Concatenating two numpy array

Question

I have two numpy arrays which I have to join them side-by side, for example one has a shape of (100,1,300,1) and another one has a shape of (100,1,400,1), the output shape should be (100,1,700,1). I have written below codes but I need to join both np_predict and np_predict_borders as the way I told

np_predict = model.predict(np.array(images))
np_predict=np_predict.reshape(np_predict.shape[0],1,np_predict.shape[1],1)

np_predict_e=model.predict(np.array(images_e))
np_predict_e = np_predict_e.reshape(np_predict_e.shape[0], 1, np_predict_e.shape[1], 1)

I am not sure what command I have to use in numpy to join them?

You have the command in your title.

Mr. T
– Mr. T

2021-02-22 08:57:07 +00:00
Commented Feb 22, 2021 at 8:57 — Mr. T
– Mr. T, Commented Feb 22, 2021 at 8:57

rozumir · Accepted Answer · 2021-02-22 09:06:01Z

1

Use np.concatenate, in axis parameter you define direction of concatenation.

>>> import numpy as np
>>> a = np.zeros((100,1,300,1))
>>> b = np.zeros((100,1,400,1))
>>> c = np.concatenate((a,b),axis=2)
>>> c.shape
(100, 1, 700, 1)

answered Feb 22, 2021 at 9:06

rozumir

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2 Comments

Mah Over a year ago

Can you explain what is the direction of concatenations, and what are axis=0,1, or 2?

rozumir Over a year ago

@Mah "The axis along which the arrays will be joined", you can understand this as dimmension, your array have 4 dim, so if you want to concat at 3rd dim, you type axis=2

joostblack · Accepted Answer · 2021-02-22 09:02:14Z

0

You can do this in many ways with numpy. One possibility is using np.dstack:

import numpy as np


A=np.zeros((100,1,300,1))
B = np.ones((100,1,400,1))
C = np.dstack((A,B))
print(C.shape)

output:

(100, 1, 700, 1)

answered Feb 22, 2021 at 9:02

joostblack

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