How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
PCHIP slope selection
Definition
Inputs: An integer , strictly increasing real nodes , and real values . All operations here are over the real numbers.
Output: Slopes and the piecewise cubic Hermite interpolant determined by these nodes, values, and slopes under Piecewise cubic Hermite interpolant.
Put and for . Write for the sign of a real number.
- If , set .
- If , for each interior node , set when . When , put , , and
- For , at the left endpoint compute Set if . Otherwise set if and ; in all remaining cases set .
- For , at the right endpoint compute Apply the preceding clip and cap rule with replaced by and replaced by .
For , the algorithm returns the Hermite pieces from the stated values and selected slopes. The two-node branch is the line through the two input points.
Depends on
Used by
- A natural cubic spline undershoots a nonnegative table Example
- PCHIP loses third-order value accuracy next to a smooth extremum Example
- PCHIP preserves a flat part of monotone data Example
- PCHIP slope selection has no zero denominator Lemma
- PCHIP slopes are second-order accurate on uniform nonstationary grids Lemma
- PCHIP endpoint slopes lie in the Hermite monotonicity square Theorem
- PCHIP has third-order value accuracy on uniform nonstationary grids Theorem
- PCHIP is C1, monotone on each data segment, and has no interval overshoot Theorem
Dependency tree · two levels
2 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- F. N. Fritsch and J. Butland, A Method for Constructing Local Monotone Piecewise Cubic Interpolants, SIAM Journal on Scientific and Statistical Computing 5 (1984), pp. 300–304 (standard reference, not scraped)
- SciPy v1.18.0, PchipInterpolator documentation, Notes (standard reference, not scraped)