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intervals.R
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/
intervals.R
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## Interval dataframe and merged interval-incubation dataframe
library(bbmle)
library(ggplot2)
library(dplyr)
library(purrr)
library(tidyr)
library(cowplot)
library(ggforce)
library(shellpipes)
theme_set(theme_bw())
loadEnvironments()
maxDays <- 1000
minDays <- 0
tidyInts <- (rdsRead()
%>% select(dateSerial
, dateGen
)
%>% gather(key=Type,value=Days, everything())
%>% filter(between(Days, minDays, maxDays)) ## experimenting removing outliers
)
print(dim(tidyInts))
## taking out wait time
#wait_times <- tidyInts %>% filter(Type == "wait_time")
interval_df <- (tidyInts
%>% transmute(Type = ifelse(grepl("Serial",Type),"Serial","Generation")
, Days
)
%>% group_by(Type)
%>% mutate(Mean = mean(Days, na.rm=TRUE)
, SD = mean(Days, na.rm=TRUE)
)
)
interval_merge <- (interval_df
%>% bind_rows(.,incubations)
%>% ungroup()
%>% mutate(Type = factor(Type, levels=c("Serial","Generation"
, "Dogs", "Biter_rep", "Non-Biter", "Biter")
, labels=c("Serial Interval", "Generation Interval"
, "Incubation Period: Dogs"
, "Weighted Incubation Period"
, "Incubation Period: Non-Biter"
, "Incubation Period: Biter"
)
)
)
)
print(interval_merge %>% select(-Days) %>% distinct())
print(interval_merge %>% group_by(Type) %>% summarise(count = n()))
saveVars(interval_merge, interval_df, bites)