From 9a01cc2d8a70873a92cd2e8ac16f508ac8c97019 Mon Sep 17 00:00:00 2001
From: PharmCat <v.s.arnautov@yandex.ru>
Date: Wed, 17 Feb 2021 00:40:10 +0300
Subject: [PATCH] v0.3.1 #doc

---
 Project.toml           | 2 +-
 change.log             | 4 ++++
 docs/Project.toml      | 2 ++
 docs/src/instanduse.md | 4 ++--
 src/Metida.jl          | 1 +
 src/utils.jl           | 2 +-
 src/varstruct.jl       | 2 ++
 test/test.jl           | 5 ++++-
 8 files changed, 17 insertions(+), 5 deletions(-)

diff --git a/Project.toml b/Project.toml
index e344578a..f9e7eebe 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "Metida"
 uuid = "a1dec852-9fe5-11e9-361f-8d9fde67cfa2"
 authors = ["Vladimir Arnautov <mail@pharmcat.net>"]
-version = "0.3.0"
+version = "0.3.1"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
diff --git a/change.log b/change.log
index ca44f3f8..1454bc89 100644
--- a/change.log
+++ b/change.log
@@ -1,3 +1,7 @@
+v0.3.1
+  * export fix
+  * doc fix
+
 v0.3.0
   * effect model remake
   * subject keyword removed
diff --git a/docs/Project.toml b/docs/Project.toml
index 4cbdc5bc..696d51c1 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -4,10 +4,12 @@ StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 CSV        = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 MixedModels = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 
 
 [compat]
 Documenter = "≥0.22"
+Plots = "0.28, 0.29, 1.0"
 StatsPlots = "≥0.14"
 CSV        = "0.7, 0.8"
 DataFrames = "≥0.22"
diff --git a/docs/src/instanduse.md b/docs/src/instanduse.md
index 3406c301..c5fdf7ab 100644
--- a/docs/src/instanduse.md
+++ b/docs/src/instanduse.md
@@ -40,7 +40,7 @@ fit!(lmm)
 
 ### Model construction
 
-[Metida.LMM](@ref)
+[`LMM`](@ref)
 
 * `model` - example: `@formula(var ~ sequence + period + formulation)`
 
@@ -51,7 +51,7 @@ fit!(lmm)
 
 ### Fitting
 
-[Metida.fit!](@ref)
+[`fit!`](@ref)
 
 * `solver` - `:default` solving with Optim.jl, for `:nlopt` and `:cuda` MetidaNLopt.jl and MetidaCu.jl should be installed.
 
diff --git a/src/Metida.jl b/src/Metida.jl
index 1c3cf889..b1d24778 100644
--- a/src/Metida.jl
+++ b/src/Metida.jl
@@ -21,6 +21,7 @@ AR, Autoregressive,
 ARH, HeterogeneousAutoregressive,
 CS, CompoundSymmetry,
 CSH, HeterogeneousCompoundSymmetry,
+ARMA, AutoregressiveMovingAverage,
 fit!, LMM, VarEffect, theta, logreml, m2logreml, thetalength, dof_satter, dof_contain, rankx, caic,
 gmatrix, rmatrix, vmatrix!
 
diff --git a/src/utils.jl b/src/utils.jl
index e7736223..6d7b0a1d 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -225,7 +225,7 @@ function vmatrix(lmm, i)
 end
 
 function nblocks(lmm)
-    return length.covstr.vcovblock
+    return length(lmm.covstr.vcovblock)
 end
 """
     hessian(lmm, theta)
diff --git a/src/varstruct.jl b/src/varstruct.jl
index fa321be9..71c99eea 100644
--- a/src/varstruct.jl
+++ b/src/varstruct.jl
@@ -391,6 +391,7 @@ function updatenametype!(ct, rcnames, csp, schema, s)
     append!(rcnames, rcoefnames(schema, csp[3], s))
 end
 ################################################################################
+#=
 function subjmatrix!(subj, data, subjz, i)
     if length(subj) > 0
         if length(subj) == 1
@@ -405,6 +406,7 @@ function subjmatrix!(subj, data, subjz, i)
         subjz[i]    = trues(size(data, 1),1)
     end
 end
+=#
 ################################################################################
 function makeblocks(subjz)
     blocks = Vector{Vector{Int}}(undef, 0)
diff --git a/test/test.jl b/test/test.jl
index 6e69eb71..15cf0203 100644
--- a/test/test.jl
+++ b/test/test.jl
@@ -48,6 +48,7 @@ include("testdata.jl")
     @test length(modelmatrix(lmm)) == 120
     @test isa(response(lmm), Vector)
     @test sum(Metida.hessian(lmm))    ≈ 1118.160713481362 atol=1E-2
+    @test Metida.nblocks(lmm) == 5
     #AI like algo
     Metida.fit!(lmm; aifirst = true, init = Metida.theta(lmm), blocksolve = true)
     @test Metida.m2logreml(lmm) ≈ 16.241112644506067 atol=1E-6
@@ -200,11 +201,13 @@ end
 end
 
 @testset "  Model: Noblock, different subjects, ARMA/SI              " begin
+    io = IOBuffer();
     #SPSS 904.236!!!
     lmm = Metida.LMM(@formula(response ~ 1 + factor), ftdf3; contrasts=Dict(:factor => DummyCoding(; base=1.0)),
     random = Metida.VarEffect(Metida.@covstr(s2|r1&r2), Metida.ARMA),
     )
-    Metida.fit!(lmm;)
+    Metida.fit!(lmm; verbose = 3, io = io)
+    println(io, lmm.log)
     @test Metida.m2logreml(lmm)  ≈ 903.2467964711996 atol=1E-8
 end