for line in f:
line = line.rstrip()
output = []
folder_metadata = parse_folder_for_metadata(line)
cosy_output = CosyOutput()
cosy_output.injectFile(os.path.join(line, "2-Cosy/screen.txt"))
row_numbers = cosy_output.getRowNumbersWithKeyValuePair("time", 120e-12, comparison="gt")
if row_numbers == []:
continue
step = int(cosy_output.returnTableValue("step number", row_numbers[0]))
number_of_macroparticles = int(cosy_output.returnTableValue("number macroparticles", row_numbers[0]))
number_of_electrons = number_of_macroparticles * args.number_of_electrons_per_macroparticle
files = []
for filename in os.listdir(os.path.join(line, "2-Cosy")):
if filename.startswith(str(step) + "-x"):
files.append(os.path.join(line, "2-Cosy/" + filename))
simulation_output = SimulationOutput()
for path in files:
simulation_output.injectFile(path)
simulation_output.convertCoordinatesToBetterUnits(mass_of_macroparticle)
simulation_output = simulation_output.boostCoordinates("z")
ex = simulation_output.calcEmittance("x") / args.number_of_electrons_per_macroparticle
ez = simulation_output.calcEmittance("z") / args.number_of_electrons_per_macroparticle
if ex == 0 or ez == 0:
continue
output.append(str(number_of_electrons))
output.append(str(ex))
output.append(str(ez))
output.append(folder_metadata["applied_field"])
print ",".join(output)
cosy_output.injectFile(os.path.join(args.directory,"screen.txt"))
for row in cosy_output.rows:
step_number = row.getCellWithFieldname("step number").getValue()
if step_number % 10 == 0:
output = []
output.append(str(row.getCellWithFieldname("z").getValue()))
simulation_output = SimulationOutput()
for filename in os.listdir(args.directory):
if filename.startswith(str(step_number)+"-x-"):
pathname = os.path.join(args.directory,filename)
if os.path.isfile(pathname):
simulation_output.injectFile(pathname)
simulation_output.convertCoordinatesToBetterUnits(mass_of_macroparticle)
simulation_output = simulation_output.boostCoordinates("z")
eta_z = simulation_output.calcEta("z")
ez = simulation_output.calcEmittance("z")
position = simulation_output.returnAllColumnValues("z")
momentum = simulation_output.returnAllColumnValues("p_z")
mean_position = numpy.mean(position)
mean_momentum = numpy.mean(momentum)
mean_positionxmomentum = numpy.mean([x*p for x,p in zip(position,momentum)])
mean_position_squared = numpy.mean([x*x for x in position])
mean_momentum_squared = numpy.mean([p*p for p in momentum])
var_position = numpy.var(position,ddof=0)
var_momentum = numpy.var(momentum,ddof=0)
eta_z_2 = ez**2/var_position
#lorentz_gamma, e_spread = simulation_output.calcEnergySpread("z")
gamma_z = simulation_output.calcGamma("z")
#momentum = simulation_output.returnAllColumnValues("p_z")
output.append(str(numpy.sqrt(eta_z)*args.number_of_electrons_per_macroparticle))#to move it into the m of macroparticle instead of me
output.append(str(numpy.sqrt(eta_z_2)*args.number_of_electrons_per_macroparticle))#to move it into the m of macroparticle instead of me
