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Added reset_score subroutine. Closes #79 on github.

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Paul Romano 2012-04-01 12:41:46 -04:00
parent 1262759289
commit 821c672cc7
1 changed files with 75 additions and 59 deletions
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134
src/tally.F90
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@ -1295,46 +1295,6 @@ contains
end function get_next_bin
!===============================================================================
! ADD_TO_SCORE accumulates a scoring contribution to a specific tally bin and
! specific response function. Note that we don't need to add the square of the
! contribution since that is done at the cycle level, not the history level
!===============================================================================
subroutine add_to_score(score, val)
type(TallyScore), intent(inout) :: score
real(8), intent(in) :: val
score % n_events = score % n_events + 1
score % value = score % value + val
end subroutine add_to_score
!===============================================================================
! ACCUMULATE_SCORE accumulates scores from many histories (or many generations)
! into a single realization of a random variable.
!===============================================================================
elemental subroutine accumulate_score(score)
type(TallyScore), intent(inout) :: score
real(8) :: val
! Add the sum and square of the sum of contributions from each cycle
! within a cycle to the variables sum and sum_sq. This will later allow us
! to calculate a variance on the tallies
val = score % value/(n_particles*gen_per_batch)
score % sum = score % sum + val
score % sum_sq = score % sum_sq + val*val
! Reset the single batch estimate
score % value = ZERO
end subroutine accumulate_score
!===============================================================================
! SYNCHRONIZE_TALLIES accumulates the sum of the contributions from each history
! within the batch to a new random variable
@ -1790,25 +1750,6 @@ contains
end function get_label
!===============================================================================
! CALCULATE_STATISTICS determines the sample mean and the standard deviation of
! the mean for a TallyScore.
!===============================================================================
elemental subroutine statistics_score(score)
type(TallyScore), intent(inout) :: score
! Calculate sample mean and standard deviation of the mean -- note that we
! have used Bessel's correction so that the estimator of the variance of the
! sample mean is unbiased.
score % sum = score % sum/n_active
score % sum_sq = sqrt((score % sum_sq/n_active - score % sum**2) / &
(n_active - 1))
end subroutine statistics_score
!===============================================================================
! TALLY_STATISTICS computes the mean and standard deviation of the mean of each
! tally and stores them in the val and val_sq attributes of the TallyScores
@ -1832,4 +1773,79 @@ contains
end subroutine tally_statistics
!===============================================================================
! ADD_TO_SCORE accumulates a scoring contribution to a specific tally bin and
! specific response function. Note that we don't need to add the square of the
! contribution since that is done at the cycle level, not the history level
!===============================================================================
subroutine add_to_score(score, val)
type(TallyScore), intent(inout) :: score
real(8), intent(in) :: val
score % n_events = score % n_events + 1
score % value = score % value + val
end subroutine add_to_score
!===============================================================================
! ACCUMULATE_SCORE accumulates scores from many histories (or many generations)
! into a single realization of a random variable.
!===============================================================================
elemental subroutine accumulate_score(score)
type(TallyScore), intent(inout) :: score
real(8) :: val
! Add the sum and square of the sum of contributions from each cycle
! within a cycle to the variables sum and sum_sq. This will later allow us
! to calculate a variance on the tallies
val = score % value/(n_particles*gen_per_batch)
score % sum = score % sum + val
score % sum_sq = score % sum_sq + val*val
! Reset the single batch estimate
score % value = ZERO
end subroutine accumulate_score
!===============================================================================
! STATISTICS_SCORE determines the sample mean and the standard deviation of the
! mean for a TallyScore.
!===============================================================================
elemental subroutine statistics_score(score)
type(TallyScore), intent(inout) :: score
! Calculate sample mean and standard deviation of the mean -- note that we
! have used Bessel's correction so that the estimator of the variance of the
! sample mean is unbiased.
score % sum = score % sum/n_active
score % sum_sq = sqrt((score % sum_sq/n_active - score % sum**2) / &
(n_active - 1))
end subroutine statistics_score
!===============================================================================
! RESET_SCORE zeroes out the value and accumulated sum and sum-squared for a
! single TallyScore.
!===============================================================================
elemental subroutine reset_score(score)
type(TallyScore), intent(inout) :: score
score % n_events = 0
score % value = ZERO
score % sum = ZERO
score % sum_sq = ZERO
end subroutine reset_score
end module tally