ltool

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Documentation: https://nikolaos-siomos.github.io/ltool/

ltool is a layer detection tool based on the Wavelet Covariance Transform (WCT) for lidar profile analysis.

It provides:

  • A programmatic Python API (get_layers)
  • A standalone CLI (ltool_standalone) for local processing
  • An SCC/server CLI (ltool_scc) for server-side processing using an .ini configuration
  • Export of retrieved layers to NetCDF and generation of diagnostic plots

Installation

From PyPI:

pip install ltool

For development:

pip install -e .

Quick start

Python API

from ltool.__ltool__ import get_layers

layer_obj = get_layers(
    height=height,
    sig=sig,
    sig_err=sig_err,
    method="optimized_prm",
)

print(layer_obj.layers)

Export and plots:

layer_obj.export_to_netcdf(dir_out="/path/to/output", save_netcdf=True)
layer_obj.visualize(dir_out="/path/to/output", save_plots=True)

Standalone CLI

Run on a directory of NetCDF files:

ltool_standalone \
  --input_path /absolute/path/to/data \
  --method optimized_prm \
  --save_plots \
  --save_netcdf

SCC/server CLI

ltool_scc \
  --measurement_id 123456 \
  --config_file /absolute/path/to/ltool.ini

Layer detection methods

The --method option controls how bases/tops are selected. Choices:

  • height_based
  • wct_based
  • snr_based
  • prm_based
  • optimized_wct
  • optimized_snr
  • optimized_prm (default)

See docs/methods/pairing.md for the full explanation.

Documentation (MkDocs)

Serve docs locally:

mkdocs serve

Build static site:

mkdocs build

Project layout

Recommended structure:

.
├── pyproject.toml
├── src/
│   └── ltool/
├── examples/
├── docs/
├── mkdocs.yml
└── .gitlab-ci.yml

Release (PyPI)

Build:

rm -rf dist build *.egg-info
python -m build

Upload:

python -m twine upload dist/*

License

This project is licensed under the terms of the GNU AFFERO GENERAL PUBLIC LICENSE.

Contact

Maintainer: Nikolaos Siomos
LMU
Email: nikolaos.siomos@lmu.de

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for nsiomos from gravatar.com nsiomos

Credits

Author: Nikolaos Siomos

License

AGPL-3.0-or-later

Requires

Python <3.14, >=3.8

Provides Extra

docs

Classifiers

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