Dear Feng,
Thanks a lot for your explanation.
Following your explanation, I also found that there are some walkers
which have the scores
between 1/8 and 2/8, but the walkers were not copied to 2 walkers.
When the score is less than 1/8, the walker will be kept itself, then
the sign is "=> 0" or "=> 1"
About the term "walkers will be copied", are coordinates copied or
selection score (weight)? Thanks a lot!
All the best,
Qinghua
On 05/27/2018 04:16 AM, Feng Pan wrote:
> Hi, Qinghua
>
> the selection score is the ratio of the replica selection weight over the
> total weight,
> so if you have 8 replicas here, and the score is below 1/8, the walker will
> keep
> itself. If the score is between 1/8 and 2/8, the walker will be copied to 2
> walkers, as
> shown like => 2 walkers.
>
> When the entropy is above the threshold, the selection will be calculated,
> but if
> every selection score is below 1/8, there will be no resampling, every
> walker will
> be kept just itself.
>
> Best
> Feng
>
> On Fri, May 25, 2018 at 7:00 PM, Qinghua Liao <scorpio.liao.gmail.com>
> wrote:
>
>> Hello Amber developers,
>>
>> Currently, I am running ABMD with multiple walkers, but I have some
>> questions regarding interpreting the output.
>> Here is my input for the multiple walkers:
>>
>> selection_freq = 500
>> selection_constant = 0.00001
>> selection_epsilon = 0.0
>>
>> And here are some output from the simulations:
>> #
>> NFE : selection score for walker 1 is 0.930991 / 7.992304 = 0.116 => 0
>> walker(s)
>> NFE : selection score for walker 2 is 0.881570 / 7.992304 = 0.110 => 1
>> walker(s)
>> NFE : selection score for walker 3 is 0.945704 / 7.992304 = 0.118 => 1
>> walker(s)
>> NFE : selection score for walker 4 is 0.951837 / 7.992304 = 0.119 => 1
>> walker(s)
>> NFE : selection score for walker 5 is 0.973335 / 7.992304 = 0.122 => 1
>> walker(s)
>> NFE : selection score for walker 6 is 1.103148 / 7.992304 = 0.138 => 1
>> walker(s)
>> NFE : selection score for walker 7 is 0.967854 / 7.992304 = 0.121 => 1
>> walker(s)
>> NFE : selection score for walker 8 is 1.237866 / 7.992304 = 0.155 => 2
>> walker(s)
>> NFE : Selection entropy 0.005597 is greater than threshold 0.000000
>> NFE : Selection resampling : new 1 comes from 2
>> #
>> #
>> NFE : selection score for walker 1 is 1.042757 / 7.817606 = 0.133 => 1
>> walker(s)
>> NFE : selection score for walker 2 is 0.956335 / 7.817606 = 0.122 => 1
>> walker(s)
>> NFE : selection score for walker 3 is 0.775833 / 7.817606 = 0.099 => 1
>> walker(s)
>> NFE : selection score for walker 4 is 0.906343 / 7.817606 = 0.116 => 1
>> walker(s)
>> NFE : selection score for walker 5 is 0.938005 / 7.817606 = 0.120 => 1
>> walker(s)
>> NFE : selection score for walker 6 is 0.851424 / 7.817606 = 0.109 => 1
>> walker(s)
>> NFE : selection score for walker 7 is 1.232238 / 7.817606 = 0.158 => 1
>> walker(s)
>> NFE : selection score for walker 8 is 1.114672 / 7.817606 = 0.143 => 1
>> walker(s)
>> NFE : Selection entropy 0.009795 is greater than threshold 0.000000
>> #
>>
>> How should I understand the selection score, how is it calculated? What
>> does "=>0 (1,2) walker(s)" mean?
>> For the first assessment, the selection entropy is 0.005597,
>> which is greater than the threshold 0.0, and then there is a selection
>> resampling (new 1 comes from 2). For the second
>> assessment, the selection entropy is also greater than the threshold,
>> but there is no resampling. Why is this different?
>>
>> I appreciate any of your responds.
>>
>>
>> All the best,
>> Qinghua
>>
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>> http://lists.ambermd.org/mailman/listinfo/amber
>>
>
>
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Received on Sun May 27 2018 - 14:30:01 PDT
