demos.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
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     },
     "metadata": {},
     "execution_count": 1
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, UnitOperation, Distillation, Vessel, BlackBox, Pump, Stream, StreamFlag, Valve,HeatExchanger, SvgContext\n",
    "from pyflowsheet import VerticalLabelAlignment, HorizontalLabelAlignment\n",
    "from pyflowsheet.internals import Tubes, CatalystBed, Trays\n",
    "\n",
    "from IPython.core.display import SVG, HTML\n",
    "\n",
    "pfd= Flowsheet(\"V100-DS10\",\"Simple Distillation\", \"Demo Flowsheet for testing functionality\")\n",
    "\n",
    "Feed= StreamFlag(\"F100\", \"Feed\", position=(-80,480))\n",
    "PA10=Pump(\"DS10-PA10\",\"Vertical Vessel\", position=(60,480))\n",
    "BA10=Vessel(\"DS10-WA10\",\"Vertical Vessel\", position=(160,280), size=(60,120),capLength=20,internals=[Tubes()])\n",
    "VA10=Valve(\"DS10-VA10\",\"Control Valve\", position=(260,250) )\n",
    "KA10=Distillation(\"DS10-KA10\",\"Distillation Tower\", hasCondenser=False, hasReboiler=True,position=(360,100), size=(60,320), internals=[Trays(numberOfTrays=13)])\n",
    "BA11=Vessel(\"DS10-BA11\",\"Horizontal Vessel\", angle=90, position=(560,400), size=(40,100), capLength=20,internals=[CatalystBed()] )\n",
    "P1= StreamFlag(\"P1\", \"Product 1\", position=(700,40))\n",
    "P2= StreamFlag(\"P2\", \"Product 2\", position=(-80,580))\n",
    "PA11=Pump(\"DS10-PA11\",\"Bottom Pump\", position=(700,580))\n",
    "\n",
    "pfd.addUnits( [Feed,PA10,BA10,VA10,KA10,BA11,P1,P2,PA11 ] )\n",
    "\n",
    "pfd.connect(\"S01\", Feed[\"Out\"], PA10[\"In\"] ) \n",
    "pfd.connect(\"S02\", PA10[\"Out\"], BA10[\"In\"] ) \n",
    "pfd.connect(\"S03\", BA10[\"Out\"], VA10[\"In\"] ) \n",
    "pfd.connect(\"S07\", VA10[\"Out\"], KA10[\"Feed\"] ) \n",
    "pfd.connect(\"S04\", KA10[\"Bottom\"], BA11[\"In\"] ) \n",
    "pfd.connect(\"S05\", KA10[\"VOut\"], P1[\"In\"] ) \n",
    "pfd.connect(\"S06\", BA11[\"Out\"], PA11[\"In\"] )\n",
    "pfd.connect(\"S08\", PA11[\"Out\"], P2[\"In\"] )\n",
    "#Examples for Styling\n",
    "pfd.streams[\"S05\"].lineColor=(255,0,0,0,255)\n",
    "pfd.streams[\"S05\"].dashArray=\"10 10\"\n",
    "\n",
    "PA11.flip(axis=\"horizontal\")\n",
    "P2.flip(axis=\"horizontal\")\n",
    "\n",
    "KA10.setTextAnchor(HorizontalLabelAlignment.RightOuter,VerticalLabelAlignment.Center,(10,0) )\n",
    "ctx= SvgContext(\"img/small_process.svg\")\n",
    "\n",
    "img = pfd.draw(ctx)\n",
    "SVG(img.render(scale=1))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
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0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"20.0\" y=\"180\">P2</text></g></svg>"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, UnitOperation, Distillation, Vessel, BlackBox, Pump, Stream, StreamFlag, Valve,HeatExchanger, SvgContext\n",
    "from IPython.core.display import SVG, HTML\n",
    "from pyflowsheet import VerticalLabelAlignment, HorizontalLabelAlignment\n",
    "from pyflowsheet.internals import RandomPacking\n",
    "\n",
    "pfd2= Flowsheet(\"V100-DS20\",\"Simple Distillation\", \"Demo Flowsheet for testing functionality\")\n",
    "\n",
    "Feed= StreamFlag(\"F100\", \"Feed\", position=(0,200))\n",
    "WA10=HeatExchanger(\"DS10-WA10\",\"Pre-Heater\", position=(160,200))\n",
    "KA10=Distillation(\"DS10-KA10\",\"Distillation Tower\", hasCondenser=True, hasReboiler=True,position=(300,120), size=(40,200), internals=[RandomPacking()])\n",
    "P1= StreamFlag(\"P1\", \"Product 1\", position=(500,120))\n",
    "P2= StreamFlag(\"P2\", \"Product 2\", position=(0,120))\n",
    "\n",
    "pfd2.addUnits( [Feed,WA10,KA10,P1,P2] )\n",
    "\n",
    "pfd2.connect(\"S01\", Feed[\"Out\"], WA10[\"TIn\"] ) \n",
    "pfd2.connect(\"S02\", WA10[\"TOut\"], KA10[\"Feed\"] ) \n",
    "pfd2.connect(\"S03\", KA10[\"Top\"], P1[\"In\"] ) \n",
    "pfd2.connect(\"S04\", KA10[\"Bottom\"], WA10[\"SIn\"] ) \n",
    "pfd2.connect(\"S05\", WA10[\"SOut\"], P2[\"In\"] ) \n",
    "pfd2.showGrid=False\n",
    "#P2.rotate(180)\n",
    "P2.flip(axis=\"horizontal\")\n",
    "WA10.flip(axis=\"vertical\")\n",
    "KA10.setTextAnchor(HorizontalLabelAlignment.RightOuter,VerticalLabelAlignment.Center,(10,0) )\n",
    "\n",
    "ctx2= SvgContext(\"img/simple_column.svg\")\n",
    "img2 = pfd2.draw(ctx2)\n",
    "SVG(img2.render(scale=1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
      "image/svg+xml": "<svg baseProfile=\"full\" height=\"360px\" style=\"background-color:rgb(0, 128, 128)\" version=\"1.1\" viewBox=\"-40,60,540.0,360\" width=\"540.0px\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:ev=\"http://www.w3.org/2001/xml-events\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><defs><marker id=\"id3\" markerHeight=\"4\" markerWidth=\"4\" orient=\"auto\" refX=\"2\" refY=\"2\"><path d=\"M0,0 V4 L2,2 Z\" stroke-width=\"1\"/></marker></defs><g id=\"S01\"><path d=\"M 40 220.0  L 40 220  L 100 220  L 104.0 220.0 \" fill=\"none\" marker-end=\"url(#id3)\" stroke=\"rgb(0, 0, 255)\" stroke-width=\"2\"/><text fill=\"rgb(165, 165, 165)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"50\" y=\"230\">S01</text></g><g id=\"S02\"><path d=\"M 40 120.0  L 40 120  L 110 120  L 110 210  L 110.0 214.0 \" fill=\"none\" marker-end=\"url(#id3)\" stroke=\"rgb(0, 0, 255)\" stroke-width=\"2\"/><text fill=\"rgb(165, 165, 165)\" font-family=\"Arial\" font-size=\"10\" 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marker-end=\"url(#id3)\" stroke=\"rgb(0, 0, 255)\" stroke-width=\"2\"/><text fill=\"rgb(165, 165, 165)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"310\" y=\"200\">S06</text></g><g id=\"S07\"><path d=\"M 310.0 226.0  L 310 230  L 310 280  L 390 280  L 390 320  L 400 320 \" fill=\"none\" marker-end=\"url(#id3)\" stroke=\"rgb(0, 0, 255)\" stroke-width=\"2\"/><text fill=\"rgb(165, 165, 165)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"310\" y=\"260\">S07</text></g><g id=\"F100T\"><path d=\"M 0 210.0  L 20.0 210.0  L 20.0 200  L 40 220.0  L 20.0 240  L 20.0 230.0  L 0 230.0  Z\" fill=\"rgb(165, 165, 165)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"F100\"><text fill=\"rgb(255, 255, 255)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"20.0\" y=\"260\">F100</text></g><g id=\"F200T\"><path d=\"M 0 110.0  L 20.0 110.0  L 20.0 100  L 40 120.0  L 20.0 140  L 20.0 130.0  L 0 130.0  Z\" fill=\"rgb(165, 165, 165)\" 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0, 0)\" stroke-width=\"2\"/></g><g id=\"P2\"><text fill=\"rgb(255, 255, 255)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"420.0\" y=\"260\">P2</text></g><g id=\"P1T\"><path d=\"M 400 110.0  L 420.0 110.0  L 420.0 100  L 440 120.0  L 420.0 140  L 420.0 130.0  L 400 130.0  Z\" fill=\"rgb(165, 165, 165)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P1\"><text fill=\"rgb(255, 255, 255)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"420.0\" y=\"160\">P1</text></g><g id=\"P3T\"><path d=\"M 400 310.0  L 420.0 310.0  L 420.0 300  L 440 320.0  L 420.0 340  L 420.0 330.0  L 400 330.0  Z\" fill=\"rgb(165, 165, 165)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P3\"><text fill=\"rgb(255, 255, 255)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"420.0\" y=\"360\">P3</text></g></svg>"
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, UnitOperation, Distillation, Vessel, BlackBox, Pump, Stream, StreamFlag, Valve,HeatExchanger, SvgContext, Mixer,Splitter\n",
    "from IPython.core.display import SVG, HTML\n",
    "from pyflowsheet.internals import Tubes\n",
    "\n",
    "pfd3= Flowsheet(\"V100-DS20\",\"Simple Distillation\", \"Demo Flowsheet for testing functionality\")\n",
    "\n",
    "Feed= StreamFlag(\"F100\", \"Feed\", position=(0,200))\n",
    "Feed2= StreamFlag(\"F200\", \"Feed\", position=(0,100))\n",
    "MX10= Mixer(\"MX10\", \"Mixer\", position=(100,210))\n",
    "WA10=Vessel(\"DS10-WA10\",\"Condenser\", position=(180,180), angle=90, size=(40,80), internals=[Tubes()])\n",
    "\n",
    "SP10= Splitter(\"SP10\", \"Splitter\", position=(300,210))\n",
    "\n",
    "P2= StreamFlag(\"P1\", \"Product 1\", position=(400,100))\n",
    "P1= StreamFlag(\"P2\", \"Product 2\", position=(400,200))\n",
    "P3= StreamFlag(\"P3\", \"Product 2\", position=(400,300))\n",
    "\n",
    "\n",
    "\n",
    "pfd3.addUnits( [Feed,Feed2, MX10, WA10, SP10, P1,P2,P3] )\n",
    "\n",
    "pfd3.connect(\"S01\", Feed[\"Out\"], MX10[\"In1\"] ) \n",
    "pfd3.connect(\"S02\", Feed2[\"Out\"], MX10[\"In2\"] ) \n",
    "pfd3.connect(\"S03\", MX10[\"Out\"], WA10[\"In\"] ) \n",
    "pfd3.connect(\"S04\", WA10[\"Out\"], SP10[\"In\"] ) \n",
    "pfd3.connect(\"S05\", SP10[\"Out1\"], P1[\"In\"] ) \n",
    "pfd3.connect(\"S06\", SP10[\"Out2\"], P2[\"In\"] ) \n",
    "pfd3.connect(\"S07\", SP10[\"Out3\"], P3[\"In\"] ) \n",
    "pfd3.showGrid=False\n",
    "\n",
    "for s in pfd3.streams.values():\n",
    "    s.lineColor=(0,0,255,255)\n",
    "    s.textColor=(165,165,165,255)\n",
    "\n",
    "for u in pfd3.unitOperations.values():\n",
    "    u.lineColor=(0,0,0,255)\n",
    "    u.fillColor=(165,165,165,255)\n",
    "    u.textColor=(255,255,255,255)\n",
    "\n",
    "ctx3= SvgContext(\"img/styling_colouring.svg\", (0,128,128) )\n",
    "\n",
    "img3 = pfd3.draw(ctx3)\n",
    "SVG(img3.render(scale=1))\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
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y=\"135\"/></g><g id=\"SP2\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"510.0\" y=\"160\">SP2</text></g><g id=\"P1T\"><path d=\"M 560 130.0  L 580.0 130.0  L 580.0 120  L 600 140.0  L 580.0 160  L 580.0 150.0  L 560 150.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P1\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"580.0\" y=\"180\">P1</text></g><g id=\"P2T\" transform=\"translate(20.0,0) scale(-1,1) translate(-20.0,0)\"><path d=\"M 0 410.0  L 20.0 410.0  L 20.0 400  L 40 420.0  L 20.0 440  L 20.0 430.0  L 0 430.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P2\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"20.0\" y=\"460\">P2</text></g><g id=\"P3T\"><path d=\"M 560 10.0  L 580.0 10.0  L 580.0 0  L 600 20.0  L 580.0 40  L 580.0 30.0  L 560 30.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P3\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"580.0\" y=\"60\">P3</text></g></svg>"
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, UnitOperation, Distillation, Vessel, BlackBox, Pump, Stream, StreamFlag, Valve,HeatExchanger, Mixer, Splitter, Port, SvgContext\n",
    "from pyflowsheet.internals import Tubes,RandomPacking\n",
    "from IPython.core.display import SVG, HTML\n",
    "from pyflowsheet import VerticalLabelAlignment, HorizontalLabelAlignment\n",
    "\n",
    "pfd= Flowsheet(\"V100-DS10\",\"Complex Distillation\", \"Demo Flowsheet for testing externalized columns peripherals and routing\")\n",
    "\n",
    "Feed= StreamFlag(\"Feed\", \"Feed\", position=(0,250))\n",
    "HX1=HeatExchanger(\"Preheater\",\"Pre-Heater\", position=(160,250))\n",
    "TWR1=Distillation(\"Tower\",\"Distillation Tower\", hasCondenser=False, hasReboiler=False,position=(300,120), size=(40,300), internals=[RandomPacking(start=0, end=0.4),RandomPacking(start=0.6, end=1.0)])\n",
    "MX1= Mixer(\"MX1\", \"Mixer\", position=(400,450))\n",
    "SP1= Splitter(\"SP1\", \"Splitter\", position=(460,450))\n",
    "REB=Vessel(\"Reboiler\",\"Falling Film Evaporator\", position=(390,340), size=(40,80),capLength=20,internals=[Tubes(7)] )\n",
    "REB.ports[\"Out2\"] = Port(\"Out2\", REB, (0, .25), (-1, 0), intent=\"out\")\n",
    "COND=Vessel(\"Condenser\",\"Condenser\", position=(390,40), size=(40,100), internals=[Tubes()])\n",
    "COND.ports[\"Out2\"] = Port(\"Out2\", COND, (0, 0.15), (-1, 0), intent=\"out\")\n",
    "\n",
    "\n",
    "SP2= Splitter(\"SP2\", \"Reflux-Splitter\", position=(500,130))\n",
    "P1= StreamFlag(\"P1\", \"Product 1\", position=(560,120))\n",
    "P2= StreamFlag(\"P2\", \"Product 2\", position=(0,400))\n",
    "P3= StreamFlag(\"P3\", \"Product 3\", position=(560,0))\n",
    "\n",
    "#rotate units to resemble the actual plant layout\n",
    "\n",
    "COND.rotate(105)\n",
    "\n",
    "SP2.rotate(90)\n",
    "P2.flip(axis=\"horizontal\")\n",
    "REB.flip(axis=\"vertical\")\n",
    "\n",
    "pfd.addUnits( [Feed,HX1,TWR1,MX1, SP1, REB,COND,SP2, P1,P2,P3] )\n",
    "\n",
    "pfd.connect(\"S01\", Feed[\"Out\"], HX1[\"TIn\"] ) \n",
    "pfd.connect(\"S02\", HX1[\"TOut\"], TWR1[\"Feed\"] ) \n",
    "pfd.connect(\"S04\", TWR1[\"LOut\"], MX1[\"In1\"] ) \n",
    "pfd.connect(\"S05\", HX1[\"SOut\"], P2[\"In\"] ) \n",
    "pfd.connect(\"S06\", MX1[\"Out\"], SP1[\"In\"] ) \n",
    "pfd.connect(\"S08\", SP1[\"Out2\"], REB[\"In\"] ) \n",
    "pfd.connect(\"S09\", REB[\"Out\"], MX1[\"In2\"] ) \n",
    "pfd.connect(\"S10\", REB[\"Out2\"], TWR1[\"VIn\"] ) \n",
    "pfd.connect(\"S11\", TWR1[\"VOut\"], COND[\"In\"] ) \n",
    "pfd.connect(\"S12\", COND[\"Out\"], SP2[\"In\"] )\n",
    "pfd.connect(\"S13\", SP2[\"Out2\"], P1[\"In\"] ) \n",
    "pfd.connect(\"S14\", SP2[\"Out3\"], TWR1[\"RIn\"] ) \n",
    "pfd.connect(\"S15\", COND[\"Out2\"], P3[\"In\"] )\n",
    "pfd.connect(\"S07\", SP1[\"Out1\"], HX1[\"SIn\"] ) \n",
    "\n",
    "#If you do not like the automatic stream layout, you can manually define a sequence of relative steps (relative to last point). The first element is the difference in x direction, the second element is the difference in y. The route starts at the source connector.\n",
    "\n",
    "pfd.streams[\"S07\"].manualRouting=[(14,0),(0,30),(-240,0),(0,-260),(-70,0)] \n",
    "pfd.streams[\"S05\"].labelOffset=(10,30)\n",
    "pfd.streams[\"S07\"].labelOffset=(25,10)\n",
    "pfd.streams[\"S15\"].labelOffset=(10,-10)\n",
    "pfd.streams[\"S11\"].labelOffset=(10,-10)\n",
    "\n",
    "#Change the label positions to make them more readable\n",
    "TWR1.setTextAnchor(HorizontalLabelAlignment.RightOuter,VerticalLabelAlignment.Center,(10,0) )\n",
    "REB.setTextAnchor(HorizontalLabelAlignment.RightOuter,VerticalLabelAlignment.Center,(10,0) )\n",
    "\n",
    "#pfd.showGrid=True\n",
    "ctx= SvgContext(\"img/externalized_column_with_preheater.svg\")\n",
    "img = pfd.draw(ctx)\n",
    "SVG(img.render(width=1280, height=640 ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-23T20:55:03.875134Z",
     "start_time": "2020-12-23T20:55:03.658789Z"
    }
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
      "image/svg+xml": "<svg baseProfile=\"full\" height=\"560px\" style=\"background-color:rgb(255, 255, 255)\" version=\"1.1\" viewBox=\"-40,-40,1080,560\" width=\"1080px\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:ev=\"http://www.w3.org/2001/xml-events\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><defs><marker id=\"id10\" markerHeight=\"4\" markerWidth=\"4\" orient=\"auto\" refX=\"2\" refY=\"2\"><path d=\"M0,0 V4 L2,2 Z\" stroke-width=\"1\"/></marker></defs><g id=\"S01\"><path d=\"M 40 420.0  L 40 420  L 50 420  L 50 350  L 280 350  L 280 340 \" fill=\"none\" marker-end=\"url(#id10)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"50\" y=\"430\">S01</text></g><g id=\"S02\"><path d=\"M 280.0 200.0  L 280 200  L 280 20  L 300 20 \" fill=\"none\" marker-end=\"url(#id10)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"280\" y=\"200\">S02</text></g><g id=\"FeedT\"><path d=\"M 0 410.0  L 20.0 410.0  L 20.0 400  L 40 420.0  L 20.0 440  L 20.0 430.0  L 0 430.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"Feed\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"20.0\" y=\"460\">Feed</text></g><g id=\"HXT\"><path d=\"M 280.0 220.0  L 260.0 220.0  A 20.0 20.0 0 1,1 300.0 220.0 Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><rect fill=\"rgb(255, 255, 255)\" height=\"100.0\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"40\" x=\"260\" y=\"220.0\"/><path d=\"M 280.0 320.0  L 300.0 320.0  A 20.0 20.0 0 1,1 260.0 320.0 Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><line stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" x1=\"268.0\" x2=\"268.0\" y1=\"220.0\" y2=\"320.0\"/><line stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" x1=\"276.0\" x2=\"276.0\" y1=\"220.0\" y2=\"320.0\"/><line stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" x1=\"284.0\" x2=\"284.0\" y1=\"220.0\" y2=\"320.0\"/><line stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" x1=\"292.0\" x2=\"292.0\" y1=\"220.0\" y2=\"320.0\"/></g><g id=\"HX\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"280.0\" y=\"360\">HX</text></g><g id=\"P2T\"><path d=\"M 300 10.0  L 320.0 10.0  L 320.0 0  L 340 20.0  L 320.0 40  L 320.0 30.0  L 300 30.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"P2\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"320.0\" y=\"60\">P2</text></g><g id=\"text\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Consolas\" font-size=\"12\" text-anchor=\"start\" x=\"320\" y=\"235\">T1 = 128 °C</text></g><g id=\"text\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Consolas\" font-size=\"12\" text-anchor=\"start\" x=\"320\" y=\"250\">T2 = 133 °C</text></g><g id=\"text\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Consolas\" font-size=\"12\" text-anchor=\"start\" x=\"320\" y=\"265\">T3 = 138 °C</text></g><g id=\"text\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Consolas\" font-size=\"12\" text-anchor=\"start\" x=\"320\" y=\"280\">T4 = 143 °C</text></g><g id=\"text\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Consolas\" font-size=\"12\" text-anchor=\"start\" x=\"320\" y=\"295\">T5 = 148 °C</text></g><g id=\"Profile\"><image height=\"250\" width=\"250\" x=\"0\" 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y=\"100\"/><rect fill-opacity=\"0\" height=\"200\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"500\" x=\"500\" y=\"100\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"750.0\" y=\"320\">T1</text></g></svg>"
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, UnitOperation, Distillation, Vessel, BlackBox, Pump, Stream, StreamFlag, Valve,HeatExchanger, SvgContext,   TextElement\n",
    "from pyflowsheet.annotations.table import Table\n",
    "from pyflowsheet.annotations.figure import Figure\n",
    "\n",
    "from IPython.core.display import SVG, HTML\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "#Turn the interactive plotting option off to prohibit the plot to be shown twice\n",
    "plt.ioff()\n",
    "\n",
    "#Create your dataframe\n",
    "df = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD'))\n",
    "\n",
    "pfd= Flowsheet(\"V100-DS20\",\"Simple Distillation\", \"Demo Flowsheet for testing functionality\")\n",
    "\n",
    "Feed= StreamFlag(\"Feed\", \"Feed\", position=(0,400))\n",
    "HX=Vessel(\"HX\",\"Condenser\", position=(260,200),  size=(40,140), internals=\"tubes\")\n",
    "P2= StreamFlag(\"P2\", \"Product 2\", position=(300,000))\n",
    "\n",
    "pfd.addUnits( [Feed,HX,P2] )\n",
    "pfd.connect(\"S01\", Feed[\"Out\"], HX[\"In\"] ) \n",
    "pfd.connect(\"S02\", HX[\"Out\"], P2[\"In\"] ) \n",
    "\n",
    "#Create a new table object and pass the pandas table as the data argument. It will internally be rendered as a  matplotlib Table\n",
    "T1 = Table(\"T1\", \"DemoTable\", data=df, position=(500,100), size=(500,200),figsize=(12,5))\n",
    "\n",
    "#Create your plot. Pass it to the Figure annotation. Pass the figure object as the fig parameter. It will internally be rendered into a base64 encoded string and embedded into the SVG drawing.\n",
    "fig=df.plot(kind=\"line\",figsize=(5,5))\n",
    "F1 = Figure(\"Profile\", \"DemoFigure\", fig=plt.gcf(), position=(00,50), size=(250,250))\n",
    "\n",
    "#You can also create very simple tables on your own by creating callouts. In a real application the numbers would of course come from a real data source (simulation or plant data)\n",
    "for i in range(1,6):\n",
    "    pfd.callout(f\"T{i} = {123+5*i} °C\", (320,220+15*i) )\n",
    "\n",
    "pfd.addAnnotations([F1,T1])\n",
    "\n",
    "ctx= SvgContext(\"img/plots_and_tables.svg\")\n",
    "img = pfd.draw(ctx)\n",
    "SVG(img.render(scale=1))\n",
    "\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<IPython.core.display.SVG object>"
      ],
      "image/svg+xml": "<svg baseProfile=\"full\" height=\"355px\" style=\"background-color:rgb(255, 255, 255)\" version=\"1.1\" viewBox=\"-40,125,940.0,355\" width=\"940.0px\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:ev=\"http://www.w3.org/2001/xml-events\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><defs><marker id=\"id6\" markerHeight=\"4\" markerWidth=\"4\" orient=\"auto\" refX=\"2\" refY=\"2\"><path d=\"M0,0 V4 L2,2 Z\" stroke-width=\"1\"/></marker></defs><g id=\"S01\"><path d=\"M 40 210.0  L 40 210  L 100 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"50\" y=\"220\">S01</text></g><g id=\"S02\"><path d=\"M 180 210.0  L 180 210  L 240 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"190\" y=\"220\">S02</text></g><g id=\"S03\"><path d=\"M 320 210.0  L 320 210  L 380 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"330\" y=\"220\">S03</text></g><g id=\"S04\"><path d=\"M 460 210.0  L 460 210  L 520 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"470\" y=\"220\">S04</text></g><g id=\"S05\"><path d=\"M 600 210.0  L 600 210  L 660 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"610\" y=\"220\">S05</text></g><g id=\"S06\"><path d=\"M 740 210.0  L 740 210  L 800 210 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"750\" y=\"220\">S06</text></g><g id=\"S07\"><path d=\"M 140.0 240  L 140 240  L 140 360 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"140\" y=\"260\">S07</text></g><g id=\"S08\"><path d=\"M 700.0 240  L 700 240  L 700 360 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"700\" y=\"260\">S08</text></g><g id=\"S09\"><path d=\"M 420.0 180  L 420 180  L 420 170  L 280 170  L 280 180 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"420\" y=\"165\">S09</text></g><g id=\"S10\"><path d=\"M 560.0 240  L 560 240  L 560 250  L 280 250  L 280 240 \" fill=\"none\" marker-end=\"url(#id6)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"10\" text-anchor=\"middle\" x=\"560\" y=\"260\">S10</text></g><g id=\"FeedT\"><path d=\"M 0 200.0  L 20.0 200.0  L 20.0 190  L 40 210.0  L 20.0 230  L 20.0 220.0  L 0 220.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"Feed\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"20.0\" y=\"250\">Feed</text></g><g id=\"ProductT\"><path d=\"M 800 200.0  L 820.0 200.0  L 820.0 190  L 840 210.0  L 820.0 230  L 820.0 220.0  L 800 220.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"Product\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"820.0\" y=\"250\">Product</text></g><g id=\"WasteT\" transform=\"rotate(90,140.0,380.0 ) \"><path d=\"M 120 370.0  L 140.0 370.0  L 140.0 360  L 160 380.0  L 140.0 400  L 140.0 390.0  L 120 390.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"Waste\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"140.0\" y=\"420\">Waste</text></g><g id=\"SideProductT\" transform=\"rotate(90,700.0,380.0 ) \"><path d=\"M 680 370.0  L 700.0 370.0  L 700.0 360  L 720 380.0  L 700.0 400  L 700.0 390.0  L 680 390.0  Z\" fill=\"rgb(255, 255, 255)\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\"/></g><g id=\"SideProduct\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"700.0\" y=\"420\">SideProduct</text></g><g id=\"PretreatmentT\"><rect fill=\"rgb(255, 255, 255)\" height=\"60\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"80\" x=\"100\" y=\"180\"/></g><g id=\"Pretreatment\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"140.0\" y=\"215.0\">Pretreatment</text></g><g id=\"ReactionT\"><rect fill=\"rgb(255, 255, 255)\" height=\"60\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"80\" x=\"240\" y=\"180\"/></g><g id=\"Reaction\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"280.0\" y=\"215.0\">Reaction</text></g><g id=\"Gas-RecoveryT\"><rect fill=\"rgb(255, 255, 255)\" height=\"60\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"80\" x=\"380\" y=\"180\"/></g><g id=\"Gas-Recovery\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"420.0\" y=\"215.0\">Gas-Recovery</text></g><g id=\"SeparationT\"><rect fill=\"rgb(255, 255, 255)\" height=\"60\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"80\" x=\"520\" y=\"180\"/></g><g id=\"Separation\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"560.0\" y=\"215.0\">Separation</text></g><g id=\"PurificationT\"><rect fill=\"rgb(255, 255, 255)\" height=\"60\" stroke=\"rgb(0, 0, 0)\" stroke-width=\"2\" width=\"80\" x=\"660\" y=\"180\"/></g><g id=\"Purification\"><text fill=\"rgb(0, 0, 0)\" font-family=\"Arial\" font-size=\"12\" text-anchor=\"middle\" x=\"700.0\" y=\"215.0\">Purification</text></g></svg>"
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "source": [
    "from pyflowsheet import Flowsheet, BlackBox, Stream, StreamFlag, Port, SvgContext,VerticalLabelAlignment, HorizontalLabelAlignment\n",
    "from IPython.core.display import SVG, HTML\n",
    "\n",
    "pfd= Flowsheet(\"V100\",\"Block Flow Diagram\", \"Demo Flowsheet for showing block-flow diagram style\")\n",
    "\n",
    "SP1=BlackBox(\"Pretreatment\",\"Removal of catalyst poisons\", position=(100,180), size=(80,60))\n",
    "SP2=BlackBox(\"Reaction\",\"Catalytic reaction\", position=(240,180), size=(80,60))\n",
    "SP3=BlackBox(\"Gas-Recovery\",\"Recycling of unconverted gaseous feedstock\", position=(380,180), size=(80,60))\n",
    "SP4=BlackBox(\"Separation\",\"Recycling of solvent\", position=(520,180), size=(80,60))\n",
    "SP5=BlackBox(\"Purification\",\"Removal of side product\", position=(660,180), size=(80,60))\n",
    "\n",
    "Feed= StreamFlag(\"Feed\", \"\", position=(0,190))\n",
    "Product= StreamFlag(\"Product\", \"\", position=(800,190))\n",
    "Waste= StreamFlag(\"Waste\", \"\", position=(120,360))\n",
    "SideProduct= StreamFlag(\"SideProduct\", \"\", position=(680,360))\n",
    "\n",
    "steps=[SP1,SP2,SP3,SP4,SP5]\n",
    "\n",
    "for sp in steps:\n",
    "    sp.setTextAnchor(HorizontalLabelAlignment.Center,VerticalLabelAlignment.Center,(0,5) )\n",
    "\n",
    "Waste.rotate(90)\n",
    "SideProduct.rotate(90)\n",
    "\n",
    "#Add additional ports to the process steps for recycles and removal of unwanted components\n",
    "SP1.ports[\"Out2\"] = Port(\"Out2\", SP1, (0.5, 1), (0, 1), intent=\"out\")\n",
    "SP5.ports[\"Out2\"] = Port(\"Out2\", SP5, (0.5, 1), (0, 1), intent=\"out\")\n",
    "SP3.ports[\"Out2\"] = Port(\"Out2\", SP3, (0.5, 0), (0, -1), intent=\"out\")\n",
    "SP4.ports[\"Out2\"] = Port(\"Out2\", SP4, (0.5, 1), (0, 1), intent=\"out\")\n",
    "SP2.ports[\"In2\"] = Port(\"In2\", SP2, (0.5, 0), (0, -1))\n",
    "SP2.ports[\"In3\"] = Port(\"In3\", SP2, (0.5, 1), (0, 1))\n",
    "\n",
    "#Add all units to the diagram\n",
    "pfd.addUnits( [Feed,Product,Waste, SideProduct, SP1,SP2, SP3, SP4, SP5] )\n",
    "\n",
    "#Create stream connectivity\n",
    "pfd.connect(\"S01\", Feed[\"Out\"], SP1[\"In\"] ) \n",
    "pfd.connect(\"S02\", SP1[\"Out\"], SP2[\"In\"] ) \n",
    "pfd.connect(\"S03\", SP2[\"Out\"], SP3[\"In\"] ) \n",
    "pfd.connect(\"S04\", SP3[\"Out\"], SP4[\"In\"] ) \n",
    "pfd.connect(\"S05\", SP4[\"Out\"], SP5[\"In\"] ) \n",
    "pfd.connect(\"S06\", SP5[\"Out\"], Product[\"In\"] ) \n",
    "pfd.connect(\"S07\", SP1[\"Out2\"], Waste[\"In\"] ) \n",
    "pfd.connect(\"S08\", SP5[\"Out2\"], SideProduct[\"In\"] ) \n",
    "pfd.connect(\"S09\", SP3[\"Out2\"], SP2[\"In2\"] ) \n",
    "pfd.connect(\"S10\", SP4[\"Out2\"], SP2[\"In3\"] ) \n",
    "\n",
    "#Change the label offset for stream S09 to make it more readable\n",
    "pfd.streams[\"S09\"].labelOffset=(0,-5)\n",
    "\n",
    "#Create a rendering context for the flowsheet and display it. pfd.draw(ctx) will also save the file to disc.\n",
    "ctx= SvgContext(\"img/blockflowprocess.svg\")\n",
    "img = pfd.draw(ctx)\n",
    "SVG(img.render(scale=1))"
   ]
  },
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