python numpy machine epsilon

I am trying to understand what is machine epsilon. According to the Wikipedia, it can be calculated as follows:

def machineEpsilon(func=float):
    machine_epsilon = func(1)
    while func(1)+func(machine_epsilon) != func(1):
        machine_epsilon_last = machine_epsilon
        machine_epsilon = func(machine_epsilon) / func(2)
    return machine_epsilon_last

However, it is suitable only for double precision numbers. I am interested in modifying it to support also single precision numbers. I read that numpy can be used, particularly numpy.float32 class. Can anybody help with modifying the function?

Answers:

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Method 1

An easier way to get the machine epsilon for a given float type is to use np.finfo():

print(np.finfo(float).eps)
# 2.22044604925e-16

print(np.finfo(np.float32).eps)
# 1.19209e-07

Method 2

Another easy way to get epsilon is:

In [1]: 7./3 - 4./3 -1
Out[1]: 2.220446049250313e-16

Method 3

It will already work, as David pointed out!

>>> def machineEpsilon(func=float):
...     machine_epsilon = func(1)
...     while func(1)+func(machine_epsilon) != func(1):
...         machine_epsilon_last = machine_epsilon
...         machine_epsilon = func(machine_epsilon) / func(2)
...     return machine_epsilon_last
... 
>>> machineEpsilon(float)
2.220446049250313e-16
>>> import numpy
>>> machineEpsilon(numpy.float64)
2.2204460492503131e-16
>>> machineEpsilon(numpy.float32)
1.1920929e-07

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0