import matplotlib.pyplot as plt
import sys
from math import pi as Pi
from Scattering import scattering2D as scat
from Utils import utils as ut
imag_i = 1.j
if (len(sys.argv)!=2):
sys.exit("ABORT: filen-string needed")
filen = str(sys.argv[1]) # namestring of calculation
data_direc = "../../VSC2/AverageDwellTime-20130618/" + filen
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)
import scipy.sparse.linalg as spsl
from cmath import *
import matplotlib.pyplot as plt
import sys
import pickle
from Utils import utils as ut
from Scattering import scattering2D as scat
from Packets import transmission as trans
Pi = np.pi
I = 0. + 1.J
par = ut.read_input('.')
try:
filen = par['filen'] # namestring of calculation where scatter data is stored
pic_filen = par['pic_filen'] # namestring of calculation where waveplots are stored
lead_width = float(par['lead_width'])
modes_min = float(par['modes_min'])
modes_max = float(par['modes_max'])
refmodes = int(par['refmodes']) # number of modes to be considered
except KeyError:
raw_input("WARNING: parameter missing in pinput.dat")
expo = 1
kmean = 0.5 * (modes_max + modes_min) * np.pi / lead_width
dk = kmean * 10**(-expo)
nin_Max = int(0.5 * (modes_max + modes_min)) # nin_Max = n_open_modes
#!/usr/bin/env python
import sys
import subprocess
import os
import numpy as np
from Utils import utils as ut
par = ut.read_input('./')
try:
filen = par['filen']
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")
nin_Max = int(0.5 * (modes_max + modes_min)) # nin_Max = n_open_modes
pos_range = (0, int(0.33*nin-0.5*ptc), int(0.5*nin-0.5*ptc))#, int(0.67*nin-0.5*ptc), nin-ptc)
in_str = open("peak.xml", "r").readlines()
out_str = [[open("tdtpeak.%i.%i.xml"%(i,j), "w") for i in range(len(pos_range))] for j in range(len(pos_range))]
for line in in_str:
line = line.strip() #entfernt alle trailing characters vorne und hinten
for i in range(len(pos_range)):
for j in range(len(pos_range)):