lowtran
Atmospheric absorption extinction, scatter and irradiance model in Python and Matlab.
https://github.com/space-physics/lowtran
Category: Atmosphere
Sub Category: Radiative Transfer
Keywords
atmosphere atmospheric-modelling f2py fortran geoscience lowtran matlab matlab-python-interface python
Last synced: about 7 hours ago
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Repository metadata
LOWTRAN atmospheric absorption extinction, scatter and irradiance model--in Python and Matlab
- Host: GitHub
- URL: https://github.com/space-physics/lowtran
- Owner: space-physics
- License: mit
- Created: 2015-03-31T19:19:59.000Z (about 10 years ago)
- Default Branch: main
- Last Pushed: 2024-12-19T01:14:46.000Z (4 months ago)
- Last Synced: 2025-04-10T05:05:12.350Z (17 days ago)
- Topics: atmosphere, atmospheric-modelling, f2py, fortran, geoscience, lowtran, matlab, matlab-python-interface, python
- Language: Python
- Homepage:
- Size: 3.17 MB
- Stars: 108
- Watchers: 10
- Forks: 43
- Open Issues: 6
- Releases: 10
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
README.md
Lowtran in Python
LOWTRAN7 atmospheric absorption extinction model.
Updated to be platform independent and easily accessible from Python and
Matlab.
The main LOWTRAN program is accessible from Python by using direct memory transfers instead of the cumbersome and error-prone process of writing/reading text files.
xarray.Dataset
high-performance, simple N-D array data is passed out, with appropriate metadata.
Gallery
See below for how to make these examples.
Install
Lowtran requires a Fortran compiler and CMake.
We use f2py
(part of numpy
) to seamlessly use Fortran libraries from Python by special compilation of the Fortran library with auto-generated shim code.
For Python 3.12, make sure to install setuptools using pip, i.e., pip install setuptools
and make sure meson is available on the system.
If a Fortran compiler is not already installed, install Gfortran:
- Linux:
apt install gfortran
- Mac:
brew install gcc
- Windows: Windows Subsystem for Linux
Install Python Lowtran code
pip install -e .
Examples
In these examples, optionally write to HDF5 with the -o
option.
We present Python examples of:
-
ground-to-space transmittance: TransmittanceGround2Space.py
-
sun-to-observer scattered radiance (why the sky is blue): ScatterRadiance.py
-
sun-to-observer irradiance: SolarIrradiance.py
-
observer-to-observer solar single-scattering solar radiance (up-going) with custom Pressure, Temperature and partial pressure for 12 species: UserDataHorizontalRadiance.py
-
observer-to-observer transmittance with custom Pressure, Temperature and partial pressure for 12 species: UserDataHorizontalTransmittance.py
-
observer-to-observer transmittance: HorizontalTransmittance.py
Matlab
Matlab users can seamlessly access Python modules, as demonstrated in
RunLowtran.m.
Here's what's you'll need:
-
Install Lowtran in Python as at the top of this Readme.
-
From Matlab, verify everything is working by:
runtests('lowtran')
Notes
LOWTRAN7
User manual
Refer to this to understand what parameters are set to default.
Currently I don't have any aerosols enabled for example, though it's possible to add them into the code.
Right now a lot of configuration features aren't implemented, please request those you want.
Reference
- Original 1994 Lowtran7 Code
LOWFIL
program in reference/lowtran7.10.f was not connected as we had previously implemented a filter function directly in Python.LOWSCAN
spectral sampling (scanning) program inreference/lowtran7.13.f
was not connected as we had no need for coarser spectral resolution.
Owner metadata
- Name: Space Physics
- Login: space-physics
- Email:
- Kind: organization
- Description: Space Physics modeling and analysis
- Website:
- Location: 1 au
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/36680810?v=4
- Repositories: 63
- Last ynced at: 2023-09-11T07:54:00.349Z
- Profile URL: https://github.com/space-physics
GitHub Events
Total
- Issues event: 2
- Watch event: 8
- Fork event: 1
Last Year
- Issues event: 2
- Watch event: 8
- Fork event: 1
Committers metadata
Last synced: 6 days ago
Total Commits: 380
Total Committers: 3
Avg Commits per committer: 126.667
Development Distribution Score (DDS): 0.013
Commits in past year: 3
Committers in past year: 2
Avg Commits per committer in past year: 1.5
Development Distribution Score (DDS) in past year: 0.333
Name | Commits | |
---|---|---|
scivision | s****n | 375 |
scivision | s****n@n****m | 4 |
Jonas Krimmer | 3****r | 1 |
Committer domains:
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 25
Total pull requests: 2
Average time to close issues: over 1 year
Average time to close pull requests: 5 days
Total issue authors: 20
Total pull request authors: 2
Average comments per issue: 1.16
Average comments per pull request: 0.0
Merged pull request: 1
Bot issues: 0
Bot pull requests: 0
Past year issues: 1
Past year pull requests: 0
Past year average time to close issues: 40 minutes
Past year average time to close pull requests: N/A
Past year issue authors: 1
Past year pull request authors: 0
Past year average comments per issue: 0.0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
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- OctagonHex (3)
- aschneid42 (2)
- chrismolli (1)
- SmithPeng (1)
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- bpdavis86 (1)
- justapythonuser (1)
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Top Pull Request Authors
- WhiteChimney (1)
- jkrimmer (1)
Top Issue Labels
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- question (2)
Top Pull Request Labels
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 481 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 19
- Total maintainers: 1
pypi.org: lowtran
Model of Earth atmosphere absorption and transmission vs. wavelength and location.
- Homepage:
- Documentation: https://lowtran.readthedocs.io/
- Licenses: mit
- Latest release: 3.1.0 (published about 2 years ago)
- Last Synced: 2025-04-25T12:30:57.158Z (1 day ago)
- Versions: 19
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 481 Last month
- Docker Downloads: 0
-
Rankings:
- Docker downloads count: 4.203%
- Dependent packages count: 10.002%
- Average: 15.106%
- Dependent repos count: 21.718%
- Downloads: 24.499%
- Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- msys2/setup-msys2 v2 composite
- numpy *
- python-dateutil *
- xarray *
Score: 12.014827390715178