julia> typemax(Int64) 9223372036854775807
On Fri, Jan 24, 2014 at 1:08 PM, Joe Bogner <[email protected]> wrote: > Neat... > > julia> 9223372036854775807 > 9223372036854775807 > > julia> 9223372036854775807+1 > -9223372036854775808 > > Need to use BigInt > > julia> BigInt(9223372036854775807)+1 > 9223372036854775808 > > > > On Fri, Jan 24, 2014 at 12:56 PM, Dan Bron <[email protected]> wrote: >> What's the highest value a signed integer can represent on your platform >> (ie. 32 bit or 64 bit)? >> >> |>:{.i:_j1 >> 9223372036854775807 >> >> 1 + |>:{.i:_j1 NB. Now floating-point >> 9.22337e18 >> >> -Dan >> >> >> ----- Original Message --------------- >> >> Subject: Re: [Jchat] [Jprogramming] more fork examples >> From: Devon McCormick <[email protected]> >> Date: Fri, 24 Jan 2014 12:31:53 -0500 >> To: Chat forum <[email protected]> >> >> What's 2147483647+1 in Julia? >> >> >> On Fri, Jan 24, 2014 at 10:07 AM, Joe Bogner <[email protected]> wrote: >> >>> My experience with python is that it's difficult to set up an scipy >>> environment on windows. There are packaged solutions, like Anaconda[1] >>> that simplify it greatly, but it's still a 340MB download. I've >>> installed all the packages manually before and dealt with the >>> dependencies. It probably took about an hour of trial and error. My >>> install folder is 800MB >>> >>> It works well once it's up and running. I haven't had it break, but >>> I'm also afraid to update anything. Fortunately, it's a relatively >>> complete environment for what I'm using it for. >>> >>> I would not want to try and push it out to a team. >>> >>> R just works and it's package manager has never let me down. It's easy >>> to update packages and the dependencies are resolved. It's generally >>> fast enough for what I'm doing. >>> >>> I've played with Julia on and off over the past year and it's looking >>> more and more like a useful platform. There wasn't a pre-built 64-bit >>> binary as-of 6 months ago. It was released about 4 months ago. I read >>> this article yesterday that re-invigorated my interest. >>> http://www.evanmiller.org/why-im-betting-on-julia.html As a language >>> geek, it's neat to see what's really happening under the hood. It's >>> array handling is fairly clean >>> (http://docs.julialang.org/en/latest/manual/arrays/) >>> >>> >>> julia> [1 2 3] + 1 >>> 1x3 Array{Int32,2}: >>> 2 3 4 >>> >>> julia> [1 2 3] + [2 3 4] >>> 1x3 Array{Int32,2}: >>> 3 5 7 >>> >>> This made me cringe... Probably a slightly nicer way to do it: >>> >>> julia> map(x->length(x) > 0 ? first(x) : -1, map((y) -> find((x) -> >>> x==y,[1,2,3] >>> ),[1,2,5,1])) >>> >>> 4-element Array{Int32,1}: >>> 1 >>> 2 >>> -1 >>> 1 >>> >>> Compared to >>> >>> (1 2 3) i. (1 2 5 1) >>> 0 1 3 0 >>> >>> Sidenote: (Julia arrays are 1-based and I substituted -1 instead of >>> length for not found): >>> >>> That being said, it does have coroutines and worker processes, >>> http://docs.julialang.org/en/latest/manual/parallel-computing/ >>> >>> [1] - http://continuum.io/downloads >>> ---------------------------------------------------------------------- >>> For information about J forums see http://www.jsoftware.com/forums.htm >>> >> >> >> >> -- >> Devon McCormick, CFA >> ---------------------------------------------------------------------- >> For information about J forums see http://www.jsoftware.com/forums.htm >> ---------------------------------------------------------------------- >> For information about J forums see http://www.jsoftware.com/forums.htm ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
