Generador_SDG1062X.ipynb

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    "# SDG1062X Function Generator as an arbitrary waveform generator. Development of a pyVISA communication library.\n",
    "\n",
    "- **Author:** Juan del Pino Mena\n",
    "- **Version:** v03\n",
    "\n",
    "\n",
    "# Changelog\n",
    "\n",
    "- **V01 - 01/02/2022 - Juan del Pino Mena**\n",
    "    - Initial implementation.\n",
    "    - Methods for sending samples to the arbitrary waveform generator .\n",
    "- **V02 - 30/03/2022 - Juan del Pino Mena**\n",
    "    - Implementation of burst commands, to trigger signals at demand.\n",
    "    - New function to quicky configure and send sample sending from a .csv file to the function generator.\n",
    "- **V03 - 05/04/2022 - Juan del Pino Mena**\n",
    "    - English translation.\n",
    "    - Minor improvements and notebook reorganization.\n",
    "    - Added pip commands to automatically install requirements\n",
    "    \n",
    "## Known issues\n",
    "\n",
    "- Seems like sending long samples vectors causes the generator to not detect the command termination. This causes the next command to be interpreted as samples and  to output some weird, digital shapes at the end of the desired function. This is paliated by sending inmediately after an empty command with only \"\\r\\n\"."
   ]
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   "source": [
    "---\n",
    "\n",
    "# Introduction\n",
    "\n",
    "## Python requirements\n",
    "\n",
    "- numpy\n",
    "- matplotlib\n",
    "- pyvisa\n"
   ]
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      "WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.\n",
      "Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.\n",
      "To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.\n",
      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n"
     ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (1.20.2+mkl)\n"
     ]
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      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n",
      "WARNING: You are using pip version 21.1.dev0; however, version 22.1 is available.\n",
      "You should consider upgrading via the 'S:\\WinPython\\python-3.9.4.amd64\\python.exe -m pip install --upgrade pip' command.\n",
      "WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.\n",
      "Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.\n",
      "To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.\n",
      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (3.4.1)\n",
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      "Requirement already satisfied: numpy>=1.16 in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from matplotlib) (1.20.2+mkl)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from matplotlib) (2.4.7)\n",
      "Requirement already satisfied: pillow>=6.2.0 in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from matplotlib) (8.2.0)\n",
      "Requirement already satisfied: six in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from cycler>=0.10->matplotlib) (1.15.0)\n"
     ]
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     "text": [
      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n",
      "WARNING: You are using pip version 21.1.dev0; however, version 22.1 is available.\n",
      "You should consider upgrading via the 'S:\\WinPython\\python-3.9.4.amd64\\python.exe -m pip install --upgrade pip' command.\n",
      "WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.\n",
      "Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.\n",
      "To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.\n",
      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pyvisa in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (1.11.3)\n",
      "Requirement already satisfied: typing-extensions in s:\\winpython\\python-3.9.4.amd64\\lib\\site-packages (from pyvisa) (3.7.4.3)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: S:\\WinPython\\python-3.9.4.amd64\\Include\\UNKNOWN\n",
      "sysconfig: S:\\WinPython\\python-3.9.4.amd64\\Include\n",
      "WARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\n",
      "WARNING: You are using pip version 21.1.dev0; however, version 22.1 is available.\n",
      "You should consider upgrading via the 'S:\\WinPython\\python-3.9.4.amd64\\python.exe -m pip install --upgrade pip' command.\n"
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   ],
   "source": [
    "import pip\n",
    "\n",
    "pip.main(['install', 'numpy'])\n",
    "pip.main(['install', 'matplotlib'])\n",
    "pip.main(['install', 'pyvisa'])"
   ]
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   "id": "1c52725b-f149-4a92-b3f7-0677cceb167d",
   "metadata": {},
   "source": [
    "---"
   ]
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   "cell_type": "markdown",
   "id": "17eaabc0-3bb8-4781-8baa-e12332a18139",
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    "\n",
    "## Function generator network interface configuration\n",
    "\n",
    "1. Connect the function generator and your PC to the same local network. Some considerations:\n",
    "    - This library was developed using wired Ethernet LAN cables for both devices.\n",
    "    - The router and hub on the GranaSat Lab nº 11 has a 192.168.1.0/24 network. If I'm not wrong, the router has not Wi-Fi enabled so it won't work over Wi-Fi (like IMUDS or eduroam). Make sure you are connected to this LAN by typing `ipconfig` (windows), or `ifconfig` or `ip addr` (linux). Your address should be on that network. You may need to deactivate the Wi-Fi connection of your laptop (modern PCs can can use both simultaneously and this can be troublesome).\n",
    "    - For convenience, this guide sets a fixed IP to the generator and assumes you are using DHCP on your PC. This way, there is no need to figure out what IP is the generator using everytime you power it up.\n",
    "2. Access the LAN interface setup on the function generator and configure a fixed IP.\n",
    "    - \"Utility\" button >> Page 2 >> Interface >> LAN setup \n",
    "    - Set IP address to a free IP i.e.: 192.168.1.101\n",
    "    - Set the subnet mask to: 255.255.255.0 (meaning /24)\n",
    "    - Gateway: 192.168.1.1\n",
    "    - Accept. A message pops saying: \"Set Up successfully.\"\n",
    "    - Make sure DHCP is off.\n",
    "3. Check if the device is accessible.\n",
    "    - Do a ping to the device: `ping 192.168.1.101` (windows & linux).\n",
    "    - [Optional] If you have it installed, nmap can give you some more information about the device. `sudo nmap -O 192.168.1.101` (linux). It should appear as a 'Texas Instruments' network device."
   ]
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   "source": [
    "![ping](images/ping.png)\n",
    "![nmap](images/nmap.png)"
   ]
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    "## References\n",
    "\n",
    "[1] SDG Series Arbitrary Waveform Generator Programming Guide. PG02_E04A. Siglent Technologies CO. LTD.\n",
    "\n",
    "[2] SDG1000X Series Function/Arbitrary Waveform Generator User Manual. UM0201X-E01D. Siglent Technologies CO. LTD.\n",
    "\n",
    "[3] PyVISA documentation. https://pyvisa.readthedocs.io/en/latest/index.html"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4055234d-d360-4318-8148-9f83e4b0c6f9",
   "metadata": {},
   "source": [
    "### SDG1000X Programming Guide"
   ]
  },
  {
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   "id": "c2c667c0-4596-44eb-87d9-543a5526d264",
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    {
     "data": {
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       "\n",
       "        <iframe\n",
       "            width=\"1000\"\n",
       "            height=\"700\"\n",
       "            src=\"./docs/SDG_programming_guide.pdf\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
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    "from IPython.display import IFrame, display\n",
    "IFrame(\"./docs/SDG_programming_guide.pdf\", width=1000, height=700)"
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   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa0a84c7-50dc-4099-a37c-c223a0837e90",
   "metadata": {},
   "source": [
    "# SDG1062X PyVISA communication library"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fe46ef9-56e4-4c21-a4a7-93d5c84c6dc9",
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   "source": [
    "## Library implementation: class."
   ]
  },
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   "source": [
    "import pyvisa as visa\n",
    "import binascii\n",
    "\n",
    "\n",
    "class SDG1062X:\n",
    "    \"\"\"\n",
    "    Methods to communicate with the Siglent SDG1062X arbitrary waveform \n",
    "    generator. May be compatible with other device series like SDG1000X, 2000X \n",
    "    and 6000X/X-E.\n",
    "    Usage of SCPI (Standard Commands for Programmable Instruments) commands.\n",
    "    \n",
    "    CHANGELOG\n",
    "    - V01 - 01/02/2022 - Juan del Pino Mena\n",
    "        - Initial implementation.\n",
    "        - Methods for sending samples to the arbitrary waveform generator.\n",
    "    - V02 - 30/03/2022 - Juan del Pino Mena\n",
    "        - Implementation of burst commands, to trigger signals at demand.\n",
    "    - V03 - 05/04/2022 - Juan del Pino Mena\n",
    "        - English translation.\n",
    "    \n",
    "    KNOWN ISSUES\n",
    "    - Seems like sending long samples vectors causes the generator to not detect\n",
    "    the command termination. This causes the next command to be interpreted as \n",
    "    samples and  to output some weird, digital shapes at the end of the desired \n",
    "    function. This can be paliated by sending inmediately after an empty command \n",
    "    with only \"\\r\\n\".    \n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, device_resource : str, timeout=50, chunk_size=24*1024*1024):\n",
    "        \"\"\"\n",
    "        Constructor. Default configuration based on Siglent's python example.\n",
    "        :param device_resource: Device resource identification.\n",
    "        \"\"\"\n",
    "        self.timeout = timeout\n",
    "        self.chunk_size = chunk_size\n",
    "        self.device_resource = device_resource\n",
    "        self.device_resource_manager = visa.ResourceManager('@py')\n",
    "        self.device = self.device_resource_manager.open_resource(self.device_resource, \n",
    "                                                                 timeout=self.timeout, \n",
    "                                                                 chunk_size=self.chunk_size)\n",
    "        self.device.write_termination = ''\n",
    "        \n",
    "    def query(self, cmd: str):\n",
    "        \"\"\"\n",
    "        Sends a command and waits for a reply.\n",
    "        :param cmd: command to send\n",
    "        \"\"\"\n",
    "        return self.device.query(cmd)\n",
    "        \n",
    "    def write(self, cmd: str, termination=\"\", encoding=\"latin1\"):\n",
    "        \"\"\"\n",
    "        Sends a command without expecting a reply.\n",
    "        :param cmd: command to send\n",
    "        \"\"\"\n",
    "        return self.device.write(cmd, encoding=encoding, termination=termination)\n",
    "        \n",
    "    # SYSTEM COMMANDS\n",
    "    \n",
    "    def identify(self):\n",
    "        \"\"\"\n",
    "        Asks the function generator to identify itself.\n",
    "        Sends: *IDN?\n",
    "        \"\"\"\n",
    "        cmd = \"*IDN?\"\n",
    "        return self.query(cmd)\n",
    "    \n",
    "    def reset(self):\n",
    "        \"\"\"\n",
    "        Resets the function generator.\n",
    "        Sends: *RST\n",
    "        \"\"\"\n",
    "        cmd = \"*RST\"\n",
    "        return self.write(cmd)\n",
    "    \n",
    "    # OUTPUT COMMANDS\n",
    "    \n",
    "    def output_config(self, channel: int, enabled: bool, load: str):\n",
    "        \"\"\"\n",
    "        Output channels configuration.\n",
    "        C<channel>:OUTPut ON|OFF,LOAD,<load>\n",
    "        Programming Guide pag. 17\n",
    "        \n",
    "        :param channel: Output channel (1 or 2).\n",
    "        :param enabled: Wether if output is enabled. True: ON, False: OFF\n",
    "        :param load: Output load, in ohms. Can be \"HZ\" (High Impedance).\n",
    "        \"\"\"\n",
    "        if enabled:\n",
    "            output = \"ON\"\n",
    "        else:\n",
    "            output = \"OFF\"\n",
    "        cmd = f\"C{str(channel)}:OUTPut {output},LOAD,{load}\"\n",
    "        return self.write(cmd)\n",
    "    \n",
    "    def output_basic_wave(self, \n",
    "                          channel: int, \n",
    "                          wave_type: str, \n",
    "                          freq: int,\n",
    "                          amp: float):\n",
    "        \"\"\"\n",
    "        Generates a basic wave.\n",
    "        C<channel>:BaSic_WaVe WVTP,<wave_type>,FRQ,<freq>,AMP,<amp>\n",
    "        Programming guide pag 18,19,20\n",
    "        :param channel: Output channel (1 or 2).\n",
    "        :param wave_type: Output signal name. Only tested with \"SINE\" and \"ARB\"\n",
    "        :param freq: Frequency of the signal period repetition.\n",
    "        :param amp: signal Vpp amplitude.\n",
    "        \"\"\"\n",
    "        cmd = f\"C{str(channel)}:BaSic_WaVe WVTP,{wave_type},FRQ,{freq},AMP,{amp}\"\n",
    "        return self.write(cmd)\n",
    "    \n",
    "    # ARBITRARY WAVE COMMANDS\n",
    "        \n",
    "    def arb_output(self, channel, wave_name):\n",
    "        \"\"\"\n",
    "        Output a device-stored arbitrary waveform.\n",
    "        Programming guide pag 30, 31\n",
    "        :param channel: Output channel (1 or 2).\n",
    "        :param wave_name: Name of the signal to output.\n",
    "        \"\"\"\n",
    "        cmd = f\"C{channel}:ARWV NAME,{wave_name}\"\n",
    "        return self.write(cmd)\n",
    "    \n",
    "    def arb_sample_rate(self, \n",
    "                        channel: int, \n",
    "                        sample_rate: int, \n",
    "                        interpolation=\"LINE\",\n",
    "                        sample_rate_mode=\"DDS\"):\n",
    "        \"\"\"\n",
    "        Sets the sampling mode and rate of the arbitrary function generator.\n",
    "        <channel>:SampleRATE MODE,<mode>,VALUE,<sample_rate>,INTER,<interpolation>\n",
    "        Programming guide pag 48, 49\n",
    "        \n",
    "        For the SDG1062X model, I strongly recommend using DDS (Direct Digital \n",
    "        Synthesis) over TARB (True ARB), as SDG1062X does not have linear or \n",
    "        sinc interpolation. in DDS, samples are stair-interpolated but in TARB \n",
    "        are not, and signal is much more step.\n",
    "        \n",
    "        :param channel: Output channel (1 or 2).\n",
    "        :param sample_rate: Sampling frequency (only for TARB)\n",
    "        :param sample_rate_mode: \"DDS\" or \"TARB\"\n",
    "        :param interpolation: \"LINE\", \"HOLD\" or \"SINC\". Doesn't work on SDG1062X\n",
    "        \"\"\"\n",
    "        cmd = f\"C{channel}:SRATE MODE,{sample_rate_mode},VALUE,{sample_rate},INTER,{interpolation}\"\n",
    "        return self.write(cmd)\n",
    "    \n",
    "    def arb_send_samples(self,\n",
    "                         channel: int,\n",
    "                         wave_name: str, \n",
    "                         freq: int, \n",
    "                         amp: float, \n",
    "                         bin_data: str,\n",
    "                         len_data: int):\n",
    "        \"\"\"\n",
    "        Send arbiatry function data to the signal generator. Must be \n",
    "        pre-converted to binary-ascii. Use the utils to convert data to the \n",
    "        right format. (at the end of this class, marked as staticmethods)\n",
    "        \n",
    "        C<channel>:WVDT WVNM,<wave_name>,FREQ,<freq>,AMPL,<amp>,WAVEDATA,<wave_data>\n",
    "        Programming guide pag 42,43\n",
    "        \n",
    "        :param wave_name: The name your signal will be stored as.\n",
    "        :param wave_data: Sample vector with samples formatted as binascii\n",
    "        \"\"\"\n",
    "        cmd = f\"C{channel}:WVDT WVNM,{wave_name},FREQ,{freq:.3f},AMPL,{amp:.3f},OFST,0.0,PHASE,0.0,WAVEDATA,{bin_data}\"\n",
    "        print(f\"bytes: {len(cmd)}\")\n",
    "        return self.write(cmd, encoding='latin1', termination='')\n",
    "    \n",
    "    def arb_get_samples(self, wave_name):\n",
    "        \"\"\"\n",
    "        Get user-defined wave data\n",
    "        C<channel>:WVDT? USER,<wave_name>\n",
    "        Programming guide pag 43\n",
    "        \n",
    "        :param wave name:\n",
    "        :type wave_name str\n",
    "        \"\"\"        \n",
    "        cmd = f\"WVDT? USER,{wave_name}\"\n",
    "        return self.query(cmd)\n",
    "    \n",
    "    # BURST COMMANDS\n",
    "    \n",
    "    def burst_config(self, channel: int, state: str, trigger_source='INT'):\n",
    "        \"\"\"\n",
    "        Busrt configuration.\n",
    "        \n",
    "        <channel>:BursTWaVe <parameter>,<value>\n",
    "        Programming guide pag 27, 28\n",
    "        \n",
    "        :param channel Generator channel (1 or 2)\n",
    "        :param state {'ON', 'OFF'} Enable/Disable burst\n",
    "        :param trigger_source {'EXT', 'INT', 'MAN'} (External, Internal, Manual)\n",
    "        :param trigger_delay seconds to wait to trigger the generator.\n",
    "        \"\"\"\n",
    "        cmd = f\"C{channel}:BursTWaVe STATE,{state},TRSR,{trigger_source}\"\n",
    "        self.write(cmd)\n",
    "        \n",
    "    def burst_send_manual_single_channel(self, channel: int, trigger_delay=0):\n",
    "        \"\"\"\n",
    "        Sends a manual trigger to a channel.\n",
    "\n",
    "        <channel>:BursTWaVe <parameter>,<value>\n",
    "        Programming guide pag 27, 28\n",
    "        \n",
    "        :param channel Generator channel (1 or 2)\n",
    "        :param trigger_delay seconds to wait to trigger the generator.\n",
    "        \"\"\"        \n",
    "        cmd = f\"C{channel}:BursTWaVe STATE,ON,TRSR,MAN,DLAY,{trigger_delay}\"\n",
    "        self.write(cmd)\n",
    "        cmd = f\"C{channel}:BursTWaVe MTRIG\"\n",
    "        self.write(cmd)\n",
    "        \n",
    "    def burst_send_manual_both_channels(self, \n",
    "                                        ch1_trigger_delay=0,\n",
    "                                        ch2_trigger_delay=0):\n",
    "        \"\"\"\n",
    "        Sends a manual trigger to both channels.\n",
    "        \n",
    "        <channel>:BursTWaVe <parameter>,<value>\n",
    "        Programming guide pag 27, 28\n",
    "        \n",
    "        :param ch1_trigger_delay trigger delay of channel 1\n",
    "        :param ch2_trigger_delay trigger delay of channel 2\n",
    "        \"\"\"\n",
    "        cmd = f\"C1:BursTWaVe STATE,ON,TRSR,MAN,DLAY,{ch1_trigger_delay}\"\n",
    "        self.write(cmd)\n",
    "        cmd = f\"C2:BursTWaVe STATE,ON,TRSR,MAN,DLAY,{ch2_trigger_delay}\"\n",
    "        self.write(cmd)\n",
    "        \n",
    "        cmd = f\"C1:BursTWaVe MTRIG\"\n",
    "        self.write(cmd)\n",
    "        cmd = f\"C2:BursTWaVe MTRIG\"\n",
    "        self.write(cmd)\n",
    "        \n",
    "    # STATIC METHODS, UTILS\n",
    "    \n",
    "    @staticmethod\n",
    "    def samples_int_C2_to_bytes(samples_int_C2 : list):\n",
    "        \"\"\"\n",
    "        Standalone function (util) to convert a sample vector in two's \n",
    "        complement-ready format (unsigned int) to binascii.\n",
    "         \n",
    "        The generator expects a two's complement, littl-endian, 2-bytes samples. \n",
    "        Based on Siglent's Python example: first transforms the data to hex,\n",
    "        switches byte order and then converts to binany-ascii using \n",
    "        binascii.unhexlify() from binascii python library.\n",
    "        \n",
    "        :param samples_int_C2: list of samples in C2, unsigned.\n",
    "        :returns samples_bytes: list of samples in binary ascii ready to be sent \n",
    "        \"\"\"        \n",
    "        # transforma enteros a hex de forma más compacta que en el ejemplo de Siglent.\n",
    "        samples_hex = [f\"{(sample):04x}\" for sample in samples_int_C2]\n",
    "        \n",
    "        # invierte el orden de los bytes en hexadecimal (little)\n",
    "        samples_hex_little = [sample[2:4] + sample[:2] for sample in samples_hex]\n",
    "        \n",
    "        # convierte los datos hex little a binario codificado en ascii\n",
    "        samples_bytes = [binascii.unhexlify(sample) for sample in samples_hex_little]\n",
    "        \n",
    "        return samples_bytes\n",
    "    \n",
    "    @staticmethod\n",
    "    def samples_float_to_int_C2(samples_float : list, amp=None):\n",
    "        \"\"\"\n",
    "        Standalone function (util) to convert a sample vector in floating point\n",
    "        to integer. Negatives are transformed to two's complement unsigned int.\n",
    "        \n",
    "        Sample values are selected from the amp param. All values are scaled by\n",
    "        this value. If no amplitude is specified, the function will select the\n",
    "        absolute maximum as signal amplitude.  \n",
    "        \n",
    "        IMPORTANT: Although the function generator datasheet indicates a 14 bit \n",
    "        vertical resolution, the device expects 16-bit samples which i suspect\n",
    "        transforms internally to the DAC maximum resolution. \n",
    "        This means the maximum sample value range it's not [-8192, +8191] but \n",
    "        [-32768, +32767].\n",
    "        \n",
    "        :param samples_float list of samples in float, can be signed.\n",
    "        :param amp: maximum absolute signal amplitude.\n",
    "        :type amp float\n",
    "        :returns samples_int_C2: list of samples on int C2, unsigned format.\n",
    "        \"\"\"\n",
    "        if not amp:  # Por defecto usa el rango máximo de la señal.\n",
    "            amp = max(abs(samples_float))\n",
    "            \n",
    "        n_bits_dac = 16  # nº de bits del DAC. Aunque diga que son 14, entiende 16.\n",
    "        n_points_totales = 2 ** n_bits_dac\n",
    "        n_points = (n_points_totales / 2) - 1  # nº de cuantos del DAC, de cero a un extremo.\n",
    "        factor = n_points / amp  # Factor de escalado de las muestras\n",
    "        \n",
    "        samples_int_signed = [int(round(sample * factor)) \n",
    "                              for sample in samples_float]\n",
    "        samples_int_C2 = []\n",
    "        for sample in samples_int_signed:\n",
    "            if sample < 0:\n",
    "                samples_int_C2.append(sample + n_points_totales)\n",
    "            else:\n",
    "                samples_int_C2.append(sample)\n",
    "                \n",
    "        return samples_int_C2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73badd78-1ff9-4085-bea6-a111775f1d15",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fce3090-e14b-44cd-9100-d7e985bbd043",
   "metadata": {},
   "source": [
    "## Library basic usage example.\n",
    "\n",
    "This teaches the absolute basics of how the class work. Feel free to experiment.\n",
    "\n",
    "See below for a util to configure and send samples from a file automatically.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9df7f2c5-da54-4b68-90dc-4a67f243eccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DEVICE_IP is a constant throughout all this notebook\n",
    "# If you are using any other interface you'll need to find how to identify the\n",
    "# resource. Check pyVISA documentation.\n",
    "\n",
    "DEVICE_IP = \"192.168.1.178\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6cda4311-417f-47a6-bb82-0d1df0d38923",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Siglent Technologies,SDG1062X,SDG1XCAD1R3295,1.01.01.33R1B6\\n'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Identify the device\n",
    "\n",
    "Generador = SDG1062X(device_resource=f\"TCPIP0::{DEVICE_IP}::inst0::INSTR\")\n",
    "Generador.identify()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b1705502-a2c3-4131-8a7a-8a616501011d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Generador.reset()  # Reset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fda191ab-2c25-44e1-8f2c-8636a2bad95d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output a sine wave of 10 kHz and 2 Vpp with a HZ load on channel 1.\n",
    "Generador.output_config(channel=1, enabled=True, load=\"HZ\")\n",
    "Generador.output_basic_wave(channel=1, wave_type=\"SINE\", freq=1e4, amp=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "92e78651-07f6-4d3f-9a5a-778b6ed4ba9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "41"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Output a sine wave of 10 kHz and 2 Vpp with a HZ load on channel 2.\n",
    "Generador.output_config(channel=2, enabled=True, load=\"HZ\")\n",
    "Generador.output_basic_wave(channel=2, wave_type=\"SINE\", freq=1e4, amp=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "003dce4a-dc00-41aa-a6be-e8d891a03bf2",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# Configure and send samples to the generator automatically. \n",
    "\n",
    "This function opens a communication channel with the generator, reads a .csv file with samples (expecting samples taken with Picoscope Tree Inspection Kit from ADIME) and sends its samples to the signal generator. Sets all configuration and parameters automatically.\n",
    "\n",
    "***IMPORTANT**: FOR NOW IT ONLY READS FILES WITH \"ENGLISH\" LOCALIZATION FORMAT (\".\" decimal, \",\" delimiter)*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4dbfefb-64fd-4472-9c0e-d6c334751c91",
   "metadata": {},
   "source": [
    "## Auxiliary function to graph samples once sent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7b37fff8-c52a-46a7-b4f6-67ba2ef8a106",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "def graphSamples(time, emitter, receiver, title, xlim=[]):\n",
    "    \"\"\"\n",
    "    Graphs signal samples vectors.\n",
    "    \n",
    "    :param time: time vector, in seconds\n",
    "    :param emitter: emitter samples\n",
    "    :param receiver: receiver samples\n",
    "    \n",
    "    :param title: graph title\n",
    "    :param xlim: horizontal limits in ms\n",
    "    :param ylim: vertical limits\n",
    "    \"\"\"\n",
    "    \n",
    "    t_ms = np.array(time) * 1e3\n",
    "    receiver_mV = np.array(receiver) * 1e3\n",
    "    \n",
    "    plt.rcParams[\"font.family\"] = \"Libertinus Serif\"\n",
    "    plt.rcParams['font.size'] = 14\n",
    "    plt.rcParams['mathtext.fontset'] = 'custom'\n",
    "    plt.rcParams['mathtext.rm'] = 'Libertinus Serif'\n",
    "    plt.rcParams['mathtext.it'] = 'Libertinus Serif:italic'\n",
    "    plt.rcParams['mathtext.bf'] = 'Libertinus Serif:bold'\n",
    "\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=[10, 5])\n",
    "    \n",
    "    fig.canvas.toolbar_visible = True\n",
    "    fig.canvas.header_visible = True\n",
    "    fig.canvas.resizable = True\n",
    "\n",
    "\n",
    "    plot_1 = ax.plot(t_ms, emitter, linestyle=\"solid\", marker=\".\", markersize=4, linewidth=1, color='tab:blue', label=\"Emitter\")\n",
    "    \n",
    "    ax.grid(True, which='major', color='#DDDDDD', linestyle='-', linewidth=0.6)\n",
    "    ax.grid(True, which='minor', color='#DDDDDD', linestyle=':', linewidth=0.6)\n",
    "    ax.ticklabel_format(axis='y', style='sci', scilimits=(-3,3))\n",
    "    ax.tick_params(axis ='y', labelcolor = 'tab:blue')\n",
    "    ax.set_ylabel(r'Voltage (V)', color='tab:blue')\n",
    "    ax.set_xlabel(r'Time (ms)')\n",
    "    ax.minorticks_on()\n",
    "\n",
    "    \n",
    "    ax2 = ax.twinx()\n",
    "    plot_2 = ax2.plot(t_ms, receiver_mV, linestyle=\"solid\", marker=\".\", markersize=4, linewidth=1, color='tab:red', label=\"Receiver\")\n",
    "    \n",
    "    ax2.grid(True, which='major', color='#DDDDDD', linestyle='-', linewidth=0.6)\n",
    "    ax2.grid(True, which='minor', color='#DDDDDD', linestyle=':', linewidth=0.6)\n",
    "    ax2.ticklabel_format(axis='y', style='sci', scilimits=(-3,3))\n",
    "    ax2.tick_params(axis ='y', labelcolor = 'tab:red')\n",
    "    ax2.set_ylabel(r'Voltage (mV)', color='tab:red')\n",
    "    ax2.minorticks_on()\n",
    "\n",
    "    lns = plot_1 + plot_2\n",
    "    labels = [l.get_label() for l in lns]\n",
    "    plt.legend(lns, labels, loc=\"lower right\")\n",
    "    \n",
    "    plt.title(title)\n",
    "    plt.xlabel(\"Tiempo (ms)\")\n",
    "    \n",
    "    if xlim:\n",
    "        plt.xlim(xlim)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f33cbcc-946c-49b9-a633-4df7f54c4065",
   "metadata": {},
   "source": [
    "## Main function.\n",
    "\n",
    "Usage examples below.\n",
    "\n",
    "***IMPORTANT**: DECLARE `SDG1062X` CLASS AND GLOBAL VARIABLE `DEVICE_IP` BEFORE EXECUTING THIS SECTION OF CODE*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0db1f729-46aa-4240-a765-a2f0b1fcb797",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "import os\n",
    "\n",
    "\n",
    "Generador = SDG1062X(device_resource=f\"TCPIP0::{DEVICE_IP}::inst0::INSTR\")\n",
    "\n",
    "\n",
    "def send_samples_file(path_to_file : str, \n",
    "                      sample_init : int, \n",
    "                      sample_end : int,\n",
    "                      delimiter=\",\"):\n",
    "    \"\"\"\n",
    "    Does all the operations necessary to send samples to the arbitrary waveform\n",
    "    generator from a .csv file. This file must be plain text, with 3 columns.\n",
    "    Expected format:\n",
    "    \n",
    "     Time,        Channel A,   Channel B       # Channel names\n",
    "     (ms),        (V),         (mV)            # Channel units\n",
    "    \n",
    "    -7.50678836,  0.00488341,  0.30521300      # X data rows\n",
    "    -7.50423836, -0.01587108,  0.30521300\n",
    "     ...          ...          ...\n",
    "     \n",
    "    Default column delimiter is ',' (it's configurable) and decimal point \n",
    "    delimiter is '.' (obligatory at the moment)\n",
    "    \n",
    "    Generator channel 1 will be the Emitter (column ChannelA) and channel 2 will\n",
    "    be the receiver (column ChannelB).\n",
    "    \n",
    "    By default this signal repeats itself periodically. To avoid this, set the \n",
    "    burst configuration (example below)\n",
    "    \n",
    "    :param path_to_file relative path to the .csv file to send\n",
    "    :sample_init: sample index from where to begin sending\n",
    "    :sample_end: sample index to where end sending.\n",
    "    \n",
    "    NOTA: The number of samples must not exceed 16000.\n",
    "    \n",
    "    Juan Del Pino Mena, March 2022\n",
    "    \"\"\"\n",
    "    \n",
    "    # -------------------------- OBJETO GENERADOR ---------------------------- #\n",
    "    \n",
    "    Generador.identify()\n",
    "    Generador.reset()\n",
    "    time.sleep(1)\n",
    "    \n",
    "    \n",
    "    # ----------------------- LECTURA DE LOS FICHEROS ------------------------ #\n",
    "    \n",
    "    # lectura de la 2ª fila como str, para identificar las unidades\n",
    "    units = np.loadtxt(path_to_file,  \n",
    "                       delimiter=delimiter, \n",
    "                       dtype=str,\n",
    "                       skiprows=1,\n",
    "                       max_rows=1)\n",
    "    \n",
    "    # lectura de los datos como números en coma flotante\n",
    "    t, ch_a, ch_b = np.loadtxt(path_to_file, \n",
    "                               delimiter=delimiter, \n",
    "                               unpack=True, \n",
    "                               skiprows=3, \n",
    "                               dtype=float)\n",
    "\n",
    "    \n",
    "    # ----------------------- ADECUACIÓN DE LOS DATOS ------------------------ #\n",
    "    \n",
    "    t = t - t[0] # start at t0 = 0\n",
    "    \n",
    "    if units[0] == \"(ms)\":\n",
    "        t *= 1e-3;  # ms to s\n",
    "    elif units[0] == \"(us)\":\n",
    "        t *= 1e-6;  # us to s\n",
    "        \n",
    "    if units[1] == \"(mV)\":\n",
    "        ch_a *= 1e-3;  # mV to V\n",
    "    if units[2] == \"(mV)\":\n",
    "        ch_b *= 1e-3;  # mV to V\n",
    "        \n",
    "    L = len(t)      # longitud del vector de muestras\n",
    "    Ts = t[-1] / L  # periodo de muestreo\n",
    "    Fs = int(1/Ts)  # frecuencia de muestreo\n",
    "    \n",
    "    sample_num = sample_end - sample_init\n",
    "    \n",
    "    print(f\"Frecuencia de muestreo: {Fs/1e3:.3f} kHz\")\n",
    "    \n",
    "    t2 = np.arange(0, sample_num, 1) * Ts  # nuevo vector temporal\n",
    "    tmax = t2[-1]  # tiempo máximo, final del vector\n",
    "    freq_rep = int(1/tmax)  # frecuencia de repetición de la señal completa\n",
    "\n",
    "    emitter = ch_a[sample_init:sample_end]\n",
    "    receiver = ch_b[sample_init:sample_end]\n",
    "\n",
    "    print(f\"Periodo de repetición de la señal: {tmax*1e3:.3f} ms\\n\"\n",
    "          F\"Frecuencia de repetición de la señal: {freq_rep:.3f} Hz\")\n",
    "    print(f\"Longitud de los vectores de muestras: {len(t2)}\")\n",
    "\n",
    "    vmax_emitter = max(abs(emitter))\n",
    "    vmax_receiver = max(abs(receiver))\n",
    "    \n",
    "    print(f\"vmax,emitter: {vmax_emitter:.3f} V (abs)\\n\"\n",
    "          f\"vmax,receiver: {vmax_receiver*1e3:.3f} mV (abs)\")\n",
    "    print(f\"2*vmax,emitter: {2*vmax_emitter:.3f} V (abs)\\n\"\n",
    "          f\"2*vmax,receiver: {2*vmax_receiver*1e3:.3f} mV (abs)\")\n",
    "\n",
    "    vpp_emitter = max(emitter) - min(emitter)\n",
    "    vpp_receiver = max(receiver) - min(receiver)\n",
    "    \n",
    "    print(f\"vpp,emitter: {vpp_emitter:.3f} V\\n\"\n",
    "          f\"vpp,receiver: {vpp_receiver*1e3:.3f} mV\")\n",
    "    \n",
    "    \n",
    "    # ------------------------ CONVERSIÓN A BINARIO -------------------------- #\n",
    "    \n",
    "    # Emisor\n",
    "    \n",
    "    emitter_intC2 = Generador.samples_float_to_int_C2(emitter)\n",
    "    emitter_bytes = Generador.samples_int_C2_to_bytes(emitter_intC2)\n",
    "\n",
    "    emitter_bytearray = b\"\"\n",
    "    for item in emitter_bytes:\n",
    "        emitter_bytearray += item\n",
    "    emitter_binascii = emitter_bytearray.decode(\"latin1\")\n",
    "    \n",
    "    # Receptor\n",
    "    \n",
    "    receiver_intC2 = Generador.samples_float_to_int_C2(receiver)\n",
    "    receiver_bytes = Generador.samples_int_C2_to_bytes(receiver_intC2)\n",
    "\n",
    "    receiver_bytearray = b\"\"\n",
    "    for item in receiver_bytes:\n",
    "        receiver_bytearray += item\n",
    "    receiver_binascii = receiver_bytearray.decode(\"latin1\")\n",
    "    \n",
    "    \n",
    "    # ---------------------- GUARDADO EN ARCHIVO BIN ------------------------- #\n",
    "    \n",
    "    arbol_file = str(path_to_file.split('/')[-1]).split('.')[0]\n",
    "    save_folder = str(path_to_file.split('.')[0])\n",
    "    \n",
    "    try:\n",
    "        os.mkdir(save_folder)\n",
    "    except FileExistsError:\n",
    "        print(\"¡Sobreescribiendo datos!\")\n",
    "    print(f\"save_folder = {save_folder}\")\n",
    "\n",
    "    \n",
    "    # Guardando el binario\n",
    "    with open(f\"{save_folder}/{arbol_file}_e.bin\", \"wb\") as f:  # Emisor\n",
    "        f.write(emitter_bytearray)\n",
    "    with open(f\"{save_folder}/{arbol_file}_r.bin\", \"wb\") as f:  # Receptor\n",
    "        f.write(receiver_bytearray)\n",
    "    \n",
    "    # Lectura del archivo binario\n",
    "    with open(f\"{save_folder}/{arbol_file}_e.bin\", \"rb\") as f:\n",
    "        emitter_bindata = f.read().decode(\"latin1\")\n",
    "    with open(f\"{save_folder}/{arbol_file}_r.bin\", \"rb\") as f:\n",
    "        receiver_bindata = f.read().decode(\"latin1\")\n",
    "\n",
    "    print(f\"Longitud de datos binarios: {len(emitter_bindata)}\")\n",
    "    \n",
    "    \n",
    "    # -------------------- ENVÍO DE DATOS AL GENERADOR ----------------------- #\n",
    "    \n",
    "    # El canal 1 (Emisor) se envía al canal 1 del generador\n",
    "    \n",
    "    emitter_wave_name = f\"{arbol_file}_e\"\n",
    "    Generador.arb_send_samples(channel=1,\n",
    "                               wave_name=emitter_wave_name,\n",
    "                               freq=freq_rep,\n",
    "                               amp=vmax_emitter,\n",
    "                               bin_data=emitter_bindata,\n",
    "                               len_data=len(emitter_bindata))\n",
    "    Generador.write(\"\\r\\n\")\n",
    "    time.sleep(1)\n",
    "    Generador.arb_output(channel=1, wave_name=f\"{emitter_wave_name}\")\n",
    "    \n",
    "    time.sleep(1)\n",
    "    \n",
    "    # El canal 2 (Receptor) se envía al canal 2 del generador  \n",
    "    \n",
    "    receiver_wave_name = f\"{arbol_file}_r\"\n",
    "    Generador.arb_send_samples(channel=2,\n",
    "                               wave_name=receiver_wave_name, \n",
    "                               freq=freq_rep, \n",
    "                               amp=vmax_receiver, \n",
    "                               bin_data=receiver_bindata,\n",
    "                               len_data=len(receiver_bindata))\n",
    "    Generador.write(\"\\r\\n\")\n",
    "    time.sleep(1)\n",
    "    Generador.arb_output(channel=2, wave_name=f\"{receiver_wave_name}\")\n",
    "    \n",
    "    print(\"\\nDONE\")\n",
    "    \n",
    "    graphSamples(t2, emitter, receiver, \n",
    "                 title=f\"{path_to_file} | Sent signals. [COMPLETE]\")\n",
    "    graphSamples(t2, emitter, receiver, \n",
    "                 title=f\"{path_to_file} | Sent signals. [ZOOM]\", xlim=[0, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5b47a3ba-2ed8-4202-add7-96d43faa0e17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frecuencia de muestreo: 392.176 kHz\n",
      "Periodo de repetición de la señal: 20.396 ms\n",
      "Frecuencia de repetición de la señal: 49.000 Hz\n",
      "Longitud de los vectores de muestras: 8000\n",
      "vmax,emitter: 7.074 V (abs)\n",
      "vmax,receiver: 68.307 mV (abs)\n",
      "2*vmax,emitter: 14.147 V (abs)\n",
      "2*vmax,receiver: 136.613 mV (abs)\n",
      "vpp,emitter: 11.043 V\n",
      "vpp,receiver: 131.242 mV\n",
      "¡Sobreescribiendo datos!\n",
      "save_folder = samples/Arbol_42_original/Arbol_42_A1_5\n",
      "Longitud de datos binarios: 16000\n",
      "bytes: 16080\n",
      "bytes: 16080\n",
      "\n",
      "DONE\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "49351f7401614bdda342dea0e21a66c7",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1bbd84382c2c4904ab29baff6b0a20e6",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' 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      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Path to the .csv samples file. (a .bin file will be saved on the same path)\n",
    "# Expects a plain text file with '.' as decimal separator and ',' delimiter.\n",
    "path_to_file = \"samples/Arbol_42_original/Arbol_42_A1_5.csv\"\n",
    "\n",
    "# Sets the configuration and sends samples to the arbitrary waveform generator.\n",
    "# Channel 1 will be the Emitter\n",
    "# Channel 2 will be the Receiver\n",
    "send_samples_file(path_to_file, \n",
    "                  sample_init=2900,  # These parameters sets the init and end of \n",
    "                  sample_end=10900)  # the sample vector to send. \n",
    "                                     # Must not be longer than 16000"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65788a44-7695-4232-8559-27fbf4b5d884",
   "metadata": {},
   "source": [
    "# Burst (trigger individual signal periods)\n",
    "\n",
    "By default, the signal generator outputs continuos signal periods. \n",
    "\n",
    "This commands tell the device to only output a single period when certain conditions are met. In this case, when we trigger it manually.\n",
    "\n",
    "By limitations of this method (can't trigger both channels true simultaneously), it's possible that signals are a bit delayed one of another. You can avoid this by setting a small (ms, us or ns) delay on channel 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5c982d87-7125-41b3-a14c-f7c09777b93c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Deactivates burst\n",
    "Generador.burst_config(channel=1, state=\"OFF\")\n",
    "Generador.burst_config(channel=2, state=\"OFF\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1d874670-e7db-48d8-b792-a10178de35f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Activates burst and sends a manual trigger to both channels\n",
    "# This is what you want to execute if are outputting TIK singals\n",
    "Generador.burst_send_manual_both_channels()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fa185291-15b3-48ef-a08f-1e90e65cd072",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Activates both channels burst mode and sends a manual trigger for both\n",
    "# channels, but with a configurable delay on every channel.\n",
    "# This can be used to test if TIK equipment detects the arrival time correctly.\n",
    "\n",
    "emitter_delay_s = 100e-6  # Emitter delay in seconds. Moves signal closer to each other.\n",
    "receiver_delay_s = 0  # Receiver delay. in seconds. Moves signals away from each other.\n",
    "\n",
    "Generador.burst_send_manual_both_channels(ch1_trigger_delay=emitter_delay_s,\n",
    "                                          ch2_trigger_delay=receiver_delay_s)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8daff617-23d4-4f5e-85ab-8f1b98be2ce5",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "--- \n",
    "\n",
    "# Generator repair process (untraslated).\n",
    "\n",
    "Parece que esta fuente en particular tiene un problema con ciertas versiones de su firmware que hacen que se llene el almacenamiento con ficheros temporales tipo logs, y al saturarse la memoria no puede arrancar el sistema.\n",
    "\n",
    "Síntomas: sin previo aviso, de un encendido para otro, no arranca. La pantalla muestra el logo de siglent pero se apaga y no vuelve a aparecer. No reacciona a los botones frontales, ni hay nada a la salida de los  \n",
    "\n",
    "La tolerancia especificada por el fabricante en los raíles es del 5%.\n",
    "\n",
    "### Main Board.\n",
    "\n",
    "Es probablemente donde se halla el error porque se comunica directamente con la pantalla por un ribbon cable.\n",
    "Al encenderse, el LED HL1 (ARM LED) se enciende con poca intensidad y luego se iluminan más intensamente.\n",
    "\n",
    "Al estabilizarse, el LED HL1 (ARM LED) se enciende y parpadea dos veces rápido una vez cada 1.26 segundos (0.79 Hz)\n",
    "\n",
    "\n",
    "\n",
    "#### Test Points:\n",
    "\n",
    "Comprobación de voltajes DC.\n",
    "\n",
    "- **TP87** Esperado: 5 V. Lectura: 5.06 V\n",
    "- **TP88** Esperado: 3.3 V. Lectura: 3.37 V\n",
    "- **TP86** Esperado: 16 V. Lectura: 14.93 V -> discrepancia del 6.7 %.\n",
    "\n",
    "#### CLK\n",
    "\n",
    "- **TP22** Reloj del chip ARM, CLK 25 MHz. Lectura: 24.88 MHz.\n",
    "\n",
    "### Channel Board.\n",
    "\n",
    "El LED D1 (FPGA_LED) Parpadea con frecuencia de 1 Hz (0.98 Hz medido con osciloscopio).\n",
    "\n",
    "#### Test Points:\n",
    "\n",
    "Comprobación de voltajes DC\n",
    "\n",
    "- **TP13 VCC5V**: Lectura: 4.95 V (tercera medida, no hace buen contacto el pad) <!-- **<font color='red'>10 mV</font>** -->\n",
    "- **TP11 VCC3V3**: Lectura: 3.34 V (no hace buen contacto al principio)\n",
    "- **TP15 VCC1V2**: Lectura: 1.248 V\n",
    "- **TP18 AVEE-5V**: Lectura: -5.03 V\n",
    "- **TP16 AVEE5V**: Lectura: 4.98 V\n",
    "- **TP12 AVCC15V**: Lectura: 15.20 V\n",
    "- **TP14 AVEE-15V**: Lectura: -14.97 V\n",
    "\n",
    "#### CLK\n",
    "\n",
    "- **R19**: Reloj del chip FPGA, CLK 25 MHz. Lectura: (osciloscopio): 24.94 MHz (es un buen resultado teniendo en cuenta la interferencia de la sonda del osciloscopio)\n",
    "\n",
    "## Solución:\n",
    "\n",
    "Parece ser un bug del sistema. La solución era reinstalar el sistema de la fuente con una imagen de recuperación, se puede encontrar en la carpeta `firmware` de este notebook. Luego, actualizar a la última versión del firmware disponible.-"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "969fb958-8bb2-40fc-b7b4-3b279f2843d8",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# Residual code, experiments. Notes, troubles, debugging and other details from the development of the library (untraslated)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82dc3e52-2997-47a2-9d57-9c3e2a0a8dcc",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Pruebas\n",
    "\n",
    "Hay dos opciones, o bien usar la librería de vxi11 o pyVISA. Son equivalentes. El código en vxi11 es más sencillo y directo. Sin embargo, para la librería debemos usar PyVISA por cierta funcionalidad que no tiene VXI11 (o por lo menos no está documentada) al enviar muestras."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b8e0f750-63ef-4d30-afd8-6bcd0b654fcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SGD found: Siglent Technologies,SDG1062X,SDG1XCAD1R3295,1.01.01.33R1B6\n"
     ]
    }
   ],
   "source": [
    "IP = \"192.168.1.178\"\n",
    "SGD_VISA = visa.ResourceManager('@py').open_resource(f'TCPIP0::{IP}::inst0::INSTR')\n",
    "print(\"SGD found: \" + SGD_VISA.query('*IDN?').strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "080800a5-4785-4a15-9464-0beeb47c67ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\r\\n'"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SGD_VISA.write_termination"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "af868ce2-6e91-4307-8280-f5345dac28bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SGD found: Siglent Technologies,SDG1062X,SDG1XCAD1R3295,1.01.01.22R5\n"
     ]
    }
   ],
   "source": [
    "#SGD_vxi11 = vxi11.Instrument(\"192.168.1.101\")\n",
    "#print(\"SGD found: \" + SGD_vxi11.ask(\"*IDN?\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c17871eb-2f9d-4afd-ab2a-fd902374155d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SGD_vxi11.ask(\"*RST\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1651201-94e6-4b53-bbbc-2d34a18b737b",
   "metadata": {},
   "source": [
    "\n",
    "## Lectura de datos de árboles en .csv, conversión a binario, guardado en fichero .bin y envío de muestras al generador\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7177f49f-9e6a-427b-8040-f5755a168264",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frecuencia de muestreo: 392.196 kHz\n",
      "Tiempo máximo: 20.398 ms; Frecuencia de repetición de la señal: 49.000 Hz\n",
      "longitud de muestras: t2: 8000, emitter: 8000, receiver: 8000\n",
      "vmax,emitter: 7.221 V\n",
      "vmax,receiver: 69.039 mV\n",
      "2*vmax,emitter: 14.443 V\n",
      "2*vmax,receiver: 138.078 mV\n",
      "vpp,emitter: 11.063 V\n",
      "vpp,receiver: 128.678 mV\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "filename = \"samples/Arbol_42_original/Arbol_42_A1_1.csv\"\n",
    "t, ch_a, ch_b = np.loadtxt(filename, delimiter=',', unpack=True, skiprows=3)\n",
    "\n",
    "# Ajustes de unidades\n",
    "time_offset = 1e-3 * abs(t[1])  # offset para eliminar tiempo negativo\n",
    "t = t * 1e-3 + time_offset  # ms to s, empezar en t0 = 0\n",
    "ch_b = ch_b * 1e-3  # mV to V\n",
    "\n",
    "L = len(ch_a)\n",
    "Ts = t[-1] / L  # periodo de muestreo\n",
    "Fs = int(1/Ts)  # frecuencia de muestreo\n",
    "\n",
    "print(f\"Frecuencia de muestreo: {Fs/1e3:.3f} kHz\")\n",
    "\n",
    "sample_init = 2900\n",
    "sample_end = 10900\n",
    "sample_num = sample_end - sample_init\n",
    "\n",
    "t2 = np.arange(0, sample_num, 1) * Ts  # nuevo vector temporal\n",
    "tmax = sample_num * Ts  # tiempo máximo, final del vector\n",
    "freq_rep = int(1/tmax)  # frecuencia de repetición de la señal completa\n",
    "\n",
    "emitter = ch_a[sample_init:sample_end]\n",
    "receiver = ch_b[sample_init:sample_end]\n",
    "\n",
    "print(f\"Tiempo máximo: {tmax*1e3:.3f} ms; Frecuencia de repetición de la señal: {freq_rep:.3f} Hz\")\n",
    "print(f\"longitud de muestras: t2: {len(t2)}, emitter: {len(emitter)}, receiver: {len(receiver)}\")\n",
    "\n",
    "vmax_emitter = max(abs(emitter))\n",
    "vmax_receiver = max(abs(receiver))\n",
    "print(f\"vmax,emitter: {vmax_emitter:.3f} V\\nvmax,receiver: {vmax_receiver*1e3:.3f} mV\")\n",
    "print(f\"2*vmax,emitter: {2*vmax_emitter:.3f} V\\n2*vmax,receiver: {2*vmax_receiver*1e3:.3f} mV\")\n",
    "\n",
    "vpp_emitter = max(emitter) - min(emitter)\n",
    "vpp_receiver = max(receiver) - min(receiver)\n",
    "print(f\"vpp,emitter: {vpp_emitter:.3f} V\\nvpp,receiver: {vpp_receiver*1e3:.3f} mV\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0c6c788a-1d1c-4a63-8b8f-478dae27383d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 65508, 65508, 0, 22, 0, 65508, 65508, 0, 65486, 65508, 0, 0, 22, 44, 22, 65508, 66, 0, 0]\n",
      "[b'\\x00\\x00', b'\\xe4\\xff', b'\\xe4\\xff', b'\\x00\\x00', b'\\x16\\x00', b'\\x00\\x00', b'\\xe4\\xff', b'\\xe4\\xff', b'\\x00\\x00', b'\\xce\\xff', b'\\xe4\\xff', b'\\x00\\x00', b'\\x00\\x00', b'\\x16\\x00', b',\\x00', b'\\x16\\x00', b'\\xe4\\xff', b'B\\x00', b'\\x00\\x00', b'\\x00\\x00']\n",
      "b'\\x00\\x00\\xe4\\xff\\xe4\\xff\\x00\\x00\\x16\\x00\\x00\\x00\\xe4\\xff\\xe4\\xff\\x00\\x00\\xce\\xff\\xe4\\xff\\x00\\x00\\x00\\x00\\x16\\x00,\\x00\\x16\\x00\\xe4\\xffB\\x00\\x00\\x00\\x00\\x00'\n",
      "\u0000\u0000äÿäÿ\u0000\u0000\u0016\u0000\u0000\u0000äÿäÿ\u0000\u0000Îÿäÿ\u0000\u0000\u0000\u0000\u0016\u0000,\u0000\u0016\u0000äÿB\u0000\u0000\u0000\u0000\u0000\n"
     ]
    }
   ],
   "source": [
    "emitter_intC2 = Generador.samples_float_to_int_C2(emitter)\n",
    "emitter_bytes = Generador.samples_int_C2_to_bytes(emitter_intC2)\n",
    "\n",
    "emitter_bytearray = b\"\"\n",
    "for item in emitter_bytes:\n",
    "    emitter_bytearray += item\n",
    "emitter_binascii = emitter_bytearray.decode(\"latin1\")\n",
    "\n",
    "print(emitter_intC2[-20:])\n",
    "print(emitter_bytes[-20:])\n",
    "print(emitter_bytearray[-40:])\n",
    "print(emitter_binascii[-40:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "12a0f067-60a5-4abd-b556-eaaa73c0ec4d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 0, 0, 65362, 0, 65362, 0, 0, 65362, 0, 0, 0, 0, 65362, 0, 65362, 0, 65362, 65188, 0]\n",
      "[b'\\x00\\x00', b'\\x00\\x00', b'\\x00\\x00', b'R\\xff', b'\\x00\\x00', b'R\\xff', b'\\x00\\x00', b'\\x00\\x00', b'R\\xff', b'\\x00\\x00', b'\\x00\\x00', b'\\x00\\x00', b'\\x00\\x00', b'R\\xff', b'\\x00\\x00', b'R\\xff', b'\\x00\\x00', b'R\\xff', b'\\xa4\\xfe', b'\\x00\\x00']\n",
      "b'\\x00\\x00\\x00\\x00\\x00\\x00R\\xff\\x00\\x00R\\xff\\x00\\x00\\x00\\x00R\\xff\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00R\\xff\\x00\\x00R\\xff\\x00\\x00R\\xff\\xa4\\xfe\\x00\\x00'\n",
      "\u0000\u0000\u0000\u0000\u0000\u0000Rÿ\u0000\u0000Rÿ\u0000\u0000\u0000\u0000Rÿ\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000Rÿ\u0000\u0000Rÿ\u0000\u0000Rÿ¤þ\u0000\u0000\n"
     ]
    }
   ],
   "source": [
    "receiver_intC2 = Generador.samples_float_to_int_C2(receiver)\n",
    "receiver_bytes = Generador.samples_int_C2_to_bytes(receiver_intC2)\n",
    "\n",
    "receiver_bytearray = b\"\"\n",
    "for item in receiver_bytes:\n",
    "    receiver_bytearray += item\n",
    "receiver_binascii = receiver_bytearray.decode(\"latin1\")\n",
    "\n",
    "print(receiver_intC2[-20:])\n",
    "print(receiver_bytes[-20:])\n",
    "print(receiver_bytearray[-40:])\n",
    "print(receiver_binascii[-40:])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0989b34-e104-4b6f-ab82-09a5d768f71d",
   "metadata": {},
   "source": [
    "### Lectura del fichero y envío de los datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "7955c77c-a065-462c-8313-a524a9b0bc72",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "¡Sobreescribiendo datos!\n",
      "save_path = samples/Arbol_42_bin/Arbol_42_A1_1\n",
      "\n",
      "\n",
      "\u0000\u0000äÿäÿ\u0000\u0000\u0016\u0000\u0000\u0000äÿäÿ\u0000\u0000Îÿäÿ\u0000\u0000\u0000\u0000\u0016\u0000,\u0000\u0016\u0000äÿB\u0000\u0000\u0000\u0000\u0000\n",
      "\u0000\u0000\u0000\u0000\u0000\u0000Rÿ\u0000\u0000Rÿ\u0000\u0000\u0000\u0000Rÿ\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000Rÿ\u0000\u0000Rÿ\u0000\u0000Rÿ¤þ\u0000\u0000\n",
      "longitud de datos: 16000\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "arbol_file = str(filename.split('/')[-1]).split('.')[0]\n",
    "save_path = f\"samples/Arbol_42_bin/{arbol_file}\"\n",
    "try:\n",
    "    os.mkdir(save_path)\n",
    "except FileExistsError:\n",
    "    print(\"¡Sobreescribiendo datos!\")\n",
    "print(f\"save_path = {save_path}\")\n",
    "\n",
    "# Canal A - Emisor\n",
    "with open(f\"{save_path}/{arbol_file}_e.bin\", \"wb\") as f:\n",
    "    f.write(emitter_bytearray)\n",
    "# Canal B - Receptor\n",
    "with open(f\"{save_path}/{arbol_file}_r.bin\", \"wb\") as f:\n",
    "    f.write(receiver_bytearray)\n",
    "    \n",
    "with open(f\"{save_path}/{arbol_file}_e.bin\", \"rb\") as f:\n",
    "    emitter_bindata = f.read().decode(\"latin1\")\n",
    "with open(f\"{save_path}/{arbol_file}_r.bin\", \"rb\") as f:\n",
    "    receiver_bindata = f.read().decode(\"latin1\")\n",
    "\n",
    "print(\"\\n\")\n",
    "print(emitter_bindata[-40:])\n",
    "print(receiver_bindata[-40:])\n",
    "\n",
    "print(f\"longitud de datos: {len(emitter_bindata)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be7688ae-f728-454a-9056-426ad92338b5",
   "metadata": {},
   "source": [
    "### Problema con el envío de muestras: Muestras adicionales indeseadas al final de la señal.\n",
    "\n",
    "Parece no enterarse de cuando termina el envío de muestras cuando son un número grande. Si envías por ejemplo 8 muestras, el dispositivo acepta los datos y los guarda en un fichero, pero si se envían grandes cantidades de muestras en binario, parece no captar el final de la secuencia y por ello se envía un comando vacío con el carácter de parada. Si no, incorpora al archivo de muestras el siguiente comando que se ejecute. Es muy extraño y desconozco la causa.\n",
    "\n",
    "Se puede apreciar claramente si se envía una señal y no se ejecuta nada más. Si se envían pocas muestras y no se envía ningún otro comando, si se accede al menú de señales arbitrarias de usuario aparece el archivo creado. Sin embargo si se hace exactamente lo mismo con una señal de longitud significativa (por encima de las 500 ó 1000 muestras según mis pruebas) no aparece el archivo hasta que otro comando es enviado porque el dispositivo cree que la transferencia no ha acabado.\n",
    "\n",
    "Es irrelevante indicar la longitud de los datos, el aparato ignora el parámetro.\n",
    "\n",
    "En el ejemplo del fabricante, usa un delimitador de envío (`write_termination`) igual a un string vacío: `\"\"`; por defecto la librería usa `\"\\r\\n\"`. Parece que los comandos usuales no tienen problema con ningún delimitador, pero sí influye en el envío de muestras. Independientemente del delimitador, la fuente confunde el siguiente comando con muestras. El manual no indica nada en este aspecto."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "61f3bae1-73be-4659-b18e-5ccc60b36864",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bytes: 16080\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "emitter_wave_name = f\"{arbol_file}_e\"\n",
    "Generador.arb_send_samples(channel=1,\n",
    "                           wave_name=emitter_wave_name,\n",
    "                           freq=freq_rep,\n",
    "                           amp=vmax_emitter,\n",
    "                           bin_data=emitter_bindata,\n",
    "                           len_data=len(emitter_bindata))\n",
    "Generador.write(\"\\r\\n\")\n",
    "Generador.arb_output(channel=1, wave_name=f\"{emitter_wave_name}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a4fac6f0-4ebe-4a02-ab1a-37db05627845",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Generador.arb_sample_rate(channel=1, sample_rate=400e3, interpolation=\"LINE\", sample_rate_mode=\"TARB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "85199b12-dfa2-4c08-bdd2-2e10e92cbbed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Generador.arb_sample_rate(channel=1, sample_rate=400e3, interpolation=\"LINE\", sample_rate_mode=\"DDS\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "559b9140-e54d-4770-8629-aadaae54bdda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bytes: 16080\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "receiver_wave_name = f\"{arbol_file}_r\"\n",
    "Generador.arb_send_samples(channel=2,\n",
    "                           wave_name=receiver_wave_name, \n",
    "                           freq=freq_rep, \n",
    "                           amp=vmax_receiver, \n",
    "                           bin_data=receiver_bindata,\n",
    "                           len_data=len(receiver_bindata))\n",
    "Generador.write(\"\\r\\n\")\n",
    "Generador.arb_output(channel=2, wave_name=f\"{receiver_wave_name}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8c2f0576-ca4a-4795-8e6c-c7588b8eb103",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Generador.arb_sample_rate(channel=2, sample_rate=Fs, interpolation=\"HOLD\", sample_rate_mode=\"TARB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "741ea0fc-9e0a-4fa8-aa35-925752796809",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selección de la muestra a la salida\n",
    "Generador.arb_output(channel=2, wave_name=f\"{receiver_wave_name}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "672a0605-a798-456d-8066-9f7707392933",
   "metadata": {},
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     "ename": "NameError",
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      "\u001b[0;31mNameError\u001b[0m: name 't2' is not defined"
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   ],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Libertinus Serif\"\n",
    "plt.rcParams['font.size'] = 14\n",
    "plt.rcParams['mathtext.fontset'] = 'custom'\n",
    "plt.rcParams['mathtext.rm'] = 'Libertinus Serif'\n",
    "plt.rcParams['mathtext.it'] = 'Libertinus Serif:italic'\n",
    "plt.rcParams['mathtext.bf'] = 'Libertinus Serif:bold'\n",
    "\n",
    "fig, ax = plt.subplots(figsize=[9, 6])\n",
    "plot_1 = plt.plot(t2, emitter, linestyle=\"solid\", marker=\".\", markersize=2, linewidth=1, label=r'Emitter', color='tab:blue')\n",
    "\n",
    "ax.grid(True, which='major', color='#DDDDDD', linestyle='-', linewidth=0.6)\n",
    "ax.grid(True, which='minor', color='#DDDDDD', linestyle=':', linewidth=0.6)\n",
    "ax.ticklabel_format(axis='y', style='sci', scilimits=(-3,3))\n",
    "ax.tick_params(axis ='y', labelcolor = 'tab:blue')\n",
    "ax.set_ylabel(r'Voltaje (V)', color='tab:blue')\n",
    "ax.minorticks_on()\n",
    "ax.set_ylim([-8, 4])\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "plot_2 = plt.plot(t2, receiver, linestyle=\"solid\", marker=\".\", markersize=2, linewidth=1, label=r'Receiver', color='tab:red')\n",
    "\n",
    "ax2.ticklabel_format(axis='y', style='sci', scilimits=(-3,3))\n",
    "ax2.tick_params(axis ='y', labelcolor = 'tab:red')\n",
    "ax2.set_ylabel(r'Voltaje (V)', color='tab:red')\n",
    "ax2.minorticks_on()\n",
    "ax2.set_ylim([-0.1, 0.1])\n",
    "\n",
    "lns = plot_1 + plot_2\n",
    "labels = [l.get_label() for l in lns]\n",
    "plt.legend(lns, labels, loc=\"lower right\")\n",
    "plt.xlabel(\"tiempo (s)\")\n",
    "plt.xlim([0, tmax/5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b120585f-21d7-4952-9bc1-82b29bd306b3",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 't2' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [1]\u001b[0m, in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      8\u001b[0m ax1 \u001b[38;5;241m=\u001b[39m fig\u001b[38;5;241m.\u001b[39madd_subplot(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m      9\u001b[0m ax2 \u001b[38;5;241m=\u001b[39m fig\u001b[38;5;241m.\u001b[39madd_subplot(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m---> 11\u001b[0m ax1\u001b[38;5;241m.\u001b[39mplot(\u001b[43mt2\u001b[49m, np\u001b[38;5;241m.\u001b[39marray(emitter_int), linestyle\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msolid\u001b[39m\u001b[38;5;124m\"\u001b[39m, linewidth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtab:blue\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     12\u001b[0m ax2\u001b[38;5;241m.\u001b[39mplot(t2, np\u001b[38;5;241m.\u001b[39marray(receiver_int), linestyle\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msolid\u001b[39m\u001b[38;5;124m\"\u001b[39m, linewidth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtab:blue\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 't2' is not defined"
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       "   </g>\n",
       "  </g>\n",
       " </g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<Figure size 648x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "fig = plt.figure(figsize=[9, 6])\n",
    "ax1 = fig.add_subplot(2, 1, 1)\n",
    "ax2 = fig.add_subplot(2, 1, 2)\n",
    "\n",
    "ax1.plot(t2, np.array(emitter_int), linestyle=\"solid\", linewidth=1, color=\"tab:blue\")\n",
    "ax2.plot(t2, np.array(receiver_int), linestyle=\"solid\", linewidth=1, color=\"tab:blue\")\n",
    "\n",
    "# Están en complemento a dos y con bytes desordenados, no saldrá la señal tal cual"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "965e4760-fa30-4a24-8f8b-f1dac1bf0fc4",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Envío de una señal arbitraria de prueba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a8cb2f19-1547-44b8-a910-5ce8398c334a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Conversión de hexadecimal a entero, interpretando complemento a dos, con signo\n",
    "def twosComplement_hex(hexval):\n",
    "    bits = 16 # Number of bits in a hexadecimal number format\n",
    "    val = int(hexval, bits)\n",
    "    if val & (1 << (bits-1)):\n",
    "        val -= 1 << bits\n",
    "    return val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "79c221e4-2b95-4a61-a185-9fc43363cba1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# convertimos de vuelta a hex para confirmar que el método es correcto.\n",
    "def twosComplement_int(intvector):\n",
    "    n_points = 2 ** 16\n",
    "    samples_hex = []\n",
    "    for sample in intvector:\n",
    "        if sample < 0:\n",
    "            samples_hex.append(f\"{(sample + n_points):04x}\")\n",
    "        else:\n",
    "            samples_hex.append(f\"{(sample):04x}\")\n",
    "    return samples_hex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "8ccb72c2-3251-4fd5-b656-1dc1d97240e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vector de enteros: \t[-32768, -32768, -4096, -4096, 0, 0, 4096, 4096, 32767, 32767]\n",
      "Vector hex original: \t['8000', '8000', 'f000', 'f000', '0000', '0000', '1000', '1000', '7fff', '7fff']\n",
      "Vector reconvertido: \t['8000', '8000', 'f000', 'f000', '0000', '0000', '1000', '1000', '7fff', '7fff']\n"
     ]
    }
   ],
   "source": [
    "wave_points_hex = [\"8000\", \"8000\", \"f000\", \"f000\", \"0000\", \"0000\", \"1000\", \"1000\", \"7fff\", \"7fff\"]\n",
    "wave_points_int = [twosComplement_hex(point) for point in wave_points_hex]  # son valores adecuados que buscamos\n",
    "samples_hex = twosComplement_int(wave_points_int)  # convertimos de vuelta a hex para confirmar que el método es correcto.\n",
    "\n",
    "print(f\"Vector de enteros: \\t{wave_points_int}\")\n",
    "print(f\"Vector hex original: \\t{wave_points_hex}\")\n",
    "print(f\"Vector reconvertido: \\t{samples_hex}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d10ce59-77da-4ccf-be71-6bb293073762",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### IMPORTANTE: VALOR DE LAS MUESTRAS\n",
    "\n",
    "Por ensayo y error, usando el programa de ejmplo de Siglent, aunque el datasheet diga que la resolución vertical son 14 bits, entiende **16 bits** en muestras arbitrarias.\n",
    "Por tanto, **los valores máximos y mínimos NO SON -8192 y +8191**, sino:\n",
    "\n",
    "- máx: `0x7fff` ->`+32767` (2^(16) - 1)\n",
    "- mín: `0x8000` ->`-32768` (- 2^(16-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "7b678f9b-17e8-486f-bc8b-72767d99ef6f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-2.000061037018952, -2.000061037018952, -0.250007629627369, -0.250007629627369, 0.0, 0.0, 0.250007629627369, 0.250007629627369, 2.0, 2.0]\n"
     ]
    }
   ],
   "source": [
    "# Pasando el vector de muestras enteras a float, simulando una señal real\n",
    "# Test de los métodos de la clase.\n",
    "\n",
    "amp = 2\n",
    "n_bits = 16\n",
    "n_points = 2 ** (n_bits - 1) -1\n",
    "factor = n_points / amp\n",
    "\n",
    "# int to float\n",
    "wave_points_float = [point / factor for point in wave_points_int]  # vector float, con signo.\n",
    "print(wave_points_float)  # Debería corresponderse con la amplitud a la salida"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "2c781874-a7fe-42df-a7bd-36ab05d78b55",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[32768, 32768, 61440, 61440, 0, 0, 4096, 4096, 32767, 32767]\n"
     ]
    }
   ],
   "source": [
    "# Conversión de muestras float a int C2\n",
    "samples_intC2 = Generador.samples_float_to_int_C2(samples_float=wave_points_float, amp=2)\n",
    "print(samples_intC2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "77fe5952-46cf-4059-8140-7e274ef408bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[b'\\x00\\x80', b'\\x00\\x80', b'\\x00\\xf0', b'\\x00\\xf0', b'\\x00\\x00', b'\\x00\\x00', b'\\x00\\x10', b'\\x00\\x10', b'\\xff\\x7f', b'\\xff\\x7f']\n"
     ]
    }
   ],
   "source": [
    "# Conversión de muestras int C2 a binascii\n",
    "samples_binascii = Generador.samples_int_C2_to_bytes(samples_int_C2=samples_intC2)\n",
    "print(samples_binascii)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "152e7850-5983-4871-ba60-abe4d38219e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'\\x00\\x80\\x00\\x80\\x00\\xf0\\x00\\xf0\\x00\\x00\\x00\\x00\\x00\\x10\\x00\\x10\\xff\\x7f\\xff\\x7f'\n"
     ]
    }
   ],
   "source": [
    "# Guardado de la señal\n",
    "bin_data = b\"\"\n",
    "for item in samples_binascii:\n",
    "    bin_data += item\n",
    "print(bin_data)\n",
    "\n",
    "wave_name = \"testsignal1\"\n",
    "with open(f\"{wave_name}.bin\", \"wb\") as f:\n",
    "    f.write(bin_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "484f8ec5-40d1-42af-8427-7f665b764a21",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u0000\u0000\u0000ð\u0000ð\u0000\u0000\u0000\u0000\u0000\u0010\u0000\u0010ÿÿ\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Carga la señal.\n",
    "with open(f\"{wave_name}.bin\", \"rb\") as f:\n",
    "    data = f.read().decode(\"latin1\")\n",
    "print(data)\n",
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "c3f5ad39-2b46-45eb-b1b0-414fbec9b056",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bytes: 80\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Envío del vector de muestras de prueba\n",
    "Generador.arb_send_samples(channel=1,\n",
    "                           wave_name=wave_name, \n",
    "                           freq=100,\n",
    "                           amp=amp, \n",
    "                           bin_data=data,\n",
    "                           len_data=len(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "a75d8125-f56b-4353-a83c-e6193c9e2c13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selección del tipo de muestreo\n",
    "# No parece que haga nada...\n",
    "Generador.arb_sample_rate(channel=1, sample_rate=\"\", interpolation=\"LINE\", sample_rate_mode=\"TARB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e0bb7c5b-3133-40b2-be92-ad6faa2c92e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selección de la muestra a la salida\n",
    "Generador.arb_output(channel=1, wave_name=wave_name)  \n",
    "# Funciona correctamente. Deberíamos ver a la salida la función de más abajo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "003108d7-572a-4233-baf9-f386ce21dd15",
   "metadata": {},
   "source": [
    "Funciona correctamente. Debería verse esta señal en el generador y en el osciloscopio:"
   ]
  },
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   "execution_count": 73,
   "id": "4b8e3429-bea9-4ccb-9067-d1d00d08ab18",
   "metadata": {},
   "outputs": [
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     },
     "metadata": {
      "needs_background": "light"
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     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "onda_repetida = []\n",
    "onda_repetida.extend(wave_points_float)\n",
    "onda_repetida.extend(onda_repetida)\n",
    "onda_repetida.extend(onda_repetida)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=[9, 3])\n",
    "plot_1 = plt.plot(np.arange(len(onda_repetida)), onda_repetida, linestyle=\"solid\", marker=\".\", markersize=5, linewidth=1, color='tab:blue')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f9e1c07-f1cf-4b7f-b3af-286adc571f95",
   "metadata": {},
   "source": [
    "# Otras pruebas. Experimentos. (untraslated)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a88d54e8-404b-472b-b4ef-c631fc5b9f5d",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Pruebas de codificación binaria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "456706e6-7c31-432a-88ca-a9f016fbd0f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0038\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "57340"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = 56\n",
    "print(f\"{x:04x}\")  # imprimir en hexadecimal con padding de 4 caracteres.\n",
    "\n",
    "# No funciona si es negativo. Hay que convertir los datos de decimal con signo a\n",
    "# decimal sin signo estilo complemento a dos.\n",
    "# Para ello se suma a la cantidad 2 ** n_bits el valor negativo: 2^16 + (-8196) = 57340\n",
    "\n",
    "x = -8196\n",
    "y = 2 ** 16 + x\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d280176d-9c81-45c0-bcb6-c845125ed297",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.09001548  4.53724853  1.87075963 -0.64251741  2.43947107  3.47376636\n",
      "  0.70263805 -3.39314602  4.85104018 -0.39021399]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np  # Usado para experimentar. la función no depende de numpy.\n",
    "\n",
    "n_bits = 12  # Nº de bits del DAC del generador\n",
    "n_ptos = 2**n_bits  # nº de cuantos del DAC\n",
    "v_max = 5  # Voltaje máximo absoluto, de la señal\n",
    "factor = n_ptos / (v_max * 2)\n",
    "\n",
    "samples_f = np.random.uniform(-v_max, v_max, size=(1, 10))  # Vector de prueba\n",
    "samples_f = samples_f[0]\n",
    "\n",
    "print(samples_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "49c3f73b-9b35-4443-8c01-99ff1cb3645a",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'SDG1062X' object has no attribute 'samples_to_bin'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[0;32mIn [38]\u001b[0m, in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0m samples_b_func \u001b[38;5;241m=\u001b[39m \u001b[43mGenerador\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msamples_to_bin\u001b[49m(samples_f, v_max, byteorder\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlittle\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28mprint\u001b[39m(samples_b_func)\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'SDG1062X' object has no attribute 'samples_to_bin'"
     ]
    }
   ],
   "source": [
    "samples_b_func = Generador.samples_to_bin(samples_f, v_max, byteorder=\"little\")\n",
    "print(samples_b_func)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "541093b1-ad41-4873-b04c-0df9805941a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import ceil\n",
    "import binascii\n",
    "\n",
    "v_max = 1\n",
    "\n",
    "n_bits = 16\n",
    "n_bytes = ceil(n_bits / 8)  # nº de bytes en los que codificar los datos\n",
    "byteorder = \"little\"\n",
    "n_points = 2 ** n_bits  # nº de cuantos del DAC\n",
    "factor = n_points / v_max  # Factor de escalado de las muestras\n",
    "\n",
    "samples_int_C2 = [-8192, -5461, 8196, 0, 1]\n",
    "\n",
    "# samples_int = [int(round(sample * factor)) for sample in samples_float]\n",
    "# samples_int_C2 = [n_points + sample for sample in samples_int if sample < 0]\n",
    "samples_hex = [] \n",
    "\n",
    "for sample in samples_int_C2:\n",
    "    if sample < 0:\n",
    "        samples_hex.append(f\"{(sample + n_points):04x}\")\n",
    "    else:\n",
    "        samples_hex.append(f\"{(sample):04x}\")\n",
    "\n",
    "print(samples_hex)\n",
    "        \n",
    "samples_bytes = [sample[2:4] + sample[:2] for sample in samples_hex]\n",
    "print(samples_bytes)\n",
    "samples_bytes = [binascii.unhexlify(sample) for sample in samples_bytes]\n",
    "print(samples_bytes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c1ce131-1908-42cb-a00c-e7b5dcc74d9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_bits = 16\n",
    "n_bytes = ceil(n_bits / 8)  # nº de bytes en los que codificar los datos\n",
    "byteorder = \"little\"\n",
    "n_points = 2 ** n_bits  # nº de cuantos del DAC\n",
    "factor = n_points / v_max  # Factor de escalado de las muestras\n",
    "\n",
    "samples_int = wave_points\n",
    "\n",
    "#samples_int = [int(round(sample * factor)) for sample in samples_float]\n",
    "samples_int_C2 = [n_points + sample for sample in samples_int if sample < 0]\n",
    "samples_hex = [f\"{sample:04x}\" for sample in samples_int_C2]\n",
    "samples_hex"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58aa0b14-3fe7-4cc0-b7e6-b1441ff33dc4",
   "metadata": {},
   "source": [
    "## Código de ejemplo de Siglent, ligeramente modificado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "303fe49d-5729-4b5f-8978-0352b546b52f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import binascii\n",
    "import pyvisa as visa\n",
    "import random\n",
    "import time\n",
    "\n",
    "\n",
    "# 0xE000: 1110 0000 0000 0000: decimal (complemento a dos): -8192\n",
    "# 0xF000: 1111 0000 0000 0000: decimal (C2): -4096\n",
    "# wave_int_samples = \n",
    "#wave_data = [\"8000\", \"8000\", \"f000\", \"f000\", \"0000\", \"0000\", \"1000\", \"1000\", \"7fff\", \"7fff\"]\n",
    "wave_data = [0x8000, 0x8000, 0xf000, 0xf000, 0x0000, 0x0000, 0x1000, 0x1000, 0x7fff, 0x7fff]\n",
    "wave_points = []\n",
    "wave_points += wave_data          # En entero PYTHON LO INTERPRETA SIN SIGNO.\n",
    "\n",
    "print(wave_data)\n",
    "print(wave_points)\n",
    "print(len(wave_points))\n",
    " \n",
    "def create_wave_file():\n",
    "    \"\"\"create a file\"\"\"\n",
    "    f = open(\"wave1.bin\", \"wb\")\n",
    "    for a in wave_points:\n",
    "        b = hex(a)                # En hexadecimal\n",
    "        b = b[2:]                 # Elimina el '0x'. También desaparecen los ceros a la izquierda.\n",
    "        len_b = len(b)            # Longitud de la muestra hexadecimal. \n",
    "        if (0 == len_b):\n",
    "            b = '0000'            # Si está vacío\n",
    "        elif (1 == len_b):\n",
    "            b = '000' + b         # Sólo 1 dígito\n",
    "        elif (2 == len_b):\n",
    "            b = '00' + b          # 2 dígitos\n",
    "        elif (3 == len_b):\n",
    "            b = '0' + b           # 3 dígitos. Si tiene 4, no importa.\n",
    "        b = b[2:4] + b[:2]        # change big-endian to little-endian. Altera el orden de los bytes.\n",
    "        c = binascii.unhexlify(b) # Hexadecimal integer to ASCii encoded string\n",
    "        f.write(c)\n",
    "        print(c)\n",
    "    f.close()\n",
    "    \n",
    "def send_wave_data(dev):\n",
    "    \"\"\"send wave1.bin to the device\"\"\"\n",
    "    f = open(\"wave1.bin\", \"rb\")    #wave1.bin is the waveform to be sent\n",
    "    data = f.read().decode(\"latin1\")\n",
    "    print('write class:', type(data))\n",
    "    print('write bytes:',len(data))\n",
    "    dev.write_termination = ''\n",
    "    dev.write(\"C1:WVDT WVNM,wave1,FREQ,2000.0,AMPL,4.0,OFST,0.0,PHASE,0.0,WAVEDATA,%s\"%(data),encoding='latin1')    #\"X\" series (SDG1000X/SDG2000X/SDG6000X/X-E)&amp;amp;lt;/pre&amp;amp;gt;\n",
    "    dev.write(\"C1:ARWV NAME,wave1\")\n",
    "    f.close()\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef15a3cf-79c4-4482-9ecc-585e9d77a0b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "device_resource = 'TCPIP0::192.168.1.101::inst0::INSTR'\n",
    "\n",
    "rm=visa.ResourceManager()\n",
    "device=rm.open_resource(device_resource, timeout=50000, chunk_size = 24*1024*1024)\n",
    "create_wave_file()\n",
    "send=send_wave_data(device) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33328456-6c70-48ff-9788-a77561cdfd4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "2 ** 14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "496997d8-3a21-47d4-9dd1-7590e6b367a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "wave_points_int_rec = [twosComplement_hex(point) for point in samples_hex]  # confirmamos que sí son valores adecuados que buscamos\n",
    "print(wave_points_int_rec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53a9191d-afbb-4f10-acaa-3f22062cd5ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "wave_points_hex_little = [point[2:4] + point[:2] for point in wave_points_hex]  # little-endian\n",
    "print(wave_points_hex_little)\n",
    "\n",
    "wave_points_bin = [binascii.unhexlify(point) for point in wave_points_hex_little]  # binario\n",
    "print(wave_points_bin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9dd84f2f-1417-45b5-aa6f-fd51c68772fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "wave_points_int_rec = [twosComplement_hex(point) for point in wave_points_hex_little]  # confirmamos que sí son valores adecuados que buscamos\n",
    "print(wave_points_int_rec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4b6b074-e17d-4892-8b35-5de85b0ba443",
   "metadata": {},
   "outputs": [],
   "source": [
    "Generador.arb_send_samples(channel=1,\n",
    "                           wave_name=f\"wave1_example\", \n",
    "                           freq=2000, \n",
    "                           amp=4, \n",
    "                           wave_data=bindata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "673fe5e3-952d-457e-9e6d-8211f1fa2ef2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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