CODEWITHSUNDEEP
pythonarraysnumpyappend
Joseph
Joseph

Reputation: 73

Append arrays of different dimensions to get a single array

l have three vectors (numpy arrays), vector_1, vector_2, vector_3 as follow :

Dimension(vector1)=(200,2048)

Dimension(vector2)=(200,8192)

Dimension(vector3)=(200,32768)

l would like to append these vectors to get vector_4 :

Dimension(vector4)= (200,2048+8192+32768)= (200, 43008)

Add respectively vector1 then vector2 then vector3

l tries the following :

vector4=numpy.concatenate((vector1,vector2,vector3),axis=0)

ValueError: all the input array dimensions except for the concatenation axis must match exactly

and

vector4=numpy.append(vector4,[vector1,vector2,vectors3],axis=0)

TypeError: append() missing 1 required positional argument: 'values'

Upvotes: 1

Views: 4969

Answers (2)

juanpa.arrivillaga
juanpa.arrivillaga

Reputation: 95948

The error message is pretty much telling you exactly what is the problem:

ValueError: all the input array dimensions except for the concatenation axis must match exactly

But you are doing the opposite, the concatenation axis dimensions match exactly but the others don't. Consider:

In [3]: arr1 = np.random.randint(0,10,(20, 5))

In [4]: arr2 = np.random.randint(0,10,(20, 3))

In [5]: arr3 = np.random.randint(0,10,(20, 11))

Note the dimensions. Just give it the correct axis. So use the second rather than the first:

In [8]: arr1.shape, arr2.shape, arr3.shape
Out[8]: ((20, 5), (20, 3), (20, 11))

In [9]: np.concatenate((arr1, arr2, arr3), axis=1)
Out[9]:
array([[3, 1, 4, 7, 3, 6, 1, 1, 6, 7, 4, 6, 8, 6, 2, 8, 2, 5, 0],
       [4, 2, 2, 1, 7, 8, 0, 7, 2, 2, 3, 9, 8, 0, 7, 3, 5, 9, 6],
       [2, 8, 9, 8, 5, 3, 5, 8, 5, 2, 4, 1, 2, 0, 3, 2, 9, 1, 0],
       [6, 7, 3, 5, 6, 8, 3, 8, 4, 8, 1, 5, 4, 4, 6, 4, 0, 3, 4],
       [3, 5, 8, 8, 7, 7, 4, 8, 7, 3, 8, 7, 0, 2, 8, 9, 1, 9, 0],
       [5, 4, 8, 3, 7, 8, 3, 2, 7, 8, 2, 4, 8, 0, 6, 9, 2, 0, 3],
       [0, 0, 1, 8, 6, 4, 4, 4, 2, 8, 4, 1, 4, 1, 3, 1, 5, 5, 1],
       [1, 6, 3, 3, 9, 2, 3, 4, 9, 2, 6, 1, 4, 1, 5, 6, 0, 1, 9],
       [4, 5, 4, 7, 1, 4, 0, 8, 8, 1, 6, 0, 4, 6, 3, 1, 2, 5, 2],
       [6, 4, 3, 2, 9, 4, 1, 7, 7, 0, 0, 5, 9, 3, 7, 4, 5, 6, 1],
       [7, 7, 0, 4, 1, 9, 9, 1, 0, 1, 8, 3, 6, 0, 5, 1, 4, 0, 7],
       [7, 9, 0, 4, 0, 5, 5, 9, 8, 9, 9, 7, 8, 8, 2, 6, 2, 3, 1],
       [4, 1, 6, 5, 4, 5, 6, 7, 9, 2, 5, 8, 6, 6, 6, 8, 2, 3, 1],
       [7, 7, 8, 5, 0, 8, 5, 6, 4, 4, 3, 5, 9, 8, 7, 9, 8, 8, 1],
       [3, 9, 3, 6, 3, 2, 2, 4, 0, 1, 0, 4, 3, 0, 1, 3, 4, 1, 3],
       [5, 1, 9, 7, 1, 8, 3, 9, 4, 7, 6, 7, 4, 7, 0, 1, 2, 8, 7],
       [6, 3, 8, 0, 6, 2, 1, 8, 1, 0, 0, 3, 7, 2, 1, 5, 7, 0, 7],
       [5, 4, 7, 5, 5, 8, 3, 2, 6, 1, 0, 4, 6, 9, 7, 3, 9, 2, 5],
       [1, 4, 8, 5, 7, 2, 0, 2, 6, 2, 6, 5, 5, 4, 6, 1, 8, 8, 1],
       [4, 4, 5, 6, 2, 6, 0, 5, 1, 8, 4, 5, 8, 9, 2, 1, 0, 4, 2]])

In [10]: np.concatenate((arr1, arr2, arr3), axis=1).shape
Out[10]: (20, 19)

Upvotes: 0

timgeb
timgeb

Reputation: 78690

I believe you are looking for numpy.hstack.

>>> import numpy as np
>>> a = np.arange(4).reshape(2,2)
>>> b = np.arange(6).reshape(2,3)
>>> c = np.arange(8).reshape(2,4)
>>> a
array([[0, 1],
       [2, 3]])
>>> b
array([[0, 1, 2],
       [3, 4, 5]])
>>> c
array([[0, 1, 2, 3],
       [4, 5, 6, 7]])
>>> np.hstack((a,b,c))
array([[0, 1, 0, 1, 2, 0, 1, 2, 3],
       [2, 3, 3, 4, 5, 4, 5, 6, 7]])

Upvotes: 1

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