Untitled Folder/Untitled1.ipynb

Untitled1.ipynb

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      "source": "import numpy as np\nimport pandas as pd",
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      "cell_type": "code",
      "source": "t = 1\nalpha = 1\nt, alpha",
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          "end_time": "2022-05-25T11:34:38.474538Z"
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      "cell_type": "code",
      "source": "zeta = np.linspace(1,2,5)\nzeta",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "array([1.  , 1.25, 1.5 , 1.75, 2.  ])"
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      "cell_type": "code",
      "source": "lam = np.linspace(1,2,5)\nlam",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": "array([1.  , 1.25, 1.5 , 1.75, 2.  ])"
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      "cell_type": "code",
      "source": "y2 = [[np.exp(-t*((1+z)*alpha-l)) for z in zeta] for l in lam]\ny2",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "[[0.36787944117144233,\n  0.2865047968601901,\n  0.22313016014842982,\n  0.17377394345044514,\n  0.1353352832366127],\n [0.4723665527410147,\n  0.36787944117144233,\n  0.2865047968601901,\n  0.22313016014842982,\n  0.17377394345044514],\n [0.6065306597126334,\n  0.4723665527410147,\n  0.36787944117144233,\n  0.2865047968601901,\n  0.22313016014842982],\n [0.7788007830714049,\n  0.6065306597126334,\n  0.4723665527410147,\n  0.36787944117144233,\n  0.2865047968601901],\n [1.0,\n  0.7788007830714049,\n  0.6065306597126334,\n  0.4723665527410147,\n  0.36787944117144233]]"
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          "end_time": "2022-05-25T11:34:38.542956Z"
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      },
      "cell_type": "code",
      "source": "y2 = pd.DataFrame()\ny2.index = zeta\nfor l in lam:\n    y2[l] = [np.exp(-t*((1+z)*alpha-l)) for z in zeta]",
      "execution_count": 6,
      "outputs": []
    },
    {
      "metadata": {
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          "start_time": "2022-05-25T11:34:38.554079Z",
          "end_time": "2022-05-25T11:34:38.588683Z"
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      "cell_type": "code",
      "source": "y2",
      "execution_count": 7,
      "outputs": [
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          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/plain": "          1.00      1.25      1.50      1.75      2.00\n1.00  0.367879  0.472367  0.606531  0.778801  1.000000\n1.25  0.286505  0.367879  0.472367  0.606531  0.778801\n1.50  0.223130  0.286505  0.367879  0.472367  0.606531\n1.75  0.173774  0.223130  0.286505  0.367879  0.472367\n2.00  0.135335  0.173774  0.223130  0.286505  0.367879",
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