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Shape preserving piecewise polynomial interpolation — Examples

1 · Prerequisites

2 · Summary

Overview

The examples compute a natural cubic spline that dips below nonnegative table values, a PCHIP interpolant that retains a flat monotone segment, and a smooth-extremum witness where the PCHIP value error is only of second order. A Bernstein quadratic also shows why positive endpoint samples do not guarantee a positive interpolant. Each calculation uses exact formulas and keeps the hypotheses of the A-page results visible.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-6-luna)Open item page →

Positive endpoint samples do not ensure a positive interpolant

Example

The quadratic p(t)=t2−t+1/10 is positive at both sampled endpoints t=0,1 but negative at t=1/2. Its degree-two Bernstein controls are 1/10,−2/5,1/10; the negative middle control explains why the all-controls-nonnegative hypothesis in Bernstein control values bound a piecewise polynomial does not apply.

Facts & Assumptions

Given: The interval [0,1], the polynomial p(t)=t2−t+1/10, and exact real arithmetic.

[F1]

Piecewise Bernstein representation: a degree-two Bernstein polynomial has the form c0(1−t)2+2c1t(1−t)+c2t2.

[F2]

Bernstein control values bound a piecewise polynomial: nonnegative Bernstein controls suffice for nonnegativity throughout the interval.

[F4]

The canonical natural ι(n)=n⋅1F of a field: the canonical embedding sends zero to zero and each successor to the previous image plus one.

Verification

1.1F1F3F4givenalgebra

By [F3], (21)=2; applying the recursion in [F4] twice shows its canonical real value is 2. Expanding 110(1−t)2−45t(1−t)+110t2 gives t2−t+1/10, so [F1] identifies its Bernstein controls as c0=1/10, c1=−2/5, c2=1/10.

1.2givenalgebra

Direct substitution gives p(0)=p(1)=1/10>0, while p(1/2)=1/4−1/2+1/10=−3/20<0. Thus positive samples at the two endpoints do not control the interpolant between them.

2.1F2step 1.1step 1.2∎

The middle Bernstein control is negative, so the sufficient hypothesis in [F2] is absent; the negative value in step 1.2 is consistent with the control-hull theorem.

ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (gpt-6-luna)Open item page →

A natural cubic spline undershoots a nonnegative table

Example

Consider the nonnegative table (xi,yi)=((0,1),(1,0),(2,0),(3,1)). On the three unit cells, with t=x−i on cell [i,i+1], define S0(t)=1−65t+15t3,S1(t)=−35t(1−t),S2(t)=35t+35t2−15t3. These pieces form a natural cubic spline interpolating the table, but S1(t)<0 for 0<t<1. PCHIP on the same data has a flat middle segment at zero and remains between the nonnegative cell endpoints.

Facts & Assumptions

Given: The four tabulated nodes and values, the displayed piecewise cubic S, and exact real arithmetic.

[F1]

Natural cubic splines: a natural cubic spline is C2, piecewise cubic, and has second derivative zero at its first and last knots.

[F2]

PCHIP slope selection: PCHIP selects zero interior slope when adjacent secants have nonpositive product and uses the Hermite pieces from the resulting nodal slopes.

[F3]

PCHIP is C1, monotone on each data segment, and has no interval overshoot: every PCHIP cell is monotone between its endpoint values; a flat cell is constant.

[F4]

Sum, product, quotient, and chain rules from difference quotients: the power rule (xm)′=mxm−1 holds for every integer m≥1.

Verification

1.1givenF1F4algebra

Each displayed piece has endpoint values S0(0)=1, S0(1)=0, S1(0)=S1(1)=0, S2(0)=0, and S2(1)=1, so the pieces interpolate the given table. By [F4], their first derivatives are S0′=−6/5+3t2/5, S1′=−3/5+6t/5, and S2′=3/5+6t/5−3t2/5; the derivative values match at both shared knots. Their second derivatives are S0′′=6t/5, S1′′=6/5, and S2′′=6/5−6t/5; these match at shared knots, and S0′′(0)=S2′′(1)=0. By [F1], this is a natural cubic spline.

2.1givenstep 1.1algebra

For 0<t<1, S1(t)=−3t(1−t)/5<0, although every tabulated value is nonnegative. Thus the natural cubic spline undershoots the data range on the middle cell.

3.1F2F3givenalgebra∎

The secants are d0=−1, d1=0, and d2=1. By [F2], the interior slopes at nodes 1 and 2 are both zero because each neighboring pair includes a zero secant; the Hermite piece joining the two zero values with zero slopes is constant zero. By [F3], the first and last PCHIP pieces remain between 1 and 0, and between 0 and 1, respectively. Hence PCHIP is nonnegative throughout the interval and does not reproduce the natural spline's undershoot.

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PCHIP preserves a flat part of monotone data

Example

For nodes 0,1,2,3 and values 0,1,1,2, the PCHIP data are monotone with one flat interval. The algorithm selects slopes (3/2,0,0,3/2), and the interpolant is constant on [1,2] while remaining monotone on the adjoining cells.

Facts & Assumptions

Given: The nodes x=(0,1,2,3), values y=(0,1,1,2), and exact real arithmetic.

[F1]

PCHIP slope selection: the secant slopes determine the zero, harmonic-mean, and one-sided endpoint rules, and the output pieces are cubic Hermite pieces.

[F2]

PCHIP is C1, monotone on each data segment, and has no interval overshoot: each segment is monotone between its data endpoints, and a zero-secant segment is constant.

Verification

1.1givenF1algebra

The secants are d0=1, d1=0, and d2=1. The interior rule in [F1] gives m1=m2=0. The endpoint rule gives m^0=((3)(1)−0)/2=3/2 and, by reflection, m^3=3/2; neither clip nor cap changes these values.

2.1F1step 1.1algebra

On the middle cell both endpoint values are 1 and both slopes are zero, so the Hermite formula is the constant polynomial 1. On the first cell it is −t3/2+3t/2, and on the last cell it is 1+3t2/2−t3/2, for normalized local coordinate t∈[0,1].

3.1F2step 2.1given∎

The shape theorem [F2] makes the first and last pieces monotone from 0 to 1 and from 1 to 2 and makes the middle piece constant. Thus the interpolant is globally nondecreasing, has no overshoot, and retains the flat interval exactly.

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PCHIP loses third-order value accuracy next to a smooth extremum

Example

Fix f(x)=x2 on [−1,1]. For each integer n≥2, use the uniform grid xj=−1+jh, j=0,…,2n, with h=1/n. The function is smooth and has a strict extremum at zero. On the cell [−h,0], PCHIP's local maximum error is at least 2h2/27, so no uniform Ch3 value-error bound on this fixed interval can hold across the extremum.

Facts & Assumptions

Given: An integer n≥2, h=1/n, f(x)=x2 on [−1,1], the uniform nodes xj=−1+jh for j=0,…,2n, and exact real arithmetic.

[F1]

PCHIP slope selection: opposite-sign neighboring secants give zero interior slope; same-sign secants use the weighted harmonic mean.

[F2]

Piecewise cubic Hermite interpolant: the segment is formed from endpoint values and slopes using H00,H01,H10,H11.

[F3]

PCHIP has third-order value accuracy on uniform nonstationary grids: the third-order value bound assumes a uniform grid and a derivative bounded away from zero on the whole interval.

[F4]

Sum, product, quotient, and chain rules from difference quotients: the power rule (xm)′=mxm−1 holds for every integer m≥1.

[F5]

Heine-Borel by bisection: every closed bounded interval [a,b] is compact: every closed interval [u,v] with u≤v is compact.

[F6]

Extreme value theorem: a continuous real function on a nonempty compact subset of R attains a greatest and a least value: a continuous real function on a nonempty compact subset of R attains its maximum.

Verification

1.1givenF1algebra

The secants on [−2h,−h], [−h,0], [0,h], and [h,2h] are −3h, −h, h, and 3h. At x=−h, the equal-width weights are 3h,3h, so [F1] gives m(−h)=6h/(3h/(−3h)+3h/(−h))=−3h/2. At x=0 the adjacent secants have opposite signs, so [F1] gives m(0)=0.

2.1F2step 1.1algebra

With t=(x+h)/h on [−h,0], [F2] gives Ph(x)/h2=H00(t)−32H10(t)=1−32t+12t3, whereas f(x)/h2=(1−t)2. Therefore (Ph(x)−f(x))/h2=12t(1−t)2.

3.1F3F4F5F6step 2.1givenalgebra∎

On this cell, step 2.1 gives the error E(x)=∣Ph(x)−f(x)∣=h22t(1−t)2, since 0≤t≤1. This expression is a polynomial in x through t=(x+h)/h, so [F4] makes it differentiable, hence continuous, on the cell. As h>0, the interval [−h,0] is nonempty and compact by [F5]; [F6] therefore gives an attained maximum of E there. Since t=1/3 corresponds to a point of the cell and step 2.1 gives E=2h2/27 at that point, the maximum is at least 2h2/27. Any uniform bound ∣Ph−f∣≤Ch3 on these grids with C independent of n would imply 2/27≤Ch=C/n for all sufficiently large n, which is impossible as n→∞. The hypothesis ∣f′∣≥c>0 in [F3] also fails because [F4] gives f′(0)=0.