for f in i.getFluxes():
folder = "flux3.5e" + str(i)
print(folder)
try:
p = i.getInputParameters(glob.glob(f + "/*/output*")[0])
os.chdir(f)
temperatures = i.getTemperatures()
meanValues = mk.getIslandDistribution(temperatures, False, False)
except (OSError, IndexError):
print("error changing to flux {}".format(f))
continue
os.chdir(workingPath)
vs = meanValues.getGrowthSlope()
s = (0.3 * 400 * 400) / meanValues.getIslandsAmount()
vg = meanValues.getGyradiusSlope()
rtt = mk.getRtt(temperatures)
d = fun.fractalD(rtt / p.flux)
rg = meanValues.getLastGyradius()
print(len(d), len(s), len(rg))
command = "d * ((s*vs)/rg**2)"
y = eval(command)
x = meanValues.getTotalRatio()
print(len(x), len(y))
try:
plt.ylabel(command)
plt.loglog(x, y, label=f)
plt.loglog(x, x / 6e10, label="total ratio {}".format(f))
plt.legend(loc='upper left', prop={'size': 6})
plt.savefig("dSVsRgVsRate.png")
except ValueError:
plt.close()
meanValues = mk.getIslandDistribution(temperatures,
sqrt=False,
interval=False,
growth=False)
except OSError:
print("error changing to {}".format(folder))
a = 0 #do nothing
os.chdir(workingPath)
islands = meanValues.getIslandsAmount()
indexes = np.where(islands > 0)
islands = islands[indexes]
v = (0.7 * flux * 400 * 400 / (islands)) / (flux**0.77)
t = np.array(temperatures)[indexes]
n = (flux**0.23) / (islands)
r = np.array(mk.getRtt(t)) / (flux**0.33)
plt.loglog(r, v, ".", label="N " + folder)
if (i == -1):
indexes = np.array(range(0, 13))
x = r[indexes]
y = v[indexes]
popt = curve_fit(f.power, x, y)
a = popt[0][0]
b = popt[0][1]
label = "{}x^{}".format(a, b)
y = f.power(x, a, b)
plt.loglog(x, y, label=label)
if (i == -1):
indexes = np.array(range(len(islands) - 15, len(islands) - 2))
x = r[indexes]
temperatures = list(range(120, 221, 5))
for i in range(-6, 1):
folder = "flux3.5e" + str(i)
flux = float("3.5e" + str(i))
print(folder)
try:
os.chdir(folder)
meanValues = mk.getIslandDistribution(temperatures, False, False)
except OSError:
print("error changing to {}".format(folder))
a = 0 #do nothing
os.chdir(workingPath)
mtt = meanValues.getAeRatioTimesPossible() #/flux**.063
r = np.array(mk.getRtt(temperatures)) #/flux**0.5
plt.loglog(mtt, r, "-", label="N " + folder)
if (i < -7):
popt = curve_fit(f.power, r, mtt)
a = popt[0][0]
b = popt[0][1]
x = r
a = 2e2
b = 2 / 3
label = "{}x^{}".format(a, b)
y = f.power(x, a, b)
plt.loglog(x, y, label=label)
plt.legend(loc='lower right', prop={'size': 6})
plt.savefig("aeRatioVsRate.png")
plt.close()
temperatures = list(range(120, 501, 5))
initFlux = -6
endFlux = 0
for i in range(initFlux, endFlux):
folder = "flux3.5e" + str(i)
flux = float("3.5e" + str(i))
print(folder)
try:
os.chdir(folder)
meanValues = mk.getIslandDistribution(temperatures, False)
except OSError:
print("error changing to {}".format(folder))
a = 0 #do nothing
os.chdir(workingPath)
plt.title("Average island growth")
plt.loglog(1 / (np.array(temperatures) * 8.62e-5),
4e4 * meanValues.getGrowthSlope(),
label="4e4*area " + folder)
plt.loglog(1 / (np.array(temperatures) * 8.62e-5),
np.array(mk.getRtt(temperatures)),
"--",
label="rate " + folder)
plt.legend(loc='lower left', prop={'size': 6})
plt.savefig("rateRttVsTemperature.png")
plt.close()
print("Good bye!")
coverage = int(sys.argv[1])
for f in i.getFluxes():
try:
p = i.getInputParameters(glob.glob(f+"/*/output*")[0])
os.chdir(f)
temperatures = i.getTemperatures()
meanValues = mk.getIslandDistribution(temperatures, sqrt=False, interval=False, growth=False, verbose = False, flux=-1, maxCoverage=coverage)
except (OSError, IndexError):
print ("error changing to {}".format(f))
continue
os.chdir(workingPath)
v = 0.82*400*400/meanValues.getIslandsAmount()*(p.flux**0.21)
n = meanValues.getIslandsAmount()/(p.flux**0.23)
r = np.array(mk.getRtt(temperatures))/(p.flux**0.33)
plt.loglog(r, n, "-", label="N "+f+" "+str(coverage))
if (i == 0):
x = r
c = []
exponent = []
for i in temperatures:
if (i > 250):
c.append(220)
exponent.append(-0.666)
else:
c.append(0.25)
exponent.append(-0.333)
y = c * r ** exponent
plt.loglog(x, y, "*", label="fit")
if (i == -1000):
yPower = 0.3
xPower = 0
#plt.title("Average island growth")
plt.grid(True)
plt.xlabel(r"$\frac{{ r_{{tt}} }} {{ F^{{ {} }} }}$".format(xPower))
plt.ylabel(r'Average radius growth rate/flux $\frac{{ \sqrt{{ \dot{{r}} }} }}{{F^{{ {} }} }} }}$'.format(yPower))
workingPath = os.getcwd()
temperatures = list(range(120,221,5))
for i in range(-6,5):
folder = "flux3.5e"+str(i)
flux = float("3.5e"+str(i))
print(folder)
try:
os.chdir(folder)
meanValues = mk.getIslandDistribution(temperatures)
except OSError:
print ("error changing to {}".format(folder))
a = 0 #do nothing
os.chdir(workingPath)
plt.loglog(np.array(mk.getRtt(temperatures))/flux**xPower, meanValues.getGrowthSlope()/(flux**yPower), label=folder)
plt.legend(loc='upper left', prop={'size':6})
plt.savefig("radiusVsRtt.png")
plt.close()
print("Good bye!")
print(folder)
verbose = False
sqrt = False
growth = False
try:
os.chdir(folder)
resultsFractal.append(mk.getAllFractalDimensions(
temperatures, verbose))
except OSError:
print("ERROR changing to {}".format(folder))
continue
os.chdir(workingPath)
while (len(temperatures) > len(resultsFractal[-1])):
resultsFractal[-1].append(float('nan'))
rttFlux = np.log(mk.getRtt(temperatures) / flux**0.333)
x = np.concatenate((x, rttFlux))
filename = "fractalD" + '{:E}'.format(flux) + ".txt"
with open(filename, 'w', newline='') as csvfile:
outwriter = csv.writer(csvfile,
delimiter=' ',
quotechar='|',
quoting=csv.QUOTE_MINIMAL)
outwriter.writerow(["%index", "temp", "flux", "shapeF"])
for index, temp in enumerate(temperatures):
outwriter.writerow([index, temp, flux, resultsFractal[-1][index]])
plt.plot(np.log(rttFlux), np.array(resultsFractal[-1]), ".-", label=folder)
#plt.ylim(1,2.1)
#plt.plot(temperatures, np.array(resultsFractal[-1]), ".-", label=folder)
plt.legend(loc='upper left', prop={'size': 6})
flux = float("3.5e"+str(i))
print(folder)
try:
os.chdir(folder)
meanValues = mk.getIslandDistribution(temperatures, False, False)
except OSError:
print ("error changing to {}".format(folder))
a = 0 #do nothing
os.chdir(workingPath)
totalRatio = (meanValues.getTotalRatio()/(flux**0.81))**(1)
x = totalRatio
y = f.fractalD(x)
gyradius = 4e7*(meanValues.getGyradiusSlope()/(flux**0.88))**(3/4*(np.array(y)-1))
gyradius = 1.3e5*(meanValues.getGyradiusSlope()/(flux**0.88))**(3*(np.array(y)-1))
r = mk.getRtt(temperatures)/flux**0.36
inverseTemperature = 1/(kb*np.array(temperatures))
plt.semilogy(inverseTemperature, gyradius, "-", label="gyradius "+folder)
plt.semilogy(inverseTemperature, totalRatio, "--", label="total ratio "+folder)
if (i < -7):
popt = curve_fit(f.power, r, totalRatio)
a = popt[0][0]
b = popt[0][1]
a = 8e-11
b = 1.33
label = "{}x^{}".format(a, b)
x = r
y = f.power(x, a, b)
plt.loglog(x, y, label=label)
plt.legend(loc='lower left', prop={'size':6})
plt.savefig("gyradiusVsTemperature.png")