def plot(query, xlabel, ylabel, output, out_folder,
bulge=0.4, xbin=10, ybin=10, xmin=-0.1, xmax=6):
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query))
#sphericals
mask = (data[:, 2] > bulge) & (data[:, 3] > 0.5)
xe = data[:, 0][mask]
ye = data[:, 1][mask]
# disks
disks = (data[:, 2] <= bulge) & (data[:, 3] > 0.5)
xd = data[:, 0][disks]
yd = data[:, 1][disks]
#IR bright
mask = data[:, 4] > 1e-3
xir = data[:, 0][mask]
yir = data[:, 1][mask]
#calculate means and percentiles
xmd, y50d, y16d, y84d = dm.average_bins(xd, yd, xmin, xmax, nxbins=20)
xmt, y50t, y16t, y84t = dm.average_bins(data[:, 0], data[:, 1], xmin, xmax, nxbins=20)
xme, y50e, y16e, y84e = dm.average_bins(xe, ye, xmin, xmax, nxbins=20)
xmir, y50ir, y16ir, y84ir = dm.average_bins(xir, yir, xmin, xmax, nxbins=20)
#figure
fig = P.figure()
ax1 = fig.add_subplot(111)
#plots
# ax1.errorbar(xmt, y50t, yerr = [y50t, y84t], label = 'Total',
# c = 'k')
# ax1.errorbar(xmd, y50d, yerr = [y50d, y84d], label = 'Late-types',
# c = 'b', ls = '--')
# ax1.errorbar(xme, y50e, yerr = [y16e, y84e-y50e], label = 'Early-types',
# c = 'r', ls = '-.')
ax1.errorbar(xmir, y50ir, yerr=[y16ir, y84ir], label='$S_{250} > 1$ mJy',
c='m', ls=':')
ax1.plot(xmt, y50t, 'k-', label='Total')
ax1.plot(xmd, y50d, 'b--', label='Late-types')
ax1.plot(xme, y50e, 'r-.', label='Early-types')
# ax1.fill_between(xmt, y16t, y50t, label = 'Total')
# ax1.fill_between(xmd, y16d, y50d, label = 'Late-type')
# ax1.fill_between(xme, y16e, y50e, label = 'Early-type')
# ax1.fill_between(xmir, y16ir, y50ir, label = '$S_{250} > 5$ mJy')
#limits and labels
ax1.set_xlim(0.0, xmax - .3)
ax1.set_ylim(1e-3, 100.0)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
ax1.set_yscale('log')
#legend
ax1.legend(shadow=True, fancybox=True, loc='lower right')
#save and close
P.savefig(out_folder + output)
P.close()
def plot_properties(query,
xlabel,
ylabel,
output,
out_folder,
flux=5,
band=250,
pmin=0.1,
pmax=1.0,
xbin=15,
ybin=11,
xmin=7.9,
xmax=11.7,
ymin=0,
ymax=50):
'''
Plots
'''
#get data
data = sq.get_data_sqlitePowerTen(path, db, query)
#set 1: all galaxies
xd = data[:, 0]
yd = data[:, 1]
#set 2
mask = data[:, 1] > flux
xe = data[:, 0][mask]
ye = data[:, 1][mask]
#x limits for the right hand (scatter) plot
secxmin, secxmax = 0.99 * N.min(xe), 1.005 * N.max(xe)
if 'mstardot' in query:
secxmax = 1200.
if 'burst' in query:
secxmax = 1500.
#hess
sd, sdmin, sdmax = h.hess_plot(xd,
yd,
N.ones(len(xd)),
xmin,
xmax,
xbin,
ymin,
ymax,
ybin,
pmax=pmax,
pmin=pmin)
se, semin, semax = h.hess_plot(xe,
ye,
N.ones(len(xe)),
secxmin,
secxmax,
xbin - 4,
flux,
ymax,
ybin - 1,
pmax=pmax,
pmin=pmin)
#figure
# f, (ax1, ax2) = P.subplots(1, 2, sharey=True)
# f, (ax1, ax2) = P.subplots(1, 2, figsize=(10,10))
f, (ax1, ax2) = P.subplots(1, 2)
f.subplots_adjust(wspace=0.0,
hspace=0.01,
left=0.08,
bottom=0.07,
right=0.97,
top=0.93)
#hess plots
ims = ax1.imshow(sd,
vmin=sdmin,
vmax=sdmax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, ymin, ymax],
aspect='auto',
alpha=1)
ims = ax2.imshow(se,
vmin=semin,
vmax=semax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[secxmin, secxmax, flux, ymax],
aspect='auto',
alpha=1)
#flux limit lines
ax1.axhline(flux, color='green', ls='--')
ax2.axhline(flux, color='green', ls='--')
#scatter to the second plot
ax2.scatter(xe, ye, s=6, color='b')
#percentiles
xbin_midd, y50d, y16d, y84d = dm.percentile_bins(xd, yd, xmin, xmax)
md = (y50d > 0) | (y16d > 0) | (y84d > 0)
xbin_mide, y50e, y16e, y84e = dm.percentile_bins(xe, ye, secxmin, secxmax)
me = (y50e > 0) | (y16e > 0) | (y84e > 0)
ax1.plot(xbin_midd[md], y50d[md], 'r-')
ax1.plot(xbin_midd[md], y16d[md], 'r--')
ax1.plot(xbin_midd[md], y84d[md], 'r--')
ax2.plot(xbin_mide[me], y50e[me], 'r-')
ax2.plot(xbin_mide[me], y16e[me], 'r--')
ax2.plot(xbin_mide[me], y84e[me], 'r--')
#add text
P.text(0.5,
0.95,
'All galaxies',
horizontalalignment='center',
verticalalignment='center',
transform=ax1.transAxes)
P.text(0.5,
0.95,
r'%s > %.1f $ mJy' % (ylabel.split()[0], flux),
horizontalalignment='center',
verticalalignment='center',
transform=ax2.transAxes)
#labels
ax1.set_xlabel(xlabel)
ax2.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
#y tick positions
# ax1.set_yticks(yticks)
#ax2.set_yticks(yticks[1:-2])
#limits
ax1.set_xlim(xmin, xmax)
ax2.set_xlim(secxmin, secxmax)
ax1.set_ylim(ymin, ymax)
ax2.set_ylim(ymin, ymax)
ax2.set_yticks(ax2.get_yticks()[1:-1])
# ax2.set_xticks(ax2.get_xticks()[1:])
#make grid
ax1.grid()
ax2.grid()
P.savefig(out_folder + output)
def plot_ages(query,
xlabel,
ylabel,
output,
out_folder,
flux=5,
band=250,
title='$2.0 < z < 4.0$',
pmin=0.05,
pmax=1.0,
xbin=10,
ybin=15,
xmin=7.9,
xmax=11.7,
ymin=-1.5,
ymax=1.8,
scatters=False,
mean=False):
'''
Plots age versus a given quantity.
'''
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query))
#observable galaxies
mask = data[:, 1] > flux
xe = data[:, 0][mask]
ye = N.log10(data[:, 1][mask])
#all galaxies
xd = data[:, 0]
yd = N.log10(data[:, 1])
mask = yd != N.nan
xd = xd[mask]
yd = yd[mask]
#hess
sd, sdmin, sdmax = h.hess_plot(xd,
yd,
N.ones(len(xd)),
xmin,
xmax,
xbin,
ymin,
ymax,
ybin,
pmax=pmax,
pmin=pmin)
se, semin, semax = h.hess_plot(xe,
ye,
N.ones(len(xe)),
xmin,
xmax,
xbin,
N.log10(flux),
ymax,
ybin,
pmax=pmax,
pmin=pmin)
#figure
fig = P.figure()
fig.suptitle(title)
f, (ax1, ax2) = P.subplots(1, 2, sharey=True)
f.subplots_adjust(wspace=0.0,
hspace=0.01,
left=0.08,
bottom=0.07,
right=0.97,
top=0.93)
#contours
ims = ax1.imshow(sd,
vmin=sdmin,
vmax=sdmax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, ymin, ymax],
aspect='auto',
alpha=1)
ims = ax2.imshow(se,
vmin=semin,
vmax=semax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, N.log10(flux), ymax],
aspect='auto',
alpha=1)
#percentiles
xbin_midd, y50d, y16d, y84d = dm.percentile_bins(xd, yd, xmin, xmax)
md = (y50d > 0) & (y16d > 0) & (y84d > 0)
xbin_mide, y50e, y16e, y84e = dm.percentile_bins(xe, ye, xmin, xmax)
me = (y50e > 0) & (y16e > 0) & (y84e > 0)
ax1.plot(xbin_midd[md], y50d[md], 'r-')
ax1.plot(xbin_midd[md], y16d[md], 'r--')
ax1.plot(xbin_midd[md], y84d[md], 'r--')
ax2.plot(xbin_mide[me], y50e[me], 'r-')
ax2.plot(xbin_mide[me], y16e[me], 'r--')
ax2.plot(xbin_mide[me], y84e[me], 'r--')
#dots
if scatters:
ax1.scatter(xd, yd, c='b', s=10, marker='h', label='All galaxies')
ax2.scatter(xe,
ye,
c='r',
s=10,
marker='o',
label=r'$S_{%i} > %.1f$ mJy' % (band, flux))
#hlines
if mean:
#mean size
mean_disk = N.mean(yd)
mean_early = N.mean(ye)
ax1.axhline(mean_disk, c='b', label='Mean')
ax2.axhline(mean_early, c='r', label='Mean')
#add text
P.text(0.5,
0.95,
'All galaxies',
horizontalalignment='center',
verticalalignment='center',
transform=ax1.transAxes)
P.text(0.5,
0.95,
r'$S_{%i} > %.1f$ mJy' % (band, flux),
horizontalalignment='center',
verticalalignment='center',
transform=ax2.transAxes)
#labels
ax1.set_xlabel(xlabel)
ax2.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
#ax2.set_yticks([])
#limits
#ax1.set_ylim(ymin, ymax)
#ax2.set_ylim(ymin, ymax)
ax1.set_xlim(xmin, xmax)
ax2.set_xlim(xmin, xmax)
#yticks
#ax1.set_yticks(y1ticks)
#ax2.set_yticks(y2ticks)
#make grid
ax1.grid()
ax2.grid()
#write a legend
ax1.legend(shadow=True,
fancybox=True,
numpoints=1,
loc='upper left',
scatterpoints=1)
ax2.legend(shadow=True,
fancybox=True,
numpoints=1,
loc='upper left',
scatterpoints=1)
P.savefig(out_folder + output)
xmax1 = 11.7
ymin = 0.1;
ymax = 10
query1 = """select galprop.mstar, galprop.r_disk, Pow10(galprop.mbulge - galprop.mstar)
from FIR, galprop where
FIR.z >= 2.0 and
FIR.z < 4.0 and
FIR.gal_id = galprop.gal_id and
FIR.halo_id = galprop.halo_id and
galprop.tmerge > 0.5 and
FIR.spire250_obs > 1e-15 and
FIR.spire250_obs < 1e6
"""
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query1))
#slice the data
disks = data[:, 2] <= bulge
xd1 = data[:, 0][disks]
yd1 = data[:, 1][disks]
#old algorithm
so1, somin1, somax1 = hess_plot_old(xd1, yd1, N.ones(len(xd1)),
xmin1, xmax1, xbin1,
ymin, ymax, ybin1,
pmax=pmax, pmin=pmin)
#new algorithm
sn1, snmin1, snmax1 = hess_plot(xd1, yd1, N.ones(len(xd1)),
xmin1, xmax1, xbin1,
ymin, ymax, ybin1,
pmax=pmax, pmin=pmin)
def plot_size(query,
xlabel,
ylabel,
output,
out_folder,
bulge=0.4,
title='$2.0 < z < 4.0$',
pmin=0.05,
pmax=1.0,
xbin=15,
ybin=15,
y1ticks=[1, 3, 5, 7, 10],
y2ticks=[1, 3, 5, 7],
xmin=7.9,
xmax=11.7,
ymin=0.1,
ymax=10,
scatters=False,
mean=False):
'''
Plots size versus a given quantity.
'''
#get data
data = sq.get_data_sqlitePowerTen(path, db, query)
#sphericals
mask = data[:, 2] > bulge
xe = data[:, 0][mask]
ye = data[:, 1][mask]
# disks
disks = data[:, 2] <= bulge
xd = data[:, 0][disks]
yd = data[:, 1][disks]
#hess
sd, sdmin, sdmax = h.hess_plot(xd,
yd,
N.ones(len(xd)),
xmin,
xmax,
xbin,
ymin,
ymax,
ybin,
pmax=pmax,
pmin=pmin)
se, semin, semax = h.hess_plot(xe,
ye,
N.ones(len(xe)),
xmin,
xmax,
xbin,
ymin,
ymax,
ybin,
pmax=pmax,
pmin=pmin)
#figure
# fig = P.figure(figsize = (12, 12))
fig = P.figure()
fig.suptitle(title)
fig.subplots_adjust(wspace=0.0,
hspace=0.01,
left=0.08,
bottom=0.07,
right=0.97,
top=0.93)
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
#contours
# ax1.contourf(sd, origin = 'lower', colors = 'b',
# linewidths = 0.8, linestyles = '-',
# extent = [xmin, xmax, ymin, ymax],
# rightside_up = True, alpha = 0.7)#,
# #levels = [0.01, 0.3, 0.6, 0.9])
# ax2.contourf(se, origin = 'lower', colors = 'r',
# linewidths = 0.8, linestyles = '-',
# extent = [xmin, xmax, ymin, ymax],
# rightside_up = True, alpha = 0.7)
ims = ax1.imshow(sd,
vmin=sdmin,
vmax=sdmax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, ymin, ymax],
aspect='auto',
alpha=1)
ims = ax2.imshow(se,
vmin=semin,
vmax=semax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, ymin, ymax],
aspect='auto',
alpha=1)
#percentiles
xbin_midd, y50d, y16d, y84d = dm.percentile_bins(xd, yd, xmin, xmax)
md = (y50d > 0) & (y16d > 0) & (y84d > 0)
xbin_mide, y50e, y16e, y84e = dm.percentile_bins(xe, ye, xmin, xmax)
me = (y50e > 0) & (y16e > 0) & (y84e > 0)
ax1.plot(xbin_midd[md], y50d[md], 'r-')
ax1.plot(xbin_midd[md], y16d[md], 'r--')
ax1.plot(xbin_midd[md], y84d[md], 'r--')
ax2.plot(xbin_mide[me], y50e[me], 'r-')
ax2.plot(xbin_mide[me], y16e[me], 'r--')
ax2.plot(xbin_mide[me], y84e[me], 'r--')
#dots
if scatters:
ax1.scatter(xd, yd, c='b', s=10, marker='h', label='Late-type')
ax2.scatter(xe, ye, c='r', s=10, marker='o', label='Early-type')
#hlines
if mean:
#mean size
mean_disk = N.mean(yd)
mean_early = N.mean(ye)
ax1.axhline(mean_disk, c='b', label='Mean')
ax2.axhline(mean_early, c='r', label='Mean')
#add text
P.text(0.5,
0.95,
'Late-type galaxies',
horizontalalignment='center',
verticalalignment='center',
transform=ax1.transAxes)
P.text(0.5,
0.95,
'Early-type galaxies',
horizontalalignment='center',
verticalalignment='center',
transform=ax2.transAxes)
#labels
ax1.set_xlabel(xlabel)
ax2.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
ax2.set_yticks([])
#limits
ax1.set_ylim(ymin, ymax)
ax2.set_ylim(ymin, ymax)
ax1.set_xlim(xmin, xmax)
ax2.set_xlim(xmin, xmax)
#yticks
ax1.set_yticks(y1ticks)
ax2.set_yticks(y2ticks)
#make grid
#ax1.grid()
#ax2.grid()
#write a legend
ax1.legend(shadow=True,
fancybox=True,
numpoints=1,
loc='upper left',
scatterpoints=1)
ax2.legend(shadow=True,
fancybox=True,
numpoints=1,
loc='upper left',
scatterpoints=1)
P.savefig(out_folder + output)
def plot_size2(query,
xlabel,
ylabel,
output,
out_folder,
bulge=0.4,
title='$2.0 < z < 4.0$',
pmin=0.05,
pmax=1.0,
xbin=15,
ybin=15,
xmin=7.9,
xmax=11.7,
ymin=0.1,
ymax=10):
'''
Plots size versus a given quantity.
'''
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query))
# disks
disks = data[:, 2] <= bulge
xd = data[:, 0][disks]
yd = data[:, 1][disks]
#hess
sd, sdmin, sdmax = h.hess_plot(xd,
yd,
N.ones(len(xd)),
xmin,
xmax,
xbin,
ymin,
ymax,
ybin,
pmax=pmax,
pmin=pmin)
#figure
fig = P.figure()
fig.suptitle(title)
ax1 = fig.add_subplot(111)
ims = ax1.imshow(sd,
vmin=sdmin,
vmax=sdmax,
origin='lower',
cmap=cm.gray,
interpolation=None,
extent=[xmin, xmax, ymin, ymax],
aspect='auto',
alpha=1)
#percentiles
xbin_midd, y50d, y16d, y84d = dm.percentile_bins(xd, yd, xmin, xmax)
md = (y50d > 0) & (y16d > 0) & (y84d > 0)
ax1.plot(xbin_midd[md], y50d[md], 'r-')
ax1.plot(xbin_midd[md], y16d[md], 'r--')
ax1.plot(xbin_midd[md], y84d[md], 'r--')
#add text
P.text(0.5,
0.95,
'Late-type galaxies',
horizontalalignment='center',
verticalalignment='center',
transform=ax1.transAxes)
#labels
ax1.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
#limits
ax1.set_ylim(ymin, ymax)
ax1.set_xlim(xmin, xmax)
#yticks
#ax1.set_yticks(y1ticks)
#make grid
#ax1.grid()
#write a legend
ax1.legend(shadow=True,
fancybox=True,
numpoints=1,
loc='upper left',
scatterpoints=1)
P.savefig(out_folder + output)
FIR.spire250_obs < 1e6 and
FIR.gal_id = galprop.gal_id and
FIR.halo_id = galprop.halo_id
'''
query2 = '''select galprop.mstar, galprop.r_disk, Pow10(galprop.mbulge - galprop.mstar)
from FIR, galprop where
galprop.tmerge > 0.5 and
FIR.z >= 2.0 and
FIR.z < 4.0 and
FIR.spire250_obs > 5e-3 and
FIR.spire250_obs < 1e6 and
FIR.gal_id = galprop.gal_id and
FIR.halo_id = galprop.halo_id
'''
#get data query1
data = sq.get_data_sqlitePowerTen(path, db, query1)
# disks
disks = data[:, 2] <= bulge
xd1 = data[:, 0][disks]
yd1 = data[:, 1][disks]
#get data query1
data = sq.get_data_sqlitePowerTen(path, db, query2)
# disks
disks = data[:, 2] <= bulge
xd2 = data[:, 0][disks]
yd2 = data[:, 1][disks]
#find all galaxies in similar Mstellar range as SPIRE bright
yd2min = N.min(yd2)
yd2max = N.max(yd2)
msk = (yd1 >= yd2min) & (yd1 <= yd2max)
#print out some info
def plot_ages(query, xlabel, ylabel, output, out_folder,
flux = 5, band = 250, title = '$2.0 < z < 4.0$',
pmin = 0.05, pmax = 1.0,
xbin = 10, ybin = 15,
xmin = 7.9, xmax = 11.7, ymin = -1.5, ymax = 1.8,
scatters = False, mean = False):
'''
Plots age versus a given quantity.
'''
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query))
#observable galaxies
mask = data[:,1] > flux
xe = data[:,0][mask]
ye = N.log10(data[:,1][mask])
#all galaxies
xd = data[:,0]
yd = N.log10(data[:,1])
mask = yd != N.nan
xd = xd[mask]
yd = yd[mask]
#hess
sd, sdmin, sdmax = h.hess_plot(xd, yd, N.ones(len(xd)),
xmin, xmax, xbin,
ymin, ymax, ybin,
pmax = pmax, pmin = pmin)
se, semin, semax = h.hess_plot(xe, ye, N.ones(len(xe)),
xmin, xmax, xbin,
N.log10(flux), ymax, ybin,
pmax = pmax, pmin = pmin)
#figure
fig = P.figure()
fig.suptitle(title)
f, (ax1, ax2) = P.subplots(1, 2, sharey=True)
f.subplots_adjust(wspace = 0.0, hspace = 0.01, left = 0.08, bottom = 0.07,
right = 0.97, top = 0.93)
#contours
ims = ax1.imshow(sd, vmin = sdmin, vmax = sdmax,
origin = 'lower', cmap = cm.gray,
interpolation = None,
extent = [xmin, xmax, ymin, ymax],
aspect = 'auto', alpha = 1)
ims = ax2.imshow(se, vmin = semin, vmax = semax,
origin = 'lower', cmap = cm.gray,
interpolation = None,
extent = [xmin, xmax, N.log10(flux), ymax],
aspect = 'auto', alpha = 1)
#percentiles
xbin_midd, y50d, y16d, y84d = dm.percentile_bins(xd, yd, xmin, xmax)
md = (y50d > 0) & (y16d > 0) & (y84d > 0)
xbin_mide, y50e, y16e, y84e = dm.percentile_bins(xe, ye, xmin, xmax)
me = (y50e > 0) & (y16e > 0) & (y84e > 0)
ax1.plot(xbin_midd[md], y50d[md], 'r-')
ax1.plot(xbin_midd[md], y16d[md], 'r--')
ax1.plot(xbin_midd[md], y84d[md], 'r--')
ax2.plot(xbin_mide[me], y50e[me], 'r-')
ax2.plot(xbin_mide[me], y16e[me], 'r--')
ax2.plot(xbin_mide[me], y84e[me], 'r--')
#dots
if scatters:
ax1.scatter(xd, yd, c='b', s = 10,
marker = 'h', label = 'All galaxies')
ax2.scatter(xe, ye, c='r', s = 10,
marker = 'o', label = r'$S_{%i} > %.1f$ mJy' % (band, flux))
#hlines
if mean:
#mean size
mean_disk = N.mean(yd)
mean_early = N.mean(ye)
ax1.axhline(mean_disk, c = 'b', label = 'Mean')
ax2.axhline(mean_early, c = 'r', label = 'Mean')
#add text
P.text(0.5, 0.95, 'All galaxies',
horizontalalignment='center',
verticalalignment='center',
transform = ax1.transAxes)
P.text(0.5, 0.95, r'$S_{%i} > %.1f$ mJy' % (band, flux),
horizontalalignment='center',
verticalalignment='center',
transform = ax2.transAxes)
#labels
ax1.set_xlabel(xlabel)
ax2.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
#ax2.set_yticks([])
#limits
#ax1.set_ylim(ymin, ymax)
#ax2.set_ylim(ymin, ymax)
ax1.set_xlim(xmin, xmax)
ax2.set_xlim(xmin, xmax)
#yticks
#ax1.set_yticks(y1ticks)
#ax2.set_yticks(y2ticks)
#make grid
ax1.grid()
ax2.grid()
#write a legend
ax1.legend(shadow = True, fancybox = True,
numpoints = 1, loc = 'upper left',
scatterpoints = 1)
ax2.legend(shadow = True, fancybox = True,
numpoints = 1, loc = 'upper left',
scatterpoints = 1)
P.savefig(out_folder + output)
xmax1 = 11.7
ymin = 0.1
ymax = 10
query1 = """select galprop.mstar, galprop.r_disk, Pow10(galprop.mbulge - galprop.mstar)
from FIR, galprop where
FIR.z >= 2.0 and
FIR.z < 4.0 and
FIR.gal_id = galprop.gal_id and
FIR.halo_id = galprop.halo_id and
galprop.tmerge > 0.5 and
FIR.spire250_obs > 1e-15 and
FIR.spire250_obs < 1e6
"""
#get data
data = N.array(sq.get_data_sqlitePowerTen(path, db, query1))
#slice the data
disks = data[:, 2] <= bulge
xd1 = data[:, 0][disks]
yd1 = data[:, 1][disks]
#old algorithm
so1, somin1, somax1 = hess_plot_old(xd1,
yd1,
N.ones(len(xd1)),
xmin1,
xmax1,
xbin1,
ymin,
ymax,
ybin1,
pmax=pmax,