examples/enkf_jallon.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import plotly.io as pio\n",
    "\n",
    "from time_series_prediction import settings, utils\n",
    "from biophysical_models import models\n",
    "\n",
    "pio.templates.default = 'plotly_white'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# settings.switch_device('cuda')\n",
    "settings.device == torch.device('cpu')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hidden_layers = [6, 10, 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvs = utils.SweepEnKF(\n",
    "    'jallon', \n",
    "    'activation_function', \n",
    "    ['ELU', 'ELU', 'ELU', 'ELU'], \n",
    "    train_sweep=False,\n",
    "    noise=5e-2,\n",
    "    hidden_layers=hidden_layers,\n",
    "    train_kwargs={'lr_hold': 10, 'subseq_len': 50},\n",
    "    n_train=4000,\n",
    "    n_test=4000,\n",
    "    n_warmup=1000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvs.train(200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = cvs.plot_test(3).update_layout(\n",
    "    height=1000\n",
    ")\n",
    "for i, name in enumerate(models.JallonHeartLungs().state_names):\n",
    "    fig.update_yaxes(title_text=name, row=i+1, col=1)\n",
    "fig.update_traces(showlegend=False).update_layout(height=1200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hidden_layers = [20, 30, 20]\n",
    "cvs2 = utils.SweepEnKF(\n",
    "    'jallon', \n",
    "    'activation_function', \n",
    "    ['ELU', 'ELU', 'ELU', 'ELU'], \n",
    "    train_sweep=False,\n",
    "    noise=5e-2,\n",
    "    hidden_layers=hidden_layers,\n",
    "    train_kwargs={'lr_hold': 10, 'subseq_len': 50},\n",
    "    n_train=4000,\n",
    "    n_test=4000,\n",
    "    n_warmup=1000,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvs2.train(200, [0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = cvs2.plot_test(0).update_layout(\n",
    "    height=1200\n",
    ")\n",
    "for i, name in enumerate(models.JallonHeartLungs().state_names):\n",
    "    fig.update_yaxes(title_text=name, row=i+1, col=1)\n",
    "fig.update_traces(showlegend=False)"
   ]
  }
 ],
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