Proteins and PCA

gistfile1.py

{
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  "name": "Sandbox"
 },
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "from sklearn import cluster"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn import decomposition"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cd Documents/"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/valentinesvensson/Documents"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f = pd.ExcelFile(\"2012-11-12_Omics dataset_449 ID.xls\")"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f.sheet_names"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "[u'overlapping proteins']"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = f.parse(\"overlapping proteins\")"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Index: 449 entries, gi|29826323           to gi|60814531          ",
        "Data columns:",
        "nonRelapse_HPV_1        449  non-null values",
        "nonRelapse_HPV_55       449  non-null values",
        "Relapse_HPV_18          449  non-null values",
        "Relapse_HPV_23          449  non-null values",
        "nonRelapse_HPV_42       449  non-null values",
        "nonRelapse_HPV_50       449  non-null values",
        "nonRelapse_HPV_20       449  non-null values",
        "nonRelapse_nonHPV_53    449  non-null values",
        "Relapse_nonHPV_45       449  non-null values",
        "nonRelapse_nonHPV_61    449  non-null values",
        "nonRelapse_nonHPV_52    449  non-null values",
        "nonRelapse_nonHPV_38    449  non-null values",
        "Relapse_nonHPV_40       449  non-null values",
        "Relapse_nonHPV_49       449  non-null values",
        "dtypes: float64(14)"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.boxplot();",
      "xticks(rotation=90);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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H8Pnnn+Pmm2/G999/f7UBP7maqud9+PNssk9M/8ZzZFYF5nspodhOVtgnHRqy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\nRjpxQRAEEyOduCAIgomRTlwQBMHE/H+tw7O+Y5sKDwAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log_df = np.log2(df)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(8,4)",
      "log_df.boxplot(rot=90);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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3OyA317fPqAqzcyP++HxfP4NDXXAoB+p/D/heFzXhnACkHPwVQ84r/32G2TFY7yXOoRKk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\nYII=\n"
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "s = df[\"Relapse_HPV_18\"]",
      "s.hist(bins=64);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log_df[\"Relapse_HPV_18\"].hist(bins=64);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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YY3PvbjF4AQDwERkvEAJkvEAwkPECABAwDF4P2Zx12Ny7RP9kvI7pEoyxuXe3xh28mzZt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\nAICP/h/XC6gaMZ+NzwAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sklearn.decomposition.pca import PCA"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 113
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c = PCA()"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 69
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y = c.fit(df)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 71
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pca = PCA(n_components=2)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 139
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pca.fit(log_df)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 140,
       "text": [
        "PCA(copy=True, n_components=2, whiten=False)"
       ]
      }
     ],
     "prompt_number": 140
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(pca.explained_variance_ratio_)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 0.36502262  0.14706291]"
       ]
      }
     ],
     "prompt_number": 141
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Y = pca.transform(log_df)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 142
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from mpl_toolkits.mplot3d import Axes3D",
      "fig = plt.figure()",
      "ax = fig.add_subplot(111, projection='3d')"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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l5eRrVtEP2/ZCk4nL5UJDQ0Nef09tBxIWq+z36AGAPa9kMik71hRL0AXmUoioG7mRuJad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\nv1bKppVTqZRs6jE2NoannnoKBw8exPvvvy8L0/e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      }
     ],
     "prompt_number": 121
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure()",
      "ax = fig.add_subplot(111, projection='3d')",
      "ax.scatter3D([x[0] for x in Y], [x[1] for x in Y], [x[2] for x in Y], c=ward.labels_);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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XJxwOj1kRRnsPM0VB+rnpbII6XudxKgpmvn1kik7vvfde7r33Xq688kp+85vf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\nMmfOBu64IwWH4xhdu2bhdHoxGo/Q0tJEbW0XkpOvxmA4iM/3Dg6Hhe3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5OVlWwGZkZMg3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\nHTp06AgD/x8UW6wpSoEuEQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 134
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "ax.scatter3D?"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 129
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ward = Ward(n_clusters=2).fit(log_df)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 145
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "DATA = np.array(log_df)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 166
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "ward = Ward(n_clusters=2).fit(DATA.T)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 169
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ward.labels_"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 171,
       "text": [
        "array([0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0])"
       ]
      }
     ],
     "prompt_number": 171
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for index, label in enumerate(ward.labels_):",
      "    if label:",
      "        print(log_df.icol(index).name)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Relapse_HPV_18",
        "nonRelapse_HPV_42",
        "nonRelapse_HPV_50"
       ]
      }
     ],
     "prompt_number": 197
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "col.name"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 195,
       "text": [
        "u'nonRelapse_HPV_55'"
       ]
      }
     ],
     "prompt_number": 195
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log_df"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 189,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Index: 449 entries, gi|29826323           to gi|60814531          ",
        "Data columns:",
        "nonRelapse_HPV_1        449  non-null values",
        "nonRelapse_HPV_55       449  non-null values",
        "Relapse_HPV_18          449  non-null values",
        "Relapse_HPV_23          449  non-null values",
        "nonRelapse_HPV_42       449  non-null values",
        "nonRelapse_HPV_50       449  non-null values",
        "nonRelapse_HPV_20       449  non-null values",
        "nonRelapse_nonHPV_53    449  non-null values",
        "Relapse_nonHPV_45       449  non-null values",
        "nonRelapse_nonHPV_61    449  non-null values",
        "nonRelapse_nonHPV_52    449  non-null values",
        "nonRelapse_nonHPV_38    449  non-null values",
        "Relapse_nonHPV_40       449  non-null values",
        "Relapse_nonHPV_49       449  non-null values",
        "dtypes: float64(14)"
       ]
      }
     ],
     "prompt_number": 189
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "figsize(12, 8)",
      "plt.scatter([x[0] for x in Y], [x[1] for x in Y], c=ward.labels_);"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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Zcvz4bfXy5MpF1LVrlEFbvHjBYiEiBXuQBwQEUDh/frafOEElpbgMnFDqvkdg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\n"
      }
     ],
     "prompt_number": 162
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "labels = pd.Series(ward.labels_)"
     ],
     "language": "python",
     "outputs": [],
     "prompt_number": 150
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "[r[1] for r in filter(lambda t: t[1] if t[0] else None, zip(ward.labels_, range(len(ward.labels_))))]"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 217,
       "text": [
        "[2, 4, 5]"
       ]
      }
     ],
     "prompt_number": 217
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "enumerate(labels)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 208,
       "text": [
        "<enumerate at 0x111e83280>"
       ]
      }
     ],
     "prompt_number": 208
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.ix[:,r]"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 221,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Index: 449 entries, gi|29826323           to gi|60814531          ",
        "Data columns:",
        "nonRelapse_HPV_55    449  non-null values",
        "nonRelapse_HPV_50    449  non-null values",
        "dtypes: float64(2)"
       ]
      }
     ],
     "prompt_number": 221
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "labels.shape"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 163,
       "text": [
        "(449,)"
       ]
      }
     ],
     "prompt_number": 163
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "log_df"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 161,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>",
        "Index: 449 entries, gi|29826323           to gi|60814531          ",
        "Data columns:",
        "nonRelapse_HPV_1        449  non-null values",
        "nonRelapse_HPV_55       449  non-null values",
        "Relapse_HPV_18          449  non-null values",
        "Relapse_HPV_23          449  non-null values",
        "nonRelapse_HPV_42       449  non-null values",
        "nonRelapse_HPV_50       449  non-null values",
        "nonRelapse_HPV_20       449  non-null values",
        "nonRelapse_nonHPV_53    449  non-null values",
        "Relapse_nonHPV_45       449  non-null values",
        "nonRelapse_nonHPV_61    449  non-null values",
        "nonRelapse_nonHPV_52    449  non-null values",
        "nonRelapse_nonHPV_38    449  non-null values",
        "Relapse_nonHPV_40       449  non-null values",
        "Relapse_nonHPV_49       449  non-null values",
        "dtypes: float64(14)"
       ]
      }
     ],
     "prompt_number": 161
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pca.transform(log_df)"
     ],
     "language": "python",
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 106,
       "text": [
        "array([[-3.03249704, -1.2374229 ],",
        "       [-5.5342696 , -8.80235742],",
        "       [-4.46004917, -1.1572106 ],",
        "       [-6.14007311, -1.49876692],",
        "       [-5.65016228, -2.02010734],",
        "       [-1.13293312, -0.55233149],",
        "       [-1.81901615,  0.689343  ],",
        "       [-5.12259389, -0.56784334],",
        "       [-3.00162921, -0.63358425],",
        "       [-1.6310363 , -2.40860083],",
        "       [-1.53486216, -0.04242968],",
        "       [-1.45020585, -2.39608771],",
        "       [-1.23299703, -0.33970829],",
        "       [ 0.72138588, -2.48535195],",
        "       [-0.04655719, -0.45608988],",
        "       [-4.35150518,  0.26197092],",
        "       [-1.44470347,  0.65024674],",
        "       [-0.94325566,  0.17551883],",
        "       [ 0.69847754, -1.1138108 ],",
        "       [-2.06839502,  1.17910051],",
        "       [-1.15026982,  0.6050358 ],",
        "       [-2.55608647, -0.22890359],",
        "       [-4.13196567,  0.32564373],",
        "       [ 0.19301585, -1.05032433],",
        "       [-0.6668699 , -0.31125273],",
        "       [-0.39578337,  0.11312215],",
        "       [-1.61788289,  0.35072526],",
        "       [-3.07066953,  0.08160317],",
        "       [-2.10121695, -0.21011067],",
        "       [-0.48148683, -0.19239622],",
        "       [-1.3607598 ,  0.4419596 ],",
        "       [-2.48102856,  1.37887396],",
        "       [-1.80767826,  0.49541338],",
        "       [-0.08028248, -1.46129213],",
        "       [ 0.98982257, -1.03893671],",
        "       [-2.89014577,  0.27962934],",
        "       [-1.37169002,  0.54332827],",
        "       [-0.19317353,  0.54208353],",
        "       [-2.46462611, -0.42605117],",
        "       [-1.79492901,  0.18127533],",
        "       [-2.54711599, -0.0193097 ],",
        "       [ 0.20373735, -0.28687687],",
        "       [ 0.51980189, -0.2898956 ],",
        "       [-3.56061617,  0.31787198],",
        "       [ 0.5397059 , -0.46687155],",
        "       [-1.37550458,  0.75174637],",
        "       [-1.91900169,  0.57059328],",
        "       [-1.93725445,  0.55023397],",
        "       [-0.03369795, -0.367535  ],",
        "       [-0.48224277, -0.59222454],",
        "       [ 0.33971871,  0.01621434],",
        "       [-0.51058496, -0.42656844],",
        "       [-3.45398174,  1.6815504 ],",
        "       [-0.10788975, -0.52982791],",
        "       [ 0.57235314, -0.30594326],",
        "       [ 0.46745187,  0.19497068],",
        "       [-0.1909257 , -0.01240147],",
        "       [ 0.01058597,  0.34861259],",
        "       [ 0.43920743, -0.21250567],",
        "       [ 0.22418945, -0.14566339],",
        "       [-1.80934847,  0.26202449],",
        "       [ 0.03557471,  0.25954675],",
        "       [ 1.7218585 , -0.12326706],",
        "       [ 0.06791169, -0.81545783],",
        "       [ 0.67757257, -0.12414546],",
        "       [ 0.71866402, -0.2719643 ],",
        "       [ 0.64843641, -0.59787818],",
        "       [-0.87023412,  0.01119138],",
        "       [ 0.15229162, -0.00323243],",
        "       [-0.05086555,  0.06815002],",
        "       [-0.86159978,  0.60425615],",
        "       [-2.21414903,  0.36782841],",
        "       [ 1.44096392, -0.19656431],",
        "       [-2.3110518 ,  0.63257525],",
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        "       [ 1.79333334, -1.00848264],",
        "       [-0.80056401,  0.06681617],",
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        "       [-0.70538473, -0.20191123],",
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        "       [ 0.26078793, -1.89822368],",
        "       [-0.39703121,  0.47514054],",
        "       [ 0.04154644, -1.29152697],",
        "       [-0.70505872, -0.15954976],",
        "       [-0.66021258,  0.62287817],",
        "       [-0.458107  , -0.25070717],",
        "       [ 0.12047372,  0.52080569],",
        "       [ 0.17324646, -0.12663503],",
        "       [-1.5407567 ,  0.35875898],",
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        "       [-0.37430896, -0.47073135],",
        "       [-0.22642774, -0.67067039],",
        "       [ 0.87549147,  0.0072466 ],",
        "       [ 0.5545676 , -0.36039755],",
        "       [ 0.32748441, -0.02625531],",
        "       [-0.28389248,  0.0703218 ],",
        "       [-1.82084934,  0.01286031],",
        "       [ 1.37652775,  0.70815773],",
        "       [ 0.62449228,  0.50592008],",
        "       [-1.34782431,  0.34750575],",
        "       [-1.38167942,  0.38662681],",
        "       [ 1.24574616, -0.53011624],",
        "       [ 0.61656329, -0.14925457],",
        "       [-0.22242184, -1.08618212],",
        "       [-1.46843797,  0.56460707],",
        "       [-0.6935118 ,  0.29214224],",
        "       [ 0.39273963,  0.24883458],",
        "       [-0.83670199, -0.36886724],",
        "       [ 0.88803627,  0.07549986],",
        "       [-2.41650527,  0.2177531 ],",
        "       [ 0.09245279, -0.00136725],",
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        "       [ 0.58167584, -0.36335997],",
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        "       [ 1.13684861, -0.16165503],",
        "       [-2.10849869,  1.19777327],",
        "       [ 0.61878215, -0.65676523],",
        "       [-0.53310453, -0.45631559],",
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        "       [ 0.87277353,  0.49147708],",
        "       [ 0.31518162, -0.56628032],",
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        "       [-1.39148657,  0.04178635],",
        "       [-1.49906576,  1.1094871 ],",
        "       [ 0.77571393, -1.70447358],",
        "       [-0.51374301, -0.69765507],",
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        "       [ 0.64959915, -1.04134233],",
        "       [-0.41538086,  0.85275902],",
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        "       [ 0.83318378, -0.77476333],",
        "       [-0.47450121, -0.10004835],",
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        "       [-0.29022341, -0.15014415],",
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        "       [-0.92345695, -0.73880798],",
        "       [-0.33121042, -0.53138074],",
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        "       [-0.78530937,  0.29458675],",
        "       [-0.28163459,  0.87943505],",
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        "       [-0.74383469,  0.03053691],",
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        "       [ 0.65158093, -0.02191136],",
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        "       [-0.17651921,  0.64519926],",
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        "       [ 1.50985622,  0.03998345],",
        "       [-1.58139933,  0.58920738],",
        "       [ 0.15357469, -0.02835437],",
        "       [ 0.11695018,  0.48312364],",
        "       [ 0.59954713,  0.13829472],",
        "       [ 0.40407036,  0.33523542],",
        "       [ 1.85576705, -0.53080528],",
        "       [ 0.89455749, -0.02300088],",
        "       [ 1.05666447, -0.06442673],",
        "       [ 0.94143669,  0.04829879],",
        "       [ 0.84923126,  0.58629965],",
        "       [ 0.99905495, -0.39460737],",
        "       [ 0.31497922,  0.09953706],",
        "       [ 1.18175013, -1.45085813],",
        "       [ 0.66562146,  0.23534451],",
        "       [-0.32394029,  0.07425056],",
        "       [ 0.95830682, -0.18290679],",
        "       [ 1.11027376,  0.70022629],",
        "       [ 0.42219994,  0.37473186],",
        "       [ 0.36988263,  0.89088135],",
        "       [ 0.83217724, -0.71085453],",
        "       [ 0.50875696,  0.54462735],",
        "       [ 0.0431149 ,  0.31038283],",
        "       [ 0.41273399, -0.5470119 ],",
        "       [ 0.31622591,  0.34124106],",
        "       [-1.1665599 ,  1.00025622],",
        "       [ 1.71103981, -0.78828768],",
        "       [ 1.91129395, -0.87376442],",
        "       [ 0.28221783,  0.47699533],",
        "       [ 0.02016478,  0.2063174 ],",
        "       [ 1.26024379, -0.91548186],",
        "       [ 0.15721858,  0.83816947],",
        "       [ 0.89960214,  0.33812936],",
        "       [ 0.71066298, -0.68037441],",
        "       [ 0.84368379,  0.2831692 ],",
        "       [-0.18981705, -0.10812401],",
        "       [ 0.92223333,  0.40534302],",
        "       [ 1.01622105,  0.1423606 ],",
        "       [ 0.36193625,  0.25257477],",
        "       [ 0.22718195,  0.06033967],",
        "       [-0.40226564,  0.61522797],",
        "       [-0.02386024,  0.41104118],",
        "       [ 0.68474847, -0.02103518],",
        "       [ 0.77782107, -0.05412903],",
        "       [ 0.63183666,  0.32579251],",
        "       [ 0.56424242, -0.01131207],",
        "       [ 1.03000256,  0.05158584],",
        "       [ 0.39803349, -0.04523633],",
        "       [ 0.24043043,  0.57434876],",
        "       [ 0.82110456, -0.51188781],",
        "       [ 0.86934335,  0.13319593],",
        "       [ 1.22667488, -0.14272529],",
        "       [ 1.31609209, -0.46146071],",
        "       [ 0.64034112, -0.00093335],",
        "       [-0.56851548, -0.15482538],",
        "       [ 0.30822545, -0.01328795],",
        "       [-0.10667123,  0.15349903],",
        "       [ 0.46016392,  0.5493164 ],",
        "       [ 0.05610203,  0.50751082],",
        "       [ 0.72976297, -0.14837213],",
        "       [ 0.7618325 , -0.05117181],",
        "       [ 1.02966109,  0.10192818],",
        "       [ 0.60409986,  0.25688753],",
        "       [ 0.57785273,  0.52839532],",
        "       [ 0.26012805,  0.36904485],",
        "       [ 0.32208963, -0.40200167],",
        "       [ 2.18389511, -1.07371455],",
        "       [ 1.01332808, -0.35118742],",
        "       [ 2.00325704, -0.65101614],",
        "       [ 0.67828275,  0.49115459],",
        "       [ 0.33298549, -0.4518478 ],",
        "       [ 0.36880283,  0.02749993],",
        "       [-0.0542574 ,  0.0176664 ],",
        "       [ 0.72127032, -0.16703391],",
        "       [-0.08521952,  0.22778726],",
        "       [ 0.14602457,  0.19456034],",
        "       [ 0.72679837, -0.23292244],",
        "       [-0.24523709,  0.45987317],",
        "       [ 0.48263418, -0.20198621],",
        "       [-0.56030882,  0.6281141 ],",
        "       [-0.32415104,  0.81452721],",
        "       [ 0.4478018 ,  0.08900125],",
        "       [-0.02860932, -0.19351436],",
        "       [ 0.38671395, -1.16481606],",
        "       [ 0.25111364, -0.1510581 ],",
        "       [-0.03514379,  0.3791988 ],",
        "       [ 0.52496126, -0.26500158],",
        "       [ 0.79708192, -0.22418254],",
        "       [ 0.32832548,  0.46037571],",
        "       [ 1.0051783 , -0.08836223],",
        "       [ 1.00438442,  0.36367648],",
        "       [ 0.73796749,  0.50136044],",
        "       [ 0.5086748 , -1.01939247],",
        "       [ 0.60338665,  0.93848263],",
        "       [ 1.68217834,  0.83818059],",
        "       [ 0.56623588, -0.62758291],",
        "       [-0.2563214 , -0.96564462],",
        "       [-0.12839079,  0.85837309],",
        "       [ 0.99089583,  0.56870323],",
        "       [ 0.50722747, -0.41524302],",
        "       [-1.14856515,  1.03858379],",
        "       [ 0.41305685,  0.54155656],",
        "       [ 0.22594307, -4.03047421]])"
       ]
      }
     ],
     "prompt_number": 106
    }
   ]
  }
 ]
}