Using D and std.ndslice as a Numpy Replacement
Ilya Yaroshenko via Digitalmars-d-announce
digitalmars-d-announce at puremagic.com
Sat Jan 2 16:17:23 PST 2016
On Sunday, 3 January 2016 at 00:09:33 UTC, Jack Stouffer wrote:
> On Saturday, 2 January 2016 at 23:51:09 UTC, Ilya Yaroshenko
> wrote:
>> This benchmark is _not_ lazy, so ndslice faster than Numpy
>> only 3.5 times.
>
> I don't know what you mean here, I made sure to call
> std.array.array to force allocation.
In the article:
auto means = 100_000.iota <---- 100_000.iota is lazy range
.sliced(100, 1000)
.transposed
.map!(r => sum(r) / r.length)
.array; <---- allocation of the result
In GitHub:
means = data <---- data is allocated array, it is
fair test for real world
.sliced(100, 1000)
.transposed
.map!(r => sum(r, 0L) / cast(double) r.length)
.array; <---- allocation of the result
-- Ilya
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