import WimPyDD as WD
import numpy as np
import matplotlib.pyplot as pl


pl.clf()
vmin, delta_eta0=WD.streamed_halo_function()

pl.clf()

# defines the effective Hamiltonian for spin-independent interaction parameterizing the Wilson coefficients
# interms of the effective scale M: c_1^tau=[c_1,c_1^1]=[c_1^p+c_1^n,c_1^p+c_1^n] with c_1^p=c_1^n=1/M^2
SI_M=WD.eft_hamiltonian('SI',{1: lambda M:1./M**2*np.array([2,0])})

# loads response functions for built-in experiment WD.XENON_1T_2018 (j_chi=0.5 defalult spin value)
WD.load_response_functions(WD.XENON_1T_2018,SI_M,verbose=False)

# calling mchi_vs_exclusion without passing M corresponds to setting M=1 (holds for any parameter without a default value
# the rate is proportional to 1/M^4, so the exclusion plot is on the same quantity.
mchi,one_over_M4=WD.mchi_vs_exclusion(WD.XENON_1T_2018, SI_M, vmin,delta_eta0)

# plots M=(1/M^4)^(-1/4)
pl.plot(mchi,one_over_M4**(-1./4.))
pl.xlabel('$m_\chi$ (GeV)')
pl.ylabel('$M$ (GeV)')
pl.xscale('log')
pl.yscale('log')
pl.show()