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Use randn! for stochastic forcing implementations #351

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Mar 11, 2024
Merged

Use randn! for stochastic forcing implementations #351

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e11e3bb
use randn! for stochastic forcing
navidcy Mar 10, 2024
f4ef394
better line break
navidcy Mar 10, 2024
feb78dc
better phrasing
navidcy Mar 10, 2024
cb37bc5
no need to use CUDA.randn
navidcy Mar 10, 2024
4a27891
add missing end
navidcy Mar 10, 2024
9ac215a
remove GeophysicalFlows
navidcy Mar 10, 2024
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1 change: 1 addition & 0 deletions docs/Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
DocumenterCitations = "daee34ce-89f3-4625-b898-19384cb65244"
GeophysicalFlows = "44ee3b1c-bc02-53fa-8355-8e347616e15e"
JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
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17 changes: 11 additions & 6 deletions examples/barotropicqgql_betaforced.jl
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Expand Up @@ -79,14 +79,19 @@ nothing #hide


# Next we construct function `calcF!` that computes a forcing realization every timestep.
# First we make sure that if `dev=GPU()`, then `CUDA.rand()` function is called for random
# numbers uniformly distributed between 0 and 1.
random_uniform = dev==CPU() ? rand : CUDA.rand
# For that, we call `randn!` to obtain complex numbers whose real and imaginary part
# are normally-distributed with zero mean and variance 1/2.
#
# We ensure that either `Random.randn!` or `CUDA.randn! is called according to the chosen
# `dev`, then `CUDA.rand()` function is called for random numbers uniformly distributed
# between 0 and 1.
random_normal! = dev==CPU() ? Random.randn! :
dev==GPU() ? CUDA.randn! :
error("dev must be CPU() or GPU()")

function calcF!(Fh, sol, t, clock, vars, params, grid)
T = eltype(grid)
@. Fh = sqrt(forcing_spectrum) * cis(2π * random_uniform(T)) / sqrt(clock.dt)

random_normal!(Fh)
@. Fh *= sqrt(forcing_spectrum) / sqrt(clock.dt)
return nothing
end
nothing #hide
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17 changes: 11 additions & 6 deletions examples/singlelayerqg_betaforced.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -80,14 +80,19 @@ nothing #hide


# Next we construct function `calcF!` that computes a forcing realization every timestep.
# First we make sure that if `dev=GPU()`, then `CUDA.rand()` function is called for random
# numbers uniformly distributed between 0 and 1.
random_uniform = dev==CPU() ? rand : CUDA.rand
# For that, we call `randn!` to obtain complex numbers whose real and imaginary part
# are normally-distributed with zero mean and variance 1/2.
#
# We ensure that either `Random.randn!` or `CUDA.randn! is called according to the chosen
# `dev`, then `CUDA.rand()` function is called for random numbers uniformly distributed
# between 0 and 1.
random_normal! = dev==CPU() ? Random.randn! :
dev==GPU() ? CUDA.randn! :
error("dev must be CPU() or GPU()")

function calcF!(Fh, sol, t, clock, vars, params, grid)
T = eltype(grid)
@. Fh = sqrt(forcing_spectrum) * cis(2π * random_uniform(T)) / sqrt(clock.dt)

random_normal!(Fh)
@. Fh *= sqrt(forcing_spectrum) / sqrt(clock.dt)
return nothing
end
nothing #hide
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17 changes: 11 additions & 6 deletions examples/twodnavierstokes_stochasticforcing.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -72,14 +72,19 @@ nothing #hide


# Next we construct function `calcF!` that computes a forcing realization every timestep.
# First we make sure that if `dev=GPU()`, then `CUDA.rand()` function is called for random
# numbers uniformly distributed between 0 and 1.
random_uniform = dev==CPU() ? rand : CUDA.rand
# For that, we call `randn!` to obtain complex numbers whose real and imaginary part
# are normally-distributed with zero mean and variance 1/2.
#
# We ensure that either `Random.randn!` or `CUDA.randn! is called according to the chosen
# `dev`, then `CUDA.rand()` function is called for random numbers uniformly distributed
# between 0 and 1.
random_normal! = dev==CPU() ? Random.randn! :
dev==GPU() ? CUDA.randn! :
error("dev must be CPU() or GPU()")

function calcF!(Fh, sol, t, clock, vars, params, grid)
T = eltype(grid)
@. Fh = sqrt(forcing_spectrum) * cis(2π * random_uniform(T)) / sqrt(clock.dt)

random_normal!(Fh)
@. Fh *= sqrt(forcing_spectrum) / sqrt(clock.dt)
return nothing
end
nothing #hide
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17 changes: 11 additions & 6 deletions examples/twodnavierstokes_stochasticforcing_budgets.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -74,14 +74,19 @@ nothing #hide


# Next we construct function `calcF!` that computes a forcing realization every timestep.
# First we make sure that if `dev=GPU()`, then `CUDA.rand()` function is called for random
# numbers uniformly distributed between 0 and 1.
random_uniform = dev==CPU() ? rand : CUDA.rand
# For that, we call `randn!` to obtain complex numbers whose real and imaginary part
# are normally-distributed with zero mean and variance 1/2.
#
# We ensure that either `Random.randn!` or `CUDA.randn! is called according to the chosen
# `dev`, then `CUDA.rand()` function is called for random numbers uniformly distributed
# between 0 and 1.
random_normal! = dev==CPU() ? Random.randn! :
dev==GPU() ? CUDA.randn! :
error("dev must be CPU() or GPU()")

function calcF!(Fh, sol, t, clock, vars, params, grid)
T = eltype(grid)
@. Fh = sqrt(forcing_spectrum) * cis(2π * random_uniform(T)) / sqrt(clock.dt)

random_normal!(Fh)
@. Fh *= sqrt(forcing_spectrum) / sqrt(clock.dt)
return nothing
end
nothing #hide
Expand Down
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