ax2.set_title("Dose")
ax3.set_title("Dose TLE")
ax4.set_title("PhS, rel. unc")
ax5.set_title("Dose, rel. unc")
ax6.set_title("Dose TLE, rel. unc")
# BIN EDGES!
xbins = np.linspace(-410 / 2., 410 / 2., 256 + 1)
ybins = np.linspace(-410 / 2., 410 / 2., 256 + 1)
counts = plot.plot2dhist(ax1,
all['X'],
all['Y'],
xbins=xbins,
ybins=ybins,
log=True)
plot.plot1dhist(ax4, (1. / np.sqrt(counts.flatten())) * 100.,
bins=unc_axis,
range=(min(unc_axis), max(unc_axis)),
log=True,
count=True)
ax2.imshow(doseim_.imdata.squeeze(), extent=[0, 41, 0, 41], cmap='gray')
plot.plot1dhist(ax5, doseuncim_.imdata.flatten(), bins=unc_axis, log=True)
ax3.imshow(dosetleim_.imdata.squeeze(), extent=[0, 41, 0, 41], cmap='gray')
plot.plot1dhist(ax6, dosetleuncim_.imdata.flatten(), bins=unc_axis, log=True)
f.savefig(indir.replace('/', '_') + '_unc.pdf', bbox_inches='tight')
plot.close('all')
ax4.set_title("Secon Phot")
ax5.set_title("Nonphot")
# BIN EDGES!
xbins = np.linspace(-410/2.,410/2.,256+1)
ybins = np.linspace(-410/2.,410/2.,256+1)
a = plot.plot2dhist( ax1, all['X'], all['Y'], xbins=xbins,ybins=ybins, log=True)
a = plot.plot2dhist( ax2, phot_trans['X'], phot_trans['Y'], xbins=xbins,ybins=ybins, log=True)
a = plot.plot2dhist( ax3, phot_scatter['X'], phot_scatter['Y'], xbins=xbins,ybins=ybins, log=True)
a = plot.plot2dhist( ax4, phot_other['X'], phot_other['Y'], xbins=xbins,ybins=ybins, log=True)
a = plot.plot2dhist( ax5, nonphot['X'], nonphot['Y'], xbins=xbins,ybins=ybins, log=True)
#,norm=matplotlib.colors.LogNorm(),vmin=1e0,vmax=1e2)
plot.plot1dhist(ax6,all_E,count=True)
plot.plot1dhist(ax7,phot_trans_E,count=True)
plot.plot1dhist(ax8,phot_scatter_E,count=True)
plot.plot1dhist(ax9,phot_other_E,count=True)
ax9.set_xlim(0,2)
plot.plot1dhist(ax10,nonphot_E,count=True)
d = {
'e-':'Electron',
'e+':'Positron',
'gamma':'Photon'
}
plot.plotbar(ax14,partname,relabel=d,log=True)
plot.plotbar(ax15,['Total Counts' for i in range(len(all['X']))]+['Prim Trans' for i in range(len(phot_trans['X']))]+['Prim Scat' for i in range(len(phot_scatter['X']))]+['Secon Phot' for i in range(len(phot_other['X']))],rotation=30)
ax15.text(0.05, 0.95, 'Trans/Total: '+str( len(phot_trans['X'])/float(len(all['X'])) ) , ha='left', va='center', transform=ax15.transAxes)
for rootfile in rootfiles:
all = dump.get2D(rootfile,['X','Y'])
f, (ax1 ,ax2 )= plot.subplots(nrows=1, ncols=2, sharex=False, sharey=False)#,figsize=(28,10))
f.subplots_adjust(hspace=.5)
f.subplots_adjust(wspace=.5)
ax1.set_title("X,Y")
ax2.set_title("unc histo")
# BIN EDGES!
xbins = np.linspace(-410/2.,410/2.,256+1)
ybins = np.linspace(-410/2.,410/2.,256+1)
counts = plot.plot2dhist( ax1, all['X'], all['Y'], xbins=xbins,ybins=ybins, log=True)
#,norm=matplotlib.colors.LogNorm(),vmin=1e0,vmax=1e2)
#plot.plot1dhist(ax2,counts.flatten(),bins=np.linspace(0,200,100), log=True,count=True)
#with np.errstate(divide='ignore', invalid='ignore'):
#unc = np.true_divide(1.,counts.flatten()*100.)
#unc[unc == np.inf] = 0
#unc[unc == np.nan] = 0
plot.plot1dhist(ax2,(1./np.sqrt(counts.flatten()))*100.,bins=np.linspace(0,50,50), range=(0,50), log=True,count=True)
f.savefig(rootfile+'.unc.pdf', bbox_inches='tight')
plot.close('all')
f, ((ax1 ,ax2, ax3 ),(ax4, ax5, ax6))= plot.subplots(nrows=2, ncols=3, sharex=False, sharey=False)#,figsize=(28,10))
#f.subplots_adjust(hspace=.5)
#f.subplots_adjust(wspace=.5)
f.suptitle('Runtime: '+runtime+'s', fontsize=10)
ax1.set_title("PhS, X,Y")
ax2.set_title("Dose")
ax3.set_title("Dose TLE")
ax4.set_title("PhS, rel. unc")
ax5.set_title("Dose, rel. unc")
ax6.set_title("Dose TLE, rel. unc")
# BIN EDGES!
xbins = np.linspace(-410/2.,410/2.,256+1)
ybins = np.linspace(-410/2.,410/2.,256+1)
counts = plot.plot2dhist( ax1, all['X'], all['Y'], xbins=xbins,ybins=ybins, log=True)
plot.plot1dhist(ax4,(1./np.sqrt(counts.flatten()))*100.,bins=unc_axis, range=(min(unc_axis),max(unc_axis)), log=True,count=True)
ax2.imshow( doseim_.imdata.squeeze() , extent = [0,41,0,41], cmap='gray')
plot.plot1dhist( ax5, doseuncim_.imdata.flatten(), bins=unc_axis, log=True)
ax3.imshow( dosetleim_.imdata.squeeze() , extent = [0,41,0,41], cmap='gray')
plot.plot1dhist( ax6, dosetleuncim_.imdata.flatten(), bins=unc_axis, log=True)
f.savefig(indir.replace('/','_')+'_unc.pdf', bbox_inches='tight')
plot.close('all')
ax1.set_title("X,Y")
ax2.set_title("unc histo")
# BIN EDGES!
xbins = np.linspace(-410 / 2., 410 / 2., 256 + 1)
ybins = np.linspace(-410 / 2., 410 / 2., 256 + 1)
counts = plot.plot2dhist(ax1,
all['X'],
all['Y'],
xbins=xbins,
ybins=ybins,
log=True)
#,norm=matplotlib.colors.LogNorm(),vmin=1e0,vmax=1e2)
#plot.plot1dhist(ax2,counts.flatten(),bins=np.linspace(0,200,100), log=True,count=True)
#with np.errstate(divide='ignore', invalid='ignore'):
#unc = np.true_divide(1.,counts.flatten()*100.)
#unc[unc == np.inf] = 0
#unc[unc == np.nan] = 0
plot.plot1dhist(ax2, (1. / np.sqrt(counts.flatten())) * 100.,
bins=np.linspace(0, 50, 50),
range=(0, 50),
log=True,
count=True)
f.savefig(rootfile + '.unc.pdf', bbox_inches='tight')
plot.close('all')
a = plot.plot2dhist(ax4,
phot_other['X'],
phot_other['Y'],
xbins=xbins,
ybins=ybins,
log=True)
a = plot.plot2dhist(ax5,
nonphot['X'],
nonphot['Y'],
xbins=xbins,
ybins=ybins,
log=True)
#,norm=matplotlib.colors.LogNorm(),vmin=1e0,vmax=1e2)
plot.plot1dhist(ax6, all_E, count=True)
plot.plot1dhist(ax7, phot_trans_E, count=True)
plot.plot1dhist(ax8, phot_scatter_E, count=True)
plot.plot1dhist(ax9, phot_other_E, count=True)
ax9.set_xlim(0, 2)
plot.plot1dhist(ax10, nonphot_E, count=True)
d = {'e-': 'Electron', 'e+': 'Positron', 'gamma': 'Photon'}
plot.plotbar(ax14, partname, relabel=d, log=True)
plot.plotbar(ax15, ['Total Counts' for i in range(len(all['X']))] +
['Prim Trans' for i in range(len(phot_trans['X']))] +
['Prim Scat' for i in range(len(phot_scatter['X']))] +
['Secon Phot' for i in range(len(phot_other['X']))],
rotation=30)
ax15.text(0.05,
axrow[0].set_title(label + '\n$\sum$ Dose: ' +
plot.sn(fracties_totaal[-1]))
axrow[1].set_title(label + ' Profile')
axrow[1].plot(*yim_.getprofile('y'), color='steelblue', label='x')
axrow[1].plot(*yim_.getprofile('x'), color='indianred', label='y')
axrow[1].legend(loc='upper right', bbox_to_anchor=(1., 1.), frameon=False)
axrow[1].axvline(41. / 2. - 8., color='#999999',
ls='--') #10x10 at isoc is 16x16 at epid level
axrow[1].axvline(41. / 2. + 8., color='#999999', ls='--')
axrow[1].set_xlim(0, 41)
plot.set_metric_prefix_y(axrow[1])
axrow[2].set_title(label + ' relunc')
plot.plot1dhist(axrow[2],
uim_.imdata.flatten(),
bins=np.linspace(0, 100, 50),
log=True)
frac_trans = 1.
frac_nontrans = 1.
if args.phosphor:
npart_trans = 112525576.
npart_tot = 127153038.
frac_trans = npart_trans / npart_tot
frac_nontrans = 1. - frac_trans
sumim = image.image(imyields[0], type='yield')
sumim.imdata = sumim.imdata.squeeze() * frac_nontrans + image.image(
imyields[1], type='yield').imdata.squeeze() * frac_trans
axes[-1][0].imshow(sumim.imdata, extent=[0, 41, 0, 41], cmap='gray')
axes[-1][0].set_title('Sum' + '\n$\sum$ Dose: ' + plot.sn(sumim.imdata.sum()))
fracties_isocentrum.append( yim_.getcenter().mean() )
fracties_totaal.append( yim_.imdata.sum() )
axrow[0].imshow( yim_.imdata.squeeze() , extent = [0,41,0,41], cmap='gray')
axrow[0].set_title(label + '\n$\sum$ Dose: '+ plot.sn(fracties_totaal[-1]))
axrow[1].set_title(label + ' Profile')
axrow[1].plot(*yim_.getprofile('y'), color = 'steelblue' , label='x')
axrow[1].plot(*yim_.getprofile('x'), color = 'indianred' , label='y')
axrow[1].legend(loc='upper right', bbox_to_anchor=(1., 1.),frameon=False)
axrow[1].axvline(41./2.-8., color='#999999', ls='--') #10x10 at isoc is 16x16 at epid level
axrow[1].axvline(41./2.+8., color='#999999', ls='--')
axrow[1].set_xlim(0,41)
plot.set_metric_prefix_y(axrow[1])
axrow[2].set_title(label+' relunc')
plot.plot1dhist( axrow[2], uim_.imdata.flatten(), bins=np.linspace(0,100,50), log=True)
frac_trans=1.
frac_nontrans=1.
if args.phosphor:
npart_trans=112525576.
npart_tot=127153038.
frac_trans=npart_trans/npart_tot
frac_nontrans=1.-frac_trans
sumim = image.image(imyields[0],type='yield')
sumim.imdata=sumim.imdata.squeeze()*frac_nontrans+image.image(imyields[1],type='yield').imdata.squeeze()*frac_trans
axes[-1][0].imshow( sumim.imdata , extent = [0,41,0,41], cmap='gray')
axes[-1][0].set_title('Sum' + '\n$\sum$ Dose: '+ plot.sn(sumim.imdata.sum()))
axes[-1][1].set_title('Sum Profile')
sharey=False) #,figsize=(28,10))
f.subplots_adjust(hspace=.5, wspace=.5)
ax1.set_title("Positions")
ax2.set_title("Energy")
xbins = np.linspace(-panelsize / 2., panelsize / 2., numpix + 1)
ybins = xbins
xbins2 = plot.chopcentral(xbins, 5)
ybins2 = xbins2
xbins3 = np.linspace(-5, 5, 10 + 1)
ybins3 = xbins3
xbins4 = np.linspace(-10, 0, 10 + 1)
ybins4 = xbins4
plot.plot2dhist(ax1,
fpos_e['X'],
fpos_e['Z'],
xbins=xbins,
ybins=ybins,
log=True)
plot.plot1dhist(ax2, fE_e, count=True)
#ax3.pcolormesh(pos_e[0], pos_e[1], pos_e[2].T)#, log=True)
#ax3.pcolormesh(pos_e[0], pos_e[1], pos_e[2])#, log=True)
ax4.step(E_e[0][:-1], E_e[1])
f.savefig(rootfile + '.pdf', bbox_inches='tight')
plot.close('all')