gridoxide 0.0.2

//! The measurement Jacobian `H` and the gain matrix `G = HᵀWH`.
//!
//! # State layout
//!
//! State estimation's unknowns are not power flow's. There are no PV buses
//! here — a generator's voltage is something to be estimated, not asserted — so
//! *every* bus contributes a magnitude, and every bus but the angle reference
//! contributes an angle:
//!
//! ```text
//! x = [ θ₀ … θ_{N-1} except the reference ,  V₀ … V_{N-1} ]
//! ```
//!
//! giving `n = 2N − 1`, against power flow's `n_angle + n_pq`
//! (`solver::newton_raphson_cached`). Confusing the two layouts is the easiest
//! way to produce a Jacobian that is subtly, consistently wrong, so
//! [`StateLayout`] owns the mapping and nothing else indexes by hand.
//!
//! # Why the normal equations
//!
//! `H` is rectangular (`m × n`), and gridoxide's [`LinearSolver`] backends are
//! all square — they are power flow's Jacobian solvers. Forming the normal
//! equations `G Δx = HᵀW r` makes the system square *and* symmetric, so all
//! five backends carry state estimation with no new solver abstraction. The
//! cost is conditioning: `G` squares `H`'s condition number, which is why the
//! plan keeps the option of an orthogonal method open and why phase 4 prefers
//! equality constraints over huge weights.

use crate::measurement::{AngleFrame, Measurement, MeasurementKind, Target};
use crate::se::functional::{
    current_partials_of, local_current_partials_of, power_partials_of, Partial,
};
use crate::types::Bus;

use super::SeNetwork;

/// Maps buses to positions in the state vector.
pub struct StateLayout {
    pub n_buses: usize,
    /// The bus whose angle is held at zero, if one is pinned.
    ///
    /// A network measured only in magnitudes and powers is invariant under a
    /// global phase shift, so without a reference `G` is singular by
    /// construction no matter how many measurements there are. But that
    /// invariance disappears the moment a *phasor* measurement supplies an
    /// absolute angle — and pinning a reference on top of one would then be a
    /// false constraint, rotating the whole estimate away from the angles that
    /// were actually measured. So this is `None` exactly when the measurement
    /// set determines the phase by itself.
    pub angle_ref: Option<usize>,
    /// Position of each bus's angle unknown, or `None` for the reference.
    theta_pos: Vec<Option<usize>>,
    /// Where the magnitude block starts, i.e. the number of angle unknowns.
    vmag_offset: usize,
}

impl StateLayout {
    /// Builds the layout for a measurement set.
    ///
    /// A reference is pinned only when the measurements contain no voltage
    /// angle; see [`angle_ref`](Self::angle_ref).
    ///
    /// When one is pinned it is the *physical node a source feeds*, not the
    /// virtual slack bus behind it. power-grid-model normalizes by setting its
    /// slack bus's angle to zero, and its slack bus is that physical node,
    /// since it has no virtual bus at all. Pinning the virtual bus instead
    /// leaves every angle offset by the drop across the source impedance — a
    /// constant, invisible in magnitudes, and exactly the 6.5e-3 rad uniform
    /// shift the transmission-case fixture showed before this was fixed. Stiff
    /// sources hide it, which is why the smaller fixtures agreed either way.
    pub fn new(buses: &[Bus], measurements: &[Measurement], net: &SeNetwork) -> Self {
        let phase_is_measured = measurements
            .iter()
            .any(|m| m.kind == MeasurementKind::VoltageAngle && m.weight() > 0.0);

        let angle_ref = (!phase_is_measured).then(|| {
            net.source_branches
                .iter()
                .position(|feeding| !feeding.is_empty())
                .or_else(|| {
                    buses
                        .iter()
                        .position(|b| matches!(b.bus_type, crate::types::BusType::Slack))
                })
                .unwrap_or(0)
        });

        let mut theta_pos = vec![None; buses.len()];
        let mut next = 0;
        for i in 0..buses.len() {
            if Some(i) != angle_ref {
                theta_pos[i] = Some(next);
                next += 1;
            }
        }
        Self { n_buses: buses.len(), angle_ref, theta_pos, vmag_offset: next }
    }

    /// Number of unknowns: `2N` when the phase is measured, `2N − 1` when a
    /// reference has to be pinned.
    pub fn n_unknowns(&self) -> usize {
        self.vmag_offset + self.n_buses
    }

    /// Column of a bus's angle, or `None` for the reference bus.
    pub fn theta(&self, bus: usize) -> Option<usize> {
        self.theta_pos[bus]
    }

    /// Column of a bus's voltage magnitude.
    pub fn vmag(&self, bus: usize) -> usize {
        self.vmag_offset + bus
    }
}

/// One row of `H`: the nonzero partials of a measurement, as `(column, value)`.
///
/// Rows are short — a voltage measurement touches one column, a branch flow
/// four, a bus injection two per adjacent bus — which is what keeps `G` sparse.
pub type Row = Vec<(usize, f64)>;

/// Accumulates a partial into a row.
///
/// Only the reference bus's angle is dropped, because it is not an unknown at
/// all. A numerically zero partial is *kept*: `H`'s pattern has to depend on the
/// topology alone, not on the current state. Dropping zeros would shrink the row
/// at a flat start — where many `sin(θ_i − θ_k)` terms vanish exactly — and grow
/// it again on the next iteration, changing the gain matrix's sparsity pattern
/// between iterations and invalidating the cached symbolic factorization
/// (`sparse::RealSparseSystem` documents that its argsort assumes positional
/// correspondence, and faer asserts on the mismatch).
fn push(row: &mut Row, col: Option<usize>, value: f64) {
    if let Some(col) = col {
        row.push((col, value));
    }
}

/// Partials of the bus injections `P_i`, `Q_i` with respect to a neighbour's
/// angle and magnitude — the classic power-flow Jacobian expressions.
///
/// Superseded by [`CurrentFunctional::power_partials`], which derives the same
/// numbers for every target rather than for injections alone. Kept as a
/// test-only oracle: it is an independent derivation, so agreeing with it is
/// evidence beyond a finite-difference check of the new code against itself.
#[cfg(test)]
fn injection_partials(
    net: &SeNetwork,
    buses: &[Bus],
    p_inj: &[f64],
    q_inj: &[f64],
    i: usize,
    k: usize,
) -> (f64, f64, f64, f64) {
    let y_ik = net.ybus.get(i, k);
    let (g, b) = (y_ik.re, y_ik.im);
    let (v_i, v_k) = (buses[i].voltage_mag, buses[k].voltage_mag);

    if i == k {
        let v2 = v_i * v_i;
        (
            // dP/dθ, dP/dV, dQ/dθ, dQ/dV
            -q_inj[i] - b * v2,
            p_inj[i] / v_i + g * v_i,
            p_inj[i] - g * v2,
            q_inj[i] / v_i - b * v_i,
        )
    } else {
        let (s, c) = (buses[i].voltage_ang - buses[k].voltage_ang).sin_cos();
        (
            v_i * v_k * (g * s - b * c),
            v_i * (g * c + b * s),
            -v_i * v_k * (g * c + b * s),
            v_i * (g * s - b * c),
        )
    }
}

/// Adds a functional's partials to `row`, in the estimator's column layout.
///
/// Takes `(at, coefficients)` borrowed rather than a whole
/// [`CurrentFunctional`], so a caller already holding a coefficient slice — a
/// zero-injection constraint hands over a Y-bus row directly — does not
/// allocate a copy of it per row per iteration.
fn add_functional_row(
    row: &mut Row,
    layout: &StateLayout,
    at: usize,
    coefficients: &[(usize, num_complex::Complex<f64>)],
    v: &[num_complex::Complex<f64>],
    active: bool,
    scratch: &mut Vec<Partial>,
) {
    scratch.clear();
    power_partials_of(at, coefficients, v, scratch);
    push_partials(row, layout, scratch, active);
}

/// Writes partials into a row, taking the real or imaginary half of each.
///
/// A partial repeated on one bus is summed, not overwritten: `Row` is an
/// association list and `gain_and_rhs` sums duplicates. That is what makes a
/// node injection's overlapping Y-bus and source terms come out right, and a
/// half-open branch's self-loop with it.
fn push_partials(row: &mut Row, layout: &StateLayout, partials: &[Partial], real: bool) {
    for p in partials {
        let (d_th, d_v) = if real {
            (p.d_dtheta.re, p.d_dvmag.re)
        } else {
            (p.d_dtheta.im, p.d_dvmag.im)
        };
        push(row, layout.theta(p.bus), d_th);
        push(row, Some(layout.vmag(p.bus)), d_v);
    }
}

/// One bus-injection row on its own, for callers that need the same partials
/// outside the measurement set — `se::constraints` builds its constraint rows
/// from exactly this, since a zero-injection constraint and an injection
/// measurement differ only in how the system consumes the row.
///
/// `v` is the state as complex phasors, passed in because a caller building
/// many rows should form it once.
pub fn injection_row(
    layout: &StateLayout,
    net: &SeNetwork,
    v: &[num_complex::Complex<f64>],
    bus: usize,
    active: bool,
    scratch: &mut Vec<Partial>,
) -> Row {
    let mut row = Row::new();
    add_functional_row(&mut row, layout, bus, net.ybus.row(bus), v, active, scratch);
    row
}

/// Builds `H`, one row per measurement, in the same order.
pub fn measurement_jacobian(
    measurements: &[Measurement],
    buses: &[Bus],
    net: &SeNetwork,
    layout: &StateLayout,
) -> Vec<Row> {
    let model = crate::se::MeasurementModel::new(measurements, net);
    measurement_jacobian_with(measurements, buses, layout, &model)
}

/// [`measurement_jacobian`] against an already-resolved model.
///
/// Two arms, not five. A voltage row is a single unit entry; every power row is
/// its functional's partials, whatever target produced it.
pub fn measurement_jacobian_with(
    measurements: &[Measurement],
    buses: &[Bus],
    layout: &StateLayout,
    model: &crate::se::MeasurementModel,
) -> Vec<Row> {
    let v: Vec<num_complex::Complex<f64>> = buses
        .iter()
        .map(|b| num_complex::Complex::from_polar(b.voltage_mag, b.voltage_ang))
        .collect();
    let mut scratch = Vec::new();

    measurements
        .iter()
        .enumerate()
        .map(|(i, m)| {
            let mut row = Row::new();
            // A measurement on a de-energized bus contributes no row at all,
            // not a zero-weighted one: an empty row leaves its columns
            // untouched, which is what lets `mask_untouched` pin them.
            if !model.is_live(i) {
                return row;
            }
            match (m.kind, m.target) {
                (MeasurementKind::VoltageMagnitude, Target::Bus(b)) => {
                    push(&mut row, Some(layout.vmag(b)), 1.0)
                }
                (MeasurementKind::VoltageAngle, Target::Bus(b)) => {
                    push(&mut row, layout.theta(b), 1.0)
                }
                _ => {
                    if let Some(f) = model.functional(i) {
                        scratch.clear();
                        match m.target {
                            Target::BranchTerminalCurrent { frame, .. } => match frame {
                                AngleFrame::Global => {
                                    current_partials_of(&f.coefficients, &v, &mut scratch)
                                }
                                AngleFrame::Local => local_current_partials_of(
                                    f.at,
                                    &f.coefficients,
                                    &v,
                                    &mut scratch,
                                ),
                            },
                            _ => power_partials_of(f.at, &f.coefficients, &v, &mut scratch),
                        }
                        let real = matches!(
                            m.kind,
                            MeasurementKind::ActivePower | MeasurementKind::CurrentReal
                        );
                        push_partials(&mut row, layout, &scratch, real);
                    }
                }
            }
            row
        })
        .collect()
}

/// Pins state variables that nothing reaches, and reports which.
///
/// A column no row touches leaves an all-zero row and column in `G`, making the
/// whole system singular even when the rest of it is perfectly determined.
/// Writing an identity there with a zero right-hand side holds that variable at
/// its current value and lets the observable part solve — the same masking
/// `bde::mask_scenario` uses for a converged block, and for the same reason:
/// dropping the row instead would change the sparsity pattern and invalidate a
/// cached symbolic factorization.
///
/// "Touched" is structural — any appearance in a row, regardless of value — so
/// that the mask, and hence the sparsity pattern, is identical across
/// iterations. Whether a present-but-degenerate column is *usefully* determined
/// is a different question, and
/// [`observability`](super::observability)'s.
pub fn mask_untouched(
    triplets: &mut Vec<(usize, usize, f64)>,
    rhs: &mut [f64],
    row_sets: &[&[Row]],
    n: usize,
) -> Vec<usize> {
    let mut touched = vec![false; n];
    for rows in row_sets {
        for row in rows.iter() {
            for &(c, _) in row {
                touched[c] = true;
            }
        }
    }
    let mut untouched = Vec::new();
    for (c, &seen) in touched.iter().enumerate() {
        if !seen {
            triplets.push((c, c, 1.0));
            rhs[c] = 0.0;
            untouched.push(c);
        }
    }
    untouched
}

/// Assembles `G = HᵀWH` as triplets, and `HᵀW r` as a dense vector.
///
/// `G = Σ_m w_m·hₘhₘᵀ`, so it is built as a sum of per-row outer products —
/// cheap because rows are short. Duplicate `(row, col)` triplets are summed by
/// the sparse backends, which is also what makes a self-loop branch's repeated
/// columns come out right.
pub fn gain_and_rhs(
    rows: &[Row],
    measurements: &[Measurement],
    residuals: &[f64],
) -> (Vec<(usize, usize, f64)>, Vec<f64>, usize) {
    let n = rows
        .iter()
        .flat_map(|r| r.iter().map(|&(c, _)| c + 1))
        .max()
        .unwrap_or(0);
    let mut triplets = Vec::new();
    let mut rhs = vec![0.0; n];

    for ((row, m), &r) in rows.iter().zip(measurements).zip(residuals) {
        // An infinite sigma contributes nothing, by design — but it has to
        // contribute nothing *numerically*, not structurally. Skipping the row
        // outright would make the triplet list's length and order depend on a
        // measurement's sigma, i.e. on a value rather than on the topology and
        // the measurement set's shape. That breaks two things that assume
        // otherwise: `RealSparseSystem`'s cached argsort, which relies on
        // positional correspondence between calls, and `PersistentEstimator`'s
        // stated validity condition, which promises a weight scales `G`'s values
        // and never its pattern. Stamping an exact zero keeps both true and is
        // numerically identical.
        //
        // A non-finite weight means a zero sigma, i.e. a perfectly known
        // measurement, which would properly be a hard constraint rather than a
        // very heavy row. `checked_sigma` rejects it at the door, so this clamp
        // is a guard on an unreachable case rather than a modelling decision.
        let w = m.weight();
        let w = if w.is_finite() { w } else { 0.0 };
        for &(i, hi) in row {
            rhs[i] += w * hi * r;
            for &(j, hj) in row {
                triplets.push((i, j, w * hi * hj));
            }
        }
    }
    (triplets, rhs, n)
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::branch_flow::Terminal;
    use crate::measurement::Target;
    use crate::se::measurement_functions;

    /// Every row of `H` against central differences of `h(x)`.
    ///
    /// This is the real guard on this module: the injection partials in
    /// particular are eight sign-sensitive expressions that are easy to write
    /// plausibly and wrongly, and a consistently wrong Jacobian still converges
    /// — to the wrong answer, slowly, in a way that looks like a bad fixture.
    pub(super) fn assert_jacobian_matches_finite_differences(
        measurements: &[Measurement],
        buses: &[Bus],
        net: &SeNetwork,
        tol: f64,
    ) {
        let layout = StateLayout::new(buses, measurements, net);
        let rows = measurement_jacobian(measurements, buses, net, &layout);
        let n = layout.n_unknowns();
        let h = 1e-7;

        // Dense the rows out for easy comparison, summing duplicates.
        let mut dense = vec![vec![0.0; n]; measurements.len()];
        for (r, row) in rows.iter().enumerate() {
            for &(c, val) in row {
                dense[r][c] += val;
            }
        }

        for col in 0..n {
            let bump = |delta: f64| {
                let mut b = buses.to_vec();
                // Columns below `vmag(0)` are angles, the rest magnitudes.
                if col < layout.vmag(0) {
                    let bus = (0..buses.len())
                        .find(|&i| layout.theta(i) == Some(col))
                        .expect("angle column maps to a bus");
                    b[bus].voltage_ang += delta;
                } else {
                    b[col - layout.vmag(0)].voltage_mag += delta;
                }
                measurement_functions(measurements, &b, net)
            };
            let plus = bump(h);
            let minus = bump(-h);

            for (r, m) in measurements.iter().enumerate() {
                let numeric = (plus[r] - minus[r]) / (2.0 * h);
                let analytic = dense[r][col];
                assert!(
                    (numeric - analytic).abs() < tol,
                    "row {r} ({:?} on {:?}), column {col}: analytic {analytic}, numeric {numeric}",
                    m.kind,
                    m.target,
                );
            }
        }
    }

    fn measurement(kind: MeasurementKind, target: Target) -> Measurement {
        Measurement { kind, target, value: 0.0, sigma: 1.0 }
    }

    /// The unified row reproduces the closed-form injection partials it
    /// replaced.
    ///
    /// `injection_partials` is the classic power-flow Jacobian written out as
    /// eight expressions in `p_inj`, `q_inj`, `g`, `b` and the angle difference.
    /// `power_partials_of` derives the same numbers from `S = V_at · conj(I)`
    /// without ever naming them. Two independent derivations agreeing to 1e-12
    /// at an arbitrary state is stronger evidence than either one agreeing with
    /// finite differences of itself, which is why the old form is retained
    /// `#[cfg(test)]` rather than deleted.
    #[test]
    fn the_unified_row_matches_the_closed_form_it_replaced() {
        let (net, mut buses) = super::super::tests::two_bus_net();
        // Nothing zero by symmetry: distinct magnitudes and a real angle spread.
        buses[0].voltage_mag = 1.037;
        buses[0].voltage_ang = 0.147;
        buses[1].voltage_mag = 0.962;
        buses[1].voltage_ang = -0.083;

        let (p_inj, q_inj) = crate::network::power_injections(&buses, &net.ybus);
        let v: Vec<num_complex::Complex<f64>> = buses
            .iter()
            .map(|b| num_complex::Complex::from_polar(b.voltage_mag, b.voltage_ang))
            .collect();

        let mut compared = 0;
        for bus in 0..buses.len() {
            let mut partials = Vec::new();
            power_partials_of(bus, net.ybus.row(bus), &v, &mut partials);
            for p in &partials {
                let (dp_dth, dp_dv, dq_dth, dq_dv) =
                    injection_partials(&net, &buses, &p_inj, &q_inj, bus, p.bus);
                assert!((p.d_dtheta.re - dp_dth).abs() < 1e-12, "dP/dθ at ({bus},{})", p.bus);
                assert!((p.d_dvmag.re - dp_dv).abs() < 1e-12, "dP/dV at ({bus},{})", p.bus);
                assert!((p.d_dtheta.im - dq_dth).abs() < 1e-12, "dQ/dθ at ({bus},{})", p.bus);
                assert!((p.d_dvmag.im - dq_dv).abs() < 1e-12, "dQ/dV at ({bus},{})", p.bus);
                compared += 1;
            }
        }
        assert!(compared >= 4, "expected several neighbours to compare, got {compared}");
    }

    /// Covers every target kind at once, on a network where no partial is zero
    /// by symmetry.
    #[test]
    fn jacobian_matches_finite_differences_for_every_target_kind() {
        let (net, buses) = super::super::tests::two_bus_net();
        let measurements = vec![
            measurement(MeasurementKind::VoltageMagnitude, Target::Bus(1)),
            measurement(MeasurementKind::VoltageAngle, Target::Bus(1)),
            measurement(MeasurementKind::ActivePower, Target::Bus(1)),
            measurement(MeasurementKind::ReactivePower, Target::Bus(1)),
            measurement(
                MeasurementKind::ActivePower,
                Target::BranchTerminal { branch: 0, terminal: Terminal::From },
            ),
            measurement(
                MeasurementKind::ReactivePower,
                Target::BranchTerminal { branch: 0, terminal: Terminal::To },
            ),
            measurement(MeasurementKind::ActivePower, Target::SourceInjection { branch: 0 }),
            measurement(MeasurementKind::ReactivePower, Target::ShuntInjection { bus: 1 }),
            measurement(MeasurementKind::ActivePower, Target::NodeInjection(1)),
            measurement(MeasurementKind::ReactivePower, Target::NodeInjection(1)),
        ];
        assert_jacobian_matches_finite_differences(&measurements, &buses, &net, 1e-5);
    }

    /// The layout is `2N − 1`, and the reference bus has no angle column.
    #[test]
    fn state_layout_excludes_only_the_reference_angle() {
        let (net, buses) = super::super::tests::two_bus_net();
        let layout = StateLayout::new(&buses, &[], &net);
        assert_eq!(layout.n_unknowns(), 2 * buses.len() - 1);
        let reference = layout.angle_ref.expect("no angle measurements, so a reference is pinned");
        assert_eq!(layout.theta(reference), None);
        for i in 0..buses.len() {
            if i != reference {
                assert!(layout.theta(i).is_some(), "bus {i} should carry an angle unknown");
            }
        }
    }

    /// A sigma going to infinity must change `G`'s *values* and not its
    /// pattern.
    ///
    /// This is what `PersistentEstimator` promises ("a weight scales `G`'s
    /// values, never its pattern") and what `RealSparseSystem`'s cached argsort
    /// requires, since it assumes the value slice it is handed corresponds
    /// positionally to the one the pattern was built from. `gain_and_rhs` used
    /// to `continue` past a zero-weight row, which broke both: the triplet list
    /// got shorter when a sensor was disabled. Batch estimation makes that live
    /// — a scenario that disables a sensor would hand faer a mismatched slice.
    #[test]
    fn an_infinite_sigma_changes_values_but_not_the_gain_pattern() {
        let (net, buses) = super::super::tests::two_bus_net();
        let finite = vec![
            measurement(MeasurementKind::VoltageMagnitude, Target::Bus(1)),
            measurement(MeasurementKind::ActivePower, Target::Bus(1)),
        ];
        let mut disabled = finite.clone();
        disabled[1].sigma = f64::INFINITY;

        let layout = StateLayout::new(&buses, &finite, &net);
        let residuals = [0.1, 0.2];
        let pattern = |ms: &[crate::measurement::Measurement]| {
            let rows = measurement_jacobian(ms, &buses, &net, &layout);
            let (triplets, _, _) = gain_and_rhs(&rows, ms, &residuals);
            triplets
        };

        let a = pattern(&finite);
        let b = pattern(&disabled);
        assert_eq!(
            a.iter().map(|&(i, j, _)| (i, j)).collect::<Vec<_>>(),
            b.iter().map(|&(i, j, _)| (i, j)).collect::<Vec<_>>(),
            "disabling a sensor must not move, add or drop a triplet position"
        );
        assert!(
            a.iter().zip(&b).any(|(x, y)| x.2 != y.2),
            "the values should differ — otherwise the sigma did nothing at all"
        );
        // And the disabled row really is inert, not merely present.
        let rows = measurement_jacobian(&disabled, &buses, &net, &layout);
        let (_, rhs, _) = gain_and_rhs(&rows, &disabled, &residuals);
        let only_voltage = vec![finite[0]];
        let vrows = measurement_jacobian(&only_voltage, &buses, &net, &layout);
        let (_, vrhs, _) = gain_and_rhs(&vrows, &only_voltage, &residuals[..1]);
        for (x, y) in rhs.iter().zip(&vrhs) {
            assert!((x - y).abs() < 1e-15, "an infinite sigma still moved the rhs: {x} vs {y}");
        }
    }

    /// `G` must be symmetric — it is `HᵀWH` — and its diagonal non-negative.
    #[test]
    fn gain_matrix_is_symmetric() {
        let (net, buses) = super::super::tests::two_bus_net();
        let measurements = vec![
            measurement(MeasurementKind::VoltageMagnitude, Target::Bus(1)),
            measurement(MeasurementKind::ActivePower, Target::Bus(1)),
            measurement(
                MeasurementKind::ReactivePower,
                Target::BranchTerminal { branch: 0, terminal: Terminal::From },
            ),
        ];
        let layout = StateLayout::new(&buses, &measurements, &net);
        let rows = measurement_jacobian(&measurements, &buses, &net, &layout);
        let (triplets, _, n) = gain_and_rhs(&rows, &measurements, &[0.1, 0.2, 0.3]);

        let mut dense = vec![vec![0.0; n]; n];
        for (i, j, v) in triplets {
            dense[i][j] += v;
        }
        for i in 0..n {
            assert!(dense[i][i] >= -1e-12, "diagonal {i} is negative: {}", dense[i][i]);
            for j in 0..n {
                assert!(
                    (dense[i][j] - dense[j][i]).abs() < 1e-9,
                    "G is not symmetric at ({i},{j}): {} vs {}",
                    dense[i][j],
                    dense[j][i]
                );
            }
        }
    }
}