(you may like that visual noise if the code finds more than 1 year's use)
Which matters more to you saving time or saving space?
On Tuesday, October 25, 2016 at 4:39:33 AM UTC-4, Martin Florek wrote:
>
> Thnaks, It is true, but when I apply @benchmark v3 is 6 times slower as
> v1, also has a large allocation and I do not want it. For me speed is
> important and v3 is not without visual noise, too. Any more thoughts?
>
> ben1 = @benchmark mapeBase_v1(a,f)
> BenchmarkTools.Trial:
> samples: 848
> evals/sample: 1
> time tolerance: 5.00%
> memory tolerance: 1.00%
> memory estimate: 32.00 bytes
> allocs estimate: 1
> minimum time: 4.35 ms (0.00% GC)
> median time: 5.87 ms (0.00% GC)
> mean time: 5.89 ms (0.00% GC)
> maximum time: 7.57 ms (0.00% GC)
>
> ben2 = @benchmark mapeBase_v3(a,f)
> BenchmarkTools.Trial:
> samples: 145
> evals/sample: 1
> time tolerance: 5.00%
> memory tolerance: 1.00%
> memory estimate: 977.03 kb
> allocs estimate: 14
> minimum time: 32.69 ms (0.00% GC)
> median time: 33.91 ms (0.00% GC)
> mean time: 34.55 ms (0.10% GC)
> maximum time: 49.03 ms (3.25% GC)
>
>
>
>
> On Tuesday, 25 October 2016 09:43:20 UTC+2, Jeffrey Sarnoff wrote:
>>
>> This may do what you want.
>>
>> function mapeBase_v3(actuals::Vector{Float64}, forecasts::Vector{Float64})
>> # actuals - actual target values
>> # forecasts - forecasts (model estimations)
>>
>> sum_reldiffs = sumabs((x - y) / x for (x, y) in zip(actuals, forecasts) if
>> x != 0.0) # Generator
>>
>> count_zeros = sum( map(x->(x==0.0), actuals) )
>> count_nonzeros = length(actuals) - count_zeros
>> sum_reldiffs, count_nonzeros
>> end
>>
>>
>>
>>
>> On Tuesday, October 25, 2016 at 3:15:54 AM UTC-4, Martin Florek wrote:
>>>
>>> Hi all,
>>> I'm new in Julia and I'm doing refactoring. I have the following
>>> function:
>>>
>>> function mapeBase_v1(A::Vector{Float64}, F::Vector{Float64})
>>> s = 0.0
>>> count = 0
>>> for i in 1:length(A)
>>> if(A[i] != 0.0)
>>> s += abs( (A[i] - F[i]) / A[i])
>>> count += 1
>>> end
>>> end
>>>
>>> s, count
>>>
>>> end
>>>
>>> I'm looking for a simpler variant which is as follows:
>>>
>>> function mapeBase_v2(A::Vector{Float64}, F::Vector{Float64})
>>> # A - actual target values
>>> # F - forecasts (model estimations)
>>>
>>> s = sumabs((x - y) / x for (x, y) in zip(A, F) if x != 0) # Generator
>>>
>>> count = length(A) # ???
>>> s, countend
>>>
>>>
>>> However with this variant can not determine the number of non-zero
>>> elements. I found option with length(A[A .!= 0.0]), but it has a large
>>> allocation. Please, someone knows a solution with generator, or variant v1
>>> is very good choice?
>>>
>>>
>>> Thanks in advance,
>>> Martin
>>>
>>>
