merging/concatenating arrays with different elements

Question

How to merge a mix of different elements (matlab style) in numpy?

[array([ 0.]), 0.0, 0.0011627, 0.0, 2.69, 0.0, array([ 3.8269, 7.0184]), array([ 4.4e-16, 2.1e+00])]

(I tried np.concatenate, but obviously it only takes arrays as input). Basically, I want to dynamically concatenate elements from a vector by indexing. I tried:

 V = np.array([1,2,3,4,5,6])
 Y = np.array([7,8,9,10,11,12])

 Z = np.array([V[0:2],Y[0],V[3],Y[1:3],V[4:],Y[4:]])

It works, but has array elements inside. I just want a flat vector of numbers (Matlab style) as later I make a matrix (called RES) with a bunch of these vectors. Even a simple

 np.savetxt('TT',RES,fmt='%1.1e')

fails because it expects floats and not arrays inside.

Guess this should be simple. np.hstack does the job. But is there any other easy way to do Matlab style indexing & combining of vectors and scalars?

unutbu · Accepted Answer · 2014-02-24 14:28:56Z

31

You could use np.r_:

In [32]: Z = np.r_[V[0:2],Y[0],V[3],Y[1:3],V[4:],Y[4:]]

In [33]: Z
Out[33]: array([ 1,  2,  7,  4,  8,  9,  5,  6, 11, 12])

answered Feb 24, 2014 at 14:28

unutbu

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3 Comments

nahsivar Over a year ago

This is wonderful. Such methods seem to be hidden though as I've not come across them (np.s_, np.r_, np.c_ ) anywhere, yet! Gracias!

unutbu Over a year ago

Yes, this one is mentioned in the NumPy Reference Guide, but not the User Guide.

Sergey Antopolskiy Over a year ago

@nahsivar please accept the answer if it resolved your question

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