How to convert 2D float numpy array to 2D int numpy array?

Question

How to convert real numpy array to int numpy array? Tried using map directly to array but it did not work.

Answer 1

you can use np.int_:

>>> x = np.array([[1.0, 2.3], [1.3, 2.9]])
>>> x
array([[ 1. ,  2.3],
       [ 1.3,  2.9]])
>>> np.int_(x)
array([[1, 2],
       [1, 2]])

Answer 2

Use the astype method.

>>> x = np.array([[1.0, 2.3], [1.3, 2.9]])
>>> x
array([[ 1. ,  2.3],
       [ 1.3,  2.9]])
>>> x.astype(int)
array([[1, 2],
       [1, 2]])

Answer 3

If you're not sure your input is going to be a Numpy array, you can use asarray with dtype=int instead of astype:

>>> np.asarray([1,2,3,4], dtype=int)
array([1, 2, 3, 4])

If the input array already has the correct dtype, asarray avoids the array copy while astype does not (unless you specify copy=False):

>>> a = np.array([1,2,3,4])
>>> a is np.asarray(a)  # no copy :)
True
>>> a is a.astype(int)  # copy :(
False
>>> a is a.astype(int, copy=False)  # no copy :)
True

Answer 4

Some numpy functions for how to control the rounding: rint, floor,trunc, ceil. depending how u wish to round the floats, up, down, or to the nearest int.

>>> x = np.array([[1.0,2.3],[1.3,2.9]])
>>> x
array([[ 1. ,  2.3],
       [ 1.3,  2.9]])
>>> y = np.trunc(x)
>>> y
array([[ 1.,  2.],
       [ 1.,  2.]])
>>> z = np.ceil(x)
>>> z
array([[ 1.,  3.],
       [ 2.,  3.]])
>>> t = np.floor(x)
>>> t
array([[ 1.,  2.],
       [ 1.,  2.]])
>>> a = np.rint(x)
>>> a
array([[ 1.,  2.],
       [ 1.,  3.]])

To make one of this in to int, or one of the other types in numpy, astype (as answered by BrenBern):

a.astype(int)
array([[1, 2],
       [1, 3]])

>>> y.astype(int)
array([[1, 2],
       [1, 2]])