def get_results(self):
lattice = pymc.GrapheneLattice(6)
FK = pymc.Hamiltonian(lattice, t=-1, U=2, cp=1, T=0.2)
FK.put_adatoms(18, "random")
obs = pymc.ObsList([pymc.DeltaObs(FK),
pymc.EnergyObs(FK), pymc.CVObs(FK),
pymc.CorrelationObs(FK), pymc.NeObs(FK)])
obs_conv = pymc.ObsList(
[pymc.DeltaObs(FK), pymc.EnergyObs(FK), pymc.CorrelationObs(FK)])
series = pymc.ObsSeries(obs, ["T"])
sym = pymc.Simulator(FK, pymc.metropolis_numpy, obs, obs_conv)
T_range = [0.2, 0.18, 0.16, 0.14, 0.12,
0.10, 0.08, 0.06, 0.04, 0.03, 0.02, 0.01]
for T in T_range:
FK.T = T
sym.run_termalization(10**2)
res = sym.run_measurements(10**2)
series.add(res, [T])
expected = np.loadtxt(
"tests/simulate/half_filling_1.csv", delimiter=",")
res = series.get_df().values
return (expected, res)
def prepare_model_E(self, n, nad, order):
l1 = pymc.GrapheneLattice(n)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2, T=0.01)
o_energy = pymc.EnergyObs(FK)
for _ in range(50):
FK.put_adatoms(nad, order)
FK.calculate_eigv()
o_energy.calculate()
return o_energy.get_result()
import pymc
import matplotlib.pyplot as plt
from tqdm import tqdm
import numpy as np
lattice = pymc.GrapheneLattice(6)
FK = pymc.Hamiltonian(lattice, t=-1, U=2, cp=-1, T=0.2)
FK.put_adatoms(6 * 3, "random")
obs = pymc.ObsList([
pymc.DeltaObs(FK),
pymc.EnergyObs(FK),
pymc.CVObs(FK),
pymc.CorrelationObs(FK),
pymc.NeObs(FK)
])
obs_conv = pymc.ObsList(
[pymc.DeltaObs(FK),
pymc.EnergyObs(FK),
pymc.CorrelationObs(FK)])
series = pymc.ObsSeries(obs, ["T"])
sym = pymc.Simulator(FK, pymc.metropolis_numpy, obs, obs_conv)
T_range = [
0.2, 0.18, 0.16, 0.14, 0.12, 0.10, 0.08, 0.06, 0.04, 0.03, 0.02, 0.01
]
for T in tqdm(T_range, desc="Main loop"):
FK.T = T
sym.run_termalization(10**4)