{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adquisición de datos automatizada\n",
    "![](logo_fifa.png)\n",
    "\n",
    "En este notebook vamos a presentar la adquisición automática de datos, a partir de un osciloscopio Tektronix TDS2000. La idea es que saquemos información relevante de estos datos, veremos que tenemos a mano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import visa\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para la adquisición hicimos una clase que abstrae el uso del osciloscopio TDS2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class Osciloscopio(object):\n",
    "    '''Clase para el manejo osciloscopio TDS2000 usando PyVISA de interfaz'''\n",
    "    def __init__(self, resource):\n",
    "        #Defino el recurso\n",
    "        self._osci = visa.ResourceManager(\"@py\").open_resource(resource)\n",
    "        self._osci.query(\"*IDN?\")\n",
    "\n",
    "        #Configuración de curva\n",
    "        self._osci.write('DAT:ENC RPB') # Modo de transmision: Binario positivo. \n",
    "        self._osci.write('DAT:WID 1') #1 byte de dato. Con RPB 127 es la mitad de la pantalla\n",
    "        self._osci.write(\"DAT:STAR 1\") #La curva mandada inicia en el primer dato\n",
    "        self._osci.write(\"DAT:STOP 2500\") #La curva mandada finaliza en el último dato\n",
    "\n",
    "\n",
    "        #Adquisición por sampleo\n",
    "        self._osci.write(\"ACQ:MOD SAMP\")\n",
    "\n",
    "        #Seteo de canal\n",
    "        self.setCanal(canal = 1, escala = 20e-3)\n",
    "        self.setCanal(canal = 2, escala = 20e-3)\n",
    "        self.setTiempo(escala = 1e-3, cero = 0)\n",
    "\n",
    "        #Bloquea el control del osciloscopio\n",
    "        self._osci.write(\"LOC\")\n",
    "\n",
    "    def __del__(self):\n",
    "        self._osci.write(\"UNLOC\") #Desbloquea el control del osciloscopio\n",
    "        self._osci.close()\n",
    "\n",
    "    def setCanal(self, canal, escala, cero = 0):\n",
    "        #if coup != \"DC\" or coup != \"AC\" or coup != \"GND\":\n",
    "        #coup = \"DC\"\n",
    "        #self._osci.write(\"CH{0}:COUP \".format(canal) + coup) #Acoplamiento DC\n",
    "        #self._osci.write(\"CH{0}:PROB \n",
    "        print\n",
    "        self._osci.write(\"CH{0}:SCA {1}\".format(canal,escala))\n",
    "        self._osci.write(\"CH{0}:POS {1}\".format(canal,cero))\n",
    "\n",
    "    def getCanal(self,canal):\n",
    "        return self._osci.query(\"CH{0}?\".format(canal))\n",
    "\n",
    "    def setTiempo(self, escala, cero = 0):\n",
    "        self._osci.write(\"HOR:SCA {0}\".format(escala))\n",
    "        self._osci.write(\"HOR:POS {0}\".format(cero))\t\n",
    "        \n",
    "    def getTiempo(self):\n",
    "        return self._osci.query(\"HOR?\")\n",
    "    \n",
    "    def getVentana(self,canal):\n",
    "        self._osci.write(\"SEL:CH{0} ON\".format(canal)) #Hace aparecer el canal en pantalla. Por si no está habilitado\n",
    "        self._osci.write(\"DAT:SOU CH{0}\".format(canal)) #Selecciona el canal\n",
    "        #xze primer punto de la waveform\n",
    "        #xin intervalo de sampleo\n",
    "        #ymu factor de escala vertical\n",
    "        #yoff offset vertical\n",
    "        xze, xin, yze, ymu, yoff = self._osci.query_ascii_values('WFMPRE:XZE?;XIN?;YZE?;YMU?;YOFF?;', \n",
    "                                                                 separator=';') \n",
    "        data = (self._osci.query_binary_values('CURV?', datatype='B', \n",
    "                                               container=np.array) - yoff) * ymu + yze        \n",
    "        tiempo = xze + np.arange(len(data)) * xin\n",
    "        return tiempo, data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rm = visa.ResourceManager('@py')\n",
    "rm.list_resources()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "osci = Osciloscopio('USB0::0x0699::0x0363::C108013::INSTR')\n",
    "osci.setCanal(1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fa81c388860>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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x52HU048VM7WyQmXUExZGPU7Q+MnUWDFVVyzoWWijL1bmSwTQ+Iu0/RZLK/eBWzIOK3ou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\nEJIYNH5CCEkMGj8hhCQGjZ8QQhLj/wExBOJY+7mAtwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa82028f2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t,V = osci.getVentana(1)\n",
    "plt.plot(t,V,\"r-\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}