denoise_RC/denoise try.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8dfdb267-e85d-4c46-af7a-5b37c1a14254",
   "metadata": {},
   "outputs": [],
   "source": [
    "import reservoirpy as rpy\n",
    "from reservoirpy.datasets import lorenz\n",
    "from reservoirpy.datasets import rossler\n",
    "\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "rpy.verbosity(False)\n",
    "\n",
    "rpy.set_seed(42)\n",
    "\n",
    "name_idx = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4d5e41d9-3d27-4f02-b191-b5b6c760a88a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_noise(time_series, noise_type=\"random\", noise_level=0.5):\n",
    "    \"\"\"\n",
    "    对输入的时间序列添加噪声。\n",
    "    \n",
    "    参数:\n",
    "        time_series (numpy.ndarray): 输入的时间序列。\n",
    "        noise_type (str): 噪声类型，可选值为 \"random\"（随机噪声）, \"sin\"（正弦噪声）, 或 \"gaussian\"（正态分布噪声）。\n",
    "        noise_level (float): 噪声强度，决定噪声幅度。\n",
    "    \n",
    "    返回:\n",
    "        numpy.ndarray: 添加噪声后的时间序列。\n",
    "    \"\"\"\n",
    "    if noise_type == \"random\":\n",
    "        noise = np.random.uniform(-noise_level, noise_level, len(time_series))\n",
    "    elif noise_type == \"sin\":\n",
    "        noise = noise_level * np.sin(30 * np.pi * np.arange(len(time_series)) / len(time_series))\n",
    "    elif noise_type == \"gaussian\":\n",
    "        noise = np.random.normal(0, noise_level, len(time_series))\n",
    "    else:\n",
    "        raise ValueError(\"Unsupported noise_type. Choose from 'random', 'sin', or 'gaussian'.\")\n",
    "    \n",
    "    return time_series + np.stack((noise,noise,noise)).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3a675a87",
   "metadata": {},
   "outputs": [],
   "source": [
    "def show(t1, t2, figsize1=(18, 6)):\n",
    "    plt.figure(figsize=figsize1)\n",
    "\n",
    "    plt.subplot(3, 1, 1)\n",
    "    plt.plot(t2[:,0], label='prediction')\n",
    "    plt.plot(t1[:,0], label='target', linestyle='--', color='#ff7f0e')\n",
    "    \n",
    "    plt.title('Lorenz X-component')\n",
    "\n",
    "    plt.subplot(3, 1, 2)\n",
    "    plt.plot(t2[:,1], label='prediction')\n",
    "    plt.plot(t1[:,1], label='target', linestyle='--', color='#ff7f0e')\n",
    "    \n",
    "    plt.title('Lorenz Y-component')\n",
    "\n",
    "    plt.subplot(3, 1, 3)\n",
    "    plt.plot(t2[:,2], label='prediction')\n",
    "    plt.plot(t1[:,2], label='target', linestyle='--', color='#ff7f0e')\n",
    "    \n",
    "    plt.title('Lorenz Z-component')\n",
    "    \n",
    "    fig = plt.figure(figsize=(12,5), dpi=150)\n",
    "    \n",
    "    rmse = np.sqrt(np.mean((t1 - t2)**2))\n",
    "    fig.suptitle(\"Lorenz Attractor-RMSE: {:.8f}\".format(rmse))\n",
    "    \n",
    "    ax = fig.add_subplot(121, projection='3d')\n",
    "    ax.plot(t2[:,0], t2[:,1], t2[:,2])\n",
    "    ax.set_title(\"Lorenz\")\n",
    "\n",
    "    ax = fig.add_subplot(122, projection='3d')\n",
    "    ax.plot(t1[:,0], t1[:,1], t1[:,2], color='#ff7f0e')\n",
    "    ax.set_title(\"Processed Lorenz\")\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2aafc56f-a9b6-47ea-906d-cacb635c91eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = lorenz(10000, h=0.001)[2000:,:]\n",
    "\n",
    "norm01 = lambda x: (x - np.min(x, axis=0)) / (np.max(x, axis=0) - np.min(x, axis=0)) * 2 - 1\n",
    "\n",
    "data = norm01(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "03bef5f4-84c2-4da8-bcc6-316b1f7b4316",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = add_noise(data[:1000,:], 'gaussian', noise_level=0.8)\n",
    "target_input = data[:1000,:]\n",
    "\n",
    "test_data = add_noise(data[1000:2000,:], \"gaussian\", noise_level=0.8)\n",
    "target_test = data[1000:2000,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2eaef879",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1500x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(test_data, target_test, figsize1=(15,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c9fc396b",
   "metadata": {},
   "outputs": [],
   "source": [
    "name_idx += 1\n",
    "\n",
    "inp = rpy.nodes.Input(input_dim=3)\n",
    "oup1 = rpy.nodes.Output(output_dim=3, name='output1'+str(name_idx))\n",
    "oup2 = rpy.nodes.Output(output_dim=3, name='output2'+str(name_idx))\n",
    "oup3 = rpy.nodes.Output(output_dim=3, name='output3'+str(name_idx))\n",
    "\n",
    "rdo1 = rpy.nodes.Ridge(output_dim=3, ridge=1e-7, name='reo1'+str(name_idx))\n",
    "rdo2 = rpy.nodes.Ridge(output_dim=3, ridge=1e-7, name='reo2'+str(name_idx))\n",
    "rdo3 = rpy.nodes.Ridge(output_dim=3, ridge=1e-7, name='reo3'+str(name_idx))\n",
    "\n",
    "res1 = rpy.nodes.Reservoir(1000, lr=0.8, sr=0.9, noise_fb=0, equation='external', activation='sig')\n",
    "res2 = rpy.nodes.Reservoir(1000, lr=0.2, sr=0.9, noise_fb=0, equation='external', activation='tanh')\n",
    "res3 = rpy.nodes.Reservoir(1000, lr=0.2, sr=0.9, noise_fb=0, equation='external', activation='tanh')\n",
    "\n",
    "esn = inp >> res1 >> rdo1 >> res2 >> rdo2 >> res3 >> rdo3 >> oup3 & \\\n",
    "      rdo1 >> oup1 & \\\n",
    "      rdo2 >> oup2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bb139e3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "esn = esn.fit(input_data, {'reo1'+str(name_idx):target_input,\n",
    "                           'reo2'+str(name_idx):target_input,\n",
    "                           'reo3'+str(name_idx):target_input})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a43ae7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = esn.run(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4402b7e5-08d0-48f3-ad5a-9c53da163731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABXYAAAKvCAYAAADOXpedAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAABcSAAAXEgFnn9JSAAEAAElEQVR4nOzdd3hb5dk/8K+WZcuyLNvxip3Yzh527CRQoAQClLJaCgHKLrtASxfQUqAUUuDtekt/Xby0BV5WaZktsykzQBhhxivTTux4T1nytjWe3x9+n8ORLMmSJdmS8/1cl68WS+foSHKk+9znfu5bI4QQICIiIiIiIiIiIqKEoZ3tAyAiIiIiIiIiIiKi8DCxS0RERERERERERJRgmNglIiIiIiIiIiIiSjBM7BIRERERERERERElGCZ2iYiIiIiIiIiIiBIME7tERERERERERERECYaJXSIiIiIiIiIiIqIEw8QuERERERERERERUYJhYpeIiIiIiIiIiIgowTCxS0RERERERERERJRgmNglIiIiIiIiIiIiSjBM7BIRERERERERERElGCZ2iYiIiIiIiIiIiBIME7tERERERERERERECYaJXSIiIiIiIiIiIqIEw8QuERHNSZs3b4ZGo4FGo5ntQznkuN1uFBQUKK//a6+9NuU2mzdvxubNm9HY2BjwPo2Njcr9EpXdbleeg91un+3DmZJ8D9U/Wq0WFosFa9aswXXXXYddu3YF3cdll13mtf327dunfNzS0lKvbQI5ePAgbrnlFhx++OHIyMiAwWBAbm4u1qxZg7PPPhu/+93vUFVVNWm7xsZGv88t0M/DDz885TFP12effYaLL74YhYWFMBqNyM/Px6ZNm/Dmm29GZf9bt27Fpk2bkJ+fD6PRiMLCQlx88cX47LPPgm4Xyuty8cUX+93W5XLhjTfewH//93/j/PPPx7Jly6DVaqHRaHDZZZeFfOwDAwPYvHkzysrKYDabkZ6ejsMPPxz33HMPxsfHA26n/vwP9lNfXx/ysTidTqxZs0bZNtjzePzxx/G9730PGzZsQHFxMVJTU5GcnIyFCxdi06ZNePbZZwNuK4TABx98gNtuuw3HHXcccnNzYTAYkJ6ejvXr1+OWW25Ba2tryMdNREREc5wgIiKag+644w4BQPCrbua9+OKLymsPQJx//vlTbiPvu3Xr1oD32bp1a8K/pw0NDcpzaGhomO3DmZI81tTUVJGbmytyc3PFvHnzhEajUW4zGAziwQcfDLiPSy+91Ovv4eqrrw76mNu3b/e6f6D3+29/+5swmUxe97NYLMJsNnv9rqioaNK26vfBYrEozy3QzxNPPBHW6xaq+++/X+j1euVY0tPTvV7bO+64I6L9qz8HNRqNSE9PV/5br9eL+++/P+C28n4ZGRkBX5frrrvO77bq19f359JLLw3p2BsbG0VxcbGynclkEkajUfnvtWvXCpvNFvR5GwyGoO9rOP8G1a/lVM8jNTXV677p6ekiKSnJ63cnnXSSGBwcnLTt3Xff7XU/jUYjrFar19+FxWIRzz//fMjHTkRERHMXK3aJiIgoqh588EEAwHXXXQeNRoN//etfsNlss3xUFIkf/vCH6OjoQEdHB7q7uzEyMoLnnnsOCxYsgNPpxDXXXIO9e/cG3cfChQuh0Wjw5JNPYmRkJOD9HnroIQBAcXFxwPt8/PHHuOSSSzA8PIw1a9bgmWeeweDgIBwOBwYGBtDV1YXnnnsOl112GVJTU4Me1+9//3vluQX6Oe+884LuYzo++OADXHvttXC5XDjzzDPR3NwMu92O7u5uXHPNNQCAn/3sZ3jqqaemtf+nnnoKP/vZzwAA11xzDbq7u2G329Hc3IwzzzwTLpcL1157LT744IOg+/nnP/8Z8HX505/+FHC7tLQ0bNiwAd///vfxyCOPoKKiIuRjd7lcOP3009HY2Ij8/Hy89tprGBoawvDwMJ544gmkpaVhx44dASuGpS9+8YtB39dgf2NqNTU1+PnPf45FixYhNzd3yvtfddVVeOSRR1BXV4fR0VHY7XaMjo5i//79+O53vwsAePXVV3HjjTdO2tbpdMJiseDaa6/Fm2++iaGhIfT19WFoaAjPPvssFi5ciP7+fnz961/H7t27Qzp+IiIimsNmO7NMREQUC6zYnR0dHR1Cr9cLnU4nWltbxXHHHScAiD/84Q9Bt5PvFSt244s81kCVo++8845yn1tuucXvfWTF7saNG8XGjRsFAPHYY4/5ve/w8LBStXr77bcHfL8vvPBCAUDk5OQIu90e9DkMDw9P+p36fXjooYeCbh8rGzZsEABEWVmZGB8fn3T7ySefLACI4uJi4XK5wtq3y+USRUVFAoA45ZRTJt0+NjYmSktLBQCxYcMGv/sI5d9kIG63W3g8Hq/fyfc+lIrdBx54QHn8999/f9Ltf//735XbX3/99Um3y8//jRs3hn3svlwulzjssMMEAPHqq68qr2uolcf+XHDBBQKASElJmfTe79ixI2AlshBCHDhwQKSkpAgA4sorr5z2MRAREdHcwIpdIiIiHw6HA3feeSfWrVsHi8WClJQULF26FN/61rdw4MCBgNvJ3otvvfUWurq6cMMNN2DZsmUwmUx++4S+/PLLOPvss1FQUACj0YiMjAwce+yxuO+++wL2jzzuuOOg0WiwefNmCCFw//3344gjjoDFYkFaWhqOOuoo/O1vf/O7rW+v02A/0/Xoo4/C5XLhxBNPxPz583HppZcCAP73f/836DFJxx9/vNdxyIq64uJiHH/88cr9fI9X3e9S9tc87rjjAADPPvssTjrpJOTk5ECr1Xr16K2trcXmzZtxwgknYPHixUhJSYHFYsHatWtx2223oaenZ8rnvHv3blx33XVYtWoV0tLSYDabsXz5cpx//vl49tln4fF4AEy8dyUlJcp2JSUlXs9BHq9aR0cHfvSjH2H16tVITU1FamoqVq9ejZtuugmdnZ1+j0fdP7axsRH79+/H1VdfjZKSEhiNxpCrFEOxYcMGpSJ2586dU97/8ssvB/B5Va6vZ599Fg6HY9Jr5auyshLAxGuanp4e9DFTUlKmPK6ZduDAAbz77rsAJqqhDQbDpPvccsstACbez3feeSes/b/99ts4ePCg137UkpKS8MMf/hAA8O6776KhoSGs/U9F9tOdrkceeQTAxOfBUUcdNen2888/X/n7ePTRR6f9OKG455578Mknn+CSSy7Bl7/85ajs88gjjwQAjIyMTFrNUFFRgYyMjIDblpSUKJ+FH3/8cVSOh4iIiBKXfrYPgIiIKJ7s3LkTp5xyClpaWgAAycnJMBgMqK+vR319PR566CE8/vjjOPvsswPuo76+Hueffz46OzuV7dVGRkZwySWX4JlnnlF+Z7FY4HA4sG3bNmzbtg2PPvoo/v3vfwc8wXe73di0aROef/556PV6mEwmDAwMYPv27di+fTvq6uqUZdhSenp60GXEAwMDGB4envI1CkYmcC+55BIAwDnnnIPvfOc7qKysxGeffYZ169b5PSaZpMzIyEBSUpJye3Z2tvK//f396OvrA4BJzyNQcu/GG2/Eb3/7W2g0GlitVmi13te0v/rVryoJsOTkZJhMJvT19aGyshKVlZV4+OGH8cYbb2D58uV+9/+rX/0Kt956q5K8lfuor6/Hvn378OSTT6Kvrw9WqxWZmZmYN2+ekiyeN28edDqdsq/MzEyvfb/99ts488wzlSFrMoG6a9cu7Nq1Cw888ABeeOEFbNiwwe+xAcD777+Pa665BoODgzCZTH4TiNHidrunvM8555yD7373u9i6dSsaGxsnJZllwvfyyy8PaX/y3+lsKC4uxsGDB7Fx40a89dZbYW2rHih4yimn+L3Phg0bkJaWhoGBAbz66qteFzZC3X9aWhqOPvpov/c59dRTlf//6quvKu0fZtvw8DDee+89AN7HqKbRaHDKKafgvvvuw6uvvhqzY9m3bx/uuOMOZGdn47e//W3U9rtt2zYAgNlsRk5OTtjbJycnAwjt3xwRERHNbazYJSIi+j8DAwM4/fTT0dLSgoKCArz88ss
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(pred['output1'+str(name_idx)], target_test)\n",
    "show(pred['output2'+str(name_idx)], target_test)\n",
    "show(pred['output3'+str(name_idx)], target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d223f1cc",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABXwAAAKtCAYAAACUtKZfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAABcSAAAXEgFnn9JSAAEAAElEQVR4nOzdeXhjZdk/8G+2pknTJN3XmS4zwwyztTMDAoIMIMq+74tsIovIq4IiKgIKovhDxdcFFJQBREFAWR2RZYZ9h26zL933adKma5rl+f3R9zmcpEmaNEmbdr6f6+qlNDk5JznT5D537ue+NUIIASIiIiIiIiIiIiKa87SzfQBERERERERERERElBhM+BIRERERERERERHNE0z4EhEREREREREREc0TTPgSERERERERERERzRNM+BIRERERERERERHNE0z4EhEREREREREREc0TTPgSERERERERERERzRNM+BIRERERERERERHNE0z4EhEREREREREREc0TTPgSERERERERERERzRNM+BIRERERERERERHNE0z4EhEREREREREREc0TTPgSERERERERERERzRNM+BIRERERERERERHNE0z4EhEREREREREREc0TTPgSEdG8dPvtt0Oj0UCj0cz2oex3fD4fSkpKlNf/5ZdfnnKb22+/HbfffjuamprC3qepqUm531zV39+vPIf+/v7ZPpwpyXOo/tFqtbBarVi9ejWuu+46bN26NeJjXHbZZQHbv/fee1Pud+XKlQHbhNPc3Izvf//7OPjgg5GVlQWDwYCCggKsXr0aZ511Fu69917U1tZO2q6pqSnkcwv3s2HDhimPebo++eQTXHzxxSgtLYXRaERRURHOOOMMvPbaa9N+TCEE3n33Xdxyyy046qijUFBQAIPBAJvNhnXr1uH73/8+2tvbw26vfv+M5uf1118P2D74nE/109zcHLB9tOfnlltuiel1+fnPfx7Vvys1l8uFu+++G5///OeRl5cHo9GI0tJSHH300TH/HUe7/1heu6OPPjrq/RMREdH+Qz/bB0BERETzy8aNG9HR0aH891/+8hd86UtfirjNj3/8YwDAUUcdhfLy8pD3aWpqUu43V5O+/f39ynO47LLLYLfbZ/eAopSRkQGLxQJgIqHf19eH+vp61NfX44EHHsD999+PK664IqrHeuihh3DooYeGvf3999/Hli1bpnycxx57DFdddRVGRkaU31mtVoyMjCjH9s9//hNlZWURv0iwWq0wmUwR9zXV7dP14IMP4tprr4XX6wUA2Gw2dHd345lnnsEzzzyD2267bVr/1u+6666AZKhGo4HNZsPAwAA++eQTfPLJJ/jDH/6ARx99FKeeeuqk7S0WCwoKCiLuw+l0Ynx8HEajEatWrQq4zWazTbn9vn374PP5UFRUhNLS0rD3y83NhU6nC3lbZmZmxH2o7dixQ/nbi9amTZtwwQUXoLu7GwCQlpYGs9mM9vZ2tLe3Y/PmzTj99NNRXV2d0P1P9dp5PB44HA4AwMEHHxzVYxIREdF+RhAREc1Dt912mwAg+FE3804//XQBQFx33XVCo9EIo9Eo+vr6Im4jz9WmTZvC3mfTpk1z/pw2NjYqz6GxsXG2D2dK8lhvu+22gN+PjY2JZ555RixYsEAAEHq9Xmzfvj3kY1x66aUCgFi4cKHQaDTCZrOJkZGRsPu8+uqrBQBRXl4e9nx/8MEHQqvVCgBi9erV4qmnnhJDQ0PK7T09PeKZZ54Rl112mVi+fPmk7dXn4aGHHoruxUiwd955R+h0OgFAnH766aK1tVUIIcS+ffuU1wCAeOKJJ2J+7Ntuu01YrVZxzTXXiNdee015vUdGRsTTTz8tFi5cKACItLQ0sXXr1pgf3+12i5ycHAFAnH/++TFv39XVJfR6vQAgbr755km3J/rvxOfzic9//vMCgDjssMOieh956623hMlkEgDEmWeeKT788EPh9/uFEEIMDw+LDz74QPzwhz8Ue/fuTcr+I7nnnnuUxwj3d0dERET7N7Z0ICIiooTp7u7GCy+8AJ1Ohx/84AdYv3493G43Hnvssdk+NEogo9GI0047TTmvXq8XDz/8cMRtKioqcOSRR2JgYABPP/10yPuMjo7i8ccfh0ajwSWXXBL2se699174/X7k5+fjjTfewFlnnYWMjAzl9ry8PJx22ml46KGH8NFHH03jGSbfTTfdBJ/Ph1WrVuEf//iHUuWak5OD+++/H8cddxwA4Hvf+x58Pl9Mj3366aejqakJ9913H44++milQtlkMuHMM8/E5s2bYTKZMD4+jl/+8pcxH/u//vUv9PX1AQCuvPLKmLffsGEDvF4vNBoNvvrVr8a8fax++9vf4p133sFFF12EL3/5y1Pef2RkBJdccglGR0dx/fXX4+mnn8ZBBx2ktGEwm804+OCDceedd6KioiLh+5/Kn//8ZwDAEUccgaVLl8b9eERERDT/MOFLREQUZGBgAD/5yU+wdu1aZbn3kiVLcO2112Lv3r1ht5M9FTdv3oyenh7ccMMNOOCAA2A2m0P2a3zxxRdx1llnoaSkBEajEVlZWTjyyCNx3333YXx8POQ+jjrqKGg0Gtx+++0QQuCBBx7AIYccAqvViszMTBx22GH461//GnLbWPpqTtcjjzwCr9eLY489FsXFxbj00ksBTLR1iHRM0tFHHx1wHLK9Q3l5eUCvyuDjveyyy5TbZP/Ro446CgDw9NNP48tf/jLy8/Oh1WoDlsg3NDTg9ttvxzHHHINFixbBZDLBarVizZo1uOWWW7Bv374pn/O2bdtw3XXXYfny5cjMzITFYsHSpUtx/vnn4+mnn4bf7wcwce7UyaGKioqA5yCPV62rqwvf/e53sWLFCmRkZCAjIwMrVqzATTfdpCwzD6buf9rU1IQ9e/bgqquuQkVFBYxGY9iWGdNxxBFHKInWaNowXH755QAm2jqE8vTTT2NgYGDSaxWspqYGwMRrarPZIu4zWe0Y4rF371689dZbAIDvfOc7MBgMk+7z/e9/H8DE+XzjjTdievzq6mpkZWWFvb2iokL5e/rwww9jemzgs4RjZWUljjnmmJi3l+8H69evx+LFi2PePhaNjY344Q9/iJycHPz617+OaptHH30Ue/fuRWFhIX7xi1/M+P4jeeedd7Bt2zYA00u2ExER0f6BPXyJiIhUtmzZguOPPx5tbW0AgPT0dBgMBuzevRu7d+/GQw89hMceewxnnXVW2MfYvXs3zj//fHR3dyvbq42OjuKSSy7BU089pfzOarViYGAAb775Jt5880088sgj+Pe//x02aePz+XDGGWfg2WefhV6vh9lsxuDgIN577z2899572LVr16R+kVP11RwcHAzohzodMpEjqzPPPvtsfOMb30BNTQ0++eQTrF27NuQxyeRlVlYW0tLSlNvz8vKU/3W5XHA6nQAm97gMl/S78cYb8atf/QoajQZ2ux1abeB33SeffLIyMCo9PR1msxlOpxM1NTWoqanBhg0b8Oqrr4atorv77rvxgx/8QEnqysfYvXs3du7ciSeeeAJOpxN2ux3Z2dnIzc1VksjBvUmzs7MDHvv111/H6aefrgyFkonVrVu3YuvWrXjwwQfx3HPP4Ygjjgh5bMBEcujqq6/G0NAQzGZzyMRiokRThXr22Wfj+uuvx6ZNm9DU1DQp+SwTwZdffnlUjyf/TmdDeXk5mpubsX79emzevDmmbdWDDI8//viQ9zniiCOQmZmJwcFB/Pe//034cK709HQA0Z03tebmZrz66qsAgCuuuCLmL4jefPNN7Ny5E8DMJCy/9rWvYXh4GH/4wx+U95OpPPLIIwCAc845R3mdZnL/kchku81mwznnnBP34xEREdE8Nds9JYiIiJJhOj18XS6XqKioEABESUmJePHFF4XP5xNCCFFTUyMOPfRQAUAYjUZRU1MzaXu5P4vFIpYuXSpeffVVZfsdO3Yo97v44osFAFFZWSkee+wxMTAwIIQQYnR0VDz77LOisrJS6esZbP369QKAyMrKEjabTWzYsEHpz9na2ipOOeUUAUBotVqxc+fOqJ9
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_data = add_noise(data[1000:2000,:], \"sin\", noise_level=0.5)\n",
    "target_test = data[1000:2000,:]\n",
    "\n",
    "pred = esn.run(test_data, reset=True)\n",
    "\n",
    "show(test_data, target_test)\n",
    "show(pred['output1'+str(name_idx)], target_test)\n",
    "show(pred['output2'+str(name_idx)], target_test)\n",
    "show(pred['output3'+str(name_idx)], target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8a903964",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = add_noise(data[:1000,:], 'sin', noise_level=0.1)\n",
    "target_input = data[1:1001,:]\n",
    "\n",
    "test_data = add_noise(data[1000:2000,:], \"sin\", noise_level=0.1)\n",
    "target_test = data[1001:2001,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5227c898",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(test_data, target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a0d147a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "inp_1 = rpy.nodes.Input(input_dim=3)\n",
    "res_1 = rpy.nodes.Reservoir(500, lr=0.3, sr=0.9, equation='internal')\n",
    "rdo_1 = rpy.nodes.Ridge(output_dim=3, ridge=1e-7)\n",
    "\n",
    "esn_1 = inp_1 >> res_1 >> rdo_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e9365021",
   "metadata": {},
   "outputs": [],
   "source": [
    "esn_1 = esn_1.fit(input_data, target_input, warmup=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f066fa6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_len = 1000\n",
    "u = input_data[-1,:]\n",
    "\n",
    "pred = np.zeros((test_len,3))\n",
    "\n",
    "for t in range(test_len):\n",
    "    u = esn_1.run(u)\n",
    "    \n",
    "    pred[t,:] = u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2161cec3",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1800x750 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(pred, target_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "43b4a129",
   "metadata": {},
   "outputs": [],
   "source": [
    "inp_2 = rpy.nodes.Input(input_dim=3)\n",
    "res_2 = rpy.nodes.Reservoir(500, lr=0.3, sr=0.9, equation='external')\n",
    "rdo_2 = rpy.nodes.Ridge(output_dim=3, ridge=1e-7)\n",
    "\n",
    "esn_2 = inp_2 >> res_2 >> rdo_2\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}