tulip_rs 0.1.15

//use crate::common::validate_inputs;
use crate::common_simd::options::{validate_inputs, validate_options};
use crate::indicators::rocr::{
    min_data, output_length, IndicatorState, INPUTS_WIDTH, OPTIONS_WIDTH,
};
use crate::indicators::simd_indicators::road_train::{Asset, Driver, PrimeMover};
use crate::types::IndicatorError;
use std::simd::Simd;
//use crate::indicators::ad::output_length;
use crate::indicators::simd_indicators::rocr_simd::calc_simd;

/// SIMD driver for the Rate of Change Ratio (ROCR) indicator, processing `N` option-set lanes per scheduling epoch.
struct RocrDriver {}

impl Driver<bool, usize> for RocrDriver {
    /// Processes one epoch of output bars for `N` option-set lanes 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 bool>,
        options: Vec<Option<&usize>>,
    ) {
        let len = outputs[0][0].len();
        let mut i_simd = {
            let mut i = [0usize; N];
            for (lane, option) in options.iter().enumerate() {
                if let Some(&period) = option {
                    i[lane] = period;
                }
            }
            Simd::from_array(i)
        };
        // Optimization 2: Pre-compute all input and output pointers
        let output_ptrs = crate::extract_output_ptrs!(outputs, N, output_ptr);

        // Optimization 2: Pre-compute all input and output pointers
        let input_ptrs = crate::extract_input_ptrs!(inputs, N, real_ptrs);
        let one_splat = Simd::splat(1);

        // Optimization 3: Simplified main loop with pre-computed offsets
        for j in 0..len {
            let new_vals = crate::extract_simd_inputs_at_index_array!(i_simd, N,
                new @ input_ptrs
            );
            /*let new_vals = crate::extract_simd_inputs_at_index_splat!(i, N,
                new @ input_ptrs
            );*/
            let old_vals = crate::extract_simd_inputs_at_index!(j, N,
                new @ input_ptrs
            );
            /*let (old_vals, new_vals) = crate::extract_simd_at_indices!(N, input_ptrs,
                old_vals @ j,
                new_vals @ i
            );*/

            let rocr = calc_simd(new_vals, old_vals);

            // Store results using pre-computed pointers
            crate::write_simd_at_indices!(N, j,
                output_ptrs => rocr
            );
            i_simd += one_splat;
        }
    }
}

/// Calculates the Rate of Change Ratio (ROCR) indicator for one asset with `N` different
/// option sets simultaneously using SIMD parallelism.
///
/// Applies each of the `N` period configurations to the same shared input series, computing
/// ROCR values for all option sets in a single SIMD-accelerated pass via [`PrimeMover`].
///
/// # Arguments
/// * `inputs` - Shared input: `inputs[0]` is the `real` price series.
/// * `options` - An array of `N` option sets; `options[i][0]` is the `period` for lane `i`.
/// * `_optional_outputs` - Unused; ROCR has no optional outputs.
///
/// # Returns
/// `Ok((outputs, states))` where `outputs[i][0]` is the `rocr` series for option set `i`
/// and `states[i]` is the final [`IndicatorState`] for option set `i`.
/// Returns `Err(IndicatorError)` if any input slice is too short or options are invalid.
pub fn indicator_by_options<const N: usize>(
    inputs: &[&[f64]; INPUTS_WIDTH],
    options: &[&[f64; OPTIONS_WIDTH]; N],
    _optional_outputs: Option<&[bool]>,
) -> Result<(Vec<Vec<Vec<f64>>>, Vec<IndicatorState>), IndicatorError> {
    validate_inputs::<OPTIONS_WIDTH>(inputs, options, min_data)?;
    validate_options(options, None)?;

    let periods: [usize; N] = std::array::from_fn(|i| options[i][0] as usize);

    let mut road_train = PrimeMover::<N, bool, usize>::new();
    let mut output_buffers: Vec<Vec<Vec<f64>>> = (0..N)
        .map(|i| {
            vec![{
                let capacity = output_length(inputs[0].len(), options[i]);
                crate::uninit_vec!(f64, capacity)
            }]
        })
        .collect();

    for i in 0..N {
        let asset_inputs = vec![inputs[0]];
        unsafe {
            // Get a mutable reference to the output buffer for this asset
            let output_buffer = &mut output_buffers[i][0];
            let asset_outputs = vec![std::slice::from_raw_parts_mut(
                output_buffer.as_mut_ptr(),
                output_buffer.len(),
            )];

            road_train.add_asset(Asset::new(
                asset_inputs,
                asset_outputs,
                i,
                periods[i],
                periods[i],
                false,
                Some(&periods[i]),
            ));
        }
    }
    let mut driver = RocrDriver {};
    road_train.drive(&mut driver);

    let mut states = Vec::with_capacity(N);
    for i in 0..N {
        states.push(IndicatorState::new(inputs[0], periods[i]));
    }
    Ok((output_buffers, states))
}

/*pub fn indicator_by_assets_from_state<const N: usize>(
    inputs: &[ &[ &[f64]; INPUTS_WIDTH]; N],
    states: &mut [IndicatorState; N],
    _optional_outputs: Option<&[bool]>,
) -> Result<[Vec<Vec<f64>>; N], IndicatorError>
{
    let len = inputs[0][0].len();

    // Validate all inputs have same length
    for i in 0..N {
        if inputs[i][0].len() != len {
            return Err(IndicatorError::InvalidInputs);
        }
    }

    // Extract EMAs and multipliers from states
    let mut emas = Simd::from_array(std::array::from_fn(|i| states[i].get_ema()));
    let multipliers = states[0].get_multipliers();
    let multipliers_simd = (Simd::splat(multipliers.0), Simd::splat(multipliers.1));

    // Create output arrays and process directly
    let mut ema_lines: [Vec<Vec<f64>>; N] = std::array::from_fn(|_| {
        vec![crate::uninit_vec!(f64, len)]
    });

    for i in 0..len {
        //let values: [f64; N] = (0..N).map(|j| inputs[j][0][i]).collect::<Vec<_>>().try_into().unwrap();
        let values: [f64; N] = std::array::from_fn(|j| inputs[j][0][i]);

        let vals = Simd::from_array(values);
        emas = calc_simd(vals, emas, multipliers_simd);
        let outputs = emas.to_array();
        for j in 0..N {
            unsafe { *ema_lines[j].get_unchecked_mut(0).get_unchecked_mut(i) = outputs[j] }
        }
    }

    // Update states with final EMA values
    let final_emas = emas.to_array();
    for i in 0..N {
        states[i].set_ema(final_emas[i]);
    }

    Ok(ema_lines)
}*/