Fix reconstruct: throw ArgumentError on invalid input type

.github/workflows/ci.yml

@@ -36,7 +36,7 @@ jobs:
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
+      - uses: actions/cache@v3
         env:
           cache-name: cache-artifacts
         with:

docs/src/pca.md

@@ -117,6 +117,10 @@ predict(::KernelPCA)
 predict(::KernelPCA, ::AbstractVecOrMat{T}) where {T<:Real}
 reconstruct(::KernelPCA, ::AbstractVecOrMat{T}) where {T<:Real}
 size(::KernelPCA)
+```
+!!! note
+	If `reconstruct` is called with an input that is not an `AbstractVecOrMat` of real numbers, an `ArgumentError` is thrown indicating the invalid input type and the expected type.
+```
 projection(::KernelPCA)
 eigvals(::KernelPCA)
 eigvecs(::KernelPCA)
@@ -164,6 +168,10 @@ fit
 size(::PPCA)
 mean(::PPCA)
 var(::PPCA)
+```
+!!! note
+	If `reconstruct` is called with an input that is not an `AbstractVecOrMat` of real numbers, an `ArgumentError` is thrown indicating the invalid input type and the expected type.
+```
 cov(::PPCA)
 projection(::PPCA)
 loadings(::PPCA)
@@ -188,6 +196,9 @@ Here, ``\mathbf{W}`` is the factor loadings or weight matrix.
 predict(::PPCA, ::AbstractVecOrMat{T}) where {T<:Real}
 reconstruct(::PPCA, ::AbstractVecOrMat{T}) where {T<:Real}
 ```
+```
+!!! note
+	If `reconstruct` is called with an input that is not an `AbstractVecOrMat` of real numbers, an `ArgumentError` is thrown indicating the invalid input type and the expected type.
 
 Auxiliary functions:
 

src/types.jl

@@ -23,8 +23,14 @@ projection(model::AbstractDimensionalityReduction) = error("'projection' is not
     reconstruct(model::AbstractDimensionalityReduction, y)
 
 Return the model response (a.k.a. the dependent variable).
+Throws an `ArgumentError` if `y` is not an `AbstractVecOrMat` of real numbers, indicating the invalid 
+input type and the expected type.
 """
-reconstruct(model::AbstractDimensionalityReduction, y) = error("'reconstruct' is not defined for $(typeof(model)).")
+function reconstruct(model::AbstractDimensionalityReduction, y)
+    throw(ArgumentError("Invalid input type $(typeof(y)) for reconstruct(::$(typeof(model))). " * 
+    "Expected an AbstractVecOrMat of real numbers."
+    ))
+end
 
 abstract type LinearDimensionalityReduction <: AbstractDimensionalityReduction end
 

test/pca.jl

@@ -43,6 +43,12 @@ import SparseArrays
     @test reconstruct(M, Y[:,1]) ≈ P * Y[:,1]
     @test reconstruct(M, Y) ≈ P * Y
 
+    @test_throws ArgumentError reconstruct(M, 123)
+    @test_throws ArgumentError reconstruct(M, Dict())
+    @test_throws ArgumentError reconstruct(M, "abc")
+    @test_throws ArgumentError reconstruct(M, 8923.29)
+    @test_throws ArgumentError reconstruct(M, 1+2im)
+
 
     ## PCA with non-zero mean