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```{index} single: PDL::Ufunc; Perl module
```

# PDL::Ufunc

```{pperl-module-badges} PDL::Ufunc
```

Unary reductions and aggregations over PDL arrays. This module holds
every operation that collapses one or more dimensions of a piddle
down to a summary — sums, products, means, extrema, percentiles,
sort-based reductions, and cumulative variants.

These are the first functions most users reach for. They behave
the same on 1-D arrays as on higher-rank arrays, and they all share
a consistent story about bad values, type promotion, and when they
reduce everything vs. just one axis.


##  Synopsis

    use PDL;
    my $a = pdl [1, 2, 3, 4, 5];
    print $a->sum, "\n";    # 15
    print $a->avg, "\n";    # 3
    print $a->min, "\n";    # 1
    print $a->max, "\n";    # 5

## Functions

### Full-array reductions

#### [`sum`](Ufunc/sum)

Add up every element of a PDL and return the total as a 0-dimensional PDL.

### Other Functions

#### `qsortvec`

`qsortvec($pdl)` — sort rows of a 2D pdl lexicographically, return sorted data.

#### `qsortveci`

`qsortveci($pdl)` — sort rows of a 2D pdl lexicographically, return index piddle.

#### `minimum_n_ind`

`minimum_n_ind($pdl, $n)` — 3-arg c2rust: (a, c, m_size)

#### `maximum_n_ind`

`maximum_n_ind($pdl, $n)` — 3-arg c2rust: (a, c, m_size)

#### `pctover`

`pctover($pdl, $pct)` — 3-arg c2rust: (a, p, b) where p is pct as a scalar pdl `pctover($pdl, $percentile)` — Excel/NIST linear-interpolation percentile. Mirrors `Ufunc.pd` pp_def('pctover') algorithm: rank = 1 + p*(n-1); interp between sorted[floor(rank)-1] and sorted[ceil(rank)-1]. The c2rust version produces rounding errors on the boundary (17.0000000007 != 17); this pure-Rust path avoids the double→double→double chain and is bit-exact when the interpolation happens on aligned indices.

#### `all`

`all($pdl)` — 1 if all elements nonzero, via full andover reduction

#### `any`

`any($pdl)` — 1 if any element nonzero, via full orover reduction

#### `minmax`

`minmax($pdl)` — return a 2-element list: (min_value, max_value). Iterates all elements via pdl_at_flat, tracking min and max.

#### `pct`

`pct($pdl, $p)` — percentile, delegates to pctover then extracts scalar. Returns a 0-d PDL scalar.

#### `oddpct`

`oddpct($pdl, $p)` — odd percentile (nearest-rank method). Sort the data, return element at index floor((n-1) * p). Returns a 0-d PDL scalar.

#### `stats`

`stats($pdl)` — compute 7 summary statistics. Returns (`$mean`, `$prms`, `$median`, `$min`, `$max`, `$adev`, `$rms`).

```{toctree}
:hidden:
:maxdepth: 1

Ufunc/sum
```