From 53b7209c33eeeb46330c8f98035bbac196dff875 Mon Sep 17 00:00:00 2001
From: Anthony Lee <awllee@gmail.com>
Date: Mon, 23 Jul 2018 22:37:31 +0100
Subject: [PATCH] fix 0.7 deprecations

---
 src/MonteCarloMarkovKernels.jl | 11 ++++++++++-
 src/adaptiveMetropolis.jl      | 12 +++---------
 src/randomWalkMetropolis.jl    |  8 ++------
 src/simulateChain.jl           |  1 -
 test/visualize_test.jl         |  4 ++--
 5 files changed, 17 insertions(+), 19 deletions(-)

diff --git a/src/MonteCarloMarkovKernels.jl b/src/MonteCarloMarkovKernels.jl
index dbeddcc..cd7948f 100644
--- a/src/MonteCarloMarkovKernels.jl
+++ b/src/MonteCarloMarkovKernels.jl
@@ -1,9 +1,18 @@
 __precompile__()
 
 module MonteCarloMarkovKernels
+using StaticArrays
+
+using Compat.LinearAlgebra
+using Compat.Random
 import Compat.Statistics.mean
 
-import Compat.undef
+import Compat: undef, UndefInitializer
+if VERSION.minor < 7
+  MVector{d, Float64}(::UndefInitializer) where d = MVector{d, Float64}()
+  mul! = A_mul_B!
+end
+
 if VERSION.minor == 7
   function mychol(A)
     return cholesky(A).L
diff --git a/src/adaptiveMetropolis.jl b/src/adaptiveMetropolis.jl
index e727e75..add5d14 100644
--- a/src/adaptiveMetropolis.jl
+++ b/src/adaptiveMetropolis.jl
@@ -1,9 +1,3 @@
-using StaticArrays
-using Compat.LinearAlgebra
-using Compat.Random
-
-if VERSION.minor == 6 mul! = A_mul_B! end
-
 ## Makes an adaptive Metropolis kernel proposed by:
 ## Haario, H., Saksman, E. and Tamminen, J., 2001. An adaptive Metropolis
 ## algorithm. Bernoulli, 7(2), pp.223-242.
@@ -18,9 +12,9 @@ function makeAMKernel(logTargetDensity::F, Σ::SMatrix{d, d, Float64},
   # A::MMatrix{d, d, Float64} = chol(Symmetric(S))'
   A::MMatrix{d, d, Float64} = mychol(S)
 
-  scratchv::MVector{d, Float64} = MVector{d, Float64}()
-  scratchz::MVector{d, Float64} = MVector{d, Float64}()
-  prevx::MVector{d, Float64} = MVector{d, Float64}()
+  scratchv::MVector{d, Float64} = MVector{d, Float64}(undef)
+  scratchz::MVector{d, Float64} = MVector{d, Float64}(undef)
+  prevx::MVector{d, Float64} = MVector{d, Float64}(undef)
   ldprevx = Ref(-Inf)
 
   accepts = Ref(0)
diff --git a/src/randomWalkMetropolis.jl b/src/randomWalkMetropolis.jl
index bab6e95..66adb1f 100644
--- a/src/randomWalkMetropolis.jl
+++ b/src/randomWalkMetropolis.jl
@@ -1,15 +1,11 @@
-using StaticArrays
-using Compat.LinearAlgebra
-using Compat.Random
-
 ## Makes a random walk Metropolis kernel
 function makeRWMKernel(logTargetDensity::F,
   Σ::SMatrix{d, d, Float64}) where {F<:Function, d}
   # A::SMatrix{d, d, Float64} = chol(Symmetric(Σ))'
   A::SMatrix{d, d, Float64} = mychol(Σ)
 
-  scratchv::MVector{d, Float64} = MVector{d, Float64}()
-  prevx::MVector{d, Float64} = MVector{d, Float64}()
+  scratchv::MVector{d, Float64} = MVector{d, Float64}(undef)
+  prevx::MVector{d, Float64} = MVector{d, Float64}(undef)
   ldprevx = Ref(-Inf)
 
   accepts = Ref(0)
diff --git a/src/simulateChain.jl b/src/simulateChain.jl
index 76121c8..345a82c 100644
--- a/src/simulateChain.jl
+++ b/src/simulateChain.jl
@@ -1,4 +1,3 @@
-using StaticArrays
 using ProgressMeter
 
 function simulateChain!(chain::Vector{T}, P::F, x0::T) where {F<:Function, T}
diff --git a/test/visualize_test.jl b/test/visualize_test.jl
index 337cac9..2ce9117 100644
--- a/test/visualize_test.jl
+++ b/test/visualize_test.jl
@@ -23,7 +23,7 @@ end
 logtarget = makelogMVN(SVector{2, Float64}(μ1), SMatrix{2, 2, Float64}(Σ1))
 
 niterations = 2^20
-chain = Vector{SVector{2, Float64}}(niterations)
+chain = Vector{SVector{2, Float64}}(undef, niterations)
 
 srand(12345)
 
@@ -33,7 +33,7 @@ simulateChain!(chain, P_AM, Szero2)
 @test mean(chain) ≈ μ1 atol = 0.01
 @test MonteCarloMarkovKernels.cov(chain) ≈ Σ1 atol = 0.05
 
-vs = Vector{Vector{Float64}}(2)
+vs = Vector{Vector{Float64}}(undef, 2)
 for i = 1:2
   vs[i] = (x->x[i]).(chain)
 end