Unexpected behavior when tracing index array in python

Question

I'm running into some unexpected behavior using a while loop to get index quantities related to tracing quantities from one array to another.

My input code is:

from numpy import array
from numpy.ma import where as mwhere
from numpy.ma import masked_array, masked
start_pts = array([False, True, False, False, False, False, True, False, False, False, True])
active    = array([True, True, True, True, True, True, True, True, True, True, True])
spline_index = array([0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2])
pt0     = array([1, 0, 3, 0, 6, 4, 0, 8, 9, 10, 0])
m_a_pt0 = masked_array(pt0, start_pts)

for i in range(3):
    # start pt
    pt = mwhere((spline_index[active] == i) & (start_pts[active] == 1))
    print pt
    while pt[0]:
        pt = mwhere((spline_index[active] == i) & (m_a_pt0[active] == pt[0]))
        print i, pt

I am expecting an output of:

(array([1]),)
0 (array([0]),)
0 (array([3]),)
0 (array([2]),)
0 (array([], dtype=int64,)
(array([6]),)
1 (array([4]),)
1 (array([5]),)
1 (array([], dtype=int64),)
(array([10]),)
2 (array([9]),)
2 (array([8]),)
2 (array([7]),)
2 (array([], dtype=int64),)

But instead the while loop exits when pt = array([0],) and I get:

(array([1]),)
0 (array([0]),)
(array([6]),)
1 (array([4]),)
1 (array([5]),)
1 (array([], dtype=int64),)
(array([10]),)
2 (array([9]),)
2 (array([8]),)
2 (array([7]),)
2 (array([], dtype=int64),)

But if I test a value where:

test = (array([0]),)
print mwhere((spline_index[active] == 0) & (m_a_pt0[active] == test[0]))

This returns the expected tuple with array:

(array([3]),)

Why is my while loop prematurely exiting for array([0]), when values still exist?

BrenBarn · Accepted Answer · 2017-05-26 17:41:09Z

2

Numpy arrays with length one have the truth value of their single element. See for instance this question. If you want to check if the array is empty, check if its length is zero.

answered May 26, 2017 at 17:41

BrenBarn

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1 Comment

stagermane Over a year ago

Thanks! I was trying to do a more "pythonic" check as seen here, but missed that it is not valid for arrays.

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