{
 "metadata": {
  "name": "",
  "signature": "sha256:4333d63d09055aa78d14e3ecde9af0bd1e9d7675ce5f4deb7c71a6b878b92f27"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Preamble"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This was taken and slightly adapted from the example section of the abjad documentation. I am not the author of the content (only the porting to noteook format). I have removed all diacritics for now."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from abjad import *\n",
      "%load_ext abjad.ext.ipython"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Bartok - Mikrokosmos"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We\u2019ll construct the fragment top-down from containers to notes. We could have done it the other way around but it will be easier to keep the big picture in mind this way. Later, you can rebuild the example bottom-up as an exercise.\n",
      "\n",
      "First let\u2019s create an empty score with a pair of staves connected by a brace:"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "The score"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We\u2019ll construct the fragment top-down from containers to notes. We could have done it the other way around but it will be easier to keep the big picture in mind this way. Later, you can rebuild the example bottom-up as an exercise.\n",
      "\n",
      "First let\u2019s create an empty score with a pair of staves connected by a brace:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "score = Score([])\n",
      "piano = instrumenttools.Piano([])\n",
      "staff_group = StaffGroup(context_name='PianoStaff', name='Piano')\n",
      "attach(piano, staff_group)\n",
      "upper_staff = Staff([])\n",
      "lower_staff = Staff([])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "staff_group.append(upper_staff)\n",
      "staff_group.append(lower_staff)\n",
      "score.append(staff_group)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "The measures"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let\u2019s add some empty measures:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_measures = []\n",
      "upper_measures.append(Measure((2, 4), []))\n",
      "upper_measures.append(Measure((3, 4), []))\n",
      "upper_measures.append(Measure((2, 4), []))\n",
      "upper_measures.append(Measure((2, 4), []))\n",
      "upper_measures.append(Measure((2, 4), []))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import copy\n",
      "lower_measures = copy.deepcopy(upper_measures)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_staff.extend(upper_measures)\n",
      "lower_staff.extend(lower_measures)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "The notes"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let\u2019s add some notes.\n",
      "\n",
      "We begin with the upper staff:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_measures[0].extend(\"a'8 g'8 f'8 e'8\")\n",
      "upper_measures[1].extend(\"d'4 g'8 f'8 e'8 d'8\")\n",
      "upper_measures[2].extend(\"c'8 d'16 e'16 f'8 e'8\")\n",
      "upper_measures[3].append(\"d'2\")\n",
      "upper_measures[4].append(\"d'2\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The first three measures of the lower staff contain only one voice:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lower_measures[0].extend(\"b4 d'8 c'8\")\n",
      "lower_measures[1].extend(\"b8 a8 af4 c'8 bf8\")\n",
      "lower_measures[2].extend(\"a8 g8 fs8 g16 a16\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The last two measures of the lower staff contain two voices each.\n",
      "\n",
      "We use LilyPond \\voiceOne and \\voiceTwo commands to set the direction of stems in different voices. And we set is_simltaneous to true for each of the last two measures:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_voice = Voice(\"b2\", name='upper voice')\n",
      "command = indicatortools.LilyPondCommand('voiceOne')\n",
      "attach(command, upper_voice)\n",
      "lower_voice = Voice(\"b4 a4\", name='lower voice')\n",
      "command = indicatortools.LilyPondCommand('voiceTwo')\n",
      "attach(command, lower_voice)\n",
      "lower_measures[3].extend([upper_voice, lower_voice])\n",
      "lower_measures[3].is_simultaneous = True"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_voice = Voice(\"b2\", name='upper voice')\n",
      "command = indicatortools.LilyPondCommand('voiceOne')\n",
      "attach(command, upper_voice)\n",
      "lower_voice = Voice(\"g2\", name='lower voice')\n",
      "command = indicatortools.LilyPondCommand('voiceTwo')\n",
      "attach(command, lower_voice)\n",
      "lower_measures[4].extend([upper_voice, lower_voice])\n",
      "lower_measures[4].is_simultaneous = True"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here\u2019s our work so far:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "show(score)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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/UAC+QsGov5fbWm6TvAZXY9HoJPRm4X5m2v8oA3HM+VVtM6CdzUKFr8WijS23SF6FK7Io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\nXFgAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "The details"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Ok, let\u2019s add the details. First, notice that the bottom staff has a treble clef just like the top staff. Let\u2019s change that:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clef = Clef('bass')\n",
      "attach(clef, lower_staff)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now let\u2019s add dynamics. For the top staff, we\u2019ll add them to the first note of the first measure and the second note of the second measure. For the bottom staff, we\u2019ll add dynamicings to the second note of the first measure and the fourth note of the second measure:\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dynamic = Dynamic('pp')\n",
      "attach(dynamic, upper_measures[0][0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dynamic = Dynamic('mp')\n",
      "attach(dynamic, upper_measures[1][1])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dynamic = Dynamic('pp')\n",
      "attach(dynamic, lower_measures[0][1])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dynamic = Dynamic('mp')\n",
      "attach(dynamic, lower_measures[1][3])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let\u2019s add a double bar to the end of the piece:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "score.add_final_bar_line()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "BarLine('|.')"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And see how things are coming out:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "show(score)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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6HM3m4JGj68Ae5hhKPNYt2BKT0iTfd5+IGU0wsOD3WEay9PX9fMbDFiPuv74fb+bR0bkg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\nTCBHaG9zdHNjcmlwdCA5LjE0nbNcWAAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notice that the beams of the eighth and sixteenth notes appear as you would usually expect: grouped by beat. We get this for free thanks to LilyPond\u2019s default beaming algorithm. But this is not the way Bart\u00f3k notated the beams. Let\u2019s set the beams as Bart\u00f3k did with some crossing the bar lines:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "upper_leaves = upper_staff.select_leaves(allow_discontiguous_leaves=True)\n",
      "lower_leaves = lower_staff.select_leaves(allow_discontiguous_leaves=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "beam = Beam()\n",
      "attach(beam, upper_leaves[:4])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "beam = Beam()\n",
      "attach(beam, lower_leaves[1:5])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "beam = Beam()\n",
      "attach(beam, lower_leaves[6:10])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "show(score)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAB8CAAAAABY77maAAAABGdBTUEAALGPC/xhBQAAAAFzUkdC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\nb2Z0d2FyZQBHUEwgR2hvc3RzY3JpcHQgOS4xNJ2zXFgAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now some slurs:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "slur = Slur()\n",
      "attach(slur, upper_leaves[:5])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "slur = Slur()\n",
      "attach(slur, upper_leaves[5:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "slur = Slur()\n",
      "attach(slur, lower_leaves[1:6])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 26
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Hairpins:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "crescendo = Crescendo()\n",
      "attach(crescendo, upper_leaves[-7:-2])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "decrescendo = Decrescendo()\n",
      "attach(decrescendo, upper_leaves[-2:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A ritardando marking above the last seven notes of the upper staff:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "markup = Markup('ritard.')\n",
      "text_spanner = spannertools.TextSpanner()\n",
      "override(text_spanner).text_spanner.bound_details__left__text = markup\n",
      "attach(text_spanner, upper_leaves[-7:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 29
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And ties connecting the last two notes in each staff:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tie = Tie()\n",
      "attach(tie, upper_leaves[-2:])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "note_1 = lower_staff[-2]['upper voice'][0]\n",
      "note_2 = lower_staff[-1]['upper voice'][0]\n",
      "notes = [note_1, note_2]\n",
      "tie = Tie()\n",
      "attach(tie, notes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The final result:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "show(score)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}