Need help with array calculation

I would like to ask for help about array calculation

I want to plot contourline of f in which:

    f =  q + p*ln(p )

To do that,

    n = 100
    p = range(0, stop = 200, length =n )
    q = range(0, stop = 200, length = n)
    p_grid = repeat(p, 1, n)
    q_grid = repeat(q', n, 1)

Then, how to generate f_grid? ( f = q + p*ln(p ))
If possible, I can use PyPlot to plot:

  contour(p_grid, q_grid, f_grid, levels=0);

( in case of f2 : f2 = q²+ p*(p - 1)
I could create: f2_grid = (q_grid.^2 + p_grid.^2 - p_grid)

First, let’s define f as an actual function:

julia> f = (x, y) -> x + y * log(y)
#11 (generic function with 1 method)

You can broadcast this function over p and q to create a grid:

julia> f.(p, q')
100×100 Array{Float64,2}:

But you actually don’t need to! In fact, Plots.jl already knows how to plot the contour of a function if you just pass it the input vectors p and q and the function itself:

julia> using Plots

julia> n = 100

julia> q = range(0, stop = 200, length = n)

julia> p = range(0, stop = 200, length =n )

julia> f = (x, y) -> x + y * log(y)
#11 (generic function with 1 method)

julia> contour(p, q, f)

Note that we also don’t need to generate p_grid or q_grid because Plots.jl is smart enough to work directly from the vectors.


Because of the way broadcasting works you very rarely need to define grids like p_grid and q_grid. So if you find yourself using repeat on a vector, there’s a good chance you’re doing something unnecessary.

In fact the same is true for both Matlab and numpy too, so this technique is quite outdated these days.


Fantastic! Thank you very much for you quick reply.
I have only used PyPlot. This may makes me switch to Plots!