Question

我的数据有d数组：

--> d
array([[  60.41202301,   58.39997156,   55.3667636 , ...,  -84.87512796,
         -86.79190447,  -86.19353546],
       [  60.10975935,   58.05402795,   55.3898762 , ...,  -86.60428129,
         -88.12205283,  -89.45247056],
       [  60.14155715,   58.09627498,   55.7903388 , ...,  -89.18612111,
         -90.50667213,  -92.67073841],
       ..., 
       [  85.91138845,   84.50241834,   82.63664476, ...,  -71.04692203,
         -87.06297169, -100.36565732],
       [  82.74086966,   81.80343637,   79.96785709, ...,  -64.08451752,
         -79.18141593,  -99.36881913],
       [  79.15278282,   78.42730549,   77.1980837 , ...,  -58.38254858,
         -75.93821858,  -93.55287173]])

和另外2个数组，每个像素的半径和角度值：

--> radius
array([[ 42.42640687,  41.72529209,  41.03656906, ...,  37.80211634,
         38.41874542,  39.05124838],
       [ 41.72529209,  41.01219331,  40.31128874, ...,  37.01351105,
         37.64306045,  38.28837944],
       [ 41.03656906,  40.31128874,  39.59797975, ...,  36.23534186,
         36.87817783,  37.53664876],
       ..., 
       [ 41.72529209,  41.01219331,  40.31128874, ...,  37.01351105,
         37.64306045,  38.28837944],
       [ 42.42640687,  41.72529209,  41.03656906, ...,  37.80211634,
         38.41874542,  39.05124838],
       [ 43.13930922,  42.44997055,  41.77319715, ...,  38.60051813,
         39.20459157,  39.8246155 ]])
--> angle
array([[ 3.92699082,  3.94393835,  3.96145992, ...,  5.3664717 ,
         5.38712992,  5.40712726],
       [ 3.91004329,  3.92699082,  3.94453288, ...,  5.38291054,
         5.40372591,  5.42384811],
       [ 3.89252172,  3.90944876,  3.92699082, ...,  5.40006024,
         5.42101525,  5.44124371],
       ..., 
       [ 2.37314202,  2.35619449,  2.33865243, ...,  0.90027477,
         0.8794594 ,  0.8593372 ],
       [ 2.35619449,  2.33924696,  2.32172539, ...,  0.9167136 ,
         0.89605538,  0.87605805],
       [ 2.33980252,  2.32287349,  2.30539079, ...,  0.93247652,
         0.91199029,  0.89213384]])

我还有p0，我想要优化的对象：

--> p0
[1.0, 500.0, 0.5, 0.5, 5.2, 0.4]

我的职能定义：

def rotation(B,radiusref,angleref):
    return B[0] + (B[1] * radiusref * np.cos(angleref-B[2]) * np.sin(B[3]) * np.cos(B[3])**B[5] ) / (radiusref**2 * ( np.sin(angleref-B[2])**2 + np.cos(B[3])**2*np.cos(angleref-B[2])**2 ) + B[4]**2*np.cos(B[3])**2 )**B[5]/2.0

def errfunc(p0,d,radius,angle):
    return rotation(p0,radius,angle) - d

然后，我尝试运行optimize.leastsq以找到最佳解决方案，并收到以下错误消息：

--> fit = optimize.leastsq(errfunc,p0,args=(d,radius,angle))
ValueError: object too deep for desired array
Traceback (innermost last):
  File "<console>", line 1, in <module>
  File "/home/luisgdh/Ureka/python/lib/python2.7/site-packages/scipy/optimize/minpack.py", line 379, in leastsq
    gtol, maxfev, epsfcn, factor, diag)
error: Result from function call is not a proper array of floats.

为什么会这样？

如果我尝试运行errfunc，我会得到此

--> errfunc(p0,d,radius,angle)
array([[-311.96251984, -307.50362989, -301.89956899, ...,  121.84425081,
     128.7017239 ,  132.9161849 ],
   [-312.24524019, -307.79621255, -302.61362546, ...,  127.21717127,
     133.70343473,  139.86845861],
   [-312.81581149, -308.43470253, -303.66703887, ...,  133.56598817,
     139.87929082,  146.89601654],
   ..., 
   [-156.59031196, -150.97315566, -144.78021889, ...,  305.55786014,
     324.82275173,  341.21407515],
   [-149.69283006, -144.54525672, -138.38451089, ...,  297.67836311,
     316.06244785,  339.38095877],
   [-142.47209078, -137.53819725, -131.98946431, ...,  291.05301549,
     311.92874028,  332.71166956]])

Answer 1

我解决了自己的问题，如果有人再次发现这个问题，那么，minimalsq并不能很好地处理2d数据，所以我通过以下方式转换了1d数据中的2d数据：

d1radius = radius.ravel()
d1angle=angle.ravel()
d1data=d.ravel()

并重新定义了该功能：

def errfunc(p0,d1data,d1radius,d1angle):
    return rotation(p0,d1radius,d1angle) - d1data

最后：

fit = optimize.leastsq(errfunc,p0,args=(d1data,d1radius,d1angle))

Python优化最小化错误函数调用的结果不是正确的浮点数组

1 个答案: