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ANYtimeSeries provides a QT-based interface for exploring and editing time-series data.

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ANYtimeSeries

ANYtimeSeries provides a Qt-based interface for exploring, editing and analysing time-series data. The goal is efficient processing and a clear understanding of the loaded signals, whether they originate from laboratory tests, numerical simulations or OrcaFlex studies.

The application supports a broad range of formats for loading and visualising time-series information. For a comprehensive walkthrough—covering the full workflow, control reference and screenshots—see the documentation.

Key features

Data import and management

  • Load multiple files at once; the editor automatically identifies common variables for quick comparison across tests.
  • Native support for text, binary and tabular formats (csv, xlsx, mat, h5, tdms, parquet, …) alongside OrcaFlex .sim studies.
  • Preload OrcaFlex simulations, reuse previous selections and broadcast object/variable choices across matching simulations to keep large projects in sync.
  • Extract surface pressure time series by pairing .sim files with diffraction (.owr) models and a set of user-specified panel coordinates.
  • Cache OrcaFlex selections and diffraction models so subsequent loads are instant.

Editing and transformation

  • Quickly manipulate series via predefined operations (multiply/divide, negate, convert degrees↔radians, rolling averages, absolute value, square-root sum of squares, mean, zero-shifting utilities and more).
  • Apply custom expressions per variable (e.g. *2, +offset) or evaluate full calculator expressions to build user-defined channels instead of overwriting the originals.
  • Limit operations to a time window and optionally resample data when exporting selections to CSV.

Filtering, statistics and extreme values

  • Apply low-, high-, band-pass or band-stop filters to the active selection and feed the filtered data into plots or statistics.
  • Open the Statistics window for a sortable table, histograms, descriptive metrics and clipboard export (TSV).
  • Launch the Extreme Value Statistics tool to perform Generalized Pareto fits, return-level calculations and diagnostic plotting, including guidance for stabilising challenging fits.

Visualisation

  • Plot selected variables in a single figure or side-by-side grid using Plotly, Bokeh or Matplotlib backends.
  • Embed plots inside the main window or open them in a separate browser window, toggle shared axes, annotate maxima/minima and trim labels.
  • Generate rolling means, mean overlays and XYZ scatter animations to inspect vector responses.

OrcaFlex integration

  • Search objects and variables with live filtering, strip redundant substrings from labels and specify arc-length/extras directly in the selector.
  • Reuse selections for future .sim files, apply them to batches of simulations and automatically align similarly named objects via configurable stripping rules.

SWAN tool

  • Includes a standalone SWANtool workflow with support for non-stationary NetCDF (.nc) files in the current version.

Convenience utilities

  • Switch between light and dark themes, embed plots, open external viewers and manage offsets/scaling presets via save/load dialogs.
  • Track file loading progress with an integrated progress bar and optional preloading callbacks.

AnytimeSeries dark mode

AnytimeSeries light mode

AnytimeSeries statistics

Installation

pip install anytimes

For running on Windows without a Python environment installed, download the .exe file from releases. If you prefer to build the executable yourself, follow the PyInstaller packaging guide to produce a standalone ANYtimeSeries.exe from the sources.

Requirements

The package metadata is the source of truth. Installation includes numpy, pandas, openpyxl, scipy, xarray, netCDF4, PySide6, matplotlib, pyextremes, and tqdm. Plotly and Bokeh are optional plotting backends. OrcFxAPI requires a licensed OrcaFlex installation or the OrcaFlex demo.

Usage

After installation, import the GUI module in your Python project:

from anytimes import anytimes_gui

The module exposes Qt widgets for building custom time-series exploration tools.

You can also launch the GUI from the command line using the anytimes entry point or Python's module launcher:

anytimes
python -m anytimes
python run_gui.py

You can start the GUI programmatically by calling:

anytimes_gui.main()

License

Released under the MIT License. See LICENSE for details.

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ANYtimeSeries provides a QT-based interface for exploring and editing time-series data.

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