Yes, this is nice.
I had expected, that
b=reshape(a, ...)
is equivalent to
b=reshape(copy(a), ...)
i.e. changing the values in b wouldn't be visible in a. And that a function
creating only a new binding to the same values would be reshape! Compare
also with resize!
But anyway, great. Now I can get Matlab-type "linear indices":
julia> vector(a)=reshape(a, prod(size(a)))
vector (generic function with 1 method)
julia> a=[1 2; 3 4; 5 6]
3x2 Array{Int64,2}:
1 2
3 4
5 6
julia> vector(a)[3]=0
0
julia> a
3x2 Array{Int64,2}:
1 2
3 4
0 6
Am Samstag, 11. Oktober 2014 22:33:30 UTC+2 schrieb Peter Simon:
>
> It's not necessary because you can assign the result of reshape to the
> same variable with virtually no overhead:
>
> julia> a = rand(1000,100,100);
>
> julia> @time a = reshape(a,prod(size(a)));
> elapsed time: 1.1732e-5 seconds (336 bytes allocated)
>
> --Peter
>
> On Saturday, October 11, 2014 1:20:13 PM UTC-7, Stephan Buchert wrote:
>>
>> julia> a=[1 2; 3 4; 5 6]
>> 3x2 Array{Int64,2}:
>> 1 2
>> 3 4
>> 5 6
>>
>> julia> b=reshape(a, prod(size(a)));
>>
>> julia> b[3]=0
>> 0
>>
>> julia> a
>> 3x2 Array{Int64,2}:
>> 1 2
>> 3 4
>> 0 6
>>
>>
