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Contents
# frozen_string_literal: true
# Methods that calculate something
module AICalculate
##
# Calculate and return list1 and list2
# * return list1 (Array) List with all the rows from the table
# * return list2 (Array) List with similar rows (same table name) from the neighbours tables
# @param p_table (Table)
# rubocop:disable Metrics/MethodLength
# rubocop:disable Metrics/AbcSize
def get_list1_and_list2_from(p_table)
# create <list1> with all the rows from the table
list1 = []
count = 1
p_table.rows.each do |i|
list1 << { id: count, weight: 0, data: i }
count += 1
end
# create a <list2> with similar rows (same table name) from the neighbours tables
list2 = []
concept.neighbors.each do |n|
n[:concept].tables.each do |t2|
next if t2.name != p_table.name
t2.rows.each do |i|
list2 << { id: count, weight: 0, data: i }
count += 1
end
end
end
[list1, list2]
end
# rubocop:enable Metrics/MethodLength
# rubocop:enable Metrics/AbcSize
def calculate_nearness_between_texts(text1, text2)
return 0.0 if text2.nil? || text2.empty?
words = text1.split(' ')
count = 0
words.each { |w| count += 1 if text2.include?(w) }
(count * 100 / words.count)
end
# rubocop:disable Metrics/MethodLength
# rubocop:disable Metrics/AbcSize
def reorder_list_with_row(list, row)
# evaluate every row of the list2
list.each do |r|
if r[:id] == row[:id]
r[:weight] = -300
else
val = 0
s = row[:data].count
s.times do |i|
val += calculate_nearness_between_texts(row[:data][i], r[:data][i])
end
val /= s
r[:weight] = val
end
end
list.sort! { |a, b| a[:weight] <=> b[:weight] }
list.reverse!
end
# rubocop:enable Metrics/MethodLength
# rubocop:enable Metrics/AbcSize
end
Version data entries
27 entries across 27 versions & 1 rubygems