def get_home_location():
location_dict = read_file.read_location_file()
home_dict = {}
for location, data in location_dict.items():
if data['type'] == 'Home (private)':
home_dict[location] = data
return home_dict
def recommend():
unknown_user_checkins_dict = read_file.read_checkins_file('unknown_user')
location_info_dict = read_file.read_location_file()
average_location_dict = get_average_location(unknown_user_checkins_dict,
location_info_dict)
candidate_location_distance_dict = compute_distance(
average_location_dict, location_info_dict)
result_rank = rank_candidate_location(candidate_location_distance_dict)
return result_rank
def get_candidate_category():
candidate_data = read_file.read_candidate_file()
location_data = read_file.read_location_file()
candidate_category_dic = {}
for single_candidate in candidate_data:
for location_key, location_value in location_data.items():
if single_candidate == location_key:
candidate_category_dic[single_candidate] = location_value[
"type"]
category_data = load_category()
result_dic = {}
for candidate_key, candidate_value in candidate_category_dic.items():
for high_category in category_data["response"]["categories"]:
for mid_category in high_category["categories"]:
if candidate_value == mid_category["name"]:
result_dic[candidate_key] = {}
result_dic[candidate_key]["category"] = high_category[
"name"]
if mid_category["categories"] != []:
for low_category in mid_category["categories"]:
if candidate_value == low_category["name"]:
result_dic[candidate_key] = {}
result_dic[candidate_key][
"category"] = mid_category["name"]
if low_category["categories"] != []:
for last_category in low_category["categories"]:
if candidate_value == last_category["name"]:
result_dic[candidate_key] = {}
result_dic[candidate_key][
"category"] = low_category["name"]
candidate_popularity_list = popularity_recommendation.candidate_popularity(
)
for single_result_key, single_result_value in result_dic.items():
count = 0
for candidate_popularity in candidate_popularity_list:
count += 1
if single_result_key == candidate_popularity:
result_dic[single_result_key]["popularity"] = count
#pprint.pprint(result_dic)
return result_dic
def compute_distance(user_home_location_dict):
candidate_list = read_file.read_candidate_file()
location_info_dict = read_file.read_location_file()
candidate_location_distance_dict = {}
for user_name, home_location in user_home_location_dict.items():
candidate_location_distance_dict[user_name] = {}
for candidate_location in candidate_list:
# candidate location
candidate_position = (
location_info_dict[candidate_location]['latitude'],
location_info_dict[candidate_location]['longitude'])
# user home location
home_position = (home_location['latitude'],
home_location['longitude'])
distance_number = distance.distance(candidate_position,
home_position).miles
candidate_location_distance_dict[user_name][
candidate_location] = distance_number
return candidate_location_distance_dict
def knownUser_unKnownLocation():
# 3884 known users with 100 unknown location
new_dic = {}
known_user_data = read_file.read_checkins_file("known_user")
known_user_list = list(known_user_data.keys())
loc_list = []
pprint.pprint("test")
for keyname, valuename in known_user_data.items():
for dailyvalue in valuename:
for eachvalue in dailyvalue:
eachloc = eachvalue["location"]
loc_list.append(eachloc)
new_dic[keyname] = loc_list
pprint.pprint("test2")
##pprint.pprint(new_dic)
pprint.pprint("test3")
known_loc = read_file.read_location_file()
pprint.pprint("test4")
user_dict = {}
for keyname, listvalue in new_dic.items():
user_dict[keyname] = {}
for locKey in known_loc.keys():
user_dict[keyname][locKey] = 0
for value in listvalue:
user_dict[keyname][value] += 1
pprint.pprint("loop2")
pprint.pprint(user_dict["9448"])
unknown_loc = read_file.read_candidate_file()
knownUser_unknownLoc = (len(known_user_data), len(unknown_loc)
) #(2,3,4)变为3维
maxtrix_knownUser_unknownLoc = np.zeros(knownUser_unknownLoc)
#pprint.pprint(np.zeros(knownUser_unknownLoc))
##pprint.pprint("build zero matrix")
'''
def get_person_location_type():
user_data = read_file.read_checkins_file("unknown_user")
location_data = read_file.read_location_file()
user_location_dic = {}
for user_id,user_location in user_data.items():
user_location_dic[user_id] = []
for daily_location in user_location:
for location in daily_location:
if location["location"] != "?":
location_type = location_data[location["location"]]["type"]
if "\x1a\x1a" in location_type:
location_type = "Café"
user_location_dic[user_id].append(location_type)
for user_id,user_location_type in user_location_dic.items():
user_location_dic[user_id] = {}
for single_location_type in user_location_type:
user_location_dic[user_id][single_location_type] = user_location_type.count(single_location_type)
#pprint.pprint(user_location_dic)
return user_location_dic