[Solved] Convert ndarray from float64 to integer
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?
Solution #1:
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:
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.])
The int* functions from NumPy
>>> np.int64(arr)
array([1, 2, 3, 4])
>>> np.int_(arr)
array([1, 2, 3, 4])
The NumPy *array functions themselves:
>>> 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])
The astype method (that was already mentioned but for completeness sake):
>>> 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:
There’s also a really useful discussion about converting the array in place, 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.