(Suggestion) Handling div-by-zero

[rtbs-dev]

Hi there! Running into a number of division warnings throughout the layout algorithm code, and thought I might offer up a few solutions for consideration

• I've used a "safe-divide" template for any time I do large matrix normalization (e.g. bulk vector norms in a denominator), and this works pretty great for me:

def _safe_div(num, den):
   return np.divide(
       num,
       den,
       out=np.zeros_like(num, dtype=float),
       where=den != 0,
   )

• another option for e.g. logs is to use np.mask.<ufunc>, which automatically handles errors in a pretty nice way, though the api won't assume any replacements so you need to start writing masked_array.filled(0.) or similar to get back a normal numpy array. This one is super nice for the dev side ,but users aren't generally familiar so I tend to hide masking details until I'm done with them.

For reference, here's an example just now when using the edge_layout='curved' option:

python3.11/site-packages/netgraph/_utils.py:360: RuntimeWarning: invalid value encountered in divide
  v = v / np.linalg.norm(v, axis=-1)[:, None] # unit vector

Some additive-smoothing code I was writing ran into stuff like this all the time before I switched to either a pre-allocated np.zeros_like or an np.mask.