Numpy arrays with arraysd

Question

Is it possible to fulfill numpy arrays with arrays? I want to obtain a following structure without specifying values by hand

ves = np.zeros((12,12), dtype=object)
ves[0][0] = np.array([0,0,0])
ves[0][1] = np.array([0,0,0])
ves[0][2] = np.array([0,0,0])
ves[0][3] = np.array([0,0,0])
and so on...

In order to obtain the expected result, I have tried ves = np.zeros((12,12), dtype=array), but it does not work.

It works fine, but I do not want to put values np.array([0,0,0]) by hand. I have tried specified dtype=array, but it didn't work — Monica
– Monica, Commented Mar 14, 2017 at 13:07
It seems like you want a 3D tensor. Can you try ves = np.zeros((12, 12, 3), dtype="int32")? — Robert Valencia
– Robert Valencia, Commented Mar 14, 2017 at 13:16
Do you understand the difference between this (12,12) object array and a (12,12,3) integer array? — hpaulj
– hpaulj, Commented Mar 14, 2017 at 13:20

Naveen Honest Raj K · Accepted Answer · 2017-03-14 13:15:00Z

2

import numpy as np 

v = np.zeros([12,12,3])

As per my understanding through your explanation, it seems you wanted a three dimension matrix where each cell needs three 0 values for 12*12 places. So the above code creates the value filled ndarray.

answered Mar 14, 2017 at 13:15

Naveen Honest Raj K

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2 Comments

Monica Over a year ago

Thank you! Could you help me to understand what is the difference between np.zeros([12,12,3]) and np.zeros((12,12,3))?

zinjaai Over a year ago

There is no difference in the result. In the first case you input a list (marked by square brackets) in the second you input a tuple (round brackets). See here for more details: stackoverflow.com/questions/626759/…

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