On Mon, 2021-07-26 at 01:04 -0400, Ivan Gonzalez wrote:
> It would be nice to be able to use the Python syntax we already use to
> format the precision of floating numbers in numpy:
> > > > a = np.array([-np.pi, np.pi])
> > > > print(f"{a:+.2f}")
> [-3.14 +3.14]
> This is particularly useful when you have large arrangements. The
> problem
> is that if you want to do it today, it is not implemented:
> > > > print(f"{a:+.2f}")
> Traceback (most recent call last):
> File "", line 1, in
> TypeError: unsupported format string passed to numpy.ndarray.__format__
This discussion has recently surfaced again and I am wondering what the
stance on it is for people?
The PR is: https://github.com/numpy/numpy/pull/19550
I.e. that things like "f{arr:.2f}" would be enabled in certain cases,
at least for all floating point and complex values.
I am wondering more about the general API progression here, since I do
not think we have any prior art to compare to.
* NumPy arrays are N-D objects (containers), do we want f/e formatting
to work for it?
* NumPy printing has a lot more option than just how to format each
element. Are we happy to say that implemeting `.2f` is fine without
unlocking other things?
* Some formatting might come with an expectation that the result has
that length `f"{3.123:30e}"` gas a length of 30, but for an
array that is obviously not true? Do we care about that?
I do not have much of an opinion on this. It feels a bit limited to
me, but if users thinks it is useful in practice I am happy to allow
it.
The PR had some other discussion about `__format__` being currently not
always correct/matching the Python behavior for scalars. But, I
believe these problems are either fixed, or can be fixed before we
merge.
Without any input, we may discuss this briefly in the community meeting
and likely give the go-ahead based on no opposition :).
Cheers,
Sebastian
>
> In this PR (https://github.com/numpy/numpy/pull/19550) I propose a very
> basic formatting implementation for numeric numbers that uses
> `array2string` just like it currently does `str`
>
> At first, since we are only considering formatting the numeric type,
> floating numbers specifically, we are only interested in being able to
> change the precision, the sign, and possibly the rounding or
> truncation.
> Since the `array2string` function already does everything we need, we
> only
> need to implement the` __format__` function of the `ndarray` class
> which
> parses a predefined format (similar to the one already used by Python
> for
> built-in data types) to indicate the parameters before said.
>
> I propose a mini format specification inspired in the [Format
> Specification
> Mini-
> Language](https://docs.python.org/3/library/string.html#formatspec).
>
> ```
> format_spec ::= [sign][.precision][type]
> sign ::= "+" | "-" | " "
> precision ::= [0-9]+
> type ::= "f" | "e"
> ```
>
> We are going to consider only 3 arguments of the `array2string`
> function:`
> precision`, `suppress_small`,` sign`. In particular, the `type` token
> sets
> the` suppress_small` argument to True when the type is `f` and False
> when
> it is `e`. This is in order to mimic Python's behavior in truncating
> decimals when using the fixed-point notation.
>
> As @brandon-rhodes said in gh-5543, the behavior when you try to format
> an
> array containing Python objects, the behavior should be the same as
> Python
> has implemented by default in the `object` class: ` format (a, "") `
> should
> be equivalent to `str (a)` and `format(a, "not empty")` should raise an
> exception.
>
> What remains to be defined is the behavior when trying to format an
> array
> with a non-numeric data type (`np.numeric`) other than `np.object_`.
> Should
> we raise an exception? In my opinion yes, since in the future
> formatting is
> extended -- for example, for dates -- people are aware that before that
> was
> not implemented.
>
> I'm open to suggestions.
>
> - Ivan
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