Coding and Cookies

The following resources have been assembled to take your python skills to the next level so you can:

• Effectively work with geospatial data
• Break-up your analysis and run several instances of your program
• Move your analysis to an HPC and retrieve results

Resources:

• Introduction to Spatial Data Science
• Python
  • Learning Data Analysis in Python Notebooks
  • Interactive Geospatial Python Notebooks: These notebooks have been prepared for those new to geospatial data science in python. Special attention has been given to using interactive plots for choosing both points of interest (POI) and areas of interest (AOI) to customize analysis location.
• HPC 
  • CSU Alpine 101
  • Linux 101
  • Set-up Virtual Environment on HPC
    1. With Interactive Geospatial Python Notebooks cloned (use: "git clone https://github.com/GeospatialCentroid/interactive_geospatial_python.git" from shell)
    2. Make the setup script executable using "chmod +x setup_script.sh"
    3. Run the setup script "./setup_script.sh"
  • Run jobs using Slurm (the HPC job scheduler)
    1. Duplicate and edit the job_template.sh file with "cp job_template.sh job_template{year}.sh"
       1. Open the new file with "vi job_template{year}.sh"
          • Enter edit mode, press the Esc key then 'i'
          • Change the 'year' value used in the file (two locations)
          • Update the email address
          • Save and close the file, press the Esc key then type ':wq' followed by the Enter key
    2. Use the command "sbatch job_template{year}.sh" to submit the job
    3. Then use "squeue --user={user_id}@colostate.edu --long" to check the status of the job
       •  See Useful Slurm commands for more information

Additional Resources:

• Command Line to GitHub

• Learn How to Get an ACCESS Account and Allocation

• ACCESS Knowledge Base Resources

• Scientific Data Analysis Pipelines and Reproducibility

• Make a README

• Closing Survey