orange-spectra — spectroscopy widgets for Orange Data Mining

English ｜ 中文

Eleven spectroscopy widgets for Orange Data Mining. They share their algorithms and the .speclib library format with SpectraView, a desktop spectroscopy viewer. Fetch spectra from public databases by URL, compare and search them, build reusable reference libraries, decompose mixtures, and draw aquaphotomics aquagrams — all inside Orange's visual workflow canvas.

The output Table follows the Orange-Spectroscopy convention (column names = wavelength/wavenumber, one spectrum per row), so it plugs straight into the Spectra viewer widget or into PCA / PLS chemometrics pipelines.

Install

⚠️ Know which Orange you run first — the desktop App and a pip‑installed Orange are separate Python environments. Installing into the wrong one means the widgets won't appear.

Works on Windows, macOS (Apple Silicon & Intel), and Linux — it's pure Python (numpy / scipy / matplotlib / Orange3).

A. Desktop App (the standalone program from orangedatamining.com): Options ▸ Add-ons… ▸ Add more…, type orange-spectra, tick it, OK, and restart. On macOS, download the Mac .dmg from https://orangedatamining.com/download/.

B. pip Orange (started with python -m Orange.canvas):

pip install orange-spectra
python -m Orange.canvas

On macOS use python3 / pip3 (e.g. install Python via Homebrew: brew install python).

If Orange fails to start with ImportError: PyQt5 … not available, it's missing a Qt binding — install one:

pip install PyQt5 PyQtWebEngine

After (re)starting Orange, a Spectra category with the eleven widgets appears in the toolbox.

Quick start

1. Drop in Import Spectrum URL, enter 4119 (IRUG's PB15 phthalocyanine blue Raman spectrum) → Fetch.
2. Fetch a few reference spectra → feed them to the Spectral Library Spectra input → Add input spectra to library → Save… as a .speclib. (or skip fetching: pick the built-in UCL Raman Library of Pigments in the Library box and press Add built-in — 55 reference pigments in one click; the data is downloaded from UCL on first use and cached.)
3. Feed an unknown spectrum to the library's Query input → the Hits output is the ranked match table.
4. Feed a mixed spectrum to Mixture Analysis Mixture and the references (or the library's Library output) to References → get component proportions and R².

Every widget has an ℹ How to use box and a 📖 Open tutorial button in its top‑left corner, and F1 (or the ? button) opens its online help page.

Built-in UCL pigment library

The Spectral Library widget offers the UCL Raman Library of Pigments (55 natural and synthetic pigments in use before ~1850 AD):

I. M. Bell, R. J. H. Clark and P. J. Gibbs, "Raman spectroscopic library of natural and synthetic pigments (pre- ≈ 1850 AD)", Spectrochim. Acta A 53 (1997) 2159–2179. doi:10.1016/S1386-1425(97)00140-6

Please cite the paper when you use these spectra in published work.

The data is not redistributed with this package. On first use the widget downloads the spectra from UCL's own website (falling back to the Internet Archive's copy if UCL's server is unreachable from your region) and caches them at ~/.orange-spectra/ucl_pigments_raman.speclib; after that it works offline. Set the ORANGE_SPECTRA_CACHE environment variable to move the cache, or ORANGE_SPECTRA_UCL_BASE to point at a mirror. If you already have the .spc files, build the cache offline with orangespectra.core.build_ucl_library_from_folder(folder).

Notes on the data: intensities are raw counts (no baseline or instrument response correction — baseline-correct your query the way you normally would before searching), measurement ranges differ per pigment, and UCL notes the downloadable band positions are uncorrected and may differ slightly from the values tabulated on its site.

Supported URL formats

• IRUG detail pages (jqPlot‑embedded data)
• SOPRANO pages (Dygraph‑embedded data)
• JCAMP-DX (AFFN plain‑number format)
• Two‑column CSV/TSV
• Spectra embedded in Plotly / Highcharts / Chart.js interactive charts (generic x/y fallback)

Compressed JCAMP (SQZ/DIF) is not parsed here — open it in SpectraView and export first.

Documentation

Full tutorial with real‑data demos: https://tai-shengyeh.github.io/spectraview/orange.html (English).

Notes

• You only need to install once; updating requires a reinstall (pip install --upgrade orange-spectra) and an Orange restart.
• Source, issues, and the desktop SpectraView app: https://github.com/Tai-ShengYeh/spectraview.

License

MIT.

中文說明

orange-spectra — Orange Data Mining 光譜 widgets

English ｜ 中文

十一個給 Orange Data Mining 的光譜學 widgets， 與桌面版光譜檢視程式 SpectraView 共用演算法與 .speclib 光譜庫格式。可用網址從公開資料庫抓光譜、比對與搜尋、建立可重複使用的 參考光譜庫、拆解混合光譜，並繪製 aquaphotomics 雷達圖——全部在 Orange 的視覺化 工作流程畫布中完成。

輸出的 Table 採 Orange-Spectroscopy 慣例（欄名＝波長/波數、每列一條光譜），可直接接其 Spectra 檢視 widget 或 PCA / PLS 等化學計量學流程。

安裝

⚠️ 先確認你的 Orange 是哪一種——桌面版 App 與 pip 版是不同的 Python 環境，裝錯不會出現 widgets。

可在 Windows、macOS（Apple 晶片與 Intel）、Linux 執行——純 Python （numpy / scipy / matplotlib / Orange3）。

A. 桌面版 App（orangedatamining.com 下載的獨立程式）： Options ▸ Add-ons… ▸ Add more… 輸入 orange-spectra → 打勾 → OK → 重啟。 macOS 到 https://orangedatamining.com/download/ 下載 Mac 版 .dmg。

B. pip 版 Orange（python -m Orange.canvas 啟動）：

pip install orange-spectra
python -m Orange.canvas

macOS 請用 python3 / pip3（可用 Homebrew 裝 Python： brew install python）。

若 Orange 開不了並出現 ImportError: PyQt5 … not available，是少了 Qt 綁定， 補裝：

pip install PyQt5 PyQtWebEngine

重新啟動 Orange，工具箱會出現 Spectra 分類（11 個 widgets）。

快速上手

1. 拖出 Import Spectrum URL，輸入 4119（IRUG 的 PB15 酞菁藍 Raman 譜） → Fetch。
2. 多抓幾條參考譜 → 接 Spectral Library 的 Spectra 輸入 → Add input spectra to library → Save… 存成 .speclib。 （也可以不用自己抓：在 Library 區選內建的 UCL 顏料拉曼庫按 Add built-in，一鍵載入 55 種參考顏料；資料第一次使用時自 UCL 官網下載並快取。）
3. 未知譜接 Library 的 Query 輸入 → Hits 輸出就是排名表。
4. 混合譜接 Mixture Analysis 的 Mixture、參考譜（或 Library 的 Library 輸出）接 References → 得成分比例與 R²。

每個 widget 左上角都有「ℹ 說明 How to use」盒子與「📖 開啟線上教學」按鈕；選取 widget 按 F1（或 ? 鈕）會開啟線上說明頁。

內建 UCL 顏料拉曼庫

Spectral Library widget 內建 UCL 顏料拉曼庫（約 1850 年以前使用的 55 種天然與合成顏料）：

I. M. Bell, R. J. H. Clark and P. J. Gibbs, "Raman spectroscopic library of natural and synthetic pigments (pre- ≈ 1850 AD)", Spectrochim. Acta A 53 (1997) 2159–2179. doi:10.1016/S1386-1425(97)00140-6

發表時使用到這些光譜請引用上面這篇論文。

**本套件不隨附這批資料。**第一次使用時 widget 會自 UCL 官網下載 （若你所在地區連不上 UCL 伺服器，會自動改抓 Internet Archive 的存檔副本）， 快取在 ~/.orange-spectra/ucl_pigments_raman.speclib，之後完全離線可用。 環境變數 ORANGE_SPECTRA_CACHE 可改快取位置、ORANGE_SPECTRA_UCL_BASE 可指定鏡像；已有 .spc 檔者可用 orangespectra.core.build_ucl_library_from_folder(資料夾) 離線建庫。

資料注意事項：強度為原始 counts（未做基線與儀器響應校正——比對前請照 你平常的流程先對未知譜做基線校正）；各顏料量測範圍不同；UCL 官網註明 可下載檔案的譜帶位置未經校正，可能與其網頁表格數值略有出入。

支援的網址格式

• IRUG 詳情頁（jqPlot 內嵌資料）
• SOPRANO 頁（Dygraph 內嵌資料）
• JCAMP-DX（AFFN 純數字格式）
• 兩欄 CSV/TSV
• Plotly / Highcharts / Chart.js 互動圖內嵌的 x/y 資料（通用後備解析）

壓縮的 JCAMP（SQZ/DIF）這裡不解析——請先用 SpectraView 開啟後匯出。

教學文件

含真實數據 Demo 的完整教學： https://tai-shengyeh.github.io/spectraview/orange.html （English）。

注意

• 安裝一次即可，更新才需重裝（pip install --upgrade orange-spectra） ＋重開 Orange。
• 原始碼、issues、桌面版 SpectraView： https://github.com/Tai-ShengYeh/spectraview。

授權

MIT。