On 30 November 2010 18:21, Edward d'Auvergne <
edward@xxxxxxxxxxxxx> wrote:
> Hi,
>
> I'll have to look at this patch later. The Gna! website
> (
http://gna.org) looks like it has been hacked, so I can't reach the
> task to download the patch :S Hopefully I can have it applied
> tomorrow, but the next 2 days will be almost impossible for me due to
> a day long meeting.
>
> Cheers,
>
> Edward
>
>
>
> On 29 November 2010 23:28, Pavel Kaderavek <
pavel.kaderavek@xxxxxxxxx> wrote:
>> This change is related to the task #6397 (
https://gna.org/task/?6397)
>>
>> kada _at_ chemi _dot_ muni _dot_ cz
>>
>>
https://mail.gna.org/public/relax-devel/2010-11/msg00001.html
>>
https://gna.org/task/download.php?file_id=11449
>>
>> This patch includes change in func_mf, func_local_tm, func_diff, func_all,
>> dfunc_mf, dfunc_local_tm, dfunc_diff, dfunc_all, d2func_mf, d2func_local_tm,
>> d2func_diff, d2func_all functions of class Mf in a file maths_fns/mf.py.
>> Functions were modified in order to handle data for more interactions.
>>
>> On 27 November 2010 09:25, Edward d'Auvergne <
edward@xxxxxxxxxxxxx> wrote:
>>>
>>> Hi,
>>>
>>> First make a backup copy just in case, then simply perform an 'svn up'
>>> and then 'svn diff'. This should work without clashes. If there is a
>>> clash, this is a normal part of software development. This really
>>> shouldn't be necessary. But if you need to resolve a clash, you need
>>> to edit the file and find the '<<<<<', '=====', and '>>>>>' marks.
>>> This separates code from the old file and the new file for you to
>>> manually edit and merge. If it's too confusing, just ask again.
>>>
>>> Cheers,
>>>
>>> Edward
>>>
>>>
>>> On 25 November 2010 19:25, Pavel Kaderavek <
pavel.kaderavek@xxxxxxxxx>
>>> wrote:
>>> > Hi,
>>> >
>>> > We prepared another set of changes according to discussion in:
>>> >
https://mail.gna.org/public/relax-devel/2010-11/msg00001.html
>>> > and previous.
>>> >
>>> > Normally, we use command "svn diff" to create a patch by comparing new
>>> > code
>>> > and code of our branch in the repository. As the current changes are
>>> > applied
>>> > on the already patched version of the code (not present in the current
>>> > repository revision of our branch obtained by "svn up"), we would like
>>> > to
>>> > ask you how the patch should be created.
>>> >
>>> > Regards,
>>> > Pavel
>>> >
>>> >
>>> > On 15 November 2010 19:21, Edward d'Auvergne <
edward@xxxxxxxxxxxxx>
>>> > wrote:
>>> >>
>>> >> Hi,
>>> >>
>>> >> I'm now back from a few weeks holidays. This is correct, a double
>>> >> looping will be required. I think this will still be efficient as the
>>> >> "for k in xrange(self.num_interactions[0])" loops are not very
>>> >> expensive. The alternative is to bring the "for j in
>>> >> xrange(data.total_num_params):" loop, but this would duplicate
>>> >> calculations and hence be even more expensive. This will also be
>>> >> required in the d2func_* methods as well.
>>> >>
>>> >> On a different note, as the code is becoming more complex, I would
>>> >> recommend for a future patch that "data = "" so that we
>>> >> always use "self.data[0][k].dri_prime[j]" for each element rather than
>>> >> "data..dri_prime[j]". This will help with debugging in the future as
>>> >> we could end up mixing the self.data elements.
>>> >>
>>> >> Also for the Rex interaction, there are plans for the future to allow
>>> >> for it to be non-quadratic for situations closer to slow exchange or
>>> >> intermediate. For slow exchange the interaction is then linear with
>>> >> field strength, and the value ranges from linear (alpha=1) to
>>> >> quadratic (alpha=2). So the alpha value between 1 and 2 might become
>>> >> an optimisable parameter and hence this interaction type will become
>>> >> more complex and require its own code paths. So if this branch
>>> >> separates out the Rex interaction, this would be of benefit to the
>>> >> rest of relax. Though the separation might be essential for the
>>> >> powerful code restructuring currently anyway.
>>> >>
>>> >> Cheers,
>>> >>
>>> >> Edward
>>> >>
>>> >>
>>> >>
>>> >>
>>> >> On 27 October 2010 20:45, Pavel Kaderavek <
pavel.kaderavek@xxxxxxxxx>
>>> >> wrote:
>>> >> > Hi,
>>> >> > sorry for a late response. Your suggestions seem reasonable. I would
>>> >> > add
>>> >> > just a two comments.
>>> >> > 1) We should keep as before not only ri_prime but probably also chi2,
>>> >> > dchi2
>>> >> > and d2chi2 as well.
>>> >> > .
>>> >> > 2)The consideration of Rex as an additional interaction is a one of
>>> >> > the
>>> >> > suitable approaches and it fits the general idea. We have to consider
>>> >> > that
>>> >> > it requires to add new interaction into the list of the interactions
>>> >> > (
>>> >> > __init__ function in class Mf, file maths_fns/mf.py).
>>> >> > It might be done just within the __init__ function (class Mf, file
>>> >> > maths_fns/mf.py). It will be based on the presence of Rex term within
>>> >> > the
>>> >> > loaded variable param_types. The other possibility is to do it before
>>> >> > calling this __init__ function (number of interactions is one of its
>>> >> > arguments).
>>> >> >
>>> >> > Then I address to discussion one additional problem related to the
>>> >> > patch
>>> >> > in
>>> >> > the preparation. Within the functions related to the derivations:
>>> >> > dfunc_mf,
>>> >> > dfunc_local_tm, dfunc_all, dfunc_diff (class Mf, maths_fns/mf.py)
>>> >> > there
>>> >> > is a
>>> >> > small complication. It will be illustrated using "dfunc_mf" function
>>> >> > as
>>> >> > an
>>> >> > example. The original code is following:
>>> >> >
>>> >> > data = "">
>>> >> >
>>> >> > # Calculate the spectral density gradient components.
>>> >> > if data.calc_djw_comps:
>>> >> > data.calc_djw_comps(data, params)
>>> >> >
>>> >> > # Diffusion tensor correlation times.
>>> >> > self.diff_data.calc_dti(data, self.diff_data)
>>> >> >
>>> >> > # Loop over the gradient.
>>> >> > for j in xrange(data.total_num_params):
>>> >> > # Calculate the spectral density gradients.
>>> >> > if data.calc_djw[j]:
>>> >> > data.djw = data.calc_djw[j](data, params, j)
>>> >> > else:
>>> >> > data.djw = data.djw * 0.0
>>> >> >
>>> >> > # Calculate the relaxation gradient components.
>>> >> > data.create_dri_comps(data, params)
>>> >> >
>>> >> > # Calculate the R1, R2, and sigma_noe gradients.
>>> >> > data.dri_prime[j] = data.create_dri_prime[j](data)
>>> >> >
>>> >> > # Loop over the relaxation values and modify the NOE
>>> >> > gradients.
>>> >> > data.dri[j] = data.dri_prime[j]
>>> >> > for m in xrange(data.num_ri):
>>> >> > if data.create_dri[m]:
>>> >> > data.create_dri[m](data, m, data.remap_table[m],
>>> >> > data.get_dr1, params, j)
>>> >> >
>>> >> > # Calculate the chi-squared gradient.
>>> >> > data.dchi2[j] = dchi2_element(data.relax_data, data.ri,
>>> >> > data.dri[j], data.errors)
>>> >> >
>>> >> > If the loop over interactions is incorporated, it is necessary to do
>>> >> > it
>>> >> > before "data.calc_djw_comps" is calculated. However then we get into
>>> >> > the
>>> >> > conflict with calculation of "modification of NOE gradients" and also
>>> >> > calculation of "dchi2". These quantities can be calculated only when
>>> >> > contributions from all interactions has been already evaluated (it is
>>> >> > similar to already discussed ri_prime). In this case it is
>>> >> > complicated
>>> >> > by
>>> >> > the presence of loop over fitted parameters. The possible solution
>>> >> > would
>>> >> > be
>>> >> > to make the loop over the interactions the inner one. However this
>>> >> > seems
>>> >> > to
>>> >> > require repeating the loop over interactions twice within the code:
>>> >> >
>>> >> > data = "">
>>> >> >
>>> >> > # Loop over the interactions
>>> >> > for k in xrange(self.num_interactions[0]):
>>> >> > # Calculate the spectral density gradient components.
>>> >> > if data[k].calc_djw_comps:
>>> >> > data[k].calc_djw_comps(data[k], params)
>>> >> >
>>> >> > # Diffusion tensor correlation times.
>>> >> > self.diff_data.calc_dti(data[k], self.diff_data)
>>> >> >
>>> >> > # Loop over the gradient.
>>> >> > for j in xrange(data.total_num_params):
>>> >> > # Loop over the interactions
>>> >> > for k in xrange(self.num_interactions[0])
>>> >> > # Calculate the spectral density gradients.
>>> >> > if data[k].calc_djw[j]:
>>> >> > data[k].djw = data[k].calc_djw[j](data[k],
>>> >> > params,
>>> >> > j)
>>> >> > else:
>>> >> > data[k].djw = data[k].djw * 0.0
>>> >> >
>>> >> > # Calculate the relaxation gradient components.
>>> >> > data[k].create_dri_comps(data[k], params)
>>> >> >
>>> >> > # Calculate the R1, R2, and sigma_noe gradients.
>>> >> > data[k].dri_prime[j] =
>>> >> > data[k].create_dri_prime[j](data[k]) #
>>> >> > later
>>> >> > data[k].dri_prime[j] will be replaced by data.dri_prime[j]
>>> >> >
>>> >> > # but you suggest
>>> >> > not
>>> >> > to
>>> >> > include both changes into the following patch together
>>> >> >
>>> >> >
>>> >> > # Loop over the relaxation values and modify the NOE
>>> >> > gradients.
>>> >> > data.dri[j] = data.dri_prime[j]
>>> >> > for m in xrange(data.num_ri):
>>> >> > if data.create_dri[m]:
>>> >> > data.create_dri[m](data, m, data.remap_table[m],
>>> >> > data.get_dr1, params, j)
>>> >> >
>>> >> > # Calculate the chi-squared gradient.
>>> >> > data.dchi2[j] = dchi2_element(data.relax_data,
>>> >> > data.ri,
>>> >> > data.dri[j], data.errors)
>>> >> >
>>> >> > Additionally I would notify that variable "total_num_params" needs to
>>> >> > be
>>> >> > kept at the position self.data[0] (similar to your suggestion in your
>>> >> > last
>>> >> > mail, concerning ri_prime)
>>> >> > What do you think about this?
>>> >> > Regards
>>> >> > Pavel
>>> >> >
>>> >> > On 22 October 2010 19:46, Edward d'Auvergne <
edward@xxxxxxxxxxxxx>
>>> >> > wrote:
>>> >> >>
>>> >> >> Hi,
>>> >> >>
>>> >> >> This is a good idea. First I would suggest putting this into 2
>>> >> >> patches, as this is easier to check and apply. Don't worry about
>>> >> >> breaking the code at this point - it is in your own special branch
>>> >> >> so
>>> >> >> as long as it works in the end, you can smash it into a million
>>> >> >> pieces
>>> >> >> and put it back together again if you like. Commits to the
>>> >> >> repository
>>> >> >> are better when they are many small ones, as they can be more easily
>>> >> >> managed. For example if something is found to be designed not
>>> >> >> ideally, or there is a fatal bug, that patch/commit can be reverted
>>> >> >> and then new code can be worked on. And small patches make it much
>>> >> >> easier for the other relax developers to read and catch potential
>>> >> >> hidden bugs or design issues.
>>> >> >>
>>> >> >> This is an intriguing problem, as the data flow hits a fork here.
>>> >> >> ri_prime is the correct target for the merging of the data from all
>>> >> >> the interactions, as this needs to occur before the calculation of
>>> >> >> the
>>> >> >> NOE using sigma_noe and the R1. The relaxation rates R1, R2, and
>>> >> >> sigma_noe add. However the NOE does not. I just thought I'd
>>> >> >> explain
>>> >> >> the logic for others to follow ;)
>>> >> >>
>>> >> >> I would suggest we store ri_prime somewhere else. What I can do is
>>> >> >> to
>>> >> >> apply a patch for the first change to accommodate for the multiple
>>> >> >> relaxation interactions. Then I could make a change myself,
>>> >> >> creating
>>> >> >> a special Python object for 'data[i]'. We can store the ri_prime
>>> >> >> data
>>> >> >> this special object. Essentially, it will be like the current code
>>> >> >> base. We could have specific interaction data in say:
>>> >> >>
>>> >> >> self.data[10][0].jw (or self.data[0].jw if data = "">
>>> >> >>
>>> >> >> This is new. But as before we could have:
>>> >> >>
>>> >> >> self.data[10].ri_prime (or data.ri_prime if data = "">
>>> >> >>
>>> >> >> So the forking can all be managed within the self.data[i] data
>>> >> >> structures. What do you think? Also, we will have to work out how
>>> >> >> to
>>> >> >> modify or replace func_ri_prime and func_ri_prime_rex in the
>>> >> >> maths_fns.ri_prime module. This is where the merging of data
>>> >> >> streams
>>> >> >> currently occurs. Maybe Rex needs to be considered as its own
>>> >> >> interaction, as this is added to produce ri_prime?
>>> >> >>
>>> >> >> Regards,
>>> >> >>
>>> >> >> Edward
>>> >> >>
>>> >> >>
>>> >> >> P. S. I just talked to Kathleen Hall and she seemed very interested
>>> >> >> in what you are doing here!
>>> >> >>
>>> >> >>
>>> >> >>
>>> >> >> On 22 October 2010 18:26, Pavel Kaderavek
>>> >> >> <
pavel.kaderavek@xxxxxxxxx>
>>> >> >> wrote:
>>> >> >> > Hi,
>>> >> >> > I am continuing in the discussion started in my post
>>> >> >> >
https://mail.gna.org/public/relax-devel/2010-09/msg00020.html
>>> >> >> > It covers changes of functions func_mf.py, func_local_tm ,
>>> >> >> > func_diff,
>>> >> >> > func_all and their equivalents for a first and second derivatives
>>> >> >> > (class
>>> >> >> > Mf,
>>> >> >> > file maths_fns/mf.py).
>>> >> >> >
>>> >> >> > I would like to include into next patch also treatment of the
>>> >> >> > fact,
>>> >> >> > that
>>> >> >> > it
>>> >> >> > is necessary to sum together contributions of all interactions. It
>>> >> >> > seems
>>> >> >> > to
>>> >> >> > me that the most suitable way is to do that by the modification
>>> >> >> > just
>>> >> >> > revised
>>> >> >> > functions (func_mf.py, func_local_tm ...)
>>> >> >> > I would suggest to initialize ri_prime before loop over
>>> >> >> > interactions
>>> >> >> > and
>>> >> >> > then step by step add the contributions into the ri_prime:
>>> >> >> >
>>> >> >> > data = "" # the
>>> >> >> > cases
>>> >> >> > when `i` is replaced by `0` were discussed in your last mail
>>> >> >> > ri_prime=0
>>> >> >> >
>>> >> >> >
>>> >> >> > for j in xrange(self.num_interactions[i]):
>>> >> >> >
>>> >> >> > ...
>>> >> >> > ...
>>> >> >> >
>>> >> >> > # Calculate the R1, R2, and sigma_noe values.
>>> >> >> > ri_prime = ri_prime +
>>> >> >> > data[j].create_ri_prime(data[j])
>>> >> >> >
>>> >> >> > data[0].ri_prime = ri_prime
>>> >> >> >
>>> >> >> >
>>> >> >> > When the loop over interactions is finished the accumulated
>>> >> >> > relaxation
>>> >> >> > rate
>>> >> >> > is copied into the data storage of the first interaction. Then it
>>> >> >> > is
>>> >> >> > possible to call functions, where total ri_prime is needed:
>>> >> >> >
>>> >> >> > # Calculate the NOE values.
>>> >> >> > data[0].ri = data[0].ri_prime * 1.0
>>> >> >> > for m in xrange(data[0].num_ri):
>>> >> >> > if data[0].create_ri[m]:
>>> >> >> > data[0].create_ri[m](data[0], m,
>>> >> >> > data[0].remap_table[m],
>>> >> >> > data[0].get_r1, params)
>>> >> >> >
>>> >> >> > # Calculate the chi-squared value.
>>> >> >> > data[0].chi2 = chi2(data[0].relax_data, data[0].ri,
>>> >> >> > data[0].errors)
>>> >> >> >
>>> >> >> > Regards,
>>> >> >> > Pavel
>>> >> >> >
>>> >> >> > On 19 October 2010 13:49, Edward d'Auvergne <
edward@xxxxxxxxxxxxx>
>>> >> >> > wrote:
>>> >> >> >>
>>> >> >> >> Hi,
>>> >> >> >>
>>> >> >> >> Sorry for the delay, I just came back from a 2 week holiday.
>>> >> >> >> This
>>> >> >> >> is
>>> >> >> >> correct, the func_mf, func_local_tm, etc. methods are working on
>>> >> >> >> a
>>> >> >> >> single spin. This is stored in self.data[0]. The other
>>> >> >> >> functions
>>> >> >> >> work on multiple spin data located in self.data[0], self.data[1],
>>> >> >> >> etc.
>>> >> >> >>
>>> >> >> >> Regards,
>>> >> >> >>
>>> >> >> >> Edward
>>> >> >> >>
>>> >> >> >>
>>> >> >> >>
>>> >> >> >> On 14 October 2010 19:38, Pavel Kaderavek
>>> >> >> >> <
pavel.kaderavek@xxxxxxxxx>
>>> >> >> >> wrote:
>>> >> >> >> > Hi,
>>> >> >> >> >
>>> >> >> >> > I would like to announce a small clarification of my previous
>>> >> >> >> > mail
>>> >> >> >> > about
>>> >> >> >> > changes in functions func_mf, func_local_tm, func_diff,
>>> >> >> >> > func_all,
>>> >> >> >> > and
>>> >> >> >> > their
>>> >> >> >> > derivatives (class Mf, file maths_fns/mf.py). Loop suggested in
>>> >> >> >> > my
>>> >> >> >> > last
>>> >> >> >> > post:
>>> >> >> >> >
>>> >> >> >> >
https://mail.gna.org/public/relax-devel/2010-09/msg00020.html
>>> >> >> >> >
>>> >> >> >> > is valid just for the functions func_diff, func_all, and their
>>> >> >> >> > equivalents
>>> >> >> >> > for a first and second derivatives.
>>> >> >> >> > While for the functions func_mf, func_local_tm, and
>>> >> >> >> > corresponding
>>> >> >> >> > derivatives the index of self.num_interactions should be set to
>>> >> >> >> > `0`
>>> >> >> >> > instead
>>> >> >> >> > of index `i`
>>> >> >> >> >
>>> >> >> >> > for j in xrange(self.num_interactions[0]):
>>> >> >> >> >
>>> >> >> >> > (The rest of the loop remains the same)
>>> >> >> >> > That comes from the fact that these functions (func_mf,
>>> >> >> >> > func_local_tm,
>>> >> >> >> > ...
>>> >> >> >> > ) are called for each spin separately. As it is indicated by
>>> >> >> >> > the
>>> >> >> >> > preceding
>>> >> >> >> > statement:
>>> >> >> >> >
>>> >> >> >> > data = "">
>>> >> >> >> >
>>> >> >> >> > Regards,
>>> >> >> >> > Pavel
>>> >> >> >> >
>>> >> >> >> > On 29 September 2010 10:53, Edward d'Auvergne
>>> >> >> >> > <
edward@xxxxxxxxxxxxx>
>>> >> >> >> > wrote:
>>> >> >> >> >>
>>> >> >> >> >> Hi,
>>> >> >> >> >>
>>> >> >> >> >> This is the perfect approach. It will abstract the
>>> >> >> >> >> calculations
>>> >> >> >> >> so
>>> >> >> >> >> that we will not need to touch many of maths_fns modules.
>>> >> >> >> >> With
>>> >> >> >> >> this
>>> >> >> >> >> code in place, I would aim at then making the test suite pass
>>> >> >> >> >> again
>>> >> >> >> >> by
>>> >> >> >> >> having the correct data structures pass into maths_fns.mf.
>>> >> >> >> >> The
>>> >> >> >> >> last
>>> >> >> >> >> step would be to input CSA tensors and the multi-dipole
>>> >> >> >> >> interactions
>>> >> >> >> >> via user functions. If you make a patch for all of the
>>> >> >> >> >> func_*(),
>>> >> >> >> >> dfunc_*(), and d2func_*() methods, I can check and apply it
>>> >> >> >> >> quickly.
>>> >> >> >> >>
>>> >> >> >> >> Regards,
>>> >> >> >> >>
>>> >> >> >> >> Edward
>>> >> >> >> >>
>>> >> >> >> >>
>>> >> >> >> >> On 28 September 2010 12:07, Pavel Kaderavek
>>> >> >> >> >> <
pavel.kaderavek@xxxxxxxxx>
>>> >> >> >> >> wrote:
>>> >> >> >> >> > Hi,
>>> >> >> >> >> > we were thinking about next necessary changes in the CST
>>> >> >> >> >> > branch.
>>> >> >> >> >> >
>>> >> >> >> >> > Now we need to break through the problem, which implies the
>>> >> >> >> >> > fact
>>> >> >> >> >> > we
>>> >> >> >> >> > split
>>> >> >> >> >> > the relaxation rate calculation into contributions of
>>> >> >> >> >> > individual
>>> >> >> >> >> > interactions. Each of them has its own data class to store
>>> >> >> >> >> > its
>>> >> >> >> >> > parameters
>>> >> >> >> >> > (so far called data[i][j], where the [i] was a spin index
>>> >> >> >> >> > and
>>> >> >> >> >> > [j]
>>> >> >> >> >> > was
>>> >> >> >> >> > the
>>> >> >> >> >> > interaction index).
>>> >> >> >> >> >
>>> >> >> >> >> > It seems to us, that it the best way to deal with it is to
>>> >> >> >> >> > edit
>>> >> >> >> >> > functions:
>>> >> >> >> >> > func_mf, func_local_tm , func_diff, func_all and their
>>> >> >> >> >> > equivalents
>>> >> >> >> >> > for a
>>> >> >> >> >> > first and second derivatives (defined in mf.py file).
>>> >> >> >> >> >
>>> >> >> >> >> > Within these functions the calculations of direction
>>> >> >> >> >> > cosines,
>>> >> >> >> >> > diffusion
>>> >> >> >> >> > tensor weight calculations, components of the spectral
>>> >> >> >> >> > densities
>>> >> >> >> >> > and
>>> >> >> >> >> > so
>>> >> >> >> >> > on
>>> >> >> >> >> > are performed. All these must be calculated for each
>>> >> >> >> >> > interaction
>>> >> >> >> >> > separately,
>>> >> >> >> >> > because each interaction has its own data storage (which
>>> >> >> >> >> > replaced
>>> >> >> >> >> > previously
>>> >> >> >> >> > used one data class container for the whole IS spin system).
>>> >> >> >> >> >
>>> >> >> >> >> > Instead of:
>>> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >> > # Direction cosine calculations.
>>> >> >> >> >> > if self.diff_data.calc_di:
>>> >> >> >> >> > self.diff_data.calc_di(data, self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Diffusion tensor weight calculations.
>>> >> >> >> >> > self.diff_data.calc_ci(data, self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Diffusion tensor correlation times.
>>> >> >> >> >> > self.diff_data.calc_ti(data, self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Calculate the components of the spectral
>>> >> >> >> >> > densities.
>>> >> >> >> >> > if data.calc_jw_comps:
>>> >> >> >> >> > data.calc_jw_comps(data, params)
>>> >> >> >> >> >
>>> >> >> >> >> > # Calculate the R1, R2, and sigma_noe values.
>>> >> >> >> >> > data.ri_prime = data.create_ri_prime(data)
>>> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >> > we would suggest to introduce a loop over interacations
>>> >> >> >> >> > for j in xrange(self.num_interactions[i]):
>>> >> >> >> >> > # Direction cosine calculations.
>>> >> >> >> >> > if self.diff_data.calc_di:
>>> >> >> >> >> > self.diff_data.calc_di(data[j],
>>> >> >> >> >> > self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Diffusion tensor weight calculations.
>>> >> >> >> >> > self.diff_data.calc_ci(data[j], self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Diffusion tensor correlation times.
>>> >> >> >> >> > self.diff_data.calc_ti(data[j], self.diff_data)
>>> >> >> >> >> >
>>> >> >> >> >> > # Calculate the components of the spectral
>>> >> >> >> >> > densities.
>>> >> >> >> >> > if data.calc_jw_comps:
>>> >> >> >> >> > data.calc_jw_comps(data[j], params)
>>> >> >> >> >> >
>>> >> >> >> >> > # Calculate the R1, R2, and sigma_noe
>>> >> >> >> >> > components.
>>> >> >> >> >> > data.ri_prime = data.create_ri_prime(data[j])
>>> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >> > It must be accompanied in the next step by a change the
>>> >> >> >> >> > ri_prime
>>> >> >> >> >> > function so
>>> >> >> >> >> > that it just calculate only a product of specific
>>> >> >> >> >> > interaction
>>> >> >> >> >> > constant
>>> >> >> >> >> > and
>>> >> >> >> >> > corresponding linear combination of spectral densities.
>>> >> >> >> >> > While
>>> >> >> >> >> > the
>>> >> >> >> >> > final
>>> >> >> >> >> > sumation over all interactions should be done in a separate
>>> >> >> >> >> > step.
>>> >> >> >> >> >
>>> >> >> >> >> > Moreover it will be also necessary to distinguish within the
>>> >> >> >> >> > function
>>> >> >> >> >> > setup_equation the type of equation used for contribution of
>>> >> >> >> >> > individual
>>> >> >> >> >> > interactions according to their type.
>>> >> >> >> >> >
>>> >> >> >> >> > Best
>>> >> >> >> >> > Pavel
>>> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >> > On 10 September 2010 15:43, Edward d'Auvergne
>>> >> >> >> >> > <
edward@xxxxxxxxxxxxx>
>>> >> >> >> >> > wrote:
>>> >> >> >> >> >>
>>> >> >> >> >> >> Hi Pavel,
>>> >> >> >> >> >>
>>> >> >> >> >> >> I missed it in the patches, but there were tab characters
>>> >> >> >> >> >> '\t'
>>> >> >> >> >> >> causing
>>> >> >> >> >> >> problems. These are now fixed. relax requires that a tab
>>> >> >> >> >> >> is
>>> >> >> >> >> >> replaced
>>> >> >> >> >> >> by 4 spaces. I have also added you to the copyright
>>> >> >> >> >> >> notices
>>> >> >> >> >> >> (
http://svn.gna.org/viewcvs/relax?view=rev&revision=11543)
>>> >> >> >> >> >> of
>>> >> >> >> >> >> the
>>> >> >> >> >> >> files you have modified.
>>> >> >> >> >> >>
>>> >> >> >> >> >> Regards,
>>> >> >> >> >> >>
>>> >> >> >> >> >> Edward
>>> >> >> >> >> >>
>>> >> >> >> >> >> On 10 September 2010 15:36, Edward d'Auvergne
>>> >> >> >> >> >> <
edward@xxxxxxxxxxxxx>
>>> >> >> >> >> >> wrote:
>>> >> >> >> >> >> > Hi,
>>> >> >> >> >> >> >
>>> >> >> >> >> >> > I've carefully checked the patches and committed them
>>> >> >> >> >> >> > with
>>> >> >> >> >> >> > the
>>> >> >> >> >> >> > messages you wrote. Sorry again for the delays. It
>>> >> >> >> >> >> > should
>>> >> >> >> >> >> > be
>>> >> >> >> >> >> > faster
>>> >> >> >> >> >> > now that I am no longer in the tropical wilderness of far
>>> >> >> >> >> >> > north
>>> >> >> >> >> >> > Australia.
>>> >> >> >> >> >> >
>>> >> >> >> >> >> > Regards,
>>> >> >> >> >> >> >
>>> >> >> >> >> >> > Edward
>>> >> >> >> >> >> >
>>> >> >> >> >> >> >
>>> >> >> >> >> >> > On 6 September 2010 13:23, Edward d'Auvergne
>>> >> >> >> >> >> > <
edward@xxxxxxxxxxxxx>
>>> >> >> >> >> >> > wrote:
>>> >> >> >> >> >> >> Hi Pavel,
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >> Sorry for the delayed response. I was at the ICMRBS
>>> >> >> >> >> >> >> conference
>>> >> >> >> >> >> >> in
>>> >> >> >> >> >> >> Australia and then travelled through the tropical north
>>> >> >> >> >> >> >> end
>>> >> >> >> >> >> >> of
>>> >> >> >> >> >> >> Australia afterwards. I came back yesterday out of the
>>> >> >> >> >> >> >> remote
>>> >> >> >> >> >> >> wilderness and can soon start looking at this patches.
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >> Regards,
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >> Edward
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >> On 31 August 2010 18:00, Pavel Kaderavek
>>> >> >> >> >> >> >> <
pavel.kaderavek@xxxxxxxxx>
>>> >> >> >> >> >> >> wrote:
>>> >> >> >> >> >> >>> Hi,
>>> >> >> >> >> >> >>>
>>> >> >> >> >> >> >>> some time ago, we submitted two patches regarding CST
>>> >> >> >> >> >> >>> branch.
>>> >> >> >> >> >> >>> We
>>> >> >> >> >> >> >>> are
>>> >> >> >> >> >> >>> not
>>> >> >> >> >> >> >>> sure if we should wait for some additional comment from
>>> >> >> >> >> >> >>> your
>>> >> >> >> >> >> >>> side,
>>> >> >> >> >> >> >>> or
>>> >> >> >> >> >> >>> we can
>>> >> >> >> >> >> >>> continue with introducing further changes in the code.
>>> >> >> >> >> >> >>> Next step would be a splitting of the relaxation
>>> >> >> >> >> >> >>> equation
>>> >> >> >> >> >> >>> so
>>> >> >> >> >> >> >>> that
>>> >> >> >> >> >> >>> contribution to the relaxation due to the individual
>>> >> >> >> >> >> >>> types
>>> >> >> >> >> >> >>> of
>>> >> >> >> >> >> >>> interaction
>>> >> >> >> >> >> >>> (dipole-dipole, CSA) can be calculated separately.
>>> >> >> >> >> >> >>>
>>> >> >> >> >> >> >>>
>>> >> >> >> >> >> >>> Regars,
>>> >> >> >> >> >> >>>
>>> >> >> >> >> >> >>> Pavel, Petr
>>> >> >> >> >> >> >>>
>>> >> >> >> >> >> >>
>>> >> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >> >
>>> >> >> >> >
>>> >> >> >> >
>>> >> >> >
>>> >> >> >
>>> >> >
>>> >> >
>>> >
>>> >
>>
>>
>
Re: CST branch