问Scipy Curve Fit:提供的函数不返回有效的浮点数

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In [3]: import numpy as np

In [4]: from scipy.optimize import curve_fit

In [5]: x = np.array([1.0, 2., 3, 4.])

In [6]: y = x

In [7]: def f(x, a):                       # try a nan
   ...:     return np.nan
   ...: 

In [9]: curve_fit(f, x, y, 2.0)
/home/br/virtualenvs/scipy-dev/local/lib/python2.7/site-packages/scipy/optimize/minpack.py:604: OptimizeWarning: Covariance of the parameters could not be estimated
  category=OptimizeWarning)
Out[9]: (array([ 2.]), array([[ inf]]))

In [10]: def g(x, a):
   ....:     return 'nonsense'
   ....: 

In [11]: curve_fit(g, x, y, 2.0)
<snip>
TypeError: unsupported operand type(s) for -: 'str' and 'numpy.ndarray'

In [12]: def h(x, a):
   ....:     return 1j
   ....: 

In [13]: curve_fit(h, x, y, 2.0)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
TypeError: Cannot cast array data from dtype('complex128') to dtype('float64') according to the rule 'safe'
<snip>

error: Result from function call is not a proper array of floats.