import numpy as np
import matplotlib.pyplot as plt
h = 0.1
y = 1
x = 0
X = np.zeros(100)
Y = np.zeros(100)
for i in range(1, 100):
y = 1.1*y-0.2*(x/y)
y1 = 1.1*y-0.2*((x+0.1)/y)
y2= 1.05*y-0.1*(x/y)+0.05*y1-0.1*((x+0.1)/y1)
x+=h
X[i]=x
Y[i]=y2
print(x,y2)
plt.plot(X,Y,color='red')
plt.scatter(x,y2)
plt.show()
0.1 1.2062003675195896
0.2 1.2912341018482063
0.30000000000000004 1.3714761633812256
0.4 1.447920039866351
0.5 1.521330627291211
0.6 1.5923296550583603
0.7 1.6614479537132871
0.7999999999999999 1.7291600028687955
0.8999999999999999 1.7959084591571093
0.9999999999999999 1.862122823465604
1.0999999999999999 1.9282346449593193
1.2 1.9946907208222076
1.3 2.061965219585434
1.4000000000000001 2.1305713368948784
1.5000000000000002 2.2010728874785936
1.6000000000000003 2.274096093885348
1.7000000000000004 2.350341722603248
1.8000000000000005 2.430597625571267
1.9000000000000006 2.5157516618656266
2.0000000000000004 2.606804898046024
2.1000000000000005 2.7048849183576205
2.2000000000000006 2.811259023618854
2.3000000000000007 2.9273470691022316
2.400000000000001 3.054733697529132
2.500000000000001 3.1951797732668226
2.600000000000001 3.350632924085153
2.700000000000001 3.5232372466610804
2.800000000000001 3.715342421261476
2.9000000000000012 3.929512689466804
3.0000000000000013 4.168536348251872
3.1000000000000014 4.435436573180868
3.2000000000000015 4.733484476067398
3.3000000000000016 5.066215312593037
3.4000000000000017 5.437448683305935
3.5000000000000018 5.851313433621045
3.600000000000002 6.312277783573018
3.700000000000002 6.825185039756393
3.800000000000002 7.395295090842274
3.900000000000002 8.028331786008762
4.000000000000002 8.730536252502995
4.100000000000001 9.508726223158902
4.200000000000001 10.37036150775095
4.300000000000001 11.323615840259002
4.4 12.377455453784016
4.5 13.54172486450732
4.6 14.827240477662368
4.699999999999999 16.245892757478266
4.799999999999999 17.810757827966164
4.899999999999999 19.536219492951066
4.999999999999998 21.43810278396294
5.099999999999998 23.533820266243097
5.1999999999999975 25.842532459165813
5.299999999999997 28.38532386073499
5.399999999999997 31.18539620921943
5.4999999999999964 34.26828077095173
5.599999999999996 37.662071614163736
5.699999999999996 41.397682016674
5.799999999999995 45.509126362431935
5.899999999999995 50.03383011053061
5.999999999999995 55.01297067257346
6.099999999999994 60.49185231260516
6.199999999999994 66.52031849075952
6.299999999999994 73.15320541013271
6.399999999999993 80.45084089921764
6.499999999999993 88.47959317289653
6.5999999999999925 97.31247446718727
6.699999999999992 107.0298050407519
6.799999999999992 117.71994358410079
6.8999999999999915 129.48009068041313
6.999999999999991 142.41717262540595
7.099999999999991 156.64881364372707
7.19999999999999 172.30440534254214
7.29999999999999 189.52628312662088
7.39999999999999 208.4710202713216
7.499999999999989 229.31085141925297
7.599999999999989 252.2352384427733
7.699999999999989 277.45259290855483
7.799999999999988 305.1921708039555
7.899999999999988 335.70615675083525
7.999999999999988 369.27195665496794
8.099999999999987 406.1947196339784
8.199999999999987 446.8101121510108
8.299999999999986 491.48736957404685
8.399999999999986 540.6326529027893
8.499999999999986 594.6927411792259
8.599999999999985 654.1590931496128
8.699999999999985 719.5723151024156
8.799999999999985 791.5270754992133
8.899999999999984 870.6775110773018
8.999999999999984 957.7431735706247
9.099999999999984 1053.515571110354
9.199999999999983 1158.8653637725959
9.299999999999983 1274.750278687471
9.399999999999983 1402.2238166652708
9.499999999999982 1542.444829490982
9.599999999999982 1696.6880549536277
9.699999999999982 1866.3557053835402
9.799999999999981 2052.9902150480125
9.89999999999998 2258.288262290848
