Science Score: 67.0%
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✓DOI references
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Low similarity (14.6%) to scientific vocabulary
Keywords
Repository
A Python package to create neutral landscape models
Basic Info
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- Stars: 12
- Watchers: 5
- Forks: 3
- Open Issues: 3
- Releases: 3
Topics
Metadata Files
README.md
NLMpy 
NLMpy is a Python package for the creation of neutral landscape models that
are widely used by landscape ecologists to model ecological patterns across
landscapes. NLMpy can create both continuous patterns to represent landscape
characteristics such as elevation or moisture gradients, or categorical patterns
to represent landscape characteristics such as vegetation patches or land parcel
boundaries.
NLMpy aims to:
- be open-source so it can be easily adapted or developed for specific modelling requirements.
- be cross-platform it can be used on any computer system.
- bring together a wide range of neutral landscape model algorithms.
- be easily integrated with geographic information system data.
- enable novel combinations and integrations of different neutral landscape model algorithms.
A full description of the package can be found in the accompanying software paper.
Quick examples
All the NLMpy neutral landscape models are produced as two-dimensional NumPy arrays, so the
results can be easily incorporated into broader Python workflows.
Using NLMpy to create a midpoint displacement neutral landscape model can be achieved with
only two lines of code:
python
from nlmpy import nlmpy
nlm = nlmpy.mpd(nRow=50, nCol=50, h=0.75)
But as described in the software paper a wide variety of different patterns can be produced.
Citation
If you use NLMpy in your research we would be very grateful if you could please cite the
software using the following freely available software paper:
Some of the neutral landscape models available in NLMpy were developed elsewhere. Therefore, we
think it is good practice to cite the original source a neutral landscape model so that there is appropriate
credit given not just for the implementation in NLMpy but also for the original idea. The freely available
NLMpy software paper and the
docstring preceding each function contains a reference when relevant.
We would then recommend formatting statements such as the following to give credit to both the idea and software implementation:
- "We used a midpoint displacement (Fournier et al. 1982) based neutral landscape model as implemented in NLMpy (Etherington et al. 2015)"
- "The NLMpy software (Etherington et al. 2015) was used to create Perlin noise neutral landscape models (Etherington 2022)."
Installation
NLMpy is available on the Python Package Index, so it can be installed using:
pip install nlmpy
If that does not work you could also simply move the NLMpy.py file to the same location
on your computer as a Python script that wants to import NLMpy, then when those scripts are
executed they will import all the NLMpy functions. So while this approach does not
actually install NLMpy onto your computer, it does at least allow you to make use of the
functionality of NLMpy within a neighbouring Python script.
Package dependencies
- numpy
- scipy
- numba
Community guidelines
We very much welcome input from others! If you find a bug, need some help, or can think of some extra functionality that would be useful, please raise an issue. Better still, please feel free to fork the project and raise a pull request if you think and can fix a bug, clarify the documentation, or improve the functionality yourself.
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, we would really appreciate it if you could please cite it as follows:"
authors:
- family-names: "Etherington"
given-names: "Thomas R."
orcid: "https://orcid.org/0000-0002-3187-075X"
- family-names: "Holland"
given-names: "E. Penelope"
orcid: "https://orcid.org/0000-0002-4334-6234"
- family-names: "O'Sullivan"
given-names: "David"
orcid: "https://orcid.org/0000-0001-8078-3241"
title: "NLMpy"
version: 1.1.0
doi: 10.5281/zenodo.5533033
date-released: 2021-09-28
url: "https://github.com/tretherington/nlmpy"
preferred-citation:
type: article
authors:
- family-names: "Etherington"
given-names: "Thomas R."
orcid: "https://orcid.org/0000-0002-3187-075X"
- family-names: "Holland"
given-names: "E. Penelope"
orcid: "https://orcid.org/0000-0002-4334-6234"
- family-names: "O'Sullivan"
given-names: "David"
orcid: "https://orcid.org/0000-0001-8078-3241"
doi: "10.1111/2041-210X.12308"
journal: "Methods in Ecology and Evolution"
month: 2
start: 164 # First page number
end: 168 # Last page number
title: "NLMpy: a PYTHON software package for the creation of neutral landscape models within a general numerical framework"
issue: 2
volume: 6
year: 2015
GitHub Events
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- Push event: 1
Last Year
- Push event: 1
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 4
- Total pull requests: 5
- Average time to close issues: 1 day
- Average time to close pull requests: less than a minute
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 1.75
- Average comments per pull request: 0.0
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Past Year
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- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
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- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- tretherington (3)
- zjans (1)
Pull Request Authors
- tretherington (5)
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Packages
- Total packages: 1
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Total downloads:
- pypi 57 last-month
- Total dependent packages: 1
- Total dependent repositories: 7
- Total versions: 12
- Total maintainers: 1
pypi.org: nlmpy
A Python package to create neutral landscape models
- Homepage: https://github.com/tretherington/nlmpy
- Documentation: https://nlmpy.readthedocs.io/
- License: MIT License
-
Latest release: 1.2.0
published over 2 years ago