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LICENSE 0 → 100644
View file @ a39f1e8b
Copyright (c) 2017 The Board of Trustees of the University of Illinois
All rights reserved.
Developed by: Daniel Johnson, E. A. Huerta, Roland Haas, Debopam Sanyal,
Brockton Brendal
NCSA Gravity Group
National Center for Supercomputing Applications
University of Illinois at Urbana-Champaign
http://gravity.ncsa.illinois.edu/
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to
deal with the Software without restriction, including without limitation the
rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimers.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimers in the documentation
and/or other materials provided with the distribution.
Neither the names of the National Center for Supercomputing Applications,
University of Illinois at Urbana-Champaign, nor the names of its
contributors may be used to endorse or promote products derived from this
Software without specific prior written permission.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
WITH THE SOFTWARE.
POWER/monitor_waveform.sh deleted 100755 → 0
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#!/bin/bash
folder=$1
run=${folder##*/}
./power.py $folder
./plot_monitor.py $run
POWER/plot.py deleted 100755 → 0
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#!/usr/bin/env python
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import sys
run_name = sys.argv[1]
python_strain = np.loadtxt("./Extrapolated_Strain/"+run_name+"/"+run_name+"_radially_extrapolated_strain.dat")
py_t = python_strain[:, 0]
py_hplus = python_strain[:, 1]
run_name_without_resolution = run_name.split("_")[0]
matplotlib.rcParams.update({'font.size': 12})
matplotlib.rcParams.update({'font.family': 'serif'})
plt.title(run_name_without_resolution)
plt.plot(py_t, py_hplus)
plt.xlim((0,None))
plt.ylabel('${\mathfrak{R}} [h(t)]$')
plt.xlabel('Time [M]')
plt.savefig("./Extrapolated_Strain/"+run_name+"/strain_plot.png")
POWER/plot_monitor.py deleted 100755 → 0
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#!/usr/bin/env python
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import sys
run_name = sys.argv[1]
python_strain = np.loadtxt("./Extrapolated_Strain/"+run_name+"/"+run_name+"_strain_at_500.dat")
py_t = python_strain[:, 0]
py_hplus = python_strain[:, 1]
run_name_without_resolution = run_name.split("_")[0]
matplotlib.rcParams.update({'font.size': 12})
matplotlib.rcParams.update({'font.family': 'serif'})
plt.title(run_name_without_resolution)
plt.plot(py_t, py_hplus)
plt.xlim((0,None))
plt.ylabel('${\mathfrak{R}} [h(t)]$')
plt.xlabel('Time [M]')
plt.show()
POWER/power.py deleted 100755 → 0
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#!/usr/bin/env python3
# Based off of SimulationTools Mathematica Package
# http://www.simulationtools.org/
import numpy as np
import glob
import os
import h5py
import string
import math
import sys
import warnings
import scipy.optimize
import scipy.interpolate
#-----Function Definitions-----#
#Function used in getting psi4 from simulation
def joinDsets(dsets):
"""joints multiple datasets which each have a
time like first column, eg iteration number of
time. Removes overlapping segments, keeping the
last segment.
dsets = iterable of 2d array like objects with data"""
# joins multiple datasets of which the first column is assumed to be "time"
if(not dsets):
return None
length = 0
for d in dsets:
length += len(d)
newshape = list(dsets[0].shape)
newshape[0] = length
dset = np.empty(shape=newshape, dtype=dsets[0].dtype)
usedlength = 0
for d in dsets:
insertpointidx = np.where(dset[0:usedlength,0] >= d[0,0])
if(insertpointidx[0].size):
insertpoint = insertpointidx[0][0]
else:
insertpoint = usedlength
newlength = insertpoint+len(d)
dset[insertpoint:newlength] = d
usedlength = newlength
return dset[0:usedlength]
#Function used in getting psi4 from simulation
def loadHDF5Series(nameglob, series):
"""load HDF5 timeseries data and concatenate the content of multiple files
nameglob = a shell glob that matches all files to be loaded,
files are sorted alphabetically
series = HDF5 dataset name of dataset to load from files"""
dsets = list()
for fn in sorted(glob.glob(nameglob)):
fh = h5py.File(fn)
dsets.append(fh[series])
return joinDsets(dsets)
#Convert radial to tortoise coordinates
def RadialToTortoise(r, M):
"""
Convert the radial coordinate to the tortoise coordinate
r = radial coordinate
M = ADMMass used to convert coordinate
return = tortoise coordinate value
"""
return r + 2. * M * math.log( r / (2. * M) - 1.)
#Convert modified psi4 to strain
def psi4ToStrain(mp_psi4, f0):
"""
Convert the input mp_psi4 data to the strain of the gravitational wave
mp_psi4 = Weyl scalar result from simulation
f0 = cutoff frequency
return = strain (h) of the gravitational wave
"""
#TODO: Check for uniform spacing in time
t0 = mp_psi4[:, 0]
list_len = len(t0)
complexPsi = np.zeros(list_len, dtype=np.complex_)
complexPsi = mp_psi4[:, 1]+1.j*mp_psi4[:, 2]
freq, psif = myFourierTransform(t0, complexPsi)
dhf = ffi(freq, psif, f0)
hf = ffi(freq, dhf, f0)
time, h = myFourierTransformInverse(freq, hf, t0[0])
hTable = np.column_stack((time, h))
return hTable
#Fixed frequency integration
# See https://arxiv.org/abs/1508.07250 for method
def ffi(freq, data, f0):
"""
Integrates the data according to the input frequency and cutoff frequency
freq = fourier transform frequency
data = input on which ffi is performed
f0 = cutoff frequency
"""
f1 = f0/(2*math.pi)
fs = freq
gs = data
mask1 = (np.sign((fs/f1) - 1) + 1)/2
mask2 = (np.sign((-fs/f1) - 1) + 1)/2
mask = 1 - (1 - mask1) * (1 - mask2)
fs2 = mask * fs + (1-mask) * f1 * np.sign(fs - np.finfo(float).eps)
new_gs = gs/(2*math.pi*1.j*fs2)
return new_gs
#Fourier Transform
def myFourierTransform(t0, complexPsi):
"""
Transforms the complexPsi data to frequency space
t0 = time data points
complexPsi = data points of Psi to be transformed
"""
psif = np.fft.fft(complexPsi, norm="ortho")
l = len(complexPsi)
n = int(math.floor(l/2))
newpsif = psif[l-n:]
newpsif = np.append(newpsif, psif[:l-n])
T = np.amin(np.diff(t0))*l
freq = range(-n, l-n)/T
return freq, newpsif
#Inverse Fourier Transform
def myFourierTransformInverse(freq, hf, t0):
l = len(hf)
n = int(math.floor(l/2))
newhf = hf[n:]
newhf = np.append(newhf, hf[:n])
amp = np.fft.ifft(newhf, norm="ortho")
df = np.amin(np.diff(freq))
time = t0 + range(0, l)/(df*l)
return time, amp
def angular_momentum(x, q, m, chi1, chi2, LInitNR):
eta = q/(1.+q)**2.
m1 = (1.+(1.-4.*eta)**0.5)/2.
m2 = m - m1
S1 = m1**2. * chi1
S2 = m2**2. * chi2
Sl = S1+S2
Sigmal = S2/m2 - S1/m1
DeltaM = m1 - m2
mu = eta
nu = eta
GammaE = 0.5772156649;
e4 = -(123671./5760.)+(9037.* math.pi**2.)/1536.+(896.*GammaE)/15.+(-(498449./3456.)+(3157.*math.pi**2.)/576.)*nu+(301. * nu**2.)/1728.+(77.*nu**3.)/31104.+(1792. *math.log(2.))/15.
e5 = -55.13
j4 = -(5./7.)*e4+64./35.
j5 = -(2./3.)*e5-4988./945.-656./135. * eta;
a1 = -2.18522;
a2 = 1.05185;
a3 = -2.43395;
a4 = 0.400665;
a5 = -5.9991;
CapitalDelta = (1.-4.*eta)**0.5
l = (eta/x**(1./2.)*(
1. +
x*(3./2. + 1./6.*eta) +
x**2. *(27./8. - 19./8.*eta + 1./24.*eta**2.) +
x**3. *(135./16. + (-6889./144. + 41./24. * math.pi**2.)*eta + 31./24.*eta**2. + 7./1296.*eta**3.) +
x**4. *((2835./128.) + eta*j4 - (64.*eta*math.log(x)/3.))+
x**5. *((15309./256.) + eta*j5 + ((9976./105.) + (1312.*eta/15.))*eta*math.log(x))+
x**(3./2.)*(-(35./6.)*Sl - 5./2.*DeltaM* Sigmal) +
x**(5./2.)*((-(77./8.) + 427./72.*eta)*Sl + DeltaM* (-(21./8.) + 35./12.*eta)*Sigmal) +
x**(7./2.)*((-(405./16.) + 1101./16.*eta - 29./16.*eta**2.)*Sl + DeltaM*(-(81./16.) + 117./4.*eta - 15./16.*eta**2.)*Sigmal) +
(1./2. + (m1 - m2)/2. - eta)* chi1**2. * x**2. +
(1./2. + (m2 - m1)/2. - eta)* chi2**2. * x**2. +
2.*eta*chi1*chi2*x**2. +
((13.*chi1**2.)/9. +
(13.*CapitalDelta*chi1**2.)/9. -
(55.*nu*chi1**2.)/9. -
29./9.*CapitalDelta*nu*chi1**2. +
(14.*nu**2. *chi1**2.)/9. +
(7.*nu*chi1*chi2)/3. +
17./18.* nu**2. * chi1 * chi2 +
(13.* chi2**2.)/9. -
(13.*CapitalDelta*chi2**2.)/9. -
(55.*nu*chi2**2.)/9. +
29./9.*CapitalDelta*nu*chi2**2. +
(14.*nu**2. * chi2**2.)/9.)
* x**3.))
return l - LInitNR
#Get cutoff frequency
def getCutoffFrequency(sim_name):
"""
Determine cutoff frequency of simulation
sim_name = string of simulation
return = cutoff frequency
"""
filename = main_dir+"/output-0000/%s.par" % (sim_name)
with open(filename) as file:
contents = file.readlines()
for line in contents:
line_elems = line.split(" ")
if(line_elems[0] == "TwoPunctures::par_b"):
par_b = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::center_offset[0]"):
center_offset = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::par_P_plus[1]"):
pyp = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::par_P_minus[1]"):
pym = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::target_M_plus"):
m1 = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::target_M_minus"):
m2 = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::par_S_plus[2]"):
S1 = float(line_elems[-1])
if(line_elems[0] == "TwoPunctures::par_S_minus[2]"):
S2 = float(line_elems[-1])
xp = par_b + center_offset
xm = -1*par_b + center_offset
LInitNR = xp*pyp + xm*pym
M = m1+m2
q = m1/m2
chi1 = S1/math.pow(m1, 2.)
chi2 = S2/math.pow(m2, 2.)
# .014 is the initial guess for cutoff frequency
omOrbPN = scipy.optimize.fsolve(angular_momentum, .014, (q, M, chi1, chi2, LInitNR))[0]
omOrbPN = omOrbPN**(3./2.)
omGWPN = 2. * omOrbPN
omCutoff = 0.75 * omGWPN
return omCutoff
#-----Main-----#
#Initialize simulation data
if(len(sys.argv) < 2):
print("Pass in the number n of the n innermost detector radii to be used in the extrapolation (optional, default=all) and the simulation folders (e.g., ./power.py 6 ./simulations/J0040_N40 /path/to/my_simulation_folder).")
sys.exit()
elif(os.path.isdir(sys.argv[1])):
radiiUsedForExtrapolation = 7 #use the first n radii available
paths = sys.argv[1:]
elif(not os.path.isdir(sys.argv[1])):
radiiUsedForExtrapolation = int(sys.argv[1]) #use the first n radii available
if(radiiUsedForExtrapolation < 1 or radiiUsedForExtrapolation > 7):
print("Invalid specified radii number")
sys.exit()
paths = sys.argv[2:]
for sim_path in paths:
main_dir = sim_path
sim = sim_path.split("/")[-1]
simdirs = main_dir+"/output-????/%s/" % (sim)
f0 = getCutoffFrequency(sim)
#Create data directories
main_directory = "Extrapolated_Strain"
sim_dir = main_directory+"/"+sim
if not os.path.exists(main_directory):
os.makedirs(main_directory)
if not os.path.exists(sim_dir):
os.makedirs(sim_dir)
#Get ADMMass
ADMMass = -1
filename = main_dir+"/output-0000/%s/TwoPunctures.bbh" % (sim)
with open(filename) as file:
contents = file.readlines()
for line in contents:
line_elems = line.split(" ")
if(line_elems[0] == "initial-ADM-energy"):
ADMMass = float(line_elems[-1])
#Get Psi4
radii = [100, 115, 136, 167, 214, 300, 500]
psi4dsetname_100 = 'l2_m2_r'+str(radii[0])+'.00'
psi4dsetname_115 = 'l2_m2_r'+str(radii[1])+'.00'
psi4dsetname_136 = 'l2_m2_r'+str(radii[2])+'.00'
psi4dsetname_167 = 'l2_m2_r'+str(radii[3])+'.00'
psi4dsetname_214 = 'l2_m2_r'+str(radii[4])+'.00'
psi4dsetname_300 = 'l2_m2_r'+str(radii[5])+'.00'
psi4dsetname_500 = 'l2_m2_r'+str(radii[6])+'.00'
mp_psi4_100 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_100)
mp_psi4_115 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_115)
mp_psi4_136 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_136)
mp_psi4_167 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_167)
mp_psi4_214 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_214)
mp_psi4_300 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_300)
mp_psi4_500 = loadHDF5Series(simdirs+"mp_psi4.h5", psi4dsetname_500)
mp_psi4_vars = [mp_psi4_100, mp_psi4_115, mp_psi4_136, mp_psi4_167, mp_psi4_214, mp_psi4_300, mp_psi4_500]
#Get Tortoise Coordinate
tortoise = [None] * 7
for i in range(0, 7):
tortoise[i] = -RadialToTortoise(radii[i], ADMMass)
strain = [None]*7
phase = [None]*7
amp = [None]*7
for i in range(0, 7):
#Get modified Psi4 (Multiply real and imaginary psi4 columns by radii and add the tortoise coordinate to the time colum)
mp_psi4_vars[i][:, 0] += tortoise[i]
mp_psi4_vars[i][:, 1] *= radii[i]
mp_psi4_vars[i][:, 2] *= radii[i]
#Fixed-frequency integration twice to get strain
hTable = psi4ToStrain(mp_psi4_vars[i], f0)
time = hTable[:, 0]
h = hTable[:, 1]
hplus = h.real
hcross = h.imag
newhTable = np.column_stack((time, hplus, hcross))
warnings.filterwarnings('ignore')
finalhTable = newhTable.astype(float)
np.savetxt("./Extrapolated_Strain/"+sim+"/"+sim+"_strain_at_"+str(radii[i])+".dat", finalhTable)
strain[i] = finalhTable
#Get phase and amplitude of strain
h_phase = np.unwrap(np.angle(h))
while(h_phase[0] < 0):
h_phase[:] += 2*math.pi
angleTable = np.column_stack((time, h_phase))
angleTable = angleTable.astype(float)
phase[i] = angleTable
h_amp = np.absolute(h)
ampTable = np.column_stack((time, h_amp))
ampTable = ampTable.astype(float)
amp[i] = ampTable
#Interpolate phase and amplitude
t = phase[0][:, 0]
last_t = phase[radiiUsedForExtrapolation - 1][-1, 0]
last_index = 0;
for i in range(0, len(phase[0][:, 0])):
if(t[i] > last_t):
last_index = i
break
last_index = last_index-1
t = phase[0][0:last_index, 0]
dts = t[1:] - t[:-1]
dt = float(np.amin(dts))
t = np.arange(phase[0][0, 0], phase[0][last_index, 0], dt)
interpolation_order = 9
for i in range(0, radiiUsedForExtrapolation):
interp_function = scipy.interpolate.interp1d(phase[i][:, 0], phase[i][:, 1], kind=interpolation_order)
resampled_phase_vals = interp_function(t)
while(resampled_phase_vals[0] < 0):
resampled_phase_vals[:] += 2*math.pi
phase[i] = np.column_stack((t, resampled_phase_vals))
interp_function = scipy.interpolate.interp1d(amp[i][:, 0], amp[i][:, 1], kind=interpolation_order)
resampled_amp_vals = interp_function(t)
amp[i] = np.column_stack((t, resampled_amp_vals))
#Extrapolate
phase_extrapolation_order = 1
amp_extrapolation_order = 2
radii = np.asarray(radii, dtype=float)
radii = radii[0:radiiUsedForExtrapolation]
A_phase = np.power(radii, 0)
A_amp = np.power(radii, 0)
for i in range(1, phase_extrapolation_order+1):
A_phase = np.column_stack((A_phase, np.power(radii, -1*i)))
for i in range(1, amp_extrapolation_order+1):
A_amp = np.column_stack((A_amp, np.power(radii, -1*i)))
radially_extrapolated_phase = np.empty(0)
radially_extrapolated_amp = np.empty(0)
for i in range(0, len(t)):
b_phase = np.empty(0)
for j in range(0, radiiUsedForExtrapolation):
b_phase = np.append(b_phase, phase[j][i, 1])
x_phase = np.linalg.lstsq(A_phase, b_phase)[0]
radially_extrapolated_phase = np.append(radially_extrapolated_phase, x_phase[0])
b_amp = np.empty(0)
for j in range(0, radiiUsedForExtrapolation):
b_amp = np.append(b_amp, amp[j][i, 1])
x_amp = np.linalg.lstsq(A_amp, b_amp)[0]
radially_extrapolated_amp = np.append(radially_extrapolated_amp, x_amp[0])
radially_extrapolated_h_plus = np.empty(0)
radially_extrapolated_h_cross = np.empty(0)
for i in range(0, len(radially_extrapolated_amp)):
radially_extrapolated_h_plus = np.append(radially_extrapolated_h_plus, radially_extrapolated_amp[i] * math.cos(radially_extrapolated_phase[i]))
radially_extrapolated_h_cross = np.append(radially_extrapolated_h_cross, radially_extrapolated_amp[i] * math.sin(radially_extrapolated_phase[i]))
np.savetxt("./Extrapolated_Strain/"+sim+"/"+sim+"_radially_extrapolated_strain.dat", np.column_stack((t, radially_extrapolated_h_plus, radially_extrapolated_h_cross)))
POWER/simulations/J0040_N40/Horizons.h5 deleted 100644 → 0
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File deleted
POWER/simulations/J0040_N40/output-0000/J0040_N40/TwoPunctures.bbh deleted 100644 → 0
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# ==================================
# Numerical Relativity Metadata file
# ==================================
#
# This file contains information about the simulation provided by the
# TwoPunctures thorn. The format is described in the NR Data Format Document
# http://arxiv.org/abs/0709.0093 [draft SVN r707].
[metadata]
initial-ADM-energy = 0.9914380459677640811
initial-ADM-angular-momentumx = 0
initial-ADM-angular-momentumy = 0
initial-ADM-angular-momentumz = 1.010179735247381805
initial-separation = 16.28895279716000033
initial-data-type = Bowen-York
initial-data-bibtex-keys = Bowen:1980yu Brandt:1997tf Ansorg:2004ds
initial-bh-position1x = 8.144476398580000165
initial-bh-position1y = 0
initial-bh-position1z = 0
initial-bh-position2x = -8.144476398580000165
initial-bh-position2y = 0
initial-bh-position2z = 0
initial-bh-momentum1x = 0
initial-bh-momentum1y = 0.06201624793359999943
initial-bh-momentum1z = 0
initial-bh-momentum2x = -0
initial-bh-momentum2y = -0.06201624793359999943
initial-bh-momentum2z = 0
initial-bh-spin1x = 0
initial-bh-spin1y = 0
initial-bh-spin1z = 0
initial-bh-spin2x = 0
initial-bh-spin2y = 0
initial-bh-spin2z = 0
initial-bh-puncture-adm-mass1 = 0.5000000000000063283
initial-bh-puncture-adm-mass2 = 0.5000000000000063283
POWER/simulations/J0040_N40/output-0000/J0040_N40/ml_bssn-ml_ham.norm1.asc deleted 100644 → 0
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# Scalar ASCII output created by CarpetIOScalar
# created on nid22248 by elihu on Apr 24 2017 at 19:17:53-0500
# parameter filename: "/scratch/sciteam/elihu/simulations/J0040_N40/output-0000/J0040_N40.par"
# Build ID: build-sim-h2ologin2.ncsa.illinois.edu-elihu-2016.12.02-22.38.15-4497
# Simulation ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
# Run ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
#
# ML_BSSN::H (ml_bssn-ml_ham)
# 1:iteration 2:time 3:data
# data columns: 3:H
0 0 3.79947155914401e-12
256 0.432 3.79947155914401e-12
512 0.864 3.79666296698173e-12
768 1.296 3.80576357579658e-12
1024 1.728 3.82551540416214e-12
1280 2.16 3.84842960911371e-12
1536 2.592 1.79384151835681e-11
1792 3.024 1.91145230445222e-11
2048 3.456 4.14052788404381e-12
2304 3.888 4.58591180155506e-11
2560 4.32 3.84667837128416e-11
2816 4.752 2.12713563570343e-11
3072 5.184 6.3350755113462e-11
3328 5.616 5.27687135020937e-11
3584 6.048 5.39969921036114e-11
3840 6.48 7.92653073971886e-11
4096 6.912 7.50470305296641e-11
4352 7.344 7.48000420455252e-11
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32000 54 17796.0770735437
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32512 54.864 11100.2139258386
32768 55.296 17685.1346435113
33024 55.728 14099.5298308229
33280 56.16 11703.8438047565
33536 56.592 17554.0111209613
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34304 57.888 17506.9723096164
34560 58.32 14126.6587255037
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35072 59.184 17149.8977357508
35328 59.616 13995.371046431
35584 60.048 12377.6935454986
35840 60.48 16986.6000160517
36096 60.912 13914.0965812308
36352 61.344 12311.4911708126
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37120 62.64 12203.2308426398
37376 63.072 16863.8010450173
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38656 65.232 12002.9697252996
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39168 66.096 13421.4056018058
39424 66.528 11895.7694143065
39680 66.96 16377.5841711814
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40448 68.256 16128.0901724043
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40960 69.12 11673.1405447036
41216 69.552 15910.9886246838
41472 69.984 12813.6646449734
41728 70.416 11642.3520683933
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42240 71.28 12034.3157781595
42496 71.712 11369.8797601769
42752 72.144 15663.5952879014
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43264 73.008 11317.3226956064
43520 73.44 15558.6354375698
43776 73.872 11672.550931648
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52736 88.992 12982.5739372272
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53248 89.856 9417.27656064769
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55040 92.88 11762.2927663067
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57088 96.336 9600.07158831502
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60160 101.52 9290.58442321763
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61184 103.248 11128.1071651992
61440 103.68 10698.7414593258
61696 104.112 9206.79730796487
61952 104.544 11091.9490630426
62208 104.976 10643.5715321331
62464 105.408 9150.75405390098
62720 105.84 10921.6327893588
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63232 106.704 9117.30867287501
63488 107.136 10860.6774945778
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64000 108 9057.78617147117
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64512 108.864 10396.9180908268
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65024 109.728 10579.4492867677
65280 110.16 10282.9010125573
65536 110.592 8925.13648386203
65792 111.024 10537.9880223572
66048 111.456 10179.0328919836
66304 111.888 8821.4645480054
66560 112.32 10452.3014460176
POWER/simulations/J0040_N40/output-0000/J0040_N40/ml_bssn-ml_ham.norm2.asc deleted 100644 → 0
View file @ e1d6a466
# Scalar ASCII output created by CarpetIOScalar
# created on nid22248 by elihu on Apr 24 2017 at 19:17:53-0500
# parameter filename: "/scratch/sciteam/elihu/simulations/J0040_N40/output-0000/J0040_N40.par"
# Build ID: build-sim-h2ologin2.ncsa.illinois.edu-elihu-2016.12.02-22.38.15-4497
# Simulation ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
# Run ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
#
# ML_BSSN::H (ml_bssn-ml_ham)
# 1:iteration 2:time 3:data
# data columns: 3:H
0 0 1.83270251237336e-09
256 0.432 1.83270251237336e-09
512 0.864 1.83162742636247e-09
768 1.296 1.84440611696836e-09
1024 1.728 1.85937728458509e-09
1280 2.16 1.86078854975996e-09
1536 2.592 9.15645028768613e-07
1792 3.024 8.23437105000234e-07
2048 3.456 8.87377565644614e-08
2304 3.888 1.3918159364401e-06
2560 4.32 1.24064871658189e-06
2816 4.752 8.9850047838967e-07
3072 5.184 1.60096725489648e-06
3328 5.616 1.5428435675182e-06
3584 6.048 1.61576182328167e-06
3840 6.48 1.77025163823813e-06
4096 6.912 1.83863434224465e-06
4352 7.344 1.95674771929355e-06
4608 7.776 1.7967861586475e-06
4864 8.208 1.94925029460726e-06
5120 8.64 1.98931882453518e-06
5376 9.072 1.88114955038261e-06
5632 9.504 2.15675444185897e-06
5888 9.936 2.13561179873189e-06
6144 10.368 2.09678542777685e-06
6400 10.8 2.46224907675815e-06
6656 11.232 2.29389618102887e-06
6912 11.664 2.50181579764512e-06
7168 12.096 2.7448698203725e-06
7424 12.528 4731941.80292132
7680 12.96 896686.638600317
7936 13.392 3.00217404442787e-06
8192 13.824 4731941.80330375
8448 14.256 1247427.22259229
8704 14.688 3.14352708066486e-06
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16640 28.08 11633305.4779459
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21248 35.856 19780839.1855752
21504 36.288 17760190.4681824
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22016 37.152 23512199.8881071
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26112 44.064 28087986.4657369
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26880 45.36 28112086.6759169
27136 45.792 25657734.1037044
27392 46.224 31326480.9676025
27648 46.656 28144053.7590515
27904 47.088 25319919.6336338
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28416 47.952 27842240.6202388
28672 48.384 25419337.2861762
28928 48.816 31771881.5385067
29184 49.248 28151991.9911912
29440 49.68 25513637.4118183
29696 50.112 31877513.9237577
29952 50.544 28446046.981778
30208 50.976 25581235.4295528
30464 51.408 32115492.7017026
30720 51.84 28282759.6989629
30976 52.272 26239544.792777
31232 52.704 32383991.7870645
31488 53.136 28133568.8511325
31744 53.568 26205890.6321437
32000 54 32960829.4156412
32256 54.432 28058993.4902596
32512 54.864 26874725.3519551
32768 55.296 32824214.5368631
33024 55.728 28452674.9832064
33280 56.16 27704674.6396019
33536 56.592 32690720.995217
33792 57.024 28349221.7321294
34048 57.456 28417408.5153048
34304 57.888 32391531.4553881
34560 58.32 27885023.7871091
34816 58.752 28424356.8963219
35072 59.184 31862673.0125301
35328 59.616 27491354.2128046
35584 60.048 28376055.8603169
35840 60.48 31607523.5883511
36096 60.912 27344048.9356367
36352 61.344 28274382.3020214
36608 61.776 31386675.893506
36864 62.208 27082810.124036
37120 62.64 28089477.1710564
37376 63.072 31495950.7598477
37632 63.504 26823512.7764927
37888 63.936 27882793.2515508
38144 64.368 31208082.9452939
38400 64.8 26763700.861926
38656 65.232 27808987.7659129
38912 65.664 31075700.351725
39168 66.096 26571719.8461127
39424 66.528 27674762.6997991
39680 66.96 30861619.3954722
39936 67.392 26304505.9548829
40192 67.824 27489292.5349607
40448 68.256 30642108.9556565
40704 68.688 26120365.0319802
40960 69.12 27323060.16096
41216 69.552 30432184.5197783
41472 69.984 25807282.104836
41728 70.416 27243760.4315196
41984 70.848 30174115.5678809
42240 71.28 24375585.895064
42496 71.712 26502863.7164488
42752 72.144 30123674.819264
43008 72.576 23986585.2975081
43264 73.008 26395145.002756
43520 73.44 29957331.7918651
43776 73.872 23815641.5203598
44032 74.304 26205238.0882971
44288 74.736 29861865.3110082
44544 75.168 23438538.9571413
44800 75.6 25962193.8380039
45056 76.032 29565985.2782956
45312 76.464 23320502.5871669
45568 76.896 25720581.9828628
45824 77.328 29221787.4990882
46080 77.76 22904574.4546014
46336 78.192 25586208.0132566
46592 78.624 28926775.5004183
46848 79.056 22153388.0259386
47104 79.488 25481940.5667103
47360 79.92 28571618.0431304
47616 80.352 21720248.855059
47872 80.784 25249595.2733703
48128 81.216 28397806.8529453
48384 81.648 21559121.3523996
48640 82.08 25112733.2315089
48896 82.512 28135328.4005486
49152 82.944 20998641.0456948
49408 83.376 24327728.0340276
49664 83.808 28013220.52393
49920 84.24 20672689.355955
50176 84.672 24070711.2228047
50432 85.104 27780972.9161958
50688 85.536 20323110.8532426
50944 85.968 23906868.0735729
51200 86.4 27675635.5432506
51456 86.832 19966102.6733509
51712 87.264 23712285.2557461
51968 87.696 27453833.2738179
52224 88.128 19814298.891928
52480 88.56 23530514.1585417
52736 88.992 27190813.1265451
52992 89.424 19404337.9370166
53248 89.856 23511183.9906106
53504 90.288 27055784.3146424
53760 90.72 19353954.6989125
54016 91.152 23484508.8425896
54272 91.584 25156113.0535808
54528 92.016 19185469.0865539
54784 92.448 22786613.4848263
55040 92.88 24944373.9450727
55296 93.312 18768190.8722915
55552 93.744 22325332.1571442
55808 94.176 24602003.7586059
56064 94.608 19154715.3009446
56320 95.04 22434682.628685
56576 95.472 24724103.7608773
56832 95.904 22588644.9155784
57088 96.336 21795375.7501723
57344 96.768 23103064.556767
57600 97.2 21662336.7503338
57856 97.632 20964559.533856
58112 98.064 23285925.9498029
58368 98.496 21771898.8488326
58624 98.928 20981000.6766812
58880 99.36 23214473.0246825
59136 99.792 21611241.0121113
59392 100.224 20742007.2158864
59648 100.656 22976948.8539627
59904 101.088 21430135.9521977
60160 101.52 20590268.7360073
60416 101.952 22825181.5399346
60672 102.384 21343419.4640455
60928 102.816 20411076.2585736
61184 103.248 22757247.5435772
61440 103.68 21444530.5416813
61696 104.112 20526032.3929114
61952 104.544 22747859.121738
62208 104.976 21416769.4679027
62464 105.408 20479734.1046558
62720 105.84 22551519.4433706
62976 106.272 21340304.7495954
63232 106.704 20476080.3615769
63488 107.136 22450166.2475091
63744 107.568 21252841.3313166
64000 108 20385442.409501
64256 108.432 22359465.7115241
64512 108.864 21191354.3154255
64768 109.296 20306145.8525469
65024 109.728 22156995.1072383
65280 110.16 21116086.0109669
65536 110.592 20194533.9952484
65792 111.024 22097011.5680412
66048 111.456 21042472.7174768
66304 111.888 20079929.0871408
66560 112.32 22011870.5983601
POWER/simulations/J0040_N40/output-0000/J0040_N40/ml_bssn-ml_ham.norm_inf.asc deleted 100644 → 0
View file @ e1d6a466
# Scalar ASCII output created by CarpetIOScalar
# created on nid22248 by elihu on Apr 24 2017 at 19:17:53-0500
# parameter filename: "/scratch/sciteam/elihu/simulations/J0040_N40/output-0000/J0040_N40.par"
# Build ID: build-sim-h2ologin2.ncsa.illinois.edu-elihu-2016.12.02-22.38.15-4497
# Simulation ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
# Run ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
#
# ML_BSSN::H (ml_bssn-ml_ham)
# 1:iteration 2:time 3:data
# data columns: 3:H
0 0 5.56591877037396e-05
256 0.432 5.56591877037396e-05
512 0.864 5.56591877037396e-05
768 1.296 5.56591877037396e-05
1024 1.728 5.56591877037396e-05
1280 2.16 5.56591877037396e-05
1536 2.592 0.0977681729240488
1792 3.024 0.109884759345241
2048 3.456 0.0366541866863516
2304 3.888 0.0977681729240488
2560 4.32 0.115581495417329
2816 4.752 0.115582396305211
3072 5.184 0.0977681729240488
3328 5.616 0.115581495417329
3584 6.048 0.115582396305211
3840 6.48 0.0977681729240488
4096 6.912 0.115581495417329
4352 7.344 0.11558240415557
4608 7.776 0.115582431168928
4864 8.208 0.115588298267499
5120 8.64 0.115589524648927
5376 9.072 0.115585660723041
5632 9.504 0.115588298267499
5888 9.936 0.115589524648927
6144 10.368 0.115585660723041
6400 10.8 0.115588298267499
6656 11.232 0.115589524648927
6912 11.664 0.115585660723041
7168 12.096 0.115588298267499
7424 12.528 34996032714.8434
7680 12.96 23330688476.5621
7936 13.392 0.115588298267499
8192 13.824 34996032714.8434
8448 14.256 23330688476.5621
8704 14.688 0.115588298267499
8960 15.12 34996032714.8434
9216 15.552 93322753906.2492
9472 15.984 93322753906.2489
9728 16.416 34996032714.8434
9984 16.848 93322753906.2492
10240 17.28 93322753906.2489
10496 17.712 93322753906.2514
10752 18.144 93322753906.252
11008 18.576 93322753906.25
11264 19.008 93322753906.2514
11520 19.44 93322753906.252
11776 19.872 93322753906.2509
12032 20.304 93322753906.2514
12288 20.736 104988098144.534
12544 21.168 93322753906.25
12800 21.6 93322753906.2514
13056 22.032 104988098144.531
13312 22.464 96679687499.9989
13568 22.896 93322753906.2514
13824 23.328 99449157714.8418
14080 23.76 96679687499.9989
14336 24.192 93322753906.2514
14592 24.624 99449157714.8418
14848 25.056 126462447928.815
15104 25.488 138122572802.899
15360 25.92 99449157714.8418
15616 26.352 126462447928.815
15872 26.784 133754004287.769
16128 27.216 96679687500.0122
16384 27.648 121883998974.228
16640 28.08 133754004287.769
16896 28.512 105122342705.722
17152 28.944 121883998974.228
17408 29.376 131620489060.88
17664 29.808 105122342705.722
17920 30.24 104988098144.532
18176 30.672 105122342705.731
18432 31.104 104988098144.534
18688 31.536 104988098144.532
18944 31.968 143539428710.938
19200 32.4 159635543823.242
19456 32.832 104988098144.532
19712 33.264 143539428710.938
19968 33.696 153173446655.273
20224 34.128 105122342705.732
20480 34.56 136154174804.688
20736 34.992 153173446655.273
20992 35.424 136154174804.688
21248 35.856 154387179762.125
21504 36.288 113644942641.261
21760 36.72 136154174804.688
22016 37.152 154387179762.125
22272 37.584 113644942641.261
22528 38.016 136154174804.688
22784 38.448 154387179762.125
23040 38.88 145422105677.426
23296 39.312 136154174804.688
23552 39.744 154387179762.125
23808 40.176 145422105677.426
24064 40.608 136154174804.688
24320 41.04 154387179762.125
24576 41.472 159635543823.242
24832 41.904 136154174804.688
25088 42.336 154387179762.125
25344 42.768 159635543823.242
25600 43.2 136154174804.688
25856 43.632 154387179762.125
26112 44.064 159635543823.242
26368 44.496 136154174804.688
26624 44.928 142431259155.273
26880 45.36 153173446655.273
27136 45.792 136154174804.688
27392 46.224 143747869879.005
27648 46.656 144785165786.743
27904 47.088 137843746459.111
28160 47.52 146274747326.97
28416 47.952 144785165786.743
28672 48.384 146762079559.266
28928 48.816 146274747326.97
29184 49.248 144785165786.743
29440 49.68 146762079559.266
29696 50.112 146274747326.97
29952 50.544 144785165786.743
30208 50.976 146762079559.266
30464 51.408 146274747326.97
30720 51.84 144785165786.743
30976 52.272 146762079559.266
31232 52.704 146274747326.97
31488 53.136 144785165786.743
31744 53.568 146762079559.266
32000 54 146274747326.97
32256 54.432 144785165786.743
32512 54.864 157437825169.836
32768 55.296 146274747326.97
33024 55.728 144785165786.743
33280 56.16 157437825169.836
33536 56.592 140605095608.748
33792 57.024 144785165786.743
34048 57.456 157437825169.836
34304 57.888 140605095608.748
34560 58.32 144785165786.743
34816 58.752 157437825169.836
35072 59.184 140575603756.589
35328 59.616 144785165786.743
35584 60.048 157437825169.836
35840 60.48 140575603756.589
36096 60.912 144785165786.743
36352 61.344 157437825169.836
36608 61.776 140575603756.589
36864 62.208 144785165786.743
37120 62.64 157437825169.836
37376 63.072 156830260872.085
37632 63.504 146903671440.668
37888 63.936 157437825169.836
38144 64.368 156830260872.085
38400 64.8 151162378489.971
38656 65.232 157437825169.836
38912 65.664 156830260872.085
39168 66.096 151162378489.971
39424 66.528 157437825169.836
39680 66.96 156830260872.085
39936 67.392 151162378489.971
40192 67.824 149808672023.937
40448 68.256 156830260872.085
40704 68.688 151162378489.971
40960 69.12 141664429800.581
41216 69.552 156830260872.085
41472 69.984 151162378489.971
41728 70.416 141664429800.581
41984 70.848 156830260872.085
42240 71.28 151162378489.971
42496 71.712 141664429800.581
42752 72.144 156830260872.085
43008 72.576 151162378489.971
43264 73.008 145469448265.826
43520 73.44 165927283714.392
43776 73.872 158100145533.028
44032 74.304 145469448265.826
44288 74.736 165927283714.392
44544 75.168 158100145533.028
44800 75.6 145469448265.826
45056 76.032 154766321182.252
45312 76.464 158100145533.028
45568 76.896 137843746459.111
45824 77.328 147614966216.415
46080 77.76 137235949598.401
46336 78.192 143169650966.329
46592 78.624 147614966216.415
46848 79.056 137235949598.401
47104 79.488 143169650966.329
47360 79.92 165927283714.392
47616 80.352 150321202769.391
47872 80.784 143169650966.329
48128 81.216 165927283714.392
48384 81.648 150321202769.391
48640 82.08 145469448265.826
48896 82.512 156830260872.085
49152 82.944 158100145533.028
49408 83.376 145469448265.826
49664 83.808 156830260872.085
49920 84.24 146110539239.112
50176 84.672 155265403036.634
50432 85.104 156830260872.085
50688 85.536 146110539239.112
50944 85.968 155265403036.634
51200 86.4 156830260872.085
51456 86.832 146110539239.112
51712 87.264 147050678910.689
51968 87.696 156830260872.085
52224 88.128 144128411685.982
52480 88.56 147050678910.689
52736 88.992 146111726760.865
52992 89.424 136560618877.432
53248 89.856 155265403036.634
53504 90.288 146111726760.865
53760 90.72 136560618877.432
54016 91.152 155265403036.634
54272 91.584 146111726760.865
54528 92.016 136560618877.432
54784 92.448 155265403036.634
55040 92.88 146111726760.865
55296 93.312 136560618877.432
55552 93.744 155265403036.634
55808 94.176 146111726760.865
56064 94.608 136560618877.432
56320 95.04 143169650966.329
56576 95.472 146111726760.865
56832 95.904 136560618877.432
57088 96.336 143169650966.329
57344 96.768 146111726760.865
57600 97.2 136560618877.432
57856 97.632 143169650966.329
58112 98.064 146111726760.865
58368 98.496 134296539239.582
58624 98.928 143169650966.329
58880 99.36 135369539260.866
59136 99.792 134296539239.582
59392 100.224 97855480462.3841
59648 100.656 107853523328.005
59904 101.088 109362602233.884
60160 101.52 97697257995.5928
60416 101.952 104988098144.532
60672 102.384 109362602233.884
60928 102.816 96679687500.0021
61184 103.248 104988098144.532
61440 103.68 109362602233.884
61696 104.112 104988098144.531
61952 104.544 104988098144.532
62208 104.976 109362602233.884
62464 105.408 104988098144.531
62720 105.84 109502440318.464
62976 106.272 109362602233.884
63232 106.704 113296508789.042
63488 107.136 104988098144.532
63744 107.568 109362602233.884
64000 108 113296508789.042
64256 108.432 104988098144.532
64512 108.864 109362602233.884
64768 109.296 113296508789.042
65024 109.728 104988098144.532
65280 110.16 109362602233.884
65536 110.592 113296508789.042
65792 111.024 104988098144.532
66048 111.456 109362602233.884
66304 111.888 113296508789.042
66560 112.32 110595198255.398
POWER/simulations/J0040_N40/output-0000/J0040_N40/ml_bssn-ml_mom.norm1.asc deleted 100644 → 0
View file @ e1d6a466
# Scalar ASCII output created by CarpetIOScalar
# created on nid22248 by elihu on Apr 24 2017 at 19:17:53-0500
# parameter filename: "/scratch/sciteam/elihu/simulations/J0040_N40/output-0000/J0040_N40.par"
# Build ID: build-sim-h2ologin2.ncsa.illinois.edu-elihu-2016.12.02-22.38.15-4497
# Simulation ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
# Run ID: run-J0040_N40-nid22248-elihu-2017.04.25-00.15.02-4471
#
# ML_BSSN::M1 (ml_bssn-ml_mom)
# 1:iteration 2:time 3:data
# data columns: 3:M1 4:M2 5:M3
0 0 8.6207472471582e-15 1.62104953298638e-14 9.70179111865345e-15
256 0.432 8.6207472471582e-15 1.62104953298638e-14 9.70179111865345e-15
512 0.864 8.6143991688058e-15 1.62004198399352e-14 9.69544576606851e-15
768 1.296 8.61526045735754e-15 1.62086787851847e-14 9.69626647517913e-15
1024 1.728 8.62082115319179e-15 1.62409602062434e-14 9.70283163781361e-15
1280 2.16 8.64668401797841e-15 1.63019578323117e-14 9.72936631200873e-15
1536 2.592 1.56694576670811e-11 1.4241409027006e-11 9.77877658906048e-15
1792 3.024 1.88399179473363e-11 1.60502118358878e-11 2.56996023371336e-12
2048 3.456 4.81640662807299e-12 4.68643973052594e-12 4.83087110556355e-12
2304 3.888 4.54215926113083e-11 4.24589967199846e-11 6.90819677579805e-12
2560 4.32 4.18501677737961e-11 3.62944072281112e-11 7.33240965117308e-12
2816 4.752 2.21349367769502e-11 2.1791475986588e-11 1.37960294806288e-11
3072 5.184 6.39358687150127e-11 6.08844856790185e-11 1.58532422400848e-11
3328 5.616 6.11895925688541e-11 5.47698154278519e-11 1.91025820164876e-11
3584 6.048 5.48399036549175e-11 5.33341587748667e-11 2.97943998939392e-11
3840 6.48 8.07681072696676e-11 7.78429612201754e-11 2.37224052206415e-11
4096 6.912 8.47244323582879e-11 7.73036763775268e-11 3.40885211981043e-11
4352 7.344 9.10049480225714e-11 8.88809120444635e-11 5.40995723321259e-11
4608 7.776 9.68484261608573e-11 9.49702944652323e-11 4.20745148319398e-11
4864 8.208 9.87247144085296e-11 9.14689901188231e-11 4.64697293739412e-11
5120 8.64 1.09976705402656e-10 1.194709115747e-10 8.40703155171112e-11
5376 9.072 1.16393299246399e-10 1.15263542707073e-10 6.58519639099673e-11
5632 9.504 1.15435596957208e-10 1.09550686644983e-10 6.42819888673868e-11
5888 9.936 1.29747764989285e-10 1.39963932046578e-10 1.06128459874029e-10
6144 10.368 1.35043552710492e-10 1.34263505138568e-10 8.86949196167697e-11
6400 10.8 1.48443619458725e-10 1.43468738503259e-10 9.76761867321049e-11
6656 11.232 1.49954350802037e-10 1.59365186155075e-10 1.26988445650208e-10
6912 11.664 1.78849188617872e-10 1.76784422479801e-10 1.33678027277349e-10
7168 12.096 1.8017056274905e-10 1.79161506530176e-10 1.34859374556579e-10
7424 12.528 783.516391312308 783.516391312321 783.516391312293
7680 12.96 42.1007110770956 42.1007110770937 42.1010764182489
7936 13.392 2.0777813562932e-10 2.14191989950478e-10 1.69973087569189e-10
8192 13.824 783.516391438979 783.516391439015 783.51639143899
8448 14.256 81.500223651816 81.5002236518223 81.500588993004
8704 14.688 2.29947925517931e-10 2.4192235999904e-10 1.99987771163804e-10
8960 15.12 1567.03278287208 1567.03278287213 1567.0327828721
9216 15.552 244.500670950939 244.500670950943 244.50088615185
9472 15.984 163.000447300753 163.000447300751 163.000447300732
9728 16.416 1567.03278290392 1567.03278290399 1567.03278290397
9984 16.848 407.501118265182 407.501118265177 407.501242025579
10240 17.28 326.000894632607 326.00089463261 326.000894632619
10496 17.712 1573.85700227302 1573.85700227309 1572.15094745527
10752 18.144 1059.48411264648 892.181268093224 581.045762485699
11008 18.576 757.243015449574 489.001341972624 489.001341972639
11264 19.008 1512.64878235483 1512.6487823549 1510.11607901965
11520 19.44 1052.0709846487 884.768140090679 587.191041121684
11776 19.872 1200.51457029933 664.03122335388 661.667386142394
12032 20.304 1534.75012109688 1534.75012109696 1530.93886585687
12288 20.736 1684.02453583432 1349.41884675682 756.964505569928
12544 21.168 1314.45824217518 775.273696762363 907.728545734925
12800 21.6 1598.05106205495 1598.05106205503 1594.00948611774
13056 22.032 1820.65482607343 1484.36088795352 893.033690909059
13312 22.464 1423.31975666856 884.198520672021 1071.05875789087
13568 22.896 1661.86226031519 1671.1885174583 1667.31576642787
13824 23.328 1873.01305647724 1536.80658732965 946.059846092075
14080 23.76 1489.76980413051 950.639400764464 1135.77677351483
14336 24.192 1661.13400123104 1669.95378365451 1666.20118773615
14592 24.624 1907.75191250155 1571.53043647959 981.189772594474
14848 25.056 1548.31900504085 1009.13648272555 1192.16306797317
15104 25.488 1687.79583418517 1704.42244959326 1700.9785114929
15360 25.92 1888.18154502763 1551.93642070652 961.793439054632
15616 26.352 1635.00471749322 1095.82219514203 1348.037241433
15872 26.784 878.27071963855 893.880428775365 891.191412652937
16128 27.216 1952.86437311282 1616.59569288518 1026.88903055228
16384 27.648 2439.7232465705 1900.54072416701 2149.399684718
16640 28.08 2145.57197718008 2160.73336405299 2033.36653229771
16896 28.512 2528.91709998585 2192.62606473478 1635.61144564084
17152 28.944 2986.02491300533 2415.05714508504 2660.05101962762
17408 29.376 2972.65654201233 2852.43563342313 2516.11702561917
17664 29.808 3046.95014830667 2710.25510903212 2146.44161632143
17920 30.24 3064.19785438612 2471.74530777879 2707.7428650798
18176 30.672 3220.34512263783 3053.90160265348 2648.81095358119
18432 31.104 3155.57961259812 2820.45519217903 2254.04357963283
18688 31.536 3569.27271935903 2937.24175271614 3165.98655150807
18944 31.968 3612.40526560396 3524.76492092699 3290.37429676871
19200 32.4 3497.37648918091 3162.24191712044 2868.7922093507
19456 32.832 3634.08879472319 2976.38004887694 3174.90930812802
19712 33.264 4139.24234810527 4074.91421258053 4010.59827899084
19968 33.696 4042.29658454875 3735.70410850664 3682.98390565906
20224 34.128 4510.29074653765 3855.3885430602 4031.33340506533
20480 34.56 6673.79262263696 6632.13033040956 6570.36488322015
20736 34.992 4268.15839027603 3974.08594387255 3882.21232538404
20992 35.424 4679.92814319084 4018.14801713018 4129.00879410484
21248 35.856 6732.84077131516 6688.67259337208 6631.71103773394
21504 36.288 4437.08574472589 4123.3048636148 3995.55351596045
21760 36.72 4803.1951712472 4114.57795325283 4220.70883041249
22016 37.152 9764.28240967407 9670.17201046016 9574.35138344222
22272 37.584 6682.57109760553 6279.04903841089 6131.10582306992
22528 38.016 5591.82281294442 4793.79324976625 4923.74126718236
22784 38.448 9892.6016971009 9854.05584472686 9722.39438992078
23040 38.88 7395.06166277921 6985.16886332628 6808.08946111022
23296 39.312 7433.64996105713 6616.90846066247 6732.16763934297
23552 39.744 13087.6782688998 13107.0210210877 12964.2811129243
23808 40.176 10797.9303886394 11172.2895999494 11028.0641157857
24064 40.608 7603.48175017254 6785.71271580723 6961.42093444013
24320 41.04 13338.0078502601 13349.6223925818 13214.251896055
24576 41.472 11148.5219043088 11548.7564213792 11364.7296115442
24832 41.904 7788.18878038325 6980.14371986332 7127.90921116468
25088 42.336 13686.0087220164 13688.0796299261 13562.2309094062
25344 42.768 13115.3233596175 14276.2795499797 14065.9488285514
25600 43.2 8074.84092515772 7286.9290288753 7386.78961845073
25856 43.632 15153.1102090061 15148.0550203695 15030.7569871019
26112 44.064 13164.9338344471 14255.1082045591 14079.5227365394
26368 44.496 9140.63361214839 8341.14343855135 8446.05251239245
26624 44.928 15853.2156358542 15848.4199103401 15746.0253841977
26880 45.36 13216.9729521215 14301.1567832813 14071.4163683524
27136 45.792 9409.50905764951 8559.66229034728 8592.64479203709
27392 46.224 16073.9786177718 16001.4995356392 15980.8879678907
27648 46.656 13327.514682691 14408.2047123237 14130.058851262
27904 47.088 9238.10538028506 8660.54286863178 8676.57430011978
28160 47.52 16455.1667379167 16394.3411479599 16302.842714038
28416 47.952 13149.6168855969 14318.3175232472 14129.7641889727
28672 48.384 9262.70785758003 8680.70217322492 8690.93440069308
28928 48.816 16406.0823468225 16255.2740286688 16190.153712705
29184 49.248 13337.7307793242 14310.4231411427 14166.5302057392
29440 49.68 9285.49500484782 8725.91402599628 8741.31476905068
29696 50.112 16464.6045175664 16389.6268239907 16349.0110665131
29952 50.544 13558.7231334796 14329.7775610454 14209.1735986027
30208 50.976 9343.33663618045 8814.2291762066 8833.09011449776
30464 51.408 16644.530504822 16442.0965466141 16434.8912620741
30720 51.84 13444.0725970881 14160.6550673739 14087.4388045466
30976 52.272 9817.69361064564 9284.75135147276 9182.32310816872
31232 52.704 16858.9921574616 16635.8187288655 16633.4140439027
31488 53.136 13378.6730773522 14023.8360757428 13957.0457686838
31744 53.568 9836.00189206803 9271.38176358222 9130.23512993202
32000 54 17381.6529658244 17182.0187071928 17149.5106643555
32256 54.432 13382.4233282106 13963.9635615489 13882.7295567643
32512 54.864 10297.7626560983 9698.81304197954 9427.04387999825
32768 55.296 17277.6137398427 17052.7060116677 16980.8938307183
33024 55.728 13515.6399328089 14153.9186716444 14083.031578492
33280 56.16 10573.2114060826 10058.6733833959 9786.84714844179
33536 56.592 17238.3050641318 17002.9267346434 16928.3086675869
33792 57.024 13582.6054662113 14179.8957221213 14132.2958327787
34048 57.456 10892.6425039305 10503.8954747563 10244.4108032514
34304 57.888 17239.2605556553 17005.8003357885 16918.6289203378
34560 58.32 13346.7482788783 13970.2997134954 13839.3513531131
34816 58.752 11017.642960595 10659.6592632938 10399.8881615042
35072 59.184 16915.3994729199 16672.0481296237 16666.6286520332
35328 59.616 13250.1829918915 13844.3706469858 13712.6643260962
35584 60.048 11005.964122626 10637.8116229576 10352.1149985955
35840 60.48 16777.6489516566 16555.4635910953 16573.8145417359
36096 60.912 13168.5571580224 13747.0442526123 13602.0931901293
36352 61.344 10947.623744362 10535.3763426178 10258.7446431223
36608 61.776 16610.628743521 16374.527689617 16408.5543818787
36864 62.208 13001.9330501757 13466.428294746 13411.9635226617
37120 62.64 10839.4079125408 10411.0868013735 10201.0128020458
37376 63.072 16623.7674897789 16345.1288903744 16403.236602452
37632 63.504 12866.1041117468 13416.0346927721 13125.9558732754
37888 63.936 10712.5624163266 10368.4386893527 10238.6621243812
38144 64.368 16343.5539726326 16006.1549911183 16019.2880340424
38400 64.8 12728.1559205102 13121.4313914598 12894.0417445169
38656 65.232 10666.0471353123 10264.8655406281 10138.910121497
38912 65.664 16257.5486663912 15916.3395971988 15949.4797261739
39168 66.096 12666.4240197804 12985.543322266 12760.1668761744
39424 66.528 10589.3281638525 10144.0464682922 10064.8978376474
39680 66.96 16133.4681724217 15760.8597698049 15778.1477687466
39936 67.392 12397.7778138791 12631.3828428073 12460.0421946811
40192 67.824 10465.983120133 10015.1193322541 9936.2205723258
40448 68.256 15856.62528606 15427.4665894275 15453.9519892884
40704 68.688 12300.4012292013 12488.2992886706 12326.1236247111
40960 69.12 10346.4060638228 9899.92752429247 9808.41783153329
41216 69.552 15635.6268106029 15239.6134362676 15268.5047419598
41472 69.984 12050.9354827644 12153.1739910259 12034.4345591677
41728 70.416 10318.9143672836 9858.59302892922 9735.82892875283
41984 70.848 15354.4395418978 14958.217156874 14959.4393506506
42240 71.28 11318.6661279199 11470.2020611976 11306.864612139
42496 71.712 10052.4339516554 9623.22181909252 9593.91777357489
42752 72.144 15380.1728204312 14951.5633160717 14963.8931356848
43008 72.576 11054.5699090135 11102.2795164512 11052.682026122
43264 73.008 10001.2277837656 9540.40243543277 9471.67881542408
43520 73.44 15273.2569092189 14800.8194022095 14831.1162252523
43776 73.872 10991.1361405983 10987.2386657241 10924.6559754954
44032 74.304 9856.29527849692 9384.64845632615 9329.9315254116
44288 74.736 15174.5226951381 14683.6509544097 14702.2083333654
44544 75.168 10690.2019366189 10590.8220467547 10542.1391066598
44800 75.6 9635.99102157694 9164.49262480158 9097.58364577842
45056 76.032 14918.4352979233 14427.9497655565 14418.3247008741
45312 76.464 10730.7899409015 10633.5873712433 10463.4297234407
45568 76.896 9495.3304792598 9054.67941599846 8937.26248481908
45824 77.328 14606.6271810417 14133.7672785737 14118.1492453663
46080 77.76 10494.3329640472 10293.4183332236 10129.0028464293
46336 78.192 9419.28154028462 8931.36351471088 8777.96912709443
46592 78.624 14445.2734787187 13961.4951622338 13956.1994635973
46848 79.056 10082.1071797857 10107.1925993356 9939.12161293936
47104 79.488 9385.86715508754 8755.99250764606 8591.47325259511
47360 79.92 14171.421295036 13658.782078623 13659.90026085
47616 80.352 9824.29699856304 9748.7143828106 9590.37735701846
47872 80.784 9218.332918074 8549.52130821736 8362.25856072097
48128 81.216 14003.1999767388 13491.3011190662 13521.2674867981
48384 81.648 9692.83868097987 9621.33583754411 9451.97295381636
48640 82.08 9084.99172551393 8438.70403997911 8266.6498678039
48896 82.512 13716.9532117363 13189.7480846719 13258.6210520795
49152 82.944 9403.5543221397 9258.80376253434 9123.48379748205
49408 83.376 8950.82475806915 8292.35265324333 8199.54367676998
49664 83.808 13575.7320306638 13032.9385041874 13109.7097316697
49920 84.24 9291.79769886579 9147.33252450089 9033.384485142
50176 84.672 8747.63938664704 8092.41445109527 8006.08379991774
50432 85.104 13267.6347103672 12701.0348344484 12760.1330367874
50688 85.536 9044.54339063141 8832.2805147266 8721.02167825933
50944 85.968 8576.4648820535 7929.54338903708 7834.00349296076
51200 86.4 13111.5085148267 12559.4077920558 12624.882253824
51456 86.832 8809.06855154039 8532.44454884569 8409.94354578297
51712 87.264 8428.52797054992 7766.77209879115 7692.16507534336
51968 87.696 12854.0684204717 12269.8736009291 12338.822099613
52224 88.128 8698.75369083009 8416.82763676773 8292.62484997236
52480 88.56 8303.93221765894 7630.18636353527 7571.13828799412
52736 88.992 12659.3954872132 12064.3637513036 12132.1975744415
52992 89.424 8430.79270076199 8077.34603537214 7963.19395648959
53248 89.856 8263.87762197709 7505.78581636943 7429.14678231676
53504 90.288 12555.6871289215 11961.5801720669 12041.1600217092
53760 90.72 8497.42097942508 8154.3091180301 8059.73585143552
54016 91.152 8320.02887973182 7563.09092555629 7510.97723510024
54272 91.584 11671.2691216077 11064.8816502594 11153.6912652687
54528 92.016 8504.70616773541 8123.47069405456 8039.06630051329
54784 92.448 8081.40577363791 7353.70856494765 7400.14174661625
55040 92.88 11533.45200599 10925.6894720421 11089.9436506357
55296 93.312 8258.82953301259 7835.54782098185 7796.26710158343
55552 93.744 8475.47719338247 7740.40210669113 7896.17497733172
55808 94.176 11228.1285659159 10585.5257512469 10754.7113447788
56064 94.608 8612.13639938176 8159.2377218359 8157.22353659846
56320 95.04 8643.37895920908 7902.41388435131 8147.66691292234
56576 95.472 11302.6794695587 10595.3179860318 10896.0101063865
56832 95.904 10384.1165303125 9892.19198149889 9984.87945815195
57088 96.336 8507.81880169289 7775.23995039925 8099.50976336657
57344 96.768 10947.6184636622 10254.1327261518 10694.6180976698
57600 97.2 10154.1841012763 9599.51895282117 9714.66507687692
57856 97.632 8284.02250975198 7586.982434919 7939.70316229714
58112 98.064 11138.8489825889 10415.6765966902 10857.6143828255
58368 98.496 10368.1353848882 9840.38046527591 9990.14975333534
58624 98.928 8490.95715712079 7818.35967945985 8203.60988425084
58880 99.36 11093.0099327593 10364.1933068403 10800.1835297814
59136 99.792 10386.4934219513 9808.71522230999 9917.99344599723
59392 100.224 8491.86342608994 7824.06868102931 8163.50703491965
59648 100.656 11042.2000773633 10344.4430845847 10730.8344378998
59904 101.088 10280.8172156762 9726.65880743977 9771.23408464221
60160 101.52 8353.14653286248 7714.90790560301 7982.40988824667
60416 101.952 10905.3270983762 10235.90064362 10571.2066705757
60672 102.384 10209.9018472031 9629.5116275706 9667.25088013094
60928 102.816 8258.65146907187 7655.92670133611 7901.44756061506
61184 103.248 10812.2439282376 10179.6920126938 10535.9635304686
61440 103.68 10171.7313282037 9520.30390960038 9583.74121837443
61696 104.112 8258.18857434341 7615.52144550554 7868.06744553231
61952 104.544 10746.1042549416 10086.7189781542 10456.9550468288
62208 104.976 10126.1348967406 9447.48025090424 9515.25479470609
62464 105.408 8199.62662303342 7549.96269202229 7813.75286315928
62720 105.84 10575.5260819859 9925.82055833994 10289.529331689
62976 106.272 10025.1623786128 9330.42166424517 9413.76448592313
63232 106.704 8165.2803528413 7487.99479899327 7750.61859635492
63488 107.136 10503.5254592809 9855.55333915365 10208.9559756801
63744 107.568 9920.95910922792 9217.40906184571 9293.13355007986
64000 108 8086.16866852896 7402.15482064609 7654.04207806786
64256 108.432 10397.2097226444 9750.05114456685 10102.7395399565
64512 108.864 9843.43869791801 9146.78239273871 9226.75436545764
64768 109.296 8026.79444289195 7340.3969697063 7569.46789211773
65024 109.728 10217.0124387471 9586.28688424613 9913.7933006463
65280 110.16 9759.91542875866 9098.11170747803 9160.19433309139
65536 110.592 7954.13211087594 7358.63737580132 7561.80154913109
65792 111.024 10169.156297485 9538.32784605411 9855.55582649194
66048 111.456 9661.23863357322 8987.63729041954 9034.77102738955
66304 111.888 7871.23564528249 7235.21293182217 7430.30711811698
66560 112.32 10131.9686531122 9501.36067712825 9760.6397798837

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