CODEWITHSUNDEEP
pythonnumpyipython
ninjaSurfer
ninjaSurfer

Reputation: 157

Numpy array, power operator, wrong value/sign

When I execute the below on Ipython:

test = np.array([1,2,3,4])
test**50

it returns:

array([          1, -2147483648, -2147483648, -2147483648])

which has both the wrong value and sign. Any clues why I might be getting this?

Upvotes: 2

Views: 1290

Answers (1)

MB-F
MB-F

Reputation: 23637

As mentioned in the comments, this happens because the integer data type overflows. Numpy initializes the array with a low level int data type because that fits the data you provided.

test = np.array([1,2,3,4])
test.dtype
# dtype('int32')

test[0] = 2**31 - 1  # works
test[0] = 2**31      # OverflowError: Python int too large to convert to C long

A 32 bit signed integer is used (on my system), which can hold values between -2147483648 and 2147483647.

You can force the array to have a different data type, e.g. floating point:

test = np.array([1, 2, 3, 4], dtype=float)
# test = np.array([1.0, 2.0, 3.0, 4.0])  # this is the same
test**50

# array([  1.00000000e+00,   1.12589991e+15,   7.17897988e+23, 1.26765060e+30])

Here is a list of data types that can be passed as strings to the dtype argument.

If you want Python's large integers instead of floating point precision, this works too (performance warning):

test = np.array([1,2,3,4], dtype=object)
test**50

# array([1, 1125899906842624, 717897987691852588770249, 
#        1267650600228229401496703205376], dtype=object)

Upvotes: 2

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