Here in my code, I need to use quad to compute J-ij and Jp_ij as following:
import numpy as np
from scipy.integrate import quad
xData = {'xCa': np.array([0.08177462, 0.07454374, 0.06799069, 0.0612067 , 0.05375614,
0.04635545, 0.03826685, 0.03011176, 0.02174885, 0.01294261]), \
'xH': np.array([0., 0.00880058, 0.01676501, 0.02492618, 0.0339801 ,
0.04296084, 0.05264879, 0.06251044, 0.07260724, 0.08314678]), \
'xCl': np.array([0.08177462, 0.08334432, 0.08475571, 0.08613288, 0.08773624,
0.08931629, 0.09091563, 0.0926222 , 0.09435609, 0.09608939])}
Ax = 2.921
cations = {'Ca' : 2, 'H' : 1}
anions = {'Cl' : 1}
ionicDic = dict()
for dd in (cations, anions):
ionicDic.update(dd)
ionic_dic = {f'x{i}': ionicDic[i] for i in ionicDic}
arr1 = np.array(list(xData.values()))
arr2 = np.array([ionic_dic[k] for k in xData])
ionicArray = (np.sum(np.transpose(arr1) * arr2 ** 2, axis=1) / 2) ** 0.5
def xij(a, b):
x_ij = 6 * a * b * Ax * ionicArray
return x_ij
def J_ij(c):
int_fun = lambda t : (np.log(t) / (c * t / (np.log(t)))) * \
(1 - np.exp(c * t / (np.log(t))))
integral_part = quad(int_fun, 0, 1, limlst=1000)[0]
Jij = (c / 4.0) - 1 + integral_part
return Jij
def Jp_ij(d):
int_fun_p = lambda t: (t / (d * t / (np.log(t))) ** 2) * \
(1 - (1 - (d * t / (np.log(t)))) * np.exp(d * t np.log(t))))
integral_part_p = quad(int_fun_p, 0, 1, limlst=1000)[0]
Jpij = (1 / 4.0) + 1 + integral_part_p
return Jpij
AB = ['J_Ca_H', 'P', 'JP_Ca_H']
for k in AB:
if (k.split('_'))[0] == 'J':
i = (k.split('_'))[1]
j = (k.split('_'))[2]
n = list(xij(ionicDic[i], ionicDic[j]))
m = []
for num in n:
m.append(J_ij(num))
xData.update({f'J_{i}_{j}': m})
print(xData)
elif (k.split('_'))[0] == 'JP':
ip = (k.split('_'))[1]
jp = (k.split('_'))[2]
np = list(xij(ionicDic[ip], ionicDic[jp]))
m = []
for ii in np:
m.append(Jp_ij(ii))
xData.update({f'JP_{ip}_{jp}': mp})
else:
print(f'No higher order term for the {k} item to calculate!!')
continue
J_ij works well while the Jp_ij gives error:
>>> retval = _quad(func, a, b, args, full_output, epsabs, epsrel, limit
>>> return _quadpack._qagse(func,a,b,args,full_output,epsabs,epsrel,limit)
>>> int_fun_p = lambda t: (t / (d * t / (np.log(t))) ** 2) * (1 - (1 - (d * t / (np.log(t)))) * np.exp(d * t / (np.log(t))))
AttributeError: 'list' object has no attribute 'log'
I got totally mixed up because if I pass (Jp_ij(15.84)),as the first value that must be passed in it, it works but in for loop it raise an error. What should I do to fix error??
Here My problem was being careless with the Numpy name (np) as name of a list in for loop. Something kind of like Why does code like `str = str(...)` cause a TypeError, but only the second time? where str is passed as a name to a variable.
