plt.legend(fontsize = 12)
plt.tick_params(axis='both', which='major', labelsize=12)
plt.savefig(fpath + fname + suffix[k])
plt.show()
#%% DISSOLUTION/PRECIPITATION RATE
titles = ['Dissolution rate', 'Precipitation rate' ]
comp = ['portlandite', 'calcite']
suffix = ['_CH_rate', '_CC_rate' ]
s =2
for k in range(0, len(comp)):
plt.figure(figsize=(8,4))
for i in range(0, len(names)):
rate = np.abs(cf.get_rate(results[names[i]][comp[k]],
results[names[i]]['time'][2] - results[names[i]]['time'][1],
step = s ))
#print(len(rate))
plt.plot(np.array(results[names[i]]['time'][::s])/3600,
rate,
ls=linetype[i], label = label[i])
plt.title(titles[k])
plt.xlabel('Time (h)')
plt.ylabel('Rate (mol/s)')
plt.yscale("log")
plt.legend()
plt.savefig(fpath + fname + suffix[k])
plt.show()
#plt.savefig(fpath + fname + '_CH_rate')
#%% POINTS
f = ('C', 'C') # ('Ca', 'Ca') ('Volume CH', 'vol_CH') ('Volume CC', 'vol_CC') ('pH', 'pH') ('De', 'De')('Porosity', 'poros')
plt.legend()
plt.savefig(fpath + fname + suffix[k])
plt.show()
#%% DISSOLUTION RATE
titles = ['Dissolution rate', 'Precipitation rate']
comp = ['portlandite', 'calcite']
suffix = ['_CH_rate', '_CC_rate']
limits = [[-0.1, 0], [0, 0.1]]
rate = {}
for i in range(0, len(names)):
rate[names[i]] = {}
for k in range(0, len(comp)):
rate[names[i]][comp[k]] = cf.get_rate(
results[names[i]][comp[k]],
results[names[i]]['time'][2] - results[names[i]]['time'][1])
rstart = 0
rend = len(results[names[1]]['time']) - 1
for k in range(0, len(comp)):
plt.figure(figsize=(8, 4))
for i in range(0, len(names)):
plt.plot(results[names[i]]['time'][rstart:rend],
rate[names[i]][comp[k]][rstart:rend],
ls=linetype[i],
label=label[i])
plt.title(titles[k])
#plt.ylim(limits[k])
plt.xlabel('Time (s)')
plt.ylabel('Rate (mol/s)')
plt.tick_params(axis='both', which='major', labelsize=12)
plt.savefig(fpath + fname + suffix[k])
plt.show()
#%% DISSOLUTION AND PRECIPITATION RATE
titles = ['Dissolution rate', 'Precipitation rate']
comp = ['portlandite', 'calcite']
suffix = ['_CH_rate', '_CC_rate']
s = 1
for k in range(0, len(comp)):
plt.figure(figsize=(8, 4))
for i in range(0, len(names)):
rate = np.abs(
cf.get_rate(sres[names[i]][comp[k]],
sres[names[i]]['time'][2] - sres[names[i]]['time'][1],
step=s))
t = sres[names[i]]['time']
r = rate
l = len(sres[names[i]]['time']) - len(rate)
if (l > 0):
t = sres[names[i]]['time'][l:]
r = rate
elif (l < 0):
t = sres[names[i]]['time']
r = rate[np.abs(l):]
plt.plot(t[10:r2], r[10:r2], ls=linetype[i], label=label[i])
plt.title(titles[k])
plt.xlabel('Time (s)')
plt.ylabel('Rate (mol/s)')
