Hello Everybody,
I'd been continuing my effort to produce some specialized heme parameters
and decided that it might be the simplest to use paramfit and a large
number of QM derived structures+energies. But after the QM is done, I've
questions.
1) During the optimization process Gaussian produces a number of structures
with energies that are sub-optimal configurations, is there any reason why
these cannot or should not be used for parameter fitting? or other concerns
in that regard?
2) Is there a way to run paramfit on multiple processors?
3) I derived the correction constant K using the method described in the
tutorial, and then ran it to find parameters by list as well as the default
(since I want to optimize all parameters), in both circumstances it set the
initial value of K to zero, this obviously deviates from the output files
in the tutorial.. so I probably need help with this.
4) I am getting some warning related to dihedral spans lacking data
coverage, given that Is fitting dehedral parameters to the heme system
unnecessary or is this not a significant message?
5) Any other pointers would be greatly appreciated.
Thank you,
-David Poole
Here are the relevant input and output files, the latter is truncated at
points just for space on the list messages.
fit_parameters.in
RUNTYPE=FIT
COORDINATE_FORMAT=TRAJECTORY
NSTRUCTURES=1001
K=-1922732.27618371
PARAMETERS_TO_FIT=DEFAULT
FUNC_TO_FIT=SUM_SQUARES_AMBER_STANDARD
QM_ENERGY_UNITS=HARTREE
ALGORITHM=GENETIC
OPTIMIZATIONS=500
MAX_GENERATIONS=50000
GENERATIONS_TO_CONV=20
GENERATIONS_TO_SIMPLEX=10
GENERATIONS_WITHOUT_SIMPLEX=10
MUTATION_RATE=0.075
PARENT_PERCENT=0.25
SEARCH_SPACE=1.0
WRITE_ENERGY=fit_parameters_04_energy.dat
WRITE_FRCMOD=fit_parameters_04.frcmod
fit_parameter.out
* AMBER Bond Angle and Dihedral Parameter Optimiser *
* v3.0.0 *
Execution started at:
| Mon Sep 7 11:38:13 2015
|
| Random seed = 1441651093
Reading job control file: fit_parameters.in
Job Control: Read a total of 23 lines from job_control file. 18 options
set.
Reading prmtop file : fixed_2.prmtop
Prmtop (unique): Found 13 unique bonds.
Prmtop (unique): Found 22 unique angles.
Prmtop (unique): Found 42 unique dihedrals.
Prmtop (unique): Found 44 unique dihedral terms.
Reading mdcrd file: all_log_structures.mdcrd
Reading mdcrd file : all_log_structures.mdcrd
Coordinate file passed format check
Reading energy file or directory : all_log_energies.dat
---------------------------------------------------------------------
| OPTIONS SUMMARY |
| ---------------
|
| Summary of Run Type Options:
|
| Run Mode = FIT, Minimiser = GENETIC
|
| Function to be Fit = SUM_SQUARES_AMBER_STANDARD
|
|
|
| Terms to be fit:
|
| UNIQUE_BONDS = 13, UNIQUE ANGLES = 22, UNIQUE DIHEDRALS = 42
|
| NBONDS = 91, NANGLES = 168, NDIHEDRALS = 320
|
| Total dimensions of fit = 114
|
|
|
| Sample structures for least squares fit = 1001
|
|
|
|
|
| Energy Correction Term (K) = 0.00000000
|
|
|
| OPTIMIZATIONS = 500
|
| MAX GENERATIONS = 50000
|
| MUTATION RATE = 0.07
|
|
|
| Estimate Memory Usage (per cpu):
|
| Coordinate info will be read from disk as required.
|
| OPTION STORAGE = 131 bytes
|
| PRMTOP STORAGE = 874562 bytes
|
| COORDINATE STORAGE = 2074112 bytes
|
| GA ARRAY STORAGE = 456000 bytes
|
|
|
| TOTAL ESTIMATED MEMORY USAGE = 3404805 bytes
|
|
|
---------------------------------------------------------------------
WARNING: h4-c2-na-hn dihedral is missing 9 data points in the range
0.0000 to 3.1416 radians.
<Truncated>
WARNING: c3-c2-c2-c3 dihedral is missing 9 data points in the range
0.0000 to 3.1416 radians.
* Input structures passed dihedral span check.
------------------------------- INITIAL PARAMETERS
--------------------------
------
Parameters for force field equation: AMBER_STANDARD:
(* means parameter is NOT constant during fit)
K = 0.000000 kcal/mol
(c2-h4)*Kr = 348.6000 kcal/(mol A)^2,*r_eq = 1.0840 A
<Truncated>
IMP (c2-c2-c2-c3)*Kp = 1.1000 kcal/mol, Np = 2.0000, Phase =
180.0001 Deg
-----------------------------------------------------------------------------
------
Sum of squares for initial parameters = 3700596316869135.0000000000
kcal^2/mo
l^2
R^2 value for initial parameters = 0.588313
Calculated energy with initial parameters for structure 1 = 372.804549
KCal/m
ol
Actual energy for structure 1 should be =
-1922382.389732 K
Cal/mol
--------------------------GENETIC ALGORITHM MINIMISATION
--------------------
-------
Minimising function SUM_SQUARES_AMBER_STANDARD, using the GENETIC
ALGORITHM
Running SIMPLEX REFINEMENT every 10 converged gen, then break for 10
-----------------------------------------------------------------------------
--------
GENERATIONS_TO_CONVERGE = 20 MAX_GENERATIONS = 50000 CONV_LIMIT =
1.00E
+01
OPTIMIZATIONS = 500 PARENT_PERCENT = 0.25
SEARCH_SPACE = 1.00 MAX_GENERATIONS = 50000
------------------------------------ CONVERGENCE
----------------------------
--------
Gen 0: Best= 3737064547674845.50000 Mean= 4.3387e+16 Elapsed=
0/3
Gen 1: Best= 3734895501632929.00000 Mean= 3.8512e+15 Elapsed=
1/3
Gen 2: Best= 3722321266414401.00000 Mean= 3.7601e+15 Elapsed=
:
R^2 value for initial parameters = 0.588313
Calculated energy with initial parameters for structure 1 = 372.804549
KCal/mol
Actual energy for structure 1 should be =
-1922382.389732 KCal/mol
--------------------------GENETIC ALGORITHM MINIMISATION
---------------------------
Minimising function SUM_SQUARES_AMBER_STANDARD, using the GENETIC
ALGORITHM
Running SIMPLEX REFINEMENT every 10 converged gen, then break for 10
-------------------------------------------------------------------------------------
GENERATIONS_TO_CONVERGE = 20 MAX_GENERATIONS = 50000 CONV_LIMIT =
1.00E+01
OPTIMIZATIONS = 500 PARENT_PERCENT = 0.25
SEARCH_SPACE = 1.00 MAX_GENERATIONS = 50000
------------------------------------ CONVERGENCE
------------------------------------
Gen 0: Best= 3737064547674845.50000 Mean= 4.3387e+16 Elapsed=
0/3
Gen 1: Best= 3734895501632929.00000 Mean= 3.8512e+15 Elapsed=
1/3
Gen 2: Best= 3722321266414401.00000 Mean= 3.7601e+15 Elapsed=
2/3
Gen 3: Best= 3711452850436978.50000 Mean= 3.7361e+15 Conv=
0/20
Gen 4: Best= 3707060632432145.00000 Mean= 3.7221e+15 Conv=
0/20
Gen 5: Best= 3700834433631478.50000 Mean= 3.714e+15 Conv=
0/20
Gen 6: Best= 3698366613824640.50000 Mean= 3.7083e+15 Conv=
0/20
Gen 7: Best= 3694454498694381.00000 Mean= 3.7041e+15 Conv=
0/20
Gen 8: Best= 3692951446031217.50000 Mean= 3.7009e+15 Conv=
0/20
Gen 9: Best= 3692354203638458.50000 Mean= 3.6988e+15 Conv=
0/20
Gen 10: Best= 3691484864346694.00000 Mean= 3.6972e+15 Conv=
0/20
Gen 11: Best= 3689650891060643.00000 Mean= 3.6961e+15 Conv=
0/20
Gen 12: Best= 3689650891060643.00000 Mean= 3.695e+15 Conv=
1/20
Gen 13: Best= 3689650891060643.00000 Mean= 3.6943e+15 Conv=
2/20
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Received on Mon Sep 14 2015 - 04:00:03 PDT
