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    {
      "execution_count": null, 
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      "source": [
        "%matplotlib inline"
      ], 
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    {
      "source": [
        " \nInput normalization\n===================\n\nExample usage of the Normalize augmentation. \n \n\n"
      ], 
      "cell_type": "markdown", 
      "metadata": {}
    }, 
    {
      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "import numpy as np\nimport matplotlib.pyplot as plt\n\nfrom astronet.augmentations import Normalize\n\nx1 = np.random.rand(1,50,50)*9\nx2 = np.random.rand(1,50,50)*2\nx3 = np.random.rand(1,50,50)*5\nx4 = np.random.rand(1,50,50)*1\nX = np.array([x1,x2,x3,x4])\ny = np.ones(4)\n\naugment = Normalize()\nXtransformed, _, _ = augment.apply(X, y, None)\n\nfig, ax = plt.subplots(len(X),2, figsize=(3,6), subplot_kw={'xticks': [], 'yticks': []})\nax[0][0].set_title(\"Before\")\nax[0][1].set_title(\"After\")\nfor i in range(len(X)):\n    ax[i][0].imshow(X[i][0], vmin=0, vmax=10)\n    ax[i][1].imshow(Xtransformed[i][0], vmin=0, vmax=10)"
      ], 
      "outputs": [], 
      "metadata": {
        "collapsed": false
      }
    }
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