Name | nlmod JSON |
Version |
0.9.0
JSON |
| download |
home_page | None |
Summary | Python package to build, run and visualize MODFLOW 6 groundwater models in the Netherlands. |
upload_time | 2024-11-26 15:05:45 |
maintainer | None |
docs_url | None |
author | O. Ebbens, R. Caljé, D.A. Brakenhoff |
requires_python | >=3.8 |
license | The MIT License (MIT) Copyright (c) 2024 O.N. Ebbens, D.A. Brakenhoff, R. Calje Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
keywords |
hydrology
groundwater
modeling
modflow 6
flopy
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
# nlmod
<img src="docs/_static/logo_10000_2.png" width="256"/>
[![nlmod](https://github.com/gwmod/nlmod/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/gwmod/nlmod/actions/workflows/ci.yml)
[![Codacy Badge](https://app.codacy.com/project/badge/Grade/f1797b66e98b42b294bc1c5fc233dbf3)](https://app.codacy.com/gh/gwmod/nlmod/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
[![Codacy Badge](https://app.codacy.com/project/badge/Coverage/f1797b66e98b42b294bc1c5fc233dbf3)](https://app.codacy.com/gh/gwmod/nlmod/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_coverage)
[![PyPI version](https://badge.fury.io/py/nlmod.svg)](https://badge.fury.io/py/nlmod)
[![Documentation Status](https://readthedocs.org/projects/nlmod/badge/?version=stable)](https://nlmod.readthedocs.io/en/stable/?badge=stable)
Python package to build, run and visualize MODFLOW 6 groundwater models in the Netherlands.
`nlmod` was built to allow users to write scripts to quickly download relevant data
from publicly available sources, and build and post-process groundwater flow and
transport models at different spatial and temporal scales to answer specific
geohydrological questions. Scripting these steps, from downloading data to building
groundwater models, makes models more reproducible and transparent.
The functions in `nlmod` have four main objectives:
1. Create and adapt the temporal and spatial discretization of a MODFLOW model using an
xarray Dataset (`nlmod.dims`).
2. Download and read data from external sources, project this data on the modelgrid and
add this data to an xarray Dataset (`nlmod.read`).
3. Use data in an xarray Dataset to build modflow packages for both groundwater flow
and transport models using FloPy (`nlmod.sim`, `nlmod.gwf` and `nlmod.gwt` for
Modflow 6 and `nlmod.modpath` for Modpath).
4. Visualise modeldata in Python (`nlmod.plot`) or GIS software (`nlmod.gis`).
More information can be found on the documentation-website:
https://nlmod.readthedocs.io/.
## Installation
Install the module with pip:
`pip install nlmod`
`nlmod` has the following required dependencies:
* `flopy`
* `xarray`
* `netcdf4`
* `rasterio`
* `rioxarray`
* `affine`
* `geopandas`
* `owslib`
* `hydropandas`
* `shapely`
* `pyshp`
* `rtree`
* `matplotlib`
* `dask`
* `colorama`
* `joblib`
* `bottleneck`
There are some optional dependecies, only needed (and imported) in a single method.
Examples of this are `geocube`, `rasterstats` (both used in nlmod.util.zonal_statistics),
`h5netcdf` (used for hdf5 files backend in xarray), `scikit-image`
(used in nlmod.read.rws.calculate_sea_coverage).
To install `nlmod` with the optional dependencies use:
`pip install nlmod[full]`
When using pip the dependencies are automatically installed. Some dependencies are
notoriously hard to install on certain platforms. Please see the
[dependencies](https://github.com/ArtesiaWater/hydropandas#dependencies) section of the
`hydropandas` package for more information on how to install these packages manually.
## Getting started
Start with the Jupyter Notebooks in the examples folder. These notebooks illustrate how to use the `nlmod` package.
Raw data
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"description": "# nlmod\n\n<img src=\"docs/_static/logo_10000_2.png\" width=\"256\"/>\n\n[![nlmod](https://github.com/gwmod/nlmod/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/gwmod/nlmod/actions/workflows/ci.yml)\n[![Codacy Badge](https://app.codacy.com/project/badge/Grade/f1797b66e98b42b294bc1c5fc233dbf3)](https://app.codacy.com/gh/gwmod/nlmod/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)\n[![Codacy Badge](https://app.codacy.com/project/badge/Coverage/f1797b66e98b42b294bc1c5fc233dbf3)](https://app.codacy.com/gh/gwmod/nlmod/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_coverage)\n[![PyPI version](https://badge.fury.io/py/nlmod.svg)](https://badge.fury.io/py/nlmod)\n[![Documentation Status](https://readthedocs.org/projects/nlmod/badge/?version=stable)](https://nlmod.readthedocs.io/en/stable/?badge=stable)\n\nPython package to build, run and visualize MODFLOW 6 groundwater models in the Netherlands.\n\n`nlmod` was built to allow users to write scripts to quickly download relevant data\nfrom publicly available sources, and build and post-process groundwater flow and\ntransport models at different spatial and temporal scales to answer specific\ngeohydrological questions. Scripting these steps, from downloading data to building\ngroundwater models, makes models more reproducible and transparent.\n\nThe functions in `nlmod` have four main objectives:\n\n1. Create and adapt the temporal and spatial discretization of a MODFLOW model using an \n xarray Dataset (`nlmod.dims`).\n2. Download and read data from external sources, project this data on the modelgrid and \n add this data to an xarray Dataset (`nlmod.read`).\n3. Use data in an xarray Dataset to build modflow packages for both groundwater flow \n and transport models using FloPy (`nlmod.sim`, `nlmod.gwf` and `nlmod.gwt` for \n Modflow 6 and `nlmod.modpath` for Modpath).\n4. Visualise modeldata in Python (`nlmod.plot`) or GIS software (`nlmod.gis`).\n\nMore information can be found on the documentation-website:\nhttps://nlmod.readthedocs.io/.\n\n## Installation\n\nInstall the module with pip:\n\n`pip install nlmod`\n\n`nlmod` has the following required dependencies: \n\n* `flopy`\n* `xarray`\n* `netcdf4`\n* `rasterio`\n* `rioxarray`\n* `affine`\n* `geopandas`\n* `owslib`\n* `hydropandas`\n* `shapely`\n* `pyshp`\n* `rtree`\n* `matplotlib`\n* `dask`\n* `colorama`\n* `joblib`\n* `bottleneck`\n\nThere are some optional dependecies, only needed (and imported) in a single method.\nExamples of this are `geocube`, `rasterstats` (both used in nlmod.util.zonal_statistics),\n`h5netcdf` (used for hdf5 files backend in xarray), `scikit-image`\n(used in nlmod.read.rws.calculate_sea_coverage).\nTo install `nlmod` with the optional dependencies use:\n\n`pip install nlmod[full]`\n\nWhen using pip the dependencies are automatically installed. Some dependencies are\nnotoriously hard to install on certain platforms. Please see the\n[dependencies](https://github.com/ArtesiaWater/hydropandas#dependencies) section of the\n`hydropandas` package for more information on how to install these packages manually.\n\n## Getting started\n\nStart with the Jupyter Notebooks in the examples folder. These notebooks illustrate how to use the `nlmod` package.\n",
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