def get_interpolated_gap(self, tol=0.001, abs_tol=False, spin=None):
"""
Expects a DOS object and finds the gap
Args:
tol: tolerance in occupations for determining the gap
abs_tol: Set to True for an absolute tolerance and False for a
relative one.
spin: Possible values are None - finds the gap in the summed
densities, Up - finds the gap in the up spin channel,
Down - finds the gap in the down spin channel.
Returns:
(gap, cbm, vbm):
Tuple of floats in eV corresponding to the gap, cbm and vbm.
"""
tdos = self.y if len(self.ydim) == 1 else np.sum(self.y, axis=1)
if not abs_tol:
tol = tol * tdos.sum() / tdos.shape[0]
energies = self.x
below_fermi = [i for i in range(len(energies)) if energies[i] < self.efermi and tdos[i] > tol]
above_fermi = [i for i in range(len(energies)) if energies[i] > self.efermi and tdos[i] > tol]
vbm_start = max(below_fermi)
cbm_start = min(above_fermi)
if vbm_start == cbm_start:
return 0.0, self.efermi, self.efermi
# Interpolate between adjacent values
terminal_dens = tdos[vbm_start : vbm_start + 2][::-1]
terminal_energies = energies[vbm_start : vbm_start + 2][::-1]
start = get_linear_interpolated_value(terminal_dens, terminal_energies, tol)
terminal_dens = tdos[cbm_start - 1 : cbm_start + 1]
terminal_energies = energies[cbm_start - 1 : cbm_start + 1]
end = get_linear_interpolated_value(terminal_dens, terminal_energies, tol)
return end - start, end, start
def get_interpolated_value(self, x: float) -> List[float]:
"""
Returns an interpolated y value for a particular x value.
Args:
x: x value to return the y value for
Returns:
Value of y at x
"""
if len(self.ydim) == 1:
return get_linear_interpolated_value(self.x, self.y, x)
return [get_linear_interpolated_value(self.x, self.y[:, k], x) for k in range(self.ydim[1])]
def get_interpolated_value(self, x):
"""
Returns an interpolated y value for a particular x value.
Args:
x: x value to return the y value for
Returns:
Value of y at x
"""
if len(self.ydim) == 1:
return get_linear_interpolated_value(self.x, self.y, x)
else:
return [get_linear_interpolated_value(self.x, self.y[:, k], x)
for k in range(self.ydim[1])]
def test_get_linear_interpolated_value(self):
xvals = [0, 1, 2, 3, 4, 5]
yvals = [3, 6, 7, 8, 10, 12]
self.assertEqual(
coord.get_linear_interpolated_value(xvals, yvals, 3.6), 9.2)
self.assertRaises(ValueError, coord.get_linear_interpolated_value,
xvals, yvals, 6)
def get_interpolated_value(self, frequency):
"""
Returns interpolated density for a particular frequency.
Args:
frequency: frequency to return the density for.
"""
return get_linear_interpolated_value(self.frequencies,
self.densities, frequency)
def get_interpolated_value(self, energy, integrated=False):
"""
Returns the COHP for a particular energy.
Args:
energy: Energy to return the COHP value for.
"""
inter = {}
for spin in self.cohp:
if not integrated:
inter[spin] = get_linear_interpolated_value(
self.energies, self.cohp[spin], energy)
elif self.icohp is not None:
inter[spin] = get_linear_interpolated_value(
self.energies, self.icohp[spin], energy)
else:
raise ValueError("ICOHP is empty.")
return inter
def get_interpolated_value(self, frequency):
"""
Returns interpolated density for a particular frequency.
Args:
frequency: frequency to return the density for.
"""
return get_linear_interpolated_value(self.frequencies,
self.densities, frequency)
def get_interpolated_value(self, energy: float):
"""
Returns interpolated density for a particular energy.
Args:
energy: Energy to return the density for.
"""
f = {}
for spin in self.densities.keys():
f[spin] = get_linear_interpolated_value(self.energies, self.densities[spin], energy)
return f
def get_interpolated_value(self, energy, integrated=False):
"""
Returns the COHP for a particular energy.
Args:
energy: Energy to return the COHP value for.
"""
inter = {}
for spin in self.cohp:
if not integrated:
inter[spin] = get_linear_interpolated_value(self.energies,
self.cohp[spin],
energy)
elif self.icohp is not None:
inter[spin] = get_linear_interpolated_value(self.energies,
self.icohp[spin],
energy)
else:
raise ValueError("ICOHP is empty.")
return inter
def get_interpolated_gap(self, tol=0.001, abs_tol=False, spin=None):
"""
Expects a DOS object and finds the gap
Args:
tol: tolerance in occupations for determining the gap
abs_tol: Set to True for an absolute tolerance and False for a
relative one.
spin: Possible values are None - finds the gap in the summed
densities, Up - finds the gap in the up spin channel,
Down - finds the gap in the down spin channel.
Returns:
(gap, cbm, vbm):
Tuple of floats in eV corresponding to the gap, cbm and vbm.
"""
tdos = self.y if len(self.ydim) == 1 else np.sum(self.y, axis=1)
if not abs_tol:
tol = tol * tdos.sum() / tdos.shape[0]
energies = self.x
below_fermi = [i for i in range(len(energies))
if energies[i] < self.efermi and tdos[i] > tol]
above_fermi = [i for i in range(len(energies))
if energies[i] > self.efermi and tdos[i] > tol]
vbm_start = max(below_fermi)
cbm_start = min(above_fermi)
if vbm_start == cbm_start:
return 0.0, self.efermi, self.efermi
else:
# Interpolate between adjacent values
terminal_dens = tdos[vbm_start:vbm_start + 2][::-1]
terminal_energies = energies[vbm_start:vbm_start + 2][::-1]
start = get_linear_interpolated_value(terminal_dens,
terminal_energies, tol)
terminal_dens = tdos[cbm_start - 1:cbm_start + 1]
terminal_energies = energies[cbm_start - 1:cbm_start + 1]
end = get_linear_interpolated_value(terminal_dens,
terminal_energies, tol)
return end - start, end, start
def get_interpolated_value(self, energy):
"""
Returns interpolated density for a particular energy.
Args:
energy: Energy to return the density for.
"""
f = {}
for spin in self.densities.keys():
f[spin] = get_linear_interpolated_value(self.energies,
self.densities[spin],
energy)
return f
