Using python array's column as boolean to change another column's values

Question

I am farily new to python, so that may be why I haven't been able to search properly in this site for an answer to my problem, in case someone know about it already.

I am reading several data files consisting in six columns: XYZ coordinates and 3-vector components around a sphere. I am using the X and Z coordinates to find the angle location of my vectors, and using the angle results as a new column to my array, as a fourth column. So, I have a 7 column array.

The angles are calculated with np.arctan and they get (-) or (+) sign depending on the quadrant the XZ coordinates are located.

Now, I want to make all the angles around the upper half of the sphere (Z positive) positive and spanning from 0º to 180º. On the other hand, I want my angles around the lower half to be negative, and going from 0º to -180º.

The operations to change sign and apply the 0º-180º range are easy to implement. But, I want to use the third column of my array (Z coordinates) as the boolean to decide how to change the angles (fourth column of the array). I have read quite a lot of info about slicing arrays, or modifying columns/rows based on arbitrary boolean conditions applied to the same columns/rows.

I am trying to avoid combining for-loops and if-statements, and learn how to use the power of the python :)

Thanks in advance!

You should use np.arctan2(a, b) in place of np.arctan(a/b). i think this might solve your entire problem — Eric
– Eric, Commented Feb 5, 2016 at 17:10
It might help if you could provide sample data, and what you might expect the output to be. If you have some code, even better! — Wayne Werner
– Wayne Werner, Commented Feb 5, 2016 at 17:12
Thank you Eric, that has fixed it! I guess I need to re-read about arctan2 more carefully. — Carlos E. MV
– Carlos E. MV, Commented Feb 7, 2016 at 20:45
Wayne, I didn't think it was necessary to post a chunck of my data. Apologies for that, next time I will be mroe thorough in my question. — Carlos E. MV
– Carlos E. MV, Commented Feb 8, 2016 at 11:56

Eric · Accepted Answer · 2016-02-05 17:13:02Z

1

np.where(cond, if_true, if_false) solves the problem you think you have:

fixed_angle = np.where(z > 0, angle, -angle)

The problem you actually have is that you are not using atan2, or as it's spelt in numpy, np.arctan2

answered Feb 5, 2016 at 17:13

Eric

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2 Comments

Carlos E. MV Over a year ago

Thanks for the detailed answer Eric!

Carlos E. MV Over a year ago

Double thanks! I've just found out it also converts my angle range to the one desired. Where can I add stars to your comment???

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