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Sensitivities.py
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Sensitivities.py
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#!/bin/sh /cvmfs/icecube.opensciencegrid.org/py2-v2/icetray-start
#METAPROJECT icerec/V05-01-00
import os
import src/ING as ING
import matplotlib as mlp
import numpy as np
mlp.use('Agg')
import matplotlib.pyplot as plt
mass = [100,250,350,500,750,1000,2500,5000,7500,10000,25000,50000,75000]
channel = [5,8,11,13]
life = [1, 10, 100, 1000, 10000]
medmass = [1, 10, 100, 1000, 10000]
masslist = [100, 250, 350, 500, 750, 1000, 2500, 5000, 7500, 10000, 25000, 50000, 75000]
medmasslist = [1, 10, 100, 1000, 10000]
lifetimelist = [1, 10, 100, 1000, 10000]
channellist = [5, 8, 11, 13]
ACC = []
NS = []
FLUX = []
SI = []
SD = []
nlim = []
dNdE_e = []
dNdE_ae = []
dNdE_mu = []
dNdE_amu = []
N_e = []
N_ae = []
N_mu = []
N_amu = []
fluxconv2 = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/conversion_darksusy/SDCS.txt")
for Mass in mass: #[100,200,350,500,750,1000,2500,5000,7500,10000,25000,50000,75000,100000]:
a1= []
a2= []
a3= []
a4= []
aa1= []
aa2= []
aa3= []
aa4= []
for Channel in channel: #[5,8,11,13]:
b1= []
b2= []
b3= []
b4= []
bb1= []
bb2= []
bb3= []
bb4= []
for Life in life: # [0.00042,0.042,0.42,4.2]:
c1= []
c2= []
c3= []
c4= []
cc1= []
cc2= []
cc3= []
cc4= []
for Medmass in medmass: #[10,100,1000,10000]:
if os.path.isfile("/home/ctoennis/analyses/standard_analysis_framework/spectra_wimpsim/wa-sunsum-m" + str(Mass) + "-ch" + str(Channel) + "-x" + str(Medmass) + "-l" + str(Life) + "-009080-000000-read-earth_mu.dat"):
c1.append( ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/spectra_wimpsim/wa-sunsum-m" + str(Mass) + "-ch" + str(Channel) + "-x" + str(Medmass) + "-l" + str(Life) + "-009080-000000-read-earth_e.dat"))
c2.append( ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/spectra_wimpsim/wa-sunsum-m" + str(Mass) + "-ch" + str(Channel) + "-x" + str(Medmass) + "-l" + str(Life) + "-009080-000000-read-earth_ae.dat"))
c3.append( ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/spectra_wimpsim/wa-sunsum-m" + str(Mass) + "-ch" + str(Channel) + "-x" + str(Medmass) + "-l" + str(Life) + "-009080-000000-read-earth_mu.dat"))
c4.append( ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/spectra_wimpsim/wa-sunsum-m" + str(Mass) + "-ch" + str(Channel) + "-x" + str(Medmass) + "-l" + str(Life) + "-009080-000000-read-earth_amu.dat"))
cc1.append(c3[-1].Integral(c3[-1].points[0][0],c3[-1].points[-1][0]))
cc2.append(c4[-1].Integral(c4[-1].points[0][0],c4[-1].points[-1][0]))
cc3.append(sum([x[1] for x in c3[-1].points])/200.)
cc4.append(sum([x[1] for x in c4[-1].points])/200.)
else:
c1.append("none")
c2.append("none")
c3.append("none")
c4.append("none")
cc1.append("none")
cc2.append("none")
cc3.append("none")
cc4.append("none")
b1.append(c1)
b2.append(c2)
b3.append(c3)
b4.append(c4)
bb1.append(cc1)
bb2.append(cc2)
bb3.append(cc3)
bb4.append(cc4)
a1.append(b1)
a2.append(b2)
a3.append(b3)
a4.append(b4)
aa1.append(bb1)
aa2.append(bb2)
aa3.append(bb3)
aa4.append(bb4)
dNdE_e.append(a1)
dNdE_ae.append(a2)
dNdE_mu.append(a3)
dNdE_amu.append(a4)
N_e.append(aa1)
N_ae.append(aa2)
N_mu.append(aa3)
N_amu.append(aa4)
for Channel in range(len(channel)):
nlom = []
CCC = []
for Life in range(len(life)):
nlum = []
BCC = []
for Medmass in range(len(medmass)):
if os.path.isfile("/home/ctoennis/analyses/standard_analysis_framework/new_sens/ns_limit-med" + str(Medmass) + "-gl" + str(Life) + "-ch" + str(Channel) + ".txt"):
nlum.append(ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/new_sens/ns_limit-med" + str(Medmass) + "-gl" + str(Life) + "-ch" + str(Channel) + ".txt"))
else:
nlum.append("none")
if os.path.isfile("/home/ctoennis/analyses/standard_analysis_framework/northern_ing/Acceptance/rev_med" + str(medmass[Medmass]) + "_lifetime" + str(life[Life]) + "_channel" + str(channel[Channel]) + "_track.txt"):
BCC.append(ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/northern_ing/Acceptance/rev_med" + str(medmass[Medmass]) + "_lifetime" + str(life[Life]) + "_channel" + str(channel[Channel]) + "_track.txt"))
else:
BCC.append("none")
nlom.append(nlum)
CCC.append(BCC)
nlim.append(nlom)
ACC.append(CCC)
ardid = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/mardid.txt")
antares = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/ANTARES.txt")
SDCS_ardid = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/mardid_SDCS.txt")
SICS_ardid = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/mardid_SICS.txt")
SDCS_HAWC = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/HAWC.txt")
SDCS_HAWC_tau = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/HAWC_tau.txt")
SDCS_IC_bb = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/SDCS_IC_bb_new.txt")
SDCS_IC_WW = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/SDCS_IC_WW_new.txt")
SDCS_IC_tt = ING.Graph.FromFile("/home/ctoennis/analyses/standard_analysis_framework/SDCS_IC_tt_new.txt")
AU = 149597870.71
plt.rc('font', size=24) # controls default text sizes
plt.rc('axes', titlesize=20) # fontsize of the axes title
plt.rc('axes', labelsize=20) # fontsize of the x and y labels
plt.rc('xtick', labelsize=20) # fontsize of the tick labels
plt.rc('ytick', labelsize=20) # fontsize of the tick labels
plt.rc('legend', fontsize=14) # legend fontsize
plt.rc('font',**{'family':'serif','serif':['Times']})
plt.rc('text', usetex=True)
for Channel in range(4):
FLUX_a = []
SD_a = []
for Life in range(5):
FLUX_b = []
SD_b = []
for Medmass in range(4):
FLUX_p = []
SD_p = []
if ACC[Channel][Life][Medmass] == "none":
for Mass in range(len(mass)):
FLUX_p.append([mass[Mass],1])
SD_p.append([mass[Mass],1])
FLUX_i = ING.Graph(FLUX_p)
SD_i = ING.Graph(SD_p)
FLUX_b.append(FLUX_i)
SD_b.append(SD_i)
continue
if nlim[Channel][Life][Medmass] == "none":
for Mass in range(len(mass)):
FLUX_p.append([mass[Mass],1])
SD_p.append([mass[Mass],1])
FLUX_i = ING.Graph(FLUX_p)
SD_i = ING.Graph(SD_p)
FLUX_b.append(FLUX_i)
SD_b.append(SD_i)
continue
for Mass in range(len(mass)):
if N_mu[Mass][Channel][Life][Medmass] == "none" or (N_mu[Mass][Channel][Life][Medmass]+N_amu[Mass][Channel][Life][Medmass]) == 0.0:
continue
if ACC[Channel][Life][Medmass].Eval(mass[Mass]) == 0.0:
continue
flux = nlim[Channel][Life][Medmass].Eval(mass[Mass])*2*365.0*86400*1000000.0/(ACC[Channel][Life][Medmass].Eval(mass[Mass])) #the factor of 2 accounts for the treatment of neutrinos and antineutrinos
capt = flux*4.0*np.pi*np.power(AU,2)/((N_mu[Mass][Channel][Life][Medmass]+N_amu[Mass][Channel][Life][Medmass])*365.0*86400) #capture rate
FLUX_p.append([mass[Mass],flux])
SD_p.append([mass[Mass],capt/fluxconv2.Eval(mass[Mass])])
FLUX_i = ING.Graph(FLUX_p)
SD_i = ING.Graph(SD_p)
FLUX_b.append(FLUX_i)
SD_b.append(SD_i)
FLUX_a.append(FLUX_b)
SD_a.append(SD_b)
FLUX.append(FLUX_a)
SD.append(SD_a)
fig, ax = plt.subplots()
plt.loglog([x[0] for x in FLUX[0][3][1].points],[x[1] for x in FLUX[0][3][1].points],"purple",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3, bb',linewidth=1.5)
plt.loglog([x[0] for x in FLUX[1][4][2].points],[x[1] for x in FLUX[1][4][2].points],"k",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3 WW',linewidth=1.5)
plt.loglog([x[0] for x in FLUX[2][4][1].points],[x[1] for x in FLUX[2][4][1].points],"r",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3 tt',linewidth=1.5)
plt.loglog([x[0] for x in FLUX[3][4][1].points],[x[1] for x in FLUX[3][4][1].points],"darkgreen",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3 nunu',linewidth=1.5)
ax.tick_params(axis='both', length=12, width=1)
ax.tick_params(axis='both', which='minor', length=9)
plt.title(r"Flux sensitivity")
plt.ylim((1e5,1e10))
plt.xlim((1e2,1e5))
legend = plt.legend(loc='upper right')#,bbox_to_anchor=(1.1, 1.0))
for label in legend.get_lines():
label.set_linewidth(1.5)
#plt.text(230.0,5e5,"IceCube Preliminary",color="r")
plt.ylabel(r"Flux [Yr$^{-1}$km$^{-2}]$")
plt.xlabel(r"M$_{\rm DM}$ [GeV]")
plt.savefig("/home/ctoennis/analyses/standard_analysis_framework/flux_new.png",format="png")
plt.clf()
fig, ax = plt.subplots()
#print(SD[0])
plt.loglog([x[0] for x in SDCS_ardid.points],[x[1] for x in SDCS_ardid.points],"purple",label=r'Antares',linewidth=1.5,linestyle='--')
plt.loglog([x[0] for x in SD[0][4][2].points],[x[1] for x in SD[0][4][2].points],"darkgreen",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3, $V \to b \bar b$',linewidth=1.5)
plt.loglog([x[0] for x in SD[1][4][2].points],[x[1] for x in SD[1][4][2].points],"b",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3, $V \to W^+ W^-$',linewidth=1.5)
plt.loglog([x[0] for x in SD[2][4][1].points[1:]],[x[1] for x in SD[2][4][1].points[1:]],"r",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3, $V \to \tau \bar \tau$',linewidth=1.5)
plt.loglog([x[0] for x in SD[3][4][1].points[1:]],[x[1] for x in SD[3][4][1].points[1:]],"k",label=r'$\gamma c \tau / R_{\rm sun}$ = 4.3, $V \to \nu \bar \nu$',linewidth=1.5)
plt.loglog([x[0] for x in SDCS_HAWC_tau.points],[x[1] for x in SDCS_HAWC_tau.points],"r",label=r'HAWC 4 year, $V \to 2 \tau$ ',linewidth=1.5,linestyle='-.')
plt.xlim((1e2,1e5))
plt.ylim((1e-9,1e0))
plt.title(r"Sensitivity")
ax.tick_params(axis='both', length=12, width=1)
ax.tick_params(axis='both', which='minor', length=9)
plt.gca().yaxis.set_minor_locator(mlp.ticker.LogLocator(base=10,subs=range(10)))
legend = plt.legend(loc='upper right')
for label in legend.get_lines():
label.set_linewidth(1.5)
#plt.text(430.0,5e-8,"IceCube Preliminary",color="r")
plt.ylabel(r"$\sigma_{\rm SD}$ [pb]")
plt.xlabel(r"M$_{\rm DM}$ [GeV]")
plt.savefig("/home/ctoennis/analyses/standard_analysis_framework/SDCS_new.png",format="png")
plt.clf()
fig, ax = plt.subplots()
plt.loglog([x[0] for x in SD[0][3][2].points],[x[1] for x in SD[0][3][2].points],"darkgreen",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.43, $V \to b \bar b$',linewidth=1.5)
plt.loglog([x[0] for x in SD[1][3][2].points],[x[1] for x in SD[1][3][2].points],"b",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.43, $V \to W^+ W^-$',linewidth=1.5)
plt.loglog([x[0] for x in SD[2][3][1].points[1:]],[x[1] for x in SD[2][3][1].points[1:]],"r",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.43, $V \to \tau \bar \tau$',linewidth=1.5)
plt.loglog([x[0] for x in SD[3][3][1].points[1:]],[x[1] for x in SD[3][3][1].points[1:]],"k",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.43, $V \to \nu \bar \nu$',linewidth=1.5)
plt.xlim((1e2,1e5))
plt.ylim((1e-9,1e0))
plt.title(r"Sensitivity")
ax.tick_params(axis='both', length=12, width=1)
ax.tick_params(axis='both', which='minor', length=9)
plt.gca().yaxis.set_minor_locator(mlp.ticker.LogLocator(base=10,subs=range(10)))
legend = plt.legend(loc='upper right')
for label in legend.get_lines():
label.set_linewidth(1.5)
#plt.text(430.0,5e-8,"IceCube Preliminary",color="r")
plt.ylabel(r"$\sigma_{\rm SD}$ [pb]")
plt.xlabel(r"M$_{\rm DM}$ [GeV]")
plt.savefig("/home/ctoennis/analyses/standard_analysis_framework/SDCS_1s.png",format="png")
plt.clf()
fig, ax = plt.subplots()
plt.loglog([x[0] for x in SDCS_IC_bb.points],[x[1] for x in SDCS_IC_bb.points],"darkgreen",label=r'Jeff Regular DM $b \bar b$',linewidth=1.5,linestyle='-.')
plt.loglog([x[0] for x in SDCS_IC_WW.points],[x[1] for x in SDCS_IC_WW.points],"b",label=r'Jeff Regular DM $W^+ W^- $ ',linewidth=1.5,linestyle='-.')
plt.loglog([x[0] for x in SDCS_IC_tt.points],[x[1] for x in SDCS_IC_tt.points],"r",label=r'Jeff Regular DM $\tau \bar \tau $ ',linewidth=1.5,linestyle='-.')
plt.loglog([x[0] for x in SD[0][0][2].points],[x[1] for x in SD[0][0][2].points],"darkgreen",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.0043, $V \to b \bar b$',linewidth=1.5)
plt.loglog([x[0] for x in SD[1][0][2].points],[x[1] for x in SD[1][0][2].points],"b",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.0043, $V \to W^+ W^-$',linewidth=1.5)
plt.loglog([x[0] for x in SD[2][0][2].points[1:]],[x[1] for x in SD[2][0][2].points[1:]],"r",label=r'$\gamma c \tau / R_{\rm sun}$ = 0.0043, $V \to \tau \bar \tau$',linewidth=1.5)
plt.xlim((2e2,1e4))
plt.ylim((1e-6,1e2))
plt.title(r"Sensitivity")
ax.tick_params(axis='both', length=12, width=1)
ax.tick_params(axis='both', which='minor', length=9)
legend = plt.legend(loc='upper right')
plt.gca().yaxis.set_minor_locator(mlp.ticker.LogLocator(base=10,subs=range(10)))
for label in legend.get_lines():
label.set_linewidth(1.5)
#plt.text(430.0,5e-8,"IceCube Preliminary",color="r")
plt.ylabel(r"$\sigma_{\rm SD}$ [pb]")
plt.xlabel(r"M$_{\rm DM}$ [GeV]")
plt.savefig("/home/ctoennis/analyses/standard_analysis_framework/SDCS_new_short.png",format="png")