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.
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