Overview#
This notebook gives a general overview of the features included in the dataset.
Show imports
%load_ext autoreload
%autoreload 2
import os
import dimcat as dc
import pandas as pd
import plotly.express as px
from dimcat import filters, plotting
from IPython.display import display
import utils
RESULTS_PATH = os.path.abspath(os.path.join(utils.OUTPUT_FOLDER, "overview"))
os.makedirs(RESULTS_PATH, exist_ok=True)
def make_output_path(
filename: str,
extension=None,
path=RESULTS_PATH,
) -> str:
return utils.make_output_path(filename=filename, extension=extension, path=path)
def save_figure_as(
fig, filename, formats=("png", "pdf"), directory=RESULTS_PATH, **kwargs
):
if formats is not None:
for fmt in formats:
plotting.write_image(fig, filename, directory, format=fmt, **kwargs)
else:
plotting.write_image(fig, filename, directory, **kwargs)
Loading data
D = utils.get_dataset("handel_keyboard", corpus_release="v2.4")
package = D.inputs.get_package()
package_info = package._package.custom
git_tag = package_info.get("git_tag")
utils.print_heading("Data and software versions")
print("Georg Friedrich Händel – Grobschmied Variations (The Harmonious Blacksmith), HWV 430 version v2.4")
print(f"Datapackage '{package.package_name}' @ {git_tag}")
print(f"dimcat version {dc.__version__}\n")
D
Data and software versions
--------------------------
Georg Friedrich Händel – Grobschmied Variations (The Harmonious Blacksmith), HWV 430 version v2.4
Datapackage 'handel_keyboard' @ v2.4
dimcat version 3.4.0
Dataset
=======
{'inputs': {'basepath': None,
'packages': {'handel_keyboard': ["'handel_keyboard.measures' (MuseScoreFacetName.MuseScoreMeasures)",
"'handel_keyboard.notes' (MuseScoreFacetName.MuseScoreNotes)",
"'handel_keyboard.expanded' (MuseScoreFacetName.MuseScoreHarmonies)",
"'handel_keyboard.chords' (MuseScoreFacetName.MuseScoreChords)",
"'handel_keyboard.metadata' (FeatureName.Metadata)"]}},
'outputs': {'basepath': None, 'packages': {}},
'pipeline': []}
filtered_D = filters.HasHarmonyLabelsFilter(keep_values=[True]).process(D)
all_metadata = filtered_D.get_metadata()
assert len(all_metadata) > 0, "No pieces selected for analysis."
all_metadata
TimeSig | KeySig | last_mc | last_mn | length_qb | last_mc_unfolded | last_mn_unfolded | length_qb_unfolded | volta_mcs | all_notes_qb | ... | P86 (composer) | wikidata | musicbrainz | viaf | imslp | staff_1_ambitus | staff_1_instrument | staff_2_ambitus | staff_2_instrument | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
corpus | piece | |||||||||||||||||||||
handel_keyboard | hwv430d_Grobschmied_Aria | {1: '4/4'} | {1: 4} | 10 | 9 | 33.0 | 15 | 13 | 49.0 | () | 118.00 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/8cea9064-6469-4f7... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 28-61 (E1-C#4) | Piano |
hwv430d_Grobschmied_Var1 | {1: '4/4'} | {1: 4} | 9 | 8 | 35.0 | 9 | 8 | 35.0 | () | 109.00 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/49671912-7caf-4a9... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 35-61 (B1-C#4) | Piano | |
hwv430d_Grobschmied_Var2 | {1: '4/4'} | {1: 4} | 9 | 8 | 35.0 | 9 | 8 | 35.0 | () | 98.50 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/a2537e39-31cc-4b4... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 35-64 (B1-E4) | Piano | |
hwv430d_Grobschmied_Var3 | {1: '4/4'} | {1: 4} | 10 | 8 | 33.0 | 18 | 16 | 64.0 | (9], [10) | 76.67 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/eb340003-0458-41c... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-80 (G#3-G#5) | Piano | 40-64 (E2-E4) | Piano | |
hwv430d_Grobschmied_Var4 | {1: '4/4'} | {1: 4} | 11 | 8 | 34.0 | 15 | 12 | 48.0 | (10], [11) | 107.50 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/a1d2fc88-b43c-4ab... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-78 (G#3-F#5) | Piano | 35-61 (B1-C#4) | Piano | |
hwv430d_Grobschmied_Var5 | {1: '4/4'} | {1: 4} | 13 | 12 | 51.0 | 13 | 12 | 51.0 | () | 136.75 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/8684d851-9b46-42e... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 54-83 (F#3-B5) | Piano | 28-61 (E1-C#4) | Piano |
6 rows × 55 columns
mean_composition_years = utils.corpus_mean_composition_years(all_metadata)
chronological_order = mean_composition_years.index.to_list()
corpus_colors = dict(zip(chronological_order, utils.CORPUS_COLOR_SCALE))
corpus_names = {
corp: utils.get_corpus_display_name(corp) for corp in chronological_order
}
chronological_corpus_names = list(corpus_names.values())
corpus_name_colors = {
corpus_names[corp]: color for corp, color in corpus_colors.items()
}
mean_composition_years
corpus
handel_keyboard 1720.0
Name: mean_composition_year, dtype: float64
Composition dates#
This section relies on the dataset’s metadata.
valid_composed_start = pd.to_numeric(all_metadata.composed_start, errors="coerce")
valid_composed_end = pd.to_numeric(all_metadata.composed_end, errors="coerce")
print(
f"Composition dates range from {int(valid_composed_start.min())} {valid_composed_start.idxmin()} "
f"to {int(valid_composed_end.max())} {valid_composed_end.idxmax()}."
)
Composition dates range from 1720 ('handel_keyboard', 'hwv430d_Grobschmied_Aria') to 1720 ('handel_keyboard', 'hwv430d_Grobschmied_Aria').
Mean composition years per corpus#
def make_summary(metadata_df):
piece_is_annotated = metadata_df.label_count > 0
return metadata_df[piece_is_annotated].copy()
Show source
summary = make_summary(all_metadata)
bar_data = pd.concat(
[
mean_composition_years.rename("year"),
summary.groupby(level="corpus").size().rename("pieces"),
],
axis=1,
).reset_index()
N = len(summary)
fig = px.bar(
bar_data,
x="year",
y="pieces",
color="corpus",
color_discrete_map=corpus_colors,
title=f"Temporal coverage of the {N} annotated pieces in the Distant Listening Corpus",
)
fig.update_traces(width=5)
fig.update_layout(**utils.STD_LAYOUT)
fig.update_traces(width=5)
save_figure_as(fig, "pieces_timeline_bars")
fig.show()
summary
TimeSig | KeySig | last_mc | last_mn | length_qb | last_mc_unfolded | last_mn_unfolded | length_qb_unfolded | volta_mcs | all_notes_qb | ... | P86 (composer) | wikidata | musicbrainz | viaf | imslp | staff_1_ambitus | staff_1_instrument | staff_2_ambitus | staff_2_instrument | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
corpus | piece | |||||||||||||||||||||
handel_keyboard | hwv430d_Grobschmied_Aria | {1: '4/4'} | {1: 4} | 10 | 9 | 33.0 | 15 | 13 | 49.0 | () | 118.00 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/8cea9064-6469-4f7... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 28-61 (E1-C#4) | Piano |
hwv430d_Grobschmied_Var1 | {1: '4/4'} | {1: 4} | 9 | 8 | 35.0 | 9 | 8 | 35.0 | () | 109.00 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/49671912-7caf-4a9... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 35-61 (B1-C#4) | Piano | |
hwv430d_Grobschmied_Var2 | {1: '4/4'} | {1: 4} | 9 | 8 | 35.0 | 9 | 8 | 35.0 | () | 98.50 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/a2537e39-31cc-4b4... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-76 (G#3-E5) | Piano | 35-64 (B1-E4) | Piano | |
hwv430d_Grobschmied_Var3 | {1: '4/4'} | {1: 4} | 10 | 8 | 33.0 | 18 | 16 | 64.0 | (9], [10) | 76.67 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/eb340003-0458-41c... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-80 (G#3-G#5) | Piano | 40-64 (E2-E4) | Piano | |
hwv430d_Grobschmied_Var4 | {1: '4/4'} | {1: 4} | 11 | 8 | 34.0 | 15 | 12 | 48.0 | (10], [11) | 107.50 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/a1d2fc88-b43c-4ab... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 56-78 (G#3-F#5) | Piano | 35-61 (B1-C#4) | Piano | |
hwv430d_Grobschmied_Var5 | {1: '4/4'} | {1: 4} | 13 | 12 | 51.0 | 13 | 12 | 51.0 | () | 136.75 | ... | Q7302 | https://imslp.org/wiki/Special:ReverseLookup/8... | https://www.wikidata.org/wiki/Q3793888 | https://musicbrainz.org/work/8684d851-9b46-42e... | https://viaf.org/viaf/4651167867552523060002/ | https://imslp.org/wiki/Suite_in_E_major%2C_HWV... | 54-83 (F#3-B5) | Piano | 28-61 (E1-C#4) | Piano |
6 rows × 55 columns
Composition years histogram#
Show source
hist_data = summary.reset_index()
hist_data.corpus = hist_data.corpus.map(corpus_names)
fig = px.histogram(
hist_data,
x="composed_end",
color="corpus",
labels=dict(
composed_end="decade",
count="pieces",
),
color_discrete_map=corpus_name_colors,
title=f"Temporal coverage of the {N} annotated pieces in the Distant Listening Corpus",
)
fig.update_traces(xbins=dict(size=10))
fig.update_layout(**utils.STD_LAYOUT)
fig.update_legends(font=dict(size=16))
save_figure_as(fig, "pieces_timeline_histogram", height=1250)
fig.show()
Dimensions#
Overview#
def make_overview_table(groupby, group_name="pieces"):
n_groups = groupby.size().rename(group_name)
absolute_numbers = dict(
measures=groupby.last_mn.sum(),
length=groupby.length_qb.sum(),
notes=groupby.n_onsets.sum(),
labels=groupby.label_count.sum(),
)
absolute = pd.DataFrame.from_dict(absolute_numbers)
absolute = pd.concat([n_groups, absolute], axis=1)
sum_row = pd.DataFrame(absolute.sum(), columns=["sum"]).T
absolute = pd.concat([absolute, sum_row])
return absolute
absolute = make_overview_table(summary.groupby("workTitle"))
# print(absolute.astype(int).to_markdown())
absolute.astype(int)
pieces | measures | length | notes | labels | |
---|---|---|---|---|---|
Suite in E Major | 6 | 53 | 221 | 1701 | 350 |
sum | 6 | 53 | 221 | 1701 | 350 |
def summarize_dataset(D):
all_metadata = D.get_metadata()
summary = make_summary(all_metadata)
return make_overview_table(summary.groupby(level=0))
corpus_summary = summarize_dataset(D)
print(corpus_summary.astype(int).to_markdown())
| | pieces | measures | length | notes | labels |
|:----------------|---------:|-----------:|---------:|--------:|---------:|
| handel_keyboard | 6 | 53 | 221 | 1701 | 350 |
| sum | 6 | 53 | 221 | 1701 | 350 |
Measures#
all_measures = D.get_feature("measures")
print(
f"{len(all_measures.index)} measures over {len(all_measures.groupby(level=[0,1]))} files."
)
all_measures.head()
60 measures over 6 files.
mc | mn | quarterbeats | duration_qb | keysig | timesig | act_dur | mc_offset | numbering_offset | dont_count | barline | breaks | repeats | next | volta | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
corpus | piece | i | |||||||||||||||
handel_keyboard | hwv430d_Grobschmied_Aria | 0 | 1 | 1 | 0 | 4.0 | 4 | 4/4 | 1 | 0 | <NA> | <NA> | <NA> | <NA> | firstMeasure | (2,) | <NA> |
1 | 2 | 2 | 4 | 4.0 | 4 | 4/4 | 1 | 0 | <NA> | <NA> | <NA> | line | <NA> | (3,) | <NA> | ||
2 | 3 | 3 | 8 | 4.0 | 4 | 4/4 | 1 | 0 | <NA> | <NA> | <NA> | <NA> | <NA> | (4,) | <NA> | ||
3 | 4 | 4 | 12 | 4.0 | 4 | 4/4 | 1 | 0 | <NA> | <NA> | <NA> | <NA> | <NA> | (5,) | <NA> | ||
4 | 5 | 5 | 16 | 1.0 | 4 | 4/4 | 1/4 | 0 | <NA> | <NA> | double | line | <NA> | (6,) | <NA> |
all_measures.get_default_analysis().plot_grouped()
Harmony labels#
All symbols, independent of the local key (the mode of which changes their semantics).
try:
all_annotations = D.get_feature("harmonylabels").df
except Exception:
all_annotations = pd.DataFrame()
n_annotations = len(all_annotations.index)
includes_annotations = n_annotations > 0
if includes_annotations:
display(all_annotations.head())
print(f"Concatenated annotation tables contains {all_annotations.shape[0]} rows.")
no_chord = all_annotations.root.isna()
if no_chord.sum() > 0:
print(
f"{no_chord.sum()} of them are not chords. Their values are:"
f" {all_annotations.label[no_chord].value_counts(dropna=False).to_dict()}"
)
all_chords = all_annotations[~no_chord].copy()
print(
f"Dataset contains {all_chords.shape[0]} tokens and {len(all_chords.chord.unique())} types over "
f"{len(all_chords.groupby(level=[0,1]))} documents."
)
all_annotations["corpus_name"] = all_annotations.index.get_level_values(0).map(
utils.get_corpus_display_name
)
all_chords["corpus_name"] = all_chords.index.get_level_values(0).map(
utils.get_corpus_display_name
)
else:
print("Dataset contains no annotations.")
mc | mn | quarterbeats | duration_qb | mc_onset | mn_onset | timesig | staff | voice | volta | ... | numeral_or_applied_to_numeral | intervals_over_bass | intervals_over_root | scale_degrees | scale_degrees_and_mode | scale_degrees_major | scale_degrees_minor | globalkey | localkey | chord | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
corpus | piece | i | |||||||||||||||||||||
handel_keyboard | hwv430d_Grobschmied_Aria | 0 | 1 | 1 | 0 | 2.0 | 0 | 0 | 4/4 | 2 | 1 | <NA> | ... | I | (M3, P5) | (M3, P5) | (1, 3, 5) | (1, 3, 5), major | (1, 3, 5) | (1, #3, 5) | E | I | I |
1 | 1 | 1 | 2 | 0.5 | 1/2 | 1/2 | 4/4 | 2 | 1 | <NA> | ... | V | (m3, m6) | (M3, P5) | (7, 2, 5) | (7, 2, 5), major | (7, 2, 5) | (#7, 2, 5) | E | I | V6 | ||
2 | 1 | 1 | 5/2 | 0.5 | 5/8 | 5/8 | 4/4 | 2 | 1 | <NA> | ... | V | (M3, P5) | (M3, P5) | (5, 7, 2) | (5, 7, 2), major | (5, 7, 2) | (5, #7, 2) | E | I | V | ||
3 | 1 | 1 | 3 | 1.0 | 3/4 | 3/4 | 4/4 | 2 | 1 | <NA> | ... | I | (M3, P5) | (M3, P5) | (1, 3, 5) | (1, 3, 5), major | (1, 3, 5) | (1, #3, 5) | E | I | I | ||
4 | 2 | 2 | 4 | 0.5 | 0 | 0 | 4/4 | 2 | 1 | <NA> | ... | V | (M2, P5) | (P4, P5) | (1, 2, 5) | (1, 2, 5), major | (1, 2, 5) | (1, 2, 5) | E | I | V6(4) |
5 rows × 51 columns
Concatenated annotation tables contains 346 rows.
Dataset contains 346 tokens and 44 types over 6 documents.