Getting NaN when summing values in list with a for loop python-CodePudding

I am trying to obtain this sum:

But I have been having issues with the second term.

This is my code so far:

hbar = 1.05457e-34
kB_si = 1.380649e-23
T = 3500
path = 'C:\\Users\\valit\\'  #path to file
file = 'data_175_phonopy_.dat'


k,f = np.loadtxt(path  file, unpack=True)

f = f//1e-12 #to convert THz to Hz
# print(f)

nondeg = []
for i in f:
    if i not in nondeg:
        nondeg.append(i)

svib = 0
for i in range(len(nondeg)):
    svib = svib   (-kB_si * (math.exp((-hbar * nondeg[i])/(kB_si * T))) - (1/T) * hbar * nondeg[i] / (math.exp((hbar * nondeg[i])/(kB_si * T)) - 1)) #nan

print(svib)

When I print svib I get Nan with the following message:

nan
C:\Users\valit\svib_modes.py:45: RuntimeWarning: invalid value encountered in double_scalars
  svib =  svib - ((1/T) * hbar * nondeg[i] / (math.exp((hbar * nondeg[i])/(kB_si * T)) - 1))

I know the issue is the second term because I added the two terms separately, and the first one gives me a really small number. Do you have any suggestions on how to get rid of the NaN? I apologize if my question is really simple, but I have been stuck for a while and could not find a way to solve it.

Thank y'all in advance.

CodePudding user response：

There are likely values in your file that are not numbers and performing arithmatic operations on nan result in nan. i.e. nan * 3 == nan and nan 3 == nan.

If you just want to ignore the nan values in your file, and only operate on the numbers, you could just filter them out:

f = f[~numpy.isnan(f)]

Just make sure you do want to ignore the nan values and they're not there due to some problem you cannot safely ignore.

CodePudding user response：

There are several causes for this error, as stated in 'invalid value encountered in double_scalars' warning, possibly numpy. So it is very difficult to help you without the data.

However, I would recommend you to investigate if a division-by-zero is taking place, because it seems to be a common cause for this error.

Also, you're calculating a very long expression in one shot. I should say this is a very bad practice.

Instead, split your expression in smaller parts and calculate it step by step, doing the required validations before each step.

E.g, instead of:

x = a / b   c * d / e

it would be more rational to do something like:

if (b == 0):
  # raise error, or do something about it

x = a / b

if (e == 0):
  # raise error, or do something about it

x  = c * d / e