dirs = subprocess.check_output(['find . -iname "*autogen*" | sort -k1.13'], shell=True).split('\n')[:-1] numprots = [1e9, 1e8, 1e7, 1e6] for typ in typs: ctsetsets = [] for line, numprot in zip( dirs, [item for item in numprots for i in range(len(typs) / 4)]): for haha in ['iba', 'ipnl']: if haha + 'lyso' in line and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ, addnoise=addnoise)) if haha + 'zinv' in line and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ, addnoise=addnoise)) assert (len(ctsetsets) == 4) megaplot(ctsetsets, 'PMMA_phantom') print 'Mean detection yield in', typ, 'study over', sum( [ctset['totnprim'] for ctset in ctsetsets]), 'primaries in', sum([ ctset['nreal'] for ctset in ctsetsets
########################################################################################################### # BOTTOM ROW IBA f, ((ax4, ax5, ax6), (ax1, ax2, ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2( ax1, auger.getctset(1e9, 'fromclus-sorted/spots-iba/run.k0Zs', 'fromclus-sorted/spots-iba/run.Y1My', typ, manualshift=volume_offset)) ax1.set_title('KES, Spot A,\nyield: ' + plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]') yield_av = auger.plot_all_ranges_2( ax2, auger.getctset(1e9, 'fromclus-sorted/spots-iba/run.tsUO', 'fromclus-sorted/spots-iba/run.TUEA', typ, manualshift=volume_offset)) ax2.set_title('KES, Spot B,\nyield: ' + plot.sn(yield_av), fontsize=8) ax2.set_xlabel('Position [mm]')
########################################################################################################### # BOTTOM ROW IBA f, ((ax4, ax5, ax6), (ax1, ax2, ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2(ax1, auger.getctset( 840964615, 'fromclus-sorted/layers-beide/run.e8ai', 'fromclus-sorted/layers-beide/run.96ra', typ, manualshift=volume_offset), firstcolor='steelblue', secondcolor=None) yield_av = auger.plot_all_ranges_2(ax1, auger.getctset( 848710335, 'fromclus-sorted/layers-beide/run.m4RU', 'fromclus-sorted/layers-beide/run.tLiY', typ, manualshift=volume_offset), firstcolor='seagreen', secondcolor=None) ax1.set_title('KES, Spot A,\nyield: ' + plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]')
#f.savefig('spotplot-sums.pdf', bbox_inches='tight') #plot.close('all') ################################################################################ #typ='ipnl-auger-tof-1.root' #typ='ipnl-auger-notof-1.root' #typ='iba-auger-tof-3.root' typ='iba-auger-notof-3.root' #nieuwe sums. distal layer #22 , 4 , #4 : 65802598.6018 , 7 : 88235302.6706 , 10 : 67298112.2064 , 43 : 64073566.2641 , ctset_4 = auger.getctset(65802598,'run.4Zh8','run.8Yoh',typ) ctset_7 = auger.getctset(88235302,'run.MjnN','run.a5rv',typ) ctset_10 = auger.getctset(67298112,'run.XXMy','run.btzm',typ)#XXMy + 3x HyIv ctset_43 = auger.getctset(64073566,'run.iohj','run.hDu1',typ) ctset_sum_0 = auger.sumctset('sum',ctset_4,ctset_7,ctset_10,ctset_43) f, ((ax1,ax2,ax3),(ax4,ax5,ax6)) = plot.subplots(nrows=2, ncols=3, sharex=False, sharey=False) auger.plotrange(ax1,ctset_4) auger.plotrange(ax2,ctset_7) auger.plotrange(ax3,ctset_10) auger.plotrange(ax4,ctset_43) ax5.axis('off') auger.plotrange(ax6,ctset_sum_0)
'ipnl4mm-auger-tof-1.root', 'iba-auger-tof-1.root', 'ipnl-auger-notof-1.root', 'ipnl4mm-auger-notof-1.root', 'iba-auger-notof-1.root', 'ipnl-auger-tof-3.root', 'ipnl4mm-auger-tof-3.root', 'iba-auger-tof-3.root', 'ipnl-auger-notof-3.root', 'ipnl4mm-auger-notof-3.root', 'iba-auger-notof-3.root'] # typs=['ipnl-auger-tof-1.root','iba-auger-tof-1.root','ipnl-auger-notof-3.root','iba-auger-notof-3.root'] dirs = subprocess.check_output(['find . -iname "*autogen*" | sort -k1.13'],shell=True).split('\n')[:-1] numprots = [1e9,1e8,1e7,1e6] for typ in typs: ctsetsets = [] for line,numprot in zip(dirs,[item for item in numprots for i in range(len(typs)/4)]): for haha in ['iba','ipnl','ipnl4mm']: if haha+'lyso' in line and haha+'-' in typ: print (haha,line,typ) ctsetsets.append( auger.getctset(numprot,line[2:10],line[2:10],typ) ) if haha+'zinv' in line and haha+'-' in typ: print (haha,line,typ) ctsetsets.append( auger.getctset(numprot,line[2:10],line[2:10],typ) ) assert(len(ctsetsets)==4) megaplot(ctsetsets,'PMMA_phantom') print 'Mean detection yield in',typ,'study over',sum([ctset['totnprim'] for ctset in ctsetsets]),'primaries in',sum([ctset['nreal'] for ctset in ctsetsets]),'realisations:',sum([ctset['detyieldmu'] for ctset in ctsetsets])
y=1.08) #plt.legend()#shadow = True,frameon = True,fancybox = True,ncol = 1,fontsize = 'x-small',loc = 'lower right') #plt.tight_layout(rect = [-0.1, 0.0, 1.0, 1.1])#L,B,R,T plt.savefig(studyname + '-' + typ + '-FOP-dist.pdf') #, bbox_inches='tight') plt.close('all') ############################################################################################# # TODO add pgemissions plots. for typ in typs: ctsetsets = [] ctsetsets.append(auger.getctset(1e9, '1e9', '1e9', typ)) ctsetsets.append(auger.getctset(1e8, '1e8', '1e8', typ)) ctsetsets.append(auger.getctset(1e7, '1e7', '1e7', typ)) ctsetsets.append(auger.getctset(1e6, '1e6', '1e6', typ)) #ctsetsets.append( auger.getctset(1e9,'run.3poV','run.wucX',typ) ) #ctsetsets.append( auger.getctset(1e8,'run.1XRe','run.lTdI',typ) ) #ctsetsets.append( auger.getctset(1e7,'run.oPE7','run.RWkp',typ) ) #ctsetsets.append( auger.getctset(1e6,'run.7bG6','run.pijb',typ) ) megaplot(ctsetsets, 'waterbox_redo') print 'Mean detection yield in', typ, 'study over', sum( [ctset['totnprim'] for ctset in ctsetsets]), 'primaries in', sum([ ctset['nreal'] for ctset in ctsetsets ]), 'realisations:', sum([ctset['detyieldmu'] for ctset in ctsetsets])
# BOTTOM ROW IBA f, ((ax4, ax5, ax6), (ax1, ax2, ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-tof-1.root' typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2( ax1, auger.getctset(1e9, 'run.o5zC', 'run.o5zC', typ, manualshift=volume_offset, addnoise=addnoise)) ax1.set_title('KES, 1e9,\nyield: ' + plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]') yield_av = auger.plot_all_ranges_2( ax2, auger.getctset(1e8, 'run.fFpk', 'run.fFpk', typ, manualshift=volume_offset, addnoise=addnoise)) ax2.set_title('KES, 1e8,\nyield: ' + plot.sn(yield_av), fontsize=8) ax2.set_xlabel('Position [mm]')
#ctsetsets.append( auger.getctset(1e9,'run.TtIT','run.SmHn',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e8,'run.t4Fb','run.w9Te',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(27200000,'run.YtND','run.SQy4',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e7,'run.WQUJ','run.JJQQ',typ,manualshift=shift) ) #megaplot(ctsetsets,'spot40',emisfops=None,labels=["$10^9$","$10^8$","$2.7\cdot10^7$","$10^7$"]) #shift = 22.20-29.04 #ctsetsets = [] #ctsetsets.append( auger.getctset(1e9,'run.EYBe','run.6HvZ',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e8,'run.W3sR','run.q7v2',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(47300000,'run.R9KU','run.rTUp',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e7,'run.1jXf','run.8NDz',typ,manualshift=shift) ) #megaplot(ctsetsets,'spot61',emisfops=None,labels=["$10^9$","$10^8$","$4.7\cdot10^7$","$10^7$"]) ctsetsets = [] ctsetsets.append( auger.getctset(840964615,'run.CKCH','run.lrnj',typ) )#elay ctsetsets.append( auger.getctset(848710335,'run.3At2','run.Ydep',typ) )#geolay megaplot(ctsetsets,'layer29',emisfops=None,labels=['Iso-Energy Layer','Iso-Depth Layer'],axlabel='Grouping Method') ctsetsets = [] ctsetsets.append( auger.getctset(1068263318,'run.7coj','run.ptEe',typ) )#elay, same as elay61 ctsetsets.append( auger.getctset(1071596684,'run.KXRm','run.jTj9',typ) )#geolay megaplot(ctsetsets,'layer40',emisfops=None,labels=['Iso-Energy Layer','Iso-Depth Layer'],axlabel='Grouping Method') ctsetsets = [] ctsetsets.append( auger.getctset(1068263318,'run.7coj','run.ptEe',typ,manualshift=15.37-19.00) )#elay ctsetsets.append( auger.getctset(979533764,'run.8aMd','run.wM5z',typ,manualshift=18.57-23.51) )#geolay megaplot(ctsetsets,'layer61',emisfops=None,labels=['Iso-Energy Layer','Iso-Depth Layer'],axlabel='Grouping Method') #############################################################################################
from scipy.ndimage.filters import gaussian_filter ########################################################################################################### #volume_offset=-141.59+7.96#spot sources volume_offset=150-141.59+7.96#spot sources ########################################################################################################### # BOTTOM ROW IBA f, ((ax4,ax5,ax6),(ax1,ax2,ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2(ax1, auger.getctset(1e9,'fromclus-sorted/spots-iba/run.k0Zs','fromclus-sorted/spots-iba/run.Y1My',typ,manualshift=volume_offset) ) ax1.set_title('KES, Spot A,\nyield: '+plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]') yield_av = auger.plot_all_ranges_2(ax2, auger.getctset(1e9,'fromclus-sorted/spots-iba/run.tsUO','fromclus-sorted/spots-iba/run.TUEA',typ,manualshift=volume_offset) ) ax2.set_title('KES, Spot B,\nyield: '+plot.sn(yield_av), fontsize=8) ax2.set_xlabel('Position [mm]') yield_av = auger.plot_all_ranges_2(ax3, auger.getctset(1e9,'fromclus-sorted/spots-iba/run.tf1u','fromclus-sorted/spots-iba/run.cDeA',typ,manualshift=volume_offset) ) ax3.set_title('KES, Spot C,\nyield: '+plot.sn(yield_av), fontsize=8) ######## TopRow IPNL typ = 'ipnl-auger-tof-1.root' #shift = 13.76-19.44
#volume_offset=-141.59+7.96#spot sources volume_offset=0 addnoise = False #addnoise = 'onlynoise' ########################################################################################################### # BOTTOM ROW IBA f, ((ax4,ax5,ax6),(ax1,ax2,ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-tof-1.root' typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2(ax1, auger.getctset(1e9,'run.o5zC','run.o5zC',typ,manualshift=volume_offset,addnoise=addnoise) ) ax1.set_title('KES, 1e9,\nyield: '+plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]') yield_av = auger.plot_all_ranges_2(ax2, auger.getctset(1e8,'run.fFpk','run.fFpk',typ,manualshift=volume_offset,addnoise=addnoise) ) ax2.set_title('KES, 1e8,\nyield: '+plot.sn(yield_av), fontsize=8) ax2.set_xlabel('Position [mm]') yield_av = auger.plot_all_ranges_2(ax3, auger.getctset(1e7,'run.Gfu4','run.Gfu4',typ,manualshift=volume_offset,addnoise=addnoise) ) ax3.set_title('KES, 1e7\nyield: '+plot.sn(yield_av), fontsize=8) ######## TopRow IPNL typ = 'ipnl-auger-tof-1.root' typ = 'ipnl-auger-notof-3.root'
#f.savefig('spotplot-sums.pdf', bbox_inches='tight') #plot.close('all') ################################################################################ #typ='ipnl-auger-tof-1.root' #typ='ipnl-auger-notof-1.root' #typ='iba-auger-tof-3.root' typ = 'iba-auger-notof-3.root' #nieuwe sums. distal layer #22 , 4 , #4 : 65802598.6018 , 7 : 88235302.6706 , 10 : 67298112.2064 , 43 : 64073566.2641 , ctset_4 = auger.getctset(65802598, 'run.4Zh8', 'run.8Yoh', typ) ctset_7 = auger.getctset(88235302, 'run.MjnN', 'run.a5rv', typ) ctset_10 = auger.getctset(67298112, 'run.XXMy', 'run.btzm', typ) #XXMy + 3x HyIv ctset_43 = auger.getctset(64073566, 'run.iohj', 'run.hDu1', typ) ctset_sum_0 = auger.sumctset('sum', ctset_4, ctset_7, ctset_10, ctset_43) f, ((ax1, ax2, ax3), (ax4, ax5, ax6)) = plot.subplots(nrows=2, ncols=3, sharex=False, sharey=False) auger.plotrange(ax1, ctset_4) auger.plotrange(ax2, ctset_7) auger.plotrange(ax3, ctset_10)
'ipnl-auger-tof-1.root', 'iba-auger-tof-1.root', 'ipnl-auger-notof-1.root', 'iba-auger-notof-1.root', 'ipnl-auger-tof-3.root', 'iba-auger-tof-3.root', 'ipnl-auger-notof-3.root', 'iba-auger-notof-3.root'] # typs=['ipnl-auger-tof-1.root','iba-auger-tof-1.root','ipnl-auger-notof-3.root','iba-auger-notof-3.root'] dirs = subprocess.check_output(['find . -iname "*autogen*" | sort -k1.13'],shell=True).split('\n')[:-1] numprots = [1e9,1e8,1e7,1e6] for typ in typs: ctsetsets = [] for line,numprot in zip(dirs,[item for item in numprots for i in range(len(typs)/4)]): for haha in ['iba','ipnl']: if haha+'lyso' in line and haha+'-' in typ: print (haha,line,typ) ctsetsets.append( auger.getctset(numprot,line[2:10],line[2:10],typ,addnoise=addnoise) ) if haha+'zinv' in line and haha+'-' in typ: print (haha,line,typ) ctsetsets.append( auger.getctset(numprot,line[2:10],line[2:10],typ,addnoise=addnoise) ) assert(len(ctsetsets)==4) megaplot(ctsetsets,'PMMA_phantom') print 'Mean detection yield in',typ,'study over',sum([ctset['totnprim'] for ctset in ctsetsets]),'primaries in',sum([ctset['nreal'] for ctset in ctsetsets]),'realisations:',sum([ctset['detyieldmu'] for ctset in ctsetsets]) tableio.print2d(resultstable) tableio.write(resultstable,'resultstable.tsv')
#############gate_run_submit_cluster_nomove.sh mac/main-int7rpct.mac 10 #############gate_run_submit_cluster_nomove.sh mac/main-int6ct.mac 10 #############gate_run_submit_cluster_nomove.sh mac/main-int6rpct.mac 10 #############xTcG #############b2Aj #############bfrX #############rOx1 #############41VE #############NE7B #############yjzw #############wfmx #typ='ipnl' typ='iba' ctset_int_6 = auger.getctset(1e6,'run.yjzw','run.wfmx',typ) ctset_int_7 = auger.getctset(1e7,'run.41VE','run.NE7B',typ) ctset_int_8 = auger.getctset(1e8,'run.bfrX','run.rOx1',typ) ctset_int_9 = auger.getctset(1e9,'run.xTcG','run.b2Aj',typ) f, ((ax1,ax2),(ax3,ax4)) = plot.subplots(nrows=2, ncols=2, sharex=False, sharey=False) auger.plotrange(ax1,ctset_int_9) auger.plotrange(ax2,ctset_int_8) auger.plotrange(ax3,ctset_int_7) auger.plotrange(ax4,ctset_int_6) f.subplots_adjust(hspace=.5) ax1.set_xlim(-40,40) ax2.set_xlim(-40,40) ax3.set_xlim(-40,40)
pgemis_smooth_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y_smooth) pgemis_smooth_rpctfo=auger.get_fop(pgemis_rpct_x,pgemis_rpct_y_smooth) pgemis_ct_y_smooth20 = gaussian_filter(pgemis_ct_y, sigma=20) pgemis_ct_y_smooth20 = pgemis_ct_y_smooth20/pgemis_ct_y_smooth20.max() pgemis_smooth20_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y_smooth20) ########################################################################################################### #detection in local frame, remove shift. coords already centered as zero, so can just add the shift det_offset = -17.31 ipnl = auger.getctset(1e9,'fromcluster/run.8ZQJ','fromcluster/run.ahDK','ipnl-auger-tof-1.root') pgipnl_ct_x = np.array(ipnl['ct']['x']) pgipnl_ct_x = pgipnl_ct_x+det_offset pgipnl_ct_y = np.array(ipnl['ct']['av']) pgipnl_ct_y = pgipnl_ct_y-(pgipnl_ct_y[pgipnl_ct_y < np.percentile(pgipnl_ct_y, 25)].mean()) #remove floor pgipnl_ct_y = pgipnl_ct_y/pgipnl_ct_y.max() #scale pgipnl_rpct_x = np.array(ipnl['rpct']['x']) pgipnl_rpct_x = pgipnl_rpct_x+det_offset pgipnl_rpct_y = np.array(ipnl['rpct']['av']) pgipnl_rpct_y = pgipnl_rpct_y-(pgipnl_rpct_y[pgipnl_rpct_y < np.percentile(pgipnl_rpct_y, 25)].mean()) #remove floor pgipnl_rpct_y = pgipnl_rpct_y/pgipnl_rpct_y.max() #scale pgipnl_ctfo = np.mean(ipnl['ct']['falloff'])+det_offset pgipnl_rpctfo = np.mean(ipnl['rpct']['falloff'])+det_offset
'ipnl-auger-tof-3.root', 'ipnl4mm-auger-tof-3.root', 'iba-auger-tof-3.root', 'ipnl-auger-notof-3.root', 'ipnl4mm-auger-notof-3.root', 'iba-auger-notof-3.root' ] # typs=['ipnl-auger-tof-1.root','iba-auger-tof-1.root','ipnl-auger-notof-3.root','iba-auger-notof-3.root'] dirs = subprocess.check_output(['find . -iname "*autogen*" | sort -k1.13'], shell=True).split('\n')[:-1] numprots = [1e9, 1e8, 1e7, 1e6] for typ in typs: ctsetsets = [] for line, numprot in zip( dirs, [item for item in numprots for i in range(len(typs) / 4)]): for haha in ['iba', 'ipnl', 'ipnl4mm']: if haha + 'lyso' in line and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ)) if haha + 'zinv' in line and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ)) assert (len(ctsetsets) == 4) megaplot(ctsetsets, 'PMMA_phantom') print 'Mean detection yield in', typ, 'study over', sum( [ctset['totnprim'] for ctset in ctsetsets]), 'primaries in', sum([ ctset['nreal'] for ctset in ctsetsets ]), 'realisations:', sum([ctset['detyieldmu'] for ctset in ctsetsets])
########################################################################################################### #volume_offset=-141.59+7.96#spot sources volume_offset=150-141.59+7.96#spot sources ########################################################################################################### # BOTTOM ROW IBA f, ((ax4,ax5,ax6),(ax1,ax2,ax3)) = plot.subplots(nrows=2, ncols=3, sharex=True, sharey=False) typ = 'iba-auger-notof-3.root' yield_av = auger.plot_all_ranges_2(ax1,auger.getctset(840964615,'fromclus-sorted/layers-beide/run.e8ai','fromclus-sorted/layers-beide/run.96ra',typ,manualshift=volume_offset),firstcolor='steelblue',secondcolor=None) yield_av = auger.plot_all_ranges_2(ax1,auger.getctset(848710335,'fromclus-sorted/layers-beide/run.m4RU','fromclus-sorted/layers-beide/run.tLiY',typ,manualshift=volume_offset),firstcolor='seagreen',secondcolor=None) ax1.set_title('KES, Spot A,\nyield: '+plot.sn(yield_av), fontsize=8) ax1.set_ylabel('PG detected [counts]') yield_av = auger.plot_all_ranges_2(ax2,auger.getctset(1068263318,'fromclus-sorted/layers-beide/run.E2tF','fromclus-sorted/layers-beide/run.qE8o',typ,manualshift=volume_offset),firstcolor='steelblue',secondcolor=None) yield_av = auger.plot_all_ranges_2(ax2,auger.getctset(1071596684,'fromclus-sorted/layers-beide/run.r48i','fromclus-sorted/layers-beide/run.c0rg',typ,manualshift=volume_offset),firstcolor='seagreen',secondcolor=None) ax2.set_title('KES, Spot B,\nyield: '+plot.sn(yield_av), fontsize=8) ax2.set_xlabel('Position [mm]') yield_av = auger.plot_all_ranges_2(ax3,auger.getctset(1068263318,'fromclus-sorted/layers-beide/run.E2tF','fromclus-sorted/layers-beide/run.qE8o',typ,manualshift=volume_offset),firstcolor='steelblue',secondcolor=None) yield_av = auger.plot_all_ranges_2(ax3,auger.getctset(979533764,'fromclus-sorted/layers-beide/run.c4UF','fromclus-sorted/layers-beide/run.bj2R',typ,manualshift=volume_offset),firstcolor='seagreen',secondcolor=None) ax3.set_title('KES, Spot C,\nyield: '+plot.sn(yield_av), fontsize=8) ######## TopRow IPNL
pgemis_rpct_y_smooth = gaussian_filter(pgemis_rpct_y, sigma=smooth_param) pgemis_rpct_y_smooth = pgemis_rpct_y_smooth / pgemis_rpct_y_smooth.max() #pgemis_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y) pgemis_rpctfo = auger.get_fop(pgemis_rpct_x, pgemis_rpct_y) #pgemis_smooth_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y_smooth) pgemis_smooth_rpctfo = auger.get_fop(pgemis_rpct_x, pgemis_rpct_y_smooth) ########################################################################################################### #detection in local frame, remove shift. coords already centered as zero, so can just add the shift det_offset = 13.61 ipnl = auger.getctset(1e9, 'fromcluster/run.13px', 'fromcluster/run.13px', 'ipnl-auger-tof-1.root') #CT IS NONSENSE DATA #pgipnl_ct_x = np.array(ipnl['ct']['x']) #pgipnl_ct_x = pgipnl_ct_x+det_offset #pgipnl_ct_y = np.array(ipnl['ct']['av']) #pgipnl_ct_y = pgipnl_ct_y-(pgipnl_ct_y[pgipnl_ct_y < np.percentile(pgipnl_ct_y, 25)].mean()) #remove floor #pgipnl_ct_y = pgipnl_ct_y/pgipnl_ct_y.max() #scale pgipnl_rpct_x = np.array(ipnl['rpct']['x']) pgipnl_rpct_x = pgipnl_rpct_x + det_offset #pgipnl_rpct_y = np.array(ipnl['rpct']['av']) pgipnl_rpct_y = np.array(ipnl['rpct']['data'][0]) pgipnl_rpct_y = pgipnl_rpct_y - ( pgipnl_rpct_y[pgipnl_rpct_y < np.percentile(pgipnl_rpct_y, 25)].mean() ) #remove floor pgipnl_rpct_y = pgipnl_rpct_y / pgipnl_rpct_y.max() #scale
#ctsetsets.append( auger.getctset(1e6,'run.rFN5','run.jUPf',typ) )# 5 , 0 # AGJb , :done #megaplot(ctsetsets,'spot61',[[6.715,20.58]]) #ctsetsets.append( auger.getctset(1e9,'run.9WZ0','run.xEMN',typ) )# #ctsetsets.append( auger.getctset(1e8,'run.E3So','run.okUi',typ) )# #ctsetsets.append( auger.getctset(1e7,'run.aNrj','run.GERe',typ) )# , 1 # , w9gm :done #ctsetsets.append( auger.getctset(1e6,'run.7OvR','run.ykAn',typ) )# #megaplot(ctsetsets,'spot29',[[-1.75,0.291]]) #ctsetsets.append( auger.getctset(1e9,'run.AuZu','run.ECUY',typ) )# 2 , 1 # vWKg , wS3i :done #ctsetsets.append( auger.getctset(1e8,'run.XkoP','run.cLDV',typ) )# , 6 # , kDxT :done #ctsetsets.append( auger.getctset(1e7,'run.V4ER','run.Hhup',typ) )# #ctsetsets.append( auger.getctset(1e6,'run.zE43','run.MUoq',typ) )# 7 , # EdQf , :done #megaplot(ctsetsets,'spot40',[[-10.6,-7.59]]) ctsetsets.append( auger.getctset(1e9,'run.kVk7','run.iias',typ) ) ctsetsets.append( auger.getctset(1e8,'run.cj4U','run.RWsd',typ) ) ctsetsets.append( auger.getctset(1e7,'run.ngMk','run.Ho8b',typ) ) ctsetsets.append( auger.getctset(1e6,'run.WbDj','run.f9cL',typ) ) megaplot(ctsetsets,'waterbox') #ctsetsets.append( auger.getctset(1e9,'run.1vRP','run.KvuV',typ) )# , 11 # , g4RC :done #ctsetsets.append( auger.getctset(1e8,'run.SwIj','run.XYSQ',typ) )# 50 , # SwIj , :done #ctsetsets.append( auger.getctset(1e7,'run.UAJZ','run.ebjM',typ) ) #ctsetsets.append( auger.getctset(1e6,'run.BPnu','run.q7Vn',typ) ) #megaplot(ctsetsets,'waterboxshifted') #compare 144MeV against shifted 139mev #ctsetsets.append( auger.getctset(1e9,'run.LswJ','run.KvuV',typ) ) #ctsetsets.append( auger.getctset(1e8,'run.IdLD','run.XYSQ',typ) ) #ctsetsets.append( auger.getctset(1e7,'run.pDRM','run.ebjM',typ) )
pgemis_rpct_y_smooth = gaussian_filter(pgemis_rpct_y, sigma=smooth_param) pgemis_rpct_y_smooth = pgemis_rpct_y_smooth / pgemis_rpct_y_smooth.max() pgemis_ctfo = auger.get_fop(pgemis_ct_x, pgemis_ct_y) pgemis_rpctfo = auger.get_fop(pgemis_rpct_x, pgemis_rpct_y) pgemis_smooth_ctfo = auger.get_fop(pgemis_ct_x, pgemis_ct_y_smooth) pgemis_smooth_rpctfo = auger.get_fop(pgemis_rpct_x, pgemis_rpct_y_smooth) ########################################################################################################### #detection in local frame, remove shift. coords already centered as zero, so can just add the shift det_offset = -17.31 ipnl = auger.getctset(1e9, 'fromcluster/run.8ZQJ', 'fromcluster/run.ahDK', 'ipnl-auger-tof-1.root') pgipnl_ct_x = np.array(ipnl['ct']['x']) pgipnl_ct_x = pgipnl_ct_x + det_offset pgipnl_ct_y = np.array(ipnl['ct']['av']) pgipnl_ct_y = pgipnl_ct_y - ( pgipnl_ct_y[pgipnl_ct_y < np.percentile(pgipnl_ct_y, 25)].mean() ) #remove floor pgipnl_ct_y = pgipnl_ct_y / pgipnl_ct_y.max() #scale pgipnl_rpct_x = np.array(ipnl['rpct']['x']) pgipnl_rpct_x = pgipnl_rpct_x + det_offset pgipnl_rpct_y = np.array(ipnl['rpct']['av']) pgipnl_rpct_y = pgipnl_rpct_y - ( pgipnl_rpct_y[pgipnl_rpct_y < np.percentile(pgipnl_rpct_y, 25)].mean() ) #remove floor
dirs = subprocess.check_output(['find . -iname "*autogen*" | sort -k1.13'], shell=True).split('\n')[:-1] numprots = [1e9, 1e9, 1e8, 1e8, 1e7, 1e7] typ = None for dirr, numprot in zip(dirs, numprots): if numprot != 1e9: continue ctsetsets = [] if 'iba' in dirr: typ = 'iba-perdet.root' ctsetsets.append( auger.getctset(numprot, dirr[2:10], dirr[2:10], typ, addnoise=addnoise)) if 'ipnl' in dirr: typ = 'ipnl-perdet.root' ctsetsets.append( auger.getctset(numprot, dirr[2:10], dirr[2:10], typ, addnoise=addnoise)) megaplot(ctsetsets, 'PMMA_phantom') print 'Mean detection yield in', typ, 'study over', sum( [ctset['totnprim'] for ctset in ctsetsets]), 'primaries in', sum([
print(dirs) numprots = [1e9, 1e9] for typ in typs: ctsetsets = [] for line, numprot in zip( dirs, [item for item in numprots for i in range(len(typs) / len(numprots))]): for haha in ['iba', 'ipnl']: if (haha + 'lyso' in line) and haha + '-' in typ: print(haha, line, typ, numprot) ctsetsets.append( auger.getctset(numprot, line[2:14], None, typ, addnoise=addnoise, precolli=precolli)) PHYSDET_PROFILE_IPNL = ctsetsets[-1]['ct']['av'] if haha + 'zinv' in line and haha + '-' in typ: print(haha, line, typ, numprot) ctsetsets.append( auger.getctset(numprot, line[2:14], None, typ, addnoise=addnoise, precolli=precolli)) PHYSDET_PROFILE_IBA = ctsetsets[-1]['ct']['av'] megaplot(ctsetsets, 'physabs-physcolli')
######################################################################################################### #typ='ipnl-auger-notof-1.root' #typ='ipnlf-auger-tof-1.root' #typ='ipnlf-auger-notof-1.root' #typ='iba-auger-tof-3.root' typ = 'ipnl-auger-tof-1.root' typ = 'iba-auger-notof-3.root' #we dont know what the added or reduced noise level is when changing energy windows, so we cant compare performance for ipnl3 and iba1. #we could study the signal only. #geolayaers geolabels = ["mid", "75\%", "dist 2", "dist"] ctset_dist = auger.getctset(197149701, 'run.YKEk', 'run.pwy4', typ) #-1 ctset_dist2 = auger.getctset(395650000, 'run.C8rL', 'run.r0LF', typ) # -1-2 ctset_75 = auger.getctset(1381819491, 'run.oVKm', 'run.dltw', typ) # -6 ctset_mid = auger.getctset(1428709464, 'run.LqMK', 'run.WZUT', typ) # -12 #elayers elabels = ["mid", "75\%", "dist"] ctset_dist_e = auger.getctset(488628830, 'run.Mwtv', 'run.EKMm', typ) # 0 ctset_75_e = auger.getctset(1285014551, 'run.gFh9', 'run.q4DU', typ) # 10 ctset_mid_e = auger.getctset(976598251, 'run.G8o6', 'run.UQ32', typ) # 24 ######################################################################################################### from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt
for i,ctset in enumerate(ctsets): auger.plotfodist(ax1,ctset,i,emisfops,labels,axlabel) if emisfops is not None and len(emisfops) == 1: ax1.set_title(studyname+', $CT_{FOP_{em}}$ = '+str(emisfops[0][0])[:5]+', $RPCT_{FOP_{em}}$ = '+str(emisfops[0][1])[:5], y=1.08) #plt.legend()#shadow = True,frameon = True,fancybox = True,ncol = 1,fontsize = 'x-small',loc = 'lower right') #plt.tight_layout(rect = [-0.1, 0.0, 1.0, 1.1])#L,B,R,T plt.savefig(studyname+'-'+typ+'-FOP-dist.pdf')#, bbox_inches='tight') plt.close('all') ############################################################################################# # TODO add pgemissions plots. for typ in typs: ctsetsets = [] ctsetsets.append( auger.getctset(1e9,'1e9','1e9',typ) ) ctsetsets.append( auger.getctset(1e8,'1e8','1e8',typ) ) ctsetsets.append( auger.getctset(1e7,'1e7','1e7',typ) ) ctsetsets.append( auger.getctset(1e6,'1e6','1e6',typ) ) #ctsetsets.append( auger.getctset(1e9,'run.3poV','run.wucX',typ) ) #ctsetsets.append( auger.getctset(1e8,'run.1XRe','run.lTdI',typ) ) #ctsetsets.append( auger.getctset(1e7,'run.oPE7','run.RWkp',typ) ) #ctsetsets.append( auger.getctset(1e6,'run.7bG6','run.pijb',typ) ) megaplot(ctsetsets,'waterbox_redo') print 'Mean detection yield in',typ,'study over',sum([ctset['totnprim'] for ctset in ctsetsets]),'primaries in',sum([ctset['nreal'] for ctset in ctsetsets]),'realisations:',sum([ctset['detyieldmu'] for ctset in ctsetsets])
numprots = [1e9, 1e8, 1e7] #,1e6] for typ in typs: ctsetsets = [] for line, numprot in zip( dirs, [item for item in numprots for i in range(len(typs) / len(numprots))]): for haha in ['iba', 'ipnl']: if (haha + 'lyso' in line or haha + 'bgo' in line) and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ, addnoise=addnoise, precolli=precolli)) if haha + 'zinv' in line and haha + '-' in typ: print(haha, line, typ) ctsetsets.append( auger.getctset(numprot, line[2:10], line[2:10], typ, addnoise=addnoise, precolli=precolli)) assert (len(ctsetsets) == 3) megaplot(ctsetsets, 'PMMA_phantom') print 'Mean detection yield in', typ, 'study over', sum( [ctset['totnprim'] for ctset in ctsetsets]), 'primaries in', sum([
######################################################################################################### #typ='ipnl-auger-notof-1.root' #typ='ipnlf-auger-tof-1.root' #typ='ipnlf-auger-notof-1.root' #typ='iba-auger-tof-3.root' typ='ipnl-auger-tof-1.root' typ='iba-auger-notof-3.root' #we dont know what the added or reduced noise level is when changing energy windows, so we cant compare performance for ipnl3 and iba1. #we could study the signal only. #geolayaers geolabels = ["mid","75\%","dist 2","dist"] ctset_dist = auger.getctset(197149701,'run.YKEk','run.pwy4',typ) #-1 ctset_dist2 = auger.getctset(395650000,'run.C8rL','run.r0LF',typ) # -1-2 ctset_75 = auger.getctset(1381819491,'run.oVKm','run.dltw',typ) # -6 ctset_mid = auger.getctset(1428709464,'run.LqMK','run.WZUT',typ) # -12 #elayers elabels = ["mid","75\%","dist"] ctset_dist_e = auger.getctset(488628830,'run.Mwtv','run.EKMm',typ) # 0 ctset_75_e = auger.getctset(1285014551,'run.gFh9','run.q4DU',typ) # 10 ctset_mid_e = auger.getctset(976598251,'run.G8o6','run.UQ32',typ) # 24 ######################################################################################################### from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt
#ctsetsets.append( auger.getctset(1e9,'run.TtIT','run.SmHn',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e8,'run.t4Fb','run.w9Te',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(27200000,'run.YtND','run.SQy4',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e7,'run.WQUJ','run.JJQQ',typ,manualshift=shift) ) #megaplot(ctsetsets,'spot40',emisfops=None,labels=["$10^9$","$10^8$","$2.7\cdot10^7$","$10^7$"]) #shift = 22.20-29.04 #ctsetsets = [] #ctsetsets.append( auger.getctset(1e9,'run.EYBe','run.6HvZ',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e8,'run.W3sR','run.q7v2',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(47300000,'run.R9KU','run.rTUp',typ,manualshift=shift) ) #ctsetsets.append( auger.getctset(1e7,'run.1jXf','run.8NDz',typ,manualshift=shift) ) #megaplot(ctsetsets,'spot61',emisfops=None,labels=["$10^9$","$10^8$","$4.7\cdot10^7$","$10^7$"]) ctsetsets = [] ctsetsets.append(auger.getctset(840964615, 'run.CKCH', 'run.lrnj', typ)) #elay ctsetsets.append(auger.getctset(848710335, 'run.3At2', 'run.Ydep', typ)) #geolay megaplot(ctsetsets, 'layer29', emisfops=None, labels=['Iso-Energy Layer', 'Iso-Depth Layer'], axlabel='Grouping Method') ctsetsets = [] ctsetsets.append(auger.getctset(1068263318, 'run.7coj', 'run.ptEe', typ)) #elay, same as elay61 ctsetsets.append(auger.getctset(1071596684, 'run.KXRm', 'run.jTj9', typ)) #geolay megaplot(ctsetsets, 'layer40',
pgemis_rpct_y_smooth = pgemis_rpct_y_smooth/pgemis_rpct_y_smooth.max() #pgemis_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y) pgemis_rpctfo=auger.get_fop(pgemis_rpct_x,pgemis_rpct_y) #pgemis_smooth_ctfo=auger.get_fop(pgemis_ct_x,pgemis_ct_y_smooth) pgemis_smooth_rpctfo=auger.get_fop(pgemis_rpct_x,pgemis_rpct_y_smooth) ########################################################################################################### #detection in local frame, remove shift. coords already centered as zero, so can just add the shift det_offset = 13.61 ipnl = auger.getctset(1e9,'fromcluster/run.13px','fromcluster/run.13px','ipnl-auger-tof-1.root') #CT IS NONSENSE DATA #pgipnl_ct_x = np.array(ipnl['ct']['x']) #pgipnl_ct_x = pgipnl_ct_x+det_offset #pgipnl_ct_y = np.array(ipnl['ct']['av']) #pgipnl_ct_y = pgipnl_ct_y-(pgipnl_ct_y[pgipnl_ct_y < np.percentile(pgipnl_ct_y, 25)].mean()) #remove floor #pgipnl_ct_y = pgipnl_ct_y/pgipnl_ct_y.max() #scale pgipnl_rpct_x = np.array(ipnl['rpct']['x']) pgipnl_rpct_x = pgipnl_rpct_x+det_offset #pgipnl_rpct_y = np.array(ipnl['rpct']['av']) pgipnl_rpct_y = np.array(ipnl['rpct']['data'][0]) pgipnl_rpct_y = pgipnl_rpct_y-(pgipnl_rpct_y[pgipnl_rpct_y < np.percentile(pgipnl_rpct_y, 25)].mean()) #remove floor pgipnl_rpct_y = pgipnl_rpct_y/pgipnl_rpct_y.max() #scale #pgipnl_ctfo = np.mean(ipnl['ct']['falloff'])+det_offset