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Fix issue 378 #379

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Oct 2, 2024
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fix time maps import
sildater committed Oct 1, 2024

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This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
commit 3fdfd39c716975158073da070f283154bd972161
186 changes: 93 additions & 93 deletions docs/source/Tutorial/notebook.ipynb
Original file line number Diff line number Diff line change
@@ -47,11 +47,12 @@
},
"id": "PeabdL1k7YC4",
"outputId": "fcb7d1be-27a1-4c79-c5d3-8cbfa54cae44",
"scrolled": true,
"pycharm": {
"is_executing": true
}
},
"scrolled": true
},
"outputs": [],
"source": [
"# Install partitura\n",
"! pip install partitura\n",
@@ -64,21 +65,20 @@
"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"
],
"outputs": []
]
},
{
"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"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -103,15 +103,15 @@
"execution_count": 3,
"id": "photographic-profession",
"metadata": {},
"outputs": [],
"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')"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -220,12 +220,12 @@
"execution_count": 4,
"id": "c9179e78",
"metadata": {},
"outputs": [],
"source": [
"path_to_musicxml = pt.EXAMPLE_MUSICXML\n",
"part = pt.load_musicxml(path_to_musicxml)[0]\n",
"print(part.pretty())"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -250,20 +250,20 @@
"execution_count": 5,
"id": "423aac6a",
"metadata": {},
"outputs": [],
"source": [
"part.notes"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "0a929369",
"metadata": {},
"outputs": [],
"source": [
"dir(part.notes[0])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -278,23 +278,23 @@
"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())"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "eba2fa93",
"metadata": {},
"outputs": [],
"source": [
"part.remove(a_new_note)\n",
"# print(part.pretty())"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -313,10 +313,10 @@
"execution_count": 9,
"id": "e95eb0f7",
"metadata": {},
"outputs": [],
"source": [
"part.beat_map(part.notes[0].end.t)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -331,10 +331,10 @@
"execution_count": 10,
"id": "05346a03",
"metadata": {},
"outputs": [],
"source": [
"part.time_signature_map(part.notes[0].end.t)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -356,22 +356,22 @@
"execution_count": 11,
"id": "74943a93",
"metadata": {},
"outputs": [],
"source": [
"for measure in part.iter_all(pt.score.Measure):\n",
" print(measure)"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "6cbfd044",
"metadata": {},
"outputs": [],
"source": [
"for note in part.iter_all(pt.score.GenericNote, include_subclasses=True, start=0, end=24):\n",
" print(note)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -388,6 +388,7 @@
"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",
@@ -405,18 +406,17 @@
"# 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)"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "f9d738a5",
"metadata": {},
"outputs": [],
"source": [
"# print(part.pretty())"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -436,21 +436,21 @@
"execution_count": 15,
"id": "5d82a340",
"metadata": {},
"outputs": [],
"source": [
"path_to_midifile = pt.EXAMPLE_MIDI\n",
"performedpart = pt.load_performance_midi(path_to_midifile)[0]"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "4e3090d9",
"metadata": {},
"outputs": [],
"source": [
"performedpart.notes"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -465,6 +465,7 @@
"execution_count": 17,
"id": "d6eb12f2",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np \n",
"\n",
@@ -491,14 +492,14 @@
" 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)"
],
"outputs": []
]
},
{
"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",
@@ -509,54 +510,53 @@
" np.random.randint(40,60, size=(1,l+1)),\n",
" np.random.randint(40,60, size=(1,l+1))\n",
" ))"
],
"outputs": []
]
},
{
"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))"
],
"outputs": []
]
},
{
"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)"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "834582d5",
"metadata": {},
"outputs": [],
"source": [
"# pt.save_score_midi(p, \"CatPerformance.mid\", part_voice_assign_mode=2)"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "006f02ed",
"metadata": {},
"outputs": [],
"source": [
"# pt.save_musicxml(p, \"CatScore.xml\")"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -602,6 +602,7 @@
"execution_count": 23,
"id": "first-basin",
"metadata": {},
"outputs": [],
"source": [
"# Note array from a score\n",
"\n",
@@ -613,8 +614,7 @@
"\n",
"# Get note array.\n",
"score_note_array = score_part.note_array()"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -629,11 +629,11 @@
"execution_count": 24,
"id": "alternate-coordinate",
"metadata": {},
"outputs": [],
"source": [
"# Lets see the first notes in this note array\n",
"print(score_note_array[:10])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -650,10 +650,10 @@
"execution_count": 25,
"id": "subtle-millennium",
"metadata": {},
"outputs": [],
"source": [
"print(score_note_array.dtype.names)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -686,6 +686,7 @@
"execution_count": 26,
"id": "passing-lending",
"metadata": {},
"outputs": [],
"source": [
"# Note array from a performance\n",
"\n",
@@ -697,8 +698,7 @@
"\n",
"# Get note array!\n",
"performance_note_array = performance_part.note_array()"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -713,10 +713,10 @@
"execution_count": 27,
"id": "pointed-stupid",
"metadata": {},
"outputs": [],
"source": [
"print(performance_note_array.dtype.names)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -737,10 +737,10 @@
"execution_count": 28,
"id": "subject-reducing",
"metadata": {},
"outputs": [],
"source": [
"print(performance_note_array[:5])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -755,6 +755,7 @@
"execution_count": 29,
"id": "spread-performer",
"metadata": {},
"outputs": [],
"source": [
"note_array = np.array(\n",
" [(60, 0, 2, 40),\n",
@@ -771,8 +772,7 @@
"\n",
"# Note array to `PerformedPart`\n",
"performed_part = pt.performance.PerformedPart.from_note_array(note_array)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -787,11 +787,11 @@
"execution_count": 30,
"id": "changed-check",
"metadata": {},
"outputs": [],
"source": [
"# export as MIDI file\n",
"pt.save_performance_midi(performed_part, \"example.mid\")"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -808,6 +808,7 @@
"execution_count": 31,
"id": "figured-coordinator",
"metadata": {},
"outputs": [],
"source": [
"extended_score_note_array = pt.utils.music.ensure_notearray(\n",
" score_part,\n",
@@ -817,18 +818,17 @@
" # 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",
")"
],
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "vietnamese-pathology",
"metadata": {},
"outputs": [],
"source": [
"extended_score_note_array.dtype.names"
],
"outputs": []
]
},
{
"cell_type": "code",
@@ -837,6 +837,7 @@
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"print(extended_score_note_array[['id', \n",
" 'step', \n",
@@ -845,8 +846,7 @@
" 'ks_fifths', \n",
" 'ks_mode', #'is_downbeat'\n",
" ]][:10])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -879,6 +879,7 @@
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# Path to the MusicXML file\n",
"score_fn = os.path.join(MUSICXML_DIR, 'Chopin_op10_no3.musicxml')\n",
@@ -914,8 +915,7 @@
"\n",
"accented_note_idxs = np.where(accent_note_array['accent'])\n",
"print(accent_note_array[accented_note_idxs][:5])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -944,6 +944,7 @@
"execution_count": 35,
"id": "essential-academy",
"metadata": {},
"outputs": [],
"source": [
"# TODO: change the example\n",
"# Path to the MusicXML file\n",
@@ -953,8 +954,7 @@
"score_part = pt.load_musicxml(score_fn)\n",
"# compute piano roll\n",
"pianoroll = pt.utils.compute_pianoroll(score_part)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -969,6 +969,7 @@
"execution_count": 36,
"id": "massive-monaco",
"metadata": {},
"outputs": [],
"source": [
"piano_range = True\n",
"time_unit = 'beat'\n",
@@ -979,8 +980,7 @@
" time_div=time_div, # Number of cells per time unit\n",
" piano_range=piano_range # Use range of the piano (88 keys)\n",
")"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1007,14 +1007,14 @@
"execution_count": 37,
"id": "mature-dylan",
"metadata": {},
"outputs": [],
"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()"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1031,13 +1031,13 @@
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"pianoroll, note_indices = pt.utils.compute_pianoroll(score_part, return_idxs=True)\n",
"\n",
"# MIDI pitch, start, end\n",
"print(note_indices[:5])"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1055,6 +1055,7 @@
"execution_count": 39,
"id": "parental-links",
"metadata": {},
"outputs": [],
"source": [
"pianoroll = pt.utils.compute_pianoroll(score_part)\n",
"\n",
@@ -1064,8 +1065,7 @@
"ppart = pt.performance.PerformedPart.from_note_array(new_note_array)\n",
"\n",
"pt.save_performance_midi(ppart, \"newmidi.mid\")"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1112,13 +1112,13 @@
"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)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1140,6 +1140,7 @@
"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",
@@ -1150,8 +1151,7 @@
"\n",
"# loading a match file\n",
"performed_part, alignment = pt.load_match(match_fn)"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1175,10 +1175,10 @@
"execution_count": 42,
"id": "radio-interim",
"metadata": {},
"outputs": [],
"source": [
"alignment[:10]"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1197,6 +1197,7 @@
"execution_count": 43,
"id": "published-understanding",
"metadata": {},
"outputs": [],
"source": [
"# note array of the score\n",
"snote_array = score_part.note_array()\n",
@@ -1209,8 +1210,7 @@
"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]]"
],
"outputs": []
]
},
{
"cell_type": "markdown",
@@ -1227,6 +1227,7 @@
"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",
@@ -1248,13 +1249,12 @@
" 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",
" _, stime_to_ptime_map = pt.musicanalysis.performance_codec.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)"
],
"outputs": []
]
},
{
"cell_type": "code",
@@ -1263,6 +1263,7 @@
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"fig, ax = plt.subplots(1, figsize=(15, 8))\n",
"color = plt.cm.rainbow(np.linspace(0, 1, len(tempo_curves)))\n",
@@ -1284,8 +1285,7 @@
"plt.legend(frameon=False, bbox_to_anchor = (1.15, .9))\n",
"plt.grid(axis='x')\n",
"plt.show()"
],
"outputs": []
]
},
{
"cell_type": "markdown",