nRow = len(ls.selectedTimeStep)/nCol
fig, ax = plt.subplots(1,1,sharex=False,sharey=True,figsize=(8,6))
SaveName = __file__.split('/')[-1].split('.')[0]
kpath = ls.kpath
cut = ls.cut
print kpath
specialKPoints = ls.specialKPoints
x = ls.x
h**o = dP.getHomo()
evolvingBands = range(0, h**o + 7)
time, exe = dP.getProjectedPartition()
time, eigen = dP.getAdiabaticEigenvalue()
colors = ma.getColors(5,cmap='gnuplot')
#for index, step in enumerate(ls.selectedTimeStep):
excited = np.abs(exe[0,kpath,:] - exe[0,kpath,:])
norm = ls.norm/np.max(exe[:,kpath,:] - exe[0,kpath,:])
eigenvalue = eigen[0,kpath,:]
line = []
scatter = []
for i in evolvingBands:
if i < h**o:
part = excited[:,i]
if ls.drawfill:
s = ax.fill_between(x, eigenvalue[:,i] - norm*part,
eigenvalue[:,i] + norm*part,
#!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import pyramids.io.result as dP
import pyramids.plot.setting as ma
import pyramids.plot.PlotUtility as pu
#------------------------------------------------------------------------------
time, exe = dP.getProjectedPartition()
time, eigen = dP.getAdiabaticEigenvalue()
#print eigen[:,1,:]
#h**o = dP.getHomo()
#print h**o
print exe.shape, eigen.shape
c = ma.getColors(exe.shape[2], cmap='brg')
norm = 50.0 #/np.max(exe[:,:,:] - exe[0,:,:])
#print norm
kpts = [0]
for kpt in kpts:
fig, ax = plt.subplots(1, 1, sharex=True, sharey=False, figsize=(8, 6))
SaveName = __file__.split('/')[-1].split('.')[0] + str(kpt)
h**o = 0
for i, band in enumerate(eigen[0, kpt, :]):
#print band
if band < 0:
h**o = i
evolvingBands = range(0, h**o + 40)
X, Y = np.meshgrid(time, eigen[0, kpt, evolvingBands])
Z = np.transpose(exe[0, kpt, evolvingBands] - exe[:, kpt, evolvingBands])
#print reciprocal_vectors
points = np.array([
(reciprocal_vectors[0, 0:2] * i + reciprocal_vectors[1, 0:2] * j +
reciprocal_vectors[2, 0:2] * k) for i in range(-1, 2)
for j in range(-1, 2) for k in range(0, 1)
])
#from ase.dft.kpoints import monkhorst_pack
#kpts = np.array([np.dot(k,atoms.cell) for k in monkhorst_pack((12,12,1))])
from scipy.spatial import Voronoi, voronoi_plot_2d
vor = Voronoi(points)
voronoi_plot_2d(vor, ax)
eigen = dp.readEigFile('siesta.EIG')
time, partAll = dp.getProjectedPartition()
xlimits = None
ylimits = None
if os.path.exists('localSetting.py'):
import localSetting as ls
conf = ls.nesting
xlimits = conf.xlimits
ylimits = conf.ylimits
import os
kargs = getPropertyFromPosition(
xlabel=r'$k_x (\AA^{-1})$',
ylabel=r"$k_y (\AA^{-1})$",
title='',
