# random (c39b2)

Random Number Generator Controlling Commands

The commands described in this section are for a control of

the random number generators in CHARMM.

* Syntax | Syntax of the random command

* Function | Purpose of each of the flags and parameters

The commands described in this section are for a control of

the random number generators in CHARMM.

* Syntax | Syntax of the random command

* Function | Purpose of each of the flags and parameters

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Syntax of RANDom commands

---------------------------------------------------------------------------

Current Syntax:

RANDom specifications:

RANDom specifications:

RANDom { [CLCG] { [TIME] } } [UNIForm] [ASIN] [SCALe real] [OFFSet real] [TEST]

{ { ISEEd 4X(int } } [GAUSsian real ] [ACOS]

{ }

{ SYSTem { [TIME] } }

{ { ISEEd seed-specs} }

{ }

{ USER { [TIME] } }

{ { ISEEd seed-specs} }

{ }

{ OLDRandom [ISEEd int] }

seed-specs::= repeat integer ?NSEED number of times. For the default

CLCG RNG 4 integer numbers need to be specified. For the

standard fortran randum_number() routine one need to

specify ?NSEED integer numbers. This number is compiler

dependent!

Integer random number generator IRANdom specifications:

IRANdom [SERIes int] [SETUp] [BEGInt int] [ENDInt int]

[SEED int]

---------------------------------------------------------------------------

Syntax of RANDom commands

---------------------------------------------------------------------------

Current Syntax:

RANDom specifications:

RANDom specifications:

RANDom { [CLCG] { [TIME] } } [UNIForm] [ASIN] [SCALe real] [OFFSet real] [TEST]

{ { ISEEd 4X(int } } [GAUSsian real ] [ACOS]

{ }

{ SYSTem { [TIME] } }

{ { ISEEd seed-specs} }

{ }

{ USER { [TIME] } }

{ { ISEEd seed-specs} }

{ }

{ OLDRandom [ISEEd int] }

seed-specs::= repeat integer ?NSEED number of times. For the default

CLCG RNG 4 integer numbers need to be specified. For the

standard fortran randum_number() routine one need to

specify ?NSEED integer numbers. This number is compiler

dependent!

Integer random number generator IRANdom specifications:

IRANdom [SERIes int] [SETUp] [BEGInt int] [ENDInt int]

[SEED int]

---------------------------------------------------------------------------

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1) RANDom command.

The expression ?RAND will have a random number substituted for it

during command line evaluation. The default is to provide a number

from a uniform distribution, between 0.0 and 1.0; the RANDom command

allows modification of the distribution type and specification of

other factors. The only required keyword is the distribution type,

which must be second; for a GAUSsian distribution, a value for sigma

is required; the default mean is 0.0.

There is a variety of random number generators (RNG) available in

OLDRandom - legacy RNG. It is not appropriate to use for production

simulations anymore, but it can be used for simple testing

and for comparison with older results and test cases. "Use

The Source Luke" to find out the CHARMM command line

parameters to switch back to either old random or old

CLCG. It is very convenient to put these flags into

test.com script and compare the test results with older

CHARMM versions. The alternative would be to put random

command in test/datadir.def file and in some 40 or so test

cases input scripts which don't stream datadir.def.

CLCG - new RNG that supports 100 series and uses 4 seeds. It is a

modern RNG and is the default choice.

SYSTem - whatever is provided by random_number() routine in

fortran. It supports only one series but uses different

numbers of seeds, depending on compilers and integer(8)

vs integer(4) compilation. Use ?NRAND value to query

USER - a user_random() function is provided in

charmm/usersb.src. This routine can be replaced by users

to test their own RNG.

Additional keywords:

UNIForm uniform distribution - default

GAUSSian sigma Gaussian distribution. Value of sigma must be specified

SCALe scale multiply the number by scale

OFFSet offset add offset to the number

ACOS treat the number as a cosine and return the angle (deg)

ASIN treat the number as a sine and return the angle (deg)

ISEEd iseed specify a new random seed(s) (integer(s)). Use

?NSEED parameter to query how many seeds are

needed for the current random number generator.

NOTE: No big numbers for CLCG (iseed < 2 giga).

No limit for SYSTem random generator.

TIME seeds are assigned from the current system time.

The default.

TEST this command will test the random number generator for

its poriodicity.

PARAllel stores the seeds from all the processors in

the restart file, so parallel run can be

restored if needed. Without the parallel

keyword every processors has its own random

number series initialized from system time.

Note that OLDRandom sub-command sets OLDRNG, which runs "old" random

number generator instead of "new" CLCG method. CLCG unsets OLDRNG, and

runs the CLCG random number generator.

About the seeds:

The use of fixed seeds is discouraged for production runs so

by default the system clock provides an initial seeds for the

RNGs. One can specify seeds on the RANDom command or in some other

commands, eg DYNA. The seed number stored in the trajectory file is

for legacy RNG (OLDRandom) and its use is deprecated. However the full

functionality of seed storage is implemented for the restart file. It

is implemented so that the restart files from older versions of CHARMM

can still be used, only the seed is ignored when running from the old

restart file. The new restart file saves all the necessary seeds.

Examples:

RANDOM GAUSS 0.2 SCALE 10.0 ! gaussian mean of 0.0 with a sigma of 2.

RANDOM UNIFORM SCALE 360. ! uniform 0. to 360

RANDOM UNIFORM ACOS SCALE .5 ! uniform angles with cosines from 0. to .5

RAND GAUS 5. OFFS 60. ! gaussian mean of 60. with a sigma of 5.

RAND UNIF ISEED 7734 ! uniform new random seed

Subsequent use of ?RAND will substitute a number from the appropriate

distribution.

2) IRANdom command.

This command is designed to generate series of random integers taken

from uniform distributions between user-specified limits. Each series

or distribution must first be set up with the IRANdom SETUp command,

in which the lower and upper limits of the distribution, the series

number, and an integer seed are specified. E.g.

IRAND SERIES 1 SETUp BEGI 1 ENDI 18 SEED 2346

IRAND SERIES 2 SETUp BEGI 1 ENDI 402 SEED 4028987

The random integers for each series are then generated with the commands

IRAND SERIES 1

IRAND SERIES 2

etc.

The ?iran expression accesses the last random integer generated.

The purpose of the multiple series feature is at least two-fold. First, it

allows users to generate random numbers easily from many different

distributions during the same charmm run (e.g. for use in different parts

of the same calculation). Second, it may help the user avoid correlations

between random numbers generated for different parts of a calculation.

An internal counter, corresponding initially to the seed, is incremented

by several units with each instance of the IRANdom command; by separating

the seeds of the various distributions sufficiently, the user can thus avoid

cross-series correlations. The use of multiple seeds for a given series

should be unnecessary and is discouraged. The IRANdom function has an

overall period of no less than 10^12 for distribution widths of 10^10 or less.

IRANdom can also be used to effectively generate random real numbers, through

a division of the generated integers by a constant, with the use of the

CALC command.

1) RANDom command.

The expression ?RAND will have a random number substituted for it

during command line evaluation. The default is to provide a number

from a uniform distribution, between 0.0 and 1.0; the RANDom command

allows modification of the distribution type and specification of

other factors. The only required keyword is the distribution type,

which must be second; for a GAUSsian distribution, a value for sigma

is required; the default mean is 0.0.

There is a variety of random number generators (RNG) available in

OLDRandom - legacy RNG. It is not appropriate to use for production

simulations anymore, but it can be used for simple testing

and for comparison with older results and test cases. "Use

The Source Luke" to find out the CHARMM command line

parameters to switch back to either old random or old

CLCG. It is very convenient to put these flags into

test.com script and compare the test results with older

CHARMM versions. The alternative would be to put random

command in test/datadir.def file and in some 40 or so test

cases input scripts which don't stream datadir.def.

CLCG - new RNG that supports 100 series and uses 4 seeds. It is a

modern RNG and is the default choice.

SYSTem - whatever is provided by random_number() routine in

fortran. It supports only one series but uses different

numbers of seeds, depending on compilers and integer(8)

vs integer(4) compilation. Use ?NRAND value to query

USER - a user_random() function is provided in

charmm/usersb.src. This routine can be replaced by users

to test their own RNG.

Additional keywords:

UNIForm uniform distribution - default

GAUSSian sigma Gaussian distribution. Value of sigma must be specified

SCALe scale multiply the number by scale

OFFSet offset add offset to the number

ACOS treat the number as a cosine and return the angle (deg)

ASIN treat the number as a sine and return the angle (deg)

ISEEd iseed specify a new random seed(s) (integer(s)). Use

?NSEED parameter to query how many seeds are

needed for the current random number generator.

NOTE: No big numbers for CLCG (iseed < 2 giga).

No limit for SYSTem random generator.

TIME seeds are assigned from the current system time.

The default.

TEST this command will test the random number generator for

its poriodicity.

PARAllel stores the seeds from all the processors in

the restart file, so parallel run can be

restored if needed. Without the parallel

keyword every processors has its own random

number series initialized from system time.

Note that OLDRandom sub-command sets OLDRNG, which runs "old" random

number generator instead of "new" CLCG method. CLCG unsets OLDRNG, and

runs the CLCG random number generator.

About the seeds:

The use of fixed seeds is discouraged for production runs so

by default the system clock provides an initial seeds for the

RNGs. One can specify seeds on the RANDom command or in some other

commands, eg DYNA. The seed number stored in the trajectory file is

for legacy RNG (OLDRandom) and its use is deprecated. However the full

functionality of seed storage is implemented for the restart file. It

is implemented so that the restart files from older versions of CHARMM

can still be used, only the seed is ignored when running from the old

restart file. The new restart file saves all the necessary seeds.

Examples:

RANDOM GAUSS 0.2 SCALE 10.0 ! gaussian mean of 0.0 with a sigma of 2.

RANDOM UNIFORM SCALE 360. ! uniform 0. to 360

RANDOM UNIFORM ACOS SCALE .5 ! uniform angles with cosines from 0. to .5

RAND GAUS 5. OFFS 60. ! gaussian mean of 60. with a sigma of 5.

RAND UNIF ISEED 7734 ! uniform new random seed

Subsequent use of ?RAND will substitute a number from the appropriate

distribution.

2) IRANdom command.

This command is designed to generate series of random integers taken

from uniform distributions between user-specified limits. Each series

or distribution must first be set up with the IRANdom SETUp command,

in which the lower and upper limits of the distribution, the series

number, and an integer seed are specified. E.g.

IRAND SERIES 1 SETUp BEGI 1 ENDI 18 SEED 2346

IRAND SERIES 2 SETUp BEGI 1 ENDI 402 SEED 4028987

The random integers for each series are then generated with the commands

IRAND SERIES 1

IRAND SERIES 2

etc.

The ?iran expression accesses the last random integer generated.

The purpose of the multiple series feature is at least two-fold. First, it

allows users to generate random numbers easily from many different

distributions during the same charmm run (e.g. for use in different parts

of the same calculation). Second, it may help the user avoid correlations

between random numbers generated for different parts of a calculation.

An internal counter, corresponding initially to the seed, is incremented

by several units with each instance of the IRANdom command; by separating

the seeds of the various distributions sufficiently, the user can thus avoid

cross-series correlations. The use of multiple seeds for a given series

should be unnecessary and is discouraged. The IRANdom function has an

overall period of no less than 10^12 for distribution widths of 10^10 or less.

IRANdom can also be used to effectively generate random real numbers, through

a division of the generated integers by a constant, with the use of the

CALC command.