pivotpy 1.1.4

A description of your project

PivotPy

A Python Processing Tool for Vasp Input/Output. A CLI is available in Powershell, see Vasp2Visual.

<style>a{text-decoration: none !important;color:lightkblue;font-weight:bold;} a:focus,a:active,a:hover{color:hotpink !important;}</style>

 ▶ Index● 
 ▶ XmlElementTree 
 ▶ StaticPlots 
 ▶ InteractivePlots 
 ▶ Utilities 
 ▶ StructureIO 
 ▶ Widgets 
 ▶ MainAPI 

Install

pip install pivotpy

How to use

• Use commnad pivotpy in regular terminal to quickly launch documentation any time.
• See Full Documentation.
• For CLI, use Vasp2Visual.
• See PDF Slides for detailed introduction.

Changelog for version 1.1.1

splot_[rgb,color,dos]_lines and iplot_[rgb,dos]_lines now accept another arguement query_data which replaces elements, orbs, labels if provided. This argument is a dictionary whose keys are replaced by labels, last item in its values is in the form of (elements, orbs). It will be extend in future for fermi plots when you select individul bands as well.

These two are equivalent and later one is simplified with each item showing a single color/line:

plot_command(elements=[range(2),range(2)],orbs=[0,[1,2,3]],labels=['s','p'])  
plot_command(query_data = {'s': (range(2),0),'p': (range(2),[1,2,3])}) # version >= 1.1.1

Changelog for version 1.0.10 onward

A new module api is added which consists of selective functions and classes and it is enough for common user. Now import pivotpy as pp exports only whaterver is inside api, access other modules separately.

CLI commnds

• Use pivotpy in system terminal to launch DOCS.
• Use pivotpy_get_poscar to download POSCAR.
• Use pivotpy_get_kpath to create fine controlled KPATH.
• More to come.

New: Plot in Terminal without GUI

Use pp.plt2text(colorful=True/False) after matplotlib's code and your figure will appear in terminal. You need to zoom out alot to get a good view like below.

Tip: Use file matplotlib2terminal.py on github independent of this package to plot in terminal.

New: Ipywidgets-based GUI

See GIF here:

New: Live Slides in Jupyter Notebook

Navigate to ipyslides or do pip install ipyslides to create beautiful data driven presentation in Jupyter Notebook.

import os, pivotpy as pp
with pp.set_dir('E:/Research/graphene_example/ISPIN_1/bands'):
    vr=pp.Vasprun(elim=[-5,5])
vr.data

Loading from PowerShell Exported Data...





Data(
    sys_info = Data(
        SYSTEM = C2
        NION = 2
        NELECT = 8
        TypeION = 1
        ElemName = ['C']
        E_Fermi = -3.3501
        fields = ['s', 'py', 'pz', 'px', 'dxy', 'dyz', 'dz2', 'dxz', 'x2-y2']
        incar = Data(
            SYSTEM = C2
            PREC = high
            ALGO = N
            LSORBIT = T
            NELMIN = 7
            ISMEAR = 0
            SIGMA = 0.10000000
            LORBIT = 11
            GGA = PS
        )
        ElemIndex = [0, 2]
        ISPIN = 1
    )
    dim_info = Data(
        kpoints = (NKPTS,3)
        kpath = (NKPTS,1)
        bands = ⇅(NKPTS,NBANDS)
        dos = ⇅(grid_size,3)
        pro_dos = ⇅(NION,grid_size,en+pro_fields)
        pro_bands = ⇅(NION,NKPTS,NBANDS,pro_fields)
    )
    kpoints = <ndarray:shape=(90, 3)>
    kpath = <list:len=90>
    bands = Data(
        E_Fermi = -3.3501
        ISPIN = 1
        NBANDS = 21
        evals = <ndarray:shape=(90, 21)>
        indices = range(1, 22)
    )
    tdos = Data(
        E_Fermi = -3.3501
        ISPIN = 1
        tdos = <ndarray:shape=(301, 3)>
    )
    pro_bands = Data(
        labels = ['s', 'py', 'pz', 'px', 'dxy', 'dyz', 'dz2', 'dxz', 'x2-y2']
        pros = <ndarray:shape=(2, 90, 21, 9)>
    )
    pro_dos = Data(
        labels = ['s', 'py', 'pz', 'px', 'dxy', 'dyz', 'dz2', 'dxz', 'x2-y2']
        pros = <ndarray:shape=(2, 301, 10)>
    )
    poscar = Data(
        SYSTEM = C2
        volume = 105.49324928
        basis = <ndarray:shape=(3, 3)>
        rec_basis = <ndarray:shape=(3, 3)>
        positions = <ndarray:shape=(2, 3)>
        labels = ['C 1', 'C 2']
        unique = Data(
            C = range(0, 2)
        )
    )
)

Matplotlib's static plots

• Add anything from legend,colorbar, colorwheel. In below figure, all three are shown.
• Use aliases such as sbands, sdos,srgb,irgb,scolor,idos for plotting.

#collapse_input
import pivotpy as pp, numpy as np
import matplotlib.pyplot as plt 
vr1=pp.Vasprun('E:/Research/graphene_example/ISPIN_2/bands/vasprun.xml')
vr2=pp.Vasprun('E:/Research/graphene_example/ISPIN_2/dos/vasprun.xml')
axs = pp.get_axes(ncols=3,widths=[2,1,2.2],sharey=True,wspace=0.05,figsize=(8,2.6))
elements=[0,[0],[0,1]]
orbs=[[0],[1],[2,3]]
labels=['s','$p_z$','$(p_x+p_y)$']
ti_cks=dict(ktick_inds=[0,30,60,-1],ktick_vals=['Γ','M','K','Γ'])
args_dict=dict(elements=elements,orbs=orbs,labels=labels,elim=[-20,15])
vr1.splot_bands(ax=axs[0],**ti_cks,elim=[-20,15])
vr1.splot_rgb_lines(ax=axs[2],**args_dict,**ti_cks,colorbar=True,)
vr2.splot_dos_lines(ax=axs[1],vertical=True,spin='both',include_dos='pdos',**args_dict,legend_kwargs={'ncol': 3},colormap='RGB_m')
axs[2].color_wheel(xy=(0.7,1.15),scale=0.2,labels=[l+'$^{⇅}$' for l in labels])
pp._show() 

 elements[0] = 0 is converted to range(0, 2) which picks all ions of 'C'.To just pick one ion at this index, wrap it in brackets [].

Interactive plots using plotly

args_dict['labels'] = ['s','p_z','p_x+p_y']
fig1 = vr1.iplot_rgb_lines(**args_dict)
#pp.iplot2html(fig1) #Do inside Google Colab, fig1 inside Jupyter
from IPython.display import Markdown
Markdown("[See Interactive Plot](https://massgh.github.io/InteractiveHTMLs/iGraphene.html)")

See Interactive Plot

Brillouin Zone (BZ) Processing

• Look in pivotpy.sio module or pivotpy.api.POSCAR class for details on generating mesh and path of KPOINTS as well as using Materials Projects' API to get POSCAR right in the working folder. Below is a screenshot of interactive BZ plot. You can double click on blue points and hit Ctrl + C to copy the high symmetry points relative to reciprocal lattice basis vectors.
• Same color points lie on a sphere, with radius decreasing as red to blue and gamma point in gold color. These color help distinguishing points but the points not always be equivalent, for example in FCC, there are two points on mid of edges connecting square-hexagon and hexagon-hexagon at equal distance from center but not the same points.
• Any colored point's hover text is in gold background.

Look the output of pivotpy.sio.splot_bz.

import pivotpy as pp 
pp.sio.splot_bz([[1,0,0],[0,1,0],[0,0,1]],color=(1,1,1,0.2),light_from=(0.5,0,2),colormap='RGB').set_axis_off()
#pp.iplot2html(fig2) #Do inside Google Colab, fig1 inside Jupyter
from IPython.display import Markdown
Markdown("[See Interactive BZ Plot](https://massgh.github.io/InteractiveHTMLs/BZ.html)")

See Interactive BZ Plot

Plotting Two Calculations Side by Side

• Here we will use shift_kpath to demonstrate plot of two calculations on same axes side by side

#nbdev_collapse_input
import matplotlib.pyplot as plt
import pivotpy as pp 
plt.style.use('bmh')
vr1=pp.Vasprun('E:/Research/graphene_example/ISPIN_1/bands/vasprun.xml')
shift_kpath=vr1.data.kpath[-1] # Add last point from first export in second one.
vr2=pp.Vasprun('E:/Research/graphene_example/ISPIN_2/bands/vasprun.xml',shift_kpath=shift_kpath,try_pwsh=False)
last_k=vr2.data.kpath[-1]
axs=pp.get_axes(figsize=(5,2.6))
K_all=[*vr1.data.kpath,*vr2.data.kpath] # Merge kpath for ticks
kticks=[K_all[i] for i in [0,30,60,90,120,150,-1]]
ti_cks=dict(xticks=kticks,xt_labels=['Γ','M','K','Γ','M','K','Γ'])
vr1.splot_bands(ax=axs)
vr2.splot_bands(ax=axs,txt='Graphene(Left: ISPIN=1, Right: ISPIN=2)',ctxt='m')
axs.modify_axes(xlim=[0,last_k],ylim=[-10,10],**ti_cks)
pp._show()

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Interpolation

Amost every bandstructure and DOS plot function has an argument interp_nk which is a dictionary with keys n (Number of additional points between adjacent points) and k (order of interpolation 0-3). n > k must hold.

#collapse_input
import pivotpy as pp, matplotlib.pyplot as plt
plt.style.use('ggplot')
k = vr1.data.kpath
ef = vr1.data.bands.E_Fermi
evals = vr1.data.bands.evals-ef
#Let's interpolate our graph to see effect. It is useful for colored graphs.
knew,enew=pp.interpolate_data(x=k,y=evals,n=10,k=3)
plot = plt.plot(k,evals,'m',lw=5,label='real data')
plot = plt.plot(k,evals,'w',lw=1,label='interpolated',ls='dashed')
pp.s_plots.add_text(ax=plt.gca(),txts='Graphene')

LOCPOT,CHG Visualization

check out the class pivotpy.LOCPOT to visulize local potential/charge and magnetization in a given direction.

Running powershell commands from python.

Some tasks are very tideious in python while just a click way in powershell. See below, and try to list processes in python yourself to see the difference!

pp.g_utils.ps2std(ps_command='(Get-Process)[0..4]')

NPM(K)    PM(M)      WS(M)     CPU(s)      Id  SI Process
Name
------    -----      -----     ------      --  -- -------
6     1.36       5.43       0.00    7052   0 Aggreg…
18     6.52      15.29       0.00    5104   0 AppHel…
25    21.84      43.36       6.64   14344   1 Applic…
8     1.85       7.72       0.02   20412   1 AppVSh…
8     1.57       6.93       0.00   26512   0 AppVSh…

Advancaed: Poweshell Cell/Line Magic %%ps/%ps

• You can create a IPython cell magic to run powershell commands directly in IPython Shell/Notebook (Powershell core installation required).
• Cell magic can be assigned to a variable foo by %%ps --out foo
• Line magic can be assigned to a variable by foo = %ps powershell_command

Put below code in ipython profile's startup file (create one) "~/.ipython/profile_default/startup/powershell_magic.py"

from IPython.core.magic import register_line_cell_magic
from IPython import get_ipython
@register_line_cell_magic
def ps(line, cell=None):
    if cell:
        return get_ipython().run_cell_magic('powershell',line,cell)
    else:
        get_ipython().run_cell_magic('powershell','--out posh_output',line)
        return posh_output.splitlines()

Additionally you need to add following lines in "~/.ipython/profile_default/ipython_config.py" file to make above magic work.

from traitlets.config.application import get_config
c = get_config()
c.ScriptMagics.script_magics = ['powershell']
c.ScriptMagics.script_paths = {
    'powershell' : 'powershell.exe -noprofile -command -',
    'pwsh': 'pwsh.exe -noprofile -command -'
}

%%ps 
Get-ChildItem 'E:\Research\graphene_example\'

    Directory: E:\Research\graphene_example





Mode                 LastWriteTime         Length Name    

----                 -------------         ------ ----    

da----        11/28/2021   8:04 PM                ISPIN_1 

da----          5/9/2020   1:05 PM                ISPIN_2 

-a----          5/9/2020   1:01 PM          75331 OUTCAR  

-a----          5/9/2020   1:01 PM         240755 vasprun.

                                                  xml     

x = %ps (Get-ChildItem 'E:\Research\graphene_example\').Name
x

['ISPIN_1', 'ISPIN_2', 'OUTCAR', 'vasprun.xml']

Functions Reference

<style>a{text-decoration: none !important;color:lightkblue;font-weight:bold;} a:focus,a:active,a:hover{color:hotpink !important;}</style>

 ▶ Index● 
 ▶ XmlElementTree 
 ▶ StaticPlots 
 ▶ InteractivePlots 
 ▶ Utilities 
 ▶ StructureIO 
 ▶ Widgets 
 ▶ MainAPI