---

NN_PATH  <-here("analysis/books/adult_comparision/nn_analysis/nns/nn_by_gendered_word_cleaned_downsampled_kidbook.csv")
nn_words  <- read_csv(NN_PATH)

MODEL_PATHS <- here("analysis/books/adult_comparision/nn_analysis/nns/")
all_models <- list.files(MODEL_PATHS, full.names = T)

all_nns <- map_df(all_models, function(x) {read_csv(x) %>% mutate(path = x)}) %>% 
  mutate(model_type = case_when(str_detect(basename(path),"kidbook") ~ "kid", 
                                str_detect(basename(path),"coca") ~ "coca"),
         run = str_extract(str_extract(path, "_\\d+\\.csv"), "\\d+"),
         run = case_when(is.na(run) ~ "1", TRUE ~ run)) %>%
    select(-path)

tidy_nns <- all_nns %>%
  filter(word1 != word2) %>%
  group_by(model_type, run, gender_type, word1) %>%
  arrange(-cos_dist) 

all_nns %>%
  filter(word1 != word2) %>%
  filter(model_type == "kid") %>%
  DT::datatable(caption = "kid")

all_nns %>%
  filter(word1 != word2) %>%
  filter(model_type == "coca", run == "1") %>%
  DT::datatable(caption = "coca1")