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Add and test StratMetropolis functions that take GeneralAgeData i…
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@brenhinkeller
brenhinkeller committed Jul 9, 2024
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2 changes: 1 addition & 1 deletion Project.toml
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name = "Chron"
uuid = "68885b1f-77b5-52a7-b2e7-6a8014c56b98"
authors = ["C. Brenhin Keller <[email protected]>"]
version = "0.6.0"
version = "0.6.1"

[deps]
DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
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142 changes: 134 additions & 8 deletions src/StratMetropolis.jl
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Expand Up @@ -4,6 +4,7 @@
"""
```julia
StratMetropolis(smpl::ChronAgeData, [hiatus::HiatusData,] config::StratAgeModelConfiguration)
StratMetropolis(smpl::GeneralAgeData, [hiatus::HiatusData,] config::StratAgeModelConfiguration)
```
Runs the main Chron.jl age-depth model routine for a stratigraphic set of
samples defined by sample heights and simple Gaussian age constraints in the
Expand Down Expand Up @@ -39,7 +40,7 @@
Height = copy(smpl.Height)::Vector{Float64}
Height_sigma = smpl.Height_sigma::Vector{Float64} .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = copy(smpl.Age_Sidedness)::Vector{Float64} # Bottom is a maximum age and top is a minimum age
Chronometer = smpl.Chronometer
chronometer = smpl.Chronometer
(bottom, top) = extrema(Height)
model_heights = bottom:resolution:top

Expand All @@ -60,7 +61,7 @@
Height_sigma = [0; Height_sigma; 0] .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = [-1.0; Age_Sidedness; 1.0;] # Bottom is a maximum age and top is a minimum age
model_heights = (bottom-offset):resolution:(top+offset)
Chronometer = (:None, Chronometer..., :None)
chronometer = (:None, chronometer..., :None)
end
active_height_t = bottom .<= model_heights .<= top

Expand All @@ -77,7 +78,7 @@

# Run the Markov chain
ages = Normal.(Age, Age_sigma)
agedist, lldist = stratmetropolis(Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve, Chronometer, systematic)
agedist, lldist = stratmetropolis(Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve, chronometer, systematic)

# Crop the result
agedist = agedist[active_height_t,:]
Expand All @@ -86,7 +87,7 @@

return mdl, agedist, lldist
end
function StratMetropolis(smpl::ChronAgeData, hiatus::HiatusData, config::StratAgeModelConfiguration)
function StratMetropolis(smpl::ChronAgeData, hiatus::HiatusData, config::StratAgeModelConfiguration, systematic=nothing)
# Run stratigraphic MCMC model, with hiata
@info "Generating stratigraphic age-depth model..."

Expand All @@ -103,6 +104,7 @@
Height = copy(smpl.Height)::Vector{Float64}
Height_sigma = smpl.Height_sigma::Vector{Float64} .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = copy(smpl.Age_Sidedness)::Vector{Float64} # Bottom is a maximum age and top is a minimum age
chronometer = smpl.Chronometer
(bottom, top) = extrema(Height)
model_heights = bottom:resolution:top

Expand All @@ -123,6 +125,7 @@
Height_sigma = [0; Height_sigma; 0] .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = [-1.0; Age_Sidedness; 1.0;] # Bottom is a maximum age and top is a minimum age
model_heights = (bottom-offset):resolution:(top+offset)
chronometer = (:None, chronometer..., :None)
end
active_height_t = bottom .<= model_heights .<= top
npoints = length(model_heights)
Expand All @@ -140,7 +143,133 @@

# Run the Markov chain
ages = Normal.(Age, Age_sigma)
agedist, lldist, hiatusdist = stratmetropolis(hiatus, Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve)
agedist, lldist, hiatusdist = stratmetropolis(hiatus, Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve, chronometer, systematic)

# Crop the result
agedist = agedist[active_height_t,:]
model_heights = model_heights[active_height_t]
mdl = StratAgeModel(model_heights, agedist)

return mdl, agedist, hiatusdist, lldist
end
function StratMetropolis(smpl::GeneralAgeData, config::StratAgeModelConfiguration, systematic=nothing)
# Run stratigraphic MCMC model
@info "Generating stratigraphic age-depth model..."

# Model configuration -- read from struct
resolution = config.resolution
burnin = config.burnin
nsteps = config.nsteps
sieve = config.sieve
bounding = config.bounding

# Stratigraphic age constraints
ages = unionize(smpl.Age_Distribution)::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
Height = copy(smpl.Height)::Vector{Float64}
Height_sigma = smpl.Height_sigma::Vector{Float64} .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = copy(smpl.Age_Sidedness)::Vector{Float64} # Bottom is a maximum age and top is a minimum age
chronometer = smpl.Chronometer
(bottom, top) = extrema(Height)
model_heights = bottom:resolution:top

aveuncert = nanmean(std.(ages))
absdiff = diff(sort!(mean.(ages[Age_Sidedness.==0])))
maxdiff = isempty(absdiff) ? 0.0 : nanmaximum(absdiff)
proposal_sigma = sqrt(aveuncert^2 + (maxdiff/10)^2)

if bounding>0
# If bounding is requested, add extrapolated top and bottom bounds to avoid
# issues with the stratigraphic markov chain wandering off to +/- infinity
(youngest, oldest) = extrema(mean.(ages))
dt_dH = (oldest-youngest)/(top-bottom)
offset = round((top-bottom)*bounding/resolution)*resolution
ages = unionize([Normal(oldest+offset*dt_dH, aveuncert/10);
ages;
Normal(youngest-offset*dt_dH, aveuncert/10)])
Height = [bottom-offset; Height; top+offset]
Height_sigma = [0; Height_sigma; 0] .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = [-1.0; Age_Sidedness; 1.0;] # Bottom is a maximum age and top is a minimum age
model_heights = (bottom-offset):resolution:(top+offset)
chronometer = (:None, chronometer..., :None)
end
active_height_t = bottom .<= model_heights .<= top

# Start with a linear fit as an initial proposal
(a,b) = hcat(fill!(similar(Height), 1), Height) \ mean.(ages)
model_ages = a .+ b .* collect(model_heights)

# Select sidedness method
sidedness = if smpl.Sidedness_Method === :fast || all(iszero, smpl.Age_Sidedness)
FastSidedness(Age_Sidedness)
else
CDFSidedness(Age_Sidedness)
end

# Run the Markov chain
agedist, lldist = stratmetropolis(Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve, chronometer, systematic)

# Crop the result
agedist = agedist[active_height_t,:]
model_heights = model_heights[active_height_t]
mdl = StratAgeModel(model_heights, agedist)

return mdl, agedist, lldist
end
function StratMetropolis(smpl::GeneralAgeData, hiatus::HiatusData, config::StratAgeModelConfiguration, systematic=nothing)
# Run stratigraphic MCMC model
@info "Generating stratigraphic age-depth model..."

# Model configuration -- read from struct
resolution = config.resolution
burnin = config.burnin
nsteps = config.nsteps
sieve = config.sieve
bounding = config.bounding

# Stratigraphic age constraints
ages = unionize(smpl.Age_Distribution)::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
Height = copy(smpl.Height)::Vector{Float64}
Height_sigma = smpl.Height_sigma::Vector{Float64} .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = copy(smpl.Age_Sidedness)::Vector{Float64} # Bottom is a maximum age and top is a minimum age
chronometer = smpl.Chronometer
(bottom, top) = extrema(Height)
model_heights = bottom:resolution:top

aveuncert = nanmean(std.(ages))
absdiff = diff(sort!(mean.(ages[Age_Sidedness.==0])))
maxdiff = isempty(absdiff) ? 0.0 : nanmaximum(absdiff)
proposal_sigma = sqrt(aveuncert^2 + (maxdiff/10)^2)

if bounding>0
# If bounding is requested, add extrapolated top and bottom bounds to avoid
# issues with the stratigraphic markov chain wandering off to +/- infinity
(youngest, oldest) = extrema(mean.(ages))
dt_dH = (oldest-youngest)/(top-bottom)
offset = round((top-bottom)*bounding/resolution)*resolution
ages = unionize([Normal(oldest+offset*dt_dH, aveuncert/10);
ages;
Normal(youngest-offset*dt_dH, aveuncert/10)])
Height = [bottom-offset; Height; top+offset]
Height_sigma = [0; Height_sigma; 0] .+ 1E-9 # Avoid divide-by-zero issues
Age_Sidedness = [-1.0; Age_Sidedness; 1.0;] # Bottom is a maximum age and top is a minimum age
model_heights = (bottom-offset):resolution:(top+offset)
chronometer = (:None, chronometer..., :None)
end
active_height_t = bottom .<= model_heights .<= top

# Start with a linear fit as an initial proposal
(a,b) = hcat(fill!(similar(Height), 1), Height) \ mean.(ages)
model_ages = a .+ b .* collect(model_heights)

# Select sidedness method
sidedness = if smpl.Sidedness_Method === :fast || all(iszero, smpl.Age_Sidedness)
FastSidedness(Age_Sidedness)
else
CDFSidedness(Age_Sidedness)
end

# Run the Markov chain
agedist, lldist, hiatusdist = stratmetropolis(hiatus, Height, Height_sigma, model_heights, sidedness, ages, model_ages, proposal_sigma, burnin, nsteps, sieve, chronometer, systematic)

# Crop the result
agedist = agedist[active_height_t,:]
Expand Down Expand Up @@ -401,9 +530,6 @@

return mdl, agedist, lldist
end

## --- Stratigraphic MCMC model with hiatus, for radiocarbon ages # # # # # #

function StratMetropolis14C(smpl::ChronAgeData, hiatus::HiatusData, config::StratAgeModelConfiguration)
# Run stratigraphic MCMC model, with hiata
@info "Generating stratigraphic age-depth model..."
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5 changes: 4 additions & 1 deletion test/runtests.jl
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Expand Up @@ -4,6 +4,9 @@ using Test, Statistics, Distributions
const make_plots = get(ENV, "MAKE_PLOTS", false) == "true"
@testset "Utilities" begin include("testUtilities.jl") end
@testset "Eruption / deposition age distributions" begin include("testDist.jl") end
@testset "Strat only" begin include("testStratOnly.jl") end
@testset "Strat only" begin
include("testStratOnly.jl")
include("testStratOnlyGeneral.jl")
end
@testset "Radiocarbon" begin include("testRadiocarbon.jl") end
@testset "Coupled model" begin include("testCoupled.jl") end
12 changes: 6 additions & 6 deletions test/testCoupled.jl
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## --- Standard coupled eruption-deposition modelling

nSamples = 5 # The number of samples you have data for
smpl = ChronAgeData(nSamples)
nsamples = 5 # The number of samples you have data for
smpl = ChronAgeData(nsamples)
smpl.Name = ("KJ08-157", "KJ04-75", "KJ09-66", "KJ04-72", "KJ04-70",)
smpl.Height .= [ -52.0, 44.0, 54.0, 82.0, 93.0,]
smpl.Height_sigma .= [ 3.0, 1.0, 3.0, 3.0, 3.0,]
smpl.Age_Sidedness .= zeros(nSamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Age_Sidedness .= zeros(nsamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Path = abspath("../examples/DenverUPbExampleData/") # Where are the data files?
smpl.inputSigmaLevel = 2 # i.e., are the data files 1-sigma or 2-sigma. Integer.
smpl.Age_Unit = "Ma" # Unit of measurement for ages and errors in the data files
Expand Down Expand Up @@ -124,11 +124,11 @@ println("StratMetropolisDist with fitted Gaussians:")

## -- Test coupled with Isoplot.jl Pb-loss-aware eruption ages

nSamples = 3 # The number of samples you have data for
smpl = ChronAgeData(nSamples)
nsamples = 3 # The number of samples you have data for
smpl = ChronAgeData(nsamples)
smpl.Name = ("KR18-04", "KR18-01", "KR18-05")
smpl.Height .= [ 0.0, 100.0, 200.0] # Arbitrary heights
smpl.Age_Sidedness .= zeros(nSamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Age_Sidedness .= zeros(nsamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Path = abspath("../examples/ConcordiaExampleData/") # Where are the data files?
smpl.inputSigmaLevel = 1 # i.e., are the data files 1-sigma or 2-sigma. Integer.
smpl.Age_Unit = "Ma" # Unit of measurement for ages and errors in the data files
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18 changes: 9 additions & 9 deletions test/testRadiocarbon.jl
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Expand Up @@ -7,15 +7,15 @@
## --- Test age-depth model

# Input the number of samples we wish to model (must match below)
nSamples = 4
# Make an instance of a ChronSection object for nSamples
smpl = ChronAgeData(nSamples)
nsamples = 4
# Make an instance of a ChronSection object for nsamples
smpl = ChronAgeData(nsamples)
smpl.Name = ("Sample 1", "Sample 2", "Sample 3", "Sample 4") # Et cetera
smpl.Age_14C .= [ 6991, 7088, 7230, 7540,] # Measured ages
smpl.Age_14C_sigma .= [ 30, 70, 50, 50,] # Measured 1-σ uncertainties
smpl.Height .= [ -355, -380,-397.0,-411.5,] # Depths below surface should be negative
smpl.Height_sigma .= fill(0.01, nSamples) # Usually assume little or no sample height uncertainty
smpl.Age_Sidedness .= zeros(nSamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Height_sigma .= fill(0.01, nsamples) # Usually assume little or no sample height uncertainty
smpl.Age_Sidedness .= zeros(nsamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Age_Unit = "Years BP" # Unit of measurement for ages
smpl.Height_Unit = "m" # Unit of measurement for Height and Height_sigma

Expand All @@ -24,8 +24,8 @@ smpl.Height_Unit = "m" # Unit of measurement for Height and Height_sigma
calibration = intcal13

# Calculate calendar age PDFs for each sample
smpl.Params = fill(NaN, length(calibration.Age_Calendar), nSamples)
for i = 1:nSamples
smpl.Params = fill(NaN, length(calibration.Age_Calendar), nsamples)
for i = 1:nsamples
# The likelihood that a measured 14C age could result from a sample of
# a given calendar age is proportional to the intergral of the product
# of the two respective distributions
Expand Down Expand Up @@ -98,8 +98,8 @@ hiatus.Duration_sigma = [ 30.5, 20.0 ]
calibration = intcal20

# Calculate calendar age PDFs for each sample
smpl.Params = fill(NaN, length(calibration.Age_Calendar), nSamples)
for i = 1:nSamples
smpl.Params = fill(NaN, length(calibration.Age_Calendar), nsamples)
for i = 1:nsamples
# The likelihood that a measured 14C age could result from a sample of
# a given calendar age is proportional to the intergral of the product
# of the two respective distributions
Expand Down
17 changes: 5 additions & 12 deletions test/testStratOnly.jl
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@@ -1,13 +1,13 @@
# Make an instance of a ChronAgeData object for nSamples
nSamples = 6
smpl = ChronAgeData(nSamples)
# Make an instance of a ChronAgeData object for nsamples
nsamples = 6
smpl = ChronAgeData(nsamples)
@test smpl isa ChronAgeData
smpl.Name = ("minimum age", "Sample 1", "Sample 2", "Sample 3", "Sample 4", "maximum age") # Et cetera
smpl.Age .= [ 690.0, 699.1, 708.8, 723.0, 754.0, 812.0] # Measured ages
smpl.Age_sigma .= [ 7.0, 3.0, 7.0, 5.0, 5.0, 6.0] # Measured 1-σ uncertainties
smpl.Height .= [-350.0, -355.0, -380.0, -397.0, -411.5, -420.0] # Depths below surface should be negative
smpl.Height_sigma .= fill(0.01, nSamples) # Usually assume little or no sample height uncertainty
smpl.Age_Sidedness .= zeros(nSamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Height_sigma .= fill(0.01, nsamples) # Usually assume little or no sample height uncertainty
smpl.Age_Sidedness .= zeros(nsamples) # Sidedness (zeros by default: geochron constraints are two-sided). Use -1 for a maximum age and +1 for a minimum age, 0 for two-sided
smpl.Age_Sidedness[1] = 1. # Minimum age
smpl.Age_Sidedness[end] = -1. # Maximum age
smpl.Age_Unit = "Years BP" # Unit of measurement for ages
Expand Down Expand Up @@ -60,10 +60,3 @@ hiatus.Duration_sigma = [ 3.1, 2.0 ]
@test size(hiatusdist) == (nHiatuses, config.nsteps)
@test mean(hiatusdist, dims=2) ≈ [10.580012942504894; 18.96167245288326;;] atol=2
@test -Inf < mean(lldist) < 0

## --- Strat only, general Distributions-based case

# Make an instance of a ChronAgeData object for nSamples
nSamples = 4
smpl = GeneralAgeData(nSamples)
@test smpl isa GeneralAgeData
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Release notes:

  • Add and test StratMetropolis functions that take GeneralAgeData objects as an input

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Registration pull request created: JuliaRegistries/General/110769

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.6.1 -m "<description of version>" 9fc0987660f96eb8a5a8f639d7cc27edac6232b3
git push origin v0.6.1

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