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()