def Pig_xy(self):
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
self.T = self.gen_data[self.feed][self.run][self.feed]['temperature']
rho, N = self.rho[self.feed][self.run], self.N[self.feed][self.run]
vapor_box = self.findVapBox(rho, self.mol)
num_box = len(rho.keys())
if num_box == 3:
liquid_box = 'box2'
else:
liquid_box = 'box1'
# get pressure
p_mean = 0.
p_stdev = 0.
factor = 1 / N_av * R['nm**3*kPa/(mol*K)'] * self.T
for mol in rho.keys():
mean, stdev = rho[mol][vapor_box]['mean'], rho[mol][vapor_box][
'stdev']
p_mean += mean * factor
p_stdev += math.pow(stdev, 2) * math.pow(factor, 2)
p_stdev = math.sqrt(p_stdev)
file_description = '%s Pig %s dP' % (self.xlabel[0],
self.xlabel[1])
file_name = 'Pig_x_mol%s' % self.mol
X = self.getX(box=liquid_box)
writeCSV([X['mean']], [p_mean], [calc95conf(X['stdev'], nIndep)],
[calc95conf(p_stdev, nIndep)], [self.feed], file_name,
file_description)
file_name = 'Pig_y_mol%s' % self.mol
X = self.getX(box=vapor_box)
writeCSV([X['mean']], [p_mean], [calc95conf(X['stdev'], nIndep)],
[calc95conf(p_stdev, nIndep)], [self.feed], file_name,
file_description)
def XvX(self):
if (0 in self.indep) and (len(self.indep) == 1): raise NotImplemented
N = self.N[self.feed][self.run]
mol_frac = self.X[self.feed][self.run]
X = self.getX()
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
if '95conf' in X.keys():
dX = X['95conf']
else:
dX = calc95conf(X['stdev'], nIndep)
file_description = '%s x (mol/mol) %s dx' % (self.xlabel[0],
self.xlabel[1])
for box in N['1'].keys():
for mol1 in N.keys():
print(mol_frac.keys())
if mol1 in mol_frac[box].keys():
file_name = 'X_mol%s_%s-vs-%s.dat' % (mol1, box,
self.xlabel[0])
x_mean, x_stdev = mol_frac[box][mol1]['mean'], mol_frac[
box][mol1]['stdev']
if box == 'box1':
print(x_mean, x_stdev)
if ('P-box' in self.xlabel[0]) and (x_mean < 0.75):
assert self.T, 'Temperature needed for vapor p'
rho = self.rho[self.feed][self.run]
x_mean, x_stdev = calculateIGMolFrac(
rho, mol1, box, X, self.T)
writeCSV([X['mean']], [x_mean], [dX],
[calc95conf(x_stdev, nIndep)], [self.feed],
file_name, file_description)
def DensvX(self):
assert 'box' in self.box, 'Box needed for density'
if (0 in self.indep) and (len(self.indep) == 1): raise NotImplemented
X = self.getX()
rho = self.rho[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run][self.feed]
nIndep = gen_data['numIndep']
file_description = '%s density(g/mL) %s dd' % (
self.xlabel[0], self.xlabel[1])
file_name = 'Dens_v_%s_%s.dat' % (self.xlabel[0], self.box)
density = {'mean': 0., 'stdev': 0.}
for mol in rho.keys():
factor = gen_data['molecular weight'][mol] / N_av * math.pow(
10, 21)
if self.box in rho[mol]:
dens_molec_nm3 = {
'mean': rho[mol][self.box]['mean'],
'stdev': rho[mol][self.box]['stdev']
}
density['mean'] += dens_molec_nm3['mean'] * factor
density['stdev'] += math.pow(dens_molec_nm3['stdev'] * factor,
2)
density['stdev'] = math.sqrt(density['stdev'])
writeCSV([X['mean']], [density['mean']],
[calc95conf(X['stdev'], nIndep)],
[calc95conf(density['stdev'], nIndep)], [self.feed],
file_name, file_description)
def dGvX(self):
assert len(self.boxes) == 2, 'Too many boxes {}'.format(self.boxes)
file_description = '%s dG(kJ/mol) %s dG' % (self.xlabel[0],
self.xlabel[1])
N = self.N[self.feed][self.run]
dG = self.dG[self.feed][self.run]
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
boxFrom, boxTo = self.boxes
X = self.getX()
assert 'box' in boxFrom, 'Wrong notation for box'
molecules = sorted([
i for i in N.keys()
if ((N[i][boxTo]['mean'] > 0.) and (N[i][boxFrom]['mean'] > 0.))
])
for mol in molecules:
file_name = 'dG-mol%s_vs_%s_%s-->%s.dat' % (mol, self.xlabel[0],
boxFrom, boxTo)
if (0 in self.indep) and (len(self.indep) == 1):
dG_vals = dG[mol]['--'.join([boxFrom, boxTo])]['raw']
x_vals = X['raw']
writeCSV(x_vals, dG_vals, None, None,
[self.feed for i in x_vals], file_name,
file_description)
else:
dG_mean, dG_stdev = (dG[mol]['--'.join([boxFrom,
boxTo])]['mean'],
dG[mol]['--'.join([boxFrom,
boxTo])]['stdev'])
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeCSV([X['mean']], [dG_mean], [X['95conf']],
[calc95conf(dG_stdev, nIndep)], [self.feed],
file_name, file_description)
def dUvX(self):
U = self.U[self.feed][self.run]
N = self.N[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run][self.feed]
file_description = 'Q(%s) %s dQ %s' % (
self.units, self.xlabel[0], self.xlabel[1])
file_name = 'dU_%s_mixture.dat' % self.box
X = self.getX()
N1_tot = sum(N[i]['box1']['mean'] for i in N.keys())
N1 = {
'mean': N1_tot,
'stdev': math.pow(sum(N[i]['box1']['stdev']**2 for i in N.keys()),
0.5)
} # mol
N2_tot = sum(N[i][self.box]['mean'] for i in N.keys())
N2 = {
'mean':
N2_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
nIndep = gen_data['numIndep']
dU = (U['box1']['mean'] / N1_tot -
U[self.box]['mean'] / N2_tot) * 8.314 / 1000
ddU = math.pow(
(1 / N1_tot)**2 * U['box1']['stdev']**2 +
(-1 * U['box1']['mean'] / N1['mean']**2)**2 * N1['stdev']**2 +
(1 / N2_tot)**2 * U[self.box]['stdev']**2 +
(-1 * U[self.box]['mean'] / N2['mean']**2)**2 * N2['stdev']**2,
0.5) * 8.314 / 1000
dU_mean, dU_stdev = dU, ddU
writeCSV([X['mean']], [dU_mean], [calc95conf(X['stdev'], nIndep)],
[calc95conf(dU_stdev, nIndep)], [self.feed], file_name,
file_description)
def XvX(self):
assert 'box' in self.box, 'Box needed for mole frac plot'
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
N = self.N[self.feed][self.run]
x = self.getX(box=self.box)
file_description = 'x (mol/mol) x (mol/mol) dx dx'
for mol in N.keys():
y = self.getX(box=self.box, myMol=mol)
if y['mean'] > 0.:
file_name = 'XvX_%s_%s.dat' % (self.mol, mol)
writeCSV([x['mean']], [y['mean']],
[calc95conf(x['stdev'], nIndep)],
[calc95conf(y['stdev'], nIndep)], [self.feed],
file_name, file_description)
def getX(self):
# pressure info ----------------------
numIndep = self.gen_data[self.feed][self.run]['numIndep']
# try:
# convert number density to pressure [kPa]
# (molec/nm**3)*(mol/molec)*(nm**3*kPa/(mol*K))*K = kPa
my_box = self.findVapBox(self.rho[self.feed][self.run], self.mol)
rho = self.rho[self.feed][self.run][self.mol][my_box]
p_mean = rho['mean'] / N_av * R['nm**3*kPa/(mol*K)'] * self.T
p_stdev = rho['stdev'] / N_av * R['nm**3*kPa/(mol*K)'] * self.T
p_raw = [
i / N_av * R['nm**3*kPa/(mol*K)'] * self.T for i in rho['raw']
]
# except :
# pressure = self.P[self.feed][self.run][self.box]
# print('No num dens. data for feed {}, using box pressure'.format(feed))
# print(' - This assumes box is unary')
# p_mean, p_stdev = pressure['mean'], pressure['stdev']
p_95conf = calc95conf(p_stdev, numIndep)
C_95conf = p_mean * self.kH_mean * math.pow(
math.pow(self.kH_95conf / self.kH_mean, 2) +
math.pow(p_95conf / p_mean, 2), 0.5)
return {
'mean': p_mean * self.kH_mean,
'95conf': C_95conf,
'raw': [i * self.kH_mean for i in p_raw]
}
def dHigvX(self):
U = self.U[self.feed][self.run]
dH_store = self.dHmixt[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run]
file_name = 'dHig_vapor_to_%s.dat' % self.box
X = self.getX()
N = self.N[self.feed][self.run]
P = self.P[self.feed][self.run]
N1_tot = sum(N[i][self.box]['mean'] for i in N.keys())
_rho_ = self.rho[self.feed][self.run]
rho_total = getRhoTotal(_rho_)
N1 = {
'mean':
N1_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
vapor_box = 'box3'
N2 = {'mean': sum(N[i]['box3']['mean'] for i in N.keys())}
N2['stdev'] = math.pow(sum(N[i]['box3']['stdev']**2 for i in N.keys()),
0.5)
nIndep = gen_data['numIndep']
# dH = ((U[self.box]['mean']/N1['mean'] - U[vapor_box]['mean']/N2['mean'])*8.314/1000 - 8.314/1000*self.T -
# dH_store['box3-->box2']['mean'])
H_box1 = U[self.box]['mean'] / N1['mean']
H_box2 = P['box2']['mean'] * 1000. / rho_total['box2'] * N_av / R[
'\AA**3*kPa/(mol*K)']
H_box3 = U[vapor_box]['mean'] / N2['mean'] - P['box3'][
'mean'] * 1000. / rho_total['box3'] * N_av / R['\AA**3*kPa/(mol*K)']
dH = (H_box1 - H_box2 - H_box3) * R['kJ/(mol*K)']
ddH = math.pow(
(1 / N1['mean'])**2 * U['box1']['stdev']**2 +
(-1 * U['box1']['mean'] / N1['mean']**2)**2 * N1['stdev']**2 +
(1 / N2['mean'])**2 * U[vapor_box]['stdev']**2 +
(-1 * U[vapor_box]['mean'] / N2['mean']**2)**2 * N2['stdev']**2 +
dH_store['box3-->box2']['stdev']**2, 0.5) * 8.314 / 1000
dH_mean, dH_stdev = dH, ddH
file_description = 'dHig %s ddHig %s' % (self.xlabel[0],
self.xlabel[1])
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeAGR([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
def dHvX(self):
P = self.P[self.feed][self.run]
U = self.U[self.feed][self.run]
_rho_ = self.rho[self.feed][self.run]
rho_total = getRhoTotal(_rho_)
dH = self.dHmixt[self.feed][self.run]
N = self.N[self.feed][self.run]
N1_tot = sum(N[i][self.box]['mean'] for i in N.keys())
N1 = {
'mean':
N1_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
gen_data = self.gen_data[self.feed][self.run]
file_description = 'Q(%s) %s dQ %s' % (
self.units, self.xlabel[0], self.xlabel[1])
if self.boxes:
boxFrom, boxTo = self.boxes
# else:
# boxFrom = self.box
# boxTo = 'box1'
file_name = 'dH_%s_mixture.dat' % boxTo
assert 'box' in boxFrom, 'Wrong notation for box'
transfer = boxFrom + '-->' + boxTo
transfer2 = 'box2-->box1'
X = self.getX()
nIndep = gen_data['numIndep']
H_zeo = (U['box1']['mean'] / N1_tot + 0.1 * 1000. / rho_total['box1'] *
N_av / R['\AA**3*kPa/(mol*K)']) * R['kJ/(mol*K)']
dH_mean, dH_stdev = (dH[transfer]['mean'] + dH[transfer2]['mean'] -
H_zeo,
math.pow(
dH[transfer]['stdev']**2 +
4 * dH[transfer2]['stdev']**2, 0.5))
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeAGR([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
def Txy(self):
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
rho, N = self.rho[self.feed][self.run], self.N[self.feed][self.run]
try:
vapor_box = self.findVapBox(rho, self.mol)
except KeyError:
vapor_box = 'box2'
num_box = len(rho['1'].keys())
if num_box == 3:
liquid_box = 'box2'
else:
liquid_box = 'box1'
T = self.gen_data[self.feed][self.run][self.feed]['temperature']
file_description = '%s T %s ' % (self.xlabel[0], self.xlabel[1])
file_name = 'Tx_mol%s' % self.mol
X = self.getX(box=liquid_box)
writeCSV([X['mean']], [T], [calc95conf(X['stdev'], nIndep)], [0.],
[self.feed], file_name, file_description)
file_name = 'Ty_mol%s' % self.mol
X = self.getX(box=vapor_box)
writeCSV([X['mean']], [T], [calc95conf(X['stdev'], nIndep)], [0.],
[self.feed], file_name, file_description)
def RvX(self):
assert self.mol, 'Molecule needed to calculate recovery'
assert self.box, 'Box needed to calculate recovery'
if (0 in self.indep) and (len(self.indep) == 1): raise NotImplemented
N = self.N[self.feed][self.run]
# N: feed, run, mol, box, mean/stdev
X = self.getX()
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
file_name = 'R_mol%s_box%s-vs-%s.dat' % (self.mol, self.box,
self.xlabel[0])
file_description = '%s Recovery %s dR' % (self.xlabel[0],
self.xlabel[1])
Ni_tot = sum(N[self.mol][i]['mean'] for i in N[self.mol].keys())
R_mean = N[self.mol]['box%s' % self.box]['mean'] / Ni_tot * 100
R_stdev = pow(
pow(
1 / Ni_tot -
N[self.mol]['box%s' % self.box]['mean'] / pow(Ni_tot, 2), 2) *
pow(N[self.mol]['box%s' % self.box]['stdev'], 2), 0.5) * 100
writeCSV([X['mean']], [R_mean], [calc95conf(X['stdev'], nIndep)],
[calc95conf(R_stdev, nIndep)], [self.feed], file_name,
file_description)
def rho_vapor(self):
nIndep = self.gen_data[self.feed][self.run][self.feed]['numIndep']
self.T = self.gen_data[self.feed][self.run][self.feed]['temperature']
rho, N = self.rho[self.feed][self.run], self.N[self.feed][self.run]
vapor_box = self.findVapBox(rho, self.mol)
factor = 1 / N_av * R['nm**3*kPa/(mol*K)'] * self.T
X = self.getX()
file_description = '%s Pig %s dP' % (self.xlabel[0],
self.xlabel[1])
file_name = 'rho-mol%s-%s_vs_%s.dat' % (self.mol, vapor_box,
self.xlabel[0])
if (0 in self.indep) and (len(self.indep) == 1):
vals = rho[self.mol][vapor_box]['raw']
x_vals = X['raw']
writeCSV(x_vals, vals, None, None, [self.feed for i in x_vals],
file_name, file_description)
else:
mean, stdev = rho[self.mol][vapor_box]['mean'], rho[
self.mol][vapor_box]['stdev']
writeCSV([X['mean']], [mean], [calc95conf(X['stdev'], nIndep)],
[calc95conf(stdev, nIndep)], [self.feed], file_name,
file_description)
def dHigvX(self):
U = self.U[self.feed][self.run]
N = self.N[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run][self.feed]
file_name = 'dHig_vapor_to_%s.dat' % self.box
X = self.getX()
N1_tot = sum(N[i][self.box]['mean'] for i in N.keys())
N1 = {
'mean':
N1_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
vapor_box = 'box3'
N2_tot = sum(N[i][vapor_box]['mean'] for i in N.keys())
N2 = {
'mean':
N2_tot,
'stdev':
math.pow(sum(N[i][vapor_box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
nIndep = gen_data['numIndep']
dH = (U[self.box]['mean'] / N1_tot - U[vapor_box]['mean'] /
N2_tot) * 8.314 / 1000 - 8.314 / 1000 * self.T
ddH = math.pow(
(1 / N1_tot)**2 * U['box1']['stdev']**2 +
(-1 * U['box1']['mean'] / N1['mean']**2)**2 * N1['stdev']**2 +
(1 / N2_tot)**2 * U[vapor_box]['stdev']**2 +
(-1 * U[vapor_box]['mean'] / N2['mean']**2)**2 * N2['stdev']**2,
0.5) * 8.314 / 1000
dH_mean, dH_stdev = dH, ddH
file_description = 'dHig %s ddHig %s' % (self.xlabel[0],
self.xlabel[1])
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeCSV([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
def dHvX(self):
dH = self.dHmixt[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run][self.feed]
file_description = 'Q(%s) %s dQ %s' % (
self.units, self.xlabel[0], self.xlabel[1])
if self.boxes:
boxFrom, boxTo = self.boxes
# else:
# boxFrom = self.box
# boxTo = 'box1'
file_name = 'dH_%s_mixture.dat' % boxTo
assert 'box' in boxFrom, 'Wrong notation for box'
transfer = boxFrom + '-->' + boxTo
X = self.getX()
nIndep = gen_data['numIndep']
dH_mean, dH_stdev = dH[transfer]['mean'], dH[transfer]['stdev']
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeCSV([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
def SvX(self):
'''
this is a special case of SvC, where we plot P as opposed to C
and the boxFrom might not be the same for each molecule
(ex: in the case of IG or kH adsorption)
:param P: Pressure of x axis (note: not pressure data)
'''
if (0 in self.indep) and (len(self.indep) == 1): raise NotImplemented
rho = self.rho[self.feed][self.run]
K = self.K[self.feed][self.run]
if 'P-box' in self.xlabel[0]:
P = self.P[self.feed][self.run]
X = self.getX()
file_description = '%s S(%s) %s dS' % (
self.xlabel[0], self.units, self.xlabel[1])
gen_data = self.gen_data[self.feed][self.run][self.feed]
nIndep = gen_data['numIndep']
for mol_pair in K['box1']:
K_to = K['box1'][mol_pair]
mol1, mol2 = map(int, mol_pair.split('/'))
file_name = 'S_%s-vs-%s.dat' % (mol_pair, self.xlabel[0])
if (('P' in self.xlabel[0]) or ('C' in self.xlabel[0])):
if 'P-box' in self.xlabel[0]:
vapor_box_a = self.findVapBox(rho, '%i' % mol1)
vapor_box_b = self.findVapBox(rho, '%i' % mol2)
pa, pa_stdev = P[vapor_box_a]['mean'], P[vapor_box_a][
'stdev']
pb, pb_stdev = P[vapor_box_b]['mean'], P[vapor_box_b][
'stdev']
K_from = {
'mean': pa / pb,
'stdev': eProp_division(pa, pa_stdev, pb, pb_stdev)
}
elif 'P' in self.xlabel[0]:
vapor_box = self.findVapBox(rho, '%i' % mol1)
K_from = K[vapor_box][mol_pair]
elif 'C' in self.xlabel[0]:
K_from = K['box2'][mol_pair]
S_mean = K_to['mean'] / K_from['mean']
S_stdev = eProp_division(K_to['mean'], K_to['stdev'],
K_from['mean'], K_from['stdev'])
writeCSV([X['mean']], [S_mean],
[calc95conf(X['stdev'], nIndep)],
[calc95conf(S_stdev, nIndep)], [self.feed], file_name,
file_description)
elif 'kH' in self.xlabel[0]:
if mol_pair == '%s/1' % self.mol:
K_to['95conf'] = calc95conf(K_to['stdev'], nIndep)
MW_W = gen_data['molecular weight']['1']
MW_D = gen_data['molecular weight'][self.mol]
S_mean = (K_to['mean'] *
(self.density[0] / X['mean'] - 1) * MW_D / MW_W)
w = X['mean'] / self.density[0]
S_long = K_to['mean'] / ((w / MW_D) / ((1 - w) / MW_W))
dS_dKto = (self.density[0] / X['mean'] - 1) * MW_D / MW_W
dS_drho = K_to['mean'] / X['mean'] * MW_D / MW_W
dS_dC = -K_to['mean'] * self.density[0] / math.pow(
X['mean'], 2) * MW_D / MW_W
S_95conf = math.sqrt(
math.pow(dS_dKto * K_to['95conf'], 2) +
math.pow(dS_drho * self.density[1], 2) +
math.pow(dS_dC * X['95conf'], 2))
writeCSV([X['mean']], [S_mean], [X['95conf']], [S_95conf],
[self.feed], file_name, file_description)
elif self.mol == '1':
K = 1 / K_to['mean']
dK = K * K_to['stdev'] / K_to['mean']
K_to = {'stdev': dK, 'mean': K}
K_to['95conf'] = calc95conf(K_to['stdev'], nIndep)
MW_W = gen_data['molecular weight']['2']
MW_D = gen_data['molecular weight'][self.mol]
S_mean = (K_to['mean'] *
(self.density[0] / X['mean'] - 1) * MW_D / MW_W)
w = X['mean'] / self.density[0]
S_long = K_to['mean'] / ((w / MW_D) / ((1 - w) / MW_W))
dS_dKto = (self.density[0] / X['mean'] - 1) * MW_D / MW_W
dS_drho = K_to['mean'] / X['mean'] * MW_D / MW_W
dS_dC = -K_to['mean'] * self.density[0] / math.pow(
X['mean'], 2) * MW_D / MW_W
S_95conf = math.sqrt(
math.pow(dS_dKto * K_to['95conf'], 2) +
math.pow(dS_drho * self.density[1], 2) +
math.pow(dS_dC * X['95conf'], 2))
writeCSV([X['mean']], [S_mean], [X['95conf']], [S_95conf],
[self.feed], file_name, file_description)
else:
print('mol pair', mol_pair,
'will not be considered for selectivity')
else:
print(self.xlabel, 'not considered')
def QvX(self):
'''
:var X: either solution concentration (g/mL) or pressure (kPa)
'''
assert self.units, 'Units must be defined for isotherm'
N = self.N[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run][self.feed]
file_description = '%s Q(%s) %s dQ' % (
self.xlabel[0], self.units, self.xlabel[1])
X = self.getX()
nIndep = gen_data['numIndep']
mols_adsorbed = self.getMolAds(N)
if (self.film == True):
rho = self.rho[self.feed][self.run]
zeolite_mass_g = gen_data['zeolite']['mass (g)'] + extra_film_mass
else:
zeolite_mass_g = gen_data['zeolite']['mass (g)']
for mol in mols_adsorbed:
file_name = 'Qmol%s-%s-w%sin-zeo-vs-%s.dat' % (
mol, self.units, ''.join(mols_adsorbed),
self.xlabel[0][:self.xlabel[0].find('(')])
if (self.film == True):
# subtract the no. of molecules in vapor space
vapor_box = self.findVapBox(rho, mol)
numInVap = rho[mol][vapor_box]['mean'] * film_vapor_volume
if self.units == 'molec/uc':
qfactor = 1 / gen_data['zeolite']['unit cells']
elif self.units == 'g/g':
qfactor = ((gen_data['molecular weight'][mol] / N_av) /
zeolite_mass_g)
elif self.units == 'mol/kg':
if self.film == True:
qfactor = (1 / N_av) / (zeolite_mass_g / 1000.)
else:
qfactor = gen_data['zeolite'][' mol/kg / 1 mlcl adsorbed']
if (0 in self.indep) and (len(self.indep) == 1):
if not self.film:
Q_vals = [i * qfactor for i in N[mol]['box1']['raw']]
Q_stdev = [
N[mol]['box1']['stdev'] * qfactor for i in Q_vals
]
else:
raise NotImplemented
writeCSV(
X['raw'], Q_vals, None, None,
['%s/%i' % (self.feed, j) for j in range(1, nIndep + 1)],
file_name, file_description)
else:
if not self.film:
Q_mean, Q_stdev = (N[mol]['box1']['mean'] * qfactor,
N[mol]['box1']['stdev'] * qfactor)
else:
Q_mean, Q_stdev = ((N[mol]['box1']['mean'] - numInVap) *
qfactor,
(N[mol]['box1']['stdev'] - numInVap) *
qfactor)
if '95conf' in X.keys():
dX = X['95conf']
else:
dX = calc95conf(X['stdev'], nIndep)
writeCSV([X['mean']], [Q_mean], [dX],
[calc95conf(Q_stdev, nIndep)], [self.feed], file_name,
file_description)
