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Merge pull request #625 from cmu-delphi/lcb/doc-fixups
Doc cleanup
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DESCRIPTION

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Type: Package
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Package: epiprocess
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Title: Tools for basic signal processing in epidemiology
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Version: 0.11.6
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Version: 0.11.7
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Authors@R: c(
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person("Jacob", "Bien", role = "ctb"),
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person("Logan", "Brooks", , "[email protected]", role = c("aut", "cre")),

NEWS.md

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- `epix_as_of_current()` introduced as an alias for `epix_as_of(.$versions_end)`.
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- Added `dplyr::filter` implementation for `epi_archive`s.
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## Improvements
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- Various documentation has been updated, simplified, and improved with better
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examples.
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# epiprocess 0.11
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## Highlights
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`{epiprocess}` should once again not require Rtools or a compiler to be able to
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install! We've also updated some function interfaces to be more consistent
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throughout the package & with tidyverse, and improved the generality of and
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fixed bugs in various functions and documentation.
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## Breaking changes
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- `growth_rate()` argument order and names have changed. You will need to

R/archive.R

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#' Perform second (costly) round of validation that `x` is a proper `epi_archive`
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#'
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#' Does not validate `geo_type` or `time_type` against `geo_value` and
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#' `time_value` columns. These are assumed to have been set to compatibly.
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#'
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#' @return * Of `validate_epi_archive`: an `epi_archive`,
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#' [invisibly][base::invisible] (or raises an error if `x` was invalid)
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#'

R/autoplot.R

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#' Automatically plot an epi_df or epi_archive
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#'
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#' @param object,x An `epi_df` or `epi_archive`
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#' @param ... <[`tidy-select`][dplyr_tidy_select]> One or more unquoted
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#' @param ... <[`tidy-select`][dplyr::dplyr_tidy_select]> One or more unquoted
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#' expressions separated by commas. Variable names can be used as if they
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#' were positions in the data frame, so expressions like `x:y` can
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#' be used to select a range of variables.
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#' @param .max_facets `r lifecycle::badge("deprecated")`
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#' @param .facet_filter Select which facets will be displayed. Especially
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#' useful for when there are many `geo_value`'s or keys. This is a
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#' <[`rlang`][args_data_masking]> expression along the lines of [dplyr::filter()].
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#' <[`rlang`][rlang::args_data_masking]> expression along the lines of [dplyr::filter()].
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#' However, it must be a single expression combined with the `&` operator. This
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#' contrasts to the typical use case which allows multiple comma-separated expressions
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#' which are implicitly combined with `&`. When multiple variables are selected

R/epi_df.R

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#' which can be seen as measured variables at each key. In brief, an `epi_df`
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#' represents a snapshot of an epidemiological data set at a point in time.
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#'
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#' @details An `epi_df` is a tibble with (at least) the following columns:
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#' @details An `epi_df` is a kind of tibble with (at least) the following
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#' columns:
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#'
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#' - `geo_value`: A character vector representing the geographical unit of
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#' observation. This could be a country code, a state name, a county code,
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#' etc.
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#' - `time_value`: A date or integer vector representing the time of observation.
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#'
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#' Other columns can be considered as measured variables, which we also refer to
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#' as signal variables. An `epi_df` object also has metadata with (at least)
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#' the following fields:
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#' as indicators or signals. An `epi_df` object also has metadata with (at
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#' least) the following fields:
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#'
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#' * `geo_type`: the type for the geo values.
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#' * `time_type`: the type for the time values.
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#' * `as_of`: the time value at which the given data were available.
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#'
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#' Most users should use `as_epi_df`. The input tibble `x` to the constructor

R/grouped_epi_archive.R

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}
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#' @rdname epix_slide
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#'
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#' @importFrom data.table key address rbindlist setDF copy
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#' @importFrom tibble as_tibble new_tibble validate_tibble
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#' @importFrom dplyr group_by groups
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#' @importFrom rlang !! !!! enquo quo_is_missing enquos is_quosure sym syms
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#' env missing_arg
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#'
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#' @export
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epix_slide.grouped_epi_archive <- function(
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.x,

R/inline-roxygen.R

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#'
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#' @keywords internal
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tidyselect_arg_roxygen <- '
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<[`tidy-select`][dplyr_tidy_select]> An unquoted column
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<[`tidy-select`][dplyr::dplyr_tidy_select]> An unquoted column
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name (e.g., `cases`), multiple column names (e.g., `c(cases, deaths)`),
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[other tidy-select expression][tidyselect::language], or a vector of
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characters (e.g. `c("cases", "deaths")`). Variable names can be used as if

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