Convert ndarray from float64 to integer
PythonNumpyScipyPython Problem Overview
I've got an ndarray
in python with a dtype
of float64
. I'd like to convert the array to be an array of integers. How should I do this?
int()
won't work, as it says it can't convert it to a scalar. Changing the dtype
field itself obviously doesn't work, as the actual bytes haven't changed. I can't seem to find anything on Google or in the documentation - what's the best way to do this?
Python Solutions
Solution 1 - Python
Use .astype
.
>>> a = numpy.array([1, 2, 3, 4], dtype=numpy.float64)
>>> a
array([ 1., 2., 3., 4.])
>>> a.astype(numpy.int64)
array([1, 2, 3, 4])
See the documentation for more options.
Solution 2 - Python
While astype
is probably the "best" option there are several other ways to convert it to an integer array. I'm using this arr
in the following examples:
>>> import numpy as np
>>> arr = np.array([1,2,3,4], dtype=float)
>>> arr
array([ 1., 2., 3., 4.])
int*
functions from NumPy
The >>> np.int64(arr)
array([1, 2, 3, 4])
>>> np.int_(arr)
array([1, 2, 3, 4])
*array
functions themselves:
The NumPy >>> np.array(arr, dtype=int)
array([1, 2, 3, 4])
>>> np.asarray(arr, dtype=int)
array([1, 2, 3, 4])
>>> np.asanyarray(arr, dtype=int)
array([1, 2, 3, 4])
astype
method (that was already mentioned but for completeness sake):
The >>> arr.astype(int)
array([1, 2, 3, 4])
Note that passing int
as dtype to astype
or array
will default to a default integer type that depends on your platform. For example on Windows it will be int32
, on 64bit Linux with 64bit Python it's int64
. If you need a specific integer type and want to avoid the platform "ambiguity" you should use the corresponding NumPy types like np.int32
or np.int64
.
Solution 3 - Python
There's also a really useful discussion about converting the array in place, <https://stackoverflow.com/questions/4389517/in-place-type-conversion-of-a-numpy-array>;. If you're concerned about copying your array (which is whatastype()
does) definitely check out the link.
Solution 4 - Python
All I used is
numpyfloat = (1.0, 2.0, 4.0)
a = numpy.array(numpyfloat, dtype=numpy.int)
That's just it