diff --git a/BovedasObsidian/Tesis De Grado Berlatzky/.obsidian/workspace.json b/BovedasObsidian/Tesis De Grado Berlatzky/.obsidian/workspace.json index dbbd2fc..076f16e 100644 --- a/BovedasObsidian/Tesis De Grado Berlatzky/.obsidian/workspace.json +++ b/BovedasObsidian/Tesis De Grado Berlatzky/.obsidian/workspace.json @@ -61,16 +61,38 @@ "state": { "type": "markdown", "state": { - "file": "Gestión de proyectos/Informe de Proyecto de gestión de proyectos.md", + "file": "Notas de paper Sensors-14-02595.md", "mode": "source", "source": false }, "icon": "lucide-file", - "title": "Informe de Proyecto de gestión de proyectos" + "title": "Notas de paper Sensors-14-02595" } } ], "currentTab": 3 + }, + { + "id": "3319fed463f06a87", + "type": "tabs", + "children": [ + { + "id": "ef38306e06987184", + "type": "leaf", + "state": { + "type": "pdf", + "state": { + "file": "Materiales/Adicionales/EstimacionEspectral.pdf", + "page": 1, + "left": -10, + "top": 276, + "zoom": 1.453139856959775 + }, + "icon": "lucide-file-text", + "title": "EstimacionEspectral" + } + } + ] } ], "direction": "vertical" @@ -220,20 +242,20 @@ "pdf-plus:PDF++: Toggle auto-paste": false } }, - "active": "cce2a7351ee882d4", + "active": "ef38306e06987184", "lastOpenFiles": [ + "Notas de paper Sensors-14-02595.md", + "Duda que surge de escribir la primera simulación.md", + "Gestión de proyectos/Informe de Proyecto de gestión de proyectos.md", "Notas del libro Introduction to radar systems de Merrill Skolnik.md", "Esquemas/Esquemas Secundarios/Procesmiento de la señal.canvas", "Notas de tesis de doctorado de Ing. Edgardo Jose Marchi.md", - "Notas de paper Sensors-14-02595.md", - "Duda que surge de escribir la primera simulación.md", "Esquemas/Esquema del proyecto.canvas", "Esquemas/Esquemas Secundarios/Pre-procesamiento de la señal vital.canvas", "Posible objetivo de la tesis.md", "Notas del paper Understanding the Lomb-Scargle Periodogram.md", "Comienzo de las simulaciones.md", "Gestión de proyectos/Consulta de la introducción de Informe de proyecto.md", - "Gestión de proyectos/Informe de Proyecto de gestión de proyectos.md", "Gestión de proyectos", "Esquemas/Esquemas Secundarios", "Esquemas", diff --git a/Simulaciones/PrimerasSimulaciones.ipynb b/Simulaciones/PrimerasSimulaciones.ipynb index 5fb51f8..f8ed3f5 100644 --- a/Simulaciones/PrimerasSimulaciones.ipynb +++ b/Simulaciones/PrimerasSimulaciones.ipynb @@ -128,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -256,6 +256,8 @@ "\n", "Periodo_Muestreo_Lenta = 0.002\n", "\n", + "Velocidad_Luz_V2 = 29979245800\n", + "\n", "###### Comienzo las simulaciones de la señal lenta\n", "np.random.seed(42)\n", "\n", @@ -274,8 +276,6 @@ "Resultado_Desfasaje = Evaluacion_Señal_Lenta(ValoresLinea, Distancia_Paciente, Amplitud_Respitatoria, Frecuencia_Respiratoria,\n", " Fase_Respiracion, Amplitud_Cardiaca, Frecuencia_Cardiaca, Fase_Cardiaca)\n", "\n", - "Velocidad_Luz_V2 = 29979245800\n", - "\n", "Fesfasaje = Resultado_Desfasaje/Velocidad_Luz_V2 * 2 ## El *2 esta porque el trayecto es ida y vuelta de la onda\n", "\n", "###### Comienzo de La señal rapida\n", @@ -402,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -448,13 +448,211 @@ "plt.tight_layout()\n", "plt.show()" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Segunda Simulacion: Exploracion de los metodos de analisis espectral\n", + "-------------------------------------------" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Frecuencia respiratoria: 0.279597545259111\n", + "Frecuencia cardiaca: 0.7890046601106091\n", + "Amplitud respiratoria 1.1605714451279328\n", + "Amplitud cardiaca 0.01731993941811405\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import scipy.signal as signal\n", + "import matplotlib.pyplot as plt\n", + "import random\n", + "import spectrum\n", + "\n", + "def Evaluacion_Señal_Lenta(Tiempo, Distancia, AmpResp, FrecResp, FaseResp, AmpCard, FrecCard, FaseCard):\n", + " # AmpResp es la Amplitud Respiratoria\n", + " # FrecResp es la Frecuencia Respiratoria\n", + " # FaseResp es la Fase de la señal de la respiracion\n", + " # AmpCard es la Amplitud Cardiaca\n", + " # FrecCard es la Frecuancia Cardiaca\n", + " # FaseCard es la Fase de la señal cardiaca\n", + " Señal_Respiratoria = AmpResp * np.sin(2*np.pi*FrecResp*Tiempo + FaseResp)\n", + " Señal_Cardiaca = AmpCard * np.sin(2*np.pi* FrecCard*Tiempo + FaseCard)\n", + " return Distancia + Señal_Respiratoria + Señal_Cardiaca\n", + "\n", + "###### Defino las constantes para las generaciones de los pulsos de señal lenta\n", + "### Comienzo por la definicion de las constantes de la señal lenta\n", + "Amplitud_Respiratoria_Minima = 0.4\n", + "Amplitud_Respiratoria_Maxima = 1.2\n", + "Amplitud_Cardiaca_Minima = 0.01 ## Este valor es un valor inicial para simular el ritmo cardiaco\n", + "Amplitud_Cardiaca_Maxima = 0.02 ## Este valor es un valor inicial para la simulacion del ritmo cardiaco\n", + "\n", + "Frecuencia_Respiratoria_Inferior = 0.1\n", + "Frecuencia_Respiratoria_Superior = 0.4\n", + "Frecuencia_Cardiaca_Superior = 60/60 ## Esto es 60 / frecuencia_Minima porque son ciclos por minuto y tengo que transformar a segundos\n", + "Frecuencia_Cardiaca_Inferior = 60/80 ##\n", + "\n", + "Distancia_Paciente_Minima = 400\n", + "Distancia_Paciente_Maxima = 1000\n", + "\n", + "Periodo_Muestreo_Lenta = 0.0001\n", + "\n", + "###### Comienzo las simulaciones de la señal lenta\n", + "### Muestra de las variables aleatorias\n", + "np.random.seed(42)\n", + "\n", + "Distancia_Paciente = np.random.uniform(Distancia_Paciente_Minima, Distancia_Paciente_Maxima) \n", + "\n", + "Amplitud_Respitatoria = np.random.uniform(low = Amplitud_Respiratoria_Minima, high = Amplitud_Respiratoria_Maxima, size = 1)\n", + "Amplitud_Cardiaca = np.random.uniform(low = Amplitud_Cardiaca_Minima, high = Amplitud_Cardiaca_Maxima, size = 1)\n", + "\n", + "Frecuencia_Respiratoria = np.random.uniform(low = Frecuencia_Respiratoria_Inferior, high = Frecuencia_Respiratoria_Superior, size = 1)\n", + "Frecuencia_Cardiaca = np.random.uniform(low = Frecuencia_Cardiaca_Inferior, high = Frecuencia_Cardiaca_Superior, size = 1)\n", + "\n", + "Fase_Respiracion = np.random.uniform(0, np.pi)\n", + "Fase_Cardiaca = np.random.uniform(0, np.pi)\n", + "\n", + "### Muestreo la señal lenta generada / Genero la señal lenta\n", + "Timepo_Inicio = 0\n", + "Tiempo_Fin = 1000\n", + "ValoresLinea = np.linspace(Timepo_Inicio,Tiempo_Fin,int(Tiempo_Fin/Periodo_Muestreo_Lenta))\n", + "Resultado_Desfasaje = Evaluacion_Señal_Lenta(ValoresLinea, Distancia_Paciente, Amplitud_Respitatoria, Frecuencia_Respiratoria,\n", + " Fase_Respiracion, Amplitud_Cardiaca, Frecuencia_Cardiaca, Fase_Cardiaca)\n", + "\n", + "plt.figure()\n", + "plt.plot(ValoresLinea,Resultado_Desfasaje)\n", + "plt.grid()\n", + "\n", + "print(\"Frecuencia respiratoria:\",Frecuencia_Respiratoria[0])\n", + "print(\"Frecuencia cardiaca:\", Frecuencia_Cardiaca[0])\n", + "\n", + "print(\"Amplitud respiratoria\", Amplitud_Respitatoria[0])\n", + "print(\"Amplitud cardiaca\", Amplitud_Cardiaca[0])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAk0AAAGwCAYAAAC0HlECAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAARFpJREFUeJzt3Xl8VPW9//H3ZDIz2ROSkA0SQEAWZRMUo6ggkc2iVq51oQqWq9XCVUtrLWrdWi9eq7VqUdtaQfsTrW0VqyIaWV0gCojIIgqiASEBErIns35/f0wYM1lkiCEzwOv5eMwjOed8c873zCcz857vOXPGYowxAgAAwHeKCncHAAAAjgWEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCEB3uDkQCn8+nPXv2KDExURaLJdzdAQAAITDGqLq6Wjk5OYqKOvrjQIQmSXv27FFubm64uwEAANph165d6t69+1HfDqFJUmJioiRp586dSk1NDXNvTmxut1tvv/22xo0bJ5vNFu7unNCoReSgFpGDWkSW8vJy9erVK/A6frQRmqTAIbnExEQlJSWFuTcnNrfbrbi4OCUlJfGEFGbUInJQi8hBLSKL2+2WpE47tYYTwQEAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBGENTXPnztXpp5+uxMREZWRk6JJLLtG2bduC2owePVoWiyXodsMNNwS1KS4u1oUXXqi4uDhlZGTo1ltvlcfj6cxdAQAAx7mwXtxy5cqVmjlzpk4//XR5PB7dfvvtGjdunLZs2aL4+PhAu+uuu0733XdfYDouLi7wu9fr1YUXXqisrCx98MEH2rt3r6655hrZbDb97//+b6fuDwAAOH6FNTQtWbIkaHrBggXKyMjQunXrdO655wbmx8XFKSsrq9V1vP3229qyZYveeecdZWZmaujQofrtb3+r2267Tffcc4/sdvtR3QcAAHBiiKivUamsrJSkFt//9vzzz+v//b//p6ysLE2ePFm/+c1vAqNNq1ev1qBBg5SZmRloP378eN14443avHmzhg0b1mI7TqdTTqczMF1VVSXJfzn2Q5dkR3gcuv+pQ/hRi8hBLSIHtYgsnV2HiAlNPp9Pt9xyi84++2ydeuqpgflXXXWVevTooZycHG3cuFG33Xabtm3bppdfflmSVFJSEhSYJAWmS0pKWt3W3Llzde+997aYv3z58qBDfwifwsLCcHcBjahF5KAWkYNaRIa6urpO3V7EhKaZM2dq06ZNeu+994LmX3/99YHfBw0apOzsbI0dO1Y7duxQ796927WtOXPmaPbs2YHpqqoq5ebmasyYMUpLS2vfDqBDuN1uFRYW6oILLuDLMMOMWkQOahE5qEVkKSsr69TtRURomjVrll5//XWtWrVK3bt3/862I0eOlCRt375dvXv3VlZWlj788MOgNqWlpZLU5nlQDodDDoejxXybzcaDIEJQi8hBLSIHtYgc1CIydHYNwnrJAWOMZs2apVdeeUXLli1Tr169Dvs3GzZskCRlZ2dLkvLz8/Xpp59q3759gTaFhYVKSkrSwIEDj0q/AQDAiSesI00zZ87UwoUL9eqrryoxMTFwDlJycrJiY2O1Y8cOLVy4UJMmTVJaWpo2btyon//85zr33HM1ePBgSdK4ceM0cOBAXX311XrwwQdVUlKiO++8UzNnzmx1NAkAAKA9wjrS9OSTT6qyslKjR49WdnZ24PaPf/xDkmS32/XOO+9o3Lhx6t+/v37xi19oypQpeu211wLrsFqtev3112W1WpWfn68f//jHuuaaa4Ku6wQAAPB9hXWkyRjznctzc3O1cuXKw66nR48eWrx4cUd1CwAAoAW+ew4AACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAACAEBCaAAAAQkBoAgAACAGhCQAAIASEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAACAEBCaAAAAQkBoAgAACAGhCQAAIASEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAACAEBCaAAAAQkBoAgAACAGhCQAAIASEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAACAEBCaAAAAQkBoAgAACAGhCQAAIASEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBGENTXPnztXpp5+uxMREZWRk6JJLLtG2bduC2jQ0NGjmzJlKS0tTQkKCpkyZotLS0qA2xcXFuvDCCxUXF6eMjAzdeuut8ng8nbkrAADgOBfW0LRy5UrNnDlTa9asUWFhodxut8aNG6fa2tpAm5///Od67bXX9M9//lMrV67Unj17dOmllwaWe71eXXjhhXK5XPrggw/07LPPasGCBbrrrrvCsUsAAOA4FR3OjS9ZsiRoesGCBcrIyNC6det07rnnqrKyUn/729+0cOFCnX/++ZKk+fPna8CAAVqzZo3OPPNMvf3229qyZYveeecdZWZmaujQofrtb3+r2267Tffcc4/sdnuL7TqdTjmdzsB0VVWVJMntdsvtdh/FPcbhHLr/qUP4UYvIQS0iB7WILJ1dh7CGpuYqKyslSampqZKkdevWye12q6CgINCmf//+ysvL0+rVq3XmmWdq9erVGjRokDIzMwNtxo8frxtvvFGbN2/WsGHDWmxn7ty5uvfee1vMX758ueLi4jp6t9AOhYWF4e4CGlGLyEEtIge1iAx1dXWdur2ICU0+n0+33HKLzj77bJ166qmSpJKSEtntdqWkpAS1zczMVElJSaBN08B0aPmhZa2ZM2eOZs+eHZiuqqpSbm6uxowZo7S0tI7aJbSD2+1WYWGhLrjgAtlstnB354RGLSIHtYgc1CKylJWVder2IiY0zZw5U5s2bdJ777131LflcDjkcDhazLfZbDwIIgS1iBzUInJQi8hBLSJDZ9cgIi45MGvWLL3++utavny5unfvHpiflZUll8ulioqKoPalpaXKysoKtGn+abpD04faAAAAfF9hDU3GGM2aNUuvvPKKli1bpl69egUtHz58uGw2m5YuXRqYt23bNhUXFys/P1+SlJ+fr08//VT79u0LtCksLFRSUpIGDhzYOTsCAACOe2E9PDdz5kwtXLhQr776qhITEwPnICUnJys2NlbJycmaMWOGZs+erdTUVCUlJel//ud/lJ+frzPPPFOSNG7cOA0cOFBXX321HnzwQZWUlOjOO+/UzJkzWz0EBwAA0B5hDU1PPvmkJGn06NFB8+fPn6/p06dLkh555BFFRUVpypQpcjqdGj9+vJ544olAW6vVqtdff1033nij8vPzFR8fr2nTpum+++7rrN0AAAAngLCGJmPMYdvExMRo3rx5mjdvXpttevToocWLF3dk1wAAAIJExIngAAAAkY7QBAAAEAJCEwAAQAgITQAAACEgNAEAAISA0AQAABACQhMAAEAICE0AAAAhIDQBAACEgNAEAAAQAkITAABACAhNAAAAISA0AQAAhIDQBAAAEAJCEwAAQAgITQAAACEgNAEAAISA0AQAABACQhMAAEAICE0AAAAhIDQBAACEgNAEAAAQAkITAABACAhNAAAAISA0AQAAhIDQBAAAEAJCEwAAQAgITQAAACEgNAEAAISA0AQAABACQhMAAEAICE0AAAAhIDQBAACEgNAEAAAQAkITAABACAhNAAAAISA0AQAAhIDQBAAAEAJCEwAAQAgITQAAACEgNAEAAISA0AQAABACQhMAAEAICE0AAAAhIDQBAACEgNAEAAAQAkITAABACAhNAAAAISA0AQAAhIDQBAAAEAJCEwAAQAgITQAAACEIa2hatWqVJk+erJycHFksFi1atCho+fTp02WxWIJuEyZMCGpTXl6uqVOnKikpSSkpKZoxY4Zqamo6cS8AAMCJIKyhqba2VkOGDNG8efPabDNhwgTt3bs3cHvhhReClk+dOlWbN29WYWGhXn/9da1atUrXX3/90e46AAA4wUSHc+MTJ07UxIkTv7ONw+FQVlZWq8u2bt2qJUuW6KOPPtKIESMkSY8//rgmTZqkhx56SDk5OR3eZwAAcGIKa2gKxYoVK5SRkaEuXbro/PPP1+9+9zulpaVJklavXq2UlJRAYJKkgoICRUVFqaioSD/84Q9bXafT6ZTT6QxMV1VVSZLcbrfcbvdR3BsczqH7nzqEH7WIHNQiclCLyNLZdYjo0DRhwgRdeuml6tWrl3bs2KHbb79dEydO1OrVq2W1WlVSUqKMjIygv4mOjlZqaqpKSkraXO/cuXN17733tpi/fPlyxcXFdfh+4MgVFhaGuwtoRC0iB7WIHNQiMtTV1XXq9iI6NF1xxRWB3wcNGqTBgwerd+/eWrFihcaOHdvu9c6ZM0ezZ88OTFdVVSk3N1djxowJjGIhPNxutwoLC3XBBRfIZrOFuzsnNGoROahF5KAWkaWsrKxTtxfRoam5k046Senp6dq+fbvGjh2rrKws7du3L6iNx+NReXl5m+dBSf7zpBwOR4v5NpuNB0GEoBaRg1pEDmoROahFZOjsGhxT12navXu3ysrKlJ2dLUnKz89XRUWF1q1bF2izbNky+Xw+jRw5MlzdBAAAx6GwjjTV1NRo+/btgemdO3dqw4YNSk1NVWpqqu69915NmTJFWVlZ2rFjh371q1+pT58+Gj9+vCRpwIABmjBhgq677jo99dRTcrvdmjVrlq644go+OQcAADpUWEea1q5dq2HDhmnYsGGSpNmzZ2vYsGG66667ZLVatXHjRl100UU6+eSTNWPGDA0fPlzvvvtu0KG1559/Xv3799fYsWM1adIkjRo1Sn/5y1/CtUsAAOA4FdaRptGjR8sY0+byt95667DrSE1N1cKFCzuyWwAAAC0cU+c0AQAAhAuhCQAAIATtOjy3c+dOvfvuu/r6669VV1enrl27atiwYcrPz1dMTExH9xEAACDsjig0Pf/883r00Ue1du1aZWZmKicnR7GxsSovL9eOHTsUExOjqVOn6rbbblOPHj2OVp8BAAA6XcihadiwYbLb7Zo+fbr+/e9/Kzc3N2i50+nU6tWr9eKLL2rEiBF64okndNlll3V4hwEAAMIh5ND0wAMPBK6P1BqHw6HRo0dr9OjRuv/++/XVV191RP8AAAAiQsih6bsCU3NpaWl8hxsAADiufO/rNBljtHz5ctXX1+uss85Sly5dOqJfAAAAEeWILjlQUVGhadOmadCgQbruuutUVVWlc845RwUFBZo8ebIGDBigjRs3Hq2+AgAAhM0RhaZf/vKXWr16ta644gp9+umnmjBhgrxer1avXq2ioiINGDBAd9xxx9HqKwAAQNgc0eG5N998UwsXLtR5552n6dOnKzc3V8uWLdPIkSMlSf/3f/+niy666Kh0FAAAIJyOaKSptLRUJ598siSpW7duiomJCbr0QF5envbv39+xPQQAAIgARxSafD6frFZrYNpqtcpisQSmm/4OAABwPDniT889/fTTSkhIkCR5PB4tWLBA6enpkqTq6uqO7R0AAECEOKLQlJeXp7/+9a+B6aysLP39739v0QYAAOB4c0Shiat8AwCAE9URndMEAABwogp5pOmxxx4LeaU33XRTuzoDAAAQqUIOTY888kjQ9P79+1VXV6eUlBRJ/quFx8XFKSMjg9AEAACOOyEfntu5c2fgdv/992vo0KHaunWrysvLVV5erq1bt+q0007Tb3/726PZXwAAgLBo1zlNv/nNb/T444+rX79+gXn9+vXTI488ojvvvLPDOgcAABAp2hWa9u7dK4/H02K+1+tVaWnp9+4UAABApGlXaBo7dqx++tOfav369YF569at04033qiCgoIO6xwAAECkaFdoeuaZZ5SVlaURI0bI4XDI4XDojDPOUGZmpp5++umO7iMAAEDYHfHXqEhS165dtXjxYn3xxRfaunWrJKl///6BL/MFAAA43rQrNB3St29f9e3bt6P6AgAAELFCPjz3wAMPqL6+PqS2RUVFeuONN9rdKQAAgEgTcmjasmWL8vLy9LOf/Uxvvvmm9u/fH1jm8Xi0ceNGPfHEEzrrrLN0+eWXKzEx8ah0GAAAIBxCPjz33HPP6ZNPPtGf/vQnXXXVVaqqqpLVapXD4VBdXZ0kadiwYfrv//5vTZ8+XTExMUet0wAAAJ3tiM5pGjJkiP7617/qz3/+szZu3Kivv/5a9fX1Sk9P19ChQ5Wenn60+gkAABBW7ToRPCoqSkOHDtXQoUM7uDsAAACRqV3XaQIAADjREJoAAABCQGhqwhgT7i4AAIAIRWhqgswEAADacsShye12Kzo6Wps2bToa/QkrMhMAAGjLEYcmm82mvLw8eb3eo9GfsOLwHAAAaEu7Ds/dcccduv3221VeXt7R/QkrH5kJAAC0oV3XafrTn/6k7du3KycnRz169FB8fHzQ8vXr13dI5zobmQkAALSlXaHpkksu6eBuRAgOzwEAgDa0KzTdfffdHd2PiEBkAgAAbWn3JQcqKir09NNPa86cOYFzm9avX69vvvmmwzrX2XyMNAEAgDa0a6Rp48aNKigoUHJysr766itdd911Sk1N1csvv6zi4mI999xzHd3PTuH1hbsHAAAgUrVrpGn27NmaPn26vvjiC8XExATmT5o0SatWreqwznU2LjkAAADa0q7Q9NFHH+mnP/1pi/ndunVTSUnJ9+5UuHi55gAAAGhDu0KTw+FQVVVVi/mff/65unbt+r07FS6MNAEAgLa0KzRddNFFuu++++R2uyVJFotFxcXFuu222zRlypQO7WBn8pKZAABAG9oVmh5++GHV1NQoIyND9fX1Ou+889SnTx8lJibq/vvv7+g+dhovI00AAKAN7fr0XHJysgoLC/Xee+9p48aNqqmp0WmnnaaCgoKO7l+n4pIDAACgLe0KTQ0NDYqJidGoUaM0atSoju5T2HAiOAAAaEu7QlNKSorOOOMMnXfeeRozZozy8/MVGxvb0X3rdJwIDgAA2tKuc5reeecdTZgwQUVFRbrooovUpUsXjRo1SnfccYcKCws7uo+dhotbAgCAtrQrNI0aNUq333673n77bVVUVGj58uXq06ePHnzwQU2YMKGj+9hpOKcJAAC0pd3fPff555/rL3/5i6655hpNmTJFr732mn7wgx/oD3/4Q8jrWLVqlSZPnqycnBxZLBYtWrQoaLkxRnfddZeys7MVGxurgoICffHFF0FtysvLNXXqVCUlJSklJUUzZsxQTU1Nu/bJxzlNAACgDe0KTd26ddOZZ56pJUuW6Mwzz9Sbb76pAwcO6JVXXtHNN98c8npqa2s1ZMgQzZs3r9XlDz74oB577DE99dRTKioqUnx8vMaPH6+GhoZAm6lTp2rz5s0qLCzU66+/rlWrVun6669vz25xnSYAANCmdp0I3rVrV3322WcqKSlRSUmJSktLVV9fr7i4uCNaz8SJEzVx4sRWlxlj9Mc//lF33nmnLr74YknSc889p8zMTC1atEhXXHGFtm7dqiVLluijjz7SiBEjJEmPP/64Jk2apIceekg5OTmtrtvpdMrpdAamD13d3OXyBC7YifA4dP9Th/CjFpGDWkQOahFZOrsO7QpNGzZsUEVFhVatWqWVK1fq9ttv15YtWzR06FCNGTOmQy5wuXPnTpWUlARd+yk5OVkjR47U6tWrdcUVV2j16tVKSUkJBCZJKigoUFRUlIqKivTDH/6w1XXPnTtX9957b4v5H639SFXFm7933/H9HcsfKDjeUIvIQS0iB7WIDHV1dZ26vXaFJsl/2YGLLrpIZ599ts466yy9+uqreuGFF1RUVNQhoenQF/9mZmYGzc/MzAwsKykpUUZGRtDy6OhopaamfucXB8+ZM0ezZ88OTFdVVSk3N1fDThuu0YN7fe++o/3cbrcKCwt1wQUXyGazhbs7JzRqETmoReSgFpGlrKysU7fXrtD08ssva8WKFVqxYoW2bNmi1NRUjRo1Sg8//LDOO++8ju5jh3M4HHI4HC3mW6KsPAgihM1moxYRglpEDmoROahFZOjsGrQrNN1www0699xzdf311+u8887ToEGDOrpfysrKkiSVlpYqOzs7ML+0tFRDhw4NtNm3b1/Q33k8HpWXlwf+/kjw3XMAAKAt7QpNzYPK0dCrVy9lZWVp6dKlgZBUVVWloqIi3XjjjZKk/Px8VVRUaN26dRo+fLgkadmyZfL5fBo5cuQRb5PMBAAA2tLuc5q8Xq8WLVqkrVu3SpIGDhyoiy++WFarNeR11NTUaPv27YHpnTt3asOGDUpNTVVeXp5uueUW/e53v1Pfvn3Vq1cv/eY3v1FOTo4uueQSSdKAAQM0YcIEXXfddXrqqafkdrs1a9YsXXHFFW1+cu4794nUBAAA2tCu0LR9+3ZNmjRJ33zzjfr16yfJ/4m03NxcvfHGG+rdu3dI61m7dq3GjBkTmD50cva0adO0YMEC/epXv1Jtba2uv/56VVRUaNSoUVqyZIliYmICf/P8889r1qxZGjt2rKKiojRlyhQ99thj7dktLm4JAADa1K7QdNNNN6l3795as2aNUlNTJfnPYP/xj3+sm266SW+88UZI6xk9evR3fkmuxWLRfffdp/vuu6/NNqmpqVq4cOGR7UAbGGkCAABtaVdoWrlyZVBgkqS0tDQ98MADOvvsszusc53Ny0gTAABoQ7u+RsXhcKi6urrF/JqaGtnt9u/dqXAxvnD3AAAARKp2haYf/OAHuv7661VUVCRjjIwxWrNmjW644QZddNFFHd3HTsPhOQAA0JZ2habHHntMvXv3Vn5+vmJiYhQTE6Ozzz5bffr00aOPPtrRfew0nAgOAADa0q5zmlJSUvTqq69q+/btgUsODBgwQH369OnQznU2HyNNAACgDUcUmnw+n37/+9/rP//5j1wul8aOHau7775bsbGxR6t/ncpLZgIAAG04osNz999/v26//XYlJCSoW7duevTRRzVz5syj1bdOx+E5AADQliMKTc8995yeeOIJvfXWW1q0aJFee+01Pf/88/L5jo+PnXlFaAIAAK07otBUXFysSZMmBaYLCgpksVi0Z8+eDu9YODDSBAAA2nJEocnj8QR9hYkk2Ww2ud3uDu1UuHgITQAAoA1HdCK4MUbTp0+Xw+EIzGtoaNANN9yg+Pj4wLyXX36543rYiTze4+MwIwAA6HhHFJqmTZvWYt6Pf/zjDutMuLm94e4BAACIVEcUmubPn3+0+hERGGkCAABtadcVwY9XnNMEAADaQmhqgtAEAADaQmhqws3hOQAA0AZCUxOMNAEAgLYQmprwMtIEAADaQGhqws1IEwAAaAOhqQnOaQIAAG0hNDXh8TLSBAAAWkdoasLL4TkAANAGQlMTLg7PAQCANhCamuCSAwAAoC2EpiY4pwkAALSF0NQE5zQBAIC2EJqa4JIDAACgLYSmJtwcngMAAG0gNDXhMYw0AQCA1hGamvAy0gQAANpAaGqCc5oAAEBbCE1NuBhpAgAAbSA0NeH2MNIEAABaR2hqwunxhrsLAAAgQhGammjwcHgOAAC0jtDUhMvjkzEEJwAA0BKhqRkXn6ADAACtIDQ10+AmNAEAgJYITc1wMjgAAGgNoakZJyNNAACgFYSmZhhpAgAArSE0NcM5TQAAoDWEpmacXBUcAAC0gtDUjNPN4TkAANASoakZRpoAAEBrCE3NcCI4AABoDaGpGU4EBwAArSE0NcNIEwAAaA2hqRnOaQIAAK0hNDVT52KkCQAAtERoaobQBAAAWkNoaqbO6Ql3FwAAQASK6NB0zz33yGKxBN369+8fWN7Q0KCZM2cqLS1NCQkJmjJlikpLS7/XNmsZaQIAAK2I6NAkSaeccor27t0buL333nuBZT//+c/12muv6Z///KdWrlypPXv26NJLL/1e26tzMdIEAABaig53Bw4nOjpaWVlZLeZXVlbqb3/7mxYuXKjzzz9fkjR//nwNGDBAa9as0Zlnntmu7dU6GWkCAAAtRXxo+uKLL5STk6OYmBjl5+dr7ty5ysvL07p16+R2u1VQUBBo279/f+Xl5Wn16tXfGZqcTqecTmdguqqqKvB7rdMtt9t9dHYGh3XovqcG4UctIge1iBzUIrJ0dh0iOjSNHDlSCxYsUL9+/bR3717de++9Ouecc7Rp0yaVlJTIbrcrJSUl6G8yMzNVUlLyneudO3eu7r333laXfVNapsWLF3fULqCdCgsLw90FNKIWkYNaRA5qERnq6uo6dXsRHZomTpwY+H3w4MEaOXKkevTooZdeekmxsbHtXu+cOXM0e/bswHRVVZVyc3MlSba4BE2adHb7O43vxe12q7CwUBdccIFsNlu4u3NCoxaRg1pEDmoRWcrKyjp1exEdmppLSUnRySefrO3bt+uCCy6Qy+VSRUVF0GhTaWlpq+dANeVwOORwOFpdVu/y8kCIADabjTpECGoROahF5KAWkaGzaxDxn55rqqamRjt27FB2draGDx8um82mpUuXBpZv27ZNxcXFys/Pb/c2uOQAAABoTUSPNP3yl7/U5MmT1aNHD+3Zs0d33323rFarrrzySiUnJ2vGjBmaPXu2UlNTlZSUpP/5n/9Rfn5+uz85J3HJAQAA0LqIDk27d+/WlVdeqbKyMnXt2lWjRo3SmjVr1LVrV0nSI488oqioKE2ZMkVOp1Pjx4/XE0888b226fYauTw+2aOPqUE4AABwlEV0aHrxxRe/c3lMTIzmzZunefPmdeh261we2aPtHbpOAABwbGM4pYlDo0s1fP8cAABohtDURILdKkmqbiA0AQCAYISmJpJi/Ucrq+q50isAAAhGaGoiMcZ/vYdKQhMAAGiG0NREYox/pInQBAAAmiM0NZHkaDw8xzlNAACgGUJTE0mxHJ4DAACtIzQ1cejwHCeCAwCA5ghNTRw6EZzQBAAAmiM0NZEY479OE4fnAABAc4SmJpIOjTQ1EJoAAEAwQlMThy5uyUgTAABojtDURKKDT88BAIDWEZqaSI7zjzQdrHPLGBPm3gAAgEhCaGqiS6xdkuTy+FTr8oa5NwAAIJIQmpqItVsVZ/d/gq6sxhnm3gAAgEhCaGomLcE/2nSgxhXmngAAgEhCaGomLd4hiZEmAAAQjNDUTFq8f6SprJaRJgAA8C1CUzOHDs+VE5oAAEAThKZm0hL8h+cOcHgOAAA0QWhqJnB4jhPBAQBAE4SmZtIbR5rKahlpAgAA3yI0NRO45EA1I00AAOBbhKZmMhJjJEml1Q1h7gkAAIgkhKZmspL9oamizq16vkoFAAA0IjQ1kxQTHfgqlZIqRpsAAIAfoakZi8Wi7MbRpr2V9WHuDQAAiBSEplZkJ8dKkkoqGWkCAAB+hKZWZAVGmghNAADAj9DUikOH5xhpAgAAhxCaWsFIEwAAaI7Q1ApOBAcAAM0RmlrRLSVOkrSrvC7MPQEAAJGC0NSKvFR/aKpq8Kiijq9TAQAAhKZWxdqtykj0f3Hv12WMNgEAAEJTm3qk+UebvuYQHQAAEKGpTXmp8ZKk4rLaMPcEAABEAkJTGwIjTRyeAwAAIjS1icNzAACgKUJTGw59gu5rDs8BAAARmtp0UtcESVJplVNVDe4w9wYAAIQboakNybE2ZSX5rwz+RWlNmHsDAADCjdD0Hfpm+kebPi+tDnNPAABAuBGavsPJmYmSCE0AAIDQ9J1Obhxp4vAcAAAgNH2HQyNN2xhpAgDghEdo+g59G0PT/mqnymv54l4AAE5khKbvkOCIVq90/9epbNxdEd7OAACAsCI0Hcbg7smSpI27K8PcEwAAEE6EpsMY3D1FEqEJAIATHaHpML4daaoIb0cAAEBYEZoO45ScJEVZpH3VTpVUNoS7OwAAIEyOm9A0b9489ezZUzExMRo5cqQ+/PDDDllvnD06cOmBj4sPdsg6AQDAsee4CE3/+Mc/NHv2bN19991av369hgwZovHjx2vfvn0dsv4zeqVKkop2lnfI+gAAwLEnOtwd6Ah/+MMfdN111+naa6+VJD311FN644039Mwzz+jXv/51i/ZOp1NOpzMwXVVVJUlyu91yu90t2o/IS9Zzq6XVOw60uhwd59D9y/0cftQiclCLyEEtIktn18FijDGdusUO5nK5FBcXp3/961+65JJLAvOnTZumiooKvfrqqy3+5p577tG9997bYv7ChQsVFxfXYn6NW7pjrT9f3j/CowRbx/UfAAC0T11dna666ipVVlYqKSnpqG/vmB9pOnDggLxerzIzM4PmZ2Zm6rPPPmv1b+bMmaPZs2cHpquqqpSbm6sxY8YoLS2t1b95tvgDfb6vRsl9hmv8KZmttsH353a7VVhYqAsuuEA2G+k0nKhF5KAWkYNaRJYPPyvu1O0d86GpPRwOhxwOR4v5NputzQdBfu80fb6vRqt3HtQPhnY/2l084X1XLdC5qEXkoBaRg1qEX9GXZbrm2Y87dZvH/Ing6enpslqtKi0tDZpfWlqqrKysDtvO6P4ZkqSlW/fpGD+iCQDAMW/hh8Vyezv39fiYD012u13Dhw/X0qVLA/N8Pp+WLl2q/Pz8DttO/klpirNbVVLVoM17qjpsvQAA4MitD8NlgI750CRJs2fP1l//+lc9++yz2rp1q2688UbV1tYGPk3XEWJsVp3bt6skqXBL6WFaAwCAo2V/tVO7yutlsXTudo+L0HT55ZfroYce0l133aWhQ4dqw4YNWrJkSYuTw7+vgoH+9b21uaRD1wsAAEJ3aJTppPSWn3g/mo6L0CRJs2bN0tdffy2n06mioiKNHDmyw7dxwYBM2a1R+qykWls4RAcAQFgcCk2DuyV36naPm9DUGZLjbCoY6D8h/N/rd4e5NwAAnJg+/rpCkjSoO6Epok05zX+5gVc3fCO31xfm3gAAcGJxeXz6ZHeFJGkooSmynXtyV3VNdOhAjUtvbNwb7u4AAHBC2bynUk6PT13ibOqZxjlNEc1mjdL0s3pKkv6y6kuu2QQAQCda97X/fKbhPbrI0skfnyM0tcPUkXmKtVm1ZW+VVn6+P9zdAQDghPH+9gOSpBE9Uzt924SmdkiJs2vqyDxJ0gNvfiavj9EmAACOtjqXR+/vKJMknd/4TR2didDUTrPO76PkWJs+K6nWCx927hcGAgBwIlqxbb9cHp9yU2PVNyOh07dPaGqnlDi7bh7bV5L0v4u36qsDtWHuEQAAx7d/fLRLknThoJxOP59JkqI7fYvHkWln9dRbm0tUtLNcP/37Or3003wlx7X9rddfHajVCx8Wa93XB+Xy+tQ3I1EXDs7S6JMzFBXV+cUH2vJ1Wa2WfLpHa4uj5Nu4VxMHd1OMzRrubgE4ge3YX6NVX/jPI77yjNyw9IHQ9D1Yoyx65PKhumTe+9pWWq2rnl6jP189XN27BH8E8rOSKj2+dLsWb9qrph+227i7Uv9ev1u9u8brxtF9dPHQHNmsDP4dzsFal/723k4t37ZPB2td6pEWrx8MydaU07rzwv49Vda59fu3P9PzRcWN/6tRKvznp/rd4m361YR+umx4LgG/Axysdem1jXu0+ZsqOWxRGtkrTRcMzJQ9msc/Tgwuj08bd1eorNallFibTu2WrHjHd0eS3y/ZJmOkggGZ6pEW30k9DUZo+p5yUmL13IwzdOVf1mjzniqNe2SVfjQiV4O7J6uizq3l2/bp3S8OBNqP6ddVFw3NUZw9Wmu+LNO/1u7Wjv21+uU/P9EjhZ/r+nNP0uWn5/Li34p6l1fPvL9TT63YoWqnJzB/T2WDVn9Zpj++84VuPK+3rhqZx/3XDks2lejORZt0oMYpSTqrd6osNQf0lTNO31Q06LZ/f6p/rdutuyefolPb+dUFdS6P1n19UGu+LNNne6u1r9opI6NEh0090+PUu2uCTuoar95dE9S9S5ysx1lAO1Dj1J9X7tDzRcWqc3kD859b/bW6pcRq5pg+umxE905981Ra1aB/rdutwi2lKi6vkyM6SgOzk3TBwExNHpJz2BcyIBQ+n9HWkip9sL1M7+84oA93lgc9BmxWiyacmq2rz+yh03u2vJTAy+t3a8nmEkVZpFvH9+vs7gdYDBcaUlVVlZKTk3XgwAGlpaW1ax27yut084sfa31xRYtlFos0aVC2bjq/r/plJQYtq25w6/miYj397s7Ai1VavF3jTsnSeSena2B2srp3iVVUlEXGGNW5vPqqrFbb99Vo+74a7TxQq6/KanWw1i1JSo23Ky81Tqd2S9ZpeSka3D1FsfZjJ0C43W4tXrxYkyZNks3mP9TZ4Pbq5fXf6NGln6u0yn8fDchO0k/PPUl5aXFa99VBLfjgK31TUS9Jykh06Geje+uKM47/8OTx+lRW69KBGqd8PslnjCwWKcERrcQYmxJjog97H2zZU6VH3vlchVtKJUm9u8brd5cM0oi8JC1evFjjxk/Q8x99o4ff/lz1bq8sFunSYd117dk9DxueXB6ftpVU673tB7Ty831a9/VBub2hPeXYrVHqmR6n7ORYpSXYlZ7gUFq8XSlxNsXZoxVntyrWblWMzSqfz8jtNfL6jNw+nzxeI7fXJ7fXJ5fHJ3fTaa9Pbo+R1+dTRlKMeqXHq0eafztHK6TtKq/Twg+L9ewHXwVeKAY0BpNap0evbtgTePznpcbpprF9g0aemz8uDj0XGEnxdusRn9vh8fq0Ytt+vfjRLi3ftq/NTwDH2636weAcTRnevdUXshNRa89RaMkYox37a1W0s0wfbC/T6i/LVF7rCmrTJc6mnunxKqls0N7KhsD8U3KSNP2snpo0KFsWi/TCh7s0d/FWeXxGN4/tq59fcHKgbVlZmdLT01VZWamkpKSjvl+EJnVMaJL8/yQrtu3XW5tL9E1FvWJsVg3pnqzJQ3IOO5TY4Pbqn2t36amVXwZe/JuKs1vl8Rq5jvCrW6xRFvXuGq+B2Uk6OStRGYkxSkuwy974ZOzy+HSwzqWDdW5V1LlUXuu/lTX+PFjr8j8xO6xKdNiUGm9Xl3i7UuNs/p/xdnWJsyvKYlFlvVuV9W5VN7jV4PapweOVy+OT12eCb8bI5zPyNf7rWSwWRVksctiiZI+SSvd8oz4n9VSsI1rFZXV6b/sBVTf4R5a6pcTq1vH9dNGQnKDDRC6PT/9at1vzlm8P3H9p8Xad1SddvdLilBATLZfHp3q3VzUNHlU7Papp8KjG6ZHHZ5QSa1NKnE1d4uxN9tGu1AS7Ym1WuTw+OT0+ldU4ta/aqX3VDSqrcQX2ucHtlT06So5oqxIc0f5bTHRjeAmetkZZ1OD296Wh8eby+GSMP/T4jGTU8mHZ4PJqX7VTpVUNjX1w6kCNU4d7BMfYopQa59+nLnHf1q/B7dOGXRXaVlod+F/56bkn6aaxfRVjs7Z4cdhTUa8H3vxM//lkT2Dd3VJiNbh7srKSYxRrs8pnpKoGt/ZVOfVNRb2276tuEZJykmN0Zu80DcvropzkGEVZLDpY59LOA7X6cn+tduz3vxlwejr3a4qioyzKTolRdlKsbNH+/0mvz8jT+H/r/+kPZF6fP5zG2vyhLcZmVazt2xAXa7PK7fWpvM6lz/ZWacf+bz8oMqhbsmZfcLJG9+saCCENbq+eLyrWkyu260CN/4UlwRGtQd2SlRpvV4Pbo6++2aeo2ARV1ntUUecOPBfYo7+tb2q8TanxjsDjMy3erhibVdFWi3w+qbS6QZ/trdYHOw4EtiNJI3p00Y9G5OrUbsmqd3u05sty/Wvdbu1s8gGXjESHTsvroh5pceoSb1d0k8efw2aVIzoqsO/xjYE2zh4tm9Wiinq3Dta6tK/aqZLKBu2rblBJZYNKqpzaV9Wginq3kmKi1SXervR4h7omOpSeYG/86VC0NUpen09enwLPHx6f/6eRUZTFImuU/9b0d6vFIotFgeeeFrX0GXm9386PtlqUFGNTcqz/Fu+I9j8vWaPk9PhUVe9WWXW93lv7iTLz+uhgvTvwnOmItiopNlopsc1qEW9TSpxdFkken5Hb07hdY2SM8e+T79BzoRRlscgiKSpKssgiNc6TJKfbK6fH53/e8PiCpxt/d7XyuPH6/K8d/jcRjb97/G8gvD6jGFuU4u3RirVbFW+PVpzDqrjG+tmtUap1eVTn8qrG6VGt06Nap1e1To88Pp8c0YceA1GKtVllJO0+WKfPS2tahKQ4u1Vn9ErV2b3TdVafNA3ISgo8j2/6plL/b83XeuXjb9p87P9wWDc9dNmQoDc3hKYw6KjQ1BHcXp/e335Ayz7bp4++Oqgd+2taPAiSYqJ1cmai+mQkqFd6vHqmxyszKUaStL/aqS/312jDrgqtLz4YGJk51nVLidWMUb009cw8OaLbHjlxeXx6ae0uzVu+Peidy/HMGmVRlzi77FaLLBaLfMYEgmEooqMsGn9qlm4Z21d9M78dCW3rHfX64oOa//5XemtTSUghPjnWphE9uujck7vq3JO7qmda3GFHLHw+o28q6vXlgVrtq2pQWa1LZTVOldW4VFHvVp3Lo3qXV3Uurxo8XkVHRckaZVF0lEXRVots1ijZrP4XO1uT6cDv0VGySNpb2aCvDtRq18G6kEfA2sNikUb1SdePz+yhcQMz29z/OpdHz37wtf723rcjz0dLarxdlw7rpstPzw2q+yHGGBXtLNe/1+3W4k/3qrbJoRQgFI7oKA3NTVF+7zSd3SddQ7qnHPa8vYO1Lr340S49X/S1dh/0vwHOTY3VT8/travOyGtxTiWhKQwiKTQ15/H6dLDOrVqnR9FWi5JjbUpwRIc0TG6MUUlVg7burdKWPVX6cn+t9tc4VV7rCryzibZalBLrP+SREud/Z5TWOIKU1jjiEmWxqNblUWX9odEo/7vG8jr/SFR5rUvGSEmN784SY/zvWByNIy/RURZFRVlktfhf4KMa3wFGWfzvoqTGd0Ien2qdLm3a8pl69Oojl09KT3BoRM8uGp7X5YhOQHZ5fFpffFDrvj6ovZX1qmnwBEYEWhv5qWgcaTtYF7xvZbUuNbh9ckT7X3BT4+3KSIxRRpJDafGOwP3miPaPLDS4vYF3ZNUNHtU43YERrerGn/53dt++M4u1W2WzRjW+K/a/M7bI/0LblD06ShmJMcpMcigjMUZdEx3KTIpRary91cNKXp9RjdOjyjq3f38a9+nQPkZFWXRyZoJG9UlXSpy9xd8f7jBErdOjj4sr9HlptUqrG+Ty+GSRRQkx0cpIdCgrKUb9sxPVLSU24g/reH1G+6obtKu8XvurnfL4fPIZI2tUlKIbRy2+/ekPaMYYNXi8qnf5Rw3r3V453V5/mHN7FR1lUUqcXT3T4jQsr4tS41vex23x+Yw276nS9v3VqqhzK9oi7dj6qcacfYbSEmMbRw39NTk00lFe66/xocdnWeNIsdPjlafx8d410aEeqfEaeVKqTsvrEvKJ5w1urzburtTG3RUqqWxQeZ0rMMLpM0ZOt09Oj1cNbp/q3F7VN45M1Lv8o6hJsTZ1ibc1/v/6/4ezkmKUmRyjzMQYdYm3qbrBo7Ial8pqndrfOIrq/+l/vopu8txhtTb+jPKPyniNf6TIZ4w8Xv9P/6i2/3mwtfoFpq3fznd5faqsd6uqcQS5zuWV0+OV0+2Twxal5FibkhzRaqg8oEEn91TXxBilJTjUJc7mH4lq8KjyUA3qvq3BwTr/iMuh4G6NipI1yj+C5L/570sjyTT22TTet/5p/zL/aF5U4+iOf2QvJtoqR+D3KNmjo1o83iwW/+Fue/ShNxL+323WqMaRb6/qGmvmv/lHk+pcHrm9RnF2q+Id0Yq3Ryve4f89zm6V3Rqlhsa61ze+gTFGykmJUc+0eA3MSfrON7mHU1nnls8YpcTZ2nwOITSFQSSHphMN5wtEDmoROahF5KAWkaWzQxOfbwUAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAACAEBCaAAAAQkBoAgAACAGhCQAAIASEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAE0eHuQCQwxkiSqqurZbPZwtybE5vb7VZdXZ2qqqqoRZhRi8hBLSIHtYgs1dXVkr59HT/aCE2SysrKJEm9evUKc08AAMCRKisrU3Jy8lHfDqFJUmpqqiSpuLi4U+50tK2qqkq5ubnatWuXkpKSwt2dExq1iBzUInJQi8hSWVmpvLy8wOv40UZokhQV5T+1Kzk5mQdBhEhKSqIWEYJaRA5qETmoRWQ59Dp+1LfTKVsBAAA4xhGaAAAAQkBokuRwOHT33XfL4XCEuysnPGoROahF5KAWkYNaRJbOrofFdNbn9AAAAI5hjDQBAACEgNAEAAAQAkITAABACAhNAAAAITjhQ9O8efPUs2dPxcTEaOTIkfrwww/D3aVj3qpVqzR58mTl5OTIYrFo0aJFQcuNMbrrrruUnZ2t2NhYFRQU6IsvvghqU15erqlTpyopKUkpKSmaMWOGampqgtps3LhR55xzjmJiYpSbm6sHH3zwaO/aMWfu3Lk6/fTTlZiYqIyMDF1yySXatm1bUJuGhgbNnDlTaWlpSkhI0JQpU1RaWhrUpri4WBdeeKHi4uKUkZGhW2+9VR6PJ6jNihUrdNppp8nhcKhPnz5asGDB0d69Y8qTTz6pwYMHBy6KmJ+frzfffDOwnDqEzwMPPCCLxaJbbrklMI96dI577rlHFosl6Na/f//A8oirgzmBvfjii8Zut5tnnnnGbN682Vx33XUmJSXFlJaWhrtrx7TFixebO+64w7z88stGknnllVeClj/wwAMmOTnZLFq0yHzyySfmoosuMr169TL19fWBNhMmTDBDhgwxa9asMe+++67p06ePufLKKwPLKysrTWZmppk6darZtGmTeeGFF0xsbKz585//3Fm7eUwYP368mT9/vtm0aZPZsGGDmTRpksnLyzM1NTWBNjfccIPJzc01S5cuNWvXrjVnnnmmOeusswLLPR6POfXUU01BQYH5+OOPzeLFi016erqZM2dOoM2XX35p4uLizOzZs82WLVvM448/bqxWq1myZEmn7m8k+89//mPeeOMN8/nnn5tt27aZ22+/3dhsNrNp0yZjDHUIlw8//ND07NnTDB482Nx8882B+dSjc9x9993mlFNOMXv37g3c9u/fH1geaXU4oUPTGWecYWbOnBmY9nq9Jicnx8ydOzeMvTq+NA9NPp/PZGVlmd///veBeRUVFcbhcJgXXnjBGGPMli1bjCTz0UcfBdq8+eabxmKxmG+++cYYY8wTTzxhunTpYpxOZ6DNbbfdZvr163eU9+jYtm/fPiPJrFy50hjjv+9tNpv55z//GWizdetWI8msXr3aGOMPwVFRUaakpCTQ5sknnzRJSUmB+/9Xv/qVOeWUU4K2dfnll5vx48cf7V06pnXp0sU8/fTT1CFMqqurTd++fU1hYaE577zzAqGJenSeu+++2wwZMqTVZZFYhxP28JzL5dK6detUUFAQmBcVFaWCggKtXr06jD07vu3cuVMlJSVB93tycrJGjhwZuN9Xr16tlJQUjRgxItCmoKBAUVFRKioqCrQ599xzZbfbA23Gjx+vbdu26eDBg520N8eeyspKSd9+SfW6devkdruD6tG/f3/l5eUF1WPQoEHKzMwMtBk/fryqqqq0efPmQJum6zjUhsdS67xer1588UXV1tYqPz+fOoTJzJkzdeGFF7a4z6hH5/riiy+Uk5Ojk046SVOnTlVxcbGkyKzDCRuaDhw4IK/XG3RHS1JmZqZKSkrC1Kvj36H79rvu95KSEmVkZAQtj46OVmpqalCb1tbRdBsI5vP5dMstt+jss8/WqaeeKsl/X9ntdqWkpAS1bV6Pw93XbbWpqqpSfX390didY9Knn36qhIQEORwO3XDDDXrllVc0cOBA6hAGL774otavX6+5c+e2WEY9Os/IkSO1YMECLVmyRE8++aR27typc845R9XV1RFZh+gjag3gmDVz5kxt2rRJ7733Xri7csLq16+fNmzYoMrKSv3rX//StGnTtHLlynB364Sza9cu3XzzzSosLFRMTEy4u3NCmzhxYuD3wYMHa+TIkerRo4deeuklxcbGhrFnrTthR5rS09NltVpbnIVfWlqqrKysMPXq+Hfovv2u+z0rK0v79u0LWu7xeFReXh7UprV1NN0GvjVr1iy9/vrrWr58ubp37x6Yn5WVJZfLpYqKiqD2zetxuPu6rTZJSUkR+cQXLna7XX369NHw4cM1d+5cDRkyRI8++ih16GTr1q3Tvn37dNpppyk6OlrR0dFauXKlHnvsMUVHRyszM5N6hElKSopOPvlkbd++PSIfFydsaLLb7Ro+fLiWLl0amOfz+bR06VLl5+eHsWfHt169eikrKyvofq+qqlJRUVHgfs/Pz1dFRYXWrVsXaLNs2TL5fD6NHDky0GbVqlVyu92BNoWFherXr5+6dOnSSXsT+YwxmjVrll555RUtW7ZMvXr1Clo+fPhw2Wy2oHps27ZNxcXFQfX49NNPg4JsYWGhkpKSNHDgwECbpus41IbH0nfz+XxyOp3UoZONHTtWn376qTZs2BC4jRgxQlOnTg38Tj3Co6amRjt27FB2dnZkPi6O+NTx48iLL75oHA6HWbBggdmyZYu5/vrrTUpKStBZ+Dhy1dXV5uOPPzYff/yxkWT+8Ic/mI8//th8/fXXxhj/JQdSUlLMq6++ajZu3GguvvjiVi85MGzYMFNUVGTee+8907dv36BLDlRUVJjMzExz9dVXm02bNpkXX3zRxMXFccmBZm688UaTnJxsVqxYEfSR3rq6ukCbG264weTl5Zlly5aZtWvXmvz8fJOfnx9YfugjvePGjTMbNmwwS5YsMV27dm31I7233nqr2bp1q5k3bx4frW7m17/+tVm5cqXZuXOn2bhxo/n1r39tLBaLefvtt40x1CHcmn56zhjq0Vl+8YtfmBUrVpidO3ea999/3xQUFJj09HSzb98+Y0zk1eGEDk3GGPP444+bvLw8Y7fbzRlnnGHWrFkT7i4d85YvX24ktbhNmzbNGOO/7MBvfvMbk5mZaRwOhxk7dqzZtm1b0DrKysrMlVdeaRISEkxSUpK59tprTXV1dVCbTz75xIwaNco4HA7TrVs388ADD3TWLh4zWquDJDN//vxAm/r6evOzn/3MdOnSxcTFxZkf/vCHZu/evUHr+eqrr8zEiRNNbGysSU9PN7/4xS+M2+0OarN8+XIzdOhQY7fbzUknnRS0DRjzk5/8xPTo0cPY7XbTtWtXM3bs2EBgMoY6hFvz0EQ9Osfll19usrOzjd1uN926dTOXX3652b59e2B5pNXBYowxRz4+BQAAcGI5Yc9pAgAAOBKEJgAAgBAQmgAAAEJAaAIAAAgBoQkAACAEhCYAAIAQEJoAAABCQGgCAAAIAaEJAAAgBIQmAEfF9OnTZbFYWty2b98e7q4BQLtEh7sDAI5fEyZM0Pz584Pmde3aNWja5XLJbrd3ZrcAoF0YaQJw1DgcDmVlZQXdxo4dq1mzZumWW25Renq6xo8fL0natGmTJk6cqISEBGVmZurqq6/WgQMHAuuqra3VNddco4SEBGVnZ+vhhx/W6NGjdcsttwTaWCwWLVq0KKgPKSkpWrBgQWB6165d+tGPfqSUlBSlpqbq4osv1ldffRVYPn36dF1yySV66KGHlJ2drbS0NM2cOVNutzvQxul06rbbblNubq4cDof69Omjv/3tbzLGqE+fPnrooYeC+rBhwwZG2YDjAKEJQKd79tlnZbfb9f777+upp55SRUWFzj//fA0bNkxr167VkiVLVFpaqh/96EeBv7n11lu1cuVKvfrqq3r77be1YsUKrV+//oi263a7NX78eCUmJurdd9/V+++/r4SEBE2YMEEulyvQbvny5dqxY4eWL1+uZ599VgsWLAgKXtdcc41eeOEFPfbYY9q6dav+/Oc/KyEhQRaLRT/5yU9ajK7Nnz9f5557rvr06dO+OwxAZDAAcBRMmzbNWK1WEx8fH7j913/9lznvvPPMsGHDgtr+9re/NePGjQuat2vXLiPJbNu2zVRXVxu73W5eeumlwPKysjITGxtrbr755sA8SeaVV14JWk9ycrKZP3++McaYv//976Zfv37G5/MFljudThMbG2veeuutQL979OhhPB5PoM1ll11mLr/8cmOMMdu2bTOSTGFhYav7/c033xir1WqKioqMMca4XC6Tnp5uFixYEMK9BiCScU4TgKNmzJgxevLJJwPT8fHxuvLKKzV8+PCgdp988omWL1+uhISEFuvYsWOH6uvr5XK5NHLkyMD81NRU9evX74j688knn2j79u1KTEwMmt/Q0KAdO3YEpk855RRZrdbAdHZ2tj799FNJ/kNtVqtV5513XqvbyMnJ0YUXXqhnnnlGZ5xxhl577TU5nU5ddtllR9RXAJGH0ATgqImPj2/1kFR8fHzQdE1NjSZPnqz/+7//a9E2Ozs75HOBLBaLjDFB85qei1RTU6Phw4fr+eefb/G3TU9Qt9lsLdbr8/kkSbGxsYftx3//93/r6quv1iOPPKL58+fr8ssvV1xcXEj7ACByEZoAhN1pp52mf//73+rZs6eio1s+LfXu3Vs2m01FRUXKy8uTJB08eFCff/550IhP165dtXfv3sD0F198obq6uqDt/OMf/1BGRoaSkpLa1ddBgwbJ5/Np5cqVKigoaLXNpEmTFB8fryeffFJLlizRqlWr2rUtAJGFE8EBhN3MmTNVXl6uK6+8Uh999JF27Niht956S9dee628Xq8SEhI0Y8YM3XrrrVq2bJk2bdqk6dOnKyoq+Cns/PPP15/+9Cd9/PHHWrt2rW644YagUaOpU6cqPT1dF198sd59913t3LlTK1as0E033aTdu3eH1NeePXtq2rRp+slPfqJFixYF1vHSSy8F2litVk2fPl1z5sxR3759lZ+f3zF3FICwIjQBCLucnBy9//778nq9GjdunAYNGqRbbrlFKSkpgWD0+9//Xuecc44mT56sgoICjRo1qsW5UQ8//LByc3N1zjnn6KqrrtIvf/nLoMNicXFxWrVqlfLy8nTppZdqwIABmjFjhhoaGo5o5OnJJ5/Uf/3Xf+lnP/uZ+vfvr+uuu061tbVBbWbMmCGXy6Vrr732e9wzACKJxTQ/AQAAjhGjR4/W0KFD9cc//jHcXWnh3Xff1dixY7Vr1y5lZmaGuzsAOgDnNAFAB3I6ndq/f7/uueceXXbZZQQm4DjC4TkA6EAvvPCCevTooYqKCj344IPh7g6ADsThOQAAgBAw0gQAABACQhMAAEAICE0AAAAhIDQBAACEgNAEAAAQAkITAABACAhNAAAAISA0AQAAhOD/A6DC4haOS5MsAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Estimacion_PMUSIC = spectrum.pmusic(Resultado_Desfasaje, IP=100, NSIG=20, sampling=1/Periodo_Muestreo_Lenta)\n", + "Fig_MMUSIC = Estimacion_PMUSIC.plot()\n", + "\n", + "# Obtener la figura y los ejes\n", + "fig = plt.gcf()\n", + "ax = fig.axes[0]\n", + "\n", + "# Establecer los límites de los ejes\n", + "ax.set_xlim([0, 2]) # Reemplaza f_min y f_max por los valores deseados\n", + "#ax.set_ylim([p_min, p_max]) # Reemplaza p_min y p_max por los valores deseados\n", + "\n", + "# Mostrar el gráfico\n", + "plt.show()\n", + "\n", + "Fig_MMUSIC = Estimacion_PMUSIC.plot()\n", + "\n", + "fig1 = plt.gcf()\n", + "\n", + "ax1 = fig1.axes[0]\n", + "\n", + "ax1.set_xlim([0, 0.5]) # Reemplaza f_min y f_max por los valores deseados\n", + "#ax.set_ylim([p_min, p_max]) # Reemplaza p_min y p_max por los valores deseados\n", + "\n", + "# Mostrar el gráfico\n", + "plt.show()\n", + "\n", + "Fig_MMUSIC = Estimacion_PMUSIC.plot()\n", + "\n", + "fig1 = plt.gcf()\n", + "\n", + "ax1 = fig1.axes[0]\n", + "\n", + "ax1.set_xlim([0, 0.1]) # Reemplaza f_min y f_max por los valores deseados\n", + "#ax.set_ylim([p_min, p_max]) # Reemplaza p_min y p_max por los valores deseados\n", + "\n", + "# Mostrar el gráfico\n", + "plt.show()\n", + "\n", + "Fig_MMUSIC = Estimacion_PMUSIC.plot()\n", + "\n", + "fig1 = plt.gcf()\n", + "\n", + "ax1 = fig1.axes[0]\n", + "\n", + "\n", + "# Mostrar el gráfico\n", + "plt.show()" + ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "PrimerKernel", "language": "python", - "name": "python3" + "name": "primerkernel" }, "language_info": { "codemirror_mode": { @@ -466,7 +664,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.6" + "version": "3.12.3" } }, "nbformat": 4,