Commit df446344 authored by Marco Govoni's avatar Marco Govoni
Browse files

Preparing 3.1.1

parent 3179d1ea
......@@ -64,7 +64,7 @@ author = u'Marco Govoni'
# built documents.
#
# The short X.Y version.
version = '3.1.0'
version = '3.1.1'
# The full version, including alpha/beta/rc tags.
release = version
......
%% Cell type:markdown id: tags:
This tutorial can be downloaded [link](http://greatfire.uchicago.edu/west-public/westpy/raw/master/doc/tutorials/westpy_100.ipynb).
%% Cell type:markdown id: tags:
# 1.0 Getting Started: Ground State
%% Cell type:markdown id: tags:
We are going to generate an input file for the [QuantumEspresso](https://www.quantum-espresso.org/) code or [Qbox](http://qboxcode.org/). Each code will compute the ground state electronic stucture for the methane molecule using Density Functional Theory.
%% Cell type:markdown id: tags:
## Step 1: Load westpy
%% Cell type:code id: tags:
``` python
from westpy import *
```
%%%% Output: stream
_ _ _____ _____ _____
| | | | ___/ ___|_ _|
| | | | |__ \ `--. | |_ __ _ _
| |/\| | __| `--. \ | | '_ \| | | |
\ /\ / |___/\__/ / | | |_) | |_| |
\/ \/\____/\____/ \_/ .__/ \__, |
| | __/ |
|_| |___/
WEST version : 3.1.0
Today : 2018-06-29 15:23:25.768394
WEST version : 3.1.1
Today : 2018-09-19 15:21:13.244247
%% Cell type:markdown id: tags:
## Step 2: Geometry
%% Cell type:code id: tags:
``` python
geom = Geometry()
```
%% Cell type:markdown id: tags:
Let's define a cubic cell of edge 25 Bohr.
%% Cell type:code id: tags:
``` python
geom.setCell((25,0,0),(0,25,0),(0,0,25))
```
%% Cell type:markdown id: tags:
We load the atomic positions from a XYZ file, available online.
%% Cell type:code id: tags:
``` python
geom.addAtomsFromOnlineXYZ( "http://www.west-code.org/doc/training/methane/CH4.xyz" )
```
%% Cell type:markdown id: tags:
We associate pseudopotential files to each species.
%% Cell type:code id: tags:
``` python
geom.addSpecies( "C", "http://www.quantum-simulation.org/potentials/sg15_oncv/upf/C_ONCV_PBE-1.0.upf")
geom.addSpecies( "H", "http://www.quantum-simulation.org/potentials/sg15_oncv/upf/H_ONCV_PBE-1.0.upf")
```
%% Cell type:markdown id: tags:
## Step 3.1: Ground State
%% Cell type:markdown id: tags:
The ground state calculation is defined by the geometry, a choice of the exchange-correlation functional, and by setting an energy cutoff for the wavefunctions.
%% Cell type:code id: tags:
``` python
gs = GroundState(geom,xc="PBE",ecut=40.0)
```
%% Cell type:markdown id: tags:
We are now able to generate the input file for QuantumEspresso.
%% Cell type:code id: tags:
``` python
gs.generateInputPW()
```
%%%% Output: stream
Generated file: pw.in
%% Cell type:markdown id: tags:
We can inspect the file pw.in
%% Cell type:code id: tags:
``` python
with open("pw.in","r") as file :
data = file.read()
print(data)
```
%%%% Output: stream
&CONTROL
calculation = 'scf'
restart_mode = 'from_scratch'
pseudo_dir = './'
outdir = './'
prefix = 'calc'
wf_collect = .TRUE.
/
&SYSTEM
ibrav = 0
nat = 5
ntyp = 2
ecutwfc = 40.0
nbnd = 8
input_dft = 'PBE'
nosym = .TRUE.
noinv = .TRUE.
/
&ELECTRONS
diago_full_acc = .TRUE.
conv_thr = 1.d-8
/
ATOMIC_SPECIES
C 12.011 C_ONCV_PBE-1.0.upf
H 1.008 H_ONCV_PBE-1.0.upf
ATOMIC_POSITIONS {bohr}
C 0.0 0.0 0.0
H 1.185992116575257 -1.185803143962673 1.185992116575257
H -1.185992116575257 1.185992116575257 1.185992116575257
H -1.185992116575257 -1.185992116575257 -1.185992116575257
H 1.185992116575257 1.185992116575257 -1.185992116575257
K_POINTS {gamma}
CELL_PARAMETERS {bohr}
25.0 0.0 0.0
0.0 25.0 0.0
0.0 0.0 25.0
%% Cell type:markdown id: tags:
We can optionally also download the pseudopotentials files.
%% Cell type:code id: tags:
``` python
gs.downloadPseudopotentials()
```
%%%% Output: stream
Downloaded file: C_ONCV_PBE-1.0.upf , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/upf/C_ONCV_PBE-1.0.upf
Downloaded file: H_ONCV_PBE-1.0.upf , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/upf/H_ONCV_PBE-1.0.upf
%% Cell type:markdown id: tags:
## Step 3.2: Ground State with Qbox
%% Cell type:markdown id: tags:
To generate the input for Qbox we can simply update Species to use the xml formats.
%% Cell type:code id: tags:
``` python
gs.updateSpecies("C", "http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml")
gs.updateSpecies("H", "http://www.quantum-simulation.org/potentials/sg15_oncv/xml/H_ONCV_PBE-1.0.xml")
```
%% Cell type:markdown id: tags:
We are now able to generate the input file for QuantumEspresso.
%% Cell type:code id: tags:
``` python
gs.generateInputQbox()
```
%%%% Output: stream
Generated file: qbox.in
%% Cell type:markdown id: tags:
We can inspect the file qbox.in
%% Cell type:code id: tags:
``` python
with open("qbox.in","r") as file :
data = file.read()
print(data)
```
%%%% Output: stream
set cell 25.0 0.0 0.0 0.0 25.0 0.0 0.0 0.0 25.0
species Carbon http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
species Hydrogen http://www.quantum-simulation.org/potentials/sg15_oncv/xml/H_ONCV_PBE-1.0.xml
atom C1 Carbon 0.0 0.0 0.0
atom H2 Hydrogen 1.185992116575257 -1.185803143962673 1.185992116575257
atom H3 Hydrogen -1.185992116575257 1.185992116575257 1.185992116575257
atom H4 Hydrogen -1.185992116575257 -1.185992116575257 -1.185992116575257
atom H5 Hydrogen 1.185992116575257 1.185992116575257 -1.185992116575257
set ecut 40.0
set wf_dyn JD
set xc PBE
set scf_tol 1.e-8
randomize_wf
run -atomic_density 0 100 5
save gs.xml
%% Cell type:markdown id: tags:
We can optionally also download the pseudopotentials files.
%% Cell type:code id: tags:
``` python
gs.downloadPseudopotentials()
```
%%%% Output: stream
Downloaded file: C_ONCV_PBE-1.0.xml , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
Downloaded file: H_ONCV_PBE-1.0.xml , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/xml/H_ONCV_PBE-1.0.xml
%% Cell type:code id: tags:
``` python
```
......
%% Cell type:markdown id: tags:
This tutorial can be downloaded [link](http://greatfire.uchicago.edu/west-public/westpy/raw/master/doc/tutorials/westpy_101.ipynb).
%% Cell type:markdown id: tags:
# 1.1 Ground State Calculation with Qbox
%% Cell type:markdown id: tags:
We are going to generate an input file for the [Qbox](http://qboxcode.org/) code. The code will compute the ground state electronic stucture for the methane molecule using Density Functional Theory.
%% Cell type:markdown id: tags:
## Step 1: Load westpy
%% Cell type:code id: tags:
``` python
from westpy import *
```
%%%% Output: stream
_ _ _____ _____ _____
| | | | ___/ ___|_ _|
| | | | |__ \ `--. | |_ __ _ _
| |/\| | __| `--. \ | | '_ \| | | |
\ /\ / |___/\__/ / | | |_) | |_| |
\/ \/\____/\____/ \_/ .__/ \__, |
| | __/ |
|_| |___/
WEST version : 3.1.0
Today : 2018-06-29 15:23:42.948747
WEST version : 3.1.1
Today : 2018-09-19 15:21:57.535713
%% Cell type:markdown id: tags:
## Step 2: Geometry
%% Cell type:code id: tags:
``` python
geom = Geometry()
```
%% Cell type:markdown id: tags:
Let's define a cubic cell of edge 25 Bohr.
%% Cell type:code id: tags:
``` python
geom.setCell((25,0,0),(0,25,0),(0,0,25))
```
%% Cell type:markdown id: tags:
We load the atomic positions from a XYZ file, available online.
%% Cell type:code id: tags:
``` python
geom.addAtomsFromOnlineXYZ( "http://www.west-code.org/doc/training/methane/CH4.xyz" )
```
%% Cell type:markdown id: tags:
We associate pseudopotential files to each species.
%% Cell type:code id: tags:
``` python
geom.addSpecies( "C", "http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml")
geom.addSpecies( "H", "http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml")
```
%% Cell type:markdown id: tags:
## Step 3.1: Ground State
%% Cell type:markdown id: tags:
The ground state calculation is defined by the geometry, a choice of the exchange-correlation functional, and by setting an energy cutoff for the wavefunctions.
%% Cell type:code id: tags:
``` python
gs = GroundState(geom,xc="PBE",ecut=40.0)
```
%% Cell type:markdown id: tags:
We are now able to generate the input file for Qbox.
%% Cell type:code id: tags:
``` python
gs.generateInputQbox()
```
%%%% Output: stream
Generated file: qbox.in
%% Cell type:markdown id: tags:
We can inspect the file qbox.in
%% Cell type:code id: tags:
``` python
with open("qbox.in","r") as file :
data = file.read()
print(data)
```
%%%% Output: stream
set cell 25.0 0.0 0.0 0.0 25.0 0.0 0.0 0.0 25.0
species Carbon http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
species Hydrogen http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
atom C1 Carbon 0.0 0.0 0.0
atom H2 Hydrogen 1.185992116575257 -1.185803143962673 1.185992116575257
atom H3 Hydrogen -1.185992116575257 1.185992116575257 1.185992116575257
atom H4 Hydrogen -1.185992116575257 -1.185992116575257 -1.185992116575257
atom H5 Hydrogen 1.185992116575257 1.185992116575257 -1.185992116575257
set ecut 40.0
set wf_dyn JD
set xc PBE
set scf_tol 1.e-8
randomize_wf
run -atomic_density 0 100 5
save gs.xml
%% Cell type:markdown id: tags:
We can optionally also download the pseudopotentials files.
%% Cell type:code id: tags:
``` python
gs.downloadPseudopotentials()
```
%%%% Output: stream
Downloaded file: C_ONCV_PBE-1.0.xml , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
Downloaded file: C_ONCV_PBE-1.0.xml , from url: http://www.quantum-simulation.org/potentials/sg15_oncv/xml/C_ONCV_PBE-1.0.xml
%% Cell type:code id: tags:
``` python
```
......
%% Cell type:markdown id: tags:
This tutorial can be downloaded [link](http://greatfire.uchicago.edu/west-public/westpy/raw/master/doc/tutorials/westpy_200.ipynb).
%% Cell type:markdown id: tags:
# 2.0 Plot Density of States
%% Cell type:markdown id: tags:
We are going to plot the electronic density of states.
%% Cell type:markdown id: tags:
## Step 1: Load westpy
%% Cell type:code id: tags:
``` python
from westpy import *
```
%%%% Output: stream
_ _ _____ _____ _____
| | | | ___/ ___|_ _|
| | | | |__ \ `--. | |_ __ _ _
| |/\| | __| `--. \ | | '_ \| | | |
\ /\ / |___/\__/ / | | |_) | |_| |
\/ \/\____/\____/ \_/ .__/ \__, |
| | __/ |
|_| |___/
WEST version : 3.1.0
Today : 2018-06-29 15:24:08.077663
WEST version : 3.1.1
Today : 2018-09-19 15:22:31.298822
%% Cell type:markdown id: tags:
## Step 2: Electronic Structure
%% Cell type:code id: tags:
``` python
es = ElectronicStructure()
```
%% Cell type:markdown id: tags:
We add keys that will be used to browse the electronic structure.
%% Cell type:code id: tags:
``` python
es.addKey("eks","Kohn-Sham energy (eV)")
es.addKey("eqp","Quasiparticle energy (eV)")
```
%% Cell type:markdown id: tags:
We add three data points.
%% Cell type:code id: tags:
``` python
es.addDataPoint([1,1,1],"eks",-4.6789)
es.addDataPoint([1,1,2],"eks",-4.3789)
es.addDataPoint([1,1,1],"eqp",-4.5789)
```
%% Cell type:markdown id: tags:
We can plot the DOS for both the key "eks" and "eqp"
%% Cell type:code id: tags:
``` python
%matplotlib inline
es.plotDOS(k=1,s=1,energyKeys=["eks","eqp"],energyRange=[-5,-4,0.01])
```
%%%% Output: stream
Requested (emin,emax) : -5 -4
Detected (emin,emax) : -4.6789 -4.3789
output written in : dos.png
waiting for user to close image preview...
%%%% Output: display_data
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)
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)
%% Cell type:code id: tags:
``` python
```
......
from setuptools import setup
setup(name='westpy',
version='3.1.0',
version='3.1.1',
packages=['westpy'],
description='Python analysis tools for WEST',
url='https://github.com/west-code-development/westpy.git',
......
......@@ -9,7 +9,7 @@ from westpy.dataContainer import *
from westpy.electronicStructure import *
from westpy.session import *
__version__ = '3.1.0'
__version__ = '3.1.1'
def header() :
"""Prints welcome header."""
......
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