Error(s) in re-building vignettes:
  ...
--- re-building ‘stoRy.Rmd’ using rmarkdown

		Information on package 'stoRy'

Description:

Package:                   stoRy
Title:                     Download, Explore, and Analyze Literary
                           Theme Ontology Data
Version:                   0.2.0
Date:                      2021-11-02
Authors@R:                 c(person(given = "Paul", family =
                           "Sheridan", role = c("aut", "cre"), email =
                           "paul.sheridan.stats@gmail.com", comment =
                           c(ORCID = "0000-0002-5484-1951")),
                           person(given = "Oshan", family = "Modi",
                           role = "aut"), person(given = "Mikael",
                           family = "Onsjö", role = "aut"))
Description:               Download, explore, and analyze Literary
                           Theme Ontology themes and thematically
                           annotated story data. To learn more about
                           the project visit
                           <https://github.com/theme-ontology/theming>
                           and <https://themeontology.org>.
License:                   GPL-3
URL:                       https://github.com/theme-ontology/stoRy,
                           https://github.com/theme-ontology/theming,
                           https://themeontology.org/
BugReports:                https://github.com/theme-ontology/stoRy/issues
Depends:                   R (>= 3.5.0)
Imports:                   cli, crayon, dplyr, fansi, httr, lifecycle,
                           purrr, R6, rappdirs, readr, rlang, stringr,
                           tibble, tidyjson, tidyr, utils
Suggests:                  covr, curl, isa2, jsonlite, knitr, progress,
                           rmarkdown, testthat
VignetteBuilder:           knitr
Config/testthat/edition:   3
Encoding:                  UTF-8
RoxygenNote:               7.1.2
NeedsCompilation:          no
Packaged:                  2021-11-07 23:27:21 UTC; Paul
Author:                    Paul Sheridan [aut, cre]
                           (<https://orcid.org/0000-0002-5484-1951>),
                           Oshan Modi [aut], Mikael Onsjö [aut]
Maintainer:                Paul Sheridan
                           <paul.sheridan.stats@gmail.com>
Repository:                CRAN
Date/Publication:          2021-11-08 05:10:02 UTC
Built:                     R 4.3.0; ; 2023-03-17 12:30:30 UTC; unix

Index:

Collection              R6 class representing a collection of LTO
                        thematically annotated stories
Story                   R6 class representing an LTO thematically
                        annotated story
Theme                   R6 class representing an LTO literary theme
Themeset                R6 class representing an LTO themeset
clone-lto               Clone LTO data
get_enriched_themes     Find over-represented themes in a collection
get_featured_themes     Find the most frequently occurring themes in a
                        collection
get_similar_stories     Find similar stories to a given story
get_story_clusters      Find clusters of similar stories
lto                     Work with LTO versions
lto-demo                LTO demo data
stoRy-package           stoRy: Download, Explore, and Analyze Literary
                        Theme Ontology Data
stoRy_cache             Manage cached files
stoRy_opt               Set 'stoRy' package global options

Further information is available in the following vignettes in
directory
'/home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/stoRy/doc':

stoRy: stoRy (source, pdf)

get_similar_stories           package:stoRy            R Documentation

_F_i_n_d _s_i_m_i_l_a_r _s_t_o_r_i_e_s _t_o _a _g_i_v_e_n _s_t_o_r_y

_D_e_s_c_r_i_p_t_i_o_n:

     *[Maturing]*

     'get_similar_stories' calculates the top 'n' most thematically
     similar stories to a given story.

_U_s_a_g_e:

     get_similar_stories(
       query_story,
       background_collection = NULL,
       top_n = 10,
       weights = list(choice = 3, major = 2, minor = 1),
       explicit = TRUE,
       min_freq = 1,
       blacklist = NULL,
       metric = c("hgt", "tfidf")
     )
     
_A_r_g_u_m_e_n_t_s:

query_story: A 'Story()' class object defining a story of interest.
          Thematically similar stories to this one will be returned.

background_collection: A 'Collection()' class object the stories in
          which to search for similar stories to the 'query_story'
          input story.

          If 'NULL', the collection of all stories in the actively
          loaded LTO version is used.

   top_n: Maximum number of similar stories to report. The default is
          'top_n=10'.

          If 'Inf', all stories in the background collection are
          reported.

 weights: A list assigning nonnegative weights to choice, major, and
          minor theme levels. The default weighting 'list(choice = 3,
          major = 2, minor = 1)' counts each _choice_ usage three
          times, each _major_ theme usage twice, and each _minor_ theme
          usage once. Use the uniform weighting 'list(choice = 1, major
          = 1, minor = 1)' weights theme usages equally regardless of
          level. At least one weight must be positive.

explicit: Set to 'FALSE' to include ancestor themes of the explicit
          thematic annotations.

min_freq: Drop themes occurring less than this number of times from the
          analysis. The default 'min_freq=1' results in no themes are
          discarded.

blacklist: A 'Themeset()' class object. A themeset containing themes to
          be dropped from the analysis.

          If 'NULL', no themes are filtered.

  metric: A character vector specifying the choice of weighting to use
          in the _cosine similarity_ measure used to evaluate story
          thematic similarity. Use 'metric = "hgt"' for hypergeometric
          test P-value weights and 'metric = "tfidf"' for TF-IDF
          weights.

          The default specification of 'metric = c("hgt", "tfidf")'
          results in hypergeometric test P-values being used as
          weights.

_V_a_l_u_e:

     Returns a 'tibble' with 'top_n' rows (stories) and 5 columns:

       'story_id':       'n'-th most thematically similar story to the querystory         
                                                                                          
       'title':          Reference story title                                            
       'description':    Reference story description                                      
       'score':          Cosine similarity score with hypergeometric test weights 
                         (if 'metric = "hgt"') or TF-IDF weights (if 'metric = "tfidf"'). 
       'common_themes':  List of themes common to both the query andreference story       
      
_R_e_f_e_r_e_n_c_e_s:

     Paul Sheridan, Mikael Onsjö, Claudia Becerra, Sergio Jimenez,
     Georg Dueñas (2019). _An Ontology-Based Recommender System with an
     Application to the Star Trek Television Franchise_. _Future
     Internet_, 11(9), 182. DOI: doi: 10.3390/fi11090182 (URL:
     https://doi.org/10.3390/fi11090182)

_E_x_a_m_p_l_e_s:

     ## Not run:
     
     # Retrieve the top 10 most similar stories to the classic "The Twilight
     # Zone" series episode "Nightmare at 20,000 Feet" (1959):
     set_lto("demo")
     query_story <- Story$new(story_id = "tz1959e5x03")
     result_tbl <- get_similar_stories(query_story)
     result_tbl
     
     # Retrieve the top 10 most similar stories to the classic "The Twilight 
     # Zone" series episode "Nightmare at 20,000 Feet" (1959) without taking
     # minor themes into account:
     set_lto("demo")
     query_story <- Story$new(story_id = "tz1959e5x03")
     result_tbl <- get_similar_stories(query_story, weights = list(choice = 3, major = 2, minor = 0))
     result_tbl
     
     # Retrieve the top 10 most similar stories to the classic "The Twilight 
     # Zone" series episode "Nightmare at 20,000 Feet" (1959) when implicitly
     # featured themes are included in the similarity calculation:
     set_lto("demo")
     query_story <- Story$new(story_id = "tz1959e5x03")
     result_tbl <- get_similar_stories(query_story, explicit = FALSE)
     result_tbl
     ## End(Not run)
     

lto-demo                 package:stoRy                 R Documentation

_L_T_O _d_e_m_o _d_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     A family of datasets extracted from LTO v0.3.3, comprising 2872
     LTO themes and 335 thematically annotated _The Twilight Zone_
     American media franchise stories.

     Found in the data are thematic annotations for

        • 156 _The Twilight Zone_ (1959) television series episodes

        • 3 _Twilight Zone: The Movie_ (1983) film sub-stories

        • 110 _The Twilight Zone_ (1985) television series episodes

        • 3 _Twilight Zone: Rod Serling's Lost Classics_ (1994) film
          sub-stories

        • 43 _The Twilight Zone_ (2002) television series episodes

        • 20 _The Twilight Zone_ (2019) television series episodes

_F_o_r_m_a_t:

     The data consists of four 'tibble' class objects:

       1. 'metadata_tbl': a 'tibble' of LTO demo data summary
          information with 7 rows and 2 columns:

            name:   Metadatum name (e.g. version, encoding, etc.) 
            value:  Metadatum value (e.g. "demo", "UTF-8", etc.)  
           
       2. 'themes_tbl': a 'tibble' of LTO demo data themes with 2872
          rows (themes) and 11 columns:

            theme_index:  Integer ID (unique)                       
            theme_name:   Theme name (unique)                       
            description:  Theme definition                          
            notes:        Theme definition elaborations and caveats 
            aliases:      Theme name aliases                        
            template:     Theme special cases                       
            parents:      Parent themes                             
            ancestors:    Ancestor themes                           
            examples:     Example usages                            
            references:   Reference URLs                            
            source:       Path to file where theme is defined       
           
       3. 'stories_tbl': a 'tibble' of LTO demo data stories with 335
          rows (stories) and 10 columns:

            story_index:          Integer ID (unique)                              
            story_id:             Story ID (unique)                                
            title:                Official title                                   
            date:                 Release date                                     
            description:          Information used for identifying the story       
            component_story_ids:  Sub-story story IDs (used for framestories)      
                                                                                   
            collections:          Collection IDs of collections to which the story 
                                  belongs 
            references:           Reference URLs                                   
            themes:               Thematic annotations                             
            source:               Path to file where story is defined              
           
       4. 'collections_tbl': a 'tibble' of LTO demo data collections
          with 5 rows (story collections) and 9 columns:

            collection_index:     Integer ID (unique)                                    
            collection_id:        Collection ID (unique)                                 
            title:                The collection ID stripped of all colon separated 
                                  prefixes 
            date:                 Earliest and latest dates of stories in the collection 
            description:          Minimal information defining the collection            
            component_story_ids:  Story IDs of member stories of thecollection           
                                                                                         
            references:           Reference URLs                                         
            themes:               Collection level thematic annotations                  
            source:               Path to file where collection is defined               
           
_N_o_t_e:

     The data is stored internally in the package 'R/sysdata.rda' file
     and cannot be accessed directly. Check the examples below for more
     on how to best explore the data.

_S_o_u_r_c_e:

     Theme Ontology. (2021, October 31). LTO v0.3.3.
     <https://github.com/theme-ontology/theming/releases/tag/v0.3.3>

_R_e_f_e_r_e_n_c_e_s:

     The Twilight Zone. (2021, July 25). In Wikipedia
     <https://en.wikipedia.org/wiki/The_Twilight_Zone>

_E_x_a_m_p_l_e_s:

     # Print a copy of LTO demo version metadata to console:
     set_lto("demo")
     demo_metadata_tbl <- clone_active_metadata_tbl()
     demo_metadata_tbl
     
     # Print a copy of LTO demo themes to console:
     set_lto("demo")
     demo_themes_tbl <- clone_active_themes_tbl()
     demo_themes_tbl
     
     # Print a copy of LTO demo stories to console:
     set_lto("demo")
     demo_stories_tbl <- clone_active_stories_tbl()
     demo_stories_tbl
     
     # Print a copy of LTO demo collections to console:
     set_lto("demo")
     demo_collections_tbl <- clone_active_collections_tbl()
     demo_collections_tbl
     # Print collection IDs to console:
     demo_collections_tbl$collection_id
     # Print The Twilight Zone (2019) component story IDs to console:
     library(dplyr)
     collection_id <- "Collection: tvseries: The Twilight Zone (2019)"
     demo_collections_tbl %>%
       filter(collection_id %in% !!collection_id) %>%
       pull(component_story_ids) %>%
       unlist(use.names = FALSE)
     

Quitting from lines 332-335 (stoRy.Rmd) 
Error: processing vignette ‘stoRy.Rmd’ failed with diagnostics:
DLL requires the use of native symbols
--- failed re-building ‘stoRy.Rmd’

SUMMARY: processing the following file failed:
  ‘stoRy.Rmd’

Error: Vignette re-building failed.
Execution halted