import os
import json
import datetime
import pandas as pd
import networkx as nx
from libcity.utils import ensure_dir
from logging import getLogger
from libcity.evaluator.abstract_evaluator import AbstractEvaluator
[docs]class MapMatchingEvaluator(AbstractEvaluator):
def __init__(self, config):
self.metrics = config['metrics'] # 评估指标, 是一个 list
self.allowed_metrics = ['RMF', 'AN', 'AL']
self.config = config
self.save_modes = config.get('save_modes', ['csv', 'json'])
self.multi_traj = config.get('multi_traj', False)
self.evaluate_result = {} # 每一种指标的结果
self._check_config()
self._logger = getLogger()
self.rel_info = {}
self.rd_nwk = None
self.route = None
self.result = None
self.merged_result = None
self.lcs = None
def _check_config(self):
if not isinstance(self.metrics, list):
raise TypeError('Evaluator type is not list')
for metric in self.metrics:
if metric not in self.allowed_metrics:
raise ValueError('the metric {} is not allowed in TrafficStateEvaluator'.format(str(metric)))
[docs] def collect(self, batch):
"""
Args:
batch: {'route': ground truth, 'result': matched result, 'rd_nwk': road network}
set self.rd_nwk, self.result, self.rel_info,
set self.merged_result based on self.result and self.rd_nwk
set truth_sequence and self.lcs if we have ground truth
"""
# self.rd_nwk
self.rd_nwk = batch["rd_nwk"]
# self.route (optional)
if batch["route"] is not None:
self.route = batch["route"]
else:
self.route = None
# self.result
self.result = batch["result"]
# self.rel_info
for point1 in self.rd_nwk.adj:
for point2 in self.rd_nwk.adj[point1]:
geo = self.rd_nwk.adj[point1][point2]
self.rel_info[geo['geo_id']] = {}
self.rel_info[geo['geo_id']]["distance"] = geo['distance']
self.rel_info[geo['geo_id']]['point1'] = point1
self.rel_info[geo['geo_id']]['point2'] = point2
# self.merged_result
self.merge_result()
if self.route is not None:
# find the longest common subsequence
self.find_lcs()
[docs] def evaluate(self):
"""
evaluation saved at self.evaluate_result
"""
for usr_id, usr_value in self.route.items():
for traj_id, route in usr_value.items():
route = route[:, 1]
lcs = self.lcs[usr_id][traj_id]
merged_result = self.merged_result[usr_id][traj_id]
if 'RMF' in self.metrics:
d_plus = 0
d_sub = 0
d_total = 0
for rel_id in route:
d_total += self.rel_info[rel_id]['distance']
i = j = k = 0
while i < len(lcs):
while route[j] != lcs[i]:
d_sub += self.rel_info[route[j]]['distance']
j += 1
i += 1
j += 1
i = 0
while j < len(route):
d_sub += self.rel_info[route[j]]['distance']
j += 1
while i < len(lcs):
while merged_result[k] != lcs[i]:
d_plus += self.rel_info[merged_result[k]]['distance']
k += 1
i += 1
k += 1
while k < len(merged_result):
d_sub += self.rel_info[merged_result[k]]['distance']
k += 1
RMF = (d_plus + d_sub) / d_total
if usr_id not in self.evaluate_result.keys():
self.evaluate_result[usr_id] = {traj_id: {'RMF': RMF}}
else:
self.evaluate_result[usr_id][traj_id] = {'RMF': RMF}
if 'AN' in self.metrics:
AN = len(lcs) / len(route)
self.evaluate_result[usr_id][traj_id]['AN'] = AN
if 'AL' in self.metrics:
d_lcs = 0
d_tru = 0
for rel_id in lcs:
d_lcs += self.rel_info[rel_id]['distance']
for rel_id in route:
d_tru += self.rel_info[rel_id]['distance']
AL = d_lcs / d_tru
self.evaluate_result[usr_id][traj_id]['AL'] = AL
[docs] def _save_atom(self, save_path, filename):
"""
generate dyna
"""
# path
save_path = os.path.join(save_path, filename)
ensure_dir(save_path)
# open dyna
dyna_file = open(os.path.join(save_path, filename + '_reult.dyna'), 'w')
# title
if self.multi_traj:
dyna_file.write('dyna_id,type,time,entity_id,location,traj_id\n')
else:
dyna_file.write('dyna_id,type,time,entity_id,location\n')
# dyna
dyna_type = 'trajectory'
dyna_id = 0
for usr_id, usr_value in self.merged_result.items():
for traj_id, merged_result in usr_value.items():
for rel_id in merged_result:
if self.multi_traj:
dyna_file.write(str(dyna_id) + ',' + dyna_type + ',' + '' + ','
+ str(usr_id) + ',' + str(rel_id) + ',' + str(traj_id) + '\n')
else:
dyna_file.write(str(dyna_id) + ',' + dyna_type + ',' + '' + ','
+ str(usr_id) + ',' + str(rel_id) + '\n')
dyna_id += 1
# close
dyna_file.close()
# config
config = dict()
config['geo'] = dict()
config['geo']['including_types'] = ['LineString']
config['geo']['LineString'] = dict()
config['rel'] = dict()
config['rel']['including_types'] = ['geo']
config['rel']['geo'] = dict()
config['usr'] = dict()
config['usr']['properties'] = dict()
config['info'] = dict()
config['info']['geo_file'] = self.config.get('geo_file')
config['info']['rel_file'] = self.config.get('rel_file')
config['info']['dyna_file'] = self.config.get('dyna_file')
config['info']['usr_file'] = self.config.get('usr_file')
json.dump(config, open(os.path.join(save_path, 'config.json'), 'w', encoding='utf-8'),
ensure_ascii=False, indent=4)
[docs] def save_result(self, save_path, filename=None):
"""
将评估结果保存到 save_path 文件夹下的 filename 文件中
Args:
save_path: 保存路径
filename: 保存文件名
yyyy_mm_dd_hh_mm_ss_model_dataset_result.geo .rel .dyna: 模型输出(原子文件)
yyyy_mm_dd_hh_mm_ss_model_dataset_result.csv: 模型原始输出
yyyy_mm_dd_hh_mm_ss_model_dataset_result.json(geojson): 原始输出扩充得到的连通路径
yyyy_mm_dd_hh_mm_ss_model_dataset.json: 评价结果
yyyy_mm_dd_hh_mm_ss_model_dataset.csv: 评价结果
"""
ensure_dir(save_path)
# set filename
if filename is None: # 使用时间戳
filename = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S') + '_' + \
self.config['model'] + '_' + self.config['dataset']
# yyyy_mm_dd_hh_mm_ss_model_dataset_result.geo .rel .dyna: 模型输出(原子文件)
self._save_atom(save_path, filename)
# yyyy_mm_dd_hh_mm_ss_model_dataset_result.json: 模型输出(geojson)
self._logger.info('geojson is saved at ' +
os.path.join(save_path, '{}_result.json'.format(filename)))
geojson_obj = {'type': "FeatureCollection", 'features': []}
for usr_id, usr_value in self.merged_result.items():
for traj_id, merged_result in usr_value.items():
feature_i = dict()
feature_i['type'] = 'Feature'
feature_i['properties'] = {'usr_id': usr_id, 'traj_id': traj_id}
feature_i['geometry'] = {}
feature_i['geometry']['type'] = 'LineString'
feature_i['geometry']['coordinates'] = []
lat_last = None
lon_last = None
for rel_id in merged_result:
lat_origin = self.rd_nwk.nodes[self.rel_info[rel_id]["point1"]]['lat']
lon_origin = self.rd_nwk.nodes[self.rel_info[rel_id]["point1"]]['lon']
lat_destination = self.rd_nwk.nodes[self.rel_info[rel_id]["point2"]]['lat']
lon_destination = self.rd_nwk.nodes[self.rel_info[rel_id]["point2"]]['lon']
if lat_last is None and lon_last is None:
feature_i['geometry']['coordinates'].append([lon_origin, lat_origin])
feature_i['geometry']['coordinates'].append([lon_destination, lat_destination])
lat_last = lat_destination
lon_last = lon_destination
else:
if lat_last == lat_origin and lon_last == lon_origin:
feature_i['geometry']['coordinates'].append([lon_destination, lat_destination])
lat_last = lat_destination
lon_last = lon_destination
else:
feature_i['geometry']['coordinates'].append([lon_origin, lat_origin])
feature_i['geometry']['coordinates'].append([lon_destination, lat_destination])
lat_last = lat_destination
lon_last = lon_destination
geojson_obj['features'].append(feature_i)
json.dump(geojson_obj, open(save_path + '/' + filename + '_result.json', 'w', encoding='utf-8'),
ensure_ascii=False, indent=4)
if self.route is not None:
# evaluate
self.evaluate()
# yyyy_mm_dd_hh_mm_ss_model_dataset.json: 评价结果
if 'json' in self.save_modes:
self._logger.info('Evaluate result is ' + json.dumps(self.evaluate_result))
with open(os.path.join(save_path, '{}.json'.format(filename)), 'w') as f:
json.dump(self.evaluate_result, f, indent=4)
self._logger.info('Evaluate result is saved at ' +
os.path.join(save_path, '{}.json'.format(filename)))
# yyyy_mm_dd_hh_mm_ss_model_dataset.csv: 评价结果
csv_res = []
if 'csv' in self.save_modes:
for usr_id, usr_value in self.evaluate_result.items():
for traj_id, _ in usr_value.items():
csv_res_i = [usr_id, traj_id]
for metric in self.metrics:
csv_res_i.append(self.evaluate_result[usr_id][traj_id][metric])
csv_res.append(csv_res_i)
df = pd.DataFrame(csv_res)
df.columns = ['usr_id', 'traj_id'] + self.allowed_metrics
df.to_csv(os.path.join(save_path, '{}.csv'.format(filename)), index=False)
self._logger.info('Evaluate result is saved at ' +
os.path.join(save_path, '{}.csv'.format(filename)))
self._logger.info("\n" + str(df))
[docs] def find_lcs(self):
"""
self.merged_result + self.route => self.lcs
Returns:
"""
self.lcs = {}
for usr_id, usr_value in self.route.items():
for traj_id, result in usr_value.items():
seq1 = result[:, 1]
seq2 = self.merged_result[usr_id][traj_id]
len1, len2 = len(seq1), len(seq2)
res = [[0 for _ in range(len1 + 1)] for _ in range(len2 + 1)] # python 初始化二维数组 [len1+1],[len2+1]
for i in range(1, len2 + 1): # 开始从1开始，到len2+1结束
for j in range(1, len1 + 1): # 开始从1开始，到len2+1结束
if seq2[i - 1] == seq1[j - 1]:
res[i][j] = res[i - 1][j - 1] + 1
else:
res[i][j] = max(res[i - 1][j], res[i][j - 1])
lcs = []
i, j = len2, len1
while i > 0 and j > 0:
# 开始从1开始，到len2+1结束
if seq2[i - 1] == seq1[j - 1]:
lcs.append(seq2[i - 1])
i = i - 1
j = j - 1
else:
if res[i - 1][j] > res[i][j - 1]:
i = i - 1
elif res[i - 1][j] < res[i][j - 1]:
j = j - 1
else:
i = i - 1
lcs.reverse()
if usr_id not in self.lcs.keys():
self.lcs[usr_id] = {traj_id: lcs}
else:
self.lcs[usr_id][traj_id] = lcs
[docs] def merge_result(self):
"""
merge breaks in self.result.
and the output will be saved at self.merged_result
"""
self.merged_result = {}
for usr_id, usr_value in self.result.items():
for traj_id, result in usr_value.items():
result = list(result[:, 1])
result = list(filter(None, result))
merged_result = []
i = 0
last_road = None
last_point = None
while i < len(result):
if last_road is not None:
if last_road == result[i]:
i += 1
else:
if last_point != self.rel_info[result[i]]['point1']:
try:
path = nx.dijkstra_path(self.rd_nwk,
source=last_point,
target=self.rel_info[result[i]]['point1'],
weight='distance')
j = 0
while j < len(path) - 1:
point1 = path[j]
point2 = path[j + 1]
for rel_id in self.rel_info.keys():
if self.rel_info[rel_id]["point1"] == point1 and \
self.rel_info[rel_id]["point2"] == point2:
merged_result.append(rel_id)
break
j += 1
merged_result.append(result[i])
except:
# shortest_path does not exist
merged_result.append(result[i])
else:
merged_result.append(result[i])
last_road = result[i]
last_point = self.rel_info[result[i]]['point2']
i += 1
else:
merged_result.append(result[i])
last_road = result[i]
last_point = self.rel_info[result[i]]['point2']
i += 1
if usr_id not in self.merged_result.keys():
self.merged_result[usr_id] = {traj_id: merged_result}
else:
self.merged_result[usr_id][traj_id] = merged_result