Manipulate Cartesian data to use in the WATS polar plot

Three operations are performed. First, within each stage, the first row is repeated at the end, to close the loop. Second, multiple points are interpolated (still in a Cartesian coordinates) so that the polar graph doesn't have sharp edges. These sharp edges would be artifacts of the conversion, and not reflect the observed data. Third, the Cartesian points are converted to polar coordinates.

Usage

polarize_cartesian(
  ds_linear,
  ds_stage_cycle,
  y_name,
  stage_id_name,
  cycle_tally_name = "cycle_tally",
  proportion_through_cycle_name = "proportion_through_cycle",
  periodic_lower_name = "position_lower",
  periodic_center_name = "position_center",
  periodic_upper_name = "position_upper",
  plotted_point_count_per_cycle = 120,
  graph_floor = min(base::pretty(ds_linear[[y_name]]))
)

Arguments

ds_linear

The data.frame to containing the simple linear data. There should be one record per observation.

ds_stage_cycle

The data.frame to containing the reoccurring/periodic bands. There should be one record per observation per stage. If there are three stages, this tibble::tibble should have three times as many rows as ds_linear.

y_name

The variable name containing the dependent/criterion variable.

stage_id_name

The variable name indicating which stage the record belongs to. For example, before the first interruption, the stage_id is "1", and is "2" afterwards.

cycle_tally_name

The variable name indicating how many complete cycles have occurred at that observation.

proportion_through_cycle_name

The variable name showing how far through a cycle the observation (or summarized observations) occurred.

periodic_lower_name

The variable name showing the lower bound of a stage's periodic estimate.

periodic_center_name

The variable name showing the center estimate of a stage's periodic estimate.

periodic_upper_name

The variable name showing the upper bound of a stage's periodic estimate.

plotted_point_count_per_cycle

The number of points that are plotted per cycle. If the polar graph has 'sharp corners', then increase this value.

graph_floor

The value of the criterion/dependent variable at the center of the polar plot.

Value

Returns a tibble::tibble.

Examples

library(Wats)
ds_linear <-
  Wats::county_month_birth_rate_2005_version |>
  dplyr::filter(county_name == "oklahoma") |>
  augment_year_data_with_month_resolution(date_name = "date")

h_spread <- function(scores) { quantile(x = scores, probs = c(.25, .75)) }
portfolio <- annotate_data(
  ds_linear        = ds_linear,
  dv_name          = "birth_rate",
  center_function  = median,
  spread_function  = h_spread
)
rm(ds_linear)

polarized <- polarize_cartesian(
  ds_linear      = portfolio$ds_linear,
  ds_stage_cycle = portfolio$ds_stage_cycle,
  y_name         = "birth_rate",
  stage_id_name  = "stage_id"
)

library(ggplot2)
polarized$ds_stage_cycle_polar |>
  ggplot(aes(color = factor(stage_id))) +
  geom_path(aes(x = polar_lower_x , y = polar_lower_y), linetype = 2) +
  geom_path(aes(x = polar_center_x, y = polar_center_y), linewidth = 2) +
  geom_path(aes(x = polar_upper_x , y = polar_upper_y), linetype = 2) +
  geom_path(aes(x = observed_x    , y = observed_y), data = polarized$ds_observed_polar) +
  coord_fixed(ratio = 1) +
  guides(color = NULL)