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Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"
Dec 21, 2020 - School of Engineering and Applied Science
Bennett, Jeffrey A.; DeCarolis, Joseph F.; Clarens, Andres F., 2020, "Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"", https://doi.org/10.18130/V3/QB0NPX, University of Virginia Dataverse, V1
This archive includes the model and data used to produce the publication "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico" by Bennett et al. The temoatools.zip file is an archived version of temoatools, the Python library used to run and analyze the simulations, along with data i...
PR_RenewableResourceEval.py
Dec 21, 2020 - Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"
Python Source Code - 2.2 KB - MD5: 99b6dc6ffd40a81933b1e9dcb6f5c375
https://github.com/EnergyModels/RenewableResourceEval Settings to run RenewableResourceEval.py for Puerto Rico
README.md
Dec 21, 2020 - Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"
Markdown Text - 3.9 KB - MD5: 510605d2861a143e2a5ac657e0059f70
RenewableResourceEval.py
Dec 21, 2020 - Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"
Python Source Code - 13.9 KB - MD5: ac429cc509ae0e102f0bf6d39c93c2d1
https://github.com/EnergyModels/RenewableResourceEval ArcMap script to quantify renewable resources
temoatools.zip
Dec 21, 2020 - Model and data for "Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico"
ZIP Archive - 9.7 MB - MD5: 6fa777f3e0f1fd1ef74040c5e4c53bc8
Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
Dec 15, 2020
Driscoll, Kevin; Nooney, Laine; Allen, Kera, 2020, "Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User", https://doi.org/10.18130/V3/IHCHYM, University of Virginia Dataverse, V1, UNF:6:yKhFoCPXQu+cbQYYCqIyBw== [fileUNF]
Data, code, and documentation for reproducing the figures published in Nooney, Laine, Kevin Driscoll, and Kera Allen. “From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User.” Information & Culture 55, no. 2 (June 18, 2020): 105–29.
letters_pages.1980-1982.tab
Dec 15, 2020 - Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
Tabular Data - 3.1 KB - 5 Variables, 75 Observations - UNF:6:Pjksq+M44y9f+WQM5vyNOg==
Page and letter counts for three computer magazines: Byte, Creative Computing, and Softalk
README.txt
Dec 15, 2020 - Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
Plain Text - 7.1 KB - MD5: 2bf9e899996630f169fef900fcbc6475
Definitions for the variables in the data files, details on running the Python code, and a copy of the coding form used in the content analysis.
Replication for From Programming to Products.html
Dec 15, 2020 - Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
HTML - 1.7 MB - MD5: 067cc6dd84dda2c7fc444ad9ea3ba53f
Snapshot of the Python code including inline output
Replication for From Programming to Products.ipynb
Dec 15, 2020 - Replication Data for: From Programming to Products: Softalk Magazine and the Rise of the Personal Computer User
Jupyter Notebook - 1.0 MB - MD5: 51e8d2d9844612cc5a97938160b549e1
Code for reproducing the figures. See README for details on setting up the Python environment.
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