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generate_compatible_profiles.py
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generate_compatible_profiles.py
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#this class generates n_i, n_z and Phi for a given n_e, T_e, T_i and T_z
#so that that the orderings in PERFECT are satisfied
from __future__ import division
from perfect_simulation import perfect_simulation,normalized_perfect_simulation #to get info about simulation
import h5py #to write profiles
import numpy #matrix things, etc
from bezier_transition import bezier_transition,derivative_bezier_transition #for smooth transition between 2 functionsx
import scipy.constants #constants
import scipy.optimize
import os
from nu_r import nu_r #nu_r
from coulomb_logarithms import lambda_ee as coulombLog #lambda=ln(Lambda)
from perfectProfilesFile import perfectProfiles
from perfectGlobalMultiplierProfileFile import create_globalMultiplier_of_Npsi
from set_species_param import set_species_param
from mtanh import generate_m2tanh_profile, extrapolate_m2tanh_sections, match_heat_flux_proxy, derivative_m3tanh_transition
from sinusoidal import generate_sin_profile
from generate_nonuniform_grid import generate_nonuniform_grid_Int_arctan
from global_multiplier import generate_global_multiplier
from n_mtanh import n_mtanh_const_delta_from_n_LCFS
from T_mtanh import T_mtanh_const_delta_from_T_LCFS
#for debugging purposes
import matplotlib.pyplot as plt
#print things
verbose=False
###############################
# GLOBAL VARIABLES
psiMinPed = None #pedestal start in psiN
psiMaxPed = None #pedestal end in psiN
psiMin = None #domain start in psiN
psiMax = None #domain end in psiN
Nspecies = None
mtanh = None
mtanh_const_delta = None
species = None
dxdpsiN_at_a = None
psiList = None
pairList = None
Npsi = None
main_index = None
e_index = None
imp_index = None
Zs = None
ms = None
#Needed to extrapolate to final constant Phi
TiHatPed = None
etaiHatPed = None
#Needed for eta_i
TiHatAft = None
dTiHatAftdpsi = None
specialeta = None
niPed = None
niCoreGrad = None
dniHatAftdpsi = None
niHatPed = None
niHatAft = None
# Needed for constant n_e case
neHatPre = None
dneHatPredpsi = None
# Needed for mtanh_const_delta profiles
deltaT = None
AT = None
TPed = None
globalMode = None
globalDelta = None
globalomega = None
globalPsiAHat = None
# END GLOBAL VARIABLES
##############################
def sample_funclist(f_i,x):
#samples a list of 1d functions f_i
#returns a 2D array A_ij = f_i(x_j)
if isinstance(f_i, (list, tuple, numpy.ndarray)):
f_ij = [f(x) for f in f_i]
else:
#if not a list, we just sample
f_ij = f_i(x)
return numpy.array(f_ij)
def write_outputs(simul,THats,dTHatdss,nHats,dnHatdss,etaHats,detaHatdss,PhiHat,dPhiHatds,psi,dpsi_ds,C):
s = simul.psi
#psi(s)
psiN = psi(s)
psi = psiN/simul.psiAHat
#dpsi_ds(s)
dhds = dpsi_ds(s)
#tranpose
THats = numpy.transpose(sample_funclist(THats,psiN))
dTHatdss = numpy.transpose(sample_funclist(dTHatdss,psiN))
nHats = numpy.transpose(sample_funclist(nHats,psiN))
dnHatdss = numpy.transpose(sample_funclist(dnHatdss,psiN))
etaHats = numpy.transpose(sample_funclist(etaHats,psiN))
detaHatdss = numpy.transpose(sample_funclist(detaHatdss,psiN))
PhiHat = sample_funclist(PhiHat,psiN)
dPhiHatds = sample_funclist(dPhiHatds,psiN)
#convert back to s derivatives
dPhiHatds = dPhiHatds * dhds
dhds = dhds[:,numpy.newaxis]
dTHatdss =dTHatdss * dhds
dnHatdss = dnHatdss * dhds
detaHatdss = detaHatdss * dhds
#if we need to generate a global term multiplier, we do so here.
if simul.inputs.useGlobalTermMultiplier == 1:
C = numpy.transpose(sample_funclist(C,psiN))
create_globalMultiplier_of_Npsi("globalTermMultiplier.h5",Npsi,C)
# Write profiles
#print simul.input_dir+"/"+simul.inputs.profilesFilename
try:
outputfile = perfectProfiles(simul.input_dir+"/"+simul.inputs.profilesFilename)
except IOError:
print "#######################################################"
print simul.input_dir+"/"+simul.inputs.profilesFilename + " already exists, cannot generate input profiles hdf5 file."
print "#######################################################"
else:
if Nspecies == 1:
outputfile.create_profiles_for_Npsi(Npsi,1,PhiHat,dPhiHatds,THats[:,[main_index]],dTHatdss[:,[main_index]],nHats[:,[main_index]],dnHatdss[:,[main_index]],etaHats[:,[main_index]],detaHatdss[:,[main_index]])
elif Nspecies == 2:
outputfile.create_profiles_for_Npsi(Npsi,2,PhiHat,dPhiHatds,THats[:,[main_index,e_index]],dTHatdss[:,[main_index,e_index]],nHats[:,[main_index,e_index]],dnHatdss[:,[main_index,e_index]],etaHats[:,[main_index,e_index]],detaHatdss[:,[main_index,e_index]])
elif Nspecies == 3:
outputfile.create_profiles_for_Npsi(Npsi,Nspecies,PhiHat,dPhiHatds,THats,dTHatdss,nHats,dnHatdss,etaHats,detaHatdss)
else:
print "#######################################################"
print "Nspecies > 3 in profile writing function. How could this happen?"
print "#######################################################"
def get_psiN(nonuniform,simul,**kwargs):
#get new psiN coordinate from input
if nonuniform:
grid_type = kwargs["grid_type"]
if grid_type == "Int_arctan":
a = kwargs["transition_length"]
b = kwargs["pedestal_grid_density"]
c=1
s = simul.inputs.psi
psiAHat=simul.inputs.psiAHat
# by design of non-uniform grid, s[0]=psiN[0], s[-1]=psiN[-1]
# for the physical psiN. Not true for indices between
if "leftshift" in kwargs.keys():
leftshift = (psiMaxPed-psiMinPed)*kwargs["leftshift"]
else:
leftshift = 0
if "rightshift" in kwargs.keys():
rightshift = (psiMaxPed-psiMinPed)*kwargs["rightshift"]
else:
rightshift = 0
psiN1= psiMinPed - leftshift
psiN2= psiMaxPed + rightshift
actual_psi,dactual_psi_ds = generate_nonuniform_grid_Int_arctan(simul.input,a,b,c,psiN1,psiN2)
else:
"generate_compatible_profiles: ERROR: unrecognized grid type!"
exit(1)
#function psiN(s) (here: psi) in terms of psi(s) (here: actual_psi)
psi=lambda x: actual_psi(x)/psiAHat #nonuniform psiN
dpsi_ds = lambda x: dactual_psi_ds(x)/psiAHat
else:
psi= lambda x: x
dpsi_ds = lambda x: 1.0 + 0*x #trivial mapping
return (psi,dpsi_ds)
def update_domain_size(simul,psiN_ped_width,midShift,psiDiamFact,leftBoundaryShift,rightBoundaryShift):
psiMid=1-psiN_ped_width/2.0+midShift
psiDiameter=psiDiamFact*psiN_ped_width
simul.inputs.psiDiameter = psiDiameter
simul.inputs.psiMid = psiMid
simul.inputs.leftBoundaryShift = leftBoundaryShift
simul.inputs.rightBoundaryShift = rightBoundaryShift
def update_species_parameters(species_list,species_filename,norm_filename,simulation):
set_species_param(species_list,species_filename,norm_filename,simulation)
Zs=simulation.inputs.charges
if not isinstance(Zs, (list, tuple, numpy.ndarray)):
Zs=numpy.array([Zs])
ms=simulation.inputs.masses
if not isinstance(Zs, (list, tuple, numpy.ndarray)):
ms=numpy.array([ms])
return (Zs,ms)
def update_Delta_omega(simul):
#print "Delta before:" + str(simul.Delta)
if simul.units=="SI":
Delta = simul.mBar*simul.vBar/(simul.eBar*simul.BBar*simul.RBar)
omega = simul.ePhiBar/(simul.eBar*simul.BBar*simul.RBar*simul.vBar)
simul.inputs.Delta=Delta
simul.inputs.omega=omega
else:
print "Only SI units are currently supported"
return (Delta,omega)
#print "Delta after:" + str(Delta)
def update_nu_r(simul,n,T):
if simul.units=="SI":
logLambda=coulombLog(n,T) #n,T not used beyond this point
print "logLambda: "+str(logLambda)
nur = nu_r(simul.RBar,simul.nBar,simul.TBar,logLambda)
simul.inputs.nu_r=nur
return nur
else:
print "Only SI units are currently supported"
def generate_ne_profile(simul,**kwargs):
global neHatPre
global dneHatPredpsi
# for use in d-He scan where the electron profile is fixed
if "nScale_"+species[e_index] in kwargs.keys():
neScale=kwargs["nScale_"+species[e_index]]
else:
neScale=1.0
nePed=neScale*kwargs["nped_"+species[e_index]]
neCoreGrad=neScale*kwargs["dnCoredx_"+species[e_index]]*dxdpsiN_at_a
nepedGrad=neScale*kwargs["dnpeddx_"+species[e_index]]*dxdpsiN_at_a
neSOLGrad=neScale*kwargs["dnSOLdx_"+species[e_index]]*dxdpsiN_at_a
if mtanh_const_delta:
n_LCFS = nePed + nepedGrad * (psiMaxPed-psiMinPed)
BT = AT/(2*numpy.sqrt(TPed))
(neHat,dneHatds) = n_mtanh_const_delta_from_n_LCFS(nePed,n_LCFS,neCoreGrad,psiMaxPed-psiMinPed,psiMinPed,Zs[e_index],BT,deltaT)
neHatPre = lambda psiN: nePed + neCoreGrad * (psiN - psiMinPed)
dneHatPredpsi = lambda psiN: neCoreGrad + 0.0 * psiN
elif mtanh:
(neHat,dneHatds) = generate_m2tanh_profile(nePed,neCoreGrad,nepedGrad,neSOLGrad,psiMaxPed-psiMinPed,psiMinPed)
#(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(neHat,dneHatds,psiMin,psiMinPed,psiMaxPed,psiMax)
(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(neHat,dneHatds,psiMinPed,psiMinPed,psiMaxPed,psiMaxPed)
neHatPre = core
dneHatPredpsi = ddx_core
else:
neHatPre =(lambda psiN: (nePed-neCoreGrad*(psiMinPed-psiMin) + neCoreGrad* (psiN-psiMin)))
neHatPed =(lambda psiN: (nePed + nepedGrad* (psiN-psiMinPed)))
neHatAft =(lambda psiN: (nePed+nepedGrad*(psiMaxPed-psiMinPed) + neSOLGrad* (psiN-psiMaxPed)))
dneHatPredpsi = (lambda psiN: neCoreGrad + psiN*0)
dneHatPeddpsi = (lambda psiN: nepedGrad + psiN*0)
dneHatAftdpsi = (lambda psiN: neSOLGrad + psiN*0)
nelist=[neHatPre,neHatPed,neHatAft]
dnedpsiList = [dneHatPredpsi,dneHatPeddpsi,dneHatAftdpsi]
(neHat,dneHatdpsi)=derivative_bezier_transition(nelist,dnedpsiList,psiList,pairList)
dneHatds = lambda x : dneHatdpsi(x)
return (neHat,dneHatds)
def generate_ni_profile(**kwargs):
# for use in d-He scan where the electron profile varies
global niPed
global niCoreGrad
global niHatPed
global niHatAft
global dniHatAftdpsi
if "nScale_"+species[main_index] in kwargs.keys():
niScale=kwargs["nScale_"+species[main_index]]
else:
niScale=1.0
niPed=niScale*kwargs["nped_"+species[main_index]]
niCoreGrad=niScale*kwargs["dnCoredx_"+species[main_index]]*dxdpsiN_at_a
nipedGrad=niScale*kwargs["dnpeddx_"+species[main_index]]*dxdpsiN_at_a
niSOLGrad=niScale*kwargs["dnSOLdx_"+species[main_index]]*dxdpsiN_at_a
# generate n_i
if mtanh_const_delta:
print niPed
print nipedGrad
print psiMinPed
print psiMaxPed
n_LCFS = niPed + nipedGrad * (psiMaxPed-psiMinPed)
BT = AT/(2*numpy.sqrt(TPed))
(niHat,dniHatds,niHatAft,dniHatAftdpsi) = n_mtanh_const_delta_from_n_LCFS(niPed,n_LCFS,niCoreGrad,psiMaxPed-psiMinPed,psiMinPed,Zs[main_index],BT,deltaT)
niHatPed = lambda psiN: niPed + nipedGrad * (psiN-psiMinPed)
print "!!!!!!!!!!!!!!!!"
print "desired n_LCFS: " + str(n_LCFS)
print "actual n_LCFS: " + str(niHat(psiMaxPed))
elif mtanh:
(niHat,dniHatds) = generate_m2tanh_profile(niPed,niCoreGrad,nipedGrad,niSOLGrad,psiMaxPed-psiMinPed,psiMinPed)
#(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(niHat,dniHatds,psiMin,psiMinPed,psiMaxPed,psiMax)
(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(niHat,dniHatds,psiMinPed,psiMinPed,psiMaxPed,psiMaxPed)
niHatPed = ped
niHatAft = sol
dniHatAftdpsi = ddx_sol
else:
niHatPre =(lambda psiN: (niPed + niCoreGrad*(psiN-psiMinPed)))
niHatPed =(lambda psiN: (niPed + nipedGrad* (psiN-psiMinPed)))
niHatAft =(lambda psiN: (niPed+nipedGrad*(psiMaxPed-psiMinPed) + niSOLGrad* (psiN-psiMaxPed)))
dniHatPredpsi = (lambda psiN: niCoreGrad + 0*psiN)
dniHatPeddpsi = (lambda psiN: nipedGrad + 0*psiN)
dniHatAftdpsi = (lambda psiN: niSOLGrad + 0*psiN)
nilist=[niHatPre,niHatPed,niHatAft]
dnidpsiList = [dniHatPredpsi,dniHatPeddpsi,dniHatAftdpsi]
(niHat,dniHatds)=derivative_bezier_transition(nilist,dnidpsiList,psiList,pairList)
return (niHat,dniHatds)
def generate_T_profiles_sameflux(nt,nb,breakpoint_shift,T_transition_length,**kwargs):
global TiHatPed
global TiHatAft
global dTiHatAftdpsi
# mtanh_const_delta profiles:
global deltaT
global globalMode
global AT
global TPed
#THats = numpy.zeros((Nspecies,Npsi))
#dTHatdpsis = numpy.zeros((Nspecies,Npsi))
THats = [None]*Nspecies
dTHatdpsis = [None]*Nspecies
dTHatdss = [None]*Nspecies
TScale=[0]*Nspecies
Tpeds=[0]*Nspecies
TCoreGrads=[0]*Nspecies
TpedGrads=[0]*Nspecies
TSOLGrads=[0]*Nspecies
#Pre,Ped,Aft will contain functions describe T in core, ped and outwards.
THatPre=[0]*Nspecies
THatPed=[0]*Nspecies
THatAft=[0]*Nspecies
dTHatPredpsi=[0]*Nspecies
dTHatPeddpsi=[0]*Nspecies
dTHatAftdpsi=[0]*Nspecies
#reading T related parameters
for i in range(Nspecies):
if "TScale_"+species[i] in kwargs.keys():
TScale[i]=kwargs["TScale_"+species[i]]
else:
TScale[i]=1.0
Tpeds[i]=TScale[i]*kwargs["Tped_"+species[i]]
TCoreGrads[i]=TScale[i]*kwargs["dTCoredx_"+species[i]]*dxdpsiN_at_a
TpedGrads[i]=TScale[i]*kwargs["dTpeddx_"+species[i]]*dxdpsiN_at_a
TSOLGrads[i]=TScale[i]*kwargs["dTSOLdx_"+species[i]]*dxdpsiN_at_a
TScale=numpy.array(TScale)
Tpeds=numpy.array(Tpeds)
TCoreGrads=numpy.array(TCoreGrads)
TSOLGrads=numpy.array(TSOLGrads)
TpedGrads=numpy.array(TpedGrads)
if mtanh_const_delta:
transition_length = T_transition_length*(psiMaxPed-psiMinPed)
# we always want the transition to end at the same place and start at the same density...
#... thus we shift the start when we change the transition length
transition_start = psiMinPed - (T_transition_length -1)*(psiMaxPed-psiMinPed)
deltaTe = 0.01
T_LCFS = Tpeds[e_index] + TpedGrads[e_index] * (psiMaxPed - psiMinPed)
#(THats[i],dTHatdss[i],local_AT[i],local_Taft[i],local_dTaftdpsi[i]) = T_parameter_wrapper(Zs[i],Tpeds[i],T_LCFS,TCoreGrads[i],(psiMaxPed - psiMinPed),psiMinPed)
FSARHat=1.0 # since RBar = major radius
RHat=FSARHat # simplify notation by "R=<R>"
Delta = globalDelta
psiAHat = globalPsiAHat
AT = deltaTe*psiAHat/(numpy.sqrt(ms[e_index])*RHat*Delta)
(THats[e_index],dTHatdss[e_index],ATe,Teaft,dTeaftdpsi) = T_mtanh_const_delta_from_T_LCFS(Tpeds[e_index],T_LCFS,TCoreGrads[e_index],(psiMaxPed - psiMinPed),psiMinPed,Zs[e_index],AT)
THats[main_index] = lambda psiN: Tpeds[main_index] + TCoreGrads[main_index] * (psiN - psiMinPed)
dTHatdss[main_index] = lambda psiN: TCoreGrads[main_index] + 0.0* psiN
if globalMode == "const_ne":
AT = ATe
deltaT = deltaTe
TPed = Tpeds[e_index]
elif globalMode == "const_Phi":
deltaTi = 0.1
AT = deltaTi*psiAHat/(numpy.sqrt(ms[main_index])*RHat*Delta)
deltaT = deltaTi
TPed = Tpeds[main_index]
(THats[main_index],dTHatdss[main_index]) = match_heat_flux_proxy(TPed,TpedGrads[main_index],TpedGrads[main_index],TSOLGrads[main_index],transition_length,transition_start,nt,nb,psiMin,psiMax)
#(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(THats[main_index],dTHatdss[main_index],psiMin,psiMinPed,psiMaxPed,psiMax)
(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(THats[main_index],dTHatdss[main_index],psiMinPed,psiMinPed,psiMaxPed,psiMaxPed)
else:
print "generate_compatible_profiles: ERROR: Unrecognized mode!"
sys.exit(2)
print "!!!!!!!!!!!!!!!!"
print "desired T_LCFS: " + str(T_LCFS)
print "actual T_LCFS: " + str(THats[e_index](psiMaxPed))
return (THats,dTHatdss)
elif mtanh:
transition_length = T_transition_length*(psiMaxPed-psiMinPed)
# we always want the transition to end at the same place and start at the same density...
#... thus we shift the start when we change the transition length
transition_start = psiMinPed - (T_transition_length -1)*(psiMaxPed-psiMinPed)
#... and change the Tped
Tped = Tpeds[main_index] - TpedGrads[main_index]*(T_transition_length -1)*(psiMaxPed-psiMinPed)
#(THats[main_index],dTHatdss[main_index]) = match_heat_flux_proxy(Tped,TpedGrads[main_index],TpedGrads[main_index],TSOLGrads[main_index],transition_length,transition_start,nt,nb,psiMin,psiMax)
(THats[main_index],dTHatdss[main_index]) = match_heat_flux_proxy(Tped,TpedGrads[main_index],TpedGrads[main_index],TSOLGrads[main_index],transition_length,transition_start,nt,nb,psiMin,psiMaxPed)
#(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(THats[main_index],dTHatdss[main_index],psiMin,psiMinPed,psiMaxPed,psiMax)
(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(THats[main_index],dTHatdss[main_index],psiMinPed,psiMinPed,psiMaxPed,psiMaxPed)
TiHatPed = ped
TiHatAft = sol
dTiHatAftdpsi = ddx_sol
if Nspecies >= 2:
(THats[e_index],dTHatdss[e_index]) = generate_m2tanh_profile(Tpeds[e_index],TCoreGrads[e_index],TpedGrads[e_index],TSOLGrads[e_index],psiMaxPed-psiMinPed,psiMinPed)
else:
breakpoint=psiMinPed + breakpoint_shift
Tp=Tpeds[main_index] + TCoreGrads[main_index] *(breakpoint-psiMinPed)
if (TCoreGrads[main_index] != TSOLGrads[main_index]) and (TPedGrads[main_index] != TSOLGrads[main_index]):
print "generate_compatible_profiles: Warning: sameflux option uses the Core T gradients of the main species everywhere"
dTdpsi=TCoreGrads[main_index]
d1=breakpoint - psiMin
d2=psiMax - breakpoint
f=lambda x : x*(Tp-d1*x)**(3.0/2.0) - (nb*1.0/nt)*(Tp + dTdpsi*d2)**(3.0/2.0)*dTdpsi
dTdpsiTop=scipy.optimize.fsolve(f,0)[0] #[0] since returns an numpy.ndarray
dTdpsiBot=dTdpsi
THatPre[main_index] =(lambda psiN: (Tpeds[main_index] + dTdpsiTop*(psiN-breakpoint)))
THatPed[main_index] =(lambda psiN: (Tpeds[main_index] + dTdpsiBot*(psiN-breakpoint)))
THatAft[main_index] =(lambda psiN: (Tpeds[main_index] + dTdpsiBot*(psiN-breakpoint)))
dTHatPredpsi[main_index] =(lambda psiN: dTdpsiTop + 0*psiN)
dTHatPeddpsi[main_index] =(lambda psiN: dTdpsiBot + 0*psiN)
dTHatAftdpsi[main_index] =(lambda psiN: dTdpsiBot + 0*psiN)
Tlist=[THatPre[main_index],THatPed[main_index]]
dTdpsilist=[dTHatPredpsi[main_index],dTHatPeddpsi[main_index]]
(THats[main_index],dTHatdpsis[main_index])=derivative_bezier_transition(Tlist,dTdpsilist,[breakpoint],pairList[:-1])
dTHatdss[main_index]= lambda x : dTHatdpsis[main_index](x)
#T2=simul.TBar*bezier_transition(Tlist,[breakpoint],pairList[:-1],numpy.array([psiMidPed]))[0]
TiHatPed = THatPed[main_index]
TiHatAft = THatAft[main_index]
dTiHatAftdpsi = dTHatAftdpsi[main_index]
if Nspecies >= 2:
#T_e:
THatPre[e_index] =(lambda psiN: (Tpeds[e_index] + TCoreGrads[e_index]*(psiN-psiMinPed)))
THatPed[e_index] =(lambda psiN: (Tpeds[e_index] + TpedGrads[e_index]*(psiN-psiMinPed)))
THatAft[e_index] =(lambda psiN: (Tpeds[e_index] + TpedGrads[e_index]*(psiMaxPed-psiMinPed) + TSOLGrads[e_index]*(psiN-psiMaxPed)))
dTHatPredpsi[e_index] = (lambda psiN: TCoreGrads[e_index] + 0*psiN)
dTHatPeddpsi[e_index] = (lambda psiN: TpedGrads[e_index] + 0*psiN)
dTHatAftdpsi[e_index] = (lambda psiN: TSOLGrads[e_index] + 0*psiN)
Tlist=[THatPre[e_index],THatPed[e_index],THatAft[e_index]]
dTdpsiList = [dTHatPredpsi[e_index],dTHatPeddpsi[e_index],dTHatAftdpsi[e_index]]
(THats[e_index],dTHatdpsis[e_index])=derivative_bezier_transition(Tlist,dTdpsiList,psiList,pairList)
dTHatdss[e_index]=lambda x : dTHatdpsis[e_index](x)
if Nspecies == 3:
THats[imp_index]=THats[main_index]
#dTHatdpsis[imp_index]=dTHatdpsis[main_index]
dTHatdss[imp_index]=dTHatdss[main_index]
return (THats,dTHatdss)
def generate_T_profiles(**kwargs):
global TiHatPed
global TiHatAft
global dTiHatAftdpsi
# mtanh_const_delta profiles:
global deltaT
global globalMode
global AT
global TPed
#THats = numpy.zeros((Nspecies,Npsi))
#dTHatdpsis = numpy.zeros((Nspecies,Npsi))
THats = [None]*Nspecies
dTHatdpsis = [None]*Nspecies
dTHatdss = [None]*Nspecies
TScale=[0]*Nspecies
Tpeds=[0]*Nspecies
TCoreGrads=[0]*Nspecies
TpedGrads=[0]*Nspecies
TSOLGrads=[0]*Nspecies
#Pre,Ped,Aft will contain functions describe T in core, ped and outwards.
THatPre=[0]*Nspecies
THatPed=[0]*Nspecies
THatAft=[0]*Nspecies
dTHatPredpsi=[0]*Nspecies
dTHatPeddpsi=[0]*Nspecies
dTHatAftdpsi=[0]*Nspecies
#reading T related parameters
for i in range(Nspecies):
if "TScale_"+species[i] in kwargs.keys():
TScale[i]=kwargs["TScale_"+species[i]]
else:
TScale[i]=1.0
Tpeds[i]=TScale[i]*kwargs["Tped_"+species[i]]
TCoreGrads[i]=TScale[i]*kwargs["dTCoredx_"+species[i]]*dxdpsiN_at_a
TpedGrads[i]=TScale[i]*kwargs["dTpeddx_"+species[i]]*dxdpsiN_at_a
TSOLGrads[i]=TScale[i]*kwargs["dTSOLdx_"+species[i]]*dxdpsiN_at_a
TSOLGrads[i]=TScale[i]*kwargs["dTSOLdx_"+species[i]]*dxdpsiN_at_a
TScale=numpy.array(TScale)
Tpeds=numpy.array(Tpeds)
TCoreGrads=numpy.array(TCoreGrads)
TSOLGrads=numpy.array(TSOLGrads)
TpedGrads=numpy.array(TpedGrads)
if mtanh_const_delta:
deltaTe = 0.01
T_LCFS = Tpeds[e_index] + TpedGrads[e_index] * (psiMaxPed - psiMinPed)
#(THats[i],dTHatdss[i],local_AT[i],local_Taft[i],local_dTaftdpsi[i]) = T_parameter_wrapper(Zs[i],Tpeds[i],T_LCFS,TCoreGrads[i],(psiMaxPed - psiMinPed),psiMinPed)
FSARHat=1.0 # since RBar = major radius
RHat=FSARHat # simplify notation by "R=<R>"
Delta = globalDelta
psiAHat = globalPsiAHat
AT = deltaTe*psiAHat/(numpy.sqrt(ms[e_index])*RHat*Delta)
(THats[e_index],dTHatdss[e_index],ATe,Teaft,dTeaftdpsi) = T_mtanh_const_delta_from_T_LCFS(Tpeds[e_index],T_LCFS,TCoreGrads[e_index],(psiMaxPed - psiMinPed),psiMinPed,Zs[e_index],AT)
THats[main_index] = lambda psiN: Tpeds[main_index] + TCoreGrads[main_index] * (psiN - psiMinPed)
dTHatdss[main_index] = lambda psiN: TCoreGrads[main_index] + 0.0* psiN
if globalMode == "const_ne":
AT = ATe
deltaT = deltaTe
TPed = Tpeds[e_index]
elif globalMode == "const_Phi":
deltaTi = 0.1
AT = deltaTi*psiAHat/(numpy.sqrt(ms[main_index])*RHat*Delta)
deltaT = deltaTi
TPed = Tpeds[main_index]
TiHatAft = THats[main_index]
dTiHatAftdpsi = dTHatdss[main_index]
TiHatPed = THats[main_index]
else:
print "generate_compatible_profiles: ERROR: Unrecognized mode!"
sys.exit(2)
print "!!!!!!!!!!!!!!!!"
print "desired T_LCFS: " + str(T_LCFS)
print "actual T_LCFS: " + str(THats[e_index](psiMaxPed))
return (THats,dTHatdss)
elif mtanh:
for i in range(Nspecies):
(THats[i],dTHatdss[i]) = generate_m2tanh_profile(Tpeds[i],TCoreGrads[i],TpedGrads[i],TSOLGrads[i],psiMaxPed-psiMinPed,psiMinPed)
(core,ped,sol,ddx_core,ddx_ped,ddx_sol) = extrapolate_m2tanh_sections(THats[main_index],dTHatdss[main_index],psiMinPed,psiMinPed,psiMaxPed,psiMaxPed)
TiHatPed = ped
TiHatAft = sol
dTiHatAftdpsi = ddx_sol
else:
#Generating functions from the parameters
for i in range(Nspecies):
THatPre[i] =(lambda psiN,i=i: (Tpeds[i] + TCoreGrads[i]*(psiN-psiMinPed)))
THatPed[i] =(lambda psiN,i=i: (Tpeds[i] + TpedGrads[i]*(psiN-psiMinPed)))
THatAft[i] =(lambda psiN,i=i: (Tpeds[i] + TpedGrads[i]*(psiMaxPed-psiMinPed) + TSOLGrads[i]*(psiN-psiMaxPed)))
dTHatPredpsi[i] = (lambda psiN,i=i: TCoreGrads[i])
dTHatPeddpsi[i] = (lambda psiN,i=i: TpedGrads[i])
dTHatAftdpsi[i] = (lambda psiN,i=i: TSOLGrads[i])
Tlist=[THatPre[i],THatPed[i],THatAft[i]]
dTdpsiList = [dTHatPredpsi[i],dTHatPeddpsi[i],dTHatAftdpsi[i]]
(THats[i],dTHatdpsis[i])=derivative_bezier_transition(Tlist,dTdpsiList,psiList,pairList)
dTHatdss[i]=lambda x,i=i: dTHatdpsis[i](x)
TiHatPed = THatPed[main_index]
TiHatAft = THatAft[main_index]
dTiHatAftdpsi = dTHatAftdpsi[main_index]
return (THats,dTHatdss)
def generate_etai_profile(Delta,omega,**kwargs):
etaiHatPre =(lambda psiN: (niPed+ niCoreGrad* (psiN-psiMinPed)))
detaiHatPredpsi =(lambda psiN: niCoreGrad + 0*psiN)
linear_eta = True
if linear_eta:
return (etaiHatPre,detaiHatPredpsi)
if mtanh_const_delta:
etaiHatAft = lambda psiN: 8*niHatAft(psiN)
detaiHatAftdpsi =lambda psiN: 8*dniHatAftdpsi(psiN)
(etaiHat,detaiHatds) = derivative_m3tanh_transition([etaiHatPre,etaiHatAft],[detaiHatPredpsi,detaiHatAftdpsi],psiMinPed/2+psiMaxPed/2,psiMaxPed-psiMinPed)
elif mtanh: # or mtanh_const_delta:
#PhiTopPoint=psiMax/2.0 + psiMaxPed/2.0
PhiTopPoint=psiMaxPed
print "PhiTopPoint: " +str(PhiTopPoint)
width = (psiMaxPed - psiMinPed)
print "width: " +str(width)
prefactor=1.0
if mtanh_const_delta:
#Note: Aft and ped overlap at top point
PhiTop=prefactor*(TiHatAft(PhiTopPoint)/Zs[main_index])*numpy.log(etaiHatPre(PhiTopPoint)*1.0/niHatAft(PhiTopPoint))*(2.0*omega/Delta)
else:
PhiTop=prefactor*(TiHatPed(PhiTopPoint)/Zs[main_index])*numpy.log(etaiHatPre(PhiTopPoint)*1.0/niHatAft(PhiTopPoint))*(2.0*omega/Delta)
print "niHatAft: " +str(niHatAft(PhiTopPoint))
print "etaiHatPre: " +str(etaiHatPre(PhiTopPoint))
print "TiHatPed: " +str(TiHatPed(PhiTopPoint))
etaiHatAft =(lambda psiN: niHatAft(psiN)*numpy.exp(PhiTop*Zs[main_index]/TiHatAft(psiN)))
detaiHatAftdpsi = (lambda psiN: (dniHatAftdpsi(psiN) - niHatAft(psiN)*PhiTop*Zs[main_index]*dTiHatAftdpsi(psiN)/(TiHatAft(psiN))**2)*numpy.exp(PhiTop*Zs[main_index]/TiHatAft(psiN)))
(etaiHat,detaiHatds) = derivative_m3tanh_transition([etaiHatPre,etaiHatAft],[detaiHatPredpsi,detaiHatAftdpsi],psiMaxPed,width)
#DEBUG PLOT
if verbose:
plot_psi = numpy.linspace(psiMin,psiMax)
plt.hold(True)
plt.plot(plot_psi,etaiHat(plot_psi))
plt.plot(plot_psi,etaiHatPre(plot_psi))
plt.plot(plot_psi,etaiHatAft(plot_psi))
plt.show()
else:
if specialeta:
etaiHatPed =(lambda psiN: (niPed+2*niCoreGrad* (psiN-psiMinPed)))
detaiHatPeddpsi =(lambda psiN: 2*niCoreGrad + 0*psiN)
else:
etaiHatPed =(lambda psiN: (niPed+ niCoreGrad* (psiN-psiMinPed)))
detaiHatPeddpsi =(lambda psiN: niCoreGrad + 0*psiN)
PhiTopPoint=psiMaxPed
prefactor=1.0
PhiTop=prefactor*(TiHatPed(PhiTopPoint)/Zs[main_index])*numpy.log(etaiHatPed(PhiTopPoint)*1.0/niHatPed(PhiTopPoint))*(2.0*omega/Delta)
etaiHatAft =(lambda psiN: niHatAft(psiN)*numpy.exp(PhiTop*Zs[main_index]/TiHatAft(psiN)))
detaiHatAftdpsi = (lambda psiN: (dniHatAftdpsi(psiN) - niHatAft(psiN)*PhiTop*Zs[main_index]*dTiHatAftdpsi(psiN)/(TiHatAft(psiN))**2)*numpy.exp(PhiTop*Zs[main_index]/TiHatAft(psiN)))
etailist=[etaiHatPre,etaiHatPed,etaiHatAft]
detaidpsilist=[detaiHatPredpsi,detaiHatPeddpsi,detaiHatAftdpsi]
(etaiHat,detaiHatds) =derivative_bezier_transition(etailist,detaidpsilist,psiList,pairList)
return (etaiHat,detaiHatds)
def generate_etaz_profile(Delta,omega,**kwargs):
imp_conc=kwargs["imp_conc"]
if specialeta==True:
gradScale=4.0725
etazHatInner=(lambda psiN: imp_conc*(niPed+niCoreGrad*(psiN-psiMinPed)))
etazHatMiddle=(lambda psiN: imp_conc*(niPed-gradScale*niCoreGrad*(psiN-psiMinPed)))
etazHatOuter=(lambda psiN: imp_conc*(niPed-gradScale*niCoreGrad*(psiMaxPed-psiMinPed) + niCoreGrad* (psiN-psiMaxPed)))
detazHatInnerdpsi=(lambda psiN: imp_conc*niCoreGrad)
detazHatMiddledpsi=(lambda psiN: -imp_conc*gradScale*niCoreGrad)
detazHatOuterdpsi=(lambda psiN: imp_conc*niCoreGrad)
etailist=[etazHatInner,etazHatMiddle,etazHatOuter]
detaidpsilist = [detazHatInnerdpsi,detazHatMiddledpsi,detazHatOuterdpsi]
(etazHat,detazHatdpsi) = derivative_bezier_transition(etailist,psiList[:1]+psiList[-1:],pairList[:1]+pairList[-1:])
detazHatds = lambda x : detazHatdpsi(x)
else:
etazHat=lambda x : imp_conc*(niPed+niCoreGrad*(x-psiMinPed))
detazHatds = lambda x: imp_conc*niCoreGrad + 0*x #add 0*x to make it return ndarray when x is one.
return (etazHat,detazHatds)
def generate_Phi_profile(etaiHat,niHat,TiHat,detaiHatdpsi,dniHatdpsi,dTiHatdpsi,Zi,Delta,omega):
PhiHat=lambda x : numpy.log(etaiHat(x)/niHat(x))*TiHat(x)/Zi*Delta/(2*omega)
dPhiHatdpsi=lambda x : (-etaiHat(x)*dniHatdpsi(x)/niHat(x)**2 + detaiHatdpsi(x)/niHat(x))*TiHat(x)*niHat(x)/etaiHat(x) + numpy.log(etaiHat(x)/niHat(x))*dTiHatdpsi(x)
return (PhiHat,dPhiHatdpsi)
def generate_eta_from_n_Phi_profile(nHat,PhiHat,THat,dnHatdpsi,dPhiHatdpsi,dTHatdpsi,Z,Delta,omega):
etaHat=lambda x: nHat(x)*numpy.exp((Z*omega*2/Delta)*PhiHat(x)/THat(x))
detaHatdpsi=lambda x: (dnHatdpsi(x) + (2*omega/Delta)*(nHat(x)*Z/THat(x))*(dPhiHatdpsi(x)-PhiHat(x)*dTHatdpsi(x)/THat(x)))*numpy.exp((Z*omega*2/Delta)*PhiHat(x)/THat(x))
return (etaHat,detaHatdpsi)
def generate_n_from_eta_Phi_profile(etaHat,PhiHat,THat,detaHatdpsi,dPhiHatdpsi,dTHatdpsi,Z,Delta,omega):
nHat=lambda x : etaHat(x)*numpy.exp(-(Z*omega*2/Delta)*PhiHat(x)/THat(x))
dnHatdpsi=lambda x : (detaHatdpsi(x) - (2*omega/Delta)*(etaHat(x)*Z/THat(x))*(dPhiHatdpsi(x)-PhiHat(x)*dTHatdpsi(x)/THat(x)))*numpy.exp(-(Z*omega*2/Delta)*PhiHat(x)/THat(x))
return (nHat,dnHatdpsi)
def generate_n_from_eta_X_profile(etaHat,X,detaHatds,dXds,Z):
nHat=lambda x : etaHat(x)*X(x)**Z
dnHatdpsi=lambda x : detaHatds(x)*X(x)**Z + etaHat(x)*Z*X(x)**(Z-1)*dXds(x)
return (nHat,dnHatdpsi)
def generate_compatible_profiles(simul,xwidth,nonuniform=False,sameflux=False,oldsameflux=False,sameeta=False,samefluxshift=0,specialEta=False,psiDiamFact=5,transitionFact=0.2,dxdpsiN=1,midShift=0,upShift_denom=3.0,downShift_denom=float("Inf"),m2tanh=False,m2tanh_const_delta=False,mode="const_Phi",leftBoundaryShift=0.0,rightBoundaryShift=0.0,T_transition_length=1.0,**kwargs):
#NOTE: uses the dx/dpsi at minor radius for both core and SOL, which assumes that
#simulated region is small enough that it doesn't change much.
if mode == "periodic":
generate_periodic_profiles(simul,xwidth,nonuniform,dxdpsiN,psiDiamFact,midShift,upShift_denom,downShift_denom,leftBoundaryShift,rightBoundaryShift,**kwargs)
return
if (mode == "mtanh_const_delta_eta") or (mode == "mtanh_eta"):
generate_compatible_profiles_etas(simul,xwidth,nonuniform,dxdpsiN,psiDiamFact,midShift,upShift_denom,downShift_denom,leftBoundaryShift,rightBoundaryShift,mode,**kwargs)
return
e=scipy.constants.e
log=numpy.log
exp=numpy.exp
sqrt=numpy.sqrt
global psiMinPed
global psiMaxPed
global psiMin
global psiMax
global Nspecies
global species
global dxdpsiN_at_a
global psiList
global pairList
global Npsi
global main_index
global e_index
global imp_index
global specialeta
global Zs
global ms
global globalDelta
global globalomega
global globalPsiAHat
global mtanh
global mtanh_const_delta
global globalMode
globalMode = mode
mtanh_const_delta = m2tanh_const_delta
mtanh = m2tanh
specialeta = specialEta
species=simul.species
Nspecies=len(species)
#intepret possible keywords in the keyword-argument dict kwargs
if Nspecies == 1:
main_index=kwargs["mI"]
elif Nspecies == 2:
main_index=kwargs["mI"]
e_index=kwargs["eI"]
elif Nspecies == 3:
main_index=kwargs["mI"]
imp_index=kwargs["zI"]
e_index=kwargs["eI"]
else:
print "Script is too poor to handle an arbitrary number of species!"
return -1
if dxdpsiN == 1:
print "Intepreting gradients as being given in psi_N."
else:
print "Intepreting gradients as being given in x space"
print "Will use function specified by dx_dpsi to convert"
dxdpsiN_at_a = dxdpsiN
x_ped_width=xwidth
psiN_ped_width=x_ped_width/dxdpsiN_at_a
#calculate new psiMid and diameter for this profile
midShift=midShift*psiN_ped_width
#2015-12-16: -psiN_ped_width/3.0 was the old default.
upShift=-psiN_ped_width/upShift_denom
downShift=psiN_ped_width/downShift_denom
update_domain_size(simul,psiN_ped_width,midShift,psiDiamFact,leftBoundaryShift,rightBoundaryShift)
(Delta,omega) = update_Delta_omega(simul)
globalDelta = Delta
globalomega = omega
globalPsiAHat = simul.psiAHat
#these things do not depend on whether the grid is uniform or nonuniform
# if intepreted as midpoint of physical psiN coordinate, etc.
# this is by design, since s[0] and s[-1] coincide with psiN start and stop
Npsi=simul.inputs.Npsi
psiMid = simul.inputs.psiMid
psiMin = simul.inputs.psiMin
psiMax = simul.inputs.psiMax
#start and stop pedestal in physical psiN
psiMinPed=psiMid-psiN_ped_width/2.0+downShift
psiMaxPed=psiMid+psiN_ped_width/2.0+upShift
psiMidPed=(psiMinPed+psiMaxPed)/2.0
#list of psi where our profiles change slope
psiList=[psiMinPed,psiMaxPed]
print "pedestal start,stop: " + str(psiList)
if specialEta and (mode == "const_ne"):
print "generate_compatible_profiles: WARNING: specialEta and mode == const_ne is incompatible. specialEta will be ignored"
# not too relevant for mtanh
offset=(psiMaxPed-psiMinPed)*transitionFact
pairList=[[offset,offset],[offset,offset]]
#allocate arrays
THats = [None]*Nspecies
dTHatdss = [None]*Nspecies
nHats = [None]*Nspecies
dnHatdss = [None]*Nspecies
etaHats = [None]*Nspecies
detaHatdss = [None]*Nspecies
#this modifies the charge and mass of the species in the simulation to match species file, and reads the new parameters back
species_filename= os.path.join(os.path.dirname(__file__), 'species_database.namelist')
(Zs,ms)=update_species_parameters(simul.species,species_filename,simul.norm,simul)
if (mode == "const_ne") and (Nspecies == 2):
# for two species there is no really difference between const_Phi and const_ne
mode = "const_Phi"
globalMode = "const_Phi"
if "nScale_"+species[e_index] in kwargs.keys():
kwargs["nScale_"+species[main_index]]=kwargs["nScale_"+species[e_index]]
kwargs["nped_"+species[main_index]] = kwargs["nped_"+species[e_index]]
kwargs["dnCoredx_"+species[main_index]] = kwargs["dnCoredx_"+species[e_index]]
kwargs["dnpeddx_"+species[main_index]] = kwargs["dnpeddx_"+species[e_index]]
kwargs["dnSOLdx_"+species[main_index]] = kwargs["dnSOLdx_"+species[e_index]]
if mtanh_const_delta:
if sameflux==False:
(THats,dTHatdss) = generate_T_profiles(**kwargs)
else:
if "nScale_"+species[main_index] in kwargs.keys():
niScale=kwargs["nScale_"+species[main_index]]
else:
niScale=1.0
niPed=niScale*kwargs["nped_"+species[main_index]]
niCoreGrad=niScale*kwargs["dnCoredx_"+species[main_index]]*dxdpsiN_at_a
nipedGrad=niScale*kwargs["dnpeddx_"+species[main_index]]*dxdpsiN_at_a
nt=niPed + niCoreGrad * (psiMin - psiMinPed)
nb=niPed + nipedGrad * (psiMaxPed - psiMinPed)
(THats,dTHatdss) = generate_T_profiles_sameflux(nt,nb,samefluxshift,T_transition_length,**kwargs)
if mode == "const_Phi":
#generate n_i profile
(nHats[main_index],dnHatdss[main_index]) = generate_ni_profile(**kwargs)
elif mode == "const_ne":
if Nspecies == 3:
(nHats[e_index],dnHatdss[e_index]) = generate_ne_profile(simul,**kwargs)
# generate ion etas
c=float(kwargs["imp_conc"])
etaHats[main_index] = lambda x: neHatPre(x)/(Zs[main_index]*(1+2*c))
detaHatdss[main_index] = lambda x: dneHatPredpsi(x)/(Zs[main_index]*(1+2*c))
# generate ion densities
etaHats[imp_index] = lambda x: c*etaHats[main_index](x)
detaHatdss[imp_index] = lambda x: c*detaHatdss[main_index](x)
X = lambda x: sqrt(1/(16*c**2) + nHats[e_index](x)/(2*c*Zs[main_index]*etaHats[main_index](x)))-1/(4*c)
dXds = lambda x: 1/(sqrt(1/(16*c**2) + nHats[e_index](x)/(2*c*Zs[main_index]*etaHats[main_index](x)))*4*Zs[main_index]*c*etaHats[main_index](x))*(dnHatdss[e_index](x) - nHats[e_index](x)*(detaHatdss[main_index](x)/etaHats[main_index](x)))
(nHats[main_index],dnHatdss[main_index]) = generate_n_from_eta_X_profile(etaHats[main_index],X,detaHatdss[main_index],dXds,Zs[main_index])
(nHats[imp_index],dnHatdss[imp_index]) = generate_n_from_eta_X_profile(etaHats[imp_index],X,detaHatdss[imp_index],dXds,Zs[imp_index])
else:
print "Unsupported number of species. This should never happen!"
sys.exit(2)
if mtanh_const_delta == False:
if sameflux==True:
nt=nHats[main_index](psiMin)
#nb=nHats[main_index](psiMax)
nb=nHats[main_index](psiMaxPed)
(THats,dTHatdss) = generate_T_profiles_sameflux(nt,nb,samefluxshift,T_transition_length,**kwargs)
elif (oldsameflux==True):
#this setting uses the old ni profile generation to generatea temporary
# n_i profile to generate sameflux T profiles that are the same as in
# the constant_Phi case.
# Useful for comparing const_Phi and const_ne with the same T
#NOTE: need inputs specifying n_i to generate the temporary profile
# does not really match the heat flux proxy for the actual n_i profiles
# used in the const n_e case.
(nH,dnHds) = generate_ni_profile(**kwargs)
nt=nH(psiMin)
nb=nH(psiMax)
(THats,dTHatdss) = generate_T_profiles_sameflux(nt,nb,samefluxshift,T_transition_length,**kwargs)
else:
(THats,dTHatdss) = generate_T_profiles(**kwargs)
#with n_i and T_i generated, we can evaluate logLambda at a suitable point
#which is done to calculate reference collisionality nu_r
T=simul.TBar*THats[main_index](psiMidPed)
n=simul.nBar*nHats[main_index](psiMidPed)
print "T: "+str(T)
print "n: "+str(n)
nu_r=update_nu_r(simul,n,T)
print "nu_r: " + str(nu_r)
if mode == "const_Phi":
(etaHats[main_index],detaHatdss[main_index]) = generate_etai_profile(Delta,omega,**kwargs)
(PhiHat,dPhiHatds) = generate_Phi_profile(etaHats[main_index],nHats[main_index],THats[main_index],detaHatdss[main_index],dnHatdss[main_index],dTHatdss[main_index],Zs[main_index],Delta,omega)
#if Phi=0 at top of the pedestal, this gives the top of the n_z pedestal.
#To make n_z and n_i same at points, those points should satisfy
# eta_z=n_i (n_i/eta_i)^(-[Zz/Zi] Ti/Tz)
#etaHats[imp_index] = 0.01*nHats[main_index][psiMinPedIndex]
if (Nspecies>2) and (sameeta==False):
if sameeta==True:
etaHats[imp_index]=etaHats[main_index]
detaHatdss[imp_index]=detaHatdss[main_index]
else:
(etaHats[imp_index],detaHatdss[imp_index]) = generate_etaz_profile(Delta,omega,**kwargs)
if (Nspecies > 2):
(nHats[imp_index],dnHatdss[imp_index]) = generate_n_from_eta_Phi_profile(etaHats[imp_index],PhiHat,THats[imp_index],detaHatdss[imp_index],dPhiHatds,dTHatdss[imp_index],Zs[imp_index],Delta,omega)
if (Nspecies > 1):
#n_e from quasi-neutrality
if (Nspecies == 2):
nHats[e_index]=lambda x : Zs[main_index]*nHats[main_index](x)
dnHatdss[e_index]= lambda x : Zs[main_index]*dnHatdss[main_index](x)
elif (Nspecies == 3):
nHats[e_index]=lambda x : Zs[imp_index]*nHats[imp_index](x) + Zs[main_index]*nHats[main_index](x)
dnHatdss[e_index]=lambda x: Zs[imp_index]*dnHatdss[imp_index](x) + Zs[main_index]*dnHatdss[main_index](x)
elif mode == "const_ne":
# generate Phi
PhiHat = lambda x: -(Delta/(Zs[main_index]*2*omega))*THats[main_index](x)*log(sqrt(1/(16*c**2) + nHats[e_index](x)/(2*c*Zs[main_index]*etaHats[main_index](x)))-1/(4*c))
dPhiHatds = lambda x: -(Delta/(Zs[main_index]*2*omega))*(dTHatdss[main_index](x)*log(X(x)) + THats[main_index](x)*dXds(x)/X(x))
if Nspecies > 1:
#eta_e from n_e
(etaHats[e_index], detaHatdss[e_index]) = generate_eta_from_n_Phi_profile(nHats[e_index],PhiHat,THats[e_index],dnHatdss[e_index],dPhiHatds,dTHatdss[e_index],Zs[e_index],Delta,omega)
#get psiN, dpsiN_ds that maps from uniform grid to physical psi
(psi,dpsi_ds) = get_psiN(nonuniform,simul,**kwargs)
if simul.inputs.useGlobalTermMultiplier == 1:
multiplier_delta_a = kwargs["multiplier_transition_shift"]
multiplier_delta_b = multiplier_delta_a
multiplier_c = kwargs["multiplier_edge_value"]
multiplier_Delta = kwargs["multiplier_transition_length"]
#multiplier_delta_a = 0.04
#multiplier_delta_b = 0.04
#multiplier_c =0.1
#multiplier_Delta = 1/200.0
C=generate_global_multiplier(psiMin,psiMax,Delta=multiplier_Delta,delta_a=multiplier_delta_a,delta_b=multiplier_delta_b,c=multiplier_c)
else:
C=lambda x: 1.0 + 0*x
#sample profiles at physical psi
#rescale derivatives from physical psi to internal uniform grid
write_outputs(simul,THats,dTHatdss,nHats,dnHatdss,etaHats,detaHatdss,PhiHat,dPhiHatds,psi,dpsi_ds,C)
##########################################################
# generate_compatible_profiles_constant_ne
#########################################################
def generate_compatible_profiles_constant_ne(simul,xwidth,nonuniform=False,sameflux=False,oldsameflux=False,sameeta=False,samefluxshift=0,specialEta=False,psiDiamFact=5,transitionFact=0.2,dxdpsiN=1,midShift=0,upShift_denom=3.0,downShift_denom=float("Inf"),m2tanh=False,T_transition_length=1.0,**kwargs):
generate_compatible_profiles(simul,xwidth,nonuniform,sameflux,oldsameflux,sameeta,samefluxshift,specialEta,psiDiamFact,transitionFact,dxdpsiN,midShift,upShift_denom,downShift_denom,m2tanh,mode="const_ne",T_transition_length=1.0,**kwargs)
def generate_compatible_profiles_etas(simul,xwidth,nonuniform,dxdpsiN,psiDiamFact,midShift,upShift_denom,downShift_denom,leftBoundaryShift,rightBoundaryShift,mode,**kwargs):
from const_delta import single_ion_all_eta_Phi, single_ion_all_eta_dPhidpsiN
from mtanh_const_delta import eta_parameter_wrapper, T_parameter_wrapper
from numpy import sqrt
from eta_mtanh import eta_from_n_LCFS
global psiMinPed
global psiMaxPed
global main_index
global e_index
global psiMin
global psiMax
global Nspecies
global main_index
global Npsi
species=simul.species
Nspecies=len(species)