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I was a huge fan of Matlab way back. I wrote a hundred small Matlab programs for usage in the research department of the company I worked in. Doing data operati

I was a huge fan of Matlab way back. I wrote a hundred small Matlab programs for usage in the research department of the company I worked in. Doing data operations in Matlab was way more elegant than in say, Numpy which I tried later. Development was fast and ergonomics were good. After using Ruby for years, returning to Matlab style code in Julia felt somewhat awkward. Instead of my_array.length you have length(my_array). In my personal preference the method call is just a nicer way of doing the same thing. The single-instruction-multiple-data or dot notation sometimes worked and sometimes didn't, so you had to resort to loops anyway. % Julia a=[1 2 3 4] a.^2 log.(a) # Ruby a=[1,2,3,4] a.map{|element| element.pow(2)} a.map{|element| Math.log(element)} Ruby and map or each have their verbosity but overall it feels a more robust "hammer" for general programming tasks. On the other hand, Julia can be really dense and still easy to understand. Other languages of course take some of these things even further. Maybe some day I will find an ergonomics and nicety first successor to both. Plotting with two Y axes or generating histograms in Julia was also way harder than I remember it being in Matlab. Also manually having to load the file before every run to see the changes in action added a lot of overhead to the workflow. The workflow I was used to in Matlab involved very frequent making changes to code, running of the code that usually made some plot. Which is one command in Matlab, and plotting was fast, in 2001 already, on Windows NT 4. In Julia, you have to first load the modified file, then run it. Plotting takes a long time. One just can't get nearly as productive with it in 2021, compared to Matlab of 2001 vintage. What language would I pick if I had to do some quick analysis from some tables downloaded from the internet? Probably Julia still. If I had free access to Matlab, I would probably use it though.

jhgb 6y ago
> Instead of my_array.length you have length(my_array). In my personal preference the method call is just a nicer way of doing the same thing. Well...they're both method calls, aren't they? (So they're both the nicer way?)
- leephillips 6y ago
  Those who are attached to the class-based OOP model used, for example, in Python will find the dot notation more natural. But Julia’s multiple dispatch is a superset of this, and unarguably more powerful and flexible. Python OOP leads to monstrosities like >>> ', '.join(['1', '2', '3']) '1, 2, 3' >>> '1, 2, 3'.split(', ') ['1', '2', '3']
  - deetsb 6y ago
    As I’m clearly missing the bigger picture, what do you find to be super offensive about this? I read the first as the concat symbol applied to an iterable leads to string concated by the concat symbol. I read the second as an iterable broken by split symbol leads to an iterable of the chunks.
    - leephillips 6y ago
      It’s hard to remember what order to put things in, because the two methods follow opposite conventions. And that’s because this type of OO design has no obvious method of organization. In the first case, I want to do something to a list: join it into a string. So, clearly, I need a list method? But no, I need to engage in some form of indirection; for some reason, I need to reach for a string method. Even if there is no string that I want to use as a delimiter. In that case, I need to use a string method on an empty string. OK, I’ll play along. Now I want to take the string and split it into an array. Now that I’ve been educated, I know better than to try the sensible thing. Pre-enlightenment, I would have reached for a method applied to the thing that I wanted to transform. But now I know I should think backwards, and use a method applied to the delimiter. OOPs.
      - leephillips 6y ago
        Here it is in Julia: julia> join([1 2 3], ", ") "1, 2, 3" julia> split("1, 2, 3", ", ") 3-element Vector{SubString{String}}: "1" "2" "3" Note how they are both functions. The data that they operate on is the first argument, in both cases. The optional second argument is the obvious next most important thing, the delimiter. Other optional arguments come after that. There is nothing to remember, because it makes sense.
vchuravy 6y ago
Broadcasting and map are two different operations. If all the inouts have the same shape broadcast is equivalent to map, but in Julia you can also just use map. `map(el->el^2, a)` and inspired by Ruby ``` map(a) do element log(element) end ``` The latter being syntax sugar for the former.
leephillips 6y ago
The standard way to make a histogram in Julia is histogram(data) Using the latest version (1.6 - although 1.6.1 just came out) the time to first plot is just a few seconds. After that, plotting in the REPL is instantaneous. I probably don’t understand what you’re getting at when you speak of making frequent changes to code. REPL-based development in Julia is excellent, and there are Pluto notebooks as well.
- Gravityloss 6y ago
  The way I would like to work is to have the repl open on the left hand side of the screen and code editor (like Sublime text, I'm sure many use Vim) on the right hand side. I would run the code in repl (just using up-arrow and enter), get some plot, modify the code in the editor, save it, and rerun it repl. Repl is used for connecting inputs to the program, not for editing. Often times you want to develop some small program that is part of a bigger program. So you run the big program up to the point it calls the small program. Or you run with some mock data. Then you have all your inputs for the small program, so you can start iterating it. Run - observe - edit - run - observe - edit. In Matlab this worked because it detected if the file had changed, and reloaded it. You didn't specifically have to call load("my_function.m") before every call to it. This means you can just lift code from the big program and iterate on it in repl.
  - rsfern 6y ago
    Check out Revise.jl, it enables this workflow, and it’s awesome. https://docs.julialang.org/en/v1/manual/workflow-tips/#Revise-based-workflows https://docs.julialang.org/en/v1/manual/workflow-tips/#Revis...
    - leephillips 6y ago
      Also, my Julia REPL is in a term buffer in vim, and I communicate with it (in both directions) from my editing buffer using the vim-sendtowindow plugin.
  - deleted 6y ago
    [deleted]

jhgb 6y ago

> Instead of my_array.length you have length(my_array). In my personal preference the method call is just a nicer way of doing the same thing. Well...they're both method calls, aren't they? (So they're both the nicer way?)

leephillips 6y ago
Those who are attached to the class-based OOP model used, for example, in Python will find the dot notation more natural. But Julia’s multiple dispatch is a superset of this, and unarguably more powerful and flexible. Python OOP leads to monstrosities like >>> ', '.join(['1', '2', '3']) '1, 2, 3' >>> '1, 2, 3'.split(', ') ['1', '2', '3']
- deetsb 6y ago
  As I’m clearly missing the bigger picture, what do you find to be super offensive about this? I read the first as the concat symbol applied to an iterable leads to string concated by the concat symbol. I read the second as an iterable broken by split symbol leads to an iterable of the chunks.
  - leephillips 6y ago
    It’s hard to remember what order to put things in, because the two methods follow opposite conventions. And that’s because this type of OO design has no obvious method of organization. In the first case, I want to do something to a list: join it into a string. So, clearly, I need a list method? But no, I need to engage in some form of indirection; for some reason, I need to reach for a string method. Even if there is no string that I want to use as a delimiter. In that case, I need to use a string method on an empty string. OK, I’ll play along. Now I want to take the string and split it into an array. Now that I’ve been educated, I know better than to try the sensible thing. Pre-enlightenment, I would have reached for a method applied to the thing that I wanted to transform. But now I know I should think backwards, and use a method applied to the delimiter. OOPs.
    - leephillips 6y ago
      Here it is in Julia: julia> join([1 2 3], ", ") "1, 2, 3" julia> split("1, 2, 3", ", ") 3-element Vector{SubString{String}}: "1" "2" "3" Note how they are both functions. The data that they operate on is the first argument, in both cases. The optional second argument is the obvious next most important thing, the delimiter. Other optional arguments come after that. There is nothing to remember, because it makes sense.

vchuravy 6y ago

Broadcasting and map are two different operations. If all the inouts have the same shape broadcast is equivalent to map, but in Julia you can also just use map. `map(el->el^2, a)` and inspired by Ruby ``` map(a) do element log(element) end ``` The latter being syntax sugar for the former.

leephillips 6y ago

The standard way to make a histogram in Julia is histogram(data) Using the latest version (1.6 - although 1.6.1 just came out) the time to first plot is just a few seconds. After that, plotting in the REPL is instantaneous. I probably don’t understand what you’re getting at when you speak of making frequent changes to code. REPL-based development in Julia is excellent, and there are Pluto notebooks as well.

Gravityloss 6y ago
The way I would like to work is to have the repl open on the left hand side of the screen and code editor (like Sublime text, I'm sure many use Vim) on the right hand side. I would run the code in repl (just using up-arrow and enter), get some plot, modify the code in the editor, save it, and rerun it repl. Repl is used for connecting inputs to the program, not for editing. Often times you want to develop some small program that is part of a bigger program. So you run the big program up to the point it calls the small program. Or you run with some mock data. Then you have all your inputs for the small program, so you can start iterating it. Run - observe - edit - run - observe - edit. In Matlab this worked because it detected if the file had changed, and reloaded it. You didn't specifically have to call load("my_function.m") before every call to it. This means you can just lift code from the big program and iterate on it in repl.
- rsfern 6y ago
  Check out Revise.jl, it enables this workflow, and it’s awesome. https://docs.julialang.org/en/v1/manual/workflow-tips/#Revise-based-workflows https://docs.julialang.org/en/v1/manual/workflow-tips/#Revis...
  - leephillips 6y ago
    Also, my Julia REPL is in a term buffer in vim, and I communicate with it (in both directions) from my editing buffer using the vim-sendtowindow plugin.
- deleted 6y ago
  [deleted]