NeuralAmpModeler-rs 3.0.0

// SPDX-License-Identifier: Apache-2.0
// Copyright (c) 2026 Fábio Henrique de Lima Silva (fhl.bsb@gmail.com) All rights reserved.

//! Zero-latency partitioned FFT convolution state for the Linear model.
//!
//! Implements hybrid convolution: the direct head (first `P` samples) is
//! computed in the time domain, while the tail (remaining `N-P` samples) is
//! computed in the frequency domain via overlap-save FFT blocks.
//!
//! # Architecture
//!
//! The IR `h[n]` of length `N` is partitioned into:
//! - **Head** (`h[0..P]`): convolved directly in the time domain with zero
//!   latency (no block delay).
//! - **Tail** (`h[P..N]`): partitioned into `K = ceil((N-P)/P)` blocks of
//!   at most `P` samples each, zero-padded to `2P`, and pre-transformed
//!   into the frequency domain via RFFT.
//!
//! At runtime, every `P` samples the input window of size `2P` is FFT'd
//! and stored in a circular frequency delay line (FDL). The accumulated
//! product of the FDL entries with the corresponding tail spectra is
//! inverse-transformed, yielding `P` valid output samples that are buffered
//! for per-sample consumption.
//!
//! # RT-Safety
//! - All buffers are pre-allocated at construction (`AlignedVec<f32>`,
//!   64-byte aligned for SIMD).
//! - The `RfftPlanner` pre-computes twiddle/bit-reversal tables once.
//! - Hot-path operations use only stack-allocated temporaries and
//!   pre-existing slice references — zero heap allocation, zero locks.

use crate::common::diagnostics::NamErrorCode;
use crate::math::common::AlignedVec;
use crate::math::common::dispatch::InstructionSet;
use crate::math::common::dispatch::SimdMathConfig;
use crate::math::dsp::fft::RfftPlanner;
use core::fmt;

/// State for zero-latency partitioned FFT (overlap-save) convolution.
///
/// Handles the tail portion of the impulse response (samples from partition
/// size `P` to the end `N-1`). The head (samples 0..P) is computed directly
/// in the time domain by `LinearModel::process_sample`.
///
/// # Buffer Layout
///
/// | Buffer            | Size              | Purpose                                   |
/// |-------------------|-------------------|-------------------------------------------|
/// | `h_fdl_re/im`     | `K × (P+1)`       | Pre-computed tail IR spectra (flat)       |
/// | `fdl_re/im`       | `K × (P+1)`       | Circular frequency delay line (flat)      |
/// | `input_buf`       | `2P`              | Input window for forward RFFT             |
/// | `fft_re/im`       | `P+1`             | Forward RFFT output (compact spectrum)    |
/// | `acc_re/im`       | `P+1`             | Complex MAC accumulation                  |
/// | `output_buf`      | `2P`              | IFFT output (time domain)                 |
/// | `tail_output_buf` | `P`               | Valid tail samples ready for consumption  |
///
/// where `K = ceil((N-P)/P)` is the number of tail partitions.
///
/// The spectrum buffers (`h_fdl_*` and `fdl_*`) are stored as flat
/// `AlignedVec<f32>` with stride `P+1` (number of bins). Partition `k`
/// occupies indices `[k * num_bins .. (k+1) * num_bins]`. This flat layout
/// avoids pointer indirection in the hot-path MAC loop and keeps all FDL
/// data in a single contiguous region for cache locality.
pub struct LinearFftState {
    /// Partition size `P` (head length = tail block size). Must be a power
    /// of two ≤ `N`.
    pub p: usize,
    /// Total receptive field `N` (= IR length).
    pub n: usize,
    /// Number of tail partitions `K = ceil((N-P)/P)`.
    pub num_partitions: usize,
    /// Number of complex bins per partition = `P + 1`.
    pub num_bins: usize,
    /// Real-to-complex FFT planner for block size `2P`.
    pub rfft: RfftPlanner<f32>,
    /// Pre-computed real spectra of the tail IR partitions. Flat buffer of
    /// length `K × num_bins`. Partition `k` starts at index `k * num_bins`.
    pub h_fdl_re: AlignedVec<f32>,
    /// Pre-computed imaginary spectra of the tail IR partitions.
    pub h_fdl_im: AlignedVec<f32>,
    /// Frequency delay line — real part. Flat circular buffer of past input
    /// spectra, length `K × num_bins`. Partition `k` starts at `k * num_bins`.
    pub fdl_re: AlignedVec<f32>,
    /// Frequency delay line — imaginary part.
    pub fdl_im: AlignedVec<f32>,
    /// Circular write index into `fdl_re` / `fdl_im` (0..K-1).
    /// Points to the next position that will be written. In `process_tail_block`,
    /// the FDL is read before writing: old spectra are consumed for the tail
    /// convolution, then the new input spectrum replaces the oldest entry.
    pub fdl_write_idx: usize,
    /// Input window buffer of size `2P` for the forward RFFT.
    /// Filled from the `MirroredBuffer` history in `LinearModel`.
    pub input_buf: AlignedVec<f32>,
    /// Forward RFFT output — real bins (size `P+1`).
    pub fft_re: AlignedVec<f32>,
    /// Forward RFFT output — imaginary bins (size `P+1`).
    pub fft_im: AlignedVec<f32>,
    /// Complex MAC accumulation buffer — real part (size `P+1`).
    pub acc_re: AlignedVec<f32>,
    /// Complex MAC accumulation buffer — imaginary part (size `P+1`).
    pub acc_im: AlignedVec<f32>,
    /// IFFT output buffer (size `2P`). Valid tail samples reside in
    /// indices `P..2P-1`.
    pub output_buf: AlignedVec<f32>,
    /// Circular buffer holding the `P` valid tail output samples from the
    /// most recent `process_tail_block` call. Read sequentially by
    /// `LinearModel::process_sample` in the FFT path.
    pub tail_output_buf: AlignedVec<f32>,
    /// Current read position within `tail_output_buf` (0 ≤ `sample_counter` < `P`).
    /// Incremented by `LinearModel::process_sample`; triggers a new tail
    /// block computation when it reaches `P`.
    pub sample_counter: usize,
    /// Instruction set captured at construction time to avoid runtime CPU
    /// feature checks in the audio hot path.
    pub isa: InstructionSet,
}

impl fmt::Debug for LinearFftState {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        f.debug_struct("LinearFftState")
            .field("p", &self.p)
            .field("n", &self.n)
            .field("num_partitions", &self.num_partitions)
            .field("num_bins", &self.num_bins)
            .field("fdl_write_idx", &self.fdl_write_idx)
            .field("sample_counter", &self.sample_counter)
            .finish_non_exhaustive()
    }
}

impl LinearFftState {
    /// Creates a new `LinearFftState` for the given impulse response.
    ///
    /// `p` is the partition size (head length), which must be a power of
    /// two and ≤ `weights.len()`. `weights` are the IR samples in
    /// **forward-time order** (i.e., `weights[0]` is the response at the
    /// current sample). They are read-only: only the tail portion
    /// (`weights[P..N]`) is used by this state; the head (`weights[0..P]`)
    /// is convolved directly by `LinearModel`.
    ///
    /// All internal buffers are pre-allocated with 64-byte alignment
    /// (`AlignedVec<f32>`) at construction time. No further heap
    /// allocations occur during processing.
    ///
    /// # Panics
    ///
    /// Panics if `p` is not a power of two, or if `p > weights.len()`.
    pub fn new(p: usize, weights: &[f32]) -> Result<Self, NamErrorCode> {
        let n = weights.len();
        assert!(p.is_power_of_two(), "P must be a power of two, got {p}");
        assert!(p <= n, "P ({p}) must be ≤ N ({n})");

        let block_size = 2 * p;
        let num_bins = p + 1;
        // ceil((N-P)/P), saturated at 0 when P==N
        let num_partitions = if n > p { (n - p).div_ceil(p) } else { 0 };

        let mut rfft = RfftPlanner::<f32>::new(block_size);

        let fdl_total = num_partitions * num_bins;
        let mut h_fdl_re = AlignedVec::<f32>::new(fdl_total, 0.0f32)?;
        let mut h_fdl_im = AlignedVec::<f32>::new(fdl_total, 0.0f32)?;

        // Reusable padded buffer for the forward RFFT (zero-padded IR segment)
        let mut padded = AlignedVec::<f32>::new(block_size, 0.0f32)?;
        let mut h_re = AlignedVec::<f32>::new(num_bins, 0.0f32)?;
        let mut h_im = AlignedVec::<f32>::new(num_bins, 0.0f32)?;

        for k in 0..num_partitions {
            let start = p + k * p;
            let end = (start + p).min(n);
            let seg_len = end - start;

            // Copy IR segment and zero-fill the tail of padded
            for i in 0..seg_len {
                padded[i] = weights[start + i];
            }
            padded[seg_len..].fill(0.0f32);

            rfft.process_forward(&padded, &mut h_re, &mut h_im);

            // Store spectrum at stride position k * num_bins
            let offset = k * num_bins;
            h_fdl_re[offset..offset + num_bins].copy_from_slice(&h_re);
            h_fdl_im[offset..offset + num_bins].copy_from_slice(&h_im);
        }

        // Initialize FDL with zeros (no past input yet)
        let fdl_re = AlignedVec::<f32>::new(fdl_total, 0.0f32)?;
        let fdl_im = AlignedVec::<f32>::new(fdl_total, 0.0f32)?;

        // fdl_write_idx starts at K-1 so that the first read uses all-zero
        // FDL entries (correct for silence before the first block).
        let fdl_write_idx = num_partitions.saturating_sub(1);
        let isa = SimdMathConfig::current().instruction_set;

        Ok(Self {
            p,
            n,
            num_partitions,
            num_bins,
            rfft,
            h_fdl_re,
            h_fdl_im,
            fdl_re,
            fdl_im,
            fdl_write_idx,
            input_buf: AlignedVec::<f32>::new(block_size, 0.0f32)?,
            fft_re: AlignedVec::<f32>::new(num_bins, 0.0f32)?,
            fft_im: AlignedVec::<f32>::new(num_bins, 0.0f32)?,
            acc_re: AlignedVec::<f32>::new(num_bins, 0.0f32)?,
            acc_im: AlignedVec::<f32>::new(num_bins, 0.0f32)?,
            output_buf: AlignedVec::<f32>::new(block_size, 0.0f32)?,
            tail_output_buf: AlignedVec::<f32>::new(p, 0.0f32)?,
            sample_counter: 0,
            isa,
        })
    }

    /// Returns a slice over the real spectrum of tail partition `k`.
    ///
    /// # Panics
    ///
    /// Panics if `k >= num_partitions`.
    #[inline]
    pub fn h_fdl_re_partition(&self, k: usize) -> &[f32] {
        let offset = k * self.num_bins;
        &self.h_fdl_re[offset..offset + self.num_bins]
    }
}

mod process;

#[cfg(test)]
#[path = "linear_fft_test.rs"]
mod tests;