python: getting around division by zero

Question

I have a big data set of floating point numbers. I iterate through them and evaluate np.log(x) for each of them. I get

RuntimeWarning: divide b         


        

Answer 1

The answer given by Enrico is nice, but both solutions result in a warning:

RuntimeWarning: divide by zero encountered in log

As an alternative, we can still use the where function but only execute the main computation where it is appropriate:

# alternative implementation -- a bit more typing but avoids warnings.
loc = np.where(myarray>0)
result2 = np.zeros_like(myarray, dtype=float)
result2[loc] =np.log(myarray[loc])

# answer from Enrico...
myarray= np.random.randint(10,size=10)
result = np.where(myarray>0, np.log(myarray), 0)

# check it is giving right solution:
print(np.allclose(result, result2))

My use case was for division, but the principle is clearly the same:

x = np.random.randint(10, size=10)
divisor = np.ones(10,)
divisor[3] = 0 # make one divisor invalid

y = np.zeros_like(divisor, dtype=float)
loc = np.where(divisor>0) # (or !=0 if your data could have -ve values)
y[loc] = x[loc] / divisor[loc]