`pure=true` default to align with Base

I see why the pure keyword was added, but having pure=false contradicts Julia's behavior, which assumes mapped functions are pure. For instance:

julia> using SparseArrays

julia> A = sparse([1, 1, 2, 3], [1, 3, 2, 3], [3, 1, 2, 3])
3×3 SparseMatrixCSC{Int64, Int64} with 4 stored entries:
 3  ⋅  1
 ⋅  2  ⋅
 ⋅  ⋅  3

julia> map(x -> x^2 + rand(), A)
3×3 SparseMatrixCSC{Float64, Int64} with 9 stored entries:
 9.54687  0.85208  1.86548
 0.85208  4.31839  0.85208
 0.85208  0.85208  9.26578

This default behavior is also inconsistent with most programmers' expectations, as map is a functional construct and therefore tends to assume side-effect free functions. This could lead to bugs; it also means that any code using map on a vector of unknown type can't take advantage of the performance enhancements provided by PooledArrays, since pure is not a keyword for the map method in base. As a result, I propose defaulting to pure=true.

The relevant entry point is PooledArrays' map method with the pure keyword; compare its default with Base Julia's map behavior. Reproduce the issue's SparseArrays example, then inspect the surrounding implementation and any existing map coverage. Done means the default is aligned with Base and the example behavior is verified.