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
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
doLog = False
Mrks = ["-", "--"]
lfmv.ppInit()
P0 = -150
P1 = 150
L0 = -60
L1 = 60
pBin = np.linspace(P0, P1, Np)
pC = 0.5 * (pBin[0:-1] + pBin[1:])
lBin = np.linspace(L0, L1, Nl)
lC = 0.5 * (lBin[0:-1] + lBin[1:])
NumSpc = len(Spcs)
for n in range(NumSpc):
R, Phi, Lambda = lfmpp.getSphLoss(fIns[n])
X, pI, lI = np.histogram2d(Phi, Lambda, [pBin, lBin])
Xs = ndimage.filters.gaussian_filter(X, 1, mode='nearest')
print("Species %s" % (Spcs[n]))
nS = len(pSlcs)
for i in range(nS):
pS = pSlcs[i]
dP = np.abs(pC - pS)
I = np.abs(pC - pS).argmin()
pStr = "%s%s" % (Cols[i], Mrks[n])
if (n == 0):
labS = "Phi = %d" % (pS)
else:
labS = "_ignore"
plt.plot(lC, X[I, :], pStr, label=labS)
xbins = 50
ybins = 50
Nb = 50
Ns = len(spcs)
fig = plt.figure(1, figsize=(10, 10))
aCut = 80
cMin = 1
cMax = 200
cNorm = LogNorm(vmin=cMin, vmax=cMax)
for i in range(Ns):
fIn = dirStub + "/" + spcs[i] + "." + fileStub
pid, alph0 = lfmpp.getPitch(fIn)
Rf, Pf, Lf = lfmpp.getSphLoss(fIn, inMask=(alph0 >= aCut))
Ri, Pi, Li = lfmpp.getSphLoss(fIn, inMask=(alph0 < aCut))
Np = 2 * i + 1
plt.subplot(Ns, 2, Np)
xe, ye, Hi = h2d(Pi, Li, Nb)
plt.pcolormesh(xe, ye, Hi, norm=cNorm)
cbar = plt.colorbar()
plt.xlim((-180, 180))
plt.ylim((-60, 60))
plt.subplot(Ns, 2, Np + 1)
#plt.hist2d(Pf,Lf,[xbins,ybins],cmap=cMap,normed=False,cmin=0,cmax=200)
xe, ye, Hf = h2d(Pf, Lf, Nb)
plt.pcolormesh(xe, ye, Hf, norm=cNorm)
cbar = plt.colorbar()
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)
if (Np < K):
K = Np
if (subVTI):
lfmpp.subH5p(fIn, Mask, K, fOut=fOut, xEq=False)
# else:
import os
import lfmViz as lfmv
import lfmPostproc as lfmpp
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
fIn = '/Users/soratka1/Work/magnetoloss/synth/e.100keV.h5part'
#fIn = '/Users/soratka1/Work/magnetoloss/debug/e.100keV.h5part'
aCut = 80
pCut = 10
lCut = 30
lCut0 = 5
pid, alph0 = lfmpp.getPitch(fIn)
Rf,Pf,Lf = lfmpp.getSphLoss(fIn,inMask=(alph0>aCut))
Out = lfmpp.getOut(fIn)
Out = Out & (alph0>aCut)
ids = pid[Out]
#hiLat = (np.abs(Lf) > lCut) & (np.abs(Pf) < pCut)
hiLat = (np.abs(Lf) < lCut0) & (np.abs(Pf) < pCut)
#Ri,Pi,Li = lfmpp.getSphLoss(fIn,inMask=(alph0<aCut))
print("Found %d high-lat electrons"%(hiLat.sum()))
pIds = ids[hiLat]
print(pIds)
Np = len(pIds)
fileStub = "100keV.h5part" 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) )