bass-foundry/plugins/weld/core/tests/dsp.rs

use weld_core::{Engine, Listen, Settings};

fn signal(n: usize, hz: f32) -> f32 {
    (std::f32::consts::TAU * hz * n as f32 / 48000.).sin() * 0.5
}

#[test]
fn layer_output_is_the_main_input_with_zero_latency() {
    let mut engine = Engine::new(48000., 2).unwrap();
    engine.set_settings(Settings::default()).unwrap();
    assert_eq!(engine.latency_samples(), 0);
    for n in 0..4800 {
        let x = [signal(n, 110.), -signal(n, 220.)];
        let out = engine.process_sample(x, [signal(n, 330.), 0.25]);
        assert_eq!(out, x);
    }
}

#[test]
fn sum_modes_add_the_sidechain() {
    for listen in [Listen::Sum, Listen::SumDry] {
        let mut engine = Engine::new(48000., 2).unwrap();
        engine
            .set_settings(Settings {
                listen,
                ..Settings::default()
            })
            .unwrap();
        for n in 0..480 {
            let x = [signal(n, 110.), signal(n, 120.)];
            let s = [signal(n, 330.), -signal(n, 90.)];
            let out = engine.process_sample(x, s);
            for c in 0..2 {
                assert!((out[c] - (x[c] + s[c])).abs() < 1e-6);
            }
        }
    }
}

#[test]
fn mono_bypass_and_output_gain() {
    let mut engine = Engine::new(44100., 1).unwrap();
    engine
        .set_settings(Settings {
            output: -6.,
            ..Settings::default()
        })
        .unwrap();
    let out = engine.process_sample([0.5, 0.], [0., 0.]);
    assert!((out[0] - 0.5 * 10f32.powf(-6. / 20.)).abs() < 1e-6);
    assert_eq!(out[1], 0.);
    engine
        .set_settings(Settings {
            bypass: true,
            ..Settings::default()
        })
        .unwrap();
    assert_eq!(engine.process_sample([0.3, 0.], [0.9, 0.]), [0.3, 0.]);
}

#[test]
fn analyzer_reports_sidechain_presence_and_level() {
    let mut engine = Engine::new(48000., 2).unwrap();
    engine.set_settings(Settings::default()).unwrap();
    for n in 0..4800 {
        engine.process_sample([signal(n, 100.); 2], [0.; 2]);
    }
    let frame = engine.take_analyzer();
    assert!(!frame.side_seen);
    assert!(frame.side_db < -100.);
    assert!((frame.main_db - (-9.03)).abs() < 0.1, "{}", frame.main_db);
    for n in 0..4800 {
        engine.process_sample([0.; 2], [signal(n, 100.); 2]);
    }
    let frame = engine.take_analyzer();
    assert!(frame.side_seen);
    assert!((frame.side_db - (-9.03)).abs() < 0.1);
    assert!((frame.side_peak_db - (-6.02)).abs() < 0.1);
}

#[test]
fn invalid_settings_and_rates_are_rejected() {
    assert!(Engine::new(0., 2).is_err());
    assert!(Engine::new(48000., 3).is_err());
    let mut engine = Engine::new(48000., 2).unwrap();
    assert!(engine
        .set_settings(Settings {
            output: f32::NAN,
            ..Settings::default()
        })
        .is_err());
    let json = serde_json::to_string(&Settings::default()).unwrap();
    assert_eq!(
        serde_json::from_str::<Settings>(&json).unwrap(),
        Settings::default()
    );
}

use weld_core::{Analyzer, Chain, Fit, Mode, Section, Status};

fn random_fit(seed: u64) -> Fit {
    let mut s = seed;
    let mut rand = move || {
        s = s
            .wrapping_mul(6364136223846793005)
            .wrapping_add(1442695040888963407);
        (s >> 11) as f32 / (1u64 << 53) as f32
    };
    let mut fit = Fit {
        flip: rand() > 0.5,
        count: 1 + (rand() * 3.99) as usize,
        ..Fit::NONE
    };
    for section in &mut fit.sections {
        *section = Section {
            fc: 30. * 600f32.powf(rand()),
            q: 0.2 * 20f32.powf(rand()),
        };
    }
    fit
}

#[test]
fn every_chain_is_flat_in_magnitude() {
    for seed in 1..40 {
        let fit = random_fit(seed);
        for i in 0..200 {
            let f = 20. * 1000f32.powf(i as f32 / 199.);
            let (re, im) = fit.response(f, 48000.);
            let db = 10. * (re * re + im * im).log10();
            assert!(db.abs() < 0.01, "{fit:?} at {f} Hz: {db}");
        }
    }
}

#[test]
fn the_running_chain_matches_its_response() {
    let fit = random_fit(3);
    for f in [50f32, 333., 2100., 9000.] {
        let mut chain = Chain::new(fit, 48000.);
        let (mut i_sum, mut q_sum, mut energy) = (0f64, 0f64, 0f64);
        let n = 96000;
        for k in 0..n {
            let t = k as f64 / 48000.;
            let w = std::f64::consts::TAU * f as f64 * t;
            let y = chain.process(0, w.cos() as f32) as f64;
            if k > n / 2 {
                i_sum += y * w.cos();
                q_sum += -y * w.sin();
                energy += y * y;
            }
        }
        let m = (n / 2 - 1) as f64;
        let (re, im) = fit.response(f, 48000.);
        let measured = (2. * i_sum / m, 2. * q_sum / m);
        assert!(
            (measured.0 - re as f64).abs() < 0.01,
            "{f}: {measured:?} vs {re},{im}"
        );
        assert!(
            (measured.1 - im as f64).abs() < 0.01,
            "{f}: {measured:?} vs {re},{im}"
        );
        assert!((2. * energy / m - 1.).abs() < 0.01);
    }
}

#[test]
fn the_impulse_response_starts_at_sample_zero() {
    let mut chain = Chain::new(random_fit(5), 48000.);
    let first = chain.process(0, 1.);
    assert!(first.abs() > 0.01, "{first}");
}

#[test]
fn a_new_fit_crossfades_without_clicks() {
    let mut engine = Engine::new(48000., 2).unwrap();
    engine.set_settings(Settings::default()).unwrap();
    let link = engine.link();
    let x = |n: usize| signal(n, 97.) + 0.3 * signal(n, 1210.);
    let max_input_step = (1..48000)
        .map(|n| (x(n) - x(n - 1)).abs())
        .fold(0f32, f32::max);
    let mut previous = [0f32; 2];
    let mut largest = 0f32;
    for n in 0..48000 {
        if n == 4800 {
            link.push_fit(Fit {
                flip: true,
                count: 2,
                sections: [
                    Section { fc: 300., q: 0.7 },
                    Section { fc: 2000., q: 2. },
                    Section::default(),
                    Section::default(),
                ],
            });
        }
        let out = engine.process_sample([x(n), x(n)], [0.; 2]);
        if n > 0 {
            largest = largest.max((out[0] - previous[0]).abs());
        }
        previous = out;
    }
    assert!(
        largest <= 1.5 * max_input_step,
        "{largest} vs {max_input_step}"
    );
    assert!(engine.fit().flip);
    assert_eq!(engine.fit().count, 2);
}

#[test]
fn sum_uses_the_aligned_layer_and_sum_dry_the_unprocessed_one() {
    for listen in [Listen::Sum, Listen::SumDry] {
        let mut engine = Engine::new(48000., 1).unwrap();
        engine
            .set_settings(Settings {
                listen,
                ..Settings::default()
            })
            .unwrap();
        engine.set_fit(Fit {
            flip: true,
            ..Fit::NONE
        });
        let out = engine.process_sample([0.5, 0.], [0.2, 0.]);
        let expected = if listen == Listen::Sum { -0.3 } else { 0.7 };
        assert!((out[0] - expected).abs() < 1e-6, "{listen:?} {out:?}");
    }
}

#[test]
fn blocks_reach_the_worker_and_drops_are_counted() {
    let mut engine = Engine::new(48000., 2).unwrap();
    engine.set_settings(Settings::default()).unwrap();
    let link = engine.link();
    assert!(link.pop_settings().is_some());
    for n in 0..256 * 70 {
        engine.process_sample([signal(n, 100.); 2], [signal(n, 100.); 2]);
    }
    assert_eq!(link.dropped(), 6);
    let block = link.pop_block().unwrap();
    assert!((block.a[10] - signal(10, 100.)).abs() < 1e-6);
    assert_eq!(block.a, block.b);
}

#[test]
fn silence_holds_the_fit_and_produces_no_nan() {
    let flipped = Fit {
        flip: true,
        ..Fit::NONE
    };
    let mut analyzer = Analyzer::new(48000., flipped);
    analyzer.set_settings(Settings::default());
    let zeros = [0f32; 256];
    let mut last = None;
    for _ in 0..400 {
        analyzer.push(&zeros, &zeros);
        if let Some(update) = analyzer.poll() {
            assert!(update.fit.is_none());
            last = Some(update.report);
        }
    }
    let report = last.unwrap();
    assert_eq!(report.status, Status::NoSidechain);
    assert_eq!(report.fit, flipped);
    assert!(report.cost_db.is_finite() && report.recovered_db.is_finite());
    assert!(report
        .bands
        .iter()
        .all(|b| b.before.is_finite() && b.after.is_finite()));
}

#[test]
fn follow_mode_finds_the_flip_and_then_holds_still() {
    let mut analyzer = Analyzer::new(48000., Fit::NONE);
    analyzer.set_settings(Settings {
        mode: Mode::Follow,
        ..Settings::default()
    });
    let a: Vec<f32> = (0..48000 * 6)
        .map(|n| signal(n, 87.3) + 0.3 * signal(n, 261.9) + 0.1 * signal(n, 611.))
        .collect();
    let b: Vec<f32> = a.iter().map(|v| -0.7 * v).collect();
    let mut accepted = Vec::new();
    let mut last = None;
    for (x, y) in a.chunks(256).zip(b.chunks(256)) {
        analyzer.push(x, y);
        if let Some(update) = analyzer.poll() {
            if let Some(fit) = update.fit {
                accepted.push(fit);
            }
            last = Some(update.report);
        }
    }
    assert_eq!(accepted.len(), 1, "{accepted:?}");
    assert!(accepted[0].flip);
    let report = last.unwrap();
    assert_eq!(report.status, Status::Aligned);
    assert!(report.recovered_db > 10., "{}", report.recovered_db);
    assert!((report.recovered_db - report.cost_db).abs() < 0.2);
}

#[test]
fn learn_measures_and_applies_on_exit() {
    let mut analyzer = Analyzer::new(48000., Fit::NONE);
    let learn = Settings {
        mode: Mode::Learn,
        ..Settings::default()
    };
    analyzer.set_settings(learn);
    let a: Vec<f32> = (0..48000 * 2)
        .map(|n| signal(n, 87.3) + 0.3 * signal(n, 261.9))
        .collect();
    let b: Vec<f32> = a.iter().map(|v| -v).collect();
    for (x, y) in a.chunks(256).zip(b.chunks(256)) {
        analyzer.push(x, y);
        let _ = analyzer.poll();
    }
    analyzer.set_settings(Settings {
        mode: Mode::Hold,
        ..learn
    });
    let update = analyzer.poll().expect("leaving Learn reports at once");
    assert!(analyzer.current().flip);
    // Learn may already have applied the flip while measuring.
    assert!(update.fit.is_none_or(|f| f.flip));
    // Hold never refits, even when the layers change.
    let c: Vec<f32> = a.clone();
    for (x, y) in a.chunks(256).zip(c.chunks(256)) {
        analyzer.push(x, y);
        if let Some(update) = analyzer.poll() {
            assert!(update.fit.is_none());
        }
    }
    assert!(analyzer.current().flip);
}