I love Lisp and Scheme too. Though like sex at 19, nothing has ever felt quite like the first months with APL.
For "production" math research, nothing comes close to Haskell for me. Every time I consider straying, the ease of parallelism draws me back.
I have written a fair bit of Scheme, using my own preprocessor that avoids most parentheses. I stay clear of that loaded debate, this is for personal use. The code is poetic, though not as dense as APL or Haskell. As Bill Joy once opined, what you can fit on a screen matters.
My own favorite Haskell code is a very terse implementation of monadic parsing. Typed trees are not far off from strings, and then one has algebraic data types as parsing. (Pattern matching is parsing a bit at a time, without reifying the activity for program control.)
APL gets unexpected mileage from a core of array handling. I dream of a Lisp-like language tuned to parse algebraic data types as its core activity, with macros as its "middle of the plate" pitch rather than as a strapped-on afterthought. (I'm not trolling here, this is my honest opinion. In 10,000 runs of the simulation, I doubt Lisp macros would be this clumsy in most runs.)
Ultimately we all long for better language tools to express pattern as code. My electric guitar never sounded like what's in my head, and for code I'm still reaching too. Though APL was wonderful in its day.
Playing with J (~ APL) certainly feels magical (though I can never remember the syntax a day later) and APL like Lisp gets a lot of leverage from a powerful vocabulary on a rich data structure (arrays and lists respectively). However the "One Great Datastructure" flattens the domain and doesn't self-document, nor constrain you from unintended uses, the way a rich type system does, so I find reading and maintaining Lisp (and I assume the same applies to APL) to be frustrating and tedious.
Writing this, I'm reminded how J felt full of "tricks" much like using Perl: there are these tricks you can use to get the result you wanted that isn't necessarily the most faithful expression of the problem.
For "production" math research, nothing comes close to Haskell for me. Every time I consider straying, the ease of parallelism draws me back.
I have written a fair bit of Scheme, using my own preprocessor that avoids most parentheses. I stay clear of that loaded debate, this is for personal use. The code is poetic, though not as dense as APL or Haskell. As Bill Joy once opined, what you can fit on a screen matters.
My own favorite Haskell code is a very terse implementation of monadic parsing. Typed trees are not far off from strings, and then one has algebraic data types as parsing. (Pattern matching is parsing a bit at a time, without reifying the activity for program control.)
APL gets unexpected mileage from a core of array handling. I dream of a Lisp-like language tuned to parse algebraic data types as its core activity, with macros as its "middle of the plate" pitch rather than as a strapped-on afterthought. (I'm not trolling here, this is my honest opinion. In 10,000 runs of the simulation, I doubt Lisp macros would be this clumsy in most runs.)
Ultimately we all long for better language tools to express pattern as code. My electric guitar never sounded like what's in my head, and for code I'm still reaching too. Though APL was wonderful in its day.