{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "002cd541-3c41-446a-8092-f6a48de22ac5", "metadata": { "tags": [] }, "outputs": [], "source": [ "import CSV\n", "import TypedTables: Table, columnnames\n", "import Printf: @sprintf, @printf # For converting numbers to strings\n", "import LinearAlgebra: BLAS\n", "BLAS.set_num_threads(1) # BFGS uses BLAS operations, but they are relatively small so it's actually more efficient to run BLAS single-threaded." ] }, { "cell_type": "markdown", "id": "affc1ba4-b8c1-43cc-9dfb-b3256faa5445", "metadata": { "tags": [] }, "source": [ "Load the isochrone table using `CSV.read` into a `TypedTables.Table` structure. This contains an isochrone table from PARSEC that has 26 steps in [M/H] and 71 steps in `logAge=log10(age [yr])` for a total of 1846 unique isochrones. For this example, this isochrone table actually has more steps in `logAge` than we want to use, so we will only use a subset of the available isochrones. In particular, the spacing of `ΔlogAge=0.05` dex results in the most recent time bins (`logAge < 8`) having too little stellar mass to measure robustly." ] }, { "cell_type": "code", "execution_count": 2, "id": "93643d0d-4f2e-40c3-b8b7-c8e81e4e5bf8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Table with 50 columns and 709192 rows:\n", " Zini MH logAge Mini int_IMF Mass logL logTe ⋯\n", " ┌─────────────────────────────────────────────────────────────────────────\n", " 1 │ 2.4652e-5 -2.19174 6.6 0.1 1.17111 0.1 -1.436 3.5769 ⋯\n", " 2 │ 2.4652e-5 -2.19174 6.6 0.105145 1.2127 0.105 -1.411 3.5791 ⋯\n", " 3 │ 2.4652e-5 -2.19174 6.6 0.109821 1.24828 0.109 -1.387 3.5809 ⋯\n", " 4 │ 2.4652e-5 -2.19174 6.6 0.124 1.34512 0.124 -1.321 3.5865 ⋯\n", " 5 │ 2.4652e-5 -2.19174 6.6 0.129464 1.37867 0.129 -1.298 3.5885 ⋯\n", " 6 │ 2.4652e-5 -2.19174 6.6 0.140418 1.4407 0.14 -1.252 3.5923 ⋯\n", " 7 │ 2.4652e-5 -2.19174 6.6 0.149107 1.4856 0.149 -1.219 3.595 ⋯\n", " 8 │ 2.4652e-5 -2.19174 6.6 0.183261 1.63379 0.182 -1.1 3.6048 ⋯\n", " 9 │ 2.4652e-5 -2.19174 6.6 0.197245 1.68445 0.196 -1.057 3.6085 ⋯\n", " 10 │ 2.4652e-5 -2.19174 6.6 0.207292 1.71805 0.206 -1.029 3.6111 ⋯\n", " 11 │ 2.4652e-5 -2.19174 6.6 0.210274 1.72762 0.209 -1.021 3.6119 ⋯\n", " 12 │ 2.4652e-5 -2.19174 6.6 0.225868 1.77492 0.225 -0.977 3.6159 ⋯\n", " 13 │ 2.4652e-5 -2.19174 6.6 0.246817 1.83218 0.246 -0.925 3.621 ⋯\n", " 14 │ 2.4652e-5 -2.19174 6.6 0.261505 1.86868 0.261 -0.893 3.6246 ⋯\n", " 15 │ 2.4652e-5 -2.19174 6.6 0.285683 1.92332 0.285 -0.84 3.6305 ⋯\n", " 16 │ 2.4652e-5 -2.19174 6.6 0.307343 1.96739 0.307 -0.796 3.6357 ⋯\n", " 17 │ 2.4652e-5 -2.19174 6.6 0.33773 2.02284 0.337 -0.737 3.6427 ⋯\n", " 18 │ 2.4652e-5 -2.19174 6.6 0.355357 2.05211 0.355 -0.705 3.6465 ⋯\n", " 19 │ 2.4652e-5 -2.19174 6.6 0.366732 2.07002 0.366 -0.685 3.6492 ⋯\n", " 20 │ 2.4652e-5 -2.19174 6.6 0.404464 2.12461 0.404 -0.62 3.6576 ⋯\n", " 21 │ 2.4652e-5 -2.19174 6.6 0.436853 2.16644 0.436 -0.569 3.6643 ⋯\n", " 22 │ 2.4652e-5 -2.19174 6.6 0.453571 2.18648 0.453 -0.544 3.6677 ⋯\n", " 23 │ 2.4652e-5 -2.19174 6.6 0.457007 2.19048 0.457 -0.539 3.6683 ⋯\n", " ⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "table = CSV.read(\"../../../../Work/Resources/isochrones/parsec/jwst/nircam_nov22/table.dat\", Table; comment=\"#\", delim=' ', ignorerepeated=true, \n", " header=[\"Zini\", \"MH\", \"logAge\", \"Mini\", \"int_IMF\", \"Mass\", \"logL\", \"logTe\", \"logg\", \"label\", \"McoreTP\", \"C_O\", \"period0\", \"period1\", \"period2\", \n", " \"period3\", \"period4\", \"pmode\", \"Mloss\", \"tau1m\", \"X\", \"Y\", \"Xc\", \"Xn\", \"Xo\", \"Cexcess\", \"Z\", \"mbolmag\", \"F070W\", \"F090W\", \"F115W\", \n", " \"F150W\", \"F200W\", \"F277W\", \"F356W\", \"F444W\", \"F150W2\", \"F322W2\", \"F140M\", \"F162M\", \"F182M\", \"F210M\", \"F250M\", \"F300M\", \"F335M\", \n", " \"F360M\", \"F410M\", \"F430M\", \"F460M\", \"F480M\"])" ] }, { "cell_type": "markdown", "id": "f4453708-dcec-4859-a337-8d1ee10da379", "metadata": {}, "source": [ "Check the available columns in the table" ] }, { "cell_type": "code", "execution_count": 3, "id": "7b453c29-3569-4d6d-a121-3d87df302d1d", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(:Zini, :MH, :logAge, :Mini, :int_IMF, :Mass, :logL, :logTe, :logg, :label, :McoreTP, :C_O, :period0, :period1, :period2, :period3, :period4, :pmode, :Mloss, :tau1m, :X, :Y, :Xc, :Xn, :Xo, :Cexcess, :Z, :mbolmag, :F070W, :F090W, :F115W, :F150W, :F200W, :F277W, :F356W, :F444W, :F150W2, :F322W2, :F140M, :F162M, :F182M, :F210M, :F250M, :F300M, :F335M, :F360M, :F410M, :F430M, :F460M, :F480M)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "columnnames(table)" ] }, { "cell_type": "code", "execution_count": 4, "id": "5b1f0e60-a550-4751-a30e-3f4f4596efd8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "71-element Vector{Float64}:\n", " 6.6\n", " 6.65\n", " 6.7\n", " 6.75\n", " 6.8\n", " 6.85\n", " 6.9\n", " 6.95\n", " 7.0\n", " 7.05\n", " 7.1\n", " 7.15\n", " 7.2\n", " ⋮\n", " 9.55001\n", " 9.60001\n", " 9.65001\n", " 9.70001\n", " 9.75001\n", " 9.80001\n", " 9.85001\n", " 9.90001\n", " 9.95001\n", " 10.00001\n", " 10.05001\n", " 10.10001" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "unique(table.logAge) # These are `log10(age)`, where the age is in years." ] }, { "cell_type": "markdown", "id": "28ecab1d-69c8-4bb4-8ab0-e5eec8282e09", "metadata": {}, "source": [ "For the most metal-poor PARSEC isochrones (e.g., -2.2 [M/H]), there are multiple individual isochrones with the same [M/H] but different `Zini`. This can be seen as `length(unique(table.Zini)) > length(unique(table.MH))` below." ] }, { "cell_type": "code", "execution_count": 5, "id": "d36ef094-3948-40be-9cec-1b8d1ddbacc8", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "26-element Vector{Float64}:\n", " -2.19174\n", " -2.1\n", " -2.0\n", " -1.9\n", " -1.8\n", " -1.7\n", " -1.6\n", " -1.5\n", " -1.4\n", " -1.3\n", " -1.2\n", " -1.1\n", " -1.0\n", " -0.9\n", " -0.8\n", " -0.7\n", " -0.6\n", " -0.5\n", " -0.4\n", " -0.3\n", " -0.2\n", " -0.1\n", " 0.0\n", " 0.1\n", " 0.2\n", " 0.3" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "unique(table.MH) # These are metallicities, [M/H]" ] }, { "cell_type": "code", "execution_count": 6, "id": "61d75162-ffd1-4588-877b-ee18eda68985", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "29-element Vector{Float64}:\n", " 2.4652e-5\n", " 3.1035e-5\n", " 3.9069e-5\n", " 4.9184e-5\n", " 0.00012351\n", " 0.00015547\n", " 0.0001957\n", " 0.00024632\n", " 0.00031003\n", " 0.00039019\n", " 0.00049103\n", " 0.00061788\n", " 0.00077741\n", " ⋮\n", " 0.0024432\n", " 0.0030686\n", " 0.0038518\n", " 0.0048313\n", " 0.0060543\n", " 0.0075779\n", " 0.0094713\n", " 0.011816\n", " 0.01471\n", " 0.018261\n", " 0.022594\n", " 0.027842" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "unique(table.Zini)" ] }, { "cell_type": "markdown", "id": "b73ea4b3-50c3-4619-bbc9-f7dee8596655", "metadata": {}, "source": [ "For bookkeeping purposes, it is simplest for each isochrone to be identifiable by a unique [M/H], so we we will use the `Zini` values to calculate new [M/H] values. These are now *initial* metallicities. " ] }, { "cell_type": "code", "execution_count": 7, "id": "faa7cd65-752f-4fb0-8635-154a8a35a680", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32m\u001b[1mPrecompiling\u001b[22m\u001b[39m StarFormationHistories\n", "\u001b[32m ✓ \u001b[39mStarFormationHistories\n", "\u001b[32m ✓ \u001b[39m\u001b[90mStarFormationHistories → DataFramesExt\u001b[39m\n", "\u001b[32m ✓ \u001b[39m\u001b[90mStarFormationHistories → TypedTablesExt\u001b[39m\n", " 3 dependencies successfully precompiled in 6 seconds. 223 already precompiled.\n" ] }, { "data": { "text/plain": [ "29-element Vector{Float64}:\n", " -2.800020899214084\n", " -2.7000110527475605\n", " -2.6000175983197713\n", " -2.5000097946519406\n", " -2.100012070548602\n", " -2.0000162211614816\n", " -1.9000073196768041\n", " -1.8000170782347085\n", " -1.7000105737090876\n", " -1.6000092093397091\n", " -1.5000150464034467\n", " -1.4000147226611754\n", " -1.3000117782255178\n", " ⋮\n", " -0.8000106239270766\n", " -0.7000142637672999\n", " -0.60001623283198\n", " -0.5000166309399301\n", " -0.40001148522876795\n", " -0.3000154566956319\n", " -0.20001378845202145\n", " -0.10003154653740931\n", " 0.0\n", " 0.09998742559427609\n", " 0.1999864995269065\n", " 0.299992911269662" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: MH_from_Z\n", "# Rewrite [M/H] column. \n", "for i in eachindex(table)\n", " table.MH[i] = MH_from_Z(table.Zini[i], 0.01471)\n", "end\n", "unique(table.MH)" ] }, { "cell_type": "markdown", "id": "32a19a5f-43bb-4744-b9be-195185940352", "metadata": {}, "source": [ "## Observational Model \n", "\n", "We'll construct a model Hess diagram from the populations in this isochrone table. First we need to set up our observational models for photometric error and incompleteness. You would typically measure these from artificial star tests but we'll make up some models here using functions built into StarFormationHistories.jl." ] }, { "cell_type": "code", "execution_count": 8, "id": "1577b33d-fb20-40f2-b24d-9e2773bcc7d2", "metadata": { "tags": [] }, "outputs": [], "source": [ "import StarFormationHistories: Martin2016_complete, exp_photerr" ] }, { "cell_type": "code", "execution_count": 9, "id": "40c54453-9882-493d-ad23-5a3edac215f8", "metadata": { "tags": [] }, "outputs": [], "source": [ "distmod = 25.0 # Distance modulus \n", "F090W_complete(m) = Martin2016_complete(m,1.0,28.5,0.7)\n", "F150W_complete(m) = Martin2016_complete(m,1.0,27.5,0.7)\n", "F090W_error(m) = min( exp_photerr(m, 1.03, 15.0, 36.0, 0.02), 0.4 )\n", "F150W_error(m) = min( exp_photerr(m, 1.03, 15.0, 35.0, 0.02), 0.4 );" ] }, { "cell_type": "markdown", "id": "c98e8a43-e6b6-4d39-acf9-c7904be3bf06", "metadata": {}, "source": [ "We'll make a few plots showing the adopted models. Below we set up PyPlot.jl (a wrapper for Python's matplotlib package)." ] }, { "cell_type": "code", "execution_count": 10, "id": "f40a687d-fcbd-481d-8707-d107e7e96cf0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import PyPlot as plt\n", "import PyPlot: @L_str # For LatexStrings\n", "import PyCall: @pyimport\n", "plt.rc(\"text\", usetex=true)\n", "plt.rc(\"text.latex\", preamble=\"\\\\usepackage{amsmath}\") # for \\text\n", "plt.rc(\"font\", family=\"serif\", serif=[\"Computer Modern\"], size=14)\n", "plt.rc(\"figure\", figsize=(5,5))\n", "plt.rc(\"patch\", linewidth=1, edgecolor=\"k\", force_edgecolor=true)\n", "# https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html\n", "plt.rc(\"image\", interpolation=\"none\")" ] }, { "cell_type": "code", "execution_count": 11, "id": "6a4b1a66-34cf-495e-8e9a-101edb617d3f", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "(0.0, 0.41895850114873723)" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "plotmags=20.0:0.05:33.0\n", "\n", "fig,ax1=plt.subplots()\n", "ax1.plot(plotmags,F090W_complete.(plotmags),label=\"F090W\")\n", "ax1.plot(plotmags,F150W_complete.(plotmags),label=\"F150W\")\n", "ax1.set_xlabel(\"Apparent Magnitude\")\n", "ax1.set_ylabel(\"Completeness\")\n", "ax1.legend(loc=\"lower left\")\n", "\n", "plotmags=20.0:0.05:33.0\n", "fig,ax1=plt.subplots()\n", "ax1.plot(plotmags,F090W_error.(plotmags),label=\"F090W\")\n", "ax1.plot(plotmags,F150W_error.(plotmags),label=\"F150W\")\n", "ax1.set_xlabel(\"Apparent Magnitude\")\n", "ax1.set_ylabel(\"Photometric Error\")\n", "ax1.legend(loc=\"upper left\")\n", "ax1.set_ylim([0.0,ax1.get_ylim()[2]])" ] }, { "cell_type": "markdown", "id": "828b9bf7-4502-474b-9cab-1ab877bb63b8", "metadata": {}, "source": [ "We put a maximum on the magnitude error in the model because most of the time one would place a cut on the photometric catalog in either signal to noise (e.g., SNR>5) or magnitude error (e.g., error < 0.4). From a practical perspective, if we allow the photometric error model to grow too large, it will hurt the efficiency of `partial_cmd_smooth` for template creation later." ] }, { "cell_type": "markdown", "id": "6af00e21-3a97-4bc1-ad61-4138ca22d67d", "metadata": {}, "source": [ "## Template Construction\n", "\n", "We may now define our mock star formation history. We will use `partial_cmd_smooth` to construct the templates for a Hess diagram model with F150W on the y-axis and F090W-F150W on the x-axis, with an initial mass function model from InitialMassFunctions.jl. We'll construct all 1846 templates, one for every isochrone in our table, but this may not always be necessary." ] }, { "cell_type": "code", "execution_count": 12, "id": "b483e8fe-724d-4dc2-b648-c476ec4356f4", "metadata": { "tags": [] }, "outputs": [], "source": [ "import StarFormationHistories: partial_cmd_smooth\n", "import InitialMassFunctions: Kroupa2001" ] }, { "cell_type": "code", "execution_count": 13, "id": "b79bdea6-d984-4457-8510-e93584b9d3d7", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Some additional setup\n", "edges = (range(-0.65, 1.75, length=100), range(distmod-7.0, distmod+3.0, length=100)) # The bin edges for the Hess diagrams (17,28)\n", "imf = Kroupa2001(0.08, 100.0) # Initial mass function model\n", "unique_logAge = unique(table.logAge)\n", "unique_MH = unique(table.MH)\n", "template_norm = 1e3 # The stellar mass of the populations in each template\n", "\n", "# Now define the subset of unique logAges for which isochrones are available\n", "# that we actually want to use for our example.\n", "# As stated above, the isochrone file we read in has a uniform grid spacing of \n", "# `ΔlogAge=0.05`. We will only use a spacing of 0.1 dex for logAge < 9 if isochrone_cut is true.\n", "isochrone_cut::Bool = false\n", "if isochrone_cut\n", " logAge_cutval = 9\n", " selection = vcat( findall( <=(logAge_cutval), unique_logAge)[begin:2:end],\n", " findall( >(logAge_cutval), unique_logAge) )\n", " unique_logAge = unique_logAge[selection]\n", "end" ] }, { "cell_type": "code", "execution_count": 14, "id": "683f1421-60b9-42d4-a8d5-d7a06230c790", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of final isochrones is: 2059" ] } ], "source": [ "@printf(\"Number of final isochrones is: %i\",length(unique_logAge) * length(unique_MH))" ] }, { "cell_type": "code", "execution_count": 15, "id": "912a394f-be4a-41e9-af43-2071cc96b14e", "metadata": { "tags": [] }, "outputs": [], "source": [ "# # Constructing the templates; single-threaded with push!\n", "# templates = Vector{Matrix{Float64}}(undef,0)\n", "# template_logAge = Vector{Float64}(undef,0)\n", "# template_MH = Vector{Float64}(undef,0)\n", "# # We don't strictly need to save the initial masses (m_ini) or the isochrone magnitudes (iso_mags), \n", "# # but we'll use them later in this example so we'll save them now. \n", "# template_mini = Vector{Vector{Float64}}(undef,0)\n", "# template_isomags = Vector{Vector{Vector{Float64}}}(undef,0)\n", "# for logage in unique_logAge \n", "# for mh in unique_MH\n", "# # Combination of a logage and an MH defines a unique isochrone.\n", "# # Pick out all entries in `table` that match this combination; these will be row indices\n", "# # into the table of the stars in this specific isochrone.\n", "# local good = findall( (table.MH .== mh) .& (table.logAge .== logage) )\n", "# # Chop off the last entry in the isochrone because its the 30 mag weird thing that parsec does.\n", "# local m_ini = table.Mini[good][begin:end-1] # These are the initial masses of the stars in the isochrone, in solar masses.\n", "# push!(template_mini, m_ini)\n", "# local iso_mags = [table.F090W[good][begin:end-1], table.F150W[good][begin:end-1]] # These are the absolute magnitudes we want from the isochrone.\n", "# push!(template_isomags, iso_mags)\n", "# # Create template and push\n", "# push!(templates, partial_cmd_smooth( m_ini, iso_mags, [F090W_error, F150W_error], 2, [1,2], imf, [F090W_complete, F150W_complete]; \n", "# dmod=distmod, normalize_value=template_norm, edges=edges).weights )\n", "# push!(template_logAge, logage)\n", "# push!(template_MH, mh)\n", "# end\n", "# end" ] }, { "cell_type": "code", "execution_count": 16, "id": "2fd9ae3b-f4a0-4e90-993a-b1337481c96a", "metadata": {}, "outputs": [], "source": [ "# Constructing the templates; multi-threaded with pre-allocated arrays\n", "templates = Vector{Matrix{Float64}}(undef, length(unique_logAge) * length(unique_MH))\n", "template_logAge = Vector{Float64}(undef, length(templates))\n", "template_MH = Vector{Float64}(undef, length(templates))\n", "# We don't strictly need to save the initial masses (m_ini) or the isochrone magnitudes (iso_mags), \n", "# but we'll use them later in this example so we'll save them now. \n", "template_mini = Vector{Vector{Float64}}(undef, length(templates))\n", "template_isomags = Vector{Vector{Vector{Float64}}}(undef, length(templates))\n", "# Multi-threaded, nested loop iterating over unique_MH (outer loop) and unique_logAge (inner loop). \n", "# Using `enumerate` also gets us index `i` of iteration.\n", "Base.Threads.@threads for (i, (mh, logage)) in collect(enumerate(Iterators.product(unique_MH, unique_logAge)))\n", " # Combination of a logage and an MH defines a unique isochrone.\n", " # Pick out all entries in `table` that match this combination; these will be row indices\n", " # into the table of the stars in this specific isochrone.\n", " local good = findall( (table.MH .== mh) .& (table.logAge .== logage) )\n", " # Chop off the last star because its the 30 mag weird thing that parsec does.\n", " local m_ini = table.Mini[good][begin:end-1] # These are the initial masses of the stars in the isochrone, in solar masses.\n", " template_mini[i] = m_ini\n", " local iso_mags = [table.F090W[good][begin:end-1], table.F150W[good][begin:end-1]] # These are the absolute magnitudes we want from the isochrone.\n", " template_isomags[i] = iso_mags\n", " # Create templates\n", " templates[i] = partial_cmd_smooth(m_ini, iso_mags, [F090W_error, F150W_error], 2, [1,2], imf, [F090W_complete, F150W_complete]; \n", " dmod=distmod, normalize_value=template_norm, edges=edges).weights\n", " template_logAge[i] = logage\n", " template_MH[i] = mh\n", "end" ] }, { "cell_type": "code", "execution_count": 17, "id": "e259cfbb-14b6-474b-b057-62cfb9ee6dc9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10.10001 -2.800020899214084\n" ] } ], "source": [ "# Write single isochrone to file\n", "# Some extra info here https://discourse.julialang.org/t/formatting-float64-output-with-csv-write/23479\n", "# let idx = length(unique_MH)*70 + findfirst(==(first(unique_MH)), unique_MH) # 1821\n", "let idx = length(unique_MH)*(findmin( x -> abs(exp10(x-9) - 12.59), unique_logAge)[2] - 1) + findfirst(==(first(unique_MH)), unique_MH) # 1821\n", " logage = template_logAge[idx]\n", " mh = template_MH[idx]\n", " println(logage, \" \", mh)\n", " # local good = findall((table.MH .== mh) .& (table.logAge .== logage))\n", " # open(\"isochrone.txt\",\"w\") do file\n", " # print(file, \"m_ini F090W F150W F277W\\n\")\n", " # for i in good[begin:end-1]\n", " # @printf(file, \"%.10f %.3f %.3f %.3f\\n\", table.Mini[i], table.F090W[i], table.F150W[i], table.F277W[i])\n", " # end\n", " # end\n", "end" ] }, { "cell_type": "code", "execution_count": 18, "id": "c7993fed-6e57-46b9-a8bc-8aa88a889e52", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Sort the template_logAge and template_MH so we have a guarantee for later\n", "permidx = sortperm(template_logAge)\n", "template_logAge = template_logAge[permidx]\n", "template_MH = template_MH[permidx]\n", "templates = templates[permidx];" ] }, { "cell_type": "markdown", "id": "20dcd127-b83b-4829-bcac-d52b960fa9f5", "metadata": {}, "source": [ "We'll plot a few templates for reference." ] }, { "cell_type": "code", "execution_count": 19, "id": "4eb63679-b3d4-42ae-a449-ae7e36af0638", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# When displaying the templates we will divide them by template_norm so that that units of the templates are\n", "# [N / M_sun], or expected number of stars per bin per solar mass of stars formed.\n", "# Plotting in absolute magnitude here rather than apparent on y-axis\n", "# display_templates = (100,1495,1821) # Before option of using isochrone_cut\n", "display_templates = ( length(unique_MH)*(findmin( x -> abs(x - 6.8), unique_logAge)[2] - 1) + \n", " findmin( x -> abs(x - (-0.1)), unique_MH)[2],\n", " length(unique_MH)*(findmin( x -> abs(exp10(x-9) - 2.82), unique_logAge)[2] - 1) + \n", " findmin( x -> abs(x - (-1.0)), unique_MH)[2],\n", " length(unique_MH)*(findmin( x -> abs(exp10(x-9) - 12.59), unique_logAge)[2] - 1) + \n", " findmin( x -> abs(x - (-2.8)), unique_MH)[2] )\n", " # findfirst(==(first(unique_MH)), unique_MH) )\n", "\n", "fig,axs=plt.subplots(1,3,sharey=true,sharex=true,figsize=(15,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.075)\n", "\n", "im1 = axs[1].imshow(permutedims(templates[display_templates[1]]) ./ template_norm, origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2] .- distmod)...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=1e-8), rasterized=true) \n", "im2 = axs[2].imshow(permutedims(templates[display_templates[2]]) ./ template_norm, origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2] .- distmod)...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=1e-8), rasterized=true) \n", "im3 = axs[3].imshow(permutedims(templates[display_templates[3]]) ./ template_norm, origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2] .- distmod)...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=1e-8), rasterized=true) \n", "# im1.set_clim( [0.5, im1.get_clim()[2]] )\n", "for ax in axs\n", " ax.set_xlabel(L\"F090W$-$F150W\")\n", "end\n", "axs[1].set_ylabel(\"F150W\")\n", "axs[1].set_ylim(reverse(extrema(edges[2])).-distmod) \n", "axs[1].set_xlim(extrema(edges[1]))\n", "# Label the templates with their ages and metallicities\n", "axs[1].text(0.95,0.95,(@sprintf \"Age: %.2f Gyr \\n [M/H]: %.1f\" exp10(template_logAge[display_templates[1]])/1e9 template_MH[display_templates[1]]), transform=axs[1].transAxes,ha=\"right\",va=\"top\")\n", "axs[2].text(0.1,0.95,(@sprintf \"Age: %.2f Gyr \\n [M/H]: %.1f\" exp10(template_logAge[display_templates[2]])/1e9 template_MH[display_templates[2]]), transform=axs[2].transAxes,ha=\"left\",va=\"top\")\n", "axs[3].text(0.1,0.95,(@sprintf \"Age: %.2f Gyr \\n [M/H]: %.1f\" exp10(template_logAge[display_templates[3]])/1e9 template_MH[display_templates[3]]), transform=axs[3].transAxes,ha=\"left\",va=\"top\")\n", "fig.colorbar(im1, ax=axs[1], pad=0.01)\n", "fig.colorbar(im2, ax=axs[2], pad=0.01)\n", "fig.colorbar(im3, ax=axs[3], pad=0.01)\n", "\n", "# Optionally, plot photometric error bars along the left. Errors are small in this model so they don't show very well.\n", "plot_errors::Bool = false\n", "if plot_errors\n", " # Set up points to show the photometric errors\n", " error_points = minimum(edges[2])+1.0:0.5:maximum(edges[2])-0.5\n", " error_points_x = repeat([minimum(edges[1])+0.15], length(error_points))\n", " \n", " # Plot the photometric error points\n", " for ax in axs\n", " ax.errorbar(error_points_x, error_points, yerr=F150W_error.(error_points), xerr=sqrt.(F090W_error.(error_points_x .+ error_points).^2 .+ F150W_error.(error_points).^2), ls=\"\") # , fmt='', ecolor=None, elinewidth=None, capsize=None\n", " end\n", "end\n", "\n", "# Optionally, overplot the isochrones themselves for comparison\n", "plot_isochrones::Bool = true\n", "if plot_isochrones\n", " alphas = (0.5,0.5,0.5)\n", " for (i,t_i) in enumerate(display_templates)\n", " local good = findall( (table.MH .== template_MH[t_i]) .& (table.logAge .== template_logAge[t_i]) )\n", " local iso_mags = [table.F090W[good][begin:end-1], table.F150W[good][begin:end-1]] # These are the absolute magnitudes we want from the isochrone. \n", " axs[i].scatter(iso_mags[1] .- iso_mags[2], iso_mags[2],marker=\".\", c=\"orange\", s=1, alpha=alphas[i])\n", " end\n", "end\n", "# plt.savefig(\"template_example.pdf\",bbox_inches=\"tight\")" ] }, { "cell_type": "markdown", "id": "195fa6ee-6810-4ea1-8391-15bf967eac30", "metadata": {}, "source": [ "## Building a Model Hess Diagram\n", "\n", "We may now use `construct_x0_mdf` and `calculate_coeffs_mdf` to create a mock star formation history with constant star formation rate and a reasonable metallicity evolution for a dwarf galaxy. " ] }, { "cell_type": "code", "execution_count": 20, "id": "b9922650-38c6-45ce-b64c-8acf60deb156", "metadata": { "tags": [] }, "outputs": [], "source": [ "import StarFormationHistories: construct_x0_mdf, calculate_coeffs_mdf" ] }, { "cell_type": "code", "execution_count": 21, "id": "6052ae80-5598-4640-82e8-1999ddd817e1", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "71-element Vector{Float64}:\n", " 0.3546754852763317\n", " 0.39795243976854205\n", " 0.44650998135479464\n", " 0.5009924391101048\n", " 0.5621227621472895\n", " 0.6307121127124647\n", " 0.7076706298151519\n", " 0.7940195062200948\n", " 0.8909045390546783\n", " 0.9996113338407332\n", " 1.1215823636987226\n", " 1.2584361100895634\n", " 1.4119885390804652\n", " ⋮\n", " 316.1121376527206\n", " 354.68365207520725\n", " 397.9616030676007\n", " 446.5202627454242\n", " 501.00397502014556\n", " 562.1357056512223\n", " 630.726635562751\n", " 707.6869247211959\n", " 794.0377894053578\n", " 890.9250531259797\n", " 999.6343510072705\n", " 810.7874311842759" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Set overall stellar mass of complex population and metallicity evolution variables\n", "stellar_mass = 1e7\n", "α, β, σ = 0.1, -1.87, 0.1 # -0.1, -0.5, 0.1\n", "# max_logage sets the highest bin edge for the template_logAge\n", "# if template_logage was [6.6,6.7,6.8], I would set max_logAge=6.9, \n", "# representing the rightmost bin edge. In our case, our oldest template\n", "# is quite old, so we'll make it either the Hubble time or the maximum of \n", "# template_logAge plus the isochrone logage grid spacing, which is 0.05.\n", "# max_logAge = min(log10(13.7e9), maximum(template_logAge) + 0.05)\n", "T_max = min(13.7, exp10(maximum(unique_logAge)+ 0.05)/1e9)\n", "max_logAge = log10(T_max * 1e9)\n", "# Get initial guess for stellar mass coefficients.\n", "# We have to divide `stellar_mass` by `template_norm` here because `template_norm` is the total amount of stellar mass in each template, \n", "# since we passed `normalize_value=template_norm` when constructing the templates with `partial_cmd_smooth`. As such, when computing \n", "# coefficients, we need to normalize out the adopted `normalize_value` for the templates.\n", "x0_mdf = construct_x0_mdf(template_logAge, T_max; normalize_value=stellar_mass / template_norm)" ] }, { "cell_type": "code", "execution_count": 22, "id": "3924dea5-5ec9-4def-a509-83aad446ab4f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.0000000000000002e7" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Check sum of x0_mdf * template_norm; should equal stellar_mass\n", "sum(x0_mdf) * template_norm" ] }, { "cell_type": "markdown", "id": "e6ff5afc-47bd-4c4e-9d7d-7aa06a0af66a", "metadata": {}, "source": [ "The above coefficients are the amount of stellar mass formed in each age bin of `unique(template_logAge)`. To construct the complex Hess diagram, we need individual per-template weights, which we can get with `calculate_coeffs_mdf`." ] }, { "cell_type": "code", "execution_count": 23, "id": "a280e026-ba10-4f83-bc4b-365adb17a74a", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "2059-element Vector{Float64}:\n", " 2.0774487661255844e-116\n", " 1.2259099971069627e-106\n", " 2.651625167725607e-97\n", " 2.1162850803717393e-88\n", " 3.8714448827814896e-57\n", " 2.0772592204779136e-50\n", " 4.1081211720955453e-44\n", " 2.981060528961156e-38\n", " 7.975095776546787e-33\n", " 7.84340370564942e-28\n", " 2.8356607021243346e-23\n", " 3.773991167821277e-19\n", " 1.848166988977186e-15\n", " ⋮\n", " 3.479788626121185e-18\n", " 1.445217171479717e-22\n", " 2.2078339187838887e-27\n", " 1.2406132585250885e-32\n", " 2.562643689989885e-38\n", " 1.9497482102204798e-44\n", " 5.452893528736057e-51\n", " 5.628156079458223e-58\n", " 2.119330307269925e-65\n", " 2.9581805702825195e-73\n", " 1.5159136200760106e-81\n", " 2.853524813787372e-90" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x0 = calculate_coeffs_mdf(x0_mdf, template_logAge, template_MH, T_max, α, β, σ)" ] }, { "cell_type": "markdown", "id": "cf8c1697-2991-469e-91e1-053cd21e46c1", "metadata": {}, "source": [ "Let's plot the cumulative SFH and mean [M/H] of our model population." ] }, { "cell_type": "code", "execution_count": 24, "id": "945738c9-4ecb-4039-ac86-20f388b52d5d", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "([6.6, 6.65, 6.7, 6.75, 6.8, 6.85, 6.9, 6.95, 7.0, 7.05 … 9.65001, 9.70001, 9.75001, 9.80001, 9.85001, 9.90001, 9.95001, 10.00001, 10.05001, 10.10001], [1.0, 0.9999645324514724, 0.9999247372074956, 0.9998800862093601, 0.9998299869654491, 0.9997737746892345, 0.9997107034779632, 0.9996399364149818, 0.9995605344643599, 0.9994714440104544 … 0.6741419731491225, 0.6343458128423624, 0.58969378656782, 0.5395933890658053, 0.48337981850068307, 0.42030715494440796, 0.3495384624722884, 0.27013468353175263, 0.1810421782191546, 0.08107874311842758], [0.0007301391778410239, 0.0007301391778410237, 0.0007301391778410242, 0.000730139177841024, 0.0007301391778410239, 0.0007301391778410237, 0.0007301391778410242, 0.0007301391778410241, 0.0007301391778410239, 0.0007301391778410242 … 0.0007301391778410242, 0.000730139177841024, 0.0007301391778410241, 0.000730139177841024, 0.000730139177841024, 0.0007301391778410241, 0.000730139177841024, 0.0007301391778410241, 0.0007301391778410239, 0.0007301391778410239], [-0.5003989802960739, -0.5004475580599371, -0.5005020632066869, -0.5005632189862201, -0.5006318368982151, -0.5007088274602199, -0.5007952122896429, -0.5008921376599632, -0.5010008897110452, -0.5011229115153801 … -0.9466925595632898, -1.0011998230888994, -1.0623590537122782, -1.1309764552665305, -1.2079609175110564, -1.2943433956348684, -1.391272022482317, -1.5000242679783078, -1.6220417785243162, -1.7589454984711883])" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: calculate_cum_sfr\n", "unique_template_logAge, cum_sfr_arr, sfr_arr, mean_mh_arr = calculate_cum_sfr(x0, template_logAge, template_MH, T_max; normalize_value=template_norm)" ] }, { "cell_type": "code", "execution_count": 25, "id": "4d851844-a437-46d9-98f6-8a3e908464df", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject Text(457.3650849792141, 0.5, '$\\\\langle$[M/H]$\\\\rangle$')" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=false,figsize=(10,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.35)\n", "\n", "axs[1].plot( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(cum_sfr_arr, 0.0), label=\"Input SFH\" )\n", "\n", "axs[1].set_xlim([T_max,-0.1])\n", "axs[1].set_ylim([0.0,1.1])\n", "axs[1].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[1].set_ylabel(\"Cumulative SF\")\n", "axs[1].legend()\n", "\n", "axs[2].plot( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(mean_mh_arr, β), label=\"Input SFH\" )\n", "axs[2].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[2].set_ylabel(L\"$\\langle$[M/H]$\\rangle$\")" ] }, { "cell_type": "code", "execution_count": 26, "id": "9229fcf8-d85d-44a3-93ac-9cdb6fac1606", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "7-element Vector{Float64}:\n", " 0.0007301391778410239\n", " 0.0007301391778410237\n", " 0.0007301391778410242\n", " 0.000730139177841024\n", " 0.0007301391778410241\n", " 0.0007301391778410238\n", " 0.0007301391778410244" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Look at the unique values of the SFRs\n", "unique(sfr_arr)" ] }, { "cell_type": "code", "execution_count": 27, "id": "a6cfda68-21bf-4add-a072-0767642ddb38", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,ax1 = plt.subplots()\n", "ax1.bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFH\")\n", "ax1.set_xlabel(L\"log$_{10}$(Age [yr])\")\n", "ax1.set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "ax1.set_ylim([0.0, ax1.get_ylim()[2]])\n", "ax1.legend()" ] }, { "cell_type": "markdown", "id": "8a9a2a22-cf33-4107-a0c9-8f566f8ea0c0", "metadata": {}, "source": [ "Now let's make a model Hess diagram with this SFH. We can simply write `composite = sum( coeffs .* models)` if we want, but we also provide the `composite!` function that is more efficient." ] }, { "cell_type": "code", "execution_count": 28, "id": "9d767186-dd61-4ee3-b8ce-357e1bae9f43", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "99×99 Matrix{Float64}:\n", " 0.0 0.0 0.0 … 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 … 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 4.7461e-105 1.2101e-96 2.13242e-96 0.0 0.0\n", " 1.62227e-8 4.39528e-8 9.23015e-8 0.0 0.0\n", " 6.47261e-7 1.63819e-6 2.89898e-6 … 2.35262e-60 0.0\n", " 1.30993e-5 2.78702e-5 4.50146e-5 6.37266e-28 1.51965e-30\n", " 0.000131899 0.000234432 0.000354662 1.34935e-16 1.78572e-19\n", " ⋮ ⋱ \n", " 0.0946179 0.126277 0.166761 7.13111e-5 5.41444e-5\n", " 0.120871 0.161966 0.205216 5.60572e-5 4.21829e-5\n", " 0.155129 0.208495 0.24635 4.12576e-5 3.09016e-5\n", " 0.192861 0.255337 0.264476 … 2.84541e-5 2.12879e-5\n", " 0.213438 0.259621 0.24085 1.84096e-5 1.37977e-5\n", " 0.190311 0.216917 0.201787 1.11875e-5 8.41799e-6\n", " 0.143899 0.167347 0.21799 6.39379e-6 4.83577e-6\n", " 0.112542 0.145776 0.315974 3.44096e-6 2.61572e-6\n", " 0.101706 0.162612 0.431167 … 1.74606e-6 1.33199e-6\n", " 0.104666 0.218471 0.522809 8.36611e-7 6.38481e-7\n", " 0.116075 0.283444 0.547689 3.7942e-7 2.88684e-7\n", " 0.141261 0.342103 0.502006 1.64316e-7 1.25094e-7" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1 = sum( x0 .* templates)" ] }, { "cell_type": "code", "execution_count": 29, "id": "aec656ce-cbcb-4fb0-a20b-b8f87217c63c", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "99×99 Matrix{Float64}:\n", " 0.0 0.0 0.0 … 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 … 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0\n", " 4.7461e-105 1.2101e-96 2.13242e-96 0.0 0.0\n", " 1.62227e-8 4.39528e-8 9.23015e-8 0.0 0.0\n", " 6.47261e-7 1.63819e-6 2.89898e-6 … 2.35262e-60 0.0\n", " 1.30993e-5 2.78702e-5 4.50146e-5 6.37266e-28 1.51965e-30\n", " 0.000131899 0.000234432 0.000354662 1.34935e-16 1.78572e-19\n", " ⋮ ⋱ \n", " 0.0946179 0.126277 0.166761 7.13111e-5 5.41444e-5\n", " 0.120871 0.161966 0.205216 5.60572e-5 4.21829e-5\n", " 0.155129 0.208495 0.24635 4.12576e-5 3.09016e-5\n", " 0.192861 0.255337 0.264476 … 2.84541e-5 2.12879e-5\n", " 0.213438 0.259621 0.24085 1.84096e-5 1.37977e-5\n", " 0.190311 0.216917 0.201787 1.11875e-5 8.41799e-6\n", " 0.143899 0.167347 0.21799 6.39379e-6 4.83577e-6\n", " 0.112542 0.145776 0.315974 3.44096e-6 2.61572e-6\n", " 0.101706 0.162612 0.431167 … 1.74606e-6 1.33199e-6\n", " 0.104666 0.218471 0.522809 8.36611e-7 6.38481e-7\n", " 0.116075 0.283444 0.547689 3.7942e-7 2.88684e-7\n", " 0.141261 0.342103 0.502006 1.64316e-7 1.25094e-7" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model2 = similar(model1)\n", "import StarFormationHistories: composite!\n", "composite!(model2, x0, templates)\n", "model2" ] }, { "cell_type": "code", "execution_count": 30, "id": "fcb096ff-4a03-4119-ba63-010857138d46", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "true" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1 ≈ model2" ] }, { "cell_type": "markdown", "id": "fc8e9b28-b772-4b13-89ac-98a182fcf71e", "metadata": {}, "source": [ "Let's plot the smooth model." ] }, { "cell_type": "code", "execution_count": 31, "id": "ce2d87a4-3b13-42ef-92c7-223deb160f2f", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,ax1=plt.subplots()\n", "\n", "im1=ax1.imshow(permutedims(model2), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5), rasterized=true) \n", "ax1.set_xlabel(L\"F090W$-$F150W\")\n", "ax1.set_ylabel(\"F150W\")\n", "ax1.set_ylim(reverse(extrema(edges[2]))) \n", "ax1.set_xlim(extrema(edges[1]))\n", "fig.colorbar(im1)" ] }, { "cell_type": "markdown", "id": "3d7ff261-5b9e-45f7-82dc-47d7c9c89b49", "metadata": {}, "source": [ "## Sampling Methods for CMDs and Hess Diagrams\n", "\n", "The templates are constructed such that the 2D histogram pixel values give the expected number of stars in that bin for a population with total stellar mass `normalize_value` (in our case we defined the variable `template_norm=1e3` and used that as our `normalize_value` for the templates). As such the pixel values of this complex model also represent expected numbers of stars per bin for our defined SFH. We may, therefore, simply Poisson sample it to obtain a reasonable observational realization of the Hess diagram:" ] }, { "cell_type": "code", "execution_count": 32, "id": "db0239d9-90d8-49a8-9bd9-81634becee2b", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "99×99 Matrix{Float64}:\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " ⋮ ⋮ ⋱ ⋮ \n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 2.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 1.0 0.0 0.0 1.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 1.0 0.0 0.0 3.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 0.0 0.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 1.0 3.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 1.0 0.0 2.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 3.0 1.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 1.0 1.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 1.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 1.0 1.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import Distributions: Poisson\n", "import Random: AbstractRNG, default_rng\n", "function poisson_sample!(sample::T, model::S, rng::AbstractRNG=default_rng()) where {T <: AbstractArray{<:Number}, S <: AbstractArray{<:Number}}\n", " @assert axes(sample) == axes(model)\n", " for i in eachindex(sample, model)\n", " sample[i] = rand(rng,Poisson(model[i]))\n", " end\n", "end\n", "poisson_sample(model::AbstractArray{<:Number}, rng::AbstractRNG=default_rng()) = (sample = similar(model); poisson_sample!(sample, model, rng); return sample)\n", "model3 = poisson_sample(model2)" ] }, { "cell_type": "code", "execution_count": 33, "id": "e2b55299-0164-41aa-853f-6acb6ae0471d", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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ezsSVCAAAACChejjTZm9mZiMjI3b27Fm7fPnyDr+r5nElAgAsOg/Cz4nQKV71Ofv27QvV8+8DQDv78ssvXVnzvczMvvOd77iy5kf49u7d68qaO/HFF19E7g9PLS4u2qFDh3a6GYkwiAAAAAAS6vVwJgYRAAAAQEK9PoggJwIAAABAIlyJANCT/Lm5o/IgHj16FKr37bffurLG/2rZzDY9dzgAbKcXXnjBlePyHj7++GNX3r9/f2ib9penT592ZT8nQl+rk/X6OhEMIgAAAICECGcCAAAAgAS4EgEAAAAkRDgTAPSIJ0+euLI/D3pUHoRfT78wNA/Cjw0GgE6ieRD++jhBELjywYMHXVnXljAzO378uCtrHkRfX1+rmtlWCGcCAAAAgAS4EgEAAAAktGvXrk2HM+kV8k7DIAIAAABIqNfDmRhEAOhquq5DXMzvw4cPXfnx48eR+9PchwMHDrSiiQDQUtrXPfdcc//V8/tE9fzzz7uy5kFo/2pmVqlUXPmv/uqvmnpddK62GkSUSiVbWFiwIAisWq3a+Pi4TUxMhOpUq1XL5/M2NDRkZmapVGpdHQAAAGArcSWiTZRKJSuXy5bP583s6UwAw8PDtrS0ZIVCwcyeDiCGh4ft+vXrlkqlzMwsl8vZ7OysTU1N7VTTAQAA0GNaMcXrZp+/k9qm5YVCITQQSKVSlsvlbG5uzqrVqpmZ5fN5m5iYcAMIM7Pp6WnL5XLb3VwAAACgZ7XNIKJYLK4bDJw7d87Mnl6lMDO7evWqC2Oqqw8o6nUA9J5areZu33zzTeTtq6++creHDx+Gbo8ePXK3J0+euNvzzz8fuh04cMDd9uzZ424AsJ2+/PLL0E198cUX7qZ9oC9q29dffx15u337trsNDg6GbqdPn3a3XlAPZ9rsrVO1zSBibGxs3QBBBUFgQRBYOp1ety2VSlm5XN7K5gEAAABOPZxps7dO1TY5EfPz8+seu3btmpmZZbNZF9LUyMDAgC0vLzfc9vjx49BMK/fv399kSwGgO/j944MHD3awNQCATtLWw598Pm/5fL7h1QefLsmuZmZmrK+vz91OnTrV4lYCQGfy+8ezZ8/udJMAoGP0ejhT21yJ8I2Pj1s2m3XJ1ppM7VtZWYncNj09bX/zN3/j7t+/f5+BBNAFdH5yXfHTn7f866+/duVHjx65sq4L4T9P51X314LoprUh/P7x1q1bDCSANhO15sMLL7wQqre2tubK3/nOd1w5bv2H1dVVV967d68rf/LJJ6F63/ve91z56NGjrvzxxx+H6jXzo283YYrXNjQ3N2cDAwNualezpyFLZo2vOARBEDnI2Ldvn+3bt28rmgkAHc3vHwn3BAA0q+0GEcVi0YIgCA0g6oOEVCoVedVhdHR0u5oIAACAHsc6EW2kXC7byspKaL2IIAjc9K3nz58PLaluZi7hOpvNbl9DAQAA0NPIiWgT1WrVZmZm7MKFC1YsFt3jCwsLNjk5aWZPV6ceHR11q1qbPV2kTq9aAOheGhusOQy1Ws2VNQfCLJwHoXOp+3HC+muQxgZ3Uw4EgM6jeRBxNA/i7t27DeucOHEi8vkaLu6vfXPr1q2Gzzl48GBTbUN3aptBxPDwsAVBEBpA1NUHCel02ubn5y2Xy9nIyIhVq1UbHBy0iYmJ7W4uAAAAelivhzO1zSBCZwiIk8lkLJPJbHFrAAAAAETp3OEPAAAAsENamRMxMjJiZ8+etcuXL+/wu2pe21yJAACfn98QlQehuRKaA2Fm9vnnn7uyrs7s0zwIjS3WxwFgJ2leVxztw/r6+lzZX/9B62neg58T8eKLL7ry888/3/D5vaiV60QsLi7aoUOHWtGsbcOVCAAAAACJcCUCAAAASGjXrl2bToxmilcAaBENYdIwJTOzJ0+euLKGNmmY0hdffBF6joY36XP8lex1Ktdev0QPYOtp/6bTuPr9nm574YUXIutpONKRI0ca1vNDRP/85z+78smTJ115bW0tVE/7RC03O/1st2plOFMnIpwJAAAAQCK9PYQEAAAANoB1IgAAAAAk0uvhTAwiAOw4jdmNKpuFcyK++uorV9ZpD/0pXjUGWON3/ZwIncKwk38ZAtAZovIJ/Mc1P0Gna717926onuZ8Kb+e0lyw5eVlV/bzwvR1gToGEQAAAEBChDMBAAAASKTXw5k6d/gDAAAAYEdwJQLAttPcBrNw3oKW4+pp7oOWdc0I3/PPP+/KmgNhFp5/HQC2k+Z/+WvdaL/1ySefuLLmMJiZHTp0yJWj+kqfvtYPfvCDhs/329fra0OoXr8SwZkAAAAAJNTrgwjCmQAAAAAkwpUIAAAAIKFevxLBIALAttM1HszC8bdx60RovsPDhw9dWWN+/bnSdT0IzXvw50EHgJ2ieQZBEIS2vfzyy66s/daJEydC9arVqitrHoXmPfj5DC+99JIr+3kQUe3DP+v1QQThTAAAAAASYWgJAAAAJNTrVyIYRAAAAAAJMYgAgG2g+Q1+7K3mSMTV09wHzYnQenv27Ak9R3MidG0IfRwAtsJG1ld45ZVXQvfX1tZcWfMlNO/BzOyzzz5zZc2D0LUlTp8+Hfm62g8fOXKkqbaitzGIAAAAABLiSgQAAACARHbv3m27d29ujqLNPn8ndW7LAQAAAOwIrkQA2BYabxu3ToSWdV0IM7Mvv/wyclvd/v37Q/d1bQjNiQCArRCVB6G5DWbRa9XcunUrdD+VSrmyroNz586dUL2DBw82fK3Dhw+7svaH/n3yIJIjnAkAAABAYp08CNgswpkAAAAAJMKVCAAAACAhwpkAYItE5UH4+QyaB6H1dC0I/3kaG7x3715XPnDgQOg5GifsryEBAK0WtR6Ev66DruXQ19fnytq3+fWUrgthFu7rVldXXVlzNDQ/wizcdyK5Xh9EEM4EAAAAIBGuRAAAAAAJ9fqVCAYRAAAAQEIMIgBgi0St+aCPm4XzIB49euTKfk6EPk/zGzSu1597nbUhAGwlXb/GbP1aDFGP61oOuo/Tp0+H6v3+9793ZT9fQum6ES+99JIrnzlzxpWDIAg9R3MxgKQYRAAAAAAJcSUCAAAAQCK9PohgdiYAAAAAiXAlAkDL+LkOmgcRtWaEWXQehF+vVqu5suZBaKyxzpVu1tm/8gBof1E5EL579+6F7mv+lvadfj+q+V+aR7F7d/h34OXlZVfW9XI+/fRTVz527FhTbUVzev1KBIMIAAAAIKFeH0QQzgQAAAAgEa5EAGiZuDCluKlb9b6GQPnTGT733D93WRrOpI8DgJnZN99848p+HxG3bTOvE7c/f/rpmzdvNqx348aN0P1UKuXKOhXsoUOHQvU0lHP//v0N2+O3AZvTqVciyuWylUolMzNbXFy0fD5v6XQ68X745gUAAAAS6tRBRKlUsqmpKTMzm5ubs9HRUatUKon3QzgTAAAA0APK5bLNzMy4++fPn7dqtWrVajXxvrgSAQAAACS0k1ci5ubmrFKpWD6fX7etWq1aPp+3oaEhM3saEjcxMWFmZplMxubn513dlZUVMzMbGBhI3AYGEQA2ReOBNZ/BLDoPQuN6/ftffPFF5P50SkPNl9A4X82VANC74nIdWplHFbcvnZLVp9Otfvzxx67s92G3b9925QcPHriyn4uhuRPaj/q5E2id7R5E1AcHZmZXr151AwO/zvDwsF2/ft2dE7lczmZnZ10IUzabdfULhYJNTEyEzp9mMYgAAAAA2lw6nbZCoWBmZteuXWtYJ5/PrxsUTE9PW39/vxtE1BWLRQuCwO0zKXIiAAAAgITqVyI2e2ulq1evujCmuvqAoj4jU728srLiBhBBECR+LQYRAAAAQEKtHETcv38/dPPDeZsRBIEFQdBwutZUKmXlctnMniZXV6tVO3/+vAVBYHNzcxt6/4QzAdgU7eg0Dte///nnn7vy/fv3Q/V0m8b5vvDCC6F6R44cceWTJ082LHfy6p8ANqfZ9R+2a52ITz/91JVffPHFUL27d+823N+TJ09C9zW3TPvb559/PrId+p/IV155JbLtaB+nTp0K3f/pT39qf/u3f5toH3EzLA0MDNjy8rLLmTAzm5ycdNsb5Vc8C4MIAAAAIKFWJlbfuHEjlAS/b9++Te23kfpVilqt1pL9MYgAAAAAEmrlIOLQoUObnkkrboal+lSurUROBAAAANDh6ms9NEqSDoJgQ9O4xuFKBIDEvv76a1eOWuPBLDoPwq+ndM2Hvr6+0Lb+/n5X1s6QPAgAZtH5DXF5C61+TV0bQkNStN80M9uzZ48rayy7rqljZnbgwAFX1ryKl156KVRPc8P8fDJsjZ1cbK6RVCplqVQq8qrD6Ohoy17LjEEEAAAAsCHt9iPW+fPnrVKphB6rD1J1kblWIJwJAAAA6CD16Vx9uVzOisVi6LFCobDhBeXicCUCAAAASGi7w5mCILCZmRkLgsCq1apdvXrVzMyGhobcatTpdNrm5+ctl8vZyMiIVatVGxwc3NAUrs/CIALoMN9++23D8u7d4QuLGm+rWnHpNWptCM2BMAvH9mo8sN8GbevevXtd2Y/r1ZkrDh48mLTZALqM5mSZRecC+HkL9+7dc2Vdf2Yj/HyLKDdv3gzdX11ddWXtO/2pPbVv17Uh/HUiNO/M34at0cpBxMjIiO3Zs8cuXbpkly5dalg3lUpZPp83M4u9spDJZCyTyWyqXc1gEAEAAADsoMXFxU1P8brdGEQAAAAACbXb7EzbjUEEAAAAkBCDCAAdReNjnzx54sqaH2EWHaerscF+3kRUZ/bo0aPQfY3f1ZwIv57mTmjZb5vmQcTlROgc6QCg/YVZuG/Rvk7XbjALr0fTzPPj6n311VehbTpjjvZ7cQ4fPuzKmttgFu7n64uJma1fnVjX0fGPC7AVGEQAAAAACXElAgAAAEAiu3fvXjcz4kb20ak6t+UAAAAAdkRbXYkolUq2sLDgFtEYHx9ftzhGM3WAbqbxsbr2Qtxc5VG/dMSt1xAX86vrP2jZz4nQOdz9fUS9rs6R7sctR8UxA+hNd+/eDd0/evSoK3/yySeu7K+b0NfX58ra1+n+/JwDzXU4ceJEZJv0tW7fvh3ZBu07o/pe//7+/ftdWXMgzDa/3gWS2+51ItpN2wwiSqWSlctlt4hGEAQ2PDxsS0tLbkGNZuoAAAAAW62Vg4hOXCeibcKZCoWCW7Lb7OkvALlczubm5qxarTZdBwAAAMDWaptBRLFYtFwuF3rs3LlzZvb0CkSzdQAAAICtVr8Ssdlbp2qbcKaxsTEbGhradB2g22nsbNysDlE5ErqehL+2hO5bt2lug1l4bQjdputHmIVzJOLmX9fX1ZhfPwfCX9cCQG/zcxO0n9H8CL/P+eijj1z55ZdfbrhvzTkzC+c06Otof2hmtry83HBbXD+qZb+f0xCX06dPN2wrdgZTvLaJ+fn5dY9du3bNzMyy2WzTdXyPHz8OLfbiL+ICAL3K7x8fPHiwg60BAHSStglnaiSfz1s+n7d0Or3hOjMzM9bX1+dup06d2qrmAkBH8fvHs2fP7nSTAKBj9Ho4U9sOIsbHxy2bzYYSqTdSZ3p62tbW1tztxo0bW9FcAOg4fv/47rvv7nSTAKBj9Pogom3CmdTc3JwNDAzETtvaTB2zp3PO67zzQDeJWjOi0f06jev1O69ardbw+X7Mb1Qsr857HtcGP+b3hRdecOUXX3yxYRmt5/ePhHui0/h5Bnv37nVlXZvm1q1bkfvQ2R1fe+01V9Z1JszCfefq6mrDsv+6mremeRhmZoODg66s+WRnzpwJ1dN26OeVdSGw09ruSkSxWLQgCEKDA13gpdk6AAAAwFZp5ZWIkZERO3v2rF2+fHmH31Xz2moQUS6XbWVlJRSeFARBaPrWZuoAAAAAW6mVg4jFxUV79913O2a1arM2CmeqVqs2MzNjFy5csGKx6B5fWFiwycnJpusAvSRuilcNJYoKe/JD/XR/Gprkz9qjIUx6Gd4PZ9JpEDWEyQ9n0nZoaJNO9woAPu0vfBpmpKFIZuHpo7U/+93vfufKx48fj9y3hlHpDGdmZp999pkra4hgX19fqJ6GWOk0rv50tBrWyTTXaCdtM4gYHh62IAhCg4O6ethSM3UAAACArcY6EW3CT0zaaB0AAABgq/X6IKKtciIAAAAAtL+2uRIBIDnNddD8AzOzb7/9tuE2zXvQKV19GvOreQ9m4ThfLfs5Ebp/zXvw43o190FjlQEgTtwUrzoFqj9dq07D+ujRI1ceGhpy5Zs3b4aeo4vaaj6D9rU+3ba2thbaprkOmhPhr2f1xhtvuLKf24GdtWvXrtjcxGb30amafucXLlzYynYAAAAAHaPXF5trehCxsLBgP//5z7eyLQAAAAA6QNPhTAMDA5bJZOzKlSu2trZmmUzGfvjDH25l2wAAAIC21OuJ1U0PInK5nP3whz90A4fr168zoADaiB+Xq+tBaFnjNzWnwr+v8bvLy8uhenfu3HFlzYnQ1zELxydrTsSBAwdC9TQPwt8GAFHi1onQXDA/l0Bnezx58qQrVyoVV9Y8Bf85mi/h54Ldvn3blXUNirjcCc0Li1sf5+jRo5HbsP1aOYgYGRmxPXv22KVLlzpmwbmmBxEXL14M3T9z5ox7rD6g2LVrl6XTaQYUAAAAQJMWFxfXDVzbXUumeD1z5oxduHDBarWaTU5O2uDgoP3oRz9qxa4BAACAttPridWbmuL1/v37dvXqVSsUClYul61Wq1k6nbaf/OQnNjY21qo2AgAAAG2FnIgm/ehHP7K/+7u/cwOH+fl5K5VKbuDw4x//2CYnJ+3MmTNb2V4AQnMY4nIidE70OFovCAJX9uc3j4o19mN59X5/f78rp1KpUD29hBsXDwwAraA5WpoHEUfXpNC1bu7evRuqpzlemoPmryeg+xscHHTl7373u6F6hw8fduXnnmN5L7SPps/GX/7yl1atVq1UKpnZ0xAmBg4AAADoRVyJaFIQBFapVOw//If/YGZm//W//lf7l//yX25VuwAAAIC2xSCiSWNjY3b16lV3///9v/9nP/vZz6y/v9/OnTvHgAIAAADoEU0PIi5cuBC6/+abb9qbb75pZgwogHbg50RofsOjR49cOS6PQmN0dU50P6dC44H1VxT/FxWN39UYZD/vQWOIAaAVdI0G3+PHjxvW07K//oPmPmjfqf2hWTgfTfs9n+ZI6Ho72g+bhfviI0eORO4P26/Xr0Q0PcVrPYypkTfffNN+/OMfW39/v42Pj9v3vvc9m56ebkkDAQAAgHbT61O8bnqdiF//+td24cIF27Nnj50/f96Wl5ftrbfesmw224r2AQAAAGgziad4NXs6cCgUClYsFs3MrK+vzy5evGjj4+P21ltvbU1LAQAAgDaxe/fudVP3bmQfnarpQcTCwoJduHDBSqWSra6uWiqVYuAA7LBarebKzeZE6BoPcc/RfWvZLBzzq/vw5zDXzvGFF15w5RdffDFUT7cBwEZp/6b9meYVmJndunXLldPptCv/9re/dWX/P3dR/a2fM6Z5Z7qOjp9jcfLkSVfWPtHvD3WNHbSXXs+JaHoQUa1WrVqt2tjYmE1OTjJwAAAAAFpgZGTE9uzZY5cuXbJLly7tdHOa0vQgIpvN2t///d9vZVsAAACAjtDKKxGLi4t26NChVjRr2zQ9iBgfH9/KdgAAAAAdg3CmJl28eHEr2wFgAzRGV2OBzcJxuhqLG5X3YBbOdXjw4IErr6yshOrp/jRu2F/voa+vz5UPHDjgygcPHgzV07hhYCP889/Pz0FviPq73759O3Rf+6qPP/7YlaPWjDALrwcRBEHDslk4XyIqL8yn7fne974X2sa5jHa1oTPz17/+tZXLZVteXnYfnlQqZf/u3/07+7f/9t+2sn0AAABA2+FKRAI/+9nPLJfLmdnTQcPAwICZPf2VMggCy+fztmvXLpubm7P/+B//Y+tbCwAAALSBXh9END057ZUrV2x5edlWV1ftyZMntrKyYh988IF98MEHtrKyYk+ePLEnT57Y+++/b++//779/Oc/38p2AwAAANghTV+JCILA3n777WfWS6fT9vbbb9vPfvazTTUMwLNtJCdC43U1xtffx5dffunKn3/+eaiebtNfUfwcC53fXF9r//79/lsBNqXZuHH/c7KRfaAzaJ5BPXKi7sMPP3RlXUdH12vw13W4f/9+w7KfO6F9oq4ZoTliZuFcM82D8Ne0OHLkiKF9dfKVhM1qusdMepCGhoYSNwYAAADoBIQzNemDDz4IzdbyLP/3//7fDTUIAAAAQHtr+krE1NSUvfLKKzY5OWlDQ0OhZeLNnoY7raysWKVSsWKxaPPz8y1vLAAAANAOev1KRNODiHQ6bdeuXbPZ2VmbmppaNy+y2dMZmy5cuGB///d/b2fOnGllOwE0oPG2usaDmdnjx49dWWN7/XpK8yj0+X4cueZVxOVE6DZdC2Lv3r2RbQBaQc9ZzXUg76E3ad9mFs59iFofx1+/Rvs9raePm4X7Qe3r7t27F6r3+uuvN6wX10ejvTCISCCdTtsvfvEL+8UvfmFra2tWrVbN7J+ne/WThgAAAAB0nw3/JNPX12dvvvmmmT1dfO5Xv/qVDQ0NsdgcAAAAut7u3btDq5JvdB+dqulBxM9//nP7L//lv4Qee+edd2xsbMxdkTB7OqXjf//v/93++q//unWtBNCQhmz4l+t12kG99K714qaF1ef7+9bL9Tp1q3/5/8CBA66s07oSzoSttpGwJZ26+IUXXmhlc7ADtA/TaVzNwufHZ5995sp6DsT1ezrttb9v7Qe1DTrldaP7dalUquHjaD+9Hs7U9PCnVqvZj370o9BjU1NTls/nrVKp2OrqqlUqFZuZmbEf//jH9r/+1/9qeWMBAACAbjMyMmJnz561y5cv73RTmtb0TzUXL160wcFB+8lPfmKvvPKKvfPOO5bP511Ik9nTEKeJiQk7f/68TU5OEtoEAACArtTKKxGLi4t26NChVjRr2zR9JWLXrl1Wq9VsYWHBzMyWl5cjF5RLpVLMzgQAAICuVR9EbPbWqZq+ElEqlUJv9Ny5c1Yqlezf//t/vyUNA/BsOhWgH5d7//59V9YpmTU/wn+O5kjo9LE+TQTT/AY/jlxje3VKRabZxFbTc3l1ddWVjxw5ElmPPIjuov2jn99w/fr1hvU+/fRTV/YTXnUfOm22n1um+9PzTftAs3Dfefz48YaPA+2s6W/ymZkZq9VqtrS0ZEEQuKsSmUzGXn31VXvnnXfs2rVr9p/+03+y//k//6eNjo5uZbsBAACAHcPsTE26du3ausd+/OMfu/L/+B//w2ZnZy0IAnvzzTftrbfeak0LAQAAgDbT67MztSym4O2337a33367VbsDAAAA0KYITO4BOrd1J494sZ7mNGjeg5nZ7du3Xfmjjz5y5ZWVFVfWOdHNwms+HDx40JX9WN6obYODg6F6ej9qTnRgK2jeTdy5p3Hu5Op0Ps1P0LUcNEfM7OnkMHV/+MMfXFn7RM2lMQv3dfv27XPlY8eOherpd66eU6dOnQrV07Vz9BzlPOwcvX4lYssCsX7+859v1a4BAACAHdXrszNt2SCiUqls1a4BAAAA7KCmr5n95Cc/aXq0FASBXb161f7u7/5uww0DAAAA2lWvhzM1PYhIp9P2k5/8xNLp9DPrBkGwLj4b2+fbb78N3df4TEXcZWfSGG6N2fWv/r3//vuu/Oc//9mV79y503BfZuE436NHj7ryK6+8Eqr3ne98x5V1bn0/Nljvd9pKnOhsGtuu5+i9e/dC9aLyJdbW1kL3+/r6Wtg6bBXt0/T/IR9//HGo3h//+EdX/u1vf+vKmiuh6z2YhXMYBgYGItuguQ/a7/nrP7z00kuR+0BnYIrXJk1MTFi5XLZf/OIXTdX/z//5P2+4UQAAAADa15b9FK0r1QIAAADdhHCmBHK5XNN1p6enEzcGAAAA6BSdPAjYrESDiDNnzjRdl/jR7aV5EH5OxJMnTxo+x8+VeP7551vfMLSczn3+ySefuPKNGzdC9fT+rVu3XDkuX0k7Q10zwo/l1fnSNTbYXyeCtSGwXXR9ALNwHoTmR/jnpOaG+ftA5/niiy8aljUXzMzs5s2brvzZZ581LGsfaBbuHzU/Iq5/1Lyw73//+6F6uo0cRXSiRGfthx9+aNVq1arVqmWzWXv11Ve3qFkAAABA++r1cKamU8L37Nlj4+PjFgSBjY+PM4AAAABAz6rPzrTZW6dq+kpEX1+f/epXv2KaRgAAAKDHNT2IOHfuXGgA8atf/WrdJZgf/vCHrWsZEmlFToSOhv1YULSP69evu/If/vAHV9YYX7PwfPh6Tujn2J/r/OTJk658/PhxV/ZzHXT2Nd2HPyubricBbCU/pjxqnYg4d+/edWVmGOxM2j/+5je/cWVdN8cs3F/qd9/Bgwdd2V/35vTp0648NDTkypoDYRZeY0fzJfycG3JHOx/hTE3yF5lLp9NWq9VsbGzM5ufnm1qEDgAAAOgG9UHEZm9mZiMjI3b27Fm7fPnyDr+r5jV9JcKf0eLMmTN25swZO3/+vL399tvrRtS//vWvuTIBAAAAPMPi4mLHpQw0fSUialrI/v7+hpfkFhYWNtwoAAAAoJ218kpEJ2r6SkS1WrWPPvpoXRx9EATrHg+CwEqlks3MzLSupVhHj7nmPcTlROhz4k7cAwcOtKKJaIH33nsvdP8f//EfXVnjfDUHwqcxukeOHGlYNgvH9uo5oHOi+/c1htjPgSC3Btslbp2IZp+n5+/XX38dWY85/dvHO++8E7qveRDvvvuuK+uaOmbhPkzLGnVx+PDh0HP0/ldffeXK/q/HDx8+dGXNidA8CnSHXs+JaLonXFhYaJj3UKvVbG5ubt1jnXxQAAAAAERrehCRTqctl8s1VbdWq9nPfvazDTcKAAAAaGetWOehJ9aJyGazdvHixaZ3XK1WN9QgAAAAoN0RztSkfD6faMfT09OJG4NkovIg/JwIva/P8U/cqHwJPx4eW08H4f/n//yf0DbNkVhbW3Plffv2herpnOYaH64xun5st54fWvZ/KdFzQvftz5cObJe4PAXNZ/jiiy8i62mcu58TwZon7eN3v/udK/s5EbpOhP49/RkmdQ0I7bf0XPHXWNK1RzQXzD9XNNfspZdeavwmgC6QaMXqJFhEBQAAAN2KKxEAAAAAEmEQ0UZKpZItLCxYEARWrVZtfHzcJiYmYp8zOjrKmhQAAADANmqbQUSpVLJyuexyL4IgsOHhYVtaWrJCodDwObOzs1YqlbazmW0lap0If770uBhPpbkTOjJ+/vnnQ/WY+39rVCoVV/7f//t/u/Lvf//7UD1d+FHXcvBjfjWP4dGjR66s8bt+LG/ULyJ+vHlUHgT5M2h3Gifv07wHf4FV/QywZsTW89e9WV1ddeV/+Id/cOWPPvooVE//btofDQwMhOrp96eu66Dfb34uWFTOjJ9no/lpJ0+edGXNR0N36PXZmdqm5YVCwaamptz9VCpluVzO5ubmGs70VK1WbXFxcTubCAAAAJgZK1a3zSCiWCyuW4fi3LlzZmYNrzYUi0W7cOHCtrQNAAAAwD9rm+uwY2NjTS8JXywWbWxszMrl8ha3qr1FhTP5ISrNhjP5YVB1fvgSUx22xp/+9KfQfb2yplff/L+ZTt2ql+j9enfu3HFlDVXT88anl1X17+5PH6shTHo+cLke7UjDTR48eBDaNjg46Moapvfb3/42VE/Pcz/EUxHe1Br+3+mf/umfXFn7Nr/P0f9H6N9WQzrNzG7cuOHK+t2nvwrHTfOrf+e4UFLFudF9SKxuE/Pz8+seu3btmpk9XeiuLggCW1lZsXQ63dQg4vHjx/b48WN3//79+y1oLQB0Pr9/9P/jBgCI1uuDiLYJZ2okn89bPp+3dDrtHpubm3vmjE1qZmbG+vr63O3UqVNb0VQA6Dh+/3j27NmdbhIAoEO07SBifHzcstlsKNm6VCqFrko0Y3p62tbW1txNL2ECQC/z+8d33313p5sEAB2j1xOr2yacSc3NzdnAwMC6qV3L5XJoUNGMffv2rYvn7hYa264x781O8erH0OuJrPv2cyI0rrNbj20raSyu/iftD3/4Q6je3bt3XTmVSrmy/+vwd7/7XVfWv5k/i1lUHoSGrPjTXUblRPhxxwcPHnRlcmQ6l98/dlO455dfftlUvevXr7vyoUOHXPkHP/hBqN57773nyhoD7+dHnDhxIlE7e53+nTTX4Te/+U2o3s2bN11Z88L8fIR/8S/+hSvrj4bav5qFvxe1P9PX8XMYtB/UPlXPG7Nwbs3Ro0cN3WvXrl2bnqKVQUQLFYtFC4IgNIAIgsCuXr1qlUolNINTPScil8vZ4OBg4gEGAAAAgOTaahBRLpdtZWUlNBgIgsBKpVLDPIi5uTkrlUpugToAAABgO/R6YnXbDCKq1arNzMzYhQsXrFgsuscXFhZscnKy4XP8FUUBAACA7cAgok0MDw9bEAShAUSdnxtRrVatUCi4uuPj4zY6Oppo1qZuEJUToWWz8FzXcesF6Ims+RL+CU5ORLz3338/dF/zIKLmJjcLx86+8cYbrvz666+H6ukaDZ999pkr61SdZuH4do071hwN/1zR2E6N9dYYXzOzAwcONCwD7UL7PT/3R505c8aVP/nkE1f2f6TSvs7/rKm1tTVX7uvra6qt3U77Oj/XQY/zrVu3XNk/xpob9tJLL7nyX/7lX4bqaV+lfaWuGWEW/l774IMPXPnIkSOuvLKyEnqOrjei+/PzBl977TVX1vf08ssvh+qxbgQ6Xducwaurq03XTafTbvpXAAAAYLtxJQIAAABAIrt379707Eybff5O6tyWAwAAANgRXInoElH5EWbheNSoNSP8fWiMp587ods0prPX1gvQ2GedQ/7jjz8O1dMcBF3jQVdiNzN79dVXXdlflyGKxuV+/vnnoW3Ly8uurLkTmuugceP+No0B9/+2GmtMXgzakZ7LWtYYdf++xqxXKpVQPd2mfaAfiqv9r+ZEaN/bC7Hw+n61T9S8E7PwsdD1H/7qr/4qVE/Xzmk210Sf4/d1SvMoPv30U1f2w0z0dQ8fPuzK/neu9om67174u/eaXg9n4koEAAAAgEQYRAAAAAA7aGRkxM6ePWuXL1/e6aY0jWtrAAAAQEKtDGdaXFy0Q4cOtaJZ24ZBRJfQ/AY/PlPnSI/LiVBx9fQDExV33GxMf7vTucqvX78e2nbz5k1X1jUZ/E7g+9//vitrHsT+/fs33T7NV/FjfjVH4uHDh66s54N/rujfLS7fRdeG0L870I7u3LnjyjqHv5nZvXv3XFnXU9GyWfgzrusF+J9jzVPSffhrrXSbarUauv/OO++4svajx48fD9XT+9/73vdcudX5A5oXZhbuBzUPIi6/UPtR/R7016DQ9+vnvqG7kBMBAAAAAAlwJQIAAABIqNevRDCIAAAAABJiEIGu0Ow6ERo3H7dOhJ7U/v6UzpcelR/h76/dafz07du3Xdlfh+HgwYOuPDQ05MonTpwI1dvKdRQ0RjcIgtA2va8x3BoL7J8DunJm3DoRmhMBtCPN79G8Bf18m4Xj17WvfOONN0L1NG7+yJEjrvzgwYPIeppvobkY/f39oed00voBH330UcPH//znP4fu/+Vf/qUr67oyfv+oNIdko8dE/4ba7/k5LrpNzxV93P/u0+87XTPCz4vR3I5eWx8EvYUzGgAAAEiIKxEAAAAAEun1QQSzMwEAAABIhCsRHUxHr83mRMTFw0flRGicvF9Pt2m8qJbNwvkD7WB1dTV0X+N8NZdAj4Mfx3zq1KnIbdtF47F1Hnv//qNHj1xZ82L8X0D07xm37ke3rAOC7qXx53r+a39oFv4Maa7Phx9+GLk/XTPGj4fXvk5zifR1dqq/aJafP/D73//elTVnQPuLo0ePhp5z7NgxV9b8gTitWEtD/07a12l+iln473H37l1XjsqVMFv/vVbn96O6Dz+fDN2FKxEAAAAAkACDCAAAAACJEM4EAAAAJNTr4UwMIjpY1InX7DoRfmyw5jooPw7Uz6Vo1B4/j0K36ZzhW01je2/duuXKKysroXr63jWWV+c0bzaud6tpXovmPSwvL4fq6boWGhOu54c/b7n+rXWdCD/um5wIdJJ0Ou3K//AP/xDapvHwhw4dityHflb0/PfzByqViitrjL9+njRm3iych/XKK6+4st9Ht3qdAc0T+Pjjj13Z7/P1/eq24eHhlrZHj+VG8yPW1tZcOW7tIu0T9bjqMfefMzAw0PA14/IeWBuiu/X6IIJwJgAAAACJMEQGAAAAEur1KxEMIgAAAIAN6ORBwGYxiOhgUSeun7OgMfAaT69ls+h1IvzX0ZjRZvIjzMI5ErqtFXNoa3s078HM7NNPP3Vlfb9+Xsbx48cbltvRw4cPXVnjfzWu2iwcX6zvXc8HP+ZX43c1hlvLjZ4HtBvtF/7pn/7Jlf1zWfMlND9CP1tm0Z8NP78hKl9IY/z/+Mc/hrbpGgutyAuI8t5774Xu37hxw5VTqZQr+98Nr7/+uitvZW5YK96v9oOaM+b3j5ozpsdc/7b+31L3NzQ05Mrtvu4HsFUYRAAAAAAJEc4EAAAAIBEGEehYUSeeP1WrXtZ//Phxw3Kj59X50/3p/vzpZJO21ddseNPq6qorf/bZZ66soT5m4cvMR44ccWW9dN/u/JCxBw8euLJeXtfHzcJTGOrUvlFha2bhMCWd1tWf4pVwJrQ7Dck5ePCgK9++fTtUT/scfY4/davuQ/vOuFAW3d8HH3zgyv60n9qHnT592pX9kKpmQ4m07TrlrB+m9N3vfteVdWrZdqffQXFTqH744YeufOfOndA2PeZRfaLf98ZNGQv0IgYRAAAAQEK9fiWCdSIAAAAAJMIgAgAAAEAihDN1sKhpWP3cBs1b0Nh4PydC4z91fzo9q1k4BlWfo68blV/xLFHTj2q7zcIxsRqT/PLLL4fqtXqKxJ3g53no1IQrKysNHzcL50RE5a7E/W3jpjr082SAdtPsZ1/zBPQz5H+e1IEDB1xZp4U1C0/5qm3Qx1999dXQcw4fPuzKv//9711Zp341C+dEaN6D3z9q36lTkfrTnJ44ccJ2WrNT2vo5KlE0T0y/n5aXl0P1dJvuW/tEv3+Myok4c+ZMqN5WToOL9tLr4UwMIgAAAICEen0QQTgTAAAAgES4EgEAAAAk1OtXIhhEdDCN14w7CTV/QGNn/TnDtZ7y5+HW+PpmcyL0vj7Hj+XVuGGNOdX4fDOzF1980ZUPHTrUsN2dRo+L/i38nAidO17Lfsyw/n31b6b5DP7fVnMfNO6bOdHRLbTvMDP76KOPXFnPeS2bhT+HGnev60eYhfs0/azpc3SNAv85yu/3rl+/7sovvfSSK8et46I5Y63IgWh2jQbVbN5DHD8vq+7WrVuh+9rvffrpp67sfydpPd2mf4u4turfXdcAMTMbHh6OfB66S68PIghnAgAAAJAIVyIAAACAhHr9SgSDCAAAACAhBhHoCnEnYbPrREStJeDnSmgcrD4nqmwWjvdvtp7GLvuxqc3G4u4EfQ9m4Xhbf97xqHr6d9I8ETOzBw8euLLGWfu5E7oPbZMeO3+9B42l1jjrqHhkoBO89tprrvyb3/wmtE37IP1sxa2jo59JP5/hO9/5jivr51PdvHkzdF/zLzTWXteBMTM7efKkK3/88ceu/MYbb0S2we8/1EbWM2i279XvDe2/NY/Lb0OzuROaz+DX0/VxNCdC/7Zm4f5S+149dn5frvl32j/qOh9AL2nf/4kBAAAAbarXr0SQWA0AAAAgEa5EAAAAAAn1+pUIBhFdotlY+6g1I/z7+hw/bl7jRJsp+/ej1pnwXzdu3YmovIq4+dK3i/+e9LhqW/33pDSu14+rXl5eduXPP/+84XPMwn9rbZN2WH58s85Lr3kQ5ESgk927d8+VdX0Fs3B8/d27d13Z/zxpDL1+nvw+Rj9DGv+vfXQqlQo9Z3V11ZU1D+Lo0aOheppLofvw10rQPAHNo2hWXB5cVL1mcyU2kodhZlatVhu+lt8/+mtw1Pk5Y0rPAc1P8fMtjh071rANr7zySuS+gW5GOBMAAADQQ6rVqo2Pj1sQBBveB4MIAAAAIKF6ONNmb9utVCpZEARWLBY3tR/CmQAAAICEOjUnIpvNmtn60MqkGER0CY239U9Ijb3XmHw/7lXnRY9b20D3ofHAGifsx/s3mxOhbdKyxqz6bdWyri1hFp7zW2OV/TyPjYjKy/Dfe1QH4a+RobkTmuvgz6uu93UOeH9eez1+UTkuzeZEtPO6HEAjev5rzoGe42bhWHtdo8Hvm/Rzp/2M//nW0ABdVyCqPWbh/i0u3l/zCbSP8HPBNJ9D+4WhoaFQPX3v6XS6YRvMotdv0HpxeRR+H6b0OyRuPQm/b6+7fft26L7mjejxi8tVi8rT8L/7otaQ0JwbM7P+/n5Xpu/EVpmbm7NKpWL5fH7dtmq1avl83n3mU6mUTUxMtLwNnN0AAABAQtt9JaI+ODAzu3r1asOBQbVateHhYbt+/bq70pDL5Wx2dtampqY21VYfgwgAAAAgoe0eRKTTaSsUCmZmdu3atYZ18vm8TUxMhEKVpqenrb+/v+WDCBKrAQAAgC5w9erVdaGL9QFFqVRq6WtxJaJLxOVEqLicCI0R1XjPuJyIqLUh4tZ1iFtPQtugZT8nQu9H5UeYhWODNd45bj2JqHyJuPwNbat/XJUey7i1PfR9PHjwILRN43x17nN/3Y+ov6G+v7g57rW8E+ttAK2iMerXr18PbdO+SXMV/M+d7kM/g3Hr6GhfoJ/BEydOhJ7zySefuLLG/uu6BH49bU9cPoL2lZpDZRbuB+Ny0DRXodm1ITSPQnMO9HG/TXfu3HHl48ePR+5b8x40T8Es/PeM+p4wC39P6veEHle/39P9nT592pWPHDkS2VZ0t3ZLrA6CwIIgCOU41aVSKSuXyy6pul5/MxhEAAAAAAm1chDhT6Swb9++dRNBPItOluAbGBhwi9WWSiUrl8tmZjYzM2MjIyM2NjaW6LXMGEQAAAAAO+rUqVOh+z/96U/tb//2b1v6GvUrD9ls1rLZ7KZzJBhEAAAAADvoxo0boWmhk16FMItf92FlZWUjzYrFIKJLNJsTERWv69+Pi+vXOFHNfYgqm0XnRMS1IS4nImoe9LicCC37c45rzK++Pz2u/ntSccdfY4A1hyFu7QudI92fg1xjtXV//rGMWs9DY7j9TkqPg8ZLkxOBTqPx+ho3r7lRZuEY+IGBAVeuVCqhehqvr59df70X/dxon6Gftffeey/0HM0Z0H7g7t27oXr6nnSdCL8v0c+4vr8//elPoXp6LPycKqX9gvLzEZTGWmveg/862i9rH+Yff6Vr2PzjP/5j5P6iymbRuW/699PXMQuv+/Hyyy9Htg+9pVU5DYcOHQqdYxtR78Ma5ToEQbDpxeV8zM4EAAAAdLhUKmWpVCryqsPo6GhLX48rEQAAAEBC7TY7k5nZ+fPn113Jqydc68xMrcCVCAAAAKCD1Kdz9eVyOSsWi6HHCoWCW6SulbgS0SWi1gEwix7l+rG8UWs0xD2v2fUforb584zr/vR9+O3RuGGNddUcgbh6fnysxvZq2V9PQuk+NO/Bj0/W468xtn48sb7fuPnqNRZa31+z60RoG/z3F/Xeo+KHgU6n5/nHH3/syv6aCgcOHGj4fH/dA+3TNCdC6/mx9vpaus3vRzWvQtdK8PtyXYdCp43UvsMsHONfn/rRzOwHP/hBqJ72RydPnnRl/Q+MH2utr6Xt9vPWND9N+zD/u0HzJf785z+7sn+MPv30U1fW4+rndel3heZ86N/M7x+1np4rg4ODoXqa4wK0UhAENjMzY0EQWLVatatXr5qZ2dDQkJtpKZ1O2/z8vOVyORsZGbFqtWqDg4M2MTHR8vYwiAAAAAASamU408jIiO3Zs8cuXbpkly5dalg3lUpZPp83M4u9spDJZCyTyWyqXc1gEAEAAAAk1MpBxOLi4qZnZ9puDCK6RLPhTHqp1r8MHDXFq19P96/b4qZ4jQpn8vet70PL/qVtDRnSsn+pXC9Z63SGcdOr6nPiwnii2ueHKemx0MvrOo2rWTicQEMVdGpJ/3kaUhU3zaOWNVzCn7pRQwuiwjeATqNhMn6oiX52o6ZnNQuHDGl4jz9lrH6O9fOknzu/P1NxU0lraKOGCPnhNNp/aH/k94/ah+l/Xvw+R/sWTdjU9+GHiOo2DSWKmi7WLNy3+WGcGsKkf8/bt283tQ8/7Ez/1lGhm/5/6PR4pdPpyH0DvYJBBAAAAJBQO87OtJ2YnQkAAABAIm11JaJUKtnCwoLLOh8fH2+YTV6tVq1QKNjg4KAtLy/byMiIjY2N7UCLAQAAgN7TNoOIUqlk5XLZZZ0HQWDDw8O2tLQUykAvlUpWKBRsfn7e1Xvrrbd6fhARlUtgFo7xjMqPMAvnJ2gMbFzeQlROhP+cqG3+1IQaR6uvozka/vvQON+4afy07Mfbatyw5gJorKwfy6sxzrpvPz5W8yB0m19Pp2LUaQr9eaD1eRqH7P899VhG5UFozLZZ+DjExS4DnUTPa52a0yzct2hfojkHZuHPeNRn39+f9m865amfE6H7077Jnzb1yJEjrnzv3j1X9vMCBgYGXFn7FT/GX9v0xz/+0ZUPHz4cqqf9oOaUaB/hr5D72muvufKtW7ci26DH/IMPPnBlP8RDv5M0Z0NzUMzC71ePv//doHkV+p107Nixho+bmb3++uuurMe/v7/f0JsIZ2oThULBzXFr9rTzzOVyNjc351baC4LAxsfH7cqVK67etWvX3HYAAABgO9QHEZu9daq2GUQUi0XL5XKhx86dO2dmT68+mJnNzMzYuXPnQr/OZLPZ0EwZAAAAALZW2wwixsbGbGhoKLZOsVi00dFRM/vn8CcAAACgk42MjNjZs2ft8uXLO92UprVNTkQ9x0Fdu3bNzJ5ebTAzF7Y0Nzdn58+ft2q1aqOjo5bP5yNX5nv8+HEo5lLjJbtJ3DoRui0uJ0LjR7Ucl4+g9eLWf9DX0vhfv57uL6rdcds0ztWvp7HLmqfg39d53zVnIC72OSq+1iz8njSHwV8nQmOK9eqaxi2bReer+HHWGtMdlQfhx1zre/djwtF9/P7RzxXqFnHrMkT1iX6+ln4m446T5lTpZ1o/W35fon3B0aNHI9v94YcfurJ+Pv08A31d7ac0t8EsOg/OX+vms88+c2Xtw3R9Cq3j70+3ab6GWfi963Hxc8H0u1vzEfxjqff1Of7r6rHQbXpcT548aVE0PwW9q9cXm2ubKxGN5PN5y+fzlk6n3QBiYWHBJiYmLJVKWSaTsVwuZ2+99VbkPmZmZqyvr8/dTp06tV3NB4C25vePZ8+e3ekmAQA6RNsOIsbHxy2bzYaSrc1s3RWHbDZrQRDY3Nxcw/1MT0/b2tqau924cWPL2gwAncTvH999992dbhIAdIxeT6xum3AmNTc3ZwMDA6GpXeuXG6PyJpaWlho+vm/fPsIyAKABv3/s1nBPANgKvT7Fa9sNIorFogVBEBpABEFgqVTKUqnUujjJumclZXc7zYPwcyJ0fmw9Wf0TNyoe2M+J0Hr6WnHrP0StE+HP3R21ToS/9kWzovah8bpm4bnKo+Jy/bb6x7nRvvz9Ra0ZYRbOfdCYa39/+vfQ9+S3LyonQmMu/ThhzZfw9wd0A/9HJY3/17yFuFn/tJ/y+zr9vOtnKOpxs3Bfoq8b1wa/D1N+m6L2p32B9k3+WhpK+ybNZ/D7M8050Peua0aYhfPJdM0Hf0CrfbFu8/Pg9L3r3zZuTSKtp8fklVdeCT1Hc8g++uijyHpAr2ircKZyuWwrKyuhEKYgCNwUr+fPn7fFxcXQc+odSz35GgAAAMDWapsrEdVq1WZmZuzChQtWLBbd4wsLCzY5OWlmTxOth4eHrVqtWjqdNjOzXC5nY2NjkbMzAQAAAK1GOFObGB4etiAIQgOIunpoUyqVsqWlJcvlcu6y4tDQUCj0CQAAAMDWaptBRLOrTqdSKQYNDWhMrT+3uN7XctzoV/MW/JyIqNwHLftrUETlRDS7TsRGcyKUHiP/Pel9bYPGHfvHVetpXK6fw6D7iCqbhedf121+W5W2yY/11vnqNdZb8yD8Oak1JwLoRv7c/3/84x9dWT9rcblg+nnXz61Zc+vy+P2j9oNROWf+vjWvwl9LRrfpPu7evRuqp23Xffv5A5rfoG3V/Ah/DYo//elPrqw5WZr34O9PX9dfR0dzNvQ5fk6Evnd9T9ofmoX7QW275j1ou33kQcCstVciRkZGbM+ePXbp0iW7dOlSK5q35dpmEAEAAAB0ChabAwAAAIAEGEQAAAAASIRwpi6hl9P82P2oNSTi8gzi1nyIitHX142L+W02JyKurVFtbzbPw4+j1TyGzR4j/3hF1Ytrgx5j/xjpe9T4Xz8mWfMb+vr6XHlwcNCVNf7XLD4GGOhUuobB3r17Q9s0fEA/79evXw/V07wizSXw8xH086mfcf2srqyshJ6j27SP0M+tWXg9A923399q+3Sbnxeg6zdo/+H3e7o/7Y/iFifU46prKvj9lOY+RK1V5G/Tsp+Dpm3Xvtz/u+t9Pa4vv/yyK/vrUvX397syfSXMmJ2JKxEAAAAAEuFKBAAAAJAQVyIAAAAAIAGuRHShuHUioubQNoseDfsx+RqLG7WehP+cZnMiota0aLatzc6/7otakyJqzvc4cWtk6DHy14nY7NoQ/hoPGk99+PBhV9b50f2Ya//cAbqBn3+kNE/gs88+c2U/dl/XMtL9+f2CxvhrrL3mD/i5CRprH5WfZRbOv9CYfL/P0X5Bt/lrWmjbtf/xX1fXg9D9af+h3y1m4TUp9Dn++g/a1+nr+rkm2hfrc/y/reZ5aZv8/lGP+bFjx1xZvzMymUzoOfSPQBifCAAAACAhwpkAAAAAJFIfRGz2ZvZ0xeqzZ8/a5cuXd/hdNY8rEQAAAMAO6sQVqxlEdCE/NlXjYzXO16+n8ah6eS1uLQeNTY0q+22IW1NhszkRrRC1b//xqDUk/OMVNfe5H8urx0yf47+O/t00tlrnsTcLrwfx0ksvubLmR/jPAbqRxu5/8sknoW2at6Cx/34fpusK6GfSz0fQnKMvvvjClfVz6/cRfvx/nd8/RvUffo6Ftknr+bkOUetYaH9tFj4W+t71ePnrMETlyPn1NBdD+1j/uGquSNzaF9o+3aZ/Z7Nw/3jy5ElXHhkZMaBZhDMBAAAAQAIMIgAAAAAkQjgTAAAAsAGdHI60WQwiupA/l7XGoGqsa1xORNRaCWbROREa9xr3HG1PXL6Flv1Y3s2u3xCXtxDFfx29H9eGqHUx/Hhn3ab78/+eGuersd4a42sWzoM4evSoK2tOhB+fDHQ7/SyYhddO0KRGP9Ze14nQfs//HGuMv+ZE6LoOcetWaF+neQBm4b5A+6wvv/wyVE/j//X9+X2JvpbWe/jwYaiefldoHoTm2Plt0O8afd0gCEL19DjrvuPyN3R/ui6EWfi74ciRI66s/Z5ZuO88fvy4NaJ/P/85gBk5EYQzAQAAAEiEQQQAAACARAhn6kJxU7zqJXW9FO0/L2q6V1/clKVR9eKmgtU2aKiNfxm+2XCmqPAo/3Wjwpn0dZoNqfLbo/uOKvvP0/fr/510WladTlLDl8zMXn75ZVfWEI5Om4caaKW7d++G7muYkn6G7ty5E6oXNV2ohuCYhcMSNbQpqo7fhqhQJH+b7lv7ATOztbU1V9Z+yw+90nAp7c/8KWf1tTR8aGVlxZX1u8Us3J/F9b3Ly8uuHDUVuL9//a7xw5n0/Wr4kR+K9NprrzXc5r8PIA7hTAAAAACQAFciAAAAgIS4EgEAAAAACXAlogv503ZqTL3G9fpTGGo93UdcLkDU9KV+zK/GwWq8f1xORNRz/DYoP45W96FxtHFTuuqvAvre46ZHbDZHQ7f57yEqH0TjoM3M+vv7XVlzHU6ePBmqd+zYMVf2Y6aBXnXixInQff18lctlVx4aGgrV02lP79+/78p+TL7W07LmN/j5Y9ofRfWvZuH8C32OPxWs5jBov+X3j34+R53/HaJTneo+dN/+FK9R9TTvwSzcJ+o+/P5R36PmLfh5J5rXon2ln+ugU7760/4CO2FkZMT27Nljly5dskuXLu10c5rCIAIAAABIqJXhTIuLix038QnhTAAAAAASYRABAAAAIBHCmbqQf2lNcx80LtS/bKbbNG7Vj4+NWk9CY1bj1mGIWydCY4W1HJePoPyY36h1IvycCI09jspv8F9T78etqxGVV+HHBuu2uL+T5jdofLcf1zs4OOjK/t8QwFPan2lfqesXmIVzxvQ5ft6CrrEQlZPlr+WjuQm6ZoTf70X1H59++mlkPe2P/LZGrU2jORBm4b5Tczvi8ts0H0Hfk98/al+n/bKfs6drOei206dPh+rpsX3jjTdc2c9d0fv+cQaaxexMAAAAAJAAgwgAAAAAiXANDwAAAEio18OZGET0AI3lffHFF13ZjxE9ePCgK+vc6X58rMbiaiypxv7786BrTK3G5fpxtLq/uJyIqA+dn+ugr6uvFZcToaLyHvz7UcfBLDqHxJ8HXfMWNObXz4nQ+c01P8L/e/rrSwBYTz93ujaErvFgZvbRRx+5svaVfl+nax1oOSp/zCzcn+m6B3497TO0b/Pzq3QdC+1//LZqv6fHYW1tLVRP+xJ9XW23n+dx584dV9b+MS6/Tfft96O6TY+/X+/IkSOuHPVd1ai9AJIjnAkAAABAIlyJAAAAABLq9XAmrkQAAAAASIQrET0gas0BP4Ze4+t13nKN6zULx+lqWeNtNa7X3xaXE6H349Zo2GxOhL+ehD5P9x0X8xsV5+uvyRA1T7ufExE1X73msZiF51/XudP9HAh//wDW8/uqutdffz2y3u9+9ztX9vMHtI/V/lH7Ac1ZMItem0bXZDAL91u6HoVfT/cR1QeahfM+dJufY6FrZmj/pu/P7/d0H1F5Yf7ran/m9/GaB6F9oN9Wfa1jx465suZKmIW/F7UNrBkBNI9PCwAAAJAQ4UwAAAAAkACDCAAAAGAHjYyM2NmzZ+3y5cs73ZSmEc7UYzReV3MgzMK5Dxor689VHpVbELUWhFk450D35+cwRMUnx9F9xK3/ENe+KBqr7M+xHpcHEVUvat/+PjTO18910FheXQMkrg0AGtPPUxAEruznjGkc/ssvv+zKfl+i/YT2sZq34K/9srKy4spReWZm4c+7bvPrad6B9ql+n+P37XV+7oT2q7q/uLWBlB4jP4dBQzn0b+H3m5onpu/Dr/fqq682bIPu20ceBDaqleFMi4uL6/qGdseVCAAAAACJMIgAAAAAkAjX8AAAAICEen12JgYRPUbjSv15s6NyHeLyBzQ2Vcv+mgoaO/vFF1+4suZe+K8V14aobc3W83Mnmlknwo+b1fu6b79D0FyFuHpRcb7+sYyac72TOyKgHZw4ccKV/fVxTp486cq3b9925aNHj4bq6ef4ww8/dGX93N67dy/0HP0cf/rppw0fNwv30XH9ntaLeo5ZOL8hKtfBLPye4vowpd81Guft92dRbfXrafs0v+Tw4cORbfXXAwLQWoQzAQAAAEiEQQQAAACARAhnAgAAABIiJwI96+DBg6H7UfH//rzeum6BlnUebp333K93//79hmUzs88//9yV49aqiFqfwp+rvNkYYj9Hok7ja/04YY3Z1ef7c7Hr8Wt2LY2ovAwA28NfV0Dvp9NpV9a1JczCn3/97H/wwQeu7K/p8uDBg4bP0cfNwnka2l/4+Rvar2qfGLeOjvaVfj+q70nr6feE30/p/bg+WvMlNF/Oz4mI0tfXF7qv+x8cHGzYbr/tADaGcCYAAAAAiTAUBwAAABLq9XAmrkQAAAAASIQrEXBefPFFV46a49vMbGBgwJVfeuklV75165Yr61znZmbLy8uuvLq66spra2uhehoDrNv8elFrTcTNl67b/LjcqLUw9BcCP9ch6jl+rG3UXOz+HOZ6P2rudL9eXJ4HgNbRz+Hp06dd+fvf/36oXtR6OalUypX9/lFzGm7cuNFwX2bhvvOzzz5zZb/P0dwHzTPz+z3tOzUXw89Vi8rX0mPi53n4eWx1usaDWfi46HP8967vcf/+/Q3bYBbuY/U4Hzt2LFRP8/TIjwA2hk8OAAAAkBDhTAAAAACQAFci0JBOZ3r48OHQNg1nOn78uCufPHnSle/duxd6zt27d135zp07DR83C08Nq5fu/cvrUfX8sCd9Hxoy4IcSNRMWFBcupL8k+FMT6iV6Letld7NwqIGW/bAA3ab78EMVNCQNwOZoyIs/raj6N//m37iyhtpoP6qhn2bhaWLPnj3ryh999FGonobnaHv8kFOdvlv7R79f1hAm7Tv9UCLlhw/V+WFKUdO/+qFD2j7l93sawqqvFTdtrYboaviSv7+4vyeAaAwiAAAAgIQIZwIAAACABBhEAAAAAEiEcCYkpvGyOj2flnXqV7NwzK9O9+rH6N68edOVb9++7cp+7oTG/Go5LsdC2+3H/EblKmh8bVzsreZY+LkJGkMclR/h39epFzWXwyw8Da5u82OSX3jhBVdmCkNg+2lfkk6nXVmniPWVy2VX9vvRSqXiyidOnHBl7SvNwjkX2j/607Bqvxw1dbRZuE/T0Au/T1S6Tfft93vaT+nr+rkSmveh09Z+8sknoXr6fjXP4+jRo6F6fo4EsBGtDGcaGRmxPXv22KVLl+zSpUutaN6W438WAAAAwA5aXFxcN0lCuyOcCQAAAEAiXIkAAAAAEur12ZkYRGBL+GsU6P3BwUFXPnLkSKiebtMYVn++dI2D3b9/vyv7Mb96X9eM8HMi9EOsZY0F9uOEoz74fj3NidAYaT+HQWOFdZvOZ24WzonQ2GC/nsYa63zpALaHfgaVn6OkfcS/+lf/ypX9nLEzZ8648vvvv+/Kx44di9y/9hF+n6X1NIdB148wC6/To32T9md+fkRUn+r3j5ovEbd2g7ZBvyf8dSt0LQ39DvFzLPS7gXUigI0hnAkAAABAIm11JaJUKtnCwoIFQWDVatXGx8dtYmIiVKdcLlupVDKzp7P8DA4O2tTU1E40FwAAAD2KcKY2USqVrFwuWz6fN7OnU88NDw/b0tKSFQoFMzOrVqtWKpVCg4ZyuWzj4+M2Pz+/I+0GAAAAek3bDCIKhUJoIJBKpSyXy9nk5KTlcjlLp9OWz+ctl8uFnpfJZEJzXaP9aSyqH8ur+Q1a9mN0NZY3bv2HqBG+/3jUPrSssbtx+/P3rbHCGg+s8cRm4fwLjTvWNSPMwnHDWs+ffz2uvQDaR9Q6Ln7OmPJzqpTmQWiOgJ8/oNNJan/rrzvhP69O88z8/kb7PX2+30dHrbfj949K+zp9r2bh7xSt56+3o8dW28eaOkDz2iYnolgsrhsgnDt3zszMhS+trKy4KxVKFxQDAAAAtlo9nGmzt07VNoOIsbExGxoaiq0zOTlpc3NzNj4+7q4+zM7O2uTk5Da0EAAAAIBZG4UzNcppuHbtmpmZZbNZ9289pKlYLNrY2JhNT09bJpOJ3O/jx49DlzTX1tbMLDxdHNqH/l3ipi/VEJ+oKQfNwiFCesnav/Sul9T1MnxU2RdXL+pyvR8ioG3V9+GHKel71+PiX9bXY9nJv3Rg6/j9Y33qZPrH9qdTPW+0f9T7re4fm62n+9Zyq/tHPV5m4XOccCY8S/188c/fVvSVHd3f1tpYOp2u5fP50GOVSqU2NjZWy2QyNTOrjY2N1VZXVyP38dOf/rRmZty4cePGjRs3bty4bfh248aNWq1Wqz18+LB2/Pjxlu33+PHjtYcPH27lf6m3xK5aLebn1R00Pj5uAwMDbmYms6czMc3MzLirFrOzsy7pulKpNNyP/0vbkydPbGVlxQYHB1v26+z9+/ft1KlTduPGjVCiWq/ieIRxPNbjmITt1PHw+8dvv/3Wbty4YX/xF38RSprdKP7O63FMwjgeYRyPsHY5HrVazR48eGAnTpxwkwM8evQodgKAJPbu3Rua3KBTtOV1u7m5uXUDCDOzixcv2tLSkrs/NTVlY2NjNjw8bHNzc+vWlDB7OquPP7NPKpXaknYfOnSID73geIRxPNbjmIS1w/F45ZVXWr7Pdnhf7YZjEsbxCON4hLXD8fBXNt+/f39H/se/ldpuEFEsFi0IgtAAIggCW1lZsYGBgXX10+m0TU9PhwYXAAAAALZO28zOZPY0XGllZSW0mFwQBFYqlSydTlu1Wm34vFQqZcPDw9vVTAAAAKCntc0golqt2szMjA0MDFixWHS3es6D2dNpYGdnZ0PPC4LAFhYWGoYybZd9+/bZT3/603VhU72K4xHG8ViPYxLWrcejW9/XZnBMwjgeYRyPMI5He2ubxOr+/v7Ilae1iXNzc7a0tOTyGgYHB0NXLgAAAABsrbYZRAAAAADoDG0TzgQAAACgMzCIAAAAAJAIgwgAAAAAibTdOhGdolqtWj6ft6GhITN7Os1sMzNEDQ8P2/T0tGWzWTN7mihuZh2THL7R973R57W7Xj0P4szNzVmlUrF8Pt9U/W49N1TSY9Lp50cvfi7oG9frxfPgWegfw3qtb+w6NSRWqVRqqVSqtrq66h6bmpqq5fP5Zz7XzEK3iYmJLWxpa230fW/meLWzXj0PGqlUKrWJiYnaxMRELZVK1aamppp+XjeeG7Xaxo9JrdbZ50cvfi7oG9frxfMgCv1jWK/2jd2I2Zk2YHJy0lKpVGjkHASB9ff327MO5+TkpFsYL5vNujUwOsFG3/dmjlc769Xz4FmGh4ctm8029ctSt54bviTHxKyzz49e/FzQN67Xi+dBM+gfw3qpb+xG5ERswNWrV92lxbr6uhWlUin2uUNDQzYxMWETExMdd/Jv9H1v5ni1s149D1qpW8+Nzerk86MXPxf0jev14nnQat18fmwU50Z7YRCRUBAEFgRBw5M3lUpZuVxuah+lUqmpuu1io++7FcerHfXqedBK3XputEonnh+9+Lmgb1yvF8+DVuvm82Ozev3caCcMIhKqVquR2wYGBmx5eTn2+QsLC1YqlezcuXNmZjY6OtoRH4SNvu/NHq921avnQSt167nRCp16fvTi54K+cb1ePA9arZvPj83g3GgvzM7UYkEQxG4vFArul4VMJmOTk5M2Pj5ulUplG1q3dZ71vlv9vHbXq+dBK3XrudGMbj0/evFzQd+4Xi+eB63WzedHHM6N9sKViITq8YiNrKysPPP5/qXJTCZj1Wq17eMbN/q+N3u82lWvnget1K3nRit06vnRi58L+sb1evE8aLVuPj82g3OjvfTslYhyuWwXL15suv6VK1csk8nYwMCAmTX+FSAIgtgPfi6XswsXLlgmk3GP1fcXd+myHWz0fW/meLWzXj0PWqlbz43Naofzg/6xefSN6/XiedBq3Xx+bBTnRvvp2UFEJpOxpaWlxM9LpVKWSqUifwkYHR2NfO7s7KwNDQ2FPgD1/bT7LAMbfd+bOV7trFfPg1bq1nNjs9rh/KB/bB5943q9eB60WjefHxvFudF+CGfagPPnz6+Lv6uPguurKDaSz+fXrTRZKpUslUrFPq9dbPR9b/R57a5Xz4NW6tZzYzM6/fzoxc8FfeN6vXgetFo3nx8bwbnRhnZmjbvOVqlUaul0OvTY1NRUrVAouPurq6u1bDZbW1paco8tLCzU5ufnQ3XS6XTosXa20ffdzPM6Ua+eB8+STqcbriLaS+eGL8kx6fTzoxc/F/SN6/XiedAM+sewXuobu1HPhjNtRjqdtvn5ecvlcjYyMmLVatUGBwdDI+SVlRW7du1a6FJkNpu1UqlkuVzOzJ7+olAoFDpmBL3R993M8zpRr54HjQRBYDMzMxYEgVWrVbt69aqZPV0YaGpqysx669ww2/gx6fTzoxc/F/SN6/XieRCF/jGsV/vGbrSrVuuStdMBAAAAbAtyIgAAAAAkwiACAAAAQCIMIgAAAAAkwiACAAAAQCIMIgAAAAAkwiACAAAAQCIMIgAAAAAkwiACAAAAQCIMIgAAAAAkwiAC2y4IApucnLShoSHbtWuXjY6O2uTkpOVyOZucnLTR0VHr7++3Xbt2hZ5XrVZtcnLSZmdnbXZ21ubm5tbtu1wuuzq5XK5hnWftZ25uzkZHR23Xrl02NDRkk5OTbluxWLTx8XHbtWuX9ff3h7bVnzs0NGT9/f02Pj6+mcO04ePktyeXyzXcNjw8bMVi0YIgsCAI3PFQnXKsgG5B/9gc+kegDdSAHVIoFGpmVqtUKuu2ra6u1jKZjNtWqVRqqVSqtrq66upMTU3V8vm8u7+0tFRLp9OhOhMTE6E6zeynzsxqY2NjDdueTqdr2Wy24baFhYWG+9uoJMepVnv6HicmJmoTExO1VCpVm5qaarhfMwvdJiYmQts78VgB3YL+sTn0j8DOYRCBHRPX+ddqtdr8/HxtYWGhVqs9/bLzO/vV1dWajoPT6fS6OktLS6E6zeynbmxsrJZKpRq2bWxsrGZmoS8QfV+tlOQ4+TKZTOSX5MTERK1QKNQKhULDfXfisQK6Bf1jc+gfgZ1DOBPaVjabtWq1amZmV69etaGhodD2VCplZmalUsmCILBqtbquTiaTcXWa2Y+anJy0IAjWPa6uXr267rEgCOLfWIvpcUpiaGjIJiYmbGJiwtLp9Lrt3XisgG5B/9gc+kdg6zCIQFupVquuo02lUpbNZl1MaqOOPJVKWblctpWVFTMzGxgYaLjfcrnc1H5UNpu1VCplhUJh3b6mp6ctnU7b/Pz8uvbXv5i3UqPjtBH1Lzb/vXfTsQK6Bf1jc+gfge3BIAJtxf/FKJ1Ox/6KNDAwYMvLy64zr39Z1tV/yalUKk3tx3f+/HkrFouhx0qlkmUyGRsbG3O/8um2jX5hJdHoOCW1sLBgpVLJzp07Z2Zmo6Oj7suvm44V0C3oH5tD/whsDwYR2HH5fN7NqLGRWSjqHe/U1JQtLCyEtsVdPo7aj6q3R/dTv2Rdn01DL0Nv5eXnzR4nX6FQsLGxMUulUpbJZBLtt92PFdAt6B+bQ/8IbL/ndroBQC6Xs3Q6Hdlp1jvaRvSXtXw+b+Pj41YsFt0vO/XnDg0NNb0fpZehs9mslctl98tUOp22dDpthULBJiYmtvzy87OOU1L+r3OZTMaFAcT9ctcJxwroFvSPzaF/BLYfVyLQNlKpVMM5u+txvI2+HIIgCH35zc/PWyaTsWKxaOl02l0OzmQyifaj9DJ0/fJz3djYmIsnjrr8XC6XbXh4uOmbH0/rizpOSeRyuXWvUz8+1Wp1x44VgMboH+kfgXbDlQi0lfovMiqVSlkqlYr8hWd0dDRyH/Vf2+odcpL91I2Pj9vc3JwVi8V1Xw71hYYazaxRl8lkbGlpKXL7RjQ6TknMzs7a0NBQ6EusflzS6XTiY1632WMFIBr9Y3PoH4HtwZUIdITz589bpVIJPVZPbqt/ATaKWS0UCjY9PZ1oP776ZehcLucuP9fVv6zy+fymvrS2Wz6ft4mJidBj/n8oOFZAZ6B/bC36R6A5DCKw45qJYc3lcutmtigUCuumzNNfgOqzXUxNTSXej+/8+fNmZg3jVCcnJ21lZWXLLz9vJNa3PhWhrx7SoPXy+bxduXLFPdbJxwroFvSPzaF/BLYf4UzYdkEQ2MzMjOuAL168aNls1kZHRyM7z/o82rlczkZGRqxardrg4GDo16L67BwaD+vPRtLMfhoZHx+PjHMdGxtb94tUK2zkOOnzgv9/gan65fGhoSH3H4ZsNmulUskdq2q16hL+6jrpWAHdgv6xOfSPwM7bVavVajvdCAAAAACdg3AmAAAAAIkwiAAAAACQCIMIAAAAAIkwiAAAAACQCIMIAAAAAIkwiAAAAACQCIMIAAAAAIkwiAAAAACQCIMIAAAAAIkwiAAAAACQCIMIAAAAAIkwiAAAAACQyP8HtIHqBRv3qJgAAAAASUVORK5CYII=", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=true,figsize=(10,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.0)\n", "\n", "im1=axs[1].imshow(permutedims(model2), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5), rasterized=true) \n", "axs[1].text(0.1,0.9,\"Smooth\",transform=axs[1].transAxes)\n", "axs[2].imshow(permutedims(model3), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5,vmax=im1.get_clim()[2]), rasterized=true) \n", "axs[2].text(0.1,0.9,\"Poisson-Sampled\",transform=axs[2].transAxes)\n", "axs[1].set_xlabel(L\"F090W$-$F150W\")\n", "axs[2].set_xlabel(L\"F090W$-$F150W\")\n", "axs[1].set_ylabel(\"F150W\")\n", "axs[1].set_ylim(reverse(extrema(edges[2]))) \n", "axs[1].set_xlim(extrema(edges[1]))\n", "fig.colorbar(im1, ax=axs, pad=0.005)" ] }, { "cell_type": "markdown", "id": "5fa33827-24e8-4943-91f1-85a22f25a208", "metadata": {}, "source": [ "To sample the color-magnitude diagram (CMD) directly we could use `generate_stars_mass_composite`," ] }, { "cell_type": "code", "execution_count": 34, "id": "d3527a3e-f946-477e-8d21-10c009aaf205", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2.242130 seconds (5.07 M allocations: 1.097 GiB, 196.20% compilation time)\n" ] }, { "data": { "text/plain": [ "(Vector{StaticArraysCore.SVector{1, Float64}}[[[0.9083666536495625]], [[0.25784097909029025]], [[0.4508529121717616]], [[0.28918946166001386]], [], [[0.09860755299372617]], [[0.1157098623405801]], [[0.2865831715946679]], [[0.2951919349799215]], [[0.2103895528927366]] … [[0.24900826706006152]], [[0.15494321020253296]], [[0.3214294053167704]], [[0.10638255140558214]], [[0.7311418854198203]], [], [], [[0.3545041482558462]], [], []], Vector{StaticArraysCore.SVector{2, Float64}}[[[28.83548412583513, 28.16251701748439]], [[31.06845592701241, 30.084712142433734]], [[30.223431238843848, 29.35896777074739]], [[30.906001402920687, 29.930591665332777]], [], [[32.43334833524872, 31.28259315970932]], [[32.240249479821024, 31.09100820713627]], [[30.984995382267556, 29.903241962365932]], [[30.962172414592047, 29.86352478521305]], [[31.465621253685427, 30.319936011512176]] … [[33.89684858274402, 32.71972532675991]], [[35.14580340366173, 33.8737125440467]], [[33.463873172957875, 32.26021030807795]], [[36.666138988989545, 35.08847735462781]], [[30.082443423719994, 29.26735648185978]], [], [], [[33.59812899222108, 32.22392154871349]], [], []])" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: generate_stars_mass_composite, NoBinaries\n", "@time starcat = generate_stars_mass_composite(template_mini, template_isomags, [\"F090W\", \"F150W\"], stellar_mass, x0, imf; \n", " dist_mod=distmod, binary_model=NoBinaries())" ] }, { "cell_type": "markdown", "id": "88dde706-f9c1-4048-9e4c-2530a42023b9", "metadata": { "tags": [] }, "source": [ "We'll concatenate the per-population samples returned from `generate_stars_mass_composite` into a single `Vector{SVector}`. " ] }, { "cell_type": "code", "execution_count": 35, "id": "52cfc0bd-6487-43d6-b3c3-66e24448488a", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "14745458-element Vector{StaticArraysCore.SVector{2, Float64}}:\n", " [28.83548412583513, 28.16251701748439]\n", " [31.06845592701241, 30.084712142433734]\n", " [30.223431238843848, 29.35896777074739]\n", " [30.906001402920687, 29.930591665332777]\n", " [32.43334833524872, 31.28259315970932]\n", " [32.240249479821024, 31.09100820713627]\n", " [30.984995382267556, 29.903241962365932]\n", " [30.962172414592047, 29.86352478521305]\n", " [31.465621253685427, 30.319936011512176]\n", " [32.54314514411157, 31.33845329442149]\n", " [30.60402777374194, 29.481417207688807]\n", " [28.757377295246364, 28.041360258870604]\n", " [30.327305390926554, 29.200307596906036]\n", " ⋮\n", " [32.56969918456107, 31.522742477931146]\n", " [28.811678399368624, 28.287770165551606]\n", " [33.32266329800454, 32.21964529419607]\n", " [35.28428863798872, 34.08671293898492]\n", " [35.536530349227604, 34.30528600320833]\n", " [34.2038303134102, 33.03459815445435]\n", " [33.89684858274402, 32.71972532675991]\n", " [35.14580340366173, 33.8737125440467]\n", " [33.463873172957875, 32.26021030807795]\n", " [36.666138988989545, 35.08847735462781]\n", " [30.082443423719994, 29.26735648185978]\n", " [33.59812899222108, 32.22392154871349]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# starcat_mags = reduce(hcat,reduce(vcat,starcat[2])) # To make a 2D matrix\n", "starcat_mags = reduce(vcat,starcat[2])" ] }, { "cell_type": "code", "execution_count": 36, "id": "d28eb80e-5812-493c-a5e3-fd772e90bc40", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of sampled stars is 1.47e+07\n", "Stellar mass of sampled system at birth was 1.00e+07\n", "Present-day stellar mass of sampled system is 4.61e+06\n", "Absolute magnitude of sampled system is M_{F090W} = -13.29\n" ] } ], "source": [ "println(@sprintf(\"Number of sampled stars is %.2e\",length(starcat_mags)))\n", "println(@sprintf(\"Stellar mass of sampled system at birth was %.2e\",stellar_mass))\n", "println(@sprintf(\"Present-day stellar mass of sampled system is %.2e\",sum(reduce(vcat,starcat[1]))[1]))\n", "import StarFormationHistories: mag2flux, flux2mag\n", "println(@sprintf(\"Absolute magnitude of sampled system is M_{F090W} = %.2f\",flux2mag( sum( x -> mag2flux(first(x)), starcat_mags) ) - distmod))" ] }, { "cell_type": "markdown", "id": "8a6557a5-ecdc-4f9b-8c09-348999e786c8", "metadata": {}, "source": [ "The number of sampled stars is very large as we have not imposed a faint-end magnitude cut, which is supported through the `mag_lim` and `mag_lim_name` keyword arguments. However, the sampling is still very fast." ] }, { "cell_type": "markdown", "id": "ce6d273c-cde8-4d2d-8408-e94073ed9238", "metadata": {}, "source": [ "Now we'll mock observe the \"pure\" catalog with the same observational models we used to construct the templates using `model_cmd`." ] }, { "cell_type": "code", "execution_count": 37, "id": "ba1600c9-2729-472e-b23d-8f3d93fabcec", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2×212790 Matrix{Float64}:\n", " 26.1109 29.4789 26.5488 26.5561 … 26.8878 27.9307 25.2945 27.7433\n", " 26.3463 28.5098 26.6388 26.6696 26.2649 27.178 24.4521 27.1318" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Construct new / read cached catalog (for reproducibility)\n", "import StarFormationHistories: model_cmd\n", "read_obs_mags::Bool = true\n", "if read_obs_mags\n", " obs_mags = CSV.read(joinpath(@__DIR__,\".ipynb_checkpoints/obs_mags.txt\"), Table; delim=' ', header=1)\n", " obs_mags = permutedims([obs_mags.F090W obs_mags.F150W])\n", "else\n", " # Apply observational effects to \"pure\" catalog\n", " obs_mags = model_cmd( starcat_mags, [F090W_error, F150W_error], [F090W_complete, F150W_complete])\n", " # Concatenate into 2D matrix\n", " obs_mags = reduce(hcat,obs_mags)\n", " # Optionally write out to file; use .ipynb_checkpoints to prevent commit to github\n", " write_obs_mags::Bool = false\n", " if write_obs_mags\n", " CSV.write(joinpath(@__DIR__,\".ipynb_checkpoints/obs_mags.txt\"), Table(F090W=obs_mags[1,:], F150W=obs_mags[2,:]); delim=' ')\n", " end\n", "end\n", "display(obs_mags)" ] }, { "cell_type": "markdown", "id": "bbe08dca-ac72-4e10-ad08-8904216f83fe", "metadata": { "tags": [] }, "source": [ "Now we'll compute the Hess diagram with `bin_cmd` and compare with our smooth and Poisson-sampled versions. " ] }, { "cell_type": "code", "execution_count": 38, "id": "0ed75236-08cb-4e7a-bca9-f8bf3a5d2875", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "177026" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Total number of stars in the observed CMD space\n", "count( obs_mags[2,:] .< maximum(edges[2]) )" ] }, { "cell_type": "code", "execution_count": 39, "id": "0975e57e-ef82-4304-85da-6994142db7f1", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "99×99 Matrix{Float64}:\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " ⋮ ⋮ ⋱ ⋮ \n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 2.0 1.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 1.0 1.0 2.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 1.0 0.0 0.0 1.0 0.0 0.0 2.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: bin_cmd\n", "model4 = bin_cmd(view(obs_mags,1,:) .- view(obs_mags,2,:), view(obs_mags,2,:), edges=edges).weights" ] }, { "cell_type": "code", "execution_count": 40, "id": "35b9d228-2262-42dc-85bb-c9441347141f", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=3,sharex=true,sharey=true,figsize=(15,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.0)\n", "\n", "im1=axs[3].imshow(permutedims(model2), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5), rasterized=true)\n", "axs[3].text(0.1,0.9,\"c) Smooth Model\",transform=axs[3].transAxes)\n", "axs[1].scatter(view(obs_mags,1,:) .- view(obs_mags,2,:), view(obs_mags,2,:), s=1, marker=\".\", c=\"k\", alpha=0.05, rasterized=true, label=\"CMD-Sampled\")\n", "axs[1].text(0.1,0.9,\"a) Sampled CMD\",transform=axs[1].transAxes)\n", "axs[2].imshow(permutedims(model4), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5,vmax=im1.get_clim()[2]), rasterized=true, label=\"CMD-Sampled\")\n", "axs[2].text(0.1,0.9,\"b) Sampled Hess Diagram\",transform=axs[2].transAxes)\n", "\n", "axs[1].set_xlabel(L\"F090W$-$F150W\")\n", "axs[2].set_xlabel(L\"F090W$-$F150W\")\n", "axs[3].set_xlabel(L\"F090W$-$F150W\")\n", "axs[1].set_ylabel(\"F150W\")\n", "axs[1].set_ylim(reverse(extrema(edges[2]))) \n", "axs[1].set_xlim(extrema(edges[1]))\n", "\n", "fig.colorbar(im1, ax=axs, pad=0.005)\n", "# plt.savefig(\"mcsample_example.pdf\",bbox_inches=\"tight\")\n", "# fig.colorbar(im1)" ] }, { "cell_type": "code", "execution_count": 41, "id": "7a164970-a20e-4f70-bf9b-7bc2b314f97f", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=3,sharex=true,sharey=true,figsize=(15,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.0)\n", "\n", "im1=axs[1].imshow(permutedims(model2), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5), rasterized=true) \n", "axs[1].text(0.1,0.9,\"Smooth Model\",transform=axs[1].transAxes)\n", "axs[2].imshow(permutedims(model3), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5,vmax=im1.get_clim()[2]), rasterized=true) \n", "axs[2].text(0.1,0.9,\"Poisson-Sampled\",transform=axs[2].transAxes)\n", "axs[3].imshow(permutedims(model4), origin=\"lower\", \n", " extent=(extrema(edges[1])..., extrema(edges[2])...), \n", " aspect=\"auto\", cmap=\"Greys\", norm=plt.matplotlib.colors.LogNorm(vmin=2.5,vmax=im1.get_clim()[2]), rasterized=true, label=\"CMD-Sampled\") \n", "axs[3].text(0.1,0.9,\"CMD-Sampled\",transform=axs[3].transAxes)\n", "\n", "axs[1].set_xlabel(L\"F090W$-$F150W\")\n", "axs[2].set_xlabel(L\"F090W$-$F150W\")\n", "axs[3].set_xlabel(L\"F090W$-$F150W\")\n", "axs[1].set_ylabel(\"F150W\")\n", "axs[1].set_ylim(reverse(extrema(edges[2]))) \n", "axs[1].set_xlim(extrema(edges[1]))\n", "fig.colorbar(im1, ax=axs, pad=0.005)" ] }, { "cell_type": "markdown", "id": "c0cda9b1-e1a8-4233-8240-04acf99a6b4f", "metadata": {}, "source": [ "The mock Hess diagram created by Poisson-sampling the smooth model (labelled \"Poisson-Sampled\") and the Hess diagram created by sampling stars via `generate_stars_mass_composite` and mock observing them with `model_cmd` (labelled \"CMD-Sampled\") are highly consistent. The Poisson-sampled method is more efficient if a Hess diagram is all that is required, but if you need individual stars (e.g., for forming a star catalog for injection into images) then you should go the CMD-sampled route." ] }, { "cell_type": "code", "execution_count": 42, "id": "9bfa581e-21dc-46e9-8e4f-adafbfda7392", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "99×99 Matrix{Float64}:\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " ⋮ ⋮ ⋱ ⋮ \n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 2.0 1.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 1.0 1.0 2.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 1.0 0.0 0.0 1.0 0.0 0.0 2.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 … 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", " 0.0 0.0 1.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Choose which sampled Hess diagram to use for model fitting; choosing CMD-sampled instance here.\n", "data = model4" ] }, { "cell_type": "markdown", "id": "9206cc3e-9e5e-4b98-a50b-b3476bae832c", "metadata": {}, "source": [ "## SFH Fitting: Constrained Metallicity Evolution\n", "\n", "Given that we constructed our model population with a linear [M/H] AMR, it will be optimally recovered when fitting under the same general AMR model. This can be achieved by using `fit_templates_mdf` to fit the SFH simultaneously with a linear [M/H] AMR using the full template grid. \n", "\n", "Note that in real data, the parameter σ (which sets the width of the metallicity distribution function at fixed age) can be difficult to constrain. As such, it is often preferable to fix σ rather than fitting it. This approach is supported by `fit_templates_mdf`. For the purposes of this example, we will allow σ to be fit to show it can be recovered robustly in the case of synthetic data." ] }, { "cell_type": "code", "execution_count": 43, "id": "b8b79983-b8af-437b-9714-5d30df00ba62", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(map = StarFormationHistories.LogTransformMDFResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([3.508418671731614, 1.3456027739328649, 1.0069690221762135, 0.8179572713196054, 0.8114159857527945, 0.973616395070588, 0.9800666895329524, 1.1068831105088601, 1.627718479821283, 1.4029916662040582 … 817.2169374177233, 388.2087514806638, 753.3490647864803, 842.4088046843362, 935.6366391060493, 1028.8649686430667, 791.3828033459278, 0.10138399732854143, -1.8854585348214077, 0.11351451057635713], [1.3754429895196163, 1.2228210488351765, 0.9616598534288513, 0.7906072043590903, 0.7862199738985534, 0.9370379361996616, 0.9462492094071742, 1.0602850296711588, 1.4571030890531307, 1.3102595018934462 … 295.55596786021795, 207.2441954647195, 124.5760310436129, 125.73288926876639, 98.05987003977926, 70.41750852759125, 45.00515335523419, 0.0005095772160533307, 0.005645224478769559, 0.0024158616855296244], [0.1536959277902389 -0.2012479026374323 … -9.066285364257077e-6 -0.0004719808093076918; -0.2012479026374323 0.8258326784938467 … -4.780771299072974e-5 0.0007565413117440076; … ; -9.066285364257078e-6 -4.780771299072917e-5 … 3.186855941569903e-5 -2.2238703663132454e-5; -0.00047198080930769675 0.0007565413117440026 … -2.223870366296521e-5 0.000452940724361891], * Status: success (objective increased between iterations)\n", "\n", " * Candidate solution\n", " Final objective value: 1.256451e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 3.96e-11 ≰ 0.0e+00\n", " |x - x'|/|x'| = 5.70e-12 ≰ 0.0e+00\n", " |f(x) - f(x')| = 9.09e-13 ≰ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 7.24e-16 ≰ 0.0e+00\n", " |g(x)| = 1.58e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 3 (vs limit Inf)\n", " Iterations: 118\n", " f(x) calls: 305\n", " ∇f(x) calls: 305\n", "), mle = StarFormationHistories.LogTransformMDFResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([6.49197913392421, 1.8831726965613177e-53, 5.833991756479867e-65, 4.614386099244847e-130, 2.3648727945422765e-132, 8.116237772297423e-46, 3.1435111543119115e-62, 4.3629488093216e-52, 8.107472575500926, 3.070088997553774e-16 … 1184.4005081825965, 157.8013550908007, 805.5696616625887, 831.6850796475286, 945.4230008642562, 1030.642043911546, 791.5889939853312, 0.10133019711012366, -1.8851099765568422, 0.11354675283382741], [1.122498593522727, 5.988005839522135e-44, 2.2433129535701402e-55, 3.580065792978467e-120, 1.8672429196194105e-122, 2.1783633503530182e-36, 1.155892176672584e-52, 1.3466859798606693e-42, 2.787732290771115, 2.925182907506664e-7 … 260.670443157142, 220.00561257537694, 127.51721367664335, 124.55539364072035, 99.22395505960108, 72.09801891726873, 46.64585469972445, 0.0005287507371339599, 0.005844070233860732, 0.002494864950187422], [0.029896295704035975 -1.707847037432542e7 … -1.5143354898452554e-5 -9.580741522022524e-5; -1.7078470374325424e7 1.0110767706793347e19 … 32194.9316844353 -1.0999125634158703e6; … ; -1.5143354898321254e-5 32194.931684435323 … 3.4153156898297024e-5 -2.669565308056047e-5; -9.580741522007874e-5 -1.0999125634158712e6 … -2.6695653080819717e-5 0.0004827748589226024], * Status: success (objective increased between iterations)\n", "\n", " * Candidate solution\n", " Final objective value: 1.461988e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 6.93e+00 ≰ 0.0e+00\n", " |x - x'|/|x'| = 2.29e-02 ≰ 0.0e+00\n", " |f(x) - f(x')| = 1.14e-12 ≰ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 7.78e-16 ≰ 0.0e+00\n", " |g(x)| = 6.03e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 4 (vs limit Inf)\n", " Iterations: 138\n", " f(x) calls: 402\n", " ∇f(x) calls: 402\n", "))" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: fit_templates_mdf\n", "mdf_α, mdf_β, mdf_σ = 0.15, -2.25, 0.2 # -0.15, -0.2, 0.2 # initial guess for the metallicity evolution parameters\n", "mdf_result = fit_templates_mdf(templates,\n", " data,\n", " template_logAge, template_MH, T_max;\n", " x0=vcat(construct_x0_mdf(template_logAge, T_max; normalize_value=1e4),\n", " [mdf_α,mdf_β,mdf_σ]))" ] }, { "cell_type": "markdown", "id": "e2263c26-6ef7-4acc-8c00-90c339d2a509", "metadata": {}, "source": [ "We will now calculate the per-template coefficients using `calculate_coeffs_mdf`, which we can use as input for other methods like `calculate_cum_sfr`, which computes cumulative SFHs, SFRs, and <[M/H]> from the fitted coefficients." ] }, { "cell_type": "code", "execution_count": 44, "id": "9ec81fba-497b-4178-a9ad-be8ae447899f", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "([6.6, 6.65, 6.7, 6.75, 6.8, 6.85, 6.9, 6.95, 7.0, 7.05 … 9.65001, 9.70001, 9.75001, 9.80001, 9.85001, 9.90001, 9.95001, 10.00001, 10.05001, 10.10001], [0.9999999999999994, 0.9996524145352975, 0.9995191032035429, 0.9994193409379006, 0.9993383044126568, 0.9992579159445568, 0.9991614579847788, 0.9990643609825126, 0.9989547000451117, 0.9987934389935812 … 0.6695482940208246, 0.6387911496512169, 0.5822108017625277, 0.5505489034446404, 0.4695857244365759, 0.4311251722875444, 0.3564895004173606, 0.2730305169714941, 0.18033528119014633, 0.07840374402133701], [0.007222472459590545, 0.0024688309578686693, 0.001646609403293299, 0.0011920791672050172, 0.0010539452244585931, 0.0011270997653305918, 0.001011183814583176, 0.0010178323302413113, 0.0013339936890145445, 0.0010247774780065195 … 0.0005695873018942864, 0.0009338559732956879, 0.00046574825610259284, 0.0010614556179324925, 0.00044939662074661515, 0.0007772500064307474, 0.0007746176318873708, 0.0007667816322348169, 0.0007514894036579741, 0.0007126647098469802], [-0.49690203568706076, -0.4969512857232596, -0.497006545172198, -0.4970685472929845, -0.49713811481583403, -0.49721617085918307, -0.4973037511788922, -0.4974020179120746, -0.49751227499792156, -0.497635985480146 … -0.9493731319162152, -1.0046350541048052, -1.0666397133606857, -1.1362062058616447, -1.2142572134555971, -1.3018353690777895, -1.4001048520639439, -1.5103616781449871, -1.6340683076470275, -1.7727467887843222])" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mdf_coeffs = calculate_coeffs_mdf(mdf_result.map.μ, template_logAge, template_MH, T_max)\n", "mdf_coeffs *= template_norm\n", " \n", "_, mdf_cum_sfr_arr, mdf_sfr_arr, mdf_mean_mh_arr =\n", " calculate_cum_sfr(mdf_coeffs, template_logAge, template_MH, T_max)" ] }, { "cell_type": "markdown", "id": "9f83529b-e92b-4bff-b8be-099ed6244cac", "metadata": {}, "source": [ "Of additional note are the uncertainty estimates, available as `mdf_result.map.σ` and `mdf_result.mle.σ`. These are essentially standard errors derived from the diagonal of the covariance matrix of the fitting parameters (discussed more below). The `mdf_result.map` result contains the maximum a posteriori result and is often very comparable to the mode of posterior samples obtained via Hamiltonian Monte Carlo (provided by `hmc_sample_mdf`). We don't generally recommend the use of `mdf_result.mle.σ`, but provide it for completeness." ] }, { "cell_type": "code", "execution_count": 45, "id": "0a655ae9-e026-4b19-b39d-7cec8d8e631e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "74-element Vector{Measurements.Measurement{Float64}}:\n", " 3.5 ± 1.4\n", " 1.3 ± 1.2\n", " 1.01 ± 0.96\n", " 0.82 ± 0.79\n", " 0.81 ± 0.79\n", " 0.97 ± 0.94\n", " 0.98 ± 0.95\n", " 1.1 ± 1.1\n", " 1.6 ± 1.5\n", " 1.4 ± 1.3\n", " 1.1 ± 1.0\n", " 1.3 ± 1.2\n", " 1.4 ± 1.3\n", " ⋮\n", " 570.0 ± 230.0\n", " 320.0 ± 240.0\n", " 820.0 ± 300.0\n", " 390.0 ± 210.0\n", " 750.0 ± 120.0\n", " 840.0 ± 130.0\n", " 936.0 ± 98.0\n", " 1029.0 ± 70.0\n", " 791.0 ± 45.0\n", " 0.10138 ± 0.00051\n", " -1.8855 ± 0.0056\n", " 0.1135 ± 0.0024" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import Measurements: uncertainty, ±\n", "mdf_result.map.μ .± mdf_result.map.σ" ] }, { "cell_type": "markdown", "id": "06f15be4-d029-436f-b778-7682c6e065a3", "metadata": {}, "source": [ "### Sampling from Inverse Hessian \n", "\n", "Another thing we can do is draw samples from the posterior approximating the posterior distribution as Gaussians and the inverse Hessian as its variance-covariance matrix. This is preferred to using the standard error uncertainties in `mdf_result.map.σ` as samples will include covariances. There are additional notes in the documentation on this approximation, but this sampling method often reproduces results from more expensive Monte Carlo sampling methods fairly well. In short, we are approximating the posterior (in the transformed fitting variables `θ = log(coeffs)`) as a multivariate Gaussian in the region of the MAP estimate. For a multivariate Gaussian, the inverse of the Hessian matrix (which the BFGS algorithm from Optim.jl computes for us) is an estimator for the variance-covariance matrix. In concert with the MAP estimate for the parameters, this gives us both the means μ and the variance-covariance matrix Σ needed to define our multivariate Gaussian approximation of the posterior, which we can then sample from using `MvNormal` from Distributions.jl." ] }, { "cell_type": "code", "execution_count": 46, "id": "a460acba-94c8-41be-8b0c-b1c087e9375b", "metadata": {}, "outputs": [], "source": [ "import Statistics: mean, median, quantile" ] }, { "cell_type": "code", "execution_count": 47, "id": "826a6997-220f-4be0-981f-9c2239a3a861", "metadata": { "tags": [] }, "outputs": [], "source": [ "# # This is effectively what rand(mdf_result.map, 10000) is doing.\n", "# mdf_dist = MvNormal(Optim.minimizer(mdf_result.map.result),\n", "# Hermitian(Optim.trace(mdf_result.map.result)[end].metadata[\"~inv(H)\"]))\n", "# mdf_sample = rand(mdf_dist, 10000)\n", "\n", "# # Transform the variables, noting that the stellar mass coefficients `mdf_sample[begin:end-3,:]` \n", "# # and σ `mdf_sample[end,:]` are fit with logarithmic transformations so we have to transform them back.\n", "# # α and β are optimized directly, without a transformation.\n", "# @views mdf_sample[begin:end-3,:] .= exp.(mdf_sample[begin:end-3,:]) .* template_norm\n", "# @views mdf_sample[end,:] .= exp.(mdf_sample[end,:])" ] }, { "cell_type": "code", "execution_count": 48, "id": "7fc87929-516a-4a6b-9eec-406748caba89", "metadata": { "tags": [] }, "outputs": [], "source": [ "mdf_sample = rand(mdf_result.map, 10000)\n", "@views mdf_sample[begin:end-3,:] *= template_norm # Correct the stellar mass coefficients for the template normalization\n", "# Calculate the cumulative SFH for each point in the sample\n", "# and find the 1-σ range\n", "mdf_cum_sfr = Vector{Vector{Float64}}(undef,0)\n", "mdf_sfr = Vector{Vector{Float64}}(undef,0)\n", "mdf_mh = Vector{Vector{Float64}}(undef,0)\n", "for x in eachcol(mdf_sample)\n", " tmp_coeffs = calculate_coeffs_mdf(x, template_logAge, template_MH, T_max)\n", " _, mdf_1, mdf_2, mdf_3 = calculate_cum_sfr(tmp_coeffs, template_logAge, template_MH, T_max)\n", " push!(mdf_cum_sfr, mdf_1)\n", " push!(mdf_sfr, mdf_2)\n", " push!(mdf_mh, mdf_3)\n", "end\n", "mdf_cum_sfr = reduce(hcat, mdf_cum_sfr) \n", "mdf_sfr = reduce(hcat, mdf_sfr) \n", "mdf_mh = reduce(hcat, mdf_mh) \n", "\n", "# Now calculate quantiles\n", "mdf_cum_lower = quantile.(eachrow(mdf_cum_sfr), 0.16)\n", "mdf_cum_med = median.(eachrow(mdf_cum_sfr))\n", "mdf_cum_upper = quantile.(eachrow(mdf_cum_sfr), 0.84)\n", "mdf_sfr_lower = quantile.(eachrow(mdf_sfr), 0.16)\n", "mdf_sfr_med = median.(eachrow(mdf_sfr))\n", "mdf_sfr_upper = quantile.(eachrow(mdf_sfr), 0.84)\n", "mdf_mh_lower = quantile.(eachrow(mdf_mh), 0.16)\n", "mdf_mh_med = median.(eachrow(mdf_mh))\n", "mdf_mh_upper = quantile.(eachrow(mdf_mh), 0.84);" ] }, { "cell_type": "markdown", "id": "e7105901-b13c-41b3-bacd-b166f5afcf04", "metadata": {}, "source": [ "We can look at the sampled values for the AMR slope α, intercept β, and MDF width σ:" ] }, { "cell_type": "code", "execution_count": 49, "id": "ec80d39d-5192-4eda-a318-ed66d7e2a1de", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(0.1, -1.87, 0.1)\n" ] }, { "data": { "text/plain": [ "3×10000 Matrix{Float64}:\n", " 0.101585 0.101617 0.102398 … 0.100629 0.102003 0.102155\n", " -1.88572 -1.88779 -1.89482 -1.87759 -1.89185 -1.89197\n", " 0.111513 0.11937 0.112699 0.114819 0.109386 0.111424" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "println((α, β, σ))\n", "mdf_sample[end-2:end,:]" ] }, { "cell_type": "markdown", "id": "423a6482-a2ee-4e43-8c07-ea358e4f1bde", "metadata": { "tags": [] }, "source": [ "We can look at the marginal distributions of the metallicity variables using the \"corner\" python package:" ] }, { "cell_type": "code", "execution_count": 50, "id": "59db177a-855f-40fa-a419-90795e3df8c9", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "@pyimport corner # Easy marginal distributions\n", "fig=plt.figure(figsize=(7,7))\n", "# fig.suptitle(\"Linear M/H\")\n", "corner.corner( permutedims(@view mdf_sample[end-2:end,:]),\n", " fig=fig,\n", " labels=[L\"\\alpha\", L\"\\beta\", L\"\\sigma\"],\n", " quantiles=[0.16,0.5,0.84],\n", " max_n_ticks=4,\n", " show_titles=false,\n", " title_kwargs=Dict(\"fontsize\"=>17),\n", " label_kwargs=Dict(\"fontsize\"=>25))\n", "fig.subplots_adjust(hspace=0.0, wspace=0.0)" ] }, { "cell_type": "markdown", "id": "3ffabed6-f019-4f34-9950-4534bcbfb115", "metadata": {}, "source": [ "We see that the inverse Hessian has captured some covariance between the parameters. Now we'll plot the cumulative SFH and metallicity evolution." ] }, { "cell_type": "code", "execution_count": 51, "id": "8a63d181-7d1c-44a3-b2b1-84dff2441054", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Now plot cumulative SFH and MH evolution for the metallicity evolution model\n", "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=false,figsize=(10,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.35)\n", "\n", "axs[1].plot( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(mdf_cum_sfr_arr,0.0), label=\"Result\" ) # This is MAP result\n", "# axs[1].plot( exp10.(unique_template_logAge)./1e9, mdf_cum_med, label=\"Result\" ) # This is median of samples\n", "axs[1].plot( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(cum_sfr_arr,0.0), label=\"Input SFH\", ls=\"--\" )\n", "axs[1].fill_between( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(mdf_cum_lower,0.0), vcat(mdf_cum_upper,0.0), alpha=0.3, fc=\"k\")\n", "\n", "axs[1].set_xlim([T_max,0.0])\n", "axs[1].set_ylim([0.0,1.05])\n", "axs[1].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[1].set_ylabel(\"Cumulative SF\")\n", "axs[1].legend()\n", "\n", "axs[2].plot( vcat( exp10.(unique_template_logAge)./1e9, T_max), vcat(mdf_mh_med, mdf_result.map.μ[end-1]), label=\"Result\" )\n", "axs[2].fill_between( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(mdf_mh_lower, mdf_result.map.μ[end-1]), vcat(mdf_mh_upper, mdf_result.map.μ[end-1]), alpha=0.3, fc=\"k\")\n", "axs[2].plot( vcat(exp10.(unique_template_logAge)./1e9, T_max), vcat(mean_mh_arr, β), label=\"Input AMR\", ls=\"--\" )\n", "\n", "axs[2].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[2].set_ylabel(L\"$\\langle$[M/H]$\\rangle$\")\n", "axs[2].legend()\n", "# plt.savefig(\"example_cumsfh.pdf\", bbox_inches=\"tight\")" ] }, { "cell_type": "markdown", "id": "81616642-1c3d-43de-8899-f318cac7f743", "metadata": {}, "source": [ "The above plots show that we are able to measure the cumulative SFH and age-metallicity relation simultaneously and that they are statistically consistent with the input model. We will now look at the SFRs in each log(Age) bin. " ] }, { "cell_type": "code", "execution_count": 52, "id": "ca6df6c4-8d99-4862-a574-d6666dd5acd4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "72×2 Matrix{Float64}:\n", " 0.00398107 0.0\n", " 0.00446684 3.54675e-5\n", " 0.00501187 7.52628e-5\n", " 0.00562341 0.000119914\n", " 0.00630957 0.000170013\n", " 0.00707946 0.000226225\n", " 0.00794328 0.000289297\n", " 0.00891251 0.000360064\n", " 0.01 0.000439466\n", " 0.0112202 0.000528556\n", " 0.0125893 0.000628517\n", " 0.0141254 0.000740675\n", " 0.0158489 0.000866519\n", " ⋮ \n", " 3.98116 0.29039\n", " 4.46694 0.325858\n", " 5.01199 0.365654\n", " 5.62354 0.410306\n", " 6.30972 0.460407\n", " 7.07962 0.51662\n", " 7.94347 0.579693\n", " 8.91271 0.650462\n", " 10.0002 0.729865\n", " 11.2204 0.818958\n", " 12.5895 0.918921\n", " 13.7 1.0" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[ vcat(exp10.(unique_template_logAge)./1e9, T_max) 1.0.-vcat(cum_sfr_arr,0.0) ]" ] }, { "cell_type": "code", "execution_count": 53, "id": "64bbf9b0-e9a7-4db9-816b-4b924a57d346", "metadata": {}, "outputs": [], "source": [ "# Construct an interpolator that, given a fraction of total stellar mass `x`, will find the lookback time `t` \n", "# at which the fraction of stellar mass formed *more recently* than `t` is `x`.\n", "import Interpolations: extrapolate, interpolate, Gridded, Linear, Flat\n", "# recent_sfh_interp = extrapolate(interpolate((vcat(exp10.(unique_template_logAge)./1e9, T_max),), 1 .- vcat(cum_sfr_arr,0.0), Gridded(Linear())), Flat())\n", "sfh_quantile = extrapolate(interpolate((1 .- vcat(cum_sfr_arr,0.0),), vcat(exp10.(unique_template_logAge)./1e9, T_max), Gridded(Linear())), Flat());" ] }, { "cell_type": "code", "execution_count": 54, "id": "c2467b5c-8cd3-4d38-b121-5ceea99e37c3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "7.247410788638328" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "log10(sfh_quantile(0.001)) + 9" ] }, { "cell_type": "code", "execution_count": 55, "id": "141780b5-7a2d-4dba-903f-c4b097b4cdb2", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8.149038152771372\n", "7.247410788638328\n" ] }, { "data": { "image/png": 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iIjIpJmpEREREJsVEjYiIiMikLD/qc3BwEOPj4wCU2aC7urpyTgxINtfUBPzlX966T7WB5U5ENmfpRM3n88Hv92etQ6YutbHa5INkM3V1wI4dRkdB1cZyJyKbs2zTZywWyyyXsZTX68Xw8HDONdmIiIiIrMSyiVoikcisWbacKIp5t5FNzc0B3/iGcpubMzoaqhaWOxHZnGUTNVEUEYlEEAqFVmxLJBJwOp0GREWGmZ8H/vqvldv8vNHRULWw3InI5iybqHV3d0MURfh8PrjdbsiyDFmW4fF4EA6HjQ6PiIiIqGyWHkwQj8fh8XgQi8XQ1tYGp9OJU6dOQRCEgq+bnZ3F7Oxs5vfJyckKR2pvoRdfRPDFF5E4dw4A4OrqQvTo0aJfH3nlFXgOHwYAOO+5B7s/8AEEv/zlSoRKOmGZExFVh6UTNUEQ4PF4IAgCIpEIEokEent7V61RGxgYwJNPPlmRmOSpKQz87d8CADo2bsTI5ctw796N7vvvr+o+y4nD9/TT8Hz843B1dRUVn/fBB+F98EGEXnwR4VdeQSwehzw1BWH9+qJeL12+DKD0D3srM8t1slQp5c4yJyKqDksnam63Gz6fD+FwGJIkwefzIRKJoLOzE/F4PG/NWn9/P770pS9lfp+cnMTWrVvLjkeemkKXz4fwE0/Aee+9mcd9Tz+NoTfeQMDnq8o+tbxGunwZsXg8U0vi+fjHS461feNGeO6/H7F4HKEXX0Tf5z+/6muky5czMRb7IW91ZrlOgPLLnWVORFRZlu2j5vP54PF40N3dDUAZXBCNRhEMBiFJEvx+f97XNjU1YePGjVk3PXgOH0b3xz6W9UEJAMEvfxmhl15CLB6vyj5LfU3oxRfhvzkoQ0uSsNTuD3wAznvuQfCll4p6fiweL7rmzi7Mcp3oVe4scyKiyrFsjVooFEI6nV7xuNfrhSzLOHHiRFXjydRMLKmpW2r/xz+OwDe/WdIHlJZ9anmN2owFAIk33yw6vnx6PvEJ+EMhJN58c0XisJw8NVX28azELNcJoG+5s8zNaWJiAtevXzc6jIppaWlBa2ur0WEQVZRlE7VCuru7q56oBV98EQAg3nFHzu2dd9yB0EsvlfQhVco+1SYkLa/Rm/fBB+EPhRB88cWCHcQTb76pX83KmjXA1752675JVaJ8arbMAcuUuxEmJibw50/935i7OmZ0KBXTuGETfv/gf9E9WfP7/UgkEhgeHs48tnv3bjidTgQCAV2PZTWyLMPv9yOZTGYmlnc6nejv74cgCPD7/VnnaHBwECdOnMia23T37t0r9itJEpLJZOb3VCqVuR8KhRAMBpFIJAAo/dNz7WNpHHZi2UTN6XQiFovB5XKt2BaLxdDT01PVeBLnzhX8EFQ/RId/8hNs27BB932qH35aXqM3Yf16uLq6cPK73y34oR2Lx4vq01SU+nrggx/UZ18VVInyqdkyByxT7ka4fv065q6O4eEPb8BmYZ3R4ejuinwNL7w+huvXr+ueqKmJxuDgYCbx6Ovr0/UYVhSLxeD3+3H8+PGsuUoTiQQ8Hg8CgQAGBwezErW+vj709fXB7/dntuU7l5IkwePxIJFIQJblTMLl9Xrh9XqzyiPXmt6hUAg7duyA1+u1VUJt2UQtHA7D7XYjGo1mLSOVSCQQjUarPpeaNDqK9gJ93dQPUunyZWz7wAd03ydufgBreU0l+B58ELF4vGB/pFrsSF6J8mGZUyGbhXXY0qFPP1zzuVrRvauJgh1qaEKhEFwu14plF4ulzlMaj8dX7MPpdCIajaKzszPv69Vthc6lKIqIx+Po7OyEJEkrJq5Xj9ve3p7z9V6vF6IoZuZWtcua35YdTKAOHggEAvD5fJlbLBYzZMLb5OQkhHX5v7W236xFK6XpU8s+KxGHFuqUEGqz3HKRV17Rt3Znbg547jnlZuKlhMxynVRC1cscsEy5ExltZGSkrNeHQiHs3r27YKKnV2KkNq1qoSajoVAIsVhMl3iMZtkaNUBJ1sySMRf7IThewuS6WvZZiTi08j7wAEJ5RgJKly+XNWfYCvPzgHot/MZvAI2N+u1bR2a5TiqlqmUOWKbciYwWi8XgK2N099DQ0Ko1iy6XS5faR5fLVVaS5XK5EAqFEI1Gc3aPshrL1qiR+alzcoWW1bDIU1N5O76TtbHMicxHkqRMR/xyFLMPPRIjURQzAxW0UGvjCjXFWgkTNZ0I69dDvnZt1ed1lDBnm5Z9ViIOrVxdXRDWr1/RFHbyO9/Rv2bFIsxynVQKy5zIXGRZhtvtLns/brcbkiRhcHCw4PP6+/tL3nckEskaFQogM0eqFmpt3P79+zXvw0ws3fRpJoU6cwNA8qrS6bWUztRa9lmJOMrhfeABDD73XNbUELU8j5ZZrpNKYpmT3akd69UpJeI3J5SORCIAlP5gkiQhHA5nNQUufZ0kSUilUpAkKTOdlFqL5Pf7s/qCLT/eqVOnsjraqyMlk8lk1ojIUCiUFYPH48nqiB+NRov+m9WRlH6/HyMjIytiVC0fAFCMXP3RtA568Pv9kGUZ0Wg0bzPs4OBgZtvSKUYkSco5mtRorFHTibhlC5IF+gCpH1SlNP9o2Wcl4iiH7+aEqmpT2NLlg2qRWa6TSmKZk90JgoBoNIru7m7IsgxJkhCJRDJTUQSDQTidTnQtGzyz9HUAcPLkSQDKdCCBQADBYBButxtdXV1ZfbQEQUA4HM4cb7lwOIxAILBim9frzQy6U58XjUYzt1KpyU8oFEJnZyfa2trg8XgQCoU0N1XqMTpTlmXEYrFMMjsyMpK3Cdbtdmem+/B6vVnTh5TT3FpJTNR04rznnoK1BksXoa7kPisRRznEO+7IWl6onOWDfE8/rcvKCUYyy3VSSSxzqhXqfJ3BYHDF3GA+nw+SJOXsFL+0KXJ5DVR3dzf2798Pj8eTlTgIglBwftBqdJoXRRGpVArBYBAulwuyLCMSicDn86Gtra2owQqBQAButzuTkO7YsaPk/nMnTpzA4OBg5tbb2wufzwdRFBEOh/PWxi2dMDdXXGbFRE0nPZ/4BID8S/EMaZhsVMs+KxFHuXwPPgjp8mV+4MI810mlscypluTqA6Y2MRaqpcmXXKm1O4XWrF6umnO9qTV16XQa8XgcgUAgU9O2WrLm9/szNXqnTp1a0TxcjJ6enkxNWF9fH8LhcGb6kba2toLnPBaLregPB1Qn0dWKiZpOnPfeC1dXF0585zs5t0deeQX+HDOyy1NT8AeDORfN1rJPrXHoIV/z2/6biUTv0aPYXeRkvyp/MAj3449n+jsJ69cjFo+j7cEHs5OANWuA/+f/UW4mXkrILNeJXgwtc8Ay5U72lqsGR00+tMwHJooiRFG0xDxgTqcTfX19SKVSmWkxiq0hEwQBLpdL0wCEXAKBAERRXNHkvDRWdbvP58v0KVSZdfUJJmo6Ch8+jMj3vrfiw8T39NPo+9znctZqhF58EYPPPQfP4cO67VPLa1TS6CgAbZ2/o/F4zmRBXV5IvnYtZ18l9Vi5jhnw+eD//OfRe/QopNFRBL75TYS/+13Eg8HsfdXXA/fdp9zq60uOvZrMcp0spbXcDS1zwFLlTvaVb6b8coiimLPmxyjFxKJONl/qWttaBw7k4nK5Ck5HEo/HMwmlx+OBw+FAV1eXLtOXVApHfepIWL8e8WAQ/mAQwvr16Ni4ESOXL8O9e3feqQnU6Qz235x/So99lvqayCuvZKZTGP7JTwAoNSHqY57774f3ZgfxXEIvvojAc89l+kJFvvc9BL/0pazkwP/5z2e2q6TLl+H7kz/JJAmxeBzuxx+HuGVL1nqRrq4upUYpFILznnvQ/5u/aek5ucxynZRT7ixzIutbup7matTBDoWoNWSlJj16TZQLAB0dHQCA4eHhnCNQ1YEZgNIMmkgkcOLECXR1dSEYDJpy1CcTNZ0J69cXXJR6Oee99yKVZ8kdrfss9TXd999f1hxX3gcfLJjIATc7si+r1RHvuAPRo0cLvi4Wj8P3J38C/+c+B98DD8DV1QV/KARAqUXKTDkxPw+o5/HBB4EGc1/aZrhOyil3U5Q5YLlyJypWrrUuC9EyYvHkyZNFJyaSJBWV2AmCUHINYyX61+VaMisWi6G9vT1zXl0uF1wuV2bUp9/vN2WixqZPMjV5agrhJ56A98EHMXKzdiZ69Cg899+f3T9qbg74sz9Tblzz0dKKLnOA5U62pM6ztryDe6GEptRmUi2JXejmF6ZCJEnK20esGtRzlOt8yLKct1lWnd7EjFN0MFEjU+u+//5Mv6Tk1auZyVu9Dz7IpjCbYplTrcjXRKiOolw+ZYRaU5VrgEKhgQdqH7ClyYskSSX3DfP7/QWbNWOxGGRZrlitlPp3Fxqgof5Ny+NUV1QolGyKoljV0bPFYqJGltH/m79Z8ghCsjaWORlJrV3JV8tSKHEopmZmaGhoRc1PKBTCyZMncerUqRXPV/uALZ+sNpFIZBKUeI6R4aIowul0ZvpmAUpSVeqUFOFwGMFgMOfksOqi70uPsdRq57IQdVJh9e+ORqOZptjlXC5XZpWBpcdcmoDlWgarmKlFjMIOHWQZnN2+9rDMyQhqzdHw8DAAYGBgANFoFE6nM9NEps6CDyBrslVBEDJLOqn7UhOc5TVY6qS46jQR4+PjAIALFy7krdkJh8Pw+/3w+Xzo7OyEIAgQRTFrtYPh4WEcP348q4/bqVOn4PF4Mq8rNUlzOp3o7u5Gd3c3YrEYent7IUlSppZPFEXE4/EVcavLWKnnUp1HTf1biqnBisViGBoagiiKmSk0gsEg9uzZk3NN0Hg8Dp/PB4/Hk5k4uK+vD7FYLHNe1GWk1GROFEVT9k8DmKgV5nDc+plOGxsLaVOtcnM4bl0vZLyl5V7j5XJFvmZ0CBVRyb9rtVnq1aWg8slXq5SL2qG9WIIg5B19mS7wfrdazKtZek5KiVldqqkcaoJYilznaGnMZp0zLRcmaoWo8zLV1wMLC8bGQtosLAB1dcqHdSVHBNbX37peFhY4p5fRlpZBjY4EbWlpQeOGTXjh9TEAV40OpyIaN2xCS0uL0WEQVVRtvoMVq7FR+YBfswaYmDA6GtJiZubWjPWNjZU7zpo1t44zPc1Z8o2UTivlLgjK/2+NJs2tra34/YP/BdevXzc6lIppaWlBa2ur0WEQVRQTtUIcDqCtDbh6FbhyBbh2DVi3zuioKJc1a4CvfOXWfQBYXFQS7E2blA/rSr6ht7cDb78NNDcDslzZY9Etucr92jVlqo7WVqVcarjps7W1lYkMkcUxUVvN5s3A+LjSfJJKMVEzq/p64Jd/Ofuxq1eVJjBBUJK1ugoOcm5rU64RQVCSejZ/Vkeuck+llNrT9euV/18ikylnBCTVHk7PsRr1A37TJmBsTEnayPyuXwcuXlQ+rNeurfwHdl0d0NGhJGwAIEns12gE9X+0o0OpSdu0yeiIiDJkWYbb7UZvby8AwOPxwO12GxwVmR1r1FbT2Ahs3ar0e5mfBy5dUvogCYJSu1bDzSqmMj8PxGJKk5fTCSSTQFMTsGOHUlYVWDR5hW3blCRBFJVE7fx5JUFsbWXtWqXMzwPRKHDjBvCRjyjNzps3A7ffrpRHjQ4kIHMqd+Ql1Sa+ixVDFG8N929oUD6Mx8aUJK6pSfkQLiFhW3P5Mu66+ZOdznVy/TqgDh8fHARuuw24806lZuXDH65ss6dq3TrgvvuAM2eUa+byZaVWT93W0MDEXk/ptFLu6uSVTz8N3HHHrSRtxw5j4yMi0gETtWJ1dt6a5uH224GpKaWj+o0bJTdxORYX0XDzJ+bnKxNvrVmaAP38zwMtLUot2s//fHVrs9avV5K1119XkrMbN5Tr5Pp15Tphc6i+lpbtzp3KOd+6lUkaEdkGE7VS7NihfAiMjSkdxlMpZWRhiWYXFzECYPbOO4G779Y/zlo0PX3rfmcncNddyghMI6xfD/zSLwGTk8p1cuUKMDtrTCx2t7TcP/ABNncSke3wHa1UDQ1KjdrttytNLwsLJdeKXWtqwg8AXPvwh4FduyoTZ62Zmbl1/847jUvSVA6H0jettVVJxtXaUw2JPRWwNAF+3/uYpBGR7fBdrRzqbPclfjikm5owe/On4QmFXZi9SbGujv0RK8Hs5U5EVCZOz0FEZDGF1nQkouqpxv8iEzUiIououzl6eYE1iUSmoP4v1lVwZgE2fZI9NDUBJ0/euk+1ocbKvbGxEY2NjZiamsL69euNDoeo5l29ejXzf1kpTNTIHhoaAI/H6Cio2mqs3B0OBzZs2ABZltHa2oq1a9caHRJRzZqensbk5CQEQYCjgnNkMlEjIrKQTZs2YXp6GhcvXsTGjRuxYcMG1NfXV/SDgogU6XQaCwsLuHr1KiYnJ9HU1IRNFV6qjoka2cP8PPCtbyn3P/tZTtNQK2qw3Ovr67F161aMjY3h6tWrXNibyACNjY0QBAGbNm1CfYUnVbf/uxrVhtlZYP9+5f7UVE18YBNqttzr6+vxvve9D7fddhvm5uawyPn5iKqmrq4OjY2NVavFro13NSIiG3I4HFjD+fmIbI3TcxARERGZFBM1IiIiIpNiokZERERkUuyjViUXL17E2NgYAODs2bNZPzdt2oRt27YZFhsRERGZExO1Krh48SI+8MGdmJm+nvX4gQMHAADNa1vwkzfOMlkjIiKiLEzUqmBsbAwz09fR8cCX0dixFXPjlzD+0tPoeODLAIDxl57G2NgYE7VyrFkD/NVf3bpPtYHlTkQ2x0Stiho7tqLp9ruzfiedNDYCv/M7RkdB1cZyJyKb42ACIiIiIpNijRrZw/w88I//qNz/9KdrZob6msdyJyKb47sa2cPsLPDAA8r9GlpKqOax3InI5izZ9JlIJODxeCBJktGhEBEREVWMJRM1SZIQiUTQ2dkJh8OR8xYKhYwOk4iIiKgslmwnkCQJLpcLoiiu2JZMJiFJErxerwGREREREenHkona+Pg4otFozm0+nw/Hjx+vckRERERE+rNk06fb7c75eCQSgdvthiAI1Q2IiIiIqAIsmai5XK4Vj0mShKGhIXR3dxsQEREREZH+LNn0mYvf70c4HC7qubOzs5idnc38Pjk5WamwqFrWrAH+/M9v3afawHInIpuzRaIWiUSwZ8+eop8/MDCAJ598soIRUdU1NgK/93tGR0HVxnInIpuzZNPncn6/v6Qmz/7+fkxMTGRuly5dqmB0RERERNpYvkYtkUhAkqScU3Xk09TUhKampgpGRVW3sAB8//vK/V/5FaC+3th4qDpY7kRkc5ZP1ILBYElJGtnUzAzwiU8o96emgHXrjI2HqoPlTkQ2Z/mmz1gsxuk4iIiIyJYsn6hJkoT29najwyAiIiLSnaUTNVmWjQ6BiIiIqGIsnagJggBBEOB0Oo0OhYiIiEh3lh9MkEqljA6BiIiIqCIsXaNGREREZGeWr1EjAqDMUD84eOs+1QaWOxHZHBM1soc1a4CDB42OgqqN5U5ENsemTyIiIiKTYo0a2cPCApBIKPedTi4lVCtY7kRkc0zUyB5mZoBf/EXlPpcSqh0sdyKyOTZ9EhEREZkUEzUiIiIik2KiRkRERGRSTNSIiIiITIqJGhEREZFJMVEjIiIiMilOz0H20NgIPPHErftUG1juRGRzTNTIHtasAQ4fNjoKqjaWOxHZHJs+iYiIiEyKNWpkD4uLwNmzyv2dO4E6fgepCSx3IrI5JmpkD9PTwIc+pNznUkK1g+VORDbHr59EREREJsVEjYiIiMikmKgRERERmRQTNSIiIiKTYqJGREREZFJM1IiIiIhMitNzkD00NgKPP37rPtUGljsR2RwTNbKHNWuAp54yOgqqNpY7Edkcmz6JiIiITIo1amQPi4vAxYvK/W3buJRQrWC5E5HNMVEje5ieBnbsUO5zKaHawXInIpvj108iIiIik2KiRkRERGRSTNSIiIiITIqJGhEREZFJMVEjIiIiMikmakREREQmxek5yB4aGoDf/d1b96k2sNyJyOZKemfr6OioVBxZ0uk06urqMDY2VpXjkQ00NQF/8RdGR0HVxnInIpsrKVFLpVJYXFysVCxZ6jjDOBEREdU4thWQPaTTgFoDu2kT4HAYGw9VB8udiGyupETN6/VWKg5Dj0U2cP06cNttyn0uJVQ7WO5EZHMltS8eO3asUnEYeiwiIiIiM9K9I9ijjz6K+vp6nD59Wu9dExEREdWUivTY7+3txe7duyuxayIiIqKaoXui1tnZiWPHjmHjxo2rPpe1bkRERET56Z6oOZ1OvPDCC0U9NxAI6H14IiIiItvQfXqOvXv34vTp0+jv70dnZyd2794NQRDQ3t6e9bxkMglJknQ5ZigUwsjISOb3zs5OjholIiIiy9M9UauvrwegrC4AAI488xql0+m824olyzI8Hg88Hk+mdi6RSMDj8WD37t1wOp1l7Z8spKEB+O3fvnWfagPLnYhsTvd3th07dqC7uxtut7vg81KpFHw+X1nH6u3thSiKWbVnyWQSyWQSgiCUte9qO3v2bN5tW7ZswZYtW6oYjQU1NQHf+IbRUVC1sdyJyOZ0T9REUcSRI0eKem4oFNJ8nEQigUgkktXkCQAulwupVErzfo1y4MCBvNueeOIJHD58uHrBEBERkSnonqhFIpGinxsOhzUfZ2BgAIIgQBRFzfswk2effRY7d+7E2bNnceDAgczvAFibVox0WpmlHgBaWriUUK1guRORzemeqHV1deHcuXNFPbe1tVXzcSRJgiiKkGU5UzM3Pj5u2YEEO3fuzOpTt/x3WsX168D69cp9LiVUO1juRGRzuidqIyMj+Na3voXPfvazeu86SyKRgMvlQigUQl9fX+Zxj8eDeDyOYDCY97Wzs7OYnZ3N/D45OVnRWImIiIi0qMjKBF/5ylfw2GOPVWxCW1mWAQCxWAzd3d1Z2wKBAEKhEGKxWN7XDwwMoLW1NXPbunVrReIkIiIiKofuiZrX68XQ0BC+9rWvoa2tDYcOHcLRo0fx1ltv6XYMdUSnKIor+qipvxeqUevv78fExETmdunSJd1iIyIiItKL7k2fx44dy9zftWsXdu3aBQA4fvw4JEnCnj178PDDD+tyrHxTcAiCUHAy3aamJjQ1NekSAxEREVGlVG2GyN7eXgDAhQsXcPToUYyPj+PRRx/FXXfdpWl/6kCCXPI9TkRERGQlFemjls/k5CROnTqFY8eOIRAIwOl0or+/H88880zJ+3K5XEgmk3m37969u5xQiYiIiAxXlRq1M2fOYGBgAJFIBOl0Gi6XC8FgEHv37gUATExM4KmnnoLD4cDjjz9e1D79fj9CoVBmmg5VIpEAgLJXPSCLqa8H1IElN5cxoxrAcicim9M9UduzZw+GhoYwOTmJUCiEYDAISZKwY8cOHDlyBF6vd8X8aa2trTh48CAA4KmnnoLb7cZ9991X8DiiKKKvrw8+nw/RaDTzeG9vL/r6+jgHWa1pbgbKmECZLIrlTkQ2p3uiFo/Hcc8990CSJKTTaXR3d+PYsWOZ2rPVHDx4EEePHl01UQNuTcXh8XjQ3t6OZDKJ/v7+FVN2EBEREVlRRZo+0+l03tozvXm9XkuuREBERES0moosyn7+/HlNr/3Upz6FCxcusEaMSnftGpcSqkUsdyKyOd0TtXKSLJ/Ph6GhIfT39+sYEREREZE16Z6oHTlyRPNr9+3bh3379ukYDREREZF1VXUeNSIiIiIqHhM1IiIiIpNiokZERERkUkzUiIiIiEyqaouyE1VUfT3w679+6z7VBpY7EdkcEzWyh+Zm4H/8D6OjoGpjuRORzbHpk4iIiMikmKgRERERmVRJidrk5CTeeuutCoVCVIZr15Tlg9atU+5TbWC5E5HNlZSoDQ0NweVyYc+ePTh69CgmJycrFRdR6a5fV25UW1juRGRjJSVqe/fuxfnz5xEKhTA2Nobt27djz549eOaZZ5i0EREREelMUx+1Xbt24ciRI0gmkwiFQhgeHsb27dvx6U9/mkkbERERkU7KHkywa9cuHDt2DMlkEn19fUzaiIiIiHSi66jPvXv3ZiVtL7/8ciZpe+GFF/Q8FBEREZHtVWx6jr179+LkyZNIJpPwer147rnn0NHRgZ6eHiZtREREREWoyjxq+/btw8mTJzE+Po79+/fj2LFjmaTt9OnT1QiB7K6uDrj/fuVWx+kBawbLnYhsrurvbPv27cPLL7+cSdqOHDmCjo4OPPbYY0zaSLu1a4Hvfle5rV1rdDRULSx3IrI5Q7+CqkmbJElwOp1ZSduZM2eMDI2IiIjIcKZoK2htbUVvb29W0hYMBo0Oi4iIiMhQDUYHsJyatBGV5No1YPt25f5bbylLCpH9sdyJyOZMl6gRaTY2ZnQEZASWOxHZmCmaPomIiIhoJSZqRERERCbFRI2IiIjIpJioEREREZkUEzUiIiIik+KoT7KHujpg9+5b96k2sNyJyOaYqJE9rF0LDA0ZHQVVG8udiGyOX0GJiIiITKrqNWqnTp1COByGw+GAIAhIpVK4++678fjjj1c7FCIiIiJTq1qiNjExgYGBAXzuc5/DsWPHVmw/dOgQPve5z+G+++6rVkhkJ9evAz/3c8r9H/8YaGkxNh6qDpY7Edlc1RK1I0eO4MiRIwW3P/XUUxBFERs3bqxWWGQX6TTw05/euk+1geVORDZXlT5qR48exaFDh1Z93sGDBzEwMFCFiIiIiIjMr+KJ2sTEBFpbW9Ha2lrU83fv3o3JyckKR0VERERkfhVP1E6dOoWenp4Vjz/zzDP49Kc/jTNnzmQ97nQ6MTw8XOmwiIiIiEyv4omaJEk5+5z19fUhFoshGAxmPb5jxw5IklTpsIiIiIhMr+KJ2o4dO3I2ZYZCIezduxd+vz/r8TNnzmDHjh2VDouIiIjI9CqeqLlcLpw8eXLF493d3Xj55Zexffv2rMeHh4exZ8+eSodFduNwKNM0/NzPKfepNrDcicjmKj49R2trK1KpFCYnJ4uaduP8+fOcnoNK19IC/Md/GB0FVRvLnYhsrirTcxQ77cbRo0fR399fhYiIiIiIzK9qa30eOnQIhw4dwunTp1dsm5iYwKFDh+ByuYqexoOIiIjI7qq2MkFrayuOHDmCU6dO4amnnoLD4cDY2BhkWcbdd99dcNWCXNxuN5xOJ3p6euB0OiFJEoLBIGRZXjGSlGrA9euA2rdxaIhLCdUKljsR2VzVF2Xfu3cv9u7dW/Z+kskkBgcHMTg4mHnM5XIhGo2WvW+yoHRaWetRvU+1geVORDZX9URNL6IooqenB0NDQxBFEW63Gy6Xy+iwiIiIiHRj2UStvb0dfX19RodBREREVDGaBhM89thjuhxcr/0QERER2ZGmRE2vtTj1WCoqkUggFAohkUjoEBERERGReWhq+ozH4/jVX/3VsqbSkGUZsVhM8+uTyST8fj/cbje8Xi9isRi6uroQDochimLB187OzmJ2djbze64lroiIiIiMprmP2ssvv1z2wR1lLPmiJmgql8uFnp4euN1ujIyMFHztwMAAnnzySc3HJhNyOIC77rp1n2oDy52IbE5T02c4HEYgEEA0GsXi4qKmWzKZLGvx9aVJmsrlckGSJEQikYKv7e/vx8TEROZ26dIlzXGQSbS0AG+9pdw4l1btYLkTkc1pqlHbt28fAODChQs4fvw4JiYm4HK5cN999xW9D0EQVm2iLJW6v2g0iu7u7rzPa2pqQlNTk67HJiIiItJbWdNz7NixA729vQCA1157DU899RTa2trgcrmwffv2VV+vdQUBj8cDSZIQj8dzbk8mk5r2S0RERGQmus2jtmvXLuzatQsA8PzzzyMSiUAURTz88MN5X6O16TORSOSsjVMTtD3qkjJUO6angY99TLn/ve8Ba9caGw9VB8udiGyuIhPeqk2jExMTmaZRp9OJT37yk7rsv7u7G4FAYMXjat+0XP3XyOYWFwF12pjFRWNjoephuRORzVV0ZYLW1tZM06jan83hcGD37t0l9Wdbrr+/Hz6fL6vpNJFIYGBgAOFwGIIglBk5ERERkfGqtoSU2p/ttddeQ29vL2RZht/vxyOPPFLyvgRBQCAQgM/ngyAImYlzT506BafTqXfoupkbv5TzJwBcuXLFkJiIiIjIvKqSqE1OTiIUCiEYDEKSJKTTabhcrrJGfQqCoHkwglHGX3o67+8vvPACPv3pT1c7JCIiIjKxiiZqzzzzDILBIBKJBNLpNJxOJ44dO4b9+/eXtaqBVXU88GU0dmzNemxu/BLGX3q64KALIiIiqk26J2qnT59GMBhEJBJBOp2GIAg4ePAgfD5fWRPc2kFjx1Y03X53zm2bN2+ucjRERERkdrokamfOnEEwGMTJkychyzLS6TS8Xi88Hg/27t2rxyGIVrdpk9ERkBFY7kRkY5oTtXz9znw+X2Z6jtWcPn1atyk7qMatWwdwQEbtYbkTkc1pStQ+/elPIxaLAVAmuj1y5Ai8Xm/J/c58Ph/OnTunJQQiIiIi29OUqEWjUbhcLng8HuzevRsOhwMXLlwoaR/PPfdcZloNIiIiIlpJc9Pn/v370dbWpinZSiaTTNJIX9PTwK/9mnL/H/6BSwnVCpY7EdmcpkTN6XRqmqh2qd7eXtx9d+4RkEQlW1wEXnnl1n2qDSx3IrK5Oi0v8vl8uhzc7/frsh8iIiIiO9KUqKnrd5ZLr/0QERER2ZGmRI2IiIiIKo+JGhEREZFJMVEjIiIiMqmKLspOVFUtLUZHQEZguRORjTFRI3tYtw64ds3oKKjaWO5EZHNs+iQiIiIyKSZqRERERCbFRI3sYWYG+MxnlNvMjNHRULWw3InI5thHjexhYQH4+7+/dZ9qA8udiGyu7ERtcnISoVAIIyMj2L17N77whS/oERcRERFRzSu66fOxxx5DfX096uvr8fTTTwMALly4gO3bt6Ovrw/BYBC9vb34xV/8xYoFS0RERFRLikrUnnrqKUSjUfT29uKRRx7BH//xH+P06dPweDzwer2IRqOIx+M4efIkBEFAf39/peMmIiIisr2imj5HRkZw/vz5zO/BYBCf+tSn0N/fj3379mUe37VrF7q7u7F//379IyUiIiKqMUXVqHV2dq54zOl0ZiVpS4miWF5URERERKR9eo49e/bk3TYxMaF1t0RERER0U1GJmtPpxPPPP4977rkHjz32GACsqE07evQovvWtb+Gtt96C0+nUP1KiQtatA9Jp5bZundHRULWw3InI5orqo7Z371689tpr2Lt3L1wuV87nfOUrX4HD4YDX68XAwICuQRIRERHVoqLnUdu1axeOHTuWd3symcTExARaW1t1CYyIiIio1um6hBSTNDLMzAzg8Sg3LiVUO1juRGRzuiRqZ86c0WM3RNotLACRiHLjUkK1g+VORDanS6LW29urx26IiIiIaAldErV0Oq3HboiIiIhoCV0SNYfDocduiIiIiGgJXQcTEBEREZF+mKgRERERmRQTNSIiIiKTKnrCWzLG6OgoRkdH827fsmULtmzZUsWITKqlBZiaunWfagPLnYhsjomayQWDQTz55JN5tz/xxBM4fPhw9QIyK4eDaz3WIpY7EdkcEzWT8/l8eOihhwAAZ8+exYEDB/Dss89i586dAMDaNCIiIhtjomZyuZo2d+7cCafTaVBEJjU7C/h8yv1gEGhqMjYeqg6WOxHZHCe8JXuYnwf++q+V2/y80dFQtbDcicjmdEnUjh8/rsduiIiIiGgJXRK1Xbt26bEbIiIiIlqC86gRERERmZRugwkmJycxPDwMSZIgyzLGx8cBAB0dHRAEAaIo4pOf/KReh8urq6sL8Xi84schIiIiqrSyE7XTp08jEAggFosByD+wQF243eVy4dChQ/jEJz5R7qFX8Pl8SCQSuu+XiIiIyAhlJWqHDh1CKBTC/v37ceTIEYiiCEEQ0N7envW8ZDIJWZYhSRKGhoawd+9eHDp0CF/5ylfKCn6pRCKB4eFh3fZHREREZDTNidrzzz8PWZaRTCY1vf7RRx/FCy+8gIcfflhrCFlOnDiBnp4e1qjVqpYW4L33bt2n2sByJyKb0zyYIBaL4dixY5oPfOzYMUSjUc2vX2pwcBD9/f267IssyuEANm9Wbjeb2akGsNyJyOY0J2qiKJZ9cD32kUgkMk2uRERERHaiOVHT2uSp9z5OnDiB7u7ukl4zOzuLycnJrBtZ3Ows8Hu/p9xmZ42OhqqF5U5ENqc5UUun0/jhD3+o+cBnzpxBKpXS/HpAe5PnwMAAWltbM7etW7eWFQeZwPw88N/+m3LjUkK1g+VORDanOVHr7+/Hvn378Id/+If46U9/WvTrzpw5g/7+fng8HgwODmo9fFlNnv39/ZiYmMjcLl26pDkOIiIiokrRPOqztbUVw8PDmak5HA5HZmqOpcmTLMsAbk3RAShzqQ0PD2Pjxo2aAz9x4gQCgYCm1zY1NaGpqUnzsYmIiIiqoax51ARBwMsvvwxJkhAMBvHaa69BkiSMjIxkkjI1eevq6oLT6URPT0/Za4NGIhEkEgn4fL6sx9V51NTHA4EABxkQERGRZemyhJQoipprt7To7u7OOYBAXZkgGAxWLRYiIiKiSuGi7EREREQmZatETY/pPoiIiIjMwtBE7ZlnntFlP6FQCB6PB5FIBADQ1dW1ov8a2dzatcCFC8pt7Vqjo6FqYbkTkc3p0kdNq3A4jEceeaTs/Xi9Xni9Xh0iIsuqqwO2bzc6Cqo2ljsR2Zytmj6JiIiI7ERzjdrp06fLOrAsy5npNIjKduMG8Ed/pNz/4z8G1qwxNh6qDpY7Edmc5kTt5MmTOH78OABlOSktHA6H1sMTZZubA44eVe4fPswP7FrBcicim9OcqB07dgzDw8MIBAJob28v+fUjIyPs8E9ERERUQFmDCXw+Hy5cuIC9e/eW/Npdu3YhFAqVc3giIiIiWytrMIHL5UI0GtUrFiIiIiJaoqxEbceOHXC5XJpfz6ZPIiIiovzKnp6jt7dX82v37dtX7uGJiIiIbIvzqBERERGZVEmJml5LPhXjqDrknqgYa9cCP/qRcuNSQrWD5U5ENldSolbNPmV+v79qxyIbqKsDfv7nlVsdK4prBsudiGyO72xEREREJlXSPGrpdBr33HNPpWLJOg5RSW7cAL7yFeX+H/4hZ6ivFSx3IrK5khK1VCpVqTiIyjM3Bzz5pHL/4EF+YNcKljsR2VxJiVpra2ul4iAiIiKiZdhHjYiIiMikmKgRERERmRQTNSIiIiKTYqJGREREZFJM1IiIiIhMqqRRn0Sm1dwM/Nu/3bpPtYHlTkQ2x0SN7KG+Htizx+goqNpY7kRkc2z6JCIiIjIp1qiRPdy4Afzpnyr3//f/nTPU1wqWOxHZnCE1ak899RSeeeYZIw5NdjU3B/T1Kbe5OaOjoWphuRORzRmSqB08eBAejwdHjx414vBERERElmBYH7XW1lYIgmDU4YmIiIhMr+xE7fTp0+jv78czzzyDycnJol83OTmJcDhc7uGJiIiIbKuswQSPPfYYQqFQ5vdHH30U0WgUn/jEJ7Ked+bMGQwPD2NkZASSJCGRSECSJHi93nIOT0RERGRrmhO1/v5+BINBiKIIl8uFZDKJaDQKl8sFSZJw1113YXJyEl1dXZAkCQCQTqczr3c6nfja175W/l9AREREZFOaErWJiQkEg0HEYjF88pOfzNrm9/vR19eHEydOYPv27RBFEQcPHkRHRwcAQBAEiKKIvXv3lh89ERERkY1pStSOHDmCQCCwIkkDgEAggP3796O/vx9erxdHjhwpO0iiVTU3A9/5zq37VBtY7kRkc5oStUQigYGBgbzbvV4vHnvsMZw7d05zYEQlqa8HPv5xo6OgamO5E5HNVWRlgj179mDXrl2V2DWZ0OjoKEZHR/Nu37JlC7Zs2VLFiIiIiOyhIolaa2sr9nCh5JoRDAbx5JNP5t3+xBNP4PDhw5UNYm4OUEcge71AY2Nlj0fmwHInIpvTlKgtHb2Zj8PhKLh9YmICp06dwsMPP6wlBDIRn8+Hhx56CABw9uxZHDhwAM8++yx27twJANWpTbtxA/j931fu/87v8AO7VrDcicjmNCVqqyVhxUgmkxgaGmKiZgO5mjZ37twJp9NpUERERET2oClRGxoawte//nW0tbUVfM4LL7yQc5s655ooiloOT0RERFQTNCVqsiyvuqpAOp1GJBLJu83hcKCvr0/L4YmIiIhqgubBBEeOHNFcI6bWqBERERFRfpoSNafTiYMHD5Z1YJfLlbVOKJWO02IQERHZm6ZEzefzlX3g9vZ27N69u+z91DJTTItBREREFaMpUevt7S37wK2trdi3b1/Z+6llppgWwyyamoCXXrp1n2oDy52IbK4iE95SdXBajCUaGoDPfMboKKjaWO5EZHOaE7XJyUlIkoRkMomRkRFMTEygu7sb27dv1zG8wmRZxsDAADo6OjA+Po5EIgG3283RpERERGQLmhK19vZ2TExMQBRF+P1+uFwu7NixQ+/YCpJlGX6/H8FgMOuxHTt2YGhoCOFwuKrxkMHm5oC//Vvl/v/6v3KG+lrBcicim9Nco+Z0OjE0NKRnLCU5efIkQqEQPB4PXC4XAEAQBLhcLkQiEUiSxAl1a8mNG8D/9r8p9z0efmDXCpY7EdlcndYXGl1jtXv3bgiCsOLx9vZ2AErtGhEREZGVaW76zNUX7a233sr7Gr37rjmdTqRSqRWPx2IxiKJYmx3qiYiIyFY0JWr5mhTj8TiSySSCwSBee+01CIKA/v5+iKKI9vZ2bNy4saxgVxOJRJBMJnHq1KmKHoeIiIioGjQlag6HI+fj6rxoHo8HoigiHA7jk5/8pPboiiBJEiKRCIaGhiDLMi5cuJCzSXSp2dlZzM7OZn6fnJysaIxEREREWlRkHjVBECCK4qorD0xOTpZdyyaKIvr6+iDLMkKhELq6uhAOhws2fQ4MDBSc0d/uuPQUERGRNWgaTJBOp1d9TjFNnR6PR8vhcxIEAX19fXC5XOjq6oIkSXmf29/fj4mJiczt0qVLusVhBcFgEF1dXXlvS6c8ISIiIuPo2vRZ6nMqwePxIBQKwe/35x2Z2tTUhKYaXm7GlktPNTUBJ0/euk+1geVORDanKVEbGhrC008/jdbW1rzPkSQJX//61/PWvsmyjFgspuXwAICuri60t7cjGo1mPa5Oz5FIJDTv2+5sufRUQ4MyjxbVFpY7Edmc5j5q6jJNhZpB8y3e7nA4kE6ny6p1SyQSOUefJpNJALB20kFERESEMhK1gwcPorOzU/OBU6kUAoGA5te7XK6cTZtqDVtPT4/mfZMFzc8D3/qWcv+zn1VqWsj+WO5EZHOa51E7cuRI2Qcvp+kzGAyit7cXx48fz0zHIUkSBgcH4fV60d3dXXZ8ZCGzs8D+/cr9qSl+YNcKljsR2ZymdzW9aqvKGfUpiiKOHz8Ov98PQRAgyzIkSUI4HGaSRkRERLagKVE7ePCgLgfP14etWIIgcCoJIiIisi3Ni7ITERERUWVVvEPHmTNncOLEicwoza6uLjzyyCOVPiwRERGR5WmqUTt06BDq6upQX1+P+vp6dHR0oKenB2fOnMl63mOPPYauri4EAgGk02mMj4/j2LFjuOeee/DDH/5Qj/iJiIiIbEtTjdqRI0fQ09MDj8eDYDCIvXv3rnjOo48+iuPHj2Pv3r0Ih8NZk+PGYjF0d3cjHo+XvdYnERERkV1pStQmJiZw6NAhnD9/Pu/2UCiEtrY2vPzyyyu2u1wufO1rX4Pf78fXvvY1LSEQZVuzBvirv7p1n2oDy52IbE5zjVqhedRO3lx7r7+/P+9zXC4XnnrqKS2HJ1qpsRH4nd8xOgqqNpY7EdmcpkQtkUhgYGAg7/ZoNAqHwwGXy6U5MCrP6OgoRkdH827Ptd4nERERmYumRK3Q+p7ArRUH7rvvvoLPU9flJP0Fg0E8+eSTebc/8cQTOHz4cPUCqrT5eeAf/1G5/+lPc4b6WsFyJyKb0/Su1tbWlnfbhQsXIMsy3G53wX1MTExgx44dWg5PRfD5fHjooYcAAGfPnsWBAwfw7LPPYufOnQBgv9q02VnggQeU+1xKqHaw3InI5jQnaj/84Q/xkY98ZMW2QCAAh8Ox6vJQR44cwaOPPqrl8FSEXE2bO3fuhNPpLPg6NpkSERGZh6ZELRAIwOVyIRKJ4K677so8fvTo0cxoz0KT2p45cwapVAqf/OQntRyeKqjmmkyJiIhMTFOi1traioGBAezatQt79uyBIAhIJBIYGRmBKIqIRqM5Xzc5OYlgMIhDhw4hHA6XFThVRs01mRIREZmY5g4dLpcLFy5cQCgUwtDQEHbt2oW+vr6cC61fuHABgUAAkiQBAPbu3Ytjx45haGio4OhRqr58TaZbtmzJNIvmahplkygREZH+yup529raioMHD676vB07duDYsWPlHIoMxiZRIiKi6uMQKSoKm0SJiIiqj4kaFcX0o0jXrAH+/M9v3afawHInIptjokYVVbUm08ZG4Pd+r/z9kLWw3InI5pioUUWxyZSIiEg7JmpUUVqbTEu2sAB8//vK/V/5FaC+Xt/9kzmx3InI5piokT3MzACf+IRyf2oKWLfO2HioOljuRGRzdUYHQERERES5MVEjIiIiMik2fZrE2bNnc/7ctGkTtm3bZlhcREREZBwmagZbmEoBDgcOHDiQ9bj6e/PaFvzkjbNM1oiIiGoQEzWDLc5OAek0Oh74Mho7tmJu/BLGX3oaHQ98GQAw/tLTGBsbY6JGRERUg5iomURjx1Y03X531u9ERERU25iokT00NgKDg7fuU21guRORzTFRI3tYswY4eNDoKKjaWO5EZHOcnoOIiIjIpFijRvawsAAkEsp9p5NLCdUKljsR2RwTNbKHmRngF39Ruc+lhGoHy52IbI6JGtWM0dFRjI6O5t2eawF5IiIiIzFRo5oRDAbx5JNP5t3+xBNP4PDhw9ULiIiIaBVM1Khm+Hw+PPTQQwCUJboOHDiAZ599Fjt37gQA1qYREZHpMFGjmpGraXPnzp1wOp0GRURERFQYp+cgIiIiMikmakREREQmxaZPsofGRuCJJ27dp9rAcicim2OiRvawZg3AEZu1h+VORDbHpk8iIiIik2KNGtnD4iJw9qxyf+dOoI7fQWoCy52IbI6JGtnD9DTwoQ8p97mUUO1guRORzfHrJxEREZFJMVEjIiIiMinLNn3KsoyBgQHIsgxJkpBMJtHf34/u7m6jQyMiIiLShSUTNVmW4ff7EQgEIAgCACCRSKCrqwvd3d0Ih8PGBkhERESkA0s2fQ4MDGQlaQDgdDoRCAQQiUQQi8WMC46IiIhIJ5ZM1CKRCLq6ulY87nK5AIA1akRERGQLlmz6FEURw8PDKx5Xa9iSyWSVIyLDNTYCjz+OqakpnPvRj5DOs5zQli1bsGXLlioHRxVzs9wz94mIbMaSiVo0Gs35eCKRAADs2bOnmuGQGaxZAzz1FI4ePownf+mX8j7tiSeewGEuOWQfN8udiMiuLJmo5RMMBiEIArxeb8Hnzc7OYnZ2NvP75ORkpUOjKvH5fHjooYcAAGfPnsWBAwfw7LPPYufOnQDA2jQiIrIU2yRqsVgMsVgM4XA4a5BBLgMDA3jyySerExhVx+IicPEitgDYct99WUsJ7dy5E06n07DQqIJuljsAYNs2LiFFRLZjm3c1j8eDYDBY1Dxq/f39mJiYyNwuXbpUhQipoqangR07lNv0tNHRULWw3InI5mxRo+bxeNDf379qk6eqqakJTU1NFY6KiIiIqDyWr1Hz+/3Ys2cP+vr6jA6FiIiISFeWrlELhULo6OhYkaSFQqGia9fIekZHRzE6Opr1WN30NO67ef+dd97B7Z2dVY+LiIhIb5ZN1GKxGGRZzlmTJsty9QOiqgkGgysGg7QAuHbz/te//nX80Ve+UvW4iIiI9GbJRE2SJPh8PrhcLvj9fgC3kjN1G9lXrik4vv7MM8AjjwAAvvCFLxgZHhERkW4smai53W5IkoRQKJRzeyAQqHJEVE25Vhf44Ac/mLl/++23VzskIiKiirBkojYyMmJ0CFRhufqhLbU8WUvX1wO/+7vKLw2WvKxJi4YGljsR2Rrf2cgwhZKxYDCYt8YUWLkUVHrNGuAv/kLvEMnsmppY7kRka0zUyDC5BgUs5fV64fP5DF8KqtTaPSIiIr0wUSPDFLMu59IEqOBSUOk0cOWKcn/TJsDh0C3O1RJKLvRuoHQaGBtT7utc7kREZsBEjQyTqyZK67qcdTMzwG23Kb9MTQHr1ukRIgAu9G5q169XrNyJiMyAiRrRKvRMKImIiEph+SWkiIiIiOyKiRoRERGRSTFRIyIiIjIpJmpEREREJsXBBEQVwvnXiIioXEzUyBbS9fXAb/+28otJlhLi/GtV0NBgunInItIT39ks4OzZszl/btq0Cdu2bTMsLjNJr1kDfOMbRoeRxe7zr5mixrCpyXTlTkSkJyZqJrYwlQIcDhw4cCDrcfX35rUt+MkbZ5msmZTd519jjSERUeUxUTOxxdkpIJ1GxwNfRmPHVsyNX8L4S0+j44EvAwDGX3oaY2NjTNQAZSmha9eU+y0tXEqoCkxRY5hOK6sTACx3IrIlJmoW0NixFU233531O2Wrm5kB1q9XfuFSQlVhihrD69dZ7kRka0zUiGCS/lbEciAiWoaJGhHY38osWA5ERNmYqBFBe38r1gDpyxT93oiITISJGhG097diDZC+TNHvjYjIRJioEZXBKjVArPkjomrj+44+mKgRlcEqNUCs+SOiauP7jj6YqJEtpOvqgO5u5Zf6emODMSGr1PyVrL6e5U5kUrZ936kyJmpkC+mmJiAcNjoM07JKzV/JmptZ7kQmZdv3nSpjokZElsD+LkRUi5ioEZElsL8LEdWiOqMDINJD3fS0ss6jw3FrzU+yFZ/Ph3g8jng8jmeffRYA8M1nnkEaQBrAo7/1W4bGR0RUCaxRIyJLyNW0+cEPfjBz//bbb692SEQ1gd0OjMVEjYiIiPJitwNjMVEjIiKivDjNhrGYqBEREVFenGbDWEzUSBcXL17E2NgYzp49CwCZnwCwadMmbNu2zajQiPJi3xsiMjsmalS2ixcv4gMf3ImZ6euZxw4cOJC537y2BT9542yulxIZin1viMjsmKhR2cbGxjAzfR0dD3wZADD+0tPoeODLaOzYirnxSxh/6WmMjY1VNIZ0XR3w67+u/MKlhAxXrZqqcsudfW+IyOyYqJFuGju2Zt1vuv3uqh073dQE/I//UbXjUWHVqqkqt9zZ94ZqCZv6rYmJGhHpjjVVtBQTBHNgU781MVEjIt2xpoqWYoJgDvwCZU1M1MgW6qangXXrlF/ee+/WfbI1lrs1MEEwB36BsiYmamQf16+v/hwLYDNRiWxS7mZRieuPCQKRdkzULG75vGXqT85dZl1sJiIj8fojMhcmaha1MJUCHI6s+cqAW/OXqXOXMVmzHjYTkZF4/RGZCxM1i1qcnQLS6RXzlS2dy2xsbIyJmgWxmYiMxOuPyFyYqFnc8vnKls5lRlRJ6rJhAJveiYgqhYlaDeIHLJUr17JhQHFN74U6q4+OjqKhoQGbN2/mtUlEBIsnarIso7e3Fz09Peju7jY6HEso5wPWzNIOB3D//covdXXGBlMDli4bVmrT+2qd1ZcrdG3aqdw52peIcrFkoubxeNDe3g4AiEQi6OnpMTgi6yjnA9bM0s3NwHe/a3QYRbPLh7KWpvd8ndUBJSlrc/nQ9P6dRV2bRpV7JcpvtQTW6/XC5/PpdjyyJ7u8t9AtlkzUwuEwAECSJIRCIYOjsSb2bTNWLU+BkK+zuqrp/TtNf21WovwKjbYMBoMIhUJ53++YxJGqlt9b7MqSiRoVJ98ca2Q8ToGgjVnmDaxE+RUabXn48OFMIlZqEpfvg7mYmheyHjO9t7A/tD6YqNnQanOs2VHd9DSwebPyy1tvmX4pIU6BUJp817T3wAG8dfP+pbNnsfWDH6xKPNUuP61JnPraXIqpeVE/8PWgfmjn+uLID239mOW9xa79oY3ARM2GCs2xNj/xLia+/6ym/eZ7oy2mpm7pcyr2Bn3zmxvZT95r+lf/Mzb/zz8DAJwZH4eejaRa+/pUu4+Q1g/mYmpeCv0dpcj1ob006eaHtvH0vm7t2h/aCEzUbExrP7Rcidjo6Cj2dXswOzOdeV4xNXS5akJyvUFXi52/1ddCJ+Ll13RD+/srdiytfX2s0keomARPr0Rt6Yc2gMwH9tIPcLt+aFvl/7JS1y37Q5evJhO12dlZzM7OZn6fnJw0MBrzKKbJNNcb7bQ0nLeWbmlNyPLXLX2DroZiv9VblVUSBDMp1IfmM5/5jKa+PmbqI6RVpb7QLP2QXv4BbldW+b/Uet3mS0TVa2bh+kSFIq4dNZmoDQwMlDSPUzXMjV9a8XN+4l0A1bvQi2kyzfVGq8ZciBneoIv9Vm9VdkgQKiHfB8no6Cge3teNG7MzWY8X6kNTTJOiWfoIacVmSn1Z5f9S63W7WiJ6/c1X0SJ26RJjrarJRK2/vx9f+tKXMr9PTk5i61Zjq2PHX3o67+/VvtDtXlVthqSxErS+0VqlaUar1T5I1t7zy2j9aA/70NxUy82UlWD1xH01q82L2HLvR40MzxZqMlFrampCU1OT0WFkUd8Il1KbFHmhUyVZpWlGq9U+SNbf96u2/mKilV2/0BjB6n1jV5tmY3nSuXRexPqW1ipFaV81maiZUa43QrVJkRf66tIOB7B7t/KLxZcSqjarNM3kknY4cOZmTc/Im29ice3anM9bXqvBDxLzULt25Bs9bpbRtVpZvSmZ02wYj4ka2UK6uRkYGjI6DEuyctPMTMMa/NoDX8Y7f/0HwH/6T3mfZ/VaQTu7/uarAPKPIrf66FqrNyUbMc2GVZLwarF0oibLMgAgmUwaGwgRGU6tBbRarWCta7n3o7j2w3/Mao424+jacpMHqzclV7PvMte9zWbJRM3v90OSJCQSiczv0WgU7e3tCAaDBkdHZB9WGnq/vBbQKrWCtU5tel7aHG3G0bVaa/CuXLkCAFmj45eP8qds5ax7a5aaVD1ZMlELBAJGh0Am45ieBrZvV3758Y+BlhZD47ELsw+9Xzt/A6/8vwNYAJCanl71+XqpxBqGXBdxpUo0gWndp9YavBdeeAFA9kj+5aP8q8kKAxu0LpmmJsVqJU4x+7UCSyZqRMs5AOCnP1V+SaeNDMVWTD/0Pp3G1mspAIBcpUNWonP1avtsamrG889HsGXLFksmcVprlSrRD03PZrViavAefvhhhEKhnCP71f5epdKabNph0u/Vkjgr9FssFRM1sp1Lly7hyvXrmtYkpWz53hRVhUZM5jv/VkgsCqlE5+pC+1yYnoR8+hk88MADWa8pN4krVIOnN621SpXoh1btZrXNmzcD0LdfmtYElpN+W682DWCiRjZ03y4nkiWuSWoV5TQFVavJY7WlyFarcTLDKh3FKNS5WmuSmnOf45fyrhiyWhKX71yvVoMH6NunSmutUrUmcS6mWQ0AFhYWkEgkdPsf0jo1SbkJidUHNuRT6HpRr4l814WZm0WZqJHtzMxMl7wmqVVo/SZdqSaPvElVOo02lw9N799Zco2TmVbpKNVqSWpT81o8Hwmv+EAoZnBGqUkckP9cF6rBm/r3lzF78XVd+1RVolYJyP/lQ60Zy+cP/uAP8Fu/9VtFJVzqB30l5kPTOjWJlafUMYpVpnPJhYka2ZLWNUnNTus36Uo1eRRKqm5ceQsbux7M/F7scP5Cq3Q0bt6O2XfOZ8pyPvl25jlmaLIptF4uoJyf5bVfS2lNRLVOnZDrdS33fhSzF1/XtU9VJayWOK1pasYLz0cgy3LW/8no6Cj2dXvwX//rf835OrUpWZ3+aWkyp/d8aIWmJrFrx/il8tUkjo6OoqGhAZs3b16RTM/OzmZWFipl22c+8xnLNosyUSMqgtZmQ72bG8v9Jq13k0cllj4rtEqHHMuefmf8f/5Z5v63v/1tuH7jNzQdU2+FEqdc870BJhmcAaCueT0A8zeJFfPlY+n/i/p/kkgkMJun1n3mZ/+xoil5eW2Xnv9Dhfp4vvDCCwVrBc1cA1SsUrqlZJ7rqAPSiyVvW9qXc6krV65gfn4eAHI2i5ohIWaiRpa0PAF64yc/wQdEEbOzs0i//fYqry79WFqaDe0wwmo11V76bHliuHb+Bt74dgALU+N4qAJJWiUGpOSa703F5axKV2ripNZU5ZK+MZ2pEQUq33UiV1N5MbWCgLlrgJbK1T1C9dWvfhUf/ehHc35pydV1Yn7iXUx8/9mcNdaFtq3Wl7MQMyTETNSqaOH6BOansldRWJyZKnrbwvSk8vv0pKHb4HBkHp+fSmrepvbHWfrGeeXKlcy3mrfeeguTk5M4d+4cAODVV1/FlStX8N577+ELj/Ri7sZs5nWf/8IXss7deh1jUZs82lw+pKHU6gguHxrb7sB86jJSsWDWB3i5rwOAubk5NDY2ZuIpd5v6u5ZyyLVPVanXrTp1yvK4it1n3dqNqF/fnnn8BoCP/dp/xpXwE/ifzc0r9jk6OpqJf+lxlh5v5u2zWJiexFzqsvL75TeweP0qgJVv5Et/L/V/qJS/XY//2eXHW2rp9bDaPpe6Mf4zALf+F5caHx/HwsICbrvtNiyn/g/n2qeW66+ca/pv/uZvlHgL9MGrW7sxs8+6ltasa27m7bOZbTOX31CunZtN8MWc66XmJ97J9OfM9x7R0NCATZs2AVBq4dUEbW5uLuf1rvc5U2m9pgt1j/jBD36Affv2ZZ6v/p0A0NB2B+rXt2eOV9fSirpl7wPFblucmcqc54a2OzCXupw51+nZa5j4/rP46le/CgD44he/iK9+9av48Ic/jA0bNpgiIWaiVgVXr16F0AR0SH+P+tENWduax97GmnWAcO7v0DDaVnDb9NQkrgDY8OZLcMxcNWzbHOozj6+9vDErzlK23ZhKoW4d8K2/+lOkHcql+MI3/gL/clsHxlMyIt96EU31i5hdUN4M/rj/i2iqd2AxnUZ7I7Dx7p2YS9fjrbM/wvadH0JzyzrckN/FtXfe0jWWy++8i/etA4SxYcyhHjKA9rHXsHZmBDemUlij8+tmZm/gP944hw//3L0YT03qsi0TS4l/e759phfnM/sr5bqtx0LmWP/yvvdh9L1xTftcamn8y/f5ndYNmfjXNDauON66xpXNqXL0WOZ++6ZNuO2uTsxcv5a5zupuTGWusVL+h0r52/X4n11+vKWWXg+r7XOp6XP/AUD5MCvVukagvUD5/fWf/p9YuPmR9Jd/+hXc1iFg9sYcfnrpbXTd92FN13SufU6+fRntzcCGbTtR35L9fjw9dhnTV36Glh8+h3nUAQDWnDmBppZ1mLzwE+X6WHK9LL1W1jUWd66XanjnLTiagQ0Xv4d51EEGsO7iP6FpbB3mrl9F/drSz4ve7wOFrs3VrulNa4F1W1ee57nrV3Ht4lk4rl5G8MgfVvx/wTGjnMt1F7+H+rENmL1+LXOu67CI+mbg1At/jTXNykTp3//7MC69+Tr+8P8aRGur8bXcTNSqYGZmBq3NDvzaB5rRuqk9a9vb597Dq+MOfOreJrTeXnjb5fccCJ0BXB9sRXpixrBt1+rWZR6/47a2rDhL2nZpCq++7cCv3D6DuuYNCAH4+F0O7Nxah6Efy/jO2kW4PvoLuOZYi2f+3x/gAdcvYcumjbj80wv4wZnz+NSH2pR9nv0RPvWRLTePN41XJ7XH8sAHm9DYIiD0HPDwrg78gng7vp+Q8WpL9V7347fewxs/lPHgB5sxOdOoyza9Y5mQb+2vpOt29mrmWF0fuh3/LkHTPrO2LYl/+T4b6uoy8W+/Y/OK472yAdjd9QtY35H94Xrl4gX88MfnsfeXt+P9O+7C5fdSmessPfEuXkkBXZvnsL7DgbGkAxKA+25zID01hx++A3xsqwPv36H9b9flf3bZ8ZZaej2sts+lzm3Ygn/5l1F8cf/H0dC8AV/8sxfx1f/8IO55fwfOnLuMb//Tj+B9YA+mbixmbXvtjbfwV9/+Ln49V/ldSOHVtx1ofW8IV28oX8oaf/Yq1qTqMHF9EZffSePxB3dicXtH8dd0gX0K1xexZYMDn7qvDa2335kVy9/9/VtIzALym7dqut9+8z8y94Vm4Nd/Jcf18u47+I8fvl7Uuc4+3r/jpzNAMs/xNreg5PPy47few+vxMXz0tvfj6kZH9vvq/HTJ7wMFr83Vrun1uc/z25cu4tWUAz27WnX9X3jlvfz/l9+5APz0zeyuC0vP9aU3EvjgJiU5X3jrVUT+9V/Q/VuPYM+ePTAaE7UqWt/ShNYN2UsbJdcqTTLr1q5Zddvk1PTN/TRj/oZx2xz1zZnHWze0ZMVZyrZUvfJ3Jv71nzF1843ou9F/wE821GH0qtIhdIPQhvp65dvYxvbNaH9fByaS4yv22bamAb//31/GjdkZPNiULjkWea0yUqh9fTOaN6wDAGxuXYctHRvRtr65qq97N6VU4W9qbUFT06Iu2/SOpW5+JutaWarQdbtYdyNzrC0dGzE6flXTPlUNc/Pwnf53TE2lMbamYeU+6xyYm59H+sY14EYLMHdzfr25aWB+Go31Doh3tKPjzvdnHa/5RhJvnnPgfe3rc/4vpGaA/x7996zXvPDyv2buv//iFfzcL3yopL99biGNyeuzcExN49p15Vxcuz6DhZk5TM+lsZhOl/Q/u/x4Sy29Hlbb51Kb2zZgbaMDv3jP7Wje0AEA+OjPbYPz3vfjfW3r8S8/uoD/34e24erMYta2uvkZPFvvyF22yuHQfvdH0FTXArz+PWz60Eex5TYB85feRno0gbmpCdSrL5ubBm5cQ0qWMT2nnLOZuvrM+ZqcmsbVqeuYW0jn3Ofc+XPA6Bs5Y9l1z+2Qx97DJ/7/XWi97Y6sbZcvnEfih2dzXi8tdTfw5o8cRZ3rUo9X6nm5OnEFFy/+FN/5x7fzvq+W8j6w/P9Sj//npcda7XXLr81C/yfvXSv8f7nrntvxiV/JTrxG3jiL4X8/j3vuEbG4dgPw+muYa9uO65fO41//9V9x5513Gt78yUSNDJNenAMANN/1C1ioawES38PaD/wy1t8moOn8OeDSG0Xvy5EGOsZk5X5TJaIlPckpWenTcnNKjStjY5iYkEvfUTqN2yeUwRq5Jue4enUKFy9exPPPv40NTY7MB5U6U75Wbc3AQ5/M/eH6b6+dhfPeO/K8Mr/UDPD1l+IA4pnH/vbvvp+5n3jzMrbf+wHNMZtdXfP6zJey+rWtaFjfDkfdewCAU6dPZ5KOF154Af+yoQ4v/mQOkgxIL+U+X5tb8uyzKf86wOvWNmJtowNbOjagY0tH1rZ5+TIa6x26/K3FHG9i9KeYXwTevZbGTJ3yt49dS6P+ahpXJm5gbiGd87yMXl1EOp3W5X3VKHMLaYyOX8X1+nG8e/N9/d0xGQtXr+O9a4X/T3IlY+r/5cfu24Gty87zP716DW9PAc9973zmsb97Vbn/xS9+EWNjYxxMQIUVumCn59K4en0WHYV3YXqlvplWkpySUT97s4Ps2BhGN9QhJacMicWO0jcHgJw6fRr/9s/f0S1xymdmZgbp9CKa79qF9bffgbXvyZkPrsXJK5o/tBrr83+YN9QBU9M3cGk0+382feMapufSGJvMvXh8oeTv1fhZ3Ll544p9lvM+YIX3lkJf5u5r+DHkmfM5a6NG3jiL1350HqPjVzFTtwAAmb/xvZRS22Z2r1+4smoiWigZM9P7aqlW+9JSajI2L1/G2kYHNrSs/Bb/4R2bMfbOaNZ1NJm8gpdiP8AfDXwV+/bt0/Ev04aJmsnV+rfsalmaQOT6hkr6WPrBq2fitJq65vVoWN+O+qtK2davbUV69lpFjrXa/+y3f3AeD33if1nxukLJ3/Q88M3Y6wBez7nP7525gPoNm0pKDK303pIr6Vjf2pq3NuqfXr2Gi5Pq36dYnuSYXa4EQqU2i1YrGcuX1K92jWm1Wo11qclYIblqNZN1s2iqd+Cee+4xvNkTYKJmepVoYqGVym2G1bsmbm5+HleuXMHVZfu8cmUMczcnZ7SyaiZO1Zbvf/ady2/jBz9I4Dd+qfQJUgu9D/zPV8/itXPv4LVzL2YeX5qUfP3l13Hn+7M7c597O4m1DcDnXb+ALdvuWrFPq7+3FJPkmF21m2EL0frlQ6tCX1q0JGNWx0TN5HjBVlep31ArURO3tF9Vrn1e/Nkirl69CjSu07R/qqx8/7OLM5NY2+jApo1rddvnvHwZt60D9rlzJ4Z//50E/u5fJfzdv/5Fzv3edWUCv/i/2O+9xUxJjh1U4ssHFY+JGlEZ9BwQoVrar2r5PpsvvY30pQRmZmbQzEQty4ReAxQqTLeBFDcVSgxvWwf8yaOfwkd23oOzF6/gwFdO4tk/3I8JWcbT//1lS9eamcm16VlMz6Xxk58l0bwhe2WUc28nTdMn7tq0MoI4Z9+95FXMLaRXtA5MTMgV+fJBxWOiRmUr+M9fpY67aQcw2boOc3NzSONGxY+3XCX6iuTaZ13zRNmx2orDgWTLGkzP3MB3XnkF/zL0/YoPUNCq2gMpACWJ+8Cd7XDee2s6iZ3bNmN8XZ3la83M5N/PjUKSgf/0py8DeHnFdrP0iStmgMLy1gEyHhM1Klsx//yVNtfQgL/8fQ8unH0dM99PVP6AZArzjQ148lc/jFPfT+A3xI9UdYBCqYwaSEGV9wv3bMGVn/0U/+W3P4U164RMzeXObZvxg38/hz99bmXyVg6tX46L6bu3vHWA16bxmKhR2ezQcZf0ZcTUD3oPUKjU32CHgRS5Bs9oHehSKOn46TsTuDprbG19MdatbcLaRqX2Up0IeOe2zXDe+36Mj4/r3idO65fjYvruLa/Jt9q1aUdM1Khs7LhLy1lp6od87PA36G21wTNaBrqslnQA1p5moxL45bi2MFEjW2iYX8Dn/vJF3Jiexj81mONbdi2r1rQy9XPz+PLps+idSuP5+QVd9qni1DgrFRo8ow50eWf0HdS3KAtZFzNVTaGkQ5241v0xayQk1Zowm1+OawsTNbKFunQat48qa4DWbTI4GKratDKOdBrbZGUJqRd0zs85NU5+pS73VGiqmsJJRyvOnzN/QsIJs6mSmKhZmBWWgDETM4xOperj/0l1VGKqGquo5b8d0H/KGcrGRM3CtPahqdUPLjOMTjXK+OT0qvMn2RX7mlWXldeYLJcZ/vZqfiEtd8oZJnjFYaJmYVr70NTqB5cZO+BWa+mp57//o5pNUtnXjCrNTLX11fxCqnXKGSPmFLQyJmoWVqgPTUMdMDV9A5dGV9aaKWv8fRhbtm3Pel2hDy6tb0RmegMzUwfcai891Xx1AaKAnEnqO5ffxvC/JfJOuTA9M7Mi+bPSt14z9TWr1dpsuzNTbb0RX0hLnXKGcwqWhomaTa1Wa3bXlcmS1vjT+kZkpjcwM6n20lNt589h7Ttv5ExYFiavoLHekTdpfPvtBTz//Au6zVZey8lKrdZm252ZauvN9IV0NXaYU7AamKjZlNbmnnwfolva1+H964GP/VLumrh8b0TVfAO73tKExfkFAKVPummUai09VXBh+SKSRj1nK9c7WZla04Abc9Yoc6s3w5qphtxMrJQckfUwUbMprc09q32I/ixPTVy+N6JqvYHdaGxA6P/4PC6cfR3TXEJKk0IJnp6zleuZrMyvacQfPfARnPp+Ap9trNccU7WYqRlWC9aQE1UfEzXKwm/8VGmVSFZquTm1moqZnJb/e0T6YqJGWfiNfyU7DKSwO/b9yk/PKRAK1ZD/06vXcHGSyz1ZVb73K37ZMR4TNbKFhvkFdP/NP+DXpqbw2Vbgo7+iX5+4ag+kKJjg3ZzzrFpL1Zhd/dw8fv97P8Fv3gC+8Wu70LLlzqztVqkJroRqT4Fgpg71VLrV3q9q+cuO0ZiokeXkSmTGxmTcefFdAMCaNujaJ07rB5DW1xWT4HGpGoUjncY9Y1MAgH9sW4+NFq0JroRqT4HADvXWlu/9qpa/7JgFEzUypUK1Sj84e3lFIvPc37+Kr9+8L8/oG4vWDyCtrysmwavVpWqodJwCgYqR7/2qUl922K+0eEzUyDClJmNLa5WEZmCf61Yis2ZuHvibf8hs0zMWM07Ma4alaoiItGK/0uIxUSPDrNbEtzwZU6m1SksTmYYbc5ntWmZp4LQDRETVY/UZBqqJiRoZppgmvmr1d9Han8xMNXFERNWmtQnT6jMMVBMTNTKMmTofa42FNXFEVMvYhFl5TNTINuYaG7C4uAigeqMf7TAlQaFawZ++M4Grs+aeW2m2vg4LC7U34pXIDNiEWXlM1MgW5tc04i/6DlR9CSkz1QpqbYZdrVYQyD+JqdHflufXNKLvN3ZZZgmpauPIOqo0NmFWHhM1IgNUom+b1mbYYpYFcn+McytZEZuliKyPiRqRASrRt01rM2zhWsFWnD9XvbmVSF9sliKyPiZqZAv18/N4IPJdXJ+axPfT5h9pWYlRptdm5tBQp++qDGZXPz8P7z+fw76JNL6zsGB0OKbDZiki67N8ojY4OIjx8XF0dHRgZGQEbrcb3d3dRodFVeZYTGPHyM8AAPWbDA6mCBxlqg/HYho//+4kAOC7HE9ARDZk6UTN5/Ohs7MTgUAg85jb7UYymYTX6zUwMqLKsMMoUyIiKp5lE7VEIoFQKIT0smauQCCArq4uJmpkS2YaZUpERJVXZ3QAWgWDQTidzhWPq49FIpFqh0RERESkK8smarFYDKIo5twmCAKi0WiVIyIiIiLSl2UTNUmS0N7ennNbe3s7hoeHqxwRERERkb4s2UdNluWC2wVBKPic2dlZzM7OZn6fmJgAAExOTuoR3grXrl3DYjqNsXevYPbGfNa2VCqFhcU0xq6M4Ua6jts0bmuYm4daeguLMG2cdtlmljiWlvv42BiuNTSa8nxxG7dZdZtZ4qjmtqupFBbTaVy7dq1ieYG63+X97HNKW1AqlUoDSHu93pzbnU5nWhTFvK9/4okn0gB444033njjjTfeDLtdunRp1ZzHkjVqgiAU3L5ajVt/fz++9KUvZX5fXFxEMplER0cHHI78o+YmJyexdetWXLp0CRs3biwlZFvjecmN52UlnpPceF5y43nJjedlJaudk3Q6jatXr+KOO1ZfHcSSidpqkslk3oEGANDU1ISmpuwZuVdL/pbauHGjJS6EauN5yY3nZSWek9x4XnLjecmN52UlK52T1tbWop5n2cEEgiAgmUzm3CbLMnbv3l3liIiIiIj0ZdlEbf/+/ZAkKe92t9tdxWiIiIiI9GfZRM3j8SCRSKzojxaLxQAALpdL92M2NTXhiSeeWNFsWut4XnLjeVmJ5yQ3npfceF5y43lZyc7nxJFOFzM21Jw8Hg9EUVyx1qfP5+PC7ERERGR5lk7UAGBwcBDj4+Po6OjAyMgI3G43kzQiIiKyBcsnakRERER2Zdk+akRERER2x0SNiIiIyKRsOeGtFqFQCCMjI5nfOzs74fV6i3qt2+2G0+lET08PnE4nJElCMBiELMsIBoOVCrkiEokEBgYGEAgECk4aXAw79R/U67zY6VpZTi1vQJnLsKurq+j/oeX7sMM1A5R/Tux6vQwODmJkZASCIECSJPT09JRczna7VoDyz4uVrxdZltHb27vq36xHuVvu2il9pU17SaVSaZfLlQ4Gg5nH4vF4WhTFdDweL2ofTqdzxfpdLperUiFXVDgcXnVtsqXnKh+v15sOBAJZjy0/z1ai13mx07WylNfrTY+MjGQ9FgwG867Hm28fdrpm9DgndrxeXC7XinMgimI6HA4XvQ+7XSvptD7nxYrXS3d3d9rr9aa9Xm8aQMG/V49yt+K1U/ODCTweD9rb27O+bcRiMXg8HsTj8aJqTzweD/bs2YOhoSGIogi3212RedyqYXBwENFoNOffnUwmIUkS4vF4wX0kEgl0dXVh+aWV73Er0OO8APa6VlSxWAzRaDRrmhxVV1cXTp06teoSbXa7ZvQ4J4D9rpdQKASfz4dUKpX190ciEfT29iKVSq26D7tdK4A+5wWw9vUiSRI6OzsRDodz1m7pUe6WvXaMyQ/NIR6PpwGs+NZbqlK+IZtdX19f3m1erzedSqVW3YfX6007nc6c27DKNyaz0uO8qM+1m0AgkO7u7s65rbu7u6iaabtdM3qck3TafteLKIo5y3lkZKTocrbbtZJO63Ne0mlrXy+r/a16lLtVr52aHkwwMDAAQRDK7otlJ/mW3opEInC73UXVAsRisbznVBAERKPRckI0hB7nxa5EUUQkEkEoFFqxLZFIwOl0rroPu10zepwTO5IkCe3t7SseV8u+mHK227UC6HNe7E6PcrfqtVPTiZokSRBFEbIsY3BwEIODg/D7/TnfXIuRSCQQCoWQSCR0jrR6clWTS5KEoaGhojtb5nvTAYD29nYMDw+XFaMR9DgvS9nhWlF1d3dDFEX4fD643W7IsgxZluHxeBAOh4vah92uGT3OyVJ2ul4KKaac7XatFKPUv8mO14se5W7Va6emE7VEIoH29naEQiH09fWhr68PgUAA0WgUPp+v6P0kk0n4/X4kk0l4vV4kk0l0dXUVXDTeSvx+f86+NrksX3t1OUEQVn2OVZRyXlR2vVbi8ThcLhdisRja2tqwd+9eHD9+vKiaI7teM+WcE5XdrhdRFJFMJlc8rpbvauVs12ul3POistv1otKj3K187dRsoqYWSCwWW1EjEggEEAqFMgu8r8btdiMQCGRqXVwuF3p6evI2l1lJJBLBnj17jA7DdLSeF7teK4IgwOPxZP6XEokEent7DY7KWHqcE7tdLz6fL2ctT7HvtXal13mx2/VCippN1NQ+RaIormizVn8vdt6ZXPMiuVwuSJKESCRSXqAG8/v9JTXtrdZXy6zfWEpV6nlR2fVacbvdaG9vRzgcxsjICFwuFyKRCDo7O4v6JluIVa+Zcs6Jym7XS19fH5xOZ87uJYIgrHot2PVaKfe8qOx2vaj0KHcrXzs1m6ip8hWeOuGgVnboBJpIJDL9+PSSTCYt3/Fe7/Ni9WvF5/Nl1RyJoohoNIpgMAhJkuD3+8vavxWvmUqeE6tfL/F4HCMjI5l+wYODg+ju7oYsy9i9e3dZ+7bitaKq1Hmx+vVSDD3K3czXTk2vTKAOJMil2Oza4/EUnEMrV78DqwgGg5qSEUEQ8v7derwZG03rebHrtRIKhXLOP+T1eiHLMk6cOLHqPux2zehxTux6vQBY0bdTfb/t7Oxc9bV2u1aWKue82Pl6AfQpd6teOzVdo+ZyuQpevMUUmjogYTl1v1bu3xWLxTR9w9i/f3/B2kir95fQel7sfK3kU2zzsN2vmaWKPSe1dL2ofbGKWV6rlq6VUs6L3a8XPcrdsteO0RO5GUmdYG/5hLfqRLjFTEqZbyLUQCCQBlD0RKhmBI3Lj0Sj0Zx/e77HrUbrebHrteJ0OtPRaDTntmAwuGK5llzsds3ocU7seL2Ew+G0IAgrYne5XEWdk3TaftdKOq3PebH69bLahLd6lLtVr52aTtTSaeXiXv6h63Q6c170oiimRVHMeiyVSq2YDToej6cFQTDtLMfFSKVSRSUkuc5JOq3Mvr78HLpcLkufk3S6vPNi12tlZGQkLYpizi88uWbnr4VrRo9zYsfrJRgMrpgZvq+vL+8qDrVwraTT+pwXq18vagVJoTU3Syl3O107Nb/WJ6D0J4lGo2hvb0cymURPT0/O5omuri60t7ev6JQpyzL8fn/WAIT+/n7Lzz7e1tYGr9dbcK6wfOcEUNbHHB8fR0dHB0ZGRuB2uzWNlDSbcs6LXa8VSZJWnI/Ozk709fWteG6tXDN6nBM7Xi9+vz+rD3BXV1fepr1auVYAfc6LFa8Xv98PSZIyg7QEQYDL5VqxBreq2HK307XDRI2IiIjIpGp6MAERERGRmTFRIyIiIjIpJmpEREREJsVEjYiIiMikmKgRERERmRQTNSIiIiKTYqJGREREZFJM1IiIiIhMiokaEdmCLMsFF1y2MlmW4XA4MrdQKFTR4/l8vsyx2traVmxPJBIVPT4R3cJEjYgsT5Ik+P1+iKJY9GsqnezoTRRFpJX1mfMuLaSXYDCYOVa+WHw+X0VjICIFEzUiKprb7UZnZyfa2tpMVavi9/tzrguYjyRJ8Pl8tq2BqzRBEODz+ZisEVUBEzUiKlo0GoXP58taPNpoHo8H/f39Jb1GTepKSe4om9PphCAIiEQiRodCZGtM1IioJC6Xy+gQMtRaPafTWdLr1Jo0JhnlCQQCGBgYMDoMIltjokZEluX3+0uuTUskEnC73eju7oYkSaZqwrUil8tluf5+RFbCRI2ILEmSJEiSVHJtWjAYxP79+9HT05P5nbTz+XwIBAJGh0FkW0zUiMiSgsEguru7S35dMpmEIAiZ1548eVLv0GqKOtKWNZNElcFEjYgsKRaLwe12l/Wa7u5uyLKMWCymd3g1xeVy8RwSVQgTNSLSlSzL8Pv9CIVCGBwczNwvRJ0HbXBwED6fL1M7Mzg4iFAoBLfbvWIqjUQigd27d5cUWzgcxv79+zO/l9r8qTXOpedj6evK4ff70dnZmZmYtqura8Vzlk5c29nZCVmWM1OsOBwOAEryqsaldbqNrq4uRKPRsv4eIsojTURUgng8ngaQjsfjK7ZFo9G00+lMp1KprMeDwWDa5XKteDydTqfD4XBaFMWsbU6nM+1yuTK/BwKB9MjISFYMgiCUHHt3d/eKxwCki3kr1BJnMBhMO53OrP2kUqm0KIrpcDhcdNzqa3IRRTHvNjXG5cfq6+tLA0hHo9HMNq/Xm/M8FHOetZYHEa2OiRoRlSRfopZKpdIAshKVpfr6+lYkSuprgsFg1uPRaLTgvtSEsBThcDhnctTd3Z0GUDBx0hKnep5ybQsGgyUlNoUStUAgkAaQMwlOp5UEbDk17r6+vqxjRKPRFc8tJk71/BCR/tj0SUS66O3thdPpzLuMk8/nQyQSyWr2U/s1LW/CVOdqyzfPmZYVBU6cOJFz8IHa3HfixIm8r9USZ29vL1wuV87zsX//fsiyrMs8bupyUrmalxOJBDweT97XdnZ2Zu4LglD2HHlc6YFIf0zUiEgXkUikYJ8xNWHJlRAJgpDzNePj4zkfl2UZ7e3tpQeZg8vlKnqG/VLiTCQSeZNWdT9DQ0NFx1kopu7u7pz97E6cOFEw+Sq1j1+hGACYasUKIrtoMDoAIrI+tSYlXyKjEgQhq0ZNTSKWJzXqc/KN6hwfH1/1WEtFIhFIkpR3f+3t7Zkarly1bqXGqT4uSVLegRTBYFC3RMnn88HtdiORSGTNK9fR0VHwdaWcQyIyBhM1IqoaWZaRTCYzvwuCAK/Xi4GBgawESf09X21QR0dHSSMnT5w4gXg8nnd7IpFAV1dX3rnZSo1TTYCcTmemabKS1CbWgYEBhMNhAEpT6GrzzOlVK6nKV4NIRNoxUSOisqkf0MU0fS2vRRIEITM1RGdnJ0ZGRrBnzx709fXl3YcgCFkJXyHFNJOqfetisRhkWc5Z01RKnOr5qGafLZ/PB7/fn4l/ZGSkKkkicKvcWUNHpD8makSki9UmPVW35ercXmpCIYpi0f2hTp48WdT8YGqic/LkybzxlBJnd3f3qrV+sVhMt0XuvV5vJn6Xy4U9e/bost9iqKs9EJH+OJiAiHQRDAYLLnIeDAbhcrlWJCZaJn8VRbHo2qpoNFrUeqBqEpZv8ttS4zx+/DgkScqbvEYiEV2bHtVRm4FAIG9fu0pJJBK6N6MSkYKJGhGVJF+ToyiKCIfD8Hg8K5IotTO/2n9q+f78fj8SiQQSiURmsfVCRFGEIAirPi8UChWdYAmCAFEUMzGUG6cgCIhGo/B4PCtiSCQSSCaTJS8ovxq/3w9JkvKOllWptZHFNh+vRpIk3WoGiSibI51Op40OgoisQV0iSZIkiKIIURRXLB0kSRICgUBmjq7x8XF0dHTk7XOmduTPxel04vjx4zkTGo/HA7fbnbM5MhaLwefzZRIpNc58nd0jkQgGBgYyCZUgCNi9ezf8fn/WiE8tcapLagHKvGVqQlhKYiPLMrq6ujAyMrLqc9va2hCPx3P+rbIsw+PxYHh4GLIsZ8pw6d+Za3+pVKrgMd1uN3w+X1Vr8YhqhtEz7hJR7QqHw2mv17ti9v5UKpWOx+OZZY1yrRoQjUazlm8ya5x6KLQywXJLVxvQQzErE3D5KKLKYY0aERlCkiR0dXWtWlsTiUTg9/tz1iZ1dnYiHo9XtCO7HnGWq9gaNVmWCw6G0GK1GrVIJIJoNFr0wvZEVBr2USMiQ8RisaImfHU6nXn7gvl8vrwTyupFjzirJRQKVW1KDlUwGMw07RKR/pioEZEhXC4XhoeHV31eoSks+vr6Cq7RqQc94qyESCSSd6WFaonFYpl+bkRUGUzUiMgQoigiEAhkBijkEolEEAwGc44WVQUCgYrW6OgVp96Ghoay4hkcHCw4SXAlBAIBBAKBqh6TqNawjxoRGUqSpEz/pqVrU46MjMDtdhc1knBwcBBOp7OiNVp6xKlVrj5qsixjYGAgE4vL5dJ9ug8gfx81v9+Pnp6eihyTiG5hokZEthAKhTJrXtqNLMtoa2vL/B4IBCpae7a0758gCCsStUgkAlEUmaQRVQETNSIiIiKTYh81IiIiIpNiokZERERkUkzUiIiIiEyKiRoRERGRSTFRIyIiIjIpJmpEREREJsVEjYiIiMikmKgRERERmRQTNSIiIiKT+v8ANS2HwPStnCgAAAAASUVORK5CYII=", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Now plot the SFRs for the metallicity evolution model\n", "fig,ax1 = plt.subplots(figsize=(7,7))\n", "ax1.tick_params(axis=\"both\", which=\"both\", labelsize=16)\n", "# ax1.bar(unique_template_logAge, mdf_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", "ax1.bar(unique_template_logAge, mdf_sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(mdf_sfr_med .- mdf_sfr_lower) .* 1e3, \n", " (mdf_sfr_upper .- mdf_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"Result\")\n", "ax1.bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "\n", "ax1.set_xlabel(\"log(Age [yr])\", fontsize=20)\n", "ax1.set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\", fontsize=20)\n", "ax1.set_ylim([0.0, 9.0]) # ax1.set_ylim([0.0, ax1.get_ylim()[2]])\n", "\n", "# Draw vertical lines to denote times at which `x` fraction of stellar mass was formed more recently\n", "for q in (\"0.01\", \"0.001\")\n", " laq = log10(sfh_quantile(parse(Float64, q))) + 9\n", " println(laq)\n", " ax1.axvline(laq, ls=\"--\", c=\"red\")\n", " # ax1.text( log10(sfh_quantile(qn)) + 9, ax1.get_ylim()[2] - 1, L\"$\\leftarrow$ \\n $ %$q \\text{M}_*$\", transform=ax1.transData, ha=\"right\", va=\"top\")\n", " t = ax1.text(laq - 0.02, ax1.get_ylim()[2] - 0.5, \"\\$\\\\leftarrow\\$ \\n \\$ $q \\\\, \\\\text{M}_*\\$\", transform=ax1.transData, ha=\"right\", va=\"top\", fontsize=20)\n", " t.set_bbox(Dict(\"facecolor\"=>\"red\", \"alpha\"=>0.25, \"edgecolor\"=>\"red\", \"lw\"=>2, \"boxstyle\"=>\"round\"))\n", "end\n", "ax1.legend(fontsize=20)\n", "# plt.savefig(\"example_sfrs_hires.pdf\", bbox_inches=\"tight\")" ] }, { "cell_type": "markdown", "id": "e8ddecee-3c5d-4322-bf1a-a22beb1317e3", "metadata": {}, "source": [ "It is important to note that there can be strong covariances between the SFRs (or stellar mass coefficients) of neighboring time bins, as their templates can be very similar. We can calculate the correlation matrix of our posterior samples to examine these correlations." ] }, { "cell_type": "code", "execution_count": 56, "id": "7f313c41-360d-4d6e-aacb-f7bfec859222", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "5×5 Matrix{Float64}:\n", " 1.0 -0.39021 -0.204723 -0.106157 -0.0689796\n", " -0.39021 1.0 -0.0561793 -0.0479354 -0.0201329\n", " -0.204723 -0.0561793 1.0 -0.0555755 -0.0372933\n", " -0.106157 -0.0479354 -0.0555755 1.0 -0.0290286\n", " -0.0689796 -0.0201329 -0.0372933 -0.0290286 1.0" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import Statistics: cor\n", "cor(mdf_sample[1:5,:]; dims=2)" ] }, { "cell_type": "code", "execution_count": 57, "id": "fa7875f1-42a5-455a-a32a-6d7fc99bb753", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Young stellar pops show minimal correlation\n", "plt.imshow(cor(mdf_sample[1:10,:]; dims=2))\n", "plt.colorbar()" ] }, { "cell_type": "code", "execution_count": 58, "id": "b863c189-67c0-41a3-ab8c-7e8c7aec6089", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Old stellar pops show greater correlations\n", "plt.imshow(cor(mdf_sample[end-20:end-3,:]; dims=2), clim=(-1,1))\n", "plt.colorbar()" ] }, { "cell_type": "markdown", "id": "81bf2870-3f58-4c3e-a249-a60794e76b0d", "metadata": {}, "source": [ "It can also be instructive to look at corner plots of the samples to examine their covariances," ] }, { "cell_type": "code", "execution_count": 59, "id": "d4ccdaf6-5bd0-4843-94bc-c1dc45e564ed", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig=plt.figure(figsize=(7,7))\n", "corner.corner( permutedims(@view mdf_sample[end-20:end-10,:]) .* 1e3,\n", "# corner.corner( permutedims(@view mdf_sfr_sample[1:5,:]) .* 1e3,\n", " fig=fig,\n", " quantiles=[0.16,0.5,0.84],\n", " max_n_ticks=0, # turn ticks off, illustrating shape only\n", " show_titles=false,\n", " title_kwargs=Dict(\"fontsize\"=>17),\n", " label_kwargs=Dict(\"fontsize\"=>25))\n", "fig.subplots_adjust(hspace=0.0, wspace=0.0)" ] }, { "cell_type": "markdown", "id": "a0025533-b1a6-4c83-a6d4-7e73e2939f7a", "metadata": {}, "source": [ "We can also look at the overall mass-weighted metallicity distribution function that results from the combination of our star formation history and our age-metallicity relation." ] }, { "cell_type": "code", "execution_count": 60, "id": "481bb820-9d92-4855-a7cf-016b8091bd45", "metadata": {}, "outputs": [ { "data": { "image/png": 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ObGfbtiqVSs97hUKhZ1cmz/OUTCZ7HsHxUxeLxXraeJ4nx3H08OHDM/sPAMCoRh7JvvXWW77a3bhxQ/fu3TuzXSQSUblclm3bWlpakuu6Wlxc7BmBtlot1Wq1nulhP3WJRELValW2bUt6PtItFAqMYgEARk107+IPP/xQi4uLfRc4nSUWiw18bjUSiWh3d3foOul50BKqAIDzNNZ08XGRSETz8/P64IMP9OjRo7E6BgDAZTfySLbdbp94r7Oy+MaNG3rw4MHovQIAYAr4Dtm9vT1tbm52v97c3NR//ud/nhq2tVpNa2tr+sUvfjGZXgIAcAkNNZJtNpsql8sqFouam5tTuVw+tV08Hu8eig4AwKzyHbLz8/O6deuWbt26pVQqpUqlot/85jcm+wYAwKU20j3ZRCKhubm5SfcFAICpMvLq4qOn8JyG1cUAgFnneyT76aefKhwOd8+K/eijj/q29TxPuVxOb7755vg9BADgkvIdsrFYTNFoVOvr65KkVCo18IScvb29iXQQAIDLynfIlsvl7vFwknTz5k09fvy4b/u33357vJ4BAHDJ+Q7Z4/dgj27Af5pMJjNajwAAmBIjL3w67dzYozY2Nka9NAAAU8H3SHbQQqfjPM9ToVDQT3/605E6BQDANPAdsmctdDqOhU8AgFnnO2TPWuh0HAufAACzzvc9WcdxhrowC58AALPOd8i++uqrQ1346Ik9AADMInZ8AgDAEHZ8AgDAEHZ8AgDAEHZ8AgDAEGM7Pg27UAoAgGkz0qHtR3300Ucql8tyXVeRSEQrKyv60Y9+NIm+AQBwqY08kpWk1157TYlEQuvr62q321pfX9etW7f0k5/8ZFL9AwDg0ho5ZO/fv69kMqnDw0PVajU9fvxYtVpNh4eH+t73vqcHDx5Msp8AAFw6Y41k33nnnVPfv3fvntrt9jiXBgDg0hs5ZBcWFsb6HACAaTdyyJ41UmUkCwCYdb5XF//xj3/s+Toajer27dt6++23e0atrVZLa2trymazE+skAACX0VDbKs7NzZ0YoZbL5b41uVxu9J4BAHDJ+Q7ZRCKhcrms+fl5k/0BAGBq+L4na9u2r4D96KOPTkwtAwAwi3yH7PG9i/uJx+Oan5/nOVkAwMwba1vFTz/9VPV6Xa1Wq+d9z/O6R+INw3VdOY6jaDQqSbIsS+l02khdMpnU2tra0H0EAMCvkUP2448/Vjwe754n2zkGr9VqKRqNDlwQdRrXdRWPx7W5udm9pm3byufzWl1dnWhdPp9XtVodqn8AAAxr5JAtFotqNBq6ceOGPv74Y0l/P3lnc3NTnucNdT3HcZROp3sOgc9ms1pYWBgYssPWua470igbAIBhjbwZRSwW6x53F4lEVCwWu5/duHHjxBTyWUqlUne6t6MTnINGncPWVSoV3b59e6i+AR1bW1uq1+tnvp48eXLRXQUQACOPZOfm5rr/e35+Xuvr6/rrX/+qf/qnf5Ik1et1/fjHP/Z1Lc/z5HmeIpHIic8sy1K9XlcikRi7rlKpKJVKqV6v++oXcNTW1pZe/sEP9ezpVxfdFQCXxMgh22639ctf/lIffvih1tfX9ctf/lKJRELFYlG7u7tDTcm6rtv3s3A4rGazOXad53lqtVqKRCK+Q/bg4EAHBwfdr/f3933VYTrt7Ozo2dOvtPjGz/Xi4rWBbZ+6Ne394bfn1DMAQTVyyN69e1cPHz7sTtWmUim5rqtbt25pbm5uoit3h72/e1pdsVgceG/3NLlcTu++++5I3xvT68XFawq99P2Bbb5ubp9TbwAE2ViP8Ny9e7fn69XV1aGDTFLPoqXjBt3b9VtXrVZPnW4+Szab1c9+9rPu1/v7+7p2bfAIBgD68Xuv/urVq7p+/brh3uA8jBWyk9J5/Oe0EavneX3D1G9dvV4fKfxDoZBCodDQdQBw1N++3JXm5nTnzh1f7b/5rW/rz396QtBOgbFD9qOPPlK5XJbruopEIlpZWdGPfvSjoa5hWZYsy+o7ak0mkyPXdR41sm27+37nnqxt21pcXBwpgAHAr8ODL6V229f9/K+b22r+7tfa2dkhZKfAWCH72muvqVqtKhaLKRwOa319XYVCQSsrK/r3f//3oa61srKiRqPR815nYdOgqd5R6orFoqrVqhzHGaqPADAOP/fzMV1Gfk72/v37SiaTOjw8VK1W0+PHj1Wr1XR4eKjvfe97Q+9dbNu2KpVKz3uFQkGFQqH7ted5SiaTPauD/dQdN+pCKgAAhjHWSPadd9459f179+7p/v37Q10rEomoXC7Ltm0tLS3JdV0tLi727EHcarVUq9V6pof91HW4rqtCodAN5eXlZSWTSV/7IwMAMKyRQ3ZhYWGsz08Ti8UUi8X6fh6JRLS7uzt03dF6x3GYJgYAnIuRp4vb7fZYnwMAMO18j2SPH8QejUZ1+/Ztvf322z2j1larpbW1NWWz2Yl1EgCAy8h3yMZiMc3NzZ0YoQ460i6Xy43eMwAALjnfIZtIJFQulzU/P2+yPwAATA3f92Rt2yZgAQAYgu+R7K1bt059/9GjR3r//fe7Oz699tpr+ud//ueJdRAAgMtq5NXF0vPdln7605+q3W7rxo0barfbeuedd/T6669Pqn8AAFxaIz8n++DBA92+fVulUunEZw8fPtSDBw/0i1/8YqzOAQBwmY08kp2fn9dbb7116md3797lOVkAwMwbOWTn5uYGfj7Kjk8AAEyTkUP2k08+GetzAACm3cghe/v2bb3++uv6/e9/r/39fUnS/v6+Hj16pKWlJf3kJz+ZWCcBALiMRl749Oqrr+qdd97R3bt3tbm52X3fsiwVi0W98sork+gfAACX1lhH3SUSCX3yySeq1+va2NhQJBLp+zwtAACzZuSQffjwoer1uv7t3/7N91FzAADMkpHvya6trbHNIgAAA4wcsktLS7p3717fzznqDgAw60aeLl5eXtaDBw8kPT8GLxwO93xerVY56g4AMNNGDtlIJDLw87M2qwAAYNqNPF0ci8W0u7urw8PDU1/9tlwEAGBWjByyjuMMXPiUyWRGvTQAAFNh5JA963lYnpcFAMy6oUP2wYMHev311/Uv//IvJvoDAMDUGGrh082bN1Wv1yU9f062UqnoL3/5i5GOAQBw2fkeyd6/f1/hcFiNRkOHh4f65JNP9Morr/A8LAAAffgO2VqtpsePH+vGjRuSnj/CUyqVtLu7a6xzAABcZr5Dtt8h7NFodGKdAQBgmvgO2X6bS7DpBAAApxv5EZ6Odrt96vvcqwUAzDrfq4td19Vf//rXE6HaarX06aef9rzneV53FTIAALPKd8iura2dul9xu91WPp8/8R7TyACAWec7ZCORiGzbPnHazmmazabu378/VscAALjsfIdsIpHQ3bt3fV/Ydd2ROgQAwLTwHbKO4wx14VEWPrmuK8dxuo8FWZaldDo9kbpqtdq9T9xoNBSNRrW6ujp0HwEA8Mt3yA46cWcS7V3XVTwe1+bmpizLkiTZtq18Pj8wDP3U1et1eZ7Xc51oNKpGo6FCoTBUPwEA8GvsR3gmxXEcpdPpblBKz0fDtm2PXVcoFE5cJ5FIqFgsTqTvAACcJjAhWyqVTuwe1QnOarU6Vl0ymVQikZhcZwEA8CEQIet5njzPO/URIcuy+j5z67culUqdmBYulUpn3mc+ODjQ/v5+zwsAAL+GOurOlEErkcPhsJrN5kTqKpWK1tfXVa/XVS6Xzxzd5nI5vfvuuwPbAADQTyBGsmfxPG8idalUSo7jKJPJyLbtMx8zymaz2tvb6762t7dH6gcAYDYFYiR7dNHSca1Wa+J1qVRK6+vrJ1YlHxcKhRQKhfpeBwCAQQIxku3sInXaiNXzvL4hOGqd9HwxlOd5rDAGABgTiJC1LEuWZfUdfSaTybHqFhYWTuyv3AnoRqMxarcBABgoECErSSsrKycCr3PPdNACpbPqOqPc4yuQO23i8fhY/QYAoJ/AhKxt26pUKj3vFQqFnkdvPM9TMpnseaTnrLrOFouxWOxEm1gs5mvbRgAARhGIhU/S85FmuVyWbdtaWlqS67paXFzsCcFWq6VardYzPeynznEcFYtFbWxsyLIsua6rWCw29H7MAAAMIzAhK0mxWOzEiPOoSCSi3d3doeskMWIFAJy7wEwXAwAwbQhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQ1646A4c5bquHMdRNBqVJFmWpXQ6PZG6arWqtbU1eZ4n13W1vLzs69oAAIwqMCHruq7i8bg2NzdlWZYkybZt5fN5ra6ujlVXrVZVr9flOI4kyfM8xeNxbWxsqFAoGP25AACzKzDTxY7jKJ1Od4NSkrLZrGzbHruuUCj0BLVlWbJtW8ViUa7rTuxnAADgqMCEbKlU6k73dnSCs1qtjlVXqVROhPXNmzfPvDYAAOMIRMh6nifP8xSJRE58ZlmW6vX6WHWpVOpEEPtxcHCg/f39nhcAAH4F4p7soCnbcDisZrM5Vl25XD7xea1WkyQlEom+18jlcnr33Xf7fg4AwCCBGMmexfO8idc5jiPHcU4dBXdks1nt7e11X9vb2yP1AwAwmwIxkj26aOm4Vqs18brl5WUlEomBq5YlKRQKKRQKDWwDAEA/gRjJhsNhSaePPD3P6xumo9QVi0WFw2Ee3QEAGBeIkLUsS5Zl9R19JpPJidRVKhV5ntcTsKNORQMAcJZAhKwkraysqNFo9LzXWdg0aHGS37p6va5Wq9UzRex5Ho/wAACMCUzI2ratSqXS816hUDgx6kwmkz2P9Pipc11XuVxO4XBYlUql+7Jte+DCJwAAxhGIhU+SFIlEVC6XZdu2lpaW5LquFhcXe/YXbrVaqtVqPdPDfuri8bg8zzsRxpK4NwsAMCYwIStJsVhMsVis7+eRSES7u7tD151WAwCAaYGZLgYAYNoQsgAAGELIAgBgCCELAIAhgVr4BFyEra0t7ezsnNnuyZMn59AbANOEkMVM29ra0ss/+KGePf3qorsCYAoRsphpOzs7evb0Ky2+8XO9uHhtYNunbk17f/jtOfUMwDQgZAFJLy5eU+il7w9s83WTow4BDIeFTwAAGELIAgBgCCELAIAhhCwAAIaw8AkAAsjvc9lXr17V9evXDfcGoyJkASBA/vblrjQ3pzt37vhq/81vfVt//tMTgjagCFkACJDDgy+ldtvXs9tfN7fV/N2vtbOzQ8gGFCELAAHk59ltBB8LnwAAMISQBQDAEEIWAABDCFkAAAwhZAEAMISQBQDAEEIWAABDCFkAAAwhZAEAMISQBQDAEEIWAABDCFkAAAwhZAEAMISQBQDAEEIWAABDCFkAAAwhZAEAMOSFi+7AUa7rynEcRaNRSZJlWUqn0xOtKxaLajQachxnch0HAOAUgQlZ13UVj8e1ubkpy7IkSbZtK5/Pa3V1day6TghLUqlU8hXcAACMKzAh6ziO0ul0NyglKZvNamFhYWDI+qmLRCIqFAqSpFqtZqT/AAAcF5h7sqVSqTvd29EJzmq1OvE6AABMC0TIep4nz/MUiUROfGZZlur1+kTr/Do4OND+/n7PCwAAvwIRsq7r9v0sHA6r2WxOtM6vXC6n+fn57uvatWtjXQ8AMFsCEbJn8TzvXOs6stms9vb2uq/t7e2xrgcAmC2BWPh0dNHSca1Wa+J1foVCIYVCobGvAwCYTYEYyYbDYUmnjzw9z+sbpqPWAQBwHgIRspZlybKsvqPPZDI50ToAAM5DIEJWklZWVtRoNHre6yxsSiQSE68DAMC0wISsbduqVCo97xUKhe4mEtLzKeBkMtnzaI6fuqM6j/0AAGBaIBY+Sc93ZSqXy7JtW0tLS3JdV4uLiz1bILZaLdVqtZ7pYT91nucpl8vJ8zy5rqtSqSRJikajA3eTAgBgHIEJWUmKxWKKxWJ9P49EItrd3R26zrKs7t7F/Ua4AABMWmCmiwEAmDaELAAAhhCyAAAYQsgCAGAIIQsAgCGELAAAhhCyAAAYQsgCAGAIIQsAgCGELAAAhhCyAAAYQsgCAGAIIQsAgCGELAAAhhCyAAAYQsgCAGAIIQsAgCGELAAAhhCyAAAY8sJFdwAwYWtrSzs7O2e2e/LkyTn0BsCsImQxdba2tvTyD36oZ0+/uuiuAJhxhCymzs7Ojp49/UqLb/xcLy5eG9j2qVvT3h9+e049AzBrCFlMrRcXryn00vcHtvm6uX1OvQHM8Xvb4+rVq7p+/brh3uAoQhYALqm/fbkrzc3pzp07vtp/81vf1p//9ISgPUeELABcUocHX0rttq9bI183t9X83a+1s7NDyJ4jQhYALjk/t0ZwMXhOFgAAQwhZAAAMIWQBADCEkAUAwBBCFgAAQwhZAAAMIWQBADAkUM/Juq4rx3EUjUYlSZZlKZ1OT6Ru1GsDADCqwISs67qKx+Pa3NyUZVmSJNu2lc/ntbq6OlbdqNcGAGAcgQlZx3GUTqe7IShJ2WxWCwsLA4PQT92o10awcEYsMD4OEzhfgQnZUqkkx3F63uuEYrVaVSKRGLlu1GsjODgjFhgPhwlcjECErOd58jxPkUjkxGeWZaler58ahH7qbt68OdK1Jeng4EAHBwfdr/f29iRJ+/v7vn+2fj7//HN9/vnnvtp+4xvf0OHh4YW2femll/TSSy/5amvCp59+qmdPv9KVpTf1P+b/58C2//3ZX/T//vfvdfD5Jzr872cD23aOuqMtbae97cFnT6R229e/Q3/b+7/aX3+k//iP/9DLL788sK0UjL9R5/33rJMD7XZ7cMN2AGxsbLQltdfW1k58FolE2qurqyPXjXrtdrvd/tWvftWWxIsXL168eJ362t7eHphvgRjJnsXzPGN1g9pks1n97Gc/6359eHioVqulxcVFzc3N9bTd39/XtWvXtL29rStXrozUX5w/fm+XE7+3y2mafm/tdltffPGFvvvd7w5sF4iQPbog6bhWqzVW3ajXlqRQKKRQKOT7e0rSlStXLv0/PLOI39vlxO/tcpqW39v8/PyZbQKxGUU4HJZ0+qjS87y+weanbtRrAwAwrkCErGVZsiyr78gymUyOXDfqtQEAGFcgQlaSVlZW1Gg0et5zXVeSBj5i46du1GsPIxQK6Ve/+tWJ6WUEG7+3y4nf2+U0i7+3uXb7rPXH58N1XSWTyZ4wtG1b0Wi0u/2h53laXl6W4ziKxWK+6/y0AQBg0gITspJUr9f1/vvva2lpqTvSPLojU2d7xHK53DMCPavObxsAACYpUCELAMA0Ccw9WQAApg0hCwCAIYHYjGJaVatV1et1SVKj0VA0GuU+8CVQrVa1trYmz/Pkuq6Wl5dZIHeJFItFNRqNE4eC4OLM8nnehKwh9Xpdnuf1hGo0GlWj0VChULjAnmGQzn8Ydf5Ae56neDyujY0Nfm8B1vkjLj0/mWtW/oBfBrN+njcLnwzJZDKqVqs9jw1lMhkVi8WzT23AhVleXla5XO55r1gsKpPJqNFonHqaE4IlHo8rkUgwkg2ITCYjy7J6fh+e52lhYWEm/hZyT9aQZDLJObWXUKVSkW3bPe/dvHlT0vNRLoDhlEql7jRxx9HzvKcdIWtIKpU6Mb142uHxCJZUKnXiDwKA0fg583vacU/WsEqlovX1ddXr9RObaCB4jk8VS1KtVpM0uS04gVnR2fjnNOFwWM1m8xx7czEYyRqWSqXkOI4ymYxs2x74Dx2CyXEcOY7D/VhgwkY9K/wyIWTPSSqVUiKRUDwen4l/sKbF8vKyEonETKyCBCZtnPO8pwXTxQPU63XdvXvXd/uHDx92Dy44TTKZVD6fV7FY5I+2QZP6vRWLRYXDYR7dOSeT/vcNF4/zvAnZgWKxmDY2NkaqXVhYUDab7QnTzj9wx4/dw2SN83vrqFQq8jyvJ2Bn5Y/CRZnE7w3BwnneTBcb0fmvtuP38Dr3Y+Px+Hl3CUOo1+tqtVo9/4Hked5MPG4ATNp5nOcdZISsAZ0tw45PZRUKBcViMXajCTDXdZXL5RQOh1WpVLov27ZZ+HRJdB4bQTDYtq1KpdLzXqFQmJnbMOz4ZFCxWNTGxoYsy5LruopEIjwnG3ALCwt9/0Dzr0pweZ6nXC4nz/NULBZlWZZWVlbYLzwgZvk8b0IWAABDmC4GAMAQQhYAAEMIWQAADCFkAQAwhJAFAMAQQhYAAEMIWQAADCFkAQAwhJAFpoht20omk8pkMufy/cbZvrBYLCqZTM7EJvGYXez4BEyRZDKptbW1c/letm3r9u3bYx83d559Bs4bI1lgSnmep0wmo2g0qrm5OeXz+YHt6/W65ubmtLCwoEwmo3q9fmb7WCwmz/Nk23b3+ySTSdm23W2Xz+eVTCY1NzenaDQq27a7+9cCU68NYGokEokT75XL5XYqlWpHIpGBtYVCoR2JRNrpdPrM77OxsdFeXV09US+pvbGxcaL97u5uW9KJmn59BqYFI1lgBmQyGbmuO3B0Gg6HfV+vUCj0ve972sH2nfcWFxd9fw9gGhCywAyIRCJKJBLK5XKnfl6pVJRKpXxfr3N0I4DBCFlgRmQymROHZ3e0Wi3f16lUKlpeXp5Ut4CpRsgCMyKVSsmyLBWLxZ73XdfVzZs3fV/n/fff18rKyqS7B0ylFy66AwDOz8rKigqFgtLpdPe9arXa8/VZPM879b5rh23bJ6aSx3meFrjMCFlghmQyGRWLxZ57qsMseCoWi2dudOE4zqn3a4+PoIFZwHQxMENisZhisZgcx5H0fBSbSCR815fL5aEWSAGzjpAFZkwmk1GpVJJ09tTvUcO0BfAcIQvMmJWVFXmep3w+P1Ro+pkqBtCLkAWmnOu6PdsYWpalVCqlQqEw1FTx2tqar/anLXLqvNdsNn1/P2AasPAJmFKdPYVLpZLC4bASiYQKhYIkKZvNqlqtdttWKhWtra3JdV2VSiVZltWz+f+gzSc8z1Mul+s+g2vbds9933w+3z0AoNMmk8mwmQVmAqfwAFPE1Ik2kzpx5zScwoNpxnQxgDNVq1UjAQtMO0IWwED1en2oe7cA/o6QBTDQoBN3AAxGyAJTJBaLKZlMTjwUTSxS6hzmDkwzFj4BAGAII1kAAAwhZAEAMISQBQDAEEIWAABDCFkAAAwhZAEAMISQBQDAEEIWAABD/j8G1ESCeAyXOAAAAABJRU5ErkJggg==", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject Text(27.219312263257578, 0.5, 'Probability')" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Make integrated MDF plot\n", "import StarFormationHistories: mdf_amr\n", "MDF_x, MDF = mdf_amr(mdf_coeffs, template_logAge, template_MH)\n", "fig, ax1 = plt.subplots()\n", "ax1.bar(MDF_x, MDF, -abs(MDF_x[2] - MDF_x[3]), align=\"edge\", linewidth=1, edgecolor=\"k\")\n", "ax1.set_xlabel(\"[M/H]\")\n", "ax1.set_ylabel(\"Probability\")" ] }, { "cell_type": "markdown", "id": "138cba13-ccce-412f-af32-bcccfb984cf6", "metadata": {}, "source": [ "Overall the resulting fit is very consistent with the true values. We do, however, see that the SFRs at recent times (small log(Age)) are slightly higher than expected. This is in large part due to our grid being equally-spaced in log(Age) with a very fine time spacing ($\\Delta$log(Age)$=0.1$). As such, the most recent time bins contain very little stellar mass. The total stellar mass for all bins with `logAge < 7` is " ] }, { "cell_type": "code", "execution_count": 61, "id": "4a1f482e-764d-44f5-bf30-522ffea5b758", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "10550.929920025494" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Equivalent to sum(mdf_coeffs[template_logAge .<= maximum(unique_template_logAge[1:5])])\n", "# sum(mdf_result.map.μ[1:5] .* template_norm) \n", "sum(mdf_result.map.μ[findall(<(7), unique_logAge)] .* template_norm)" ] }, { "cell_type": "markdown", "id": "3065b8ab-cbe9-47b6-b193-c053f0a12c3a", "metadata": {}, "source": [ "which is of order 0.1% of the stellar mass of the system." ] }, { "cell_type": "code", "execution_count": 62, "id": "c8dceb41-843e-4d7b-b657-965ceebec58d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.10550929920025494" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sum(mdf_result.map.μ[findall(<(7), unique_logAge)] .* template_norm) / stellar_mass * 100" ] }, { "cell_type": "markdown", "id": "193b74e0-94ed-43f4-a364-50cea9b8c769", "metadata": {}, "source": [ "### Normalizing Templates to SFR\n", "\n", "It can sometimes be convenient to normalize the templates to uniform SFR, rather than uniform stellar mass per template. Below we illustrate this gives the same SFH result as above, where we used templates normalized to uniform stellar mass per template." ] }, { "cell_type": "code", "execution_count": 63, "id": "bf55a189-a4a0-4cf3-bbf8-073d2cfb1511", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Compute change in time [yr] between bins of logAge\n", "template_δt = diff(vcat(exp10.(unique_template_logAge), T_max * 1e9)) # exp10(max_logAge)))\n", "sfr_norm = 1e-3 # Star formation rate in solar masses / yr to normalize templates to\n", "# Now normalize the templates:\n", "# SFR = stellar mass / dt; sfr_norm = A * template_norm / dt; where A is a multiplicative constant\n", "# since we originally normalized all the templates to contain stellar mass = `template_norm`\n", "# Solve for A = sfr_norm * dt / template_norm\n", "sfr_templates = deepcopy(templates)\n", "for i in eachindex(sfr_templates)\n", " idx = findfirst(==(template_logAge[i]), unique_template_logAge)\n", " A = sfr_norm * template_δt[idx] / template_norm\n", " sfr_templates[i] .*= A\n", "end " ] }, { "cell_type": "code", "execution_count": 64, "id": "2186d03a-7c4b-4c35-867e-fce81cc94859", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(map = StarFormationHistories.LogTransformMDFResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([7.222472459574194, 2.468830957881689, 1.6466094032999312, 1.192079167196366, 1.0539452244539713, 1.127099765328633, 1.0111838145831034, 1.0178323302411438, 1.3339936890048765, 1.0247774780082528 … 1.0614556179282688, 0.44939662075002235, 0.7772500064301425, 0.774617631886647, 0.7667816322341894, 0.7514894036582785, 0.7126647098470569, 0.10138399732854053, -1.8854585348213766, 0.11351451057638239], [2.8250481623609063, 2.2619095688462068, 1.5435897165692978, 1.14218857311559, 1.0150312596409026, 1.0784499093364994, 0.9779813628585388, 0.9784190675836162, 1.1961202024155706, 0.9597032665257027 … 0.38514708924629004, 0.24079096918352622, 0.1278396776116526, 0.11757235160627454, 0.08189279732559253, 0.05278488582806115, 0.03817665968940224, 0.0005007502358561787, 0.005460049291052889, 0.0024818534810153773], [0.15299594606269112 -0.2063178963463079 … 1.5489043614109188e-5 -0.0001867647501861481; -0.20631789634630773 0.8393976838211493 … -6.4449415922932055e-6 -0.00015645029359665825; … ; 1.5489043614110428e-5 -6.444941592291868e-6 … 2.981213826072716e-5 -2.049108913639282e-5; -0.00018676475018614426 -0.0001564502935966578 … -2.0491089136315077e-5 0.00047802379534603935], * Status: success\n", "\n", " * Candidate solution\n", " Final objective value: 1.490959e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 5.79e-11 ≰ 0.0e+00\n", " |x - x'|/|x'| = 2.53e-11 ≰ 0.0e+00\n", " |f(x) - f(x')| = 4.55e-13 ≰ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 3.05e-16 ≰ 0.0e+00\n", " |g(x)| = 6.03e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 3 (vs limit Inf)\n", " Iterations: 122\n", " f(x) calls: 323\n", " ∇f(x) calls: 323\n", "), mle = StarFormationHistories.LogTransformMDFResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([13.364465558456837, 3.4552713108476626e-53, 9.540288048155317e-65, 6.7256021917873845e-130, 3.072032363021138e-132, 9.396022222634695e-46, 3.243469016347785e-62, 4.012098716579499e-52, 6.644464250823199, 2.242490967704015e-16 … 1.5383780190178578, 0.18267335668391074, 0.8311273670793279, 0.7647568772907527, 0.7748018423558825, 0.7527873905410589, 0.7128503908999005, 0.10133019711012366, -1.8851099765568422, 0.11354675283382741], [2.3107897703715286, 1.0986791195486064e-43, 3.668446507640307e-55, 5.218009960507355e-120, 2.425579273399506e-122, 2.5218325476097392e-36, 1.1926382189066543e-52, 1.2383815748568264e-42, 2.2846836249424176, 2.1366304548057905e-7 … 0.338576276793382, 0.2546819908440283, 0.13156283687737386, 0.11453205081852054, 0.08131693455278355, 0.052660846596762956, 0.04200603566841636, 0.000528750761340089, 0.005844070268220909, 0.002494865413033796], [0.029896316348573638 -1.7078552184837636e7 … -1.5143328440465426e-5 -9.580525865584503e-5; -1.707855218483764e7 1.011061173777915e19 … 32249.07835344585 -1.1005093891764833e6; … ; -1.5143328440362529e-5 32249.07835344584 … 3.41531572999036e-5 -2.6695652086533063e-5; -9.580525865591514e-5 -1.1005093891764835e6 … -2.669565208645928e-5 0.00048277503805102675], * Status: success (objective increased between iterations)\n", "\n", " * Candidate solution\n", " Final objective value: 1.461988e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 6.93e+00 ≰ 0.0e+00\n", " |x - x'|/|x'| = 2.29e-02 ≰ 0.0e+00\n", " |f(x) - f(x')| = 2.27e-13 ≰ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 1.56e-16 ≰ 0.0e+00\n", " |g(x)| = 6.03e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 4 (vs limit Inf)\n", " Iterations: 138\n", " f(x) calls: 402\n", " ∇f(x) calls: 402\n", "))" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# And now fit\n", "mdf_sfr_result = fit_templates_mdf(sfr_templates, data, template_logAge, template_MH, T_max;\n", " x0=vcat(fill(1,length(unique_template_logAge)),\n", " [mdf_α, mdf_β, mdf_σ]))" ] }, { "cell_type": "code", "execution_count": 65, "id": "5fb887f9-48e0-4e66-b057-6c6139bee0ce", "metadata": { "tags": [] }, "outputs": [], "source": [ "# # This is effectively what rand(mdf_sfr_result.map, 10000) is doing.\n", "# # Generate sample from the inverse Hessian matrix\n", "# mdf_sfr_dist = MvNormal(Optim.minimizer(mdf_sfr_result.map.result),\n", "# Hermitian(Optim.trace(mdf_sfr_result.map.result)[end].metadata[\"~inv(H)\"]))\n", "# mdf_sfr_sample = rand(mdf_sfr_dist, 10000)\n", "\n", "# # Transform the variables, noting that the SFR coefficients `mdf_sfr_sample[begin:end-3,:]`, α `mdf_sfr_sample[end-2,:]`,\n", "# # and σ `mdf_sfr_sample[end,:]` are fit with logarithmic transformations so we have to transform them back.\n", "# # β is optimized directly, without a transformation, as it is allowed to be negative.\n", "# @views mdf_sfr_sample[begin:end-2,:] .= exp.(mdf_sfr_sample[begin:end-2,:]) .* sfr_norm\n", "# @views mdf_sfr_sample[end,:] .= exp.(mdf_sfr_sample[end,:]);" ] }, { "cell_type": "code", "execution_count": 66, "id": "17c20d21-c9d7-42ec-82e5-ae1d05d82b94", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "71×10000 Matrix{Float64}:\n", " 0.014119 0.00498275 0.00912795 … 0.0025779 0.0115282\n", " 0.00147263 0.00546521 0.00101365 0.00156416 0.0033645\n", " 0.000838398 0.00301883 0.002098 0.00492418 0.00119213\n", " 0.000326765 0.00221172 0.00210687 0.0101222 0.000841247\n", " 0.00173096 0.00297255 0.000603937 0.00452283 0.000723277\n", " 0.00255772 0.00600708 0.00102689 … 0.00309843 0.000682239\n", " 0.00112329 0.00217053 0.00266275 0.000997668 0.00267296\n", " 0.00214535 0.0033102 0.000447465 0.00176839 0.0012357\n", " 0.000271859 0.000194402 0.000485646 0.00195109 0.000204272\n", " 0.000749874 0.00225216 0.000731541 0.00364299 0.0025928\n", " 0.000937123 0.00105515 0.00108799 … 0.000102818 0.00127776\n", " 0.00153389 0.000424915 0.000361359 0.000153056 0.000704236\n", " 0.000678687 0.000312023 0.000198507 0.000103068 0.000485186\n", " ⋮ ⋱ \n", " 0.000351858 0.00105834 0.000642025 0.000507256 0.000871406\n", " 0.00149486 0.000588927 0.000655072 … 0.00114862 0.00047633\n", " 0.000306447 0.000574588 0.000803473 0.000564577 0.00136934\n", " 0.00147384 0.000854081 0.00104109 0.000688945 0.000881082\n", " 9.41651e-5 0.00104247 0.000207967 0.000746678 0.000235776\n", " 0.00230675 0.000871546 0.00159173 0.0010083 0.00146578\n", " 0.00017393 0.000407772 0.000290916 … 0.000483488 0.000353837\n", " 0.000862812 0.000856684 0.000749756 0.000768668 0.000687389\n", " 0.000803549 0.000729406 0.000810721 0.000707933 0.000902153\n", " 0.000778658 0.000758133 0.00082588 0.000846178 0.000693\n", " 0.000746285 0.000745703 0.000708325 0.000724871 0.000809393\n", " 0.0007027 0.000707212 0.000749937 … 0.000746109 0.000685981" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mdf_sfr_sample = rand(mdf_sfr_result.map, 10000)\n", "@views mdf_sfr_sample[begin:end-3,:] *= sfr_norm # Correct the SFR coefficients for the template normalization" ] }, { "cell_type": "code", "execution_count": 67, "id": "a16529bd-f6ef-456f-93fb-5333a3d530b5", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Now calculate quantiles\n", "mdf_sfr_norm_lower = quantile.(eachrow(@view mdf_sfr_sample[begin:end-3,:]), 0.16)\n", "mdf_sfr_norm_med = median.(eachrow(@view mdf_sfr_sample[begin:end-3,:]))\n", "mdf_sfr_norm_upper = quantile.(eachrow(@view mdf_sfr_sample[begin:end-3,:]), 0.84);" ] }, { "cell_type": "code", "execution_count": 68, "id": "ec8f4fe0-41e6-47a9-9ce8-94add90d5096", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject Text(0.5, 29.371800193718016, 'log(Age [yr])')" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs = plt.subplots(nrows=1,ncols=2,sharex=true,sharey=true,figsize=(14,7))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.1)\n", "\n", "axs[1].bar(unique_template_logAge, mdf_sfr_norm_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", "# axs[1].bar(unique_template_logAge, mdf_sfr_result.map.μ[begin:end-3] .* 1e3 .* sfr_norm; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", "# axs[1].bar(unique_template_logAge, mdf_sfr_result.mle.μ[begin:end-3] .* 1e3 .* sfr_norm; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(mdf_sfr_norm_med .- mdf_sfr_norm_lower) .* 1e3, \n", " (mdf_sfr_norm_upper .- mdf_sfr_norm_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"Result, SFR Normalized\")\n", "axs[1].bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "\n", "axs[1].set_xlabel(\"log(Age [yr])\")\n", "axs[1].set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "axs[1].set_ylim([0.0, axs[1].get_ylim()[2]])\n", "axs[1].legend()\n", "\n", "axs[2].bar(unique_template_logAge, mdf_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(mdf_sfr_med .- mdf_sfr_lower) .* 1e3, \n", " (mdf_sfr_upper .- mdf_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"Result, Stellar Mass Normalized\")\n", "axs[2].bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "axs[2].legend()\n", "axs[2].set_xlabel(\"log(Age [yr])\")" ] }, { "cell_type": "markdown", "id": "1b70bc27-3f04-4f40-af32-7233c9be6625", "metadata": {}, "source": [ "## SFH Fitting: Unconstrained Fitting\n", "\n", "We will now explore the methods offered to fit SFHs without constraints on the AMR. These methods are most useful when dealing with simpler stellar populations (e.g., globular clusters / ultra-faint dwarf galaxies)." ] }, { "cell_type": "markdown", "id": "2bd1845d-9992-4826-a98f-ce4d16ee58be", "metadata": {}, "source": [ "### Simple Optimization" ] }, { "cell_type": "markdown", "id": "354c6e34-3b6a-4749-b6dc-619f4d0f677c", "metadata": {}, "source": [ "Again, the best way to fit this SFH would be to use `fit_templates_mdf` as above, because it uses the same hierarchical model as we used to generate the SFH (fitting stellar masses per bin in logage, and a mean metallicity relation with Gaussian scatter). For example purposes we will show how to use some of the simpler fitting methods that fit per-template stellar masses here. These methods are generally most useful when you have a smaller set of templates that you want to use to fit the SFH. For this purpose, we will create a smaller grid of templates centered around the real age-metallicity relation; we will accept any isochrone within ± 0.2 dex of this metallicity evolution guess." ] }, { "cell_type": "code", "execution_count": 69, "id": "16f9e079-2c7d-4a09-9188-9d0882359f21", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# new_α, new_β, new_σ = 0.15, -2.25, 0.2 # -0.15, -0.2, 0.2\n", "new_α, new_β, new_σ = α, β, σ\n", "met_func(logAge) = (T_max - exp10(logAge)/1e9) * new_α + new_β\n", "met_func_true(logAge) = (T_max - exp10(logAge)/1e9) * α + β\n", "laxplot = 6.6:0.01:10.2\n", "fig,ax1=plt.subplots()\n", "ax1.plot(exp10.(laxplot)./1e9, met_func.(laxplot),label=\"Guess\",zorder=0)\n", "ax1.plot(exp10.(laxplot)./1e9, met_func_true.(laxplot),label=\"Input\",ls=\"--\",zorder=1)\n", "ax1.set_xlim([13.0,-0.1])\n", "ax1.set_xlabel(\"Lookback Time [Gyr]\")\n", "ax1.set_ylabel(L\"$\\langle$[M/H]$\\rangle$\")\n", "ax1.legend(loc=\"upper left\")" ] }, { "cell_type": "markdown", "id": "7eebd0bc-793b-46f4-b4a3-df03af309e4f", "metadata": {}, "source": [ "Now create the limited template set." ] }, { "cell_type": "code", "execution_count": 70, "id": "f1ff4a94-e9fd-4656-aa31-3ea8ab1f2841", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Single-threaded with push!, easier with this example\n", "free_templates = Vector{Matrix{Float64}}(undef,0)\n", "free_template_logAge = Vector{Float64}(undef,0)\n", "free_template_MH = Vector{Float64}(undef,0)\n", "for logage in unique_logAge\n", " mean_met = met_func(logage)\n", " for mh in unique_MH\n", " # If the current mh is more than `new_σ` dex away from mean, skip template\n", " abs(mh - mean_met) > new_σ && continue\n", " local good = findall( (table.MH .== mh) .& (table.logAge .== logage) )\n", " # Chop off the last star because its the 30 mag weird thing that parsec does.\n", " local m_ini = table.Mini[good][begin:end-1]\n", " local iso_mags = [table.F090W[good][begin:end-1], table.F150W[good][begin:end-1]]\n", " push!(free_templates, partial_cmd_smooth( m_ini, iso_mags, [F090W_error, F150W_error], 2, [1,2], imf, [F090W_complete, F150W_complete]; \n", " dmod=distmod, normalize_value=template_norm, edges=edges).weights )\n", " push!(free_template_logAge, logage)\n", " push!(free_template_MH, mh)\n", " end\n", "end" ] }, { "cell_type": "code", "execution_count": 71, "id": "49588f69-bfe4-46da-a16c-3498f480791d", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "142" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# `templates` has 1846 entries, free_templates has ~10% of that.\n", "length(free_templates)" ] }, { "cell_type": "markdown", "id": "5c2b55bd-9db8-40dd-a306-2a8b2c0ddefa", "metadata": {}, "source": [ "Let's start off by just obtaining the maximum likelihood estimate (MLE) via `fit_templates_lbfgsb`. We'll construct the initial guess vector `x0` with `construct_x0`." ] }, { "cell_type": "code", "execution_count": 72, "id": "d20b6999-e88f-464e-91f9-360efad5c064", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "RUNNING THE L-BFGS-B CODE\n", "\n", " * * *\n", "\n", "Machine precision = 2.220D-16\n", " N = 142 M = 10\n", "\n", " * * *\n", "\n", "Tit = total number of iterations\n", "Tnf = total number of function evaluations\n", "Tnint = total number of segments explored during Cauchy searches\n", "Skip = number of BFGS updates skipped\n", "Nact = number of active bounds at final generalized Cauchy point\n", "Projg = norm of the final projected gradient\n", "F = final function value\n", "\n", " * * *\n", "\n", " N Tit Tnf Tnint Skip Nact Projg F\n", " 142 4318 4425 4827 0 43 9.301D-06 1.738D+03\n", "\n", "CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL \n", "\n", " Total User time 1.728E+00 seconds.\n", "\n" ] }, { "data": { "text/plain": [ "(1737.5617669589449, [0.0, 6.309221240969905, 0.3774519040929603, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 392.6911829473131, 1172.9042840660654, 139.87837936686887, 648.3252367693378, 300.29780211058176, 372.29568656728304, 514.5829920180571, 465.4210516330318, 325.8750298842604])" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: fit_templates_lbfgsb, construct_x0\n", "lbfgsb_result = fit_templates_lbfgsb(free_templates, data; x0=construct_x0(free_template_logAge, T_max; normalize_value=template_norm))" ] }, { "cell_type": "code", "execution_count": 73, "id": "8e50d8b0-aafd-404e-adbe-0959e068cd64", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "([6.6, 6.65, 6.7, 6.75, 6.8, 6.85, 6.9, 6.95, 7.0, 7.05 … 9.65001, 9.70001, 9.75001, 9.80001, 9.85001, 9.90001, 9.95001, 10.00001, 10.05001, 10.10001], [1.0000000000000002, 0.9993739680443234, 0.999336515410366, 0.999336515410366, 0.999336515410366, 0.999336515410366, 0.9990821198597614, 0.9990821198597614, 0.9990821198597614, 0.9986779938595978 … 0.6456013189136356, 0.6456013189136356, 0.6161223056788163, 0.5212635956705851, 0.5017426707122999, 0.4298692956046791, 0.39090454546385706, 0.2606437942905101, 0.16651675173671107, 0.07851628822506478], [0.012988237983546648, 0.0006925260292140784, 0.0, 0.0, 0.0, 0.0029679955575222135, 0.0, 0.0, 0.003337878528053956, 0.00013656437982336654 … 0.0, 0.00048579906817496435, 0.0013932240083237553, 0.00025553131347383313, 0.000838516812506095, 0.00040514980204774565, 0.00120713909004342, 0.0007774243672446133, 0.000647781729964104, 0.0007125866141560192], [-0.5000166309399301, -0.60001623283198, -0.60001623283198, -0.60001623283198, -0.60001623283198, -0.5000166309399301, -0.5000166309399301, -0.5000166309399301, -0.5000166309399301, -0.5000166309399301 … -0.8000106239270766, -1.0389870945459982, -1.042833704046062, -1.2000131046997948, -1.291372201894493, -1.2000131046997948, -1.389359303307148, -1.5683548786699604, -1.6419879799478247, -1.7588319600316495])" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Calculate the cumulative SFH, SFRs, <[M/H]>(logAge) from the above result\n", "free_coeffs = lbfgsb_result[2] .* template_norm\n", "unique_free_template_logAge, free_cum_sfr_arr, free_sfr_arr, free_mean_mh_arr = calculate_cum_sfr(free_coeffs, free_template_logAge, free_template_MH, T_max)" ] }, { "cell_type": "code", "execution_count": 74, "id": "504fb970-2d7a-4d8e-a773-e1e83521b876", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject Text(457.3650849792141, 0.5, '$\\\\langle$[M/H]$\\\\rangle$')" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=false,figsize=(10,5))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.35)\n", "\n", "axs[1].plot( exp10.(unique_free_template_logAge)./1e9, free_cum_sfr_arr, label=\"LBFGSB Fit\" )\n", "axs[1].plot( exp10.(unique_template_logAge)./1e9, cum_sfr_arr, label=\"Input SFH\", ls=\"--\" )\n", "\n", "axs[1].set_xlim([13.0,-0.1])\n", "axs[1].set_ylim([0.0,1.1])\n", "axs[1].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[1].set_ylabel(\"Cumulative SF\")\n", "axs[1].legend()\n", "\n", "axs[2].plot( exp10.(unique_free_template_logAge)./1e9, free_mean_mh_arr, label=\"LBFGSB Fit\" )\n", "axs[2].plot( exp10.(unique_template_logAge)./1e9, mean_mh_arr, label=\"Input SFH\", ls=\"--\" )\n", "axs[2].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[2].set_ylabel(L\"$\\langle$[M/H]$\\rangle$\")" ] }, { "cell_type": "markdown", "id": "caab9ea0-6093-41c0-9739-35664c2592e9", "metadata": {}, "source": [ "We can also use `fit_templates`, which uses BFGS to build a dense estimate of the inverse Hessian. This function is slower than `fit_templates_lbfgsb` above, but allows for estimation of random uncertainties." ] }, { "cell_type": "code", "execution_count": 75, "id": "f139e522-565a-4055-a316-346b75da2e9d", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(map = StarFormationHistories.LogTransformFTResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([0.6711597289310539, 2.7869798992616235, 0.6617579206189061, 0.8963766472321459, 0.49741326178208983, 0.6892953484325856, 0.4681920518786531, 0.5467529941647936, 0.5016994229523505, 0.4978142925508428 … 139.93393540620644, 203.8815721476802, 1077.116942224919, 239.99636631493289, 632.9659868554295, 333.89285764119256, 374.43089138085855, 516.1480680566715, 465.7771354059109, 328.51005657615923], [0.6398255866894301, 1.1277520383716344, 0.6306876934351933, 0.838298779219725, 0.48701329897373424, 0.6635250814782753, 0.4600502491491314, 0.5368197508581075, 0.4925265992378701, 0.48971778657192533 … 108.15321604843322, 126.88620363217886, 138.31621718821037, 142.68448609575, 69.45807213962969, 90.02224511542695, 37.90008092617126, 42.65475340429022, 39.00501498012438, 36.80885377132398], [0.9088065055460887 -0.11568958147759868 … 0.00028763446350277554 -0.0008085589057496431; -0.11568958147760107 0.1637418031594777 … -0.00046785775607621326 -0.0006903196421389435; … ; 0.0002876344635257862 -0.00046785775606924304 … 0.007012688802010941 -0.003992840437537446; -0.0008085589057456627 -0.0006903196421354701 … -0.003992840437114647 0.012554726302817983], * Status: success\n", "\n", " * Candidate solution\n", " Final objective value: 1.424759e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 6.17e-10 ≰ 0.0e+00\n", " |x - x'|/|x'| = 8.83e-11 ≰ 0.0e+00\n", " |f(x) - f(x')| = 0.00e+00 ≤ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 0.00e+00 ≤ 0.0e+00\n", " |g(x)| = 7.76e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 0 (vs limit Inf)\n", " Iterations: 377\n", " f(x) calls: 1093\n", " ∇f(x) calls: 1093\n", "), mle = StarFormationHistories.LogTransformFTResult{Vector{Float64}, Vector{Float64}, Matrix{Float64}, Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}, Vector{Float64}, Float64, Float64, Vector{Optim.OptimizationState{Float64, Optim.BFGS{LineSearches.InitialStatic{Float64}, LineSearches.HagerZhang{Float64, Base.RefValue{Bool}}, Nothing, Nothing, Optim.Flat}}}, Bool, @NamedTuple{f_limit_reached::Bool, g_limit_reached::Bool, h_limit_reached::Bool, time_limit::Bool, callback::Bool, f_increased::Bool}}}([2.2689843676955086e-43, 6.3144518028626475, 0.37484712491649863, 1.917031400992052e-16, 1.7229419394882513e-46, 2.419433153293893e-9, 3.260794512432584e-54, 6.441893295746726e-36, 2.7780620869584285e-38, 7.09544917078298e-51 … 1.7755342272965846e-11, 393.50852661045354, 1173.576491563623, 138.4681278720116, 648.3035374785914, 300.95383010320063, 372.2570399654038, 514.6704462783881, 465.32304717158456, 325.8090482151131], [2.01014420467909e-37, 1.6480564060429816, 2.357563990956066, 6.244273141105193e-11, 1.628056956909957e-40, 0.0004170367984826, 3.607313296680295e-48, 4.6756867028343156e-30, 2.1501983331866163e-32, 7.361900346321837e-45 … 4.845169729781572e-6, 261.5289522140592, 164.35299943798051, 230.5386769935891, 72.44450426176901, 94.61175663275384, 40.87886225135171, 45.27283955194375, 38.93380670968161, 36.44965668179279], [7.848585988452405e11 587.1697507411828 … 44.6542929316753 47.677106455954416; 587.1697507410009 0.06811971746062678 … -0.00016488119018180365 -0.00043672157797538434; … ; 44.65429293172184 -0.00016488119018174884 … 0.007000750661122181 -0.0038622766169505995; 47.6771064559804 -0.0004367215779751659 … -0.0038622766169505653 0.012515857269240947], * Status: success (objective increased between iterations)\n", "\n", " * Candidate solution\n", " Final objective value: 1.737581e+03\n", "\n", " * Found with\n", " Algorithm: BFGS\n", "\n", " * Convergence measures\n", " |x - x'| = 2.75e-02 ≰ 0.0e+00\n", " |x - x'|/|x'| = 1.83e-04 ≰ 0.0e+00\n", " |f(x) - f(x')| = 4.55e-13 ≰ 0.0e+00\n", " |f(x) - f(x')|/|f(x')| = 2.62e-16 ≰ 0.0e+00\n", " |g(x)| = 3.60e-09 ≤ 1.0e-08\n", "\n", " * Work counters\n", " Seconds run: 0 (vs limit Inf)\n", " Iterations: 219\n", " f(x) calls: 683\n", " ∇f(x) calls: 683\n", "))" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import StarFormationHistories: fit_templates\n", "bfgs_result = fit_templates(free_templates, data; x0=construct_x0(free_template_logAge, T_max; normalize_value=template_norm))" ] }, { "cell_type": "markdown", "id": "e089877a-2d13-4d0f-a278-63a9ea8c8e89", "metadata": {}, "source": [ "`bfgs_result.mle` contains information for the maximum likelihood estimate; this is most similar to what is returned by `fit_templates_lbfgsb` but not exactly equal due to differences in the internal convergence criteria of the fitting methods." ] }, { "cell_type": "code", "execution_count": 76, "id": "7c03b156-c251-4917-b0d6-37a80f035908", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "142-element Vector{Float64}:\n", " 2.2689843676955086e-43\n", " 0.00523056189274218\n", " -0.00260477917646168\n", " 1.917031400992052e-16\n", " 1.7229419394882513e-46\n", " 2.419433153293893e-9\n", " 3.260794512432584e-54\n", " 6.441893295746726e-36\n", " 2.7780620869584285e-38\n", " 7.09544917078298e-51\n", " 5.395976462961892e-41\n", " 0.0012950217413494336\n", " 1.1177945431752153e-63\n", " ⋮\n", " 0.30551439383293655\n", " -1.2308142769772132\n", " 1.7755342272965846e-11\n", " 0.8173436631404343\n", " 0.6722074975575651\n", " -1.4102514948572775\n", " -0.021699290746482802\n", " 0.6560279926188741\n", " -0.038646601879236187\n", " 0.08745426033101467\n", " -0.09800446144726038\n", " -0.06598166914733383" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bfgs_result.mle.μ .- lbfgsb_result[2]" ] }, { "cell_type": "markdown", "id": "0c9c68c1-e6da-4a2c-a0a4-288b9f05803b", "metadata": {}, "source": [ "Of additional note are the uncertainty estimates, available as `bfgs_result.map.σ` and `bfgs_result.mle.σ`. These are essentially standard errors derived from the diagonal of the covariance matrix of the fitting parameters. The `bfgs_result.map` result contains the maximum a posteriori result and is often very comparable to the mode of posterior samples obtained via Hamiltonian Monte Carlo (provided by `hmc_sample`) or MCMC (provided by `mcmc_sample`). We don't generally recommend the use of `bfgs_result.mle.σ`, but provide it for completeness." ] }, { "cell_type": "code", "execution_count": 77, "id": "7e569063-49cc-49b3-9d1e-27f8ab11012e", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "142-element Vector{Float64}:\n", " 0.6711597289310539\n", " 2.7869798992616235\n", " 0.6617579206189061\n", " 0.8963766472321459\n", " 0.49741326178208983\n", " 0.6892953484325856\n", " 0.4681920518786531\n", " 0.5467529941647936\n", " 0.5016994229523505\n", " 0.4978142925508428\n", " 0.4975510458750742\n", " 0.637892213308068\n", " 0.45948306349106915\n", " ⋮\n", " 462.6826840944507\n", " 172.96276963209834\n", " 139.93393540620644\n", " 203.8815721476802\n", " 1077.116942224919\n", " 239.99636631493289\n", " 632.9659868554295\n", " 333.89285764119256\n", " 374.43089138085855\n", " 516.1480680566715\n", " 465.7771354059109\n", " 328.51005657615923" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bfgs_result.map.μ" ] }, { "cell_type": "code", "execution_count": 78, "id": "377f6315-c7e8-4319-bccd-7a44dda6a3d4", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "142-element Vector{Float64}:\n", " 0.6398255866894301\n", " 1.1277520383716344\n", " 0.6306876934351933\n", " 0.838298779219725\n", " 0.48701329897373424\n", " 0.6635250814782753\n", " 0.4600502491491314\n", " 0.5368197508581075\n", " 0.4925265992378701\n", " 0.48971778657192533\n", " 0.48985142249933283\n", " 0.6216224821768226\n", " 0.45352326044880564\n", " ⋮\n", " 178.2950428855977\n", " 129.1008281466361\n", " 108.15321604843322\n", " 126.88620363217886\n", " 138.31621718821037\n", " 142.68448609575\n", " 69.45807213962969\n", " 90.02224511542695\n", " 37.90008092617126\n", " 42.65475340429022\n", " 39.00501498012438\n", " 36.80885377132398" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bfgs_result.map.σ" ] }, { "cell_type": "markdown", "id": "0a3eebe7-0b94-4ed1-9719-34a2d5c8d810", "metadata": {}, "source": [ "### Sampling from Inverse Hessian\n", "\n", "We'll now draw samples from the posterior using the same approximation techinque as we did in the previous section." ] }, { "cell_type": "code", "execution_count": 79, "id": "265e8cd2-1d28-4fe5-9242-1a62a541fe50", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "71-element Vector{Float64}:\n", " 0.011087344594003522\n", " 0.006959549089189999\n", " 0.004865645659841066\n", " 0.003781668854806038\n", " 0.0032689437725653557\n", " 0.003349323723534193\n", " 0.00249648632362979\n", " 0.0025462691387392873\n", " 0.0027453128516842277\n", " 0.002229191878752969\n", " 0.0017757246765453716\n", " 0.0018005384189252965\n", " 0.0017210896124459144\n", " ⋮\n", " 0.0011731718093661045\n", " 0.001274485831937575\n", " 0.0004984981287895128\n", " 0.0008517482604043832\n", " 0.0014894730848585404\n", " 0.0010665858680499842\n", " 0.0010824492341152312\n", " 0.000636179377288191\n", " 0.0013852804917540817\n", " 0.0008620774386505356\n", " 0.0006907097150881543\n", " 0.0007549629107942181" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hessian_sample = rand(bfgs_result.map, 10000) .* template_norm\n", "# The above is effectively doing\n", "# hessian_dist = Distributions.MvNormal(Optim.minimizer(bfgs_result.map.result),\n", "# LinearAlgebra.Hermitian(bfgs_result.map.invH))\n", "# hessian_sample = exp.(rand(hessian_dist, 10000)) .* template_norm\n", "\n", "# Calculate the cumulative SFH for each sample\n", "# and find the 1-σ quantile range for both the cumulative SFH and the SFRs\n", "hessian_cum_sfr = Vector{Vector{Float64}}(undef,0)\n", "hessian_sfr = Vector{Vector{Float64}}(undef,0)\n", "for x in eachcol(hessian_sample)\n", " _, hessian_1, hessian_2, hessian_mh = calculate_cum_sfr(x, free_template_logAge, free_template_MH, T_max)\n", " push!(hessian_cum_sfr, hessian_1)\n", " push!(hessian_sfr, hessian_2)\n", "end\n", "hessian_cum_sfr = reduce(hcat, hessian_cum_sfr) \n", "hessian_sfr = reduce(hcat, hessian_sfr) \n", "# Now calculate quantiles\n", "hessian_cum_lower = quantile.(eachrow(hessian_cum_sfr), 0.16)\n", "hessian_cum_med = median.(eachrow(hessian_cum_sfr))\n", "hessian_cum_upper = quantile.(eachrow(hessian_cum_sfr), 0.84)\n", "hessian_sfr_lower = quantile.(eachrow(hessian_sfr), 0.16)\n", "hessian_sfr_med = median.(eachrow(hessian_sfr))\n", "hessian_sfr_upper = quantile.(eachrow(hessian_sfr), 0.84)" ] }, { "cell_type": "code", "execution_count": 80, "id": "95e1b669-12d9-449d-85fb-eae6e26734fd", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Now plot cumulative SFH and MH evolution\n", "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=false,figsize=(10,6))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.35)\n", "\n", "# axs[1].plot( exp10.(unique_free_template_logAge)./1e9, cum_sfr_arr, label=\"Result\" )\n", "axs[1].plot( exp10.(unique_free_template_logAge)./1e9, hessian_cum_med, label=\"Result\" )\n", "axs[1].plot( exp10.(unique_template_logAge)./1e9, cum_sfr_arr, label=\"Input SFH\", ls=\"--\" )\n", "axs[1].fill_between( exp10.(unique_free_template_logAge)./1e9, hessian_cum_lower, hessian_cum_upper, alpha=0.3, fc=\"k\")\n", "axs[1].set_xlim([13.0,-0.1])\n", "axs[1].set_ylim([0.0,1.1])\n", "axs[1].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[1].set_ylabel(\"Cumulative SF\")\n", "axs[1].legend()\n", "\n", "axs[2].plot( exp10.(unique_free_template_logAge)./1e9, free_mean_mh_arr, label=\"Result\" )\n", "axs[2].plot( exp10.(unique_template_logAge)./1e9, mean_mh_arr, label=\"Input\", ls=\"--\" )\n", "# axs[2].plot( exp10.(unique_template_logAge)./1e9, met_func.(unique_template_logAge), c=\"k\", label=\"Guess\",ls=\"--\")\n", "axs[2].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[2].set_ylabel(L\"$\\langle$[M/H]$\\rangle$\")\n", "axs[2].legend()" ] }, { "cell_type": "markdown", "id": "41c2a74d-b711-4129-94fd-37a02ace5d12", "metadata": {}, "source": [ "We can alternatively use the `Measurements.jl` package to estimate the uncertainties on the SFRs assuming that the `bfgs_result.map.σ` are Gaussian and *uncorrelated*. In general we expect some correlation in the star formation rates between age bins (as shown above in the constrained metallicity case), but this approach can be useful for quick diagnostics. " ] }, { "cell_type": "code", "execution_count": 81, "id": "304717d6-cf60-4c67-add0-0a43c9c4f155", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "71-element Vector{Float64}:\n", " 2.6692199225573705\n", " 1.9247389480268136\n", " 1.3458984684494002\n", " 1.030343473158807\n", " 0.9021542800518171\n", " 0.9161985142653941\n", " 0.6901358672296908\n", " 0.688549708655883\n", " 0.7590019432769353\n", " 0.6048350997836405\n", " 0.48129006079513115\n", " 0.4903793281266798\n", " 0.4778889098375988\n", " ⋮\n", " 0.22101589024353976\n", " 0.1761334479232895\n", " 0.13774915711373256\n", " 0.23229273530879294\n", " 0.3018139978468668\n", " 0.2997877393446496\n", " 0.254823171209302\n", " 0.17201456290374892\n", " 0.18272979172660722\n", " 0.09318314157157727\n", " 0.041676983975795695\n", " 0.04829636501758965" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import Measurements: uncertainty, ±\n", "hessian_sfrerr = uncertainty.(calculate_cum_sfr(bfgs_result.map.μ .± bfgs_result.map.σ,\n", " free_template_logAge, free_template_MH, T_max; normalize_value=template_norm)[3]) .* 1e3" ] }, { "cell_type": "code", "execution_count": 82, "id": "1988d302-c6ba-476f-990e-d468a04c72ad", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,ax1 = plt.subplots(figsize=(7,7))\n", "# ax1.bar(unique_free_template_logAge[begin:end-1], free_sfr_arr[begin:end-1] .* 1e3; width=diff(unique_free_template_logAge), align=\"edge\", yerr = hessian_sfrerr[begin:end-1], capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"LBFGS Fit\")\n", "ax1.bar(unique_free_template_logAge, hessian_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", yerr = hessian_sfrerr, capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"BFGS Fit\")\n", "ax1.bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "ax1.set_xlabel(\"log(Age [yr])\")\n", "ax1.set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "ax1.set_ylim([0.0, ax1.get_ylim()[2]])\n", "ax1.legend()" ] }, { "cell_type": "markdown", "id": "523954ac-a54d-4c7b-98b3-4a91f0e87b67", "metadata": { "tags": [] }, "source": [ "Overall the performance here is not bad, but inferior to the constrained AMR fit we performed previously.\n", "\n", "If we make the same plot with the `hessian_sfr_lower` and `hessian_sfr_upper` vectors, which utilize the samples from the full variance-covariance matrix, we see that the uncertainties look very similar across most of the plot, but are not identical due to the inclusion of covariance between parameters." ] }, { "cell_type": "code", "execution_count": 83, "id": "d0646193-5b0f-462e-83a0-24b3b45d3563", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,ax1 = plt.subplots(figsize=(7,7))\n", "ax1.bar(unique_free_template_logAge, hessian_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(hessian_sfr_med .- hessian_sfr_lower) .* 1e3, \n", " (hessian_sfr_upper .- hessian_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"BFGS Fit\")\n", "ax1.bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFH\", alpha=0.5)\n", "ax1.set_xlabel(\"log(Age [yr])\")\n", "ax1.set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "ax1.set_ylim([0.0, ax1.get_ylim()[2]])\n", "ax1.legend()" ] }, { "cell_type": "markdown", "id": "8d313856-e36f-40bc-a19e-7085d7f1fa39", "metadata": {}, "source": [ "### Sampling via MCMC\n", "The unconstrained fitting methods are not optimal for MCMC. Since so many of the fitting coefficients are 0, our transition acceptance probabilities are extremely low, giving us fairly poor convergence unless we run very long chains." ] }, { "cell_type": "code", "execution_count": 84, "id": "b9e0d11a-4229-4140-af95-cc052c38afbe", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[33m\u001b[1m┌ \u001b[22m\u001b[39m\u001b[33m\u001b[1mWarning: \u001b[22m\u001b[39mProgressMeter by default refresh meters with additional information in IJulia via `IJulia.clear_output`, which clears all outputs in the cell. \n", "\u001b[33m\u001b[1m│ \u001b[22m\u001b[39m - To prevent this behaviour, do `ProgressMeter.ijulia_behavior(:append)`. \n", "\u001b[33m\u001b[1m│ \u001b[22m\u001b[39m - To disable this warning message, do `ProgressMeter.ijulia_behavior(:clear)`.\n", "\u001b[33m\u001b[1m└ \u001b[22m\u001b[39m\u001b[90m@ ProgressMeter ~/.julia/packages/ProgressMeter/dMfiC/src/ProgressMeter.jl:594\u001b[39m\n", "\u001b[32memcee, niter=2000000, nwalkers=1000: 100%|█████████████████████████| Time: 0:00:32\u001b[39m\n", "\u001b[34m accept_ratio_mean: 0.00904\u001b[39m\n", "\u001b[34m accept_ratio_std: 0.00468\u001b[39m\n", "\u001b[34m accept_ratio_outliers: 44\u001b[39m\n", "\u001b[34m burnin_phase: false\u001b[39m\n" ] } ], "source": [ "import StarFormationHistories: mcmc_sample\n", "import Distributions: MvNormal\n", "import LinearAlgebra: I\n", "\n", "nwalkers = 1000\n", "nsteps = 2000\n", "burn_idx = 200\n", "# Walker initial positions sampled from a multivariate normal distribution with means equal to the BFGS MLE\n", "# and identity covariance matrix. The `max` call makes sure none of the cofficients have initial conditions less than 0. \n", "mcmc_x0 = [max.(0.0, rand(MvNormal(bfgs_result.mle.μ, I))) for i in 1:nwalkers]\n", "mcmc_result = mcmc_sample(free_templates, data, mcmc_x0, nwalkers, nsteps; nthin=5); # nthin=5 to only save every 5 steps" ] }, { "cell_type": "markdown", "id": "02dbc5e5-4e24-4ca1-9449-29f167f39891", "metadata": {}, "source": [ "Note the very low transition acceptance ratio of <1%. If we plot the trace of the chains we can see that they have not reached their stationary distribution even after 2000 steps. MCMC can work well when considering fewer templates, or when fewer of the fitting coefficients are zero. However, this application is better suited to Hamiltonian Monte Carlo. " ] }, { "cell_type": "code", "execution_count": 85, "id": "9b879b91-8afd-4635-b318-72d9622ae690", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import StatsBase: fit, Histogram, normalize\n", "\n", "fig, (ax0, ax1) = plt.subplots(nrows=1,ncols=2,sharex=false,sharey=false,figsize=(10,6))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.2)\n", "\n", "ax0.axvline(burn_idx)\n", "for i in 1:size(mcmc_result,3)\n", " ax0.plot(first(axes(mcmc_result)), mcmc_result[:,end,i], alpha=0.1, rasterized=true) \n", "end\n", "\n", "ax1_hist = normalize(fit(Histogram, vec(mcmc_result[burn_idx:end,end,:]); nbins=100, closed=:left); mode=:probability) #:pdf, :density, :probability, :none\n", "ax1.bar(first(ax1_hist.edges)[2:end], ax1_hist.weights, width=step(first(ax1_hist.edges)), ec=\"k\"); # fc=\"k\"" ] }, { "cell_type": "markdown", "id": "a431f369-523a-40dd-af11-b09748cd581c", "metadata": {}, "source": [ "### Sampling via Hamiltonian Monte Carlo\n", "\n", "Let us now compare to `hmc_sample`, which utilizes the No-U-Turn sampler variant of Hamiltonian Monte Carlo implemented in `DynamicHMC.jl` to sample from the posterior. This is a more rigorous way to obtain posterior samples than using the approximation of `fit_templates` and can be more efficient than `sample_mcmc` for high-dimensional problems or when many of the coefficients are 0. However, we will show that the approximation of `fit_templates` still compares favorably with this more accurate method." ] }, { "cell_type": "code", "execution_count": 86, "id": "782f432f-a2be-4af4-b7d6-090494c3cd98", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "\u001b[32mWarmup: 100%|███████████████████████████████████████████| Time: 0:00:36\u001b[39m\n", "\u001b[32mWarmup: 100%|███████████████████████████████████████████| Time: 0:00:13\u001b[39m\n", "\u001b[32mWarmup: 100%|███████████████████████████████████████████| Time: 0:00:18\u001b[39m\n", "\u001b[32mWarmup: 100%|███████████████████████████████████████████| Time: 0:00:02\u001b[39m\n", "\u001b[32mMCMC: 100%|█████████████████████████████████████████████| Time: 0:00:47\u001b[39m\n" ] } ], "source": [ "import DynamicHMC\n", "import StarFormationHistories: hmc_sample\n", "mc_result = hmc_sample(free_templates, data, 1000; reporter=DynamicHMC.ProgressMeterReport());" ] }, { "cell_type": "markdown", "id": "eae06b46-3b74-4ce1-b8ba-aa453b1ec658", "metadata": {}, "source": [ "We can check the summary statistics to ensure the samples have a high acceptance rate and are converging properly (turning % should be ~100%)." ] }, { "cell_type": "code", "execution_count": 87, "id": "5667c03b-f0d0-4671-b991-b2cf60470b65", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Hamiltonian Monte Carlo sample of length 1000\n", " acceptance rate mean: 0.92, 5/25/50/75/95%: 0.73 0.88 0.95 0.98 1.0\n", " termination: divergence => 0%, max_depth => 0%, turning => 100%\n", " depth: 0 => 0%, 1 => 0%, 2 => 0%, 3 => 0%, 4 => 0%, 5 => 0%, 6 => 0%, 7 => 100%" ] }, "execution_count": 87, "metadata": {}, "output_type": "execute_result" } ], "source": [ "DynamicHMC.Diagnostics.summarize_tree_statistics(mc_result.tree_statistics)" ] }, { "cell_type": "markdown", "id": "448b93ae-c2a4-46f7-b221-e3e3f70c75ae", "metadata": {}, "source": [ "The parameters optimized by `full_templates` and `hmc_sample` are actually the logarithms of the coefficients, not the coefficients themselves, so we need to transform the samples here." ] }, { "cell_type": "code", "execution_count": 88, "id": "3b4a6890-33f5-4bfa-9603-8e3147bf4f19", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "142×1000 Matrix{Float64}:\n", " 96.3725 421.121 … 73.2206 63.7291\n", " 2239.11 4076.72 1295.11 1880.44\n", " 66.0671 893.285 205.897 2233.54\n", " 2667.05 69.2351 2283.2 682.311\n", " 409.332 139.381 296.755 745.094\n", " 718.071 62.1846 … 1288.15 328.395\n", " 31.3383 1314.45 382.899 451.583\n", " 979.63 29.2092 755.307 217.589\n", " 188.283 376.428 814.598 172.491\n", " 126.696 1122.53 606.123 133.953\n", " 105.018 1196.48 … 174.893 994.785\n", " 1340.08 128.147 344.691 686.584\n", " 89.1731 823.166 201.944 812.642\n", " ⋮ ⋱ \n", " 3.88147e5 2.82917e5 … 4.06886e5 2.71327e5\n", " 1.94571e5 1.63269e5 8782.75 2.54566e5\n", " 1.65551e5 1.15106e5 1.58252e5 3.27765e5\n", " 3.00481e5 93507.6 3.19237e5 2.75725e5\n", " 1.12478e6 1.03898e6 1.07204e6 1.15493e6\n", " 1.45525e5 4.16955e5 … 2.0602e5 23108.4\n", " 4.30326e5 8.29407e5 5.8902e5 5.38183e5\n", " 4.35577e5 1.68287e5 3.9299e5 4.07504e5\n", " 3.98381e5 3.47668e5 3.68688e5 3.67446e5\n", " 5.26463e5 491665.0 4.6532e5 5.84517e5\n", " 413999.0 5.47612e5 … 4.50939e5 5.03966e5\n", " 402115.0 2.63546e5 3.81213e5 3.21163e5" ] }, "execution_count": 88, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mc_matrix = exp.(mc_result.posterior_matrix) .* template_norm" ] }, { "cell_type": "markdown", "id": "f1337585-e9e8-41fe-9c21-13de2dc62570", "metadata": {}, "source": [ "Calculate statistics from the MC samples." ] }, { "cell_type": "code", "execution_count": 89, "id": "ed98dc8a-b458-4f2e-9934-a8ba9b9204db", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "71-element Vector{Float64}:\n", " 0.00912687264156707\n", " 0.004790017218165018\n", " 0.003329436130689708\n", " 0.0024272611543099056\n", " 0.002064780977697943\n", " 0.002183505582629635\n", " 0.0017044864398530755\n", " 0.0016733540459101148\n", " 0.0017417804049954448\n", " 0.0013784508728543429\n", " 0.0011399449910505755\n", " 0.0011888058743396179\n", " 0.0011599682308532113\n", " ⋮\n", " 0.0011200944160527624\n", " 0.0012330504803870226\n", " 0.00035610367957806844\n", " 0.0006518043827883646\n", " 0.001369033471843747\n", " 0.0008943038856546006\n", " 0.0009242184964425634\n", " 0.0004982006905727934\n", " 0.0013359256244834384\n", " 0.000840998544992007\n", " 0.0006874898663405812\n", " 0.0007556701845643837" ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Calculate the cumulative SFH for each sample in the chain\n", "# and find the 1-σ range\n", "mc_cum_sfr = Vector{Vector{Float64}}(undef,0)\n", "mc_sfr = Vector{Vector{Float64}}(undef,0)\n", "for x in eachcol(mc_matrix)\n", " _, mc_1, mc_2, mc_mh = calculate_cum_sfr(x, free_template_logAge, free_template_MH, T_max)\n", " push!(mc_cum_sfr, mc_1)\n", " push!(mc_sfr, mc_2)\n", "end\n", "mc_cum_sfr = reduce(hcat, mc_cum_sfr) # hcat( mc_cum_sfr... )\n", "mc_sfr = reduce(hcat, mc_sfr) # hcat( mc_sfr... )\n", "# Calculate quantiles\n", "mc_cum_lower = quantile.(eachrow(mc_cum_sfr), 0.16)\n", "mc_cum_med = median.(eachrow(mc_cum_sfr))\n", "mc_cum_upper = quantile.(eachrow(mc_cum_sfr), 0.84)\n", "mc_sfr_lower = quantile.(eachrow(mc_sfr), 0.16)\n", "mc_sfr_med = median.(eachrow(mc_sfr))\n", "mc_sfr_upper = quantile.(eachrow(mc_sfr), 0.84)" ] }, { "cell_type": "markdown", "id": "fd2c2fdf-41af-4250-bfde-b9609360cce7", "metadata": {}, "source": [ "And we'll plot the cumulative SFHs:" ] }, { "cell_type": "code", "execution_count": 90, "id": "c0d88496-3ef2-49f8-be69-4b19734c56d8", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs=plt.subplots(nrows=1,ncols=2,sharex=true,sharey=true,figsize=(10,6))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.1)\n", "\n", "axs[1].plot( exp10.(unique_free_template_logAge)./1e9, mc_cum_med, label=\"HMC Median\" )\n", "axs[1].plot( exp10.(unique_template_logAge)./1e9, cum_sfr_arr, label=\"Input SFH\", ls=\"--\" )\n", "axs[1].fill_between( exp10.(unique_free_template_logAge)./1e9, mc_cum_lower, mc_cum_upper, alpha=0.3, fc=\"k\") \n", "\n", "axs[1].set_xlim([13.0,-0.1])\n", "axs[1].set_ylim([0.0,1.1])\n", "axs[1].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[1].set_ylabel(\"Cumulative SF\")\n", "axs[1].legend()\n", "\n", "axs[2].plot( exp10.(unique_free_template_logAge)./1e9, hessian_cum_med, label=\"BFGS Result\" )\n", "axs[2].plot( exp10.(unique_template_logAge)./1e9, cum_sfr_arr, label=\"Input SFH\", ls=\"--\" )\n", "axs[2].fill_between( exp10.(unique_free_template_logAge)./1e9, hessian_cum_lower, hessian_cum_upper, alpha=0.3, fc=\"k\") \n", "axs[2].set_xlabel(\"Lookback Time [Gyr]\")\n", "axs[2].legend()" ] }, { "cell_type": "markdown", "id": "cff29c75-c2d5-441f-8a03-7388b5833d15", "metadata": {}, "source": [ "The differences are more obvious in the SFRs," ] }, { "cell_type": "code", "execution_count": 91, "id": "7cda8628-fe7a-4681-b099-ef65be8133df", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject Text(0.5, 29.371800193718016, 'log(Age [yr])')" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fig,axs = plt.subplots(nrows=1,ncols=2,sharex=true,sharey=true,figsize=(14,7))\n", "fig.subplots_adjust(hspace=0.0,wspace=0.1)\n", "\n", "axs[1].bar(unique_free_template_logAge, mc_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(mc_sfr_med .- mc_sfr_lower) .* 1e3, \n", " (mc_sfr_upper .- mc_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"HMC Result\")\n", "axs[1].bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "\n", "axs[1].set_xlabel(\"log(Age [yr])\")\n", "axs[1].set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "axs[1].legend()\n", "\n", "axs[2].bar(unique_free_template_logAge, hessian_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(hessian_sfr_med .- hessian_sfr_lower) .* 1e3, \n", " (hessian_sfr_upper .- hessian_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"BFGS Fit\")\n", "axs[2].bar(unique_template_logAge, sfr_arr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"Input SFRs\", alpha=0.5)\n", "axs[2].legend()\n", "axs[2].set_xlabel(\"log(Age [yr])\")" ] }, { "cell_type": "code", "execution_count": 92, "id": "9e72c971-56d6-4070-9f74-215b094eb944", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "PyPlot.Figure(PyObject
)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "PyObject " ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# _, _, tmp_sfr, _ = calculate_cum_sfr(bfgs_result.map.μ .* template_norm, free_template_logAge, free_template_MH)\n", "\n", "fig,ax1 = plt.subplots(figsize=(7,7))\n", "\n", "ax1.bar(unique_free_template_logAge, mc_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"HMC Result\")\n", "# ax1.bar(unique_free_template_logAge, hessian_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"BFGS Fit\", alpha=0.5) \n", "ax1.bar(unique_free_template_logAge, hessian_sfr_med .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", \n", " yerr = [(hessian_sfr_med .- hessian_sfr_lower) .* 1e3, \n", " (hessian_sfr_upper .- hessian_sfr_med) .* 1e3], \n", " capsize=3, error_kw=Dict(\"elinewidth\"=>1,\"capthick\"=>1), label=\"BFGS Fit\", alpha=0.5)\n", "# ax1.bar(unique_free_template_logAge, tmp_sfr .* 1e3; width=diff(vcat(unique_template_logAge,max_logAge)), align=\"edge\", label=\"BFGS Fit\", alpha=0.5) \n", "\n", "ax1.set_xlabel(\"log(Age [yr])\")\n", "ax1.set_ylabel(L\"SFR [$10^{-3}$ M$_\\odot$ / yr]\")\n", "ax1.set_ylim([0.0, ax1.get_ylim()[2]])\n", "ax1.legend()" ] }, { "cell_type": "markdown", "id": "94a19e50-bf63-4348-bb94-4b4374eea672", "metadata": {}, "source": [ "Thus the approximations we made above when deriving the uncertainties from the BFGS results that \n", "1. the posterior is well-approximated by a multivariate Gaussian in the fitting variables `θ = log(coeffs)` in the vicinity of the maximum a posteriori and \n", "2. the inverse Hessian approximation produced by the BFGS optimization is a good estimate of the variance-covariance matrix of said Gaussian\n", "\n", "are not fully correct, but they are good enough in most cases that they can produce very similar posterior samples to the full HMC analysis at a fraction of the computational cost (a few seconds compared to minutes or hours)." ] }, { "cell_type": "code", "execution_count": 93, "id": "094e7dc8-3e97-47ec-9eb4-856801ab3c6c", "metadata": {}, "outputs": [], "source": [ "GC.gc() # Explicit garbage collection when finished" ] }, { "cell_type": "code", "execution_count": null, "id": "74e4af33-2efd-4116-aa2a-0b101b59f846", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Julia (6 threads) 1.10.4", "language": "julia", "name": "julia-_6-threads_-1.10" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "1.10.4" }, "toc-autonumbering": false, "toc-showmarkdowntxt": false }, "nbformat": 4, "nbformat_minor": 5 }