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//use crate::common::validate_inputs;
use crate::indicators::md::{min_data, output_length, IndicatorState, INPUTS_WIDTH, OPTIONS_WIDTH};
use crate::indicators::simd_indicators::road_train::{Asset, Driver, PrimeMover};
use crate::indicators::simd_indicators::{md_simd::assets::calc_simd, sma_simd::init_state};
use crate::types::IndicatorError;
use crate::{common::validate_options, common_simd::assets::validate_inputs};
use std::simd::Simd;
/// SIMD driver that advances the Mean Deviation (MD) across `N` asset lanes per scheduling
/// epoch.
struct MdDriver {
multiplier: f64,
period: usize,
want_optional_outputs: bool,
}
impl Driver<f64> for MdDriver {
/// Processes one epoch of bars for `N` assets simultaneously using SIMD.
///
/// Reads from `inputs[asset][0]` (real), writes the MD to `outputs[asset][0]`,
/// optional SMA to `outputs[asset][1]`, and updates `states[asset]` in place.
fn next_run<const N: usize>(
&mut self,
inputs: Vec<Vec<&[f64]>>,
mut outputs: Vec<Vec<&mut [f64]>>,
mut states: Vec<&mut f64>,
_options: Vec<Option<&()>>,
) {
let len = inputs[0][0].len();
// Optimization 1: Direct array construction instead of collect+try_into
let mut sums = Simd::<f64, N>::from_array(std::array::from_fn(|i| unsafe {
**states.get_unchecked(i)
}));
let multiplier_simd = Simd::splat(self.multiplier);
// Optimization 2: Pre-compute all input and output pointers
let input_ptrs: [*const f64; N] =
std::array::from_fn(|j| unsafe { inputs.get_unchecked(j).get_unchecked(0).as_ptr() });
let real_simd: Vec<Simd<f64, N>> = crate::create_simd_vec_from_inputs!(input_ptrs, N, len);
let (md_line_ptr, sma_line_ptr) =
crate::extract_output_ptrs!(outputs, N, md_line_ptr, sma_line_ptr);
// Optimization 3: Simplified main loop with pre-computed offsets
for (j, i) in (self.period..len).enumerate() {
// Get new and old values using pre-computed pointers
let (value, prev_value, slice) = unsafe {
(
*real_simd.get_unchecked(i),
*real_simd.get_unchecked(j),
real_simd.get_unchecked(j+1/*i + 1 - self.period*/..=i),
)
};
let (md, sma) = calc_simd(value, prev_value, slice, &mut sums, multiplier_simd);
// Store results using pre-computed pointers
let results = md.to_array();
for k in 0..N {
unsafe {
*md_line_ptr[k].add(j) = results[k];
}
}
crate::store_simd_optional_outputs!(j, N,
self.want_optional_outputs, sma_line_ptr => sma
);
}
let final_sums = sums.to_array();
for (i, state) in states.iter_mut().enumerate().take(N) {
**state = final_sums[i];
}
}
}
/// Calculates the Mean Deviation (MD) for `N` assets simultaneously using SIMD parallelism.
///
/// 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` - Shared options slice; `options[0]` is the period.
/// * `optional_outputs` - Optional slice selecting extra outputs: index `0` = `sma`.
///
/// # Returns
/// `Ok((outputs, states))` where `outputs[i][0]` is the MD for asset `i`,
/// `outputs[i][1]` is the optional SMA, 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 (sums, multiplier) = init_state(&real, period);
let mut road_train = PrimeMover::<N, f64>::new();
let mut output_buffers = Vec::with_capacity(N);
let mut want_optional_outputs = false;
for (i, sum) in sums.into_iter().enumerate() {
let asset_inputs = vec![inputs[i][0]];
let (md_line, sma_line) = {
let capacity = output_length(inputs[i][0].len(), options);
(
crate::uninit_vec!(f64, capacity),
crate::init_optional_outputs_eff!(
optional_outputs, &[false],
sma_line: capacity
),
)
};
if i == 0 {
(_, want_optional_outputs) = crate::calc_want_flags!(sma_line);
}
let mut output_buffer = vec![md_line, sma_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,
period,
sum,
None,
));
output_buffers.push(output_buffer);
}
let mut driver = MdDriver {
multiplier,
period,
want_optional_outputs,
};
let sums = road_train.drive(&mut driver);
let mut states = Vec::with_capacity(N);
for (i, sum) in sums.into_iter().enumerate() {
states.push(IndicatorState::new(
unsafe { inputs.get_unchecked(i).get_unchecked(0) },
sum,
multiplier,
period,
));
}
Ok((output_buffers, states))
}