def test_hamiltonian_Ne_3(self):
l1 = pymc.GrapheneLattice(10)
FK1 = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
FK1.calculate_eigv(temp=True)
Ne1 = FK1.get_ne(temp=True, T=0.01, cp=-1)
FK2 = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
FK2.T = 0.01
FK2.cp = 1
FK2.calculate_eigv()
Ne2 = FK2.get_ne()
assert Ne1 < Ne2
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 test_hamiltonian_Ne_2(self):
l1 = pymc.GrapheneLattice(10)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
FK.put_adatoms(50, "sublattice")
FK.calculate_eigv()
Ne = FK.get_ne(T=0.01, cp=1)
np.testing.assert_almost_equal(Ne, 50)
def test_swap_in_temp_H(self):
l1 = pymc.lattice.GrapheneLattice(4)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
FK.put_adatoms(6)
ch_empty = np.random.choice(FK.empty_sites)
ch_filled = np.random.choice(FK.filled_sites)
assert FK.H[ch_empty, ch_empty] == 0
assert FK.H[ch_filled, ch_filled] == 2
assert FK.temp_H[ch_empty, ch_empty] == 0
assert FK.temp_H[ch_filled, ch_filled] == 2
FK.swap_in_temp_H(ch_filled, ch_empty)
assert FK.H[ch_empty, ch_empty] == 0
assert FK.H[ch_filled, ch_filled] == 2
assert FK.temp_H[ch_empty, ch_empty] == 2
assert FK.temp_H[ch_filled, ch_filled] == 0
FK.un_swap_in_temp_H(ch_filled, ch_empty)
assert FK.H[ch_empty, ch_empty] == 0
assert FK.H[ch_filled, ch_filled] == 2
assert FK.temp_H[ch_empty, ch_empty] == 0
assert FK.temp_H[ch_filled, ch_filled] == 2
def prepare_model(self, n, nad, order):
l1 = pymc.GrapheneLattice(n)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
o_C = pymc.CorrelationObs(FK)
for _ in range(100):
FK.put_adatoms(nad, order)
o_C.calculate()
return o_C.get_result()
def test_adatoms_sums(self):
l1 = pymc.lattice.GrapheneLattice(4)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
for mode in ["random", "sublattice", "separation"]:
FK.put_adatoms(6, order=mode)
assert np.trace(FK.H) == 12
assert len(FK.filled_sites) == 6
assert len(FK.empty_sites) == 10
def test_adatoms_sublatice(self):
l1 = pymc.lattice.GrapheneLattice(4)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
FK.put_adatoms(6, order="sublattice")
for i in FK.filled_sites:
assert i in FK.lattice.sub_matrix[1]
assert FK.H[i, i] == 2.0
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()
def prepare_model_cv(self, n, nad, order, T):
l1 = pymc.GrapheneLattice(n)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2, T=T)
o_cv = pymc.CVObs(FK)
for _ in range(50):
FK.put_adatoms(nad, order)
FK.calculate_eigv()
o_cv.calculate()
return o_cv.get_result()
def test_obs_correlation_6(self):
l1 = pymc.GrapheneLattice(10)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
o_C = pymc.CorrelationObs(FK)
for _ in range(100):
FK.put_adatoms(50, "random")
o_C.calculate()
o_C.reset()
assert o_C.get_result() is None
def test_obs_cv_2(self):
l1 = pymc.GrapheneLattice(10)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2, T=0.2)
o_cv = pymc.CVObs(FK)
for _ in range(50):
FK.put_adatoms(50, "random")
FK.calculate_eigv()
o_cv.calculate()
o_cv.reset()
assert o_cv.get_result() is None
def test_obs_correlation_6(self):
l1 = pymc.GrapheneLattice(10)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
o_C = pymc.CorrelationObs(FK)
for _ in range(100):
FK.put_adatoms(50, "random")
o_C.calculate()
d = o_C.get_result()
assert len(o_C.value_list) == 100
np.testing.assert_almost_equal(abs(d), 0, decimal=1)
def test_obs_delta_7(self):
l1 = pymc.GrapheneLattice(10)
FK = pymc.Hamiltonian(lattice=l1, t=-1, U=2)
o_delta = pymc.DeltaObs(FK)
for _ in range(100):
FK.put_adatoms(50, "random")
o_delta.calculate()
d = o_delta.get_result()
assert len(o_delta.value_list) == 100
np.testing.assert_almost_equal(d, 0, decimal=1)
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)
