p.new(xlabel=r'time [ps]',
ylabel=r'number of hydrogen bonds',
name='hbnum',
loc=3)
n = 0
for medium, values in sorted(datadict['hbnum'].iteritems()):
t = values[1]
num = values[2]
i = t > 30
m = [np.mean(num[i]), np.mean(num[i])]
x = [t[i][0], t[i][-1]]
print medium + ": %f" % m[0]
p.plot(t, num, c[n] + '-', alpha=0.2, label=medium + ', mean: %f' % m[0])
p.plot(x, m, c[n] + '-', lw=2)
n += 1
# msd
p.new(xlabel=r'time [ps]',
ylabel=r'mean square displacement [nm$^2$]',
name='msd',
xscale='log',
yscale='log')
n = 0
for medium, values in sorted(datadict['msd'].iteritems()):
p.plot(values[1], values[2], c[n] + '-', label=medium)
n += 1
# diffusion
E_s.append([array_t, array_E, r'$\omega = %.2f$'%w])
w_s = np.arange(0.001,2,0.1)
amp_s = []
for w in w_s:
F = lambda t: Fmax*np.sin(w*t)
amp = getAmplitude(x,v,a,t)
amp_s.append(amp)
# === Plotting ===
p = Plotter(show = True, pgf = False, pdf = False, loc=1)
# --- Auslenkung ---
p.new(title='Auslenkung',xlabel='t',ylabel='x')
for v,w,name in x_s: p.plot(v,w,label=name)
# --- Auslenkung ---
p.new(title='Plots für ausgeschaltete Anregung',xlabel='t')
v,w,name = x_s[0]
p.plot(v,w,label='Auslenkung x')
v,w,name = v_s[0]
p.plot(v,w,label='Geschwindigkeit v')
v,w,name = a_s[0]
p.plot(v,w,label='Beschleunigung a')
# --- Energie ---
p.new(title='Gesamte Energie', yscale='log',xlabel='t',ylabel='E')
for v,w,name in E_s: p.plot(v,w,label=name)
# --- Amplitude ---
datadict[type][0] = np.append(datadict[type][0], volume)
datadict[type][1] = np.append(datadict[type][1], energy)
datadict[type][2] = np.append(datadict[type][2], lattice)
print "%s, run %2s) lattice constant = %f, cell volume = %f, total energy = %f \n" % (
type, runnumber, lattice, volume, energy)
with open('data.pkl', 'wb') as f:
pickle.dump(datadict, f)
else:
with open('data.pkl', 'rb') as f:
datadict = pickle.load(f)
# ==== PLOT ====
for type, [volume, energy, lattice] in datadict.items():
sort = np.argsort(volume)
lattice = np.array(lattice)[sort]
volume = np.array(volume)[sort]
energy = np.array(energy)[sort]
p.new(xlabel=r'cell volume [Ang$^3$]',
ylabel=r'total energy [eV]',
name=type + "_energy")
p.plot(volume, energy, '-', label=type)
p.new(xlabel=r'cell volume [Ang$^3$]',
ylabel=r'lattice constant [Ang]',
name=type + "_lattice")
p.plot(volume, lattice, 'x', label=type)
p.make(ncols=2)
energy = float(e)
lattice = float(l)
except:
continue
datadict[type][0] = np.append(datadict[type][0], volume)
datadict[type][1] = np.append(datadict[type][1], energy)
datadict[type][2] = np.append(datadict[type][2], lattice)
print "%s, run %2s) lattice constant = %f, cell volume = %f, total energy = %f \n"%(type,
runnumber,lattice,volume,energy)
with open('data.pkl', 'wb') as f:
pickle.dump(datadict, f)
else:
with open('data.pkl', 'rb') as f:
datadict = pickle.load(f)
# ==== PLOT ====
for type, [volume,energy,lattice] in datadict.items():
sort = np.argsort(volume)
lattice = np.array(lattice)[sort]
volume = np.array(volume)[sort]
energy = np.array(energy)[sort]
p.new(xlabel=r'cell volume [Ang$^3$]', ylabel=r'total energy [eV]',name=type+"_energy")
p.plot(volume, energy, '-', label=type)
p.new(xlabel=r'cell volume [Ang$^3$]',ylabel=r'lattice constant [Ang]',name=type+"_lattice")
p.plot(volume, lattice, 'x', label=type)
p.make(ncols = 2)
w_s = np.arange(0.001, 2, 0.1)
amp_s = []
for w in w_s:
F = lambda t: Fmax * np.sin(w * t)
amp = getAmplitude(x, v, a, t)
amp_s.append(amp)
# === Plotting ===
p = Plotter(show=True, pgf=False, pdf=False, loc=1)
# --- Auslenkung ---
p.new(title='Auslenkung', xlabel='t', ylabel='x')
for v, w, name in x_s:
p.plot(v, w, label=name)
# --- Auslenkung ---
p.new(title='Plots für ausgeschaltete Anregung', xlabel='t')
v, w, name = x_s[0]
p.plot(v, w, label='Auslenkung x')
v, w, name = v_s[0]
p.plot(v, w, label='Geschwindigkeit v')
v, w, name = a_s[0]
p.plot(v, w, label='Beschleunigung a')
# --- Energie ---
p.new(title='Gesamte Energie', yscale='log', xlabel='t', ylabel='E')
for v, w, name in E_s:
p.plot(v, w, label=name)
# hbnum
print "=== hbnum ==="
p.new(xlabel=r'time [ps]', ylabel=r'number of hydrogen bonds',name='hbnum', loc = 3)
n = 0
for medium, values in sorted(datadict['hbnum'].iteritems()):
t = values[1]
num = values[2]
i = t > 30
m = [np.mean(num[i]), np.mean(num[i])]
x = [t[i][0],t[i][-1]]
print medium+": %f"%m[0]
p.plot(t, num, c[n]+'-', alpha=0.2, label=medium+', mean: %f'%m[0])
p.plot(x, m, c[n]+'-',lw=2)
n+=1
# msd
p.new(xlabel=r'time [ps]', ylabel=r'mean square displacement [nm$^2$]',name='msd', xscale='log',yscale='log')
n = 0
for medium, values in sorted(datadict['msd'].iteritems()):
p.plot(values[1], values[2], c[n]+'-', label=medium)
n += 1
# diffusion
print "=== diffusion ==="
p.new(xlabel=r'time [ps]', ylabel=r'diffusion coefficient [10$^{-5}$ cm$^2$/s]',name='diffusion')
n = 0
for medium, values in sorted(datadict['msd'].iteritems()):
