v3.2.0

EaglePlot is now also a desktop app for Windows, macOS and Linux, with Python and every
package included: download it from the release page, install it without admin rights, and
use it offline. The web app starts faster, can be installed from Chrome or Edge, and works
offline too. EaglePlot has a new logo in NCCU colors and a new loading screen.

Added

• A desktop app for Windows, macOS and Linux (packaging/desktop/): the same app
  in its own window, with Python and every package included, so it needs no Python
  install and no network. Installers are built for every release and need no admin
  rights. Settings are kept between sessions. Links open in your web browser. They are
  not code-signed yet: the first launch shows a warning (see the
  Download page).
  Data Upload → Batch Import reads folders on your computer: type the folder's path as
  usual (C:\Users\you\data, ~/data).
• A Download page on the website (docs/download.md): the web app, desktop app and
  Python package side by side, first-launch steps, the code signing policy and the
  privacy policy (EaglePlot collects no data).

Changed

• The EaglePlot logo is now in NCCU maroon and gray (it was blue): the same disc, bars
  and line, on the Home page, in the sidebar, as the browser-tab icon and in logo.ico.
  eagleplot/assets/logo.svg is the master.
• A new loading screen for the web app. The logo's pieces (the rings, the axes, the
  bars, the line and the points) fly in from all sides of the screen and lock together,
  then a highlight sweeps across while Python loads. Below it, four real steps
  (downloading Python, installing the science libraries, starting EaglePlot, opening your
  workspace) replace the endlessly sliding bar. The note about the 45 MB download appears
  only on a first visit. If loading fails, the screen says why and offers Reload
  instead of sliding forever. With reduced motion turned on in the system settings, the
  logo appears complete and nothing moves.
• The web app starts faster: ready in about 7 s instead of 11 s (measured on a fast
  local connection), and the first plot from Home ("Plot this example") appears about 4 s
  sooner. scipy is loaded in the background after the app appears, and pandas and the
  plotting libraries are imported while you read the Home page. A page that needs scipy
  says so for a moment if you open it within the first seconds.
• Install the web app like a program. Chrome and Edge offer Install EaglePlot:
  it then opens in its own window from a desktop icon, with no admin rights, and after one
  online visit it also works offline. Later visits load from the computer instead of the
  network.
• Importing eagleplot.plotting no longer imports seaborn, plotly or scipy (they load when
  a plot type needs them), and importing eagleplot.utils no longer imports pandas. This
  also makes the installed GUI start a little faster.

v3.1.0

EaglePlot now also runs in your browser, with nothing to install:
https://the-schultz-lab.github.io/eagleplot/app/. This release also makes the GUI much
faster, gives it a simpler first screen, and fixes JCAMP-DX loading, which was broken in
3.0.0 for anyone with the current jcamp package.

Added

• EaglePlot runs in your browser:
  the-schultz-lab.github.io/eagleplot/app/.
  Nothing to install and nothing uploaded: your data stays on your computer, which makes it
  usable on laptops where you can't install software. It takes 15–30 seconds to start.
  Features that can't work in a browser are turned off with an explanation instead of
  failing: loading a whole folder, downloading from NIST (the page links to NIST instead),
  and changing the theme. Settings, presets and workflows are kept in the browser. The
  documentation site and README link to it. Every change to the app is tested in a real
  browser before it is published (packaging/web/, scripts/web/smoke.js).
• EAGLEPLOT_CONFIG_DIR sets the folder that holds config.json (saved defaults,
  presets and workflows). Unset, it stays where it was.

Changed

• A "Get started" Home page. With no data loaded, Home offers three example datasets,
  each a single click away from a plot in Quick Plot, plus buttons to upload a file or
  browse all examples, instead of "Datasets 0 · Plots 0 · Analyses 0".
• Quick Plot shows the plot on the first screen. Dataset, library and plot type sit in
  one row with a Style presets button, and the dataset size and plot description share
  one line. On a 1366×768 laptop the plot used to start below the bottom of the screen.
  All pages have less empty space at the top.
• Clearer menu names: Basic is now Quick Plot, Multiplot Dashboard, Single
  Analysis Tools and Batch Batch Analysis. Page addresses are unchanged, so
  bookmarks still work.
• The sidebar's About box starts closed, and on phones the sidebar starts closed.
• Quick Plot is much faster and easier to use.
  • Settings sit on the left and the plot on the right, so you see each change as you
    make it. The plot stays in view while the settings scroll.
  • Live preview: the plot redraws as you change settings (toggle it off if you prefer).
    Generate Plot still saves the plot to the plot history.
  • Changing a setting now updates only the settings and plot area, not the whole page.
    In a test with a line plot, the time from a change to seeing it on the plot fell from
    about 1.3 s to about 0.6 s.
  • Downloads are created only when you ask for one. Before, every click re-created the
    plot as PNG at 150, 300 and 600 dpi, SVG and PDF, whether or not you were downloading.
    The export panel now has one format menu and one Download button.
  • A marker appears as soon as you click a point on an interactive plot.
• Export Results is much faster. It used to re-create every saved plot as PNG (150 and
  300 dpi), SVG and PDF, and re-save the dataset as CSV and JSON, on every click: 1.2 s per
  click with three saved plots, now 0.03 s. Files are now created only when you download them.
• PDF report: on current Streamlit it is one click, and the report is built when you
  press Download PDF Report. On older Streamlit the download button no longer
  disappears after the next click.
• Batch Analysis: results stay on screen after you run a tool. Before, they disappeared
  at the next click, including when you clicked Download CSV.
• Molecular Viz: the HTML and frequency-table exports are one click (Streamlit 1.52+),
  instead of "Export", then "Download", with the button disappearing afterwards.
• Analysis Tools is faster. Each tool now updates on its own, so changing a setting or
  running a tool no longer reloads the whole page. A setting change takes about 0.23 s
  instead of about 0.38 s. A result from one tool stays on screen while you use another, and
  downloading the peak report no longer clears it.
• Multi-Plot Dashboard:
  • Each panel has its own settings, shown above its plot. Editing a panel redraws only that
    panel, and the dashboard updates live after Generate Dashboard: a title edit shows up
    in about 0.4 s, where before you had to press Generate again.
  • The dashboard stays on screen when you change something or download it.
  • Turning shared axes off restores each panel's own axis limits.
• Advanced Plotting: each tab updates on its own, so a change in one tab no longer
  clears the plot in another. The interactive HTML file (about 5 MB) is created only when
  you download it, and the plot stays on screen afterwards.
• Plots are drawn at 150 dpi, as Quick Plot already was (other pages used 200), at
  about half the cost to draw. Unchanged Multi-Plot Dashboard panels are no longer
  redrawn when the page refreshes: a refresh of a 2×2 dashboard takes about 0.4 s instead
  of 1 s.
• A missing optional package (for example h5py for HDF5 files) is reported with what to
  install, and where installing isn't possible, says so.

Fixed

• JCAMP-DX files (.jdx, .dx) load again. With jcamp 1.3 installed, every such file
  failed with "the jcamp package is required". jcamp is now part of the formats extra
  (pip install "eagleplot[formats]").
• Quick Plot's dataset CSV download was named name.csv.csv.
• Multi-Plot Dashboard: the combined PNG and PDF downloads work. Before, pressing either
  button made the dashboard disappear without downloading anything.

v3.0.0

Plottle is now EaglePlot. PyPI does not accept the name plottle (it counts as too
similar to an existing project), so 3.0.0 is the first release on PyPI, under the new name.
Nothing else about the toolkit changes in this release.

⚠️ Changed: name, import path and command

• Install: pip install eagleplot (with extras: pip install "eagleplot[formats,nist]").
• Import: import eagleplot / from eagleplot.io import load_data. Code that imports
  plottle must be updated; there is no plottle compatibility package.
• Command: eagleplot, replacing plottle. From a source checkout:
  python -m eagleplot.cli, and the GUI is streamlit run eagleplot/Home.py.
• Setting: EAGLEPLOT_ALLOW_FOLDER_LOAD replaces PLOTTLE_ALLOW_FOLDER_LOAD. The old
  name still works for now and shows a deprecation warning.
• Links: the repository is The-Schultz-Lab/eagleplot and the documentation is at
  https://the-schultz-lab.github.io/eagleplot/.

Still works

• Session files saved by Plottle 2.x load unchanged.
• Saved defaults and presets (config.json) stay where they were.

---

v2.1.0

⚠️ Changed: import paths and the CLI command

• The package is now imported as plottle. Code that did from modules.io import load_data must change to from plottle.io import load_data. The README for 2.0.x already
  documented plottle.*, but the code still shipped as modules. The old name also meant
  installing the wheel claimed the generic top-level names modules and cli, which could
  collide with other projects.
• The CLI is the plottle command, installed by pip install. From a source checkout
  without installing, use python -m plottle.cli. The repo-root cli.py is gone.
• Setup scripts install the package (pip install -e ".[formats,nist]") rather than
  requirements.txt, so the plottle command exists after setup.

Security

• Session files no longer execute code. Loading a .json session ran pickle.loads on
  data inside it, so opening a session someone else shared ran their code. Arrays are now
  stored as dtype, shape and raw bytes. Sessions saved by 2.0.1 or earlier that contain
  pickled entries are refused, and the Export page lists what was skipped.
• Formula evaluation is sandboxed properly. Data Tools formulas used eval() with
  empty builtins, which can be escaped. They are now parsed and checked against a whitelist
  of operators and functions. SECURITY.md now describes what is and isn't guaranteed.
• .pkl files are no longer accepted by the GUI uploader or batch import. Use
  plottle.io.load_pickle() from Python for files you trust.
• Batch import from a folder reads a path on the machine running Plottle, so it is now
  available only to local connections. Set PLOTTLE_ALLOW_FOLDER_LOAD=1 to allow it
  everywhere, or 0 to turn it off.
• Uploaded files go into a private temporary directory that is deleted after loading,
  instead of a shared folder where two users uploading data.csv overwrote each other.

Fixed

• Quick Plot failed to load on Python 3.9 (TypeError: unsupported operand type(s) for |). The Molecular Viz and Batch Analysis pages had the same problem in code paths reached
  later.
• The Settings page failed on Python 3.9 and 3.10 (ModuleNotFoundError: tomllib).
  tomli is now used as a fallback.
• Quick Plot (Plotly mode): clicking a data point crashed the page with
  AttributeError: 'dict' object has no attribute 'x'. Marker labels on dates and
  categories no longer raise either.
• A pip-installed GUI was missing its assets. The logo, NCCU branding, example datasets
  and gallery images now ship inside the package.
• Theme settings: "Theme saved" was shown even when nothing was written, and saving
  discarded every comment in config.toml and could write invalid TOML. The theme is now
  written to .streamlit/config.toml in the working directory, where Streamlit reads it,
  with comments and other sections preserved. Page styling follows the active theme
  instead of a hard-coded dark palette, which left white text on a light background.
• Export → Save session: the download button disappeared after any other click, so it
  took two tries to download. It now stays available until the session changes.
• Settings: "Reset defaults", "Delete preset" and "Delete config.json" each need a
  confirmation tick first, and "Delete config.json" offers a backup download.
• The macOS setup.command and launch.command files are executable again, so Finder will
  run them from a fresh clone.
• The Data Tools page is reachable from the navigation. The sidebar can be collapsed again,
  and images have alt text.
• streamlit>=1.49 is now the declared minimum. The code needed it, but the old >=1.25
  floor allowed versions that fail.

Added

• setup.sh and launch.sh for Linux. All setup scripts now check the Python version
  first.
• formats (HDF5/NetCDF), nist (NIST WebBook lookups), test and all install extras,
  so a normal install no longer pulls in the developer tools.
• A documentation site built from the guides by build_docs.py, replacing the unbuilt
  Sphinx setup. Every guide is linked from the landing page.
• CONTRIBUTING.md, CODE_OF_CONDUCT.md, issue forms and a pull request template.

Development

• CI tests Python 3.9 to 3.12 on Linux, plus macOS and Windows, and runs the whole test
  suite. It used to run a hand-written list of files that skipped the CLI and integration
  tests. Python 3.9 is pinned to ubuntu-24.04 and macOS to macos-15.

• mypy runs with the project installed, so it checks real types instead of treating
  numpy, pandas and matplotlib as Any. ruff and mypy are pinned to exact versions.

• ruff check and ruff format --check cover the whole repository, and ruff flags
  X | None annotations that would fail on Python 3.9 (FA102).

• New tests:

  • every GUI page renders on a fresh session,
  • the "Seaborn/Plotly not installed" errors (9 of these tests were always skipped),
  • the Settings, Export and upload behaviour above.

  The suite has 1,100+ tests.

• The version number has a single source, plottle/__init__.py.

v2.0.1 macOS launchers & pandas 2.x session fix

[2.0.1] - 2026-04-08

Fixed

• Session save/load: wrap DataFrame JSON string in io.StringIO before passing to
  pd.read_json(), fixing a FileNotFoundError on pandas 2.x where a bare string
  argument is now treated as a file path rather than inline content
  (modules/utils/session_state.py)

Changed

• Added macOS one-click setup and launch scripts (setup.command, launch.command)
• Updated launch.bat to check for the virtual environment and print a helpful error
  if it is missing
• README: added platform-specific setup/launch instructions, PyPI badge, and updated
  programmatic import examples to use plottle.* namespace
• pyproject.toml: bumped minimum setuptools to 78.0, normalized license field
  to PEP 639 format, corrected author email, added build/twine dev dependencies
  and changelog URL
• modules/Home.py: use .resolve() for path construction (improves symlink and
  working-directory robustness); moved NCCU wings logo to sidebar

v2.0.0

[2.0.0] - 2026-03-17

Added

Statistical Testing Suite (modules/math.py)

• 12 new hypothesis-testing functions: one-sample/two-sample/paired t-tests, Mann-Whitney U,
  Wilcoxon signed-rank, Kruskal-Wallis, one-way ANOVA, Tukey HSD, Bonferroni correction,
  Pearson/Spearman correlation, chi-square independence
• Two-way ANOVA (anova_twoway) via optional statsmodels dependency
• Effect size display (Cohen's d with Small/Medium/Large interpretation) in the GUI

Signal Processing (modules/signal.py — new module)

• 16 functions: moving-average/Savitzky-Golay/Gaussian smoothing; Butterworth low/high/band/band-stop
  filters (zero-phase sosfiltfilt); FFT + inverse FFT + power spectrum; 1st/2nd derivative;
  polynomial/rolling-ball/asymmetric-least-squares baseline correction; cubic/linear/nearest interpolation
• "Signal Processing" tab (6 sub-tabs) added to Analysis Tools page

Peak Analysis (modules/peaks.py — new module)

• 5 functions: find_peaks, integrate_peaks, compute_fwhm, fit_peak, fit_multipeak
• Gaussian/Lorentzian/Voigt/pseudo-Voigt peak models; multi-peak simultaneous fitting
• "Peak Analysis" tab (2 sub-tabs: Find & Measure, Fit Peaks) in Analysis Tools page

Extended Plot Types (modules/plotting.py)

• 13 new plot types: bar chart (simple/grouped/stacked), waterfall plot, dual y-axis, z-colored
  scatter, bubble chart, polar plot, pair plot, 2D histogram/hexbin, interactive 3D scatter,
  scatter with regression, residual plot, interactive ternary, broken axis, inset plot
• Error bar support (yerr/xerr) added to scatter_plot and line_plot
• COLORBLIND_PALETTE (Okabe-Ito 8 colors) added; get_color_palette('colorblind', n) works
• Total plot types: 26 (was 13 at v1.0.0)

Data Manipulation Layer (modules/data_tools.py — new module)

• 12 non-destructive functions: formula columns (safe eval), normalization, transpose,
  pivot/melt, row filter, sort, merge/join, fill/drop NaN, resample, rolling transforms
• Page 9 — Data Tools: dedicated Streamlit page with 10 operation tabs

Figure Layout & Annotation (modules/annotations.py — new module)

• 7 overlay types: hline, vline, hspan, vspan, text, rectangle, ellipse
• Annotation panel added to Quick Plot (add/delete/clear overlays; persists across re-renders)
• Multi-Plot Dashboard expanded: 10 grid layouts up to 4×4; axis sharing; combined PNG/PDF export

Instrument File Import (modules/io.py)

• 5 new loaders: JCAMP-DX (.jdx/.dx), HDF5 (.h5/.hdf5), NetCDF (.nc/.cdf),
  SPC (.spc), generic ASC/text (.asc)
• mzML/mzXML loader (load_mzml) via optional pymzml dependency

Spectroscopy & Molecular Analysis (modules/spectroscopy.py, modules/molecular/ — new)

• 18 spectroscopy functions covering IR/Raman, UV-Vis/Beer-Lambert/FRET, NMR, and mass spec
• modules/molecular/ package: CPK atom data, Gaussian/ORCA/Molden vibrational parsers,
  Plotly 3D molecule + displacement-arrow figure builder (no RDKit dependency)
• Page 10 — Spectroscopy; Page 11 — Molecular Viz (vibrational mode animation)
• NIST WebBook integration (modules/nist.py): fetch IR JCAMP spectra by CAS number

Batch GUI & Automation (modules/batch.py — new module)

• 5 functions: scan_directory, batch_load_files, batch_statistics, batch_curve_fit,
  batch_peak_analysis
• Page 12 — Batch Analysis: Statistics/Curve Fit/Peak Analysis across multiple datasets + CSV export
• Workflow presets: save/load/delete named analysis pipeline configs persisted to config.json
• Batch folder import expander added to Data Upload page

PDF Report Generation (modules/report.py — new module)

• generate_pdf_report() using matplotlib.backends.backend_pdf.PdfPages (no new dependencies)
• Report section added to Export Results page (title, author, DPI slider, one-click download)

Plugin System (modules/plugin_loader.py — new module)

• Auto-discovers plugin_*.py files from the plugins/ directory via importlib.util
• discover_plugins, get_plugin_plot_types, get_plugin_analysis_tools, list_plugins
• plugins/plugin_example.py starter template; plugin status shown in Settings page

Performance Utilities (modules/io.py)

• downsample_for_preview(df, max_rows=10_000, method='systematic') — fast preview for large data
• load_large_csv(filepath, max_rows=500_000, chunksize=50_000) — chunked CSV loading
• Large-file warning (> 50 MB or > 10k rows) with auto-downsampled preview in Data Upload

New GUI Pages (7 total added)

• Page 7 — Export Results (plots, datasets, analysis JSON, session save/load, PDF report)
• Page 8 — Gallery (pre-generated example figures for all 26 plot types; "Load this config" button)
• Page 9 — Data Tools
• Page 10 — Spectroscopy
• Page 11 — Molecular Viz
• Page 12 — Batch Analysis
• Page 13 — Help (Getting Started, Plot Types, Analysis Tools, File Formats, Tips & Tricks)
• Page 14 — Settings (moved to bottom of sidebar)
• Home page redesigned: Dashboard tab (metric cards, smart CTA) + Help tab (Quick Start, formats, tips)

UX & Visual Polish

• Nunito Google Font applied globally via CSS injection
• Style presets: save/load/delete named Quick Plot configurations persisted to config.json
• "Convert to Plotly (zoom/pan)" toggle on every matplotlib figure in Quick Plot
• PNG bytes stored in session state (fixes MediaFileHandler: Missing file Streamlit bug)
• Equal-height CSS for Gallery cards; compact Data Upload (3-tab layout)

Testing

• Test suite expanded from 258 to ~900+ tests across 17 test files
• 12 new test modules: test_signal, test_peaks, test_data_tools, test_annotations,
  test_spectroscopy, test_molecular_parsers, test_batch, test_report,
  test_plugin_loader, test_nist, plus expansions to test_plotting, test_math, test_io

Code Quality

• Switched formatter from black to ruff-format
• Line length bumped to 100; E501 enforced
• .pre-commit-config.yaml: ruff, ruff-format, trailing-whitespace, end-of-file-fixer,
  check-merge-conflict

Changed

• GUI entry point renamed from modules/gui.py to modules/Home.py
• Settings page renumbered from 6_Settings.py to 14_Settings.py (sidebar ordering)
• use_container_width= fully replaced with width='stretch' / width='content' (all pages)
• black replaced by ruff-format in CI lint job and pyproject.toml dev dependencies
• ruff check now covers all new modules in CI

Fixed

• NIST WebBook IR fetch: corrected URL format to ?JCAMP=C{cas}&Index={idx}&Type=IR-SPEC
  (was returning HTTP 404 with old ?ID=cas&JCAMP=1 format)
• mpl_to_plotly conversion now re-applies style config after conversion so font sizes
  and colors persist when toggling "Convert to Plotly"
• generate_gallery.py: fixed 7 bugs (column name mismatches, dpi leaking into plot kwargs,
  duplicate kwargs, unsupported annotate kwarg for heatmap, broken figsize handling)