# the variance is computed when merging results for these attributes 
VAL_ATTR_VARIANCE = [ :area_under_roc, :percent_correct, :root_mean_squared_error, :mean_absolute_error, :r_square, :accuracy  ]
VAL_ATTR_RANKING = [ :area_under_roc, :percent_correct, :true_positive_rate, :true_negative_rate, :accuracy ]

ATTR_NICE_NAME = {}

class String
  def nice_attr()
    if ATTR_NICE_NAME.has_key?(self)
      return ATTR_NICE_NAME[self]
    else
      return self.to_s.gsub(/_id$/, "").gsub(/_/, " ").capitalize
    end
  end
end


class Object
  
  def to_nice_s
    if is_a?(Float)
      if self>0.01
        return "%.2f" % self
      else
        return self.to_s
      end
    end
    return collect{ |i| i.to_nice_s  }.join(", ") if is_a?(Array)
    return collect{ |i,j| i.to_nice_s+": "+j.to_nice_s  }.join(", ") if is_a?(Hash)
    return to_s
  end
  
  
  # checks weather an object has equal values as stored in the map
  # example o.att = "a", o.att2 = 12, o.has_values?({ att => a }) is true
  #
  # call-seq:
  #   has_values?(map) => boolean
  # 
  def has_values?(map)
    map.each { |k,v| return false if send(k)!=v }
    return true
  end
end


module Reports
  
  # = Reports::Validation
  #
  # contains all values of a validation object
  #
  class Validation
    
    @@validation_access = Reports::ValidationDB.new
    
    # for overwriting validation source (other than using webservices)
    def self.reset_validation_access(validation_access)
      @@validation_access = validation_access
    end
    
    def self.resolve_cv_uris(validation_uris)
      @@validation_access.resolve_cv_uris(validation_uris)
    end
    
    # create member variables for all validation properties
    @@validation_attributes = Lib::ALL_PROPS + 
      VAL_ATTR_VARIANCE.collect{ |a| (a.to_s+"_variance").to_sym } +
      VAL_ATTR_RANKING.collect{ |a| (a.to_s+"_ranking").to_sym }
    @@validation_attributes.each{ |a| attr_accessor a } 
  
    attr_reader :predictions
    
    def initialize(uri = nil)
      @@validation_access.init_validation(self, uri) if uri
    end
  
    # returns/creates predictions, cache to save rest-calls/computation time
    #
    # call-seq:
    #   get_predictions => Reports::Predictions
    # 
    def get_predictions
      return @predictions if @predictions
      unless @prediction_dataset_uri
        LOGGER.info("no predictions available, prediction_dataset_uri not set")
        return nil
      end
      @predictions = @@validation_access.get_predictions( self )
    end
    
    # returns the predictions feature values (i.e. the domain of the class attribute)
    #
    def get_prediction_feature_values
      return @prediction_feature_values if @prediction_feature_values
      @prediction_feature_values = @@validation_access.get_prediction_feature_values(self) 
    end
    
    # is classification validation? cache to save resr-calls
    #
    def classification?
      return @is_classification if @is_classification!=nil
      @is_classification = @@validation_access.classification?(self) 
    end
    
    def predicted_variable
      return @predicted_variable if @predicted_variable!=nil
      @predicted_variable = @@validation_access.predicted_variable(self) 
    end
    
    # loads all crossvalidation attributes, of the corresponding cv into this object 
    def load_cv_attributes
      raise "crossvalidation-id not set" unless @crossvalidation_id
      @@validation_access.init_cv(self)
    end
    
    def clone_validation
      new_val = clone
      VAL_ATTR_VARIANCE.each { |a| new_val.send((a.to_s+"_variance=").to_sym,nil) }
      return new_val
    end
  end
  
  # = Reports:ValidationSet
  #
  # contains an array of validations, including some functionality as merging validations..
  #
  class ValidationSet
    
    def initialize(validation_uris = nil)
      @unique_values = {}
      validation_uris = Reports::Validation.resolve_cv_uris(validation_uris) if validation_uris
      @validations = Array.new
      validation_uris.each{|u| @validations.push(Reports::Validation.new(u))} if validation_uris
    end
    
    def get(index)
      return @validations[index]
    end
    
    #def first()
      #return @validations.first
    #end
    
    # returns the values of the validations for __attribute__
    # * if unique is true a set is returned, i.e. not redundant info
    # * => if unique is false the size of the returned array is equal to the number of validations  
    #
    # call-seq:
    #   get_values(attribute, unique=true) => array
    # 
    def get_values(attribute, unique=true)
      a = Array.new
      @validations.each{ |v| a.push(v.send(attribute)) if !unique || a.index(v.send(attribute))==nil } 
      return a
    end
    
    # returns the number of different values that exist for an attribute in the validation set  
    #
    # call-seq:
    #   num_different_values(attribute) => integer
    # 
    def num_different_values(attribute)
      return get_values(attribute).size
    end
    
    # returns true if at least one validation has a nil value for __attribute__  
    #
    # call-seq:
    #   has_nil_values?(attribute) => boolean
    # 
    def has_nil_values?(attribute)
      @validations.each{ |v| return true unless v.send(attribute) } 
      return false
    end
    
    # loads the attributes of the related crossvalidation into all validation objects
    #
    def load_cv_attributes
      @validations.each{ |v| v.load_cv_attributes }
    end
    
    def unique_value(validation_prop)
      return @unique_values[validation_prop] if @unique_values.has_key?(validation_prop)
      val = @validations[0].send(validation_prop)        
      (1..@validations.size-1).each do |i|
          if @validations[i].send(validation_prop)!=val
            val = nil
            break
          end
      end
      @unique_values[validation_prop] = val
      return val
    end
    
    def get_true_prediction_feature_value
      if all_classification?
        class_values = get_prediction_feature_values
        if class_values.size == 2
          (0..1).each do |i|
            return class_values[i] if (class_values[i].to_s.downcase == "true" || class_values[i].to_s.downcase == "active")
          end
        end
      end
      return nil
    end
    
    def get_prediction_feature_values
      return unique_value("get_prediction_feature_values")
    end
    
    # checks weather all validations are classification validations
    #
    def all_classification?
      return unique_value("classification?")
    end

    # checks weather all validations are regression validations
    #
    def all_regression?
      # WARNING, NOT TRUE: !all_classification == all_regression? 
      return unique_value("classification?")==false
    end
    
    # returns a new set with all validation that have values as specified in the map
    #
    # call-seq:
    #   filter(map) => Reports::ValidationSet
    # 
    def filter(map)
      new_set = Reports::ValidationSet.new
      validations.each{ |v| new_set.validations.push(v) if v.has_values?(map) }
      return new_set
    end
    
    # returns a new set with all validation that the attached block accepted
    # e.g. create set with predictions: collect{ |validation| validation.get_predictions!=null } 
    #
    # call-seq:
    #   filter_proc(proc) => Reports::ValidationSet
    # 
    def collect
      new_set = Reports::ValidationSet.new
      validations.each{ |v| new_set.validations.push(v) if yield(v) }
      return new_set
    end
    
    # returns an array, with values for __attributes__, that can be use for a table
    # * first row is header row
    # * other rows are values
    #
    # call-seq:
    #   to_array(attributes, remove_nil_attributes) => array
    # 
    def to_array(attributes, remove_nil_attributes=true, true_class_value=nil)
      array = Array.new
      array.push(attributes.collect{|a| a.to_s.nice_attr})
      attribute_not_nil = Array.new(attributes.size)
      @validations.each do |v|
        index = 0
        array.push(attributes.collect do |a|
          if VAL_ATTR_VARIANCE.index(a)
            variance = v.send( (a.to_s+"_variance").to_sym )
          end
          variance = " +- "+variance.to_nice_s if variance
          attribute_not_nil[index] = true if remove_nil_attributes and v.send(a)!=nil
          index += 1
          val = v.send(a)
          val = val[true_class_value] if true_class_value!=nil && val.is_a?(Hash) && Lib::VAL_CLASS_PROPS_PER_CLASS_COMPLEMENT_EXISTS.index(a)!=nil
          val.to_nice_s + variance.to_s
        end)
      end
      if remove_nil_attributes #delete in reverse order to avoid shifting of indices
        (0..attribute_not_nil.size-1).to_a.reverse.each do |i|
          array.each{|row| row.delete_at(i)} unless attribute_not_nil[i]
        end
      end
      return array
    end
    
    # creates a new validaiton set, that contains merged validations
    # all validation with equal values for __equal_attributes__ are summed up in one validation, i.e. merged 
    #
    # call-seq:
    #   to_array(attributes) => array
    # 
    def merge(equal_attributes)
      new_set = Reports::ValidationSet.new
      
      # unique values stay unique when merging
      # derive unique values before, because model dependent props cannot be accessed later (when mergin validations from different models)
      new_set.unique_values = @unique_values
      
      #compute grouping
      grouping = Reports::Util.group(@validations, equal_attributes)
  
      Lib::MergeObjects.register_merge_attributes( Reports::Validation,
        Lib::VAL_MERGE_AVG,Lib::VAL_MERGE_SUM,Lib::VAL_MERGE_GENERAL) unless 
          Lib::MergeObjects.merge_attributes_registered?(Reports::Validation)
  
      #merge
      grouping.each do |g|
        new_set.validations.push(g[0].clone_validation)
        g[1..-1].each do |v|
          new_set.validations[-1] = Lib::MergeObjects.merge_objects(new_set.validations[-1],v)
        end
      end
      
      return new_set
    end
    
    # creates a new validaiton set, that contains a ranking for __ranking_attribute__
    # (i.e. for ranking attribute :acc, :acc_ranking is calculated)
    # all validation with equal values for __equal_attributes__ are compared
    # (the one with highest value of __ranking_attribute__ has rank 1, and so on) 
    #
    # call-seq:
    #   compute_ranking(equal_attributes, ranking_attribute) => array
    # 
    def compute_ranking(equal_attributes, ranking_attribute, class_value=nil )
    
      new_set = Reports::ValidationSet.new
      (0..@validations.size-1).each do |i|
        new_set.validations.push(@validations[i].clone_validation)
      end
      
      grouping = Reports::Util.group(new_set.validations, equal_attributes)
      grouping.each do |group|
  
        # put indices and ranking values for current group into hash
        rank_hash = {}
        (0..group.size-1).each do |i|
          val = group[i].send(ranking_attribute)
          if val.is_a?(Hash)
            if class_value != nil
              raise "no value for class value "+class_value.class.to_s+" "+class_value.to_s+" in hash "+val.inspect.to_s unless val.has_key?(class_value)
              val = val[class_value]
            else
              raise "is a hash "+ranking_attribute+", specify class value plz"
            end
          end
          rank_hash[i] = val
        end
              
        # sort group accrording to second value (= ranking value)
        rank_array = rank_hash.sort { |a, b| b[1] <=> a[1] } 
        
        # create ranks array
        ranks = Array.new
        (0..rank_array.size-1).each do |j|
          
          val = rank_array.at(j)[1]
          rank = j+1
          ranks.push(rank.to_f)
          
          # check if previous ranks have equal value
          equal_count = 1;
          equal_rank_sum = rank;
          
          while ( j - equal_count >= 0 && (val - rank_array.at(j - equal_count)[1]).abs < 0.0001 )
            equal_rank_sum += ranks.at(j - equal_count);
            equal_count += 1;
          end
          
          # if previous ranks have equal values -> replace with avg rank
          if (equal_count > 1)
            (0..equal_count-1).each do |k|
              ranks[j-k] = equal_rank_sum / equal_count.to_f;            
            end
          end
        end
        
        # set rank as validation value
        (0..rank_array.size-1).each do |j|
          index = rank_array.at(j)[0]
          group[index].send( (ranking_attribute.to_s+"_ranking=").to_sym, ranks[j])
        end
      end
      
      return new_set
    end
    
    def size
      return @validations.size
    end
    
    def validations
      @validations
    end
    
    protected
    def unique_values=(unique_values)
      @unique_values = unique_values
    end
  end
  
end