JCAMP Viewer

A JCAMP file viewer designed for researchers and students to load spectra, visualize peaks, and validate metadata without coding.

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About This Tool

JCAMP Viewer loads JCAMP-DX format files and exposes parsed spectral data in a structured model. It supports raw data arrays, units, and metadata blocks such as TITLE, DATA CLASS, and variable information. The tool focuses on domain logic: reading textual and binary blocks, handling data arrays, and preparing data for analysis and export.
Conceptually, the system validates data against JCAMP specifications, resamples or normalizes spectra when requested, and exposes findings such as peak coordinates, spectral range, and metadata completeness. It does not perform instrument control; instead it provides a robust offline view that researchers can trust to produce reproducible figures and offline analyses.
Benefit: researchers, educators, and QA engineers who work with infrared, Raman, or NMR spectra can quickly load datasets, compare spectra across samples, and share structured results. Unique value: strict conformance parsing, metadata-rich outputs, and lightweight export in CSV/JSON. Core features: file parsing, unit normalization, multiple JCAMP variants, simple peak detection, and export options.

How to Use

  1. Upload JCAMP file or paste data.
  2. Select parsing options (version, metadata scope).
  3. Run parsing to extract spectra data and metadata.
  4. Review parsed peaks, units, and completeness.
  5. Export results as CSV or JSON for further analysis.
How to use jcamp viewer

Frequently Asked Questions

Find Quick Answers

What datasets can JCAMP Viewer handle?
It handles JCAMP-DX data conforming to common spectroscopic domains (IR, Raman, NMR) and can parse both ASCII and binary-encoded YDATA blocks; it flags unsupported blocks and retains valid data.
Can I export parsed data for further analysis?
Yes, exports include CSV with peak lists, JSON metadata, and a structured spectrum object; exported files preserve units and metadata to support reproducibility.
Does it visualize data offline?
The tool provides a local, offline parsing engine that does not require external services; visualization is based on parsed data structures and can be used without internet access.

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