# scalar vs array and program control

Peter Otten __peter__ at web.de
Sat Jul 25 15:46:03 CEST 2015

```Seb wrote:

> Hello,
>
> I'm fairly new to Python, struggling to write in a more object-oriented,
> functional style.  I just wrote a function that takes two arrays
> representing sine (y) and cosine (x) angle coordinates, and returns the
> angle in degrees.  I had initially written the function to take
> array-like arguments x/y, but I'd like to generalize and take scalars as
> well.  However, the function has a subsetting operations, which don't
> work with scalars:
>
>     vmag = np.sqrt((x ** 2) + (y ** 2))
>     ang = np.arctan2(y, x)
>     ang[ang < 0] = ang[ang < 0] + (2 * np.pi) # output range 0 - 2*pi
>     ang[vmag == 0] = 0          # when magnitude is 0 the angle is also 0
>     ang[ang == 0] = 2 * np.pi   # convention
>
> If I want to take scalars x/y, I naively thought about implementing an
> if/else statement right before the subsetting operations.  However, my
> intuition tells me there must be a proper object-oriented solution to
> this.  Any tips appreciated.

Here's a "duck-typed" solution:

import numpy as np

def _f(x, y):
vmag = np.sqrt((x ** 2) + (y ** 2))
ang = np.arctan2(y, x)
ang[ang < 0] = ang[ang < 0] + (2 * np.pi) # output range 0 - 2*pi
ang[vmag == 0] = 0          # when magnitude is 0 the angle is also 0
ang[ang == 0] = 2 * np.pi   # convention
return ang

def f(x, y):
try:
return _f(x, y)
except IndexError:
return _f(np.array([x]), y)[0]

However, this is quite inefficient for scalars. Personally I'd implement two
versions, one for scalars and one for vectors. This may be a little less
convenient, but most of the time the client code has to deal either with
scalars or vectors, not both.

```