Uses a vectory specifying whether data falls into an event to reshape data, aligning by the onset of the event
align_events(
df,
df_isevent,
dovars,
leng_threshold,
before,
after,
do_norm = FALSE,
nbins = 6,
normbin = 2
)
A data frame containing all data continuously along time,
required columns: "site", "date"
.
A data frame nrow(df_isevent)==nrow(df)
specifying
whether respective dates (matching dates in df
), satisfy a condition
that is used to define events. Events are then derived by this function as
consecutive dates where this condition is satisfied (the minimum length for
defining an event is given by argument leng_threshold
). Required
columns in both df
and df_isevent
: "site", "date"
A vector of character strings specifying which columns
(by column name) of df
to re-arrange.
An integer specifying the minimum number of consecutive
dates required to define an event. All events of length lower than
leng_threshold
are dropped.
An integer specifying the number of days before the event onset to be retained in re-arranged data
An integer specifying the number of days after the event onset to be retained in re-arranged data
A logical specifying whether re-arranged data is to be
normalised by the median value of the bin
(number of bins given by argument nbins
) before the event onset,
given by argument normbin
. Defaults to FALSE
.
An integer, specifying the number of bins used to determine median values before event onset. Only used when codedo_norm=TRUE. Defaults to 6.
An integer, specifying the bin number just before the event onset, used for normalisation. Only used when codedo_norm=TRUE. Defaults to 2.
A named list of data frames (list( "df_dday", "df_dday_aggbydday")
)
containing data from all events and before + after
dates (relative
to event onset) with additional columns named "inst"
, defining the
event number (instance), and "dday"
, defining the date relative to the
respective event onset. The data frame "df_dday"
contains rearranged,
but otherwise unchanged data (unless do_norm
=TRUE). The data frame
"df_dday_aggbydday"
containes data aggregated across events with the
mean and quantiles given for each "dday"
.
df_alg <- align_events( df, truefalse, before=30, after=300 )
#> Error in df %>% left_join(df_isevent, by = c("site", "date")) %>% mutate(idx_df = 1:n()): could not find function "%>%"