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library(rstanarm)
library(simsurv)

?stan_surv

data("frail")

m_frail <- stan_surv(
  formula = Surv(eventtime, status) ~ trt + (1 | site), 
  data    = frail[1:40,], 

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# set colours for plot
colours <- RColorBrewer::brewer.pal(10, 'Spectral')

# function to make points lighter but not transparent
alpha_hex <- function(hex_code, alpha = 1){
  # split by ',' and extract number
  temp <- monochromeR::hex_to_rgb(hex_code) %>%
    str_split(., ',') %>%
    .[[1]] %>%
    parse_number()

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# have a look at whether having multiple 0 values impacts the results of model fitting to TPCs

# load libraries
librarian::shelf(rTPC, nls.multstart, tidyverse, broom)

# simulate data using Sharpe Schoolfield model
d_simulate <- tibble(temp = seq(from = 10, to = 55, length.out = 10),
                     rate = sharpeschoolhigh_1981(temp = temp, r_tref = 0.5, e = 0.6, eh = 5, th = 33, tref = 17.5)) %>%
  # add noise
  mutate(noise = rnorm(n(), 0, 0.1),

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# try write script to extract data/code accessibility statement

# try with BES journals first. The trick is in grabbing the correct node (whatever that is)
mee_url <- 'https://doi.org/10.1111/2041-210X.13585'
functionalecology_url <- 'https://doi.org/10.1111/1365-2435.14422'
animalecology_url <- 'https://doi.org/10.1111/1365-2656.13983'
appliedecology_url <- 'https://doi.org/10.1111/1365-2664.14474'

# library
library(rvest)

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# random flextable example to put a symbol in a column

librarian::shelf(tidyverse, flextable, officer)

data(mpg)

# copyright symbol
copyright_symbol <- "\U00A9"
black_dot <- "\U2B24" 

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# nimble and tidybayes example

# load packages
librarian::shelf(tidybayes, nimble, tidyverse, bayesplot, ggdist, nlist)

# run example from runMCMC

code <- nimbleCode({
  mu ~ dnorm(0, sd = 1000)
  sigma ~ dunif(0, 1000)

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# example of using cowplot and patchwork to make a plot with legends in the bottom right of a four panel plot

# load in packages
librarian::shelf(tidyverse, patchwork, cowplot)

# make a random plot with colour
p1 <- ggplot(mpg, aes(hwy, cty, col = class)) +
  geom_point()

# make other plot with colour on

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# try weighted bootstrapping of many curves
# combines approach from weighted bootstrapping and bootstrapping many curves
# https://padpadpadpad.github.io/rTPC/articles/bootstrapping_many_curves.html
# https://padpadpadpad.github.io/rTPC/articles/weighted_bootstrapping.html

# load in packages
librarian::shelf(tidyverse, rTPC, nls.multstart, broom, minpack.lm, car)

# load in data
data("chlorella_tpc")

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# example of using cowplot and patchwork to make a plot with legends in the bottom right of a four panel plot

# load in packages
librarian::shelf(tidyverse, patchwork, cowplot)

# make a random plot with colour
p1 <- ggplot(mpg, aes(hwy, cty, col = class)) +
  geom_point()

# make other plot with colour on

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# random modelling example for Stephen

# load in packages
librarian::shelf(rTPC,tidyverse, nls.multstart)

# create data
d <- chlorella_tpc %>%
  filter(curve_id < 4) %>%
  nest(data = c(everything(), -curve_id))