Julia prelude

prelude.jl

# basic packages and plotting
versioninfo()
using FFTW, DSP, DataFrames, Query, Plots, StatsPlots; #plotlyjs()
const N=100
plot(1:N,1:N |> x->cos.(2pi*x/N)+0sin.(2pi*x/N) |> fft |> x->abs.(x) |> fftshift)

# calling to C++ via LLVM
using Cxx
cxx"""#include <iostream>"""
cxx"""using namespace std;"""
icxx"""cout << 123+234 << endl;"""
#__current_compiler__ = Cxx.new_clang_instance()

# adding new packages
using Pkg
Pkg.add("CSV")
using CSV

# process tabled data
df=DataFrame(xs=1:N,ys=1:N |> x->sin.(2pi*x/N),zs=1:N |> x->cos.(2pi*x/N))
display(df)
df1 = ( @from d in df begin
        @where d.ys>.5
        @select d
        @collect DataFrame
        end )
display(df1)
CSV.write("df1.csv",df1)
@df stack(df,[:ys,:zs]) plot(:xs,:value,group=:variable)

# get help
?CSV.write

# Units
using Pkg; Pkg.add("Unitful")
using Unitful
SpeedOfLight=299_792_458u"m/s"
freq=2.959u"GHz"
len=SpeedOfLight/u"s^-1"(freq)
display(len)
ustrip(len)

# Setup Conda (working with Python packages)
ENV["PYTHON"]=""
using Pkg
Pkg.build("PyCall")
Pkg.build("PyPlot")
Pkg.add("Conda")

# SciPy
using Conda
Conda.add("scipy")
using PyCall
so=pyimport("scipy.optimize")
display(so.newton(x->cos(x)-2x,1))
using PyPlot
x=-3:.1:3
plot(x,cos.(x)-2x,x,zeros(length(x)))

# SymPy
using Pkg
Pkg.add("SymPy")
using SymPy
x=symbols(:x)
eval(solve(x^4-x-1))