from IntegralFlashData import IntegralFlashData
import numpy as np
from collections import OrderedDict
import sys
av = sys.argv
impa = '24'
if len(av) == 2:
impa = str(int(av[1]))
pbi = [2, 4, 6, 8, 12, 16, 20]
pbir = [str(p) for p in pbi]
pref = 'profile75_mpole-'
suff = '_r-35e6_a-' + impa + 'e5.dat'
ifd = IntegralFlashData()
# Make a dictionary for the data
ifdata = OrderedDict([])
pfmt = OrderedDict([])
for i in xrange(0, len(pbir)):
p = pbir[i]
iname = pref + p + suff
ifd.readInts(iname)
ifd.orderData()
# Compute the binding energy and add it to the integrals
data = ifd.getArrayData()
data['E_binding'] = data['E_internal+kinetic'] + data['E_grav']
ifd.data = data
ifd.saveOrderedData()
ifd.clrArrayData()
from IntegralFlashData import IntegralFlashData
import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt
from collections import OrderedDict
import sys
pbi = range(1,31)
N = len(pbi)
pref = 'Realization_'
suff = '_ordered.dat'
ifd = IntegralFlashData()
# Make a dictionary for the data
ifdata = OrderedDict([])
headers = []
shortheaders = []
for i in xrange(0,N):
p = pbi[i]
iname = pref + '{0:03}'.format(p) + suff
ifd.readInts(iname)
# ifd.orderData()
ifdata[p] = ifd.getArrayData()
if i==0:
headers = ifdata[p].keys()
shortheaders = [hj.replace(' > ','>').replace(' ','_') for hj in headers]
ifd.clrArrayData()
## Calculate and write the median
# Get the range of time points for each dataset and interpolate only on the datasets where we have information
t_min_vec = [d['time'][0] for k,d in ifdata.iteritems()]
from IntegralFlashData import IntegralFlashData
import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt
from collections import OrderedDict
import sys
pbi = range(1, 31)
N = len(pbi)
pref = 'Realization_'
suff = '_ordered.dat'
ifd = IntegralFlashData()
# Make a dictionary for the data
ifdata = OrderedDict([])
headers = []
shortheaders = []
for i in xrange(0, N):
p = pbi[i]
iname = pref + '{0:03}'.format(p) + suff
ifd.readInts(iname)
# ifd.orderData()
ifdata[p] = ifd.getArrayData()
if i == 0:
headers = ifdata[p].keys()
shortheaders = [
hj.replace(' > ', '>').replace(' ', '_') for hj in headers
]
ifd.clrArrayData()
## Calculate and write the mean
import matplotlib.pyplot as plt import matplotlib.lines as mlines import matplotlib as mpl from collections import OrderedDict import re import sys import os import glob as glob # matplotlib rc parameters #mpl.rcParams['font.size'] = 14.0 annotation_font_size = 20 # Common objects ifd = IntegralFlashData() headers = [] shortheaders = [] stats_co = OrderedDict([]) stats_cone = OrderedDict([]) which_stats = ['mean','median','min','max','std'] # Store the current directory this_dir = os.getcwd() ## Read in the CO integral stats #realz_dir = '/home/eugene/400k/analysis/cf_brendan' # absolute path realz_dir = '/home/eugene/simulations/flash_runs/hybrid-cone/hddt/v3/profile75/ign_true/400k/analysis/cf_brendan_pbIgnRho-7.2' prefix = '' suffix = '.dat' os.chdir(realz_dir)
from collections import OrderedDict import numpy as np import matplotlib.pyplot as plt import matplotlib.lines as mlines from IntegralFlashData import IntegralFlashData #intdataname_co = 'hybrid_ddt_time_detp_firsts.dat' intdataname_co = 'co_ddt_time_est_E_internal_firsts.dat' intdataname_cone = 'hybrid_ddt_time_est_E_internal_firsts.dat' ifd = IntegralFlashData() ifd.readInts(intdataname_co) ifd.GramsToMsun() co_data = ifd.getArrayData() ifd.clrArrayData() ifd.readInts(intdataname_cone) ifd.GramsToMsun() cone_data = ifd.getArrayData() ifd.clrArrayData() # Get averages and standard deviations for the plot co_average_mass = np.average(co_data['mass with dens > 2e7']) print 'co ave mass: ' + str(co_average_mass) co_std_mass = np.std(co_data['mass with dens > 2e7']) cone_average_mass = np.average(cone_data['mass with dens > 2e7']) print 'cone ave mass: ' + str(cone_average_mass) cone_std_mass = np.std(cone_data['mass with dens > 2e7']) co_average_time = np.average(co_data['time']) print 'co ave time: ' + str(co_average_time) co_std_time = np.std(co_data['time']) cone_average_time = np.average(cone_data['time'])
ifdata = OrderedDict([])
pfmt = OrderedDict([])
# Store the current directory
this_dir = os.getcwd()
## Read in the CO integrals
#realz_dir = '/home/dwillcox/400k/analysis/cf_brendan' # absolute path
realz_dir = '/home/eugene/simulations/flash_runs/hybrid-cone/hddt/v3/profile75/ign_true/400k/analysis/cf_brendan_pbIgnRho-7.2'
#pref = 'Realization_'
pref = '400k_Tc7e8_co_wd_R'
suff = '_ordered.dat'
os.chdir(realz_dir)
# Make a dictionary for the data
ifd = IntegralFlashData()
headers = []
shortheaders = []
rflist = glob.glob(pref + '*' + suff)
N = len(rflist)
print 'Found this many CO files: ' + str(N)
cpick = ColorPicker()
colors = cpick.pickColors(N)
first = True
for fn in rflist:
print fn
ni = int(fn.replace(pref,'').replace(suff,''))
ifd.readInts(fn)
ifd.GramsToMsun()
ifdk = 'co_' + str(ni)
from collections import OrderedDict import numpy as np import matplotlib.pyplot as plt import matplotlib.lines as mlines from IntegralFlashData import IntegralFlashData # intdataname_co = 'hybrid_ddt_time_detp_firsts.dat' intdataname_co = "co_ddt_time_est_E_internal_firsts.dat" intdataname_cone = "hybrid_ddt_time_est_E_internal_firsts.dat" ifd = IntegralFlashData() ifd.readInts(intdataname_co) ifd.GramsToMsun() co_data = ifd.getArrayData() ifd.clrArrayData() ifd.readInts(intdataname_cone) ifd.GramsToMsun() cone_data = ifd.getArrayData() ifd.clrArrayData() # Get averages and standard deviations for the plot co_average_mass = np.average(co_data["mass with dens > 2e7"]) print "co ave mass: " + str(co_average_mass) co_std_mass = np.std(co_data["mass with dens > 2e7"]) cone_average_mass = np.average(cone_data["mass with dens > 2e7"]) print "cone ave mass: " + str(cone_average_mass) cone_std_mass = np.std(cone_data["mass with dens > 2e7"]) co_average_time = np.average(co_data["time"]) print "co ave time: " + str(co_average_time) co_std_time = np.std(co_data["time"]) cone_average_time = np.average(cone_data["time"])
import matplotlib.pyplot as plt import matplotlib.lines as mlines import matplotlib as mpl from collections import OrderedDict import re import sys import os import glob as glob # matplotlib rc parameters #mpl.rcParams['font.size'] = 14.0 annotation_font_size = 20 # Common objects ifd = IntegralFlashData() headers = [] shortheaders = [] stats_co = OrderedDict([]) stats_cone = OrderedDict([]) which_stats = ['mean', 'median', 'min', 'max', 'std'] # Store the current directory this_dir = os.getcwd() ## Read in the CO integral stats #realz_dir = '/home/eugene/400k/analysis/cf_brendan' # absolute path realz_dir = '/home/eugene/simulations/flash_runs/hybrid-cone/hddt/v3/profile75/ign_true/400k/analysis/cf_brendan_pbIgnRho-7.2' prefix = '' suffix = '.dat' os.chdir(realz_dir)
ifdata = OrderedDict([])
pfmt = OrderedDict([])
# Store the current directory
this_dir = os.getcwd()
## Read in the CO integrals
#realz_dir = '/home/dwillcox/400k/analysis/cf_brendan' # absolute path
realz_dir = '/home/eugene/simulations/flash_runs/hybrid-cone/hddt/v3/profile75/ign_true/400k/analysis/cf_brendan_pbIgnRho-7.2'
#pref = 'Realization_'
pref = '400k_Tc7e8_co_wd_R'
suff = '_ordered.dat'
os.chdir(realz_dir)
# Make a dictionary for the data
ifd = IntegralFlashData()
headers = []
shortheaders = []
rflist = glob.glob(pref + '*' + suff)
N = len(rflist)
print 'Found this many CO files: ' + str(N)
cpick = ColorPicker()
colors = cpick.pickColors(N)
first = True
for fn in rflist:
print fn
ni = int(fn.replace(pref, '').replace(suff, ''))
ifd.readInts(fn)
ifd.GramsToMsun()
ifdk = 'co_' + str(ni)
from IntegralFlashData import IntegralFlashData
import numpy as np
from collections import OrderedDict
import sys
av = sys.argv
impa = '24'
if len(av)==2:
impa = str(int(av[1]))
pbi = [2, 4, 6, 8, 12, 16, 20]
pbir = [str(p) for p in pbi]
pref = 'profile75_mpole-'
suff = '_r-35e6_a-' + impa + 'e5.dat'
ifd = IntegralFlashData()
# Make a dictionary for the data
ifdata = OrderedDict([])
pfmt = OrderedDict([])
for i in xrange(0,len(pbir)):
p = pbir[i]
iname = pref + p + suff
ifd.readInts(iname)
ifd.orderData()
ifd.saveOrderedData()
ifd.clrArrayData()
# Don: 12/11/2015: just fixed re expression for dir_re to permit finding amplitude 6 files
# bringing the total number of integral files to the correct number of 35.
import os
import re
import csv
from collections import OrderedDict
## Custom imports
from IntegralFlashData import IntegralFlashData
## Setup
dir_re = re.compile('\A.*/ignMPoleA-([0-9]{1,2})e5\Z')
fil_re = re.compile(
'\Aprofile75_mpole-([0-9]{1,2})_r-35e6_a-([0-9]{1,2})e5_ordered.dat\Z')
ifd = IntegralFlashData()
data = [] # data_entry={}
def getData(f, ifd=ifd):
ifd.readInts(f)
ifd.GramsToMsun()
dat = ifd.getArrayData()
ifd.clrArrayData()
return dat
# Collect integrals from each file
for root, dirs, files in os.walk(os.getcwd()):
print 'in directory: ' + root
from IntegralFlashData import IntegralFlashData
import numpy as np
import matplotlib.pyplot as plt
from collections import OrderedDict
import sys
import bisect
import glob as glob
ifd = IntegralFlashData()
if len(sys.argv)==1:
print 'Please supply a list of input files to process!'
exit()
ifnames = sys.argv[1:]
N = len(ifnames)
min_time = 0.25
# Make a dictionary for the data
ifdata = OrderedDict([])
dettimes = OrderedDict([])
headers = []
shortheaders = []
for i in xrange(0,N):
iname = ifnames[i]
inum = iname.split('-')[1].split('.')[0]
intdatname = glob.glob('profile75_mpole-'+inum+'*_ordered.dat')
ifd.readInts(intdatname[0])
ifdata[inum] = ifd.getArrayData()
if i==0:
headers = ifdata[inum].keys()
