Rel 4.5.4 - log_lik -> loglik, doc fixes

Author: goedman

Project.toml

@@ -26,6 +26,7 @@ PrettyTables = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
+StanSample = "c1514b29-d3a0-5178-b312-660c88baa699"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"

research/sr_loo_compare.jl

@@ -40,9 +40,9 @@ model {
     D ~ normal(mu , sigma);     // Likelihood
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -70,9 +70,9 @@ model {
     D ~ normal( mu , sigma );
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -102,9 +102,9 @@ model {
   D ~ normal( mu , sigma );
 }
 generated quantities{
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -127,7 +127,7 @@ function to_paretosmooth(ll, pd = [3, 1, 2])
 end
 
 function loo_compare1(models::Vector{SampleModel}; 
-    loglikelihood_name="log_lik",
+    loglikelihood_name="loglik",
     model_names=nothing,
     sort_models=true, 
     show_psis=true)

src/require/stan/stan_axiskeys.jl

@@ -1,12 +1,12 @@
 using AxisKeys
 
-function psis_loo(model::SampleModel; loglikelihood_name="log_lik")
+function psis_loo(model::SampleModel; loglikelihood_name="loglik")
     chains = read_samples(model, :keyedarray) # Obtain KeyedArray chains
     psis_loo(chains; loglikelihood_name)
 end
 
-function psis_loo(chains::T; loglikelihood_name="log_lik") where {T <: KeyedArray}
-    ll = Array(matrix(chains, loglikelihood_name)) # Extract log_lik matrix
+function psis_loo(chains::T; loglikelihood_name="loglik") where {T <: KeyedArray}
+    ll = Array(matrix(chains, loglikelihood_name)) # Extract loglik matrix
     ll_p = to_paretosmooth(ll) # Permute dims for ParetoSmooth
     psis = psis_loo(ll_p) # Compute PsisLoo for model
 end
@@ -18,7 +18,7 @@ function to_paretosmooth(ll, pd = [3, 1, 2])
 end
 
 function loo_compare(models::Vector{SampleModel}; 
-    loglikelihood_name="log_lik",
+    loglikelihood_name="loglik",
     model_names=nothing,
     sort_models=true, 
     show_psis=true)
@@ -31,14 +31,14 @@ function loo_compare(models::Vector{SampleModel};
 end
 
 function loo_compare(chains_vec::Vector{<: KeyedArray}; 
-    loglikelihood_name="log_lik",
+    loglikelihood_name="loglik",
     model_names=nothing,
     sort_models=true, 
     show_psis=true)
 
     nmodels = length(chains_vec)
 
-    ll_vec = Array.(matrix.(chains_vec, loglikelihood_name)) # Extract log_lik matrix
+    ll_vec = Array.(matrix.(chains_vec, loglikelihood_name)) # Extract loglik matrix
     ll_vecp = map(to_paretosmooth, ll_vec) # Permute dims for ParetoSmooth
     psis_vec = psis_loo.(ll_vecp) # Compute PsisLoo for all models
 

src/require/stan/stan_compare.jl

@@ -22,11 +22,11 @@ function compare(models::Vector{SampleModel}, type::Symbol)
     lps = Matrix{Float64}[]
     for m in models
         nt = read_samples(m, :namedtuple)
-        if :log_lik in keys(nt)
+        if :loglik in keys(nt)
             append!(mnames, [m.name])
-            append!(lps, [Matrix(nt.log_lik')])
+            append!(lps, [Matrix(nt.loglik')])
         else
-            @warn "Model $(m.name) does not produce a log_lik matrix."
+            @warn "Model $(m.name) does not produce a loglik matrix."
         end
     end
     compare(lps, type; mnames)

src/require/stan/stan_psis.jl

@@ -2,21 +2,21 @@ import ParetoSmoothedImportanceSampling: psisloo, waic
 
 function psisloo(m::SampleModel, wcpp::Int64=20, wtrunc::Float64=3/4)
     nt = read_samples(m, :namedtuple)
-    if :log_lik in keys(nt)
-        lp = Matrix(nt.log_lik')
+    if :loglik in keys(nt)
+        lp = Matrix(nt.loglik')
     else
-        @warn "Model $(m.name) does not compute a log_lik matrix."
+        @warn "Model $(m.name) does not compute a loglik matrix."
     end
 
     psisloo(lp, wcpp, wtrunc)
 end
 
 function waic(m::SampleModel; pointwise=false)
     nt = read_samples(m, :namedtuple)
-    if :log_lik in keys(nt)
-        lp = Matrix(nt.log_lik')
+    if :loglik in keys(nt)
+        lp = Matrix(nt.loglik')
     else
-        @warn "Model $(m.name) does not compute a log_lik matrix."
+        @warn "Model $(m.name) does not compute a loglik matrix."
     end
 
     waic(lp; pointwise)

test/test_wd-loo-compare-2.jl

@@ -33,9 +33,9 @@ model {
     D ~ normal(mu , sigma);     // Likelihood
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -63,9 +63,9 @@ model {
     D ~ normal( mu , sigma );
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -95,9 +95,9 @@ model {
   D ~ normal( mu , sigma );
 }
 generated quantities{
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -111,7 +111,7 @@ m5_3s = SampleModel("m5.3s", stan5_3)
 rc5_3s = stan_sample(m5_3s; data)
 
 function loo_compare2(models::Vector{SampleModel}; 
-    loglikelihood_name="log_lik",
+    loglikelihood_name="loglik",
     model_names=nothing,
     sort_models=true, 
     show_psis=true)
@@ -120,7 +120,7 @@ function loo_compare2(models::Vector{SampleModel};
     model_names = [models[i].name for i in 1:nmodels]
 
     chains_vec = read_samples.(models, :dataframe) # Obtain KeyedArray chains
-    chains_vec = DataFrame.(chains_vec, :log_lik)
+    chains_vec = DataFrame.(chains_vec, :loglik)
     chains_vec = Array.(chains_vec)
     println(length(chains_vec))
     println(typeof(chains_vec[1]))
@@ -140,14 +140,14 @@ function loo_compare2(models::Vector{SampleModel};
 end
 
 function loo_compare2(ll_vec::Vector{<: Array}; 
-    loglikelihood_name="log_lik",
+    loglikelihood_name="loglik",
     model_names=nothing,
     sort_models=true, 
     show_psis=true)
 
     nmodels = length(ll_vec)
 
-    #ll_vec = Array.(matrix.(chains_vec, loglikelihood_name)) # Extract log_lik matrix
+    #ll_vec = Array.(matrix.(chains_vec, loglikelihood_name)) # Extract loglik matrix
     #ll_vecp = map(to_paretosmooth, ll_vec) # Permute dims for ParetoSmooth
     psis_vec = psis_loo.(ll_vec) # Compute PsisLoo for all models
 

test/test_wd-loo-compare.jl

@@ -33,9 +33,9 @@ model {
     D ~ normal(mu , sigma);     // Likelihood
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -63,9 +63,9 @@ model {
     D ~ normal( mu , sigma );
 }
 generated quantities {
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";
 
@@ -95,9 +95,9 @@ model {
   D ~ normal( mu , sigma );
 }
 generated quantities{
-    vector[N] log_lik;
+    vector[N] loglik;
     for (i in 1:N)
-        log_lik[i] = normal_lpdf(D[i] | mu[i], sigma);
+        loglik[i] = normal_lpdf(D[i] | mu[i], sigma);
 }
 ";