{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": 3
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "julia-1.5",
   "display_name": "Julia 1.5.3",
   "language": "julia"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "source": [
    "# Benchmarks\n",
    "This notebook compares the wrapped Fortran SLATEC implementation contained in `py3nj` with the native Julia `WignerFamilies.jl`. I use very high quantum numbers for this test, in order to amortize the cost of calling SLATEC with some Python overhead."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "WignerFamilies.jl:   619.900 μs (0 allocations: 0 bytes)\n",
      "SLATEC wrapper:   1.637 ms (83 allocations: 2.44 MiB)\n"
     ]
    }
   ],
   "source": [
    "using WignerFamilies\n",
    "using PyCall\n",
    "using BenchmarkTools\n",
    "py3nj = pyimport(\"py3nj\")\n",
    "\n",
    "j₂, j₃, m₂, m₃ = 40000, 40000, -2, 2\n",
    "w = WignerF(Float64, j₂, j₃, m₂, m₃)\n",
    "w3j = get_wigner_array(w)\n",
    "\n",
    "print(\"WignerFamilies.jl: \")\n",
    "@btime WignerFamilies.wigner3j_f!(w, w3j)\n",
    "print(\"SLATEC wrapper: \")\n",
    "@btime two_l1, three_j = py3nj.wigner.drc3jj(2j₂, 2j₃, 2m₂, 2m₃);"
   ]
  },
  {
   "source": [
    "## Comparing Allocating Versions\n",
    "\n",
    "This is perhaps a more fair test, since the wrapped SLATEC is allocating each time."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "WignerFamilies.jl:   652.100 μs (3 allocations: 625.17 KiB)\n",
      "SLATEC wrapper:   1.671 ms (83 allocations: 2.44 MiB)\n"
     ]
    }
   ],
   "source": [
    "print(\"WignerFamilies.jl: \")\n",
    "@btime WignerFamilies.wigner3j_f(Float64, j₂, j₃, m₂, m₃);\n",
    "print(\"SLATEC wrapper: \")\n",
    "@btime two_l1, three_j = py3nj.wigner.drc3jj(2j₂, 2j₃, 2m₂, 2m₃);"
   ]
  },
  {
   "source": [
    "## m_i = 0\n",
    "\n",
    "WignerFamilies.jl uses a special case for `m_i = 0` that gives it an extra factor of 2.\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "WignerFamilies.jl:   387.400 μs (3 allocations: 625.17 KiB)\n",
      "SLATEC wrapper:   1.673 ms (83 allocations: 2.44 MiB)\n"
     ]
    }
   ],
   "source": [
    "j₂, j₃, m₂, m₃ = 40000, 40000, 0, 0\n",
    "print(\"WignerFamilies.jl: \")\n",
    "@btime WignerFamilies.wigner3j_f(Float64, j₂, j₃, m₂, m₃);\n",
    "print(\"SLATEC wrapper: \")\n",
    "@btime two_l1, three_j = py3nj.wigner.drc3jj(2j₂, 2j₃, 2m₂, 2m₃);"
   ]
  }
 ]
}