Interpolation

Linear interpolation, piecewise table interpolation, extrapolation, nearest neighbor, & batch processing for X–Y data.

Linear (2 Points): estimate Y at a target X using two known points.
Linear (2 Points) Result
Estimated Y
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Slope (ΔY/ΔX)
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Table (Piecewise): paste or enter multiple X–Y points. The tool finds the surrounding interval and interpolates linearly.
Points do not need to be pre-sorted. Duplicate X values will be rejected.
Table (Piecewise) Result
Estimated Y
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Used Points
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# X Y
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Extrapolation: estimate beyond known data. Choose method: use first two points, last two points, or a selected interval.
Extrapolation is linear and depends on the selected method/interval.
Used only if Method = manual.
Used only if Method = manual.
Extrapolation Result
Estimated Y
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Used Points
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Nearest Neighbor: returns the Y value from the closest X in the table (no interpolation).
Nearest Neighbor Result
Nearest X
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Returned Y
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Batch: run multiple target X values against the same data set. One target per line.
Batch Results
# Target X Result Y Notes
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Interpolation – Overview

The Nautical Solver Interpolation tool is a general-purpose numerical utility designed to estimate unknown values between or beyond known data points. It supports multiple interpolation and extrapolation methods commonly used in engineering, scientific analysis, and technical calculations.

The calculator operates on paired X–Y data and provides transparent, deterministic results based on standard mathematical definitions. All methods are explicitly selected by the user, with no hidden assumptions.

Supported Methods
  • Linear interpolation using two known points
  • Piecewise linear interpolation from tabulated data
  • Linear extrapolation beyond the known data range
  • Nearest neighbor estimation without interpolation
  • Batch processing of multiple target values
Typical Use Cases

Interpolation is frequently used when exact values are unavailable but surrounding data is known. Common applications include engineering calculations, performance estimation, calibration tables, regression pre-processing, and numerical analysis where continuous behavior is assumed between discrete points.

Interpolation vs Extrapolation

Interpolation estimates values within the range of known data points, while extrapolation estimates values outside that range. Extrapolated results depend strongly on the chosen method and should be treated with additional caution in engineering and regulatory contexts.

Notes & Limitations
  • All methods are based on linear relationships between selected points
  • Duplicate X values are not permitted
  • Input data does not need to be pre-sorted
  • Extrapolated values may carry significant uncertainty
  • Results should be independently verified for critical applications
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