np.polyfit不适合数据

Question

我找不到调整数据的曲线（列出“ chi”和“ m”）。我使用polyfit生成曲线，但不足以捕捉点的行为。

前面的代码有一个图，显示了数据和调整之间的差异。

import matplotlib.pyplot as plt
import numpy as np

chi = [159.227326193538,157.045536099339,154.874421083320,152.714227953804,150.565205206850,148.427603026261,146.301673283577,144.187669538078,142.085847036787,139.996462714462,137.919775193605,135.856044784456,133.805533484994,131.768504980940,129.745224645753,127.735959540633,125.740978414520,123.760551704092,121.794951533770,119.844451715712,117.909327749816,115.989856823722,114.086317812809,112.198991280194,110.328159476736,108.474106341033,106.637117499424,104.817480265986,103.015483642536,101.231418318633,99.4655766715733,97.7182527663948,95.9897423558747,94.2803428805298,92.5903534686167,90.9200749361326,89.2698097868135,87.6398622121363,86.0305380913169,84.4421449913117,82.8749921668166,81.3293905602669,79.8056528018393,78.3040932094484,76.8250277887500,75.3687742331392,73.9356519237512,72.5259819294609,71.1400870068830,69.7782916003724,68.4409218420233,67.1283055516702,65.8407722368873,64.5786530929887,63.3422810030283,62.1319905377998,60.9481179558368,59.7910012034130,58.6609799145416,57.5583954109757,56.4835907022086,55.4369104854728,54.4187011457414,53.4293107557267,52.4690890758814,51.5383875543978,50.6375593272080,49.7669592179839,48.9269437381375,48.1178710868206,47.3401011509247,46.5939955050811,45.8799174116612,45.1982318207762,44.5493053702771,43.9335063857545,43.3512048805394,42.8027725557022,42.2885828000534,41.8090106901432,41.3644329902617,40.9552281524389,40.5817763164445,40.2444593097885,39.9436606477201,39.6797655332288,39.4531608570438,39.2642351976343,39.1133788212092,39.0009836817171,38.9274434208471,38.8931533680273,38.8985105404262,38.9439136429520,39.0297630682529,39.1564608967166,39.3244108964711,39.5340185233838,39.7856909210623,40.0798369208539,40.4168670418459,40.7971934908652,41.2212301624788,41.6893926389935,42.2020981904556,42.7597657746519,43.3628160371087,44.0116713110920,44.7067556176079,45.4484946654022,46.2373158509606,47.0736482585089,47.9579226600125,48.8905715151762,49.8720289714460,50.9027308640062,51.9831147157818,53.1136197374377,54.2946868273783,55.5267585717480,56.8102792444312,58.1456948070521,59.5334529089743,60.9740028873018,62.4677957668786,64.0152842602876,65.6169227678529,67.2731673776373,68.9844758654438,70.7513076948157,72.5741240170354,74.4533876711260,76.3895631838499,78.3831167697092,80.4345163309464,82.5442314575433,84.7127334272220,86.9404952054444,89.2279914454118,91.5756984880661,93.9840943620883,96.4536587839001,98.9848731576614,101.578220575274,104.234185816379,106.953255348357,109.735917326327,112.582661593151,115.493979679428,118.470364803498,121.512311871442,124.620317477080,127.794879901969,131.036499115411,134.345676774445,137.722916223849,141.168722496142,144.683602311584,148.268064078173,151.922617891649,155.647775535488,159.444050480909,163.311957886871,167.252014600072,171.264739154948,175.350651773679,179.510274366181,183.744130530113,188.052745550870,192.436646401591,196.896361743152,201.432421924170,206.045358981001,210.735706637743,215.504000306232,220.350777086043,225.276575764494,230.281936816639,235.367402405274,240.533516380936,245.780824281900,251.109873334181,256.521212451534,262.015392235454,267.592964975176,273.254484647676,279.000506917667,284.831589137604,290.748290347682,296.751171275834,302.840794337735,309.017723636798,315.282524964177,321.635765798766,328.078015307199,334.609844343848,341.231825450827,347.944532857988,354.748542482925,361.644431930971,368.632780495196]
m=[-1,-0.990000000000000,-0.980000000000000,-0.970000000000000,-0.960000000000000,-0.950000000000000,-0.940000000000000,-0.930000000000000,-0.920000000000000,-0.910000000000000,-0.900000000000000,-0.890000000000000,-0.880000000000000,-0.870000000000000,-0.860000000000000,-0.850000000000000,-0.840000000000000,-0.830000000000000,-0.820000000000000,-0.810000000000000,-0.800000000000000,-0.790000000000000,-0.780000000000000,-0.770000000000000,-0.760000000000000,-0.750000000000000,-0.740000000000000,-0.730000000000000,-0.720000000000000,-0.710000000000000,-0.700000000000000,-0.690000000000000,-0.680000000000000,-0.670000000000000,-0.660000000000000,-0.650000000000000,-0.640000000000000,-0.630000000000000,-0.620000000000000,-0.610000000000000,-0.600000000000000,-0.590000000000000,-0.580000000000000,-0.570000000000000,-0.560000000000000,-0.550000000000000,-0.540000000000000,-0.530000000000000,-0.520000000000000,-0.510000000000000,-0.500000000000000,-0.490000000000000,-0.480000000000000,-0.470000000000000,-0.460000000000000,-0.450000000000000,-0.440000000000000,-0.430000000000000,-0.420000000000000,-0.410000000000000,-0.400000000000000,-0.390000000000000,-0.380000000000000,-0.370000000000000,-0.360000000000000,-0.350000000000000,-0.340000000000000,-0.330000000000000,-0.320000000000000,-0.310000000000000,-0.300000000000000,-0.290000000000000,-0.280000000000000,-0.270000000000000,-0.260000000000000,-0.250000000000000,-0.240000000000000,-0.230000000000000,-0.220000000000000,-0.210000000000000,-0.200000000000000,-0.190000000000000,-0.180000000000000,-0.170000000000000,-0.160000000000000,-0.150000000000000,-0.140000000000000,-0.130000000000000,-0.120000000000000,-0.110000000000000,-0.100000000000000,-0.0900000000000000,-0.0800000000000000,-0.0700000000000000,-0.0599999999999999,-0.0499999999999999,-0.0400000000000000,-0.0300000000000000,-0.0200000000000000,-0.0100000000000000,0,0.0100000000000000,0.0200000000000000,0.0300000000000000,0.0400000000000000,0.0499999999999999,0.0599999999999999,0.0700000000000000,0.0800000000000000,0.0900000000000000,0.100000000000000,0.110000000000000,0.120000000000000,0.130000000000000,0.140000000000000,0.150000000000000,0.160000000000000,0.170000000000000,0.180000000000000,0.190000000000000,0.200000000000000,0.210000000000000,0.220000000000000,0.230000000000000,0.240000000000000,0.250000000000000,0.260000000000000,0.270000000000000,0.280000000000000,0.290000000000000,0.300000000000000,0.310000000000000,0.320000000000000,0.330000000000000,0.340000000000000,0.350000000000000,0.360000000000000,0.370000000000000,0.380000000000000,0.390000000000000,0.400000000000000,0.410000000000000,0.420000000000000,0.430000000000000,0.440000000000000,0.450000000000000,0.460000000000000,0.470000000000000,0.480000000000000,0.490000000000000,0.500000000000000,0.510000000000000,0.520000000000000,0.530000000000000,0.540000000000000,0.550000000000000,0.560000000000000,0.570000000000000,0.580000000000000,0.590000000000000,0.600000000000000,0.610000000000000,0.620000000000000,0.630000000000000,0.640000000000000,0.650000000000000,0.660000000000000,0.670000000000000,0.680000000000000,0.690000000000000,0.700000000000000,0.710000000000000,0.720000000000000,0.730000000000000,0.740000000000000,0.750000000000000,0.760000000000000,0.770000000000000,0.780000000000000,0.790000000000000,0.800000000000000,0.810000000000000,0.820000000000000,0.830000000000000,0.840000000000000,0.850000000000000,0.860000000000000,0.870000000000000,0.880000000000000,0.890000000000000,0.900000000000000,0.910000000000000,0.920000000000000,0.930000000000000,0.940000000000000,0.950000000000000,0.960000000000000,0.970000000000000,0.980000000000000,0.990000000000000,1]

poly = np.polyfit(chi, m, deg = 40)
fit_fn = np.poly1d(poly)

f = plt.figure()
ax = f.add_subplot(111)
ax.plot(m, chi, 'r-', label = 'data')
ax.plot(fit_fn(chi), chi, 'b-', label = 'adjust')
ax.set_xlabel('$m$')
ax.set_ylabel('$\chi^2$')
plt.legend()
plt.show()
plt.close()

Answer 1

问题是您在拟合和绘制拟合时混合了x和y坐标。由于m是x坐标（独立变量），而chi是y坐标（独立变量），因此请以正确的顺序传递它们。修改过的行用注释#

表示

poly = np.polyfit(m, chi, deg = 4) # <-----
fit_fn = np.poly1d(poly)

f = plt.figure()
ax = f.add_subplot(111)
ax.plot(m, chi, 'rx', label = 'data') # <---- Just used x to plot symbols
ax.plot(m, fit_fn(m), 'b-', lw=2, label = 'adjust') # <-----
ax.set_xlabel('$m$')
ax.set_ylabel('$\chi^2$')
plt.legend()
plt.show()
plt.close()