def plot_sw(ff, temps):
figure()
for temp in temps:
fname = 'data/radial-sw-%.2f-%.2f-%.2f.dat' % (temp, 1.3, ff/100.0)
data = loadtxt(fname)
r = data[:,0]
filling_fraction = data[:,1]
plot(r, filling_fraction/(ff/100.0), color(temp)+'-',
label = 'T = %.2f' %(temp))
N = 500
ww = 1.3
g, r = readandcompute.g_r('data/mc/ww%.2f-ff%.2f-N%d' % (ww,ff/100.0,N), temp)
plt.plot(r/2, g, color(temp)+':')
title('Radial distribution function ff = %g' % (ff/100))
xlabel(r'$r$')
ylabel('$g(r)$')
legend()
xlim(-0.2, 4)
#ylim(0, 4)
outputname = 'figs/radial-sw-%02d.pdf' % (ff)
savefig(outputname, bbox_inches=0)
print('figs/radial-sw-%02d.pdf' % (ff))
def plot_sw(ff, temps):
figure()
for temp in temps:
fname = 'data/radial-sw-%.2f-%.2f-%.2f.dat' % (temp, 1.3, ff/100.0)
data = loadtxt(fname)
r = data[:,0]
filling_fraction = data[:,1]
plot(r, filling_fraction/(ff/100.0), color(temp)+'-',
label = 'T = %.2f' %(temp))
N = 500
ww = 1.3
g, r = readandcompute.g_r('data/mc/ww%.2f-ff%.2f-N%d' % (ww,ff/100.0,N), temp)
plt.plot(r/2, g, color(temp)+':')
title('Radial distribution function ff = %g' % (ff/100))
xlabel(r'$r$')
ylabel('$g(r)$')
legend()
xlim(-0.2, 4)
matplotlib.rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
matplotlib.rc('text', usetex=True)
import readandcompute
ww = float(sys.argv[1])
#arg ww = [1.3]
ff = float(sys.argv[2])
#arg ff = [0.3]
Ns = eval(sys.argv[3])
#arg Ns = [[500, 1372, 400]]
T = float(sys.argv[4])
#arg T = [1.0]
plt.figure()
for N in Ns:
g, r = readandcompute.g_r('data/mc/ww%.2f-ff%.2f-N%d' % (ww,ff,N), T)
plt.plot(r/2, g, '-', label='$N=%d$' % N)
plt.legend(loc='best')
plt.xlabel(r'$r/\sigma$')
plt.ylabel(r'$g(r)$')
plt.title(r'$g(r)$ with $\lambda = %g$, $\eta=%g$, and $T/\epsilon = %g$'
% (ww, ff, T))
plt.savefig('figs/radial-distribution-ww%.2f-ff%.2f-T%.2g.pdf' % (ww,ff,T))
plt.show()