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...
>>> 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