Re: r24056 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 17, 2014 - 19:36

That commit message might be a bit misleading when I present it to all
relax users.  It sounds like the 'NS R1rho 3-site' model is new.  You
have to be a bit more careful what you write, as I present your text
in all of the relax announcements.

Regards,

Edward



On 17 June 2014 19:27,  <tlinnet@xxxxxxxxxxxxx> wrote:
> Author: tlinnet
> Date: Tue Jun 17 19:27:10 2014
> New Revision: 24056
>
> URL: http://svn.gna.org/viewcvs/relax?rev=24056&view=rev
> Log:
> Implemented the target function for ns r1rho 3site.
>
> Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
> models for Clustered analysis.
>
> Modified:
>     branches/disp_spin_speed/target_functions/relax_disp.py
>
> Modified: branches/disp_spin_speed/target_functions/relax_disp.py
> URL: 
> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=24056&r1=24055&r2=24056&view=diff
> ==============================================================================
> --- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
> +++ branches/disp_spin_speed/target_functions/relax_disp.py     Tue Jun 17 
> 19:27:10 2014
> @@ -784,35 +784,26 @@
>          k_AC = pC * kex_AC / pA_pC
>          dw_AC = dw_AB + dw_BC
>
> -        # Initialise.
> -        chi2_sum = 0.0
> -
> -        # Loop over the spins.
> -        for si in range(self.num_spins):
> -            # Loop over the spectrometer frequencies.
> -            for mi in range(self.num_frq):
> -                # The R20 index.
> -                r20_index = mi + si*self.num_frq
> -
> -                # Convert dw from ppm to rad/s.
> -                dw_AB_frq = dw_AB[si] * self.frqs[0, si, mi, 0, 0]
> -                dw_AC_frq = dw_AC[si] * self.frqs[0, si, mi, 0, 0]
> -
> -                # Loop over the offsets.
> -                for oi in range(self.num_offsets[0, si, mi]):
> -                    # Back calculate the R2eff values for each experiment 
> type.
> -                    ns_r1rho_3site(M0=self.M0, matrix=self.matrix, 
> r1rho_prime=r1rho_prime[r20_index], omega=self.chemical_shifts[0, si, mi, 
> oi, 0], offset=self.offset[0, si, mi, oi, 0], r1=self.r1[0, si, mi, oi, 0], 
> pA=pA, pB=pB, pC=pC, dw_AB=dw_AB_frq, dw_AC=dw_AC_frq, k_AB=k_AB, 
> k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC, k_CA=k_CA, 
> spin_lock_fields=self.spin_lock_omega1[0, si, mi, oi], 
> relax_time=self.relax_times[0, si, mi, oi], 
> inv_relax_time=self.inv_relax_times[0, si, mi, oi], 
> back_calc=self.back_calc[0, si, mi, oi], num_points=self.num_disp_points[0, 
> si, mi, oi])
> -
> -                    # For all missing data points, set the back-calculated 
> value to the measured values so that it has no effect on the chi-squared 
> value.
> -                    for di in range(self.num_disp_points[0, si, mi, oi]):
> -                        if self.missing[0, si, mi, oi, di]:
> -                            self.back_calc[0, si, mi, oi, di] = 
> self.values[0, si, mi, oi, di]
> -
> -                    # Calculate and return the chi-squared value.
> -                    chi2_sum += chi2(self.values[0, si, mi, oi], 
> self.back_calc[0, si, mi, oi], self.errors[0, si, mi, oi])
> +        # Convert dw from ppm to rad/s. Use the out argument, to pass 
> directly to structure.
> +        multiply( multiply.outer( dw_AB.reshape(1, self.NS), 
> self.nm_no_nd_ones ), self.frqs, out=self.dw_AB_struct )
> +        multiply( multiply.outer( dw_AC.reshape(1, self.NS), 
> self.nm_no_nd_ones ), self.frqs, out=self.dw_AC_struct )
> +
> +        # Reshape R20 to per experiment, spin and frequency.
> +        self.r20_struct[:] = multiply.outer( r1rho_prime.reshape(self.NE, 
> self.NS, self.NM), self.no_nd_ones )
> +
> +        # Back calculate the R2eff values for each experiment type.
> +        ns_r1rho_3site(M0=self.M0, matrix=self.matrix, 
> r1rho_prime=self.r20_struct, omega=self.chemical_shifts, 
> offset=self.offset, r1=self.r1, pA=pA, pB=pB, pC=pC, 
> dw_AB=self.dw_AB_struct, dw_AC=self.dw_AC_struct, k_AB=k_AB, k_BA=k_BA, 
> k_BC=k_BC, k_CB=k_CB, k_AC=k_AC, k_CA=k_CA, 
> spin_lock_fields=self.spin_lock_omega1, relax_time=self.relax_times, 
> inv_relax_time=self.inv_relax_times, back_calc=self.back_calc, 
> num_points=self.num_disp_points)
> +
> +        # Clean the data for all values, which is left over at the end of 
> arrays.
> +        self.back_calc = self.back_calc*self.disp_struct
> +
> +        ## For all missing data points, set the back-calculated value to 
> the measured values so that it has no effect on the chi-squared value.
> +        if self.has_missing:
> +            # Replace with values.
> +            self.back_calc[self.mask_replace_blank.mask] = 
> self.values[self.mask_replace_blank.mask]
>
>          # Return the total chi-squared value.
> -        return chi2_sum
> +        return chi2_rankN(self.values, self.back_calc, self.errors)
>
>
>      def experiment_type_setup(self):
>
>
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