18 changed files with 220 additions and 113 deletions
@ -1,28 +1,40 @@ |
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#' Retrieve CDC U.S. Coverage Map |
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#' Retrieve CDC U.S. Basemaps |
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#' |
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#' The CDC FluView application uses a composite basemap of coverage areas |
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#' within the United States that elides and scales Alaska, Hawaii and |
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#' Puerto Rico and provides elided and scaled breakouts for New York City |
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#' and the District of Columbia.\cr |
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#' The CDC FluView application uses a composite basemaps of coverage areas |
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#' within the United States that elides and scales Alaska, Hawaii, |
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#' Puerto Rico & the Virgin Islands and some further provide elided and scaled |
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#' breakouts for New York City and the District of Columbia.\cr |
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#' \cr |
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#' The basemap provides polygon identifiers by: |
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#' \cr |
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#' - `STATE_FIPS` |
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#' - `STATE_ABBR` |
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#' - `STATE_NAME` |
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#' - `HHS_Region` |
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#' - `FIPSTXT`) |
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#' \cr |
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#' This function retrieves the shapefile, projects to EPSG:5069 and |
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#' This function retrieves the given shapefile, projects to EPSG:5069 and |
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#' returns it as an `sf` (simple features) object. |
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#' |
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#' @md |
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#' @export |
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#' @param basemap select the CDC basemap. One of: |
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#' - "`national`": outline of the U.S. + AK, HI, PR + VI |
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#' - "`hhs`": outline of the U.S. + HHS Region Outlines + AK, HI, PR + VI |
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#' - "`census`": outline of the U.S. + Census Region Outlines + AK, HI, PR + VI |
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#' - "`states`": outline of the U.S. + State Outlines + AK, HI, PR + VI |
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#' - "`spread`": outline of the U.S. + State Outlines + AK, HI, PR + VI & Guam |
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#' - "`surv`": outline of the U.S. + State Outlines + AK, HI, PR + VI |
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#' @note These are just the basemaps. You need to pair it with the data you wish to visualize. |
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#' @examples \dontrun{ |
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#' plot(cdc_coverage_map()) |
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#' plot(cdc_basemap("national")) |
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#' } |
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cdc_coverage_map <- function() { |
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xsf <- sf::st_read(.cdc_basemap, quiet=TRUE, stringsAsFactors=FALSE) |
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cdc_basemap <- function(basemap = c("national", "hhs", "census", "states", "spread", "surv")) { |
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|
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switch( |
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basemap, |
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national = .national_outline, |
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hhs = .hhs_subregions_basemap, |
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census = .census_divisions_basemap, |
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states = .states_basemap, |
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spread = .spread_basemap, |
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surv = .surv_basemap |
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) -> selected_map |
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|
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xsf <- sf::st_read(selected_map, quiet=TRUE, stringsAsFactors=FALSE) |
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sf::st_crs(xsf) <- 4326 |
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sf::st_transform(xsf, 5069) |
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|
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} |
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|
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@ -1,10 +1,10 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/agd-ipt.r |
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\name{agd_ipt} |
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\alias{agd_ipt} |
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\name{age_group_distribution} |
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\alias{age_group_distribution} |
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\title{Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories} |
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\usage{ |
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agd_ipt() |
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age_group_distribution() |
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} |
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\description{ |
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Retrieves the age group distribution of influenza positive tests that are reported by |
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@ -0,0 +1,37 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/coverage-map.r |
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\name{cdc_basemap} |
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\alias{cdc_basemap} |
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\title{Retrieve CDC U.S. Basemaps} |
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\usage{ |
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cdc_basemap(basemap = c("national", "hhs", "census", "states", "spread", |
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"surv")) |
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} |
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\arguments{ |
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\item{basemap}{select the CDC basemap. One of: |
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\itemize{ |
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\item "\code{national}": outline of the U.S. + AK, HI, PR + VI |
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\item "\code{hhs}": outline of the U.S. + HHS Region Outlines + AK, HI, PR + VI |
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\item "\code{census}": outline of the U.S. + Census Region Outlines + AK, HI, PR + VI |
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\item "\code{states}": outline of the U.S. + State Outlines + AK, HI, PR + VI |
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\item "\code{spread}": outline of the U.S. + State Outlines + AK, HI, PR + VI & Guam |
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\item "\code{surv}": outline of the U.S. + State Outlines + AK, HI, PR + VI |
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}} |
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} |
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\description{ |
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The CDC FluView application uses a composite basemaps of coverage areas |
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within the United States that elides and scales Alaska, Hawaii, |
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Puerto Rico & the Virgin Islands and some further provide elided and scaled |
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breakouts for New York City and the District of Columbia.\cr |
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\cr |
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This function retrieves the given shapefile, projects to EPSG:5069 and |
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returns it as an \code{sf} (simple features) object. |
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} |
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\note{ |
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These are just the basemaps. You need to pair it with the data you wish to visualize. |
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} |
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\examples{ |
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\dontrun{ |
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plot(cdc_basemap("national")) |
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} |
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} |
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@ -1,32 +0,0 @@ |
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% Generated by roxygen2: do not edit by hand |
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% Please edit documentation in R/coverage-map.r |
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\name{cdc_coverage_map} |
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\alias{cdc_coverage_map} |
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\title{Retrieve CDC U.S. Coverage Map} |
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\usage{ |
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cdc_coverage_map() |
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} |
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\description{ |
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The CDC FluView application uses a composite basemap of coverage areas |
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within the United States that elides and scales Alaska, Hawaii and |
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Puerto Rico and provides elided and scaled breakouts for New York City |
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and the District of Columbia.\cr |
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\cr |
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The basemap provides polygon identifiers by: |
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\cr |
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\itemize{ |
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\item \code{STATE_FIPS} |
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\item \code{STATE_ABBR} |
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\item \code{STATE_NAME} |
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\item \code{HHS_Region} |
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\item \code{FIPSTXT}) |
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\cr |
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This function retrieves the shapefile, projects to EPSG:5069 and |
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returns it as an \code{sf} (simple features) object. |
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} |
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} |
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\examples{ |
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\dontrun{ |
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plot(cdc_coverage_map()) |
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} |
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} |
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@ -1,26 +1,44 @@ |
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context("basic functionality") |
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test_that("we can do something", { |
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|
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skip_on_cran() |
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|
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expect_that(agd_ipt(), is_a("data.frame")) |
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|
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expect_that(geographic_spread(), is_a("data.frame")) |
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expect_that(surveillance_areas(), is_a("data.frame")) |
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|
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expect_that(state_data_providers(), is_a("data.frame")) |
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expect_that(hospitalizations("flusurv"), is_a("data.frame")) |
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expect_that(hospitalizations("eip"), is_a("data.frame")) |
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expect_that(hospitalizations("eip", "Colorado"), is_a("data.frame")) |
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expect_that(hospitalizations("ihsp"), is_a("data.frame")) |
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expect_that(hospitalizations("ihsp", "Oklahoma"), is_a("data.frame")) |
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expect_that(ilinet("national"), is_a("data.frame")) |
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expect_that(ilinet("hhs"), is_a("data.frame")) |
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expect_that(ilinet("census"), is_a("data.frame")) |
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expect_that(ilinet("state"), is_a("data.frame")) |
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|
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expect_that(ili_weekly_activity_indicators(2017), is_a("data.frame")) |
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|
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expect_that(pi_mortality("national"), is_a("data.frame")) |
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expect_that(pi_mortality("state"), is_a("data.frame")) |
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expect_that(pi_mortality("region"), is_a("data.frame")) |
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expect_that(state_data_providers(), is_a("data.frame")) |
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|
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expect_that(surveillance_areas(), is_a("data.frame")) |
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expect_that(who_nrevss("national"), is_a("list")) |
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expect_that(who_nrevss("hhs"), is_a("list")) |
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expect_that(who_nrevss("census"), is_a("list")) |
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expect_that(who_nrevss("state"), is_a("list")) |
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expect_that(cdc_coverage_map(), is_a("sf")) |
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|
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expect_that(cdc_basemap("national"), is_a("sf")) |
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expect_that(cdc_basemap("hhs"), is_a("sf")) |
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expect_that(cdc_basemap("census"), is_a("sf")) |
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expect_that(cdc_basemap("states"), is_a("sf")) |
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expect_that(cdc_basemap("spread"), is_a("sf")) |
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expect_that(cdc_basemap("surv"), is_a("sf")) |
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|
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|
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}) |
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|
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