def TrackSigmaMatrix(infile,nameprevel,initdc,nparticles):
transfermatrixopt = io.tfsDict(infile)
prevelinex = transfermatrixopt[0]["name"].index(nameprevel)-1
gamma = transfermatrixopt[1]['gamma']
ex = transfermatrixopt[1]['ex']
ey = transfermatrixopt[1]['ey']
sige = transfermatrixopt[1]['sige']
sigt = transfermatrixopt[1]['sigt']
print transfermatrixopt[0]['name'][prevelinex-1]
print transfermatrixopt[0]['name'][prevelinex]
print transfermatrixopt[0]['name'][prevelinex+1]
matrix = np.array([
[transfermatrixopt[0]["re11"][prevelinex],transfermatrixopt[0]["re12"][prevelinex],
transfermatrixopt[0]["re13"][prevelinex],transfermatrixopt[0]["re14"][prevelinex],
transfermatrixopt[0]["re15"][prevelinex],transfermatrixopt[0]["re16"][prevelinex]],
[transfermatrixopt[0]["re21"][prevelinex],transfermatrixopt[0]["re22"][prevelinex],
transfermatrixopt[0]["re23"][prevelinex],transfermatrixopt[0]["re24"][prevelinex],
transfermatrixopt[0]["re25"][prevelinex],transfermatrixopt[0]["re26"][prevelinex]],
[transfermatrixopt[0]["re31"][prevelinex],transfermatrixopt[0]["re32"][prevelinex],
transfermatrixopt[0]["re33"][prevelinex],transfermatrixopt[0]["re34"][prevelinex],
transfermatrixopt[0]["re35"][prevelinex],transfermatrixopt[0]["re36"][prevelinex]],
[transfermatrixopt[0]["re41"][prevelinex],transfermatrixopt[0]["re42"][prevelinex],
transfermatrixopt[0]["re43"][prevelinex],transfermatrixopt[0]["re44"][prevelinex],
transfermatrixopt[0]["re45"][prevelinex],transfermatrixopt[0]["re46"][prevelinex]],
[transfermatrixopt[0]["re51"][prevelinex],transfermatrixopt[0]["re52"][prevelinex],
transfermatrixopt[0]["re53"][prevelinex],transfermatrixopt[0]["re54"][prevelinex],
transfermatrixopt[0]["re55"][prevelinex],transfermatrixopt[0]["re56"][prevelinex]],
[transfermatrixopt[0]["re61"][prevelinex],transfermatrixopt[0]["re62"][prevelinex],
transfermatrixopt[0]["re63"][prevelinex],transfermatrixopt[0]["re64"][prevelinex],
transfermatrixopt[0]["re65"][prevelinex],transfermatrixopt[0]["re66"][prevelinex]]
])
sigma0matrix = np.array([
ex / 2. * np.array([initdc['BETX'],-initdc['ALFX'],0.,0.,0.,0.]),
ex / 2. * np.array([-initdc['ALFX'],(2+initdc['ALFX']**2)/initdc['BETX'],0.,0.,0.,0.]),
ey / 2. * np.array([0.,0.,initdc['BETY'],-initdc['ALFY'],0.,0.]),
ey / 2. * np.array([0.,0.,-initdc['ALFY'],(2+initdc['ALFY']**2)/initdc['BETY'],0,0]),
np.array([0.,0.,0.,0.,0.,0.]),
np.array([0.,0.,0.,0.,0.,sige**2]),
])
orbit = np.array([transfermatrixopt[0]["x"][prevelinex],
transfermatrixopt[0]["px"][prevelinex],
transfermatrixopt[0]["y"][prevelinex],
transfermatrixopt[0]["py"][prevelinex],
transfermatrixopt[0]["t"][prevelinex],
transfermatrixopt[0]["pt"][prevelinex]])
sigma1matrix = np.dot(matrix,np.dot(sigma0matrix,np.transpose(matrix)))
# print sigma0matrix,initdc['DELTAP'],np.sqrt(sigma1matrix[5,5])
coordinates = np.transpose(
np.array([
np.random.normal(orbit[0],np.sqrt(sigma1matrix[0,0]),nparticles),
np.random.normal(orbit[1],np.sqrt(sigma1matrix[1,1]),nparticles),
np.random.normal(orbit[2],np.sqrt(sigma1matrix[2,2]),nparticles),
np.random.normal(orbit[3],np.sqrt(sigma1matrix[3,3]),nparticles),
np.random.normal(0,sigt,nparticles),
np.random.normal(initdc['DELTAP'],np.sqrt(sigma1matrix[5,5]),nparticles)#initdc['DELTAP']
])
)
return coordinates
def get_p(tfsfile):
opt = io.tfsDict(tfsfile)
return opt[1]['pc']
import cern_pymad_domain_tfs as dom
import cern_pymad_io_tfs as io
import numpy as nm
import matplotlib.pyplot as plt
import math
data = io.tfsDict("LHCB1-Optics.tfs")
keys = []
for key, val in data[0].items():
keys.append(key)
print keys
print data[1]
#plt.plot(data[0]['s'], data[0]['x'], 'b-')
plt.axis([-500, 500, -0.01, 0.01])
#plt.show()
a = nm.array(data[0]['betx'])
b= data[1]['ex']
print b * a
aa=nm.array(data[0]['x'])+nm.sqrt(b* a + nm.array(data[0]['dx'])**2 * data[1]['sige']**2)
aaa=nm.array(data[0]['x'])-nm.sqrt(b* a + nm.array(data[0]['dx'])**2 * data[1]['sige']**2)
plt.plot(data[0]['s'], data[0]['x'], 'b-',data[0]['s'], aa, 'r-',data[0]['s'], aaa, 'r-')
plt.show()
if isinstance(table.get(k)[i],str):
addvals = '"' + str(table.get(k)[i]).upper() + '"'
elif isinstance(table.get(k)[i],float):
addvals = float_to_mathematica(table.get(k)[i])
else:
addvals = str(table.get(k)[i]).upper()
mfs += addvals + ','
mfs = mfs[:-1]
mfs += '},'
mfs = mfs[:-1]
mfs += '}]'
return mfs
# Reading in the tfs file to python library
datab1 = io.tfsDict("LHCB1-Optics.tfs")
datab2 = io.tfsDict("LHCB2-Optics.tfs")
rb1 = datab1[0]
rb2 = datab2[0]
cols1 = ['name','keyword','y','px','py','betx','bety','alfx','alfy','mux','muy','dx','dy','dpx','dpy','s','x']
cols2 = ['y','betx','bety','dx','dy','s','x']
gamma1 = datab1[1]['gamma']
ex1 = datab1[1]['ex']
ey1 = datab1[1]['ey']
sige1 = datab1[1]['sige']
n1 = datab1[1]['npart']
q1 = datab1[1]['charge']
m1 = datab1[1]['mass']
s1 = nm.array(rb1.get('s'))
xc1 = nm.array(rb1.get('x'))
yc1 = nm.array(rb1.get('y'))
def TrackSigmaMatrix(infile, nameprevel, initdc, nparticles):
transfermatrixopt = io.tfsDict(infile)
prevelinex = transfermatrixopt[0]["name"].index(nameprevel) - 1
gamma = transfermatrixopt[1]['gamma']
ex = transfermatrixopt[1]['ex']
ey = transfermatrixopt[1]['ey']
sige = transfermatrixopt[1]['sige']
sigt = transfermatrixopt[1]['sigt']
print transfermatrixopt[0]['name'][prevelinex - 1]
print transfermatrixopt[0]['name'][prevelinex]
print transfermatrixopt[0]['name'][prevelinex + 1]
matrix = np.array([[
transfermatrixopt[0]["re11"][prevelinex],
transfermatrixopt[0]["re12"][prevelinex],
transfermatrixopt[0]["re13"][prevelinex],
transfermatrixopt[0]["re14"][prevelinex],
transfermatrixopt[0]["re15"][prevelinex],
transfermatrixopt[0]["re16"][prevelinex]
],
[
transfermatrixopt[0]["re21"][prevelinex],
transfermatrixopt[0]["re22"][prevelinex],
transfermatrixopt[0]["re23"][prevelinex],
transfermatrixopt[0]["re24"][prevelinex],
transfermatrixopt[0]["re25"][prevelinex],
transfermatrixopt[0]["re26"][prevelinex]
],
[
transfermatrixopt[0]["re31"][prevelinex],
transfermatrixopt[0]["re32"][prevelinex],
transfermatrixopt[0]["re33"][prevelinex],
transfermatrixopt[0]["re34"][prevelinex],
transfermatrixopt[0]["re35"][prevelinex],
transfermatrixopt[0]["re36"][prevelinex]
],
[
transfermatrixopt[0]["re41"][prevelinex],
transfermatrixopt[0]["re42"][prevelinex],
transfermatrixopt[0]["re43"][prevelinex],
transfermatrixopt[0]["re44"][prevelinex],
transfermatrixopt[0]["re45"][prevelinex],
transfermatrixopt[0]["re46"][prevelinex]
],
[
transfermatrixopt[0]["re51"][prevelinex],
transfermatrixopt[0]["re52"][prevelinex],
transfermatrixopt[0]["re53"][prevelinex],
transfermatrixopt[0]["re54"][prevelinex],
transfermatrixopt[0]["re55"][prevelinex],
transfermatrixopt[0]["re56"][prevelinex]
],
[
transfermatrixopt[0]["re61"][prevelinex],
transfermatrixopt[0]["re62"][prevelinex],
transfermatrixopt[0]["re63"][prevelinex],
transfermatrixopt[0]["re64"][prevelinex],
transfermatrixopt[0]["re65"][prevelinex],
transfermatrixopt[0]["re66"][prevelinex]
]])
sigma0matrix = np.array([
ex / 2. * np.array([initdc['BETX'], -initdc['ALFX'], 0., 0., 0., 0.]),
ex / 2. * np.array([
-initdc['ALFX'],
(2 + initdc['ALFX']**2) / initdc['BETX'], 0., 0., 0., 0.
]),
ey / 2. * np.array([0., 0., initdc['BETY'], -initdc['ALFY'], 0., 0.]),
ey / 2. * np.array([
0., 0., -initdc['ALFY'],
(2 + initdc['ALFY']**2) / initdc['BETY'], 0, 0
]),
np.array([0., 0., 0., 0., 0., 0.]),
np.array([0., 0., 0., 0., 0., sige**2]),
])
orbit = np.array([
transfermatrixopt[0]["x"][prevelinex],
transfermatrixopt[0]["px"][prevelinex],
transfermatrixopt[0]["y"][prevelinex],
transfermatrixopt[0]["py"][prevelinex],
transfermatrixopt[0]["t"][prevelinex],
transfermatrixopt[0]["pt"][prevelinex]
])
sigma1matrix = np.dot(matrix, np.dot(sigma0matrix, np.transpose(matrix)))
# print sigma0matrix,initdc['DELTAP'],np.sqrt(sigma1matrix[5,5])
coordinates = np.transpose(
np.array([
np.random.normal(orbit[0], np.sqrt(sigma1matrix[0, 0]),
nparticles),
np.random.normal(orbit[1], np.sqrt(sigma1matrix[1, 1]),
nparticles),
np.random.normal(orbit[2], np.sqrt(sigma1matrix[2, 2]),
nparticles),
np.random.normal(orbit[3], np.sqrt(sigma1matrix[3, 3]),
nparticles),
np.random.normal(0, sigt, nparticles),
np.random.normal(initdc['DELTAP'], np.sqrt(sigma1matrix[5, 5]),
nparticles) #initdc['DELTAP']
]))
return coordinates
def get_p(tfsfile):
opt = io.tfsDict(tfsfile)
return opt[1]['pc']