From a9c74166f0a168eda83d7732f45b47c502de6ef9 Mon Sep 17 00:00:00 2001 From: GabrielBuenoLeandro Date: Thu, 21 Sep 2023 19:20:23 -0300 Subject: [PATCH 01/11] adding files for multiobjective parameter estimation. All the work were develop in my undergraduate research under the guidence of Samir Martins and Wilson Rocha --- examples/multiobjective.ipynb | 801 +++++ .../multiobjective_parameter_estimation.ipynb | 3013 +++++++++++++++++ sysidentpy/multiobjective/__init__.py | 5 + .../multiobjective_parameter_estimation.py | 282 ++ 4 files changed, 4101 insertions(+) create mode 100644 examples/multiobjective.ipynb create mode 100644 examples/multiobjective_parameter_estimation.ipynb create mode 100644 sysidentpy/multiobjective/__init__.py create mode 100644 sysidentpy/multiobjective/multiobjective_parameter_estimation.py diff --git a/examples/multiobjective.ipynb b/examples/multiobjective.ipynb new file mode 100644 index 00000000..8389d1fb --- /dev/null +++ b/examples/multiobjective.ipynb @@ -0,0 +1,801 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Multiobjective parameter estimation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Example: Buck converter\n", + "\n", + "Example created by Gabriel Bueno Leandro\n", + "\n", + "
A buck converter is a type of DC/DC converter that steps down the voltage from its input to its output while increasing the current. It is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors, such as a diode and a transistor, and at least one energy storage element, such as a capacitor or inductor. Modern buck converters often replace the diode with a second transistor for synchronous rectification. Buck converters are similar to boost converters, which step up the voltage from their input to their output.
\n", + "\n", + "## Reference \n", + "\n", + "**For further information, check this reference: https://doi.org/10.1080/00207170601185053**." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# Importing the libraries and methods needed to run the notebook.\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd \n", + "from sysidentpy.model_structure_selection import FROLS\n", + "from sysidentpy.multiobjective.multiobjective_parameter_estimation import IM\n", + "from sysidentpy.basis_function._basis_function import Polynomial\n", + "from sysidentpy.utils.display_results import results\n", + "from sysidentpy.utils.plotting import plot_results\n", + "from sysidentpy.metrics import root_relative_squared_error" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dynamic Behavior" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Reading Buck's input and output data\n", + "data_train = pd.read_csv(r'datasets/buck.txt' , sep=\" \", header=None).to_numpy()\n", + "data_valid = pd.read_csv(r'datasets/buck_val.txt' , sep =\" \", header=None).to_numpy()\n", + "\n", + "# Separating the identification data\n", + "data_samples_train = data_train[:, 2]\n", + "data_out_train = data_train[:, 6]\n", + "data_int_train = data_train[:, 4]\n", + "\n", + "# Separating the validation data\n", + "data_samples_valid = data_valid[:, 2]\n", + "data_out_valid = data_valid[:, 6]\n", + "data_int_valid = data_valid[:, 4]\n", + "\n", + "# Plotting the measured output (identification and validation data)\n", + "plt.figure(1)\n", + "plt.title('Output')\n", + "plt.plot(data_samples_train, data_out_train, label='Identification', linewidth=1.5)\n", + "plt.plot(data_samples_valid, data_out_valid , label='Validation', linewidth=1.5)\n", + "plt.xlabel('Samples')\n", + "plt.ylabel('y')\n", + "plt.legend()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting the measured input(identification and validation data)\n", + "plt.figure(2)\n", + "plt.title('Input')\n", + "plt.plot(data_samples_train, data_int_train, label='Identification', linewidth=1.5)\n", + "plt.plot(data_samples_valid, data_int_valid, label='Validation', linewidth=1.5)\n", + "plt.ylim(2.1, 2.6)\n", + "plt.ylabel('u')\n", + "plt.xlabel('Samples')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Buck Converter Static Function\n", + "\n", + "The duty cycle, represented by the symbol $D$, is defined as the ratio of the time the system is on ($T_{on}$​) to the total operation cycle time ($T$). Mathematically, this can be expressed as $D=\\frac{T_{on}}{T}$. The complement of the duty cycle, represented by $D'$, is defined as the ratio of the time the system is off ($T_{off}$) to the total operation cycle time ($T$) and can be expressed as $D'=\\frac{T_{off}}{T}$.\n", + "\n", + "The load voltage ($V_o$) is related to the source voltage ($V_d$) by the equation $V_o​=D⋅V_d​=(1−D’)⋅V_d$. For this particular converter, it is known that $D′=\\frac{\\bar{u}-1}{3}​$,​ which means that the static function of this system can be derived from theory to be:\n", + "\n", + "$$\n", + "V_o = \\frac{4V_d}{3} - \\frac{V_d}{3}\\cdot \\bar{u}\n", + "$$\n", + "\n", + "If we assume that the source voltage $V_d$​ is equal to 24 V, then we can rewrite the above expression as follows:\n", + "\n", + "$$\n", + "V_o = (4 - \\bar{u})\\cdot 8\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Static data\n", + "Vd = 24\n", + "Uo = np.linspace(0, 4, 50)\n", + "Yo = (4-Uo)*Vd/3\n", + "Uo = Uo.reshape(-1, 1)\n", + "Yo = Yo.reshape(-1, 1)\n", + "plt.figure(3)\n", + "plt.title('Buck Converter Static Function')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{y}$')\n", + "plt.plot(Uo, Yo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(3)\n", + "samples = np.arange(0, 5, 5/len(Uo))\n", + "plt.title('Static input buck converte')\n", + "plt.ylabel('$\\\\bar{u}$')\n", + "plt.xlabel('Samples')\n", + "plt.plot(samples, Uo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Buck converter static gain\n", + "\n", + "The gain of a Buck converter is a measure of how its output voltage changes in response to changes in its input voltage. Mathematically, the gain can be calculated as the derivative of the converter’s static function, which describes the relationship between its input and output voltages.\n", + "In this case, the static function of the Buck converter is given by the equation:\n", + "\n", + "$$\n", + "V_o = (4 - \\bar{u})\\cdot 8\n", + "$$\n", + "\n", + "Taking the derivative of this equation with respect to $\\hat{u}$, we find that the gain of the Buck converter is equal to −8. In other words, for every unit increase in the input voltage $\\hat{u}$, the output voltage Vo​ will decrease by 8 units." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Defining the gain\n", + "gain = -8*np.ones(len(Uo)).reshape(-1, 1)\n", + "plt.figure(3)\n", + "plt.title('Gain of the Static Converter')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{gain}$')\n", + "plt.plot(Uo, gain, linewidth=1.5, label='gain', linestyle='-', marker='o')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Information about the static function and static gain of a system, along with its usual input/output data, can be used as sources of affine information to estimate the parameters of a mathematical model. In this context, a composite cost function is often used to measure the accuracy of the estimated model parameters. This cost function is typically defined as a weighted sum of several individual cost functions, each representing a different aspect of the model’s performance.\n", + "\n", + "In this case, the composite cost function is given by the equation:\n", + "\n", + "$$\n", + "\\gamma(\\hat\\theta) = w_1\\cdot J_{LS}(\\hat{\\theta})+w_2\\cdot J_{SF}(\\hat{\\theta})+w_3\\cdot J_{SG}(\\hat{\\theta})\n", + "$$\n", + "\n", + "where $\\hat{\\theta}$ represents the estimated model parameters, $w_1$​, $w_2$​, and $w_3$ are weighting factors, and $J_{LS}$​, $J_{SF}$​, and $J_{SG}$ are individual cost functions representing the least squares, static function, and static gain aspects of the model’s performance, respectively.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\55359\\OneDrive\\Área de Trabalho\\Clone_git\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", + " You'll have to use FROLS(estimator=LeastSquares()) instead. \n", + " The only change is that you'll have to define the estimator first instead of passing a string like 'least_squares'. \n", + " This change will make easier to implement new estimators and it'll improve code readability.\n", + " warnings.warn(message, FutureWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Informing test and validation data\n", + "x_train = data_int_train.reshape(-1, 1)\n", + "y_train = data_out_train.reshape(-1, 1)\n", + "x_valid = data_int_valid.reshape(-1, 1)\n", + "y_valid = data_out_valid.reshape(-1, 1)\n", + "\n", + "basis_function = Polynomial(degree=2)\n", + "\n", + "model = FROLS(\n", + " order_selection=True,\n", + " n_info_values=8,\n", + " extended_least_squares=False,\n", + " ylag=2, xlag=2,\n", + " info_criteria='aic',\n", + " estimator='least_squares',\n", + " basis_function=basis_function\n", + ")\n", + "\n", + "model.fit(X=x_train, y=y_train)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "with the parameters all in hand, we can already calculate the parameters in a multiobjective way:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", + "mult = IM(model_type=model.model_type,\n", + " final_model = model.final_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The method will now be called to perform several calculations related to the performance of the objectives. These calculations include the computation of the performance matrix (J), the weights matrix (w), the Euclidean norm (E), and the values of $\\theta$ for each weight. Additionally, the method will also calculate the product of matrix H and matrix R, as well as the product of matrix Q and matrix R." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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w1w2w3J_lsJ_sgJ_sf||J||:
00.9900800.0030780.0068420.9925849.825995e-020.3054920.261455
10.9900800.0023470.0075730.9919901.551666e-010.2665910.286111
20.9900800.0015380.0083820.9908853.048969e-010.2208060.382836
30.9900800.0006420.0092770.9882481.000000e+000.1428081.000000
40.8944950.0986630.0068420.9951001.364999e-030.6604850.244160
........................
22900.0068420.3335270.6596320.9999765.944270e-080.0000200.245246
22910.0068420.2630390.7301190.9999856.124624e-080.0000180.245248
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22940.0068420.0030780.9900800.9999711.094929e-050.0000130.245244
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2295 rows × 7 columns

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" + ], + "text/plain": [ + " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", + "0 0.990080 0.003078 0.006842 0.992584 9.825995e-02 0.305492 0.261455\n", + "1 0.990080 0.002347 0.007573 0.991990 1.551666e-01 0.266591 0.286111\n", + "2 0.990080 0.001538 0.008382 0.990885 3.048969e-01 0.220806 0.382836\n", + "3 0.990080 0.000642 0.009277 0.988248 1.000000e+00 0.142808 1.000000\n", + "4 0.894495 0.098663 0.006842 0.995100 1.364999e-03 0.660485 0.244160\n", + "... ... ... ... ... ... ... ...\n", + "2290 0.006842 0.333527 0.659632 0.999976 5.944270e-08 0.000020 0.245246\n", + "2291 0.006842 0.263039 0.730119 0.999985 6.124624e-08 0.000018 0.245248\n", + "2292 0.006842 0.185020 0.808139 0.999993 6.466930e-08 0.000016 0.245250\n", + "2293 0.006842 0.098663 0.894495 1.000000 7.400899e-08 0.000015 0.245252\n", + "2294 0.006842 0.003078 0.990080 0.999971 1.094929e-05 0.000013 0.245244\n", + "\n", + "[2295 rows x 7 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Method to calculate the parameters\n", + "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(y_train=y_train[2:],\n", + " gain=gain,y_static=Yo,\n", + " x_static=Uo, psi=model.psi)\n", + "result = {'w1': w[0,:],\n", + " 'w2': w[2,:],\n", + " 'w3': w[1,:],\n", + " 'J_ls': J[0,:],\n", + " 'J_sg': J[1,:],\n", + " 'J_sf': J[2,:],\n", + " '||J||:': E}\n", + "pd.DataFrame(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "at this point, we can select a value for $\\theta$ that corresponds to the weights in our model. This value of $\\theta$ will determine the relative importance of each objective in the performance matrix, and will affect the overall performance of the model." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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RegressorsParametersERR
0y(k-1)2.9687E-019.999E-01
1y(k-2)6.4693E-012.042E-05
2x1(k-1)y(k-1)4.0624E-031.108E-06
311.5405E+004.688E-06
4y(k-1)^22.7671E-013.922E-07
5x1(k-1)-4.1302E-018.389E-07
6y(k-2)y(k-1)-5.3474E-015.690E-07
7y(k-2)^22.5832E-013.827E-06
\n", + "
" + ], + "text/plain": [ + " Regressors Parameters ERR\n", + "0 y(k-1) 2.9687E-01 9.999E-01\n", + "1 y(k-2) 6.4693E-01 2.042E-05\n", + "2 x1(k-1)y(k-1) 4.0624E-03 1.108E-06\n", + "3 1 1.5405E+00 4.688E-06\n", + "4 y(k-1)^2 2.7671E-01 3.922E-07\n", + "5 x1(k-1) -4.1302E-01 8.389E-07\n", + "6 y(k-2)y(k-1) -5.3474E-01 5.690E-07\n", + "7 y(k-2)^2 2.5832E-01 3.827E-06" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Writing the results\n", + "model.theta = Theta[position, :].reshape(-1,1)\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model, model.theta, model.err,\n", + " model.n_terms, err_precision=3, dtype='sci'\n", + " ),\n", + " columns=['Regressors', 'Parameters', 'ERR'])\n", + "r" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "dynamic data in graphical form:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_results(y=y_valid, yhat=yhat, n=1000)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The static gain of a system can be represented graphically to provide a visual representation of how the system’s output changes in response to changes in its input. This graphical representation can be useful for understanding the behavior of the system and for designing control strategies.\n", + "\n", + "To create a graphical representation of the static gain, the input variable is typically plotted on the horizontal axis, while the corresponding changes in the output variable are plotted on the vertical axis. The resulting graph shows how the output variable changes as the input variable is varied, providing a visual representation of the system’s static gain." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(4)\n", + "plt.title('Gain')\n", + "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", + "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{g}$')\n", + "plt.ylim(-10, -6)\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The static function of a system can be represented graphically to provide a visual representation of the relationship between the system’s input and output. This graphical representation can be useful for understanding the behavior of the system and for designing control strategies.\n", + "\n", + "To create a graphical representation of the static function, the input variable is typically plotted on the horizontal axis, while the corresponding output variable is plotted on the vertical axis. The resulting graph shows how the output variable changes as the input variable is varied, providing a visual representation of the system’s static function." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(5)\n", + "plt.title('Static Curve')\n", + "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", + "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{y}$')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A Pareto-optimal curve, also known as a Pareto frontier, is a graphical representation of the trade-offs between multiple objectives in a multi-objective optimization problem. The curve shows the set of solutions that are considered optimal, in the sense that no other solution can improve one objective without worsening at least one other objective.\n", + "\n", + "To create a Pareto-optimal curve, the values of the different objectives are typically plotted on different axes, with each point on the curve representing a solution that is optimal with respect to the trade-offs between the objectives. The shape of the curve can provide insight into the nature of the trade-offs between the objectives and can help decision-makers to identify solutions that best meet their needs and preferences." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(6)\n", + "ax = plt.axes(projection='3d')\n", + "ax.plot3D( J[0,:], J[1,:], J[2,:], 'o', linewidth=0.1)\n", + "ax.set_title('Optimum pareto-curve', fontsize=15)\n", + "ax.set_xlabel('$J_{ls}$', fontsize=10)\n", + "ax.set_ylabel('$J_{sg}$', fontsize=10)\n", + "ax.set_zlabel('$J_{sf}$', fontsize=10)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "meu_env", + "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": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/multiobjective_parameter_estimation.ipynb b/examples/multiobjective_parameter_estimation.ipynb new file mode 100644 index 00000000..62e491d3 --- /dev/null +++ b/examples/multiobjective_parameter_estimation.ipynb @@ -0,0 +1,3013 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Example: Buck converter\n", + "\n", + "Example created by Gabriel Bueno Leandro\n", + "\n", + "
A buck converter is a type of DC/DC converter that decreases the voltage (while increasing the current) from its input (power supply) to its output (load). It is similar to a boost converter (elevator) and is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors (a diode and a transistor, although modern buck converters replace the diode with a second transistor used for synchronous rectification) and at least one energy storage element, a capacitor, inductor or both combined.
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Reference \n", + "\n", + "**For further information, check this reference: https://doi.org/10.1080/00207170601185053**.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:23.655307700Z", + "start_time": "2023-07-11T17:36:22.803948400Z" + } + }, + "outputs": [], + "source": [ + "# Importing the libraries and methods needed to run the notebook.\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd \n", + "from sysidentpy.model_structure_selection import FROLS\n", + "from sysidentpy.multiobjective.multiobjective_parameter_estimation import IM\n", + "from sysidentpy.basis_function._basis_function import Polynomial\n", + "from sysidentpy.utils.display_results import results\n", + "from sysidentpy.utils.plotting import plot_results\n", + "from sysidentpy.metrics import root_relative_squared_error" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dynamic Behavior" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:23.786668800Z", + "start_time": "2023-07-11T17:36:23.657311200Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Reading Buck's input and output data\n", + "data_train = pd.read_csv(r'datasets/buck.txt' , sep=\" \", header=None).to_numpy()\n", + "data_valid = pd.read_csv(r'datasets/buck_val.txt' , sep =\" \", header=None).to_numpy()\n", + "\n", + "# Separating the identification data with decimation\n", + "data_samples_train = data_train[::12, 2]\n", + "data_out_train = data_train[:, 6]\n", + "data_int_train = data_train[:, 4]\n", + "\n", + "# Separating the validation data with decimation\n", + "data_samples_valid = data_valid[::12, 2]\n", + "data_out_valid = data_valid[:, 6]\n", + "data_int_valid = data_valid[:, 4]\n", + "\n", + "# Plotting the measured output (identification and validation data)\n", + "plt.figure(1)\n", + "plt.title('Output')\n", + "plt.plot(np.arange(0,data_out_train.shape[0]), data_out_train, label='Identification', linewidth=1.5)\n", + "plt.plot(np.arange(data_out_train.shape[0], data_out_train.shape[0] + data_out_valid.shape[0]), data_out_valid , label='Validation', linewidth=1.5)\n", + "plt.xlabel('Samples')\n", + "plt.ylabel('Voltage')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:23.899524600Z", + "start_time": "2023-07-11T17:36:23.787667800Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting the measured input(identification and validation data)\n", + "plt.figure(2)\n", + "plt.title('Input')\n", + "plt.plot(np.arange(0,data_out_train.shape[0]), data_int_train, label='Identification', linewidth=1.5)\n", + "plt.plot(np.arange(data_out_train.shape[0], data_out_train.shape[0] + data_out_valid.shape[0]), data_int_valid, label='Validation', linewidth=1.5)\n", + "plt.ylim(2.1, 2.6)\n", + "plt.ylabel('u')\n", + "plt.xlabel('Samples')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Buck Converter Static Function\n", + "\n", + "The duty cycle is defined by $D=\\frac{T_{on}}{T}$ and its complement is $D'=\\frac{T_{off}}{T}$ , where T is the operation cycle. The load voltage $V_o$ relates to the source voltage $V_d$ as $V_o = D\\cdot V_d = (1 − D’)\\cdot V_d$. This converter satisfies $D' = \\frac{\\bar{u}-1}{3}$ and therefore the static function of this system is known from theory to be:\n", + "$$\n", + "V_o = \\frac{4V_d}{3} - \\frac{V_d}{3}\\cdot \\bar{u}\n", + "$$\n", + "\n", + "assuming $V_d = 24\\:V $, the expression can be rewritten as follows:\n", + "\n", + "$$\n", + "V_o = (4 - \\bar{u})\\cdot 8\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.099777400Z", + "start_time": "2023-07-11T17:36:23.919547400Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Static data\n", + "Vd = 24\n", + "Uo = np.linspace(0, 4, 50)\n", + "Yo = (4-Uo)*Vd/3\n", + "Uo = Uo.reshape(-1, 1)\n", + "Yo = Yo.reshape(-1, 1)\n", + "plt.figure(3)\n", + "plt.title('Buck Converter Static Curve')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{y}$')\n", + "plt.plot(Uo, Yo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Buck converter Static Gain\n", + "\n", + "The gain of the Buck converter can be described as the derivative of the static function, which is described by:\n", + "\n", + "$$\n", + "V_o = (4 - \\bar{u})\\cdot 8\n", + "$$\n", + "\n", + "so $gain=V_o'=-8$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.264197200Z", + "start_time": "2023-07-11T17:36:24.101783Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Defining the gain\n", + "gain = -8*np.ones(len(Uo)).reshape(-1, 1)\n", + "plt.figure(3)\n", + "plt.title('Buck Converter Static Gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{gain}$')\n", + "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Defining the gain\n", + "gain = -8*np.ones(len(Uo)).reshape(-1, 1)\n", + "plt.figure(3)\n", + "plt.title('Buck Converter Static Gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{gain}$')\n", + "plt.plot(Uo, Uo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Information about static function and static gain, together with the usual input/output data, have been used as sources of affine information to estimate the parameters of the model. The composite cost function is:\n", + "\n", + "$$\n", + "\\gamma(\\hat\\theta) = w_1\\cdot J_{LS}(\\hat{\\theta})+w_2\\cdot J_{SF}(\\hat{\\theta})+w_3\\cdot J_{SG}(\\hat{\\theta})\n", + "$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.328953300Z", + "start_time": "2023-07-11T17:36:24.264197200Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\55359\\OneDrive\\Área de Trabalho\\Clone_git\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", + " You'll have to use FROLS(estimator=LeastSquares()) instead. \n", + " The only change is that you'll have to define the estimator first instead of passing a string like 'least_squares'. \n", + " This change will make easier to implement new estimators and it'll improve code readability.\n", + " warnings.warn(message, FutureWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Informing test and validation data\n", + "x_train = data_int_train.reshape(-1, 1)\n", + "y_train = data_out_train.reshape(-1, 1)\n", + "x_valid = data_int_valid.reshape(-1, 1)\n", + "y_valid = data_out_valid.reshape(-1, 1)\n", + "\n", + "basis_function = Polynomial(degree=2)\n", + "\n", + "model = FROLS(\n", + " order_selection=True,\n", + " n_info_values=8,\n", + " extended_least_squares=False,\n", + " ylag=2, xlag=2,\n", + " info_criteria='aic',\n", + " estimator='least_squares',\n", + " basis_function=basis_function\n", + ")\n", + "\n", + "model.fit(X=x_train, y=y_train)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The next step will be to determine the weights of the objectives of interest:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.328953300Z", + "start_time": "2023-07-11T17:36:24.294748700Z" + } + }, + "outputs": [], + "source": [ + "# Matrix with the weights associated to each objective.\n", + "W = np.array([[0.98, 0.7, 0.5, 0.35, 0.25, 0.01, 0.15, 0.01],\n", + " [0.01, 0.1, 0.3, 0.15, 0.25, 0.98, 0.35, 0.01],\n", + " [0.01, 0.2, 0.2, 0.50, 0.50, 0.01, 0.50, 0.98]])" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "with the parameters all in hand, we can already calculate the parameters in a multiobjective way:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.328953300Z", + "start_time": "2023-07-11T17:36:24.297851300Z" + } + }, + "outputs": [], + "source": [ + "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", + "mult = IM(model_type=model.model_type,\n", + " final_model = model.final_model)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "now the method will be called to calculate the matrix of the performance of the objectives (J), weights (w), the Euclidean norm (E), the thetas referring to each weight (Theta), matrix H multiplied by R and the matrix Q multiplied by R.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.435488200Z", + "start_time": "2023-07-11T17:36:24.301867Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", + "0 0.990080 0.003078 0.006842 0.992584 9.825995e-02 0.305492 0.261455\n", + "1 0.990080 0.002347 0.007573 0.991990 1.551666e-01 0.266591 0.286111\n", + "2 0.990080 0.001538 0.008382 0.990885 3.048969e-01 0.220806 0.382836\n", + "3 0.990080 0.000642 0.009277 0.988248 1.000000e+00 0.142808 1.000000\n", + "4 0.894495 0.098663 0.006842 0.995100 1.364999e-03 0.660485 0.244160\n", + "... ... ... ... ... ... ... ...\n", + "2290 0.006842 0.333527 0.659632 0.999976 5.944270e-08 0.000020 0.245246\n", + "2291 0.006842 0.263039 0.730119 0.999985 6.124624e-08 0.000018 0.245248\n", + "2292 0.006842 0.185020 0.808139 0.999993 6.466930e-08 0.000016 0.245250\n", + "2293 0.006842 0.098663 0.894495 1.000000 7.400899e-08 0.000015 0.245252\n", + "2294 0.006842 0.003078 0.990080 0.999971 1.094929e-05 0.000013 0.245244\n", + "\n", + "[2295 rows x 7 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Method to calculate the parameters\n", + "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(y_train=y_train[2:],\n", + " gain=gain,y_static=Yo,\n", + " x_static=Uo, psi=model.psi)\n", + "result = {'w1': w[0,:],\n", + " 'w2': w[2,:],\n", + " 'w3': w[1,:],\n", + " 'J_ls': J[0,:],\n", + " 'J_sg': J[1,:],\n", + " 'J_sf': J[2,:],\n", + " '||J||:': E}\n", + "pd.DataFrame(result)\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "now we can choose a theta value referring to the weights:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.522223600Z", + "start_time": "2023-07-11T17:36:24.435488200Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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RegressorsParametersERR
0y(k-1)2.3307E-019.999E-01
1y(k-2)6.3209E-012.042E-05
2x1(k-1)y(k-1)1.6667E-021.108E-06
312.2930E+004.688E-06
4y(k-1)^22.7673E-013.922E-07
5x1(k-1)-5.9333E-018.389E-07
6y(k-2)y(k-1)-5.3228E-015.690E-07
7y(k-2)^22.5766E-013.827E-06
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" + ], + "text/plain": [ + " Regressors Parameters ERR\n", + "0 y(k-1) 2.3307E-01 9.999E-01\n", + "1 y(k-2) 6.3209E-01 2.042E-05\n", + "2 x1(k-1)y(k-1) 1.6667E-02 1.108E-06\n", + "3 1 2.2930E+00 4.688E-06\n", + "4 y(k-1)^2 2.7673E-01 3.922E-07\n", + "5 x1(k-1) -5.9333E-01 8.389E-07\n", + "6 y(k-2)y(k-1) -5.3228E-01 5.690E-07\n", + "7 y(k-2)^2 2.5766E-01 3.827E-06" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Writing the results\n", + "model.theta = Theta[0, :].reshape(-1,1)\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model, model.theta, model.err,\n", + " model.n_terms, err_precision=3, dtype='sci'\n", + " ),\n", + " columns=['Regressors', 'Parameters', 'ERR'])\n", + "r" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plotting dynamic data:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.667179100Z", + "start_time": "2023-07-11T17:36:24.475149700Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_results(y=y_valid, yhat=yhat, n=1000)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the static gain graphically:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.793210700Z", + "start_time": "2023-07-11T17:36:24.688253500Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(4)\n", + "plt.title('Gain')\n", + "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", + "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{g}$')\n", + "plt.ylim(-16,0)\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the static function graphically:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:24.902396Z", + "start_time": "2023-07-11T17:36:24.793210700Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(5)\n", + "plt.title('Static Curve')\n", + "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", + "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.xlabel('$\\\\bar{y}$')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "pareto-optimal curve:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.014411600Z", + "start_time": "2023-07-11T17:36:24.914906300Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(6)\n", + "ax = plt.axes(projection='3d')\n", + "ax.plot3D( J[0,:], J[1,:], J[2,:], 'o', linewidth=0.1)\n", + "ax.set_title('Optimum pareto-curve', fontsize=15)\n", + "ax.set_xlabel('$J_{ls}$', fontsize=10)\n", + "ax.set_ylabel('$J_{sg}$', fontsize=10)\n", + "ax.set_zlabel('$J_{sf}$', fontsize=10)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The found NARX polynomial model was:\n", + "\n", + "$$\n", + "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 u(k-1) y(k-1) + \\theta_4 + \\theta_5 y(k-1)^2 + \\theta_6 u(k-1) + \\theta_7 y(k-2)y(k-1) + \\theta_8 y(k-2)^2\n", + "$$\n", + "\n", + "the goal is to estimate the vector $\\hat{\\theta}$, parting from:\n", + "\n", + "$$\n", + "\\theta = [w_1\\Psi^T\\Psi + w_2(HR)^T(HR) + w_3(QR)(QR)^T]^{-1} [w_1\\Psi^T y + w_2(HR)^T\\overline{g}+w_3(QR)^T\\overline{y}]\n", + "$$\n", + "\n", + "the $\\Psi$ matrix is provided by SysIdentPy. However, it is still necessary to find the Q, H and R matrices. To do this, $q_i^T$ is first estimated:\n", + "\n", + "$$\n", + "q_i^T = \n", + "\\begin{bmatrix}\n", + "1 & \\overline{y_i} & \\overline{u_1} & \\overline{y_i}^2 & \\cdots & \\overline{y_i}^l & F_{yu} & \\overline{u_i}^2 & \\cdots & \\overline{u_i}^l\n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "where $F_{yu}$ stands for all non-linear monomials inthe model that involve $y(k)$ and $u(k)$, $l$ is the largestnon-linearity in the model and need not be the samefor input and output terms. For a model with a degree of nonlinearity equal to 2, matrix-wise the following is obtained:\n", + "\n", + "\n", + "$$\n", + "q_i^T = \n", + "\\begin{bmatrix}\n", + "1 & \\overline{y_i} & \\overline{u_i} & \\overline{y_i}^2 & \\overline{u_i}\\:\\overline{y_i} & \\overline{u_i}^2 \n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "here, it is possible to encode the $q_i^T$ matrix so that it is in compliance with SysIdentPy. To do this, 0 is considered as a constant, $y_i$ equal to 1 and $u_i$ equal to 2. The number of columns indicates the degree of nonlinearity of the system and the number of rows reflects the number of terms in the mode:\n", + "\n", + "\n", + "$$\n", + "q_i = \n", + "\\begin{bmatrix}\n", + "0 & 0\\\\\n", + "1 & 0\\\\\n", + "2 & 0\\\\\n", + "1 & 1\\\\\n", + "2 & 1\\\\\n", + "2 & 2\\\\\n", + "\\end{bmatrix}\n", + "= \n", + "\\begin{bmatrix}\n", + "1 \\\\\n", + "\\overline{y_i}\\\\\n", + "\\overline{u_i}\\\\\n", + "\\overline{y_i}^2\\\\\n", + "\\overline{u_i}\\:\\overline{y_i}\\\\\n", + "\\overline{u_i}^2\\\\\n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "the result can be easily obtained using the ‘regressor_space’ method of SysIdentPy:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.017591800Z", + "start_time": "2023-07-11T17:36:25.013411900Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R = [[0 0]\n", + " [1 0]\n", + " [2 0]\n", + " [1 1]\n", + " [2 1]\n", + " [2 2]]\n" + ] + } + ], + "source": [ + "from sysidentpy.narmax_base import RegressorDictionary # Importing the class.\n", + "object_qit = RegressorDictionary(xlag=[1], ylag=[1]) # The lag of the input and output equal to 1 ensures that there will be no repetition of terms in qit.\n", + "R_example = object_qit.regressor_space(n_inputs=1)//1000 \n", + "print(f'R = {R_example}')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "such that:\n", + "\n", + "$$\n", + "\\overline{y_i} = q_i^T R\\theta\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "\\overline{g_i} = H R\\theta\n", + "$$\n", + "\n", + "the $R$ matrix is the linear mapping of the static regressors represented by $q_i^T$. In addition, the $H$ matrix contains affine information regarding $\\overline{g_i}$, which is equal to $\\overline{g_i} = \\frac{d\\overline{y}}{d\\overline{u}}{\\big |}_{(\\overline{u_i}\\:\\overline{y_i})}$. From now on, we will begin to apply the estimation of parameters in a multi-objective manner. This will be done with the NARX polynomial model of the BUCK converter in mind. In this context, $q_i^T$ will cease to be generic and will assume a specific format for the problem at hand. For this task, the $R_qit$ method will be used, whose objective is to return the $q_i^T$ related to the model and the matrix of the linear mapping $R$:" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.021969800Z", + "start_time": "2023-07-11T17:36:25.017591800Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R matrix:\n", + "[[0. 0. 0. 1. 0. 0. 0. 0.]\n", + " [1. 1. 0. 0. 0. 0. 0. 0.]\n", + " [0. 0. 0. 0. 0. 1. 0. 0.]\n", + " [0. 0. 0. 0. 1. 0. 1. 1.]\n", + " [0. 0. 1. 0. 0. 0. 0. 0.]]\n", + "qit matrix:\n", + "[[0. 0.]\n", + " [1. 0.]\n", + " [0. 1.]\n", + " [2. 0.]\n", + " [1. 1.]]\n" + ] + } + ], + "source": [ + "R, qit = mult.R_qit()\n", + "print('R matrix:')\n", + "print(R)\n", + "print('qit matrix:')\n", + "print(qit)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "immediately:" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\n", + "q_i = \n", + "\\begin{bmatrix}\n", + "0 & 0\\\\\n", + "1 & 0\\\\\n", + "2 & 0\\\\\n", + "1 & 1\\\\\n", + "2 & 1\\\\ \n", + "\\end{bmatrix}\n", + "=\n", + "\\begin{bmatrix}\n", + "1\\\\\n", + "\\overline{y}\\\\\n", + "\\overline{u}\\\\\n", + "\\overline{y^2}\\\\\n", + "\\overline{u}\\:\\overline{y}\\\\ \n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "upon returning to the model, it is possible to observe that the method produces outputs consistent with what is expected:\n", + "\n", + "$$\n", + "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 u(k-1) y(k-1) + \\theta_4 + \\theta_5 y(k-1)^2 + \\theta_6 u(k-1) + \\theta_7 y(k-2)y(k-1) + \\theta_8 y(k-2)^2\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "and:\n", + "\n", + "$$ \n", + "R = \n", + "\\begin{bmatrix}\n", + "term/\\theta & \\theta_1 & \\theta_2 & \\theta_3 & \\theta_4 & \\theta_5 & \\theta_6 & \\theta_7 & \\theta_8\\\\\n", + "1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0\\\\\n", + "\\overline{y} & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\overline{u} & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n", + "\\overline{y^2} & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 1\\\\\n", + "\\overline{y}\\:\\overline{u} & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\end{bmatrix}\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Validation\n", + "\n", + "Model's structure that will be utilized:\n", + "\n", + "$$\n", + "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 + \\theta_4 u(k-1) + \\theta_5 u(k-1)^2 + \\theta_6 u(k-2)u(k-1)+\\theta_7 u(k-2) + \\theta_8 u(k-2)^2\n", + "$$\n", + "\n", + "$\\therefore$\n", + "\n", + "$$\n", + "model\\_final = \n", + "\\begin{bmatrix}\n", + "1001 & 0\\\\\n", + "1002 & 0\\\\\n", + "0 & 0\\\\\n", + "2001 & 0\\\\\n", + "2001 & 2001\\\\\n", + "2002 & 2001\\\\\n", + "2002 & 0\\\\\n", + "2002 & 2002\n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "defining in code:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.026952500Z", + "start_time": "2023-07-11T17:36:25.023968Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1001, 0],\n", + " [1002, 0],\n", + " [ 0, 0],\n", + " [2001, 0],\n", + " [2001, 2001],\n", + " [2002, 2001],\n", + " [2002, 0],\n", + " [2002, 2002]])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_final = np.array([[1001, 0],\n", + " [1002, 0],\n", + " [0, 0],\n", + " [2001, 0],\n", + " [2001, 2001],\n", + " [2002, 2001],\n", + " [2002, 0],\n", + " [2002, 2002]])\n", + "model_final" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.031862500Z", + "start_time": "2023-07-11T17:36:25.027952500Z" + } + }, + "outputs": [], + "source": [ + "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", + "mult2 = IM(model_type='NARMAX',\n", + " final_model = model_final)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.101857500Z", + "start_time": "2023-07-11T17:36:25.034862400Z" + } + }, + "outputs": [], + "source": [ + "def psi(X, Y):\n", + " PSI = np.zeros((len(X), 8))\n", + " for k in range(2, len(Y)):\n", + " PSI[k, 0] = Y[k-1]\n", + " PSI[k, 1] = Y[k-2]\n", + " PSI[k, 2] = 1\n", + " PSI[k, 3] = X[k-1]\n", + " PSI[k, 4] = X[k-1]**2\n", + " PSI[k, 5] = X[k-2]*X[k-1]\n", + " PSI[k, 6] = X[k-2]\n", + " PSI[k, 7] = X[k-2]**2\n", + " return np.delete(PSI, [0, 1], axis=0)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the value of theta with the lowest mean squared error obtained through the routine in Scilab was:\n", + "\n", + "$$\n", + "W_{LS} = 0,3612343\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "W_{SG} = 0,3548699\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "W_{SF} = 0,3548699\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.101857500Z", + "start_time": "2023-07-11T17:36:25.038871100Z" + } + }, + "outputs": [], + "source": [ + "PSI = psi(x_train, y_train)\n", + "W = np.array([[0.3612343],[0.2838959],[0.3548699]])" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.122382900Z", + "start_time": "2023-07-11T17:36:25.053252Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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RegressorsParametersERR
0y(k-1)5.5147E-019.999E-01
1y(k-2)4.0449E-012.042E-05
211.4287E+001.108E-06
3x1(k-1)-1.2605E+014.688E-06
4x1(k-1)^28.3274E+003.922E-07
5x1(k-2)x1(k-1)-1.1416E+018.389E-07
6x1(k-2)1.2257E+015.690E-07
7x1(k-2)^23.0846E+003.827E-06
\n", + "
" + ], + "text/plain": [ + " Regressors Parameters ERR\n", + "0 y(k-1) 5.5147E-01 9.999E-01\n", + "1 y(k-2) 4.0449E-01 2.042E-05\n", + "2 1 1.4287E+00 1.108E-06\n", + "3 x1(k-1) -1.2605E+01 4.688E-06\n", + "4 x1(k-1)^2 8.3274E+00 3.922E-07\n", + "5 x1(k-2)x1(k-1) -1.1416E+01 8.389E-07\n", + "6 x1(k-2) 1.2257E+01 5.690E-07\n", + "7 x1(k-2)^2 3.0846E+00 3.827E-06" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Writing the results\n", + "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.final_model = model_final\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model, model.theta, model.err,\n", + " model.n_terms, err_precision=3, dtype='sci'\n", + " ),\n", + " columns=['Regressors', 'Parameters', 'ERR'])\n", + "r" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.276007600Z", + "start_time": "2023-07-11T17:36:25.115874700Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_results(y=y_valid, yhat=yhat, n=1000)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the static gain graphically:" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.383278600Z", + "start_time": "2023-07-11T17:36:25.238956900Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(7)\n", + "plt.title('Gain')\n", + "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", + "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{g}$')\n", + "plt.ylim(-16,0)\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the static function graphically:" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.471991600Z", + "start_time": "2023-07-11T17:36:25.383278600Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(8)\n", + "plt.title('Static Curve')\n", + "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", + "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.xlabel('$\\\\bar{y}$')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "pareto-optimal curve:" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.557244700Z", + "start_time": "2023-07-11T17:36:25.473992800Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(9)\n", + "ax = plt.axes(projection='3d')\n", + "ax.plot3D( J[0,:], J[1,:], J[2,:], 'o', linewidth=0.1)\n", + "ax.set_title('Optimum pareto-curve', fontsize=15)\n", + "ax.set_xlabel('$J_{ls}$', fontsize=10)\n", + "ax.set_ylabel('$J_{sg}$', fontsize=10)\n", + "ax.set_zlabel('$J_{sf}$', fontsize=10)\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "comparison between the norm of the objectives and specifying the \"best $\\theta$\" in relation to this approach:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.561257100Z", + "start_time": "2023-07-11T17:36:25.558245400Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.5514724 , 0.40449004, 1.42868214, -12.60549003,\n", + " 8.32739763, -11.41573513, 12.25729978, 3.08460885])" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Theta[position,:]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "here is an improved version of the text: 'The approach of the weight matrix was not the same as addressed in ‘IniciacaoCientifica2007’. However, the results were quite similar, with the exception of the constant term. Recapping, this routine provides me with:" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,5514724\\\\\n", + "\\theta_2 = 0,40449004,\\\\\n", + "\\theta_3 = 1,42868214\\\\\n", + "\\theta_4 = -12,60549003\\\\\n", + "\\theta_5 = 8,32739763\\\\\n", + "\\theta_6 = -11,41573513\\\\\n", + "\\theta_7 = 12,25729978\\\\\n", + "\\theta_8 = 3,08460885\\\\\n", + "\\end{matrix}\n", + "$$\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "and ‘IniciacaoCientifica2007’ provides:\n", + "\n", + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,549144\\\\\n", + "\\theta_2 = 0,408028\\\\\n", + "\\theta_3 = 1,45097\\\\\n", + "\\theta_4 = -12,557882\\\\\n", + "\\theta_5 = 8,1516315\\\\\n", + "\\theta_6 = -11,097284\\\\\n", + "\\theta_7 = 12,215782\\\\\n", + "\\theta_8 = 2,9319577\\\\\n", + "\\end{matrix}\n", + "$$\n", + "\n", + "whereas:\n", + "\n", + "$$\n", + "E_{Scilab} = 17,426613\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "E_{Python} = 17,474865\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.565769100Z", + "start_time": "2023-07-11T17:36:25.561257100Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R matrix:\n", + "[[0. 0. 1. 0. 0. 0. 0. 0.]\n", + " [1. 1. 0. 0. 0. 0. 0. 0.]\n", + " [0. 0. 0. 1. 0. 0. 1. 0.]\n", + " [0. 0. 0. 0. 1. 1. 0. 1.]]\n", + "qit matrix:\n", + "[[0. 0.]\n", + " [1. 0.]\n", + " [0. 1.]\n", + " [0. 2.]]\n" + ] + } + ], + "source": [ + "R, qit = mult2.R_qit()\n", + "print('R matrix:')\n", + "print(R)\n", + "print('qit matrix:')\n", + "print(qit)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "model's structure that will be utilized (‘IniciacaoCientifica2007’):\n", + "\n", + "$$\n", + "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 + \\theta_4 u(k-1) + \\theta_5 u(k-1)^2 + \\theta_6 u(k-2)u(k-1)+\\theta_7 u(k-2) + \\theta_8 u(k-2)^2\n", + "$$\n", + "\n", + "$$\n", + "q_i = \n", + "\\begin{bmatrix}\n", + "0 & 0\\\\\n", + "1 & 0\\\\\n", + "2 & 0\\\\\n", + "2 & 2\\\\ \n", + "\\end{bmatrix}\n", + "=\n", + "\\begin{bmatrix}\n", + "1\\\\\n", + "\\overline{y}\\\\\n", + "\\overline{u}\\\\\n", + "\\overline{u^2}\n", + "\\end{bmatrix}\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "and:\n", + "\n", + "$$ \n", + "R = \n", + "\\begin{bmatrix}\n", + "term/\\theta & \\theta_1 & \\theta_2 & \\theta_3 & \\theta_4 & \\theta_5 & \\theta_6 & \\theta_7 & \\theta_8\\\\\n", + "1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\overline{y} & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "\\overline{u} & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0\\\\\n", + "\\overline{u^2} & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 1\n", + "\\end{bmatrix}\n", + "$$\n", + "\n", + "consistent with matrix R:\n", + "\n", + "R = [0 0 1 0 0 0 0 0;1 1 0 0 0 0 0 0;0 0 0 1 0 0 1 0;0 0 0 0 1 1 0 1]; // R \n", + "\n", + "or:\n", + "\n", + "$$ \n", + "R = \n", + "\\begin{bmatrix}\n", + "0 & 0 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n", + "1 & 1 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n", + "0 & 0 & 0 & 1 & 0 & 0 & 1 & 0\\\\\n", + "0 & 0 & 0 & 0 & 1 & 1 & 0 & 1\n", + "\\end{bmatrix}\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Biobjective otimization of the model's parameters for prediction of output voltage of the Buck converter CC-CC using as objectives the static curve information and the prediction error " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.568942Z", + "start_time": "2023-07-11T17:36:25.566771800Z" + } + }, + "outputs": [], + "source": [ + "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", + "mult3 = IM(sg=False, sf=True, model_type='NARMAX',\n", + " final_model = model_final, norm=True)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the value of theta with the lowest mean squared error obtained through the routine in Scilab was:\n", + "\n", + "$$\n", + "W_{LS} = 0,9931126\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "W_{SF} = 0,0068874\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.660520200Z", + "start_time": "2023-07-11T17:36:25.571454900Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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w1w2J_lsJ_sg||J||:
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" + ], + "text/plain": [ + " w1 w2 J_ls J_sg ||J||:\n", + "0 0.990080 0.009920 0.990861 1.000000 0.990937\n", + "1 0.987127 0.012873 0.990862 0.987041 0.990936\n", + "2 0.984182 0.015818 0.990865 0.974317 0.990937\n", + "3 0.981247 0.018753 0.990867 0.961788 0.990938\n", + "4 0.978320 0.021680 0.990871 0.949519 0.990939\n", + "... ... ... ... ... ...\n", + "1995 0.002555 0.997445 0.999993 0.000071 0.999993\n", + "1996 0.002547 0.997453 0.999995 0.000071 0.999995\n", + "1997 0.002540 0.997460 0.999994 0.000071 0.999994\n", + "1998 0.002532 0.997468 0.999996 0.000071 0.999996\n", + "1999 0.002525 0.997475 1.000000 0.000070 1.000000\n", + "\n", + "[2000 rows x 5 columns]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "W = np.zeros((2, 2000))\n", + "W[0, :] = np.logspace(-0.01, -6, num=2000, base=2.71)\n", + "W[1, :] = np.ones(2000) - W[0, :]\n", + "J, w, E, Theta, HR, QR, position = mult3.affine_information_least_squares(y_train=y_train[2:],\n", + " y_static=Yo,\n", + " x_static=Uo, psi=PSI, W=W)\n", + "result = {'w1': w[0,:],\n", + " 'w2': w[1,:],\n", + " 'J_ls': J[0,:],\n", + " 'J_sg': J[1,:],\n", + " '||J||:': E}\n", + "pd.DataFrame(result)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.775500300Z", + "start_time": "2023-07-11T17:36:25.662525800Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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RegressorsParametersERR
0y(k-1)5.4941E-019.999E-01
1y(k-2)4.0804E-012.042E-05
211.3873E+001.108E-06
3x1(k-1)-1.2515E+014.688E-06
4x1(k-1)^28.1171E+003.922E-07
5x1(k-2)x1(k-1)-1.1047E+018.389E-07
6x1(k-2)1.2227E+015.690E-07
7x1(k-2)^22.9043E+003.827E-06
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" + ], + "text/plain": [ + " Regressors Parameters ERR\n", + "0 y(k-1) 5.4941E-01 9.999E-01\n", + "1 y(k-2) 4.0804E-01 2.042E-05\n", + "2 1 1.3873E+00 1.108E-06\n", + "3 x1(k-1) -1.2515E+01 4.688E-06\n", + "4 x1(k-1)^2 8.1171E+00 3.922E-07\n", + "5 x1(k-2)x1(k-1) -1.1047E+01 8.389E-07\n", + "6 x1(k-2) 1.2227E+01 5.690E-07\n", + "7 x1(k-2)^2 2.9043E+00 3.827E-06" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Writing the results\n", + "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.final_model = model_final\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model, model.theta, model.err,\n", + " model.n_terms, err_precision=3, dtype='sci'\n", + " ),\n", + " columns=['Regressors', 'Parameters', 'ERR'])\n", + "r" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.870151400Z", + "start_time": "2023-07-11T17:36:25.708903700Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_results(y=y_valid, yhat=yhat, n=1000)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:25.956170500Z", + "start_time": "2023-07-11T17:36:25.855611300Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(10)\n", + "plt.title('Static Curve')\n", + "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", + "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.xlabel('$\\\\bar{y}$')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.030539300Z", + "start_time": "2023-07-11T17:36:25.943142500Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(11)\n", + "plt.title('Costs Functions')\n", + "plt.plot(J[1,:], J[0,:], 'o')\n", + "plt.xlabel('Static Curve Information')\n", + "plt.ylabel('Prediction Error')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "being the selected $\\theta$:" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.034601700Z", + "start_time": "2023-07-11T17:36:26.030539300Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.54940884],\n", + " [ 0.40803995],\n", + " [ 1.38725622],\n", + " [-12.51466373],\n", + " [ 8.11712593],\n", + " [-11.04664177],\n", + " [ 12.22693929],\n", + " [ 2.90425532]])" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Theta[position, :].reshape(-1,1)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "or still:\n", + "\n", + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,54937794\\\\\n", + "\\theta_2 = 0,40809777\\\\\n", + "\\theta_3 = 1,38818561\\\\\n", + "\\theta_4 = -12,51509306\\\\\n", + "\\theta_5 = 8,11602829\\\\\n", + "\\theta_6 = -11,04448619\\\\\n", + "\\theta_7 = 12,22693625\\\\\n", + "\\theta_8 = 2,90315019\\\\\n", + "\\end{matrix}\n", + "$$\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "parameters found IniciacaoCientifica2007:\n", + " \n", + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,5494135\\\\\n", + "\\theta_2 = 0,4080312\\\\\n", + "\\theta_3 = 3,3857601\\\\\n", + "\\theta_4 = -12,513688\\\\\n", + "\\theta_5 = 8,116575\\\\\n", + "\\theta_6 = -11,04592\\\\\n", + "\\theta_7 = 12,227184\\\\\n", + "\\theta_8 = 2,9038468\\\\\n", + "\\end{matrix}\n", + "$$\n", + "\n", + "\n", + "whereas:\n", + "\n", + "$$\n", + "E_{Scilab} = 17,408934\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "E_{Python} = 17,408947\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Multiobjective otimization of the model's parameters for prediction of output voltage of the Buck converter CC-CC using as objectives the static curve information, the prediction error and the static gain " + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.038110800Z", + "start_time": "2023-07-11T17:36:26.035606500Z" + } + }, + "outputs": [], + "source": [ + "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", + "mult4 = IM(sf=False, sg=True, model_type='NARMAX',\n", + " final_model = model_final, \n", + " norm=False)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "the value of theta with the lowest mean squared error obtained through the routine in Scilab was:\n", + "\n", + "$$\n", + "W_{LS} = 0,9931126\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "W_{SF} = 0,0068874\n", + "$$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.121025300Z", + "start_time": "2023-07-11T17:36:26.038110800Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " w1 w2 J_ls J_sg ||J||:\n", + "0 1.000000 0.000000 17.407256 3.579839e+01 39.806245\n", + "1 0.997012 0.002988 17.407528 2.109245e-01 17.408806\n", + "2 0.994033 0.005967 17.407540 2.082048e-01 17.408785\n", + "3 0.991063 0.008937 17.407559 2.056622e-01 17.408774\n", + "4 0.988102 0.011898 17.407585 2.031813e-01 17.408771\n", + "... ... ... ... ... ...\n", + "1995 0.002555 0.997445 17.511595 3.443914e-07 17.511595\n", + "1996 0.002547 0.997453 17.511604 3.143891e-07 17.511604\n", + "1997 0.002540 0.997460 17.511607 3.515715e-07 17.511607\n", + "1998 0.002532 0.997468 17.511820 3.295491e-07 17.511820\n", + "1999 0.002525 0.997475 17.511609 3.080806e-07 17.511609\n", + "\n", + "[2000 rows x 5 columns]" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "W = np.zeros((2, 2000))\n", + "W[0, :] = np.logspace(0, -6, num=2000, base=2.71)\n", + "W[1, :] = np.ones(2000) - W[0, :]\n", + "# W = np.array([[0.9931126], \n", + " #[0.0068874]])\n", + "J, w, E, Theta, HR, QR, position = mult4.affine_information_least_squares(y_train=y_train[2:],\n", + " gain=gain,y_static=Yo,\n", + " x_static=Uo, psi=PSI, W=W)\n", + "result = {'w1': w[0,:],\n", + " 'w2': w[1,:],\n", + " 'J_ls': J[0,:],\n", + " 'J_sg': J[1,:],\n", + " '||J||:': E}\n", + "pd.DataFrame(result)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.234880200Z", + "start_time": "2023-07-11T17:36:26.123024200Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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RegressorsParametersERR
0y(k-1)5.4940E-019.999E-01
1y(k-2)4.0806E-012.042E-05
211.4853E+001.108E-06
3x1(k-1)-1.2581E+014.688E-06
4x1(k-1)^28.1686E+003.922E-07
5x1(k-2)x1(k-1)-1.1122E+018.389E-07
6x1(k-2)1.2210E+015.690E-07
7x1(k-2)^22.9455E+003.827E-06
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" + ], + "text/plain": [ + " Regressors Parameters ERR\n", + "0 y(k-1) 5.4940E-01 9.999E-01\n", + "1 y(k-2) 4.0806E-01 2.042E-05\n", + "2 1 1.4853E+00 1.108E-06\n", + "3 x1(k-1) -1.2581E+01 4.688E-06\n", + "4 x1(k-1)^2 8.1686E+00 3.922E-07\n", + "5 x1(k-2)x1(k-1) -1.1122E+01 8.389E-07\n", + "6 x1(k-2) 1.2210E+01 5.690E-07\n", + "7 x1(k-2)^2 2.9455E+00 3.827E-06" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Writing the results\n", + "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.final_model = model_final\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model, model.theta, model.err,\n", + " model.n_terms, err_precision=3, dtype='sci'\n", + " ),\n", + " columns=['Regressors', 'Parameters', 'ERR'])\n", + "r" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.355391Z", + "start_time": "2023-07-11T17:36:26.163688700Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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ff/+d4uJievTowcMPP8zSpUtrraEUExPDK6+8wnPPPcfAgQMpLy/n999/x2Qy0bt3b5566ikWLlxom9/jDzqdjtdee427776bTp06cfz4cQ4dOkTfvn155513GDlypN/ey5Vp06bx0ksvMXjwYAwGA7t37+bo0aOce+65zJo1i1WrVjkM8R1oLVq04KOPPuL666+nZcuW7N+/n1OnTnHttdfyySef2BpZ7rjxxht544036N+/P40aNeKPP/7g+PHjnH/++fzrX//i/ffft/XIrV+/vtprn3jiCfr3709UVBQ5OTm11vOqyWAw8NJLL/Hcc88xYMAAjEYjv//+Ow0aNODKK6/kzTff5P/+7//qLBKiEEL4k6JKTFIhhBBCCCGE8Jr0VAkhhBBCCCGED6RRJYQQQgghhBA+kEaVEEIIIYQQQvhAGlVCCCGEEEII4QNpVAkhhBBCCCGED6RRJYQQQgghhBA+kEaVnfHjxzN+/Pi6ToYQQgghhBAijETVdQJCSV5eXl0nQQghhBBCCBFmpKdKCCGEEEIIIXwgjSohhBBCCCGE8IE0qoQQQgghhBDCB9KoEkIIIYQQQggfSKNKCCGEEEIIIXwgjSohhBBCCCGE8IE0qoQQQgghhBDCB9KoEkIIIYQQQggfSKNKCCGEEEIIIXwgjSohhBBCCCGE8IE0qoQQQgghhBDCB1F1nQAhhBBCCCFE4JnMKpk5BeSfKqV5o1h6pSai1yl1nayIII0qIYQQQgghIlxGVh7zV2eTV1Rq29YyIZa5I7swvGvLOkyZc6dOnaK8vJzExMS6TopTMvxPCCGEEEKICJaRlcf0ZduqNagADheVMn3ZNjKy8gLyvpdddhndunXjggsu4IILLqBHjx6MGjWKDz74wO1zDB06lD/++CMg6fMn6akSQgghhBAizKiqyplyk8vjTGaVuZ/8hqp1DkAB5n2STf+OyS6HAjaI1qMong0XnD9/PmPGjAHAaDTyzTffMHv2bE6cOMGUKVNcvv7EiRMevV9dkUZVmJAxsEIIIYQQAiwNqmsXbeGn/b43OFTg8MlSus370uWxF7VrygfT+nrcsLIyGAz87W9/o7CwkMcee4wbb7yR3bt3s3DhQvbu3UtRURGdOnXiX//6Fz169GDYsGEATJ48mTvvvJNJkyaRnp7O6tWrycvLQ1EUBg0axOOPP05sbKxXafIXGf4XBjKy8hjw1DpuSP+eme/+wg3p3zPgqXUB66oVQgghhBChLZwfrV9yySWUlZXx008/MX36dIYNG8aGDRvYunUrbdu25d///jcAX3zxBQDp6elMnjyZzz//nDfffJMXXniBH3/8kXfffZfvvvuO1atX1+XHAaSnKuRZx8DW7LK1joF9ZXzPkJ5cKIQQQggh/EtRFD6Y1tet4X+ZOQXc/PoPLo9745aL6ZXqPBiEN8P/tDRt2hSAoqIi3nvvPdq1a0dZWRkHDx6kSZMm/Prrr5qvGzRoED179qRFixYUFBRw4sQJmjRpwpEjR3xOk6+kURXCTGaV+auznY6Bnb86m6FdWshQQCGEEEKIekRRFOIMrm/lB3ZqRsuEWA4XlWreUypAi4RYBnZqFrT7yYKCAgCSkpLYunUrkydPpqSkhI4dOxIVFYWqaqXUMuzxueeeY/369SQmJnLuuedSXl7u8PhgkkZVCMvMKagVpcWeCuQVlZKZU0DfDknBS5gQQgghhAgLep3C3JFdmL5sGwpUa1hZm1BzR3YJ6gP6devWERcXR3R0NI8++ijvvvsuXbt2BWDJkiXk5ORovu7pp5/m0KFDrFu3joYNGwIwcuTIoKXbGZlTFcLyTzluUHlznBBCCCGEqH+Gd23JK+N70iKhejCHFgmxQZ1KYjQaWbNmDc8++yz33HMPRqMRnU5nCzLxyy+/8Oabb2I0Gm2vMRgMnDp1CoDTp08TExODXq+nrKyMJUuWsHv3bsrLy4OSfmekpyqENW/kXhQTd48TQgghhBD10/CuLRnapUXQo0nPnTuXRx99FICYmBjat2/P/PnzGTFiBKqqcuONN3LTTTdhNptp06YNEyZM4JlnnuHYsWMkJyczbtw47r33Xm6++WbuvvtuZs+eTb9+/YiLi+PCCy9k1KhR7N69O6CfwR2KGgqDEEPEkCFDAFi7dm0dp8TCZFYZ8NQ6l2Ngv/vnZTKnSgghhBBCiDoiw/9CmHUMLNQOm1lXY2CFEEIIIYQQ1UmjKsSFyhhYIYQQQgghhDaZUxUGrGNgOzy0BoDLOjcj/R8XSw+VEEIIIYQQIUB6qsKEfQPqrMYNpEElhBBCCCFEiJBGVRjyw0LWQgghhBBCCD+RRpUQQgghhBBC+EAaVWFIOqqEEEIIIYQIHdKoEkIIIYQQQggfSKMqDMmcKiGEEEIIIUKHNKrCkCIDAIUQQgghhDcOboM3/m75f4ClpaWRlpbG3r17a+17/fXXSUtL44UXXvDq3Fu3biUtLc2tY1esWMFll13m1fu4SxpVQgghhBBC1Bfb34V9G2HHe0F5u6ZNm/Lxxx/X2r5ixQoaNmwYlDQEgzSqwpAM/xNCCCGEqOdUFYzF7v13dBfs3wK5WyDrI8vrf/3Q8vf+LZb97pxHVT1O5siRI1m1ahVms9m2bceOHRiNRrp06WLbZjabWbx4MZdffjkXXngh1157LRs3brTtz8/PZ9q0afTs2ZMhQ4awadOmau+Tm5vLtGnT6N27N5deeinPPfccRqPR4/R6Kypo7ySEEEIIIYTwnarCkmFwYKv35yg5BkuGe/aas/vArRkePeG/5JJL+PTTT9m8eTMDBgwA4MMPP+Taa69lw4YNtuNeeuklPvzwQ15++WXS0tL48ssvmTFjBm+//Tbdu3fnnnvuoWnTpmzYsIFTp04xffr0qo9SUsLNN9/MlVdeyX//+18KCgq46667MJvN3HvvvZ59Ri9JT1UYko4qIYQQQoj6LjzuCKOiohg5cqRtCGBpaSlffPEFo0ePrnbcRx99xJQpUzjvvPOIiopixIgRXHbZZXz44YccPHiQH3/8kfvuu4+GDRvSsmVL7rjjDttrv/nmG4xGI7NmzSImJoaWLVsyc+ZM3n777eB9zqC9kxBCCCGEEMJ3imLpMSovcf81h3do90zdmgEturt3jug4r+ahjBkzhnHjxnH69Gm+/vprevbsSbNmzaodc+zYMc4+++xq29q0acPOnTs5cuQIAK1atbLta9u2re3fBw8epKCggIsvvti2TVVVysvLOX78uMfp9YY0qsKEajeGVZFJVUIIIYQQ9ZuigCHe/eOjGlT+QweYq/4f1cCz83ihc+fOtG/fns8//5zVq1czceLEWse0bt2aAwcOVNt24MABmjdvTosWLWx/d+jQAYDDhw/bjmvRogVt27YlIyPDtu306dMcP36cxMTEQHykWmT4X5gwmT2fGCiEEEIIIQQA8c2gYXNodT78/TnL/xs2t2wPgjFjxvDGG2+Qk5PD4MGDa+2/7rrrWLx4Mb/99hsmk4nPP/+cdevWcfXVV9OqVSsGDBjAggULKCoq4ujRo7z44ou211566aUUFxfzv//9D6PRyMmTJ/nnP//JPffcE7TOCOmpChMmL6KtCCGEEEIIAUBCa7g7C/QGSy/XhbeAyQhRMUF5+7///e889dRTTJw4kaio2k2QW265BbPZzD333MPRo0dp164dzz77LL169QLgmWeeYf78+Vx66aU0bNiQMWPGsH37dgAaNmzIG2+8wZNPPsn//vc/zGYzvXv35pVXXgnKZwNQVFXu1q2GDBkCwNq1a+s4JbWdMZo491+WLs1b+qcwd+R5dZwiIYQQQgghBMjwv7AhPVVCCCGEEEKEJmlUhQn7OVVKmITQFEIIIYQQoj6QRlWYMNs3qqRNJYQQQgghRMiQRlWYkOF/QgghhBBChCZpVIUJ+54qszSwhBBCCCGECBnSqAoT9j1V0qYSQgghhBAidEijKkzYB6qQhYCFEEIIIYQIHdKoChNms92/patKCCGEEEKIkCGNqjBhP/xPOqqEEEIIIYQIHdKoChP2Q/7M0qoSQgghhBAiZEijKkyYVYn+J4QQQgghRCiSRlWYqBaoQhpVQgghhBBChAxpVIUJ+0aVtKmEEEIIIYQIHdKoChMy/E8IIYQQQojQJI2qMCHrVAkhhBBCCBGapFEVJux7p6SjSgghhBBCiNAR1o2q7du3c+6557J169Za+8rKynjppZcYNmwY3bp1Y8iQITz22GMUFRXVQUp9ZzLb/1taVUIIIYQQQoSKqLpOgLf27dvH7bffjtlsrrWvoqKCyZMns3XrVq6++mpuvfVWduzYwbJly2z/NxgMdZBq71Vbp0q6qoQQQgghhAgZYdmo+uqrr5gzZ47DXqdly5axdetW7r//fiZNmgTAuHHjaNmyJS+88AJfffUVV155ZTCT7LPqgSrqMCFCCCGEEEKIasKuUTVlyhS+/fZbOnbsyMCBA/n0009rHfPOO+/Qtm1bbrnllmrbx40bR3l5OYmJicFKrt9IT5UQQgghhBChKezmVO3du5dZs2bx8ccfk5KSUmv/kSNH2LdvH4MGDUKv1wNQUlJCRUUFzZo145577qFv375BTrXvTBJSXQghhBBCiJAUdj1Va9ascTofas+ePQC0adOGd955hyVLlpCbm0t0dDRDhgxhzpw5NG/ePFjJ9RuzhFQXQgghhBAiJIVdo8pVgAnrPKv333+f/Px8pkyZQvv27fnpp5948803+e233/joo49ISEgIRnL9xr4hJR1VQgghhBBChI6wa1S5YjQaAUt0wPfee4/u3bsDMHToUFq3bs1jjz3GkiVLuOeee+oymR6zH/InPVVCCCGEEEKEjrCbU+VKXFwcAD169LA1qKzGjRuHXq9n8+bNdZE0n9ivUyVzqoQQQgghhAgdEdeoatGiBQDNmjWrtc9gMJCQkMCpU6eCnSyf2QeqkDaVEEIIIYQQoSPiGlVpaWnExcWxa9euWvtOnz5NQUEBbdq0qYOU+aZaoAppVQkhhBBCCBEyIq5RZTAY+Pvf/86+fftYuXJltX2vvvoqQNgt/AuyTpUQQgghhBChKuICVQDMmjWLzMxMHnroIX7++WfOPfdcfvjhBz799FP69evHqFGj6jqJHqu2TpUEqhBCCCGEECJkRGSjqmnTprz33nu89NJLfPXVV3z00Ue0aNGC22+/nWnTpqHThV8HnblaT1UdJkQIIYQQQghRjaKqMpbMasiQIQCsXbu2jlNS29tb9zPn4ywAzmvVmM/uGljHKRJCCCGEEEJABM6pilTVAlVIV5UQQgghhBAhQxpVYcK+ISV9i0IIIYQQQoSOiJxTFYnK7RpVx06X8tFPf1FYYiSxYQwtGsfSKzURvU6pwxQK4R8ms8r3e46zZe8xQKFvhyT6tE+S8i2E8Ji1Ptn4Zz47DhRRWmEiRq9DURRKK0w0iI7i/DZN6N8pWeoZIYRPZE6VnVCdU5WRlcf9H+7gVGmFw2NaJsQyd2QXhndtGcSUCeFfGVl5PLjiVwpLyqttbxIXzZNjukn5FkK4zVF94ojUM0IIX8jwvxCXkZXH9GXbnDaoAPKKSpm+bBsZWXlBSpkQ/pWRlce0Zds0b4AKS8qZJuVbCOEmZ/WJI1LPCCF8IY2qEGYyq8xfnY0nXYnzV2dLIAsRdkxmlXmf/ObyOCnfQghX3K1PHJF6RgjhDWlUhbDMnALyikrdPl7F0mOVmVMQuEQJEQCZOQUcPlnm8jgp30IIV9ytTxyRekYI4Q1pVIWw/FPuN6j88Toh6oonZVbKtxDCGX/UEVLPCCE8JY2qENa8UWxQXydEXfGkzEr5FkI44486QuoZIYSnpFEVwnqlJtIywf2KXcESBbBXamLgEiVEAPRKTaRF4xiXx0n5FkK44m594ojUM0IIb0ijKoTpdQpzR3bBk1Uz5o7sIutsiLCj1ynMu+o8l8dJ+RZCuOJufeKI1DNCCG9IoyrEDe/aklfG98QQ5fyrapkQyyvje8r6GiJsDe/akkXje9IkLrrWvqZx0SyS8i2EcJO1PnHx01mN1DNCCF9E1XUChGvDu7ake+u9/Li/UHP/izdcwBXdWsqTNRH2hndtydAuLeg0Zw3WiMb/+vu5TOyXKuVbCOGR4V1b0rNtUzL3nQAgRq9wXuvGxOh1KIpCidHEL38VAfDaxIu4JK251DNCCK9JoypMlBjNDveltWgkPwQiYlSYzdgvEdO5ZWMp30II7yhVdUfbpHhWzBhg+1tVVdo/tAZVhW5tEqSeEUL4RIb/hYliY4WTfaYgpkSIwCopq16ey02yCKcQwjuq6rj+UBSFeIPl2XLNekcIITwljaowUeykwi8pc9zgEiLc1HyAUF7huJdWCCGcKS13Xn/EGfSA8weXQgjhDmlUhYkS6akS9USJsWZPlTSqhBDesW8sKRqj+xrGVPZUye+oEMJHMqcqBJnMKt/vOc7GP/PZcaCI0nKT0wr/uS938t+vd1eurZHExH4pLqMFClHXTGaVzX8c48NtB/jrxBkMegVFUTh+uqzacR/9dIDPfz3EsdNGSitMNIiO4vw2TejfKZk+7ZNkHoQQAgBjhZmlm3PIzCmguLQcFIXcY8W2/cVlFZjMqq3OMJlVTKrloc3TGb+j1+korTARG6WnWaNY2iQ2oF8HqWeEEO5RVGcDjuuZIUOGALB27do6S0NGVh4PrviVs8/s4rGo10CBh8tv41e1vdvnUBSYMjCV2SO6BDClQngvIyuPWe9v9/npcJO4aJ4c001CIAtRzy1Yk83iDTm4uqGx1hkAD674lcKScpfnlnpGCOEO6c4IIRlZeUxbto3CknLG6Ddyvj6H83U5jNFv9Og8qgqvbshhwZrsAKVUCO9Zy7k/htsUlpQzbdk2MrLy/JAyIUQ4WrAmm1fdaFBBVZ1h/a11h9QzQgh3SKMqRJjMKotWredS5SdG6b5jjH6Dbd/V+u8YpfuOy5RttOao2+dM35iDUSb5ixBiMqvMXZXl9/POX52NySyd7kLUN8YKM4s35ATlvaSeEUI4I3OqQkRmTgEry6dDTO19TZRi/mt42fZ3Sulyt85pVuGtLfu4baD7QweFCKTMnAKOnDL6/bx5RaVk5hTQt0OS388thAhdb23Z51YPlT9IPSOEcEZ6qkJE/qlSZhpnUKE6ngxrUhVmGmd4dN79BSW+Jk0Iv8k/VRqW5xZChKZg/8ZJPSOEcEQaVSGieaNYVpkHMMr4mMNj3jZdBqj0ZJfb522XGOeH1AnhH80bxYbluYUQoSnYv3FSzwghHJFGVYjolZpIi8YaY//s/CNqLf81vMKK2PlunVOnwIS+KX5InRD+0Ss1kbMaGfx+XstyAol+P68QIrRN6JtCsIKdSz0jhHBGGlUhQq9TmHfVeRxXG3NGjcZRoHtVhU8rerkVsGLywFRZr0qEFL1OYf6orn4/79yRXWQdGSHqIUOUjimDUoPyXlLPCCGckTvuEDK8a0vmjR/KIN1SzZXfwbIG1d+jMtkUO9PheRQFpg6SdapEaBretSWLxvckxg8N/qZx0Swa31PWjxGiHps9ogtT3WxYWeuMReN70iQu2qPXSD0jhHBGFv+1EwqL/4Il7PSRd26n1R9va+43A58n38q+Nn/noLkZR4pKyco7yZGTZZzXqhEfzxggPVQi5K3+5RB3vvsziXFRpCY3xKBXUBSF0goTDaKjKC2v4KfcIgAGdEjErMLpsnJ2HDwFwNJbL2ZAx2by5FgIAcD9H27ngx//on1SnGU4vV19cn6bJvTvlEyf9km2OsNkVvl+z3E27TnKXwUlHDtt5HRpOTsOnbKd89b+Kcy5UnqohBCuSUj1EKTXKbQafBs4aFTpgCuPLYFjS+DuX6FJW97JzGX2il9pmRAnDSoRFs5UWBb/Pf/sprx+S69a+19a/6etUTXn7+dxbsvGGCvMnPPw5wD0aNNUbnSEEDbWdRlv7NOOSW4sJaLXKfTvlEz/Tsm2bafLKug69wvb3y0TGkg9I4Rwi9x9h6o2F8LA+10ft7AbAHEGPQAlxopApkoIvykps5TVuBjtZzvR+qobmXiD5RhDlM62vVjKuhDCTnGZ5UFNvIM6xR0NovXVzyn1jBDCTdKoCmUX3QJRTsK3KnoY/iRQddNZbDQFI2VC+MxaVuMNes39OruJhXExVcfEVZZ1eYAghLBnrRPiHNQp7qjZK1Uiv6lCCDdJoyqUJbSGCicLDaomyHgQqHoyZ336L0Sos94AOXqqbDJXTfdsaHeM9d/Wp9JCCAH2D2r8N7OhWH5ThRBukjlVoW74U5DxT8f7L30YCnOJjW4EwIETJUx580cuTklkYr8UmV8lQo7JrLL5j2N8/mseALsPn8JYYa5VVssqqhpNP+eeoFdqEgCqapk38e+MnfRo24R+HapPPhees34nH247wIGCEowm1bKeWGVvYVm5me4aE/2FCAXGCjNLN+fw55GTAOzJP8WlnZt7VU7tH+YArP39CCVlFYzp2YZ+HZOl7AshHJLof3ZCJfpfLfMSXB5ymekF9pYnVdumKDBloIRWF6EjIyuPWe9vrzWkpmZZzcjK474PdnDa7ilxk7hojBVmzeE4TeKieXJMNwl57AVH34kjktcilCxYk83iDTnUvJGJN+h5Zuz5HpXTjKw85q/OJq9Ie4SIN+cUQtQf0qiyE7KNqm//A+sfc3lYSulyze2yZpUIBRlZeUxbts3pMVMHpXJB26ZMX7at1k2SO2QtGc+48504Inkt6tqCNdm8uiHH6THultOMrDy36x0p+0IILTI2LBz0uNGnl6dvzLGFmhWiLpjMKnNXZbk8bvGGHOZ9ku1Vgwpg/ursWsN3hDZ3vxNHJK9FXTJWmFnsokEF7pVTk1ll/mr36x0p+0IILdKoCgcJrWHwbIe7VRWWlg/hMmUbrTlaa79Zhbe27AtgAoVwLjOngCOnjC6PU4HDJ50EZ3Ehr6iUzJwCr19fn7j7nTgieS3q0ltb9rnVCHKnnGbmFDgc8uftOYUQ9Y80qsJFzwkOdykKTIxey5KYp9kUO1PzmP0FJYFKmRAu5Z/yvqEUyu8VzvyRT5LXoq548pvmqpx6U46l7AshapJGVbhIaA19bnd6iElVmGmcobmvXWJcIFIlhFuaN3Ky3loYv1c480c+SV6LuuLJb5qrcupNOZayL4SoSRpV4aTv7RDb1OHuZyquBVR6sqvadp0CE/qmBDZtQjjRKzXREqLbBQVo0TgWb4MWt0yIpVdqopevrl/c/U4ckbwWdWlC3xS36gl3ymmv1ERaJrjfSJKyL4TQIo2qcJLQGm76wOHuB6I/4L+GV1gRO7/a9skDU2W9KlGn9DqF+aO6ujxuyqBU5l1liVTpTcNq7sguso6Mm9z9ThyRvBZ1yRClY8qgVJfHuVNO9TqFuSO7uF3nSNkXQmiRO+1w07gV6GMc7lZVeLPicsAy10rCqYtQMbxrSxaN74lBX/tmxL6sDu/aklfG96RFjSfHTeKiiTPoNc/dNC5awhx7wfqdRGt8J45IXotQMXtEF6Y6aFjFx+g9KqfWesdZj5Wn5xRC1C+yTpWdkF2nqqaKMvj+Vfj6/2rtymgwghcL+xHTOJl37h8nPVQi5Lz67R4WfL6TNk1j6dIygYtTEpnYL6VWWTWZVTJzCsg/VUrzRlXDbb7fc5xNe47y6rd7Manw3NjzuapHa3ly7INnv9rF82v/pF1iA5LiDeQVlZJ3sgyAtk1jOXyyFKMJHh11Hjf2bid5LULKhP99z8Y/j9O1VWM6NW/ImJ5t6Ncx2atyaq13Dp0oYduBE2zYfYwDJ84w8vyWLBx3gZR9IYRDUXWdAOGFqBjNBhXA8DNrGB6zBsqAqBuCmy4h3FBiNAEw+JzmPH51N4fH6XUKfTsk1drev1My/Tsl88FPBzl6qoy0Fo3lRsdHZyq/k2FdW/LQiHP56Ke/uPeD7QBcd1FbVm0/xJ/5p+nQvKHktQg5pZXrMN5+aUeu6OZbL1JVvZPENRedzX++2MlL6/eQFB8jZV8I4ZR0Y4SrSx5yuKtc1ZEefSMU5gYxQUK4p8RYAUB8jG/PdOIrhwJazye8V1zZqLIOr4yPqRpmGRcTVZXXZabgJ04IF4ory2Wcj3WKljiD5ZxSzwghXJFGVbi65J8Od0UrZiaXL4eFjnsBhKgrNW/gvWW92bGeT3ivpKyyoVuZp9a8tWzT2+W13FiK0GN7UONjnaLFek6pZ4QQrkijKpxd+rDDXRWqHsakBzExQrjHegPf0Neeqhhr74nc6PvKesNo7T2070WMj4my/V0iN5YiBNUsv/5k7f2SekYI4YrMqQpnPW6E71+CMydq7RplfIQmW9sS98sP9EpJ0gwEIESwmMwqm/84xofbDvDN7mMAHCw8g8msej1PIbayPL+wdjcvrf+zcu0YKevOmMwq3+85zsY/89lxoIgz5RUYK1T2FxQDcOB4MSazSmx0Vf4dKCgmtvKXYsl3e/hs+yG6t2lC/07J9GmfJPNMRJ0wVphZujmHzJwCjp+yBFXZmXeSc85q5Ncy2SDK8vBm+4ETXPvKZto0bcA1HgTC0Aq4I9eMEJFJov/ZCZvof/YO/ACvXW77U8Wyvs+VZY/zm1oValZRYMpACa8ugi8jK49Z72/X7OWIN+h5Zuz5HocoXrAmm1c35Gjuk7KuLSMrjwdX/EphSbnT42KidMRE6ThZ6vrJfJO4aJ4c001CTIugWrAmm8UbctC6efFnmczIymPmu79QVhkIw547dVdGVh7zV2eTV1Rq29YyIZa5I7vINSNEBJLHueGsMNfSS9Wgqe3HxaTqKFAbkkwhrTlqO1RV4dUNOSxYk103aRX1UkZWHtOWbXM4bKzYaGLasm1kZOW5fU5nDSqQsq7F+j24alABlFWY3WpQARSWlHv8/QnhC+v17+hpsL/KpPWa0WpQgeu6KyMrj+nLtlVrUAEcLiplulwzQkQkaVSFs4XdYPl11Yb/6TGTqJxmacx/2BQ7s9ZL0jfmYHTwIyGEP5nMKnNXZbl17PzV2ZjMrjvNjRVmFjtpUNmTsm5hMqvM++S3gL6Hu9+fEL7w5Pr3pUz6WneZzCrzV2drNvys2+SaESLySKMqnI1JB51lsoN1hLZS+Y9yVc9M44xaLzGr8NaWfcFJn6jXMnMKOHLK6NaxeUWlZOYUuDzurS37HD6hrknKukVmTgGHKxfyDRR3vz8hfOHJ9e9LmfS17srMKajVQ2VP9TF9QojQJIEqwln3sZB8DiweXGvXaOMj1eZU2dtfUBLolAlB/inHNxXeHu9p2ZWy7vn3EOrvI+ovT69nb8ukr3WXu6+Xa0aIyCI9VRHCOorAnbAj7RLjApsYIYDmjWL9frynZVfKuuffQ6i/j6i/PL2evS2TvtZd7r5erhkhIos0qsJdfDPU+OYcVFoAluF/JaqB42pjzcN1CkzomxLEBIr6qldqImc1Mrh1rCUceqLL4yb0TcHdYMRS1i16pSbSonFMQN/D3e9PCF94cv37UiZ9rbt6pSbSMiHWYVoVH9MnhAhN0qgKd6oJ5fq3OXFRVVCKEmJJUk7SVdlbLQIgwOSBqbKGjwgKvU5h/qiubh07d2QXt9ZuMUTpmDJIe1hrTVLWLfQ6hXlXnRfQ93D3+xPCF55c/76USV/rLr1OYe5Iy5IONVOgOHmdECK8yTpVdsJynap5CbU2mVXLU3qrlNLlsnaPqDMZWXnc/e4vlGqt9RKj55nrvFunytE6NVLWtWVk5fHAhztchkuPidLRwKB3K/x607hoFsg6VSLInC2r4M8y6XSNPTfqLlmnSoj6RRpVdsKyUbXjfVg5Hcy1b5Qq0HOvcSq5ra/kvan95Km9qDPf7Mzn5jd+oFGMnrQWjWnTtAHX9GxDv47JXj+tNVaYWbo5h617j/PboZPknSyj81kN+eTOgVLWHfgz/zSXP/steqB3+0TOlFdgrFCJjdZzdmKc7TsBSwSz/FOlNG8US4+zm7Ds+31s2nOMb3YdA+D1my9m0DnN5Gm7qBMf/XiAez/cQdMGUZzXKoHubZrQv1Myfdon+bVMmswqm/84xofbDrB2Zz6ny0zcPrgDs4alufU+JrNKh4fWAHDHpR24Z6h7rxNChB+J/hfunEQAXHXxm6zaqHB1ckO5yRR1qrTC8qQ3rUVjPpzezy/nNETpmDyoA5MHdeCDHw9w/4c7OCuhgZR1J0rLLd9DcuMYlk/p6/TYvh2Sqv09eVAHbumfSsc5nwNw/tlN5OZQ1J3K9UO6n92Upbf2Ctjb6HUKA9OaMTCtGZOW/sDXv+dzdlKc22Xf/rhOZzWSa0aICCZ3HxGsQZQegOIy58N9hAi04jLLzXxcTGCe48RXnrfEKGXdGWtdEG/w7nuI0uuIqWy0Sr0i6pJ14dyoIDZS4iqvm2KN4YDuUBRpUAkRycK6UbV9+3bOPfdctm7dWmvfzTffTFpamuZ/WseHtfhm0LA5xDap2hbdAKVRMwDN8eBCBJO1sRNv0Afk/HEG6wMEKevOWOuCuBjvv4eqBqzktag7FZWNqmD2/MRXXjclHjxQMJtlhoUQ9UXYDv/bt28ft99+O2Zz7cnvALt27aJr16784x//qLWvQ4cOgU5ecKkmGPc2bF0MWR9YtkXH08RcRFdlL3Fnyuo2faLesz7ZjQ9QT1VD6alyS7HRt54qsNxYFhRXnUuIumCq/O2P0od2T5XJbtq69FMJEdnCslH11VdfMWfOHIqKijT35+fnU1BQwJgxYxg1alSQU1cHFnarva3kOH2/HsOnMcBxmPJmWy5OSWRivxSZcyKCylhhZtMfltD++48VY6ww+70MxlQOdT1yspSnv9hF3w5Jfp+wHq5MZpXv9xxn45/5rM3OB+DY6TKvvgeTWUWtfPL+zBe76NG2Cf06+D84gBCOGCvMvLVlHxm/HQaC21CJibK826fbD5L1V6FbwTFM0lMlRL0RdtH/pkyZwrfffkvHjh3p3Lkzn376KW+++Sa9e/e2HbNx40YmTZrEU089xejRo90+d1hG/wOnEQDLVT33lU9llXkAIOGmRXAtWJNN+sYc7O8rdIplDSl/lUFHocKbxEXzZD0P952RlceDK37VDI/uaV3g7FyS1yIYtOoTgKmDAv+b5iyMu7PyX2KsoMu/vgDgxRsv4O/dWwU0nUKIuhN2XRZ79+5l1qxZfPzxx6SkpGges3PnTgDOOeccAEpKShwOE4wI3cfCJO2G4GjjI7YGFYCqwqsbcliwJjtYqRP1lPUmpOYNkNmPZTAjK49py7Zprr1UWFLOtGXbyMjK8/l9wpE1bxytN+VJXeDqXPU9r0XgOapPIPC/ac4aVOC8/Nv3VCkyAFCIiBZ2jao1a9YwdepUDAaDw2OsjaqPP/6Y/v37c8EFF9CzZ08eeOABCgoKgpXUOmVWnVfe6RtzMGosxiqEPxgrzKRvdHwTAr6XQZNZZd4nv7k8bv7q7Ho3BMfdvAHX34Mn56qPeS0CLxj1ibP3XuykQWVPq/xH8vNcIUR1YdeoctaYstq9ezcA2dnZPPDAA/z3v//lqquu4pNPPuGGG27g5MmTgU5m8MU3g/jmWKvz39W25KsJHFcbax5uVuGtLfuCljxRv7y1ZZ/mE2V7vpbBzJwCDp90HYQlr6iUzJz68TDFyt28Adffgyfnqo95LQIvGPWJs/d29zGBVvmvFqhCOqqEiGhhGajCleuvv57i4mImTZqETmdpNw4fPpzU1FSefPJJXnvtNe655546TqWfJbSGe7IwPtWJmPIi0iuuYI25L0aiHb5kf0FJEBMo6hN3y5YvZTD/VGlAjo0Enn5eZ9+Dp+eqb3ktAi8Y9Ym/zlmz/Nv3XIXXDHYhhKfCrqfKHTfddBNTpkyxNajst+v1ejZu3FhHKQuwqBgUvaWd/Hf9VqcNKoB2iXHBSJWoh9wtW76UweaNYgNybCTw9PM6+x48PVd9y2sReMGoT/x1zprl32zXkjJLq0qIiBaRjSpHDAYDjRs3pri4uK6T4l+FuXDoZzj0C9HlpwDoo/ud85Qcuip7ac3RWi/RKTChb0qQEyrqiwl9U3AVYdvXMtgrNZEWjWNcHtcyIZZeqYlev084cjdvwPX34Mm56mNei8ALRn3i7L3dHbWnVf7te6qkUSVEZIu4RtWuXbu48soreeyxx2rtO378OCdOnKBdu3Z1kLIAWtgNFl8CiwejmIwAxFPKZzFz+DTmYTbFzqz1kskDU2W9KhEwhigdkwemOj3G1zKo1ynMu+o8l8fNHdml3q2h5G7egOvvwZNz1ce8FoEXjPrE2XtPGeT8va20yr80qoSoPyLurrpdu3YcPXqUlStXcujQoWr7nnnmGQCuvvrqukha4IxJB1316XHWCbHlqp6ZxhnVtgdjTQ8hZo/owlSNmxGdH8vg8K4tWTS+J03iag91bRoXzaLxPevt2knO8gY8qwtcnau+57UIPEf1iULgf9Os7+3ocYGz8m/fkDJJJEAhIlrEBaqIjY3l//7v/7j//vsZO3YsN954I40aNWLt2rVs2bKFkSNHcsUVV9R1Mv2r+1hIPgcWD66169fhH5G7LRoOFNGhWTyfzxwkPVQiaGaP6MKf+adZu/MofVITGdrlLCb0TfFrGRzetSVDu7Rg85/HmLAkE4BF43sytEuLet9rYs2bc+aswaTCxe2a0iQ+ml4pSUzs59n3YD3X93uOs2nPUV7dsBeTGZ6+7nyuvqB1vc9rEXizR3ThQEEJa7KO2LbdflkH7vtb56C8971/68zSzTlk5hSwblc+JjM8dU03rr3wbIflX3qqhKg/Iq5RBTBy5EiSk5N59dVXSU9Px2QykZqayr/+9S9uuOGGuk5egClgFwC2Z7um3BbfnDuW/0xSwxhpUImgK61cO+b6Xm0ZfUHrgLyHXqcw8JxmxEbrKC03c16rBLnJr2Qyq5gqq4T0iRfRJM71shSO6HUK/Tsl079TMh9tO8iRk2V0btFI8loETWlF9YZJbJQ+aO9tiNIxeVAHJg/qQP8n13Gw8AznnOW8/Ns3pFRpVAkR0cK6UXXnnXdy5513au7r27cvffv2DXKK6lB8M2jYHOKaQX7lQp3RDSC+GfEnLV9zibGiDhMo6qviMhMAcYbA3/zEG6IoLTdSYjQF/L3CxRm7vIgz+K/KjzdEAWUUl0m9IoKnZnnT6+rmQWF8jKU+c1XX2A/5k+F/QkS2sG5UCTuqCca9bVkIY8nfLNuiGkDxUZJPFdKao5SUxddtGkW9ZG3Mx8cEvrqJi9FzvBiK5QGCjTUvovWKX3uq49y8qRTCn2qWt6g66iW1PqBw9VBBhv8JUX9IoypSLOxWe9uZAlg8mG7Apljobfwo6MkSwtpTFYxGVXzljU5JmdzoWwWqUWvNa2nAimCqWd7qauhpwxjrCBDndY2sUyVE/SGNqkgxJh1WTgdz7RscVYni7rIpHCst46b074mL0Xs1UV0ITxgrzCzdnEP+yTMA/H6oiG6tAzfXyWRWqTBZbnD++9VOXvkmql6XdZNZ5fs9x/n4578AqDCZ2fTnMfq0T/LLd9Ag2pKfL63/g3e35tK9TRP6d0r22/mFsGctz0eKSqttj9LXTVmLjbK876vf7uHbXfmM6dmGfh2TnYdUN0ujSohIpqgyc9JmyJAhAKxdu7aOU+KlQ79oRgAcx5NsLW1ba7uiwJSBEl5d+N+CNdks3pBDzcol3qDnmbHn+z30dkZWHg+u+JXCknLN/fWtrDvLjyZx0Tw5pptP38GCNdm8uiFHc58/zi+EPWfl+cZeZ/PEmO5BTY+j8q9Vv23LPcGYlzcD8K+/d+HWAe6teSWECD/169FtPWO9oT3tYCiUqsKrG3JYsCY7eIkSEc96w6H1tKbYaGLasm1kZOX57f0ysvKYtmybwwYV1K+y7io/CkvKffoOnDWo/HF+Iey5Ks/LMw8Etaw5K/9a9Zs5kHOqDm6DVwfDq5dY/i2EqFPSqIok1giAjSxPySrQU6DGc1xt7PRl6RtzMFZIWCLhO2OFmcVObrit5q/OrjYsxlsms8q8T35z+/hIL+ue5Ic334G736+35xfCnrvlOVhlzZv6zS+BKg5ugzf+bvm/tSH1XHd47W+Q9wvk/Qw73vPu3EIIv5FGVSRJaA13Z8Fl/wIgGhOrTf04TJLTl5lVeGvLviAkUES6t7bs0+yhqimvqJTMnAKf3y8zp4DDJ8vcPj7Sy7on+eHNd+Du9+vt+YWw5255DlZZ86Z+M9k1pDwOqf7LO/BEK1g6EvZthDdGwv+GWhpSRfvBbNd7l5kO3z4Fuz6HwlwP30gI4Q8SqCKSFOZCyXGoqJrIe6V+K++bLkFB5YTaiIM003zp/oKSYKVSRDBPylH+qVLXBwXgHJFc1j3ND0+P9zTv/PEdi/rLk/ITjLLmTf1mtmtIueypOrgNVkyFogPQoKnl99xk16gsP+34taoJ1j9R9fe8IrfTKoTwD2lURRKNsOqJnOSzmDm2v1NKl2u+tF1iXMCSJeoPT8pR80axPr+fN+eI5LLuaX54eryneeeP71jUX56Un2CUNW/qN/ueKofR/6yNqRM5Vb1Pp854nU763mF5yNqkdoAqIUTgyPC/SDImHXTV28nW6K7lqp6ZxhmaL9MpMKFvSoATJ+qDCX1TcCfAccuEWHqlJvr8fr1SE2nROMbt4yO9rHuSH958B+5+v96eXwh77pbnYJU1b+q36oEqKv9hnSO1/kl4vAW8fgUc3119OJ8vtryovXalECKgpFEVSbqPhUna4eBHGx9hlXmA5r7JA1Pr3Ro+IjAMUTqmDHIdMnjuyC5+WctIr1OYd9V5bh8f6WXdk/zw5jtw9/v19vxC2HO3PAerrHlTv9kHqmh28jdLkIm3rrbMkfp2AZSfqTZk3z8UuPRhmVslRJBF7t2FAHA6qVZRYOqg+rN2jwiO2SO6MNXBjUd8jJ5F43v6dQ2j4V1bsmh8T5rERTs8pj6VdVt+NNAe3d00Ltqn78D6/Tq6hfX1/ELYqyrP2tf3nZd1DGpZc1b+teq35jkr+DXmFr4z3M6YrOmWIBOlhQFOpQrrH5PeKiGCTBb/tRP2i/8CFB2E9EugvBTKTgKgRjXgx5FfsfaQnk9+zuPQyVL6dkhk6S29I/qpvahbVyz8lt8Pn6Zn2ya0S4xjTM829OuYHLAnyiazyvd7jrNpz1H+KijhlwOF5J4o5fw2jflgWv96V9aPnCyl9xOWumx0j1a0btqAfh2S6dM+yS/fgbHCzNLNOWzYfZSNfx5HAZZN6u238wth7/jpMi587GsAxl3Uhvd+/AuAtyf1pn/H5KCnx1r+n1/3B6dKTdw39BymX9qxquwf3Aaf3kPF4WyiVGPQ04cuCka/YhnBIoQICglUEWlUE4x7G75bCLs+A0AxxHNxMxMXN6sgsVzPE5uhU/NG9e4mUwRXaYXlec3sEedycUrg5zvodQr9OyXTv5PlBmvJdzk88mk2ZyfG18uyXlpuWfQ7zqBn4fUX+P38higdkwd14LqLzqbHI1+hYpkDIw0qEQillevLGfQ6pgzuYGtU1VV5s5b/r37PJzOngNRmDS1pObgNPppsieBnKgvsTVZMAhhPW373a5q0Flr1COS7CyFqkEZVpNHq7i85DosHAzAFeILlFJdpVMJC+FFxWQVguamvC/ExlvctMdbPsm69xuMMga3m7c9fUmYiIa7+NWBF4JVY65MYPQZ9VRmLquNGfHxl/VZsrICda2DlDCg94cd3UMCQAOM/hLPOA50OVNUS1CIqBnZ/Ce+Pr/2yY7sBFeKSJAqgEEEijapIMyYdVk4Hc4XdxsoRnrooNp73CPwAJcYKzZcL4S/Wxkx8gG/qHbHe7Fsbd/WN9Rq3Ni4DxRClI1qvUG5SKTZWkOBkbpsQ3iq2q0+i7RpVdd0zGhcTxWXKTwz7+gEo/ct/J/7HZ9Cym6XhpCiW/1fTwPI/rQYVwIrJVf+WNauECAppVEWa7mMh+Rxbz1Q1k9aSn5cMP2y3/UAJEQiqarnBBsuT5brQMMZSvdXbnqogNmrjY6IoLCmXhzUiYKw9VfExeqL1VQ2pOm1UHdzGnP230SpmL/gjgF9sE7htHTRqBrGN3XuN5oPUStZ5VUKIoJBGVb2gYO2tahBtecK348AJrn1lM22aNuCaAAcQEPWHNVjEt7vzsYbA+fWvIi5Jiwl6+YqtnEe19+hpprz5IxenJDKxX0pEz6+yD9bxQ04BAAXFZWz681jAAkiYzCrWZvO97/9C88ax9EpJivi8FsFjMqv8uN9SngtLyvlxX4Ft346/ijivVULwf78qh/q1KvN1qJ/O0pi65XNIStXokXLBxYNUmVclRPBI9D87ERH9DywRABcPhuKjlr/jkkGnY/2g95n+yWHbhF978QY9z4w9X8IgC69lZOXx4IpfKSypvYBlk7honhzTLWjlKyMrj7vf+4XS8uplXVFgysDIDK3uLP8hMN+Bs/eM5LwWweOqXINlsd25I7sEp37ZuQbWPgpHsz1+qQqVodgVS0Nq0jpIaOVgeJ8HDv1So1FV+SB1yrfSqBIiiOQxYqQpzIXifLj+naptqonNFz/PMx9/R1LFEc2XFRtNTFu2jYysvCAlVESSjKw8pi3b5vDGp7CkPGjly5qWmg0qsMzvfnVDDgvWeH5DFMpc5T/4/ztw9Z6RmtcieNwp1wCHi0qZHoz6ZecaePcGrxpUhWoM/+34Jsw5AnMOw327ILk9RMf61qACiG9m+c8qLgkaNq++TQgRcNKoijQLu8HiS+C1y22b1DMn6Lf+ej6NeZhNsTOdvnz+6uxqK8AL4YrJrDLvk9/cOjbQ5ctkVpm7KsvlcekbczBq9NiGI0/yH/zzHXjynpGU1yJ4PClj1tIcsPqlMBcO/WxpUHnApEKFqnBMjWdk2QLy4ysbUf5oSNmnrTgfxi2v2qaaLH8X51v2CyGCQhpVkWZMumVyqh3rSPNyVc9M4wynL88rKiUzp8DpMULYy8wp4PDJMreODXT5yswp4Mgp1wttmlV4a8u+gKUjmDzJf/DPd+DJe0ZSXovg8bRcqwSofinMrXpY6aHJxnvoUvY6/cpe5gAtMAeiwWdN25KhVdvOnLA8WF18ifYyK0KIgJBGVaTpPtYyOVXDaOMjrDIPcHmK/FP+CGMk6gtPy0sgy5cn595fUBKwdASTN/np63fg6esjJa9F8HhbRv1ev3jRKLH0TjUkW22PEQNGLMsMmAMxhV3jQaqNLsqyXwgRFBL9rx6omhzrnuaNYgOVFBGBPC0vgSxfnpy7XWJcwNIRTN7kp6/fgaevj5S8FsHjbRn1W/1SmAs/LYWYBChzb52nChUKiefqskc4QrKtMWVlCsQoWIn+J0TIkJ6qSBTfzDJJNeFswNKgOoOB46rrdS9aJsTSKzUxwAkUkaRXaiItGrs3PyDQ5atXaiJnNTK4PE6nwIS+KQFLRzB5kv/g4XdwcBu88XfL/718z0jKaxE8npZrBT/XLwu7wcan3WpQWTugrjHOqxzq19LWoFKqHRfo+cqyLIoQdUkaVZFINcG4t6HP7bZNupiGJCkn6arspTVHHb507sgusl6V8IhepzDvqvPcOjbQ5UuvU5g/qqvL4yYPTI2YNZQ8yX/w8DvY/Dzs2whrH6nWuPLkPSMpr0XweFLGrKXZL/VLYS5sfhGi3e9d/VNtRb6awBE1qVbv1IXtmtj+HZDhfwAmIzRoCo1aVW1TFDh91BJgQ4JVCBEUsk6VnYhZp2pegsbGqgWAAVJKl1fbGx+j55nrZJ0q4T1n68k0jYtmQZDXqZr1/nZKjKZq2yN57SRX6/m4/R0U5kLJcTi6C1ZOB9VuzFLXa+DyedCkrcv3jOS8FsGTkZXHPe/9whmNJRKs/LZOlTUohQcK1IaMKHuCAhKqNais5T/OEM1zX+8GYOT5rXjhhgt8S6MWN37zmefeEEYhhPekUWUnYhpVO9633AyZK2rtUnVR7Or9FK8U9GTdznxOlZmYPqg99w3vLD1Uwmcms0r3eRkUG81c3rkZaS0b069DMn3aJwW9fJnMKpv/OMZza3ezLbeQlKQ4vrxncET3mpjMKj3mf8GpMhOXpiWT0MBA66YNPPsONG/QapjyjWUtnCZtMZlVvt9znI1/5vPt7qP8nneaFo1j2PDAZRGd1yJ4nl+7m2e/+oMuLRtxWeez6J2aiE6ncOx0Gc0bWYb8+aWHypMGVZN2UF6CceIXLN0JW/ce58+jp9l3/AzNGhrY9OAQDFE6nv1qN8+v/QOAK7u35KUbe/qWTi1OfvPRRcHoVyxzr4QQASWBKiKRk4mryqS1dG7Vg/8Ck9/8ka+yj9AmKU4aVMIv9DoF6wPl+aO70bpJgzpNy8C0ZhSXm5i27CcS4w0Rf5NvyX/Lc7JHRnXjbE8DRLg7TMgaXnpeEXqdQv9OyfTvlMwlace5fvH3xMVERXxei+Cx9lL1aZ/MfcPS/P8GHvdQKXDNEmjZDUNUDJObw+RBHfhpfwHXvLKFBoaq8m8fRj0gIdVBglUIESKkUVWPxRv0AJSUmVwcKYR7yk1m20Kv1vJV1+JjKsu5MfLLucmsUlp5Axrnaf57emOpEao53mD5SZE6RfhTSZmlB8Z6LfudJ+X+li/grC4QWzvwU5y1/BureoxMdoOBAjanSggREuRRYqSyRgCMbVK1LbqBZXuluBjLD0CxUWPIgBBesG+4WG8w/OaXd+DJtpb/e8CajvpQzu1v5uJjPMx/T24sL7oNkjvV6tmKq7zprQ95LYKnuLJe8XudApD7PZw70r1jY5tAk7M1G1RQ9VCh2O6hQrWeqkC2qWy/+XbDd2v85gshAksaVZHKGgEwbUTVtuh4KK6KBtQwxvpUTZ4qC/+w3tRH6xX/D//a8iKUFsGG/2iG+XbEVs7rQe+J9VrW6xRiPMl/T6OD/fiaZQhgjYaYfZ0i03WFv1jrlYaB6KlaMgx+X+3iIAViE2HyN5DQ2uFR1p60M+UmTJUtKFMwhv9B1W9+x79Vbavxmy+ECCwZ/heptJ46lxyvNuba0G8rAJ9tP0j2wSK6t2lC/051E1RAhD+TWWXjH8cAy9OaTX8e870s5X4Pe7+BX96uuiko2GP5b92jMPif0LaP01NYGxcFxUZuXLyFMpOZs5vGcU3PNvTrmBwxZd1kVtm427Jcgk6BzXuOu5f/XkQ8s7xJ5QR4O9a8NplVbkjfQrlJjci8FsFhrDCzdHMOW/ceB+DAiRJMZtU/5agwF478BnHNoMTxMiMAjF0G5wyFKOfrZsVGVzX6bkzfQrnJTF5hmW2byRyI1X8rufGbLxEAhQgsif5nJ2Ki/4HLaECfpDzMXdnnaL60SVw0TwYx/LUIf45Ca/tcljyMRKeVrgc+3MHJUu3haPEGPc+MDf+lBHzKf3fyWMuUb6tNgM/IyuPBj36l8Ix2SPdIyWsRHAvWZLN4Qw41b1D8Uo48eZDQIAmmbXTaQwWulzQAiNIpvHjjBYG5BiQCoBB1Tob/RaruYy1RfzQsOfd/DhtUAIUl5Uxbto2MrLxApU5EkIysPKYt26Z5M+F1WSrMhV2fW54iu6IxDM0+XY4aVGCZqxHuZd2n/PdlSNDRXbbX29LgoEEFkZHXIjgWrMnmVY0GFfipHLnboLpgItz7u1sNKkfXoL0Ksxq4a8DJbz6T1kqDSoggkEZVPbRi20G3jpu/OrvaeHAhajKZVeZ98pvL4zwqS9anyO9c73pYjlWNSHTupsur9IUQn/Lf22F/Vh9PgYXd6k1ei+AwVphZvCHH5XFelyO3HyQocOFEl0P+PC3/INeAEJFKGlWRzBoNiMrx57FNKDEkcUzVjlxUU15RKZk5BYFLnwh7mTkFHD5Z5vI4j8qSpzf6F91Wa16Vu+myCtey7nX+u9ugUqJBcRAcQBcFY9LrTV6L4Hhryz7NHqqavC5H7tYvN38KbS50eZin5R8CdA0U5sLpfGjQtGqborf8fTpfAlUIEQTSqIpUhblQnA/jloOu8qZINfFWuydIVopojXs9APmnSgOYSBHuPCkfbh3rzQ//j6/VulHyptyGY1n3Ov/dvbEcuxQmr9PeVzmkqL7ktQiO/QUlbh/rcTlyK3y6AnHJ0DQ1MGnw8XUOLewGy6+DMyeqtqkmy9/Lr/OtV1oI4RaJ/heptCrQslNM/WMqUytHM6SULnd5muaNYv2cMBFJPCkfLo/1OgqdHkYv8jpdvrymrnmV/+42XGObWgJRFFsfwCig0YdQX/JaBEe7xDi3j/WoHBXmWsKnu+JmpD+v0uCH1zk0Jt11oAohREBJT1WkGpNuqUg1lKt6ZhpnuDxFy4RYeqUm+jtlIoL0Sk2kRWPXNx9ulSVvn6SOXlRrIVp30+VR+kKQx/nvbsM1Og4mr7dM0DcZLUOImpxdtV9R4LRl/ZteTU/Xi7wWwTGhbwruBEz3qBy5W+51Bmh9gdsNKvC8roEAXQMSqEKIOieNqkjlpIJ9q+trrDIPcHmKuSO7yLoywim9TmHeVee5PM6tsjR8geP5O86smFwrAqC76fIofSHI4/x358ZSHwvTNkNS5fCn14ZahhDZ93CpKiy/FhZfgv757vUir0VwGKJ0TBnkeuid2+XI3QaVPhZuz3QZ6a/WyzysayAY14BcX0LUBWlU1QvVK9hb+6cydVCqw2q3aVw0i8b3lPVkhFuGd23JovE9aRxbu2fU7bJUmAsZsy1zALxRGTRBK11N4qIdviw+Rh/2Zd36ORsaXOR/YS70vQMUF9X+tUuqGlTgtNfbmu/1Ja9FcMwe0YWpDhpWHpcjd3vA//5s9XLvAXfKP1gaYAG9BqzBqRLtPkd0A8t2IUTAyeK/diJq8V+AA5mwfCzEJsCJfZZtigI3fAANkzEamrI020RmTgHrd+VTYYYFY7oy9qK28iRZeGzfsWIuefob9DqYPrgjfTsk0ad9kntlyZ0FaP/2OJzdG167vPa+GgvR2jOZVb7fc5yNf+az40ARP+0vpMxkZvbwNCYN6hAxZX3NjkPMWP4zLRvHcs2FbWrnv7uL/N6TXftp/aFfYPHg2sfWyPeaeb39r0KKjWbuurQDM4emRUxei+C4/8PtfPDjX3RIjqd7mwTG9GxDv47JnpWj71+GL+aAanZykGIZ2eFGtD9napb/Xw4UUlJe9b7ntWrEZ3cN8uk9nCrMhVOH4cR+WDHJsi0uGcZ/BKgOF0kXQviHBKqIZK8Ntfy/WjSgymE7gAGYPK+IyYM6MOjf68ktKOGcsxrLjY/wimKN3B+l575hae6/MPd7uOhW+OkNxzc+vWdAvzssN/ce0usU+ndKpn+nZABGvbSJ7QcKad+8UUSV9TOVN2/ntGhUO/8Lc+HSObD+cecn+dvjHg9/slczrycuyeTb3Udpm9wwovJaBIexwlKmb+jdlkkD23t3kozZro+ZsRWae1BnOVCz/E9a+gNf/55v229WA3wNaPXKlRyv/kBkXlFg0yBEPSbD/yKZG8N2rOIMlrksJUaNyEFCuMG6mKXO05vnJcPgxyXOnySfP67yTSqDJtgPZ7ELmuBOZLv4CC3rxZWfJz6mxrw065wSVw2qccstDVct1nyPS67a5ka+W9MSaXktgqO4zDIcOD7Gi+e/hbmw63PLOnbO/O1xvzSotDSoMSQ34AODNH/zK99TY4i0EMK/pKcqknUfC8nnaA/bmbS22rAd64+W9UdMCE+ZK28YPOqRKMyFc0fB76scH6OPqWpEWXtf7anYel8Bl09i4wyRWdatnyeu5twqd+eUOOuh8jLfIzWvRXBYG+PWh34ecbfcO3qQ4AfR+up1ofXBU8B48JsvhPA/6akSQFWjSp4oC2+ZKjua9IqbjSprD4qzBhVYhuZYb/j98CS2YYT2nlg/T7z9Dai7a1LFJTufzO5lvkdqr6AIjmKjpTHe0JueKndc+nBgzltJqREOyixT2IWIaNJTFems0YDQwenDlm0a0YAaRFkq/8Xf7mHFT3/RvU0T+ndKdj/QgKjXTGaVn3Mtc/cqzComs+q63LjzJLnnzdUjcvnhSawh2vIsafn3+/lmZ37Yl3Xr5PgNuy2L9BaUGKvy3508HvRPGHSv87V5vMx3a16v+vkgfxWUeBdoQNQ71jKde7wYgL1Hi7kkzY06BSwPEo78Zhn29+Nrjo8zxEOPG/2UYm01h/vlnSjhmpc3ERut5/xA1TvWobqKHkqOWbbZD9WVYBVCBIxE/7MTcdH/oCoa0B9fw4anLNtqRANasPk0r27I0Xx5k7honhzTTcIgC4cysvKYvzqbvKJS27aWCbHMHdnFcbkpzIXt78I3C5zPpZq0rnZELjcj0WlZsCY7osp6RlYeD674lcKS8mrbbZ/FvBFWTgezg56iqAZw50/uBafwMN8d5XW8Qc8zY88Pq3wWweOyTLsqN+5GubztKzi7l5epdC0jK4973tvOmXLnQ1/9Xu9ofn4FW88ySLAKIQJEhv9FuoXdLPMhrA0qqIoGVLlgqqObTIDCknKmLdtGRlZe4NMqwk5GVh7Tl22r1qACOFxUynRn5cYaOMFZg+rmz7RDHFufxEbHV21zI2iCswYVhF9Zz8jKY9qybbVuPsHyWRYve4ftBwqg5z8cn+Sa19xrUBXmwul8S75bKTrL36fza+W5s7wuNprCKp9F8Lgq026Vm+ELcLn4bXQcNPY+yqUr1nrRVYMKAlDvSLAKIeqMNKoinZMKVtVFcbdxhlunmb86O/CTbEVYMZlV5q/ORqtUWLdplht35/k0dbAQ52tDLcsElBdXf8Pl19oeFNRkrDCz2EmDyl44lHWTWWXeJ785PWZF7HzO/+GflsiKjrg7cX1hN1h+XY3lGcyWv5dfVy3P3c3rcMhnETzulGlwUW6si4hr1kp2pm32aekAZ5zVi8747XroPtYyJFfLpLWW/UKIgJBGVaRzUsGuuvBNVpoHuHWavKJSMnMK/JkyEeYycwpq9VDZU9EoN9bgFK44Wy/Jiyexb23Z5/ZNTjiU9cycAg6fLHO4vzVH+ayiF04Hd3e9zv0bSw+WZ3A3r8Mhn0XwuCrTVk7LjTt1y+AHq8/T9DNX9aIjcj0IEf6kUVWP5Z30rOLPP+X5D4WIXO6Wh2rHuRucwlmYYy+exO4vKHH9vnZCvaw7S19rjrIpdiZXRmXiNBDjtf9z/w09yHNP8jrU81kEjydlQfNY6wLXzob+Rcc5Hw7rB76Uab9dD9YAVdYHITGNLX87i/AphPCZNKrqAwdzUFJji+mq7KU1R906TfNGsQFKoAhH7paHascNX2CJSuVM5yt9SJW2dolxHh0f6mXdWfo2xc50fQJXC6I65Xy+iid5Her5LILHk7JQ69hqC1w76Sf9x6qADftzmLYgvdamMBeK8y2LeVvrWrPJ8ndx7fmPQgj/kUZVfeBgDsrw7XfyaczDbt2EtUyIpVdqYgATKcJNr9REWibEOrzFVqhRbqzzHVQXk7fPOs/5fmvQhFj7oAl6h0ETACb0TXE1dd0mHMp6r9REWjTWDoE+3ziBCtVF1d7jJs/f1PpwJrGD3cbaAULczetwyGcRPM7KtD3NcuNOD7ghPqDBKays9aKn/HY9LOxmmVv62uVgqhxOWV5s+dvBnFMhhH9Io6o+cDIHxYSemW4Eq5g7sousLSOq0esU5o7sornPWlKqlRtf51JZWYMmlNoHTTBpBk2wMkTpmDLIvXkU4VDW9TqFeVdpNz7nGt4iSnESVRG0oyq6Yn04U/Cn3Ua1VoAQd/M6HPJZBI+zMm1Ps9y46gGPagBTNwW8lwqq6kVPS7bfrgcP5j8KIfxLGlX1gZP5EPop62gxYILDH4CmcdEsGt9T1pQRmoZ3bckr43vW2t4iIZZXapabMenOb3x6z3A+l8r+PF7cNMwe0YWpg1IjpqwP79qSReN7EhtVVY235ihPl1+L0ybV8Kec7XXMg3x3ltfxMfqwymcRPNYy3SQuutY+p9enqx7wijMBDU5Rk7VedKfHyu/1jkT/E6LOyOK/diJy8V8rFwt3GivMLN2cw3/X7uZ0meWW7KzGMWx+cIg8TRYupTz4me3fHZrF8+U9g6uXm8Jcy/poX8+Hveu1T+LG4r02PiwAbC3rW/cW8PXOfAAWje/J0C4twrKsP/rpb7z23T5bgAqXfFn408N8t+b1a9/lcPhkGTf0OpvHRncLy3wWwVNWbiLt/zIAmDQglUs7N6dP+yTtcmNdSHz9445POPwp6DMtQKl1zGRWLVENi86Qf6qU7EMnyTl2mh0HTwGw7LZe9O2Q7P/rYVcGvDOu9vYx6ZDcCeKSoElb/76nEAIHjx1FRLHNQWkCpYWWbTq9JSJQ5RwUQ5O2TB7Uga9/z2drZVjXBtF6ufkRHktoEF27QeXO0D9PIlOdOqy9/dhuQHV602CI0jF5UAcmD+pA5//7nNJyM+e1Sgjbsl5WYXkI4laD6tKHfXszD/Pdmtd7j5XwTmYuLRMahG0+i+ApM1X1td43LI3YaAc93O7WLXXQoALLUMC+HZKqbSsuq+C8uV8AcGG7xMBcD1oNKoAVk6v+7cvDFSGEJmlU1QdaPzpmuzkoYKtgo/UyIlT4ptZNgr/mUtnz001DvCGK0nIjJUYXwTNC2Bmj2Tbs7+6oFY7nUxnioceNvr2Zl/keb7DcFBcbK3x7f1EvlJRZrke9TiEmyslvkjt1i68PEvysgV0DsdhYQQODi2io3hiTDiung1njetNFwehX/P+eQojwnlO1fft2zj33XLZu3er0uJKSEv72t79x2WWXBSllIcbLOSgyLlR4Q1dzcSRXk8h7T3dvLpU9P03GjosJ/5v90goTm2Jncl/0h84DVExY6ftEfS/zPS7G8hrrzbIQzlivxziDHsXZYmvOyiP450GCn+l0CnGVDamAXQ8yr0qIOhG2jap9+/Zx++23Yza7iHIFPPbYY+zfvz8IqQpRHlSw9r9fpeVyAyQ8V6unytUk8q1ePDX1001DvCH8b/ZLjSbXYdSj4/wTTtrLfG8YAY1XETzW67FhjIvBNG37wOiXHe+/+tWgRPzzVFxlvSPXgxCRJSyH/3311VfMmTOHoiLXw3u+/PJLVqxYQXR07WhCojb7uCX5J8u4Kf174mL09EpJYmK/FAzOhmKIesVkVvl+z3E27am+eHS1NlVhLlw6x/Uk8jpgMquYKh/KvLB2N1v2HqNfh2THE+JDjDUIxLbcE7xmeMv5weUldXpzaZ0Ts/mPY1z7ymbaNG3ANT3b0K9jACbpi7BmMqt8n3MMgDNGE5v+PKZ9Tbozn+q98SE3d8hkVtEplt/ZBz74hegoHbFRepIbxqDTKbRu2sBhPWRf5x48cQZVVTl22khphYkYvQ5FUSgzmTm7aRwT2x6lR2xTlCgDnD5iOYFit66cBKsQwu/CLvrflClT+Pbbb+nYsSOdO3fm008/5c0336R37961jj1y5AhXXXUVV155Jd988w0A69atc3juiI7+dyATlo+1rNdx6pBlm6LADR9Aw2SISyLjr2juWP4zFWbtIqEoMGVgKrNHaK9NJOqPjKw8HlzxK4Ul5bX2RekUXrzxAoa3KXdvzoO3Nz3WMm2ugDJLNK2aZdrRTYOz9DeJi+bJMd1COuT3gjXZLN6Qg4oljPrV+o3MivoQ7faJAmMW+2/IT9FBSL8EzhRVLS4a3QDu+Emz4ZaRlcdd7/6CsaL2qIJ4g55nxp4f0nktgsfRdal5Tc5LcH3CMekhNdTNWb1TU83P7MlrAfbFag17VKg2sD/EGpxChLuw63bYu3cvs2bN4uOPPyYlJcXhcaqq8uCDD5KYmMgDDzwQvASGKuvCndYGFVjqVruFO6ct2+awQQWgqvDqhhwWrMkOeHJF6MrIymPasm0Of9wrzCrTlm0L/CRya5m2NqigVpnW4ir9hSXlTFu2jYysPO/TFkAL1mTzql2DyjqfynGHj+rfG0vVBOPehlZ265NFx0Nx5RPwwlzbZmteazWoAIqNppDOaxE8zq7LWtektQdccXILc+nDIdegclbv1GT/mT19LcBM4wzK1ZpzWSt/32URYCECIuyG/61ZswaDweDyuNdff50ffviBd955h9hY1wvwRTzNaECWClbVRTFPud3tU6VvzOHev3WWoYD1kMmsMu+T39w69jn9LdxtfhPF0Xyq6DjfJpE7KdOOIlx5kv75q7NDbu0qY4WZxRtybH8HJYx6TVqN1ZLj1devmleEyawyd1WWW6cMxbwWwePudWkrJ+48sOk01A8p8w9P6p2a5n3yG96MJ1plHsCfxtZ8FjOn9s5Ja91fE1AI4bawuyt2p0G1c+dOnnvuOWbMmEG3bm5UvvWBkwnmvw5fwdLi2sMnHTGr8NaWfX5KmAgnmTkFHD5Z5tax95hed9ygAt/n+XgRNMGT9OcVlZJZuWZbqHhry75qUTm1n0bbCUT0M82Ia7WfgGfmFHDklNGtU4ZiXovgcfe6zCsq5Zdff63spXJR7j1Z9y7APKl3ajp8sowjp7x7rVV4TfIQInz5pVG1dOlSTKbQiJ5VVlbGvffey3nnncfUqVPrOjlhoaDEvRsfe/sLSgKQEhHq8k+VunWcdd0kFSc9D3UQoMLd9Ht7fKDVvO5+NKdxX7mTei4Q0c/cbMyGe16L4PHku7/w44GWwDfOHthM3RRSUf/qqmxHqxUUqA0pJqZqo32wCruhukII33k1/M9kMqHXVz0lWrBgAR988AGzZ8+mf//+fkucN/7973+Tm5vLsmXLqkUHtIZeLygoIDo6mkaNGtVVEuuOyQgNmloeW5UWWrYpCs2Vk3RVDnFCbcRB3Hu61y4xLnDpFCGreSP3htK6NSytzzTfElOYC6fzLWX6zAnLNkUPsY0t2wtzawWqcDf93h4faDWvO618VlW7pRECEf2sMBeO7tLed3QXxCVCk7Zhn9ciePz+3Sel+vd8Pqqrsr0ydm7tjdZ5p1YSrEIIv/G4p2rnzp1ce+211bbNmzeP48ePM2nSJGbMmMGBAwf8lkBPrV+/HqPRyNixY+nbt6/tv7y8PPLy8ujbty8zZsyos/TVKevEfmuDCkCFLutv5dOYh927EcYSMntC35SAJFGEtl6pibRoHOP0GGsvlclZ9eKPeT4Lu8Hy66oaVGB5en3mhGW7xrwLd9Jv1TIhll6pib6n048m9E2x9f1Z87lCrd4baG1QqSiBmYy+sBt8PEV738dTbPneKzWRsxq5Hq4NoZnXInjcvS5bJsRivnqx86F/dbREgzOe1Ds1tWgcw1mNvHutBKsQIrjcblSZTCaef/55rrvuOgYOHFht3/XXX88XX3zBTTfdxIYNG7jyyit59tlnKSkJ/hCx//znP7z++uu1/ktOTiY5OZnXX3+df/7zn0FPV0hwMhfCrOiZaXSvsTl5YKoEqain9DqFeVed5/QYazQ6PU4W5vbHPB/N8lzJwQ2DO+m3mjuyS8gFTjBE6ZgyyPIU3prPUYqDJRD8HfXPys181+sU5o/q6tYpQzGvRfC4e10uuCwBXbNz4MKJ2gf87VHfe8ADwJN6p6Z5V53H/FHevXaVeQCjjY9o7/RgkXQhhHvcvjNOT0/nrbfe4pVXXmHWrFm19jdu3JiHH36Yjz/+mAsuuIDFixczbNgwVq5c6c/0unThhRfSr1+/Wv/FxMQQExNDv3796NrVvR/6iONkLoRu8jquuPEumsQ5XiRZUWDqIFmnqr4b3rUli8b3dFhW7q24A7OzJ8mDH/TPfAcvAlWA6/Q3jYtm0fieIbt20uwRXZg6KJWZxhlUqAHuDdTiQb5b8zrOoF0e4mP0IZ3XIniclRXrNXnJ50MsyyX8uET7JF/+X2AT6QNX9U5N9vWQ9bUJDTybsREfo2fOiM7eJFcI4QW3r9AWLVpQXFzMli1b6Nu3b7U5VfY6derE0qVL+eKLL3jqqaeYPXs277zzDnPmzKF79+5+S7jwgou5EMPbJTL04aG2Fdv/Kijhh30nyDtZRp/2ibx5a2/poRKA5QZhaJcW9Hnia46eNnJhuyb8tL8QgMRzB6Hr1h1WaAwRi2kMHYcEIEU1FrV0wZp+a1lf8t0+SivMPDa6Kzf0ahvyvSaz+zXklaIL2fTbeQyO+rX2AbEJ/o/6p8l1vlvzevMfx/hw2wG+yD5CabmZB4elMXlwh5DPaxE8w7u2JK+olPmrs+nQLJ4rurakb4ck+rRPQn/ygCXq3zdPOg5SEYJD/+zZ1zsb/8xnx4EiSitMqGb4+a+quU23X9qBWUPTql0bw7u2pEurBAb9e321c3Zt1QhDlI4YvQ5FUfj5QCFnys3cN/Qcpl9gQH9sF8Q2hVL35p0KIbzndqNq9OjRtGnThjlz5rBt2zbeeecdp8cPGzaMSy+9lPT0dNLT07n++usZNWoUs2bNolmz0Al1Wq84W9ujco6Efl4R/Tsl079TMgDPfLmLF9b9yTlnNZIGlahGr1Nst9MzLunIbUt/BGDOH2PhDwcvKjtpmdvnr8nR1uArMQlQuM+yzT66VVySw5sGvU6xlfWM346w92gxHZs3DP2b/MJcWNiN6eC4Bi8tCmz0M2u+GxpCUeUcWif5rtcpDExrxsC0Zox5eRPbcgtJDYe8FkF3ptzSYOrZtin3DUur2uHO2lQhOPSvJvt6x+pwUSl9FlT1/rZpGqd5bZSW125MLhhzPt3aJNj+HvfqFrbmFJDSLB798+fWToD9vFOQQBVC+JFHd8kXXXQRq1atctrjZDKZyM7O5t1332Xu3Ll8/vnnGI1GzGYzH3/8McOHD2fp0qU+JxzgzjvvZNeuXfTu7XqNpXXr1rFu3Tq/vG/Y8mIOSpzBcnxxWWiEzBehxVouGjewDGlpzVG+ajEJHIVSV3T+nRxtDb5ibVCBJfzd8mstw4TcuRED4ivLeYmxwsWRIcCdzxToJ/bWfC+yC0pkjSrmIt/jY8Ior0XQlVTWKdZyYjN8gfMAFX3vCGCqAisupvrnKi7Tvja0tkdHVa9rbddXmcmr33whhPc8DqkeGxvL7Nmzq2377LPP2L59Ozt27GDnzp2UlZWhVq4217RpUwYNGkTPnj1p3bo1r7/+OgsWLGDdunW8+OKL9TO0eV3pPhaSz4HFg2vvc7DCenxlZS83QKImk1m1PVVuHGtpVG2KnQmHnbxINft3cvSYdFg5Hcwa5VMXBaNfces01nkcYfHwYPgC+OJhh0OgTvWYTKNAP7HXzHe7qGJO8j2s8loEXXHlb02tuVUZszWOtrPlRRj2eIBSFVhx0dU/a4lR+9rQ2h6tr/5s3HZ9GSvgYs9/84UQ3vNqnaqa7r33XgB0Oh0dOnTgggsuoGfPnvTo0YOUlJRqx1555ZUsW7aMJ598kieeeIIFCxb4IwnCY+7NQbE+wS92UMmL+uuM3VCUxg2ibCG+Z0WvQOco8p+/gyd48aBAS8Nw6j1xcXPZ6Jd0GP10YNPgQ76HVa+gCDrNnqrCXMt8qvVPoP27pcCYxUFJXyBE1WgYFTu4NrR6qgw1Xlt1fVXWz6ccPOU6thtQnQ6RFkJ4xi+NqjvuuIMLLriA888/n4YNG7o8fvz48fz222+sX7/e5bHCz2xzIeKh6C/LNidzIRpEWyrsX/8qZMqbP3JxSiIT+6XI/CrBqTPlgKV5/tuhk+6tcxaI4Al+uGmIrSzn/9uwhzc37yM2Ws/ZiXFc07MN/Tomh87cn8JczJfMQflmAYpGw1VV4fRljxOU/n8v890QbcnL5d/v55NfDlWuUZUk9Uo9ZzKrfL/nOD/tLwDgSNEZTGbVcu25HPIaoOUDgsRkrt5Q/PSXg/yaewIUhTPlFRgrVAx6haOnjbVeW7Onynp9vZe5nzU7DvHZiXHab7pictW/ZV6VEH6hqNZxekG2ePFinnvuOX7//fe6eHtNQ4ZYopKtXesgXHAkmJegsbFGr1VlBZuRlcfd7/5CaUX1mzdFgSkDJbR6fZaRlcf/rfyNo6fLAMtcqqv1G7k7agVRioNeqsEPwqUuhvB4Q7NM1zzG8U3DgjXZvLohx+H+eIOeZ8aeHxphv934rMfvyyepoXeLhfo7LTXz3VleS71Sf2Vk5fHgil8pLCmvtr1JXDQLhyVySek651H/Ln0YBt8fhJT6X0ZWHvNXZ5NXVOrV6396+HLb9a51fY3Sfccz0Yu062XrUN0wbpAKEUrq7LHgqFGjeOyxx+rq7esvJwsA209czcjKY9qybbUaVGB5Gv7qhhwWrMkOcGJFKMrIymP6sm22BhXYL0TrZMHfnv8ITIJ8mIztqkEFlqGv05ZtIyMrz5dU+iwjK4+ZxhmUq44n6/+n/Lrg9ap5mO+u8lrqlfrJ+ltTs0EFUFhSblmbav3jjhtUEKTlA/zPWpd626ACeGGdJdSqo+trlXkAo4yPar9YFgAWwq/qrFF11llncc0119TV29dfbizcaTKrzF2V5fJU6RtzMGo0ukTkMplV5q/OrjWrwdXNvt8W/NXi5SLAxgozi100qOzNX51da5hOsJjMKvM++Y1V5gGMNj6ieUyB2pCPTIMIWhI9yHdP8lrqlfrDWq6dmWmcQQV1VLcEkKO61FNvbtnP6dIKt66vuhmXJET9IQPY6yNncyEO/cwvv/7KkVO1x27XZFbhrS37/Js2EdIycwo0n6r+aE7jvvKp2i8K2IK/vnlryz6PbmjyikrJzCkIWHqcycwpQH/yL7oqe+mgHKy2z6xaeqb+aZzEYZL4JfdEcBLlYjFxCnNtf3qS11Kv1B+ZOQUcPlnm9JgfzWncawyvusUdjupST5lVuOe9n51eX9FqBQVqQ46pjW3bVOzmUttdq0II7/klUIUIM+84n7h6IQDL3TrV/oISvyRJhIf8U9o3AU6DVPh7wd+aCnPhdL4lAMuZygaFooPYBMv2wlzNgAnelF1Hnz/Q8k+VVstjVbXMQVJV0CmW26n0mIWklC7neLHrByJ+4cZi4tbv3NO8lnqlfnB1PbXmaN3WLQHkz7ok98QZp/tXxs61/KPayODK9fyswjAPhQg10lNVH7mYC/FH/2fdPlW7xDg/JUqEg+aNYmtts4ZSr1CDtOBvTQu7wfLrqhpUYFkP68wJy3YHN//elF2tzx8MNd9XUar/v9qxjYMQpAI8mlPlaV5LvVI/uLqe3IooGqYL2PqzLmnbtIHT/VrDs21VhywCLITfSKOqPnIxF6L9kFs5q5HB5Wl0Ckzom+LftImQ1is1kZYJsdUeeFYFqXAwAMXfC/7W5GWgigl9U/AkpIMl9Hei5+nzg16piczVz6Rc1a6yy1UdM40zLMemJAUnUR7MqfIkr6VeqT96pSbSwslDAJdzNS99OGwDLVjrUl/pFHhu3AVOry9nczElWIUQ/iONqvrIxVwI/ckDzB/V1eVpJg9MlXVl6hm9TmHuyOohr9268QkkLwNVGKJ0TBmU6vbbzB3Zpc7Wq9KfPMCwSwbyTsVlmvsfL7+JVeYBAETrg5hGF/MzrXM1PMlrqVfqD71OYd5V52nua81R9qituNfRXE2ATkMDlLLAs9alvl6tkwem0jA2yun11ZqjdKyci1krWEWN+Y9CCO8FbZ2qzZs3s2jRImJiYrj44ouZPHkyitbYlTpUL9apArfXl8nIymPW+9urVmavJOvJiIysPO79YDtNyg7TVDlFe+UQzxtern1gbAJM3xL46Fy7MrTnCo5Jh+ROThcAXrAmm8UbchxO9I6P0fPMdXW8TpUb12xKqWUeZM6CEcGrWz1cq8pZXku9Un9prVO1L9aNMOn3ZIdl5D97vq5Tte/JK23/dnR92eelCtoNOZlTJYTPgtao+uSTT3jggQd48cUXefvttxk4cCC33nprMN7abfWmUbXjfVg5HcwVtffVWAzQZFbZ/McxnvpiJ1mHTnJeq0Z8PGOAPEkW/GtVFo/83N/1gcH4sfZxAWBjhZmlm3PYuvc4eUWlHCos5cSZcsb3OZv5V3Wrsx4qwPIUefu7Dhc/VYH/cAsvl1qe2tvfZAWcB3WJlX1e/5F/mv0FZ2jROIYND1wm9Uo9ZjKrDHhqLXlFZYzu0YoZSdvotOUBFK2yBfC3x6HfHcFNZICYzCqZOQUcOlHCtgMnOFJURklZOSgKZ8orMFaoGPQK5WbLMOQf9xVw4owlX2pe7zXrsiOnyuhfso5nDa+iR2OtL1kAWAi/CVr0v/79+/Pmm2/Sq1cv+vbti9EYpAhVorbuYyH5HFg8uPa+SWuhVQ/bn3qdwsC0ZhwsOsODK36lZUIDufERAJwxmphpnMFzMa+ic7Qw5/CngpOYMemub+6dMETpmDyoA5MHdQDgwY928O4PB2jRuEHdNqjAeZQ9LE+d34+6EqiDOtWDusTKPq+/33uc6xd/T1xMlNQr9Zxep6BU9qFM6R7NOU16wlmv2KLSVjNuGZw7MsgpDBy9TqFvhyQgiWsuOtvl8Zf8Z72tUVVTzbrs6S928eL6AXTpfDFTd95S+wUOrlMhhOf89iv26aefOm0oJSUl0atXLwDi4+Np2rSpv95aeMPNuRBWcTGW9ndxmZNV7UW9UmI08aM5je+6Pqp9wKiXoPOI4CTGy3lVjsQZKsu7MQTKu7NAHBD4OWuueFiX2IuvzOcSqVcEVddbl/f7w+JLtBtUAO+ND16iwlxcjGW+a1TxEe0D3LhOhRDu8VtP1X333UejRo0YMWIE11xzDd27d/fXqUUguFirCqg2XCreYKmYS4wOhmKIeqfYWGEJefxr9e22MfurbrdsCNZYfWc396hO51XVFF95I1JSFgLlvW0fGP0yrJhSe19MY2g/GDbW4XwID+sSe9YbvmKpVwRVvy9Fgx8hYcN8zeGuAFzyYBBTFd6sDy5uO+Agz9y4ToUQ7vFbT9UzzzxDjx49+PDDDxk3bhwjRozgf//7H/n5+f56C+FPHoahDqkn9yIkxJUc4unyazHXqEZsg+UCvT5VTc5u7hdf4nIYnb2QKu8Lu9VqUNlmwloXP61LXoa0B2hY2QNeYjQRpOm9IkQZK8yUmyxlIOHbfzluUIFlfqFwS3zlNfZq0oNeX6dCCPf4rafqyiuv5Morr+TYsWOsWrWKlStX8vTTT7Nw4UL69+/PmDFjuOyyy4iOjvbXWwpfeDgXIjbacuN84Hgx17y8CYNeQafTERejp1dKEhP7pciciHrCZFb5fs9xXj46EZxdzoFen6omH+dV2WtgsJTlTX8c5dpXNtOmaQOu6dmGfh2TgzLHyjpxPf9UKV36P0vHzfej2N1kWoP7mdHD1a/A6oAnyTEv5lVZxVTWGSazyg3pWyg3qZzdNC6oeS3qnsmssn5n1fC03/s+Tefv/1mtzNsoerh6URBTF3rsH0Bs2XOcXqmJDq+VBpXX2OITF2JsNo87j2gMFx79iiVKamGu2735QojaAhr977fffuPLL79k7dq17Nmzh8aNGzNq1CjGjRtHhw4dAvW2Xqs30f+s3AxDnZGVx93v/UJpudnhqSQccv1gH/p4lO47no5+lWhF+4ny7vNmcs51DhacDJRDv2jf3E/51u3J2BlZedz17i8YK2qX93iDnmfGBja8un2I5dYcpalyis7Rh3la92KtY28pu4+fG/TGZFY5VaodDSzgCnNh/xb4WGN44tWLoV1fzRu1jKw8HvzoVwrPlNd+HcHJa1H3aoZTt5b5fjF7eIjXa79g9MvQ46YgpzJ0ZGTlcfvynzGZq27dWibEMndkl1rXSkZWHjPf/YWyyrrMrTD1MgRQCK8FtFGVm5tLRkYGX375JVlZWbZeqoqKCoYPH86jjz5Kw4YNA/X2Hqt3jSo3wlBnXLuTacu2uX3KqYOkYRWpMrLybGXBeuPjaH2qQjWOK8qeYu74ocG9KfZhvSqo/hmdWTS+Z0A+V0ZWHtOXbbOtM+POTZB1fSqroDeqvAhn724+Q+DyWtQ9rXIgN/6O1awfrKx9VK/YXStaeTtRl8G86DfRXMZOQqsL4TO/j9cqLCzk7bff5vrrr2fYsGE8++yzlJeXM3v2bDZu3Mh3333HnXfeSUZGBg899JC/3154wsVcCPPVi5m7KsujU6ZvzNF8wi/Cm8msMu+T32x/b4qdyacxD2sv+As0UUo4TBLzV2dXe6IacD7MqzKZVbfLeyA+l8msMn91drUbppnGGZSres3jVRX+ZfyHX9PgFQ/nVNUsS64EvQyJoHBUDpyVeSB4yzSEGK36wcq6zXqtOKrLlpqHc7VxvvYbeBElVQhRnd8aVV988QUzZsxg4MCBPProo+zdu5frr7+eDz/8kFWrVjFx4kSaNGlCQkICM2bMYMCAAWzcuNFfby+84SIM9daGl3PklGdr35hVeGvLPt/TJkJKZk4Bh0+W2f5252ZfBfKKSsnMKQhSKvEpaEJmToHb5T0Qnyszp4C8olLb3605yh61FfeWT9U8forxbt40D/drGrziYTj7mmXJlaCXIREUWuXAVZln3DLoMy0IqQs9NeuHmuzrW2d1WXnlVHqJCyOE//ktUMXMmTNRFIU+ffpwzTXX8Le//Q2DweDw+KZNm3LBBRf46+2Ft5yEoS4ryKc1RzlIM49Oub+gxA8JE6Ek/5T2zb5WT9UU4918pfbSfG3A+RA0wdN0+vtz1TzfptiZTo9Pj1lYa+hfnfEgnL03+RbUMiSCQus7dVXmeW98vR365+414Oq4aLWCArUh0VTQiMpjFQVOH7WsV+XB0hNCiOr81qi64447GDNmDK1atXLr+H//+9/+emvhCyfDpS4BNsXWnrPhSrvEOJ+TJUJL80axtn97erNv/9qAK8yFo7u09x3dBXGJDm8YPE2nvz9XzfPNNM5wGAhEVWFueQgM/bPyYK0qb/ItqGVIBIXWdzrfOIE50W8TpTgYQl6P16dy9xpwddzK2Lm1N6oqLL+26u962nAVwld+G/53xx13uN2gEiHEyXApVRfFv/R3eXQ6nQIT+qb4IWEilPRKTaRF4xiPXqNgiUrVKzUxMInSsrCbdhQ6sGx3MqeqV2oiZzVy3LtuLxCfq1dqIi0TYlEIo6F/Vh4Mu/S0LAW9DImg0CoHcw1vOW5QQb1en8q+ftBiX986q8uczlmT9aqE8IksLFTfte0Do7SDDSijXuayv43y6HSTB6bKelURSK9TmHfVeYD1R1n7Oy5XFWYaZ9h++OeO7BLctYZ8mFOl1ynMH9XVrbcJxOfS6xTmjrREznQVCCQ9ZqFf39tnHsyrsi9L7gh6GRJBoVUOnNUtKPp6fcNvXz/UvBpq1rfO6rIfzWnc52jO2qiXLfcEQgivyN1vfefiyf4lnw9h0fiexBmcRGPCMiRbwqlHtuFdW7JofE++jb2Ue8u1J4vfWz6dVeYBtEiIrRbeN2i6j4Vxb2vvs1/g0gHrZ3RU3uNj9AEN8T28a0teGd+T5/S3UOHg5lJV4VnjGNvfTeOiaRTrt5Hc3nM2r+rQz9Xy3ZrPTeIcrx4d6LwWdc9aDqzld5V5ALcZ79M++IZ36310Omv90CKh+hA/rfrWUV22KXYm/3XwsMZVb74QwrmArlMVburdOlUAO96HldPArLGAq04PoxdB97GYzCqb/zjGh9sO8NeJMxj0CgcKz/DXiVJ6tk3g3Sn9pIeqPijMpeL0MR55+XUeMbxp26xieVr60wWPY+x6A71SE+uud8GLdZNqsi/vX/x2hNIKM7OHpzFpUIfgfC43PsO/e2+lf6dk+rRPovcTX3PstCXaV9DXqbLyIt9NZpXv9xxn45/57DhQxPa/Cik2mrnr0g7MHJomPVT1xOY/j3H//z6lbewZbupo5O9//qv2QTe+B+eE0JDXOmQyq2TmFJB/qpTmjWKd1rfWuuypL3aSdegkdyT9xL1nFqK4+M0XQnguBB5vijrlNFraOlu0NL1OYWBaMwamVUUCTN+wl8fX/E67pIbSoKovFnYjCnjEYOkxsS4iaf05v/DnOTDqjrpKncXwpyDjn9r7rAtcumBf3ke9tIntBwpp37xR8G7yx6RT/tFUojXml5jRoxuziAe6dw5OWtw1Jh1WTgdzRe19DvJdr1Po3ymZ/p2SAZi4JJNvdx+lbXJDaVDVI6UVpqoAOH86OGj5OAmgUEmvU+jbIcntYwemNeNA4Rke+vhXdjYfgTL0Kpe/+UIIz8mdsPBo2I69uBjLsILiMo2bKBGZxqSjVs5ZUmoN7A+ROQ99psFtX2vv82KBy/jK4TMlxiCW8+5jHQ6D2j9sSWg+SfZx6CVYhvxBkPNa1LniMhMzjTOowMEw81CpW8JYtWvLy998IYRz0lMlPAqHbC/eYCk+JUaNYQQi8hTmQnInCoYuJOkLjd6oG5aHzvCckuPa2zXWTXIlrrKcF5cFqZwX5kLJcZoop6ttNmN5ChbrfHpj3fKyLrEKel6L0FCYyx61Fa8lP8DUYwtq7w+luiVM2a4to8nn61QIoU0aVcKrYTuAbQJssTxVrh8qJzA7HHQSSsNz/HjT0DDYvSeV+fy83RBLlaphBS3XTIReIZLPNfk49LJhjPVBjdQp9cnI9cMYGQMcc3BAKNUtYcrWU1VW4fVvvhDCOWlUCRfzqtY6HGPdINpSSf9x+CTXvLyJmCgdzRrF0iaxAf06WCbQy7yIyFEx6lV0n8xApzroRRj+VHAT5IwfbxoM0ZbmzNtb9vHxtr+IidLRwBDF+W2a2AJF+LWc26W95py1clXHzj5P0cWshua11WcatL4QXru89j4ndYmVIcrymVZu+4ufco6j6HTExejplZLExH4pMnczwliDKGyJm8U9xf/VXOgaCK26JUzFRll+r3MLirnmu9akJT7HE8furH2gG9epEEKbNKqEhbMx1hrDpTKy8rj73V8AOG0081NuYbWXvbR+D03ionlyTDcJiRwBFqzJ5rMNpVyom6oZjnfHhU/QvfOIOkiZA9b117SWC/BgLZYFa7J5/4e/AMgpOFNt36Y9x3n5Wz+X88ohlox+pXqvWqUpxlms/7Y1TX74KjSvrcJcKNirve/oLohLdDjscsGabBZvyAHgQGEpBwpLbfu+ys7nic9/Z8pAWbYhUmRk5THr/e00NR6mqZLIX8pU7XXZxi2Dc0cGP4ERJCMrj7vf+wWAsgqVn3ILaaTsh5jqAYcAr4ZICyEsJKS6nXoZUt3Kg3DIGVl5TFu2ze1Ty1oz4W3Bmmxe3ZDDvtgba+2r9YMcKkN0/BBW3fq53eWXcu5GulNKl9d6zwsf/YrjxXUcUh28zndP8lrWwwt/9r8hWvVKLaFSr4QhR7/XYVWfCxEmZCyFsBiTbhkWpUUXZYu8ZDKrzF2V5dGp56/OxmSWtns4MlaYbb0HM40zKK+xIK31B7hc1TE3ambofM9j0i1rrmjRuY4kZv+53eWXcm4XXbEmVYV/Gf/h//f0JzfrEXue5nX6xhyMFbVDzYvwUPM3xFKvaF+rKsjQPx84+72eaZxRa4Fxa32uOrhWhRDOSaNKWFiHS2mxGy6VmVPAkVNGj06dV1RKZk6BrykUdeCtLftQgdYcZY/ainvLp2keN8U4i6Wne4fO99x9rGXNFS2T1rkMSW793J7wSzlv24c/+/5bc9e95VNZa75Q8z1rhbevK16EVfc0r82q5TUiPNX8DfnRnMZ95VM1j/228zwIpWHFYcbZ7/WP5jSH9fmfff/t9hBpIUQVmVMlLCojjmmyzkuZV0T+qVLHxznh7etE3dpfUAJQtTCnA6/HPE1K6fLQ+p49nCdoz/q5PeXz51/YjU41NlmH5DxreBWoPvzPL+/pbx5GXvQmr739fkTdq1leteoWa5m/ZOc82DlPhqF5yVndYJ/vtiijlf/vtGkWbELyXQgPSU+VsHBzuFTzRrFend7b14m61S4xDnAxRMduWFpIfc/Obu4XX+L0QYL1c3vK588/Jh1zjQVQ7YdYzjTO8P97+puz4Voaw4q8yWtvvx9R92qWV2fDis3oZBiaD5zVDfbD/2xRRq3D/2SxZSG8Io0qYeHmcKleqYmc1cjg0albJsTSKzXR1xSKOjChbwoKsMo8gNHGRzSPGW2cz5vm4aH3PXsxv8fK+rk94fPnr4z8p16tHe59inEWq8wD/PuegdBnGtz2tfa+SWtrDb30NK91iuU1IjzV/A2x1C2Pah5rus31UF3hmLPf61XmAUwyztLcZ3YwVFcI4Zw0qkQVZ8OlDv0MhbnodQrzR3X16LRzR3YJzTV1hEuGKB339Y6lq7KXDsrBavvMquU7TeQUEILfsxfze6wMUTqmDEr16O18/vwLu8HiS9BrhYHHMsTS7+8ZKCXHtbfb1SVWnub15IGpsl5VGLP/DWnNUad1S/SZI0FPXyRx9Xv9hkadAljqIBe9+UKI2iSkup16HVIdPA6rPuv97ZQYHSzWCDSNi2ZBKK6lIzxjVy5qjr23yrh2Z2h+zz6GVreuneSskvRbOd/xvsMFi1UV5pb/gzfNwzXf86LHvuLY6RAIqW7lRb67ymtFQdapiiAZWXkM/7Cz7W9HdYvM6/Gdo9/riboM5kW/qR3oxrpIuvQUCuE2aVTZqfeNKic3dVoVrMmssvmPY3y47QB/nThDaXkFv+WdpmlcNC/e2JM+7ZNC8ym68IyTcmFGD1e/gu58B/OX6tr3iyDjn9r73LxpMFaYWbo5h617j5NXVEpMlI5fDxZRboZHR3Xlxt5t/VfOD/0CiwfX2jyqbD5Jaf04t2Vj+nVIrnVthVyjysO6xMqa15k5BRSXlrOv4AyHikq5OKUpb0/qIz1UEWbrylfo+fMcohWNh3OKHq5eJDf1flLz9/qn3EIAeih/sDJmbu0XTPkWWvUIahqFCHcS/U9U6T4WYhprT/C3Hy5VGTFNr1MYmNaMgWnNAPg59wRXv7yZOEMU/TsmBzPlIpC6j4XkczRv9nVT1oX2D2+fadD6Qnjt8tr7Jq11K+2GKB2TB3Vg8qAOtm2XPfMNe48W0+mshv5pUBXmWobMHfuj2mazqqBTVBI5xfyrunJ2uARosC7RoDWU0W6Jhppq5vWL6/7g6S930z65oTSoIk1hLscapHBv+VSeN2gs53HDcjhnePDTFaFq/l53mrOGcpNKk8rh27W4ESVVCFGdNKpEdR6GQ7YXH2MpTiVGjafTInwV5sKxXdr7ju2CuMTQ/tF1Nr/Hy5uGeIOfy7rG3AVVBZ1iGUjweszTHDc84J/3CgY3l2hwJa4yn4ulTok8C7txJXClo7hHy8fJ0L8gcDSvyp3ffCFEdfLoT1TnYThke3EGSyjoYifzrEQYWtgNVmgHT2DFlNCfzOxDaHVHbGW9zE9lXSNSYc1Q6taHFmHBzSUaXImPsZzD2dxNEabGpGNSHJQRcP5bJPxmpnEGJhxdq85/84UQ1UmjSlTXZxqM9S5iWsPKmz5jhZlykzlQKRTBVJgLl86xzG/Q4sENcp0Z/qTj9Ct6y34PNfRnr2xlKHVGOw6l/ikDiQmn4W/dx8K45dr7Ri9yO1yztSFZXCY9VRGnbR8+afew9r5RL0HnEcFNTz31ozmN5xvdo73TyVBdIURtYfToUwTN+zdpb3cxHCAmqurG9e53fyYlOV5zUr0II656ccym0J9InvGg432qybK/z3SPThkbbWngLPkuh+/3HGdMzzb065jsXTl3kcevxzxNp/J32LznuMNryT7e0JY9x+mVmlj315wPQ4mtGlTWKTvzTjLlzR+5OCWRif1SZH5VJFjYjasd7Vt1u+X/MuwsYKx1xqbYmVinValQfc04D4bqCiGkp0po8WIIYEZWHn2frIqa+Nmvh3lp/R5u+t9WLnzsKzKy8gKRUhFozhbQBbjUwZPmUDIm3XlPlYc9bQvWZPPZr5Y13XYdOc3HvxxiwpJMus/7wrty7iSPVRX+ZfwH5SbV4bWUkZXHiZJy2983pH/PgKfW1f0158NQYrB8rtuXbwOgqLSCL7OP8Pia30n7v89ZsCbbnykVQZaRlcfcqJmUqw5uQby4LoX7MrLyqKgcTDLTOIOKyu+h1mOYcBiJIEQIkUaVqK3zCEu3vxaN4QAZWXlMW7aNQrsbO3uFJeVMW7at7m/yhOe6j7VEydPSIBF63Bjc9Hij+1i46kXtfcMWuD0UDSwNqlc35GjuKzaavCvnTvJ4tHG+bW0qqH0tZWTlMX3ZNsw1FsY4XFTK9Lq+5nwYSmytU0orag8jVlV4dUOONKzClLXMLj3dm9HGR7UPmrwu9HvAw5T12rJaZR7AJOMs7YM9GKorhJBGldCysBusmqG97+PqgQlMZpV5n/zm1mnnr87GVPPuT4Suwlw49HNllLwqqvV55lXPQ0LrOkiYF1Y5GN6X8YDbwSqMFWYWO2hQ2fO4nNtFV7S+yjqaL0U5QmuOar6HscLM/NXZmovlqnbH1ek152wosYN8N5lV5q7Kcnnq9I05GDUaXSJ0mcwq81dn04qjdFX20kE5WG2/WbXULaaT8gAuEBz9XjuNAOhlMB8h6iNpVInaxqSD4mhYhs4y5KvyyVVmTgGHT5a5ddq8olIycwr8lUoRaAu7WX5Q7ebAqCoo1lv298bXTbq84eNQNIC3tuzTbMDU5HE5t4uuWHP4zX8NL1vmPGi8x1tb9pFXVOrwtKo3afE3L/I9M6eAI6eMLk9tVi3fiQgfmTkF5BWVsil2Jp/GPMzzhpdtDxDslxDQv3t9HaYycjn6vZ5r/Aeqo8pNIgAK4TZpVInauo8F1cETYNUM6x+zPbnKP+X4pk6Lp8eLOuQkzHfYzXnwYSia1f6CErffzqNy7jScup6ZRu1eY3fTU6fXnBf57kl6PflORN2zfrczjTMoVy3zHK1l3X4JgZ8ulHDqgeDo2lpqHs4Uo4MIgG7Wj0IIif4nHLn0YUvjSYsuyhb+uXmjWI9O6+nxog51HwvJ58DiwbX3TV4HrXoEPUk+8TKqpVW7xDi338qjcu4kn0cbH+E3NdWn9NT5NedhvnuSXk++E1H3rN/tKvMA/jS25rOYObWOGW18lIe7XBfspNULzq6t9JjntHfIIsBCuE16qoS2HjdCg6ba+yattU0i7pWaSIvGMW6dsmVCLL1SE/2VQhFIDuZTWec8cPpwHSTKRz4OAZzQN6V2dCwNHpVzF/ncnBMO32NC3xRaJsQ6TJPiaVoCxcN875WayFmNDC5Pq1Ms34kIH71SE7mg8Um6OZlP1Tm+uO7LbIRy9nstQwCF8J00qoS2hNYw0kHEtGO7LTeChbnodQrzrjrPrVPOHdml7tfOEe5xMJ/KOueB5Q7WIAplHka1rMkQpWPKIO1eI3selXOtfKYqn193MIF87sguGKJ0zB3ZBag9F0uxO67OrzkP812vU5g/qqvL004emCrrVYUZvU7hY+M0VjuZT/VMxRN1X2YjlLPfaxkCKITvFFV1+Gyi3hkyZAgAa9c6CCFd38xLcOMYy3CAjKw8Hlzxq2ZY9aZx0SwY043hXVv6O4UiUHa8Dyung7mi1i5V0aNcvSj8Qh57UJ6dWbAmm8UbcmoFrYiP0fPMded7Vs6d5HO5quO+8mmsMg+wbdO6ljKy8pi/Orta0IqWCbHMHdklNK45L/M9IyuPWe9vp8RoqrZdUWDKwFRmj+jirxSKYNrxPuaPp6FTTbV2mdGhG/Nq+NUtYcbR7/W+WDeWyJAhgEI4JI0qO9KoquH7V+CLOaDx44eih2GPQ5+qUNUms8r3e47zWdYhlm89QLRO4Y1be9GnfZI8eQxHh37RnOdz6h9radT+ouCnx1c73oePp2oHYVF0cMlDcP44aNLW5amMFWaWbs7hxfV7KDpTzszLOnLX5ed4V84d5POVZY9jbNaVYee1ABT6dkhyeC2ZzCqZOQXknyqleSPLkL+QueZ2vA8rp4FZox7R6S1r4Ti4iTaZVTb/cYynv9rJ9r9OknZWQ1bfOVB6qMKdgzLPlG/Db65mmLL+Xm/8M5+vs/P582gx8xp/wkTju9pDijV+84UQ1ckvk3As40HtBhVYtmc8WG2TXqfQv1Mydw85BwCTqtKvgzSowpLd2klW1scv0Sd2h+cwEA+iWrpiiNIxeVAHurex9MK0S473vJw7mE9lHbzXnBM0jY/hvmGduW9YGv07Jjt8D73O0uga1aM1fUPtmus+FsYt1943+EGnw4r0OoWBac24ub9l2GXzxrHSoAp3GnWLzbFd4Vm3hCHr7/WDV3Rh5uWW3+ybHTWoQPM3XwhRnfw6CcfGpFueTmlxElI7LsYSVNKsQmm5LM4ZluzWTqopdvX08F0M8tKHHe/zYjJ2vMFS1ouNDh4+OKMxn8qiaj5VVCg1jnzxjoM5eOsfd2tx0ThrPpfVHiYpwoyTuoUVU8K3bglj8TGW3/mnG97n1W++EMIirBtV27dv59xzz2Xr1q219u3cuZNp06bRr18/evbsycSJE9myZUsdpDKMdR8LVzkIVjFsgcMnzHHRVZVysVFugsKSk7WT1HCOBNXjRohprL3Pi8nYcZU3IyXe3Oxr5LGVGR0zjTNCq8fJF84iACr6aguKa7E2XmvOrxJhyEm5lyhzdcP60GKNMtCr33whhEXYNqr27dvH7bffjtlcuyckOzubcePGkZ2dzc0338zdd99NQUEBt9xyC2vWrKmD1IaxVQ7GT2c84PAJs06nEGew3mzKTVBY6j7WEjpfg2IXUj/sJLSGspPa+1ZMdqvXxJ5PPVVO8njtwHdZZR4QOT1VfaY53qeaXA69tDZe5SFNBHBS7gnnuiWMNawcXVJSZvLqN18IYRGWi/9+9dVXzJkzh6Ii7Sg0TzzxBIqi8Pbbb3P22WcDMGbMGK644gqeeuoprrjiChQlQm5WAm34U5DxT+19dosA2zOZVfSV+XvXOz+h0yk0iI7i/DZN6N8pWQJXhLrCXCg5Dsf+qLbZrCroFJXs3btJa3F++H6HXpRpRwzRljxYue0AP+49BopCmcnM2U3juKZnG/o5mQelOW8Ny4yqrZmbaU0qOUfj2PTnsci4ZtxcUFxLbJSlUZVXeIZrXt6EQa+g0+mIi9HTKyWJif1SZK5VOCjMxXT6OH9mbyPNbrOKgoIanuvfRYCYymsn/1Qp/0uaxm2nF2nPrfKwfoxEIR0USNS5sIv+N2XKFL799ls6duxI586d+fTTT3nzzTfp3bs3AEajkbvuuotmzZrx6KOPVnvtXXfdxRdffMHmzZtJSkqqdW6J/udA9qfw/k21t49JtwwHiEuyRUxzFlrdqklcNE9KiPXQZRcC23qTr6pVw/8Aeug+CN/vsDAXcjbCqhm19129GNr1dSsC4II12by6IcfpMfEGPc+MdRBmXSPUeM18Tim1BHiIiGvmQCYsGwNlp2rvc5LvGVl53PPeL5xxMj9TwqyHCfu6pbKs1yzzErI7uLSur6HKD6THPFf7YI3f/Pok5JevEHUu7B7t7d27l1mzZvHxxx+TkpJSa7/BYGDRokW1GlQVFRXs2rWLhg0bkpDgxropoopWgwpqDZfKyMpj2rJtThtUAIUl5Uxbto2MrDw/J1T4xZh0zJWTla33OtabnnLVMtcnrL/Dhd20G1QAH7s3Ud6dBhVYhgU6zCcn89bKVT0zjVVpDOv8tnptqHaDChzmu7VOcdagAsuN+asbcliwJtsfKRUBkJGVx0zjDMrVyrqlsqzXrFvCuoyHGUfXl2aDCrwaIh0pMrLymL5sW7UGFcDholKmh3vdLPwm7BpVa9asYerUqRgMBreOP3HiBD/++CO33347+/bt46677iIqKixHPdYdZ5PMKycWm8wq8z75zaPTzl+djckcVh2l9YKp63Xcon9Sc99o46PVFqMNy+9wTLplXSotis5l0ARjhZnFbjSo7GnmU/exlN/ytebxo42PVMtnp+cJFx7mu8msMndVlkdvkb4xB2OFRBwNNdbfh1XmAYw2PqJ5jLVuCesyHkacXV/PGsfgaAyTquhhuPbvQ6QymVXmr86uteA7YNsm5VZAGDaq3G1MWd16663cdNNNfPPNN1x++eVce+21AUpZBOs8Aka9rL1v1MvQtg+ZOQUcPlnm0WnzikrJzCnwQwKF3xTm8tuP35JQUr3RYFar1k6yF5bfoY/rVb21ZZ/mj6szjvLpsx2Hqv1tzWdPzxMWPMz3zJwCjpwyevQWZtXy/YjQkplTgP7kX3RV9tJBOVhtX826JazLeBhxdn3NMqzA0bRzpR6uV5WZU1Crh8qeipRbYRHxXTaTJ08mOjqarVu38s477zB27FiWL18uQwA94ayr/2PLeiOn/vaVV6fOP+W4ohJ1YGE3ugPPG6rPedApVWsnWef5WIXld+hD0IT9BSVevWW1fKoMBnLy+CFbPpeoBv5Sm5FMEdGq4yh3YZnfVh7ku7ef09vvRwRO/qlSNsXOtP3tqm4J6zIeJpzl8UzjDJ6JXkSUUvshiFnRo7t6USCTFnLcLY9SbkXY9VR5asSIEQwdOpSHH36YBx98kD///JO33nqrrpMVXtxYN+RvXw716tTNG8V69ToRIGPSMSuWZy2O5jzUFJbfobP1qgb/0+l6LO0S47x6y2r5VLnw7z/23mfL3wYYOUd3kETlNCtj57p3nnDjwTph3n5Ob78fETjNG8W6NZ/K/ngRWM7yeJV5AA8Yay5KbnGo8631br0qd8ujlFsR8Y0qeyNHjgQgK8uzcfr1XvexlifMjuiiMF+9mBaNYzw6bcsESzhSEUK6j0Wd5Giez6O15vmE7XfobL2q9Y87nYw9oW+KdrhhJ2rlkwdBKpyeJ9x4sE5Yr9REzmrk2XBvnWL5fkRo6ZWayNaGQ1zOp4IIKONhwtX19WzMq5rb2/yeXu+CVfRKTaRlQqzDel9Byq2wiLhG1a5du7j88st56qnawRWKi4sBiInx7OZfAJ2c9EQN/ie6Zufw5JAmHp1y7sgusr5DCNLXGEzvbNGFsP4OnQVgUfQOA1YYonRMGZTq0VvVyicnC6A6ClKheZ5wNNjJfAy7SfB6ncL8UV09OvXkgamyXlUI0p88wLMDVZfzqSBCyngYcHV9zTX+w0nd7zqgTyTR6xTmjtRersFaUqXcCojARlVKSgqnTp1ixYoV5OfnV9v36quWJy9Dh3o3VK1ei2/meF/lk/1LPh/CovE9aRIX7fRUTeOiWTS+p6zrEIoKc+H0EYhpZNtUgY4CtSHJFNKao0CEfId9pjnep5qcBqyYPaILUweluuyxio/R186nwlw49DMc213tWEfBQCBC8tvqWyeRw2pMgh/etSWLxvckzqB3ekpFgamDZJ2qkLWwG/3WXsvzhpdtQV5qzqeKqDIeJpxdX0vNwx0GqwDXAX0izfCuLXllfE8S46v37rVIiOUVKbeiUtgt/mvvhRde4MUXX6y2+C9Ywq7fe++9tGjRghtuuIEGDRqwbt06Nm/ezPDhw1m4cCGKRm0hi/+6sPlF+HKO9j5FD5fMhvPHYWp8Nt/vOc7GP/PZcaCI0goTO/4qosIMC8Z0ZexFbeWJTqhyY0HaTeP30Kd9UmR8h1/MgS0vau9T9DDscegz3eHLjRVmlm7OITOngOLSclAUtuUWUlphZvawNCYN7lA7nzTyuKabWmWQ3CiWNokN6NchOXLyG2DH+/DxNEsDqiZFD1cvsvTk2TGZVTb/cYwPtx3grxNnMOgVDhaWknviDN1bN+bD6f2lhyqU7XgfVk4Hc+0ALCZ07On/NB2G3Bo5ZTzM1Ly+zGaVn/8q4q6olcyKel/7RXa/+fVpIeDNfx7jxv9tBWDprRczoGMzKbfCJiIbVQDff/89ixYtYvv27VRUVNChQweuu+46brjhBnQ67R9faVS5wY0bQuYV1do0+D/r2X+8hI+m9+XCdjLuOGQ5uflRdVEoo1+pdcMb1rwsz86MfmkTvxz4//buOz6Kav8b+Gd2k90lFZIACQEhVI0hIGjoCiKKBUUQriLYpXhV/KkXu4DY7r3qVRRQuIAFFBFRRCFcH7EgLWIUDCg11IQa0rPZNs8fk9nsZnu2737erxclM7O7J7PnnJnvnFaORXdcihHZbW0PcHKO9aIC3184G1ff9rBHnxl2fvsYWGMnWB3wENBzLBCX6vJG7cOth/H8mt24rmc65t/e108JJZ8p+R1YeIXt9sk/Au16Bzo15MSpSi36vfwdMhVl2Kx60PULPKwjw9m2Q+dw68JtAIA9L1yDOFXET6JNHgjr3PDQQw/hoYcesruvf//+6N+/f4BTFAUGPOj6yb4dcsVTU2/n6TSFjtzxQFp3uzc/1RPzkdj5siAkyo/GLHLdauKheLXUlaZW52BadCfneLRuDsZ2uN7jzww79gIqANj6tvQHcHmjxjolPImQxqHI/1LokbsDnjClQD/kCcRucjD+1MXyE5GOi/1SU+wvQZ5xFFABNuMhLMWrXNxoUvC5GOuj0Z4NRqr8K3c8cKODPN3/gWZNHezyZr/8KHB2r91dXYUTaG085dHnhSVnk4S4OQiedUoYkcdqalqaAykjlECLFGl7lEx4EC4sW19qLxhqNcbWyk3zgQui9+G1ycFa5hS9wrqlioLA2ZN9KIAx9qdhjVPzqXLIszPoWETjYPLYlbdGZjcPH7SaWEpoyOsOb/adDO5+SzUf+H4+cEUEnmdL/acC+U842NkwCP77F52ed9YpYcROnlfCCNSVAR83dCeOxLolTCkVAjSxCmj1JiQvv9bxgV9Mlv6N0u/OGL6jZ8hP2FJFnnH2ZL/jAIdP9lvESM8nF/54ADfM3YT7P/gFi346BJ2Bj3pChr21kxr+NYgK7B/0RmR2d2jm1OqOqBry+vKth+3ndTvnWaYXlfhf9zmReZ6bcrb2nRvnXdMwMUXxmSrcsmALHlnxGzbtOxMd5y7cjFkE0UHdAkWMWwvMU+AYTSJiGyZf+E/i4zA6vFUUompqdQAwWQRSrGuoqbCeqMLXOFGFm9wZ3P/IH+aB5q+s24P3fiq2e5ggAJOHcCrkkOFgMPn19S9ht5iFjGQNZo7KjrzpY300YYW7eX3JZ1/gnt132Rwjn+d4lRKvj+8VeefZUsUJ4D9ulHs75z2/qBSPfPo7tHrbhzJRce7CTH5RKRat/AKfK56y2bfk4vdxz7ibg5Aqsie/qBRPrv4D5bV687bDmgmuXxglrVU/7z+LiYul2f+2Pz0cbZM0QU4RhRK2VJHnnI6HaNDQ3cPZTSYgTdf93k/FeGXdHl+ljpqjYTzVzt8KrDY3XTuptEKLacsKkV9UGvAkhjp38/qN72zC54X2F0GV1eiMmBrp5zk5E+j3gOP9FgsBW8ovKsXUZYV2AyogSs5dGPlh+w68s3wVMg3HrLbLeX5TYRHr/xAhly3LgAoA/q0f5/hFzWjND2dGtlSREwyqyHP9p7p1M6QzmLDQyU2mpUWbitkVMJje7AksHIpev/wD8jWj6eKclmav3RNZFxRXXQBddE9yN69n4gxMJ35HBs6az3O1qMYBsR3KxATEitbjsCLuPDe1fb7jfXYmvjGaRMxcU+TWW0f8uQsDRpOIoeuH42v1s9LCvw7qFtb/wWc0iZj11W67+z43Xu74hS4WSo80JhODKnKMQRU1jxs3Qx9tPQx3qxyTCHy09bAvUkbNMWYRTII05kFe6Ff+Vy8qMF3XGESLkFqsCorLApxIP+o/FRjxov19fe50OQugu3l9s2Y6vlY/i/+q/2M+v3GoR3fFCaQI1fhSM9Pq+Ig7z02NWQTHlyHb8RoFxWU4VaVz660j/tyFgYLiMkzXPQC9KM3U6KhuYf0ffAXFZThZWW9330mkYpF+pOMXO2hVjkSWgZSJo2eoCQZV1DxOuwBKN0PlJw959JZHymq9SxM1X+54/HTFCru7RuvmYI1psM3201Vaf6cqsL51MHHCr0uAhUOdPol1N+9a3mDKFOYbTKVV8CqLuPNsKXc8AEctFKLNE3BPz0VEn7swcLpKizWmwRite8Hufsu6hfV/cLkqK/fH5jve6WQ5lUjD7n/kDIMqap7+U53slG6GHts91qO37JgS512ayCspcSqrn5uO82mqTWKEDdD1Yu0kd/Ou8xvMF+wGrxF3npvyYBZAT89FxJ+7EOfo/NurW1j/B5ersjJd9wAMDq8J0TMLoIktVeQEgypqPmc3Q1DAcMXTaI8zbr2VQgAmDejkk2RR81zcvQt0DUvXVYka/CFm4bSYjHNiktVxAoCMZA3yslKCkEo/cvqgwOR03MCkAZ3gPASVxlPlCIfQRbA/SYU8GYiliDzPTfV2MrNYk/EaeVkpaJuocny8hag4dyFO/r7OiUnQNbTQnjEl2dQtrP+DLy8rBelJaof715gGI0ZwFETYtipHKuuWqiAmhEISgypqPmc3QzAh5seX8bNmultvdf+QLKhimB2DomHmP2XtWSgUsQCAWBjxtP4eTNb9H5R2umfNHJUNpcJVGBGGmrl2kipGgcmXZzl9a3k8lbMB+01F7Hm25MEsgEqFgNk35bj1tlFx7kKcsvIY/nM5kCpUmtc6ihe0NnUL6//gUyoEzLrxYqfHOJ0F0EVrfqQwcqIKcoLrVFngOlXN8P2rwI+v2N8nKIGhT2FeWR+8tl1rdyA/16kKAXbWaBIBq5aXTtqPASBy16mSebF2EiBNq77wp2K7eX208me8HvselDDa7NOLCjyun2ru/hevVuL1cVG01pKH64TlF5Xi0ZU7UauzPZdRd+5CmcX3KopSfS//K3slbyvr/xBib50qWYZwDlvVD7l+kwhes+qL347j/z7dCQD4+qHByMl0o+6iqMGgygKDqmZw8yZU9+x5fLClGNsPncOfpVU4UaFFl7Q4rH/kCj6hDLZdK4EvpwEmg80uvajE4/opMOWMw4R+HZGXlRL5T//XP+V4dktBCVzzEtB/msOX6wwmc17fd6oaR8/XISNJgx9nDIPq9C67iys/nPgfnGjRAx1S4jC2T3sM7JoW+efZ0q6VwOopcDhpxbBngV5/My8oDkhPibfsP4tVhcfw0/6zOF+rx215HfDi6J7Rde5CmZO6xSQoYbpxPmIuuTUICSNnjCYR2w6ew6YDp/HDX2fw16lqdGilwXePDYNq079cPkhtWlYjyapfj+Pxz6Sgas3fB6FXh5bBTRCFFN7Nknfc7LqjilHg/su74L935eHp66UgLDVBw4AqFOSOB+6z/yBBnjwhr3MqBnRJjY6bVQ/XTmrKMq+/eksuACBeE2M3r8vjqebe1gefPzAIb956CYZ0bx0d59mS01kA0Thew6JrkVIhYEiP1njrtj7mVqn0pBbRd+5CmZO6RXH/RgZUIUqpEDCoWxqevDYbTzVcrxM1KqkO6zPJ8QujYM0qq3Wq2CZBTfCOlrzn4U1onFoasFyjs316SaGh6aUiXqW0e1xEcrp2EjwaNxCvkib+SNKWACW/AdWnIXesNELAAbEdDOpWgNG9tZcimtOJbxo4uFmT82ct65TQUn4UOLvXapO5bjm7N+LH30QCm7LlwRjISGQZSJk4poqaYFBF3vNwAU/5RtPeeAgKgvKjQPUpQGPRN1xQokxMQBrKkYkziGv4zqJCM1pNHIlveICwWjdVWuvq43GQbysVENFdcQIx9eeBxSO8T3e46z0BiHUyrbYipqGusRWnlvInH9SEmDd7Aqsn29+3enJEt2hECrnur7G8XnvZmh/OOFEFOcOgirzn4QKe8o1mTT1vgELCmz2Bj8cDWovBxaIRKUI1PlD/G5s105GgjqKgCvCq1cRSfMN5e8zwdykosCB3UhOdBAtRJTkTuOMrx/tHLwDSutkNZhMa6pTaej6oCSljFjnM986CZAod8eayZXG99mFrfrixXJuK3f+oqSi7UyK/GfasFDzZIw9eLT8KtLwAmhipkj5XVY8JC7dCazCiRWwMerVviUHd0tC/c5SM3QkVYxbZDCaXz748UcUlp6uiZ0wVILWabHoNMGjt75cnrHBB3ZDXPzcMgjr9Qrx81nbmrO3DV+KynCsRRR0sHUtq53jf6vsb/99kdjFNrHT2thw4gzHzfka9wQRNrDJ6J/4IFbnjYUztBuWiobb77vsOaNc70CkiD8l1WI3OaHG9vgDLXbXmf/8i8MgfETdhhWXrlInrVFETbKki33BzAc/8olLcPH8zAMAIYMuhMhQercDmg+cw/8eDuP2/29H3xW+RX1QamHSTWxNVzFq7J7q+l+RMxwEV0NjFxcnT2PyiUlz52g/mn3eeqJRearFGFQDM+frP6Dq3ziRnevyS/KJSvPjNnwCAk1U6FB6rwO7SKvx6tBxf/l6CSUsKkDtrA89vEOQXleL2/2632iZPzrLl4NlgJIk8kF9Uimve/NH8s+X12vmaVQ0isHunkRNVkBMMqsg33LwZmrqsEJVa593+ymv1mLqskDdBgdCw8O/O3wqsNss3Pm1wvvHQaPteRv7T9TEObhryi0oxdVkhyuuktV4ycQZpKEe5GG9eo8cAhXncWnxtSXSdW2c86Fokn2edwfkj4xqdkec3wH7YvgPvLF8Flfac+QFCjajCAbEdysQE/OubIn4fIUwuWxV19q/XnxsvR42ocvIOioicsMLEiSrICQZV5DtObkJFAO8qbkUmzrj9drPX7uFAUH97syewcCh6/fIPqxYUhSD9sFT9ms1LouZ76T8V6P93x/sFpd2xA0aTiFlf7bbatlkzHR+o/42WQo15mxImq3FrQBSdW2fcnCjEWHYEM9cUefTWPL+BYTSJGLp+OL5WP4sP1f8yP0iIgw7dFSeQIlTjS81Mfh8hyl4d1tRJpCJecDZrqclla344Mpos/8+8S9YYVJHv9J/qcJcAYKppBTZrprsdWJVWaFFQXOajxJFdYxbBJEhDK+UbH/lfvajAdJ3t1LlR9b3kjne8z8GaLAXFZThZWW+1bbruAehF61FTCvN5VprPc1SdW2cGPOzyEOXcXJyq8mwqep7fwCgoLrOb54UmeZ7fR2iyV4fZM1N3h+s3c3Om1HDBiSrIGQZV5Ftu3AzJT+XdcbrKybgW8l7uePx0xQq7u0br5mCNabDdfVHzvcS3BmI0jvfbWZPF3rlZYxqM0boX7L6FPG7N2eujTv+pLs/7HznNm7aZ59f/Tldp3c7z/D5Cj7vfyQemkViov9b1gRE0tsp6ogoGVWSNQRX5loubIb2owCydkxXZm2iT6OTGinwiJc66X7w8nsqZqPlemjFhhbvnxtF5jppz64wb571nUfPGa/D8+p+jc2wvz/P7CD2efCeOHryZRdhiwJyogpxhUEW+5eJmKFYwYZbqI7feKiNZg7ysFF+ljJpqmKTi4mSteQSLXlSYB5LHivYHKEfd9+LOWjoWT2LzslKQnqQ2/5yJM8gRDiEVFeZxa3VirN3zHHXn1hkXE4WYhj6DXgkVTo9piuc3MPJaVeOKhONWeV4nxtjkeX4foalpHebMOTHJ+QFuzJQaTqy6/7GlippgUEW+52zCChH40HClW+OqZo7K5toy/tQwSYXyk/HmdaliYLIaSG5P1H0vueNdd2u1mLBCqRAw68aLzbs2a6abB+zLNNDbPc9Rd26dcTJGEwAUP7yENYZpHk1+w/MbGMq5ufjAMMMqz8fCYJPn+X2EpqZ1mDMnkYoXdBNdHxghXQCtuv+xpYqaYFBFvudswgoBuCNmo9MJK1rFxeLdiX0wMifDXykkQGqBUTRMUtGwqelAcktR/b30HOt8vzxhRUNgNTInA+9O7IOWcbFWA/ZtJwORznNUn1tnhj3r8pDNmumIUzlfOjlereT5DSTLusVOnn9aeJjfR4izrMOcaRUXi7wJzzqfKRWC3ZlSw5HRqqUqiAmhkCSIIkNt2fDhwwEA331nfyFU8sCP/5ZuNF14uM0HOKhPwe7SKsQKwPv39kP/zql8ehkoJb8DC6+w2XyT/mV0yhkAQRCQ2aoFBnZJi+7vpeIE8M6lgL7W9bGzGrukGU0ith08h307N+HuortsDv0g5wN07T04us+tMxUngP9kuzzM+Hw5tuw/i1WFx3CsrBb1BhOOna9FpdaI+wZ3wlPXsUUk4BzULZ9esgy3jLqB30eYkOuwTQdOY9exClRr9dhVUgUAWHZPHgZ0TZO+Swfft41H/gBaXuDfRPvRS9/swaJNxQCAf43NxfjLOgQ5RRRKYoKdAIpQvScAP7/h8iZ07uk7cfqxU8h76TsYAQzskgpB4MU2WERIrVat4mLx1m19gp2c0JGcCUzbAszt7dHLlAoBg7qlYVB8FmC1pJICgAl3DuwEtEvzXTojTXImcMVTwI+vOD6m7z1QVh7DkB4XYEiP1ubND33yG9buLEG7lnG8gQ8BJlGAQhDRuXUCv48wYq7Dukn1VK3OgOznNwAA+nRq1fhdxrcGYuNcP3h6s6fVg6dwY7VOFdskqAl2/yP/SM4E7vjKxUHSiuvxKim2N4mAVs/29IApPwpUnwI0yeZNoqBEmZiAjJiqiOiq4VMpWdINvjNNu7g0TAaC6tON2xSxQOtuQIsUwOjZOktRqY+L2UJ/XWJ3LZz4hi6BtTr7E66Qn1jleemG2ygK5kkqFCLzfDjTxCjNXTlr6o2NO+QHT86WQoAADHgwrK8tnKiCnGFQRf6T1M7FAdKK6y1qTpi31PAGKHDe7Al8PB7QNj41FEQjUoRqvFL3QsQMLPYpVzf4TcZWyZOB4ONxjceY9MCZvUBdGbB4hN+SGjGSM12M12jQJLCKa3hYU6MzOnoF+YNVnpduOhUQzZNU9P3WyYLaFPIUCgFxsQ4eWKRkOV8KASKw9Z2wvrZwogpyhkEV+U9yJnD1Sy4PU8zNRVdVGQCgtp43QAFjMZhcJnfKMUDp3lTi0caTG3zA7jk2U8TwHLtrwN+lrkWuWNysxasbbvzq+aAmoOzVKxaTVOwb9EYQEkW+FK9ueGBh73rtYikEAGE9aYVllz+DkUEVWeOYKvKvgQ8ClSXAtnlOD/t/igfRCR/j4U9+hVKpQIdWcRjbpz0GyoNgyfdyxwNp3e0OLn4o7t94K/sWqOy8LOoN+LvL/Gzm5Bzjvu+Adr19mrSIJXcnXnyVk4ME6bspPwq0vACqGOmZ4f92n8SBU1VIS9SgfQonXfE7J3l+tO4FPNt5dODTRD5jNInmh28vf7Nb6rZvMKJFbAx6tW+JQd1uQf/xHaBcOcHxm3z/ovSnGWOrjCYRBcVlOF2lRZtEaZ2zQJZlo5EtVeQYgyryv9zxTm9CDRDwYsM6F78frwQA/HqkHF/+XoJ4lRKvj+/FqXcDRB5MfvR8HXo8tx6Th2Thqetcz74WVdycPEG+uScfcdmduKFr0dZ38EreVrz3kzRDV2llPUor681Hzfv+IFrGxeLVMT1Zr/jJks3FuAfSuoSCII2Xle97fzlchgFdUoOaPmqe/KJSPLn6D5TX6gEAPx8ss9q/+eA5zP/xIPq3OIYV7ryhh3VkflEpZq/dg9KKxi6GGckazByVHbCybOSYKnKC3f/I/+JbO90dAxGzVB/ZXbeqRmfE1GWFyC8q9Vfqotr3x0UYRelu5y9Te/whZuG0mIxzYhJEEXjvp2K8sm5PkFMZgtydPOHoNmkyEHVS4z5FjDRJRfWpsO0CExRudif+MXMyvv6pwOkx5bV61it+8sq6PVj4axVOi8mQbznLkWCuV974dh/PexjKLyrF1GWF5oDKmcN1cagSnU1Y0cDOBDPOPn/askKrgAoATlZoMS2AZdlkEUhx9j9qikEV+Z+bN0POFgSevXYPnwr5UvlRGI//hqX/K4A8mDxdOI+n9fdgsu7/oETjLIyLNhVDZ+CsjFbcHVu15BppMpD6ysZtJoM0ScXH48N6wHZQDHwQuPUTp4dccWIhNmumu/V2rFd8S2cw4ZufCpAmVOAfusnm1ikTBNyvexRpQgUycYbnPcwYTSJmfbXb7eNPIhV969/DasGNiXjcCKyMJhGz1+6BvRwjbwtUnrIMpEzMw9QEgyoKjIEPunUT6iiwKq3QoqC4zM4rqFne7Anlf4fiQ8MMcyWQjBp8o34WX6pnWd2UmkTgo62Hg5LMkObu5AmOcKKK5nHZDVDi6AGNJdYrvvXR1sP4WTMdX6ufxQfqf5u3p6AKa9Qz8bX6WWzWTOd5DzMFxWU4adGF1h06xGKN9hL3DnbxcKmguMymhcqSiMCVZcvAzchnjdQEgyoKnFz3ptJ19JT5dJWzqVrJI2MWwSRIs6PJM3NZztA1XfeA1eFHylws6BiN3FqLzYn7vnO7TJCF+NaAKsHlYc5avi2xXvGdI2W1mK57AHpRabVdYadu4XkPH839rvaKHVAfm+z6QMBpa5W7nx+IPGW1ThW7/1ETDKoocOJbAy1auXWovZuhNolu9NEm9+SOR9G1X9jdNVr3AtaYBltt65jiRYtMJEtq14zWKla7XknOBGYcAvrc5fJQdwIr1iu+0zElDmtMgzFa94Ld/ZZ1C897+Gjud3USqdh9/ZfuL4fgILBy9/MDkaes1qli9z9qgld3CpzkTOD+792qYJu2VmUkS1Onku9cnJlk9bNJtD8trUIAJg3oFIAUhaHkTGDaFiDGzYt59migXS8goY3LCVzIiRg1cOENbh3qbHwV6xXfmjSgE+zVIk3rFp738JKXlYL0JLXHr8tI1qBX7iXu15EOugHmZaUgI1ljN28B0vqKgcpTll3+2FJFTTGoosBKyXJZwYoi8I3hMvTBXvO2maOyua6MjykT2sAkSKsqnDS1tJr5z9L9Q7LMa/6QHSlZwC1L3TvWqJMeLDxSJAVk1HxtswFN81u+AdYrvqaqPo7n+9YjFRWQ7ze1YgwOiO1QJiYgVpQWYuZ5Dy9KhYBZN17s8evM37O7deTIVx1+/sxR0tIeTXON/HOg8pSJE1WQE7xTosBzUcEKAnB9zC9YrZmNruoyvDuxD9eT8aXyo0DJb0DNGSgU0tiHJKHOZuY/QQCmXM51qtyS0cu9Li571wH7NwCn93A6dW8lZwKT3W/5tgysWsXFsl7xhzd74u7dd+ND9b/Mm9QwoLviBFKEanypmYnnbwjcmkLkOyNzMvDuxD5oGRfr8li75Sujl+sPyX8S2Lvebt04MicDCyb2QXqy9QPZ9GQNFgSwLFtPVMGgiqwJosj2S9nw4cMBAN99912QUxIFKk4Ac3tLT+5deeQPLqLqS7NsBw6LsH4CuOjK33DnwE5sofJEWTEwvz9g8GCw9KwK/6UnWnhw3i80fILFd+Whf+dUtpT4w66VwJfTpGUDmtCLSjyun4KHHnkGXdu4nmiEQpPRJGLbwXPYfPAMjpfV4my1DhV1OuwurUasAnj/nn6Oy9eWd4D/PePeBzmoG40mEV2eXgcAmHJ5Z8wYeWFAy/Kkxduxaf9ZAMDdgzph5ijPW/AocvGOiYIjORP4e4FX/aypmcYskqbztiBfkgxQAmMW4f7LOzOg8pQn3QAVSk6n7isenHcRAgZ1TWNA5S+546VZLe2QJ6ngqQ9vSoWAQd3SMGPkRZg7oS8+njwAS+7uBwAwisDALk4eWLi5tAoAhy35lu/dpU1CwMsyJ6ogZ3jXRMGTkgVc/x/3jmVXKd9xcuPzQvrbnObbG+52AzQZeZ59yY3zXiOqcbvpaxjOHQ5MmgiAFMhaYkAbeeJUUjdykwjUu1oo3t16z41FgYPBqvsfO3pREwyqKLha93DvuBCtYMNS+VHg7F6rTfKloZN4nOfZG+7OBjjs2cCkJ1rI592JeKEez6uWIebtXszj/hTfGlCqAAAVYhzOJWXjLFqaJ8BRCAyqIk2cqrHnQ029bddPKx4srWLvuh/sEStW61Rx8V9qgkEVBVf7vsADBYDSzW6AR7f5P02R7s2ewOrJdnfdc+pldrf0lqvuaC1SgN4TApeeaJGS5X7XIj6k8T2LCXDQMKuoGnr80XsWHlf8w2oCHIosSoWAFrFSa1Wtzuj8YHlpFY2biwI3uR4Fu8cdu/+RMzGuDyHyszY9gHFLgRW3uT52yTUwPrwLypSO/k+XnxlNIgqKy3Cyog6nq7TYU1KJY2W1qDeYoI5RQBOrRFqCGoCIs9U61OkN0BlEq32WNyiCICCjpQYpcWqkxKtQXqtDyzjp35QENdKTpHU8lGMW2QwmtxpTddN8VgzeyuglTfetPW+7b8KnnE7dXwb8Hfh1KaCvdX3smz2xLHshsvoMD8uJK+QJAzYdOI1dxyqs6gd1jAKCIJi3aWKVyGypQbw6Bqcr63GyUguVUoDOaP94e9ssj9fEKtE6UYP0lmrUaI0QAby0s3HBcHniGzX0GPbTOAwDAA3QSftx2J1ncs1oEiEPwX3o41+hUAhoERuDXu1bYlC3NNvylZIFTP4RWDjMfh3ZVPlR82RVgZ5xTy5nWw+dhUkESssbJ8T58a9TuP6tn5yWuURNLCAIUAhAz8xk/HGiAiYRMIkm1GiNKKnQIrOlBhdlJKFCq0dpuRaZrVpgYBc7541CHmf/s8DZ/4Ko4gSwYJB7FSyAH679DkP7XernRPlPflEpZq/dg9IKD2aK84GMZA1mjspGyZ/bcM/uu2z2X1//EvYgC5OHcCp1r5UVA0uuBpIygUvuAAo/AKpKgPt/YFDlT8d+ARZf5fbhg7RvoSauHV4d0zNspvrOLyrFk6v/QHmtPthJMbtJ8TNei30PsYJtS4U8898a02Bsf3o42ia5uVg2hTx38mLLuFj75ausGFgw0L2HIDe+DfS5A1q9ERc+lw8A+NctuRh/aQdvku9UsMuZw/NGIYvd/yg0JGfih6Gfokx0b6rdoeuH44ftO/ycKP/ILyrFtGWFAQ+oAKC0QoupywrxeeEJq+0msfFpmCgC7/1UjFfW7Ql08iJLSpa0yO/93wOX3QNM/oGL/gZCUjv3uxZBWsMqvrYEU5cVIr+o1I8J8438olJMXVYYUgEVAKwxDcZo3Qt298kz/wEcUxVJ3M2L5bV6++UrJcu9MagA8NVDwN71AWupCoVy5vC8UchiUEUhwWgS8cR3lbipfg4qxBZuvWbo+uEwlh3xc8p8y2gSMXvtHgS7eficmASDKBX//xquxR9iFk6LyebB5ACwaFMxdK5mciLnYtSNg0gEQfqZ/Cs5E5j8I8QWKdC7eYmTFweevXZPSC/oaTSJmPXV7mAnwyW5/4u9U8nOMZGhOXnRbvnyZCmKT26FYvt8q4W8/SHUylmo10vUiEEVhYSC4jKcqtLhGNri7voZbg9GVc7NDasB5wXFZUFpoWrqJFJRC2mGrt9MXXGTbg4G18/FSaSajzGJwEdbDwcphUReSMnC9ps340rta24/pNmsmQ5FxTEUFJf5OXHNV1BchpOV9cFOhkPnxCScFZPMzxHKkGTzsGbnsfLgJI58qjl5sbRCa798yWNQ3dBi43PmhyD+EmrlzOF5o5DDoIpCwumqxkCjED1wVf2/3L4Zwps9gb3r/ZQy37L8PYMpFgYkCVJaBimKAAjQIdbmuCNlbvR1JwpBp2pFHEO6Rw9pNmumQ3/Y+dTswRQq9Yc9mTiDNKECL+stZ7YUcb/uUaQJFeab4HM1uuAkkHyquXnR7uuSM4HJ3wPqRLffZ7NmOuJqSpqVBldCsZyFYprIFoMqCgltEq37VB9Cezyqm+b+G3xyK1D4oY9T5XtNf89Ay8QZ5AiHMFAoMm+7WvkrLhaKkSMcsnn61zHFjYVsiUKQXNY8fUhz+aaJIfuQJtj1hzObNdPxtfpZvKF617wtBVVYo56Jr9XPYrNmOgCgTSK7wEaC5uZFh69LyQImrPLovW74/mq/lNVQLGehmCayxaCKQkJeVgraJqqstu0Ws3BOTIRBdHNg81cPAW9dErI3RID0e2YkB69ylG98PlD/y7wtBZX4Rv2M1Y0PACgEYNKATkFIJZH38rJSkJ4k3cBHykMay98p1EzXPQC9qLTaJs8GrReVmK57AABwWVZKoJNGftCcvJiRLC3r4VDH/tK6lW52BQQglVUfDwEItXLm8rxRyGBQRSFBqRAw+6Ycq20nkYoB9e9gWP3r7ncFPH9IqmRDNLBSKgTMHJWNYM1/5e6NDwDcPyQLqhhWERSelAoBs2682Pyz/JBGL7qZp796CHg9G5g/EDhR6KdUeqbp7xRK3J39L1bJOiUSNCcvzhyV7XrdpTY9pK6AHszgiTd7Alve8VlwFWrlzK3zRiGBtRuFjJE5GXh3Yh/EqRpv+nWIxTGke/aUGZACq/VPhuQkFiNzMrBgYp+gtFgVJF6FX65aaXeffOMjCMCUy7lOFYU/uU5pGRdrfkhzZb37k1eg6gRwejewbCzw3tCQCK7Mv1OL0F+iW16qwfJ2kFOqRw7L8uVMq7hYvDuxj/vrLcmLA7dIhdu3qf97RgqufMTd382fPD5vFHRc/NcCF/8NDUaTiC37z2JV4TEcK6tFvcEE/fnj+EScgZZCNZSeTkje5mLgpneAzD7+SXAzGU0iujy9zvxzZks12iZqUG8wQR2jQL3BiN2l1QCAlpoYZLWOg84gQh2jgMFkwq4TVR593vhL2+OVMblQntwJLLzCvN0EAQqImNNuAdIv7I87B3ZiCxVFFKNJxLaD57DpwGnsOlaBC2p34aXzM6D09P5enQQkdwiJ+uRsVT0ufen/AQAGdk5Bnd5grh/UMQoIgmDeVlKhxfmG9XZ6tkuASRSgUgrQGe0fb2+b5fEmUcTvxytt0pSOc9isfhhKQcRhZUcoYjVIxzmMM72MnZXSGoQHXroWMWytiihNy5fWYMTO4xUwmoBXx/TEuEs7NK+lxVAP7P9/wKcTXB8LAFAA8a2B+DSflVGjSUTO8+tRZ7C+77i9XwecLNfiZKXWbnk5UV6H8jqD0/fObKnG+Ro9avW2S5dc3zMdc2/rwxaqMBP6j7oo6igVAob0aI0hPVqbtz22cicGFL6DV/sbMOb3ez17w9O7gQ9uAFK7Aze8EfSbIVnTyvLKC9MxZ3RjF8idx8px07zNAIArLmyDt269xLyv+GwNhr32g0eflxKvlj4zvjUgKADRhIOmdMQnpSAdZ/Hc367gwrQUkZQKAYO6pWFQt7SGLQPwtxfVWKh/EslCnftvVF8p1Scf3gSMWQj0uNYv6XWH1mAEAKhjFPh48gCnxz7zxR9Yvl1qtX/yuosxqGua0+NdOVFeh0GvbjT/nIkzaCVUQYQAoeGhV6fYCmDSB4BJB+WyYvOxbKmKPLblCxjyr404VlaHbm0Tmx8YxKiBdr2lFqu68wBcrZtoAmpOSX++eQxQxQMjXvDqmq8QgKYxT3KLWLx0c67T1z22cic+Lzzu9JjhF6XjwOlqbDl4zmaf+XpNYYVBFYWFeLUSOsSiOO4iaSDr4hFAfYX7b6CrAUp/A96/AWjVKSSeNDcVp7Ye6xRv8XOcyrqoxqusj3VHbPVxoKQOgAC5sa+1UIm1Xf6F2y9NB0Sjx+9JFK7OtuiEu6tn4HPNbM/HONZXSl2Mk9oB178RlOCqVieV13i168u45TFxzag7bN6vyXtYTnBjpi0HFg0FAKwG0AkfAwAUvFGMCvEN16xanfPWGpeSM4HH/vSwxQpASUNXXS+v+TqjCYYmazIkuFXmXJezOFWMzbVdVuPteaOgCOs2+J07d+Kiiy7C9u3bbfbt2LED9913Hy677DLk5OTgmmuuwdtvvw2djmtkhCO54qmpN0oDWac09LcWPLxB0NdIT5rfv0GaKTCI4yQMRuvHX/FNKlfLyrbpTUycG5V6U4/tHgssHNrQ9U/67ETU4vaddwCLr/Zpf3SiUBevjkEhemDbyPWA2oNB8ZYqS6Tg6vXsgNclNfXSTZc7QZLlMe4EYa7fz/o97E2AY6aIwezYR7z+TAovcp6rqffBwzqLFisRShg9GQEgX/M/GNWsa36tnfS7V+bcCLxUSofBl73PpdAXtkHV4cOH8fe//x0mk21zcEFBAe644w7s3bsXd911F55++ml069YN77zzDqZMmWL3NRTaEhoqHvNTr5Qs6enVgzs8myVIpq+RZgqUW69ezgR+/8SHKXatVm9daTatqC1vfpqOcWoR6/nT5iVtnwYU1hW9uSeOIgYYs8jj9yQKV3J5O9uiU/Mf0siqTkh1yeKrgHcuC0hwJbdUufPU3PIYXwRVqhgFVBbjopzN/If7vsP/lFfY30cRS85nXrdUyRparP6850/8Qz/Z89frqhuv+R/e5HZwZa/FyJ2Hmu5co+PVbKmKNGHZ/e/bb7/FM888g4oK+92/nnvuOSQkJGD16tVo3VoalzNhwgS88soreP/997FhwwZce23w+sKT5zQNFdRP+05jzLyfoTOKDWs3pOLOe76HaukIN/tc26Gvkf796iHguzlSt8LrXgN63+bWy+VBupsPnsGJ89L4DFEUcbZa53Tgd9NOMMfL62A0ieZ+1GqLQOrEeet9zTH/bG/sSXodr5Xb6apz33fSk0CiKNGioXzN+34f3hUUiI9fjHaJZXjl3MNoYayGCHjeLdBkBM7uA/57FZCQDiS0afY4Tp3BhA+2FKOguAw1Wj3QZCIJuaXqfI0Omw+cRf/OqQ7rhxiLGTn2lFQgPUnjVV1iNImIUQI6Jw/TLcdXUfSRy9d7PxzA4k2HoIlVokNKHMb2aY+BXdOal/9i1DAqNNhvag+jKI13alYurq8ESn9D/eLrUKFohTplAhYmPog9Qmeb6/X5OtveTeeq6l2WObiR90vK66COsf/6wiNluHneJof3D64mk3H3eL0JSE9SIy1Rjdp6I46frzVPltXc99cajNDEKJEar8K5Gh20BiPUSs/S30IVg17tW2JQtzQX5zm0hN3sf5MnT8aPP/6Irl274sILL8TXX3+NDz/8EP369QMAlJaWYujQoRg7dixefvllq9f++eefGD16NG6//XY8//zzNu/N2f9CU35RKR5e8Tt0BvsBkyAA0wZlYkbPOmDpSN98qCIGUMRKkzrEpTq8McovKsWTq/9AecPMWt5qGReLV8dI3fBmr92D0gqteV9GsgYzR2Xb3eeui4VifKN+xvyzSRSgEERsGf45Bg65ysvUE4WHV9btwXs/Fdvd1wGnsFo9CzVCC3TCSe8/TKEEEjOd1iP20rfwp2KPQhK57mg6/XJ+USlmrNqFSm3jk2+5LmnOVM2O6rx0nMMm9SOIFYw4aWqJMmUauqjKoX7gJwxasBcnyqUHTodfvd7jz6Tw4qx8AVK3t9fH92pW/vv9WDlGz9uMeNTi2T5G3LZnijdJNas2qSEIIk6IaXhM/wD+EDu7fI2zMvf4Z7tQXe+6tUmAO+FXdHN0nkNR2HX/O3ToEB599FF88cUX6NSpk83+1q1bY8OGDXjooYds9p09exYAoFCE3a8dtfKLSjF1WaHDgAoARBGY//MJvLI7WZrEwpO1LRwxGQBDHVBxtKG7wM3Af3KBF9PN3XvktPkqoAKA8lo9pi4rxNRlhTZB08kKrcN9rmTiDHKEQ0hFBeQxt3pRgQNiO5SJCfjXN0XILyr11a9BFLJc3fAdQ1sMqp+LW7VP44yYjIrEbkCMF2vKmYyN9cj7N1jVIc7S5+mNllx3WJbj/KJSTFtWaBVQAVJdMq3Jse6wV+eZ6xahEsaGdoNEoQ7/0N6FWysfxA9/sV6JJq7KFwDU6Iw2edVdxoYLWA3icDy5t8+u+QmKesQLOnRXlOBz1fP4UfUw1qieQU/hkMPXOCtz7gRUAAMqd9g7z6Eq7Lr/rVu3DiqVyuH+mJgYu8EWACxZsgQA0L9/f38kjXzMaBIxc02R28cv2lSMx66+FqrH/gQqTkhdcJrbJbCp+nLpDwCc3Qdx8QjkmFLwo8qEFKEaz+vvxhemId5/jhPeVL6Ws3PJbdMxMKG74gQA4EvNTAxY2xMjstPDppmdyFM6gwkLXdzwAdKi4yeRhkH1c5Fan4Cfp3aGcvFwoK4cXtUnclfjs/ukcR1GvVVruK5tb6v09RQO4amYj/GKYYJbT84BqRV7RHa6+f/26g25a6N8rDtl3mgSMeur3Tbb7dUtcajHN+pnpR/WA6J6tVtpp/DmbvmSeZL/ZCaLzlVGE6SJq+Rr/qIrAe15T5Jsl0owoaNwFh1xFp+rnkepmIJ6NN531kGNZ/X3msukO2WOvNec/BJoYRdUOQuonJk/fz62bNmCiy++GFdeeaWPU0X+UFBchlNV7s/WaBKBj7Yexr1DOgOpnRsrWl8GVw0EkwHtcdr8cOyV2IV4EYtxVkxyWvkGy3TdA3gt9j3ECkbz5BTyv3pRicf1U1Cq1aKguAwDuqQGL6FEfvTR1sMe3fDoEIvSynoUVCRjwGN/Sa1LvupiXN+weG7FUenPhzdDizgUqc+iUmyBBKEe+02Z6KM8iA+FV1CJFm49wCmtkMqx/H9HRItj3SnzBcVlOFlZb7PdnbpFp+TkUNHA0/LlSf6TGS2mNzcHWDFq6Zo/+Xvgvw0PP3y0RIgcYDW1PPZFKAUTzopJKK9LxO4d/0FNam6zuuWTe5qTXwIt7IKq5pg/fz7eeustpKWl4a233mL3vzBxusrzyulIWW3jD3JFaxlcacv9sh6TRjACMCLeReULwOrGqDlPoptjjWkwDugyrcZTyUbrXsBuMQtA8845Ubiwqh88cLpKC8SkAh0HAE8eA04WAe/7eLKj+nIkoRwQgHhBeph0ieIgAKCVogatILVyvWrxAAeQ6pNFhusxXFGIlkIVUoRq7Ns9E8cvuMn9382L49ypW1qF19BtaqbmlC9Przkmk2VLVZN8lZIFPPqn1GRaWSIFWNoKv1zzkxRSuuMbWrTq/3cH9DGJ2K0+g0qxBZKEOo/GZ5F7Qv0eJaKDKoPBgBdeeAGffvop2rZti6VLl6JDhw7BTha5qU2i5+MYOqbE2W60DK7kynbRcCnA8mHrlSOWla9MbtkyQoEkQWt+Ep0mVJorZLnVqw5qvG8YiXHKH90KvlwFaqIoPUk2NcyeZKk555woXNitH9xgVS40SUCngVJwpYgFSn/3XetVE4KdXi5qwQh1kwc4D8d8gRihsS7rtXMWsve+Y3WDZ9mKroYOaUIlTohp0OrmA8iUWuG+fR4Y8YLdyTQ8qRvkCXBkSnu/CEWc5pQvT685RtFJUAVI13ug4Zr/l/mar1t4JQRtOWIF/wT4akMl1IZKq4ci3YUSfBj7ClSC3lwOLctjORKterIE6iFrOAv1e5SIDapqamowffp0bNq0Cd26dcPChQvRrl27YCeLPJCXlYK2iSq3uwAqBGDSgE6OD7CsbB9vqGzLDgPvX+fz7oGuyC1bMssn0XKFbB2ELYJGMGC5YN3q1TQIA4AM4TxUghGfK2binJhg3qeEESaxcQrafWIHpKAS5+TXJWuQl5Xi59+cKHgmDeiEF7/506MuSg7LhUYqN35tvXKTZUAFADHGesTUnLC6wbPXit5dKIGYfwuwuZ3UHVFbDrw/SnqyH98agADUnAbUSehfX4ntGg3ixDosMlyPGxRbkamQuiomC7UwiArECCYYRAG7xSxk4BzKxCRkJGuaN+01hR1Py1dzrjl2u/85YnHNVz72F8b98zMsMjyFJNRAAROUAciYrRRNr+uN5VEas9V4ndYhFq2EGqtrd9Pru71rvvyAxFGrmLvBWk/hEF6MWQwICIlhC02Fwz1KRAZVtbW1uO+++1BYWIj+/fvjnXfeQWJiYrCTRR5SKgTMvikHU5e5t5Dm/UOybBbJdUiubNte2NiCVXYYWHpNQwtWaNEI0kxC9lq9HN00qQQjMoQKu/sA4Dn9ndgpdoMOsQCAmaOyQ3oAKJG3VDEKTL48y+XsZJbcKhcBbL3yNcFkkMZ0yfTV0r+W2wx1EAC0RR0gAA/FfIlYQXooJNc/MhMUeFZ/N/aKF0CPWCwYlY05X//p59+CQoGn5as51xyTq5YqB5QqDSbffBUGLEsEIKItyvCleiaSUI2YhjAwGA2qVtdp6Gy32bm+29vWXSixCtAsAy5nPWIsuyqeNKWgl1L67j5XzUSp2Mr8HvZa2prus9wmt4zLreKujnenJS8c7lEiMqh67rnnUFhYiGHDhmHu3LnNntyCgm9kTgbendgHj67ciVoHK00KAjB5SBaeui67eR9iGWA9vg/Qa4Gas8Diq/zWHzsUPB/zET4wXI1flbl44tYRYbEGBJG35HrC1TpQreJi8Yqna6M0bb2qPgMs9mJh8hAlB1T2qAQjZihX4I24hzDlxn4YmZPBoCqKuFO+4tVKvD6ueetUGS2KkcuWqiZG5mRg7sR++MeqXTimVWFA/TsARMRCjx44gs/UL5pbVUP83t0uVw9S7feIaeyq2FUosXqvjnYDOfeCvKaf7/p4+y15Y5SbcFzVw/O6OEgiLqj67bff8PXXXyM2NhaXX3451q9fb3PMBRdcgEsuuSQIqaPmGJmTgRHZ6diy/yxWFR7DsbJanKjQ4lRlPbIzEvHl3we730LlSoxa+tMiubE/NiAFWiW/A8vcG/wdDnoqj+A15SLph/Z/BDcxRAH01HXZeOzqC/HBlmJsP3QOpRVaqGIU+O2YdEMyb8IlGJmT4d1TUU2S9EduCTfUNwRZw0OyNdyXhsTsxhDdVCB2BVDuu3X8KDzYK1/Hz9ehQmvAnQM74vkbLm522TI6m6jCDSNzMpASr8L497aZe2nooIKm82BMrF+JWr0CF+EgXq58AgIaF+cNwxjLY6EYSN6h/hF3DOwFZaxRqktaXhDsJDkVcUHV5s2bAQB6vR6zZ8+2e8zNN9/MoCrMKBUChvRojSE9WgMAPv3lKJ74/A9kJLfwXUDVlNyCBQCxGqDr0MbuPYIAnDsELL0WYn050DD5gzwJRNh5sycwqyLYqSAKGFWMAvdf3gX3X97FvC1n5gZU1xtwcbtk33UzkeuRWI30sMayNfy/VwH19lvD5Ru5sL6h++RWAIDQ4osgJ4QCrWn5enTl71hdeALtklt4VbZs1qlqhjq97Qs/njzA4qcRgHaC9BBk6UgIiRlA1+HA5rcitudKqFIatcCmfzVuCPH7lLAOqh566CE89NBDVtsefPBBPPjgg0FKEQVKnErKujU691Yt9xm5ew8ApGcD/9iHsvMVGP36V1itfgEnxZb4ztAL02O/hhAm3X1MghKKm98NdjKIgi5OpUR1vcG/9Ypla/jjTVrDRREoPwp8PBbH9UlYXNMPD7b8BWmGMwBMjWtbhQtBAdz8HsR1wU4IBVu8+ZrtXVDi0UQVDtTWu1G+5Zbm/ysClCrpaekVT0gtzoAUcC0ZEdFDBEJKQ10S6sI6qKLoFa9WAoDDcVYBE6NGrTIBx5CBQfVzoUMMAAF3/GMeUtQNFb4iFjDqpIkwProJqC8PYoJtfT94BYbnXh3sZBAFXbw6BqiqD1y90rQ1HADiWwH/txsvLN+Fb/88je5DnsSES9OlfXqtdIMHAKf3AstuBnSVQHxbwKAH6k4HJt3uuv97oF1vYN3GYKeEgixOvma7E9A40dyJKix5FNg1LaNyObU3REAUpWt9zVngg+sivptvQMl1SYhjUEVhydxS5WUF7QvyU225fzYAxCfEAzFKi6PigLjewD/2Wd8Y6bVSJQxI24w6KQirONYQgFUCognwaBJo98hdFQWuhU0EQGqpAkKgXolRo1bfMLueJqbxxs7yBq9978aWLnm71qIlSxEL1Fc11ifLxwAJbYHcvwE7lgLl7s+ASOQtX7VUGYzeB1W1vmqJtvdQBACS2jZ281WqpNYtkwnQ1QCqeODEr8Ant5gPF+W/hDDu6ksAGFRRmNI0BCzHy2oxdv5mqJQCBEFAnd4AvVFezyAVdw7s1OwxV0aTiG0Hz2HzwTM4XlaLs9U61OkN0BlEqGMUUMcoIAgCzlbX27y28Mh55GWl2vYdl7v+yFQt7H94Qgrw+N7Gp2CiKN0wyd0Q9A2riguCdNNk0jfeXJn0gBAD6GuAFimArlraV3VSqsiTMjHvXF8M0W5EOsqg16Q26/wQRRKjSYTBIHXZfWfjfnxReByiKOJstQ71RhM6tIrD2D7tMbBrmtfjrYwmEQXFZSg5X4vCY+dxqqIetfV6QBCgNRihiVFiT6kUIB05WwujSbT/mZZ1CSA9PbekbliMNSEFeHRPY/0x6GHpaboqoWElcJMUgAGO65hzB4GVt0mBWc44YNdKoKoUGLME+OIe6QFQQlsAAlB9EtC0bFjrigjQxErX4Z/2ncKYeRWoN5igjlGghSoGPTOTkZqgRlqiGulJ0lpEjsqYq8V/jSbRalIr+XPk63Wd3oCScq3N67YePOf0cz1mea03X+cb1ljqMcI8Ptuor8ew13/GudoajLooFS/deDGUMUogNh6oLZOCMPn6Dthe80/uAj4Z1+xkmsdu+ng8uPx+Xo8JFZRAi1ZhU5cIotjMTqkRaPjw4QCA7777LsgpIWfyi0rxf5/+bnewaVPNnW49v6gUT67+A+W1zZ+5KiNZg5mjskNrGlBDPaBU4eo3f8K+U1VQwYDXbsvDjb24MDZFL0/Ke7xKidfHN286aPmzZq/dg9IK2xs7R1rGxeLVUJhSuKH+MM/KY9RJN46GeusWM0O9dEzDz4P/uRHHz9cBAA6/en2wUk9Bkl9UiodX/A6dwb1xxs6unSsKjuLJ1dJstSOy22LRHZdafY6z5Ve8+Vx/sFcXNCsN2srGYQZCTOODVEBqQZPLKmDdI0ZXg08378GVO+7DSTEFvySMwD2JW4GKEuDu9dJDErksNxzvMsirOonz/70Rx00tsdaYh3+k70ZszSlg4mogMd32eMv3sHx/daL0b4zaqi4JdWyporCSX1Tq9mLAgFRm5YUI3Q2sPP0MR0ortJi2rBALJvYJ/s2QrKFiUgjSZLE6xIbkNKpEgeJpea/RGTF1WSHebUa5zi8qxbRlhR535i2v1Tf7M33K8sbG8kan6Q2PZVcoNN47UfRpzvXU2bXTsqXKZNFS5Yvr9skAXrMd1QXNSoN5Aq2GFjFNvJupSEF1KwMG1b8NHWKQl5yKeyb/u/FhiZ3jXUpOx6SkpSg6XQdAwLS756GVBm4GRW68f4jjaAoKG0aTiJlripr12kWbit16SmY0iZj11e5mfYYjs9fuaXbfb39RWLTzK8JyDngi73lT3j0t10aTiNlr93g1OjIU6xIiR7y5ZgP287tlICUHWN5+jkx+Z3+XM2d1QaDSIFMK8nhwAUpB8EmrkF6Q3g8AYmOVYdPK5AsMqihsFBSX4VSVrlmvNYnAR1sPu/UZJyttx0g1lwjpqVtBcZnP3tMXLPuNs6WKopU35d3Tcl1QXOZRlz9ffCZRMHlzzXZ07bS3+K83n+Pu5/qSq7ogkPcNlvcCPhtPZiFWGV03GAyqKGycrvLuhuRIWa3fPyPQ79tclnWnwJYqilLelktPXu+rOiDU6hIiR3yRV5u+h8Xkf+bp1f1RJvxZztx970CUdYXlA1Z/BFWK6Aozouu3pbDWJlHj+iAnOqbE+f0zAv2+zSWw+x+R1+XSk9f7qg4ItbrEHaxiopMv8mrT9zDZaanyR5nwZzlz970DUdaVFoXTH41K/gjUQhmDKgobeVkpaJuoatZrFQIwaUAntz4jPcl3/X8FyNO7h9YATHb/I/KuvHtarvOyUpCR7N1NUijWJUSOeHPNdnTttJ6owvvPcfdzfUmuCxxdegN536Dwc/e/aMOgisKGUiFg9k05zXrt/UOy3FqvSqkQMOvGi5v1GY7MHJUdcpWVZXLYUkXRypvy7mm5VioEzByV7dWaLaFYlxA54s01G7Cf3412Jqrw9nNk8if5u5zJdYHlZwY6Dea0sNeKTzGoorAyMicD707sgziV0q3jBQGYcrln61TJn9HcRYNlGcma0JpO3YJl5cl6lKKZXN5bxsW6dXy8Wtnsqc1H5mRgwcQ+HrcOt4qLDf506l7glOrRy9NrNuD82mmv+5/l53hz3U4P4DVbrgvSm7ReBzINgP8nqog2XKeKws7InAyMyE43r5p+/HwdVErBvFr6qUodSiq06JIWh/WPXNGsSnZkTgZuvuQMPv3lmHnbwM4pqNMboDOIViu0aw1GtIj1bFX4YOOU6kSN5Dpl28Fz2HzwDP77UzF0DTdseR1bYv+ZGpyv1eO2vA54cXRPr8r1yJwMtE5Q41RV46yDnVPjpG6IgoAz1VrsPy1NqiMAWHZfP/TvnBqydQmRK02v2cfKalFvMOHwuWrU6Kwj7n+NzcXYvu0d5ner7n9NovWRORl49vp6PL9mN9ITVWjXsgXqDSar63Wd3gC9UQrcLu2UguyMJJTV6tAmMfDXbPm8FBSX4XSVNihp8PdEFdGGQRWFJaVCwJAerTGkR2ubfev+KMUDywuRmqDx6qmVwWKaIYUAfDx5QLPfK9RYj6liRUqkVAgY1C0Ng7ql4fPCEzjVMNX6svsHYNba3fh4+1G0TdL45oanyVtMHNAJ9wzOAgD8euQ8xi7YAgCIUykxqGua958XZKxiyN41+/4Pd+DbPaesjuvSJsFpGXPUUiXT6o0AgIFdW+ONv/X2MtX+p1QIGNAlNXifbzVRBQuqt9j9jyKO3M2gRmfw6n1qvXx9KLOsO/lwisgxVYwC8Q11Sq3O6JfPiFc3do1SKRsvy7FedkEmCmXxdroEurruWrZU2QuqauqlMhqndr+7YTSzqG7YGu4DrLEp4sSrpQZYb2+Aavx0AxUKrMdUsSIlciZOJdUpNfX+edAivz8AxMY0lsdYJS/RFLns9SSRgyJHjKbG/zft/gc0BmXxKnbEcgeHAvgWa2yKOPE+ugGqtXh9pAUenFKdyDGhSf+8BB89qJFZdi22fH/AOpBSRUhQxYkqyJ6m5Qxw3VJlctVS1VBG49UMqtxhPVFFEBMSIZjrKOJoYqWa4VxVPSYs3GqeXEKlFKAzijaDVptOPCFvO3Cm2vyeJpMIo0mMmOZxqynVI+R3IvIV0eLGbevBc1DFSmVky4EzGDPvZ9QbTB7XJ5bHn6vRWX3eodPVuLx7aygVgnX3P3+sxhkETc9nKE/iQ4Fjr6Xp3R8OYPGmQw7L0JGyOvOxJedrzeVRPn7/aem6vev4eegMJq9n8Y10/linKprLO4Mqiij5RaWYsWoXAMAIYMuhMp+8rwig74vf4tUxPcN2WmNL1k3+QUwIUYjJLyrFmerGmfluW7TN/P9TVTqcqtLZe5lX5qz7E2//cACvjumJ3h1ambdHQve//KJSnKrUmn++bdE2ZCRrMHNUdkTUpdQ8+UWlWPN7ic32fadr3H6POoOIwmMVdvf9vz/PoMdz6zF5iGdLqkQbX69TlV9UikNnG7/DaCvv4V9jEzXILyrF1GWFqNT6Z9xDea0eU5cVIr+o1C/vH0gcU0VkK7+oFNOWFcJOryK/k+uXTfvPmLeF+9Nd+Xw26e2IkxVaTIuQupQ8J1+rdZYDpPxAFIH3firGK+v2+PVzwpkv16mSy7uhSQUaTeWdQRVFBKNJxKyvdgfks2av3WO3L3c4UViUfA5OJZLqkNlr9yDYJfu1/+01/z+cH3g4O5/ytkioS8kzgbxWyxZtKobO4N8ALlz5aqIKlncJgyqKCAXFZThZWe/6QB8ordCioNg33QqDhd3/iKwVFJehtELr+kA/OxWgeszfXJ1PEZFRl5JnAnmtlplE4KOthwP6meHCVy1VLO8SBlUUEU5XBfZmKNCf52ucRpXIWriX6VDj7vnkeY8uwfq+j5TVBuVzQ52v1qlieZcwqKKI0CZRE9Gf52uWlSdjKqLwL9Ohxt3zyfMeXYL1fXdMiQvK54Y6Xz1gZXmXMKiiiJCXlYL0JHVAPisjWYO8rJSAfJa/WNadbKkikuqQjGSNnZVzAisjOTJuOlydTwGRUZeSZwJ5rZYpBGDSgE4B/cxw4at1qljeJQyqKCIoFQJm3XhxQD5r5qjssJ+Vi93/iKwpFQJmjpKmXg5miZDTEO6cnU/550ioS8kzgbxWy+4fksX1qhywvP4rvbgXYHmXMJdRxBiZk4F3J/ZBy7hYv7x/q7hYvDuxT0SstaDkRBVENkbmZGDBxD5ID0JrUSTVLzJH5zM9WYMFEfa7kvv8fa2WCQIw5XKuU+WMZZCj8PJmgOWdi/9ShBmZk4ER2enYdvAcNh04jV3HKqxWY9cZRbsrtTva1kIVg17tW2JQtzT075waMU9ZLKdUD+dpm4l8Ta5DCorLcLpKizaJGvTt2ArbD57DqsJjOFZWi3qDyeP6xPJ4TawSaQlqKBQCMlu1wMAu9uuXSCiZ9s5nXlZKxNSl1DyW1+qth87CYBJRWafHqQotTlZqHZYhvQlIT1IjLVGN2nojjp+XyqN8vEKhQJxaibxOqbhzYCe2ULlg1f3PB/cC0V7eGVRRxFEqBAzqloZB3dKCnZSQxSnViRxTKgQM6JJqtW1Ij9YY0qN1kFIU3uydTyJeq4PP6l7ARzcD0VzeGcITRSGOqSIiIopuvlqniiQMqoiikGXdyaCKiIgo+ih9NFEFSRhUEUUhBdepIiIiimqW46t91f0vmjGoIopC/uhHTUTeM5pE8/9r6g1WPxMR+ZL1RBVBTEiEYFBFFIWsplFlRUoUEvKLSjH4nxvNPx8pq8Xgf25EflFpEFNFRJHKqvsfbwa8xqCKKAoJHFNFFFLyi0oxbVkhSiu0VttPVmgxbVkhAysi8jmFD9epIgZVRFHJMpBiTEUUXEaTiNlr98BeRz952+y1e9gVkIh8ipNT+BaDKqIopOSU6kQho6C4zKaFypIIoLRCi4LissAliogiHlunfItBFVEUYvc/otBxuspxQNWc44iI3MFxVL7FoIooCllWo6xTiYKrTaLGp8cREbmD3f98i0EVUZQTWKkSBVVeVgoykjVwVBIFABnJGuRlpQQyWUQU4RSMAnyKp5MoGgmcUp0oVCgVAmaOygYAm8BK/nnmqGx21SEin2JLlW8xqCKKchxTRRR8I3MysGBiH6QnW3fxS0/WYMHEPhiZkxGklBFRpOKDGt+KCXYCiCi4GFQRhYaRORkYkZ2OguIynK7Sok2i1OWPNz5E5A/s/u9bDKqIopBlNco6lSh0KBUCBnRJDXYyiIjIQ+z+RxTl2FJFRERE5B0GVURRyHqdquClg4iIiCgSMKgiinJsqSIiIiLyDoMqoijHmIqIiCj6GE2i+f+HzlRb/UyeY1BFFIUEi6kqOPsPERFRdMkvKsXgf240/7z458MY/M+NyC8qDWKqwhuDKiIiIiKiKJFfVIppywpRWqG12n6yQotpywoZWDUTgyqiKMTGKSIiouhjNImYvXYP7HX0k7fNXruHXQGbgUEVEREREVEUKCgus2mhsiQCKK3QoqC4LHCJihAMqoiIiIiIosDpKscBVXOOo0YMqoiiEHv/ERERRZ82iRqfHkeNGFQREREREUWBvKwUZCRrHD5cFQBkJGuQl5USyGRFBAZVRFGIE1UQERFFH6VCwMxR2QBse63IP88clQ2lgjcKnmJQRUREREQUJUbmZGDBxD5IT7bu4peerMGCiX0wMicjSCkLbzHBTgAREREREQXOyJwMjMhOR0FxGU5XadEmUeryxxaq5mNQRRSFBPb/IyIiimpKhYABXVKDnYyIwe5/REREREREXgj7oGrnzp246KKLsH37drv79Xo9Ro8ejSeffDLAKSMiIiIiomgQ1kHV4cOH8fe//x0mk8nufqPRiBkzZuDPP/8McMqIiIiIiChahG1Q9e2332L8+PE4c+aM3f0lJSW48847sW7dugCnjCj0mUTR/P+tB8/BaBKdHE1EREREzoRlUDV58mQ8+OCDaN26NW644Qab/V9++SVGjhyJXbt2YerUqUFIIVHoyi8qxcIfD5l/vm3RNgz+50bkF5UGMVVERERE4Sssg6pDhw7h0UcfxRdffIFOnTrZ7P/rr78wdOhQrF27FuPGjQt8AolCVH5RKaYtK0RVvcFq+8kKLaYtK2RgRURERNQMYTml+rp166BSqRzuf/TRR837jx8/HqhkEYU0o0nE7LV7YK+jnwhpJfXZa/dgRHY616kgIiIi8kBYtlQ5C6jc2U8UjQqKy1BaoXW4XwRQWqFFQXFZ4BJFREREFAHCMqgiIs+drnIcUDXnOCIiIiKSMKgiihJtEjU+PY6IiIiIJAyqiKJEXlYKMpI1cDRaSgCQkaxBXlZKIJNFREREFPYYVBFFCaVCwMxR2QBgE1jJP88clc1JKoiIiIg8xKCKKIqMzMnAgol9kJ5s3cUvPVmDBRP7YGRORpBSRkRERBS+wnJKdSJqvpE5GRiRnY6C4jKcrtKiTaLU5Y8tVERERETNw6CKKAopFQIGdEkNdjKIiIiIIoIgiqK9tUCj0vDhwwEA3333XZBTQkRERERE4YJjqoiIiIiIiLzAoIqIiIiIiMgLDKqIiIiIiIi8wKCKiIiIiIjICwyqiIiIiIiIvMCgioiIiIiIyAsMqoiIiIiIiLzAoIqIiIiIiMgLDKqIiIiIiIi8wKCKiIiIiIjICwyqiIiIiIiIvMCgioiIiIiIyAuCKIpisBMRKnr27Amj0YiMjIxgJ4WIiIiIiIIsIyMDy5Ytc3kcW6osqNVqxMTEBDsZREREREQURthSRURERERE5AW2VBEREREREXmBQRUREREREZEXGFQRERERERF5gUFVCDp//jzmzJmDYcOGITc3FzfeeCNWrVoV7GRRgO3duxcPP/ww+vfvj5ycHFx55ZV46aWXUFVVZXVcSUkJZsyYgcGDB6N3794YP348vvvuO7vvuX//fjzwwAMYMGAALrnkEtx555349ddfA/HrUIAZjUZMmDABPXr0sNnHPEMyk8mEZcuW4cYbb0Rubi6uuOIKPPnkkzh16pTVccwzZKm4uBjTp09Hv379kJOTg2uvvRbvv/8+TCaT1XHMN9Ft586duOiii7B9+3abff7KG4WFhbjrrrtw2WWX4dJLL8XUqVNx4MABn/5ejnCiihBTW1uLiRMnYt++fZgwYQI6d+6M/Px8bN26Ff/3f/+HqVOnBjuJFACHDh3C2LFjoVQqcfvttyMjIwO///471qxZg65du+LTTz9FXFwczpw5g7/97W8oLy/HpEmT0LZtW6xatQq7d+/Ga6+9hlGjRpnf8+DBg7j11luhVqsxYcIExMfH4+OPP8aJEyewZMkS5OXlBfE3Jl+bN28e5s6dC0AK0GXMM2RpxowZWLNmDYYPH47LL78cxcXFWL58OdLT07F69WokJSUxz5CV48ePY+zYsairq8Ptt9+ODh064Ntvv8WWLVtw6623Yvbs2QBY10S7w4cPY+LEiThz5gw+/PBD9OvXz7zPX3mjoKAA99xzDzIzMzFu3DiYTCZ8+OGHqKurw8qVK9GlSxf//tIihZT33ntP7N69u/j111+bt5lMJvHee+8VL774YrGkpCSIqaNAueeee8SLL75Y3Lt3r9X2Dz74QOzevbu4aNEiURRF8fnnnxd79Ogh/vrrr+ZjtFqteOONN4r9+vUTa2pqzNvvvfdeMTc3Vzx69Kh5W1lZmTh48GDxuuuuE00mk59/KwqUnTt3itnZ2WJOTo7YvXt3q33MMyT79ttvxe7du4uzZs2y2r569Wqxe/fu4nvvvSeKIvMMWXvhhRfE7t27i998843V9jvuuEPs3r27eODAAVEUmW+i2f/+9z/xsssuE7t37y52795d3LZtm9V+f+QNk8kkXn/99eKgQYPE8+fPm489cuSImJubK953331++m0bsftfiPnyyy/Rtm1bXH/99eZtgiDgvvvug16vx9q1a4OYOgoEnU6HHTt2oG/fvujevbvVvtGjRwMAfvnlFxiNRnz11Vfo3bs3+vTpYz5GrVbjjjvuwPnz5/HDDz8AAM6ePYtNmzbhqquuQocOHczHtmrVCuPGjcOBAwewa9cuv/9u5H81NTV4/PHHMWTIEPTu3dtqH/MMWfrkk08QHx+Pxx57zGr79ddfj8mTJ6NTp07MM2Tj8OHDAIChQ4dabb/qqqsAAH/99RfzTRSbPHkyHnzwQbRu3Ro33HCDzX5/5Y0//vgD+/fvx9ixY9GyZUvzsRdccAFGjhyJn3/+GadPn/bPL92AQVUIqaqqwqFDh9CrVy+bffI2ViyRLyYmBl9//TXmzJljs+/s2bMAAIVCgf3796O2ttbmxhlozC87d+60+tedYym8yePuXnzxRZt9zDMkMxqN+OWXX5CXl4eEhAQAgFarhU6ng0qlwmOPPYarr76aeYZsZGVlAYDNOJXi4mIAQNu2bZlvotihQ4fw6KOP4osvvkCnTp1s9vsrb/z+++9W2y3l5ubCZDLhjz/+8PTX8QiDqhBy6tQpiKKIjIwMm30tWrRAcnIyjh8/HoSUUSApFAp06NABF1xwgc2+JUuWAAD69etnHkhuL7+kp6cDgDm/nDx50uGxbdu2tTqWwtf//vc/fP7555gzZw7S0tJs9jPPkOz48eOor69H+/btsWHDBowaNQq9evVC7969ce+99+LQoUMAmGfI1uTJk5GVlYUnn3wSW7duxfHjx7Fs2TJ8+umnGDBgAPr27ct8E8XWrVuHKVOmQKVS2d3vr7whH9uuXTuX7+svDKpCiDyrW1xcnN39Go0GdXV1gUwShZAvv/wSn332GTIyMjBu3Din+UWj0QCAOb9UV1cDAOLj422ObdGihdWxFJ5OnTqF5557Drfccou5G05TzDMkq6ioAABs3rwZjz/+OIYNG4Z58+bhgQcewI4dO3Dbbbfh2LFjzDNko02bNnjkkUdw8uRJ3HXXXRg+fDjmzJmDnj17Yt68eRAEgfkmijkKpmT+yhvysfbeN1D5KMav704eERsmYhQdTMgoiiIUCsbB0eiLL77AM888g7i4OMydOxfx8fEO8wnQmIfk/OIsbzU9lsKPKIp44oknkJiYiKefftrpca72Mc9EB51OB0DqqvP222/j6quvBiCNi8nOzsa0adPw1ltv4YorrnD4Hswz0WnhwoV4/fXX0bFjR/zjH/9AWloaduzYgeXLl+POO+/EkiVLWNeQQ/7KG6GQjxhUhRA5EtdqtXb3a7Vau02gFNnkqbETExPx7rvvIjc3F0BjfrH35EXOQ4mJiR4fS+Fn6dKl2LZtG+bNm4f6+nrU19cDAPR6PQCgrKwMSqWSeYbM5Ke5bdu2NQdUsiuvvBIZGRnYsmULrrvuOgDMMySprq7GvHnz0KZNG3z22WdITk4GAIwYMQLZ2dmYMWMGFixYgMsuuwwA8w3Z8td1yNmx8jZ/5yOG/iGkffv2EATB3C/UUm1tLSorK839Qiny6fV6PPXUU5g7dy7atm2LZcuW4dJLLzXvb9++PQDYzS/yNjm/uHMsA/bw9f3330MURfPiiPKf3377DQAwYMAA3HzzzcwzZCZ/z/bG3snbq6qqmGfISnFxMbRaLUaMGGEOqGSjRo1CXFwctm7dynxDDvkrb8jHNl243HKbv/MRg6oQEh8fjy5dutidnUSe3cRy+kmKXEajEY899hhWr16NHj164LPPPsOFF15odUznzp2RmJhod0bIpvmlZ8+eUCgUTo+95JJLfP1rUIA88cQTWLp0qc2fHj16AJBasv79738zz5BZSkoKLrjgAhw+fNjcsikzmUw4fvw42rdvzzxDVuTxMkaj0WafKIowmUwQRZH5hhzyV96Qe/HYmyly586dEATB7syAvsSgKsTceOONOHHiBL755hvzNlEUsXjxYqhUKnNXDIpsb731FjZs2IDc3FwsX77cPMuNpZiYGFx33XXYsWMHCgsLzdvr6+vx4YcfIi0tDZdffjkA6anzwIEDsWHDBhw7dsx87Pnz580BW3Z2tv9/MfKLnJwcDBw40OaP/CR54MCB6Nu3L/MMWRk7dixqamrw3//+12r7ypUrcf78eVx//fXMM2SlW7duyMzMRH5+vk2LwGeffQatVotBgwYx35BD/sobubm5yMrKwmeffYby8nLzsUePHsWGDRswbNgwtGrVyq+/myA6GzFGAafVajF27FgcOXIEkyZNQlZWFtavX48tW7ZgxowZuPfee4OdRPKzkpISjBgxAkajEY8++qjdgCotLQ2DBg3CmTNncPPNN6Ourg533303UlNTsWrVKuzevRtvvPGGVRC+b98+/O1vf0N8fDzuuusuqFQqLF++HCUlJVi6dKlV10KKDJMmTUJBQQH27t1r3sY8QzKdToc77rgDv/32G2644Qbk5eVhz549WLlyJbp27YqVK1eiRYsWzDNkZfPmzZgyZQpatmyJW2+9FWlpafjtt9+wZs0adO7cGStWrEBSUhLzDeHtt9/GO++8gw8//BD9+vUzb/dX3tiyZQvuv/9+tG/fHrfffjt0Oh3ef/996PV6fPLJJ+jcubNff18GVSGorKwMb7zxBjZu3IiamhpkZWXhrrvuwujRo4OdNAqAL7/8Ek888YTTY/Ly8vDRRx8BAI4dO4bXX38dW7ZsgV6vR48ePTBt2jS7s3b9+eefeOONN/Drr79CoVAgJycHjzzyiN2F9Sj82QuqAOYZalRXV4dFixZh7dq1KC0tRWpqKkaMGIFHHnnEvCgwwDxD1nbv3o358+djx44dqKmpMU948sADD1hNBsB8E90cBVWA//LGtm3b8Pbbb6OoqAgtWrRA37598eijj6JLly7++jXNGFQRERERERF5gWOqiIiIiIiIvMCgioiIiIiIyAsMqoiIiIiIiLzAoIqIiIiIiMgLDKqIiIiIiIi8wKCKiIiIiIjICwyqiIiIiIiIvMCgioiIiIiIyAsMqoiIiIiIiLwQE+wEEBERyYxGI1avXo01a9Zg3759qK2tRWpqKvr27YuJEyeiT58+wU6iSz169EBeXh4++uijYCeFiIgChEEVERGFBJPJhAcffBDff/89hg0bhmnTpiEhIQHHjx/HF198gW+++QZPPfUU7rrrrmAnlYiIyAqDKiIiCgkbNmzAxo0b8eijj2LKlClW++6//36MHTsWr732GkaMGIHMzMwgpZKIiMgWx1QREVFI2LFjBwBg6NChNvsSEhIwYcIEGAwGFBYWBjhlREREzjGoIiKikJCQkAAA+OSTT2AwGGz2T5w4Ebt378aoUaPM27799lvcc8896NevHy6++GL069cPU6dORVFRkdVre/TogRdeeAFff/01brrpJvTs2RNXXHEF5s+fD1EUkZ+fj9GjRyM3NxcjRozA4sWLrV4/adIkjBgxAkVFRZgwYQJyc3MxePBgPP/88ygrK3P5u1VWVuKf//wnhg8fjpycHAwePBhPPfUUSkpKrI6rq6vDK6+8gpEjRyI3Nxf9+vXDlClT8Ouvv7p9HomIKPAEURTFYCeCiIjoyJEjGD16NGpra9G6dWsMHz4ceXl5uPTSS9G2bVub4z/44AO8/PLLyMvLw9VXX43Y2FgUFRXhyy+/RHx8PDZu3Ij4+HgAUlDVrl071NTUYOLEiUhNTcWKFSuwb98+DBs2DIWFhZg4cSJat26NTz75BHv37sV//vMfXHfddQCkoOqvv/6CKIq49NJLMWTIEPz5559YtWoVOnbsiNWrV1t9luVEFRUVFbj11ltRUlKCcePGoWvXrjhy5AhWrFgBtVqNTz/9FB07dgQATJs2DZs3b8btt9+Ozp074+zZs1i+fDnKy8uxatUqXHjhhYH4KoiIyEMcU0VERCGhY8eOWLx4MZ588klz0LFixQoAQNeuXXHTTTfhrrvugkqlgtFoxIIFC5CdnY33338fSqXS/D5JSUlYvHgxNm/ejKuvvtq8vaSkBJ999hlyc3MBAH379sVNN92EH374AZ999hl69uwJAMjLy8N1112H77//3hxUAVJr0/jx4zFnzhzztm7duuHll1/G0qVL8eCDD9r9vd58800cPXoUy5YtwyWXXGLePmbMGIwZMwYvvvgiFi1ahLKyMmzcuBG33XYbnnjiCfNxAwcOxIwZM/DHH38wqCIiClHs/kdERCGjT58+WL9+Pd5//33ce++96NmzJ5RKJQ4cOIDXX38dt9xyC8rLy6FUKvHTTz/ZBFS1tbWIjY01/99Shw4dzAEVAHTp0gWAFMzJAZX8MwCcOnXKJn0PP/yw1c8TJkxAYmIiNmzYYPf3EUUR69atQ+fOndGxY0eUlZWZ/6SmpqJ3797YvHkzampqkJCQgMTERKxfvx4rV67EmTNnAAC9evXChg0bMG7cOLfPIxERBRZbqoiIKKQolUoMGDAAAwYMAABUVVXh22+/xTvvvIO9e/di3rx5eOaZZ6BSqfDrr79i/fr1OHr0KI4dO4aSkhLIvdpNJpPV+6alpVn9LAdfrVu3ttoeEyNdGpv2jm/VqpXNsbGxsejQoQOKi4vt/i7nz59HeXk5ysvLzb+PPSdPnkSXLl3w6quv4qmnnsJzzz0HAOjevTsGDx6MUaNGITs72+HriYgouBhUERFR0NXW1uK9995Du3bt8Le//c1qX2JiIsaMGYP+/ftjxIgR2L59OwDg+eefx6effoquXbuiV69euOKKK3DhhReiuLgYs2fPtvkMOYhqShAEt9KoUqnsbjcYDFatZZaMRiMAqauho+6BAJCeng4AuOqqqzBo0CBs2rQJP//8M7Zv344lS5Zg6dKlePrpp3HHHXe4lVYiIgosBlVERBR0Go0GS5cuRWpqKm655Ra7QUq7du2QkJCAFi1aYMeOHfj0009xww034LXXXrMKjH7//Xe/pPHMmTOoqakxT0gBADqdDsePH0fnzp3tviYlJQVxcXGorKzEwIEDbfZv3rwZCoUCarUa1dXV2Lt3L9q3b4+rr77aPB7sr7/+wp133ol58+YxqCIiClEcU0VEREGnUCgwevRolJSU4LXXXrPpugcA33zzDcrLyzFy5EiUl5cDkLrHWQZUZWVlWLVqFYDGViJfMZlMWLp0qdW2999/H7W1tbjhhhvsvkapVOKqq67C/v378c0331jt++uvvzBlyhS89NJLiImJwb59+zBhwgTMnz/f6riuXbsiMTHR3C2RiIhCD2toIiIKCU888QT279+PJUuW4KeffsI111yDdu3aoba2Ftu2bcPGjRsxZMgQTJw4EVVVVWjZsiXeffdd1NbWon379jh+/Dg+//xzVFVVAZBm6/O1RYsW4ejRo+jduzd27dqFL774Ar169cLtt9/u8DWPP/44fvnlFzz++OP4+eef0atXL5SWlmLFihVQKpWYOXMmAGmSjsGDB2PFihWorKxEXl4ejEYjNmzYgGPHjlnNCEhERKGFQRUREYWE+Ph4LFu2DKtXr0Z+fj5WrlyJ8vJyxMXFoVu3bpgzZw7Gjh0LhUKBlJQULFmyBG+88QZWrFgBnU6Htm3b4pprrsHdd9+NkSNHYtOmTbj33nt9msbly5dj1qxZWL9+PVq3bo2pU6di2rRpDsdbAUDbtm3x+eefY8GCBdi4cSPWrl2LVq1aIS8vD9OmTbOagGLu3LlYsmQJ1q1bhx9++AEAcOGFF+K1116zWvSYiIhCCxf/JSIicmHSpEkoKCjA3r17g50UIiIKQRxTRURERERE5AUGVURERERERF5gUEVEREREROQFjqkiIiIiIiLyAluqiIiIiIiIvMCgioiIiIiIyAsMqoiIiIiIiLzAoIqIiIiIiMgLDKqIiIiIiIi8wKCKiIiIiIjICwyqiIiIiIiIvMCgioiIiIiIyAv/H4hh65dFUFJPAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_results(y=y_valid, yhat=yhat, n=1000)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.452301700Z", + "start_time": "2023-07-11T17:36:26.302207200Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(12)\n", + "plt.title('Gain')\n", + "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", + "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", + "plt.xlabel('$\\\\bar{u}$')\n", + "plt.ylabel('$\\\\bar{g}$')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.508762500Z", + "start_time": "2023-07-11T17:36:26.422233300Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(11)\n", + "plt.title('Costs Functions')\n", + "plt.plot(J[1,:], J[0,:], 'o')\n", + "plt.xlabel('Gain Information')\n", + "plt.ylabel('Prediction Error')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "being the selected $\\theta$:" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.509766600Z", + "start_time": "2023-07-11T17:36:26.505017200Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.54939784],\n", + " [ 0.40805605],\n", + " [ 1.48525188],\n", + " [-12.58066118],\n", + " [ 8.16862327],\n", + " [-11.12171304],\n", + " [ 12.20954877],\n", + " [ 2.94548199]])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Theta[position, :].reshape(-1,1)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "or still:\n", + "\n", + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,54937289\\\\\n", + "\\theta_2 = 0,40810168\\\\\n", + "\\theta_3 = 1,48663719\\\\\n", + "\\theta_4 = -12,58127183\\\\\n", + "\\theta_5 = 8,16780294\\\\\n", + "\\theta_6 = -11,11998621\\\\\n", + "\\theta_7 = 12,20927355\\\\\n", + "\\theta_8 = 2,9446532 \\\\\n", + "\\end{matrix}\n", + "$$\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "parameters found IniciacaoCientifica2007:\n", + " \n", + "$$\n", + "\\begin{matrix}\n", + "\\theta_1 = 0,549144\\\\\n", + "\\theta_2 = 0,408028\\\\\n", + "\\theta_3 = 1,45097\\\\\n", + "\\theta_4 = -12,557882\\\\\n", + "\\theta_5 = 8,1516315\\\\\n", + "\\theta_6 = -11,097284\\\\\n", + "\\theta_7 = 12,215782\\\\\n", + "\\theta_8 = 2,9319577\\\\\n", + "\\end{matrix}\n", + "$$\n", + "\n", + "whereas:\n", + "\n", + "$$\n", + "E_{Scilab} = 17,408997\n", + "$$\n", + "\n", + "and:\n", + "\n", + "$$\n", + "E_{Python} = 17,408781\n", + "$$" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Matrix Q:" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "ExecuteTime": { + "end_time": "2023-07-11T17:36:26.518219Z", + "start_time": "2023-07-11T17:36:26.508762500Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1.00000000e+00, 3.20000000e+01, 0.00000000e+00, 0.00000000e+00],\n", + " [1.00000000e+00, 3.13469388e+01, 8.16326531e-02, 6.66389005e-03],\n", + " [1.00000000e+00, 3.06938776e+01, 1.63265306e-01, 2.66555602e-02],\n", + " [1.00000000e+00, 3.00408163e+01, 2.44897959e-01, 5.99750104e-02],\n", + " [1.00000000e+00, 2.93877551e+01, 3.26530612e-01, 1.06622241e-01],\n", + " [1.00000000e+00, 2.87346939e+01, 4.08163265e-01, 1.66597251e-01],\n", + " [1.00000000e+00, 2.80816327e+01, 4.89795918e-01, 2.39900042e-01],\n", + " [1.00000000e+00, 2.74285714e+01, 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"text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "e03fe37868962894ce69ba1512be75d7d9445f7474f41c85c2a9ae3e524aa256" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/sysidentpy/multiobjective/__init__.py b/sysidentpy/multiobjective/__init__.py new file mode 100644 index 00000000..c4a9a891 --- /dev/null +++ b/sysidentpy/multiobjective/__init__.py @@ -0,0 +1,5 @@ +# Authors: +# Gabriel Bueno Leandro +# Samir Angelo Milani Martins +# Wilson Rocha Lacerda Junior +# License: BSD 3 clause diff --git a/sysidentpy/multiobjective/multiobjective_parameter_estimation.py b/sysidentpy/multiobjective/multiobjective_parameter_estimation.py new file mode 100644 index 00000000..b7fb464e --- /dev/null +++ b/sysidentpy/multiobjective/multiobjective_parameter_estimation.py @@ -0,0 +1,282 @@ +import numpy as np +from sysidentpy.model_structure_selection import FROLS +from sysidentpy.basis_function import Polynomial +from sysidentpy.narmax_base import RegressorDictionary + +# from sysidentpy import basis_function + + +class IM(FROLS): + """Multiobjective parameter estimation using technique proposed by Nepomuceno et. al. + + Reference: + NEPOMUCENO, E. G.; TAKAHASHI, R. H. C. ; AGUIRRE, L. A. . Multiobjective parameter + estimation for nonlinear systems: Affine information and least-squares formulation. + International Journal of Control (Print), v. 80, p. 863-871, 2007. + + Parameters + ---------- + sg : bool, default=True + Presence of data referring to static gain. + sf : bool, default=True + Presence of data regarding static function. + model_type : string, default='NARMAX' + Model type. + final_model : ndarray, default = ([[0],[0]]) + Template code. + """ + + def __init__( + self, + sg=True, + sf=True, + model_type="NARMAX", + final_model=np.zeros((1, 1)), + norm=True, + ): + self.sg = sg + self.sf = sf + self.n_inputs = np.max(final_model // 1000) - 1 + self.non_degree = np.shape(final_model)[1] + self.model_type = model_type + self.final_model = final_model + self.norm = norm + # self.basis_function = Polynomial(degree=non_degree) + + def Exp(self, qit): + N_aux = np.zeros((int(np.shape(qit)[0]), int(np.max(qit)))) + for k in range(0, int(np.max(qit))): + for i in range(0, np.shape(qit)[0]): + for j in range(0, np.shape(qit)[1]): + if k + 1 == qit[i, j]: + N_aux[i, k] = 1 + N_aux[i, k] + return N_aux + + def R_qit(self): + """Assembly of the matrix of the linear mapping R, where to locate the terms uses the regressor-space method + + Returns: + -------- + R : ndarray of int + Matrix of the linear mapping composed by zeros and ones. + qit : ndarray of int + Row matrix that helps in locating the terms of the linear mapping matrix + and will later be used in the making of the static regressor matrix (Q). + """ + # 65 to 68 => Construction of the generic qit matrix. + xlag = [] + for i in range(0, self.n_inputs): + xlag.append(1) + object_qit = RegressorDictionary(xlag=xlag, ylag=[1]) + # With xlag and ylag equal to 1 there is no repetition of terms, being ideal for qit assembly. + qit = object_qit.regressor_space(n_inputs=self.n_inputs) // 1000 + model = self.final_model // 1000 + # 73 to 78 => Construction of the generic R matrix. + R = np.zeros((np.shape(qit)[0], np.shape(model)[0])) + b = [] + for i in range(0, np.shape(qit)[0]): + for j in range(0, np.shape(model)[0]): + if (qit[i, :] == model[j, :]).all(): + R[i, j] = 1 + if sum(R[i, :]) == 0: + b.append(i) # Identification of null rows of the R matrix. + R = np.delete( + R, b, axis=0 + ) # Eliminating the null rows from the generic R matrix. + qit = np.delete( + qit, b, axis=0 + ) # Eliminating the null rows from the generic qit matrix. + return R, self.Exp(qit) + + def static_function(self, x_static, y_static): + """Matrix of static regressors. + + Parameters + ---------- + y_static : array-like of shape = n_samples_static_function, default = ([0]) + Output of static function. + x_static : array-like of shape = n_samples_static_function, default = ([0]) + Static function input. + + Returns: + ------- + Q.dot(R) : ndarray of floats + Returns the multiplication of the matrix of static regressors (Q) and linear mapping (R). + """ + R, qit = self.R_qit() + # 102 to 107 => Assembly of the matrix Q. + Q = np.zeros((len(y_static), len(qit))) + for i in range(0, len(y_static)): + for j in range(0, len(qit)): + Q[i, j] = y_static[i, 0] ** (qit[j, 0]) + for k in range(0, self.n_inputs): + Q[i, j] = Q[i, j] * x_static[i, k] ** (qit[j, 1 + k]) + return Q.dot(R), Q + + def static_gain(self, x_static, y_static, gain): + """Matrix of static regressors referring to derivative. + + Parameters + ---------- + y_static : array-like of shape = n_samples_static_function, default = ([0]) + Output of static function. + x_static : array-like of shape = n_samples_static_function, default = ([0]) + Static function input. + gain : array-like of shape = n_samples_static_gain, default = ([0]) + Static gain input. + + Returns: + -------- + (G+H).dot(R) : ndarray of floats + Matrix of static regressors for the derivative (gain) multiplied + he matrix of the linear mapping R. + """ + R, qit = self.R_qit() + # 130 to 151 => Construction of the matrix H and G (Static gain). + H = np.zeros((len(y_static), len(qit))) + G = np.zeros((len(y_static), len(qit))) + for i in range(0, len(y_static)): + for j in range(1, len(qit)): + if y_static[i, 0] == 0: + if (qit[j, 0]) == 1: + H[i, j] = gain[i] + else: + H[i, j] = 0 + else: + H[i, j] = gain[i] * qit[j, 0] * y_static[i, 0] ** (qit[j, 0] - 1) + for k in range(0, self.n_inputs): + if x_static[i, k] == 0: + if (qit[j, 1 + k]) == 1: + G[i, j] = 1 + else: + G[i, j] = 0 + else: + G[i, j] = qit[j, 1 + k] * x_static[i, k] ** (qit[j, 1 + k] - 1) + return (G + H).dot(R), H + G + + def weights(self): + """Weights givenwith each objective. + + Returns: + ------- + w : ndarray of floats + Matrix with the weights. + """ + w1 = np.logspace(-0.01, -5, num=50, base=2.71) + w2 = w1[::-1] + a1 = [] + a2 = [] + a3 = [] + for i in range(0, len(w1)): + for j in range(0, len(w2)): + if w1[i] + w2[j] <= 1: + a1.append(w1[i]) + a2.append(w2[j]) + a3.append(1 - (w1[i] + w2[j])) + if self.sg != False and self.sf != False: + W = np.zeros((3, len(a1))) + W[0, :] = a1 + W[1, :] = a2 + W[2, :] = a3 + else: + W = np.zeros((2, len(a1))) + W[0, :] = a2 + W[1, :] = np.ones(len(a1)) - a2 + return W + + def affine_information_least_squares( + self, + y_static=np.zeros(1), + x_static=np.zeros(1), + gain=np.zeros(1), + y_train=np.zeros(1), + psi=np.zeros((1, 1)), + W=np.zeros((1, 1)), + ): + """Calculation of parameters via multi-objective techniques. + + Parameters + ---------- + y_static : array-like of shape = n_samples_static_function, default = ([0]) + Output of static function. + x_static : array-like of shape = n_samples_static_function, default = ([0]) + Static function input. + gain : array-like of shape = n_samples_static_gain, default = ([0]) + Static gain input. + y_train : array-like of shape = n_samples, defalult = ([0]) + The target data used in the identification process. + psi : ndarray of floats, default = ([[0],[0]]) + Matrix of static regressors. + + Returns + ------- + J : ndarray + Matrix referring to the objectives. + W : ndarray + Matrix referring to weights. + E : ndarray + Matrix of the Euclidean norm. + Array_theta : ndarray + Matrix with parameters for each weight. + HR : ndarray + H matrix multiplied by R. + QR : ndarray + Q matrix multiplied by R. + w : ndarray, default = ([[0],[0]]) + Matrix with weights. + """ + HR = None + QR = None + # 217 to 218 => Checking if the weights add up to 1. + if np.round(sum(W[:, 0]), 5) != 1: + W = self.weights() + E = np.zeros(np.shape(W)[1]) + Array_theta = np.zeros((np.shape(W)[1], np.shape(self.final_model)[0])) + # 222 to 257 => Calculation of the Parameters as a result of the input data. + PSI_aux1 = (psi).T.dot(psi) + PSI_aux2 = (psi.T).dot(y_train) + for i in range(0, np.shape(W)[1]): + theta1 = W[0, i] * PSI_aux1 + theta2 = W[0, i] * PSI_aux2 + w = 1 + if self.sf == True: + if i == 0: + QR = self.static_function(x_static, y_static)[0] + QR_aux1 = (QR.T).dot(QR) + QR_aux2 = (QR.T).dot(y_static) + theta1 = W[w, i] * QR_aux1 + theta1 + theta2 = theta2 + (W[w, i] * QR_aux2).reshape(-1, 1) + w = w + 1 + if self.sg == True: + if i == 0: + HR = self.static_gain(x_static, y_static, gain)[0] + HR_aux1 = (HR.T).dot(HR) + HR_aux2 = (HR.T).dot(gain) + theta1 = W[w, i] * HR_aux1 + theta1 + theta2 = theta2 + (W[w, i] * HR_aux2).reshape(-1, 1) + w = w + 1 + if i == 0: + J = np.zeros((w, np.shape(W)[1])) + Theta = ((np.linalg.inv(theta1)).dot(theta2)).reshape(-1, 1) + Array_theta[i, :] = Theta.T + J[0, i] = (((y_train) - (psi.dot(Theta))).T).dot( + (y_train) - (psi.dot(Theta)) + ) + w = 1 + if self.sg == True: + J[w, i] = (((gain) - (HR.dot(Theta))).T).dot((gain) - (HR.dot(Theta))) + w = w + 1 + if self.sf == True: + J[w, i] = (((y_static) - (QR.dot(Theta))).T).dot( + (y_static) - (QR.dot(Theta)) + ) + for i in range(0, np.shape(W)[1]): + E[i] = np.sqrt(np.sum(J[:, i] ** 2)) # Normalizing quadratic errors. + if self.norm == True: + for i in range(0, np.shape(J)[0]): + J[i, :] = J[i, :] / np.max(J[i, :]) + E = E / np.max(E) + # Finding the smallest squared error in relation to the three objectives. + min_value = min(E) + position = list(E).index(min_value) + return J, W, E, Array_theta, HR, QR, position From 433a514de1e57e46b34431d16a181b0cbb35952a Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Thu, 21 Sep 2023 19:48:25 -0300 Subject: [PATCH 02/11] refactoring all methods with focus on efficiency, better readability, improved docstrings, improved loops, improved conditions and many more. Besides, rewrite the notebooks to follow the new code --- examples/datasets/buck_id.csv | 1002 ++++++++++++++ examples/datasets/buck_valid.csv | 1000 ++++++++++++++ examples/multiobjective.ipynb | 352 +++-- .../multiobjective_parameter_estimation.ipynb | 1190 ++++++++--------- .../multiobjective_parameter_estimation.py | 282 ---- .../__init__.py | 2 + .../estimators.py | 472 +++++++ 7 files changed, 3209 insertions(+), 1091 deletions(-) create mode 100644 examples/datasets/buck_id.csv create mode 100644 examples/datasets/buck_valid.csv delete mode 100644 sysidentpy/multiobjective/multiobjective_parameter_estimation.py rename sysidentpy/{multiobjective => multiobjective_parameter_estimation}/__init__.py (88%) create mode 100644 sysidentpy/multiobjective_parameter_estimation/estimators.py diff --git a/examples/datasets/buck_id.csv b/examples/datasets/buck_id.csv new file mode 100644 index 00000000..69b1b6b5 --- /dev/null +++ b/examples/datasets/buck_id.csv @@ -0,0 +1,1002 @@ 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+0.01992,2.51,12.0 +0.01993,2.51,12.0 +0.01994,2.51,12.0 +0.01995,2.51,12.0 +0.01996,2.51,12.0 +0.01997,2.51,12.0 +0.01998,2.51,12.0 +0.01999,2.51,12.0 diff --git a/examples/multiobjective.ipynb b/examples/multiobjective.ipynb index 8389d1fb..7197d5b8 100644 --- a/examples/multiobjective.ipynb +++ b/examples/multiobjective.ipynb @@ -11,9 +11,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Example: Buck converter\n", + "## Example: Buck converter\n", "\n", - "Example created by Gabriel Bueno Leandro\n", + "Example created by Gabriel Bueno Leandro, Samir Milani Martins and Wilson Rocha\n", "\n", "
A buck converter is a type of DC/DC converter that steps down the voltage from its input to its output while increasing the current. It is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors, such as a diode and a transistor, and at least one energy storage element, such as a capacitor or inductor. Modern buck converters often replace the diode with a second transistor for synchronous rectification. Buck converters are similar to boost converters, which step up the voltage from their input to their output.
\n", "\n", @@ -28,12 +28,11 @@ "metadata": {}, "outputs": [], "source": [ - "# Importing the libraries and methods needed to run the notebook.\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", - "import pandas as pd \n", + "import pandas as pd\n", "from sysidentpy.model_structure_selection import FROLS\n", - "from sysidentpy.multiobjective.multiobjective_parameter_estimation import IM\n", + "from sysidentpy.multiobjective_parameter_estimation import AILS\n", "from sysidentpy.basis_function._basis_function import Polynomial\n", "from sysidentpy.utils.display_results import results\n", "from sysidentpy.utils.plotting import plot_results\n", @@ -49,40 +48,32 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ "# Reading Buck's input and output data\n", - "data_train = pd.read_csv(r'datasets/buck.txt' , sep=\" \", header=None).to_numpy()\n", - "data_valid = pd.read_csv(r'datasets/buck_val.txt' , sep =\" \", header=None).to_numpy()\n", - "\n", - "# Separating the identification data\n", - "data_samples_train = data_train[:, 2]\n", - "data_out_train = data_train[:, 6]\n", - "data_int_train = data_train[:, 4]\n", - "\n", - "# Separating the validation data\n", - "data_samples_valid = data_valid[:, 2]\n", - "data_out_valid = data_valid[:, 6]\n", - "data_int_valid = data_valid[:, 4]\n", + "df_train = pd.read_csv(r'datasets/buck_id.csv')\n", + "df_valid = pd.read_csv(r'datasets/buck_valid.csv')\n", "\n", "# Plotting the measured output (identification and validation data)\n", "plt.figure(1)\n", "plt.title('Output')\n", - "plt.plot(data_samples_train, data_out_train, label='Identification', linewidth=1.5)\n", - "plt.plot(data_samples_valid, data_out_valid , label='Validation', linewidth=1.5)\n", + "plt.plot(df_train.sampling_time, df_train.y, label='Identification', linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.y , label='Validation', linewidth=1.5)\n", "plt.xlabel('Samples')\n", "plt.ylabel('y')\n", "plt.legend()\n", @@ -91,17 +82,19 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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Ngn9yPPKrB/j5KmYA0KaKj31jLoYQ9BfuNEJbmIQv5WOjAUSivS8nFUMoxeefaY7wRl9CfdlMAmPp41AIbd7MCUiCvtvyCkBVSXkWP4D2GILroHKb+m0hpKIqwKRiCKVaCMV85aW4ZLKZBFxkMbiMNJuAIvcHUwge05b1UyHkEFwHlYO3PV8tBCFi/5NUDKEkC6GluIVQiksm25aQQnBsIWSzZiEYfuJrDGFbl5G7enMZNny1ECTqTOV8DKHcHWQJJptG6cBLcRm1lf/NOg6FoKYQDE/JZhWPDYRw2Km7+nIWQtrTRqekXWl1S9ZzCyGnxYt14CUFlZNQCBZDcE3fbXkF0KbqlYWQ6xva5yEE/7miLT8PwZ82FyJEtRDCGEIiFkIUhRB2okU7vlKDyr3AQkjC0vEIUwgek1W8iiHU1wQPSlU4TyDl2GWUUwhVaX/aXEjkF+ZcDKHcQeWo5Fxaxe6tUiyEpILKrmcq93GXkS2h6THZrF/DTr9z/ARGDqrnc/sEmR1dB5VzCsEnJViIRHYZJRRDiOwyisNCSCqo7FohtCU3D8EDTCF4TNYzl9HAftVc+PlP5v8vJYYZBd+HnQYuowgaITGXESW6jBzGEHpNUFnNZWT4ie/DToNUDu7qy3g+MS0V9YXU+6ByDBZCEkFliCeG0IddRn235RWAbzGEznDpMspWgIUQqb2+T0yLqhAkFd0ETCyobDEEl/TdllcAWVU8zfMGhMoqhlxGPrnJConc3HzQ1tPUFbkEeEUVQh+cmGbDTg1fyap6OyYfcumg+9Cw06jzLnLXpNy/XWQLIeI8hIoIKscwMc1iCIaPtGXVu7UQCimhu4iE9woBIroocmXK3Q7HMYTIuToIh532gqCyxRAMX/FtlFFHUim3QeW8QvBUCUZO5ue9hZBTCMXk8zyoHNtMZbMQDA/JZv3tHCG3PkBfcxmVYCGU/beLeL5sKTEEz2cqO5+YZsNODU9pU79zGeF6TWVtX5rTRyJ7UBJd9M/hPATfYwg5Beg0w2JbAorcH0wheIz67jJyPMoo73n3tMkSed6FUv74ATEMO41YXzYLaDK5m8CtQkhyxTQPMIXgMb5PTHPtMsp7WtzV6JTIo6oSG8ue0MS0/MzsBFZMA9y+lVhQ2fCUrPo7axfCmcoO62vPoupnmyP/FKrJmDmRLYSoMYSIE780oXkXcVkIFkMwfCTr6ZrKOVzPQ1DfLYTIyfwSchmVuh6Cq4lp+WR+SUzEA6cWgg07NXylLev5xDQcv5wlNTgnIpEH3SRqIUQoF/lCRw0qJzTvIq8PLIbgClMIHpNVf90n0C5bpIXnI9DerfjZ5uguMs8thKgdeKkznxMbZutaIfTdbrHvtrwCyGaVtMe/kGsXruaHnbqpzzmRg8q+xxB6i4UQ07BTnxOIxUzfbXkF4PtM5dybvKvHMeu7ywiiTlWmMiyEYtW5dkG5Ji4LwVxGhocEE9M87R1pH3XjymWUe7Ar3mWUpIUQBbMQusaGnRq+oup56opQtEgZQCNQCUHl6KOqEmqEy+R7vscQ8h23DTt1hSkEj2nzbE3ljuSDyo4eSN9nKkdeIS4pCyE4eYQiri2EwvLlJGchOExwl7WgsuEpwTwET3tH4ggqh/V66jKKPjPb89QVvcZCiCt1Rd/tFvtuyysA9X3YaS6o7Eoh5Gcqu6nPOb7PQyh5YloUhRDl7TvJ9R8Kz+8AUwiGr6jn2U7zQWVXLiPPZypHt9Z6iYXgWsG4Jg4LwXU67QrDFILHJDV4MSrOg8od6vWNyC4j1YR+uDgsBIfDWJ0Th4WQZPwneUwheIzv92a7y8iVhZCU6yEa0deLMQuhLMRmIfh5/5UDUwgeo6i3AVZwbyF0rNc3UlFXTOtVMQSP5yHEcT7f38JiJjaFICKjROQxEVkhIstE5OvdlP2UiLSJyIy45KlEfL838wFv56OM/CT6ekBmIZQFsxCcE+cSRxngG6q6WET6A4tE5PequrywkIikgWuA38YoS0Wi+K0QnAeVPV8PIfKKab5rcoshGF0Qm4WgqmtUdXH4fSOwAhjRSdHzgPuB9+KSpVIJnkV/O5acZK5nKvs6GU+IGi+plFxGji2EXpG6wnNlHjNliSGIyBhgCvB8h+0jgJOBm4ocf46ILBSRhWvXro1NTv/we9ip6/TX+eR2nirByC6jisl26mjFNBJyGXU8v7O6/Lz/ykHsCkFEGggsgPNVdUOH3dcDF6vm1uDrHFW9WVWnqurUYcOGxSSpfyQ2ejEi7S4jN/ie/jpIXdELLIRSXEY+p64wC8E5ccYQEJFqAmVwt6rO76TIVGBu+KY5FDhORDKq+ss45aoUfI8h5IRztYym757gYB5ChIK+ZzstyWVE8fb0pvTXfdxCiE0hSNDLzwFWqOoPOiujqmMLyt8G/NqUQTuqfg87Tbl+HpP2PBRBKsJCoIQOvFh1EevrVemvzUKIi+nA6cBSEWkKt30bGA2gqt3GDQz/LYScsnI3U9n3UUae5zJy3oFH1PhmIfQaYlMIqvo0JVxZVT0zLlkqFd9jCO3TEPpGLiOhEtZUzp2/G0qKIRBBC/YiC6Gw3j6IzVT2GK2YFdPc1Od7LqOURBxRlZRp57wD72MWguepU8qBKQSP8T/I6jioXAHDTqO5x5K2EIoQ2ULoUL7rCks7vytyw2adL8jh5/1XDkwh+Izv8S3nFoLfw05FJJp7LPHAZB+xEPIWkasV08xCMIXgMcF7pr83p+vV3LyPIUQNKieWyyh3elcxhFLfwHuJy8jXN5IyYArBY3xfIKc9dYXjeQietlmImssom1CnErWDjPgmHPUNPHELwfG4Z19vwDJgCsFjfB8Al3Lsws1V5KtVlJKII6p8GHbaHZE7cMcKxjlxWQhuqqtETCF4TOKu6CI4DyqHn94mt6uYoLJrC8H3GIJZCK4wheAxit/DTh0vh0A26/nENCLOVO6zFkK5cXyNLYZgCsFn/J+YFkjnfB6Cm+qcE7iMomAWQlkwC8E5phA8RsHre7N9UIvjeQi+ttn3BXIStxB6SwzB1xswfkwh+Iz6G2AF9y6j9m7FzzZHV4BmIZSFuFJX9GFMIXiMer5ATsq1y8jzUR659hYNLCdtIRQjco4Q3y2Ejud3VY+nN2AZMIXgMd7HEMJPV6OM8vV62uj2F1JfLYTc6SN24FFWTItSX2+xEMxlZArBZ5LKkRYV50Flvw2E6CvEJTZeOGqqidxEM0cuo94SQzALwRSCz/i+QE6uv3A3D8HzYaeRV4hLKnVFqT7/ohXmDohYn1kIlU6k9RBE5LLOtqvqFW7FMQrx3kJwXJ/vFkKO4vrAcwvBdVDZLIReQ9QFcj4u+F4HHA+scC+OUYjvMQTnQeXw01clWFoyv0qwEKLKaBZCXyGSQlDV7xf+LyLXAQ/GIpGxLR7fnM5dRnkLwc82R25v4hZCMcxC6ByzEHoaQ+gH7O5SEGNbciNZfL418xaCo/p8Xw8h+gpxlRJDcDTs1CyEXkPUGMJS2u+KNDAMsPhBjFTEvRmXheBpmyMn80vM19fHYgj5YbOuJ6Z5egOWgagxhOMLvmeAd1U1E4M8Rojvs3ahcOaum/rarSI/2xx9ZnZfsxA6nL9s5NrraMU0399IykDUGMJf4hbE2JZ85+jxvdkeZO0jFkLUILrvecsjWwhRF7xIykJwnbrCYgg2D8FTKuHWbA+yuqnP9zb7n8uo8Pzd7Y6oeX1fMc2S2znHFIKnVMK9mXPtuI/p+dno6C71hHMZOXuj9zyXkevsiomt6+APphA8xfdZu1A46sbxTGUntbkn+qiqpCwEx6OCnM98do1ZCK4xheApFZHR17XLyPPn0ft5CH3WQrAYgitMIXiOr50jFL4xu7IQAny1iqIn8+urFoLFECodUwie4vusXXA/7NR3syhyUNl7CyF/QMT9vloIudPbPARXmELwFN9n7UIpb8zRUHxvb/BpMYQe1uecuFJX9F1MIXhKJWT+bF8fwN08BL/b6/k8hNhiCMXoJTEEcxmZQvCVxCZ/loD7eQjqbfwA2rs7b9dDiHrOyBaC5yumWXI755hC8BTf0zgE5N6Y+4aFENlllPhM5WIdeDjRzNXENLMQeg2mEDylEiyEyEtKRkQpdc2B8tIeM4nQ4mLrFcdBbMnozELoK5hC8BTPB9wAJXaQEch6biJEHtSiWZJ1GZU5qGwWQq/BFIKveJ7GAUpZHyAifuuDPhxUNguhrxCbQhCRUSLymIisEJFlIvL1TsqcKCJLRKRJRBaKyKfjkqfS8D2NA7THN1wmt/NY/5WwQlxS5p1ZCDuEWQiR10PoCRngG6q6WET6A4tE5PequrygzALgQVVVEZkE3AeMj1GmiqES7s3259FVUFm9DqJ7H1Q2C2EHMQshNgtBVdeo6uLw+0ZgBTCiQ5lN2t6b7ITNDMlTCbem62STiQ/OKUIqcsyktww79d1CiLpeQ0Qq4S0sZsoSQxCRMcAU4PlO9p0sIn8E/hc4q4vjzwldSgvXrl0bq6y+0L5Ajr83p7gedorfCjBHURdZn7MQOpy/XEQeFltyxY7rqxxiVwgi0gDcD5yvqhs67lfVB1R1PHAScGVndajqzao6VVWnDhs2LFZ5faEShp3G4cL1WgFGXiEuaQvBVQzB8xXTLLmdc2JVCCJSTaAM7lbV+d2VVdUngXEiMjROmSqFykhd4TqorJ63N/j03kIoSsQO3PcV02JbIMfnuzBe4hxlJMAcYIWq/qCLMnuE5RCR/YEaYF1cMlUS+fxAHr+ttD+P7mYq+/wsRl8hLuGGOEs1UYpFVFi+XJiF4Jo4RxlNB04HlopIU7jt28BoAFW9CfgS8GURaQWagZnqyiFd6VSEhRB8uvzFKqK9UVwyicYQHKWa8H3FtNgWyOm7xKYQVPVpitwiqnoNcE1cMlQylRBDyP28xcflR0PV8+R2OZdR0RhmQhaCpMPTu3LxmIXQ17CZyp5SEQvkOBbN94lpuQ7IXwshFwRui3pAkd0RffSJxRA6nH+HsRiCKQRPqYQFciKncoiI56mMSnCRJWQhpMxCcFOtz3dhvJhC8JRKGGWUk82VyyirWiHZTosUTNpCyBazEOKKIfSS1BV9GFMInlIJMQTnFgK+tzf4LD6qKukYQh8ZZZQKQ6CRXWTFMJeRKQRPqYQFcqIne4tGUE0ltLdIwaQ0W+QYguPUFYlZCKECzGbc1GdBZVMIvqIV9LLiztBWr5/F6Kk6koohRHQZ5WMMjiamJW0hFHWRRaWCHrqYMIXgOT7fminHS6b5HlT2P9tpQkHlpN6sc0F0VwrBLARTCL7Sfm/6e3O6Dir7nu00+gpxCQUnS3UZuQoqJ2YhOHYZmYVgCsFXKmKBHMepZIJcRv62OPKw96Q0W8nDTos9/r5bCI6DymYhmELwlUq4N2OZh1AJ7S1aMqlRRiXGECp+PQSzEFxjCsFTKmHYqXOXEX4/iu2pK3ydqRxx2Cm9zEKwGIIzTCF4SmUMO436xhwN/9dDCD69txCKuVCijjIqOWhb4UFlsxBMIfhKRVgIeY+CKwvB75miOeVc1CJKLIYQ1WUU0UJI14T1FXHJ5F1QZe5OXAeVK+GhixlTCJ5SCbPo48gt5vOzGHnBtMQtBEfDTtPVwWfbVjf1ucZmKjvHFIK35JLb+XtzRl90Phr+p66I6CJLPIYQdaZyRAuhqEKIGKR2jc1Udo4pBE+piOR2UVM5REQ9T26Xm4fXFi13RdzibE/kYacRYwh5hdBa5MRRg9SOyQeViy5QERGzEEwheEoluDNzM5XdZTv1+1GsSgePS1GF4Hu2U+cuo4gKxjXOYwgV8BYWM6YQPKUSFshJhx1K8TfmaAQuI3/bW50OZNvaFiG3T7nflqGEbKcRXTyRXUYJWQgiwTkthuAMUwieUgkL5KRDC6HN5RKaTmqKh5rQQmgtphA0SzJB5dywrwgxhCidd1SXUVIxBAjcRhZDcIYpBE+pBOs15+8vOlErIp5nv6Y6skLA89QVERVWVAshqRgCBFaRs5nK+Uod11c5mELwlEpIbpe3EBzG9PxtLVRXhQoh42lQuZQYQkkWgqcxBAgtBNdB5b6LKQRPyQVqUx73kPlRNw4npvmsACPHEHwfdqrZaPLlg8rFXEYJWgiplLmMHGIKwVNy96bPwzBFhJQ4dBl5biFEjiH4Puw0agxBBFLV/s5DgMBCsKCyM0wheErurTvl+S+UTonDoLLfL2fRYwgJabZcJ7/uje7LlRL0TtdEiCF0OH85KRZDeP0PsGFNtLrMQjCF4CvtLiO/b86UiMOgst/rIbQrBF9jCKGF8OwN3ZeLGkOAwG2U2VKkvgRjCOnq7l1ad30JbvlstLqSysnkEX235Z6jFaIQ0ilxNw/BewshjCFkfI0hRDxnKfJV10OmpXh9pZzfJVV1XcuXk2vD29Hqyrmecoq1D2IKwVOyFRBDgGBymrugst+ICNVp8T+GUJQSLISqOmgtphASjCFU13ctX6lpsXOjlSJfx96HKQRPyb11+zzKKMemFjejPHxfDwEC+TZv7aajaWsNfNqJtCOqhVBCDKGqDjLNxSoMT59Ad1JVB80fdr6v1NFHZiGYQvCVfAzBc43Qpsq8xasd1aYVoQCffWNd1zuvHAqb1+G1hVCSy6gECyGR+I/Cm890vitbLClfx/KhQvB9JEeM9N2We04lDDsF2HfEQAbUVTupK+t5DAFg5/61DKyP0N4kGlKzEzTsAo17dl8u6jwEgKpSYggJdCcDRkD1Tp3vMwuhZEwheEolTEwD2G/kwOJB1ogEuYz8bvAeOzfQkonim06oHaOnReiYS4ghVNdBaxGXUZIxhMY9uh4W21aiQshbCKYQDM/IxRB896nXVadpybQ5WSTH9wVyAOqq0rS0RlAISTWkqr64z7+kGEIECyHJGEJ1feAa6iyAbBZCyVQlLUC5+L/X3+fvbnm+03177tzAa+9tAuCkybtyzL7DOfeuRQCM36U/fz99DEtWf8Tdz7/JsP61jB26E01vref0g3Zj/uLVfLg58FXeftaBnHHrCwBcedK+1FaluPaRlby/aftx3P3rqrjqpH353bJ3+d+la7jjrAOpSgsX3vsyf93Q/gD6biHUVadRhbHfehiASSMHsmT1R9uVS0nXC+n8aNYU/uWel4DA4vCZuuoUr767iTHf/N/8tlzbzkj/lstz3qR3lycjYHUdrH8TZhdcx+Oug52Gwi/O7Fl9774Cv74QWj6CVU/DLhPhkK/Br74GU06HdK4bSWjYKcDDF8FLd7VbCyMOgAG7tpebXeS+qh0AWzYE3/uwhSCulj8sF1OnTtWFCxeWfNy9L77JxfcvjUEiN4wduhN/fv/j7bbPPecgDtq9MQGJorH8nQ0c96OnnNW336hB/OqfpzurzzWP/fE9/v62Fzvdt6rub7fdMHt7xRg7f3oC7jhh222Ne8K617YvG0W+lb+Be07rvsxn/h0evRIuXQtVNdFldcHrfwgmn7nkvMXQOM5tnX5QVGPHZuOJyCgReUxEVojIMhH5eidl/k5EloR/z4jIfnHJc8i4oXFV7YQNzZ2PiCg+5j1Z9tl1gNP6PDeIOHL8zkmL0D27H97Jxh146fvkse1ZT7siyYlpw6e4r7MPWwhxuowywDdUdbGI9AcWicjvVbXQlv4zcLiqfigixwI3A9PiEKa2ujLDJb4rBNf4HkOoSHbUC1BVXySfUZIxhDr3dfbhGEJsv6CqrlHVxeH3jcAKYESHMs+oam5WyXPAyLjkqU37/SOv+7jzB87VCJ5KwfRBDLSs37Hjq2q73/9WLjaXYAzBJX3YQiiLSheRMcAUoPOobsA/AL/p4vhzRGShiCxcu3Ztj2ToV1uZP/KEXf0Osrpm5OB+SYvghl33T1qCdjZ3M5EuCkOLzGt4/Q8wYGSyq8Q5q68a6vrWM1dI7EFlEWkAngCuVtX5XZQ5EvgJ8GlV7fbu7WlQOUduyGA6JWzNZEmngtw06ZQEmTtVaW1T6qpTZNqUNlVUoSoleU9sVUoY/++PAPD0xUcytKGW1rYsWQ1y5qdTQnPBeeqqUjS3tuWHkOYem0xWOfq/nuSvG1r4+dnTmLDrQFICNeHKXGkRqtKV4erKZpWtbVm2tmWpTqXy+Y2qwuR3WVVqqlJks1CVFqrTKTZtyZAWYWtblqqUkMkq/WurvJ+dDcGciS2ZLNXp4LetTgsbPvqQQdVZqgckHGfItsHWj4POsrpfMDoIgsyguTkDtf2j19eWga2bgrUH/roUfnYMNHwCvhY+h5oNzlPugHIO1aCNqaqgjemaYMSQajBZr7W5fbGf3PoOmg22SRpaNwf70tWB26uYRVS5FH2wYh12KiLVwP3A3d0og0nALcCxxZSBC+qq298ocumMC7cVUhvh6jTuVEtddXq7OnKdeo7+XXTsOcsl8gxYT0mlhLrU9tehOxrCC1xP5VlvIpJva64dwxo9GbiQSkNdQbC/ftCO1Zeuaq+jIVR2VbXbniNJRLZvY+FbfrrDc5Xu8GCnPWmHB8Q5ykiAOcAKVf1BF2VGA/OB01X11bhkiZPaKleX0P+3YsPIB44ra7S6EZE4LYTpwOnAUhFpCrd9GxgNoKo3AZcBjcBPQndKRlWnxiiTM8Y09mPVus077N7Ye/gA/rT2Y3aq0BiH0ceoCfMG7TIxWTmMWOgzE9Ncs27TFt78YDNTRg/eoXo2b83Q9NZ67+dJGEaeVU/D8P1Ki0MYPlD07bVXKITW1lZWr15NS0uxnCtGuairq2PkyJFUV1duXMQwehnJBpXLxerVq+nfvz9jxozxPhlcX0BVWbduHatXr2bs2LFJi2MYRkQqY0xjEVpaWmhsbDRl4AkiQmNjo1lshlFh9AqFAP6nie5r2O9hGJVHr1EIhmEYxo5hCsERDQ0NnW4/88wzmTdvXo/qbGpq4uGHH87//+CDD/Ld734XgLVr1zJt2jSmTJnCU089xXHHHcf69etLPsfjjz/OM8+0r0l70003cccdd/RIXsMwKpteEVTurTQ1NbFw4UKOO+44AE444QROOCHIdb9gwQLGjx/P7bffDsChhx7ao3M8/vjjNDQ0cMghhwBw7rnnOpDcMIxKpNcphMsfWsbydzY4rXOfXQfwnS9OiFRWVTnvvPN49NFHGTt27DZLSy5atIgLL7yQTZs2MXToUG677TaGDx/OEUccwbRp03jsscdYv349c+bMYdq0aVx22WU0Nzfz9NNP861vfYvm5mYWLlzIP/7jP/Jv//ZvNDc3M3nyZJ599ln23ntvFi5cyNChQ7njjju47rrrEBEmTZrEnXfeyUMPPcRVV13F1q1baWxs5O6776a5uZmbbrqJdDrNXXfdxY9//GMWLFhAQ0MDF110EU1NTZx77rls3ryZcePGceuttzJ48OBO5e2pQjIMwx/MZeSYBx54gJUrV7J06VJ++tOf5t0xra2tnHfeecybN49FixZx1llncckll+SPy2QyvPDCC1x//fVcfvnl1NTUcMUVVzBz5kyampqYOXNmvuzkyZO32VdfX5/ft2zZMq6++moeffRRXn75ZX74wx8C8OlPf5rnnnuOl156idNOO41rr72WMWPGcO6553LBBRfQ1NS0Xaf+5S9/mWuuuYYlS5YwceJELr/88i7lNQyj8ul1FkLUN/m4ePLJJ5k1axbpdJpdd92Vz3zmMwCsXLmSV155hc997nMAtLW1MXz48Pxxp5xyCgAHHHAAq1at6vH5H330UWbMmMHQocHM5yFDhgDBXI2ZM2eyZs0atm7dWnR+wEcffcT69es5/PBgBa4zzjiDU0891bm8hmH4Q69TCD7Q2ZBLVWXChAk8++yznR5TWxuk3E2n02QymR6fW1U7Pf95553HhRdeyAknnMDjjz/O7Nmze3wOcCevYRj+YC4jxxx22GHMnTuXtrY21qxZw2OPPQbAJz/5SdauXZtXCK2trSxbtqzbuvr378/GjRtLOv9nP/tZ7rvvPtatCzKJf/DBB0Dwxj9iRLBgXS4Q3d05Bg4cyODBg3nqqacAuPPOO/PWgmEYvRNTCI45+eST2XPPPZk4cSJf+cpX8p1oTU0N8+bN4+KLL2a//fZj8uTJ2wz37IwjjzyS5cuXM3nyZO69995I558wYQKXXHIJhx9+OPvttx8XXnghALNnz+bUU0/l0EMPzbuTAL74xS/ywAMPMHny5Hznn+P222/nX//1X5k0aRJNTU1cdtllpVwKwzAqjF6R3G7FihXsvffeCUlkdIX9LobhFUXTB5iFYBiGYQCmEAzDMIwQUwiGYRgGYArBMAzDCDGFYBiGYQCmEAzDMIwQUwgOOOKII/jtb3+7zbbrr7+er371q12Wzw2d7Spt9ezZs7nuuuu6Pe8vf/lLli9fnv//sssu4w9/+EOJ0huGYQSYQnDArFmzmDt37jbb5s6dy6xZs4oe+/DDDzNo0KAenbejQrjiiis46qijelSXYRhG78tl9Jtvwl+Xuq1zl4lw7He73D1jxgwuvfRStmzZQm1tLatWreKdd97h5z//ORdccAHNzc3MmDGj06ygY8aMyaetvvrqq7njjjsYNWoUw4YN44ADDgDgpz/9KTfffDNbt25ljz324M4776SpqYkHH3yQJ554gquuuor777+fK6+8kuOPP54ZM2awYMECLrroIjKZDJ/61Ke48cYbqa2tZcyYMZxxxhk89NBDtLa28otf/ILx48e7vV6GYVQkZiE4oLGxkQMPPJBHHnkECKyDmTNncvXVV7Nw4UKWLFnCE088wZIlS7qsY9GiRcydO5eXXnqJ+fPn8+KLL+b3nXLKKbz44ou8/PLL7L333syZM4dDDjmEE044ge9973s0NTUxbty4fPmWlhbOPPNM7r33XpYuXUomk+HGG2/M7x86dCiLFy/mK1/5SlG3lGEYfYfeZyF08yYfJzm30YknnsjcuXO59dZbue+++7j55pvJZDKsWbOG5cuXM2nSpE6Pf+qppzj55JPp168fQH5lNIBXXnmFSy+9lPXr17Np0yaOPvrobmVZuXIlY8eOZa+99gKC1NX//d//zfnnnw9sm7p6/vz5O9p0wzB6CWYhOOKkk05iwYIFLF68mObmZgYPHsx1113HggULWLJkCV/4whdoaWnpto7O0lZDsC7zDTfcwNKlS/nOd75TtJ5i+aksdbVhGJ1hCsERDQ0NHHHEEZx11lnMmjWLDRs2sNNOOzFw4EDeffddfvOb33R7/GGHHcYDDzxAc3MzGzdu5KGHHsrv27hxI8OHD6e1tZW77747v72r1NXjx49n1apVvP7664ClrjYMIxq9z2WUILNmzeKUU05h7ty5jB8/nilTpjBhwgR23313pk+f3u2x+++/PzNnzmTy5Mnstttu2yxneeWVVzJt2jR22203Jk6cmFcCp512GmeffTY/+tGPmDdvXr58XV0dP/vZzzj11FPzQeVzzz03nkYbhtFrsPTXRmzY72IYXmHprw3DMIxomEIwDMMwgF6kECrN9dXbsd/DMCqPXqEQ6urqWLdunXVCnqCqrFu3jrq6uqRFMQyjBHrFKKORI0eyevVq1q5dm7QoRkhdXR0jR45MWgzDMEqgVyiE6upqxo4dm7QYhmEYFU1sLiMRGSUij4nIChFZJiJf76TMeBF5VkS2iMhFccliGIZhFCdOCyEDfENVF4tIf2CRiPxeVZcXlPkA+BfgpBjlMAzDMCIQm4WgqmtUdXH4fSOwAhjRocx7qvoi0BqXHIZhGEY0yhJDEJExwBTg+R4efw5wTvjvJhFZ2UNRhgLv9/DYOPFVLvBXNpOrNEyu0uiNcj2iqsd0VyB2hSAiDcD9wPmquqEndajqzcDNDmRZqKpTd7Qe1/gqF/grm8lVGiZXafRVuWKdhyAi1QTK4G5VtcT7hmEYHhPnKCMB5gArVPUHcZ3HMAzDcEOcLqPpwOnAUhFpCrd9GxgNoKo3icguwEJgAJAVkfOBfXrqWorADrudYsJXucBf2Uyu0jC5SqNPylVx6a8NwzCMeOgVuYwMwzCMHccUgmEYhhGgqhXzBxwDrAReB77ZyX4BfhTuXwLsX+xYYAjwe+C18HNwwb5vheVXAkcnINv3gD+G5R8ABoXbxwDNQFP4d1OZ5ZoNvF1w/uNKvWYxyXVvgUyrgKYyX69bgfeAVzocs8P3WExyJX1/dSVX0vdXV3Ildn8Bo4DHCCb4LgO+7vL+ypcvVsCXPyANvAHsDtQALxMEoAvLHAf8JryoBwHPFzsWuDb3wwDfBK4Jv+8TlqsFxobHp8ss2+eBqvD7NQWyjel4s5ZZrtnARZ2cL9I1i0uuDsd/H7isXNcr3HcYsH/Hc+3oPRajXIndX0XkSuz+6k6uJO8vYDjtyqE/8CoO+7DcXyW5jA4EXlfVP6nqVmAucGKHMicCd2jAc8AgERle5NgTgdvD77fTnlfpRGCuqm5R1T8TaNkDyymbqv5OVTPh8c8BpeaTjuuadUXUaxarXOGQ578B7ikir0u5UNUnCfJzdWRH77FY5Er4/uruenVFotcrRxL3l3afCshFHwZUVgxhBPBWwf+r6ZAbqZsy3R37CVVdA0H+JWDnEs4Xt2yFnEXw5pBjrIi8JCJPiMihCcj1NRFZIiK3isjgEs4Xt1wAhwLvquprBdvivl7dsaP3WFxyFVLu+6sYSd1fUUj0/uokFZCLPgyoLIUgnWzTiGWiHNuT85VStseyicglBNlj7w43rQFGq+oU4ELg5yIyoIxy3QiMAyaHsny/hPPFKVeOWWz79laO69UTynG9iguRzP3VHUneX1FI7P4qMRVQyW2sJIWwmiCwkmMk8E7EMt0d+27OVAw/3yvhfHHLhoicARwP/J2GjsHQBFwXfl9E4Bvcq1xyqeq7qtqmqlngp7SboVGvWZzXqwo4hSAASChvOa5Xd+zoPRaXXEneX12S8P3VLUneX92kAnLRh+UbUxF/BLOq/0QQHMkFZCZ0KPMFtg3IvFDsWIKRFoUBmWvD7xPYNiDzJ7oOKscl2zHAcmBYh7qG5WQhCFC9DQwpo1zDC46/gMBPGfmaxSVXwTV7otzXq2D/GDofzdPjeyxGuRK7v4rIldj91Z1cSd5f4f93ANd3Uu8O92H5urrb6dsfQQT+VQINfEm47Vzg3IKL9t/h/qXA1O6ODbc3AgsIhmwtKPwhgUvC8iuBYxOQ7XUCH2ATBcPZgC8RDD17GVgMfLHMct0Zll0CPMi2D3CkaxaHXOG+23J1FGwr1/W6h8B90ErwdvYPru6xmORK+v7qSq6k769O5Ury/gI+TeDuWUKH4bg46sNU1VJXGIZhGAGVFEMwDMMwYsQUgmEYhgGYQjAMwzBCTCEYhmEYgCkEwzAMI8QUgtGnEZFLRGRZmCahSUSmxXiux0XEu4XbDSNHnEtoGobXiMjBBLN091fVLSIylGDCkGH0ScxCMPoyw4H3VXULgKq+r6rviMhlIvKiiLwiIjeH2S1zb/j/JSJPisgKEfmUiMwXkddE5KqwzBgR+aOI3B5aHfNEpF/HE4vI50XkWRFZLCK/CHPUICLfFZHl4bHXlfFaGIYpBKNP8ztglIi8KiI/EZHDw+03qOqnVHVfoJ7AisixVVUPA24CfgX8M7AvcKaINIZlPgncrKqTgA3AVwtPGloilwJHqer+wELgQhEZApxMkM5gEnBVDG02jC4xhWD0WVR1E3AAcA6wFrhXRM4EjhSR50VkKfAZgpwwOR4MP5cCyzTIU7+FIE9MLpHYW6r6f+H3uwjSDhRyEMHiJf8nIk3AGcBuBMqjBbhFRE4BNrtqq2FEwWIIRp9GVduAx4HHQwXwT8Akghwyb4nIbKCu4JAt4We24Hvu/9zz1DEfTGcpjn+vqrM6yiMiBwKfBU4DvkagkAyjLJiFYPRZROSTIrJnwabJBEnAAN4P/fozelD16DBgDUHu/Kc77H8OmC4ie4Ry9BORvcLzDVTVh4HzQ3kMo2yYhWD0ZRqAH4vIIIIFYl4ncB+tJ3AJrQJe7EG9K4AzROR/CDJQ3li4U1XXhq6pe0SkNtx8KbAR+JWI1BFYERf04NyG0WMs26lhOCRc3vDXYUDaMCoKcxkZhmEYgFkIhmEYRohZCIZhGAZgCsEwDMMIMYVgGIZhAKYQDMMwjBBTCIZhGAYA/x9OVckBot6shQAAAABJRU5ErkJggg==", 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" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -109,8 +102,8 @@ "# Plotting the measured input(identification and validation data)\n", "plt.figure(2)\n", "plt.title('Input')\n", - "plt.plot(data_samples_train, data_int_train, label='Identification', linewidth=1.5)\n", - "plt.plot(data_samples_valid, data_int_valid, label='Validation', linewidth=1.5)\n", + "plt.plot(df_train.sampling_time, df_train.input, label='Identification', linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.input, label='Validation', linewidth=1.5)\n", "plt.ylim(2.1, 2.6)\n", "plt.ylabel('u')\n", "plt.xlabel('Samples')\n", @@ -141,17 +134,19 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -170,32 +165,6 @@ "plt.show()" ] }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(3)\n", - "samples = np.arange(0, 5, 5/len(Uo))\n", - "plt.title('Static input buck converte')\n", - "plt.ylabel('$\\\\bar{u}$')\n", - "plt.xlabel('Samples')\n", - "plt.plot(samples, Uo, linewidth=1.5, linestyle='-', marker='o')\n", - "plt.show()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -219,12 +188,14 @@ "outputs": [ { "data": { - "image/png": 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", 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7e3t0dHQ0ugwzs/5E5RY04x6ImZn1Aw4QMzPLxQFiZma5OEDMzCwXB4iZmeXiADEzs1wcIGZmlosDxMzMcnGAmJlZLg4QMzPLxQFiZma5OEDMzCwXB4iZmeXiADEzs1wcIGZmlktTBYikmyWtSo91klaVaXdWuo/6Y5LOrm+VZmYGDbgnek8i4n3d05K+AmwubiPpUGA+MB14CbhL0g8jYm3dCjUzs+baA+mW7nV+CkW3tk0OBlZExIsRsRO4F/jHetZnZmZNGiDAccCzZfYqVgPHSxolaW9gDjC+3IokLZDUIaljw4YNfVSumVnrqfshLEnLgf1LLLooIr6Xpk+l9N4HEbFG0peAnwBbgYeBneX6i4hFwCLI7om+G6WbmVmBugdIRMzqabmkQcBcYFoP61gMLE7tPw901rJGMzPrXVOdRE9mAU9ERNlQkPT6iHhO0gSysDm6btWZmRnQnOdA5lF0+ErSGEl3FsxaIulx4A7gExHx53oWaGZmTbgHEhGnl5jXRXayvPv5cfWsyczMdtWMeyBmZtYPOEDMzCwXB4iZmeXiADEzs1wcIGZmlosDxMzMcnGAmJlZLg4QMzPLxQFiZma5OEDMzCyXqr7KRNJM4J+ATWT35XgEWB0Rf619aWZm1syq/S6s64FPpNe9GXg3cAhwUG3LMjOzZldtgDwZEd9N07fWuhgzM+s/qj0Hcq+kc9I9y83MrIVVuwdyCHAo8C+SHgRWAasiwnsjZmYtpqoAiYi5AJKG8mqYHIUPZ5mZtZyyASLpgYiYnqY/ExELJR0DPBoRW4CO9KgZSVOAq4EhwE7g4xHxQIl2JwFXAW3ANRHxxVrWUWjpyvV8edmv6dq0jTEjh3Le7Mm8+4ixNZs/UPpo1b4H+va1at+tsH21oIgovUBaGRFHpOmjI+KXkm4h2+sYBDxOdhnvIxFxW02KkX4MfC0ifiRpDnB+RMwoatMG/Ab4B6AT+BVwakQ83tv629vbo6Oj8sxbunI9F97+KNt2vPy3eUMHt/GeaWNZ8uD63Z7/hbmHAfT7Plq174G+fa3adytsX5UhUvacd08B8vOIOL7Msr3IDmEdBhwWEedWU03ZYqRlwLURcbOkU4F3RsT7i9ocDVwaEbPT8wsBIuILva2/2gA59os/Y/2mbdVsQlX2bMuuYXjp5Vf6dR+t2vdA375W7Xugb9/YkUP5zwtmVvOSsgFS9hBWqfCQNAo4BdgOPAbcEhHfrqaSXpwNLJN0BdkVYseUaDMWeKbgeSdwZLkVSloALACYMGFCVcV09WF4QH1+QBvxS9AqfQ/07WvVvgf69tXyc63ay3i/C4wGPg98GdgsaU01K5C0XNLqEo+TgY8B50TEeOAcYHGpVZSYV3o3CoiIRRHRHhHto0ePrqZUxowcWnJ+W5mrmKudP3bkUMYOgD5ate+Bvn2t2vdA375yn2t5VBsgwyPis8CzEXECcCrwrWpWEBGzIuLQEo/vAacBt6emtwLTS6yiExhf8Hwc0FXldlTkvNmTGTq47TXzhg5u49Qjx9dk/nmzJw+IPlq174G+fa3adytsX61U+/9Atqd//yppaEQskXQv8KUa1dMFnADcA8wE1pZo8yvgjZIOBNYD84D3l2i327pPNJW6iqF94r41md+tv/fRqn0P9O1r1b5bZft2V9mT6CUbS+8B7gY+BLQDvwDOioiafBeWpLeSXZ47iCysPh4RD0oaQ3a57pzUbg5wJdllvNdGxOcqWX+1J9HNzCzHVVi9rlH6INlVWN+OiMdyFlZXDhAzs6pVfxVWybVIa4FHgYfJvsbkGxGxbncqMzOz/qnak+jfBP4IbATeBqyW9Kikz0oaXPPqzMysaVV7Ev0DETGl+4mkq8nOh7wAfBU4s3almZlZM6t2D2SzpDd3P4mIVcBREXEFcGwtCzMzs+ZW7R7IR4EbJK0iOwcyGej+r5N71q4sMzNrdlXtgUTEE2T/ue8u4PXAk8A7JL0O+I/al2dmZs2q2j0QIuJlsv8lXnwPkP9Vk4rMzKxfqPYciJmZGeAAMTOznBwgZmaWiwPEzMxycYCYmVkuDhAzM8vFAWJmZrk4QMzMLBcHiJmZ5dJUASJpiqQVklZJ6pBU6p7oSLpW0nOSVte7RjMzyzRVgACXAwvTV8Zfkp6X8i3gpDrVZGZmJTRbgASwT5oeAXSVbBTxc+BP9SrKzMx2VfWXKfaxs4Flkq4gC7djdneFkhYACwAmTJiwu6szM7Ok7gEiaTmwf4lFFwEnAudExBJJpwCLgVm7019ELAIWAbS3t8furMvMzF5V9wCJiLKBIOk64Kz09FbgmroUZWZmVWu2cyBdwAlpeiawtoG1mJlZD5otQOYDX5H0MPB50rkLSWMk3dndSNJNwC+ByZI6JX24IdWambWwpjqJHhH3AdNKzO8C5hQ8P7WedZmZ2a6abQ/EzMz6CQeImZnl4gAxM7NcHCBmZpaLA8TMzHJxgJiZWS4OEDMzy8UBYmZmuThAzMwsFweImZnl4gAxM7NcHCBmZpaLA8TMzHJxgJiZWS4OEDMzy6WpAkTSFEkrJK2S1CFpeok24yXdLWmNpMcknVVqXWZm1reaKkCAy4GFETEFuCQ9L7YT+FREHAwcBXxC0pvqV6KZmUHzBUgA+6TpEWT3SH9tg4g/RMRDaXoLsAYYW7cKzcwMaLJb2gJnA8skXUEWbsf01FjSJOAI4P4e2iwg3Vt9woQJtarTzKzlKSLq26G0HNi/xKKLgBOBeyNiiaRTgAURMavMeoYB9wKfi4jbK+m7vb09Ojo6clZuZtaSVHZBvQOkJ5I2AyMjIiQJ2BwR+5RoNxj4AbAsIr5a6fodIGZmVSsbIM12DqQLOCFNzwTWFjdIwbIYWFNNeJiZWW012zmQ+cBVkgYB20nnLiSNAa6JiDnAscAHgUclrUqv+3RE3NmAes3MWlZTBUhE3AdMKzG/C5hT0KbsLpWZmdVHsx3CMjOzfsIBYmZmuThAzMwsFweImZnl4gAxM7NcHCBmZpaLA8TMzHJxgJiZWS4OEDMzy8UBYmZmuThAzMwsFweImZnl4gAxM7NcHCBmZpaLA8TMzHJxgJiZWS5NFSCSpkhaIWmVpA5J00u0GSLpAUkPS3pM0sJG1Gpm1uqaKkCAy4GFETEFuCQ9L/ZXYGZEHA5MAU6SdFTdKjQzM6DJbmkLBLBPmh4BdO3SICKArenp4PSIulRnZmZ/02wBcjawTNIVZHtHx5RqJKkNeBA4CPj3iLi/3AolLQAWAEyYMKHW9ZqZtSxlf9DXsUNpObB/iUUXAScC90bEEkmnAAsiYlYP6xoJfBc4MyJW99Z3e3t7dHR05CvczKw1qeyCegdITyRtBkZGREgSsDki9unlNZ8B/hIRV/S2fgeImVnVygZIs51E7wJOSNMzgbXFDSSNTnseSBoKzAKeqFeBZmaWabZzIPOBqyQNAraTzl1IGgNcExFzgAOAb6fzIHsAt0TEDxpVsJlZq2qqAImI+4BpJeZ3AXPS9CPAEXUuzczMijTbISwzM+snHCBmZpaLA8TMzHJxgJiZWS4OEDMzy8UBYmZmuThAzMwsFweImZnl4gAxM7NcHCBmZpaLA8TMzHJxgJiZWS4OEDMzy8UBYmZmuThAzMwsFweImZnl0lQBImmKpBWSVknqkDS9h7ZtklZK8t0IzcwaoKkCBLgcWBgRU4BL0vNyzgLW1KMoMzPbVbMFSAD7pOkRQFepRpLGAW8HrqlTXWZmVqSp7okOnA0sk3QFWbgdU6bdlcD5wPDeVihpAbAAYMKECTUp0szMGrAHImm5pNUlHicDHwPOiYjxwDnA4hKvfwfwXEQ8WEl/EbEoItojon306NE13RYzs1amiGh0DX8jaTMwMiJCkoDNEbFPUZsvAB8EdgJDyA553R4RH+ht/e3t7dHR0dEHlZuZDVgqt6DZzoF0ASek6ZnA2uIGEXFhRIyLiEnAPOBnlYSHmZnVVrOdA5kPXCVpELCddO5C0hjgmoiY08jizMzsVU11CKuv+RCWmVnV+s0hLDMz6yccIGZmlosDxMzMcnGAmJlZLi11El3SBuCpnC/fD3i+huXUiuuqjuuqjuuqzkCs6/mIOKnUgpYKkN0hqSMi2htdRzHXVR3XVR3XVZ1Wq8uHsMzMLBcHiJmZ5eIAqdyiRhdQhuuqjuuqjuuqTkvV5XMgZmaWi/dAzMwsFweImZnl4gApIOkkSb+W9KSkC0osl6R/TcsfkTS1iWqbIWmzpFXpcUkdarpW0nOSVpdZ3pDxqqCuuo9V6ne8pLslrZH0mKSzSrSp+5hVWFcjfr6GSHpA0sOproUl2jRivCqpqyE/Y6nvNkkrJf2gxLLajldE+JGdB2oDfgu8AdgTeBh4U1GbOcCPyL6d8ijg/iaqbQbwgzqP2fHAVGB1meWNGq/e6qr7WKV+DwCmpunhwG+a4Weswroa8fMlYFiaHgzcDxzVBONVSV0N+RlLff8zcGOp/ms9Xt4DedV04MmI+F1EvAT8B3ByUZuTgesiswIYKemAJqmt7iLi58CfemjSkPGqoK6GiIg/RMRDaXoLsAYYW9Ss7mNWYV11l8Zga3o6OD2Kr/ppxHhVUldDSBoHvB24pkyTmo6XA+RVY4FnCp53susvUSVt+kKl/R6ddqt/JOmQOtTVm0aNVyUaOlaSJgFHkP31WqihY9ZDXdCAMUuHY1YBzwE/iYimGK8K6oLG/IxdCZwPvFJmeU3HywHyqlI3TSn+q6KSNn2hkn4fAiZGxOHAvwFL+7qoCjRqvHrT0LGSNAxYApwdES8ULy7xkrqMWS91NWTMIuLliJgCjAOmSzq0qElDxquCuuo+XpLeATwXEQ/21KzEvNzj5QB5VScwvuD5OLJ7tFfbpi/02m9EvNC9Wx0RdwKDJe1Xh9p60qjx6lEjx0rSYLIP6Rsi4vYSTRoyZr3V1eifr4jYBNwDFH+pX0N/xsrV1aDxOhZ4l6R1ZIe5Z0q6vqhNTcfLAfKqXwFvlHSgpD2BecD3i9p8H/jv6UqGo4DNEfGHZqhN0v6SlKank723G+tQW08aNV49atRYpT4XA2si4qtlmtV9zCqpqxFjJmm0pJFpeigwC3iiqFkjxqvXuhoxXhFxYUSMi4hJZJ8RP4uIDxQ1q+l4Dcpf7sASETsl/Q9gGdlVT9dGxGOSzkjLrwbuJLuK4UngReBDTVTbe4GPSdoJbAPmRbrsoq9IuonsapP9JHUCnyE7odjQ8aqgrrqPVXIs8EHg0XT8HODTwISC2hoxZpXU1YgxOwD4tqQ2sg/gWyLiB03wO1lJXY36GdtFX46Xv8rEzMxy8SEsMzPLxQFiZma5OEDMzCwXB4iZmeXiADEzs1x8Ga9Zg0n6f2RfYrgzItobXY9ZpXwZr5mZ5eJDWGZmlosDxKyBJK1I34CLpLGSOhpcklnFHCBmDZK+K2kC8FSa9Wbg0cZVZFYdB4hZ4xwE/L7gO5IcINavOEDMGucwXhsY7cAjDarFrGoOELPG2Zfsm1qRdDDZrUi9B2L9hi/jNWsQSeOBH5LdS2I1MD8ixvf8KrPm4QAxM7NcfAjLzMxycYCYmVkuDhAzM8vFAWJmZrk4QMzMLBcHiJmZ5eIAMTOzXBwgZmaWy/8Ha/fI+5TE7awAAAAASUVORK5CYII=", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -264,7 +235,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\55359\\OneDrive\\Área de Trabalho\\Clone_git\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", + "C:\\Users\\wilso\\Desktop\\projects\\GitHub\\gabriel\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", " You'll have to use FROLS(estimator=LeastSquares()) instead. \n", " The only change is that you'll have to define the estimator first instead of passing a string like 'least_squares'. \n", " This change will make easier to implement new estimators and it'll improve code readability.\n", @@ -274,7 +245,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -283,11 +254,10 @@ } ], "source": [ - "# Informing test and validation data\n", - "x_train = data_int_train.reshape(-1, 1)\n", - "y_train = data_out_train.reshape(-1, 1)\n", - "x_valid = data_int_valid.reshape(-1, 1)\n", - "y_valid = data_out_valid.reshape(-1, 1)\n", + "x_train = df_train.input.values.reshape(-1, 1)\n", + "y_train = df_train.y.values.reshape(-1, 1)\n", + "x_valid = df_valid.input.values.reshape(-1, 1)\n", + "y_valid = df_valid.y.values.reshape(-1, 1)\n", "\n", "basis_function = Polynomial(degree=2)\n", "\n", @@ -308,31 +278,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "with the parameters all in hand, we can already calculate the parameters in a multiobjective way:" + "The Affine Information Least Squares method will now be called to perform several calculations related to the performance of the objectives. These calculations include the computation of the performance matrix (J), the weights matrix (w), the Euclidean norm (E), and the values of $\\theta$ for each weight. Additionally, the method will also calculate the product of matrix H and matrix R, as well as the product of matrix Q and matrix R." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [ - "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", - "mult = IM(model_type=model.model_type,\n", - " final_model = model.final_model)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The method will now be called to perform several calculations related to the performance of the objectives. These calculations include the computation of the performance matrix (J), the weights matrix (w), the Euclidean norm (E), and the values of $\\theta$ for each weight. Additionally, the method will also calculate the product of matrix H and matrix R, as well as the product of matrix Q and matrix R." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, "outputs": [ { "data": { @@ -367,53 +319,53 @@ " \n", " \n", " 0\n", - " 0.990080\n", - " 0.003078\n", " 0.006842\n", - " 0.992584\n", - " 9.825995e-02\n", - " 0.305492\n", - " 0.261455\n", + " 0.003078\n", + " 0.990080\n", + " 0.999970\n", + " 1.095046e-05\n", + " 0.000013\n", + " 0.245244\n", " \n", " \n", " 1\n", - " 0.990080\n", - " 0.002347\n", " 0.007573\n", - " 0.991990\n", - " 1.551666e-01\n", - " 0.266591\n", - " 0.286111\n", + " 0.002347\n", + " 0.990080\n", + " 0.999938\n", + " 2.294674e-05\n", + " 0.000016\n", + " 0.245236\n", " \n", " \n", " 2\n", - " 0.990080\n", - " 0.001538\n", " 0.008382\n", - " 0.990885\n", - " 3.048969e-01\n", - " 0.220806\n", - " 0.382836\n", + " 0.001538\n", + " 0.990080\n", + " 0.999885\n", + " 6.504949e-05\n", + " 0.000018\n", + " 0.245223\n", " \n", " \n", " 3\n", - " 0.990080\n", - " 0.000642\n", " 0.009277\n", - " 0.988248\n", - " 1.000000e+00\n", - " 0.142808\n", - " 1.000000\n", + " 0.000642\n", + " 0.990080\n", + " 0.999717\n", + " 4.505604e-04\n", + " 0.000021\n", + " 0.245183\n", " \n", " \n", " 4\n", - " 0.894495\n", - " 0.098663\n", " 0.006842\n", - " 0.995100\n", - " 1.364999e-03\n", - " 0.660485\n", - " 0.244160\n", + " 0.098663\n", + " 0.894495\n", + " 1.000000\n", + " 7.393244e-08\n", + " 0.000015\n", + " 0.245252\n", " \n", " \n", " ...\n", @@ -427,53 +379,53 @@ " \n", " \n", " 2290\n", - " 0.006842\n", - " 0.333527\n", " 0.659632\n", - " 0.999976\n", - " 5.944270e-08\n", - " 0.000020\n", - " 0.245246\n", + " 0.333527\n", + " 0.006842\n", + " 0.995896\n", + " 3.965701e-04\n", + " 1.000000\n", + " 0.244489\n", " \n", " \n", " 2291\n", - " 0.006842\n", - " 0.263039\n", " 0.730119\n", - " 0.999985\n", - " 6.124624e-08\n", - " 0.000018\n", - " 0.245248\n", + " 0.263039\n", + " 0.006842\n", + " 0.995632\n", + " 5.602985e-04\n", + " 0.972842\n", + " 0.244412\n", " \n", " \n", " 2292\n", - " 0.006842\n", - " 0.185020\n", " 0.808139\n", - " 0.999993\n", - " 6.466930e-08\n", - " 0.000016\n", - " 0.245250\n", + " 0.185020\n", + " 0.006842\n", + " 0.995364\n", + " 8.321075e-04\n", + " 0.868299\n", + " 0.244300\n", " \n", " \n", " 2293\n", - " 0.006842\n", - " 0.098663\n", " 0.894495\n", - " 1.000000\n", - " 7.400899e-08\n", - " 0.000015\n", - " 0.245252\n", + " 0.098663\n", + " 0.006842\n", + " 0.995100\n", + " 1.365000e-03\n", + " 0.660485\n", + " 0.244160\n", " \n", " \n", " 2294\n", - " 0.006842\n", - " 0.003078\n", " 0.990080\n", - " 0.999971\n", - " 1.094929e-05\n", - " 0.000013\n", - " 0.245244\n", + " 0.003078\n", + " 0.006842\n", + " 0.992584\n", + " 9.825994e-02\n", + " 0.305492\n", + " 0.261455\n", " \n", " \n", "\n", @@ -482,38 +434,41 @@ ], "text/plain": [ " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", - "0 0.990080 0.003078 0.006842 0.992584 9.825995e-02 0.305492 0.261455\n", - "1 0.990080 0.002347 0.007573 0.991990 1.551666e-01 0.266591 0.286111\n", - "2 0.990080 0.001538 0.008382 0.990885 3.048969e-01 0.220806 0.382836\n", - "3 0.990080 0.000642 0.009277 0.988248 1.000000e+00 0.142808 1.000000\n", - "4 0.894495 0.098663 0.006842 0.995100 1.364999e-03 0.660485 0.244160\n", + "0 0.006842 0.003078 0.990080 0.999970 1.095046e-05 0.000013 0.245244\n", + "1 0.007573 0.002347 0.990080 0.999938 2.294674e-05 0.000016 0.245236\n", + "2 0.008382 0.001538 0.990080 0.999885 6.504949e-05 0.000018 0.245223\n", + "3 0.009277 0.000642 0.990080 0.999717 4.505604e-04 0.000021 0.245183\n", + "4 0.006842 0.098663 0.894495 1.000000 7.393244e-08 0.000015 0.245252\n", "... ... ... ... ... ... ... ...\n", - "2290 0.006842 0.333527 0.659632 0.999976 5.944270e-08 0.000020 0.245246\n", - "2291 0.006842 0.263039 0.730119 0.999985 6.124624e-08 0.000018 0.245248\n", - "2292 0.006842 0.185020 0.808139 0.999993 6.466930e-08 0.000016 0.245250\n", - "2293 0.006842 0.098663 0.894495 1.000000 7.400899e-08 0.000015 0.245252\n", - "2294 0.006842 0.003078 0.990080 0.999971 1.094929e-05 0.000013 0.245244\n", + "2290 0.659632 0.333527 0.006842 0.995896 3.965701e-04 1.000000 0.244489\n", + "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972842 0.244412\n", + "2292 0.808139 0.185020 0.006842 0.995364 8.321075e-04 0.868299 0.244300\n", + "2293 0.894495 0.098663 0.006842 0.995100 1.365000e-03 0.660485 0.244160\n", + "2294 0.990080 0.003078 0.006842 0.992584 9.825994e-02 0.305492 0.261455\n", "\n", "[2295 rows x 7 columns]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Method to calculate the parameters\n", - "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(y_train=y_train[2:],\n", - " gain=gain,y_static=Yo,\n", - " x_static=Uo, psi=model.psi)\n", - "result = {'w1': w[0,:],\n", - " 'w2': w[2,:],\n", - " 'w3': w[1,:],\n", - " 'J_ls': J[0,:],\n", - " 'J_sg': J[1,:],\n", - " 'J_sf': J[2,:],\n", - " '||J||:': E}\n", + "test = AILS(final_model=model.final_model)\n", + "\n", + "J, w, E, Theta, HR, QR, position = test.affine_information_least_squares(\n", + " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=model.psi\n", + ")\n", + "result = {\n", + " \"w1\": w[0, :],\n", + " \"w2\": w[2, :],\n", + " \"w3\": w[1, :],\n", + " \"J_ls\": J[0, :],\n", + " \"J_sg\": J[1, :],\n", + " \"J_sf\": J[2, :],\n", + " \"||J||:\": E,\n", + "}\n", "pd.DataFrame(result)" ] }, @@ -521,12 +476,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "at this point, we can select a value for $\\theta$ that corresponds to the weights in our model. This value of $\\theta$ will determine the relative importance of each objective in the performance matrix, and will affect the overall performance of the model." + "At this point, we can select a value for $\\theta$ that corresponds to the weights in our model. This value of $\\theta$ will determine the relative importance of each objective in the performance matrix, and will affect the overall performance of the model." ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -620,42 +575,39 @@ "7 y(k-2)^2 2.5832E-01 3.827E-06" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.theta = Theta[position, :].reshape(-1, 1)\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", " results(\n", - " model.final_model, model.theta, model.err,\n", - " model.n_terms, err_precision=3, dtype='sci'\n", - " ),\n", - " columns=['Regressors', 'Parameters', 'ERR'])\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", "r" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "dynamic data in graphical form:" - ] - }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] }, "metadata": {}, @@ -677,14 +629,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" + "
" ] }, "metadata": {}, @@ -714,14 +666,14 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -734,7 +686,7 @@ "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{y}$')\n", + "plt.xlabel('$\\\\bar{y}$')\n", "plt.legend()\n", "plt.show()" ] @@ -750,14 +702,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -792,7 +744,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.8.11" }, "orig_nbformat": 4 }, diff --git a/examples/multiobjective_parameter_estimation.ipynb b/examples/multiobjective_parameter_estimation.ipynb index 62e491d3..438513b7 100644 --- a/examples/multiobjective_parameter_estimation.ipynb +++ b/examples/multiobjective_parameter_estimation.ipynb @@ -5,9 +5,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Example: Buck converter\n", + "## Example: Buck converter\n", "\n", - "Example created by Gabriel Bueno Leandro\n", + "Example created by Gabriel Bueno Leandro, Samir Milani Martins and Wilson Rocha Lacerda Junior\n", "\n", "
A buck converter is a type of DC/DC converter that decreases the voltage (while increasing the current) from its input (power supply) to its output (load). It is similar to a boost converter (elevator) and is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors (a diode and a transistor, although modern buck converters replace the diode with a second transistor used for synchronous rectification) and at least one energy storage element, a capacitor, inductor or both combined.
" ] @@ -34,12 +34,11 @@ }, "outputs": [], "source": [ - "# Importing the libraries and methods needed to run the notebook.\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", - "import pandas as pd \n", + "import pandas as pd\n", "from sysidentpy.model_structure_selection import FROLS\n", - "from sysidentpy.multiobjective.multiobjective_parameter_estimation import IM\n", + "from sysidentpy.multiobjective_parameter_estimation import AILS\n", "from sysidentpy.basis_function._basis_function import Polynomial\n", "from sysidentpy.utils.display_results import results\n", "from sysidentpy.utils.plotting import plot_results\n", @@ -66,37 +65,29 @@ "outputs": [ { "data": { - "image/png": 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Cfrdx40YwDIPt27dLOuaWLVtwxx13KNE9nlmzZqF79+4N1hcXFyM/P1/RtswICTMEQVgH0swQErn11luxcuVKHD58uMF3H3zwAbp3744ePXpIOmbTpk2RmJioVBdDkpWVhbi4OE3aMjIkzBAEYW58BBgSZghpXHXVVcjMzMSCBQt81ldVVeHzzz/HuHHj8Je//AUtWrRAYmIi8vLy8Omnn4Y8pr+Zaf/+/Rg4cCDi4+PRuXNnLF++vME+jz76KDp06IDExES0bdsWTz31FJxOJwBgwYIFeOaZZ7Bz504wDAOGYfj++puZdu/ejaFDhyIhIQHp6em44447UFFRwX8/ZcoUjBs3Di+//DKys7ORnp6Oe++9l2/LrFB5WYIgCEIdWBZwVunTtiMRYJiwm8XExGDSpElYsGAB/vrXv4Kp3+eLL75AbW0tbrvtNnz66ad49NFH0ahRI3z77beYOHEi2rZti0svvTTs8d1uN8aPH4+MjAxs2rQJ5eXlPv41HCkpKViwYAFycnKwe/du3H777UhJScEjjzyCCRMm4JdffsHSpUvx448/AgBSU1MbHKOqqgqjRo1Cnz59sGXLFpSUlOC2227D1KlTfYS1VatWITs7G6tWrcKBAwcwYcIEdO/eHbfffnvY8zEqJMwQBGEdyMxkLJxVwPM5+rT9+HEgNknUprfccgteeuklrF69GkOGDAHgMTGNHz8ezZs3x0MPPcRve99992Hp0qX44osvRAkzP/74I/bs2YNDhw6hRYsWAIDnn3++gZ/Lk08+yS+3adMGM2bMwOeff45HHnkECQkJSE5ORkxMDLKysoK29fHHH+P8+fP46KOPkJTkOfd58+Zh9OjRePHFF9GsWTMAQJMmTTBv3jzY7XZ06tQJV155JVasWEHCDEEQBEGYlU6dOqFfv3744IMPMGTIEBw8eBBr167FDz/8AJfLhRdeeAGff/45jh07hpqaGtTU1PDCQjj27NmDVq1a8YIMAPTt27fBdl9++SXmzp2LAwcOoKKiAnV1dWjUqJGk89izZw+6devm07f+/fvD7XZj7969vDDTpUsX2O12fpvs7Gzs3r1bUltGg4QZgiCsA2lmjIUj0aMh0attCdx6662YOnUq3nzzTXz44Ydo3bo1Lr/8crz00kt47bXXMHfuXOTl5SEpKQnTpk1DbW2tqOOyAe5Jxs/8tWnTJtxwww145plnMHLkSKSmpuKzzz7DK6+8IukcWJZtcOxAbTocjgbfud1uSW0ZDRJmCIKwECTMGAqGEW3q0Zvrr78eDzzwAD755BMsXLgQt99+OxiGwdq1azF27Fj83//9HwCPD8z+/ftx4YUXijpu586dceTIERw/fhw5OR6T28aNG322Wb9+PVq3bo0nnniCX+cfXRUbGwuXyxW2rYULF6KyspLXzqxfvx42mw0dOnQQ1V+zQtFMBEGYHCpnQMgnOTkZEyZMwOOPP47jx49jypQpAID27dtj+fLl2LBhA/bs2YM777wTJ06cEH3cYcOGoWPHjpg0aRJ27tyJtWvX+ggtXBtHjhzBZ599hoMHD+L111/H4sWLfbZp06YNCgsLUVBQgFOnTqGmpqZBWzfddBPi4+MxefJk/PLLL1i1ahXuu+8+TJw4kTcxWRUSZgiCMDesUD1OwgwRObfeeivOnj2LYcOGoVWrVgCAp556Cj169MDIkSMxePBgZGVlYdy4caKPabPZsHjxYtTU1KB379647bbb8Nxzz/lsM3bsWDz44IOYOnUqunfvjg0bNuCpp57y2eaaa67BqFGjMGTIEDRt2jRgeHhiYiKWLVuGM2fO4JJLLsG1116Lyy+/HPPmzZM+GCaDYQMZ9CxEeXk5UlNTUVZWJtmZiiAIE3B4I/DhKM/yjH1AirXfQI1MdXU1CgsLkZubi/j4eL27Q5gApe4Z0swQBGFyKGkeQUQ7JMwQBGFuWPKZIYhoh4QZgiBMDmlmCCLa0VWYWbNmDUaPHo2cnJygZcz37NmDMWPGIDU1FSkpKejTpw+OHDmifWcJgjAmQgdg0swQRFSiqzBTWVmJbt26BfW0PnjwIAYMGIBOnTph9erV2LlzJ5566ilyLCMIwgsVmjQcFo8rIRREqXtF16R5+fn5DepTCHniiSdwxRVXYM6cOfy6tm3batE1xThf60JCrD38hgRBRAj5zBgFLrNsVVUVEhISdO4NYQaqqjyFSP2zEkvFsBmA3W43vv32WzzyyCMYOXIkduzYgdzcXMycOTNkjD9XN4OjvLxcg94GZtXvJbh5wRY8PLIj7h3SXrd+EISlIc2MYbDb7WjcuDFKSkoAePKeBEuvT0Q3LMuiqqoKJSUlaNy4sU+tqEgwrDBTUlKCiooKvPDCC/j73/+OF198EUuXLsX48eOxatUqDBo0KOB+s2fPxjPPPKNxbwPzyFe7AAAvLdtLwgxBqAZpZowEV9WZE2gIIhSNGzcOWQlcLIYVZriiV1xmRAB8ZsR33nknqDAzc+ZMTJ8+nf9cXl6Oli1bqt/hALjd9GAlCNWhDMCGgmEYZGdnIzMzE06nU+/uEAbG4XDI1shwGFaYycjIQExMDDp37uyz/sILL8S6deuC7hcXF4e4uDi1uycKN70lEoT6+FiZ6DdnFOx2u2ITFUGEw7B5ZmJjY3HJJZdg7969Puv37duH1q1b69QraZBihiC0gHxmCCLa0VUzU1FRgQMHDvCfuYqgaWlpaNWqFR5++GFMmDABAwcOxJAhQ7B06VL873//w+rVq/XrtARIM0MQGkAZgAki6tFVmNm6dSuGDBnCf+Z8XSZPnowFCxbg6quvxjvvvIPZs2fj/vvvR8eOHfHVV19hwIABenVZEuQzQxBaQL8zgoh2dBVmBg8eHDZhzi233IJbbrlFox4pC8kyBKEBpI0hiKjHsD4zVsBFD1mCUB8qZ0AQUQ8JMypCKb0JQgvIAZggoh0SZlSEzEwEoQHkAEwQUY9h88yYFafLjdMVtahzu+EiaSbqOVftRNl5b+KwnNQE2GyU3l1ZBL+zumr9uqEl1eWAIxGw0yNcFWorgaozAFggJYfG2QTQFVKQOpcbFzzxvd7dIAzCgZIKXPn6WtTUeX06BndsigU399axVxZEqI159zLgiROAw8JFDk/tB94ZADTrCty+Qu/eWI/jO4D3Bns/N+9F42wCyMykICXnagKuT0uK1bgnhBHYU1yOmjo3GAaItXt+ajuOlOrbKSvirvP9fGK3Pv3QioMrPRqoY1v17ok1WfW87+djW8l8aQJImFEQ4e1+/9D2eOf/egAA2mYk6dMhQlfq6uuL9W+XgeXTB3rWudyhdiEiwV+YsfrE43Z5l61+rkbB/x4jDAcJMyrCMB7fCMoEHJ3UuTzXPcbOwF7vJ1NHflTKE20TjU8oOgnHmhBt95gJIWFGQXwy/jIM7Lwwo1OHCF3hBJcYGwNHvZmJhBkVcPlVZmYs7mBNwoz2+N9jhOEgYUZB/CcqW/3okmYmOuFMSjE2G2LqNTMuN0v5h5TGHWUTjVCAEZqcCPUgzYzhIWFGQfz9IWxkZopqnAIzU4zd1mA9oRCuKPOZYYU+M6SZUZxAY0qaGcNDwoyC+E9SnDBDPp/RCecA7LB7NTPC9YRC+GtmWItrK4T3j9XPVQ8CaWGiTftnQkiYURCfSYpleadPMitEJ0KfmRi7V5ghzYzC+L81W/0tmnxm1MVH01f/u7X6PWUBSJhREH+fGc4PkcxM0Ykwmslh8/7UKDO0wvj7jVjdv4GEGXURamG45Ivkm2R4SJhRkDqXbzST18xEk1c0InQAttkYcJYmyjWjMP4mAMsLM4KJlUyWyiO8f2Li69eRZsbokDCjAHUuN2rqXKit832wcGam05W1enSL0Jnyas9DkTMxxdRrZ4S1mgh5HD92BFUn9vuurC7TpzNaUF0GnD/r/Vx21PoOz1ridgNnCr2f7fXZ20uPNnQ0JwwFCTMKMPy1Nej5tx/xf/N/5tc5BG/ipVVOfL3zuE69I/TgVEUNFmw4BABg6u3unFAz/LU1OF56Xq+uWYrf/3kbEvcu8l256Hbg3El9OqQmJ34BXroA2PJP77r3BgHfztCvT1bj42uA82e8n+0Oz99PrgP+lk6Co4EhYUYBCk9VoqLGV2qf1K8NOmU14j/vOlqqca8IPTlYUsEvV9R4NDFjuzfn1+07eU7zPlmRWsSgmnU0/OLUXu07ozYndgOuGvBOqRxFW3TpjiU5KhjL9AuArtf4fu+klxCjQsKMCuQ1T0VqggNJcTGYOqQ9AMr8Gm0I/aS4l7nZ4/PQrWVjAH7+VUTEPMI+gE41C3Hw3mPArDKgWZ7nCytGn3B+Gx1G+q0n84dicGM8bTdw31Zg+DNA95u831MovGEhYUYmgcKuhWG43po85KgXTTiDCK8xVKNJUYTh7wAAm93z14rRJ5zQYosJvJ6QT6AxFi7TWBsWEmZkEsiEKgzDddQLNvQmHl0II5aEpYJiSLhVFG/4e/1vjvNxsGL0iSuIMGNFLZQesKxAmBGYLoXjTU7AhoWEGZkEElGEmhnuIUuJ0qKLYNebLzhJ94MiOLksy7xmpn4SsuIEzwlodj8fIdIWKINwHO0CAUb4NmJFIdkikDAjk0AJ8YR1eOhNPDoJlluIE3SdlGtGNm43y2tGvZqZ+knIihM8J6DZHIHXE/IQjqP/GAfahjAUJMzIJJCZSViHh97Eo5NgwiuXa4Z8ZuTjFIwxrw2NBs0M5xfkv56Qh3Ac/U15/DYWFJItAgkzMmEDGpq80Jt4dCI0MwkFXq8PFd0PchG+IPB+atHgM+NvZiI/DmUQjqNwjIU/YCsKyRaBhBmZhMuhxGlpqKRBdBFMWLFTNJNiCIUZO+8zY2EzUyDnVOF6Qh78ODINtV8NtiGMBgkzKiBMacWZFYKF6hLWRCisCP0HyeyoHEJTnsPuJ8xYUVsR1AGYtAWKEGx8yQHYFAQxDBJiCauZqX/IFlP6+qgimFmR09QdOVMFlmXBMEzA7YjwcAKj3cZ4x5GbiFw1OvVKRZzVnr/+WgOXRrXfWBYoP+6Z3O2xQFKGNu1qBe9gHWJatKKQbBFIMyOTQNFMcQ5hnhnP8v6SCry9+qBm/SL05Zn//cYvx8YIotvq74d/bTqMaZ8XaN0tS/HltiIAAhMT4DXB/PCkDj1SEZYFNr/rWQ402e77Qf0+LH0MeK0z8OqFwEvtgIJP1W9TS7Yv9Pz1H197nHd5w+va9YeQBAkzMgmkmHn8igv55Z6tm/DLBUfPBtiasCJpSbH88v2XX8AvD++cyS/vOFKqZZcsx7F6badPtfqM+rGOb6x9h9TEWeVdbt0f6D/NW7oBAE7sVL8PRzf7fj62Tf02taSixPPXX9N12XTvcl21dv0hJEHCjEz8yxl8c98AtGiSyH9u1igeL17jeeiQn0T0wJmZVs4YhMyUeH790E7N8N97+wMgp3C5cE7WD4/s6F3ZZZznr9UcNYVRNG0u89QMunsd0OvW+u81OF//MbWa/wg3xkOf8l2flAFc/Z7vNoThIGFGJv7TkTD7L4edcotEHS6+ZlDDnxhnFqFwfXk0qMsEWDeaSVhrKlDdIC3Ot4EwY7UxDlIuAhDU/LLYOVsIEmZk4u8yE2jy4nOLUBbgqMFbM6ihcMtHNJFwK4sGdZkA6ybN47QgjA0QPmO0zKvjP6ZWc4blo5kCCDP8OFvsnC0ECTMy8TczOQJMXnx4NpmZogYuO20gYYYSKSoD93Lg85vjJh3WFT7U0EwEK2WgZSi6v8BkOTNTkDw+wnVWE5ItBAkzMmmgmbE3HNIYyvoaVbgENYMcgTR19evIZ0Ye3MuBjzbUp8KxhSaeYDlQtNTMCE1dgLXGFwg+xsJ1VhPgLAQJMzJp4DNjC6SZoayv0YRQ42IPoZkhh3B5cC8HPr854URkpYnHFcSfQ0uNgX8bVjO5BNN+AdZOxmgRSJiRib+ZKaAwYyczUzQhFFoDaWZ4MxP5UMmCdwC2B8gzA1hLcxBUMxPj+70WfeCw0vgCXuEspM+Mxc7ZQpAwI5OG0UyBzApcfSaavKIBl0BoDegzUy/gsCyZmuQQ2AFYMBH5m0XMTLBIGz6aSYNz9ddKWE0zEzKayaJRchaChBmZ+GcADugATPV4ogqhxiWwps67jiLcIod3APYJzbZ5In4Aa71FB3NO1dLMZPXQ7JBmJm6cLXbOFoKEGbn4ySf2AJMXt+5kOWWPjAYqqj0PPJ+aQQKEpicScCPneKnn99TgN2fFyBOu1pS/CYQzf5wrVrf9ij8bCodcxlyrwJ1PQDNT/bpzx33Xu11AnQXrgJkQEmZk4j8VBYxeqX8Tr6x18fVkCGtyrPQ8Br+8GkBgwRbw1cx8s+t4wG2I0Ly2fB9fzsDhb9rlJviv79O4Vyry+UTP32BmpsPrgW0L1Gl7x7+Bl9s3TPN/ai9w4Ed12tSaPd8A5fXP5lCaGXed7zi/1Qd4MRdwUiFhvSFhRib+odm2ABNYh2Yp/PLOo6Uq94jQk883H+GXmzdOCLiNcPL9489K1ftkRbYf8dY569ayse+XjVt5/qqtrdAS7u2/eU/f9W0u8y4XbVWnbe64jB1IzgLiGnm/O75DnTa1RngeOd0bfp/e3rssHOdT+wBnJXDyV9W6RoiDhBmZsALdjLCopJB4hx0zhncAQD4SVkdoVpo9Pi/odncPbgeAItwihXOc/scN3X2KegIArny1fiMLmZk4E8+Qx33XZ7QHhj1Tv41KTsCcb8yQx4GH9gIzj2pbE0oT6n+Hl94NxKc2/DomFhj+rGfZar5CFoGEGZkINTP2AP4R/HeUWyQqsAnugUDOv/7fUYRbZNQFSpjHYcXIE1GRNioJb4HattoYs/W/wxDPcMuds8UgYUYmwmimQM9VDgcVm4wKhO4bgcL0+e+4Ehd0P0REqHIR3twrFpl0WFYgUITITquWJsoVIMeN1fKucM9xJsRDPKRjeQghiNAEEmZk4qOZCfUmTvV4ogKhz1RIzQyVuJAFp5kJlArBctFMQqEsUKSN2hoDd4CQZatlxBWjmbGakGwxSJhREHsI1QzlmokOhGamBlE2AhxkdpQFn/030G/OaloDoVAWSjOjmjBT74sjFKSsNsacMBNKw+IvJAvfZEkxozskzMjE12cm+Hbe+kz0Jm5lfMoEhdDM2MnMJAu+LlNAzYzFtAZCgSFQEUS1NVGBkslZTfvFEcrM5C/AWakquwUgYUYmwmimkGYmG2dmoh+AlfHVzAS/HxxkZpIFp5kJqP2ymtZAKJSF1Myo5QAcyGdGw5pQWiDFAZgX4OhZbiR0FWbWrFmD0aNHIycnBwzDYMmSJT7fT5kyBQzD+Pzr06ePPp0NgvDF2hbih8A9dKkWj7XxiWYS4QBMDuGRwfmeBXyBsFrUCX8eTOAoA5vd81ctTRSvmQkUzWSR+le8MBPKAdjvnEkzYyh0FWYqKyvRrVs3zJs3L+g2o0aNQnFxMf/vu+++07CH4RFWzQ6o8vb7jhyArY2PmSmEcEsOwPLgXgoCZdz2ydZqhQknWMVsDptGPjM+wozFzEz8fRLKAdhfA2aBe8tCBHCN1478/Hzk5+eH3CYuLg5ZWVka9Ug6wts5lGaGMzMdL9M/7fX5WhcSYu16dyOq4e6Hc9UW0R5oTEWNZ9xChmYDngk+mBBgFkIVQAS856dWSv1KrmZRgNDs2gp12tQaZ30mbjGh2RUnPX9Z4YsIeQDrjeF9ZlavXo3MzEx06NABt99+O0pKQhc3q6mpQXl5uc8/NRG++CU4ggsInFnh6Jnz+MeP+1XtUyhW7DmJC/+6FG+tPqBbH6yM2Hc1zgS19fBZlFbVhtmaEFJZU8cLgSFDswFgz/806pWKnNjl+RsoYZ5w/cndgNIBBvt+AE7XPysChWbvWwrUVinbptZUl3nqTwEN608J4YTk0iPA799ZQ+tnIQwtzOTn5+Pjjz/GypUr8corr2DLli0YOnQoamqCVymdPXs2UlNT+X8tW7ZUuZfeG/qhkR2DbnVxq8b88o6jZ4NupzaPfuV5MM5Zule3PliZpDjvhNOsUVzQ7S5p4y19UXiK6jNJoeisVwPROj2p4QaxgnUlezTokcpUnfH8rSkL/H2zrt7l2nPKtn18u3dZWBdKWBOqzOTFc8/84V0OVQk852Lv8vHtIDOTsTC0MDNhwgRceeWV6Nq1K0aPHo3vv/8e+/btw7fffht0n5kzZ6KsrIz/d/ToUVX7yPlvpiXFolmj+KDbpSfH4bUJ3QCQE7CV4XyoLu+U6VOnyZ/s1ATkZngmXXIClgbnd9asUVzgaCaGAfrc41m2QrQN5wtz4ZjA3yc19S4r7QTMtd37DiAp3bs+o723XbOPsc+YhfgtJjQB+txbv4+TNDMGQ1efGalkZ2ejdevW2L8/uJkmLi4OcXHB34iVhs+CLWJbPrcIOX1aFk4uCSXIcHCROJQ4TxquUAnzOLgIHytENIWqywTURzgxAFjlzzdQJBPfrkWixoT9DyegCO8roc+MiN87oS6G1sz4c/r0aRw9ehTZ2dl6d4WHyzMj5l520ORlebhaXSGisnkokWJk1IWqy8TBR9uYfKIFAtdG8ketXDMhC1xaZIyljJlPtmV6jhsJXTUzFRUVOHDA64haWFiIgoICpKWlIS0tDbNmzcI111yD7OxsHDp0CI8//jgyMjJw9dVX69hrX7yCfHhphnP6pKyv1sVdf21DRbZxOKjERUQ4+YrZUsJoTUyg2kj+2Bwe51WlQ6VDCVJWSZznM2bhNDOCkHQyMxkKXYWZrVu3YsiQIfzn6dOnAwAmT56Mt99+G7t378ZHH32E0tJSZGdnY8iQIfj888+RkpKiV5cbwJuZRGhmuDdJF72JWxZOTrWFmmjrodxDkeEtMhlphWOTEag2kj/2GMAJ5U0+oap1W2WMpZiZfAQ4EmaMhK7CzODBg32SzvmzbNkyDXsTGZyZScTcxSf4ojdx6+KSopmhLMAR4RRjZrJSheNweWaE3yktWPAJ+wJMFVbRfkWkmbFIQkYLYSqfGSPidQCmN3FC4DMjQVNH94M06lxiHIAtojUAwmcAFn6ntGDhCqWZsUhBT+GYhdXMCMaZkuYZChJmZCLJzMQ7fJJEb1W4+0GMZoaLZqJQfWlwZtqQPjNWibQBBJqZEFm71TpfdzREM0moL2WVc7YgJMzIhI9mErFtDDl8Wh4Xy0W3kQOwWvAOwKLMTFbQzHC1kUKZmVTSknCTdkAH4Gg0MwkqZ5OZyVCQMCMTr2ZGhJmp/k3yZHm1ml0idITTskgJzT5L5QwkwYVmi3IArjytQY9UxllfLkCMmalG4QzANfW1l0JpZtSqCaUVkZiZas6BHICNBQkzMik4Wip6W/5N3M3ik5+PqNQjQk9eWuYpEyHGh4q7H2Z//zsOlCg8CVmYH371FPqziwnNPrIBOLpFg16phNsFbF/oWRbjAPzxNUC1QvXoaiqAA8s9y6E0M4vvVL4mlJb89l/BB5EOwIU/eWo6id2PUB0SZmRSU+dRAR8rDf92wqWvB4ACHeszEeqRVF+N/IJmyWG3HdGlGb/8WzEJM2JJjPVoBCpCVRxv3c+7fGKnyj1SEeGE2XZQ8O26jvcunz2kTNulgheu1v0bft8h37usdE0oLYlP9S6H08y07utdPlsofj9CdUiYkQlnv7++V4uw28bG2DAzvxMAcgK2Ktx1HdU1K+y2Y7s3x2UXZHj2o4gm0XAOwCHHuEkboEv9BG/maBven4MBWvYOvt3Ah4DU+qK6SvmwcP4yyVlAeruG319ym3fZzGPsFlmbCfDcV9w4S/G1IVSHhBmZeH0kxA0l1eOxNnVi6gYJoAg36Tj531wYU54VIk/C1WUSwtcNkhCdE7LtEJFMgKAmFMw9xi4JSfMA7zi7BL5u9PPVHRJmZMK9UTvEJBaB0G+G3sStBsuy3iKIIu8HinCTDvebiwnnZW2FaBsxOWY4lM6tw03yITMPW2iMxRJwnOn3qzckzMjEKfVNnE+URje/1RBeU4fI+4ETgkm4FQ9fzkCsZsbMJpBQSev8UVqwEFsTCjB3ckKpQgk3zj6aGXqe6w0JMzKRrJmpn+QoUZr1EF5T0ZqZ+vuBhFvx8Ka8qNLMiDEzKSy8hcoxw2GFshFSajMBgnEWplSg36/ekDAjE1EJvARQCnvr4hRoV8QLM5wPFd0PYvHmmQmnmbGQ1kCUz4zCiQJdIvx1rDDGUgUxe4BzJs2M7pAwI5M6PrW6WDMT+UhYlboIzEwxdnIAlopTTG0mwBpZgMWYejgCTbJKtK1HTSgtkSqU2AKYmUgzozskzMiEd/gUUzYbwugVehO3Gpx2hWEAm9j7gYRbyXDjLD6aSaHoHj3g+i7KzMQJFgqZfMRohSwRMSbVATiQmYnQGxJmZOI1M1EobrTDXVOxWhnPtiTcSoV7gYguM5MYzYzCgoVbhPOxFZysfYRdMQ7AgvpM/G70PNcbEeI+EYqqWs+PWGpo9p/naiJu83ytC6Xna8GA8ZkEY2y2Bp8ZBmiaHCdKU+B2s6h1uRHvCFGdlwhKnUT/KcCbn+hcqGy2hA9l5z2TiGgH4PMmzrYdLteLEKU1BlzNJTGh2a7In2e6U1vpXZZiZqo6I1hJwozekDAjg5o6F77bfQKABDNT/URXdPY8fvj1BEZ0CZ8pVsgL3/+Od346KGkfhgEKZ18Zdrsb3tuEgqOl2PLkMKQmiHgTJHz4ZLMn/XtY84cATghesOEQ7h3SHk1T4lTpm1U4eqYKh057Ci+KDs3+5Utg6BNAWluVe6cCa1/x/BUlzNT/Zn94Crj4/+S163YB/73H97ih2vz0RuDxInlt6oHL6VuWQEw+H26bn9/2riPNjO6QmUkGJeXet5F+7TNE7XNR88b88q6isuAbBiGQIBMb43sZ4/w+i/2dbT50BrUuN9bs+1Nyvwivtk2K/8vgjpn88sE/KxTvk9XYe8JbA6hri9QQWwJoN8S7fPI3lXqkMpymNS58rS+k1pdUiW8kv11hTahOVwTfruUlnr9m9ZmpPOVdTskBRj4Xfp8LxwRYScKM3pAwIwMuvDolPgYdmqWI2ic10YFbB+QCUM5vZsvjw/jleIcNe/+eH2Lr8NDPMjI4E9+MER1E79O3XTo6ZXnuHXICDg83xr1aN0Gj+DBv0TkXewskmjXahut333vDb9v9Rs9fJfxXhMJJz5uDbzfo0frtTT6+MfHAjD1A41bh9+n+F6D1AN91pJnRHRJmZCA1kolD6dwidgk+GoR61EV4P9jJCVg0dWLrMnEoXa9IayTVZlLQAVgYycSEGGthm2ac0KWMrxCbv1+hCc/dYpAwIwOpkUwcSucWEU6eDOQLNiQaRYbomkF+UHi2ePhSBmLH2OwRTZKimRTM+SI2v41QCDCjwCgmMWAg/H1rzCjIWQwSZmTAZyKVrJnhUtgr8yYu+sEeApZ+jLLxTrTS7gcKzxaPkxcYRY6x2ZO6uUUUe+TgBTclNDMiShn4f2/GMZZSyFNIAyGPnp96Q8KMDCLVzHCTnVL1mcSo3MMJK5T3Rj5Si45yUPFR8dRJHWNbgJwgZiKiPDNKaGZEaiyE/TLjGEsZXyH+wiW9DOoOCTMyqJP6llgPJ/xoOXmFE1bIxCGfiO+H+omZNDPh4cdYrDbUrnBWXK2RojlQ0qQmtl0fzYwJx1iK5ksIaWYMBwkzMogk4yugbkkDNsiPKpywIiySSD/LyKgTWzPID9LMiEdqYVfz+8xI8OkQmtTkagrEaixsdvBedmYc44g1M+QzYzRImJGB5MiKerzRTFpqZkILTi6aSGXDFx2NUDOjlNnRynhLGUg0M5lRawBEFs0EAKzMFyW+XRHZwM08xhFHM/lvT79dvSFhRgacyluqwycfvaKCZiZYNJMkzQy9ZUREndiaQX5w2ysVqm9lnG6pZiaTV86WZGYSTLBytSRukQ7Awm3MOMYROwD7+8wo0x0icqicgQzkOgCfKKuWtN/JcmnbCzl6tgqVtXU4X+sNnyw6W8XXcyoR1IoqKa/x+S4QDrvNJxorJd4R9SUQuLG1SzQzcZq9yloThrZqjOT6V5z5oLpcpR6pTE19xmMpodkAUFcNOOIjb1eK+YXbprYq8vb0QqnQbJJmdIeEGRms+r0EQCRmJs9kt7OoDAvWF2JK/9yw+7y8bC/mrToQdrvE2MBq4THz1jdYN+DFVQG3fe67PXjuuz1h2xLisDP46u5+uKhFY0n7WQWXm8X+Ek85Aqmh+pzJ5IXvf8eUfm2o0GcIFm331P8R/ZvjJp0NrwMDHgQS01TqmQpUl3mLRkoJzQaAD0YC9/4ceduFP9UfU4yvTv02b/cDnjol3ZlWT356wfNXspmJfGaMBpmZZMDVRCo/L0292jvX+0AtOFoqap/tR3wr/6YnxaJzdiPcNagdAOC9iT3ROj0R/5zcCwDw5JUX+mwfF2NrULPJ//tAy4DnPOME//z3YxiPlurX4yZ9+1UA4T3QOUdabZwRnZvxy8dLzyvWJyvSrJFH22ALlZVWSIeR3uUzf6jQIxU5IyiAmNoy/Pb2GKDNZZ7lP/fKa5ubnCtLwm+bdx23E3D+TMhNDQdT/zyLD1Pny58OI/xWkDCjNyYSoY0HZ4K5Mi9b0n4t0xIxa3RnzPrfb3xukrBt+fm8fH5nH7TP9NaDGtEly6cC922XtcVtlwWuEtzmsW8brPOv5/Tol7vw+dajAIB9ft9x+4/tnoN/3HAx7v73Nnz/y4mo9vngfDkYBmicGCtp3/y8bKQlxeJMZS05AYeB80vq105cYVe0GwqktQPOHDRhtE39vZCSI84RFwCu/wiYk+vZ1+0Sv58/nC/JRdeH3zb/RWDLfM8+Zhtjrr+X3iVtv3ZDPVXYOQGZNDO6Q5oZGXACRiS1kez1pgWxUUQNfVeMU3TAW1soen/Qkdbp4uDGkMKzQxNR/SuzRttwE6RYLRTgK7zIOV+uNIFY84tZx5g/T7mmXfrd6g0JMzKINM+MZx9puWb8BQUpzze1cVBtoYhzzHBQSQNxRJSY0LTRNtzvSYowo1BGXqn5V8yanDDSaCYAPteFNDO6Q8KMDCTXiREgNQuw/3YGkmX4t2RnFE/Ecu4Fz37aZ4U2I5ILTQKCkgYmm2h5WUbCuSpVK0nqJG/WshGRJs1rAP1u9YaEGRnURRiaDQhyi4jVzPj5ozAGUs1Q1WdhjpnIflIxCtfrsiqS88wA5tXMcInvpPzUfXLNyBDepIYsm3WMZWlmBL9V0szoDgkzMqiL5MFaj7dytlifGeP+WLwZjUkzE6nPDI2hOCJ6gTBtSYMIzEwMAzD1/h+aamZMOsaR5plpgHGfz9ECCTMy4JPmRSLMSMz66vTXzEhuUT342kIGFrjUJiLzhwBeuI3iMRRDRFm37SZ1To3EARjwCiCa+syYdIxlaWYEkGZGd0iYkYHkOjECOAFIrFnBfzsDWZn4849mE0mkdbo4qKSBOCIaZ7NG2kSimQG8AoisaCYJtZkA845xpLWZGhC9zz6jQMKMDPR1ADaONMM7AEfxRBxRlI0Ab70ueiiGIiLfJLOaQHjNjMTHtBJaEim1mQDzjrFSZibSzOgOCTMyqK6L3E+CC8U9fLoypEbD5WZxprIWpypqfNYbSTPDnX+1M3prC8kJ0we8mgb/61xb5yZtjYCKas/kE5EDcI3ZMlRHaGbiI4tqI29aSk0owLwFPWvrz1Oumam2Un5fCFmQMBMhLMtiZ30pAqmFBQHvm3hlrQvXvrMh6HadnvoePf62PKI+agV3Lp9uPhq1pqZ1B04BkG9memLxL1ix5yQAjyDT+/kfcfmrPynTSZNTdt6JWt5nJoLQ7GWPAyd+UaFnKrHmJc/f0+FrsvnACSBf3RZZu1VngENrPctSNTM/zYmsTT2oPO1djiQ025HkXf7vPUCFiNIPhGpEJMyUlpbin//8J2bOnIkzZzy1OLZv345jx44p2jkjU1PnfVvu0CxZ8v6dcxohI9mT9n7HkVKwAdSULMuqknfkX7f2Rqu0REwbdgFapSXio1t6yzpe//bp/PK5apO9mSnM6cqa8BsFIL+rtyTGrqIyAMCh05UorXLi8OmqgPdHtHH4tPftN6dxgvgdm7TxLq99WbkOqc3BlZHtl1lfl626LLL9937nXRZr4orjSqsYSGUcjtP7vcvJzYJvF4zx7/p+llsPi5CFZGFm165d6NChA1588UW8/PLLKC0tBQAsXrwYM2fOVLp/hkXo28AVv5NCclwMfpw+iP8cSKEhXJcSF4M3b+zBf5ZjZrrsgqZY88gQTBvWAWseGYKBHZpGfjAAPVo14ZejNekbZwoa1715RPv/X5/WmNKvjedYAXIPRavGSwh3b7VKS5SmARPWF4oGoXDE3z1/I/VfEe4n9kHT527PXzOZmbjzzOgIRGIebtYFmFUGZHbxfDab87PFkHwFp0+fjilTpmD//v2Ij/dO4vn5+VizZo2inTMywppKkZoWhPsFcp4VrnPUV6fmMFLSPIZhJEdnWQ250UyAINdMgDGM0mH1IeL6V7IjVUyG3MiiSPYzYzSTUpFMXMSXmc7dgkgWZrZs2YI777yzwfrmzZvjxIkTinTKDAhT90eaKE1o9w80gQnXxcXYfBS4xhFlPPC5ZqLUWVVONmiOUJmU3dGgUQhDxBFjwsnKQC8BqiE3mokV/oZFjpcZS0bwEVsyhRkl8voQspH85I2Pj0d5ecOogL1796JpU3nmCjNRJ0iYF6mWRCgEBYpYEa6LjTG2rzYXxROtocWcacghQzMTKtcMCTPehIKSi3nKjVQxG3LDpIVCkNhnmxnLGShVl8lmwnO3IJJnyLFjx+LZZ5+F0+m5cAzD4MiRI3jsscdwzTXXKN5BoyK3sCDga5IIp5mJtfubmSJuVhWkZjS2Gk4lNDMhsgBHqYzoQ0TZfwEFigiaDLmChY9GR6xmxoTaCaWy/5q1YrjFkPzkffnll/Hnn38iMzMT58+fx6BBg9C+fXukpKTgueeeU6OPhkRuXhHA19ckkGmhroFfjvfBYqSkeQBVfa6TWZsJCC0QRqsvkhDu3pLslyScrKJBw8WZfFg3EEkl+4g0Myb0meE1M3J9ZkxoYrMgkq9io0aNsG7dOqxcuRLbt2+H2+1Gjx49MGzYMDX6Z1jkZnzliLEzqHOzYR2AGYYxtGbGwTuvRqlmhjOByLgfvGamwGH60Q5f2FWq9ks4WZlpso0Un/N1ArY4afu7hckvrayZUcgB2IwmNgsSsVph6NCheOihh/DII49ELMisWbMGo0ePRk5ODhiGwZIlS4Jue+edd4JhGMydOzeyDiuMN3pFni9LKF8T4TobA0M7ANu5iThKNQguBcxM9hD3QpQOqw/eWmgyHIDNNNlGilATFYnwFolmxszRTHLNTLxmJgruLQMjWSR9/fXXA65nGAbx8fFo3749Bg4cCLs9fIGyyspKdOvWDTfffHNIf5slS5bg559/Rk5OjtTuqoa3SrJ8zQwAuALmFvGukxPyqwW8UBatZiYlHYDrjyV0+iUzk7BKvQwHYDNNtpEi9BGKZIKNRDNjRu2EYg7AJhTkLIhkYea1117Dn3/+iaqqKjRp0gQsy6K0tBSJiYlITk5GSUkJ2rZti1WrVqFly5Yhj5Wfn4/8/PyQ2xw7dgxTp07FsmXLcOWVV0rtrmqcqfLUPZFrZuLexovOnkdO4wQkxsbA7WZRdt6JY6XV/HY2xi9qSmXZRqoZixuH2rroNDNxGaHl5Znx3AvnqutwprLWx92htKoWTVMkmgsshjNSvyThZBVpVlwzIdes5o4gaR7XppnGV2pl8GBwgtzZQ0BtFRCb6PFVqizx1MeyxwIpWfLaIMIiWSf+/PPP45JLLsH+/ftx+vRpnDlzBvv27cOll16Kf/zjHzhy5AiysrLw4IMPyu6c2+3GxIkT8fDDD6NLly6i9qmpqUF5ebnPPzX4clsRAHkOwID3bXzKh1vQ+a/LUHKuGsNe/QkX/205Jn+wmd+uoZlJf02NME8ONxHfunCLXt3RlbX7PbWZ5Ai33L5r959Cz78vx3e7i/nvhr+2Bv/ZclReJ03O89/tARCBwCj8jR7bao4aOqcPRr6vzeYtQ7DzM+n7r/+H4INEzQwArA+svTccvyzy/JXtAFx/7hvnAc9nA2cPAx+NAV7pCMzN8/xd+4q8NoiwSJ6Jn3zySbz22mto164dv659+/Z4+eWXMXPmTLRo0QJz5szB+vXrZXfuxRdfRExMDO6//37R+8yePRupqan8v3DaoUjJa94ICQ47ruomz/Q1prvv/gdLKvHHqYYVWO024zgAP3VVZ7RtmoSHRnTk1/Vq4ylpEK1+qpxQ2iotMeJjXJqbhhZNEmC3MWBZoKC+kCnHq8v3yemi6WkU75k0WkYyxqmtvMunTDCOJ3bL259LfFd6RN5xxD5oUgTPsWNb5bWpFYlpnr9yqosDQCc/i8G2D72FOjmKTDImJkayMFNcXIy6uoaqy7q6Oj4DcE5ODs6dOyerY9u2bcM//vEPLFiwQFJSupkzZ6KsrIz/d/SoOm+zdwxshz1/G4XpwzvIOs7M/Avxl97eB22waKAG0UyyWpXHrQNysXLGYGSlestZTB3aHoBvZuRoQVgQtFVaUpitg9M6PQnrHh2K2y7LBQDU1Ll8vq+qjW6bPGdmGt8jgvpXD+721tAxg6OmXP+LwfV18mT7sIg1M9mAq+Z6ls0SosyNcYeR8o7TeQxw8/fez4He6Mxwz5kcycLMkCFDcOedd2LHjh38uh07duDuu+/G0KFDAQC7d+9Gbm6urI6tXbsWJSUlaNWqFWJiYhATE4PDhw9jxowZaNOmTdD94uLi0KhRI59/ZiJYNJC/Zt1ItZkAr5mJZQF3lDmrCk9XTp4Z/2NEq/9RMFyRZgDm4GvouEJvZwTkCjNK1QuS8pwxmyOsUqHZYo5hljExMZKv4vz58zFx4kT07NkTDodH7VtXV4fLL78c8+fPBwAkJyfjlVfk2QgnTpzYIOR75MiRmDhxIm6++WZZxzYawudFsGggo0czCX1FnG434uQ61ZkIYT4guQ7hgHeyrvETZowmwGqN7KzbZoq4kfsmz+d9kTuJShhrM40voFw0ExC+/hcJM6ojWZjJysrC8uXL8fvvv2Pfvn1gWRadOnVCx45e/4khQ4aIOlZFRQUOHDjAfy4sLERBQQHS0tLQqlUrpKen+2zvcDiQlZXl05bVCFYOwOb3AzHatCZ0hK5zsYiLokLFQm2aQ0aeGe8x6jUzUVoaIhiys26bKbGbXIFAKcEiEs2MGcYXUK7QJBA+V41ZxsTERHwVO3XqhE6dOslqfOvWrT6Cz/Tp0wEAkydPxoIFC2Qd20wITazVdYFV4A2EGYNJM8K35WjLNSMUQBUxM9ULRGRm8sVbmTwaNDNyzUxKCW6RaGZMooVQVDMTpmSGGe45kxORMFNUVISvv/4aR44cQW2tryf4q6++Kvo4gwcPlpSm/dChQ6K3NSvnawNPYP5mJiOEZgsRTuLR5gTsbFBDSx7cWPqbmaIdp1ummclMNXRka2YU8l+RMtRm0nwByhWaBHzNTGyAF1KzjImJkSzMrFixAmPGjEFubi727t2Lrl274tChQ2BZFj169FCjj1HFeWcwzYzfCmPJMnzRzDo3G32aGS77r51RxK8lmANwNNdncrlZ/oU3YjOTqTQzSvnMSDxOgxcRK/vMKOgALDRVBRKWzaKtMjGSnwozZ87EjBkz8MsvvyA+Ph5fffUVjh49ikGDBuG6665To49RRXUQYUZr589I5k17lBabrIu0mnMQyMzUEOE9ZZermTHDxCI7minCc/UXRCT5zJgoWgxQOJopTMkMM9xzJkeyMLNnzx5MnjwZABATE4Pz588jOTkZzz77LF588UXFOxht1IjUzBjNZwbwOr9Gn2ZGpmOqH8EcgKM5mkl4T0XuAGwiB1W5k1+kWpIG7UoRZsjM5HNcIWYZExMj+amQlJSEmpoaAJ7keAcPetNunzp1SrmeRSl/VtQEXN/QZ8Z4cL4MVbUmeTNTiDq5IcN+cPW6/ItL1ta5UXY+Oh+KQmFGtgOwGSYW2Wam+sn1zKEApiOV2uXGt/SwOVKB19ZnWlfCAVj4olEZYB48W2iO+87ESBZm+vTpw5cquPLKKzFjxgw899xzuOWWW9CnTx/FOxgNxMV4L8Onm70Zi4WFBeMdvnlbjPiWzuVHueL1tT65V6wOV3bArrBmxp/zThd6/X05dhWVKtKOmTh4qoJfjjhijJu0ls1UoEcqo1RodtkR4NMJ4vfzrwklycxU32ZdNfDdw+L30wNnNXCuvvaZEqHZwtfL378JvMm7A6UJloQkJD99X331VVx66aUAgFmzZmH48OH4/PPP0bp1az5pHiENrhQA4CvYPDumC54e7amD9PBI39w6xhNlgLGCOlNnKmXWOzERFTUe1fypIFo1qfRqk4ZWaYk+9wKH08Xi1+PqFE81MsWCCvIRC/IZ9b+zhDQFeqQyciOuWlziXS6SUPy1zL/8i4Sxzrwwsjb14Jy3iCuaXhh8O7EkZXiLe9r9qts3rU9hUvIb4KyS3xYREMkiadu2bfnlxMREvPXWW4p2KBrJSI7DoReuDPr9zf09pSH2FBt7Envqqs7496bDqKlzR5VmhjOBXH1xBDWDAtC8cQLWPNIw8eTd/96G7385ETSxopXhHID7tUsPs2UIuowHVv7dHM6YcjUzyZnAfduBN3pIc8j1HxspgmNsIjBxMfCvq40/xlz/4lMBR3zobcXAMMDTZ72f5+Z5i3zetQ74W0Z9u2RqUgvJmpm2bdvi9OnTDdaXlpb6CDqEuhjQygTAawLw9/ewMpwDsNolJ7zRYtEzthyKRIwpVa9IC5ToI3e+Unw15DgAA+aJGFMykikcPs7B0eVPqCWShZlDhw7B5Wp4QWpqanDs2DFFOkWEx2hJ8zi4sGJnFEU0cZqSYL4uShGt0WKAMJePDL8kM0XbKNFHWwQRTf7tSn1rMssYK5n9NxwMAzARCJaEJESLpV9//TW/vGzZMqSmpvKfXS4XVqxYEbKaNaEsRtXMcBN6NOWaccqt5iwSTusVbRmWAa9wLKtchDBcmWWN+yMClNFsCMsLiD1fo9SEUhslw7LFYHcAdS7jj4uJES3MjBs3DoDH+Y7LM8PhcDjQpk0b2ZWyCfPDTejRpD1QOjQ7GDFRrJnhzJbyNDN+6n5FolhUQhHNTATnK7smlElKRiiZ/VcMNgeAatLMqIjoK+mufxvMzc3Fli1bkJGRoVqnCP2J9KWV82mIKgdgtwJaAxHwWq8oGlsOpxICo/At3O00tjCjxBt8JOcrt13eZ8bgkzbXP82EGRP5a5kUyVeysLBQjX4QEjGqhtxrZooe7YF3olXbzFTvjxRFY8tRp4QpT+gf4XICjgSZvVIRJTQbkZyvXM2BWRITunQwMwnbJRRHlDDz+uuviz7g/fffH3FnCPEY3QE4mkwhvAlEZc0Mp5WIpkgxDt6UJyuaSWh2MfgbsiLRTBGcr2I1oQwetcP1T1MzE4x/35kYUVfytddeE3UwhmFImNEIo2pmYqKw2CTvnKq6Zib6THgcvGZGjpnJJsiibfRJRQkzTSTnKzc0mxyAA2M3Sci6iRElzJBpyXgYVJbhJ5saZ/RMuJxwoXaeGU5Y+vOcMpmGzQSn6ZPlAMwwnjdktxOoKPEkljMqdQpcY+H5ijFv1FYB1TITc3KajrpqT+p+lSP8Isaltc+MiYqcmhRZdxrLsmDNUFCM0AzOp+G2j7bq3BPt+HJbEQANHIDrj//NrmIs/eWEqm0ZjS+2edLsyxYYuTfxd/oDe7+X2SsVObxemeNw5/u/MBrzLf8Ens8GNr0prz2hn84n18s7lprsX+b5q5Yw40j0/cyNy/q56rRHRCbMfPTRR8jLy0NCQgISEhJw0UUX4V//+pfSfSNCYMRCk4BvuvloEXSbN/Y4VjZJjFW1ncs6NOWXo63YZHaqZ4xlaWYAIO867/LxHfKOpRb+Jtqr3438WKktPH/LwiQ0/XZG5G0IScoAUlt5lo8Z+IUmpr6EwflSdY5/zXygSa7nLwDE1NdrckVPzTqtiajQ5N13340rrrgC//nPf/D5559j1KhRuOuuu0T71hDyMaYoA9w5qB2/HC1ZgDkzU5fmjVRtp3vLxrhjoKdkSDRFiwFeH6xL28osEjnmdeDSuzzLRvVfEPbr0cNAtxsiP9ZVcxseMxyNWkTeHsMAk5bUt2lgJ2DO3NPlanWOn9UVeKAAyLvW87n/A77tEoojWcf2xhtv4O2338akSZP4dWPHjkWXLl0wa9YsPPjgg4p2kAiMQRUzPqaWaIm6cWmUARgQ1GeKEkGRo06JDMAcRvdfEDrPyjWDRJL3Ra5TbCQ1obSGj2ayh95OKcwS5WViJD99i4uL0a9fvwbr+/Xrh+Li4gB7EGpgVDOTMNokWtLuK5LQTSSOKIwWAxTKM8Nh9GKIQiFArmBhjyAjr12muTSSmlBao0c5A2G7hOJIfjK0b98e//nPfxqs//zzz3HBBRco0inCvDgEk020aA/q+Dwz6mtmorGQJ6BwMU+jJzATCllyCyFGIljIFWb8a0IZES0LTQrbMeo9ZwFE6zALCgrQvXt3PPvss7j++uuxZs0a9O/fHwzDYN26dVixYkVAIYeILmw2BjYGcLPRk3afN4FooJmJidKSBorm8jF6AjOuX4xNfmizPYJz9Sl7EIEwYoYaWLxmRqO+UZ4Z1RH9S+nRowd69uyJkydPYvPmzcjIyMCSJUuwaNEiZGRkYPPmzbj6apWcqQhTEW1p9zlzmjZmpvoMy1EythycWU0Rnxm7wesHKak14DUCGpqZ/GtCGRG+0CRpZqyCaLF0/fr1+OCDD/DYY4/B6XRi/PjxeOmllzB06FA1+0eYkBg7g1pXdGgPXG6W16RrY2aKzizAiiTN44hkgtcSJf05IhHclDJtAcatgUU+M5ZD9JOhb9++eP/993HixAm8/fbbKCoqwvDhw9GuXTs899xzKCoqUrOfhInwljSwvvZA6Ihr18LMZIvO+kzcvaRIlmWjV3bmtQYKRNpEErklO5rJBDWwuH5pnQHYqONhASS/5iQkJGDy5MlYvXo19u3bh7/85S949913kZubiyuuuEKNPhImwxFFxSaF50gOwOqhigOwUScWt4ImkEj8g2RHM5mgBpZLJ2HGqNpACyDr6duuXTs89thjeOKJJ9CoUSMsW7ZMqX4RJoZ7ez5bZf1sl0JhRhMH4PqxPVF+XvW2jEC10wWWZVFZ68nPoYwDcP3EcvaQMaNtuCyxipiZuGOwQNUZiftECFcTClAvw65cqss8f7U2M5077qmBRShOxE+Gn376CZMnT0ZWVhYeeeQRjB8/HuvXK1RPhNCd2JjIJw1OM3PDe5uw98Q5pbpkSL7e6U0Tr3ZtJsA7tr8cK8f8ddYuAHu89Dw6PbUUebN+4Nc5FHEArp9YincCi++Ufzyl+fIWz18ltAbCY8zJBYpElBhQUoh685LwpRS05twJ4ORuz7LWDsCApwbW6YPatBtFSJqxjh49ir/97W9o164dhgwZgoMHD+KNN97A8ePH8f7776NPnz5q9ZPQmPuGXoB2TZPw+BWdJO87pnsOv7ynWGYVXoNTeMr7lqVFIsNebZrwywVHS1VvT0/+s9VTXLKixquaz0iOk3/g1oKkn0Vb5B9PaWorPH8zO8s/VlwK0FFg/i/eGX6ftHbhtwmHsAbWn3vkH09J/vzdu9yilzZtpuX6fv75HW3ajSJECzPDhw9Hbm4u3nrrLVx77bXYs2cP1q1bh5tvvhlJSUlq9pHQgaYpcVgxYzDuGCj9wfboqE4Y3NFTFNHqUTecA/B9Q9tr0l6LJon429gunrYtPrb+TOjVEjYlNDNpbYHbVnqWjejDwNZf12FPyz8WwwB/+dRbg0iMD4tQEImUMa8DOT08y0YbY64/WXmewphaYHcAt/7o/WxE86bJEa3HTEhIwFdffYWrrroKdrtG9SwI0xItUTeKRtmIxB6luWYUjRbjnFSN6KDK1e9hFHQolxJNo5QfiVEjeLSOZOLQqg5UlCL6an799ddq9oOwGNGSOM8bZaN+JBNHtGYBVsRfhsPIeT84zQyj4OQnJWmbUpO8UcfYrXEpAw6hkGjQ2npmRrsnMBFVRMuEq2g1Z5Fw4cnRpplRJJKJw8gZWXlhRsHzlZI8T2nNjOHMTBonzOPQWniKMkiYIVQhWnLNcJonRSfaMPBaL4sLiv4oGvpu5Fo5nDCjZN4iKVmPlZp0DauZ0cnMpLXwFGWQMEOoAqepcLqtPeEqmsxNJHyGZYsLiv4ompQw2jQzUrIeK1V80ahjrJtmxoAFNy0ECTOEKsREiWaGM/XEaJD9l4PPAhxlZiZFnayNqjUABA7ACvrM2KX4zCilmTFo2QglMyxLQSg8UTST4pAwQ6hCtNRn4jQzWvrMcOYWl8W1Xv4oqv3i3pJZN2C0cVRVM+MSv62WbWoJ7wCscXQRaWZUhYQZQhWixgGY95nR0AHYFh1aL/+XV2UdgA1cDFEVB2AJmijFHICNamaqv956mplYgwl4FoCEGUIVOAfg8mqDPcgUhnPC1dIBmDO3lJyr0axNI6Co9ks4kRnNDMJNdEpqDriJ1CmiLpBS7fKmLYPdp0YIza4z2JhYABJmTITNRLkJuInn35uOoKS8WufeqAeXFFDRHChh4MwtZypr8fXO45q1qzX+t7uiwoxwIvt1iXLHlYtQHaWGmWnHv6WFSsvpA9fmimcjP4YauHXSzAh9oAo+1rbtKICEGRPRv30GerRqjBsvbaV3V8IyuGMmv3ygpELHnqiL06V9aPaF2Y345Z0Wr88kRNExjon1Lp/ap9xx5SL0L1FSmGk3xLtcXdrw+/QLPH85Ie/i/wNa9QNaXhp5m808ZTfgMFi5G5dOodmxid5lyjmjOCTMmAiH3YZF9/TH81fn6d2VsPTOTUPn+knXylE3XG0mLX1mkuJi+FpQVi4X4e8zo3j4e/8HPH+N5DPDCnzMlBRmmvf0agYC+bCkNvf8Hfe25+/YN4Fbvpdncup0peev0cx4bp1CswHgof3ePlBEk6KQMEOoRjRE3eiRARjw+s1EU+I8xcPfjVg7SC1hBgh9vrzTsQoRY0YaX8ArzOkRXeTjBBw9v10tIGGGUA0+cZ6Fo254B2AN88wA0ZNhWYji2i8jRtsIo1yUDh0OFdHEaQkUFWbq2zNa+LvbIMKMke47C0DCDKEa0ZA4j3cA1tDMBERHhuWGDsAKP66MmNRNC81MIAdg3uShQskIwFhjzPkl6WFmMnIUnckhYYZQDW9BROtOuHo4AAvbs7LPjD/qaWYMZAbxEWa01MyokahPMHEbSQvh0ik0279NI42JBSBhhlANb0FE6064vAOwxj4z0VCfSXUHYCOWNFArmgkIY1bjzEwqJOoDDDbGOjoAC02HRvMlMjkkzBCq4YiCLMCcMOHQXDNDDsCyMaTPjECCU9xnRicHYMBY2i+9QrMBz/ga8b6zALoKM2vWrMHo0aORk5MDhmGwZMkSn+9nzZqFTp06ISkpCU2aNMGwYcPw888/69NZQjL2KKjPxAkTihZBFAFf0sDCY+uP8mamemHBSG/IQgdgpZNkhoxmUkEzwzBeU5mRxlhPB2Bhu0YaEwugqzBTWVmJbt26Yd68eQG/79ChA+bNm4fdu3dj3bp1aNOmDUaMGIE///xT454SkeB1ALau9kA3B2C79QVF9R2AOTOTgSYVNXxXOEJpBHhfnWgw5emUAZjDiPedBdC1jGd+fj7y8/ODfn/jjTf6fH711Vcxf/587Nq1C5dffrna3SNkwqX4P3LmPFiWBWOicgxiqaz1vElr7QDMaYKKzlahps6FuBiNKwDrgGoOwGcKPZoJI9yfvDCjwvXkJtHyACUwzp2ob1cNU141UFECNDZI5vKa+ozkemtmzp9V5/hul0dQiolT5/gGxTQ+M7W1tXjvvfeQmpqKbt26Bd2upqYG5eXlPv8IfeAm+A/WF+LhL3fp3BvlOVNZyy9rWZsJ8Pro/PFnJTo+uRTna61XhbeBA7BamplTe4EvJit77EjZ+ZnnrxqCFTeJLr4D2CDQhq9+ESgvUqddzk/nn5cbowZWbSWwf5lnWW/NzD8vB07tV/74b/YG5rQFnNatiRcIwwsz33zzDZKTkxEfH4/XXnsNy5cvR0ZGRtDtZ8+ejdTUVP5fy5YtNewtIWR452b88o4jKr2F6MjBP701pzKStX0L6tm6ic/n3cfKNG1fDy5olqzsAVv18S4XbVX22JFSVi9UuGpDbxcJXa72Lh8TnG/RFu9y857Ktpl3vXf5+HZljx0JpUe9y60H6NOHvOu8yyd/Uf74pw8AtRXAn3uUP7aBMbwwM2TIEBQUFGDDhg0YNWoUrr/+epSUlATdfubMmSgrK+P/HT16NOi2hLqM7JKFL+/qC8Ca+VA4598LMpNh01gz06xRPF4Y763RxVq8zsuQjk0R71DY9JLaArhrvWfZKP4LnG/J0CeVP/aAacCVr3qWhX4zXJvj3weSgr8oRsQVcwQ1sAygPeSuc1ImkNFenz6MfA7IHeRZNlKUl8kxvDCTlJSE9u3bo0+fPpg/fz5iYmIwf/78oNvHxcWhUaNGPv8I/bBbuKQBJ6BpHcnEYTOCj4dG2NUqF8FnxTWIgyo34avlz8FH0ggEC75NlfyujDTGekcycVBEk+IYXpjxh2VZ1NTU6N0NQiR8DSELZgHWK8cMj0CWsaJztfCUVIsWM1pkidrZaQNFF6ndps1AEU2cJsSuszBjxCgvk6PrFa2oqMCBAwf4z4WFhSgoKEBaWhrS09Px3HPPYcyYMcjOzsbp06fx1ltvoaioCNddd12IoxJGgg8htqBmhi8yqXFYdrQgtJypFi1mJK0BoH522kDh2Wq3aTfQGLt1LGUgRK37zuLm5lDoKsxs3boVQ4YM4T9Pnz4dADB58mS88847+P3337Fw4UKcOnUK6enpuOSSS7B27Vp06dJFry4TEomxcHI37pwUj7IhGqBatJhhNTMqPZoDZQHWTDNjIJ8ZvSKZONS671jracDFoqswM3jw4JCOi4sWLdKwN4QaWLmkgV7ZfwPhtvgbmWraL953wWmMXDNqT7YBNTMqm16MZFLRs8ikENLMKA69UhKqwpkHnFbUzPAVs3WaAAVDakUznhDVzUyAsTQHqmlmdPSZMYSZySA+M6r5EVn7ORAKEmYIVfFWd7aeZsZbykD/n5EVHayFShLVqpIbrbKz6oJFgFpJagtQRqqBpbYZTyyhin7KQaiZiTItjf5PYcLScJOQmwXcFtPOOOsFCNUm2nAImrWiZsbHAVi10GyhMGOAyVZtzQGvJQkgzKhuZjLQ+OpuZgpwHRTBes8BsZAwQ6iK0DxQq4B25nytyzAJ4px1xolmKq82gFZBRVQLzRa+odcZIOVDTX35FbVDs0uPeKRFlxMoO6pum9xxK0+pc3wpGMbMVN9+jcLldoQOwHr7f2kMCTOEqggnoRve2yTrWPtPnsOFf12Kh74wRp2nv33rSReuWkK3MAjHdvp/dqKk3Lq1WFRzshYmint/SPDttKDsGHBit2dZNZNPvWDhrAS+exh4u7/3O9VCs+uPe2wrcGi9Om2I5cdZnr+6m5nqx2TTW8oKeQZ50dMDEmYIVUlw2JHXPBUAsKdY3lvIu2v+AAB8tb1Idr+UoEmi54GUm5GkS/v5XbN9Pu8vqQiypflRrSo4wwAXjPAslx7R1wl4x7+8y2ppDpoJ0locXOkpsgkA2d2AtHbqtCmsgVW8U502xOJI8PxNyQ69ndpw9xygcLFJEmYIQhUYhsE/J/cCYL1cM1yJhjHdcnRpP95hx6EXrkTnbE/JDquNr5AerRurd/BrBOVR9Iy4Eb5Vq2XyiU0E/u8rz7LzvHf9HT8BMbHqtJnaArjoBs+y3n4z3PXtoXOV9LaDgKadPMtKOp6TZoYg1IMzEbjcrGH8XZSAi2bSzQG4nhgL5/LhsKtp//cJzzaAkyqgblI37nzr6oUZxq6+f4Uwn4+eqF37Sgpq1GeK4qR5JMwQqiPMkGsl7YFRyhnEWLiYJ4eqiQmNEp4tFCjUjLbh/Wbqfay0yIbLlzTQWVjkSzcYSJhRdEys+wwIBwkzhOoIJ3srhRDXGSTPTIyFi3lyqCowCt/S9Z5sOdSqYA14hRdOM6NFmLJRik0aJQMwoE5mZAtpvqVCwgyhOsKJyGmRCZdlWcOYmbioJpeFtF7+qBoxxjDGMYNwaGFm4tvSQEthlFwzahfVlIIqmZGt+wwIBwkzhOr4mJksopkRmnRUS7UvEi6hnKXNTKr7dBgo5T6gspkpJvRnNdvUe3w5zZuami+xqJEZmTQzBKEeNhsDTnlhFSdVoUlHtYRuIrFyMU8O1VP5GEFzIJyI1NQc+B9bC5OLEcYX8GpmjGRmUlLAI2GGINSF0x5YxQFYeB56V83m2rdiMU8O1coZcBipfhCgrubAfyLXwsxkFM2M2lXJpWBTQ8Cz7jMgHCTMEJrgDR+2xo9NeB4OnTIAc3BmLpeFNTOqC4xGMDMJTWmMiveUv/CiqQOwjsKi2+0NXTaSZkYtB+Ao09KQMENoAuckW+U0yJuvTDiTjo3xmNH0xFHf/pkqg/h7KITwUay6kzU3sZw/o247odAqR4gePjOcAHXmD/0ixoRCg5F8Zs6dUPCgbJBl60PCDKEJXPjyqLlr+fwsZuar7ccAaGD+EAGnmXl9xX7sLirTuTcKwmpoyuMm9IWjgRO/qNtWMH56UfBBzVB0fzOThpqZQ2uBf16uj9Zg52feZSOZmX56EdjxsTLHJM0MQajLmO7elP9nq2p17IkyHCutAqBMJXC5DO/cjF/+rdg6wowwSqxFkwR1G8u71rvMFXvUmrhU73JqC/XaSc4E2g4BYuIBRyLQ5Wr12uJoO9jTFgAUF+hTA+t/93uXGQNoZjpd6V0+tk2ZYwq1eyTMEITyPD26C2K55G4W8JvhzuGhER107gkwsksWRnbxCDRWCs/mTHmT+rYGo3Zo9uV/BTqM8izrlWuGa/eBneqWF2AYYNIS4MmTwBPFwMCH1GuLI6sr8NA+72e98/mofT+Joet4YOiTnmXFxoPMTAShOsIaTWaHi2ZSNZmbBDhzlxXGlsM7xhpNPGrUypEC164R6gapgRFrYOkNf88ppKkiMxNBqA8X0WQFnxlOa6B3jhkOK40th+blIlSplSMBI6XaVwPheekdoq2mT5IUFI+iI80MQaiOw26dXDNOg5Qy4LBaHh9AUMhTqzFWI1RWLG4X+MnHCM6paiCMINJbM2MEMxOg/D3no5mxzouNGEiYITTDW93Z/D+yOr5itjF+QlbMAsz5JWk2xnrmmhG2aVUzE8MYI58PAONoZhROJkgOwAShPg4LOgAbz8xk/rHl4EpGaKaZ4bMA66GZEbRpVc0MYJyCnobTzCilqSIzE0GoDp8F2AKVs71mJmP8hLxmJvOPLYeT18xobGbSw2fGRzNjYWFGzzH2wSDCjNKaKnIAJgj14aJSrKCZcXFaA6NoZrixtZDPDBeZpVm5CD1T7gujWYyQnVYt9I4Y4zCKZkbx8SDNDEGojsNCTqq81sAomhkLmfA4eAdgrTUzepqZbDHGmWjVQM8xFmKUMbYrLMyQAzBBqA83KZ2qqNG5J/IpP+95GBtFM8P57hw7e17nnihHZY3nAa+5z0zFn9q0J8TqYdkcnCaitlLffhgF7nqf+QNwhvnt1tWEz0dDZiaCUB9Oe/DAZwXYePC0zr2JnJLyavx+4hwAAzkA12uIlv56AnOW/q5zb+RTVVuHVXs9QoXm0Uw7PwH2LdOmTY7tH9X3waKRTBzc+X0wMvzkrSTV5dq1JQVOU3WuGJh7EVBTEXi72krghVbAuwPDHJDMTAShOlflZfPLvx43bw2hfSe9D5zuLZvo2BMvAztk8Ms7jpTq1xGFEGqYLs1N06bR9sO8y8d3aNMmR0V95WSX+bWWIRHWwCo/rl27Zwu1a0sKzXsB6e09y5UlQNnRwNsd/RmoqwZOhimCSpoZglCf2we2xbU9PQX0zBxCzEUMdclphLSkWJ174+HiVk3w9k09AFgjoom7P5qmxKFt02RtGm3dF+h9h2dZawdVLrpn6FPatqs1l/8VSKh/AdByjHWPngpCUjpw3zYgub5YrOwxIWGGIDQhhq/PZN4Jl0/mZpDsvxx2C0U0ufTKsKx0EjOxWL0ukxA9xljv6KlwKDUmPk6/5n8OSIGEGUJTrJDcjU/mZpDsvxxWSkro1Cv0Xa/QYS66x8oJ8zhsOkQ06R09FQ6l7jsyMxGENlghuZvToJoZKxWb5DMsax36btcp3b4rijQzdh0KeupePiEMit135ABMEJrgrSFk3h+aS+tqziKxUrHJOq1zzHDolTgvKjUzGo6x4c1MCo0JaWYIQhs404yZzUyaJ3MTSYyFik3qVi7CrlPtoGjJMwPokzjP8JoZpe47SppHEJrgsJm/PlOdweoycXirkptXUOTgBDLN8/jYdKodxL2R26PAzKRH5WzD+8wodN+RAzBBaIPdAqYQ3gRiMJ8ZzuzlMvHYcnD3h12vaCatJ7+oimbiqpOTmYlHqfuOzEwEoQ1WMIXwmhmjmplMrPXi4MPftfZLsuvkMxOVZibKM8Oj2JhErwNwFLwGEEaCMxucLJef6fR8rQsMA1TU1KHa6alZEmOzIS7GBjfLIj05jt8mLsYGRqHiclzNIOM5AHO1r2pxvtaFhNjIqi+fr3WhoqYObpYNGBlltzFwswDLskhNcCAlPvAE7HJ79o93NOxHsP6xLIuaOjfOVtUC0MPMVP9IPPMHUFcLxMhMilh1Bqit8ByXm6hi4j2f7bEAYwNiE72ZX6PJAbiiJPJjsCxQfsxrVhGOrz+xyZ5tjQx334kZE5YNXiizTvBcrSgBSo9477e6asAe59GMJTSW3WWjQcIMoSmcn8lP+/7Eou1FGN+jRUTH2Xb4LK55e0PIbS7vlIkVv5fwy/OnXBJRW0Kqauvw8g/7ABjPzCT04bnwr0vx4/SBaJ+ZIukYa/b9iUkfbJa0z50D22LmFRc2WD/+rfXYd7ICW58chqQ476Pm5z9OY8J7m3DvkHZ4eGQnn31uW7iVv2aA1yypGZwwUbwTeLsfcO/PXrOIVJY+Dmx6M/x2HfKBipOe5WgwM3F+Qd9MAxrlAB1GSj/G/x4Ati9UtFu6wt133z8CNGoOXHhV8G2DCTN1NZ6aVxzfTg9+jKteA3rdEllfDYqxXi0Jy9O/vbeG0M6jpREf50W/Yop2G9NAuBBOisJlORQJagYN69xMkWMqRYsmCYiL8f6k31vzh+RjPL54d4N1cTE2/l8gTcm7QdrZWVSG804XNh8647P+b9/+BgB4c9XBBvv4X6cRWo9x6/5Ao3oB+/R+oFpGDTExggwA7Pveu5xzceTtmYXO47zLkdbAKtri+etvlouJ9/6zx0V2bD3oPNa7fHx7mI2DmI/OnfD9HOr8v3lQVLfMBAkzhKZ0zErBg8M6APCG30aE364PDrsAfx/XVUbPxFEnqBk0skuW6u1JIcZuw5d39eM/R+L/579PZkoc9v49n//39k09Izho6DZCcdOlraS3J4f0dsD0XwHUC21aRtyM/6cl1f8NuORWoPednuVIx5fbb9J/gSa53vVPnvT+m/6bvH5qSY9JQN+pnuVwYxLsB+RvZnvc4KY1hSFhhtAczlHVpWAIsd1mg00hn5hQ8KUMDGZi4lA7+kdrq49Sfk6S0aOsgV7nqgdyx1dM9Fek5kG94MfEFeBL4b0hUpiJBpOlABJmCM3h86HIibrxe+5r5SjKlzIwWCQTh3AcIpkbw+0jVrhwC7VufruYYs7WI7FbNGFXSJixxwS/ocwWGRbynhMRcu2v0THFD005SJghNCdGhYKIWmlK+GRuBkuYx6F0KLP/FbKLfEDKElSNgB7J86Jp8pGbOE9MKLvZIsPEjkmwzL5RLngb84lMWBqHEvlQ/GZZrfKRuAyaY4ZDrlAXzp9FrCnPzLW3AOhU1sCY95QqyNV8iallZTrNjNh7LphmxuC5dFSGhBlCc7gQYiXT7jvsjCZzgW41g0SidO4b/yEVe9qmF2Y4fwOj1/QxK3LHl68yHkqYMeZvNChitYFBHYCj+1412dUmrIAaWYBjbLawCS9ZBdJ761YzSCRCjZEa2czFamZ8zEwio5mUuD6KYdPBZyaazExyM97ympkY66TtD6mtEuEAHOWCt67CzJo1azB69Gjk5OSAYRgsWbKE/87pdOLRRx9FXl4ekpKSkJOTg0mTJuH48eP6dZhQhBi+2KSCPjMihAslahZx2iTNawaJRGhmUqNGk1hhRti22OtsqHpd9lCRJWphzHtKFbSIZjIbIcdEhAOw0etPqYyuwkxlZSW6deuGefPmNfiuqqoK27dvx1NPPYXt27dj0aJF2LdvH8aMGaNDTwklUcMBWEyUjRKTpddnxphKTWG/lDjfBg7AIk9bWAbBXwMXNBO7kUxTelR2jibNjJIOwFYZN970Fs7MFMwBOLqFGV3F2vz8fOTn5wf8LjU1FcuXL/dZ98Ybb6B37944cuQIWrXSOJkWoRiOeu1BVW0dyqudaBSktg/gCfGtra/vw9VEAjz1mIQw/H/BOXKmComxdsTYbIJ8Md7l2BgbnC6WN3cIv+MoOVftOQejmpkEmpnTleLrX52vdeG804VjpedDbhdMaCw6W+Xz+ZggU3LJuRqf76tqXAH3q6zRUgsSBm5iqTolfh/neeD8WRmTijHvKVWwR1gDq/I0UHsOvJhttoilUHDncvZQ6PpL/q8YlacAZxVwrlhae6VHgn8XqtZVsO/iUoCEJtL6oCCm0tGVlZWBYRg0btw46DY1NTWoqfE+xMvLyzXoGSEFTnuws6gMvf72Ixbd0w9dm6cG3Pb6dzdi17EyvHp9N3z/izdd92/FvteVYcILGCNeWyOz517M4AC8/sBpbDx4Gn3bpYfcp+BoKca9uV7U8YOFZg94cVXQfZ7++lc8/fWvkvfTFW6y/c8k4OalQOu+obevOQfMjqzOWFTCaWZO7BJfA+u3rz3XQziZ22IAR5Jq3dQUbkxKfgW+vAW47sPA2wnNTCueBda+0nCbWBE12ebmSe9jKAZMB4Y9rewxJWDMJ3IAqqur8dhjj+HGG29Eo0aNgm43e/ZspKam8v9atmypYS8JMVzcqjFyM5LAMECty91AMBGy9fBZ1Na5MfUT3xou/j4r/dplIL9rdsh2hXWLQhHrZ0sR1iaKi7EhJS4G+V2NVcqAw25jkJ7kfcv95Vj42kJz/OpcCWkQzSQQZq7t6Z28/cdIONb+64XyULB9AGDG8A5h+64aXcZ7l0/sCr/92cO+n2PivctXvgLk9PCk8O92Y/BjWMVcIobW/aTXwDq2DQALMHbP+HbI92gDxr8LpLX1lIPwp999inZbVYQCc9FWvy+DOAALBRlhLabRcz1/Bz4SvD1hHSvhPyH2uODf+e+ns/+SKTQzTqcTN9xwA9xuN956662Q286cORPTp3urhZaXl5NAYzAykuOw6qHBuP2jrVj+20nJvhKDOzbFgpt7B/zu0AtXhty3zWPfAgBSExwoO++xu+c1T8VuwaT/5d19cdM/f8a5ao8qde/fA5tCjcq2p4bj4S924ottRaKS1/n7E+6eNQJ5s37wfOe3rXC+fXRUJ7x8XTeZvTUol00HSvYAu/8jzq9DGIHS5jJgyje+319ym3f56re9yyd/9WgmAESVmYmrgTWrMQBW5BjXmzb6TQWGP+td36wLcH+QgpUj/u75B4ivYq4XjVsBd/wEvDcogBlHhAPwE8UNtVtDn/D8A4Bn073HnRVCePz2IWDL+4GPOateg955LHD9RyFPR2sML8w4nU5cf/31KCwsxMqVK0NqZQAgLi4OcXEmqpYaxXD+HS6JyfOUMPGECgM2aqSSFOTUvwoVsST8zgLDFBopETcRRz0JBjGaNDMcthiPIChqjC0YweSPTUTivGDPLibMczHc94F3imAffTD0XcEJMvv378eqVauQnh7a9k+YC853RmryPKWdb/3nEKUTz+kBn5hQREST//mLFeasIPSFREoWYKFmIWKhxOLjGQi7o16YkTDGZsvsKwW7mCivYMJMuMJqERTeNJGAraswU1FRgQMHDvCfCwsLUVBQgLS0NOTk5ODaa6/F9u3b8c0338DlcuHECY8DaFpaGmJjRXq/E4bFweebCayZcQeZiNUOizZqRWwpyElMKPb5pVtFa62QUp8p0uR6Vh/DcEQyxnZDv4PLQ4w2MNIkgaI1M8Iisea5P3W9K7Zu3YohQ4bwnzlfl8mTJ2PWrFn4+uuvAQDdu3f32W/VqlUYPHiwVt0kVIKbcINpZoL5e6gta1hBM8OdQyS5ZoQRS6GG2vqaGQlZgCPORxPlZiZJ2i8RJQzMTrDMyD4CTITCTLhoMZOjqzAzePDgkL4LhkpvTihOuOR5aiZRC6VVMGoRSSlwgoYzAs2M0C8m1BWwuiwjqX5QpLllfO5Dqw9oAKQkz+MEnkh9ZswgLAYdDxEOwOEQrZkxwTgFwPyvoIRpCWdm0iojrP+zwag5ZKTAj62IMfQ/f5tIKUVsaQPTIqV+kHDykTTZRLtmJgLtl5US5fnDnRvr8r2PfJYjrGkXkQOwebD22RGGxm4LbQoJJuSojTV8ZiI3M4nF8sKMpGgm0sxEBGf6EBMNFhXRTAJTUFABWW3NjDmx9tkRhsYRxklVq8KD/nOyFcxMUhyAI5VJLCDzhUaSCUQgzEgaUKsPYhgiGWMra2aE/kA+ArKWZiZzuneQMEPoBjfhnq1y8gnshETi76EEVnAA5rRL5dVOnKmsRbXT8+bLsizO13qWa+vc+PNcTch6TNHtAFyvAaguBc6dCLzN+VJPjZuKk5G1wZCZCQBwthCoC1JLrLYKKDsGnCn0fLayZkYoqJUVAbWVnmV/zcy5k6FrKwWCHIAJQh0435QvtxXhvwXH8PmdfdGjlbdQ2dBXfgq4n3+5AbnEx/j+yK0wSXNju+zXk1j2q6dg66/PjMTTX/+KL7cVYdm0gRg5N3ytKv93NKE7UdSEZv+62PPv8qc9mYE5tn4AfPNgw/38076LxuLjGQhOMPnvvcBPLwL3bfed0Pf9AHxynd8+UaKZefMSz98718Dnl7hhHvDz25BMbLKsrhkd87+CEqZlYIemaJoSBxvjCc/+9bhvjabausCamRkjOirS/svXdUOb9EQ8Pz4Pf72qMwCgV+smltDM9G+fgezUeB9T0OZDZ/DltiIAwF//+0tEx+2QmYL+7dMxtnuOEt00Nm0HAyk53gn32Dbf74WCjFCAyX9RfBs+mhnJPTQ/wgm29AhQ+afv919PbbiPlTUMNhvQ9VrfdT/N8XX6Ldpcv61AFzHosfDHvu5DoEkucO0HYTY0541ImhlCN3q2boItTwzD1E+245tdxSH9O8LVXIqEa3u24Islts9Mxi0DchVvQy86ZqVg48zL8cTi3fj453p1tNDs7rf9TZe28m4XApuNwce39VGuo0Ym+yJgxh5g+0fA1/eF9ut4MkIzE6LcAbjvPcCRDd7P/mMcyD/E4o6suHY+8MuX3s8s6zsOrlrP3yteAnrdIv64WXnAAwUiNiSfGYKICG+NJnP+iIyM2MgsK2ijVENKVJNUot1nxt//RcwYW12YAQKUHhAKMzLz7ViUKLgrCKMTaY0mIjw+OWNCWDSCCT1ROL02xCYhF4pkonyE/f1f/IWZQAKelc1MHEK/IYbx08xEQY2qCCBhhtCdcCHaROQwQSZLt5/6Pli9KxIv4Y1qElM/SCrRnmfGv86SmBDtaNDMNBBUAggzVg5Rj4AouCsIoyOlwrNSRKNGX4i/FkzpSuSWQivNTDTelA00M2KEmWjQzAiEvAY+M/Uh7KqZmcx5H5IwQ+iO3aa9Zibay375Z1e2QgkH1bBLSOwmlWjXzPgLcGK0X1GhmREKMy7faCbOAVg1zYw5H45RcFcQRoc3M5EDsOKwQUKY/Gs2kf9vCNR0AI52zYz/W4W/ZibQW0c0CN5CjZXLicAOwGRmEhIFdwVhdMJVzyaUQSgs+mdXDqapisLptSFaRTMRFM3EITQzuZ2BQ7OjwRFaAlFwVxBGJ1D1bDba7UAKIXQAFprxxIbB01WAumamaM8z08DM5Az9PRAdwoxPjSa/IpzkABwQClQndIernl1a5UTR2SoA6mtpwr0QW3FaKTnnrX1TWev7gCQFQQi4iaWuWno9nHBEe54Zf84V+45xbVXDbaLBAVgosFWdASpPCb6sfzaqZmYy531IwgyhO1zBya93HsfXO483+D42Rvk3Mf96TFYlzuEdu6e//pVf/vOcb1G/YKHZBLwq//JjwNw8hQ8e7ZoZv9/hf+8VsU+E96qZNBmxSd7lP/cASx9tuI2eDsD2OJXajhx6ghG6M/CCpmjWKA5xMTaffxyf3aFc+vx3/q8HWqcn4r1JPRU7ppHhyjUA8BlToYB4Xc8WuOnSVuiUlYL7h7bXtH+moOmFQHY3T/0l4T+O/tMiP3a0a2Za9AJa9/csxyYHH2Ph5BnpOPW7H2jaCRj6VOT91YpxgkKSNofvWMTEA83ygMzO2vcrfw6QfgEw7Gnt2w4DaWYI3clrkYqfHx+mSVujumZjVNdsTdoyAu2aJouua7V02kCVe2NSHPH1lYvVIAoFGCE2O3Dzd+G3qzoDzKmvnRapP11iGnDvz5HtqzXNOgOzyvTuRUMuvdPzz4CQZoYgCEIvoj3PjFgococIAwkzBEEQukECjCiEfjLRaI7TFHOOLwkzBEEQekETsziiIYLJMJgzIQMJMwRBEIbAnJOIJkRDbhlCFnSHEARB6AVpZsRBwgwRBrpDCIIgdIOEGVGQAzARBhJmCCIApPAnNIE0M+IgzYyGmPOepDuEIAiCMDYk9GmIOV/lSJghCILQDcEkTcVVCSJiSJghCCIo8Q56RKgKaRykQyYnIgB0VxAE0YA3b/TUsHr7puioYaUfJMyIpvtNnjpOzemeJBpCtZkIgmjAlRdl48qLoqeGlW6QZkY8497SuweEgSHNDEEQhG6QMEMQSkDCDEEQhF74aGbIAZggIoWEGYIgCN0gzQxBKAEJMwRBEHpBPjMEoQgkzBBEAGiKIbSBCbJMEIQUSJghCILQC9LMEIQikDBDEAShG+QATBBKQMIMQRCEXpBmhiAUgYQZgiAI3SBhhiCUgIQZgiAIvSDNDGE07LF69yAiqJwBQRCEXpAwQxiNy2YAB1YA3f+id08kQcIMQRAEQRAekjKAqZv17oVkyMxEEARhBFiKZiKISCFhhiAIgiAIU0PCDEEQBEEQpoaEGYIgCIIgTA0JMwRBEARBmBoSZgiCIAwBOQATRKToKsysWbMGo0ePRk5ODhiGwZIlS3y+X7RoEUaOHImMjAwwDIOCggJd+kkQBEEQhHHRVZiprKxEt27dMG/evKDf9+/fHy+88ILGPSMIgiAIwizomjQvPz8f+fn5Qb+fOHEiAODQoUMa9YggCIIgCLNhuQzANTU1qKmp4T+Xl5fr2BvCrCTE2lFeXad3N4hogiEXRoKIFMv9embPno3U1FT+X8uWLfXuEmFC3p/UC63TE/HO//XUuyuE1ekxCWjV1/OPIIiIYFjWGDm0GYbB4sWLMW7cuAbfHTp0CLm5udixYwe6d+8e8jiBNDMtW7ZEWVkZGjVqpHCvCYIgCILQG8uZmeLi4hAXF6d3NwiCIAiC0AjLmZkIgiAIgogudNXMVFRU4MCBA/znwsJCFBQUIC0tDa1atcKZM2dw5MgRHD9+HACwd+9eAEBWVhaysrJ06TNBEARBEMZCV5+Z1atXY8iQIQ3WT548GQsWLMCCBQtw8803N/j+6aefxqxZs0S1UV5ejtTUVPKZIQiCIAiLYhgHYLUgYYYgCIIgrA35zBAEQRAEYWpImCEIgiAIwtSQMEMQBEEQhKkhYYYgCIIgCFNDwgxBEARBEKaGhBmCIAiCIEwNCTMEQRAEQZgaEmYIgiAIgjA1JMwQBEEQBGFqLFc12x8uwXF5ebnOPSEIgiAIQiopKSlgGCbkNpYXZs6dOwcAaNmypc49IQiCIAhCKmLKEVm+NpPb7cbx48dFSXZSKS8vR8uWLXH06FFL1n2i8zM/Vj9Hq58fYP1zpPMzP2qfI2lmANhsNrRo0ULVNho1amTZmxSg87MCVj9Hq58fYP1zpPMzP3qeIzkAEwRBEARhakiYIQiCIAjC1JAwI4O4uDg8/fTTiIuL07srqkDnZ36sfo5WPz/A+udI52d+jHCOlncAJgiCIAjC2pBmhiAIgiAIU0PCDEEQBEEQpoaEGYIgCIIgTA0JMwRBEARBmBoSZiLkrbfeQm5uLuLj49GzZ0+sXbtW7y6JYvbs2bjkkkuQkpKCzMxMjBs3Dnv37vXZZsqUKWAYxudfnz59fLapqanBfffdh4yMDCQlJWHMmDEoKirS8lQCMmvWrAZ9z8rK4r9nWRazZs1CTk4OEhISMHjwYPz6668+xzDquXG0adOmwTkyDIN7770XgPmu35o1azB69Gjk5OSAYRgsWbLE53ulrtnZs2cxceJEpKamIjU1FRMnTkRpaanKZxf6/JxOJx599FHk5eUhKSkJOTk5mDRpEo4fP+5zjMGDBze4pjfccIMhzg8Ifw2VuieNeA0BBPw9MgyDl156id/GyNdQzLxg9N8hCTMR8Pnnn2PatGl44oknsGPHDlx22WXIz8/HkSNH9O5aWH766Sfce++92LRpE5YvX466ujqMGDEClZWVPtuNGjUKxcXF/L/vvvvO5/tp06Zh8eLF+Oyzz7Bu3TpUVFTgqquugsvl0vJ0AtKlSxefvu/evZv/bs6cOXj11Vcxb948bNmyBVlZWRg+fDhfwwsw9rkBwJYtW3zOb/ny5QCA6667jt/GTNevsrIS3bp1w7x58wJ+r9Q1u/HGG1FQUIClS5di6dKlKCgowMSJE3U9v6qqKmzfvh1PPfUUtm/fjkWLFmHfvn0YM2ZMg21vv/12n2v67rvv+nyv1/kB4a8hoMw9acRrCMDnvIqLi/HBBx+AYRhcc801PtsZ9RqKmRcM/ztkCcn07t2bveuuu3zWderUiX3sscd06lHklJSUsADYn376iV83efJkduzYsUH3KS0tZR0OB/vZZ5/x644dO8babDZ26dKlanY3LE8//TTbrVu3gN+53W42KyuLfeGFF/h11dXVbGpqKvvOO++wLGvscwvGAw88wLZr1451u90sy5r7+gFgFy9ezH9W6pr99ttvLAB206ZN/DYbN25kAbC///67ymflxf/8ArF582YWAHv48GF+3aBBg9gHHngg6D5GOT+WDXyOStyTRjlHMddw7Nix7NChQ33Wmeka+s8LZvgdkmZGIrW1tdi2bRtGjBjhs37EiBHYsGGDTr2KnLKyMgBAWlqaz/rVq1cjMzMTHTp0wO23346SkhL+u23btsHpdPqMQU5ODrp27WqIMdi/fz9ycnKQm5uLG264AX/88QcAoLCwECdOnPDpd1xcHAYNGsT32+jn5k9tbS3+/e9/45ZbbvEpxGbm6ydEqWu2ceNGpKam4tJLL+W36dOnD1JTUw13zmVlZWAYBo0bN/ZZ//HHHyMjIwNdunTBQw895PNGbIbzk3tPmuEcAeDkyZP49ttvceuttzb4zizX0H9eMMPv0PKFJpXm1KlTcLlcaNasmc/6Zs2a4cSJEzr1KjJYlsX06dMxYMAAdO3alV+fn5+P6667Dq1bt0ZhYSGeeuopDB06FNu2bUNcXBxOnDiB2NhYNGnSxOd4RhiDSy+9FB999BE6dOiAkydP4u9//zv69euHX3/9le9boGt3+PBhADD0uQViyZIlKC0txZQpU/h1Zr5+/ih1zU6cOIHMzMwGx8/MzDTUOVdXV+Oxxx7DjTfe6FOw76abbkJubi6ysrLwyy+/YObMmdi5cydvYjT6+SlxTxr9HDkWLlyIlJQUjB8/3me9Wa5hoHnBDL9DEmYixL8cOcuyYUuUG42pU6di165dWLdunc/6CRMm8Mtdu3ZFr1690Lp1a3z77bcNfqBCjDAG+fn5/HJeXh769u2Ldu3aYeHChbzDYSTXzgjnFoj58+cjPz8fOTk5/DozX79gKHHNAm1vpHN2Op244YYb4Ha78dZbb/l8d/vtt/PLXbt2xQUXXIBevXph+/bt6NGjBwBjn59S96SRz5Hjgw8+wE033YT4+Hif9Wa5hsHmBcDYv0MyM0kkIyMDdru9gRRZUlLSQGo1Mvfddx++/vprrFq1Ci1atAi5bXZ2Nlq3bo39+/cDALKyslBbW4uzZ8/6bGfEMUhKSkJeXh7279/PRzWFunZmOrfDhw/jxx9/xG233RZyOzNfP6WuWVZWFk6ePNng+H/++achztnpdOL6669HYWEhli9f7qOVCUSPHj3gcDh8rqmRz8+fSO5JM5zj2rVrsXfv3rC/ScCY1zDYvGCG3yEJMxKJjY1Fz549edUgx/Lly9GvXz+deiUelmUxdepULFq0CCtXrkRubm7YfU6fPo2jR48iOzsbANCzZ084HA6fMSguLsYvv/xiuDGoqanBnj17kJ2dzat4hf2ura3FTz/9xPfbTOf24YcfIjMzE1deeWXI7cx8/ZS6Zn379kVZWRk2b97Mb/Pzzz+jrKxM93PmBJn9+/fjxx9/RHp6eth9fv31VzidTv6aGvn8AhHJPWmGc5w/fz569uyJbt26hd3WSNcw3Lxgit+hLPfhKOWzzz5jHQ4HO3/+fPa3335jp02bxiYlJbGHDh3Su2thufvuu9nU1FR29erVbHFxMf+vqqqKZVmWPXfuHDtjxgx2w4YNbGFhIbtq1Sq2b9++bPPmzdny8nL+OHfddRfbokUL9scff2S3b9/ODh06lO3WrRtbV1en16mxLMuyM2bMYFevXs3+8ccf7KZNm9irrrqKTUlJ4a/NCy+8wKamprKLFi1id+/ezf7lL39hs7OzTXFuQlwuF9uqVSv20Ucf9Vlvxut37tw5dseOHeyOHTtYAOyrr77K7tixg4/mUeqajRo1ir3ooovYjRs3shs3bmTz8vLYq666Stfzczqd7JgxY9gWLVqwBQUFPr/JmpoalmVZ9sCBA+wzzzzDbtmyhS0sLGS//fZbtlOnTuzFF19siPMLd45K3pNGvIYcZWVlbGJiIvv222832N/o1zDcvMCyxv8dkjATIW+++SbbunVrNjY2lu3Ro4dPaLORARDw34cffsiyLMtWVVWxI0aMYJs2bco6HA62VatW7OTJk9kjR474HOf8+fPs1KlT2bS0NDYhIYG96qqrGmyjBxMmTGCzs7NZh8PB5uTksOPHj2d//fVX/nu3280+/fTTbFZWFhsXF8cOHDiQ3b17t88xjHpuQpYtW8YCYPfu3euz3ozXb9WqVQHvycmTJ7Msq9w1O336NHvTTTexKSkpbEpKCnvTTTexZ8+e1fX8CgsLg/4mV61axbIsyx45coQdOHAgm5aWxsbGxrLt2rVj77//fvb06dOGOL9w56jkPWnEa8jx7rvvsgkJCWxpaWmD/Y1+DcPNCyxr/N8hU38iBEEQBEEQpoR8ZgiCIAiCMDUkzBAEQRAEYWpImCEIgiAIwtSQMEMQBEEQhKkhYYYgCIIgCFNDwgxBEARBEKaGhBmCIAiCIEwNCTMEQUQNDMNgyZIleneDIAiFIWGGIAhFKSkpwZ133olWrVohLi4OWVlZGDlyJDZu3Kh31wiCsCgxeneAIAhrcc0118DpdGLhwoVo27YtTp48iRUrVuDMmTN6d40gCItCmhmCIBSjtLQU69atw4svvoghQ4agdevW6N27N2bOnMlX93711VeRl5eHpKQktGzZEvfccw8qKir4YyxYsACNGzfGN998g44dOyIxMRHXXnstKisrsXDhQrRp0wZNmjTBfffdB5fLxe/Xpk0b/O1vf8ONN96I5ORk5OTk4I033gjZ32PHjmHChAlo0qQJ0tPTMXbsWBw6dIj/fvXq1ejduzeSkpLQuHFj9O/fH4cPH1Z20AiCkA0JMwRBKEZycjKSk5OxZMkS1NTUBNzGZrPh9ddfxy+//IKFCxdi5cqVeOSRR3y2qaqqwuuvv47PPvsMS5cuxerVqzF+/Hh89913+O677/Cvf/0L7733Hr788kuf/V566SVcdNFF2L59O2bOnIkHH3wQy5cvD9iPqqoqDBkyBMnJyVizZg3WrVuH5ORkjBo1CrW1tairq8O4ceMwaNAg7Nq1Cxs3bsQdd9wBhmGUGSyCIJRDdqlKgiAIAV9++SXbpEkTNj4+nu3Xrx87c+ZMdufOnUG3/89//sOmp6fznz/88EMWAHvgwAF+3Z133skmJiay586d49eNHDmSvfPOO/nPrVu3ZkeNGuVz7AkTJrD5+fn8ZwDs4sWLWZZl2fnz57MdO3Zk3W43/31NTQ2bkJDALlu2jD19+jQLgF29erX0QSAIQlNIM0MQhKJcc801OH78OL7++muMHDkSq1evRo8ePbBgwQIAwKpVqzB8+HA0b94cKSkpmDRpEk6fPo3Kykr+GImJiWjXrh3/uVmzZmjTpg2Sk5N91pWUlPi03bdv3waf9+zZE7Cf27Ztw4EDB5CSksJrlNLS0lBdXY2DBw8iLS0NU6ZMwciRIzF69Gj84x//QHFxsdzhIQhCBUiYIQhCceLj4zF8+HD89a9/xYYNGzBlyhQ8/fTTOHz4MK644gp07doVX331FbZt24Y333wTAOB0Ovn9HQ6Hz/EYhgm4zu12h+1LMLOQ2+1Gz549UVBQ4PNv3759uPHGGwEAH374ITZu3Ih+/frh888/R4cOHbBp0yZJY0EQhPqQMEMQhOp07twZlZWV2Lp1K+rq6vDKK6+gT58+6NChA44fP65YO/6CxqZNm9CpU6eA2/bo0QP79+9HZmYm2rdv7/MvNTWV3+7iiy/GzJkzsWHDBnTt2hWffPKJYv0lCEIZSJghCEIxTp8+jaFDh+Lf//43du3ahcLCQnzxxReYM2cOxo4di3bt2qGurg5vvPEG/vjjD/zrX//CO++8o1j769evx5w5c7Bv3z68+eab+OKLL/DAAw8E3Pamm25CRkYGxo4di7Vr16KwsBA//fQTHnjgARQVFaGwsBAzZ87Exo0bcfjwYfzwww/Yt28fLrzwQsX6SxCEMlCeGYIgFCM5ORmXXnopXnvtNRw8eBBOpxMtW7bE7bffjscffxwJCQl49dVX8eKLL2LmzJkYOHAgZs+ejUmTJinS/owZM7Bt2zY888wzSElJwSuvvIKRI0cG3DYxMRFr1qzBo48+ivHjx+PcuXNo3rw5Lr/8cjRq1Ajnz5/H77//joULF+L06dPIzs7G1KlTceeddyrSV4IglINhWZbVuxMEQRByadOmDaZNm4Zp06bp3RWCIDSGzEwEQRAEQZgaEmYIgiAIgjA1ZGYiCIIgCMLUkGaGIAiCIAhTQ8IMQRAEQRCmhoQZgiAIgiBMDQkzBEEQBEGYGhJmCIIgCIIwNSTMEARBEARhakiYIQiCIAjC1JAwQxAEQRCEqSFhhiAIgiAIU/P/9uMaht3EMwoAAAAASUVORK5CYII=", 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", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ "# Reading Buck's input and output data\n", - "data_train = pd.read_csv(r'datasets/buck.txt' , sep=\" \", header=None).to_numpy()\n", - "data_valid = pd.read_csv(r'datasets/buck_val.txt' , sep =\" \", header=None).to_numpy()\n", - "\n", - "# Separating the identification data with decimation\n", - "data_samples_train = data_train[::12, 2]\n", - "data_out_train = data_train[:, 6]\n", - "data_int_train = data_train[:, 4]\n", - "\n", - "# Separating the validation data with decimation\n", - "data_samples_valid = data_valid[::12, 2]\n", - "data_out_valid = data_valid[:, 6]\n", - "data_int_valid = data_valid[:, 4]\n", + "df_train = pd.read_csv(r'examples/datasets/buck_id.csv')\n", + "df_valid = pd.read_csv(r'examples/datasets/buck_valid.csv')\n", "\n", "# Plotting the measured output (identification and validation data)\n", "plt.figure(1)\n", "plt.title('Output')\n", - "plt.plot(np.arange(0,data_out_train.shape[0]), data_out_train, label='Identification', linewidth=1.5)\n", - "plt.plot(np.arange(data_out_train.shape[0], data_out_train.shape[0] + data_out_valid.shape[0]), data_out_valid , label='Validation', linewidth=1.5)\n", - "plt.xlabel('Samples')\n", - "plt.ylabel('Voltage')\n", + "plt.plot(df_train.sampling_time, df_train.y, label='Identification', linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.y , label='Validation', linewidth=1.5)\n", + "plt.xlabel(\"Samples\")\n", + "plt.ylabel(\"Voltage\")\n", "plt.legend()\n", "plt.show()" ] @@ -113,21 +104,23 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "# Plotting the measured input(identification and validation data)\n", + "# Plotting the measured input (identification and validation data)\n", "plt.figure(2)\n", "plt.title('Input')\n", - "plt.plot(np.arange(0,data_out_train.shape[0]), data_int_train, label='Identification', linewidth=1.5)\n", - "plt.plot(np.arange(data_out_train.shape[0], data_out_train.shape[0] + data_out_valid.shape[0]), data_int_valid, label='Validation', linewidth=1.5)\n", + "plt.plot(df_train.sampling_time, df_train.input, label='Identification', linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.input, label='Validation', linewidth=1.5)\n", "plt.ylim(2.1, 2.6)\n", "plt.ylabel('u')\n", "plt.xlabel('Samples')\n", @@ -166,12 +159,14 @@ "outputs": [ { "data": { - "image/png": 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amgYOHKiHH35YnTp10qlTp7Rz50599tlnmjt3bo0jTu3bt1dYWJjeffdddenSRY0bN1ZsbKxiY2P117/+VUlJSRo+fLjGjBmj1q1b6/Dhw9q6das2bNig//3f/63VdU2fPl3/93//p1tuuUXdu3dXWFiYsrOzNWfOHOXn5+ull15ynHvppZdKkmbNmqWkpCQFBgaqa9euGjp0qEJCQnTbbbfpqaee0qlTp5SamqojR45U+X6XXnqpPvzwQ6WmpqpXr14KCAhwmho9+2e6bNkyXX755Zo8ebIuvfRSHT16VMuXL9djjz2mzp07m17XO++8oxEjRigpKUljx45VUlKSmjdvrtzcXC1dulQLFy7U+vXr1a5dO1199dWKiIjQPffco+eff15BQUF6++23nZ667K6xY8dq1qxZuv322xUWFqZbbrnF6eu33nqr3n33XV199dV65JFH1LdvXwUHB2vPnj1atWqVrr/+et1www3n/H3RQHl79TLgTa5SUeHh4Ub37t2NV155xTh16pTT+bm5ucZNN91kREREGOHh4caoUaOMdevWuUztZGRkGElJSUZ4eLhht9uN9u3bG48++qjj62emoiodPXrU+M1vfmNEREQYmZmZNfY/KyvLGD16tNGuXTsjJCTEuOCCC4wePXoYf/jDH4wDBw44zisvLzdmzZpldOzY0QgODjZatmxpjBo1ysjJyXH6vMGDBxuXXHJJle8zevRol6mdgoICIywszJBkvPXWWy77ePDgQePhhx824uPjjeDgYCMiIsLo1auX8eyzzxrHjx83DOPXVNRLL73k8jMWLlxodO7c2QgODq6SEvr++++Nm2++2YiMjDSCg4ON6Oho48orrzTmzp3rOKfyPrvzMzUMw1izZo0xYcIEo1u3bkZERIQRGBhotGrVyhgxYoTx2WefOZ1bXFxs/L//9/+MVq1aGTabzSkxtHTpUqNbt25GaGio0bp1a+PJJ580li1bViVdd/jwYeOmm24ymjVr5viMSmdfr2EYRk5OjjF27FgjOjraCA4ONmJjY42bb77Z2L9/f43XdvLkSeO1114zBgwYYDRt2tQICgoyYmNjjRtvvNH49NNPnc5du3atMXDgQOOCCy4wWrdubUyZMsX429/+5jIVdc0111T7fQcOHGhIMu644w6XXy8tLTVefvllx8+rcePGRufOnY1x48YZ27dvr/G6gEo2wzAMz5dTAAAAdY81NgAAwG9Q2AAAAL9BYQMAAPwGhQ0AAPAbFDYAAMBvUNgAAAC/0eAKG8MwVFhYKFLuAAD4nwZX2Bw7dkzh4eE6duyYt7sCAADqWIMrbAAAgP+isAEAAH6DwgYAAPgNChsAAOA3KGwAAIDfoLABAAB+g8IGAAD4DQobAADgNyhsAACA36CwAQAAfoPCBgAA+I0gb3fAH5RXGFqbfVgHjp1SZJNQ9Y2PUGCAzdvdAgCgwaGwOU/LN+UqZekW5RacchyLCQ/VlOQEjUiM8WLPAABoeJiKOg/LN+Vq/PwNTkWNJOUVnNL4+Ru0fFOul3oGAEDDRGFTS+UVhlKWbpHh4muVx1KWblF5haszAABAfaCwqaW12YerjNScyZCUW3BKa7MPe65TAAA0cBQ2tXTgmHlRU5vzAADA+aOwqaXIJqF1eh4AADh/FDa11Dc+QjHhoaop1P3zgWMyjNPrbMorDGXsyNfHWXuVsSOf9TcAANQxm1H5V7eBKCwsVHh4uAoKCtS0adPz+qzKVJQkp0XEtrPeX3NpjK7qEqmXVmwjFg4AQD2isDlPZs+x+cO1Cdp79KReXPaTykxGZipHe1JH9aS4AQCgDlDY1IHqnjy8budh3fzXDJnNOtkkRYeH6punr+RpxQAAnCeePFwHAgNsGtC+hcuvlZYbpkWN5BwLN/sMAADgHhYP1zNi4QAAeA6FTT0jFg4AgOcwFVXPKmPheQWnXG6/IEn2oAB1iGwsiZ3CAQA4Hywe9gCzWPiZYsNDdXu/dnr3u91EwgEAqCUKGw8xi4Xf/ZsLtXBtjrIPFblsRyQcAAD3Udh4kNk0U8HJUvWb8blOlVa4bEckHAAA97DGxoPMYuFb9hWaFjUSkXAAANxFKsoHEAkHAKBuUNj4ACLhAADUDaaifIA7kfAAm1RWfnq6ikg4AACu+cyITWpqqrp27aqmTZuqadOmGjBggJYtW+b4umEYmjp1qmJjYxUWFqYhQ4Zo8+bNXuxx3QkMsGlKcoKkX1NQZ6swpLvmrdUD89frNy9+qdveWqNHFmXptrfW6LJZX2r5plzPdRgAAB/lM4VNmzZt9OKLL2rdunVat26drrzySl1//fWO4mX27Nl65ZVXNGfOHGVmZio6OlpDhw7VsWPHvNzzujEiMUapo3oqOtx5uikmPFSv3tpdt/ZpK8OQPtuUp7xC57U2eQWnNH7+BoobAECD59Nx74iICL300ksaO3asYmNjNXHiRD399NOSpOLiYkVFRWnWrFkaN26c25/pzbi3O8ymmcorDPV6IU1HT5a6bEckHAAAHxqxOVN5ebkWLVqkoqIiDRgwQNnZ2crLy9OwYcMc59jtdg0ePFjffvtttZ9VXFyswsJCp5cvq4yEX9+9tQa0b+EoUtZmHzYtaiTnSDgAAA2VTxU2P/74oxo3biy73a77779fixcvVkJCgvLy8iRJUVFRTudHRUU5vmZm5syZCg8Pd7zatm1bb/2vT0TCAQComU8VNp06dVJWVpbWrFmj8ePHa/To0dqyZYvj6zab8xSLYRhVjp1t0qRJKigocLxycnLqpe/1jUg4AAA186m4d0hIiC6++GJJUu/evZWZmalXX33Vsa4mLy9PMTG/7pd04MCBKqM4Z7Pb7bLb7fXXaQ9xJxIuSZ9vzVPvC5srwGYjEg4AaHB8qrA5m2EYKi4uVnx8vKKjo5WWlqYePXpIkkpKSrR69WrNmjXLy730jMpI+Pj5G2ST8y7hZ77/+zc79cXWAyoqKdfBY8WOc9glHADQEPjMVNTkyZP19ddfa+fOnfrxxx/17LPPKj09XXfccYdsNpsmTpyoGTNmaPHixdq0aZPGjBmjRo0a6fbbb/d21z3GLBIeHR6quaN66q939lJYcIB25p9wKmokIuEAgIbBZ0Zs9u/frzvvvFO5ubkKDw9X165dtXz5cg0dOlSS9NRTT+nkyZN64IEHdOTIEfXr108rV65UkyZNvNxzzxqRGKOhCdGmkfDGocE6WVpcpZ2h0yM7KUu3aGhCNNNSAAC/5NPPsakPvv4cm/ORsSNft721psbzFt7bn13CAQB+yWemonD+iIQDABo6n5mKwvlzN+rdrFGwJDbTBAD4HwobP+JuJPzFz37SzkMnNHf1DuUW/Dp6Q3IKAGB1rLHxM8s35Wr8/A2SXEfCG9uDdLy4zGXbyrGa1FE9KW4AAJbEGhs/U1MkfOWjlysk0PV0U2UhlLJ0i8orGlS9CwDwE0xF+aHqIuEZO/JVUm5etJy5mSbJKQCA1VDY+KnKXcLPRnIKAODPmIpqYNhMEwDgzxixaWDcSU4FBdgUHhbseE8sHABgFaSiGiCz5NSZ7EEBev76S9Q0NFjPf7KFWDgAwBIobBqo5ZtylbK0asHy6NCO+uSHXH3180HTtsTCAQC+isKmATObYqqoMPTG6v/o5RU/m7a16XSE/Junr2RaCgDgM1hj04CZJacCAmzq1S6i2rbEwgEAvohUFFwiFg4AsCIKG7hELBwAYEVMRcEld2LhTUOD1OfC5pKIhAMAfAOLh2HKnVj48EuiNCwhWi+v3EYkHADgdRQ2qJZZLHxQh5ZavHGvSk32nSISDgDwBgob1Mhsmmnj7iO6KTVD5Sa/QkTCAQCexhob1MgsFn6qtMK0qJGIhAMAPI9UFGqNSDgAwNdQ2KDWiIQDAHwNU1GoNXci4fagALVvdYEkIuEAgPrH4mGcF3ci4VFN7bqjX5wWrt1NJBwAUK8obHDezCLh9wyK18LvdmvHwSKX7YiEAwDqGoUN6oTZNNOxU6XqO/0LnSwtd9mOSDgAoC6xxgZ1wiwSvmlvoWlRIxEJBwDULVJRqFdEwgEAnkRhg3pFJBwA4ElMRaFeuRMJD7BJp/47XUUkHABwPlg8jHrnTiRcOr1T+Pc5BcorJBIOAKgdpqJQ70Ykxih1VE9FhztPN8WEh+q1W7trVP92kqQVm/c7FTWSlFdwSuPnb9DyTbke6y8AwLoYsYHHmE0zlVcY6jUtTUdPlLpsRyQcAOAu1tjAY8wi4WuzD5sWNRKRcACA+5iKgtcRCQcA1BUKG3gdkXAAQF2hsIHXVUbCa1o9s3xzrkrKKlReYShjR74+ztqrjB35Kq9oUMvEAADVYPEwfIJZJNx21vu4Fo10orhcB48XO44RCQcAVGLEBj7BLBIeHR6quaN66m939VajkEDtyj/hVNRIRMIBAL8iFQWfMSIxRkMTok0j4Y3tQTpRUnVDTUOnR3ZSlm7R0IRoIuEA0IBR2MCnVBcJP3Cs2EWL04iEAwAkH5qKmjlzpvr06aMmTZooMjJSI0eO1LZt25zOGTNmjGw2m9Orf//+XuoxPIlIOADAHT5T2KxevVoTJkzQmjVrlJaWprKyMg0bNkxFRUVO540YMUK5ubmO12effealHsOT3I16N2sUXM89AQD4Mp+Zilq+fLnT+3nz5ikyMlLr16/X5Zdf7jhut9sVHR3t6e7By9zZJVySZny6Va2bNdLFkY3ZKRwAGiCfKWzOVlBQIEmKiIhwOp6enq7IyEg1a9ZMgwcP1vTp0xUZGemNLsKDAgNsmpKcoPHzN1SJgFe+bxIapG37j+u6Od/o5t5ttGLzfuUWsFM4ADQkPvkcG8MwdP311+vIkSP6+uuvHcffe+89NW7cWHFxccrOztZzzz2nsrIyrV+/Xna73eVnFRcXq7j410WnhYWFatu2Lc+xsajlm3KVsnSLy4KlZ1xzTVyUpW935LtsWzlWkzqqJ8UNAPgpnyxsJkyYoE8//VTffPON2rRpY3pebm6u4uLitGjRIt14440uz5k6dapSUlKqHKewsa7qpphKyirU84U0HS8uc9mWncIBwL/5zOLhSg899JCWLFmiVatWVVvUSFJMTIzi4uK0fft203MmTZqkgoICxysnJ6euuwwPq4yEX9+9tQa0b+FUoKzfdcS0qJGcY+EAAP/jM2tsDMPQQw89pMWLFys9PV3x8fE1tsnPz1dOTo5iYsynFex2u+k0FfwPsXAAaNh8prCZMGGCFixYoI8//lhNmjRRXl6eJCk8PFxhYWE6fvy4pk6dqt/97neKiYnRzp07NXnyZLVs2VI33HCDl3sPX3GuO4WTnAIA/+IzhU1qaqokaciQIU7H582bpzFjxigwMFA//vij3nnnHR09elQxMTG64oor9N5776lJkyZe6DF8kbux8P8cPKajJ0r0/CeuFyKzuBgArMknFw/XJ3b39n/u7hTuCskpALA2n1s8DJyv6nYKf+P2nnomqZNp28rCJ2XpFpVXNKiaHwD8gs9MRQF1qbqdwjNMnnNTiQ01AcC6KGzgt8x2Cic5BQD+i6koNDjnmpwCAFgHIzZocNxJTjUNDVKfC5tLIhIOAFZCKgoNklly6ky/7RKppMRovbzyZyLhAGARFDZosMw21BzcsZU+3LBXJeUVLtsRCQcA30VhgwbNbJrp+5yjujH1W9PIN5tpAoBvYo0NGjSz5NSJkvJqn2NDJBwAfBOpKMAFIuEAYE0UNoALRMIBwJqYigJccCcSHhIUoPiWF0giEg4AvoLFw4AJdyLhrZrYdUffdnpvXQ6RcADwARQ2QDXMIuH3DrpIizJ36+f9x122IxIOAN5BYQPUwGya6fipMvWZ/rlOlpa7bEckHAA8jzU2QA3MIuE/7i0wLWokIuEA4A2kooBaIhIOAL6HwgaoJSLhAOB7mIoCasmdSLjNJp0oLpNEJBwAPIHFw8B5cCcSLklDE6L0454C5RUSCQeA+sRUFHAeRiTGKHVUT0WHO083xYSH6i+3ddeYgRdKktK27HcqaiQpr+CUxs/foOWbcj3VXQDwe4zYAHXAbJqpvMJQr2lpOnqi1GU7IuEAULdYYwPUAbNI+Nrsw6ZFjUQkHADqGlNRQD0iEg4AnkVhA9QjIuEA4FkUNkA9qoyE17R65tMf9+nUf59iXF5hKGNHvj7O2quMHfkqr2hQy+AA4LyweBioZ2aRcNtZ7y+Jbaqbe7fV3NU72CkcAGqJwgbwALNdwqckJ8geHKjH3/9eh4tKXLZlp3AAcB+FDeAh1T15eO+Rk7ri5VUqKXf9nyOxcABwD3FvwEPMIuGStPvwCdOiRiIWDgDuYvEw4AOIhQNA3aCwAXwAsXAAqBtMRQE+wJ2dwoMCbGrWKFgSO4UDgBkWDwM+wp2dwkODA/Q/vdoqbet+5REJB4AqmIoCfER1O4XPvqmrBnVoqVOlFfrXml1ORY3ETuEAUIkRG8DHmE0zlZZVqMcLaTpeXOayHZFwAGCNDeBzzGLh63YdMS1qJCLhACAxFQVYBpFwAKgZhQ1gEUTCAaBmFDaARbi7U/i2/YUyDINdwgE0SCweBizE3Z3Ce7Rtpn0FJ7W/sNhxjEg4gIaAERvAQswi4dHhoUq9o6f+cG2CAgOkjTlHnYoaiUg4gIbBZwqbmTNnqk+fPmrSpIkiIyM1cuRIbdu2zekcwzA0depUxcbGKiwsTEOGDNHmzZu91GPAO0Ykxuibp6/Uwnv769Vbu2vhvf31zdNXKunSGI0eeKGahYW4bFc5opOydAvTUgD8ls8UNqtXr9aECRO0Zs0apaWlqaysTMOGDVNRUZHjnNmzZ+uVV17RnDlzlJmZqejoaA0dOlTHjh3zYs8Bz6uMhF/fvbUGtG/heG7N2uzDyi8qMW13ZiQcAPyRzzzHZvny5U7v582bp8jISK1fv16XX365DMPQn//8Zz377LO68cYbJUn//Oc/FRUVpQULFmjcuHHe6DbgU4iEA2jofGbE5mwFBQWSpIiICElSdna28vLyNGzYMMc5drtdgwcP1rfffmv6OcXFxSosLHR6Af7K3ah3q8Z2SSI5BcDv+MyIzZkMw9Bjjz2myy67TImJiZKkvLw8SVJUVJTTuVFRUdq1a5fpZ82cOVMpKSn111nAh7izS7gkvfnVDu09elKvpP2sXDbTBOBHfHLE5sEHH9QPP/yghQsXVvmazeb8FA/DMKocO9OkSZNUUFDgeOXk5NR5fwFfERhg05TkBEmq8rybyvdBATal/3xIT/77B6eiRiI5BcD6fK6weeihh7RkyRKtWrVKbdq0cRyPjo6W9OvITaUDBw5UGcU5k91uV9OmTZ1egD+rLhI+d1RPfTThN6abZJKcAmB1PjMVZRiGHnroIS1evFjp6emKj493+np8fLyio6OVlpamHj16SJJKSkq0evVqzZo1yxtdBnzWiMQYDU2IdrlLeE1radhME4CV+UxhM2HCBC1YsEAff/yxmjRp4hiZCQ8PV1hYmGw2myZOnKgZM2aoQ4cO6tChg2bMmKFGjRrp9ttv93LvAd9jtks4ySkA/sxnCpvU1FRJ0pAhQ5yOz5s3T2PGjJEkPfXUUzp58qQeeOABHTlyRP369dPKlSvVpEkTD/cWsC420wTgz9grCmhgyisMXTbry2qTUyGBAVr95BDFNAtTeYXhckoLAHwRhQ3QAJltpnmmlo1DdHu/dvrfdXuIhAOwDAoboIFavilXKUu3VCla7rv8Ir2XmaOf8lxvVVI5VpM6qifFDQCfQ2EDNGBm00xFxWXqM/1znSgpd9nOptPx8W+evpJpKQA+xWcWDwPwPLPk1A97CkyLGolIOADf5XMP6APgfUTCAVgVhQ2AKoiEA7AqpqIAVOHOZpo2SYUnSx3viYUD8AUsHgbgkjuRcEm657J4dW/bTDM+20osHIDXUdgAMGUWCZ98dRdt3H1U//i/bNO2xMIBeAOFDYBqVTfFtGJTnu6fv77a6Spi4QA8iTU2AKplFgmXpKZhwdVOUxELB+BppKIA1BqxcAC+hsIGQK0RCwfga5iKAlBr7sTCG4UEqmubcElEwgHUPxYPAzgv7sTCO0c30a192+qvq38hEg6gXlHYADhvZrHw/+ndRu+u2a38ohKX7YiEA6hrFDYA6oTZNFPu0ZMa/FK6SsorXLYjEg6gLrHGBkCdMIuF78w/YVrUSETCAdQtUlEA6hWRcACeRGEDoF4RCQfgSUxFAahX7kTCAwNsahp2+p8jIuEAzgeLhwHUO3ci4fagAN3Uq42++OmA8oiEA6glpqIA1LsRiTFKHdVT0eHO000x4aF66aauuqJTKxWXVejd73Y7FTWSlFdwSuPnb9DyTbme7DIAi2LEBoDHmE0zlZZVqOe0NB07VeayHZFwAO5ijQ0AjzGLhK/bdcS0qJGIhANwH1NRALyOSDiAukJhA8DriIQDqCsUNgC8rjISXtPqmU37CmQYhsorDGXsyNfHWXuVsSNf5RUNaqkggGqweBiATzCLhNvOet+1Tbj2F57S/sJixzEi4QAqMWIDwCeYRcKjw0OVekdPPX/9JQoKsOmHPQVORY1EJBzArxixAeBTzCLh5RWG+s34XIeOl7hsRyQcgFTLuHdOTo7atm1b130BANNI+Nrsw6ZFjUQkHMBptZqK6ty5s5577jkVFRXVdX8AwCUi4QDc4XZh8+KLL+ro0aOSpLS0NK1cuVIdOnTQvHnz6qtvAODgbtS7VWN7PfcEgC9zu7CZMWOGDh8+LEkaOHCgvvvuO7344ov6wx/+oB49eig9Pb2++ggAbkfC30j/jw4dLyYSDjRQbi8ebtKkib7//ntddNFFTsdPnjypmTNn6o9//KOGDRuml156SRdffHG9dLYusHgYsK6aIuHBgTaVlhtqGhqkoMAAHS76dU0OkXCgYTjvuLdhGBo2bJjuu+8+LVmyRImJiXr88cd17NixuugfADhUFwmfO6qnPn14kKKbhqrwVJlTUSMRCQcaCrdTUZMnT1ZERIQkae7cucrMzFRmZqa2bt2qwMBAde3aVRMmTFD37t317rvvKiEhQYsXL1bv3r3rrfMAGp4RiTEamhBtGgk35HoQ2tDpkZ2UpVs0NCGaSDjgp2r1HJu2bduqf//+jlfv3r1ltzsv2JsxY4YWLFigTZs21Vln6wJTUYD/ytiRr9veWlPjeQvv7U8kHPBTtX6OTU3uuecePffcc7X5eACoFSLhAGpV2LgjMjJSX375ZX19PABU4W4kPCjg1+WFZk86BmBN9bZXlM1m0+DBg8+pzVdffaXk5GTFxsbKZrPpo48+cvr6mDFjZLPZnF79+/evw14DsDJ3I+G//+hHpW87oOWbcnXZrC9121tr9MiiLN321hpdNutLFhgDFuZTm2AWFRWpW7dumjNnjuk5I0aMUG5uruP12WefebCHAHxZYIBNU5ITJKlKcVP5vk2zMB05Uaox8zJ1//wNyi1wnpYiPQVYW71NRdVGUlKSkpKSqj3HbrcrOjraQz0CYDWVkfCUpVucipbo/z7HZkinSE37dIvmr9ntsj3pKcDafKqwcUd6eroiIyPVrFkzDR48WNOnT1dkZKS3uwXAh1QXCZekay6NNS1sJDbUBKzMUoVNUlKS/ud//kdxcXHKzs7Wc889pyuvvFLr16+vEjevVFxcrOLiYsf7wsJCT3UXgBeZ7RIukZ4C/JmlCptbbrnF8f8nJiaqd+/eiouL06effqobb7zRZZuZM2cqJSXFU10EYAHupqfcPQ+A7/CpxcPnKiYmRnFxcdq+fbvpOZMmTVJBQYHj5c4zeAD4N3fSU80bBatv/OmnrbOhJmAdlhqxOVt+fr5ycnIUE2O+qZ3dbjedpgLQMFWmp8bP3+DYQPNsR06U6oVPtqhXXDPN+Ownp4XIbKgJ+C6fGrE5fvy4srKylJWVJUnKzs5WVlaWdu/erePHj+uJJ55QRkaGdu7cqfT0dCUnJ6tly5a64YYbvNtxAJZjtqFmTHiohiZESZLe/nanHlqYRSQcsJBa7RVVX9LT03XFFVdUOT569GilpqZq5MiR2rhxo44ePaqYmBhdccUVeuGFF9S2bVu3vwd7RQE4k9mThz/fkqd7/7VeZv9C2nQ6Qv7N01cSCQd8iE9NRQ0ZMkTV1VkrVqzwYG8ANARm6akL7MGmRY1EJBzwVT41FQUAvoJIOGBNFDYA4AKRcMCafGoqCgB8RWUkPK/glMvUlCSFBQfq0tbhktglHPAVPrV42BNYPAzAXcs35Wr8/A2SXEfCJaljVGPd2qed3vr6FyLhgA+gsAGAaizflFtlQ82Y8FDd0rut3l27WwePFbtsVzlWkzqqJ8UN4EEUNgBQA7NppryCU7p89iqVlFe4bEckHPA81tgAQA3MIuHZh4pMixqJSDjgDaSiAKCWiIQDvofCBgBqiUg44HuYigKAWnInEh4YYFOjkEBJRMIBT2DxMACcB3ci4SGBAbqxZ2ul/3xQeUTCgXrFVBQAnIfqdgl/+aau+m2XSJWUV2hRZo5TUSOxSzhQHxixAYA6YDbNVFZeoR4vpOnYqTKX7YiEA3WLNTYAUAfMIuGZO4+YFjUSkXCgrjEVBQD1iEg44FkUNgBQj4iEA55FYQMA9agyEl7T6pnv9xxRRYWh8gpDGTvy9XHWXmXsyFd5RYNaBgmcNxYPA0A9M4uE2856n9i6qQ4UFuvAGRtrEgkHzg0jNgBQz8wi4dHhoUq9o6em35CooACbNu0tdCpqJCLhwLlixAYAPMQsEl5eYajfjM916HiJy3ZEwgH3EfcGAA8xi4SvzT5sWtRIRMKBc8FUFAB4GZFwoO5Q2ACAl7kb9W7Z2F7PPQGsj8IGALzM3Uj4nC+3O0ZtiIUDrrF4GAB8QE2R8JDAAJWUV6hlY7vu6NdO76/LUS47hQNVUNgAgI9YvilXKUu3uCxYLo5sogcXbNBPecdctq0c7Ukd1ZPiBg0ahQ0A+BCzSLgkFRWXqff0z3WypNxlW2LhAHFvAPApZpFwSfphT4FpUSMRCwckFg8DgGUQCwdqRmEDABbBTuFAzZiKAgCLqIyF5xWcktniSJtNOn6qVFL163UAf8XiYQCwELNY+Nl+2yVSm/YWKq+QSDgaFqaiAMBCzHYKjwkP1V9u6667f3OhJOnzrQecihqJncLRMDBiAwAWVN1O4b2npenIiVKX7YiEw9+xxgYALKi6ncLNihqJSDj8H1NRAOBHiISjoWPEBgD8yLlGwklOwd9Q2ACAH3EnEi5JS3/Yq4PHTmnmsp/YTBN+hcXDAOBnatopvDpspgmrY40NAPgZs0h4dHio5o7qqXlj+shstqmy8ElZukXlFQ3qf/fCTzAVBQB+aERijIYmRLtcP5OxI1/V1Swkp2BlFDYA4KfMIuEkp+DPfGoq6quvvlJycrJiY2Nls9n00UcfOX3dMAxNnTpVsbGxCgsL05AhQ7R582bvdBYALIrNNOHPfKqwKSoqUrdu3TRnzhyXX589e7ZeeeUVzZkzR5mZmYqOjtbQoUN17NgxD/cUAKyrMjlVXag7LDhQl8SeDliUVxjK2JGvj7P2KmNHPmtv4NN8NhVls9m0ePFijRw5UtLp0ZrY2FhNnDhRTz/9tCSpuLhYUVFRmjVrlsaNG+fW55KKAgD3NtNs3+oC3davnf7+dTaRcFiGT43YVCc7O1t5eXkaNmyY45jdbtfgwYP17bffmrYrLi5WYWGh0wsAGrrqNtN8bGhHRTW1a8fBIk37ZKtTUSOxmSZ8m2UWD+fl5UmSoqKinI5HRUVp165dpu1mzpyplJSUeu0bAFhRdcmpW/u01WWzV6mkrKJKO0Onn3eTsnSLhiZE86Ri+BTLjNhUstmc/wMyDKPKsTNNmjRJBQUFjldOTk59dxEALKMyOXV999Ya0L6Fo0jZcbDIZVFT6cxIOOBLLDNiEx0dLen0yE1MzK/zugcOHKgyinMmu90uu91e7/0DAH9CJBxWZZkRm/j4eEVHRystLc1xrKSkRKtXr9bAgQO92DMA8D9EwmFVPjVic/z4cf3nP/9xvM/OzlZWVpYiIiLUrl07TZw4UTNmzFCHDh3UoUMHzZgxQ40aNdLtt9/uxV4DgP9xZzPNQJtNocGn//cxu4TDV/hU3Ds9PV1XXHFFleOjR4/W22+/LcMwlJKSor/+9a86cuSI+vXrp9dff12JiYlufw/i3gDgHnci4cGBNt3Qo7W+2n5IeUTC4QN8qrDxBAobAHDf8k25Slm6pcpzbJ4Y1kkrt+Rpxeb9LtuxSzi8hcIGAFAts2mmsvIK9XwhTYWnyly2s+n0juLfPH0l01LwGJ9aYwMA8D1mm2lm7jxiWtRI7BIO77BMKgoA4FuIhMMXUdgAAGqFSDh8EYUNAKBW3NklXJLW7z6siv/uCM5O4ahvLB4GANSaWSTcdtb7wR1b6dquMXol7Wd2Cke9orABAJwXs0j4H65NUOGpUk1ZslmnSl3vO0UsHHWNwgYAcN6qe/Lwln2FSp7zjem0E7Fw1CXi3gCA82YWCZekgpOl1a6lIRaOusTiYQBAvSIWDk+isAEA1Cti4fAkpqIAAPXKnZ3CQwJtimvRSBI7heP8sHgYAFDv3NkpvMUFIbq9Xzv9e/0eIuGoNQobAIBHmMXCxw2+SO9l7tHW3EKX7YiE41xQ2AAAPMZsmqmouEx9pn+uEyXlLtsRCYe7WGMDAPAYs1j4D3sKTIsaiUg43EcqCgDgdUTCUVcobAAAXkckHHWFqSgAgNe5Ewm3STp6okQSkXCYY/EwAMAnuBMJl6QrOrXS1txC5RUWO44RCUclpqIAAD5hRGKMUkf1VHS483RTTHio/nJbD907KF6StGrbQaeiRpLyCk5p/PwNWr4p12P9hW9ixAYA4FPMppnKKwz1npamIydKXbYjEg6JNTYAAB9jFglfm33YtKiRiITjNKaiAACWQCQc7qCwAQBYApFwuIPCBgBgCZWR8JpWzyzeuEenSstVXmEoY0e+Ps7aq4wd+SqvaFBLShssFg8DACzDLBJuO+t9bHioSsordOh4ieMYkfCGgREbAIBlmEXCo8NDNXdUT82/p5+ahAZpX8Epp6JGIhLeUJCKAgBYyojEGA1NiDaNhIcFB+rYqbIq7QydHtlJWbpFQxOiiYT7KQobAIDlVBcJP3Cs2EWL04iE+z+mogAAfoNIOBixAQD4DXej3k1CgyWxmaY/orABAPgNd3YJl6QXlm7WjgPH9Y//y1Zuwa+jNySnrI+4NwDAr9QUCW/WKFhHq9lvSpJSR/WkuLEo1tgAAPxKTZHwzx8dLHuQ6z9/lYVQytItPNDPopiKAgD4neoi4Rk78lVcVmHaluSUtVHYAAD8klkknOSUf2MqCgDQoLCZpn9jxAYA0KC4k5wKtEnBgb/GvomFWwepKABAg2OWnDpTUIBNzyR1VutmYXr+ky3Ewi2CwgYA0CAt35SrlKVVC5Ynh3fS51v367Mf80zbEgv3XZYqbKZOnaqUlBSnY1FRUcrLM//lOxuFDQCgktkUk2EYemfNLk35eLNpW5tOR8i/efpKpqV8iOXW2FxyySX6/PPPHe8DAwO92BsAgJWZJadsNps6Rjapti2xcN9kucImKChI0dHR3u4GAMDPEQu3JsvFvbdv367Y2FjFx8fr1ltv1S+//OLtLgEA/BCxcGuy1IhNv3799M4776hjx47av3+/pk2bpoEDB2rz5s1q0cL1MGBxcbGKi4sd7wsLCz3VXQCAhbkTC29iD1KvuOaSiIT7CkstHj5bUVGR2rdvr6eeekqPPfaYy3NcLTiWxOJhAECN3ImF/+biFrquW2v9+fOfiYT7AEsXNpI0dOhQXXzxxUpNTXX5dVcjNm3btqWwAQC4xSwWPiwhSu+v26OTpeUu2xEJ9w5LTUWdrbi4WFu3btWgQYNMz7Hb7bLb7R7sFQDAn1S3oeZtfdvp2r98ozIXO4EbOl3cpCzdoqEJ0UxLeYilCpsnnnhCycnJateunQ4cOKBp06apsLBQo0eP9nbXAAB+zCwWfuREqcuiphKRcM+zVGGzZ88e3XbbbTp06JBatWql/v37a82aNYqLi/N21wAADRCRcN9jqcJm0aJF3u4CAAAORMJ9j6UKGwAAfIk7kfDgQJvaNA+TRCTcEyyfijpX7BUFAKhL7kTCmzUK1h392unDDXuJhNczChsAAM6TWST8gSHt9f66Pfpxb4HLdkTC6x6FDQAAdcBsmulESZl6T/tcJ0rMn3fDLuF1hzU2AADUAbNI+Pc5BaZFjUQkvK5ZbhNMAACshEi4Z1HYAABQj4iEexZTUQAA1CN3IuE2SfnHT+9rSCT8/LB4GACAeuZOJFySBndspW15hcor/HXzZiLh54apKAAA6tmIxBiljuqp6HDn6aaY8FDNub2Hxg9pL0la/fNBp6JGkvIKTmn8/A1avinXY/21MkZsAADwELNppvIKQ72npenIiVKX7YiEu481NgAAeIhZJHxt9mHTokYiEn4umIoCAMDLiITXHQobAAC8jEh43aGwAQDAyyoj4TWtnvn3+hydKCmTdHq9TsaOfH2ctVcZO/JVXtGglsyaYvEwAAA+wCwSbvvv+8r/2yGysW7r205vff0LO4W7QGEDAICPMNslfEpygsLDQvTIoo06cKzYZVt2Cj+NwgYAAB9S3ZOH9xee0qDZq1RSVuGyLbFw4t4AAPgUs0i4JP1ysMi0qJGIhUssHgYAwDKIhdeMwgYAAIsgFl4zpqIAALAId3YKDwywqVFIoKSGuVM4i4cBALAQd3YKDwkM0A09Wmv19oPKa2CRcKaiAACwkOp2Cv/j/3TT0IQolZRX6L11OU5FjdQwdgpnxAYAAAsym2YqK69QzxfSVHiqzGU7f4+Es8YGAAALMouFZ+48YlrUSP4fCWcqCgAAP9LQI+GM2AAA4EfONRLub8kpChsAAPyIO5FwSdqYc0RHikr0wqeu96ayanKKxcMAAPiZmnYKr47VN9NkjQ0AAH7GLBIeHR6q1Dt6avoNiaZtKwuflKVbVF5hvbEPpqIAAPBDIxJjNDQh2uX6mYwd+dW2tXJyisIGAAA/ZRYJ9+fkFFNRAAA0MP68mSYjNgAANDDuJKca24PUK665JGtFwklFAQDQALmzmWb/iyI0sntrvfrFdstEwilsAABooJZvylXK0qrPsRmRGK33MnN0oqTcZTtfjoRT2AAA0ICZTTP9vP+Yrn71a5WZRL59dTNN1tgAANCAmSWn8o+XmBY1ku9GwklFAQCAKqwaCaewAQAAVVg1Es5UFAAAqMKdSHhwoE2xzXxrl3BLLh5+44039NJLLyk3N1eXXHKJ/vznP2vQoEFutWXxMAAA7nEnEh4eFqzb+rbVx1n7fCISbrmpqPfee08TJ07Us88+q40bN2rQoEFKSkrS7t27vd01AAD8itlmmjHhoZo2MlHd2oSr4GSp5q7+xamokaS8glMaP3+Dlm/K9WSXrTdi069fP/Xs2VOpqamOY126dNHIkSM1c+bMGtszYgMAwLkxm2Y6WVKu3tPSVFTN8248HQm31BqbkpISrV+/Xs8884zT8WHDhunbb7912aa4uFjFxcWO94WFhfXaRwAA/I1ZJDwr56hpUSN5JxJuqamoQ4cOqby8XFFRUU7Ho6KilJeX57LNzJkzFR4e7ni1bdvWE10FAMDv+WIk3FKFTSWbzXk4yzCMKscqTZo0SQUFBY5XTk6OJ7oIAIDf88VIuKWmolq2bKnAwMAqozMHDhyoMopTyW63y263e6J7AAA0KDVFwivX2PSNj/BYnyw1YhMSEqJevXopLS3N6XhaWpoGDhzopV4BANAwBQbYNCU5QdKvG2NWqnw/JTnBo8+zsVRhI0mPPfaY/va3v+kf//iHtm7dqkcffVS7d+/W/fff7+2uAQDQ4JhFwqPDQ72y+7elpqIk6ZZbblF+fr6ef/555ebmKjExUZ999pni4uK83TUAABqkEYkxGpoQzZOHvYHn2AAA4L8sNxUFAABghsIGAAD4DQobAADgNyhsAACA36CwAQAAfoPCBgAA+A0KGwAA4DcobAAAgN+gsAEAAH7DclsqnK/KBy0XFhZ6uScAAOBcNWnSRDab+VYNDa6wOXbsmCSpbdu2Xu4JAAA4VzVtidTg9oqqqKjQvn37aqz4zlVhYaHatm2rnJwcv92Dyt+vkeuzPn+/Rn+/Psn/r5HrO3+M2JwlICBAbdq0qbfPb9q0qV/+sp7J36+R67M+f79Gf78+yf+vkeurPyweBgAAfoPCBgAA+A0Kmzpit9s1ZcoU2e12b3el3vj7NXJ91ufv1+jv1yf5/zVyffWvwS0eBgAA/osRGwAA4DcobAAAgN+gsAEAAH6DwgYAAPgNCptz8MYbbyg+Pl6hoaHq1auXvv7662rPX716tXr16qXQ0FBddNFFmjt3rod6Wnvnco3p6emy2WxVXj/99JMHe+y+r776SsnJyYqNjZXNZtNHH31UYxsr3cNzvT6r3b+ZM2eqT58+atKkiSIjIzVy5Eht27atxnZWuYe1uT6r3cPU1FR17drV8fC2AQMGaNmyZdW2scr9k879+qx2/842c+ZM2Ww2TZw4sdrzPH0PKWzc9N5772nixIl69tlntXHjRg0aNEhJSUnavXu3y/Ozs7N19dVXa9CgQdq4caMmT56shx9+WB988IGHe+6+c73GStu2bVNubq7j1aFDBw/1+NwUFRWpW7dumjNnjlvnW+0enuv1VbLK/Vu9erUmTJigNWvWKC0tTWVlZRo2bJiKiopM21jpHtbm+ipZ5R62adNGL774otatW6d169bpyiuv1PXXX6/Nmze7PN9K90869+urZJX7d6bMzEy9+eab6tq1a7XneeUeGnBL3759jfvvv9/pWOfOnY1nnnnG5flPPfWU0blzZ6dj48aNM/r3719vfTxf53qNq1atMiQZR44c8UDv6pYkY/HixdWeY8V7WMmd67Py/TMMwzhw4IAhyVi9erXpOVa+h+5cn9XvoWEYRvPmzY2//e1vLr9m5ftXqbrrs+r9O3bsmNGhQwcjLS3NGDx4sPHII4+YnuuNe8iIjRtKSkq0fv16DRs2zOn4sGHD9O2337psk5GRUeX84cOHa926dSotLa23vtZWba6xUo8ePRQTE6OrrrpKq1atqs9uepTV7mFtWfX+FRQUSJIiIiJMz7HyPXTn+ipZ8R6Wl5dr0aJFKioq0oABA1yeY+X75871VbLa/ZswYYKuueYa/fa3v63xXG/cQwobNxw6dEjl5eWKiopyOh4VFaW8vDyXbfLy8lyeX1ZWpkOHDtVbX2urNtcYExOjN998Ux988IE+/PBDderUSVdddZW++uorT3S53lntHp4rK98/wzD02GOP6bLLLlNiYqLpeVa9h+5enxXv4Y8//qjGjRvLbrfr/vvv1+LFi5WQkODyXCvev3O5Pivev0WLFmnDhg2aOXOmW+d74x42uN29z8fZ26QbhlHt1umuznd13JecyzV26tRJnTp1crwfMGCAcnJy9PLLL+vyyy+v1356ihXvobusfP8efPBB/fDDD/rmm29qPNeK99Dd67PiPezUqZOysrJ09OhRffDBBxo9erRWr15t+sffavfvXK7PavcvJydHjzzyiFauXKnQ0FC323n6HjJi44aWLVsqMDCwysjFgQMHqlSilaKjo12eHxQUpBYtWtRbX2urNtfoSv/+/bV9+/a67p5XWO0e1gUr3L+HHnpIS5Ys0apVq9SmTZtqz7XiPTyX63PF1+9hSEiILr74YvXu3VszZ85Ut27d9Oqrr7o814r371yuzxVfvn/r16/XgQMH1KtXLwUFBSkoKEirV6/Wa6+9pqCgIJWXl1dp4417SGHjhpCQEPXq1UtpaWlOx9PS0jRw4ECXbQYMGFDl/JUrV6p3794KDg6ut77WVm2u0ZWNGzcqJiamrrvnFVa7h3XBl++fYRh68MEH9eGHH+rLL79UfHx8jW2sdA9rc32u+PI9dMUwDBUXF7v8mpXun5nqrs8VX75/V111lX788UdlZWU5Xr1799Ydd9yhrKwsBQYGVmnjlXtYb8uS/cyiRYuM4OBg4+9//7uxZcsWY+LEicYFF1xg7Ny50zAMw3jmmWeMO++803H+L7/8YjRq1Mh49NFHjS1bthh///vfjeDgYOPf//63ty6hRud6jX/605+MxYsXGz///LOxadMm45lnnjEkGR988IG3LqFax44dMzZu3Ghs3LjRkGS88sorxsaNG41du3YZhmH9e3iu12e1+zd+/HgjPDzcSE9PN3Jzcx2vEydOOM6x8j2szfVZ7R5OmjTJ+Oqrr4zs7Gzjhx9+MCZPnmwEBAQYK1euNAzD2vfPMM79+qx2/1w5OxXlC/eQwuYcvP7660ZcXJwREhJi9OzZ0ymGOXr0aGPw4MFO56enpxs9evQwQkJCjAsvvNBITU31cI/P3blc46xZs4z27dsboaGhRvPmzY3LLrvM+PTTT73Qa/dURivPfo0ePdowDOvfw3O9PqvdP1fXJsmYN2+e4xwr38PaXJ/V7uHYsWMd/760atXKuOqqqxx/9A3D2vfPMM79+qx2/1w5u7DxhXtoM4z/ruIBAACwONbYAAAAv0FhAwAA/AaFDQAA8BsUNgAAwG9Q2AAAAL9BYQMAAPwGhQ0AAPAbFDYA/MKMGTPUuHFjx2vGjBne7hIAL+ABfQD8wuHDh3X48GHH+4iICEVERHixRwC8gcIGAAD4DaaiAFje8uXLFRYWprKyMsexrVu3ymaz6dChQ17sGQBPo7ABYHlZWVm65JJLFBQU5HSsdevWatmypRd7BsDTKGwAWN7333+v7t27Ox3buHGjunXr5p0OAfAaChsAlpeVlVWliHF1DID/o7ABYGknT57U9u3bnUZsKioqtGHDBgoboAGisAFgaTt27FB5ebk6derkOLZixQrl5+dT2AANEIUNAEtr0aKFbDab1q5dK0las2aNHnzwQYWFhalDhw5e7h0AT+M5NgAsb/r06frjH/+oxo0ba8iQIYqNjdUXX3yhzMxMb3cNgIdR2AAAAL/BVBQAAPAbFDYAAMBvUNgAAAC/QWEDAAD8BoUNAADwGxQ2AADAb1DYAAAAv0FhAwAA/AaFDQAA8BsUNgAAwG9Q2AAAAL9BYQMAAPwGhQ0AAPAb/x9G7rRjUSOxvwAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -179,14 +174,14 @@ "# Static data\n", "Vd = 24\n", "Uo = np.linspace(0, 4, 50)\n", - "Yo = (4-Uo)*Vd/3\n", + "Yo = (4 - Uo) * Vd / 3\n", "Uo = Uo.reshape(-1, 1)\n", "Yo = Yo.reshape(-1, 1)\n", "plt.figure(3)\n", - "plt.title('Buck Converter Static Curve')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{y}$')\n", - "plt.plot(Uo, Yo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.title(\"Buck Converter Static Curve\")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{y}$\")\n", + "plt.plot(Uo, Yo, linewidth=1.5, linestyle=\"-\", marker=\"o\")\n", "plt.show()" ] }, @@ -216,67 +211,27 @@ } }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, { "data": { - "image/png": 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", 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", 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" ] }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Defining the gain\n", - "gain = -8*np.ones(len(Uo)).reshape(-1, 1)\n", - "plt.figure(3)\n", - "plt.title('Buck Converter Static Gain')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{gain}$')\n", - "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] + "metadata": { + "needs_background": "light" }, - "metadata": {}, "output_type": "display_data" } ], "source": [ "# Defining the gain\n", - "gain = -8*np.ones(len(Uo)).reshape(-1, 1)\n", + "gain = -8 * np.ones(len(Uo)).reshape(-1, 1)\n", "plt.figure(3)\n", - "plt.title('Buck Converter Static Gain')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{gain}$')\n", - "plt.plot(Uo, Uo, linewidth=1.5, linestyle='-', marker='o')\n", + "plt.title(\"Buck Converter Static Gain\")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{gain}$\")\n", + "plt.plot(Uo, gain, linewidth=1.5, label=\"gain\", linestyle=\"-\", marker=\"o\")\n", "plt.legend()\n", "plt.show()" ] @@ -295,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.328953300Z", @@ -307,7 +262,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\55359\\OneDrive\\Área de Trabalho\\Clone_git\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", + "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\gabriel\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", " You'll have to use FROLS(estimator=LeastSquares()) instead. \n", " The only change is that you'll have to define the estimator first instead of passing a string like 'least_squares'. \n", " This change will make easier to implement new estimators and it'll improve code readability.\n", @@ -317,20 +272,19 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Informing test and validation data\n", - "x_train = data_int_train.reshape(-1, 1)\n", - "y_train = data_out_train.reshape(-1, 1)\n", - "x_valid = data_int_valid.reshape(-1, 1)\n", - "y_valid = data_out_valid.reshape(-1, 1)\n", + "x_train = df_train.input.values.reshape(-1, 1)\n", + "y_train = df_train.y.values.reshape(-1, 1)\n", + "x_valid = df_valid.input.values.reshape(-1, 1)\n", + "y_valid = df_valid.y.values.reshape(-1, 1)\n", "\n", "basis_function = Polynomial(degree=2)\n", "\n", @@ -338,10 +292,11 @@ " order_selection=True,\n", " n_info_values=8,\n", " extended_least_squares=False,\n", - " ylag=2, xlag=2,\n", - " info_criteria='aic',\n", - " estimator='least_squares',\n", - " basis_function=basis_function\n", + " ylag=2,\n", + " xlag=2,\n", + " info_criteria=\"aic\",\n", + " estimator=\"least_squares\",\n", + " basis_function=basis_function,\n", ")\n", "\n", "model.fit(X=x_train, y=y_train)" @@ -357,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.328953300Z", @@ -367,9 +322,13 @@ "outputs": [], "source": [ "# Matrix with the weights associated to each objective.\n", - "W = np.array([[0.98, 0.7, 0.5, 0.35, 0.25, 0.01, 0.15, 0.01],\n", - " [0.01, 0.1, 0.3, 0.15, 0.25, 0.98, 0.35, 0.01],\n", - " [0.01, 0.2, 0.2, 0.50, 0.50, 0.01, 0.50, 0.98]])" + "W = np.array(\n", + " [\n", + " [0.98, 0.7, 0.5, 0.35, 0.25, 0.01, 0.15, 0.01],\n", + " [0.01, 0.1, 0.3, 0.15, 0.25, 0.98, 0.35, 0.01],\n", + " [0.01, 0.2, 0.2, 0.50, 0.50, 0.01, 0.50, 0.98],\n", + " ]\n", + ")" ] }, { @@ -383,7 +342,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.328953300Z", @@ -393,8 +352,7 @@ "outputs": [], "source": [ "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", - "mult = IM(model_type=model.model_type,\n", - " final_model = model.final_model)" + "mult = AILS(final_model=model.final_model)" ] }, { @@ -407,7 +365,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.435488200Z", @@ -448,53 +406,53 @@ " \n", " \n", " 0\n", - " 0.990080\n", - " 0.003078\n", " 0.006842\n", - " 0.992584\n", - " 9.825995e-02\n", - " 0.305492\n", - " 0.261455\n", + " 0.003078\n", + " 0.990080\n", + " 0.999970\n", + " 1.095046e-05\n", + " 0.000013\n", + " 0.245244\n", " \n", " \n", " 1\n", - " 0.990080\n", - " 0.002347\n", " 0.007573\n", - " 0.991990\n", - " 1.551666e-01\n", - " 0.266591\n", - " 0.286111\n", + " 0.002347\n", + " 0.990080\n", + " 0.999938\n", + " 2.294674e-05\n", + " 0.000016\n", + " 0.245236\n", " \n", " \n", " 2\n", - " 0.990080\n", - " 0.001538\n", " 0.008382\n", - " 0.990885\n", - " 3.048969e-01\n", - " 0.220806\n", - " 0.382836\n", + " 0.001538\n", + " 0.990080\n", + " 0.999885\n", + " 6.504949e-05\n", + " 0.000018\n", + " 0.245223\n", " \n", " \n", " 3\n", - " 0.990080\n", - " 0.000642\n", " 0.009277\n", - " 0.988248\n", - " 1.000000e+00\n", - " 0.142808\n", - " 1.000000\n", + " 0.000642\n", + " 0.990080\n", + " 0.999717\n", + " 4.505604e-04\n", + " 0.000021\n", + " 0.245183\n", " \n", " \n", " 4\n", - " 0.894495\n", - " 0.098663\n", " 0.006842\n", - " 0.995100\n", - " 1.364999e-03\n", - " 0.660485\n", - " 0.244160\n", + " 0.098663\n", + " 0.894495\n", + " 1.000000\n", + " 7.393244e-08\n", + " 0.000015\n", + " 0.245252\n", " \n", " \n", " ...\n", @@ -508,53 +466,53 @@ " \n", " \n", " 2290\n", - " 0.006842\n", - " 0.333527\n", " 0.659632\n", - " 0.999976\n", - " 5.944270e-08\n", - " 0.000020\n", - " 0.245246\n", + " 0.333527\n", + " 0.006842\n", + " 0.995896\n", + " 3.965701e-04\n", + " 1.000000\n", + " 0.244489\n", " \n", " \n", " 2291\n", - " 0.006842\n", - " 0.263039\n", " 0.730119\n", - " 0.999985\n", - " 6.124624e-08\n", - " 0.000018\n", - " 0.245248\n", + " 0.263039\n", + " 0.006842\n", + " 0.995632\n", + " 5.602985e-04\n", + " 0.972842\n", + " 0.244412\n", " \n", " \n", " 2292\n", - " 0.006842\n", - " 0.185020\n", " 0.808139\n", - " 0.999993\n", - " 6.466930e-08\n", - " 0.000016\n", - " 0.245250\n", + " 0.185020\n", + " 0.006842\n", + " 0.995364\n", + " 8.321075e-04\n", + " 0.868299\n", + " 0.244300\n", " \n", " \n", " 2293\n", - " 0.006842\n", - " 0.098663\n", " 0.894495\n", - " 1.000000\n", - " 7.400899e-08\n", - " 0.000015\n", - " 0.245252\n", + " 0.098663\n", + " 0.006842\n", + " 0.995100\n", + " 1.365000e-03\n", + " 0.660485\n", + " 0.244160\n", " \n", " \n", " 2294\n", - " 0.006842\n", - " 0.003078\n", " 0.990080\n", - " 0.999971\n", - " 1.094929e-05\n", - " 0.000013\n", - " 0.245244\n", + " 0.003078\n", + " 0.006842\n", + " 0.992584\n", + " 9.825994e-02\n", + " 0.305492\n", + " 0.261455\n", " \n", " \n", "\n", @@ -563,39 +521,41 @@ ], "text/plain": [ " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", - "0 0.990080 0.003078 0.006842 0.992584 9.825995e-02 0.305492 0.261455\n", - "1 0.990080 0.002347 0.007573 0.991990 1.551666e-01 0.266591 0.286111\n", - "2 0.990080 0.001538 0.008382 0.990885 3.048969e-01 0.220806 0.382836\n", - "3 0.990080 0.000642 0.009277 0.988248 1.000000e+00 0.142808 1.000000\n", - "4 0.894495 0.098663 0.006842 0.995100 1.364999e-03 0.660485 0.244160\n", + "0 0.006842 0.003078 0.990080 0.999970 1.095046e-05 0.000013 0.245244\n", + "1 0.007573 0.002347 0.990080 0.999938 2.294674e-05 0.000016 0.245236\n", + "2 0.008382 0.001538 0.990080 0.999885 6.504949e-05 0.000018 0.245223\n", + "3 0.009277 0.000642 0.990080 0.999717 4.505604e-04 0.000021 0.245183\n", + "4 0.006842 0.098663 0.894495 1.000000 7.393244e-08 0.000015 0.245252\n", "... ... ... ... ... ... ... ...\n", - "2290 0.006842 0.333527 0.659632 0.999976 5.944270e-08 0.000020 0.245246\n", - "2291 0.006842 0.263039 0.730119 0.999985 6.124624e-08 0.000018 0.245248\n", - "2292 0.006842 0.185020 0.808139 0.999993 6.466930e-08 0.000016 0.245250\n", - "2293 0.006842 0.098663 0.894495 1.000000 7.400899e-08 0.000015 0.245252\n", - "2294 0.006842 0.003078 0.990080 0.999971 1.094929e-05 0.000013 0.245244\n", + "2290 0.659632 0.333527 0.006842 0.995896 3.965701e-04 1.000000 0.244489\n", + "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972842 0.244412\n", + "2292 0.808139 0.185020 0.006842 0.995364 8.321075e-04 0.868299 0.244300\n", + "2293 0.894495 0.098663 0.006842 0.995100 1.365000e-03 0.660485 0.244160\n", + "2294 0.990080 0.003078 0.006842 0.992584 9.825994e-02 0.305492 0.261455\n", "\n", "[2295 rows x 7 columns]" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Method to calculate the parameters\n", - "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(y_train=y_train[2:],\n", - " gain=gain,y_static=Yo,\n", - " x_static=Uo, psi=model.psi)\n", - "result = {'w1': w[0,:],\n", - " 'w2': w[2,:],\n", - " 'w3': w[1,:],\n", - " 'J_ls': J[0,:],\n", - " 'J_sg': J[1,:],\n", - " 'J_sf': J[2,:],\n", - " '||J||:': E}\n", - "pd.DataFrame(result)\n" + "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(\n", + " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=model.psi\n", + ")\n", + "result = {\n", + " \"w1\": w[0, :],\n", + " \"w2\": w[2, :],\n", + " \"w3\": w[1, :],\n", + " \"J_ls\": J[0, :],\n", + " \"J_sg\": J[1, :],\n", + " \"J_sf\": J[2, :],\n", + " \"||J||:\": E,\n", + "}\n", + "pd.DataFrame(result)" ] }, { @@ -608,7 +568,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.522223600Z", @@ -646,49 +606,49 @@ " \n", " 0\n", " y(k-1)\n", - " 2.3307E-01\n", + " 3.0979E-01\n", " 9.999E-01\n", " \n", " \n", " 1\n", " y(k-2)\n", - " 6.3209E-01\n", + " 6.4935E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", " x1(k-1)y(k-1)\n", - " 1.6667E-02\n", + " 2.1891E-04\n", " 1.108E-06\n", " \n", " \n", " 3\n", " 1\n", - " 2.2930E+00\n", + " 1.2835E+00\n", " 4.688E-06\n", " \n", " \n", " 4\n", " y(k-1)^2\n", - " 2.7673E-01\n", + " 2.8345E-01\n", " 3.922E-07\n", " \n", " \n", " 5\n", " x1(k-1)\n", - " -5.9333E-01\n", + " -3.2103E-01\n", " 8.389E-07\n", " \n", " \n", " 6\n", " y(k-2)y(k-1)\n", - " -5.3228E-01\n", + " -5.4834E-01\n", " 5.690E-07\n", " \n", " \n", " 7\n", " y(k-2)^2\n", - " 2.5766E-01\n", + " 2.6492E-01\n", " 3.827E-06\n", " \n", " \n", @@ -697,32 +657,37 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 2.3307E-01 9.999E-01\n", - "1 y(k-2) 6.3209E-01 2.042E-05\n", - "2 x1(k-1)y(k-1) 1.6667E-02 1.108E-06\n", - "3 1 2.2930E+00 4.688E-06\n", - "4 y(k-1)^2 2.7673E-01 3.922E-07\n", - "5 x1(k-1) -5.9333E-01 8.389E-07\n", - "6 y(k-2)y(k-1) -5.3228E-01 5.690E-07\n", - "7 y(k-2)^2 2.5766E-01 3.827E-06" + "0 y(k-1) 3.0979E-01 9.999E-01\n", + "1 y(k-2) 6.4935E-01 2.042E-05\n", + "2 x1(k-1)y(k-1) 2.1891E-04 1.108E-06\n", + "3 1 1.2835E+00 4.688E-06\n", + "4 y(k-1)^2 2.8345E-01 3.922E-07\n", + "5 x1(k-1) -3.2103E-01 8.389E-07\n", + "6 y(k-2)y(k-1) -5.4834E-01 5.690E-07\n", + "7 y(k-2)^2 2.6492E-01 3.827E-06" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Writing the results\n", - "model.theta = Theta[0, :].reshape(-1,1)\n", + "model.theta = Theta[0, :].reshape(-1, 1)\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", " results(\n", - " model.final_model, model.theta, model.err,\n", - " model.n_terms, err_precision=3, dtype='sci'\n", - " ),\n", - " columns=['Regressors', 'Parameters', 'ERR'])\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", "r" ] }, @@ -736,7 +701,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.667179100Z", @@ -746,9 +711,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" + "
" ] }, "metadata": {}, @@ -769,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.793210700Z", @@ -779,9 +744,9 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -790,12 +755,26 @@ ], "source": [ "plt.figure(4)\n", - "plt.title('Gain')\n", - "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", - "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{g}$')\n", - "plt.ylim(-16,0)\n", + "plt.title(\"Gain\")\n", + "plt.plot(\n", + " Uo,\n", + " gain,\n", + " linewidth=1.5,\n", + " linestyle=\"-\",\n", + " marker=\"o\",\n", + " label=\"Buck converter static gain\",\n", + ")\n", + "plt.plot(\n", + " Uo,\n", + " HR.dot(model.theta),\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + " linewidth=1.5,\n", + " label=\"NARX model gain\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{g}$\")\n", + "plt.ylim(-16, 0)\n", "plt.legend()\n", "plt.show()" ] @@ -810,7 +789,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.902396Z", @@ -820,9 +799,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -831,11 +810,18 @@ ], "source": [ "plt.figure(5)\n", - "plt.title('Static Curve')\n", - "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", - "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.xlabel('$\\\\bar{y}$')\n", + "plt.title(\"Static Curve\")\n", + "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", + "plt.plot(\n", + " Uo,\n", + " QR.dot(model.theta),\n", + " linewidth=1.5,\n", + " label=\"NARX ​​static representation\",\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.xlabel(\"$\\\\bar{y}$\")\n", "plt.legend()\n", "plt.show()" ] @@ -850,7 +836,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.014411600Z", @@ -860,9 +846,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -871,12 +857,12 @@ ], "source": [ "plt.figure(6)\n", - "ax = plt.axes(projection='3d')\n", - "ax.plot3D( J[0,:], J[1,:], J[2,:], 'o', linewidth=0.1)\n", - "ax.set_title('Optimum pareto-curve', fontsize=15)\n", - "ax.set_xlabel('$J_{ls}$', fontsize=10)\n", - "ax.set_ylabel('$J_{sg}$', fontsize=10)\n", - "ax.set_zlabel('$J_{sf}$', fontsize=10)\n", + "ax = plt.axes(projection=\"3d\")\n", + "ax.plot3D(J[0, :], J[1, :], J[2, :], \"o\", linewidth=0.1)\n", + "ax.set_title(\"Optimum pareto-curve\", fontsize=15)\n", + "ax.set_xlabel(\"$J_{ls}$\", fontsize=10)\n", + "ax.set_ylabel(\"$J_{sg}$\", fontsize=10)\n", + "ax.set_zlabel(\"$J_{sf}$\", fontsize=10)\n", "plt.show()" ] }, @@ -945,7 +931,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.017591800Z", @@ -967,10 +953,13 @@ } ], "source": [ - "from sysidentpy.narmax_base import RegressorDictionary # Importing the class.\n", - "object_qit = RegressorDictionary(xlag=[1], ylag=[1]) # The lag of the input and output equal to 1 ensures that there will be no repetition of terms in qit.\n", - "R_example = object_qit.regressor_space(n_inputs=1)//1000 \n", - "print(f'R = {R_example}')" + "from sysidentpy.narmax_base import RegressorDictionary # Importing the class.\n", + "\n", + "object_qit = RegressorDictionary(\n", + " xlag=[1], ylag=[1]\n", + ") # The lag of the input and output equal to 1 ensures that there will be no repetition of terms in qit.\n", + "R_example = object_qit.regressor_space(n_inputs=1) // 1000\n", + "print(f\"R = {R_example}\")" ] }, { @@ -995,7 +984,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.021969800Z", @@ -1008,11 +997,11 @@ "output_type": "stream", "text": [ "R matrix:\n", - "[[0. 0. 0. 1. 0. 0. 0. 0.]\n", - " [1. 1. 0. 0. 0. 0. 0. 0.]\n", - " [0. 0. 0. 0. 0. 1. 0. 0.]\n", - " [0. 0. 0. 0. 1. 0. 1. 1.]\n", - " [0. 0. 1. 0. 0. 0. 0. 0.]]\n", + "[[0 0 0 1 0 0 0 0]\n", + " [1 1 0 0 0 0 0 0]\n", + " [0 0 0 0 0 1 0 0]\n", + " [0 0 0 0 1 0 1 1]\n", + " [0 0 1 0 0 0 0 0]]\n", "qit matrix:\n", "[[0. 0.]\n", " [1. 0.]\n", @@ -1023,10 +1012,10 @@ } ], "source": [ - "R, qit = mult.R_qit()\n", - "print('R matrix:')\n", + "R, qit = mult.build_linear_mapping()\n", + "print(\"R matrix:\")\n", "print(R)\n", - "print('qit matrix:')\n", + "print(\"qit matrix:\")\n", "print(qit)" ] }, @@ -1123,7 +1112,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.026952500Z", @@ -1144,26 +1133,30 @@ " [2002, 2002]])" ] }, - "execution_count": 18, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model_final = np.array([[1001, 0],\n", - " [1002, 0],\n", - " [0, 0],\n", - " [2001, 0],\n", - " [2001, 2001],\n", - " [2002, 2001],\n", - " [2002, 0],\n", - " [2002, 2002]])\n", + "model_final = np.array(\n", + " [\n", + " [1001, 0],\n", + " [1002, 0],\n", + " [0, 0],\n", + " [2001, 0],\n", + " [2001, 2001],\n", + " [2002, 2001],\n", + " [2002, 0],\n", + " [2002, 2002],\n", + " ]\n", + ")\n", "model_final" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.031862500Z", @@ -1173,13 +1166,12 @@ "outputs": [], "source": [ "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", - "mult2 = IM(model_type='NARMAX',\n", - " final_model = model_final)" + "mult2 = AILS(final_model=model_final)" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.101857500Z", @@ -1191,14 +1183,14 @@ "def psi(X, Y):\n", " PSI = np.zeros((len(X), 8))\n", " for k in range(2, len(Y)):\n", - " PSI[k, 0] = Y[k-1]\n", - " PSI[k, 1] = Y[k-2]\n", + " PSI[k, 0] = Y[k - 1]\n", + " PSI[k, 1] = Y[k - 2]\n", " PSI[k, 2] = 1\n", - " PSI[k, 3] = X[k-1]\n", - " PSI[k, 4] = X[k-1]**2\n", - " PSI[k, 5] = X[k-2]*X[k-1]\n", - " PSI[k, 6] = X[k-2]\n", - " PSI[k, 7] = X[k-2]**2\n", + " PSI[k, 3] = X[k - 1]\n", + " PSI[k, 4] = X[k - 1] ** 2\n", + " PSI[k, 5] = X[k - 2] * X[k - 1]\n", + " PSI[k, 6] = X[k - 2]\n", + " PSI[k, 7] = X[k - 2] ** 2\n", " return np.delete(PSI, [0, 1], axis=0)" ] }, @@ -1228,7 +1220,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.101857500Z", @@ -1238,12 +1230,12 @@ "outputs": [], "source": [ "PSI = psi(x_train, y_train)\n", - "W = np.array([[0.3612343],[0.2838959],[0.3548699]])" + "W = np.array([[0.3612343], [0.2838959], [0.3548699]])" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.122382900Z", @@ -1301,22 +1293,24 @@ "0 0.361234 0.35487 0.283896 1.0 1.0 1.0 1.0" ] }, - "execution_count": 22, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "J, w, E, Theta, HR, QR, position = mult2.affine_information_least_squares(y_train=y_train[2:],\n", - " gain=gain,y_static=Yo,\n", - " x_static=Uo, psi=PSI, W=W)\n", - "result = {'w1': w[0,:],\n", - " 'w2': w[2,:],\n", - " 'w3': w[1,:],\n", - " 'J_ls': J[0,:],\n", - " 'J_sg': J[1,:],\n", - " 'J_sf': J[2,:],\n", - " '||J||:': E}\n", + "J, w, E, Theta, HR, QR, position = mult2.affine_information_least_squares(\n", + " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + ")\n", + "result = {\n", + " \"w1\": w[0, :],\n", + " \"w2\": w[2, :],\n", + " \"w3\": w[1, :],\n", + " \"J_ls\": J[0, :],\n", + " \"J_sg\": J[1, :],\n", + " \"J_sf\": J[2, :],\n", + " \"||J||:\": E,\n", + "}\n", "pd.DataFrame(result)" ] }, @@ -1330,7 +1324,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.123384200Z", @@ -1429,29 +1423,34 @@ "7 x1(k-2)^2 3.0846E+00 3.827E-06" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.theta = Theta[position, :].reshape(-1, 1)\n", "model.final_model = model_final\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", " results(\n", - " model.final_model, model.theta, model.err,\n", - " model.n_terms, err_precision=3, dtype='sci'\n", - " ),\n", - " columns=['Regressors', 'Parameters', 'ERR'])\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", "r" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.276007600Z", @@ -1461,9 +1460,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" + "
" ] }, "metadata": {}, @@ -1484,7 +1483,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.383278600Z", @@ -1494,9 +1493,9 @@ "outputs": [ { "data": { - "image/png": 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Gr37+Soeqt73YSFJGRoYWL16sCxcuqG7dupKk0NBQbdiwQampqTpz5ow+/fRTZ/6+++5TRkaGZsyYIZvNpiNHjuj1119XWlqaM+Pn56eePXuqcuXKevHFF7M8bpcuXbRw4ULt3r1bDodDixcv1vz581W0aFF169ZNs2bN0p49e2S327VmzRpt3LhRnTt3ztE5BQUFqVmzZs4nwhYuXFiS1KxZM6WkpOijjz6SzWbThQsXNHLkSA0bNizbQuLv76/k5GSZpqmQkBDdd999mjBhgs6dO6f09HRFR0era9euunDhwg3n8vLy0muvvaYpU6YoLS1NQUFB8vf3V9GiRTMdKyUlRXa7Xfny5ZN0pUBNnz5dkpxPgPbz89PFixczHScna3RVt27d9M0332jTpk2y2+369ttvXQrUxYsXFRAQIG9vbyUmJuq1116TJJfy606UGwDIQ/5VvaSiH62jEoUDXLaXKByg6Efr6F/VS962Yz/55JMKDw9XeHi46tevr/nz52vy5MnO20LDhw9XSkqKGjVqpF69erm81LdQoUKaPXu2YmNj1bhxY0VFRemhhx5Sjx49XI5hGIZef/11bd++XV988UWmGTp06KBBgwZpxIgRioiI0MKFC/Xhhx8qKChIffr0Uc+ePTVs2DBFRERo5syZmjx5surXr5/jc+zevbuOHz+url27OrcVKFBAH3/8sbZs2aJ7771XLVu2lJeXl6Kjo7N9nGbNmun8+fOqW7euLly4oLfeekuFChVSp06d1KBBA3377bf66KOPXK7kXM+UKVMUFxenxo0b65577tHFixc1fvz4TMcqVqyYnn/+eY0YMUJ169bVkCFD9OCDD8rX11e//vqrpCvPO3r33Xc1fPhwl2PkdI0kqUaNGs4nZNerV0/z589Xw4YN5evrK0l64403tHr1atWpU0ddunRRSEiIqlat6pzB3Qzz775e0AO1aNFCkrRhwwY3TwIAWbM7TG09lKjTF1NVvGCA6pcPypUrNoAkHTp0SA6HQ6Ghoc5tgwYNUoUKFTRs2DA3TpYzXLkBgDzI28tQw9A71LF2aTUMvYNig1x18OBB9e7dW0eOHJF05Xcabdq0SU2bNnXzZDnDE4oBAICLVq1a6eDBg+rVq5eSkpJUunRpjR8/3nmLMq/jthQAALAUbksBAABLodwAAABLodwAAABLodwAAABLodwAAABLodwAAABLodwAQF4VFyO9X//KP2+zKlWq6Kmnnsr07tJLlixxvkHjtebPn68qVaro448/zrRv1KhRqlatmvOtHMLDw1WrVi21b99eK1eulHTlzSKfeuopde7cWampqS5fP27cOHXo0EEpKSm37gRzKCoqStOmTctRtnnz5lqyZMktn2HFihVq167dLX/cfxLKDQDkRaYpbXhVOrv/yj9z4VeSXX0/pJyYP3++Hn74YX366afKyMjItL9Dhw7asWOH82PLli26//77NWLECB06dEheXl56++23dfHiRY0dO9blcVevXq3o6Gjlz5//Vp2aR3nggQe0atUqd4/h0Sg3AHC7maZkS7m5j/2rpRM7rnz9iR1XPr+Zr/8LZSgqKkpTp07VTz/9dN1cbGysEhISNGrUKDkcDq1bt+6Gjx0QEKC+ffvK4XBo//79kqTChQvr/fff15o1a7RgwQLFxsbqrbfe0rRp01SmTJksH2fUqFEaN26c+vXrp/DwcLVq1UqxsbEaP3686tWrp0aNGumrr75y5vfv368nn3xS9evX17333quxY8e6vGP2V199pRYtWig8PFwjR47U5cuXnftM09Snn36q+++/XxEREXrkkUf0888/3/BcJencuXMaNmyY6tatqxYtWmjevHmqWrWqjh07JknauHGjHnroITVs2FC1atXSo48+qt9//12S69WyLVu2qHnz5oqOjlaTJk1Uv359DRo0SMnJyTma45+Kt18AgNvJNKU590tHt/y9x/nikZvLl20g9V0rGTl/T6pWrVrJNE09++yzWrZsmYoUKZJlbt68eerevbsCAgL0yCOPaM6cOTe8jZKcnKwZM2aoYMGCLr/CPywsTOPGjdPLL7+s/Pnza/To0apXr951H2vx4sWaPXu2oqOjNWLECD3++ON64YUXFBsbq88//1zjxo1Tx44dlZKSol69eqlLly6aNm2aLl68qOHDh+v5559XdHS0YmNjNW7cOM2aNUv16tXTl19+qWXLljnfP+nzzz/X3LlzFR0drdDQUC1fvlx9+vTRmjVrVKxYsevOOHz4cBmGoQ0bNsjhcGj48OGy2+2SpFOnTmnIkCGaOnWqmjdvrnPnzumZZ57R9OnT9fbbb2d6rOPHjys+Pl7ffPON4uPj1bNnT33++ed66qmnrjvDPxlXbgDgtvOcN70cOXKkgoKCNGrUqEzPv5Gu/KDdtGmTevbsKUnq3r27Dh48qK1bt7rkVq5cqYiICIWHh6t69epq3ry5Tp06pQULFqh48eIu2ZYtW6pQoUJKT09Xy5YtbzhjgwYNFBERIS8vLzVo0ECBgYGKioqSj4+PmjVrJpvNprNnz2rDhg3y9fXV8OHDFRAQoODgYL388svauHGjzpw5oxUrVqh169Zq2LChfHx89Mgjj6hq1arO48yfP1/9+vVTWFiYfH191bVrV4WGhmrFihXXnS8+Pl7ff/+9Ro8erSJFiigoKEijR4927g8KCtKqVavUvHlzJScn69SpUypatKji4+OzfcyBAwcqICBAd955pyIjI3Xo0KEb/j39k3HlBgBuJ8O4cgUl/VLO8qYpfdxWOvWzZNqveRxvqUR16bHVObsa4xt4U1dtrvLz89OUKVPUuXNnzZkzR0WLFnXZ//nnnysjI0MdO3Z0bsvIyNCcOXNUv35957b27dtr4sSJkq48l2fEiBGqXLmyKlWq9KfTNfX888/rrrvukt1u19ChQzV37lz5+GT/4+naK0re3t4qVKiQ83Pjj3N2OBxKSEhQqVKl5O3t7dx/9XbX1ash1apVc3nssmXLOv98/Phxvfnmm3rnnXdczrV69erZziZJJ0+edDnWnx/X19dXK1eu1BdffCHDMFS5cmUlJydf95yDg4Ndvv4f+LaQN4VyAwC3m2FIfjl8cuzBf0snd2XebtqvbD/6o1Txxlc3/o5y5cpp/Pjxev7559WlSxfn9rS0NC1atEgTJkzQPffc49z+66+/6qmnnlJcXJxCQ0MzPV7Tpk319ttvq3///goKClLXrl2d+6ZMmaJdu3Zp8eLFkqTOnTvrzTff1IsvvpjtfEYOS1vp0qV14sQJ2e12Z8E5cuSIpCtloUSJEjp69KjL15w6dcpZwEqUKKHBgwe73HI7cuRItrfrripVqpSkK+WofPnyzj9ftWbNGn322WdasGCB7rzzTknS+PHj9euvv+bovHBj3JYCgLzCNKWNryn7/zR7XdmfC//X3rZtWz344INauHChc9vXX38twzDUoUMHlShRwvlx7733qnLlylm+LPyqpk2bqm/fvho/frzi4uIkSatXr9bs2bM1depUhYSEKCQkRJMmTdL8+fNveOsnJ64+d+add95Ramqqzpw5owkTJqhBgwYqXbq0HnzwQf373/9WTEyMMjIytHTpUu3a9f/Fsnv37oqOjnbOu2nTJrVr107btm277nGLFy+uZs2a6e2331ZSUpKSkpL01ltvOfdfvHhRXl5eCggIkGma+u6777Rs2TKlp6f/7XPGFZQbAMgr7DYp6bgkRzYBh3Th+JVcLhg9erTuvvtu5+eff/65OnToIF9f30zZHj16aPny5UpISMj28YYOHarQ0FANHz5cu3bt0ujRozV69GjVrVvXmWnYsKGGDh2ql19+Wb/88svfmr9gwYKaO3eufv31VzVt2lTt27dX6dKlNXXqVElS3bp19dZbb2nixImKiIjQunXr1KhRI+fXP/bYY+rUqZMGDBig8PBwTZgwQWPGjFGLFi1ueOwJEybIMAzdd9996ty5s/O5PL6+vurcubPuuecetWvXTg0aNFB0dLR69+6tQ4cOyWbLnbW1OsO0yI27Y8eOaeLEidq+fbtM01TdunX1wgsvuNznvOrqN+aGDRtye0wAuL6kY1LK2ez35w+WCpfOvXnwl/zwww+qW7euAgICJF15SXqnTp20c+dO+fv7u3k667PMlZuBAweqcOHC2rhxozZu3KgiRYpowIAB7h4LAG5O4TJSqdrZf1BsPMKbb76p6OhoZWRkKDk5WdHR0brnnnsoNrnEEuUmKSlJxYoV05AhQxQYGKj8+fOrV69e+vXXX5WUlOTu8QAA/zCTJk3Szp071aBBAzVv3lze3t4uz7vB7eUxr5ZKTU3N9ncABAcHa/bs2S7b1q1bp9KlS6tw4cK5MR4AAE6VKlXSJ5984u4x/rE8ptzs2rVLvXr1ynLf9OnTXX7x04IFCzRnzhxFR0fn1ngAACCP8JhyExkZ6Xw/kuzYbDa98cYbWr16tWbOnKkGDRrk0nQAACCv8JhycyOJiYl6+umnZbPZtGjRoixfJQUAAKzPEk8oTk9P1xNPPKECBQpowYIFFBsAAP7BLHHlJiYmRnv27JG/v78aNmzosm/VqlXOX4UNAACszxLlpnXr1jd8Pg4AAPhnsMRtKQAAgKsoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIoNwAAwFIsWW5GjBihqKgod48BAADcwHLlZtGiRVq5cqW7xwAAAG5iqXJz8OBBffDBB+rWrZu7RwEAAG7i4+4Bcio1NVXx8fFZ7gsODpaXl5eGDRumV155Rbt379ahQ4dyeUIAAJAXeEy52bVrl3r16pXlvunTp2vjxo1q1KiRmjZtqt27d+fydAAAIK/wmHITGRmp/fv3Z7lvxYoV2rdvn7744otcngoAAOQ1HlNurmf58uU6dOiQ7rnnHklSWlqa7Ha7IiIitGLFCpUqVcrNEwIAgNxiiXIze/Zsl8+nTZumrVu3at68eW6aCAAAuIulXi0FAABgiSs3fzZo0CB3jwAAANyEKzcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSKDcAAMBSLFNu0tLS9Nprr6lRo0aqW7euevfurbi4OHePBQAAcpllys3YsWO1Z88eLV26VLGxsQoNDdWQIUPcPRYAAMhlPu4e4FZISEjQ8uXLtXr1ahUvXlySNHz4cB06dEimacowDDdPCAAAcovHlJvU1FTFx8dnue/QoUMqWLCgdu7cqYEDByoxMVF169bV6NGjKTYAAPzDeEy52bVrl3r16pXlvrffflsXL17U+vXrNW/ePPn6+mrcuHHq37+/li5dKm9v71yeFgAAuIvHlJvIyEjt378/y31r166V3W7XyJEjFRQUJEl64YUX1LBhQx06dEgVK1bMzVEBAIAbWeIJxVfLi81mc26z2+2SJNM03TITAABwD8uUm3r16mnMmDFKTExUSkqKJk6cqGrVqqlSpUruHg8AAOQiS5QbSYqOjlalSpXUqVMnNWnSRJcuXdIHH3zg7rEAAEAuM8x/4H2bFi1aSJI2bNjg5kkAAMCtZpkrNwAAABLlBgAAWAzlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWArlBgAAWIqPuwewCrvD1NZDiTp9MVXFCwaofvkgeXsZfymX1zJ5cSbmznuZvDgTc+e9DDMxd274S+Vm//79Cg0NlY9P3ulGR48e1bhx47Rr1y55e3urSZMmeumll1SoUKHbfuy1P5/Uq1/vVYWL2zTW51ONzeil3wrW0ysdqupf1UveVC6vZfLiTMyd9zJ5cSbmznsZZnLf3CeTUp1fV7JwgNsyucUwTdO82S8KCwuTr6+vKlasqLCwMOfH3XffnStlIivdunVTRESEnn32WaWkpOiZZ55RuXLl9Prrr2fKtmjRQpK0YcOGv33ctT+f1NOf/SRTppb7vaxaXr9pl6OCOtnGSzIU/Wgd/at6yRzlJOWpDHMzN3Mzt5Xnzosz3Z65pUZe/3MWoM2OGpKU65ncLDg5vvQya9YsPfTQQypUqJA+//xzDR48WGXKlJHNZtPSpUu1b98+GYahcuXKqU2bNurbt2+uFp24uDjVrVtXpmnKNE0ZhqF8+fLd1mPaHaZe/XqvTEn3eu1WLa/fJEm1vH7TI17/1k9mFX227JTuKVBHny77SZUNm+oYv7rkHvLaqO1mFX287LRkSBWMdEUY+10y3b1itN0M0+xlZ2Uahu4ybIow9rlkHvT6VtvMuzVr2QaZhlTGsKnenzKdvTZpq3m3opfFSIZUSjbV93LNdPT6QVscd2v68u/UMDhS7y/fouKyKdLrF5dce6/N+tFRTVOXfS8Z0h1KVwOvvS6Zdl4/KtZRTe8u2yzTMFREaZky//Laqs2Oanpn2RaZhqGCSlNDrz0umVZe2xTrqK43l22XDClQabrnT5kWXv/VD44aemP5DjUom0+vL/9JfrKpsdf/XHLNvHboe0dNjV+2UzIkb2WoyZ/WrqnXTm1y1NKry3bLNAxJDt37p8dp4rVbmxy19MryPZKhLL8HbiYzdsVeNahwh15ZsedvP1ZuZpibuT117rw40+2aWzL1vM9CVfI6rud9FqqjrboMGbmaefXrvWpVtUSu3aLK8ZWbOnXqaPny5Spbtqw6d+6sgQMHqmXLls79W7du1UsvvaQuXbrohx9+0PHjx7Vo0SIFBQXdkkFTU1MVHx+f5b7g4GAtXLhQkyZNksPhkN1uV+3atfXxxx9nWXBu1ZWb2LgEPfzhj9IfzbmGcUhexk1fCIOHc5iGJFNX/5U1DOnqv1V2GTKdz9s35S2HjGsypqR0+Uh/fPXV/zj4/fGVV3MOGUqVr0sun2zy+lMmRf5/ZK7MFKhUeV+TsctLF5VPkuE8ViFdvjLXH5kMeSlJ+a85I1NFdEk+sl+T8VaiClwzz5XjBemifK/JpctbZ1TYZe7iOp8pE28WdZkpxDgvP2U4Mzb56IQZ9EfmyrFKGYnyV7ozkyZfHTfvcPn7LmOczZQ5bBbPNPedRrwCrsmlyk+HzBLX5EyVN04pn2zOzGX5Kc4s6TJTReNEpsyvZhmXTGXjmAKV5sxckr/2mWVd5g4zjij/NZkU+WuPeZdznqu5asZh5VfqNbkA7XaUd/n7run1mwpck0lWgHY6Ql1mqu0Vp4K67MxcVD795KjksiZ1vQ6ogC7Ly5AcppSsfNrmqOLyfVLP61cV1CVn5qICtcURlunvO9LrFxW6JndBgdrsqOby993Ia68KKeWaTH5976juMlNjr59V+JpMkvLrW0dNl3O7z2u3CivZmTmvAopx1NK1r6cxJTX32qEiLrmC+rc93OWxWnr/pKK66MycU0Gts9d1WZf7vbe7ZBJVUGvt9Vwep433NgXpwjWZQlppj3TJtPf+UXdck0lQIX1tb3jN98mVv6eO3rG6Q0nO3FkV1jJ7o2v+nqTSxhm1997q/LqV9kgdNYtf8ziGyhqn1cH7R+e2FfYGOmKGXLNuUlkjXp28Y52ZpfZ7dMQs4fw7lKQ7jXh19v7BmellG6nvHLUkSQuebKCGoXcoN+S43ISHh2vFihUqW7asatWqpWXLlql8+fIumZiYGC1dulRTp07VkCFDVKhQIb322mu3ZNAtW7aoV69eWe6bPn26jh07ppSUFPXp00fnzp3Ts88+q3Llyuntt9/OlL9V5Wb5zuMa8sVO3eu1S5/6vZlp/3kzv2zydX6L+SpdRYxLmXIXzHzKkPcfmQwVNFIzZVJMf2XIW4Ykb9mV30jLlLlk+snxxze+j+wKMNIzZdJMH2fGW3b5GfZMGZvpJVNezrm9ZMrHcGTK2U3J+OObnlIHALiW3TT0s1leHf+4VTb1odrqWLt0rhz7L70UvEaNGlqxYkWm7RUrVtT3338vwzD0xBNPaPPmzX97wKsiIyO1f//+LD9KlCihqVOnql+/fgoMDFTp0qX1/PPP6+uvv1ZycvItm+HPihcMkGTqOZ+vlGG6/lVmmF46bIaoftp0LWq2UfXSPtBhs0SWuUNmSdVJm6k6aTP1m1kqy8xBs7RqpX2ommkf6qBZOsvMAbOMqqfNVvW02dpvls0ys88sp7vT5urutLn6xbwzy8wv5l2qkvaJZjfbqsppn2qPeVeWuZ/NCqqQ9pkqpH2mXY4KWWZ2OSrortTPVD51nnY5ymeTKa+KqZ+oYuon2p1NZrejvKqkzlWV1Ll/ZIw/ZQz9z3GX7k6drQ8bb1LV1Nn6n+OuLHM/O+5SzdRZqpk6Sz877syUsZuGfnbcqdqpMxSeGq2fHXfKnkVmj+NORaR+oIjUD7Qn20w51U99X/VT39deR7ksM3sd5dQw9T3Na7BS96RO1V5H2SxzvzjKqknaZDVJm6xfssnsc5TVfWnvqFnaO9qXbaaMWqS9pRZpb2mfo0yWmf2OMmqdNlGt0yZqf7aZ0mqT9rq+rPu52qZN0K+O0lnmfnWUVoe08eqQNj7bzAFHKXVKe1Wd08bqgKNUtpkH08bowbQxOphN5qCjpLqnvaTuaS/poKNklpk4R0k9bButFbWi9bBttOKuk4uyjVSUbaR+c5TIMvObo4Qes43QY7YR18mE6HHbs3rc9qwOOUKyzBxyhOgp21A9ZRuq37PJ/O4IUX/bEK2r+qaetg3W747iWeYOO4prkG2gBtkG6nC2mWANsT2tIbandcQR/MfVx//nMA0dcQTrOVs/PWfrd93MiPQnNSL9SR11FMsyc9RRTKPSH9d/Kr+oF9L76lg2uWOOO/RS+mN6Kf0xHXPckWXmuOMOvZLeS6+k99Lx62TGp/fU+PSeOu4IyjJzwhGkCekPa3OFIXo9/SGduE7uzfQeejO9h046imaZOekoqnfSu+qd9K46lU3mlKOo3k3vonfTu+iUWSTrjFlE72V01HsZHf/I6E8ZKd4soukZHfRTuT76IKOD4rPJnTYLa0ZGO83IaK9V9vrKyhp7PX2U0UYfZbTRWntElpl19rqam3G/5mbc/8cVqsy+sYfr04xW+jSj1R9Xuv6ft2Gqltdvutdrt6SrPzNzR46fc9O/f38VLlxYkvTKK6+oR48eOnLkiAYMGKDQ0FDZbDZ98sknKlKkiCSpaNGiSkhIuC1D/9nJkydlt9vlcPz/1QVfX18ZhiFvb+/bdtz65YPUqeA+1Ur/LdM+H8OhWsZv6lRwnx5v3Fb7f1h23VzHAr9IMlQrI29kbu3c+/7IHMomc0jtChyQZKhmNpmaxiH9q0DcdTKmahi/6/6Cv6v3fV20Z8t61Uj/PctcdeN3NStwRJKh6hmHM2W8DVPVjcNqWuDYdTPVjMNqVOCEJEPVss0cUcMCpyQZqppxJMtMVeOIIgueUY+WUfrvf7eoavrRLHN3G0dVJ3+iJEN3Z2SdCTOOqlb+85IMhWWbOabq+S/8kTmWZaaKcUx350+WZKhKtpnjqlLgsjq1aaPNuyercvrxLHOVjeOqkD9NkqHKGVlnKhkndGf+dEmGKmWcyDZTJr9DkqGK2WQqGidVMr/+yJzMMhNqnFRIfm/9q8ND2rh3skLTs88FBV65FVgh41SWmQrGKRUO9L9BJl4FAgMlGSqfkfnWurdhqrwRr3yBV27z3ZVN5i4jXgH5C6lZl6e05sBk3ZV+OsvcncZpeQVeuc13Z0Z2mTNS4B2SDJXLOJMp42WYKmecUUZg8A0zNr8QSYbKZpzNMlPWOKtU/1K6p/uzWvbmZJVJzzpXxkjQRb8rt/DKZGT+2eFlmCptJOi8XzlJhkpfJ3PWr/wfmcQsM6WMRJ3xr6iIR57Vl29OVqn0L7LNnfC7cnuuZMbCLDMljXM66nfl1luJjEVZZkoY5/S7X9U/Mkuyzui84gJq/JFZnkVGCtF5HchXW0/2elafvjlZIelfZ5krriT9EhCuLUa4ZqaNUIbp5XL1PcP0UikjQa8GjJRkZJspYZzTKwEvXDdT3EjSywEvXjfznM9XOhBQX/XL35qnqeTEX3q1lCQdOHBA48aN07Zt2+Tn5ye73S5vb2+98cYbateundavX6+3335b33zzza2eOZPExES1adNGbdq00QsvvKDk5GQ9++yzKly4sN57771M+Vv2ainT1Pn3GqtQ4p4sb8s4TEMXgqqpyKBNOj+tyfVzRatKhpF3MszN3MzN3FaeOy/OdCvnDqqmg1WHKOKHJzPtv2p74w8lSRHf504momX3bPffan/5F9VUqlRJ8+bN0/Hjx7Vv3z55e3urWrVqCg4OliQFBQXpueeeu2WDXk9QUJBmz56td955R02aNJG/v7+aN2+uESNG3N4D220qYjstZfN8Ey/DVJH005ItOWc5KW9lmJu5mZu5rTx3XpzpVs1ti1fEb9NlyrjmqcX/z5ShiLjpkmHkTua3DySzm2TksVdLWcmt/D03SjompZyV3TS15/gFJV6yKSjQT9VKF5K3YUj5g6XCpXOWk5m3MszN3MzN3FaeOy/OdKvm9i8szWktpWS+NemU/8rFCKVkvu14yzMFiktDf5Z8/LPP3EKUGwAArOiPApSta8pUrmQK584rpSTeWwoAAGsqXObKR05yuZXJJbwrOAAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBTKDQAAsBSPKzeXL19Wjx49tGTJEpfthw4dUu/evRUeHq7GjRtrxowZbpoQAAC4k0eVmwMHDqhnz57auXOny/b09HT1799fNWrU0JYtWzRr1izNnz9fa9ascc+gAADAbTym3MTGxqp3797q3LmzSpUq5bJv27ZtOn36tAYPHiw/Pz9VrVpVUVFRmj9/vpumBQAA7uLj7gGuSk1NVXx8fJb7goODFRYWppiYGPn7+2vu3Lku+w8cOKDy5cvLz8/Pua1ixYqaNWvWbZ0ZAADkPXmm3OzatUu9evXKct/06dPVsmXLbL82JSVF+fLlc9mWL18+Xbp06ZbOCAAA8r48U24iIyO1f//+v/S1gYGBunz5ssu2y5cvK3/+/LdiNAAA4EE85jk311OpUiX9/vvvysjIcG47ePCgKlWq5MapAACAO1ii3ERGRqpo0aKaNGmS0tLStG/fPs2bN09du3Z192gAACCX5ZnbUn+Hj4+P5syZo3HjxqlRo0YKDAxUVFSUunTp4u7RAABALjNM0zTdPURua9GihSRpw4YNbp4EAADcapa4LQUAAHAV5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFgK5QYAAFiKx5Wby5cvq0ePHlqyZInL9i1btqhHjx6KiIjQvffeq9dee02XL19205QAAMBdPKrcHDhwQD179tTOnTtdtsfHx6t///568MEHtWXLFi1cuFA7duzQO++8455BAQCA23hMuYmNjVXv3r3VuXNnlSpVymXf0aNH1bx5c3Xv3l3e3t4qWbKkOnbsqG3btrlpWgAA4C4+7h7gqtTUVMXHx2e5Lzg4WGFhYYqJiZG/v7/mzp3rsj8iIkIRERHOzx0Oh7755htVq1btts4MAADynjxTbnbt2qVevXpluW/69Olq2bJljh4nPT1dL7/8so4ePcptKQAA/oHyTLmJjIzU/v37/9ZjnD59WsOGDVNycrIWLFigkJCQWzQdAADwFB7znJsb2b17t7p06aKSJUvqiy++UMmSJd09EgAAcIM8c+Xm7zh69Kj69u2rqKgoDRkyxN3jAAAAN7JEufnkk0908eJFffzxx/r444+d20uVKqVVq1a5bzAAAJDrDNM0TXcPkdtatGghSdqwYYObJwEAALeaZZ5zAwAAIFFuAACAxVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApVBuAACApXhcubl8+bJ69OihJUuWZLn/0qVLatOmjaZNm5bLkwEAgLzAo8rNgQMH1LNnT+3cuTPbzKuvvqrff/8912YCAAB5i8eUm9jYWPXu3VudO3dWqVKlsswsWbJEJ06cUJ06dXJ5OgAAkFf4uHuAq1JTUxUfH5/lvuDgYIWFhSkmJkb+/v6aO3dupkxcXJymTZumL774QsOHD7/d4wIAgDwqz5SbXbt2qVevXlnumz59ulq2bJnt16ampmro0KF66aWXFBIScrtGBAAAHiDPlJvIyEjt37//L33ta6+9psjISLVo0eIWTwUAADxNnik3f8eKFSvk6+urZcuWSbryiqmdO3dq/fr1+vrrr907HAAAyFWWKDe7d+92+TwqKkr169fXoEGD3DQRAABwF495tRQAAEBOGKZpmu4eIrddfW7Ohg0b3DwJAAC41bhyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALIVyAwAALMXjys3ly5fVo0cPLVmyxGX78ePHNWDAAEVERCgyMlIjR45USkqKm6YEAADu4lHl5sCBA+rZs6d27tzpst1ms6lv374qUaKENm3apDVr1ujw4cOaNGmSewYFAABu4+PuAXIqNjZWzz33nJ5++mmdO3fOZV9MTIxsNptefPFFeXt7K1++fHrvvfd06dIlN00LAADcJc+Um9TUVMXHx2e5Lzg4WGFhYYqJiZG/v7/mzp3rsn/37t0KCwvT1KlTtWLFCknS/fffr2HDht32uQEAQN6SZ8rNrl271KtXryz3TZ8+XS1btsz2a5OSkvTdd9+pevXqWrdunU6fPq1Bgwbprbfe0pgxYzLlT58+LbvdrhYtWtyy+QEAwO1XsmRJffbZZ9fN5JlyExkZqf379/+lr/Xz81OxYsU0cOBASVLZsmXVr18/jRs3Lsty4+/vL5vN9rfmBQAAeVOeKTd/R2hoqNauXSuHwyEvryvPkXY4HDJNM8v89u3bc3M8AACQizzq1VLZadOmjex2u15//XXZbDYdO3ZMM2bMUMeOHd09GgAAyGWWKDdBQUFasGCBDh8+rHvvvVddu3ZVw4YN9dxzz7l7NAAAkMsMM7t7NwAAAB7IElduclNCQoLLb0KeMGGCMjIyssx+++236tChg2rXrq02bdooJiYml6f9a27mHJ944gnVqFFD4eHhzo/vvvsulyf+axITE9WqVStt2bIl24ynrqGUs/Pz1PXbt2+f+vTpo/r166tRo0Z6/vnnlZiYmGXWE9fwZs7PU9cwNjZW3bp1U506ddSoUSONHz9eqampWWY9cQ1v5vw8dQ0lyW63KyoqSqNGjco245b1M3FTHn30UfO5554zL126ZB45csRs166d+eGHH2bKHTp0yKxRo4b5zTffmOnp6eaqVavMmjVrmqdOnXLD1Dcnp+domqYZGRlpbtmyJZcn/Pu2b99utmzZ0qxcubL5448/Zpnx5DXMyfmZpmeu3+XLl81GjRqZU6dONdPS0szExETzySefNPv165cp64lreDPnZ5qeuYYJCQlmjRo1zMWLF5t2u92Mj48327dvb06dOjVT1hPX8GbOzzQ9cw2vmjJlihkWFmaOHDkyy/3uWj+u3NyEw4cPa+vWrRoxYoTy5cunsmXLasCAAZo/f36m7NKlSxUREaGWLVvKx8dHbdu2Vb169bRw4UI3TJ5zN3OOR48eVVJSkqpWreqGSf+6pUuXavjw4Tf8JY+euoY5PT9PXb8TJ04oLCxMAwcOlJ+fn4oWLaoePXpo27ZtmbKeuIY3c36euoZBQUHavHmzunTpIsMwdP78eaWlpSkoKChT1hPX8GbOz1PXULpydWr9+vVq3bp1thl3rR/l5iYcOHBARYoUUUhIiHNbaGioTpw4oQsXLrhkDx48qMqVK7tsq1ixovbt25crs/5VN3OO//vf/5Q/f34NGzZMDRo0UPv27bVo0aLcHvmmNW7cWN98843atm173ZynrmFOz89T169ChQr66KOP5O3t7dy2bt06VatWLVPWE9fwZs7PU9dQkgoUKCBJatq0qTp06KDg4GB16dIlU84T11DK+fl56homJCToxRdf1KRJk5QvX75sc+5aP0v8npvckpKSkmkRr35+6dIlFSpU6LrZgICAPP9+VzdzjjabTbVr19awYcNUqVIlbdmyRYMGDVL+/PnVpk2bXJ37ZgQHB+co56lrmNPz89T1u5ZpmpoyZYpiYmKy/I2lnrqGV93o/KywhuvXr1dSUpKGDx+uwYMH66OPPnLZ7+lreKPz88Q1dDgcGjFihPr06aOwsLDrZt21fly5uQmBgYG6fPmyy7arn+fPn99le758+TI9eSw1NTVTLq+5mXPs1KmTPvroI1WtWlW+vr5q3LixOnXqpDVr1uTavLeTp65hTnn6+iUnJ2vw4MH6+uuv9dlnn6lKlSqZMp68hjk5P09fQ+nKD7qQkBCNGDFCmzZtUlJSkst+T15D6cbn54lrOHPmTPn5+SkqKuqGWXetH+XmJlSqVEnnz5/X2bNnndvi4uJUokQJFSxY0CVbuXJlHThwwGXbwYMHValSpVyZ9a+6mXNctGhRpn8BbTab/P39c2XW281T1zCnPHn9jhw5ogcffFDJyclatGhRlj/4Jc9dw5yen6eu4U8//aR//etfLm+DY7PZ5Ovrm+n/8j1xDW/m/DxxDZcvX66tW7cqIiJCERERWrlypVauXKmIiIhMWbet3219urIFPfzww+awYcPMixcvOl9J9N5772XKHTx40KxRo4a5atUq5zPEa9SoYf72229umPrm5PQc586dazZs2NDcs2ePabfbzZiYGLNmzZrmtm3b3DD1X3O9VxN58hpedb3z89T1O3/+vHnfffeZo0aNMu12+3WznriGN3N+nrqGycnJZtOmTc3XX3/dTEtLM48dO2Z27drVfOWVVzJlPXENb+b8PHUNrzVy5MhsXy3lrvWj3NykM2fOmIMGDTLr169vNmjQwJw4caKZkZFhmqZp1q5d21y+fLkz+91335kPPPCAWbt2bbNdu3bmf/7zH3eNfVNyeo4Oh8OcPn262axZM7NmzZpmu3btzDVr1rhz9Jv25x/+VlnDq653fp66fnPmzDErV65s1qpVy6xdu7bLh2l6/hrezPl56hqapmkeOHDA7NOnjxkREWE2a9bMnDx5spmWlmaapuevoWnm/Pw8eQ2v+nO5yQvrx28oBgAAlsJzbgAAgKVQbgAAgKVQbgAAgKVQbgAAgKVQbgAAgKVQbgAAgKVQbgAAgKVQbgBYxowZMxQeHu78mDFjhrtHAuAG/BI/AJZx/vx5lzcmLFy4sIoUKeK+gQC4BeUGAABYCrelAFjCd999p5o1ayojI8O5LS4uTlWqVFFiYqIbJwOQ2yg3ACxh3759qlixonx8fJzbfvnlF4WEhCgoKMiNkwHIbZQbAJawb98+3X333S7b9u7dq7CwMDdNBMBdKDcALOGXX37JVGT27dtHuQH+gSg3ADxeamqqDh8+7HLlxuFwaM+ePZQb4B+IcgPA4x05ckR2u13ly5d3btu0aZPOnz+vKlWquHEyAO5AuQHg8YoUKSLDMLR7925J0s6dOzV+/HgFBATorrvucu9wAHIdv+cGgCVER0dr7ty5CgwMVP369VW8eHHFxsZq8eLF7h4NQC6j3AAAAEvhthQAALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALAUyg0AALCU/wN933ZxKCYT9gAAAABJRU5ErkJggg==", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -1505,12 +1504,26 @@ ], "source": [ "plt.figure(7)\n", - "plt.title('Gain')\n", - "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", - "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{g}$')\n", - "plt.ylim(-16,0)\n", + "plt.title(\"Gain\")\n", + "plt.plot(\n", + " Uo,\n", + " gain,\n", + " linewidth=1.5,\n", + " linestyle=\"-\",\n", + " marker=\"o\",\n", + " label=\"Buck converter static gain\",\n", + ")\n", + "plt.plot(\n", + " Uo,\n", + " HR.dot(model.theta),\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + " linewidth=1.5,\n", + " label=\"NARX model gain\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{g}$\")\n", + "plt.ylim(-16, 0)\n", "plt.legend()\n", "plt.show()" ] @@ -1525,7 +1538,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.471991600Z", @@ -1535,9 +1548,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -1546,11 +1559,18 @@ ], "source": [ "plt.figure(8)\n", - "plt.title('Static Curve')\n", - "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", - "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.xlabel('$\\\\bar{y}$')\n", + "plt.title(\"Static Curve\")\n", + "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", + "plt.plot(\n", + " Uo,\n", + " QR.dot(model.theta),\n", + " linewidth=1.5,\n", + " label=\"NARX ​​static representation\",\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.xlabel(\"$\\\\bar{y}$\")\n", "plt.legend()\n", "plt.show()" ] @@ -1565,7 +1585,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.557244700Z", @@ -1575,9 +1595,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -1586,12 +1606,12 @@ ], "source": [ "plt.figure(9)\n", - "ax = plt.axes(projection='3d')\n", - "ax.plot3D( J[0,:], J[1,:], J[2,:], 'o', linewidth=0.1)\n", - "ax.set_title('Optimum pareto-curve', fontsize=15)\n", - "ax.set_xlabel('$J_{ls}$', fontsize=10)\n", - "ax.set_ylabel('$J_{sg}$', fontsize=10)\n", - "ax.set_zlabel('$J_{sf}$', fontsize=10)\n", + "ax = plt.axes(projection=\"3d\")\n", + "ax.plot3D(J[0, :], J[1, :], J[2, :], \"o\", linewidth=0.1)\n", + "ax.set_title(\"Optimum pareto-curve\", fontsize=15)\n", + "ax.set_xlabel(\"$J_{ls}$\", fontsize=10)\n", + "ax.set_ylabel(\"$J_{sg}$\", fontsize=10)\n", + "ax.set_zlabel(\"$J_{sf}$\", fontsize=10)\n", "plt.show()" ] }, @@ -1605,7 +1625,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.561257100Z", @@ -1616,17 +1636,17 @@ { "data": { "text/plain": [ - "array([ 0.5514724 , 0.40449004, 1.42868214, -12.60549003,\n", - " 8.32739763, -11.41573513, 12.25729978, 3.08460885])" + "array([ 0.5514725 , 0.40449005, 1.42867821, -12.60548844,\n", + " 8.32740046, -11.41574101, 12.25729936, 3.08461192])" ] }, - "execution_count": 28, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Theta[position,:]" + "Theta[position, :]" ] }, { @@ -1691,7 +1711,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.565769100Z", @@ -1704,10 +1724,10 @@ "output_type": "stream", "text": [ "R matrix:\n", - "[[0. 0. 1. 0. 0. 0. 0. 0.]\n", - " [1. 1. 0. 0. 0. 0. 0. 0.]\n", - " [0. 0. 0. 1. 0. 0. 1. 0.]\n", - " [0. 0. 0. 0. 1. 1. 0. 1.]]\n", + "[[0 0 1 0 0 0 0 0]\n", + " [1 1 0 0 0 0 0 0]\n", + " [0 0 0 1 0 0 1 0]\n", + " [0 0 0 0 1 1 0 1]]\n", "qit matrix:\n", "[[0. 0.]\n", " [1. 0.]\n", @@ -1717,10 +1737,10 @@ } ], "source": [ - "R, qit = mult2.R_qit()\n", - "print('R matrix:')\n", + "R, qit = mult2.build_linear_mapping()\n", + "print(\"R matrix:\")\n", "print(R)\n", - "print('qit matrix:')\n", + "print(\"qit matrix:\")\n", "print(qit)" ] }, @@ -1798,7 +1818,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.568942Z", @@ -1808,8 +1828,7 @@ "outputs": [], "source": [ "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", - "mult3 = IM(sg=False, sf=True, model_type='NARMAX',\n", - " final_model = model_final, norm=True)" + "mult3 = AILS(static_function=True, static_gain=False, final_model=model_final, normalize=True)" ] }, { @@ -1832,7 +1851,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.660520200Z", @@ -1873,41 +1892,41 @@ " 0\n", " 0.990080\n", " 0.009920\n", - " 0.990861\n", + " 0.990863\n", " 1.000000\n", - " 0.990937\n", + " 0.990939\n", " \n", " \n", " 1\n", " 0.987127\n", " 0.012873\n", - " 0.990862\n", - " 0.987041\n", - " 0.990936\n", + " 0.990865\n", + " 0.987032\n", + " 0.990939\n", " \n", " \n", " 2\n", " 0.984182\n", " 0.015818\n", - " 0.990865\n", - " 0.974317\n", - " 0.990937\n", + " 0.990867\n", + " 0.974307\n", + " 0.990939\n", " \n", " \n", " 3\n", " 0.981247\n", " 0.018753\n", - " 0.990867\n", - " 0.961788\n", - " 0.990938\n", + " 0.990870\n", + " 0.961803\n", + " 0.990940\n", " \n", " \n", " 4\n", " 0.978320\n", " 0.021680\n", - " 0.990871\n", - " 0.949519\n", - " 0.990939\n", + " 0.990873\n", + " 0.949509\n", + " 0.990941\n", " \n", " \n", " ...\n", @@ -1922,32 +1941,32 @@ " 0.002555\n", " 0.997445\n", " 0.999993\n", - " 0.000071\n", + " 0.000072\n", " 0.999993\n", " \n", " \n", " 1996\n", " 0.002547\n", " 0.997453\n", - " 0.999995\n", - " 0.000071\n", - " 0.999995\n", + " 0.999994\n", + " 0.000072\n", + " 0.999994\n", " \n", " \n", " 1997\n", " 0.002540\n", " 0.997460\n", - " 0.999994\n", + " 0.999996\n", " 0.000071\n", - " 0.999994\n", + " 0.999996\n", " \n", " \n", " 1998\n", " 0.002532\n", " 0.997468\n", - " 0.999996\n", + " 0.999998\n", " 0.000071\n", - " 0.999996\n", + " 0.999998\n", " \n", " \n", " 1999\n", @@ -1964,22 +1983,22 @@ ], "text/plain": [ " w1 w2 J_ls J_sg ||J||:\n", - "0 0.990080 0.009920 0.990861 1.000000 0.990937\n", - "1 0.987127 0.012873 0.990862 0.987041 0.990936\n", - "2 0.984182 0.015818 0.990865 0.974317 0.990937\n", - "3 0.981247 0.018753 0.990867 0.961788 0.990938\n", - "4 0.978320 0.021680 0.990871 0.949519 0.990939\n", + "0 0.990080 0.009920 0.990863 1.000000 0.990939\n", + "1 0.987127 0.012873 0.990865 0.987032 0.990939\n", + "2 0.984182 0.015818 0.990867 0.974307 0.990939\n", + "3 0.981247 0.018753 0.990870 0.961803 0.990940\n", + "4 0.978320 0.021680 0.990873 0.949509 0.990941\n", "... ... ... ... ... ...\n", - "1995 0.002555 0.997445 0.999993 0.000071 0.999993\n", - "1996 0.002547 0.997453 0.999995 0.000071 0.999995\n", - "1997 0.002540 0.997460 0.999994 0.000071 0.999994\n", - "1998 0.002532 0.997468 0.999996 0.000071 0.999996\n", + "1995 0.002555 0.997445 0.999993 0.000072 0.999993\n", + "1996 0.002547 0.997453 0.999994 0.000072 0.999994\n", + "1997 0.002540 0.997460 0.999996 0.000071 0.999996\n", + "1998 0.002532 0.997468 0.999998 0.000071 0.999998\n", "1999 0.002525 0.997475 1.000000 0.000070 1.000000\n", "\n", "[2000 rows x 5 columns]" ] }, - "execution_count": 31, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1988,20 +2007,16 @@ "W = np.zeros((2, 2000))\n", "W[0, :] = np.logspace(-0.01, -6, num=2000, base=2.71)\n", "W[1, :] = np.ones(2000) - W[0, :]\n", - "J, w, E, Theta, HR, QR, position = mult3.affine_information_least_squares(y_train=y_train[2:],\n", - " y_static=Yo,\n", - " x_static=Uo, psi=PSI, W=W)\n", - "result = {'w1': w[0,:],\n", - " 'w2': w[1,:],\n", - " 'J_ls': J[0,:],\n", - " 'J_sg': J[1,:],\n", - " '||J||:': E}\n", + "J, w, E, Theta, HR, QR, position = mult3.affine_information_least_squares(\n", + " y_train=y_train[2:], y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + ")\n", + "result = {\"w1\": w[0, :], \"w2\": w[1, :], \"J_ls\": J[0, :], \"J_sg\": J[1, :], \"||J||:\": E}\n", "pd.DataFrame(result)" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.775500300Z", @@ -2100,29 +2115,34 @@ "7 x1(k-2)^2 2.9043E+00 3.827E-06" ] }, - "execution_count": 32, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.theta = Theta[position, :].reshape(-1, 1)\n", "model.final_model = model_final\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", " results(\n", - " model.final_model, model.theta, model.err,\n", - " model.n_terms, err_precision=3, dtype='sci'\n", - " ),\n", - " columns=['Regressors', 'Parameters', 'ERR'])\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", "r" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.870151400Z", @@ -2132,9 +2152,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -2147,7 +2167,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.956170500Z", @@ -2157,9 +2177,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -2168,18 +2188,25 @@ ], "source": [ "plt.figure(10)\n", - "plt.title('Static Curve')\n", - "plt.plot(Uo, Yo, linewidth=1.5, label='Static curve', linestyle='-', marker='o')\n", - "plt.plot(Uo, QR.dot(model.theta), linewidth=1.5, label='NARX ​​static representation', linestyle='-', marker='^')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.xlabel('$\\\\bar{y}$')\n", + "plt.title(\"Static Curve\")\n", + "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", + "plt.plot(\n", + " Uo,\n", + " QR.dot(model.theta),\n", + " linewidth=1.5,\n", + " label=\"NARX ​​static representation\",\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.xlabel(\"$\\\\bar{y}$\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.030539300Z", @@ -2189,9 +2216,9 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -2200,10 +2227,10 @@ ], "source": [ "plt.figure(11)\n", - "plt.title('Costs Functions')\n", - "plt.plot(J[1,:], J[0,:], 'o')\n", - "plt.xlabel('Static Curve Information')\n", - "plt.ylabel('Prediction Error')\n", + "plt.title(\"Costs Functions\")\n", + "plt.plot(J[1, :], J[0, :], \"o\")\n", + "plt.xlabel(\"Static Curve Information\")\n", + "plt.ylabel(\"Prediction Error\")\n", "plt.show()" ] }, @@ -2217,7 +2244,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.034601700Z", @@ -2228,23 +2255,23 @@ { "data": { "text/plain": [ - "array([[ 0.54940884],\n", + "array([[ 0.54940883],\n", " [ 0.40803995],\n", - " [ 1.38725622],\n", - " [-12.51466373],\n", - " [ 8.11712593],\n", - " [-11.04664177],\n", - " [ 12.22693929],\n", - " [ 2.90425532]])" + " [ 1.38725684],\n", + " [-12.51466387],\n", + " [ 8.11712907],\n", + " [-11.04664806],\n", + " [ 12.22693917],\n", + " [ 2.9042585 ]])" ] }, - "execution_count": 36, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Theta[position, :].reshape(-1,1)" + "Theta[position, :].reshape(-1, 1)" ] }, { @@ -2312,7 +2339,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.038110800Z", @@ -2322,9 +2349,7 @@ "outputs": [], "source": [ "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", - "mult4 = IM(sf=False, sg=True, model_type='NARMAX',\n", - " final_model = model_final, \n", - " norm=False)" + "mult4 = AILS(static_function=False, static_gain=True, final_model=model_final, normalize=False)" ] }, { @@ -2347,7 +2372,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.121025300Z", @@ -2389,15 +2414,15 @@ " 1.000000\n", " 0.000000\n", " 17.407256\n", - " 3.579839e+01\n", - " 39.806245\n", + " 3.579467e+01\n", + " 39.802903\n", " \n", " \n", " 1\n", " 0.997012\n", " 0.002988\n", " 17.407528\n", - " 2.109245e-01\n", + " 2.109260e-01\n", " 17.408806\n", " \n", " \n", @@ -2405,7 +2430,7 @@ " 0.994033\n", " 0.005967\n", " 17.407540\n", - " 2.082048e-01\n", + " 2.082067e-01\n", " 17.408785\n", " \n", " \n", @@ -2413,7 +2438,7 @@ " 0.991063\n", " 0.008937\n", " 17.407559\n", - " 2.056622e-01\n", + " 2.056636e-01\n", " 17.408774\n", " \n", " \n", @@ -2421,7 +2446,7 @@ " 0.988102\n", " 0.011898\n", " 17.407585\n", - " 2.031813e-01\n", + " 2.031788e-01\n", " 17.408771\n", " \n", " \n", @@ -2436,41 +2461,41 @@ " 1995\n", " 0.002555\n", " 0.997445\n", - " 17.511595\n", - " 3.443914e-07\n", - " 17.511595\n", + " 17.511596\n", + " 3.340081e-07\n", + " 17.511596\n", " \n", " \n", " 1996\n", " 0.002547\n", " 0.997453\n", - " 17.511604\n", - " 3.143891e-07\n", - " 17.511604\n", + " 17.511596\n", + " 3.320125e-07\n", + " 17.511596\n", " \n", " \n", " 1997\n", " 0.002540\n", " 0.997460\n", - " 17.511607\n", - " 3.515715e-07\n", - " 17.511607\n", + " 17.511597\n", + " 3.300289e-07\n", + " 17.511597\n", " \n", " \n", " 1998\n", " 0.002532\n", " 0.997468\n", - " 17.511820\n", - " 3.295491e-07\n", - " 17.511820\n", + " 17.511598\n", + " 3.280571e-07\n", + " 17.511598\n", " \n", " \n", " 1999\n", " 0.002525\n", " 0.997475\n", - " 17.511609\n", - " 3.080806e-07\n", - " 17.511609\n", + " 17.511599\n", + " 3.260972e-07\n", + " 17.511599\n", " \n", " \n", "\n", @@ -2479,22 +2504,22 @@ ], "text/plain": [ " w1 w2 J_ls J_sg ||J||:\n", - "0 1.000000 0.000000 17.407256 3.579839e+01 39.806245\n", - "1 0.997012 0.002988 17.407528 2.109245e-01 17.408806\n", - "2 0.994033 0.005967 17.407540 2.082048e-01 17.408785\n", - "3 0.991063 0.008937 17.407559 2.056622e-01 17.408774\n", - "4 0.988102 0.011898 17.407585 2.031813e-01 17.408771\n", + "0 1.000000 0.000000 17.407256 3.579467e+01 39.802903\n", + "1 0.997012 0.002988 17.407528 2.109260e-01 17.408806\n", + "2 0.994033 0.005967 17.407540 2.082067e-01 17.408785\n", + "3 0.991063 0.008937 17.407559 2.056636e-01 17.408774\n", + "4 0.988102 0.011898 17.407585 2.031788e-01 17.408771\n", "... ... ... ... ... ...\n", - "1995 0.002555 0.997445 17.511595 3.443914e-07 17.511595\n", - "1996 0.002547 0.997453 17.511604 3.143891e-07 17.511604\n", - "1997 0.002540 0.997460 17.511607 3.515715e-07 17.511607\n", - "1998 0.002532 0.997468 17.511820 3.295491e-07 17.511820\n", - "1999 0.002525 0.997475 17.511609 3.080806e-07 17.511609\n", + "1995 0.002555 0.997445 17.511596 3.340081e-07 17.511596\n", + "1996 0.002547 0.997453 17.511596 3.320125e-07 17.511596\n", + "1997 0.002540 0.997460 17.511597 3.300289e-07 17.511597\n", + "1998 0.002532 0.997468 17.511598 3.280571e-07 17.511598\n", + "1999 0.002525 0.997475 17.511599 3.260972e-07 17.511599\n", "\n", "[2000 rows x 5 columns]" ] }, - "execution_count": 38, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -2503,22 +2528,18 @@ "W = np.zeros((2, 2000))\n", "W[0, :] = np.logspace(0, -6, num=2000, base=2.71)\n", "W[1, :] = np.ones(2000) - W[0, :]\n", - "# W = np.array([[0.9931126], \n", - " #[0.0068874]])\n", - "J, w, E, Theta, HR, QR, position = mult4.affine_information_least_squares(y_train=y_train[2:],\n", - " gain=gain,y_static=Yo,\n", - " x_static=Uo, psi=PSI, W=W)\n", - "result = {'w1': w[0,:],\n", - " 'w2': w[1,:],\n", - " 'J_ls': J[0,:],\n", - " 'J_sg': J[1,:],\n", - " '||J||:': E}\n", + "# W = np.array([[0.9931126],\n", + "# [0.0068874]])\n", + "J, w, E, Theta, HR, QR, position = mult4.affine_information_least_squares(\n", + " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + ")\n", + "result = {\"w1\": w[0, :], \"w2\": w[1, :], \"J_ls\": J[0, :], \"J_sg\": J[1, :], \"||J||:\": E}\n", "pd.DataFrame(result)" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.234880200Z", @@ -2617,29 +2638,34 @@ "7 x1(k-2)^2 2.9455E+00 3.827E-06" ] }, - "execution_count": 39, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1,1)\n", + "model.theta = Theta[position, :].reshape(-1, 1)\n", "model.final_model = model_final\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", " results(\n", - " model.final_model, model.theta, model.err,\n", - " model.n_terms, err_precision=3, dtype='sci'\n", - " ),\n", - " columns=['Regressors', 'Parameters', 'ERR'])\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", "r" ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.355391Z", @@ -2649,9 +2675,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -2664,7 +2690,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.452301700Z", @@ -2674,9 +2700,9 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -2685,18 +2711,32 @@ ], "source": [ "plt.figure(12)\n", - "plt.title('Gain')\n", - "plt.plot(Uo, gain, linewidth=1.5, linestyle='-', marker='o', label='Buck converter static gain')\n", - "plt.plot(Uo, HR.dot(model.theta), linestyle='-', marker='^', linewidth=1.5, label='NARX model gain')\n", - "plt.xlabel('$\\\\bar{u}$')\n", - "plt.ylabel('$\\\\bar{g}$')\n", + "plt.title(\"Gain\")\n", + "plt.plot(\n", + " Uo,\n", + " gain,\n", + " linewidth=1.5,\n", + " linestyle=\"-\",\n", + " marker=\"o\",\n", + " label=\"Buck converter static gain\",\n", + ")\n", + "plt.plot(\n", + " Uo,\n", + " HR.dot(model.theta),\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + " linewidth=1.5,\n", + " label=\"NARX model gain\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{g}$\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.508762500Z", @@ -2706,9 +2746,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -2717,10 +2757,10 @@ ], "source": [ "plt.figure(11)\n", - "plt.title('Costs Functions')\n", - "plt.plot(J[1,:], J[0,:], 'o')\n", - "plt.xlabel('Gain Information')\n", - "plt.ylabel('Prediction Error')\n", + "plt.title(\"Costs Functions\")\n", + "plt.plot(J[1, :], J[0, :], \"o\")\n", + "plt.xlabel(\"Gain Information\")\n", + "plt.ylabel(\"Prediction Error\")\n", "plt.show()" ] }, @@ -2734,7 +2774,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 44, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.509766600Z", @@ -2745,23 +2785,23 @@ { "data": { "text/plain": [ - "array([[ 0.54939784],\n", - " [ 0.40805605],\n", - " [ 1.48525188],\n", - " [-12.58066118],\n", - " [ 8.16862327],\n", - " [-11.12171304],\n", - " [ 12.20954877],\n", - " [ 2.94548199]])" + "array([[ 0.54939785],\n", + " [ 0.40805603],\n", + " [ 1.48525191],\n", + " [-12.58066069],\n", + " [ 8.16862612],\n", + " [-11.12171883],\n", + " [ 12.20954833],\n", + " [ 2.94548497]])" ] }, - "execution_count": 43, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Theta[position, :].reshape(-1,1)" + "Theta[position, :].reshape(-1, 1)" ] }, { @@ -2828,7 +2868,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 46, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.518219Z", @@ -2839,65 +2879,31 @@ { "data": { "text/plain": [ - "array([[1.00000000e+00, 3.20000000e+01, 0.00000000e+00, 0.00000000e+00],\n", - " [1.00000000e+00, 3.13469388e+01, 8.16326531e-02, 6.66389005e-03],\n", - " [1.00000000e+00, 3.06938776e+01, 1.63265306e-01, 2.66555602e-02],\n", - " [1.00000000e+00, 3.00408163e+01, 2.44897959e-01, 5.99750104e-02],\n", - " [1.00000000e+00, 2.93877551e+01, 3.26530612e-01, 1.06622241e-01],\n", - " [1.00000000e+00, 2.87346939e+01, 4.08163265e-01, 1.66597251e-01],\n", - " [1.00000000e+00, 2.80816327e+01, 4.89795918e-01, 2.39900042e-01],\n", - " [1.00000000e+00, 2.74285714e+01, 5.71428571e-01, 3.26530612e-01],\n", - 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"execution_count": 45, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "mult4.static_gain(Uo, Yo, gain)[1]" + "mult4.build_static_gain_information(Uo, Yo, gain)[1]" ] } ], @@ -2999,7 +2971,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.8.11" }, "orig_nbformat": 4, "vscode": { diff --git a/sysidentpy/multiobjective/multiobjective_parameter_estimation.py b/sysidentpy/multiobjective/multiobjective_parameter_estimation.py deleted file mode 100644 index b7fb464e..00000000 --- a/sysidentpy/multiobjective/multiobjective_parameter_estimation.py +++ /dev/null @@ -1,282 +0,0 @@ -import numpy as np -from sysidentpy.model_structure_selection import FROLS -from sysidentpy.basis_function import Polynomial -from sysidentpy.narmax_base import RegressorDictionary - -# from sysidentpy import basis_function - - -class IM(FROLS): - """Multiobjective parameter estimation using technique proposed by Nepomuceno et. al. - - Reference: - NEPOMUCENO, E. G.; TAKAHASHI, R. H. C. ; AGUIRRE, L. A. . Multiobjective parameter - estimation for nonlinear systems: Affine information and least-squares formulation. - International Journal of Control (Print), v. 80, p. 863-871, 2007. - - Parameters - ---------- - sg : bool, default=True - Presence of data referring to static gain. - sf : bool, default=True - Presence of data regarding static function. - model_type : string, default='NARMAX' - Model type. - final_model : ndarray, default = ([[0],[0]]) - Template code. - """ - - def __init__( - self, - sg=True, - sf=True, - model_type="NARMAX", - final_model=np.zeros((1, 1)), - norm=True, - ): - self.sg = sg - self.sf = sf - self.n_inputs = np.max(final_model // 1000) - 1 - self.non_degree = np.shape(final_model)[1] - self.model_type = model_type - self.final_model = final_model - self.norm = norm - # self.basis_function = Polynomial(degree=non_degree) - - def Exp(self, qit): - N_aux = np.zeros((int(np.shape(qit)[0]), int(np.max(qit)))) - for k in range(0, int(np.max(qit))): - for i in range(0, np.shape(qit)[0]): - for j in range(0, np.shape(qit)[1]): - if k + 1 == qit[i, j]: - N_aux[i, k] = 1 + N_aux[i, k] - return N_aux - - def R_qit(self): - """Assembly of the matrix of the linear mapping R, where to locate the terms uses the regressor-space method - - Returns: - -------- - R : ndarray of int - Matrix of the linear mapping composed by zeros and ones. - qit : ndarray of int - Row matrix that helps in locating the terms of the linear mapping matrix - and will later be used in the making of the static regressor matrix (Q). - """ - # 65 to 68 => Construction of the generic qit matrix. - xlag = [] - for i in range(0, self.n_inputs): - xlag.append(1) - object_qit = RegressorDictionary(xlag=xlag, ylag=[1]) - # With xlag and ylag equal to 1 there is no repetition of terms, being ideal for qit assembly. - qit = object_qit.regressor_space(n_inputs=self.n_inputs) // 1000 - model = self.final_model // 1000 - # 73 to 78 => Construction of the generic R matrix. - R = np.zeros((np.shape(qit)[0], np.shape(model)[0])) - b = [] - for i in range(0, np.shape(qit)[0]): - for j in range(0, np.shape(model)[0]): - if (qit[i, :] == model[j, :]).all(): - R[i, j] = 1 - if sum(R[i, :]) == 0: - b.append(i) # Identification of null rows of the R matrix. - R = np.delete( - R, b, axis=0 - ) # Eliminating the null rows from the generic R matrix. - qit = np.delete( - qit, b, axis=0 - ) # Eliminating the null rows from the generic qit matrix. - return R, self.Exp(qit) - - def static_function(self, x_static, y_static): - """Matrix of static regressors. - - Parameters - ---------- - y_static : array-like of shape = n_samples_static_function, default = ([0]) - Output of static function. - x_static : array-like of shape = n_samples_static_function, default = ([0]) - Static function input. - - Returns: - ------- - Q.dot(R) : ndarray of floats - Returns the multiplication of the matrix of static regressors (Q) and linear mapping (R). - """ - R, qit = self.R_qit() - # 102 to 107 => Assembly of the matrix Q. - Q = np.zeros((len(y_static), len(qit))) - for i in range(0, len(y_static)): - for j in range(0, len(qit)): - Q[i, j] = y_static[i, 0] ** (qit[j, 0]) - for k in range(0, self.n_inputs): - Q[i, j] = Q[i, j] * x_static[i, k] ** (qit[j, 1 + k]) - return Q.dot(R), Q - - def static_gain(self, x_static, y_static, gain): - """Matrix of static regressors referring to derivative. - - Parameters - ---------- - y_static : array-like of shape = n_samples_static_function, default = ([0]) - Output of static function. - x_static : array-like of shape = n_samples_static_function, default = ([0]) - Static function input. - gain : array-like of shape = n_samples_static_gain, default = ([0]) - Static gain input. - - Returns: - -------- - (G+H).dot(R) : ndarray of floats - Matrix of static regressors for the derivative (gain) multiplied - he matrix of the linear mapping R. - """ - R, qit = self.R_qit() - # 130 to 151 => Construction of the matrix H and G (Static gain). - H = np.zeros((len(y_static), len(qit))) - G = np.zeros((len(y_static), len(qit))) - for i in range(0, len(y_static)): - for j in range(1, len(qit)): - if y_static[i, 0] == 0: - if (qit[j, 0]) == 1: - H[i, j] = gain[i] - else: - H[i, j] = 0 - else: - H[i, j] = gain[i] * qit[j, 0] * y_static[i, 0] ** (qit[j, 0] - 1) - for k in range(0, self.n_inputs): - if x_static[i, k] == 0: - if (qit[j, 1 + k]) == 1: - G[i, j] = 1 - else: - G[i, j] = 0 - else: - G[i, j] = qit[j, 1 + k] * x_static[i, k] ** (qit[j, 1 + k] - 1) - return (G + H).dot(R), H + G - - def weights(self): - """Weights givenwith each objective. - - Returns: - ------- - w : ndarray of floats - Matrix with the weights. - """ - w1 = np.logspace(-0.01, -5, num=50, base=2.71) - w2 = w1[::-1] - a1 = [] - a2 = [] - a3 = [] - for i in range(0, len(w1)): - for j in range(0, len(w2)): - if w1[i] + w2[j] <= 1: - a1.append(w1[i]) - a2.append(w2[j]) - a3.append(1 - (w1[i] + w2[j])) - if self.sg != False and self.sf != False: - W = np.zeros((3, len(a1))) - W[0, :] = a1 - W[1, :] = a2 - W[2, :] = a3 - else: - W = np.zeros((2, len(a1))) - W[0, :] = a2 - W[1, :] = np.ones(len(a1)) - a2 - return W - - def affine_information_least_squares( - self, - y_static=np.zeros(1), - x_static=np.zeros(1), - gain=np.zeros(1), - y_train=np.zeros(1), - psi=np.zeros((1, 1)), - W=np.zeros((1, 1)), - ): - """Calculation of parameters via multi-objective techniques. - - Parameters - ---------- - y_static : array-like of shape = n_samples_static_function, default = ([0]) - Output of static function. - x_static : array-like of shape = n_samples_static_function, default = ([0]) - Static function input. - gain : array-like of shape = n_samples_static_gain, default = ([0]) - Static gain input. - y_train : array-like of shape = n_samples, defalult = ([0]) - The target data used in the identification process. - psi : ndarray of floats, default = ([[0],[0]]) - Matrix of static regressors. - - Returns - ------- - J : ndarray - Matrix referring to the objectives. - W : ndarray - Matrix referring to weights. - E : ndarray - Matrix of the Euclidean norm. - Array_theta : ndarray - Matrix with parameters for each weight. - HR : ndarray - H matrix multiplied by R. - QR : ndarray - Q matrix multiplied by R. - w : ndarray, default = ([[0],[0]]) - Matrix with weights. - """ - HR = None - QR = None - # 217 to 218 => Checking if the weights add up to 1. - if np.round(sum(W[:, 0]), 5) != 1: - W = self.weights() - E = np.zeros(np.shape(W)[1]) - Array_theta = np.zeros((np.shape(W)[1], np.shape(self.final_model)[0])) - # 222 to 257 => Calculation of the Parameters as a result of the input data. - PSI_aux1 = (psi).T.dot(psi) - PSI_aux2 = (psi.T).dot(y_train) - for i in range(0, np.shape(W)[1]): - theta1 = W[0, i] * PSI_aux1 - theta2 = W[0, i] * PSI_aux2 - w = 1 - if self.sf == True: - if i == 0: - QR = self.static_function(x_static, y_static)[0] - QR_aux1 = (QR.T).dot(QR) - QR_aux2 = (QR.T).dot(y_static) - theta1 = W[w, i] * QR_aux1 + theta1 - theta2 = theta2 + (W[w, i] * QR_aux2).reshape(-1, 1) - w = w + 1 - if self.sg == True: - if i == 0: - HR = self.static_gain(x_static, y_static, gain)[0] - HR_aux1 = (HR.T).dot(HR) - HR_aux2 = (HR.T).dot(gain) - theta1 = W[w, i] * HR_aux1 + theta1 - theta2 = theta2 + (W[w, i] * HR_aux2).reshape(-1, 1) - w = w + 1 - if i == 0: - J = np.zeros((w, np.shape(W)[1])) - Theta = ((np.linalg.inv(theta1)).dot(theta2)).reshape(-1, 1) - Array_theta[i, :] = Theta.T - J[0, i] = (((y_train) - (psi.dot(Theta))).T).dot( - (y_train) - (psi.dot(Theta)) - ) - w = 1 - if self.sg == True: - J[w, i] = (((gain) - (HR.dot(Theta))).T).dot((gain) - (HR.dot(Theta))) - w = w + 1 - if self.sf == True: - J[w, i] = (((y_static) - (QR.dot(Theta))).T).dot( - (y_static) - (QR.dot(Theta)) - ) - for i in range(0, np.shape(W)[1]): - E[i] = np.sqrt(np.sum(J[:, i] ** 2)) # Normalizing quadratic errors. - if self.norm == True: - for i in range(0, np.shape(J)[0]): - J[i, :] = J[i, :] / np.max(J[i, :]) - E = E / np.max(E) - # Finding the smallest squared error in relation to the three objectives. - min_value = min(E) - position = list(E).index(min_value) - return J, W, E, Array_theta, HR, QR, position diff --git a/sysidentpy/multiobjective/__init__.py b/sysidentpy/multiobjective_parameter_estimation/__init__.py similarity index 88% rename from sysidentpy/multiobjective/__init__.py rename to sysidentpy/multiobjective_parameter_estimation/__init__.py index c4a9a891..6c5de613 100644 --- a/sysidentpy/multiobjective/__init__.py +++ b/sysidentpy/multiobjective_parameter_estimation/__init__.py @@ -3,3 +3,5 @@ # Samir Angelo Milani Martins # Wilson Rocha Lacerda Junior # License: BSD 3 clause + +from .estimators import AILS diff --git a/sysidentpy/multiobjective_parameter_estimation/estimators.py b/sysidentpy/multiobjective_parameter_estimation/estimators.py new file mode 100644 index 00000000..f0131c6b --- /dev/null +++ b/sysidentpy/multiobjective_parameter_estimation/estimators.py @@ -0,0 +1,472 @@ +""" Affine Information Least Squares for NARMAX models""" + +import numpy as np +from sysidentpy.narmax_base import RegressorDictionary + + +class AILS: + """Affine Information Least Squares (AILS) for NARMAX Parameter Estimation. + + AILS is a non-iterative multiobjective Least Squares technique used for finding + Pareto-set solutions in NARMAX (Nonlinear AutoRegressive Moving Average with + eXogenous inputs) model parameter estimation. This method is suitable for + linear-in-the-parameter model structures. + + Two types of auxiliary information can be incorporated: static function and + steady-state gain. + + Parameters + ---------- + static_gain : bool, default=True + Flag indicating the presence of data related to steady-state gain. + static_function : bool, default=True + Flag indicating the presence of data concerning static function. + final_model : ndarray, default=[[0], [0]] + Model code representation. + + References + ---------- + 1. Nepomuceno, E. G., Takahashi, R. H. C., & Aguirre, L. A. (2007). + "Multiobjective parameter estimation for nonlinear systems: Affine information and + least-squares formulation." + International Journal of Control, 80, 863-871. + """ + + def __init__( + self, + static_gain=True, + static_function=True, + final_model=np.zeros((1, 1)), + normalize=True, + ): + self.n_inputs = np.max(final_model // 1000) - 1 + self.degree = np.shape(final_model)[1] + self.final_model = final_model + self.static_gain = static_gain + self.static_function = static_function + self.normalize = normalize + + def get_term_clustering(self, qit): + """ + Get the term clustering of the model. + + This function takes a matrix `qit` and compute the term clustering based + on their values. It calculates the number of occurrences of each value + for each row in the matrix. + + Parameters + ---------- + qit : ndarray + Input matrix containing terms clustering to be sorted. + + Returns + ------- + N_aux : ndarray + A new matrix with rows representing the number of occurrences of each value + for each row in the input matrix `qit`. The columns correspond to different + values. + + Examples + -------- + >>> qit = np.array([[1, 2, 2], + ... [1, 3, 1], + ... [2, 2, 3]]) + >>> result = get_term_clustering(qit) + >>> print(result) + [[1. 2. 0. 0.] + [2. 0. 1. 0.] + [0. 2. 1. 0.]] + + Notes + ----- + The function calculates the number of occurrences of each value (from 1 to + the maximum value in the input matrix `qit`) for each row and returns a matrix + where rows represent rows of the input matrix `qit`, and columns represent + different values. + + """ + max_value = int(np.max(qit)) + counts_matrix = np.zeros((qit.shape[0], max_value)) + + for k in range(1, max_value + 1): + counts_matrix[:, k - 1] = np.sum(qit == k, axis=1) + + return counts_matrix + + def build_linear_mapping(self): + """ + Assemble the linear mapping matrix R using the regressor-space method. + + This function constructs the linear mapping matrix R, which plays a key role in + mapping the parameter vector to the cluster coefficients. It also generates a + row matrix qit that assists in locating terms within the linear mapping matrix. + This qit matrix is later used in creating the static regressor matrix (Q). + + Returns + ------- + R : ndarray of int + A constant matrix of ones and zeros that maps the parameter vector to + cluster coefficients. + qit : ndarray of int + A row matrix that helps locate terms within the linear mapping matrix R and + is used in the creation of the static regressor matrix (Q). + + Notes + ----- + The linear mapping matrix R is constructed using the regressor-space method. + It plays a crucial role in the parameter estimation process, facilitating the + mapping of parameter values to cluster coefficients. The qit matrix aids in + term localization within the linear mapping matrix R and is subsequently used + to build the static regressor matrix (Q). + + """ + xlag = [1] * self.n_inputs + + object_qit = RegressorDictionary(xlag=xlag, ylag=[1]) + # Given xlag and ylag equal to 1, there is no repetition of terms, which is + # ideal for building qit. + qit = object_qit.regressor_space(n_inputs=self.n_inputs) // 1000 + model = self.final_model // 1000 + R = np.all(qit[:, None, :] == model, axis=2).astype(int) + # Find rows with all zeros in R (sum of row elements is 0) + null_rows = list(np.where(np.sum(R, axis=1) == 0)[0]) + + R = np.delete(R, null_rows, axis=0) + qit = np.delete(qit, null_rows, axis=0) + return R, self.get_term_clustering(qit) + + def build_static_function_information(self, x_static, y_static): + """ + Construct a matrix of static regressors for a NARMAX model. + + Parameters + ---------- + y_static : array-like, shape (n_samples_static_function,) + Output of the static function. + x_static : array-like, shape (n_samples_static_function,) + Static function input. + + Returns + ------- + Q_dot_R : ndarray of floats, shape (n_samples_static_function, n_parameters) + The result of multiplying the matrix of static regressors (Q) with the + linear mapping matrix (R), where n_parameters is the number of model + parameters. + static_covariance: ndarray of floats, shape (n_parameters, n_parameters) + The covariance QR'QR + static_response: ndarray of floats, shape (n_parameters,) + The response QR'y + + Notes + ----- + This function constructs a matrix of static regressors (Q) based on the provided + static function outputs (y_static) and inputs (x_static). The linear mapping + matrix (R) should be precomputed before calling this function. The result + Q_dot_R represents the static regressors for the NARMAX model. + + """ + R, qit = self.build_linear_mapping() + Q = y_static ** qit[:, 0] + for k in range(self.n_inputs): + Q *= x_static ** qit[:, 1 + k] + + Q = Q.reshape(len(y_static), len(qit)) + + QR = Q.dot(R) + static_covariance = (QR.T).dot(QR) + static_response = (QR.T).dot(y_static) + return QR, static_covariance, static_response + + def build_static_gain_information(self, x_static, y_static, gain): + """ + Construct a matrix of static regressors referring to the derivative (gain). + + Parameters + ---------- + y_static : array-like, shape (n_samples_static_function,) + Output of the static function. + x_static : array-like, shape (n_samples_static_function,) + Static function input. + gain : array-like, shape (n_samples_static_gain,) + Static gain input. + + Returns + ------- + HR : ndarray of floats, shape (n_samples_static_function, n_parameters) + The matrix of static regressors for the derivative (gain) multiplied by the + linear mapping matrix R. + gain_covariance : ndarray of floats, shape (n_parameters, n_parameters) + The covariance matrix (HR'HR) for the gain-related regressors. + gain_response : ndarray of floats, shape (n_parameters,) + The response vector (HR'y) for the gain-related regressors. + + Notes + ----- + This function constructs a matrix of static regressors (G+H) for the derivative + (gain) based on the provided static function outputs (y_static), inputs + (x_static), and gain values. The linear mapping matrix (R) should be + precomputed before calling this function. + + """ + R, qit = self.build_linear_mapping() + H = np.zeros((len(y_static), len(qit))) + G = np.zeros((len(y_static), len(qit))) + for i in range(0, len(y_static)): + for j in range(1, len(qit)): + if y_static[i, 0] == 0: + if (qit[j, 0]) == 1: + H[i, j] = gain[i] + else: + H[i, j] = 0 + else: + H[i, j] = gain[i] * qit[j, 0] * y_static[i, 0] ** (qit[j, 0] - 1) + for k in range(0, self.n_inputs): + if x_static[i, k] == 0: + if (qit[j, 1 + k]) == 1: + G[i, j] = 1 + else: + G[i, j] = 0 + else: + G[i, j] = qit[j, 1 + k] * x_static[i, k] ** (qit[j, 1 + k] - 1) + + HR = (G + H).dot(R) + gain_covariance = (HR.T).dot(HR) + gain_response = (HR.T).dot(gain) + return HR, gain_covariance, gain_response + + def set_weights(self): + """ + Set weights assigned to each objective in the multi-objective optimization. + + Returns + ------- + weights : ndarray of floats + An array containing the weights for each objective. + + Notes + ----- + This method calculates the weights to be assigned to different objectives in + multi-objective optimization. The choice of weights depends on the presence + of static function and static gain data. If both are present, a set of weights + for dynamic, gain, and static objectives is computed. If either static function + or static gain is absent, a simplified set of weights is generated. + + """ + w1 = np.logspace(-0.01, -5, num=50, base=2.71) + if self.static_function is False or self.static_gain is False: + w2 = 1 - w1 + return np.vstack([w1, w2]) + + w2 = w1[::-1] + w1_grid, w2_grid = np.meshgrid(w1, w2) + w3_grid = 1 - (w1_grid + w2_grid) + mask = w1_grid + w2_grid <= 1 + dynamic_weight = np.flip(w1_grid[mask]) + gain_weight = np.flip(w2_grid[mask]) + static_weight = np.flip(w3_grid[mask]) + return np.vstack([dynamic_weight, gain_weight, static_weight]) + + def get_cost_function(self, y, psi, theta): + """ + Calculate the cost function based on residuals. + + Parameters + ---------- + y : ndarray of floats + The target data used in the identification process. + psi : ndarray of floats, shape (n_samples, n_parameters) + The matrix of regressors. + theta : ndarray of floats + The parameter vector. + + Returns + ------- + cost_function : float + The calculated cost function value. + + Notes + ----- + This method computes the cost function value based on the residuals between + the target data (y) and the predicted values using the regressors (dynamic + and static) and parameter vector (theta). It quantifies the error in the + model's predictions. + + """ + residuals = y - psi.dot(theta) + return residuals.T.dot(residuals) + + def build_system_data(self, y, static_gain, static_function): + """ + Construct a list of output data components for the NARMAX system. + + Parameters + ---------- + y : ndarray of floats + The target data used in the identification process. + static_gain : ndarray of floats + Static gain output data. + static_function : ndarray of floats + Static function output data. + + Returns + ------- + system_data : list of ndarrays + A list containing data components, including the target data (y), + static gain data (if present), and static function data (if present). + + Notes + ----- + This method constructs a list of data components that are used in the NARMAX + system identification process. The components may include the target data (y), + static gain data (if enabled), and static function data (if enabled). + + """ + if not self.static_gain: + return [y] + [static_function] + + if not self.static_function: + return [y] + [static_gain] + + return [y] + [static_gain] + [static_function] + + def build_affine_data(self, psi, HR, QR): + """ + Construct a list of affine data components for NARMAX modeling. + + Parameters + ---------- + psi : ndarray of floats, shape (n_samples, n_parameters) + The matrix of dynamic regressors. + HR : ndarray of floats, shape (n_samples_static_gain, n_parameters) + The matrix of static gain regressors. + QR : ndarray of floats, shape (n_samples_static_function, n_parameters) + The matrix of static function regressors. + + Returns + ------- + affine_data : list of ndarrays + A list containing affine data components, including the matrix of static + regressors (psi), static gain regressors (if present), and static function + regressors (if present). + + Notes + ----- + This method constructs a list of affine data components used in the NARMAX + modeling process. The components may include the matrix of static regressors + (psi), static gain regressors (if enabled), and static function regressors + (if enabled). + + """ + if not self.static_gain: + return [psi] + [QR] + + if not self.static_function: + return [psi] + [HR] + + return [psi] + [HR] + [QR] + + def affine_information_least_squares( + self, + y_static=np.zeros(1), + x_static=np.zeros(1), + gain=np.zeros(1), + y_train=np.zeros(1), + psi=np.zeros((1, 1)), + weighing_matrix=np.zeros((1, 1)), + ): + """Calculation of parameters via multi-objective techniques. + + Parameters + ---------- + y_static : array-like of shape = n_samples_static_function, default = ([0]) + Output of static function. + x_static : array-like of shape = n_samples_static_function, default = ([0]) + Static function input. + gain : array-like of shape = n_samples_static_gain, default = ([0]) + Static gain input. + y_train : array-like of shape = n_samples, default = ([0]) + The target data used in the identification process. + psi : ndarray of floats, default = ([[0],[0]]) + Matrix of static regressors. + + Returns + ------- + J : ndarray + Matrix referring to the objectives. + weighing_matrix : ndarray + Matrix referring to weights. + euclidean_norm : ndarray + Matrix of the Euclidean norm. + Array_theta : ndarray + Matrix with parameters for each weight. + HR : ndarray + H matrix multiplied by R. + QR : ndarray + Q matrix multiplied by R. + w : ndarray, default = ([[0],[0]]) + Matrix with weights. + """ + if np.round(sum(weighing_matrix[:, 0]), 5) != 1: + weighing_matrix = self.set_weights() + + HR, QR = None, None + n_parameters = weighing_matrix.shape[1] + num_objectives = self.static_function + self.static_gain + 1 + euclidean_norm = np.zeros(n_parameters) + theta = np.zeros((n_parameters, self.final_model.shape[0])) + dynamic_covariance = (psi).T.dot(psi) + dynamic_response = (psi.T).dot(y_train) + + if self.static_function: + QR, static_covariance, static_response = ( + self.build_static_function_information(x_static, y_static) + ) + if self.static_gain: + HR, gain_covariance, gain_response = self.build_static_gain_information( + x_static, y_static, gain + ) + J = np.zeros((num_objectives, n_parameters)) + system_data = self.build_system_data(y_train, gain, y_static) + affine_information_data = self.build_affine_data(psi, HR, QR) + for i in range(n_parameters): + theta1 = weighing_matrix[0, i] * dynamic_covariance + theta2 = weighing_matrix[0, i] * dynamic_response + + w = 1 + if self.static_function: + theta1 += weighing_matrix[w, i] * static_covariance + theta2 += weighing_matrix[w, i] * static_response.reshape(-1, 1) + w += 1 + + if self.static_gain: + theta1 += weighing_matrix[w, i] * gain_covariance + theta2 += weighing_matrix[w, i] * gain_response.reshape(-1, 1) + w += 1 + + tmp_theta = np.linalg.lstsq(theta1, theta2, rcond=None)[0] + theta[i, :] = tmp_theta.T + + for j in range(num_objectives): + residuals = self.get_cost_function( + system_data[j], affine_information_data[j], tmp_theta + ) + J[j, i] = residuals + + euclidean_norm[i] = np.linalg.norm(J[:, i]) + + if self.normalize is True: + J /= np.max(J, axis=1)[:, np.newaxis] + euclidean_norm /= np.max(euclidean_norm) + + euclidean_norm = euclidean_norm / np.max(euclidean_norm) + + position = np.argmin(euclidean_norm) + return ( + J, + weighing_matrix, + euclidean_norm, + theta, + HR, + QR, + position, + ) From b149f70accf7173c8989faf360cc2f62dd50af81 Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sat, 23 Sep 2023 23:51:20 -0300 Subject: [PATCH 03/11] improved docs and adapted examples --- examples/multiobjective.ipynb | 107 +++++++++++++++++----------------- 1 file changed, 55 insertions(+), 52 deletions(-) diff --git a/examples/multiobjective.ipynb b/examples/multiobjective.ipynb index 7197d5b8..3814cbc1 100644 --- a/examples/multiobjective.ipynb +++ b/examples/multiobjective.ipynb @@ -36,7 +36,8 @@ "from sysidentpy.basis_function._basis_function import Polynomial\n", "from sysidentpy.utils.display_results import results\n", "from sysidentpy.utils.plotting import plot_results\n", - "from sysidentpy.metrics import root_relative_squared_error" + "from sysidentpy.metrics import root_relative_squared_error\n", + "from sysidentpy.utils.narmax_tools import set_weights" ] }, { @@ -48,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -82,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -134,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -183,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -228,7 +229,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -245,10 +246,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -283,7 +284,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -323,7 +324,7 @@ " 0.003078\n", " 0.990080\n", " 0.999970\n", - " 1.095046e-05\n", + " 1.095045e-05\n", " 0.000013\n", " 0.245244\n", " \n", @@ -333,7 +334,7 @@ " 0.002347\n", " 0.990080\n", " 0.999938\n", - " 2.294674e-05\n", + " 2.294701e-05\n", " 0.000016\n", " 0.245236\n", " \n", @@ -343,7 +344,7 @@ " 0.001538\n", " 0.990080\n", " 0.999885\n", - " 6.504949e-05\n", + " 6.505062e-05\n", " 0.000018\n", " 0.245223\n", " \n", @@ -353,7 +354,7 @@ " 0.000642\n", " 0.990080\n", " 0.999717\n", - " 4.505604e-04\n", + " 4.505632e-04\n", " 0.000021\n", " 0.245183\n", " \n", @@ -363,7 +364,7 @@ " 0.098663\n", " 0.894495\n", " 1.000000\n", - " 7.393244e-08\n", + " 7.393225e-08\n", " 0.000015\n", " 0.245252\n", " \n", @@ -394,7 +395,7 @@ " 0.006842\n", " 0.995632\n", " 5.602985e-04\n", - " 0.972842\n", + " 0.972841\n", " 0.244412\n", " \n", " \n", @@ -434,14 +435,14 @@ ], "text/plain": [ " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", - "0 0.006842 0.003078 0.990080 0.999970 1.095046e-05 0.000013 0.245244\n", - "1 0.007573 0.002347 0.990080 0.999938 2.294674e-05 0.000016 0.245236\n", - "2 0.008382 0.001538 0.990080 0.999885 6.504949e-05 0.000018 0.245223\n", - "3 0.009277 0.000642 0.990080 0.999717 4.505604e-04 0.000021 0.245183\n", - "4 0.006842 0.098663 0.894495 1.000000 7.393244e-08 0.000015 0.245252\n", + "0 0.006842 0.003078 0.990080 0.999970 1.095045e-05 0.000013 0.245244\n", + "1 0.007573 0.002347 0.990080 0.999938 2.294701e-05 0.000016 0.245236\n", + "2 0.008382 0.001538 0.990080 0.999885 6.505062e-05 0.000018 0.245223\n", + "3 0.009277 0.000642 0.990080 0.999717 4.505632e-04 0.000021 0.245183\n", + "4 0.006842 0.098663 0.894495 1.000000 7.393225e-08 0.000015 0.245252\n", "... ... ... ... ... ... ... ...\n", "2290 0.659632 0.333527 0.006842 0.995896 3.965701e-04 1.000000 0.244489\n", - "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972842 0.244412\n", + "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972841 0.244412\n", "2292 0.808139 0.185020 0.006842 0.995364 8.321075e-04 0.868299 0.244300\n", "2293 0.894495 0.098663 0.006842 0.995100 1.365000e-03 0.660485 0.244160\n", "2294 0.990080 0.003078 0.006842 0.992584 9.825994e-02 0.305492 0.261455\n", @@ -449,16 +450,16 @@ "[2295 rows x 7 columns]" ] }, - "execution_count": 8, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "test = AILS(final_model=model.final_model)\n", - "\n", - "J, w, E, Theta, HR, QR, position = test.affine_information_least_squares(\n", - " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=model.psi\n", + "w = set_weights(static_function=True, static_gain=True)\n", + "mo_estimator = AILS(final_model=model.final_model)\n", + "J, E, theta, HR, QR, position = mo_estimator.estimate(\n", + " y=y_train, gain=gain, y_static=Yo, X_static=Uo, X=x_train, weighing_matrix=w\n", ")\n", "result = {\n", " \"w1\": w[0, :],\n", @@ -481,7 +482,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -513,26 +514,26 @@ " \n", " \n", " 0\n", - " y(k-1)\n", - " 2.9687E-01\n", + " 1\n", + " 1.5405E+00\n", " 9.999E-01\n", " \n", " \n", " 1\n", - " y(k-2)\n", - " 6.4693E-01\n", + " y(k-1)\n", + " 2.9687E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", - " x1(k-1)y(k-1)\n", - " 4.0624E-03\n", + " y(k-2)\n", + " 6.4693E-01\n", " 1.108E-06\n", " \n", " \n", " 3\n", - " 1\n", - " 1.5405E+00\n", + " x1(k-1)\n", + " -4.1302E-01\n", " 4.688E-06\n", " \n", " \n", @@ -543,14 +544,14 @@ " \n", " \n", " 5\n", - " x1(k-1)\n", - " -4.1302E-01\n", + " y(k-2)y(k-1)\n", + " -5.3474E-01\n", " 8.389E-07\n", " \n", " \n", " 6\n", - " y(k-2)y(k-1)\n", - " -5.3474E-01\n", + " x1(k-1)y(k-1)\n", + " 4.0624E-03\n", " 5.690E-07\n", " \n", " \n", @@ -565,23 +566,25 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 2.9687E-01 9.999E-01\n", - "1 y(k-2) 6.4693E-01 2.042E-05\n", - "2 x1(k-1)y(k-1) 4.0624E-03 1.108E-06\n", - "3 1 1.5405E+00 4.688E-06\n", + "0 1 1.5405E+00 9.999E-01\n", + "1 y(k-1) 2.9687E-01 2.042E-05\n", + "2 y(k-2) 6.4693E-01 1.108E-06\n", + "3 x1(k-1) -4.1302E-01 4.688E-06\n", "4 y(k-1)^2 2.7671E-01 3.922E-07\n", - "5 x1(k-1) -4.1302E-01 8.389E-07\n", - "6 y(k-2)y(k-1) -5.3474E-01 5.690E-07\n", + "5 y(k-2)y(k-1) -5.3474E-01 8.389E-07\n", + "6 x1(k-1)y(k-1) 4.0624E-03 5.690E-07\n", "7 y(k-2)^2 2.5832E-01 3.827E-06" ] }, - "execution_count": 9, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.theta = Theta[position, :].reshape(-1, 1)\n", + "model.theta = theta[position, :].reshape(-1, 1) # get the best theta concerning the objectives\n", + "# the model structure is exactly the same, but the order of the regressors is changed in estimate method. Thats why you have to change the model.final_model\n", + "model.final_model = mo_estimator.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", @@ -600,7 +603,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -629,12 +632,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -666,7 +669,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -702,7 +705,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { From c495876c8a424514af4815ec552eaa59f83e5966 Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sat, 23 Sep 2023 23:51:59 -0300 Subject: [PATCH 04/11] add set_weights as a narmax_tool method in utils --- sysidentpy/utils/narmax_tools.py | 41 ++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) diff --git a/sysidentpy/utils/narmax_tools.py b/sysidentpy/utils/narmax_tools.py index e1772ae5..70baf832 100644 --- a/sysidentpy/utils/narmax_tools.py +++ b/sysidentpy/utils/narmax_tools.py @@ -43,3 +43,44 @@ def regressor_code( return regressor_code else: return regressor_code + + +def set_weights( + *, + static_function: bool = True, + static_gain: bool = True, + start: float = -0.01, + stop: float = -5, + num: int = 50, + base: float = 2.71, +) -> np.ndarray: + """ + Set log-spaced weights assigned to each objective in the multi-objective optimization. + + Returns + ------- + weights : ndarray of floats + An array containing the weights for each objective. + + Notes + ----- + This method calculates the weights to be assigned to different objectives in + multi-objective optimization. The choice of weights depends on the presence + of static function and static gain data. If both are present, a set of weights + for dynamic, gain, and static objectives is computed. If either static function + or static gain is absent, a simplified set of weights is generated. + + """ + w1 = np.logspace(start=start, stop=stop, num=num, base=base) + if static_function is False or static_gain is False: + w2 = 1 - w1 + return np.vstack([w1, w2]) + + w2 = w1[::-1] + w1_grid, w2_grid = np.meshgrid(w1, w2) + w3_grid = 1 - (w1_grid + w2_grid) + mask = w1_grid + w2_grid <= 1 + dynamic_weight = np.flip(w1_grid[mask]) + gain_weight = np.flip(w2_grid[mask]) + static_weight = np.flip(w3_grid[mask]) + return np.vstack([dynamic_weight, gain_weight, static_weight]) From 463fa43bd9ad012a9693583ffae19b176c22262f Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sat, 23 Sep 2023 23:53:18 -0300 Subject: [PATCH 05/11] move set_weights to narmax_tools in utils. Add a build_psi method and rename affine_information_least_squares to estimate --- .../estimators.py | 121 +++++++++--------- 1 file changed, 58 insertions(+), 63 deletions(-) diff --git a/sysidentpy/multiobjective_parameter_estimation/estimators.py b/sysidentpy/multiobjective_parameter_estimation/estimators.py index f0131c6b..792d2fa3 100644 --- a/sysidentpy/multiobjective_parameter_estimation/estimators.py +++ b/sysidentpy/multiobjective_parameter_estimation/estimators.py @@ -1,7 +1,8 @@ """ Affine Information Least Squares for NARMAX models""" import numpy as np -from sysidentpy.narmax_base import RegressorDictionary +from sysidentpy.narmax_base import RegressorDictionary, InformationMatrix +from sysidentpy.basis_function import Polynomial class AILS: @@ -41,6 +42,9 @@ def __init__( ): self.n_inputs = np.max(final_model // 1000) - 1 self.degree = np.shape(final_model)[1] + self.xlag = 1 + self.ylag = 1 + self.max_lag = 1 self.final_model = final_model self.static_gain = static_gain self.static_function = static_function @@ -91,7 +95,7 @@ def get_term_clustering(self, qit): for k in range(1, max_value + 1): counts_matrix[:, k - 1] = np.sum(qit == k, axis=1) - return counts_matrix + return counts_matrix.astype(int) def build_linear_mapping(self): """ @@ -135,7 +139,7 @@ def build_linear_mapping(self): qit = np.delete(qit, null_rows, axis=0) return R, self.get_term_clustering(qit) - def build_static_function_information(self, x_static, y_static): + def build_static_function_information(self, X_static, y_static): """ Construct a matrix of static regressors for a NARMAX model. @@ -143,7 +147,7 @@ def build_static_function_information(self, x_static, y_static): ---------- y_static : array-like, shape (n_samples_static_function,) Output of the static function. - x_static : array-like, shape (n_samples_static_function,) + X_static : array-like, shape (n_samples_static_function,) Static function input. Returns @@ -160,7 +164,7 @@ def build_static_function_information(self, x_static, y_static): Notes ----- This function constructs a matrix of static regressors (Q) based on the provided - static function outputs (y_static) and inputs (x_static). The linear mapping + static function outputs (y_static) and inputs (X_static). The linear mapping matrix (R) should be precomputed before calling this function. The result Q_dot_R represents the static regressors for the NARMAX model. @@ -168,7 +172,7 @@ def build_static_function_information(self, x_static, y_static): R, qit = self.build_linear_mapping() Q = y_static ** qit[:, 0] for k in range(self.n_inputs): - Q *= x_static ** qit[:, 1 + k] + Q *= X_static ** qit[:, 1 + k] Q = Q.reshape(len(y_static), len(qit)) @@ -177,7 +181,7 @@ def build_static_function_information(self, x_static, y_static): static_response = (QR.T).dot(y_static) return QR, static_covariance, static_response - def build_static_gain_information(self, x_static, y_static, gain): + def build_static_gain_information(self, X_static, y_static, gain): """ Construct a matrix of static regressors referring to the derivative (gain). @@ -185,7 +189,7 @@ def build_static_gain_information(self, x_static, y_static, gain): ---------- y_static : array-like, shape (n_samples_static_function,) Output of the static function. - x_static : array-like, shape (n_samples_static_function,) + X_static : array-like, shape (n_samples_static_function,) Static function input. gain : array-like, shape (n_samples_static_gain,) Static gain input. @@ -204,7 +208,7 @@ def build_static_gain_information(self, x_static, y_static, gain): ----- This function constructs a matrix of static regressors (G+H) for the derivative (gain) based on the provided static function outputs (y_static), inputs - (x_static), and gain values. The linear mapping matrix (R) should be + (X_static), and gain values. The linear mapping matrix (R) should be precomputed before calling this function. """ @@ -221,51 +225,19 @@ def build_static_gain_information(self, x_static, y_static, gain): else: H[i, j] = gain[i] * qit[j, 0] * y_static[i, 0] ** (qit[j, 0] - 1) for k in range(0, self.n_inputs): - if x_static[i, k] == 0: + if X_static[i, k] == 0: if (qit[j, 1 + k]) == 1: G[i, j] = 1 else: G[i, j] = 0 else: - G[i, j] = qit[j, 1 + k] * x_static[i, k] ** (qit[j, 1 + k] - 1) + G[i, j] = qit[j, 1 + k] * X_static[i, k] ** (qit[j, 1 + k] - 1) HR = (G + H).dot(R) gain_covariance = (HR.T).dot(HR) gain_response = (HR.T).dot(gain) return HR, gain_covariance, gain_response - def set_weights(self): - """ - Set weights assigned to each objective in the multi-objective optimization. - - Returns - ------- - weights : ndarray of floats - An array containing the weights for each objective. - - Notes - ----- - This method calculates the weights to be assigned to different objectives in - multi-objective optimization. The choice of weights depends on the presence - of static function and static gain data. If both are present, a set of weights - for dynamic, gain, and static objectives is computed. If either static function - or static gain is absent, a simplified set of weights is generated. - - """ - w1 = np.logspace(-0.01, -5, num=50, base=2.71) - if self.static_function is False or self.static_gain is False: - w2 = 1 - w1 - return np.vstack([w1, w2]) - - w2 = w1[::-1] - w1_grid, w2_grid = np.meshgrid(w1, w2) - w3_grid = 1 - (w1_grid + w2_grid) - mask = w1_grid + w2_grid <= 1 - dynamic_weight = np.flip(w1_grid[mask]) - gain_weight = np.flip(w2_grid[mask]) - static_weight = np.flip(w3_grid[mask]) - return np.vstack([dynamic_weight, gain_weight, static_weight]) - def get_cost_function(self, y, psi, theta): """ Calculate the cost function based on residuals. @@ -365,13 +337,40 @@ def build_affine_data(self, psi, HR, QR): return [psi] + [HR] + [QR] - def affine_information_least_squares( + def build_psi(self, X: np.ndarray, y: np.ndarray) -> np.ndarray: + psi_builder = RegressorDictionary() + xlag_code = psi_builder._list_input_regressor_code(self.final_model) + ylag_code = psi_builder._list_output_regressor_code(self.final_model) + xlag = psi_builder._get_lag_from_regressor_code(xlag_code) + ylag = psi_builder._get_lag_from_regressor_code(ylag_code) + self.max_lag = psi_builder._get_max_lag_from_model_code(self.final_model) + if self.n_inputs != 1: + xlag = self.n_inputs * [list(range(1, self.max_lag + 1))] + + psi_builder.xlag = xlag + psi_builder.ylag = ylag + regressor_code = psi_builder.regressor_space(self.n_inputs) + pivv = psi_builder._get_index_from_regressor_code( + regressor_code, self.final_model + ) + self.final_model = regressor_code[pivv] + + lagged_data = InformationMatrix(xlag=xlag, ylag=ylag).build_input_output_matrix( + X=X, y=y + ) + + psi = Polynomial(degree=self.degree).fit( + lagged_data, max_lag=self.max_lag, predefined_regressors=pivv + ) + return psi + + def estimate( self, y_static=np.zeros(1), - x_static=np.zeros(1), + X_static=np.zeros(1), gain=np.zeros(1), - y_train=np.zeros(1), - psi=np.zeros((1, 1)), + y=np.zeros(1), + X=np.zeros((1, 1)), weighing_matrix=np.zeros((1, 1)), ): """Calculation of parameters via multi-objective techniques. @@ -380,11 +379,11 @@ def affine_information_least_squares( ---------- y_static : array-like of shape = n_samples_static_function, default = ([0]) Output of static function. - x_static : array-like of shape = n_samples_static_function, default = ([0]) + X_static : array-like of shape = n_samples_static_function, default = ([0]) Static function input. gain : array-like of shape = n_samples_static_gain, default = ([0]) Static gain input. - y_train : array-like of shape = n_samples, default = ([0]) + y : array-like of shape = n_samples, default = ([0]) The target data used in the identification process. psi : ndarray of floats, default = ([[0],[0]]) Matrix of static regressors. @@ -393,40 +392,37 @@ def affine_information_least_squares( ------- J : ndarray Matrix referring to the objectives. - weighing_matrix : ndarray - Matrix referring to weights. euclidean_norm : ndarray Matrix of the Euclidean norm. - Array_theta : ndarray + theta : ndarray Matrix with parameters for each weight. HR : ndarray H matrix multiplied by R. QR : ndarray Q matrix multiplied by R. - w : ndarray, default = ([[0],[0]]) - Matrix with weights. + position : ndarray, default = ([[0],[0]]) + Position of the best theta set. """ - if np.round(sum(weighing_matrix[:, 0]), 5) != 1: - weighing_matrix = self.set_weights() - + psi = self.build_psi(X, y) + y = y[self.max_lag :] HR, QR = None, None n_parameters = weighing_matrix.shape[1] num_objectives = self.static_function + self.static_gain + 1 euclidean_norm = np.zeros(n_parameters) theta = np.zeros((n_parameters, self.final_model.shape[0])) - dynamic_covariance = (psi).T.dot(psi) - dynamic_response = (psi.T).dot(y_train) + dynamic_covariance = psi.T.dot(psi) + dynamic_response = psi.T.dot(y) if self.static_function: QR, static_covariance, static_response = ( - self.build_static_function_information(x_static, y_static) + self.build_static_function_information(X_static, y_static) ) if self.static_gain: HR, gain_covariance, gain_response = self.build_static_gain_information( - x_static, y_static, gain + X_static, y_static, gain ) J = np.zeros((num_objectives, n_parameters)) - system_data = self.build_system_data(y_train, gain, y_static) + system_data = self.build_system_data(y, gain, y_static) affine_information_data = self.build_affine_data(psi, HR, QR) for i in range(n_parameters): theta1 = weighing_matrix[0, i] * dynamic_covariance @@ -463,7 +459,6 @@ def affine_information_least_squares( position = np.argmin(euclidean_norm) return ( J, - weighing_matrix, euclidean_norm, theta, HR, From 0e4ea4d8acdf98be1da4acab37981993421df4a7 Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sat, 23 Sep 2023 23:54:21 -0300 Subject: [PATCH 06/11] refactoring the notebook with better details, organizations, readability and adapting to the new methods in estimate function --- .../multiobjective_parameter_estimation.ipynb | 719 +++++++++--------- 1 file changed, 370 insertions(+), 349 deletions(-) diff --git a/examples/multiobjective_parameter_estimation.ipynb b/examples/multiobjective_parameter_estimation.ipynb index 438513b7..c71035c7 100644 --- a/examples/multiobjective_parameter_estimation.ipynb +++ b/examples/multiobjective_parameter_estimation.ipynb @@ -5,11 +5,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Example: Buck converter\n", + "## Example: Multiobjective Parameter Estimation for NARMAX models - An Overview\n", "\n", "Example created by Gabriel Bueno Leandro, Samir Milani Martins and Wilson Rocha Lacerda Junior\n", "\n", - "
A buck converter is a type of DC/DC converter that decreases the voltage (while increasing the current) from its input (power supply) to its output (load). It is similar to a boost converter (elevator) and is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors (a diode and a transistor, although modern buck converters replace the diode with a second transistor used for synchronous rectification) and at least one energy storage element, a capacitor, inductor or both combined.
" + "Multiobjective parameter estimation represents a fundamental paradigm shift in the way we approach the parameter tuning problem for NARMAX models. Instead of seeking a single set of parameter values that optimally fits the model to the data, multiobjective approaches aim to identify a set of parameter solutions, known as the Pareto front, that provide a trade-off between competing objectives. These objectives often encompass a spectrum of model performance criteria, such as goodness-of-fit, model complexity, and robustness." ] }, { @@ -23,6 +23,15 @@ "\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Use case: Buck converter\n", + " \n", + "
A buck converter is a type of DC/DC converter that decreases the voltage (while increasing the current) from its input (power supply) to its output (load). It is similar to a boost converter (elevator) and is a type of switched-mode power supply (SMPS) that typically contains at least two semiconductors (a diode and a transistor, although modern buck converters replace the diode with a second transistor used for synchronous rectification) and at least one energy storage element, a capacitor, inductor or both combined.
" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -42,7 +51,8 @@ "from sysidentpy.basis_function._basis_function import Polynomial\n", "from sysidentpy.utils.display_results import results\n", "from sysidentpy.utils.plotting import plot_results\n", - "from sysidentpy.metrics import root_relative_squared_error" + "from sysidentpy.metrics import root_relative_squared_error\n", + "from sysidentpy.utils.narmax_tools import set_weights" ] }, { @@ -77,9 +87,8 @@ } ], "source": [ - "# Reading Buck's input and output data\n", - "df_train = pd.read_csv(r'examples/datasets/buck_id.csv')\n", - "df_valid = pd.read_csv(r'examples/datasets/buck_valid.csv')\n", + "df_train = pd.read_csv(r'datasets/buck_id.csv')\n", + "df_valid = pd.read_csv(r'datasets/buck_valid.csv')\n", "\n", "# Plotting the measured output (identification and validation data)\n", "plt.figure(1)\n", @@ -133,14 +142,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Buck Converter Static Function\n", + "### Buck Converter Static Function\n", + "\n", + "The duty cycle, represented by the symbol $D$, is defined as the ratio of the time the system is on ($T_{on}$​) to the total operation cycle time ($T$). Mathematically, this can be expressed as $D=\\frac{T_{on}}{T}$. The complement of the duty cycle, represented by $D'$, is defined as the ratio of the time the system is off ($T_{off}$) to the total operation cycle time ($T$) and can be expressed as $D'=\\frac{T_{off}}{T}$.\n", + "\n", + "The load voltage ($V_o$) is related to the source voltage ($V_d$) by the equation $V_o​=D⋅V_d​=(1−D’)⋅V_d$. For this particular converter, it is known that $D′=\\frac{\\bar{u}-1}{3}​$,​ which means that the static function of this system can be derived from theory to be:\n", "\n", - "The duty cycle is defined by $D=\\frac{T_{on}}{T}$ and its complement is $D'=\\frac{T_{off}}{T}$ , where T is the operation cycle. The load voltage $V_o$ relates to the source voltage $V_d$ as $V_o = D\\cdot V_d = (1 − D’)\\cdot V_d$. This converter satisfies $D' = \\frac{\\bar{u}-1}{3}$ and therefore the static function of this system is known from theory to be:\n", "$$\n", "V_o = \\frac{4V_d}{3} - \\frac{V_d}{3}\\cdot \\bar{u}\n", "$$\n", "\n", - "assuming $V_d = 24\\:V $, the expression can be rewritten as follows:\n", + "If we assume that the source voltage $V_d$​ is equal to 24 V, then we can rewrite the above expression as follows:\n", "\n", "$$\n", "V_o = (4 - \\bar{u})\\cdot 8\n", @@ -190,15 +202,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Buck converter Static Gain\n", + "### Buck converter Static Gain\n", "\n", - "The gain of the Buck converter can be described as the derivative of the static function, which is described by:\n", + "The gain of a Buck converter is a measure of how its output voltage changes in response to changes in its input voltage. Mathematically, the gain can be calculated as the derivative of the converter’s static function, which describes the relationship between its input and output voltages.\n", + "In this case, the static function of the Buck converter is given by the equation:\n", "\n", "$$\n", "V_o = (4 - \\bar{u})\\cdot 8\n", "$$\n", "\n", - "so $gain=V_o'=-8$\n" + "Taking the derivative of this equation with respect to $\\hat{u}$, we find that the gain of the Buck converter is equal to −8. In other words, for every unit increase in the input voltage $\\hat{u}$, the output voltage Vo​ will decrease by 8 units.\n", + "\n", + "so $gain=V_o'=-8$" ] }, { @@ -237,15 +252,10 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "Information about static function and static gain, together with the usual input/output data, have been used as sources of affine information to estimate the parameters of the model. The composite cost function is:\n", - "\n", - "$$\n", - "\\gamma(\\hat\\theta) = w_1\\cdot J_{LS}(\\hat{\\theta})+w_2\\cdot J_{SF}(\\hat{\\theta})+w_3\\cdot J_{SG}(\\hat{\\theta})\n", - "$$\n" + "### Building a dynamic model using the mono-objective approach" ] }, { @@ -262,7 +272,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\Users\\wilso\\Desktop\\projects\\GitHub\\gabriel\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", + "C:\\Users\\wilso\\Desktop\\projects\\GitHub\\gabriel\\sysidentpy\\sysidentpy\\utils\\deprecation.py:37: FutureWarning: Passing a string to define the estimator will rise an error in v0.4.0. \n", " You'll have to use FROLS(estimator=LeastSquares()) instead. \n", " The only change is that you'll have to define the estimator first instead of passing a string like 'least_squares'. \n", " This change will make easier to implement new estimators and it'll improve code readability.\n", @@ -272,7 +282,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -303,46 +313,25 @@ ] }, { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The next step will be to determine the weights of the objectives of interest:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "ExecuteTime": { - "end_time": "2023-07-11T17:36:24.328953300Z", - "start_time": "2023-07-11T17:36:24.294748700Z" - } - }, - "outputs": [], - "source": [ - "# Matrix with the weights associated to each objective.\n", - "W = np.array(\n", - " [\n", - " [0.98, 0.7, 0.5, 0.35, 0.25, 0.01, 0.15, 0.01],\n", - " [0.01, 0.1, 0.3, 0.15, 0.25, 0.98, 0.35, 0.01],\n", - " [0.01, 0.2, 0.2, 0.50, 0.50, 0.01, 0.50, 0.98],\n", - " ]\n", - ")" - ] - }, - { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ + "### Affine Information Least Squares Algorithm (AILS)\n", + "\n", + "AILS is a multiobjective parameter estimation algorithm, based on a set of affine information pairs. The multiobjective approach proposed in the mentioned paper and implemented in SysIdentPy leads to a convex multiobjective optimization problem, which can be solved by AILS. AILS is a LeastSquares-type non-iterative scheme for finding the Pareto-set solutions for the multiobjective problem.\n", "\n", - "with the parameters all in hand, we can already calculate the parameters in a multiobjective way:" + "So, with the model structure defined (we will be using the one built using the dynamic data above), one can estimate the parameters using the multiobjective approach.\n", + "\n", + "The information about static function and static gain, besides the usual dynamic input/output data, can be used to build the pair of affine information to estimate the parameters of the model. We can model the cost function as:\n", + "\n", + "$$\n", + "\\gamma(\\hat\\theta) = w_1\\cdot J_{LS}(\\hat{\\theta})+w_2\\cdot J_{SF}(\\hat{\\theta})+w_3\\cdot J_{SG}(\\hat{\\theta})\n", + "$$\n" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.328953300Z", @@ -351,8 +340,23 @@ }, "outputs": [], "source": [ - "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", - "mult = AILS(final_model=model.final_model)" + "# you can use any set of model structure you want in your use case\n", + "mo_estimator = AILS(final_model=model.final_model)\n", + "\n", + "# setting the log-spaced weights of each objective function\n", + "w = set_weights(static_function=True, static_gain=True)\n", + "\n", + "# you can also use something like\n", + "\n", + "# w = np.array(\n", + "# [\n", + "# [0.98, 0.7, 0.5, 0.35, 0.25, 0.01, 0.15, 0.01],\n", + "# [0.01, 0.1, 0.3, 0.15, 0.25, 0.98, 0.35, 0.01],\n", + "# [0.01, 0.2, 0.2, 0.50, 0.50, 0.01, 0.50, 0.98],\n", + "# ]\n", + "# )\n", + "\n", + "# to set the weights. Each row correspond to each objective" ] }, { @@ -360,12 +364,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "now the method will be called to calculate the matrix of the performance of the objectives (J), weights (w), the Euclidean norm (E), the thetas referring to each weight (Theta), matrix H multiplied by R and the matrix Q multiplied by R.\n" + "AILS has an `estimate` method that returns the cost functions (J), the Euclidean norm of the cost functions (E), the estimated parameters referring to each weight (theta), the regressor matrix of the gain and static_function affine information HR and QR, respectively.\n" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.435488200Z", @@ -410,7 +414,7 @@ " 0.003078\n", " 0.990080\n", " 0.999970\n", - " 1.095046e-05\n", + " 1.095045e-05\n", " 0.000013\n", " 0.245244\n", " \n", @@ -420,7 +424,7 @@ " 0.002347\n", " 0.990080\n", " 0.999938\n", - " 2.294674e-05\n", + " 2.294701e-05\n", " 0.000016\n", " 0.245236\n", " \n", @@ -430,7 +434,7 @@ " 0.001538\n", " 0.990080\n", " 0.999885\n", - " 6.504949e-05\n", + " 6.505062e-05\n", " 0.000018\n", " 0.245223\n", " \n", @@ -440,7 +444,7 @@ " 0.000642\n", " 0.990080\n", " 0.999717\n", - " 4.505604e-04\n", + " 4.505632e-04\n", " 0.000021\n", " 0.245183\n", " \n", @@ -450,7 +454,7 @@ " 0.098663\n", " 0.894495\n", " 1.000000\n", - " 7.393244e-08\n", + " 7.393225e-08\n", " 0.000015\n", " 0.245252\n", " \n", @@ -481,7 +485,7 @@ " 0.006842\n", " 0.995632\n", " 5.602985e-04\n", - " 0.972842\n", + " 0.972841\n", " 0.244412\n", " \n", " \n", @@ -521,14 +525,14 @@ ], "text/plain": [ " w1 w2 w3 J_ls J_sg J_sf ||J||:\n", - "0 0.006842 0.003078 0.990080 0.999970 1.095046e-05 0.000013 0.245244\n", - "1 0.007573 0.002347 0.990080 0.999938 2.294674e-05 0.000016 0.245236\n", - "2 0.008382 0.001538 0.990080 0.999885 6.504949e-05 0.000018 0.245223\n", - "3 0.009277 0.000642 0.990080 0.999717 4.505604e-04 0.000021 0.245183\n", - "4 0.006842 0.098663 0.894495 1.000000 7.393244e-08 0.000015 0.245252\n", + "0 0.006842 0.003078 0.990080 0.999970 1.095045e-05 0.000013 0.245244\n", + "1 0.007573 0.002347 0.990080 0.999938 2.294701e-05 0.000016 0.245236\n", + "2 0.008382 0.001538 0.990080 0.999885 6.505062e-05 0.000018 0.245223\n", + "3 0.009277 0.000642 0.990080 0.999717 4.505632e-04 0.000021 0.245183\n", + "4 0.006842 0.098663 0.894495 1.000000 7.393225e-08 0.000015 0.245252\n", "... ... ... ... ... ... ... ...\n", "2290 0.659632 0.333527 0.006842 0.995896 3.965701e-04 1.000000 0.244489\n", - "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972842 0.244412\n", + "2291 0.730119 0.263039 0.006842 0.995632 5.602985e-04 0.972841 0.244412\n", "2292 0.808139 0.185020 0.006842 0.995364 8.321075e-04 0.868299 0.244300\n", "2293 0.894495 0.098663 0.006842 0.995100 1.365000e-03 0.660485 0.244160\n", "2294 0.990080 0.003078 0.006842 0.992584 9.825994e-02 0.305492 0.261455\n", @@ -536,15 +540,14 @@ "[2295 rows x 7 columns]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Method to calculate the parameters\n", - "J, w, E, Theta, HR, QR, position = mult.affine_information_least_squares(\n", - " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=model.psi\n", + "J, E, theta, HR, QR, position = mo_estimator.estimate(\n", + " X=x_train, y=y_train, gain=gain, y_static=Yo, X_static=Uo, weighing_matrix=w\n", ")\n", "result = {\n", " \"w1\": w[0, :],\n", @@ -563,12 +566,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "now we can choose a theta value referring to the weights:" + "Now we can set theta related to any weight results" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.522223600Z", @@ -605,50 +608,50 @@ " \n", " \n", " 0\n", - " y(k-1)\n", - " 3.0979E-01\n", + " 1\n", + " 2.2930E+00\n", " 9.999E-01\n", " \n", " \n", " 1\n", - " y(k-2)\n", - " 6.4935E-01\n", + " y(k-1)\n", + " 2.3307E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", - " x1(k-1)y(k-1)\n", - " 2.1891E-04\n", + " y(k-2)\n", + " 6.3209E-01\n", " 1.108E-06\n", " \n", " \n", " 3\n", - " 1\n", - " 1.2835E+00\n", + " x1(k-1)\n", + " -5.9333E-01\n", " 4.688E-06\n", " \n", " \n", " 4\n", " y(k-1)^2\n", - " 2.8345E-01\n", + " 2.7673E-01\n", " 3.922E-07\n", " \n", " \n", " 5\n", - " x1(k-1)\n", - " -3.2103E-01\n", + " y(k-2)y(k-1)\n", + " -5.3228E-01\n", " 8.389E-07\n", " \n", " \n", " 6\n", - " y(k-2)y(k-1)\n", - " -5.4834E-01\n", + " x1(k-1)y(k-1)\n", + " 1.6667E-02\n", " 5.690E-07\n", " \n", " \n", " 7\n", " y(k-2)^2\n", - " 2.6492E-01\n", + " 2.5766E-01\n", " 3.827E-06\n", " \n", " \n", @@ -657,24 +660,25 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 3.0979E-01 9.999E-01\n", - "1 y(k-2) 6.4935E-01 2.042E-05\n", - "2 x1(k-1)y(k-1) 2.1891E-04 1.108E-06\n", - "3 1 1.2835E+00 4.688E-06\n", - "4 y(k-1)^2 2.8345E-01 3.922E-07\n", - "5 x1(k-1) -3.2103E-01 8.389E-07\n", - "6 y(k-2)y(k-1) -5.4834E-01 5.690E-07\n", - "7 y(k-2)^2 2.6492E-01 3.827E-06" + "0 1 2.2930E+00 9.999E-01\n", + "1 y(k-1) 2.3307E-01 2.042E-05\n", + "2 y(k-2) 6.3209E-01 1.108E-06\n", + "3 x1(k-1) -5.9333E-01 4.688E-06\n", + "4 y(k-1)^2 2.7673E-01 3.922E-07\n", + "5 y(k-2)y(k-1) -5.3228E-01 8.389E-07\n", + "6 x1(k-1)y(k-1) 1.6667E-02 5.690E-07\n", + "7 y(k-2)^2 2.5766E-01 3.827E-06" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Writing the results\n", - "model.theta = Theta[0, :].reshape(-1, 1)\n", + "model.theta = theta[-1, :].reshape(-1, 1) # setting the theta estimated for the first combination of the weights\n", + "# the model structure is exactly the same, but the order of the regressors is changed in estimate method. Thats why you have to change the model.final_model\n", + "model.final_model = mo_estimator.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", @@ -696,12 +700,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Plotting dynamic data:" + "### The dynamic results for that chosen theta is" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.667179100Z", @@ -711,7 +715,7 @@ "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -729,12 +733,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "the static gain graphically:" + "### The static gain result is" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.793210700Z", @@ -744,7 +748,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -784,12 +788,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "the static function graphically:" + "### The static function result is" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:24.902396Z", @@ -799,7 +803,68 @@ "outputs": [ { "data": { - "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(5)\n", + "plt.title(\"Static Curve\")\n", + "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", + "plt.plot(\n", + " Uo,\n", + " QR.dot(model.theta),\n", + " linewidth=1.5,\n", + " label=\"NARX ​​static representation\",\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.xlabel(\"$\\\\bar{y}$\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Getting the best weight combination based on the norm of the cost function" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", 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" ] @@ -809,6 +874,50 @@ } ], "source": [ + "model.theta = theta[position, :].reshape(-1, 1) # setting the theta estimated for the best combination of the weights\n", + "# the model structure is exactly the same, but the order of the regressors is changed in estimate method. Thats why you have to change the model.final_model\n", + "model.final_model = mo_estimator.final_model\n", + "yhat = model.predict(X=x_valid, y=y_valid)\n", + "rrse = root_relative_squared_error(y_valid, yhat)\n", + "r = pd.DataFrame(\n", + " results(\n", + " model.final_model,\n", + " model.theta,\n", + " model.err,\n", + " model.n_terms,\n", + " err_precision=3,\n", + " dtype=\"sci\",\n", + " ),\n", + " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", + ")\n", + "r\n", + "### The dynamic results for that chosen theta is\n", + "plot_results(y=y_valid, yhat=yhat, n=1000)\n", + "### The static gain result is\n", + "plt.figure(4)\n", + "plt.title(\"Gain\")\n", + "plt.plot(\n", + " Uo,\n", + " gain,\n", + " linewidth=1.5,\n", + " linestyle=\"-\",\n", + " marker=\"o\",\n", + " label=\"Buck converter static gain\",\n", + ")\n", + "plt.plot(\n", + " Uo,\n", + " HR.dot(model.theta),\n", + " linestyle=\"-\",\n", + " marker=\"^\",\n", + " linewidth=1.5,\n", + " label=\"NARX model gain\",\n", + ")\n", + "plt.xlabel(\"$\\\\bar{u}$\")\n", + "plt.ylabel(\"$\\\\bar{g}$\")\n", + "plt.ylim(-16, 0)\n", + "plt.legend()\n", + "plt.show()\n", + "### The static function result is\n", "plt.figure(5)\n", "plt.title(\"Static Curve\")\n", "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", @@ -831,12 +940,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "pareto-optimal curve:" + "You can also plot the pareto-set solutions" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.014411600Z", @@ -846,7 +955,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -859,31 +968,38 @@ "plt.figure(6)\n", "ax = plt.axes(projection=\"3d\")\n", "ax.plot3D(J[0, :], J[1, :], J[2, :], \"o\", linewidth=0.1)\n", - "ax.set_title(\"Optimum pareto-curve\", fontsize=15)\n", + "ax.set_title(\"Pareto-set solutions\", fontsize=15)\n", "ax.set_xlabel(\"$J_{ls}$\", fontsize=10)\n", "ax.set_ylabel(\"$J_{sg}$\", fontsize=10)\n", "ax.set_zlabel(\"$J_{sf}$\", fontsize=10)\n", "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Details about the method" + ] + }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "The found NARX polynomial model was:\n", + "The polynomial NARX model built using the mono-objective approach has the following structure:\n", "\n", "$$\n", "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 u(k-1) y(k-1) + \\theta_4 + \\theta_5 y(k-1)^2 + \\theta_6 u(k-1) + \\theta_7 y(k-2)y(k-1) + \\theta_8 y(k-2)^2\n", "$$\n", "\n", - "the goal is to estimate the vector $\\hat{\\theta}$, parting from:\n", + "The, the goal when using the static function and static gain information in the multiobjective scenario is to estimate the vector $\\hat{\\theta}$ based on:\n", "\n", "$$\n", "\\theta = [w_1\\Psi^T\\Psi + w_2(HR)^T(HR) + w_3(QR)(QR)^T]^{-1} [w_1\\Psi^T y + w_2(HR)^T\\overline{g}+w_3(QR)^T\\overline{y}]\n", "$$\n", "\n", - "the $\\Psi$ matrix is provided by SysIdentPy. However, it is still necessary to find the Q, H and R matrices. To do this, $q_i^T$ is first estimated:\n", + "The $\\Psi$ matrix is built using the usual mono-objective dynamic modeling approach in SysIdentPy. However, it is still necessary to find the Q, H and R matrices. AILS have the methods to compute all of those matrices. Basically, to do that, $q_i^T$ is first estimated:\n", "\n", "$$\n", "q_i^T = \n", @@ -892,8 +1008,7 @@ "\\end{bmatrix}\n", "$$\n", "\n", - "where $F_{yu}$ stands for all non-linear monomials inthe model that involve $y(k)$ and $u(k)$, $l$ is the largestnon-linearity in the model and need not be the samefor input and output terms. For a model with a degree of nonlinearity equal to 2, matrix-wise the following is obtained:\n", - "\n", + "where $F_{yu}$ stands for all non-linear monomials in the model that are related to $y(k)$ and $u(k)$, $l$ is the largest non-linearity in the model for input and output terms. For a model with a degree of nonlinearity equal to 2, we can obtain:\n", "\n", "$$\n", "q_i^T = \n", @@ -902,8 +1017,7 @@ "\\end{bmatrix}\n", "$$\n", "\n", - "here, it is possible to encode the $q_i^T$ matrix so that it is in compliance with SysIdentPy. To do this, 0 is considered as a constant, $y_i$ equal to 1 and $u_i$ equal to 2. The number of columns indicates the degree of nonlinearity of the system and the number of rows reflects the number of terms in the mode:\n", - "\n", + "It is possible to encode the $q_i^T$ matrix so that it follows the model encoding defined in SysIdentPy. To do this, 0 is considered as a constant, $y_i$ equal to 1 and $u_i$ equal to 2. The number of columns indicates the degree of nonlinearity of the system and the number of rows reflects the number of terms:\n", "\n", "$$\n", "q_i = \n", @@ -926,12 +1040,12 @@ "\\end{bmatrix}\n", "$$\n", "\n", - "the result can be easily obtained using the ‘regressor_space’ method of SysIdentPy:" + "Finally, the result can be easily obtained using the ‘regressor_space’ method of SysIdentPy" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.017591800Z", @@ -953,11 +1067,11 @@ } ], "source": [ - "from sysidentpy.narmax_base import RegressorDictionary # Importing the class.\n", + "from sysidentpy.narmax_base import RegressorDictionary\n", "\n", "object_qit = RegressorDictionary(\n", - " xlag=[1], ylag=[1]\n", - ") # The lag of the input and output equal to 1 ensures that there will be no repetition of terms in qit.\n", + " xlag=1, ylag=1\n", + ")\n", "R_example = object_qit.regressor_space(n_inputs=1) // 1000\n", "print(f\"R = {R_example}\")" ] @@ -979,7 +1093,9 @@ "\\overline{g_i} = H R\\theta\n", "$$\n", "\n", - "the $R$ matrix is the linear mapping of the static regressors represented by $q_i^T$. In addition, the $H$ matrix contains affine information regarding $\\overline{g_i}$, which is equal to $\\overline{g_i} = \\frac{d\\overline{y}}{d\\overline{u}}{\\big |}_{(\\overline{u_i}\\:\\overline{y_i})}$. From now on, we will begin to apply the estimation of parameters in a multi-objective manner. This will be done with the NARX polynomial model of the BUCK converter in mind. In this context, $q_i^T$ will cease to be generic and will assume a specific format for the problem at hand. For this task, the $R_qit$ method will be used, whose objective is to return the $q_i^T$ related to the model and the matrix of the linear mapping $R$:" + "where $R$ is the linear mapping of the static regressors represented by $q_i^T$. In addition, the $H$ matrix holds affine information regarding $\\overline{g_i}$, which is equal to $\\overline{g_i} = \\frac{d\\overline{y}}{d\\overline{u}}{\\big |}_{(\\overline{u_i}\\:\\overline{y_i})}$.\n", + "\n", + "From now on, we will begin to apply the parameter estimation in a multiobjective manner. This will be done with the NARX polynomial model of the BUCK converter in mind. In this context, $q_i^T$ will be generic and will assume a specific format for the problem at hand. For this task, the $R_qit$ method will be used, whose objective is to return the $q_i^T$ related to the model and the matrix of the linear mapping $R$:" ] }, { @@ -997,22 +1113,22 @@ "output_type": "stream", "text": [ "R matrix:\n", - "[[0 0 0 1 0 0 0 0]\n", - " [1 1 0 0 0 0 0 0]\n", - " [0 0 0 0 0 1 0 0]\n", - " [0 0 0 0 1 0 1 1]\n", - " [0 0 1 0 0 0 0 0]]\n", + "[[1 0 0 0 0 0 0 0]\n", + " [0 1 1 0 0 0 0 0]\n", + " [0 0 0 1 0 0 0 0]\n", + " [0 0 0 0 1 1 0 1]\n", + " [0 0 0 0 0 0 1 0]]\n", "qit matrix:\n", - "[[0. 0.]\n", - " [1. 0.]\n", - " [0. 1.]\n", - " [2. 0.]\n", - " [1. 1.]]\n" + "[[0 0]\n", + " [1 0]\n", + " [0 1]\n", + " [2 0]\n", + " [1 1]]\n" ] } ], "source": [ - "R, qit = mult.build_linear_mapping()\n", + "R, qit = mo_estimator.build_linear_mapping()\n", "print(\"R matrix:\")\n", "print(R)\n", "print(\"qit matrix:\")\n", @@ -1024,7 +1140,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "immediately:" + "So" ] }, { @@ -1051,7 +1167,7 @@ "\\end{bmatrix}\n", "$$\n", "\n", - "upon returning to the model, it is possible to observe that the method produces outputs consistent with what is expected:\n", + "You can notice that the method produces outputs consistent with what is expected:\n", "\n", "$$\n", "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 u(k-1) y(k-1) + \\theta_4 + \\theta_5 y(k-1)^2 + \\theta_6 u(k-1) + \\theta_7 y(k-2)y(k-1) + \\theta_8 y(k-2)^2\n", @@ -1085,7 +1201,7 @@ "source": [ "## Validation\n", "\n", - "Model's structure that will be utilized:\n", + "The following model structure will be used to validate the approach:\n", "\n", "$$\n", "y(k) = \\theta_1 y(k-1) + \\theta_2 y(k-2) + \\theta_3 + \\theta_4 u(k-1) + \\theta_5 u(k-1)^2 + \\theta_6 u(k-2)u(k-1)+\\theta_7 u(k-2) + \\theta_8 u(k-2)^2\n", @@ -1165,7 +1281,6 @@ }, "outputs": [], "source": [ - "# Calling the class referring to the calculation of the parameters via the multiobjective technique\n", "mult2 = AILS(final_model=model_final)" ] }, @@ -1199,7 +1314,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "the value of theta with the lowest mean squared error obtained through the routine in Scilab was:\n", + "The value of theta with the lowest mean squared error obtained with the same code implemented in Scilab was:\n", "\n", "$$\n", "W_{LS} = 0,3612343\n", @@ -1220,7 +1335,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.101857500Z", @@ -1230,12 +1345,12 @@ "outputs": [], "source": [ "PSI = psi(x_train, y_train)\n", - "W = np.array([[0.3612343], [0.2838959], [0.3548699]])" + "w = np.array([[0.3612343], [0.2838959], [0.3548699]])" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.122382900Z", @@ -1293,14 +1408,14 @@ "0 0.361234 0.35487 0.283896 1.0 1.0 1.0 1.0" ] }, - "execution_count": 21, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "J, w, E, Theta, HR, QR, position = mult2.affine_information_least_squares(\n", - " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + "J, E, theta, HR, QR, position = mult2.estimate(\n", + " y=y_train, X=x_train, gain=gain, y_static=Yo, X_static=Uo, weighing_matrix=w\n", ")\n", "result = {\n", " \"w1\": w[0, :],\n", @@ -1311,6 +1426,7 @@ " \"J_sf\": J[2, :],\n", " \"||J||:\": E,\n", "}\n", + "# the order of the weights is different because the way we implemented in Python, but the results are very close as expected\n", "pd.DataFrame(result)" ] }, @@ -1319,12 +1435,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "dynamic data in graphical form:" + "Dynamic results" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.123384200Z", @@ -1361,20 +1477,20 @@ " \n", " \n", " 0\n", - " y(k-1)\n", - " 5.5147E-01\n", + " 1\n", + " 1.4287E+00\n", " 9.999E-01\n", " \n", " \n", " 1\n", - " y(k-2)\n", - " 4.0449E-01\n", + " y(k-1)\n", + " 5.5147E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", - " 1\n", - " 1.4287E+00\n", + " y(k-2)\n", + " 4.0449E-01\n", " 1.108E-06\n", " \n", " \n", @@ -1385,20 +1501,20 @@ " \n", " \n", " 4\n", - " x1(k-1)^2\n", - " 8.3274E+00\n", + " x1(k-2)\n", + " 1.2257E+01\n", " 3.922E-07\n", " \n", " \n", " 5\n", - " x1(k-2)x1(k-1)\n", - " -1.1416E+01\n", + " x1(k-1)^2\n", + " 8.3274E+00\n", " 8.389E-07\n", " \n", " \n", " 6\n", - " x1(k-2)\n", - " 1.2257E+01\n", + " x1(k-2)x1(k-1)\n", + " -1.1416E+01\n", " 5.690E-07\n", " \n", " \n", @@ -1413,25 +1529,24 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 5.5147E-01 9.999E-01\n", - "1 y(k-2) 4.0449E-01 2.042E-05\n", - "2 1 1.4287E+00 1.108E-06\n", + "0 1 1.4287E+00 9.999E-01\n", + "1 y(k-1) 5.5147E-01 2.042E-05\n", + "2 y(k-2) 4.0449E-01 1.108E-06\n", "3 x1(k-1) -1.2605E+01 4.688E-06\n", - "4 x1(k-1)^2 8.3274E+00 3.922E-07\n", - "5 x1(k-2)x1(k-1) -1.1416E+01 8.389E-07\n", - "6 x1(k-2) 1.2257E+01 5.690E-07\n", + "4 x1(k-2) 1.2257E+01 3.922E-07\n", + "5 x1(k-1)^2 8.3274E+00 8.389E-07\n", + "6 x1(k-2)x1(k-1) -1.1416E+01 5.690E-07\n", "7 x1(k-2)^2 3.0846E+00 3.827E-06" ] }, - "execution_count": 22, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1, 1)\n", - "model.final_model = model_final\n", + "model.theta = theta[position, :].reshape(-1, 1)\n", + "model.final_model = mult2.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", @@ -1450,7 +1565,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.276007600Z", @@ -1478,12 +1593,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "the static gain graphically:" + "Static gain" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.383278600Z", @@ -1533,12 +1648,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "the static function graphically:" + "Static function" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.471991600Z", @@ -1548,7 +1663,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -1580,12 +1695,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "pareto-optimal curve:" + "Pareto-set solutions" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.557244700Z", @@ -1615,17 +1730,9 @@ "plt.show()" ] }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "comparison between the norm of the objectives and specifying the \"best $\\theta$\" in relation to this approach:" - ] - }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.561257100Z", @@ -1636,17 +1743,17 @@ { "data": { "text/plain": [ - "array([ 0.5514725 , 0.40449005, 1.42867821, -12.60548844,\n", - " 8.32740046, -11.41574101, 12.25729936, 3.08461192])" + "array([ 1.42867821, 0.5514725 , 0.40449005, -12.60548863,\n", + " 12.25729955, 8.32740057, -11.41574116, 3.08461195])" ] }, - "execution_count": 27, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Theta[position, :]" + "theta[position, :]" ] }, { @@ -1654,50 +1761,25 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "here is an improved version of the text: 'The approach of the weight matrix was not the same as addressed in ‘IniciacaoCientifica2007’. However, the results were quite similar, with the exception of the constant term. Recapping, this routine provides me with:" + "The following table show the results reported in ‘IniciacaoCientifica2007’ and the ones obtained with SysIdentPy implementation" ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,5514724\\\\\n", - "\\theta_2 = 0,40449004,\\\\\n", - "\\theta_3 = 1,42868214\\\\\n", - "\\theta_4 = -12,60549003\\\\\n", - "\\theta_5 = 8,32739763\\\\\n", - "\\theta_6 = -11,41573513\\\\\n", - "\\theta_7 = 12,25729978\\\\\n", - "\\theta_8 = 3,08460885\\\\\n", - "\\end{matrix}\n", - "$$\n" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "and ‘IniciacaoCientifica2007’ provides:\n", - "\n", - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,549144\\\\\n", - "\\theta_2 = 0,408028\\\\\n", - "\\theta_3 = 1,45097\\\\\n", - "\\theta_4 = -12,557882\\\\\n", - "\\theta_5 = 8,1516315\\\\\n", - "\\theta_6 = -11,097284\\\\\n", - "\\theta_7 = 12,215782\\\\\n", - "\\theta_8 = 2,9319577\\\\\n", - "\\end{matrix}\n", - "$$\n", - "\n", - "whereas:\n", - "\n", + "| Variable | Value | Value2 |\n", + "|----------|--------------|--------------|\n", + "| θ₁ | 0.5514725 | 0.549144 |\n", + "| θ₂ | 0.40449005 | 0.408028 |\n", + "| θ₃ | 1.42867821 | 1.45097 |\n", + "| θ₄ | -12.60548863 | -12.55788 |\n", + "| θ₅ | 8.32740057 | 8.1516315 |\n", + "| θ₆ | -11.41574116 | -11.09728 |\n", + "| θ₇ | 12.25729955 | 12.215782 |\n", + "| θ₈ | 3.08461195 | 2.9319577 |\n", + "\n", + "where:\n", "$$\n", "E_{Scilab} = 17,426613\n", "$$\n", @@ -1711,7 +1793,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.565769100Z", @@ -1724,15 +1806,15 @@ "output_type": "stream", "text": [ "R matrix:\n", - "[[0 0 1 0 0 0 0 0]\n", - " [1 1 0 0 0 0 0 0]\n", - " [0 0 0 1 0 0 1 0]\n", - " [0 0 0 0 1 1 0 1]]\n", + "[[1 0 0 0 0 0 0 0]\n", + " [0 1 1 0 0 0 0 0]\n", + " [0 0 0 1 1 0 0 0]\n", + " [0 0 0 0 0 1 1 1]]\n", "qit matrix:\n", - "[[0. 0.]\n", - " [1. 0.]\n", - " [0. 1.]\n", - " [0. 2.]]\n" + "[[0 0]\n", + " [1 0]\n", + " [0 1]\n", + " [0 2]]\n" ] } ], @@ -1813,12 +1895,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Biobjective otimization of the model's parameters for prediction of output voltage of the Buck converter CC-CC using as objectives the static curve information and the prediction error " + "### Biobjective optimization: An use case applied to Buck converter CC-CC using as objectives the static curve information and the prediction error (dynamic) " ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.568942Z", @@ -1827,8 +1909,7 @@ }, "outputs": [], "source": [ - "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", - "mult3 = AILS(static_function=True, static_gain=False, final_model=model_final, normalize=True)" + "bi_objective = AILS(static_function=True, static_gain=False, final_model=model_final, normalize=True)" ] }, { @@ -1851,7 +1932,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.660520200Z", @@ -1998,17 +2079,17 @@ "[2000 rows x 5 columns]" ] }, - "execution_count": 30, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "W = np.zeros((2, 2000))\n", - "W[0, :] = np.logspace(-0.01, -6, num=2000, base=2.71)\n", - "W[1, :] = np.ones(2000) - W[0, :]\n", - "J, w, E, Theta, HR, QR, position = mult3.affine_information_least_squares(\n", - " y_train=y_train[2:], y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + "w = np.zeros((2, 2000))\n", + "w[0, :] = np.logspace(-0.01, -6, num=2000, base=2.71)\n", + "w[1, :] = np.ones(2000) - w[0, :]\n", + "J, E, theta, HR, QR, position = bi_objective.estimate(\n", + " y=y_train, X=x_train, y_static=Yo, X_static=Uo, weighing_matrix=w\n", ")\n", "result = {\"w1\": w[0, :], \"w2\": w[1, :], \"J_ls\": J[0, :], \"J_sg\": J[1, :], \"||J||:\": E}\n", "pd.DataFrame(result)" @@ -2016,7 +2097,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 44, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.775500300Z", @@ -2053,20 +2134,20 @@ " \n", " \n", " 0\n", - " y(k-1)\n", - " 5.4941E-01\n", + " 1\n", + " 1.3873E+00\n", " 9.999E-01\n", " \n", " \n", " 1\n", - " y(k-2)\n", - " 4.0804E-01\n", + " y(k-1)\n", + " 5.4941E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", - " 1\n", - " 1.3873E+00\n", + " y(k-2)\n", + " 4.0804E-01\n", " 1.108E-06\n", " \n", " \n", @@ -2077,20 +2158,20 @@ " \n", " \n", " 4\n", - " x1(k-1)^2\n", - " 8.1171E+00\n", + " x1(k-2)\n", + " 1.2227E+01\n", " 3.922E-07\n", " \n", " \n", " 5\n", - " x1(k-2)x1(k-1)\n", - " -1.1047E+01\n", + " x1(k-1)^2\n", + " 8.1171E+00\n", " 8.389E-07\n", " \n", " \n", " 6\n", - " x1(k-2)\n", - " 1.2227E+01\n", + " x1(k-2)x1(k-1)\n", + " -1.1047E+01\n", " 5.690E-07\n", " \n", " \n", @@ -2105,25 +2186,24 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 5.4941E-01 9.999E-01\n", - "1 y(k-2) 4.0804E-01 2.042E-05\n", - "2 1 1.3873E+00 1.108E-06\n", + "0 1 1.3873E+00 9.999E-01\n", + "1 y(k-1) 5.4941E-01 2.042E-05\n", + "2 y(k-2) 4.0804E-01 1.108E-06\n", "3 x1(k-1) -1.2515E+01 4.688E-06\n", - "4 x1(k-1)^2 8.1171E+00 3.922E-07\n", - "5 x1(k-2)x1(k-1) -1.1047E+01 8.389E-07\n", - "6 x1(k-2) 1.2227E+01 5.690E-07\n", + "4 x1(k-2) 1.2227E+01 3.922E-07\n", + "5 x1(k-1)^2 8.1171E+00 8.389E-07\n", + "6 x1(k-2)x1(k-1) -1.1047E+01 5.690E-07\n", "7 x1(k-2)^2 2.9043E+00 3.827E-06" ] }, - "execution_count": 31, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1, 1)\n", - "model.final_model = model_final\n", + "model.theta = theta[position, :].reshape(-1, 1)\n", + "model.final_model = bi_objective.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", @@ -2142,7 +2222,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 45, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.870151400Z", @@ -2167,7 +2247,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 46, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.956170500Z", @@ -2177,7 +2257,7 @@ "outputs": [ { "data": { - "image/png": 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", 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vY7FYWLhwIW+99Vam55KSkvjjjz+IjIzE29ubv//+m3Llyt33HklJSdy8eRMPDw8Ahg4dSq9evRg8eDCvvvoqr7322n1fExwczLlz50hNTSUgIABPT09+++03YmNjqVGjBtHR0fz666+kp6fj4eFBeHg4s2fP5sSJE3z99ddomkb58uXp0aMHEydOZP/+/ZhMJv71r3/RsmVL6/cJDw9nz5493Lp1i08++YRt27bxyy+/oCgK7du3p0+fPgQHB6NpGhcvXuTWrVtMmTIFNzc3Bg0aRJkyZWjWrBnNmjVj4sSJAJQpU4ZJkyZhMpkYMmQImqZhMpkYN24czzzzDAsWLLD5PYxGIxcuXODKlSuEhYVx9epV67K0ixYtIjw8nIMHD5KUlET16tWZPHkys2fP5siRIyxdupQ9e/bQvn17XnnlFUJCQjh//jxms5l+/frRvn17/P39efbZZzl+/DiJiYlMmzaNJ554uB6TbbMuUaIE06ZNu+/4ncXOnZKdLLt1cCTj9d9jQsWIGaOSznJjqGTZIneun4M7U7CmQcI5eKTGQ71laGgoPj4+NGnSJNPxtWvX0qpVK9zc3GjXrh0RERG8++67APzyyy/s3buXq1evUrJkSQYOHMhTTz0FZEzrvr6+hIaGWuORuyUmJhITE8OKFSuAjOikTp06NG3alPbt21OxYkUSEhL44Ycf0Ol0BAQEcODAAQYOHMixY8d4//33CQ8PByAqKop//vmHiIgIrl69yo8//pipWUPGmiWjR4/mxIkTrF27lkWLFqEoCn379rV+5ipVqjBlyhQ2b97M1KlTGT16NFevXmXFihUYjUZ8fX2ZNGkSNWrUYPny5Xz77bc0aNAADw8PPv/8c06cOEFiYmKW3+Pxxx9n/PjxLFu2jKVLlzJ+/Hhq1apFaGgoaWlplCpVinnz5mGxWOjQoQOXL19m4MCBLFmyhB49erBnT8baREuXLqVs2bJMnTqVxMREunbtyssvvwxAvXr1GDVqFF9++SWRkZHW/1655fw3xeQhW+uMPKlcYYPbR2xacpkvTlVhVMpncl22yJiAs5iCuXkJpj0P1rhNg5QE6P49eGQfM9hTtmxZQkJCCA4O5oUXXrAeX758OaqqEhAQQEpKCpcuXWLAgAFARgwyfPhwzp8/z4ABA6yNGuDChQt8++23BAYGEhgYyPz581HV/y1A5e7uzpgxYxgzZgyJiYl06tQpUz06nQ6DwcCwYcMoUaIEly5dIj0980+td5w+fdq6CmCFChUYOnTofa+5s3rfsWPHiI+Pp2/fvgBcv36dc+cy1gG/0+waNGjApEmTAKhcubJ1bZOTJ09a/8djMpmoWrUqzZo148yZMwwePBi9Xs+gQYOy/B61atUCoGLFiuzevTtTjW5ubvz999/Wz3zr1i1MJpPNz3zy5Enreizu7u5Ur16d8+cz1kF/7rnnrN/jr7/+svn1OeH0t5vnJXtrZqfgxutHxjE7JVCybPFgNn+aEX/cTbPkSXbdvHlzqlatal03+ujRo5jNZhYvXsx3333HwoUL8fT0tN4DcUeVKlUYO3YsH374IcnJyaSlpTFkyBBCQkLo27cvlSpV4uuvv870NVeuXCE2NpYZM2YwZ84cpk6dSnp6OoqioGkaR44cYcOGDXz11VeMGTMGi8WCpmnodDoslsyfv1q1ataV/G7evElAQMB9n+3OzXPVqlWjRo0azJ8/nwULFtC1a1dq1qwJ/G/Fv927d/P0009n+jrIaPhTpkxhwYIFBAYG4uXlRUxMDI8++ijff/89gwYNska09r7HnavZ7nbnM2/ZsoWLFy/yxRdfMGzYMFJSUux+5urVq7Nz504g46eUY8eOPfR6SPYUqcna3prZ1ynDPFNbgvRLbq+ZvZEZqZ0lyxb2xf0J5rTMx8xpGcfzwKhRo/jjjz+AjKm6c+fOmZ738fFh4cKFdOzYMdPxV199lVdffZXp06eTlpbGiy++iJeXF5ARsdz5Mf3OOtkVKlTg6tWrvPnmm5QoUYL+/fuj1+t5/vnn+eyzz/jiiy8oXrw4Xbt2xWg0UqFCBa5cuUKDBg0wmUxMnTqVYsWKAdCiRQu2b9+On58fZrOZ9957z+7ne/bZZ3nllVfw8/MjLS2NevXqWX/xuWXLFqKiorBYLNb1ve8WGhpKUFAQZnPGT8iffPIJZcqUYejQofz73/9Gp9Px3nvvZfk9bGnQoAEjRoxg1qxZzJw5E19fX4xGI1WqVOHKlSt4enpy7NgxfvjhB+vX+Pr6MmbMGPz8/EhNTeX999/nkUcesfs9HobTr7pXEKrezrJ7qButEclfmgd90kJYO3mwg6sTougIDg6mffv2spekDUUqBrEn47rszFn2I9xkjXEU2+d+SLdJi+W6bCGEQxWpGMQeW2uMmFCJ4zFeufAD32vL8FCSZY0RIfJZWFiYo0twWjJZY3/N7HSdkffT/oUHt9ApGr3UaB4zxckaI0KIAieTNdi9LrvNXddlu2FGxUKkWwhDbrwPNC/YGoUQRZpM1lm4k2W73c6yFQWKk8Zc4+ec/8aXtdv2yjojQogCIZN1Fuxl2Sd1VakeH8Wr8b9T2vIkjXRHJc8WQuQrmayzYCvLdlPSqVWhGL7KZ5zWKvKaekj2fxRC5DuZrLOSxf6P+4MjOah/irrKaev+jzMNX9Ez4eOCrVEIUSTIZJ1Ld9bMvnv/x0bqMX4pNopfo6MkyxZC5CmZrHPJZp6t6XiKeGps9qGiVoU6ylnJsoUQeUIm61yylWcbFAsXlIr8anmRerozsv+jECLPyGSdW3by7FZ3rs3WVAyKGSPpLDBOonvC/WsJCyHEg5LJOo/duTbbcNe12c8ocUS5DWfTzwskyxZC5IpM1nnMVpadjoobaby+6308LY/xlHJFsmwhRI7IZJ3HbGfZZq4o5Zljak9V5TI6RaOnuhF301+SZQshHohM1nntAdYZydj/0cwq48dyXbYQ4oHIZF1AbK2Z/YRyjV/dAtm28BPenLRMsmwhhF0yWRcQe+uM/IMHrx7/lDlaKcorNyXLFkLYJJN1AbG3Znai4sHYtD5U4AY6RcNP3UgZ02XJsoUQmWQ5WZtMJkJCQrhw4QJpaWkMGjSIihUrMnDgQOt2935+frRv374ganVtdrLstvdk2QbFzFq3kfS/HoSsmS2EuCPLZv3TTz9RpkwZpk6dyj///EOXLl1477336NevH/379y+oGgu1uqWT8UnJnGWXIYkVxo/Z+c1hplxryvCU6UwsPoKAti9LNCJEEZVls27bti1t2rSxPlZVlYMHD3L69GmioqJ48sknCQkJwd3dPd8LLazsZdlnqUTDi4v5XltFSSVVsmwhirgsM+uSJUvi7u5OYmIiH3zwAUOGDKFevXqMGDGChQsXUqVKFWbMmFFQtRZK9rJsTafnndShlCTFuv9jJdM5ybKFKKKyvRrk4sWLvPfee/Tq1Qtvb29u3LhBqVKlAGjVqhUTJkzI9yILtRzt/ziK4TcGgvZGxn3sQogiI8vJ+q+//qJ///4EBgbSvXt3AAICAti/fz8A27dvp3bt2vlfZRFka/9HN0zMME4n/puu/GfbbllnRIgiJMvJevbs2dy4cYOZM2cyc+ZMAIKDg5k0aRIGg4Hy5cvLZJ1P7GXZx5Xq1Lj4G00utqes7P8oRJGhaJqmZf+ynImLi6NFixZERUVRuXLlvH77omF2E7h04L7D2mN18b78DmPN4TRSjwOQohlomjoNY5lKbA2Wy/2EKIzkDkZnlcX+j7HBkRzRe9JAO2nd/3G24Qt6JIwt2BqFEAVG7mB0Qbb2f3xRPUFksRDWR62XLFuIQkgmaxdkb/9HTy5TfYsvFTVPasv+j0IUKjJZuyB7+z/GKRVZa25MXdn/UYhCRyZrV2Qnz259z/6Pbko6C4yf4CP7Pwrh8mSyLkTu3f8R4BnlAhvcAmX/RyFcnEzWhYi9/R+Nsv+jEC5PJutCxN7+j1eV8nxj6iD7PwrhwmSyLkxyuP+jXJcthOuQyboIsLf/43q3QLYumkznScslyxbCyclkXQTY3/+xJK8dC2OOVpoKyg3JsoVwYjJZFwH2938sRWiaP49y3br/Y2nZ/1EIpySTdVGQo/0fQ+h7PRjZ/1EI5yKTdRFmK8suSyKrjKO5FBHIzztOyLXZQjgJmayLMHtZ9nmlItUPzqHegTW8b3lC1swWwgnIZF2E2cuyn3q0LP20Meg0M63V3egUDV91s6wzIoQDyWRdlNnJslVgU3Akv+nr4qtsQq9ouGHiU8M39E8IKtgahRCATNbCjrqlk+mq/o5eyYhJFAXeUPfxfbHPWbttr2TZQhQwmayFTTbXGdF0NGU3N9d1oJTFU7JsIQqQTNbCJlt5tl6xcE6pxDntUZqohyTLFqIAyWQtbLOTZ7cIjmS8/jtqK2es+z/OMEyjZ8KYAi5QiKJFJmuRI7b2f2ysHmVNsbH8ummTZNlC5JMsJ2uTyURISAgXLlwgLS2NQYMGUaNGDYKDg1EUhaeffpqxY8ei00nPLyrsZdlPc5aaG7tRweLJ87rTkmULkcey7LI//fQTZcqUYdGiRcydO5cJEyYwefJkhgwZwqJFi9A0jaioqIKqVTgBe1l2nFKJzZZ6NFBPyf6PQuSDLCfrtm3b0qZNG+tjVVWJjY2lcePGADRr1oytW7fSqlWr/K1SOA87WXare/Z/NJLOPOMUfBJCC7Y+IQqpLCfrkiVL4u7uTmJiIh988AFDhgxB0zQURbE+f/PmzQIpVDi3e/d/VBSoozvLerdANvxnuWTZQjykbMPmixcv0qdPHzp37oy3t3emfDopKYlSpUrla4HCNXxVaT0K96wzoqmUIomWMQP4LHkMjZQ712UfkIYtRA5l2az/+usv+vfvT2BgIN27dwfgueeeIyYmBoAtW7bQsGHD/K9SOD17+z9eUh5lQXoLnlbib+//KFm2ELmRZWY9e/Zsbty4wcyZM5k5cyYAo0aNYuLEiXzxxRdUq1YtU6YtirAH3v8xnWXGcZJlC5FDiqZpWvYvy5m4uDhatGhBVFQUlStXzuu3Fy6k0+QIlqUMpJhish7TNLhOCfbWCeGL4xUZlfIZE4uPIKDty3KZnxB2yB2MIl/ZWzPbhIHXY0fztOURKil/y3XZQmRD7mYR+cremtn/KGX5zNSdx5Vr1v0f3U1XJcsWwg6ZrEX+esAs26CY+cVtFL2uj0H2fxTifjJZC4ewtf/jo1xnrTGYCz9PZM2uM3JtthB3kclaOIS9LPuK8ghVdk0lYccy/s/yGI1UWTNbCJDJWjiIvSz78Ucr8IHlIx5T/qG9+ic6RcNH1swWQiZr4SBZ7P/4c3Akr+l30l3dgkrG/o8T9N8zKGFYwdYohBORyVo4nbqlk+msbkO9vf+jToG2+p1MK/YNP8cckSxbFEkyWQunY3vNbAVvNnNxbXtKWKrI/o+iyJHJWjgd22tma5xVKpGsGWih7pX9H0WRI5O1cD528uw3giOZqP+WJ5Ur1v0fPzfM4u2E4AIuUIiCJ5O1cBl1SyfTTf0t0/6PzdQD/FjsU9b+vlOybFGoyWQtXIa9/R9f4gC31nekrOVJybJFoSWTtXAZ9vZ/PKdU4pilMq+oRyTLFoWWTNbCddjJslsERzJe/x31tZPWLHum4Ut6Jowt4AKFyD8yWQuXl7HOyJZMWXYj9Tg/u43mP1EbJMsWhYJM1sLl2VxnRNNRjQvU2OLL45ondZUzkmULlyaTtXB5tvd/tBCnVGKD5QWe151Gp2j0UGX/R+G6ZLIWrs9Olt3qzprZmopBMWMknR+MYXRPGFfABQrx8KRZi0KrbulkfFI2Y7i9ZraiQG3lHOvdhrP2JxOzY1VGJU+V/R+FS5BmLQot21m2Silu0X73u9SwPE4N5aJk2cIlSGYtCi3bWbaZy8qjzE9vxdNKPDpFo6cqWbZwfjJZi8LLTpbd+p79H41KOsuM4yTLFk7tgSbrffv24e/vD0BsbCxNmzbF398ff39/1q5dm68FCpHXbO3/+JRymQ1uwziz6QdW746Ta7OF08l2sp47dy4//fQTxYsXB+DQoUP069eP/v3753txQuQHe/s/mhUDT236kFOWBrxtKSn7Pwqnku1k7enpSXh4uPXxwYMH2bRpE7179yYkJITExMR8LVCIvGZv/8eyj1ZhkuVtXlZi6ar+Lvs/CqeS7WTdpk0b4uLirI/r1auHj48PderUYdasWcyYMYOgoKB8LVKIPJXF/o9zgyOppT9BZ3UrCuCGiVH6Hxma8H6BlijEvXJ8NUirVq2oU6eO9d8PHTqU50UJ4Sh1SyfTTv0TnZLxWKdAZ3UbwcVWsmbXWcmyhcPkuFkHBASwf/9+ALZv307t2rXzvCghHOWrSutRyJxnW1D4PyKouuZN3kmaQyPlTpZ9QBq2KDA5vnQvNDSUCRMmYDAYKF++PBMmTMiPuoRwiGopsXBPnq0qGheowBPKFeqqp1AU8FE3E57alanrjsovHkWBUDRN07J/Wc7ExcXRokULoqKiqFy5cl6/vRAFrmpwJFP0s+mm/oaqaFg0+K+5Ee+lD+V0WAdHlyeKALmDUYgHULd0Mp3U7ahKxmyjU6CduoMpxb5jTcwxybJFvpM7GIV4ALauzbag4EsUZ9d24H1LZdn/UeQrmayFeAC2rs1WFY1zVETRLLRWd8v+jyJfyWQtxIOwc222V3Akn+jn4qtsQq9ouGEizPANAxLk3gORt2SyFuIh1C2dTFf1d/S3s2xFgRbqPua6fcmq3/ZKli3yjEzWQjwEW1l2uqbjDXaQsKEj5S1PSpYt8oRM1kI8BFtZtl6xcE55gotaOZqqByXLFnlCJmshHoadLLt5cCTj9d/xrHIevWLBDRPTDeH0ShhdwAWKwkImayHyQcaa2VvQKxYgI8t+RT1MhHEcl88cZvWeC5JnixyRyVqIfGAvy66rnMQ8rxmxlh74aPGyZrZ4YDJZC5EP7GXZPFKdP7TajFIX0FuNvr1m9hbJs0W2ZLIWIj/YybKNQP/gX5hvmEwT3UEADKTzoX4FYxICCrBA4WpkshaigNUtnUIj3VGU22tm6xULvdRo2peULFvYJ5O1EAXMVp6toBGePoG5K/fRU7spWba4j0zWQhQwW3m2osB13Pk/9Sd6qhslyxb3kclaiIJmJ89+ITiSOYbPaKnbDYARE8P0ywlJeKcgqxNOSiZrIZxE3dLJNNUdsGbZqqLRQ91Iz+J/SpYtZLIWwlnYyrIBJmtfEbFyN701RbLsIkwmayGchK0sW6fAX5TmTd1v+KqbJcsuwmSyFsJZ2MmyGwVH8rV+Gu3UGBQysuxA/RKCEgYWbH3CoWSyFsLJ1S2dTAt1N7q7smwfdQvvFlvPyp3nJcsuImSyFsLJ2cqyNWAk89i4Zjdvax6SZRcBMlkL4eTsZdmXKctLusN0VX+/nWXLmtmF2QM163379uHv7w/A2bNn8fPzo1evXowdOxaLxZKvBQpR5A38HUKv3/fPyykz+K+5EXdmbjdMhOgXEp+Q7NByRf7ItlnPnTuX0aNHk5qaCsDkyZMZMmQIixYtQtM0oqKi8r1IIcT96pZOpr36pzXL1inwprqV4W4rWBZzWrLsQibbZu3p6Ul4eLj1cWxsLI0bNwagWbNmbNu2Lf+qE0LY9VWl9ShkzrItKLynrKBmZDcGJM2lkXInyz4gDdvFZdus27Rpg17/v99DapqGcvsWq5IlS3Lz5s38q04IYZetLFtVNOKpgKdyCW/1D8myC5EcXw2i0/2vvyclJVGqVKk8LUgI8YDsXJf9WnAkU/Sz6ab+hoqGGybG6n/gXwlDCrY+kadyfDXIc889R0xMDABbtmyhYcOGeV6UECL36pZOppO6HVXJiEh0CnRQ/2S88QcuXftH1hlxUTlu1kFBQYSHh9OjRw9MJhNt2rTJj7qEELlkL8v21/1K8vRXWLJiKT5JiyXPdjGKpmn3rxzzkOLi4mjRogVRUVFUrlw5r99eCJGV2U3g0oH7DptKPcml67d4gqtY0KFXLCRrRpqlfoWxTCW2Bjd3QLHiQckdjEIUNnaybAPQNngFEcaxPKucB0CPmX/pVzI2oX8BFihyQ+5gFKIIqV5ao6pyybpmtkEx00uN5oWSVyXLdnLSrIUoQmzl2SoWFqQH8t+I7yTLdmLSrIUoQuzt/6hDY7bhc3qpUbJmtpOSzFqIosROnl0veA3LDKE8rzsFgJ50ybKdjEzWQgieLW3iWd35u7JsC73VKF4qHidZtpOQyVoIYXPNbB0a/7aMZGzEcXyUU7JmtoPJZC2EsJtlpyt6wgxz6aVGS5btYDJZCyHsZtl1g39mkWEiL+mOAGAgnX/pVzA2IaAgqxNIsxZCZKFO6VTqp5y0Ztl6xcJbajQb9F6s3BXH5+uPEZ+QzONlihPY5hmJRvKRxCBCCLtsXZetoPG9NpbjqyZgTohjiXE8aQkX5brsfCbNWghhl70sO1kpTpB+CZFuI2mkHOVf+pUkm8ySZecjiUGEEPbZvS77F3roopls+A5FAT81mtnp3sQnVCjgAosOadZCiBx7vEwJaieexYSKETMGxUKkWwiDCGHZjnNMizohWXYekxhECJFjo73K4aNuxqiYrcfKkMRCRpGwJhhdwhnJsvOYNGshRI61uzYfwz3dw6IzcEapzLv6SCLdQiTLzmPSrIUQORf3J6pmynRI1UykWFQGpX2AO8noFI1eajRPcon4hGQHFVp4SGYthMg5O794fDcsmoGJMzCh4oYZFQuRbiP50DKMKzdasO1kxt2PkmfnnEzWQog8cyfLdrudZSsKlCCV79TJ/PaZLxMitpKWEC95di5IsxZC5BlbWbamM5Bavi6dld9Yqw/kU8M3kmfngjRrIUTesZNlu+nhzbQJXNdK8oa6H52i4atupgIJkmc/IMmshRB5x06WDfBPWDR/Jj5DNeUiesWCGyY+N8xkuFsoq/dckCw7GzJZCyEKxGivcnRXf0OvWICMPLuZepBPU8fz6fKNkmVnI9eT9ZtvvomHhwcAlStXZvLkyXlWlBCi8Gl3bT5mHdy9LpQFlSa6A/xXF8hBy5PWLPtjU3+mrjsq0/VdctWsU1NTAViwYEGeFiOEKMRs5Nk6zJzUHucmJXhVPQyAr7qZ8PSuxCc4oEYnlqtmfeTIEZKTk+nfvz/p6ekMGzaM+vXr53FpQohCxU6e3TcsmoGJX1NPOWXNssMN03jfMEGy7LvkKrMuVqwYAQEBfPfdd4wbN47hw4eTnp6e/RcKIcQ9Mq7N3pIpy35ZPcqc9BCmL1snWfZtuWrWVatWpVOnTiiKQtWqVSlTpgxXr17N69qEEEWAzXVGUKmtO02kMYhZhq/kumxy2awjIiIICwsD4PLlyyQmJlKhgqxjK4TIBTtZ9hlLJf60PEND9Tg6RaNHEb8uO1eZdffu3Rk5ciR+fn4oisKkSZPQ6+WSbSFELtjJsvvfzrJNmg6DYsGIiTmGzxmgTmTVrjg+K2L7PyqapmnZvyxn4uLiaNGiBVFRUVSuXDmv314IUQT8Z/te3vhvS4opmafuo5bKfJQ+mMuW0nxtDOf9tA9INDzC5K51C3XDlptihBBOyWaWrah46q6w2jCa74xTi1SWLc1aCOGcbGXZmpmzlsf4j7kR9XRnbmfZm4pEli1BsxDCOdnJsgPurJmtqRgUM0bS+cEYxtvKJyzbcZ5pUccLZZYtk7UQwqXcWTPbcNea2bV151ilDWXlyqWF9rpsadZCCJdiL8suq0tiidsEFhgnF8osW5q1EMK12Mmyz1vKsyj9DZ5R4gplli2ZtRDCtdjJsgfczrLTUTFgxk1JZ5FxIr20CVy5mcK2E669/6M0ayFEoTDaqxxv/Pd/WTZADSWetcpQxn56mPWWFylj/pslxnDeT/iAkSvTAFymYUsMIoQoFGzv/6inbDEdM9XPmKoLJ1C/1GXzbGnWQojCwWaWnY6+TGW+NHWjg+4PfNQt6BQNH3WLy+XZEoMIIQqHLPZ/jAiLpkZiHB3UGBTAiIkR+iVMLf6hy6yZLZO1EKLQG+1VjlbqbnRKxmNV0eiubqFt0k8MX77XJa7NlmYthCj0bOXZKDDe+G/mqJ8SrF/s9Fm2NGshROFnI89WgIuWsrysO0RX9Xenz7IlsxZCFH528uzuYdEMT/yMzupWFMCNNEbqF/KJ21Cny7JlshZCFFmjvcrRTv3TmmXrFOiibqVHyjKGL9vjVFm2NGshRJFlO8tWGGFYxiLDeEbpFzpNli3NWghRdNnMsjUuWB7hWeUcndVtt7Nsx+//KJm1EKLospNl+4ZFMzTxC7qov6Oi4YaJ0foFjDUMc9j+jzJZCyHEPUZ7laOj+geqkrFFrU6BTup23k2bT1DELodk2dKshRDiHvay7MGGn1lp+Jix+vkFnmVLsxZCiHvZybLPWSpQSblGBzWmwLPsXGXWFouF0NBQjh49itFoZOLEiTz55JN5XZsQQjiGnSzbLyyaDxK/oru6xZplj9PPY4QaSIrJzH8PXsq3a7Nz1aw3bNhAWloaS5cuZe/evYSFhTFr1qw8KUgIIZxVxprZ2zJl2e3UHVw1z6FFmImrqSql06/ly5rZuYpBdu3aRdOmTQGoX78+Bw8efOhChBDC2dnOsnW8rd/AgvTh1DUf5gP9qnzJs3PVrBMTE3F3d7c+VlWV9PT0PClICCGcls0s2wJlq2LQ0lluHIefGp0v64zkKgZxd3cnKSnJ+thisaDXyyXbQohCLos1s/tNjiQ8OYhnlfMA6LDwL/1KvnF/L0++da4m6xdeeIEtW7YAsHfvXmrWrJknxQghhKv66PUnqKpcQrm9zoibko6vuoXRXuXy5P1zNQ63atWKrVu30rNnTzRNY9KkSXlSjBBCuKp21+Zj1gHa/44ZdBrtrs0H6j/0++eqWet0OsaPH//Q31wIIQoNG3m2qpkg7s88eXsJmoUQIi9kkWfnBbmDUQghXIA0ayGEcAHSrIUQwgVIsxZCCBeQL79gNJvNAFy6dCk/3l4IIQq1ihUr3nejYb4066tXrwLQu3fv/Hh7IYQo1KKioqhcuXKmY4qmaZqd1+daSkoKBw8epEKFCqiqmtdvL4QQhZqtyTpfmrUQQoi8Jb9gFEIIF+DQZm2xWPj444/p0aMH/v7+nD17NtPz0dHRdOvWjR49erBs2TKnqWvevHl06NABf39//P39OXXqVIHVtm/fPvz9/e877qhzlV1djjxXJpOJwMBAevXqRffu3YmKisr0vKPOWXZ1Oeqcmc1mRo4cSc+ePenduzfnzp3L9Lyjzld2dTnyzxjAtWvX8PLy4uTJk5mO5/n50hxo3bp1WlBQkKZpmrZnzx5t4MCB1ufS0tK0li1bagkJCVpqaqrWtWtX7cqVKw6vS9M07aOPPtIOHDhQILXcbc6cOVrHjh01Hx+fTMcdea6yqkvTHHeuNE3TIiIitIkTJ2qapml///235uXlZX3Okecsq7o0zXHnbP369VpwcLCmaZr2xx9/OM3fx6zq0jTH/hlLS0vTBg8erLVu3Vo7ceJEpuN5fb4cOllntePMyZMn8fT0pHTp0hiNRl588UV27tzp8LoAYmNjmTNnDn5+fnzzzTcFUhOAp6cn4eHh9x135LnKqi5w3LkCaNu2LR9++KH18d2/7HbkOcuqLnDcOWvZsiUTJkwAID4+nvLly1ufc+T5yqoucOyfsSlTptCzZ08effTRTMfz43w5tFlnteNMYmIiHh4e1udKlixJYmKiw+sC6NChA6Ghofz73/9m165dbNy4sUDqatOmjc1NHhx5rrKqCxx3riDjPLi7u5OYmMgHH3zAkCFDrM858pxlVRc49pzp9XqCgoKYMGECbdq0sR539J8xe3WB487XypUrKVeunHWwu1t+nC+HNuusdpy597mkpKRMH95RdWmaxttvv025cuUwGo14eXlx6NChAqnLHkeeq6w4w7m6ePEiffr0oXPnznh7e1uPO/qc2avLGc7ZlClTWLduHWPGjOHWrVuA48+Xvboceb5WrFjBtm3b8Pf35/DhwwQFBVnvMcmP8+XQZp3VjjPVq1fn7NmzJCQkkJaWxs6dO2nQoIHD60pMTKRjx44kJSWhaRoxMTHUqVOnQOqyx5HnKiuOPld//fUX/fv3JzAwkO7du2d6zpHnLKu6HHnOVq9ebY0RihcvjqIo1ojGkecrq7oceb4WLlzIjz/+yIIFC6hVqxZTpkyhQoUKQP6cL4euZ21rx5mff/6ZW7du0aNHD4KDgwkICEDTNLp168Zjjz3mFHUNHTqUPn36YDQaeeWVV/Dy8iqQuu7lDOcqu7ocea5mz57NjRs3mDlzJjNnzgTAx8eH5ORkh56z7Opy1Dlr3bo1I0eOpHfv3qSnpxMSEsKvv/7q8D9j2dXlLH8fIX//TspNMUII4QLkphghhHAB0qyFEMIFSLMWQggXIM1aCCFcgDRrIYRwAQ69dE+IgtarVy+SkpJQVZWVK1c6uhwhHphcuieEEC5AYhAhhHAB0qxFkXD06FF69uxpfRwbG0ufPn0cWJEQOSPNWhQJTz/9NOfPn8dsNgMQFhZGUFCQg6sS4sHJLxhFkaDT6ahRowbHjx/n7NmzPP7449SuXdvRZQnxwKRZiyKjfv367N69m8WLF/Ptt986uhwhckRiEFFkPP/880ybNo2WLVs6dFVCIXJDmrUoMqpVq4bBYOCdd95xdClC5Jg0a1FkzJ8/n48++ogSJUo4uhQhckyatSj0zp07R9u2bUlJSaFLly6OLkeIXJE7GIUQwgXIZC2EEC5AmrUQQrgAadZCCOECpFkLIYQLkGYthBAuQJq1EEK4AGnWQgjhAqRZCyGEC5BmLYQQLuD/AVCBVPFxXjUeAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -2206,7 +2286,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 47, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.030539300Z", @@ -2239,84 +2319,25 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "being the selected $\\theta$:" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "ExecuteTime": { - "end_time": "2023-07-11T17:36:26.034601700Z", - "start_time": "2023-07-11T17:36:26.030539300Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0.54940883],\n", - " [ 0.40803995],\n", - " [ 1.38725684],\n", - " [-12.51466387],\n", - " [ 8.11712907],\n", - " [-11.04664806],\n", - " [ 12.22693917],\n", - " [ 2.9042585 ]])" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Theta[position, :].reshape(-1, 1)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "or still:\n", - "\n", - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,54937794\\\\\n", - "\\theta_2 = 0,40809777\\\\\n", - "\\theta_3 = 1,38818561\\\\\n", - "\\theta_4 = -12,51509306\\\\\n", - "\\theta_5 = 8,11602829\\\\\n", - "\\theta_6 = -11,04448619\\\\\n", - "\\theta_7 = 12,22693625\\\\\n", - "\\theta_8 = 2,90315019\\\\\n", - "\\end{matrix}\n", - "$$\n" + "where the best estimated $\\theta$ is" ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "parameters found IniciacaoCientifica2007:\n", - " \n", - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,5494135\\\\\n", - "\\theta_2 = 0,4080312\\\\\n", - "\\theta_3 = 3,3857601\\\\\n", - "\\theta_4 = -12,513688\\\\\n", - "\\theta_5 = 8,116575\\\\\n", - "\\theta_6 = -11,04592\\\\\n", - "\\theta_7 = 12,227184\\\\\n", - "\\theta_8 = 2,9038468\\\\\n", - "\\end{matrix}\n", - "$$\n", - "\n", - "\n", - "whereas:\n", + "| Variable | SysIdentPy | IniciacaoCientifica2007 |\n", + "|----------|--------------|--------------------------|\n", + "| θ₁ | 0.54940883 | 0.5494135 |\n", + "| θ₂ | 0.40803995 | 0.4080312 |\n", + "| θ₃ | 1.38725684 | 3.3857601 |\n", + "| θ₄ | -12.51466378 | -12.513688 |\n", + "| θ₅ | 8.11712897 | 8.116575 |\n", + "| θ₆ | -11.04664789 | -11.04592 |\n", + "| θ₇ | 12.22693907 | 12.227184 |\n", + "| θ₈ | 2.90425844 | 2.9038468 |\n", + "\n", + "where:\n", "\n", "$$\n", "E_{Scilab} = 17,408934\n", From f294ba8022bc3bd0663a9b0f72050f0dd2e34c83 Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sat, 23 Sep 2023 23:54:58 -0300 Subject: [PATCH 07/11] adding tests for AILS class --- .../tests/__init__.py | 0 .../tests/test_mo_estimators.py | 333 ++++++++++++++++++ 2 files changed, 333 insertions(+) create mode 100644 sysidentpy/multiobjective_parameter_estimation/tests/__init__.py create mode 100644 sysidentpy/multiobjective_parameter_estimation/tests/test_mo_estimators.py diff --git a/sysidentpy/multiobjective_parameter_estimation/tests/__init__.py b/sysidentpy/multiobjective_parameter_estimation/tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/sysidentpy/multiobjective_parameter_estimation/tests/test_mo_estimators.py b/sysidentpy/multiobjective_parameter_estimation/tests/test_mo_estimators.py new file mode 100644 index 00000000..5bb3e843 --- /dev/null +++ b/sysidentpy/multiobjective_parameter_estimation/tests/test_mo_estimators.py @@ -0,0 +1,333 @@ +""" Tests for AILS methods""" + +import numpy as np +from sysidentpy.multiobjective_parameter_estimation.estimators import AILS +from sysidentpy.utils.narmax_tools import set_weights +from numpy.testing import assert_array_equal, assert_almost_equal, assert_allclose + + +df_train = np.genfromtxt( + "examples/datasets/buck_id.csv", delimiter=",", skip_header=True +) +df_valid = np.genfromtxt( + "examples/datasets/buck_valid.csv", delimiter=",", skip_header=True +) + +Vd = 24 +Uo = np.linspace(0, 4, 50) +Yo = (4 - Uo) * Vd / 3 +Uo = Uo.reshape(-1, 1) +Yo = Yo.reshape(-1, 1) + +gain = -8 * np.ones(len(Uo)).reshape(-1, 1) +x_train = df_train[:, 1].reshape(-1, 1) +y_train = df_train[:, 2].reshape(-1, 1) +x_valid = df_valid[:, 1].reshape(-1, 1) +y_valid = df_valid[:, 2].reshape(-1, 1) + +w = set_weights(static_function=True, static_gain=True) +final_model = np.array( + [ + [0, 0], + [1001, 0], + [1002, 0], + [2001, 0], + [1001, 1001], + [1002, 1001], + [2001, 1001], + [1002, 1002], + ] +) + +final_model = np.array( + [ + [1001, 0], + [1002, 0], + [2001, 1001], + [0, 0], + [1001, 1001], + [2001, 0], + [1002, 1001], + [1002, 1002], + ] +) + + +def test_default_values(): + default = { + "static_gain": True, + "static_function": True, + "final_model": np.zeros((1, 1)), + "normalize": True, + } + model = AILS() + model_values = [ + model.static_gain, + model.static_function, + model.final_model, + model.normalize, + ] + assert list(default.values()) == model_values + + +def test_get_term_clustering(): + qit = np.array([[0, 0], [1, 0], [2, 0], [1, 1], [2, 1]]) + + expected_result = np.array(np.array([[0, 0], [1, 0], [0, 1], [2, 0], [1, 1]])) + estimator = AILS() + result = estimator.get_term_clustering(qit) + assert_array_equal(result, expected_result) + + +def test_build_linear_mapping(): + estimator = AILS(final_model=final_model) + R, qit = estimator.build_linear_mapping() + expected_result = np.array([[0, 0], [1, 0], [0, 1], [2, 0], [1, 1]]) + assert_array_equal(expected_result, qit) + assert isinstance(R, np.ndarray) + assert isinstance(qit, np.ndarray) + assert R.shape == (5, 8) + assert qit.shape == (5, 2) + assert R.dtype == np.int + assert qit.dtype == np.int + + +def test_build_static_function_information(): + mo_estimator = AILS(final_model=final_model) + QR, static_covariance, static_response = ( + mo_estimator.build_static_function_information(Uo, Yo) + ) + # those values were taken from matlab implementation to compare + # with this scenario + static_covariance_mat = np.array( + [ + [ + 1.72408163e04, + 1.72408163e04, + 1.67183673e04, + 8.00000000e02, + 4.17959184e05, + 1.04489796e03, + 4.17959184e05, + 4.17959184e05, + ], + [ + 1.72408163e04, + 1.72408163e04, + 1.67183673e04, + 8.00000000e02, + 4.17959184e05, + 1.04489796e03, + 4.17959184e05, + 4.17959184e05, + ], + [ + 1.67183673e04, + 1.67183673e04, + 2.67605287e04, + 1.04489796e03, + 3.20903526e05, + 2.08979592e03, + 3.20903526e05, + 3.20903526e05, + ], + [ + 8.00000000e02, + 8.00000000e02, + 1.04489796e03, + 5.00000000e01, + 1.72408163e04, + 1.00000000e02, + 1.72408163e04, + 1.72408163e04, + ], + [ + 4.17959184e05, + 4.17959184e05, + 3.20903526e05, + 1.72408163e04, + 1.08074657e07, + 1.67183673e04, + 1.08074657e07, + 1.08074657e07, + ], + [ + 1.04489796e03, + 1.04489796e03, + 2.08979592e03, + 1.00000000e02, + 1.67183673e04, + 2.69387755e02, + 1.67183673e04, + 1.67183673e04, + ], + [ + 4.17959184e05, + 4.17959184e05, + 3.20903526e05, + 1.72408163e04, + 1.08074657e07, + 1.67183673e04, + 1.08074657e07, + 1.08074657e07, + ], + [ + 4.17959184e05, + 4.17959184e05, + 3.20903526e05, + 1.72408163e04, + 1.08074657e07, + 1.67183673e04, + 1.08074657e07, + 1.08074657e07, + ], + ] + ) + static_response_mat = np.array( + [ + [17240.81632653], + [17240.81632653], + [16718.36734694], + [800.0], + [417959.18367347], + [1044.89795918], + [417959.18367347], + [417959.18367347], + ] + ) + assert_allclose(static_covariance_mat, static_covariance) + assert_allclose(static_response_mat, static_response) + assert_almost_equal(QR.mean(), 136.2933673469388) + assert QR.shape == (50, 8) + + +def test_build_static_gain_information(): + mo_estimator = AILS(final_model=final_model) + HR, gain_covariance, gain_response = mo_estimator.build_static_gain_information( + Uo, Yo, gain + ) + # those values were taken from matlab implementation to compare + # with this scenario + gain_covariance_mat = np.array( + [ + [ + 3.20000000e03, + 3.20000000e03, + 2.80000000e03, + 0.00000000e00, + 1.02400000e05, + -4.00000000e02, + 1.02400000e05, + 1.02400000e05, + ], + [ + 3.20000000e03, + 3.20000000e03, + 2.80000000e03, + 0.00000000e00, + 1.02400000e05, + -4.00000000e02, + 1.02400000e05, + 1.02400000e05, + ], + [ + 2.80000000e03, + 2.80000000e03, + 2.45000000e03, + 0.00000000e00, + 8.96000000e04, + -3.50000000e02, + 8.96000000e04, + 8.96000000e04, + ], + [ + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + 0.00000000e00, + ], + [ + 1.02400000e05, + 1.02400000e05, + 8.96000000e04, + 0.00000000e00, + 4.41364898e06, + -1.28000000e04, + 4.41364898e06, + 4.41364898e06, + ], + [ + -4.00000000e02, + -4.00000000e02, + -3.50000000e02, + 0.00000000e00, + -1.28000000e04, + 5.00000000e01, + -1.28000000e04, + -1.28000000e04, + ], + [ + 1.02400000e05, + 1.02400000e05, + 8.96000000e04, + 0.00000000e00, + 4.41364898e06, + -1.28000000e04, + 4.41364898e06, + 4.41364898e06, + ], + [ + 1.02400000e05, + 1.02400000e05, + 8.96000000e04, + 0.00000000e00, + 4.41364898e06, + -1.28000000e04, + 4.41364898e06, + 4.41364898e06, + ], + ] + ) + gain_response_mat = np.array( + [ + [3200.0], + [3200.0], + [2800.0], + [0.0], + [102400.0], + [-400.0], + [102400.0], + [102400.0], + ] + ) + assert_allclose(gain_covariance_mat, gain_covariance) + assert_allclose(gain_response_mat, gain_response) + assert_almost_equal(HR.mean(), -98.75) + assert HR.shape == (50, 8) + + +def test_estimate(): + mo_estimator = AILS(final_model=final_model) + J, E, theta, _, _, position = mo_estimator.estimate( + y=y_train, gain=gain, y_static=Yo, X_static=Uo, X=x_train, weighing_matrix=w + ) + expected_theta = np.array( + [ + [1.54048245], + [0.29686668], + [0.64693309], + [-0.41302211], + [0.27670633], + [-0.53473868], + [0.00406244], + [0.25831577], + ] + ) + assert_allclose(expected_theta, theta[position, :].reshape(-1, 1), rtol=1e-05) + assert J.shape == (3, 2295) + assert E.shape == (2295,) + assert position == 1065 From 32bfdc62562a511ee30dd54324012a4280b10a2c Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sun, 24 Sep 2023 11:57:24 -0300 Subject: [PATCH 08/11] rename regressor_code variable as enconding because it was the same name of the method --- sysidentpy/utils/narmax_tools.py | 25 ++++++++++++++----------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/sysidentpy/utils/narmax_tools.py b/sysidentpy/utils/narmax_tools.py index 70baf832..2f3f5665 100644 --- a/sysidentpy/utils/narmax_tools.py +++ b/sysidentpy/utils/narmax_tools.py @@ -1,8 +1,10 @@ -from ..narmax_base import RegressorDictionary -from ._check_arrays import _num_features +""" Utils methods for NARMAX modeling""" import numpy as np +from ..narmax_base import RegressorDictionary +from ._check_arrays import _num_features + def regressor_code( *, @@ -18,7 +20,7 @@ def regressor_code( else: n_inputs = 1 # only used to create the regressor space base - regressor_code = RegressorDictionary( + encoding = RegressorDictionary( xlag=xlag, ylag=ylag, model_type=model_type, basis_function=basis_function ).regressor_space(n_inputs) @@ -26,23 +28,23 @@ def regressor_code( if basis_name != "Polynomial" and basis_function.ensemble: repetition = basis_function.n * 2 basis_code = np.sort( - np.tile(regressor_code[1:, :], (repetition, 1)), + np.tile(encoding[1:, :], (repetition, 1)), axis=0, ) - regressor_code = np.concatenate([regressor_code[1:], basis_code]) + encoding = np.concatenate([encoding[1:], basis_code]) elif basis_name != "Polynomial" and basis_function.ensemble is False: repetition = basis_function.n * 2 - regressor_code = np.sort( - np.tile(regressor_code[1:, :], (repetition, 1)), + encoding = np.sort( + np.tile(encoding[1:, :], (repetition, 1)), axis=0, ) if basis_name == "Polynomial" and model_representation == "neural_network": - return regressor_code[1:] + return encoding[1:] elif basis_name == "Polynomial" and model_representation is None: - return regressor_code + return encoding else: - return regressor_code + return encoding def set_weights( @@ -55,7 +57,8 @@ def set_weights( base: float = 2.71, ) -> np.ndarray: """ - Set log-spaced weights assigned to each objective in the multi-objective optimization. + Set log-spaced weights assigned to each objective in the multi-objective + optimization. Returns ------- From bb21601091170fc0b12cd81471313ff03e195c09 Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sun, 24 Sep 2023 11:58:14 -0300 Subject: [PATCH 09/11] added type hints, remove unused variables, improve readability --- .../estimators.py | 72 +++++++++++++------ 1 file changed, 51 insertions(+), 21 deletions(-) diff --git a/sysidentpy/multiobjective_parameter_estimation/estimators.py b/sysidentpy/multiobjective_parameter_estimation/estimators.py index 792d2fa3..5b579e1b 100644 --- a/sysidentpy/multiobjective_parameter_estimation/estimators.py +++ b/sysidentpy/multiobjective_parameter_estimation/estimators.py @@ -1,8 +1,11 @@ """ Affine Information Least Squares for NARMAX models""" +from typing import Tuple, List + import numpy as np -from sysidentpy.narmax_base import RegressorDictionary, InformationMatrix + from sysidentpy.basis_function import Polynomial +from sysidentpy.narmax_base import InformationMatrix, RegressorDictionary class AILS: @@ -35,22 +38,20 @@ class AILS: def __init__( self, - static_gain=True, - static_function=True, - final_model=np.zeros((1, 1)), - normalize=True, + static_gain: bool = True, + static_function: bool = True, + final_model: np.ndarray = np.zeros((1, 1)), + normalize: bool = True, ): self.n_inputs = np.max(final_model // 1000) - 1 self.degree = np.shape(final_model)[1] - self.xlag = 1 - self.ylag = 1 self.max_lag = 1 self.final_model = final_model self.static_gain = static_gain self.static_function = static_function self.normalize = normalize - def get_term_clustering(self, qit): + def get_term_clustering(self, qit: np.ndarray) -> np.ndarray: """ Get the term clustering of the model. @@ -139,7 +140,9 @@ def build_linear_mapping(self): qit = np.delete(qit, null_rows, axis=0) return R, self.get_term_clustering(qit) - def build_static_function_information(self, X_static, y_static): + def build_static_function_information( + self, X_static: np.ndarray, y_static: np.ndarray + ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]: """ Construct a matrix of static regressors for a NARMAX model. @@ -181,7 +184,9 @@ def build_static_function_information(self, X_static, y_static): static_response = (QR.T).dot(y_static) return QR, static_covariance, static_response - def build_static_gain_information(self, X_static, y_static, gain): + def build_static_gain_information( + self, X_static: np.ndarray, y_static: np.ndarray, gain: np.ndarray + ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]: """ Construct a matrix of static regressors referring to the derivative (gain). @@ -238,7 +243,9 @@ def build_static_gain_information(self, X_static, y_static, gain): gain_response = (HR.T).dot(gain) return HR, gain_covariance, gain_response - def get_cost_function(self, y, psi, theta): + def get_cost_function( + self, y: np.ndarray, psi: np.ndarray, theta: np.ndarray + ) -> np.ndarray: """ Calculate the cost function based on residuals. @@ -267,7 +274,12 @@ def get_cost_function(self, y, psi, theta): residuals = y - psi.dot(theta) return residuals.T.dot(residuals) - def build_system_data(self, y, static_gain, static_function): + def build_system_data( + self, + y: np.ndarray, + static_gain: np.ndarray, + static_function: np.ndarray, + ) -> List[np.ndarray]: """ Construct a list of output data components for the NARMAX system. @@ -301,7 +313,9 @@ def build_system_data(self, y, static_gain, static_function): return [y] + [static_gain] + [static_function] - def build_affine_data(self, psi, HR, QR): + def build_affine_data( + self, psi: np.ndarray, HR: np.ndarray, QR: np.ndarray + ) -> List[np.ndarray]: """ Construct a list of affine data components for NARMAX modeling. @@ -338,6 +352,22 @@ def build_affine_data(self, psi, HR, QR): return [psi] + [HR] + [QR] def build_psi(self, X: np.ndarray, y: np.ndarray) -> np.ndarray: + """ + Build the matrix of dynamic regressor for NARMAX modeling. + + Parameters + ---------- + X : ndarray of floats + The input data to be used in the training process. + y : ndarray of floats + The output data to be used in the training process. + + Returns + ------- + psi : ndarray of floats, shape (n_samples, n_parameters) + The matrix of dynamic regressors. + + """ psi_builder = RegressorDictionary() xlag_code = psi_builder._list_input_regressor_code(self.final_model) ylag_code = psi_builder._list_output_regressor_code(self.final_model) @@ -366,13 +396,13 @@ def build_psi(self, X: np.ndarray, y: np.ndarray) -> np.ndarray: def estimate( self, - y_static=np.zeros(1), - X_static=np.zeros(1), - gain=np.zeros(1), - y=np.zeros(1), - X=np.zeros((1, 1)), - weighing_matrix=np.zeros((1, 1)), - ): + y_static: np.ndarray = np.zeros(1), + X_static: np.ndarray = np.zeros(1), + gain: np.ndarray = np.zeros(1), + y: np.ndarray = np.zeros(1), + X: np.ndarray = np.zeros((1, 1)), + weighing_matrix: np.ndarray = np.zeros((1, 1)), + ) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.int64]: """Calculation of parameters via multi-objective techniques. Parameters @@ -405,7 +435,7 @@ def estimate( """ psi = self.build_psi(X, y) y = y[self.max_lag :] - HR, QR = None, None + HR, QR = np.zeros((1, 1)), np.zeros((1, 1)) n_parameters = weighing_matrix.shape[1] num_objectives = self.static_function + self.static_gain + 1 euclidean_norm = np.zeros(n_parameters) From 5de886d3bb2249703f0d5ccda1d3c8d29e88d54d Mon Sep 17 00:00:00 2001 From: Wilson Rocha Date: Sun, 24 Sep 2023 11:58:52 -0300 Subject: [PATCH 10/11] improve use case explanation and adapt code to new methods --- .../multiobjective_parameter_estimation.ipynb | 411 +++++++++--------- 1 file changed, 200 insertions(+), 211 deletions(-) diff --git a/examples/multiobjective_parameter_estimation.ipynb b/examples/multiobjective_parameter_estimation.ipynb index c71035c7..e42c50db 100644 --- a/examples/multiobjective_parameter_estimation.ipynb +++ b/examples/multiobjective_parameter_estimation.ipynb @@ -87,14 +87,14 @@ } ], "source": [ - "df_train = pd.read_csv(r'datasets/buck_id.csv')\n", - "df_valid = pd.read_csv(r'datasets/buck_valid.csv')\n", + "df_train = pd.read_csv(r\"datasets/buck_id.csv\")\n", + "df_valid = pd.read_csv(r\"datasets/buck_valid.csv\")\n", "\n", "# Plotting the measured output (identification and validation data)\n", "plt.figure(1)\n", - "plt.title('Output')\n", - "plt.plot(df_train.sampling_time, df_train.y, label='Identification', linewidth=1.5)\n", - "plt.plot(df_valid.sampling_time, df_valid.y , label='Validation', linewidth=1.5)\n", + "plt.title(\"Output\")\n", + "plt.plot(df_train.sampling_time, df_train.y, label=\"Identification\", linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.y, label=\"Validation\", linewidth=1.5)\n", "plt.xlabel(\"Samples\")\n", "plt.ylabel(\"Voltage\")\n", "plt.legend()\n", @@ -127,12 +127,12 @@ "source": [ "# Plotting the measured input (identification and validation data)\n", "plt.figure(2)\n", - "plt.title('Input')\n", - "plt.plot(df_train.sampling_time, df_train.input, label='Identification', linewidth=1.5)\n", - "plt.plot(df_valid.sampling_time, df_valid.input, label='Validation', linewidth=1.5)\n", + "plt.title(\"Input\")\n", + "plt.plot(df_train.sampling_time, df_train.input, label=\"Identification\", linewidth=1.5)\n", + "plt.plot(df_valid.sampling_time, df_valid.input, label=\"Validation\", linewidth=1.5)\n", "plt.ylim(2.1, 2.6)\n", - "plt.ylabel('u')\n", - "plt.xlabel('Samples')\n", + "plt.ylabel(\"u\")\n", + "plt.xlabel(\"Samples\")\n", "plt.legend()\n", "plt.show()" ] @@ -282,7 +282,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -329,6 +329,13 @@ "$$\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Multiobjective parameter estimation considering 3 different objectives: the prediction error, the static function and the static gain " + ] + }, { "cell_type": "code", "execution_count": 7, @@ -340,7 +347,7 @@ }, "outputs": [], "source": [ - "# you can use any set of model structure you want in your use case\n", + "# you can use any set of model structure you want in your use case, but in this notebook we will use the one obtained above the compare with other work\n", "mo_estimator = AILS(final_model=model.final_model)\n", "\n", "# setting the log-spaced weights of each objective function\n", @@ -676,7 +683,9 @@ } ], "source": [ - "model.theta = theta[-1, :].reshape(-1, 1) # setting the theta estimated for the first combination of the weights\n", + "model.theta = theta[-1, :].reshape(\n", + " -1, 1\n", + ") # setting the theta estimated for the last combination of the weights\n", "# the model structure is exactly the same, but the order of the regressors is changed in estimate method. Thats why you have to change the model.final_model\n", "model.final_model = mo_estimator.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", @@ -842,6 +851,21 @@ "execution_count": 13, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Regressors Parameters ERR\n", + "0 1 1.5405E+00 9.999E-01\n", + "1 y(k-1) 2.9687E-01 2.042E-05\n", + "2 y(k-2) 6.4693E-01 1.108E-06\n", + "3 x1(k-1) -4.1302E-01 4.688E-06\n", + "4 y(k-1)^2 2.7671E-01 3.922E-07\n", + "5 y(k-2)y(k-1) -5.3474E-01 8.389E-07\n", + "6 x1(k-1)y(k-1) 4.0624E-03 5.690E-07\n", + "7 y(k-2)^2 2.5832E-01 3.827E-06\n" + ] + }, { "data": { "image/png": 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", @@ -874,7 +898,10 @@ } ], "source": [ - "model.theta = theta[position, :].reshape(-1, 1) # setting the theta estimated for the best combination of the weights\n", + "# the variable `position` returned in `estimate` method give the position of the best weight combination\n", + "model.theta = theta[position, :].reshape(\n", + " -1, 1\n", + ") # setting the theta estimated for the best combination of the weights\n", "# the model structure is exactly the same, but the order of the regressors is changed in estimate method. Thats why you have to change the model.final_model\n", "model.final_model = mo_estimator.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", @@ -890,10 +917,11 @@ " ),\n", " columns=[\"Regressors\", \"Parameters\", \"ERR\"],\n", ")\n", - "r\n", - "### The dynamic results for that chosen theta is\n", + "print(r)\n", + "\n", + "# The dynamic results for that chosen theta is\n", "plot_results(y=y_valid, yhat=yhat, n=1000)\n", - "### The static gain result is\n", + "# The static gain result is\n", "plt.figure(4)\n", "plt.title(\"Gain\")\n", "plt.plot(\n", @@ -917,7 +945,7 @@ "plt.ylim(-16, 0)\n", "plt.legend()\n", "plt.show()\n", - "### The static function result is\n", + "# The static function result is\n", "plt.figure(5)\n", "plt.title(\"Static Curve\")\n", "plt.plot(Uo, Yo, linewidth=1.5, label=\"Static curve\", linestyle=\"-\", marker=\"o\")\n", @@ -945,7 +973,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.014411600Z", @@ -1045,7 +1073,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.017591800Z", @@ -1069,9 +1097,7 @@ "source": [ "from sysidentpy.narmax_base import RegressorDictionary\n", "\n", - "object_qit = RegressorDictionary(\n", - " xlag=1, ylag=1\n", - ")\n", + "object_qit = RegressorDictionary(xlag=1, ylag=1)\n", "R_example = object_qit.regressor_space(n_inputs=1) // 1000\n", "print(f\"R = {R_example}\")" ] @@ -1335,7 +1361,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.101857500Z", @@ -1350,7 +1376,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.122382900Z", @@ -1408,7 +1434,7 @@ "0 0.361234 0.35487 0.283896 1.0 1.0 1.0 1.0" ] }, - "execution_count": 28, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1440,7 +1466,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.123384200Z", @@ -1539,7 +1565,7 @@ "7 x1(k-2)^2 3.0846E+00 3.827E-06" ] }, - "execution_count": 29, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1565,7 +1591,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.276007600Z", @@ -1598,7 +1624,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.383278600Z", @@ -1653,7 +1679,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.471991600Z", @@ -1700,7 +1726,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.557244700Z", @@ -1732,7 +1758,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.561257100Z", @@ -1747,7 +1773,7 @@ " 12.25729955, 8.32740057, -11.41574116, 3.08461195])" ] }, - "execution_count": 35, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1768,16 +1794,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "| Variable | Value | Value2 |\n", - "|----------|--------------|--------------|\n", - "| θ₁ | 0.5514725 | 0.549144 |\n", - "| θ₂ | 0.40449005 | 0.408028 |\n", - "| θ₃ | 1.42867821 | 1.45097 |\n", - "| θ₄ | -12.60548863 | -12.55788 |\n", - "| θ₅ | 8.32740057 | 8.1516315 |\n", - "| θ₆ | -11.41574116 | -11.09728 |\n", - "| θ₇ | 12.25729955 | 12.215782 |\n", - "| θ₈ | 3.08461195 | 2.9319577 |\n", + "| Theta | SysIdentPy | IniciacaoCientifica2007 |\n", + "|-------------|--------------|-------------------------------|\n", + "| $\\theta_1$ | 0.5514725 | 0.549144 |\n", + "| $\\theta_2$ | 0.40449005 | 0.408028 |\n", + "| $\\theta_3$ | 1.42867821 | 1.45097 |\n", + "| $\\theta_4$ | -12.60548863 | -12.55788 |\n", + "| $\\theta_5$ | 8.32740057 | 8.1516315 |\n", + "| $\\theta_6$ | -11.41574116 | -11.09728 |\n", + "| $\\theta_7$ | 12.25729955 | 12.215782 |\n", + "| $\\theta_8$ | 3.08461195 | 2.9319577 |\n", "\n", "where:\n", "$$\n", @@ -1788,12 +1814,14 @@ "\n", "$$\n", "E_{Python} = 17,474865\n", - "$$" + "$$\n", + "\n", + "#### Note: as mentioned before, the order of the regressors in the model change, but it is the same structure. The tables shows the respective regressor parameter concerning `SysIdentPy` and `IniciacaoCientifica2007`, but the order `θ₁`, `θ₂` and so on are not the same of the ones in model.final_model" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.565769100Z", @@ -1900,7 +1928,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.568942Z", @@ -1909,7 +1937,9 @@ }, "outputs": [], "source": [ - "bi_objective = AILS(static_function=True, static_gain=False, final_model=model_final, normalize=True)" + "bi_objective = AILS(\n", + " static_function=True, static_gain=False, final_model=model_final, normalize=True\n", + ")" ] }, { @@ -1932,7 +1962,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.660520200Z", @@ -2079,7 +2109,7 @@ "[2000 rows x 5 columns]" ] }, - "execution_count": 43, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -2097,7 +2127,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.775500300Z", @@ -2196,7 +2226,7 @@ "7 x1(k-2)^2 2.9043E+00 3.827E-06" ] }, - "execution_count": 44, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -2222,7 +2252,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.870151400Z", @@ -2247,7 +2277,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:25.956170500Z", @@ -2286,7 +2316,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.030539300Z", @@ -2326,16 +2356,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "| Variable | SysIdentPy | IniciacaoCientifica2007 |\n", - "|----------|--------------|--------------------------|\n", - "| θ₁ | 0.54940883 | 0.5494135 |\n", - "| θ₂ | 0.40803995 | 0.4080312 |\n", - "| θ₃ | 1.38725684 | 3.3857601 |\n", - "| θ₄ | -12.51466378 | -12.513688 |\n", - "| θ₅ | 8.11712897 | 8.116575 |\n", - "| θ₆ | -11.04664789 | -11.04592 |\n", - "| θ₇ | 12.22693907 | 12.227184 |\n", - "| θ₈ | 2.90425844 | 2.9038468 |\n", + "| Theta | SysIdentPy | IniciacaoCientifica2007 |\n", + "|-------------|--------------|--------------------------|\n", + "| $\\theta_1$ | 0.54940883 | 0.5494135 |\n", + "| $\\theta_2$ | 0.40803995 | 0.4080312 |\n", + "| $\\theta_3$ | 1.38725684 | 3.3857601 |\n", + "| $\\theta_4$ | -12.51466378 | -12.513688 |\n", + "| $\\theta_5$ | 8.11712897 | 8.116575 |\n", + "| $\\theta_6$ | -11.04664789 | -11.04592 |\n", + "| $\\theta_7$ | 12.22693907 | 12.227184 |\n", + "| $\\theta_8$ | 2.90425844 | 2.9038468 |\n", "\n", "where:\n", "\n", @@ -2355,12 +2385,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Multiobjective otimization of the model's parameters for prediction of output voltage of the Buck converter CC-CC using as objectives the static curve information, the prediction error and the static gain " + "### Multiobjective parameter estimation considering 2 different objectives: the prediction error and the static gain " ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.038110800Z", @@ -2369,8 +2399,9 @@ }, "outputs": [], "source": [ - "# Calling the class referring to the calculation of the parameters via the biobjective technique\n", - "mult4 = AILS(static_function=False, static_gain=True, final_model=model_final, normalize=False)" + "bi_objective_gain = AILS(\n", + " static_function=False, static_gain=True, final_model=model_final, normalize=False\n", + ")" ] }, { @@ -2393,7 +2424,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.121025300Z", @@ -2436,7 +2467,7 @@ " 0.000000\n", " 17.407256\n", " 3.579467e+01\n", - " 39.802903\n", + " 39.802904\n", " \n", " \n", " 1\n", @@ -2525,7 +2556,7 @@ ], "text/plain": [ " w1 w2 J_ls J_sg ||J||:\n", - "0 1.000000 0.000000 17.407256 3.579467e+01 39.802903\n", + "0 1.000000 0.000000 17.407256 3.579467e+01 39.802904\n", "1 0.997012 0.002988 17.407528 2.109260e-01 17.408806\n", "2 0.994033 0.005967 17.407540 2.082067e-01 17.408785\n", "3 0.991063 0.008937 17.407559 2.056636e-01 17.408774\n", @@ -2540,19 +2571,19 @@ "[2000 rows x 5 columns]" ] }, - "execution_count": 37, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "W = np.zeros((2, 2000))\n", - "W[0, :] = np.logspace(0, -6, num=2000, base=2.71)\n", - "W[1, :] = np.ones(2000) - W[0, :]\n", + "w = np.zeros((2, 2000))\n", + "w[0, :] = np.logspace(0, -6, num=2000, base=2.71)\n", + "w[1, :] = np.ones(2000) - w[0, :]\n", "# W = np.array([[0.9931126],\n", "# [0.0068874]])\n", - "J, w, E, Theta, HR, QR, position = mult4.affine_information_least_squares(\n", - " y_train=y_train[2:], gain=gain, y_static=Yo, x_static=Uo, psi=PSI, weighing_matrix=W\n", + "J, E, theta, HR, QR, position = bi_objective_gain.estimate(\n", + " X=x_train, y=y_train, gain=gain, y_static=Yo, X_static=Uo, weighing_matrix=w\n", ")\n", "result = {\"w1\": w[0, :], \"w2\": w[1, :], \"J_ls\": J[0, :], \"J_sg\": J[1, :], \"||J||:\": E}\n", "pd.DataFrame(result)" @@ -2560,7 +2591,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.234880200Z", @@ -2597,20 +2628,20 @@ " \n", " \n", " 0\n", - " y(k-1)\n", - " 5.4940E-01\n", + " 1\n", + " 1.4853E+00\n", " 9.999E-01\n", " \n", " \n", " 1\n", - " y(k-2)\n", - " 4.0806E-01\n", + " y(k-1)\n", + " 5.4940E-01\n", " 2.042E-05\n", " \n", " \n", " 2\n", - " 1\n", - " 1.4853E+00\n", + " y(k-2)\n", + " 4.0806E-01\n", " 1.108E-06\n", " \n", " \n", @@ -2621,20 +2652,20 @@ " \n", " \n", " 4\n", - " x1(k-1)^2\n", - " 8.1686E+00\n", + " x1(k-2)\n", + " 1.2210E+01\n", " 3.922E-07\n", " \n", " \n", " 5\n", - " x1(k-2)x1(k-1)\n", - " -1.1122E+01\n", + " x1(k-1)^2\n", + " 8.1686E+00\n", " 8.389E-07\n", " \n", " \n", " 6\n", - " x1(k-2)\n", - " 1.2210E+01\n", + " x1(k-2)x1(k-1)\n", + " -1.1122E+01\n", " 5.690E-07\n", " \n", " \n", @@ -2649,25 +2680,25 @@ ], "text/plain": [ " Regressors Parameters ERR\n", - "0 y(k-1) 5.4940E-01 9.999E-01\n", - "1 y(k-2) 4.0806E-01 2.042E-05\n", - "2 1 1.4853E+00 1.108E-06\n", + "0 1 1.4853E+00 9.999E-01\n", + "1 y(k-1) 5.4940E-01 2.042E-05\n", + "2 y(k-2) 4.0806E-01 1.108E-06\n", "3 x1(k-1) -1.2581E+01 4.688E-06\n", - "4 x1(k-1)^2 8.1686E+00 3.922E-07\n", - "5 x1(k-2)x1(k-1) -1.1122E+01 8.389E-07\n", - "6 x1(k-2) 1.2210E+01 5.690E-07\n", + "4 x1(k-2) 1.2210E+01 3.922E-07\n", + "5 x1(k-1)^2 8.1686E+00 8.389E-07\n", + "6 x1(k-2)x1(k-1) -1.1122E+01 5.690E-07\n", "7 x1(k-2)^2 2.9455E+00 3.827E-06" ] }, - "execution_count": 38, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Writing the results\n", - "model.theta = Theta[position, :].reshape(-1, 1)\n", - "model.final_model = model_final\n", + "model.theta = theta[position, :].reshape(-1, 1)\n", + "model.final_model = bi_objective_gain.final_model\n", "yhat = model.predict(X=x_valid, y=y_valid)\n", "rrse = root_relative_squared_error(y_valid, yhat)\n", "r = pd.DataFrame(\n", @@ -2686,7 +2717,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.355391Z", @@ -2711,7 +2742,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.452301700Z", @@ -2721,7 +2752,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -2757,7 +2788,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.508762500Z", @@ -2794,79 +2825,21 @@ ] }, { - "cell_type": "code", - "execution_count": 44, - "metadata": { - "ExecuteTime": { - "end_time": "2023-07-11T17:36:26.509766600Z", - "start_time": "2023-07-11T17:36:26.505017200Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0.54939785],\n", - " [ 0.40805603],\n", - " [ 1.48525191],\n", - " [-12.58066069],\n", - " [ 8.16862612],\n", - " [-11.12171883],\n", - " [ 12.20954833],\n", - " [ 2.94548497]])" - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Theta[position, :].reshape(-1, 1)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "or still:\n", - "\n", - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,54937289\\\\\n", - "\\theta_2 = 0,40810168\\\\\n", - "\\theta_3 = 1,48663719\\\\\n", - "\\theta_4 = -12,58127183\\\\\n", - "\\theta_5 = 8,16780294\\\\\n", - "\\theta_6 = -11,11998621\\\\\n", - "\\theta_7 = 12,20927355\\\\\n", - "\\theta_8 = 2,9446532 \\\\\n", - "\\end{matrix}\n", - "$$\n" - ] - }, - { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "parameters found IniciacaoCientifica2007:\n", - " \n", - "$$\n", - "\\begin{matrix}\n", - "\\theta_1 = 0,549144\\\\\n", - "\\theta_2 = 0,408028\\\\\n", - "\\theta_3 = 1,45097\\\\\n", - "\\theta_4 = -12,557882\\\\\n", - "\\theta_5 = 8,1516315\\\\\n", - "\\theta_6 = -11,097284\\\\\n", - "\\theta_7 = 12,215782\\\\\n", - "\\theta_8 = 2,9319577\\\\\n", - "\\end{matrix}\n", - "$$\n", + "| Theta | SysIdentPy | IniciacaoCientifica2007 |\n", + "|-------------|---------------|---------------------------|\n", + "| $\\theta_1$ | 0.54939785 | 0.54937289 |\n", + "| $\\theta_2$ | 0.40805603 | 0.40810168 |\n", + "| $\\theta_3$ | 1.48525190 | 1.48663719 |\n", + "| $\\theta_4$ | -12.58066084 | -12.58127183 |\n", + "| $\\theta_5$ | 8.16862622 | 8.16780294 |\n", + "| $\\theta_6$ | -11.12171897 | -11.11998621 |\n", + "| $\\theta_7$ | 12.20954849 | 12.20927355 |\n", + "| $\\theta_8$ | 2.94548501 | 2.9446532 |\n", "\n", - "whereas:\n", + "where:\n", "\n", "$$\n", "E_{Scilab} = 17,408997\n", @@ -2876,7 +2849,16 @@ "\n", "$$\n", "E_{Python} = 17,408781\n", - "$$" + "$$\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Additional Information\n", + "\n", + "You can also access the matrix Q and H using the following methods" ] }, { @@ -2889,7 +2871,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.518219Z", @@ -2900,31 +2882,31 @@ { "data": { "text/plain": [ - "array([[17240.81632653, 17240.81632653, 800. , 1044.89795918,\n", - " 2089.79591837, 2089.79591837, 1044.89795918, 2089.79591837],\n", - " [17240.81632653, 17240.81632653, 800. , 1044.89795918,\n", - " 2089.79591837, 2089.79591837, 1044.89795918, 2089.79591837],\n", - " [ 800. , 800. , 50. , 100. ,\n", - " 269.3877551 , 269.3877551 , 100. , 269.3877551 ],\n", - " [ 1044.89795918, 1044.89795918, 100. , 269.3877551 ,\n", - " 816.32653061, 816.32653061, 269.3877551 , 816.32653061],\n", - " [ 2089.79591837, 2089.79591837, 269.3877551 , 816.32653061,\n", - " 2638.54142407, 2638.54142407, 816.32653061, 2638.54142407],\n", - " [ 2089.79591837, 2089.79591837, 269.3877551 , 816.32653061,\n", - " 2638.54142407, 2638.54142407, 816.32653061, 2638.54142407],\n", - " [ 1044.89795918, 1044.89795918, 100. , 269.3877551 ,\n", - " 816.32653061, 816.32653061, 269.3877551 , 816.32653061],\n", - " [ 2089.79591837, 2089.79591837, 269.3877551 , 816.32653061,\n", - " 2638.54142407, 2638.54142407, 816.32653061, 2638.54142407]])" + "array([[ 50. , 800. , 800. , 100. ,\n", + " 100. , 269.3877551 , 269.3877551 , 269.3877551 ],\n", + " [ 800. , 17240.81632653, 17240.81632653, 1044.89795918,\n", + " 1044.89795918, 2089.79591837, 2089.79591837, 2089.79591837],\n", + " [ 800. , 17240.81632653, 17240.81632653, 1044.89795918,\n", + " 1044.89795918, 2089.79591837, 2089.79591837, 2089.79591837],\n", + " [ 100. , 1044.89795918, 1044.89795918, 269.3877551 ,\n", + " 269.3877551 , 816.32653061, 816.32653061, 816.32653061],\n", + " [ 100. , 1044.89795918, 1044.89795918, 269.3877551 ,\n", + " 269.3877551 , 816.32653061, 816.32653061, 816.32653061],\n", + " [ 269.3877551 , 2089.79591837, 2089.79591837, 816.32653061,\n", + " 816.32653061, 2638.54142407, 2638.54142407, 2638.54142407],\n", + " [ 269.3877551 , 2089.79591837, 2089.79591837, 816.32653061,\n", + " 816.32653061, 2638.54142407, 2638.54142407, 2638.54142407],\n", + " [ 269.3877551 , 2089.79591837, 2089.79591837, 816.32653061,\n", + " 816.32653061, 2638.54142407, 2638.54142407, 2638.54142407]])" ] }, - "execution_count": 46, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "mult4.build_static_function_information(Uo, Yo)[1]" + "bi_objective_gain.build_static_function_information(Uo, Yo)[1]" ] }, { @@ -2937,7 +2919,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2023-07-11T17:36:26.520765Z", @@ -2948,32 +2930,39 @@ { "data": { "text/plain": [ - "array([[ 3200. , 3200. , 0. , -400. ,\n", - " -1600. , -1600. , -400. , -1600. ],\n", - " [ 3200. , 3200. , 0. , -400. ,\n", - " -1600. , -1600. , -400. , -1600. ],\n", - " [ 0. , 0. , 0. , 0. ,\n", + "array([[ 0. , 0. , 0. , 0. ,\n", " 0. , 0. , 0. , 0. ],\n", - " [ -400. , -400. , 0. , 50. ,\n", - " 200. , 200. , 50. , 200. ],\n", - " [-1600. , -1600. , 0. , 200. ,\n", - " 1077.55102041, 1077.55102041, 200. , 1077.55102041],\n", - " [-1600. , -1600. , 0. , 200. ,\n", - " 1077.55102041, 1077.55102041, 200. , 1077.55102041],\n", - 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assert R.dtype == np.int - assert qit.dtype == np.int + assert R.dtype == int + assert qit.dtype == int def test_build_static_function_information():