# These operations work best with the pipe and other tidyverse conventions
library(dplyr)
library(magrittr)
library(purrr)
library(tidyr)
library(ggplot2)
# one sample
sample_3 <- example_LL_data[9:12, ] %>%
left_join(example_tin_tares$`2020-05-24`) %>%
add_w()
ggflowcurve(sample_3)
# three samples, faceted
example_LL_data %>%
left_join(example_tin_tares$`2020-05-24`) %>%
add_w() %>%
ggflowcurve()+
facet_wrap(~expt_mix_num)
# add colors and vertical arrows mapped to the LL in order to highlight the blow count of
# 25
lines_data <- example_LL_data %>%
left_join(example_tin_tares$`2020-05-24`) %>%
add_w() %>%
group_by(expt_mix_num) %>%
nest() %>%
mutate(LL = map_dbl(data, compute_LL),
blow_count = 25) %>%
ungroup()
fulldata <- example_LL_data %>%
left_join(example_tin_tares$`2020-05-24`) %>%
add_w()
ggflowcurve(fulldata, color = factor(expt_mix_num))+
geom_segment(data= lines_data,
aes(x= blow_count, xend= blow_count, y= -Inf, yend = LL*0.99),
arrow = arrow(length = unit(0.1, "in"))) +
labs(color= "Mix number")+
facet_wrap(~expt_mix_num)
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