这个问题有一个答案here但是解决方案对我来说似乎没有用。
我的功能如下：
def slopefunction_cf(xin,amp,phase,off,freq,intercept,t):
fitted =np.zeros((4,12))
for im in t:
fitted[:,im-1] = intercept[im-1]+[amp*np.sin(freq*(im)+phase)+off]*xin
return fitted.ravel()
其中intercept和t是附加参数，至少我会以args =
的形式传递我试过了：
popt, pcov = curve_fit(slopefunction_cf, np.arange(0,4), datain, p0=paramin, args=(intercept,t) )
并收到错误：
TypeError: func_wrapped() takes exactly 1 argument (3 given)
然后我尝试了我链接的答案中建议的内容并将其转换为：
def define_var_args(interceptin,tin):
def slopefunction_cf(xin,amp,phase,off,freq):
intercept = interceptin
t = tin
fitted =np.zeros((4,12))
for im in t:
fitted[:,im-1] = intercept[im-1]+[amp*np.sin(freq*(im)+phase)+off]*xin
return fitted.ravel()
然后调用curve_fit：
popt, pcov = curve_fit(define_var_args(intercept, t), np.arange(0,4), datain, p0=paramin )
但我收到以下错误（我复制了所有内容）
--> 115 popt, pcov = curve_fit(define_var_args(interceptconus, t), np.arange(0,4), datain.ravel(), p0=paramin )
116
117 print popt
/software/centos6/x86_64/canopy-1.7.4/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/minpack.pyc in curve_fit(f, xdata, ydata, p0, sigma, absolute_sigma, check_finite, bounds, method, jac, **kwargs)
734 # Remove full_output from kwargs, otherwise we're passing it in twice.
735 return_full = kwargs.pop('full_output', False)
--> 736 res = leastsq(func, p0, Dfun=jac, full_output=1, **kwargs)
737 popt, pcov, infodict, errmsg, ier = res
738 cost = np.sum(infodict['fvec'] ** 2)
/software/centos6/x86_64/canopy-1.7.4/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/minpack.pyc in leastsq(func, x0, args, Dfun, full_output, col_deriv, ftol, xtol, gtol, maxfev, epsfcn, factor, diag)
375 if not isinstance(args, tuple):
376 args = (args,)
--> 377 shape, dtype = _check_func('leastsq', 'func', func, x0, args, n)
378 m = shape[0]
379 if n > m:
/software/centos6/x86_64/canopy-1.7.4/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/minpack.pyc in _check_func(checker, argname, thefunc, x0, args, numinputs, output_shape)
24 def _check_func(checker, argname, thefunc, x0, args, numinputs,
25 output_shape=None):
---> 26 res = atleast_1d(thefunc(*((x0[:numinputs],) + args)))
27 if (output_shape is not None) and (shape(res) != output_shape):
28 if (output_shape[0] != 1):
/software/centos6/x86_64/canopy-1.7.4/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/minpack.pyc in func_wrapped(params)
452 if transform is None:
453 def func_wrapped(params):
--> 454 return func(xdata, *params) - ydata
455 elif transform.ndim == 1:
456 def func_wrapped(params):
TypeError: 'NoneType' object is not callable
我甚至不确定错误是什么 - 如果代码或我的数据中的某些内容？它有点模糊。
是否有其他方法可以传递其他参数？
编辑：添加一些数据并略微更改上述功能
t = np.arange(1,13)
paramin = [0.40569370873086791, 1, -0.88134718450091365, 0.5]
datain = [-3.45083921, -3.405628 , -2.57401114, -1.7632551 , -1.29342567,
-1.44200248, -2.05366981, -2.51467815, -2.79597983, -2.95528074,
-2.90766603, -3.60850134, -3.90036107, -3.87760971, -3.18549774,
-2.43304533, -2.1734368 , -2.43953997, -3.1183866 , -3.57696154,
-3.72915335, -3.67344888, -3.29697388, -4.10385938, -4.88945667,
-4.82385939, -4.10568684, -3.50093464, -3.26766599, -3.78206157,
-4.51782818, -4.95149472, -4.93689182, -4.75850421, -4.22849458,
-4.91811193, -5.34080606, -5.40676402, -4.66050702, -4.29447163,
-4.16430688, -4.75008652, -5.57106708, -5.58801663, -5.96637981,
-5.51549722, -4.94026303, -5.42975354]
intercept = [-3.39651633, -3.33601661, -2.55447417, -1.69869584, -1.26867791,
-1.41340658, -2.02249291, -2.56860547, -2.74926044, -2.91082705,
-2.78895263, -3.57335517]
我已经“raveled”了数据，所以我在问题的开头修改了这个功能。 使用这些数据我在新笔记本中重现我的错误。
解决方案：
我的代码中有两个问题： 1）我没有返回嵌套函数 2）我没有把xin作为嵌套函数的参数 3）我不得不把这颗星放在p
之前现在可行了
def define_extravar(interceptin,tin):
def slopefunction_cf(xin,*p):
intercept = interceptin
t = tin
fitted =np.zeros((4,12))
amp,phase,off,freq = p
for im in t:
fitted[:,im-1] = intercept[im-1]+[amp*np.sin(freq*(im)+phase)+off]*xin
return fitted.ravel()
return slopefunction_cf