#!/usr/bin/env python
##############################################################
#
# Name: recommend.py
#
# Description: recommendation class
#              (1)The recommendation is ranking based
#              This means item is ranked according to relevant to
#              the target user preference.
#              (2)This class is methond independent
# Usage: see testRec
#
# Author: Jun Wang j.wang@ewi.tudelft.nl  Sept. 2005
#
##############################################################
import sys, math

from skotvdataread import readSKOData
from common import DictList
from similarity import simMeasure

class recommend:
    """Recommendation"""
    def __init__(self,My_preference = []):
        self.My_preference = My_preference
        self.Relevant_items = []

    def loadMyPreference(self,My_preference):
        self.My_preference = My_preference
    
    def getMyPreference(self):
        """get My Preference"""
        return self.My_preference
    

    def loadOtherUserPreference(self, Other_user_preference):
        self.Other_user_preference = Other_user_preference
        
    def getOtherUserPreference(self):
        return self.Other_user_preference
    
    
    def computeRec(self, My_method):
        self.Relevant_items = My_method.U2IRelevance\
                              (self.My_preference,self.Other_user_preference)
        return self.Relevant_items
        
def testRec():
    #load user preference data
    User_profiles = readSKOData(100)
    #sort item_id for each user
    for user in User_profiles.keys():
        temp = DictList(User_profiles[user])
        #temp._shift()
        temp.sortedby('item_id',order = 'increase')
        User_profiles[user] = temp
        del temp
    targetUser = User_profiles.pop(99)


    measure = simMeasure()
    rec = recommend(targetUser)
    rec.loadOtherUserPreference(User_profiles)
    Relevant_items = rec.computeRec(measure)
    print 'recommended item list:'
    for i in range(len(Relevant_items)):
        print '[rank:%d,item_id:%d]' % \
                   (Relevant_items[i]['rank']*100, Relevant_items[i]['item_id'] )
    
if '__main__'==__name__:
    testRec()