• python爬山算法求函数值


    爬山算法求函数值

    f(x,y)=e^{-x^2-y^2}+2e^{-(x-5)^2-(y-5)^2}

    算法思路说明:

    没时间了。。。明天再说 

    1. import random, math
    2. import numpy as np
    3. def f(x,y):
    4. def mul(x,y):
    5. return math.exp(-x**2-y**2)
    6. return mul(x,y)+2*mul(x-5,y-5)
    7. def get_para(x,y,x_delta,y_delta):
    8. para = [[x,y],[x-x_delta, y],[x+x_delta, y],[x,y+y_delta],[x,y-y_delta],
    9. [x-x_delta, y-y_delta],[x+x_delta, y-y_delta],[x-x_delta,y+y_delta],[x-x_delta,y-y_delta],
    10. [x-x_delta, y+y_delta],[x+x_delta, y+y_delta],[x+x_delta,y+y_delta],[x+x_delta,y-y_delta]]
    11. # print('para',para)
    12. rs = []
    13. for xy in para:
    14. rs.append(f(xy[0],xy[1]))
    15. # print('rssrsrs',rs)
    16. best_index = rs.index(max(rs))
    17. # print('best_index',best_index)
    18. # print('best_para',para[best_index])
    19. return para[best_index]
    20. if __name__ == '__main__':
    21. print(f(20,2))
    22. x_delta=0.1
    23. y_delta=0.1
    24. x,y = 1,1
    25. xy_best = get_para(x,y,0.5,0.5)
    26. print(111,xy_best)
    27. rs_best = f(xy_best[0],xy_best[1])
    28. # print(rs_best)
    29. for i in range(10000):
    30. new_xy_best = get_para(xy_best[0],xy_best[1],x_delta,y_delta)
    31. # print(222,new_xy_best)
    32. # print(new_xy_best)
    33. if rs_best == f(new_xy_best[0],new_xy_best[1]):
    34. x_delta += 0.01
    35. y_delta += 0.01
    36. elif rs_best < f(new_xy_best[0],new_xy_best[1]):
    37. x_delta = 0.1
    38. y_delta = 0.1
    39. # print(11,rs_best, f(new_xy_best[0],new_xy_best[1]))
    40. xy_best = new_xy_best
    41. rs_best = f(new_xy_best[0],new_xy_best[1])
    42. print(i,xy_best, rs_best)
    43. print(xy_best, f(5,5))
    44. # print(rs_best,f(xy_best[0],xy_best[1]))

    运行结果:

    0 [0.4, 0.4] 0.7261490370736908
    1 [0.30000000000000004, 0.30000000000000004] 0.835270211411272
    2 [0.20000000000000004, 0.20000000000000004] 0.9231163463866358
    3 [0.10000000000000003, 0.10000000000000003] 0.9801986733067553
    4 [2.7755575615628914e-17, 2.7755575615628914e-17] 1.0
    437 [4.41999999999995, 4.41999999999995] 1.0205555955908896
    438 [4.51999999999995, 4.51999999999995] 1.261557641094735
    439 [4.6199999999999495, 4.6199999999999495] 1.4983240456498703
    440 [4.719999999999949, 4.719999999999949] 1.7097500334492415
    441 [4.819999999999949, 4.819999999999949] 1.8745097912252862
    442 [4.919999999999948, 4.919999999999948] 1.9745631431805484
    443 [5.019999999999948, 5.019999999999948] 1.9984006398293757
    [5.019999999999948, 5.019999999999948] 2.0

    参考:

    爬山算法_csuzhucong的博客-CSDN博客_爬山算法

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  • 原文地址:https://blog.csdn.net/java_raylu/article/details/125506485