## Install and Run ### **Install** - use conda to install the environment ```bash $ git clone git@github.com:zzheng93/UrbanClimateExplorer.git $ cd ./UrbanClimateExplorer/binder $ conda env create -f environment.yml $ conda activate aws_urban ``` ### **Run** - Locally ```bash $ cd ./UrbanClimateExplorer $ git pull $ cd ./docs/notebooks $ jupyter notebook ``` - HPC (e.g., NCAR's [Casper clusters](https://arc.ucar.edu/knowledge_base/70549550) with a GPU) - First, create a bash script (see below), and name it as `aws_urban_env.sh`, put it in the same folder with your `UrbanClimateExplorer` folder. ```bash #!/bin/bash source /glade/work/zhonghua/miniconda3/bin/activate aws_urban echo "ssh -N -L 8889:`hostname`:8889 $USER@`hostname`.ucar.edu" jupyter notebook --no-browser --ip=`hostname` --port=8889 ``` - Second, run the commands below Note: please use `your own job code` instead of "UIUC0021". You can find more information about `execcasper` [here](https://arc.ucar.edu/knowledge_base/72581396) ```bash $ execcasper -A UIUC0021 -l gpu_type=v100 -l walltime=06:00:00 -l select=1:ncpus=18:mpiprocs=36:ngpus=1:mem=100GB $ bash aws_urban_env.sh ``` - Thrid, launch a new terminal, copy and paste the command printed by the "echo" command, and log in. Then open your browser (e.g., Google Chrome), type `https://localhost:8889`. Note: Sometimes port `8889` may be used by others. In this case, please adjust your bash script accordingly, e.g., from `8889` to `8892`: ```bash #!/bin/bash source /glade/work/zhonghua/miniconda3/bin/activate aws_urban echo "ssh -N -L 8889:`hostname`:8892 $USER@`hostname`.ucar.edu" jupyter notebook --no-browser --ip=`hostname` --port=8892 ```