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": "b8fe1011-a0cc-46a4-98b7-d82c2b22f5b0",
  57    "metadata": {},
  58    "source": [
  59     "## Test Batch Reset"
  60    ]
  61   },
  62   {
  63    "cell_type": "code",
  64    "execution_count": null,
  65    "id": "0df1c817-d422-4cfa-a4c5-b02549cdaffa",
  66    "metadata": {
  67     "scrolled": true
  68    },
  69    "outputs": [],
  70    "source": [
  71     "train = read_pkl('train.pkl')\n",
  72     "train.keys()"
  73    ]
  74   },
  75   {
  76    "cell_type": "code",
  77    "execution_count": null,
  78    "id": "4f2623ea-3504-446e-8243-f93ccce6b62e",
  79    "metadata": {},
  80    "outputs": [],
  81    "source": [
  82     "import importlib\n",
  83     "import moisture_rnn\n",
  84     "importlib.reload(moisture_rnn)\n",
  85     "from moisture_rnn import RNN, RNNData"
  86    ]
  87   },
  88   {
  89    "cell_type": "code",
  90    "execution_count": null,
  91    "id": "948138a6-1854-428c-b5ec-75e87c9c50e7",
  92    "metadata": {},
  93    "outputs": [],
  94    "source": [
  95     "params = read_yml(\"params.yaml\", subkey=\"rnn\")\n",
  96     "params = RNNParams(params)\n",
  97     "rnn_dat = RNNData(train['PLFI1_202401'], scaler=params['scaler'], features_list = params['features_list'])\n",
  98     "rnn_dat.train_test_split(\n",
  99     "    train_frac = .9,\n",
 100     "    val_frac = .05\n",
 101     ")\n",
 102     "rnn_dat.scale_data()\n",
 103     "rnn_dat.batch_reshape(timesteps = params['timesteps'], batch_size = params['batch_size'])"
 104    ]
 105   },
 106   {
 107    "cell_type": "code",
 108    "execution_count": null,
 109    "id": "78255617-5511-4e54-a022-8dba9946bbe2",
 110    "metadata": {},
 111    "outputs": [],
 112    "source": [
 113     "reproducibility.set_seed()\n",
 114     "params.update({'batch_schedule_type': 'exp', 'bmin': 20, 'bmax': rnn_dat.hours})\n",
 115     "rnn = RNN(params)\n",
 116     "m, errs = rnn.run_model(rnn_dat, plot_period=\"predict\")"
 117    ]
 118   },
 119   {
 120    "cell_type": "code",
 121    "execution_count": null,
 122    "id": "d3a32de3-9556-491a-9bf1-3d252762f2b7",
 123    "metadata": {},
 124    "outputs": [],
 125    "source": []
 126   },
 127   {
 128    "cell_type": "code",
 129    "execution_count": null,
 130    "id": "2a7d607c-8f29-4a18-948b-4d939ebd5a34",
 131    "metadata": {},
 132    "outputs": [],
 133    "source": []
 134   },
 135   {
 136    "cell_type": "code",
 137    "execution_count": null,
 138    "id": "552c6e02-4a2d-4f50-9d6a-7e11bdbcfffc",
 139    "metadata": {},
 140    "outputs": [],
 141    "source": []
 142   },
 143   {
 144    "cell_type": "code",
 145    "execution_count": null,
 146    "id": "5cfd0dbe-8e7d-4d9e-a21c-9001a498084c",
 147    "metadata": {},
 148    "outputs": [],
 149    "source": [
 150     "params.update({'epochs': 2, 'verbose_fit': True, 'batch_size': 32, \n",
 151     "        'rnn_layers': 2, 'activation':['relu', 'relu']})\n",
 152     "rnn_dat = RNNData(train['PLFI1_202401'], scaler=params['scaler'], features_list = params['features_list'])\n",
 153     "rnn_dat.train_test_split(\n",
 154     "    train_frac = .9,\n",
 155     "    val_frac = .05\n",
 156     ")\n",
 157     "rnn_dat.scale_data()\n",
 158     "rnn_dat.batch_reshape(timesteps = params['timesteps'], batch_size = params['batch_size'])\n",
 159     "reproducibility.set_seed()\n",
 160     "rnn = RNN(params)\n",
 161     "m, errs = rnn.run_model(rnn_dat, plot_period=\"predict\")"
 162    ]
 163   },
 164   {
 165    "cell_type": "code",
 166    "execution_count": null,
 167    "id": "db2abad4-16d4-4afc-a0d8-b2dec6b872c2",
 168    "metadata": {},
 169    "outputs": [],
 170    "source": []
 171   },
 172   {
 173    "cell_type": "code",
 174    "execution_count": null,
 175    "id": "74158e6e-c84f-4a90-9f0a-c35cb711d9ed",
 176    "metadata": {},
 177    "outputs": [],
 178    "source": []
 179   },
 180   {
 181    "cell_type": "code",
 182    "execution_count": null,
 183    "id": "c022cce2-8863-43f4-96e8-c604ba2fe8bc",
 184    "metadata": {},
 185    "outputs": [],
 186    "source": []
 187   },
 188   {
 189    "cell_type": "code",
 190    "execution_count": null,
 191    "id": "81037c9e-088f-4dd2-bbfa-5b9b2d044d80",
 192    "metadata": {},
 193    "outputs": [],
 194    "source": []
 195   },
 196   {
 197    "cell_type": "code",
 198    "execution_count": null,
 199    "id": "9aaaa2ff-6757-48a6-b03b-568d2b0d01b0",
 200    "metadata": {},
 201    "outputs": [],
 202    "source": []
 203   },
 204   {
 205    "cell_type": "code",
 206    "execution_count": null,
 207    "id": "ca8637d2-d111-4054-b174-ef913f0d9206",
 208    "metadata": {},
 209    "outputs": [],
 210    "source": []
 211   },
 212   {
 213    "cell_type": "code",
 214    "execution_count": null,
 215    "id": "12217194-a9be-49bc-99ef-6b2a107ab4f3",
 216    "metadata": {},
 217    "outputs": [],
 218    "source": []
 219   },
 220   {
 221    "cell_type": "code",
 222    "execution_count": null,
 223    "id": "7c3c428e-c628-4712-bdc7-15dce26837dd",
 224    "metadata": {},
 225    "outputs": [],
 226    "source": []
 227   },
 228   {
 229    "cell_type": "code",
 230    "execution_count": null,
 231    "id": "84fe9438-2f2e-483c-a5a4-9dd3a61f50aa",
 232    "metadata": {},
 233    "outputs": [],
 234    "source": []
 235   },
 236   {
 237    "cell_type": "code",
 238    "execution_count": null,
 239    "id": "77d90197-2b50-4621-9eee-def323ed836e",
 240    "metadata": {},
 241    "outputs": [],
 242    "source": []
 243   },
 244   {
 245    "cell_type": "code",
 246    "execution_count": null,
 247    "id": "e492ae99-ea1f-4185-9a33-41573263f2f1",
 248    "metadata": {},
 249    "outputs": [],
 250    "source": []
 251   },
 252   {
 253    "cell_type": "code",
 254    "execution_count": null,
 255    "id": "56b18e34-b50b-48a6-947a-5714b65e85cf",
 256    "metadata": {},
 257    "outputs": [],
 258    "source": [
 259     "ep = 15\n",
 260     "bmin = 10\n",
 261     "bmax = 500\n",
 262     "xgrid = np.arange(0, ep)\n",
 263     "plt.plot(xgrid, calc_exp_intervals(bmin, bmax, ep))\n",
 264     "plt.plot(xgrid, calc_log_intervals(bmin, bmax, ep))"
 265    ]
 266   },
 267   {
 268    "cell_type": "code",
 269    "execution_count": null,
 270    "id": "8ae6b9d7-f108-4071-a9fc-1b7a32b26d75",
 271    "metadata": {},
 272    "outputs": [],
 273    "source": []
 274   },
 275   {
 276    "cell_type": "code",
 277    "execution_count": null,
 278    "id": "7be5f53c-6130-4d94-986b-e9b5dce7fdae",
 279    "metadata": {},
 280    "outputs": [],
 281    "source": []
 282   },
 283   {
 284    "cell_type": "code",
 285    "execution_count": null,
 286    "id": "b0b0a959-f07c-4b62-bee2-faa993320dda",
 287    "metadata": {},
 288    "outputs": [],
 289    "source": []
 290   },
 291   {
 292    "cell_type": "code",
 293    "execution_count": null,
 294    "id": "23d94e44-cff1-4a2a-9a0e-039bf401d4e3",
 295    "metadata": {},
 296    "outputs": [],
 297    "source": []
 298   },
 299   {
 300    "cell_type": "code",
 301    "execution_count": null,
 302    "id": "98382367-820a-4aad-97da-3ea2bc895b0f",
 303    "metadata": {},
 304    "outputs": [],
 305    "source": []
 306   },
 307   {
 308    "cell_type": "code",
 309    "execution_count": null,
 310    "id": "185c6f90-fe7f-4b05-b5ef-20635051f18b",
 311    "metadata": {},
 312    "outputs": [],
 313    "source": []
 314   },
 315   {
 316    "cell_type": "code",
 317    "execution_count": null,
 318    "id": "5520cd04-72b3-4550-bc54-ad78cbf77ec0",
 319    "metadata": {},
 320    "outputs": [],
 321    "source": []
 322   },
 323   {
 324    "cell_type": "code",
 325    "execution_count": null,
 326    "id": "fd0a4fa9-603f-4662-ad4e-14df33337441",
 327    "metadata": {},
 328    "outputs": [],
 329    "source": []
 330   },
 331   {
 332    "cell_type": "code",
 333    "execution_count": null,
 334    "id": "253c667a-748d-48cc-8479-50616e043609",
 335    "metadata": {},
 336    "outputs": [],
 337    "source": []
 338   },
 339   {
 340    "cell_type": "code",
 341    "execution_count": null,
 342    "id": "90cafb80-72e9-4610-8413-ca407f03dbd0",
 343    "metadata": {},
 344    "outputs": [],
 345    "source": []
 346   },
 347   {
 348    "cell_type": "code",
 349    "execution_count": null,
 350    "id": "9ebf0ccd-554f-4a0a-87e9-36de0a62a34c",
 351    "metadata": {},
 352    "outputs": [],
 353    "source": []
 354   },
 355   {
 356    "cell_type": "code",
 357    "execution_count": null,
 358    "id": "23d8d51b-6206-471a-a792-a85f4ad89637",
 359    "metadata": {},
 360    "outputs": [],
 361    "source": []
 362   },
 363   {
 364    "cell_type": "code",
 365    "execution_count": null,
 366    "id": "d25faf9f-d00f-44a6-a43f-e4a3277aad78",
 367    "metadata": {},
 368    "outputs": [],
 369    "source": []
 370   },
 371   {
 372    "cell_type": "code",
 373    "execution_count": null,
 374    "id": "e8c47be0-92f6-454f-9e04-385c3cb41831",
 375    "metadata": {},
 376    "outputs": [],
 377    "source": []
 378   },
 379   {
 380    "cell_type": "code",
 381    "execution_count": null,
 382    "id": "c8d197e6-1959-4a6f-8d2d-c67a97a123f9",
 383    "metadata": {},
 384    "outputs": [],
 385    "source": []
 386   },
 387   {
 388    "cell_type": "code",
 389    "execution_count": null,
 390    "id": "3aa5aece-79c5-42b7-98a2-3f8a3cfb8e29",
 391    "metadata": {},
 392    "outputs": [],
 393    "source": []
 394   },
 395   {
 396    "cell_type": "code",
 397    "execution_count": null,
 398    "id": "a9f8a650-330f-493e-a158-a683e2fd872d",
 399    "metadata": {},
 400    "outputs": [],
 401    "source": []
 402   },
 403   {
 404    "cell_type": "markdown",
 405    "id": "b62f4360-e9d1-4510-bb5d-1d79a3a5ac75",
 406    "metadata": {},
 407    "source": [
 408     "## Test Spatial Data"
 409    ]
 410   },
 411   {
 412    "cell_type": "code",
 413    "execution_count": null,
 414    "id": "3a04c2d3-3bf1-451d-88bc-7b1e8701cb52",
 415    "metadata": {},
 416    "outputs": [],
 417    "source": [
 418     "train = read_pkl('train.pkl')"
 419    ]
 420   },
 421   {
 422    "cell_type": "code",
 423    "execution_count": null,
 424    "id": "3d416f92-995a-427f-b76d-a6125061ee98",
 425    "metadata": {},
 426    "outputs": [],
 427    "source": [
 428     "params = read_yml(\"params.yaml\", subkey=\"rnn\")\n",
 429     "params = RNNParams(params)"
 430    ]
 431   },
 432   {
 433    "cell_type": "code",
 434    "execution_count": null,
 435    "id": "1d76cd6e-2e0e-40ae-9a58-3ed62217a33d",
 436    "metadata": {},
 437    "outputs": [],
 438    "source": [
 439     "len(train.keys())"
 440    ]
 441   },
 442   {
 443    "cell_type": "code",
 444    "execution_count": null,
 445    "id": "4735052a-f046-4d52-8666-ce14e4a0e276",
 446    "metadata": {},
 447    "outputs": [],
 448    "source": [
 449     "from itertools import islice\n",
 450     "dat = {k: train[k] for k in islice(train, 100)}"
 451    ]
 452   },
 453   {
 454    "cell_type": "code",
 455    "execution_count": null,
 456    "id": "194f815f-c889-43ed-b0e8-853b1c4a8a81",
 457    "metadata": {},
 458    "outputs": [],
 459    "source": [
 460     "dat.keys()"
 461    ]
 462   },
 463   {
 464    "cell_type": "code",
 465    "execution_count": null,
 466    "id": "99819622-555b-4027-a644-5f75c76f7fbc",
 467    "metadata": {},
 468    "outputs": [],
 469    "source": [
 470     "from data_funcs import combine_nested\n",
 471     "dd = combine_nested(dat)"
 472    ]
 473   },
 474   {
 475    "cell_type": "code",
 476    "execution_count": null,
 477    "id": "4a647e8a-61f3-4e5b-abb3-44d43d7e0844",
 478    "metadata": {},
 479    "outputs": [],
 480    "source": [
 481     "import importlib\n",
 482     "import utils\n",
 483     "importlib.reload(utils)\n",
 484     "from utils import Dict"
 485    ]
 486   },
 487   {
 488    "cell_type": "code",
 489    "execution_count": null,
 490    "id": "6335deef-ea25-40bd-8a68-842af80cebe8",
 491    "metadata": {},
 492    "outputs": [],
 493    "source": [
 494     "dd = Dict(dd)"
 495    ]
 496   },
 497   {
 498    "cell_type": "code",
 499    "execution_count": null,
 500    "id": "e86c9e4d-4ccd-4d9d-92e1-2e4299549fa4",
 501    "metadata": {},
 502    "outputs": [],
 503    "source": [
 504     "import importlib\n",
 505     "import moisture_rnn\n",
 506     "importlib.reload(moisture_rnn)\n",
 507     "from moisture_rnn import RNNData"
 508    ]
 509   },
 510   {
 511    "cell_type": "code",
 512    "execution_count": null,
 513    "id": "966c3559-740d-44d3-b98d-cc2efe63afcd",
 514    "metadata": {},
 515    "outputs": [],
 516    "source": [
 517     "rnn_dat = RNNData(dd, scaler=\"standard\", features_list = ['Ed', 'Ew', 'rain'])\n",
 518     "rnn_dat.train_test_split(   \n",
 519     "    train_frac = .9,\n",
 520     "    val_frac = .05\n",
 521     ")"
 522    ]
 523   },
 524   {
 525    "cell_type": "code",
 526    "execution_count": null,
 527    "id": "72289573-56a1-45ca-8551-b24c4c073bfd",
 528    "metadata": {},
 529    "outputs": [],
 530    "source": [
 531     "rnn_dat.scale_data()"
 532    ]
 533   },
 534   {
 535    "cell_type": "code",
 536    "execution_count": null,
 537    "id": "b35a8e1a-a161-42af-a595-2e1bae0fd0ba",
 538    "metadata": {},
 539    "outputs": [],
 540    "source": [
 541     "rnn_dat.batch_reshape(timesteps = params['timesteps'], batch_size = params['batch_size'])"
 542    ]
 543   },
 544   {
 545    "cell_type": "code",
 546    "execution_count": null,
 547    "id": "c1520e93-0df1-41d1-98b3-f50edbe13b66",
 548    "metadata": {},
 549    "outputs": [],
 550    "source": []
 551   },
 552   {
 553    "cell_type": "code",
 554    "execution_count": null,
 555    "id": "fa14f0ab-07ff-4c67-bdcb-ff225610ffa2",
 556    "metadata": {},
 557    "outputs": [],
 558    "source": [
 559     "import importlib\n",
 560     "import moisture_rnn\n",
 561     "importlib.reload(moisture_rnn)\n",
 562     "from moisture_rnn import RNN"
 563    ]
 564   },
 565   {
 566    "cell_type": "code",
 567    "execution_count": null,
 568    "id": "94f2030f-dbc9-4a6c-8e98-b932fe7691c7",
 569    "metadata": {},
 570    "outputs": [],
 571    "source": [
 572     "from moisture_rnn import ResetStatesCallback, EarlyStoppingCallback\n",
 573     "params.update({'epochs': 20, 'learning_rate': 0.0001, 'verbose_fit': True, 'rnn_layers': 2, 'rnn_units': 20, 'dense_layers': 1, 'dense_units': 10,\n",
 574     "              'activation': ['relu', 'relu'], 'features_list': ['Ed', 'Ew', 'rain']})\n",
 575     "reproducibility.set_seed(123)\n",
 576     "rnn = RNN(params)\n",
 577     "\n",
 578     "history = rnn.model_train.fit(rnn_dat.X_train, rnn_dat.y_train, \n",
 579     "                    batch_size = params['batch_size'], epochs=params['epochs'], \n",
 580     "                    callbacks = [ResetStatesCallback(params),\n",
 581     "                                EarlyStoppingCallback(patience = params['early_stopping_patience'])],\n",
 582     "                   validation_data = (rnn_dat.X_val, rnn_dat.y_val))\n",
 583     "              "
 584    ]
 585   },
 586   {
 587    "cell_type": "code",
 588    "execution_count": null,
 589    "id": "32c39f16-6d80-44ef-b58a-be12869cd638",
 590    "metadata": {},
 591    "outputs": [],
 592    "source": [
 593     "plt.figure()\n",
 594     "plt.semilogy(history.history['loss'], label='Training loss')\n",
 595     "if 'val_loss' in history.history:\n",
 596     "    plt.semilogy(history.history['val_loss'], label='Validation loss')\n",
 597     "plt.ylabel('Loss')\n",
 598     "plt.xlabel('Epoch')\n",
 599     "plt.legend(loc='upper left')\n",
 600     "plt.show()"
 601    ]
 602   },
 603   {
 604    "cell_type": "code",
 605    "execution_count": null,
 606    "id": "b5a88957-c7c7-4036-85bd-94cc4aa5c08c",
 607    "metadata": {},
 608    "outputs": [],
 609    "source": [
 610     "vpreds = rnn.model_train.predict(rnn_dat.X_val)"
 611    ]
 612   },
 613   {
 614    "cell_type": "code",
 615    "execution_count": null,
 616    "id": "f4f1ad13-6d23-4c3a-80f8-32d4cd7a9902",
 617    "metadata": {},
 618    "outputs": [],
 619    "source": [
 620     "vpreds.shape"
 621    ]
 622   },
 623   {
 624    "cell_type": "code",
 625    "execution_count": null,
 626    "id": "4e3e62bd-36f9-4ce5-befd-cecf01f13bd1",
 627    "metadata": {},
 628    "outputs": [],
 629    "source": [
 630     "rnn_dat.y_val.shape"
 631    ]
 632   },
 633   {
 634    "cell_type": "code",
 635    "execution_count": null,
 636    "id": "308ec7c9-a73b-4405-912a-454811a413ac",
 637    "metadata": {},
 638    "outputs": [],
 639    "source": [
 640     "from sklearn.metrics import mean_squared_error"
 641    ]
 642   },
 643   {
 644    "cell_type": "code",
 645    "execution_count": null,
 646    "id": "2d0cd42b-ffbd-413a-a73b-a622865c1b61",
 647    "metadata": {},
 648    "outputs": [],
 649    "source": [
 650     "mean_squared_error(vpreds, rnn_dat.y_val)"
 651    ]
 652   },
 653   {
 654    "cell_type": "code",
 655    "execution_count": null,
 656    "id": "1983a28d-f6b8-4a35-94f0-022c5ef898d2",
 657    "metadata": {},
 658    "outputs": [],
 659    "source": [
 660     "loss = tf.keras.losses.mse(rnn_dat.y_val, vpreds)\n",
 661     "loss = tf.reduce_mean(loss).numpy()\n",
 662     "loss"
 663    ]
 664   },
 665   {
 666    "cell_type": "code",
 667    "execution_count": null,
 668    "id": "28183109-605e-4392-b5ab-df79776f023a",
 669    "metadata": {},
 670    "outputs": [],
 671    "source": [
 672     "plt.scatter(vpreds, rnn_dat.y_val)"
 673    ]
 674   },
 675   {
 676    "cell_type": "code",
 677    "execution_count": null,
 678    "id": "c5335e7b-1d3f-4d76-8452-85b039b386ef",
 679    "metadata": {},
 680    "outputs": [],
 681    "source": [
 682     "hash_weights(rnn.model_train)"
 683    ]
 684   },
 685   {
 686    "cell_type": "code",
 687    "execution_count": null,
 688    "id": "1b4464b2-5ea2-4c1c-b092-9a478d5fffe4",
 689    "metadata": {},
 690    "outputs": [],
 691    "source": [
 692     "rnn.model_predict.set_weights(rnn.model_train.get_weights())"
 693    ]
 694   },
 695   {
 696    "cell_type": "code",
 697    "execution_count": null,
 698    "id": "c2a681d1-3402-4053-aec5-ecc1a94237b8",
 699    "metadata": {},
 700    "outputs": [],
 701    "source": [
 702     "hash_weights(rnn.model_predict)"
 703    ]
 704   },
 705   {
 706    "cell_type": "code",
 707    "execution_count": null,
 708    "id": "e94d82d8-5738-4d66-897c-3ac68036ec95",
 709    "metadata": {},
 710    "outputs": [],
 711    "source": []
 712   },
 713   {
 714    "cell_type": "code",
 715    "execution_count": null,
 716    "id": "cc74db07-84ed-4e33-949c-5e0548e98007",
 717    "metadata": {},
 718    "outputs": [],
 719    "source": []
 720   },
 721   {
 722    "cell_type": "code",
 723    "execution_count": null,
 724    "id": "df1309f1-6eac-4e07-b1bb-3c1a4cc9c5bf",
 725    "metadata": {},
 726    "outputs": [],
 727    "source": []
 728   },
 729   {
 730    "cell_type": "code",
 731    "execution_count": null,
 732    "id": "0166e780-3379-414b-b403-86bca3c36661",
 733    "metadata": {},
 734    "outputs": [],
 735    "source": [
 736     "preds = rnn.predict(rnn_dat.X_test[0])"
 737    ]
 738   },
 739   {
 740    "cell_type": "code",
 741    "execution_count": null,
 742    "id": "f878b950-b750-43db-b5e5-32723f9d0f07",
 743    "metadata": {},
 744    "outputs": [],
 745    "source": [
 746     "plt.plot(rnn_dat.y_test[2])\n",
 747     "plt.plot(preds)"
 748    ]
 749   },
 750   {
 751    "cell_type": "code",
 752    "execution_count": null,
 753    "id": "3aa8dd59-12f0-46ec-b422-dcd23d8076bf",
 754    "metadata": {},
 755    "outputs": [],
 756    "source": []
 757   },
 758   {
 759    "cell_type": "code",
 760    "execution_count": null,
 761    "id": "17e09a7a-19ac-4e82-af54-dcced5791669",
 762    "metadata": {},
 763    "outputs": [],
 764    "source": []
 765   },
 766   {
 767    "cell_type": "code",
 768    "execution_count": null,
 769    "id": "33072593-30a4-49a0-8372-67012e1213eb",
 770    "metadata": {},
 771    "outputs": [],
 772    "source": []
 773   },
 774   {
 775    "cell_type": "code",
 776    "execution_count": null,
 777    "id": "090b36f5-fd34-4cc7-a84d-f8dd0d582000",
 778    "metadata": {},
 779    "outputs": [],
 780    "source": []
 781   },
 782   {
 783    "cell_type": "code",
 784    "execution_count": null,
 785    "id": "7deda359-1e7f-447a-97b7-576b98712a74",
 786    "metadata": {},
 787    "outputs": [],
 788    "source": [
 789     "from moisture_rnn import ResetStatesCallback, EarlyStoppingCallback\n",
 790     "params.update({'epochs': 20, 'learning_rate': 0.0001, 'verbose_fit': True, 'rnn_layers': 2, 'rnn_units': 20, 'dense_layers': 1, 'dense_units': 10,\n",
 791     "              'activation': ['relu', 'relu'], 'features_list': ['Ed', 'Ew', 'rain']})\n",
 792     "reproducibility.set_seed(123)\n",
 793     "rnn = RNN(params)"
 794    ]
 795   },
 796   {
 797    "cell_type": "code",
 798    "execution_count": null,
 799    "id": "37d7f239-4d47-46d0-b891-b2a8d9da8c4e",
 800    "metadata": {},
 801    "outputs": [],
 802    "source": [
 803     "m, errs = rnn.run_model(rnn_dat, plot_period=\"predict\")"
 804    ]
 805   },
 806   {
 807    "cell_type": "code",
 808    "execution_count": null,
 809    "id": "150754f6-9927-4188-969a-d253bb0a5b22",
 810    "metadata": {},
 811    "outputs": [],
 812    "source": [
 813     "len(rnn_dat.X)"
 814    ]
 815   },
 816   {
 817    "cell_type": "code",
 818    "execution_count": null,
 819    "id": "8592cce5-77fe-4804-8df2-de92f058d11f",
 820    "metadata": {},
 821    "outputs": [],
 822    "source": [
 823     "len(rnn_dat.X_test)"
 824    ]
 825   },
 826   {
 827    "cell_type": "code",
 828    "execution_count": null,
 829    "id": "3047a7a3-32c2-4af0-aff9-bebdb1a877c1",
 830    "metadata": {},
 831    "outputs": [],
 832    "source": [
 833     "preds0 = rnn.predict(rnn_dat.X_test[0])"
 834    ]
 835   },
 836   {
 837    "cell_type": "code",
 838    "execution_count": null,
 839    "id": "2880b410-35a2-4d6c-ac28-2e2f366ec3a2",
 840    "metadata": {},
 841    "outputs": [],
 842    "source": [
 843     "rmse(preds0, rnn_dat.y_test[0])"
 844    ]
 845   },
 846   {
 847    "cell_type": "code",
 848    "execution_count": null,
 849    "id": "87623222-5fba-4833-8873-01933e9aba88",
 850    "metadata": {},
 851    "outputs": [],
 852    "source": [
 853     "plt.plot(rnn_dat.y_test[0])\n",
 854     "plt.plot(preds0)"
 855    ]
 856   },
 857   {
 858    "cell_type": "code",
 859    "execution_count": null,
 860    "id": "7f922046-e74f-424e-aa1c-d6d4b2eb3a46",
 861    "metadata": {},
 862    "outputs": [],
 863    "source": []
 864   },
 865   {
 866    "cell_type": "code",
 867    "execution_count": null,
 868    "id": "47a098c2-28c3-483d-b062-da1d534f7766",
 869    "metadata": {},
 870    "outputs": [],
 871    "source": []
 872   },
 873   {
 874    "cell_type": "code",
 875    "execution_count": null,
 876    "id": "4a581630-2dc0-4cdb-8647-c81d41e149bc",
 877    "metadata": {},
 878    "outputs": [],
 879    "source": []
 880   },
 881   {
 882    "cell_type": "code",
 883    "execution_count": null,
 884    "id": "36b931d4-15dc-41a8-8748-610a2406ccad",
 885    "metadata": {},
 886    "outputs": [],
 887    "source": []
 888   },
 889   {
 890    "cell_type": "code",
 891    "execution_count": null,
 892    "id": "055d98f5-4028-4822-b409-b03d437490da",
 893    "metadata": {},
 894    "outputs": [],
 895    "source": []
 896   },
 897   {
 898    "cell_type": "code",
 899    "execution_count": null,
 900    "id": "beb357ab-16dc-4c91-a121-6dfc509f4ff6",
 901    "metadata": {},
 902    "outputs": [],
 903    "source": []
 904   },
 905   {
 906    "cell_type": "code",
 907    "execution_count": null,
 908    "id": "a319b314-b156-47af-8541-f97145352e5c",
 909    "metadata": {},
 910    "outputs": [],
 911    "source": []
 912   },
 913   {
 914    "cell_type": "code",
 915    "execution_count": null,
 916    "id": "b6922358-b824-4c77-abe4-c9b605a78738",
 917    "metadata": {},
 918    "outputs": [],
 919    "source": []
 920   },
 921   {
 922    "cell_type": "markdown",
 923    "id": "d2360aef-e9c4-4a71-922d-336e53b82537",
 924    "metadata": {},
 925    "source": [
 926     "## LSTM\n",
 927     "\n",
 928     "TODO: FIX BELOW"
 929    ]
 930   },
 931   {
 932    "cell_type": "code",
 933    "execution_count": null,
 934    "id": "71d4e441-9bf1-4d57-bb37-091553e23212",
 935    "metadata": {},
 936    "outputs": [],
 937    "source": [
 938     "import importlib \n",
 939     "import moisture_rnn\n",
 940     "importlib.reload(moisture_rnn)\n",
 941     "from moisture_rnn import RNN_LSTM"
 942    ]
 943   },
 944   {
 945    "cell_type": "code",
 946    "execution_count": null,
 947    "id": "0f6ba896-e3be-4a9f-8a42-3df64aff7d63",
 948    "metadata": {},
 949    "outputs": [],
 950    "source": [
 951     "params = read_yml(\"params.yaml\", subkey=\"lstm\")\n",
 952     "params = RNNParams(params)"
 953    ]
 954   },
 955   {
 956    "cell_type": "code",
 957    "execution_count": null,
 958    "id": "0157a6bc-3a99-4b87-a42c-ab770d19ae37",
 959    "metadata": {},
 960    "outputs": [],
 961    "source": [
 962     "from moisture_rnn import ResetStatesCallback, EarlyStoppingCallback\n",
 963     "params.update({'epochs': 20, 'learning_rate': 0.0001, 'verbose_fit': True, 'rnn_layers': 2, 'rnn_units': 20, 'dense_layers': 1, 'dense_units': 10,\n",
 964     "              'activation': ['relu', 'relu'], 'features_list': ['Ed', 'Ew', 'rain']})\n",
 965     "reproducibility.set_seed(123)\n",
 966     "lstm = RNN_LSTM(params)\n",
 967     "\n",
 968     "history = lstm.model_train.fit(rnn_dat.X_train, rnn_dat.y_train, \n",
 969     "                    batch_size = params['batch_size'], epochs=params['epochs'], \n",
 970     "                    callbacks = [ResetStatesCallback(params),\n",
 971     "                                EarlyStoppingCallback(patience = params['early_stopping_patience'])],\n",
 972     "                   validation_data = (rnn_dat.X_val, rnn_dat.y_val))\n",
 973     "              "
 974    ]
 975   },
 976   {
 977    "cell_type": "code",
 978    "execution_count": null,
 979    "id": "de0c00e7-838f-41b6-9cc5-70594656d155",
 980    "metadata": {},
 981    "outputs": [],
 982    "source": []
 983   },
 984   {
 985    "cell_type": "code",
 986    "execution_count": null,
 987    "id": "430a2224-6798-48fa-b198-a32800f88f66",
 988    "metadata": {},
 989    "outputs": [],
 990    "source": []
 991   },
 992   {
 993    "cell_type": "code",
 994    "execution_count": null,
 995    "id": "ec95e7d4-6d57-441b-b673-f10625ee5dec",
 996    "metadata": {},
 997    "outputs": [],
 998    "source": []
 999   },
1000   {
1001    "cell_type": "code",
1002    "execution_count": null,
1003    "id": "9b3c8d8d-ea50-44ea-8c0c-414e07cd01ac",
1004    "metadata": {},
1005    "outputs": [],
1006    "source": []
1007   },
1008   {
1009    "cell_type": "code",
1010    "execution_count": null,
1011    "id": "03063e3c-e8f4-451d-b0cf-25bd965cd9d6",
1012    "metadata": {},
1013    "outputs": [],
1014    "source": []
1015   },
1016   {
1017    "cell_type": "code",
1018    "execution_count": null,
1019    "id": "f60a24c6-9a67-45aa-bc5c-8818aa0ca049",
1020    "metadata": {},
1021    "outputs": [],
1022    "source": []
1023   }
1024  ],
1025  "metadata": {
1026   "kernelspec": {
1027    "display_name": "Python 3 (ipykernel)",
1028    "language": "python",
1029    "name": "python3"
1030   },
1031   "language_info": {
1032    "codemirror_mode": {
1033     "name": "ipython",
1034     "version": 3
1035    },
1036    "file_extension": ".py",
1037    "mimetype": "text/x-python",
1038    "name": "python",
1039    "nbconvert_exporter": "python",
1040    "pygments_lexer": "ipython3",
1041    "version": "3.12.5"
1042   }
1043  },
1044  "nbformat": 4,
1045  "nbformat_minor": 5
1046 }