Re: [cclib-devel] Numeric -> NumPy transition

[Karol L. <kar...@kn...>]

On Tuesday 15 May 2007 22:37, Adam Tenderholt wrote:
> The Mulliken and C-squared population analysis are broken with
> revision 624. I haven't really explored it other than noticing that
> the numbers are way off and that it looks like every aoresult for a
> given MO have the same number (~1).

I can't get bad results from the CSPA method, any way I go, with code before 
the NumPy->Numeric transition, using numpy or Numeric. Can you specify which 
parsed file breaks the method?

For example, in all the three following cases:
1) before transition
>>> cclib.method.cspa.__revision__
'$Revision: 549 $'
2) after transition, using Numeric
>>> cclib.method.cspa.__revision__
'$Revision: 616 $'
>>> cclib.method.cspa.numpy.__name__
'Numeric'
3) after transition, using NumPy
>>> cclib.method.cspa.__revision__
'$Revision: 616 $'
>>> cclib.method.cspa.numpy.__name__
'numpy'

I get the same output for basicGaussian03/dvb_sp.out:
>>> a = cclib.parser.ccopen("dvb_sp.out")
>>> a.parse()
[Gaussian dvb_sp.out INFO] Creating attribute atomnos[]
[Gaussian dvb_sp.out INFO] Creating attribute natom: 20
[Gaussian dvb_sp.out INFO] Creating attribute atomcoords[]
[Gaussian dvb_sp.out INFO] Creating attribute nbasis: 60
[Gaussian dvb_sp.out INFO] Creating attribute aooverlaps[x, y]
[Gaussian dvb_sp.out INFO] Creating attribute nmo: 60
[Gaussian dvb_sp.out INFO] Creating attribute scftargets[]
[Gaussian dvb_sp.out INFO] Creating attribute scfvalues
[Gaussian dvb_sp.out INFO] Creating attribute scfenergies[]
[Gaussian dvb_sp.out INFO] Creating attribute mosyms[[]]
[Gaussian dvb_sp.out INFO] Creating attribute homos[]
[Gaussian dvb_sp.out INFO] Creating attribute moenergies
[Gaussian dvb_sp.out INFO] Creating attributes aonames[], mocoeffs[]
[Gaussian dvb_sp.out INFO] Creating attribute coreelectrons[]
>>> b = cclib.method.cspa(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'module' object is not callable
>>> b = cclib.method.CSPA(a)
>>> b.calculate()
[CSPA Gaussian log file dvb_sp.out INFO] Creating attribute aoresults: 
array[3]
[CSPA Gaussian log file dvb_sp.out INFO] Saving partitioned results in 
fragresults: array[3]
[CSPA Gaussian log file dvb_sp.out INFO] Creating fragcharges: array[1]
True
>>> b.fragcharges
array([ 6.15511175,  6.17848707,  6.17201986,  6.15511175,  6.17848707,  
0.80749953,
             0.80896859,  0.80749953,  6.1965754 ,  6.20647677,  0.82826582,
             0.82550176,  0.82109346,  6.1965754 ,  0.82550176,  6.20647677,
             0.82826582,  0.82109346,  6.17201986,  0.80896859])

-- 
written by Karol Langner
Wed May 16 02:17:02 CEST 2007