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.simstudies. - 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
.simfiles 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
.simfiles, 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.
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.
Metadata
Release files for anytimes 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| anytimes-1.1.0.tar.gz | 1.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| anytimes-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.1 MB
Release files / anytimes-1.1.0.tar.gz
| Download URL | anytimes-1.1.0.tar.gz |
|---|---|
| Size | 1.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / anytimes-1.1.0-py3-none-any.whl
| Download URL | anytimes-1.1.0-py3-none-any.whl |
|---|---|
| Size | 360.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
f5b3850ca5fcefc52aedb7b55ac222bda66558de0c21f078aad31c2910d49a5a
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 15, 2026.
Transparency log