Maximum allowed value for a numpy data type

Question

I am working with numpy arrays of a range of data types (uint8, uint16, int16, etc.). I would like to be able to check whether a number can be represented within the limits of an array for a given datatype. I am imagining something that looks like:

>>> im.dtype
dtype('uint16')
>>> dtype_max(im.dtype)
65535
>>> dtype_min(im.dtype)
0

Does something like this exist? By the way, I feel like this has to have been asked before, but my search came up empty, and all of the “similar questions” appear to be unrelated.

Edit: Of course, now that I’ve asked, one of the “related” questions does have the answer. Oops.

Asked By: jdmcbr

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Source

Answer 1

You’re looking for numpy.iinfo for integer types. Documentation here.

There’s also numpy.finfo for floating point types. Documentation here.

Answered By: Alex

Answer 2

min_value = np.iinfo(im.dtype).min
max_value = np.iinfo(im.dtype).max

docs:

np.iinfo (machine limits for integer types)
np.finfo (machine limits for floating point types)

Answered By: Bruno Gelb

Maximum allowed value for a numpy data type

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