## -----------------------------------------------------------------------------
#| echo: false
#| output: false
library(dplyr)
library(amp.dm)


## -----------------------------------------------------------------------------
#| echo: true
#| output: true
library(dplyr)
library(amp.dm)

xmpl <- system.file("example/NM.theoph.V1.csv",package="amp.dm")

# The read data function can read most common formats, for less common formats
# a manual function can passed to enable documenting the process
dat  <- read_data(xmpl, comment="Read example data")

# We can filter data with logging
dat2 <- filterr(dat,STIME<2, comment = "remove time-points") %>%
  select(ID,STIME) %>% mutate(FLAG=1)

# We can also join with logging 
dat3 <- left_joinr(dat2, dat, comment = "example join")



## -----------------------------------------------------------------------------
#| echo: true
#| output: true
get_log()


## -----------------------------------------------------------------------------
#| echo: true
#| output: false

cmnt("**Be aware** that *ID 1* is removed using `subset`")
dat4 <- subset(dat,ID!=1, select=-BMI)

srce(BMI,c(dat4.WEIGHT,dat4.HEIGHT),'d')
dat4$BMI <- dat4$WEIGHT/(dat4$HEIGHT)^2 


## -----------------------------------------------------------------------------
#| echo: true
#| output: asis
# Note it is easier to directly use inline code, e.g.: `r cmnt_print()` 
cat(cmnt_print())


## -----------------------------------------------------------------------------
#| echo: true
#| output: true
# This is also available in tabulation functions e.g. define_tbl
get_log()$srce_nfo


## -----------------------------------------------------------------------------
general_tbl(data.frame(result="this is a test"))