def body():
dh = 0.0001
dt = 0.0001
time = 100
t_finish = int(time / dt)
grid = PipeGrid(dh)
X = int(grid.shape[0] / 2)
Y = grid.shape[1] - 2
T_Tot = []
file = open('stats.csv', 'w')
file.write('Time (s), Temperature (K)\n')
T_Tot.append(grid)
file.write('{0}, {1:.2f}\n'.format(0, grid[X, Y]))
for t in np.arange(1, t_finish):
print("----{}----".format(t * dt))
z = v * dt * t
if z < L:
heated = int(z / dh)
grid[:heated, 1] = T_g
if t % reco_step == 0:
T_Tot.append(grid)
file.write('{0:.2f}, {1:.2f}\n'.format(t * dt, grid[X, Y]))
else:
grid[:, 1] = T_g
break
run(grid, T_g, k_s, rho_s, T_Tot, dh, dt)
t_start = t
for t in np.arange(t_start, t_finish):
print("----{}----".format(t * dt))
if t % reco_step == 0:
T_Tot.append(grid)
file.write('{0:.2f}, {1:.2f}\n'.format(t * dt, grid[X, Y]))
run(grid, T_g, k_s, rho_s, T_Tot, dh, dt)
t_list = np.arange(len(T_Tot)) * dt
T_plot = []
for T in T_Tot:
T_plot.append(T[X, Y])
file.close()
return t_list, T_plot
def test(cmd, smpl_paths, tmpl_paths, patterns, out_dir, demo):
# run the main process to obtain a synthesized model
#no_sketch()
res = main(cmd, smpl_paths, tmpl_paths, patterns, out_dir)
if res: return res
# simulate
log_fname = os.path.join(out_dir, "simulated.txt")
res = simulate.run(cmd, demo, patterns, out_dir, log_fname)
if res: return res
# compare logs
smpl_path = os.path.join(smpl_dir, cmd, demo)
for smpl in util.get_files_from_path(smpl_path, "txt"):
res = compare.compare(smpl, log_fname)
if res:
logging.error("conflict with " + os.path.normpath(smpl))
return res
logging.info("compared with " + os.path.normpath(smpl))
logging.info("test done")
return 0
def test(cmd, smpl_paths, tmpl_paths, patterns, out_dir, demo):
# run the main process to obtain a synthesized model
#no_sketch()
res = main(cmd, smpl_paths, tmpl_paths, patterns, out_dir)
if res: return res
# simulate
log_fname = os.path.join(out_dir, "simulated.txt")
res = simulate.run(cmd, demo, patterns, out_dir, log_fname)
if res: return res
# compare logs
smpl_path = os.path.join(smpl_dir, cmd, demo)
for smpl in util.get_files_from_path(smpl_path, "txt"):
res = compare.compare(smpl, log_fname)
if res:
logging.error("conflict with " + os.path.normpath(smpl))
return res
logging.info("compared with " + os.path.normpath(smpl))
logging.info("test done")
return 0
detectedflux = float(flux) * float(area) * float(solidangle) * float(selectionefficiency)
rateperhour = detectedflux * 60 * 60
n = int(rateperhour * float(numberofhours))
print time.asctime(
time.localtime()
), "Cosmic Ray Iron Flux is", flux, "Simulated Area is", area, "Field of View is", solidangle, "Detected Flux is", detectedflux
print time.asctime(
time.localtime()
), "Rate per hour", rateperhour, "Simulated Hours", numberofhours, "Simulated Events", n
with open(
"/afs/desy.de/user/s/steinrob/Documents/DESY/positioning/orientations/" + orientation + ".csv", "rb"
) as csvfile:
reader = csv.reader(csvfile, delimiter=",", quotechar="|")
rowcount = 0
for row in reader:
rowcount += 1
s.run(eff, rowcount, mincount=mincount, text=False, graph=False, output=sourcedata, layout=orientation, number=n)
bp.run(sourcedata, processdata, int(mincount), rowcount, text=False)
br.run(processdata, reconstructdata, rowcount, reconstructiongridwidth, eff)
message = str(time.asctime(time.localtime())) + " Completed simulation of " + str(n) + " events!"
import os, sys
import sendemail as se
name = os.path.basename(__file__)
se.send(name, message, False)
print time.asctime(
time.localtime()
), "Rate per hour", rateperhour, "Simulated Hours", numberofhours, "Simulated Events", n
with open(
"/afs/desy.de/user/s/steinrob/Documents/DESY/positioning/orientations/"
+ orientation + ".csv", 'rb') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='|')
rowcount = 0
for row in reader:
rowcount += 1
s.run(eff,
rowcount,
mincount=mincount,
text=False,
graph=False,
output=sourcedata,
layout=orientation,
number=n)
bp.run(sourcedata, processdata, int(mincount), rowcount, text=False)
br.run(processdata, reconstructdata, rowcount, reconstructiongridwidth, eff)
message = str(time.asctime(
time.localtime())) + " Completed simulation of " + str(n) + " events!"
import os, sys
import sendemail as se
name = os.path.basename(__file__)
se.send(name, message, False)
else:
sourcedata= str(cfg.data) + "simulated" + str(cfg.mincount)
processdata = str(cfg.data) + "processed"+ str(cfg.mincount)
reconstructdata = str(cfg.data) + "reconstructed"+ str(cfg.mincount)
with open("orientations/"+ cfg.orientation +".csv", 'rb') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='|')
rowcount = 0
for row in reader:
rowcount +=1
if cfg.simulate:
print time.asctime(time.localtime()),"Cosmic Ray Iron Flux is", flux, "Simulated Area is", area, "Field of View is", solidangle, "Detected Flux is", detectedflux
print time.asctime(time.localtime()),"Rate per hour", rateperhour, "Simulated Hours", cfg.numberofhours, "Simulated Events", n
s.run(eff, rowcount, mincount=cfg.mincount, text=cfg.text, graph=cfg.graph, output=sourcedata, layout=cfg.orientation, number = n)
bp.run(sourcedata, processdata, int(cfg.mincount), rowcount, text=cfg.text)
br.run(processdata, reconstructdata, rowcount, cfg.reconstructiongridwidth, eff)
message = str(time.asctime(time.localtime())) + " Completed simulation of " + str(n) + " events!"
print message
import os, sys
import sendemail as se
name = os.path.basename(__file__)
se.send(name, message)
if cfg.plotcut:
allcounts = cc.run(reconstructdata, rowcount, int(cfg.mincount))
sys.path.append('/d6/rstein/Hamburg-Cosmic-Rays/BDT')
import BDT
BDT.run(reconstructdata, rowcount, int(cfg.mincount), allcounts)
reader = csv.reader(csvfile, delimiter=',', quotechar='|')
rowcount = 0
for row in reader:
rowcount += 1
if cfg.simulate:
print time.asctime(
time.localtime()
), "Cosmic Ray Iron Flux is", flux, "Simulated Area is", area, "Field of View is", solidangle, "Detected Flux is", detectedflux
print time.asctime(
time.localtime()
), "Rate per hour", rateperhour, "Simulated Hours", cfg.numberofhours, "Simulated Events", n
s.run(eff,
rowcount,
mincount=cfg.mincount,
text=cfg.text,
graph=cfg.graph,
output=sourcedata,
layout=cfg.orientation,
number=n)
bp.run(sourcedata, processdata, int(cfg.mincount), rowcount, text=cfg.text)
br.run(processdata, reconstructdata, rowcount, cfg.reconstructiongridwidth,
eff)
message = str(time.asctime(
time.localtime())) + " Completed simulation of " + str(n) + " events!"
print message
import os, sys
import sendemail as se
name = os.path.basename(__file__)
se.send(name, message)
if cfg.plotcut:
exit(1)
# Spawn a CASA process to work with and put the config_file variable to
# the CASA variable list.
#casa = drivecasa.Casapy(working_dir=os.path.curdir,
#casa_logfile=False,
#echo_to_stdout=True)
#casa.run_script(["config_file = '{}'".format(args.config)])
# Top level simulation output directory.
# TODO-BM use the filename of the settings file as the path?
sim_dir = settings['path']
# Create a copy of the settings file.
if not os.path.isdir(sim_dir):
os.makedirs(sim_dir)
copyfile(args.config, join(sim_dir, args.config))
# Simulation.
simulate.run(settings)
# Average.
#casa.run_script_from_file('average_ms.py')
# Image.
#casa.run_script_from_file('image.py')
# Plot results.
#plot.run(settings)
# Record time taken.
from simulate import run
if __name__ == "__main__":
import sys
fileToRead = sys.argv[1]
run(fileToRead)
def output(bdt=0.96, probk=-2.0, probmu=2.0, probe=2.0, countoutput=False, text=False, dynamic=False, graph =False, random=False):
#Fit to find expected background count and exponential distribution parameter
expcount, aval = f.run(file1, t1, CommonSelection, lower, upper, lowercut, uppercut, bdt, probk, probmu, probe, text=text, graph=graph)
count = 17
significance = False
maxrandomcount = 100
if random:
randomcount=0
else:
randomcount = maxrandomcount - 1
ratioarray = []
errorarray = []
if expcount != None:
#Calculates the Branmching Ratio 100 times, and calculates a mean
while randomcount != maxrandomcount:
#iteratively add counts to the signal peak until it has a 5 sigma significance
while significance != True:
sig, entries, significance, peak, sigma, selection = s.run(file2, t2, CommonSelection, var, lower, upper, lowercut, uppercut, bdt, expcount, aval, count, probk, probmu, probe, text=text, graph=graph)
if (dynamic == True) & (peak < 3.0):
if sigma < (expcount * 0.2):
count += (int(sigma) +1)
else:
count +=20
elif significance != True:
count += int(sigma*0.01) +1
ratio, error = br.run(sig, entries, file2, t2, selection)
randomcount += 1
ratioarray.append(ratio)
errorarray.append(error)
significance = False
count += -5
averageratio = np.mean(ratioarray)
if random:
averageerror = np.mean(errorarray)/math.sqrt(float(randomcount))
print time.asctime(time.localtime()), "Final Branching Ratio is", ufloat(averageratio, averageerror)
else:
averageerror = np.mean(errorarray)
#return ratio and error for the purpose of a csv output and graph
if countoutput == True:
return averageratio, averageerror
#return just the ratio, for the purpose of minimisation
else:
return averageratio
#If the fit has not converged, or expected count is 0, return error
else:
return float('nan')
exit(1)
# Spawn a CASA process to work with and put the config_file variable to
# the CASA variable list.
casa = drivecasa.Casapy(working_dir=os.path.curdir,
casa_logfile=False,
echo_to_stdout=True)
casa.run_script(["config_file = '{}'".format(args.config)])
# Top level simulation output directory.
# TODO-BM use the filename of the settings file as the path?
sim_dir = settings['path']
# Create a copy of the settings file.
if not os.path.isdir(sim_dir):
os.makedirs(sim_dir)
copyfile(args.config, join(sim_dir, args.config))
# Simulation.
simulate.run(settings)
# Average.
casa.run_script_from_file('average_ms.py')
# Image.
casa.run_script_from_file('image.py')
# Plot results.
plot.run(settings)
