Robert Jacques wrote:
On Sat, 07 Nov 2009 12:56:35 -0500, Andrei Alexandrescu
<[email protected]> wrote:
Robert Jacques wrote:
I'd recommend rolling that into a basic statistics struct containing
common single pass metrics: i.e. sum, mean, variance, min, max, etc.
Well the problem is that if you want to compute several one-pass
statistics in one pass, you'd have to invent means to combine these
functions. That ability is already present in reduce, e.g. reduce(min,
max)(range) yields a pair containing the min and the max element after
exactly one pass through range.
Andrei
Yes, but reduce(mean, std)(range) doesn't work.
From std.algorithm's doc:
// Compute sum and sum of squares in one pass
r = reduce!("a + b", "a + b * b")(tuple(0.0, 0.0), a);
// Compute average and standard deviation from the above
auto avg = r.field[0] / a.length;
auto stdev = sqrt(r.field[1] / a.length - avg * avg);
I'm not saying there's no need for a more specialized library, just that
I purposely designed reduce to be no slouch either.
Even reduce(count) would
require the range to be mapped.
(This I don't get.)
Besides, in my use case I need lazy
evaluation, and I'd much rather add elements to a statistics struct,
than write a range wrapper.
Well if you go for surgery on an existing struct then the opportunity
for reuse is diminished.
Andrei
