def f_integral_surfaceroche_v2(theta,omega,psi,x):
"""
Returns the integral of x over the equipotential surface.
I = \int_S x(\theta) \mathrm{d}S
"""
if len(theta) < 2 or len(x) < 2 or len(theta) != len(x):
func_name = sys._getframe().f_code.co_name
print '<<',func_name,'>>'
print 'There is something wrong with the integration!'
print ''
return np.nan
for i in xrange(0,len(theta)):
if not (theta[i] >= 0.0*np.pi and theta[i] <= 0.5*np.pi):
func_name = sys._getframe().f_code.co_name
print '<<',func_name,'>>'
print 'The thetas you gave me are out of the desired range!'
print ''
return np.nan
if i > 0 and theta[i] <= theta[i-1]:
func_name = sys._getframe().f_code.co_name
print '<<',func_name,'>>'
print 'The thetas you gave me are not in ascending order!'
print ''
return np.nan
npts=len(theta)
dtheta=np.array([theta[i+1]-theta[i] for i in xrange(0,len(theta)-1)])
rocheradius=np.array([f_rocheradius(theta[i],omega,psi) for i in xrange(0,len(dtheta))])
ds=np.array([f_dalinha(theta[i],omega,psi,dtheta[i]) for i in xrange(0,len(dtheta))])
integral_roche=2.*lrr.integrate_trapezia(x,ds)
return integral_roche
def f_vw(omega,psi,npts):
"""Returns the volume inside the equipotential surface."""
thetamin=0.0; thetamax=0.5*np.pi
theta=np.array([thetamin+(thetamax-thetamin)*float(i)/float(npts-1) for i in xrange(0,npts)])
rocheradius=np.array([f_rocheradius(theta[i],omega,psi) for i in xrange(0,len(theta))])
integ=np.array([0.5*np.sin(theta[i])*rocheradius[i]**3. for i in xrange(0,len(theta))])
dtheta=np.array([theta[i+1]-theta[i] for i in xrange(0,len(theta)-1)])
vw=2.*lrr.integrate_trapezia(integ,dtheta)
return vw
def f_M_disk(outputs_list_element):
M_disk=[]
Req2=(outputs_list_element[1][6]*phc.Rsun.cgs)**2.
ln_relR=outputs_list_element[4]
d_ln_relR=np.array([outputs_list_element[4][j+1]-outputs_list_element[4][j] for j in xrange(0,len(outputs_list_element[4])-1)])
relR=outputs_list_element[5]
# over iterations...
for i in xrange(0,len(outputs_list_element[8])):
Sigmas=np.array([elem for elem in outputs_list_element[12][:,i]])
M_disk.append(2.*np.pi*Req2*lrr.integrate_trapezia(relR**2.*Sigmas,d_ln_relR))
return np.array([elem for elem in M_disk])
def f_M_disk(outputs_list_element):
M_disk = []
Req2 = (outputs_list_element[1][6] * phc.Rsun.cgs)**2.
ln_relR = outputs_list_element[4]
d_ln_relR=np.array([outputs_list_element[4][j+1]-outputs_list_element[4][j] \
for j in xrange(0,len(outputs_list_element[4])-1)])
relR = outputs_list_element[5]
# over iterations...
for i in xrange(0, len(outputs_list_element[8])):
Sigmas = np.array([elem for elem in outputs_list_element[12][:, i]])
M_disk.append(2. * np.pi * Req2 *
lrr.integrate_trapezia(relR**2. * Sigmas, d_ln_relR))
return np.array([elem for elem in M_disk])
def f_vw(omega,psi,npts):
"""Returns the volume inside the equipotential surface."""
thetamin=0.0; thetamax=0.5*np.pi
theta=np.array([thetamin+(thetamax-thetamin)*\
float(i)/float(npts-1) for i in xrange(0,npts)])
rocheradius=np.array([f_rocheradius(theta[i],omega,psi) \
for i in xrange(0,len(theta))])
integ=np.array([0.5*np.sin(theta[i])*rocheradius[i]**3. \
for i in xrange(0,len(theta))])
dtheta=np.array([theta[i+1]-theta[i] \
for i in xrange(0,len(theta)-1)])
vw=2.*lrr.integrate_trapezia(integ,dtheta)
return vw
def f_J_disk(outputs_list_element):
J_disk=[]
Req=outputs_list_element[1][6]*phc.Rsun.cgs
Req2=(outputs_list_element[1][6]*phc.Rsun.cgs)**2.
massa=outputs_list_element[1][5]
leq=(phc.G.cgs*massa*phc.Msun.cgs*Req)**0.5
ln_relR=outputs_list_element[4]
d_ln_relR=np.array([outputs_list_element[4][j+1]-outputs_list_element[4][j] for j in xrange(0,len(outputs_list_element[4])-1)])
relR=outputs_list_element[5]
# over iterations...
for i in xrange(0,len(outputs_list_element[8])):
Sigmas=np.array([elem for elem in outputs_list_element[12][:,i]])
J_disk.append(2.*np.pi*Req2*leq*lrr.integrate_trapezia(relR**2.5*Sigmas,d_ln_relR))
return np.array([elem for elem in J_disk])
def f_J_disk(outputs_list_element):
J_disk = []
Req = outputs_list_element[1][6] * phc.Rsun.cgs
Req2 = (outputs_list_element[1][6] * phc.Rsun.cgs)**2.
massa = outputs_list_element[1][5]
leq = (phc.G.cgs * massa * phc.Msun.cgs * Req)**0.5
ln_relR = outputs_list_element[4]
d_ln_relR=np.array([outputs_list_element[4][j+1]-outputs_list_element[4][j] \
for j in xrange(0,len(outputs_list_element[4])-1)])
relR = outputs_list_element[5]
# over iterations...
for i in xrange(0, len(outputs_list_element[8])):
Sigmas = np.array([elem for elem in outputs_list_element[12][:, i]])
J_disk.append(2. * np.pi * Req2 * leq *
lrr.integrate_trapezia(relR**2.5 * Sigmas, d_ln_relR))
return np.array([elem for elem in J_disk])
def f_integral_surfaceroche(theta, omega, psi, x):
"""
Returns the integral of x over the equipotential surface.
$I = \int_S x(\theta) \mathrm{d}S$
"""
if len(theta) < 2 or len(x) < 2 or len(theta) != len(x):
func_name = sys._getframe().f_code.co_name
print('<<', func_name, '>>')
print('There is something wrong with the integration!')
print('')
return np.nan
for i in xrange(0, len(theta)):
if not (theta[i] >= 0.0 * np.pi and theta[i] <= 0.5 * np.pi):
func_name = sys._getframe().f_code.co_name
print('<<', func_name, '>>')
print('The thetas you gave me are out of the desired range!')
print('')
return np.nan
if i > 0 and theta[i] <= theta[i - 1]:
func_name = sys._getframe().f_code.co_name
print('<<', func_name, '>>')
print('The thetas you gave me are not in ascending order!')
print('')
return np.nan
npts = len(theta)
dtheta=np.array([theta[i+1]-theta[i] \
for i in xrange(0,len(theta)-1)])
rocheradius=np.array([f_rocheradius(theta[i],omega,psi) \
for i in xrange(0,len(dtheta))])
drochedtheta=np.array([f_drochedtheta(theta[i],omega,psi) \
for i in xrange(0,len(dtheta))])
roche_dafac=np.array([f_roche_dafac(rocheradius[i],\
drochedtheta[i]) for i in xrange(0,len(dtheta))])
ds=np.array([f_ds(theta[i],dtheta[i],2.*np.pi,roche_dafac[i]) \
for i in xrange(0,len(dtheta))])
integral_roche = 2. * lrr.integrate_trapezia(x, ds)
return integral_roche
def line_observables(Bralpha,Pfgamma,Brgamma,Humphreys,Brackets,BL,RL,\
files_fullsed_new, fullsed_contents):
"""
In this procedure, the interesting line observables are calculated for
each of the desired lines.
"""
for ifile in xrange(0, len(files_fullsed_new)):
print("Obtaining line observables for file")
print(files_fullsed_new[ifile][0])
### First, the line observables of the desired lines are calculated
### Line observables for the Br alpha
hwidth = lbc_Bralpha[1]
lbc = lbc_Bralpha[0]
contents = fullsed_contents[ifile][1]
auxilinflux,auxiew,auxiPS,auxiFWHM = \
obtaining_flux_ew_PS(contents,lbc,hwidth)
Bralpha.append([auxilinflux, auxiew, auxiPS, auxiFWHM])
### Line observables for the Br gamma
hwidth = lbc_Brgamma[1]
lbc = lbc_Brgamma[0]
contents = fullsed_contents[ifile][1]
auxilinflux,auxiew,auxiPS,auxiFWHM = \
obtaining_flux_ew_PS(contents,lbc,hwidth)
Brgamma.append([auxilinflux, auxiew, auxiPS, auxiFWHM])
### Line observables for the Pf gamma
hwidth = lbc_Pfgamma[1]
lbc = lbc_Pfgamma[0]
contents = fullsed_contents[ifile][1]
auxilinflux,auxiew,auxiPS,auxiFWHM = \
obtaining_flux_ew_PS(contents,lbc,hwidth)
Pfgamma.append([auxilinflux, auxiew, auxiPS, auxiFWHM])
### Line observables for the Bracket's
Bracketsauxi = []
for iHump in range(0, len(lbc_Bracketoth)):
hwidth = lbc_Bracketoth[iHump][1]
lbc = lbc_Bracketoth[iHump][0]
contents = fullsed_contents[ifile][1]
auxilinflux,auxiew,auxiPS,auxiFWHM = \
obtaining_flux_ew_PS(contents,lbc,hwidth)
Bracketsauxi.append([auxilinflux, auxiew, auxiPS, auxiFWHM])
Brackets.append(Bracketsauxi)
### Line observables for the Humphrey's
Humphreysauxi = []
for iHump in range(0, len(lbc_Humphreyoth)):
hwidth = lbc_Humphreyoth[iHump][1]
lbc = lbc_Humphreyoth[iHump][0]
contents = fullsed_contents[ifile][1]
auxilinflux,auxiew,auxiPS,auxiFWHM = \
obtaining_flux_ew_PS(contents,lbc,hwidth)
Humphreysauxi.append([auxilinflux, auxiew, auxiPS, auxiFWHM])
Humphreys.append(Humphreysauxi)
### Now, obtaining the B and R fluxes defined by
### Mennickent et al. 2009PASP..121..125M
print("Obtaining the B and R fluxes defined by Mennickentet al. 2009.")
contents = fullsed_contents[ifile][1]
BLfluxauxi = []
RLfluxauxi = []
### Loop over inclinations
for incs in range(0, len(contents[1])):
xlp = contents[2][incs, :, 0] ### lambda [microns]
ylp = contents[2][incs, :, 1] ### HDUST's flux [microns^-1]
Nnpts = 50 ### this number must be >= 3. A good choice is 50.
### Obtaining F(BL) [erg/s cm^2]
llamb = np.array([lamb1_BL+(lamb2_BL-lamb1_BL)/\
float(Nnpts-1)*float(i) for i in range(0,Nnpts)])
dllamb = np.array(
[llamb[i + 1] - llamb[i] for i in range(0, Nnpts - 1)])
ylpf = np.array([lrr.interpLinND([llamb[i]],[xlp],ylp) \
for i in range(0,Nnpts)])
BLflux = lrr.integrate_trapezia(ylpf, dllamb)
BLflux = BLflux * contents[4][3]*phc.Lsun.cgs/4./np.pi/\
(dist_std*phc.pc.cgs)**2.
BLfluxauxi.append(BLflux)
### Obtaining F(RL) [erg/s cm^2]
llamb = np.array([lamb1_RL+(lamb2_RL-lamb1_RL)/\
float(Nnpts-1)*float(i) for i in range(0,Nnpts)])
dllamb = np.array(
[llamb[i + 1] - llamb[i] for i in range(0, Nnpts - 1)])
ylpf = np.array([lrr.interpLinND([llamb[i]],[xlp],ylp) \
for i in range(0,Nnpts)])
RLflux = lrr.integrate_trapezia(ylpf, dllamb)
RLflux = RLflux * contents[4][3]*phc.Lsun.cgs/4./np.pi/\
(dist_std*phc.pc.cgs)**2.
RLfluxauxi.append(RLflux)
BLfluxauxi = np.array(BLfluxauxi)
BL.append(BLfluxauxi)
RLfluxauxi = np.array(RLfluxauxi)
RL.append(RLfluxauxi)
return Bralpha, Pfgamma, Brgamma, Humphreys, Brackets, BL, RL
linflux = spt.absLineCalc(xplot, ylp[idx], vw=hwidth)
linflux=linflux * contents[4][3]*phc.Lsun.cgs/4./np.pi/\
(dist_std*phc.pc.cgs)**2.*1e5*lbc/phc.c.cgs
linfluxes.append(linflux / linflux19)
plt.plot(wvlengths, linfluxes, color=colorvec[ii])
#plt.subplot(212)
Nnpts = 50
llamb=np.array([lamb1_BL+(lamb2_BL-lamb1_BL)/\
float(Nnpts-1)*float(i) for i in range(0,Nnpts)])
dllamb = np.array(
[llamb[i + 1] - llamb[i] for i in range(0, Nnpts - 1)])
ylpf=np.array([lrr.interpLinND([llamb[i]],[xlp],ylp) \
for i in range(0,Nnpts)])
BLflux = lrr.integrate_trapezia(ylpf, dllamb)
BLflux=BLflux * contents[4][3]*phc.Lsun.cgs/4./np.pi/\
(dist_std*phc.pc.cgs)**2.
print(BLflux)
llamb=np.array([lamb1_RL+(lamb2_RL-lamb1_RL)/\
float(Nnpts-1)*float(i) for i in range(0,Nnpts)])
dllamb = np.array(
[llamb[i + 1] - llamb[i] for i in range(0, Nnpts - 1)])
ylpf=np.array([lrr.interpLinND([llamb[i]],[xlp],ylp) \
for i in range(0,Nnpts)])
RLflux = lrr.integrate_trapezia(ylpf, dllamb)
RLflux=RLflux * contents[4][3]*phc.Lsun.cgs/4./np.pi/\
(dist_std*phc.pc.cgs)**2.
print(RLflux)
lbc = lbc_Humphrey14
