Perform Neo-Riemann operations on musical chords
Project description
Music Tonnetz-Transform
Perform Neo-Riemann operations on musical chords
DESCRIPTION
This class generates transposed and Neo-Riemann chord progressions.
Calling the generate() and circular() methods returns three lists:
- The generated chord progression (in either the default midi-number or named "ISO" format)
- The transformations used in the generation
- The list of pitch names, comprising the chords that were generated
The generate() method generates a linear series of transformed chords, from beginning to end.
The circular() method generates a circular series of transformed chords. This describes movement around a circular list ("necklace") of chord transformations. Starting at position zero, we move randomly, forward or backward along the necklace, transforming the current chord.
SYNOPSIS
from music_tonnetztransform import Transform
t = Transform( # defaults:
base_note='C', # used to construct the base_chord, if not given
base_octave=4, # "
base_chord=None, # set as a list of midi numbers or named notes
chord_quality='', # '': major, 'm': minor, '7': 7th
format='midinum', # or ISO for names
semitones=7, # transposition semitones
max=4, # number of circular transformations
allowed=None, # [T], [N], [T,N], None
transforms=4, # either a list or a number of computed transformations
verbose=False,
)
generated, transforms, chords = t.generate()
# [[63, 67, 70], [70, 74, 77], [70, 75, 79], [70, 75, 79]],
# ['T3', 'T7', 'RL', 'I'],
# [['Eb', 'G', 'Bb'], ['Bb', 'D', 'F'], ['Bb', 'Eb', 'G'], ['Bb', 'Eb', 'G']])
t = Transform(format="ISO")
generated, transforms, chords = t.generate()
# [['G4', 'B4', 'D5'], ['D4', 'F#4', 'A4'], ['C#4', 'F4', 'G#4'], ['D4', 'F4', 'Bb4']],
# ... as above
t = Transform(format='ISO', transforms=['R','L','P'])
generated = t.generate()[0] # [['C4', 'E4', 'A4'], ['C4', 'F4', 'A4'], ['C4', 'F4', 'G#4']]
t = Transform(transforms=['R','L','P','T2'], max=6)
generated, transforms, chords = t.circular()
MUSICAL EXAMPLES
from music_tonnetztransform import Transform
from music21 import chord, stream
s = stream.Stream()
p = stream.Part()
t = Transform()
generated = t.generate()[0]
for notes in generated:
c = chord.Chord(notes, type='whole')
p.append(c)
s.append(p)
s.show()
from music21 import duration, chord, stream
from music_tonnetztransform import Transform
from random_rhythms import Rhythm
s = stream.Stream()
p = stream.Part()
r = Rhythm(durations=[1, 3/2, 2])
motif = r.motif()
t = Transform(max=len(motif))
generated = t.circular()[0]
for i,dura in enumerate(motif):
c = chord.Chord(generated[i])
c.duration = duration.Duration(dura)
p.append(c)
s.append(p)
s.show()
from music21 import duration, chord, stream
from chord_progression_network import Generator
from music_tonnetztransform import Transform
from random_rhythms import Rhythm
s = stream.Stream()
p = stream.Part()
r = Rhythm(durations=[1, 3/2, 2])
motifs = [ r.motif() for _ in range(3) ]
g = Generator(
net={
1: [3,4,5,6],
2: [4,5,6],
3: [2,4,5,6],
4: [1,5,6],
5: [2,3,4,7],
6: [3,4,5],
7: [3,5],
}
)
for _ in range(2):
for i,motif in enumerate(motifs):
g.max = len(motif) # set the number of chord changes to the number of motifs
g.tonic = i == 0 # only start on the tonic if on the 1st motif
g.resolve = i == len(motif) - 1 # only end with the tonic on the last motif
phrase = g.generate()
for j,dura in enumerate(motif):
c = chord.Chord(phrase[j])
c.duration = duration.Duration(dura)
p.append(c)
t = Transform(
format='ISO', # using named notes
base_chord=phrase[-1], # last chord of the previous phrase
max=len(motifs[0]), # number of durations in the first motif
verbose=True,
)
generated = t.circular()[0]
for i,dura in enumerate(motifs[0]):
c = chord.Chord(generated[i])
c.duration = duration.Duration(dura)
p.append(c)
for motif in motifs + [motifs[0]]: # repeat the motifs
g.max = len(motif)
phrase = g.generate()
for i,dura in enumerate(motif):
c = chord.Chord(phrase[i])
c.duration = duration.Duration(dura)
p.append(c)
s.append(p)
s.show()
SEE ALSO
https://metacpan.org/pod/Music::NeoRiemannianTonnetz
https://en.wikipedia.org/wiki/Neo-Riemannian_theory
https://viva.pressbooks.pub/openmusictheory/chapter/neo-riemannian-triadic-progressions/
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file music_tonnetztransform-0.1.7.tar.gz.
File metadata
- Download URL: music_tonnetztransform-0.1.7.tar.gz
- Upload date:
- Size: 45.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bf85b8e608d615fb042d89dbfb6a7a5613eec9719925294a38d8421c38c5609b
|
|
| MD5 |
c513df0abb059a92a787c30fe87a4bb3
|
|
| BLAKE2b-256 |
4b462baec45ac86ba625f54fcb4bed615f4a5c961b858ed2662cd8b0de5440a4
|
File details
Details for the file music_tonnetztransform-0.1.7-py3-none-any.whl.
File metadata
- Download URL: music_tonnetztransform-0.1.7-py3-none-any.whl
- Upload date:
- Size: 31.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e0a09147a9a26663b152bfe8fd5e1bc8cb3f408bef81ba9752a8ee646fe825bd
|
|
| MD5 |
d3f8ff66402bb1007d14a2f21652cee4
|
|
| BLAKE2b-256 |
61a3812f722236d142c2e5bb51094dae8b0238c5e74c6a4e4b26370b68360e07
|