Classification of whether a county has AP Calculus (Part 1)

I used python's Numpy to get some information about how employment, creative jobs, arts jobs, and the ratio of creative jobs and arts jobs to employment influence whether a county has AP Calculus offered within its borders.

The data was called Creative Class County Codes at Data.gov.  I used the same zip codes from the earlier project and converted them to counties by downloading a spreadsheet from UnitedStatesZipCodes.org.  The code follows:

#A helper function that is necessary to make sure the cost function never becomes infinite 

def safeLog(array):
     import numpy as np
          def helper(x):
                if x==0:
                    results=-1000000
                else:
                    results=np.log(x)
         return(results)
    return(np.vectorize(helper)(array))

#The cost function that is to be minimized

          def cost(theta,X,indicator):
               import numpy as np

     import sigmoid as sig
     import safeLog as sl
     output = sig.sigmoid(np.dot(X,theta))
     first = np.sum(indicator*sl.safeLog(output))
     last = np.sum((np.ones(len(X))-indicator)*sl.safeLog(np.ones(len(X))-output))
     return(-1/len(X)*(first+last))

#The cost gradient function that is useful for some minimizers
def costGradient(theta,X,indicator):
import numpy as np
import sigmoid as sig
output = sig.sigmoid(np.dot(X,theta))
return(1.0/len(X)*np.dot(X.T,(output-indicator)))