minor cleanup

Author: stevencarlislewalker

R/iidda.analysis/tests/testthat/test-plot-pipelining.R

@@ -1,122 +1,65 @@
-library(rlang)
 library(iidda.analysis)
 
 if (interactive()) {
-measles = ("measles_1800_to_1842.rds"
-  |> system.file(package = "iidda.analysis")
-  |> readRDS()
-)
-meningitis = ("meningitis_on.rds"
-  |> system.file(package = "iidda.analysis")
-  |> readRDS()
-)
-london_mort = ("london-mort-harmonized.rds"
-  |> system.file(package = "iidda.analysis")
-  |> readRDS()
-)
-
-iidda_bar(meningitis)
-
-harmonizer = SeriesHarmonizer()
-xx = harmonizer(london_mort)
-View(xx)
-
-cause_lookup = iidda.api::ops_staging$lookup_tables("lbom-cause-lookup")
-cause_hierachy = (cause_lookup
-  |> select(synonym, nesting_cause)
-  |> rename(cause = synonym)
-  |> distinct()
-)
-View(cause_lookup)
-
-converter = DataDictionaryConverter()
-NestingHarmonizer = function(category_level, id_variables) {
-  function(data
-      , value_variable = NULL
-      , category_variable = NULL
-      , nesting_variable = NULL
-    ) {
-    data = iidda.analysis:::resolve_var_args(data)
-    top_level_vars = c(id_variables, category_variable, value_variable)
-    grouping_vars = c(id_variables, nesting_variable)
-    final_id_vars = c(id_variables, category_variable)
-    top_level_data = (data
-      |> filter(.data[[category_variable]] == category_level)
-      |> select(all_of(top_level_vars))
-    )
-    finer_data = (data
-      |> filter(.data[[nesting_variable]] == category_level)
-      |> summarise(!!sym(value_variable) := sum(.data[[value_variable]]), .by = all_of(grouping_vars))
-      |> rename(!!sym(category_variable) := all_of(nesting_variable))
-    )
-    output_data = bind_rows(top_level_data, finer_data)
-    unique_numbers_of_repeats = (output_data
-      |> summarise(n = n(), .by = all_of(final_id_vars))
-      |> pull(n)
-      |> unique()
-    )
-    if (!identical(unique_numbers_of_repeats, 1L)) {
-      stop("Harmonization failed. Please insert more coins for a better explanation")
+  measles = ("measles_1800_to_1842.rds"
+    |> system.file(package = "iidda.analysis")
+    |> readRDS()
+  )
+  meningitis = ("meningitis_on.rds"
+    |> system.file(package = "iidda.analysis")
+    |> readRDS()
+  )
+  london_mort = ("london-mort-harmonized.rds"
+    |> system.file(package = "iidda.analysis")
+    |> readRDS()
+  )
+  
+  iidda_bar(meningitis)
+  
+  cause_lookup = iidda.api::ops_staging$lookup_tables("lbom-cause-lookup")
+  cause_hierachy = (cause_lookup
+    |> select(synonym, nesting_cause)
+    |> rename(cause = synonym)
+    |> distinct()
+  )
+  
+  
+  converter = DataDictionaryConverter()
+  NestingHarmonizer = function(category_level, id_variables) {
+    function(data
+        , value_variable = NULL
+        , category_variable = NULL
+        , nesting_variable = NULL
+      ) {
+      data = iidda.analysis:::resolve_var_args(data)
+      top_level_vars = c(id_variables, category_variable, value_variable)
+      grouping_vars = c(id_variables, nesting_variable)
+      final_id_vars = c(id_variables, category_variable)
+      top_level_data = (data
+        |> filter(.data[[category_variable]] == category_level)
+        |> select(all_of(top_level_vars))
+      )
+      finer_data = (data
+        |> filter(.data[[nesting_variable]] == category_level)
+        |> summarise(!!sym(value_variable) := sum(.data[[value_variable]]), .by = all_of(grouping_vars))
+        |> rename(!!sym(category_variable) := all_of(nesting_variable))
+      )
+      output_data = bind_rows(top_level_data, finer_data)
+      unique_numbers_of_repeats = (output_data
+        |> summarise(n = n(), .by = all_of(final_id_vars))
+        |> pull(n)
+        |> unique()
+      )
+      if (!identical(unique_numbers_of_repeats, 1L)) {
+        stop("Harmonization failed. Please insert more coins for a better explanation")
+      }
+      iidda.analysis:::iidda_return(output_data, data)
     }
-    iidda.analysis:::iidda_return(output_data, data)
   }
-}
-library(ggplot2)
-trimer = TrimSeries(zero_lead = TRUE, zero_trail = TRUE)
-(london_mort
-  |> converter()
-  |> ff(category_level = "Cholera", id_variables = c("period_start_date", "period_end_date"))
-  |> trimer()
-  |> ggplot()
-  + aes(period_end_date, deaths)
-  + geom_line()
-  + scale_x_date(minor_breaks = "years")
-  + scale_y_continuous(transform = "sqrt")
-  + theme_bw()
-)
-
-
-cholera_1842_to_1901_new = (london_mort_raw
-  |> filter(cause == "Cholera")
-  |> filter(between(period_end_date, "1841-12-31", "1901-12-31"))
-  |> select(period_start_date, period_end_date, cause, deaths)
-  |> bind_rows((london_mort_raw
-    |> filter(nesting_cause == "Cholera")
-    |> filter(between(period_end_date, "1841-12-31", "1901-12-31"))
-    |> group_by(period_start_date, period_end_date, nesting_cause)
-    |> summarise(deaths = sum(deaths))
-    |> rename(cause = nesting_cause)
-  ))
-)
-
-(meningitis
-  |> iidda_prep_bar(time_unit = "month_factor_abbr")
-  |> iidda_attach_bar()
-  |> iidda_render_plot(title = "Friend")
-)
-(meningitis
-  |> period_describer()
-  |> iidda_prep_series(time_variable = "period_mid_date")
-  |> iidda_attach_series()
-  |> iidda_render_plot()
-)
-(measles
-  |> period_describer(period_end_variable = "period_end_date")
-  |> iidda_series(series_variable = "deaths")
-)
-
-
-
-
-
-guesser = TitleChooser()
-measles |> guesser() |> attr("iidda")
-
-attr((measles), "iidda")
-iidda_title(plot_object
-    , data[[min_time]]
-    , data[[max_time]]
-    , data[[descriptor_name]] |> pull()
-    , theme
+  
+  (meningitis
+    |> iidda_prep_bar(time_unit = "month_factor_abbr")
+    |> iidda_attach_bar()
+    |> iidda_render_plot(title = "Friend")
   )
 }