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p(sigma) in VT-2005 #33

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@GYQ961

Dear Professor:
I can't really understand p(sigma) in the database VT-2005, which gives two columns data, the first column is an array from -0.025 to 0.025, but I can't really understand whether the second column is p(sigma).
If it is indeed psigma, I don't konw why calculate psigma by using the code"dd['p(sigma)']=dd['p(sigma)*A [A^2]']/dd['A']" in script
COSMO PurePython.ipynb. So I can't determine whether the second column data is p(sigma), that is sigma profile?
I have input compound 'METHANOL' in the code "def get_sigma_profile(name)", but its output showed p(sigma) calculated again was not an array, it showed 'NAN', because dd['p(sigma)*A [A^2]']/dd['A'], some numbers in dd['A'] are zero, it doesn't make sense mathematically. Why do we calculate ['p(sigma)*A [A^2]']/['A']?
The code is below, could you help me about this problem? Thank you!

def get_sigma_profile(name):
    df=pd.read_csv("profiles/VT2005/Sigma_Profile_Database_Index_v2.txt",sep='\t',engine='python')
    mask=df['Compound Name']==name
    assert(sum(mask)==1)
    index=int(df[mask]['Index No.'].iloc[0]) 
    V_COSMO = float(df[mask]['Vcosmo, A3'].iloc[0])
    with open('profiles/VT2005/Sigma_Profiles_v2/VT2005-'+'{0:04d}'.format(index)+'-PROF.txt') as fp:
        dd=pd.read_csv(fp,names=['sigma [e/A^2]','p(sigma)*A [A^2]'],sep='s+')
        dd['A'] = dd['p(sigma)*A [A^2]'].sum()
        dd['p(sigma)']=dd['p(sigma)*A [A^2]']/dd['A']
        return dd,V_COSMO
    
name='METHANOL'
psigma=get_sigma_profile(name)
print(psigma)

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