import cProfile
from dmrg import *
from mpo.asep import return_mpo
import pstats
# Set Calculation Parameters
N = 50
p = 0.1
mbd = np.array([16])
s = 0.5
# Set up calculation
mpo = return_mpo(N, (0.5, 0.5, p, 1 - p, 0.5, 0.5, s))
cProfile.run('E,EE,gap = run_dmrg(mpo,mbd=mbd,nStates=2,fname="tmp")',
'mps_stats')
p = pstats.Stats('mps_stats')
p.sort_stats('cumulative').print_stats(20)
fname = path + 'MPS_'
# Set up Plotting Stuff
if make_plt:
import matplotlib.pyplot as plt
f = plt.figure()
ax0 = f.add_subplot(311)
ax1 = f.add_subplot(323)
ax2 = f.add_subplot(324)
ax3 = f.add_subplot(325)
ax4 = f.add_subplot(326)
# Run initial Calculation
print(s0)
hamParams[-1] = s0
mpo = return_mpo(N, hamParams)
Etmp, EEtmp, gaptmp, env = run_dmrg(
mpo,
mbd=mbd,
#initGuess = 'saved_states/singleLane_MCSHD_N100mbd10_1553109008/MPS_s242',
fname=fname + 's0',
nStates=nStates,
alg=alg,
returnEnv=True,
calcLeftState=leftState)
"""
Etmp,EEtmp,gaptmp,env = run_dmrg(mpo,
mbd=mbd,
initGuess = fname+'s0',
initEnv = env,
fname=fname+'s0',
# Return Results
if len(Evec) == 1:
output = [E, EE, gap]
else:
output = [Evec, EEvec, gapvec]
if returnEntSpec:
output.append(EEs)
if returnState:
output.append(mpsList)
if returnEnv:
output.append(env)
return output
if __name__ == "__main__":
from mpo.asep import return_mpo
# Hamiltonian Parameters
p = 0.1
alpha = 0.2 # in at left
gamma = 1. - alpha # Out at left
q = 1. - p # Jump left
beta = 0.4 # Out at right
delta = 1. - beta # In at right
s = -0.5
# Get MPO
hamParams = np.array([alpha, gamma, p, q, beta, delta, s])
mpo = return_mpo(4, hamParams)
# Run idmrg
output = run_idmrg(mpo, mbd=10)
# Get initial path from input argument
path = argv[1]
# Load results file and find out initial information
fname = path + 'results.npz'
npzfile = np.load(fname)
s = npzfile['s']
N = int(npzfile['N'])
nStates = 4
p = 0.1
E = np.zeros((len(s), nStates))
PT = np.zeros((len(s), nStates))
# Loop through all results in s vector
for sInd in range(len(s)):
print('Processing s={}'.format(s[sInd]))
mpo = return_mpo(N, (0.5, 0.5, p, 1. - p, 0.5, 0.5, s[sInd]))
cmpo = curr_mpo(N, (0.5, 0.5, p, 1. - p, 0.5, 0.5, s[sInd]))
for state in range(nStates):
fname_mps = path + 'MPS_s' + str(sInd) + '_mbd0'
fname_lmps = path + 'MPS_s' + str(sInd) + '_mbd0_left'
E[sInd,
state] = contract(mps=fname_mps, mpo=mpo, state=state) / contract(
mps=fname_mps, state=state)
# Calculate PT Stuff
#PT[sInd,state]= contract(mps=fname_mps,mpo=cmpo,state=0,lstate=state)*contract(mps=fname_mps,mpo=cmpo,state=state,lstate=0)/(E[sInd,0]-E[sInd,state])
PT[sInd, state] = contract(
mps=fname_mps, lmps=fname_lmps, mpo=cmpo, state=0, lstate=state
) * contract(
mps=fname_mps, lmps=fname_lmps, mpo=cmpo, state=state,
lstate=0) / (E[sInd, 0] - E[sInd, state])
print(PT[sInd, :])