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//use crate::common::validate_inputs;
use crate::indicators::rsi::{
min_data, multiplier, output_length, IndicatorState, State, INPUTS_WIDTH, OPTIONS_WIDTH,
};
use crate::indicators::simd_indicators::road_train::{Asset, Driver, PrimeMover};
use crate::indicators::simd_indicators::rsi_simd::SimdState;
use crate::types::IndicatorError;
use crate::{common::validate_options, common_simd::assets::validate_inputs};
use std::simd::Simd;
/// SIMD driver that advances the Relative Strength Index (RSI) across `N` asset lanes per scheduling epoch.
struct RsiDriver {
multipliers: (f64, f64),
}
impl Driver<State> for RsiDriver {
/// Processes one epoch of bars for `N` assets simultaneously using SIMD.
fn next_run<const N: usize>(
&mut self,
inputs: Vec<Vec<&[f64]>>,
mut outputs: Vec<Vec<&mut [f64]>>,
mut states: Vec<&mut State>,
_options: Vec<Option<&()>>,
) {
let len = inputs[0][0].len();
//let output_len = len - self.period;
// Optimization 1: Direct array construction instead of collect+try_into
let mut state = SimdState::new(&states);
let multipliers_simd = (
Simd::splat(self.multipliers.0),
Simd::splat(self.multipliers.1),
);
// Optimization 2: Pre-compute all input and output pointers
let real_ptrs = crate::extract_input_ptrs!(inputs, N, real_ptrs);
let rsi_line_ptr = crate::extract_output_ptrs!(outputs, N, rsi_line_ptr);
// Optimization 3: Simplified main loop with pre-computed offsets
for i in 0..len {
// Get new and old values using pre-computed pointers
let current = crate::extract_simd_inputs_at_index!(i, N,
current @ real_ptrs
);
let rsi = state.calc_simd(current, multipliers_simd);
// Store results using pre-computed pointers
crate::write_simd_at_indices!(N, i,
rsi_line_ptr => rsi
);
}
state.write_states(&mut states);
}
}
/// Calculates the Relative Strength Index (RSI) for `N` assets simultaneously using SIMD
/// parallelism.
///
/// RSI is a momentum oscillator that measures the speed and magnitude of price changes
/// on a scale from 0 to 100. Uses the [`PrimeMover`] scheduler to batch assets into
/// SIMD-width groups.
///
/// # Arguments
/// * `inputs` - An array of `N` asset input sets; `inputs[i]` is `[&[f64]; INPUTS_WIDTH]`
/// containing `[real]` for asset `i`.
/// * `options` - `[period]` — the smoothing period for the RSI calculation.
/// * `_optional_outputs` - Unused; RSI produces no optional outputs.
///
/// # Returns
/// `Ok((outputs, states))` where `outputs[i][0]` is the RSI line for asset `i`
/// and `states[i]` is the final [`IndicatorState`] for asset `i`.
/// Returns `Err(IndicatorError)` if any input slice is too short or options are invalid.
pub fn indicator_by_assets<const N: usize>(
inputs: &[&[&[f64]; INPUTS_WIDTH]; N], //stock[ fields [ field [f64] ] ]
options: &[f64; OPTIONS_WIDTH],
_optional_outputs: Option<&[bool]>,
) -> Result<(Vec<Vec<Vec<f64>>>, Vec<IndicatorState>), IndicatorError> {
validate_inputs::<INPUTS_WIDTH>(inputs, min_data(options))?;
validate_options(options)?;
let period = options[0] as usize;
//let real: Vec<&[f64]> = (0..N).map(|i| inputs[i][0]).collect();
let real: [&[f64]; N] = std::array::from_fn(|i| inputs[i][0]);
//init ema, sliced inputs and multipliers
let simd_state = SimdState::init_state(&real, period);
let states = simd_state.to_states();
let multipliers = multiplier(period);
let mut road_train = PrimeMover::<N, State>::new();
let mut output_buffers = Vec::with_capacity(N);
for (i, state) in states.into_iter().enumerate() {
let asset_inputs = vec![inputs[i][0]];
let rsi_line = {
let capacity = output_length(inputs[i][0].len(), options);
crate::uninit_vec!(f64, capacity)
};
let mut output_buffer = vec![rsi_line];
//let adosc_len = output_buffer[0].len();
let mut asset_outputs = Vec::with_capacity(output_buffer.len());
for j in 0..output_buffer.len() {
unsafe {
//let slice_len = output_buffer.len() - starts[j];
// Get a mutable reference to the output buffer for this asset
let output_buffer = &mut output_buffer[j];
asset_outputs.push(std::slice::from_raw_parts_mut(
output_buffer.as_mut_ptr(), //slice from
output_buffer.len(), // slice to
));
}
}
road_train.add_asset(Asset::new(
asset_inputs,
asset_outputs,
i,
period + 1,
0,
state,
None,
));
output_buffers.push(output_buffer);
}
let mut driver = RsiDriver { multipliers };
let states_vec = road_train.drive(&mut driver);
let mut states = Vec::with_capacity(N);
for state in states_vec.into_iter() {
states.push(IndicatorState::new(state, multipliers));
}
Ok((output_buffers, states))
}