- python_plotting subdirectory - these materials accompany the "Basic Python Programming" workshop held on June 20, 2024.
- Jupyter notebooks were adapted from Software Carpentry's "Plotting and Programming in Python".
- Notebooks starting 00-08 can be followed workbook style by running the code blocks to demonstrate presented concepts. This set of Notebooks excludes the solutions to the Exercises.
- Notebooks starting S00-S08 are duplicates of the Notebooks starting 00-08, but this set of Notebooks include the solutions to the Exercises.
- Notebooks starting 09-10 provide plotting examples from Gaussian outputs.
- The notebooks are meant to be a resource for your reference after the workshop has concluded. The workshop will be a hands on coding demonstration. The notebooks include additional practice exercises.
- sub-directory - these materials accompany the "Using Hyak, Linux Operating System" workshop held on June 25, 2024. The walk-through tutorial is available on Hyak's documentation website (hyak.uw.edu).
- locator_NN_job.slurm - template single job SLURM submission script.
- locator_NN_array.slurm - template array job SLURM submission script.
- data sub-directory - Our adaptation of Populus trichocarpa genotype data and locations are licensed under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license. Original genotyping results available on DRYAD https://doi.org/10.5061/dryad.1051d. Data were published as part of a study https://doi.org/10.1111/1755-0998.12056.
- Using_Quantum_Chemistry_Software subdirectory - these materials accompany the "Using Gaussian for Computational Chemistry" workshop held on June 27, 2024.
-
Chem_Software_Hyak.pdf - This document will provide example files, helpful commands, and scripts so you are able to:
- Use the GaussView graphical user interface
- Create and submit Gaussian jobs
- Create and submit Quantum Espresso jobs
-
ethane.sh file - This file will allow slurm submission of the ethane.gjf file
-
Pseudopotential .upf files - The extra files used in the Quantum Espresso portion of the example.
- analysis sub-directory - these material accompany WS 4 "Data Analysis Basics in Python with
scikit-learn
andPyTorch
" workshop held on July 1, 2024.
- Complete Jupyter Notebook
- Jupyter Notebook with "TODO" or in-session code boxes for demonstration.
License information:
- Locator Neural Network is a copyright 2019 of C. J. Battey and released under a Non-Profit Open Software License 3.0 (NPOSL-3.0).
- Our adaptation of Populus trichocarpa genotype data and locations are licensed under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license.
- Some of the data and exercises used in WS 1 and WS 2 (above) are under the Copyright of Software Carpentry and are made available under the Creative Commons Attribution license (CC BY 4.0).