actor_aggregation: small fixes to code

R/actor_aggregation.R

@@ -23,24 +23,6 @@
 #################################### Aggregate actor results ################################
 #################################################################################################
 actor_aggregation <- function(row, actors, es_pwd, localhost, default_operator = 'OR') {
-  actor <- actors[row,]
-  if (actor$`_source.function` == "Party"){
-    years = seq(2000,2019,1)
-  } else {
-    years = c(0)
-  }
-
-  if (actor$`_source.function` == 'Party' && actor$party_only == T) {
-    actorids <- c(paste0(actor$`_source.partyId`,'_s'), paste0(actor$`_source.partyId`,'_f'))
-  } else if (actor$`_source.function` == 'Party') {
-    actorids <- c(paste0(actor$`_source.partyId`,'_s'), paste0(actor$`_source.partyId`,'_f'), paste0(actor$`_source.partyId`,'_a'))
-    actor$party_only <- F
-  } else {
-    actorids <- actor$`_source.actorId`
-    actor$party_only <- NULL
-  }
-
-  actor_aggregator <- function(year, query, actor, actorids, default_operator, localhost = F, es_pwd) {
   ### Functions
   aggregator <- function (id, duplicates) {
     article <- filter(duplicates, `_id` == id) %>%
@@ -59,6 +41,52 @@ actor_aggregation <- function(row, actors, es_pwd, localhost, default_operator =
     )
     )
   }
+
+  ### Creating aggregate measuers at daily, weekly, monthly and yearly level
+  grouper <- function(level, actor_df, actorids) {
+    by_newspaper <- actor_df %>% group_by_at(vars(level, `_source.doctype`)) %>%
+      summarise(
+        occ = mean(unlist(occ)),
+        prom = mean(unlist(prom)),
+        rel_first = mean(unlist(rel_first)),
+        first = mean(unlist(first)),
+        articles = length(`_id`),
+        level = level
+      )
+
+    aggregate <- actor_df %>% group_by_at(vars(level)) %>%
+      summarise(
+        occ = mean(unlist(occ)),
+        prom = mean(unlist(prom)),
+        rel_first = mean(unlist(rel_first)),
+        first = mean(unlist(first)),
+        articles = length(`_id`),
+        `_source.doctype` = 'agg',
+        level = level
+      )
+    output <- bind_rows(by_newspaper, aggregate) %>%
+      bind_cols(.,bind_rows(actor)[rep(seq_len(nrow(bind_rows(actor))), each=nrow(.)),])
+    return(output)
+  }
+###########################################################################################
+  actor <- actors[row,]
+  if (actor$`_source.function` == "Party"){
+    years = seq(2000,2019,1)
+  } else {
+    years = c(0)
+  }
+
+  if (actor$`_source.function` == 'Party' && actor$party_only == T) {
+    actorids <- c(paste0(actor$`_source.partyId`,'_s'), paste0(actor$`_source.partyId`,'_f'))
+  } else if (actor$`_source.function` == 'Party') {
+    actorids <- c(paste0(actor$`_source.partyId`,'_s'), paste0(actor$`_source.partyId`,'_f'), paste0(actor$`_source.partyId`,'_a'))
+    actor$party_only <- F
+  } else {
+    actorids <- actor$`_source.actorId`
+    actor$party_only <- NULL
+  }
+
+  actor_aggregator <- function(year, query, actor, actorids, default_operator, localhost = F, es_pwd) {
     if (year > 0) {
       query <- paste0('computerCodes.actors:(',paste(actorids, collapse = ' '),') && publication_date:[',year,'-01-01 TO ',year,'-12-31] && computerCodes.junk:0')
     } else {
@@ -69,8 +97,9 @@ actor_aggregation <- function(row, actors, es_pwd, localhost, default_operator =
                        localhost = localhost,
                        es_pwd = es_pwd)
     if (length(out$`_id`) > 0 ) {
+      actor_df <- out
       ### Generating actor dataframe, unnest by actorsDetail, then by actor ids. Filter out non-relevant actor ids.
-      actor_df <- out %>%
+      actor_df <- actor_df %>%
         unnest() %>%
         unnest(ids, .preserve = colnames(.)) %>%
         filter(ids1 %in% actorids) %>%
@@ -86,7 +115,6 @@ actor_aggregation <- function(row, actors, es_pwd, localhost, default_operator =
         dupe_merged <- bind_rows(lapply(art_id, aggregator, duplicates = duplicates))
         actor_df <- bind_rows(dupe_merged, actor_single)
       }
-
       ### Creating date grouping variables
       actor_df <- actor_df %>%
         mutate(
@@ -95,34 +123,8 @@ actor_aggregation <- function(row, actors, es_pwd, localhost, default_operator =
           yearmonthday = strftime(actor_df$`_source.publication_date`, format = '%Y%m%d'),
           yearweek = strftime(actor_df$`_source.publication_date`, format = "%Y%V")
         )
-      ### Creating aggregate measuers at daily, weekly, monthly and yearly level
-      grouper <- function(level) {
-        by_newspaper <- actor_df %>% group_by_at(vars(level, `_source.doctype`)) %>%
-          summarise(
-            occ = mean(unlist(occ)),
-            prom = mean(unlist(prom)),
-            rel_first = mean(unlist(rel_first)),
-            first = mean(unlist(first)),
-            articles = length(`_id`),
-            level = level
-          )
-
-        aggregate <- actor_df %>% group_by_at(vars(level)) %>%
-          summarise(
-            occ = mean(unlist(occ)),
-            prom = mean(unlist(prom)),
-            rel_first = mean(unlist(rel_first)),
-            first = mean(unlist(first)),
-            articles = length(`_id`),
-            `_source.doctype` = 'agg',
-            level = level
-          )
-        output <- bind_rows(by_newspaper, aggregate) %>%
-          bind_cols(.,bind_rows(actor)[rep(seq_len(nrow(bind_rows(actor))), each=nrow(.)),])
-        return(output)
-      }
       levels <- c('year','yearmonth','yearmonthday','yearweek')
-      aggregate_data <- bind_rows(lapply(levels, grouper))
+      aggregate_data <- bind_rows(lapply(levels, grouper, actor_df = actor_df, actorids = actorids))
       return(aggregate_data)
     } else {
       return()