Re: r25230 - in /trunk: target_functions/ test_suite/shared_data/curve_fitting/profiling/ -- August 25, 2014 - 10:33

Hi Troels,

This new target_functions.relax_disp_curve_fit module clashes with the
C module.  It is repetitive, the code already exists in the
target_functions.relax_fit module.  Why is the faster C module not
being used?

Regards,

Edward



On 25 August 2014 01:08,  <tlinnet@xxxxxxxxxxxxx> wrote:
> Author: tlinnet
> Date: Mon Aug 25 01:08:48 2014
> New Revision: 25230
>
> URL: http://svn.gna.org/viewcvs/relax?rev=25230&view=rev
> Log:
> Moved the target function for minimisation of exponential fit into the 
> target functions folder.
>
> task #7822(https://gna.org/task/index.php?7822): Implement user function to 
> estimate R2eff and associated errors for exponential curve fitting.
>
> Added:
>     trunk/target_functions/relax_disp_curve_fit.py
>       - copied, changed from r25229, 
> trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py
> Removed:
>     trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py
> Modified:
>     trunk/target_functions/__init__.py
>     
> trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py
>     trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py
>
> Modified: trunk/target_functions/__init__.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/target_functions/__init__.py?rev=25230&r1=25229&r2=25230&view=diff
> ==============================================================================
> --- trunk/target_functions/__init__.py  (original)
> +++ trunk/target_functions/__init__.py  Mon Aug 25 01:08:48 2014
> @@ -32,5 +32,6 @@
>      'mf',
>      'n_state_model',
>      'potential',
> -    'relax_disp'
> +    'relax_disp',
> +    'relax_disp_curve_fit'
>  ]
>
> Copied: trunk/target_functions/relax_disp_curve_fit.py (from r25229, 
> trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py)
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/target_functions/relax_disp_curve_fit.py?p2=trunk/target_functions/relax_disp_curve_fit.py&p1=trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py&r1=25229&r2=25230&rev=25230&view=diff
> ==============================================================================
>     (empty)
>
> Modified: 
> trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py?rev=25230&r1=25229&r2=25230&view=diff
> ==============================================================================
> --- 
> trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py 
> (original)
> +++ 
> trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py 
> Mon Aug 25 01:08:48 2014
> @@ -57,7 +57,7 @@
>  # relax module imports.
>  from status import Status; status = Status()
>  from target_functions.relax_fit import setup, func, dfunc, d2func, 
> back_calc_I
> -from relax_fit import Exponential
> +from target_functions.relax_disp_curve_fit import Exponential
>
>
>  # Alter setup.
>
> Removed: trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py?rev=25229&view=auto
> ==============================================================================
> --- trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py   
> (original)
> +++ trunk/test_suite/shared_data/curve_fitting/profiling/relax_fit.py   
> (removed)
> @@ -1,135 +0,0 @@
> -###############################################################################
> -#                                                                          
>    #
> -# Copyright (C) 2013-2014 Edward d'Auvergne                                
>    #
> -# Copyright (C) 2014 Troels E. Linnet                                      
>    #
> -#                                                                          
>    #
> -# This file is part of the program relax (http://www.nmr-relax.com).       
>    #
> -#                                                                          
>    #
> -# This program is free software: you can redistribute it and/or modify     
>    #
> -# it under the terms of the GNU General Public License as published by     
>    #
> -# the Free Software Foundation, either version 3 of the License, or        
>    #
> -# (at your option) any later version.                                      
>    #
> -#                                                                          
>    #
> -# This program is distributed in the hope that it will be useful,          
>    #
> -# but WITHOUT ANY WARRANTY; without even the implied warranty of           
>    #
> -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the            
>    #
> -# GNU General Public License for more details.                             
>    #
> -#                                                                          
>    #
> -# You should have received a copy of the GNU General Public License        
>    #
> -# along with this program.  If not, see <http://www.gnu.org/licenses/>.    
>    #
> -#                                                                          
>    #
> -###############################################################################
> -
> -# Module docstring.
> -"""Target functions for relaxation fit."""
> -
> -# Python module imports.
> -from copy import deepcopy
> -from numpy import exp, multiply, sum
> -
> -# relax module imports.
> -
> -
> -class Exponential:
> -    def __init__(self, num_params=None, num_times=None, values=None, 
> sd=None, relax_times=None, scaling_matrix=None):
> -        """Relaxation dispersion target functions for optimisation.
> -        """
> -
> -        # Store variables.
> -        self.num_params = num_params
> -        self.num_times = num_times
> -        self.values = values
> -        self.errors = sd
> -        self.relax_times = relax_times
> -        self.scaling_matrix = scaling_matrix
> -
> -        # Create the structure for holding the back-calculated R2eff 
> values (matching the dimensions of the values structure).
> -        self.back_calc = deepcopy(self.values)
> -
> -        # Define function to minimise.
> -        self.func = self.func_exp
> -        self.calc = self.calc_exp
> -
> -
> -    def chi2_rankN(self, data, back_calc_vals, errors):
> -        """Function to calculate the chi-squared value for multiple numpy 
> array axis.
> -
> -        @param data:            The multi dimensional vectors of yi values.
> -        @type data:             numpy multi dimensional array
> -        @param back_calc_vals:  The multi dimensional vectors of yi(theta) 
> values.
> -        @type back_calc_vals:   numpy multi dimensional array
> -        @param errors:          The multi dimensional vectors of sigma_i 
> values.
> -        @type errors:           numpy multi dimensional array
> -        @return:                The chi-squared value.
> -        @rtype:                 float
> -        """
> -
> -        # Calculate the chi-squared statistic.
> -        return sum((1.0 / errors * (data - back_calc_vals))**2)
> -
> -
> -    def calc_exp(self, times=None, r2eff=None, i0=None):
> -        """Calculate the function values of exponential function.
> -
> -        @keyword times: The time points.
> -        @type times:    float
> -        @keyword r2eff: The effective transversal relaxation rate.
> -        @type r2eff:    float
> -        @keyword i0:    The initial intensity.
> -        @type i0:       float
> -        @return:        The function values.
> -        @rtype:         float
> -        """
> -
> -        # Calculate.
> -        return i0 * exp( -times * r2eff)
> -
> -
> -    def calc_exp_chi2(self, r2eff=None, i0=None):
> -        """Calculate the chi-squared value of exponential function.
> -
> -
> -        @keyword r2eff: The effective transversal relaxation rate.
> -        @type r2eff:    float
> -        @keyword i0:    The initial intensity.
> -        @type i0:       float
> -        @return:        The chi-squared value.
> -        @rtype:         float
> -        """
> -
> -        # Calculate.
> -        self.back_calc[:] = self.calc_exp(times=self.relax_times, 
> r2eff=r2eff, i0=i0)
> -
> -        # Return the total chi-squared value.
> -        return self.chi2_rankN(data=self.values, 
> back_calc_vals=self.back_calc, errors=self.errors)
> -
> -
> -    def func_exp(self, params):
> -        """Target function for exponential fit.
> -
> -        @param params:  The vector of parameter values.
> -        @type params:   numpy rank-1 float array
> -        @return:        The chi-squared value.
> -        @rtype:         float
> -        """
> -
> -        # Unpack the parameter values.
> -        r2eff = params[0]
> -        i0 = params[1]
> -
> -        # Calculate and return the chi-squared value.
> -        return self.calc_exp_chi2(r2eff=r2eff, i0=i0)
> -
> -
> -    def func_exp_general(self, params, xdata, ydata):
> -        """Target function for minimisation with scipy.optimize.leastsq
> -        """
> -
> -        return self.calc_exp(xdata, *params) - ydata
> -
> -
> -    def func_exp_weighted_general(self, params, xdata, ydata, weights):
> -        """Target function for minimisation with scipy.optimize.leastsq
> -        """
> -
> -        return weights * (self.calc_exp(xdata, *params) - ydata)
>
> Modified: 
> trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py?rev=25230&r1=25229&r2=25230&view=diff
> ==============================================================================
> --- trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py    
>     (original)
> +++ trunk/test_suite/shared_data/curve_fitting/profiling/verify_error.py    
>     Mon Aug 25 01:08:48 2014
> @@ -32,7 +32,7 @@
>  from status import Status; status = Status()
>
>  # Initial try for Exponential class.
> -from relax_fit import Exponential
> +from target_functions.relax_disp_curve_fit import Exponential
>
>  # Define data path.
>  prev_data_path = status.install_path + 
> sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'
>  +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff"
>
>
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