In master Julia the result is 3. I must have changed that when I reorganised the norm code. I think that 3 is the right answer anyway. In Julia [1 2 3] is a 1x3 matrix, i.e. not a vector. If you want it to behave as a vector, make it a vector. This causes some confusion when coming from MATLAB, but it is only in the transition until you get used to `Vector`s. I also think that having matrix and vector norm in the same function is the natural solution in Julia where so much is about dispatch.
2014-03-04 1:45 GMT+01:00 Miguel Bazdresch <eorli...@gmail.com>: > In Julia 0.2.1, I get 6.0. > > -- mb > > > On Mon, Mar 3, 2014 at 7:22 PM, Carlos Becker <carlosbec...@gmail.com>wrote: > >> My mistake there, I meant the L1 norm, re-typed: >> >> ----------------------------- >> X= [[1 2 3],[4 5 6]] >> >> # now, X[1,:] is 1x3 array, containing 1 2 3 >> >> # but let's peek at its L1-norm: >> norm( X[1,:], 1 ) # --> we get 3, where I would expect 6 (1+2+3) >> ----------------------------- >> >> can you try that on v0.2? I am on 0.3 from upstream. >> >> >> ------------------------------------------ >> Carlos >> >> >> On Tue, Mar 4, 2014 at 1:19 AM, Patrick O'Leary <patrick.ole...@gmail.com >> > wrote: >> >>> This is odd, as I get norm() working just fine with any of a row, >>> column, or vector, and all getting exactly the same result of 3.741... >>> (v0.2.0, on julia.forio.com, since it's quick for me to get to). Note >>> that it will return the L2 norm by default, exactly as MATLAB does. >>> Supplying a second argument with p in it (norm([1 2 3], 1)) will return the >>> p-norm, exactly like MATLAB. >>> >>> >>> On Monday, March 3, 2014 6:12:53 PM UTC-6, Carlos Becker wrote: >>>> >>>> Hello all, >>>> >>>> today I fought for an hour with a very simple piece of code, of the >>>> kind: >>>> >>>> ----------------------------- >>>> X= [[1 2 3],[4 5 6]] >>>> >>>> # now, X[1,:] is 1x3 array, containing 1 2 3 >>>> >>>> # but let's peek at its L1-norm: >>>> norm( X[1,:] ) # --> we get 3, where I would expect 6 (1+2+3) >>>> ----------------------------- >>>> >>>> I believe this comes back to the 'how 1xN matrices should be handled'. >>>> The point is that the current behaviour is totally non-intuitive for >>>> someone coming from Matlab, >>>> and having matrix and vector norms in the same function hides this (in >>>> this case) unwanted behavior. >>>> >>>> I am not sure what is the right way to deal with this, but seems like a >>>> hard wall that more than one >>>> will hit when coming from matlab-like backgrounds. >>>> >>>> Cheers. >>>> >>> >> > -- Med venlig hilsen Andreas Noack Jensen
