logsumexp

Computes the log of the sum of exponentials of input elements.

auto logsumexp(A a)
template logsumexp(sumTemplateArgs...)
nothrow @nogc nothrow @nogc
auto
logsumexp
(
A
)
(
A a
)
if (
isSlice!A
)
auto logsumexp(A a, B b)

Members

Functions

logsumexp auto logsumexp(A a): Params a = input slice
logsumexp auto logsumexp(A a, B b): Params a = input slice b = scaling factor slice for exp(a) must have the same shape to b

Parameters

sumTemplateArgs: template arguments to pass to mir.math.sum (to compute the mean & standard deviation of the slice)

Examples

// logsumexp example from doctest https://github.com/scipy/scipy/blob/maintenance/1.0.x/scipy/special/_logsumexp.py
import mir.ndslice : iota, map, sliced, as;
import mir.math.common : log, exp;
import mir.math.sum;
import std.math : approxEqual;
{
    auto x = iota(10).as!double;
    assert(logsumexp(x).approxEqual(9.4586297444267107));
    assert(log(sum(map!exp(x))).approxEqual(logsumexp(x)));
}
{
    auto x = iota(0).as!double;
    assert(sum(x) == 0);
    assert(logsumexp(x) == -double.infinity);
    assert(log(sum(map!exp(x))).approxEqual(logsumexp(x)));
}
{
    auto a = iota(10).as!double;
    auto b = iota([10], 10, -1).as!double;
    assert(logsumexp(a, b).approxEqual(9.9170178533034665));
    assert(log(sum(map!exp(a) * b)).approxEqual(logsumexp(a, b)));
}
{
    auto a = iota(0).as!double;
    auto b = iota(0).as!double;
    assert(logsumexp(a, b) == -double.infinity);
    assert(log(sum(map!exp(a) * b)).approxEqual(logsumexp(a, b)));
}

logsumexp

Members

Functions

Parameters

Examples

See Also

Meta

Source