Yes.

That is because, that I before pre-calculated the "values" with a function
call.
The function call is now removed.

So there is a big difference between values and back_calc.

If I remember, all values are set to 2.0, errors 1.0.
Best
Troels


2014-06-18 17:29 GMT+02:00 Edward d'Auvergne <[email protected]>:

> Hi Troels,
>
> You have a chi-squared printout in all of your profiling scripts, but
> do you know why that value is so high in all scripts?
>
> Regards,
>
> Edward
>
>
>
> On 18 June 2014 17:27,  <[email protected]> wrote:
> > Author: tlinnet
> > Date: Wed Jun 18 17:27:54 2014
> > New Revision: 24110
> >
> > URL: http://svn.gna.org/viewcvs/relax?rev=24110&view=rev
> > Log:
> > Modified profiling script for MP05.
> >
> > Task #7807 (https://gna.org/task/index.php?7807): Speed-up of
> dispersion models for Clustered analysis.
> >
> > Modified:
> >
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_mp05.py
> >
> > Modified:
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_mp05.py
> > URL:
> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_mp05.py?rev=24110&r1=24109&r2=24110&view=diff
> >
> ==============================================================================
> > ---
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_mp05.py
>      (original)
> > +++
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_mp05.py
>      Wed Jun 18 17:27:54 2014
> > @@ -63,7 +63,7 @@
> >  def main():
> >      if True:
> >          # Nr of iterations.
> > -        nr_iter = 1000
> > +        nr_iter = 10
> >
> >          # Print statistics.
> >          verbose = True
> > @@ -523,11 +523,11 @@
> >          """
> >
> >          # Return chi2 value.
> > -        chi2 = self.model.func_DPL94(params)
> > +        chi2 = self.model.func_MP05(params)
> >          return chi2
> >
> >
> > -def single(num_spins=1, model=MODEL_DPL94, iter=None):
> > +def single(num_spins=1, model=MODEL_MP05, iter=None):
> >      """Calculate for a single spin.
> >
> >      @keyword num_spins:     Number of spins in the cluster.
> > @@ -541,7 +541,7 @@
> >      """
> >
> >      # Instantiate class
> > -    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, phi_ex=1.0,
> kex=5000.0, spins_params=['r2', 'phi_ex', 'kex'])
> > +    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, dw=1.0,
> pA=0.9, kex=5000.0, spins_params=['r2', 'dw', 'pA', 'kex'])
> >
> >      # Loop 100 times for each spin in the clustered analysis (to make
> the timing numbers equivalent).
> >      for spin_index in xrange(100):
> > @@ -551,7 +551,7 @@
> >      print("chi2 single:", chi2)
> >
> >
> > -def cluster(num_spins=100, model=MODEL_DPL94, iter=None):
> > +def cluster(num_spins=100, model=MODEL_MP05, iter=None):
> >      """Calculate for a number of clustered spins.
> >
> >      @keyword num_spins:     Number of spins in the cluster.
> > @@ -565,7 +565,7 @@
> >      """
> >
> >      # Instantiate class
> > -    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, phi_ex=1.0,
> kex=5000.0, spins_params=['r2', 'phi_ex', 'kex'])
> > +    C1 = Profile(num_spins=num_spins, model=model, r2=5.0, dw=1.0,
> pA=0.9, kex=5000.0, spins_params=['r2', 'dw', 'pA', 'kex'])
> >
> >      # Repeat the function call, to simulate minimisation.
> >      for i in xrange(iter):
> >
> >
> > _______________________________________________
> > relax (http://www.nmr-relax.com)
> >
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> >
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