One more is coming!

Expanded.


2014-06-18 16:01 GMT+02:00 Edward d'Auvergne <[email protected]>:

> Ok, re-regenerating the statistics now ;)
>
> On 18 June 2014 15:58,  <[email protected]> wrote:
> > Author: tlinnet
> > Date: Wed Jun 18 15:58:31 2014
> > New Revision: 24092
> >
> > URL: http://svn.gna.org/viewcvs/relax?rev=24092&view=rev
> > Log:
> > Modified profiling script for TSMK01, to use correct parameters k_AB and
> r20a.
> >
> > Or else, the lib functions is just calculating with zero?
> >
> > 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_tsmfk01.py
> >
> > Modified:
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
> > URL:
> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py?rev=24092&r1=24091&r2=24092&view=diff
> >
> ==============================================================================
> > ---
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
>   (original)
> > +++
> branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
>   Wed Jun 18 15:58:31 2014
> > @@ -110,7 +110,7 @@
> >      Class Profile inherits the Dispersion container class object.
> >      """
> >
> > -    def __init__(self, num_spins=1, model=None, r2=None, r2a=None,
> r2b=None, dw=None, pA=None, kex=None, spins_params=None):
> > +    def __init__(self, num_spins=1, model=None, r2=None, r2a=None,
> r2b=None, dw=None, pA=None, kex=None, k_AB=None, spins_params=None):
> >          """
> >          Special method __init__() is called first (acts as Constructor).
> >          It brings in data from outside the class like the variable
> num_spins.
> > @@ -136,6 +136,8 @@
> >          @type pA:               float
> >          @keyword kex:           The rate of exchange.
> >          @type kex:              float
> > +        @keyword k_AB:          The exchange rate from state A to state
> B
> > +        @type k_AB:             float
> >          @keyword spins_params:  List of parameter strings used in
> dispersion model.
> >          @type spins_params:     array of strings
> >          """
> > @@ -172,7 +174,7 @@
> >              self.error.append([1.0]*len(cpmg_point))
> >
> >          # Assemble param vector.
> > -        self.params = self.assemble_param_vector(r2=r2, r2a=r2a,
> r2b=r2b, dw=dw, pA=pA, kex=kex, spins_params=spins_params)
> > +        self.params = self.assemble_param_vector(r2=r2, r2a=r2a,
> r2b=r2b, dw=dw, pA=pA, kex=kex, k_AB=k_AB, spins_params=spins_params)
> >
> >          # Make nested list arrays of data. And return them.
> >          values, errors, cpmg_frqs, missing, frqs, exp_types,
> relax_times, offsets = self.return_r2eff_arrays()
> > @@ -316,7 +318,7 @@
> >          return values, errors, cpmg_frqs, missing, frqs, exp_types,
> relax_times, offsets
> >
> >
> > -    def assemble_param_vector(self, r2=None, r2a=None, r2b=None,
> dw=None, pA=None, kex=None, spins_params=None):
> > +    def assemble_param_vector(self, r2=None, r2a=None, r2b=None,
> dw=None, pA=None, kex=None, k_AB=None, spins_params=None):
> >          """Assemble the dispersion relaxation dispersion curve fitting
> parameter vector.
> >
> >          @keyword r2:            The transversal relaxation rate.
> > @@ -331,6 +333,8 @@
> >          @type pA:               float
> >          @keyword kex:           The rate of exchange.
> >          @type kex:              float
> > +        @keyword k_AB:          The exchange rate from state A to state
> B
> > +        @type k_AB:             float
> >          @keyword spins_params:  List of parameter strings used in
> dispersion model.
> >          @type spins_params:     array of strings
> >          @return:                An array of the parameter values of the
> dispersion relaxation model.
> > @@ -357,6 +361,8 @@
> >                  value = pA
> >              elif param_name == 'kex':
> >                  value = kex
> > +            elif param_name == 'k_AB':
> > +                value = k_AB
> >
> >              # Add to the vector.
> >              param_vector.append(value)
> > @@ -411,6 +417,8 @@
> >                      yield 'pA', 0, 0
> >                  elif param == 'kex':
> >                      yield 'kex', 0, 0
> > +                elif param == 'k_AB':
> > +                    yield 'k_AB', 0, 0
> >
> >
> >      def calc(self, params):
> > @@ -441,7 +449,7 @@
> >      """
> >
> >      # Instantiate class
> > -    C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, r2b=10.0,
> dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
> > +    C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, dw=3.0,
> k_AB=10.0, spins_params=['r2a', 'dw', 'k_AB'])
> >
> >      # Loop 100 times for each spin in the clustered analysis (to make
> the timing numbers equivalent).
> >      for spin_index in xrange(100):
> > @@ -465,7 +473,7 @@
> >      """
> >
> >      # Instantiate class
> > -    C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, r2b=10.0,
> dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
> > +    C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, dw=3.0,
> k_AB=10.0, spins_params=['r2a', 'dw', 'k_AB'])
> >
> >      # Repeat the function call, to simulate minimisation.
> >      for i in xrange(iter):
> > @@ -476,38 +484,3 @@
> >  # Execute main function.
> >  if __name__ == "__main__":
> >      main()
> > -
> > -def test_reshape():
> > -    C1 = Profile(num_spins=1, model=MODEL_TSMFK01, r2a=5.0, r2b=10.0,
> dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
> > -    end_index = C1.model.end_index
> > -    #print("end_index:", end_index)
> > -    num_spins = C1.model.num_spins
> > -    #print("num_spins:", num_spins)
> > -    num_frq = C1.model.num_frq
> > -    #print("num_frq:", num_frq)
> > -    params = C1.params
> > -    #print("params", params)
> > -
> > -    R20 = params[:end_index[1]].reshape(num_spins*2, num_frq)
> > -    R20A = R20[::2].flatten()
> > -    R20B = R20[1::2].flatten()
> > -    dw = params[end_index[1]:end_index[2]]
> > -    pA = params[end_index[2]]
> > -    kex = params[end_index[2]+1]
> > -    print("R20A", R20A, len(R20A))
> > -    print("R20B", R20B, len(R20B))
> > -    print("dw", dw, len(dw))
> > -    print("dw", pA)
> > -    print("kex", kex)
> > -
> > -    for si in range(num_spins):
> > -        for mi in range(num_frq):
> > -            r20_index = mi + si*num_frq
> > -            r20a=R20A[r20_index]
> > -            r20b=R20B[r20_index]
> > -            print("r20a", r20a, "r20b", r20b)
> > -
> > -    model = C1.calc(params)
> > -    print(model)
> > -
> > -#test_reshape()
> >
> >
> > _______________________________________________
> > relax (http://www.nmr-relax.com)
> >
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