def getPs(h5pFile, pC, Nk):
isOut = lfmpp.getOut(h5pFile)
R, PhiMP0, LambdaF, Tmp = lfmpp.getSphLoss1st(h5pFile)
ids, PhiBX = lastPhi(h5pFile)
dPhi = PhiBX - PhiMP0
Ind = (abs(dPhi) >= pC)
Ntot = Ind.sum()
ids = ids[Ind]
print("Found %d values larger than %3.2f" % (Ntot, pC))
IndR = np.random.choice(Ntot, Nk, replace=False)
ids = ids[IndR]
return ids
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 getPBlk(h5pFile, pC, Np):
#Get Np particles for each of 3 types
#pI:(0,180), (-15,0),(-180,-15)
#And have dPhi>=pC
pIL = [0, -45, -180]
pIH = [180, 0.0, -45]
Nd = len(pIL)
pIDs = np.zeros(Np * Nd, dtype=np.int)
isOut = lfmpp.getOut(h5pFile)
R, PhiMP0, LambdaF, Tmp = lfmpp.getSphLoss1st(h5pFile)
ids, PhiBX = lastPhi(h5pFile)
dPhi = PhiBX - PhiMP0
print(PhiMP0.min(), PhiMP0.max())
print(dPhi.min(), dPhi.max())
for d in range(Nd):
pcd = pC[d]
if (pC[d] >= 0):
IndPC = (dPhi >= pC[d])
else:
IndPC = (dPhi <= pC[d])
IndPI = (PhiMP0 >= pIL[d]) & (PhiMP0 <= pIH[d])
Ind = IndPC & IndPI
subIDs = ids[Ind]
subDP = dPhi[Ind]
#Pick Np randomly
Ntot = Ind.sum()
print("Found %d values w/ dP >= %f, and pI between %f and %f" %
(Ntot, pC[d], pIL[d], pIH[d]))
IndR = np.random.choice(Ntot, Np, replace=False)
rIDs = subIDs[IndR]
i0 = d * Np
i1 = i0 + Np
pIDs[i0:i1] = rIDs
print(rIDs)
print(subDP[IndR])
return pIDs
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
msDp = []
pBX = []
mDp = []
LogScl = LogNorm(1, 500)
for i in range(Ns):
#xBin = np.linspace(-180,180,100)
xBin = np.linspace(-60, 60, 100)
yBin = np.linspace(0, 30, 30)
fIn = dirStub + "/" + spcs[i] + "." + fileStub
print("Reading %s" % (fIn))
print("Species %s" % (Leg[i]))
isOut = lfmpp.getOut(fIn)
pid, NumX = lfmpp.countMPX(fIn, isOut)
R, PhiMP0, LambdaF, Tmp = lfmpp.getSphLoss1st(fIn)
R, PhiMP1, LambdaL = lfmpp.getSphLoss(fIn)
PhiBX = lastPhi(fIn)
pMP0.append(PhiMP0)
pMP1.append(PhiMP1)
mpDp.append(PhiMP1 - PhiMP0)
pBX.append(PhiBX)
msDp.append(PhiBX - PhiMP1)
mDp.append(PhiBX - PhiMP0)
Nb = 40
N0 = -60
N1 = 120
bins = np.linspace(N0, N1, Nb)
doNorm = True
Lambdas = pickle.load(f)
else:
print("No data file found, calculating")
Phis = []
Lambdas = []
for i in range(Ns):
fIn = RootDir + spcs[i] + "." + fileStub
if (doTest):
Phi = np.random.rand(Np) * P1
Lambda = np.random.rand(Np) * L1
else:
if (doFirst):
R, Phi, Lambda, Tl = lfmpp.getSphLoss1st(fIn)
else:
R, Phi, Lambda = lfmpp.getSphLoss(fIn)
Phis.append(Phi)
Lambdas.append(Lambda)
print("Writing pickle")
with open(mpDF, "wb") as f:
pickle.dump(Phis, f)
pickle.dump(Lambdas, f)
lfmv.ppInit()
fig = plt.figure(figsize=figSize)
wRat = np.ones(Ns + 1)
wRat[-1] = 0.05
spcs = ["H","O","e"] cMap="jet" Nb = 50 Ns = len(spcs) fig = plt.figure(1, figsize=(10, 10)) cMin = 1.0e-5 cMax = 1.0e-2 cNorm = LogNorm(vmin=cMin,vmax=cMax) for i in range(Ns-1): fIn = dirStub + "/" + spcs[i] + "." + fileStub Rf,Pf,Lf = lfmpp.getSphLoss(fIn) Ri,Pi,Li,Tmp = lfmpp.getSphLoss1st(fIn) Np = 2*i+1 plt.subplot(Ns-1,2,Np) #plt.hist2d(Pi,Li,[xbins,ybins],cmap=cMap,normed=True,norm=LogNorm()) xe,ye,Hi = h2d(Pi,Li,Nb) plt.pcolormesh(xe,ye,Hi,norm=cNorm) cbar=plt.colorbar() plt.xlim( (-180,180) ) plt.ylim( (-90,90) ) plt.subplot(Ns,2,Np+1) #plt.hist2d(Pf,Lf,[xbins,ybins],cmap=cMap,normed=True,norm=LogNorm()) xe,ye,Hf = h2d(Pf,Lf,Nb) plt.pcolormesh(xe,ye,Hf,norm=cNorm) cbar=plt.colorbar() plt.xlim( (-180,180) ) plt.ylim( (-90,90) )
aNumX = []
LogScl = LogNorm(1,500)
fig = plt.figure(1, figsize=(20,6))
for i in range(2):
#xBin = np.linspace(-180,180,100)
xBin = np.linspace(-60,60,100)
yBin = np.linspace(0,30,30)
fIn = dirStub + "/" + spcs[i] + "." + fileStub
print("Reading %s"%(fIn))
print("Species %s"%(Leg[i]))
isOut = lfmpp.getOut(fIn)
pid, NumX = lfmpp.countMPX(fIn,isOut)
R, PhiF, Lambda, Tmp = lfmpp.getSphLoss1st(fIn)
R,PhiL,Lambda = lfmpp.getSphLoss(fIn)
DelPhi = PhiL-PhiF
#IndF = (PhiF<=45) & (PhiF>=-45)
#IndL = (PhiL<=0) & (PhiL>=-45)
#Ind = IndF & IndL
#DelPhi = PhiL[Ind]-PhiF[Ind]
#NumX = NumX[Ind]
t**S = "%s 100 keV"%Leg[i]
plt.subplot(1,3,i+1)
#plt.hist2d(Phi,NumX,[xBin,yBin],norm=LogScl)
plt.hist2d(DelPhi,NumX,[xBin,yBin],norm=LogScl)
#plt.hist2d(DelPhi,NumX,[xBin,yBin])
plt.xlim( (-120,120) ); plt.xlabel("Delta-Phi")
plt.ylim( (0,30) ); plt.ylabel("# of Crossings")