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  • pdf文档 Julia v1.2.0 Documentation

    previously this could result in a completely different value with a different precision (#31310). • mapreduce now accepts mul�ple iterators, similar to map (#31532). • filter now supports SkipMissing-wrapped Int64},1}}(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base
    0 码力 | 1250 页 | 4.29 MB | 1 年前
    3

  • pdf文档 Julia 1.2.0 DEV Documentation

    previously this could result in a completely different value with a different precision (#31310) • mapreduce now accept mul�ple iterators, similar to map (#31532). LinearAlgebra • Added keyword arguments Int64},1}}(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base
    0 码力 | 1252 页 | 4.28 MB | 1 年前
    3

  • pdf文档 julia 1.10.10

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> sum(x) 6 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base jl:278; randCHAPTER 32. PROFILING 405 [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1692 页 | 6.34 MB | 3 月前
    3

  • pdf文档 Julia 1.10.9

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> sum(x) 6 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base jl:278; randCHAPTER 32. PROFILING 405 [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1692 页 | 6.34 MB | 3 月前
    3

  • pdf文档 Julia v1.1.1 Documentation

    maximum(skipmissing([3, missing, 2, 1])) 3 julia> mean(skipmissing([3, missing, 2, 1])) 2.0 julia> mapreduce(sqrt, +, skipmissing([3, missing, 2, 1])) 4.146264369941973 Use collect to extract non-missing /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1216 页 | 4.21 MB | 1 年前
    3

  • pdf文档 Julia 1.1.0 Documentation

    maximum(skipmissing([3, missing, 2, 1])) 3 julia> mean(skipmissing([3, missing, 2, 1])) 2.0 julia> mapreduce(sqrt, +, skipmissing([3, missing, 2, 1])) 4.146264369941973 Use collect to extract non-missing /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1214 页 | 4.21 MB | 1 年前
    3

  • pdf文档 Julia v1.7.3 Documentation

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1378 页 | 4.74 MB | 1 年前
    3

  • pdf文档 Julia 1.8.0 DEV Documentation

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1463 页 | 5.01 MB | 1 年前
    3

  • pdf文档 Julia 1.7.0 Documentation

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1378 页 | 4.74 MB | 1 年前
    3

  • pdf文档 Julia 1.7.2 Documentation

    skipmissing(Union{Missing, Int64}[3, missing, 2, 1]) julia> maximum(x) 3 julia> mean(x) 2.0 julia> mapreduce(sqrt, +, x) 4.146264369941973 Objects created by calling skipmissing on an array can be indexed /reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinear,... 3 ./reduce.jl:426; mapreduce_impl(::Base.#identity, ::Base.#scalarmax, ::Array{F... 25 ./reduce.jl:428; mapreduce_impl(::Base ::Ptr... 310 ./random.jl:278; rand [....] 2893 ./REPL[1]:3; myfunc() 2893 ./reduce.jl:270; _mapreduce(::Base.#identity, ::Base.#scalarmax, ::IndexLinea... [....] In general, if you have N samples
    0 码力 | 1378 页 | 4.74 MB | 1 年前
    3
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