试图将某些数据拟合到我称为Ffitr的函数中，但是在运行下面的代码时，我只会对所有值都使用“ nan”。如果您从返回值中删除代码是否起作用，问题就出在问题上。我怀疑这与Ffitr的日志部分有关，但后来我认为python应该显示“日志中遇到的无效值”。 Minuit将所有参数设置为nan的原因还有什么？
P.s。对不起，我的代码有点难以阅读。
import numpy as np
from iminuit import Minuit
#Parameters to fit to:
Zsrgi=np.array([1.47, 1.5, 1.54, 1.58])
Za=np.array([ 0.9468, 0.9632, 0.9707, 0.9756])
af=np.array([ 0.0575465 , 0.05547301, 0.04983955, 0.05096624, 0.04737787,
0.04716958, 0.04579672, 0.0454464 , 0.0437895 , 0.04202845,
0.04717754, 0.04625286, 0.04245786, 0.04105158, 0.04052182,
0.04077226, 0.03857616, 0.03776707, 0.03453072, 0.0414683 ,
0.0395172 , 0.03501315, 0.03553733, 0.03483842, 0.03207193,
0.03173218, 0.03206222, 0.03104359, 0.03046799, 0.02715095,
0.0273168 , 0.02622413])
amudr=np.array([ 0.01737619, 0.01377279, 0.00808912, 0.00970136, 0.00580544,
0.00496463, 0.00397211, 0.00383197, 0.0019517 , 0.00102585,
0.01227267, 0.01208733, 0.00673 , 0.00537933, 0.00521267,
0.00450733, 0.00328733, 0.002288 , 0.000658 , 0.00950714,
0.00923442, 0.00537273, 0.00533831, 0.00534351, 0.0022987 ,
0.00224545, 0.00126688, 0.00588165, 0.00582215, 0.00267405,
0.00266899, 0.0013943 ])
a=np.array([ 0.0904, 0.0755, 0.0647, 0.0552])
#coefficients
afij=np.array([ 1.09440000e+00, -1.00000000e+00, -4.73000000e-02,
-1.90580000e+00, -1.25000000e+00, -2.44535000e+02,
-1.54989000e+01, -9.39460000e+00, -3.45830000e+00])
def Ffitr(X,s,pp,k,B=2.61,Fc=92.8,mu=770): #fit function
temp1 = (2*B*X)/(4*pi*Fc)**2
temp2 = temp1*(afij[0]+afij[1]*np.log((2*B*X)/mu**2))
temp3 = temp1**2*(afij[2]+afij[3]*np.log((2*B*X)/mu**2)+\
afij[4]*(np.log((2*B*X)/mu**2))**2)
temp4 = temp1**3*(afij[5]+afij[6]*np.log((2*B*X)/mu**2)+\
afij[7]*(np.log((2*B*X)/mu**2))**2+\
afij[8]*(np.log((2*B*X)/mu**2))**3)
return Fc*pp*(1+k*s)*(1+temp2+temp3+temp4)
def chiwork(a0,a1,a2,a3,b0,b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19,b20,b21,b22,b23,b24,b25,b26,b27,b28,b29,b30,b31,\
z0,z1,z2,z3,za0,za1,za2,za3,\
am0,am1,am2,am3,am4,am5,am6,am7,am8,am9,am10,am11,am12,am13,am14,am15,am16,am17,am18,am19,am20,am21,am22,am23,am24,am25,am26,am27,am28,am29,am30,am31,\
k,y1): #chisquare
ana=np.array([a0,a1,a2,a3])
zs=np.array([z0,z1,z2,z3])
za=np.array([za0,za1,za2,za3])
am=np.array([am0,am1,am2,am3,am4,am5,am6,am7,am8,am9,am10,am11,am12,am13,am14,am15,am16,am17,am18,am19,am20,am21,am22,am23,am24,am25,am26,am27,am28,am29,am30,am31])
bss=np.array([b0,b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19,b20,b21,b22,b23,b24,b25,b26,b27,b28,b29,b30,b31])
betalat=[0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,3,3,3,3,3]
chia=sum((ana-a)**2)+sum((bss*a[betalat]/hc-amssr)**2)
chiz=sum((zs-1/Zsrgi)**2)+sum((za-Za)**2)
chiamd=sum((amudr-(1+y1*ana[betalat]**2)*ana[betalat]*am*zs[betalat]/hc)**2)
chiaf=sum((af-ana[betalat]/hc*Ffitr(am,bss**2-mssph**2,ana[betalat]/za[betalat],k))**2)
#chiaB=sum(((ampir**2/(2*amudr))-ampm)**2)
return chia+chiz+chiamd+chiaf
#minuit part
mc=Minuit(chiwork)
fminc,paramc=mc.migrad()