def PlotAdiabaticityParameter(param,sparam = PC.PhysicsConstants()):
""" Plots the adiabaticity parameter from for a given energy range on the sun.
@type param : physicsconstants
@param param : set of physical parameters used to make the plot.
@type sparam : physicsconstants
@param sparam : standard parameters
@rtype : plot
@return : generates the spectra plot
"""
import Scientific.Functions.Derivatives as sfd
Sun = bd.Sun()
print Sun.rdensity(sfd.DerivVar(0.5))
## th_24 resonance search
E = np.arange(1.0,1000.0,10.0)
adiabaticity_s1 = (np.sin(2.0*param.th24)**2/np.cos(2.0*param.th24))*(param.dmsq41/(2.0*E*param.GeV))*()
adiabaticity_s2 = (np.sin(2.0*param.th24)**2/np.cos(2.0*param.th24))*(param.dmsq51/(2.0*E*param.GeV))*()
def PlotCompareProbabilitiesMC(param,sparam = PC.PhysicsConstants(),plot_path = "../plots/"):
""" Plot osc. probabilities from MC compared with analitic calculation of probabilities.
@type param : physicsconstants
@param param : set of physical parameters used to make the plot.
@type sparam : physicsconstants
@param sparam : standard parameters
@rtype : plot
@return : generates probability comparison plot
"""
fig = plt.figure()
Enumin = 1.0
Enumax = 1.0e3
Enustep = 10.0
Enu = np.arange(Enumin,Enumax,Enustep)
# param1
param.name = "2+3"
param.neutype = "neutrino"
datapath = "../data/myMC/"+param.name+"/"+param.neutype+"/"
inter_nu, inter_anu = DM.DMOscProbabilitiesMC(param,False, datapath = datapath, crosscheck = False)
mc_osc_prob = [float(inter_nu(E)) for E in Enu]
# sparam
sparam.name = "STD"
param.neutype = "neutrino"
sdatapath = "../data/myMC/"+sparam.name+"/"+sparam.neutype+"/"
inter_nu, inter_anu = DM.DMOscProbabilitiesMC(sparam,False, datapath = sdatapath, crosscheck = False)
smc_osc_prob = [float(inter_nu(E)) for E in Enu]
# analitic
ana_osc_prob = [no.AvgNeuProb_RK_STD(0,1,E*param.GeV,param)+no.AvgNeuProb_RK_STD(1,1,E*param.GeV,param)+no.AvgNeuProb_RK_STD(2,1,E*param.GeV,param) for E in Enu]
plt.plot(Enu,mc_osc_prob,label = 'MC-2+3')
plt.plot(Enu,smc_osc_prob,label = 'MC-STD')
plt.plot(Enu,ana_osc_prob,label = 'ANA')
plt.legend()
# path = "../plots/"
filename = "PlotCompareProbabilitiesMC.png"
plt.savefig(plot_path+filename)
+ From now on to check or review this code refer to
Neutrino nucleus interaction rates at a low-energy beta beam facility
Julien Serreau, Cristina Volpe
Phys.Rev. C70 (2004) 055502
arXiv : hep-ph/0403293
"""
import numpy as np
import scipy as sp
import scipy.interpolate as interpolate
import neutrinocommon.physconst.physicsconstants as PC
pc = PC.PhysicsConstants()
def FermiFunction(W, Z=2):
""" Returns the Fermi function F(+/-Z,W) for Z = 2, evaluated using the #
method in the reference, correct to within 1%. #
Ref.: J. Phys. G: Nucl. Phys. 11, 359 (1985)
@type W : float
@param W : energy [eV]
@rtype : float
@return : fermi function value [dimensionless?]
"""
me = pc.electron_mass * pc.GeV
def PlotSingleNeuCompositionCompare(E,body,param,sparam = PC.PhysicsConstants()):
""" Plots the composition of a single mass neutrino state.
E : neutrino energy [eV]
body : body with the asociated density profile.
param : set of physical parameters used to make the plot. param can be a list.
sparam : standard parameters
"""
fig = plt.figure()
ax = plt.subplot(111)
mpl.rcParams['axes.labelsize'] = "x-large"
mpl.rcParams['xtick.labelsize'] = "x-large"
mpl.rcParams['legend.fontsize'] = "small"
mpl.rcParams['font.size'] = 18
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
linestyles = ['--','-.',':','-','-']
#B Initializing variables
param.Refresh()
fM2 = no.flavorM2(param)
sparam.Refresh()
fM2STD = no.flavorM2(sparam)
R = np.arange(1.0,0.01,-0.001)
Rho = map(lambda r : body.rdensity(r), R)
#E Initializing variables
#B Estimating Energy Scale
if(E/param.MeV <= 500.0) :
scale = param.MeV
scalen = "MeV"
elif(E/param.GeV <= 500.0) :
scale = param.GeV
scalen = "GeV"
else :
scale = param.TeV
scalen = "TeV"
#E Estimating Energy Scale
#B Adding title
#tit = "Energy : "+str(E/scale)+" "+scalen+ " Parameters :"#+" $\\th_{12}$ = " + str(param.th12) + " $\\th_{23}$ = " + str(param.th23) + " $\\th_{13}$ = "+str(param.th13)
#atit = []
#[[ atit.append(" $\\theta_{"+str(j)+str(i)+"}$ = "+format(param.th[j][i],'.4f')) for i in range(1,param.numneu+1) if i>j] for j in range(1,param.numneu+1) ]
#[[ atit.append(" $\\Delta m^2_{"+str(i)+str(j)+"}$ = "+format(param.dm2[j][i],'.4f')) for i in range(1,param.numneu+1) if i>j and j == 1] for j in range(1,param.numneu+1) ]
##[[ atit.append(" $\\Delta m^2_{"+str(j)+str(i)+"}$ = "+format(param.dm2[j][i],'.4f')) for i in range(1,param.numneu+1) if i>j and j == 1] for j in range(1,param.numneu+1) ]
#for i in range(len(atit)):
# tit = tit + atit[i]
#plt.suptitle(tit,horizontalalignment='center')
#E Adding title
##B PLOTTING MASS BASIS AS FUNCTION OF FLAVOR BASIS
for i in [1]:
#fig.add_subplot(2,param.numneu,i+1)
flavor = False
NeuComp = map(lambda x : no.NeuComposition(i,E, x, body, fM2, param,flavor),R)
plt.xlabel(r"$\rho \mathrm{[g/cm^{3}]}$")
pp = []
for k in range(param.numneu):
kNeuComp = map(lambda x: x[k],NeuComp)
# log interpolator
rholog = gt.LogSpaceEnergies(float(Rho[0]),float(Rho[-1]),100)
#print rholog , float(Rho[0]),float(Rho[-1])
rholog[-1] = Rho[-1]
inter_neu = interpolate.interp1d(Rho,kNeuComp)
logkNeuComp = map(inter_neu,rholog)
if k == 3:
#pp.append(plt.plot(Rho,kNeuComp,'o-',color = 'r',markevery = 10,markeredgewidth = 0.0, ms = 2.0))
pp.append(plt.plot(rholog,logkNeuComp,'x-',color = 'r',markevery = 10,markeredgewidth = 0.0, ms = 2.0,aa = True,solid_joinstyle = 'bevel'))
elif k == 4:
pp.append(plt.plot(Rho,kNeuComp,'o-',color = 'r',markevery = 10,markeredgewidth = 0.0, ms = 2.0))
else :
pp.append(plt.plot(Rho,kNeuComp,linestyle = linestyles[k] ,color = 'r'))
if i<=2 :
NeuCompSTD = map(lambda x : no.NeuComposition(i,E, x, body, fM2STD, sparam,flavor),R)
for k in range(sparam.numneu):
kNeuCompSTD = map(lambda x: x[k],NeuCompSTD)
plt.plot(Rho,kNeuCompSTD, color = 'k', linestyle = linestyles[k])
#Solar density
#ps = plt.vlines(150, 0.0, 1.0, linestyle = "dashed", label = r"$\rho_S$")
#B plt format
plt.title(r"Composition of $\nu_"+str(i+1)+"$")
plt.semilogx()
plt.ylim(0.0,1.0)
plt.xlim(1.0,150.0)
plt.yticks(np.arange(0.0,1.1,0.1))
xtt = [1.0,5.0,10.0,30.0,100.0]#,150.0]
#plt.xticks(xtt)
ax.set_xticks(xtt)
ax.set_xticklabels(['$1$','$5$','$10$','$30$','$100$'])#,'$\\rho_\\odot = 150$'])
#plt.xscale()
#B LEGEND
plots = []
for e in pp :
plots.append(e[0])
#plots.append(ps)
leg = ["$\\nu_e$","$\\nu_\mu$","$\\nu_\\tau$"]
ss = ["$\\nu_{s"+str(i)+"}$" for i in np.arange(1,param.numneu-3+1,1)]
if ss != []:
leg.extend(ss)
leg = plt.legend(plots,leg,loc = 6,fancybox=True,bbox_to_anchor = (0.05, 0.75))
leg.get_frame().set_alpha(0.25)
#E LEGEND
#E plt format
#B EXTRA LEGEND
box1t = osb.TextArea("STD", textprops=dict(color="k"))
box1d = osb.DrawingArea(60, 20, 0, 0)
el1 = ptc.Ellipse((10, 10), width=5, height=5, angle=0, fc="k", edgecolor = 'none')
box1d.add_artist(el1)
box2t = osb.TextArea("2+3", textprops=dict(color="k"))
box2d = osb.DrawingArea(60, 20, 0, 0)
el2 = ptc.Ellipse((10, 10), width=5, height=5, angle=0, fc="r", edgecolor = 'none')
box2d.add_artist(el2)
box1 = osb.HPacker(children=[box1t, box1d],
align="center",
pad=0, sep=1)
box2 = osb.HPacker(children=[box2t, box2d],
align="center",
pad=0, sep=5)
anchored_box1 = osb.AnchoredOffsetbox(loc=9,
child=box1, pad=5.0,
frameon=False,
#bbox_to_anchor=(0., 1.02),
#bbox_transform=ax.transAxes,
borderpad=0.,
)
anchored_box2 = osb.AnchoredOffsetbox(loc=9,
child=box2, pad=6.0,
frameon=False,
#bbox_to_anchor=(0., 1.02),
#bbox_transform=ax.transAxes,
borderpad=0.,
)
ax.add_artist(anchored_box1)
ax.add_artist(anchored_box2)
#E EXTRA LEGEND
##E PLOTTING MASS BASIS AS FUNCTION OF FLAVOR BASIS
#plt.suptitle("*Dashed colored lines are 3-flavor standard oscillations.", x = 0.15, y = 0.03)
path = "../plots/"
filename = "PlotNeuComposition_E_"+str(E/scale)+"_"+scalen+"_FIG2.eps"
plt.savefig(path + filename, dpi = 1200)
def PlotNeuCompositionCompare(E,body,param,sparam = PC.PhysicsConstants(),plot_path = "../plots/",xlim = None, fmt = "png"):
""" Plots the composition of neutrinos as a function of mass states, flavors, and density. Compares with STD.
E : neutrino energy [eV]
body : body with the asociated density profile.
param : set of physical parameters used to make the plot. param can be a list.
sparam : standard parameters
"""
fig = plt.figure(figsize = (4*param.numneu,8))
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
#B Initializing variables
param.Refresh()
fM2 = no.flavorM2(param)
fM2STD = no.flavorM2(sparam)
R = np.arange(1.0,0.01,-0.001)
Rho = map(lambda r : body.rdensity(r), R)
#E Initializing variables
#B Estimating Energy Scale
if(E/param.MeV <= 500.0) :
scale = param.MeV
scalen = "MeV"
elif(E/param.GeV <= 500.0) :
scale = param.GeV
scalen = "GeV"
else :
scale = param.TeV
scalen = "TeV"
#E Estimating Energy Scale
#B Adding title
tit = "Energy : "+str(E/scale)+" "+scalen+ " Parameters :"#+" $\\th_{12}$ = " + str(param.th12) + " $\\th_{23}$ = " + str(param.th23) + " $\\th_{13}$ = "+str(param.th13)
atit = []
try:
[[ atit.append(" $\\theta_{"+str(j)+str(i)+"}$ = "+format(param.th[j][i],'.4f')) for i in range(1,param.numneu+1) if i>j] for j in range(1,param.numneu+1) ]
[ atit.append(" $\\Delta m^2_{"+str(j)+str(1)+"}$ = "+format(param.dm2[1][j],'.3e')) for j in range(2,param.numneu+1) ]
except TypeError:
[[ atit.append(" $\\theta_{"+str(j)+str(i)+"}$ = "+"{:.4}".format(param.th[j][i])) for i in range(1,param.numneu+1) if i>j] for j in range(1,param.numneu+1) ]
[ atit.append(" $\\Delta m^2_{"+str(j)+str(1)+"}$ = "+"{:.3}".format(param.dm2[1][j])) for j in range(2,param.numneu+1) ]
for i in range(len(atit)):
tit = tit + atit[i]
plt.suptitle(tit,horizontalalignment='center')
#E Adding title
##B PLOTTING MASS BASIS AS FUNCTION OF FLAVOR BASIS
for i in np.arange(0,param.numneu,1):
fig.add_subplot(2,param.numneu,i+1)
flavor = False
NeuComp = map(lambda x : no.NeuComposition(i,E, x, body, fM2, param,flavor),R)
plt.xlabel(r"$\rho \mathrm{[g/cm^{3}]}$")
pp = []
for k in range(param.numneu):
kNeuComp = map(lambda x: x[k],NeuComp)
pp.append(plt.plot(Rho,kNeuComp, color = colors[k],lw = 3))
if i<=2 :
NeuCompSTD = map(lambda x : no.NeuComposition(i,E, x, body, fM2STD, sparam,flavor),R)
for k in range(sparam.numneu):
kNeuCompSTD = map(lambda x: x[k],NeuCompSTD)
plt.plot(Rho,kNeuCompSTD, color = colors[k], linestyle = 'dashed',lw = 3)
#Solar density
ps = plt.vlines(150, 0.0, 1.0, linestyle = "dashed", label = r"$\rho_S$")
#B plt format
plt.title(r"Composition of $\nu_"+str(i+1)+"$")
plt.semilogx()
plt.ylim(0.0,1.0)
plt.xlim(0.0,1000.0)
plt.yticks(np.arange(0.0,1.1,0.1))
#plt.xscale()
if xlim == None :
plt.xlim(Rho[0],Rho[-1])
else :
plt.xlim(xlim)
if i == param.numneu - 1 :
plots = []
for e in pp :
plots.append(e[0])
plots.append(ps)
leg = ["$\\nu_e$","$\\nu_\mu$","$\\nu_\\tau$"]
ss = ["$\\nu_{s"+str(i)+"}$" for i in np.arange(1,param.numneu-3+1,1)]
if ss != []:
leg.extend(ss)
#leg.append("$\\rho_\odot$")
plt.legend(plots,leg,bbox_to_anchor = (1.5, 0.90))
fig.subplots_adjust(left=0.05, right=0.85,hspace = 0.35)#,wspace = 0.25, top = 0.95, bottom = 0.05)
#E plt format
##E PLOTTING MASS BASIS AS FUNCTION OF FLAVOR BASIS
##B PLOTTING FLAVOR BASIS AS FUNCTION OF MASS BASIS
for i in np.arange(param.numneu,2*param.numneu,1):
fig.add_subplot(2,param.numneu,i+1)
flavor = True
NeuComp = map(lambda x : no.NeuComposition(i-param.numneu,E, x, body, fM2, param,flavor),R)
plt.xlabel(r"$\rho \mathrm{[g/cm^{-3}]}$")
pp = []
for k in range(param.numneu):
kNeuComp = map(lambda x: x[k],NeuComp)
pp.append(plt.plot(Rho,kNeuComp, color = colors[k],lw = 3))
if i<=2+param.numneu :
NeuCompSTD = map(lambda x : no.NeuComposition(i-param.numneu,E, x, body, fM2STD, sparam,flavor),R)
for k in range(sparam.numneu):
kNeuCompSTD = map(lambda x: x[k],NeuCompSTD)
plt.plot(Rho,kNeuCompSTD, color = colors[k], linestyle = 'dashed',lw = 3)
#Solar density
ps = plt.vlines(150, 0.0, 1.0, linestyle = "dashed", label = r"$\rho_S$")
#B plt format
if i == param.numneu :
plt.title(r"Composition of $\nu_e$")
elif i == param.numneu + 1:
plt.title(r"Composition of $\nu_\mu$")
elif i == param.numneu + 2:
plt.title(r"Composition of $\nu_\tau$")
else :
plt.title(r"Composition of $\nu_{s"+str(i+1-param.numneu-3)+"}$")
plt.semilogx()
plt.ylim(0.0,1.0)
plt.yticks(np.arange(0.0,1.1,0.1))
if xlim == None :
plt.xlim(Rho[0],Rho[-1])
else :
plt.xlim(xlim)
#plt.xscale()
if i == 2*param.numneu - 1 :
plots = []
for e in pp :
plots.append(e[0])
plots.append(ps)
leg = ["$\\nu_{"+str(i)+"}$" for i in np.arange(1,param.numneu+1,1)]
#leg.append("$\\rho_\odot$")
plt.legend(plots,leg,bbox_to_anchor = (1.5, 0.90))
fig.subplots_adjust(left=0.05, right=0.85)#, top = 0.85, bottom = 0.05)
##E PLOTTING FLAVOR BASIS AS FUNCTION OF MASS BASIS
plt.suptitle("*Dashed colored lines are 3-flavor standard oscillations.", x = 0.15, y = 0.03)
filename = "PlotNeuComposition_E_"+str(E/scale)+"_"+scalen+"_"+param.name+"."+fmt
plt.savefig(plot_path + filename)