"""
Created on May 17 2020
@author: Pedram Tavadze
"""
# from .elkparser import ElkParser
from .splash import welcome
from .doscarplot import DosPlot
from .vaspxml import VaspXML
from .lobsterparser import LobsterDOSParser
from .qeparser import QEDOSParser
import numpy as np
import matplotlib.pyplot as plt
# import matplotlib
plt.rcParams["mathtext.default"] = "regular"
# Roman ['rm', 'cal', 'it', 'tt', 'sf',
# 'bf', 'default', 'bb', 'frak',
# 'circled', 'scr', 'regular']
plt.rcParams["font.family"] = "Arial"
plt.rc("font", size=18) # controls default text sizes
plt.rc("axes", titlesize=22) # fontsize of the axes title
plt.rc("axes", labelsize=22) # fontsize of the x and y labels
plt.rc("xtick", labelsize=22) # fontsize of the tick labels
plt.rc("ytick", labelsize=22) # fontsize of the tick labels
# plt.rc('legend', fontsize=22) # legend fontsize
# plt.rc('figure', titlesize=22) # fontsize of the figure title
[docs]def dosplot(
filename="vasprun.xml",
mode="plain",
interpolation_factor=None,
orientation="horizontal",
spin_colors=None,
colors=None,
spins=None,
atoms=None,
orbitals=None,
elimit=None,
dos_limit=None,
cmap="jet",
linewidth=1,
vmax=None,
vmin=None,
grid=False,
savefig=None,
title=None,
plot_total=True,
code="vasp",
labels=None,
items={},
ax=None,
plt_show=True,
verbose=True,
):
"""
This function plots the density of states in different formats
Parameters
----------
filename : str, optional (default ``'vasprun.xml'``)
The most important argument needed dosplot is
**filename**. **filename** defines the path to `vasprun.xml`
from the density of states calculation. If plotting is being
carried out in the directory of the calculation, one does not
need to specify this argument.
e.g. ``filename='~/SrVO3/DOS/vasprun.xml'``
mode : str, optional (default ``'plain'``)
**mode** defines the mode of the plot. This parameter will be
explained in details with exmaples in the tutorial.
options are ``'plain'``, ``'parametric'``,
``'parametric_line'``, ``'stack'``,
``'stack_orbitals'``, ``'stack_species'``.
e.g. ``mode='stack'``
interpolation_factor : int, optional (default ``None``)
Number of points in energy axis is multiplied by this factor
and interpolated using cubic
spline.
e.g. ``interpolation_factor=3``
orientation : str, optional (default ``horizontal'``)
The orientation of the DOS plot. options are
``'horizontal', 'vertical'``
e.g. ``orientation='vertical'``
spin_colors : list str or tuples, (optional ``spin_colors=['blue',
'red']``)
**spin_colors** represent the colors the different spin
ploarizations are going to be represented in the DOS
plot. These colors can be chosen from any type of color
acceptable by matplotlib(string,rgb,html).
e.g. ``spin_colors=['blue','red']``,
``spin_colors=[(0, 0, 1),(1, 0,0 )]``,
``spin_colors=['#0000ff','#ff0000']``
.. caution:: If the calculation is spin polarized one has to
provide two colors even if one is plotting one spin. I
disregard this cation if using default.
colors : list str or tuples, optional (default, optional)
``colors`` defines the color of plots filling the area under
the curve of Total density of states. This is only important in the
``mode=stack``, ``mode=stack_species``,
``mode=stack_orbitals``. To have a better sense of this
parameter refer to the stack plots of SrVO\ :sub:`3`\. These
colors can be chosen from any type of color acceptable by
matplotlib(string,rgb,html).
e.g. ``colors=['red', 'blue', 'green', 'magenta', 'cyan']``
spins : list int, optional
``spins`` defines plotting of different spins channels present
in the calculation, If the calculation is spin non-polorized
the spins will be set by default to ``spins=[0]``. if the
calculation is spin polorized this parameter can be set to 0
or 1 or both.
e.g. ``spins=[0, 1]``
atoms : list int, optional
``atoms`` define the projection of the atoms in the Density of
States. In other words it selects only the contribution of the
atoms provided. Atoms has to be a python list(or numpy array)
containing the atom indices. Atom indices has to be order of
the input files of DFT package. ``atoms`` is only relevant in
``mode='parametric'``, ``mode='parametric_line'``,
``mode='stack_orbitals'``. keep in mind that python counting
starts from zero.
e.g. for SrVO\ :sub:`3`\ we are choosing only the oxygen
atoms. ``atoms=[2, 3, 4]``, keep in mind that python counting
starts from zero, for a **POSCAR** similar to following::
Sr1 V1 O3
1.0
3.900891 0.000000 0.000000
0.000000 3.900891 0.000000
0.000000 0.000000 3.900891
Sr V O
1 1 3
direct
0.500000 0.500000 0.500000 Sr atom 0
0.000000 0.000000 0.000000 V atom 1
0.000000 0.500000 0.000000 O atom 2
0.000000 0.000000 0.500000 O atom 3
0.500000 0.000000 0.000000 O atom 4
if nothing is specified this parameter will consider all the
atoms present.
orbitals : list int, optional
``orbitals`` define the projection of orbitals in the density
of States. In other words it selects only the contribution of
the orbitals provided. Orbitals has to be a python list(or
numpy array) containing the Orbital indices. Orbitals indices
has to be order of the input files of DFT package. The
following table represents the indecies for different orbitals
in **VASP**.
+-----+-----+----+----+-----+-----+-----+-----+-------+
| s | py | pz | px | dxy | dyz | dz2 | dxz | x2-y2 |
+-----+-----+----+----+-----+-----+-----+-----+-------+
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
+-----+-----+----+----+-----+-----+-----+-----+-------+
``orbitals`` is only relavent in ``mode='parametric'``,
``mode='parametric_line'``, ``mode='stack_species'``.
e.g. ``orbitals=[1,2,3]`` will only select the p orbitals
while ``orbitals=[4,5,6,7,8]`` will select the d orbitals.
If nothing is specified pyprocar will select all the present
orbitals.
elimit : list float, optional
Energy window limit asked to plot. ``elimit`` has to be a two
element python list(or numpy array).
e.g. ``elimit=[-2, 2]``
The default is set to the minimum and maximum of the energy
window.
dos_limit : list float, optional
``dos_limit`` defines the density of states axis limits on the
graph. It is automatically set to select 10% higher than the
maximum of density of states in the specified energy window.
e.g. ``dos_limit=[0, 30]``
cmap : str , optional (default 'jet')
The color map used for color coding the projections. ``cmap``
is only relevant in ``mode='parametric'``. a full list of
color maps in matplotlib are provided in this web
page. `https://matplotlib.org/2.0.1/users/colormaps.html
<https://matplotlib.org/2.0.1/users/colormaps.html>`_
e.g. ``cmap='plasma'``
linewidth : str, optional (default 1)
The line width with which the total DOS is ploted
e.g. linewidth=2
vmax : float, optional
The maximum value in the color bar. ``cmap`` is only relevant
in ``mode='parametric'``.
e.g. ``vmax=1.0``
vmin : float, optional
The maximum value in the color bar. ``cmap`` is only relevant
in ``mode='parametric'``.
e.g. ``vmin=-1.0``
grid : bool, optional (default Flase)
Defines If a grid is plotted in the plot. The entry should be
python boolian.
e.g. ``grid=True``
savefig : str , optional (default None)
``savefig`` defines the file that the plot is going to be
saved in. ``savefig`` accepts all the formats accepted by
matplotlib such as png, pdf, jpg, ...
If not provided the plot will be shown in the
interactive matplotlib mode.
e.g. ``savefig='DOS.png'``, ``savefig='DOS.pdf'``
title : str, optional
Defines the plot title asked to be added above the plot. If
``title`` is not defined, PyProcar will not add any title.
e.g. ``title="Total Density of States SrVO_$3$"``. One can use
LaTex format as well.
plot_total : bool, optional (default ``True``)
If the total density of states is plotted as well as other
options. The entry should be python boolian.
e.g. ``plot_total=True``
code : str, optional (default ``'vasp'``)
Defines the Density Functional Theory code used for the
calculation. The default of this argument is vasp, so if the
cal is done in vasp one does not need to define this argumnet.
e.g. ``code=vasp``, ``code=elk``, ``code=abinit``
labels : list str, optional
``labels`` define the legends plotted in defining each spin.
e.g. ``labels=['Oxygen-Up','Oxygen-Down']``,
``labels=['Oxygen-'+r'$\\uparrow$','Oxygen-'+r'$\\downarrow$']``
Side means the string will be treated as raw string. This has
to be used if LaTex formating is used.
No default is used in the ``mode=plain``, ``mode=parametric``,
``mode=parametric_line``. In ``mode=stack``, `ack_species``,
``mode=stack_orbitals`` the labels are generated automatically
based on the other parameters such as atoms and orbitals.
items : dict, optional
``items`` is only relavent for ``mode='stack'``. stack will
plot the items defined with stacked filled areas under
curve. For clarification visit the examples in the
tutorial. ``items`` need to be provided as a python
dictionary, with keys being specific species and values being
projections of ``orbitals``. The following examples can
clarify the python lingo.
e.g. ``items={'Sr':[0],'O':[1,2,3],'V':[4,5,6,7,8]}`` or
``items=dict(Sr=[0],O=[1,2,3],V=[4,5,6,7,8])``. The two
examples are equivalent to each other. This will plot the
following curves stacked on top of each other. projection of s
orbital in Sr, projection of p orbitals in O and projection of
d orbitals in V.
The default is set to take every atom and every orbital. Which
will be equivalent to ``mode='stack_species'``
ax : matplotlib ax object, optional
``ax`` is a matplotlib axes. In case one wants to put plot
generated from this plot in a different figure and treat the
output as a subplot in a larger plot.
e.g. ::
>>> # Creates a figure with 3 rows and 2 colomuns
>>> fig, axs = plt.subplots(3, 2)
>>> x = np.linspace(-np.pi, np.pi, 1000)
>>> y = np.sin(x)
>>> axs[0, 0].plot(x, y)
>>> pyprocar.dosplot(mode='plain',ax=axs[2, 2]),elimit=[-2,2])
>>> plt.show()
plt_show : bool, optional (default ``True``)
whether to show the generated plot or skip to the saving.
e.g. ``plt_show=True``
Returns
-------
fig : matplotlib figure
The generated figure
ax : matplotlib ax object
The generated ax for this density of states.
If one chooses ``plt_show=False``, one can modify the plot
using this returned object.
e.g. ::
>>> fig, ax = pyprocar.dosplot(mode='plain', plt_show=False)
>>> ax.set_ylim(-2,2)
>>> fig.show()
"""
if mode not in [
'plain', 'parametric_line', 'parametric', 'stack_species',
'stack_orbitals', 'stack'
]:
raise ValueError(
"Mode should be choosed from ['plain', 'parametric_line','parametric','stack_species','stack_orbitals','stack']"
)
if verbose:
welcome()
# Verbose section
print("Script initiated")
print("code : ", code)
print("File name : ", filename)
print("mode : ", mode)
print("spins : ", spins)
print("atoms list : ", atoms)
print("orbs. list : ", orbitals)
print("energy range : ", elimit)
print("colormap : ", cmap)
print("vmax : ", vmax)
print("vmin : ", vmin)
print("grid enabled : ", grid)
print("savefig : ", savefig)
print("title : ", title)
total = plot_total
code = code.lower()
if orientation[0].lower() == 'h':
orientation = 'horizontal'
elif orientation[0].lower() == 'v':
orientation = 'vertical'
if code == "vasp":
vaspxml = VaspXML(filename=filename,
dos_interpolation_factor=interpolation_factor)
dos_plot = DosPlot(dos=vaspxml.dos, structure=vaspxml.structure)
if atoms is None:
atoms = list(np.arange(vaspxml.structure.natoms, dtype=int))
if spins is None:
spins = list(np.arange(len(vaspxml.dos.total)))
if orbitals is None:
orbitals = list(
np.arange(len(vaspxml.dos.projected[0][0]), dtype=int))
if elimit is None:
elimit = [vaspxml.dos.energies.min(), vaspxml.dos.energies.max()]
elif code == "lobster":
vaspxml = LobsterDOSParser(
filename="DOSCAR.lobster",
dos_interpolation_factor=interpolation_factor)
dos_plot = DosPlot(dos=vaspxml.dos, structure=vaspxml.structure)
if atoms is None:
atoms = list(np.arange(vaspxml.structure.natoms, dtype=int))
if spins is None:
spins = list(np.arange(len(vaspxml.dos.total)))
if orbitals is None:
orbitals = list(
np.arange(len(vaspxml.dos.projected[0][0]), dtype=int))
if elimit is None:
elimit = [vaspxml.dos.energies.min(), vaspxml.dos.energies.max()]
elif code == "qe":
vaspxml = QEDOSParser(nscfin="nscf.in",
pdosin="pdos.in",
outfile="scf.out",
dos_interpolation_factor=interpolation_factor)
dos_plot = DosPlot(dos=vaspxml.dos, structure=vaspxml.structure)
if atoms is None:
atoms = list(np.arange(vaspxml.structure.natoms, dtype=int))
if spins is None:
spins = list(np.arange(len(vaspxml.dos.total)))
if orbitals is None:
orbitals = list(
np.arange(len(vaspxml.dos.projected[0][0]), dtype=int))
if elimit is None:
elimit = [vaspxml.dos.energies.min(), vaspxml.dos.energies.max()]
if mode == "plain":
fig, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=spin_colors,
ax=ax,
orientation=orientation,
labels=labels,
linewidth=linewidth,
)
elif mode == "parametric_line":
if not total:
fig, ax1 = dos_plot.plot_parametric_line(
atoms=atoms,
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
ax=ax,
orientation=orientation,
labels=labels,
linewidth=linewidth,
)
else:
fig, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=[(0, 0, 0), (0, 0, 0)],
ax=ax,
orientation=orientation,
linewidth=linewidth,
)
_, ax1 = dos_plot.plot_parametric_line(
atoms=atoms,
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
ax=ax1,
orientation=orientation,
labels=labels,
linewidth=linewidth,
)
elif mode == "parametric":
if not total:
fig, ax1 = dos_plot.plot_parametric(
atoms=atoms,
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
cmap=cmap,
vmin=vmin,
vmax=vmax,
elimit=elimit,
ax=ax,
orientation=orientation,
labels=labels,
)
else:
fig, ax1 = dos_plot.plot_parametric(
atoms=atoms,
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
cmap=cmap,
vmin=vmin,
vmax=vmax,
elimit=elimit,
ax=ax,
orientation=orientation,
labels=labels,
)
_, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=[(0, 0, 0), (0, 0, 0)],
ax=ax1,
orientation=orientation,
linewidth=linewidth,
)
elif mode == "stack_species":
if not total:
fig, ax1 = dos_plot.plot_stack_species(
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
else:
fig, ax1 = dos_plot.plot_stack_species(
spins=spins,
orbitals=orbitals,
spin_colors=spin_colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
_, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=[(0, 0, 0), (0, 0, 0)],
ax=ax1,
orientation=orientation,
linewidth=linewidth,
)
elif mode == "stack_orbitals":
if not total:
fig, ax1 = dos_plot.plot_stack_orbitals(
spins=spins,
atoms=atoms,
spin_colors=spin_colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
else:
fig, ax1 = dos_plot.plot_stack_orbitals(
spins=spins,
atoms=atoms,
spin_colors=spin_colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
_, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=[(0, 0, 0), (0, 0, 0)],
ax=ax1,
orientation=orientation,
linewidth=linewidth,
)
elif mode == "stack":
if not total:
fig, ax1 = dos_plot.plot_stack(
items=items,
spins=spins,
spin_colors=spin_colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
else:
fig, ax1 = dos_plot.plot_stack(
items=items,
spins=spins,
spin_colors=colors,
colors=colors,
elimit=elimit,
figsize=(12, 6),
ax=ax,
orientation=orientation,
)
_, ax1 = dos_plot.plot_total(
spins=spins,
spin_colors=[(0, 0, 0), (0, 0, 0)],
ax=ax1,
orientation=orientation,
linewidth=linewidth,
)
cond1 = vaspxml.dos.energies >= elimit[0]
cond2 = vaspxml.dos.energies <= elimit[1]
cond = np.all([cond1, cond2], axis=0)
if dos_limit is not None:
ylim = dos_limit
else:
if len(spins) > 1:
ylim = [
vaspxml.dos.total[1, cond].max() * -1.1,
vaspxml.dos.total[0, cond].max() * 1.1
]
else:
ylim = [0, vaspxml.dos.total[spins[0], cond].max() * 1.1]
if orientation == "horizontal":
ax1.set_xlabel(r"$E-E_f$ [eV]")
ax1.set_ylabel("Density of States [a.u.]")
ax1.set_xlim(elimit)
ax1.set_ylim(ylim)
elif orientation == "vertical":
ax1.set_ylabel(r"$E-E_f$ [eV]")
ax1.set_xlabel("Density of States [a.u.]")
ax1.set_ylim(elimit)
ax1.set_xlim(ylim) # we use ylim because the plot is vertical
ax1.axhline(color="black", linestyle="--")
ax1.axvline(color="black", linestyle="--")
# fig.tight_layout()
if grid:
ax1.grid()
if labels or "stack" in mode:
ax1.legend()
if title:
ax1.set_title(title, fontsize=17)
if savefig:
fig.savefig(savefig, bbox_inches="tight")
plt.close(
) # Added by Nicholas Pike to close memory issue of looping and creating many figures
return None, None
else:
plt.show(block=plt_show)
return fig, ax1
#
#
## if __name__ == "__main__":
## bandsplot(mode='parametric',elimit=[-6,6],orbitals=[4,5,6,7,8],vmin=0,vmax=1, code='elk')
## knames=['$\Gamma$', '$X$', '$M$', '$\Gamma$', '$R$','$X$'],
## kticks=[0, 8, 16, 24, 38, 49])