{ "cells": [ { "cell_type": "markdown", "id": "educated-affect", "metadata": {}, "source": [ "# V0.1.6 - System Identification Using Adaptative Filters\n", "\n", "Example created by Wilson Rocha Lacerda Junior" ] }, { "cell_type": "markdown", "id": "preliminary-announcement", "metadata": {}, "source": [ "## Generating 1 input 1 output sample data \n", "\n", "The data is generated by simulating the following model:\n", "\n", "$y_k = 0.2y_{k-1} + 0.1y_{k-1}x_{k-1} + 0.9x_{k-1} + e_{k}$\n", "\n", "If *colored_noise* is set to True:\n", "\n", "$e_{k} = 0.8\\nu_{k-1} + \\nu_{k}$\n", "\n", "where $x$ is a uniformly distributed random variable and $\\nu$ is a gaussian distributed variable with $\\mu=0$ and $\\sigma=0.1$\n", "\n", "In the next example we will generate a data with 1000 samples with white noise and selecting 90% of the data to train the model. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "pip install sysidentpy" ] }, { "cell_type": "code", "execution_count": 1, "id": "exact-trace", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from sysidentpy.polynomial_basis import PolynomialNarmax\n", "from sysidentpy.metrics import root_relative_squared_error\n", "from sysidentpy.utils.generate_data import get_miso_data, get_siso_data\n", "from sysidentpy.parameter_estimation import Estimators\n", "\n", "x_train, x_valid, y_train, y_valid = get_siso_data(n=1000,\n", " colored_noise=False,\n", " sigma=0.001,\n", " train_percentage=90)" ] }, { "cell_type": "markdown", "id": "convenient-encounter", "metadata": {}, "source": [ "One can create a model object and access the Adaptative Filters available in SysIdentPy individually. If you want to build a regressor matrix and estimate the parameters using only the Adaptative Filter method (not applying FROLS + ERR algorithm), follow the steps bellow." ] }, { "cell_type": "code", "execution_count": 3, "id": "binary-shame", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
0123456789
01.00.000000-0.488925-0.2426350.000000-0.000000-0.0000000.2390480.1186300.058872
11.0-0.2173850.969823-0.4889250.047256-0.2108250.1062850.940557-0.4741710.239048
21.0-0.503772-0.6284570.9698230.2537870.316599-0.4885700.394958-0.6094920.940557
31.00.8043580.308975-0.6284570.6469920.248526-0.5055050.095465-0.1941770.394958
41.0-0.379308-0.4429700.3089750.1438750.168022-0.1171970.196222-0.1368670.095465
\n", "
" ], "text/plain": [ " 0 1 2 3 4 5 6 7 \\\n", "0 1.0 0.000000 -0.488925 -0.242635 0.000000 -0.000000 -0.000000 0.239048 \n", "1 1.0 -0.217385 0.969823 -0.488925 0.047256 -0.210825 0.106285 0.940557 \n", "2 1.0 -0.503772 -0.628457 0.969823 0.253787 0.316599 -0.488570 0.394958 \n", "3 1.0 0.804358 0.308975 -0.628457 0.646992 0.248526 -0.505505 0.095465 \n", "4 1.0 -0.379308 -0.442970 0.308975 0.143875 0.168022 -0.117197 0.196222 \n", "\n", " 8 9 \n", "0 0.118630 0.058872 \n", "1 -0.474171 0.239048 \n", "2 -0.609492 0.940557 \n", "3 -0.194177 0.394958 \n", "4 -0.136867 0.095465 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = PolynomialNarmax()\n", "psi = model.build_information_matrix(x_train, y_train, xlag=2, ylag=1, non_degree=2) # creating the regressor matrix\n", "pd.DataFrame(psi).head()" ] }, { "cell_type": "code", "execution_count": 5, "id": "received-apparatus", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 0],\n", " [1001, 0],\n", " [2001, 0],\n", " [2002, 0],\n", " [1001, 1001],\n", " [2001, 1001],\n", " [2002, 1001],\n", " [2001, 2001],\n", " [2002, 2001],\n", " [2002, 2002]])" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[regressor_code, max_lag] = model.regressor_space(2, 2, 1, 1)\n", "regressor_code # the entire regressor space is our input in this case. But you can define specific subsets to use as an input" ] }, { "cell_type": "code", "execution_count": 6, "id": "growing-anniversary", "metadata": {}, "outputs": [], "source": [ "model.final_model = regressor_code # defines the model representation\n", "model.psi = psi" ] }, { "cell_type": "markdown", "id": "unable-culture", "metadata": {}, "source": [] }, { "cell_type": "markdown", "id": "electrical-crowd", "metadata": {}, "source": [ "Here we are using the Affine Least Mean Squares method, but you can use any of the methods available on SysIdentPy\n", "\n", "- Least Mean Squares (LMS)\n", "- Affine LMS\n", "- LMS Sign Error\n", "- Normalized LMS\n", "- Normalized LSM Sign Error\n", "- LSM Sign Regressor\n", "- Normalized LMS Sign Regressor\n", "- LMS Sign-Sign\n", "- Normalized LMS Sign-Sign\n", "- Normalized LMS Leaky\n", "- LMS Leaky\n", "- LMS Mixed Norm\n", "- LMS Fourth\n", "\n", "Also, you can use:\n", "- Least Squares (LS)\n", "- Total LS\n", "- Recursive LS" ] }, { "cell_type": "markdown", "id": "august-robertson", "metadata": {}, "source": [ "## Building the model" ] }, { "cell_type": "code", "execution_count": 7, "id": "ahead-element", "metadata": {}, "outputs": [], "source": [ "model.theta = Estimators(mu=0.01).affine_least_mean_squares(model.psi, y_train[1:, 0].reshape(-1, 1)) " ] }, { "cell_type": "markdown", "id": "realistic-alignment", "metadata": {}, "source": [ "## Simulating the model" ] }, { "cell_type": "code", "execution_count": 8, "id": "metric-layer", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0024097628318461625\n", " Regressors Parameters ERR\n", "0 1 -0.0000 0.00000000\n", "1 y(k-1) 0.1999 0.00000000\n", "2 x1(k-1) -0.0000 0.00000000\n", "3 x1(k-2) 0.8999 0.00000000\n", "4 y(k-1)^2 -0.0001 0.00000000\n", "5 x1(k-1)y(k-1) 0.1000 0.00000000\n", "6 x1(k-2)y(k-1) -0.0000 0.00000000\n", "7 x1(k-1)^2 0.0002 0.00000000\n", "8 x1(k-2)x1(k-1) -0.0000 0.00000000\n", "9 x1(k-2)^2 0.0000 0.00000000\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "yhat = model.predict(x_valid, y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "print(rrse)\n", "model.n_terms = 10 # the number of terms we selected (necessary in the 'results' methods)\n", "model.err = model.n_terms*[0] # just to use the `results` method\n", "results = pd.DataFrame(model.results(err_precision=8,\n", " dtype='dec'),\n", " columns=['Regressors', 'Parameters', 'ERR'])\n", "\n", "print(results)\n", "ee, ex, extras, lam = model.residuals(x_valid, y_valid, yhat)\n", "model.plot_result(y_valid, yhat, ee, ex)" ] }, { "cell_type": "markdown", "id": "derived-dakota", "metadata": {}, "source": [ "## Final code" ] }, { "cell_type": "code", "execution_count": null, "id": "union-mortality", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from sysidentpy.polynomial_basis import PolynomialNarmax\n", "from sysidentpy.metrics import root_relative_squared_error\n", "from sysidentpy.utils.generate_data import get_miso_data, get_siso_data\n", "from sysidentpy.parameter_estimation import Estimators\n", "\n", "x_train, x_valid, y_train, y_valid = get_siso_data(n=1000,\n", " colored_noise=False,\n", " sigma=0.001,\n", " train_percentage=90)\n", "\n", "model = PolynomialNarmax()\n", "psi = model.build_information_matrix(x_train, y_train, xlag=2, ylag=1, non_degree=2) # creating the regressor matrix\n", "[regressor_code, max_lag] = model.regressor_space(2, 2, 1, 1)\n", "regressor_code # the entire regressor space is our input in this case. But you can define specific subsets to use as an input\n", "model.final_model = regressor_code # defines the model representation\n", "model.psi = psi\n", "model.theta = Estimators(mu=0.01).affine_least_mean_squares(model.psi, y_train[1:, 0].reshape(-1, 1))\n", "yhat = model.predict(x_valid, y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "print(rrse)\n", "model.n_terms = 10 # the number of terms we selected (necessary in the 'results' methods)\n", "model.err = model.n_terms*[0] # just to use the `results` method\n", "results = pd.DataFrame(model.results(err_precision=8,\n", " dtype='dec'),\n", " columns=['Regressors', 'Parameters', 'ERR'])\n", "\n", "print(results)\n", "ee, ex, extras, lam = model.residuals(x_valid, y_valid, yhat)\n", "model.plot_result(y_valid, yhat, ee, ex)" ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:v0.1.4] *", "language": "python", "name": "conda-env-v0.1.4-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.6" } }, "nbformat": 4, "nbformat_minor": 5 }