def get_coor_hop(self):
'''
Get the site coordinates in hopping space
only considering the nearest neighbours hoppings.
'''
error_handling.empty_hop(self.hop)
visited = np.zeros(self.lat.sites, 'u2')
self.coor_hop = np.zeros(self.lat.sites, dtype=[('x','f8'), ('y','f8'), ('tag', 'S1')])
self.coor_hop['tag'] = self.lat.coor['tag']
hop = self.hop[self.hop['n'] == 1]
hop_down = np.copy(hop)
hop_down['i'] = hop['j']
hop_down['j'] = hop[ 'i']
hop_down['ang'] = -180 + hop['ang']
hop = np.concatenate([hop, hop_down])
i_visit = np.min(hop['i'])
while True:
hs = hop[hop['i'] == i_visit]
for h in hs:
if visited[h['j']] == 2:
continue
self.coor_hop['x'][h['j']] = self.coor_hop['x'][i_visit] + \
h['t'].real*cos(PI / 180 * h['ang'])
self.coor_hop['y'][h['j']] = self.coor_hop['y'][i_visit] + \
h['t'].real*sin(PI / 180 * h['ang'])
visited[h['j']] = 1
visited[i_visit] = 2
explored = np.argwhere(visited == 1)
if not explored.any():
break
i_visit = explored[0]
def change_hopping_square(self, list_hop, xlims, ylims=[-1., 1.]):
'''
Change hopping values.
:param list_hop: List of Dictionary (see set_hopping definition).
:param xlims: List or Tuple. :math:`x` interval.
:param ylims: List or Tuple. :math:`y` interval.
'''
error_handling.empty_hop(self.hop)
error_handling.set_hopping(list_hop, self.nmax)
ind = self.find_square(xlims, ylims)
self.set_new_hopping(list_hop, ind)
def set_hopping_dis(self, alpha):
'''
Set uniform hopping disorder.
:param alpha: Complex or Real number. Disorder stength.
Example usage::
sys.set_hopping_dis(alpha=0.1)
'''
error_handling.empty_hop(self.hop)
error_handling.number(alpha, 'alpha')
self.hop['t'] *= 1. + alpha * rand.uniform(-1., 1., len(self.hop))
def get_ham(self):
'''
Get the Tight-Binding Hamiltonian using sys.hop.
'''
error_handling.empty_hop(self.hop)
error_handling.hop_sites(self.hop, self.lat.sites)
if np.all(self.hop['ang'] >= 0) or np.all(self.hop['ang'] < 0):
self.ham = sparse.csr_matrix((self.hop['t'], (self.hop['i'], self.hop['j'])),
shape=(self.lat.sites, self.lat.sites)) \
+ sparse.csr_matrix((self.hop['t'].conj(), (self.hop['j'], self.hop['i'])),
shape=(self.lat.sites, self.lat.sites))
else:
self.ham = sparse.csr_matrix((self.hop['t'], (self.hop['i'], self.hop['j'])),
shape=(self.lat.sites, self.lat.sites))
if self.onsite.size == self.lat.sites:
self.ham += sparse.diags(self.onsite, 0)
def change_hopping_ellipse(self, list_hop, rx, ry, x0=0., y0=0.):
'''
Change hopping values.
:param list_hop: List of Dictionary (see set_hopping definition).
:param rx: Positive Float. Radius along :math:`x`.
:param ry: Positive Float. Radius along :math:`y`.
:param x0: Float. Default value 0. :math:`x` center.
:param y0: Float. Default value 0. :math:`y` center.
'''
error_handling.empty_hop(self.hop)
error_handling.set_hopping(list_hop, self.nmax)
error_handling.positive_real(rx, 'rx')
error_handling.positive_real(ry, 'rx')
error_handling.real_number(x0, 'x0')
error_handling.real_number(y0, 'y0')
ind = self.find_ellipse(rx, ry, x0, y0)
self.set_new_hopping(list_hop, ind)
def set_hopping_def(self, hopping_def):
'''
Set specific hoppings.
:param hopping_def: Dictionary of hoppings.
key: hopping indices, val: hopping values.
Example usage::
sys.set_hopping_def({(0, 1): 1., (1, 2): -1j})
'''
error_handling.empty_hop(self.hop)
error_handling.set_hopping_def(self.hop, hopping_def, self.lat.sites)
for key, val in hopping_def.items():
cond = (self.hop['i'] == key[0]) & (self.hop['j'] == key[1])
self.hop['t'][cond] = val
self.hop['ang'] = self.vec_hop['ang'][key[0], key[1]]
self.hop['tag'] = npc.add(self.lat.coor['tag'][key[0]],
self.lat.coor['tag'][key[1]])
def set_hopping_def(self, hopping_def):
'''
Set specific hoppings.
:param hopping_def: Dictionary of hoppings.
key: hopping indices, val: hopping values.
Example usage::
sys.set_hopping_def({(0, 1): 1., (1, 2): -1j})
'''
error_handling.empty_hop(self.hop)
error_handling.set_hopping_def(self.hop, hopping_def, self.lat.sites)
for key, val in hopping_def.items():
cond = (self.hop['i'] == key[0]) & (self.hop['j'] == key[1])
self.hop['t'][cond] = val
self.hop['ang'] = self.vec_hop['ang'][key[0], key[1]]
self.hop['tag'] = npc.add(self.lat.coor['tag'][key[0]],
self.lat.coor['tag'][key[1]])
