{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A Three tank example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a slightly larger example on residual generator design/simulation for the Three-tank example from the paper \n",
    "\n",
    "\"_Diagnosability Analysis Considering Causal Interpretations for Differential Constraints_\", Erik Frisk, Anibal Bregon, Jan Aaslund, Mattias Krysander, Belarmino Pulido, and Gautam Biswas IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans (2012), Vol. 42, No. 5, 1216-1229."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center><img src=\"../images/Three_tanks.png\" alt=\"drawing\" width=\"50%\"/></center>\n",
    "\n",
    "This example will go through the process of \n",
    "* defining a model\n",
    "* initial model analysis\n",
    "* residual generator analysis\n",
    "* generating C-code for a few residual generators\n",
    "* simulating the process and generating synthetic data\n",
    "* running the residual generators on the generated data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, the necessary imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import faultdiagnosistoolbox as fdt\n",
    "import sympy as sym\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.linalg import solve_continuous_are\n",
    "import seaborn as sns\n",
    "import os\n",
    "import TankSimulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Defining the model\n",
    "The model is a simple, linear, model in 12 equations, with threee measurements, and 6 faults as below\n",
    "\n",
    "<center><img src=\"../images/tt_equations.png\" alt=\"equations\" width=\"50%\"/></center>\n",
    "\n",
    "Using the symbolic toolbox `sympy`, the model can be defined by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Three Tank System\n",
      "\n",
      "  Type:Symbolic, dynamic\n",
      "\n",
      "  Variables and equations\n",
      "    10 unknown variables\n",
      "    3 known variables\n",
      "    6 fault variables\n",
      "    12 equations, including 3 differential constraints\n",
      "\n",
      "  Degree of redundancy: 2\n",
      "  Degree of redundancy of MTES set: 1\n",
      "\n",
      "\n",
      "  Model validation finished with 0 errors and 0 warnings.\n"
     ]
    }
   ],
   "source": [
    "modelDef = {}\n",
    "modelDef['type'] = 'Symbolic'\n",
    "modelDef['x'] = ['p1', 'p2', 'p3', 'q0', 'q1', 'q2', 'q3', 'dp1', 'dp2', 'dp3']\n",
    "modelDef['f'] = ['fV1', 'fV2', 'fV3', 'fT1', 'fT2', 'fT3']\n",
    "modelDef['z'] = ['y1', 'y2', 'y3']\n",
    "modelDef['parameters'] = ['Rv1', 'Rv2', 'Rv3', 'CT1', 'CT2', 'CT3']\n",
    "\n",
    "p1, p2, p3, q0, q1, q2, q3, dp1, dp2, dp3 = sym.symbols(modelDef['x'])\n",
    "fV1, fV2, fV3, fT1, fT2, fT3 = sym.symbols(modelDef['f'])\n",
    "y1, y2, y3 = sym.symbols(modelDef['z'])\n",
    "Rv1, Rv2, Rv3, CT1, CT2, CT3 = sym.symbols(modelDef['parameters'])\n",
    "\n",
    "modelDef['rels'] = [\n",
    "    -q1 + 1 / Rv1 * (p1 - p2) + fV1,\n",
    "    -q2 + 1 / Rv2 * (p2 - p3) + fV2,\n",
    "    -q3 + 1 / Rv3 * p3 + fV3,\n",
    "    -dp1 + 1 / CT1 * (q0 - q1) + fT1,\n",
    "    -dp2 + 1 / CT2 * (q1 - q2) + fT2,\n",
    "    -dp3 + 1 / CT3 * (q2 - q3) + fT3,\n",
    "    -y1 + p1, -y2 + q2, -y3 + q0,\n",
    "    fdt.DiffConstraint('dp1', 'p1'),\n",
    "    fdt.DiffConstraint('dp2', 'p2'),\n",
    "    fdt.DiffConstraint('dp3', 'p3')]\n",
    "\n",
    "model = fdt.DiagnosisModel(modelDef, name='Three Tank System')\n",
    "model_params = {'Rv1': 1, 'Rv2': 1, 'Rv3': 1, 'CT1': 1, 'CT2': 1, 'CT3': 1}\n",
    "\n",
    "model.Lint()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model structure can be visualized as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(num=10, clear=True)\n",
    "model.PlotModel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial model analysis\n",
    "\n",
    "A basic Dulmage-Mendelsohn decoposition illustrates isolability properties of the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(num=23, clear=True)\n",
    "model.PlotDM(ax=ax, fault=True, eqclass=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A more detailed isolability analysis, considering different causality assumptions can be done using the `IsolabilityAnalysis` class method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(num=20, clear=True)\n",
    "model.IsolabilityAnalysis(ax=ax)\n",
    "\n",
    "_, ax = plt.subplots(num=21, clear=True)\n",
    "model.IsolabilityAnalysis(ax=ax, causality='int')\n",
    "\n",
    "_, ax = plt.subplots(num=22, clear=True)\n",
    "_ = model.IsolabilityAnalysis(ax=ax, causality='der')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Residual generator analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, compute the set of MSO and MTES sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 6 MSO sets\n",
      "Found 4 MTES sets\n"
     ]
    }
   ],
   "source": [
    "msos = model.MSO()\n",
    "mtes = model.MTES()\n",
    "print(f\"Found {len(msos)} MSO sets\")\n",
    "print(f\"Found {len(mtes)} MTES sets\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Look at differential-index properties of the MSO and MTES sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5 of the MSO sets are low index\n",
      "3 of the MTES sets are low index\n"
     ]
    }
   ],
   "source": [
    "li_msos = [m for m in msos if model.IsLowIndex(m)]\n",
    "li_mtes = [m for m in mtes if model.IsLowIndex(m)]\n",
    "print(f\"{len(li_msos)} of the MSO sets are low index\")\n",
    "print(f\"{len(li_mtes)} of the MTES sets are low index\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take two MSO sets with different index properties and see how to choose redundant equations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed', 'mixed']\n",
      "['der', 'int', 'der', 'mixed', 'mixed', 'mixed', 'int', 'mixed']\n"
     ]
    }
   ],
   "source": [
    "mso1 = msos[0]\n",
    "mso2 = msos[1]\n",
    "print(model.MSOCausalitySweep(mso1))\n",
    "print(model.MSOCausalitySweep(mso2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here it is clear that in `mso1`, no choice of residual equation gives integral causality in the residual generator. However, for `mso2`, two equations are possible!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Residual generator design and code generation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, three residual generators will be designed corresponding to figures 2, 3, and 12 in the paper. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Residuals, code generation\n",
    "Residual 1 is based on the second MSO set, using equation e5 as a redundant equation, which will result in a sequential residual generator in derivative causality. The computational graph, Fig. 2 in the paper, is given by:\n",
    "\n",
    "<center><img src=\"../images/tt_r1.png\" alt=\"residual 1\" width=\"75%\"/></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating residual generator ResGen1 (C, batch)\n",
      "  Generating code for the exactly determined part: .......\n",
      "  Generating code for the residual equations\n",
      "  Writing residual generator file\n",
      "Files ResGen1.cc and ResGen1_setup.py generated\n",
      "Compile by running: python ResGen1_setup.py build_ext --inplace\n",
      "\n"
     ]
    }
   ],
   "source": [
    "eqr1 = mso2\n",
    "redeq1 = 4\n",
    "m01 = [e for e in eqr1 if e != redeq1]\n",
    "Gamma1 = model.Matching(m01)\n",
    "model.SeqResGen(Gamma1, redeq1, 'ResGen1', batch=True, language='C')\n",
    "print(\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Residual 2 is based on the same second MSO set but using equation e7 as a redundant equation, which will result in a sequential residual generator in integral causality. The computational graph, Fig. 3 in the paper, is given by:\n",
    "\n",
    "<center><img src=\"../images/tt_r2.png\" alt=\"residual 2\" width=\"75%\"/></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating residual generator ResGen2 (C, batch)\n",
      "  Generating code for the exactly determined part: ...\n",
      "  Generating code for the residual equations\n",
      "  Writing residual generator file\n",
      "Files ResGen2.cc and ResGen2_setup.py generated\n",
      "Compile by running: python ResGen2_setup.py build_ext --inplace\n",
      "\n"
     ]
    }
   ],
   "source": [
    "eqr2 = mso2\n",
    "redeq2 = 6\n",
    "m02 = [e for e in eqr2 if e != redeq2]\n",
    "Gamma2 = model.Matching(m02)\n",
    "model.SeqResGen(Gamma2, redeq2, 'ResGen2', batch=True, language='C')\n",
    "print(\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Residual 3 is based on the first MSO set using equation e2 as a redundant equation, which will result in a sequential residual generator in mixed causality. The computational graph, Fig. 12 in the paper, is given by:\n",
    "\n",
    "<center><img src=\"../images/tt_r3.png\" alt=\"residual 2\" width=\"75%\"/></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating residual generator ResGen3 (C, batch)\n",
      "  Generating code for the exactly determined part: ........\n",
      "  Generating code for the residual equations\n",
      "  Writing residual generator file\n",
      "Files ResGen3.cc and ResGen3_setup.py generated\n",
      "Compile by running: python ResGen3_setup.py build_ext --inplace\n",
      "\n"
     ]
    }
   ],
   "source": [
    "eqr3 = mso1\n",
    "redeq3 = 1\n",
    "m03 = [e for e in eqr3 if e != redeq3]\n",
    "Gamma3 = model.Matching(m03)\n",
    "model.SeqResGen(Gamma3, redeq3, 'ResGen3', batch=True, language='C')\n",
    "print(\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Residuals, compile generated code\n",
    "Now that the code is generated, compile and import the generated c-extension modules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling residual generator: ResGen1 ... Success!\n",
      "Compiling residual generator: ResGen2 ... Success!\n",
      "Compiling residual generator: ResGen3 ... Success!\n"
     ]
    }
   ],
   "source": [
    "for resName in ['ResGen1', 'ResGen2', 'ResGen3']:\n",
    "    print(f\"Compiling residual generator: {resName} ... \", end='')\n",
    "    compile_cmd = f\"python {resName}_setup.py build_ext --inplace > /dev/null\"\n",
    "    if os.system(compile_cmd) == 0:\n",
    "        print('Success!')\n",
    "    else:\n",
    "        print('Failure!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All residual generators imported/reloaded\n"
     ]
    }
   ],
   "source": [
    "import ResGen1\n",
    "import ResGen2\n",
    "import ResGen3\n",
    "print(\"All residual generators imported/reloaded\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Diagnosis properties of the three generated residuals\n",
    "Generate the fault signature matrix (FSM) and isolability properties of the three generated residual generators."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Isolability matrix')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(1, 2, num=50, clear=True, layout=\"constrained\")\n",
    "FSM = model.FSM([mso2, mso2, mso1])\n",
    "ax[0].spy(FSM, markersize=10, marker=\"o\")\n",
    "ax[0].set_yticks(range(3))\n",
    "ax[0].set_yticklabels([f\"r{k + 1}\" for k in range(3)])\n",
    "ax[0].set_xticks(range(6))\n",
    "ax[0].set_xticklabels(model.f)\n",
    "ax[0].set_title('Fault Signature Matrix')\n",
    "\n",
    "model.IsolabilityAnalysisFSM(FSM, ax=ax[1])\n",
    "ax[1].set_title('Isolability matrix')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulate\n",
    "\n",
    "Next step is to simulate the process with all faults. For this, we need a controller. Here, a simple LQR-controller is designed to follow a reference pressure in the first tank."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = TankSimulation.ThreeTank_ss(model_params)  # Get state-space matrices\n",
    "\n",
    "Q = np.eye(3)\n",
    "R = np.eye(1) * 0.5\n",
    "P = solve_continuous_are(G['A'], G['B'], Q, R)\n",
    "Lx = np.linalg.solve(R, G['B'].T @ P)\n",
    "Lr = -1 / (np.array([1, 0, 0]) @ np.linalg.inv(G['A'] - G['B'] @ Lx) @ G['B'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the reference signal and the controller function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ref(t):\n",
    "    return 0.2 * np.sin(2 * np.pi * 1 / 10 * t) + 1\n",
    "\n",
    "\n",
    "def controller(t, x):\n",
    "    return (-Lx @ x + Lr * ref(t))[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, simulate the fault-free behavior and all 6 fault modes. For each fault mode, a ramp-function is used as the fault signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = np.linspace(0, 20, 201)\n",
    "x0 = [0, 0, 0]\n",
    "sim = ({'NF': TankSimulation.SimScenario(0, lambda t: 0 * t, controller, model_params, t, x0)} |\n",
    "       {fi: TankSimulation.SimScenario(k + 1, lambda t: 0.3 * TankSimulation.ramp(t, 6, 10), controller, model_params, t, x0) for k, fi in enumerate(model.f)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot some data from the fault-free and the fV1 scenarios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(3, 2, num=40, clear=True, layout=\"constrained\")\n",
    "ax[0, 0].plot(sim['NF'].t, sim['NF'].w[0], 'b', label='p1')\n",
    "ax[0, 0].plot(sim['NF'].t, ref(sim['NF'].t), 'b--', label='p1ref')\n",
    "ax[0, 0].plot(sim['NF'].t, sim['NF'].w[1], 'r', label='p2')\n",
    "ax[0, 0].plot(sim['NF'].t, sim['NF'].w[2], 'g', label='p3')\n",
    "ax[0, 0].set_ylabel('Tank water pressure')\n",
    "ax[0, 0].set_title('Fault free simulation')\n",
    "sns.despine(ax=ax[0, 0])\n",
    "\n",
    "ax[1, 0].plot(sim['NF'].t, sim['NF'].w[3])\n",
    "ax[1, 0].set_ylabel('q0')\n",
    "sns.despine(ax=ax[1, 0])\n",
    "\n",
    "ax[2, 0].plot(sim['NF'].t, sim['NF'].f)\n",
    "ax[2, 0].set_ylabel('Fault signal')\n",
    "ax[2, 0].set_xlabel('t [s]')\n",
    "sns.despine(ax=ax[2, 0])\n",
    "\n",
    "ax[0, 1].plot(sim['fV1'].t, sim['fV1'].w[0], 'b', label='p1')\n",
    "ax[0, 1].plot(sim['fV1'].t, ref(sim['fV1'].t), 'b--', label='p1ref')\n",
    "ax[0, 1].plot(sim['fV1'].t, sim['fV1'].w[1], 'r', label='p2')\n",
    "ax[0, 1].plot(sim['fV1'].t, sim['fV1'].w[2], 'g', label='p3')\n",
    "ax[0, 1].set_ylabel('Tank water pressure')\n",
    "ax[0, 1].legend(loc='upper right', bbox_to_anchor=(1.5, 1.0))\n",
    "ax[0, 1].set_title('Fault scenario Fv1')\n",
    "sns.despine(ax=ax[0, 1])\n",
    "\n",
    "ax[1, 1].plot(sim['fV1'].t, sim['fV1'].w[3])\n",
    "ax[1, 1].set_ylabel('q0')\n",
    "sns.despine(ax=ax[1, 1])\n",
    "\n",
    "ax[2, 1].plot(sim['fV1'].t, sim['fV1'].f)\n",
    "ax[2, 1].set_ylabel('Fault signal')\n",
    "ax[2, 1].set_xlabel('t [s]')\n",
    "sns.despine(ax=ax[2, 1])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run residual generators on simulated data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the three residual generators on all generated data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = {}\n",
    "for fault_mode in ['NF'] + model.f:\n",
    "    Ts = sim[fault_mode].t[1] - sim[fault_mode].t[0]\n",
    "\n",
    "    state1 = {'p1': sim[fault_mode].w[0, 0], 'p2': sim[fault_mode].w[1, 0]}\n",
    "    state2 = {'p1': sim[fault_mode].w[0, 0], 'p2': sim[fault_mode].w[1, 0]}\n",
    "    state3 = {'p1': sim[fault_mode].w[0, 0], 'p2': sim[fault_mode].w[1, 0], 'p3': sim[fault_mode].w[2, 0]}\n",
    "    \n",
    "    r1 = ResGen1.ResGen1(sim[fault_mode].z, state1, model_params, Ts)\n",
    "    r2 = ResGen2.ResGen2(sim[fault_mode].z, state2, model_params, Ts)\n",
    "    r3 = ResGen3.ResGen3(sim[fault_mode].z, state3, model_params, Ts)\n",
    "    r1[0:2] = 0.0\n",
    "    r3[0] = 0.0\n",
    "    res[fault_mode] = np.row_stack((r1, r2, r3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and plot some results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'r3 (seq/mixed/discrete)')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot some results\n",
    "fig, ax = plt.subplots(3, 1, num=60, clear=True, layout=\"constrained\")\n",
    "for fault_mode in res:    \n",
    "    ax[0].plot(sim[fault_mode].t, res[fault_mode][0], label=fault_mode)\n",
    "    ax[1].plot(sim[fault_mode].t, res[fault_mode][1])\n",
    "    ax[2].plot(sim[fault_mode].t, res[fault_mode][2])\n",
    "sns.despine(ax=ax[0])\n",
    "ax[0].legend(bbox_to_anchor=(1.05, 1))\n",
    "ax[0].set_title('r1 (seq/derivative/discrete)')\n",
    "sns.despine(ax=ax[1])\n",
    "ax[1].set_title('r2 (seq/integral/discrete)')\n",
    "sns.despine(ax=ax[2])\n",
    "ax[2].set_title('r3 (seq/mixed/discrete)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here it is clear that the residual with numerical differentiation is unreliable and requres additional filtering."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fdt_312",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}