def trackAlpha_vsNc(x_Nc):
date = strftime("%Y_%m_%d_%H_%M")
filename = date + '_trackAlphaAfterDSB_vsNc'
with open('results/' + filename + '.csv', 'w') as csvfile:
first_time = True
for i, Nc in enumerate(x_Nc):
polymerParams['Nc'] = Nc
p0 = RCLPolymer(**polymerParams)
# Waiting time will be relaxation time (Nc dependant)
simulationParams['waitingSteps'] = np.ceil(
p0.relaxTime(simulationParams['diffusionConstant']) /
simulationParams['dt_relax']).astype(int)
simulationParams['VE_waitingSteps'] = np.ceil(
p0.relaxTime(simulationParams['diffusionConstant']) /
simulationParams['dt']).astype(int)
results = {**polymerParams, **simulationParams}
mc = Experiment(p0, results, simulationParams, trackAlpha)
if first_time:
fieldnames = ['experimentSetID'] + list(mc.results)
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
first_time = False
os.makedirs('results/' + filename + '_figures')
writer.writerow({**{'experimentSetID': str(i)}, **mc.results})
# Save MSD raw data
with open(
'results/' + filename + '_figures/nc' + str(Nc) +
'msd_data.csv', 'w') as rawdata:
rowwriter = csv.writer(rawdata)
for msd_data in mc.results['monomersMSD'].transpose():
rowwriter.writerow(msd_data)
# Save MSD curve
plt.figure()
plt.plot(mc.results['monomersMSD'].transpose())
legend = ['_o'] * polymerParams['numMonomers']
legend[simulationParams['A1']] = 'a1'
legend[simulationParams['A1'] + 1] = 'a2'
legend[simulationParams['B1']] = 'b1'
legend[simulationParams['B1'] + 1] = 'b2'
legend = tuple(legend)
plt.legend(legend)
plt.savefig('results/' + filename + '_figures/nc' + str(Nc) +
'.png')
plt.close()
def proba_v_gNc(polymerParams, simulationParams, x_g, x_Nc, errorbars=False):
date = strftime("%Y_%m_%d_%H_%M")
filename = date + '_proba-v_gNc_withVE' + '.csv'
first_time = True
N = polymerParams['numMonomers']
with open('results/' + filename, 'w') as csvfile:
for i, g in enumerate(x_g):
print("Simulation for g = %s " % g)
simulationParams['genomicDistance'] = g
for j, nc in enumerate(x_Nc):
print("Simulation for Nc = %s " % nc)
polymerParams['Nc'] = nc
### ADAPTIVE ENCOUNTER DISTANCE
xi = 2 * (nc + simulationParams['Nc_inDamageFoci']) / (
(N - 1) * (N - 2))
# scaleFactor = np.sqrt( (1-xi0)*np.sqrt(xi0) / ((1-xi)*np.s1qrt(xi)) )
simulationParams['encounterDistance'] = adaptiveEpsilon(
xi, N, polymerParams['b'])
# simulationParams['excludedVolumeCutOff'] = 3*simulationParams['encounterDistance']
### ADAPTIVE dt
simulationParams['dt'] = np.round(
(0.2 * simulationParams['encounterDistance'])**2 /
(2 * simulationParams['diffusionConstant']),
decimals=4) - 0.0001
simulationParams['numMaxSteps'] = int(60 //
simulationParams['dt'])
print("ε = %s" % (simulationParams['encounterDistance']))
p0 = RCLPolymer(**polymerParams)
simulationParams['waitingSteps'] = np.ceil(
p0.relaxTime(simulationParams['diffusionConstant']) /
simulationParams['dt_relax']).astype(int)
results = {**polymerParams, **simulationParams}
mc = Experiment(p0, results, simulationParams,
"EncounterSimulation")
if first_time:
fieldnames = ['experimentSetID'] + list(mc.results)
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
first_time = False
writer.writerow({
**{
'experimentSetID': str(i) + '_' + str(j)
},
**mc.results
})
def stats_vs_Nb(polymerParams, simulationParams, x_Nb, x_g):
date = strftime("%Y_%m_%d_%H_%M")
filename = date + '_StatsVsNb' + '.csv'
first_time = True
with open('results/' + filename, 'w') as csvfile:
for i, Nb in enumerate(x_Nb):
print("Simulation for Nb = %s breaks " % Nb)
simulationParams['Nb'] = Nb
for j, g in enumerate(x_g):
simulationParams['genomicDistance'] = g
print("and g = %s . " % g)
p0 = RCLPolymer(**polymerParams)
simulationParams['waitingSteps'] = np.ceil(
p0.relaxTime(simulationParams['diffusionConstant']) /
simulationParams['dt_relax']).astype(int)
results = {**polymerParams, **simulationParams}
mc = Experiment(p0, results, simulationParams,
"EncounterSimulation")
if first_time:
fieldnames = ['experimentSetID'] + list(mc.results)
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
first_time = False
writer.writerow({
**{
'experimentSetID': str(i) + "_" + str(j)
},
**mc.results
})
def trackAlpha_v_gNc(polymerParams, simulationParams, x_g, x_Nc):
date = strftime("%Y_%m_%d_%H_%M")
filename = date + '_trackMSD' + '.csv'
first_time = True
N = polymerParams['numMonomers']
with open('results/' + filename, 'w') as csvfile:
for i, g in enumerate(x_g):
print("Simulation for g = %s " % g)
simulationParams['genomicDistance'] = g
for j, nc in enumerate(x_Nc):
print("Simulation for Nc = %s " % nc)
polymerParams['Nc'] = nc
p0 = RCLPolymer(**polymerParams)
simulationParams['waitingSteps'] = np.ceil(
p0.relaxTime(simulationParams['diffusionConstant']) /
simulationParams['dt_relax']).astype(int)
results = {**polymerParams, **simulationParams}
mc = Experiment(p0, results, simulationParams, "trackMSD")
if first_time:
fieldnames = ['experimentSetID'] + list(mc.results)
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
first_time = False
writer.writerow({
**{
'experimentSetID': str(i) + '_' + str(j)
},
**mc.results
})