lint: increase lintr happiness

Author: dshemetov

R/archive.R

@@ -1,10 +1,10 @@
 # We use special features of data.table's `[`. The data.table package has a
 # compatibility feature that disables some/all of these features if it thinks we
 # might expect `data.frame`-compatible behavior instead. We can signal that we
-# want the special behavior via `.datatable.aware = TRUE` or by importing any
+# want the special behavior via `.datatable_aware = TRUE` or by importing any
 # `data.table` package member. Do both to prevent surprises if we decide to use
 # `data.table::` everywhere and not importing things.
-.datatable.aware <- TRUE
+.datatable_aware <- TRUE
 
 #' Validate a version bound arg
 #'
@@ -79,6 +79,7 @@ max_version_with_row_in <- function(x) {
       version_bound <- max(version_col)
     }
   }
+  version_bound
 }
 
 #' Get the next possible value greater than `x` of the same type
@@ -343,7 +344,7 @@ epi_archive <-
         # then the call to as.data.table() will fail to set keys, so we
         # need to check this, then do it manually if needed
         key_vars <- c("geo_value", "time_value", other_keys, "version")
-        DT <- as.data.table(x, key = key_vars)
+        DT <- as.data.table(x, key = key_vars) # nolint: object_name_linter
         if (!identical(key_vars, key(DT))) setkeyv(DT, cols = key_vars)
 
         maybe_first_duplicate_key_row_index <- anyDuplicated(DT, by = key(DT))
@@ -381,7 +382,7 @@ epi_archive <-
         # Runs compactify on data frame
         if (is.null(compactify) || compactify == TRUE) {
           elim <- keep_locf(DT)
-          DT <- rm_locf(DT)
+          DT <- rm_locf(DT) # nolint: object_name_linter
         } else {
           # Create empty data frame for nrow(elim) to be 0
           elim <- tibble::tibble()
@@ -543,7 +544,7 @@ epi_archive <-
         validate_version_bound(fill_versions_end, self$DT, na_ok = FALSE)
         how <- arg_match(how)
         if (self$versions_end < fill_versions_end) {
-          new_DT <- switch(how,
+          new_DT <- switch(how, # nolint: object_name_linter
             "na" = {
               # old DT + a version consisting of all NA observations
               # immediately after the last currently/actually-observed
@@ -567,7 +568,7 @@ epi_archive <-
               if (identical(address(self$DT), address(nonversion_key_vals_ever_recorded))) {
                 nonversion_key_vals_ever_recorded <- copy(nonversion_key_vals_ever_recorded)
               }
-              next_version_DT <- nonversion_key_vals_ever_recorded[
+              next_version_DT <- nonversion_key_vals_ever_recorded[ # nolint: object_name_linter
                 , version := next_version_tag
               ][
                 # this makes the class of these columns logical (`NA` is a

R/autoplot.R

@@ -112,14 +112,14 @@ autoplot.epi_df <- function(
     dplyr::mutate(
       .colours = switch(.color_by,
         all_keys = interaction(!!!all_keys, sep = "/"),
-        geo_value = geo_value,
+        geo_value = .data$geo_value,
         other_keys = interaction(!!!other_keys, sep = "/"),
         all = interaction(!!!all_avail, sep = "/"),
         NULL
       ),
       .facets = switch(.facet_by,
         all_keys = interaction(!!!all_keys, sep = "/"),
-        geo_value = as.factor(geo_value),
+        geo_value = as.factor(.data$geo_value),
         other_keys = interaction(!!!other_keys, sep = "/"),
         all = interaction(!!!all_avail, sep = "/"),
         NULL
@@ -130,10 +130,10 @@ autoplot.epi_df <- function(
     n_facets <- nlevels(object$.facets)
     if (n_facets > .max_facets) {
       top_n <- levels(as.factor(object$.facets))[seq_len(.max_facets)]
-      object <- dplyr::filter(object, .facets %in% top_n) %>%
-        dplyr::mutate(.facets = droplevels(.facets))
+      object <- dplyr::filter(object, .data$.facets %in% top_n) %>%
+        dplyr::mutate(.facets = droplevels(.data$.facets))
       if (".colours" %in% names(object)) {
-        object <- dplyr::mutate(object, .colours = droplevels(.colours))
+        object <- dplyr::mutate(object, .colours = droplevels(.data$.colours))
       }
     }
   }

R/correlation.R

@@ -75,7 +75,7 @@
 #'   cor_by = geo_value,
 #'   dt1 = -2
 #' )
-epi_cor <- function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value,
+epi_cor <- function(x, var1, var2, dt1 = 0, dt2 = 0, shift_by = geo_value, # nolint: object_usage_linter
                     cor_by = geo_value, use = "na.or.complete",
                     method = c("pearson", "kendall", "spearman")) {
   assert_class(x, "epi_df")

R/data.R

@@ -20,12 +20,15 @@
 #'       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.
+#'   \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
@@ -54,19 +57,34 @@
 #'   \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{percent_cli}{percentage of doctor’s visits with CLI (COVID-like illness) computed from medical insurance claims}
-#'   \item{case_rate_7d_av}{7-day average signal of number of new confirmed deaths due to COVID-19 per 100,000 population, daily}
+#'   \item{percent_cli}{percentage of doctor’s visits with CLI (COVID-like
+#'   illness) computed from medical insurance claims}
+#'   \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 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.
+#' 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.
 #'
 #' Modifications:
-#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{From the COVIDcast Doctor Visits API}: The signal `percent_cli` is taken directly from the API without changes.
-#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From the COVIDcast Epidata API}: `case_rate_7d_av` signal was computed by Delphi from the original JHU-CSSE data 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 is a subset of the full dataset, the signal names slightly altered, and formatted into a tibble.
+#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/doctor-visits.html}{From
+#'   the COVIDcast Doctor Visits API}: The signal `percent_cli` is taken
+#'   directly from the API without changes.
+#' * \href{https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/jhu-csse.html}{From
+#'   the COVIDcast Epidata API}: `case_rate_7d_av` signal was computed by Delphi
+#'   from the original JHU-CSSE data 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 is a subset of the full dataset, the signal names
+#'   slightly altered, and formatted into a tibble.
 #'
 #' @export
 "archive_cases_dv_subset"
@@ -128,19 +146,19 @@ some_package_is_being_unregistered <- function(parent_n = 0L) {
 #'
 #' @noRd
 delayed_assign_with_unregister_awareness <- function(x, value,
-                                                     eval.env = rlang::caller_env(),
-                                                     assign.env = rlang::caller_env()) {
-  value_quosure <- rlang::as_quosure(rlang::enexpr(value), eval.env)
+                                                     eval_env = rlang::caller_env(),
+                                                     assign_env = rlang::caller_env()) {
+  value_quosure <- rlang::as_quosure(rlang::enexpr(value), eval_env)
   this_env <- environment()
-  delayedAssign(x, eval.env = this_env, assign.env = assign.env, value = {
+  delayedAssign(x, eval.env = this_env, assign.env = assign_env, value = {
     if (some_package_is_being_unregistered()) {
       withCallingHandlers(
         # `rlang::eval_tidy(value_quosure)` is shorter and would sort of work,
         # but doesn't give the same `ls`, `rm`, and top-level `<-` behavior as
         # we'd have with `delayedAssign`; it doesn't seem to actually evaluate
         # quosure's expr in the quosure's env. Using `rlang::eval_bare` instead
         # seems to do the trick. (We also could have just used a `value_expr`
-        # and `eval.env` together rather than introducing `value_quosure` at
+        # and `eval_env` together rather than introducing `value_quosure` at
         # all.)
         rlang::eval_bare(rlang::quo_get_expr(value_quosure), rlang::quo_get_env(value_quosure)),
         error = function(err) {
@@ -193,7 +211,10 @@ delayed_assign_with_unregister_awareness <- function(x, value,
 # binding may have been created with the same name as the package promise, and
 # this binding will stick around even when the package is reloaded, and will
 # need to be `rm`-d to easily access the refreshed package promise.
-delayed_assign_with_unregister_awareness("archive_cases_dv_subset", as_epi_archive(archive_cases_dv_subset_dt, compactify = FALSE))
+delayed_assign_with_unregister_awareness(
+  "archive_cases_dv_subset",
+  as_epi_archive(archive_cases_dv_subset_dt, compactify = FALSE)
+)
 
 #' Subset of JHU daily cases from California and Florida
 #'
@@ -210,15 +231,24 @@ delayed_assign_with_unregister_awareness("archive_cases_dv_subset", as_epi_archi
 #'   \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.
+#' @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.
+#' * \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"
 
 #' Subset of JHU daily cases from counties in Massachusetts and Vermont
@@ -237,12 +267,25 @@ delayed_assign_with_unregister_awareness("archive_cases_dv_subset", as_epi_archi
 #'   \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
+#' @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.
+#' * \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"

R/epi_df.R

@@ -134,20 +134,20 @@ new_epi_df <- function(x = tibble::tibble(), geo_type, time_type, as_of,
   # If as_of is missing, then try to guess it
   if (missing(as_of)) {
     # First check the metadata for an as_of field
-    if ("metadata" %in% names(attributes(x)) &&
-      "as_of" %in% names(attributes(x)$metadata)) {
+    if (
+      "metadata" %in% names(attributes(x)) &&
+        "as_of" %in% names(attributes(x)$metadata)
+    ) {
       as_of <- attributes(x)$metadata$as_of
-    }
-
-    # Next check for as_of, issue, or version columns
-    else if ("as_of" %in% names(x)) {
+    } else if ("as_of" %in% names(x)) {
+      # Next check for as_of, issue, or version columns
       as_of <- max(x$as_of)
     } else if ("issue" %in% names(x)) {
       as_of <- max(x$issue)
     } else if ("version" %in% names(x)) {
       as_of <- max(x$version)
-    } # If we got here then we failed
-    else {
+    } else {
+      # If we got here then we failed
       as_of <- Sys.time()
     } # Use the current day-time
   }