Spreadsheet-Style Data Editor
Edit data in-table, add derived columns with formulas, and assign roles for x/y data and uncertainties.
Scientific plotting, made iterative
Build publication-ready plots in your browser and keep them editable.
pont.ink combines data editing, subplot-aware figure layout, lmfit-based fitting, visual annotation editing, and export into one workflow. You can revisit and continue work later from saved sessions and metadata-enabled exports.
Interactive Fit Workflow
Select fit regions directly on the plot, tune parameters and bounds, and bind guide lines to fitted parameters.
Editable Figure Layout
Work with multiple subplots, draggable figure and axis labels, legends, and annotation overlays directly in the canvas.
Reproducible Exports
Export PNG, SVG, or PDF plus generated Matplotlib code. Session metadata can be embedded for later reload.
How pont.ink works
-
Load data: import
.csv,.tsv,.txt,.spe,.itx,.xlsx,.xls,.json,.npy,.npz,.mat,.h5, or.hdf5, or type directly into the editor. - Shape the figure: create subplots and adjust titles, axis labels, legends, overlays, and annotations.
- Fit models: choose a region, configure parameters, inspect fit quality, and drive reference lines from fit values.
- Export and continue: save outputs and reopen editable sessions whenever needed.