1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
use crate::core::{Error, PeriodType, ValueType};
use crate::core::{Method, MovingAverage};
use crate::helpers::Peekable;
use crate::methods::EMA;

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

/// [Wilder’s Smoothing Average](http://etfhq.com/blog/2010/08/19/wilders-smoothing/) of specified `length` for timeseries of type [`ValueType`]
///
/// It is actually a simple EMA over `length*2-1` periods
///
/// # Parameters
///
/// Has a single parameter `length`: [`PeriodType`]
///
/// `length` should be > `0` and < `PeriodType::MAX`/`2`
///
/// # Input type
///
/// Input type is [`ValueType`]
///
/// # Output type
///
/// Output type is [`ValueType`]
///
/// # Examples
///
/// ```
/// use yata::prelude::*;
/// use yata::methods::WSMA;
///
/// // WSMA of length=3
/// let mut wsma = WSMA::new(4, &2.0).unwrap();
///
/// wsma.next(&3.0);
/// wsma.next(&6.0);
///
/// assert_eq!(wsma.next(&9.0), 4.640625);
/// assert_eq!(wsma.next(&12.0), 6.48046875);
/// ```
/// # Performance
///
/// O(1)
///
/// [`ValueType`]: crate::core::ValueType
/// [`PeriodType`]: crate::core::PeriodType
#[derive(Debug, Clone, Copy)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct WSMA(EMA);

const MAX_PERIOD: PeriodType = PeriodType::MAX / 2;

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

	fn new(length: Self::Params, value: &Self::Input) -> Result<Self, Error> {
		if length > MAX_PERIOD {
			return Err(Error::WrongMethodParameters);
		}

		Ok(Self(EMA::new(length * 2 - 1, value)?))
	}

	#[inline]
	fn next(&mut self, value: &Self::Input) -> Self::Output {
		self.0.next(value)
	}
}

impl MovingAverage for WSMA {}

impl Peekable<<Self as Method>::Output> for WSMA {
	fn peek(&self) -> <Self as Method>::Output {
		self.0.peek()
	}
}

#[cfg(test)]
mod tests {
	use crate::core::Method;
	use crate::core::ValueType;
	use crate::helpers::{assert_eq_float, RandomCandles};
	use crate::methods::tests::test_const_float;

	use super::WSMA as TestingMethod;

	#[test]
	fn test_wsma_const() {
		for i in 1..=(255 / 2) {
			let input = (i as ValueType + 56.0) / 16.3251;
			let mut method = TestingMethod::new(i, &input).unwrap();

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

	#[test]
	fn test_wsma1() {
		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_wsma() {
		let candles = RandomCandles::default();
		let src: Vec<ValueType> = candles.take(300).map(|x| x.close).collect();

		(1..=(255 / 2)).for_each(|length| {
			let mut ma = TestingMethod::new(length, &src[0]).unwrap();

			let mut prev_value = src[0];

			for &x in &src {
				let value = ma.next(&x);

				let value2 = prev_value + (x - prev_value) / length as ValueType;

				prev_value = value2;

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