def load_map(self):
s = Session()
# gHase映射
self.query_geohash()
# nodes表
for n in s.query(Nodes):
if n.nid not in self.nodes:
self.nodes[n.nid] = [[n.rid],
float(n.longitude),
float(n.latitude)]
else:
self.nodes[n.nid][0].append(n.rid)
# records表
for r in s.query(Records):
self.records[r.id] = [
float(r.length), 50, 0.6852578070969514, r.oneway, r.from_node,
r.to_node
] #求平均
# for i in range(24):
for q in s.query(Quality2):
a_time = float(q.average_time)
density = float(q.density)
if self.records[q.rid][1] == 0:
self.records[q.rid][1] += a_time
else:
self.records[q.rid][1] = (a_time + self.records[q.rid][1]) / 2
if self.records[q.rid][2] == 0:
self.records[q.rid][2] = density
else:
self.records[q.rid][2] = (self.records[q.rid][2] + density) / 2
self.adj_map = self.trans_map(self.records.keys())
return self.adj_map, self.nodes
def to_db(self, allow_codes):
'''地图入库'''
# 更新
session = Session()
drop_table(Nodes, Base, engine=engine)
drop_table(Records, Base, engine=engine)
d_pos = {} #{(lon,lat):node} ，用于去重
for i, (shape, record) in enumerate(self.itrRecord()):
# if i == 100:break
points = shape.points
code = record.code
# 筛选
if code in allow_codes:
from_pos = points[0]
to_pos = points[-1]
itr = (from_pos, to_pos)
if any(self.boundery.contains_points(itr)):
# 分级存储索引
if code in self.d_level:
self.d_level[code].append(i)
else:
self.d_level[code] = [i]
l_node = []
# 存储路网
for pos in itr:
if pos in d_pos:
# 单向路判断?
node = d_pos[pos]
else:
# ind = self.get_gZone(pos)
# if ind is not None:
# self.gZone[ind].append(pos)
self.nid += 1
node = self.nid
d_pos[pos] = node
n = Nodes(id=node,
osm_id=record.osm_id,
longitude=pos[0],
latitude=pos[1],
geohash5=encode(pos[1], pos[0], 5))
session.add(n)
l_node.append(node)
r = Records(bridge=self.bool_map[record.bridge],
oneway=self.bool_map[record.oneway],
tunnel=self.bool_map[record.tunnel],
ref=record.ref,
name=record.name,
code=record.code,
fclass=record.fclass,
from_node=l_node[0],
to_node=l_node[1])
session.add(r)
record.extend(l_node) #加入属性
session.commit()
session.close()
class Cprice:
def __init__(self):
self.session = Session() #session的生命周期跟实例一样
def insert(self,**kwargs):
inst = Price(**kwargs)
self.session.add(inst)
self.session.commit()
def query(self,**kwargs):
return self.session.query(Price).filter_by(**kwargs).all()
def load_map(self):
s = Session()
# gHase映射
self.query_geohash()
# nodes表
for n in s.query(Nodes):
self.nodes.append([n.id, n.osm_id, n.longitude, n.latitude])
# records表
for r in s.query(Records):
self.records.append([r.oneway, r.from_node, r.to_node])
#self.adj_map,_ = self.trans_map(range(len(self.nodes)))
return self.adj_map, self.nodes
def get_data(day, zone):
end_day = (day + timedelta(days=7)).timestamp() #一周的时间
day = day.timestamp()
s = Session()
d_data = {} # 用字典来分段
for rst in s.query(ZoneQuality).filter(ZoneQuality.g_zone == zone).all():
date_time = rst.date_time
if (day <= date_time.timestamp() <= end_day):
hour = date_time.hour
delta = 2 - hour % 4
date_time = date_time + timedelta(hours=delta)
if date_time in d_data:
a_time, dens, flow = d_data[date_time]
d_data[date_time] = [(a_time + rst.average_speed) / 2,
(dens + rst.density) / 2,
(flow + rst.flow) / 2]
else:
d_data[date_time] = [rst.average_speed, rst.density, rst.flow]
df = pd.DataFrame(d_data).T
df.columns = ['average_speed', 'density', 'flow']
return df
class Cprice:
def __init__(self):
self.session = Session() #session的生命周期跟实例一样
def insert(self, key='url = ..', **kwargs):
var, val = key.split('=') #变量名，取值
inst = self.session.query(Price).filter(Price.href == val).first()
delta = 0 # 附带比较功能
if inst is None:
kwargs[var] = val
inst = Price(**kwargs)
self.session.add(inst)
else:
delta = self.update(inst, **kwargs)
self.session.commit()
return delta
def update(self, inst, **kwargs):
delta = kwargs['price'] - inst.price
inst.update_time = kwargs['origin_time'] #
inst.price = kwargs['price']
return delta
def get_data_1(day, zone):
day = datetime.strptime(day[:10], "%Y-%m-%d")
end_day = (day + timedelta(days=2)).timestamp() #一周的时间
day = (day - timedelta(days=5)).timestamp()
s = Session()
d_data = {} # 用字典来分段
qry = s.query(ZoneQuality_1)
for rst in qry.filter(ZoneQuality_1.g_zone == zone).all():
date_time = rst.date_time
if (day <= date_time.timestamp() <= end_day):
# hour = date_time.hour
# delta = 2 - hour%4
# date_time = date_time - timedelta(days=1)
if date_time in d_data:
a_time, dens, flow = d_data[date_time]
d_data[date_time] = [(a_time + rst.average_speed) / 2,
(dens + rst.density) / 2,
(flow + rst.flow) / 2]
else:
d_data[date_time] = [rst.average_speed, rst.density, rst.flow]
df = pd.DataFrame(d_data).T
df.columns = ['average_speed', 'density', 'flow']
return df
class Curls:
def __init__(self):
self.session = Session() #session的生命周期跟实例一样
def insert_urls(self, url, status):
insert_time = datetime.datetime.now()
inst = self.session.query(storeUrls).filter(
storeUrls.url == url).first()
if inst is None:
p = storeUrls(url=url, origin_time=insert_time, setting=status)
self.session.add(p)
self.session.commit()
else:
inst.origin_time = insert_time
self.session.commit()
def query(self, **kwargs):
return self.session.query(storeUrls).filter_by(**kwargs).all()
class Curls:
def __init__(self):
self.session = Session() #session的生命周期跟实例一样
def update(self,key='url = ..',**kwargs):
var,val = key.split('=') #变量名，取值
inst = self.session.query(storeUrls).filter(storeUrls.url == val).first()
delta = 0 # 附带比较功能
if inst is None:
kwargs[var] = val
inst = storeUrls(**kwargs)
self.session.add(inst)
else:
# inst.__dict__.update(kwargs) # 无效
for k,v in kwargs.items():
exec(f'inst.{k}="{v}"')
delta = self.update_(inst)
self.session.commit()
return delta
def update_(self,inst):
return 0
def query(self,**kwargs):
return self.session.query(storeUrls).filter_by(**kwargs).all()
def __init__(self):
self.session = Session() #session的生命周期跟实例一样
def query_geohash(self):
s = Session()
for id, ghash in s.query(Nodes.id, Nodes.geohash5).all():
self.d_gHash[ghash] = self.d_gHash.get(ghash, []) + [id]
return self.d_gHash