Data cube for handling atmospheric observations of profiling remote sensing instruments.
Project description
pyLARDA v3
pyLARDA for accessing and analysing ground based remote sensing data. It tries to simplify following tasks:
- finding netcdf files in a complex folder structure
- loading data from differently formatted netcdfs
- stitching data from consecutive files together
- simplify common plotting tasks
Documentation is available at larda-doc
Quick Setup (pypi)
requires python3.8 or newer
python3 -m venv larda-env
source larda-env/bin/activate
python3 -m pip install pyLARDA
Requirements
The pyLARDA remote backend is only targeted on unix operating system.
Building the documentation requires some more dependencies:
sphinx
recommonmark
sphinx_rtd_theme
Setup (github)
For development, local data sources and the backend, pyLARDA module can be installed with:
python3 -m venv larda-env
source larda-env/bin/activate
mkdir larda3
cd larda3
git clone https://github.com/lacros-tropos/larda.git
cd larda
python3 -m pip install --editable .
Depending on your datasource of choice:
remote
You just need to know the link to the backend backend of choice and may move to Quickstart.
local
For local data it is necessary to include the source in a certain directory structure. For the setup of the config files consult the Guide to config-files.
├── larda # github managed source code
│ ├── docs
│ ├── examples
│ ├── ListCollector.py
│ ├── pyLARDA # actual python module
│ ├── README.md
│ ├── requirements.txt
│ └── run_docs.sh
├── larda-cfg # configuration files
│ ├── campaigns.toml
│ ├── [single campaign].toml
│ └── [single campaign].toml
├── larda-connectordump
│ └── [auto generated subfolder for each campaign]
├── larda-description
│ ├── [...].rst
└── larda-doc # folder if you want to generate the docs
└── ...
Quickstart
Make sure that the module is available at your pythonpath when in doubt use sys.path.append('dir')
.
import pyLARDA
link_to_backend = 'http://...'
# or use pyLARDA.LARDA('local')
larda = pyLARDA.LARDA('remote', uri=link_to_backend)
print('available campaigns', larda.campaign_list)
larda.connect('campaign_name')
MIRA_Zg = larda.read("MIRA","Zg", [dt_begin, dt_end], [0, 4000])
fig, ax = pyLARDA.Transformations.plot_timeheight2
(MIRA_Zg, range_interval=[500, 3000], z_converter='lin2z')
fig.savefig('MIRA_Z.png', dpi=250)
For more examples refer to the scripts in the examples
directory.
Architecture
Documentation
An online version of the documentation is available at https://lacros-tropos.github.io/larda-doc/.
For building simply run .\run_docs.sh
, when the additinal libraries (sphinx
, recommonmark
and sphinx_rtd_theme
are available; see above).
History
This version of the LACROS research data analyser (LARDA) is based on two prior versions in C and python2 respectively. Major changes are the migration to python3, netcdf4 and the inclusion of radar Doppler spectra.
License
Copyright 2024, pyLARDA-dev-team (Johannes Bühl, Martin Radenz, Willi Schimmel, Teresa Vogl, Moritz Lochmann, Johannes Röttenbacher, Andi Klamt)
MIT License For details see the LICENSE file.
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