R conflating length 1 vectors and scalars is something to avoid. MATLAB does the same thing, and it was a bad idea there, too. Perl had the same error where it autoflattened an array of arrays unless you carefully inserted reference marks. So much of programming is getting data into the appropriate structure, and anything that gets in the way is a problem.
Boxing and unboxing is much more complicated than you would first think because of arrays. Say I have a class A with a subclass B. I can put an instance of B in an array of A. But when you say double[], you probably want a contiguous hunk of memory directly storing values. C++ fully exposes this semantic difference. Julia began its type system by insisting on unboxed arrays of doubles. Java compromised between making numeric computing not ridiculously inefficient and not complicating its semantics enormously.
Your gripe about Number not having any methods is spot on, and is why Stepanov invented the math that led to the Standard Template Library in C++ and part of why Common Lisp went with multiple dispatch in CLOS. This is a ubiquitous problem with single dispatch object systems.
How does it work in MATLAB and Perl? In R, they're pretty upfront about the fact that there's really no such thing as a scalar, but you can emulate it with a length-1 vector.
I'll definitely have to think about how I want data laid out for matrices and things. Lots of things to consider when you want to balance performance and syntax, etc.
What are your opinions on single vs. multiple dispatch mechanisms?
MATLAB does the same thing as R (or really, historically, R does the same thing as MATLAB): scalars are length 1 vectors. Perl 5 doesn't do that, but if you write @(1, 2, @(3, 4)), which in most languages would give you a list of length three containing two scalars and another list, you instead get a list of length four.
These choices make certain programming tasks more straightforward at the expense of all other programming tasks. Which is fine if you know the language is meant for just those tasks.
For single vs multiple dispatch, multiple dispatch is the clear winner in all respects except familiarity is multiple dispatch.
For balancing syntax, I remember the BitC folks saying that their best decision was using S-expressions for syntax until the language semantics stabilized, because they ended up changing deep things that would have been a real pain if they had a more structured syntax. Then they built a syntax besides S-expressions after the semantics stabilized.
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R conflating length 1 vectors and scalars is something to avoid. MATLAB does the same thing, and it was a bad idea there, too. Perl had the same error where it autoflattened an array of arrays unless you carefully inserted reference marks. So much of programming is getting data into the appropriate structure, and anything that gets in the way is a problem.
Boxing and unboxing is much more complicated than you would first think because of arrays. Say I have a class A with a subclass B. I can put an instance of B in an array of A. But when you say double[], you probably want a contiguous hunk of memory directly storing values. C++ fully exposes this semantic difference. Julia began its type system by insisting on unboxed arrays of doubles. Java compromised between making numeric computing not ridiculously inefficient and not complicating its semantics enormously.
Your gripe about Number not having any methods is spot on, and is why Stepanov invented the math that led to the Standard Template Library in C++ and part of why Common Lisp went with multiple dispatch in CLOS. This is a ubiquitous problem with single dispatch object systems.
How does it work in MATLAB and Perl? In R, they're pretty upfront about the fact that there's really no such thing as a scalar, but you can emulate it with a length-1 vector.
I'll definitely have to think about how I want data laid out for matrices and things. Lots of things to consider when you want to balance performance and syntax, etc.
What are your opinions on single vs. multiple dispatch mechanisms?
MATLAB does the same thing as R (or really, historically, R does the same thing as MATLAB): scalars are length 1 vectors. Perl 5 doesn't do that, but if you write
@(1, 2, @(3, 4)), which in most languages would give you a list of length three containing two scalars and another list, you instead get a list of length four.These choices make certain programming tasks more straightforward at the expense of all other programming tasks. Which is fine if you know the language is meant for just those tasks.
For single vs multiple dispatch, multiple dispatch is the clear winner in all respects except familiarity is multiple dispatch.
For balancing syntax, I remember the BitC folks saying that their best decision was using S-expressions for syntax until the language semantics stabilized, because they ended up changing deep things that would have been a real pain if they had a more structured syntax. Then they built a syntax besides S-expressions after the semantics stabilized.