knitr::opts_chunk$set(echo = TRUE) library(geosciencebc2019008)
# load catalogue entire_cat <- read_csv('../input/catalogs/20190430_combined_catalogue.csv') %>% sf::st_as_sf(coords = c('X', 'Y'), crs = 26910, remove = FALSE) %>% dplyr::select(-X1) # npmma catalogue npgmma_extents <- sf::st_read('../input/shapefiles/npgmma_extent.shp') %>% st_transform(crs = 26910) npgmma_cat = entire_cat %>% dplyr::filter(st_contains(npgmma_extents,entire_cat,sparse=FALSE)) # ksmma catalogue ksmma_extents <- sf::st_read('../input/shapefiles/ksmma_extent.shp') %>% st_transform(crs = 26910) ksmma_cat = entire_cat %>% dplyr::filter(st_contains(ksmma_extents,entire_cat,sparse=FALSE))
p1 = cat_bvalue_plot(entire_cat, 'ALL') + ggsave('../output/b_value_plots/entire_cat.jpeg', width=8, height=4, unit='in', dpi=600) p2 = cat_bvalue_plot(npgmma_cat, 'NPGMMA') + ggsave('../output/b_value_plots/npgmma.jpeg', width=8, height=4, unit='in', dpi=600) p3 = cat_bvalue_plot(ksmma_cat, 'KSMMA') + ggsave('../output/b_value_plots/ksmma.jpeg', width=8, height=4, unit='in', dpi=600)
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