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use crate::core::{Error, PeriodType, ValueType, Window};
use crate::core::{Method, MovingAverage};
use crate::helpers::Peekable;

#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};

/// [Weighted Moving Average](https://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average) of specified `length` for timeseries of type [`ValueType`].
///
/// # Parameters
///
/// Has a single parameter `length`: [`PeriodType`]
///
/// `length` should be > `0`
///
/// # Input type
///
/// Input type is [`ValueType`]
///
/// # Output type
///
/// Output type is [`ValueType`]
///
/// # Examples
///
/// ```
/// use yata::prelude::*;
/// use yata::methods::WMA;
///
/// // WMA of length=3
/// let mut wma = WMA::new(3, &3.0).unwrap();
///
/// wma.next(&3.0);
/// wma.next(&6.0);
///
/// assert_eq!(wma.next(&9.0), 7.0);
/// assert_eq!(wma.next(&12.0), 10.0);
/// ```
///
/// # Performance
///
/// O(1)
///
/// # See also
///
/// [Volume Weighted Moving Average](crate::methods::VWMA) for computing weighted moving average with custom weights over every value
///
/// [`ValueType`]: crate::core::ValueType
/// [`PeriodType`]: crate::core::PeriodType
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct WMA {
	invert_sum: ValueType,
	float_length: ValueType,
	total: ValueType,
	numerator: ValueType,
	window: Window<ValueType>,
}

impl Method for WMA {
	type Params = PeriodType;
	type Input = ValueType;
	type Output = Self::Input;

	fn new(length: Self::Params, &value: &Self::Input) -> Result<Self, Error> {
		match length {
			0 => Err(Error::WrongMethodParameters),
			length => {
				let length2 = length as usize;
				let sum = ((length2 * (length2 + 1)) / 2) as ValueType;
				let float_length = length as ValueType;
				Ok(Self {
					invert_sum: sum.recip(),
					float_length,
					total: -value * float_length,
					numerator: value * sum,
					window: Window::new(length, value),
				})
			}
		}
	}

	#[inline]
	fn next(&mut self, &value: &Self::Input) -> Self::Output {
		let prev_value = self.window.push(value);

		self.numerator += self.float_length.mul_add(value, self.total);
		self.total += prev_value - value;

		self.numerator * self.invert_sum
	}
}

impl MovingAverage for WMA {}

impl Peekable<<Self as Method>::Output> for WMA {
	fn peek(&self) -> <Self as Method>::Output {
		self.numerator * self.invert_sum
	}
}

#[cfg(test)]
#[allow(clippy::suboptimal_flops)]
mod tests {
	use super::{Method, WMA as TestingMethod};
	use crate::core::ValueType;
	use crate::helpers::{assert_eq_float, RandomCandles};
	use crate::methods::tests::test_const;
	use crate::methods::Conv;

	#[test]
	fn test_wma_const() {
		for i in 1..255 {
			let input = (i as ValueType + 56.0) / 16.3251;
			let mut method = TestingMethod::new(i, &input).unwrap();

			let output = method.next(&input);
			test_const(&mut method, &input, &output);
		}
	}

	#[test]
	fn test_wma1() {
		let mut candles = RandomCandles::default();

		let mut ma = TestingMethod::new(1, &candles.first().close).unwrap();

		candles.take(100).for_each(|x| {
			assert_eq_float(x.close, ma.next(&x.close));
		});
	}

	#[test]
	fn test_wma() {
		let candles = RandomCandles::default();

		let src: Vec<ValueType> = candles.take(300).map(|x| x.close).collect();

		(1..255).for_each(|ma_length| {
			let mut ma = TestingMethod::new(ma_length, &src[0]).unwrap();
			let mut conv =
				Conv::new((1..=ma_length).map(|x| x as ValueType).collect(), &src[0]).unwrap();
			let ma_length = ma_length as usize;

			let div = (1..=ma_length).sum::<usize>() as ValueType;
			src.iter().enumerate().for_each(|(i, x)| {
				let value = ma.next(x);
				let value2 = (0..ma_length).fold(0.0, |s, v| {
					let j = i.saturating_sub(v);
					s + src[j] * (ma_length - v) as ValueType
				}) / div;
				let value3 = conv.next(x);

				assert_eq_float(value2, value);
				assert_eq_float(value3, value);
			});
		});
	}
}