Create README.md

README.md

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+# california-inlabru-forecasts
+
+This folder contains all neccessary data and code to reproduce the forecasts and figures in "Pseudo-prospective testing of 5-year earthquake forecasts for California using inlabru", Bayliss, Naylor, Kamranzad and Main (submitted 2021).  
+UCERF3 data downloaded from https://pubs.usgs.gov/of/2013/1165/ in June 2019.  
+The strain rate model used in this work is available at https://platform.openquake.org/maps/82 and was downloaded in April 2021.   
+The exact versions are included in the 'Data' folder to ensure future reproducibility.
+The Comcat_catalogues folder contains the catalogues used to test the forecasts. The included code downloads these directly, but they are saved here in case of any changes to the catalogue.
+
+California_forecast_inlabru_testing.Rmd is an R-markdown file that runs all steps for model generation and then tests the models with the `pyCSEP` python package using the R package `reticulate`.  
+inlabru_import_functions.R contains functions to generate the two types of forecast as well as process some of the input data.  
+pycsep_testing.py runs only the pyCSEP testing using the inlabru forecasts, which are included in the 'Forecasts' folder.  
+
+-----------------------------------------------------------------------------------
+
+System information:
+R version 4.1.0 (2021-05-18)
+Platform: x86_64-w64-mingw32/x64 (64-bit)
+Running under: Windows 10 x64 (build 19041)
+AMD Ryzen 5 3600 processor, 64GB RAM
+
+R packages (forecast model assembly, fitting and simulation):  
+reticulate_1.20  
+RColorBrewer_1.1-2  
+maptools_1.1-1      
+dplyr_1.0.6       
+raster_3.4-13
+future.apply_1.8.1
+future_1.22.1       
+sf_1.0-2
+INLA_21.06.11      
+foreach_1.5.1     
+Matrix_1.3-3      
+fields_12.5       
+viridis_0.6.1      
+viridisLite_0.4.0   
+spam_2.7-0         
+dotCall64_1.0-1    
+rgeos_0.5-5        
+rgdal_1.5-23       
+inlabru_2.3.1      
+sp_1.4-5           
+ggplot2_3.3.5   
+
+
+Most packages can be downloaded directly from CRAN, with the exception of INLA which is using the current (as of December 2021) testing version,
+downloaded with `install.packages("INLA",repos=c(getOption("repos"),INLA="https://inla.r-inla-download.org/R/testing"), dep=TRUE)`  
+The latest version of inlabru should also be installed using `remotes::install_github("inlabru-org/inlabru", ref="devel")` 
+
+The forecast models take approx 2 hours each to run fully, including the simulation step and grid-based projections. 
+
+------------------------------------------------------------------------------
+
+Python packages (pycsep testing + plotting):  
+Python 3.8.5  
+pycsep 0.5.1  
+numpy 1.20.3  
+matplotlib  3.4.3  
+cartopy 0.18.0  
+pandas  1.3.4  
+seaborn 0.11.1  
+
+All python packages installed with conda, pyCSEP installed with `conda install --channel conda-forge pycsep`  
+File pycsep_testing.py runs these steps only.
+
+For further details on installation of the INLA package see https://www.r-inla.org/download-install  
+For further details on installation of inlabru see https://github.com/inlabru-org/inlabru  
+For further details on installation of pyCSEP, see https://docs.cseptesting.org/getting_started/installing.html  
+
+All websites last accessed 16/12/2021