slideAlong

Lazy convolution for tensors.

Suitable for advanced convolution algorithms.

auto slideAlong(Slice!(Iterator, N, kind) slice)
template slideAlong(size_t params, alias fun, SDimensions...)
@optmath
static if(allSatisfy!(isSizediff_t, SDimensions) && params > 1 && __traits(isSame, naryFun!fun, fun))
@optmath
auto
slideAlong
(
Iterator
size_t N
SliceKind kind
)
(
Slice!(Iterator, N, kind) slice
)
if (
params <= 'z' - 'a' + 1 &&
SDimensions.length > 0
)
auto slideAlong(S[] slice)
auto slideAlong(S slice)
alias slideAlong = .map!(naryFun!fun)
alias slideAlong = .slideAlong!(params, naryFun!fun, staticMap!(toSizediff_t, SDimensions))

Members

Aliases

slideAlong alias slideAlong = .slideAlong!(params, naryFun!fun, staticMap!(toSizediff_t, SDimensions)): Undocumented in source.
slideAlong alias slideAlong = .map!(naryFun!fun): Undocumented in source.

Functions

slideAlong auto slideAlong(Slice!(Iterator, N, kind) slice)
auto slideAlong(S[] slice)
auto slideAlong(S slice)

Parameters

params: convolution windows length.
fun: one dimensional convolution function with params arity.
SDimensions: dimensions to perform lazy convolution along. Negative dimensions are supported.

Examples

auto data = [4, 5].iota;

alias scaled = a => a * 0.25;

auto v = data.slideAlong!(3, "a + 2 * b + c", 0).map!scaled;
auto h = data.slideAlong!(3, "a + 2 * b + c", 1).map!scaled;

assert(v == [4, 5].iota[1 .. $ - 1, 0 .. $]);
assert(h == [4, 5].iota[0 .. $, 1 .. $ - 1]);

slideAlong

Members

Aliases

Functions

Parameters

Examples

See Also

Meta

Source