fmda/rnn_workshop.ipynb

   1 {
   2  "cells": [
   3   {
   4    "cell_type": "markdown",
   5    "id": "244c2fb0-4339-476c-a2db-a641e124e25a",
   6    "metadata": {},
   7    "source": [
   8     "# v2.1 exploration trying to make it work better"
   9    ]
  10   },
  11   {
  12    "cell_type": "code",
  13    "execution_count": null,
  14    "id": "e6cc7920-e380-4b81-bac0-cd6840450e9a",
  15    "metadata": {},
  16    "outputs": [],
  17    "source": [
  18     "# Environment\n",
  19     "import os\n",
  20     "import os.path as osp\n",
  21     "import numpy as np\n",
  22     "import pandas as pd\n",
  23     "import tensorflow as tf\n",
  24     "import matplotlib.pyplot as plt\n",
  25     "import sys\n",
  26     "# Local modules\n",
  27     "sys.path.append('..')\n",
  28     "import reproducibility\n",
  29     "import pandas as pd\n",
  30     "from utils import print_dict_summary\n",
  31     "from data_funcs import rmse\n",
  32     "from moisture_rnn import RNNParams, RNNData, RNN, RNN_LSTM, create_rnn_data2\n",
  33     "from moisture_rnn_pkl import pkl2train\n",
  34     "from tensorflow.keras.callbacks import Callback\n",
  35     "from utils import hash2\n",
  36     "import copy\n",
  37     "import logging\n",
  38     "import pickle\n",
  39     "from utils import logging_setup, read_yml, read_pkl, hash_ndarray, hash_weights\n",
  40     "import yaml\n",
  41     "import copy"
  42    ]
  43   },
  44   {
  45    "cell_type": "code",
  46    "execution_count": null,
  47    "id": "f58e8839-bf0e-4995-b966-c09e4df001ce",
  48    "metadata": {},
  49    "outputs": [],
  50    "source": [
  51     "logging_setup()"
  52    ]
  53   },
  54   {
  55    "cell_type": "markdown",
  56    "id": "b62f4360-e9d1-4510-bb5d-1d79a3a5ac75",
  57    "metadata": {},
  58    "source": [
  59     "## Tests"
  60    ]
  61   },
  62   {
  63    "cell_type": "code",
  64    "execution_count": null,
  65    "id": "91155de8-1927-4485-80c9-095fb4d8613d",
  66    "metadata": {
  67     "scrolled": true
  68    },
  69    "outputs": [],
  70    "source": [
  71     "# data_file = 'data/test_CA_202401.pkl'\n",
  72     "# train = pkl2train([data_file])\n",
  73     "# # with open(\"train.pkl\", 'wb') as file:\n",
  74     "# #     logging.info('Writing the rain cases into file %s',\"train.pkl\")\n",
  75     "# #     pickle.dump(train, file)\n",
  76     "# train.keys()\n",
  77     "\n",
  78     "train = read_pkl(\"train.pkl\")"
  79    ]
  80   },
  81   {
  82    "cell_type": "code",
  83    "execution_count": null,
  84    "id": "a5979f46-7e1a-4552-a92f-fc17d2ca75b4",
  85    "metadata": {},
  86    "outputs": [],
  87    "source": [
  88     "train.keys()"
  89    ]
  90   },
  91   {
  92    "cell_type": "code",
  93    "execution_count": null,
  94    "id": "1bc6a3c7-e068-4d83-9ab0-131eaeec289e",
  95    "metadata": {},
  96    "outputs": [],
  97    "source": [
  98     "case = \"FBFW1_202401\"\n",
  99     "dat = train[case]"
 100    ]
 101   },
 102   {
 103    "cell_type": "code",
 104    "execution_count": null,
 105    "id": "84a4e8b6-9762-4406-b71e-bb6bf990fd9b",
 106    "metadata": {},
 107    "outputs": [],
 108    "source": [
 109     "params = read_yml(\"params.yaml\", subkey=\"rnn\")\n",
 110     "params = RNNParams(params)\n",
 111     "params"
 112    ]
 113   },
 114   {
 115    "cell_type": "code",
 116    "execution_count": null,
 117    "id": "92b7a5ed-5215-43a7-933c-5dd146241944",
 118    "metadata": {},
 119    "outputs": [],
 120    "source": [
 121     "rnn_dat = RNNData(dat, scaler = params['scaler'], features_list = params['features_list'])\n",
 122     "rnn_dat.train_test_split(\n",
 123     "    train_frac = .9,\n",
 124     "    val_frac = .05\n",
 125     ")\n",
 126     "rnn_dat.scale_data()"
 127    ]
 128   },
 129   {
 130    "cell_type": "code",
 131    "execution_count": null,
 132    "id": "9141a034-5912-4087-aaaa-a4c221e77495",
 133    "metadata": {},
 134    "outputs": [],
 135    "source": [
 136     "import importlib\n",
 137     "import moisture_rnn\n",
 138     "importlib.reload(moisture_rnn)\n",
 139     "from moisture_rnn import RNN"
 140    ]
 141   },
 142   {
 143    "cell_type": "code",
 144    "execution_count": null,
 145    "id": "2c570a67-0b67-4fe4-a536-68cf5a1f8256",
 146    "metadata": {},
 147    "outputs": [],
 148    "source": [
 149     "params.update({'epochs': 20})\n",
 150     "reproducibility.set_seed(123)\n",
 151     "rnn = RNN(params)\n"
 152    ]
 153   },
 154   {
 155    "cell_type": "code",
 156    "execution_count": null,
 157    "id": "034300ff-a71e-4807-85d7-368197962ab5",
 158    "metadata": {},
 159    "outputs": [],
 160    "source": [
 161     "m, errs = rnn.run_model(rnn_dat)"
 162    ]
 163   },
 164   {
 165    "cell_type": "code",
 166    "execution_count": null,
 167    "id": "1f5183e0-5e58-4ff3-9a1f-0f707241a698",
 168    "metadata": {},
 169    "outputs": [],
 170    "source": [
 171     "rnn.model_train"
 172    ]
 173   },
 174   {
 175    "cell_type": "code",
 176    "execution_count": null,
 177    "id": "0dc33ddc-cb10-4b0c-b7f2-af3302e28a23",
 178    "metadata": {},
 179    "outputs": [],
 180    "source": []
 181   },
 182   {
 183    "cell_type": "code",
 184    "execution_count": null,
 185    "id": "ebb4d0d3-0a9e-428e-bd56-6899bde36df7",
 186    "metadata": {},
 187    "outputs": [],
 188    "source": []
 189   },
 190   {
 191    "cell_type": "markdown",
 192    "id": "a42cc05f-1438-459f-9a15-64276aa2f651",
 193    "metadata": {},
 194    "source": [
 195     "## Test RNN"
 196    ]
 197   },
 198   {
 199    "cell_type": "code",
 200    "execution_count": null,
 201    "id": "d27c7277-c9e1-4fd1-b050-d4b6bc737822",
 202    "metadata": {},
 203    "outputs": [],
 204    "source": [
 205     "import importlib\n",
 206     "import utils\n",
 207     "importlib.reload(utils)\n",
 208     "from utils import read_pkl"
 209    ]
 210   },
 211   {
 212    "cell_type": "code",
 213    "execution_count": null,
 214    "id": "7a9a5414-d33f-4f0d-b1e5-b320b22d60f5",
 215    "metadata": {},
 216    "outputs": [],
 217    "source": [
 218     "train = read_pkl(\"train.pkl\")"
 219    ]
 220   },
 221   {
 222    "cell_type": "code",
 223    "execution_count": null,
 224    "id": "e0147836-f6ba-4141-9c9d-7c2e5d676bc2",
 225    "metadata": {},
 226    "outputs": [],
 227    "source": [
 228     "params = read_yml(\"params.yaml\", subkey=\"rnn\")\n",
 229     "params = RNNParams(params)"
 230    ]
 231   },
 232   {
 233    "cell_type": "code",
 234    "execution_count": null,
 235    "id": "4219f8e0-cf44-43a6-830b-fc859c3d954b",
 236    "metadata": {},
 237    "outputs": [],
 238    "source": [
 239     "params.update({'activation': ['linear', 'linear'], 'epochs':300, 'val_frac': .2, 'scaler': 'minmax', 'rnn_layers': 1, 'dense_layers': 1})"
 240    ]
 241   },
 242   {
 243    "cell_type": "code",
 244    "execution_count": null,
 245    "id": "722bd100-beaa-49c7-a1ab-b72765c89ebe",
 246    "metadata": {},
 247    "outputs": [],
 248    "source": [
 249     "rnn_dat = RNNData(train['NV020_202401'], scaler = params['scaler'], features_list = params['features_list'])"
 250    ]
 251   },
 252   {
 253    "cell_type": "code",
 254    "execution_count": null,
 255    "id": "2eb4adf9-c4eb-493c-9f62-59ba17f6da2f",
 256    "metadata": {},
 257    "outputs": [],
 258    "source": [
 259     "rnn_dat.train_test_split(\n",
 260     "    train_frac = params['train_frac'],\n",
 261     "    val_frac = params['val_frac']\n",
 262     ")"
 263    ]
 264   },
 265   {
 266    "cell_type": "code",
 267    "execution_count": null,
 268    "id": "2b4fa4e1-c1b9-483a-83ac-cf0ee46662fa",
 269    "metadata": {},
 270    "outputs": [],
 271    "source": [
 272     "rnn_dat.scale_data()"
 273    ]
 274   },
 275   {
 276    "cell_type": "code",
 277    "execution_count": null,
 278    "id": "fc362aa4-fe28-4848-9575-bb17f72ac9fd",
 279    "metadata": {},
 280    "outputs": [],
 281    "source": [
 282     "import importlib\n",
 283     "import moisture_rnn\n",
 284     "importlib.reload(moisture_rnn)\n",
 285     "from moisture_rnn import RNN"
 286    ]
 287   },
 288   {
 289    "cell_type": "code",
 290    "execution_count": null,
 291    "id": "79381a0b-2338-4a09-876e-91e50b968d3f",
 292    "metadata": {},
 293    "outputs": [],
 294    "source": [
 295     "rnn = RNN(params)"
 296    ]
 297   },
 298   {
 299    "cell_type": "code",
 300    "execution_count": null,
 301    "id": "155cebc4-e7f6-47ae-943e-556c3939ab95",
 302    "metadata": {},
 303    "outputs": [],
 304    "source": [
 305     "rnn.predict(rnn_dat.X_test)"
 306    ]
 307   },
 308   {
 309    "cell_type": "code",
 310    "execution_count": null,
 311    "id": "7d28dd8c-3d90-43ba-842e-4d4ed5deb823",
 312    "metadata": {},
 313    "outputs": [],
 314    "source": [
 315     "rnn.model_predict.summary()"
 316    ]
 317   },
 318   {
 319    "cell_type": "code",
 320    "execution_count": null,
 321    "id": "1f928e06-867e-4cc5-ab94-83b30b923374",
 322    "metadata": {},
 323    "outputs": [],
 324    "source": [
 325     "reproducibility.set_seed(123)\n",
 326     "rnn = RNN(params)\n",
 327     "m, errs = rnn.run_model(rnn_dat)"
 328    ]
 329   },
 330   {
 331    "cell_type": "code",
 332    "execution_count": null,
 333    "id": "4b4ca16e-7c40-4bb9-b971-dd0efa4e8a83",
 334    "metadata": {},
 335    "outputs": [],
 336    "source": []
 337   },
 338   {
 339    "cell_type": "code",
 340    "execution_count": null,
 341    "id": "54c917e9-20a6-4b8d-b6ab-04fdb0333467",
 342    "metadata": {},
 343    "outputs": [],
 344    "source": []
 345   },
 346   {
 347    "cell_type": "code",
 348    "execution_count": null,
 349    "id": "7c659050-e74e-4f07-b95a-3f7b57653061",
 350    "metadata": {},
 351    "outputs": [],
 352    "source": []
 353   },
 354   {
 355    "cell_type": "code",
 356    "execution_count": null,
 357    "id": "e86c9e4d-4ccd-4d9d-92e1-2e4299549fa4",
 358    "metadata": {},
 359    "outputs": [],
 360    "source": []
 361   },
 362   {
 363    "cell_type": "code",
 364    "execution_count": null,
 365    "id": "966c3559-740d-44d3-b98d-cc2efe63afcd",
 366    "metadata": {},
 367    "outputs": [],
 368    "source": []
 369   },
 370   {
 371    "cell_type": "code",
 372    "execution_count": null,
 373    "id": "52c1df9f-87ab-4882-aca1-e90cca7bd470",
 374    "metadata": {},
 375    "outputs": [],
 376    "source": []
 377   },
 378   {
 379    "cell_type": "code",
 380    "execution_count": null,
 381    "id": "1addf015-b2c1-42df-a769-39df81dd5d14",
 382    "metadata": {},
 383    "outputs": [],
 384    "source": []
 385   },
 386   {
 387    "cell_type": "code",
 388    "execution_count": null,
 389    "id": "3262a73f-0bd7-4e78-ade0-ca53a7da2b84",
 390    "metadata": {},
 391    "outputs": [],
 392    "source": []
 393   },
 394   {
 395    "cell_type": "code",
 396    "execution_count": null,
 397    "id": "eecfd38b-0a1a-4de3-b568-2f53ffbcc78c",
 398    "metadata": {},
 399    "outputs": [],
 400    "source": []
 401   },
 402   {
 403    "cell_type": "markdown",
 404    "id": "2298a1a1-b72c-4c7e-bcb6-2cdefe96fe3e",
 405    "metadata": {},
 406    "source": [
 407     "## Test Data Creation"
 408    ]
 409   },
 410   {
 411    "cell_type": "code",
 412    "execution_count": null,
 413    "id": "c4645246-edce-4544-9809-5ffb0760ae25",
 414    "metadata": {},
 415    "outputs": [],
 416    "source": [
 417     "import importlib\n",
 418     "import moisture_rnn_pkl\n",
 419     "importlib.reload(moisture_rnn_pkl)\n",
 420     "from moisture_rnn_pkl import pkl2train"
 421    ]
 422   },
 423   {
 424    "cell_type": "code",
 425    "execution_count": null,
 426    "id": "5b662edb-7a79-4532-b0d7-2492b1ad917d",
 427    "metadata": {},
 428    "outputs": [],
 429    "source": [
 430     "file_names=['test_CA_202401.pkl', 'test_NW_202401.pkl']\n",
 431     "file_dir='data'\n",
 432     "file_paths = [osp.join(file_dir,file_name) for file_name in file_names]"
 433    ]
 434   },
 435   {
 436    "cell_type": "code",
 437    "execution_count": null,
 438    "id": "1185c995-e9fa-4586-96c2-44b159ccf477",
 439    "metadata": {
 440     "scrolled": true
 441    },
 442    "outputs": [],
 443    "source": [
 444     "train = pkl2train(file_paths)"
 445    ]
 446   },
 447   {
 448    "cell_type": "code",
 449    "execution_count": null,
 450    "id": "665291be-0f40-46b5-9a63-27a58965f8ca",
 451    "metadata": {},
 452    "outputs": [],
 453    "source": [
 454     "train.keys()"
 455    ]
 456   },
 457   {
 458    "cell_type": "code",
 459    "execution_count": null,
 460    "id": "6b61a406-eed8-4595-9c3f-4c11e1aed7c8",
 461    "metadata": {},
 462    "outputs": [],
 463    "source": []
 464   },
 465   {
 466    "cell_type": "code",
 467    "execution_count": null,
 468    "id": "e234b0f6-3cc9-46d1-926a-d825c58e3991",
 469    "metadata": {},
 470    "outputs": [],
 471    "source": []
 472   },
 473   {
 474    "cell_type": "code",
 475    "execution_count": null,
 476    "id": "7fdf595c-68e1-4e93-a5ec-d6e20e2f1bdf",
 477    "metadata": {},
 478    "outputs": [],
 479    "source": []
 480   },
 481   {
 482    "cell_type": "code",
 483    "execution_count": null,
 484    "id": "fc3e8264-da29-4261-a560-ef457f42ed70",
 485    "metadata": {},
 486    "outputs": [],
 487    "source": []
 488   },
 489   {
 490    "cell_type": "code",
 491    "execution_count": null,
 492    "id": "7deda359-1e7f-447a-97b7-576b98712a74",
 493    "metadata": {},
 494    "outputs": [],
 495    "source": []
 496   },
 497   {
 498    "cell_type": "code",
 499    "execution_count": null,
 500    "id": "7fc05c26-9a54-4863-8956-d76913128701",
 501    "metadata": {},
 502    "outputs": [],
 503    "source": []
 504   },
 505   {
 506    "cell_type": "markdown",
 507    "id": "2afc2cf7-eab1-4a85-8632-4d306aead358",
 508    "metadata": {},
 509    "source": [
 510     "## Test RNN"
 511    ]
 512   },
 513   {
 514    "cell_type": "code",
 515    "execution_count": null,
 516    "id": "bfd419f0-9092-470d-81b7-d3b45e4bdc0b",
 517    "metadata": {},
 518    "outputs": [],
 519    "source": []
 520   },
 521   {
 522    "cell_type": "code",
 523    "execution_count": null,
 524    "id": "545ece65-9f4a-4b45-b87f-ea3a23032cac",
 525    "metadata": {},
 526    "outputs": [],
 527    "source": []
 528   },
 529   {
 530    "cell_type": "code",
 531    "execution_count": null,
 532    "id": "1e9ec6f9-8598-4560-b71e-222f5b4c4968",
 533    "metadata": {},
 534    "outputs": [],
 535    "source": []
 536   },
 537   {
 538    "cell_type": "code",
 539    "execution_count": null,
 540    "id": "e2a7840d-f7e4-424d-b343-06f913f9d3f6",
 541    "metadata": {},
 542    "outputs": [],
 543    "source": []
 544   },
 545   {
 546    "cell_type": "code",
 547    "execution_count": null,
 548    "id": "52e2942b-3bed-4c3d-8082-c7069d791036",
 549    "metadata": {},
 550    "outputs": [],
 551    "source": []
 552   },
 553   {
 554    "cell_type": "code",
 555    "execution_count": null,
 556    "id": "def73f2c-5d2f-42c6-8c2d-328ac5e8db20",
 557    "metadata": {},
 558    "outputs": [],
 559    "source": []
 560   },
 561   {
 562    "cell_type": "code",
 563    "execution_count": null,
 564    "id": "888dd72a-4eef-414b-ac33-f6f4bfbefe60",
 565    "metadata": {},
 566    "outputs": [],
 567    "source": [
 568     "errs"
 569    ]
 570   },
 571   {
 572    "cell_type": "code",
 573    "execution_count": null,
 574    "id": "7f40cdfd-b33a-43c1-8bc4-44a0ea6817ff",
 575    "metadata": {},
 576    "outputs": [],
 577    "source": [
 578     "import importlib \n",
 579     "import moisture_rnn\n",
 580     "importlib.reload(moisture_rnn)\n",
 581     "from moisture_rnn import RNN"
 582    ]
 583   },
 584   {
 585    "cell_type": "code",
 586    "execution_count": null,
 587    "id": "bdf0ba2e-f944-4c86-a20e-a59e023897cb",
 588    "metadata": {},
 589    "outputs": [],
 590    "source": [
 591     "params = read_yml(\"params.yaml\", subkey=\"rnn\")\n",
 592     "params = RNNParams(params)"
 593    ]
 594   },
 595   {
 596    "cell_type": "code",
 597    "execution_count": null,
 598    "id": "9dbd51b0-9342-4b90-a250-0ac2c75d3066",
 599    "metadata": {},
 600    "outputs": [],
 601    "source": [
 602     "reproducibility.set_seed()\n",
 603     "rnn = RNN(params)\n",
 604     "m, errs = rnn.run_model(rnn_dat)"
 605    ]
 606   },
 607   {
 608    "cell_type": "code",
 609    "execution_count": null,
 610    "id": "c6d7d34c-dfae-4370-a398-a287790eff53",
 611    "metadata": {},
 612    "outputs": [],
 613    "source": []
 614   },
 615   {
 616    "cell_type": "markdown",
 617    "id": "d2360aef-e9c4-4a71-922d-336e53b82537",
 618    "metadata": {},
 619    "source": [
 620     "## LSTM\n",
 621     "\n",
 622     "TODO: FIX BELOW"
 623    ]
 624   },
 625   {
 626    "cell_type": "code",
 627    "execution_count": null,
 628    "id": "71d4e441-9bf1-4d57-bb37-091553e23212",
 629    "metadata": {},
 630    "outputs": [],
 631    "source": [
 632     "import importlib \n",
 633     "import moisture_rnn\n",
 634     "importlib.reload(moisture_rnn)\n",
 635     "from moisture_rnn import RNN_LSTM"
 636    ]
 637   },
 638   {
 639    "cell_type": "code",
 640    "execution_count": null,
 641    "id": "59480f19-3567-4b24-b6ff-d9292dc8c2ec",
 642    "metadata": {},
 643    "outputs": [],
 644    "source": [
 645     "with open(\"params.yaml\") as file:\n",
 646     "    params = yaml.safe_load(file)[\"lstm\"]\n",
 647     "    \n",
 648     "rnn_dat2 = create_rnn_data2(train[case],params)"
 649    ]
 650   },
 651   {
 652    "cell_type": "code",
 653    "execution_count": null,
 654    "id": "2adff592-7aa4-4e59-a229-cad4a133297e",
 655    "metadata": {},
 656    "outputs": [],
 657    "source": [
 658     "params.update({'epochs': 10})"
 659    ]
 660   },
 661   {
 662    "cell_type": "code",
 663    "execution_count": null,
 664    "id": "b20539f0-eed2-44de-9269-ae8696c8e7c8",
 665    "metadata": {},
 666    "outputs": [],
 667    "source": []
 668   },
 669   {
 670    "cell_type": "code",
 671    "execution_count": null,
 672    "id": "6bfbcbb5-b631-4594-9ae5-618c4fe68e7b",
 673    "metadata": {},
 674    "outputs": [],
 675    "source": [
 676     "reproducibility.set_seed()\n",
 677     "rnn = RNN(params)\n",
 678     "m, errs = rnn.run_model(rnn_dat2)"
 679    ]
 680   },
 681   {
 682    "cell_type": "code",
 683    "execution_count": null,
 684    "id": "dd8a9700-f479-4c11-8655-ca7b45222402",
 685    "metadata": {},
 686    "outputs": [],
 687    "source": []
 688   },
 689   {
 690    "cell_type": "code",
 691    "execution_count": null,
 692    "id": "de46c481-74a7-46cc-8334-678ad8230cce",
 693    "metadata": {},
 694    "outputs": [],
 695    "source": [
 696     "import importlib\n",
 697     "importlib.reload(moisture_rnn)\n",
 698     "from moisture_rnn import RNN_LSTM"
 699    ]
 700   },
 701   {
 702    "cell_type": "code",
 703    "execution_count": null,
 704    "id": "2b6a699a-68e8-49ef-95f2-409137502fb6",
 705    "metadata": {},
 706    "outputs": [],
 707    "source": [
 708     "with open(\"params.yaml\") as file:\n",
 709     "    params = yaml.safe_load(file)[\"lstm\"]\n",
 710     "\n",
 711     "rnn_dat2 = create_rnn_data2(train[case],params)\n",
 712     "params"
 713    ]
 714   },
 715   {
 716    "cell_type": "code",
 717    "execution_count": null,
 718    "id": "188c0d5d-f3f6-4a61-83b0-b21dfc5d01b7",
 719    "metadata": {},
 720    "outputs": [],
 721    "source": [
 722     "params.update({\n",
 723     "    'learning_rate': 0.000001,\n",
 724     "    'epochs': 10,\n",
 725     "    'clipvalue':1.0\n",
 726     "})"
 727    ]
 728   },
 729   {
 730    "cell_type": "code",
 731    "execution_count": null,
 732    "id": "6a9d612e-8cd2-40ca-a789-91c99c3d6ccd",
 733    "metadata": {},
 734    "outputs": [],
 735    "source": [
 736     "reproducibility.set_seed()\n",
 737     "lstm = RNN_LSTM(params)\n",
 738     "m, errs = lstm.run_model(rnn_dat2)"
 739    ]
 740   },
 741   {
 742    "cell_type": "code",
 743    "execution_count": null,
 744    "id": "ec95e7d4-6d57-441b-b673-f10625ee5dec",
 745    "metadata": {},
 746    "outputs": [],
 747    "source": []
 748   },
 749   {
 750    "cell_type": "code",
 751    "execution_count": null,
 752    "id": "9b3c8d8d-ea50-44ea-8c0c-414e07cd01ac",
 753    "metadata": {},
 754    "outputs": [],
 755    "source": []
 756   },
 757   {
 758    "cell_type": "code",
 759    "execution_count": null,
 760    "id": "03063e3c-e8f4-451d-b0cf-25bd965cd9d6",
 761    "metadata": {},
 762    "outputs": [],
 763    "source": []
 764   },
 765   {
 766    "cell_type": "code",
 767    "execution_count": null,
 768    "id": "f60a24c6-9a67-45aa-bc5c-8818aa0ca049",
 769    "metadata": {},
 770    "outputs": [],
 771    "source": []
 772   }
 773  ],
 774  "metadata": {
 775   "kernelspec": {
 776    "display_name": "Python 3 (ipykernel)",
 777    "language": "python",
 778    "name": "python3"
 779   },
 780   "language_info": {
 781    "codemirror_mode": {
 782     "name": "ipython",
 783     "version": 3
 784    },
 785    "file_extension": ".py",
 786    "mimetype": "text/x-python",
 787    "name": "python",
 788    "nbconvert_exporter": "python",
 789    "pygments_lexer": "ipython3",
 790    "version": "3.12.5"
 791   }
 792  },
 793  "nbformat": 4,
 794  "nbformat_minor": 5
 795 }