How to stack a 'numpy masked array' and a 'numpy array'

Question

I have two numpy arrays:

A  = [ 186.,  176., 158.,  180.,  186.,  168.,  168.,  164.,  178.,  170.,  189.,  195.,
       172.,  187., 180.,  186.,  185.,  168.,  179.,  178.,  183.,  179.,  170.,  175.]

B = [  -1., 60., 45., 58., 70., 70., 60., 64., 68., 78., 80., 78.,
       66., 74., 84., 85., 75., 60., 71., 67., 88., -1., 70., 60.]

I want to stack only Positive values and I don't know how?

I used numpy masked array to mask "-1"s from B

thank you

" stack only Positive values": What does that mean? If C is the result of the operation you want to do, could you add to your question exactly what C would be? — Warren Weckesser
– Warren Weckesser, Commented Nov 15, 2013 at 22:56

Saullo G. P. Castro · Accepted Answer · 2013-11-16 13:38:34Z

4

Assuming you want to stack a and b for every position where b>=0:

check = (b>=0)
c = np.vstack((a[check], b[check]))

should do the job...

answered Nov 16, 2013 at 13:38

Saullo G. P. Castro

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Last Life Hump · Accepted Answer · 2013-11-15 21:14:14Z

0

Maybe use an unsigned value for it?

unsigned int array[2] = {0, 1};

http://en.wikipedia.org/wiki/Integer_(computer_science)#value_and_representation

answered Nov 15, 2013 at 21:14

Last Life Hump

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A.E. Drew · Accepted Answer · 2013-11-16 13:48:27Z

0

If you only need to stack 1-dimensional arrays and the removal of negative numbers from B will make its shape the same as A, this should work:

np.vstack( (A, B[B >= 0.0]) )

answered Nov 16, 2013 at 13:48

A.E. Drew

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2 Comments

Saullo G. P. Castro Over a year ago

this will must probably give you a ValueError since the arrays being stacked have different sizes...

A.E. Drew Over a year ago

@SaulloCastro Well it's unclear what the op wants, but yes I see what you mean. More likely he wants to filter out the elements in A and B if the element in B is negative, as your answer suggests.

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