Plotting for weighted bases

[TSGut]

See JuliaApproximation/MultivariateOrthogonalPolynomials.jl#73 (comment) and JuliaApproximation/MultivariateOrthogonalPolynomials.jl#73 (comment)

So I think this does actually just work as you said @dlfivefifty. At least testing it for weighted Zernike and weighted Jacobi gives the expected correct plots.

[codecov]

Codecov Report

Merging #96 (fc2f50e) into master (f3e0d96) will increase coverage by 1.18%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master      #96      +/-   ##
==========================================
+ Coverage   89.58%   90.77%   +1.18%     
==========================================
  Files           7        7              
  Lines         509      531      +22     
==========================================
+ Hits          456      482      +26     
+ Misses         53       49       -4     

Impacted Files	Coverage Δ
src/plotting.jl	81.25% <100.00%> (+2.67%)	⬆️
src/ContinuumArrays.jl	86.20% <0.00%> (+0.49%)	⬆️
src/operators.jl	82.60% <0.00%> (+14.60%)	⬆️

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[dlfivefifty]

Can you add tests? See

ContinuumArrays.jl/test/runtests.jl

Line 600 in f3e0d96

@testset "Plotting" begin

We probably want to add tests to the quick-and-dirty weighted Chebyshev defined above

ContinuumArrays.jl/test/runtests.jl

Line 515 in f3e0d96

wT = w .* T

[TSGut]

Yes, will do.

[TSGut]

This works for finite case and PaddedLayout infinite case. I'm not sure if there is an easy way to make this work for more generic infinite case of e.g. broadcast vectors as well but that doesn't seem supported for the unweighted bases either so that's probably fine for now.

[dlfivefifty]

Can you bump the patch version so I can merge and tag?

[TSGut]

I guess 0.7.5 is ok? done.