analysis_global_optima.ipynb

{
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  {
   "cell_type": "code",
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   "id": "357129b8-4c67-4876-9fcf-ecefae5c0f78",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9d9bb4c5-7f01-45a0-8d29-0b2a423c33ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfe = pd.read_csv('r490.csv')\n",
    "dfe = dfe[dfe['r1_charge_heater'] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2e99e24a-cea8-4f47-a7cd-1a3686600f63",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>optimization mode</th>\n",
       "      <th>process_ron</th>\n",
       "      <th>process_yield</th>\n",
       "      <th>r1_charge_heater</th>\n",
       "      <th>r1_temp</th>\n",
       "      <th>r1_pressure</th>\n",
       "      <th>r2_temp</th>\n",
       "      <th>r2_pressure</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>optimization target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>process_ron</th>\n",
       "      <td>max</td>\n",
       "      <td>83.775</td>\n",
       "      <td>97.763</td>\n",
       "      <td>3.380</td>\n",
       "      <td>138.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>process_yield</th>\n",
       "      <td>max</td>\n",
       "      <td>83.224</td>\n",
       "      <td>98.195</td>\n",
       "      <td>0.051</td>\n",
       "      <td>132.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r1_charge_heater</th>\n",
       "      <td>min</td>\n",
       "      <td>83.246</td>\n",
       "      <td>98.183</td>\n",
       "      <td>0.005</td>\n",
       "      <td>132.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                    optimization mode  process_ron  process_yield  \\\n",
       "optimization target                                                 \n",
       "process_ron                       max       83.775         97.763   \n",
       "process_yield                     max       83.224         98.195   \n",
       "r1_charge_heater                  min       83.246         98.183   \n",
       "\n",
       "                     r1_charge_heater  r1_temp  r1_pressure  r2_temp  \\\n",
       "optimization target                                                    \n",
       "process_ron                     3.380    138.0         50.0    142.0   \n",
       "process_yield                   0.051    132.0         90.0    128.0   \n",
       "r1_charge_heater                0.005    132.0         60.0    128.0   \n",
       "\n",
       "                     r2_pressure  \n",
       "optimization target               \n",
       "process_ron                 70.0  \n",
       "process_yield               90.0  \n",
       "r1_charge_heater            60.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_cols = ['process_ron', 'process_yield', 'r1_charge_heater']\n",
    "target_modes = [np.argmax, np.argmax, np.argmin]\n",
    "\n",
    "monitored_cols = target_cols + ['r1_temp', 'r1_pressure', 'r2_temp', 'r2_pressure']\n",
    "\n",
    "ixs = []\n",
    "for target_col, target_mode in zip(target_cols, target_modes):\n",
    "    ix_best = target_mode(dfe[target_col])\n",
    "    ixs.append(ix_best)\n",
    "\n",
    "global_sol = dfe.iloc[ixs][monitored_cols].copy()\n",
    "global_sol.index = target_cols\n",
    "global_sol.index.rename('optimization target', inplace=True)\n",
    "global_sol['optimization mode'] = [tm.__name__.replace('arg','') for tm in target_modes]\n",
    "global_sol = global_sol[['optimization mode'] + list(global_sol.columns)[:-1]]\n",
    "global_sol['r1_charge_heater'] /= 1000000\n",
    "global_sol.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7f36e451-eb7b-4271-8139-34f5d75eceb3",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>optimization mode</th>\n",
       "      <th>process_ron</th>\n",
       "      <th>process_yield</th>\n",
       "      <th>r1_charge_heater</th>\n",
       "      <th>r1_temp</th>\n",
       "      <th>r1_pressure</th>\n",
       "      <th>r2_temp</th>\n",
       "      <th>r2_pressure</th>\n",
       "      <th>ron_loss_perc</th>\n",
       "      <th>yield_loss_perc</th>\n",
       "      <th>ch_increase_ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>optimization target</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>process_ron</th>\n",
       "      <td>max</td>\n",
       "      <td>83.78</td>\n",
       "      <td>97.76</td>\n",
       "      <td>3.38</td>\n",
       "      <td>138.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.44</td>\n",
       "      <td>679.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>process_yield</th>\n",
       "      <td>max</td>\n",
       "      <td>83.22</td>\n",
       "      <td>98.19</td>\n",
       "      <td>0.05</td>\n",
       "      <td>132.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r1_charge_heater</th>\n",
       "      <td>min</td>\n",
       "      <td>83.25</td>\n",
       "      <td>98.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>132.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    optimization mode  process_ron  process_yield  \\\n",
       "optimization target                                                 \n",
       "process_ron                       max        83.78          97.76   \n",
       "process_yield                     max        83.22          98.19   \n",
       "r1_charge_heater                  min        83.25          98.18   \n",
       "\n",
       "                     r1_charge_heater  r1_temp  r1_pressure  r2_temp  \\\n",
       "optimization target                                                    \n",
       "process_ron                      3.38    138.0         50.0    142.0   \n",
       "process_yield                    0.05    132.0         90.0    128.0   \n",
       "r1_charge_heater                 0.00    132.0         60.0    128.0   \n",
       "\n",
       "                     r2_pressure  ron_loss_perc  yield_loss_perc  \\\n",
       "optimization target                                                \n",
       "process_ron                 70.0           0.00             0.44   \n",
       "process_yield               90.0           0.66             0.00   \n",
       "r1_charge_heater            60.0           0.63             0.01   \n",
       "\n",
       "                     ch_increase_ratio  \n",
       "optimization target                     \n",
       "process_ron                     679.62  \n",
       "process_yield                    10.18  \n",
       "r1_charge_heater                  1.00  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_ron = np.max(global_sol['process_ron'])\n",
    "max_yield = np.max(global_sol['process_yield'])\n",
    "min_ch = np.min(global_sol['r1_charge_heater'])\n",
    "\n",
    "global_sol['ron_loss_perc'] = (max_ron - global_sol['process_ron']) * 100 / max_ron\n",
    "global_sol['yield_loss_perc'] = (max_yield - global_sol['process_yield']) * 100 / max_yield\n",
    "global_sol['ch_increase_ratio'] = global_sol['r1_charge_heater']/ min_ch\n",
    "global_sol.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "97afdf6a-b4aa-45f8-a762-506711f919b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "global_sol.to_csv(\"tmp/table2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2a226c5-7267-4d5c-873f-b4d764974296",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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