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141 lines
3.8 KiB
Ruby
141 lines
3.8 KiB
Ruby
# frozen_string_literal: true
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class ReviewableScore < ActiveRecord::Base
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belongs_to :reviewable
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belongs_to :user
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belongs_to :reviewed_by, class_name: 'User'
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belongs_to :meta_topic, class_name: 'Topic'
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# To keep things simple the types correspond to `PostActionType` for backwards
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# compatibility, but we can add extra reasons for scores.
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def self.types
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@types ||= PostActionType.flag_types.merge(
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needs_approval: 9
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)
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end
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# When extending post action flags, we need to call this method in order to
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# get the latests flags.
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def self.reload_types
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@types = nil
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types
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end
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def self.add_new_types(type_names)
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next_id = types.values.max + 1
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type_names.each_with_index do |name, idx|
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@types[name] = next_id + idx
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end
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end
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def self.statuses
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@statuses ||= Enum.new(
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pending: 0,
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agreed: 1,
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disagreed: 2,
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ignored: 3
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)
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end
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def self.score_transitions
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{
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approved: statuses[:agreed],
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rejected: statuses[:disagreed],
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ignored: statuses[:ignored]
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}
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end
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# Generate `pending?`, `rejected?`, etc helper methods
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statuses.each do |name, id|
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define_method("#{name}?") { status == id }
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self.class.define_method(name) { where(status: id) }
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end
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def score_type
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Reviewable::Collection::Item.new(reviewable_score_type)
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end
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def took_action?
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take_action_bonus > 0
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end
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def self.calculate_score(user, type_bonus, take_action_bonus)
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score = user_flag_score(user) + type_bonus + take_action_bonus
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score > 0 ? score : 0
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end
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# A user's flag score is:
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# 1.0 + trust_level + user_accuracy_bonus
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# (trust_level is 5 for staff)
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def self.user_flag_score(user)
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1.0 + (user.staff? ? 5.0 : user.trust_level.to_f) + user_accuracy_bonus(user)
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end
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# A user's accuracy bonus is:
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# if 5 or less flags => 0.0
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# if > 5 flags => (agreed flags / total flags) * 5.0
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def self.user_accuracy_bonus(user)
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user_stat = user&.user_stat
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return 0.0 if user_stat.blank? || user.bot?
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calc_user_accuracy_bonus(user_stat.flags_agreed, user_stat.flags_disagreed)
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end
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def self.calc_user_accuracy_bonus(agreed, disagreed)
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agreed ||= 0
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disagreed ||= 0
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total = (agreed + disagreed).to_f
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return 0.0 if total <= 5
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accuracy_axis = 0.7
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percent_correct = agreed / total
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positive_accuracy = percent_correct >= accuracy_axis
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bottom = positive_accuracy ? accuracy_axis : 0.0
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top = positive_accuracy ? 1.0 : accuracy_axis
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absolute_distance = positive_accuracy ?
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percent_correct - bottom :
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top - percent_correct
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axis_distance_multiplier = 1.0 / (top - bottom)
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positivity_multiplier = positive_accuracy ? 1.0 : -1.0
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(absolute_distance * axis_distance_multiplier * positivity_multiplier * (Math.log(total, 4) * 5.0))
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.round(2)
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end
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def reviewable_conversation
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return if meta_topic.blank?
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Reviewable::Conversation.new(meta_topic)
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end
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end
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# == Schema Information
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#
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# Table name: reviewable_scores
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#
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# id :bigint not null, primary key
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# reviewable_id :integer not null
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# user_id :integer not null
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# reviewable_score_type :integer not null
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# status :integer not null
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# score :float default(0.0), not null
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# take_action_bonus :float default(0.0), not null
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# reviewed_by_id :integer
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# reviewed_at :datetime
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# meta_topic_id :integer
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# created_at :datetime not null
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# updated_at :datetime not null
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# reason :string
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# user_accuracy_bonus :float default(0.0), not null
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#
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# Indexes
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#
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# index_reviewable_scores_on_reviewable_id (reviewable_id)
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# index_reviewable_scores_on_user_id (user_id)
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#
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