monor opt, clean, docs, test

PharmCat · Aug 21, 2024 · 8e7229b · 8e7229b
1 parent b76211b
commit 8e7229b
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diff --git a/docs/src/index.md b/docs/src/index.md
@@ -38,7 +38,7 @@ Implemented covariance structures:
 
 Actually Metida can fit datasets with wore than  160k observation and 40k subjects levels on PC with 64 GB RAM. This is not "hard-coded" limitation, but depends on your model and data structure. Fitting of big datasets can take a lot of time. Optimal dataset size is less than 100k observations with maximum length of block less than 400.
 
-!!! note
+!!! warning
 
     Julia v1.8 or higher required.
 

diff --git a/src/Metida.jl b/src/Metida.jl
@@ -20,6 +20,7 @@ import Random: default_rng, AbstractRNG, rand!
 
 export @formula, @covstr, @lmmformula,
 SI, ScaledIdentity,
+SWC, ScaledWeightedCov,
 DIAG, Diag,
 AR, Autoregressive,
 ARH, HeterogeneousAutoregressive,

diff --git a/src/fvalue.jl b/src/fvalue.jl
@@ -1,8 +1,5 @@
 # fvalue.jl
 
-#=
-Metida.fvalue(lmm, [0 0 1 0 0 0; 0 0 0 1 0 0; 0 0 0 0 1 0])
-=#
 """
     fvalue(lmm::LMM, l::Matrix)
 

diff --git a/src/reml.jl b/src/reml.jl
@@ -88,7 +88,12 @@ function reml_sweep_β(lmm, data, θ::Vector{T}; maxthreads::Int = 4) where T #
         end
         θ₁      = sum(accθ₁)
         θ₂      = sum(accθ₂)
-        βm      = sum(accβm)
+        if length(accβm) > 1
+            for i = 2:length(accβm)
+                accβm[1] += accβm[i]
+            end
+        end
+        βm = accβm[1]
         noerror = all(erroracc)
         noerror = noerror * checkmatrix!(θ₂)
         θs₂     = Symmetric(θ₂)

diff --git a/src/utils.jl b/src/utils.jl
@@ -16,10 +16,7 @@ end
 function fixedeffn(lmm::LMM)
     fixedeffn(lmm.f) 
 end
-#=
-function nterms(mf::ModelFrame)
-    mf.schema.schema.count
-=#
+
 function nterms(rhs::Union{Tuple{Vararg{AbstractTerm}}, Nothing, AbstractTerm})
     if isa(rhs, Term)
         p = 1