On Jan 23, 2008 6:55 AM, Stefan van der Walt <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> The numpy documentation standard example shows:
>
> Parameters
> ----------
> var1 : array_like
> Array_like means all those objects -- lists, nested lists, etc. --
> that can be converted to an array.
> var2 : integer
> Write out the full type
> long_variable_name : {'hi', 'ho'}, optional
> Choices in brackets, default first when optional.
>
> I'd like to know:
>
> 1. "array_like" describes objects that can be forced to quack like
> ndarrays. Are there any other such "special" descriptions?
>
I can't think of any, but that doesn't mean there aren't any.
> 2. How do we specify default values?
>
I like to put them first in the list: {-1, integer}
> 3. Why do we need the "optional" keyword (the function signature
> already indicates that the parameter is optional).
>
It's extra information, true, but that isn't always a bad thing. It's like
looking up "whole numbers" in a book index and, instead of the page
reference, the index directs you to "numbers, whole". Flip, flip, flip.
Drives me crazy. Besides, the function signature might be missing.
> 4. Do we really need the "Other Parameters" list? It would make more
> sense to split positional and keyword arguments, but I'm not even
> sure that is necessary, since that information is already specified in
> the
> function signature.
>
I agree, but Travis likes this section and I don't feel strongly about it.
>
> 5. Is the {'hi', 'ho'} syntax used when a parameter can only assume a
> limited number of values? In Python {} is a dictionary, so why not
> use ('hi','ho') instead?
>
Either would be fine. IIRC, the {} was inherited from epydoc consolidated
fields.
Chuck
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