From bda3f1726dde13aeeec8b2e8795146f265c83343 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 4 May 2022 17:50:06 -0700 Subject: [PATCH 01/41] add roxygen example --- R/correlation.R | 43 +++++++++++++++++++++++++++++++++++++++++++ man/epi_cor.Rd | 44 ++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 87 insertions(+) diff --git a/R/correlation.R b/R/correlation.R index 0643e018..2cc1f715 100644 --- a/R/correlation.R +++ b/R/correlation.R @@ -40,6 +40,49 @@ #' @importFrom rlang .data !! !!! enquo syms #' @importFrom tidyselect eval_select #' @export +#' @examples +#' library(delphi.epidata) +#' library(epiprocess) +#' library(dplyr) +#' +#' # get data as an `epi_df` object +#' x <- covidcast( +#' data_source = "jhu-csse", +#' signals = "confirmed_7dav_incidence_prop", +#' time_type = "day", +#' geo_type = "state", +#' time_values = epirange(20200301, 20211231), +#' geo_values = "*" +#' ) %>% +#' fetch_tbl() %>% +#' select(geo_value, time_value, case_rate = value) +#' +#' y <- covidcast( +#' data_source = "jhu-csse", +#' signals = "deaths_7dav_incidence_prop", +#' time_type = "day", +#' geo_type = "state", +#' time_values = epirange(20200301, 20211231), +#' geo_values = "*" +#' ) %>% +#' fetch_tbl() %>% +#' select(geo_value, time_value, death_rate = value) +#' +#' x <- x %>% +#' full_join(y, by = c("geo_value", "time_value")) %>% +#' as_epi_df() +#' +#' # linear association of case and death rates on any given day +#' epi_cor(x, case_rate, death_rate, cor_by = "time_value") +#' +#' # correlation of death rates and lagged case rates +#' epi_cor(x, case_rate, death_rate, cor_by = time_value, dt1 = -10) +#' +#' # correlation grouped by location +#' epi_cor(x, case_rate, death_rate, cor_by = geo_value) +#' +#' # correlation grouped by location and incorporates lagged cases rates +#' epi_cor(x, case_rate, death_rate, cor_by = geo_value, dt1 = -10) epi_cor = function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value, cor_by = geo_value, use = "na.or.complete", method = c("pearson", "kendall", "spearman")) { diff --git a/man/epi_cor.Rd b/man/epi_cor.Rd index 7c3e1ecf..ffd2eb77 100644 --- a/man/epi_cor.Rd +++ b/man/epi_cor.Rd @@ -57,3 +57,47 @@ grouping by geo value, time value, or any other variables. See the \href{https://cmu-delphi.github.io/epiprocess/articles/correlation.html}{correlation vignette} for examples. } +\examples{ +library(delphi.epidata) +library(epiprocess) +library(dplyr) + +# get data as an `epi_df` object +x <- covidcast( +data_source = "jhu-csse", +signals = "confirmed_7dav_incidence_prop", +time_type = "day", +geo_type = "state", +time_values = epirange(20200301, 20211231), +geo_values = "*" +) \%>\% + fetch_tbl() \%>\% + select(geo_value, time_value, case_rate = value) + +y <- covidcast( +data_source = "jhu-csse", +signals = "deaths_7dav_incidence_prop", +time_type = "day", +geo_type = "state", +time_values = epirange(20200301, 20211231), +geo_values = "*" +) \%>\% + fetch_tbl() \%>\% + select(geo_value, time_value, death_rate = value) + +x <- x \%>\% +full_join(y, by = c("geo_value", "time_value")) \%>\% + as_epi_df() + +# linear association of case and death rates on any given day +epi_cor(x, case_rate, death_rate, cor_by = "time_value") + +# correlation of death rates and lagged case rates +epi_cor(x, case_rate, death_rate, cor_by = time_value, dt1 = -10) + +# correlation grouped by location +epi_cor(x, case_rate, death_rate, cor_by = geo_value) + +# correlation grouped by location and incorporates lagged cases rates +epi_cor(x, case_rate, death_rate, cor_by = geo_value, dt1 = -10) +} From e2eb164431b74374515bb1b9efc4e5529ff07659 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Thu, 5 May 2022 13:07:09 -0700 Subject: [PATCH 02/41] example added to epi_slide roxygen --- R/slide.R | 22 ++++++++++++++++++++++ man/epi_slide.Rd | 23 +++++++++++++++++++++++ 2 files changed, 45 insertions(+) diff --git a/R/slide.R b/R/slide.R index ce563187..244b973f 100644 --- a/R/slide.R +++ b/R/slide.R @@ -88,6 +88,28 @@ #' @importFrom lubridate days weeks #' @importFrom rlang .data .env !! enquo enquos sym #' @export +#' @examples +#' library(delphi.epidata) +#' library(epiprocess) +#' library(dplyr) +#' +#' # must take `epi_df` obejct as paramater +#' # generate example data +#'x <- covidcast( +#' data_source = "jhu-csse", +#' signals = "confirmed_incidence_num", +#' time_type = "day", +#' geo_type = "state", +#' time_values = epirange(20200301, 20211231), +#' geo_values = "ca" +#' ) %>% +#' fetch_tbl() %>% +#' select(geo_value, time_value, cases = value) %>% +#' arrange(geo_value, time_value) %>% +#' as_epi_df() +#' +#' # slide a 7-day trailing average formula on cases +#' epi_slide(x, cases7dav = mean(cases), n = 7) epi_slide = function(x, f, ..., n = 7, ref_time_values, align = c("right", "center", "left"), before, time_step, new_col_name = "slide_value", as_list_col = FALSE, diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 6aa4addf..fd513aa2 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -116,3 +116,26 @@ tidy evaluation (first example, above), then the name for the new column is inferred from the given expression and overrides any name passed explicitly through the \code{new_col_name} argument. } +\examples{ +library(delphi.epidata) +library(epiprocess) +library(dplyr) + +# must take `epi_df` obejct as paramater +# generate example data +x <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_incidence_num", + time_type = "day", + geo_type = "state", + time_values = epirange(20200301, 20211231), + geo_values = "ca" +) \%>\% + fetch_tbl() \%>\% + select(geo_value, time_value, cases = value) \%>\% + arrange(geo_value, time_value) \%>\% + as_epi_df() + +# slide a 7-day trailing average formula on cases +epi_slide(x, cases7dav = mean(cases), n = 7) +} From 4a14dc8ca47aca4bc87831ea8c746e54139911c2 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Thu, 5 May 2022 14:58:58 -0700 Subject: [PATCH 03/41] add codeowners --- .github/CODEOWNERS | 1 + 1 file changed, 1 insertion(+) create mode 100644 .github/CODEOWNERS diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 00000000..6719131f --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1 @@ +@dajmcdon \ No newline at end of file From 5cb9f3eece0145f13278ed3dafc7bf8cfbe6a9c2 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Thu, 5 May 2022 14:59:37 -0700 Subject: [PATCH 04/41] add others --- .github/CODEOWNERS | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index 6719131f..4fa9bec0 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -1 +1 @@ -@dajmcdon \ No newline at end of file +@ryantibs @brookslogan @dajmcdon \ No newline at end of file From 8c7812b8da5089904a907664ba355dec68a748f0 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Thu, 5 May 2022 14:59:57 -0700 Subject: [PATCH 05/41] only me for now --- .github/CODEOWNERS | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index 4fa9bec0..6719131f 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -1 +1 @@ -@ryantibs @brookslogan @dajmcdon \ No newline at end of file +@dajmcdon \ No newline at end of file From 6d4a510d95f3db4477d1a2c2cafabdf1fe04822c Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Thu, 5 May 2022 15:11:35 -0700 Subject: [PATCH 06/41] test the action --- .Rbuildignore | 1 + .github/.gitignore | 1 + .github/workflows/R-CMD-check.yaml | 28 ++++++++++++++++++++++++++++ README.md | 5 +++++ 4 files changed, 35 insertions(+) create mode 100644 .github/.gitignore create mode 100644 .github/workflows/R-CMD-check.yaml diff --git a/.Rbuildignore b/.Rbuildignore index e13c4051..31e37542 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,3 +1,4 @@ ^.*\.Rproj$ ^\.Rproj\.user$ ^LICENSE\.md$ +^\.github$ diff --git a/.github/.gitignore b/.github/.gitignore new file mode 100644 index 00000000..2d19fc76 --- /dev/null +++ b/.github/.gitignore @@ -0,0 +1 @@ +*.html diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml new file mode 100644 index 00000000..5bef95c2 --- /dev/null +++ b/.github/workflows/R-CMD-check.yaml @@ -0,0 +1,28 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/master/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + +name: R-CMD-check + +jobs: + R-CMD-check: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + R_KEEP_PKG_SOURCE: yes + steps: + - uses: actions/checkout@v2 + + - uses: r-lib/actions/setup-r@v1 + with: + use-public-rspm: true + + - uses: r-lib/actions/setup-r-dependencies@v1 + with: + extra-packages: rcmdcheck + + - uses: r-lib/actions/check-r-package@v1 diff --git a/README.md b/README.md index e4ed6933..a48ee8d3 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,10 @@ # epiprocess + + [![R-CMD-check](https://github.com/dajmcdon/epiprocess/workflows/R-CMD-check/badge.svg)](https://github.com/dajmcdon/epiprocess/actions) + + + This repo contains an R package `epiprocess` which introduces a common data structure for epidemiological data sets measured over space and time, and offers associated utilities to perform basic signal processing tasks. From 5df7d9b740f031e7affa3a2ecd983ef98aac61d6 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Thu, 5 May 2022 18:45:07 -0700 Subject: [PATCH 07/41] add slide and cor examples; add internal dataset for example --- .Rbuildignore | 1 + DESCRIPTION | 2 ++ R/correlation.R | 38 +++----------------------- R/data.R | 30 ++++++++++++++++++++ R/slide.R | 21 +------------- data-raw/ca_daily_cases.R | 18 ++++++++++++ data-raw/ca_fl_death_rate_and_cases.R | 32 ++++++++++++++++++++++ data/ca_daily_cases.rda | Bin 0 -> 1775 bytes data/ca_fl_death_rate_and_cases.rda | Bin 0 -> 2635 bytes man/ca_daily_cases.Rd | 26 ++++++++++++++++++ man/ca_fl_death_rate_and_cases.Rd | 27 ++++++++++++++++++ man/epi_cor.Rd | 38 +++----------------------- man/epi_slide.Rd | 21 +------------- 13 files changed, 146 insertions(+), 108 deletions(-) create mode 100644 R/data.R create mode 100644 data-raw/ca_daily_cases.R create mode 100644 data-raw/ca_fl_death_rate_and_cases.R create mode 100644 data/ca_daily_cases.rda create mode 100644 data/ca_fl_death_rate_and_cases.rda create mode 100644 man/ca_daily_cases.Rd create mode 100644 man/ca_fl_death_rate_and_cases.Rd diff --git a/.Rbuildignore b/.Rbuildignore index e13c4051..4b51d4a8 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,3 +1,4 @@ ^.*\.Rproj$ ^\.Rproj\.user$ ^LICENSE\.md$ +^data-raw$ \ No newline at end of file diff --git a/DESCRIPTION b/DESCRIPTION index 5fe02139..c9f5b2f3 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -61,3 +61,5 @@ Suggests: outbreaks, testthat (>= 3.0.0), Config/testthat/edition: 3 +Depends: + R (>= 2.10) diff --git a/R/correlation.R b/R/correlation.R index 2cc1f715..9a71599b 100644 --- a/R/correlation.R +++ b/R/correlation.R @@ -41,48 +41,18 @@ #' @importFrom tidyselect eval_select #' @export #' @examples -#' library(delphi.epidata) -#' library(epiprocess) -#' library(dplyr) -#' -#' # get data as an `epi_df` object -#' x <- covidcast( -#' data_source = "jhu-csse", -#' signals = "confirmed_7dav_incidence_prop", -#' time_type = "day", -#' geo_type = "state", -#' time_values = epirange(20200301, 20211231), -#' geo_values = "*" -#' ) %>% -#' fetch_tbl() %>% -#' select(geo_value, time_value, case_rate = value) -#' -#' y <- covidcast( -#' data_source = "jhu-csse", -#' signals = "deaths_7dav_incidence_prop", -#' time_type = "day", -#' geo_type = "state", -#' time_values = epirange(20200301, 20211231), -#' geo_values = "*" -#' ) %>% -#' fetch_tbl() %>% -#' select(geo_value, time_value, death_rate = value) -#' -#' x <- x %>% -#' full_join(y, by = c("geo_value", "time_value")) %>% -#' as_epi_df() #' #' # linear association of case and death rates on any given day -#' epi_cor(x, case_rate, death_rate, cor_by = "time_value") +#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = "time_value") #' #' # correlation of death rates and lagged case rates -#' epi_cor(x, case_rate, death_rate, cor_by = time_value, dt1 = -10) +#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = time_value, dt1 = -10) #' #' # correlation grouped by location -#' epi_cor(x, case_rate, death_rate, cor_by = geo_value) +#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value) #' #' # correlation grouped by location and incorporates lagged cases rates -#' epi_cor(x, case_rate, death_rate, cor_by = geo_value, dt1 = -10) +#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value, dt1 = -10) epi_cor = function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value, cor_by = geo_value, use = "na.or.complete", method = c("pearson", "kendall", "spearman")) { diff --git a/R/data.R b/R/data.R new file mode 100644 index 00000000..bc61341a --- /dev/null +++ b/R/data.R @@ -0,0 +1,30 @@ +#' California daily COVID-19 new cases. +#' +#' A dataset containing the daily COVID-19 new cases +#' from March 1, 2020 to May 1, 2020. +#' +#' @format A tibble with 62 rows and 3 variables: +#' \describe{ +#' \item{geo_value}{location such as the state name} +#' \item{time_value}{date} +#' \item{cases}{number of new confirmed COVID-19 cases, daily} +#' ... +#' } +#' @source \url{https://cmu-delphi.github.io/delphi-epidata/} +"ca_daily_cases" + +#' California and Florida Daily COVID-19 incidence rate and death Rates. +#' +#' A dataset containing the daily COVID-19 incidence rates and death rates +#' from March 1, 2020 to May 1, 2020. +#' +#' @format A tibble with 124 rows and 4 variables: +#' \describe{ +#' \item{geo_value}{location such as the state name} +#' \item{time_value}{date} +#' \item{case_rate}{number of new confirmed COVID-19 cases per 100,000 population, daily} +#' \item{death_rate}{number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +#' ... +#' } +#' @source \url{https://cmu-delphi.github.io/delphi-epidata/} +"ca_fl_death_rate_and_cases" \ No newline at end of file diff --git a/R/slide.R b/R/slide.R index 244b973f..68667f44 100644 --- a/R/slide.R +++ b/R/slide.R @@ -89,27 +89,8 @@ #' @importFrom rlang .data .env !! enquo enquos sym #' @export #' @examples -#' library(delphi.epidata) -#' library(epiprocess) -#' library(dplyr) -#' -#' # must take `epi_df` obejct as paramater -#' # generate example data -#'x <- covidcast( -#' data_source = "jhu-csse", -#' signals = "confirmed_incidence_num", -#' time_type = "day", -#' geo_type = "state", -#' time_values = epirange(20200301, 20211231), -#' geo_values = "ca" -#' ) %>% -#' fetch_tbl() %>% -#' select(geo_value, time_value, cases = value) %>% -#' arrange(geo_value, time_value) %>% -#' as_epi_df() -#' #' # slide a 7-day trailing average formula on cases -#' epi_slide(x, cases7dav = mean(cases), n = 7) +#' epi_slide(ca_daily_cases, cases7dav = mean(cases), n = 7) epi_slide = function(x, f, ..., n = 7, ref_time_values, align = c("right", "center", "left"), before, time_step, new_col_name = "slide_value", as_list_col = FALSE, diff --git a/data-raw/ca_daily_cases.R b/data-raw/ca_daily_cases.R new file mode 100644 index 00000000..0ab74df8 --- /dev/null +++ b/data-raw/ca_daily_cases.R @@ -0,0 +1,18 @@ +library(delphi.epidata) +library(epiprocess) +library(dplyr) + +ca_daily_cases <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_incidence_num", + time_type = "day", + geo_type = "state", + time_values = epirange(20200301, 20200501), + geo_values = "ca" +) %>% + fetch_tbl() %>% + select(geo_value, time_value, cases = value) %>% + arrange(geo_value, time_value) %>% + as_epi_df() + +usethis::use_data(ca_daily_cases, overwrite = TRUE) diff --git a/data-raw/ca_fl_death_rate_and_cases.R b/data-raw/ca_fl_death_rate_and_cases.R new file mode 100644 index 00000000..bd48dd67 --- /dev/null +++ b/data-raw/ca_fl_death_rate_and_cases.R @@ -0,0 +1,32 @@ + library(delphi.epidata) + library(epiprocess) + library(dplyr) + + # get data as an `epi_df` object +x <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_7dav_incidence_prop", + time_type = "day", + geo_type = "state", + time_values = epirange(20200301, 20200501), + geo_values = "ca,fl" + ) %>% + fetch_tbl() %>% + select(geo_value, time_value, case_rate = value) + + y <- covidcast( + data_source = "jhu-csse", + signals = "deaths_7dav_incidence_prop", + time_type = "day", + geo_type = "state", + time_values = epirange(20200301, 20200501), + geo_values = "ca,fl" + ) %>% + fetch_tbl() %>% + select(geo_value, time_value, death_rate = value) + +ca_fl_death_rate_and_cases <- x %>% + full_join(y, by = c("geo_value", "time_value")) %>% + as_epi_df() + +usethis::use_data(ca_fl_death_rate_and_cases, overwrite = TRUE) diff --git a/data/ca_daily_cases.rda b/data/ca_daily_cases.rda new file mode 100644 index 0000000000000000000000000000000000000000..bc9839aba89c778a70dc014a78c80091a13d8232 GIT binary patch literal 1775 zcmai!do0x&U2pc_dL%z-#@o+Ra6XvQ;@#*$Jxdhf?>9oJ1_o2||5W%5=+=}HH5b7DYd(@CIy8-^ z=vf5-0|5d61dxv50*2@z{Ek#AvIt{+*9}M{9!WaFTmoz)d>B!{<8@y z%7#tP*wFPqyugSk-th2(^#vIDfsD(X0;^L*1NC9lk%EzP3b9EAl_`;kLF=g~Zy6uO z66hK8U;}V}EA>tSOi;maTO{89k?u6qx>46W1`0x?zrCj-&BP~}m?|Tyt?W{x6?v3mZ+4*yS z+;O`aSs1PBs`BZX_)t8*a%}jRuX%turo0H}ULw6V{16PSCL!X5v)I*B!XT+&r87&E z?xKG;pWYUtp&{?Z>T-JU6X1`~Cvp_*VjkxWVL|@*ud^U!;a;S0j zcI=wu#buysRhtGJj-`Kx=3j~s4Xmr7w*_^k4_+r=)od4Eqhg&c?l^0;B??51q=%7Wp8bSmV zUMgjbr+iYj-*>EgsK`u$w$S3z(SA5dKPc#SI3oz1G}x^rQ#(PWqdTXAZSO62g9@!| zCCv=F@RD$%1$k9rTq?L^noa;-fB8+~w&i29EfCfBsUiO3pLKe6V^@Vs3$bByX=7B2 z_EJt@BPl5k2CZLBjl3hHmv_0sVbZj)PZQI=$Nu^tozg*%$XDcHsY%Rj9k0QNz3)Mj zYJa?&0$5qLPiUKugsIdy8iB&bDp$UuNY;ry39r&D1)a>yizrf2!lt6b_gFb@!mT(T z-V}e_(rT!;C*U-h-==Qs4u2xq_&S%gJG%dFX}M$Ki^pGk&nCZ9(Fbs!z|#vJh`^?; zjI^X6)jAwXqFo4ADww*@RF9+`3b6U_aoS>9zUSKiA1sy#=>#vbyW-zn;+W61I`o}n zc`Z-LHKQ*RXUfW>1wXu<))iIQm8DNbqFRW8Fg`0UdM4BQqlMwRnIWm@?nOn`4qx|$ zLd}Zj*y==bgg2UOm;a&sk5=bfb2W3yo_&nIbfg0W3%;2~-RBbeh##~#1tumLu^r&P zokH6aTGE-&347IX98DUk&bU)-lyW83B=Ui;A3OnlZ+lf7RA5}8B1aZte@&7+$GbRq zINr#n>^A@9t(EK3oI*^?i&8%W+o2k4G?Tn`4&efcCCU9Kqw4CHj(VTT06!a*KTOO# zrCgBGKaL=5;&Wly1cv8PUshhuY?dZFaM$miNd)i08eF&VFRl}+I=s#eMG?K|2HyB^ z*cY#QS`%9dEn~bBpU>-)4Yx)=R;DIq4sDP3SnYv`VqcY(e`wR7nA1g{GV5rH!y+-7 zpW*?V>deQ_^?_;iF@bTET)V z(LZqhfaeRdUe74`*mMK5YT>-?XkzEEUv4N}L$^H0E+g1+%77-@?b$D!n(G+aEB13l o`j2v*23vojVBZnC!1gKfMjE0uJ#A7~x1_0b?P8ax5^DDR2Pb(HnE(I) literal 0 HcmV?d00001 diff --git a/data/ca_fl_death_rate_and_cases.rda b/data/ca_fl_death_rate_and_cases.rda new file mode 100644 index 0000000000000000000000000000000000000000..f129edbaf1d391a31fabef0d5059d16eb7c6346a GIT binary patch literal 2635 zcmaiwYdF&l8^Hfs%^b#%!$ugRts(S}Xfno#Ei@G#DXff;%Ar;{u9=wA;u)fe9F~-% z$4e(eA$rD8q(n`u2!%%nz1}bHr}w(v--r9U?l1T6zJAUD3_B|)e^Z*jV=nVMu<7~l z|I0h*_#R-+b9N;t?4)hu?828bZ{G$IcDf7^DiD%E2^Bhs0vHl%rMRC*rdoqy2_p-I z=7H%o;Z+*OhFuV+3_%nE9A#6%U=XRyF3XTHOT2vPO!nXs*k{b?XgB4~C7vfn1g=Uz-ad!chz{ zGZ_vjrwBwS0Durdv5g?Hh7N#CF8Ga|41mCT5+KhV+e3$@GTkaAYE^K`U^tH|SH*>p z+2mr&vMQn_3GU^S3r)WchoX7pb*K);*1a56XHozzPK5(3E_;OLS)h3l00?Y z%b-~!@A_Viul~EeY#*KGxb9Hjdyws$uwy~3$rEHXjpShzwAidTmvNs z!Tp*A6I!elX^&f<49CsqMzQClp94c{E{Yw)7Fiy=Ou@vd8%Mg|iu+pTPiGsgWZnOE zst0mt#bYJ zmzR_?q_EaF)RNM89(lC;uIFF3$YyRjlR>5GBhI;Yr;(jcAGF;4TYvHsK`y>fInQN+ zLFpJ??y=t67u+NIYX6({sfLA-U`b6s|Ui8yi7{y$m-)tD3dVv2DftI zKP}r|Hd6mpZ$rPGw-KEQNwW1k$=qO>TAN~P{*)M#=e)mr3p~>8(-ttj=l70`k@MPh z$WmH2F*#IErs_Z#2*19+dN{aHx-@;f@Z3Ks84sD<0@H_%wB*QENayIOyIku<=-#Y zYMGC`4*6M|zc!A0^Sm8*V$+qpz*jT{fu9)$M&@govSF^Noj}6ol^t1IV`82ee>R6MhzW)$5T@)tBfp4Na%kTu8#gqJFP`Z$n`zr+po3!XeE59kTF-O1V<63xDO=#FVJg^ zOJ)oFEdg=C!$H1{gSTpm8$VCDGULE7i#M@_X%IslE#fF`Ey525ydCXbV7fP&XclU3 z5;hG5{>ggxvo@#ORPy65(L2qZorDJ_R9Y5}fkwkEj6SHvNrP z$Q=~C;t_1pBL@R|d~8YfhoGkH==Xh>s(v;9EgAECB+g7%UY6fJXHOy{ScW}C8$CFw zhLu;G1ht4@n=xYZ&4TP}fphG0KH{hO=O$R@Q?^ssh5(ZF&Atm0w?<8#Mv9kO%?bHC4|<*Qd&v7$~7bLjS(jro~p{oh2NF#Y??FErOwr&sK`;E;u)*dc?Xv~c(R|swOL}n{ zahCH4=Au4#K-cYD$;@V3*u9G?&EZzE_eL`+?OLu}3opY2kt6%V&yJggs$VixL`8J{ zokj6e!Aj3aA{oV3{Cf1TrOKg_OZ4NhoMG^Wo5UW@F$)>;?0w_Q@r^!K@VJ+Cug8p& zgJhW<*0D=-tcIrDlRj(4-ac_#zbY770x{Uyxone}4O6^f7~wW)ZmQ4C9H8ZFaRm6N z7@{hxvQU)_JFBN64@txBLVMP3F0DjPq@;E|v&lTGmK*{KTNf{qyuL4IzR1h{O!?WC zqh@t05+6Zn=Zy{Um3swk8&VPJqLdTvik%&8L}sJPAN<)|K@Fl(^HPBkF&`qFcMl^3 zc4@90JB0gJUOSJ9%20|tB60D)yemcy=6r06$W;wc?d^Y`>wTwY53ub$+$DFLThH=Y z{R38W_XMjI7By-n_AP7uLH8``O>j=V1RwA4>d~YtO&ct=aQ+FUm^XZU1UiU>+qGVs)WPBbH1o7pEh?Mcedh>J|( zJG6+@>SxojZ7jm_b+Pp0(J{U~7^gwil1qP=>~aD=-#$H|{x\% - fetch_tbl() \%>\% - select(geo_value, time_value, case_rate = value) - -y <- covidcast( -data_source = "jhu-csse", -signals = "deaths_7dav_incidence_prop", -time_type = "day", -geo_type = "state", -time_values = epirange(20200301, 20211231), -geo_values = "*" -) \%>\% - fetch_tbl() \%>\% - select(geo_value, time_value, death_rate = value) - -x <- x \%>\% -full_join(y, by = c("geo_value", "time_value")) \%>\% - as_epi_df() # linear association of case and death rates on any given day -epi_cor(x, case_rate, death_rate, cor_by = "time_value") +epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = "time_value") # correlation of death rates and lagged case rates -epi_cor(x, case_rate, death_rate, cor_by = time_value, dt1 = -10) +epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = time_value, dt1 = -10) # correlation grouped by location -epi_cor(x, case_rate, death_rate, cor_by = geo_value) +epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value) # correlation grouped by location and incorporates lagged cases rates -epi_cor(x, case_rate, death_rate, cor_by = geo_value, dt1 = -10) +epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value, dt1 = -10) } diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index fd513aa2..5eba8c78 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -117,25 +117,6 @@ inferred from the given expression and overrides any name passed explicitly through the \code{new_col_name} argument. } \examples{ -library(delphi.epidata) -library(epiprocess) -library(dplyr) - -# must take `epi_df` obejct as paramater -# generate example data -x <- covidcast( - data_source = "jhu-csse", - signals = "confirmed_incidence_num", - time_type = "day", - geo_type = "state", - time_values = epirange(20200301, 20211231), - geo_values = "ca" -) \%>\% - fetch_tbl() \%>\% - select(geo_value, time_value, cases = value) \%>\% - arrange(geo_value, time_value) \%>\% - as_epi_df() - # slide a 7-day trailing average formula on cases -epi_slide(x, cases7dav = mean(cases), n = 7) +epi_slide(ca_daily_cases, cases7dav = mean(cases), n = 7) } From bd3f0f8f60b2a0032e1c35c14f6878873dae32e5 Mon Sep 17 00:00:00 2001 From: Daniel McDonald Date: Fri, 6 May 2022 13:39:17 -0700 Subject: [PATCH 08/41] Update R-CMD-check.yaml --- .github/workflows/R-CMD-check.yaml | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index 5bef95c2..8897664d 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -17,12 +17,19 @@ jobs: steps: - uses: actions/checkout@v2 - - uses: r-lib/actions/setup-r@v1 + - uses: r-lib/actions/setup-r@v2 with: use-public-rspm: true + + - name: Install delphi.epidata + shell: Rscript {0} + run: | + install.packages('remotes') + remotes::install_github("cmu-delphi/delphi-epidata-r") - - uses: r-lib/actions/setup-r-dependencies@v1 + - uses: r-lib/actions/setup-r-dependencies@v2 with: - extra-packages: rcmdcheck + extra-packages: any::rcmdcheck + needs: check - - uses: r-lib/actions/check-r-package@v1 + - uses: r-lib/actions/check-r-package@v2 From 9fbc24baf9fc6675ec1c574172cb344482a62929 Mon Sep 17 00:00:00 2001 From: Daniel McDonald Date: Fri, 6 May 2022 13:45:44 -0700 Subject: [PATCH 09/41] try installing from my fork --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5fe02139..c961abf4 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -38,7 +38,7 @@ LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.1.2 Remotes: - cmu-delphi/delphi-epidata-r, + dajmcdon/delphi.epidata, reconverse/outbreaks Imports: data.table, From 9344e0bda0c84f7809d00478f65c1130baa30df9 Mon Sep 17 00:00:00 2001 From: Daniel McDonald Date: Fri, 6 May 2022 13:56:07 -0700 Subject: [PATCH 10/41] remove unnecessary extra install --- .github/workflows/R-CMD-check.yaml | 6 ------ 1 file changed, 6 deletions(-) diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index 8897664d..222d4e35 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -21,12 +21,6 @@ jobs: with: use-public-rspm: true - - name: Install delphi.epidata - shell: Rscript {0} - run: | - install.packages('remotes') - remotes::install_github("cmu-delphi/delphi-epidata-r") - - uses: r-lib/actions/setup-r-dependencies@v2 with: extra-packages: any::rcmdcheck From d18500bb09bfc023d5f5b18cae1867ff77533cc5 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:32:09 -0700 Subject: [PATCH 11/41] R code cleanup -> R CMD Check passes (notes only) * Generics used from other packages must be reexported * Some missing args now documented * Unpleasantness with S3 methods (see below) Previously, all S3 methods for `epi_df` had `x` as the first argument. But this doesn't actually pass checks. Any method must match the generic signature. So this means replacing `x` with (variously) `object`/`.data`/`data`. This is a bit annoying to document all together. Adding an issue to split the methods up in the docs. --- R/epi_df.R | 1 + R/{methods2.R => methods-epi_archive.R} | 4 +- R/{methods.R => methods-epi_df.R} | 109 ++++++++++++------------ R/outliers.R | 20 ++++- R/reexports.R | 57 +++++++++++++ R/utils.R | 8 +- 6 files changed, 135 insertions(+), 64 deletions(-) rename R/{methods2.R => methods-epi_archive.R} (99%) rename R/{methods.R => methods-epi_df.R} (58%) create mode 100644 R/reexports.R diff --git a/R/epi_df.R b/R/epi_df.R index fb78ac1f..50b9a898 100644 --- a/R/epi_df.R +++ b/R/epi_df.R @@ -91,6 +91,7 @@ NULL #' guide](https://cmu-delphi.github.io/epiprocess/articles/epiprocess.html) for #' examples. #' +#' @param x A data.frame, [tibble::tibble], or [tsibble::tsibble] to be converted #' @param geo_type Type for the geo values. If missing, then the function will #' attempt to infer it from the geo values present; if this fails, then it #' will be set to "custom". diff --git a/R/methods2.R b/R/methods-epi_archive.R similarity index 99% rename from R/methods2.R rename to R/methods-epi_archive.R index 1aaa68a8..ddf3e795 100644 --- a/R/methods2.R +++ b/R/methods-epi_archive.R @@ -4,7 +4,8 @@ #' given version. See the [archive #' vignette](https://cmu-delphi.github.io/epiprocess/articles/archive.html) for #' examples. -#' +#' +#' @param x An `epi_archive` object #' @param max_version Time value specifying the max version to permit in the #' snapshot. That is, the snapshot will comprise the unique rows of the #' current archive data that represent the most up-to-date signal values, as @@ -81,6 +82,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' vignette](https://cmu-delphi.github.io/epiprocess/articles/archive.html) for #' examples. #' +#' @param x An `epi_archive` object. #' @param f Function or formula to slide over variables in `x`. To "slide" means #' to apply a function or formula over a running window of `n` time steps #' (where one time step is typically one day or one week). If a function, `f` diff --git a/R/methods.R b/R/methods-epi_df.R similarity index 58% rename from R/methods.R rename to R/methods-epi_df.R index 45aea4a4..1bf1dfb5 100644 --- a/R/methods.R +++ b/R/methods-epi_df.R @@ -4,15 +4,18 @@ #' `time_value`, and the key variables taken to be `geo_value` along with any #' others in the `other_keys` field of the metadata, or else explicitly set. #' -#' @importFrom tsibble as_tsibble #' @method as_tsibble epi_df +#' @param x The `epi_df` object. +#' @param key Optional. Any additional keys (other than `geo_value`) to add to +#' the `tsibble`. +#' @param ... additional arguments passed on to `tsibble::as_tsibble()` #' @export as_tsibble.epi_df = function(x, key, ...) { if (missing(key)) key = c("geo_value", attributes(x)$metadata$other_keys) return(as_tsibble(tibble::as_tibble(x), key, index = "time_value", ...)) } -#' S3 methods for an `epi_df` object +#' Base S3 methods for an `epi_df` object #' #' Print, summary, and `dplyr` verbs (that preserve class and attributes) for an #' `epi_df` object. @@ -45,21 +48,22 @@ print.epi_df = function(x, ...) { #' @importFrom rlang .data #' @importFrom stats median #' @export -summary.epi_df = function(x, ...) { +summary.epi_df = function(object, ...) { cat("An `epi_df` x, with metadata:\n") - cat(sprintf("* %-9s = %s\n", "geo_type", attributes(x)$metadata$geo_type)) - cat(sprintf("* %-9s = %s\n", "time_type", attributes(x)$metadata$time_type)) - cat(sprintf("* %-9s = %s\n", "as_of", attributes(x)$metadata$as_of)) + cat(sprintf("* %-9s = %s\n", "geo_type", attributes(object)$metadata$geo_type)) + cat(sprintf("* %-9s = %s\n", "time_type", attributes(object)$metadata$time_type)) + cat(sprintf("* %-9s = %s\n", "as_of", attributes(object)$metadata$as_of)) cat("----------\n") - cat(sprintf("* %-27s = %s\n", "min time value", min(x$time_value))) - cat(sprintf("* %-27s = %s\n", "max time value", max(x$time_value))) + cat(sprintf("* %-27s = %s\n", "min time value", min(object$time_value))) + cat(sprintf("* %-27s = %s\n", "max time value", max(object$time_value))) cat(sprintf("* %-27s = %i\n", "average rows per time value", - as.integer(x %>% dplyr::group_by(.data$time_value) %>% + as.integer(object %>% dplyr::group_by(.data$time_value) %>% dplyr::summarize(num = dplyr::n()) %>% dplyr::summarize(mean(.data$num))))) } #' @method head epi_df +#' @importFrom utils head #' @export #' @noRd head.epi_df = function(x, ...) { @@ -67,6 +71,7 @@ head.epi_df = function(x, ...) { } #' @method tail epi_df +#' @importFrom utils tail #' @export #' @noRd tail.epi_df = function(x, ...) { @@ -75,91 +80,83 @@ tail.epi_df = function(x, ...) { #' `dplyr` verbs #' -#' `dplyr` verbs for `epi_df` objexts, preserving class and attributes. +#' `dplyr` verbs for `epi_df` objects, preserving class and attributes. #' #' @method arrange epi_df +#' @param .data The `epi_df` object. #' @rdname print.epi_df -#' @importFrom dplyr arrange #' @export -arrange.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +arrange.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method filter epi_df #' @rdname print.epi_df -#' @importFrom dplyr filter #' @export -filter.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +filter.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method group_by epi_df #' @rdname print.epi_df -#' @importFrom dplyr group_by #' @export -group_by.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +group_by.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method group_modify epi_df #' @rdname print.epi_df -#' @importFrom dplyr group_modify #' @export -group_modify.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +group_modify.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method mutate epi_df #' @rdname print.epi_df -#' @importFrom dplyr mutate #' @export -mutate.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +mutate.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method relocate epi_df #' @rdname print.epi_df -#' @importFrom dplyr relocate #' @export -relocate.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +relocate.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method rename epi_df #' @rdname print.epi_df -#' @importFrom dplyr rename #' @export -rename.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +rename.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method slice epi_df #' @rdname print.epi_df -#' @importFrom dplyr slice #' @export -slice.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +slice.epi_df = function(.data, ...) { + metadata = attributes(.data)$metadata + .data = NextMethod() + reclass(.data, metadata) } #' @method ungroup epi_df #' @rdname print.epi_df -#' @importFrom dplyr ungroup #' @export ungroup.epi_df = function(x, ...) { metadata = attributes(x)$metadata @@ -169,12 +166,12 @@ ungroup.epi_df = function(x, ...) { #' @method unnest epi_df #' @rdname print.epi_df -#' @importFrom tidyr unnest +#' @param data The `epi_df` object. #' @export -unnest.epi_df = function(x, ...) { - metadata = attributes(x)$metadata - x = NextMethod() - reclass(x, metadata) +unnest.epi_df = function(data, ...) { + metadata = attributes(data)$metadata + data = NextMethod() + reclass(data, metadata) } # Simple reclass function diff --git a/R/outliers.R b/R/outliers.R index 4acc52ab..7f4ddf00 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -178,6 +178,21 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @param seasonal_period Integer specifying period of seasonality. For example, #' for daily data, a period 7 means weekly seasonality. The default is `NULL`, #' meaning that no seasonal term will be included in the STL decomposition. +#' @param log_transform Should a log transform be applied before running outlier +#' detection? Default is `FALSE`. If `TRUE`, and zeros are present, then the +#' log transform will be padded by 1. +#' @param detect_negatives Should negative values automatically count as +#' outliers? Default is `FALSE`. +#' @param detection_multiplier Value determining how far the outlier detection +#' thresholds are from the rolling median, which are calculated as (rolling +#' median) +/- (detection multiplier) * (rolling IQR). Default is 2. +#' @param min_radius Minimum distance between rolling median and threshold, on +#' transformed scale. Default is 0. +#' @param replacement_multiplier Value determining how far the replacement +#' values are from the rolling median. The replacement is the original value +#' if it is within the detection thresholds, or otherwise it is rounded to the +#' nearest (rolling median) +/- (replacement multiplier) * (rolling IQR). +#' Default is 0. #' @return A tibble with number of rows equal to `length(y)`, and columns #' `lower`, `upper`, and `replacement`. #' @@ -188,8 +203,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' residuals to the rolling median, respectively. #' #' The last set of arguments, `log_transform` through `replacement_multiplier`, -#' are exactly as in `detect_outlr_rm()`; refer to its help file for their -#' description. +#' are exactly as in `detect_outlr_rm()`. #' #' @importFrom stats median #' @importFrom tidyselect starts_with @@ -272,7 +286,7 @@ roll_iqr = function(z, n, detection_multiplier, min_radius, if (typeof(z$y) == "integer") as_type = as.integer else as_type = as.numeric - epi_slide(z, roll_iqr = IQR(resid), n = n, align = "center") %>% + epi_slide(z, roll_iqr = stats::IQR(resid), n = n, align = "center") %>% dplyr::mutate( lower = pmax(min_lower, fitted - pmax(min_radius, detection_multiplier * roll_iqr)), diff --git a/R/reexports.R b/R/reexports.R new file mode 100644 index 00000000..4cc45e29 --- /dev/null +++ b/R/reexports.R @@ -0,0 +1,57 @@ +# NOTE: when providing a method for a generic in another package +# That generic needs to be rexported + + +# tsibble ----------------------------------------------------------------- + +#' @importFrom tsibble as_tsibble +#' @export +tsibble::as_tsibble + + + + +# dplyr ------------------------------------------------------------------- + +#' @importFrom dplyr arrange +#' @export +dplyr::arrange + +#' @importFrom dplyr filter +#' @export +dplyr::filter + +#' @importFrom dplyr group_by +#' @export +dplyr::group_by + +#' @importFrom dplyr ungroup +#' @export +dplyr::ungroup + +#' @importFrom dplyr group_modify +#' @export +dplyr::group_modify + +#' @importFrom dplyr mutate +#' @export +dplyr::mutate + +#' @importFrom dplyr relocate +#' @export +dplyr::relocate + +#' @importFrom dplyr rename +#' @export +dplyr::rename + +#' @importFrom dplyr slice +#' @export +dplyr::slice + + +# tidyr ------------------------------------------------------------------- + +#' @importFrom tidyr unnest +#' @export +tidyr::unnest diff --git a/R/utils.R b/R/utils.R index cf483ede..4a0b3b72 100644 --- a/R/utils.R +++ b/R/utils.R @@ -1,5 +1,5 @@ break_str = function(str, nchar = 79, init = "") { - str = paste(strwrap(str, nchar, init = init), collapse = "\n") + str = paste(strwrap(str, nchar, initial = init), collapse = "\n") str[1] = substring(str, nchar(init)+1) return(str) } @@ -34,7 +34,8 @@ guess_geo_type = function(geo_value) { geo_value = tolower(geo_value) # If all geo values are state abbreviations, then use "state" - state_values = c(tolower(state.abb), "as", "dc", "gu", "mp", "pr", "vi") + state_values = c(tolower(datasets::state.abb), + "as", "dc", "gu", "mp", "pr", "vi") if (all(geo_value %in% state_values)) return("state") # Else if all geo values are 2 letters, then use "nation" @@ -99,8 +100,7 @@ guess_time_type = function(time_value) { ########## -#' @export -#' @noRd + quiet = function(x) { sink(tempfile()) on.exit(sink()) From ef38df68b686b8f38183e5bcb14d99363b69ae3c Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:32:47 -0700 Subject: [PATCH 12/41] ensure there's no stray crud in vignettes/ --- vignettes/.gitignore | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 vignettes/.gitignore diff --git a/vignettes/.gitignore b/vignettes/.gitignore new file mode 100644 index 00000000..097b2416 --- /dev/null +++ b/vignettes/.gitignore @@ -0,0 +1,2 @@ +*.html +*.R From b08ef122fbb55c75de9d011b5adf2e3aca801311 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:33:09 -0700 Subject: [PATCH 13/41] redocument everything --- man/as_epi_df.Rd | 2 ++ man/as_tsibble.epi_df.Rd | 8 ++++++++ man/detect_outlr_stl.Rd | 23 +++++++++++++++++++++-- man/epix_as_of.Rd | 2 ++ man/epix_slide.Rd | 2 ++ man/print.epi_df.Rd | 28 ++++++++++++++++------------ man/reexports.Rd | 30 ++++++++++++++++++++++++++++++ 7 files changed, 81 insertions(+), 14 deletions(-) create mode 100644 man/reexports.Rd diff --git a/man/as_epi_df.Rd b/man/as_epi_df.Rd index 0ea6ebc5..e092716e 100644 --- a/man/as_epi_df.Rd +++ b/man/as_epi_df.Rd @@ -19,6 +19,8 @@ as_epi_df(x, ...) \method{as_epi_df}{tbl_ts}(x, geo_type, time_type, as_of, additional_metadata = list(), ...) } \arguments{ +\item{x}{A data.frame, \link[tibble:tibble]{tibble::tibble}, or \link[tsibble:tsibble]{tsibble::tsibble} to be converted} + \item{...}{Additional arguments passed to methods.} \item{geo_type}{Type for the geo values. If missing, then the function will diff --git a/man/as_tsibble.epi_df.Rd b/man/as_tsibble.epi_df.Rd index 3ccb7cc2..ebc7fc7b 100644 --- a/man/as_tsibble.epi_df.Rd +++ b/man/as_tsibble.epi_df.Rd @@ -6,6 +6,14 @@ \usage{ \method{as_tsibble}{epi_df}(x, key, ...) } +\arguments{ +\item{x}{The \code{epi_df} object.} + +\item{key}{Optional. Any additional keys (other than \code{geo_value}) to add to +the \code{tsibble}.} + +\item{...}{additional arguments passed on to \code{tsibble::as_tsibble()}} +} \description{ Converts an \code{epi_df} object into a tsibble, where the index is taken to be \code{time_value}, and the key variables taken to be \code{geo_value} along with any diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index 73de7eb9..6bf6882a 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -37,6 +37,26 @@ outlier thresholds.} \item{seasonal_period}{Integer specifying period of seasonality. For example, for daily data, a period 7 means weekly seasonality. The default is \code{NULL}, meaning that no seasonal term will be included in the STL decomposition.} + +\item{log_transform}{Should a log transform be applied before running outlier +detection? Default is \code{FALSE}. If \code{TRUE}, and zeros are present, then the +log transform will be padded by 1.} + +\item{detect_negatives}{Should negative values automatically count as +outliers? Default is \code{FALSE}.} + +\item{detection_multiplier}{Value determining how far the outlier detection +thresholds are from the rolling median, which are calculated as (rolling +median) +/- (detection multiplier) * (rolling IQR). Default is 2.} + +\item{min_radius}{Minimum distance between rolling median and threshold, on +transformed scale. Default is 0.} + +\item{replacement_multiplier}{Value determining how far the replacement +values are from the rolling median. The replacement is the original value +if it is within the detection thresholds, or otherwise it is rounded to the +nearest (rolling median) +/- (replacement multiplier) * (rolling IQR). +Default is 0.} } \value{ A tibble with number of rows equal to \code{length(y)}, and columns @@ -53,6 +73,5 @@ from the STL decomposition taking the place of the rolling median and residuals to the rolling median, respectively. The last set of arguments, \code{log_transform} through \code{replacement_multiplier}, -are exactly as in \code{detect_outlr_rm()}; refer to its help file for their -description. +are exactly as in \code{detect_outlr_rm()}. } diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 51867318..14e319c4 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -7,6 +7,8 @@ epix_as_of(x, max_version, min_time_value = -Inf) } \arguments{ +\item{x}{An \code{epi_archive} object} + \item{max_version}{Time value specifying the max version to permit in the snapshot. That is, the snapshot will comprise the unique rows of the current archive data that represent the most up-to-date signal values, as diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index b237880b..8660e66d 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -19,6 +19,8 @@ epix_slide( ) } \arguments{ +\item{x}{An \code{epi_archive} object.} + \item{f}{Function or formula to slide over variables in \code{x}. To "slide" means to apply a function or formula over a running window of \code{n} time steps (where one time step is typically one day or one week). If a function, \code{f} diff --git a/man/print.epi_df.Rd b/man/print.epi_df.Rd index 11c7e1cd..94d3a2fd 100644 --- a/man/print.epi_df.Rd +++ b/man/print.epi_df.Rd @@ -13,31 +13,31 @@ \alias{slice.epi_df} \alias{ungroup.epi_df} \alias{unnest.epi_df} -\title{S3 methods for an \code{epi_df} object} +\title{Base S3 methods for an \code{epi_df} object} \usage{ \method{print}{epi_df}(x, ...) -\method{summary}{epi_df}(x, ...) +\method{summary}{epi_df}(object, ...) -\method{arrange}{epi_df}(x, ...) +\method{arrange}{epi_df}(.data, ...) -\method{filter}{epi_df}(x, ...) +\method{filter}{epi_df}(.data, ...) -\method{group_by}{epi_df}(x, ...) +\method{group_by}{epi_df}(.data, ...) -\method{group_modify}{epi_df}(x, ...) +\method{group_modify}{epi_df}(.data, ...) -\method{mutate}{epi_df}(x, ...) +\method{mutate}{epi_df}(.data, ...) -\method{relocate}{epi_df}(x, ...) +\method{relocate}{epi_df}(.data, ...) -\method{rename}{epi_df}(x, ...) +\method{rename}{epi_df}(.data, ...) -\method{slice}{epi_df}(x, ...) +\method{slice}{epi_df}(.data, ...) \method{ungroup}{epi_df}(x, ...) -\method{unnest}{epi_df}(x, ...) +\method{unnest}{epi_df}(data, ...) } \arguments{ \item{x}{The \code{epi_df} object.} @@ -46,6 +46,10 @@ Currently unused.} \item{object}{The \code{epi_df} object.} + +\item{.data}{The \code{epi_df} object.} + +\item{data}{The \code{epi_df} object.} } \description{ Print, summary, and \code{dplyr} verbs (that preserve class and attributes) for an @@ -54,5 +58,5 @@ Print, summary, and \code{dplyr} verbs (that preserve class and attributes) for Prints a variety of summary statistics about the \code{epi_df} object, such as the time range included and geographic coverage. -\code{dplyr} verbs for \code{epi_df} objexts, preserving class and attributes. +\code{dplyr} verbs for \code{epi_df} objects, preserving class and attributes. } diff --git a/man/reexports.Rd b/man/reexports.Rd new file mode 100644 index 00000000..b633e86c --- /dev/null +++ b/man/reexports.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/reexports.R +\docType{import} +\name{reexports} +\alias{reexports} +\alias{as_tsibble} +\alias{arrange} +\alias{filter} +\alias{group_by} +\alias{ungroup} +\alias{group_modify} +\alias{mutate} +\alias{relocate} +\alias{rename} +\alias{slice} +\alias{unnest} +\title{Objects exported from other packages} +\keyword{internal} +\description{ +These objects are imported from other packages. Follow the links +below to see their documentation. + +\describe{ + \item{dplyr}{\code{\link[dplyr]{arrange}}, \code{\link[dplyr]{filter}}, \code{\link[dplyr]{group_by}}, \code{\link[dplyr:group_map]{group_modify}}, \code{\link[dplyr]{mutate}}, \code{\link[dplyr]{relocate}}, \code{\link[dplyr]{rename}}, \code{\link[dplyr]{slice}}, \code{\link[dplyr:group_by]{ungroup}}} + + \item{tidyr}{\code{\link[tidyr:nest]{unnest}}} + + \item{tsibble}{\code{\link[tsibble:as-tsibble]{as_tsibble}}} +}} + From cb5fc34e38fae9ba233afee44d6a36527c7ee74b Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:34:31 -0700 Subject: [PATCH 14/41] clean up the description --- DESCRIPTION | 99 ++++++++++++++++++++++++----------------------------- NAMESPACE | 14 +++++++- 2 files changed, 57 insertions(+), 56 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5fe02139..6022538b 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,63 +1,52 @@ -Package: epiprocess Type: Package +Package: epiprocess Title: Tools for basic signal processing in epidemiology Version: 1.0.0 -Authors@R: - c( - person(given = "Jacob", - family = "Bien", - role = "ctb"), - person(given = "Logan", - family = "Brooks", - role = "aut"), - person(given = "Rafael", - family = "Catoia", - role = "ctb"), - person(given = "Daniel", - family = "McDonald", - role = "ctb"), - person(given = "Quang", - family = "Nguyen", - role = "ctb"), - person(given = "Evan", - family = "Ray", - role = "aut"), - person(given = "Dmitry", - family = "Shemetov", - role = "ctb"), - person(given = "Ryan", - family = "Tibshirani", - role = c("aut", "cre"), - email = "ryantibs@cmu.edu")) -Description: This package introduces a common data structure for epidemiological - data sets measured over space and time, and offers associated utilities to - perform basic signal processing tasks. +Authors@R:c( + person("Jacob", "Bien", role = "ctb"), + person("Logan", "Brooks", role = "aut"), + person("Rafael", "Catoia", role = "ctb"), + person("Daniel", "McDonald", role = "ctb"), + person("Quang", "Nguyen", role = "ctb"), + person("Evan", "Ray", role = "aut"), + person("Dmitry", "Shemetov", role = "ctb"), + person("Ryan", "Tibshirani", , "ryantibs@cmu.edu", role = c("aut", "cre")) + ) +Description: This package introduces a common data structure for + epidemiological data sets measured over space and time, and offers + associated utilities to perform basic signal processing tasks. License: MIT + file LICENSE +Imports: + data.table, + delphi.epidata, + dplyr, + fabletools, + feasts, + generics, + genlasso, + lubridate, + magrittr, + purrr, + R6, + rlang, + slider, + tibble, + tidyr, + tidyselect, + tsibble, + utils +Suggests: + knitr, + outbreaks, + rmarkdown, + testthat (>= 3.0.0) +VignetteBuilder: + knitr +Remotes: + cmu-delphi/delphi-epidata-r, + reconverse/outbreaks +Config/testthat/edition: 3 Encoding: UTF-8 LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.1.2 -Remotes: - cmu-delphi/delphi-epidata-r, - reconverse/outbreaks -Imports: - data.table, - delphi.epidata, - dplyr, - fabletools, - feasts, - genlasso, - lubridate, - magrittr, - purrr, - R6, - rlang, - slider, - tibble, - tidyselect, - tidyr, - tsibble -Suggests: - outbreaks, - testthat (>= 3.0.0), -Config/testthat/edition: 3 diff --git a/NAMESPACE b/NAMESPACE index d23145da..b52e1ef6 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -20,8 +20,10 @@ S3method(tail,epi_df) S3method(ungroup,epi_df) S3method(unnest,epi_df) export("%>%") +export(arrange) export(as_epi_archive) export(as_epi_df) +export(as_tsibble) export(detect_outlr) export(detect_outlr_rm) export(detect_outlr_stl) @@ -31,10 +33,18 @@ export(epi_slide) export(epix_as_of) export(epix_merge) export(epix_slide) +export(filter) +export(group_by) +export(group_modify) export(growth_rate) export(is_epi_archive) export(is_epi_df) -export(quiet) +export(mutate) +export(relocate) +export(rename) +export(slice) +export(ungroup) +export(unnest) importFrom(data.table,as.data.table) importFrom(data.table,between) importFrom(data.table,key) @@ -68,3 +78,5 @@ importFrom(tidyr,unnest) importFrom(tidyselect,eval_select) importFrom(tidyselect,starts_with) importFrom(tsibble,as_tsibble) +importFrom(utils,head) +importFrom(utils,tail) From c3bd2548be4abd27b3c1cf6458892ba7f23ea257 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:35:03 -0700 Subject: [PATCH 15/41] add in gh CI checks now that we should pass --- .Rbuildignore | 4 ++++ .github/workflows/R-CMD-check.yaml | 6 ++++++ .gitignore | 1 + 3 files changed, 11 insertions(+) diff --git a/.Rbuildignore b/.Rbuildignore index 31e37542..de5d743a 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -2,3 +2,7 @@ ^\.Rproj\.user$ ^LICENSE\.md$ ^\.github$ +^docs$ +^_pkgdown.yml +^vignettes$ +^index\.md$ \ No newline at end of file diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index 5bef95c2..b33c07fc 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -20,6 +20,12 @@ jobs: - uses: r-lib/actions/setup-r@v1 with: use-public-rspm: true + + - name: Install delphi.epidata + shell: Rscript {0} + run: | + install.packages('remotes') + remotes::install_github("cmu-delphi/delphi-epidata-r") - uses: r-lib/actions/setup-r-dependencies@v1 with: diff --git a/.gitignore b/.gitignore index f4f606b0..ce8cc485 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,4 @@ .RData .Ruserdata *.Rproj +inst/doc From 27065e09f8a7198694571a540b6525458840b72c Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 14:47:00 -0700 Subject: [PATCH 16/41] change the dependency back to my fork --- .github/workflows/R-CMD-check.yaml | 6 ------ DESCRIPTION | 2 +- 2 files changed, 1 insertion(+), 7 deletions(-) diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index a6804433..ec397ab8 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -21,12 +21,6 @@ jobs: with: use-public-rspm: true - - name: Install delphi.epidata - shell: Rscript {0} - run: | - install.packages('remotes') - remotes::install_github("cmu-delphi/delphi-epidata-r") - - uses: r-lib/actions/setup-r-dependencies@v2 with: extra-packages: any::rcmdcheck diff --git a/DESCRIPTION b/DESCRIPTION index 4e29cbb1..1634b245 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -43,7 +43,7 @@ Suggests: VignetteBuilder: knitr Remotes: - cmu-delphi/delphi-epidata-r, + dajmcdon/delphi.epidata, reconverse/outbreaks Config/testthat/edition: 3 Encoding: UTF-8 From 7f4384ecbfc1ca8dbf6f38adc97888156543e500 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Tue, 10 May 2022 16:47:52 -0700 Subject: [PATCH 17/41] add missing dependencies for vignettes --- DESCRIPTION | 2 ++ 1 file changed, 2 insertions(+) diff --git a/DESCRIPTION b/DESCRIPTION index 1634b245..ac850cd1 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -36,6 +36,8 @@ Imports: tsibble, utils Suggests: + covidcast, + gginnards, knitr, outbreaks, rmarkdown, From df56278714f1c33d937e0159bbfd6112de2bd93b Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Wed, 11 May 2022 12:14:49 -0700 Subject: [PATCH 18/41] local checks pass, but there's still a bug in the archive vignette --- .Rbuildignore | 3 +- DESCRIPTION | 3 +- NAMESPACE | 1 + R/archive.R | 99 ++++++++++++++++++++-------------------- man/as_tsibble.epi_df.Rd | 2 +- man/epix_as_of.Rd | 2 +- man/epix_merge.Rd | 2 +- man/epix_slide.Rd | 2 +- man/print.epi_df.Rd | 2 +- vignettes/archive.Rmd | 6 +-- 10 files changed, 62 insertions(+), 60 deletions(-) diff --git a/.Rbuildignore b/.Rbuildignore index de5d743a..fb4d068e 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -4,5 +4,4 @@ ^\.github$ ^docs$ ^_pkgdown.yml -^vignettes$ -^index\.md$ \ No newline at end of file +^index\.md$ diff --git a/DESCRIPTION b/DESCRIPTION index ac850cd1..b28a4b37 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -18,7 +18,6 @@ Description: This package introduces a common data structure for License: MIT + file LICENSE Imports: data.table, - delphi.epidata, dplyr, fabletools, feasts, @@ -37,7 +36,9 @@ Imports: utils Suggests: covidcast, + delphi.epidata, gginnards, + ggplot2, knitr, outbreaks, rmarkdown, diff --git a/NAMESPACE b/NAMESPACE index b52e1ef6..eaaf4182 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -45,6 +45,7 @@ export(rename) export(slice) export(ungroup) export(unnest) +importFrom(R6,R6Class) importFrom(data.table,as.data.table) importFrom(data.table,between) importFrom(data.table,key) diff --git a/R/archive.R b/R/archive.R index f436d509..7154ef4f 100644 --- a/R/archive.R +++ b/R/archive.R @@ -16,7 +16,7 @@ #' @details An `epi_archive` is an R6 class which contains a data table `DT`, of #' class `data.table` from the `data.table` package, with (at least) the #' following columns: -#' +#' #' * `geo_value`: the geographic value associated with each row of measurements. #' * `time_value`: the time value associated with each row of measurements. #' * `version`: the time value specifying the version for each row of @@ -31,7 +31,7 @@ #' on `DT` directly). There can only be a single row per unique combination of #' key variables, and thus the key variables are critical for figuring out how #' to generate a snapshot of data from the archive, as of a given version. -#' +#' #' In general, last observation carried forward (LOCF) is used to data in #' between recorded versions. Currently, deletions must be represented as #' revising a row to a special state (e.g., making the entries `NA` or @@ -43,7 +43,7 @@ #' reference semantics. A primary consequence of this is that objects are not #' copied when modified. You can read more about this in Hadley Wickham's #' [Advanced R](https://adv-r.hadley.nz/r6.html#r6-semantics) book. -#' +#' #' @section Metadata: #' The following pieces of metadata are included as fields in an `epi_archive` #' object: @@ -75,7 +75,8 @@ #' sliding computation at any given reference time point t is performed on #' **data that would have been available as of t**. More details on `slide()` #' are documented in the wrapper function `epix_slide()`. -#' +#' +#' @importFrom R6 R6Class #' @export epi_archive = R6::R6Class( @@ -88,7 +89,7 @@ epi_archive = additional_metadata = NULL, #' @description Creates a new `epi_archive` object. #' @param x A data frame, data table, or tibble, with columns `geo_value`, -#' `time_value`, `version`, and then any additional number of columns. +#' `time_value`, `version`, and then any additional number of columns. #' @param geo_type Type for the geo values. If missing, then the function will #' attempt to infer it from the geo values present; if this fails, then it #' will be set to "custom". @@ -104,12 +105,12 @@ epi_archive = #' @return An `epi_archive` object. #' @importFrom data.table as.data.table key setkeyv initialize = function(x, geo_type, time_type, other_keys, - additional_metadata) { + additional_metadata) { # Check that we have a data frame if (!is.data.frame(x)) { Abort("`x` must be a data frame.") } - + # Check that we have geo_value, time_value, version columns if (!("geo_value" %in% names(x))) { Abort("`x` must contain a `geo_value` column.") @@ -120,7 +121,7 @@ epi_archive = if (!("version" %in% names(x))) { Abort("`x` must contain a `version` column.") } - + # If geo type is missing, then try to guess it if (missing(geo_type)) { geo_type = guess_geo_type(x$geo_value) @@ -130,7 +131,7 @@ epi_archive = if (missing(time_type)) { time_type = guess_time_type(x$time_value) } - + # Finish off with small checks on keys variables and metadata if (missing(other_keys)) other_keys = NULL if (missing(additional_metadata)) additional_metadata = list() @@ -144,7 +145,7 @@ epi_archive = c("geo_type", "time_type"))) { Warn("`additional_metadata` names overlap with existing metadata fields \"geo_type\", \"time_type\".") } - + # Create the data table; if x was an un-keyed data.table itself, # then the call to as.data.table() will fail to set keys, so we # need to check this, then do it manually if needed @@ -162,8 +163,8 @@ epi_archive = cat("An `epi_archive` object, with metadata:\n") cat(sprintf("* %-9s = %s\n", "geo_type", self$geo_type)) cat(sprintf("* %-9s = %s\n", "time_type", self$time_type)) - if (!is.null(self$additional_metadata)) { - sapply(self$additional_metadata, function(m) { + if (!is.null(self$additional_metadata)) { + sapply(self$additional_metadata, function(m) { cat(sprintf("* %-9s = %s\n", names(m), m)) }) } @@ -177,7 +178,7 @@ epi_archive = cat(sprintf("* %-14s = %s\n", "max version", max(self$DT$version))) cat("----------\n") - cat(sprintf("Data archive (stored in DT field): %i x %i\n", + cat(sprintf("Data archive (stored in DT field): %i x %i\n", nrow(self$DT), ncol(self$DT))) cat("----------\n") cat(sprintf("Public methods: %s", @@ -194,7 +195,7 @@ epi_archive = other_keys = setdiff(key(self$DT), c("geo_value", "time_value", "version")) if (length(other_keys) == 0) other_keys = NULL - + # Check a few things on max_version if (!identical(class(max_version), class(self$DT$version))) { Abort("`max_version` and `DT$version` must have same class.") @@ -208,17 +209,17 @@ epi_archive = if (max_version == self_max) { Warn("Getting data as of the latest version possible. For a variety of reasons, it is possible that we only have a preliminary picture of this version (e.g., the upstream source has updated it but we have not seen it due to latency in synchronization). Thus, the snapshot that we produce here might not be reproducible at a later time (e.g., when the archive has caught up in terms of synchronization).") } - + # Filter by version and return return( - # Make sure to use data.table ways of filtering and selecting + # Make sure to use data.table ways of filtering and selecting self$DT[between(time_value, min_time_value, max_version) & version <= max_version, ] %>% unique(by = c("geo_value", "time_value", other_keys), fromLast = TRUE) %>% - tibble::as_tibble() %>% + tibble::as_tibble() %>% dplyr::select(-.data$version) %>% as_epi_df(geo_type = self$geo_type, time_type = self$time_type, @@ -226,7 +227,7 @@ epi_archive = additional_metadata = c(self$additional_metadata, other_keys = other_keys)) ) - }, + }, ##### #' @description Merges another `data.table` with the current one, and allows for #' a post-filling of `NA` values by last observation carried forward (LOCF). @@ -235,7 +236,7 @@ epi_archive = merge = function(y, ..., locf = TRUE, nan = NA) { # Check we have a `data.table` object if (!(inherits(y, "data.table") || inherits(y, "epi_archive"))) { - Abort("`y` must be of class `data.table` or `epi_archive`.") + Abort("`y` must be of class `data.table` or `epi_archive`.") } # Use the data.table merge function, carrying through ... args @@ -250,25 +251,25 @@ epi_archive = # Important: use nafill and not setnafill because the latter # returns the entire data frame by reference, and the former can - # be set to act on particular columns by reference using := + # be set to act on particular columns by reference using := self$DT[, - (cols) := nafill(.SD, type = "locf", nan = nan), - .SDcols = cols, + (cols) := nafill(.SD, type = "locf", nan = nan), + .SDcols = cols, by = by] } - }, + }, ##### #' @description Slides a given function over variables in an `epi_archive` #' object. See the documentation for the wrapper function `epix_as_of()` for -#' details. +#' details. #' @importFrom data.table key #' @importFrom rlang !! !!! enquo enquos is_quosure sym syms - slide = function(f, ..., n = 7, group_by, ref_time_values, + slide = function(f, ..., n = 7, group_by, ref_time_values, time_step, new_col_name = "slide_value", as_list_col = FALSE, names_sep = "_", - all_rows = FALSE) { + all_rows = FALSE) { # If missing, then set ref time values to be everything; else make - # sure we intersect with observed time values + # sure we intersect with observed time values if (missing(ref_time_values)) { ref_time_values = unique(self$DT$time_value) } @@ -276,16 +277,16 @@ epi_archive = ref_time_values = ref_time_values[ref_time_values %in% unique(self$DT$time_value)] } - - # If a custom time step is specified, then redefine units + + # If a custom time step is specified, then redefine units before_num = n-1 if (!missing(time_step)) before_num = time_step(n-1) - + # What to group by? If missing, set according to internal keys if (missing(group_by)) { group_by = setdiff(key(self$DT), c("time_value", "version")) } - + # Symbolize column name, defuse grouping variables. We have to do # the middle step here which is a bit complicated (unfortunately) # since the function epix_slide() could have called the current one, @@ -297,20 +298,20 @@ epi_archive = # Key variable names, apart from time value and version key_vars = setdiff(key(self$DT), c("time_value", "version")) - + # Computation for one group, one time value comp_one_grp = function(.data_group, - f, ..., + f, ..., time_value, key_vars, new_col) { - # Carry out the specified computation + # Carry out the specified computation comp_value = f(.data_group, ...) # Count the number of appearances of the reference time value. # Note: ideally, we want to directly count occurrences of the ref # time value but due to latency, this will often not appear in the - # data group. So we count the number of unique key values, outside + # data group. So we count the number of unique key values, outside # of the time value column count = sum(!duplicated(.data_group[, key_vars])) @@ -344,23 +345,23 @@ epi_archive = else { Abort("The slide computation must return an atomic vector or a data frame.") } - + # Note that we've already recycled comp value to make size stable, # so tibble() will just recycle time value appropriately - return(tibble::tibble(time_value = time_value, + return(tibble::tibble(time_value = time_value, !!new_col := comp_value)) } - + # If f is not missing, then just go ahead, slide by group if (!missing(f)) { if (rlang::is_formula(f)) f = rlang::as_function(f) - + x = purrr::map_dfr(ref_time_values, function(t) { self$as_of(t, min_time_value = t - before_num) %>% - tibble::as_tibble() %>% + tibble::as_tibble() %>% dplyr::group_by(!!!group_by) %>% dplyr::group_modify(comp_one_grp, - f = f, ..., + f = f, ..., time_value = t, key_vars = key_vars, new_col = new_col, @@ -378,14 +379,14 @@ epi_archive = if (length(quos) > 1) { Abort("If `f` is missing then only a single computation can be specified via `...`.") } - + quo = quos[[1]] f = function(x, quo, ...) rlang::eval_tidy(quo, x) new_col = sym(names(rlang::quos_auto_name(quos))) x = purrr::map_dfr(ref_time_values, function(t) { self$as_of(t, min_time_value = t - before_num) %>% - tibble::as_tibble() %>% + tibble::as_tibble() %>% dplyr::group_by(!!!group_by) %>% dplyr::group_modify(comp_one_grp, f = f, quo = quo, @@ -396,12 +397,12 @@ epi_archive = dplyr::ungroup() }) } - + # Unnest if we need to if (!as_list_col) { x = tidyr::unnest(x, !!new_col, names_sep = names_sep) } - + # Join to get all rows, if we need to, then return if (all_rows) { cols = c(as.character(group_by), "time_value") @@ -412,7 +413,7 @@ epi_archive = } ) ) - + #' Convert to `epi_archive` format #' #' Converts a data frame, data table, or tibble into an `epi_archive` @@ -448,15 +449,15 @@ epi_archive = #' #' @export as_epi_archive = function(x, geo_type, time_type, other_keys, - additional_metadata = list()) { - epi_archive$new(x, geo_type, time_type, other_keys, additional_metadata) + additional_metadata = list()) { + epi_archive$new(x, geo_type, time_type, other_keys, additional_metadata) } #' Test for `epi_archive` format #' #' @param x An object. #' @return `TRUE` if the object inherits from `epi_archive`. -#' +#' #' @export is_epi_archive = function(x) { inherits(x, "epi_archive") diff --git a/man/as_tsibble.epi_df.Rd b/man/as_tsibble.epi_df.Rd index ebc7fc7b..98ca7f74 100644 --- a/man/as_tsibble.epi_df.Rd +++ b/man/as_tsibble.epi_df.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/methods.R +% Please edit documentation in R/methods-epi_df.R \name{as_tsibble.epi_df} \alias{as_tsibble.epi_df} \title{Convert to tsibble format} diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 14e319c4..86cc1bda 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/methods2.R +% Please edit documentation in R/methods-epi_archive.R \name{epix_as_of} \alias{epix_as_of} \title{Generate a snapshot from an \code{epi_archive} object} diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index c48476c8..b9badcfe 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/methods2.R +% Please edit documentation in R/methods-epi_archive.R \name{epix_merge} \alias{epix_merge} \title{Merge two \code{epi_archive} objects} diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 8660e66d..2f84309d 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/methods2.R +% Please edit documentation in R/methods-epi_archive.R \name{epix_slide} \alias{epix_slide} \title{Slide a function over variables in an \code{epi_archive} object} diff --git a/man/print.epi_df.Rd b/man/print.epi_df.Rd index 94d3a2fd..9ac3af99 100644 --- a/man/print.epi_df.Rd +++ b/man/print.epi_df.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/methods.R +% Please edit documentation in R/methods-epi_df.R \name{print.epi_df} \alias{print.epi_df} \alias{summary.epi_df} diff --git a/vignettes/archive.Rmd b/vignettes/archive.Rmd index b9a12f6f..3b498a27 100644 --- a/vignettes/archive.Rmd +++ b/vignettes/archive.Rmd @@ -36,8 +36,8 @@ dv <- covidcast( signals = "smoothed_adj_cli", time_type = "day", geo_type = "state", - time_value = epirange(20200601, 20211201), - geo_value = "ca,fl", + time_values = epirange(20200601, 20211201), + geo_values = "ca,fl", issues = epirange(20200601, 20211201) ) %>% fetch_tbl() @@ -88,7 +88,7 @@ and therefore the key variables are critical for figuring out how to generate a snapshot of data from the archive, as of a given version (also described below). ```{r} -key(x$DT) +# key(x$DT) ``` In general, last observation carried forward (LOCF) is used to data in between From 4b279147c79708c0b9a05f7d09f145d01939983a Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Wed, 11 May 2022 12:50:00 -0700 Subject: [PATCH 19/41] allow an error in the archive vignette. I cannot determine the reason for the error. Creating an issue. --- vignettes/archive.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/vignettes/archive.Rmd b/vignettes/archive.Rmd index 3b498a27..90997fbc 100644 --- a/vignettes/archive.Rmd +++ b/vignettes/archive.Rmd @@ -87,8 +87,8 @@ below). There can only be a single row per unique combination of key variables, and therefore the key variables are critical for figuring out how to generate a snapshot of data from the archive, as of a given version (also described below). -```{r} -# key(x$DT) +```{r, error=TRUE} +key(x$DT) ``` In general, last observation carried forward (LOCF) is used to data in between From f92f55c163eabf3d33aaeafa4f2a0771c001d79c Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 11 May 2022 13:53:57 -0700 Subject: [PATCH 20/41] create new built-in dataset and document; update examples in roxygen --- .Rbuildignore | 6 ++- .github/.gitignore | 1 + .github/CODEOWNERS | 1 + .github/workflows/R-CMD-check.yaml | 29 +++++++++++ DESCRIPTION | 2 +- R/archive.R | 21 ++++++-- R/correlation.R | 22 ++++++-- R/data.R | 69 ++++++++++++++------------ R/slide.R | 6 ++- README.md | 5 ++ data-raw/archive_cases_dv.R | 34 +++++++++++++ data-raw/ca_daily_cases.R | 18 ------- data-raw/ca_fl_death_rate_and_cases.R | 32 ------------ data-raw/epix_doctor_visits.R | 19 ------- data-raw/jhu_csse_daily.R | 62 +++++++++++++++++++++++ data/archive_cases_dv.rda | Bin 0 -> 40398 bytes data/ca_daily_cases.rda | Bin 1775 -> 0 bytes data/ca_fl_death_rate_and_cases.rda | Bin 2635 -> 0 bytes data/epix_doctor_visits.rda | Bin 6327 -> 0 bytes data/jhu_csse_daily.rda | Bin 0 -> 1361 bytes man/archive_cases_dv.Rd | 42 ++++++++++++++++ man/as_epi_archive.Rd | 18 +++++-- man/ca_daily_cases.Rd | 26 ---------- man/ca_fl_death_rate_and_cases.Rd | 27 ---------- man/epi_cor.Rd | 22 ++++++-- man/epi_slide.Rd | 6 ++- man/epix_doctor_visits.Rd | 27 ---------- man/is_epi_archive.Rd | 3 +- man/jhu_csse_daily.Rd | 32 ++++++++++++ 29 files changed, 328 insertions(+), 202 deletions(-) create mode 100644 .github/.gitignore create mode 100644 .github/CODEOWNERS create mode 100644 .github/workflows/R-CMD-check.yaml create mode 100644 data-raw/archive_cases_dv.R delete mode 100644 data-raw/ca_daily_cases.R delete mode 100644 data-raw/ca_fl_death_rate_and_cases.R delete mode 100644 data-raw/epix_doctor_visits.R create mode 100644 data-raw/jhu_csse_daily.R create mode 100644 data/archive_cases_dv.rda delete mode 100644 data/ca_daily_cases.rda delete mode 100644 data/ca_fl_death_rate_and_cases.rda delete mode 100644 data/epix_doctor_visits.rda create mode 100644 data/jhu_csse_daily.rda create mode 100644 man/archive_cases_dv.Rd delete mode 100644 man/ca_daily_cases.Rd delete mode 100644 man/ca_fl_death_rate_and_cases.Rd delete mode 100644 man/epix_doctor_visits.Rd create mode 100644 man/jhu_csse_daily.Rd diff --git a/.Rbuildignore b/.Rbuildignore index 4b51d4a8..31e99c14 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,4 +1,8 @@ ^.*\.Rproj$ ^\.Rproj\.user$ ^LICENSE\.md$ -^data-raw$ \ No newline at end of file +<<<<<<< HEAD +^data-raw$ +======= +^\.github$ +>>>>>>> 9344e0bda0c84f7809d00478f65c1130baa30df9 diff --git a/.github/.gitignore b/.github/.gitignore new file mode 100644 index 00000000..2d19fc76 --- /dev/null +++ b/.github/.gitignore @@ -0,0 +1 @@ +*.html diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 00000000..6719131f --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1 @@ +@dajmcdon \ No newline at end of file diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml new file mode 100644 index 00000000..222d4e35 --- /dev/null +++ b/.github/workflows/R-CMD-check.yaml @@ -0,0 +1,29 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/master/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + branches: [main, master] + +name: R-CMD-check + +jobs: + R-CMD-check: + runs-on: ubuntu-latest + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + R_KEEP_PKG_SOURCE: yes + steps: + - uses: actions/checkout@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + use-public-rspm: true + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::rcmdcheck + needs: check + + - uses: r-lib/actions/check-r-package@v2 diff --git a/DESCRIPTION b/DESCRIPTION index c9f5b2f3..f83553a9 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -38,7 +38,7 @@ LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.1.2 Remotes: - cmu-delphi/delphi-epidata-r, + dajmcdon/delphi.epidata, reconverse/outbreaks Imports: data.table, diff --git a/R/archive.R b/R/archive.R index 3099538f..7cdd95d0 100644 --- a/R/archive.R +++ b/R/archive.R @@ -448,11 +448,23 @@ epi_archive = #' #' @export #' @examples +#' library(delphi.epidata) +#' library(epiprocess) +#' library(data.table) #' library(dplyr) #' -#' x <- epix_doctor_visits %>% -#' select(geo_value, time_value, version, percent_cli) %>% -#' as_epi_archive() +#' # must be given a dataframe and contain a `version` column +#' covidcast(data_source = "jhu-csse", +#' signals = "confirmed_7dav_incidence_prop", +#' time_type = "day", +#' geo_type = "state", +#' time_value = epirange(20200601, 20200603), +#' geo_values = "ca,fl", +#' issues = epirange(20200601, 20200603) +#' ) %>% +#' fetch_tbl() %>% +#' select(geo_value, time_value, version = issue, case_rate = value) %>% +#' as_epi_archive() as_epi_archive = function(x, geo_type, time_type, other_keys, additional_metadata = list()) { epi_archive$new(x, geo_type, time_type, other_keys, additional_metadata) @@ -465,7 +477,8 @@ as_epi_archive = function(x, geo_type, time_type, other_keys, #' #' @export #' @examples -#' is_epi_archive(epix_doctor_visits) +#' is_epi_archive(jhu_csse_daily) # FALSE +#' is_epi_archive(archive_cases_dv) # TRUE is_epi_archive = function(x) { inherits(x, "epi_archive") } diff --git a/R/correlation.R b/R/correlation.R index 9a71599b..67781716 100644 --- a/R/correlation.R +++ b/R/correlation.R @@ -43,16 +43,30 @@ #' @examples #' #' # linear association of case and death rates on any given day -#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = "time_value") +#' epi_cor(x = jhu_csse_daily, +#' var1 = case_rate_7d_av, +#' var2 = death_rate_7d_av, +#' cor_by = "time_value") #' #' # correlation of death rates and lagged case rates -#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = time_value, dt1 = -10) +#' epi_cor(x = jhu_csse_daily, +#' var1 = case_rate_7d_av, +#' var2 = death_rate_7d_av, +#' cor_by = time_value, +#' dt1 = -10) #' #' # correlation grouped by location -#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value) +#' epi_cor(x = jhu_csse_daily, +#' var1 = case_rate_7d_av, +#' var2 = death_rate_7d_av, +#' cor_by = geo_value) #' #' # correlation grouped by location and incorporates lagged cases rates -#' epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value, dt1 = -10) +#' epi_cor(x = jhu_csse_daily, +#' var1 = case_rate_7d_av, +#' var2 = death_rate_7d_av, +#' cor_by = geo_value, +#' dt1 = -10) epi_cor = function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value, cor_by = geo_value, use = "na.or.complete", method = c("pearson", "kendall", "spearman")) { diff --git a/R/data.R b/R/data.R index 6f0ad775..35482929 100644 --- a/R/data.R +++ b/R/data.R @@ -1,48 +1,51 @@ -#' California daily COVID-19 new cases. +#' JHU daily cases and deaths from California and Florida #' -#' A dataset containing the daily COVID-19 new cases -#' from March 1, 2020 to May 1, 2020. +#' This data source of confirmed COVID-19 cases and deaths +#' is based on reports made available by the Center for +#' Systems Science and Engineering at Johns Hopkins University. +#' This example data ranges from June 1 to June 15, 2020. #' -#' @format A tibble with 62 rows and 3 variables: +#' @format A tibble with 30 rows and 6 variables: #' \describe{ -#' \item{geo_value}{location such as the state name} -#' \item{time_value}{date} -#' \item{cases}{number of new confirmed COVID-19 cases, daily} -#' ... -#' } -#' @source \url{https://cmu-delphi.github.io/delphi-epidata/} -"ca_daily_cases" - -#' California and Florida Daily COVID-19 incidence rate and death Rates. -#' -#' A dataset containing the daily COVID-19 incidence rates and death rates -#' from March 1, 2020 to May 1, 2020. -#' -#' @format A tibble with 124 rows and 4 variables: -#' \describe{ -#' \item{geo_value}{location such as the state name} -#' \item{time_value}{date} -#' \item{case_rate}{number of new confirmed COVID-19 cases per 100,000 population, daily} -#' \item{death_rate}{number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +#' \item{geo_value}{the geographic value associated with each row of measurements.} +#' \item{time_value}{the time value associated with each row of measurements.} +#' \item{case_rate_7d_av}{7-day average signal of number of new confirmed COVID-19 cases per 100,000 population, daily} +#' \item{death_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +#' \item{cases}{Number of new confirmed COVID-19 cases, daily} +#' \item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} #' ... #' } -#' @source \url{https://cmu-delphi.github.io/delphi-epidata/} -"ca_fl_death_rate_and_cases" +#' @source COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. +#' \url{https://github.com/CSSEGISandData/COVID-19} +"jhu_csse_daily" - -#' California and Florida daily percentage of doctor’s visits with COVID-like illness. +#' Daily doctor visits and cases from California and Florida in archive format #' -#' An epi_archive dataset containing the daily COVID-19 percentage of doctor’s visits with CLI (COVID-like illness) -#' computed from medical insurance claims from June 1, 2020 to July 1, 2020. +#' This data source is based on information about outpatient visits, +#' provided to us by health system partners, and also contains confirmed +#' COVID-19 cases based on reports made available by the Center for +#' Systems Science and Engineering at Johns Hopkins University. +#' This example data ranges from June 1 to June 15, 2020. #' -#' @format A tibble with 718 rows and 4 variables: +#' @format An `epi_archive` data format. The data table DT has 160 rows and 5 columns: #' \describe{ #' \item{geo_value}{the geographic value associated with each row of measurements.} #' \item{time_value}{the time value associated with each row of measurements.} -#' \item{version}{the time value specifying the version for each row of measurements. For example, if in a given row the version is January 15, 2022 and time_value is January 14, 2022, then this row contains the measurements of the data for January 14, 2022 that were available one day later.} +#' \item{version}{ the time value specifying the version for each row of measurements. } #' \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} +#' \item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} #' ... #' } -#' @source \url{https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html} -"epix_doctor_visits" +#' @source These data sources are provided under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution license:} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{Doctor Visits} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/hospital-admissions.html}{Hospital Admissions} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/indicator-combination-inactive.html}{Indicator Combination:} signals with names beginning `nmf_` +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/quidel.html}{Quidel} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/fb-survey.html}{COVID-19 Trends and Impact Survey} +#' +#' COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. +#' \url{https://github.com/CSSEGISandData/COVID-19} +"archive_cases_dv" + diff --git a/R/slide.R b/R/slide.R index 68667f44..6759288d 100644 --- a/R/slide.R +++ b/R/slide.R @@ -89,8 +89,12 @@ #' @importFrom rlang .data .env !! enquo enquos sym #' @export #' @examples +#' library(dplyr) +#' #' # slide a 7-day trailing average formula on cases -#' epi_slide(ca_daily_cases, cases7dav = mean(cases), n = 7) +#' jhu_csse_daily %>% +#' group_by(geo_value) %>% +#' epi_slide(cases_7dav = mean(cases), n = 7) epi_slide = function(x, f, ..., n = 7, ref_time_values, align = c("right", "center", "left"), before, time_step, new_col_name = "slide_value", as_list_col = FALSE, diff --git a/README.md b/README.md index e4ed6933..a48ee8d3 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,10 @@ # epiprocess + + [![R-CMD-check](https://github.com/dajmcdon/epiprocess/workflows/R-CMD-check/badge.svg)](https://github.com/dajmcdon/epiprocess/actions) + + + This repo contains an R package `epiprocess` which introduces a common data structure for epidemiological data sets measured over space and time, and offers associated utilities to perform basic signal processing tasks. diff --git a/data-raw/archive_cases_dv.R b/data-raw/archive_cases_dv.R new file mode 100644 index 00000000..ff005f82 --- /dev/null +++ b/data-raw/archive_cases_dv.R @@ -0,0 +1,34 @@ +library(delphi.epidata) +library(epiprocess) +library(data.table) +library(dplyr) + +archive_cases_dv <- covidcast( + data_source = "doctor-visits", + signals = "smoothed_adj_cli", + time_type = "day", + geo_type = "state", + time_value = epirange(20200601, 20200615), + geo_values = "ca,fl", + issues = epirange(20200601, 20200615) +) %>% + fetch_tbl() %>% + select(geo_value, time_value, version = issue, percent_cli = value) %>% + as_epi_archive() + +case_rate <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_7dav_incidence_prop", + time_type = "day", + geo_type = "state", + time_value = epirange(20200601, 20200615), + geo_values = "ca,fl", + issues = epirange(20200601, 20200615) +) %>% + fetch_tbl() %>% + select(geo_value, time_value, version = issue, case_rate = value) %>% + as_epi_archive() + +epix_merge(archive_cases_dv, case_rate, all = TRUE) + +usethis::use_data(archive_cases_dv, overwrite = TRUE) diff --git a/data-raw/ca_daily_cases.R b/data-raw/ca_daily_cases.R deleted file mode 100644 index 0ab74df8..00000000 --- a/data-raw/ca_daily_cases.R +++ /dev/null @@ -1,18 +0,0 @@ -library(delphi.epidata) -library(epiprocess) -library(dplyr) - -ca_daily_cases <- covidcast( - data_source = "jhu-csse", - signals = "confirmed_incidence_num", - time_type = "day", - geo_type = "state", - time_values = epirange(20200301, 20200501), - geo_values = "ca" -) %>% - fetch_tbl() %>% - select(geo_value, time_value, cases = value) %>% - arrange(geo_value, time_value) %>% - as_epi_df() - -usethis::use_data(ca_daily_cases, overwrite = TRUE) diff --git a/data-raw/ca_fl_death_rate_and_cases.R b/data-raw/ca_fl_death_rate_and_cases.R deleted file mode 100644 index bd48dd67..00000000 --- a/data-raw/ca_fl_death_rate_and_cases.R +++ /dev/null @@ -1,32 +0,0 @@ - library(delphi.epidata) - library(epiprocess) - library(dplyr) - - # get data as an `epi_df` object -x <- covidcast( - data_source = "jhu-csse", - signals = "confirmed_7dav_incidence_prop", - time_type = "day", - geo_type = "state", - time_values = epirange(20200301, 20200501), - geo_values = "ca,fl" - ) %>% - fetch_tbl() %>% - select(geo_value, time_value, case_rate = value) - - y <- covidcast( - data_source = "jhu-csse", - signals = "deaths_7dav_incidence_prop", - time_type = "day", - geo_type = "state", - time_values = epirange(20200301, 20200501), - geo_values = "ca,fl" - ) %>% - fetch_tbl() %>% - select(geo_value, time_value, death_rate = value) - -ca_fl_death_rate_and_cases <- x %>% - full_join(y, by = c("geo_value", "time_value")) %>% - as_epi_df() - -usethis::use_data(ca_fl_death_rate_and_cases, overwrite = TRUE) diff --git a/data-raw/epix_doctor_visits.R b/data-raw/epix_doctor_visits.R deleted file mode 100644 index 2c2ceb7f..00000000 --- a/data-raw/epix_doctor_visits.R +++ /dev/null @@ -1,19 +0,0 @@ -library(delphi.epidata) -library(epiprocess) -library(data.table) -library(dplyr) - -epix_doctor_visits <- covidcast( - data_source = "doctor-visits", - signals = "smoothed_adj_cli", - time_type = "day", - geo_type = "state", - time_value = epirange(20200601, 20200701), - geo_value = "ca,fl", - issues = epirange(20200601, 20200701) -) %>% - fetch_tbl() %>% - select(geo_value, time_value, version = issue, percent_cli = value) - - -usethis::use_data(epix_doctor_visits, overwrite = TRUE) diff --git a/data-raw/jhu_csse_daily.R b/data-raw/jhu_csse_daily.R new file mode 100644 index 00000000..11b48f2c --- /dev/null +++ b/data-raw/jhu_csse_daily.R @@ -0,0 +1,62 @@ +library(delphi.epidata) +library(epiprocess) +library(dplyr) + +confirmed_7dav_incidence_prop <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_7dav_incidence_prop", + time_type = "day", + geo_type = "state", + time_values = epirange(20200601, 20200615), + geo_values = "ca,fl" +) %>% + fetch_tbl() %>% + select(geo_value, time_value, case_rate_7d_av = value) %>% + arrange(geo_value, time_value) + +deaths_7dav_incidence_prop <- covidcast( + data_source = "jhu-csse", + signals = "deaths_7dav_incidence_prop", + time_type = "day", + geo_type = "state", + time_values = epirange(20200601, 20200615), + geo_values = "ca,fl" +) %>% + fetch_tbl() %>% + select(geo_value, time_value, death_rate_7d_av = value) %>% + arrange(geo_value, time_value) + +confirmed_incidence_num <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_incidence_num", + time_type = "day", + geo_type = "state", + time_values = epirange(20200601, 20200615), + geo_values = "ca,fl" +) %>% + fetch_tbl() %>% + select(geo_value, time_value, cases = value) %>% + arrange(geo_value, time_value) + +confirmed_7dav_incidence_num <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_7dav_incidence_num", + time_type = "day", + geo_type = "state", + time_values = epirange(20200601, 20200615), + geo_values = "ca,fl" +) %>% + fetch_tbl() %>% + select(geo_value, time_value, cases_7d_av = value) %>% + arrange(geo_value, time_value) + +jhu_csse_daily <- confirmed_7dav_incidence_prop %>% + full_join(deaths_7dav_incidence_prop, + by = c("geo_value", "time_value")) %>% + full_join(confirmed_incidence_num, + by = c("geo_value", "time_value")) %>% + full_join(confirmed_7dav_incidence_num, + by = c("geo_value", "time_value")) %>% + as_epi_df() + +usethis::use_data(jhu_csse_daily, overwrite = TRUE) diff --git a/data/archive_cases_dv.rda b/data/archive_cases_dv.rda new file mode 100644 index 0000000000000000000000000000000000000000..ce3e0ce34679a412812cfca04092a084948c49dd GIT binary patch literal 40398 zcmagFV{oQV)IRvcwr$(CZBLSkZBA_4wry)-+nLz5wfVj8f46G)%U*TbRb748eNLaN zPge_Tn{zPEDj$g*PAI0UO8)FuVQx!I?7~!WC%t zgjJD}8Gzmg4GlsF08kB_1OcGAF3>IJvM!(jEv)sOPMQ7#WhY>DCW1dxgGwv4SP@s+ zD4L_5wC3U;uZ;e5Li~)t&#tW4xrH_a`I!USS@7h;3cRzY7QjIMZLZywx&l1%9{>== z*r_~dyO!!1RuUql5f#o$M*yHa0B{i%6=+gnoM)t)R$&Ee{wR7MEBJy?9UR{|;Mz1K z#}B~WG-8L{)0IC3K6Mk@WR zIi-d39zp9Uv)D)h7U_%%stdF8#p6LYOiAksqN9db34F3pVa$-ql0;b8 zgR8VRbklM2}5~pg$k1$>< 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zyFjv&r@Q!O?v-=QfqayHi_p@1{w_j60e&el(;z0WkW&E0*IYRWLKxI=<{AR>Xg(!` zic|uh65<|SL z#LYRHbd>nQ83KP(M&!$GCtTI_EN(RV%SONawxfx(6Wff#`Y`ZgXdv28VYuy}!K zina*o6Ji7&g{n+021>3BB(vdw6HHmBoE-cJA&}VO1Qt?5{^SjTO@G#aCUU^X%sFBW zf$VU!E*j8!?gG%*YsL|O?b0ftdDF0cBsFZEpQ%{T!bW1LG3YjRs6POLzm`{*W5^AR zA|z|wx1Q>@l;eWHlO}cyl}qtqxaRikYKMg zl*d1|FGQU}Cm;cF0we\% - select(geo_value, time_value, version, percent_cli) \%>\% - as_epi_archive() +# must be given a dataframe and contain a `version` column +covidcast(data_source = "jhu-csse", +signals = "confirmed_7dav_incidence_prop", +time_type = "day", +geo_type = "state", +time_value = epirange(20200601, 20200603), +geo_values = "ca,fl", +issues = epirange(20200601, 20200603) +) \%>\% +fetch_tbl() \%>\% +select(geo_value, time_value, version = issue, case_rate = value) \%>\% +as_epi_archive() } diff --git a/man/ca_daily_cases.Rd b/man/ca_daily_cases.Rd deleted file mode 100644 index 89c881ba..00000000 --- a/man/ca_daily_cases.Rd +++ /dev/null @@ -1,26 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/data.R -\docType{data} -\name{ca_daily_cases} -\alias{ca_daily_cases} -\title{California daily COVID-19 new cases.} -\format{ -A tibble with 62 rows and 3 variables: -\describe{ -\item{geo_value}{location such as the state name} -\item{time_value}{date} -\item{cases}{number of new confirmed COVID-19 cases, daily} -... -} -} -\source{ -\url{https://cmu-delphi.github.io/delphi-epidata/} -} -\usage{ -ca_daily_cases -} -\description{ -A dataset containing the daily COVID-19 new cases -from March 1, 2020 to May 1, 2020. -} -\keyword{datasets} diff --git a/man/ca_fl_death_rate_and_cases.Rd b/man/ca_fl_death_rate_and_cases.Rd deleted file mode 100644 index a45a98a4..00000000 --- a/man/ca_fl_death_rate_and_cases.Rd +++ /dev/null @@ -1,27 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/data.R -\docType{data} -\name{ca_fl_death_rate_and_cases} -\alias{ca_fl_death_rate_and_cases} -\title{California and Florida Daily COVID-19 incidence rate and death Rates.} -\format{ -A tibble with 124 rows and 4 variables: -\describe{ -\item{geo_value}{location such as the state name} -\item{time_value}{date} -\item{case_rate}{number of new confirmed COVID-19 cases per 100,000 population, daily} -\item{death_rate}{number of new confirmed deaths due to COVID-19 per 100,000 population, daily} -... -} -} -\source{ -\url{https://cmu-delphi.github.io/delphi-epidata/} -} -\usage{ -ca_fl_death_rate_and_cases -} -\description{ -A dataset containing the daily COVID-19 incidence rates and death rates -from March 1, 2020 to May 1, 2020. -} -\keyword{datasets} diff --git a/man/epi_cor.Rd b/man/epi_cor.Rd index fefaa931..70b01737 100644 --- a/man/epi_cor.Rd +++ b/man/epi_cor.Rd @@ -60,14 +60,28 @@ for examples. \examples{ # linear association of case and death rates on any given day -epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = "time_value") +epi_cor(x = jhu_csse_daily, + var1 = case_rate_7d_av, + var2 = death_rate_7d_av, + cor_by = "time_value") # correlation of death rates and lagged case rates -epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = time_value, dt1 = -10) +epi_cor(x = jhu_csse_daily, + var1 = case_rate_7d_av, + var2 = death_rate_7d_av, + cor_by = time_value, + dt1 = -10) # correlation grouped by location -epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value) +epi_cor(x = jhu_csse_daily, + var1 = case_rate_7d_av, + var2 = death_rate_7d_av, + cor_by = geo_value) # correlation grouped by location and incorporates lagged cases rates -epi_cor(ca_fl_death_rate_and_cases, case_rate, death_rate, cor_by = geo_value, dt1 = -10) +epi_cor(x = jhu_csse_daily, + var1 = case_rate_7d_av, + var2 = death_rate_7d_av, + cor_by = geo_value, + dt1 = -10) } diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 5eba8c78..2558b761 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -117,6 +117,10 @@ inferred from the given expression and overrides any name passed explicitly through the \code{new_col_name} argument. } \examples{ +library(dplyr) + # slide a 7-day trailing average formula on cases -epi_slide(ca_daily_cases, cases7dav = mean(cases), n = 7) + jhu_csse_daily \%>\% + group_by(geo_value) \%>\% + epi_slide(cases_7dav = mean(cases), n = 7) } diff --git a/man/epix_doctor_visits.Rd b/man/epix_doctor_visits.Rd deleted file mode 100644 index 7462a331..00000000 --- a/man/epix_doctor_visits.Rd +++ /dev/null @@ -1,27 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/data.R -\docType{data} -\name{epix_doctor_visits} -\alias{epix_doctor_visits} -\title{California and Florida daily percentage of doctor’s visits with COVID-like illness.} -\format{ -A tibble with 718 rows and 4 variables: -\describe{ -\item{geo_value}{the geographic value associated with each row of measurements.} -\item{time_value}{the time value associated with each row of measurements.} -\item{version}{the time value specifying the version for each row of measurements. For example, if in a given row the version is January 15, 2022 and time_value is January 14, 2022, then this row contains the measurements of the data for January 14, 2022 that were available one day later.} -\item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} -... -} -} -\source{ -\url{https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html} -} -\usage{ -epix_doctor_visits -} -\description{ -An epi_archive dataset containing the daily COVID-19 percentage of doctor’s visits with CLI (COVID-like illness) -computed from medical insurance claims from June 1, 2020 to July 1, 2020. -} -\keyword{datasets} diff --git a/man/is_epi_archive.Rd b/man/is_epi_archive.Rd index ff0ed004..69a45d5e 100644 --- a/man/is_epi_archive.Rd +++ b/man/is_epi_archive.Rd @@ -16,5 +16,6 @@ is_epi_archive(x) Test for \code{epi_archive} format } \examples{ -is_epi_archive(epix_doctor_visits) +is_epi_archive(jhu_csse_daily) # FALSE +is_epi_archive(archive_cases_dv) # TRUE } diff --git a/man/jhu_csse_daily.Rd b/man/jhu_csse_daily.Rd new file mode 100644 index 00000000..d3b1faad --- /dev/null +++ b/man/jhu_csse_daily.Rd @@ -0,0 +1,32 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{jhu_csse_daily} +\alias{jhu_csse_daily} +\title{JHU daily cases and deaths from California and Florida} +\format{ +A tibble with 30 rows and 6 variables: +\describe{ +\item{geo_value}{the geographic value associated with each row of measurements.} +\item{time_value}{the time value associated with each row of measurements.} +\item{case_rate_7d_av}{7-day average signal of number of new confirmed COVID-19 cases per 100,000 population, daily} +\item{death_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +\item{cases}{Number of new confirmed COVID-19 cases, daily} +\item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} +... +} +} +\source{ +COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. +\url{https://github.com/CSSEGISandData/COVID-19} +} +\usage{ +jhu_csse_daily +} +\description{ +This data source of confirmed COVID-19 cases and deaths +is based on reports made available by the Center for +Systems Science and Engineering at Johns Hopkins University. +This example data ranges from June 1 to June 15, 2020. +} +\keyword{datasets} From 06822953699a0d19dcc1a58d0be40e55f4b82510 Mon Sep 17 00:00:00 2001 From: kenmawer Date: Wed, 11 May 2022 13:59:11 -0700 Subject: [PATCH 21/41] Replaced all instances of gginnards. --- vignettes/advanced.Rmd | 10 ++++------ vignettes/archive.Rmd | 20 ++++++++------------ 2 files changed, 12 insertions(+), 18 deletions(-) diff --git a/vignettes/advanced.Rmd b/vignettes/advanced.Rmd index f93e8fba..724cfef0 100644 --- a/vignettes/advanced.Rmd +++ b/vignettes/advanced.Rmd @@ -367,18 +367,16 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), k_week_ahead(x, ahead = 28, as_of = FALSE)) # Plot them, on top of latest COVID-19 case rates -p <- ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + +ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + facet_grid(vars(geo_value), vars(as_of), scales = "free") + scale_x_date(minor_breaks = "month", date_labels = "%b %y") + labs(x = "Date", y = "Reported COVID-19 case rates") + - theme(legend.position = "none") - -gginnards::append_layers( - p, geom_line(data = x_latest, aes(x = time_value, y = case_rate), - inherit.aes = FALSE, color = "gray50"), pos = "bottom") + theme(legend.position = "none") + + geom_line(data = x_latest, aes(x = time_value, y = case_rate), + inherit.aes = FALSE, color = "gray50") ``` We can see that these forecasts, which come from training an ARX model jointly diff --git a/vignettes/archive.Rmd b/vignettes/archive.Rmd index b9a12f6f..73ce4905 100644 --- a/vignettes/archive.Rmd +++ b/vignettes/archive.Rmd @@ -175,19 +175,17 @@ snapshots <- map_dfr(versions, function(v) { bind_rows(x_latest %>% mutate(version = self_max)) %>% mutate(latest = version == self_max) -p <- ggplot(snapshots %>% filter(!latest), +ggplot(snapshots %>% filter(!latest), aes(x = time_value, y = percent_cli)) + geom_line(aes(color = factor(version))) + geom_vline(aes(color = factor(version), xintercept = version), lty = 2) + facet_wrap(~ geo_value, scales = "free_y", ncol = 1) + scale_x_date(minor_breaks = "month", date_labels = "%b %y") + labs(x = "Date", y = "% of doctor's visits with CLI") + - theme(legend.position = "none") - -gginnards::append_layers( - p, geom_line(data = snapshots %>% filter(latest), + theme(legend.position = "none") + + geom_line(data = snapshots %>% filter(latest), aes(x = time_value, y = percent_cli), - inherit.aes = FALSE, color = "black"), pos = "top") + inherit.aes = FALSE, color = "black") ``` We can see some interesting and highly nontrivial revision behavior: at some @@ -377,18 +375,16 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), k_week_ahead(x, ahead = 28, as_of = FALSE)) # Plot them, on top of latest COVID-19 case rates -p <- ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + +ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + facet_grid(vars(geo_value), vars(as_of), scales = "free") + scale_x_date(minor_breaks = "month", date_labels = "%b %y") + labs(x = "Date", y = "Reported COVID-19 case rates") + - theme(legend.position = "none") - -gginnards::append_layers( - p, geom_line(data = x_latest, aes(x = time_value, y = case_rate), - inherit.aes = FALSE, color = "gray50"), pos = "bottom") + theme(legend.position = "none") + + geom_line(data = x_latest, aes(x = time_value, y = case_rate), + inherit.aes = FALSE, color = "gray50") ``` Each row displays the forecasts for a different location (CA and FL), and each From 8d819faa3df8c3100e0a7d2d41191947ee03e1bb Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 11 May 2022 14:08:27 -0700 Subject: [PATCH 22/41] resolve build check warning --- DESCRIPTION | 24 ------------------------ 1 file changed, 24 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5a2bd1a4..893645e5 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -53,30 +53,6 @@ Encoding: UTF-8 LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.1.2 -Remotes: - dajmcdon/delphi.epidata, - reconverse/outbreaks -Imports: - data.table, - delphi.epidata, - dplyr, - fabletools, - feasts, - genlasso, - lubridate, - magrittr, - purrr, - R6, - rlang, - slider, - tibble, - tidyselect, - tidyr, - tsibble -Suggests: - outbreaks, - testthat (>= 3.0.0), -Config/testthat/edition: 3 Depends: R (>= 2.10) From 758fd5c136d5a905fffe8aea038d372cbae879a3 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 11 May 2022 18:16:45 -0700 Subject: [PATCH 23/41] make changes according to PR feedback --- R/archive.R | 31 ++++++++++++++++--------------- R/data.R | 6 ------ R/slide.R | 18 ++++++++++++++++-- man/archive_cases_dv.Rd | 5 ----- man/as_epi_archive.Rd | 31 ++++++++++++++++--------------- man/epi_slide.Rd | 18 ++++++++++++++++-- man/jhu_csse_daily.Rd | 1 - 7 files changed, 64 insertions(+), 46 deletions(-) diff --git a/R/archive.R b/R/archive.R index 3a50d45d..9840d40c 100644 --- a/R/archive.R +++ b/R/archive.R @@ -449,23 +449,24 @@ epi_archive = #' #' @export #' @examples -#' library(delphi.epidata) -#' library(epiprocess) -#' library(data.table) #' library(dplyr) #' -#' # must be given a dataframe and contain a `version` column -#' covidcast(data_source = "jhu-csse", -#' signals = "confirmed_7dav_incidence_prop", -#' time_type = "day", -#' geo_type = "state", -#' time_value = epirange(20200601, 20200603), -#' geo_values = "ca,fl", -#' issues = epirange(20200601, 20200603) -#' ) %>% -#' fetch_tbl() %>% -#' select(geo_value, time_value, version = issue, case_rate = value) %>% -#' as_epi_archive() +#' df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), +#' county = c(1, 3, 2, 5), +#' time_value = c("2020-06-01", +#' "2020-06-02", +#' "2020-06-01", +#' "2020-06-02"), +#' version = c("2020-06-02", +#' "2020-06-03", +#' "2020-06-02", +#' "2020-06-03"), +#' cases = c(1, 2, 3, 4), +#' cases_rate = c(0.01, 0.02, 0.01, 0.05)) +#' +#' x <- df %>% as_epi_archive(geo_type = "state", +#' time_type = "day", +#' other_keys = "county") as_epi_archive = function(x, geo_type, time_type, other_keys, additional_metadata = list()) { epi_archive$new(x, geo_type, time_type, other_keys, additional_metadata) diff --git a/R/data.R b/R/data.R index 35482929..06ae93b8 100644 --- a/R/data.R +++ b/R/data.R @@ -13,7 +13,6 @@ #' \item{death_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} #' \item{cases}{Number of new confirmed COVID-19 cases, daily} #' \item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} -#' ... #' } #' @source COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. #' \url{https://github.com/CSSEGISandData/COVID-19} @@ -35,15 +34,10 @@ #' \item{version}{ the time value specifying the version for each row of measurements. } #' \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} #' \item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} -#' ... #' } #' @source These data sources are provided under the terms of the #' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution license:} #' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{Doctor Visits} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/hospital-admissions.html}{Hospital Admissions} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/indicator-combination-inactive.html}{Indicator Combination:} signals with names beginning `nmf_` -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/quidel.html}{Quidel} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/fb-survey.html}{COVID-19 Trends and Impact Survey} #' #' COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. #' \url{https://github.com/CSSEGISandData/COVID-19} diff --git a/R/slide.R b/R/slide.R index 6759288d..65bc88d9 100644 --- a/R/slide.R +++ b/R/slide.R @@ -91,10 +91,24 @@ #' @examples #' library(dplyr) #' -#' # slide a 7-day trailing average formula on cases +#' # slide a 7-day trailing average formula on cases #' jhu_csse_daily %>% #' group_by(geo_value) %>% -#' epi_slide(cases_7dav = mean(cases), n = 7) +#' epi_slide(cases_7dav = mean(cases), n = 7, +#' align = "right") +#' +#' # slide a left-aligned 7-day trailing average +#' jhu_csse_daily %>% +#' group_by(geo_value) %>% +#' epi_slide(cases_7dav = mean(cases), n = 7, +#' align = "left") +#' +#' # nested new columns +#' jhu_csse_daily %>% +#' group_by(geo_value) %>% +#' epi_slide(a = data.frame(cases_2dav = mean(cases), +#' cases_2dma = mad(cases)), +#' n = 2, as_list_col = TRUE) epi_slide = function(x, f, ..., n = 7, ref_time_values, align = c("right", "center", "left"), before, time_step, new_col_name = "slide_value", as_list_col = FALSE, diff --git a/man/archive_cases_dv.Rd b/man/archive_cases_dv.Rd index 49c3db99..2d4594a1 100644 --- a/man/archive_cases_dv.Rd +++ b/man/archive_cases_dv.Rd @@ -12,7 +12,6 @@ An \code{epi_archive} data format. The data table DT has 160 rows and 5 columns: \item{version}{ the time value specifying the version for each row of measurements. } \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} \item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} -... } } \source{ @@ -20,10 +19,6 @@ These data sources are provided under the terms of the \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution license:} \itemize{ \item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{Doctor Visits} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/hospital-admissions.html}{Hospital Admissions} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/indicator-combination-inactive.html}{Indicator Combination:} signals with names beginning \code{nmf_} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/quidel.html}{Quidel} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/fb-survey.html}{COVID-19 Trends and Impact Survey} } COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. diff --git a/man/as_epi_archive.Rd b/man/as_epi_archive.Rd index cd885e7f..81dfb09d 100644 --- a/man/as_epi_archive.Rd +++ b/man/as_epi_archive.Rd @@ -49,21 +49,22 @@ would be equivalent to:\preformatted{x <- epi_archive$new(df, geo_type = "state" } } \examples{ -library(delphi.epidata) -library(epiprocess) -library(data.table) library(dplyr) -# must be given a dataframe and contain a `version` column -covidcast(data_source = "jhu-csse", -signals = "confirmed_7dav_incidence_prop", -time_type = "day", -geo_type = "state", -time_value = epirange(20200601, 20200603), -geo_values = "ca,fl", -issues = epirange(20200601, 20200603) -) \%>\% -fetch_tbl() \%>\% -select(geo_value, time_value, version = issue, case_rate = value) \%>\% -as_epi_archive() +df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), + county = c(1, 3, 2, 5), + time_value = c("2020-06-01", + "2020-06-02", + "2020-06-01", + "2020-06-02"), + version = c("2020-06-02", + "2020-06-03", + "2020-06-02", + "2020-06-03"), + cases = c(1, 2, 3, 4), + cases_rate = c(0.01, 0.02, 0.01, 0.05)) + +x <- df \%>\% as_epi_archive(geo_type = "state", + time_type = "day", + other_keys = "county") } diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 2558b761..87c8b4fd 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -119,8 +119,22 @@ through the \code{new_col_name} argument. \examples{ library(dplyr) -# slide a 7-day trailing average formula on cases + # slide a 7-day trailing average formula on cases jhu_csse_daily \%>\% group_by(geo_value) \%>\% - epi_slide(cases_7dav = mean(cases), n = 7) + epi_slide(cases_7dav = mean(cases), n = 7, + align = "right") + + # slide a left-aligned 7-day trailing average + jhu_csse_daily \%>\% + group_by(geo_value) \%>\% + epi_slide(cases_7dav = mean(cases), n = 7, + align = "left") + + # nested new columns + jhu_csse_daily \%>\% + group_by(geo_value) \%>\% + epi_slide(a = data.frame(cases_2dav = mean(cases), + cases_2dma = mad(cases)), + n = 2, as_list_col = TRUE) } diff --git a/man/jhu_csse_daily.Rd b/man/jhu_csse_daily.Rd index d3b1faad..4fd22e6e 100644 --- a/man/jhu_csse_daily.Rd +++ b/man/jhu_csse_daily.Rd @@ -13,7 +13,6 @@ A tibble with 30 rows and 6 variables: \item{death_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} \item{cases}{Number of new confirmed COVID-19 cases, daily} \item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} -... } } \source{ From 094bf64912f842b35b955db8c2082f2a4f87da54 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 11 May 2022 23:10:27 -0700 Subject: [PATCH 24/41] outlier examples added --- R/outliers.R | 49 +++++++++++++++++++++++++++++++++++++++++ man/detect_outlr.Rd | 29 ++++++++++++++++++++++++ man/detect_outlr_rm.Rd | 10 +++++++++ man/detect_outlr_stl.Rd | 11 +++++++++ 4 files changed, 99 insertions(+) diff --git a/R/outliers.R b/R/outliers.R index 7f4ddf00..5da7b739 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -44,6 +44,34 @@ #' STL decomposition. #' #' @export +#' @examples +#' library(dplyr) +#' +#' detection_methods = bind_rows( +#' tibble(method = "rm", +#' args = list(list(detect_negatives = TRUE, +#' detection_multiplier = 2.5)), +#' abbr = "rm"), +#' tibble(method = "stl", +#' args = list(list(detect_negatives = TRUE, +#' detection_multiplier = 2.5, +#' seasonal_period = 7)), +#' abbr = "stl_seasonal"), +#' tibble(method = "stl", +#' args = list(list(detect_negatives = TRUE, +#' detection_multiplier = 2.5, +#' seasonal_period = NULL)), +#' abbr = "stl_nonseasonal")) +#' +#' x <- jhu_csse_daily %>% +#' select(geo_value,time_value,cases) %>% +#' as_epi_df()%>% +#' group_by(geo_value) %>% +#' mutate(outlier_info = detect_outlr( +#' x = time_value, y = cases, +#' methods = detection_methods, +#' combiner = "median")) %>% +#' unnest(outlier_info) detect_outlr = function(x = seq_along(y), y, methods = tibble::tibble(method = "rm", args = list(list()), @@ -120,6 +148,16 @@ detect_outlr = function(x = seq_along(y), y, #' `lower`, `upper`, and `replacement`. #' #' @export +#' @examples +#' library(dplyr) +# # Detect outliers based on a rolling median +#' jhu_csse_daily %>% +#' select(geo_value,time_value,cases) %>% +#' as_epi_df()%>% +#' group_by(geo_value) %>% +#' mutate(outlier_info = detect_outlr_rm( +#' x = time_value, y = cases)) %>% +#' unnest(outlier_info) detect_outlr_rm = function(x = seq_along(y), y, n = 21, log_transform = FALSE, detect_negatives = FALSE, @@ -208,6 +246,17 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @importFrom stats median #' @importFrom tidyselect starts_with #' @export +#' @examples +#' library(dplyr) +# # Detects outliers based on a seasonal-trend decomposition using LOESS +#' jhu_csse_daily %>% +#' select(geo_value,time_value,cases) %>% +#' as_epi_df()%>% +#' group_by(geo_value) %>% +#' mutate(outlier_info = detect_outlr_stl( +#' x = time_value, y = cases, +#' seasonal_period = 7 )) %>% # weekly seasonality for daily data +#' unnest(outlier_info) detect_outlr_stl = function(x = seq_along(y), y, n_trend = 21, n_seasonal = 21, diff --git a/man/detect_outlr.Rd b/man/detect_outlr.Rd index d832cd6d..4614c254 100644 --- a/man/detect_outlr.Rd +++ b/man/detect_outlr.Rd @@ -63,3 +63,32 @@ For convenience, the outlier detection method can be specified (in the "stl", shorthand for \code{detect_outlr_stl()}, which detects outliers via an STL decomposition. } +\examples{ + library(dplyr) + + detection_methods = bind_rows( + tibble(method = "rm", + args = list(list(detect_negatives = TRUE, + detection_multiplier = 2.5)), + abbr = "rm"), + tibble(method = "stl", + args = list(list(detect_negatives = TRUE, + detection_multiplier = 2.5, + seasonal_period = 7)), + abbr = "stl_seasonal"), + tibble(method = "stl", + args = list(list(detect_negatives = TRUE, + detection_multiplier = 2.5, + seasonal_period = NULL)), + abbr = "stl_nonseasonal")) + + x <- jhu_csse_daily \%>\% + select(geo_value,time_value,cases) \%>\% + as_epi_df()\%>\% + group_by(geo_value) \%>\% + mutate(outlier_info = detect_outlr( + x = time_value, y = cases, + methods = detection_methods, + combiner = "median")) \%>\% + unnest(outlier_info) +} diff --git a/man/detect_outlr_rm.Rd b/man/detect_outlr_rm.Rd index 55410eb9..c6149158 100644 --- a/man/detect_outlr_rm.Rd +++ b/man/detect_outlr_rm.Rd @@ -52,3 +52,13 @@ A tibble with number of rows equal to \code{length(y)}, and columns Detects outliers based on a distance from the rolling median specified in terms of multiples of the rolling interquartile range (IQR). } +\examples{ +library(dplyr) +jhu_csse_daily \%>\% + select(geo_value,time_value,cases) \%>\% + as_epi_df()\%>\% + group_by(geo_value) \%>\% + mutate(outlier_info = detect_outlr_rm( + x = time_value, y = cases)) \%>\% + unnest(outlier_info) +} diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index 6bf6882a..cd72bc7e 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -75,3 +75,14 @@ residuals to the rolling median, respectively. The last set of arguments, \code{log_transform} through \code{replacement_multiplier}, are exactly as in \code{detect_outlr_rm()}. } +\examples{ +library(dplyr) +jhu_csse_daily \%>\% + select(geo_value,time_value,cases) \%>\% + as_epi_df()\%>\% + group_by(geo_value) \%>\% + mutate(outlier_info = detect_outlr_stl( + x = time_value, y = cases, + seasonal_period = 7 )) \%>\% # weekly seasonality for daily data + unnest(outlier_info) +} From 03b083d63fe457f1f320729ebdcae248095ea320 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Wed, 11 May 2022 23:31:17 -0700 Subject: [PATCH 25/41] save wip epix method examples --- R/methods-epi_archive.R | 14 ++++++++++++++ man/epix_as_of.Rd | 4 ++++ man/epix_merge.Rd | 12 ++++++++++++ 3 files changed, 30 insertions(+) diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index ddf3e795..c8af70bf 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -27,6 +27,9 @@ #' ``` #' #' @export +#' @examples +#' epix_as_of(archive_cases_dv, +#' max_version = max(archive_cases_dv$DT$version)) epix_as_of = function(x, max_version, min_time_value = -Inf) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") return(x$as_of(max_version, min_time_value)) @@ -67,6 +70,17 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' ``` #' #' @export +#' @examples +#' # create two example epi_archive datasets +#' x <- archive_cases_dv$DT %>% +#' select(geo_value,time_value,version,case_rate) %>% +#' as_epi_archive() +#' y <- archive_cases_dv$DT %>% +#' select(geo_value,time_value,version,percent_cli) %>% +#' as_epi_archive() +#' +#' # a full join stored in x +#' epix_merge(x, y, all = TRUE) epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") return(x$merge(y, ..., locf = locf, nan = nan)) diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 86cc1bda..7423192a 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -35,3 +35,7 @@ This is simply a wrapper around the \code{as_of()} method of the is equivalent to:\preformatted{x$as_of(max_version = v) } } +\examples{ +epix_as_of(archive_cases_dv, + max_version = max(archive_cases_dv$DT$version)) +} diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index b9badcfe..41e63519 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -41,3 +41,15 @@ This is simply a wrapper around the \code{merge()} method of the is equivalent to:\preformatted{x$merge(y) } } +\examples{ +# create two example epi_archive datasets +x <- archive_cases_dv$DT \%>\% + select(geo_value,time_value,version,case_rate) \%>\% + as_epi_archive() +y <- archive_cases_dv$DT \%>\% + select(geo_value,time_value,version,percent_cli) \%>\% + as_epi_archive() + +# a full join stored in x +epix_merge(x, y, all = TRUE) +} From c8707a055617a095833415551fa581ce75134f2c Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Thu, 12 May 2022 12:42:21 -0700 Subject: [PATCH 26/41] finish examples for epix_ --- R/methods-epi_archive.R | 12 ++++++++++++ man/epix_merge.Rd | 1 + man/epix_slide.Rd | 12 ++++++++++++ 3 files changed, 25 insertions(+) diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index c8af70bf..08e37ac9 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -71,6 +71,7 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' #' @export #' @examples +#' library(dplyr) #' # create two example epi_archive datasets #' x <- archive_cases_dv$DT %>% #' select(geo_value,time_value,version,case_rate) %>% @@ -181,6 +182,17 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' #' @importFrom rlang enquo #' @export +#' @examples +#' # every date is a reference time point for the 3 day average sliding window +#' fc_time_values <- seq(as.Date("2020-06-01"), +#' as.Date("2020-06-15"), +#' by = "1 day") +#' epix_slide(x = archive_cases_dv, +#' f = ~ mean(.x$case_rate), +#' n = 3, +#' group_by = geo_value, +#' ref_time_values = fc_time_values, +#' new_col_name = 'case_rate_3d_av') epix_slide = function(x, f, ..., n = 7, group_by, ref_time_values, time_step, new_col_name = "slide_value", as_list_col = FALSE, names_sep = "_", all_rows = FALSE) { diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index 41e63519..cae278e9 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -42,6 +42,7 @@ is equivalent to:\preformatted{x$merge(y) } } \examples{ +library(dplyr) # create two example epi_archive datasets x <- archive_cases_dv$DT \%>\% select(geo_value,time_value,version,case_rate) \%>\% diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 2f84309d..231f2646 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -121,3 +121,15 @@ Finally, this is simply a wrapper around the \code{slide()} method of the is equivalent to:\preformatted{x$slide(x, new_var = comp(old_var), n = 120) } } +\examples{ +# every date is a reference time point for the 3 day average sliding window +fc_time_values <- seq(as.Date("2020-06-01"), + as.Date("2020-06-15"), + by = "1 day") +epix_slide(x = archive_cases_dv, + f = ~ mean(.x$case_rate), + n = 3, + group_by = geo_value, + ref_time_values = fc_time_values, + new_col_name = 'case_rate_3d_av') +} From 74761ac9662dab29b220e5ef3e35c40c4f542c4e Mon Sep 17 00:00:00 2001 From: kenmawer Date: Thu, 12 May 2022 13:49:02 -0700 Subject: [PATCH 27/41] Removed gginnards --- DESCRIPTION | 1 - 1 file changed, 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index b28a4b37..189c39dd 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -37,7 +37,6 @@ Imports: Suggests: covidcast, delphi.epidata, - gginnards, ggplot2, knitr, outbreaks, From c910106c8fadbba99d92336bb6c8514175d37c50 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Thu, 12 May 2022 21:08:33 -0700 Subject: [PATCH 28/41] resolve dplyr::select issue in examples --- NAMESPACE | 1 + R/archive.R | 2 -- R/methods-epi_archive.R | 7 +++---- R/outliers.R | 19 ++++++++----------- R/slide.R | 2 -- man/as_epi_archive.Rd | 2 -- man/detect_outlr.Rd | 12 +++++------- man/detect_outlr_rm.Rd | 3 +-- man/detect_outlr_stl.Rd | 3 +-- man/epi_slide.Rd | 2 -- man/epix_as_of.Rd | 2 +- man/epix_merge.Rd | 5 ++--- 12 files changed, 22 insertions(+), 38 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index eaaf4182..11f488e4 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -59,6 +59,7 @@ importFrom(dplyr,group_modify) importFrom(dplyr,mutate) importFrom(dplyr,relocate) importFrom(dplyr,rename) +importFrom(dplyr,select) importFrom(dplyr,slice) importFrom(dplyr,ungroup) importFrom(lubridate,days) diff --git a/R/archive.R b/R/archive.R index 9840d40c..9fb7c27b 100644 --- a/R/archive.R +++ b/R/archive.R @@ -449,8 +449,6 @@ epi_archive = #' #' @export #' @examples -#' library(dplyr) -#' #' df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), #' county = c(1, 3, 2, 5), #' time_value = c("2020-06-01", diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index 08e37ac9..cedb0374 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -28,7 +28,7 @@ #' #' @export #' @examples -#' epix_as_of(archive_cases_dv, +#' epix_as_of(x = archive_cases_dv, #' max_version = max(archive_cases_dv$DT$version)) epix_as_of = function(x, max_version, min_time_value = -Inf) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") @@ -71,13 +71,12 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' #' @export #' @examples -#' library(dplyr) #' # create two example epi_archive datasets #' x <- archive_cases_dv$DT %>% -#' select(geo_value,time_value,version,case_rate) %>% +#' dplyr::select(geo_value,time_value,version,case_rate) %>% #' as_epi_archive() #' y <- archive_cases_dv$DT %>% -#' select(geo_value,time_value,version,percent_cli) %>% +#' dplyr::select(geo_value,time_value,version,percent_cli) %>% #' as_epi_archive() #' #' # a full join stored in x diff --git a/R/outliers.R b/R/outliers.R index 5da7b739..c6df6f22 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -44,27 +44,26 @@ #' STL decomposition. #' #' @export +#' @importFrom dplyr select #' @examples -#' library(dplyr) -#' -#' detection_methods = bind_rows( -#' tibble(method = "rm", +#' detection_methods = dplyr::bind_rows( +#' dplyr::tibble(method = "rm", #' args = list(list(detect_negatives = TRUE, #' detection_multiplier = 2.5)), #' abbr = "rm"), -#' tibble(method = "stl", +#' dplyr::tibble(method = "stl", #' args = list(list(detect_negatives = TRUE, #' detection_multiplier = 2.5, #' seasonal_period = 7)), #' abbr = "stl_seasonal"), -#' tibble(method = "stl", +#' dplyr::tibble(method = "stl", #' args = list(list(detect_negatives = TRUE, #' detection_multiplier = 2.5, #' seasonal_period = NULL)), #' abbr = "stl_nonseasonal")) #' #' x <- jhu_csse_daily %>% -#' select(geo_value,time_value,cases) %>% +#' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df()%>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr( @@ -149,10 +148,9 @@ detect_outlr = function(x = seq_along(y), y, #' #' @export #' @examples -#' library(dplyr) # # Detect outliers based on a rolling median #' jhu_csse_daily %>% -#' select(geo_value,time_value,cases) %>% +#' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df()%>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr_rm( @@ -247,10 +245,9 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @importFrom tidyselect starts_with #' @export #' @examples -#' library(dplyr) # # Detects outliers based on a seasonal-trend decomposition using LOESS #' jhu_csse_daily %>% -#' select(geo_value,time_value,cases) %>% +#' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df()%>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr_stl( diff --git a/R/slide.R b/R/slide.R index 65bc88d9..07652c3d 100644 --- a/R/slide.R +++ b/R/slide.R @@ -89,8 +89,6 @@ #' @importFrom rlang .data .env !! enquo enquos sym #' @export #' @examples -#' library(dplyr) -#' #' # slide a 7-day trailing average formula on cases #' jhu_csse_daily %>% #' group_by(geo_value) %>% diff --git a/man/as_epi_archive.Rd b/man/as_epi_archive.Rd index 81dfb09d..bb32ebfd 100644 --- a/man/as_epi_archive.Rd +++ b/man/as_epi_archive.Rd @@ -49,8 +49,6 @@ would be equivalent to:\preformatted{x <- epi_archive$new(df, geo_type = "state" } } \examples{ -library(dplyr) - df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), county = c(1, 3, 2, 5), time_value = c("2020-06-01", diff --git a/man/detect_outlr.Rd b/man/detect_outlr.Rd index 4614c254..297fb42b 100644 --- a/man/detect_outlr.Rd +++ b/man/detect_outlr.Rd @@ -64,26 +64,24 @@ For convenience, the outlier detection method can be specified (in the STL decomposition. } \examples{ - library(dplyr) - - detection_methods = bind_rows( - tibble(method = "rm", + detection_methods = dplyr::bind_rows( + dplyr::tibble(method = "rm", args = list(list(detect_negatives = TRUE, detection_multiplier = 2.5)), abbr = "rm"), - tibble(method = "stl", + dplyr::tibble(method = "stl", args = list(list(detect_negatives = TRUE, detection_multiplier = 2.5, seasonal_period = 7)), abbr = "stl_seasonal"), - tibble(method = "stl", + dplyr::tibble(method = "stl", args = list(list(detect_negatives = TRUE, detection_multiplier = 2.5, seasonal_period = NULL)), abbr = "stl_nonseasonal")) x <- jhu_csse_daily \%>\% - select(geo_value,time_value,cases) \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df()\%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr( diff --git a/man/detect_outlr_rm.Rd b/man/detect_outlr_rm.Rd index c6149158..39cbacf3 100644 --- a/man/detect_outlr_rm.Rd +++ b/man/detect_outlr_rm.Rd @@ -53,9 +53,8 @@ Detects outliers based on a distance from the rolling median specified in terms of multiples of the rolling interquartile range (IQR). } \examples{ -library(dplyr) jhu_csse_daily \%>\% - select(geo_value,time_value,cases) \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df()\%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr_rm( diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index cd72bc7e..ea1e8cb1 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -76,9 +76,8 @@ The last set of arguments, \code{log_transform} through \code{replacement_multip are exactly as in \code{detect_outlr_rm()}. } \examples{ -library(dplyr) jhu_csse_daily \%>\% - select(geo_value,time_value,cases) \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df()\%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr_stl( diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 87c8b4fd..1e42dbf3 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -117,8 +117,6 @@ inferred from the given expression and overrides any name passed explicitly through the \code{new_col_name} argument. } \examples{ -library(dplyr) - # slide a 7-day trailing average formula on cases jhu_csse_daily \%>\% group_by(geo_value) \%>\% diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 7423192a..94961074 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -36,6 +36,6 @@ is equivalent to:\preformatted{x$as_of(max_version = v) } } \examples{ -epix_as_of(archive_cases_dv, +epix_as_of(x = archive_cases_dv, max_version = max(archive_cases_dv$DT$version)) } diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index cae278e9..59bade72 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -42,13 +42,12 @@ is equivalent to:\preformatted{x$merge(y) } } \examples{ -library(dplyr) # create two example epi_archive datasets x <- archive_cases_dv$DT \%>\% - select(geo_value,time_value,version,case_rate) \%>\% + dplyr::select(geo_value,time_value,version,case_rate) \%>\% as_epi_archive() y <- archive_cases_dv$DT \%>\% - select(geo_value,time_value,version,percent_cli) \%>\% + dplyr::select(geo_value,time_value,version,percent_cli) \%>\% as_epi_archive() # a full join stored in x From c5f09ef433992e7e6ed39fd205a427a9a1642b1a Mon Sep 17 00:00:00 2001 From: kenmawer Date: Fri, 13 May 2022 10:38:42 -0700 Subject: [PATCH 29/41] Fixed the wrong layering of the ggplots. --- vignettes/advanced.Rmd | 6 +++--- vignettes/archive.Rmd | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/vignettes/advanced.Rmd b/vignettes/advanced.Rmd index 724cfef0..5d6855f1 100644 --- a/vignettes/advanced.Rmd +++ b/vignettes/advanced.Rmd @@ -369,14 +369,14 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), # Plot them, on top of latest COVID-19 case rates ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + + geom_line(data = x_latest, aes(x = time_value, y = case_rate), + inherit.aes = FALSE, color = "gray50") + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + facet_grid(vars(geo_value), vars(as_of), scales = "free") + scale_x_date(minor_breaks = "month", date_labels = "%b %y") + labs(x = "Date", y = "Reported COVID-19 case rates") + - theme(legend.position = "none") + - geom_line(data = x_latest, aes(x = time_value, y = case_rate), - inherit.aes = FALSE, color = "gray50") + theme(legend.position = "none") ``` We can see that these forecasts, which come from training an ARX model jointly diff --git a/vignettes/archive.Rmd b/vignettes/archive.Rmd index a6e01e6c..120e6ad5 100644 --- a/vignettes/archive.Rmd +++ b/vignettes/archive.Rmd @@ -377,14 +377,14 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), # Plot them, on top of latest COVID-19 case rates ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + + geom_line(data = x_latest, aes(x = time_value, y = case_rate), + inherit.aes = FALSE, color = "gray50") + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + facet_grid(vars(geo_value), vars(as_of), scales = "free") + scale_x_date(minor_breaks = "month", date_labels = "%b %y") + labs(x = "Date", y = "Reported COVID-19 case rates") + - theme(legend.position = "none") + - geom_line(data = x_latest, aes(x = time_value, y = case_rate), - inherit.aes = FALSE, color = "gray50") + theme(legend.position = "none") ``` Each row displays the forecasts for a different location (CA and FL), and each From ccf748abb3e84a723b2187fd0f728ede5765d3c4 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Wed, 18 May 2022 12:27:59 -0700 Subject: [PATCH 30/41] rebuild docs --- DESCRIPTION | 2 +- man/as_epi_archive.Rd | 12 ++++++++---- man/epi_archive.Rd | 36 ++++++++++++++++++------------------ man/epi_slide.Rd | 12 ++++++++---- man/epix_as_of.Rd | 12 ++++++++---- man/epix_merge.Rd | 12 ++++++++---- man/epix_slide.Rd | 12 ++++++++---- 7 files changed, 59 insertions(+), 39 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index b28a4b37..6c62ae60 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -52,4 +52,4 @@ Config/testthat/edition: 3 Encoding: UTF-8 LazyData: true Roxygen: list(markdown = TRUE) -RoxygenNote: 7.1.2 +RoxygenNote: 7.2.0 diff --git a/man/as_epi_archive.Rd b/man/as_epi_archive.Rd index 191b708b..1144c47f 100644 --- a/man/as_epi_archive.Rd +++ b/man/as_epi_archive.Rd @@ -42,9 +42,13 @@ examples. } \details{ This simply a wrapper around the \code{new()} method of the \code{epi_archive} -class, so for example:\preformatted{x <- as_epi_archive(df, geo_type = "state", time_type = "day") -} +class, so for example: -would be equivalent to:\preformatted{x <- epi_archive$new(df, geo_type = "state", time_type = "day") -} +\if{html}{\out{
}}\preformatted{x <- as_epi_archive(df, geo_type = "state", time_type = "day") +}\if{html}{\out{
}} + +would be equivalent to: + +\if{html}{\out{
}}\preformatted{x <- epi_archive$new(df, geo_type = "state", time_type = "day") +}\if{html}{\out{
}} } diff --git a/man/epi_archive.Rd b/man/epi_archive.Rd index fff4e714..5214b01d 100644 --- a/man/epi_archive.Rd +++ b/man/epi_archive.Rd @@ -84,17 +84,17 @@ are documented in the wrapper function \code{epix_slide()}. \section{Methods}{ \subsection{Public methods}{ \itemize{ -\item \href{#method-new}{\code{epi_archive$new()}} -\item \href{#method-print}{\code{epi_archive$print()}} -\item \href{#method-as_of}{\code{epi_archive$as_of()}} -\item \href{#method-merge}{\code{epi_archive$merge()}} -\item \href{#method-slide}{\code{epi_archive$slide()}} -\item \href{#method-clone}{\code{epi_archive$clone()}} +\item \href{#method-epi_archive-new}{\code{epi_archive$new()}} +\item \href{#method-epi_archive-print}{\code{epi_archive$print()}} +\item \href{#method-epi_archive-as_of}{\code{epi_archive$as_of()}} +\item \href{#method-epi_archive-merge}{\code{epi_archive$merge()}} +\item \href{#method-epi_archive-slide}{\code{epi_archive$slide()}} +\item \href{#method-epi_archive-clone}{\code{epi_archive$clone()}} } } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-new}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-new}{}}} \subsection{Method \code{new()}}{ Creates a new \code{epi_archive} object. \subsection{Usage}{ @@ -130,8 +130,8 @@ An \code{epi_archive} object. } } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-print}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-print}{}}} \subsection{Method \code{print()}}{ \subsection{Usage}{ \if{html}{\out{
}}\preformatted{epi_archive$print()}\if{html}{\out{
}} @@ -139,8 +139,8 @@ An \code{epi_archive} object. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-as_of}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-as_of}{}}} \subsection{Method \code{as_of()}}{ Generates a snapshot in \code{epi_df} format as of a given version. See the documentation for the wrapper function \code{epix_as_of()} for details. @@ -150,8 +150,8 @@ See the documentation for the wrapper function \code{epix_as_of()} for details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-merge}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-merge}{}}} \subsection{Method \code{merge()}}{ Merges another \code{data.table} with the current one, and allows for a post-filling of \code{NA} values by last observation carried forward (LOCF). @@ -162,8 +162,8 @@ See the documentation for the wrapper function \code{epix_merge()} for details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-slide}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-slide}{}}} \subsection{Method \code{slide()}}{ Slides a given function over variables in an \code{epi_archive} object. See the documentation for the wrapper function \code{epix_as_of()} for @@ -185,8 +185,8 @@ details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-clone}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-epi_archive-clone}{}}} \subsection{Method \code{clone()}}{ The objects of this class are cloneable with this method. \subsection{Usage}{ diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 6aa4addf..9656a8af 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -104,12 +104,16 @@ incomplete windows) is therefore left up to the user, either through the specified function or formula \code{f}, or through post-processing. If \code{f} is missing, then an expression for tidy evaluation can be specified, -for example, as in:\preformatted{epi_slide(x, cases_7dav = mean(cases), n = 7) -} +for example, as in: + +\if{html}{\out{
}}\preformatted{epi_slide(x, cases_7dav = mean(cases), n = 7) +}\if{html}{\out{
}} -which would be equivalent to:\preformatted{epi_slide(x, function(x, ...) mean(x$cases), n = 7, +which would be equivalent to: + +\if{html}{\out{
}}\preformatted{epi_slide(x, function(x, ...) mean(x$cases), n = 7, new_col_name = "cases_7dav") -} +}\if{html}{\out{
}} Thus, to be clear, when the computation is specified via an expression for tidy evaluation (first example, above), then the name for the new column is diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 86cc1bda..c10db01b 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -29,9 +29,13 @@ examples. } \details{ This is simply a wrapper around the \code{as_of()} method of the -\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then:\preformatted{epix_as_of(x, max_version = v) -} +\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then: -is equivalent to:\preformatted{x$as_of(max_version = v) -} +\if{html}{\out{
}}\preformatted{epix_as_of(x, max_version = v) +}\if{html}{\out{
}} + +is equivalent to: + +\if{html}{\out{
}}\preformatted{x$as_of(max_version = v) +}\if{html}{\out{
}} } diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index b9badcfe..1dfbc3aa 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -35,9 +35,13 @@ examples. } \details{ This is simply a wrapper around the \code{merge()} method of the -\code{epi_archive} class, so if \code{x} and \code{y} are an \code{epi_archive} objects, then:\preformatted{epix_merge(x, y) -} +\code{epi_archive} class, so if \code{x} and \code{y} are an \code{epi_archive} objects, then: -is equivalent to:\preformatted{x$merge(y) -} +\if{html}{\out{
}}\preformatted{epix_merge(x, y) +}\if{html}{\out{
}} + +is equivalent to: + +\if{html}{\out{
}}\preformatted{x$merge(y) +}\if{html}{\out{
}} } diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 2f84309d..414b4c2e 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -115,9 +115,13 @@ should never be used in place of \code{epi_slide()}, and only used when version-aware sliding is necessary (as it its purpose). Finally, this is simply a wrapper around the \code{slide()} method of the -\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then:\preformatted{epix_slide(x, new_var = comp(old_var), n = 120) -} +\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then: -is equivalent to:\preformatted{x$slide(x, new_var = comp(old_var), n = 120) -} +\if{html}{\out{
}}\preformatted{epix_slide(x, new_var = comp(old_var), n = 120) +}\if{html}{\out{
}} + +is equivalent to: + +\if{html}{\out{
}}\preformatted{x$slide(x, new_var = comp(old_var), n = 120) +}\if{html}{\out{
}} } From 3c83c725278ba45eafc42f32dbeb826394ddc963 Mon Sep 17 00:00:00 2001 From: "Daniel J. McDonald" Date: Wed, 18 May 2022 12:48:26 -0700 Subject: [PATCH 31/41] handle minor formatting feedback from @brookslogan --- R/archive.R | 20 ++++----- R/methods-epi_archive.R | 56 ++++++++++++------------ R/outliers.R | 94 ++++++++++++++++++++--------------------- man/as_epi_archive.Rd | 14 +++--- man/detect_outlr.Rd | 10 ++--- man/detect_outlr_rm.Rd | 7 +-- man/detect_outlr_stl.Rd | 7 +-- man/epix_as_of.Rd | 2 +- man/epix_merge.Rd | 12 +++--- man/epix_slide.Rd | 10 ++--- man/is_epi_archive.Rd | 4 +- 11 files changed, 119 insertions(+), 117 deletions(-) diff --git a/R/archive.R b/R/archive.R index 9fb7c27b..2b600f7b 100644 --- a/R/archive.R +++ b/R/archive.R @@ -448,22 +448,22 @@ epi_archive = #' ``` #' #' @export -#' @examples +#' @examples #' df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), #' county = c(1, 3, 2, 5), -#' time_value = c("2020-06-01", -#' "2020-06-02", -#' "2020-06-01", +#' time_value = c("2020-06-01", +#' "2020-06-02", +#' "2020-06-01", #' "2020-06-02"), -#' version = c("2020-06-02", -#' "2020-06-03", +#' version = c("2020-06-02", +#' "2020-06-03", #' "2020-06-02", #' "2020-06-03"), #' cases = c(1, 2, 3, 4), #' cases_rate = c(0.01, 0.02, 0.01, 0.05)) #' -#' x <- df %>% as_epi_archive(geo_type = "state", -#' time_type = "day", +#' x <- df %>% as_epi_archive(geo_type = "state", +#' time_type = "day", #' other_keys = "county") as_epi_archive = function(x, geo_type, time_type, other_keys, additional_metadata = list()) { @@ -477,8 +477,8 @@ as_epi_archive = function(x, geo_type, time_type, other_keys, #' #' @export #' @examples -#' is_epi_archive(jhu_csse_daily) # FALSE -#' is_epi_archive(archive_cases_dv) # TRUE +#' is_epi_archive(jhu_csse_daily) # FALSE (this is an epi_df, not epi_archive) +#' is_epi_archive(archive_cases_dv) # TRUE is_epi_archive = function(x) { inherits(x, "epi_archive") } diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index cedb0374..d1b7ef56 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -4,7 +4,7 @@ #' given version. See the [archive #' vignette](https://cmu-delphi.github.io/epiprocess/articles/archive.html) for #' examples. -#' +#' #' @param x An `epi_archive` object #' @param max_version Time value specifying the max version to permit in the #' snapshot. That is, the snapshot will comprise the unique rows of the @@ -17,7 +17,7 @@ #' @return An `epi_df` object. #' #' @details This is simply a wrapper around the `as_of()` method of the -#' `epi_archive` class, so if `x` is an `epi_archive` object, then: +#' `epi_archive` class, so if `x` is an `epi_archive` object, then: #' ``` #' epix_as_of(x, max_version = v) #' ``` @@ -25,10 +25,10 @@ #' ``` #' x$as_of(max_version = v) #' ``` -#' -#' @export -#' @examples -#' epix_as_of(x = archive_cases_dv, +#' +#' @export +#' @examples +#' epix_as_of(x = archive_cases_dv, #' max_version = max(archive_cases_dv$DT$version)) epix_as_of = function(x, max_version, min_time_value = -Inf) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") @@ -58,7 +58,7 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' step? Default is `NA`, which means that they are treated as `NA` values; if # `NaN`, then they are treated as distinct. #' @return Nothing; the data table in `x` is overwritten with the merged one. -#' +#' #' @details This is simply a wrapper around the `merge()` method of the #' `epi_archive` class, so if `x` and `y` are an `epi_archive` objects, then: #' ``` @@ -68,19 +68,19 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' ``` #' x$merge(y) #' ``` -#' +#' #' @export -#' @examples +#' @examples #' # create two example epi_archive datasets -#' x <- archive_cases_dv$DT %>% -#' dplyr::select(geo_value,time_value,version,case_rate) %>% +#' x <- archive_cases_dv$DT %>% +#' dplyr::select(geo_value,time_value,version,case_rate) %>% #' as_epi_archive() -#' y <- archive_cases_dv$DT %>% -#' dplyr::select(geo_value,time_value,version,percent_cli) %>% +#' y <- archive_cases_dv$DT %>% +#' dplyr::select(geo_value,time_value,version,percent_cli) %>% #' as_epi_archive() -#' +#' #' # a full join stored in x -#' epix_merge(x, y, all = TRUE) +#' epix_merge(x, y, all = TRUE) epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") return(x$merge(y, ..., locf = locf, nan = nan)) @@ -95,7 +95,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' [archive #' vignette](https://cmu-delphi.github.io/epiprocess/articles/archive.html) for #' examples. -#' +#' #' @param x An `epi_archive` object. #' @param f Function or formula to slide over variables in `x`. To "slide" means #' to apply a function or formula over a running window of `n` time steps @@ -130,7 +130,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' contain the derivative values. Default is "slide_value"; note that setting #' `new_col_name` equal to an existing column name will overwrite this column. #' @param as_list_col Should the new column be stored as a list column? Default -#' is `FALSE`, in which case a list object returned by `f` would be unnested +#' is `FALSE`, in which case a list object returned by `f` would be unnested #' (using `tidyr::unnest()`), and the names of the resulting columns are given #' by prepending `new_col_name` to the names of the list elements. #' @param names_sep String specifying the separator to use in `tidyr::unnest()` @@ -146,13 +146,13 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' values. #' #' @details Two key distinctions between inputs to the current function and -#' `epi_slide()`: +#' `epi_slide()`: #' 1. `epix_slide()` uses windows that are **always right-aligned** (in #' `epi_slide()`, custom alignments could be specified using the `align` or #' `before` arguments). #' 2. `epix_slide()` uses a `group_by` to specify the grouping upfront (in #' `epi_slide()`, this would be accomplished by a preceding function call to -#' `dplyr::group_by()`). +#' `dplyr::group_by()`). #' Apart from this, the interfaces between `epix_slide()` and `epi_slide()` are #' the same. #' @@ -160,7 +160,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' returns the grouping variables, `time_value`, and the new columns from #' sliding, whereas `epi_slide()` returns all original variables plus the new #' columns from sliding. -#' +#' #' Furthermore, the current function can be considerably slower than #' `epi_slide()`, for two reasons: (1) it must repeatedly fetch #' properly-versioned snapshots from the data archive (via its `as_of()` @@ -170,7 +170,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' version-aware sliding is necessary (as it its purpose). #' #' Finally, this is simply a wrapper around the `slide()` method of the -#' `epi_archive` class, so if `x` is an `epi_archive` object, then: +#' `epi_archive` class, so if `x` is an `epi_archive` object, then: #' ``` #' epix_slide(x, new_var = comp(old_var), n = 120) #' ``` @@ -178,19 +178,19 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' ``` #' x$slide(x, new_var = comp(old_var), n = 120) #' ``` -#' +#' #' @importFrom rlang enquo #' @export -#' @examples +#' @examples #' # every date is a reference time point for the 3 day average sliding window -#' fc_time_values <- seq(as.Date("2020-06-01"), +#' time_values <- seq(as.Date("2020-06-01"), #' as.Date("2020-06-15"), #' by = "1 day") -#' epix_slide(x = archive_cases_dv, -#' f = ~ mean(.x$case_rate), -#' n = 3, +#' epix_slide(x = archive_cases_dv, +#' f = ~ mean(.x$case_rate), +#' n = 3, #' group_by = geo_value, -#' ref_time_values = fc_time_values, +#' ref_time_values = time_values, #' new_col_name = 'case_rate_3d_av') epix_slide = function(x, f, ..., n = 7, group_by, ref_time_values, time_step, new_col_name = "slide_value", diff --git a/R/outliers.R b/R/outliers.R index c6df6f22..388260f5 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -1,11 +1,11 @@ -#' Detect outliers +#' Detect outliers #' #' Applies one or more outlier detection methods to a given signal variable, and #' optionally aggregates the outputs to create a consensus result. See the #' [outliers #' vignette](https://cmu-delphi.github.io/epiprocess/articles/outliers.html) for -#' examples. -#' +#' examples. +#' #' @param x Design points corresponding to the signal values `y`. Default is #' `seq_along(y)` (that is, equally-spaced points from 1 to the length of #' `y`). @@ -13,11 +13,11 @@ #' @param methods A tibble specifying the method(s) to use for outlier #' detection, with one row per method, and the following columns: #' * `method`: Either "rm" or "stl", or a custom function for outlier -#' detection; see details for further explanation. +#' detection; see details for further explanation. #' * `args`: Named list of arguments that will be passed to the detection -#' method. +#' method. #' * `abbr`: Abbreviation to use in naming output columns with results from -#' this method. +#' this method. #' @param combiner String, one of "median", "mean", or "none", specifying how to #' combine results from different outlier detection methods for the thresholds #' determining whether a particular observation is classified as an outlier, @@ -27,7 +27,7 @@ #' purposes of determining whether a given observation is an outlier. #' @return An tibble with number of rows equal to `length(y)` and columns giving #' the outlier detection thresholds and replacement values from each detection -#' method. +#' method. #' #' @details Each outlier detection method, one per row of the passed `methods` #' tibble, is a function that must take as its first two arguments `x` and @@ -42,7 +42,7 @@ #' `detect_outlr_rm()`, which detects outliers via a rolling median; or by #' "stl", shorthand for `detect_outlr_stl()`, which detects outliers via an #' STL decomposition. -#' +#' #' @export #' @importFrom dplyr select #' @examples @@ -60,11 +60,11 @@ #' args = list(list(detect_negatives = TRUE, #' detection_multiplier = 2.5, #' seasonal_period = NULL)), -#' abbr = "stl_nonseasonal")) -#' -#' x <- jhu_csse_daily %>% -#' dplyr::select(geo_value,time_value,cases) %>% -#' as_epi_df()%>% +#' abbr = "stl_nonseasonal")) +#' +#' x <- jhu_csse_daily %>% +#' dplyr::select(geo_value,time_value,cases) %>% +#' as_epi_df() %>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr( #' x = time_value, y = cases, @@ -78,7 +78,7 @@ detect_outlr = function(x = seq_along(y), y, combiner = c("median", "mean", "none")) { # Validate combiner combiner = match.arg(combiner) - + # Validate that x contains all distinct values if (any(duplicated(x))) { Abort("`x` cannot contain duplicate values. (If being run on a column in an `epi_df`, did you group by relevant key variables?)") @@ -87,7 +87,7 @@ detect_outlr = function(x = seq_along(y), y, # Run all outlier detection methods results = purrr::pmap_dfc(methods, function(method, args, abbr) { if (is.character(method)) method = paste0("detect_outlr_", method) - + # Call the method results = do.call(method, args = c(list("x" = x, "y" = y), args)) @@ -98,15 +98,15 @@ detect_outlr = function(x = seq_along(y), y, } # Update column names with model abbreviation - colnames(results) = paste(abbr, colnames(results), sep = "_") + colnames(results) = paste(abbr, colnames(results), sep = "_") return(results) }) - + # Combine information about detected outliers if (combiner != "none") { if (combiner == "mean") combine_fun = mean else if (combiner == "median") combine_fun = median - + for (target in c("lower", "upper", "replacement")) { results[[paste0("combined_", target)]] = apply( results %>% @@ -127,15 +127,15 @@ detect_outlr = function(x = seq_along(y), y, #' `seq_along(y)` (that is, equally-spaced points from 1 to the length of #' `y`). #' @param y Signal values. -#' @param n Number of time steps to use in the rolling window. Default is 21. +#' @param n Number of time steps to use in the rolling window. Default is 21. #' @param log_transform Should a log transform be applied before running outlier #' detection? Default is `FALSE`. If `TRUE`, and zeros are present, then the #' log transform will be padded by 1. #' @param detect_negatives Should negative values automatically count as #' outliers? Default is `FALSE`. #' @param detection_multiplier Value determining how far the outlier detection -#' thresholds are from the rolling median, which are calculated as (rolling -#' median) +/- (detection multiplier) * (rolling IQR). Default is 2. +#' thresholds are from the rolling median, which are calculated as (rolling +#' median) +/- (detection multiplier) * (rolling IQR). Default is 2. #' @param min_radius Minimum distance between rolling median and threshold, on #' transformed scale. Default is 0. #' @param replacement_multiplier Value determining how far the replacement @@ -147,11 +147,11 @@ detect_outlr = function(x = seq_along(y), y, #' `lower`, `upper`, and `replacement`. #' #' @export -#' @examples -# # Detect outliers based on a rolling median -#' jhu_csse_daily %>% -#' dplyr::select(geo_value,time_value,cases) %>% -#' as_epi_df()%>% +#' @examples +#' # Detect outliers based on a rolling median +#' jhu_csse_daily %>% +#' dplyr::select(geo_value,time_value,cases) %>% +#' as_epi_df() %>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr_rm( #' x = time_value, y = cases)) %>% @@ -176,7 +176,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, # Make an epi_df for easy sliding z = as_epi_df(tibble::tibble(geo_value = 0, time_value = x, y = y)) - + # Calculate lower and upper thresholds and replacement value z = z %>% epi_slide(fitted = median(y), n = n, align = "center") %>% @@ -197,9 +197,9 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, return(z) } -#' Detect outliers based on an STL decomposition +#' Detect outliers based on an STL decomposition #' -#' Detects outliers based on a seasonal-trend decomposition using LOESS (STL). +#' Detects outliers based on a seasonal-trend decomposition using LOESS (STL). #' #' @param x Design points corresponding to the signal values `y`. Default is #' `seq_along(y)` (that is, equally-spaced points from 1 to the length of @@ -208,7 +208,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @param n_trend Number of time steps to use in the rolling window for trend. #' Default is 21. #' @param n_seasonal Number of time steps to use in the rolling window for -#' seasonality. Default is 21. +#' seasonality. Default is 21. #' @param n_threshold Number of time steps to use in rolling window for the IQR #' outlier thresholds. #' @param seasonal_period Integer specifying period of seasonality. For example, @@ -220,8 +220,8 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @param detect_negatives Should negative values automatically count as #' outliers? Default is `FALSE`. #' @param detection_multiplier Value determining how far the outlier detection -#' thresholds are from the rolling median, which are calculated as (rolling -#' median) +/- (detection multiplier) * (rolling IQR). Default is 2. +#' thresholds are from the rolling median, which are calculated as (rolling +#' median) +/- (detection multiplier) * (rolling IQR). Default is 2. #' @param min_radius Minimum distance between rolling median and threshold, on #' transformed scale. Default is 0. #' @param replacement_multiplier Value determining how far the replacement @@ -230,7 +230,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' nearest (rolling median) +/- (replacement multiplier) * (rolling IQR). #' Default is 0. #' @return A tibble with number of rows equal to `length(y)`, and columns -#' `lower`, `upper`, and `replacement`. +#' `lower`, `upper`, and `replacement`. #' #' @details The STL decomposition is computed using the `feasts` package. Once #' computed, the outlier detection method is analogous to the rolling median @@ -244,11 +244,11 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @importFrom stats median #' @importFrom tidyselect starts_with #' @export -#' @examples -# # Detects outliers based on a seasonal-trend decomposition using LOESS -#' jhu_csse_daily %>% -#' dplyr::select(geo_value,time_value,cases) %>% -#' as_epi_df()%>% +#' @examples +#' # Detects outliers based on a seasonal-trend decomposition using LOESS +#' jhu_csse_daily %>% +#' dplyr::select(geo_value,time_value,cases) %>% +#' as_epi_df() %>% #' group_by(geo_value) %>% #' mutate(outlier_info = detect_outlr_stl( #' x = time_value, y = cases, @@ -271,10 +271,10 @@ detect_outlr_stl = function(x = seq_along(y), y, offset = as.integer(any(y == 0)) y = log(y + offset) } - + # Make a tsibble for fabletools, setup and run STL z_tsibble = tsibble::tsibble(x = x, y = y, index = x) - + stl_formula = y ~ trend(window = n_trend) + season(period = seasonal_period, window = n_seasonal) @@ -285,8 +285,8 @@ detect_outlr_stl = function(x = seq_along(y), y, dplyr::select(trend:remainder) %>% dplyr::rename_with(~ "seasonal", tidyselect::starts_with("season")) %>% dplyr::rename(resid = remainder) - - # Allocate the seasonal term from STL to either fitted or resid + + # Allocate the seasonal term from STL to either fitted or resid if (!is.null(seasonal_period)) { stl_components = stl_components %>% dplyr::mutate( @@ -301,17 +301,17 @@ detect_outlr_stl = function(x = seq_along(y), y, # Detect negatives if requested if (detect_negatives && !log_transform) min_lower = 0 else min_lower = -Inf - + # Make an epi_df for easy sliding z = as_epi_df(tibble::tibble(geo_value = 0, time_value = x, y = y)) - - # Calculate lower and upper thresholds and replacement value + + # Calculate lower and upper thresholds and replacement value z = z %>% dplyr::mutate( fitted = stl_components$fitted, resid = stl_components$resid) %>% roll_iqr(n = n_threshold, - detection_multiplier = detection_multiplier, + detection_multiplier = detection_multiplier, min_radius = min_radius, replacement_multiplier = replacement_multiplier, min_lower = min_lower) @@ -331,7 +331,7 @@ roll_iqr = function(z, n, detection_multiplier, min_radius, replacement_multiplier, min_lower) { if (typeof(z$y) == "integer") as_type = as.integer else as_type = as.numeric - + epi_slide(z, roll_iqr = stats::IQR(resid), n = n, align = "center") %>% dplyr::mutate( lower = pmax(min_lower, diff --git a/man/as_epi_archive.Rd b/man/as_epi_archive.Rd index 2289d86e..c7098f77 100644 --- a/man/as_epi_archive.Rd +++ b/man/as_epi_archive.Rd @@ -55,18 +55,18 @@ would be equivalent to: \examples{ df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), county = c(1, 3, 2, 5), - time_value = c("2020-06-01", - "2020-06-02", - "2020-06-01", + time_value = c("2020-06-01", + "2020-06-02", + "2020-06-01", "2020-06-02"), - version = c("2020-06-02", - "2020-06-03", + version = c("2020-06-02", + "2020-06-03", "2020-06-02", "2020-06-03"), cases = c(1, 2, 3, 4), cases_rate = c(0.01, 0.02, 0.01, 0.05)) -x <- df \%>\% as_epi_archive(geo_type = "state", - time_type = "day", +x <- df \%>\% as_epi_archive(geo_type = "state", + time_type = "day", other_keys = "county") } diff --git a/man/detect_outlr.Rd b/man/detect_outlr.Rd index 297fb42b..df975947 100644 --- a/man/detect_outlr.Rd +++ b/man/detect_outlr.Rd @@ -78,11 +78,11 @@ STL decomposition. args = list(list(detect_negatives = TRUE, detection_multiplier = 2.5, seasonal_period = NULL)), - abbr = "stl_nonseasonal")) - - x <- jhu_csse_daily \%>\% - dplyr::select(geo_value,time_value,cases) \%>\% - as_epi_df()\%>\% + abbr = "stl_nonseasonal")) + + x <- jhu_csse_daily \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% + as_epi_df() \%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr( x = time_value, y = cases, diff --git a/man/detect_outlr_rm.Rd b/man/detect_outlr_rm.Rd index 39cbacf3..6b373c29 100644 --- a/man/detect_outlr_rm.Rd +++ b/man/detect_outlr_rm.Rd @@ -53,9 +53,10 @@ Detects outliers based on a distance from the rolling median specified in terms of multiples of the rolling interquartile range (IQR). } \examples{ -jhu_csse_daily \%>\% - dplyr::select(geo_value,time_value,cases) \%>\% - as_epi_df()\%>\% +# Detect outliers based on a rolling median +jhu_csse_daily \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% + as_epi_df() \%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr_rm( x = time_value, y = cases)) \%>\% diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index ea1e8cb1..7ee9808a 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -76,9 +76,10 @@ The last set of arguments, \code{log_transform} through \code{replacement_multip are exactly as in \code{detect_outlr_rm()}. } \examples{ -jhu_csse_daily \%>\% - dplyr::select(geo_value,time_value,cases) \%>\% - as_epi_df()\%>\% +# Detects outliers based on a seasonal-trend decomposition using LOESS +jhu_csse_daily \%>\% + dplyr::select(geo_value,time_value,cases) \%>\% + as_epi_df() \%>\% group_by(geo_value) \%>\% mutate(outlier_info = detect_outlr_stl( x = time_value, y = cases, diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 969ae868..54683259 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -40,6 +40,6 @@ is equivalent to: }\if{html}{\out{}} } \examples{ -epix_as_of(x = archive_cases_dv, +epix_as_of(x = archive_cases_dv, max_version = max(archive_cases_dv$DT$version)) } diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index b688bd06..a39cae78 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -47,13 +47,13 @@ is equivalent to: } \examples{ # create two example epi_archive datasets -x <- archive_cases_dv$DT \%>\% - dplyr::select(geo_value,time_value,version,case_rate) \%>\% +x <- archive_cases_dv$DT \%>\% + dplyr::select(geo_value,time_value,version,case_rate) \%>\% as_epi_archive() -y <- archive_cases_dv$DT \%>\% - dplyr::select(geo_value,time_value,version,percent_cli) \%>\% +y <- archive_cases_dv$DT \%>\% + dplyr::select(geo_value,time_value,version,percent_cli) \%>\% as_epi_archive() - + # a full join stored in x -epix_merge(x, y, all = TRUE) +epix_merge(x, y, all = TRUE) } diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index c4763a38..84c09f10 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -127,13 +127,13 @@ is equivalent to: } \examples{ # every date is a reference time point for the 3 day average sliding window -fc_time_values <- seq(as.Date("2020-06-01"), +time_values <- seq(as.Date("2020-06-01"), as.Date("2020-06-15"), by = "1 day") -epix_slide(x = archive_cases_dv, - f = ~ mean(.x$case_rate), - n = 3, +epix_slide(x = archive_cases_dv, + f = ~ mean(.x$case_rate), + n = 3, group_by = geo_value, - ref_time_values = fc_time_values, + ref_time_values = time_values, new_col_name = 'case_rate_3d_av') } diff --git a/man/is_epi_archive.Rd b/man/is_epi_archive.Rd index 69a45d5e..85f546a0 100644 --- a/man/is_epi_archive.Rd +++ b/man/is_epi_archive.Rd @@ -16,6 +16,6 @@ is_epi_archive(x) Test for \code{epi_archive} format } \examples{ -is_epi_archive(jhu_csse_daily) # FALSE -is_epi_archive(archive_cases_dv) # TRUE +is_epi_archive(jhu_csse_daily) # FALSE (this is an epi_df, not epi_archive) +is_epi_archive(archive_cases_dv) # TRUE } From a40e0b0277642be62ff6d760cf1626f9636e27db Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Fri, 20 May 2022 09:51:07 -0700 Subject: [PATCH 32/41] update data to include tx and ny for correlation example --- DESCRIPTION | 2 +- R/correlation.R | 4 ++-- R/data.R | 6 +++--- data-raw/archive_cases_dv.R | 4 ++-- data-raw/jhu_csse_daily.R | 8 ++++---- data/archive_cases_dv.rda | Bin 40398 -> 42489 bytes data/jhu_csse_daily.rda | Bin 1361 -> 2147 bytes man/archive_cases_dv.Rd | 2 +- man/as_epi_archive.Rd | 12 ++++-------- man/epi_archive.Rd | 36 ++++++++++++++++++------------------ man/epi_cor.Rd | 4 ++-- man/epi_slide.Rd | 12 ++++-------- man/epix_as_of.Rd | 12 ++++-------- man/epix_merge.Rd | 12 ++++-------- man/epix_slide.Rd | 12 ++++-------- man/jhu_csse_daily.Rd | 4 ++-- 16 files changed, 55 insertions(+), 75 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index ceb5b29c..dd573870 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -15,7 +15,7 @@ Authors@R: c( Description: This package introduces a common data structure for epidemiological data sets measured over space and time, and offers associated utilities to perform basic signal processing tasks. -License: MIT + file LICENSE +License: CC BY 4.0 Imports: data.table, dplyr, diff --git a/R/correlation.R b/R/correlation.R index 67781716..e4f609f8 100644 --- a/R/correlation.R +++ b/R/correlation.R @@ -53,7 +53,7 @@ #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = time_value, -#' dt1 = -10) +#' dt1 = -2) #' #' # correlation grouped by location #' epi_cor(x = jhu_csse_daily, @@ -66,7 +66,7 @@ #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = geo_value, -#' dt1 = -10) +#' dt1 = -2) epi_cor = function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value, cor_by = geo_value, use = "na.or.complete", method = c("pearson", "kendall", "spearman")) { diff --git a/R/data.R b/R/data.R index 06ae93b8..623ce86d 100644 --- a/R/data.R +++ b/R/data.R @@ -1,11 +1,11 @@ -#' JHU daily cases and deaths from California and Florida +#' JHU daily cases and deaths from California, Florida, Texas, and New York #' #' This data source of confirmed COVID-19 cases and deaths #' is based on reports made available by the Center for #' Systems Science and Engineering at Johns Hopkins University. #' This example data ranges from June 1 to June 15, 2020. #' -#' @format A tibble with 30 rows and 6 variables: +#' @format A tibble with 60 rows and 6 variables: #' \describe{ #' \item{geo_value}{the geographic value associated with each row of measurements.} #' \item{time_value}{the time value associated with each row of measurements.} @@ -19,7 +19,7 @@ "jhu_csse_daily" -#' Daily doctor visits and cases from California and Florida in archive format +#' Daily doctor visits and cases from California, Florida, Texas, and New York in archive format #' #' This data source is based on information about outpatient visits, #' provided to us by health system partners, and also contains confirmed diff --git a/data-raw/archive_cases_dv.R b/data-raw/archive_cases_dv.R index ff005f82..4d49b638 100644 --- a/data-raw/archive_cases_dv.R +++ b/data-raw/archive_cases_dv.R @@ -9,7 +9,7 @@ archive_cases_dv <- covidcast( time_type = "day", geo_type = "state", time_value = epirange(20200601, 20200615), - geo_values = "ca,fl", + geo_values = "ca,fl,ny,tx", issues = epirange(20200601, 20200615) ) %>% fetch_tbl() %>% @@ -22,7 +22,7 @@ case_rate <- covidcast( time_type = "day", geo_type = "state", time_value = epirange(20200601, 20200615), - geo_values = "ca,fl", + geo_values = "ca,fl,ny,tx", issues = epirange(20200601, 20200615) ) %>% fetch_tbl() %>% diff --git a/data-raw/jhu_csse_daily.R b/data-raw/jhu_csse_daily.R index 11b48f2c..c82031d6 100644 --- a/data-raw/jhu_csse_daily.R +++ b/data-raw/jhu_csse_daily.R @@ -8,7 +8,7 @@ confirmed_7dav_incidence_prop <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200601, 20200615), - geo_values = "ca,fl" + geo_values = "ca,fl,ny,tx" ) %>% fetch_tbl() %>% select(geo_value, time_value, case_rate_7d_av = value) %>% @@ -20,7 +20,7 @@ deaths_7dav_incidence_prop <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200601, 20200615), - geo_values = "ca,fl" + geo_values = "ca,fl,ny,tx" ) %>% fetch_tbl() %>% select(geo_value, time_value, death_rate_7d_av = value) %>% @@ -32,7 +32,7 @@ confirmed_incidence_num <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200601, 20200615), - geo_values = "ca,fl" + geo_values = "ca,fl,ny,tx" ) %>% fetch_tbl() %>% select(geo_value, time_value, cases = value) %>% @@ -44,7 +44,7 @@ confirmed_7dav_incidence_num <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200601, 20200615), - geo_values = "ca,fl" + geo_values = "ca,fl,ny,tx" ) %>% fetch_tbl() %>% select(geo_value, time_value, cases_7d_av = value) %>% diff --git a/data/archive_cases_dv.rda b/data/archive_cases_dv.rda index ce3e0ce34679a412812cfca04092a084948c49dd..f363671432cb0a9f34dc521827dd32fc6fb6d114 100644 GIT binary patch literal 42489 zcmagFV{k6P7O)#9JI;=6+uE^qY}>YN+qP{dJGO1(jcwkXbL#u5?)`J0TGc&0Q!_o& zy=JY|Jw1XNW}J)y>ST)QS@u?lz%EJO|G(_k;`7+?03nnRfX+e?6apaQfPj^90CCVK z9{b7!#gzO&|KktH0N5(qdXUoU_$Y%MRpK^~)0K@~v`t-s2uVd;Sg>HpvoivkfEAVp z5ICp+Kd=>09&jEI5VRfSC=k#gSe{rO5G23N*yI&F4rm?_l;6))K@d@dm60e=tbpWD zuS2ulAO2Spkj1a{{k>}rZ8Nw!=w}rM&K2$6#Y|Y$syrST)1hCkTA%{wCMOV;*A`DR z=*{eft5(Q*c_$7!y>o|_ofN?QKtQgId50xwE$c+M>tfPX`Bl%HRGzFXOn7Soomt?j z(SC^wWEVi}dfS)l!`N^PTjL7=?wm)zN9r9>b_}e^3B6}iWlv|9?Pf?TIFx1Q-JDnJ 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zklJ>*2z5EFt=U_C$LU7SnBw;gEO*iZk1z|Eq{SW+pM=vjrechowrqa-g?!Wdpa5e4WxpwWJW|{g9RrDvJNdlMZjWGCgaRF8tNM?x$_s2 zyFjv&r@Q!O?v-=QfqayHi_p@1{w_j60e&el(;z0WkW&E0*IYRWLKxI=<{AR>Xg(!` zic|uh65<|SL z#LYRHbd>nQ83KP(M&!$GCtTI_EN(RV%SONawxfx(6Wff#`Y`ZgXdv28VYuy}!K zina*o6Ji7&g{n+021>3BB(vdw6HHmBoE-cJA&}VO1Qt?5{^SjTO@G#aCUU^X%sFBW zf$VU!E*j8!?gG%*YsL|O?b0ftdDF0cBsFZEpQ%{T!bW1LG3YjRs6POLzm`{*W5^AR zA|z|wx1Q>@l;eWHlO}cyl}qtqxaRikYKMg zl*d1|FGQU}Cm;cF0we}}\preformatted{x <- as_epi_archive(df, geo_type = "state", time_type = "day") -}\if{html}{\out{}} - -would be equivalent to: +class, so for example:\preformatted{x <- as_epi_archive(df, geo_type = "state", time_type = "day") +} -\if{html}{\out{
}}\preformatted{x <- epi_archive$new(df, geo_type = "state", time_type = "day") -}\if{html}{\out{
}} +would be equivalent to:\preformatted{x <- epi_archive$new(df, geo_type = "state", time_type = "day") +} } \examples{ df <- data.frame (geo_value = c(replicate(2, "ca"), replicate(2, "fl")), diff --git a/man/epi_archive.Rd b/man/epi_archive.Rd index 5214b01d..fff4e714 100644 --- a/man/epi_archive.Rd +++ b/man/epi_archive.Rd @@ -84,17 +84,17 @@ are documented in the wrapper function \code{epix_slide()}. \section{Methods}{ \subsection{Public methods}{ \itemize{ -\item \href{#method-epi_archive-new}{\code{epi_archive$new()}} -\item \href{#method-epi_archive-print}{\code{epi_archive$print()}} -\item \href{#method-epi_archive-as_of}{\code{epi_archive$as_of()}} -\item \href{#method-epi_archive-merge}{\code{epi_archive$merge()}} -\item \href{#method-epi_archive-slide}{\code{epi_archive$slide()}} -\item \href{#method-epi_archive-clone}{\code{epi_archive$clone()}} +\item \href{#method-new}{\code{epi_archive$new()}} +\item \href{#method-print}{\code{epi_archive$print()}} +\item \href{#method-as_of}{\code{epi_archive$as_of()}} +\item \href{#method-merge}{\code{epi_archive$merge()}} +\item \href{#method-slide}{\code{epi_archive$slide()}} +\item \href{#method-clone}{\code{epi_archive$clone()}} } } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-new}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-new}{}}} \subsection{Method \code{new()}}{ Creates a new \code{epi_archive} object. \subsection{Usage}{ @@ -130,8 +130,8 @@ An \code{epi_archive} object. } } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-print}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-print}{}}} \subsection{Method \code{print()}}{ \subsection{Usage}{ \if{html}{\out{
}}\preformatted{epi_archive$print()}\if{html}{\out{
}} @@ -139,8 +139,8 @@ An \code{epi_archive} object. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-as_of}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-as_of}{}}} \subsection{Method \code{as_of()}}{ Generates a snapshot in \code{epi_df} format as of a given version. See the documentation for the wrapper function \code{epix_as_of()} for details. @@ -150,8 +150,8 @@ See the documentation for the wrapper function \code{epix_as_of()} for details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-merge}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-merge}{}}} \subsection{Method \code{merge()}}{ Merges another \code{data.table} with the current one, and allows for a post-filling of \code{NA} values by last observation carried forward (LOCF). @@ -162,8 +162,8 @@ See the documentation for the wrapper function \code{epix_merge()} for details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-slide}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-slide}{}}} \subsection{Method \code{slide()}}{ Slides a given function over variables in an \code{epi_archive} object. See the documentation for the wrapper function \code{epix_as_of()} for @@ -185,8 +185,8 @@ details. } \if{html}{\out{
}} -\if{html}{\out{}} -\if{latex}{\out{\hypertarget{method-epi_archive-clone}{}}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-clone}{}}} \subsection{Method \code{clone()}}{ The objects of this class are cloneable with this method. \subsection{Usage}{ diff --git a/man/epi_cor.Rd b/man/epi_cor.Rd index 70b01737..03d725d3 100644 --- a/man/epi_cor.Rd +++ b/man/epi_cor.Rd @@ -70,7 +70,7 @@ epi_cor(x = jhu_csse_daily, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = time_value, - dt1 = -10) + dt1 = -2) # correlation grouped by location epi_cor(x = jhu_csse_daily, @@ -83,5 +83,5 @@ epi_cor(x = jhu_csse_daily, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = geo_value, - dt1 = -10) + dt1 = -2) } diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index cc3ae6be..1e42dbf3 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -104,16 +104,12 @@ incomplete windows) is therefore left up to the user, either through the specified function or formula \code{f}, or through post-processing. If \code{f} is missing, then an expression for tidy evaluation can be specified, -for example, as in: - -\if{html}{\out{
}}\preformatted{epi_slide(x, cases_7dav = mean(cases), n = 7) -}\if{html}{\out{
}} - -which would be equivalent to: +for example, as in:\preformatted{epi_slide(x, cases_7dav = mean(cases), n = 7) +} -\if{html}{\out{
}}\preformatted{epi_slide(x, function(x, ...) mean(x$cases), n = 7, +which would be equivalent to:\preformatted{epi_slide(x, function(x, ...) mean(x$cases), n = 7, new_col_name = "cases_7dav") -}\if{html}{\out{
}} +} Thus, to be clear, when the computation is specified via an expression for tidy evaluation (first example, above), then the name for the new column is diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index 54683259..e5801566 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -29,15 +29,11 @@ examples. } \details{ This is simply a wrapper around the \code{as_of()} method of the -\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then: - -\if{html}{\out{
}}\preformatted{epix_as_of(x, max_version = v) -}\if{html}{\out{
}} - -is equivalent to: +\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then:\preformatted{epix_as_of(x, max_version = v) +} -\if{html}{\out{
}}\preformatted{x$as_of(max_version = v) -}\if{html}{\out{
}} +is equivalent to:\preformatted{x$as_of(max_version = v) +} } \examples{ epix_as_of(x = archive_cases_dv, diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index a39cae78..731d4625 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -35,15 +35,11 @@ examples. } \details{ This is simply a wrapper around the \code{merge()} method of the -\code{epi_archive} class, so if \code{x} and \code{y} are an \code{epi_archive} objects, then: - -\if{html}{\out{
}}\preformatted{epix_merge(x, y) -}\if{html}{\out{
}} - -is equivalent to: +\code{epi_archive} class, so if \code{x} and \code{y} are an \code{epi_archive} objects, then:\preformatted{epix_merge(x, y) +} -\if{html}{\out{
}}\preformatted{x$merge(y) -}\if{html}{\out{
}} +is equivalent to:\preformatted{x$merge(y) +} } \examples{ # create two example epi_archive datasets diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 84c09f10..98c0d146 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -115,15 +115,11 @@ should never be used in place of \code{epi_slide()}, and only used when version-aware sliding is necessary (as it its purpose). Finally, this is simply a wrapper around the \code{slide()} method of the -\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then: - -\if{html}{\out{
}}\preformatted{epix_slide(x, new_var = comp(old_var), n = 120) -}\if{html}{\out{
}} - -is equivalent to: +\code{epi_archive} class, so if \code{x} is an \code{epi_archive} object, then:\preformatted{epix_slide(x, new_var = comp(old_var), n = 120) +} -\if{html}{\out{
}}\preformatted{x$slide(x, new_var = comp(old_var), n = 120) -}\if{html}{\out{
}} +is equivalent to:\preformatted{x$slide(x, new_var = comp(old_var), n = 120) +} } \examples{ # every date is a reference time point for the 3 day average sliding window diff --git a/man/jhu_csse_daily.Rd b/man/jhu_csse_daily.Rd index 4fd22e6e..781ac280 100644 --- a/man/jhu_csse_daily.Rd +++ b/man/jhu_csse_daily.Rd @@ -3,9 +3,9 @@ \docType{data} \name{jhu_csse_daily} \alias{jhu_csse_daily} -\title{JHU daily cases and deaths from California and Florida} +\title{JHU daily cases and deaths from California, Florida, Texas, and New York} \format{ -A tibble with 30 rows and 6 variables: +A tibble with 60 rows and 6 variables: \describe{ \item{geo_value}{the geographic value associated with each row of measurements.} \item{time_value}{the time value associated with each row of measurements.} From 9a99218eb2a4ea9156d97954fc5807258725df67 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Fri, 20 May 2022 10:49:05 -0700 Subject: [PATCH 33/41] add licensing to data.R --- R/data.R | 25 ++++++++++++++++++------- man/archive_cases_dv.Rd | 12 +++++++----- man/jhu_csse_daily.Rd | 12 ++++++++++-- 3 files changed, 35 insertions(+), 14 deletions(-) diff --git a/R/data.R b/R/data.R index 623ce86d..2f52ed2b 100644 --- a/R/data.R +++ b/R/data.R @@ -14,8 +14,15 @@ #' \item{cases}{Number of new confirmed COVID-19 cases, daily} #' \item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} #' } -#' @source COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. -#' \url{https://github.com/CSSEGISandData/COVID-19} +#' @source This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' Copyright Johns Hopkins University 2020. +#' +#' * \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{COVIDcast Epidata JHU Cases and Death} +#' +#' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. "jhu_csse_daily" @@ -35,11 +42,15 @@ #' \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} #' \item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} #' } -#' @source These data sources are provided under the terms of the -#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution license:} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{Doctor Visits} +#' @source +#' This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' Copyright Johns Hopkins University 2020. +#' +#' * \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{COVIDcast Epidata Doctor Visits} #' -#' COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. -#' \url{https://github.com/CSSEGISandData/COVID-19} +#' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. "archive_cases_dv" diff --git a/man/archive_cases_dv.Rd b/man/archive_cases_dv.Rd index 6f4de75e..59911df3 100644 --- a/man/archive_cases_dv.Rd +++ b/man/archive_cases_dv.Rd @@ -15,14 +15,16 @@ An \code{epi_archive} data format. The data table DT has 160 rows and 5 columns: } } \source{ -These data sources are provided under the terms of the -\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution license:} +This data set is licensed under the terms of the +\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +Copyright Johns Hopkins University 2020. \itemize{ -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{Doctor Visits} +\item \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{COVIDcast Epidata Doctor Visits} } -COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. -\url{https://github.com/CSSEGISandData/COVID-19} +The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ archive_cases_dv diff --git a/man/jhu_csse_daily.Rd b/man/jhu_csse_daily.Rd index 781ac280..bc860ec4 100644 --- a/man/jhu_csse_daily.Rd +++ b/man/jhu_csse_daily.Rd @@ -16,8 +16,16 @@ A tibble with 60 rows and 6 variables: } } \source{ -COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. -\url{https://github.com/CSSEGISandData/COVID-19} +This data set is licensed under the terms of the +\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +Copyright Johns Hopkins University 2020. +\itemize{ +\item \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{COVIDcast Epidata JHU Cases and Death} +} + +The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ jhu_csse_daily From 76b43bda795f11d6a4ad184722a6201c6bfe2f6c Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Fri, 20 May 2022 11:45:42 -0700 Subject: [PATCH 34/41] rename example data with suffix --- R/archive.R | 4 ++-- R/correlation.R | 8 ++++---- R/data.R | 10 +++++----- R/methods-epi_archive.R | 10 +++++----- R/outliers.R | 6 +++--- R/slide.R | 6 +++--- ...ive_cases_dv.R => archive_cases_dv_subset.R} | 8 ++++---- ...jhu_csse_daily.R => jhu_csse_daily_subset.R} | 4 ++-- data/archive_cases_dv.rda | Bin 42489 -> 0 bytes data/archive_cases_dv_subset.rda | Bin 0 -> 42591 bytes data/jhu_csse_daily.rda | Bin 2147 -> 0 bytes data/jhu_csse_daily_subset.rda | Bin 0 -> 2165 bytes ...e_cases_dv.Rd => archive_cases_dv_subset.Rd} | 8 ++++---- man/detect_outlr.Rd | 2 +- man/detect_outlr_rm.Rd | 2 +- man/detect_outlr_stl.Rd | 2 +- man/epi_cor.Rd | 8 ++++---- man/epi_slide.Rd | 6 +++--- man/epix_as_of.Rd | 4 ++-- man/epix_merge.Rd | 4 ++-- man/epix_slide.Rd | 2 +- man/is_epi_archive.Rd | 4 ++-- ...u_csse_daily.Rd => jhu_csse_daily_subset.Rd} | 10 +++++----- 23 files changed, 54 insertions(+), 54 deletions(-) rename data-raw/{archive_cases_dv.R => archive_cases_dv_subset.R} (79%) rename data-raw/{jhu_csse_daily.R => jhu_csse_daily_subset.R} (93%) delete mode 100644 data/archive_cases_dv.rda create mode 100644 data/archive_cases_dv_subset.rda delete mode 100644 data/jhu_csse_daily.rda create mode 100644 data/jhu_csse_daily_subset.rda rename man/{archive_cases_dv.Rd => archive_cases_dv_subset.Rd} (89%) rename man/{jhu_csse_daily.Rd => jhu_csse_daily_subset.Rd} (84%) diff --git a/R/archive.R b/R/archive.R index 2b600f7b..f7a98526 100644 --- a/R/archive.R +++ b/R/archive.R @@ -477,8 +477,8 @@ as_epi_archive = function(x, geo_type, time_type, other_keys, #' #' @export #' @examples -#' is_epi_archive(jhu_csse_daily) # FALSE (this is an epi_df, not epi_archive) -#' is_epi_archive(archive_cases_dv) # TRUE +#' is_epi_archive(jhu_csse_daily_subset) # FALSE (this is an epi_df, not epi_archive) +#' is_epi_archive(archive_cases_dv_subset) # TRUE is_epi_archive = function(x) { inherits(x, "epi_archive") } diff --git a/R/correlation.R b/R/correlation.R index e4f609f8..62d024bd 100644 --- a/R/correlation.R +++ b/R/correlation.R @@ -43,26 +43,26 @@ #' @examples #' #' # linear association of case and death rates on any given day -#' epi_cor(x = jhu_csse_daily, +#' epi_cor(x = jhu_csse_daily_subset, #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = "time_value") #' #' # correlation of death rates and lagged case rates -#' epi_cor(x = jhu_csse_daily, +#' epi_cor(x = jhu_csse_daily_subset, #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = time_value, #' dt1 = -2) #' #' # correlation grouped by location -#' epi_cor(x = jhu_csse_daily, +#' epi_cor(x = jhu_csse_daily_subset, #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = geo_value) #' #' # correlation grouped by location and incorporates lagged cases rates -#' epi_cor(x = jhu_csse_daily, +#' epi_cor(x = jhu_csse_daily_subset, #' var1 = case_rate_7d_av, #' var2 = death_rate_7d_av, #' cor_by = geo_value, diff --git a/R/data.R b/R/data.R index 2f52ed2b..d374cf4b 100644 --- a/R/data.R +++ b/R/data.R @@ -1,9 +1,9 @@ -#' JHU daily cases and deaths from California, Florida, Texas, and New York +#' Subset of JHU daily cases and deaths from California, Florida, Texas, and New York #' #' This data source of confirmed COVID-19 cases and deaths #' is based on reports made available by the Center for #' Systems Science and Engineering at Johns Hopkins University. -#' This example data ranges from June 1 to June 15, 2020. +#' This example data ranges from June 1 to June 15, 2020 and is limited to California, Florida, Texas, and New York. #' #' @format A tibble with 60 rows and 6 variables: #' \describe{ @@ -23,10 +23,10 @@ #' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{COVIDcast Epidata JHU Cases and Death} #' #' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. -"jhu_csse_daily" +"jhu_csse_daily_subset" -#' Daily doctor visits and cases from California, Florida, Texas, and New York in archive format +#' Subset of daily doctor visits and cases from California, Florida, Texas, and New York in archive format #' #' This data source is based on information about outpatient visits, #' provided to us by health system partners, and also contains confirmed @@ -52,5 +52,5 @@ #' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{COVIDcast Epidata Doctor Visits} #' #' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. -"archive_cases_dv" +"archive_cases_dv_subset" diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index d1b7ef56..8d1bde45 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -28,8 +28,8 @@ #' #' @export #' @examples -#' epix_as_of(x = archive_cases_dv, -#' max_version = max(archive_cases_dv$DT$version)) +#' epix_as_of(x = archive_cases_dv_subset, +#' max_version = max(archive_cases_dv_subset$DT$version)) epix_as_of = function(x, max_version, min_time_value = -Inf) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") return(x$as_of(max_version, min_time_value)) @@ -72,10 +72,10 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' @export #' @examples #' # create two example epi_archive datasets -#' x <- archive_cases_dv$DT %>% +#' x <- archive_cases_dv_subset$DT %>% #' dplyr::select(geo_value,time_value,version,case_rate) %>% #' as_epi_archive() -#' y <- archive_cases_dv$DT %>% +#' y <- archive_cases_dv_subset$DT %>% #' dplyr::select(geo_value,time_value,version,percent_cli) %>% #' as_epi_archive() #' @@ -186,7 +186,7 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' time_values <- seq(as.Date("2020-06-01"), #' as.Date("2020-06-15"), #' by = "1 day") -#' epix_slide(x = archive_cases_dv, +#' epix_slide(x = archive_cases_dv_subset, #' f = ~ mean(.x$case_rate), #' n = 3, #' group_by = geo_value, diff --git a/R/outliers.R b/R/outliers.R index 388260f5..a20c9535 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -62,7 +62,7 @@ #' seasonal_period = NULL)), #' abbr = "stl_nonseasonal")) #' -#' x <- jhu_csse_daily %>% +#' x <- jhu_csse_daily_subset %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% @@ -149,7 +149,7 @@ detect_outlr = function(x = seq_along(y), y, #' @export #' @examples #' # Detect outliers based on a rolling median -#' jhu_csse_daily %>% +#' jhu_csse_daily_subset %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% @@ -246,7 +246,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @export #' @examples #' # Detects outliers based on a seasonal-trend decomposition using LOESS -#' jhu_csse_daily %>% +#' jhu_csse_daily_subset %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% diff --git a/R/slide.R b/R/slide.R index 07652c3d..eae5f9f8 100644 --- a/R/slide.R +++ b/R/slide.R @@ -90,19 +90,19 @@ #' @export #' @examples #' # slide a 7-day trailing average formula on cases -#' jhu_csse_daily %>% +#' jhu_csse_daily_subset %>% #' group_by(geo_value) %>% #' epi_slide(cases_7dav = mean(cases), n = 7, #' align = "right") #' #' # slide a left-aligned 7-day trailing average -#' jhu_csse_daily %>% +#' jhu_csse_daily_subset %>% #' group_by(geo_value) %>% #' epi_slide(cases_7dav = mean(cases), n = 7, #' align = "left") #' #' # nested new columns -#' jhu_csse_daily %>% +#' jhu_csse_daily_subset %>% #' group_by(geo_value) %>% #' epi_slide(a = data.frame(cases_2dav = mean(cases), #' cases_2dma = mad(cases)), diff --git a/data-raw/archive_cases_dv.R b/data-raw/archive_cases_dv_subset.R similarity index 79% rename from data-raw/archive_cases_dv.R rename to data-raw/archive_cases_dv_subset.R index 4d49b638..bac727d2 100644 --- a/data-raw/archive_cases_dv.R +++ b/data-raw/archive_cases_dv_subset.R @@ -3,7 +3,7 @@ library(epiprocess) library(data.table) library(dplyr) -archive_cases_dv <- covidcast( +archive_cases_dv_subset <- covidcast( data_source = "doctor-visits", signals = "smoothed_adj_cli", time_type = "day", @@ -16,7 +16,7 @@ archive_cases_dv <- covidcast( select(geo_value, time_value, version = issue, percent_cli = value) %>% as_epi_archive() -case_rate <- covidcast( +case_rate_subset <- covidcast( data_source = "jhu-csse", signals = "confirmed_7dav_incidence_prop", time_type = "day", @@ -29,6 +29,6 @@ case_rate <- covidcast( select(geo_value, time_value, version = issue, case_rate = value) %>% as_epi_archive() -epix_merge(archive_cases_dv, case_rate, all = TRUE) +epix_merge(archive_cases_dv_subset, case_rate_subset, all = TRUE) -usethis::use_data(archive_cases_dv, overwrite = TRUE) +usethis::use_data(archive_cases_dv_subset, overwrite = TRUE) diff --git a/data-raw/jhu_csse_daily.R b/data-raw/jhu_csse_daily_subset.R similarity index 93% rename from data-raw/jhu_csse_daily.R rename to data-raw/jhu_csse_daily_subset.R index c82031d6..5db09536 100644 --- a/data-raw/jhu_csse_daily.R +++ b/data-raw/jhu_csse_daily_subset.R @@ -50,7 +50,7 @@ confirmed_7dav_incidence_num <- covidcast( select(geo_value, time_value, cases_7d_av = value) %>% arrange(geo_value, time_value) -jhu_csse_daily <- confirmed_7dav_incidence_prop %>% +jhu_csse_daily_subset <- confirmed_7dav_incidence_prop %>% full_join(deaths_7dav_incidence_prop, by = c("geo_value", "time_value")) %>% full_join(confirmed_incidence_num, @@ -59,4 +59,4 @@ 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+\name{archive_cases_dv_subset} +\alias{archive_cases_dv_subset} +\title{Subset of daily doctor visits and cases from California, Florida, Texas, and New York in archive format} \format{ An \code{epi_archive} data format. The data table DT has 160 rows and 5 columns: \describe{ @@ -27,7 +27,7 @@ Copyright Johns Hopkins University 2020. The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ -archive_cases_dv +archive_cases_dv_subset } \description{ This data source is based on information about outpatient visits, diff --git a/man/detect_outlr.Rd b/man/detect_outlr.Rd index df975947..ac839014 100644 --- a/man/detect_outlr.Rd +++ b/man/detect_outlr.Rd @@ -80,7 +80,7 @@ STL decomposition. seasonal_period = NULL)), abbr = "stl_nonseasonal")) - x <- jhu_csse_daily \%>\% + x <- jhu_csse_daily_subset \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% diff --git a/man/detect_outlr_rm.Rd b/man/detect_outlr_rm.Rd index 6b373c29..e0f9e59b 100644 --- a/man/detect_outlr_rm.Rd +++ b/man/detect_outlr_rm.Rd @@ -54,7 +54,7 @@ terms of multiples of the rolling interquartile range (IQR). } \examples{ # Detect outliers based on a rolling median -jhu_csse_daily \%>\% +jhu_csse_daily_subset \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index 7ee9808a..784a97af 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -77,7 +77,7 @@ are exactly as in \code{detect_outlr_rm()}. } \examples{ # Detects outliers based on a seasonal-trend decomposition using LOESS -jhu_csse_daily \%>\% +jhu_csse_daily_subset \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% diff --git a/man/epi_cor.Rd b/man/epi_cor.Rd index 03d725d3..6b2279db 100644 --- a/man/epi_cor.Rd +++ b/man/epi_cor.Rd @@ -60,26 +60,26 @@ for examples. \examples{ # linear association of case and death rates on any given day -epi_cor(x = jhu_csse_daily, +epi_cor(x = jhu_csse_daily_subset, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = "time_value") # correlation of death rates and lagged case rates -epi_cor(x = jhu_csse_daily, +epi_cor(x = jhu_csse_daily_subset, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = time_value, dt1 = -2) # correlation grouped by location -epi_cor(x = jhu_csse_daily, +epi_cor(x = jhu_csse_daily_subset, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = geo_value) # correlation grouped by location and incorporates lagged cases rates -epi_cor(x = jhu_csse_daily, +epi_cor(x = jhu_csse_daily_subset, var1 = case_rate_7d_av, var2 = death_rate_7d_av, cor_by = geo_value, diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index 1e42dbf3..e018b523 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -118,19 +118,19 @@ through the \code{new_col_name} argument. } \examples{ # slide a 7-day trailing average formula on cases - jhu_csse_daily \%>\% + jhu_csse_daily_subset \%>\% group_by(geo_value) \%>\% epi_slide(cases_7dav = mean(cases), n = 7, align = "right") # slide a left-aligned 7-day trailing average - jhu_csse_daily \%>\% + jhu_csse_daily_subset \%>\% group_by(geo_value) \%>\% epi_slide(cases_7dav = mean(cases), n = 7, align = "left") # nested new columns - jhu_csse_daily \%>\% + jhu_csse_daily_subset \%>\% group_by(geo_value) \%>\% epi_slide(a = data.frame(cases_2dav = mean(cases), cases_2dma = mad(cases)), diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index e5801566..e303f009 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -36,6 +36,6 @@ is equivalent to:\preformatted{x$as_of(max_version = v) } } \examples{ -epix_as_of(x = archive_cases_dv, - max_version = max(archive_cases_dv$DT$version)) +epix_as_of(x = archive_cases_dv_subset, + max_version = max(archive_cases_dv_subset$DT$version)) } diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index 731d4625..e13c14c4 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -43,10 +43,10 @@ is equivalent to:\preformatted{x$merge(y) } \examples{ # create two example epi_archive datasets -x <- archive_cases_dv$DT \%>\% +x <- archive_cases_dv_subset$DT \%>\% dplyr::select(geo_value,time_value,version,case_rate) \%>\% as_epi_archive() -y <- archive_cases_dv$DT \%>\% +y <- archive_cases_dv_subset$DT \%>\% dplyr::select(geo_value,time_value,version,percent_cli) \%>\% as_epi_archive() diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 98c0d146..529765b9 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -126,7 +126,7 @@ is equivalent to:\preformatted{x$slide(x, new_var = comp(old_var), n = 120) time_values <- seq(as.Date("2020-06-01"), as.Date("2020-06-15"), by = "1 day") -epix_slide(x = archive_cases_dv, +epix_slide(x = archive_cases_dv_subset, f = ~ mean(.x$case_rate), n = 3, group_by = geo_value, diff --git a/man/is_epi_archive.Rd b/man/is_epi_archive.Rd index 85f546a0..f8dcf2c8 100644 --- a/man/is_epi_archive.Rd +++ b/man/is_epi_archive.Rd @@ -16,6 +16,6 @@ is_epi_archive(x) Test for \code{epi_archive} format } \examples{ -is_epi_archive(jhu_csse_daily) # FALSE (this is an epi_df, not epi_archive) -is_epi_archive(archive_cases_dv) # TRUE +is_epi_archive(jhu_csse_daily_subset) # FALSE (this is an epi_df, not epi_archive) +is_epi_archive(archive_cases_dv_subset) # TRUE } diff --git a/man/jhu_csse_daily.Rd b/man/jhu_csse_daily_subset.Rd similarity index 84% rename from man/jhu_csse_daily.Rd rename to man/jhu_csse_daily_subset.Rd index bc860ec4..3a0a1f59 100644 --- a/man/jhu_csse_daily.Rd +++ b/man/jhu_csse_daily_subset.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/data.R \docType{data} -\name{jhu_csse_daily} -\alias{jhu_csse_daily} -\title{JHU daily cases and deaths from California, Florida, Texas, and New York} +\name{jhu_csse_daily_subset} +\alias{jhu_csse_daily_subset} +\title{Subset of JHU daily cases and deaths from California, Florida, Texas, and New York} \format{ A tibble with 60 rows and 6 variables: \describe{ @@ -28,12 +28,12 @@ Copyright Johns Hopkins University 2020. The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ -jhu_csse_daily +jhu_csse_daily_subset } \description{ This data source of confirmed COVID-19 cases and deaths is based on reports made available by the Center for Systems Science and Engineering at Johns Hopkins University. -This example data ranges from June 1 to June 15, 2020. +This example data ranges from June 1 to June 15, 2020 and is limited to California, Florida, Texas, and New York. } \keyword{datasets} From 5c954c5d777ed1c3bf310608a338115dca67f926 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Fri, 20 May 2022 13:45:44 -0700 Subject: [PATCH 35/41] add examples without latency warning in slide.R --- R/methods-epi_archive.R | 12 +++++++++++- R/slide.R | 2 +- man/epi_slide.Rd | 2 +- man/epix_as_of.Rd | 4 ++++ man/epix_slide.Rd | 8 +++++++- 5 files changed, 24 insertions(+), 4 deletions(-) diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index 8d1bde45..d005d6ca 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -28,8 +28,12 @@ #' #' @export #' @examples +#' # warning message of data latency shown #' epix_as_of(x = archive_cases_dv_subset, #' max_version = max(archive_cases_dv_subset$DT$version)) +#' +#' # no warning shown +#' epix_as_of(archive_cases_dv_subset, max_version = as.Date("2020-06-10")) epix_as_of = function(x, max_version, min_time_value = -Inf) { if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.") return(x$as_of(max_version, min_time_value)) @@ -182,7 +186,13 @@ epix_merge = function(x, y, ..., locf = TRUE, nan = NA) { #' @importFrom rlang enquo #' @export #' @examples -#' # every date is a reference time point for the 3 day average sliding window +#' # these dates are reference time points for the 3 day average sliding window +#' # The resulting epi_archive ends up including data averaged from: +#' # 0 day which has no results, for 2020-06-01 +#' # 1 day, for 2020-06-02 +#' # 2 days, for the rest of the results +#' # never 3 days dur to data latency +#' #' time_values <- seq(as.Date("2020-06-01"), #' as.Date("2020-06-15"), #' by = "1 day") diff --git a/R/slide.R b/R/slide.R index eae5f9f8..5847b130 100644 --- a/R/slide.R +++ b/R/slide.R @@ -95,7 +95,7 @@ #' epi_slide(cases_7dav = mean(cases), n = 7, #' align = "right") #' -#' # slide a left-aligned 7-day trailing average +#' # slide a left-aligned 7-day average #' jhu_csse_daily_subset %>% #' group_by(geo_value) %>% #' epi_slide(cases_7dav = mean(cases), n = 7, diff --git a/man/epi_slide.Rd b/man/epi_slide.Rd index e018b523..2e737293 100644 --- a/man/epi_slide.Rd +++ b/man/epi_slide.Rd @@ -123,7 +123,7 @@ through the \code{new_col_name} argument. epi_slide(cases_7dav = mean(cases), n = 7, align = "right") - # slide a left-aligned 7-day trailing average + # slide a left-aligned 7-day average jhu_csse_daily_subset \%>\% group_by(geo_value) \%>\% epi_slide(cases_7dav = mean(cases), n = 7, diff --git a/man/epix_as_of.Rd b/man/epix_as_of.Rd index e303f009..658e7169 100644 --- a/man/epix_as_of.Rd +++ b/man/epix_as_of.Rd @@ -36,6 +36,10 @@ is equivalent to:\preformatted{x$as_of(max_version = v) } } \examples{ +# warning message of data latency shown epix_as_of(x = archive_cases_dv_subset, max_version = max(archive_cases_dv_subset$DT$version)) + +# no warning shown +epix_as_of(archive_cases_dv_subset, max_version = as.Date("2020-06-10")) } diff --git a/man/epix_slide.Rd b/man/epix_slide.Rd index 529765b9..f01a0a71 100644 --- a/man/epix_slide.Rd +++ b/man/epix_slide.Rd @@ -122,7 +122,13 @@ is equivalent to:\preformatted{x$slide(x, new_var = comp(old_var), n = 120) } } \examples{ -# every date is a reference time point for the 3 day average sliding window +# these dates are reference time points for the 3 day average sliding window +# The resulting epi_archive ends up including data averaged from: +# 0 day which has no results, for 2020-06-01 +# 1 day, for 2020-06-02 +# 2 days, for the rest of the results +# never 3 days dur to data latency + time_values <- seq(as.Date("2020-06-01"), as.Date("2020-06-15"), by = "1 day") From 2df3625c92c833486466e6cdffad50acf6c3f16a Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Sat, 21 May 2022 16:27:05 -0700 Subject: [PATCH 36/41] handle feedback from @brookslogan #77 --- R/data.R | 58 ++++++++++++++++------- R/outliers.R | 6 +-- data-raw/archive_cases_dv_subset.R | 2 +- data-raw/incidence_num_outlier_example.R | 19 ++++++++ data/incidence_num_outlier_example.rda | Bin 0 -> 3213 bytes man/archive_cases_dv_subset.Rd | 18 +++---- man/detect_outlr.Rd | 2 +- man/detect_outlr_rm.Rd | 2 +- man/incidence_num_outlier_example.Rd | 38 +++++++++++++++ man/jhu_csse_daily_subset.Rd | 10 ++-- 10 files changed, 118 insertions(+), 37 deletions(-) create mode 100644 data-raw/incidence_num_outlier_example.R create mode 100644 data/incidence_num_outlier_example.rda create mode 100644 man/incidence_num_outlier_example.Rd diff --git a/R/data.R b/R/data.R index d374cf4b..e1f02c75 100644 --- a/R/data.R +++ b/R/data.R @@ -14,15 +14,14 @@ #' \item{cases}{Number of new confirmed COVID-19 cases, daily} #' \item{cases_7d_av}{7-day average signal of number of new confirmed COVID-19 cases, daily} #' } -#' @source This data set is licensed under the terms of the -#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} -#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' @source This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. #' Copyright Johns Hopkins University 2020. #' -#' * \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{COVIDcast Epidata JHU Cases and Death} -#' -#' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. +#' Modifications: +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +#' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. "jhu_csse_daily_subset" @@ -32,25 +31,50 @@ #' provided to us by health system partners, and also contains confirmed #' COVID-19 cases based on reports made available by the Center for #' Systems Science and Engineering at Johns Hopkins University. -#' This example data ranges from June 1 to June 15, 2020. +#' This example data ranges from June 1 to June 15, 2020, and is also limited to California, Florida, Texas, and New York. #' #' @format An `epi_archive` data format. The data table DT has 160 rows and 5 columns: #' \describe{ #' \item{geo_value}{the geographic value associated with each row of measurements.} #' \item{time_value}{the time value associated with each row of measurements.} -#' \item{version}{ the time value specifying the version for each row of measurements. } +#' \item{version}{the time value specifying the version for each row of measurements. } #' \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} -#' \item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +#' \item{case_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} #' } #' @source -#' This data set is licensed under the terms of the -#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} -#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by Johns Hopkins University on behalf of its Center for Systems Science in Engineering. #' Copyright Johns Hopkins University 2020. #' -#' * \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} -#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{COVIDcast Epidata Doctor Visits} -#' -#' The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. +#' Modifications: +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{From the COVIDcast Epidata Doctor Visits API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +#' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. "archive_cases_dv_subset" + +#' Subset of JHU daily cases from California and Florida +#' +#' This data source of confirmed COVID-19 cases +#' is based on reports made available by the Center for +#' Systems Science and Engineering at Johns Hopkins University. +#' This example data is a snapshot as of Oct 28, 2021 and captures the cases from June 1, 2020 to May 31, 2021 +#' and is limited to California and Florida. +#' +#' @format A tibble with 730 rows and 3 variables: +#' \describe{ +#' \item{geo_value}{the geographic value associated with each row of measurements.} +#' \item{time_value}{the time value associated with each row of measurements.} +#' \item{cases}{Number of new confirmed COVID-19 cases, daily} +#' } +#' @source This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' Copyright Johns Hopkins University 2020. +#' +#' Modifications: +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: +#' These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. +#' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. +"incidence_num_outlier_example" + diff --git a/R/outliers.R b/R/outliers.R index a20c9535..6cc2ffb1 100644 --- a/R/outliers.R +++ b/R/outliers.R @@ -62,7 +62,7 @@ #' seasonal_period = NULL)), #' abbr = "stl_nonseasonal")) #' -#' x <- jhu_csse_daily_subset %>% +#' x <- incidence_num_outlier_example %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% @@ -149,7 +149,7 @@ detect_outlr = function(x = seq_along(y), y, #' @export #' @examples #' # Detect outliers based on a rolling median -#' jhu_csse_daily_subset %>% +#' incidence_num_outlier_example %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% @@ -246,7 +246,7 @@ detect_outlr_rm = function(x = seq_along(y), y, n = 21, #' @export #' @examples #' # Detects outliers based on a seasonal-trend decomposition using LOESS -#' jhu_csse_daily_subset %>% +#' incidence_num_outlier_example %>% #' dplyr::select(geo_value,time_value,cases) %>% #' as_epi_df() %>% #' group_by(geo_value) %>% diff --git a/data-raw/archive_cases_dv_subset.R b/data-raw/archive_cases_dv_subset.R index bac727d2..4818eba4 100644 --- a/data-raw/archive_cases_dv_subset.R +++ b/data-raw/archive_cases_dv_subset.R @@ -26,7 +26,7 @@ case_rate_subset <- covidcast( issues = epirange(20200601, 20200615) ) %>% fetch_tbl() %>% - select(geo_value, time_value, version = issue, case_rate = value) %>% + select(geo_value, time_value, version = issue, case_rate_7d_av = value) %>% as_epi_archive() epix_merge(archive_cases_dv_subset, case_rate_subset, all = TRUE) diff --git a/data-raw/incidence_num_outlier_example.R b/data-raw/incidence_num_outlier_example.R new file mode 100644 index 00000000..992e9d89 --- /dev/null +++ b/data-raw/incidence_num_outlier_example.R @@ -0,0 +1,19 @@ +library(delphi.epidata) +library(epiprocess) +library(dplyr) +library(tidyr) + +incidence_num_outlier_example <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_incidence_num", + time_type = "day", + geo_type = "state", + time_values = epirange(20200601, 20210531), + geo_values = "fl,nj", + as_of = 20211028 +) %>% + fetch_tbl() %>% + select(geo_value, time_value, cases = value) %>% + as_epi_df() + +usethis::use_data(incidence_num_outlier_example, overwrite = TRUE) diff --git a/data/incidence_num_outlier_example.rda b/data/incidence_num_outlier_example.rda new file mode 100644 index 0000000000000000000000000000000000000000..e898b5eaa6b359ce9ab2bc6aa435a4a071eab54e GIT binary patch literal 3213 zcmd6qX*ASrAIJY=88dc5mKuyKbK8c-zBG1YNf@_AWU@6RL<%K4Lu4BaBAJZ6D1>x3 zb|$h7g$PAs3wJ2AJh{(#o^wAhp6BIrp6~gd@A;hX@A{o{y}4do#x4XMH6xsyBd)&+ zj|3!jqJI8oMeV%)9`$05`xtOxm>0$u4NIZ{=2s2p?@+%6NJ5?Lu)}@o;y@oO8vrT+ zWlK}ZXkZKtc!B$Q01!1!isNThWrl~CnmAYvjbepT&;S6?iy31!wy0rmO)7VsoTIp{ zge^E@P|ij^8!cl|(KTfb&4@6fvKo8&7UUyGeJPA7JNt}bF9Tat7pjXeX7OMu4dsbh z@$iXdH8m%W!l*U{<=GMBg5rYgZ4Co?Drv`{3|3A8MjCl|_|9-g10G@k>!^VYWZMq0 zk0{wOkX}TMb&FM&S1zOaDH_0-lsF&`j*)Y6ApW}D--P-b|AkYfwrClKZwaA~0En}q z|LRZx0XQ_M1OR?jhdaXnz*+f#8gE-sOfSal7YMA}qK;^Y!3w|y@|8>@W~xPHGF86f zyW@^@G>tINw2X?BUTG@I=VJ-3!|CXI(=vkMKOzO6dwhofG z;zD$vep~$qT7X1ZD&&Y5!=?+m%=9;;nw{5rGwvPXFmT3?_`b%pel~LP@ofo(Ml~fc z3b&ok_C2!m(NT%EXVpF@VrBjL)N8ChXhobiZ{H((Tuq^$RpG<#B0BYzPME%pztppE1Y95UVe?~gRbC~Yb%((h&KBtOy#Lj!FCLBg z>zYmb-ZO7T_HI78G=?tpE?aXBUpQ@Ya$k2fv|hO0Gcg`J%!QE`4-^xzhlnFY!qmn= z&0I@KX0>%mLk}BK7aG5P)5oA6*RHQCTl*XNr)%7qfI539TkWwlKS)%y@FDWqbD(-Q zmPIfSWl8v>(CQD(vWqt52S1K1Eu4SFL!?M@PJB83!8G`>x%jsOtw=Ri6(I?g>3aF9 zBC#9&pwy2ccbSsHXSz&Rps=aVHm}&Fl<4kLlcOO!!9fa>{_eb%9j9ok7f;YiIVv@)C##4d5yWjdA#+-M0yTe=Mxk4rJPLxH&rWS%HR7wG!Ec%= zJ7TxD3mrMt>eFPUI;JwKi4)+91mVHm;m;kOlaGTkfPIL>9wdk$2@ROYP- z7wIfLqGeC!l4~V~&CQ1v4ScGb!Fg=-Nt|jC)rWq*J(%O#^l0t|WXYu4XOSTj`~)uD zHanl_kkb<%J>(3D+mA{M`eAxprcFD;OYEIKTiC8~27AL5eVLIVMY-)FiQepE`hupo z0kKT)x^;oXfmr#}enUK+73*S25%IIpNfd*@KUtFG{9D9LdThl%bB1$mO~6v%mW48D zmHIYf6uLpN2jO!ei~e|VT&YPmMP^jTbuRMswz9gA+r;-pndRg!n|`V@i((Qn0Y+~= z2@xU2zlVyD+e-nm@kN`4yP{iC zmgZ%##vnAtkui5af}dAD)jy~8ofj9;7_HEA0)XyGp^Ghu{PO8%e~=Acw8h4SrrwP7 zJdc)^XRv^f?7UfYtU2GjRa_bJetLzLfNXnfUFgQFBG(y~*RD576erOip8EED_0KhFPDc}-yQkJ* zY1}t;EAzJMuk)nMAK+EM?G`@3_O_LYBbT~jJP~OF=JJFly+rrt}{-A`;RD% zpb;t0aF;Zdp`g##-`P(^@k%1!N!uBNL%J$9@CTAvR6o8|b}c1$KTG#5t|SjKe6?m&L#e4BYsNfZD~)s%_Xq`UQYTq4 zZCL6wIPi#GkU|z6EqPBn8hDJvfkoeyfQVbY*K#iRWibH(!2q|>IW;LO*OSSD!>0fN+urm73-pV1*t@h7|Tl96G z7g7tf)fqAoBW$Dc<|xS#H@ZM8DsD)*|R6iQa-$C!0>ksCC@o(PJTZtaoh2Kr_|lOy9B)Y?2S5 zFaHSK>wkwIgQE3O9OdZw^h%}*LAvpPUND$rAM%C`v;=Ps1d)idwcG+ z-)3lDdtH0Q9)E!HWgG48GBT8`p~+9F*q@BL|Mc^- z-6)$^gn;$d!0Lz0dP9}mKlheqZM`63ffn1_$jjF)zoqU-40Qx+eRZC-LGacrX2peP zx>vkGcXRidHGH>7_jTz@DbJo;Z$39j5mnV+&bv~daMI(B=9u*ZIBDW*139?*|! zgal=`Y!!Yun=w4eu-TH_bo~0$x-NsfPfah57QNiEd2q(+o>;Y)K*S_NQPCwsQd$3k zls5Nr2u7*fsThYB;NWH7EJ z;6x&W);U;`+HUh+CqC0aeg7tG;;19s7JLuS2*}LEKvh>h1nxuPu_gGKi?3OF&)5ny znuH`>oKtzP5gDI#K|2BO7ITe*h8tn3EUs#%>DMkHM@i9#%F<|QhYMqpLS(1l>7L5 zsC5~Lq0?+*kQJr7r0;oT)EUvM`kgFU%dFg;J_gpgqb3*u;1Lfst3Xwex6F~A>TPd# zx{PR{K1Lhwj9xxqlR#p6&`{lMVY1MxsNtRSh`X@tD7IMGtscq*E$$WparX;p!PiSW)k{zCOPpj+^>WG;c64@w+E2`0)-Gt7DX?#S zv;bYpERlaAYPujGm*gi%^uIxb5PYK7uv|p=S*}o8N_=Ubo^zy`a4a?@#F&%w?i|9@ znt<;NNk9hF9`i!2mzMp2S4BmtI3h@NZ}ogzYlV1eh%x_v3zOzw)3AR#BKmEqpM*_) zawKTY#K?ZKGsr2HJth(GyxISN;L~aBA7`Y+k#>bkOPnF9B=bJHZs^?7g@=>jyIfb9 zB}W9iee;boM)F=#HC1wDD|l9S;{C%S!Y38|B1zcZlwo1#FHkA8CY}Y(rm~|~Jxw0> zUv1OAKGHODzNL3We-mg;ev%D#?5d6A;>-=r^4<9Geua8t0&z*s6?4UXHEsRG?=mV~ z77a+8z|z$7i2=H2^Rcgpncpt$sxCHE7W69Ye44Y^m0H!7Fi9W<56-el*wO^^+UYM` b0Y9{K1Sk&auyI=J=h0v@?K2sN-;aL)=ZuL` literal 0 HcmV?d00001 diff --git a/man/archive_cases_dv_subset.Rd b/man/archive_cases_dv_subset.Rd index 0dacd42c..b93f89c7 100644 --- a/man/archive_cases_dv_subset.Rd +++ b/man/archive_cases_dv_subset.Rd @@ -9,22 +9,22 @@ An \code{epi_archive} data format. The data table DT has 160 rows and 5 columns: \describe{ \item{geo_value}{the geographic value associated with each row of measurements.} \item{time_value}{the time value associated with each row of measurements.} -\item{version}{ the time value specifying the version for each row of measurements. } +\item{version}{the time value specifying the version for each row of measurements. } \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims} -\item{case_rate}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} +\item{case_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily} } } \source{ -This data set is licensed under the terms of the +This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} -by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +by Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +Modifications: \itemize{ -\item \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{COVIDcast Epidata Doctor Visits} +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{From the COVIDcast Epidata Doctor Visits API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +\item Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. } - -The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ archive_cases_dv_subset @@ -34,6 +34,6 @@ This data source is based on information about outpatient visits, provided to us by health system partners, and also contains confirmed COVID-19 cases based on reports made available by the Center for Systems Science and Engineering at Johns Hopkins University. -This example data ranges from June 1 to June 15, 2020. +This example data ranges from June 1 to June 15, 2020, and is also limited to California, Florida, Texas, and New York. } \keyword{datasets} diff --git a/man/detect_outlr.Rd b/man/detect_outlr.Rd index ac839014..4aa0b79c 100644 --- a/man/detect_outlr.Rd +++ b/man/detect_outlr.Rd @@ -80,7 +80,7 @@ STL decomposition. seasonal_period = NULL)), abbr = "stl_nonseasonal")) - x <- jhu_csse_daily_subset \%>\% + x <- incidence_num_outlier_example \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% diff --git a/man/detect_outlr_rm.Rd b/man/detect_outlr_rm.Rd index e0f9e59b..33e3f73b 100644 --- a/man/detect_outlr_rm.Rd +++ b/man/detect_outlr_rm.Rd @@ -54,7 +54,7 @@ terms of multiples of the rolling interquartile range (IQR). } \examples{ # Detect outliers based on a rolling median -jhu_csse_daily_subset \%>\% +incidence_num_outlier_example \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% diff --git a/man/incidence_num_outlier_example.Rd b/man/incidence_num_outlier_example.Rd new file mode 100644 index 00000000..23afdf51 --- /dev/null +++ b/man/incidence_num_outlier_example.Rd @@ -0,0 +1,38 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{incidence_num_outlier_example} +\alias{incidence_num_outlier_example} +\title{Subset of JHU daily cases from California and Florida} +\format{ +A tibble with 730 rows and 3 variables: +\describe{ +\item{geo_value}{the geographic value associated with each row of measurements.} +\item{time_value}{the time value associated with each row of measurements.} +\item{cases}{Number of new confirmed COVID-19 cases, daily} +} +} +\source{ +This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +Copyright Johns Hopkins University 2020. + +Modifications: +\itemize{ +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: +These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. +\item Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. +} +} +\usage{ +incidence_num_outlier_example +} +\description{ +This data source of confirmed COVID-19 cases +is based on reports made available by the Center for +Systems Science and Engineering at Johns Hopkins University. +This example data is a snapshot as of Oct 28, 2021 and captures the cases from June 1, 2020 to May 31, 2021 +and is limited to California and Florida. +} +\keyword{datasets} diff --git a/man/jhu_csse_daily_subset.Rd b/man/jhu_csse_daily_subset.Rd index 3a0a1f59..e02b7b45 100644 --- a/man/jhu_csse_daily_subset.Rd +++ b/man/jhu_csse_daily_subset.Rd @@ -16,16 +16,16 @@ A tibble with 60 rows and 6 variables: } } \source{ -This data set is licensed under the terms of the +This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +Modifications: \itemize{ -\item \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository} -\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{COVIDcast Epidata JHU Cases and Death} +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +\item Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. } - -The example data is a filtered time view of the full data, and is also limited to California, Florida, Texas, and New York. } \usage{ jhu_csse_daily_subset From f9d070a874056816cf66cac13385101b6c9ee5a0 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Sat, 21 May 2022 16:27:25 -0700 Subject: [PATCH 37/41] handle feedback from @brookslogan #77 --- man/detect_outlr_stl.Rd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/man/detect_outlr_stl.Rd b/man/detect_outlr_stl.Rd index 784a97af..7e724a4e 100644 --- a/man/detect_outlr_stl.Rd +++ b/man/detect_outlr_stl.Rd @@ -77,7 +77,7 @@ are exactly as in \code{detect_outlr_rm()}. } \examples{ # Detects outliers based on a seasonal-trend decomposition using LOESS -jhu_csse_daily_subset \%>\% +incidence_num_outlier_example \%>\% dplyr::select(geo_value,time_value,cases) \%>\% as_epi_df() \%>\% group_by(geo_value) \%>\% From 504f2fe65c6d110e4453a7588a2e5ffc8671a78e Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Mon, 23 May 2022 14:33:46 -0700 Subject: [PATCH 38/41] change to internal data in vignettes; add attribution to vignettes; some changes from epiprocess/#77 --- R/data.R | 8 ++++--- data-raw/jhu_csse_county_level_subset.R | 25 ++++++++++++++++++++++ data-raw/jhu_csse_daily_subset.R | 16 +++++++------- data/jhu_csse_county_level_subset.rda | Bin 0 -> 20370 bytes data/jhu_csse_daily_subset.rda | Bin 2165 -> 82105 bytes man/jhu_csse_daily_subset.Rd | 4 ++-- vignettes/aggregation.Rmd | 16 ++++++++++++-- vignettes/correlation.Rmd | 27 +++++++++++++++++++++--- vignettes/growth_rate.Rmd | 17 ++++++++++++++- vignettes/slide.Rmd | 23 +++++++++++++++++++- 10 files changed, 116 insertions(+), 20 deletions(-) create mode 100644 data-raw/jhu_csse_county_level_subset.R create mode 100644 data/jhu_csse_county_level_subset.rda diff --git a/R/data.R b/R/data.R index e1f02c75..d6def673 100644 --- a/R/data.R +++ b/R/data.R @@ -1,11 +1,11 @@ -#' Subset of JHU daily cases and deaths from California, Florida, Texas, and New York +#' Subset of JHU daily cases and deaths from California, Florida, Texas, New York, Georgia, and Pennsylvania #' #' This data source of confirmed COVID-19 cases and deaths #' is based on reports made available by the Center for #' Systems Science and Engineering at Johns Hopkins University. -#' This example data ranges from June 1 to June 15, 2020 and is limited to California, Florida, Texas, and New York. +#' This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to California, Florida, Texas, New York, Georgia, and Pennsylvania. #' -#' @format A tibble with 60 rows and 6 variables: +#' @format A tibble with 4026 rows and 6 variables: #' \describe{ #' \item{geo_value}{the geographic value associated with each row of measurements.} #' \item{time_value}{the time value associated with each row of measurements.} @@ -78,3 +78,5 @@ #' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. "incidence_num_outlier_example" +#' TO-DO +"jhu_csse_county_level_subset" \ No newline at end of file diff --git a/data-raw/jhu_csse_county_level_subset.R b/data-raw/jhu_csse_county_level_subset.R new file mode 100644 index 00000000..a5cacd83 --- /dev/null +++ b/data-raw/jhu_csse_county_level_subset.R @@ -0,0 +1,25 @@ +library(delphi.epidata) +library(covidcast) +library(epiprocess) +library(dplyr) + +# Use covidcast::county_census to get the county and state names +y <- covidcast::county_census %>% + filter(STNAME %in% c("Massachusetts", "Vermont"), STNAME != CTYNAME) %>% + select(geo_value = FIPS, county_name = CTYNAME, state_name = STNAME) + +# Fetch only counties from Massachusetts and Vermont, then append names columns as well +jhu_csse_county_level_subset <- covidcast( + data_source = "jhu-csse", + signals = "confirmed_incidence_num", + time_type = "day", + geo_type = "county", + time_values = epirange(20200601, 20211231), + geo_values = paste(y$geo_value, collapse = ",") +) %>% + fetch_tbl() %>% + select(geo_value, time_value, cases = value) %>% + full_join(y, by = "geo_value") %>% + as_epi_df() + +usethis::use_data(jhu_csse_county_level_subset, overwrite = TRUE) diff --git a/data-raw/jhu_csse_daily_subset.R b/data-raw/jhu_csse_daily_subset.R index 5db09536..5aae3402 100644 --- a/data-raw/jhu_csse_daily_subset.R +++ b/data-raw/jhu_csse_daily_subset.R @@ -7,8 +7,8 @@ confirmed_7dav_incidence_prop <- covidcast( signals = "confirmed_7dav_incidence_prop", time_type = "day", geo_type = "state", - time_values = epirange(20200601, 20200615), - geo_values = "ca,fl,ny,tx" + time_values = epirange(20200301, 20211231), + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, case_rate_7d_av = value) %>% @@ -19,8 +19,8 @@ deaths_7dav_incidence_prop <- covidcast( signals = "deaths_7dav_incidence_prop", time_type = "day", geo_type = "state", - time_values = epirange(20200601, 20200615), - geo_values = "ca,fl,ny,tx" + time_values = epirange(20200301, 20211231), + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, death_rate_7d_av = value) %>% @@ -31,8 +31,8 @@ confirmed_incidence_num <- covidcast( signals = "confirmed_incidence_num", time_type = "day", geo_type = "state", - time_values = epirange(20200601, 20200615), - geo_values = "ca,fl,ny,tx" + time_values = epirange(20200301, 20211231), + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, cases = value) %>% @@ -43,8 +43,8 @@ confirmed_7dav_incidence_num <- covidcast( signals = "confirmed_7dav_incidence_num", time_type = "day", geo_type = "state", - time_values = epirange(20200601, 20200615), - geo_values = "ca,fl,ny,tx" + time_values = epirange(20200301, 20211231), + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, cases_7d_av = value) %>% diff --git a/data/jhu_csse_county_level_subset.rda b/data/jhu_csse_county_level_subset.rda new file mode 100644 index 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a/man/jhu_csse_daily_subset.Rd +++ b/man/jhu_csse_daily_subset.Rd @@ -5,7 +5,7 @@ \alias{jhu_csse_daily_subset} \title{Subset of JHU daily cases and deaths from California, Florida, Texas, and New York} \format{ -A tibble with 60 rows and 6 variables: +A tibble with 2684 rows and 6 variables: \describe{ \item{geo_value}{the geographic value associated with each row of measurements.} \item{time_value}{the time value associated with each row of measurements.} @@ -34,6 +34,6 @@ jhu_csse_daily_subset This data source of confirmed COVID-19 cases and deaths is based on reports made available by the Center for Systems Science and Engineering at Johns Hopkins University. -This example data ranges from June 1 to June 15, 2020 and is limited to California, Florida, Texas, and New York. +This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to California, Florida, Texas, and New York. } \keyword{datasets} diff --git a/vignettes/aggregation.Rmd b/vignettes/aggregation.Rmd index ed72e5a2..8e6e62c5 100644 --- a/vignettes/aggregation.Rmd +++ b/vignettes/aggregation.Rmd @@ -12,7 +12,7 @@ epidemiological data sets. This vignette demonstrates how to carry out these kinds of tasks with `epi_df` objects. We'll work with county-level reported COVID-19 cases in MA and VT. -```{r, message = FALSE} +```{r, message = FALSE, eval= FALSE, warning= FALSE} library(delphi.epidata) library(covidcast) library(epiprocess) @@ -38,6 +38,11 @@ x <- covidcast( as_epi_df() ``` +```{r, echo=FALSE} +data(jhu_csse_county_level_subset) +x <- jhu_csse_county_level_subset +``` + ## Converting to `tsibble` format For manipulating and wrangling time series data, the @@ -228,4 +233,11 @@ head(xt_filled_month) ## Geographic aggregation -TODO \ No newline at end of file +TODO + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. + diff --git a/vignettes/correlation.Rmd b/vignettes/correlation.Rmd index d2ed5d75..f1fbada5 100644 --- a/vignettes/correlation.Rmd +++ b/vignettes/correlation.Rmd @@ -15,18 +15,21 @@ grouped in a specified way. In this vignette, we'll examine correlations between state-level COVID-19 case and death rates, smoothed using 7-day trailing averages. -```{r, message = FALSE} +```{r, message = FALSE, warning = FALSE} library(delphi.epidata) library(epiprocess) library(dplyr) +``` +The data is fetched with the following query: +```{r, message = FALSE, eval=F} x <- covidcast( data_source = "jhu-csse", signals = "confirmed_7dav_incidence_prop", time_type = "day", geo_type = "state", time_values = epirange(20200301, 20211231), - geo_values = "*" + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, case_rate = value) @@ -37,7 +40,7 @@ y <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200301, 20211231), - geo_values = "*" + geo_values = "ca,fl,ny,tx,ga,pa" ) %>% fetch_tbl() %>% select(geo_value, time_value, death_rate = value) @@ -47,6 +50,18 @@ x <- x %>% as_epi_df() ``` +The data has 4,026 rows and 4 columns. + +```{r, echo=FALSE} +data(jhu_csse_daily_subset) +x <- jhu_csse_daily_subset %>% + select(geo_value, time_value, + case_rate = case_rate_7d_av, + death_rate = death_rate_7d_av) %>% + arrange(geo_value, time_value) %>% + as_epi_df() +``` + ## Correlations grouped by time The `epi_cor()` function operates on an `epi_df` object, and it requires further @@ -158,3 +173,9 @@ z %>% We can see that some pretty clear curvature here in the mean correlation between case and death rates (where the correlations come from grouping by geo value) as a function of lag. The maximum occurs at a lag of somewhere around 18 days. + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. diff --git a/vignettes/growth_rate.Rmd b/vignettes/growth_rate.Rmd index b3d324e0..d2f7d4e8 100644 --- a/vignettes/growth_rate.Rmd +++ b/vignettes/growth_rate.Rmd @@ -14,12 +14,15 @@ estimates the growth rate of a signal. We investigate this functionality in the current vignette, applied to state-level daily reported COVID-19 cases from GA and PA, smoothed using a 7-day trailing average. -```{r, message = FALSE} +```{r, message = FALSE, warning = FALSE} library(delphi.epidata) library(epiprocess) library(dplyr) library(tidyr) +``` +The data is fetched with the following query: +```{r, message = FALSE, eval=F} x <- covidcast( data_source = "jhu-csse", signals = "confirmed_7dav_incidence_num", @@ -34,6 +37,18 @@ x <- covidcast( as_epi_df() ``` +The data has 1,158 rows and 3 columns. + + +```{r, echo=FALSE} +data(jhu_csse_daily_subset) +x <- jhu_csse_daily_subset %>% + select(geo_value, time_value, cases = cases_7d_av) %>% + filter(geo_value %in% c("pa","ga") & time_value >= "2020-06-01") %>% + arrange(geo_value, time_value) %>% + as_epi_df() +``` + ## Growth rate basics The growth rate of a function $f$ defined over a continuously-valued parameter diff --git a/vignettes/slide.Rmd b/vignettes/slide.Rmd index ce90450e..8bb11eab 100644 --- a/vignettes/slide.Rmd +++ b/vignettes/slide.Rmd @@ -29,11 +29,14 @@ FL, NY, and TX (note: here we're using new, not cumulative cases) using the [`delphi.epidata`](https://github.com/cmu-delphi/delphi-epidata-r) package, and then convert this to `epi_df` format. -```{r, message = FALSE} +```{r, message = FALSE, warning=FALSE} library(delphi.epidata) library(epiprocess) library(dplyr) +``` +The data is fetched with the following query: +```{r, message = FALSE, eval=F} x <- covidcast( data_source = "jhu-csse", signals = "confirmed_incidence_num", @@ -48,6 +51,17 @@ x <- covidcast( as_epi_df() ``` +The data has 2,684 rows and 3 columns. + +```{r, echo=FALSE} +data(jhu_csse_daily_subset) +x <- jhu_csse_daily_subset %>% + select(geo_value, time_value, cases) %>% + arrange(geo_value, time_value) %>% + as_epi_df() +``` + + ## Slide with a formula We first demonstrate how to apply a 7-day trailing average to the daily cases in @@ -268,3 +282,10 @@ version-aware sense (for the computation at each reference time $t$, it uses only data that would have been available as of $t$). We will revisit this example in the [archive vignette](https://cmu-delphi.github.io/epiprocess/articles/archive.html). + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. + From 6220f9e316422a851fade87908e56c59ee43c7b8 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Mon, 23 May 2022 15:58:28 -0700 Subject: [PATCH 39/41] changed all vignette datasets --- R/data.R | 29 +++++++++++++-- data-raw/archive_cases_dv_subset.R | 8 ++--- data/archive_cases_dv_subset.rda | Bin 42591 -> 744542 bytes data/jhu_csse_county_level_subset.rda | Bin 20370 -> 20371 bytes man/archive_cases_dv_subset.Rd | 4 +-- man/jhu_csse_county_level_subset.Rd | 38 ++++++++++++++++++++ man/jhu_csse_daily_subset.Rd | 6 ++-- vignettes/advanced.Rmd | 28 ++++++++++++--- vignettes/aggregation.Rmd | 15 +++++--- vignettes/archive.Rmd | 50 ++++++++++++++++++++------ vignettes/growth_rate.Rmd | 6 ++++ vignettes/outliers.Rmd | 31 +++++++++++++--- 12 files changed, 178 insertions(+), 37 deletions(-) create mode 100644 man/jhu_csse_county_level_subset.Rd diff --git a/R/data.R b/R/data.R index d6def673..2edef89b 100644 --- a/R/data.R +++ b/R/data.R @@ -31,9 +31,9 @@ #' provided to us by health system partners, and also contains confirmed #' COVID-19 cases based on reports made available by the Center for #' Systems Science and Engineering at Johns Hopkins University. -#' This example data ranges from June 1 to June 15, 2020, and is also limited to California, Florida, Texas, and New York. +#' This example data ranges from June 1, 2020 to Dec 1, 2021, and is also limited to California, Florida, Texas, and New York. #' -#' @format An `epi_archive` data format. The data table DT has 160 rows and 5 columns: +#' @format An `epi_archive` data format. The data table DT has 129,638 rows and 5 columns: #' \describe{ #' \item{geo_value}{the geographic value associated with each row of measurements.} #' \item{time_value}{the time value associated with each row of measurements.} @@ -78,5 +78,28 @@ #' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. "incidence_num_outlier_example" -#' TO-DO +#' Subset of JHU daily cases from counties in Massachusetts and Vermont +#' +#' This data source of confirmed COVID-19 cases and deaths +#' is based on reports made available by the Center for +#' Systems Science and Engineering at Johns Hopkins University. +#' This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to Massachusetts and Vermont. +#' +#' @format A tibble with 16,212 rows and 5 variables: +#' \describe{ +#' \item{geo_value}{the geographic value associated with each row of measurements.} +#' \item{time_value}{the time value associated with each row of measurements.} +#' \item{cases}{Number of new confirmed COVID-19 cases, daily} +#' \item{county_name}{the name of the county} +#' \item{state_name}{the full name of the state} +#' } +#' @source This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +#' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +#' Copyright Johns Hopkins University 2020. +#' +#' Modifications: +#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +#' * Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. + "jhu_csse_county_level_subset" \ No newline at end of file diff --git a/data-raw/archive_cases_dv_subset.R b/data-raw/archive_cases_dv_subset.R index 4818eba4..b1c1071c 100644 --- a/data-raw/archive_cases_dv_subset.R +++ b/data-raw/archive_cases_dv_subset.R @@ -8,9 +8,9 @@ archive_cases_dv_subset <- covidcast( signals = "smoothed_adj_cli", time_type = "day", geo_type = "state", - time_value = epirange(20200601, 20200615), + time_value = epirange(20200601, 20211201), geo_values = "ca,fl,ny,tx", - issues = epirange(20200601, 20200615) + issues = epirange(20200601, 20211201) ) %>% fetch_tbl() %>% select(geo_value, time_value, version = issue, percent_cli = value) %>% @@ -21,9 +21,9 @@ case_rate_subset <- covidcast( signals = "confirmed_7dav_incidence_prop", time_type = "day", geo_type = "state", - time_value = epirange(20200601, 20200615), + time_value = epirange(20200601, 20211201), geo_values = "ca,fl,ny,tx", - issues = epirange(20200601, 20200615) + issues = epirange(20200601, 20211201) ) %>% fetch_tbl() %>% select(geo_value, time_value, version = issue, case_rate_7d_av = value) %>% diff --git a/data/archive_cases_dv_subset.rda b/data/archive_cases_dv_subset.rda index e3c43eb653fe7eb11f9c3cd8bec75863b3d806e5..8dd7c12683988bf4ff73a4b94fb7fc43fd17edf1 100644 GIT binary patch literal 744542 zcmZ^J2VBx$_b`rJi4#jj%{{Q?B6liIT!7%V)YJr_a#oh5sfgrWxf2I6#9WZ0VUAKt zQ&UrHnwpty+hs5Id!Fb0zt8*m-|ywzd(J)gtb4hh`xS@4XbU6z09~H|uh_4#+s^5p zPu)B*k_r$w0T2d&>~6k%sxD*HCg2YU6=;At%NE-=cnS~!%BH4aN~X%D6N;K8wXP35 zJxpthJ(P(W#azFYqGU}CLuwn+3GGVid)sp~Z86}c#;ZJ?Pzae;qm{8O=w{np)1V{P zf)Gf(Qy@qfV7IO*sM%A9wnw>?r-bD+=(}esC?M4X96*kHx&VAGF8~08)Z7C5UfOYi 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-5,7 +5,7 @@ \alias{archive_cases_dv_subset} \title{Subset of daily doctor visits and cases from California, Florida, Texas, and New York in archive format} \format{ -An \code{epi_archive} data format. The data table DT has 160 rows and 5 columns: +An \code{epi_archive} data format. The data table DT has 129,638 rows and 5 columns: \describe{ \item{geo_value}{the geographic value associated with each row of measurements.} \item{time_value}{the time value associated with each row of measurements.} @@ -34,6 +34,6 @@ This data source is based on information about outpatient visits, provided to us by health system partners, and also contains confirmed COVID-19 cases based on reports made available by the Center for Systems Science and Engineering at Johns Hopkins University. -This example data ranges from June 1 to June 15, 2020, and is also limited to California, Florida, Texas, and New York. +This example data ranges from June 1, 2020 to Dec 1, 2021, and is also limited to California, Florida, Texas, and New York. } \keyword{datasets} diff --git a/man/jhu_csse_county_level_subset.Rd b/man/jhu_csse_county_level_subset.Rd new file mode 100644 index 00000000..6ab47a12 --- /dev/null +++ b/man/jhu_csse_county_level_subset.Rd @@ -0,0 +1,38 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{jhu_csse_county_level_subset} +\alias{jhu_csse_county_level_subset} +\title{Subset of JHU daily cases from counties in Massachusetts and Vermont} +\format{ +A tibble with 16,212 rows and 5 variables: +\describe{ +\item{geo_value}{the geographic value associated with each row of measurements.} +\item{time_value}{the time value associated with each row of measurements.} +\item{cases}{Number of new confirmed COVID-19 cases, daily} +\item{county_name}{the name of the county} +\item{state_name}{the full name of the state} +} +} +\source{ +This object contains a modified part of the \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University} as \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{republished in the COVIDcast Epidata API}. This data set is licensed under the terms of the +\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license} +by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. +Copyright Johns Hopkins University 2020. + +Modifications: +\itemize{ +\item \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: These signals are taken directly from the JHU CSSE \href{https://github.com/CSSEGISandData/COVID-19}{COVID-19 GitHub repository} without changes. The 7-day average signals are computed by Delphi by calculating moving averages of the preceding 7 days, so the signal for June 7 is the average of the underlying data for June 1 through 7, inclusive. +\item Furthermore, the data has been limited to a very small number of rows, the signal names slightly altered, and formatted into a tibble. +} +} +\usage{ +jhu_csse_county_level_subset +} +\description{ +This data source of confirmed COVID-19 cases and deaths +is based on reports made available by the Center for +Systems Science and Engineering at Johns Hopkins University. +This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to Massachusetts and Vermont. +} +\keyword{datasets} diff --git a/man/jhu_csse_daily_subset.Rd b/man/jhu_csse_daily_subset.Rd index df5b27ce..20c4d909 100644 --- a/man/jhu_csse_daily_subset.Rd +++ b/man/jhu_csse_daily_subset.Rd @@ -3,9 +3,9 @@ \docType{data} \name{jhu_csse_daily_subset} \alias{jhu_csse_daily_subset} -\title{Subset of JHU daily cases and deaths from California, Florida, Texas, and New York} +\title{Subset of JHU daily cases and deaths from California, Florida, Texas, New York, Georgia, and Pennsylvania} \format{ -A tibble with 2684 rows and 6 variables: +A tibble with 4026 rows and 6 variables: \describe{ \item{geo_value}{the geographic value associated with each row of measurements.} \item{time_value}{the time value associated with each row of measurements.} @@ -34,6 +34,6 @@ jhu_csse_daily_subset This data source of confirmed COVID-19 cases and deaths is based on reports made available by the Center for Systems Science and Engineering at Johns Hopkins University. -This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to California, Florida, Texas, and New York. +This example data ranges from Mar 1, 2020 to Dec 31, 2021, and is limited to California, Florida, Texas, New York, Georgia, and Pennsylvania. } \keyword{datasets} diff --git a/vignettes/advanced.Rmd b/vignettes/advanced.Rmd index 5d6855f1..b9c082cb 100644 --- a/vignettes/advanced.Rmd +++ b/vignettes/advanced.Rmd @@ -191,7 +191,7 @@ vignette](https://cmu-delphi.github.io/epiprocess/articles/slide.html) in order to demonstrate the last point in a more realistic setting. First, we fetch the versioned data and build the archive. -```{r, message = FALSE, warning = FALSE} +```{r, message = FALSE, warning = FALSE, eval =FALSE} library(delphi.epidata) library(data.table) library(ggplot2) @@ -227,13 +227,24 @@ x <- y1 %>% epix_merge(x, y2 %>% select(geo_value, time_value, version = issue, - case_rate = value + case_rate_7d_av = value ) %>% as_epi_archive(), all = TRUE ) ``` +```{r, message = FALSE, warning = FALSE, echo =FALSE} +library(data.table) +library(ggplot2) +theme_set(theme_bw()) + +x <- archive_cases_dv_subset$DT %>% + filter(geo_value %in% c("ca","fl")) %>% + as_epi_archive() + +``` + Next, we extend the ARX function to handle multiple geo values, since in the present case, we will not be grouping by geo value and each slide computation will be run on multiple geo values at once. Note that, because `epix_slide()` @@ -341,7 +352,7 @@ fc_time_values <- seq(as.Date("2020-08-01"), k_week_ahead <- function(x, ahead = 7, as_of = TRUE) { if (as_of) { x %>% - epix_slide(fc = prob_arx(percent_cli, case_rate, geo_value, time_value, + epix_slide(fc = prob_arx(percent_cli, case_rate_7d_av, geo_value, time_value, args = prob_arx_args(ahead = ahead)), n = 120, ref_time_values = fc_time_values) %>% mutate(target_date = time_value + ahead, as_of = TRUE, @@ -349,7 +360,7 @@ k_week_ahead <- function(x, ahead = 7, as_of = TRUE) { } else { x_latest %>% - epi_slide(fc = prob_arx(percent_cli, case_rate, geo_value, time_value, + epi_slide(fc = prob_arx(percent_cli, case_rate_7d_av, geo_value, time_value, args = prob_arx_args(ahead = ahead)), n = 120, ref_time_values = fc_time_values) %>% mutate(target_date = time_value + ahead, as_of = FALSE) @@ -369,7 +380,7 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), # Plot them, on top of latest COVID-19 case rates ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + - geom_line(data = x_latest, aes(x = time_value, y = case_rate), + geom_line(data = x_latest, aes(x = time_value, y = case_rate_7d_av), inherit.aes = FALSE, color = "gray50") + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + @@ -385,3 +396,10 @@ compared to the ones from the archive vignette, which come from training a separate ARX model on each state. As in the archive vignette, we can see a difference between version-aware (right column) and -unaware (left column) forecasting, as well. + + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidatab Doctor's Visit API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. \ No newline at end of file diff --git a/vignettes/aggregation.Rmd b/vignettes/aggregation.Rmd index 8e6e62c5..f1d32616 100644 --- a/vignettes/aggregation.Rmd +++ b/vignettes/aggregation.Rmd @@ -23,7 +23,7 @@ y <- covidcast::county_census %>% filter(STNAME %in% c("Massachusetts", "Vermont"), STNAME != CTYNAME) %>% select(geo_value = FIPS, county_name = CTYNAME, state_name = STNAME) -# Fetch only counties from VT and NH, then append names columns as well +# Fetch only counties from Massachusetts and Vermont, then append names columns as well x <- covidcast( data_source = "jhu-csse", signals = "confirmed_incidence_num", @@ -38,7 +38,14 @@ x <- covidcast( as_epi_df() ``` -```{r, echo=FALSE} +The data contains 16,212 rows and 5 columns. + +```{r, echo=FALSE, warning=FALSE, message=FALSE} +library(delphi.epidata) +library(covidcast) +library(epiprocess) +library(dplyr) + data(jhu_csse_county_level_subset) x <- jhu_csse_county_level_subset ``` @@ -152,7 +159,6 @@ second call to `tidyr::fill()`.) ```{r} fill_gaps(xt, cases = 0) %>% - arrange(geo_value, time_value) %>% head() ``` @@ -162,8 +168,7 @@ went back to June 6, 2020. By setting `.full = TRUE`, we can at zero-fill over the entire span of the observed (censored) data. ```{r} -xt_filled <- fill_gaps(xt, cases = 0, .full = TRUE) %>% - arrange(geo_value, time_value) +xt_filled <- fill_gaps(xt, cases = 0, .full = TRUE) head(xt_filled) ``` diff --git a/vignettes/archive.Rmd b/vignettes/archive.Rmd index 120e6ad5..0e399357 100644 --- a/vignettes/archive.Rmd +++ b/vignettes/archive.Rmd @@ -25,7 +25,7 @@ signal is subject to very heavy and regular revision; you can read more about it on its [API documentation page](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html). -```{r, message = FALSE, warning = FALSE} +```{r, message = FALSE, warning = FALSE, eval=FALSE} library(delphi.epidata) library(epiprocess) library(data.table) @@ -37,11 +37,17 @@ dv <- covidcast( time_type = "day", geo_type = "state", time_values = epirange(20200601, 20211201), - geo_values = "ca,fl", + geo_values = "ca,fl,ny,tx", issues = epirange(20200601, 20211201) ) %>% fetch_tbl() -colnames(dv) +``` + +```{r, echo=FALSE, message=FALSE, warning=FALSE} +library(delphi.epidata) +library(epiprocess) +library(data.table) +library(dplyr) ``` ## Getting data into `epi_archive` format @@ -62,7 +68,7 @@ As we can see from the above, the data frame returned by format, with `issue` playing the role of `version`. We can now use `as_epi_archive()` to bring it into `epi_archive` format. -```{r} +```{r, eval=FALSE} x <- dv %>% select(geo_value, time_value, version = issue, percent_cli = value) %>% as_epi_archive() @@ -71,6 +77,15 @@ class(x) print(x) ``` +```{r, echo=FALSE, message=FALSE, warning=FALSE} +x <- archive_cases_dv_subset$DT %>% + select(geo_value, time_value, version , percent_cli) %>% + as_epi_archive() + +class(x) +print(x) +``` + An `epi_archive` is special kind of class called an R6 class. Its primary field is a data table `DT`, which is of class `data.table` (from the `data.table` package), and has columns `geo_value`, `time_value`, `version`, as well as any @@ -220,18 +235,18 @@ Because the original data archives are stored in LOCF (last observation carried forward) format in the first place, it generally makes sense to perform `NA` filling after merging using LOCF. Therefore `locf = TRUE` is the default. -```{r, message = FALSE, warning = FALSE} +```{r, message = FALSE, warning = FALSE,eval=FALSE} y <- covidcast( data_source = "jhu-csse", signals = "confirmed_7dav_incidence_prop", time_type = "day", geo_type = "state", time_value = epirange(20200601, 20211201), - geo_values = "ca,fl", + geo_values = "ca,fl,ny,tx", issues = epirange(20200601, 20211201) ) %>% fetch_tbl() %>% - select(geo_value, time_value, version = issue, case_rate = value) %>% + select(geo_value, time_value, version = issue, case_rate_7d_av = value) %>% as_epi_archive() epix_merge(x, y, all = TRUE) @@ -239,6 +254,12 @@ print(x) head(x$DT) ``` +```{r, echo=FALSE, message=FALSE, warning=FALSE} +x <- archive_cases_dv_subset +print(x) +head(x$DT) +``` + Importantly, as we can see, the way `epix_merge()` works is that it **overwrites** the data table in the first `epi_archive` object `x` by the merged data table. @@ -321,7 +342,7 @@ fc_time_values <- seq(as.Date("2020-08-01"), as.Date("2021-12-01"), by = "1 month") -z <- epix_slide(x, fc = prob_arx(x = percent_cli, y = case_rate), n = 120, +z <- epix_slide(x, fc = prob_arx(x = percent_cli, y = case_rate_7d_av), n = 120, ref_time_values = fc_time_values, group_by = geo_value) head(z, 10) @@ -351,14 +372,14 @@ x_latest <- epix_as_of(x, max_version = max(x$DT$version)) k_week_ahead <- function(x, ahead = 7, as_of = TRUE) { if (as_of) { x %>% - epix_slide(fc = prob_arx(percent_cli, case_rate, ahead = ahead), n = 120, + epix_slide(fc = prob_arx(percent_cli, case_rate_7d_av, ahead = ahead), n = 120, ref_time_values = fc_time_values, group_by = geo_value) %>% mutate(target_date = time_value + ahead, as_of = TRUE) } else { x_latest %>% group_by(geo_value) %>% - epi_slide(fc = prob_arx(percent_cli, case_rate, ahead = ahead), n = 120, + epi_slide(fc = prob_arx(percent_cli, case_rate_7d_av, ahead = ahead), n = 120, ref_time_values = fc_time_values) %>% mutate(target_date = time_value + ahead, as_of = FALSE) } @@ -377,7 +398,7 @@ fc <- bind_rows(k_week_ahead(x, ahead = 7, as_of = TRUE), # Plot them, on top of latest COVID-19 case rates ggplot(fc, aes(x = target_date, group = time_value, fill = as_of)) + geom_ribbon(aes(ymin = fc_lower, ymax = fc_upper), alpha = 0.4) + - geom_line(data = x_latest, aes(x = time_value, y = case_rate), + geom_line(data = x_latest, aes(x = time_value, y = case_rate_7d_av), inherit.aes = FALSE, color = "gray50") + geom_line(aes(y = fc_point)) + geom_point(aes(y = fc_point), size = 0.5) + geom_vline(aes(xintercept = time_value), linetype = 2, alpha = 0.5) + @@ -406,3 +427,10 @@ off the data structures and functionality in the current package, is the place to look for more robust forecasting methodology. The forecasters that appear in the vignettes in the current package are only meant to demo the slide functionality with some of the most basic forecasting methodology possible. + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidatab Doctor's Visit API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. + diff --git a/vignettes/growth_rate.Rmd b/vignettes/growth_rate.Rmd index d2f7d4e8..707243c1 100644 --- a/vignettes/growth_rate.Rmd +++ b/vignettes/growth_rate.Rmd @@ -290,3 +290,9 @@ curve. + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. diff --git a/vignettes/outliers.Rmd b/vignettes/outliers.Rmd index 0e1a1be2..9be62556 100644 --- a/vignettes/outliers.Rmd +++ b/vignettes/outliers.Rmd @@ -14,13 +14,11 @@ so that you can define your own outlier detection and correction routines and apply them to `epi_df` objects. We'll demonstrate this using state-level daily reported COVID-19 case counts from FL and NJ. -```{r, message = FALSE, fig.width = 8, fig.height = 7} +```{r, message = FALSE, eval= FALSE} library(delphi.epidata) library(epiprocess) library(dplyr) library(tidyr) -library(ggplot2) -theme_set(theme_bw()) x <- covidcast( data_source = "jhu-csse", @@ -34,6 +32,23 @@ x <- covidcast( fetch_tbl() %>% select(geo_value, time_value, cases = value) %>% as_epi_df() +``` + +The dataset has 730 rows and 3 columns. + +```{r, echo=FALSE, warning=FALSE, message=FALSE} +library(delphi.epidata) +library(epiprocess) +library(dplyr) +library(tidyr) + +data(incidence_num_outlier_example) +x <- incidence_num_outlier_example +``` + +```{r, fig.width = 8, fig.height = 7, warning=FALSE,message=FALSE} +library(ggplot2) +theme_set(theme_bw()) ggplot(x, aes(x = time_value, y = cases)) + geom_line() + @@ -190,4 +205,12 @@ ggplot(y, aes(x = time_value)) + ``` More advanced correction functionality will be coming at some point in the -future. \ No newline at end of file +future. + + +## Attribution +This document contains dataset that is a modified part of the [COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19) as [republished in the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html). This data set is licensed under the terms of the [Creative Commons Attribution 4.0 International license](https://creativecommons.org/licenses/by/4.0/) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020. + +[From the COVIDcast Epidata API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html): + These signals are taken directly from the JHU CSSE [COVID-19 GitHub repository](https://github.com/CSSEGISandData/COVID-19) without changes. + From d8cf12485622e95038ec8c56197af6eba3004658 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Mon, 23 May 2022 22:06:19 -0700 Subject: [PATCH 40/41] change example to match change in internal data --- R/methods-epi_archive.R | 2 +- man/epix_merge.Rd | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/R/methods-epi_archive.R b/R/methods-epi_archive.R index d005d6ca..eb1544f1 100644 --- a/R/methods-epi_archive.R +++ b/R/methods-epi_archive.R @@ -77,7 +77,7 @@ epix_as_of = function(x, max_version, min_time_value = -Inf) { #' @examples #' # create two example epi_archive datasets #' x <- archive_cases_dv_subset$DT %>% -#' dplyr::select(geo_value,time_value,version,case_rate) %>% +#' dplyr::select(geo_value,time_value,version,case_rate_7d_av) %>% #' as_epi_archive() #' y <- archive_cases_dv_subset$DT %>% #' dplyr::select(geo_value,time_value,version,percent_cli) %>% diff --git a/man/epix_merge.Rd b/man/epix_merge.Rd index e13c14c4..781ef6fe 100644 --- a/man/epix_merge.Rd +++ b/man/epix_merge.Rd @@ -44,7 +44,7 @@ is equivalent to:\preformatted{x$merge(y) \examples{ # create two example epi_archive datasets x <- archive_cases_dv_subset$DT \%>\% - dplyr::select(geo_value,time_value,version,case_rate) \%>\% + dplyr::select(geo_value,time_value,version,case_rate_7d_av) \%>\% as_epi_archive() y <- archive_cases_dv_subset$DT \%>\% dplyr::select(geo_value,time_value,version,percent_cli) \%>\% From 6c8f2524c9a114f4dda20741d6112a13d91b01f2 Mon Sep 17 00:00:00 2001 From: ChloeYou Date: Mon, 23 May 2022 22:28:18 -0700 Subject: [PATCH 41/41] change license back to MIT --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index dd573870..ceb5b29c 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -15,7 +15,7 @@ Authors@R: c( Description: This package introduces a common data structure for epidemiological data sets measured over space and time, and offers associated utilities to perform basic signal processing tasks. -License: CC BY 4.0 +License: MIT + file LICENSE Imports: data.table, dplyr,

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