[MMTK] modes to numpy arrays

Ramon Crehuet rcrehuet at gmail.com
Mon Sep 5 09:49:42 UTC 2011


Dear Konrad,
Thanks for your help. I finally used numpy.asarray() as it is a clearer
representation of the modes. By the way, is there any example that projects
a trajectory onto the normal modes? I think it is simple to code but I was a
bit worried about performance. That's why I am asking if there is already
something implemented.
Cheers,
Ramon


2011/9/1 Konrad Hinsen <research at khinsen.fastmail.net>

> On 31 août 11, at 11:44, Ramon Crehuet wrote:
>
>  I would like to convert a NormalModes object into a numpy array. I tried:
>> modes = NormalModes(universe)
>> m_numpy = modes.array
>> and
>> m2_numpy = numpy.asarray(modes)
>> which do not give the same... (though it gives arrays with the same shape,
>> so they are not simple a transposition).
>> Curiously, modes[0].array and modes.array[0] are also different, and in
>> particular:
>> np.all(modes[0].array==m2_**numpy[0]) is True. So m2_numpy seems to
>> contain as vectors, each mode. By then, what is modes.array...?
>>
>
>
> It's an array that contains the normal modes vectors in some way, the
> details depending on how the modes were obtained (i.e.
> vibrational/energetic/**brownian, using a subspace or not, using a sparse
> representation or not, ...). In fact, it is the array containing the result
> from the last LAPACK call made in the normal mode calculation.
>
> If you want to use that array directly (which I don't really recommend),
> the best guide to its interpretation is the code that extracts individual
> modes in MMTK. For a VibrationalModes object, those are:
>
>    # mode vector in mass-weighted coordinates
>
>    def rawMode(self, item):
>        index = self.sort_index[item]
>        f = self.frequencies[index]
>        if self.imaginary[index]:
>            f = f*1.j
>        return VibrationalMode(self.universe, item, f, self.array[index])
>
>    # mode vector in Cartesian coordinates scaled by a thermal amplitude
>
>    def __getitem__(self, item):
>        index = self.sort_index[item]
>        f = self.frequencies[index]
>        if self.imaginary[index]:
>            f = f*1.j
>        if self.temperature is None or item < 6:
>            amplitude = 1.
>        else:
>            amplitude = N.sqrt(2.*self.temperature***Units.k_B/Units.amu) /
> \
>                        (2.*N.pi*f)
>        return VibrationalMode(self.universe, item, f,
>                               amplitude*self.array[index]/**self.weights)
>
> This shows that you need at the very least modes.array AND modes.sort_index
> to extract any useful information from that array.
>
> numpy.asarray() converts any sequence-like data into an array. It's similar
> to
>
>   numpy.array([m for m in modes])
>
> meaning that it ends up calling modes.__getitem__, which applies mass
> weighting and a thermal amplitude. It also sorts the modes by eigenvalue.
>
> Konrad.
> --
> ------------------------------**------------------------------**---------
> Konrad Hinsen
> Centre de Biophysique Moléculaire, CNRS Orléans
> Synchrotron Soleil - Division Expériences
> Saint Aubin - BP 48
> 91192 Gif sur Yvette Cedex, France
> Tel. +33-1 69 35 97 15
> E-Mail: research at  khinsen dot fastmail dot net
> ------------------------------**------------------------------**---------
>
>
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