Added jitting of layout comparison, small but easy gains

check_other_performance.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import clifford as cf\n",
    "import numpy as np\n",
    "import timeit\n",
    "layout,blades = cf.Cl(5)\n",
    "n_dims = len(layout.blades)+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def setup(n_dims):\n",
    "    a = cf.MultiVector(layout,value=np.random.rand(n_dims))\n",
    "    b = cf.MultiVector(layout,value=np.random.rand(n_dims))\n",
    "    return (a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "5.86 µs ± 243 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit a,b = setup(n_dims)\n",
    "a*b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "layout,blades = cf.Cl(4,1)\n",
    "n_dims = len(layout.blades)+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def setup(n_dims):\n",
    "    a = cf.MultiVector(layout,value=np.random.rand(n_dims))\n",
    "    b = cf.MultiVector(layout,value=np.random.rand(n_dims))\n",
    "    return (a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.85 µs ± 104 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit a,b = setup(n_dims)\n",
    "a*b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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