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Removing need to have coeffs (inout) in the scattdata_init routines
This commit is contained in:
Adam Nelson
parent
33f74b5c90
commit
8088eda6fd
1 changed files with 45 additions and 31 deletions
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@ -49,7 +49,7 @@ module scattdata_header
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import ScattData
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class(ScattData), intent(inout) :: this ! Scattering Object to work with
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real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix
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real(8), intent(inout) :: coeffs(:,:,:) ! Coefficients to use
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real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use
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end subroutine scattdata_init_
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pure function scattdata_calc_f_(this, gin, gout, mu) result(f)
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@ -169,31 +169,36 @@ contains
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subroutine scattdatalegendre_init(this, mult, coeffs)
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class(ScattDataLegendre), intent(inout) :: this ! Object to work on
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real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix
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real(8), intent(inout) :: coeffs(:,:,:) ! Coefficients to use
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real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use
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real(8) :: dmu, mu, f, norm
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integer :: imu, Nmu, gout, gin, groups, order
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real(8), allocatable :: energy(:,:)
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real(8), allocatable :: matrix(:,:,:)
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groups = size(coeffs,dim=3)
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order = size(coeffs,dim=1)
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! Get scattxs value first before anything happens to coeffs
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! make a copy of coeffs that we can use to extract data and normalize
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allocate(matrix(order,groups,groups))
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matrix = coeffs
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! Get scattxs value
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allocate(this % scattxs(groups))
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! Get this by summing the now un-normalized P0 coefficient in coeffs
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! Get this by summing the un-normalized P0 coefficient in matrix
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! over all outgoing groups
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this % scattxs = sum(coeffs(1,:,:),dim=1)
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this % scattxs = sum(matrix(1,:,:),dim=1)
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allocate(energy(groups,groups))
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energy = ZERO
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! Build energy transfer probability matrix from data in coeffs
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! while also normalizing coeffs itself (making CDF of f(mu=1)=1)
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! Build energy transfer probability matrix from data in matrix
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! while also normalizing matrix itself (making CDF of f(mu=1)=1)
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do gin = 1, groups
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do gout = 1, groups
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norm = coeffs(1,gout,gin)
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norm = matrix(1,gout,gin)
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energy(gout,gin) = norm
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if (norm /= ZERO) then
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coeffs(:,gout,gin) = coeffs(:,gout,gin) / norm
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matrix(:,gout,gin) = matrix(:,gout,gin) / norm
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end if
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end do
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end do
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@ -201,10 +206,10 @@ contains
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call scattdata_init(this, order, energy, mult)
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allocate(this % max_val(groups))
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! Set dist values from coeffs and initialize max_val
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! Set dist values from matrix and initialize max_val
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do gin = 1, groups
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do gout = this % gmin(gin), this % gmax(gin)
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this % dist(gin) % data(:,gout) = coeffs(:,gout,gin)
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this % dist(gin) % data(:,gout) = matrix(:,gout,gin)
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end do
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allocate(this % max_val(gin) % data(this % gmin(gin):this % gmax(gin)))
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this % max_val(gin) % data = ZERO
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@ -240,32 +245,37 @@ contains
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subroutine scattdatahistogram_init(this, mult, coeffs)
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class(ScattDataHistogram), intent(inout) :: this ! Object to work on
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real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix
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real(8), intent(inout) :: coeffs(:,:,:) ! Coefficients to use
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real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix
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real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use
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integer :: imu, gin, gout, groups, order
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real(8) :: norm
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real(8), allocatable :: energy(:,:)
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real(8), allocatable :: matrix(:,:,:)
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groups = size(coeffs,dim=3)
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order = size(coeffs,dim=1)
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! Get scattxs value first before anything happens to coeffs
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! make a copy of coeffs that we can use to extract data and normalize
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allocate(matrix(order,groups,groups))
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matrix = coeffs
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! Get scattxs value
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allocate(this % scattxs(groups))
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! Get this by summing the now un-normalized P0 coefficient in coeffs
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! Get this by summing the un-normalized P0 coefficient in matrix
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! over all outgoing groups
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this % scattxs = sum(sum(coeffs(:,:,:),dim=1),dim=1)
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this % scattxs = sum(sum(matrix(:,:,:),dim=1),dim=1)
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allocate(energy(groups,groups))
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energy = ZERO
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! Build energy transfer probability matrix from data in coeffs
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! while also normalizing coeffs itself (making CDF of f(mu=1)=1)
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! Build energy transfer probability matrix from data in matrix
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! while also normalizing matrix itself (making CDF of f(mu=1)=1)
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do gin = 1, groups
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do gout = 1, groups
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norm = sum(coeffs(:,gout,gin))
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norm = sum(matrix(:,gout,gin))
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energy(gout,gin) = norm
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if (norm /= ZERO) then
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coeffs(:,gout,gin) = coeffs(:,gout,gin) / norm
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matrix(:,gout,gin) = matrix(:,gout,gin) / norm
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end if
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end do
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end do
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@ -287,11 +297,11 @@ contains
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this % gmin(gin):this % gmax(gin)))
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do gout = this % gmin(gin), this % gmax(gin)
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! Store the histogram
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this % fmu(gin) % data(:,gout) = coeffs(:,gout,gin)
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this % fmu(gin) % data(:,gout) = matrix(:,gout,gin)
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! Integrate the histogram
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this % dist(gin) % data(1,gout) = this % dmu * coeffs(1,gout,gin)
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this % dist(gin) % data(1,gout) = this % dmu * matrix(1,gout,gin)
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do imu = 2, order
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this % dist(gin) % data(imu,gout) = this % dmu * coeffs(imu,gout,gin) + &
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this % dist(gin) % data(imu,gout) = this % dmu * matrix(imu,gout,gin) + &
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this % dist(gin) % data(imu - 1,gout)
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end do
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@ -309,15 +319,20 @@ contains
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subroutine scattdatatabular_init(this, mult, coeffs)
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class(ScattDataTabular), intent(inout) :: this ! Object to work on
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real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix
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real(8), intent(inout) :: coeffs(:,:,:) ! Coefficients to use
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real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use
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integer :: imu, gin, gout, groups, order
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real(8) :: norm
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real(8), allocatable :: energy(:,:)
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real(8), allocatable :: matrix(:,:,:)
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groups = size(coeffs,dim=3)
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order = size(coeffs,dim=1)
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! make a copy of coeffs that we can use to extract data and normalize
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allocate(matrix(order,groups,groups))
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matrix = coeffs
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! Build the angular distribution mu values
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allocate(this % mu(order))
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this % dmu = TWO / real(order - 1,8)
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@ -327,7 +342,7 @@ contains
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end do
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this % mu(order) = ONE
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! Get scattxs before anything happens to coeffs
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! Get scattxs
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allocate(this % scattxs(groups))
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! Get this by integrating the scattering distribution over all mu points
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! and then combining over all outgoing groups
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@ -336,8 +351,8 @@ contains
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norm = ZERO
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do gout = 1, groups
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do imu = 2, order
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norm = norm + HALF * this % dmu * (coeffs(imu - 1,gout,gin) + &
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coeffs(imu,gout,gin))
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norm = norm + HALF * this % dmu * (matrix(imu - 1,gout,gin) + &
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matrix(imu,gout,gin))
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end do
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end do
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this % scattxs(gin) = norm
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@ -345,15 +360,14 @@ contains
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allocate(energy(groups,groups))
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energy = ZERO
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! Build energy transfer probability matrix from data in coeffs
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! Build energy transfer probability matrix from data in matrix
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do gin = 1, groups
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do gout = 1, groups
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norm = ZERO
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do imu = 2, order
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norm = norm + HALF * this % dmu * &
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(coeffs(imu - 1,gout,gin) + coeffs(imu,gout,gin))
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(matrix(imu - 1,gout,gin) + matrix(imu,gout,gin))
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end do
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! energy(gout,gin) = sum(coeffs(:,gout,gin))
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energy(gout,gin) = norm
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end do
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end do
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@ -367,7 +381,7 @@ contains
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do gout = this % gmin(gin), this % gmax(gin)
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! Coeffs contain f(mu), put in f(mu) as that is where the
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! PDF lives
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this % fmu(gin) % data(:,gout) = coeffs(:,gout,gin)
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this % fmu(gin) % data(:,gout) = matrix(:,gout,gin)
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! Force positivity
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do imu = 1, order
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