Python for network analysis
Build, process, and analyze networks. GOSTNets is built on top of geopandas, networkx, osmnx, and peartree.
Eventually we will have the tool available on pip and conda, but for now, please use the setup.py in this repository
conda create --name test python=3.8
conda activate test
conda install -c conda-forge rtree=0.9.3 geopandas rasterio geojson
pip install GOSTnets
conda create --name test python=3.8
conda activate test
conda install -c conda-forge rtree=0.9.3 geopandas rasterio geojson git
git clone https://github.com/worldbank/GOSTnets.git
python setup.py build
python setup.py install
Clone this repo in your local environment (for example in: C:\repos\GOSTnets). Then run the docker container:
docker run -i -t -p 8888:8888 -v ${PWD}:/home -v C:\repos\GOSTnets:/GOSTnets --name anaconda3_gostnets_c1 d3netxer/anaconda3_gostnets_v1
note in the docker command how you are mapping the 8888 port in the docker container to your local machine. You are also creating a volume to the GOSTnets repository code. You are also creating another volume in your present working directory, this is where your project code should be. Then within your container first activate the 'geo_env' anaconda environment conda activate geo_env
. Then use the following command to launch jupyter notebook from the container:
jupyter notebook --ip='0.0.0.0' --port=8888 --no-browser --allow-root --notebook-dir=/home
It will read from your present working directory and the notebook will be exposed through the mapped 8888 port, for you to open with your browser. A tip is that a great development set-up is to your VS Code and install the docker extensions. Once the container is running you can attach to it using VS Code, then you are able to easily use VS Code to write your code and run commands in your docker container.
note: graph-tool is also installed in this docker container.
First you will run the continuumio/anaconda3 docker container:
docker run -i -t -p 8888:8888 -v ${PWD}:/home --name anaconda3 continuumio/anaconda3
Then inside the container you will install the dependencies (followed these instructions: https://geopandas.org/en/stable/getting_started/install.html)
conda create -n geo_env
conda activate geo_env
conda config --env --add channels conda-forge
conda config --env --set channel_priority strict
conda install python=3 geopandas rasterio geojson git gdal geopy boltons pulp jupyterlab osmnx
optional: you can also install graph-tool using Conda and these instructions: https://git.skewed.de/count0/graph-tool/-/wikis/installation-instructions
Then you will commit your image.
conda install -c conda-forge gdal
pip install geopy
pip install boltons
pip install pulp
Jupyter Notebook is used in many GOSTnets examples. We recommend installing it within your environment
conda install -c conda-forge jupyterlab
Documentation available at readthedocs
Plenty of examples and tutorials using Jupyter Notebooks live inside of the Implementations folder within the GOST_PublicGoods Github repo
in the docs dir, run:
sphinx-apidoc -f -o source/ ../GOSTnets
in the docs dir, run:
make html
Every function contains a docstring which can be brought up in use to check the inputs for various functions. For example:
import GOSTnets as gn
gn.edge_gdf_from_graph?
returns:
Signature: gn.edge_gdf_from_graph(G, crs={'init': 'epsg:4326'}, attr_list=None, geometry_tag='geometry', xCol='x', yCol='y')
#### Function for generating a GeoDataFrame from a networkx Graph object ###
REQUIRED: a graph object G
OPTIONAL: crs - projection of format {'init' :'epsg:4326'}. Defaults to
WGS84. Note: here we are defining the crs of the input geometry -
we do NOT reproject to this crs. To reproject, consider using
geopandas' to_crs method on the returned gdf.
attr_list: list of the keys which you want to be moved over to
the GeoDataFrame.
geometry_tag - the key in the data dictionary for each edge which
contains the geometry info.
xCol - if no geometry is present in the edge data dictionary, the
function will try to construct a straight line between the start
and end nodes, if geometry information is present in their data
dictionaries. Pass the Longitude info as 'xCol'.
yCol - likewise, determining the Latitude tag for the node's data
dictionary allows us to make a straight line geometry where an
actual geometry is missing.
RETURNS: a GeoDataFrame object of the edges in the graph
#-------------------------------------------------------------------------#
These docstrings have been written for every function, and should help new and old users alike with the options and syntax.