Lunar - SW08

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scope"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0. 0. 0.]\n",
      " [0. 0. 0.]\n",
      " [0. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "PI = np.pi\n",
    "\n",
    "def create_aray(n,m)->np.ndarray:\n",
    "    \"\"\"\n",
    "    Creare an empty array of size (n x m) and return it\n",
    "\n",
    "    Parameters:\n",
    "        m (int):            Width of array\n",
    "        n (int):            Heigh of array\n",
    "\n",
    "    Returns:\n",
    "        arr (np.ndarray)    2D numpy array   \n",
    "    \"\"\"\n",
    "    \n",
    "    arr = np.zeros((n,m))\n",
    "    return arr\n",
    "\n",
    "print(create_aray(3,3))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1   2   3   4   5   6   7   8   9  10]\n",
      " [ 11  12  13  14  15  16  17  18  19  20]\n",
      " [ 21  22  23  24  25  26  27  28  29  30]\n",
      " [ 31  32  33  34  35  36  37  38  39  40]\n",
      " [ 41  42  43  44  45  46  47  48  49  50]\n",
      " [ 51  52  53  54  55  56  57  58  59  60]\n",
      " [ 61  62  63  64  65  66  67  68  69  70]\n",
      " [ 71  72  73  74  75  76  77  78  79  80]\n",
      " [ 81  82  83  84  85  86  87  88  89  90]\n",
      " [ 91  92  93  94  95  96  97  98  99 100]]\n"
     ]
    }
   ],
   "source": [
    "print(np.arange(1,101).reshape((10,10)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## JSON files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Age': 21, 'Facutly': 'EESE'}\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "my_dict={}\n",
    "my_dict[\"Matteo\"]={\"Age\":21, \"Facutly\":\"EESE\"}\n",
    "my_dict[\"Michi\"]={\"Age\": 23, \"Faculty\": \"Cacone\"}\n",
    "\n",
    "print(my_dict[\"Matteo\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = \"henlo.json\"\n",
    "with open(file, mode=\"w+\") as fp:\n",
    "    json.dumps(obj=my_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  0.  50. 100.]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "print(np.linspace(0,100,3))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}

SW08_Notes