On Thursday, November 6, 2014 9:14:10 AM UTC-6, Sebastian Good wrote:
>
> Working through the excellent coursera machine-learning course, I found
> myself using the row-wise (axis-wise) dot product in Octave, but found
> there was no obvious equivalent in Julia.
>
> In Octave/Matlab, one can call dot(a,b,2) to get the row-wise dot product
> of two mxn matrices, returned as a new column vector of size mx1.
>
> Even though Julia makes for loops faster, I like sum(dot(a,b,2)) for its
> concision over the equivalent array comprehension or explicit for loop.
>
> Hopefully I'm just missing an overload or alternate name?
>
julia> a = rand(10,4)
10x4 Array{Float64,2}:
0.134279 0.135088 0.33185 0.956108
0.977812 0.219557 0.887589 0.468597
0.69524 0.310889 0.449669 0.717189
0.385896 0.675195 0.0810221 0.179553
0.717348 0.138556 0.52147 0.458516
0.821631 0.337048 0.367002 0.320554
0.531433 0.0298744 0.344748 0.722242
0.708596 0.550999 0.629017 0.787594
0.803008 0.380515 0.729874 0.744713
0.166205 0.5589 0.605327 0.246186
julia> b = randn(10,4)
10x4 Array{Float64,2}:
0.551047 -0.284285 -1.33048 0.0216755
-1.16133 -0.552537 0.395243 -1.72303
-0.0181444 -0.481539 -0.985497 0.352999
1.20222 -0.557973 0.428804 -1.1013
2.31078 0.0909548 0.329372 0.651853
0.341906 -0.109811 -0.360118 0.550494
0.988644 1.02413 0.570208 0.48143
-1.75465 0.147909 -1.35159 0.89136
-0.105066 -1.04501 -0.682836 0.600948
0.556118 -1.24914 -2.45667 -1.02942
julia> sum(a .* b,2)
10x1 Array{Float64,2}:
-0.385205
-1.71347
-0.3523
-0.0758094
2.14088
0.288209
1.10028
-1.30999
-0.532863
-2.34624
