run-bluesky.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8e6b1b0b-cc90-4db6-8e53-d99081d22ced",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "079b40a4-2d3b-4543-8694-c43a667591ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bluesky import RunEngine\n",
    "from bluesky.callbacks.best_effort import BestEffortCallback\n",
    "from ophyd.sim import det, motor\n",
    "import bluesky.plans as bp\n",
    "import matplotlib.pyplot as plt\n",
    "# plt.ion()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "24c9fc2e-c0a3-4151-898e-0de054059c9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "det.kind = 'hinted'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "64bc07b8-010c-448d-a732-2bcd28babe2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "motor.kind = 'hinted'\n",
    "motor.delay = 0.5  # seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "59e80ffb-58c1-42aa-8cb9-92de09534fac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bec = BestEffortCallback()\n",
    "RE = RunEngine()\n",
    "RE.subscribe(bec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "954b7ed2-c41f-4cae-8957-839633c259df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 1     Time: 2021-12-06 18:46:43\n",
      "Persistent Unique Scan ID: '6d65bc4c-b8fc-4542-a428-b59535a57610'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+\n",
      "|   seq_num |       time |      motor |        det |\n",
      "+-----------+------------+------------+------------+\n",
      "|         1 | 18:46:44.6 |     -1.000 |      0.607 |\n",
      "|         2 | 18:46:45.1 |     -0.800 |      0.726 |\n",
      "|         3 | 18:46:45.6 |     -0.600 |      0.835 |\n",
      "|         4 | 18:46:46.1 |     -0.400 |      0.923 |\n",
      "|         5 | 18:46:46.6 |     -0.200 |      0.980 |\n",
      "|         6 | 18:46:47.1 |      0.000 |      1.000 |\n",
      "|         7 | 18:46:47.7 |      0.200 |      0.980 |\n",
      "|         8 | 18:46:48.2 |      0.400 |      0.923 |\n",
      "|         9 | 18:46:48.7 |      0.600 |      0.835 |\n",
      "|        10 | 18:46:49.2 |      0.800 |      0.726 |\n",
      "|        11 | 18:46:49.7 |      1.000 |      0.607 |\n",
      "+-----------+------------+------------+------------+\n",
      "generator scan ['6d65bc4c'] (scan num: 1)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('6d65bc4c-b8fc-4542-a428-b59535a57610',)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9a197f0bb484bb78d06182925425909",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    det vs motor\n",
       "                </div>\n",
       "                <img 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' width=500.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.scan([det], motor, -1, 1, 11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bd5766ed-d884-416e-8512-6fa3b5ad7600",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 2     Time: 2021-12-06 18:47:01\n",
      "Persistent Unique Scan ID: 'e46d2cde-43ef-4054-96ea-1ad6aa7d6dd7'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+\n",
      "|   seq_num |       time |      motor |        det |\n",
      "+-----------+------------+------------+------------+\n",
      "|         1 | 18:47:02.2 |     -1.000 |      0.607 |\n",
      "|         2 | 18:47:02.7 |     -0.800 |      0.726 |\n",
      "|         3 | 18:47:03.2 |     -0.600 |      0.835 |\n",
      "|         4 | 18:47:03.7 |     -0.400 |      0.923 |\n",
      "|         5 | 18:47:04.2 |     -0.200 |      0.980 |\n",
      "|         6 | 18:47:04.7 |      0.000 |      1.000 |\n",
      "|         7 | 18:47:05.2 |      0.200 |      0.980 |\n",
      "|         8 | 18:47:05.7 |      0.400 |      0.923 |\n",
      "|         9 | 18:47:06.2 |      0.600 |      0.835 |\n",
      "|        10 | 18:47:06.8 |      0.800 |      0.726 |\n",
      "|        11 | 18:47:07.3 |      1.000 |      0.607 |\n",
      "+-----------+------------+------------+------------+\n",
      "generator scan ['e46d2cde'] (scan num: 2)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('e46d2cde-43ef-4054-96ea-1ad6aa7d6dd7',)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RE(bp.scan([det], motor, -1, 1, 11))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f5ae8f6-3494-48e5-9a55-d92710c8ab01",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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