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, <tlinnet@xxxxxxxxxxxxx> 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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