import simulate_toric as st
import random
import load_errors
n_trials = 100
success_count = 0
size=6
tSteps=5
random.seed(0)
## Load error vector from file
evecs3,evecs4 = load_errors.load("example_errorvec.txt")
error_vector4 = evecs4[evecs4.keys()[0]]
for i in range(n_trials):
[x,z],[x2,z2] = st.run3D(size,tSteps,error_vector4)
if x==1 and z==1 and x2==1 and z2==1: success_count+=1
print 'lattice size: ',size
print 'time steps: ', tSteps
print 'random errors applied according the test error vector'
print
print success_count,' /',n_trials,' were successfully decoded: ',success_count
def run3Dtest(size=8,tSteps=100,errorVec3 = testvec4, errorVec4=testvec4,timespace=[1,1],boundary_weight = 1):
errvec_file = "error_vectors/basic_0.txt"
errorVec3, errorVec4 = [[] if x=={} else x[0.0] for x in load_errors.load(errvec_file)]
t0 = time.time()
L=planar_lattice.PlanarLattice(size)
PL=planar_lattice.PlanarLattice3D(size)
L.applyRandomErrors(0,0) # leave this here for initialisation
# t1 = time.time()
# print 'initialisation ',t1-t0
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette",errorVec3, errorVec4)
L.measureNoisyStabilizers("star",errorVec3,errorVec4)
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
# print 'P anyons', sum([len(_) for _ in PL.anyon_positions_P])
# print 'S anyons', sum([len(_) for _ in PL.anyon_positions_S])
# t2 = time.time()
# print 'loop over timeslices ', t2 -t1
matchingX=perfect_matching.match_planar_3D(size,"plaquette",PL.anyon_positions_P,timespace,boundary_weight)
# t3 = time.time()
# print 'perfect matching ', t3 -t2
#matchingZ=perfect_matching.match_toric_3D(size,PL.anyon_positions_S,timespace)
flipsX=squashMatching(size,"X",matchingX)
#flipsZ=squashMatching(size,matchingZ)
# t4 = time.time()
# print 'squash matching ',t4-t3
# L.showArray("errors","X")
Lbefore = copy.copy(L)
#L.apply_flip_array("Z",flipsZ)
L.apply_flip_array("X",flipsX)
if L.measure_logical[0]==-1:
Lbefore.showArray("errors","X")
L.showArray("errors","X")
#L.showArray("errors","Z")
return L.measure_logical()
def run3Dtest(size=8,tSteps=100,errorVec=testvec4,timespace=[1,1]):
errvec_file = "error_vectors/basic_0.txt"
error_vector3, error_vector4 = [[] if x=={} else x[0.0] for x in load_errors.load(errvec_file)]
errorVec = error_vector4
# print error_vector3
# print error_vector4
L=toric_lattice.PlanarLattice(size)
PL=toric_lattice.Lattice3D(size)
L.applyRandomErrors(0,0) # leave this here for initialisation
xcount = 0
zcount = 0
#t0=time.time()
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette",errorVec)
L.measureNoisyStabilizers("star",errorVec)
#for p0,p1 in L.positions_Q:
# x,z = L.array[p0][p1]
# if x ==-1: xcount +=1
# if z ==-1: zcount +=1
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
# print xcount, zcount
# t1 = time.time()
# print 'tsteps completed ',t1-t0
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
# print 'P anyons', sum([len(_) for _ in PL.anyon_positions_P])
# print 'S anyons', sum([len(_) for _ in PL.anyon_positions_S])
#print PL.anyon_positions_P
# t2 = time.time()
#print 'find anyons ',t2-t1
matchingX=perfect_matching.match_toric_3D(size,PL.anyon_positions_P,timespace)
# t3 = time.time()
#print 'matching X ',t3-t2
matchingZ=perfect_matching.match_toric_3D(size,PL.anyon_positions_S,timespace)
flipsX=squashMatching(size,matchingX)
flipsZ=squashMatching(size,matchingZ)
# t4 = time.time()
# print 'squash matching ',t4-t3
# L.showArray("errors","X")
L.apply_flip_array("Z",flipsZ)
L.apply_flip_array("X",flipsX)
# L.showArray("errors","X")
#L.showArray("errors","Z")
return L.measure_logical()
def run3Dtest(size=8, tSteps=100, errorVec=testvec4, timespace=[1, 1]):
errvec_file = "error_vectors/basic_0.txt"
error_vector3, error_vector4 = [[] if x == {} else x[0.0]
for x in load_errors.load(errvec_file)]
errorVec = error_vector4
# print error_vector3
# print error_vector4
L = toric_lattice.PlanarLattice(size)
PL = toric_lattice.Lattice3D(size)
L.applyRandomErrors(0, 0) # leave this here for initialisation
xcount = 0
zcount = 0
#t0=time.time()
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette", errorVec)
L.measureNoisyStabilizers("star", errorVec)
#for p0,p1 in L.positions_Q:
# x,z = L.array[p0][p1]
# if x ==-1: xcount +=1
# if z ==-1: zcount +=1
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
# print xcount, zcount
# t1 = time.time()
# print 'tsteps completed ',t1-t0
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
# print 'P anyons', sum([len(_) for _ in PL.anyon_positions_P])
# print 'S anyons', sum([len(_) for _ in PL.anyon_positions_S])
#print PL.anyon_positions_P
# t2 = time.time()
#print 'find anyons ',t2-t1
matchingX = perfect_matching.match_toric_3D(size, PL.anyon_positions_P,
timespace)
# t3 = time.time()
#print 'matching X ',t3-t2
matchingZ = perfect_matching.match_toric_3D(size, PL.anyon_positions_S,
timespace)
flipsX = squashMatching(size, matchingX)
flipsZ = squashMatching(size, matchingZ)
# t4 = time.time()
# print 'squash matching ',t4-t3
# L.showArray("errors","X")
L.apply_flip_array("Z", flipsZ)
L.apply_flip_array("X", flipsX)
# L.showArray("errors","X")
#L.showArray("errors","Z")
return L.measure_logical()
def run3Dtest(size=8,
tSteps=100,
errorVec3=testvec4,
errorVec4=testvec4,
timespace=[1, 1],
boundary_weight=1):
errvec_file = "error_vectors/basic_0.txt"
errorVec3, errorVec4 = [[] if x == {} else x[0.0]
for x in load_errors.load(errvec_file)]
t0 = time.time()
L = planar_lattice.PlanarLattice(size)
PL = planar_lattice.PlanarLattice3D(size)
L.applyRandomErrors(0, 0) # leave this here for initialisation
# t1 = time.time()
# print 'initialisation ',t1-t0
for i in range(tSteps): # loop over time
L.measureNoisyStabilizers("plaquette", errorVec3, errorVec4)
L.measureNoisyStabilizers("star", errorVec3, errorVec4)
PL.addMeasurement(L) # add the updated 2D lattice to 3D array
L.measurePlaquettes(0) # measure one more layer with
L.measureStars(0) # perfect stabilizers and add
PL.addMeasurement(L) # this to the parity Lattice
PL.findAnyons()
# print 'P anyons', sum([len(_) for _ in PL.anyon_positions_P])
# print 'S anyons', sum([len(_) for _ in PL.anyon_positions_S])
# t2 = time.time()
# print 'loop over timeslices ', t2 -t1
matchingX = perfect_matching.match_planar_3D(size, "plaquette",
PL.anyon_positions_P,
timespace, boundary_weight)
# t3 = time.time()
# print 'perfect matching ', t3 -t2
#matchingZ=perfect_matching.match_toric_3D(size,PL.anyon_positions_S,timespace)
flipsX = squashMatching(size, "X", matchingX)
#flipsZ=squashMatching(size,matchingZ)
# t4 = time.time()
# print 'squash matching ',t4-t3
# L.showArray("errors","X")
Lbefore = copy.copy(L)
#L.apply_flip_array("Z",flipsZ)
L.apply_flip_array("X", flipsX)
if L.measure_logical[0] == -1:
Lbefore.showArray("errors", "X")
L.showArray("errors", "X")
#L.showArray("errors","Z")
return L.measure_logical()
