numpy.ipynb

{
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  "metadata": {
    "colab": {
      "name": "numpy.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/scott87730/AI--a050e102/blob/master/numpy.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "du7-Z7lDfnV0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "13019de2-0317-4b94-effc-f569dcc3a543"
      },
      "source": [
        "import numpy as np\n",
        "np.linspace(2.0, 3.0, num=5)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2.  , 2.25, 2.5 , 2.75, 3.  ])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HB8J0432gOZZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "748a4337-3f37-466b-8a11-2a4b17fdeba3"
      },
      "source": [
        "import numpy as np\n",
        "np.linspace(2.0, 3.0, num=5, endpoint=False)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2. , 2.2, 2.4, 2.6, 2.8])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ipAohN6Xgria",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "2b03b6c8-a8b9-4fd9-dcf9-50e422040167"
      },
      "source": [
        "import numpy as np\n",
        "np.linspace(2.0, 3.0, num=5, retstep=True)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([2.  , 2.25, 2.5 , 2.75, 3.  ]), 0.25)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "DCtON5NTgvTK",
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        "colab": {
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          "height": 34
        },
        "outputId": "06d3cae9-4cd4-4e29-b558-97ee9d5a52e6"
      },
      "source": [
        "import numpy as np\n",
        "ar2=np.array([[0,3,5],[2,8,7]])\n",
        "ar2.shape"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2, 3)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
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          "height": 51
        },
        "outputId": "e2178296-1c88-40da-b014-2104b57d6ca6"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "a=np.array([[0,1],[2,3]])\n",
        "\n",
        "a.reshape(1,4)\n",
        "a.reshape(4,1)\n",
        "\n",
        "print(a)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[0 1]\n",
            " [2 3]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "w31ovyOHg0BK",
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        "colab": {}
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      "source": [
        " "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kh6t0gmMg1o6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "2e474846-a092-4f42-b2b3-2168c049f742"
      },
      "source": [
        "b = a.reshape(1,4)\n",
        "b\n",
        "#b.shape"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 1, 2, 3]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8pp1DdMMg4sh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "8ebb5efc-5c7e-4867-9690-f04d486d113c"
      },
      "source": [
        "\n",
        "c = a.reshape(4,1)\n",
        "c.shape"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cF1sf_MOg7Px",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "7a18664b-ce63-4080-da74-f620c80cc3fb"
      },
      "source": [
        "import numpy as np\n",
        "x= np.arange(2,10).reshape(2,4)\n",
        "x"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[2, 3, 4, 5],\n",
              "       [6, 7, 8, 9]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9_nAhl_bg81p",
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          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "outputId": "0bd26438-6a7c-4598-edcf-29aa7c436223"
      },
      "source": [
        "import numpy as np\n",
        "x= np.arange(24).reshape(4,3,2)\n",
        "x"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[ 0,  1],\n",
              "        [ 2,  3],\n",
              "        [ 4,  5]],\n",
              "\n",
              "       [[ 6,  7],\n",
              "        [ 8,  9],\n",
              "        [10, 11]],\n",
              "\n",
              "       [[12, 13],\n",
              "        [14, 15],\n",
              "        [16, 17]],\n",
              "\n",
              "       [[18, 19],\n",
              "        [20, 21],\n",
              "        [22, 23]]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "kZo7IjHTg_rb",
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          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "outputId": "c01bdab2-a620-46ae-bf13-8beda6fbf2d6"
      },
      "source": [
        "np.arange(24).reshape(3,4,2)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[ 0,  1],\n",
              "        [ 2,  3],\n",
              "        [ 4,  5],\n",
              "        [ 6,  7]],\n",
              "\n",
              "       [[ 8,  9],\n",
              "        [10, 11],\n",
              "        [12, 13],\n",
              "        [14, 15]],\n",
              "\n",
              "       [[16, 17],\n",
              "        [18, 19],\n",
              "        [20, 21],\n",
              "        [22, 23]]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
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        "id": "YDzIl6RshFb0",
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          "height": 272
        },
        "outputId": "c7e642f0-b867-459a-c853-f63d3bf07e8e"
      },
      "source": [
        "np.arange(24).reshape(4,3,2)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[ 0,  1],\n",
              "        [ 2,  3],\n",
              "        [ 4,  5]],\n",
              "\n",
              "       [[ 6,  7],\n",
              "        [ 8,  9],\n",
              "        [10, 11]],\n",
              "\n",
              "       [[12, 13],\n",
              "        [14, 15],\n",
              "        [16, 17]],\n",
              "\n",
              "       [[18, 19],\n",
              "        [20, 21],\n",
              "        [22, 23]]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
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      "source": [
        " "
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      "execution_count": 0,
      "outputs": []
    }
  ]
}