cossio
cossio
For example: ``` P = abs.(randn(5,4,2)); p = view(P,:,1,1); p ./=sum(p); ``` Then: ``` julia> Categorical(p) ERROR: MethodError: Cannot `convert` an object of type Array{Float64,1} to an object of type...
Fixes https://github.com/JuliaStats/Distributions.jl/issues/1089. Since the sampler for truncated normal takes samples from `Exponential`, I also modified the `Exponential` sampler to return values following the parameter type.

``` julia> SpecialFunctions.erfi(big"1") ERROR: MethodError: no method matching erfi(::BigFloat) ``` Since `SpecialFunctions.erf` works with `BigFloat`, I suspect that `erfi` could work too without much hassle?
Currently if you try to `Pkg.test` a project without an UUID, it will throw this error: ``` ERROR: trying to test unnamed project ``` Even if the project has a...
``` julia> repeat(Trues(2,3), 2,3) 4×9 Matrix{Bool}: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1...
These should be specialized to return FillArrays types: ```julia julia> one(Ones(3,3)) # could return Eye(3) 3×3 Matrix{Float64}: 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 julia> one(Zeros(3,3)) # could...
Suppose I execute the following code in a fresh REPL (I haven't imported `SpecialFunctions`): ```julia julia> f(x) = erf(x); julia> f(1) ERROR: UndefVarError: erf not defined Stacktrace: [1] f(::Int64) at...
```julia using BSON import LinearAlgebra as LA e = LA.eigen(randn(5,5)) BSON.@save "temp.bson" e BSON.@load "temp.bson" e # ERROR ``` Stacktrace: ``` ERROR: UndefVarError: LinearAlgebra not defined Stacktrace: [1] (::BSON.var"#31#32")(m::Module, f::String)...
I get this warning: ``` ┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`. ``` when running the example https://github.com/cstjean/ScikitLearn.jl/blob/master/examples/Classifier_Comparison.ipynb.