Hi Edward.

For the Jacobian to work with minfx, the parameter vector send to the
function should match 1:1 with the one to
chi2 function.

Best
Troels

2014-09-02 10:41 GMT+02:00 Edward d'Auvergne <[email protected]>:
> Hi Troels,
>
> I just noticed a problem here.  For the Jacobian (as well as the
> gradient and Hessian), you will need one element of the dR2eff/dr20a
> gradient for each R20a parameter in the model.  Same for the
> dR2eff/ddw gradient element.  You currently return a list of 3
> elements, but I'm guessing that the parameter vector sent into the
> target function is not simply [R20a, dw, k_AB].
>
> Regards,
>
> Edward
>
> On 2 September 2014 10:29,  <[email protected]> wrote:
>> Author: tlinnet
>> Date: Tue Sep  2 10:29:46 2014
>> New Revision: 25529
>>
>> URL: http://svn.gna.org/viewcvs/relax?rev=25529&view=rev
>> Log:
>> In the lib function of TSMFK01, returned the Jacobian as list of 
>> derivatives. This is for easier manipulation in target function.
>>
>> task #7824(https://gna.org/task/index.php?7824): Model parameter ERROR 
>> estimation from Jacobian and Co-variance matrix of dispersion models.
>>
>> Modified:
>>     branches/est_par_error/lib/dispersion/tsmfk01.py
>>
>> Modified: branches/est_par_error/lib/dispersion/tsmfk01.py
>> URL: 
>> http://svn.gna.org/viewcvs/relax/branches/est_par_error/lib/dispersion/tsmfk01.py?rev=25529&r1=25528&r2=25529&view=diff
>> ==============================================================================
>> --- branches/est_par_error/lib/dispersion/tsmfk01.py    (original)
>> +++ branches/est_par_error/lib/dispersion/tsmfk01.py    Tue Sep  2 10:29:46 
>> 2014
>> @@ -142,6 +142,8 @@
>>      @type k_AB:             float
>>      @keyword tcp:           The tau_CPMG times (1 / 4.nu1).
>>      @type tcp:              numpy float array of rank [NE][NS][NM][NO][ND]
>> +    @return:                The Jacobian returned as list of derivatives.  
>> This is for easier manipulation and possible back scaling from rad/s to 
>> normal units in relax.
>> +    @rtype:                 list of numpy arrays
>>      """
>>
>>      # Get the partial derivatives.
>> @@ -149,7 +151,7 @@
>>      get_d_f_d_dw = d_f_d_dw(r20a=r20a, dw=dw, k_AB=k_AB, tcp=tcp)
>>      get_d_f_d_k_AB = d_f_d_k_AB(r20a=r20a, dw=dw, k_AB=k_AB, tcp=tcp)
>>
>> -    return transpose(array( [get_d_f_d_r20a , get_d_f_d_dw, get_d_f_d_k_AB] 
>> ) )
>> +    return [get_d_f_d_r20a , get_d_f_d_dw, get_d_f_d_k_AB]
>>
>>
>>  def d_f_d_r20a(r20a=None, dw=None, k_AB=None, tcp=None):
>>
>>
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