# sp_ax.plot(nu, b, 'k--')
(nu, b, _) = calc_mo_white_nu(1000, cosmo)
st_ax.plot(nu, b, 'k-')
sp_ax.plot(nu, b, 'k-')
(nu, b, _) = calc_sheth_tormen_nu(1000, cosmo)
st_ax.plot(nu, b, 'g-')
sp_ax.plot(nu, b, 'g-')
age_bins = 5
mass_bins = 7
ifile = 'properties.dat'
agelabel = 'Sub-Max-Form. Age'
overall_data = ([],[])
for (i, s) in enumerate(snaps):
snap_dir = 'snap{0}{1}'.format(s, snap_id)
direc = '{0}Desktop/age-clustering-data/{1}/attempt1_sub_form_jp/'.format(home, snap_dir)
data = readfile('{0}{1}'.format(direc, ifile), col = 28, delim = ' ', skip = 1)
col_j = ['k', 'b', 'c', 'g', 'm', 'r'] #Colors of Age bins that are plotted
for age_i in range(0, age_bins + 1):
bias = []
mass = []
for mass_i in range(1, mass_bins + 1):
b_data = readfile('{0}bias/bias_{1}_{2}'.format(direc, mass_i, age_i), col = 2, delim = ',', skip = 1)
idx1 = where(logical_and(b_data[0] >= 5 * h, b_data[0] <= 15 * h))[0]
idx2 = where(logical_and(data[0] == mass_i, data[1] == age_i))[0]
bias.append(sum(b_data[1][idx1]) / len(b_data[1][idx1]))
mass.append(data[4][idx2][0])
bias = array(bias)
mass = array(mass)
if symbs[i] == 'p' or symbs[i] == '*':
symsize = 5.
else:
elif sys.argv[6] == 'True' or sys.argv[6] == 'true' or sys.argv[
6] == '1':
log_flag = True
else:
raise TypeError(
'Log-flag should be be some type of boolean value such as (true, false, 1, or 0).'
)
except IndexError:
print 'No Log-flag given assuming linear space.'
if not check_max_min_step(low, high, step):
raise RuntimeError(
'Given min, max, step don\'t make sense: minimum: {0} maximum: {1} '
'step: {2}'.format(low, high, step))
##Setup and Input Error check complete
#Create new radius values
if not log_flag:
r_new = np.linspace(low, high, (high - low) / step + 1.)
else:
r_new = np.logspace(low, high, (high - low) / step + 1.)
zeros = np.zeros(len(r_new))
#Read in old correlation file.
##THE FOLLOWING ONLY WORKS WITH BOYLAN-KOLCHIN'S CORREL FILES
infile_data = readfile(infile, col=4, delim=' ', skip=2)
new_cf_func = inter.splrep(infile_data[0], infile_data[1])
new_corr = create_corr_struct(r_new, inter.splev(r_new, new_cf_func),
zeros, zeros, zeros, 0)
plt.loglog(infile_data[0], infile_data[1])
plt.loglog(new_corr['data'].r, new_corr['data'].cf, '*')
plt.show()
write_corr_file(outfile, new_corr)
print 'File {0} saved.'.format(outfile)
titles = ('Max-Formation-FOF Age', 'Root-Formation-FOF Age',
'Max-Assembly-FOF Age', 'Root-Assembly-FOF Age',
'Max-Formation-subhalo Age', 'Root-Formation-subhalo Age',
'Max-Assembly-subhalo Age', 'Root-Assembly-subhalo Age')
outs = ('prop_table_fof_form_jp.tex', 'prop_table_fof_form_gao.tex',
'prop_table_fof_assem_jp.tex', 'prop_table_fof_assem_gao.tex',
'prop_table_sub_form_jp.tex', 'prop_table_sub_form_gao.tex',
'prop_table_sub_assem_jp.tex', 'prop_table_sub_assem_gao.tex')
snaps = (22, 27, 31, 36, 40, 45, 51, 67)
zs = (6.196857, 4.179475, 3.060424, 2.0700316, 1.5036374, 0.98870987,
0.5641763, 0.)
snap_postfix = '-1'
files = 'properties.dat'
for (t, l, o, tt) in zip(tables, table_labels, outs, titles):
o_direc = join(b_o_direc, o)
of = setup_file(o_direc)
for (sn, z) in zip(snaps, zs):
t_direc = join(b_t_direc, 'snap{0}{1}'.format(sn, snap_postfix), t)
#data = []
#for f in files:
fn = join(t_direc, files)
try:
#data.append(readfile(fn, col = 28, delim = ' ', skip = 1))
data = readfile(fn, col = 28, delim = ' ', skip = 1)
data.extend((z, t_direc))
except IOError:
print('Unable to open: ', fn, file=stderr)
data = None
if data != None:
write_tex(of, l, data, sn == snaps[-1])
close_file(of)
st_ax.plot(nu, b, 'k--')
sp_ax.plot(nu, b, 'k--')
(nu, b, _) = calc_mo_white_nu(1000, cosmo)
st_ax.plot(nu, b, 'k-')
sp_ax.plot(nu, b, 'k-')
(nu, b, _) = calc_sheth_tormen_nu(1000, cosmo)
st_ax.plot(nu, b, 'g-')
sp_ax.plot(nu, b, 'g-')
age_bins = 5
mass_bins = 7
ifile = 'properties.dat'
agelabel = 'Sub-Max-Form. Age'
for (i, s) in enumerate(snaps):
snap_dir = 'snap{0}{1}'.format(s, snap_id)
direc = '{0}Desktop/age-clustering-data/{1}/attempt1_sub_form_jp/'.format(home, snap_dir)
data = readfile('{0}{1}'.format(direc, ifile), col = 28, delim = ' ', skip = 1)
col_j = ['k', 'b', 'c', 'g', 'm', 'r'] #Colors of Age bins that are plotted
for age_i in range(0, age_bins + 1):
bias = []
mass = []
for mass_i in range(1, mass_bins + 1):
b_data = readfile('{0}bias/bias_{1}_{2}'.format(direc, mass_i, age_i), col = 2, delim = ',', skip = 1)
idx1 = where(logical_and(b_data[0] >= 5 * h, b_data[0] <= 15 * h))[0]
idx2 = where(logical_and(data[0] == mass_i, data[1] == age_i))[0]
bias.append(sum(b_data[1][idx1]) / len(b_data[1][idx1]))
mass.append(data[4][idx2][0])
bias = array(bias)
mass = array(mass)
if symbs[i] == 'p' or symbs[i] == '*':
symsize = 5.
else:
print 'Check your minimum, maximum and step inputs: minimum: {0} maximum: {1} '
'step: {2}'.format(sys.argv[3], sys.argv[4], sys.argv[5])
try:
if sys.argv[6] == 'False' or sys.argv[6] == 'false' or sys.argv[6] == '0':
log_flag = False
elif sys.argv[6] == 'True' or sys.argv[6] == 'true' or sys.argv[6] == '1':
log_flag = True
else:
raise TypeError('Log-flag should be be some type of boolean value such as (true, false, 1, or 0).')
except IndexError:
print 'No Log-flag given assuming linear space.'
if not check_max_min_step(low, high, step):
raise RuntimeError('Given min, max, step don\'t make sense: minimum: {0} maximum: {1} '
'step: {2}'.format(low, high, step))
##Setup and Input Error check complete
#Create new radius values
if not log_flag:
r_new = np.linspace(low, high, (high - low) / step + 1.)
else:
r_new = np.logspace(low, high, (high - low) / step + 1.)
zeros = np.zeros(len(r_new))
#Read in old correlation file.
##THE FOLLOWING ONLY WORKS WITH BOYLAN-KOLCHIN'S CORREL FILES
infile_data = readfile(infile, col = 4, delim = ' ', skip = 2)
new_cf_func = inter.splrep(infile_data[0], infile_data[1])
new_corr = create_corr_struct(r_new, inter.splev(r_new, new_cf_func), zeros, zeros, zeros, 0)
plt.loglog(infile_data[0], infile_data[1])
plt.loglog(new_corr['data'].r, new_corr['data'].cf, '*')
plt.show()
write_corr_file(outfile, new_corr)
print 'File {0} saved.'.format(outfile)
