Plot Templates in SciDAVis: Consistent Figures, Faster

Every journal has its own figure style: specific fonts, axis label sizes, legend placement, line widths. Recreating those settings by hand for each of twenty figures — and again when a reviewer asks for changes — is slow and error-prone. SciDAVis templates solve exactly this: design the look once, save it as a template file, and spawn every new figure from it. It takes five minutes to set up and pays back on the very first revision round.

What a template actually saves

With the plot you want to clone active, choose File → Save as Template. SciDAVis writes a template file capturing the graphical recipe of the plot. The details, straight from the official Handbook:

Templates are not only for 2D plots. The File menu template commands work for every object type, each with its own extension:

• 2D plots → .qpt files
• 3D plots → .qst files
• Tables → .qtt files (number of rows and columns)
• Matrices → .qmt files (number of rows and columns)

Saving a template

1. Build one reference figure and style it exactly the way your journal or lab wants it: fonts, label sizes, legend position, axis title wording style, grid on/off, background color, figure dimensions.
2. Make that plot window the active window.
3. Choose File → Save as Template and save the .qpt file somewhere the whole team can reach — a shared folder or the group’s version-control repository. Give it a descriptive name like journal-2col-2026.qpt rather than template1.qpt.

Applying a template to new data

1. Choose File → Open Template (also on the File toolbar) and pick your .qpt file. SciDAVis creates a new, empty plot carrying all the graphical parameters of the reference figure — geometry, fonts, colors, labels.
2. Add your data curves with the Add/Remove Curve command of the plot window.
3. Set the curve styles (colors, symbols, line widths) to match your house style, and check that the axis auto-scaling looks right for this dataset.
4. Export the figure (File → Export Graph) at the resolution your target venue requires.

That is the whole loop: Open Template → add curves → style curves → export. When a reviewer demands “all figures in 9pt Arial with the legend inside the panel,” you update the one .qpt file and regenerate — no manual re-styling of twenty figures.

The team workflow: one style, many authors

Templates shine in groups where several people produce figures for the same paper or thesis:

• Appoint a style owner. One person designs the reference figure against the journal’s author guidelines and saves the master .qpt.
• Version it. Keep the template in the group’s shared repository with a changelog (“v3: legend moved inside panel per reviewer”). Everyone regenerates from the current version.
• Pair with a style sheet. Since curve styles are not saved in the template, keep a one-page note with the group: “curves: 1.5pt, colors #1f77b4 / #ff7f0e, symbols circle/square…”. Authors apply it after adding curves.
• Separate templates per context. A two-column journal figure, a slide figure, and a thesis figure need different sizes and font scales — maintain one .qpt per context instead of stretching one.

Templates vs. Preferences: pick the right tool

SciDAVis offers a second route to consistent styling: Edit → Preferences has a 2D-plot section where you can change the default look of every new plot (general options, default curve style, ticks, fonts, printing). Use this rule of thumb:

• Preferences = your personal global default. Good when one style fits everything you do.
• Templates = named, shareable styles for specific families of plots. Good for journals, theses, and teams — and you can keep several side by side.

The two compose nicely: set sane global defaults in Preferences, then use templates for the venues that demand something special.

Efficiency gains for journal submission

• First submission: figures come out uniform from the start — consistent fonts and label sizes across all panels, which editors and reviewers notice.
• Revisions: a global style change becomes “edit template, regenerate, re-export” instead of opening every figure.
• Co-author sanity: no more figures where panel (a) uses Times and panel (d) uses Helvetica because two people plotted them.
• Reproducibility: the .qpt file documents the exact figure recipe — archive it with the paper’s data.

Limitations to know before you commit

• Curve drawing styles are not stored — budget a minute per figure to re-apply them.
• Axis scales are not stored — each new plot auto-scales; check log-vs-linear choices manually.
• A template is tied to the plot family it was designed for — a single-panel template will not magically lay out a four-panel figure (use multi-panel plots for that).
• Templates capture a moment in time: if the journal changes its guidelines, update and re-save the template rather than patching figures individually.

FAQ

Can I share a template with a collaborator on another computer?

Yes — a template is just a file (.qpt for plots). Send it by email or share it in your group’s repository; the collaborator opens it with File → Open Template. Fonts referenced by the template should exist on their machine for pixel-identical results.

Why didn’t my curve colors come back when I opened the template?

By design, templates do not store curve drawing styles — only geometry, fonts, colors of labels/legends, and text. Re-apply your curve styles after adding data.

Do templates work for 3D plots and tables too?

Yes. Save 3D plots as .qst (window and layer geometries, fonts, colors) and tables/matrices as .qtt/.qmt (row/column counts). The same File-menu commands apply.

Should I use a template or just change the Preferences?

Use Preferences for your personal everyday default; use templates when a specific venue or project demands its own look, when several people must produce identical figures, or when you need multiple styles in parallel.

Next steps

• Multi-Panel Plots in SciDAVis — combine templated panels into publication figures
• Exporting Publication-Quality Figures — resolutions, formats and vector output
• Curve Fitting in SciDAVis — fit first, then template the result plot
• Python Scripting in SciDAVis — generate whole figure sets from templates programmatically
• All SciDAVis Tutorials — back to the tutorial hub