Numpy object array of numerical arrays

Question

I want to create an array with dtype=np.object, where each element is an array with a numerical type, e.g int or float. For example:

>>> a = np.array([1,2,3])
>>> b = np.empty(3,dtype=np.object)
>>> b[0] = a
>>> b[1] = a
>>> b[2] = a

Creates what I want:

>>> print b.dtype
object

>>> print b.shape
(3,)

>>> print b[0].dtype
int64

but I am wondering whether there isn't a way to write lines 3 to 6 in one line (especially since I might want to concatenate 100 arrays). I tried

>>> b = np.array([a,a,a],dtype=np.object)

but this actually converts all the elements to np.object:

>>> print b.dtype
object

>>> print b.shape
(3,)

>>> print b[0].dtype
object

Does anyone have any ideas how to avoid this?

tom10 · Accepted Answer · 2010-07-19 03:46:30Z

3

It's not exactly pretty, but...

import numpy as np

a = np.array([1,2,3])
b = np.array([None, a, a, a])[1:]

print b.dtype, b[0].dtype, b[1].dtype
# object int32 int32

answered Jul 19, 2010 at 3:46

tom10

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Comments

joeln · Accepted Answer · 2015-01-27 02:15:22Z

3

a = np.array([1,2,3])
b = np.empty(3, dtype='O')
b[:] = [a] * 3

should suffice.

edited Jan 27, 2015 at 2:15

answered Jan 26, 2015 at 11:38

joeln

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Comments

astrofrog · Accepted Answer · 2010-07-18 18:19:35Z

0

I can't find any elegant solution, but at least a more general solution to doing everything by hand is to declare a function of the form:

def object_array(*args):
    array = np.empty(len(args), dtype=np.object)
    for i in range(len(args)):
        array[i] = args[i]
    return array

I can then do:

a = np.array([1,2,3])
b = object_array(a,a,a)

I then get:

>>> a = np.array([1,2,3])
>>> b = object_array(a,a,a)
>>> print b.dtype
object
>>> print b.shape
(3,)
>>> print b[0].dtype
int64

answered Jul 18, 2010 at 18:19

astrofrog

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Comments

SiggyF · Accepted Answer · 2010-07-17 21:04:55Z

-1

I think anyarray is what you need here:

b = np.asanyarray([a,a,a])
>>> b[0].dtype
dtype('int32')

not sure what happened to the other 32bits of the ints though.

Not sure if it helps but if you add another array of a different shape, it converts back to the types you want:

import numpy as np
a = np.array([1,2,3])
b = np.array([1,2,3,4])
b = np.asarray([a,b,a], dtype=np.object)
print(b.dtype)
>>> object
print(b[0].dtype)
>>> int32

edited Jul 17, 2010 at 21:04

answered Jul 17, 2010 at 20:09

SiggyF

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2 Comments

SiggyF Over a year ago

That must be my python running in 32bit.

astrofrog Over a year ago

That doesn't seem to work, as b.dtype is of type np.int64, not np.object.

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