01_DeepVIV_sec21.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/helonayala/pinn/blob/main/01_DeepVIV_sec21.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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      "cell_type": "markdown",
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      "source": [
        "Physics-informed Artificial Neural Network\n",
        "\n",
        "Author: Helon Ayala, October 2020\n",
        "\n",
        "Based on: https://github.com/maziarraissi/DeepVIV\n",
        "\n",
        "(translated to Keras layer subclassing and tf 2.0)\n",
        "\n",
        "# Quick description\n",
        "\n",
        "In this notebook we reproduce the results of the paper \n",
        "\n",
        "* Raissi, Maziar, Zhicheng Wang, Michael S. Triantafyllou, and George Em Karniadakis.\"Deep learning of vortex-induced vibrations.\" Journal of Fluid Mechanics 861 (2019): 119-137.\n",
        "\n",
        "in particular Section 2.1. Please refer to the paper for a detailed description of the method and case study. In the following we restrict to the information needed for the notebook to be self-contained.\n",
        "\n",
        "# Problem definition\n",
        "\n",
        "In summary, we will use the Physics-informed artificial neural networks (PINNs) for solving the forward and inverse problems related to the dynamics of a mass-spring-damper of the form\n",
        "\n",
        "$$\n",
        "\\rho \\ddot x (t) + b \\dot x (t) + k x (t) = f (t)\n",
        "$$\n",
        "\n",
        "where the terms are described as follows\n",
        "* $\\rho, b, k$: inertia, viscous friction, and rigidity, respectively;\n",
        "* $x(t)$: displacement;\n",
        "* $f(t)$: sum of external forces\n",
        "\n",
        "(please note I exchanged $\\eta$ to $x$ if you compare to the notation used in the original paper)\n",
        "\n",
        "On one hand, the forward problem relates to solving numerically the 2nd order ODE described in the EOM given. On the other hand, the inverse problem is related to inferring the parameters of the system: $\\rho, b,k$\n",
        "\n",
        "# Assumptions\n",
        "\n",
        "We work under the assumptions that\n",
        "* we know the time series $[x(t),f(t)]$, and\n",
        "* we know the constitutive model of the system under study (thus, PINN).\n",
        "\n",
        "# Imports and definitions \n"
      ]
    },
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      "metadata": {
        "id": "mw8KsF78Wz6E",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "tags": []
      },
      "source": [
        "#@title\n",
        "!pip install -U tensorflow-addons\n",
        "!pip install -q \"tqdm>=4.36.1\"\n",
        "\n",
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from scipy.io import loadmat\n",
        "\n",
        "# progress bar for model.fit function\n",
        "import tensorflow_addons as tfa\n",
        "import tqdm\n",
        "\n",
        "from IPython.display import clear_output\n",
        "\n",
        "# set random seed for reproduction\n",
        "tf.random.set_seed(42)\n",
        "\n",
        "# initialize tqdm callback\n",
        "tqdm_callback = tfa.callbacks.TQDMProgressBar(\n",
        "  leave_epoch_progress = True,\n",
        "  leave_overall_progress = True,\n",
        "  show_epoch_progress = False,\n",
        "  show_overall_progress = True,\n",
        "  )\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Defaulting to user installation because normal site-packages is not writeable\n",
            "Requirement already up-to-date: tensorflow-addons in /home/helon/.local/lib/python3.8/site-packages (0.11.2)\n",
            "Requirement already satisfied, skipping upgrade: typeguard>=2.7 in /home/helon/.local/lib/python3.8/site-packages (from tensorflow-addons) (2.10.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "75cBAbWtPgSS"
      },
      "source": [
        "# Load data and plot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GbOcBr1xPYah",
        "outputId": "55921f50-e666-45eb-9a54-7f06afc8df5e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        }
      },
      "source": [
        "VIVdata = loadmat('data/VIV_displacement_lift_drag.mat')\n",
        "# data from https://www.dropbox.com/s/gxeyasawxlj7nyu/Data.tar.gz?dl=0\n",
        "\n",
        "x,f,t = VIVdata['eta_structure'], VIVdata['lift_structure'], VIVdata['t_structure']\n",
        "\n",
        "N_train = t.shape[0] # how much data ?\n",
        "\n",
        "# time series plots \n",
        "plt.figure(figsize=[14,5])\n",
        "plt.subplot(121)\n",
        "plt.plot(t,x,'k')\n",
        "plt.legend('x'), plt.xlabel('t'), plt.grid()\n",
        "\n",
        "plt.subplot(122)\n",
        "plt.plot(t,f,'k')\n",
        "plt.legend('f'), plt.xlabel('t'), plt.grid()\n",
        "plt.show()"
      ],
      "execution_count": 2,
      "outputs": [
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vGZg2iUxR2Da"
      },
      "source": [
        "# Definition of the custom classes from tf.keras\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "# layer class\n",
        "class tToXandF(tf.keras.layers.Layer):\n",
        "    \"\"\"\n",
        "    Here we define the layers for the PINNs usign tf.keras and subclassing.\n",
        "\n",
        "    Although semantically I think it would be clearer to use 2 layers objects (1 for the $\\hat x = f(t) $ and 1 for the ODE/inverse problem), I had to use one layer for both PINN blocks. \n",
        "\n",
        "    I could not make it work with 2 different layers, probably because of the inner functioning of the tf.GradientTape function (to be investigated ...).\n",
        "    \"\"\"\n",
        "    def __init__(self, layerWidth, actFcn, timevec, name=\"tToX\", **kwargs):\n",
        "        super(tToXandF, self).__init__(name=name, **kwargs)\n",
        "\n",
        "        # rescale data\n",
        "        self.minX = np.min(timevec)\n",
        "        self.maxX = np.max(timevec)\n",
        "\n",
        "        # instantiates hidden layers recursively\n",
        "        self.denseList = []\n",
        "        for nNeurons in layerWidth:\n",
        "            self.denseList.append(\n",
        "                tf.keras.layers.Dense(nNeurons, activation=actFcn)\n",
        "            )  # hidden layers\n",
        "\n",
        "        self.denseList.append(tf.keras.layers.Dense(1))  # output layer\n",
        "\n",
        "        self.b = tf.Variable(0.05, name=\"b\", trainable=True, dtype=tf.float32)\n",
        "        self.k = tf.Variable(2.0, name=\"k\", trainable=True, dtype=tf.float32)\n",
        "\n",
        "    def call(self, t):\n",
        "\n",
        "        with tf.GradientTape(\n",
        "            persistent=True  # persistent for 2nd order derivative\n",
        "        ) as tape:\n",
        "\n",
        "            tape.watch(t)\n",
        "            # part 1: calculate  t->x\n",
        "            x = 1-2*(self.maxX - t) / (self.maxX - self.minX) # rescale [-1,1]\n",
        "            for nLayers in range(self.denseList.__len__()):\n",
        "                x = self.denseList[nLayers](x)\n",
        "\n",
        "            # part 2a: calculate the gradients of x wrt t\n",
        "            xp = tape.gradient(x, t)\n",
        "            xpp = tape.gradient(xp, t)\n",
        "\n",
        "            # part 2b: calculate the EOM\n",
        "            f = 2.0 * xpp + self.b * xp + self.k * x\n",
        "\n",
        "        return x, f\n",
        "\n",
        "# model class\n",
        "class PINN(tf.keras.Model):\n",
        "    def __init__(self,timevec, layerWidth=10 * [32], actFcn=tf.sin, name=\"PINN\", **kwargs):\n",
        "        super(PINN, self).__init__(name=name, **kwargs)\n",
        "\n",
        "        self.tToXandF = tToXandF(layerWidth=layerWidth, actFcn=actFcn, timevec= timevec)\n",
        "\n",
        "    def call(self, t):\n",
        "        return self.tToXandF(t)\n",
        "\n",
        "# Callbacks for watching variables\n",
        "class VariableValue(tf.keras.callbacks.Callback):\n",
        "    def __init__(self, vars_to_track):\n",
        "        super(VariableValue, self).__init__()\n",
        "        self.vars_to_track = vars_to_track\n",
        "        self.valueList = [] # list with all variables tracked (each epoch is an element)\n",
        "\n",
        "    def on_epoch_begin(self, epoch, logs):\n",
        "        tftensor2np = [x.numpy() for x in self.vars_to_track] # convert tf.tensor to list of numpy\n",
        "        self.valueList.append(tftensor2np) # append for tracking\n",
        "\n",
        "# Callbacks for watching variables\n",
        "class PlotOutput(tf.keras.callbacks.Callback):\n",
        "    def __init__(self,x,y,atEveryEpoch = 10):\n",
        "        super(PlotOutput, self).__init__()\n",
        "        self.x = x\n",
        "        self.y = y\n",
        "        self.atEveryEpoch = atEveryEpoch\n",
        "    def on_epoch_begin(self, epoch, logs):\n",
        "        # plot measured vs. predicted outputs\n",
        "\n",
        "        if not (epoch % self.atEveryEpoch):\n",
        "            yh1, yh2 = self.model.predict(self.x)\n",
        "\n",
        "            clear_output(wait=True)\n",
        "\n",
        "            plt.figure(figsize=[14,5])\n",
        "            plt.subplot(121)\n",
        "            plt.plot(self.x, self.y[0], 'k-',linewidth = 3, label=\"true\")\n",
        "            plt.plot(self.x, yh1,'ro', label=\"predicted\")   \n",
        "            plt.legend(), plt.title(epoch)\n",
        "            \n",
        "            plt.subplot(122)\n",
        "            plt.plot(self.x, self.y[1], 'k-',linewidth = 3, label=\"true\")\n",
        "            plt.plot(self.x, yh2,'ro', label=\"predicted\")\n",
        "            plt.legend(), plt.title(epoch)\n",
        "            plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HxQAewRtTVmO"
      },
      "source": [
        "# Instantiate PINN model and define hyperparameters"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "# default parameters are the same as DeepVIV paper\n",
        "mdl = PINN(timevec = t)  \n",
        "\n",
        "# learning rate and number of epochs\n",
        "lrvec = np.array([1e-3, 1e-4, 1e-5, 1e-6])\n",
        "epvec = np.array([2e3, 3e3, 3e3, 2e3], dtype=\"int32\")\n",
        "\n",
        "# callback - variables to watch\n",
        "varList = [mdl.tToXandF.b, mdl.tToXandF.k]\n"
      ]
    },
    {
      "source": [
        "# Train model"
      ],
      "cell_type": "markdown",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mO8G5W0DSrbb",
        "outputId": "8901ebe8-b544-4305-b56e-f34a6cb95ad2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 318,
          "referenced_widgets": [
            "3921934ad1ad476fbc3bafe5b4f780b6",
            "169da55f4fd7479395e480706fea1dba",
            "6e5161332976477084b5ea1e217550f9",
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            "b9e020a6970046c8bdedd3dcb90454c4",
            "26de2b22f208492aadebe27546060cd6",
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            "ddbf5df9774b49688438dd0122fc5bd8",
            "83fd393928394c6ebd23f997f84afacf",
            "902850135ba9427395a99b98f3a78124",
            "b9dffa975309451abbe6100bc87be583",
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            "56176577e185456eb1c7ca61b5e7950c",
            "f44e15e0c8e44d4492d68cf5ffd5d423"
          ]
        },
        "tags": []
      },
      "source": [
        "nTrain = lrvec.shape[0]\n",
        "history = []\n",
        "clbkVarValue = []\n",
        "pltCalback = PlotOutput(x=t, y=[x,f],atEveryEpoch = 50)\n",
        "for i in range(nTrain):\n",
        "    print(\"Learning rate:\", lrvec[i])\n",
        "\n",
        "    clbkVarValue.append(VariableValue(varList)) # instantiate callback (for saving identified values)\n",
        "\n",
        "    mdl.compile(\n",
        "        tf.keras.optimizers.Adam(learning_rate=lrvec[i]), loss=\"mse\", metrics=\"mse\"\n",
        "    )\n",
        "    history.append(\n",
        "        mdl.fit(\n",
        "            x=t,\n",
        "            y=[x, f],\n",
        "            epochs=epvec[i],\n",
        "            batch_size=N_train,\n",
        "            # verbose=0,\n",
        "            # callbacks=[tqdm_callback, clbkVarValue[i]],\n",
        "            verbose=0,\n",
        "            callbacks=[pltCalback,clbkVarValue[i]],\n",
        "            )\n",
        "        )\n",
        "\n",
        "mdl.summary()\n"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"PINN\"\n_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\ntToX (tToXandF)              multiple                  9603      \n=================================================================\nTotal params: 9,603\nTrainable params: 9,603\nNon-trainable params: 0\n_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "source": [
        "# Plot training convergence"
      ],
      "cell_type": "markdown",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1008x360 with 1 Axes>",
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422.915225 244.004799 \nL 423.152031 244.024889 \nL 424.099256 243.691967 \nL 424.809675 244.070846 \nL 425.283287 244.254579 \nL 425.993706 244.212119 \nL 426.704125 244.23069 \nL 428.361768 244.54709 \nL 430.256218 244.70144 \nL 432.861086 244.947148 \nL 433.808311 244.91074 \nL 434.281923 244.745875 \nL 434.755536 244.282624 \nL 434.992342 243.812714 \nL 435.229148 243.076792 \nL 435.465954 241.92277 \nL 435.939567 237.664009 \nL 436.413179 229.867483 \nL 437.360404 211.420574 \nL 437.59721 210.737247 \nL 437.834016 213.444269 \nL 438.070823 221.116136 \nL 438.307629 232.6408 \nL 438.544435 238.680034 \nL 439.254854 218.96354 \nL 439.49166 219.954818 \nL 439.965272 226.886805 \nL 440.202078 224.178114 \nL 440.675691 215.008178 \nL 440.912497 213.738624 \nL 441.149303 214.014853 \nL 441.386109 214.083117 \nL 441.859722 211.569813 \nL 442.096528 211.531126 \nL 442.333334 213.814895 \nL 443.990978 243.64146 \nL 444.227784 240.6933 \nL 444.701396 231.693025 \nL 444.938203 230.175761 \nL 445.175009 230.510784 \nL 445.885427 234.248783 \nL 446.122234 236.282159 \nL 446.832652 245.414857 \nL 447.069458 245.882026 \nL 447.779877 243.338006 \nL 448.25349 242.099061 \nL 448.727102 240.480322 \nL 448.963908 240.321238 \nL 449.200714 240.70498 \nL 449.911133 242.427948 \nL 450.384745 243.48476 \nL 451.095164 245.511452 \nL 451.568776 245.990463 \nL 452.752807 246.832017 \nL 453.463226 246.798962 \nL 454.173645 246.871089 \nL 455.357676 246.526363 \nL 455.831288 246.155383 \nL 456.304901 245.384497 \nL 456.778513 243.96636 \nL 457.252125 241.291592 \nL 457.725738 236.545846 \nL 458.19935 229.103593 \nL 458.909769 213.542664 \nL 459.620188 197.726335 \nL 459.856994 194.175605 \nL 460.0938 192.381097 \nL 460.330606 193.208599 \nL 460.567412 197.566208 \nL 460.804219 206.970048 \nL 461.277831 245.717455 \nL 461.514637 237.099907 \nL 461.751443 220.108928 \nL 461.98825 211.461064 \nL 462.225056 209.265072 \nL 462.461862 212.755527 \nL 462.698668 222.209531 \nL 463.172281 247.687545 \nL 463.645893 226.095256 \nL 463.882699 221.512619 \nL 464.119505 222.499771 \nL 464.356312 228.586828 \nL 464.829924 247.54802 \nL 465.06673 244.445782 \nL 465.540343 231.666945 \nL 465.777149 231.121754 \nL 466.013955 234.519409 \nL 466.487568 246.847302 \nL 466.724374 247.61209 \nL 467.197986 239.61759 \nL 467.434792 238.013773 \nL 467.671599 239.102715 \nL 468.382017 248.194953 \nL 468.618823 247.46768 \nL 469.092436 243.3767 \nL 469.329242 242.884534 \nL 469.566048 243.819562 \nL 470.039661 247.50498 \nL 470.276467 248.407548 \nL 470.513273 248.093401 \nL 470.986885 246.179201 \nL 471.223692 245.84004 \nL 471.460498 246.180242 \nL 472.170917 248.481139 \nL 472.407723 248.588344 \nL 473.354948 247.480969 \nL 473.591754 247.6826 \nL 474.302172 248.706594 \nL 474.538979 248.798132 \nL 475.012591 248.585357 \nL 475.486203 248.381086 \nL 475.959816 248.51705 \nL 476.907041 248.998619 \nL 477.854266 248.922131 \nL 478.564684 248.983063 \nL 479.985521 249.263631 \nL 482.827196 249.476187 \nL 486.852901 249.828724 \nL 488.984157 249.898399 \nL 489.694576 249.767472 \nL 490.168188 249.506251 \nL 490.641801 248.918068 \nL 491.115413 247.633803 \nL 491.589026 244.946143 \nL 492.062638 239.789142 \nL 492.53625 231.218422 \nL 493.246669 212.685492 \nL 493.957088 193.317449 \nL 494.4307 186.085997 \nL 494.667506 186.565762 \nL 494.904313 191.387888 \nL 495.141119 202.813352 \nL 495.614731 249.818739 \nL 496.088344 207.623686 \nL 496.32515 202.302788 \nL 496.561956 204.619575 \nL 496.798762 215.075628 \nL 497.272375 248.829494 \nL 497.745987 216.728248 \nL 497.982793 214.295746 \nL 498.219599 219.651898 \nL 498.693212 249.842218 \nL 498.930018 242.738638 \nL 499.166824 229.744839 \nL 499.40363 224.493214 \nL 499.640437 226.466035 \nL 500.350855 249.610828 \nL 500.824468 233.985818 \nL 501.061274 233.275327 \nL 501.29808 237.844113 \nL 501.771693 251.013559 \nL 502.008499 247.725481 \nL 502.245305 242.174629 \nL 502.482111 239.660929 \nL 502.718917 241.040664 \nL 503.19253 250.0113 \nL 503.429336 250.910192 \nL 503.902948 245.244537 \nL 504.139755 244.47297 \nL 504.376561 246.001724 \nL 504.850173 250.93092 \nL 505.086979 250.894986 \nL 505.560592 247.824281 \nL 505.797398 247.494521 \nL 506.034204 248.353844 \nL 506.507817 250.626105 \nL 506.744623 250.432302 \nL 507.455042 247.447125 \nL 507.928654 246.408818 \nL 508.16546 245.254242 \nL 508.639073 240.292227 \nL 510.296716 217.019383 \nL 510.533522 217.543135 \nL 510.770328 220.915591 \nL 511.007135 227.470913 \nL 511.480747 248.642264 \nL 511.717553 250.834356 \nL 512.191166 235.953259 \nL 512.427972 232.126767 \nL 512.664778 231.856195 \nL 512.901584 235.059827 \nL 513.612003 251.917657 \nL 513.848809 249.386906 \nL 514.322422 241.35916 \nL 514.559228 240.588581 \nL 514.796034 242.245958 \nL 515.506453 251.982977 \nL 515.743259 251.39379 \nL 516.216871 247.104772 \nL 516.453677 246.249532 \nL 516.690484 246.802055 \nL 517.400902 251.897041 \nL 517.637708 252.223141 \nL 517.874515 251.54206 \nL 518.348127 249.757345 \nL 518.584933 249.593378 \nL 518.82174 250.036351 \nL 519.532158 252.28738 \nL 519.768964 252.410344 \nL 520.242577 251.764237 \nL 520.479383 251.435004 \nL 520.716189 251.313034 \nL 520.952995 251.43877 \nL 521.90022 252.579986 \nL 522.373833 252.511433 \nL 523.084251 252.218905 \nL 523.557864 252.348024 \nL 524.505089 252.795614 \nL 525.215507 252.781689 \nL 526.162732 252.758812 \nL 528.7676 253.091418 \nL 531.372469 253.26825 \nL 533.977337 253.418898 \nL 534.924562 253.281804 \nL 535.398174 253.004868 \nL 535.871787 252.325022 \nL 536.108593 251.695104 \nL 536.345399 250.737976 \nL 536.819011 247.224315 \nL 537.292624 240.356247 \nL 537.766236 229.263006 \nL 539.42388 181.549279 \nL 539.660686 180.242041 \nL 539.897492 183.413622 \nL 540.134298 193.204562 \nL 540.371104 214.505692 \nL 540.607911 246.569154 \nL 541.081523 200.65976 \nL 541.318329 195.632082 \nL 541.555136 199.808241 \nL 541.791942 214.780629 \nL 542.028748 245.745834 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254.137315 \nL 555.053089 253.930228 \nL 556.23712 250.850556 \nL 556.473927 249.604725 \nL 556.947539 245.209862 \nL 557.421151 238.559443 \nL 558.368376 220.121296 \nL 558.841989 211.954664 \nL 559.078795 209.424429 \nL 559.315601 208.689568 \nL 559.552407 210.002167 \nL 559.789214 214.020579 \nL 560.02602 221.218271 \nL 560.736438 253.255417 \nL 561.446857 229.149888 \nL 561.683663 226.708699 \nL 561.920469 227.417844 \nL 562.157276 231.078415 \nL 562.867694 253.416812 \nL 563.1045 253.73037 \nL 563.814919 239.81728 \nL 564.051725 238.846005 \nL 564.288531 240.146673 \nL 564.762144 248.131951 \nL 565.235756 255.346205 \nL 565.472563 254.787988 \nL 566.182981 247.869281 \nL 566.419787 247.309075 \nL 566.656594 247.960966 \nL 567.130206 251.697898 \nL 567.603818 255.153699 \nL 567.840625 255.630323 \nL 568.077431 255.240618 \nL 568.787849 252.730695 \nL 569.024656 252.442958 \nL 569.261462 252.561579 \nL 569.735074 253.649001 \nL 570.445493 255.557104 \nL 570.682299 255.820472 \nL 570.919105 255.855201 \nL 571.392718 255.501935 \nL 572.103136 254.903602 \nL 572.576749 254.887336 \nL 573.287167 255.311664 \nL 574.234392 255.918481 \nL 574.944811 256.113357 \nL 576.128842 256.10915 \nL 578.260098 255.854087 \nL 578.970516 255.578727 \nL 579.444129 255.216395 \nL 579.917741 254.577144 \nL 580.391354 253.44094 \nL 580.864966 251.466585 \nL 581.338578 248.133118 \nL 581.812191 242.874012 \nL 582.285803 235.346623 \nL 583.233028 215.119743 \nL 583.943447 200.504032 \nL 584.417059 195.117742 \nL 584.653865 194.962367 \nL 584.890672 197.069644 \nL 585.127478 202.204822 \nL 585.60109 223.690302 \nL 585.837896 236.28772 \nL 586.074703 235.032162 \nL 586.548315 217.958798 \nL 586.785121 215.00591 \nL 587.021927 216.1245 \nL 587.258734 221.305831 \nL 587.969152 248.007885 \nL 588.679571 227.648215 \nL 588.916377 226.73043 \nL 589.153183 229.531796 \nL 589.38999 235.919996 \nL 589.863602 254.630078 \nL 590.100408 255.60205 \nL 590.574021 243.054901 \nL 590.810827 239.804693 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186.090882 \nL 609.518517 242.34004 \nL 609.755323 201.975995 \nL 609.99213 188.890329 \nL 610.228936 189.211891 \nL 610.465742 202.653231 \nL 610.702548 240.679184 \nL 610.939355 227.274157 \nL 611.176161 203.114784 \nL 611.412967 198.567681 \nL 611.649773 208.077949 \nL 611.886579 238.148991 \nL 612.123386 241.06629 \nL 612.360192 214.183159 \nL 612.596998 208.211461 \nL 612.833804 216.72279 \nL 613.07061 243.430091 \nL 613.307417 246.102931 \nL 613.544223 222.549881 \nL 613.781029 217.161547 \nL 614.017835 225.753193 \nL 614.254641 249.59872 \nL 614.491448 249.187345 \nL 614.728254 229.916604 \nL 614.96506 225.640926 \nL 615.201866 234.172187 \nL 615.438672 253.623784 \nL 615.675479 251.205779 \nL 615.912285 236.404911 \nL 616.149091 233.254908 \nL 616.385897 241.149203 \nL 616.622703 255.879476 \nL 616.85951 253.535777 \nL 617.096316 242.430469 \nL 617.333122 239.958862 \nL 617.569928 246.421193 \nL 617.806735 256.771946 \nL 618.043541 255.381225 \nL 618.280347 247.460589 \nL 618.517153 245.345711 \nL 618.753959 250.034236 \nL 618.990766 257.141944 \nL 619.227572 256.932069 \nL 619.464378 251.600016 \nL 619.701184 249.6203 \nL 619.93799 252.54561 \nL 620.174797 257.296085 \nL 620.411603 257.912236 \nL 620.885215 252.751854 \nL 621.122021 254.229931 \nL 621.358828 257.317065 \nL 621.595634 258.373318 \nL 622.069246 255.033556 \nL 622.306052 255.514419 \nL 622.779665 258.527813 \nL 623.016471 257.832465 \nL 623.253277 256.658834 \nL 623.490084 256.530732 \nL 623.963696 258.472604 \nL 624.200502 258.431567 \nL 624.674115 257.341611 \nL 624.910921 257.715911 \nL 625.147727 258.382791 \nL 625.384533 258.643251 \nL 625.858146 257.979638 \nL 626.094952 257.992475 \nL 626.568564 258.665472 \nL 626.80537 258.659957 \nL 627.278983 258.310045 \nL 627.752595 258.633476 \nL 627.989401 258.760635 \nL 628.936626 258.645738 \nL 629.410239 258.818877 \nL 630.120657 258.720491 \nL 631.067882 258.858844 \nL 631.778301 258.873451 \nL 632.488719 258.928933 \nL 633.435944 258.968451 \nL 635.093588 259.013048 \nL 636.040813 258.875486 \nL 636.514425 258.580642 \nL 636.751231 258.269282 \nL 636.988037 257.74547 \nL 637.224844 256.883402 \nL 637.46165 255.503793 \nL 637.698456 253.357185 \nL 638.172068 245.652091 \nL 638.645681 232.505325 \nL 640.303324 174.450874 \nL 640.540131 172.291384 \nL 640.776937 175.290797 \nL 641.013743 186.608269 \nL 641.487355 242.647956 \nL 641.724162 202.175041 \nL 641.960968 188.978169 \nL 642.197774 188.717915 \nL 642.43458 200.535965 \nL 642.671386 232.123 \nL 642.908193 231.343344 \nL 643.144999 205.591004 \nL 643.381805 199.030072 \nL 643.618611 205.378317 \nL 644.092224 242.750818 \nL 644.32903 219.000969 \nL 644.565836 209.886766 \nL 644.802642 213.721157 \nL 645.276255 244.944644 \nL 645.749867 219.921417 \nL 645.986673 222.772313 \nL 646.460286 247.146417 \nL 646.933898 228.674611 \nL 647.170704 231.376383 \nL 647.644317 250.335356 \nL 648.117929 236.035933 \nL 648.354735 238.631986 \nL 648.828348 254.034735 \nL 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373.422728 264.405215 \nL 374.369953 264.305853 \nL 375.080371 264.295614 \nL 376.264402 263.961386 \nL 376.738015 263.653493 \nL 377.211627 263.130002 \nL 378.632464 261.234839 \nL 378.869271 261.398444 \nL 379.106077 261.84808 \nL 380.053302 264.406699 \nL 380.290108 264.474209 \nL 380.76372 263.947746 \nL 381.237333 263.456938 \nL 381.474139 263.44638 \nL 381.947751 263.857342 \nL 382.421364 264.364553 \nL 382.894976 264.486047 \nL 384.079007 264.117995 \nL 385.973457 264.472015 \nL 387.157488 264.399334 \nL 389.762356 264.519578 \nL 395.208899 264.272166 \nL 395.919318 263.965736 \nL 396.39293 263.553957 \nL 396.866542 262.862834 \nL 398.050573 260.59724 \nL 398.28738 260.638767 \nL 398.524186 261.076119 \nL 399.471411 264.443557 \nL 399.708217 264.552366 \nL 400.181829 263.807801 \nL 400.655442 263.202635 \nL 400.892248 263.268043 \nL 401.839473 264.542986 \nL 402.076279 264.564971 \nL 403.023504 264.045804 \nL 403.497116 264.207562 \nL 404.207535 264.570601 \nL 404.681147 264.549872 \nL 405.628372 264.394336 \nL 407.522822 264.576635 \nL 408.943659 264.543635 \nL 411.074915 264.612976 \nL 415.811039 264.445869 \nL 416.284651 264.229625 \nL 416.758264 263.799237 \nL 417.468682 262.903506 \nL 417.705489 262.83415 \nL 417.942295 263.048521 \nL 418.652713 264.370434 \nL 418.88952 264.307124 \nL 419.599938 263.285984 \nL 420.310357 263.158788 \nL 420.547163 262.80008 \nL 421.494388 260.677012 \nL 421.731194 260.635148 \nL 421.968 260.849735 \nL 422.204807 261.314956 \nL 422.678419 262.957451 \nL 423.152031 264.504082 \nL 423.388838 264.638435 \nL 423.625644 264.325203 \nL 424.099256 263.4066 \nL 424.336062 263.265168 \nL 424.572869 263.401746 \nL 425.520094 264.543466 \nL 425.993706 264.551354 \nL 426.704125 264.148618 \nL 427.177737 264.237655 \nL 427.888156 264.637288 \nL 428.361768 264.650979 \nL 429.545799 264.498373 \nL 432.387474 264.637505 \nL 434.281923 264.692478 \nL 437.59721 264.693552 \nL 439.49166 264.608356 \nL 440.438885 264.404764 \nL 441.149303 263.978015 \nL 441.622916 263.399606 \nL 442.096528 262.47876 \nL 443.043753 260.238148 \nL 443.280559 260.11656 \nL 443.517365 260.423356 \nL 443.990978 262.32917 \nL 444.46459 264.420532 \nL 444.701396 264.748825 \nL 444.938203 264.529029 \nL 445.648621 263.15795 \nL 445.885427 263.162819 \nL 446.35904 263.946535 \nL 446.832652 264.698087 \nL 447.069458 264.747872 \nL 448.016683 264.111475 \nL 448.490296 264.324475 \nL 449.200714 264.755158 \nL 449.674327 264.698747 \nL 450.384745 264.524161 \nL 451.095164 264.662407 \nL 451.805583 264.775659 \nL 454.647257 264.78171 \nL 462.935474 264.796253 \nL 464.593118 264.654732 \nL 465.06673 264.500967 \nL 465.540343 264.159325 \nL 466.013955 263.454364 \nL 466.487568 262.119083 \nL 467.671599 257.493069 \nL 467.908405 258.001655 \nL 468.382017 261.773906 \nL 468.618823 263.849107 \nL 468.85563 264.742895 \nL 469.092436 264.221522 \nL 469.566048 261.959909 \nL 469.802854 261.710405 \nL 470.039661 262.326705 \nL 470.513273 264.471599 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264.851409 \nL 505.323786 264.474936 \nL 505.797398 262.383566 \nL 506.034204 262.675997 \nL 506.507817 264.770691 \nL 506.744623 264.893028 \nL 507.218235 263.670979 \nL 507.455042 263.631605 \nL 508.16546 264.96275 \nL 508.875879 264.226974 \nL 509.586297 264.972658 \nL 509.823104 264.907444 \nL 510.296716 264.594808 \nL 510.533522 264.643959 \nL 511.007135 264.95735 \nL 511.480747 264.899542 \nL 511.95436 264.789335 \nL 512.901584 264.974304 \nL 513.612003 264.892173 \nL 514.559228 264.969895 \nL 517.400902 264.600952 \nL 517.874515 264.246758 \nL 518.348127 263.574968 \nL 518.82174 262.485174 \nL 519.768964 260.027674 \nL 520.005771 259.895906 \nL 520.242577 260.186775 \nL 520.479383 260.947375 \nL 521.189802 264.454887 \nL 521.426608 264.966563 \nL 521.663414 264.852293 \nL 522.373833 263.274593 \nL 522.610639 263.19815 \nL 522.847445 263.47513 \nL 523.557864 264.876336 \nL 523.79467 264.998667 \nL 524.031476 264.902174 \nL 524.741895 264.346798 \nL 524.978701 264.35203 \nL 525.452313 264.658437 \nL 525.925926 264.981674 \nL 526.399538 264.999958 \nL 527.346763 264.771702 \nL 529.241213 265.001373 \nL 530.425244 264.968525 \nL 532.082887 265.050174 \nL 536.108593 265.065337 \nL 540.607911 265.051425 \nL 542.028748 264.90118 \nL 542.50236 264.712125 \nL 542.975973 264.322319 \nL 543.449585 263.519271 \nL 543.923198 262.018796 \nL 545.107229 256.631838 \nL 545.344035 256.994379 \nL 545.580841 258.481044 \nL 546.29126 264.859168 \nL 546.528066 264.649261 \nL 547.001678 262.103619 \nL 547.238485 261.578324 \nL 547.475291 262.027148 \nL 548.185709 265.075949 \nL 548.422516 264.85404 \nL 548.896128 263.554902 \nL 549.132934 263.435306 \nL 549.36974 263.823685 \nL 549.843353 264.964774 \nL 550.080159 265.080178 \nL 550.790578 264.302822 \nL 551.027384 264.366353 \nL 551.737802 265.099417 \nL 551.974609 265.084282 \nL 552.685027 264.752358 \nL 553.15864 264.936344 \nL 553.632252 265.120853 \nL 555.289896 265.083418 \nL 556.000314 265.090554 \nL 556.947539 265.054936 \nL 557.894764 265.046297 \nL 558.841989 264.813187 \nL 559.315601 264.531692 \nL 559.789214 263.959135 \nL 560.262826 262.883813 \nL 560.973245 260.151188 \nL 561.446857 258.652481 \nL 561.683663 258.66663 \nL 561.920469 259.474129 \nL 562.867694 265.102913 \nL 563.1045 264.662017 \nL 563.578113 262.903404 \nL 563.814919 262.617237 \nL 564.051725 262.958717 \nL 564.762144 265.036741 \nL 564.99895 265.030221 \nL 565.709369 264.085735 \nL 565.946175 264.168005 \nL 566.656594 265.059431 \nL 566.8934 265.104491 \nL 567.840625 264.705228 \nL 569.024656 265.122534 \nL 569.97188 264.977881 \nL 571.155912 265.162884 \nL 572.339943 265.11751 \nL 573.76078 265.170461 \nL 575.892036 265.197672 \nL 584.653865 264.978335 \nL 585.127478 264.72326 \nL 585.60109 264.192272 \nL 586.074703 263.117826 \nL 586.548315 261.175411 \nL 587.49554 256.309842 \nL 587.732346 256.368686 \nL 587.969152 257.612344 \nL 588.679571 264.678348 \nL 588.916377 264.84069 \nL 589.626796 261.479458 \nL 589.863602 261.822054 \nL 590.574021 265.043072 \nL 590.810827 264.856841 \nL 591.284439 263.584663 \nL 591.521245 263.515487 \nL 592.46847 265.081087 \nL 593.178889 264.373284 \nL 593.415695 264.542699 \nL 593.889308 265.128008 \nL 594.126114 265.198885 \nL 595.073339 264.863167 \nL 595.783757 265.244453 \nL 596.25737 265.157265 \nL 596.730982 265.048477 \nL 598.151819 265.220579 \nL 598.862238 265.175764 \nL 600.046269 265.240093 \nL 602.177525 265.064786 \nL 602.651137 264.851243 \nL 603.12475 264.42304 \nL 603.598362 263.563457 \nL 604.071974 261.961533 \nL 605.019199 257.620691 \nL 605.256006 257.572177 \nL 605.492812 258.545551 \nL 606.20323 264.814697 \nL 606.440037 265.18425 \nL 607.150455 262.146765 \nL 607.387261 262.225437 \nL 608.09768 265.074489 \nL 608.334486 265.128924 \nL 609.044905 263.829798 \nL 609.281711 264.058065 \nL 609.755323 265.022883 \nL 609.99213 265.203121 \nL 610.228936 265.072966 \nL 610.702548 264.645166 \nL 610.939355 264.679025 \nL 611.649773 265.233045 \nL 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265.198101 \nL 672.035356 265.274523 \nL 672.745775 264.17807 \nL 672.982581 264.253424 \nL 673.693 265.320402 \nL 673.929806 265.373536 \nL 674.640224 264.894811 \nL 674.877031 264.916725 \nL 675.824256 265.456804 \nL 677.008287 265.2558 \nL 677.955511 265.484087 \nL 679.376349 265.425127 \nL 680.56038 265.478776 \nL 682.454829 265.500739 \nL 688.374985 265.485295 \nL 689.795822 265.324666 \nL 690.50624 265.030337 \nL 690.979853 264.600045 \nL 691.453465 263.786754 \nL 691.927078 262.37227 \nL 692.874303 258.671142 \nL 693.111109 258.461007 \nL 693.347915 258.992721 \nL 693.821527 262.255969 \nL 694.29514 265.249811 \nL 694.531946 265.244537 \nL 695.242365 262.918804 \nL 695.479171 262.973945 \nL 695.952783 264.482784 \nL 696.189589 265.201788 \nL 696.426396 265.45359 \nL 696.663202 265.225957 \nL 697.136814 264.417905 \nL 697.37362 264.343805 \nL 697.610427 264.572122 \nL 698.084039 265.335963 \nL 698.320845 265.509056 \nL 698.557652 265.452036 \nL 699.26807 265.002253 \nL 699.741683 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "plt.figure(figsize=[14,5])\n",
        "for i in range(nTrain):\n",
        "    plt.plot(history[i].history['loss'])\n",
        "plt.semilogy(), plt.legend(lrvec), plt.ylabel('loss'), plt.xlabel('epoch')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h8FuQIYjZByb",
        "outputId": "50ece255-9fa8-40e3-b01c-d2dc62bc1301",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 371
        },
        "tags": []
      },
      "source": [
        "xh, fh = mdl.predict(t)\n",
        "\n",
        "plt.figure(figsize=[14, 10])\n",
        "plt.subplot(221)\n",
        "plt.plot(t, x, \"b-\", t, xh, \"ro\")\n",
        "plt.legend([\"y\", \"xh\"])\n",
        "plt.subplot(223)\n",
        "plt.plot(x,xh, \"ro\")\n",
        "xmin, ymax = (np.min([x.min(),xh.min()]),np.max([x.max(),xh.max()]))\n",
        "plt.plot(np.array([xmin,ymax]),np.array([xmin,ymax]), color = 'black', linewidth = 2) # this is just a 45º line\n",
        "plt.xlabel('x'), plt.ylabel('xh')\n",
        "\n",
        "plt.subplot(222)\n",
        "plt.plot(t, f, \"b-\", t, fh, \"ro\")\n",
        "plt.legend([\"f\", \"fh\"])\n",
        "plt.subplot(224)\n",
        "plt.plot(f,fh, \"ro\")\n",
        "xmin, ymax = (np.min([f.min(),fh.min()]),np.max([f.max(),fh.max()]))\n",
        "plt.plot(np.array([xmin,ymax]),np.array([xmin,ymax]), color = 'black', linewidth = 2) # this is just a 45º line\n",
        "plt.xlabel('f'), plt.ylabel('fh')\n",
        "\n",
        "plt.show()\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 1008x720 with 4 Axes>",
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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "source": [
        "# Parameter identification analysis"
      ],
      "cell_type": "markdown",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iQwpF_E7P8QB",
        "outputId": "22713aed-eed0-42d7-f4d3-c2b6293e31bd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "tags": []
      },
      "source": [
        "\n",
        "btrue = 0.084\n",
        "ktrue = 2.2020\n",
        "print(\"Values identified for the ODE (rho = 2.0, b = %0.4f, k = %0.4f are the real values)\" % (btrue, ktrue))\n",
        "print(\"bhat: %f ( %f %% error ) | khat: %f ( %f %% error )\" % (mdl.tToXandF.b.numpy(), np.abs((btrue - mdl.tToXandF.b.numpy())/btrue * 100 ), mdl.tToXandF.k.numpy(), np.abs((ktrue - mdl.tToXandF.k.numpy())/ktrue * 100 )))\n",
        "\n",
        "plt.figure(figsize=[14, 5])\n",
        "plt.subplot(121)\n",
        "leg = lrvec.tolist()\n",
        "leg.append('true')\n",
        "epoch = 0\n",
        "for i in range(nTrain):\n",
        "    hatMatrix = np.array(clbkVarValue[i].valueList)\n",
        "    epochi,_ = hatMatrix.shape    \n",
        "    plt.plot(range(epochi),hatMatrix[:,0:1])\n",
        "    epoch = np.max((epoch,epochi))\n",
        "epochvec = np.linspace(1,epoch)\n",
        "plt.plot(epochvec,np.ones(epochvec.shape)*btrue,'k--',linewidth = 3)\n",
        "plt.xlabel('epoch'), plt.legend(leg), plt.title('b')\n",
        "\n",
        "plt.subplot(122)\n",
        "for i in range(nTrain):\n",
        "    hatMatrix = np.array(clbkVarValue[i].valueList)\n",
        "    plt.plot(hatMatrix[:,1:])\n",
        "plt.plot(epochvec,np.ones(epochvec.shape)*ktrue,'k--',linewidth = 3)\n",
        "plt.xlabel('epoch'), plt.legend(leg), plt.title('k')\n",
        "plt.show()\n",
        "\n"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Values identified for the ODE (rho = 2.0, b = 0.0840, k = 2.2020 are the real values)\nbhat: 0.084378 ( 0.450244 % error ) | khat: 2.201468 ( 0.024139 % error )\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}