[Tutor] Fitting data to error function

[Colin Ross]

Hi all,

I am attempting to optimize the parameters I_0 and w_0 in the function
(func(x,I_0,w_0) shown below) to fit a set of data. However when I run this
code I recieve the error shown below. Any suggestions would be greatly
appreciated.

Code:

import numpy as np

import math

from math import *

# data

xdata = np.array([0.1,1.0,2.0,3.0,4.0,5.0])

ydata = np.array([0.1,0.9,2.2,2.8,3.9,5.1])

# Initial guess.

x0 = np.array([0.0, 0.0])


# Data errors:

sigma = np.array([1.0,1.0,1.0,1.0,1.0,1.0])

# Error function

def func(x,a,b):

    return ((a)/2.)*(math.erfc((np.sqrt(2.)*x*1.E-3)/b))


# Optimization

import scipy.optimize as optimization

print optimization.curve_fit(func, xdata, ydata, x0, sigma)

The error I am recieving is as follows:

TypeError: only length-1 arrays can be converted to Python scalars