{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Chron.jl standalone age-depth model with simple Gaussian age constraints\n", "\n", "This Jupyter notebook demonstrates an example age-depth model using [Chron.jl](https://github.com/brenhinkeller/Chron.jl). For more information, see [github.com/brenhinkeller/Chron.jl](https://github.com/brenhinkeller/Chron.jl) and [doi.org/10.17605/osf.io/TQX3F](https://doi.org/10.17605/osf.io/TQX3F). \n", "\n", "\"Launch \n", "

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\n", "\n", "Hint: `shift`-`enter` to run a single cell, or from the `Cell` menu select `Run All` to run the whole file. Any code from this notebook can be copied and pasted into the Julia REPL or a `.jl` script.\n", "***\n", "\n", "## Load required Julia packages" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Load (and install if necessary) the Chron.jl package\n", "using Chron\n", "using Plots, DelimitedFiles" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "***\n", "## Enter sample information\n", "Paste your data in here!" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Input the number of samples we wish to model (must match below)\n", "nSamples = 4\n", "\n", "# Make an instance of a ChronSection object for nSamples\n", "smpl = ChronAgeData(nSamples)\n", "smpl.Name = (\"Sample 1\", \"Sample 2\", \"Sample 3\", \"Sample 4\") # Et cetera\n", "smpl.Age = [ 6991, 7088, 7230, 7540,] # Measured ages\n", "smpl.Age_sigma = [ 30, 70, 50, 50,] # Measured 1-σ uncertainties\n", "smpl.Height[:] = [ -355, -380,-397.0,-411.5,] # Depths below surface should be negative\n", "smpl.Height_sigma[:] = fill(0.01, nSamples) # Usually assume little or no sample height uncertainty\n", "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\n", "smpl.Path = \"MyData/\" # Where do you want output files to be stored\n", "\n", "smpl.Age_Unit = \"ka\"; # Unit of measurement for ages\n", "smpl.Height_Unit = \"m\"; # Unit of measurement for Height and Height_sigma" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that smpl.Height *must* increase with increasing stratigraphic height -- i.e., stratigraphically younger samples must be more positive. For this reason, it is convenient to represent depths below surface as negative numbers.\n", "\n", "***\n", "## Option A: Configure and run stratigraphic model, no hiatuses\n", "\n", "To run the stratigraphic MCMC model, we call the `StratMetropolis` function, which uses the Gaussian mean age and standard deviation set in `smpl.Age` and `smpl.Age_sigma`" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Generating stratigraphic age-depth model...\n", "Burn-in: 5660000 steps\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32mBurn-in... 100%|█████████████████████████████████████████| Time: 0:00:02\u001b[39m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Collecting sieved stationary distribution: 16980000 steps\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32mCollecting... 100%|██████████████████████████████████████| Time: 0:00:06\u001b[39m\n" ] }, { "data": { "image/png": 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Smaller is slower!\n", "config.bounding = 0.5 # how far away do we place runaway bounds, as a fraction of total section height\n", "(bottom, top) = extrema(smpl.Height)\n", "npoints_approx = round(Int,length(bottom:config.resolution:top) * (1 + 2*config.bounding))\n", "config.nsteps = 30000 # Number of steps to run in distribution MCMC\n", "config.burnin = 10000*npoints_approx # Number to discard\n", "config.sieve = round(Int,npoints_approx) # Record one out of every nsieve steps\n", "\n", "# Run the stratigraphic MCMC model\n", "(mdl, agedist, lldist) = StratMetropolis(smpl, config)\n", "\n", "# Write the results to file\n", "run(`mkdir -p $(smpl.Path)`) # Make sure that the path exists\n", "writedlm(smpl.Path*\"agedist.csv\", agedist, ',') # Stationary distribution of the age-depth model\n", "writedlm(smpl.Path*\"height.csv\", mdl.Height, ',') # Stratigraphic heights corresponding to each row of agedist\n", "writedlm(smpl.Path*\"age.csv\", mdl.Age, ',') # Mean age of resulting model\n", "writedlm(smpl.Path*\"age_025CI.csv\", mdl.Age_025CI, ',') # 2.5% confidence interval of resulting model\n", "writedlm(smpl.Path*\"age_975CI.csv\", mdl.Age_975CI, ',') # 97.5% confidence interval of resulting model\n", "writedlm(smpl.Path*\"lldist.csv\", lldist, ',') # Log likelihood distribution (to check for stationarity)\n", "\n", "# Plot the log likelihood to make sure we're converged (n.b burnin isn't recorded)\n", "hdl = plot(lldist,xlabel=\"Step number\",ylabel=\"Log likelihood\",label=\"\",line=(0.85,:darkblue))\n", "savefig(hdl,smpl.Path*\"lldist.pdf\")\n", "display(hdl)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The most important output of this process is `agedist`, which contains the full stationary distribution of the age-depth model. We can save it to a file, but if this notebook is running remotely, you may have trouble getting it out of here (see section **Getting your data out**)!\n", "***\n", "## Plot results" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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reverse(mdl.Height)], fill=(round(Int,minimum(mdl.Height)),0.5,:blue), label=\"model\")\n", "plot!(hdl, mdl.Age, mdl.Height, linecolor=:blue, label=\"\", fg_color_legend=:white) # Center line\n", "t = smpl.Age_Sidedness .== 0 # Two-sided constraints (plot in black)\n", "any(t) && plot!(hdl, smpl.Age[t], smpl.Height[t], xerror=(smpl.Age[t]-smpl.Age_025CI[t],smpl.Age_975CI[t]-smpl.Age[t]),label=\"data\",seriestype=:scatter,color=:black)\n", "t = smpl.Age_Sidedness .== 1 # Minimum ages (plot in cyan)\n", "any(t) && plot!(hdl, smpl.Age[t], smpl.Height[t], xerror=(smpl.Age[t]-smpl.Age_025CI[t],zeros(count(t))),label=\"\",seriestype=:scatter,color=:cyan,msc=:cyan)\n", "any(t) && zip(smpl.Age[t], smpl.Age[t].+nanmean(smpl.Age_sigma[t])*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label=\"\", color=:cyan)\n", "t = smpl.Age_Sidedness .== -1 # Maximum ages (plot in orange)\n", "any(t) && plot!(hdl, smpl.Age[t], smpl.Height[t], xerror=(zeros(count(t)),smpl.Age_975CI[t]-smpl.Age[t]),label=\"\",seriestype=:scatter,color=:orange,msc=:orange)\n", "any(t) && zip(smpl.Age[t], smpl.Age[t].-nanmean(smpl.Age_sigma[t])*4, smpl.Height[t]) .|> x-> plot!([x[1],x[2]],[x[3],x[3]], arrow=true, label=\"\", color=:orange)\n", "plot!(hdl, xlabel=\"Age ($(smpl.Age_Unit))\", ylabel=\"Height ($(smpl.Height_Unit))\")\n", "savefig(hdl,smpl.Path*\"AgeDepthModel.svg\")\n", "savefig(hdl,smpl.Path*\"AgeDepthModel.pdf\")\n", "display(hdl)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Interpolated age at height=-404: 7383.644684683442 +140.9269426924493/-137.6523109420841 ka" ] }, { "data": { "image/png": "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"\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Stratigraphic height at which to interpolate\n", "height = -404\n", "\n", "age_at_height = linterp1s(mdl.Height,mdl.Age,height)\n", "age_at_height_min = linterp1s(mdl.Height,mdl.Age_025CI,height)\n", "age_at_height_max = linterp1s(mdl.Height,mdl.Age_975CI,height)\n", "print(\"Interpolated age at height=$height: $age_at_height +$(age_at_height_max-age_at_height)/-$(age_at_height-age_at_height_min) $(smpl.Age_Unit)\")\n", "\n", "# Optional: interpolate full age distribution\n", "interpolated_distribution = Array{Float64}(undef,size(agedist,2))\n", "for i=1:size(agedist,2)\n", " interpolated_distribution[i] = linterp1s(mdl.Height,agedist[:,i],height)\n", "end\n", "hdl = histogram(interpolated_distribution, nbins=50, fill=(0.75,:darkblue), label=\"\")\n", "plot!(hdl, xlabel=\"Age ($(smpl.Age_Unit)) at height=$height\", ylabel=\"Likelihood (unnormalized)\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are other things we can plot as well, such as deposition rate:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 0.600877 seconds (1.69 M allocations: 418.460 MiB, 10.63% gc time, 67.73% compilation time)\n" ] }, { "data": { "image/png": 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"# binwidth = 100 # Same units as smpl.Age\n", "binoverlap = 10\n", "ages = collect(minimum(mdl.Age):binwidth/binoverlap:maximum(mdl.Age))\n", "bincenters = ages[1+Int(binoverlap/2):end-Int(binoverlap/2)]\n", "spacing = binoverlap\n", "\n", "# Calculate rates for the stratigraphy of each markov chain step\n", "dhdt_dist = Array{Float64}(undef, length(ages)-binoverlap, config.nsteps)\n", "@time for i=1:config.nsteps\n", " heights = linterp1(reverse(agedist[:,i]), reverse(mdl.Height), ages)\n", " dhdt_dist[:,i] .= abs.(heights[1:end-spacing] - heights[spacing+1:end]) ./ binwidth\n", "end\n", "\n", "# Find mean and 1-sigma (68%) CI\n", "dhdt = nanmean(dhdt_dist,dim=2)\n", "dhdt_50p = nanmedian(dhdt_dist,dim=2)\n", "dhdt_16p = nanpctile(dhdt_dist,15.865,dim=2) # Minus 1-sigma (15.865th percentile)\n", "dhdt_84p = nanpctile(dhdt_dist,84.135,dim=2) # Plus 1-sigma (84.135th percentile)\n", "# Other confidence intervals (10:10:50)\n", "dhdt_20p = nanpctile(dhdt_dist,20,dim=2)\n", "dhdt_80p = nanpctile(dhdt_dist,80,dim=2)\n", "dhdt_25p = nanpctile(dhdt_dist,25,dim=2)\n", "dhdt_75p = nanpctile(dhdt_dist,75,dim=2)\n", "dhdt_30p = nanpctile(dhdt_dist,30,dim=2)\n", "dhdt_70p = nanpctile(dhdt_dist,70,dim=2)\n", "dhdt_35p = nanpctile(dhdt_dist,35,dim=2)\n", "dhdt_65p = nanpctile(dhdt_dist,65,dim=2)\n", "dhdt_40p = nanpctile(dhdt_dist,40,dim=2)\n", "dhdt_60p = nanpctile(dhdt_dist,60,dim=2)\n", "dhdt_45p = nanpctile(dhdt_dist,45,dim=2)\n", "dhdt_55p = nanpctile(dhdt_dist,55,dim=2)\n", "\n", "# Plot results\n", "hdl = plot(bincenters,dhdt, label=\"Mean\", color=:black, linewidth=2)\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_16p; reverse(dhdt_84p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"68% CI\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_20p; reverse(dhdt_80p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_25p; reverse(dhdt_75p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_30p; reverse(dhdt_70p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_35p; reverse(dhdt_65p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_40p; reverse(dhdt_60p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,[bincenters; reverse(bincenters)],[dhdt_45p; reverse(dhdt_55p)], fill=(0,0.2,:darkblue), linealpha=0, label=\"\")\n", "plot!(hdl,bincenters,dhdt_50p, label=\"Median\", color=:grey, linewidth=1)\n", "plot!(hdl, xlabel=\"Age ($(smpl.Age_Unit))\", ylabel=\"Depositional Rate ($(smpl.Height_Unit) / $(smpl.Age_Unit) over $binwidth $(smpl.Age_Unit))\", fg_color_legend=:white)\n", "savefig(hdl,smpl.Path*\"DepositionRateModelCI.pdf\")\n", "display(hdl)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "***\n", "## Option B: Configure and run stratigraphic model, including hiatuses\n", "We can also deal with discrete hiatuses in the stratigraphic section if we know where they are and about how long they lasted. We need some different models and methods though. In particular, in addition to the `ChronAgeData` struct, we also need a `HiatusData` struct now, and will have a new `hiatusdist` output." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Generating stratigraphic age-depth model...\n", "Burn-in: 3400000 steps\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32mBurn-in... 100%|█████████████████████████████████████████| Time: 0:00:01\u001b[39m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Collecting sieved stationary distribution: 10200000 steps\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32mCollecting... 100%|██████████████████████████████████████| Time: 0:00:04\u001b[39m\n" ] }, { "data": { "image/png": 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hiatuses\n", "nHiatuses = 2 # The number of hiatuses you have data for\n", "hiatus = HiatusData(nHiatuses) # Struct to hold data\n", "hiatus.Height = [-371.5, -405.0 ]\n", "hiatus.Height_sigma = [ 0.0, 0.0 ]\n", "hiatus.Duration = [ 100.0, 123.0]\n", "hiatus.Duration_sigma = [ 30.5, 20.0]\n", "\n", "# Configure the stratigraphic Monte Carlo model\n", "config = StratAgeModelConfiguration()\n", "# If in doubt, you can probably leave these parameters as-is\n", "config.resolution = 0.2 # Same units as sample height. Smaller is slower!\n", "config.bounding = 0.1 # how far away do we place runaway bounds, as a fraction of total section height\n", "(bottom, top) = extrema(smpl.Height)\n", "npoints_approx = round(Int,length(bottom:config.resolution:top) * (1 + 2*config.bounding))\n", "config.nsteps = 30000 # Number of steps to run in distribution MCMC\n", "config.burnin = 10000*npoints_approx # Number to discard\n", "config.sieve = round(Int,npoints_approx) # Record one out of every nsieve steps\n", "\n", "# Run the model. Note the new `hiatus` argument and `hiatusdist` result\n", "(mdl, agedist, hiatusdist, lldist) = StratMetropolis(smpl, hiatus, config); sleep(0.5)\n", "\n", "# Write the results to file\n", "run(`mkdir -p $(smpl.Path)`) # Make sure that the path exists\n", "writedlm(smpl.Path*\"agedist_hiatus.csv\", agedist, ',') # Stationary distribution of the age-depth model\n", "writedlm(smpl.Path*\"height_hiatus.csv\", mdl.Height, ',') # Stratigraphic heights corresponding to each row of agedist\n", "writedlm(smpl.Path*\"age_hiatus.csv\", mdl.Age, ',') # Mean age of resulting model\n", "writedlm(smpl.Path*\"age_025CI_hiatus.csv\", mdl.Age_025CI, ',') # 2.5% confidence interval of resulting model\n", "writedlm(smpl.Path*\"age_975CI_hiatus.csv\", mdl.Age_975CI, ',') # 97.5% confidence interval of resulting model\n", "writedlm(smpl.Path*\"lldist_hiatus.csv\", lldist, ',') # Log likelihood distribution (to check for stationarity)\n", "\n", "# Plot results (mean and 95% confidence interval for both model and data)\n", "hdl = plot([mdl.Age_025CI; reverse(mdl.Age_975CI)],[mdl.Height; reverse(mdl.Height)], fill=(minimum(mdl.Height),0.5,:blue), label=\"model\")\n", "plot!(hdl, mdl.Age, mdl.Height, linecolor=:blue, label=\"\", fg_color_legend=:white)\n", "plot!(hdl, smpl.Age, smpl.Height, xerror=smpl.Age_sigma*2,label=\"data\",seriestype=:scatter,color=:black)\n", "plot!(hdl, xlabel=\"Age ($(smpl.Age_Unit))\", ylabel=\"Height ($(smpl.Height_Unit))\")\n", "savefig(hdl,smpl.Path*\"AgeDepthModelHiatus.pdf\");\n", "display(hdl)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "***\n", "## Getting your data out\n", "As shown below, we have access to the system command line, so we can use the unix command `ls` to see all the files we have written. We'll try this first using `;` to access Julia's command-line shell mode:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AgeDepthModel.pdf\n", "AgeDepthModel.svg\n", "AgeDepthModelHiatus.pdf\n", "DepositionRateModelCI.pdf\n", "age.csv\n", "age_025CI.csv\n", "age_025CI_hiatus.csv\n", "age_975CI.csv\n", "age_975CI_hiatus.csv\n", "age_hiatus.csv\n", "agedist.csv\n", "agedist_hiatus.csv\n", "height.csv\n", "height_hiatus.csv\n", "lldist.csv\n", "lldist.pdf\n", "lldist_hiatus.csv\n" ] } ], "source": [ "; ls MyData" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, we could do the same thing using the `run` function:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AgeDepthModel.pdf\n", "AgeDepthModel.svg\n", "AgeDepthModelHiatus.pdf\n", "DepositionRateModelCI.pdf\n", "age.csv\n", "age_025CI.csv\n", "age_025CI_hiatus.csv\n", "age_975CI.csv\n", "age_975CI_hiatus.csv\n", "age_hiatus.csv\n", "agedist.csv\n", "agedist_hiatus.csv\n", "height.csv\n", "height_hiatus.csv\n", "lldist.csv\n", "lldist.pdf\n", "lldist_hiatus.csv\n" ] }, { "data": { "text/plain": [ "Process(`\u001b[4mls\u001b[24m \u001b[4mMyData\u001b[24m`, ProcessExited(0))" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "run(`ls MyData`)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you're running this notebook online, getting these files out of here may be harder though. For SVG files, one option is to view them in markdown cells, which you should then be able to right click and download as real vector graphics. e.g. pasting something like\n", "```\n", "\n", "```\n", "in a markdown cell such as this one" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Meanwhile, for the csv files we could try something like `; cat agedist.csv`, but agedist is probably too big to print. Let's try using ffsend instead, which should give you a download link. In fact, while we're at it, we might as well archive and zip the entire directory!" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Make gzipped tar archive of the the whole MyData directory\n", "run(`tar -zcf archive.tar.gz ./MyData`);" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Download prebuilt ffsend linux binary\n", "isfile(\"ffsend\") || download(\"https://github.com/timvisee/ffsend/releases/download/v0.2.65/ffsend-v0.2.65-linux-x64-static\", \"ffsend\")\n", "\n", "# Make ffsend executable\n", "run(`chmod +x ffsend`);" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/bin/bash: ./ffsend: cannot execute binary file\n" ] } ], "source": [ "; ./ffsend upload archive.tar.gz" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You could alternatively use the ffsend command in this way to transfer individual files, for instance `; ./ffsend upload MyData/agedist.csv`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Keep in mind that any changes you make to this online notebook won't persist after you close the tab (or after it times out) even if you save your changes! You have to either copy-paste or `file`>`Download as` a copy.\n", "*** \n", "[![DOI](https://raw.githubusercontent.com/brenhinkeller/Chron.jl/main/readme_figures/osf_io_TQX3F.svg?sanitize=true)](https://doi.org/10.17605/osf.io/TQX3F)" ] } ], "metadata": { "@webio": { "lastCommId": null, "lastKernelId": null }, "kernelspec": { "display_name": "Julia 1.9.0-beta4", "language": "julia", "name": "julia-1.9" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "1.9.0" } }, "nbformat": 4, "nbformat_minor": 2 }