Python Numpy - Treat really small numbers as zero

Question

I want to calculate the Determinant of a Singular Matrix (which has a 0 determinant) with Numpy and when I print the determinant it shows a really small number (which is nearly zero = -7.09974814699e-30) but not zero itself...

when I try to print the determinant either with %s, %d or %f, sometimes it's zero, sometimes -0 and sometimes -7.09974814699e-30 .

Here's the Code :

import numpy as np

array = np.arange(16)
array = array.reshape(4, -1)
determinant = np.linalg.det(array)

print("Determinant is %s" % determinant)
print("Determinant is %d" % determinant)
print("Determinant is %f" % determinant)

Determinant is -7.09974814699e-30
Determinant is 0
Determinant is -0.000000

How can I make Numpy treat really small numbers such as -7.09974814699e-30 as zero and show zero to me. I also asked this question before, if you take a look at the matrix you see that it's filled with really small numbers but not zero while it should be a diagonal matrix with numbers on the diagonal and zeros elsewhere...

Thank you...

Answer 1

>>> if np.abs(determinant) < 0.000001:
...     determinant=0
...
>>> print determinant
0

In case of array you can do it using a single operation (see my answer to your other question: https://stackoverflow.com/a/36395905/5088142)

To set array elements that are less than eps to zero:

array[np.abs(array) < eps] = 0