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Project description
ltool
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.iniconfiguration - 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_basedwct_basedsnr_basedprm_basedoptimized_wctoptimized_snroptimized_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 details
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