Python Origin Plotting

Python Origin Plotting

Use this skill to turn tabular data and plotting requirements into reproducible OriginPro projects driven by Python originpro.

Prerequisites

• Windows with OriginPro installed and licensed.
• Python that can import originpro and pandas.
• Input data supplied by the user as Excel or CSV.
• No API keys or secret environment variables are required.

Security Notes

• Inspect scripts/originpro_plot_template.py before running it in a new environment.
• Do not commit or publish user data files, generated figures, audit CSV files, or .opju projects.
• Keep script outputs inside the user-selected project/output folder and an explicit temp folder such as E:/origin_tmp.
• Do not download remote code or send user data to network services as part of this skill.

First Pass

1. Locate existing artifacts before writing code:
   • *origin*.py, *.opju, *.opj, plots_origin/, exported Origin_*.png
   • PowerShell: Get-ChildItem -Recurse -File -Include *origin*.py,*.opju,*.opj,*.png
2. Identify the input file, sheet name, required columns, desired chart types, output folder, and whether Origin should be visible.
3. Reuse any existing project script style first, especially workbook setup, LabTalk styling, export naming, and temp-path handling.
4. For a new project, copy and adapt scripts/originpro_plot_template.py.

Standard Workflow

1. Load and clean data with pandas.

   • Read Excel or CSV.
   • Drop rows missing required plotting columns.
   • Sort data in the expected visual order.
   • Create short axis labels while preserving long labels in separate worksheet columns.
   • Export an audit CSV such as origin_input_data_sorted.csv with encoding="utf-8-sig".

2. Start a clean Origin project.

   • import originpro as op
   • op.set_show(True) when the user should see Origin.
   • op.new() before creating new workbooks and graph pages.
   • Create a workbook with op.new_book(...), write the DataFrame with wks.from_df(df), then set column designations and labels.

3. Create graphs in Origin.

   • Use Origin graph pages and layers rather than matplotlib when the user asks for Origin output.
   • Add plots with gl.add_plot(wks, coly=..., colx=..., type=...).
   • For dual-axis charts, add a second layer and explicitly manage right-Y axis titles and limits.

4. Style through Origin APIs and LabTalk.

   • Set axis titles with gl.axis("x").title and gl.axis("y").title.
   • Use gl.lt_exec(...) or gp.lt_exec(...) for labels, legends, grids, tick rotation, and template-specific styling.
   • Call gl.rescale() after adding plots.
   • Avoid graph titles when they overlap exports; prefer page long names and filenames.

5. Export figures and save the Origin project.

   • Export PNG/TIFF with gp.save_fig(...).
   • Save .opju with op.save(...).
   • If output paths contain Chinese characters or Origin refuses direct export, save first to an ASCII temp directory, then copy to the final path.
   • Use timestamped or versioned .opju names if the final project file may be locked.

6. Close Origin cleanly.

   • Put save/export logic in try.
   • Put op.exit() in finally.
   • Do not leave hidden Origin COM sessions running.

References

Read these only when needed:

• references/originpro-workflow.md: detailed implementation patterns, chart recipes, and script structure.
• references/troubleshooting.md: common originpro, COM, Chinese-path, export, and locked-file failures.

Validation Checklist

• The script runs without Python exceptions on the target machine.
• Output folder contains an audit CSV, exported figure files, and a saved .opju.
• Figure files are non-empty and have recent modification times.
• The .opju opens in Origin and contains the worksheet plus graph pages.
• If Origin or originpro is not installed, say so clearly and do not fake Origin output with matplotlib unless the user asks for a fallback.