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.github/workflows/CI.yml

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@@ -7,7 +7,7 @@ on:
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pull_request:
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env:
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JULIA_CMDSTAN_HOME: "/home/worker/cmdstan-2.26.0/"
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JULIA_CMDSTAN_HOME: "/home/worker/cmdstan-2.27.0/"
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jobs:
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test:
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OLDWD=`pwd`
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cd ~
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pwd
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wget https://github.com/stan-dev/cmdstan/releases/download/v2.26.0/cmdstan-2.26.0.tar.gz
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tar -xzpf cmdstan-2.26.0.tar.gz
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wget https://github.com/stan-dev/cmdstan/releases/download/v2.27.0/cmdstan-2.27.0.tar.gz
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tar -xzpf cmdstan-2.27.0.tar.gz
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ls -lia .
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make -C $JULIA_CMDSTAN_HOME build
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cd $OLDWD
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env:
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JULIA_CMDSTAN_HOME: "/home/runner/cmdstan-2.26.0/"
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JULIA_CMDSTAN_HOME: "/home/runner/cmdstan-2.27.0/"
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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with:
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-runtest@latest
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env:
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JULIA_CMDSTAN_HOME: "/home/runner/cmdstan-2.26.0/"
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JULIA_CMDSTAN_HOME: "/home/runner/cmdstan-2.27.0/"
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- uses: julia-actions/julia-processcoverage@v1
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if: matrix.version == '1' && matrix.os == 'ubuntu-latest' && matrix.num_threads == 1
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- uses: codecov/codecov-action@v1

Project.toml

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@@ -1,7 +1,7 @@
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name = "ParetoSmoothedImportanceSampling"
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uuid = "98f080ec-61e2-11eb-1c7b-31ea1097256f"
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authors = ["@alvaro1101, Rob J Goedman <goedman@icloud.com"]
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version = "1.0.0"
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authors = ["@alvaro1101, Rob J Goedman <goedman@icloud.com>"]
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version = "1.1.0"
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[deps]
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CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -17,11 +17,10 @@ StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[compat]
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CSV = "0.8"
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DataFrames = "0.22, 1.0"
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Distributions = "0.24, 0.25"
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CSV = "0.9"
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DataFrames = "1.2"
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Distributions = "0.25"
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JSON = "0.21"
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StanSample = "3.0"
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StatsFuns = "0.9"
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StatsPlots = "0.14"
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julia = "1"

test/test_demo_wells.jl

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@@ -1,7 +1,8 @@
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using ParetoSmoothedImportanceSampling
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using StanSample, StatsFuns
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using Statistics, StatsFuns
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using Printf
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using JSON
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using StanSample
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using Test
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ProjDir = @__DIR__
@@ -22,7 +23,7 @@ data1 = (p = m, N = n, y = Int.(y), x = x)
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# Fit the model in Stan
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rc1 = stan_sample(sm1; data=data1)
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if success(rc1)
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nt1 = read_samples(sm1)
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nt1 = read_samples(sm1, :namedtuple)
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# Compute LOO and standard error
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log_lik = nt1.log_lik'
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rc2 = stan_sample(sm1; data=data2)
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if success(rc2)
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nt2 = read_samples(sm1)
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nt2 = read_samples(sm1, :namedtuple)
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# Compute LOO and standard error
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log_lik = nt2.log_lik'
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loo2, loos2, pk2 = psisloo(log_lik)
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# Fit the model in Stan
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rc3 = stan_sample(sm3; data=standatacv)
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if success(rc3)
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nt3 = read_samples(sm3)
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nt3 = read_samples(sm3, :namedtuple)
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# Compute LOO and standard error
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log_likt = nt3.log_likt'
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local n_sam, n_obs = size(log_likt)

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