stillyslalom

Long ago, I trawled through Matlab's docs to come up with a set of Julia packages matching what's build into Matlab: https://discourse.julialang.org/t/julia-for-matlab-users-clu...

I don't think you'd actually want to include each of those packages in a standard distro: does the average user really need to programmatically send emails or deal with Voronoi tessellations? Probably not, but I still think there's value in a batteries-included approach, especially when working with students.

Take a look at DataFramesMeta for nicer manipulation of Julia's dataframes. Your example would look like

  julia> df = DataFrame(y = rand(10^6), filter=randn(10^6));

  julia> @transform!(df, :x = cumsum(:y .* :filter))
  1000000×3 DataFrame
       Row │ y          filter      x
           │ Float64    Float64     Float64
  ─────────┼────────────────────────────────────
         1 │ 0.0726663   1.7213       0.125081
         2 │ 0.183898   -0.392131     0.0529686
         3 │ 0.150274    1.08083      0.21539
      ⋮    │     ⋮          ⋮            ⋮

It's particularly nice in conjunction with @chain [1].

[1] https://juliadata.github.io/DataFramesMeta.jl/dev/#Chaining-...

For long-tail adverse events? It's easy to engineer power distribution systems for the average case, but unless we accept occasional brownouts as a cost of doing business, we need to build robustness into our generation fleet. Let's say we get another Krakatoa-scale eruption that reduces insolation (and thus drops solar & wind output while increasing heating demand). Some amount of firm generation (hydro, gas peaker, nuclear) is insurance against correlated failure in the global climate system.

iPads can run out of battery or get smashed in turbulence or fall prey to bugs/malware; old-fashioned steam gauges cannot. The FAA's regulations are written in blood - the aviation fatality rate has fallen sharply over the years [0] thanks to a combination of technological advancement and regulation. Aircraft builders are still free to do pretty much whatever they want within the 'experimental' category, provided they mount a placard informing occupants that the aircraft is experimental.

[0] https://aviation-safety.net/graphics/infographics/Fatal-Acci...

You may want to look at [DaemonMode.jl](https://github.com/dmolina/DaemonMode.jl), which spins up a persistent Julia process in the background so you don't have to pay the TTFP penalty more than once, even when shell-scripting.

Comparing OpenBLAS and MKL with `peakflops` in Julia, there's definitely an advantage for MKL:

    julia> using LinearAlgebra

    julia> BLAS.vendor()
    :openblas64

    julia> BLAS.set_num_threads(1)

    julia> peakflops()
    3.9023447970402664e10


    julia> using LinearAlgebra
    
    julia> BLAS.vendor()
    :mkl
    
    julia> BLAS.set_num_threads(1)
    
    julia> peakflops()
    4.8113846984735275e10

That's close to the ~50 Gflops I saw in @celrod's benchmarks.

The current market doesn't price the externalities of carbon emissions. Without accurate pricing, market forces will stall some distance away from the optimal level of emissions, and we'll be worse off. Governments are the only entities powerful enough to solve such a widely-distributed coordination problem, and properly-functioning markets are contingent on properly-functioning governments.

This presentation is more than five years old, and some of the details have changed. See https://julialang.org/learning/ for more up-to-date introductory material.

Generalized nullables exist in Base already (http://docs.julialang.org/en/release-0.4/manual/types/#nulla...), unless you had something else in mind.

I've seen a decent amount of chatter over the past year on the Julia mailing list from people integrating Julia into production. It's still in the beta stage, though, so risk-averse corporate users are generally being advised to hold tight until 1.0 is released. This (somewhat outdated) thread should give you some idea of where things are headed: https://groups.google.com/d/topic/julia-users/2mR24E0EtIg/di...

Unfortunately, the series is no longer available on Netflix due to contract expiration.