Hello Feng,
Thanks a lot for your reply.
A few more questions:
Leading to 0 walker means that the walker will be stayed with itself or
copied by another walker
which leads to 2 walkers?
Leading to 1 walker means that this walker might be stayed with itself or
can copied by another walker which leads to 1 walker too?
What would be the selection scores of all walkers if the ABMD with
multiple walkers is converged?
Thanks so much!
All the best,
Qinghua
On 05/28/2018 04:05 AM, Feng Pan wrote:
> Hi, Qinghua
>
> Yes, you are right, I made a mistake. I check the codes. A random number
> between 0 to 1/8
> should be added to the score.
> For example, for the first replica, if the sum is below 1/8 (like the score
> is below 1/8 and
> the random number is also small), this replica leads to zero walkers. If
> the sum is between
> 1/8 and 2/8, leads to 1 walker. The following replicas will be calculated
> to make sure the
> total number of walkers is 8.
> So basically when you see the score is below 1/8, the walker could be 0 or
> 1.
>
>
> When I say walkers will be copied, I mean the coordinates
> will be copied.
>
> Best
> Feng
>
> On Sun, May 27, 2018 at 5:08 PM, Qinghua Liao <scorpio.liao.gmail.com>
> wrote:
>
>> 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
>>>>
>>>> _______________________________________________
>>>> AMBER mailing list
>>>> AMBER.ambermd.org
>>>> http://lists.ambermd.org/mailman/listinfo/amber
>>>>
>>>
>>
>> _______________________________________________
>> AMBER mailing list
>> AMBER.ambermd.org
>> http://lists.ambermd.org/mailman/listinfo/amber
>>
>
>
_______________________________________________
AMBER mailing list
AMBER.ambermd.org
http://lists.ambermd.org/mailman/listinfo/amber
Received on Mon May 28 2018 - 06:00:05 PDT
