Copies_and_views.ipynb

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      "name": "Copies and views.ipynb",
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      "name": "python3",
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    "language_info": {
      "name": "python"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/hiro106/colab_notebooks_for_learning/blob/main/Copies_and_views.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "Tkjt48w3wc-p"
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      "source": [
        "# https://numpy.org/doc/stable/user/basics.copies.html"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "JKapjVRcw6xH"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### View"
      ],
      "metadata": {
        "id": "hPMh_JiQRiQk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = np.arange(10)"
      ],
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      "execution_count": 23,
      "outputs": []
    },
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        "id": "DrX_4rpuwgss",
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      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y = x[1:3] # creates a view"
      ],
      "metadata": {
        "id": "di5R3FkAwgvU"
      },
      "execution_count": 25,
      "outputs": []
    },
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        "y"
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      "execution_count": 26,
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          "data": {
            "text/plain": [
              "array([1, 2])"
            ]
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          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x[1:3] = [10,11]"
      ],
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      "outputs": []
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        {
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          "data": {
            "text/plain": [
              "array([ 0, 10, 11,  3,  4,  5,  6,  7,  8,  9])"
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          "metadata": {},
          "execution_count": 28
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              "array([10, 11])"
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          "execution_count": 29
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            "text/plain": [
              "array([ 0, 10, 11,  3,  4,  5,  6,  7,  8,  9])"
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            "text/plain": [
              "array([ 0,  5, 11,  3,  4,  5,  6,  7,  8,  9])"
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          "metadata": {},
          "execution_count": 32
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      "cell_type": "code",
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        "y.base is x"
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              "True"
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          "metadata": {},
          "execution_count": 33
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      "cell_type": "markdown",
      "source": [
        "### Copy"
      ],
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        "id": "03KEVtsrR3Nq"
      }
    },
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      "cell_type": "code",
      "source": [
        "x = np.arange(9)"
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        "id": "bCDF2YAwQxSL"
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          "execution_count": 35
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        "x = np.arange(9).reshape(3, 3)"
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            "text/plain": [
              "array([[0, 1, 2],\n",
              "       [3, 4, 5],\n",
              "       [6, 7, 8]])"
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          "execution_count": 37
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              "array([ 5, 11])"
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        "x[[1, 2]] = [[10, 11, 12], [13, 14, 15]]"
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              "       [10, 11, 12],\n",
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