def cirDist(k2s):
'''
circle distortion
'''
norder = 7
# slow but general ---
sext = nsls2.ring.getElements('sext','sh1')[0]
sext.put('K2',k2s[0])
sext = nsls2.ring.getElements('sext','sh3')[0]
sext.put('K2',k2s[1])
sext = nsls2.ring.getElements('sext','sh4')[0]
sext.put('K2',k2s[2])
sext = nsls2.ring.getElements('sext','sl3')[0]
sext.put('K2',k2s[3])
sext = nsls2.ring.getElements('sext','sl2')[0]
sext.put('K2',k2s[4])
sext = nsls2.ring.getElements('sext','sl1')[0]
sext.put('K2',k2s[5])
K2 = [nsls2.ring.bl[k].K2 for k in nsls2.ring.klist]
temp = [CTPS(0,i) for i in xrange(1,nv+1)]
for i,k in enumerate(nsls2.ring.klist):
temp = sm.lmPass(nsls2.ring.mlist[i][:nv,:nv],temp)
temp = sm.thickSextPass(L[i],K2[i],2,temp)
# --- attach thin octupole to sext
temp = sm.thinOctPass(K2[i]/abs(K2[i])*10.,temp)
temp = sm.lmPass(nsls2.ring.mlist[-1][:nv,:nv],temp)
mf = np.array([[temp[i].element(jj) for jj in xrange(mlen)] for i in xrange(nv)])
#mf = np.array([sm.aline(temp[i],powerindex) for i in xrange(nv)])
elemtx = mf[:,1:5]
#6. Derive normalized map M=(BK)^(-1).mm.BK, see my notes 'Relation to Normal Form' of Wednesday, March 30, 2011 10:34 PM
# here #mfbk is the first 4 rows of M, it is
mfbk = jfdf.d3(bKi[1:5,1:5],mf,bK)
mfbk,scalemf,As,Asm = scalingmf(mfbk,powerindex)
Ms = sqdf.squarematrix(mfbk,norder,powerindex,sequencenumber,tol)
try:
#print Ms[-1],Ms.shape,phix0,1,powerindex,scalemf,sequencenumber[1,0,0,0],norder
ux1,uxbar,Jx,scalex,Msx,As2x,Asm2x = \
jfdf.UMsUbarexpJ(Ms,phix0,1,powerindex,scalemf,sequencenumber[1,0,0,0],ypowerorder=norder)
uy1,uybar,Jy,scaley,Msy,As2y,Asm2y = \
jfdf.UMsUbarexpJ(Ms,phiy0,1,powerindex,scalemf,sequencenumber[0,0,1,0],ypowerorder=norder)
except:
return [1.0e8]*12
# --- particle one by one
zx,zy = [],[]
for xy in xylist:
#11. Prepare data for |wx|,thetax,|wy|,thetay to plot Poincare section of thetax,|wy|,thetay
section1 = [] #section1 is without joined blocks
for row in xy:
row1 = row+(ux1,uy1)
section1.append(tuneshift(row1[0],row1[1],row1[2],row1[3],row1[4],row1[5],
bKi4b4,scalex,scaley,powerindex,norder))
st1 = zip(*section1)
#print 'K2s = %.2f:'%k2s
zmax = max(st1[0])
zmin = min(st1[0])
zav = np.mean(st1[0])
zx1 = (zmax-zmin)/zav
#print "for wx1 without resonance block, (zmax-zmin)/zmean = ", zx1
zmax = max(st1[1])
zmin = min(st1[1])
zav = np.mean(st1[1])
zy1 = (zmax-zmin)/zav
#print "for wy1 without resonance block, (zmax-zmin)/zmean = ", zy1
#print ''
zx.append(zx1)
zy.append(zy1)
xlist = np.linspace(-3e-2, 3e-2,30) # a list of x
ylist = np.linspace( 1e-6, 1e-2,10) # a list of y
xyplane = [[i,j] for i in xlist for j in ylist]
nu,da = [],[]
for x,y in xyplane:
t1,t2,t3,t4,t5,t6,t7,t8 = tuneshift(x,0,y,0,ux1,uy1,
bKi4b4,scalex,scaley,powerindex,norder)
nu.append([t5,t6])
da.append([t7,t8])
da = np.array(da)
nux = [i[0].real/2/np.pi for i in nu]
nuy = [i[1].real/2/np.pi for i in nu]
#nux = [i[0].imag/2/np.pi for i in nu]
#nuy = [i[1].imag/2/np.pi for i in nu]
dnuxda = np.max(np.abs(nux))
dnuyda = np.max(np.abs(nuy))
dax = np.max(np.abs(da[:,0]))
day = np.max(np.abs(da[:,1]))
#k2c = [sc.K2 for sc in chsext]
return zx+zy+[dnuxda,dnuyda,dax,day]#+k2c
def cirDist():
'''
circle distortion
'''
norder = 7
K2 = [nsls2.ring.bl[k].K2 for k in nsls2.ring.klist]
temp = [CTPS(0, i) for i in xrange(1, nv + 1)]
for i, k in enumerate(nsls2.ring.klist):
temp = sm.lmPass(nsls2.ring.mlist[i][:nv, :nv], temp)
temp = sm.thickSextPass(L[i], K2[i], 1, temp)
temp = sm.lmPass(nsls2.ring.mlist[-1][:nv, :nv], temp)
mf = np.array([[temp[i].element(jj) for jj in xrange(mlen)]
for i in xrange(nv)])
#mf = np.array([sm.aline(temp[i],powerindex) for i in xrange(nv)])
elemtx = mf[:, 1:5]
#6. Derive normalized map M=(BK)^(-1).mm.BK, see my notes 'Relation to Normal Form' of Wednesday, March 30, 2011 10:34 PM
# here #mfbk is the first 4 rows of M, it is
mfbk = jfdf.d3(bKi[1:5, 1:5], mf, bK)
mfbk, scalemf, As, Asm = scalingmf(mfbk, powerindex)
Ms = sqdf.squarematrix(mfbk, norder, powerindex, sequencenumber, tol)
try:
#print Ms[-1],Ms.shape,phix0,1,powerindex,scalemf,sequencenumber[1,0,0,0],norder
ux1,uxbar,Jx,scalex,Msx,As2x,Asm2x = \
jfdf.UMsUbarexpJ(Ms,phix0,1,powerindex,scalemf,sequencenumber[1,0,0,0],ypowerorder=norder)
uy1,uybar,Jy,scaley,Msy,As2y,Asm2y = \
jfdf.UMsUbarexpJ(Ms,phiy0,1,powerindex,scalemf,sequencenumber[0,0,1,0],ypowerorder=norder)
except:
return [1.0e8] * 12
# --- particle one by one
zxy = []
for xy in xylist:
#11. Prepare data for |wx|,thetax,|wy|,thetay to plot Poincare section of thetax,|wy|,thetay
section1 = [] #section1 is without joined blocks
for row in xy:
row1 = row + (ux1, uy1)
section1.append(
tuneshift(row1[0], row1[1], row1[2], row1[3], row1[4], row1[5],
bKi4b4, scalex, scaley, powerindex, norder))
st1 = zip(*section1)
#print 'K2s = %.2f:'%k2s
#zmax = max(st1[0])
#zmin = min(st1[0])
#zav = np.mean(st1[0])
#zx1 = (zmax-zmin)/zav
#print "for wx1 without resonance block, (zmax-zmin)/zmean = ", zx1
#zmax = max(st1[1])
#zmin = min(st1[1])
#zav = np.mean(st1[1])
#zy1 = (zmax-zmin)/zav
#print "for wy1 without resonance block, (zmax-zmin)/zmean = ", zy1
#print ''
zxy.append(st1)
return zxy