scipy.optimize.curve_fit：不是一个适当的浮点数组错误 [英] scipy.optimize.curve_fit: not a proper array of floats error

问题描述

我试图使用optimization.curve_fit来找到两个数组之间的最小二乘解，但是我不断收到错误：函数调用的结果不是一个合适的float数组。我粘贴下面的代码。任何想法如何解决这一问题？

  import numpy as np 
导入scipy.optimize作为优化
 
 pcone = np.array（[[ -  0.01043151]，
 [-0.00135030]，
 [-0.02566969]，
 [-0.02822495]，
 [-0.05463625]，
 [-0.00969918]，
 [-0.01332421]，
 [-0.03364439]，
 [-0.04009642]，
 [-0.03556982]]）
 
 pctwo = np.array（[[0.02550008]，
 [0.04422852]，
 [0.06685288]，
 [0.04751296]，
 [0.02439405]，
 [0.09654185 ]，
 [0.03161849]，
 [0.03834721]，
 [0.01653997]，
 [-0.00802414]]）
 
 def func（x，a ，b，c）：
 return a + b * x + c * x * x 
 
 print optimization.curve_fit（func，pcone，pctwo）
  curve_fit 需要一维数组。在将它们传递给 curve_fit  pcone 和 pctwo  
 
 
例如，这个工程：
 
 
  [数组（[0.05720879,0.65281483，-2.67840575]），
 array（[[5.90887090e-04，4.15822858e-02，6.14439732e-01]，
 [4.15822858e-02，4.07354227e + 00，6.94784914e + 01]，
 [6.14439732e-01 ，6.94784914e + 01，1.29240335e + 03]]））
  
创建了 pcone 和 pctwo ，可能会更清晰地创建它们作为一维数组，而不是稍后将它们弄平。）
 
I'm trying to use optimization.curve_fit to find the least square solution between two arrays, but I keep getting error: Result from function call is not a proper array of floats. I pasted my code below. Any ideas how to fix this? Thank you!
import numpy as np
import scipy.optimize as optimization

pcone = np.array([[-0.01043151],
  [-0.00135030],
  [-0.02566969],
  [-0.02822495],
  [-0.05463625],
  [-0.00969918],
  [-0.01332421],
  [-0.03364439],
  [-0.04009642],
  [-0.03556982]])

pctwo = np.array([[0.02550008],
  [0.04422852],
  [0.06685288],
  [0.04751296],
  [0.02439405],
  [0.09654185],
  [0.03161849],
  [0.03834721],
  [0.01653997],
  [-0.00802414]])

def func(x, a, b, c):
    return a + b*x + c*x*x

print optimization.curve_fit(func, pcone, pctwo)

解决方案
Your arrays have shape (10, 1).  That is, they are two-dimensional, with a trivial second dimension.  In the simplest case, curve_fit expects one-dimensional arrays.  Flatten pcone and pctwo into one-dimensional arrays before passing them to curve_fit.

For example, this works:
In [8]: curve_fit(func, pcone.ravel(), pctwo.ravel())
Out[8]: 
(array([ 0.05720879,  0.65281483, -2.67840575]),
 array([[  5.90887090e-04,   4.15822858e-02,   6.14439732e-01],
        [  4.15822858e-02,   4.07354227e+00,   6.94784914e+01],
        [  6.14439732e-01,   6.94784914e+01,   1.29240335e+03]]))
(You haven't shown how pcone and pctwo were created.  It would probably be cleaner to create them as 1-D arrays in the first place, instead of flattening them later.)

                        
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