Hmmm, ok, now I'm re-re-regenerating. The final results are clearly going to be very interesting :)
Edward On 18 June 2014 16:04, Troels Emtekær Linnet <[email protected]> wrote: > 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) >> > >> > This is the relax-commits mailing list >> > [email protected] >> > >> > To unsubscribe from this list, get a password >> > reminder, or change your subscription options, >> > visit the list information page at >> > https://mail.gna.org/listinfo/relax-commits >> >> _______________________________________________ >> relax (http://www.nmr-relax.com) >> >> This is the relax-devel mailing list >> [email protected] >> >> >> To unsubscribe from this list, get a password >> reminder, or change your subscription options, >> visit the list information page at >> https://mail.gna.org/listinfo/relax-devel > > _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-devel
