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tsoc
openmm
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c2505aad
Commit
c2505aad
authored
Jan 15, 2015
by
Jason Swails
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``XXX`` -> :class:`XXX`
principle -> principal... I'm a bozo.
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c2191b61
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docs-source/usersguide/theory.rst
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c2505aad
...
@@ -1399,7 +1399,7 @@ normal distribution).
...
@@ -1399,7 +1399,7 @@ normal distribution).
What this means is that the random numbers used by integrators and forces within
What this means is that the random numbers used by integrators and forces within
OpenMM cannot have any discernible pattern to them. Patterns can be induced in
OpenMM cannot have any discernible pattern to them. Patterns can be induced in
PRNGs in two principl
e
ways:
PRNGs in two princip
a
l ways:
1. The PRNG uses a bad algorithm with a short period.
1. The PRNG uses a bad algorithm with a short period.
2. Two PRNGs are started using the same seed
2. Two PRNGs are started using the same seed
...
@@ -1421,23 +1421,24 @@ only within a single simulation, but between two different simulations of the
...
@@ -1421,23 +1421,24 @@ only within a single simulation, but between two different simulations of the
same system as well (including any restarts of previous simulations).
same system as well (including any restarts of previous simulations).
Every stochastic force and integrator that does (or could) make use of random
Every stochastic force and integrator that does (or could) make use of random
numbers has two instance methods attached to it:
`
`getRandomNumberSeed()`
` and
numbers has two instance methods attached to it:
:class:
`getRandomNumberSeed()`
`
`setRandomNumberSeed(int seed)`
`
. If you set a unique random seed for
two
and :class:
`setRandomNumberSeed(int seed)`. If you set a unique random seed for
different simulations (or different forces/integrators if applicable),
OpenMM
two
different simulations (or different forces/integrators if applicable),
guarantees that the generated sequences of random numbers will be
different (by
OpenMM
guarantees that the generated sequences of random numbers will be
contrast, no guarantee is made that the same seed will result in
identical
different (by
contrast, no guarantee is made that the same seed will result in
random number sequences).
identical
random number sequences).
Since breaking simulations up into pieces and/or running multiple replicates of
Since breaking simulations up into pieces and/or running multiple replicates of
a system to obtain more complete statistics is common practice, a new strategy
a system to obtain more complete statistics is common practice, a new strategy
has been employed for OpenMM versions 6.3 and later with the aim of trying to
has been employed for OpenMM versions 6.3 and later with the aim of trying to
ensure that each simulation will be started with a unique random seed. A random
ensure that each simulation will be started with a unique random seed. A random
seed value of 0 (the default) will cause a unique random seed to be generated
seed value of 0 (the default) will cause a unique random seed to be generated
when a new
`
`Context`
`
is instantiated.
when a new
:class:
`Context` is instantiated.
Prior to the introduction of this feature, deserializing a serialized
Prior to the introduction of this feature, deserializing a serialized
``System`` XML file would result in each stochastic force or integrator being
:class:`System` XML file would result in each stochastic force or integrator
assigned the same random seed as the original instance that was serialized. If
being assigned the same random seed as the original instance that was
you use a ``System`` XML file generated by a version of OpenMM older than 6.3
serialized. If you use a :class:`System` XML file generated by a version of
to start a new simulation, you should manually set the random number seed of
OpenMM older than 6.3 to start a new simulation, you should manually set the
each stochastic force or integrator to 0 (or another unique value).
random number seed of each stochastic force or integrator to 0 (or another
unique value).
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