MaguedAlaghbary/AFQ

Geothermal Heat Flow model of Africa using random forest # AFQ Geothermal Heat Flow model of Africa using random forest regression The code reproduces the resuls published in Fronieters in Science ======= The code reproduces the results published in Fronieters in Science The provided Jupyter notebook reproduces the model and and figures in the paper, including supplimentary material. The notebook also generates some additional tests and figures, not included in the paper. # Instructions: Please install the following enviroment and packages : conda create -n AFQ python=3.7 anaconda ======= If anaconda distro is not yet installed please install the latest veriosn from docs.anaconda.com If GMT is not yet installed please install the latest veriosn from generic-mapping-tools.org conda create -n AFQ python=3.9 anaconda activate AFQ conda config --set channel_priority flexible conda update --all conda install -c defaults -c conda-forge numpy xarray dask pyproj pandas scipy imageio conda install -c defaults -c conda-forge geopandas fiona rasterio matplotlib cartopy basemap conda install -c defaults -c conda-forge gstools pykrige affine scikit-learn conda install -c defaults -c conda-forge affine conda install -c defaults -c conda-forge xarray netcdf4 packaging gmt conda install -c defaults -c conda-forge pygmt==0.5.0 conda install -c conda-forge scikit-optimize pip install agrid conda install jupyter notebook for windows users : conda install scikit-learn-intelex ======= conda install --force-reinstall -y -c defaults -c conda-forge xarray dask pyproj pandas scipy conda install --force-reinstall -y -c defaults -c conda-forge geopandas fiona rasterio matplotlib affine conda install --force-reinstall -y -c defaults -c conda-forge xarray netcdf4 packaging gmt pygmt conda install --force-reinstall -y -c conda-forge scikit-optimize pooch jupyter notebook conda install --force-reinstall -y -c anaconda seaborn conda update --force-reinstal …