Merge axis in numpy array

Question

I want to convert X,Y,Z numpy array to (X*Z)*Y numpy array.

Code(Slow):

 def rearrange(data):
        samples,channels,t_insts=data.shape
        append_data=np.empty([0,channels])
        for sample in range(0,samples):
            for t_inst in range(0,t_insts):
                channel_data=data[sample,:,t_inst]
                append_data=np.vstack((append_data,channel_data))
        return append_data.shape

I am looking for a better vectorized approach if possible

Divakar · Accepted Answer · 2015-08-10 10:25:06Z

11

You can use np.transpose to swap rows with columns and then reshape -

data.transpose(0,2,1).reshape(-1,data.shape[1])

Or use np.swapaxes to do the swapping of rows and columns and then reshape -

data.swapaxes(1,2).reshape(-1,data.shape[1])

answered Aug 10, 2015 at 10:25

Divakar

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2 Comments

Gulzar Over a year ago

Is there some more general method for this? Say I want to convert array of shape (4,5,6,7,8,9) to (4,5*6*8,7,9)

Divakar Over a year ago

@Gulzar a.transpose(0,1,2,4,3,5) and then reshape to desired shape. Idea being - Bring the axes to be merged in sequence and then reshape. This could be a relevant post - stackoverflow.com/a/47978032

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