Miscellaneous improvements

Project.toml

@@ -1,15 +1,14 @@
 name = "ExpFamilyPCA"
 uuid = "9c724b78-6801-4402-8a63-53f028696012"
 authors = ["Logan-Mondal-Bhamidipaty"]
-version = "1.1.0"
+version = "2.0.0"
 
 [deps]
 CompressedBeliefMDPs = "0a809e47-b8eb-4578-b4e8-4c2c5f9f833c"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 FunctionWrappers = "069b7b12-0de2-55c6-9aab-29f3d0a68a2e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
-Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Sobol = "ed01d8cd-4d21-5b2a-85b4-cc3bdc58bad4"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
@@ -21,11 +20,10 @@ Distances = "0.10"
 FunctionWrappers = "1"
 LogExpFunctions = "0.3"
 Optim = "1"
-Parameters = "0.12"
 Sobol = "1"
 Statistics = "1"
 Symbolics = "6"
-julia = "1"
+julia = "1.10"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

src/ExpFamilyPCA.jl

@@ -4,7 +4,6 @@ using Distances
 using FunctionWrappers: FunctionWrapper
 using LogExpFunctions
 using Optim
-using Parameters
 using Sobol
 using Symbolics
 

src/compressor.jl

@@ -3,10 +3,10 @@ import CompressedBeliefMDPs  # `import` rather than `using` to keep tidey namesp
 """
     EPCACompressor(epca::EPCA)
 
-    Compressor for `CompressedBeliefMDPs.jl`.
+Compressor for `CompressedBeliefMDPs.jl`.
 """
-struct EPCACompressor <: CompressedBeliefMDPs.Compressor
-    epca::EPCA
+struct EPCACompressor{E<:EPCA} <: CompressedBeliefMDPs.Compressor
+    epca::E
 end
 
 function (c::EPCACompressor)(beliefs)
@@ -20,4 +20,4 @@ end
 
 function CompressedBeliefMDPs.fit!(c::EPCACompressor, beliefs)
     ExpFamilyPCA.fit!(c.epca, beliefs)
-end
+end

src/constructors/epca1.jl

@@ -1,13 +1,18 @@
-struct EPCA1 <: EPCA
-    F::Union{Function, FunctionWrapper}  # Legendre dual of the log-partition
-    g::Union{Function, FunctionWrapper}  # link function
-    V::AbstractMatrix{<:Real}
-    options::Options
+struct EPCA1{
+    FT1<:Union{Function, FunctionWrapper},
+    FT2<:Union{Function, FunctionWrapper},
+    MT<:AbstractMatrix{<:Real},
+    OT<:Options
+} <: EPCA
+    F::FT1  # Legendre dual of the log-partition
+    g::FT2  # link function
+    V::MT
+    options::OT
 end
 
 function _make_loss(epca::EPCA1, X)
-    @unpack F, g = epca
-    @unpack μ, ϵ = epca.options
+    (; F, g) = epca
+    (; μ, ϵ) = epca.options
     @assert ϵ >= 0 "ϵ must be non-negative."
 
     L(x, θ) = begin
@@ -44,7 +49,7 @@ function EPCA(
     options = Options()
 )
     @assert isfinite(f(options.μ)) "μ must be in the range of g meaning f(μ) should be finite."
-    @unpack low, high, tol, maxiter = options
+    (; low, high, tol, maxiter) = options
     g = _invert_legendre(f, options)
     V = _initialize_V(indim, outdim, options)
     epca = EPCA1(F, g, V, options)

src/constructors/epca2.jl

@@ -1,13 +1,18 @@
-struct EPCA2 <: EPCA
-    G::Union{Function, FunctionWrapper}  # log-parition function
-    g::Union{Function, FunctionWrapper}  # link function
-    V::AbstractMatrix{<:Real}
-    options::Options
+struct EPCA2{
+    FT1<:Union{Function, FunctionWrapper},
+    FT2<:Union{Function, FunctionWrapper},
+    MT<:AbstractMatrix{<:Real},
+    OT<:Options
+} <: EPCA
+    G::FT1  # log-parition function
+    g::FT2  # link function
+    V::MT
+    options::OT
 end
 
 function _make_loss(epca::EPCA2, X)
-    @unpack G, g = epca
-    @unpack tol, μ, ϵ = epca.options
+    (; G, g) = epca
+    (; tol, μ, ϵ) = epca.options
     @assert ϵ >= 0 "ϵ must be non-negative."
 
     L(x, θ) = begin

src/constructors/epca3.jl

@@ -1,13 +1,18 @@
-struct EPCA3 <: EPCA
-    B::Union{Function, FunctionWrapper, PreMetric}  # Bregman divergence
-    g::Union{Function, FunctionWrapper}  # link function
-    V::AbstractMatrix{<:Real}
-    options::Options
+struct EPCA3{
+    FT1<:Union{Function, FunctionWrapper, PreMetric},
+    FT2<:Union{Function, FunctionWrapper},
+    MT<:AbstractMatrix{<:Real},
+    OT<:Options
+} <: EPCA
+    B::FT1  # Bregman divergence
+    g::FT2  # link function
+    V::MT
+    options::OT
 end
 
 function _make_loss(epca::EPCA3, X)
-    @unpack B, g = epca
-    @unpack μ, ϵ = epca.options
+    (; B, g) = epca
+    (; μ, ϵ) = epca.options
     @assert ϵ >= 0 "ϵ must be non-negative."
 
     L(x, θ) = begin

src/constructors/epca4.jl

@@ -1,13 +1,18 @@
-struct EPCA4 <: EPCA
-    Bg::Function  # Bregman divergence composed with the link function in the 2nd slot, that is Bg(⋅, ⋅) = B_F(⋅, g(⋅)).
-    g::Function  # link function
-    V::AbstractMatrix{<:Real}
-    options::Options
+struct EPCA4{
+    FT1<:Function,
+    FT2<:Function,
+    MT<:AbstractMatrix{<:Real},
+    OT<:Options
+} <: EPCA
+    Bg::FT1  # Bregman divergence composed with the link function in the 2nd slot, that is Bg(⋅, ⋅) = B_F(⋅, g(⋅)).
+    g::FT2  # link function
+    V::MT
+    options::OT
 end
 
 function _make_loss(epca::EPCA4, X)
     Bg = epca.Bg
-    @unpack μ, ϵ = epca.options
+    (; μ, ϵ) = epca.options
     @assert ϵ >= 0 "ϵ must be non-negative."
 
     L(x, θ) = begin
@@ -51,4 +56,4 @@ function EPCA(
         options = options
     )
     return epca
-end
+end

src/epca.jl

@@ -121,7 +121,7 @@ function fit!(
         steps_per_print,
         epca.options
     )
-    epca.V[:] = V
+    epca.V[:] = V  # TODO: delete this line?
     return A
 end
 

src/family/gamma.jl

@@ -21,7 +21,7 @@ function GammaEPCA(
     indim::Integer, 
     outdim::Integer;
     options::Options = Options(
-        A_init_value = -2,
+        A_init_value = -2.0,
         A_upper = -eps(),
         V_lower = eps()
     )
@@ -47,11 +47,11 @@ function ItakuraSaitoEPCA(
     indim::Integer, 
     outdim::Integer; 
     options::Options = Options(
-        A_init_value = -2,
+        A_init_value = -2.0,
         A_upper = -eps(),
         V_lower = eps()
     )
 )
     epca = GammaEPCA(indim, outdim; options = options)
     return epca
-end
+end

src/family/negative_binomial.jl

@@ -23,7 +23,7 @@ function NegativeBinomialEPCA(
     outdim::Integer, 
     r::Integer;
     options::Options = Options(
-        A_init_value = -1,
+        A_init_value = -1.0,
         A_upper = -eps(),
         V_lower = eps()
     )
@@ -40,4 +40,4 @@ function NegativeBinomialEPCA(
         options = options
     )
     return epca
-end
+end

src/family/pareto.jl

@@ -22,11 +22,11 @@ function ParetoEPCA(
     outdim::Integer, 
     m::Real; 
     options::Options = Options(
-        μ = 2,
-        A_init_value = 2,
+        μ = 2.0,
+        A_init_value = 2.0,
         A_lower = 1 / outdim,
-        V_init_value = -2,
-        V_upper = -1,
+        V_init_value = -2.0,
+        V_upper = -1.0,
     )
 )
     @assert m > 0 "Minimum value m must be positive."
@@ -43,4 +43,4 @@ function ParetoEPCA(
         options = options
     )
     return epca
-end
+end

src/options.jl

@@ -20,29 +20,29 @@ Defines a struct `Options` for configuring various parameters used in optimizati
 - `tol::Real`: Tolerance for stopping binary search. Default is `1e-10`.
 - `maxiter::Real`: Maximum iterations for binary search. Default is `1e6`.
 """
-@with_kw struct Options
+@kwdef struct Options{T<:Real}
     # symbolic calculus 
     metaprogramming::Bool = true
 
     # loss hyperparameters
-    μ::Real = 1
-    ϵ::Real = eps()
+    μ::T = 1.0
+    ϵ::T = eps()
 
-    A_init_value::Real = 1.0
-    A_lower::Union{Real, Nothing} = nothing
-    A_upper::Union{Real, Nothing} = nothing
+    A_init_value::T = 1.0
+    A_lower::Union{T, Nothing} = nothing
+    A_upper::Union{T, Nothing} = nothing
     A_use_sobol::Bool = false
 
-    V_init_value::Real = 1.0
-    V_lower::Union{Real, Nothing} = nothing
-    V_upper::Union{Real, Nothing} = nothing
+    V_init_value::T = 1.0
+    V_lower::Union{T, Nothing} = nothing
+    V_upper::Union{T, Nothing} = nothing
     V_use_sobol::Bool = false
 
     # binary search options
-    low = -1e10
-    high = 1e10
-    tol = 1e-10
-    maxiter = 1e6
+    low::Float64 = -1e10
+    high::Float64 = 1e10
+    tol::Float64 = 1e-10
+    maxiter::Int = 10^6
 end
 
 """
@@ -60,12 +60,12 @@ Other fields inherit from the `Options` struct.
 """
 function NegativeDomain(;
     metaprogramming::Bool = true,
-    μ::Real = 1,
+    μ::Real = 1.0,
     ϵ::Real = eps(),
     low = -1e10,
     high = 1e10,
     tol = 1e-10,
-    maxiter = 1e6,
+    maxiter = 10^6,
 )
     options = Options(
         metaprogramming = metaprogramming,
@@ -75,9 +75,9 @@ function NegativeDomain(;
         high = high,
         tol = tol,
         maxiter = maxiter,
-        A_init_value = -1,
+        A_init_value = -1.0,
         A_upper = -1e-4,
-        V_init_value = 1,
+        V_init_value = 1.0,
         V_lower = 1e-4,
     )
     return options
@@ -98,12 +98,12 @@ Other fields inherit from the `Options` struct.
 """
 function PositiveDomain(
     metaprogramming::Bool = true,
-    μ::Real = 1,
+    μ::Real = 1.0,
     ϵ::Real = eps(),
     low = -1e10,
     high = 1e10,
     tol = 1e-10,
-    maxiter = 1e6,
+    maxiter = 10^6,
 )
     options = Options(
         metaprogramming = metaprogramming,
@@ -113,10 +113,10 @@ function PositiveDomain(
         high = high,
         tol = tol,
         maxiter = maxiter,
-        A_init_value = 1,
+        A_init_value = 1.0,
         A_upper = 1e-4,
-        V_init_value = 1,
+        V_init_value = 1.0,
         V_lower = 1e-4,
     )
     return options
-end
+end