On Thu, 2022-09-08 at 21:15 -0400, Warren Weckesser wrote:
> On 9/8/22, Andrew Nelson <[email protected]> wrote:
>
> >
<snip>
> > For many types, this function makes an attempt to return a string
> > that would yield an object with the same value when passed to
> > eval();
>
> Sebastian, is this an explicit goal of the change? (Personally, I've
> gotten used to not taking this too seriously, but my world view is
> biased by the long-term use of NumPy, which has never followed this
> guideline.)
>
To me, that should be mainly a guiding principle maybe not a strict
goal. But I do wonder if there are any alternative thoughts on what
the representation should be?
Since I doubt Python will add infix operators that allow `123.4_f64`
soon that is probably not worth a thought :).
For booleans I think we previously had rather settled on `np.True_` and
`np.False_`.
Cheers,
Sebastian
> If that is a goal, than the floating point types with precision
> greater than double precision will need to display the argument of
> the
> type as a string. For example, the following is run on a platform
> where numpy.longdouble is extended precision (80 bits):
>
> ```
> In [161]: longpi = np.longdouble('3.14159265358979323846')
>
> In [162]: longpi
> Out[162]: 3.1415926535897932385
>
> In [163]: np.longdouble(3.1415926535897932385) # Argument is parsed
> as 64 bit float
> Out[163]: 3.141592653589793116
>
> In [164]: np.longdouble('3.1415926535897932385') # Correctly
> reproduces the longdouble
> Out[164]: 3.1415926535897932385
> ```
>
> Warren
>
> >
> > I think it definitely we should definitely have:
> >
> > repr(np.float32(34.3)) == 'float32(34.3)'
> > And
> > str(np.float32(34.3)) == '34.3'
> >
> > It seems buglike not to have that.
> >
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