{ "cells": [ { "cell_type": "markdown", "id": "blessed-heavy", "metadata": { "colab_type": "text", "id": "view-in-github" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "id": "legitimate-immigration", "metadata": {}, "source": [ "# An Introduction to Symbolic Music Processing with Partitura\n", "\n", "Partitura is python 3 package for symbolic music processing developed and maintained at OFAI Vienna / CP JKU Linz (and other contributors). It's inteded to give a lightweight musical part representation that makes many score properties easily accessible for a variety of tasks. Furthermore it's a very useful I/O utility to parse computer formats of symbolic music. " ] }, { "cell_type": "markdown", "id": "nonprofit-communication", "metadata": { "id": "3tvQmcSB7rrL" }, "source": [ "## 1. Install and import\n", "\n", "Partitura is available in github https://github.com/CPJKU/partitura\n", "\n", "You can install it with `pip install partitura`.\n", "\n", "However if you are interested in features that still have to be officially released, it's better to install the develop branch." ] }, { "cell_type": "code", "execution_count": null, "id": "facial-quarterly", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "PeabdL1k7YC4", "outputId": "fcb7d1be-27a1-4c79-c5d3-8cbfa54cae44", "scrolled": true, "pycharm": { "is_executing": true } }, "outputs": [], "source": [ "# Install partitura\n", "! pip install partitura\n", " \n", "# To be able to access helper modules in the repo for this tutorial\n", "# (not necessary if the jupyter notebook is run locally instead of google colab)\n", "!git clone https://github.com/CPJKU/partitura_tutorial.git\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "import sys, os\n", "sys.path.insert(0, os.path.join(os.getcwd(), \"partitura_tutorial\", \"content\"))\n", "sys.path.insert(0,'/content/partitura_tutorial/content')\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "impressed-principle", "metadata": {}, "outputs": [], "source": [ "import glob\n", "import partitura as pt\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "toxic-italian", "metadata": { "id": "CX8wCxyK7emp" }, "source": [ "#### Dataset for this tutorial\n", "\n", "In this tutorial we are going to use the [Vienna 4x22 Corpus](https://repo.mdw.ac.at/projects/IWK/the_vienna_4x22_piano_corpus/index.html) which consists of performances of 4 classical piano pieces, which have been aligned to their corresponding scores.\n", "\n", "The dataset contains:\n", "\n", "* Scores in MusicXML format (4 scores)\n", "* Performances in MIDI files (88 in total, 22 performances per piece, each by a different pianist)\n", "* Score to performance alignments in Match file format (88 in total one file per performance)" ] }, { "cell_type": "code", "execution_count": 3, "id": "photographic-profession", "metadata": {}, "outputs": [ { "data": { "text/plain": "Output()", "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "51b999065d4e4460b960ff64e7507006" } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# setup the dataset\n", "from load_data import init_dataset\n", "DATASET_DIR = init_dataset()\n", "MUSICXML_DIR = os.path.join(DATASET_DIR, 'musicxml')\n", "MIDI_DIR = os.path.join(DATASET_DIR, 'midi')\n", "MATCH_DIR = os.path.join(DATASET_DIR, 'match')" ] }, { "cell_type": "markdown", "id": "valued-helena", "metadata": {}, "source": [ "## 2. Loading and Exporting Files\n", "\n", "One of the main use cases of partitura is to load and export common symbolic music formats." ] }, { "cell_type": "markdown", "id": "sonic-better", "metadata": {}, "source": [ "### Supported Formats\n", "\n", "#### Reading\n", "\n", "##### Symbolic Scores\n", "\n", "These methods return a `Part`, a `PartGroup` or a list of `Part` objects.\n", "\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|MusicXML| `partitura.load_musicxml`| |\n", "|MIDI| `partitura.load_score_midi`|Pitch spelling, key signature (optional) and other information is inferred with methods in `partitura.musicanalysis`. \n", "|MEI| `partitura.load_mei`|\n", "|Humdrum Kern| `partitura.load_kern`|\n", "|MuseScore|`partitura.load_via_musescore`| Requires [MuseScore](https://musescore.org/en). Loads all formats supported by MuseScore. Support on Windows is still untested.\n", "\n", "##### Symbolic Performances\n", "\n", "These methods return a `PerformedPart`.\n", "\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|MIDI|`partitura.load_performance_midi`| Loads MIDI file as a performance, including track, channel and program information. Time signature and tempo information are only used to compute the time of the MIDI messages in seconds. Key signature information is ignored\n", "\n", "##### Alignments\n", "\n", "These methods return score-to-performance alignment (discussed below).\n", "\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|Match file| `partitura.load_match`| Returns alignment, a performance as `PerformedPart` and optionally a `Part`. See usage below.\n", "|Nakamura et al. corresp file | `partitura.load_nakamuracorresp`|\n", "|Nakamura et al. match file| `partitura.load_nakamuramatch`|\n", "\n", "#### Writing\n", "\n", "##### Symbolic Scores\n", "\n", "Support for MEI and Humdrum Kern is coming!\n", "\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|MusicXML| `partitura.save_musicxml`|\n", "|MIDI| `partitura.save_score_midi`| Includes Key signature, time signature and tempo information.\n", "\n", "##### Symbolic Performances\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|MIDI|`partitura.save_performance_midi`| Does not include key signature or time signature information\n", "\n", "##### Alignments\n", "\n", "A companion library for music alignment is in preparation!\n", "\n", "|Format| Method|Notes|\n", "|:---|:---|:---|\n", "|Match file| `partitura.save_match`| \n" ] }, { "cell_type": "markdown", "id": "dd98b602", "metadata": {}, "source": [ "## 3. Internal Representations\n", "\n", "### 3.1 The Part Object\n", "\n", "The ```part``` object is the central object of partitura. It contains a score.\n", "- it is a timeline object\n", "- time is measured in divs\n", "- its elements are timed objects, i.e. they have a starting time and an ending time\n", "- external score files are loaded into a part\n", "- parts can be exported into score files\n", "- it contains many useful methods related to its properties\n", "\n", "Here's a visual representation of the ```part``` object representing the first measure of Chopin's Nocturne Op. 9 No. 2" ] }, { "cell_type": "markdown", "id": "5754b952", "metadata": {}, "source": [ "![Timeline_chopin2.png](https://github.com/CPJKU/partitura_tutorial/raw/main/static/Timeline_chopin2.png)" ] }, { "cell_type": "code", "execution_count": 4, "id": "c9179e78", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Part id=\"P1\" name=\"Piano\"\n", " │\n", " ├─ TimePoint t=0 quarter=12\n", " │ │\n", " │ └─ starting objects\n", " │ │\n", " │ ├─ 0--48 Measure number=1\n", " │ ├─ 0--48 Note id=n01 voice=1 staff=2 type=whole pitch=A4\n", " │ ├─ 0--48 Page number=1\n", " │ ├─ 0--24 Rest id=r01 voice=2 staff=1 type=half\n", " │ ├─ 0--48 System number=1\n", " │ └─ 0-- TimeSignature 4/4\n", " │\n", " ├─ TimePoint t=24 quarter=12\n", " │ │\n", " │ ├─ ending objects\n", " │ │ │\n", " │ │ └─ 0--24 Rest id=r01 voice=2 staff=1 type=half\n", " │ │\n", " │ └─ starting objects\n", " │ │\n", " │ ├─ 24--48 Note id=n02 voice=2 staff=1 type=half pitch=C5\n", " │ └─ 24--48 Note id=n03 voice=2 staff=1 type=half pitch=E5\n", " │\n", " └─ TimePoint t=48 quarter=12\n", " │\n", " └─ ending objects\n", " │\n", " ├─ 0--48 Measure number=1\n", " ├─ 0--48 Note id=n01 voice=1 staff=2 type=whole pitch=A4\n", " ├─ 24--48 Note id=n02 voice=2 staff=1 type=half pitch=C5\n", " ├─ 24--48 Note id=n03 voice=2 staff=1 type=half pitch=E5\n", " ├─ 0--48 Page number=1\n", " └─ 0--48 System number=1\n" ] } ], "source": [ "path_to_musicxml = pt.EXAMPLE_MUSICXML\n", "part = pt.load_musicxml(path_to_musicxml)[0]\n", "print(part.pretty())" ] }, { "cell_type": "markdown", "id": "874a18d5", "metadata": {}, "source": [ "![score_example.png](https://github.com/CPJKU/partitura_tutorial/raw/main/static/score_example.png)" ] }, { "cell_type": "markdown", "id": "c5bae1ed", "metadata": {}, "source": [ "### Part Notes\n", "\n", "Each ```part``` object contains a list notes. Notes inherit from the ```TimedObject``` class. Like all ```TimedObjects``` they contain a (possibly coincident) start time and end time, encoded as ```TimePoint``` objects." ] }, { "cell_type": "code", "execution_count": 5, "id": "423aac6a", "metadata": {}, "outputs": [ { "data": { "text/plain": "[,\n ,\n ]" }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "part.notes" ] }, { "cell_type": "code", "execution_count": 6, "id": "0a929369", "metadata": {}, "outputs": [ { "data": { "text/plain": "['__class__',\n '__delattr__',\n '__dict__',\n '__dir__',\n '__doc__',\n '__eq__',\n '__format__',\n '__ge__',\n '__getattribute__',\n '__gt__',\n '__hash__',\n '__init__',\n '__init_subclass__',\n '__le__',\n '__lt__',\n '__module__',\n '__ne__',\n '__new__',\n '__reduce__',\n '__reduce_ex__',\n '__repr__',\n '__setattr__',\n '__sizeof__',\n '__str__',\n '__subclasshook__',\n '__weakref__',\n '_ref_attrs',\n '_sym_dur',\n 'alter',\n 'alter_sign',\n 'articulations',\n 'beam',\n 'doc_order',\n 'duration',\n 'duration_from_symbolic',\n 'duration_tied',\n 'end',\n 'end_tied',\n 'fermata',\n 'id',\n 'iter_chord',\n 'midi_pitch',\n 'octave',\n 'ornaments',\n 'replace_refs',\n 'slur_starts',\n 'slur_stops',\n 'staff',\n 'start',\n 'step',\n 'symbolic_duration',\n 'tie_next',\n 'tie_next_notes',\n 'tie_prev',\n 'tie_prev_notes',\n 'tuplet_starts',\n 'tuplet_stops',\n 'voice']" }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(part.notes[0])" ] }, { "cell_type": "markdown", "id": "c2287849", "metadata": {}, "source": [ "You can create notes (without timing information) and then add it to a part by specifying start and end times (in divs!). Use each note object only once! You can remove notes from a part." ] }, { "cell_type": "code", "execution_count": 7, "id": "2a8293c9", "metadata": {}, "outputs": [], "source": [ "a_new_note = pt.score.Note(id='n04', step='A', octave=4, voice=1)\n", "part.add(a_new_note, start=3, end=15)\n", "# print(part.pretty())" ] }, { "cell_type": "code", "execution_count": 8, "id": "eba2fa93", "metadata": {}, "outputs": [], "source": [ "part.remove(a_new_note)\n", "# print(part.pretty())" ] }, { "cell_type": "markdown", "id": "a8649483", "metadata": {}, "source": [ "### Converting from divs to musical units and back\n", "\n", "Integer divs are useful for encoding scores but unwieldy for human readers. Partitura offers a variety of ```*unit*_maps``` from the timeline unit \"div\" to musical units such as \"beats\" (in two different readings) or \"quarters\". For the inverse operation the corresponding ```inv_*unit*_map``` exist as well. Quarter to div ratio is a fixed value for a ```part``` object, but units like beats might change with time signature, so these ```maps``` are implemented as ```part``` methods.\n", "\n", "Let's look at how to get the ending position in beats of the last note in our example ```part```." ] }, { "cell_type": "code", "execution_count": 9, "id": "e95eb0f7", "metadata": {}, "outputs": [ { "data": { "text/plain": "array(4.)" }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "part.beat_map(part.notes[0].end.t)" ] }, { "cell_type": "markdown", "id": "6a2b7c10", "metadata": {}, "source": [ "Some musical information such as key and time signature is valid for a segment of the score but only encoded in one location. To retrieve the \"currently active\" time or key signature at any score position, ```maps``` are available too." ] }, { "cell_type": "code", "execution_count": 10, "id": "05346a03", "metadata": {}, "outputs": [ { "data": { "text/plain": "array([4., 4., 4.])" }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "part.time_signature_map(part.notes[0].end.t)" ] }, { "cell_type": "markdown", "id": "bf1d6ae9", "metadata": {}, "source": [ "### Iterating over arbitrary musical objects in a part\n", "\n", "The ```part``` class contains a central method ```iter_all``` to iterate over all instances of the ```TimedObject``` class or its subclasses of a part. The ```iter_all``` method returns an iterator and takes five optional parameters: \n", "- A ```TimedObject``` subclass whose instances are returned. You can find them all in the partitura/partitura/score.py file. Default is all classes.\n", "- A ```include_subclasses``` flag. If true, instances of subclasses are returned too. E.g. ``` part.iter_all(pt.score.TimedObject, include_subclasses=True)``` returns all objects or ```part.iter_all(pt.score.GenericNote, include_subclasses=True)``` returns all notes (grace notes, standard notes)\n", "- A start time in divs to specify the search interval (default is beginning of the part)\n", "- An end time in divs to specify the search interval (default is end of the part)\n", "- A ```mode``` parameter to define whether to search for starting or ending objects, defaults to starting." ] }, { "cell_type": "code", "execution_count": 11, "id": "74943a93", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0--48 Measure number=1\n" ] } ], "source": [ "for measure in part.iter_all(pt.score.Measure):\n", " print(measure)" ] }, { "cell_type": "code", "execution_count": 12, "id": "6cbfd044", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0--48 Note id=n01 voice=1 staff=2 type=whole pitch=A4\n", "0--24 Rest id=r01 voice=2 staff=1 type=half\n" ] } ], "source": [ "for note in part.iter_all(pt.score.GenericNote, include_subclasses=True, start=0, end=24):\n", " print(note)" ] }, { "cell_type": "markdown", "id": "d1455a5f", "metadata": {}, "source": [ "### Example: Adding a new measure and a note at its downbeat\n", "\n", "Let's use class retrieval, time mapping, and object creation together and add a new measure with a single beat-length note at its downbeat. This code works even if you know nothing about the underlying score." ] }, { "cell_type": "code", "execution_count": 13, "id": "fe430921", "metadata": {}, "outputs": [], "source": [ "# figure out the last measure position, time signature and beat length in divs\n", "measures = [m for m in part.iter_all(pt.score.Measure)]\n", "last_measure_number = measures[-1].number\n", "append_measure_start = measures[-1].end.t \n", "Last_measure_ts = part.time_signature_map(append_measure_start)\n", "\n", "Last_measure_ts = part.time_signature_map(append_measure_start)\n", "one_beat_in_divs_at_the_end = append_measure_start - part.inv_beat_map(part.beat_map(append_measure_start)-1)\n", "append_measure_end = append_measure_start + one_beat_in_divs_at_the_end*Last_measure_ts[0]\n", "\n", "# add a measure\n", "a_new_measure = pt.score.Measure(number = last_measure_number+1)\n", "part.add(a_new_measure, start=append_measure_start, end=append_measure_end)\n", "# add a note\n", "a_new_note = pt.score.Note(id='n04', step='A', octave=4, voice=1)\n", "part.add(a_new_note, start=append_measure_start, end=append_measure_start+one_beat_in_divs_at_the_end)" ] }, { "cell_type": "code", "execution_count": 14, "id": "f9d738a5", "metadata": {}, "outputs": [], "source": [ "# print(part.pretty())" ] }, { "cell_type": "markdown", "id": "129e4c8b", "metadata": {}, "source": [ "### 3.2 The PerformedPart Object\n", "\n", "The ```PerformedPart``` class is a wrapper for MIDI files. Its structure is much simpler:\n", "- a notes property that consists of list of MIDI notes as dictionaries\n", "- a controls property that consists of list of MIDI CC messages\n", "- some more utility methods and properties" ] }, { "cell_type": "code", "execution_count": 15, "id": "5d82a340", "metadata": {}, "outputs": [], "source": [ "path_to_midifile = pt.EXAMPLE_MIDI\n", "performedpart = pt.load_performance_midi(path_to_midifile)[0]" ] }, { "cell_type": "code", "execution_count": 16, "id": "4e3090d9", "metadata": {}, "outputs": [ { "data": { "text/plain": "[{'midi_pitch': 69,\n 'note_on': 0.0,\n 'note_off': 2.0,\n 'track': 0,\n 'channel': 1,\n 'velocity': 64,\n 'id': 'n0',\n 'sound_off': 2.0},\n {'midi_pitch': 72,\n 'note_on': 1.0,\n 'note_off': 2.0,\n 'track': 0,\n 'channel': 2,\n 'velocity': 64,\n 'id': 'n1',\n 'sound_off': 2.0},\n {'midi_pitch': 76,\n 'note_on': 1.0,\n 'note_off': 2.0,\n 'track': 0,\n 'channel': 2,\n 'velocity': 64,\n 'id': 'n2',\n 'sound_off': 2.0}]" }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "performedpart.notes" ] }, { "cell_type": "markdown", "id": "2bf8c482", "metadata": {}, "source": [ "### 3.3 Tiny example with cats on keyboards" ] }, { "cell_type": "code", "execution_count": 17, "id": "d6eb12f2", "metadata": {}, "outputs": [], "source": [ "import numpy as np \n", "\n", "def addnote(midipitch, part, voice, start, end, idx):\n", " \"\"\"\n", " adds a single note by midipitch to a part\n", " \"\"\"\n", " offset = midipitch%12\n", " octave = int(midipitch-offset)/12\n", " name = [(\"C\",0),\n", " (\"C\",1),\n", " (\"D\",0),\n", " (\"D\",1),\n", " (\"E\",0),\n", " (\"F\",0),\n", " (\"F\",1),\n", " (\"G\",0),\n", " (\"G\",1),\n", " (\"A\",0),\n", " (\"A\",1),\n", " (\"B\",0)]\n", " # print( id, start, end, offset)\n", " step, alter = name[int(offset)]\n", " part.add(pt.score.Note(id='n{}'.format(idx), step=step, \n", " octave=int(octave), alter=alter, voice=voice, staff=str((voice-1)%2+1)), \n", " start=start, end=end)" ] }, { "cell_type": "code", "execution_count": 18, "id": "572e856c", "metadata": {}, "outputs": [], "source": [ "l = 200\n", "p = pt.score.Part('CoK', 'Cat on Keyboard', quarter_duration=8)\n", "dur = np.random.randint(1,20, size=(4,l+1))\n", "ons = np.cumsum(dur, axis = 1)\n", "pitch = np.row_stack((np.random.randint(20,40, size=(1,l+1)),\n", " np.random.randint(60,80, size=(1,l+1)),\n", " np.random.randint(40,60, size=(1,l+1)),\n", " np.random.randint(40,60, size=(1,l+1))\n", " ))" ] }, { "cell_type": "code", "execution_count": 19, "id": "f9f03a50", "metadata": {}, "outputs": [], "source": [ "for k in range(l):\n", " for j in range(4):\n", " addnote(pitch[j,k], p, j+1, ons[j,k], ons[j,k]+dur[j,k+1], \"v\"+str(j)+\"n\"+str(k))" ] }, { "cell_type": "code", "execution_count": 20, "id": "09fb6b45", "metadata": {}, "outputs": [], "source": [ "p.add(pt.score.TimeSignature(4, 4), start=0)\n", "p.add(pt.score.Clef(1, \"G\", line = 3, octave_change=0),start=0)\n", "p.add(pt.score.Clef(2, \"G\", line = 3, octave_change=0),start=0)\n", "pt.score.add_measures(p)\n", "pt.score.tie_notes(p)" ] }, { "cell_type": "code", "execution_count": 21, "id": "834582d5", "metadata": {}, "outputs": [], "source": [ "# pt.save_score_midi(p, \"CatPerformance.mid\", part_voice_assign_mode=2)" ] }, { "cell_type": "code", "execution_count": 22, "id": "006f02ed", "metadata": {}, "outputs": [], "source": [ "# pt.save_musicxml(p, \"CatScore.xml\")" ] }, { "cell_type": "markdown", "id": "identical-gathering", "metadata": {}, "source": [ "## 4. Extracting Information from Scores and Performances\n", "\n", "For many MIR tasks we need to extract specific information out of scores or performances. \n", "Two of the most common representations are **note arrays** and **piano rolls**. \n", "\n", "**Note that there is some overlap in the way that these terms are used.**\n", "\n", "Partitura provides convenience methods to extract these common features in a few lines!" ] }, { "cell_type": "markdown", "id": "ordinary-psychology", "metadata": {}, "source": [ "### 4.1 Note Arrays\n", "\n", "A **note array** is a 2D array in which each row represents a note in the score/performance and each column represents different attributes of the note.\n", "\n", "In partitura, note arrays are [structured numpy arrays](https://numpy.org/devdocs/user/basics.rec.html), which are ndarrays in which each \"column\" has a name, and can be of different datatypes. \n", "This allows us to hold information that can be represented as integers (MIDI pitch/velocity), floating point numbers (e.g., onset time) or strings (e.g., note ids). \n", "\n", "In this tutorial we are going to cover 3 main cases\n", "\n", "* Getting a note array from `Part` and `PerformedPart` objects\n", "* Extra information and alternative ways to generate a note array\n", "* Creating a custom note array from scratch from a `Part` object\n", "\n", "\n", "#### 4.1.1. Getting a note array from `Part` and `PerformedPart` objects\n", "\n", "##### Getting a note array from `Part` objects" ] }, { "cell_type": "code", "execution_count": 23, "id": "first-basin", "metadata": {}, "outputs": [], "source": [ "# Note array from a score\n", "\n", "# Path to the MusicXML file\n", "score_fn = os.path.join(MUSICXML_DIR, 'Chopin_op38.musicxml')\n", "\n", "# Load the score into a `Part` object\n", "score_part = pt.load_musicxml(score_fn)\n", "\n", "# Get note array.\n", "score_note_array = score_part.note_array()" ] }, { "cell_type": "markdown", "id": "looking-whole", "metadata": {}, "source": [ "It is that easy!" ] }, { "cell_type": "code", "execution_count": 24, "id": "alternate-coordinate", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(-4., 1., -2. , 0.5, 0, 8, 60, 4, 'n2', 16)\n", " (-4., 1., -2. , 0.5, 0, 8, 72, 1, 'n1', 16)\n", " (-3., 2., -1.5, 1. , 8, 16, 60, 4, 'n4', 16)\n", " (-3., 2., -1.5, 1. , 8, 16, 72, 1, 'n3', 16)\n", " (-1., 1., -0.5, 0.5, 24, 8, 60, 4, 'n6', 16)\n", " (-1., 1., -0.5, 0.5, 24, 8, 72, 1, 'n5', 16)\n", " ( 0., 2., 0. , 1. , 32, 16, 60, 4, 'n8', 16)\n", " ( 0., 2., 0. , 1. , 32, 16, 72, 1, 'n7', 16)\n", " ( 2., 1., 1. , 0.5, 48, 8, 60, 4, 'n10', 16)\n", " ( 2., 1., 1. , 0.5, 48, 8, 72, 1, 'n9', 16)]\n" ] } ], "source": [ "# Lets see the first notes in this note array\n", "print(score_note_array[:10])" ] }, { "cell_type": "markdown", "id": "toxic-publicity", "metadata": {}, "source": [ "![example_note_array-2.png](https://raw.githubusercontent.com/CPJKU/partitura_tutorial/main/static/example_note_array.png)\n", "\n", "By default, Partitura includes some of the most common note-level information in the note array:" ] }, { "cell_type": "code", "execution_count": 25, "id": "subtle-millennium", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "('onset_beat', 'duration_beat', 'onset_quarter', 'duration_quarter', 'onset_div', 'duration_div', 'pitch', 'voice', 'id', 'divs_pq')\n" ] } ], "source": [ "print(score_note_array.dtype.names)" ] }, { "cell_type": "markdown", "id": "exact-practice", "metadata": {}, "source": [ "* `onset_beat` is the onset time in beats (as indicated by the time signature). In partitura, negative onset times in beats represent pickup measures. Onset time 0 is the start of the first measure.\n", "* `duration_beat` is the duration of the note in beats\n", "* `onset_quarter` is the onset time of the note in quarters (independent of the time signature). Similarly to onset time in beats, negative onset times in quarters represent pickup measures and onset time 0 is the start of the first measure.\n", "* `duration_quarter`is the duration of the note in quarters\n", "* `onset_div` is the onset of the note in *divs*, which is generally a number that allows to represent the note position and duration losslessly with integers. In contrast to onset time in beats or quarters, onset time in divs always start at 0 at the first \"element\" in the score (which might not necessarily be a note).\n", "* `duration_div` is the duration of the note in divs.\n", "* `pitch` is the MIDI pitch (MIDI note number) of the note\n", "* `voice` is the voice of the note (in polyphonic music, where there can be multiple notes at the same time)\n", "* `id` is the note id (as appears in MusicXML or MEI formats)" ] }, { "cell_type": "markdown", "id": "compressed-baseball", "metadata": {}, "source": [ "##### Getting a note array from a `PerformedPart`\n", "\n", "In a similar way, we can obtain a note array from a MIDI file in a few lines" ] }, { "cell_type": "code", "execution_count": 26, "id": "passing-lending", "metadata": {}, "outputs": [], "source": [ "# Note array from a performance\n", "\n", "# Path to the MIDI file\n", "performance_fn = os.path.join(MIDI_DIR, 'Chopin_op38_p01.mid')\n", "\n", "# Loading the file to a PerformedPart\n", "performance_part = pt.load_performance_midi(performance_fn)\n", "\n", "# Get note array!\n", "performance_note_array = performance_part.note_array()" ] }, { "cell_type": "markdown", "id": "bright-equity", "metadata": {}, "source": [ "Since performances contain have other information not included in scores, the default fields in the note array are a little bit different:" ] }, { "cell_type": "code", "execution_count": 27, "id": "pointed-stupid", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "('onset_sec', 'duration_sec', 'pitch', 'velocity', 'track', 'channel', 'id')\n" ] } ], "source": [ "print(performance_note_array.dtype.names)" ] }, { "cell_type": "markdown", "id": "cathedral-generator", "metadata": {}, "source": [ "* `onset_sec` is the onset time of the note in seconds. Onset time in seconds is always $\\geq 0$ (otherwise, the performance would violate the laws of physics ;)\n", "* `duration_sec` is the duration of the note in seconds\n", "* `pitch` is the MIDI pitch\n", "* `velocity` is the MIDI velocity\n", "* `track` is the track number in the MIDI file\n", "* `channel` is the channel in the MIDI file\n", "* `id` is the ID of the notes (automatically generated for MIDI file according to onset time)" ] }, { "cell_type": "code", "execution_count": 28, "id": "subject-reducing", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(5.6075 , 5.5025 , 72, 37, 0, 0, 'n0')\n", " (5.63375, 5.47625, 60, 27, 0, 0, 'n1')\n", " (6.07 , 5.04 , 72, 45, 0, 0, 'n2')\n", " (6.11125, 4.99875, 60, 26, 0, 0, 'n3')\n", " (6.82625, 4.28375, 60, 39, 0, 0, 'n4')]\n" ] } ], "source": [ "print(performance_note_array[:5])" ] }, { "cell_type": "markdown", "id": "naval-prescription", "metadata": {}, "source": [ "We can also create a `PerformedPart` directly from a note array" ] }, { "cell_type": "code", "execution_count": 29, "id": "spread-performer", "metadata": {}, "outputs": [], "source": [ "note_array = np.array(\n", " [(60, 0, 2, 40),\n", " (65, 0, 1, 15),\n", " (67, 0, 1, 72),\n", " (69, 1, 1, 90),\n", " (66, 2, 1, 80)],\n", " dtype=[(\"pitch\", \"i4\"),\n", " (\"onset_sec\", \"f4\"),\n", " (\"duration_sec\", \"f4\"),\n", " (\"velocity\", \"i4\"),\n", " ]\n", ")\n", "\n", "# Note array to `PerformedPart`\n", "performed_part = pt.performance.PerformedPart.from_note_array(note_array)" ] }, { "cell_type": "markdown", "id": "catholic-dealer", "metadata": {}, "source": [ "We can then export the `PerformedPart` to a MIDI file!" ] }, { "cell_type": "code", "execution_count": 30, "id": "changed-check", "metadata": {}, "outputs": [], "source": [ "# export as MIDI file\n", "pt.save_performance_midi(performed_part, \"example.mid\")" ] }, { "cell_type": "markdown", "id": "typical-taxation", "metadata": {}, "source": [ "#### 4.1.2. Extra information and alternative ways to generate a note array\n", "\n", "Sometimes we require more information in a note array." ] }, { "cell_type": "code", "execution_count": 31, "id": "figured-coordinator", "metadata": {}, "outputs": [], "source": [ "extended_score_note_array = pt.utils.music.ensure_notearray(\n", " score_part,\n", " include_pitch_spelling=True, # adds 3 fields: step, alter, octave \n", " include_key_signature=True, # adds 2 fields: ks_fifths, ks_mode\n", " include_time_signature=True, # adds 2 fields: ts_beats, ts_beat_type \n", " # include_metrical_position=True, # adds 3 fields: is_downbeat, rel_onset_div, tot_measure_div\n", " include_grace_notes=True # adds 2 fields: is_grace, grace_type\n", ")" ] }, { "cell_type": "code", "execution_count": 32, "id": "vietnamese-pathology", "metadata": {}, "outputs": [ { "data": { "text/plain": "('onset_beat',\n 'duration_beat',\n 'onset_quarter',\n 'duration_quarter',\n 'onset_div',\n 'duration_div',\n 'pitch',\n 'voice',\n 'id',\n 'step',\n 'alter',\n 'octave',\n 'is_grace',\n 'grace_type',\n 'ks_fifths',\n 'ks_mode',\n 'ts_beats',\n 'ts_beat_type',\n 'ts_mus_beats',\n 'divs_pq')" }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "extended_score_note_array.dtype.names" ] }, { "cell_type": "code", "execution_count": 33, "id": "crude-courage", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[('n2', 'C', 0, 4, -1, 1) ('n1', 'C', 0, 5, -1, 1)\n", " ('n4', 'C', 0, 4, -1, 1) ('n3', 'C', 0, 5, -1, 1)\n", " ('n6', 'C', 0, 4, -1, 1) ('n5', 'C', 0, 5, -1, 1)\n", " ('n8', 'C', 0, 4, -1, 1) ('n7', 'C', 0, 5, -1, 1)\n", " ('n10', 'C', 0, 4, -1, 1) ('n9', 'C', 0, 5, -1, 1)]\n" ] } ], "source": [ "print(extended_score_note_array[['id', \n", " 'step', \n", " 'alter', \n", " 'octave', \n", " 'ks_fifths', \n", " 'ks_mode', #'is_downbeat'\n", " ]][:10])" ] }, { "cell_type": "markdown", "id": "greek-failure", "metadata": {}, "source": [ "[//]:![example_extended_note_array_cof.png](https://raw.githubusercontent.com/CPJKU/partitura_tutorial/main/static/example_extended_note_array_cof.png)\n", "
\n", "\n", "
" ] }, { "cell_type": "markdown", "id": "global-elite", "metadata": {}, "source": [ "#### 4.1.3. Creating a custom note array from scratch from a `Part` object\n", "\n", "Sometimes we are interested in other note-level information that is not included in the standard note arrays. \n", "With partitura we can create such a note array easily!\n", "\n", "For example, imagine that we want a note array that includes whether the notes have an accent mark." ] }, { "cell_type": "code", "execution_count": 34, "id": "invalid-rhythm", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(0.25, 47, 1) (1.25, 47, 1) (2.25, 47, 1) (3. , 68, 1) (3.25, 47, 1)]\n" ] } ], "source": [ "# Path to the MusicXML file\n", "score_fn = os.path.join(MUSICXML_DIR, 'Chopin_op10_no3.musicxml')\n", "\n", "# Load the score into a `Part` object\n", "score_part = pt.load_musicxml(score_fn)[0]\n", "\n", "def get_accent_note_array(part):\n", " \n", " fields = [(\"onset_beat\", \"f4\"), \n", " (\"pitch\", \"i4\"),\n", " (\"accent\", \"i4\")]\n", " # Get all notes in the part\n", " notes = part.notes_tied\n", " # Beat map (maps divs to score time in beats)\n", " beat_map = part.beat_map\n", " N = len(notes)\n", " note_array = np.zeros(N, dtype=fields)\n", " for i, n in enumerate(notes):\n", " # MIDI pitch\n", " note_array[i]['pitch'] = n.midi_pitch\n", " # Get the onset time in beats\n", " note_array[i]['onset_beat'] = beat_map(n.start.t)\n", " \n", " # Iterate over articulations in the note\n", " if n.articulations:\n", " for art in n.articulations:\n", " if art == 'accent':\n", " note_array[i]['accent'] = 1\n", " return note_array\n", "\n", "accent_note_array = get_accent_note_array(score_part)\n", "\n", "accented_note_idxs = np.where(accent_note_array['accent'])\n", "print(accent_note_array[accented_note_idxs][:5])" ] }, { "cell_type": "markdown", "id": "after-season", "metadata": {}, "source": [ "
\n", "\n", "
" ] }, { "cell_type": "markdown", "id": "adjusted-fundamental", "metadata": {}, "source": [ "### 4.2 Piano rolls\n", "\n", "Piano rolls are 2D matrices that represent pitch and time information. The time represents time steps (at a given resolution), while the pitch axis represents which notes are active at a given time step. We can think of piano rolls as the symbolic equivalent of spectrograms. \n", "\n", "#### Extracting a piano roll" ] }, { "cell_type": "code", "execution_count": 35, "id": "essential-academy", "metadata": {}, "outputs": [], "source": [ "# TODO: change the example\n", "# Path to the MusicXML file\n", "score_fn = os.path.join(MUSICXML_DIR, 'Chopin_op10_no3.musicxml')\n", "\n", "# Load the score\n", "score_part = pt.load_musicxml(score_fn)\n", "# compute piano roll\n", "pianoroll = pt.utils.compute_pianoroll(score_part)" ] }, { "cell_type": "markdown", "id": "entire-nitrogen", "metadata": {}, "source": [ "The `compute_pianoroll` method has a few arguments to customize the resulting piano roll" ] }, { "cell_type": "code", "execution_count": 36, "id": "massive-monaco", "metadata": {}, "outputs": [], "source": [ "piano_range = True\n", "time_unit = 'beat'\n", "time_div = 10\n", "pianoroll = pt.utils.compute_pianoroll(\n", " note_info=score_part, # a `Part`, `PerformedPart` or a note array\n", " time_unit=time_unit, # beat, quarter, div, sec, etc. (depending on note_info)\n", " time_div=time_div, # Number of cells per time unit\n", " piano_range=piano_range # Use range of the piano (88 keys)\n", ")" ] }, { "cell_type": "markdown", "id": "quality-coast", "metadata": {}, "source": [ "An important thing to remember is that in piano rolls generated by `compute_pianoroll`, rows (the vertical axis) represent the pitch dimension and the columns (horizontal) the time dimension. \n", "This results in a more intuitive way of plotting the piano roll. \n", "For other applications the transposed version of this piano roll might be more useful (i.e., rows representing time steps and columns representing pitch information).\n", "\n", "Since piano rolls can result in very large matrices where most of the elements are 0, the output of `compute_pianoroll` is a [scipy sparse matrix](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csc_matrix.html). To convert it to a regular numpy array, we can simply use `pianoroll.toarray()`" ] }, { "cell_type": "markdown", "id": "intended-answer", "metadata": {}, "source": [ "Let's plot the piano roll!" ] }, { "cell_type": "code", "execution_count": 37, "id": "mature-dylan", "metadata": {}, "outputs": [ { "data": { "text/plain": "
", "image/png": 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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, figsize=(20, 10))\n", "ax.imshow(pianoroll.toarray(), origin=\"lower\", cmap='gray', interpolation='nearest', aspect='auto')\n", "ax.set_xlabel(f'Time ({time_unit}s/{time_div})')\n", "ax.set_ylabel('Piano key' if piano_range else 'MIDI pitch')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "funky-tract", "metadata": {}, "source": [ "In some cases, we want to know the \"coordinates\" of each of the notes in the piano roll. The `compute_pianoroll` method includes an option to return " ] }, { "cell_type": "code", "execution_count": 38, "id": "palestinian-owner", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[59 0 4]\n", " [40 4 12]\n", " [40 4 6]\n", " [56 4 6]\n", " [64 4 8]]\n" ] } ], "source": [ "pianoroll, note_indices = pt.utils.compute_pianoroll(score_part, return_idxs=True)\n", "\n", "# MIDI pitch, start, end\n", "print(note_indices[:5])" ] }, { "cell_type": "markdown", "id": "economic-denial", "metadata": {}, "source": [ "#### Generating a note array from a piano roll\n", "\n", "Partitura also includes a method to generate a note array from a piano roll, which can be used to generate a MIDI file. \n", "This method would be useful, e.g., for music generation tasks" ] }, { "cell_type": "code", "execution_count": 39, "id": "parental-links", "metadata": {}, "outputs": [], "source": [ "pianoroll = pt.utils.compute_pianoroll(score_part)\n", "\n", "new_note_array = pt.utils.pianoroll_to_notearray(pianoroll)\n", "\n", "# We can export the note array to a MIDI file\n", "ppart = pt.performance.PerformedPart.from_note_array(new_note_array)\n", "\n", "pt.save_performance_midi(ppart, \"newmidi.mid\")" ] }, { "cell_type": "markdown", "id": "floating-madison", "metadata": {}, "source": [ "## 5. Handling Alignment Information (Match files)\n", "\n", "### 5.1 Loading Alignments\n", "An important use case of partitura is to handle symbolic alignment information\n", "\n", "**Note that partitura itself does not contain methods for alignment**\n", "\n", "Partitura supports 2 formats for encoding score-to-performance alignments\n", "\n", "* Our match file format, introduced by Gerhard et al. ;)\n", " * Datasets including match files: Vienna4x22, Magaloff, Zeilinger, Batik, and soon ASAP!\n", "* The format introduced by [Nakamura et al. (2017)](https://eita-nakamura.github.io/articles/EN_etal_ErrorDetectionAndRealignment_ISMIR2017.pdf)\n", "\n", "Let's load an alignment!\n", "\n", "We have two common use cases\n", "\n", "* We have both the match file and the symbolic score file (e.g., MusicXML or MEI)\n", "* We have only the match file (only works for our format!)" ] }, { "cell_type": "markdown", "id": "crucial-virus", "metadata": {}, "source": [ "#### 5.1.1. Loading an alignment if we only have a match file\n", "\n", "A useful property of match files is that they include information about the **score and the performance**. Therefore, it is possible to create both a `Part` and a `PerformedPart` directly from a match file.\n", "\n", "* Match files contain all information included in performances in MIDI files, i.e., a MIDI file could be reconstructed from a match file.\n", "\n", "* Match files include all information information about pitch spelling and score position and duration of the notes in the score, as well as time and key signature information, and can encode some note-level markings, like accents. Nevertheless, it is important to note that the score information included in a match file is not necessarily complete. For example, match files do not generally include dynamics or tempo markings." ] }, { "cell_type": "code", "execution_count": 40, "id": "rolled-cloud", "metadata": {}, "outputs": [], "source": [ "# path to the match\n", "match_fn = os.path.join(MATCH_DIR, 'Chopin_op10_no3_p01.match')\n", "# loading a match file\n", "performed_part, alignment, score_part = pt.load_match(match_fn, create_part=True)" ] }, { "cell_type": "markdown", "id": "wooden-looking", "metadata": {}, "source": [ "#### 5.1.2. Loading an alignment if we have both score and match files\n", "\n", "In many cases, however, we have access to both the score and match files. Using the original score file has a few advantages:\n", "\n", "* It ensures that the score information is correct. Generating a `Part` from a match file involves inferring information for non-note elements (e.g., start and end time of the measures, voice information, clefs, staves, etc.).\n", "* If we want to load several performances of the same piece, we can load the score only once!\n", "\n", "This should be the preferred way to get alignment information!" ] }, { "cell_type": "code", "execution_count": 41, "id": "latest-smell", "metadata": {}, "outputs": [], "source": [ "# path to the match\n", "match_fn = os.path.join(MATCH_DIR, 'Chopin_op10_no3_p01.match')\n", "# Path to the MusicXML file\n", "score_fn = os.path.join(MUSICXML_DIR, 'Chopin_op10_no3.musicxml')\n", "# Load the score into a `Part` object\n", "score_part = pt.load_musicxml(score_fn)[0]\n", "\n", "# loading a match file\n", "performed_part, alignment = pt.load_match(match_fn)" ] }, { "cell_type": "markdown", "id": "pending-college", "metadata": {}, "source": [ "Score-to-performance alignments are represented by lists of dictionaries, which contain the following keys:\n", "\n", "* `label`\n", "\n", " * `'match'`: there is a performed note corresponding to a score note\n", " * `'insertion'`: the performed note does not correspond to any note in the score\n", " * `'deletion'`: there is no performed note corresponding to a note in the score\n", " * `'ornament'`: the performed note corresponds to the performance of an ornament (e.g., a trill). These notes are matched to the main note in the score. Not all alignments (in the datasets that we have) include ornamnets! Otherwise, ornaments are just treated as insertions.\n", "* `score_id`: id of the note in the score (in the `Part` object) (only relevant for matches, deletions and ornaments)\n", "* `performance_id`: Id of the note in the performance (in the `PerformedPart`) (only relevant for matches, insertions and ornaments)" ] }, { "cell_type": "code", "execution_count": 42, "id": "radio-interim", "metadata": {}, "outputs": [ { "data": { "text/plain": "[{'label': 'match', 'score_id': 'n1', 'performance_id': 0},\n {'label': 'match', 'score_id': 'n2', 'performance_id': 2},\n {'label': 'match', 'score_id': 'n3', 'performance_id': 3},\n {'label': 'match', 'score_id': 'n4', 'performance_id': 1},\n {'label': 'match', 'score_id': 'n5', 'performance_id': 5},\n {'label': 'match', 'score_id': 'n6', 'performance_id': 4},\n {'label': 'match', 'score_id': 'n7', 'performance_id': 6},\n {'label': 'match', 'score_id': 'n8', 'performance_id': 7},\n {'label': 'match', 'score_id': 'n9', 'performance_id': 8},\n {'label': 'match', 'score_id': 'n10', 'performance_id': 9}]" }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "alignment[:10]" ] }, { "cell_type": "markdown", "id": "exact-decrease", "metadata": {}, "source": [ "### 5.2 Getting information from the alignments\n", "\n", "Partitura includes a few methods for getting information from the alignments.\n", "\n", "Let's start by getting the subset of score notes that have a corresponding performed note" ] }, { "cell_type": "code", "execution_count": 43, "id": "published-understanding", "metadata": {}, "outputs": [], "source": [ "# note array of the score\n", "snote_array = score_part.note_array()\n", "# note array of the performance\n", "pnote_array = performed_part.note_array()\n", "# indices of the notes that have been matched\n", "matched_note_idxs = pt.utils.music.get_matched_notes(snote_array, pnote_array, alignment)\n", "\n", "# note array of the matched score notes\n", "matched_snote_array = snote_array[matched_note_idxs[:, 0]]\n", "# note array of the matched performed notes\n", "matched_pnote_array = pnote_array[matched_note_idxs[:, 1]]" ] }, { "cell_type": "markdown", "id": "alike-doctor", "metadata": {}, "source": [ "#### Comparing tempo curves\n", "\n", "In this example, we are going to compare tempo curves of different performances of the same piece. Partitura includes a utility function called `get_time_maps_from_alignment`which creates functions (instances of [`scipy.interpolate.interp1d`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html)) that map score time to performance time (and the other way around)." ] }, { "cell_type": "code", "execution_count": 44, "id": "offshore-bridal", "metadata": {}, "outputs": [], "source": [ "# get all match files\n", "matchfiles = glob.glob(os.path.join(MATCH_DIR, 'Chopin_op10_no3_p*.match'))\n", "matchfiles.sort()\n", "\n", "# Score time from the first to the last onset\n", "score_time = np.linspace(snote_array['onset_beat'].min(),\n", " snote_array['onset_beat'].max(),\n", " 100)\n", "# Include the last offset\n", "score_time_ending = np.r_[\n", " score_time, \n", " (snote_array['onset_beat'] + snote_array['duration_beat']).max() # last offset\n", "]\n", "\n", "tempo_curves = np.zeros((len(matchfiles), len(score_time)))\n", "for i, matchfile in enumerate(matchfiles):\n", " # load alignment\n", " performance, alignment = pt.load_match(matchfile)\n", " ppart = performance[0]\n", " # Get score time to performance time map\n", " _, stime_to_ptime_map = pt.utils.music.get_time_maps_from_alignment(\n", " ppart, score_part, alignment)\n", " # Compute naïve tempo curve\n", " performance_time = stime_to_ptime_map(score_time_ending)\n", " tempo_curves[i,:] = 60 * np.diff(score_time_ending) / np.diff(performance_time)" ] }, { "cell_type": "code", "execution_count": 45, "id": "brazilian-honey", "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": "
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\n" }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, figsize=(15, 8))\n", "color = plt.cm.rainbow(np.linspace(0, 1, len(tempo_curves)))\n", "for i, tempo_curve in enumerate(tempo_curves):\n", " ax.plot(score_time, tempo_curve, \n", " label=f'pianist {i + 1:02d}', alpha=0.4, c=color[i])\n", "\n", "# plot average performance\n", "ax.plot(score_time, tempo_curves.mean(0), label='average', c='black', linewidth=2)\n", "\n", "# get starting time of each measure in the score\n", "measure_times = score_part.beat_map([measure.start.t for measure in score_part.iter_all(pt.score.Measure)])\n", "# do not include pickup measure\n", "measure_times = measure_times[measure_times >= 0]\n", "ax.set_title('Chopin Op. 10 No. 3')\n", "ax.set_xlabel('Score time (beats)')\n", "ax.set_ylabel('Tempo (bpm)')\n", "ax.set_xticks(measure_times)\n", "plt.legend(frameon=False, bbox_to_anchor = (1.15, .9))\n", "plt.grid(axis='x')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "2372b392", "metadata": {}, "source": [ "## The end of the tutorial, the start of your yet untold adventures in symbolic music processing...\n", "\n", "Thank you for trying out partitura! We hope it serves you well. \n", "\n", "If you miss a particular functionality or encounter a bug, we appreciate it if you raise an issue on GitHub: https://github.com/CPJKU/partitura/issues" ] } ], "metadata": { "colab": { "authorship_tag": "ABX9TyNCzhR7KnjsrjKGf/HDyInO", "include_colab_link": true, "name": "Partitura tutorial", "provenance": [] }, "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": "3.8.11" } }, "nbformat": 4, "nbformat_minor": 5 }