Merge branch 'main' into v1.2

src/main/R/Analysis/srv.R

@@ -150,9 +150,9 @@ p2_aggr <- ggplot(data=aggr, mapping =  aes(x=1, y=share, fill=mode)) +
   scale_fill_locuszoom() +
   theme_void()
 
-g <- arrangeGrob(p1_aggr, p2_aggr, ncol = 2)
+g <- arrangeGrob(p1_aggr, p2_aggr, nrow = 2)
 ggsave(filename = "modal-split.png", path = ".", g,
-       width = 12, height = 2, device='png', dpi=300)
+       width = 6, height = 2, device='png', dpi=300)
 
 
 #########
@@ -186,4 +186,78 @@ shortDistance <- sum(filter(sim, dist_group=="0 - 1000")$trips)
 numTrips = (shortDistance - calib_sum * tripShare) / (tripShare - 1)
 
 
+########################
+
+srv0 <- srv %>%
+  filter(dist_group=="0 - 1000") %>%
+  mutate(sum_group = sum(trips))
+
+srv13 <- srv %>%
+  filter(dist_group=="1000 - 3000") %>%
+  mutate(sum_group = sum(trips))
+
+srv35 <- srv %>%
+  filter(dist_group=="3000 - 5000") %>%
+  mutate(sum_group = sum(trips))
+
+srv510 <- srv %>%
+  filter(dist_group=="5000 - 10000") %>%
+  mutate(sum_group = sum(trips))
+
+srv1020 <- srv %>%
+  filter(dist_group=="10000 - 20000") %>%
+  mutate(sum_group = sum(trips))
+
+srv20 <- srv %>%
+  filter(dist_group=="20000+") %>%
+  mutate(sum_group = sum(trips))
+
+srv <- bind_rows(srv0,srv13,srv35,srv510,srv1020,srv20) %>%
+  mutate(share_group = trips / sum_group)
+
+sim0 <- sim %>%
+  filter(dist_group=="0 - 1000") %>%
+  mutate(sum_group = sum(trips))
+
+sim13 <- sim %>%
+  filter(dist_group=="1000 - 3000") %>%
+  mutate(sum_group = sum(trips))
+
+sim35 <- sim %>%
+  filter(dist_group=="3000 - 5000") %>%
+  mutate(sum_group = sum(trips))
+
+sim510 <- sim %>%
+  filter(dist_group=="5000 - 10000") %>%
+  mutate(sum_group = sum(trips))
+
+sim1020 <- sim %>%
+  filter(dist_group=="10000 - 20000") %>%
+  mutate(sum_group = sum(trips))
+
+sim20 <- sim %>%
+  filter(dist_group=="20000+") %>%
+  mutate(sum_group = sum(trips))
+
+sim <- bind_rows(sim0,sim13,sim35,sim510,sim1020,sim20) %>%
+  mutate(share_group = trips / sum_group)
+
+by_distance <- bind_rows(filter(srv, mode!="total_distance_distribution"), sim) %>%
+  mutate(mode=fct_relevel(mode, "walk", "bike", "pt", "ride", "car"))
+
+dist_order <- factor(by_distance$dist_group, level = levels)
+dist_order <- fct_explicit_na(dist_order, "100000+")
+
+g <- ggplot(by_distance, aes(y=share_group, x=source, fill=mode)) +
+  labs(subtitle = paste("Kelheim scenario", substring(f, 52)), x="distance [m]", y="share") +
+  geom_bar(position="stack", stat="identity", width = 0.5) +
+  facet_wrap(dist_order, nrow = 1) +
+  scale_fill_locuszoom() +
+  theme_minimal()
+g
+
+ggsave(filename = "modal-distance-distribution-relative.png", path = ".", g,
+       width = 12, height = 10, device='png', dpi=300)
+
+