Mixing
Expanding Vector List Each by List of Instances - Julia
I would like to expand a vector of values each by a vector containing the number of each instance. I have come up with the following code which does the job but it seems like this is a common use so I am probably missing something.
valuelist = ["a","b","d","z"]
numberofinstance = [3,5,1,11]
valuevector = String
for i in 1:length(numberofinstance)
append!(valuevector , repeat([valuelist[i]], numberofinstance[i]))
end
julia expand
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
add a comment |
I would like to expand a vector of values each by a vector containing the number of each instance. I have come up with the following code which does the job but it seems like this is a common use so I am probably missing something.
valuelist = ["a","b","d","z"]
numberofinstance = [3,5,1,11]
valuevector = String
for i in 1:length(numberofinstance)
append!(valuevector , repeat([valuelist[i]], numberofinstance[i]))
end
julia expand
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22
add a comment |
I would like to expand a vector of values each by a vector containing the number of each instance. I have come up with the following code which does the job but it seems like this is a common use so I am probably missing something.
valuelist = ["a","b","d","z"]
numberofinstance = [3,5,1,11]
valuevector = String
for i in 1:length(numberofinstance)
append!(valuevector , repeat([valuelist[i]], numberofinstance[i]))
end
julia expand
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
I would like to expand a vector of values each by a vector containing the number of each instance. I have come up with the following code which does the job but it seems like this is a common use so I am probably missing something.
valuelist = ["a","b","d","z"]
numberofinstance = [3,5,1,11]
valuevector = String
for i in 1:length(numberofinstance)
append!(valuevector , repeat([valuelist[i]], numberofinstance[i]))
end
julia expand
julia expand
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
asked Jan 2 at 18:17
fsmartfsmart
1,27321738
1,27321738
I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22
add a comment |
I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22
I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22
I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22
add a comment |
1 Answer
1
active
oldest
votes
If you are fine with using a package (basically a stdlib), the function you are looking for is called inverse_rle in StatsBase.jl:
julia> using StatsBase
julia> inverse_rle(valuelist, numberofinstance)
20-element Array{String,1}:
"a"
"a"
"a"
"b"
"b"
"b"
"b"
"b"
"d"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
julia> @btime inverse_rle($valuelist, $numberofinstance);
76.799 ns (1 allocation: 240 bytes)
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
If you want to avoid packages, you could, in principle, broadcast repeat or ^ (powering) like so,
vcat(collect.(.^(valuelist, numberofinstance))...)
but I'd argue that this is relatively hard to parse and also slower than inverse_rle,
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime vcat(collect.(.^($valuelist, $numberofinstance))...)
472.615 ns (9 allocations: 800 bytes)
However, since Julia allows you to write fast loops you can easily define your own simple function. The following is much faster than your solution (as fast as the implementation in StatsBase):
function multiply(vs, ns)
r = Vector{String}(undef, sum(ns))
c = 1
@inbounds for i in axes(ns, 1)
for k in 1:ns[i]
r[c] = vs[i]
c += 1
end
end
r
end
Benchmark:
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime multiply($valuelist, $numberofinstance);
76.469 ns (1 allocation: 240 bytes)
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
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active
oldest
votes
If you are fine with using a package (basically a stdlib), the function you are looking for is called inverse_rle in StatsBase.jl:
julia> using StatsBase
julia> inverse_rle(valuelist, numberofinstance)
20-element Array{String,1}:
"a"
"a"
"a"
"b"
"b"
"b"
"b"
"b"
"d"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
julia> @btime inverse_rle($valuelist, $numberofinstance);
76.799 ns (1 allocation: 240 bytes)
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
If you want to avoid packages, you could, in principle, broadcast repeat or ^ (powering) like so,
vcat(collect.(.^(valuelist, numberofinstance))...)
but I'd argue that this is relatively hard to parse and also slower than inverse_rle,
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime vcat(collect.(.^($valuelist, $numberofinstance))...)
472.615 ns (9 allocations: 800 bytes)
However, since Julia allows you to write fast loops you can easily define your own simple function. The following is much faster than your solution (as fast as the implementation in StatsBase):
function multiply(vs, ns)
r = Vector{String}(undef, sum(ns))
c = 1
@inbounds for i in axes(ns, 1)
for k in 1:ns[i]
r[c] = vs[i]
c += 1
end
end
r
end
Benchmark:
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime multiply($valuelist, $numberofinstance);
76.469 ns (1 allocation: 240 bytes)
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
add a comment |
If you are fine with using a package (basically a stdlib), the function you are looking for is called inverse_rle in StatsBase.jl:
julia> using StatsBase
julia> inverse_rle(valuelist, numberofinstance)
20-element Array{String,1}:
"a"
"a"
"a"
"b"
"b"
"b"
"b"
"b"
"d"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
julia> @btime inverse_rle($valuelist, $numberofinstance);
76.799 ns (1 allocation: 240 bytes)
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
If you want to avoid packages, you could, in principle, broadcast repeat or ^ (powering) like so,
vcat(collect.(.^(valuelist, numberofinstance))...)
but I'd argue that this is relatively hard to parse and also slower than inverse_rle,
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime vcat(collect.(.^($valuelist, $numberofinstance))...)
472.615 ns (9 allocations: 800 bytes)
However, since Julia allows you to write fast loops you can easily define your own simple function. The following is much faster than your solution (as fast as the implementation in StatsBase):
function multiply(vs, ns)
r = Vector{String}(undef, sum(ns))
c = 1
@inbounds for i in axes(ns, 1)
for k in 1:ns[i]
r[c] = vs[i]
c += 1
end
end
r
end
Benchmark:
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime multiply($valuelist, $numberofinstance);
76.469 ns (1 allocation: 240 bytes)
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
add a comment |
If you are fine with using a package (basically a stdlib), the function you are looking for is called inverse_rle in StatsBase.jl:
julia> using StatsBase
julia> inverse_rle(valuelist, numberofinstance)
20-element Array{String,1}:
"a"
"a"
"a"
"b"
"b"
"b"
"b"
"b"
"d"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
julia> @btime inverse_rle($valuelist, $numberofinstance);
76.799 ns (1 allocation: 240 bytes)
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
If you want to avoid packages, you could, in principle, broadcast repeat or ^ (powering) like so,
vcat(collect.(.^(valuelist, numberofinstance))...)
but I'd argue that this is relatively hard to parse and also slower than inverse_rle,
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime vcat(collect.(.^($valuelist, $numberofinstance))...)
472.615 ns (9 allocations: 800 bytes)
However, since Julia allows you to write fast loops you can easily define your own simple function. The following is much faster than your solution (as fast as the implementation in StatsBase):
function multiply(vs, ns)
r = Vector{String}(undef, sum(ns))
c = 1
@inbounds for i in axes(ns, 1)
for k in 1:ns[i]
r[c] = vs[i]
c += 1
end
end
r
end
Benchmark:
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime multiply($valuelist, $numberofinstance);
76.469 ns (1 allocation: 240 bytes)
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
If you are fine with using a package (basically a stdlib), the function you are looking for is called inverse_rle in StatsBase.jl:
julia> using StatsBase
julia> inverse_rle(valuelist, numberofinstance)
20-element Array{String,1}:
"a"
"a"
"a"
"b"
"b"
"b"
"b"
"b"
"d"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
"z"
julia> @btime inverse_rle($valuelist, $numberofinstance);
76.799 ns (1 allocation: 240 bytes)
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
If you want to avoid packages, you could, in principle, broadcast repeat or ^ (powering) like so,
vcat(collect.(.^(valuelist, numberofinstance))...)
but I'd argue that this is relatively hard to parse and also slower than inverse_rle,
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime vcat(collect.(.^($valuelist, $numberofinstance))...)
472.615 ns (9 allocations: 800 bytes)
However, since Julia allows you to write fast loops you can easily define your own simple function. The following is much faster than your solution (as fast as the implementation in StatsBase):
function multiply(vs, ns)
r = Vector{String}(undef, sum(ns))
c = 1
@inbounds for i in axes(ns, 1)
for k in 1:ns[i]
r[c] = vs[i]
c += 1
end
end
r
end
Benchmark:
julia> @btime yoursolution($valuelist, $numberofinstance);
693.329 ns (13 allocations: 1.55 KiB)
julia> @btime multiply($valuelist, $numberofinstance);
76.469 ns (1 allocation: 240 bytes)
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
edited Jan 2 at 19:24
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
answered Jan 2 at 19:02
crstnbrcrstnbr
4,46811124
4,46811124
add a comment |
add a comment |
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I found the function in StatsBase.jl. See my updated answer.
– crstnbr
Jan 2 at 19:22