Struct ConstantDerivativeMatrixProof 

pub struct ConstantDerivativeMatrixProof<C = f64> { /* private fields */ }

A constant derivative Jacobian whose rank is computed without a numerical tolerance.

Every finite f64 coefficient is interpreted as the exact binary rational number represented by its bits. Rank is then recomputed with arbitrary- precision rational elimination. The stored rank is therefore evidence about the lowered matrix itself, not a sample-state estimate or a backend-dependent floating-point classification. The binary64 constructor retains binary64 coefficients for numerical time backends; from_exact retains rational coefficients for symbolic compatibility projection. Both representations share the same exact elimination and rank owner.

Implementations

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impl ConstantDerivativeMatrixProof

Signature links:ConstantDerivativeMatrixProof

pub fn new( dimension: usize, coefficients: Vec<f64>, ) -> Result<ConstantDerivativeMatrixProof, Diagnostic>

Signature links:newusizeVecf64ResultConstantDerivativeMatrixProofDiagnostic

Construct and exactly classify one square constant derivative matrix.

Errors

Returns EQ0705 for an empty/non-square matrix or a non-finite coefficient.

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impl ConstantDerivativeMatrixProof<Ratio<BigInt>>

Signature links:ConstantDerivativeMatrixProofRatioBigInt

pub fn from_exact( dimension: usize, coefficients: Vec<Ratio<BigInt>>, ) -> Result<ConstantDerivativeMatrixProof<Ratio<BigInt>>, Diagnostic>

Signature links:from_exactusizeVecRatioBigIntResultConstantDerivativeMatrixProofRatioBigIntDiagnostic

Construct a matrix from exact symbolic coefficients without first rounding their sums or products to binary64.

Errors

Rejects empty/non-square matrices and raw rationals with zero denominators.

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impl<C> ConstantDerivativeMatrixProof<C>

Signature links:ConstantDerivativeMatrixProof

pub const fn dimension(&self) -> usize

Signature links:dimensionusize

Number of state coordinates and residual rows.

pub fn coefficients(&self) -> &[C]

Signature links:coefficients[C]

Complete row-major coefficient storage.

pub fn row(&self, row: usize) -> Option<&[C]>

Signature links:rowusizeOption[C]

One residual row in state-coordinate order.

pub const fn exact_rank(&self) -> usize

Signature links:exact_rankusize

Exact rank over the binary rational values represented by the matrix.

pub fn compatibility_residual( &self, additional_columns: &[Vec<Ratio<BigInt>>], rhs: &[Ratio<BigInt>], ) -> Result<Vec<f64>, Diagnostic>

Signature links:compatibility_residualVecRatioBigIntRatioBigIntResultVecf64Diagnostic

Orthogonal residual of M a + C u = rhs in the original row coordinates. additional_columns supplies C column by column. Elimination and the least-squares projection use exact binary rationals; only the returned residual is rounded to binary64. The RHS is already exact so coefficient accumulation cannot erase a constrained direction before projection. Callers own residual scaling/tolerance. This does not decide infinity-norm tolerance feasibility.

Errors

Returns EQ0705 for invalid dimensions, nonfinite inputs, or a residual that cannot be represented as a finite binary64 value.

pub fn is_compatible( &self, additional_columns: &[Vec<Ratio<BigInt>>], column: &[Ratio<BigInt>], ) -> Result<bool, Diagnostic>

Signature links:is_compatibleVecRatioBigIntRatioBigIntResultboolDiagnostic

Whether a column belongs exactly to the span of M and the additional columns, before rounding any residual. This is not a tolerance test.

Errors

Returns EQ0705 for nonfinite inputs or mismatched row dimensions.

pub fn require_index_one_regularity( &self, state_jacobian: &[f64], ) -> Result<(), Diagnostic>

Signature links:require_index_one_regularityf64Result()Diagnostic

Require local index-one regularity of the constant-mass residual. state_jacobian is the row-major Jacobian of the regular residuals with respect to values, excluding initial equations and their tangents. This checks one point; it performs no index reduction or state selection.

Errors

Returns EQ0705 for an invalid Jacobian or a singular/high-index block.

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impl ConstantDerivativeMatrixProof

Signature links:ConstantDerivativeMatrixProof

pub fn monomial_rows(&self) -> Option<Vec<MonomialDerivativeRow>>

Signature links:monomial_rowsOptionVecMonomialDerivativeRow

Derive the monomial row view used only for explicit-ODE normalization.

Returns None unless every row has exactly one non-zero coefficient and every state coordinate occurs exactly once.

Trait Implementations

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impl<C> Clone for ConstantDerivativeMatrixProof<C>

where C: Clone,

Signature links:CloneConstantDerivativeMatrixProofClone

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fn clone(&self) -> ConstantDerivativeMatrixProof<C>

Signature links:cloneConstantDerivativeMatrixProof

Returns a duplicate of the value.

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fn clone_from(&mut self, source: &Self)

Signature links:unstableSourceclone_from

Performs copy-assignment from source.

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impl<C> Debug for ConstantDerivativeMatrixProof<C>

where C: Debug,

Signature links:DebugConstantDerivativeMatrixProofDebug

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Signature links:fmtFormatterResult()Error

Formats the value using the given formatter.

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impl<C> PartialEq for ConstantDerivativeMatrixProof<C>

where C: PartialEq,

Signature links:PartialEqConstantDerivativeMatrixProofPartialEq

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fn eq(&self, other: &ConstantDerivativeMatrixProof<C>) -> bool

Signature links:eqConstantDerivativeMatrixProofbool

Tests for self and other values to be equal, and is used by ==.

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fn ne(&self, other: &Rhs) -> bool

Signature links:unstableSourcene&Rhsbool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<C> StructuralPartialEq for ConstantDerivativeMatrixProof<C>