def plot_selection_new(ident, dt=1.0, w=10.0):
dx, dy = ident.x1 - ident.x0, ident.y1 - ident.y0
ang = np.mod(np.arctan2(dy, dx), 2.0 * np.pi)
r = np.sqrt(dx**2 + dy**2)
drdt = r / (ident.t1 - ident.t0)
sa, ca = np.sin(ang), np.cos(ang)
dx = np.array([-dt, -dt, ident.t1 + dt, ident.t1 + dt, -dt]) * drdt
dy = np.array([w, -w, -w, w, w])
x = ca * dx - sa * dy + ident.x0
y = sa * dx + ca * dy + ident.y0
ppg.pgline(x, y)
ppg.pgpt1(x[0], y[0], 17)
ppg.pgpt1(x[1], y[1], 17)
ppg.pgsch(0.65)
ppg.pgslw(2)
if (x[0] < x[1]) & (ident.x0 < ident.x1):
ppg.pgptxt(x[1], y[1] - 1.5 * w, 0.0, 0.0, " %05d" % ident.norad)
else:
ppg.pgptxt(x[0], y[0] + 0.5 * w, 0.0, 0.0, " %05d" % ident.norad)
ppg.pgsch(1.0)
ppg.pgslw(1)
return
def plotsigsff(sig, sf, file, nbin):
psplot = file + ".ps"
psplotinit(psplot)
tot = N.ones(len(sf), 'f')
(sigbin, sfbin) = my.binitsumequal(sig, sf, nbin)
(sigbin, totbin) = my.binitsumequal(sig, tot, nbin)
print sfbin
print totbin
(sff, sfferr) = my.ratioerror(sfbin, totbin)
ppgplot.pgbox("", 0.0, 0, "L", 0.0, 0)
ymin = -.05
ymax = 1.05
xmin = min(sig) - 10.
#xmax=max(sig)-200.
xmax = 350.
ppgplot.pgenv(xmin, xmax, ymin, ymax, 0)
ppgplot.pglab("\gS\d5\u (gal/Mpc\u2\d)", "Fraction EW([OII])>4 \(2078)",
"")
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
sig = N.array(sig, 'f')
sff = N.array(sff, 'f')
ppgplot.pgsci(2)
ppgplot.pgline(sigbin, sff)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, sff, 17)
my.errory(sigbin, sff, sfferr)
ppgplot.pgend()
def plotdVdz():
nv = 3.
nr = 1.
ppgplot.pgbeg("dVdz.ps/vcps", 1, 1) #color port.
ppgplot.pgpap(8., 1.25)
ppgplot.pgpage
ppgplot.pgsch(1.2) #font size
ppgplot.pgslw(3) #line width
# 1st panel with symbols w/ stddev errorbars
x1 = .15
x2 = .45
x3 = .6
x4 = .95
y1 = .15
y2 = .425
y3 = .575
y4 = .85
xlabel = 14.1 - 14.
ylabel = 1.15
schdef = 1.2
slwdef = 4
ppgplot.pgsch(schdef)
xmin = 0.
xmax = 1.1
ymin = 0.
ymax = 1.2
ppgplot.pgsvp(x1, x4, y1, y4) #sets viewport
ppgplot.pgslw(slwdef) #line width
ppgplot.pgswin(xmin, xmax, ymin, ymax) #axes limits
ppgplot.pgbox('bcnst', .2, 2, 'bcvnst', .2, 2) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "z") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, "(1/DH)\u3\d c dV\dc\u/dv/d\gW")
z = N.arange(0., 5., .1)
beta = ((1 + z)**2 - 1) / ((1 + z)**2 + 1)
dV = N.zeros(len(z), 'd')
for i in range(len(z)):
#dz=dv/(1+z[i])*(1- ((1+z[i])**2 -1)/((1+z[i])**2+1))**(-2)
#z1=z[i]-0.5*dz
#z2=z[i]+0.5*dz
#dV[i]=my.dL(z2,h) - my.dL(z1,h)
dA = my.DA(z[i], h) * 206264. / 1000.
dV[i] = DH * (1 + z[i]) * (dA)**2 / (my.E(
z[i])) / (1 - beta[i])**2 / DH**3
#dV[i]=DH*(1+z[i])**2*(dA)**2/(my.E(z[i]))/DH**3#for comparison w/Hogg
if z[i] < 1:
print i, z[i], dV[i], dV[i]**(1. / 3.)
ppgplot.pgline(z, dV)
ppgplot.pgend()
def resetdefaults():
"""
resetdefaults():
Reset global plotting variables to default values.
"""
global ppgplot_font_, ppgplot_linestyle_, ppgplot_linewidth_, \
ppgplot_color_, ppgplot_font_size_
ppgplot.pgscf(ppgplot_font_)
ppgplot.pgsls(ppgplot_linestyle_)
ppgplot.pgslw(ppgplot_linewidth_)
ppgplot.pgsci(ppgplot_colors_[ppgplot_color_])
ppgplot.pgsch(ppgplot_font_size_)
def resetdefaults():
"""
resetdefaults():
Reset global plotting variables to default values.
"""
global ppgplot_font_, ppgplot_linestyle_, ppgplot_linewidth_, \
ppgplot_color_, ppgplot_font_size_
ppgplot.pgscf(ppgplot_font_)
ppgplot.pgsls(ppgplot_linestyle_)
ppgplot.pgslw(ppgplot_linewidth_)
ppgplot.pgsci(ppgplot_colors_[ppgplot_color_])
ppgplot.pgsch(ppgplot_font_size_)
def dm_time_plot(dms, times, sigmas, dm_arr, sigma_arr, time_arr,
Total_observed_time, xwin):
"""
Plot DM vs Time subplot for the spd plots.
Input:
dms: list of dms of single pulse events to be plotted.
times: list of times of single pulse events to be plotted.
sigmas: list of sigmas of single pulse events to be plotted.
dm_arr: array of dms of the main single pulse group (plotted in black).
sigma_arr: array of sigmas of the main single pulse group (plotted in black).
time_arr: array of times of single pulse group (plotted in black).
Total_observed_time: float : Total observation time
xwin: True or False. Use xwin or vcps window.
"""
min_dm = Num.min(dms)
max_dm = Num.max(dms)
ppgplot.pgswin(0, Total_observed_time, min_dm, max_dm)
ppgplot.pgsch(0.8)
ppgplot.pgslw(3)
ppgplot.pgbox("BCNST", 0, 0, "BCNST", 0, 0)
ppgplot.pgslw(3)
ppgplot.pgmtxt('B', 2.5, 0.5, 0.5, "Time (s)")
ppgplot.pgmtxt('L', 1.8, 0.5, 0.5, "DM (pc cm\u-3\d)")
snr_range = 12.0
cand_symbols = []
cand_symbols_group = []
for i in range(len(sigmas)):
if sigmas[i] > 20.00:
sigmas[i] = 20.0
cand_symbol = int((sigmas[i] - 5.0) / snr_range * 6.0 + 20.5)
cand_symbols.append(min(cand_symbol, 26))
cand_symbols = Num.array(cand_symbols)
for i in range(len(dm_arr)):
cand_symbol = int((sigma_arr[i] - 5.0) / snr_range * 6.0 + 20.5)
cand_symbols_group.append(min(cand_symbol, 26))
cand_symbols_group = Num.array(cand_symbols_group)
dms = Num.array(dms)
times = Num.array(times)
dm_arr = Num.array(dm_arr)
time_arr = Num.array(time_arr)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds = Num.nonzero(cand_symbols == ii)[0]
ppgplot.pgshls(1, 0.0, 0.5, 0.0)
ppgplot.pgpt(times[inds], dms[inds], ii)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds_1 = Num.nonzero(cand_symbols_group == ii)[0]
if xwin:
ppgplot.pgshls(1, 0.0, 0.8, 0.0)
else:
ppgplot.pgshls(1, 0.0, 0.0, 0.0)
ppgplot.pgpt(time_arr[inds_1], dm_arr[inds_1], ii)
def redraw():
ppgplot.pgslct(imagePlot['pgplotHandle'])
ppgplot.pgslw(3)
ppgplot.pggray(boostedImage, xlimits[0], xlimits[1] - 1, ylimits[0],
ylimits[1] - 1, imageMinMax[0], imageMinMax[1],
imagePlot['pgPlotTransform'])
if plotSources: plotCircles(dr2Objects, margins)
if plotHa:
reduceddr2cat = []
for selected in extendedHaSources:
reduceddr2cat.append(dr2Objects[selected])
plotCircles(reduceddr2cat, margins)
if plotGrid:
print("Plotting grid")
ppgplot.pgsci(6)
xVals = [p[0] for p in pixelGrid]
yVals = [p[1] for p in pixelGrid]
ppgplot.pgpt(xVals, yVals, 2)
if plotPointings:
ppgplot.pgsfs(2)
ppgplot.pgslw(10)
for p in pointings:
if p['type'] == "Maximum": ppgplot.pgsci(2)
if p['type'] == "Minimum": ppgplot.pgsci(4)
ppgplot.pgcirc(p['x'], p['y'], 30)
ppgplot.pgslw(1)
if plotBrightStars:
ppgplot.pgsci(3)
ppgplot.pgsfs(2)
ppgplot.pgslw(10)
for b in brightStars:
ppgplot.pgcirc(b['x'], b['y'], 40)
def plotold():
xmin=2.2
xmax=3.2
ymin=-2.5
ymax=-.5
psplotinit('fSsigma3Gyr.ps')
ppgplot.pgbox("",0.0,0,"",0.0,0)
ppgplot.pgenv(xmin,xmax,ymin,ymax,0,30)
ppgplot.pglab("\gs (km/s)",'fS(10\u11\d:10\u13\d)',"")
ppgplot.pgsci(1)
ppgplot.pgline(sigma,frac)
ppgplot.pgsls(2)
ppgplot.pgsci(2)
ppgplot.pgline(sigma08,frac08)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
ppgplot.pgend()
xmin=2.2
xmax=3.2
ymin=11.
ymax=14.2
psplotinit('maccretsigma3Gyr.ps')
ppgplot.pgbox("",0.0,0,"",0.0,0)
ppgplot.pgenv(xmin,xmax,ymin,ymax,0,30)
ppgplot.pglab("\gs (km/s)",'M\dacc\u (M\d\(2281)\u)',"")
ppgplot.pgsci(1)
ppgplot.pgline(sigma,maccret)
ppgplot.pgsls(2)
ppgplot.pgsci(2)
ppgplot.pgline(sigma08,maccret08)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
mylines=N.arange(-20.,20.,.4)
mylineswidth=3
ppgplot.pgsls(4)
ppgplot.pgslw(mylineswidth)
x=N.arange(0.,5.,1.)
lines=mylines
for y0 in lines:
y=3*x +y0
ppgplot.pgline(x,y)
ppgplot.pgsls(1)
ppgplot.pgend()
os.system('cp maccretsigma.ps /Users/rfinn/SDSS/paper/.')
os.system('cp fSsigma.ps /Users/rfinn/SDSS/paper/.')
def resetdefaults():
"""
resetdefaults():
Reset global plotting variables to default values.
"""
global ppgplot_font_, ppgplot_linestyle_, ppgplot_linewidth_, \
ppgplot_color_, ppgplot_font_size_
ppgplot.pgscf(ppgplot_font_)
ppgplot.pgsls(ppgplot_linestyle_)
ppgplot.pgslw(ppgplot_linewidth_)
ppgplot.pgsci(ppgplot_colors_[ppgplot_color_])
# My little add-on to switch the background to white
reset_colors()
ppgplot.pgsch(ppgplot_font_size_)
def dm_time_plot(dms, times, sigmas, dm_arr, sigma_arr, time_arr, Total_observed_time, xwin):
"""
Plot DM vs Time subplot for the spd plots.
Input:
dms: list of dms of single pulse events to be plotted.
times: list of times of single pulse events to be plotted.
sigmas: list of sigmas of single pulse events to be plotted.
dm_arr: array of dms of the main single pulse group (plotted in black).
sigma_arr: array of sigmas of the main single pulse group (plotted in black).
time_arr: array of times of single pulse group (plotted in black).
Total_observed_time: float : Total observation time
xwin: True or False. Use xwin or vcps window.
"""
min_dm = Num.min(dms)
max_dm = Num.max(dms)
ppgplot.pgswin(0, Total_observed_time, min_dm, max_dm)
ppgplot.pgsch(0.8)
ppgplot.pgslw(3)
ppgplot.pgbox("BCNST", 0, 0, "BCNST", 0, 0)
ppgplot.pgslw(3)
ppgplot.pgmtxt('B', 2.5, 0.5, 0.5, "Time (s)")
ppgplot.pgmtxt('L', 1.8, 0.5, 0.5, "DM (pc cm\u-3\d)")
snr_range = 12.0
cand_symbols = []
cand_symbols_group = []
for i in range(len(sigmas)):
if sigmas[i] > 20.00:
sigmas[i] = 20.0
cand_symbol = int((sigmas[i] - 5.0)/snr_range * 6.0 + 20.5)
cand_symbols.append(min(cand_symbol, 26))
cand_symbols = Num.array(cand_symbols)
for i in range(len(dm_arr)):
cand_symbol = int((sigma_arr[i] - 5.0)/snr_range * 6.0 + 20.5)
cand_symbols_group.append(min(cand_symbol, 26))
cand_symbols_group = Num.array(cand_symbols_group)
dms = Num.array(dms)
times = Num.array(times)
dm_arr = Num.array(dm_arr)
time_arr = Num.array(time_arr)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds = Num.nonzero(cand_symbols == ii)[0]
ppgplot.pgshls(1, 0.0, 0.5, 0.0)
ppgplot.pgpt(times[inds], dms[inds], ii)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds_1 = Num.nonzero(cand_symbols_group == ii)[0]
if xwin:
ppgplot.pgshls(1, 0.0, 0.8, 0.0)
else:
ppgplot.pgshls(1, 0.0, 0.0, 0.0)
ppgplot.pgpt(time_arr[inds_1], dm_arr[inds_1], ii)
def makeplot():
psplotinit("noise.ps")
DATAMIN = 0.
DATAMAX = 15.
ppgplot.pgbox("", 0.0, 0, "L", 0.0, 0)
#print "making graph, ncl = ",ncl
path = os.getcwd()
f = path.split('/')
#print path
#print f
prefix = f[4]
title = prefix
ymin = -.05
ymax = max(aveaperr) + .1
#ymax=10.
ppgplot.pgenv(DATAMIN, DATAMAX, ymin, ymax, 0)
ppgplot.pglab("linear size N of aperture (pixel)", "rms in Sky (ADU/s)",
title)
ppgplot.pgsci(2) #red
ppgplot.pgslw(4) #line width
x = N.sqrt(avearea)
y = aveaperr
ppgplot.pgpt(x, y, 7)
#errory(x,y,erry)
ppgplot.pgsci(1) #black
#ppgplot.pgpt(isoarea,fluxerriso,3)
#x1=N.sqrt(contsubisoarea)
#y1=contsuberr
#x1=N.sqrt(isoarea)
#y1=fluxerriso
#y=n*y1
#ppgplot.pgpt(x1,y1,1)
#ppgplot.pgsci(4)#blue
#ppgplot.pgpt(x1,y,1)
#ppgplot.pgsci(1)#black
x = N.arange(0, 50, 1)
y = x * (a + b * a * x)
#y=N.sqrt(x)*.02
ppgplot.pgline(x, y)
#errory(x,y,erry)
ppgplot.pgend()
def plotsig10sffall(sigspec, sigphot, sf, file, nbin):
psplot = file + ".ps"
psplotinit(psplot)
ppgplot.pgbox("", 0.0, 0, "L", 0.0, 0)
ymin = -.01
ymax = 1.01
#xmin=min(sigspec)-10.
#xmax=max(sig)-200.
#xmax=400.
xmin = -1.
xmax = 2.7
ppgplot.pgenv(xmin, xmax, ymin, ymax, 0, 10)
ppgplot.pglab("\gS\d10\u (gal/Mpc\u2\d)", "Fraction EW([OII])>4 \(2078)",
"")
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
tot = N.ones(len(sf), 'f')
(sigbin, sfbin) = my.binitsumequal(sigspec, sf, nbin)
(sigbin, totbin) = my.binitsumequal(sigspec, tot, nbin)
(sff, sfferr) = my.ratioerror(sfbin, totbin)
#sig=N.array(sig,'f')
#sff=N.array(sff,'f')
ppgplot.pgsci(2)
sigbin = N.log10(sigbin)
ppgplot.pgline(sigbin, sff)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, sff, 17)
my.errory(sigbin, sff, sfferr)
(sigbin, sfbin) = my.binitsumequal(sigphot, sf, nbin)
(sigbin, totbin) = my.binitsumequal(sigphot, tot, nbin)
(sff, sfferr) = my.ratioerror(sfbin, totbin)
#sig=N.array(sig,'f')
#sff=N.array(sff,'f')
ppgplot.pgslw(4) #line width
ppgplot.pgsci(4)
sigbin = N.log10(sigbin)
ppgplot.pgline(sigbin, sff)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, sff, 21)
#my.errory(sigbin,sff,sfferr)
ppgplot.pgend()
def plotsighaall(sig, psig, o2b, file, nbin):
o2b = N.array(o2b, 'f')
sig = N.array(sig, 'f')
psig = N.array(psig, 'f')
#o2b=o2b+4.
o2 = N.compress(o2b > -500., o2b)
sig = N.compress(o2b > -500., sig)
psig = N.compress(o2b > -500., psig)
psplot = file + ".ps"
psplotinit(psplot)
#ppgplot.pgsch(0.7)
ppgplot.pgslw(7)
(sigbin, o2bin) = my.binit(sig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgswin(-2., 2., -5., 20.)
ppgplot.pgbox('blcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gS\d10\u (gal/Mpc\u2\d)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'EW(H\ga) (\(2078))')
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgpt(sigbin, o2bin, 17)
ppgplot.pgpt(N.log10(sig), o2, 1)
#my.errory(sigbin,o2bin,yerr)
#print 'dude2', sigbin, o2bin
ppgplot.pgsci(2)
ppgplot.pgline(sigbin, o2bin)
(sigbin, o2bin) = my.binit(psig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, o2bin, 21)
#my.errory(sigbin,o2bin,yerr)
ppgplot.pgsci(4)
ppgplot.pgline(sigbin, o2bin)
ppgplot.pgsci(1)
ppgplot.pgend()
def dm_time_plot(dms, times, sigmas, dm_arr, sigma_arr, time_arr,
Total_observed_time, xwin):
"""
Plot DM vs Time.
"""
min_dm = Num.min(dms)
max_dm = Num.max(dms)
ppgplot.pgsvp(0.48, 0.97, 0.1, 0.54)
ppgplot.pgswin(0, Total_observed_time, min_dm, max_dm)
ppgplot.pgsch(0.8)
ppgplot.pgslw(3)
ppgplot.pgbox("BCNST", 0, 0, "BCNST", 0, 0)
ppgplot.pgslw(3)
ppgplot.pgmtxt('B', 2.5, 0.5, 0.5, "Time (s)")
ppgplot.pgmtxt('L', 1.8, 0.5, 0.5, "DM (pc cm\u-3\d)")
snr_range = 12.0
cand_symbols = []
cand_symbols_group = []
for i in range(len(sigmas)):
if sigmas[i] > 20.00:
sigmas[i] = 20.0
cand_symbol = int((sigmas[i] - 5.0) / snr_range * 6.0 + 20.5)
cand_symbols.append(min(cand_symbol, 26))
cand_symbols = Num.array(cand_symbols)
for i in range(len(dm_arr)):
cand_symbol = int((sigma_arr[i] - 5.0) / snr_range * 6.0 + 20.5)
cand_symbols_group.append(min(cand_symbol, 26))
cand_symbols_group = Num.array(cand_symbols_group)
dms = Num.array(dms)
times = Num.array(times)
dm_arr = Num.array(dm_arr)
time_arr = Num.array(time_arr)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds = Num.nonzero(cand_symbols == ii)[0]
ppgplot.pgshls(1, 0.0, 0.5, 0.0)
ppgplot.pgpt(times[inds], dms[inds], ii)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds_1 = Num.nonzero(cand_symbols_group == ii)[0]
if xwin:
ppgplot.pgshls(1, 0.0, 0.8, 0.0)
else:
ppgplot.pgshls(1, 0.0, 0.0, 0.0)
ppgplot.pgpt(time_arr[inds_1], dm_arr[inds_1], ii)
def dm_time_plot(dms, times, sigmas, dm_arr, sigma_arr, time_arr, Total_observed_time, xwin):
"""
Plot DM vs Time.
"""
min_dm = Num.min(dms)
max_dm = Num.max(dms)
ppgplot.pgsvp(0.48, 0.97, 0.1, 0.54)
ppgplot.pgswin(0, Total_observed_time, min_dm, max_dm)
ppgplot.pgsch(0.8)
ppgplot.pgslw(3)
ppgplot.pgbox("BCNST", 0, 0, "BCNST", 0, 0)
ppgplot.pgslw(3)
ppgplot.pgmtxt('B', 2.5, 0.5, 0.5, "Time (s)")
ppgplot.pgmtxt('L', 1.8, 0.5, 0.5, "DM (pc cm\u-3\d)")
snr_range = 12.0
cand_symbols = []
cand_symbols_group = []
for i in range(len(sigmas)):
if sigmas[i] > 20.00:
sigmas[i] = 20.0
cand_symbol = int((sigmas[i] - 5.0)/snr_range * 6.0 + 20.5)
cand_symbols.append(min(cand_symbol, 26))
cand_symbols = Num.array(cand_symbols)
for i in range(len(dm_arr)):
cand_symbol = int((sigma_arr[i] - 5.0)/snr_range * 6.0 + 20.5)
cand_symbols_group.append(min(cand_symbol, 26))
cand_symbols_group = Num.array(cand_symbols_group)
dms = Num.array(dms)
times = Num.array(times)
dm_arr = Num.array(dm_arr)
time_arr = Num.array(time_arr)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds = Num.nonzero(cand_symbols == ii)[0]
ppgplot.pgshls(1, 0.0, 0.5, 0.0)
ppgplot.pgpt(times[inds], dms[inds], ii)
for ii in [26, 25, 24, 23, 22, 21, 20]:
inds_1 = Num.nonzero(cand_symbols_group == ii)[0]
if xwin:
ppgplot.pgshls(1, 0.0, 0.8, 0.0)
else:
ppgplot.pgshls(1, 0.0, 0.0, 0.0)
ppgplot.pgpt(time_arr[inds_1], dm_arr[inds_1], ii)
def startPlotter(self):
if self.plotDeviceIsOpened:
raise ValueError("You already started a plot!")
devId = pgplot.pgopen(self.deviceName)
self.plotDeviceIsOpened = True
if not self.widthInches is None:
pgplot.pgpap(self.widthInches, self.yOnXRatio)
# For devices /xs, /xw, /png etc, should make the paper white and the ink black. Only for /ps does pgplot default to that.
#
deviceWithoutFile = self.deviceName.split('/')[-1]
if deviceWithoutFile == 'xs' or deviceWithoutFile == 'xw' or deviceWithoutFile == 'png':
pgplot.pgscr(0, 1.0, 1.0, 1.0)
pgplot.pgscr(1, 0.0, 0.0, 0.0)
pgplot.pgsvp(self._vXLo, self._vXHi, self._vYLo, self._vYHi)
if self.fixAspect:
pgplot.pgwnad(self.worldXLo, self.worldXHi, self.worldYLo,
self.worldYHi)
else:
pgplot.pgswin(self.worldXLo, self.worldXHi, self.worldYLo,
self.worldYHi)
pgplot.pgsfs(2)
pgplot.pgslw(1)
pgplot.pgsch(self._charHeight)
self._setColourRepresentations()
# Set up things so calling pgplot.pggray() won't overwrite the CR of any of the colours in self.colours.
#
(minCI, maxCI) = pgplot.pgqcir()
if minCI <= self.maxCI:
pgplot.pgscir(self.maxCI + 1, maxCI)
(xLoPixels, xHiPixels, yLoPixels, yHiPixels) = pgplot.pgqvsz(3)
(xLoInches, xHiInches, yLoInches, yHiInches) = pgplot.pgqvsz(1)
self.xPixelWorld = (xHiInches - xLoInches) / (xHiPixels - xLoPixels)
self.yPixelWorld = (yHiInches - yLoInches) / (yHiPixels - yLoPixels)
def plotgal(xg,yg,final,finalsf,ncl):
ppgplot.pgslw(6)
ppgplot.pgsls(1)
xmin = (-1.*c.pscale[ncl]*(c.xc[ncl]-1))
xmax = (c.pscale[ncl]*(c.xmax[ncl]-c.xc[ncl]))
ymin = (-1.*c.pscale[ncl]*(c.yc[ncl]-1))
ymax = (c.pscale[ncl]*(c.ymax[ncl]-c.yc[ncl]))
ppgplot.pgbox("",0.0,0,"L",0.0,0)
dx=5.
ppgplot.pgenv(xmin-dx,xmax+dx,ymin-dx,ymax+dx,0)
ppgplot.pglab("\gD DEC (\")","\gD RA (\")","")
ppgplot.pgtext(-4,-4,"X")
r = (0.5*c.r200pix[ncl]*c.pscale[ncl])
ppgplot.pgslw(1)
ppgplot.pgsls(2)
ppgplot.pgsfs(2)
ppgplot.pgcirc(0,0,r)
#print "cluster ",ncl," r200: ",c.r200pix[ncl],c.r200Mpc[ncl], " Mpc"
ppgplot.pgslw(3)
ppgplot.pgsls(1)
x = (xg - c.xc[ncl])*c.pscale[ncl]
y = (yg - c.yc[ncl])*c.pscale[ncl]
x = (N.compress((final > 0) & (finalsf < 1), xg) - c.xc[ncl])*c.pscale[ncl]
y = (N.compress((final > 0) & (finalsf < 1), yg) - c.yc[ncl])*c.pscale[ncl]
ppgplot.pgpt(x,y,22)
x = (N.compress((final > 0) & (finalsf > 0), xg) - c.xc[ncl])*c.pscale[ncl]
y = (N.compress((final > 0) & (finalsf > 0), yg) - c.yc[ncl])*c.pscale[ncl]
ppgplot.pgpt(x,y,18)
def plotsigo2(sig, o2, file, nbin):
psplot = file + ".ps"
psplotinit(psplot)
(sigbin, o2bin) = my.binit(sig, o2, nbin)
ppgplot.pgbox("", 0.0, 0, "L", 0.0, 0)
ymin = -10.
ymax = 2.
xmin = min(sig) - 10.
#xmax=max(sig)-200.
xmax = 350.
ppgplot.pgenv(xmin, xmax, ymin, ymax, 0)
ppgplot.pglab("\gS\d5\u (gal/Mpc\u2\d)", "EW([OII]) (\(2078))", "")
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
sig = N.array(sig, 'f')
o2 = N.array(o2, 'f')
ppgplot.pgpt(sig, o2, 1)
ppgplot.pgsci(2)
ppgplot.pgline(sigbin, o2bin)
ppgplot.pgsci(1)
ppgplot.pgend()
def plotsigo2all(sig, psig, o2b, file, nbin):
#o2=N.zeros(len(o2b),'f')
#for i in range(len(o2b)):
#print i, sig[i], psig[i], o2b[i]
# if o2b[i] < 0:
# o2[i]=-1*o2b[i]
#print "hey", o2[i]
o2 = o2b
psplot = file + ".ps"
psplotinit(psplot)
ppgplot.pgsch(0.7)
(sigbin, o2bin) = my.binit(sig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgswin(-1., 3., -.5, 10.)
ppgplot.pgbox('bcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gS\d10\u (gal/Mpc\u2\d)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'EW([OII]) (\(2078))')
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgsci(2)
ppgplot.pgpt(sigbin, o2bin, 17)
#print 'dude2', sigbin, o2bin
ppgplot.pgline(sigbin, o2bin)
(sigbin, o2bin) = my.binit(psig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgsci(4)
ppgplot.pgpt(sigbin, o2bin, 21)
ppgplot.pgline(sigbin, o2bin)
ppgplot.pgsci(1)
ppgplot.pgend()
def redraw():
ppgplot.pgslct(imagePlot["pgplotHandle"])
ppgplot.pgslw(3)
ppgplot.pggray(
boostedImage,
xlimits[0],
xlimits[1] - 1,
ylimits[0],
ylimits[1] - 1,
imageMinMax[0],
imageMinMax[1],
imagePlot["pgPlotTransform"],
)
if plotSources:
plotCircles(dr2Objects, margins)
if plotHa:
reduceddr2cat = []
for selected in extendedHaSources:
reduceddr2cat.append(dr2Objects[selected])
plotCircles(reduceddr2cat, margins)
if plotGrid:
print ("Plotting grid")
ppgplot.pgsci(6)
xVals = [p[0] for p in pixelGrid]
yVals = [p[1] for p in pixelGrid]
ppgplot.pgpt(xVals, yVals, 2)
if plotPointings:
ppgplot.pgsfs(2)
ppgplot.pgslw(10)
for p in pointings:
if p["type"] == "Maximum":
ppgplot.pgsci(2)
if p["type"] == "Minimum":
ppgplot.pgsci(4)
ppgplot.pgcirc(p["x"], p["y"], 30)
ppgplot.pgslw(1)
if plotBrightStars:
ppgplot.pgsci(3)
ppgplot.pgsfs(2)
ppgplot.pgslw(10)
for b in brightStars:
ppgplot.pgcirc(b["x"], b["y"], 40)
def plotngalsigmaradcuts():
nr = 1.
nv = 3.
bbJmax = -18.
ppgplot.pgbeg("ngalmhalo-radcut.ps/vcps", 1, 1) #color port.
ppgplot.pgpap(8., 1.25)
ppgplot.pgpage
ppgplot.pgsch(1.2) #font size
ppgplot.pgslw(3) #line width
# 1st panel with symbols w/ stddev errorbars
str1 = "R\dp\u < "
str2 = " R\dv\u"
x1 = .1
x2 = .45
x3 = .6
x4 = .95
y1 = .15
y2 = .425
y3 = .575
y4 = .85
xlabel = 14.25 - 14.
ylabel = 1.14
ppgplot.pgsvp(x1, x2, y3, y4) #sets viewport
g.cutonlbj(bbJmax)
#print "within plotradcuts, after cutonlbj, len(g.x1) = ",len(g.x1)
nr = 1.
c.measurengalcontam(nv, nr, g)
#print "nr = ",nr, " ave contam = ",N.average(c.contam)
sub1plotngalmcl(c.mass, c.membincut, c.obsmembincut)
ppgplot.pgsch(.8)
ppgplot.pgslw(3)
#label="R\dp\u < "+str(nr)+"R\dv\u"
label = str1 + str(nr) + str2
ppgplot.pgtext(xlabel, ylabel, label)
nr = .5
ppgplot.pgsvp(x1, x2, y1, y2) #sets viewport
#ppgplot.pgpanl(1,1)
c.measurengalcontam(nv, nr, g)
#print "nr = ",nr, " ave contam = ",N.average(c.contam)
sub1plotngalmcl(c.mass, c.membincut, c.obsmembincut)
label = str1 + str(nr) + str2
ppgplot.pgsch(.8)
ppgplot.pgslw(3)
ppgplot.pgtext(xlabel, ylabel, label)
ppgplot.pgend()
def sub1plotngalmcl(x, y1, y2):
schdef = 1.2
slwdef = 4
ppgplot.pgsch(schdef)
xmin = -.5
xmax = 1.
ymin = 0.
ymax = 60.
#nbin=5
ppgplot.pgslw(slwdef) #line width
ppgplot.pgswin(xmin, xmax, ymin, ymax) #axes limits
ppgplot.pgbox('bcnlst', 1.0, 0, 'bcvnst', 10., 2) #tickmarks and labeling
ppgplot.pgmtxt(
'b', 2.5, 0.5, 0.5,
"log\d10\u(10\u14\d M\dhalo\u/h\u-1\d M\d\(2281)\u)") #xlabel
ppgplot.pgmtxt('l', 2.1, 0.5, 0.5, "N\dgal\u")
(xbin, ybin, ybinerr) = my.biniterr(x, y1, nbin)
print y1
print 'ybin for y1 = ', ybin
xbin = N.log10(
xbin) + 12. - 14. #add back 10^12 Msun, then divide by 10^14
ppgplot.pgsch(1.5)
ppgplot.pgpt(xbin, ybin, 7)
ppgplot.pgslw(3)
ppgplot.pgerrb(6, xbin, ybin, ybinerr, 2.)
#my.errory(xbin,ybin,ybinerr)
(xbin, ybin, ybinerr) = my.biniterr(x, y2, nbin)
print y2
print 'ybin = ', ybin
xbin = N.log10(
xbin) + 12. - 14. #add back 10^12 Msun, then divide by 10^14
ppgplot.pgsch(1.75)
ppgplot.pgpt(xbin, ybin, 17)
ppgplot.pgsch(schdef)
ppgplot.pgerrb(6, xbin, ybin, ybinerr, 2.)
ppgplot.pgslw(slwdef)
def gotoit():
nbin = 10
#c=Cluster()
#g=Galaxy()
clusterfile = "clusters.spec.dat"
print "reading in cluster file to get cluster parameters"
c.creadfiles(clusterfile)
print "got ", len(c.z), " clusters"
c.convarray()
c.Kcorr()
go2 = [] #combined arrays containing all galaxies
gsf = [] #combined arrays containing all galaxies
gsig5 = []
gsig10 = []
gsig52r200 = [] #spec catalogs extended out to 2xR200
gsig102r200 = [] #spec catalogs extended out to 2xR200
gsig5phot = []
gsig10phot = []
sgo2 = [] #combined arrays containing all galaxies
sgha = [] #combined arrays containing all galaxies
sgsf = [] #combined arrays containing all galaxies
sgsig5 = []
sgsig10 = []
sgsig52r200 = [] #spec catalogs extended out to 2xR200
sgsig102r200 = [] #spec catalogs extended out to 2xR200
sgsig5phot = []
sgsig10phot = []
if (mode < 1):
c.getsdssphotcats()
c.getsdssspeccats()
gr = [] #list of median g-r colors
psplotinit('summary.ps')
x1 = .1
x2 = .45
x3 = .6
x4 = .95
y1 = .15
y2 = .45
y3 = .55
y4 = .85
ppgplot.pgsch(1.2) #font size
ppgplot.pgslw(2)
#for i in range(len(c.z)):
cl = [10]
(xl, xu, yl, yu) = ppgplot.pgqvp(0)
print "viewport = ", xl, xu, yl, yu
complall = []
for i in range(len(c.z)):
#for i in cl:
gname = "g" + str(i)
gname = Galaxy()
gspecfile = "abell" + str(c.id[i]) + ".spec.dat"
gname.greadfiles(gspecfile, i)
print "number of members = ", len(gname.z)
if len(gname.z) < 10:
print "less than 10 members", len(gname.z)
continue
gname.convarray()
#gname.cullmembers()
#gname.getmemb()#get members w/in R200
#gr.append(N.average(gname.g-gname.r))
gspec2r200file = "abell" + str(c.id[i]) + ".spec2r200.dat"
gname.greadspecfiles(gspec2r200file, c.dL[i], c.kcorr[i], i)
print i, c.id[i], " getnearest, first call", len(gname.ra), len(
gname.sra), sum(gname.smemb)
#gname.getnearest(i)
(gname.sig52r200, gname.sig102r200) = gname.getnearestgen(
gname.ra, gname.dec, gname.sra, gname.sdec, i
) #measure distances from ra1, dec1 to members in catalog ra2, dec2
sig52r200 = N.compress(gname.memb > 0, gname.sig52r200)
gsig52r200[len(gsig5phot):] = sig52r200
sig102r200 = N.compress(gname.memb > 0, gname.sig102r200)
gsig102r200[len(gsig10phot):] = sig102r200
gphotfile = "abell" + str(c.id[i]) + ".phot.dat"
gname.greadphotfiles(gphotfile, c.dL[i], c.kcorr[i])
gname.getnearest(i)
#print "len of local density arrays = ",len(gname.sig5),len(gname.sig5phot)
#print gspecfile, c.z[i],c.kcorr[i]
(ds5, ds10) = gname.gwritefiles(gspecfile, i)
o2 = N.compress(gname.memb > 0, gname.o2)
go2[len(go2):] = o2
sf = N.compress(gname.memb > 0, gname.sf)
gsf[len(gsf):] = sf
sig5 = N.compress(gname.memb > 0, gname.sig5)
gsig5[len(gsig5):] = sig5
sig10 = N.compress(gname.memb > 0, gname.sig10)
gsig10[len(gsig10):] = sig10
sig5phot = N.compress(gname.memb > 0, gname.sig5phot)
gsig5phot[len(gsig5phot):] = sig5phot
sig10phot = N.compress(gname.memb > 0, gname.sig10phot)
gsig10phot[len(gsig10phot):] = sig10phot
ds5 = N.array(ds5, 'f')
ds10 = N.array(ds10, 'f')
#print len(ds5),len(ds10)
#ppgplot.pgsvp(xl,xu,yl,yu)
ppgplot.pgsvp(0.1, .9, .08, .92)
ppgplot.pgslw(7)
label = 'Abell ' + str(
c.id[i]) + ' (z=%5.2f, \gs=%3.0f km/s)' % (c.z[i], c.sigma[i])
ppgplot.pgtext(0., 1., label)
ppgplot.pgslw(2)
ppgplot.pgsvp(x1, x2, y1, y2) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(-1., 3., -1., 3.) #axes limits
ppgplot.pgbox('bcnst', 1, 2, 'bcvnst', 1, 2) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5,
"\gS\d10\u(phot) (gal/Mpc\u2\d)") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, "\gS\d10\u(spec) (gal/Mpc\u2\d)")
x = N.arange(-5., 10., .1)
y = x
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgline(x, y)
x = N.log10(sig10phot)
y = N.log10(sig10)
ppgplot.pgsch(.7)
ppgplot.pgpt(x, y, 17)
xp = N.array([-0.5], 'f')
yp = N.array([2.5], 'f')
ppgplot.pgpt(xp, yp, 17)
ppgplot.pgtext((xp + .1), yp, 'spec(1.2xR200) vs phot')
ppgplot.pgsci(4)
xp = N.array([-0.5], 'f')
yp = N.array([2.2], 'f')
ppgplot.pgpt(xp, yp, 21)
ppgplot.pgtext((xp + .1), yp, 'spec(2xR200) vs phot')
y = N.log10(sig102r200)
ppgplot.pgsch(.9)
ppgplot.pgpt(x, y, 21)
ppgplot.pgsch(1.2)
ppgplot.pgslw(2) #line width
ppgplot.pgsci(1)
#ppgplot.pgenv(-200.,200.,-1.,20.,0,0)
#ppgplot.pgsci(2)
#ppgplot.pghist(len(ds5),ds5,-200.,200.,30,1)
#ppgplot.pgsci(4)
#ppgplot.pghist(len(ds10),ds10,-200.,200.,30,1)
#ppgplot.pgsci(1)
#ppgplot.pglab("\gD\gS","Ngal",gspecfile)
#ppgplot.pgpanl(1,2)
g = N.compress(gname.memb > 0, gname.g)
r = N.compress(gname.memb > 0, gname.r)
V = N.compress(gname.memb > 0, gname.V)
dmag = N.compress(gname.memb > 0, gname.dmagnearest)
dnearest = N.compress(gname.memb > 0, gname.nearest)
dz = N.compress(gname.memb > 0, gname.dz)
#ppgplot.pgsvp(x3,x4,y1,y2) #sets viewport
#ppgplot.pgenv(-.5,3.,-1.,5.,0,0)
#ppgplot.pgpt((g-V),(g-r),17)
#ppgplot.pgsci(1)
#ppgplot.pglab("g - M\dV\u",'g-r',gspecfile)
ppgplot.pgsvp(x1, x2, y3, y4) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(
(c.ra[i] + 2. * c.r200deg[i] / N.cos(c.dec[i] * N.pi / 180.)),
(c.ra[i] - 2 * c.r200deg[i] / N.cos(c.dec[i] * N.pi / 180.)),
(c.dec[i] - 2. * c.r200deg[i]), (c.dec[i] + 2. * c.r200deg[i]))
ppgplot.pgbox('bcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "RA") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, "Dec")
#ppgplot.pglab("RA",'Dec',gspecfile)
ppgplot.pgsfs(2)
ppgplot.pgcirc(c.ra[i], c.dec[i], c.r200deg[i])
ppgplot.pgsls(4)
ppgplot.pgcirc(c.ra[i], c.dec[i], 1.2 * c.r200deg[i])
ppgplot.pgsls(1)
#ppgplot.pgcirc(c.ra[i],c.dec[i],c.r200deg[i]/N.cos(c.dec[i]*N.pi/180.))
ppgplot.pgsci(2)
ppgplot.pgpt(gname.ra, gname.dec, 17)
ppgplot.pgsci(4)
ppgplot.pgpt(gname.photra, gname.photdec, 21)
ppgplot.pgsci(1)
#calculate completeness w/in R200
dspec = N.sqrt((gname.ra - c.ra[i])**2 + (gname.dec - c.dec[i])**2)
dphot = N.sqrt((gname.photra - c.ra[i])**2 +
(gname.photdec - c.dec[i])**2)
nphot = 1. * len(N.compress(dphot < c.r200deg[i], dphot))
nspec = 1. * len(N.compress(dspec < c.r200deg[i], dspec))
s = "Completeness for cluster Abell %s = %6.2f (nspec=%6.1f,nphot= %6.1f)" % (
str(c.id[i]), float(nspec / nphot), nspec, nphot)
print s
complall.append(float(nspec / nphot))
ppgplot.pgsvp(x3, x4, y3, y4) #sets viewport
#ppgplot.pgsvp(x1,x2,y3,y4) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(-0.005, .05, -1., 1.)
ppgplot.pgbox('bcnst', .02, 2, 'bcvnst', 1, 4) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5,
"Dist to nearest phot neighbor (deg)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'M\dV\u(phot) - M\dV\u(spec)')
ppgplot.pgsci(2)
ppgplot.pgpt(dnearest, dmag, 17)
ppgplot.pgsci(1)
x = N.arange(-30., 30., 1.)
y = 0 * x
ppgplot.pgsci(1)
ppgplot.pgsls(2)
ppgplot.pgline(x, y)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
dm = N.compress(dnearest < 0.01, dmag)
std = '%5.3f (%5.3f)' % (pylab.mean(dm), pylab.std(dm))
#ppgplot.pgslw(7)
#label='Abell '+str(c.id[i])
#ppgplot.pgtext(0.,1.,label)
ppgplot.pgslw(2)
label = '\gDM\dV\u(err) = ' + std
ppgplot.pgsch(.9)
ppgplot.pgtext(0., .8, label)
#label = "z = %5.2f"%(c.z[i])
#ppgplot.pgtext(0.,.8,label)
ppgplot.pgsch(1.2)
#ppgplot.pgsvp(x3,x4,y3,y4) #sets viewport
#ppgplot.pgenv(-.15,.15,-3.,3.,0,0)
#ppgplot.pgsci(2)
#ppgplot.pgpt(dz,dmag,17)
#ppgplot.pgsci(1)
#ppgplot.pglab("z-z\dcl\u",'\gD Mag',gspecfile)
ppgplot.pgsvp(x3, x4, y1, y2) #sets viewport
ppgplot.pgswin(-3., 3., -1., 1.)
ppgplot.pgbox('bcnst', 1, 2, 'bcvnst', 1, 4) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gDv/\gs") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'M\dV\u(phot) - M\dV\u(spec)')
ppgplot.pgsci(2)
dv = dz / (1 + c.z[i]) * 3.e5 / c.sigma[i]
ppgplot.pgpt(dv, dmag, 17)
ppgplot.pgsci(1)
x = N.arange(-30., 30., 1.)
y = 0 * x
ppgplot.pgsci(1)
ppgplot.pgsls(2)
ppgplot.pgline(x, y)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
#ppgplot.pgsvp(x1,x2,y1,y2) #sets viewport
#ppgplot.pgenv(0.,3.5,-3.,3.,0,0)
#ppgplot.pgsci(4)
#ppgplot.pgpt((g-r),dmag,17)
#ppgplot.pgsci(1)
#ppgplot.pglab("g-r",'\gD Mag',gspecfile)
#ppgplot.pgsvp(x1,x2,y1,y2) #sets viewport
#ppgplot.pgenv(-25.,-18.,-1.,1.,0,0)
#ppgplot.pgsci(4)
#ppgplot.pgpt((V),dmag,17)
#x=N.arange(-30.,30.,1.)
#y=0*x
#ppgplot.pgsci(1)
#ppgplot.pgsls(2)
#ppgplot.pgline(x,y)
#ppgplot.pgsls(1)
#ppgplot.pgsci(1)
#ppgplot.pglab("M\dV\u(spec)",'M\dV\u(phot) - M\dV\u(spec)',gspecfile)
#ppgplot.pgpage()
#ppgplot.pgpage()
#combine galaxy data
ppgplot.pgpage()
(sssig5,
sssig10) = gname.getnearestgen(gname.sra, gname.sdec, gname.sra,
gname.sdec,
i) #get spec-spec local density
(spsig5,
spsig10) = gname.getnearestgen(gname.sra, gname.sdec, gname.photra,
gname.photdec,
i) #get spec-phot local density
o2 = N.compress(gname.smemb > 0, gname.so2)
sgo2[len(sgo2):] = o2
ha = N.compress(gname.smemb > 0, gname.sha)
sgha[len(sgha):] = ha
sf = N.compress(gname.smemb > 0, gname.ssf)
sgsf[len(sgsf):] = sf
sig5 = N.compress(gname.smemb > 0, sssig5)
sgsig5[len(sgsig5):] = sig5
sig10 = N.compress(gname.smemb > 0, sssig10)
sgsig10[len(sgsig10):] = sig10
sig5phot = N.compress(gname.smemb > 0, spsig5)
sgsig5phot[len(sgsig5phot):] = sig5phot
sig10phot = N.compress(gname.smemb > 0, spsig10)
sgsig10phot[len(sgsig10phot):] = sig10phot
#gr=N.array(gr,'f')
#c.assigncolor(gr)
#for i in range(len(c.z)):
# print c.id[i],c.z[i],c.r200[i],c.r200deg[i]
print "Average Completeness w/in R200 = ", N.average(N.array(
complall, 'f'))
print "sig o2", len(gsig10), len(gsig10phot), len(go2)
print "sig o2 large", len(sgsig10), len(sgsig10phot), len(sgo2)
plotsigo2all(gsig10, gsig10phot, go2, 'o2vsig10spec', nbin)
#plotsigo2(gsig5phot,-1*go2,'o2vsig5phot',nbin)
plotsigsff(gsig5, gsf, 'sffvsig5spec', nbin) #sf frac versus sigma
plotsigsff(gsig5phot, gsf, 'sffvsig5phot', nbin) #sf frac versus sigma
plotsigsffall(gsig5, gsig5phot, gsf, 'sffvsig5all',
nbin) #sf frac versus sigma
plotsig10sffall(gsig10, gsig10phot, gsf, 'sffvsig10all',
nbin) #sf frac versus sigma
#plotsighaall(gsig10,gsig10phot,gha,'havsig10spec',20)
#plotsigo2all(sgsig10,sgsig10phot,sgo2,'o2vsig10spec.large',30)
plotsighaall(sgsig10, sgsig10phot, sgha, 'havsig10spec.large', 10)
#plotsigsffall(sgsig5,sgsig5phot,sgsf,'sffvsig5.large',nbin)#sf frac versus sigma
#plotsig10sffall(sgsig10,sgsig10phot,sgsf,'sffvsig10.large',nbin)#sf frac versus sigma
psplotinit('one2one.ps')
ppgplot.pgenv(-1.5, 2.5, -1.5, 2.5, 0)
ppgplot.pglab("\gS\d10\u(phot) (gal/Mpc\u2\d)",
"\gS\d10\u(spec) (gal/Mpc\u2\d)", "")
x = N.arange(-5., 10., .1)
y = x
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgline(x, y)
x = N.log10(gsig10phot)
y = N.log10(gsig10)
ppgplot.pgsch(.7)
ppgplot.pgpt(x, y, 17)
ppgplot.pgsch(1.)
ppgplot.pgsci(1)
ppgplot.pgend()
def setmask(command, data, cdata):
"""
Sets the mask on a dset and dumps a file containing the mask which can be applied
to other dsets using 'appmask'. This is an interactive routine which will request
input from the user and is better not used in batch processing. Repeated calls of
this routine can be used to build complex masks. The masks are always applied in
the original order so that you can mask then partially unmask for example. Note that
whatever slot you choose to define the mask will always end up masked; if you don't
want this you may want to make a copy.
Interactive usage:
setmask slot mfile append [device reset x1 x2 y1 y2] mask type
Arguments:
slot -- an example slot to plot.
mfile -- mask file
append -- append to an old mask file if possible
device -- plot device, e.g. '/xs'
reset -- rest plot limits or not
x1 -- left X plot limit
x2 -- right X plot limit
y1 -- bottom Y plot limit
y2 -- top Y plot limit
mask -- mask 'M', or unmask 'U' or quit 'Q'.
type -- type of mask: 'X' masks using ranges in X
Mask types:
X -- mask a range in X
Y -- mask a range in Y
I -- mask a range of pixel indices
P -- mask in 'phase', i.e. a range that repeats periodically.
"""
import trm.dnl.mask as mask
# generate arguments
inpt = inp.Input(DINT_ENV, DINT_DEF, inp.clist(command))
# register parameters
inpt.register('slot', inp.Input.LOCAL, inp.Input.PROMPT)
inpt.register('mfile', inp.Input.GLOBAL, inp.Input.PROMPT)
inpt.register('append', inp.Input.LOCAL, inp.Input.PROMPT)
inpt.register('device', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('reset', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('x1', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('x2', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('y1', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('y2', inp.Input.LOCAL, inp.Input.HIDE)
inpt.register('mask', inp.Input.LOCAL, inp.Input.PROMPT)
inpt.register('type', inp.Input.LOCAL, inp.Input.PROMPT)
# get inputs
slots = inpt.get_value('slot', 'slot to plot for mask definition', '1')
slist = interp_slots(slots, True, data, nfind=1)
dset = data[slist[0]]
device = inpt.get_value('device', 'plot device', '/xs')
# mask file
mfile = inpt.get_value('mfile', 'mask file to save results to', subs.Fname('mask','.msk', subs.Fname.NEW))
append = inpt.get_value('append', 'add to an old mask file if possible', True)
if append and mfile.exists():
mptr = open(mfile,'rb')
gmask = pickle.load(mptr)
gmask.app_mask(dset)
mptr.close()
else:
gmask = mask.Gmask()
# other parameters
reset = inpt.get_value('reset', 'reset plot limits automatically?', True)
# compute default limits
(x1,x2,y1,y2) = dset.plimits()
if (x2 - x1) < (x1+x2)/2./100.:
xoff = x1
x1 = 0.
x2 -= xoff
else:
xoff = 0.
yoff = 0.
if reset:
inpt.set_default('x1', x1)
inpt.set_default('x2', x2)
inpt.set_default('y1', y1)
inpt.set_default('y2', y2)
x1 = inpt.get_value('x1', 'left-hand limit of plot', x1)
x2 = inpt.get_value('x2', 'right-hand limit of plot', x2)
y1 = inpt.get_value('y1', 'bottom limit of plot', y1)
y2 = inpt.get_value('y2', 'top limit of plot', y2)
m_or_u = inpt.get_value('mask', 'M(ask), U(nmask) or Q(uit)?', 'm', lvals=['m', 'M', 'u', 'U', 'q', 'Q'])
if m_or_u.upper() == 'M':
mtext = 'mask'
else:
mtext = 'unmask'
mask_type = inpt.get_value('type', 'X, Y, P(hase), I(ndex) or Q(uit)?', 'x',
lvals=['x', 'X', 'y', 'Y', 'p', 'P', 'i', 'I', 'q', 'Q'])
# initialise plot
try:
pg.pgopen(device)
pg.pgsch(1.5)
pg.pgscf(2)
pg.pgslw(2)
pg.pgsci(4)
pg.pgenv(x1,x2,y1,y2,0,0)
(xlabel,ylabel) = dset.plabel(xoff,yoff)
pg.pgsci(2)
pg.pglab(xlabel, ylabel, dset.title)
# plot the dset
dset.plot(xoff,yoff)
x = (x1+x2)/2.
y = (y1+y2)/2.
# now define masks
ch = 'X'
while ch.upper() != 'Q':
# go through mask options
if mask_type.upper() == 'X':
print('Set cursor at the one end of the X range, Q to quit')
(xm1,y,ch) = pg.pgband(7,0,x,y)
if ch.upper() != 'Q':
print('Set cursor at the other end of ' +
'the X range, Q to quit')
xm2,y,ch = pg.pgband(7,0,xm1,y)
if ch.upper() != 'Q':
if xm1 > xm2: xm1,xm2 = xm2,xm1
umask = mask.Xmask(xoff+xm1, xoff+xm2, m_or_u.upper() == 'M')
elif mask_type.upper() == 'I':
print('Place cursor near a point and click to ' +
mtext + ' it, Q to quit')
x,y,ch = pg.pgband(7,0,x,y)
if ch.upper() != 'Q':
xmm1,xmm2,ymm1,ymm2 = pg.pgqvp(2)
xscale = (xmm2-xmm1)/(x2-x1)
yscale = (ymm2-ymm1)/(y2-y1)
# only consider good data of opposite 'polarity' to the
# change we are making.
ok = (dset.good == True) & \
(dset.mask == (m_or_u.upper() == 'M'))
if len(dset.x.dat[ok == True]):
# compute physical squared distance of cursor from
# points
sqdist = npy.power(
xscale*(dset.x.dat[ok]-(xoff+x)),2) + \
npy.power(yscale*(dset.y.dat[ok]-(yoff+y)),2)
# select the index giving the minimum distance
indices = npy.arange(len(dset))[ok]
index = indices[sqdist.min() == sqdist][0]
umask = mask.Imask(index, m_or_u.upper() == 'M')
else:
print('There seem to be no data to ' + mtext +
'; data already ' + mtext + 'ed are ignored.')
umask = None
if ch.upper() != 'Q' and umask is not None:
gmask.append(umask)
umask.app_mask(dset)
print('overplotting data')
# over-plot the dset
dset.plot(xoff,yoff)
pg.pgclos()
except pg.ioerror, err:
raise DintError(str(err))
def plotxy(y, x=None, title=None, rangex=None, rangey=None, \
labx='', laby='', rangex2=None, rangey2=None, \
labx2='', laby2='', symbol=ppgplot_symbol_, \
line=ppgplot_linestyle_, width=ppgplot_linewidth_, \
color=ppgplot_color_, font=ppgplot_font_, logx=0, logy=0, \
logx2=0, logy2=0, errx=None, erry=None, id=0, noscale=0, \
aspect=0.7727, fontsize=ppgplot_font_size_, ticks='in', \
panels=[1,1], device=ppgplot_device_, setup=1):
"""
plotxy(y, ...)
An interface to make various XY style plots using PGPLOT.
'y' is the 1D sequence object to plot.
The optional entries are:
x: x values (default = 0, 1, ...)
title: graph title (default = None)
rangex: ranges for the x-axis (default = automatic)
rangey: ranges for the y-axis (default = automatic)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: ranges for 2nd x-axis (default = None)
rangey2: ranges for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
errx: symmetric x errors (default = None)
erry: symmetric y errors (default = None)
symbol: symbol for points (default = None)
line: line style (default = 1 (solid))
width: line width (default = 1 (thin))
color: line and/or symbol color (default = 'white')
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: show ID line on plot (default = 0 (no))
noscale: turn off auto scaling (default = 0 (no))
aspect: aspect ratio (default = 0.7727 (rect))
ticks: Ticks point in or out (default = 'in')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
setup: Auto-setup the plot (default = 1)
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
# Make sure the input data is an array
y = Num.asarray(y)
# Announce the global variables we will be using
global ppgplot_dev_open_, ppgplot_dev_prep_, ppgplot_colors_
# Define the X axis limits if needed
if x is None: x = Num.arange(len(y), dtype='f')
else: x = Num.asarray(x)
# Determine the scaling to use for the first axis
if rangex is None: rangex = [x.min(), x.max()]
if rangey is None:
if noscale: rangey = [y.min(), y.max()]
else: rangey = scalerange(y)
# Prep the plotting device...
if (not ppgplot_dev_prep_ and setup):
prepplot(rangex, rangey, title, labx, laby, \
rangex2, rangey2, labx2, laby2, \
logx, logy, logx2, logy2, font, fontsize, \
id, aspect, ticks, panels, device=device)
# Choose the line color
if type(color) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[color])
else:
ppgplot.pgsci(color)
# Plot symbols (and errors) if requested
if not symbol is None:
ppgplot.pgpt(x, y, symbol)
# Error bars
if errx is not None:
if not logx:
errx = Num.asarray(errx)
ppgplot.pgerrx(x + errx, x - errx, y, 1.0)
else:
errx = 10.0**Num.asarray(errx)
ppgplot.pgerrx(Num.log10(10.0**x + errx),
Num.log10(10.0**x - errx), y, 1.0)
if erry is not None:
if not logy:
erry = Num.asarray(erry)
ppgplot.pgerry(x, y + erry, y - erry, 1.0)
else:
erry = 10.0**Num.asarray(erry)
ppgplot.pgerry(x, Num.log10(10.0**y + erry),
Num.log10(10.0**y - erry), 1.0)
# Plot connecting lines if requested
if not line is None:
# Choose the line style
ppgplot.pgsls(line)
# Choose the line width
ppgplot.pgslw(width)
ppgplot.pgline(x, y)
def plot2d(z, x=None, y=None, title=None, rangex=None, rangey=None, \
rangez=None, labx='', laby='', rangex2=None, rangey2=None, \
labx2='', laby2='', image=ppgplot_palette_, contours=None, \
logx=0, logy=0, logx2=0, logy2=0, \
line=ppgplot_linestyle_, width=ppgplot_linewidth_, \
color=ppgplot_color_, labels=ppgplot_labels_, \
labelint=ppgplot_labelint_, labelmin=ppgplot_labelmin_, \
font=ppgplot_font_, id=0, noscale=0, aspect=1, \
fontsize=ppgplot_font_size_, ticks='out', panels=[1,1], \
device=ppgplot_device_):
"""
plot2d(z, ...)
An interface to make various 2D plots using PGPLOT.
'z' is the 2D Numpy array to be plotted.
The optional entries are:
x: x values (default = 0, 1, ...)
y: y values (default = 0, 1, ...)
title: graph title (default = None)
rangex: range for the x-axis (default = automatic)
rangey: range for the y-axis (default = automatic)
rangez: range for the z-axis (default = automatic)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: range for 2nd x-axis (default = None)
rangey2: range for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
image: color palette for image (default = 'rainbow')
contours: list of contour values (default = None)
line: contour line style (default = 1 (solid))
width: contour line width (default = 1 (thin))
color: contour line color (default = 'white')
labels: color of contour labels (default = None)
labelint: contour label spacing (default = 20)
labelmin: min contour label spacing (default = 20)
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: show ID line on plot (default = 0 (no))
noscale: turn off auto scaling (default = 0 (no))
aspect: Aspect ratio (default = 1 (square))
ticks: Ticks point in or out (default = 'out')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
# Make sure the input data is a 2D array
z = Num.asarray(z)
if not len(z.shape) == 2:
print 'Input data array must be 2 dimensional.'
return
# Announce the global variables we will be using
global ppgplot_dev_open_, ppgplot_dev_prep_, pgpalette
# Define the X and Y axis limits if needed
if x is None: x = Num.arange(z.shape[1], dtype='f')
else: x = Num.asarray(x)
if y is None: y = Num.arange(z.shape[0], dtype='f')
else: y = Num.asarray(y)
# Determine the scaling to use for the axes
if rangex is None:
dx = x[-1] - x[-2]
rangex = [x[0], x[-1] + dx]
if rangey is None:
dy = y[-1] - y[-2]
rangey = [y[0], y[-1] + dy]
if rangez is None: rangez=[Num.minimum.reduce(Num.ravel(z)), \
Num.maximum.reduce(Num.ravel(z))]
# Prep the plotting device...
if (not ppgplot_dev_prep_):
prepplot(rangex, rangey, title, labx, laby, \
rangex2, rangey2, labx2, laby2, logx, logy, \
logx2, logy2, font, fontsize, id, aspect, \
ticks, panels, device=device)
if image is not None:
# Set the color indices and the color table
lo_col_ind, hi_col_ind = ppgplot.pgqcol()
lo_col_ind = lo_col_ind + 2
ppgplot.pgscir(lo_col_ind, hi_col_ind)
pgpalette.setpalette(image)
ppgplot.pgctab(pgpalette.l, pgpalette.r, pgpalette.g, pgpalette.b)
# Construct the image
ppgplot.pgimag_s(z, 0.0, 0.0, rangex[0], rangey[0], \
rangex[1], rangey[1])
reset_colors()
if contours is not None:
contours = Num.asarray(contours)
# Choose the line style
ppgplot.pgsls(line)
# Choose the line width
ppgplot.pgslw(width)
# Choose the line color for the contourlines
if type(color) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[color])
else:
ppgplot.pgsci(color)
# Construct the contours
ppgplot.pgcont_s(z, len(contours), contours, rangex[0], \
rangey[0], rangex[1], rangey[1])
# Label the contours if requested
if labels is not None:
# Choose the line color for the contourlines
if type(labels) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[labels])
else:
ppgplot.pgsci(labels)
for i in range(len(contours)):
ppgplot.pgconl_s(z, contours[i], str(contours[i]), labelint,
labelmin)
else:
l, b = w.wcs_pix2world([[x, y]], 1)[0]
return l, b
if __name__ == "__main__":
# Load stars
s = Stars()
# Load the master class
m = Skymap()
# Initialize plot
ppgplot.pgopen("/xs")
ppgplot.pgslw(2)
ppgplot.pgpap(0.0, 0.75)
# For ever loop
redraw = True
while True:
# Redraw
if redraw == True:
# Update
m.update()
# Initialize window
ppgplot.pgscr(0, 0., 0., 0.)
ppgplot.pgeras()
ppgplot.pgsvp(0.01, 0.99, 0.01, 0.99)
ppgplot.pgwnad(-1.5 * m.w, 1.5 * m.w, -m.w, m.w)
def prepplot(rangex, rangey, title=None, labx=None, laby=None, \
rangex2=None, rangey2=None, labx2=None, laby2=None, \
logx=0, logy=0, logx2=0, logy2=0, font=ppgplot_font_, \
fontsize=ppgplot_font_size_, id=0, aspect=1, ticks='in', \
panels=[1,1], device=ppgplot_device_):
"""
prepplot(rangex, rangey, ...)
Open a PGPLOT device for plotting.
'rangex' and 'rangey' are sequence objects giving min and
max values for each axis.
The optional entries are:
title: graph title (default = None)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: ranges for 2nd x-axis (default = None)
rangey2: ranges for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: Show ID line on plot (default = 0 (no))
aspect: Aspect ratio (default = 1 (square))
ticks: Ticks point in or out (default = 'in')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
global ppgplot_dev_open_, ppgplot_dev_prep_
# Check if we will use second X or Y axes
# Note: if using a 2nd X axis, the range should correspond
# to the minimum and maximum values of the 1st X axis. If
# using a 2nd Y axis, the range should correspond to the
# scalerange() values of the 1st Y axis.
if rangex2 is None:
rangex2 = rangex
otherxaxis = 0
else:
otherxaxis = 1
if rangey2 is None:
rangey2 = rangey
otheryaxis = 0
else:
otheryaxis = 1
# Open the plot device
if (not ppgplot_dev_open_):
ppgplot.pgopen(device)
# Let the routines know that we already have a device open
ppgplot_dev_open_ = 1
# Set the aspect ratio
ppgplot.pgpap(0.0, aspect)
if (panels != [1, 1]):
# Set the number of panels
ppgplot.pgsubp(panels[0], panels[1])
ppgplot.pgpage()
# Choose the font
ppgplot.pgscf(font)
# Choose the font size
ppgplot.pgsch(fontsize)
# Choose the font size
ppgplot.pgslw(ppgplot_linewidth_)
# Plot the 2nd axis if needed first
if otherxaxis or otheryaxis:
ppgplot.pgvstd()
ppgplot.pgswin(rangex2[0], rangex2[1], rangey2[0], rangey2[1])
# Decide how the axes will be drawn
if ticks == 'in': env = "CMST"
else: env = "CMSTI"
if logx2: lxenv = 'L'
else: lxenv = ''
if logy2: lyenv = 'L'
else: lyenv = ''
if otherxaxis and otheryaxis:
ppgplot.pgbox(env + lxenv, 0.0, 0, env + lyenv, 0.0, 0)
elif otheryaxis:
ppgplot.pgbox("", 0.0, 0, env + lyenv, 0.0, 0)
else:
ppgplot.pgbox(env + lxenv, 0.0, 0, "", 0.0, 0)
# Now setup the primary axis
ppgplot.pgvstd()
ppgplot.pgswin(rangex[0], rangex[1], rangey[0], rangey[1])
# Decide how the axes will be drawn
if ticks == 'in': env = "ST"
else: env = "STI"
if logx: lxenv = 'L'
else: lxenv = ''
if logy: lyenv = 'L'
else: lyenv = ''
if otherxaxis and otheryaxis:
ppgplot.pgbox("BN" + env + lxenv, 0.0, 0, "BN" + env + lyenv, 0.0, 0)
elif otheryaxis:
ppgplot.pgbox("BCN" + env + lxenv, 0.0, 0, "BN" + env + lyenv, 0.0, 0)
elif otherxaxis:
ppgplot.pgbox("BN" + env + lxenv, 0.0, 0, "BCN" + env + lyenv, 0.0, 0)
else:
ppgplot.pgbox("BCN" + env + lxenv, 0.0, 0, "BCN" + env + lyenv, 0.0, 0)
# Add labels
if not title is None: ppgplot.pgmtxt("T", 3.2, 0.5, 0.5, title)
ppgplot.pgmtxt("B", 3.0, 0.5, 0.5, labx)
ppgplot.pgmtxt("L", 2.6, 0.5, 0.5, laby)
if otherxaxis: ppgplot.pgmtxt("T", 2.0, 0.5, 0.5, labx2)
if otheryaxis: ppgplot.pgmtxt("R", 3.0, 0.5, 0.5, laby2)
# Add ID line if required
if (id == 1): ppgplot.pgiden()
# Let the routines know that we have already prepped the device
ppgplot_dev_prep_ = 1
def plot_rating_sheet(rating):
"""
Plot a fact sheet on the ratings in the database corresponding to 'rating'.
'rating' is a dictionary of information from the MySQL database (as returned
by 'get_all_rating_types()'.
"""
plot_utils.beginplot("rating_report%s.ps" % currdatetime.strftime('%y%m%d'), vertical=True)
ch0 = ppgplot.pgqch()
ppgplot.pgsch(0.5)
ch = ppgplot.pgqch()
ppgplot.pgsch(0.75)
ppgplot.pgtext(0,1,"Rating Report for %s (%s) - page 1 of 2" % (rating["name"], currdatetime.strftime('%c')))
ppgplot.pgsch(ch)
# Plot Histograms
all_ratings = get_ratings(rating["rating_id"])
range = xmin,xmax = np.min(all_ratings), np.max(all_ratings)
ppgplot.pgsci(1)
ppgplot.pgslw(1)
#===== Total/Classified/Unclassified
# Get data
ppgplot.pgsvp(0.1, 0.9, 0.75, 0.9)
(tot_counts, tot_left_edges)=np.histogram(all_ratings, bins=NUMBINS, range=range)
ppgplot.pgswin(xmin,xmax,0,np.max(tot_counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgbin(tot_left_edges, tot_counts)
(clsfd_counts, clsfd_left_edges)=np.histogram(get_ratings(rating["rating_id"], human_classification=(1,2,3,4,5,6,7)), bins=NUMBINS, range=range)
ppgplot.pgsci(3) # plot classified in green
ppgplot.pgbin(tot_left_edges, clsfd_counts)
unclsfd_counts = tot_counts-clsfd_counts
ppgplot.pgsci(2) # plot unclassified in red
ppgplot.pgbin(tot_left_edges, unclsfd_counts)
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","Counts","")
#===== Class 1/2/3
ppgplot.pgsvp(0.1, 0.9, 0.6, 0.75)
(counts, left_edges)=np.histogram(get_ratings(rating["rating_id"], human_classification=(1,2,3)), bins=NUMBINS, range=range)
ppgplot.pgswin(xmin,xmax,0,np.max(counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgsci(1) # plot in black
ppgplot.pgbin(tot_left_edges, counts)
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","Class 1/2/3","")
#===== RFI
ppgplot.pgsvp(0.1, 0.9, 0.45, 0.6)
rfi_ratings = get_ratings(rating["rating_id"], human_classification=(4,))
(counts, left_edges)=np.histogram(rfi_ratings, bins=NUMBINS, range=range)
ppgplot.pgswin(xmin,xmax,0,np.max(counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgsci(1) # plot in black
ppgplot.pgbin(tot_left_edges, counts)
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","RFI","")
#===== Noise
ppgplot.pgsvp(0.1, 0.9, 0.3, 0.45)
noise_ratings = get_ratings(rating["rating_id"], human_classification=(5,))
(counts, left_edges)=np.histogram(noise_ratings, bins=NUMBINS, range=range)
ppgplot.pgswin(xmin,xmax,0,np.max(counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgsci(1) # plot in black
ppgplot.pgbin(tot_left_edges, counts)
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","Noise","")
#===== Known/Harmonic
ppgplot.pgsvp(0.1, 0.9, 0.15, 0.3)
known_ratings = get_ratings(rating["rating_id"], human_classification=(6,7))
(counts, left_edges)=np.histogram(known_ratings, bins=NUMBINS, range=range)
ppgplot.pgswin(xmin,xmax,0,np.max(counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCNTS",0,5,"BCNTS",0,5)
ppgplot.pgsci(1) # plot in black
ppgplot.pgbin(tot_left_edges, counts)
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab(rating["name"],"Known/Harmonic","")
#===== Second page for differential histograms
plot_utils.nextpage(vertical=True)
ppgplot.pgsch(0.75)
ppgplot.pgtext(0,1,"Rating Report for %s (%s) - page 2 of 2" % (rating["name"], currdatetime.strftime('%c')))
#===== RFI - Known
ppgplot.pgsvp(0.1, 0.9, 0.75, 0.9)
if rfi_ratings.size==0 or known_ratings.size==0:
ppgplot.pgswin(0,1,0,1)
ppgplot.pgbox("BC",0,0,"BC",0,0)
ppgplot.pgsch(0.75)
ppgplot.pglab("","RFI - Known","")
ppgplot.pgsch(1.0)
ppgplot.pgptxt(0.5, 0.5, 0.0, 0.5, "Not enough data")
else:
(known_counts, known_left_edges)=np.histogram(known_ratings, bins=NUMBINS, range=range, normed=True)
(rfi_counts, rfi_left_edges)=np.histogram(rfi_ratings, bins=NUMBINS, range=range, normed=True)
diff_counts = rfi_counts - known_counts
ppgplot.pgswin(xmin,xmax,np.min(diff_counts)*1.1,np.max(diff_counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgbin(tot_left_edges, diff_counts)
ppgplot.pgsci(2) # set colour to red
ppgplot.pgline(tot_left_edges, np.zeros_like(tot_left_edges))
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","RFI - Known","")
#===== RFI - Noise
ppgplot.pgsvp(0.1, 0.9, 0.6, 0.75)
if noise_ratings.size==0 or rfi_ratings.size==0:
ppgplot.pgswin(0,1,0,1)
ppgplot.pgbox("BC",0,0,"BC",0,0)
ppgplot.pgsch(0.75)
ppgplot.pglab("","RFI - Noise","")
ppgplot.pgsch(1.0)
ppgplot.pgptxt(0.5, 0.5, 0.0, 0.5, "Not enough data")
else:
(noise_counts, noise_left_edges)=np.histogram(noise_ratings, bins=NUMBINS, range=range, normed=True)
(rfi_counts, rfi_left_edges)=np.histogram(rfi_ratings, bins=NUMBINS, range=range, normed=True)
diff_counts = rfi_counts - noise_counts
ppgplot.pgswin(xmin,xmax,np.min(diff_counts)*1.1,np.max(diff_counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCTS",0,5,"BCNTS",0,5)
ppgplot.pgbin(tot_left_edges, diff_counts)
ppgplot.pgsci(2) # set colour to red
ppgplot.pgline(tot_left_edges, np.zeros_like(tot_left_edges))
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgsch(0.75)
ppgplot.pglab("","RFI - Noise","")
#===== Known - Noise
ppgplot.pgsvp(0.1, 0.9, 0.45, 0.6)
if noise_ratings.size==0 or known_ratings.size==0:
ppgplot.pgswin(0,1,0,1)
ppgplot.pgbox("BC",0,0,"BC",0,0)
# Y-axis label is taken care of outside of if/else (below)
ppgplot.pgsch(1.0)
ppgplot.pgptxt(0.5, 0.5, 0.0, 0.5, "Not enough data")
else:
(noise_counts, noise_left_edges)=np.histogram(noise_ratings, bins=NUMBINS, range=range, normed=True)
(known_counts, known_left_edges)=np.histogram(known_ratings, bins=NUMBINS, range=range, normed=True)
diff_counts = known_counts - noise_counts
ppgplot.pgswin(xmin,xmax,np.min(diff_counts)*1.1,np.max(diff_counts)*1.1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("BCNTS",0,5,"BCNTS",0,5)
ppgplot.pgbin(tot_left_edges, diff_counts)
ppgplot.pgsci(2) # set colour to red
ppgplot.pgline(tot_left_edges, np.zeros_like(tot_left_edges))
ppgplot.pgsci(1) # reset colour to black
ppgplot.pgswin(xmin,xmax,0,1)
ppgplot.pgsch(0.5)
ppgplot.pgbox("NTS",0,5,"",0,0)
ppgplot.pgsch(0.75)
ppgplot.pglab(rating["name"],"Known - Noise","")
ppgplot.pgsch(ch0) # reset character height
def plothistsfr():
DATAMIN = -4.
DATAMAX = 15.
NBIN = int((DATAMAX-DATAMIN)*2.)
#print "ngal = ",len(g0.sfr)
ppgplot.pgbox("",0.0,0,"L",0.0,0)
ppgplot.pgenv(DATAMIN,DATAMAX,0,45,0)
ppgplot.pglab("SFR (h\d100\u\u-2\d M\d\(2281)\u yr\u-1 \d)","Number of Galaxies","")
ppgplot.pgsls(1)#dotted
ppgplot.pgslw(4) #line width
#ppgplot.pgsci(4)
#x=N.compress((abs(g0.ew) > ewmin),g0.sfr)
x=N.compress((g0.final > 0),g0.sfrc)
ppgplot.pghist(len(x),x,DATAMIN,DATAMAX,NBIN,5)
xlabel = 6.5
ylabel = 38.
ystep = 3.
dy=.4
dxl=3
dxr=.5
ppgplot.pgslw(deflw) #line width
ppgplot.pgtext(xlabel,ylabel,"CL1040")
xlin = N.array([xlabel-dxl,xlabel-dxr],'f')
ylin = N.array([ylabel+dy,ylabel+dy],'f')
ppgplot.pgslw(4) #line width
ppgplot.pgline(xlin,ylin)
ppgplot.pgslw(5)
ppgplot.pgsls(3)#dot-dash-dot-dash
#ppgplot.pgsci(3)
#x=N.compress((abs(g1.ew) > ewmin),g1.sfr)
x=N.compress((g1.final > 0),g1.sfrc)
ppgplot.pghist(len(x),x,DATAMIN,DATAMAX,NBIN,5)
ylabel = ylabel - ystep
xlin = N.array([xlabel-dxl,xlabel-dxr],'f')
ylin = N.array([ylabel+dy,ylabel+dy],'f')
ppgplot.pgline(xlin,ylin)
ppgplot.pgsls(1)
ppgplot.pgslw(deflw)
ppgplot.pgtext(xlabel,ylabel,"CL1054-12")
ppgplot.pgsls(1)#dot-dash-dot-dash
#ppgplot.pgsci(2)
ppgplot.pgslw(2) #line width
#x=N.compress((abs(g2.ew) > ewmin),g2.sfr)
x=N.compress((g2.final > 0),g2.sfrc)
ppgplot.pghist(len(x),x,DATAMIN,DATAMAX,NBIN,5)
ylabel = ylabel - ystep
ppgplot.pgslw(deflw) #line width
ppgplot.pgtext(xlabel,ylabel,"CL1216")
xlin = N.array([xlabel-dxl,xlabel-dxr],'f')
ylin = N.array([ylabel+dy,ylabel+dy],'f')
ppgplot.pgslw(2) #line width
ppgplot.pgline(xlin,ylin)
#print "Number in g2.ratios = ",len(g2.ratio)
#for ratio in g2.ratio:
# print ratio
#drawbinned(x,y,5)
ppgplot.pgsci(1)
ppgplot.pgline(fdotcut, zs)
ppgplot.pgmtxt("B", 2.4, 0.5, 0.5, "Relative Power");
# f-fdot image
ppgplot.pgsvp(margin, margin+imfract, margin, margin+imfract)
ppgplot.pgswin(min(rs), max(rs), min(zs), max(zs))
ppgplot.pgmtxt("B", 2.4, 0.5, 0.5, labx);
ppgplot.pgmtxt("L", 2.0, 0.5, 0.5, laby);
lo_col_ind, hi_col_ind = ppgplot.pgqcol()
lo_col_ind = lo_col_ind + 2
ppgplot.pgscir(lo_col_ind, hi_col_ind)
pgpalette.setpalette(image)
ppgplot.pgctab(pgpalette.l, pgpalette.r, pgpalette.g, pgpalette.b)
ppgplot.pgimag_s(pffdot, 0.0, 0.0, rgx[0], rgy[0], rgx[1], rgy[1])
ppgplot.pgsci(1)
ppgplot.pgcont_s(pffdot, len(contours), contours, rgx[0], rgy[0], rgx[1], rgy[1])
ppgplot.pgbox("BCST", 0.0, 0, "BCST", 0.0, 0)
ppgplot.pgsci(1)
ppgplot.pgbox("N", 0.0, 0, "N", 0.0, 0)
# gray axes
ppgplot.pgscr(1, 0.5, 0.5, 0.5)
ppgplot.pgsci(1)
ppgplot.pgslw(2)
ppgplot.pgline(rgx, num.asarray([0.0, 0.0]))
ppgplot.pgline(num.asarray([0.0, 0.0]), rgy)
ppgplot.pgclos()
ppgplot.pgpap(10, 0.618) ppgplot.pgask(arg.ask) for index, photometry in enumerate(allData): x_values = photometry[xColumn] y_values = photometry[yColumn] y_errors = photometry[yErrors] x_lower, x_upper = (min(x_values), max(x_values)) numpoints = len(x_values) if "JD" in xColumn: x_offset = int(x_lower) x_values = [(x-x_offset) for x in x_values] xLabel= xColumn + " - %d"%x_lower ppgplot.pgsci(1) ppgplot.pgenv(min(x_values), max(x_values), lowerY, upperY, 0, 0) ppgplot.pgslw(7) ppgplot.pgpt(x_values, y_values, 1) ppgplot.pgslw(1) ppgplot.pgerrb(2, x_values, y_values, y_errors, 0) ppgplot.pgerrb(4, x_values, y_values, y_errors, 0) ppgplot.pglab(xLabel, yLabel, photometry["runName"]) ppgplot.pgclos() if not hasEphemeris: sys.exit() # Restrict the light-curve to a subset of phase phaseLimits = (0.51, 0.70) for photometry in allData: pnew = []
# Plot A (Airmass-Time)
########################
# PS OUTPUT
###############################################################
filename=sys.argv[1]
psfile = str(filename)+".ps" # print ("psfile\n")
ppgplot.pgbegin(0,"psfile/VCPS", 1, 1)
# pgbegin(0,"psfile/PS", 1, 1)
# Plot Setting
####################################################################
ppgplot.pgpaper(8,1.25) # window/paper size (width(inch), aspect)
ppgplot.pgscf(2) # characte font (1: normal, 2: roman, 3: italic, 4: script)
ppgplot.pgslw(3) # line width
ppgplot.pgsvp(0.15, 0.9, 0.53, 0.89) # viewport in the window (relative)
ppgplot.pglab("", "", "Local Time [hour]")
ppgplot.pgsvp(0.12, 0.9, 0.53, 0.88) # viewport in the window (relative)
ppgplot.pglabel("", "Airmass", "") # label settingoto s
ppgplot.pgsch(1.0) # character height (size)
ppgplot.pgslw(3) # line width
ppgplot.pgsvp(0.15, 0.9, 0.53, 0.88) # viewport in the window (relative)
ppgplot.pgswin(t_min, t_max, a_max, a_min) # MIN,MAX of coordinate
ppgplot.pgbox('BCTS', 0.0, 0, 'BCTSNV1', 0.1, 0) # coordinate settings
ppgplot.pgbox('0', 0.0, 0, 'BCTSMV1', 0.1, 0) # coordinate settings
# Put Header/ Axes Label
#####################################################################
def plotxy(y, x=None, title=None, rangex=None, rangey=None, \
labx='', laby='', rangex2=None, rangey2=None, \
labx2='', laby2='', symbol=ppgplot_symbol_, \
line=ppgplot_linestyle_, width=ppgplot_linewidth_, \
color=ppgplot_color_, font=ppgplot_font_, logx=0, logy=0, \
logx2=0, logy2=0, errx=None, erry=None, id=0, noscale=0, \
aspect=0.7727, fontsize=ppgplot_font_size_, ticks='in', \
panels=[1,1], device=ppgplot_device_, setup=1):
"""
plotxy(y, ...)
An interface to make various XY style plots using PGPLOT.
'y' is the 1D sequence object to plot.
The optional entries are:
x: x values (default = 0, 1, ...)
title: graph title (default = None)
rangex: ranges for the x-axis (default = automatic)
rangey: ranges for the y-axis (default = automatic)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: ranges for 2nd x-axis (default = None)
rangey2: ranges for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
errx: symmetric x errors (default = None)
erry: symmetric y errors (default = None)
symbol: symbol for points (default = None)
line: line style (default = 1 (solid))
width: line width (default = 1 (thin))
color: line and/or symbol color (default = 'white')
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: show ID line on plot (default = 0 (no))
noscale: turn off auto scaling (default = 0 (no))
aspect: aspect ratio (default = 0.7727 (rect))
ticks: Ticks point in or out (default = 'in')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
setup: Auto-setup the plot (default = 1)
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
# Make sure the input data is an array
y = Num.asarray(y);
# Announce the global variables we will be using
global ppgplot_dev_open_, ppgplot_dev_prep_, ppgplot_colors_
# Define the X axis limits if needed
if x is None: x=Num.arange(len(y), dtype='f')
else: x = Num.asarray(x)
# Determine the scaling to use for the first axis
if rangex is None: rangex=[x.min(), x.max()]
if rangey is None:
if noscale: rangey=[y.min(), y.max()]
else: rangey=scalerange(y)
# Prep the plotting device...
if (not ppgplot_dev_prep_ and setup):
prepplot(rangex, rangey, title, labx, laby, \
rangex2, rangey2, labx2, laby2, \
logx, logy, logx2, logy2, font, fontsize, \
id, aspect, ticks, panels, device=device)
# Choose the line color
if type(color) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[color])
else:
ppgplot.pgsci(color)
# Plot symbols (and errors) if requested
if not symbol is None:
ppgplot.pgpt(x, y, symbol)
# Error bars
if errx is not None:
if not logx:
errx = Num.asarray(errx)
if errx.size == 1:
errx = errx.repeat(x.size)
#ppgplot.pgerrx(x+errx, x-errx, y, 1.0)
ppgplot.pgerrb(5, x, y, errx, 1.0)
else:
errx = 10.0**Num.asarray(errx)
if errx.size == 1:
errx = errx.repeat(x.size)
#ppgplot.pgerrx(Num.log10(10.0**x + errx),
# Num.log10(10.0**x - errx), y, 1.0)
ppgplot.pgerrb(5, x, y, Num.log10(errx), 1.0)
if erry is not None:
if not logy:
erry = Num.asarray(erry)
if erry.size == 1:
erry = erry.repeat(y.size)
#ppgplot.pgerry(x, y+erry, y-erry, 1.0)
ppgplot.pgerrb(6, x, y, erry, 1.0)
else:
erry = 10.0**Num.asarray(erry)
if erry.size == 1:
erry = erry.repeat(y.size)
#ppgplot.pgerry(x, Num.log10(10.0**y + erry),
# Num.log10(10.0**y - erry), 1.0)
ppgplot.pgerrb(6, x, y, Num.log10(erry), 1.0)
# Plot connecting lines if requested
if not line is None:
# Choose the line style
ppgplot.pgsls(line)
# Choose the line width
ppgplot.pgslw(width)
ppgplot.pgline(x, y)
def mratiopg():
ppgplot.pgbeg("maccratio.ps/vcps",1,1) #color port.
ppgplot.pgpap(8.,1.)
ppgplot.pgpage
ppgplot.pgsch(1.3) #font size
ppgplot.pgslw(7) #line width
# 1st panel with symbols w/ stddev errorbars
#ylabel="SFR (M\d\(2281) \u yr\u-1\d)"
ylabel="L(H\ga) (10\u41\d erg s\u-1\d)"
xlabel="M\dr\u "
x1=.15
x2=.5
x3=.5
x4=.85
y1=x1
y2=x2
y3=x3
y4=x4
emarker=18
smarker=23
xmin=N.log10(1.e14)
xmax=N.log10(2.5e15)
#ymin=-1.
#ymax=3.
ymin=0.
ymax=25.
ppgplot.pgsvp(x1,x4,y1,y4) #sets viewport
ppgplot.pgswin(xmin,xmax,ymin,ymax) #axes limits
ppgplot.pgbox('blncst',1.,2,'bcvnst',2.,2) #tickmarks and labeling
for i in range(len(lz1lm.mass)):
m=lz1lm.mass[i]
l=lz1lm.maccret[i]
h=hz1lm.maccret[i]
r=h/l
print i,m,l,h,r
#print lz1lm.maccret
#print hz1lm.maccret
#print hz3lm.maccret
r3lm=(hz3lm.maccret)/(lz3lm.maccret)
r3hm=(hz3hm.maccret)/(lz3hm.maccret)
#for i in range(len(r3)):
# print i,lz3.sigma[i],hz3.sigma[i],lz3.mass[i],hz3.mass[i]
# print i,lz01.sigma[i],hz01.sigma[i],lz01.mass[i],hz01.mass[i]
r1lm=hz1lm.maccret/lz1lm.maccret
r1hm=hz1hm.maccret/lz1hm.maccret
#ra=N.array(hz01.maccret,'d')
#rb=N.array(lz01.maccret,'d')
#r01=ra/rb
#for i in range(len(r01)):
#print "ratio ",hz01.maccret[i],lz01.maccret[i],ra[i],rb[i],r01[i]
ppgplot.pgsci(14)
ppgplot.pgsls(1)
ppgplot.pgline(N.log10(lz3lm.mass),r3lm)
ppgplot.pgsls(2)
ppgplot.pgline(N.log10(lz3hm.mass),r3hm)
ppgplot.pgsci(1)
ppgplot.pgsls(1)
ppgplot.pgline(N.log10(lz1lm.mass),r1lm)
ppgplot.pgsls(2)
ppgplot.pgline(N.log10(lz1hm.mass),r1hm)
xlabel='M\dcl\u (M\d\(2281)\u)'
ylabel='M\dacc\u(z=0.75) / M\dacc\u(z=0.07)'
ppgplot.pgsch(1.8)
ppgplot.pgslw(7)
ppgplot.pgmtxt('b',2.2,0.5,0.5,ylabel) #xlabel
ppgplot.pgmtxt('l',2.5,0.5,0.5,xlabel)
ppgplot.pgend()
def prepplot(rangex, rangey, title=None, labx=None, laby=None, \
rangex2=None, rangey2=None, labx2=None, laby2=None, \
logx=0, logy=0, logx2=0, logy2=0, font=ppgplot_font_, \
fontsize=ppgplot_font_size_, id=0, aspect=1, ticks='in', \
panels=[1,1], device=ppgplot_device_):
"""
prepplot(rangex, rangey, ...)
Open a PGPLOT device for plotting.
'rangex' and 'rangey' are sequence objects giving min and
max values for each axis.
The optional entries are:
title: graph title (default = None)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: ranges for 2nd x-axis (default = None)
rangey2: ranges for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: Show ID line on plot (default = 0 (no))
aspect: Aspect ratio (default = 1 (square))
ticks: Ticks point in or out (default = 'in')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
global ppgplot_dev_open_, ppgplot_dev_prep_
# Check if we will use second X or Y axes
# Note: if using a 2nd X axis, the range should correspond
# to the minimum and maximum values of the 1st X axis. If
# using a 2nd Y axis, the range should correspond to the
# scalerange() values of the 1st Y axis.
if rangex2 is None:
rangex2=rangex
otherxaxis=0
else: otherxaxis=1
if rangey2 is None:
rangey2=rangey
otheryaxis=0
else: otheryaxis=1
# Open the plot device
if (not ppgplot_dev_open_):
ppgplot.pgopen(device)
# My little add-on to switch the background to white
if device == '/XWIN':
reset_colors()
if device == '/AQT':
ppgplot.pgsci(0)
# Let the routines know that we already have a device open
ppgplot_dev_open_ = 1
# Set the aspect ratio
ppgplot.pgpap(0.0, aspect)
if (panels != [1,1]):
# Set the number of panels
ppgplot.pgsubp(panels[0], panels[1])
ppgplot.pgpage()
# Choose the font
ppgplot.pgscf(font)
# Choose the font size
ppgplot.pgsch(fontsize)
# Choose the font size
ppgplot.pgslw(ppgplot_linewidth_)
# Plot the 2nd axis if needed first
if otherxaxis or otheryaxis:
ppgplot.pgvstd()
ppgplot.pgswin(rangex2[0], rangex2[1], rangey2[0], rangey2[1])
# Decide how the axes will be drawn
if ticks=='in': env = "CMST"
else: env = "CMSTI"
if logx2: lxenv='L'
else: lxenv=''
if logy2: lyenv='L'
else: lyenv=''
if otherxaxis and otheryaxis:
ppgplot.pgbox(env+lxenv, 0.0, 0, env+lyenv, 0.0, 0)
elif otheryaxis:
ppgplot.pgbox("", 0.0, 0, env+lyenv, 0.0, 0)
else:
ppgplot.pgbox(env+lxenv, 0.0, 0, "", 0.0, 0)
# Now setup the primary axis
ppgplot.pgvstd()
ppgplot.pgswin(rangex[0], rangex[1], rangey[0], rangey[1])
# Decide how the axes will be drawn
if ticks=='in': env = "ST"
else: env = "STI"
if logx: lxenv='L'
else: lxenv=''
if logy: lyenv='L'
else: lyenv=''
if otherxaxis and otheryaxis:
ppgplot.pgbox("BN"+env+lxenv, 0.0, 0, "BN"+env+lyenv, 0.0, 0)
elif otheryaxis:
ppgplot.pgbox("BCN"+env+lxenv, 0.0, 0, "BN"+env+lyenv, 0.0, 0)
elif otherxaxis:
ppgplot.pgbox("BN"+env+lxenv, 0.0, 0, "BCN"+env+lyenv, 0.0, 0)
else:
ppgplot.pgbox("BCN"+env+lxenv, 0.0, 0, "BCN"+env+lyenv, 0.0, 0)
# My little add-on to switch the background to white
if device == '/AQT' or device == '/XWIN':
reset_colors()
# Add labels
if not title is None: ppgplot.pgmtxt("T", 3.2, 0.5, 0.5, title)
ppgplot.pgmtxt("B", 3.0, 0.5, 0.5, labx)
ppgplot.pgmtxt("L", 2.6, 0.5, 0.5, laby)
if otherxaxis: ppgplot.pgmtxt("T", 2.0, 0.5, 0.5, labx2)
if otheryaxis: ppgplot.pgmtxt("R", 3.0, 0.5, 0.5, laby2)
# Add ID line if required
if (id==1): ppgplot.pgiden()
# Let the routines know that we have already prepped the device
ppgplot_dev_prep_ = 1
def psplotinit(output):
file=output+"/vcps"
ppgplot.pgbeg(file,1,1)
ppgplot.pgpap(8.,1.)
ppgplot.pgsch(1.7) #font size
ppgplot.pgslw(7) #line width
def plot2d(z, x=None, y=None, title=None, rangex=None, rangey=None, \
rangez=None, labx='', laby='', rangex2=None, rangey2=None, \
labx2='', laby2='', image=ppgplot_palette_, contours=None, \
logx=0, logy=0, logx2=0, logy2=0, \
line=ppgplot_linestyle_, width=ppgplot_linewidth_, \
color=ppgplot_color_, labels=ppgplot_labels_, \
labelint=ppgplot_labelint_, labelmin=ppgplot_labelmin_, \
font=ppgplot_font_, id=0, noscale=0, aspect=1, \
fontsize=ppgplot_font_size_, ticks='out', panels=[1,1], \
device=ppgplot_device_):
"""
plot2d(z, ...)
An interface to make various 2D plots using PGPLOT.
'z' is the 2D Numpy array to be plotted.
The optional entries are:
x: x values (default = 0, 1, ...)
y: y values (default = 0, 1, ...)
title: graph title (default = None)
rangex: range for the x-axis (default = automatic)
rangey: range for the y-axis (default = automatic)
rangez: range for the z-axis (default = automatic)
labx: label for the x-axis (default = None)
laby: label for the y-axis (default = None)
rangex2: range for 2nd x-axis (default = None)
rangey2: range for 2nd y-axis (default = None)
labx2: label for the 2nd x-axis (default = None)
laby2: label for the 2nd y-axis (default = None)
logx: make the 1st x-axis log (default = 0 (no))
logy: make the 1st y-axis log (default = 0 (no))
logx2: make the 2nd x-axis log (default = 0 (no))
logy2: make the 2nd y-axis log (default = 0 (no))
image: color palette for image (default = 'rainbow')
contours: list of contour values (default = None)
line: contour line style (default = 1 (solid))
width: contour line width (default = 1 (thin))
color: contour line color (default = 'white')
labels: color of contour labels (default = None)
labelint: contour label spacing (default = 20)
labelmin: min contour label spacing (default = 20)
font: PGPLOT font to use (default = 1 (normal))
fontsize: PGPLOT font size to use (default = 1.0 (normal))
id: show ID line on plot (default = 0 (no))
noscale: turn off auto scaling (default = 0 (no))
aspect: Aspect ratio (default = 1 (square))
ticks: Ticks point in or out (default = 'out')
panels: Number of subpanels [r,c] (default = [1,1])
device: PGPLOT device to use (default = '/XWIN')
Note: Many default values are defined in global variables
with names like ppgplot_font_ or ppgplot_device_.
"""
# Make sure the input data is a 2D array
z = Num.asarray(z);
if not len(z.shape)==2:
print 'Input data array must be 2 dimensional.'
return
# Announce the global variables we will be using
global ppgplot_dev_open_, ppgplot_dev_prep_, pgpalette
# Define the X and Y axis limits if needed
if x is None: x=Num.arange(z.shape[1], dtype='f')
else: x = Num.asarray(x)
if y is None: y=Num.arange(z.shape[0], dtype='f')
else: y = Num.asarray(y)
# Determine the scaling to use for the axes
if rangex is None: rangex=[Num.minimum.reduce(x), \
Num.maximum.reduce(x)]
if rangey is None: rangey=[Num.minimum.reduce(y), \
Num.maximum.reduce(y)]
if rangez is None: rangez=[Num.minimum.reduce(Num.ravel(z)), \
Num.maximum.reduce(Num.ravel(z))]
# Prep the plotting device...
if (not ppgplot_dev_prep_):
prepplot(rangex, rangey, title, labx, laby, \
rangex2, rangey2, labx2, laby2, logx, logy, \
logx2, logy2, font, fontsize, id, aspect, \
ticks, panels, device=device)
if image is not None:
# Set the color indices and the color table
lo_col_ind, hi_col_ind = ppgplot.pgqcol()
lo_col_ind = lo_col_ind + 2
ppgplot.pgscir(lo_col_ind, hi_col_ind)
pgpalette.setpalette(image)
ppgplot.pgctab(pgpalette.l,pgpalette.r,pgpalette.g,pgpalette.b)
# Construct the image
ppgplot.pgimag_s(z, 0.0, 0.0, rangex[0], rangey[0], \
rangex[1], rangey[1])
reset_colors()
if contours is not None:
contours = Num.asarray(contours)
# Choose the line style
ppgplot.pgsls(line)
# Choose the line width
ppgplot.pgslw(width)
# Choose the line color for the contourlines
if type(color) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[color])
else:
ppgplot.pgsci(color)
# Construct the contours
ppgplot.pgcont_s(z, len(contours), contours, rangex[0], \
rangey[0], rangex[1], rangey[1])
# Label the contours if requested
if labels is not None:
# Choose the line color for the contourlines
if type(labels) == types.StringType:
ppgplot.pgsci(ppgplot_colors_[labels])
else:
ppgplot.pgsci(labels)
for i in range(len(contours)):
ppgplot.pgconl_s(z, contours[i], str(contours[i]),
labelint, labelmin)
#os.system("sex j+n.fits,ncc105jalign3.fits \n")
os.system("sex ncc105jalign3.fits \n")
#os.system("sex c1054j2cna.fits \n")
im1 = Catalog()
im1.readcat()
#os.system("sex cnc105jalign2.fits,c1054j2cna.fits \n")
#os.system("sex j+n.fits,c1054j2cna.fits \n")
#os.system("sex c1054j2cna.fits,gediscsj.fits -MAG_ZEROPOINT 23.88\n")
#os.system("sex ncc105jalign3.fits,gediscsj.fits -MAG_ZEROPOINT 22.84\n")
os.system("sex ncc105jalign3.fits,ngdim20_mp.fits\n")
im2 = Catalog()
im2.readcat()
ppgplot.pgbeg("all.ps/vcps", 2, 2)
ppgplot.pgsch(2.) #font size
ppgplot.pgslw(4) #line width
xysimple(im1.magauto, im2.magauto, "magauto mask", "magauto")
ppgplot.pgpage
y = im1.magauto - im2.magauto
ave = N.average(y)
std = scipy.stats.std(y)
print "Ave diff in mag auto = ", ave, "+/-", std
xysimple(im1.magauto, y, "magauto mask", "magauto mask - magauto")
ppgplot.pgpage
y = im1.magiso - im2.magiso
ave = N.average(y)
std = scipy.stats.std(y)
print "Ave diff in iso mags = ", ave, "+/-", std
xysimple(im1.magiso, y, "magiso mask", "magiso mask - magiso")
ppgplot.pgpage