvasModel",
|
|||
|
|
"state": {
|
|||
|
|
"_data_url": "data:image/png;base64,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
|
|||
|
|
"_figure_label": "Figure 1",
|
|||
|
|
"_model_module_version": "^0.11",
|
|||
|
|
"_size": [
|
|||
|
|
800,
|
|||
|
|
550
|
|||
|
|
],
|
|||
|
|
"_view_module_version": "^0.11",
|
|||
|
|
"layout": "IPY_MODEL_21d8b0ba77b54fbfabcdf5f52b80df1a",
|
|||
|
|
"toolbar": "IPY_MODEL_2a0670114f11457b80a6ef3ef22a34fc",
|
|||
|
|
"toolbar_position": "left"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"f7658ea254754f89ae1eaaca3822afd1": {
|
|||
|
|
"model_module": "@jupyter-widgets/base",
|
|||
|
|
"model_module_version": "2.0.0",
|
|||
|
|
"model_name": "LayoutModel",
|
|||
|
|
"state": {}
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"version_major": 2,
|
|||
|
|
"version_minor": 0
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 5
|
|||
|
|
}
|