PyTurbo_SF
The facts below are what the maker publishes about PyTurbo_SF, checked and dated. Our editors have not written about it yet.
Plans and prices
From PyTurbo_SF's own pricing page, checked 11 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| PyTurbo_SF | Free | No paid tiers or usage limits stated |
The facts
Each one read from PyTurbo_SF's own pages, with the date it was checked.
What it does
- Data export
- Yeschecked 23 Sep 2026
- Delivery mode
- desktopchecked 23 Sep 2026
- Input and results
- The example workflow accepts xarray Datasets and returns structure-function results as xarray Datasets.checked 11 Oct 2026
- Installation
- The package can be installed with pip from PyPI or installed from its GitHub source repository.checked 11 Oct 2026
- Integrations
- Required dependencies include NumPy, xarray, SciPy, pandas, and joblib; optional packages include matplotlib, Dask, Zarr, and netCDF4.checked 11 Oct 2026
- Isotropic analysis
- It provides isotropic averaging for 2D and 3D data.checked 11 Oct 2026
- Large-data considerations
- The guide recommends tuning bootstrap block sizes and suggests Dask for datasets larger than available memory.checked 11 Oct 2026
- Parallel processing
- The quick start demonstrates loky and threading backends, and the guide also lists multiprocessing as an option.checked 11 Oct 2026
- Purpose
- PyTurbo_SF is a Python package for efficient structure-function calculations on 1D, 2D, and 3D data, including turbulent-flow analysis.checked 11 Oct 2026
- Python requirement
- The installation guide states that Python 3.12 or higher is required.checked 11 Oct 2026
- Security and compliance
- The documentation pages reviewed do not state security certifications or compliance programs.checked 11 Oct 2026
- Structure-function types
- It supports longitudinal, transverse, scalar, and combined structure functions.checked 11 Oct 2026
- Support
- For installation issues, the guide directs users to GitHub Issues and community discussions.checked 11 Oct 2026
- Target users
- The documentation describes use by researchers in oceanography, atmospheric science, and fluid dynamics analyzing observational data and simulations.checked 11 Oct 2026
- Uncertainty analysis
- It uses adaptive bootstrap resampling to provide statistical uncertainty estimates and detect convergence.checked 11 Oct 2026
Money
- Free plan
- Yeschecked 23 Sep 2026
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