def read_post(filename = 'post_evaluation.dat', datadir = 'data',
double = 0, quiet = 1, comment_char = '#'):
"""
Read the post processed diagnostic variables.
call signature::
read_post(filename = 'post_evaluation.dat', datadir = 'data', double = 0, quiet = 0, comment_char = '#')
Read the post processed diagnostic variables from 'data/post_evaluation.dat.
Return an object with the variables.
Keyword arguments:
*filename*:
Name of the post evaluation file.
*datadir*:
Name of the data directory.
*double*:
Not used yet (see the read_ts options).
*quiet*:
If True do not show how many lines are being read.
*comment_char*:
The comment character.
"""
return pc.read_ts(filename = filename, datadir = datadir,
double = double, quiet = quiet, print_std = 0, plot_data = False, comment_char = comment_char)
def read_post(filename = 'post_evaluation.dat', datadir = 'data',
double = 0, quiet = 1, comment_char = '#'):
"""
Read the post processed diagnostic variables.
call signature::
read_post(filename = 'post_evaluation.dat', datadir = 'data', double = 0, quiet = 0, comment_char = '#')
Read the post processed diagnostic variables from 'data/post_evaluation.dat.
Return an object with the variables.
Keyword arguments:
*filename*:
Name of the post evaluation file.
*datadir*:
Name of the data directory.
*double*:
Not used yet (see the read_ts options).
*quiet*:
If True do not show how many lines are being read.
*comment_char*:
The comment character.
"""
return pc.read_ts(filename = filename, datadir = datadir,
double = double, quiet = quiet, print_std = 0, plot_data = False, comment_char = comment_char)
def read_ts(datadir, filename='time-series-1.dat'):
return pc.read_ts(
datadir=datadir, filename=filename, plot_data=False, quiet=True
)
import numpy as np
import matplotlib.pyplot as plt
import pencil as pc
# ======================================
# pc.read_ts()
# ======================================
ts = pc.read_ts()
t = ts.t / 2 / np.pi
N = 50
tmax = t.max()
ux = ts.ux2m
uy = ts.uy2m
rhomax = ts.rhomax
rhomin = ts.rhomin
# ======================================
# pc.read_pararm()
# ======================================
par = pc.read_param()
h = par.cs0
if (par.iprimary == 1):
q = par.pmass[1]
else:
q = par.pmass[0]
par1 = par.pmass[1]
par2 = par.pmass[0]
gamma = par.gamma
import pencil import numpy from matplotlib import pyplot from matplotlib import cm import sys import os #simulation_name = #script_name = os.path.basename(__file__) data = pencil.read_var(trimall=True) pdata = pencil.read_pvar() time_series = pencil.read_ts() parameters = pencil.read_param() npar = len(pdata.ipars) xgrid = data.x ygrid = data.y zgrid = data.z dxgrid = data.dx dygrid = data.dy dzgrid = data.dz x0 = xgrid[0] y0 = ygrid[0] z0 = zgrid[0] x1 = xgrid[-1] y1 = ygrid[-1] z1 = zgrid[-1] last_snap = numpy.floor(time_series.t[-1]/parameters.tausp) + 1 ivar_lower = 0
# -*- coding: utf-8 -*- vim: set fileencoding=utf-8 :
# Set up Python load path and configure a matplotlib backend that does not
# need X11. This needs to happen before importing the pencil module.
import sys
sys.path.append('../../../python')
import matplotlib
matplotlib.use('agg')
import pencil as pc
# Description:
# Read time series and data cube, write a few values
datadir = '../data'
ts = pc.read_ts(datadir=datadir, plot_data=False, quiet=True)
var = pc.read_var(datadir=datadir, trimall=True, quiet=True)
# Now write to file
file = open('read_data.out', 'w')
file.write('ts.times :')
for t in ts.t[0:5]:
file.write(' %g' % (t, ))
file.write('\n')
file.write('aa(5,5,0:4,1) :')
for a in var.aa[1, 0:5, 5, 5]:
file.write(' %g' % (a, ))
file.write('\n')
# Set up Python load path and configure a matplotlib backend that does not
# need X11. This needs to happen before importing the pencil module.
import sys
sys.path.append('../../../python')
import matplotlib
matplotlib.use('agg')
import pencil as pc
# Description:
# Read time series and data cube, write a few values
datadir = '../data'
ts = pc.read_ts(datadir=datadir, plot_data=False, quiet=True)
var = pc.read_var(datadir=datadir, trimall=True, quiet=True)
# Now write to file
file = open('read_data.out', 'w')
file.write('ts.times :')
for t in ts.t[0:5]:
file.write(' %g' % (t, ))
file.write('\n')
file.write('aa(5,5,0:4,1) :')
for a in var.aa[1, 0:5, 5, 5]:
file.write(' %g' % (a, ))
file.write('\n')
import pencil import numpy from matplotlib import pyplot from matplotlib import cm import sys import os base_path, script_name = os.path.split(sys.argv[0]) scratch, simulation_name = os.path.split(base_path) script_name = script_name[:-3] data = pencil.read_var(trimall=True, quiet=True) pdata = pencil.read_pvar() time_series = pencil.read_ts(quiet=True) parameters = pencil.read_param(quiet=True) npar = len(pdata.ipars) xgrid = data.x ygrid = data.y zgrid = data.z dxgrid = data.dx dygrid = data.dy dzgrid = data.dz x0 = xgrid[0] y0 = ygrid[0] z0 = zgrid[0] x1 = xgrid[-1] y1 = ygrid[-1] z1 = zgrid[-1] last_snap = int(numpy.floor(data.t / parameters.tausp) + 1)
r"\usepackage[utf8x]{inputenc}", # use utf8 fonts becasue your computer can handle it :)
r"\usepackage[T1]{fontenc}", # plots will be generated using this preamble
]
}
mpl.rcParams.update(pgf_with_latex)
import matplotlib.pyplot as plt
# Setup Figure and Axes
fig, ax = newfig(0.45)
setup_tsplot(ax)#, xlim=(.1,tser.t[-1]))
tmax = 0.
clrindx = iter(np.linspace(0,1,len(dirs)))
for dd in dirs:
if args.verbose: print(dd)
tser = pc.read_ts(datadir=dd, quiet=not args.verbose)
make_tsplot(fig, ax)
if tser.t[-1] > tmax:
ax.set_xlim(.1, tser.t[-1])
ax.legend(loc='upper left', frameon=False)
filename = dstart + '_taylor'
fig.tight_layout(pad=0.3)
if args.verbose:
print(filename)
savefig(fig, path.join(figdir, filename))
print('SUCCESS')
r"\usepackage[T1]{fontenc}", # plots will be generated using this preamble
]
}
mpl.rcParams.update(pgf_with_latex)
import matplotlib.pyplot as plt
cscheme, clr1, clr2, clr3 = select_colors()
# check that there is a figure directory
figdir = 'figures'
check_figdir(figdir)
# Setup Figure and Axes
fwidth = 0.45
tser = pc.read_ts(datadir=args.ddir, quiet=not args.verbose)
par = pc.read_param(datadir=args.ddir, quiet=True)
kpeak = par.kpeak_aa
tau0 = (tser.brms[0]*kpeak)**-1
if args.verbose:
print('tau = ', tau0)
#if args.peak:
# args.tsplot = True
fig, ax = newfig(fwidth)
ax.set_xscale('log')
ax.set_xlim(1e-2/tau0, 3e2/tau0)
#ax.set_yscale('log')
if args.helicity:
ax.set_ylabel(r'$\mathcal{H}$')#/\mathcal{H}_0$')
ax.plot(tser.t/tau0, np.abs(tser.ab_int)*10**5)#**2/tser.brms**2)#/tser.ab_int[0]))
twx = ax.twinx()
import pencil as pc import matplotlib.pyplot as plt import numpy as np import scipy.constants as scp import os global radq1, thetaq1, t, xrq1, yrq1, xrq2, yrq2, vxq1, vyq1, vxq2, vyq2, r, vq1, vq2, v, G, ap1, ap2, ap3, a, rmax, e, ep1, v, xq2, yq2, xq1, yq1, vx, vy TIMESERIES = pc.read_ts() radq1 = TIMESERIES.xq1 thetaq1 = TIMESERIES.yq1 t = TIMESERIES.t xrq1 = radq1 * np.cos(thetaq1) yrq1 = radq1 * np.sin(thetaq1) radq2 = TIMESERIES.xq2 thetaq2 = TIMESERIES.yq2 xrq2 = radq2 * np.cos(thetaq2) yrq2 = radq2 * np.sin(thetaq2) vxq1 = TIMESERIES.vxq1 vyq1 = TIMESERIES.vyq1 vxq2 = TIMESERIES.vxq2 vyq2 = TIMESERIES.vyq2 xq2 = TIMESERIES.xq2 yq2 = TIMESERIES.yq2
try:
dirs = sorted(dirs, key=lambda s: float(s.split('_')[-1]), reverse=True)
except ValueError:
dirs = sorted(dirs)
elif len(dirs) == 0:
print('choose proper datadir')
sys.exit(1)
if args.helical:
#dirs.insert(0, 'helical')
dirs.append( 'helical')
if args.verbose:
print(dirs)
clrindx = iter(np.linspace(0,1,len(dirs)))
# calculate the timescales
tser = pc.read_ts(datadir=dirs[0])
par2 = pc.read_param(quiet=True, datadir=dirs[0], param2=True)
pars = pc.read_param(quiet=True, datadir=dirs[0])
vA0 = tser.brms[0]
k0 = pars.kpeak_aa
tau0 = (vA0*k0)**-1
# Simple plot
fig, ax = newfig(0.45, ratio=0.75)
for dd in dirs:
if dstart.startswith('delta'):
tstop = 1.
else:
tstop=0
import pencil
import numpy
from matplotlib import pylab
import sys
params = pencil.read_param()
ts = pencil.read_ts()
tau = 0.014
g = 2.45
v_s = -tau * g
v_z_max = ts.vpzmax
v_z_min = ts.vpzmin
#v_z_mean = ts.vpzm
time = ts.t / tau
figure = pylab.figure()
subplot = figure.add_subplot(111)
subplot.plot(time, v_z_max, color="red", label="Maximum z-velocity")
subplot.plot(time, v_z_min, color="green", label="Minimum z-velocity")
#subplot.plot(time,v_z_min,color="black",label="Mean z-velocity")
subplot.plot(time,
numpy.repeat(v_s, len(time)),
linestyle="--",
color="grey",
label="Isolated terminal velocity")
subplot.set_title("vpzmax vs t")
subplot.set_ylabel("vpz")
subplot.set_xlabel("t (friction times)")
try:
dirs = sorted(dirs, key=lambda a: float(a.split('_')[-1]), reverse=True)
except ValueError:
pass
#dirs =sorted( [s for s in listdir('.') if (isdir(s) and s.startswith(dstart) and not isfile(join(s,'.noscale')))],
#key=lambda s: float(s.split('_')[-1]))
if args.helical:
dirs.append('helical')
dstart=dirs[0]
if args.verbose:
print(dirs)
clrindx = iter(np.linspace(0,1,len(dirs)))
dim = pc.read_dim(datadir=dstart)
krms = np.loadtxt(join(dstart, 'power_krms.dat')).flatten()[:dim.nxgrid//2]
tser0 = pc.read_ts(quiet=not args.verbose, datadir=dstart)
par0 = pc.read_param(datadir=dstart, quiet=True)
kpeak = par0.kpeak_aa
tau0 = (tser0.brms[0]*kpeak)**-1
print('tau = ',tau0)
if args.verbose:
print('krms shape: ',krms.shape)
if args.light:
cscheme = plt.cm.Paired
else:
cscheme = plt.cm.Dark2
# Simple plot
fig, ax = newfig(0.45, ratio=0.75)
ax.set_xscale('log')
"figure.figsize": figsize(0.95), # default fig size of 0.9 textwidth
"pgf.preamble": [
r"\usepackage[utf8x]{inputenc}", # use utf8 fonts becasue your computer can handle it :)
r"\usepackage[T1]{fontenc}", # plots will be generated using this preamble
]
}
mpl.rcParams.update(pgf_with_latex)
import matplotlib.pyplot as plt
fwidth = 0.45
fig, ax = newfig(fwidth)
# calculate the timescales
tser = pc.read_ts(datadir=dirs[-1])
par2 = pc.read_param(quiet=True, datadir=dirs[-1], param2=True)
pars = pc.read_param(quiet=True, datadir=dirs[-1])
vA0 = tser.brms[0]
k0 = pars.kpeak_aa
tau0 = (vA0*k0)**-1
print('tau_0 = ',tau0)
if args.twin:
twinax = ax.twinx()
twinax.set_yscale('log')
yl2 = twinax.get_ylim()
if args.verbose:
print(yl2)
#twinax.set_ylim(1,1e4)
twinax.set_ylabel(r'$E_{k\leq 7}/E_0$')