├── .spyderworkspace ├── DataDemo.py ├── DataReal.xlsx ├── IndexFirsArray.txt ├── IndexSecondArray.txt ├── IndexThirdArray.txt ├── SectionFirstPower.txt ├── SectionFirstTime.txt ├── SectionSecondPower.txt ├── SectionSecondTime.txt ├── SectionThirdPower.txt ├── SectionThirdTime.txt ├── power.txt ├── temperature.txt ├── time.txt ├── ~$DataReal.xlsx ├── 功率.txt ├── 数据显示.png ├── 时间.txt ├── 温度.txt ├── 第一段拟合效果和原数据.png ├── 第三段拟合效果和原数据.png ├── 第二段拟合效果和原数据.png └── 综合图像显示.png /.spyderworkspace: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/.spyderworkspace -------------------------------------------------------------------------------- /DataDemo.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # @Author: Kali 3 | # @Date: 2016-12-24 10:25:13 4 | # @Last Modified by: Kali 5 | # @Last Modified time: 2016-12-26 11:07:44 6 | 7 | import xlrd 8 | import matplotlib.pyplot as plt 9 | import numpy as np 10 | from scipy.optimize import leastsq 11 | import sys 12 | 13 | 14 | plt.rcParams['font.sans-serif'] = ['SimHei'] 15 | 16 | 17 | #打开excel文件 18 | data = xlrd.open_workbook('DataReal.xlsx') 19 | 20 | #获取第一张工作表（通过索引的方式） 21 | table = data.sheets()[0] 22 | 23 | # 获取时间列 24 | TimeColomn = [] 25 | for rownum in range(1,table.nrows): 26 | row = table.row_values(rownum) 27 | TimeColomn.append(row[0]) 28 | 29 | # 获取温度列 30 | TemperatureColomn = [] 31 | for rownum in range(1,table.nrows): 32 | row = table.row_values(rownum) 33 | TemperatureColomn.append(row[5]) 34 | 35 | # 获取功率列 36 | PowerColomn = [] 37 | for rownum in range(1,table.nrows): 38 | row = table.row_values(rownum) 39 | PowerColomn.append(row[4]) 40 | 41 | 42 | # 提取所需图像数据 设定阈值为 75 43 | ExpectedPowerWave = [] 44 | ExpectedTimeWave = [] 45 | ExpectedTemperatureWave = [] 46 | IndexCount = 0 47 | for Index in range(1,len(TemperatureColomn)): 48 | if(TemperatureColomn[Index - 1] == TemperatureColomn[Index]): 49 | IndexCount += 1 50 | if(IndexCount >= 75): 51 | IndexCount = 0 52 | if (PowerColomn[Index] - PowerColomn[Index - 1]) < 0: 53 | ExpectedPowerWave.append(PowerColomn[Index]) 54 | ExpectedTimeWave.append(TimeColomn[Index]) 55 | ExpectedTemperatureWave.append(TemperatureColomn[Index]) 56 | 57 | # 时间提取写入 时间.txt 文件 58 | wf = open(unicode("时间.txt","utf-8"), 'w') 59 | for i in range(0,len(ExpectedTimeWave)): 60 | wf.write(str(ExpectedTimeWave[i])) 61 | wf.write('\n') 62 | 63 | # 功率提取写入 功率.txt 文件 64 | wf = open(unicode("功率.txt","utf-8"), 'w') 65 | for i in range(0,len(ExpectedPowerWave)): 66 | wf.write(str(ExpectedPowerWave[i])) 67 | wf.write('\n') 68 | 69 | # 功率提取写入 温度.txt 文件 70 | wf = open(unicode("温度.txt","utf-8"), 'w') 71 | for i in range(0,len(ExpectedTemperatureWave)): 72 | wf.write(str(ExpectedTemperatureWave[i])) 73 | wf.write('\n') 74 | 75 | 76 | # 存储分段的索引值 77 | IndexSectionFirstArray = [] 78 | IndexSectionSecondArray = [] 79 | IndexSectionThirdArray = [] 80 | SecondFlagStart = 0 81 | ThirdFlagStart = 0 82 | SecondFlag = 0 83 | ThirdFlag = 0 84 | # IndexAArray 索引值 85 | IndexFirstArray = [] 86 | IndexSecondArray = [] 87 | IndexThirdArray = [] 88 | 89 | # 索引标志位 90 | IndexCountNum = 0 91 | IndexCountNum1 = 0 92 | IndexCountNum2 = 0 93 | # 获取 94 | for Index in range(1,len(ExpectedTemperatureWave)): 95 | # 初次判断 96 | if(ExpectedTemperatureWave[Index] - ExpectedTemperatureWave[Index - 1] <= 50): 97 | SecondFlag = 1 98 | 99 | if ThirdFlagStart == 1: 100 | if(ExpectedTemperatureWave[Index] - ExpectedTemperatureWave[Index - 1] <= 50): 101 | IndexCountNum2 += 1 102 | if IndexCountNum2 > 6: 103 | IndexThirdArray.append(Index) 104 | 105 | elif SecondFlagStart == 1 and ThirdFlagStart != 1: 106 | IndexSecondArray.append(Index) 107 | 108 | elif ThirdFlagStart != 1: 109 | IndexFirstArray.append(Index) 110 | 111 | # 开始进行第二次判断 设置权值为30 并且设置容错数值为10 112 | if SecondFlag == 1: 113 | IndexCountNum += 1 114 | if(ExpectedTemperatureWave[Index] - ExpectedTemperatureWave[Index - 1] > 30 and IndexCountNum >= 10): 115 | SecondFlagStart = 1 116 | ThirdFlag = 1 117 | # SectionSecondTemperature.append(ExpectedTemperatureWave[Index]) 118 | 119 | # 开始进行第三次判断 设置权值为50 并且设置容错数值为10 120 | if ThirdFlag == 1: 121 | IndexCountNum1 += 1 122 | if(ExpectedTemperatureWave[Index] - ExpectedTemperatureWave[Index - 1] > 30 and IndexCountNum1 >= 10): 123 | ThirdFlagStart = 1 124 | # SectionThirdTemperature.append(ExpectedTemperatureWave[Index]) 125 | 126 | 127 | 128 | ''' 分段函数对应的 x y 坐标 129 | SectionFirstTime ---> SectionFirstPower 130 | SectionSecondTime ---> SectionSecondPower 131 | SectionThirdTime ---> SectionThirdPower 132 | ''' 133 | 134 | # 根据相应的索引值提取分段函数 135 | # section time variable 136 | SectionFirstTime = [] 137 | SectionSecondTime = [] 138 | SectionThirdTime = [] 139 | # section power variable 140 | SectionFirstPower = [] 141 | SectionSecondPower = [] 142 | SectionThirdPower = [] 143 | 144 | # first section time 145 | for i in IndexFirstArray: 146 | SectionFirstTime.append(ExpectedTimeWave[i - 1]) 147 | SectionFirstPower.append(ExpectedPowerWave[i]) 148 | 149 | # second section time 150 | for j in IndexSecondArray: 151 | SectionSecondTime.append(ExpectedTimeWave[j - 1]) 152 | SectionSecondPower.append(ExpectedPowerWave[j]) 153 | 154 | # third section time 155 | for k in IndexThirdArray: 156 | SectionThirdTime.append(ExpectedTimeWave[k - 1]) 157 | SectionThirdPower.append(ExpectedPowerWave[k]) 158 | 159 | 160 | # 原始数据和提取数据对比图像 161 | plt.figure(1) 162 | plt.plot(TimeColomn,TemperatureColomn,'r') 163 | plt.plot(TimeColomn,PowerColomn,'g') 164 | plt.plot(ExpectedTimeWave,ExpectedPowerWave,'b') 165 | plt.xlabel('time') 166 | plt.ylabel('temprature/power') 167 | plt.savefig(u'数据显示.png') 168 | 169 | 170 | ''' 分段函数对应的 x y 坐标 171 | SectionFirstTime ---> SectionFirstPower 172 | SectionSecondTime ---> SectionSecondPower 173 | SectionThirdTime ---> SectionThirdPower 174 | ''' 175 | 176 | # 分段曲线拟合 177 | Polynomial1 = np.poly1d(np.polyfit(SectionFirstTime,SectionFirstPower,3)) 178 | Polynomial2 = np.poly1d(np.polyfit(SectionSecondTime,SectionSecondPower,3)) 179 | Polynomial3 = np.poly1d(np.polyfit(SectionThirdTime,SectionThirdPower,3)) 180 | 181 | 182 | 183 | # 打印预测函数 184 | print(Polynomial1) 185 | print(Polynomial2) 186 | print(Polynomial3) 187 | 188 | 189 | # 画出散点图和原坐标系比较 190 | plt.scatter(SectionFirstTime,SectionFirstPower,marker='o',color='m',label='1',s=80) 191 | plt.scatter(SectionSecondTime,SectionSecondPower,marker='o',color='c',label='2',s=80) 192 | plt.scatter(SectionThirdTime,SectionThirdPower,marker='o',color='r',label='3',s=80) 193 | plt.savefig(u'综合图像显示.png') 194 | 195 | 196 | 197 | # 分段函数散点图以及集合曲线图 198 | plt.figure(2) 199 | plt.plot(SectionFirstTime,SectionFirstPower,'r*') 200 | Coff1 = np.polyfit(SectionFirstTime,SectionFirstPower,3) 201 | y = np.polyval(Coff1,SectionFirstTime) 202 | plt.plot(SectionFirstTime,y,linestyle='-') 203 | plt.savefig(u'第一段拟合效果和原数据.png') 204 | 205 | 206 | plt.figure(3) 207 | plt.plot(SectionSecondTime,SectionSecondPower,'b*') 208 | Coff2 = np.polyfit(SectionSecondTime,SectionSecondPower,3) 209 | y = np.polyval(Coff2,SectionSecondTime) 210 | plt.plot(SectionSecondTime,y,linestyle='-') 211 | #plt.plot(SectionSecondTime,SectionSecondPower,linestyle='*') 212 | plt.savefig(u'第二段拟合效果和原数据.png') 213 | 214 | 215 | plt.figure(4) 216 | plt.plot(SectionThirdTime,SectionThirdPower,'g*') 217 | Coff3 = np.polyfit(SectionThirdTime,SectionThirdPower,3) 218 | y = np.polyval(Coff3,SectionThirdTime) 219 | plt.plot(SectionThirdTime,y,linestyle='-') 220 | #plt.plot(SectionThirdTime,SectionThirdPower,linestyle='*') 221 | plt.savefig(u'第三段拟合效果和原数据.png') 222 | 223 | 224 | 225 | # 打印三个阶段的表达式 226 | print ("\n\n\n") 227 | print ("first") 228 | print (np.poly1d(Coff1)) 229 | print ("\n") 230 | print ("second") 231 | print (np.poly1d(Coff2)) 232 | print ("\n") 233 | print ("third") 234 | print (np.poly1d(Coff3)) 235 | 236 | 237 | ''' 写入文件测试Demo 238 | IndexFirstArray IndexSecondArray IndexThirdArray 文件操作 239 | ''' 240 | # IndexFirstArray 提取写入 IndexFirstArray.txt 文件 241 | wf = open("IndexFirsArray.txt", 'w') 242 | for i in range(0,len(IndexFirstArray)): 243 | wf.write(str(IndexFirstArray[i])) 244 | wf.write('\n') 245 | 246 | # IndexSecondArray 提取写入 IndexSecondArray.txt 文件 247 | wf = open("IndexSecondArray.txt", 'w') 248 | for i in range(0,len(IndexSecondArray)): 249 | wf.write(str(IndexSecondArray[i])) 250 | wf.write('\n') 251 | 252 | # IndexThirdArray 提取写入 IndexThirdArray.txt 文件 253 | wf = open("IndexThirdArray.txt", 'w') 254 | for i in range(0,len(IndexThirdArray)): 255 | wf.write(str(IndexThirdArray[i])) 256 | wf.write('\n') 257 | 258 | 259 | ''' 写入文件测试Demo 260 | SectionFirstPower SectionSecondPower SectionThirdPower 文件操作 261 | ''' 262 | # SectionFirstPower 提取写入 SectionFirstPower.txt 文件 263 | wf = open("SectionFirstPower.txt", 'w') 264 | for i in range(0,len(SectionFirstPower)): 265 | wf.write(str(SectionFirstPower[i])) 266 | wf.write('\n') 267 | 268 | # SectionSecondPower 提取写入 SectionSecondPower.txt 文件 269 | wf = open("SectionSecondPower.txt", 'w') 270 | for i in range(0,len(SectionSecondPower)): 271 | wf.write(str(SectionSecondPower[i])) 272 | wf.write('\n') 273 | 274 | # SectionThirdTime 提取写入 SectionThirdTime.txt 文件 275 | wf = open("SectionThirdPower.txt", 'w') 276 | for i in range(0,len(SectionThirdPower)): 277 | wf.write(str(SectionThirdPower[i])) 278 | wf.write('\n') 279 | 280 | 281 | ''' 写入文件测试Demo 282 | SectionFirstTime SectionSecondTime SectionThirdTime 文件操作 283 | ''' 284 | # SectionFirstTime 提取写入 SectionFirstTime.txt 文件 285 | wf = open("SectionFirstTime.txt", 'w') 286 | for i in range(0,len(SectionFirstTime)): 287 | wf.write(str(SectionFirstTime[i])) 288 | wf.write('\n') 289 | 290 | # SectionSecondTime 提取写入 SectionSecondTime.txt 文件 291 | wf = open("SectionSecondTime.txt", 'w') 292 | for i in range(0,len(SectionSecondTime)): 293 | wf.write(str(SectionSecondTime[i])) 294 | wf.write('\n') 295 | 296 | # SectionThirdTime 提取写入 SectionThirdTime.txt 文件 297 | wf = open("SectionThirdTime.txt", 'w') 298 | for i in range(0,len(SectionThirdTime)): 299 | wf.write(str(SectionThirdTime[i])) 300 | wf.write('\n') 301 | 302 | 303 | 304 | 305 | -------------------------------------------------------------------------------- /DataReal.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/DataReal.xlsx -------------------------------------------------------------------------------- /IndexFirsArray.txt: -------------------------------------------------------------------------------- 1 | 5 2 | 6 3 | 7 4 | 8 5 | 9 6 | 10 7 | 11 8 | 12 9 | 13 10 | 14 11 | 15 12 | 16 13 | 17 14 | 18 15 | 19 16 | 20 17 | 21 18 | 22 19 | 23 20 | 24 21 | 25 22 | 26 23 | 27 24 | 28 25 | 29 26 | 30 27 | 31 28 | 32 29 | 33 30 | 34 31 | 35 32 | 36 33 | 37 34 | 38 35 | 39 36 | 40 37 | 41 38 | -------------------------------------------------------------------------------- /IndexSecondArray.txt: -------------------------------------------------------------------------------- 1 | 44 2 | 46 3 | 47 4 | 48 5 | 49 6 | 50 7 | 51 8 | 52 9 | 53 10 | 54 11 | 55 12 | 56 13 | 57 14 | 58 15 | 59 16 | 60 17 | 61 18 | 62 19 | 63 20 | 64 21 | 65 22 | 66 23 | 67 24 | 68 25 | 69 26 | 70 27 | 71 28 | 72 29 | 73 30 | 74 31 | 75 32 | 76 33 | 77 34 | 78 35 | 79 36 | 80 37 | 81 38 | 82 39 | 83 40 | 84 41 | 85 42 | 86 43 | 87 44 | 88 45 | -------------------------------------------------------------------------------- /IndexThirdArray.txt: -------------------------------------------------------------------------------- 1 | 95 2 | 97 3 | 98 4 | 99 5 | 100 6 | 101 7 | 102 8 | 103 9 | 104 10 | 105 11 | 106 12 | 107 13 | 108 14 | 109 15 | 110 16 | 111 17 | 112 18 | 113 19 | 114 20 | 115 21 | 116 22 | 117 23 | 118 24 | 119 25 | 120 26 | 121 27 | 122 28 | 123 29 | 124 30 | 125 31 | 126 32 | 127 33 | 128 34 | 129 35 | 130 36 | 131 37 | 132 38 | 133 39 | 134 40 | 135 41 | 136 42 | 137 43 | 138 44 | 139 45 | -------------------------------------------------------------------------------- /SectionFirstPower.txt: -------------------------------------------------------------------------------- 1 | 4278.38600208 2 | 4312.69150267 3 | 4258.75634119 4 | 4264.61063828 5 | 4236.83183422 6 | 4165.93414493 7 | 4302.32252855 8 | 3997.89109519 9 | 3640.70172332 10 | 3893.37003888 11 | 3819.45137584 12 | 3787.01132861 13 | 3726.86092798 14 | 3586.39895138 15 | 3316.95090865 16 | 3502.97385821 17 | 3395.13502393 18 | 3160.24248601 19 | 3236.32974593 20 | 3224.78342759 21 | 2767.87448674 22 | 2797.1895679 23 | 3084.90993258 24 | 3017.26411671 25 | 3081.22373009 26 | 2939.44149776 27 | 2550.68267668 28 | 2810.91165382 29 | 2371.3254727 30 | 2804.06291708 31 | 2319.86911841 32 | 2771.72383109 33 | 2725.8896098 34 | 2914.81899257 35 | 2813.9798779 36 | 2658.03506449 37 | 4276.9567484 38 | -------------------------------------------------------------------------------- /SectionFirstTime.txt: -------------------------------------------------------------------------------- 1 | 2458.5 2 | 2631.0 3 | 2671.6 4 | 2712.2 5 | 2751.3 6 | 2794.4 7 | 2835.0 8 | 2882.6 9 | 2967.9 10 | 3046.1 11 | 3096.7 12 | 3134.3 13 | 3174.9 14 | 3346.9 15 | 3391.0 16 | 3665.8 17 | 3769.0 18 | 3836.7 19 | 3968.1 20 | 4015.2 21 | 4060.8 22 | 4250.9 23 | 4302.5 24 | 4348.6 25 | 4392.2 26 | 4429.8 27 | 4473.0 28 | 4656.5 29 | 5130.7 30 | 5168.8 31 | 5215.0 32 | 5393.4 33 | 5437.1 34 | 5514.3 35 | 5551.9 36 | 5684.2 37 | 5768.0 38 | -------------------------------------------------------------------------------- /SectionSecondPower.txt: -------------------------------------------------------------------------------- 1 | 5634.69466216 2 | 4768.20368312 3 | 4442.64718816 4 | 4155.05173899 5 | 4155.71201407 6 | 4217.79936713 7 | 3996.72759006 8 | 3965.29871409 9 | 3699.93332297 10 | 4015.70295144 11 | 3705.84957552 12 | 3712.3050328 13 | 3931.22781979 14 | 3951.99348084 15 | 3628.09345 16 | 3925.89476607 17 | 3850.75136991 18 | 3904.11429645 19 | 3693.94125856 20 | 3745.47167534 21 | 3742.21410346 22 | 3705.5659522 23 | 3817.41420697 24 | 3550.87036311 25 | 3694.85907228 26 | 3676.2634284 27 | 3725.43011545 28 | 3587.78279069 29 | 3755.71038192 30 | 3848.3687435 31 | 3595.71773113 32 | 3721.45653109 33 | 3613.3575601 34 | 3679.59305359 35 | 3331.30803368 36 | 3695.85704532 37 | 3887.6626197 38 | 3568.45054024 39 | 3391.18563632 40 | 3301.74914905 41 | 3549.96647508 42 | 3582.70126539 43 | 3495.6838642 44 | 5088.40362043 45 | -------------------------------------------------------------------------------- /SectionSecondTime.txt: -------------------------------------------------------------------------------- 1 | 6960.7 2 | 7939.3 3 | 8154.9 4 | 8286.3 5 | 8580.1 6 | 8695.4 7 | 8744.0 8 | 8829.8 9 | 8867.4 10 | 9008.7 11 | 9053.4 12 | 9097.5 13 | 9141.1 14 | 9188.2 15 | 9276.5 16 | 9322.6 17 | 9413.3 18 | 9460.5 19 | 9500.6 20 | 9540.7 21 | 9583.8 22 | 9668.0 23 | 9754.3 24 | 9950.3 25 | 9992.4 26 | 10034.5 27 | 10072.1 28 | 10200.0 29 | 10239.6 30 | 10324.8 31 | 10410.0 32 | 10447.6 33 | 10489.3 34 | 10617.1 35 | 10654.7 36 | 10699.8 37 | 10746.0 38 | 10788.6 39 | 10828.2 40 | 10992.1 41 | 11107.9 42 | 11191.7 43 | 11276.9 44 | 11364.1 45 | -------------------------------------------------------------------------------- /SectionThirdPower.txt: -------------------------------------------------------------------------------- 1 | 6712.38954377 2 | 6088.96965604 3 | 5680.24704414 4 | 5465.96029899 5 | 5408.34903287 6 | 5710.08645173 7 | 5372.16529639 8 | 5338.95370713 9 | 5291.10547448 10 | 5058.55965755 11 | 5098.66096388 12 | 5048.6933419 13 | 4959.77633131 14 | 4964.69043658 15 | 4927.81311766 16 | 4885.56585235 17 | 4796.10147907 18 | 4768.18161679 19 | 4905.03231942 20 | 4472.70672208 21 | 4947.86051457 22 | 4724.73578964 23 | 4815.13623247 24 | 4771.98617031 25 | 4633.14504686 26 | 4596.97005723 27 | 4853.50287259 28 | 4425.30705595 29 | 4761.24397389 30 | 4643.25499278 31 | 4429.88569762 32 | 4580.54470766 33 | 4659.14572756 34 | 4877.52352476 35 | 4680.39745403 36 | 4669.63835279 37 | 4403.55933941 38 | 4582.49420012 39 | 4627.30162705 40 | 4523.20778107 41 | 4716.46510847 42 | 4785.14268968 43 | 4658.42865852 44 | 4550.45808446 45 | -------------------------------------------------------------------------------- /SectionThirdTime.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/SectionThirdTime.txt -------------------------------------------------------------------------------- /power.txt: -------------------------------------------------------------------------------- 1 | 6078.17175685 2 | 4670.72521467 3 | 3300.50054826 4 | 5454.53976218 5 | 3977.01950191 6 | 4278.38600208 7 | 4312.69150267 8 | 4258.75634119 9 | 4264.61063828 10 | 4236.83183422 11 | 4165.93414493 12 | 4302.32252855 13 | 3997.89109519 14 | 3640.70172332 15 | 3893.37003888 16 | 3819.45137584 17 | 3787.01132861 18 | 3726.86092798 19 | 3586.39895138 20 | 3316.95090865 21 | 3502.97385821 22 | 3395.13502393 23 | 3160.24248601 24 | 3236.32974593 25 | 3224.78342759 26 | 2767.87448674 27 | 2797.1895679 28 | 3084.90993258 29 | 3017.26411671 30 | 3081.22373009 31 | 2939.44149776 32 | 2550.68267668 33 | 2810.91165382 34 | 2371.3254727 35 | 2804.06291708 36 | 2319.86911841 37 | 2771.72383109 38 | 2725.8896098 39 | 2914.81899257 40 | 2813.9798779 41 | 2658.03506449 42 | 4276.9567484 43 | 4941.80637346 44 | 5174.28129754 45 | 5634.69466216 46 | 4838.09404631 47 | 4768.20368312 48 | 4442.64718816 49 | 4155.05173899 50 | 4155.71201407 51 | 4217.79936713 52 | 3996.72759006 53 | 3965.29871409 54 | 3699.93332297 55 | 4015.70295144 56 | 3705.84957552 57 | 3712.3050328 58 | 3931.22781979 59 | 3951.99348084 60 | 3628.09345 61 | 3925.89476607 62 | 3850.75136991 63 | 3904.11429645 64 | 3693.94125856 65 | 3745.47167534 66 | 3742.21410346 67 | 3705.5659522 68 | 3817.41420697 69 | 3550.87036311 70 | 3694.85907228 71 | 3676.2634284 72 | 3725.43011545 73 | 3587.78279069 74 | 3755.71038192 75 | 3848.3687435 76 | 3595.71773113 77 | 3721.45653109 78 | 3613.3575601 79 | 3679.59305359 80 | 3331.30803368 81 | 3695.85704532 82 | 3887.6626197 83 | 3568.45054024 84 | 3391.18563632 85 | 3301.74914905 86 | 3549.96647508 87 | 3582.70126539 88 | 3495.6838642 89 | 5088.40362043 90 | 5644.23727484 91 | 5902.19144573 92 | 6036.06629454 93 | 6247.57188572 94 | 6426.0584224 95 | 6594.7765909 96 | 6712.38954377 97 | 7026.59937388 98 | 6088.96965604 99 | 5680.24704414 100 | 5465.96029899 101 | 5408.34903287 102 | 5710.08645173 103 | 5372.16529639 104 | 5338.95370713 105 | 5291.10547448 106 | 5058.55965755 107 | 5098.66096388 108 | 5048.6933419 109 | 4959.77633131 110 | 4964.69043658 111 | 4927.81311766 112 | 4885.56585235 113 | 4796.10147907 114 | 4768.18161679 115 | 4905.03231942 116 | 4472.70672208 117 | 4947.86051457 118 | 4724.73578964 119 | 4815.13623247 120 | 4771.98617031 121 | 4633.14504686 122 | 4596.97005723 123 | 4853.50287259 124 | 4425.30705595 125 | 4761.24397389 126 | 4643.25499278 127 | 4429.88569762 128 | 4580.54470766 129 | 4659.14572756 130 | 4877.52352476 131 | 4680.39745403 132 | 4669.63835279 133 | 4403.55933941 134 | 4582.49420012 135 | 4627.30162705 136 | 4523.20778107 137 | 4716.46510847 138 | 4785.14268968 139 | 4658.42865852 140 | 4550.45808446 141 | -------------------------------------------------------------------------------- /temperature.txt: -------------------------------------------------------------------------------- 1 | 22.0 2 | 76.5 3 | 182.0 4 | 428.3 5 | 501.5 6 | 500.1 7 | 500.3 8 | 500.3 9 | 500.2 10 | 500.1 11 | 500.1 12 | 500.1 13 | 500.1 14 | 500.1 15 | 500.1 16 | 500.1 17 | 500.1 18 | 500.0 19 | 500.1 20 | 500.1 21 | 500.0 22 | 500.0 23 | 500.1 24 | 500.0 25 | 500.0 26 | 500.1 27 | 500.1 28 | 500.0 29 | 500.0 30 | 500.0 31 | 500.1 32 | 500.1 33 | 500.0 34 | 500.1 35 | 500.0 36 | 500.0 37 | 500.0 38 | 500.0 39 | 500.0 40 | 500.1 41 | 500.0 42 | 520.7 43 | 574.2 44 | 656.8 45 | 684.4 46 | 800.5 47 | 800.1 48 | 800.2 49 | 800.1 50 | 800.0 51 | 800.0 52 | 800.1 53 | 800.1 54 | 800.0 55 | 800.0 56 | 800.1 57 | 800.1 58 | 800.0 59 | 800.0 60 | 800.1 61 | 800.0 62 | 800.1 63 | 800.0 64 | 800.1 65 | 800.0 66 | 800.0 67 | 800.0 68 | 800.0 69 | 800.1 70 | 800.0 71 | 800.0 72 | 800.0 73 | 800.0 74 | 800.0 75 | 800.0 76 | 800.0 77 | 800.0 78 | 800.0 79 | 800.0 80 | 800.1 81 | 800.0 82 | 800.0 83 | 800.0 84 | 800.1 85 | 800.1 86 | 800.0 87 | 800.0 88 | 800.0 89 | 836.6 90 | 862.5 91 | 887.0 92 | 910.2 93 | 957.3 94 | 983.2 95 | 1006.9 96 | 1033.5 97 | 1084.0 98 | 1100.8 99 | 1100.4 100 | 1100.4 101 | 1100.3 102 | 1100.1 103 | 1100.1 104 | 1100.1 105 | 1100.1 106 | 1100.1 107 | 1100.0 108 | 1100.0 109 | 1100.0 110 | 1100.1 111 | 1100.0 112 | 1100.1 113 | 1100.0 114 | 1100.0 115 | 1100.1 116 | 1100.1 117 | 1100.0 118 | 1100.0 119 | 1100.0 120 | 1100.0 121 | 1100.1 122 | 1100.0 123 | 1100.0 124 | 1100.1 125 | 1100.0 126 | 1100.0 127 | 1100.1 128 | 1100.0 129 | 1100.0 130 | 1100.0 131 | 1100.0 132 | 1100.0 133 | 1100.1 134 | 1100.0 135 | 1100.0 136 | 1100.1 137 | 1100.0 138 | 1100.0 139 | 1100.0 140 | 1100.0 141 | -------------------------------------------------------------------------------- /time.txt: -------------------------------------------------------------------------------- 1 | 44.5 2 | 304.2 3 | 825.1 4 | 2061.9 5 | 2458.5 6 | 2631.0 7 | 2671.6 8 | 2712.2 9 | 2751.3 10 | 2794.4 11 | 2835.0 12 | 2882.6 13 | 2967.9 14 | 3046.1 15 | 3096.7 16 | 3134.3 17 | 3174.9 18 | 3346.9 19 | 3391.0 20 | 3665.8 21 | 3769.0 22 | 3836.7 23 | 3968.1 24 | 4015.2 25 | 4060.8 26 | 4250.9 27 | 4302.5 28 | 4348.6 29 | 4392.2 30 | 4429.8 31 | 4473.0 32 | 4656.5 33 | 5130.7 34 | 5168.8 35 | 5215.0 36 | 5393.4 37 | 5437.1 38 | 5514.3 39 | 5551.9 40 | 5684.2 41 | 5768.0 42 | 6141.5 43 | 6465.4 44 | 6960.7 45 | 7126.6 46 | 7939.3 47 | 8154.9 48 | 8286.3 49 | 8580.1 50 | 8695.4 51 | 8744.0 52 | 8829.8 53 | 8867.4 54 | 9008.7 55 | 9053.4 56 | 9097.5 57 | 9141.1 58 | 9188.2 59 | 9276.5 60 | 9322.6 61 | 9413.3 62 | 9460.5 63 | 9500.6 64 | 9540.7 65 | 9583.8 66 | 9668.0 67 | 9754.3 68 | 9950.3 69 | 9992.4 70 | 10034.5 71 | 10072.1 72 | 10200.0 73 | 10239.6 74 | 10324.8 75 | 10410.0 76 | 10447.6 77 | 10489.3 78 | 10617.1 79 | 10654.7 80 | 10699.8 81 | 10746.0 82 | 10788.6 83 | 10828.2 84 | 10992.1 85 | 11107.9 86 | 11191.7 87 | 11276.9 88 | 11364.1 89 | 11640.4 90 | 11795.8 91 | 11942.7 92 | 12081.1 93 | 12364.3 94 | 12519.3 95 | 12662.1 96 | 12821.6 97 | 13124.4 98 | 13281.3 99 | 13419.2 100 | 13461.8 101 | 13507.9 102 | 13558.6 103 | 13657.8 104 | 13706.0 105 | 13902.5 106 | 13945.1 107 | 14082.0 108 | 14398.4 109 | 14443.0 110 | 14488.1 111 | 14531.2 112 | 14709.2 113 | 14796.9 114 | 14839.5 115 | 14927.3 116 | 15011.5 117 | 15138.9 118 | 15180.5 119 | 15230.1 120 | 15277.7 121 | 15328.9 122 | 15377.0 123 | 15466.2 124 | 15508.4 125 | 15679.3 126 | 15766.1 127 | 15892.4 128 | 15933.5 129 | 15981.6 130 | 16020.2 131 | 16100.5 132 | 16146.1 133 | 16191.7 134 | 16233.8 135 | 16322.1 136 | 16369.2 137 | 16493.5 138 | 16580.8 139 | 16619.4 140 | 16762.3 141 | -------------------------------------------------------------------------------- /~$DataReal.xlsx: -------------------------------------------------------------------------------- 1 | lyx lyx -------------------------------------------------------------------------------- /功率.txt: -------------------------------------------------------------------------------- 1 | 6078.17175685 2 | 4670.72521467 3 | 3300.50054826 4 | 5454.53976218 5 | 3977.01950191 6 | 4278.38600208 7 | 4312.69150267 8 | 4258.75634119 9 | 4264.61063828 10 | 4236.83183422 11 | 4165.93414493 12 | 4302.32252855 13 | 3997.89109519 14 | 3640.70172332 15 | 3893.37003888 16 | 3819.45137584 17 | 3787.01132861 18 | 3726.86092798 19 | 3586.39895138 20 | 3316.95090865 21 | 3502.97385821 22 | 3395.13502393 23 | 3160.24248601 24 | 3236.32974593 25 | 3224.78342759 26 | 2767.87448674 27 | 2797.1895679 28 | 3084.90993258 29 | 3017.26411671 30 | 3081.22373009 31 | 2939.44149776 32 | 2550.68267668 33 | 2810.91165382 34 | 2371.3254727 35 | 2804.06291708 36 | 2319.86911841 37 | 2771.72383109 38 | 2725.8896098 39 | 2914.81899257 40 | 2813.9798779 41 | 2658.03506449 42 | 4276.9567484 43 | 4941.80637346 44 | 5174.28129754 45 | 5634.69466216 46 | 4838.09404631 47 | 4768.20368312 48 | 4442.64718816 49 | 4155.05173899 50 | 4155.71201407 51 | 4217.79936713 52 | 3996.72759006 53 | 3965.29871409 54 | 3699.93332297 55 | 4015.70295144 56 | 3705.84957552 57 | 3712.3050328 58 | 3931.22781979 59 | 3951.99348084 60 | 3628.09345 61 | 3925.89476607 62 | 3850.75136991 63 | 3904.11429645 64 | 3693.94125856 65 | 3745.47167534 66 | 3742.21410346 67 | 3705.5659522 68 | 3817.41420697 69 | 3550.87036311 70 | 3694.85907228 71 | 3676.2634284 72 | 3725.43011545 73 | 3587.78279069 74 | 3755.71038192 75 | 3848.3687435 76 | 3595.71773113 77 | 3721.45653109 78 | 3613.3575601 79 | 3679.59305359 80 | 3331.30803368 81 | 3695.85704532 82 | 3887.6626197 83 | 3568.45054024 84 | 3391.18563632 85 | 3301.74914905 86 | 3549.96647508 87 | 3582.70126539 88 | 3495.6838642 89 | 5088.40362043 90 | 5644.23727484 91 | 5902.19144573 92 | 6036.06629454 93 | 6247.57188572 94 | 6426.0584224 95 | 6594.7765909 96 | 6712.38954377 97 | 7026.59937388 98 | 6088.96965604 99 | 5680.24704414 100 | 5465.96029899 101 | 5408.34903287 102 | 5710.08645173 103 | 5372.16529639 104 | 5338.95370713 105 | 5291.10547448 106 | 5058.55965755 107 | 5098.66096388 108 | 5048.6933419 109 | 4959.77633131 110 | 4964.69043658 111 | 4927.81311766 112 | 4885.56585235 113 | 4796.10147907 114 | 4768.18161679 115 | 4905.03231942 116 | 4472.70672208 117 | 4947.86051457 118 | 4724.73578964 119 | 4815.13623247 120 | 4771.98617031 121 | 4633.14504686 122 | 4596.97005723 123 | 4853.50287259 124 | 4425.30705595 125 | 4761.24397389 126 | 4643.25499278 127 | 4429.88569762 128 | 4580.54470766 129 | 4659.14572756 130 | 4877.52352476 131 | 4680.39745403 132 | 4669.63835279 133 | 4403.55933941 134 | 4582.49420012 135 | 4627.30162705 136 | 4523.20778107 137 | 4716.46510847 138 | 4785.14268968 139 | 4658.42865852 140 | 4550.45808446 141 | -------------------------------------------------------------------------------- /数据显示.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/数据显示.png -------------------------------------------------------------------------------- /时间.txt: -------------------------------------------------------------------------------- 1 | 44.5 2 | 304.2 3 | 825.1 4 | 2061.9 5 | 2458.5 6 | 2631.0 7 | 2671.6 8 | 2712.2 9 | 2751.3 10 | 2794.4 11 | 2835.0 12 | 2882.6 13 | 2967.9 14 | 3046.1 15 | 3096.7 16 | 3134.3 17 | 3174.9 18 | 3346.9 19 | 3391.0 20 | 3665.8 21 | 3769.0 22 | 3836.7 23 | 3968.1 24 | 4015.2 25 | 4060.8 26 | 4250.9 27 | 4302.5 28 | 4348.6 29 | 4392.2 30 | 4429.8 31 | 4473.0 32 | 4656.5 33 | 5130.7 34 | 5168.8 35 | 5215.0 36 | 5393.4 37 | 5437.1 38 | 5514.3 39 | 5551.9 40 | 5684.2 41 | 5768.0 42 | 6141.5 43 | 6465.4 44 | 6960.7 45 | 7126.6 46 | 7939.3 47 | 8154.9 48 | 8286.3 49 | 8580.1 50 | 8695.4 51 | 8744.0 52 | 8829.8 53 | 8867.4 54 | 9008.7 55 | 9053.4 56 | 9097.5 57 | 9141.1 58 | 9188.2 59 | 9276.5 60 | 9322.6 61 | 9413.3 62 | 9460.5 63 | 9500.6 64 | 9540.7 65 | 9583.8 66 | 9668.0 67 | 9754.3 68 | 9950.3 69 | 9992.4 70 | 10034.5 71 | 10072.1 72 | 10200.0 73 | 10239.6 74 | 10324.8 75 | 10410.0 76 | 10447.6 77 | 10489.3 78 | 10617.1 79 | 10654.7 80 | 10699.8 81 | 10746.0 82 | 10788.6 83 | 10828.2 84 | 10992.1 85 | 11107.9 86 | 11191.7 87 | 11276.9 88 | 11364.1 89 | 11640.4 90 | 11795.8 91 | 11942.7 92 | 12081.1 93 | 12364.3 94 | 12519.3 95 | 12662.1 96 | 12821.6 97 | 13124.4 98 | 13281.3 99 | 13419.2 100 | 13461.8 101 | 13507.9 102 | 13558.6 103 | 13657.8 104 | 13706.0 105 | 13902.5 106 | 13945.1 107 | 14082.0 108 | 14398.4 109 | 14443.0 110 | 14488.1 111 | 14531.2 112 | 14709.2 113 | 14796.9 114 | 14839.5 115 | 14927.3 116 | 15011.5 117 | 15138.9 118 | 15180.5 119 | 15230.1 120 | 15277.7 121 | 15328.9 122 | 15377.0 123 | 15466.2 124 | 15508.4 125 | 15679.3 126 | 15766.1 127 | 15892.4 128 | 15933.5 129 | 15981.6 130 | 16020.2 131 | 16100.5 132 | 16146.1 133 | 16191.7 134 | 16233.8 135 | 16322.1 136 | 16369.2 137 | 16493.5 138 | 16580.8 139 | 16619.4 140 | 16762.3 141 | -------------------------------------------------------------------------------- /温度.txt: -------------------------------------------------------------------------------- 1 | 22.0 2 | 76.5 3 | 182.0 4 | 428.3 5 | 501.5 6 | 500.1 7 | 500.3 8 | 500.3 9 | 500.2 10 | 500.1 11 | 500.1 12 | 500.1 13 | 500.1 14 | 500.1 15 | 500.1 16 | 500.1 17 | 500.1 18 | 500.0 19 | 500.1 20 | 500.1 21 | 500.0 22 | 500.0 23 | 500.1 24 | 500.0 25 | 500.0 26 | 500.1 27 | 500.1 28 | 500.0 29 | 500.0 30 | 500.0 31 | 500.1 32 | 500.1 33 | 500.0 34 | 500.1 35 | 500.0 36 | 500.0 37 | 500.0 38 | 500.0 39 | 500.0 40 | 500.1 41 | 500.0 42 | 520.7 43 | 574.2 44 | 656.8 45 | 684.4 46 | 800.5 47 | 800.1 48 | 800.2 49 | 800.1 50 | 800.0 51 | 800.0 52 | 800.1 53 | 800.1 54 | 800.0 55 | 800.0 56 | 800.1 57 | 800.1 58 | 800.0 59 | 800.0 60 | 800.1 61 | 800.0 62 | 800.1 63 | 800.0 64 | 800.1 65 | 800.0 66 | 800.0 67 | 800.0 68 | 800.0 69 | 800.1 70 | 800.0 71 | 800.0 72 | 800.0 73 | 800.0 74 | 800.0 75 | 800.0 76 | 800.0 77 | 800.0 78 | 800.0 79 | 800.0 80 | 800.1 81 | 800.0 82 | 800.0 83 | 800.0 84 | 800.1 85 | 800.1 86 | 800.0 87 | 800.0 88 | 800.0 89 | 836.6 90 | 862.5 91 | 887.0 92 | 910.2 93 | 957.3 94 | 983.2 95 | 1006.9 96 | 1033.5 97 | 1084.0 98 | 1100.8 99 | 1100.4 100 | 1100.4 101 | 1100.3 102 | 1100.1 103 | 1100.1 104 | 1100.1 105 | 1100.1 106 | 1100.1 107 | 1100.0 108 | 1100.0 109 | 1100.0 110 | 1100.1 111 | 1100.0 112 | 1100.1 113 | 1100.0 114 | 1100.0 115 | 1100.1 116 | 1100.1 117 | 1100.0 118 | 1100.0 119 | 1100.0 120 | 1100.0 121 | 1100.1 122 | 1100.0 123 | 1100.0 124 | 1100.1 125 | 1100.0 126 | 1100.0 127 | 1100.1 128 | 1100.0 129 | 1100.0 130 | 1100.0 131 | 1100.0 132 | 1100.0 133 | 1100.1 134 | 1100.0 135 | 1100.0 136 | 1100.1 137 | 1100.0 138 | 1100.0 139 | 1100.0 140 | 1100.0 141 | -------------------------------------------------------------------------------- /第一段拟合效果和原数据.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/第一段拟合效果和原数据.png -------------------------------------------------------------------------------- /第三段拟合效果和原数据.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/第三段拟合效果和原数据.png -------------------------------------------------------------------------------- /第二段拟合效果和原数据.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/第二段拟合效果和原数据.png -------------------------------------------------------------------------------- /综合图像显示.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cyysu/python-Science-Calculate/1f224371657708c80a7434d492e410650a0d9e54/综合图像显示.png --------------------------------------------------------------------------------