def read_single_S_list(filen, i, j):
filen_i = filen+".%i.%i" % (i,j)
print "reading file: "+filen_i
try:
data = scat.read_S(data_direc, filen_i)
return data
except Exception:
if 'problems' in globals():
problems.append(filen_i)
print "WARNING: problem reading "+filen_i
return np.zeros((1, 3*nfreq, 2*nin_max, 2*nin_max), dtype='complex')
def read_single_S_list(filen, i, j):
filen_i = filen + ".%i.%i" % (i, j)
print "reading file: " + filen_i
try:
data = scat.read_S(data_direc, filen_i)
return data
except Exception:
if 'problems' in globals():
problems.append(filen_i)
print "WARNING: problem reading " + filen_i
return np.zeros((1, nfreq, 2 * nin_max, 2 * nin_max), dtype='complex')
plot_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/"
try:
obstacles = np.loadtxt(plot_direc + 'potential.dat', usecols=(1, ))
obst_mask = abs(obstacles) == 0
obst_ratio = float(np.shape(obstacles[obst_mask])[0]) / float(
np.shape(obstacles)[0])
print "filling factor of obstacles: %5f" % (1.0 - obst_ratio)
except:
obst_ratio = 0.94
print "WARNING: automatically assuming filling fraction to be 0.06"
# Weyl estimate for dwell time: A / 2Pi = W * L * (1-fill) / 2Pi
Weyl = [10 * L * 10 * obst_ratio / (2 * Pi)] * nfreq
energs = scat.read_S(data_direc, filen + ".0.0")[2]
if (len(energs) == 0):
kmin = 3.1 * np.pi / 10.
kmax = 4.9 * np.pi / 10.
dk = 0.5 * (kmin + kmax) * 10**(-7)
else:
kvals = np.sqrt(2 * energs)
dk = (kvals[-1] - kvals[-3]) / 2.0
dims = np.take(
scat.read_S(data_direc, filen + ".0.0")[1] / 2, np.arange(1, 3 * nfreq, 3))
nin_max = np.max(dims)
def read_single_S_list(filen, i, j):
filen_i = filen + ".%i.%i" % (i, j)
#!/usr/bin/env python import numpy as np import scipy as sp import scipy.optimize as spopt import matplotlib.pyplot as plt import sys from math import pi as Pi from Utils import utils as ut from Scattering import scattering2D as scat filen = str(sys.argv[1]) # namestring of calculation n = int(sys.argv[2]) # number of calculation dims = int(sys.argv[3]) # number of open modes in left lead data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/scatterdata/" energs = scat.read_S(data_direc, filen+".%i.0"%n)[2] kvals = np.sqrt(2*energs) dk = (kvals[-1] - kvals[-2]) / 1.0 filen_i = filen+".%i.%i" % (n,0) print "reading file: "+filen_i S = scat.read_S(data_direc, filen_i)[0] q_mean = np.trace(scat.calc_Q(S,dk)[0]) /(2*dims) print q_mean.real
#!/usr/bin/env python
import numpy as np
from Scattering import scattering2D as scat
from Utils_green import utils as ut
import matplotlib.pyplot as plt
filen = "sp18"
file_path = "/home/lv70071/ambichl/greens_code/calculations/Spiral-20141105/" + filen + "/"
d = 1.0
pphwl = 10
L_lead = 15.0 * d
S, dims, energs = scat.read_S(file_path, filen, old_ver=0)
nin = dims/2
Nw = np.shape(dims)[0]
modes_max = np.sqrt(2.0 * energs[-1]) * d / np.pi
# hier z.B. kleine numerische Ungenauigkeiten!
nyout = np.floor(modes_max * pphwl)
dx = d / (nyout + 1.0)
L_lead += dx
t = []
for w in range(Nw):
#t.append(S[w][:nin[w],nin[w]:])
t.append(S[w][nin[w]:,:nin[w]])
flux_factors = []
t_perf = []
for e in energs:
data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/scatterdata/"
plot_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/"
try:
obstacles = np.loadtxt(plot_direc + 'potential.dat', usecols=(1,))
obst_mask = abs(obstacles) == 0
obst_ratio = float(np.shape(obstacles[obst_mask])[0]) / float(np.shape(obstacles)[0])
print "filling factor of obstacles: %5f" % (1.0-obst_ratio)
except:
obst_ratio = 0.94
print "WARNING: automatically assuming filling fraction to be 0.06"
# Weyl estimate for dwell time: A / 2Pi = W * L * (1-fill) / 2Pi
Weyl = [10*L*10 * obst_ratio / (2*Pi)]*nfreq
energs = scat.read_S(data_direc, filen+".0.0")[2]
if (len(energs)==0):
kmin = 3.1 * np.pi / 10.
kmax = 4.9 * np.pi / 10.
dk = 0.5 * (kmin+kmax) * 10**(-7)
else:
kvals = np.sqrt(2*energs)
dk = (kvals[-1] - kvals[-3]) / 2.0
dims = np.take(scat.read_S(data_direc, filen+".0.0")[1]/2, np.arange(1,3*nfreq,3))
nin_max = np.max(dims)
def read_single_S_list(filen, i, j):
filen_i = filen+".%i.%i" % (i,j)
print "reading file: "+filen_i
try:
from Calc import transmission as trans
from Calc import localization as local
if (len(sys.argv)!=6):
sys.exit("ABORT: parameters filen, # of radius variations, # of configurations, # of frequency variations, length of system [W] needed")
filen = str(sys.argv[1]) # namestring of calculation
nr = int(sys.argv[2]) # number of radius variations
nconf = int(sys.argv[3]) # number of configurations to be averaged over
nfreq = int(sys.argv[4]) # number of frequency steps scanned over
L = float(sys.argv[5]) # length of system in units of width
data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/scatterdata/"
energs = scat.read_S(data_direc, filen+".0.0")[2]
if (len(energs)==0):
kmin = 3.1 * np.pi / 10.
kmax = 4.9 * np.pi / 10.
dk = 0.5 * (kmin+kmax) * 10**(-7)
else:
kvals = np.sqrt(2*energs)
dk = (kvals[-1] - kvals[-3]) / 2.0
dims = scat.read_S(data_direc, filen+".0.0")[1]/2
nin_max = np.max(dims)
def read_single_S_list(filen, i, j):
filen_i = filen+".%i.%i" % (i,j)
print "reading file: "+filen_i
try:
else:
print "specify machine (VSC: 1, VSC2: 2)"
if machine == 1:
pic_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC/Fibres-20130819/" + pic_filen + "/")
elif machine == 2:
pic_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + pic_filen + "/")
plot_direc = data_direc
fullout = False
S, dims = scat.read_S(data_direc, filen, old_ver=1)
modes = int(max(dims)/2)
if (len(dims)%3 == 0):
Nk = len(dims)/3
else:
sys.exit("ABORT: # of S matrices not divisible by 3")
if (refmodes > int(min(dims)/2)):
print ("WARNING: # of modes under consideration (%i)"
"> # minimum number of modes (%i)") % (refmodes,int(min(dims)/2))
t , t_q = trans.calc_t(S, dims, refmodes)
#trans.write_teigvals(t_q, refmodes)
q = []
lead_width = float(par['lead_width'])
nyout = int(par['nyout'])
modes_min = float(par['modes_min'])
modes_max = float(par['modes_max'])
nin = int(par['refmodes']) # nin = refmodes
ptc = int(par['ptc'])
except KeyError:
raw_input("WARNING: parameter missing in pinput.dat")
kmean = 0.5 * (modes_max + modes_min) * np.pi / lead_width
dk = kmean * 10**(-8)
nin_Max = int(0.5 * (modes_max + modes_min)) # nin_Max = n_open_modes
dy = lead_width / (nyout + 1)
yrange = np.arange(1,nyout+1)*dy
S, dims, energs = scat.read_S('./', filen)
t = []
t_q = []
for i in range(3):
m = dims[i]/2
n = min(m, nin)
t.append( S[i][m:,0:m] ) # full t-matrix
t_q.append( S[i][m:m+n,0:n] ) # considered part of t-matrix
def calc_modes(n):
'''
calculate normalized n-th lead mode
In Flo's code y-axis points downwards, y=0 is upper egde of lead;
modes are chosen such that most upper point is real and positive.
from Calc import localization as local
if (len(sys.argv) != 6):
sys.exit(
"ABORT: parameters filen, # of radius variations, # of configurations, # of frequency variations, length of system [W] needed"
)
filen = str(sys.argv[1]) # namestring of calculation
nr = int(sys.argv[2]) # number of radius variations
nconf = int(sys.argv[3]) # number of configurations to be averaged over
nfreq = int(sys.argv[4]) # number of frequency steps scanned over
L = float(sys.argv[5]) # length of system in units of width
data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/scatterdata/"
energs = scat.read_S(data_direc, filen + ".0.0")[2]
if (len(energs) == 0):
kmin = 3.1 * np.pi / 10.
kmax = 4.9 * np.pi / 10.
dk = 0.5 * (kmin + kmax) * 10**(-7)
else:
kvals = np.sqrt(2 * energs)
dk = (kvals[-1] - kvals[-3]) / 2.0
dims = scat.read_S(data_direc, filen + ".0.0")[1] / 2
nin_max = np.max(dims)
def read_single_S_list(filen, i, j):
filen_i = filen + ".%i.%i" % (i, j)
print "reading file: " + filen_i
modes_min = float(par['modes_min'])
modes_max = float(par['modes_max'])
refmodes = int(par['refmodes']) # number of modes to be considered
W = float(par['W'])
pphwl = float(par['points_per_hwl'])
except KeyError:
raw_input("WARNING: parameter missing in Abmessung.xml")
# read in scattering matrices
data_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + filen + "/")
print "Reading scattering matrices"
if (not os.path.exists("scatter."+filen+".dat.npy")):
S, dims, energs = scat.read_S(data_direc, filen, old_ver=0)
np.save("scatter."+filen+".dat", (S, dims, energs))
else:
S, dims, energs = np.load("scatter."+filen+".dat.npy")
# other parameters
pixel = True # whether system is transformed to y-eigenbasis
#pixel = False # whether system is transformed to y-eigenbasis
Nav = 1 # number of random noise configurations to be averaged
#phase_only = False # whether optimization w.r.t. phase only
phase_only = True # whether optimization w.r.t. phase only
#ds0 = 5.0 # step size for gradient in optimization
ds0 = 1e-2
#ds0 = 0.001
proj_list = np.zeros((refmodes,), dtype="complex")
'file'] # namestring of calculation where scatter data is stored
modes_min = float(par['modes_min'])
modes_max = float(par['modes_max'])
refmodes = int(par['refmodes']) # number of modes to be considered
W = float(par['W'])
pphwl = float(par['points_per_hwl'])
except KeyError:
raw_input("WARNING: parameter missing in Abmessung.xml")
# read in scattering matrices
data_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + filen + "/")
print "Reading scattering matrices"
if (not os.path.exists("scatter." + filen + ".dat.npy")):
S, dims, energs = scat.read_S(data_direc, filen, old_ver=0)
np.save("scatter." + filen + ".dat", (S, dims, energs))
else:
S, dims, energs = np.load("scatter." + filen + ".dat.npy")
# other parameters
pixel = True # whether system is transformed to y-eigenbasis
#pixel = False # whether system is transformed to y-eigenbasis
Nav = 1 # number of random noise configurations to be averaged
#phase_only = False # whether optimization w.r.t. phase only
phase_only = True # whether optimization w.r.t. phase only
#ds0 = 5.0 # step size for gradient in optimization
ds0 = 1e-2
#ds0 = 0.001
proj_list = np.zeros((refmodes, ), dtype="complex")
proj_list[:10] = 1.0
def read_single_S_list(filen, i, j):
filen_i = filen+".%i.%i" % (i,j)
return scat.read_S(data_direc, filen_i)
par = ut.read_input(data_direc)
try:
nr = int(par['nr']) # number of radius variations
nconf = int(par['nconf']) # number of configurations to be averaged over
nfreq = int(par['nfreq']) # number of frequency steps scanned over
lead_width = float(par['lead_width'])
nyout = int(par['nyout'])
except KeyError:
raw_input("WARNING: parameter missing in pinput.dat")
#energs = scat.read_S(data_direc, filen+".0.0")[2]
#kvals = np.sqrt(2*energs)
#dk = (kvals[-1] - kvals[-3]) / 2.0
dims = np.take(scat.read_S(data_direc + "/scatterdata/", filen + ".0.0")[1]/2, np.arange(1,3*nfreq,3))
nin_max = np.max(dims)
def read_state(filen, i, j, w, m):
filen_i = filen + ".%i.%i.%04i.%04i" % (i,j,w,m)
print "reading state: "+filen_i
try:
data = np.loadtxt(data_direc + "/states/" + "state." + filen_i + ".streu.dat",
dtype ='float', skiprows=1, usecols=(1,2), unpack=True)
state = data[0] + imag_i * data[1]
return state
except Exception:
print "WARNING: problem reading state "+filen_i
return np.array(0.)
def read_refind(filen, i, j):
Nfile = filemax - filemin + 1
data_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + filen + "/")
Slist = []
for i in np.arange(filemin, filemax+1):
file_i = "fi%i" % i
scatter_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/fi%i/" % i)
print "Reading scattering matrices fi%i" % i
if (not os.path.exists("scatter."+file_i+".dat.npy")):
S, dims, energs = scat.read_S(scatter_direc, file_i, old_ver=0)
np.save(data_direc + "scatter." + file_i + ".dat", (S, dims, energs))
else:
S, dims, energs = np.load(data_direc + "scatter." + file_i + ".dat.npy")
Slist.append(S)
for i in range(max(0,Nseg-Nfile)):
el = np.random.randint(low=0, high=len(Slist))
Slist.append(Slist[el]) # if Nseg > Nfile append randomly chosen S-matrices
Slist = np.array(Slist)
Nw = len(dims)
dw = np.sqrt(2.0*energs[2]) - np.sqrt(2.0*energs[1])
#ppwhl = 10
#W = 1.
#L = 10.*W
#kmin = modes_min * Pi / W
#kmax = modes_max * Pi / W
#kmean = 0.5*(kmax+kmin)
#dk = kmean * 10**-8
#Nk = 7
dk = 0.00023626
S, dims = scat.read_S(direc, filen)
modes = int(max(dims)/2)
if (refmodes > int(min(dims)/2):
sys.exit("ABORT: # of modes under consideration ($i) > # number of modes (%i)" % (refmodes,modes))
exit
t = []
t_q = []
for i in range(3*Nk):
m = dimlist[i]/2
n = min(m, refmodes)
t.append( S[i][m:,0:m] ) # full t-matrix
t_q.append( S[i][m:m+n,0:n] ) # considered part of t-matrix
#!/usr/bin/env python
import numpy as np
from Scattering import scattering2D as scat
from Utils import utils as ut
import sys
if (len(sys.argv)!=2):
sys.exit("ABORT: filen needed")
filen = str(sys.argv[1]) # namestring of calculation
S_dis, dims, energs = scat.read_S('./', filen+'.dis')
S_clean, dims, energs = scat.read_S('./', filen+'.clean')
dk = np.sqrt(2.0*energs[-1]) - np.sqrt(2.0*energs[-2])
t_dis = []
t_clean = []
for i in range(3):
nin = dims[i]/2
t_dis.append( S_dis[i][nin:,0:nin] )
t_clean.append( S_clean[i][nin:,0:nin] )
Q = scat.calc_Q(S_clean,dk)[0]
Q11 = Q[0:nin,0:nin]
Q11EigVec = ut.sort_eig(Q11)[1]
TransStates = np.dot( np.linalg.inv(t_dis[1]), np.dot( t_clean[1], Q11EigVec ))
if machine == 1:
data_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC/Fibres-20130819/" + filen + "/")
pic_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC/Fibres-20130819/" + pic_filen + "/")
elif machine ==2:
data_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + filen + "/")
pic_direc = ("/home/ambichl/Universitaet/Scattering-Data/"
"VSC2/Fibres-20130802/" + pic_filen + "/")
else:
print "specify machine (VSC: 1, VSC2: 2)"
plot_direc = data_direc
S, dims = scat.read_S(data_direc, filen+".1E-%i"%expo, old_ver=1)
modes = int(max(dims)/2)
t , t_q = trans.calc_t(S, dims, refmodes)
tp = (t[2] - t[0]) / (2*dk)
ShiftPhase = -I * (t[1]/np.absolute(t[1])).conj() * (t[2]/np.absolute(t[2]) - t[0]/np.absolute(t[0])) / (2*dk)
#ShiftPhase = 0.001*np.ones((3,3), dtype="complex")
ShiftFacsP = np.exp( I * ShiftPhase * dk)
ShiftFacsM = np.exp(-I * ShiftPhase * dk)
#print np.absolute(ShiftFacsM)
#!/usr/bin/env python import numpy as np import scipy as sp import scipy.optimize as spopt import matplotlib.pyplot as plt import sys from math import pi as Pi from Utils import utils as ut from Scattering import scattering2D as scat filen = str(sys.argv[1]) # namestring of calculation n = int(sys.argv[2]) # number of calculation dims = int(sys.argv[3]) # number of open modes in left lead data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen + "/scatterdata/" energs = scat.read_S(data_direc, filen + ".%i.0" % n)[2] kvals = np.sqrt(2 * energs) dk = (kvals[-1] - kvals[-2]) / 1.0 filen_i = filen + ".%i.%i" % (n, 0) print "reading file: " + filen_i S = scat.read_S(data_direc, filen_i)[0] q_mean = np.trace(scat.calc_Q(S, dk)[0]) / (2 * dims) print q_mean.real
