def makeplot(hitfreq,eventpower,rfi_found,coarsespec_freq,coarsepowers,specid=1,dolog='False', dotext=True, saveplot=''):
"""Plots both coarse power (for coarse spectrum) as a blue line
and event power (for hits) as red X's on the same figure.
hitfreq is a list of frequencies for hits in a spectrum, eventpower
is a list of the eventpowers, coarsespec_freq is a list of
frequencies for the coarse spectra bins, and coarsepowers
is a list of the powers in each bin.
freq_type is either 'topo' or 'bary' (default is topo)
specid is the value of the specid desired
if dolog='True', the power on the y-axis will be logarithmic
where is an optional string to further modify which hits are plotted.
prefix all columns with an 'h' and a period, such as h.eventpower. do
not include the phrase 'where' or the semicolon at the end. all other
syntax rules apply.
saveplot='' allows you to save the plot by inputting its name as a
string. if left blank, no plot is saved
output is a figure."""
import pylab, numpy, MySQLFunction, jd2gd, math
# pylab.rc('text', usetex=True)
# pylab.rc('font', family='serif')
#Get additional info for text header
cmd = 'select beamnum, ra, decl, obstime, IF1_rfFreq, thrscale from config where specid=%d' %specid
data = MySQLFunction.mysqlcommand(cmd)
#Combine systime with obstime to get complete time
obstime = data[0][3]
#Create Gregorian date from obstime
gd = jd2gd.caldate(obstime)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
gd = [str(gd[x]) for x in range(len(gd))]
#Insert zeros to make formatting nice
if float(gd[2])<10:
gd[2] = '0' + gd[2]
if float(gd[3])<10:
gd[3] = '0' + gd[3]
if float(gd[4])<10:
gd[4] = '0' + gd[4]
if float(gd[5])<10:
gd[5] = '0' + gd[5]
#Compile one date string
date = gd[0] + ' ' + dates[int(gd[1])-1] + ' ' + gd[2] + ' ' + gd[3] + ':' + gd[4] + ':' + gd[5][:2]
#Calculate center frequency
rfFreq=int(data[0][4])
rfFreq = rfFreq/1000000
rfFreq = rfFreq-50
cfreq = rfFreq + 100
#Determine beam and polarization
beam = int(data[0][0])
beamnum = str(math.floor(float(beam)/2))[0]
frac = float(beam)/2
if math.modf(frac)[0]==0.0:
newbeam = beamnum + 'a'
else: newbeam = beamnum + 'b'
#thrscale
thrscale=float(data[0][5])/4.0
#PLOTTING
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.12, 0.85, 0.75])
#Divide into RFI flagged or not
ginds=numpy.where(rfi_found==0)[0]
rinds=numpy.where(rfi_found>0)[0]
coarsepowers/=thrscale
#Log or not?
if dolog=='True':
pylab.semilogy(coarsespec_freq/1000000,coarsepowers,'k')
pylab.semilogy(hitfreq[rinds]/1000000,eventpower[rinds],'rx')
pylab.semilogy(hitfreq[ginds]/1000000,eventpower[ginds],'bx')
elif dolog=='False':
pylab.plot(coarsespec_freq/1000000,coarsepowers,'k')
pylab.plot(hitfreq[rinds]/1000000,eventpower[rinds],'rx')
pylab.plot(hitfreq[ginds]/1000000,eventpower[ginds],'bx')
#Add text to figure
if dotext:
pylab.figtext(0.1,.97,'Beam: %s' % newbeam)
pylab.figtext(0.3,.97,'RA: %s' %data[0][1])
pylab.figtext(0.5,.97,'Dec: %s' %data[0][2])
pylab.figtext(0.95,.97,'Date: %s' %date, ha='right')
pylab.figtext(0.1,.92,'Hit Count: %s' %len(eventpower))
pylab.figtext(0.95,.92,'Center Freq: %s MHz' %cfreq, ha='right')
#Set x-scale
lowbound = cfreq - 100
uppbound = cfreq + 100
xticks = numpy.linspace(lowbound,uppbound,21)
pylab.xticks(xticks)
#Rotate x-labels
for i in ax1.get_xticklabels(): i.set_rotation(45)
#Set labels and title
pylab.xlabel('Frequency (MHz)', size=14)
pylab.ylabel('Power (arb units)', size=14)
# pylab.title(' Coarse Spectrum and Hits for Specid=%d' %specid)
#Set axis limits
if len(eventpower) != 0:
v = [lowbound,uppbound,min(coarsepowers),max(eventpower)+1000]
else: v=[lowbound,uppbound,min(coarsepowers),max(coarsepowers)]
pylab.axis(v)
#Add grid
pylab.grid(True)
#Save plot?
if saveplot != '':
pylab.savefig('%s' %saveplot)
return fig
def makeplot(eventpower,freq,time,errbar=[0], where='',freqtype='topo',vlim=(-1,-1),frac=0.9,saveplot=''):
"""Produces a 'confetti plot' of spectra dynamically.
freqtype is the frequency type, either 'binnum', 'bary', or
'topo'.
Input:
where is a string to include additional information to
narrow the results. typically it will be used to specify a
range of specids. each column name MUST be prefixed with
the first letter of the table name and a period, like
c.obstime. don't forget to include 's.specid=c.specid if
referencing config and spec. do not include the word 'where'
at the beginning or the semicolon at the end. all other common
mysql syntax rules apply. Ex: 's.specid>1 and s.specid<=20 and
c.beamnum!=8 and c.specid=s.specid'. don't include hit table.
vlim is a tuple of (vmin,vmax). Values are used in conjuction
with norm to normalize luminance data.
frac is the fraction of hits, sorted by eventpower, before which
the size is 0.1 and after which the size is 1
saveplot='' allows you to save the plot by inputting its name
as a string. if left blank, no plot is saved
Output:
Figure instance
"""
import pylab, numpy, MySQLFunction, command, jd2gd, math
# initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.14, 0.85, 0.75])
#If no plot limits specified,
if vlim==(-1,-1):
vlim=(numpy.min(eventpower), numpy.max(eventpower))
# create array of point sizes
sorted = numpy.sort(eventpower)
index = math.floor(frac*len(eventpower))
cutoff = eventpower[index]
size = [.1 if eventpower[x]<cutoff else 1 for x in xrange(len(eventpower))]
# plot data
if len(errbar)>1:
size=20
pylab.errorbar(time,freq,xerr=errbar,fmt=None,ecolor='k', capsize=0.0)
pylab.scatter(time,freq,s=size,c=eventpower,edgecolors='none',vmin=vlim[0],vmax=vlim[1])
# add grid
pylab.grid(True,which='both')
# add labels
ax1.set_xlabel('Time (seconds)')
ax1.set_title('Dynamic Spectra - Hits')
if freqtype=='binnum':
ax1.set_ylabel('Frequency channel')
elif freqtype=='topo':
ax1.set_ylabel('Topocentric Frequency (MHz)')
elif freqtype=='bary':
ax1.set_ylabel('Barycentric Frequency (MHz)')
# gather additional info
if where=='':
cmd = command.generate('specid,obstime,AGC_Time,IF1_rfFreq','config')
elif 'c.' not in where:
where = where + ' and h.specid=c.specid'
cmd = command.generate('h.specid,c.obstime,c.AGC_Time,c.IF1_rfFreq','hit h, config c',where=where)
else:
where = where + ' and h.specid=c.specid'
cmd = command.generate('h.specid,c.obstime,c.AGC_Time,c.IF1_rfFreq','hit h, config c',where=where)
data = MySQLFunction.mysqlcommand(cmd)
# separate into arrays
length = len(data)
specid = [data[x][0] for x in xrange(length)]
day = numpy.asarray([data[x][1] for x in xrange(length)])
# get specid and hit count
uniq_IDs = set(specid)
speccount = len(uniq_IDs)
hitcount = len(eventpower)
# determine start and end dates
start = min(day)
end = max(day)
# calculate the min and max RF from the center freq
# scale y axis accordinly
rfctr=float(data[0][3])
rflo=rfctr-50e6
rfhi=rflo+200e6
rflo-=5e6 #Add offsets to get hits away from plot edges
rfhi+=5e6
# guess whether data is given in Hz or MHz
if numpy.log10(freq[0])<4:
rflo/=1e6
rfhi/=1e6
# set axes limits
v = [0,max(time),rflo,rfhi]
pylab.axis(v)
if min(freq)<rflo or max(freq)>rfhi: print "WARNING: There are hits outside freq limits"
# create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
# insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
# compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:2]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:2]
# add text to figure
pylab.figtext(0.4,.96,'Spectra Count: %s' %speccount)
pylab.figtext(0.4,.935,'Hit Count: %s' %hitcount)
pylab.figtext(0.61,.96,'Vmin,Vmax: %s %s' % (vlim[0], vlim[1]))
pylab.figtext(0.61,.935,'ALFA RFctr: %4.1f' % (rfctr/1e6))
pylab.figtext(0.8,.96,'Max Power: %s' %max(eventpower))
pylab.figtext(0.8,.935,'Min Power: %s' %min(eventpower))
pylab.figtext(0.1,.96,'Start: %s' %date1)
pylab.figtext(0.1,.935,'End: %s' %date2)
# save plot?
if saveplot != '':
pylab.savefig('%s' %saveplot)
return fig
def makeplot(bins,count,where='',dolog='False',cumulative='False',saveplot=''):
"""Creates histogram of hits per mean power bin.
where is a string to include additional information to
narrow the results. typically it will be used to specify a
range of specids. each column name MUST be prefixed with
the first letter of the table name and a period, like
c.obstime. don't forget to include 'h.specid=c.specid if
referencing config and hit. do not include the word 'where'
at the beginning or the semicolon at the end. all other common
mysql syntax rules apply. Ex: 'h.specid>1 and h.specid<=20 and
c.beamnum!=8 and c.specid=h.specid'.
setting cumulative='True' makes a cumulative histogram as mean
power increases
setting dolog='True' makes the y-axis (count) logarithmic
saveplot allows the user to have the figure saved by
inputting the file name. if left empty, no file will be saved
returns a figure"""
import pylab, MySQLFunction, command, jd2gd, math, numpy
#Data to plot?
if len(bins) != 0:
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.14, 0.85, 0.75])
#Determine bar width
width = bins[1]-bins[0]
#Logarithmic?
if dolog != 'True':
pylab.bar(bins[:-1],count,width=width)
ylabel = 'Count'
var = min(count)*0.5
else:
pylab.bar(bins[:-1],count,width=width,log='True')
ylabel = 'Count (Logarithmic)'
bottom = int(math.floor(numpy.log10(min(count)+1)))
var = 10**(bottom)
#Configure ticks
pylab.xticks([0,50,100,150,200,250,300,350,400,450,500,500+width],['0','50','100','150','200','250','300','350','400','450','500','%d'%max(bins)])
#Rotate xticks
for i in ax1.get_xticklabels(): i.set_rotation(45)
#Cumulative?
if cumulative != 'True':
cumltv = ''
else:
cumltv = '(Cumulative)'
#Set axes limits
v = [min(bins),500+width,var,max(count)*1.1]
pylab.axis(v)
#Add grid
pylab.grid(True,which='both')
#Add labels
pylab.xlabel('Mean Power')
pylab.ylabel('%s'%ylabel)
pylab.title('Hit Count Per Mean Power Bin %s'%cumltv)
#Get extra info for plot
if where=='':
cmd = command.generate('specid,obstime,AGC_Time','config')
elif 'c.' not in where:
where = where + ' and h.specid=c.specid'
cmd = command.generate('c.specid,c.obstime','config c, hit h',where=where)
data = MySQLFunction.mysqlcommand(cmd)
#Separate into arrays
length = len(data)
specid = [data[x][0] for x in range(length)]
time = numpy.asarray([data[x][1] for x in range(length)])
#Get specid count
uniq_IDs = set(specid)
speccount = len(uniq_IDs)
# determine start and end dates
start = min(time)
end = max(time)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:2]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:2]
#Add text to figure
pylab.figtext(0.1,.945,'SpecID Count: %s' %speccount)
pylab.figtext(0.95,.97,'Start: %s' %date1, ha='right')
pylab.figtext(0.95,.945,'End: %s' %date2, ha='right')
#Save figure?
if saveplot!='':
pylab.savefig('%s'%saveplot)
return fig
def makeplot(bins,count,freq_type='topo',increment_log=7,where='h.specid<100',dolog='False',saveplot=''):
"""Creates a histogram of hits at different
frequencies, separated into bins by increments of
10^(increment_log).
freq_type is either 'topo', 'bary', or 'binnum'. default is
topo
increment_log is the log of the spacing between bins. must
be an integer
where is a string to include additional information to
narrow the results. typically it will be used to specify a
range of specids. each column name MUST be prefixed with
the first letter of the table name and a period, like
c.obstime. do not include the word 'where' at the beginning
or the semicolon at the end. all other common mysql syntax
rules apply. Ex: 'h.specid>1 and h.specid<=20 and
c.beamnum!=8'. by default it will grab only the first 99
specids.
if dolog='True', the hit count is plotted on a log scale
saveplot allows the user to have the plot saved by inputting
the file name. if left empty, no file will be saved.
returns a figure"""
import pylab, numpy, math, MySQLFunction, command, jd2gd
#Are there data to plot?
if len(bins)!=0:
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.14, 0.85, 0.75])
#Configure x-ticks
if freq_type!='binnum':
lowbound = min(bins)/1000000
uppbound = max(bins)/1000000
xticks = numpy.arange(lowbound,uppbound+10**(increment_log-6),10)
pylab.xticks(xticks)
else:
lowbound = min(bins)
uppbound = max(bins)
xticks = numpy.arange(lowbound,uppbound+10**(increment_log),5000000)
pylab.xticks(xticks)
#Rotate xticks
for i in ax1.get_xticklabels(): i.set_rotation(45)
#Create xlabels
if freq_type=='topo':
xlabel = 'Topocentric Frequency (MHz)'
elif freq_type=='bary':
xlabel = 'Barycentric Frequency (MHz)'
else: xlabel = 'Bin Number'
#Determine bar width
if freq_type != 'binnum':
width = (10**increment_log)/1000000
else: width = 10**increment_log
#Make plots
if dolog=='True' and freq_type!='binnum':
pylab.bar(bins/1000000,count,log='True',width=width,align='center')
ylabel = 'Count (Logarithmic)'
elif dolog=='True':
pylab.bar(bins,count,log='True',width=width,align='center')
ylabel = 'Count (Logarithmic)'
elif freq_type!='binnum':
pylab.bar(bins/1000000,count,width=width,align='center')
ylabel = 'Count'
else:
pylab.bar(bins,count,width=width,align='center')
ylabel = 'Count'
#Determine y-axis lower limit
if dolog=='True':
bottom = int(math.floor(numpy.log10(min(count)+1)))
var = 10**bottom
else:
var = min(count)*0.5
#Set axes limits
if freq_type=='binnum':
v = [0,uppbound+width/2,var,max(count)*1.1]
pylab.axis(v)
else:
v=[lowbound-width/2,uppbound+width/2,var,max(count)*1.1]
pylab.axis(v)
#Add grid
pylab.grid(True)
#Add labels
pylab.xlabel('%s'%xlabel)
pylab.ylabel('%s'%ylabel)
pylab.title('Event Count Per Bin')
#Get extra info for plot
if where=='':
cmd = command.generate('specid,obstime,AGC_Time','config')
elif 'c.' not in where:
where = where + ' and h.specid=c.specid'
cmd = command.generate('c.specid,c.obstime','config c, hit h',where=where)
#Send command to mysql, return results
data = MySQLFunction.mysqlcommand(cmd)
#Separate into arrays
length = len(data)
specid = [data[x][0] for x in range(length)]
time = numpy.asarray([data[x][1] for x in range(length)])
#Get hit count and specid count
uniq_IDs = set(specid)
speccount = len(uniq_IDs)
hitcount = sum(count)
#Determine start and end dates
start = min(time)
end = max(time)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:2]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:2]
#Create dictionary of bin resolutions
if freq_type!='binnum':
binres = {0: '1 Hz', 1: '10 Hz', 2: '100 Hz', 3: '1 KHz', 4: '10 KHz', 5: '100 KHz',
6: '1 MHz', 7: '10 MHz', 8: '100MHz', 9: '1 GHz'}
else:
binres = {0: '1 Bin', 1: '10 Bins', 2: '100 Bins', 3: '1,000 Bins', 4: '10,000 Bins', 5: '100,000 Bins',
6: '1,000,000 Bins', 7: '10,000,000 Bins', 8: '100,000,000 Bins'}
#Add text to figure
pylab.figtext(0.1,.97,'Hit Count: %s' %hitcount)
pylab.figtext(0.1,.92,'Bin Resolution: %s' %binres[increment_log])
pylab.figtext(0.1,.945,'SpecID Count: %s' %speccount)
pylab.figtext(0.95,.97,' Start: %s' %date1, ha='right')
pylab.figtext(0.95,.945,'End: %s' %date2, ha='right')
#Save figure?
if saveplot!='':
pylab.savefig('%s'%saveplot)
return fig
def makeplot(xarr,yarr,data,where='',freqtype='binnum',vlim=(-1,-1), tslim=(-1,-1),saveplot=''):
"""Method to produce the three panel
dynamic spectrum plot. The main panel
is a pcolormesh figure of data with
the mesh defined by xarr and yarr.
The bottom panel shows a time series of
the 2D data, and the right panel shows
the average bandpass
freqtype is the frequency type for the pcolormesh, either
'binnum' or 'topo'.
Input:
where is a string to include additional information to
narrow the results. typically it will be used to specify a
range of specids. each column name MUST be prefixed with
the first letter of the table name and a period, like
c.obstime. don't forget to include 's.specid=c.specid if
referencing config and spec. do not include the word 'where'
at the beginning or the semicolon at the end. all other common
mysql syntax rules apply. Ex: 's.specid>1 and s.specid<=20 and
c.beamnum!=8 and c.specid=s.specid'. don't include hit table.
saveplot='' allows you to save the plot by inputting its name
as a string. if left blank, no plot is saved
Output:
Figure instance
"""
import numpy, pylab, jd2gd, MySQLFunction, command
#Calculate the time series and average bandpass
# for the subpanel plots
tseries=numpy.mean(data, axis=0)
bandpass=numpy.mean(data, axis=1)
#If no plot limits specified,
if vlim==(-1,-1):
vlim=(numpy.min(data), numpy.max(data))
if tslim==(-1,-1):
tslim=(numpy.min(tseries), numpy.max(tseries))
#Create figure instance, add axes and turn off labels
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.3, 0.6, 0.6])
ax2 = fig.add_axes([0.1, 0.1, 0.6, 0.2], sharex=ax1)
ax3 = fig.add_axes([0.7, 0.3, 0.2, 0.6], sharey=ax1)
for i in ax3.get_yticklabels(): i.set_visible(False)
for i in ax3.get_xticklabels(): i.set_rotation(270)
for i in ax1.get_xticklabels(): i.set_visible(False)
#Generate 2D mesh
T,F=numpy.meshgrid(xarr,yarr)
#Add plots
ax1.pcolormesh(T,F,data, vmin=vlim[0], vmax=vlim[1])
ax2.plot(xarr, tseries, 'r.')
ax3.step(bandpass, yarr, 'g-')
#Set axes labels
ax2.set_xlabel('Time (Seconds)')
if freqtype=='binnum':
ax1.set_ylabel('Frequency channel')
elif freqtype=='topo':
ax1.set_ylabel('Frequency (MHz)')
ax1.set_title('Dynamic Spectra - Coarse Bins')
ax2.set_ylabel('Mean Intensity')
ax1.set_xlim((min(xarr), max(xarr)))
ax1.set_ylim((min(yarr), max(yarr)))
ax2.set_ylim((tslim[0], tslim[1]))
#Gather additional info
if where=='':
cmd = command.generate('specid,obstime,AGC_Time','config')
elif 'c.' not in where:
where = where + ' and s.specid=c.specid'
cmd = command.generate('s.specid,c.obstime,c.AGC_Time','config c, spec s',where=where)
data = MySQLFunction.mysqlcommand(cmd)
#Separate into arrays
length = len(data)
specid = [data[x][0] for x in range(length)]
day = numpy.asarray([data[x][1] for x in range(length)])
fracday = numpy.asarray([float(data[x][2])/86400000 for x in range(length)])
time = day + fracday
#Get specid count
uniq_IDs = set(specid)
speccount = len(uniq_IDs)
#Determine start and end dates
start = min(time)
end = max(time)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:4]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:4]
#Add text to figure
pylab.figtext(0.73,.175,'SpecID Count: %s' %speccount)
pylab.figtext(0.73,.15,'Start: %s' %date1)
pylab.figtext(0.73,.125,'End: %s' %date2)
#Save plot?
if saveplot != '':
pylab.savefig('%s' %saveplot)
return fig
def makeplot(ra,dec,specid,where='',figtype='cart',ellipses='no',saveplot=''):
""" Makes a plot of RA and DEC.
where is a string specifying which data from mysql to grab.
ONLY include columns from table 'config'. do not include
the word 'where' at the beginning or the semicolon at the
end. all other common mysql syntax rules apply.
figtype is the figure type. default is 'cart' for cartesian
coordinates. 'sky' plots the ra and dec as a Mollweide
projection
if ellipses='yes', the spectra are plotted as individual ellipses
of fixed size corresponding to ALFA beam width (only for Cartesian
coordinate axis)
saveplot allows you to save the figure by specifying the
file name as a string. if left empty, the figure is not
saved.
returns a figure"""
import jd2gd, command
#Determine values to include in figure
var1 = min(specid)
var2 = max(specid)
var3 = len(specid)
#Get time info from database
cmd = command.generate('obstime','config',where=where)
data = MySQLFunction.mysqlcommand(cmd)
#Create list
day = numpy.asarray([data[x][0] for x in xrange(len(data))])
#Determine start and end dates
start = min(day)
end = max(day)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:4]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:4]
#Which fig type?
patches=[]
if figtype=='cart':
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.12, 0.85, 0.75])
#Plot data
if ellipses=='yes':
for x,y in zip(ra,dec):
circle=matplotlib.patches.Ellipse((x,y),width=.0038888,height=.058333,facecolor='b',edgecolor='b')
patches.append(circle)
p=matplotlib.collections.PatchCollection(patches)
ax1.add_collection(p)
else: ax1.scatter(ra,dec,s=.1,label='spectra')
else:
#Convert RA to degrees
length = len(ra)
ra = [ra[x]*15 for x in range(length)]
#Convert arrays to radians
ra = [math.radians(ra[x]) for x in range(length)]
dec = [math.radians(dec[x]) for x in range(length)]
#Adjust ra scale
ra = [ra[x]-numpy.pi for x in range(length)]
#Create figure
fig = pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([.1,.12,.70,.85],projection='mollweide')
#Plot data
ax1.scatter(ra,dec,label='spectra',marker='+',c='b')
#Set xtick labels
ax1.set_xticklabels(['2','4','6','8','10','12','14','16','18','20','22'])
#Create galactic plane lines
#Create l,b arrays
b = [math.radians(5)]*360 + [math.radians(-5)]*360
l = list(numpy.linspace(0,2*numpy.pi,360))*2
#Pass l,b pairs to gal2eq
bounds = []
for x in range(720):
bounds.append(astroconvert.gal2eq(l[x],b[x]))
#Separate into component arrays
ra_bounds = [bounds[x][0] for x in range(720)]
dec_bounds = [bounds[x][1] for x in range(720)]
#Convert to deg if necessary, and plot
if figtype=='sky':
ra_bounds = [ra_bounds[x]-numpy.pi for x in range(720)]
ax1.scatter(ra_bounds,dec_bounds,edgecolor='none',c='r',label='galactic plane')
else:
ra_bounds = [math.degrees(ra_bounds[x])/15 for x in range(720)]
dec_bounds = [math.degrees(dec_bounds[x]) for x in range(720)]
ax1.plot(ra_bounds,dec_bounds,'r',label='galactic plane')
#Set axis limits
ax1.set_xlim(0, 24)
ax1.set_ylim(0, 40)
#Set axis labels and title
pylab.xlabel('RA (hours)')
pylab.ylabel('Dec (degrees)')
pylab.title('Right Ascension and Declination')
#Add legend
ax1.legend(bbox_to_anchor=(0,0,1,1),loc=0)
#Add text to figure
pylab.figtext(0.1,.97,'First Specid: %d' %var1)
pylab.figtext(0.1,.945,'Last Specid: %d' %var2)
pylab.figtext(0.1,.92,'Count: %d spectra' %var3)
pylab.figtext(0.95,.97,' Start: %s' %date1, ha='right')
pylab.figtext(0.95,.945,'End: %s' %date2, ha='right')
#Include grid
pylab.grid(True)
#Save figure?
if saveplot!='':
pylab.savefig('%s'%saveplot)
return fig
def makeplot(bins,count,maximum=24,histtype='fracmax',where='',saveplot=''):
"""Plots data for event count per coarse frequency bin.
maximum is the maximum number of allowed hits per coarse bin
histtype specifies the type of histogram you intend to
plot:
'fracmax' is the fraction of spectra that reach the
max (24) for each coarse bin, and the default option,
'%full' is the percent full each coarse bin is after adding
events for all desired spectra, and
'maxcount' is the number of times each bin reaches the max
(24)
where is a string to include additional information to
narrow the results. typically it will be used to specify a
range of specids. each column name MUST be prefixed with
the first letter of the table name and a period, like
c.obstime. do not include the word 'where' at the beginning
or the semicolon at the end. all other common mysql syntax
rules apply. Ex: 'h.specid>1 and h.specid<=20 and
c.beamnum!=8'.
saveplot allows the user to have the figure saved by
inputting the file name. if left empty, no file will be saved
returns a figure"""
import pylab, MySQLFunction, jd2gd, numpy, command
#Data to plot?
if len(bins) != 0:
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.14, 0.85, 0.75])
#Set axes limits
v = [0,4096,0,max(count)]
ax1.axis(v)
#Configure xticks
xticks = numpy.arange(0,4097,256)
ax1.set_xticks(xticks)
#Rotate xticks
for i in ax1.get_xticklabels(): i.set_rotation(45)
#Add grid
pylab.grid(True)
#Plot data
pylab.bar(bins,count,width=1,align='center')
#Get extra info for plot
if 'c.' not in where:
where = where + ' and h.specid=c.specid'
cmd = command.generate('c.specid,c.obstime','config c, hit h',where=where)
data = MySQLFunction.mysqlcommand(cmd)
#Separate into arrays
length = len(data)
specid = numpy.asarray([data[x][0] for x in range(length)])
time = numpy.asarray([data[x][1] for x in range(length)])
#Get specid count
uniq_IDs = set(specid)
speccount = len(uniq_IDs)
num = sum(count)
#Get hit count and labels
if histtype=='fracmax':
title = 'Fraction of Spectra That Reach Maximum Allowed Hit Count Per Coarse Bin'
hitcount = int(num*speccount)
countlabel = 'Max Count'
if histtype=='%full':
title = 'Percent of Maximum Allowed Hits Per Coarse Bin'
hitcount = int(num*speccount*24)
countlabel = 'Hit Count'
if histtype=='maxcount':
title = 'Number of Times Each Coarse Bin Reached The Maximum Allowed Hit Count'
hitcount = sum(count)
countlabel = 'Max Count'
pylab.xlabel('Coarse Bin Number')
pylab.ylabel('Count')
pylab.title('%s' %title)
#Determine start and end dates
start = min(time)
end = max(time)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:2]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:2]
#Add text to figure
pylab.figtext(0.1,.97,'%s: %d' % (countlabel,hitcount))
pylab.figtext(0.1,.945,'SpecID Count: %s' %speccount)
pylab.figtext(0.95,.97,'Start: %s' %date1, ha='right')
pylab.figtext(0.95,.945,'End: %s' %date2, ha='right')
pylab.figtext(0.1,.92,'Limit: %d' %maximum)
#Save figure?
if saveplot!='':
pylab.savefig('%s'%saveplot)
return fig
