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nexedi
dream
Commits
11247272
Commit
11247272
authored
Oct 20, 2015
by
Georgios Dagkakis
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clean up and comments
parent
601abebe
Changes
1
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1 changed file
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30 additions
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10 deletions
+30
-10
dream/simulation/Examples/OperationalFailures.py
dream/simulation/Examples/OperationalFailures.py
+30
-10
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dream/simulation/Examples/OperationalFailures.py
View file @
11247272
...
...
@@ -4,38 +4,49 @@ import random
from
random
import
Random
Rnd
=
Random
(
3
)
# transition probabilities
p
=
0.01
g
=
0.01
r
=
0.1
f
=
0.2
# the capacity of B123
capacity
=
35
class
OpQueue
(
Queue
):
# allow to be locked between the time periods
def
canAccept
(
self
,
callerObject
=
None
):
if
self
.
locked
:
return
False
return
Queue
.
canAccept
(
self
,
callerObject
)
class
OpExit
(
Exit
):
# set numGoodParts=0 at every replication
def
initialize
(
self
):
self
.
numGoodParts
=
0
Exit
.
initialize
(
self
)
# allow to be locked between the time periods
def
canAccept
(
self
,
callerObject
=
None
):
if
self
.
locked
:
return
False
return
True
# if the status of the entity is 'Good' update numGoodParts
def
getEntity
(
self
):
activeEntity
=
Exit
.
getEntity
(
self
)
if
activeEntity
.
status
==
'Good'
:
self
.
numGoodParts
+=
1
return
activeEntity
# update the GoodExits list
def
postProcessing
(
self
):
Exit
.
postProcessing
(
self
,
MaxSimtime
=
1000.1
)
self
.
GoodExits
.
append
(
self
.
numGoodParts
)
class
OpMachine
(
Machine
):
# allow to be locked between the time periods
# also if there is failure (state=0) do not get new work
def
canAccept
(
self
,
callerObject
=
None
):
if
self
.
locked
:
return
False
...
...
@@ -43,17 +54,22 @@ class OpMachine(Machine):
return
False
return
Machine
.
canAccept
(
self
,
callerObject
)
# set state=1 at the start of each replication
def
initialize
(
self
):
Machine
.
initialize
(
self
)
self
.
state
=
1
# if the state is -1 set that the disposed Entity is 'Bad'
def
removeEntity
(
self
,
entity
):
activeEntity
=
Machine
.
removeEntity
(
self
,
entity
)
if
self
.
state
==-
1
:
activeEntity
.
status
=
'Bad'
return
activeEntity
# method invoked by the generator at every time period
def
controllerMethod
():
# for every machine calculate the state (based on transition probabilities)
for
M
in
[
M1
,
M2
,
M3
]:
rn1
=
createRandomNumber
()
rn2
=
createRandomNumber
()
...
...
@@ -68,21 +84,22 @@ def controllerMethod():
elif
M
.
state
==-
1
:
if
rn1
<
f
:
M
.
state
=
0
# unlock E and let part get from M3 to E
E
.
locked
=
False
if
len
(
M3
.
getActiveObjectQueue
())
and
(
not
M3
.
state
==
0
):
# print '----> M3->E'
Controller
.
sendSignal
(
sender
=
M3
,
receiver
=
E
,
signal
=
E
.
isRequested
)
yield
G
.
env
.
timeout
(
0
)
E
.
locked
=
True
# unlock M3 and let part get from B123 to M3
M3
.
locked
=
False
if
len
(
B123
.
getActiveObjectQueue
())
and
(
not
M3
.
state
==
0
):
# print '----> B123->M3'
Controller
.
sendSignal
(
sender
=
B123
,
receiver
=
M3
,
signal
=
M3
.
isRequested
)
yield
G
.
env
.
timeout
(
0
)
M3
.
locked
=
True
# unlock B123 and let parts get from M1 and M2 to B123
B123
.
locked
=
False
if
((
len
(
M1
.
getActiveObjectQueue
()))
and
(
not
M1
.
state
==
0
)
\
or
((
len
(
M2
.
getActiveObjectQueue
()))
and
not
M2
.
state
==
0
))
\
...
...
@@ -96,7 +113,8 @@ def controllerMethod():
if
len
(
B123
.
getActiveObjectQueue
())
==
B123
.
capacity
:
break
B123
.
locked
=
True
# unlock M1 and M2 and let parts get from NS1 to M1 and from NS2 to M2
M1
.
locked
=
False
M2
.
locked
=
False
if
len
(
M1
.
getActiveObjectQueue
())
==
0
:
...
...
@@ -105,13 +123,13 @@ def controllerMethod():
Controller
.
sendSignal
(
sender
=
NS2
,
receiver
=
M2
,
signal
=
M2
.
isRequested
)
while
1
:
yield
G
.
env
.
timeout
(
0
)
# print G.env.now, len(M1.getActiveObjectQueue()), M1.state, len(M2.getActiveObjectQueue()), M2.state
if
(
len
(
M1
.
getActiveObjectQueue
())
or
M1
.
state
==
0
)
\
and
(
len
(
M2
.
getActiveObjectQueue
())
or
M2
.
state
==
0
):
M1
.
locked
=
True
M2
.
locked
=
True
break
# returns a number from the uniform distribution (0,1)
def
createRandomNumber
():
return
Rnd
.
uniform
(
0
,
1
)
...
...
@@ -122,7 +140,7 @@ NS2=NonStarvingEntry('NS2','Entry2',entityData={'_class':'Dream.Part','status':'
M1
=
OpMachine
(
'M1'
,
'Machine1'
,
processingTime
=
{
'Fixed'
:{
'mean'
:
0.1
}})
M2
=
OpMachine
(
'M2'
,
'Machine2'
,
processingTime
=
{
'Fixed'
:{
'mean'
:
0.1
}})
M3
=
OpMachine
(
'M3'
,
'Machine3'
,
processingTime
=
{
'Fixed'
:{
'mean'
:
0.1
}})
B123
=
OpQueue
(
'B123'
,
'Queue'
,
capacity
=
10
)
B123
=
OpQueue
(
'B123'
,
'Queue'
,
capacity
=
capacity
)
E
=
OpExit
(
'E1'
,
'Exit'
)
Controller
=
EventGenerator
(
'EV'
,
'Controller'
,
start
=
0
,
interval
=
1
,
method
=
controllerMethod
)
...
...
@@ -138,9 +156,11 @@ E.defineRouting(predecessorList=[M3])
# add all the objects to a list
objectList
=
[
NS1
,
NS2
,
M1
,
M2
,
M3
,
B123
,
E
,
Controller
]
# set all objects locked at beginning
for
obj
in
objectList
:
obj
.
locked
=
True
# GoodExits will keep the number of good parts produced in every replication
E
.
GoodExits
=
[]
# call the runSimulation giving the objects and the length of the experiment
...
...
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