class MC_class():
"""
Private class for solving Monte-Carlo evolution from mcsolve
"""
def __init__(self):
#-----------------------------------#
# INIT MC CLASS
#-----------------------------------#
#----MAIN OBJECT PROPERTIES--------------------#
##holds instance of the ProgressBar class
self.bar=None
##holds instance of the Pthread class
self.thread=None
#Number of completed trajectories
self.count=0
##step-size for count attribute
self.step=1
##Percent of trajectories completed
self.percent=0.0
##used in implimenting the command line progress ouput
self.level=0.1
##times at which to output state vectors or expectation values
##number of time steps in tlist
self.num_times=len(odeconfig.tlist)
#holds seed for random number generator
self.seed=None
#holds expected time to completion
self.st=None
#number of cpus to be used
self.cpus=odeconfig.options.num_cpus
#set output variables, even if they are not used to simplify output code.
self.psi_out=None
self.expect_out=None
self.collapse_times_out=None
self.which_op_out=None
#FOR EVOLUTION FOR NO COLLAPSE OPERATORS
if odeconfig.c_num==0:
if odeconfig.e_num==0:
##Output array of state vectors calculated at times in tlist
self.psi_out=array([Qobj()]*self.num_times)#preallocate array of Qobjs
elif odeconfig.e_num!=0:#no collpase expectation values
##List of output expectation values calculated at times in tlist
self.expect_out=[]
for i in range(odeconfig.e_num):
if odeconfig.e_ops_isherm[i]:#preallocate real array of zeros
self.expect_out.append(zeros(self.num_times))
else:#preallocate complex array of zeros
self.expect_out.append(zeros(self.num_times,dtype=complex))
self.expect_out[i][0]=mc_expect(odeconfig.e_ops_data[i],odeconfig.e_ops_ind[i],odeconfig.e_ops_ptr[i],odeconfig.e_ops_isherm[i],odeconfig.psi0)
#FOR EVOLUTION WITH COLLAPSE OPERATORS
elif odeconfig.c_num!=0:
#preallocate #ntraj arrays for state vectors, collapse times, and which operator
self.collapse_times_out=zeros((odeconfig.ntraj),dtype=ndarray)
self.which_op_out=zeros((odeconfig.ntraj),dtype=ndarray)
if odeconfig.e_num==0:# if no expectation operators, preallocate #ntraj arrays for state vectors
self.psi_out=array([zeros((self.num_times),dtype=object) for q in range(odeconfig.ntraj)])#preallocate array of Qobjs
else: #preallocate array of lists for expectation values
self.expect_out=[[] for x in range(odeconfig.ntraj)]
#-------------------------------------------------#
# CLASS METHODS
#-------------------------------------------------#
def callback(self,results):
r=results[0]
if odeconfig.e_num==0:#output state-vector
self.psi_out[r]=results[1]
else:#output expectation values
self.expect_out[r]=results[1]
self.collapse_times_out[r]=results[2]
self.which_op_out[r]=results[3]
self.count+=self.step
if (not odeconfig.options.gui): #do not use GUI
self.percent=self.count/(1.0*odeconfig.ntraj)
if self.count/float(odeconfig.ntraj)>=self.level:
#calls function to determine simulation time remaining
self.level=_time_remaining(self.st,odeconfig.ntraj,self.count,self.level)
#-----
def parallel(self,args,top=None):
self.st=datetime.datetime.now() #set simulation starting time
pl=Pool(processes=self.cpus)
[pl.apply_async(mc_alg_evolve,args=(nt,args),callback=top.callback) for nt in range(0,odeconfig.ntraj)]
pl.close()
try:
pl.join()
except KeyboardInterrupt:
print("Cancel all MC threads on keyboard interrupt")
pl.terminate()
pl.join()
return
#-----
def run(self):
if odeconfig.c_num==0:
if odeconfig.ntraj!=1:#check if ntraj!=1 which is pointless for no collapse operators
odeconfig.ntraj=1
print('No collapse operators specified.\nRunning a single trajectory only.\n')
if odeconfig.e_num==0:# return psi Qobj at each requested time
self.psi_out=no_collapse_psi_out(self.num_times,self.psi_out)
else:# return expectation values of requested operators
self.expect_out=no_collapse_expect_out(self.num_times,self.expect_out)
elif odeconfig.c_num!=0:
self.seed=array([int(ceil(random.rand()*1e4)) for ll in range(odeconfig.ntraj)])
if odeconfig.e_num==0:
mc_alg_out=zeros((self.num_times),dtype=ndarray)
mc_alg_out[0]=odeconfig.psi0
else:
#PRE-GENERATE LIST OF EXPECTATION VALUES
mc_alg_out=[]
for i in range(odeconfig.e_num):
if odeconfig.e_ops_isherm[i]:#preallocate real array of zeros
mc_alg_out.append(zeros(self.num_times))
else:#preallocate complex array of zeros
mc_alg_out.append(zeros(self.num_times,dtype=complex))
mc_alg_out[i][0]=mc_expect(odeconfig.e_ops_data[i],odeconfig.e_ops_ind[i],odeconfig.e_ops_ptr[i],odeconfig.e_ops_isherm[i],odeconfig.psi0)
#set arguments for input to monte-carlo
args=(mc_alg_out,odeconfig.options,odeconfig.tlist,self.num_times,self.seed)
if not odeconfig.options.gui:
self.parallel(args,self)
else:
if qutip.settings.qutip_gui=="PYSIDE":
from PySide import QtGui,QtCore
elif qutip.settings.qutip_gui=="PYQT4":
from PyQt4 import QtGui,QtCore
from gui.ProgressBar import ProgressBar,Pthread
app=QtGui.QApplication.instance()#checks if QApplication already exists (needed for iPython)
if not app:#create QApplication if it doesnt exist
app = QtGui.QApplication(sys.argv)
thread=Pthread(target=self.parallel,args=args,top=self)
self.bar=ProgressBar(self,thread,odeconfig.ntraj,self.cpus)
QtCore.QTimer.singleShot(0,self.bar.run)
self.bar.show()
self.bar.activateWindow()
self.bar.raise_()
app.exec_()
return
class MC_class():
"""
Private class for solving Monte-Carlo evolution from mcsolve
"""
def __init__(self):
#-----------------------------------#
# INIT MC CLASS
#-----------------------------------#
#----MAIN OBJECT PROPERTIES--------------------#
##holds instance of the ProgressBar class
self.bar = None
##holds instance of the Pthread class
self.thread = None
#Number of completed trajectories
self.count = 0
##step-size for count attribute
self.step = 1
##Percent of trajectories completed
self.percent = 0.0
##used in implimenting the command line progress ouput
self.level = 0.1
##times at which to output state vectors or expectation values
##number of time steps in tlist
self.num_times = len(odeconfig.tlist)
#holds seed for random number generator
self.seed = None
#holds expected time to completion
self.st = None
#number of cpus to be used
self.cpus = odeconfig.options.num_cpus
#set output variables, even if they are not used to simplify output code.
self.psi_out = None
self.expect_out = None
self.collapse_times_out = None
self.which_op_out = None
#FOR EVOLUTION FOR NO COLLAPSE OPERATORS
if odeconfig.c_num == 0:
if odeconfig.e_num == 0:
##Output array of state vectors calculated at times in tlist
self.psi_out = array(
[Qobj()] * self.num_times) #preallocate array of Qobjs
elif odeconfig.e_num != 0: #no collpase expectation values
##List of output expectation values calculated at times in tlist
self.expect_out = []
for i in range(odeconfig.e_num):
if odeconfig.e_ops_isherm[
i]: #preallocate real array of zeros
self.expect_out.append(zeros(self.num_times))
else: #preallocate complex array of zeros
self.expect_out.append(
zeros(self.num_times, dtype=complex))
self.expect_out[i][0] = mc_expect(
odeconfig.e_ops_data[i], odeconfig.e_ops_ind[i],
odeconfig.e_ops_ptr[i], odeconfig.e_ops_isherm[i],
odeconfig.psi0)
#FOR EVOLUTION WITH COLLAPSE OPERATORS
elif odeconfig.c_num != 0:
#preallocate #ntraj arrays for state vectors, collapse times, and which operator
self.collapse_times_out = zeros((odeconfig.ntraj), dtype=ndarray)
self.which_op_out = zeros((odeconfig.ntraj), dtype=ndarray)
if odeconfig.e_num == 0: # if no expectation operators, preallocate #ntraj arrays for state vectors
self.psi_out = array([
zeros((self.num_times), dtype=object)
for q in range(odeconfig.ntraj)
]) #preallocate array of Qobjs
else: #preallocate array of lists for expectation values
self.expect_out = [[] for x in range(odeconfig.ntraj)]
#-------------------------------------------------#
# CLASS METHODS
#-------------------------------------------------#
def callback(self, results):
r = results[0]
if odeconfig.e_num == 0: #output state-vector
self.psi_out[r] = results[1]
else: #output expectation values
self.expect_out[r] = results[1]
self.collapse_times_out[r] = results[2]
self.which_op_out[r] = results[3]
self.count += self.step
if (not odeconfig.options.gui): #do not use GUI
self.percent = self.count / (1.0 * odeconfig.ntraj)
if self.count / float(odeconfig.ntraj) >= self.level:
#calls function to determine simulation time remaining
self.level = _time_remaining(self.st, odeconfig.ntraj,
self.count, self.level)
#-----
def parallel(self, args, top=None):
self.st = datetime.datetime.now() #set simulation starting time
pl = Pool(processes=self.cpus)
[
pl.apply_async(mc_alg_evolve,
args=(nt, args),
callback=top.callback)
for nt in range(0, odeconfig.ntraj)
]
pl.close()
try:
pl.join()
except KeyboardInterrupt:
print("Cancel all MC threads on keyboard interrupt")
pl.terminate()
pl.join()
return
#-----
def run(self):
if odeconfig.c_num == 0:
if odeconfig.ntraj != 1: #check if ntraj!=1 which is pointless for no collapse operators
odeconfig.ntraj = 1
print(
'No collapse operators specified.\nRunning a single trajectory only.\n'
)
if odeconfig.e_num == 0: # return psi Qobj at each requested time
self.psi_out = no_collapse_psi_out(self.num_times,
self.psi_out)
else: # return expectation values of requested operators
self.expect_out = no_collapse_expect_out(
self.num_times, self.expect_out)
elif odeconfig.c_num != 0:
self.seed = array([
int(ceil(random.rand() * 1e4)) for ll in range(odeconfig.ntraj)
])
if odeconfig.e_num == 0:
mc_alg_out = zeros((self.num_times), dtype=ndarray)
mc_alg_out[0] = odeconfig.psi0
else:
#PRE-GENERATE LIST OF EXPECTATION VALUES
mc_alg_out = []
for i in range(odeconfig.e_num):
if odeconfig.e_ops_isherm[
i]: #preallocate real array of zeros
mc_alg_out.append(zeros(self.num_times))
else: #preallocate complex array of zeros
mc_alg_out.append(zeros(self.num_times, dtype=complex))
mc_alg_out[i][0] = mc_expect(odeconfig.e_ops_data[i],
odeconfig.e_ops_ind[i],
odeconfig.e_ops_ptr[i],
odeconfig.e_ops_isherm[i],
odeconfig.psi0)
#set arguments for input to monte-carlo
args = (mc_alg_out, odeconfig.options, odeconfig.tlist,
self.num_times, self.seed)
if not odeconfig.options.gui:
self.parallel(args, self)
else:
if qutip.settings.qutip_gui == "PYSIDE":
from PySide import QtGui, QtCore
elif qutip.settings.qutip_gui == "PYQT4":
from PyQt4 import QtGui, QtCore
from gui.ProgressBar import ProgressBar, Pthread
app = QtGui.QApplication.instance(
) #checks if QApplication already exists (needed for iPython)
if not app: #create QApplication if it doesnt exist
app = QtGui.QApplication(sys.argv)
thread = Pthread(target=self.parallel, args=args, top=self)
self.bar = ProgressBar(self, thread, odeconfig.ntraj,
self.cpus)
QtCore.QTimer.singleShot(0, self.bar.run)
self.bar.show()
self.bar.activateWindow()
self.bar.raise_()
app.exec_()
return
