mailRe: [bug #22146] Unpacking of R2A and R2B is performed wrong for clustered "full" dispersion models


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Posted by Edward d'Auvergne on June 06, 2014 - 15:36:
Ok, I just checked for the problem and it is the parameter values of:

R20 = [10.1, 10.2, 10.3, 100.1, 100.2, 100.3, 20.1, 20.2, 20.3, 200.1,
200.2, 200.3, 30.1, 30.2, 30.3, 300.1, 300.2, 300.3, 40.1, 40.2, 40.3,
400.1, 400.2, 400.3]

If you look at the
specific_analyses.relax_disp.parameters.linear_constraints() function,
you will see that the R20 constraints are:

        0 <= R2 <= 200
        0 <= R2A <= 200
        0 <= R2B <= 200

You have quite a few R20 values above 200, and that is the constraint
violation.  When there is a violation, the point is skipped and, as
the grid search only has one point, then the grid search will do
nothing.  The value of 200 is reasonable as with such a relaxation
rate, you will no longer observe any peaks in your spectra.  That is
the reason for this value, and it prevents optimisation from sending
the R20 values to unreasonably high values.  Maybe you should divide
all your R20 values by 10?

Regards,

Edward








On 6 June 2014 15:28, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> wrote:

Hi Ed.

All r2, r2a and r2b values should be between 5 - 20.

Thanks.

But, how does the grid_search skip the target function?

Best
Troels



2014-06-06 15:25 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:


Note that the indices of ci match the b vector, so you can look at the
assemble_linear_constraints() function and work out which constraint
is being violated.

Regards,

Edward

On 6 June 2014 15:23, Edward d'Auvergne <edward@xxxxxxxxxxxxx> wrote:

Here, all negative ci values indicate a constraint violation, as:

ci = A.x - b,

where A and b are the constraint matrices and x is the parameter
vector.  The linear constraints used by minfx are defined as:

A.x - b >= 0.

So you will need to determine which parameters are violating the
constraints and change the input.

Regards,

Edward



On 6 June 2014 15:20, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx>
wrote:

Ah

"Constraint violated, skipping grid point."


Fitting to the spin block [':1@N', ':2@N', ':3@N', ':4@N']
----------------------------------------------------------

Unconstrained grid search size: 1 (constraints may decrease this size).



Grid search
~~~~~~~~~~~
Linear constraint matrices.
A: array([[ 1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [-1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0., -1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  0., -1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  0.,  0., -1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
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       [ 0.,  0.,  0.,  0., -1.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
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0.,
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         1.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
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         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
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         0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0., -1.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  1.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
0.,
         0.,  0.,  0., -1.]])
b: array([   0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20.
,
          0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,
          0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,
          0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,
          0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,
          0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,    0. ,  -20. ,
          0. ,    0. ,    0. ,    0. ,   -1. ,    0.5,    0. , -200. ])

Searching through 1 grid nodes.
k: 0        xk: [           1.01,            1.02,            1.03,
10.01,           10.02,           10.03,            2.01,
2.02,
2.03,           20.01,           20.02,           20.03,
3.01,
3.02,            3.03,           30.01,           30.02,
30.03,
4.01,            4.02,            4.03,           40.01,
40.02,
40.03,               1,               2,               3,
4,
0.9,             0.1]
Constraint violated, skipping grid point.
ci: array([  1.010000000000000e+00,   1.899000000000000e+01,
         1.020000000000000e+00,   1.898000000000000e+01,
         1.030000000000000e+00,   1.897000000000000e+01,
         1.001000000000000e+01,   9.990000000000000e+00,
         1.002000000000000e+01,   9.980000000000000e+00,
         1.003000000000000e+01,   9.970000000000001e+00,
         2.010000000000000e+00,   1.799000000000000e+01,
         2.020000000000000e+00,   1.798000000000000e+01,
         2.030000000000000e+00,   1.797000000000000e+01,
         2.001000000000000e+01,  -9.999999999998010e-03,
         2.002000000000000e+01,  -1.999999999999957e-02,
         2.003000000000000e+01,  -3.000000000000114e-02,
         3.010000000000000e+00,   1.699000000000000e+01,
         3.020000000000000e+00,   1.698000000000000e+01,
         3.030000000000000e+00,   1.697000000000000e+01,
         3.001000000000000e+01,  -1.001000000000000e+01,
         3.002000000000000e+01,  -1.002000000000000e+01,
         3.003000000000000e+01,  -1.003000000000000e+01,
         4.010000000000000e+00,   1.599000000000000e+01,
         4.020000000000000e+00,   1.598000000000000e+01,
         4.029999999999999e+00,   1.597000000000000e+01,
         4.001000000000001e+01,  -2.001000000000001e+01,
         4.002000000000000e+01,  -2.002000000000000e+01,
         4.003000000000000e+01,  -2.003000000000000e+01,
         1.000000000000000e+00,   2.000000000000000e+00,
         3.000000000000000e+00,   4.000000000000000e+00,
         9.999999999999998e-02,   4.000000000000000e-01,
         1.000000000000000e-01,   1.999000000000000e+02])


Optimised parameter values:
r2a (SQ CPMG - 500.00000000 MHz)        10.100000000000000
r2a (SQ CPMG - 600.00000000 MHz)        10.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        10.300000000000001
r2b (SQ CPMG - 500.00000000 MHz)       100.099999999999994
r2b (SQ CPMG - 600.00000000 MHz)       100.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       100.299999999999997
r2a (SQ CPMG - 500.00000000 MHz)        20.100000000000001
r2a (SQ CPMG - 600.00000000 MHz)        20.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        20.300000000000004
r2b (SQ CPMG - 500.00000000 MHz)       200.099999999999966
r2b (SQ CPMG - 600.00000000 MHz)       200.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       200.300000000000011
r2a (SQ CPMG - 500.00000000 MHz)        30.100000000000001
r2a (SQ CPMG - 600.00000000 MHz)        30.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        30.300000000000004
r2b (SQ CPMG - 500.00000000 MHz)       300.100000000000023
r2b (SQ CPMG - 600.00000000 MHz)       300.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       300.300000000000011
r2a (SQ CPMG - 500.00000000 MHz)        40.099999999999994
r2a (SQ CPMG - 600.00000000 MHz)        40.200000000000003
r2a (SQ CPMG - 700.00000000 MHz)        40.299999999999997
r2b (SQ CPMG - 500.00000000 MHz)       400.100000000000023
r2b (SQ CPMG - 600.00000000 MHz)       400.199999999999932
r2b (SQ CPMG - 700.00000000 MHz)       400.300000000000011
dw                           1.000000000000000
dw                           2.000000000000000
dw                           3.000000000000000
dw                           4.000000000000000
pA                           0.900000000000000
kex                       1000.000000000000000
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 600.00000000 MHz', 10.2,
10.2)
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 500.00000000 MHz', 10.1,
10.1)
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 700.00000000 MHz', 10.3,
10.3)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
100.19999999999999, 100.2)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
100.1,
100.1)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
100.3,
100.3)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 600.00000000 MHz', 20.2,
20.2)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 500.00000000 MHz', 20.1,
20.1)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
20.300000000000004, 20.3)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
200.2,
200.2)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
200.09999999999997, 200.1)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
200.3,
200.3)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 600.00000000 MHz', 30.2,
30.2)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 500.00000000 MHz', 30.1,
30.1)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
30.300000000000004, 30.3)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
300.2,
300.2)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
300.1,
300.1)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
300.3,
300.3)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 600.00000000 MHz', 40.2,
40.2)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 500.00000000 MHz',
40.099999999999994, 40.1)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 700.00000000 MHz', 40.3,
40.3)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
400.19999999999993, 400.2)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
400.1,
400.1)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
400.3,
400.3)



2014-06-06 15:14 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:


Try setting "verbosity=10" in the grid_search user function call.
This might reveal the problem.

Regards,

Edward


On 6 June 2014 15:12, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx>
wrote:

I put in a print command in the target function to see R20A and
R20B.

This is not showing when doing grid search, but only when doing
minimisation?

Best
Troels


2014-06-06 15:10 GMT+02:00 Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>:


I tried:

        ## Experiments
        # Exp 1
        sfrq_1 = 500.0*1E6
        r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ,
frq=sfrq_1)
        time_T2_1 = 0.05
        ncycs_1 = range(2,22,2)
        # Here you define the direct R2eff errors (rad/s), as being
added
or subtracted for the created R2eff point in the corresponding ncyc
cpmg
frequence.
        #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05,
0.05,
-0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05]
        r2eff_errs_1 = [0.0] * len(ncycs_1)
        exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1]

        sfrq_2 = 600.0*1E6
        r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ,
frq=sfrq_2)
        time_T2_2 = 0.06
        ncycs_2 = range(2,22,2)
        # Here you define the direct R2eff errors (rad/s), as being
added
or subtracted for the created R2eff point in the corresponding ncyc
cpmg
frequence.
        #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05,
0.05,
-0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05]
        r2eff_errs_2 = [0.0] * len(ncycs_2)
        exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2]

        sfrq_3 = 700.0*1E6
        r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ,
frq=sfrq_3)
        time_T2_3 = 0.07
        ncycs_3 = range(2,22,2)
        # Here you define the direct R2eff errors (rad/s), as being
added
or subtracted for the created R2eff point in the corresponding ncyc
cpmg
frequence.
        #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05,
0.05,
-0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05]
        r2eff_errs_3 = [0.0] * len(ncycs_3)
        exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3]

        # Collect all exps
        exps = [exp_1, exp_2, exp_3]

        R20 = [10.1, 10.2, 10.3, 100.1, 100.2, 100.3, 20.1, 20.2,
20.3,
200.1, 200.2, 200.3, 30.1, 30.2, 30.3, 300.1, 300.2, 300.3, 40.1,
40.2,
40.3, 400.1, 400.2, 400.3]
        #R20 = [10.1, 10.2, 10.3, 100.1, 100.2, 100.3, 20.1, 20.2,
20.3,
200.1, 200.2, 200.3]
        dw_arr = [1.0, 2.0, 3.0, 4.0]
        #dw_arr = [1.0, 2.0]
        pA_arr = [0.9]
        kex_arr = [1000.]

        spins = [
                ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0],
r20_key_2:
R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2:
R20[4],
r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw':
dw_arr[0]}],
                ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6],
r20_key_2:
R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2:
R20[10],
r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw':
dw_arr[1]}],
                ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12],
r20_key_2:
R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15],
r20_key_2:
R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0],
'dw':
dw_arr[2]}],
                ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18],
r20_key_2:
R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21],
r20_key_2:
R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0],
'dw':
dw_arr[3]}],
                ]

------

------------
relax> grid_search(lower=[10.1, 10.2, 10.3, 100.1, 100.2, 100.3,
20.1,
20.2, 20.3, 200.1, 200.2, 200.3, 30.1, 30.2, 30.3, 300.1, 300.2,
300.3,
40.1, 40.2, 40.3, 400.1, 400.2, 400.3, 1.0, 2.0, 3.0, 4.0, 0.9,
1000.0],
upper=[10.1, 10.2, 10.3, 100.1, 100.2, 100.3, 20.1, 20.2, 20.3,
200.1,
200.2, 200.3, 30.1, 30.2, 30.3, 300.1, 300.2, 300.3, 40.1, 40.2,
40.3,
400.1, 400.2, 400.3, 1.0, 2.0, 3.0, 4.0, 0.9, 1000.0], inc=1,
constraints=True, verbosity=1)


Fitting to the spin block [':1@N', ':2@N', ':3@N', ':4@N']
----------------------------------------------------------

Unconstrained grid search size: 1 (constraints may decrease this
size).


Grid search
~~~~~~~~~~~

Searching through 1 grid nodes.

Optimised parameter values:
r2a (SQ CPMG - 500.00000000 MHz)        10.100000000000000
r2a (SQ CPMG - 600.00000000 MHz)        10.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        10.300000000000001
r2b (SQ CPMG - 500.00000000 MHz)       100.099999999999994
r2b (SQ CPMG - 600.00000000 MHz)       100.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       100.299999999999997
r2a (SQ CPMG - 500.00000000 MHz)        20.100000000000001
r2a (SQ CPMG - 600.00000000 MHz)        20.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        20.300000000000004
r2b (SQ CPMG - 500.00000000 MHz)       200.099999999999966
r2b (SQ CPMG - 600.00000000 MHz)       200.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       200.300000000000011
r2a (SQ CPMG - 500.00000000 MHz)        30.100000000000001
r2a (SQ CPMG - 600.00000000 MHz)        30.199999999999999
r2a (SQ CPMG - 700.00000000 MHz)        30.300000000000004
r2b (SQ CPMG - 500.00000000 MHz)       300.100000000000023
r2b (SQ CPMG - 600.00000000 MHz)       300.199999999999989
r2b (SQ CPMG - 700.00000000 MHz)       300.300000000000011
r2a (SQ CPMG - 500.00000000 MHz)        40.099999999999994
r2a (SQ CPMG - 600.00000000 MHz)        40.200000000000003
r2a (SQ CPMG - 700.00000000 MHz)        40.299999999999997
r2b (SQ CPMG - 500.00000000 MHz)       400.100000000000023
r2b (SQ CPMG - 600.00000000 MHz)       400.199999999999932
r2b (SQ CPMG - 700.00000000 MHz)       400.300000000000011
dw                           1.000000000000000
dw                           2.000000000000000
dw                           3.000000000000000
dw                           4.000000000000000
pA                           0.900000000000000
kex                       1000.000000000000000
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 600.00000000 MHz',
10.2,
10.2)
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 500.00000000 MHz',
10.1,
10.1)
('CR72 full', 'Ala', ':1@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
10.3,
10.3)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
100.19999999999999, 100.2)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
100.1,
100.1)
('CR72 full', 'Ala', ':1@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
100.3,
100.3)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 600.00000000 MHz',
20.2,
20.2)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 500.00000000 MHz',
20.1,
20.1)
('CR72 full', 'Ala', ':2@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
20.300000000000004, 20.3)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
200.2,
200.2)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
200.09999999999997, 200.1)
('CR72 full', 'Ala', ':2@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
200.3,
200.3)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 600.00000000 MHz',
30.2,
30.2)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 500.00000000 MHz',
30.1,
30.1)
('CR72 full', 'Ala', ':3@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
30.300000000000004, 30.3)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
300.2,
300.2)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
300.1,
300.1)
('CR72 full', 'Ala', ':3@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
300.3,
300.3)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 600.00000000 MHz',
40.2,
40.2)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 500.00000000 MHz',
40.099999999999994, 40.1)
('CR72 full', 'Ala', ':4@N', 'r2a', 'SQ CPMG - 700.00000000 MHz',
40.3,
40.3)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 600.00000000 MHz',
400.19999999999993, 400.2)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 500.00000000 MHz',
400.1,
400.1)
('CR72 full', 'Ala', ':4@N', 'r2b', 'SQ CPMG - 700.00000000 MHz',
400.3,
400.3)

--------

It jumps over the target function?

This is a little weird?

Best
Troels



2014-06-06 15:02 GMT+02:00 Edward d'Auvergne
<edward@xxxxxxxxxxxxx>:


Hi,

Some more information is needed, as it's not possible to tell
where
this stopped.  A good idea would be to turn up the verbosity level
to
see what minfx is doing.  Did you call the grid_search user
function?
Or the minimise user function?  Did the grid search say something
like
"Searching through 1 grid nodes"?

Regards,

Edward



On 6 June 2014 14:48, Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>
wrote:

Hi Edward.

When I try to do a grid search, it does not initalize
func_CR72_full
in
the
target function?

If I make
import sys
sys.exit()

It does not stop?
Only if I do a minimise, it stops?

It is in
specific_analyses/relax_disp/optimisation.py
line 745

Inserting
            print model.func.im_func.__name__
gives func_CR72_full

How does it know how to unpack and calculate?

Best
Troels


2014-06-06 12:32 GMT+02:00 Edward d'Auvergne
<edward@xxxxxxxxxxxxx>:


Hi,

That sounds good.  Maybe it's best to have the number of fields
and
number of spins set to something different and not to 2?  That
way
the
unpacking is stressed as much as possible and there cannot be a
accidental swap of the field and spin dimensions being
unnoticed by
the test.  This is not likely, but I've encountered enough
weird
and
supposedly impossible situations in the development of relax
that
it
would not surprise me.

Cheers,

Edward

On 6 June 2014 12:27, Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>
wrote:

Check.

I am generating R2eff data for 3 fields, and 3 spins, for
full
model.
I will put the data in



test_suite/shared_data/dispersion/bug_22146_unpacking_r2a_r2b_cluster

Best
Troels


2014-06-06 12:11 GMT+02:00 Edward d'Auvergne
<edward@xxxxxxxxxxxxx>:


Hi,

Right, you have the 2 parameters in the self.num_spins*2
part.
And
I
forgot about the parameters being different for each field.
It
would
be good to then have a multi-field and multi-spin cluster
system
test
to really make sure that relax operates correctly,
especially
with
the
data going into the target function and the subsequently
unpacking
the
results into the relax data store.  For example someone
might
modify
the loop_parameters() function - this concept could be
migrated
into
the specific API and converted into a common mechanism for
all
the
analysis types as it is quite powerful - and they may not
know
that
the change they just made broke code in the
target_functions.relax_disp module.

Cheers,

Edward


On 6 June 2014 12:05, Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>
wrote:

Hi Ed.

The implementations needs:
        R20 =
params[:self.end_index[1]].reshape(self.num_spins*2,
self.num_frq)
        R20A = R20[::2].flatten()
        R20B = R20[1::2].flatten()





2014-06-06 11:55 GMT+02:00 Edward d'Auvergne
<edward@xxxxxxxxxxxxx>:


The different unpacking implementations can be tested
with
the
timeit
Python module to see which is fastest





(http://thread.gmane.org/gmane.science.nmr.relax.devel/5937/focus=6010).

Cheers,

Edward



On 6 June 2014 11:53, Edward d'Auvergne
<edward@xxxxxxxxxxxxx>
wrote:

Hi,

In this case, I think 'num_frq' should be fixed to 2.
This
dimension
corresponds to the parameters R20A and R20B so it is
always
fixed
to
2.

Regards,

Edward



On 6 June 2014 11:51, Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>
wrote:

Hi.

Another way is:

ml = params[:end_index[1]].reshape(num_spins*2,
num_frq)
R20A = ml[::2].flatten()
R20B = ml[1::2].flatten()


Best
Troels



2014-06-06 11:39 GMT+02:00 Troels Emtekær Linnet
<tlinnet@xxxxxxxxxxxxx>:


There is no doubt that it is the unpacking of the
R20A
and
R20B
in
the
target function.

I was thinking of creating a function, which do the
the
unpacking.

This unpacking function could then be tested with a
unit
test?

What do you think?
Where should I position such a function?

Best
Troels



2014-06-06 11:26 GMT+02:00 Edward d'Auvergne
<edward@xxxxxxxxxxxxx>:


Hi Troels,


The best way to handle this is to first create a
unit
test
of
the




specific_analyses.relax_disp.parameters.disassemble_param_vector()
where the problem is likely to be most easily found.
I
don't
understand how this could be a problem as the
assemble_param_vector()
and disassemble_param_vector() functions both call
the
same
loop_parameters() function for the ordering of the
parameter
values!
Maybe the problem is in the unpacking of the
parameter
vector
in
the
target functions themselves, for example in the full
B14
model:


    def func_B14_full(self, params):
        """Target function for the Baldwin (2014)
2-site
exact
solution model for all time scales.

        This assumes that pA > pB, and hence this
must
be
implemented
as a constraint.


        @param params:  The vector of parameter
values.
        @type params:   numpy rank-1 float array
        @return:        The chi-squared value.
        @rtype:         float
        """

        # Scaling.
        if self.scaling_flag:
            params = dot(params,
self.scaling_matrix)

        # Unpack the parameter values.
        R20A = params[:self.end_index[0]]
        R20B =
params[self.end_index[0]:self.end_index[1]]
        dw =
params[self.end_index[1]:self.end_index[2]]
        pA = params[self.end_index[2]]
        kex = params[self.end_index[2]+1]

        # Calculate and return the chi-squared
value.
        return self.calc_B14_chi2(R20A=R20A,
R20B=R20B,
dw=dw,
pA=pA,
kex=kex)


This R20A and R20B unpacking might be the failure
point
as
this
may
not match the loop_parameters() function - which it
must!
In
any
case, having a unit or system test catch the problem
would
be
very
useful for the stability of the dispersion analysis
in
relax.

A code example might be useful:

R20_params = array([1, 2, 3, 4])
R20A, R20B = transpose(R20_params.reshape(2, 2)
print(R20A)
print(R20B)

You should see that R20A is [1, 3], and R20B is [2,
4].
This
is
how
the parameters are handled in the loop_parameters()
function
which
defines the parameter vector in all parts of relax.
There
might
be a
quicker way to unpack the parameters, but such an
idea
could be
used
for the target functions.

Cheers,

Edward

On 6 June 2014 11:08, Troels E. Linnet
<NO-REPLY.INVALID-ADDRESS@xxxxxxx>
wrote:

URL:
  <http://gna.org/bugs/?22146>

                 Summary: Unpacking of R2A and R2B
is
performed
wrong
for
clustered "full" dispersion models
                 Project: relax
            Submitted by: tlinnet
            Submitted on: Fri 06 Jun 2014 09:08:58
AM
UTC
                Category: relax's source code
Specific analysis category: Relaxation dispersion
                Priority: 9 - Immediate
                Severity: 4 - Important
                  Status: None
             Assigned to: None
         Originator Name:
        Originator Email:
             Open/Closed: Open
                 Release: Repository: trunk
         Discussion Lock: Any
        Operating System: All systems




_______________________________________________________

Details:

The unpacking of the R2A and R2B parameters in the
"full"
model
is
performed
wrong.
This will happen performing a clustered analysis,
using
one
of
the
"full"
models.

This bug affect all analysis performed running
with a
"full"
model,
with
clustered residues.

The bug is located in the target function:
./target_functions/relax_disp.py

For all the "func_MODEL_full", the unpacking of:
R20A = params[:self.end_index[0]]
R20B = params[self.end_index[0]:self.end_index[1]]

This is wrong, since the "params" list, is
ordered:
[spin, spin, spin, [dw], pA, kex], where spin =
[nr_frq*r2a,
nr_frq*r2b]

This ordering happens in:
./specific_analysis/relax_disp/parameters.py
in the loop_parameters.py

A possible solutions i shown below.
This alter the unpacking of the parameters.

An example of profiling_cr72.py is attached.
This can be downloaded, and run in base folder of
relax:
./profiling_cr72.py .

This is with 3 frq, and 3 spins.

The current implementations would unpack:
('R20A', array([  2.,   2.,   2.,   4.,   4.,
4.,
12.,
12.,
12.]),
9)
('R20B', array([ 14.,  14.,  14.,  22.,  22.,
22.,
24.,
24.,
24.]),
9)

R2A is 2, 12, 22 for the spins 0-3
R2B is, 4, 14, 24 for the spins 0-3

The suggested unpacking loop, unpacks to:
('R20A', array([  2.,   2.,   2.,  12.,  12.,
12.,
22.,
22.,
22.]),
9)
('R20B', array([  4.,   4.,   4.,  14.,  14.,
14.,
24.,
24.,
24.]),
9)


-------
from numpy import array, concatenate, delete,
index_exp
import numpy

p = array([  1.000000000000000e+01,
1.000000000000000e+01,
1.100000000000000e+01
, 1.100000000000000e+01, 1.000000000000000e+01,
1.000000000000000e+01
, 1.100000000000000e+01, 1.100000000000000e+01,
1.000000000000000e+00
, 1.000000000000000e+00, 9.000000000000000e-01,
1.000000000000000e+03])

e = [4, 8, 10]

# Now
r2a = p[:e[0]]
print r2a
r2b = p[e[0]:e[1]]
print r2b
dw = p[e[1]:e[2]]
print dw
pA = p[e[2]]
print pA
kex = p[e[2]+1]
print kex

print "new"
ns = 2
nf = 2

ml = p[:e[1]]

R20A = array([])
R20B = array([])
for i in range(0, ns):
    # Array sorted per [spin, spin, spin], where
spin
=
[nr_frq*r2a,
nr_frq*r2b]
    spin_AB = ml[:nf*2]
    ml = delete(ml, numpy.s_[:nf*2])
    R20A = concatenate([R20A, spin_AB[:nf] ])
    R20B = concatenate([R20B, spin_AB[nf:] ])

print R20A
print R20B
print dw
print pA
print kex






_______________________________________________________

File Attachments:




-------------------------------------------------------
Date: Fri 06 Jun 2014 09:08:58 AM UTC  Name:
profiling_cr72.py
Size:
17kB
By: tlinnet

<http://gna.org/bugs/download.php?file_id=20938>




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