Getting Started/06_logic_analyzer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "97e3f98e-f224-42bc-9386-53da868ce7f9",
   "metadata": {},
   "source": [
    "# Logic Analyzer\n",
    "\n",
    "In the previous tutorial we saw that the oscilloscope is not the ideal instrument for looking at digital signals. The PSLab has another instrument more suited for this purpose: The logic analyzer.\n",
    "\n",
    "The PSLab's oscilloscope struggles with digital signals with frequencies over 50 kHz. Let's see how the logic analyzer does. This time, connect SQ1 to LA1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6fe26b39-0284-4729-8f4d-f4f621b13bb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc3affb7790>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pslab\n",
    "psl = pslab.ScienceLab()\n",
    "psl.pwm_generator.generate(channels=\"SQ1\", frequency=500_000, duty_cycles=0.5)\n",
    "t = psl.logic_analyzer.capture(channels=\"LA1\", events=8)\n",
    "x, y = psl.logic_analyzer.get_xy(t)\n",
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ae5fb02-eb22-42e9-8f83-308d6a4816e6",
   "metadata": {},
   "source": [
    "Much better!\n",
    "\n",
    "The logic analyzer also has four channels, so we can use it to look at all the PWM outputs simultaneously. Connect SQ2 to LA2, SQ3 to LA3, and SQ4 to LA4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cd8a3999-ab4a-414c-88bf-88aa4a183abf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc3af9c6790>,\n",
       " <matplotlib.lines.Line2D at 0x7fc3af9c6b90>,\n",
       " <matplotlib.lines.Line2D at 0x7fc3af9c6e90>,\n",
       " <matplotlib.lines.Line2D at 0x7fc3af9c7190>]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "psl.pwm_generator.generate(channels=4, frequency=500_000, duty_cycles=[0.1, 0.3, 0.5, 0.7], phases=[0, 0.2, 0.5, 0.8])\n",
    "t = psl.logic_analyzer.capture(channels=4, events=8)\n",
    "x1, y1, x2, y2, x3, y3, x4, y4 = psl.logic_analyzer.get_xy(t)\n",
    "plt.plot(x1, y1, x2, y2 + 1.1, x3, y3 + 2.2, x4, y4 + 3.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38e53641-21ab-4e0f-a9c4-26181fcfae99",
   "metadata": {},
   "source": [
    "Here we have offset the graphs from each other on the y-axis to make them easier to tell apart.\n",
    "\n",
    "Note that the output from the logic analyzer's `capture` method is a list of timestamps for \"events\", i.e. logic level transissions, for each channel. In order to get something which is more suitable for plotting, the logic analyzer provides a `get_xy` method, which converts the timestamps into x and y values similar to the oscilloscope's output. Each channel has its own x and y pair.\n",
    "\n",
    "That's the basics of the PSLab's six core instruments!\n",
    "\n",
    "The PSLab also provides three types of serial buses: I2C, SPI, and UART. The buses can be used to connect external sensors and devices."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}