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plot.incidence2() now works again when applied to 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
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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.