Experimental: When calling incidence() if users specify an integer(ish)
interval on an (integerish) date input these inputs will be coerced in
to grates_int_period objects. This fixes
https://github.com/reconverse/incidence2/issues/121 and (broadly) restores
earlier behaviour of the incidence() function. This functionality is subject
to change and, for that reason, is not widely documented.
library(incidence2)
x <- data.frame(onset = c(1, 3, 4, 4, 3, 4, 10))
# 2.5.0 release would error, e.g.
incidence(x, "onset", interval = 1)
#> Error in as_period.default(): Not implemented for class [numeric].
# This release - now works
incidence(x, "onset", interval = 1)
#> # incidence: 4 x 3
#> # count vars: onset
#> date_index count_variable count
#> <intper> <chr> <int>
#> 1 1 onset 1
#> 2 3 onset 2
#> 3 4 onset 3
#> 4 10 onset 1
incidence() gains a fill parameter. This is passed to complete_dates()
so is only valid when the argument complete_dates = TRUE.
For convenience we now reexport select() from
dplyr as well as
unnest() and unpack() from tidyr.
Alt text has been added to all vignette images.
Improved input checking for keep_first() and keep_last().
Temporarily remove the ympes dependency due to up stream changes.
No other user facing changes.
The bootstrap_incidence(), estimate_peak() and first_peak() functions,
and have been integrated from the downstream
i2extras package.
Added group-aware methods for common generics in base R, dplyr and tidyr:
split.incidence2()mutate.incidence2()summarise.incidence2()nest.incidence2()Added coercion methods for tibble and data.table:
as_tibble.incidence2()as.data.table.incidence2()New methods, $<-.incidence2 and rbind.incidence2, that drop the incidence2
class if the required invariants are broken.
New functions incidence_() and regroup_() that work similar to their
existing namesakes save for additional support for
tidy-select
semantics in some of their arguments.
Named vectors can now be used for the groups and counts arguments of
incidence() to allow renaming prior to aggregation. Previously this was
only possible with the date_index input.
incidence() gains a complete_dates argument defaulting to FALSE. If set
this is equivalent of a call to incidence() followed by a call to
complete_dates() with the default arguments. Users wanting more flexibility
can still call the complete_dates() function with different arguments.
All of the aforementioned new methods would previously have dispatched on the
underlying data.frame method. If you were relying on this behaviour then you
will now need to add a call to as.data.frame() prior to continuing your
pipeline.
incidence2 objects are now built upon tibbles rather than standard data
frames. This means where we do not provide methods for incidence2 objects
tibble (as opposed to data.frame) methods will be called. An overview of the
differences between tibbles and data.frames can be found at
https://tibble.tidyverse.org/articles/invariants.html.
incidence() now warns if a count variable contains missing values and
encourages users to handle these prior to calling incidence().
The Package now has a hard dependency on the R version (>= 4.1.0).
plot.incidence2() now works again when applied to incidence2 objects with
a grates_period date_index. This was inadvertently broken in the 2.2.1
release. Thanks to @Bisaloo for the report (#110).plot.incidence2() gains arguments n_breaks, fill, show_cases and
legend allowing for a wider range of plot styles. See
vignette("incidence2", package = "incidence2") for examples.interval = "day" or interval = daily in a call to incidence
will force the resultant date_index variable to be a Date. Functionally
this is a wrapper around as.Date() that ensures the underlying data are
whole numbers and that time zones are respected.incidence() will now warn if objects are created with POSIXct columns.
The motivation for this is that, internally, POSIXct objects are represented
as seconds since the UNIX epoch and, in our experience, this level of
granularity is not normally desired for aggregation.
The by parameter of complete_dates() is now defunct. This was previously
passed to an underlying seq function when, in practice, it should always
have been forced to 1 to match the precision of the underlying date_index.
complete_dates() will now error if called on an input with a allow_POSIXct = TRUE
to maintain old behaviour.
Version 2.0.0 is a major, breaking release of incidence2. We have undertaken a significant refactor that both simplifies the underlying code base and makes the user interface more consistent and robust. Although the main changes are highlighted below, users are strongly advised to read through the accompanying documentation and vignettes.
We no longer support NSE (e.g. tidyselect semantics) within the package. Our motivation for removing support for NSE are both the complexity it can bring to the underlying code (making long term maintenance harder) and the complexity it can cause for other users / developers who want to build on top of incidence2.
new_incidence(), validate_incidence(), build_incidence(), get_n(),
get_interval(), get_timespan() and facet_plot() are now defunct and
will error if called.
complete_counts() is now renamed complete_dates() and gains two new
parameters, expand and by. If expand is TRUE (default) then
complete_dates() will attempt to use
function(x) seq(min(x), max(x), by = by) to generate a complete sequence of
dates.
The incidence() function now always returns output in long format with
dedicated columns for the count variables and values (set by arguments
count_names_to and count_values_to).
incidence() is now less flexible in what it can accept for the interval
argument. For more complex date groupings users are encouraged to perform
their require data transformations prior to calling incidence().
The default plotting of incidence objects as been greatly simplified. Sensible defaults have been chosen to enable a quick visual overview of incidence objects but users are advised to call ggplot2 directly for more bespoke plotting.
cumulate() functionality (previously deprecated in 1.2.0).fill argument in complete_counts() is now 0 rather than NA.incidence() when more than one column was given for the date_index.new_incidence(): A minimal incidence constructor.validate_incidence(): Check for internal consistency of incidence-like object.build_incidence(): Allows you to construct an incidence object whilst specifying
your own date grouping function.format.incidence()cumulate() will now give a deprecation error. We have removed the function
to avoid users erroneously regressing against a cumulative count.incidence() when dates were a character vector and the the
default, daily, interval was specified.dplyr to handle list based columns (e.g. record-type objects from
vctrs). For data.frames with only atomic columns, data.table is still used.complete_counts().plot() and facet_plot() now have a centre_dates argument which can be
set to FALSE to get histogram-esque date labels for single month, quarter
and yearweek groupings.Due to multiple changes in the underlying representation of incidence2 objects this release may possibly break old workflows particularly those relying on the old implementations of date grouping:
grates for
date grouping. This introduces the s3 classes yrwk, yrmon, yrqtr, yr,
period and int_period as well as associated constructors which incidence
now builds upon. As a result of this the
aweek dependency has been dropped.keep_first and keep_last functions.incidence objects now faster due to underlying use of
data.table.show_cases = TRUE (see #42).count variable of a pre-aggregated input to
incidence function.