Creating an array of arrays will fail when the first dimension matches the first dimension

Question

I messed up some behavior of a function np.arraythat I don't understand. This code works as I expect:

arr1 = np.zeros((3,2))
arr2 = np.zeros((2,2))

np.array([arr1,arr2])

array([ array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.]]),
       array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.],
       [ 0.,  0.,  0.]])], dtype=object)

But this code gives me an error:

arr1 = np.zeros((2,3))
arr2 = np.zeros((2,2))

np.array([arr1,arr2])

ValueError: could not pass the input array from form (2,3) to form (2)

Why does it matter if the size of the first dimension matches? And how can I make a function behave like in the first example?

Answer 1

As noted in the numpy 1.9.2 array receiving a ValueError: failed to pass the input array from form (4,2) to form (4)

, . np.array . , , . .

-

In [242]: a=np.zeros((2,3));b=np.ones((2,2))

In [243]: arr=np.zeros((2,), object)
In [244]: arr[0]=a; arr[1]=b

In [245]: arr
Out[245]: 
array([array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.]]),
       array([[ 1.,  1.],
       [ 1.,  1.]])], dtype=object)
In [246]: arr[:]=[a,b]           # also works

, np.array([a.T, b]). , 2d ; 2 3 - .

In [250]: np.array([a.tolist(),b.tolist()])
Out[250]: 
array([[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]],
       [[1.0, 1.0], [1.0, 1.0]]], dtype=object)

In [251]: _.shape
Out[251]: (2, 2)

np.array , . , , ( ). .

: , np.array . .

, :

In [252]: np.array([a,a]).shape
Out[252]: (2, 2, 3)

arr[...]=[a,a], 2 .