Add simple_efficiency tests to cover numpy arrays and pandas Series

[aman-coder03]

Description

pvlib.transformer.simple_efficiency supports vectorized operations via
NumPy, but the current test coverage primarily exercises scalar inputs.

This issue proposes adding tests that explicitly cover
numpy.ndarray inputs for:

• input_power
• load_loss
• no_load_loss

including the edge case load_loss = 0.

[echedey-ls]

For reference, this is the file that contains the tests: https://github.com/pvlib/pvlib-python/blob/main/tests/test_transformer.py
It is indeed testing with pd.Series and scalar inputs. I don't oppose nor support checking extra types for simplicity.

[cwhanse]

@echedey-ls I think the three device parameters are only tested as float, not for the range of numeric described in the docstring.

[echedey-ls]

@cwhanse you are right. At first I didn't think it would make much sense to run this function on many transformers at the same time, but maybe it does to pick the best one from a list to fit an specific scenario. I still wonder if added complexity is beneficial. I think documenting this broadcast via a small docstring example is more important than testing it.

[cwhanse]

Many transformers, or perhaps the loss parameters vary with time (temperature dependent?). Either way, it's not the usual use of the function, and we could just change the docstring type from numeric to float.