## ----options, echo = FALSE----------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>", 
  fig.width=7, 
  fig.height=5 
)


## ----data---------------------------------------------------------------------
library(incidence)
set.seed(1)
dat <- sample(1:50, 200, replace = TRUE, prob = 1 + exp(1:50 * 0.1))
sex <- sample(c("female", "male"), 200, replace = TRUE)

## ----i------------------------------------------------------------------------
i <- incidence(dat, interval = 2)
i
plot(i)

## ----sex----------------------------------------------------------------------
i.sex <- incidence(dat, interval = 2, group = sex)
i.sex
plot(i.sex)

## ----names--------------------------------------------------------------------
class(i)
is.list(i)
names(i)

## ----access-------------------------------------------------------------------
## use name
head(i$dates)

head(get_dates(i))

## ----dates1-------------------------------------------------------------------
date_bins <- get_dates(i)
class(date_bins)
class(dat)

date_bins

## ----date-dates1--------------------------------------------------------------
dat_Date <- as.Date("2018-10-31") + dat
head(dat_Date)
i.date <- incidence(dat_Date, interval = 2, group = sex)
i.date
get_dates(i.date)
class(get_dates(i.date))

## ----get-dates-integer--------------------------------------------------------
get_dates(i.date, count_days = TRUE)
get_dates(i, count_days = TRUE)

## ----get-dates-center---------------------------------------------------------
get_dates(i.date, position = "center")
get_dates(i.date, position = "center", count_days = TRUE)

## ----counts1------------------------------------------------------------------
counts <- get_counts(i)
class(counts)
storage.mode(counts)

counts
get_counts(i.sex)

## ----counts1.1----------------------------------------------------------------
dim(get_counts(i.sex))
dim(i.sex)
nrow(i.sex) # number of date bins
ncol(i.sex) # number of groups

## ----groups-------------------------------------------------------------------
# Number of groups
ncol(i.sex)
ncol(i)

# Names of groups
group_names(i.sex)
group_names(i)

# You can also rename the groups
group_names(i.sex) <- c("F", "M")
group_names(i.sex)

## ----as.data.frame------------------------------------------------------------
## basic conversion
as.data.frame(i)
as.data.frame(i.sex)

## long format for ggplot2
as.data.frame(i.sex, long = TRUE)

## ----timespan-----------------------------------------------------------------
get_timespan(i)
print(date_range <- range(get_dates(i)))
diff(date_range) + 1

## ----interval-----------------------------------------------------------------
get_interval(i)
diff(get_dates(i))

## ----n------------------------------------------------------------------------
get_n(i)

## ----n2-----------------------------------------------------------------------
colSums(get_counts(i.sex))

## ----isoweek------------------------------------------------------------------
library(outbreaks)
dat <- ebola_sim$linelist$date_of_onset
i.7 <- incidence(dat, "1 epiweek", standard = TRUE)
i.7
i.7$weeks

## ----isoweek-null-------------------------------------------------------------
i$weeks

## ----isoweek3-----------------------------------------------------------------
head(as.data.frame(i.7))