//! Utilities to handle smoothing parameter changes over time.

use atomic_float::AtomicF32;
use std::sync::atomic::{AtomicI32, Ordering};

/// Controls if and how parameters gets smoothed.
#[derive(Debug, Clone, Copy)]
pub enum SmoothingStyle {
    /// No smoothing is applied. The parameter's `value` field contains the latest sample value
    /// available for the parameters.
    None,
    /// Smooth parameter changes so the current value approaches the target value at a constant
    /// rate. The target value will be reached in exactly this many milliseconds.
    Linear(f32),
    /// Smooth parameter changes such that the rate matches the curve of a logarithmic function,
    /// starting out slow and then constantly increasing the slope until the value is reached. The
    /// target value will be reached in exactly this many milliseconds. This is useful for smoothing
    /// things like frequencies and decibel gain value. **The caveat is that the value may never
    /// reach 0**, or you will end up multiplying and dividing things by zero. Make sure your value
    /// ranges don't include 0.
    Logarithmic(f32),
    /// Smooth parameter changes such that the rate matches the curve of an exponential function,
    /// starting out fast and then tapering off until the end. This is a single-pole IIR filter
    /// under the hood, while the other smoothing options are FIR filters. This means that the exact
    /// value would never be reached. Instead, this reaches 99.99% of the value target value in the
    /// specified number of milliseconds, and it then snaps to the target value in the last step.
    /// This results in a smoother transition, with the caveat being that there will be a tiny jump
    /// at the end. Unlike the `Logarithmic` option, this does support crossing the zero value.
    Exponential(f32),
}

/// A smoother, providing a smoothed value for each sample.
//
// TODO: We need to use atomics here so we can share the params object with the GUI. Is there a
//       better alternative to allow the process function to mutate these smoothers?
#[derive(Debug)]
pub struct Smoother<T> {
    /// The kind of snoothing that needs to be applied, if any.
    pub style: SmoothingStyle,
    /// The number of steps of smoothing left to take.
    ///
    // This is a signed integer because we can skip multiple steps, which would otherwise make it
    // possible to get an underflow here.
    steps_left: AtomicI32,
    /// The amount we should adjust the current value each sample to be able to reach the target in
    /// the specified tiem frame. This is also a floating point number to keep the smoothing
    /// uniform.
    ///
    /// In the case of the `Exponential` smoothing style this is the coefficient `x` that the
    /// previous sample is multplied by.
    step_size: f32,
    /// The value for the current sample. Always stored as floating point for obvious reasons.
    current: AtomicF32,
    /// The value we're smoothing towards
    target: T,
}

/// An iterator that continuously produces smoothed values. Can be used as an alternative to the
/// block-based smoothing API. Since the iterator itself is infinite, you can use
/// [`Smoother::is_smoothing()`] and [`Smoother::steps_left()`] to get information on the current
/// smoothing status.
pub struct SmootherIter<'a, T> {
    smoother: &'a Smoother<T>,
}

/// A type that can be smoothed. This exists just to avoid duplicate explicit implementations for
/// the smoothers.
pub trait Smoothable: Default + Copy {
    fn to_f32(self) -> f32;
    fn from_f32(value: f32) -> Self;
}

impl<T: Smoothable> Default for Smoother<T> {
    fn default() -> Self {
        Self {
            style: SmoothingStyle::None,
            steps_left: AtomicI32::new(0),
            step_size: Default::default(),
            current: AtomicF32::new(0.0),
            target: Default::default(),
        }
    }
}

impl<T: Smoothable> Iterator for SmootherIter<'_, T> {
    type Item = T;

    #[inline]
    fn next(&mut self) -> Option<Self::Item> {
        Some(self.smoother.next())
    }
}

impl<T: Clone> Clone for Smoother<T> {
    fn clone(&self) -> Self {
        // We can't derive clone because of the atomics, but these atomics are only here to allow
        // Send+Sync interior mutability
        Self {
            style: self.style,
            steps_left: AtomicI32::new(self.steps_left.load(Ordering::Relaxed)),
            step_size: self.step_size,
            current: AtomicF32::new(self.current.load(Ordering::Relaxed)),
            target: self.target.clone(),
        }
    }
}

impl<T: Smoothable> Smoother<T> {
    /// Use the specified style for the smoothing.
    pub fn new(style: SmoothingStyle) -> Self {
        Self {
            style,
            ..Default::default()
        }
    }

    /// Convenience function for not applying any smoothing at all. Same as `Smoother::default`.
    pub fn none() -> Self {
        Default::default()
    }

    /// The number of steps left until calling [`next()`][Self::next()] will stop yielding new
    /// values.
    #[inline]
    pub fn steps_left(&self) -> i32 {
        self.steps_left.load(Ordering::Relaxed)
    }

    /// Whether calling [`next()`][Self::next()] will yield a new value or an old value. Useful if
    /// you need to recompute something wheenver this parameter changes.
    #[inline]
    pub fn is_smoothing(&self) -> bool {
        self.steps_left() > 0
    }

    /// Produce an iterator that yields smoothed values. These are not iterators already for the
    /// sole reason that this will always yield a value, and needing to unwrap all of those options
    /// is not going to be very fun.
    #[inline]
    pub fn iter(&self) -> SmootherIter<T> {
        SmootherIter { smoother: self }
    }

    /// Reset the smoother the specified value.
    pub fn reset(&mut self, value: T) {
        self.target = value;
        self.current.store(value.to_f32(), Ordering::Relaxed);
        self.steps_left.store(0, Ordering::Relaxed);
    }

    /// Set the target value.
    pub fn set_target(&mut self, sample_rate: f32, target: T) {
        self.target = target;

        let steps_left = match self.style {
            SmoothingStyle::None => 1,
            SmoothingStyle::Linear(time)
            | SmoothingStyle::Logarithmic(time)
            | SmoothingStyle::Exponential(time) => (sample_rate * time / 1000.0).round() as i32,
        };
        self.steps_left.store(steps_left, Ordering::Relaxed);

        let current = self.current.load(Ordering::Relaxed);
        self.step_size = match self.style {
            SmoothingStyle::None => 0.0,
            SmoothingStyle::Linear(_) => (self.target.to_f32() - current) / steps_left as f32,
            SmoothingStyle::Logarithmic(_) => {
                // We need to solve `current * (step_size ^ steps_left) = target` for
                // `step_size`
                nih_debug_assert_ne!(current, 0.0);
                ((self.target.to_f32() / current) as f64).powf((steps_left as f64).recip()) as f32
            }
            // In this case the step size value is the coefficient the current value will be
            // multiplied by, while the target value is multipled by one minus the coefficient. This
            // reaches 99.99% of the target value after `steps_left`. The smoother will snap to the
            // target value after that point.
            SmoothingStyle::Exponential(_) => 0.0001f64.powf(1.0 / steps_left as f64) as f32,
        };
    }

    /// Get the next value from this smoother. The value will be equal to the previous value once
    /// the smoothing period is over. This should be called exactly once per sample.
    // Yes, Clippy, like I said, this was intentional
    #[allow(clippy::should_implement_trait)]
    #[inline]
    pub fn next(&self) -> T {
        self.next_step(1)
    }

    /// [`next()`][Self::next()], but with the ability to skip forward in the smoother.
    /// [`next()`][Self::next()] is equivalent to calling this function with a `steps` value of 1.
    /// Calling this function with a `steps` value of `n` means will cause you to skip the next `n -
    /// 1` values and return the `n`th value.
    #[inline]
    pub fn next_step(&self, steps: u32) -> T {
        nih_debug_assert_ne!(steps, 0);

        if self.steps_left.load(Ordering::Relaxed) > 0 {
            let current = self.current.load(Ordering::Relaxed);
            let target = self.target.to_f32();

            // The number of steps usually won't fit exactly, so make sure we don't end up with
            // quantization errors on overshoots or undershoots. We also need to account for the
            // possibility that we only have `n < steps` steps left. This is especially important
            // for the `Exponential` smoothing style, since that won't reach the target value
            // exactly.
            let old_steps_left = self.steps_left.fetch_sub(steps as i32, Ordering::Relaxed);
            let new = if old_steps_left <= steps as i32 {
                self.steps_left.store(0, Ordering::Relaxed);
                target
            } else {
                match &self.style {
                    SmoothingStyle::None => target,
                    SmoothingStyle::Linear(_) => current + (self.step_size * steps as f32),
                    SmoothingStyle::Logarithmic(_) => current * (self.step_size.powi(steps as i32)),
                    SmoothingStyle::Exponential(_) => {
                        // This is the same as calculating `current = (current * step_size) +
                        // (target * (1 - step_size))` in a loop since the target value won't change
                        let coefficient = self.step_size.powi(steps as i32);
                        (current * coefficient) + (target * (1.0 - coefficient))
                    }
                }
            };
            self.current.store(new, Ordering::Relaxed);

            T::from_f32(new)
        } else {
            self.target
        }
    }

    /// Get previous value returned by this smoother. This may be useful to save some boilerplate
    /// when [`is_smoothing()`][Self::is_smoothing()] is used to determine whether an expensive
    /// calculation should take place, and [`next()`][Self::next()] gets called as part of that
    /// calculation.
    pub fn previous_value(&self) -> T {
        T::from_f32(self.current.load(Ordering::Relaxed))
    }

    /// Produce smoothed values for an entire block of audio. This is useful when iterating the same
    /// block of audio multiple times. For instance when summing voices for a synthesizer.
    /// `block_values[..block_len]` will be filled with the smoothed values. This is simply a
    /// convenient function for [`next_block_exact()`][Self::next_block_exact()] when iterating over
    /// variable length blocks with a known maximum size.
    ///
    /// # Panics
    ///
    /// Panics if `block_len > block_values.len()`.
    pub fn next_block(&self, block_values: &mut [T], block_len: usize) {
        self.next_block_exact_mapped(&mut block_values[..block_len], |x| x)
    }

    /// The same as [`next_block()`][Self::next_block()], but filling the entire slice.
    pub fn next_block_exact(&self, block_values: &mut [T]) {
        self.next_block_exact_mapped(block_values, |x| x)
    }

    /// The same as [`next_block()`][Self::next_block()], but with a function applied to each
    /// produced value. Useful when applying modulation to a smoothed parameter.
    pub fn next_block_mapped(&self, block_values: &mut [T], block_len: usize, f: impl Fn(T) -> T) {
        self.next_block_exact_mapped(&mut block_values[..block_len], f)
    }

    /// The same as [`next_block_exact()`][Self::next_block()], but with a function applied to each
    /// produced value. Useful when applying modulation to a smoothed parameter.
    pub fn next_block_exact_mapped(&self, block_values: &mut [T], f: impl Fn(T) -> T) {
        // `self.next()` will yield the current value if the parameter is no longer smoothing, but
        // it's a bit of a waste to continuesly call that if only the first couple or none of the
        // values in `block_values` would require smoothing and the rest don't. Instead, we'll just
        // smooth the values as necessary, and then reuse the target value for the rest of the
        // block.
        let num_smoothed_values = block_values
            .len()
            .min(self.steps_left.load(Ordering::Relaxed) as usize);

        block_values[..num_smoothed_values].fill_with(|| f(self.next()));
        block_values[num_smoothed_values..].fill(self.target);
    }
}

impl Smoothable for f32 {
    #[inline]
    fn to_f32(self) -> f32 {
        self
    }

    #[inline]
    fn from_f32(value: f32) -> Self {
        value
    }
}

impl Smoothable for i32 {
    #[inline]
    fn to_f32(self) -> f32 {
        self as f32
    }

    #[inline]
    fn from_f32(value: f32) -> Self {
        value.round() as i32
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn linear_f32_smoothing() {
        let mut smoother: Smoother<f32> = Smoother::new(SmoothingStyle::Linear(100.0));
        smoother.reset(10.0);
        assert_eq!(smoother.next(), 10.0);

        // Instead of testing the actual values, we'll make sure that we reach the target values at
        // the expected time.
        smoother.set_target(100.0, 20.0);
        for _ in 0..(10 - 2) {
            smoother.next();
        }
        assert_ne!(smoother.next(), 20.0);
        assert_eq!(smoother.next(), 20.0);
    }

    #[test]
    fn linear_i32_smoothing() {
        let mut smoother: Smoother<i32> = Smoother::new(SmoothingStyle::Linear(100.0));
        smoother.reset(10);
        assert_eq!(smoother.next(), 10);

        // Integers are rounded, but with these values we can still test this
        smoother.set_target(100.0, 20);
        for _ in 0..(10 - 2) {
            smoother.next();
        }
        assert_ne!(smoother.next(), 20);
        assert_eq!(smoother.next(), 20);
    }

    #[test]
    fn logarithmic_f32_smoothing() {
        let mut smoother: Smoother<f32> = Smoother::new(SmoothingStyle::Logarithmic(100.0));
        smoother.reset(10.0);
        assert_eq!(smoother.next(), 10.0);

        // Instead of testing the actual values, we'll make sure that we reach the target values at
        // the expected time.
        smoother.set_target(100.0, 20.0);
        for _ in 0..(10 - 2) {
            smoother.next();
        }
        assert_ne!(smoother.next(), 20.0);
        assert_eq!(smoother.next(), 20.0);
    }

    #[test]
    fn logarithmic_i32_smoothing() {
        let mut smoother: Smoother<i32> = Smoother::new(SmoothingStyle::Logarithmic(100.0));
        smoother.reset(10);
        assert_eq!(smoother.next(), 10);

        // Integers are rounded, but with these values we can still test this
        smoother.set_target(100.0, 20);
        for _ in 0..(10 - 2) {
            smoother.next();
        }
        assert_ne!(smoother.next(), 20);
        assert_eq!(smoother.next(), 20);
    }

    /// Same as [linear_f32_smoothing], but skipping steps instead.
    #[test]
    fn skipping_linear_f32_smoothing() {
        let mut smoother: Smoother<f32> = Smoother::new(SmoothingStyle::Linear(100.0));
        smoother.reset(10.0);
        assert_eq!(smoother.next(), 10.0);

        smoother.set_target(100.0, 20.0);
        smoother.next_step(8);
        assert_ne!(smoother.next(), 20.0);
        assert_eq!(smoother.next(), 20.0);
    }

    /// Same as [linear_i32_smoothing], but skipping steps instead.
    #[test]
    fn skipping_linear_i32_smoothing() {
        let mut smoother: Smoother<i32> = Smoother::new(SmoothingStyle::Linear(100.0));
        smoother.reset(10);
        assert_eq!(smoother.next(), 10);

        smoother.set_target(100.0, 20);
        smoother.next_step(8);
        assert_ne!(smoother.next(), 20);
        assert_eq!(smoother.next(), 20);
    }

    /// Same as [logarithmic_f32_smoothing], but skipping steps instead.
    #[test]
    fn skipping_logarithmic_f32_smoothing() {
        let mut smoother: Smoother<f32> = Smoother::new(SmoothingStyle::Logarithmic(100.0));
        smoother.reset(10.0);
        assert_eq!(smoother.next(), 10.0);

        smoother.set_target(100.0, 20.0);
        smoother.next_step(8);
        assert_ne!(smoother.next(), 20.0);
        assert_eq!(smoother.next(), 20.0);
    }

    /// Same as [logarithmic_i32_smoothing], but skipping steps instead.
    #[test]
    fn skipping_logarithmic_i32_smoothing() {
        let mut smoother: Smoother<i32> = Smoother::new(SmoothingStyle::Logarithmic(100.0));
        smoother.reset(10);
        assert_eq!(smoother.next(), 10);

        smoother.set_target(100.0, 20);
        smoother.next_step(8);
        assert_ne!(smoother.next(), 20);
        assert_eq!(smoother.next(), 20);
    }

    // TODO: Tests for the exponential smoothing
}