interactive cluster graph (spider web) visualization of TMDb movie recommendations

roassal-mondrian-movie-recommendations.st

"
For a workspace (aka playground)
Works in a Moose 6.0 image

dcorking, 2017, public domain Creative Commons CC0
"

path := '/Users/dcorking/workspace/tmdb-ruby-play/nodes.csv'.
stream := FileStream readOnlyFileNamed: path.
string := stream contents. 
stream close.
nodes_table := RTTabTable new input: string usingDelimiter: $,.


path := '/Users/dcorking/workspace/tmdb-ruby-play/edges.csv'.
stream := FileStream readOnlyFileNamed: path.
string := stream contents. 
stream close.
edges_table := RTTabTable new input: string usingDelimiter: $,.

"This works better if nodes is a dictionary".
nodeDict := Dictionary new.
"nodeDict  at: 9999 put: 'Monsters Inc'."

nodes_table values do: [ :row | nodeDict at: ((row at: 2) asInteger) put: (row at: 1)].
edges_table values do: [ :row | nodeDict at: ((row at: 3) asInteger) put: (row at: 1)].
nodeDict.

edgesArray := edges_table values collect: [  :edge |
	from_id := (edge at: 2) asInteger.
	to_id := (edge at: 3) asInteger.
	fromTitle := nodeDict at: from_id.
	toTitle := nodeDict at: to_id.
	{ fromTitle . toTitle }
	 ].

nonUniqueEdges := edgesArray collect: [ :row | (row at: 1) -> (row at: 2) ].

c := RTMondrian new.
c shape circle
  color: Color red trans.
c nodes: nodeDict.
c layout cluster.
c.

c edges source: nonUniqueEdges connectFrom: #key to: #value.
c layout cluster. 
c.

tmdb-similars-graph-2.rb

# dcorking, 2017, public domain Creative Commons CC0

require 'themoviedb-api'
require 'csv'

Tmdb::Api.key ENV['TMDB_KEY']


similars = Tmdb::Movie.similar(155).results

def edge_row_content(from_movie, to_movie)
  [ to_movie.title, from_movie.id, to_movie.id ]
end

def node_row_content(movie)
  [ movie.title, movie.id ]
end


edges_array = []
nodes_array = []

similars.each do |from_movie|
  grandchildren =
    Tmdb::Movie.similar(from_movie.id).results
  edges_array << grandchildren.collect{ |to_movie| edge_row_content(from_movie, to_movie) }
  nodes_array << node_row_content(from_movie)
end

flat_edges = edges_array.flatten(1)

CSV.open('edge.csv', 'w') do |csv|
  flat_edges.each do |row|
    csv << row
  end
end

CSV.open('nodes.csv', 'w') do |csv|
  nodes_array.each do |row|
    csv << row
  end
end