def run_interval(model,loop_index,interval,VOI,edges,ind_cons,
double_list,case):
# Load the model.
vensim.load_model(model)
case = copy.deepcopy(case)
set_lookups(case)
for key,value in case.items():
vensim.set_value(key,repr(value))
'Active causes', 'Subscripts', 'Combination Subscripts', 'Minimum value',
'Maximum value', 'Range', 'Variable type', 'Main group']
attributes = range(len(attributeNames))
attributesInterest = [3, 1, 2, 12]
varTypeNames = ['All', 'Levels', 'Auxiliary', 'Data', 'Initial', 'Constant', 'Lookup',
'Group', 'Subscript Ranges', 'Constraint', 'Test Input', 'Time Base',
'Gaming']
varTypes = range(len(varTypeNames))
varTypes[0:2] = [1] # Do not look at all types
varTypes[4:] = [5] # Do not look after lookup
print 'Vensim file: '+ vensimRootName + vensimFileName + vensimExtension
print 'CSV file: '+ vensimRootName + csvFileName
print 'Converting starts...'
load_model(vensimRootName + vensimFileName + vensimExtension)
with open (vensimRootName + csvFileName, 'wb') as f:
writer = csv.writer(f)
writer.writerow(firstLine) # The first lines are written
writer.writerow(secondLine)
writer.writerow(thirdLine)
writer.writerow(blank)
writer.writerow(csvArray)
for varType in varTypes: # Now get the variables per type
type = varTypeNames[varType]
typeNr = varType
varNames = get_varnames(0, varType)
for varName in varNames: # per name, look in to their attributes
csvArray[0]=lineNumber # setup the line which needs to go to the csv
csvArray[1]=varName
def run_interval(model,loop_index,interval,VOI,edges,ind_cons,
double_list,case):
# Load the model.
vensim.load_model(model)
case = copy.deepcopy(case)
set_lookups(case)
for key,value in case.items():
vensim.set_value(key,repr(value))
# print key, repr(value), vensim.get_val(key), value-vensim.get_val(key)
# We run the model in game mode.
step = vensim.get_val(r'TIME STEP')
start_interval = interval[0]*step
end_interval = interval[1]*step
venDLL.command('GAME>GAMEINTERVAL|'+str(start_interval))
# Initiate the model to be run in game mode.
venDLL.command("MENU>GAME")
if start_interval > 0:
venDLL.command('GAME>GAMEON')
loop_on = 1
loop_off = 0
loop_turned_off = False
while True:
# Initiate the experiment of interest.
# In other words set the uncertainties to the same value as in
# those experiments.
time = vensim.get_val(r'TIME')
ema_logging.debug(time)
if time ==(2000+step*interval[0]) and not loop_turned_off:
loop_turned_off = True
if loop_index != 0:
# If loop elimination method is based on unique edge.
if loop_index-1 < ind_cons:
constant_value = vensim.get_val(edges[int(loop_index-1)][0])
if loop_off==1:
constant_value = 0
vensim.set_value('value loop '+str(loop_index),
constant_value)
vensim.set_value('switch loop '+str(loop_index),
loop_off)
# Else it is based on unique consecutive edges.
else:
constant_value = vensim.get_val(edges[int(loop_index-1)][0])
if loop_off==1:
constant_value = 0
# Name of constant value used does not fit loop index minus 'start of cons'-index.
if loop_index-ind_cons in double_list:
vensim.set_value('value cons loop '+str(loop_index-ind_cons-1),
constant_value)
vensim.set_value('switch cons loop '+str(loop_index-ind_cons-1),
loop_off)
else:
vensim.set_value('value cons loop '+str(loop_index-ind_cons),
constant_value)
vensim.set_value('switch cons loop '+str(loop_index-ind_cons),
loop_off)
venDLL.command('GAME>GAMEINTERVAL|'+str(end_interval-start_interval))
elif time ==(2000+step*interval[1]) and loop_turned_off:
loop_turned_off = False
if loop_index != 0:
# If loop elimination method is based on unique edge.
if loop_index-1 < ind_cons:
constant_value = 0
vensim.set_value('value loop '+str(loop_index),
constant_value)
vensim.set_value('switch loop '+str(loop_index),
loop_on)
# Else it is based on unique consecutive edges.
else:
constant_value = 0
# Name of constant value used does not fit loop index minus 'start of cons'-index.
if loop_index-ind_cons in double_list:
vensim.set_value('value cons loop '+str(loop_index-ind_cons-1),
constant_value)
vensim.set_value('switch cons loop '+str(loop_index-ind_cons-1),
loop_on)
else:
vensim.set_value('value cons loop '+str(loop_index-ind_cons),
constant_value)
vensim.set_value('switch cons loop '+str(loop_index-ind_cons),
loop_on)
finalT = vensim.get_val('FINAL TIME')
currentT = vensim.get_val('TIME')
venDLL.command('GAME>GAMEINTERVAL|'+str(finalT - currentT))
else:
break
finalT = vensim.get_val('FINAL TIME')
currentT = vensim.get_val('TIME')
if finalT != currentT:
venDLL.command('GAME>GAMEON')
venDLL.command('GAME>ENDGAME')
interval_series = vensim.get_data('Base.vdf',VOI)
return interval_series
def run_interval(model, loop_index, interval, VOI, edges, ind_cons, double_list, uncertain_names, uncertain_values):
# Load the model.
vensim.load_model(model)
# We don't want any screens.
vensim.be_quiet()
# We run the model in game mode.
step = vensim.get_val(r"TIME STEP")
start_interval = str(interval[0] * step)
venDLL.command("GAME>GAMEINTERVAL|" + start_interval)
# Initiate the model to be run in game mode.
venDLL.command("MENU>GAME")
while True:
if vensim.get_val(r"TIME") == 2000:
# Initiate the experiment of interest.
# In other words set the uncertainties to the same value as in
# those experiments.
for i, value in enumerate(uncertain_values):
name = uncertain_names[i]
value = uncertain_values[i]
vensim.set_value(name, value)
print vensim.get_val(r"TIME")
try:
# Run the model for the length specified in game on-interval.
venDLL.command("GAME>GAMEON")
step = vensim.get_val(r"TIME STEP")
if vensim.get_val(r"TIME") == (2000 + step * interval[0]):
if loop_index != 0:
# If loop elimination method is based on unique edge.
if loop_index - 1 < ind_cons:
constant_value = vensim.get_val(edges[int(loop_index - 1)][0])
vensim.set_value("value loop " + str(loop_index), constant_value)
vensim.set_value("switch loop " + str(loop_index), 0)
# Else it is based on unique consecutive edges.
else:
constant_value = vensim.get_val(edges[int(loop_index - 1)][0])
print constant_value
# Name of constant value used does not fit loop index minus 'start of cons'-index.
if loop_index - ind_cons in double_list:
vensim.set_value("value cons loop " + str(loop_index - ind_cons - 1), constant_value)
vensim.set_value("switch cons loop " + str(loop_index - ind_cons - 1), 0)
else:
vensim.set_value("value cons loop " + str(loop_index - ind_cons), constant_value)
vensim.set_value("switch cons loop " + str(loop_index - ind_cons), 0)
except venDLL.VensimWarning:
# The game on command will continue to the end of the simulation and
# than raise a warning.
print "The end of simulation."
break
venDLL.finish_simulation()
interval_series = vensim.get_data("Base.vdf", VOI)
interval_series = interval_series[interval[0] : interval[1]]
return interval_series
'''
import networkx as nx
import matplotlib.pyplot as plt
import cPickle
from expWorkbench.vensimDLLwrapper import VensimWarning
try:
from networkx import graphviz_layout
except ImportError:
raise ImportError("This example needs Graphviz and either PyGraphviz or Pydot")
from expWorkbench import vensim
from expWorkbench import vensimDLLwrapper as venDLL
vensim.load_model(r'C:\workspace\EMA-workbench\src\sandbox\sils\MODEL.vpm')
vars = venDLL.get_varnames()
graph = nx.DiGraph()
graph.add_nodes_from(vars)
for var in vars:
try:
causes = venDLL.get_varattrib(var, attribute=4) #cause
for cause in causes:
graph.add_edge(cause, var)
except VensimWarning:
print var
cPickle.dump(graph, open("model of Oliva.cPickle",'wb'))
'''
import networkx as nx
import matplotlib.pyplot as plt
import cPickle
from expWorkbench.vensimDLLwrapper import VensimWarning
try:
from networkx import graphviz_layout
except ImportError:
raise ImportError(
"This example needs Graphviz and either PyGraphviz or Pydot")
from expWorkbench import vensim
from expWorkbench import vensimDLLwrapper as venDLL
vensim.load_model(r'D:\epruyt\Desktop\Ageing2.vpm')
#C:\workspace\EMA-workbench\src\sandbox\sils\MODEL.vpm
vars = venDLL.get_varnames()
graph = nx.DiGraph()
graph.add_nodes_from(vars)
for var in vars:
try:
causes = venDLL.get_varattrib(var, attribute=4) #cause
for cause in causes:
graph.add_edge(cause, var)
except VensimWarning:
print var
def run_interval(model, loop_index, interval, VOI, edges, ind_cons,
double_list, uncertain_names, uncertain_values):
# Load the model.
vensim.load_model(model)
# We don't want any screens.
vensim.be_quiet()
# We run the model in game mode.
step = vensim.get_val(r'TIME STEP')
start_interval = str(interval[0] * step)
venDLL.command('GAME>GAMEINTERVAL|' + start_interval)
# Initiate the model to be run in game mode.
venDLL.command("MENU>GAME")
while True:
if vensim.get_val(r'TIME') == 2000:
# Initiate the experiment of interest.
# In other words set the uncertainties to the same value as in
# those experiments.
for i, value in enumerate(uncertain_values):
name = uncertain_names[i]
value = uncertain_values[i]
vensim.set_value(name, value)
print vensim.get_val(r'TIME')
try:
# Run the model for the length specified in game on-interval.
venDLL.command('GAME>GAMEON')
step = vensim.get_val(r'TIME STEP')
if vensim.get_val(r'TIME') == (2000 + step * interval[0]):
if loop_index != 0:
# If loop elimination method is based on unique edge.
if loop_index - 1 < ind_cons:
constant_value = vensim.get_val(edges[int(loop_index -
1)][0])
vensim.set_value('value loop ' + str(loop_index),
constant_value)
vensim.set_value('switch loop ' + str(loop_index), 0)
# Else it is based on unique consecutive edges.
else:
constant_value = vensim.get_val(edges[int(loop_index -
1)][0])
print constant_value
# Name of constant value used does not fit loop index minus 'start of cons'-index.
if loop_index - ind_cons in double_list:
vensim.set_value(
'value cons loop ' +
str(loop_index - ind_cons - 1), constant_value)
vensim.set_value(
'switch cons loop ' +
str(loop_index - ind_cons - 1), 0)
else:
vensim.set_value(
'value cons loop ' +
str(loop_index - ind_cons), constant_value)
vensim.set_value(
'switch cons loop ' +
str(loop_index - ind_cons), 0)
except venDLL.VensimWarning:
# The game on command will continue to the end of the simulation and
# than raise a warning.
print "The end of simulation."
break
venDLL.finish_simulation()
interval_series = vensim.get_data('Base.vdf', VOI)
interval_series = interval_series[interval[0]:interval[1]]
return interval_series
'''
Created on May 30, 2012
@author: jhkwakkel
'''
from expWorkbench import vensim
from expWorkbench import vensimDLLwrapper as venDLL
vensim.load_model(r'C:\workspace\EMA-workbench\src\sandbox\sils\MODEL.vpm')
venDLL.start_simulation(True, 0, True)
venDLL.continue_simulation(50)
venDLL.finish_simulation()
time_series = vensim.get_data('test.vdf', 'Rookies', step=1)
print "blaat"
