Numpy: Is this the most efficient way to add a column of ones to a 1D vector?

Question

In my Python script, I load a 1D vector from a .dat file. I want to use that vector as the first column in a matrix, where the second column is filled with 1s. This is how I did it:

I am working on vectors using python script, what I am trying to do is. I am taking a vector as my first column in my matrix, my second column consists of 1s value. This is how it looks:

x = np.loadtxt( 'x.dat' )

m = x.shape[0]

X = np.concatenate((x.reshape((m,1)), np.ones((m,1))), axis=1)

Is there any other way to achieve it?

Answer 1

The code you have used is completely perfect to me but if you are concerned about the performance of code then you can use this:

X = np.ones((m, 2))

X[:,0] = x

OR

X = np.empty((m, 2))

X[:,0] = x

X[:,1] = 1

Even when you add one more column it doesn't affect your performance this might be a surprise to you. You can change your data format to np.save/np.load instead of np.loadtxt. This is must faster.

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