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Currently similar will return an array of a different type:
similar
from juliacall import Main as jl import numpy as np x = np.random.randn(5) y = jl.similar(x) print(jl.typeof(x)) # PyArray{Float64, 1, true, true, Float64} print(jl.typeof(y)) # Vector{Float64}
This can introduce some type instabilities in libraries due to the assumption that container type is preserved by similar.
I guess we just need the "optional methods" from here: https://docs.julialang.org/en/v1/manual/interfaces/#man-interface-array
The text was updated successfully, but these errors were encountered:
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Currently
similar
will return an array of a different type:This can introduce some type instabilities in libraries due to the assumption that container type is preserved by
similar
.I guess we just need the "optional methods" from here: https://docs.julialang.org/en/v1/manual/interfaces/#man-interface-array
The text was updated successfully, but these errors were encountered: