I need to find a numpy.float64 value that is as close to zero as possible.

Numpy offers several constants that allow to do something similar:

• np.finfo(np.float64).eps = 2.2204460492503131e-16
• np.finfo(np.float64).tiny = 2.2250738585072014e-308

These are both reasonably small, but when I do this

>>> x = np.finfo(np.float64).tiny
>>> x / 2
6.9533558078350043e-310

the result is even smaller. When using an impromptu binary search I can get down to about 1e-323, before the value is rounded down to 0.0.

Is there a constant for this in numpy that I am missing? Alternatively, is there a right way to do this?

Use np.nextafter.

>>> import numpy as np
>>> np.nextafter(0, 1)
4.9406564584124654e-324
>>> np.nextafter(np.float32(0), np.float32(1))
1.4012985e-45