William Jenkins NeptuneProjects
NeptuneProjects
/ rapids_cuml_demo.py
Last active
October 27, 2020 23:28
A quick example of how you can use CUML in place of the scikit-learn library for GPU-based machine learning functions.
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| """ | |
| Written by Billy Jenkins, 27 Oct 2020, Scripps Institution of Oceanography | |
| wjenkins (at) ucsd.edu | |
| Demonstration of interchangeability between sk-learn & CUML libraries. | |
| For more information, visit https://docs.rapids.ai/api/cuml/stable/ | |
| Unfortunately, CUML only supports 'Linux-like' platforms at this time, so for | |
| Apple or Windows machines, you are stuck with the scikit-learn library and your | |
| CPU. If you have a Linux machine with a CUDA device available, the CUML |
NeptuneProjects
/ MassDownloader.py
Created
August 8, 2020 13:46
Python-based FDSN mass downloader based on Obspy
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| def mass_data_downloader(savepath, start='20141201', stop='20161201', | |
| Network='XH', Station='*', Channel='HH*'): | |
| ''' | |
| This function uses the FDSN mass data downloader to automatically download | |
| data from the XH network deployed on the RIS from Nov 2014 - Nov 2016. | |
| More information on the Obspy mass downloader available at: | |
| https://docs.obspy.org/packages/autogen/obspy.clients.fdsn.mass_downloader.html | |
| Inputs: | |
| savepath: "[string to savepath]" | |
| start: "YYYYMMDD" |