def plotCircles(objectTable, margins):
margins = checkMargins(margins)
ppgplot.pgsci(3)
ppgplot.pgsfs(2)
index = 0
print ("Margins:", margins)
for obj in objectTable:
ra = obj["ra"]
dec = obj["dec"]
c = obj["class"]
if ra > margins[1][0] and ra < margins[0][0] and dec < margins[0][1] and dec > margins[1][1]:
# print index, ra, dec, x, y, c
index += 1
colour = 1
if c == -9:
colour = 2 # Red = Saturated
if c == 1:
colour = 4 # Blue = Galaxy
if c == -3:
colour = 5 # Cyan = Probable Galaxy
if c == -1:
colour = 3 # Green = Star
if c == -2:
colour = 8 # Orange = Probable Star
if c == 0:
colour = 2 # Red = Noise
ppgplot.pgsci(colour)
ppgplot.pgcirc(obj["x"], obj["y"], 5 + (5 * obj["pStar"]))
return index + 1
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 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 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 plotCircles(objectTable, margins):
margins = checkMargins(margins)
ppgplot.pgsci(3)
ppgplot.pgsfs(2)
index = 0
print("Margins:", margins)
for obj in objectTable:
ra = obj['ra']
dec = obj['dec']
c = obj['class']
if ra > margins[1][0] and ra < margins[0][0] and dec < margins[0][
1] and dec > margins[1][1]:
# print index, ra, dec, x, y, c
index += 1
colour = 1
if c == -9: colour = 2 # Red = Saturated
if c == 1: colour = 4 # Blue = Galaxy
if c == -3: colour = 5 # Cyan = Probable Galaxy
if c == -1: colour = 3 # Green = Star
if c == -2: colour = 8 # Orange = Probable Star
if c == 0: colour = 2 # Red = Noise
ppgplot.pgsci(colour)
ppgplot.pgcirc(obj['x'], obj['y'], 5 + (5 * obj['pStar']))
return (index + 1)
xll = w.xll/w.xbin - xmin xsize = w.nx yll = w.yll/w.ybin - ymin ysize = w.ny fullFrame[yll:yll+ysize, xll:xll+xsize] = fullFrame[yll:yll+ysize, xll:xll+xsize] + boostedImage rows, cols = numpy.shape(fullFrame) # Draw the grayscale bitmap ppgplot.pggray(fullFrame, 0, cols-1 , 0, rows-1 , 0, 255, pgPlotTransform) # Draw the full reference aperture list ppgplot.pgsci(3) for s in sourceList.getSources(): (x, y) = s.abs_position ppgplot.pgcirc(x, y, 10) # ppgplot.pgslct(bitmapView) ppgplot.pgsci(2) for index, s in enumerate(referenceApertures.getSources()): window = allWindows[s.windowIndex] center = s.latestPosition if s.recentFail: print "Recent fail... will try a position at least 5 frames back" positions = s.positionLog if len(positions)>5: center = positions[-5]['position'] print "Using position:", center xcenterInt = int(center[0])
sra, sdec, m.az, m.alt, m.q, 3.0 * m.w, 2.0 * m.w)
text = text + "L: %d; O: %s; m < %.1f; C: %s; l: %.0f s" % (
m.level, m.orientation, m.maxmag, m.camera, m.length)
ppgplot.pgmtxt("B", 1.0, 0.0, 0.0, text)
ppgplot.pgsch(1.0)
# Plot stars
c = s.mag < m.maxmag
aa = s.p[c].transform_to(AltAz(location=m.loc, obstime=m.t))
mag = s.mag[c]
rad = (m.maxrad + (m.minrad - m.maxrad) * (mag - m.minmag) /
(m.maxmag - m.minmag)) * m.w / 90.0
rx, ry = forward(m.az, m.alt, aa.az.deg, aa.alt.deg)
for i in range(len(rad)):
ppgplot.pgsci(0)
ppgplot.pgcirc(rx[i], ry[i], 1.3 * rad[i])
ppgplot.pgsci(1)
ppgplot.pgcirc(rx[i], ry[i], rad[i])
# Plot grid
m.plot_horizontal_grid()
# Reset redraw
redraw = False
# Get cursor
x, y, char = ppgplot.pgcurs()
print(x, y, char)
# Quit
% (position[1], position[0], superMax, superMin, variance,
variance / numPixels))
ppgplot.pgslct(spPreview['pgplotHandle'])
boostedPreview = generalUtils.percentiles(superPixel, 20, 99)
ppgplot.pggray(boostedPreview, 0, superPixelSize - 1, 0,
superPixelSize - 1, 0, 255,
imagePlot['pgPlotTransform'])
ppgplot.pgsci(0)
ppgplot.pgsch(5)
ppgplot.pgtext(1, 2, "max: %d" % superMax)
ppgplot.pgslct(imagePlot['pgplotHandle'])
pointingObject = {'x': position[1], 'y': position[0]}
pointings.append(pointingObject)
ppgplot.pgsfs(2)
ppgplot.pgsci(5)
ppgplot.pgcirc(position[1], position[0], radius)
xpts = [
startX, startX, startX + superPixelSize,
startX + superPixelSize
]
ypts = [
startY, startY + superPixelSize, startY + superPixelSize,
startY
]
ppgplot.pgsfs(2)
ppgplot.pgsci(4)
ppgplot.pgpoly(xpts, ypts)
tempBitmap = numpy.zeros(numpy.shape(imageCopy))
tempBitmap = gridCircle(position[0], position[1], radius,
tempBitmap)
additionalMask = numpy.ma.make_mask(tempBitmap)
image = matplotlib.pyplot.imshow(boostedFullFrame, cmap='gray_r') for s in allSources: x, y = s[0], s[1] matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), 10, color='green', fill=False, linewidth=1.0)) if applyShift: for s in topSources: x, y = s[0], s[1] matplotlib.pyplot.gca().add_artist(matplotlib.pyplot.Circle((x,y), 10, color='blue', fill=False, linewidth=1.0)) rows, cols = numpy.shape(boostedFullFrame) ppgplot.pggray(boostedFullFrame, 0, cols-1, 0, rows-1, 0, 255, pgPlotTransform) ppgplot.pgsfs(2) # Set fill style to 'outline' ppgplot.pgsci(3) # Set the colour to 'green' for s in allSources: x, y = s[0], s[1] ppgplot.pgcirc(x,y, 10) """ End of the prework """ rdat.set(1) # Reset back to the first frame frameRange = maximumFrames - startFrame + 1 if arg.numframes!=None: requestedNumFrames = arg.numframes if requestedNumFrames<(frameRange): frameRange = requestedNumFrames startTime = datetime.datetime.now() timeLeftString = "??:??"
% (position[1], position[0], superMax, superMin, variance, variance / numPixels)
)
ppgplot.pgslct(spPreview["pgplotHandle"])
boostedPreview = generalUtils.percentiles(superPixel, 20, 99)
ppgplot.pggray(
boostedPreview, 0, superPixelSize - 1, 0, superPixelSize - 1, 0, 255, imagePlot["pgPlotTransform"]
)
ppgplot.pgsci(0)
ppgplot.pgsch(5)
ppgplot.pgtext(1, 2, "max: %d" % superMax)
ppgplot.pgslct(imagePlot["pgplotHandle"])
pointingObject = {"x": position[1], "y": position[0]}
pointings.append(pointingObject)
ppgplot.pgsfs(2)
ppgplot.pgsci(5)
ppgplot.pgcirc(position[1], position[0], radius)
xpts = [startX, startX, startX + superPixelSize, startX + superPixelSize]
ypts = [startY, startY + superPixelSize, startY + superPixelSize, startY]
ppgplot.pgsfs(2)
ppgplot.pgsci(4)
ppgplot.pgpoly(xpts, ypts)
tempBitmap = numpy.zeros(numpy.shape(imageCopy))
tempBitmap = gridCircle(position[0], position[1], radius, tempBitmap)
additionalMask = numpy.ma.make_mask(tempBitmap)
booleanMask = numpy.ma.mask_or(booleanMask, additionalMask)
maskedImageCopy = numpy.ma.masked_array(imageCopy, booleanMask)
print "Number of masked elements", numpy.ma.count_masked(maskedImageCopy)
print "Number of non-masked elements", numpy.ma.count(maskedImageCopy)
# imageCopy = numpy.ma.filled(maskedImageCopy, 0)
# time.sleep(1)
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()