problem_eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "from utils import T2FProblem\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib as plt\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath=\"./datasets/T2F/recon2.2_local_3state_dataset_var(R)5733_ineq(2R)11466_eq(M)5733_ex(Samples)741\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(filepath, 'rb') as f:\n",
    "    data = pickle.load(f)\n",
    "# for attr in dir(data):\n",
    "#     var = getattr(data, attr)\n",
    "#     if not callable(var) and not attr.startswith(\"__\") and torch.is_tensor(var):\n",
    "#         try:\n",
    "#             setattr(data, attr, var.to(DEVICE))\n",
    "#         except AttributeError:\n",
    "#             pass\n",
    "# data._device = DEVICE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_df=pd.DataFrame(data.Y_np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>5723</th>\n",
       "      <th>5724</th>\n",
       "      <th>5725</th>\n",
       "      <th>5726</th>\n",
       "      <th>5727</th>\n",
       "      <th>5728</th>\n",
       "      <th>5729</th>\n",
       "      <th>5730</th>\n",
       "      <th>5731</th>\n",
       "      <th>5732</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>...</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "      <td>7.410000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-2.651360e-07</td>\n",
       "      <td>-5.077263e-07</td>\n",
       "      <td>-1.010043e-06</td>\n",
       "      <td>-5.077263e-07</td>\n",
       "      <td>-5.077263e-07</td>\n",
       "      <td>-5.077263e-07</td>\n",
       "      <td>-4.070832e-07</td>\n",
       "      <td>-5.034273e-07</td>\n",
       "      <td>-5.077263e-07</td>\n",
       "      <td>-2.628323e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.276131e-07</td>\n",
       "      <td>-1.335268e-06</td>\n",
       "      <td>3.491766e-06</td>\n",
       "      <td>-6.693081e-07</td>\n",
       "      <td>2.228753e-06</td>\n",
       "      <td>5.939600e-07</td>\n",
       "      <td>1.879777e-06</td>\n",
       "      <td>5.343895e-07</td>\n",
       "      <td>8.115417e-07</td>\n",
       "      <td>8.859325e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.650407e-07</td>\n",
       "      <td>4.729435e-07</td>\n",
       "      <td>9.410051e-07</td>\n",
       "      <td>4.729435e-07</td>\n",
       "      <td>4.729435e-07</td>\n",
       "      <td>4.729435e-07</td>\n",
       "      <td>4.120443e-07</td>\n",
       "      <td>4.690700e-07</td>\n",
       "      <td>4.729435e-07</td>\n",
       "      <td>2.469742e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.037302e-06</td>\n",
       "      <td>1.788238e-06</td>\n",
       "      <td>3.431325e-06</td>\n",
       "      <td>6.433857e-07</td>\n",
       "      <td>2.179446e-06</td>\n",
       "      <td>6.841638e-07</td>\n",
       "      <td>1.776546e-06</td>\n",
       "      <td>5.510819e-07</td>\n",
       "      <td>1.152370e-06</td>\n",
       "      <td>9.919199e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-6.729473e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-1.943666e-06</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-1.241944e-06</td>\n",
       "      <td>-9.550955e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-5.795899e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.462188e-06</td>\n",
       "      <td>-4.595771e-06</td>\n",
       "      <td>-1.073024e-10</td>\n",
       "      <td>-1.603480e-06</td>\n",
       "      <td>-5.983620e-11</td>\n",
       "      <td>-5.391315e-10</td>\n",
       "      <td>-6.305575e-10</td>\n",
       "      <td>-2.605186e-10</td>\n",
       "      <td>-2.237952e-11</td>\n",
       "      <td>-1.563189e-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-5.489412e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-1.879871e-06</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-6.745520e-07</td>\n",
       "      <td>-9.494818e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-4.789089e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.000187e-06</td>\n",
       "      <td>-3.715265e-06</td>\n",
       "      <td>6.736212e-11</td>\n",
       "      <td>-1.366046e-06</td>\n",
       "      <td>4.034369e-11</td>\n",
       "      <td>-1.979656e-10</td>\n",
       "      <td>-8.196892e-11</td>\n",
       "      <td>-9.948684e-11</td>\n",
       "      <td>2.823432e-11</td>\n",
       "      <td>1.767459e-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-2.543466e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-1.851266e-06</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-6.287801e-07</td>\n",
       "      <td>-9.151318e-07</td>\n",
       "      <td>-9.476729e-07</td>\n",
       "      <td>-4.400909e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>1.801038e-10</td>\n",
       "      <td>-2.781850e-07</td>\n",
       "      <td>4.914341e-06</td>\n",
       "      <td>-9.714932e-07</td>\n",
       "      <td>3.207828e-06</td>\n",
       "      <td>6.834613e-07</td>\n",
       "      <td>3.100305e-06</td>\n",
       "      <td>7.642529e-07</td>\n",
       "      <td>3.257590e-07</td>\n",
       "      <td>9.199422e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-4.856198e-10</td>\n",
       "      <td>2.730847e-12</td>\n",
       "      <td>-3.178976e-12</td>\n",
       "      <td>2.730847e-12</td>\n",
       "      <td>2.730847e-12</td>\n",
       "      <td>2.730847e-12</td>\n",
       "      <td>7.473251e-10</td>\n",
       "      <td>-1.187412e-12</td>\n",
       "      <td>2.730847e-12</td>\n",
       "      <td>1.819256e-11</td>\n",
       "      <td>...</td>\n",
       "      <td>9.799781e-10</td>\n",
       "      <td>4.749103e-11</td>\n",
       "      <td>5.740427e-06</td>\n",
       "      <td>2.295480e-11</td>\n",
       "      <td>3.644562e-06</td>\n",
       "      <td>8.957798e-07</td>\n",
       "      <td>3.436797e-06</td>\n",
       "      <td>8.712622e-07</td>\n",
       "      <td>8.708549e-07</td>\n",
       "      <td>1.205267e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.119162e-10</td>\n",
       "      <td>5.388462e-12</td>\n",
       "      <td>1.344579e-11</td>\n",
       "      <td>5.388462e-12</td>\n",
       "      <td>5.388462e-12</td>\n",
       "      <td>5.388462e-12</td>\n",
       "      <td>1.920648e-09</td>\n",
       "      <td>4.292725e-12</td>\n",
       "      <td>5.388462e-12</td>\n",
       "      <td>4.858823e-11</td>\n",
       "      <td>...</td>\n",
       "      <td>6.603509e-07</td>\n",
       "      <td>4.573074e-07</td>\n",
       "      <td>9.448362e-06</td>\n",
       "      <td>1.358582e-10</td>\n",
       "      <td>5.861138e-06</td>\n",
       "      <td>2.497498e-06</td>\n",
       "      <td>4.593207e-06</td>\n",
       "      <td>1.795290e-06</td>\n",
       "      <td>3.441071e-06</td>\n",
       "      <td>2.851824e-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 5733 columns</p>\n",
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      ],
      "text/plain": [
       "               0             1             2             3             4     \\\n",
       "count  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02   \n",
       "mean  -2.651360e-07 -5.077263e-07 -1.010043e-06 -5.077263e-07 -5.077263e-07   \n",
       "std    2.650407e-07  4.729435e-07  9.410051e-07  4.729435e-07  4.729435e-07   \n",
       "min   -6.729473e-07 -9.476729e-07 -1.943666e-06 -9.476729e-07 -9.476729e-07   \n",
       "25%   -5.489412e-07 -9.476729e-07 -1.879871e-06 -9.476729e-07 -9.476729e-07   \n",
       "50%   -2.543466e-07 -9.476729e-07 -1.851266e-06 -9.476729e-07 -9.476729e-07   \n",
       "75%   -4.856198e-10  2.730847e-12 -3.178976e-12  2.730847e-12  2.730847e-12   \n",
       "max    1.119162e-10  5.388462e-12  1.344579e-11  5.388462e-12  5.388462e-12   \n",
       "\n",
       "               5             6             7             8             9     \\\n",
       "count  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02   \n",
       "mean  -5.077263e-07 -4.070832e-07 -5.034273e-07 -5.077263e-07 -2.628323e-07   \n",
       "std    4.729435e-07  4.120443e-07  4.690700e-07  4.729435e-07  2.469742e-07   \n",
       "min   -9.476729e-07 -1.241944e-06 -9.550955e-07 -9.476729e-07 -5.795899e-07   \n",
       "25%   -9.476729e-07 -6.745520e-07 -9.494818e-07 -9.476729e-07 -4.789089e-07   \n",
       "50%   -9.476729e-07 -6.287801e-07 -9.151318e-07 -9.476729e-07 -4.400909e-07   \n",
       "75%    2.730847e-12  7.473251e-10 -1.187412e-12  2.730847e-12  1.819256e-11   \n",
       "max    5.388462e-12  1.920648e-09  4.292725e-12  5.388462e-12  4.858823e-11   \n",
       "\n",
       "       ...          5723          5724          5725          5726  \\\n",
       "count  ...  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02   \n",
       "mean   ... -8.276131e-07 -1.335268e-06  3.491766e-06 -6.693081e-07   \n",
       "std    ...  1.037302e-06  1.788238e-06  3.431325e-06  6.433857e-07   \n",
       "min    ... -2.462188e-06 -4.595771e-06 -1.073024e-10 -1.603480e-06   \n",
       "25%    ... -2.000187e-06 -3.715265e-06  6.736212e-11 -1.366046e-06   \n",
       "50%    ...  1.801038e-10 -2.781850e-07  4.914341e-06 -9.714932e-07   \n",
       "75%    ...  9.799781e-10  4.749103e-11  5.740427e-06  2.295480e-11   \n",
       "max    ...  6.603509e-07  4.573074e-07  9.448362e-06  1.358582e-10   \n",
       "\n",
       "               5727          5728          5729          5730          5731  \\\n",
       "count  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02  7.410000e+02   \n",
       "mean   2.228753e-06  5.939600e-07  1.879777e-06  5.343895e-07  8.115417e-07   \n",
       "std    2.179446e-06  6.841638e-07  1.776546e-06  5.510819e-07  1.152370e-06   \n",
       "min   -5.983620e-11 -5.391315e-10 -6.305575e-10 -2.605186e-10 -2.237952e-11   \n",
       "25%    4.034369e-11 -1.979656e-10 -8.196892e-11 -9.948684e-11  2.823432e-11   \n",
       "50%    3.207828e-06  6.834613e-07  3.100305e-06  7.642529e-07  3.257590e-07   \n",
       "75%    3.644562e-06  8.957798e-07  3.436797e-06  8.712622e-07  8.708549e-07   \n",
       "max    5.861138e-06  2.497498e-06  4.593207e-06  1.795290e-06  3.441071e-06   \n",
       "\n",
       "               5732  \n",
       "count  7.410000e+02  \n",
       "mean   8.859325e-07  \n",
       "std    9.919199e-07  \n",
       "min   -1.563189e-11  \n",
       "25%    1.767459e-11  \n",
       "50%    9.199422e-07  \n",
       "75%    1.205267e-06  \n",
       "max    2.851824e-06  \n",
       "\n",
       "[8 rows x 5733 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>5723</th>\n",
       "      <th>5724</th>\n",
       "      <th>5725</th>\n",
       "      <th>5726</th>\n",
       "      <th>5727</th>\n",
       "      <th>5728</th>\n",
       "      <th>5729</th>\n",
       "      <th>5730</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>-5.104777e-10</td>\n",
       "      <td>2.736234e-12</td>\n",
       "      <td>1.653860e-12</td>\n",
       "      <td>2.736234e-12</td>\n",
       "      <td>2.736234e-12</td>\n",
       "      <td>2.736234e-12</td>\n",
       "      <td>1.062567e-09</td>\n",
       "      <td>-1.832964e-12</td>\n",
       "      <td>2.736234e-12</td>\n",
       "      <td>2.411327e-11</td>\n",
       "      <td>...</td>\n",
       "      <td>9.924393e-10</td>\n",
       "      <td>6.909028e-11</td>\n",
       "      <td>4.841676e-11</td>\n",
       "      <td>1.923465e-11</td>\n",
       "      <td>2.834454e-11</td>\n",
       "      <td>-2.636048e-10</td>\n",
       "      <td>-1.003037e-10</td>\n",
       "      <td>-1.312579e-10</td>\n",
       "      <td>3.478922e-11</td>\n",
       "      <td>2.155401e-11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 5733 columns</p>\n",
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      "text/plain": [
       "             0             1             2             3             4     \\\n",
       "633 -5.104777e-10  2.736234e-12  1.653860e-12  2.736234e-12  2.736234e-12   \n",
       "\n",
       "             5             6             7             8             9     \\\n",
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       "\n",
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           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "value"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "count"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "px.histogram(pd.DataFrame(sample.to_numpy().flatten()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('./results/SimpleProblem2-5733-11466-5733-741/baselineOpt-osqp/run/1705660660-302243/results.dict', 'rb') as f:\n",
    "    opt_results = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['valid_eval', 'valid_ineq_max', 'valid_ineq_mean', 'valid_ineq_num_viol_0', 'valid_ineq_num_viol_1', 'valid_ineq_num_viol_2', 'valid_eq_max', 'valid_eq_mean', 'valid_eq_num_viol_0', 'valid_eq_num_viol_1', 'valid_eq_num_viol_2', 'test_eval', 'test_ineq_max', 'test_ineq_mean', 'test_ineq_num_viol_0', 'test_ineq_num_viol_1', 'test_ineq_num_viol_2', 'test_eq_max', 'test_eq_mean', 'test_eq_num_viol_0', 'test_eq_num_viol_1', 'test_eq_num_viol_2', 'test_time', 'valid_time', 'train_time', 'test_time_total', 'valid_time_total', 'train_time_total'])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt_results.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.01993950e-02, -7.64827767e-03, -1.00827267e-02, -1.01763434e-02,\n",
       "       -7.77039220e-03,  1.61441513e-06,  1.90623243e-06, -9.01172092e-03,\n",
       "       -1.00122332e-02, -9.25951383e-03,  1.87621788e-06, -9.71268978e-03,\n",
       "       -9.55001461e-03, -9.58525519e-03,  1.66204416e-06,  2.47875762e-06,\n",
       "       -9.79765435e-03, -1.04030814e-02, -9.53603169e-03,  2.01553819e-06,\n",
       "        1.55006049e-06, -1.00214992e-02, -9.73159731e-03, -9.47782092e-03,\n",
       "        2.21552770e-06,  2.01996430e-06,  1.34743168e-06, -9.48409277e-03,\n",
       "       -9.45261368e-03, -1.00905261e-02,  1.81653277e-06, -9.93313596e-03,\n",
       "       -1.00113503e-02, -9.72165130e-03, -1.03470291e-02, -9.82794432e-03,\n",
       "       -9.42205214e-03,  1.37121772e-06,  1.75452727e-06,  2.10546735e-06,\n",
       "       -9.44671451e-03,  1.98508725e-06,  2.12353995e-06, -9.51811872e-03,\n",
       "       -9.48901808e-03, -9.52873288e-03,  2.02580515e-06,  1.50361615e-06,\n",
       "       -9.54671873e-03,  2.00192412e-06, -9.74291371e-03,  1.57366174e-06,\n",
       "       -1.01235640e-02,  1.91760433e-06, -8.86856594e-03, -9.79876911e-03,\n",
       "       -9.34380748e-03,  2.00167232e-06, -9.47214685e-03, -9.50257293e-03,\n",
       "       -9.22794522e-03, -9.55130013e-03])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt_results['valid_eval']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('./results/SimpleProblem2-5733-11466-5733-741/method/caa597b0a29e53bd08db9365c21934062c8d0a61/1705683032-043529/stats.dict', 'rb') as f:\n",
    "    y_hat=results = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_hat"
   ]
  }
 ],
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