MasonProtter

julia> code_native(Tuple{Vector{Int}}) do v
           sum(v; init=0)
       end
        .text
        .file   "#12"
        .globl  "julia_#12_1605"                # -- Begin function julia_#12_1605
        .p2align        4, 0x90
        .type   "julia_#12_1605",@function
"julia_#12_1605":                       # @"julia_#12_1605"
; ┌ @ REPL[10]:2 within `#12`

MasonProtter

julia> code_native(Tuple{Vector{Int}}) do v
           sum(v; init=0)
       end
        .text
        .file   "#58"
        .globl  "julia_#58_2730"                # -- Begin function julia_#58_2730
        .p2align        4, 0x90
        .type   "julia_#58_2730",@function
"julia_#58_2730":                       # @"julia_#58_2730"
; ┌ @ REPL[24]:2 within `#58`

MasonProtter

using LoopVectorization
using Bumper
using StrideArraysCore
using StaticTools

set_default_buffer_size!(1000)

@inline function sumArray_alloc(N)
    smallarray = Array{Float64}(undef,N)
    @turbo for i ∈ 1:N

MasonProtter

using StaticArrays, Plots, Dictionaries

struct PSL2{T <: Real}
    a::T
    b::T
    c::T
    d::T
    function PSL2(a::T,b::T,c::T,d::T) where {T}
        (a*d - b*c ≈ 1) || error("Bad PSL₂($T) parameters, must have ad - bc = 1, got $((;a, b, c, d))")
        a >= 0 ? new{T}(a,b,c,d) : new{T}(-a,-b,-c,-d)

MasonProtter

module SUFib 
using SymbolicUtils
using SymbolicUtils.Rewriters

@syms fib(x::Int)::Int

const rset = [
    @rule fib(0) => 0
    @rule fib(1) => 1
    @rule fib(~n) => fib(~n - 1) + fib(~n - 2)

MasonProtter

#+BEGIN_SRC jupyter-julia
struct ArrayString{Store <: AbstractVector{<:AbstractChar}} <: AbstractString
    chars::Store
end

ArrayString(str::String) = ArrayString(collect(str))
ArrayString(T, str::String) = ArrayString(T(collect(str))) 

Base.String(s::ArrayString) = String(s.chars)

MasonProtter

#+BEGIN_SRC jupyter-julia
using CUDA
struct StaticString{N} <: AbstractString
    chars::NTuple{N, Char}
end
macro s_str(s)
    chars = tuple(collect(s)...)
    N = length(chars)
    esc(:(StaticString{$N}($chars)))
end

MasonProtter

#+BEGIN_SRC jupyter-julia
using CUDA
struct StaticString{N} <: AbstractString
    chars::NTuple{N, Char}
end
macro s_str(s)
    chars = tuple(collect(s)...)
    N = length(chars)
    esc(:(StaticString{$N}($chars)))
end

MasonProtter

#+BEGIN_SRC julia
const ketpat = r"\|.*?\>"
ketrep(str) = "Ket("*(match(r"(?<=\|).*?(?=>)", str).match)*")"

const brapat = r"\<.*?\|"
brarep(str) = "Bra("*(match(r"(?<=<).*?(?=\|)", str).match)*")"

function rep_braket(str)
    replace(replace(str, brapat => brarep), ketpat => ketrep)
end

MasonProtter

#+BEGIN_SRC jupyter-julia
using Interpolations
xs = range(-10, 10, length=50) # 50 evenly spaced points from -5 to 5

# model function, some Gaussian
f(x; A=1, σ=2, b=0) = A * exp(-x^2/2σ) + b
ys = f.(xs)

method = BSpline(Cubic(Line(OnGrid()))) #interpolation method
f_itp = scale(interpolate(ys, method), xs) # interpolation function