Example #1
0
	def params2spec(self,d,params,components=False):
		# start with the powerlaw spectrum:
		norm = params[0]		# powerlaw norm (photons/s/keV/cm^2 at 1 keV)
		alpha = params[1]	# photon index of powerlaw (dimensionless)
		nH = params[2]		# in units of 10^22 atoms/cm^2
		Espec = zeros(len(d.energies))

		# powerlaw spectrum (ph/s/cm^2/keV)
		c1 = norm*d.energies**(-alpha)	
		Espec += c1
	
		# Sc line (adjust flux only):
		#Espec += lines.shell(d.energies, 4000, params[3].getValue())
		c2 = lines.delta(d.energies, params[3])
		#Espec += lines.spitzer(d.energies, params[3].getValue())
		Espec += c2

		comps = [c1,c2]

		# add the nuisance gaussian lines:
		npar = len(params)
		for i in [npar-6, npar-3]:			# hard coded! 2 nuisance lines!
			area = params[i]		# photons/s/cm^2
			center = params[i+1]	# keV
			sigma = params[i+2]	# keV

			# ph/s/cm^2/keV :
			#Espec += area/sigma/sqrt(2*pi)*exp( -(self.energies-center)**2/2/sigma**2 )
			cn = lines.gaussian(d.energies, area, center, sigma)
			Espec += cn
			comps.append(cn)
	
		# account for binning, which is \int_{E_l}^{E_h} dE S(E)
		dE = roll(d.energies,-1) - d.energies
		dE[-1] = dE[-2]

		# trapezoidal integration:
		dSpec = roll(Espec,-1) - Espec
		dSpec[-1] = dSpec[-2]
		Espec = dE*Espec - dE*dSpec/2			# ph/s/cm^2
		
		Espec *= d.exposure					# photons/cm^2
		Espec *= self.transmission**nH			# dimmer photons/cm^2

		# for plotting purposes:
		if components:
			compsOut = []
			for c in comps:
				dSpec = roll(c,-1) - c
				dSpec[-1] = dSpec[-2]
				c = dE*c - dE*dSpec/2			# ph/s/cm^2
				c *= d.exposure
				c *= self.transmission**nH
				compsOut.append(c)

			return Espec, compsOut
		else:
			return Espec
Example #2
0
	def params2spec(self,params):
		# start with the powerlaw spectrum:
		norm = params[0].getValue()		# powerlaw norm (photons/s/keV/cm^2 at 1 keV)
		alpha = params[1].getValue()	# photon index of powerlaw (dimensionless)
		nH = params[2].getValue()		# in units of 10^22 atoms/cm^2
		
		# powerlaw spectrum (ph/s/cm^2/keV)
		Espec = norm*self.energies**(-alpha)	
	
		# Sc line (adjust flux only):
		#Espec += lines.shell(self.energies, 4000, params[3].getValue())
		Espec += lines.delta(self.energies, params[3].getValue())
		#Espec += lines.spitzer(self.energies, params[3].getValue())

		# add the nuisance gaussian lines:
		npar = len(params)
		for i in [npar-6, npar-3]:			# hard coded! 2 nuisance lines!
			area = params[i].getValue()		# photons/s/cm^2
			center = params[i+1].getValue()	# keV
			sigma = params[i+2].getValue()	# keV

			# ph/s/cm^2/keV :
			#Espec += area/sigma/sqrt(2*pi)*exp( -(self.energies-center)**2/2/sigma**2 )
			Espec += lines.gaussian(self.energies, area, center, sigma)
		
		# account for binning, which is \int_{E_l}^{E_h} dE S(E)
		dE = np.roll(self.energies,-1) - self.energies
		dE[-1] = dE[-2]

		# trapezoidal integration:
		dSpec = np.roll(Espec,-1) - Espec
		dSpec[-1] = dSpec[-2]
		Espec = dE*Espec - dE*dSpec/2			# ph/s/cm^2
		
		Espec *= self.exposure					# photons/cm^2
		Espec *= self.transmission**nH			# dimmer photons/cm^2
		return Espec
Example #3
0
File: snr.py Project: jmrv/scandium
def sourceSpectrum(E, linemode = 2, confused = True):
	'''
	produce a true spectrum (pre-instrument) from parameters:
		params = [norm, alpha, Sc area, line 1 area, line 2 area]
	assuming 25 eV natural sigma for all lines; fix them at known energies

	modes:
		0: delta
		1: shell
		2: broadened
		3: spitzer
	'''
	sourceComponents = []

	# start with the powerlaw spectrum:
	norm = params[0]		# powerlaw norm (photons/s/keV/cm^2 at 1 keV)
	alpha = params[1]	# photon index of powerlaw (dimensionless)
	nH = params[2]		# in units of 10^22 atoms/cm^2

	# powerlaw spectrum (ph/s/cm^2/keV)
	c1 = norm*E**(-alpha)	
	sourceComponents.append(c1)

	# Sc line (adjust flux only):
	if linemode == 0:
		c2 = lines.delta(E, params[3])
		print 'delta function Sc line'
	elif linemode == 1:
		c2 = lines.shell(E, 2000, params[3])
		print 'thin shell Sc line'
	elif linemode == 2:
		c2 = lines.gaussian(E, params[3], 4.09, 0.010)
		print 'broadened (10 eV sigma) Sc line'
	elif linemode == 3:
		c2 = lines.spitzer(E, params[3])
		print 'spitzer Sc line'
		
	#print 'sc flux: %.2f' % (params[3]*1.7e5*388)
	sourceComponents.append(c2)

	# add the nuisance gaussian lines:
	for i in [4, 7]:			# hard coded! 2 nuisance lines!
		area = params[i]		# photons/s/cm^2
		center = params[i+1]	# keV
		s = params[i+2]			# keV

		# ph/s/cm^2/keV :
		#Espec += area/sigma/sqrt(2*pi)*exp( -(self.energies-center)**2/2/sigma**2 )
		ci = lines.gaussian(E, area, center, s)
		sourceComponents.append(ci)

	# confusing nearby lines:
	if confused:
		print 'confused spectrum'
		sourceComponents.append(lines.gaussian(E, params[3]*1.05, 4.22, 0.010))
		sourceComponents.append(lines.gaussian(E, params[3]*0.85, 4.04, 0.012))
		sourceComponents.append(lines.gaussian(E, params[3]*0.85, 4.22, 0.008))
		sourceComponents.append(lines.gaussian(E, params[3]*1.45, 4.13, 0.015))
		sourceComponents.append(lines.gaussian(E, params[3]*0.75, 3.98, 0.010))

	for c in sourceComponents:
		c *= phabs**nH						# absorption: dimmer ph/s/cm^2/kev

	return sourceComponents