vamos

CHANGELOG.md

@@ -6,6 +6,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 
 *Note*: We try to adhere to these practices as of version [v1.0.1].
 
+## Version [1.1.2] - 2025-01-10
+
+### Changed
+
+- Improved and streamlined some assertions related to dataset sizes. [#29]
+
 ## Version [1.1.1] - 2025-01-10
 
 ### Changed

src/tabular/adult.jl

@@ -4,13 +4,9 @@
 Loads data from the UCI 'Adult' dataset.
 """
 function load_uci_adult(n::Union{Nothing,Int}=1000; seed=data_seed)
-    # Throw an exception if n < 1:
-    if !isnothing(n) && n < 1
-        throw(ArgumentError("n must be >= 1"))
-    end
-    if !isnothing(n) && n > 32000
-        throw(ArgumentError("n must not exceed size of dataset (<=32000)"))
-    end
+
+    # Assertions:
+    ensure_positive(n)
 
     # Load data
     df = CSV.read(joinpath(data_dir, "adult.csv"), DataFrames.DataFrame)
@@ -41,9 +37,11 @@ function load_uci_adult(n::Union{Nothing,Int}=1000; seed=data_seed)
     X = MLJBase.transform(mach, df[:, DataFrames.Not(:target)])
     X = Matrix(X)
     X = permutedims(X)
-
     y = df.target
 
+    # Checks and warnings
+    request_more_than_available(n, size(X,2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/tabular/california_housing.jl

@@ -5,10 +5,8 @@ Loads California Housing data.
 """
 function load_california_housing(n::Union{Nothing,Int}=5000; seed=data_seed)
 
-    # check that n is > 0
-    if !isnothing(n) && n <= 0
-        throw(ArgumentError("n must be > 0"))
-    end
+    # Assertions:
+    ensure_positive(n)
 
     # Load:
     df = CSV.read(joinpath(data_dir, "cal_housing.csv"), DataFrames.DataFrame)
@@ -22,6 +20,9 @@ function load_california_housing(n::Union{Nothing,Int}=5000; seed=data_seed)
     # Counterfactual data:
     y = Int.(df.target)
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/tabular/credit_default.jl

@@ -5,6 +5,9 @@ Loads UCI Credit Default data.
 """
 function load_credit_default(n::Union{Nothing,Int}=5000; seed=data_seed)
 
+    # Assertions:
+    ensure_positive(n)
+
     # Load:
     df = CSV.read(joinpath(data_dir, "credit_default.csv"), DataFrames.DataFrame)
 
@@ -28,6 +31,9 @@ function load_credit_default(n::Union{Nothing,Int}=5000; seed=data_seed)
     #     X, y; features_categorical=features_categorical
     # )
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/tabular/german_credit.jl

@@ -4,15 +4,9 @@
 Loads UCI German Credit data.
 """
 function load_german_credit(n::Union{Nothing,Int}=nothing; seed=data_seed)
-    # Throw an exception if n > 1000:
-    if !isnothing(n) && n > 1000
-        throw(ArgumentError("n must be <= 1000"))
-    end
 
-    # Throw an exception if n < 1:
-    if !isnothing(n) && n < 1
-        throw(ArgumentError("n must be >= 1"))
-    end
+    # Assertions:
+    ensure_positive(n)
 
     # Load:
     df = CSV.read(joinpath(data_dir, "german_credit.csv"), DataFrames.DataFrame)
@@ -27,6 +21,9 @@ function load_german_credit(n::Union{Nothing,Int}=nothing; seed=data_seed)
     # Counterfactual data:
     y = convert(Vector, df.target)
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/tabular/gmsc.jl

@@ -5,6 +5,9 @@ Loads Give Me Some Credit (GMSC) data.
 """
 function load_gmsc(n::Union{Nothing,Int}=5000; seed=data_seed)
 
+    # Assertions:
+    ensure_positive(n)
+
     # Load:
     df = CSV.read(joinpath(data_dir, "gmsc.csv"), DataFrames.DataFrame)
 
@@ -18,6 +21,9 @@ function load_gmsc(n::Union{Nothing,Int}=5000; seed=data_seed)
     # Counterfactual data:
     y = df.target
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/utils.jl

@@ -12,6 +12,19 @@ function get_rng(seed::Union{Int,AbstractRNG})
     return seed
 end
 
+function request_more_than_available(nreq, navailable)
+    if !isnothing(nreq) && nreq > navailable
+        @warn "Requested $nreq samples but only $navailable are available. Will resort to random oversampling."
+    end
+end
+
+
+function ensure_positive(n::Union{Nothing,Int})
+    if !isnothing(n) && n < 1
+        throw(ArgumentError("`n` must be >= 1"))
+    end
+end
+
 function subsample(rng::AbstractRNG, X::AbstractMatrix, y::AbstractVector, n::Int)
     # Get the unique classes in `y`.
     classes_ = unique(y)

src/vision/cifar_10.jl

@@ -4,15 +4,22 @@
 Loads data from the CIFAR-10 dataset.
 """
 function load_cifar_10(n::Union{Nothing,Int}=nothing; seed=data_seed)
+
+    # Assertions:
+    ensure_positive(n)
+
     X, y = MLDatasets.CIFAR10()[:] # [:] gives us X, y
     X = Flux.flatten(X)
-    X = X .* 2 .- 1 # normalization between [-1, 1]
+    X = X .* 2 .- 1                 # normalization between [-1, 1]
     y = MLJBase.categorical(y)
     y = DataAPI.unwrap.(y)
     # counterfactual_data = CounterfactualExplanations.CounterfactualData(
     #     X, y; domain=(-1.0, 1.0), standardize=false
     # )
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/vision/fashion_mnist.jl

@@ -4,6 +4,10 @@
 Loads FashionMNIST data.
 """
 function load_fashion_mnist(n::Union{Nothing,Int}=nothing; seed=data_seed)
+
+    # Assertions:
+    ensure_positive(n)
+
     X, y = MLDatasets.FashionMNIST(:train)[:]
     X = Flux.flatten(X)
     X = X .* 2.0f0 .- 1.0f0
@@ -13,6 +17,9 @@ function load_fashion_mnist(n::Union{Nothing,Int}=nothing; seed=data_seed)
     #     X, y; domain=(-1.0, 1.0), standardize=false
     # )
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]

src/vision/mnist.jl

@@ -4,6 +4,10 @@
 Loads MNIST data.
 """
 function load_mnist(n::Union{Nothing,Int}=nothing; seed=data_seed)
+
+    # Assertions:
+    ensure_positive(n)
+
     X, y = MLDatasets.MNIST(:train)[:]
     X = Flux.flatten(X)
     X = X .* 2.0f0 .- 1.0f0
@@ -13,6 +17,9 @@ function load_mnist(n::Union{Nothing,Int}=nothing; seed=data_seed)
     #     X, y; domain=(-1.0, 1.0), standardize=false
     # )
 
+    # Checks and warnings
+    request_more_than_available(n, size(X, 2))
+
     # Randomly under-/over-sample:
     rng = get_rng(seed)
     if !isnothing(n) && n != size(X)[2]