def plot_mobility_kconv(self, eh=0, component='xx', itemp=0, spin=0, fontsize=14, ax=None, **kwargs):
"""
Plot the convergence of the mobility as a function of the number of k-points.
Args:
eh: 0 for electrons, 1 for holes.
component: Cartesian component to plot ('xx', 'xy', ...)
itemp: temperature index.
spin: Spin index.
fontsize: fontsize for legends and titles
ax: |matplotlib-Axes| or None if a new figure should be created.
Returns: |matplotlib-Figure|
"""
ax, fig, plt = get_ax_fig_plt(ax=ax)
ax.grid(True)
i, j = abu.s2itup(component)
irta = 0
res, temps = []
for ncfile in self.abifiles:
#kptrlattx, kptrlatty, kptrlattz = ncfile.ngkpt
kptrlatt = ncfile.reader.read_value("kptrlatt")
kptrlattx = kptrlatt[0, 0]
kptrlatty = kptrlatt[1, 1]
kptrlattz = kptrlatt[2, 2]
# nctkarr_t('mobility_mu',"dp", "three, three, two, ntemp, nsppol, nrta")]
mobility = ncfile.reader.read_variable("mobility_mu")[irta, spin, itemp, eh, j, i]
#print(mobility)
res.append([kptrlattx, mobility])
temps.append(ncfile.tmesh[itemp])
res.sort(key=lambda t: t[0])
res = np.array(res)
#print(res)
size = 14
ylabel = r"%s mobility (cm$^2$/(V$\cdot$s))" % {0: "Electron", 1: "Hole"}[eh]
ax.set_ylabel(ylabel, size=size)
#if "title" not in kwargs:
# title = r"$\frac{1}{N_k} \sum_{nk} \delta(\epsilon - \epsilon_{nk})$"
# ax.set_title(title, fontsize=fontsize)
from fractions import Fraction
ratio1 = Fraction(kptrlatty, kptrlattx)
ratio2 = Fraction(kptrlattz, kptrlattx)
text1 = '' if ratio1.numerator == ratio1.denominator else \
r'$\frac{{{0}}}{{{1}}}$'.format(ratio1.numerator, ratio1.denominator)
text2 = '' if ratio2.numerator == ratio2.denominator else \
r'$\frac{{{0}}}{{{1}}}$'.format(ratio2.numerator, ratio2.denominator)
ax.set_xlabel(r'Homogeneous $N_k \times$ ' + text1 + r'$N_k \times$ ' + text2 + r'$N_k$ $\mathbf{k}$-point grid',
size=size)
ax.plot(res[:,0], res[:,1], **kwargs)
ax.legend(loc="best", shadow=True, fontsize=fontsize)
return fig
def read_mobility(self, eh, itemp, component, spin):
"""
Read mobility from the TRANSPORT.nc file
The mobility is computed separately for electrons and holes.
"""
i,j = abu.s2itup(component)
wvals = self.read_variable("vvdos_mesh")
mobility = self.read_variable("mobility")[eh,itemp,i,j,spin,:]
return wvals, mobility
def plot_mobility_conv(self, eh=0, component='xx', itemp=0, spin=0, fontsize=14, ax=None, **kwargs):
"""
Plot the convergence of the mobility obtained in a list of files
Args:
eh: 0 for electrons, 1 for holes
component: Component to plot ('xx', 'xy', ...)
itemp: Index of the temperature.
spin: Spin index.
fontsize: fontsize for legends and titles
ax: |matplotlib-Axes| or None if a new figure should be created.
Returns: |matplotlib-Figure|
"""
ax, fig, plt = get_ax_fig_plt(ax=ax)
ax.grid(True)
i, j = abu.s2itup(component)
res = []
for ncfile in self.abifiles:
kptrlatt = ncfile.reader.read_value('kptrlatt')
kptrlattx = kptrlatt[0, 0]
kptrlatty = kptrlatt[1, 1]
kptrlattz = kptrlatt[2, 2]
#nkpt = ncfile.nkpt
mobility = ncfile.reader.read_value('mobility_mu')[itemp][i,j][spin][eh]
res.append([kptrlattx, mobility])
res.sort(key=lambda t: t[0])
res = np.array(res)
size = 14
if eh == 0:
ax.set_ylabel(r'Electron mobility (cm$^2$/(V$\cdot$s))', size=size)
elif eh == 1:
ax.set_ylabel(r'Hole mobility (cm$^2$/(V$\cdot$s))', size=size)
else:
raise ValueError("Invalid value for eh argument: %s" % eh)
from fractions import Fraction
ratio1 = Fraction(kptrlatty, kptrlattx)
ratio2 = Fraction(kptrlattz, kptrlattx)
text1 = '' if ratio1.numerator == ratio1.denominator else \
r'$\frac{{{0}}}{{{1}}}$'.format(ratio1.numerator, ratio1.denominator)
text2 = '' if ratio2.numerator == ratio2.denominator else \
r'$\frac{{{0}}}{{{1}}}$'.format(ratio2.numerator, ratio2.denominator)
ax.set_xlabel(r'Homogeneous $N_k \times$ '+ text1 + r'$N_k \times$ '+ text2 + r'$N_k$ $\mathbf{k}$-point grid',
size=size)
ax.plot(res[:,0], res[:,1], **kwargs)
ax.legend(loc="best", shadow=True, fontsize=fontsize)
return fig
def read_mobility(self, eh, itemp, component, spin):
"""
Read mobility from the TRANSPORT.nc file
The mobility is computed separately for electrons and holes.
"""
# nctkarr_t('mobility',"dp", "edos_nw, nsppol, three, three, ntemp, two"), &
i, j = abu.s2itup(component)
wvals = self.read_variable("vvdos_mesh")
mobility = self.read_variable("mobility")[eh,itemp,i,j,spin,:]
return wvals, mobility
def read_mobility(self, eh, itemp, component, spin, irta=0):
"""
Read mobility from the RTA.nc file
The mobility is computed separately for electrons and holes.
"""
# nctkarr_t('mobility',"dp", "three, three, edos_nw, ntemp, two, nsppol, nrta")
i, j = abu.s2itup(component)
wvals = self.read_variable("edos_mesh")
#wvals = self.read_value("edos_mesh") * abu.Ha_eV
mobility = self.read_variable("mobility")[irta, spin, eh, itemp, :, j, i]
return wvals, mobility
def read_vvdos(self, component='xx', spin=1):
"""
Read the group velocity density of states
The vvdos_vals array has 3 dimensions (9,nsppolplus1,nw)
1. 3x3 components of the tensor
2. the spin polarization + 1 for the sum
3. the number of frequencies
"""
i,j = abu.s2itup(component)
wmesh = self.read_variable("vvdos_mesh")[:] * abu.Ha_eV
vals = self.read_variable("vvdos_vals")
vvdos = vals[i,j,spin,:]
return wmesh, vvdos
def plot_transport_tensors_mu(self, component="xx", spin=0,
what_list=("sigma", "seebeck", "kappa", "pi"),
colormap="jet", fontsize=8, **kwargs):
"""
Plot selected Cartesian components of transport tensors as a function
of the chemical potential mu at the given temperature.
Args:
ax_list: |matplotlib-Axes| or None if a new figure should be created.
fontsize: fontsize for legends and titles
Return: |matplotlib-Figure|
"""
i, j = abu.s2itup(component)
num_plots, ncols, nrows, what_list = x2_grid(what_list)
ax_list, fig, plt = get_axarray_fig_plt(None, nrows=nrows, ncols=ncols,
sharex=True, sharey=False, squeeze=False)
ax_list = ax_list.ravel()
# don't show the last ax if numeb is odd.
if num_plots % ncols != 0: ax_list[-1].axis("off")
cmap = plt.get_cmap(colormap)
for iax, (what, ax) in enumerate(zip(what_list, ax_list)):
irow, icol = divmod(iax, ncols)
# nctkarr_t('seebeck', "dp", "three, three, edos_nw, ntemp, nsppol, nrta")
what_var = self.reader.read_variable(what)
for irta in range(self.nrta):
for itemp, temp in enumerate(self.tmesh):
ys = what_var[irta, spin, itemp, :, j, i]
label = "T = %dK" % temp
if itemp == 0: label = "%s (%s)" % (label, irta2s(irta))
if irta == 0 and itemp > 0: label = None
ax.plot(self.edos_mesh_eV, ys, c=cmap(itemp / self.ntemp), label=label, **style_for_irta(irta))
ax.grid(True)
ax.set_ylabel(transptens2latex(what, component))
ax.legend(loc="best", fontsize=fontsize, shadow=True)
if irow == nrows - 1:
ax.set_xlabel(r"$\mu$ (eV)")
self._add_vline_at_bandedge(ax, spin, "both")
if "title" not in kwargs:
fig.suptitle("Transport tensors", fontsize=fontsize)
return fig
def plot_vvtau_dos(self, component="xx", spin=0, ax=None, colormap="jet", fontsize=8, **kwargs):
r"""
Plot (v_i * v_j * tau) DOS.
$\frac{1}{N_k} \sum_{nk} v_i v_j \delta(\epsilon - \epsilon_{nk})$
Args:
component: Cartesian component to plot: "xx", "yy" "xy" ...
ax: |matplotlib-Axes| or None if a new figure should be created.
colormap: matplotlib colormap.
fontsize (int): fontsize for titles and legend
Return: |matplotlib-Figure|
"""
i, j = abu.s2itup(component)
ax, fig, plt = get_ax_fig_plt(ax=ax)
cmap = plt.get_cmap(colormap)
for irta in range(self.nrta):
# nctkarr_t('vvtau_dos', "dp", "edos_nw, three, three, ntemp, nsppol, nrta")
var = self.reader.read_variable("vvtau_dos")
for itemp, temp in enumerate(self.tmesh):
vvtau_dos = var[irta, spin, itemp, j, i, :] / (2 * abu.Ha_s)
label = "T = %dK" % temp
if (itemp == 0): label = "%s (%s)" % (label, irta2s(irta))
if (irta == 0 and itemp > 0): label = None
ax.plot(self.edos_mesh_eV, vvtau_dos, c=cmap(itemp / self.ntemp), label=label, **style_for_irta(irta))
# This to plot the vv dos along without tau
#if itemp == 1:
# # nctkarr_t('vv_dos', "dp", "edos_nw, three, three, nsppol"), &
# vv_dos_var = self.reader.read_variable("vv_dos")
# vv_dos = vv_dos_var[spin, j, i] # / (2 * abu.Ha_s)
# ax.plot(self.edos_mesh_eV, vv_dos, c=cmap(itemp / self.ntemp), label='VVDOS' % temp)
self._add_vline_at_bandedge(ax, spin, "both")
ax.grid(True)
ax.set_xlabel('Energy (eV)')
ax.set_ylabel(r'$v_{%s} v_{%s} \tau$ DOS' % (component[0], component[1]))
ax.set_yscale('log')
ax.legend(loc="best", shadow=True, fontsize=fontsize)
if "title" not in kwargs:
vvt = r'v_{%s} v_{%s} \tau' % (component[0], component[1])
title = r"$\frac{1}{N_k} \sum_{nk} %s\,\delta(\epsilon - \epsilon_{nk})$" % vvt
fig.suptitle(title, fontsize=fontsize)
return fig
def read_vvdos_tau(self, itemp, component='xx', spin=1):
"""
Read the group velocity density of states times lifetime for different temperatures
The vvdos_tau array has 4 dimensions (ntemp,9,nsppolplus1,nw)
1. the number of temperatures
2. 3x3 components of the tensor
3. the spin polarization + 1 for the sum
4. the number of frequencies
"""
i, j = abu.s2itup(component)
wmesh = self.read_variable("vvdos_mesh")[:] * abu.Ha_eV
vals = self.read_variable("vvdos_tau")
vvdos_tau = vals[itemp,i,j,spin,:] / (2 * abu.Ha_s)
return wmesh, vvdos_tau
def plot_mobility(self,
eh=0,
irta=0,
component='xx',
spin=0,
ax=None,
colormap='jet',
fontsize=8,
yscale="log",
**kwargs):
"""
Read the mobility from the netcdf file and plot it
Args:
component: Component to plot: "xx", "yy" "xy" ...
ax: |matplotlib-Axes| or None if a new figure should be created.
colormap: matplotlib colormap.
fontsize (int): fontsize for titles and legend
Return: |matplotlib-Figure|
"""
ax, fig, plt = get_ax_fig_plt(ax=ax)
cmap = plt.get_cmap(colormap)
# nctkarr_t('mobility',"dp", "three, three, edos_nw, ntemp, two, nsppol, nrta")
mu_var = self.reader.read_variable("mobility")
i, j = abu.s2itup(component)
for irta in range(self.nrta):
for itemp, temp in enumerate(self.tmesh):
mu = mu_var[irta, spin, eh, itemp, :, j, i]
label = "T = %dK" % temp
if (itemp == 0): label = "%s (%s)" % (label, irta2s(irta))
if (irta == 0 and itemp > 0): label = None
ax.plot(self.edos_mesh_eV,
mu,
c=cmap(itemp / self.ntemp),
label=label,
**style_for_irta(irta))
self._add_vline_at_bandedge(ax, spin, "cbm" if eh == 0 else "vbm")
ax.grid(True)
ax.set_xlabel('Fermi level (eV)')
ax.set_ylabel(r'%s-mobility $\mu_{%s}(\epsilon_F)$ (cm$^2$/Vs)' %
(eh2s(eh), component))
ax.set_yscale(yscale)
ax.legend(loc="best", shadow=True, fontsize=fontsize)
return fig
def read_vvdos_tau(self, itemp, component='xx', spin=1):
"""
Read the group velocity density of states
The vvdos_vals array has 3 dimensions (3, 3, nsppolplus1, nw)
1. 3x3 components of the tensor
2. the spin polarization + 1 for the sum
3. the number of frequencies
"""
# nctkarr_t('vvdos_tau', "dp", "edos_nw, nsppol_plus1, three, three, ntemp"), &
i, j = abu.s2itup(component)
wmesh = self.read_variable("vvdos_mesh")[:] * abu.Ha_eV
vals = self.read_variable("vvdos_tau")
vvdos_tau = vals[itemp, i, j, spin, :] / (2 * abu.Ha_s)
return wmesh, vvdos_tau
