def getEQXs(fIn):
isOut = lfmpp.getOut(fIn)
t,xeq = lfmpp.getH5p(fIn,"xeq",Mask=isOut)
t,yeq = lfmpp.getH5p(fIn,"yeq",Mask=isOut)
t,tCr = lfmpp.getH5p(fIn,"tCr",Mask=isOut)
t,tEq = lfmpp.getH5p(fIn,"Teq",Mask=isOut)
R = []
P = []
Np = xeq.shape[1]
print("Working with %d particles"%(Np))
for n in range(Np):
#Accumulate EQXs for time after first crossing
tCrn = tCr[:,n]
tSlc1 = tCrn.argmax()
teqn = tEq[tSlc1:,n]
ts,Ind = np.unique(teqn,return_index=True)
#Have unique EQXs
Neq = len(Ind)
if (Neq>0):
x = xeq[tSlc1:,n]
y = yeq[tSlc1:,n]
x = x[Ind]
y = y[Ind]
r = np.sqrt(x**2.0 + y**2.0)
phi = np.arctan2(y,x)
for i in range(Neq):
R.append(r[i])
P.append(phi[i])
return np.array(R),np.array(P)
def getXKA(fIn):
isOut = lfmpp.getOut(fIn, mp=True)
#Get spherical coordinates of last MP Xing
R, Phi, Lambda = lfmpp.getSphLoss(fIn)
#Get time index of last MP crossing
t, tEq = lfmpp.getH5p(fIn, "Teq", Mask=isOut)
tsEq = np.argmax(tEq, axis=0)
#Use these slices to find values at last X'ing
t, Kt = lfmpp.getH5p(fIn, "kev", Mask=isOut)
t, Vxt = lfmpp.getH5p(fIn, "vx", Mask=isOut)
t, Vyt = lfmpp.getH5p(fIn, "vy", Mask=isOut)
t, Vzt = lfmpp.getH5p(fIn, "vz", Mask=isOut)
Np = Kt.shape[1]
K = np.zeros(Np)
A = np.zeros(Np)
for i in range(Np):
tsi = tsMP[i]
vxi = Vxt[tsi, i]
vyi = Vyt[tsi, i]
vzi = Vzt[tsi, i]
vmag = np.sqrt(vxi**2.0 + vyi**2.0 + vzi**2.0)
K[i] = Kt[tsi, i]
A[i] = np.arccos(vzi / vmag) * 180 / np.pi
mlt = Phi
return mlt, K, A
def NumCross(fIn, onlyOut=True):
isOut = lfmpp.getOut(fIn)
t, tCrF = lfmpp.getH5p(fIn, "tCr")
t, pids = lfmpp.getH5p(fIn, "id")
pids = pids[-1, :]
print("\tAll particles:\n")
NumX_All = CountXs(tCrF, pids)
print("\tOnly out:\n")
NumX_Out = CountXs(tCrF[:, isOut], pids[isOut])
print("\tOnly in:\n")
NumX_In = CountXs(tCrF[:, np.logical_not(isOut)],
pids[np.logical_not(isOut)])
print("\t# of In + MP-X = %d\n" % np.sum(NumX_In > 0))
return NumX_All, NumX_Out, NumX_In
def findMaxRad(fIn):
isOut = lfmpp.getOut(fIn)
t, ids = lfmpp.getH5p(fIn, "id", Mask=isOut)
t, mp = lfmpp.getH5p(fIn, "mp", Mask=isOut)
t, x = lfmpp.getH5p(fIn, "x", Mask=isOut)
t, y = lfmpp.getH5p(fIn, "y", Mask=isOut)
t, z = lfmpp.getH5p(fIn, "z", Mask=isOut)
t, tCr = lfmpp.getH5p(fIn, "tCr", Mask=isOut)
ids = ids[0, :]
cylR = np.sqrt(x**2.0 + y**2.0)
Np = len(ids)
Rs = []
print("\tFound %d particles\n" % (Np))
print(Np)
#Find slices for which particle is in sheath
for n in range(Np):
#Find last MP xing
mpn = mp[:, n]
tCrn = tCr[:, n]
tSlc1 = tCrn.argmax()
#Find box xing
tSlc2 = np.argmax(mpn > 0)
Rn = cylR[tSlc1:tSlc2, n]
if (len(Rn) > 0):
maxRn = Rn.max()
Rs.append(maxRn)
return Rs
def mpxK(fIn):
#Get energies at last/first MPX
isOut = lfmpp.getOut(fIn, mp=True)
t, kevPT = lfmpp.getH5p(fIn, "kev")
#Last MP crossings
pid, Tmpx = lfmpp.getH5pFin(fIn, "tCr", Mask=isOut)
#First MP crossings
R, Phi, Lambda, Tmpx0 = lfmpp.getSphLoss1st(fIn)
Np = isOut.sum() #Number of out particles
mpK = np.zeros(Np)
mpK0 = np.zeros(Np)
for n in range(Np):
idn = np.int(pid[n] - 1)
#Time slices of first/last MPX
ts0 = np.argmin(Tmpx0[n] >= t)
tsF = np.argmin(Tmpx[n] >= t)
#print(n,idn,ts0,tsF)
mpK[n] = kevPT[tsF, idn]
mpK0[n] = kevPT[ts0, idn]
return mpK0, mpK
def getEQXs(fIn):
isOut = lfmpp.getOut(fIn)
t,xeq = lfmpp.getH5p(fIn,"xeq",Mask=isOut)
t,yeq = lfmpp.getH5p(fIn,"yeq",Mask=isOut)
t,tCr = lfmpp.getH5p(fIn,"tCr",Mask=isOut)
t,tEq = lfmpp.getH5p(fIn,"Teq",Mask=isOut)
t,Vx = lfmpp.getH5p(fIn,"vx",Mask=isOut)
t,Vy = lfmpp.getH5p(fIn,"vy",Mask=isOut)
t,Vz = lfmpp.getH5p(fIn,"vz",Mask=isOut)
Vmag = np.sqrt(Vx**2.0+Vy**2.0+Vz**2.0)
A = []
P = []
Np = xeq.shape[1]
print("Working with %d particles"%(Np))
for n in range(Np):
#Accumulate EQXs for time after first crossing
tCrn = tCr[:,n]
tSlc1 = tCrn.argmax()
teqn = tEq[tSlc1:,n]
ts,Ind = np.unique(teqn,return_index=True)
#Have unique EQXs
Neq = len(Ind)
if (Neq>0):
x = xeq[tSlc1:,n]
y = yeq[tSlc1:,n]
x = x[Ind]
y = y[Ind]
vm = Vmag[tSlc1:,n]
vm = vm[Ind]
vzn = Vz[tSlc1:,n]
vzn = vzn[Ind]
als = np.arccos(vzn/vm)*180.0/np.pi
r = np.sqrt(x**2.0 + y**2.0)
phi = np.arctan2(y,x)
for i in range(Neq):
A.append(als[i])
P.append(phi[i])
return np.array(A),np.array(P)
def getTimes(fIn, doTail=False):
isOut = lfmpp.getOut(fIn, mp=True, tl=doTail)
t, mpF = lfmpp.getH5p(fIn, "mp")
mp = mpF[:, isOut]
#Last MP crossings
pid, Tmpx = lfmpp.getH5pFin(fIn, "tCr", Mask=isOut)
#First MP crossings
R, Phi, Lambda, Tmpx0 = lfmpp.getSphLoss1st(fIn)
#Time of loss from box, time slice index
tsMP = np.argmax(mp, axis=0)
#Convert to physical time
Tbx = t[tsMP]
if (doTail):
#Remove particles that leave through tail but never cross MP
DelT = Tbx - Tmpx
Tbx = Tbx[DelT > 0]
Tmpx = Tmpx[DelT > 0]
pid = pid[DelT > 0]
return Tmpx, Tmpx0, Tbx, pid
import argparse
import numpy as np
import os
import lfmViz as lfmv
import lfmPostproc as lfmpp
import matplotlib as mpl
import matplotlib.pyplot as plt
dirStub = "/Users/soratka1/Work/magnetoloss/synth"
fileStub = "100keV.h5part"
spcs = ["H", "O", "e"]
Leg = ["H", "O", "e"]
Ns = len(spcs)
#fig = plt.figure(1, figsize=(10, 10))
Np = 100000.0
for i in range(Ns):
fIn = dirStub + "/" + spcs[i] + "." + fileStub
t, mpTp = lfmpp.getH5p(fIn, "mp")
mpT = mpTp.sum(axis=1)
print(mpT.shape)
plt.plot(t, mpT / Np)
plt.legend(Leg, loc='lower right')
plt.xlabel('Time [s]')
plt.ylabel('Cumulative Loss Fraction')
plt.show()
def findCrossings(fIn, PhiC=30.0, DelPhi=5):
isOut = lfmpp.getOut(fIn)
t, ids = lfmpp.getH5p(fIn, "id", Mask=isOut)
t, mp = lfmpp.getH5p(fIn, "mp", Mask=isOut)
t, x = lfmpp.getH5p(fIn, "x", Mask=isOut)
t, y = lfmpp.getH5p(fIn, "y", Mask=isOut)
t, z = lfmpp.getH5p(fIn, "z", Mask=isOut)
t, vx = lfmpp.getH5p(fIn, "vx", Mask=isOut)
t, vy = lfmpp.getH5p(fIn, "vy", Mask=isOut)
t, vz = lfmpp.getH5p(fIn, "vz", Mask=isOut)
t, tCr = lfmpp.getH5p(fIn, "tCr", Mask=isOut)
ids = ids[0, :]
phi = np.arctan2(y, x) * 180 / np.pi
if (np.abs(PhiC) > 5):
#Fix for flop
phi[phi < 0] = phi[phi < 0] + 360
Np = len(ids)
#print("\tFound %d particles\n"%(Np))
Vx = []
Vy = []
Vz = []
sM = []
zM = []
for n in range(Np):
#Find last MP xing
mpn = mp[:, n]
tCrn = tCr[:, n]
tSlc1 = tCrn.argmax()
#Find box xing
tSlc2 = np.argmax(mpn > 0)
pn = phi[tSlc1:tSlc2, n]
#print(pn.shape)
#Identify sign changes and bound for within +/- 5 degrees
#Otherwise funny business @ p=0/360
dp = pn - PhiC
dpsgn = np.sign(dp)
dpFlp = ((np.roll(dpsgn, 1) - dpsgn) != 0).astype(int)
dpFlp = (dpFlp > 0)
dpAbs = np.abs(dp) <= DelPhi
isPCr = dpFlp & dpAbs
#print(len(pn),tCr.sum())
Nx = isPCr.sum()
if (Nx > 0):
vxn = vx[tSlc1:tSlc2, n]
vyn = vy[tSlc1:tSlc2, n]
vzn = vz[tSlc1:tSlc2, n]
xn = x[tSlc1:tSlc2, n]
yn = y[tSlc1:tSlc2, n]
zn = z[tSlc1:tSlc2, n]
vxx = vxn[isPCr]
vyx = vyn[isPCr]
vzx = vzn[isPCr]
xx = xn[isPCr]
yx = yn[isPCr]
zx = zn[isPCr]
for i in range(Nx):
Vx.append(vxx[i])
Vy.append(vyx[i])
Vz.append(vzx[i])
sM.append(np.sqrt(xx[i]**2.0 + yx[i]**2.0))
zM.append(zx[i])
#print(n,isPCr)
Vx = np.array(Vx)
Vy = np.array(Vy)
Vz = np.array(Vz)
sM = np.array(sM)
zM = np.array(zM)
print("\tPhi = %5.2f, NumP = %d\n" % (PhiC, len(Vx)))
return sM, zM, Vx, Vy, Vz
K = [10, 50, 100]
Spc = ["p", "Hepp", "O"]
sLab = ["H+", "He++", "O+"]
for k in range(len(K)):
for s in range(len(Spc)):
Files.append("%s_sInj.K%02d.0001.h5part" % (Spc[s], K[k]))
fOuts.append("%s%02d.mk.png" % (Spc[s], K[k]))
T**S.append("%s %02d keV" % (sLab[s], K[k]))
Nf = len(Files)
for n in range(Nf):
fIn = RootDir + Files[n]
fOut = fOuts[n]
t, K = lfmpp.getH5p(fIn, "kev")
t, Mu = lfmpp.getH5p(fIn, "Mu")
dK = K[2:-2, :] - K[0:-4, :]
dlK = dK / (dt * K[1:-3, :])
dMu = Mu[2:-2, :] - Mu[0:-4, :]
dlMu = dMu / (dt * Mu[1:-3, :])
muf = Mu[1:-3, :].flatten()
dm = dlMu.flatten()
dk = dlK.flatten()
#Restrict to good values
Ind = (muf > 1.0e-8) & (~np.isnan(muf))
dm = dm[Ind]
subVTI = True
dirStub = "/Users/soratka1/Work/magnetoloss/synth"
fileStub = "100keV.h5part"
spcs = ["H", "O"]
Leg = ["Hydrogen", "Oxygen"]
fOut = "OxyDelP.h5part"
K = 5
i = 1 #Oxygen
fIn = dirStub + "/" + spcs[i] + "." + fileStub
print("Reading %s" % (fIn))
print("Species %s" % (Leg[i]))
t, ids = lfmpp.getH5p(fIn, "id")
isOut = lfmpp.getOut(fIn)
pid, NumX = lfmpp.countMPX(fIn, isOut)
R, PhiF, LambdaF, Tmp = lfmpp.getSphLoss1st(fIn)
R, PhiL, LambdaL = lfmpp.getSphLoss(fIn)
DelPhi = PhiL - PhiF
isOut[isOut] = (DelPhi) > 60
Mask = isOut
id0 = ids[0, Mask]
Np = Mask.sum()
print(Np)
print(K)
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fld = "/Users/soratka1/Work/magnetoloss/eqSlc/eqSlc.0250.vti"
IDs = [1335, 301, 95834, 12593, 63464, 75685]
fIn = "/Users/soratka1/Work/magnetoloss/synth/O.100keV.h5part"
Bz = lfmv.getVTI_SlcSclr(fld, fldStr='dBz')
xm = np.linspace(-15.0, 13, 560)
ym = np.linspace(-20.0, 20, 801)
xx, yy = np.meshgrid(xm, ym)
Ni = len(IDs)
#fig = plt.figure(1, figsize=(15,10))
gs = gridspec.GridSpec(Ni, 1)
t, x = lfmpp.getH5p(fIn, "x")
t, y = lfmpp.getH5p(fIn, "y")
t, z = lfmpp.getH5p(fIn, "z")
t, pids = lfmpp.getH5p(fIn, "id")
t, Om = lfmpp.getH5p(fIn, "Om")
t, Op = lfmpp.getH5p(fIn, "Op")
Omp = (Om + Op)
for n in range(len(IDs)):
pid = IDs[n]
npid = (pids == pid).argmax()
xp = x[:, npid]
yp = y[:, npid]
zp = z[:, npid]
cp = Omp[:, npid]
#ax = plt.subplot(gs[n,0])
P0 = -135; P1 = -80 else: fIn = '/Users/soratka1/Work/magnetoloss/synth/e.100keV.h5part' fIn = '/Users/soratka1/Work/magnetoloss/debug/e.100keV.h5part' #Find particles whose last Teq is in range T0 = 2250 T1 = 2300 P0 = 80; P1 = 135 fOut = "khiSub.h5part" Out = lfmpp.getOut(fIn) t,x = lfmpp.getH5p(fIn,"x") t,y = lfmpp.getH5p(fIn,"y") t,z = lfmpp.getH5p(fIn,"z") t,Teq = lfmpp.getH5pFin(fIn,"Teq") t,ids = lfmpp.getH5p(fIn,"id") id0 = ids[0,:] R,Phi,Lambda = lfmpp.getSphLoss(fIn) Out[Out] = (Phi>=P0) & (Phi<=P1) Mask = (Teq>=T0) & (Teq<=T1) & Out Np = Mask.sum() t,xeq = lfmpp.getH5p(fIn,"xeq") t,yeq = lfmpp.getH5p(fIn,"yeq")
Tail = "_csInj.K0.0001.h5part"
Stubs = ["p", "Hep", "Hepp", "O"]
Labs = ["H+", "He+", "He++", "O+"]
Plts = ["b", "g", "r", "c"]
t**S = "Single Injection (1 eV)"
figName = "cs_Kt.png"
figQ = 300
pC = [1, 10, 50, 99]
Ns = len(Stubs)
Np = len(pC)
for n in range(Ns):
fIn = Root + Stubs[n] + Tail
t, Kev = lfmpp.getH5p(fIn, "kev")
K = Kev
Kb = K.mean(axis=1) #Average(t)
dK = K.std(axis=1) #Std
T = t - t.min()
for i in range(Np):
pLab = "_"
if (i == 0):
pLab = "%s, %s Percentiles" % (Labs[n], str(pC))
Kc = np.percentile(K, pC[i], axis=1)
plt.semilogy(T, Kc, Plts[n], label=pLab)
#plt.errorbar(t,Kb,dK,label=Labs[n],errorevery=10)
#plt.plot(t,Kc,label=Labs[n])
print("Spc = %s" % (Labs[n]))
print("\tMax = %f" % (K.max()))