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Rename Age_Distribution field of GeneraAgeData to just Age
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@brenhinkeller
brenhinkeller committed Jul 9, 2024
1 parent 0680917 commit ec4e16e
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Showing 5 changed files with 47 additions and 47 deletions.
2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "Chron"
uuid = "68885b1f-77b5-52a7-b2e7-6a8014c56b98"
authors = ["C. Brenhin Keller <[email protected]>"]
version = "0.6.1"
version = "0.6.2"

[deps]
DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
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20 changes: 10 additions & 10 deletions examples/Chron1.0StratOnlyGeneral.jl
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Expand Up @@ -18,10 +18,10 @@
nsamples = 5
# Make an instance of a GeneralAgeData object for n samples
smpl = GeneralAgeData(nsamples)
smpl.Name = ( "Sample 1", "Sample 2", "Sample 3", "Sample 4", "Sample 5",) # Et cetera
smpl.Age_Distribution = [Normal(39.5,0.1), Uniform(37, 38), Normal(36.3, 0.1), Uniform(33.5,34), Normal(32.1, 0.1),] # Measured ages
smpl.Height = [ 100, 200, 300, 400, 500,] # Depths below surface should be negative
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.Name = ( "Sample 1", "Sample 2", "Sample 3", "Sample 4", "Sample 5",) # Et cetera
smpl.Age = [Normal(39.5,0.1), Uniform(37, 38), Normal(36.3, 0.1), Uniform(33.5,34), Normal(32.1, 0.1),] # Measured ages
smpl.Height = [ 100, 200, 300, 400, 500,] # Depths below surface should be negative
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 = "Ma" # Unit of measurement for ages
smpl.Height_Unit = "m" # Unit of measurement for Height and Height_sigma

Expand Down Expand Up @@ -60,13 +60,13 @@
plot!(hdl, [mdl.Age_025CI; reverse(mdl.Age_975CI)],[mdl.Height; reverse(mdl.Height)], fill=(round(Int,minimum(mdl.Height)),0.5,:blue), label="model")
plot!(hdl, mdl.Age, mdl.Height, linecolor=:blue, label="") # Center line
t = smpl.Age_Sidedness .== 0 # Two-sided constraints (plot in black)
any(t) && plot!(hdl, mean.(smpl.Age_Distribution[t]), smpl.Height[t], xerror=2*std.(smpl.Age_Distribution[t]),label="data",seriestype=:scatter,color=:black)
any(t) && plot!(hdl, mean.(smpl.Age[t]), smpl.Height[t], xerror=2*std.(smpl.Age[t]),label="data",seriestype=:scatter,color=:black)
t = smpl.Age_Sidedness .== 1 # Minimum ages (plot in cyan)
any(t) && plot!(hdl, mean.(smpl.Age_Distribution[t]), smpl.Height[t], xerror=(2*std.(smpl.Age_Distribution[t]),zeros(count(t))),label="",seriestype=:scatter,color=:cyan,msc=:cyan)
any(t) && zip(mean.(smpl.Age_Distribution[t]), mean.(smpl.Age_Distribution[t]).+nanmean(std.(smpl.Age_Distribution[t]))*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label="", color=:cyan)
any(t) && plot!(hdl, mean.(smpl.Age[t]), smpl.Height[t], xerror=(2*std.(smpl.Age[t]),zeros(count(t))),label="",seriestype=:scatter,color=:cyan,msc=:cyan)
any(t) && zip(mean.(smpl.Age[t]), mean.(smpl.Age[t]).+nanmean(std.(smpl.Age[t]))*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label="", color=:cyan)
t = smpl.Age_Sidedness .== -1 # Maximum ages (plot in orange)
any(t) && plot!(hdl, mean.(smpl.Age_Distribution[t]), smpl.Height[t], xerror=(zeros(count(t)),2*std.(smpl.Age_Distribution[t])),label="",seriestype=:scatter,color=:orange,msc=:orange)
any(t) && zip(mean.(smpl.Age_Distribution[t]), mean.(smpl.Age_Distribution[t]).-nanmean(std.(smpl.Age_Distribution[t]))*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label="", color=:orange)
any(t) && plot!(hdl, mean.(smpl.Age[t]), smpl.Height[t], xerror=(zeros(count(t)),2*std.(smpl.Age[t])),label="",seriestype=:scatter,color=:orange,msc=:orange)
any(t) && zip(mean.(smpl.Age[t]), mean.(smpl.Age[t]).-nanmean(std.(smpl.Age[t]))*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label="", color=:orange)
savefig(hdl,"AgeDepthModel.pdf")
display(hdl)

Expand Down Expand Up @@ -147,7 +147,7 @@
# Plot results (mean and 95% confidence interval for both model and data)
hdl = plot([mdl.Age_025CI; reverse(mdl.Age_975CI)],[mdl.Height; reverse(mdl.Height)], fill=(minimum(mdl.Height),0.5,:blue), label="model")
plot!(hdl, mdl.Age, mdl.Height, linecolor=:blue, label="", fg_color_legend=:white)
plot!(hdl, mean.(smpl.Age_Distribution), smpl.Height, xerror=std.(smpl.Age_Distribution)*2,label="data",seriestype=:scatter,color=:black)
plot!(hdl, mean.(smpl.Age), smpl.Height, xerror=std.(smpl.Age)*2,label="data",seriestype=:scatter,color=:black)
plot!(hdl, xlabel="Age ($(smpl.Age_Unit))", ylabel="Height ($(smpl.Height_Unit))")
savefig(hdl, "Interpolated age distribution.pdf")
display(hdl)
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60 changes: 30 additions & 30 deletions src/Objects.jl
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Expand Up @@ -24,22 +24,22 @@
Sidedness_Method::Symbol
end

function ChronAgeData(nSamples::Integer)
ChronAgeData{nSamples}(
ntuple(i->"Sample name", nSamples),
collect(1.0:nSamples), # Sample Height
zeros(nSamples), # Sample Height_sigma
fill(NaN,nSamples), # Sample ages
fill(NaN,nSamples), # Sample age uncertainty
fill(NaN,nSamples), # Sample age 2.5% CI
fill(NaN,nSamples), # Sample age 97.5% CI
fill(NaN,nSamples), # Sample 14C ages
fill(NaN,nSamples), # Sample 14C uncertainties
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
zeros(nSamples), # DistType (for Distribution-fitting only: 0=distribution to be fit, 1=single Gaussian)
Vector{Vector{Float64}}(undef,nSamples), # Stationary distribution of eruption age
ntuple(i->:Chronometer, nSamples), # Age Types (e.g., :UPb or :ArAr)
fill(NaN,5,nSamples), # Sample age distribution parameters
function ChronAgeData(nsamples::Integer)
ChronAgeData{nsamples}(
ntuple(i->"Sample name", nsamples),
collect(1.0:nsamples), # Sample Height
zeros(nsamples), # Sample Height_sigma
fill(NaN,nsamples), # Sample ages
fill(NaN,nsamples), # Sample age uncertainty
fill(NaN,nsamples), # Sample age 2.5% CI
fill(NaN,nsamples), # Sample age 97.5% CI
fill(NaN,nsamples), # Sample 14C ages
fill(NaN,nsamples), # Sample 14C uncertainties
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
zeros(nsamples), # DistType (for Distribution-fitting only: 0=distribution to be fit, 1=single Gaussian)
Vector{Vector{Float64}}(undef,nsamples), # Stationary distribution of eruption age
ntuple(i->:Chronometer, nsamples), # Age Types (e.g., :UPb or :ArAr)
fill(NaN,5,nsamples), # Sample age distribution parameters
"./", # Relative path where we can find .csv data files
2, # i.e., are the data files 1-sigma or 2-sigma
"Ma",
Expand All @@ -52,22 +52,22 @@
Name::NTuple{N, String}
Height::Vector{Float64}
Height_sigma::Vector{Float64}
Age_Distribution::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
Age::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
Age_Sidedness::Vector{Float64}
Chronometer::NTuple{N, Symbol}
Age_Unit::String
Height_Unit::String
Sidedness_Method::Symbol
end

function GeneralAgeData(nSamples::Integer)
GeneralAgeData{nSamples}(
ntuple(i->"Sample name", nSamples),
collect(1.0:nSamples), # Sample Height
zeros(nSamples), # Sample Height_sigma
fill(Uniform(0,4567),nSamples), # Sample ages
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
ntuple(i->:Chronometer, nSamples), # Age Types (e.g., :UPb or :ArAr)
function GeneralAgeData(nsamples::Integer)
GeneralAgeData{nsamples}(
ntuple(i->"Sample name", nsamples),
collect(1.0:nsamples), # Sample Height
zeros(nsamples), # Sample Height_sigma
fill(Uniform(0,4567), nsamples), # Sample ages
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
ntuple(i->:Chronometer, nsamples), # Age Types (e.g., :UPb or :ArAr)
"Ma",
"m",
:cdf,
Expand All @@ -85,12 +85,12 @@
Height_Unit::String
end

function HiatusData(nHiatuses::Integer)
function HiatusData(nhiatuses::Integer)
HiatusData(
fill(NaN,nHiatuses), # Height
fill(NaN,nHiatuses), # Height_sigma
fill(NaN,nHiatuses), # Duration
fill(NaN,nHiatuses), # Duration_sigma
fill(NaN, nhiatuses), # Height
fill(NaN, nhiatuses), # Height_sigma
fill(NaN, nhiatuses), # Duration
fill(NaN, nhiatuses), # Duration_sigma
"Ma",
"m",
)
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4 changes: 2 additions & 2 deletions src/StratMetropolis.jl
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Expand Up @@ -164,7 +164,7 @@
bounding = config.bounding

# Stratigraphic age constraints
ages = unionize(smpl.Age_Distribution)::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
ages = unionize(smpl.Age)::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
Expand Down Expand Up @@ -227,7 +227,7 @@
bounding = config.bounding

# Stratigraphic age constraints
ages = unionize(smpl.Age_Distribution)::Vector{<:Union{<:Distribution{Univariate, Continuous}}}
ages = unionize(smpl.Age)::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
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8 changes: 4 additions & 4 deletions test/testStratOnlyGeneral.jl
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Expand Up @@ -2,10 +2,10 @@
nsamples = 5
# Make an instance of a GeneralAgeData object for n samples
smpl = GeneralAgeData(nsamples)
smpl.Name = ( "Sample 1", "Sample 2", "Sample 3", "Sample 4", "Sample 5",) # Et cetera
smpl.Age_Distribution = [Normal(39.5,0.1), Uniform(37, 38), Normal(36.3, 0.1), Uniform(33.5,34), Normal(32.1, 0.1),] # Measured ages
smpl.Height = [ 100, 200, 300, 400, 500,] # Depths below surface should be negative
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.Name = ( "Sample 1", "Sample 2", "Sample 3", "Sample 4", "Sample 5",) # Et cetera
smpl.Age = [Normal(39.5,0.1), Uniform(37, 38), Normal(36.3, 0.1), Uniform(33.5,34), Normal(32.1, 0.1),] # Measured ages
smpl.Height = [ 100, 200, 300, 400, 500,] # Depths below surface should be negative
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 = "Ma" # Unit of measurement for ages
smpl.Height_Unit = "m" # Unit of measurement for Height and Height_sigma
@test smpl isa GeneralAgeData
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Release notes:

  • Rename Age_Distribution field of GeneraAgeData struct to just Age

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Registration pull request created: JuliaRegistries/General/110773

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 v0.6.2 -m "<description of version>" ec4e16e684622aba8f2fcc18a3df472636727622
git push origin v0.6.2

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