简单按照计划生成客户

Question

我正在尝试使用 Simpy v3 模拟特定时间的客户到达(不是根据统计分布生成的(。到达时间在我加载到 pandas 数据帧中的 csv 文件中定义。

在之前的 Simpy (v2.2( 版本中，激活函数"at"有一个参数，它将在特定实例中激活客户 activate(c,c.visit(timeInBank),at=5.0) .如何在 Simpy 版本 3 中执行此操作？

数据帧"df"传递每个客户的到达时间

df.head()
arrival_time  start_service  end_service  waiting_time  service_duration
09:00:20      09:01:00       09:06:00     0.40      5.00
09:01:00      09:02:20       09:04:00     1.20      1.40 

.

import random
import simpy
import pandas as pd `
def source(env, df, counter):
    for i, row in df.iterrows():
        c = client(env, 'Client%02d' % i, counter, row,time_in_bank=row["service_duration"])
        env.process(c)   
def client(env, name, counter, row, time_in_bank):
    arrive = env.now # probably some changes to be done here
    print('%s arrived at %7.4f' % (name,arrive))
    with counter.request() as req:
        results = yield req
        wait = env.now - row["waiting_time"]
        print('%s waited %6.3f' % (name, wait))
        yield env.timeout(time_in_bank)
        print('%s exited the office at %7.4f' % (name, env.now))

df = pd.read_csv("arrivals.csv",sep=",",header=0)
env = simpy.Environment()
counter = simpy.Resource(env, capacity=1)
env.process(source(env, df.head(), counter))
env.run()

Answer 1

simpy.util 中有一个start_delayed函数，可能适合您的需求。

import random
import simpy
from simpy.util import start_delayed
import pandas as pd
def source(env, df, counter):
    for i, row in df.iterrows():
        c = client(env, 'Client%02d' % i, counter, row,time_in_bank=row["service_duration"])
        # Some code to format timestamp to seconds
        delay = timestamp_to_seconds(row["arrival_time"])
        start_delayed(env, c, delay)   
def client(env, name, counter, row, time_in_bank):
    arrive = env.now # probably some changes to be done here
    print('%s arrived at %7.4f' % (name,arrive))
    with counter.request() as req:
        results = yield req
        wait = env.now - row["waiting_time"]
        print('%s waited %6.3f' % (name, wait))
        yield env.timeout(time_in_bank)
        print('%s exited the office at %7.4f' % (name, env.now))

df = pd.read_csv("arrivals.csv",sep=",",header=0)
env = simpy.Environment()
counter = simpy.Resource(env, capacity=1)
env.process(source(env, df.head(), counter))
env.run()