pic-scale 0.7.8

High performance image scaling
Documentation 
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/*
 * Copyright (c) Radzivon Bartoshyk. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 * 1.  Redistributions of source code must retain the above copyright notice, this
 * list of conditions and the following disclaimer.
 *
 * 2.  Redistributions in binary form must reproduce the above copyright notice,
 * this list of conditions and the following disclaimer in the documentation
 * and/or other materials provided with the distribution.
 *
 * 3.  Neither the name of the copyright holder nor the names of its
 * contributors may be used to endorse or promote products derived from
 * this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
 * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */

use crate::math::consts::ConstPI;
use num_traits::{AsPrimitive, Float};
use pxfm::f_expf;
use std::ops::{Mul, MulAssign, Neg};

pub(crate) trait Exponential {
    fn f_exp(self) -> Self;
}

impl Exponential for f32 {
    #[inline]
    fn f_exp(self) -> Self {
        f_expf(self)
    }
}

impl Exponential for f64 {
    fn f_exp(self) -> Self {
        pxfm::f_exp(self)
    }
}

pub(crate) fn gaussian<
    V: ConstPI + Copy + Neg<Output = V> + Mul<Output = V> + MulAssign + 'static + Float + Exponential,
>(
    x: V,
) -> V
where
    f32: AsPrimitive<V>,
{
    let sigma: V = 0.35f32.as_();
    let pi = V::const_pi();
    let mut den = 2f32.as_() * sigma * sigma;
    den *= den;
    (1f32.as_() / ((2f32.as_() * pi).sqrt() * sigma)) * (-x / den).f_exp()
}