diff --git a/postproc/time_series_chiralmhd.py b/postproc/time_series_chiralmhd.py
index 6710201..1f85ec1 100644
--- a/postproc/time_series_chiralmhd.py
+++ b/postproc/time_series_chiralmhd.py
@@ -1,285 +1,293 @@
###################
# plotting script #
###################
# import modules
import pencil as pc
import numpy as np
import pylab as plt
import matplotlib
from matplotlib import rc
import matplotlib.text as mtext
import matplotlib.transforms as mtransforms
import os
import sys
# latex fonts:
from matplotlib import rc
from matplotlib import rcParams
from mpl_toolkits.axes_grid1 import make_axes_locatable
rcParams['text.usetex'] = True
rcParams['text.latex.preamble'] = [r'\usepackage{amssymb}']
# colors
colors = ['#000075', '#ff7f0e', '#2ca02c', '#d62728',
'#9467bd', '#8c564b', '#e377c2', '#7f7f7f',
'#bcbd22', '#17becf', '#B8B8B8', '#eeeeee']
linestyles = ["-","--","-.",":"]
fig, ax = plt.subplots()
ax = plt.subplot(111)
#########################
# read in time series and parameters:
ts_rel = pc.read_ts(filename='time_series.dat', datadir='../chiral_mhd_rel/magnetic_decay/64_3D_kf10_eta1e-2_lambda51e6/data')
ts_nonrel = pc.read_ts(filename='time_series.dat', datadir='../chiral_mhd_nonrel/magnetic_decay/64_3D_kf10_eta1e-2_lambda51e6/data')
#########################
eta = 1e-2
tteta = 1./eta
# #########################
# # read in spectra
# os.chdir("../")
# pmag = pc.read_power("data/power_mag.dat")
# # this are the power spectra at different times
# tspecteta = pmag[0]/g.teta
# p = pmag[1]
# minspec = 0
# maxspec = len(tspecteta)
# #incrementspec = round(maxspec/10.,0) # number of spectra we want to plot in equi-distant steps
# # reduce timeseries array to spectra
# j=0
# jspec = 0
# jspectmp = 0
# urmsspec = []
# urmsspec.append(ts.urms[0])
# for i in range(len(ts.t)): # loop over all elements in time series
# jspec = int(round(j*len(tspecteta)/len(tteta))) # corresponding index in spectral array
# jspectmpm1 = jspectmp # save the previous jspectmp
# # if round(tteta[j],3) == round(tspecteta[jspec],3): # only write something if simulation times are equal (order of 3)
# if ((tteta[j]-tspecteta[jspec])**2<0.01): # only write something if simulation times are very equal
# jspectmp = jspec # safe the current spectral index
# print "index in spectral array =", jspectmp
# if jspectmp == jspectmpm1 : # trick to avoid double entries
# print "double entry"
# else:
# urmsspec.append(ts.urms[j]) # write urms
# j = j+1
# # if i == len(ts.t)
# # ormsspec.append(0)
# # urmsspec.append(0)
# # find maximum wavenumber
# j=0
# kmax = []
# kmax2Olambda = []
# for i in range(maxspec): #Why do I need to substract 1???
# kmax2Olambda.append(2*np.argmax(p[j])/g.lambda5)
# kmax.append(np.argmax(p[j]))
# j = j+1
# # calculate Rm
# j=0
# Rm = []
# for i in range(maxspec): #Why do I need to substract 1???
# if urmsspec[j] == 0. :
# Rm.append(0)
# else:
# Rm.append(urmsspec[j]/(g.eta*kmax[j]))
# j = j+1
# os.chdir("postproc")
# #########################
# #########################
# # find time when kpeak becomes k1:
# jkpk1 = 0
# i=0
# j=0
# for i in range(maxspec):
# if kmax[j]-1 == 0:
# jkpk1 = j
# break
# j = j+1
# tspectetakp1 = tspecteta[jkpk1]
# # find time when kpeak becomes k1:
# jabmin = np.argmin(ts.abm)
# ttetaabmin = tteta[jabmin]
# #########################
fig, ax = plt.subplots()
ax = plt.subplot(111)
-plt.axis([1e-10, max([max(ts_nonrel.t),max(ts_rel.t)])/tteta, 1e-10, 1e-1])
+plt.axis([1e-10, max([max(ts_nonrel.t),max(ts_rel.t)])/tteta, 1e-10, 1e2])
plt.ylabel('time series')
plt.xlabel('$t/t_\eta$')
plt.yscale('log')
plt.xscale('log')
# plt.axvline(x=tspectetakp1, linestyle="-", color='grey')
# plt.axvline(x=ttetaabmin, linestyle=":", color='grey')
# x1 = np.logspace(-3.8, -3.2, 100)
# plt.plot(x1, 2.05e-7*x1**(-2./3), color='grey')
# plt.text(0.000315, 4e-5, '$\propto (t/t_\eta)^{-2/3}$', color='grey')
plt.plot(ts_nonrel.t/tteta, ts_nonrel.abm,
label="$\langle\mathbf{A}\cdot\mathbf{B} \\rangle$",
linestyle=linestyles[0], color=colors[0])
-
plt.plot(ts_nonrel.t/tteta, ts_nonrel.brms,
label="$\\mathbf{B}_\\mathrm{rms}$",
linestyle=linestyles[0], color=colors[1])
plt.plot(ts_nonrel.t/tteta, ts_nonrel.urms,
label="$\\mathbf{u}_\\mathrm{rms}$",
linestyle=linestyles[0], color=colors[2])
+plt.plot(ts_nonrel.t/tteta, ts_nonrel.mu5rms,
+ label="$\\mu_\\mathrm{5,rms}$",
+ linestyle=linestyles[0], color=colors[3])
+
plt.plot(ts_rel.t/tteta, ts_rel.abm,
# label="$\langle\mathbf{A}\cdot\mathbf{B} \\rangle$",
linestyle=linestyles[1], color=colors[0])
plt.plot(ts_rel.t/tteta, ts_rel.brms,
# label="$\\mathbf{B}_\\mathrm{rms}$",
linestyle=linestyles[1], color=colors[1])
plt.plot(ts_rel.t/tteta, ts_rel.urms,
# label="$\\mathbf{u}_\\mathrm{rms}$",
linestyle=linestyles[1], color=colors[2])
+plt.plot(ts_rel.t/tteta, ts_rel.mu5rms,
+# label="$\\mathbf{u}_\\mathrm{rms}$",
+ linestyle=linestyles[1], color=colors[3])
+
+
# plt.scatter(tspecteta, kmax2Olambda,
# label='$2 k_\mathrm{p}/\lambda$',
# linestyle=linestyles[1], color=colors[1])
# plt.plot(ts.t/g.teta, 2*g.ki/g.lambda5 + ts.t/g.teta*0,
# label="$2 k_\mathrm{p,0}/\lambda$",
# linestyle=linestyles[0], color=colors[1])
#plt.plot(ts.t/g.teta, 2*ts.mu5m/g.lambda5,
# label="$2 \langle\mu_5\\rangle/\lambda$",
# linestyle=linestyles[1], color=colors[2])
# plt.plot(ts.t/g.teta, 8*g.eta*ts.brms[0]**2*g.ki*tI*(1-3./4.*(ts.t/tI)**(-1/3)),
# label="$8 \\eta B_\\mathrm{rms,0}^2 k_\mathrm{I} (1 - 3 (t/t_\mathrm{I})^{-1/3}/4)$",
# linestyle=linestyles[1], color=colors[2])
# plt.scatter(ts.t/g.teta, ts.abm + 2*ts.mu5m/g.lambda5,
# label="$\langle\mathbf{A}\cdot\mathbf{B} \\rangle + 2 \langle\mu_5\\rangle/\lambda$",
# linestyle=linestyles[1], color=colors[3])
props = dict(boxstyle='round', facecolor=colors[11],edgecolor=colors[10])
# plt.axhline(y=1e-5, xmin=5e-4, xmax=3e-2, color=colors[10], linestyle='-')
# plt.annotate( " ", xy = (5e-4, 1e-5), \
# xytext = (4e-3, 1e-5), fontsize = 7, \
# color = colors[10], arrowprops=dict(facecolor=colors[10], edgecolor=colors[10], lw=1.5, arrowstyle = '<|-|>, head_length = 1, head_width = .4'))
# plt.annotate( " ", xy = (4e-3, 1e-5), \
# xytext = (3e-2, 1e-5), fontsize = 7, \
# color = colors[10], arrowprops=dict(edgecolor=colors[10], lw=1.5, arrowstyle = '|-|'))
# plt.text(2.5e-3, 1e-5, "phase (i)", fontsize=11,
# verticalalignment='center', bbox=props)
# plt.annotate( " ", xy = (4e-2, 1e-5), \
# xytext = (0.35, 1e-5), fontsize = 7, \
# color = colors[10], arrowprops=dict(edgecolor=colors[10], lw=1.5, arrowstyle = '|-|'))
# plt.text(6.7e-2, 1e-5, "phase (ii)", fontsize=11,
# verticalalignment='center', bbox=props)
# plt.annotate( " ", xy = (0.4, 1e-5), \
# xytext = (1, 1e-5), fontsize = 7, \
# color = colors[10], arrowprops=dict(edgecolor=colors[10], lw=1.5, arrowstyle = '|-|'))
# plt.annotate( " ", xy = (1, 1e-5), \
# xytext = (5, 1e-5), fontsize = 7, \
# color = colors[10], arrowprops=dict(facecolor=colors[10], lw=1.5, edgecolor=colors[10], arrowstyle = '<|-|>, head_length = 1, head_width = .4'))
# plt.text(6.3e-1, 1e-5, "phase (iii)", fontsize=11,
# verticalalignment='center', bbox=props)
#########
# # add scaling bar:
# class RotationAwareAnnotation2(mtext.Annotation):
# def __init__(self, s, xy, p, pa=None, ax=None, **kwargs):
# self.ax = ax or plt.gca()
# self.p = p
# if not pa:
# self.pa = xy
# kwargs.update(rotation_mode=kwargs.get("rotation_mode", "anchor"))
# mtext.Annotation.__init__(self, s, xy, **kwargs)
# self.set_transform(mtransforms.IdentityTransform())
# if 'clip_on' in kwargs:
# self.set_clip_path(self.ax.patch)
# self.ax._add_text(self)
# def calc_angle(self):
# p = self.ax.transData.transform_point(self.p)
# pa = self.ax.transData.transform_point(self.pa)
# ang = np.arctan2(p[1]-pa[1], p[0]-pa[0])
# return np.rad2deg(ang)
# def _get_rotation(self):
# return self.calc_angle()
# def _set_rotation(self, rotation):
# pass
# _rotation = property(_get_rotation, _set_rotation)
# tsarray = np.logspace(-3.6, -2.6, 100)
# scaling_function = lambda tsarray: 1.9e-7*tsarray**(-2./3)
# y = scaling_function(tsarray)
# ax.plot(tsarray, y, color='grey', linewidth=0.75)
# #ax.set(yscale = 'log', xscale = 'log', ylim=(1e-6, 1e-4), xlim=(1e-5, 0.02), xlabel=r'$x$')
# annots= []
# xi=tsarray[len(tsarray)/2]
# an = RotationAwareAnnotation2("$\propto (t/t_\eta)^{-2/3}$",
# xy=(xi,scaling_function(xi)), p=(xi+.01,scaling_function(xi+.01)), ax=ax,
# xytext=(-1,1), textcoords="offset points",
# ha="center", va="bottom", color='grey')
# annots.append(an)
# #########
# rect = patches.Rectangle((1e-3,4e-2),1e-5,2e-5,linewidth=1,edgecolor='r',facecolor='red')
# ax.add_patch(rect)
# ax.add_patch(
# patches.Rectangle(
# (1e-3,4e-2),
# 1e-5,2e-5,
# fill=False # remove background
# ) )
plt.legend(loc='lower right')
# save figure
fig.savefig("time_series_chiralmhd.pdf", bbox_inches='tight')