def resizeDev():
"""
Des: resize plot area after resizing window with mouse
ABB: resize
"""
__MessHand.info("resizing plot page")
ppgplot.pgpage()
def nextplotpage(reset=1):
"""
nextplotpage():
Advance the plotting device to a new page.
The optional entry is:
reset: reset defaults or not (default = 1 (yes))
"""
global ppgplot_dev_open_, ppgplot_dev_prep_
if (ppgplot_dev_open_):
ppgplot.pgpage()
ppgplot_dev_prep_ = 0
else:
print "Can't go to the next plot page unless a plotting device is open."
if (reset): resetdefaults()
def nextplotpage(reset=0):
"""
nextplotpage():
Advance the plotting device to a new page.
The optional entry is:
reset: reset defaults or not (default = 0 (no))
"""
global ppgplot_dev_open_, ppgplot_dev_prep_
if (ppgplot_dev_open_):
ppgplot.pgpage()
ppgplot_dev_prep_ = 0
else:
print "Can't go to the next plot page unless a plotting device is open."
if (reset): resetdefaults()
def nextpage(vertical=False):
"""
Start a new page in the currently opened device.
Default is to orient paper horizontally (landscape). If vertical
is True then the paper will be oriented vertically.
"""
# New page
if ppgplot.pgqid()!=0:
ppgplot.pgpage()
ppgplot.pgswin(0,1,0,1)
if vertical:
ppgplot.pgpap(7.9, 11.0/8.5)
else:
ppgplot.pgpap(10.25, 8.5/11.0)
ppgplot.pgiden()
else:
sys.stderr.write("Cannot start new page. No pgplot device open.\n")
raise "No open pgplot device"
def main(options):
debug = options.debug
MSlist = []
for inmspart in options.inms.split(','):
for msname in glob.iglob(inmspart):
MSlist.append(msname)
if len(MSlist) == 0:
print 'Error: You must specify at least one MS name.'
print ' Use "uvplot.py -h" to get help.'
return
if len(MSlist) > 1:
print 'WARNING: Antenna selection (other than all) may not work well'
print ' when plotting more than one MS. Carefully inspect the'
print ' listings of antenna numbers/names!'
device = options.device
if device=='?':
ppgplot.pgldev()
return
if options.title == '':
plottitle = options.inms
else:
plottitle = options.title
axlimits = options.axlimits.split(',')
if len(axlimits) == 4:
xmin,xmax,ymin,ymax = axlimits
else:
print 'Error: You must specify four axis limits'
return
timeslots = options.timeslots.split(',')
if len(timeslots) != 3:
print 'Error: Timeslots format is start,skip,end'
return
for i in range(len(timeslots)):
timeslots[i] = int(timeslots[i])
if timeslots[i] < 0:
print 'Error: timeslots values must not be negative'
return
antToPlotSpl = options.antennas.split(',')
antToPlot = []
for i in range(len(antToPlotSpl)):
tmpspl = antToPlotSpl[i].split('..')
if len(tmpspl) == 1:
antToPlot.append(int(antToPlotSpl[i]))
elif len(tmpspl) == 2:
for j in range(int(tmpspl[0]),int(tmpspl[1])+1):
antToPlot.append(j)
else:
print 'Error: Could not understand antenna list.'
return
queryMode = options.query
plotLambda = options.kilolambda
badval = 0.0
xaxisvals = numpy.array([])
yaxisvals = numpy.array([])
savex = numpy.array([])
savey = numpy.array([])
numPlotted = 0
for inputMS in MSlist:
# open the main table and print some info about the MS
print 'Getting info for', inputMS
t = pt.table(inputMS, readonly=True, ack=False)
tfreq = pt.table(t.getkeyword('SPECTRAL_WINDOW'),readonly=True,ack=False)
ref_freq = tfreq.getcol('REF_FREQUENCY',nrow=1)[0]
ch_freq = tfreq.getcol('CHAN_FREQ',nrow=1)[0]
print 'Reference frequency:\t%f MHz' % (ref_freq/1.e6)
if options.wideband:
ref_wavelength = 2.99792458e8/ch_freq
else:
ref_wavelength = [2.99792458e8/ref_freq]
print 'Reference wavelength:\t%f m' % (ref_wavelength[0])
if options.sameuv and numPlotted > 0:
print 'Assuming same uvw as first MS!'
if plotLambda:
for w in ref_wavelength:
xaxisvals = numpy.append(xaxisvals,[savex/w/1000.,-savex/w/1000.])
yaxisvals = numpy.append(yaxisvals,[savey/w/1000.,-savey/w/1000.])
else:
print 'Plotting more than one MS with same uv, all in meters... do you want -k?'
xaxisvals = numpy.append(xaxisvals,[savex,-savex])
yaxisvals = numpy.append(yaxisvals,[savey,-savey])
continue
firstTime = t.getcell("TIME", 0)
lastTime = t.getcell("TIME", t.nrows()-1)
intTime = t.getcell("INTERVAL", 0)
print 'Integration time:\t%f sec' % (intTime)
nTimeslots = (lastTime - firstTime) / intTime
print 'Number of timeslots:\t%d' % (nTimeslots)
if timeslots[1] == 0:
if nTimeslots >= 100:
timeskip = int(nTimeslots/100)
else:
timeskip = 1
else:
timeskip = int(timeslots[1])
print 'For each baseline, plotting one point every %d samples' % (timeskip)
if timeslots[2] == 0:
timeslots[2] = nTimeslots
# open the antenna subtable
tant = pt.table(t.getkeyword('ANTENNA'), readonly=True, ack=False)
# Station names
antList = tant.getcol('NAME')
if len(antToPlot)==1 and antToPlot[0]==-1:
antToPlot = range(len(antList))
print 'Station list (only starred stations will be plotted):'
for i in range(len(antList)):
star = ' '
if i in antToPlot: star = '*'
print '%s %2d\t%s' % (star, i, antList[i])
# Bail if we're in query mode
if queryMode:
return
# select by time from the beginning, and only use specified antennas
tsel = t.query('TIME >= %f AND TIME <= %f AND ANTENNA1 IN %s AND ANTENNA2 IN %s' % (firstTime+timeslots[0]*intTime,firstTime+timeslots[2]*intTime,str(antToPlot),str(antToPlot)), columns='ANTENNA1,ANTENNA2,UVW')
# Now we loop through the baselines
i = 0
nb = (len(antToPlot)*(len(antToPlot)-1))/2
sys.stdout.write('Reading uvw for %d baselines: %04d/%04d'%(nb,i,nb))
sys.stdout.flush()
for tpart in tsel.iter(["ANTENNA1","ANTENNA2"]):
ant1 = tpart.getcell("ANTENNA1", 0)
ant2 = tpart.getcell("ANTENNA2", 0)
if ant1 not in antToPlot or ant2 not in antToPlot: continue
if ant1 == ant2: continue
i += 1
sys.stdout.write('\b\b\b\b\b\b\b\b\b%04d/%04d'%(i,nb))
sys.stdout.flush()
# Get the values to plot
uvw = tpart.getcol('UVW', rowincr=timeskip)
if numPlotted == 0:
savex = numpy.append(savex,[uvw[:,0],-uvw[:,0]])
savey = numpy.append(savey,[uvw[:,1],-uvw[:,1]])
if plotLambda:
for w in ref_wavelength:
xaxisvals = numpy.append(xaxisvals,[uvw[:,0]/w/1000.,-uvw[:,0]/w/1000.])
yaxisvals = numpy.append(yaxisvals,[uvw[:,1]/w/1000.,-uvw[:,1]/w/1000.])
else:
xaxisvals = numpy.append(xaxisvals,[uvw[:,0],-uvw[:,0]])
yaxisvals = numpy.append(yaxisvals,[uvw[:,1],-uvw[:,1]])
#if debug:
# print uvw.shape
# print xaxisvals.shape
# print yaxisvals.shape
#else:
# sys.stdout.write('.')
# sys.stdout.flush()
sys.stdout.write(' Done!\n')
numPlotted += 1
print 'Plotting uv points ...'
# open the graphics device, using only one panel
ppgplot.pgbeg(device, 1, 1)
# set the font size
ppgplot.pgsch(1)
ppgplot.pgvstd()
# Plot the data
if debug:
print xaxisvals
xaxisvals = numpy.array(xaxisvals)
yaxisvals = numpy.array(yaxisvals)
tmpvals = numpy.sqrt(xaxisvals**2+yaxisvals**2)
ppgplot.pgsci(1)
uvmax = max(xaxisvals.max(),yaxisvals.max())
uvmin = min(xaxisvals.min(),yaxisvals.min())
uvuplim = 0.02*(uvmax-uvmin)+uvmax
uvlolim = uvmin-0.02*(uvmax-uvmin)
if xmin == '':
minx = uvlolim
else:
minx = float(xmin)
if xmax == '':
maxx = uvuplim
else:
maxx = float(xmax)
if ymin == '':
miny = uvlolim
else:
miny = float(ymin)
if ymax == '':
maxy = uvuplim
else:
maxy = float(ymax)
if minx == maxx:
minx = -1.0
maxx = 1.0
if miny == maxy:
miny = -1.0
maxy = 1.0
ppgplot.pgpage()
ppgplot.pgswin(minx,maxx,miny,maxy)
ppgplot.pgbox('BCNST',0.0,0,'BCNST',0.0,0)
if plotLambda:
ppgplot.pglab('u [k\gl]', 'v [k\gl]', '%s'%(plottitle))
else:
ppgplot.pglab('u [m]', 'v [m]', '%s'%(plottitle))
ppgplot.pgpt(xaxisvals[tmpvals!=badval], yaxisvals[tmpvals!=badval], 1)
# Close the PGPLOT device
ppgplot.pgclos()
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 main(options):
global keepPlotting
keepPlotting = True
debug = options.debug
inputMS = glob.glob(options.inms)
if inputMS == '':
print 'Error: You must specify a MS name.'
print ' Use "uvplot.py -h" to get help.'
return
if options.inms.endswith('/'):
options.inms = options.inms[:-1]
inputMSbasename = options.inms.split('/')[-1]
if inputMSbasename == '':
# The user has not specified the full path of the MS
inputMSbasename = options.inms
device = options.device
if device=='?':
ppgplot.pgldev()
return
xaxis = options.xaxis
if xaxis == 'ha':
print 'Adding derived columns to allow plotting hour angle...'
try:
pt.addDerivedMSCal(inputMS)
except:
print 'Failed, trying to remove and add columns...'
try:
pt.removeDerivedMSCal(inputMS)
pt.addDerivedMSCal(inputMS)
except:
print 'That failed too... plotting HA seems to not be possible.'
return
yaxis = options.yaxis
column = options.column
nx, ny = options.nxy.split(',')
axlimits = options.axlimits.split(',')
if len(axlimits) == 4:
xmin,xmax,ymin,ymax = axlimits
else:
print 'Error: You must specify four axis limits'
return
showFlags = options.flag
flagCol = options.colflag
showAutocorr = options.autocorr
showStats = options.statistics
timeslots = options.timeslots.split(',')
if len(timeslots) != 2:
print 'Error: Timeslots format is start,end'
return
for i in range(len(timeslots)): timeslots[i] = int(timeslots[i])
antToPlotSpl = options.antennas.split(',')
antToPlot = []
for i in range(len(antToPlotSpl)):
tmpspl = antToPlotSpl[i].split('..')
if len(tmpspl) == 1:
antToPlot.append(int(antToPlotSpl[i]))
elif len(tmpspl) == 2:
for j in range(int(tmpspl[0]),int(tmpspl[1])+1):
antToPlot.append(j)
else:
print 'Error: Could not understand antenna list.'
return
polarizations = options.polar.split(',')
for i in range(len(polarizations)):
polarizations[i] = int(polarizations[i])
convertStokes = options.stokes
operation = options.operation
if operation != '':
operation = int(operation)
if convertStokes:
print 'Error: Stokes conversion is not compatible with special operations'
return
channels = options.channels.split(',')
if len(channels) != 2:
print 'Error: Channels format is start,end'
return
for i in range(len(channels)): channels[i] = int(channels[i])
if channels[1] == -1:
channels[1] = None # last element even if there is only one
else:
channels[1] += 1
queryMode = options.query
doUnwrap = options.wrap
if not queryMode:
# open the graphics device, use the right number of panels
ppgplot.pgbeg(device, int(nx), int(ny))
# set the font size
ppgplot.pgsch(1.5)
ppgplot.pgvstd()
# open the main table and print some info about the MS
t = pt.table(inputMS, readonly=True, ack=False)
firstTime = t.query(sortlist='TIME',columns='TIME',limit=1).getcell("TIME", 0)
lastTime = t.query(sortlist='TIME',columns='TIME',offset=t.nrows()-1).getcell("TIME", 0)
intTime = t.getcell("INTERVAL", 0)
print 'Integration time:\t%f sec' % (intTime)
nTimeslots = (lastTime - firstTime) / intTime
if timeslots[1] == -1:
timeslots[1] = nTimeslots
else:
timeslots[1] += 1
print 'Number of timeslots:\t%d' % (nTimeslots)
# open the antenna and spectral window subtables
tant = pt.table(t.getkeyword('ANTENNA'), readonly=True, ack=False)
tsp = pt.table(t.getkeyword('SPECTRAL_WINDOW'), readonly=True, ack=False)
numChannels = len(tsp.getcell('CHAN_FREQ',0))
print 'Number of channels:\t%d' % (numChannels)
print 'Reference frequency:\t%5.2f MHz' % (tsp.getcell('REF_FREQUENCY',0)/1.e6)
# Station names
antList = tant.getcol('NAME')
if len(antToPlot)==1 and antToPlot[0]==-1:
antToPlot = range(len(antList))
print 'Station list (only starred stations will be plotted):'
for i in range(len(antList)):
star = ' '
if i in antToPlot: star = '*'
print '%s %2d\t%s' % (star, i, antList[i])
# Bail if we're in query mode
if queryMode:
return
# select by time from the beginning, and only use specified antennas
tsel = t.query('TIME >= %f AND TIME <= %f AND ANTENNA1 IN %s AND ANTENNA2 IN %s' % (firstTime+timeslots[0]*intTime,firstTime+timeslots[1]*intTime,str(antToPlot),str(antToPlot)))
# values to use for each polarization
plotColors = [1,2,3,4]
labXPositions = [0.35,0.45,0.55,0.65]
labYPositions = [1.0,1.0,1.0,1.0]
if convertStokes:
polLabels = ['I','Q','U','V']
else:
polLabels = ['XX','XY','YX','YY']
# define nicely written axis labels
axisLabels = {'time': 'Time',
'ha': 'Hour angle',
'chan': 'Channel',
'freq': 'Frequency [MHz]',
'amp': 'Visibility amplitude',
'real': 'Real part of visibility',
'imag': 'Imaginary part of visibility',
'phase': 'Visibility phase [radians]'}
# Now we loop through the baselines
ppgplot.pgpage()
for tpart in tsel.iter(["ANTENNA1","ANTENNA2"]):
if not keepPlotting: return
ant1 = tpart.getcell("ANTENNA1", 0)
ant2 = tpart.getcell("ANTENNA2", 0)
if ant1 not in antToPlot or ant2 not in antToPlot: continue
if ant1 == ant2:
if not showAutocorr:
continue
# Get the values to plot, strategy depends on axis type
if xaxis == 'time' or xaxis == 'ha':
xaxisvals = getXAxisVals(tpart, xaxis, channels)
yaxisvals = getYAxisVals(tpart, yaxis, column, operation, showFlags, flagCol, channels, doUnwrap, convertStokes)
else:
xaxisvals = getXAxisVals(tsp, xaxis, channels)
yaxisvals = getYAxisVals(tpart, yaxis, column, operation, showFlags, flagCol, channels, doUnwrap, convertStokes, xaxistype=1)
if xaxisvals == None: # This baseline must be empty, go to next one
print 'No good data on baseline %s - %s' % (antList[ant1],antList[ant2])
continue
if debug:
print xaxisvals.shape
print yaxisvals.shape
for r in range(len(xaxisvals)):
print '%s'%yaxisvals[r]
if len(xaxisvals) != len(yaxisvals): # something is wrong
print 'Error: X and Y axis types incompatible'
return
# Plot the data, each polarization in a different color
ppgplot.pgsci(1)
if xmin == '':
minx = xaxisvals.min()
else:
minx = float(xmin)
if xmax == '':
maxx = xaxisvals.max()
else:
maxx = float(xmax)
if ymin == '':
miny = yaxisvals.min()
if numpy.ma.getmaskarray(yaxisvals.min()):
print 'All data flagged on baseline %s - %s' % (antList[ant1],antList[ant2])
continue
else:
miny = float(ymin)
if ymax == '':
maxy = yaxisvals.max()
else:
maxy = float(ymax)
if minx == maxx:
minx -= 1.0
maxx += 1.0
else:
diffx = maxx - minx
minx -= 0.02*diffx
maxx += 0.02*diffx
if miny == maxy:
miny -= 1.0
maxy += 1.0
else:
diffy = maxy - miny
miny -= 0.02*diffy
maxy += 0.02*diffy
#ppgplot.pgpage()
ppgplot.pgswin(minx,maxx,miny,maxy)
if xaxis == 'time' or xaxis == 'ha':
ppgplot.pgtbox('ZHOBCNST',0.0,0,'BCNST',0.0,0)
else:
ppgplot.pgbox('BCNST',0.0,0,'BCNST',0.0,0)
#ppgplot.pglab(axisLabels[xaxis], axisLabels[yaxis], '%s - %s'%(antList[ant1],antList[ant2]))
#ppgplot.pgmtxt('T', 3.0, 0.5, 0.5, inputMSbasename)
ppgplot.pglab(axisLabels[xaxis], axisLabels[yaxis], inputMSbasename + '(' + getDataDescription(column) + '): %s - %s'%(antList[ant1],antList[ant2]))
if operation != 0:
# some operations is defined
if operation == 1:
label = 'XX-YY'
elif operation == 2:
label = 'XY.YX*'
else:
print 'Special operation not defined'
return
ppgplot.pgsci(plotColors[0])
tmpvals = yaxisvals
print 'Baseline',antList[ant1],'-',antList[ant2],': Plotting',len(tmpvals[~tmpvals.mask]),'points of ' + label
ppgplot.pgpt(xaxisvals[~tmpvals.mask], tmpvals[~tmpvals.mask], 1)
addInfo(showStats, tmpvals[~tmpvals.mask], label, labXPositions[1], labYPositions[1])
else:
for j in polarizations:
ppgplot.pgsci(plotColors[j])
tmpvals = yaxisvals[:,j]
if j == polarizations[0]:
print 'Baseline',antList[ant1],'-',antList[ant2],': Plotting',len(tmpvals[~tmpvals.mask]),'points per polarization'
ppgplot.pgpt(xaxisvals[~tmpvals.mask], tmpvals[~tmpvals.mask], 1)
addInfo(showStats, tmpvals[~tmpvals.mask], polLabels[j], labXPositions[j], labYPositions[j])
ppgplot.pgpage()
# Close the PGPLOT device
ppgplot.pgclos()
if xaxis=='ha':
print 'Removing derived columns...'
pt.removeDerivedMSCal(inputMS)
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 main(options):
global keepPlotting
keepPlotting = True
debug = options.debug
inputMS = options.inms
if inputMS == "":
print "Error: You must specify a MS name."
print ' Use "uvplot.py -h" to get help.'
return
if inputMS.endswith("/"):
inputMS = inputMS[:-1]
inputMSbasename = inputMS.split("/")[-1]
if inputMSbasename == "":
# The user has not specified the full path of the MS
inputMSbasename = inputMS
device = options.device
if device == "?":
ppgplot.pgldev()
return
xaxis = options.xaxis
yaxis = options.yaxis
column = options.column
nx, ny = options.nxy.split(",")
axlimits = options.axlimits.split(",")
if len(axlimits) == 4:
xmin, xmax, ymin, ymax = axlimits
else:
print "Error: You must specify four axis limits"
return
showFlags = options.flag
flagCol = options.colflag
showAutocorr = options.autocorr
showStats = options.statistics
timeslots = options.timeslots.split(",")
if len(timeslots) != 2:
print "Error: Timeslots format is start,end"
return
for i in range(len(timeslots)):
timeslots[i] = int(timeslots[i])
antToPlotSpl = options.antennas.split(",")
antToPlot = []
for i in range(len(antToPlotSpl)):
tmpspl = antToPlotSpl[i].split("..")
if len(tmpspl) == 1:
antToPlot.append(int(antToPlotSpl[i]))
elif len(tmpspl) == 2:
for j in range(int(tmpspl[0]), int(tmpspl[1]) + 1):
antToPlot.append(j)
else:
print "Error: Could not understand antenna list."
return
polarizations = options.polar.split(",")
for i in range(len(polarizations)):
polarizations[i] = int(polarizations[i])
convertStokes = options.stokes
operation = options.operation
if operation != "":
operation = int(operation)
if convertStokes:
print "Error: Stokes conversion is not compatible with special operations"
return
channels = options.channels.split(",")
if len(channels) != 2:
print "Error: Channels format is start,end"
return
for i in range(len(channels)):
channels[i] = int(channels[i])
if channels[1] == -1:
channels[1] = None # last element even if there is only one
else:
channels[1] += 1
queryMode = options.query
doUnwrap = options.wrap
if not queryMode:
# open the graphics device, use the right number of panels
ppgplot.pgbeg(device, int(nx), int(ny))
# set the font size
ppgplot.pgsch(1.5)
ppgplot.pgvstd()
# open the main table and print some info about the MS
t = pt.table(inputMS, readonly=True, ack=False)
firstTime = t.getcell("TIME", 0)
lastTime = t.getcell("TIME", t.nrows() - 1)
intTime = t.getcell("INTERVAL", 0)
print "Integration time:\t%f sec" % (intTime)
nTimeslots = (lastTime - firstTime) / intTime
if timeslots[1] == -1:
timeslots[1] = nTimeslots
else:
timeslots[1] += 1
print "Number of timeslots:\t%d" % (nTimeslots)
# open the antenna and spectral window subtables
tant = pt.table(t.getkeyword("ANTENNA"), readonly=True, ack=False)
tsp = pt.table(t.getkeyword("SPECTRAL_WINDOW"), readonly=True, ack=False)
numChannels = len(tsp.getcell("CHAN_FREQ", 0))
print "Number of channels:\t%d" % (numChannels)
print "Reference frequency:\t%5.2f MHz" % (tsp.getcell("REF_FREQUENCY", 0) / 1.0e6)
# Station names
antList = tant.getcol("NAME")
if len(antToPlot) == 1 and antToPlot[0] == -1:
antToPlot = range(len(antList))
print "Station list (only starred stations will be plotted):"
for i in range(len(antList)):
star = " "
if i in antToPlot:
star = "*"
print "%s %2d\t%s" % (star, i, antList[i])
# Bail if we're in query mode
if queryMode:
return
# select by time from the beginning, and only use specified antennas
tsel = t.query(
"TIME >= %f AND TIME <= %f AND ANTENNA1 IN %s AND ANTENNA2 IN %s"
% (firstTime + timeslots[0] * intTime, firstTime + timeslots[1] * intTime, str(antToPlot), str(antToPlot))
)
# values to use for each polarization
plotColors = [1, 2, 3, 4]
labXPositions = [0.35, 0.45, 0.55, 0.65]
labYPositions = [1.0, 1.0, 1.0, 1.0]
if convertStokes:
polLabels = ["I", "Q", "U", "V"]
else:
polLabels = ["XX", "XY", "YX", "YY"]
# define nicely written axis labels
axisLabels = {
"time": "Time",
"chan": "Channel",
"freq": "Frequency [MHz]",
"amp": "Visibility amplitude",
"real": "Real part of visibility",
"imag": "Imaginary part of visibility",
"phase": "Visibility phase [radians]",
}
# Now we loop through the baselines
ppgplot.pgpage()
for tpart in tsel.iter(["ANTENNA1", "ANTENNA2"]):
if not keepPlotting:
return
ant1 = tpart.getcell("ANTENNA1", 0)
ant2 = tpart.getcell("ANTENNA2", 0)
if ant1 not in antToPlot or ant2 not in antToPlot:
continue
if ant1 == ant2:
if not showAutocorr:
continue
# Get the values to plot, strategy depends on axis type
if xaxis == "time":
xaxisvals = getXAxisVals(tpart, xaxis, channels)
yaxisvals = getYAxisVals(
tpart, yaxis, column, operation, showFlags, flagCol, channels, doUnwrap, convertStokes
)
else:
xaxisvals = getXAxisVals(tsp, xaxis, channels)
yaxisvals = getYAxisVals(
tpart, yaxis, column, operation, showFlags, flagCol, channels, doUnwrap, convertStokes, xaxistype=1
)
if xaxisvals == None: # This baseline must be empty, go to next one
print "No good data on baseline %s - %s" % (antList[ant1], antList[ant2])
continue
if debug:
print xaxisvals.shape
print yaxisvals.shape
for r in range(len(xaxisvals)):
print "%s" % yaxisvals[r]
if len(xaxisvals) != len(yaxisvals): # something is wrong
print "Error: X and Y axis types incompatible"
return
# Plot the data, each polarization in a different color
ppgplot.pgsci(1)
if xmin == "":
minx = xaxisvals.min()
else:
minx = float(xmin)
if xmax == "":
maxx = xaxisvals.max()
else:
maxx = float(xmax)
if ymin == "":
miny = yaxisvals.min()
if numpy.ma.getmaskarray(yaxisvals.min()):
print "All data flagged on baseline %s - %s" % (antList[ant1], antList[ant2])
continue
else:
miny = float(ymin)
if ymax == "":
maxy = yaxisvals.max()
else:
maxy = float(ymax)
if minx == maxx:
minx -= 1.0
maxx += 1.0
else:
diffx = maxx - minx
minx -= 0.02 * diffx
maxx += 0.02 * diffx
if miny == maxy:
miny -= 1.0
maxy += 1.0
else:
diffy = maxy - miny
miny -= 0.02 * diffy
maxy += 0.02 * diffy
# ppgplot.pgpage()
ppgplot.pgswin(minx, maxx, miny, maxy)
if xaxis == "time":
ppgplot.pgtbox("ZHOBCNST", 0.0, 0, "BCNST", 0.0, 0)
else:
ppgplot.pgbox("BCNST", 0.0, 0, "BCNST", 0.0, 0)
# ppgplot.pglab(axisLabels[xaxis], axisLabels[yaxis], '%s - %s'%(antList[ant1],antList[ant2]))
# ppgplot.pgmtxt('T', 3.0, 0.5, 0.5, inputMSbasename)
ppgplot.pglab(
axisLabels[xaxis],
axisLabels[yaxis],
inputMSbasename + "(" + getDataDescription(column) + "): %s - %s" % (antList[ant1], antList[ant2]),
)
if operation != 0:
# some operations is defined
if operation == 1:
label = "XX-YY"
elif operation == 2:
label = "XY.YX*"
else:
print "Special operation not defined"
return
ppgplot.pgsci(plotColors[0])
tmpvals = yaxisvals
print "Baseline", antList[ant1], "-", antList[ant2], ": Plotting", len(
tmpvals[~tmpvals.mask]
), "points of " + label
ppgplot.pgpt(xaxisvals[~tmpvals.mask], tmpvals[~tmpvals.mask], 1)
addInfo(showStats, tmpvals[~tmpvals.mask], label, labXPositions[1], labYPositions[1])
else:
for j in polarizations:
ppgplot.pgsci(plotColors[j])
tmpvals = yaxisvals[:, j]
if j == polarizations[0]:
print "Baseline", antList[ant1], "-", antList[ant2], ": Plotting", len(
tmpvals[~tmpvals.mask]
), "points per polarization"
ppgplot.pgpt(xaxisvals[~tmpvals.mask], tmpvals[~tmpvals.mask], 1)
addInfo(showStats, tmpvals[~tmpvals.mask], polLabels[j], labXPositions[j], labYPositions[j])
ppgplot.pgpage()
# Close the PGPLOT device
ppgplot.pgclos()
freqcut = pffdot[np / 2, :]
fdotcut = pffdot[:, np / 2]
image = 'antirainbow'
device = 'ffdot_combined.eps/VCPS'
device = '/XWIN'
labx = 'Fourier Frequency Offset (bins)'
laby = 'Fourier Frequency Derivative (bins)'
contours = num.asarray([0.1, 0.3, 0.5, 0.7, 0.9])
imfract = 0.65
margin = 0.08
ppgplot.pgopen(device)
ppgplot.pgpap(0.0, 1.0)
ppgplot.pgpage()
# Give z and w values and power change
ppgplot.pgsvp(margin + imfract, 1.0 - margin / 2, margin + imfract,
1.0 - margin / 2)
ppgplot.pgswin(0.0, 1.0, 0.0, 1.0)
ppgplot.pgtext(0.1, 0.8, "Frac Recovered" % frp)
ppgplot.pgtext(0.2, 0.65, "Power = %.3f" % frp)
ppgplot.pgtext(0.1, 0.4, "signal z = %.1f" % z)
ppgplot.pgtext(0.1, 0.25, "signal w = %.1f" % w)
# freq cut
ppgplot.pgsvp(margin, margin + imfract, margin + imfract, 1.0 - margin / 2)
ppgplot.pgswin(min(rs), max(rs), -0.1, 1.1)
ppgplot.pgbox("BCST", 0.0, 0, "BCNST", 0.0, 0)
ppgplot.pgline(rs, freqcut)
def main(options):
debug = options.debug
MSlist = []
device = options.device
if device == '?':
ppgplot.pgldev()
return
for inmspart in options.inms.split(','):
for msname in glob.iglob(inmspart):
MSlist.append(msname)
if len(MSlist) == 0:
print('Error: You must specify at least one MS name.')
print(' Use "uvplot.py -h" to get help.')
return
if len(MSlist) > 1:
print('WARNING: Antenna selection (other than all) may not work well')
print(' when plotting more than one MS. Carefully inspect the')
print(' listings of antenna numbers/names!')
if options.title == '':
plottitle = options.inms
else:
plottitle = options.title
axlimits = options.axlimits.split(',')
if len(axlimits) == 4:
xmin, xmax, ymin, ymax = axlimits
else:
print('Error: You must specify four axis limits')
return
timeslots = options.timeslots.split(',')
if len(timeslots) != 3:
print('Error: Timeslots format is start,skip,end')
return
for i in range(len(timeslots)):
timeslots[i] = int(timeslots[i])
if timeslots[i] < 0:
print('Error: timeslots values must not be negative')
return
doPlotColors = options.colors
antToPlotSpl = options.antennas.split(',')
antToPlot = []
for i in range(len(antToPlotSpl)):
tmpspl = antToPlotSpl[i].split('..')
if len(tmpspl) == 1:
antToPlot.append(int(antToPlotSpl[i]))
elif len(tmpspl) == 2:
for j in range(int(tmpspl[0]), int(tmpspl[1]) + 1):
antToPlot.append(j)
else:
print('Error: Could not understand antenna list.')
return
queryMode = options.query
plotLambda = options.kilolambda
badval = 0.0
xaxisvals0 = numpy.array([])
yaxisvals0 = numpy.array([])
xaxisvals1 = numpy.array([])
yaxisvals1 = numpy.array([])
xaxisvals2 = numpy.array([])
yaxisvals2 = numpy.array([])
xaxisvals3 = numpy.array([])
yaxisvals3 = numpy.array([])
xaxisvals4 = numpy.array([])
yaxisvals4 = numpy.array([])
xaxisvals5 = numpy.array([])
yaxisvals5 = numpy.array([])
savex0 = numpy.array([])
savey0 = numpy.array([])
savex1 = numpy.array([])
savey1 = numpy.array([])
savex2 = numpy.array([])
savey2 = numpy.array([])
savex3 = numpy.array([])
savey3 = numpy.array([])
savex4 = numpy.array([])
savey4 = numpy.array([])
savex5 = numpy.array([])
savey5 = numpy.array([])
numPlotted = 0
ptcolor = 0
for inputMS in MSlist:
# open the main table and print some info about the MS
print('Getting info for', inputMS)
t = pt.table(inputMS, readonly=True, ack=False)
tfreq = pt.table(t.getkeyword('SPECTRAL_WINDOW'),
readonly=True,
ack=False)
ref_freq = tfreq.getcol('REF_FREQUENCY', nrow=1)[0]
ch_freq = tfreq.getcol('CHAN_FREQ', nrow=1)[0]
print('Reference frequency:\t%f MHz' % (ref_freq / 1.e6))
if options.wideband:
ref_wavelength = 2.99792458e8 / ch_freq
else:
ref_wavelength = [2.99792458e8 / ref_freq]
print('Reference wavelength:\t%f m' % (ref_wavelength[0]))
if options.sameuv and numPlotted > 0:
print('Assuming same uvw as first MS!')
if plotLambda:
for w in ref_wavelength:
xaxisvals0 = numpy.append(
xaxisvals0, [savex0 / w / 1000., -savex0 / w / 1000.])
yaxisvals0 = numpy.append(
yaxisvals0, [savey0 / w / 1000., -savey0 / w / 1000.])
xaxisvals1 = numpy.append(
xaxisvals1, [savex1 / w / 1000., -savex1 / w / 1000.])
yaxisvals1 = numpy.append(
yaxisvals1, [savey1 / w / 1000., -savey1 / w / 1000.])
xaxisvals2 = numpy.append(
xaxisvals2, [savex2 / w / 1000., -savex2 / w / 1000.])
yaxisvals2 = numpy.append(
yaxisvals2, [savey2 / w / 1000., -savey2 / w / 1000.])
xaxisvals3 = numpy.append(
xaxisvals3, [savex3 / w / 1000., -savex3 / w / 1000.])
yaxisvals3 = numpy.append(
yaxisvals3, [savey3 / w / 1000., -savey3 / w / 1000.])
xaxisvals4 = numpy.append(
xaxisvals4, [savex4 / w / 1000., -savex4 / w / 1000.])
yaxisvals4 = numpy.append(
yaxisvals4, [savey4 / w / 1000., -savey4 / w / 1000.])
xaxisvals5 = numpy.append(
xaxisvals5, [savex5 / w / 1000., -savex5 / w / 1000.])
yaxisvals5 = numpy.append(
yaxisvals5, [savey5 / w / 1000., -savey5 / w / 1000.])
else:
print(
'Plotting more than one MS with same uv, all in meters... do you want -k?'
)
xaxisvals0 = numpy.append(xaxisvals0, [savex0, -savex0])
yaxisvals0 = numpy.append(yaxisvals0, [savey0, -savey0])
xaxisvals1 = numpy.append(xaxisvals1, [savex1, -savex1])
yaxisvals1 = numpy.append(yaxisvals1, [savey1, -savey1])
xaxisvals2 = numpy.append(xaxisvals2, [savex2, -savex2])
yaxisvals2 = numpy.append(yaxisvals2, [savey2, -savey2])
xaxisvals3 = numpy.append(xaxisvals3, [savex3, -savex3])
yaxisvals3 = numpy.append(yaxisvals3, [savey3, -savey3])
xaxisvals4 = numpy.append(xaxisvals4, [savex4, -savex4])
yaxisvals4 = numpy.append(yaxisvals4, [savey4, -savey4])
xaxisvals5 = numpy.append(xaxisvals5, [savex5, -savex5])
yaxisvals5 = numpy.append(yaxisvals5, [savey5, -savey5])
continue
firstTime = t.getcell("TIME", 0)
lastTime = t.getcell("TIME", t.nrows() - 1)
intTime = t.getcell("INTERVAL", 0)
print('Integration time:\t%f sec' % (intTime))
nTimeslots = (lastTime - firstTime) / intTime
print('Number of timeslots:\t%d' % (nTimeslots))
if timeslots[1] == 0:
if nTimeslots >= 100:
timeskip = int(nTimeslots / 100)
else:
timeskip = 1
else:
timeskip = int(timeslots[1])
print('For each baseline, plotting one point every %d samples' %
(timeskip))
if timeslots[2] == 0:
timeslots[2] = nTimeslots
# open the antenna subtable
tant = pt.table(t.getkeyword('ANTENNA'), readonly=True, ack=False)
# Station names
antList = tant.getcol('NAME')
if len(antToPlot) == 1 and antToPlot[0] == -1:
antToPlot = list(range(len(antList)))
print('Station list (only starred stations will be plotted):')
for i in range(len(antList)):
star = ' '
if i in antToPlot: star = '*'
print('%s %2d\t%s' % (star, i, antList[i]))
# Bail if we're in query mode
if queryMode:
return
# select by time from the beginning, and only use specified antennas
tsel = t.query(
'TIME >= %f AND TIME <= %f AND ANTENNA1 IN %s AND ANTENNA2 IN %s' %
(firstTime + timeslots[0] * intTime, firstTime +
timeslots[2] * intTime, str(antToPlot), str(antToPlot)),
columns='ANTENNA1,ANTENNA2,UVW')
# Now we loop through the baselines
i = 0
nb = (len(antToPlot) * (len(antToPlot) - 1)) / 2
sys.stdout.write('Reading uvw for %d baselines: %04d/%04d' %
(nb, i, nb))
sys.stdout.flush()
for tpart in tsel.iter(["ANTENNA1", "ANTENNA2"]):
ant1 = tpart.getcell("ANTENNA1", 0)
ant2 = tpart.getcell("ANTENNA2", 0)
if ant1 not in antToPlot or ant2 not in antToPlot: continue
if ant1 == ant2: continue
i += 1
sys.stdout.write('\b\b\b\b\b\b\b\b\b%04d/%04d' % (i, nb))
sys.stdout.flush()
if doPlotColors:
stNameStr = antList[ant1][0] + antList[ant2][0]
if stNameStr == 'CC': ptcolor = 0
elif stNameStr == 'RR': ptcolor = 1
elif 'C' in stNameStr and 'R' in stNameStr: ptcolor = 2
elif 'C' in stNameStr: ptcolor = 3
elif 'R' in stNameStr: ptcolor = 4
else: ptcolor = 5
# Get the values to plot
uvw = tpart.getcol('UVW', rowincr=timeskip)
if numPlotted == 0:
savex0 = numpy.append(savex0, [uvw[:, 0], -uvw[:, 0]])
savey0 = numpy.append(savey0, [uvw[:, 1], -uvw[:, 1]])
savex1 = numpy.append(savex1, [uvw[:, 0], -uvw[:, 0]])
savey1 = numpy.append(savey1, [uvw[:, 1], -uvw[:, 1]])
savex2 = numpy.append(savex2, [uvw[:, 0], -uvw[:, 0]])
savey2 = numpy.append(savey2, [uvw[:, 1], -uvw[:, 1]])
savex3 = numpy.append(savex3, [uvw[:, 0], -uvw[:, 0]])
savey3 = numpy.append(savey3, [uvw[:, 1], -uvw[:, 1]])
savex4 = numpy.append(savex4, [uvw[:, 0], -uvw[:, 0]])
savey4 = numpy.append(savey4, [uvw[:, 1], -uvw[:, 1]])
savex5 = numpy.append(savex5, [uvw[:, 0], -uvw[:, 0]])
savey5 = numpy.append(savey5, [uvw[:, 1], -uvw[:, 1]])
if plotLambda:
for w in ref_wavelength:
if ptcolor == 0:
xaxisvals0 = numpy.append(
xaxisvals0,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals0 = numpy.append(
yaxisvals0,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
elif ptcolor == 1:
xaxisvals1 = numpy.append(
xaxisvals1,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals1 = numpy.append(
yaxisvals1,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
elif ptcolor == 2:
xaxisvals2 = numpy.append(
xaxisvals2,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals2 = numpy.append(
yaxisvals2,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
elif ptcolor == 3:
xaxisvals3 = numpy.append(
xaxisvals3,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals3 = numpy.append(
yaxisvals3,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
elif ptcolor == 4:
xaxisvals4 = numpy.append(
xaxisvals4,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals4 = numpy.append(
yaxisvals4,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
elif ptcolor == 5:
xaxisvals5 = numpy.append(
xaxisvals5,
[uvw[:, 0] / w / 1000., -uvw[:, 0] / w / 1000.])
yaxisvals5 = numpy.append(
yaxisvals5,
[uvw[:, 1] / w / 1000., -uvw[:, 1] / w / 1000.])
else:
if ptcolor == 0:
xaxisvals0 = numpy.append(xaxisvals0,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals0 = numpy.append(yaxisvals0,
[uvw[:, 1], -uvw[:, 1]])
elif ptcolor == 1:
xaxisvals1 = numpy.append(xaxisvals1,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals1 = numpy.append(yaxisvals1,
[uvw[:, 1], -uvw[:, 1]])
elif ptcolor == 2:
xaxisvals2 = numpy.append(xaxisvals2,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals2 = numpy.append(yaxisvals2,
[uvw[:, 1], -uvw[:, 1]])
elif ptcolor == 3:
xaxisvals3 = numpy.append(xaxisvals3,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals3 = numpy.append(yaxisvals3,
[uvw[:, 1], -uvw[:, 1]])
elif ptcolor == 4:
xaxisvals4 = numpy.append(xaxisvals4,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals4 = numpy.append(yaxisvals4,
[uvw[:, 1], -uvw[:, 1]])
elif ptcolor == 5:
xaxisvals5 = numpy.append(xaxisvals5,
[uvw[:, 0], -uvw[:, 0]])
yaxisvals5 = numpy.append(yaxisvals5,
[uvw[:, 1], -uvw[:, 1]])
#if debug:
# print uvw.shape
# print xaxisvals.shape
# print yaxisvals.shape
#else:
# sys.stdout.write('.')
# sys.stdout.flush()
sys.stdout.write(' Done!\n')
numPlotted += 1
print('Plotting uv points ...')
# open the graphics device, using only one panel
ppgplot.pgbeg(device, 1, 1)
# set the font size
ppgplot.pgsch(1)
ppgplot.pgvstd()
xaxisvals = numpy.append(
xaxisvals0,
numpy.append(
xaxisvals1,
numpy.append(
xaxisvals2,
numpy.append(xaxisvals3, numpy.append(xaxisvals4,
xaxisvals5)))))
yaxisvals = numpy.append(
yaxisvals0,
numpy.append(
yaxisvals1,
numpy.append(
yaxisvals2,
numpy.append(yaxisvals3, numpy.append(yaxisvals4,
yaxisvals5)))))
tmpvals0 = numpy.sqrt(xaxisvals0**2 + yaxisvals0**2)
tmpvals1 = numpy.sqrt(xaxisvals1**2 + yaxisvals1**2)
tmpvals2 = numpy.sqrt(xaxisvals2**2 + yaxisvals2**2)
tmpvals3 = numpy.sqrt(xaxisvals3**2 + yaxisvals3**2)
tmpvals4 = numpy.sqrt(xaxisvals4**2 + yaxisvals4**2)
tmpvals5 = numpy.sqrt(xaxisvals5**2 + yaxisvals5**2)
# Plot the data
if debug:
print(xaxisvals0[tmpvals0 != badval])
print(yaxisvals0[tmpvals0 != badval])
ppgplot.pgsci(1)
uvmax = max(xaxisvals.max(), yaxisvals.max())
uvmin = min(xaxisvals.min(), yaxisvals.min())
uvuplim = 0.02 * (uvmax - uvmin) + uvmax
uvlolim = uvmin - 0.02 * (uvmax - uvmin)
if xmin == '':
minx = uvlolim
else:
minx = float(xmin)
if xmax == '':
maxx = uvuplim
else:
maxx = float(xmax)
if ymin == '':
miny = uvlolim
else:
miny = float(ymin)
if ymax == '':
maxy = uvuplim
else:
maxy = float(ymax)
if minx == maxx:
minx = -1.0
maxx = 1.0
if miny == maxy:
miny = -1.0
maxy = 1.0
ppgplot.pgpage()
ppgplot.pgswin(minx, maxx, miny, maxy)
ppgplot.pgbox('BCNST', 0.0, 0, 'BCNST', 0.0, 0)
if plotLambda:
ppgplot.pglab('u [k\gl]', 'v [k\gl]', '%s' % (plottitle))
else:
ppgplot.pglab('u [m]', 'v [m]', '%s' % (plottitle))
ppgplot.pgpt(xaxisvals0[tmpvals0 != badval],
yaxisvals0[tmpvals0 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.35, 0.5, 'C-C')
ppgplot.pgsci(2)
ppgplot.pgpt(xaxisvals1[tmpvals1 != badval],
yaxisvals1[tmpvals1 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.50, 0.5, 'R-R')
ppgplot.pgsci(4)
ppgplot.pgpt(xaxisvals2[tmpvals2 != badval],
yaxisvals2[tmpvals2 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.65, 0.5, 'C-R')
ppgplot.pgsci(3)
ppgplot.pgpt(xaxisvals3[tmpvals3 != badval],
yaxisvals3[tmpvals3 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.55, 0.5, 'C-I')
ppgplot.pgsci(5)
ppgplot.pgpt(xaxisvals4[tmpvals4 != badval],
yaxisvals4[tmpvals4 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.65, 0.5, 'R-I')
ppgplot.pgsci(6)
ppgplot.pgpt(xaxisvals5[tmpvals5 != badval],
yaxisvals5[tmpvals5 != badval], 1)
#if doPlotColors: ppgplot.pgmtxt('T', 1, 0.75, 0.5, 'I-I')
# Close the PGPLOT device
ppgplot.pgclos()
freqcut = pffdot[np/2, :]
fdotcut = pffdot[:, np/2]
image='antirainbow'
device='ffdot_combined.eps/VCPS'
device='/XWIN'
labx='Fourier Frequency Offset (bins)'
laby='Fourier Frequency Derivative (bins)'
contours = num.asarray([0.1, 0.3, 0.5, 0.7, 0.9])
imfract = 0.65
margin = 0.08
ppgplot.pgopen(device)
ppgplot.pgpap(0.0, 1.0)
ppgplot.pgpage()
# Give z and w values and power change
ppgplot.pgsvp(margin+imfract, 1.0-margin/2, margin+imfract, 1.0-margin/2)
ppgplot.pgswin(0.0, 1.0, 0.0, 1.0)
ppgplot.pgtext(0.1, 0.8, "Frac Recovered" % frp)
ppgplot.pgtext(0.2, 0.65, "Power = %.3f" % frp)
ppgplot.pgtext(0.1, 0.4, "signal z = %.1f" % z)
ppgplot.pgtext(0.1, 0.25, "signal w = %.1f" % w)
# freq cut
ppgplot.pgsvp(margin, margin+imfract, margin+imfract, 1.0-margin/2)
ppgplot.pgswin(min(rs), max(rs), -0.1, 1.1)
ppgplot.pgbox("BCST", 0.0, 0, "BCNST", 0.0, 0)
ppgplot.pgline(rs, freqcut)
ppgplot.pgmtxt("L", 2.0, 0.5, 0.5, "Relative Power");
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()