Pratik Bhadane
71 lines
2.2 KiB
Rust
71 lines
2.2 KiB
Rust
/// Rolling linear regression: returns (slope, intercept) for the given window.
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pub(super) fn linreg(window: &[f64]) -> (f64, f64) {
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let n = window.len() as f64;
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let sum_x: f64 = (0..window.len()).map(|i| i as f64).sum();
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let sum_y: f64 = window.iter().sum();
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let sum_xy: f64 = window.iter().enumerate().map(|(i, &y)| i as f64 * y).sum();
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let sum_x2: f64 = (0..window.len()).map(|i| (i as f64).powi(2)).sum();
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let denom = n * sum_x2 - sum_x * sum_x;
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let slope = if denom != 0.0 {
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(n * sum_xy - sum_x * sum_y) / denom
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} else {
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0.0
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};
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let intercept = (sum_y - slope * sum_x) / n;
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(slope, intercept)
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}
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pub(crate) fn rolling_linreg_apply<F>(prices: &[f64], timeperiod: usize, mut map: F) -> Vec<f64>
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where
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F: FnMut(f64, f64) -> f64,
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{
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let n = prices.len();
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let mut result = vec![f64::NAN; n];
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if timeperiod == 0 || n < timeperiod {
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return result;
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}
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if prices.iter().any(|value| !value.is_finite()) {
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for end in (timeperiod - 1)..n {
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let window = &prices[(end + 1 - timeperiod)..=end];
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let (slope, intercept) = linreg(window);
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result[end] = map(slope, intercept);
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}
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return result;
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}
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let period = timeperiod as f64;
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let last_x = (timeperiod - 1) as f64;
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let sum_x = last_x * period / 2.0;
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let sum_x2 = last_x * period * (2.0 * period - 1.0) / 6.0;
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let denom = period * sum_x2 - sum_x * sum_x;
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let mut sum_y = prices[..timeperiod].iter().sum::<f64>();
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let mut sum_xy = prices[..timeperiod]
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.iter()
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.enumerate()
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.map(|(idx, &value)| idx as f64 * value)
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.sum::<f64>();
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for end in (timeperiod - 1)..n {
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let slope = if denom != 0.0 {
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(period * sum_xy - sum_x * sum_y) / denom
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} else {
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0.0
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};
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let intercept = (sum_y - slope * sum_x) / period;
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result[end] = map(slope, intercept);
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if end + 1 < n {
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let outgoing = prices[end + 1 - timeperiod];
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let incoming = prices[end + 1];
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let prev_sum_y = sum_y;
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sum_y = prev_sum_y - outgoing + incoming;
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sum_xy = sum_xy - (prev_sum_y - outgoing) + last_x * incoming;
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}
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}
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result
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}
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