python数据处理_读取txt数据并绘图

1、导入相关模块

import matplotlib.pyplot as plt  #绘图模块
from scipy import interpolate  #插值模块
import numpy as np  #数值计算模块

2、目标文件的定义与读取

file = 'F:\XZ_DL\GLS.txt' #以高岭石波谱曲线为例
a = np.loadtxt(file)
x = a[:,0]  #读取第一列所有数据
y = a[:,1]  #读取第二列所有数据

3、函数拟合与插值

tck = interpolate.splrep(x,y)  #拟合y与x
xx = np.linspace(min(x),max(x),200)  #x插值
yy = interpolate.splev(xx,tck,der=0)
print(xx)

输出结果为：
[0.400279   0.41322232 0.42616564 0.43910896 0.45205229 0.46499561
 0.47793893 0.49088225 0.50382557 0.51676889 0.52971222 0.54265554
 0.55559886 0.56854218 0.5814855  0.59442882 0.60737215 0.62031547
 0.63325879 0.64620211 0.65914543 0.67208875 0.68503208 0.6979754
 0.71091872 0.72386204 0.73680536 0.74974868 0.76269201 0.77563533
 0.78857865 0.80152197 0.81446529 0.82740861 0.84035193 0.85329526
 0.86623858 0.8791819  0.89212522 0.90506854 0.91801186 0.93095519
 0.94389851 0.95684183 0.96978515 0.98272847 0.99567179 1.00861512
 1.02155844 1.03450176 1.04744508 1.0603884  1.07333172 1.08627505
 1.09921837 1.11216169 1.12510501 1.13804833 1.15099165 1.16393497
 1.1768783  1.18982162 1.20276494 1.21570826 1.22865158 1.2415949
 1.25453823 1.26748155 1.28042487 1.29336819 1.30631151 1.31925483
 1.33219816 1.34514148 1.3580848  1.37102812 1.38397144 1.39691476
 1.40985809 1.42280141 1.43574473 1.44868805 1.46163137 1.47457469
 1.48751802 1.50046134 1.51340466 1.52634798 1.5392913  1.55223462
 1.56517794 1.57812127 1.59106459 1.60400791 1.61695123 1.62989455
 1.64283787 1.6557812  1.66872452 1.68166784 1.69461116 1.70755448
 1.7204978  1.73344113 1.74638445 1.75932777 1.77227109 1.78521441
 1.79815773 1.81110106 1.82404438 1.8369877  1.84993102 1.86287434
 1.87581766 1.88876098 1.90170431 1.91464763 1.92759095 1.94053427
 1.95347759 1.96642091 1.97936424 1.99230756 2.00525088 2.0181942
 2.03113752 2.04408084 2.05702417 2.06996749 2.08291081 2.09585413
 2.10879745 2.12174077 2.1346841  2.14762742 2.16057074 2.17351406
 2.18645738 2.1994007  2.21234403 2.22528735 2.23823067 2.25117399
 2.26411731 2.27706063 2.29000395 2.30294728 2.3158906  2.32883392
 2.34177724 2.35472056 2.36766388 2.38060721 2.39355053 2.40649385
 2.41943717 2.43238049 2.44532381 2.45826714 2.47121046 2.48415378
 2.4970971  2.51004042 2.52298374 2.53592707 2.54887039 2.56181371
 2.57475703 2.58770035 2.60064367 2.61358699 2.62653032 2.63947364
 2.65241696 2.66536028 2.6783036  2.69124692 2.70419025 2.71713357
 2.73007689 2.74302021 2.75596353 2.76890685 2.78185018 2.7947935
 2.80773682 2.82068014 2.83362346 2.84656678 2.85951011 2.87245343
 2.88539675 2.89834007 2.91128339 2.92422671 2.93717004 2.95011336
 2.96305668 2.976     ]

4、绘图与显示

plt.plot(x,y,'-',xx,yy,color='red')     #定义样式
plt.xlabel('Wavelength(μm)')  #横坐标含义
plt.ylabel('Data Value')  #纵坐标含义
plt.title('Kaolinite')```#图名（若附中文名称需导入并定义中文模块matplotlib.font_manager）

结果显示：

常用线条样式及颜色对应参数可参考博客：https://blog.youkuaiyun.com/qq_45398466/article/details/109278791