Numerical Interpolation Calculator
Piecewise-linear, Lagrange, or natural cubic spline of tabulated (x, y). Not regression, not CAS. Runs locally.
Trust summary Engine tested · Specification checked · 13/13 tests · Production surface contract 4/4 · v1.1.0
- Input interpretation
- Enter values to calculate.
- Result
- —
- Model
- y at x from tabulated points by piecewise linear, Lagrange, or natural cubic spline.
- Scope
- Unique x; sorted internally
- Verification
- Engine tested · 13/13 tests · Production surface contract 4/4 · Specification checked · v1.1.0
- Named expert review
- Optional · Not performed
- Specification basis
- ISO 80000-2:2019 Quantities and units — Mathematics
- Evidence
- 4 golden · 2 boundary · 7 property · Production surface contract 4/4 · Artifact integrity PASS
- Production
- Embedded snapshot: unpublished · Build schema 1.1.0 ready · Semantic contract ✓ · Attestation report not published on origin · Live production status STALE (1 capability; 163 remain CURRENT) @ 2026-09-19T00:00:17.039Z
- Semantic contract
- PASS
Formulas
Core equations used by this calculator.
How to use
Enter tabulated points
At least two pairs with unique x. Linear is piecewise; Lagrange is one polynomial; spline is piecewise cubic. Discovery /spline-interpolation locks spline.
Evaluate at x
Linear and spline stay inside [x_min, x_max] unless extrapolate is on. Lagrange is defined everywhere.
Example calculations
Common configurations with formula and result.
Midpoint
(0,0) and (10,20) at x=5
Natural spline
(0,0), (1,1), (2,0) at x=0.5
Numerical Interpolation calculator specification
Version 1.1.0 · Engine tested
- Engine tested 13/13 tests · Production surface contract 4/4
- Named expert review Not performed
- Calculation version 1.1.0
- Definition
- Given tabulated points (xₖ, yₖ) with unique x, piecewise linear interpolates on the bracketing interval. Lagrange builds the unique polynomial of degree n−1 through n points. A natural cubic spline is piecewise cubic with S″=0 at the ends. Not statistical regression.
- What it calculates
- y at x from tabulated points by piecewise linear, Lagrange, or natural cubic spline.
- Inputs
- method
- x
- points?
- x0?
- y0?
- x1?
- y1?
- extrapolate?
- Outputs
- y
- n
- in_range
- extrapolated
- Formula
piecewise linear / Lagrange / natural cubic spline- Assumptions
- Unique x; sorted internally
- Natural spline ends, not clamped
- Not Akima / PCHIP / regression / CAS
- Units
- dimensionless
- Boundary conditions
- x outside table without extrapolate → VALUE_OUT_OF_RANGE
- duplicate x → INVALID_INPUT
- unknown method (including akima) → INVALID_MODE
- Example
- linear (0,0)(10,20) x=5 → 10
- Validation cases
3 published on this page · 13/13 tests · Production surface contract 4/4 · View evidence
- method=linear points=0,0;10,20 x=5 → y=10
- method=spline points=0,0;1,1;2,0 x=0.5 → y=0.6875
- method=akima points=0,0;1,1 x=0.5 → INVALID_MODE
- Specification basis
- ISO 80000-2:2019 Quantities and units — Mathematics
- Calculation version
- 1.1.0
Related tools
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Frequently asked questions
Key distinctions behind the calculation.
Is this Akima, PCHIP, or regression?
No. Methods are piecewise linear, Lagrange, and natural cubic spline. Akima, PCHIP, clamped spline, and least-squares fit are out of scope. It is not a Statistics calculator.
Where does this run?
Locally in the browser by default. REST and MCP call the same interpolation engine. /spline-interpolation is a discovery URL, not a second engine.