牛顿迭代法理论推导及python代码实现
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公式不便于在这里编辑,所以在word中编辑好了,截图过来。
用python+牛顿迭代法 求 y =(x-2)**3的解
import numpy as np import matplotlib.pyplot as plt \'\'\' 牛顿迭代法实现 y =(x-2)**3的解 \'\'\' def f(x): return (x-2)**3 def fd(x): return 3*((x-2)**2) def newtonMethod(n,assum): time = n x = assum next = 0 a = f(x) b = fd(x) print(\'a = \'+str(a)+\',b = \'+str(b)+\',time = \'+str(time)) if f(x) == 0.0: return time,x else: next = x-a/b print(\'next x = \'+str(next)) if a - f(next)<1e-6: print(\'meet f(x) = 0 , x = \'+ str(next)) ##设置跳出条件,同时输出满足f(x) = 0 的x的值 else: return newtonMethod(n+1,next) newtonMethod(0,4.0)
C:\\ProgramData\\Anaconda3\\python.exe D:/python/TensorFlow/算法实例/牛顿迭代法.py a = 8.0,b = 12.0,time = 0 next x = 3.3333333333333335 a = 2.370370370370371,b = 5.333333333333334,time = 1 next x = 2.888888888888889 a = 0.7023319615912207,b = 2.3703703703703702,time = 2 next x = 2.5925925925925926 a = 0.20809835898999132,b = 1.0534979423868311,time = 3 next x = 2.3950617283950617 a = 0.0616587730340715,b = 0.4682213077274805,time = 4 next x = 2.263374485596708 a = 0.018269266084169365,b = 0.20809835898999157,time = 5 next x = 2.1755829903978054 a = 0.005413115876790937,b = 0.09248815955110752,time = 6 next x = 2.11705532693187 a = 0.001603886185715827,b = 0.04110584868938101,time = 7 next x = 2.078036884621247 a = 0.0004752255365083959,b = 0.01826926608416941,time = 8 next x = 2.052024589747498 a = 0.00014080756637285685,b = 0.008119673815186359,time = 9 next x = 2.034683059831665 a = 4.17207604067724e-05,b = 0.0036087439178606037,time = 10 next x = 2.023122039887777 a = 1.2361706787192059e-05,b = 0.0016038861857158443,time = 11 next x = 2.015414693258518 a = 3.662727936945795e-06,b = 0.0007128383047625975,time = 12 next x = 2.0102764621723455 a = 1.0852527220580603e-06,b = 0.00031681702433894134,time = 13 next x = 2.0068509747815635 meet f(x) = 0 , x = 2.0068509747815635 Process finished with exit code 0
从运行的结果可以看出近似根x = 2.0068509747815635
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