00001 '''
00002 This module is graphical API using pymatplotlib.
00003 Specs:
00004 -- We use matplotlib OO class level api, we do not use its high-level helper modules. Favor endured stability over simplicity.
00005 -- use TkAgg for interactive mode. Beaware of Tk,pyTk installation defects in various cern distributions.
00006 -- PNG as default batch file format
00007 -- we support http mode by sending string buf via meme type image/png. Sending a premade static plot to webserver is considered a uploading process instead of http dynamic graphical mode. Therefore covered in this module.
00008 '''
00009 import sys,os
00010 import numpy,datetime
00011 import matplotlib
00012 from RecoLuminosity.LumiDB import CommonUtil
00013
00014 batchonly=False
00015 if not os.environ.has_key('DISPLAY') or not os.environ['DISPLAY']:
00016 batchonly=True
00017 matplotlib.use('Agg',warn=False)
00018 from matplotlib.backends.backend_agg import FigureCanvasAgg as CanvasBackend
00019 else:
00020 try:
00021 matplotlib.use('TkAgg',warn=False)
00022 from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg as CanvasBackend
00023 from matplotlib.backends.backend_tkagg import NavigationToolbar2TkAgg
00024 import Tkinter as Tk
00025 root=Tk.Tk()
00026 root.wm_title("Lumi GUI in TK")
00027 except ImportError:
00028 print 'unable to import GUI backend, switch to batch only mode'
00029 matplotlib.use('Agg',warn=False)
00030 from matplotlib.backends.backend_agg import FigureCanvasAgg as CanvasBackend
00031 batchonly=True
00032
00033 from matplotlib.figure import Figure
00034 from matplotlib.font_manager import fontManager,FontProperties
00035 matplotlib.rcParams['lines.linewidth']=1.5
00036 matplotlib.rcParams['grid.linewidth']=0.2
00037 matplotlib.rcParams['xtick.labelsize']=11
00038 matplotlib.rcParams['ytick.labelsize']=11
00039 matplotlib.rcParams['legend.fontsize']=10
00040 matplotlib.rcParams['axes.labelsize']=11
00041 matplotlib.rcParams['font.weight']=567
00042 def destroy(e) :
00043 sys.exit()
00044
00045 class matplotRender():
00046 def __init__(self,fig):
00047 self.__fig=fig
00048 self.__canvas=''
00049 self.colormap={}
00050 self.colormap['Delivered']='r'
00051 self.colormap['Recorded']='b'
00052 self.colormap['Effective']='g'
00053 self.colormap['Max Inst']='r'
00054
00055 def plotSumX_Run(self,rawxdata,rawydata,nticks=6,yscale='linear'):
00056 xpoints=[]
00057 ypoints={}
00058 ytotal={}
00059 xidx=[]
00060
00061
00062 for x in CommonUtil.inclusiveRange(min(rawxdata),max(rawxdata),1):
00063
00064 xpoints.append(x)
00065 xidx.append(rawxdata.index(x))
00066
00067 if len(xpoints)==0:
00068 print '[WARNING]: no data, do nothing'
00069 return
00070 t=sum(rawydata['Delivered'])
00071 denomitor=1.0
00072 unitstring='$\mu$b$^{-1}$'
00073 if t>=1.0e3 and t<1.0e06:
00074 denomitor=1.0e3
00075 unitstring='nb$^{-1}$'
00076 elif t>=1.0e6 and t<1.0e9:
00077 denomitor=1.0e6
00078 unitstring='pb$^{-1}$'
00079 elif t>=1.0e9 and t<1.0e12:
00080 denomitor=1.0e9
00081 unitstring='fb$^{-1}$'
00082 elif t>=1.0e12 and t<1.0e15:
00083 denomitor=1.0e12
00084 unitstring='ab$^{-1}$'
00085 for ylabel,yvalues in rawydata.items():
00086 ypoints[ylabel]=[]
00087 for i in xidx:
00088 ypoints[ylabel].append(sum(yvalues[0:i])/denomitor)
00089 ytotal[ylabel]=sum(yvalues)/denomitor
00090 ax=self.__fig.add_subplot(111)
00091 if yscale=='linear':
00092 ax.set_yscale('linear')
00093 elif yscale=='log':
00094 ax.set_yscale('log')
00095 else:
00096 raise 'unsupported yscale ',yscale
00097 ax.set_xlabel(r'Run',position=(0.95,0))
00098 ax.set_ylabel(r'L '+unitstring,position=(0,0.9))
00099 xticklabels=ax.get_xticklabels()
00100 for tx in xticklabels:
00101 tx.set_rotation(30)
00102 majorLocator=matplotlib.ticker.LinearLocator( nticks )
00103 majorFormatter=matplotlib.ticker.FormatStrFormatter('%d')
00104 minorLocator=matplotlib.ticker.LinearLocator(numticks=4*nticks)
00105 ax.xaxis.set_major_locator(majorLocator)
00106 ax.xaxis.set_major_formatter(majorFormatter)
00107 ax.xaxis.set_minor_locator(minorLocator)
00108 ax.set_xbound(lower=xpoints[0],upper=xpoints[-1])
00109 ax.grid(True)
00110 keylist=ypoints.keys()
00111 keylist.sort()
00112 legendlist=[]
00113 for ylabel in keylist:
00114 cl='k'
00115 if self.colormap.has_key(ylabel):
00116 cl=self.colormap[ylabel]
00117 ax.plot(xpoints,ypoints[ylabel],label=ylabel,color=cl,drawstyle='steps')
00118 legendlist.append(ylabel+' '+'%.2f'%(ytotal[ylabel])+' '+unitstring)
00119
00120
00121 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00122 ax.text(xpoints[0],1.025,str(xpoints[0]),transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00123 ax.text(xpoints[-1],1.025,str(xpoints[-1]),transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00124 ax.legend(tuple(legendlist),loc='upper left')
00125 self.__fig.subplots_adjust(bottom=0.18,left=0.1)
00126
00127 def plotSumX_Fill(self,rawxdata,rawydata,rawfillDict,nticks=6,yscale='linear'):
00128
00129 ytotal={}
00130 ypoints={}
00131 xpoints=rawfillDict.keys()
00132 if len(xpoints)==0:
00133 print '[WARNING]: no data, do nothing'
00134 return
00135 xpoints.sort()
00136 beginfo=''
00137 endinfo=''
00138 t=sum(rawydata['Delivered'])
00139 denomitor=1.0
00140 unitstring='$\mu$b$^{-1}$'
00141 if t>=1.0e3 and t<1.0e06:
00142 denomitor=1.0e3
00143 unitstring='nb$^{-1}$'
00144 elif t>=1.0e6 and t<1.0e9:
00145 denomitor=1.0e6
00146 unitstring='pb$^{-1}$'
00147 elif t>=1.0e9 and t<1.0e12:
00148 denomitor=1.0e9
00149 unitstring='fb$^{-1}$'
00150 elif t>=1.0e12 and t<1.0e15:
00151 denomitor=1.0e12
00152 unitstring='ab$^{-1}$'
00153
00154 for ylabel,yvalue in rawydata.items():
00155 ypoints[ylabel]=[]
00156 ytotal[ylabel]=sum(rawydata[ylabel])/denomitor
00157 for idx,fill in enumerate(xpoints):
00158 runlist=rawfillDict[fill]
00159 if idx==0:
00160 beginfo=str(fill)+':'+str(runlist[0])
00161 if idx==len(xpoints)-1:
00162 endinfo=str(fill)+':'+str(runlist[-1])
00163 xidx=rawxdata.index(max(runlist))
00164 ypoints[ylabel].append(sum(yvalue[0:xidx])/denomitor)
00165 ax=self.__fig.add_subplot(111)
00166 ax.set_xlabel(r'LHC Fill Number',position=(0.84,0))
00167 ax.set_ylabel(r'L '+unitstring,position=(0,0.9))
00168 ax.set_xbound(lower=xpoints[0],upper=xpoints[-1])
00169 if yscale=='linear':
00170 ax.set_yscale('linear')
00171 elif yscale=='log':
00172 ax.set_yscale('log')
00173 else:
00174 raise 'unsupported yscale ',yscale
00175 xticklabels=ax.get_xticklabels()
00176 majorLocator=matplotlib.ticker.LinearLocator( nticks )
00177 majorFormatter=matplotlib.ticker.FormatStrFormatter('%d')
00178
00179 ax.xaxis.set_major_locator(majorLocator)
00180 ax.xaxis.set_major_formatter(majorFormatter)
00181
00182 ax.grid(True)
00183 keylist=ypoints.keys()
00184 keylist.sort()
00185 legendlist=[]
00186 for ylabel in keylist:
00187 cl='k'
00188 if self.colormap.has_key(ylabel):
00189 cl=self.colormap[ylabel]
00190 ax.plot(xpoints,ypoints[ylabel],label=ylabel,color=cl,drawstyle='steps')
00191 legendlist.append(ylabel+' '+'%.2f'%(ytotal[ylabel])+' '+unitstring)
00192
00193
00194 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00195 ax.text(xpoints[0],1.025,beginfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00196 ax.text(xpoints[-1],1.025,endinfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00197 ax.legend(tuple(legendlist),loc='upper left')
00198 self.__fig.subplots_adjust(bottom=0.1,left=0.1)
00199
00200 def plotSumX_Time(self,rawxdata,rawydata,minTime,maxTime,hltpath='',nticks=6,annotateBoundaryRunnum=False,yscale='linear'):
00201 '''
00202 input:
00203 rawxdata runDict{runnumber:[delivered,recorded,recorded_hltpath]}
00204 rawydata {label:[rundata]}
00205 '''
00206 xpoints=[]
00207 ypoints={}
00208 ytotal={}
00209 xidx=[]
00210 runs=rawxdata.keys()
00211 runs.sort()
00212 for idx,run in enumerate(runs):
00213 xpoints.append(matplotlib.dates.date2num(rawxdata[run][0]))
00214 xidx.append(idx)
00215 if len(xpoints)==0:
00216 print '[WARNING]: no data, do nothing'
00217 return
00218 t=sum(rawydata['Delivered'])
00219 denomitor=1.0
00220 unitstring='$\mu$b$^{-1}$'
00221 if t>=1.0e3 and t<1.0e06:
00222 denomitor=1.0e3
00223 unitstring='nb$^{-1}$'
00224 elif t>=1.0e6 and t<1.0e9:
00225 denomitor=1.0e6
00226 unitstring='pb$^{-1}$'
00227 elif t>=1.0e9 and t<1.0e12:
00228 denomitor=1.0e9
00229 unitstring='fb$^{-1}$'
00230 elif t>=1.0e12 and t<1.0e15:
00231 denomitor=1.0e12
00232 unitstring='ab$^{-1}$'
00233
00234 for ylabel,yvalue in rawydata.items():
00235 ypoints[ylabel]=[]
00236 for i in xidx:
00237 ypoints[ylabel].append(sum(yvalue[0:i])/denomitor)
00238 ytotal[ylabel]=sum(yvalue)/denomitor
00239 ax=self.__fig.add_subplot(111)
00240 if yscale=='linear':
00241 ax.set_yscale('linear')
00242 elif yscale=='log':
00243 ax.set_yscale('log')
00244 else:
00245 raise 'unsupported yscale ',yscale
00246 dateFmt=matplotlib.dates.DateFormatter('%d/%m')
00247 majorLoc=matplotlib.ticker.LinearLocator(numticks=nticks)
00248 ax.xaxis.set_major_locator(majorLoc)
00249 minorLoc=matplotlib.ticker.LinearLocator(numticks=nticks*4)
00250 ax.xaxis.set_major_formatter(dateFmt)
00251 ax.set_xlabel(r'Date',position=(0.84,0))
00252 ax.set_ylabel(r'L '+unitstring,position=(0,0.9))
00253 ax.xaxis.set_minor_locator(minorLoc)
00254 ax.set_xbound(lower=xpoints[0],upper=xpoints[-1])
00255 xticklabels=ax.get_xticklabels()
00256 for tx in xticklabels:
00257 tx.set_horizontalalignment('left')
00258 ax.grid(True)
00259 keylist=ypoints.keys()
00260 keylist.sort()
00261 legendlist=[]
00262 for ylabel in keylist:
00263 cl='k'
00264 if self.colormap.has_key(ylabel):
00265 cl=self.colormap[ylabel]
00266 ax.plot(xpoints,ypoints[ylabel],label=ylabel,color=cl,drawstyle='steps')
00267 legendlist.append(ylabel+' '+'%.2f'%(ytotal[ylabel])+' '+unitstring)
00268
00269 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00270
00271
00272 if annotateBoundaryRunnum:
00273 ax.text(xpoints[0],1.025,str(runs[0]),transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00274 ax.text(xpoints[-1],1.025,str(runs[-1]),transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00275 yearStr=minTime.strftime('%Y')
00276 firstimeStr=minTime.strftime('%b %d %H:%M')
00277 lasttimeStr=maxTime.strftime('%b %d %H:%M')
00278 ax.set_title('Total Integrated Luminosity '+yearStr+' ('+firstimeStr+' UTC - '+lasttimeStr+' UTC)',size='small',family='fantasy')
00279 ax.legend(tuple(legendlist),loc='upper left')
00280 self.__fig.autofmt_xdate(bottom=0.18,rotation=0)
00281 self.__fig.subplots_adjust(bottom=0.1,left=0.1)
00282
00283 def plotPerdayX_Time(self,days,databyday,minTime,maxTime,boundaryInfo=[],nticks=6,annotateBoundaryRunnum=False,yscale='linear'):
00284 '''input
00285 databyday {'Delivered':[lumiperday]}
00286 boundaryInfo [[begintime,begininfo],[endtime,endinfo]]
00287 '''
00288 ax=self.__fig.add_subplot(111)
00289 t=max(databyday['Delivered'])
00290 minvar=min([x for x in databyday['Recorded'] if x>0])
00291 maxvalues={}
00292 keylist=databyday.keys()
00293 keylist.sort()
00294 for k in keylist:
00295 maxvalues[k]=max(databyday[k])
00296
00297 if yscale=='linear':
00298 ax.set_yscale('linear')
00299 elif yscale=='log':
00300 ax.set_yscale('log')
00301 for k in keylist:
00302 for i,v in enumerate(databyday[k]):
00303 if v<minvar:
00304 databyday[k][i]=minvar
00305 else:
00306 raise 'unsupported yscale ',yscale
00307 dateFmt=matplotlib.dates.DateFormatter('%d/%m')
00308 majorLoc=matplotlib.ticker.LinearLocator(numticks=nticks)
00309 minorLoc=matplotlib.ticker.LinearLocator(numticks=nticks*4)
00310 ax.xaxis.set_major_formatter(dateFmt)
00311 ax.set_xlabel(r'Date',position=(0.84,0))
00312 ax.xaxis.set_major_locator(majorLoc)
00313 ax.xaxis.set_minor_locator(minorLoc)
00314 xticklabels=ax.get_xticklabels()
00315 for tx in xticklabels:
00316 tx.set_horizontalalignment('right')
00317 ax.grid(True)
00318 legendlist=[]
00319
00320 denomitor=1.0
00321 unitstring='$\mu$b$^{-1}$'
00322 if t>=1.0e3 and t<1.0e06:
00323 denomitor=1.0e3
00324 unitstring='nb$^{-1}$'
00325 elif t>=1.0e6 and t<1.0e9:
00326 denomitor=1.0e6
00327 unitstring='pb$^{-1}$'
00328 elif t>=1.0e9 and t<1.0e12:
00329 denomitor=1.0e9
00330 unitstring='fb$^{-1}$'
00331 elif t>=1.0e12 and t<1.0e15:
00332 denomitor=1.0e12
00333 unitstring='ab$^{-1}$'
00334
00335 ax.set_ylabel(r'L '+unitstring,position=(0,0.9))
00336 for ylabel in keylist:
00337 cl='k'
00338 if self.colormap.has_key(ylabel):
00339 cl=self.colormap[ylabel]
00340 ax.plot(days,[y/denomitor for y in databyday[ylabel]],label=ylabel,color=cl,drawstyle='steps')
00341 legendlist.append(ylabel+' Max '+'%.2f'%(maxvalues[ylabel]/denomitor)+' '+unitstring)
00342 ax.legend(tuple(legendlist),loc='upper left')
00343 ax.set_xbound(lower=matplotlib.dates.date2num(minTime),upper=matplotlib.dates.date2num(maxTime))
00344 if annotateBoundaryRunnum:
00345 if len(boundaryInfo)!=0:
00346 begtime=boundaryInfo[0][0]
00347 beginfo=boundaryInfo[0][1]
00348 endtime=boundaryInfo[1][0]
00349 endinfo=boundaryInfo[1][1]
00350
00351 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00352 ax.text(matplotlib.dates.date2num(begtime),1.025,beginfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00353 ax.text(matplotlib.dates.date2num(endtime),1.025,endinfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00354 yearStr=minTime.strftime('%Y')
00355 firstimeStr=minTime.strftime('%b %d %H:%M')
00356 lasttimeStr=maxTime.strftime('%b %d %H:%M')
00357 ax.set_title('Integrated Luminosity/Day '+yearStr+' ('+firstimeStr+' UTC - '+lasttimeStr+' UTC)',size='small',family='fantasy')
00358 self.__fig.autofmt_xdate(bottom=0.18,rotation=0)
00359 self.__fig.subplots_adjust(bottom=0.18,left=0.1)
00360
00361 def plotPeakPerday_Time(self,daydict,minTime,maxTime,nticks=6,annotateBoundaryRunnum=False,yscale='linear'):
00362 '''
00363 Input: daydict={}#{day:[run,lsnum,instlumi]}
00364 '''
00365 xpoints=[]
00366 ypoints=[]
00367 legendlist=[]
00368 days=daydict.keys()
00369 days.sort()
00370 beginfo=str(daydict[days[0]][0])+':'+str(daydict[days[0]][1])
00371 endinfo=str(daydict[days[-1]][0])+':'+str(daydict[days[-1]][1])
00372 maxinfo=''
00373 ymax=0.0
00374 xmax=0
00375 minday=days[0]
00376 maxday=days[-1]
00377 minvar=0.1
00378 for day in range(minday,maxday+1):
00379 xpoints.append(day)
00380 if not daydict.has_key(day):
00381 ypoints.append(0.0)
00382 continue
00383 daymaxdata=daydict[day]
00384 ypoints.append(daymaxdata[2])
00385 if daydict[day][2]>ymax:
00386 ymax=daydict[day][2]
00387 xmax=day
00388 runmax=daydict[day][0]
00389 lsmax=daydict[day][1]
00390 maxinfo=str(runmax)+':'+str(lsmax)
00391 denomitor=1.0
00392 unitstring='$\mu$b$^{-1}$s$^{-1}$'
00393 if ymax>=1.0e3 and ymax<1.0e06:
00394 denomitor=1.0e3
00395 unitstring='nb$^{-1}$s$^{-1}$'
00396 elif ymax>=1.0e6 and ymax<1.0e9:
00397 denomitor=1.0e6
00398 unitstring='pb$^{-1}$s$^{-1}$'
00399 elif ymax>=1.0e9 and ymax<1.0e12:
00400 denomitor=1.0e9
00401 unitstring='fb$^{-1}$s$^{-1}$'
00402 elif ymax>=1.0e12 and ymax<1.0e15:
00403 denomitor=1.0e12
00404 unitstring='ab$^{-1}$s$^{-1}$'
00405
00406 ax=self.__fig.add_subplot(111)
00407 if yscale=='linear':
00408 ax.set_yscale('linear')
00409 elif yscale=='log':
00410 ax.set_yscale('log')
00411 for i,v in enumerate(ypoints):
00412 if v<minvar:
00413 ypoints[i]=minvar
00414 else:
00415 raise 'unsupported yscale ',yscale
00416 dateFmt=matplotlib.dates.DateFormatter('%d/%m')
00417 majorLoc=matplotlib.ticker.LinearLocator(numticks=nticks)
00418 minorLoc=matplotlib.ticker.LinearLocator(numticks=nticks*4)
00419 ax.xaxis.set_major_formatter(dateFmt)
00420 ax.set_xlabel(r'Date',position=(0.84,0))
00421 ax.set_ylabel(r'L '+unitstring,position=(0,0.9))
00422 ax.xaxis.set_major_locator(majorLoc)
00423 ax.xaxis.set_minor_locator(minorLoc)
00424 xticklabels=ax.get_xticklabels()
00425 for tx in xticklabels:
00426 tx.set_horizontalalignment('right')
00427 ax.grid(True)
00428 cl=self.colormap['Max Inst']
00429
00430
00431
00432
00433
00434 ax.plot(xpoints,[y/denomitor for y in ypoints],label='Max Inst',color=cl,drawstyle='steps')
00435 legendlist.append('Max Inst %.2f'%(ymax/denomitor)+' '+unitstring)
00436 ax.legend(tuple(legendlist),loc='upper left')
00437 ax.set_xbound(lower=matplotlib.dates.date2num(minTime),upper=matplotlib.dates.date2num(maxTime))
00438 if annotateBoundaryRunnum:
00439
00440 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00441 ax.text(xpoints[0],1.025,beginfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00442 ax.text(xpoints[-1],1.025,endinfo,transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00443 ax.annotate(maxinfo,xy=(xmax,ymax),xycoords='data',xytext=(0,13),textcoords='offset points',arrowprops=dict(facecolor='green',shrink=0.05),size='x-small',horizontalalignment='center',color='green',bbox=dict(facecolor='white'))
00444 yearStr=minTime.strftime('%Y')
00445 firstimeStr=minTime.strftime('%b %d %H:%M')
00446 lasttimeStr=maxTime.strftime('%b %d %H:%M')
00447 ax.set_title('Peak Luminosity/Day '+yearStr+' ('+firstimeStr+' UTC - '+lasttimeStr+' UTC)',size='small',family='fantasy')
00448 self.__fig.autofmt_xdate(bottom=0.18,rotation=0)
00449 self.__fig.subplots_adjust(bottom=0.1,left=0.1)
00450
00451 def plotInst_RunLS(self,rawxdata,rawydata,nticks=6):
00452 '''
00453 Input: rawxdata [run,fill,norbit,starttime,stoptime,totalls,ncmsls]
00454 rawydata {label:[instlumi]}
00455 '''
00456 runnum=rawxdata[0]
00457 fill=rawxdata[1]
00458 norbit=rawxdata[2]
00459 starttime=rawxdata[3]
00460 stoptime=rawxdata[4]
00461 totalls=rawxdata[-2]
00462 ncmsls=rawxdata[-1]
00463 peakinst=max(rawydata['Delivered'])
00464 lslength=float(norbit)*3564*25.0e-9
00465 totaldelivered=sum(rawydata['Delivered'])*lslength
00466 totalrecorded=sum(rawydata['Recorded'])*lslength
00467 xpoints=range(1,totalls+1)
00468
00469 ypoints={}
00470 ymax={}
00471 for ylabel,yvalue in rawydata.items():
00472 ypoints[ylabel]=yvalue
00473 ymax[ylabel]=max(yvalue)
00474 left=0.15
00475 width=0.7
00476 bottom=0.1
00477 height=0.65
00478 bottom_h=bottom+height
00479 rect_scatter=[left,bottom,width,height]
00480 rect_table=[left,bottom_h,width,0.25]
00481
00482 nullfmt=matplotlib.ticker.NullFormatter()
00483 nullloc=matplotlib.ticker.NullLocator()
00484 axtab=self.__fig.add_axes(rect_table,frameon=False)
00485 axtab.set_axis_off()
00486 axtab.xaxis.set_major_formatter(nullfmt)
00487 axtab.yaxis.set_major_formatter(nullfmt)
00488 axtab.xaxis.set_major_locator(nullloc)
00489 axtab.yaxis.set_major_locator(nullloc)
00490
00491 ax=self.__fig.add_axes(rect_scatter)
00492
00493 majorLoc=matplotlib.ticker.LinearLocator(numticks=nticks)
00494 minorLoc=matplotlib.ticker.LinearLocator(numticks=nticks*4)
00495 ax.set_xlabel(r'LS',position=(0.96,0))
00496 ax.set_ylabel(r'L $\mu$b$^{-1}$s$^{-1}$',position=(0,0.9))
00497 ax.xaxis.set_major_locator(majorLoc)
00498 ax.xaxis.set_minor_locator(minorLoc)
00499 ax.set_xbound(lower=xpoints[0],upper=xpoints[-1])
00500 xticklabels=ax.get_xticklabels()
00501 for tx in xticklabels:
00502 tx.set_horizontalalignment('right')
00503 ax.grid(True)
00504 keylist=ypoints.keys()
00505 keylist.sort()
00506 legendlist=[]
00507
00508 for ylabel in keylist:
00509 cl='k'
00510 if self.colormap.has_key(ylabel):
00511 cl=self.colormap[ylabel]
00512 ax.plot(xpoints,ypoints[ylabel],'.',label=ylabel,color=cl)
00513 legendlist.append(ylabel)
00514
00515 ax.axvline(xpoints[ncmsls-1],color='green',linewidth=0.2)
00516
00517 denomitor=1.0
00518 unitstring='/$\mu$b'
00519 if totaldelivered>=1.0e3 and totaldelivered<1.0e06:
00520 denomitor=1.0e3
00521 unitstring='/nb'
00522 elif totaldelivered>=1.0e6 and totaldelivered<1.0e9:
00523 denomitor=1.0e6
00524 unitstring='/pb'
00525 elif totaldelivered>=1.0e9 and totaldelivered<1.0e12:
00526 denomitor=1.0e9
00527 unitstring='/fb'
00528 elif totaldelivered>=1.0e12 and totaldelivered<1.0e15:
00529 denomitor=1.0e12
00530 unitstring='/ab'
00531 colLabels=('run','fill','max inst(/$\mu$b/s)','delivered('+unitstring+')','recorded('+unitstring+')')
00532 cellText=[[str(runnum),str(fill),'%.3f'%(peakinst),'%.3f'%(totaldelivered/denomitor),'%.3f'%(totalrecorded/denomitor)]]
00533
00534 sumtable=axtab.table(cellText=cellText,colLabels=colLabels,colWidths=[0.12,0.1,0.27,0.27,0.27],cellLoc='center',loc='center')
00535 trans=matplotlib.transforms.BlendedGenericTransform(ax.transData,ax.transAxes)
00536 axtab.add_table(sumtable)
00537
00538 ax.text(xpoints[0],1.02,starttime[0:17],transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00539 ax.text(xpoints[ncmsls-1],1.02,stoptime[0:17],transform=trans,horizontalalignment='left',size='x-small',color='green',bbox=dict(facecolor='white'))
00540 ax.legend(tuple(legendlist),loc='upper right',numpoints=1)
00541
00542 def drawHTTPstring(self):
00543 self.__canvas=CanvasBackend(self.__fig)
00544 cherrypy.response.headers['Content-Type']='image/png'
00545 buf=StringIO()
00546 self.__canvas.print_png(buf)
00547 return buf.getvalue()
00548
00549 def drawPNG(self,filename):
00550 self.__canvas=CanvasBackend(self.__fig)
00551 self.__canvas.print_figure(filename)
00552
00553 def drawInteractive(self):
00554 if batchonly:
00555 print 'interactive mode is not available for your setup, exit'
00556 sys.exit()
00557 self.__canvas=CanvasBackend(self.__fig,master=root)
00558 self.__canvas.show()
00559 self.__canvas.get_tk_widget().pack(side=Tk.TOP,fill=Tk.BOTH,expand=1)
00560 toolbar=NavigationToolbar2TkAgg(self.__canvas,root)
00561 toolbar.update()
00562 self.__canvas._tkcanvas.pack(side=Tk.TOP,fill=Tk.BOTH,expand=1)
00563 button = Tk.Button(master=root,text='Quit',command=sys.exit)
00564 button.pack(side=Tk.BOTTOM)
00565 Tk.mainloop()
00566 if __name__=='__main__':
00567 fig=Figure(figsize=(5,5),dpi=100)
00568 a=fig.add_subplot(111)
00569 t=numpy.arange(0.0,3.0,0.01)
00570 s=numpy.sin(2*numpy.pi*t)
00571 a.plot(t,s)
00572 m=matplotRender(fig)
00573 m.drawPNG('testmatplotrender.png')
00574 m.drawInteractive()
00575
1.7.3