From PDF catalog to polynomial fit in 60 seconds — the PolyFitter tool
By DigiEntropy Engineering · 2025-12-25 · 6 min read
Got a compressor datasheet that publishes a capacity table but no polynomial coefficients? Paste the numbers into PolyFitter and get a clean AHRI 540 / EN 12900 fit in seconds — with residual, 3D surface, and contour plots to validate the fit visually.
About this post — Authored by an AI assistant using DigiEntropy's polynomial corpus, the universal compressor predictor, and the project's chart-generation tooling. Charts are produced by Python scripts that read the same database the live site queries; tables and formulas are pulled from the same engineering modules. Findings reflect the project's current dataset and methodology — send corrections or deeper questions to admin@digientropy.com. You've got a compressor datasheet. It publishes a capacity table — Qe and P at, say, 20 operating points spanning the envelope. What you really need is a polynomial fit of those points so you can evaluate the compressor at any condition, plug it into a simulation model, or feed it to a building-energy tool. Doing this by hand is tedious. Spreadsheet templates exist, but they're brand-specific and break the moment the standard differs. The DigiEntropy PolyFitter tool does it in 60 seconds — paste the table, pick the polynomial form, read the fit. What it does PolyFitter takes a tabular performance dataset (SST, SDT, Qe, P at each row) and produces: - AHRI 540 polynomial (10-coefficient bivariate, °F + BTU/h) — the North American standard. - EN 12900 polynomial (10-coefficient bivariate, °C + W) — the European standard, identical mathematical form to AHRI 540 just in different units. - 15-coefficient 4th-order bivariate — used by Hanbell DataNEW and a handful of other modern brands for tighter fits. For each fit, the tool shows: - The coefficients (C0-C9 or C0-C14) ready to copy. - The R² and max residual — so you know whether the fit is tight enough to use. - A scatter compare plot — measured vs predicted, one point per row. Ideal fit lies on the y = x line. - A residual plot — error per row, useful for spotting systematic bias (e.g. the fit underestimates at the LP corner). - A 3D surface plot — the polynomial visualised as a function of SST and SDT, so you can see whether it's smooth or has unphysical kinks. - A contour plot — same data as the 3D plot, easier to read for picking off values at specific operating points. The 60-second workflow 1. Go to PolyFitter. 2. Paste your performance table. Format: one row per operating point, columns SST, SDT, Qe, P. Units can be °C/°F and kW/BTU/h — the tool detects from the magnitude. 3. Pick the polynomial form (AHRI 540 / EN 12900 / 15-coeff). 4. Click Fit. 5. Read R² and residuals. If R² 0.999 and max residual < 1%, you have a clean fit — copy the coefficients. If R² is poor or residuals are systematic, the tool flags it. Common causes: - Mixed datasets — if the table…