> > My strong expectation is that this is a case of refrigerator blindness.
Small scale snow-blindness? > > On Wed, Jul 20, 2011 at 9:22 AM, Marco Turchi <[email protected]>wrote: > >> Hi >> you are right about the sparse vector issue... but I'm constructing distV >> in the same way changing only + and - in the variable mean. In both the >> cases, I should have the same number of entries in the final vector. >> >> Thanks a lot for your help >> Marco >> >> >> On 20 Jul 2011, at 17:42, Ted Dunning wrote: >> >> You constructed the first vector with a dimension of 1. It looks like you >>> constructed the second one with a larger dimension of 2. >>> >>> When you offset a sparse vector, all of the zeros become non-zero and the >>> vector becomes dense. This results in a bunch of cells being created. >>> >>> On Wed, Jul 20, 2011 at 6:28 AM, marco turchi <[email protected] >>> >wrote: >>> >>> Dear All, >>>> I have a strange behaviour when I use the method Plus for Vector. >>>> >>>> I have a RandomAccessSparseVector vector, if I add a positive number, I >>>> got >>>> a new Vector where each element is the sum of the old value plus the >>>> positive number. While if I add a negative number, the new vector has 1 >>>> more >>>> entry: >>>> >>>> >>>> RandomAccessSparseVector distV = new RandomAccessSparseVector(1); >>>> distV.setQuick(0,1); >>>> double mean = 1; >>>> RandomAccessSparseVector app = >>>> (RandomAccessSparseVector)(**distV.plus(mean)); >>>> >>>> the output is >>>> {0:2.0} >>>> >>>> if I have >>>> double mean = -1; >>>> RandomAccessSparseVector app = >>>> (RandomAccessSparseVector)(**distV.plus(mean)); >>>> >>>> the output is >>>> {1:1.0,0:-1.0} >>>> >>>> For sure I'm doing something wrong. Do you have any ideas where the >>>> problem >>>> is? >>>> >>>> Thanks a lot in advance >>>> Marco >>>> >>>> >> >
