pcolor(): Warning: The default `strides(a::AbstractArray)` implementation is deprecated .......

[cwb0]

julia> versioninfo()
Julia Version 0.7.0
Commit a4cb80f3ed (2018-08-08 06:46 UTC)
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: Intel(R) Core(TM) i5-4200U CPU @ 1.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-6.0.0 (ORCJIT, haswell)
Environment:
JULIA_EDITOR = "C:\Users\Carsten\AppData\Local\atom\app-1.30.0\atom.exe" -a
JULIA_NUM_THREADS = 2

I‘ve got the following warning applying pcolor():

julia> pcolor(a1,a2,a3)
┌ Warning: The default strides(a::AbstractArray) implementation is deprecated for general arrays.
│ Specialize strides(::Adjoint) if Adjoint indeed uses a strided representation in memory.
│ Warning: inappropriately implementing this method for an array type that does not use strided
│ storage may lead to incorrect results or segfaults.
│ caller = stride at abstractarray.jl:350 [inlined]
└ @ Core .\abstractarray.jl:350
┌ Warning: The default strides(a::AbstractArray) implementation is deprecated for general arrays.
│ Specialize strides(::Adjoint) if Adjoint indeed uses a strided representation in memory.
│ Warning: inappropriately implementing this method for an array type that does not use strided
│ storage may lead to incorrect results or segfaults.
│ caller = stride at abstractarray.jl:350 [inlined]
└ @ Core .\abstractarray.jl:350
┌ Warning: The default strides(a::AbstractArray) implementation is deprecated for general arrays.
│ Specialize strides(::Adjoint) if Adjoint indeed uses a strided representation in memory.
│ Warning: inappropriately implementing this method for an array type that does not use strided
│ storage may lead to incorrect results or segfaults.
│ caller = ip:0x0
└ @ Core :-1
PyObject <matplotlib.collections.PolyCollection object at 0x0000000026F8EEF0>

with

julia> a1
1×64 Adjoint{Float64,StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}}:

julia> a2
-0.4921875:0.015625:0.4921875

julia> a3
64×64 Adjoint{Float64,Array{Float64,2}}:

[cwb0]

same warnings for

pcolormesh(a1,a2,a3)

[cwb0]

To avoid the above mentioned warnings a workaround is (see example below) to convert the transposed array B of type: (Transpose{Float64,Array{Float64,2}}) to an array of type: Array{Float64,2}.

_ _ ()_ | A fresh approach to technical computing
() | () () | Documentation: https://docs.julialang.org
_ _ | | __ _ | Type "?" for help, "]?" for Pkg help.
| | | | | | |/ ` | |
| | || | | | (| | | Version 0.7.0 (2018-08-08 06:46 UTC)
/ |_'|||_'_| | Official http://julialang.org/ release
|__/ | x86_64-w64-mingw32

julia> using PyPlot

julia> A = rand(1:8,8,8)*1.0;

julia> B = transpose(A);

julia> C = convert(Array{Float64,2},B);

julia> figure("A")
Figure(PyObject <Figure size 640x478 with 0 Axes>)

julia> pcolor(A)
PyObject <matplotlib.collections.PolyCollection object at 0x0000000026EE04E0>

julia> figure("C")
Figure(PyObject <Figure size 640x478 with 0 Axes>)

julia> pcolor(C)
PyObject <matplotlib.collections.PolyCollection object at 0x000000002787E438>

julia> figure("B")
Figure(PyObject <Figure size 640x480 with 0 Axes>)

julia> pcolor(B)
┌ Warning: The default strides(a::AbstractArray) implementation is deprecated for general arrays.
│ Specialize strides(::LinearAlgebra.Transpose) if LinearAlgebra.Transpose indeed uses a strided representation in memory.
│ Warning: inappropriately implementing this method for an array type that does not use strided
│ storage may lead to incorrect results or segfaults.
│ caller = ip:0x0
└ @ Core :-1
PyObject <matplotlib.collections.PolyCollection object at 0x00000000278E4FD0>

The warning occurs only once.

julia> figure("B1")
Figure(PyObject <Figure size 640x480 with 0 Axes>)

julia> pcolor(B)
PyObject <matplotlib.collections.PolyCollection object at 0x00000000012B1E10>

julia>

Running the same command pcolor(B) again no warning appears anymore (why?).

[cwb0]

(why?)

[Nosferican]

Still persists (see JuliaLang/julia#25321 (comment) for solution). It is very prevalent when using p[:ax] with ::Adjoint... For now one has to Matrix(obj') in order to get it to work.