from gpaw.transport.analysor import Transport_Plotter
import numpy as np
from pylab import *
import sys
plotter = Transport_Plotter()
plotter.plot_setup()
if len(sys.argv) <= 2:
if len(sys.argv[1]) <= 2:
nt = plotter.get_info('nty', int(sys.argv[1]), 0)
else:
tmp = sys.argv[1].split('-')
sam = int(tmp[0])
ref = int(tmp[1])
nt = plotter.get_info('nty', sam, 0) - plotter.get_info('nty', ref, 0)
else:
nt = plotter.get_info('nty', int(sys.argv[1]), int(sys.argv[2]))
matshow((nt[0]))
colorbar()
xlabel('Transport Direction')
ylabel('Pseudo Density')
show()
ren = vtk.vtkRenderer()
win = vtk.vtkRenderWindow()
win.AddRenderer(ren)
win.SetSize(800,600)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(win)
style = vtk.vtkInteractorStyleTrackballCamera()
iren.SetInteractorStyle(style)
atoms = plotter.atoms.copy()
calc = GPAW()
atoms.set_calculator(calc)
calc.initialize(atoms)
calc.scf.converged = True
if len(sys.argv) <= 2:
if len(sys.argv[1]) <= 2:
calc.forces.F_av = plotter.get_info('force', sys.argv[1])
else:
tmp = sys.argv[1].split('-')
ref = int(tmp[1])
sample = int(tmp[0])
calc.forces.F_av = plotter.get_info('force', sample) - plotter.get_info('force', ref)
else:
calc.forces.F_av = plotter.get_info('force', sys.argv[1], sys.argv[2])
print 'maximum', np.max(abs(calc.forces.F_av))
va = vtkAtoms(atoms)
va.add_cell()
va.add_axes()
va.add_forces()
va.add_actors_to_renderer(ren)
if usewx:
from gpaw.transport.analysor import Transport_Plotter
import numpy as np
from pylab import *
from ase import Hartree
import sys
plotter = Transport_Plotter()
plotter.plot_setup()
if len(sys.argv)<= 2:
if len(sys.argv[1]) <= 2:
vt = plotter.get_info('vt', int(sys.argv[1]), 0)
else:
tmp = sys.argv[1].split('-')
sam = int(tmp[0])
ref = int(tmp[1])
vt = plotter.get_info('vt', sam, 0) - plotter.get_info('vt', ref, 0)
else:
vt = plotter.get_info('vt', int(sys.argv[1]), int(sys.argv[2]))
plot(vt[0]*Hartree, 'b-o')
xlabel('Transport Direction')
ylabel('Effective Potential(eV)')
show()
ren = vtk.vtkRenderer()
win = vtk.vtkRenderWindow()
win.AddRenderer(ren)
win.SetSize(800, 600)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(win)
style = vtk.vtkInteractorStyleTrackballCamera()
iren.SetInteractorStyle(style)
atoms = plotter.atoms.copy()
calc = GPAW()
atoms.set_calculator(calc)
calc.initialize(atoms)
calc.scf.converged = True
if len(sys.argv) <= 2:
if len(sys.argv[1]) <= 2:
calc.forces.F_av = plotter.get_info('force', sys.argv[1])
else:
tmp = sys.argv[1].split('-')
ref = int(tmp[1])
sample = int(tmp[0])
calc.forces.F_av = plotter.get_info(
'force', sample) - plotter.get_info('force', ref)
else:
calc.forces.F_av = plotter.get_info('force', sys.argv[1], sys.argv[2])
print 'maximum', np.max(abs(calc.forces.F_av))
va = vtkAtoms(atoms)
va.add_cell()
va.add_axes()
va.add_forces()
va.add_actors_to_renderer(ren)
bias_step = int(sys.argv[1])
plotter=Transport_Plotter(fd)
plotter.plot_setup()
dos = plotter.dos(bias_step)
ee=np.linspace(-5,5,201)
plot(ee, dos, 'b-o')
dense_level=1
if dense_level>1:
from scipy import interpolate
tck = interpolate.splrep(ee, dos, s=0)
numb = len(ee)
newee = np.linspace(ee[0], ee[-1], numb * (dense_level))
newtc = interpolate.splev(newee, tck, der=0)
ee = newee
dos = newdos
plot(ee, dos, 'r-o')
eye = np.zeros([10, 1]) + 1
bias = plotter.get_info('bias', bias_step)
f1 = bias[0] * eye
f2 = bias[1] * eye
a1 = np.max(dos)
l1 = np.linspace(0, a1, 10)
plot(f1, l1, 'r--')
plot(f2, l1, 'r--')
show()
pdos = plotter.partial_dos(bias_step, 0, 0, None, atom_indices, orbital_type)
plot(energies, pdos, flags[i])
dense_level = 1
if dense_level > 1:
from scipy import interpolate
tck = interpolate.splrep(energies, pdos, s=0)
numb = len(energies)
newee = np.linspace(energies[0], energies[-1], numb * (dense_level))
newpdos = interpolate.splev(newee, tck, der=0)
ee = newee
pdos = newpdos
plot(ee, pdos, flags[i])
legends.append(item)
legend(legends)
bias = plotter.get_info("bias", bias_step)
eye = np.zeros([10, 1]) + 1
f1 = bias[0] * eye
f2 = bias[1] * eye
a1 = np.max(pdos)
l1 = np.linspace(0, a1, 10)
plot(f1, l1, "r--")
plot(f2, l1, "r--")
xlabel("Energy(eV)")
ylabel("Partial Density of States(Electron/eV)")
show()
from gpaw.transport.analysor import Transport_Plotter
import numpy as np
from pylab import *
import sys
plotter = Transport_Plotter()
plotter.plot_setup()
if len(sys.argv)<=2:
if len(sys.argv[1]) <= 2:
nt = plotter.get_info('nty', int(sys.argv[1]), 0)
else:
tmp = sys.argv[1].split('-')
sam = int(tmp[0])
ref = int(tmp[1])
nt = plotter.get_info('nty', sam, 0) - plotter.get_info('nty', ref, 0)
else:
nt = plotter.get_info('nty', int(sys.argv[1]), int(sys.argv[2]))
matshow((nt[0]))
colorbar()
xlabel('Transport Direction')
ylabel('Pseudo Density')
show()
element = element[:min]
for j, atom in enumerate(plotter.atoms):
if atom.symbol == element and j > small and j < big:
if equal is None or (equal is not None and j == equal):
atom_indices.append(j)
#print atom_indices
if orbital == 'A':
orbital_type = None
else:
orbital_type = orbital
biases = []
charges = []
for bs in range(int(bias_steps)):
try:
charge = plotter.charge(bs, 0, atom_indices, orbital_type)
bias = plotter.get_info('bias', bs, 0)
charges.append(charge)
biases.append(bias[0]-bias[1])
except IOError:
print ' no file for bias_step', bs
biases = np.array(biases)
charges = np.array(charges)
plot(biases, charges, flags[i])
dense_level=1
if dense_level>1:
from scipy import interpolate
tck = interpolate.splrep(biases, charges, s=0)
numb = len(biases)
newbiases = np.linspace(biases[0], biases[-1], numb * (dense_level))
newcharges = interpolate.splev(newbiases, tck, der=0)
biases = newbiases
from gpaw.transport.analysor import Transport_Plotter
import numpy as np
from pylab import *
import sys
plotter = Transport_Plotter()
plotter.plot_setup()
if len(sys.argv) <= 2:
if len(sys.argv[1]) <= 2:
vt = plotter.get_info('vtx', int(sys.argv[1]), 0)
else:
tmp = sys.argv[1].split('-')
sam = int(tmp[0])
ref = int(tmp[1])
vt = plotter.get_info('vtx', sam, 0) - plotter.get_info('vtx', ref, 0)
else:
vt = plotter.get_info('vtx', int(sys.argv[1]), int(sys.argv[2]))
matshow(vt[0])
colorbar()
xlabel('Transport Direction')
ylabel('Effective Potential')
show()
