This is Matlab's code:
[Q,S] = svd(A,'econ'); %S is always square.
if ~isempty(S)
S = diag(S);
tol = max(size(A)) * S(1) * eps(class(A));
r = sum(S > tol);
Q = Q(:,1:r);
end
Op maandag 30 juni 2014 07:53:19 UTC+2 schreef Andre P.:
>
> I have some Matlab code I'm porting to Julia
>
> BiasHN = rand(HN(i+1),1)*2 -1;
> BiasHN = orth(BiasHN);
>
> Was the equivalent of the orth() from Matlab added to Julia? Can't seem to
> find it.
>
> Andre
>
> On Thursday, April 3, 2014 10:32:31 PM UTC+9, Alan Edelman wrote:
>>
>> Maybe something like this
>>
>> function orth(A,thresh=eps(A[1]))
>> (U,S)=svd(A)
>> U[:, S.>S[1]*thresh]
>> end
>>
>> orth(float(A))
>>
>> 20x4 Array{Float64,2}:
>>
>> -0.223607 -0.213651 0.183753 0.265684
>>
>> -0.223607 -0.213651 0.183753 0.265684
>>
>> -0.223607 -0.213651 0.183753 0.265684
>>
>> -0.223607 -0.213651 0.183753 0.265684
>>
>> -0.223607 -0.213651 0.183753 0.265684
>>
>> -0.223607 0.0371419 -0.372503 0.0993058
>>
>> -0.223607 0.0371419 -0.372503 0.0993058
>>
>> -0.223607 0.0371419 -0.372503 0.0993058
>>
>> -0.223607 0.0371419 -0.372503 0.0993058
>>
>> -0.223607 0.0371419 -0.372503 0.0993058
>>
>> -0.223607 0.350358 0.163883 -0.0197973
>>
>> -0.223607 0.350358 0.163883 -0.0197973
>>
>> -0.223607 0.350358 0.163883 -0.0197973
>>
>> -0.223607 0.350358 0.163883 -0.0197973
>>
>> -0.223607 0.350358 0.163883 -0.0197973
>>
>> -0.223607 -0.173849 0.0248676 -0.345193
>>
>> -0.223607 -0.173849 0.0248676 -0.345193
>>
>> -0.223607 -0.173849 0.0248676 -0.345193
>>
>> -0.223607 -0.173849 0.0248676 -0.345193
>>
>> -0.223607 -0.173849 0.0248676 -0.345193
>>
>>
>>
>>
>> On Thursday, April 3, 2014 9:23:14 AM UTC-4, Alan Edelman wrote:
>>>
>>> I would use the svd with a threshold based on the norm
>>> and optionally adjustable
>>>
>>>
