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 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 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 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 plot_horizontal_grid(self):
sch, sls, sci = ppgplot.pgqch(), ppgplot.pgqls(), ppgplot.pgqci()
ppgplot.pgsci(15)
ppgplot.pgsls(2)
# Altitudes
for alt in np.arange(0.0, 90.0, 20.0):
az = np.arange(0.0, 360.0)
rx, ry = forward(self.az, self.alt, az, alt * np.ones_like(az))
for i in range(len(rx)):
if i == 0:
ppgplot.pgmove(rx[i], ry[i])
if (np.abs(rx[i]) <= 1.5 * self.w) & (np.abs(ry[i]) <= self.w):
ppgplot.pgdraw(rx[i], ry[i])
else:
ppgplot.pgmove(rx[i], ry[i])
# Azimuths
for az in np.arange(0.0, 360.0, 30.0):
alt = np.arange(0.0, 80.0)
rx, ry = forward(self.az, self.alt, az * np.ones_like(alt), alt)
for i in range(len(rx)):
if i == 0:
ppgplot.pgmove(rx[i], ry[i])
if (np.abs(rx[i]) <= 1.5 * self.w) & (np.abs(ry[i]) <= self.w):
ppgplot.pgdraw(rx[i], ry[i])
else:
ppgplot.pgmove(rx[i], ry[i])
ppgplot.pgsci(1)
ppgplot.pgsls(1)
# Horizon
az = np.arange(0.0, 360.0)
rx, ry = forward(self.az, self.alt, az, np.zeros_like(az))
for i in range(len(rx)):
if i == 0:
ppgplot.pgmove(rx[i], ry[i])
if (np.abs(rx[i]) <= 1.5 * self.w) & (np.abs(ry[i]) <= self.w):
ppgplot.pgdraw(rx[i], ry[i])
else:
ppgplot.pgmove(rx[i], ry[i])
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 linelabel(xlabel, ylabel, dx, ystep, dxl, dyl, label): #draw key
schdef = ppgplot.pgqch()
ppgplot.pgsch(1.1)
ppgplot.pgtext(xlabel, ylabel, label)
ppgplot.pgsch(1.1)
ylabel = ylabel - 2. * ystep
xs = N.arange(xlabel, (xlabel + dx), .01)
ys = ylabel * N.ones(len(xs), 'd')
ppgplot.pgsls(1)
ppgplot.pgline(xs, ys)
ppgplot.pgtext((xlabel + dxl + dx), (ylabel - dyl), "Memb")
ylabel = ylabel - ystep
ys = ylabel * N.ones(len(xs), 'd')
ppgplot.pgsls(4)
ppgplot.pgline(xs, ys)
ppgplot.pgtext((xlabel + dxl + dx), (ylabel - dyl), "Contam")
ppgplot.pgsch(schdef)
ppgplot.pgsls(1)
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)
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)
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 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)
l_max=8
ppgplot.pgslw(3) # line width
ppgplot.pgslw(2) # line width
ppgplot.pgsch(1.0) # character height (size)
for (l=l_min l<=12 l+=1){
ppgplot.pgtext(-12.012+l*0.974,0.96,"l")
}
for (l=1 l<=l_max l+=1){
ppgplot.pgtext(-0.012+l*0.974,0.96,"l")
}
ppgplot.pgslw(1) # line width
ppgplot.pgsls(1) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgbox('G', 1.0, 0, '0', 0.1, 0) # coordinate settings
ppgplot.pgsls(1) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgslw(1) # line width
ppgplot.pgsls(4) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgbox('0', 1.0, 0, 'G', 0.1, 0) # coordinate settings
ppgplot.pgsls(1) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgslw(3) # line width
ppgplot.pgsls(1) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgbox('G', 8.0, 0, 'G', 0.5, 0) # coordinate settings
ppgplot.pgsls(1) # line sytle 1: --- 2: --- 3: .-. : 4 ... 5: -...
ppgplot.pgend
phaseArray = []
angleArray = []
# Plot theta as a function of orbital phase for these parameters
for phase in numpy.arange(0.5, 1.51, 0.01):
theta = computeViewingAngle(phase, inclination, beta, phi)
phaseArray.append(phase)
angleArray.append(theta)
mainPlotWindow = ppgplot.pgopen("/xs")
ppgplot.pgask(False)
pgPlotTransform = [0, 1, 0, 0, 0, 1]
ppgplot.pgsci(1)
ppgplot.pgenv(min(phaseArray), max(phaseArray), 0, 180, 0, 0)
ppgplot.pgline(phaseArray, angleArray)
ppgplot.pgsls(2)
ppgplot.pgline([0.5, 1.5], [90, 90])
ppgplot.pglab("orbital phase", "viewing angle",
"Viewing angle \gh as a function of orbital phase.")
ppgplot.pgtext(0.6, 150,
"i:%2.0f \gb:%2.0f \gf:%2.0f" % (inclination, beta, phi))
modelPlotWindow = ppgplot.pgopen("models_i_81_b_40.ps/ps")
pgPlotTransform = [0, 1, 0, 0, 0, 1]
ppgplot.pgask(False)
mainFluxMax = 0
mainFluxMin = 1E99
for phase in numpy.arange(0.5, 1.6, 0.1):
ppgplot.pgsci(1)
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()
#power = signal.lombscargle(x, y, ang_freqs)
# normalize the power
#N = len(x)
# power *= 2 / (N * y.std() ** 2)
ppgplot.pgenv(min(frequency), max(frequency), 0, max(power), 0, 0)
ppgplot.pgline(frequency, power)
#ppgplot.pgenv(min(periods), max(periods), 0, max(power), 0, 0)
#ppgplot.pgline(periods, power)
ppgplot.pglab("Frequency (d\u-1\d)", "Amplitude", "Lomb-Scargle: " + o.id)
bestFrequency = frequency[numpy.argmax(power)]
lc = ppgplot.pgqci()
ls = ppgplot.pgqls()
ppgplot.pgsci(3)
ppgplot.pgsls(2)
ppgplot.pgline([bestFrequency, bestFrequency], [0, max(power)])
ppgplot.pgsci(lc)
ppgplot.pgsls(ls)
print "Best frequency: %f cycles per day"%bestFrequency
bestPeriod = 1/bestFrequency
print "%s Best period: %f days or %f hours"%(o.id, bestPeriod, bestPeriod * 24.)
print o.ephemeris
o.ephemeris.Period = bestPeriod
matplotlib.pyplot.plot(frequency, power, linewidth=1.0, color='k', alpha=0.75)
matplotlib.pyplot.ylim([0, 1.2 * max(power)])
matplotlib.pyplot.plot([1/o.ephemeris.Period, 1/o.ephemeris.Period], [0, 1.2 * max(power)], linewidth=1.5, linestyle='--', color='r', alpha=1)
matplotlib.pyplot.plot([bestFrequency, bestFrequency], [0, 1.2 * max(power)], linewidth=1.5, linestyle='--', color='b', alpha=1)
matplotlib.pyplot.draw()
matplotlib.pyplot.show()
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)
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 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/.')
# Graph of the x-direction
ppgplot.pgsvp(0.1, 0.7, 0.1, 0.2)
yMax = numpy.max(xCollapsed) * 1.1
yMin = numpy.min(xCollapsed) * 0.9
ppgplot.pgswin(-margins, margins, yMin, yMax)
ppgplot.pgsci(1)
ppgplot.pgbox('ABI', 1.0, 10, 'ABI', 0.0, 0)
xPoints = [x - margins for x in range(len(xCollapsed))]
ppgplot.pgsci(2)
ppgplot.pgbin(xPoints, xCollapsed, True)
numPolyPoints = 50
xFit = [float(i) * len(xCollapsed)/numPolyPoints for i in range(numPolyPoints)]
yFit = [xPoly[0]*x*x + xPoly[1]*x + xPoly[2] for x in xFit]
ppgplot.pgsci(3)
ppgplot.pgline([x - margins for x in xFit], yFit)
ppgplot.pgsls(2)
ppgplot.pgline([newxPeak-margins, newxPeak-margins], [yMin, yMax])
ppgplot.pgsci(4)
ppgplot.pgline([xBestOffset, xBestOffset], [yMin, yMax])
ppgplot.pgsls(1)
ppgplot.pgline(xGaussian, xGaussianFit)
# Graph of the y-direction
ppgplot.pgsvp(0.8, 0.9, 0.3, 0.9)
yMax = numpy.max(yCollapsed) * 1.1
yMin = numpy.min(yCollapsed) * 0.9
ppgplot.pgswin(yMin, yMax, -margins, margins)
ppgplot.pgsci(1)
ppgplot.pgbox('ABI', 0.0, 0, 'ABI', 1.0, 10)
xPoints = [x - margins for x in range(len(yCollapsed))]
ppgplot.pgsci(2)
timeToNextStep = lightCurve.period - lightCurve.time[n]
else:
timeToNextStep = lightCurve.time[n+1] - lightCurve.time[n]
print n, lightCurve.time[n], lightCurve.brightness[n], timeToNextStep
ppgplot.pgeras()
ppgplot.pgsci(1)
ppgplot.pgenv(0., lightCurve.period, 0.0, 1.0, 0, 0)
ppgplot.pglab("seconds", "brightness", "Light curve")
ppgplot.pgpt(lightCurve.time, lightCurve.brightness, 2)
ppgplot.pgsci(2)
ppgplot.pgline(lightCurve.time, lightCurve.brightness)
ppgplot.pgsci(3)
ppgplot.pgpt([lightCurve.time[n]], [lightCurve.brightness[n]], 3)
currentLineStyle = ppgplot.pgqls()
ppgplot.pgsls(2)
ppgplot.pgline([lightCurve.time[n], lightCurve.time[n]], [ 0, 1])
ppgplot.pgsls(currentLineStyle)
params = {"brightness": str(lightCurve.brightness[n]), "duration": str(timeToNextStep)}
print "Sending params:", params
response = requests.put("https://api.lifx.com/v1beta1/lights/all/state", headers=headers, params=params)
# print response.text
time.sleep(timeToNextStep)
ppgplot.pgclos()
sys.exit()
