How to disregard -inf and move to next iteration in for loop

Hello I'm hoping for some help I'm quite new to python and I wanted some advice on ways I can set up a condition so that if -inf is encounter in my data then the programme will loop to the next iteration

import numpy as np
import math
import matplotlib.pylab as plt
import pandas as pd
from scipy.interpolate import interp1d
from scipy.signal import butter, filtfilt
from scipy import interpolate
Ic = 400
lower_Ig = 720 #the lower limit of the generator current Ig
Upper_Ig = 1040 #Upper limit
Ix=range(-60,61,1)
for j in range(40, 80, 10):
    Var=(40000* j)/ 10000
    #print Var
    for c in range(lower_Ig, Upper_Ig+1, 40):
        #print c
        Names =['Vg','V3', 'V4']
        Data = pd.read_csv('/Documents/JTL_'+str(Var)+'/Ig='+str(c)+'/Grey_Zone.csv', names=Names)
        Vg = Data['Vg']
        V3 = Data['V3']
        V4 = Data ['V4']
        Prf = V4 / Vg
        #print Prf
        C = 0.802
        freq = 100
        b, a = butter(2, (5/C)/(freq/2), btype = 'low')
        yg = filtfilt(b, a, Vg)  # filter with phase shift correction
        y4 = filtfilt(b, a, V4)  # filter with phase shift correction
        SW = y4 / yg
        if SW == np.nan: #I need a condition here that if -inf is encountered then the programme should loop to next c value in for loop 
            continue 
            f = interp1d( SW, Ix )
            print f(0.25), f(0.5), f(0.75)
            print f(0.75)-f(0.25)

I have attempted using different numpy functions but I always get the same error

The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() 

I dont think I can use any() or all() since that will just include all the data and I want to ignore -inf. Any help is greatly appreciated