julia

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 How can I delete one or more rows and/or columns from an array? 回答1: Working with: julia> array = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16] 4×4 Array{Int64,2}: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 To delete a single row (here row 2): julia> newarray = array[1:end .!= 2, :] 3×4 Array{Int64,2}: 1 2 3 4 9 10 11 12 13 14 15 16 To delete a single column (here column 3): julia> newarray = array[:, 1:end .!= 3] 4×3 Array{Int64,2}: 1 2 4 5 6 8 9 10 12 13 14 16 To delete a single row and a single

问题 I have a sinusoid with length 5 seconds as below: x=sin(0:.01:2*pi*500*5); Now I would like to hear the audio of this waveform by giving a command similar as below: playsound(x,samplingfrequency); It will be useful for me if I could write this audio data to a wav or mp3 file. What is the library needed and the equivalent command in julia for this functionality? 回答1: You may play audio with https://github.com/ssfrr/AudioIO.jl And for write/read wav https://github.com/JuliaLang/Sound.jl/blob

问题 I have a sinusoid with length 5 seconds as below: x=sin(0:.01:2*pi*500*5); Now I would like to hear the audio of this waveform by giving a command similar as below: playsound(x,samplingfrequency); It will be useful for me if I could write this audio data to a wav or mp3 file. What is the library needed and the equivalent command in julia for this functionality? 回答1: You may play audio with https://github.com/ssfrr/AudioIO.jl And for write/read wav https://github.com/JuliaLang/Sound.jl/blob

问题 I'm writing a function that I would find easier to write and read if it could define another function differently depending on input or runtime values of variables (and then use that function). The following illustrates the idea (even if defining a function inside a function is of no advantage in this simple example): julia> function f(option::Bool) if option g() = println("option true") g() else g() = println("option false") g() end end; WARNING: Method definition g() in module Main at REPL

问题 The Julia Language syntax looks very similar to python, while the concept of a class (if one should address it as such a thing) is more what you use in C. There were many reasons why the creators decided on the difference with respect to the OOP. Still would it have been so hard (in comparison to create Julia in first place which is impressive) to find some canonical way to interpret python to Julia and thus get a hold of all the python libraries? 回答1: Yes. The design of Python makes it

问题 The Julia Language syntax looks very similar to python, while the concept of a class (if one should address it as such a thing) is more what you use in C. There were many reasons why the creators decided on the difference with respect to the OOP. Still would it have been so hard (in comparison to create Julia in first place which is impressive) to find some canonical way to interpret python to Julia and thus get a hold of all the python libraries? 回答1: Yes. The design of Python makes it

问题 I'm extremely dissatisfied after translating a program from Python to Julia: for small/very small inputs, Python is faster for medium inputs, Julia is faster (but not that much) for big inputs, Python is faster I think the reason is that I don't understand how memory allocation works (autodidact here, no CS background). I would post my code here but it is too long and too specific and it would not be beneficial for anybody but me. Therefore I made some experiments and now I have some

问题 I'm trying to plot data based on time : userId = 2 dateGiven = Datetime.date(2014,2,3) biometric = "heart-rate" df = DataFrames.readtable(string("data/user_",userId,"/",dateGiven,"/",biometric,".csv"), colnames = ["Time", "Heart Rate"], coltypes = {Int,Int} ) df["Time"] = map((timestamp) -> Datetime.unix2datetime(timestamp, Datetime.UTC) , df["Time"]) plot(df,x="Time",y="Heart Rate",Geom.line) I have this error : no method *(Float64,DateTime{ISOCalendar,Zone0}) in optimize_ticks at /Users