for i_t,t in enumerate(ts):
ld = LoadData(name=f"radius_{i_t}",scan=scan,savesuf=savesuf,
loadfilepath=loadfilepath,datfile=datfile)
Rs = ld.data[:,1]
Ns[i_t] = Rs.size
axarr.flat[i].plot(ts,Ns,markers[j],color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_yscale('log')
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$N(t)$")
axarr.flat[i].legend(frameon=False,handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom = 0.08,top = 0.95,left=0.08,right=0.95)
fig.savefig(ld.file_savename("N-loglin"))
Rs = ld.data[:, 1]
R_avgts[i_t] = Rs.mean()
sigma_Rts[i_t] = Rs.std()
chi_spaced[i_t] = chis[t_smalls <= t][-1]
label = rf"$<\,R\,>(t=0)={R_avg0:.1f}$"
ax.plot(R_avgts,
sigma_Rts - sigma,
chi_spaced,
lw=4,
color=colors[i],
label=label)
ax.set_title(rf"$\sigma=\num{{{sigma:.0e}}}$")
ax.set_xlabel(r"$<R>(t)$")
ax.set_ylabel(r"$\sigma(t)-\sigma(0)$")
ax.set_zlabel(r"$\chi(t)$")
ax.legend(frameon=False, handlelength=5)
ax.view_init(45, -45)
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename(f"R_avg-vs-sigma-vs-chi-sigma0is{sigma}"))
Ns = np.empty([len(ts)], float)
for i_t, t in enumerate(ts):
ld = LoadData(name=f"radius_{i_t}", scan=scan, savesuf=savesuf)
Rs = ld.data[:, 1]
Ns[i_t] = Rs.size
axarr.flat[i].plot(ts,
Ns,
markers[j],
color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$N(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("N"))
# label=rf"$\sigma=\num{{{sigma:.0e}}}$")
if i == 0:
label = rf"$\sigma=\num{{{sigma:.0e}}}$"
else:
label = None
ax.plot(R_avgts,
N_ts,
chi_spaced,
lw=4,
color=colors[j],
label=label)
#axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
ax.set_xlabel(r"$<R>(t)$")
ax.set_ylabel(r"$N(t)$")
ax.set_zlabel(r"$\chi(t)$")
ax.legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
ax.view_init(30, -45)
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("R_avg-vs-N-vs-chi"))
ld = LoadData(name=f"radius_{i_t}",
scan=scan,
savesuf=savesuf,
loadfilepath=loadfilepath,
datfile=datfile)
Rs = ld.data[:, 1]
sigma_Rts[i_t] = Rs.std()
axarr.flat[i].plot(ts,
sigma_Rts,
markers[j],
color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_xscale('log')
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$\sigma(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("sigma_R-linlog"))
print(len(ts))
fig, axarr = plt.subplots(3, len(ts) // 3)
fig.set_size_inches(width, height)
for i_t, t in enumerate(ts):
ld = LoadData(name=f"radius_{i_t}",
scan=scan,
loadfilepath=loadfilepath,
datfile=datfile)
Rs = ld.data[:, 1]
axarr.flat[i_t].hist(Rs, density=True, stacked=True)
axarr.flat[i_t].set_xlabel(r"$<R>(t)$")
axarr.flat[i_t].set_xlim(0, 20)
axarr.flat[i_t].set_ylim(0, 1)
axarr.flat[i_t].text(3, 0.5, rf"$t=\num{{{t:.1e}}}$")
fig.suptitle(rf"$<\,R\,>(t=0)={R_avg0:.1f}$" + ", " +
rf"$\sigma(t=0)=\num{{{sigma:.0e}}}$")
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("R_avg"))
plt.close(fig=fig)
ld = LoadData(name=f"radius_{i_t}",
scan=scan,
savesuf=savesuf,
loadfilepath=loadfilepath,
datfile=datfile)
Rs = ld.data[:, 1]
sigma_Rts[i_t] = Rs.std()
axarr.flat[i].plot(ts,
sigma_Rts,
markers[j],
color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_yscale('log')
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$\sigma(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("sigma_R-loglin"))
sigma_Rts = np.empty([len(ts)], float)
for i_t, t in enumerate(ts):
ld = LoadData(name=f"radius_{i_t}", scan=scan, savesuf=savesuf)
Rs = ld.data[:, 1]
sigma_Rts[i_t] = Rs.std()
axarr.flat[i].plot(ts,
sigma_Rts,
markers[j],
color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$\sigma(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("sigma_R"))
ld = LoadData(name=f"radius_{i_t}",
scan=scan,
savesuf=savesuf,
loadfilepath=loadfilepath,
datfile=datfile)
Rs = ld.data[:, 1]
R_avgts[i_t] = Rs.mean()
axarr.flat[i].plot(ts,
R_avgts,
markers[j],
color=colors[j],
label=rf"$\sigma=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].set_xscale('log')
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$<R>(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("R_avg-linlog"))
for j, sigma in enumerate(sigmas):
scan['sigma_R0'] = str(sigma)
ld = LoadData(scan=scan, savesuf=savesuf)
ts = ld.data[:, 0]
chis = ld.data[:, 1]
axarr.flat[i].set_title(rf"$<\,R\,>(t=0)={R_avg0:.1f}$")
axarr.flat[i].plot(ts,
chis,
'-',
color=colors[j],
linestyle=lines[j],
lw=4,
label=rf"$\sigma(t=0)=\num{{{sigma:.0e}}}$")
axarr.flat[i].set_xlabel(r"$t$")
axarr.flat[i].set_ylabel(r"$\chi(t)$")
axarr.flat[i].legend(frameon=False, handlelength=5)
# for ax in axarr.flat:
# ax.label_outer()
fig.subplots_adjust(bottom=0.08, top=0.95, left=0.08, right=0.95)
fig.savefig(ld.file_savename("chi-vs-t"))