diff --git a/DESCRIPTION b/DESCRIPTION
index 13f82df..9076b29 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -51,7 +51,7 @@ Suggests:
     tidyr,
     roxygen2,
     usethis,
-    testthat,
+    testthat (>= 3.0.0),
     rcmdcheck,
     httptest
 VignetteBuilder:
@@ -63,3 +63,4 @@ LazyData: true
 Remotes:
     hubverse-org/hubData
 BugReports: https://github.com/CDCgov/forecasttools/issues
+Config/testthat/edition: 3
diff --git a/NAMESPACE b/NAMESPACE
index 741e9c1..0d2c123 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -18,10 +18,10 @@ export(nhsn_soda_query)
 export(nullable_comparison)
 export(pivot_hubverse_quantiles_wider)
 export(plot_coverage_by_date)
-export(plot_forecast_quantiles)
+export(plot_hubverse_file_quantiles)
+export(plot_hubverse_loc_quant_ts)
 export(plot_hubverse_pointintervals)
-export(plot_hubverse_quantiles)
-export(plot_hubverse_quantiles_loc)
+export(plot_quantile_timeseries)
 export(plots_to_pdf)
 export(pull_nhsn)
 export(quantile_table_to_scoreable)
diff --git a/R/plot_hubverse_timeseries.R b/R/plot_hubverse_timeseries.R
new file mode 100644
index 0000000..34b4a26
--- /dev/null
+++ b/R/plot_hubverse_timeseries.R
@@ -0,0 +1,311 @@
+#' Plot a hubverse formatted quantile forecast timeseries
+#' for a single location.
+#'
+#' Given a tibble of data properly formatted
+#' for a hubverse schema forecast hub submission,
+#' plot a timeseries of quantile predictions for
+#' a given location.
+#'
+#' @param location location to plot
+#' @param forecast_data hubverse format quantile
+#' forecast data, as a [`tibble`][tibble::tibble].
+#' @param observed_data observed data,
+#' as a [`tibble`][tibble::tibble].
+#' @param location_format format of the provided location.
+#' Permitted formats are `"abbr"` (state/territory
+#' or nation two letter USPS abbreviation), `"hub"` (
+#' legacy 2-digit FIPS code for states and territories, `US`
+#' for the USA as a whole), and `"long_name"` (full English
+#' jurisdiction names; not recommended). Default `"abbr"`.
+#' @param y_transform axis transform passed as the
+#' `transform` argument to [ggplot2::scale_y_continuous()].
+#' Default `"log10"`.
+#' @param linewidth `linewidth` parameter passed to
+#' [ggplot2::geom_line()]. Default `2`.
+#' @param pointsize `size` parameter passed to
+#' [ggplot2::geom_point()]. Default `4`.
+#' @param forecast_linecolor `color` parameter passed to
+#' [ggplot2::geom_line()] for plotting forecasts.
+#' Default `"darkblue"`.
+#' @param forecast_pointcolor `color` parameter passed to
+#' [ggplot2::geom_point()] for plotting forecasts.
+#' Default `"darkblue"`.
+#' @param obs_linecolor `color` parameter passed to
+#' [ggplot2::geom_line()] for plotting observed data.
+#' Default `"black"`.
+#' @param obs_pointcolor `color` parameter passed to
+#' [ggplot2::geom_point()] for plotting observed data.
+#' Default `"black"`.
+#' @param target_name Name of the forecast target,
+#' for labeling the plot y-axis. Default `NULL`,
+#' in which case a value from the `target` column
+#' in `forecast_data` will be used.
+#' @param autotitle Boolean. Generate an automatic
+#' title for the plot from the location name
+#' and reference date? Default `TRUE`.
+#' @return the plot as a ggplot object
+#' @export
+plot_hubverse_loc_quant_ts <- function(location,
+                                       forecast_data,
+                                       observed_data,
+                                       location_format = "abbr",
+                                       y_transform = "log10",
+                                       linewidth = 2,
+                                       pointsize = 4,
+                                       forecast_linecolor = "darkblue",
+                                       forecast_pointcolor = "darkblue",
+                                       obs_linecolor = "black",
+                                       obs_pointcolor = "black",
+                                       target_name = NULL,
+                                       autotitle = TRUE) {
+  loc_table <- location_lookup(location, location_format)
+  loc_data <- forecast_data |>
+    dplyr::filter(
+      location == !!loc_table$location_code,
+      output_type == "quantile"
+    ) |>
+    dplyr::rename("date" = "target_end_date")
+  loc_obs <- observed_data |>
+    dplyr::filter(location == !!loc_table$location_code)
+
+
+  if (autotitle) {
+    loc_name <- loc_table$long_name[1]
+    plot_date <- loc_data$reference_date[1]
+    plot_title <- stringr::str_glue(
+      "{loc_name} forecasts of {plot_date}"
+    )
+  } else {
+    plot_title <- NULL
+  }
+
+  if (is.null(target_name)) {
+    target_name <- loc_data$target[1]
+  }
+
+  plot <- loc_data |>
+    plot_quantile_timeseries(
+      time_column = "date",
+      value_column = "value",
+      quantile_level_column = "output_type_id",
+      linewidth = linewidth,
+      pointsize = pointsize,
+      linecolor = forecast_linecolor,
+      pointcolor = forecast_pointcolor
+    ) +
+    ggplot2::geom_line(
+      data = loc_obs,
+      mapping = ggplot2::aes(
+        x = .data$date,
+        y = .data$value
+      ),
+      alpha = 1,
+      linewidth = linewidth,
+      color = obs_linecolor,
+      inherit.aes = FALSE
+    ) +
+    ggplot2::geom_point(
+      data = loc_obs,
+      mapping = ggplot2::aes(
+        x = .data$date,
+        y = .data$value
+      ),
+      alpha = 1,
+      size = pointsize,
+      color = obs_pointcolor,
+      inherit.aes = FALSE
+    ) +
+    ggplot2::scale_y_continuous(
+      transform = y_transform
+    ) +
+    ggplot2::labs(
+      y = target_name,
+      x = "Date"
+    ) +
+    ggplot2::ggtitle(plot_title) +
+    theme_forecasttools()
+
+
+  return(plot)
+}
+
+
+#' Plot hubverse formatted forecasts
+#' for all or a subset of forecasted
+#' locations.
+#'
+#' Plot quantiles given hubverse
+#' formatted data for all
+#' locations in the dataset or
+#' a subset of them.
+#'
+#' @param forecast_file_path path to hubverse-
+#' formatted forecast data, as a single `.csv` file.
+#' @param locations set of locations to plot. If NULL,
+#' all locations are plotted. Otherwise, a vector
+#' of location values to plot, as USPS-style
+#' abbreviations (e.g. `c("US", "AL", "AK"`),
+#' US hubverse submission location codes (
+#' e.g. `c("US", 01, 02)`), or full English
+#' jurisdiction names
+#' (e.g. `c("United States, "Alabama", "Alaska")`.
+#' Default `NULL`.
+#' @param location_input_format format of the provided location
+#' vector if it is provided.
+#' Permitted formats are `"abbr"` (state/territory
+#' or nation two letter USPS abbreviation), `"hub"` (
+#' legacy 2-digit FIPS code for states and territories, `US`
+#' for the USA as a whole), and `"long_name"` (full English
+#' jurisdiction names; not recommended). Default `"abbr"`.
+#' @param location_output_format how to code locations for
+#' the output vector.
+#' Permitted formats are `"abbr"` (state/territory
+#' or nation two letter USPS abbreviation), `"hub"` (
+#' legacy 2-digit FIPS code for states and territories, `US`
+#' for the USA as a whole), and `"long_name"` (full English
+#' jurisdiction names; not recommended). Default `"abbr"`.
+#' @param observed_data_path path to observed data
+#' to plot alongside the forecast quantiles. If `NULL`,
+#' only the forecast quantiles will be plotted. Default `NULL`.
+#' @param start_date first date to plot. If NULL, defaults
+#' to the earliest date found between the forecast timeseries (
+#' obtained from `forecast_file_path`) and the observed
+#' data timeseries (obtained from `observed_data_path`, if
+#' provided). Default NULL.
+#' @param end_date final date to plot. If NULL, defaults
+#' to the latest date found between the forecast timeseries (
+#' obtained from `forecast_file_path`) and the observed
+#' data timeseries (obtained from `observed_data_path`, if
+#' provided). Default NULL.
+#' @param location_input_format format of the provided location
+#' vector. Permitted formats are `"abbr"` (state/territory
+#' or nation two letter USPS abbreviation), `"hub"` (
+#' legacy 2-digit FIPS code for states and territories, `US`
+#' for the USA as a whole), and `"long_name"` (full English
+#' jurisdiction names; not recommended). Default `"abbr"`.
+#' @param location_output_format Location format for naming the
+#' entries of the output list. Accepts the same string
+#' keys as `location_input_format`.
+#' @param y_transform axis transform passed as the `transform`
+#' argument to [ggplot2::scale_y_continuous()]. Default `"log10"`.
+#' @param linewidth `linewidth` parameter passed to
+#' [ggplot2::geom_line()]. Default `2`.
+#' @param pointsize `size` parameter passed to
+#' [ggplot2::geom_point()]. Default `4`.
+#' @param forecast_linecolor `color` parameter
+#' passed to [ggplot2::geom_line()] for plotting forecasts.
+#' Default `"darkblue"`.
+#' @param forecast_pointcolor `color` parameter passed to
+#' [ggplot2::geom_point()] for plotting forecasts.
+#' Default `"darkblue"`.
+#' @param obs_linecolor `color` parameter passed to [ggplot2::geom_line()]
+#' for plotting observed data. Default `"black"`.
+#' @param obs_pointcolor `color` parameter passed to
+#' [ggplot2::geom_point()] for plotting observed data. Default `"black"`.
+#' @param autotitle Generate a title for the individual
+#' plots from the hubverse `reference_date` and the location
+#' name? Boolean, default `TRUE`.
+#' @return a list of ggplot objects of the plots created,
+#' one for each location
+#' @export
+plot_hubverse_file_quantiles <- function(forecast_file_path,
+                                         locations = NULL,
+                                         observed_data_path = NULL,
+                                         start_date = NULL,
+                                         end_date = NULL,
+                                         location_input_format = "abbr",
+                                         location_output_format = "abbr",
+                                         y_transform = "log10",
+                                         linewidth = 2,
+                                         pointsize = 4,
+                                         forecast_linecolor = "darkblue",
+                                         forecast_pointcolor = "darkblue",
+                                         obs_linecolor = "black",
+                                         obs_pointcolor = "black",
+                                         autotitle = TRUE) {
+  start_date <- if (!is.null(start_date)) as.Date(start_date) else NULL
+  end_date <- if (!is.null(end_date)) as.Date(end_date) else NULL
+  hubverse_cols <- readr::cols(
+    reference_date = readr::col_date(),
+    target = readr::col_character(),
+    horizon = readr::col_integer(),
+    target_end_date = readr::col_date(),
+    location = readr::col_character(),
+    output_type = readr::col_character(),
+    output_type_id = readr::col_double(),
+    value = readr::col_double()
+  )
+  forecast_data <- readr::read_csv(
+    forecast_file_path,
+    col_types = hubverse_cols
+  ) |>
+    dplyr::filter(
+      output_type == "quantile",
+    ) |>
+    dplyr::mutate(output_type_id = as.numeric(output_type_id))
+
+  if (!is.null(observed_data_path)) {
+    observed_cols <- readr::cols_only(
+      date = readr::col_date(),
+      location = readr::col_character(),
+      value = readr::col_double()
+    )
+    obs_data <- readr::read_csv(observed_data_path,
+      col_types = observed_cols
+    )
+  } else {
+    obs_data <- tibble::tibble(
+      date = as.Date(numeric(0)),
+      location = character(0),
+      value = numeric(0)
+    )
+  }
+
+  forecast_data <- forecast_data |>
+    dplyr::filter(
+      nullable_comparison(.data$target_end_date, ">=", !!start_date),
+      nullable_comparison(.data$target_end_date, "<=", !!end_date)
+    )
+
+  obs_data <- obs_data |>
+    dplyr::filter(
+      nullable_comparison(.data$date, ">=", !!start_date),
+      nullable_comparison(.data$date, "<=", !!end_date)
+    )
+
+  if (is.null(locations)) {
+    locations <- forecast_data |>
+      dplyr::distinct(location) |>
+      dplyr::pull()
+    loc_table <- location_lookup(locations, "hub")
+  } else {
+    locations <- base::unique(locations)
+    loc_table <- location_lookup(locations, location_input_format)
+  }
+
+  location_vector <- loc_table |>
+    dplyr::pull(!!to_location_table_column(location_output_format)) |>
+    purrr::set_names()
+
+  list_of_plots <- purrr::map(
+    location_vector,
+    \(loc) {
+      plot_hubverse_loc_quant_ts(
+        loc,
+        forecast_data = forecast_data,
+        observed_data = obs_data,
+        location_format = location_output_format,
+        y_transform = y_transform,
+        linewidth = linewidth,
+        pointsize = pointsize,
+        forecast_pointcolor = forecast_pointcolor,
+        forecast_linecolor = forecast_linecolor,
+        obs_pointcolor = obs_pointcolor,
+        obs_linecolor = obs_linecolor,
+        autotitle = autotitle
+      )
+    }
+  )
+
+  return(list_of_plots)
+}
diff --git a/R/plot_quantiles.R b/R/plot_quantiles.R
index e8a9289..d9c4503 100644
--- a/R/plot_quantiles.R
+++ b/R/plot_quantiles.R
@@ -1,44 +1,44 @@
-#' Plot a timeseries of quantiles
+#' Plot a timeseries of quantiles.
 #'
-#' @param data timeseries of quantiles as tidy data,
-#' with one row per timepoint per quantile level
-#' @param time_column name of the column in `data`
-#' containing timepoints
-#' @param observation_column name of the column
-#' in data containing observed values at the
-#' given quantile levels
-#' @param quantile_level_column name of the column
-#' in `data` giving the quantile level (e.g.
-#' `0.01` for the 0.01 quantile / 1st percentile)
-#' @param linesize `size` parameter passed to [ggplot2::geom_line()].
-#' Default 2.
-#' @param pointsize `size` parameter passed to [ggplot2::geom_point()]
-#' Default 4.
-#' @param linecolor `color` parameter passed to [ggplot2::geom_line()].
-#' Default `"darkblue"`.
-#' @param pointcolor `color` parameter passed to [ggplot2::geom_point()]
-#' Default `"darkblue"`.
-#' @return the resultant plot, as a ggplot object.
+#' @param data Timeseries of quantiles as tidy data,
+#' with one row per timepoint per quantile level.
+#' @param time_column Name of the column in `data`
+#' containing timepoint values, as a string.
+#' @param value_column Name of the column
+#' in data containing the timeseries values at the
+#' given quantile levels, as a string.
+#' @param quantile_level_column Name of the column in `data`
+#' containing indicating which quantile level the row contains,
+#' as a string.
+#' @param linewidth `linewidth` parameter passed to
+#' [ggplot2::geom_line()]. Default `2`.
+#' @param pointsize `size` parameter passed to
+#' [ggplot2::geom_point()] Default `4`.
+#' @param linecolor `color` parameter passed to
+#' [ggplot2::geom_line()]. Default `"darkblue"`.
+#' @param pointcolor `color` parameter passed to
+#' [ggplot2::geom_point()] Default `"darkblue"`.
+#' @return The plot, as a ggplot object.
 #' @export
-plot_forecast_quantiles <- function(data,
-                                    time_column,
-                                    observation_column,
-                                    quantile_level_column,
-                                    linesize = 2,
-                                    pointsize = 4,
-                                    pointcolor = "darkblue",
-                                    linecolor = "darkblue") {
+plot_quantile_timeseries <- function(data,
+                                     time_column,
+                                     value_column,
+                                     quantile_level_column,
+                                     linewidth = 2,
+                                     pointsize = 4,
+                                     pointcolor = "darkblue",
+                                     linecolor = "darkblue") {
   return(ggplot2::ggplot(
     mapping = ggplot2::aes(
-      x = {{ time_column }},
-      y = {{ observation_column }},
-      group = {{ quantile_level_column }},
-      alpha = 1 - abs({{ quantile_level_column }} - 0.5)
+      x = .data[[time_column]],
+      y = .data[[value_column]],
+      group = .data[[quantile_level_column]],
+      alpha = 1 - abs(.data[[quantile_level_column]] - 0.5)
     ),
     data = data
   ) +
     ggplot2::geom_line(
-      size = linesize,
+      linewidth = linewidth,
       color = linecolor
     ) +
     ggplot2::geom_point(
@@ -47,356 +47,3 @@ plot_forecast_quantiles <- function(data,
     ) +
     ggplot2::scale_alpha_continuous(guide = NULL))
 }
-
-
-#' Plot hubverse formatted quantile forecasts for a given
-#' location.
-#'
-#' Given a tibble of data properly formatted
-#' for a hubverse schema forecast hub submission,
-#' plot a timeseries quantile predictions for
-#' a given location.
-#'
-#' @param location location to plot
-#' @param forecast_data hubverse format quantile
-#' forecast data, as a [`tibble`][tibble::tibble].
-#' @param truth_data hubverse format truth data,
-#' as a [`tibble`][tibble::tibble].
-#' @param location_format format of the provided location.
-#' Permitted formats are `"abbr"` (state/territory
-#' or nation two letter USPS abbreviation), `"hub"` (
-#' legacy 2-digit FIPS code for states and territories, `US`
-#' for the USA as a whole), and `"long_name"` (full English
-#' jurisdiction names; not recommended). Default `"abbr"`.
-#' @param ytrans axis transform passed to
-#' [ggplot2::scale_y_continuous()]. Default `'log10'`.
-#' @param linesize `size` parameter passed to
-#' [ggplot2::geom_line()]. Default 2.
-#' @param pointsize `size` parameter passed to
-#' [ggplot2::geom_point()]. Default 4.
-#' @param forecast_linecolor `color` parameter passed to
-#' [ggplot2::geom_line()] for plotting forecasts.
-#' Default "darkblue".
-#' @param forecast_pointcolor `color` parameter passed to
-#' [ggplot2::geom_point()] for plotting forecasts.
-#' Default "darkblue".
-#' @param truth_linecolor `color` parameter passed to
-#' [ggplot2::geom_line()] for plotting truth data.
-#' Default "black".
-#' @param truth_pointcolor `color` parameter passed to
-#' [ggplot2::geom_point()] for plotting truth data.
-#' Default "black".
-#' @param target_name Name of the forecast target,
-#' for labeling the plot y-axis. Default `NULL`,
-#' in which case a value from the `target` column
-#' in `forecast_data` will be used.
-#' @param autotitle Boolean. Generate an automatic
-#' title for the plot from the location name
-#' and reference date? Default `TRUE`.
-#' @return the plot as a ggplot object
-#' @export
-plot_hubverse_quantiles_loc <- function(location,
-                                        forecast_data,
-                                        truth_data,
-                                        location_format = "abbr",
-                                        ytrans = "log10",
-                                        linesize = 2,
-                                        pointsize = 4,
-                                        forecast_linecolor = "darkblue",
-                                        forecast_pointcolor = "darkblue",
-                                        truth_linecolor = "black",
-                                        truth_pointcolor = "black",
-                                        target_name = NULL,
-                                        autotitle = TRUE) {
-  loc_table <- location_lookup(location, location_format)
-  loc_data <- forecast_data |>
-    dplyr::filter(
-      location == !!loc_table$location_code,
-      output_type == "quantile"
-    ) |>
-    dplyr::rename("date" = "target_end_date")
-  loc_truth <- truth_data |>
-    dplyr::filter(location == !!loc_table$location_code)
-
-
-  if (autotitle) {
-    loc_name <- loc_table$long_name[1]
-    plot_date <- loc_data$reference_date[1]
-    plot_title <- stringr::str_glue(
-      "{loc_name} forecasts of {plot_date}"
-    )
-  } else {
-    plot_title <- NULL
-  }
-
-  if (is.null(target_name)) {
-    target_name <- loc_data$target[1]
-  }
-
-  plot <- (
-    plot_forecast_quantiles(
-      loc_data,
-      date,
-      value,
-      output_type_id,
-      linesize = linesize,
-      pointsize = pointsize,
-      linecolor = forecast_linecolor,
-      pointcolor = forecast_pointcolor
-    ) +
-      ggplot2::geom_line(
-        data = loc_truth,
-        mapping = ggplot2::aes(
-          x = date,
-          y = value
-        ),
-        alpha = 1,
-        size = linesize,
-        color = truth_linecolor,
-        inherit.aes = FALSE
-      ) +
-      ggplot2::geom_point(
-        data = loc_truth,
-        mapping = ggplot2::aes(
-          x = date,
-          y = value
-        ),
-        alpha = 1,
-        size = pointsize,
-        color = truth_pointcolor,
-        inherit.aes = FALSE
-      ) +
-      ggplot2::scale_y_continuous(
-        trans = ytrans
-      ) +
-      ggplot2::labs(
-        y = target_name,
-        x = "Date"
-      ) +
-      ggplot2::ggtitle(plot_title) +
-      theme_forecasttools()
-
-  )
-
-  return(plot)
-}
-
-
-#' Plot hubverse formatted forecasts
-#' for all or a subset of forecasted
-#' locations.
-#'
-#' Plot quantiles given hubverse
-#' formatted data for all
-#' locations in the dataset or
-#' a subset of them.
-#'
-#' @param forecast_data_path path to hubverse-
-#' formatted forecast data, as a single `.csv`.
-#' @param locations set of locations to plot. If NULL,
-#' all locations are plotted. Otherwise, a vector
-#' of location values to plot, as USPS-style
-#' abbreviations (e.g. `c("US", "AL", "AK"`),
-#' US hubverse submission location codes (
-#' e.g. `c("US", 01, 02)`), or full English
-#' jurisdiction names
-#' (e.g. `c("United States, "Alabama", "Alaska")`.
-#' Default `NULL`.
-#' @param location_input_format format of the provided location
-#' vector if it is provided.
-#' Permitted formats are `"abbr"` (state/territory
-#' or nation two letter USPS abbreviation), `"hub"` (
-#' legacy 2-digit FIPS code for states and territories, `US`
-#' for the USA as a whole), and `"long_name"` (full English
-#' jurisdiction names; not recommended). Default `"abbr"`.
-#' @param location_output_format how to code locations for
-#' the output vector.
-#' Permitted formats are `"abbr"` (state/territory
-#' or nation two letter USPS abbreviation), `"hub"` (
-#' legacy 2-digit FIPS code for states and territories, `US`
-#' for the USA as a whole), and `"long_name"` (full English
-#' jurisdiction names; not recommended). Default `"abbr"`.
-#' @param truth_data_path path to hubverse formatted truth data
-#' to plot alongside the forecast quantiles. If NULL,
-#' only the forecast quantiles will be plotted. Default NULL.
-#' @param start_date first date to plot. If NULL, defaults
-#' to the earliest date found between the forecast timeseries (
-#' obtained from `forecast_data_path`) and the truth
-#' data timeseries (obtained from `truth_data_path`, if
-#' provided). Default NULL.
-#' @param end_date final date to plot. If NULL, defaults
-#' to the latest date found between the forecast timeseries (
-#' obtained from `forecast_data_path`) and the truth
-#' data timeseries (obtained from `truth_data_path`, if
-#' provided). Default NULL.
-#' @param location_input_format format of the provided location
-#' vector. Permitted formats are `"abbr"` (state/territory
-#' or nation two letter USPS abbreviation), `"hub"` (
-#' legacy 2-digit FIPS code for states and territories, `US`
-#' for the USA as a whole), and `"long_name"` (full English
-#' jurisdiction names; not recommended). Default `"abbr"`.
-#' @param location_output_format Location format for naming the
-#' entries of the output list. Accepts the same string
-#' keys as `location_input_format`.
-#' @param ytrans axis transform passed to
-#' [ggplot2::scale_y_continuous()]. Default `'log10'`.
-#' @param linesize `size` parameter passed to
-#' [ggplot2::geom_line()]. Default 2.
-#' @param pointsize `size` parameter passed to
-#' [ggplot2::geom_point()]. Default 4.
-#' @param forecast_linecolor `color` parameter
-#' passed to [ggplot2::geom_line()] for plotting forecasts.
-#' Default `"darkblue"`.
-#' @param forecast_pointcolor `color` parameter passed to
-#' [ggplot2::geom_point()] for plotting forecasts.
-#' Default "darkblue".
-#' @param truth_linecolor `color` parameter passed to [ggplot2::geom_line()]
-#' for plotting truth data. Default `"black"`.
-#' @param truth_pointcolor `color` parameter passed to [ggplot2::geom_point()]
-#' for plotting truth data. Default `"black"`.
-#' @param autotitle Boolean. Generate a title for the individual
-#' plots from the hubverse `reference_date` and the location
-#' name? Default `TRUE`.
-#' @return a list of ggplot objects of the plots created,
-#' one for each location
-#' @export
-plot_hubverse_quantiles <- function(forecast_data_path,
-                                    locations = NULL,
-                                    truth_data_path = NULL,
-                                    start_date = NULL,
-                                    end_date = NULL,
-                                    location_input_format = "abbr",
-                                    location_output_format = "abbr",
-                                    ytrans = "log10",
-                                    linesize = 2,
-                                    pointsize = 4,
-                                    forecast_linecolor = "darkblue",
-                                    forecast_pointcolor = "darkblue",
-                                    truth_linecolor = "black",
-                                    truth_pointcolor = "black",
-                                    autotitle = TRUE) {
-  hubverse_cols <- readr::cols(
-    reference_date = readr::col_date(),
-    target = readr::col_character(),
-    horizon = readr::col_integer(),
-    target_end_date = readr::col_date(),
-    location = readr::col_character(),
-    output_type = readr::col_character(),
-    output_type_id = readr::col_double(),
-    value = readr::col_double()
-  )
-  forecast_data <- readr::read_csv(
-    forecast_data_path,
-    col_types = hubverse_cols
-  ) |>
-    dplyr::filter(
-      output_type == "quantile",
-    ) |>
-    dplyr::mutate(output_type_id = as.numeric(output_type_id))
-
-  if (!is.null(truth_data_path)) {
-    truth_cols <- readr::cols_only(
-      date = readr::col_date(),
-      location = readr::col_character(),
-      value = readr::col_double()
-    )
-    truth_data <- readr::read_csv(truth_data_path,
-      col_types = truth_cols
-    )
-  } else {
-    truth_data <- tibble::tibble(
-      date = as.Date(numeric(0)),
-      location = character(0),
-      value = numeric(0)
-    )
-  }
-
-  if (is.null(locations)) {
-    locations <- forecast_data |>
-      dplyr::distinct(location) |>
-      dplyr::pull()
-    loc_table <- location_lookup(locations, "hub")
-  } else {
-    locations <- base::unique(locations)
-    loc_table <- location_lookup(locations, location_input_format)
-  }
-
-
-  if (!is.null(start_date)) {
-    truth_data <- truth_data |>
-      dplyr::filter(date >= as.Date(!!start_date))
-    forecast_data <- forecast_data |>
-      dplyr::filter(target_end_date >= as.Date(!!start_date))
-  }
-
-  if (!is.null(end_date)) {
-    truth_data <- truth_data |>
-      dplyr::filter(date <= as.Date(!!end_date))
-    forecast_data <- forecast_data |>
-      dplyr::filter(target_end_date <= as.Date(!!end_date))
-  }
-
-  location_vector <- loc_table |>
-    dplyr::pull(!!to_location_table_column(location_output_format))
-
-  result <- lapply(
-    location_vector,
-    plot_hubverse_quantiles_loc,
-    forecast_data = forecast_data,
-    truth_data = truth_data,
-    location_format = location_output_format,
-    ytrans = ytrans,
-    linesize = linesize,
-    pointsize = pointsize,
-    forecast_pointcolor = forecast_pointcolor,
-    forecast_linecolor = forecast_linecolor,
-    truth_pointcolor = truth_pointcolor,
-    truth_linecolor = truth_linecolor,
-    autotitle = autotitle
-  )
-  names(result) <- location_vector
-
-  return(result)
-}
-
-
-#' Save a list of plots as a PDF, with a
-#' grid of `nrow` by `ncol` plots per page
-#'
-#' @param list_of_plots list of plots to save to PDF
-#' @param save_path path to which to save the plots
-#' @param nrow Number of rows of plots per page
-#' (passed to [gridExtra::marrangeGrob()])
-#' Default `1`.
-#' @param ncol Number of columns of plots per page
-#' (passed to [gridExtra::marrangeGrob()]).
-#' Default `1`.
-#' @param width page width in device units (passed to
-#' [ggplot2::ggsave()]). Default `8.5`.
-#' @param height page height in device units (passed to
-#' [ggplot2::ggsave()]). Default `11`.
-#' @return `TRUE` on success.
-#' @export
-plots_to_pdf <- function(list_of_plots,
-                         save_path,
-                         nrow = 1,
-                         ncol = 1,
-                         width = 8.5,
-                         height = 11) {
-  if (!stringr::str_ends(
-    save_path, ".pdf"
-  )) {
-    cli::cli_abort("Filepath must end with `.pdf`")
-  }
-  cli::cli_inform("Saving plots to {save_path}")
-  ggplot2::ggsave(
-    filename = save_path,
-    plot = gridExtra::marrangeGrob(list_of_plots,
-      nrow = nrow,
-      ncol = ncol
-    ),
-    width = width,
-    height = height
-  )
-  return(TRUE)
-}
diff --git a/R/plot_utils.R b/R/plot_utils.R
new file mode 100644
index 0000000..1b83411
--- /dev/null
+++ b/R/plot_utils.R
@@ -0,0 +1,42 @@
+#' Save a list of ggplot plots as a PDF, with a
+#' grid of `nrow` by `ncol` plots per page
+#'
+#' @param list_of_plots List of plots to save to PDF.
+#' @param save_path Path to which to save the plots. Must
+#' end in `.pdf`.
+#' @param nrow Number of rows of plots per page
+#' (passed to [gridExtra::marrangeGrob()])
+#' Default `1`.
+#' @param ncol Number of columns of plots per page
+#' (passed to [gridExtra::marrangeGrob()]).
+#' Default `1`.
+#' @param width page width in device units (passed to
+#' [ggplot2::ggsave()]). Default `8.5`.
+#' @param height page height in device units (passed to
+#' [ggplot2::ggsave()]). Default `11`.
+#' @return Nothing, saving the plots as a side effect.
+#' @export
+plots_to_pdf <- function(list_of_plots,
+                         save_path,
+                         nrow = 1,
+                         ncol = 1,
+                         width = 8.5,
+                         height = 11) {
+  save_ext <- fs::path_ext(save_path)
+  if (!save_ext == "pdf") {
+    cli::cli_abort(paste0(
+      "{save_path} file extension must ",
+      "be 'pdf', got '{save_ext}'"
+    ))
+  }
+  cli::cli_inform("Saving plots to {save_path}")
+  ggplot2::ggsave(
+    filename = save_path,
+    plot = gridExtra::marrangeGrob(list_of_plots,
+      nrow = nrow,
+      ncol = ncol
+    ),
+    width = width,
+    height = height
+  )
+}
diff --git a/man/plot_forecast_quantiles.Rd b/man/plot_forecast_quantiles.Rd
deleted file mode 100644
index 30022ed..0000000
--- a/man/plot_forecast_quantiles.Rd
+++ /dev/null
@@ -1,50 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/plot_quantiles.R
-\name{plot_forecast_quantiles}
-\alias{plot_forecast_quantiles}
-\title{Plot a timeseries of quantiles}
-\usage{
-plot_forecast_quantiles(
-  data,
-  time_column,
-  observation_column,
-  quantile_level_column,
-  linesize = 2,
-  pointsize = 4,
-  pointcolor = "darkblue",
-  linecolor = "darkblue"
-)
-}
-\arguments{
-\item{data}{timeseries of quantiles as tidy data,
-with one row per timepoint per quantile level}
-
-\item{time_column}{name of the column in \code{data}
-containing timepoints}
-
-\item{observation_column}{name of the column
-in data containing observed values at the
-given quantile levels}
-
-\item{quantile_level_column}{name of the column
-in \code{data} giving the quantile level (e.g.
-\code{0.01} for the 0.01 quantile / 1st percentile)}
-
-\item{linesize}{\code{size} parameter passed to \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}.
-Default 2.}
-
-\item{pointsize}{\code{size} parameter passed to \code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}
-Default 4.}
-
-\item{pointcolor}{\code{color} parameter passed to \code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}
-Default \code{"darkblue"}.}
-
-\item{linecolor}{\code{color} parameter passed to \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}.
-Default \code{"darkblue"}.}
-}
-\value{
-the resultant plot, as a ggplot object.
-}
-\description{
-Plot a timeseries of quantiles
-}
diff --git a/man/plot_hubverse_quantiles.Rd b/man/plot_hubverse_file_quantiles.Rd
similarity index 58%
rename from man/plot_hubverse_quantiles.Rd
rename to man/plot_hubverse_file_quantiles.Rd
index 0970b5f..28c68f9 100644
--- a/man/plot_hubverse_quantiles.Rd
+++ b/man/plot_hubverse_file_quantiles.Rd
@@ -1,32 +1,32 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/plot_quantiles.R
-\name{plot_hubverse_quantiles}
-\alias{plot_hubverse_quantiles}
+% Please edit documentation in R/plot_hubverse_timeseries.R
+\name{plot_hubverse_file_quantiles}
+\alias{plot_hubverse_file_quantiles}
 \title{Plot hubverse formatted forecasts
 for all or a subset of forecasted
 locations.}
 \usage{
-plot_hubverse_quantiles(
-  forecast_data_path,
+plot_hubverse_file_quantiles(
+  forecast_file_path,
   locations = NULL,
-  truth_data_path = NULL,
+  observed_data_path = NULL,
   start_date = NULL,
   end_date = NULL,
   location_input_format = "abbr",
   location_output_format = "abbr",
-  ytrans = "log10",
-  linesize = 2,
+  y_transform = "log10",
+  linewidth = 2,
   pointsize = 4,
   forecast_linecolor = "darkblue",
   forecast_pointcolor = "darkblue",
-  truth_linecolor = "black",
-  truth_pointcolor = "black",
+  obs_linecolor = "black",
+  obs_pointcolor = "black",
   autotitle = TRUE
 )
 }
 \arguments{
-\item{forecast_data_path}{path to hubverse-
-formatted forecast data, as a single \code{.csv}.}
+\item{forecast_file_path}{path to hubverse-
+formatted forecast data, as a single \code{.csv} file.}
 
 \item{locations}{set of locations to plot. If NULL,
 all locations are plotted. Otherwise, a vector
@@ -38,20 +38,20 @@ jurisdiction names
 (e.g. \verb{c("United States, "Alabama", "Alaska")}.
 Default \code{NULL}.}
 
-\item{truth_data_path}{path to hubverse formatted truth data
-to plot alongside the forecast quantiles. If NULL,
-only the forecast quantiles will be plotted. Default NULL.}
+\item{observed_data_path}{path to observed data
+to plot alongside the forecast quantiles. If \code{NULL},
+only the forecast quantiles will be plotted. Default \code{NULL}.}
 
 \item{start_date}{first date to plot. If NULL, defaults
 to the earliest date found between the forecast timeseries (
-obtained from \code{forecast_data_path}) and the truth
-data timeseries (obtained from \code{truth_data_path}, if
+obtained from \code{forecast_file_path}) and the observed
+data timeseries (obtained from \code{observed_data_path}, if
 provided). Default NULL.}
 
 \item{end_date}{final date to plot. If NULL, defaults
 to the latest date found between the forecast timeseries (
-obtained from \code{forecast_data_path}) and the truth
-data timeseries (obtained from \code{truth_data_path}, if
+obtained from \code{forecast_file_path}) and the observed
+data timeseries (obtained from \code{observed_data_path}, if
 provided). Default NULL.}
 
 \item{location_input_format}{format of the provided location
@@ -65,14 +65,14 @@ jurisdiction names; not recommended). Default \code{"abbr"}.}
 entries of the output list. Accepts the same string
 keys as \code{location_input_format}.}
 
-\item{ytrans}{axis transform passed to
-\code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}. Default \code{'log10'}.}
+\item{y_transform}{axis transform passed as the \code{transform}
+argument to \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}. Default \code{"log10"}.}
 
-\item{linesize}{\code{size} parameter passed to
-\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default 2.}
+\item{linewidth}{\code{linewidth} parameter passed to
+\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default \code{2}.}
 
 \item{pointsize}{\code{size} parameter passed to
-\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}. Default 4.}
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}. Default \code{4}.}
 
 \item{forecast_linecolor}{\code{color} parameter
 passed to \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}} for plotting forecasts.
@@ -80,17 +80,17 @@ Default \code{"darkblue"}.}
 
 \item{forecast_pointcolor}{\code{color} parameter passed to
 \code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} for plotting forecasts.
-Default "darkblue".}
+Default \code{"darkblue"}.}
 
-\item{truth_linecolor}{\code{color} parameter passed to \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}
-for plotting truth data. Default \code{"black"}.}
+\item{obs_linecolor}{\code{color} parameter passed to \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}
+for plotting observed data. Default \code{"black"}.}
 
-\item{truth_pointcolor}{\code{color} parameter passed to \code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}
-for plotting truth data. Default \code{"black"}.}
+\item{obs_pointcolor}{\code{color} parameter passed to
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} for plotting observed data. Default \code{"black"}.}
 
-\item{autotitle}{Boolean. Generate a title for the individual
+\item{autotitle}{Generate a title for the individual
 plots from the hubverse \code{reference_date} and the location
-name? Default \code{TRUE}.}
+name? Boolean, default \code{TRUE}.}
 }
 \value{
 a list of ggplot objects of the plots created,
diff --git a/man/plot_hubverse_quantiles_loc.Rd b/man/plot_hubverse_loc_quant_ts.Rd
similarity index 64%
rename from man/plot_hubverse_quantiles_loc.Rd
rename to man/plot_hubverse_loc_quant_ts.Rd
index 45c18ac..2206fc4 100644
--- a/man/plot_hubverse_quantiles_loc.Rd
+++ b/man/plot_hubverse_loc_quant_ts.Rd
@@ -1,22 +1,22 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/plot_quantiles.R
-\name{plot_hubverse_quantiles_loc}
-\alias{plot_hubverse_quantiles_loc}
-\title{Plot hubverse formatted quantile forecasts for a given
-location.}
+% Please edit documentation in R/plot_hubverse_timeseries.R
+\name{plot_hubverse_loc_quant_ts}
+\alias{plot_hubverse_loc_quant_ts}
+\title{Plot a hubverse formatted quantile forecast timeseries
+for a single location.}
 \usage{
-plot_hubverse_quantiles_loc(
+plot_hubverse_loc_quant_ts(
   location,
   forecast_data,
-  truth_data,
+  observed_data,
   location_format = "abbr",
-  ytrans = "log10",
-  linesize = 2,
+  y_transform = "log10",
+  linewidth = 2,
   pointsize = 4,
   forecast_linecolor = "darkblue",
   forecast_pointcolor = "darkblue",
-  truth_linecolor = "black",
-  truth_pointcolor = "black",
+  obs_linecolor = "black",
+  obs_pointcolor = "black",
   target_name = NULL,
   autotitle = TRUE
 )
@@ -27,7 +27,7 @@ plot_hubverse_quantiles_loc(
 \item{forecast_data}{hubverse format quantile
 forecast data, as a \code{\link[tibble:tibble]{tibble}}.}
 
-\item{truth_data}{hubverse format truth data,
+\item{observed_data}{observed data,
 as a \code{\link[tibble:tibble]{tibble}}.}
 
 \item{location_format}{format of the provided location.
@@ -37,30 +37,31 @@ legacy 2-digit FIPS code for states and territories, \code{US}
 for the USA as a whole), and \code{"long_name"} (full English
 jurisdiction names; not recommended). Default \code{"abbr"}.}
 
-\item{ytrans}{axis transform passed to
-\code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}. Default \code{'log10'}.}
+\item{y_transform}{axis transform passed as the
+\code{transform} argument to \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}.
+Default \code{"log10"}.}
 
-\item{linesize}{\code{size} parameter passed to
-\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default 2.}
+\item{linewidth}{\code{linewidth} parameter passed to
+\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default \code{2}.}
 
 \item{pointsize}{\code{size} parameter passed to
-\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}. Default 4.}
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}}. Default \code{4}.}
 
 \item{forecast_linecolor}{\code{color} parameter passed to
 \code{\link[ggplot2:geom_path]{ggplot2::geom_line()}} for plotting forecasts.
-Default "darkblue".}
+Default \code{"darkblue"}.}
 
 \item{forecast_pointcolor}{\code{color} parameter passed to
 \code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} for plotting forecasts.
-Default "darkblue".}
+Default \code{"darkblue"}.}
 
-\item{truth_linecolor}{\code{color} parameter passed to
-\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}} for plotting truth data.
-Default "black".}
+\item{obs_linecolor}{\code{color} parameter passed to
+\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}} for plotting observed data.
+Default \code{"black"}.}
 
-\item{truth_pointcolor}{\code{color} parameter passed to
-\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} for plotting truth data.
-Default "black".}
+\item{obs_pointcolor}{\code{color} parameter passed to
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} for plotting observed data.
+Default \code{"black"}.}
 
 \item{target_name}{Name of the forecast target,
 for labeling the plot y-axis. Default \code{NULL},
@@ -77,6 +78,6 @@ the plot as a ggplot object
 \description{
 Given a tibble of data properly formatted
 for a hubverse schema forecast hub submission,
-plot a timeseries quantile predictions for
+plot a timeseries of quantile predictions for
 a given location.
 }
diff --git a/man/plot_quantile_timeseries.Rd b/man/plot_quantile_timeseries.Rd
new file mode 100644
index 0000000..14058f4
--- /dev/null
+++ b/man/plot_quantile_timeseries.Rd
@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plot_quantiles.R
+\name{plot_quantile_timeseries}
+\alias{plot_quantile_timeseries}
+\title{Plot a timeseries of quantiles.}
+\usage{
+plot_quantile_timeseries(
+  data,
+  time_column,
+  value_column,
+  quantile_level_column,
+  linewidth = 2,
+  pointsize = 4,
+  pointcolor = "darkblue",
+  linecolor = "darkblue"
+)
+}
+\arguments{
+\item{data}{Timeseries of quantiles as tidy data,
+with one row per timepoint per quantile level.}
+
+\item{time_column}{Name of the column in \code{data}
+containing timepoint values, as a string.}
+
+\item{value_column}{Name of the column
+in data containing the timeseries values at the
+given quantile levels, as a string.}
+
+\item{quantile_level_column}{Name of the column in \code{data}
+containing indicating which quantile level the row contains,
+as a string.}
+
+\item{linewidth}{\code{linewidth} parameter passed to
+\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default \code{2}.}
+
+\item{pointsize}{\code{size} parameter passed to
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} Default \code{4}.}
+
+\item{pointcolor}{\code{color} parameter passed to
+\code{\link[ggplot2:geom_point]{ggplot2::geom_point()}} Default \code{"darkblue"}.}
+
+\item{linecolor}{\code{color} parameter passed to
+\code{\link[ggplot2:geom_path]{ggplot2::geom_line()}}. Default \code{"darkblue"}.}
+}
+\value{
+The plot, as a ggplot object.
+}
+\description{
+Plot a timeseries of quantiles.
+}
diff --git a/man/plots_to_pdf.Rd b/man/plots_to_pdf.Rd
index 71a5038..2c8538e 100644
--- a/man/plots_to_pdf.Rd
+++ b/man/plots_to_pdf.Rd
@@ -1,8 +1,8 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/plot_quantiles.R
+% Please edit documentation in R/plot_utils.R
 \name{plots_to_pdf}
 \alias{plots_to_pdf}
-\title{Save a list of plots as a PDF, with a
+\title{Save a list of ggplot plots as a PDF, with a
 grid of \code{nrow} by \code{ncol} plots per page}
 \usage{
 plots_to_pdf(
@@ -15,9 +15,10 @@ plots_to_pdf(
 )
 }
 \arguments{
-\item{list_of_plots}{list of plots to save to PDF}
+\item{list_of_plots}{List of plots to save to PDF.}
 
-\item{save_path}{path to which to save the plots}
+\item{save_path}{Path to which to save the plots. Must
+end in \code{.pdf}.}
 
 \item{nrow}{Number of rows of plots per page
 (passed to \code{\link[gridExtra:arrangeGrob]{gridExtra::marrangeGrob()}})
@@ -34,9 +35,9 @@ Default \code{1}.}
 \code{\link[ggplot2:ggsave]{ggplot2::ggsave()}}). Default \code{11}.}
 }
 \value{
-\code{TRUE} on success.
+Nothing, saving the plots as a side effect.
 }
 \description{
-Save a list of plots as a PDF, with a
+Save a list of ggplot plots as a PDF, with a
 grid of \code{nrow} by \code{ncol} plots per page
 }
diff --git a/tests/testthat.R b/tests/testthat.R
new file mode 100644
index 0000000..a328e6d
--- /dev/null
+++ b/tests/testthat.R
@@ -0,0 +1,12 @@
+# This file is part of the standard setup for testthat.
+# It is recommended that you do not modify it.
+#
+# Where should you do additional test configuration?
+# Learn more about the roles of various files in:
+# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
+# * https://testthat.r-lib.org/articles/special-files.html
+
+library(testthat)
+library(forecasttools)
+
+test_check("forecasttools")
diff --git a/tests/testthat/test_daily_to_epiweekly.R b/tests/testthat/test_daily_to_epiweekly.R
new file mode 100644
index 0000000..42a74ab
--- /dev/null
+++ b/tests/testthat/test_daily_to_epiweekly.R
@@ -0,0 +1,93 @@
+dat <- forecasttools::example_daily_forecast_flu
+
+test_that(
+  paste0(
+    "daily_to_epiweekly works identically to a ",
+    "on the example data (unit test based on the ",
+    "example in the hubverse formatting vignette)."
+  ),
+  {
+    expected <- dat |>
+      dplyr::mutate(
+        epiweek = lubridate::epiweek(date),
+        epiyear = lubridate::epiyear(date)
+      ) |>
+      dplyr::group_by(
+        epiweek,
+        epiyear,
+        .draw,
+        location
+      ) |>
+      dplyr::filter(dplyr::n() == 7) |>
+      dplyr::summarise(
+        weekly_hosp = sum(hosp),
+        .groups = "drop"
+      )
+
+    result <- daily_to_epiweekly(
+      dat,
+      value_col = "hosp",
+      id_cols = c(".draw", "location"),
+      weekly_value_name = "weekly_hosp"
+    )
+
+    expect_equal(result, expected)
+
+    ## should be different with partial weeks
+    ## included
+    expected_with_partial <- dat |>
+      dplyr::mutate(
+        epiweek = lubridate::epiweek(date),
+        epiyear = lubridate::epiyear(date)
+      ) |>
+      dplyr::group_by(
+        epiweek,
+        epiyear,
+        .draw,
+        location
+      ) |>
+      dplyr::summarise(
+        weekly_hosp = sum(hosp),
+        .groups = "drop"
+      )
+
+    expect_true(nrow(result) < nrow(expected_with_partial))
+
+    result_with_partial <- daily_to_epiweekly(
+      dat,
+      value_col = "hosp",
+      id_cols = c(".draw", "location"),
+      weekly_value_name = "weekly_hosp",
+      strict = FALSE
+    )
+
+    expect_equal(result_with_partial, expected_with_partial)
+  }
+)
+
+test_that(paste0(
+  "daily_to_epiweekly() errors by default if more than ",
+  "seven entries for a given epiweekly trajectory"
+), {
+  dat_duplicate_row <- dat |>
+    dplyr::filter(
+      date == as.Date("2023-10-30"),
+      location == "KS",
+      .draw == 18
+    )
+  expect_equal(nrow(dat_duplicate_row), 1)
+
+  ## duplicate only one row, otherwise data
+  ## still valid. Error should still occur.
+  dat_duplicated <- dplyr::bind_rows(dat, dat_duplicate_row)
+
+  expect_error(
+    daily_to_epiweekly(
+      dat_duplicated,
+      value_col = "hosp",
+      id_cols = c(".draw", "location"),
+      weekly_value_name = "weekly_hosp"
+    ),
+    regexp = "repeated values"
+  )
+})
diff --git a/tests/testthat/test_epiweek_to_date.R b/tests/testthat/test_epiweek_to_date.R
index 83e0d3e..1043b3c 100644
--- a/tests/testthat/test_epiweek_to_date.R
+++ b/tests/testthat/test_epiweek_to_date.R
@@ -4,56 +4,50 @@ schema <- tidyr::crossing(
   day_of_week = 1:7
 )
 
-testthat::test_that(paste0(
+test_that(paste0(
   "epiweek_to_date() function's internal ",
   "validation passes for USA epiweeks for ",
   "every epiweek in 1:52 for every epiyear ",
   "in 1800:2200, for every day of the epiweek"
 ), {
-  testthat::expect_no_error(
-    with_usa_dates <- schema |>
-      dplyr::mutate(
-        date = forecasttools::epiweek_to_date(
-          epiweek,
-          epiyear,
-          epiweek_standard = "USA",
-          day_of_week = day_of_week,
-          validate = TRUE
-        )
-      )
+  expect_no_warning(
+    epiweek_to_date(
+      schema$epiweek,
+      schema$epiyear,
+      epiweek_standard = "USA",
+      day_of_week = schema$day_of_week,
+      validate = TRUE
+    )
   )
 })
 
-testthat::test_that(paste0(
+test_that(paste0(
   "epiweek_to_date() function's internal ",
   "validation passes for ISO (epi)weeks for ",
   "every epiweek in 1:52 for every epiyear ",
   "in 1800:2200, for every day of the epiweek"
 ), {
-  testthat::expect_no_error(
-    with_iso_dates <- schema |>
-      dplyr::mutate(
-        date = forecasttools::epiweek_to_date(
-          epiweek,
-          epiyear,
-          epiweek_standard = "ISO",
-          day_of_week = day_of_week,
-          validate = TRUE
-        )
-      )
+  expect_no_warning(
+    epiweek_to_date(
+      schema$epiweek,
+      schema$epiyear,
+      epiweek_standard = "ISO",
+      day_of_week = schema$day_of_week,
+      validate = TRUE
+    )
   )
 })
 
 
-testthat::test_that(paste0(
+test_that(paste0(
   "epiweek_to_date() function's internal ",
   "validation fails if you try to get the ",
   "start of an epiweek that doesn't exist ",
   "but passes if you get a valid epiweek"
 ), {
   ## 2020 had an epiweek 53
-  testthat::expect_no_error(
-    forecasttools::epiweek_to_date(
+  expect_no_error(
+    epiweek_to_date(
       53,
       2020,
       epiweek_standard = "USA",
@@ -62,8 +56,8 @@ testthat::test_that(paste0(
   )
 
   ## 2021 did not
-  testthat::expect_error(
-    forecasttools::epiweek_to_date(
+  expect_error(
+    epiweek_to_date(
       53,
       2021,
       epiweek_standard = "USA",
@@ -72,8 +66,8 @@ testthat::test_that(paste0(
   )
 
   ## a single failure should raise an error
-  testthat::expect_error(
-    forecasttools::epiweek_to_date(
+  expect_error(
+    epiweek_to_date(
       53,
       c(2020, 2021),
       epiweek_standard = "USA",
@@ -83,8 +77,8 @@ testthat::test_that(paste0(
 
   ## but the validation should be vectorized
   ## and succeed accordingly
-  testthat::expect_no_error(
-    forecasttools::epiweek_to_date(
+  expect_no_error(
+    epiweek_to_date(
       c(53, 52),
       c(2020, 2021),
       epiweek_standard = "USA",
diff --git a/tests/testthat/test_inferencedata_dataframe_to_tidydraws.R b/tests/testthat/test_inferencedata_dataframe_to_tidydraws.R
index def21b5..8a78b9e 100644
--- a/tests/testthat/test_inferencedata_dataframe_to_tidydraws.R
+++ b/tests/testthat/test_inferencedata_dataframe_to_tidydraws.R
@@ -1,11 +1,11 @@
-testthat::test_that("inferencedata_to_tidy_draws converts data correctly", {
+test_that("inferencedata_to_tidy_draws converts data correctly", {
   data("ex_inferencedata_dataframe")
   result <- inferencedata_to_tidy_draws(ex_inferencedata_dataframe)
 
-  testthat::expect_setequal(colnames(result), c("group", "data"))
-  testthat::expect_setequal(result$group, c("posterior", "predictions"))
+  expect_setequal(colnames(result), c("group", "data"))
+  expect_setequal(result$group, c("posterior", "predictions"))
 
-  testthat::expect_equal(
+  expect_equal(
     colnames(result$data[[1]]),
     c(
       ".chain", ".iteration", ".draw", "a", "b[troll_shore]", "b[drawn]",
@@ -17,7 +17,7 @@ testthat::test_that("inferencedata_to_tidy_draws converts data correctly", {
     )
   )
 
-  testthat::expect_equal(
+  expect_equal(
     colnames(result$data[[2]]),
     c(
       ".chain", ".iteration", ".draw", "obs[woken]", "obs[awash]",
@@ -25,10 +25,10 @@ testthat::test_that("inferencedata_to_tidy_draws converts data correctly", {
     )
   )
 
-  testthat::expect_no_error(
+  expect_no_error(
     tidybayes::spread_draws(result$data[[1]], a, b[x], c[y, z])
   )
-  testthat::expect_no_error(
+  expect_no_error(
     tidybayes::spread_draws(result$data[[2]], obs[a])
   )
 })
diff --git a/tests/testthat/test_simple_bottom_up.R b/tests/testthat/test_simple_bottom_up.R
index 3162c46..ee0e022 100644
--- a/tests/testthat/test_simple_bottom_up.R
+++ b/tests/testthat/test_simple_bottom_up.R
@@ -32,8 +32,8 @@ test_u_mat <- matrix(c(0.1, 0.3, 0.7), nrow = 1)
 location_names <- c("A", "B", "C")
 colnames(test_u_mat) <- location_names
 
-testthat::test_that("`validate_base_forecasts` throws an error", {
-  testthat::expect_error(validate_base_forecasts(bad_test_base_forecasts,
+test_that("`validate_base_forecasts` throws an error", {
+  expect_error(validate_base_forecasts(bad_test_base_forecasts,
     test_cp,
     value_to_aggregate_col = "hosps",
     rank_quantity_col = "rank_quantity",
@@ -42,7 +42,7 @@ testthat::test_that("`validate_base_forecasts` throws an error", {
   ))
 })
 
-testthat::test_that("`count_trajectories` returns correct number of trajs", {
+test_that("`count_trajectories` returns correct number of trajs", {
   result <- count_trajectories(test_base_forecasts,
     location_col = "location",
     date_col = "date"
@@ -51,10 +51,10 @@ testthat::test_that("`count_trajectories` returns correct number of trajs", {
     location = c("A", "B", "C"),
     n_sample_trajs = c(2, 2, 2)
   )
-  testthat::expect_equal(result, expected_output)
+  expect_equal(result, expected_output)
 })
 
-testthat::test_that("`copula2tbl` returns the expected output", {
+test_that("`copula2tbl` returns the expected output", {
   i <- 1
   location_col <- "location"
 
@@ -65,10 +65,10 @@ testthat::test_that("`copula2tbl` returns the expected output", {
     location = location_names
   )
 
-  testthat::expect_equal(result, expected_output)
+  expect_equal(result, expected_output)
 })
 
-testthat::test_that("`rank_sampled_trajectories` returns correct rankings", {
+test_that("`rank_sampled_trajectories` returns correct rankings", {
   ranked_base_forecasts <-
     rank_sampled_trajectories(test_base_forecasts,
       location_col = "location",
@@ -83,10 +83,10 @@ testthat::test_that("`rank_sampled_trajectories` returns correct rankings", {
     rank = c(1, 2, 1, 2, 1, 2)
   )
 
-  testthat::expect_equal(ranked_base_forecasts, expected_rankings)
+  expect_equal(ranked_base_forecasts, expected_rankings)
 })
 
-testthat::test_that("sample_aggregated_trajectories", {
+test_that("sample_aggregated_trajectories", {
   i <- 1
   location_col <- "location"
   test_sample <- copula2tbl(
@@ -123,5 +123,5 @@ testthat::test_that("sample_aggregated_trajectories", {
     forecast = c(123, 200)
   )
 
-  testthat::expect_equal(result, expected_output)
+  expect_equal(result, expected_output)
 })
diff --git a/tests/testthat/test_to_hubverse.R b/tests/testthat/test_to_hubverse.R
index 0a11854..048b239 100644
--- a/tests/testthat/test_to_hubverse.R
+++ b/tests/testthat/test_to_hubverse.R
@@ -1,17 +1,17 @@
-testthat::test_that(
+test_that(
   paste0(
     "get_hubverse_table errors if reference date ",
     "is the wrong day of the week"
   ),
   {
-    testthat::expect_error(
+    expect_error(
       forecasttools::get_hubverse_table(
         tibble::tibble(),
         "2025-01-01"
       ),
       "which is day number 4"
     )
-    testthat::expect_error(
+    expect_error(
       forecasttools::get_hubverse_table(
         tibble::tibble(),
         "2025-01-01",
@@ -19,7 +19,7 @@ testthat::test_that(
       ),
       "which is day number 1"
     )
-    testthat::expect_error(
+    expect_error(
       forecasttools::get_hubverse_table(
         tibble::tibble(),
         "2025-01-01",
diff --git a/vignettes/plot-hub-submission.Rmd b/vignettes/plot-hub-submission.Rmd
index 3fe07d3..83cbc80 100644
--- a/vignettes/plot-hub-submission.Rmd
+++ b/vignettes/plot-hub-submission.Rmd
@@ -31,16 +31,16 @@ library(forecasttools)
 ```
 
 # Quantile timeseries
-Much hubverse formatted output is organized into quantiles. An easy spotcheck plot shows how these quantiles evolve over the forecast horizon. We can make it using the `plot_hubverse_quantiles()` function. There is only one mandatory argument: the path to a properly hubverse-formatted `.csv` file. Let's plot some inflenza forecasts submitted to the 2023-24 FluSight Challenge by the `cfarenewal-cfaepimlight` team for the 2024-04-06 reference date:
+Much hubverse formatted output is organized into quantiles. An easy spotcheck plot shows how these quantiles evolve over the forecast horizon. We can make it using the `plot_hubverse_file_quantiles()` function. There is only one mandatory argument: the path to a properly hubverse-formatted `.csv` file. Let's plot some inflenza forecasts submitted to the 2023-24 FluSight Challenge by the `cfarenewal-cfaepimlight` team for the 2024-04-06 reference date:
 
 ```{r, message = FALSE, echo = c(2, 4)}
 # nolint start
 path_to_formatted_forecast <- "https://raw.githubusercontent.com/cdcepi/FluSight-forecast-hub/refs/heads/main/model-output/cfarenewal-cfaepimlight/2024-04-06-cfarenewal-cfaepimlight.csv"
 # nolint end
-plots <- plot_hubverse_quantiles(path_to_formatted_forecast)
+plots <- plot_hubverse_file_quantiles(path_to_formatted_forecast)
 ```
 
-`plot_hubverse_quantiles()` returns a list of all the plots generated. By default, the list names (keys) are US Postal Service style two-letter abbreviations. Let's look at the national plot:
+`plot_hubverse_file_quantiles()` returns a list of all the plots generated. By default, the list names (keys) are US Postal Service style two-letter abbreviations. Let's look at the national plot:
 
 ```{r}
 plots[["US"]]
@@ -52,10 +52,10 @@ We can also look at the plot for Colorado:
 plots[["CO"]]
 ```
 
-Of course, you may not wish to generate plots for all locations in your hubverse-formatted file at once. `plot_hubverse_quantiles()` takes an optional `locations` argument that allows you to plot only a subset. For example, let's plot the ["Four Corners" states](https://en.wikipedia.org/wiki/Four_Corners):
+Of course, you may not wish to generate plots for all locations in your hubverse-formatted file at once. `plot_hubverse_file_quantiles()` takes an optional `locations` argument that allows you to plot only a subset. For example, let's plot the ["Four Corners" states](https://en.wikipedia.org/wiki/Four_Corners):
 
 ```{r, message = FALSE}
-four_corners <- plot_hubverse_quantiles(path_to_formatted_forecast,
+four_corners <- plot_hubverse_file_quantiles(path_to_formatted_forecast,
   locations = c("AZ", "CO", "NM", "UT")
 )
 
@@ -63,33 +63,34 @@ four_corners <- plot_hubverse_quantiles(path_to_formatted_forecast,
 four_corners[["NM"]]
 ```
 
-Many hubs provide "truth data" of observed values of the forecasting target, and so `plot_hubverse_quantiles()` optionally allows you to plot this alongside the forecast data. Since this truth data often goes back years, it is useful to set a cutoff using the `start_date` argument. Here, we'll start in  December 2023.
+Many hubs provide "target data" or "truth data" of observed values of the forecasting target, and so `plot_hubverse_file_quantiles()` optionally allows you to plot this alongside the forecast data. Since this target data often goes back years, it is useful to set a cutoff using the `start_date` argument. Here, we'll start in  December 2023.
 
 ```{r, message = FALSE, echo = c(2, 4:7)}
 # nolint start
-truth_data <- "https://raw.githubusercontent.com/cdcepi/FluSight-forecast-hub/04e884dce942dd3b8766aee3d8ff1c333b4fb6fa/target-data/target-hospital-admissions.csv"
+target_data_path <- "https://raw.githubusercontent.com/cdcepi/FluSight-forecast-hub/04e884dce942dd3b8766aee3d8ff1c333b4fb6fa/target-data/target-hospital-admissions.csv"
 # nolint end
-plot_hubverse_quantiles(path_to_formatted_forecast,
+plot_hubverse_file_quantiles(path_to_formatted_forecast,
   locations = "US",
-  truth_data_path = truth_data,
+  observed_data_path = target_data_path,
   start_date = "2023-12-01"
 )
 ```
 
-The function provides some basic customization of line and point sizes and colors, via the `linesize`, `pointsize`, `forecast_linecolor`, `forecast_pointcolor`, `truth_pointcolor`, and `truth_linecolor` arguments. It also defaults to plotting a log10-scale y-axis, but this can be changed by passing a different string to `ytrans`; any valid value for the `transform = ` argument of `ggplot2::scale_y_continuous()` can be passed.
+The function provides some basic customization of plotted lines and points via the `linewidth`, `pointsize`, `forecast_linecolor`, `forecast_pointcolor`, `obs_pointcolor`, and `obs_linecolor` arguments. It also defaults to plotting on a log10-scale y-axis, but this can be changed by passing a different string to `y_transform`; any valid value for the `transform = ` argument of `ggplot2::scale_y_continuous()` can be passed.
 
 ```{r, message = FALSE}
 ## plot forecast data in green, with smaller points and
 ## lines, and plot on a linear scale
-my_custom_plot <- plot_hubverse_quantiles(path_to_formatted_forecast,
+my_custom_plot <- plot_hubverse_file_quantiles(
+  path_to_formatted_forecast,
   locations = "US",
-  truth_data_path = truth_data,
+  observed_data_path = target_data_path,
   start_date = "2023-12-01",
   forecast_linecolor = "darkgreen",
   forecast_pointcolor = "darkgreen",
   pointsize = 1,
-  linesize = 1,
-  ytrans = "identity"
+  linewidth = 1,
+  y_transform = "identity"
 )
 my_custom_plot[["US"]]
 ```
diff --git a/vignettes/scoring-flu-forecasts.Rmd b/vignettes/scoring-flu-forecasts.Rmd
index 9fcf66a..a259e39 100644
--- a/vignettes/scoring-flu-forecasts.Rmd
+++ b/vignettes/scoring-flu-forecasts.Rmd
@@ -18,7 +18,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-```{r setup, messages = "hide"}
+```{r setup, message = FALSE}
 library(forecasttools)
 library(scoringutils)
 library(dplyr)