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compact_sets/compact_sets_optimized_2.ipynb
Michael Winter b89ff9c184 Add hamiltonian weight to favor unvisited nodes 
- Add 'hamiltonian' option to weights config (default True)
- In edge weight calculation: boost unvisited nodes (10x), penalize visited (0.1x)
- Path now extends longer before getting stuck
2026-03-13 01:06:57 +01:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "b5d4c6c9-16d5-433c-bc2b-47a23642123c",
"metadata": {},
"outputs": [],
"source": [
"from itertools import chain, combinations, permutations, product, pairwise\n",
"from math import prod, log\n",
"from copy import deepcopy\n",
"import networkx as nx\n",
"from fractions import Fraction\n",
"import json\n",
"from operator import add\n",
"\n",
"def hs_array_to_fr(hs_array):\n",
" return prod([pow(dims[d], hs_array[d]) for d in range(len(dims))])\n",
"\n",
"def hs_array_to_cents(hs_array):\n",
" return (1200 * log(hs_array_to_fr(hs_array), 2))\n",
"\n",
"def expand_pitch(hs_array):\n",
" expanded_pitch = list(hs_array)\n",
" frequency_ratio = hs_array_to_fr(hs_array)\n",
" if frequency_ratio < 1:\n",
" while frequency_ratio < 1:\n",
" frequency_ratio *= 2\n",
" expanded_pitch[0] += 1\n",
" elif frequency_ratio >= 2:\n",
" while frequency_ratio >= 2:\n",
" frequency_ratio *= 1/2\n",
" expanded_pitch[0] += -1\n",
" return tuple(expanded_pitch)\n",
"\n",
"def expand_chord(chord):\n",
" return tuple(expand_pitch(p) for p in chord)\n",
"\n",
"def collapse_pitch(hs_array):\n",
" collapsed_pitch = list(hs_array)\n",
" collapsed_pitch[0] = 0\n",
" return tuple(collapsed_pitch)\n",
"\n",
"def collapse_chord(chord):\n",
" return tuple(collapse_pitch(p) for p in chord)\n",
"\n",
"def transpose_pitch(pitch, trans):\n",
" return tuple(map(add, pitch, trans))\n",
"\n",
"def transpose_chord(chord, trans):\n",
" return tuple(transpose_pitch(p, trans) for p in chord)\n",
"\n",
"def cent_difference(hs_array1, hs_array2):\n",
" return hs_array_to_cents(hs_array2) - hs_array_to_cents(hs_array1)\n",
"\n",
"def pitch_difference(hs_array1, hs_array2):\n",
" return transpose_pitch(hs_array1, [p * -1 for p in hs_array2])\n",
"\n",
"def edges(chords, min_symdiff, max_symdiff, max_chord_size): \n",
"\n",
" def reverse_movements(movements):\n",
" return {value['destination']:{'destination':key, 'cent_difference':value['cent_difference'] * -1} for key, value in movements.items()}\n",
"\n",
" def is_directly_tunable(intersection, diff):\n",
" # this only works for now when intersection if one element - need to fix that\n",
" return max([sum(abs(p) for p in collapse_pitch(pitch_difference(d, list(intersection)[0]))) for d in diff]) == 1\n",
"\n",
" for combination in combinations(chords, 2):\n",
" [expanded_base, expanded_comp] = [expand_chord(chord) for chord in combination]\n",
" edges = []\n",
" transpositions = set(pitch_difference(pair[0], pair[1]) for pair in set(product(expanded_base, expanded_comp)))\n",
" for trans in transpositions:\n",
" expanded_comp_transposed = transpose_chord(expanded_comp, trans)\n",
" intersection = set(expanded_base) & set(expanded_comp_transposed)\n",
" symdiff_len = sum([len(chord) - len(intersection) for chord in [expanded_base, expanded_comp_transposed]])\n",
" if (min_symdiff <= symdiff_len <= max_symdiff):\n",
" rev_trans = tuple(t * -1 for t in trans)\n",
" [diff1, diff2] = [list(set(chord) - intersection) for chord in [expanded_base, expanded_comp_transposed]]\n",
" base_map = {val: {'destination':transpose_pitch(val, rev_trans), 'cent_difference': 0} for val in intersection}\n",
" base_map_rev = reverse_movements(base_map)\n",
" maps = []\n",
" diff1 += [None] * (max_chord_size - len(diff1) - len(intersection))\n",
" perms = [list(perm) + [None] * (max_chord_size - len(perm) - len(intersection)) for perm in set(permutations(diff2))]\n",
" for p in perms:\n",
" appended_map = {\n",
" diff1[index]:\n",
" {\n",
" 'destination': transpose_pitch(val, rev_trans) if val != None else None, \n",
" 'cent_difference': cent_difference(diff1[index], val) if None not in [diff1[index], val] else None\n",
" } for index, val in enumerate(p)}\n",
" yield (tuple(expanded_base), tuple(expanded_comp), {\n",
" 'transposition': trans,\n",
" 'symmetric_difference': symdiff_len, \n",
" 'is_directly_tunable': is_directly_tunable(intersection, diff2),\n",
" 'movements': base_map | appended_map\n",
" },)\n",
" yield (tuple(expanded_comp), tuple(expanded_base), {\n",
" 'transposition': rev_trans,\n",
" 'symmetric_difference': symdiff_len, \n",
" 'is_directly_tunable': is_directly_tunable(intersection, diff1),\n",
" 'movements': base_map_rev | reverse_movements(appended_map)\n",
" },)\n",
"\n",
"def graph_from_edges(edges):\n",
" g = nx.MultiDiGraph()\n",
" g.add_edges_from(edges)\n",
" return g\n",
"\n",
"def generate_graph(chord_set, min_symdiff, max_symdiff, max_chord_size):\n",
" #chord_set = chords(pitch_set, min_chord_size, max_chord_size)\n",
" edge_set = edges(chord_set, min_symdiff, max_symdiff, max_chord_size)\n",
" res_graph = graph_from_edges(edge_set)\n",
" return res_graph\n",
" \n",
"def compact_sets(root, m1, m2):\n",
" \n",
" def branch(r):\n",
" b = set()\n",
" for d in range(1, len(root)):\n",
" for a in [-1, 1]:\n",
" b.add((*r[:d], r[d] + a, *r[(d + 1):]))\n",
" return b\n",
" \n",
" def grow(c, p, e):\n",
" l = len(c)\n",
" if l >= m1 and l <= m2:\n",
" #yield tuple(sorted(c, key=hs_array_to_fr))\n",
" yield c\n",
" if l < m2:\n",
" e = set(e)\n",
" for b in p:\n",
" if b not in e:\n",
" e.add(b)\n",
" yield from grow((*c, b), p | branch(b), e)\n",
" yield from grow((root,), branch(root), set((root,)))\n",
"\n",
"def display_graph(graph):\n",
" show_graph = nx.Graph(graph)\n",
" pos = nx.draw_spring(show_graph, node_size=5, width=0.1)\n",
" plt.figure(1, figsize=(12,12)) \n",
" nx.draw(show_graph, pos, node_size=5, width=0.1)\n",
" plt.show()\n",
" #plt.savefig('compact_sets.png', dpi=150)\n",
"\n",
"def path_to_chords(path, start_root):\n",
" current_root = start_root\n",
" start_chord = tuple(sorted(path[0][0], key=hs_array_to_fr))\n",
" chords = ((start_chord, start_chord,),)\n",
" for edge in path:\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" current_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, current_root) for pitch in next_ref_chord)\n",
" chords += ((next_ref_chord, next_transposed_chord,),)\n",
" return tuple(chord[1] for chord in chords)\n",
"\n",
"def write_chord_sequence(seq, path):\n",
" file = open(path, \"w+\")\n",
" content = json.dumps(seq)\n",
" content = content.replace(\"[[[\", \"[\\n\\t[[\")\n",
" content = content.replace(\", [[\", \",\\n\\t[[\")\n",
" content = content.replace(\"]]]\", \"]]\\n]\")\n",
" file.write(content)\n",
" file.close()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "5b3f30fe-02b2-4a6c-8cb2-100c7d4d0670",
"metadata": {},
"outputs": [],
"source": [
"from random import choice, choices, seed\n",
"\n",
"# This is for the static version\n",
"def stochastic_hamiltonian(graph, start_root):\n",
" \n",
" def movement_size_weights(edges):\n",
" \n",
" def max_cent_diff(edge):\n",
" res = max([abs(v) for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None])\n",
" return res\n",
" \n",
" def min_cent_diff(edge):\n",
" res = [abs(v) for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None]\n",
" res.remove(0)\n",
" return min(res)\n",
" \n",
" for e in edges:\n",
" yield 1000 if ((max_cent_diff(e) < 200) and (min_cent_diff(e)) > 1) else 0\n",
"\n",
" def hamiltonian_weights(edges):\n",
" for e in edges:\n",
" yield 10 if e[1] not in [path_edge[0] for path_edge in path] else 1 / graph.nodes[e[1]]['count']\n",
" \n",
" def contrary_motion_weights(edges):\n",
"\n",
" def is_contrary(edge):\n",
" cent_diffs = [v for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None]\n",
" cent_diffs.sort()\n",
" return (cent_diffs[0] < 0) and (cent_diffs[1] == 0) and (cent_diffs[2] > 0)\n",
"\n",
" for e in edges:\n",
" yield 10 if is_contrary(e) else 1\n",
" \n",
" def is_directly_tunable_weights(edges):\n",
" for e in edges:\n",
" yield 10 if e[2]['is_directly_tunable'] else 0\n",
"\n",
"\n",
" def is_connected_to(edges, chordrefs):\n",
" \n",
" def is_connected(edge, chordrefs):\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" tmp_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, tmp_root) for pitch in next_ref_chord)\n",
" #return min([min([sum(abs(d) for d in collapse_pitch(pitch_difference(c, p))) for p in next_transposed_chord]) for c in chordrefs]) == 0\n",
" return min([min([sum(abs(d) for d in pitch_difference(c, p)) for p in next_transposed_chord]) for c in chordrefs]) == 0\n",
"\n",
" \n",
" for e in edges:\n",
" yield 10 if is_connected(e, chordrefs) else 0\n",
"\n",
" def voice_crossing_weights(edges):\n",
" \n",
" def has_voice_crossing(edge):\n",
" source = list(edge[0])\n",
" ordered_source = sorted(source, key=hs_array_to_fr) \n",
" source_order = [ordered_source.index(p) for p in source]\n",
" destination = [transpose_pitch(edge[2]['movements'][p]['destination'], edge[2]['transposition']) for p in source]\n",
" ordered_destination = sorted(destination, key=hs_array_to_fr)\n",
" destination_order = [ordered_destination.index(p) for p in destination]\n",
" return source_order != destination_order\n",
"\n",
" for e in edges:\n",
" yield 10 if not has_voice_crossing(e) else 0\n",
"\n",
" def is_bass_rooted(chord):\n",
" return max([sum(abs(p) for p in collapse_pitch(pitch_difference(chord[0], p))) for p in chord[1:]]) == 1\n",
" \n",
" current_root = start_root\n",
" check_graph = graph.copy()\n",
" next_node = choice([node for node in graph.nodes() if is_bass_rooted(node)])\n",
" check_graph.remove_node(next_node)\n",
" start_chord = tuple(sorted(next_node, key=hs_array_to_fr))\n",
" chords = ((start_chord, start_chord,),)\n",
" for node in graph.nodes(data=True):\n",
" node[1]['count'] = 1\n",
" path = []\n",
" index = 0\n",
" pathRefChords = ((0, 0, 0, 0, 0, 0, 0, 0), (-1, 1, 0, 0, 0, 0, 0, 0), (-2, 0, 1, 0, 0, 0, 0, 0), (-2, 0, 0, 1, 0, 0, 0, 0), (-3, 0, 0, 0, 1, 0, 0, 0), (-3, 0, 0, 0, 0, 1, 0, 0))\n",
" while (nx.number_of_nodes(check_graph) > 0) and (len(path) < 50):\n",
" out_edges = list(graph.out_edges(next_node, data=True))\n",
" factors = [\n",
" movement_size_weights(out_edges), \n",
" hamiltonian_weights(out_edges), \n",
" contrary_motion_weights(out_edges), \n",
" is_directly_tunable_weights(out_edges),\n",
" voice_crossing_weights(out_edges),\n",
" #is_sustained_voice_alt(out_edges, 1, current_root)\n",
" is_connected_to(out_edges, (pathRefChords[(len(path) + index) % 6], pathRefChords[(len(path) + index + 1) % 6], pathRefChords[(len(path) + index + 2) % 6]))\n",
" #is_connected_to(out_edges, pathRefChords)\n",
" ]\n",
" index += 1\n",
" weights = [prod(a) for a in zip(*factors)]\n",
" edge = choices(out_edges, weights=weights)[0]\n",
" #edge = random.choice(out_edges)\n",
"\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" current_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, current_root) for pitch in next_ref_chord)\n",
" chords += ((next_ref_chord, next_transposed_chord,),)\n",
" \n",
" next_node = edge[1]\n",
" node[1]['count'] += 1\n",
" path.append(edge)\n",
" if next_node in check_graph.nodes:\n",
" check_graph.remove_node(next_node)\n",
" return tuple(chord[1] for chord in chords)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "96b6ba04-08fe-4ac2-a0cc-1ac9abe47b41",
"metadata": {},
"outputs": [],
"source": [
"dims = (2, 3, 5, 7, 11, 13, 17, 19)\n",
"root = (0, 0, 0, 0, 0, 0, 0, 0)\n",
"chord = (root,)\n",
"chord_set = compact_sets(root, 3, 3)\n",
"#print(len(list(chord_set)))\n",
"graph = generate_graph(chord_set, 4, 4, 3)\n",
"#len(list(chord_set))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "7c90b52a-ebc0-4823-bfb2-ad0a696a4bb8",
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "Total of weights must be greater than zero",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mValueError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[5]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m seed(\u001b[32m8729743\u001b[39m) \n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m path = \u001b[43mstochastic_hamiltonian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgraph\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mroot\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[38;5;66;03m#for edge in path:\u001b[39;00m\n\u001b[32m 4\u001b[39m \u001b[38;5;66;03m# print(edge)\u001b[39;00m\n\u001b[32m 5\u001b[39m write_chord_sequence(path, \u001b[33m\"\u001b[39m\u001b[33msirens.txt\u001b[39m\u001b[33m\"\u001b[39m)\n",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 97\u001b[39m, in \u001b[36mstochastic_hamiltonian\u001b[39m\u001b[34m(graph, start_root)\u001b[39m\n\u001b[32m 95\u001b[39m index += \u001b[32m1\u001b[39m\n\u001b[32m 96\u001b[39m weights = [prod(a) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(*factors)]\n\u001b[32m---> \u001b[39m\u001b[32m97\u001b[39m edge = \u001b[43mchoices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mout_edges\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m=\u001b[49m\u001b[43mweights\u001b[49m\u001b[43m)\u001b[49m[\u001b[32m0\u001b[39m]\n\u001b[32m 98\u001b[39m \u001b[38;5;66;03m#edge = random.choice(out_edges)\u001b[39;00m\n\u001b[32m 100\u001b[39m trans = edge[\u001b[32m2\u001b[39m][\u001b[33m'\u001b[39m\u001b[33mtransposition\u001b[39m\u001b[33m'\u001b[39m]\n",
"\u001b[36mFile \u001b[39m\u001b[32m/usr/lib/python3.13/random.py:487\u001b[39m, in \u001b[36mRandom.choices\u001b[39m\u001b[34m(self, population, weights, cum_weights, k)\u001b[39m\n\u001b[32m 485\u001b[39m total = cum_weights[-\u001b[32m1\u001b[39m] + \u001b[32m0.0\u001b[39m \u001b[38;5;66;03m# convert to float\u001b[39;00m\n\u001b[32m 486\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m total <= \u001b[32m0.0\u001b[39m:\n\u001b[32m--> \u001b[39m\u001b[32m487\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33m'\u001b[39m\u001b[33mTotal of weights must be greater than zero\u001b[39m\u001b[33m'\u001b[39m)\n\u001b[32m 488\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m _isfinite(total):\n\u001b[32m 489\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33m'\u001b[39m\u001b[33mTotal of weights must be finite\u001b[39m\u001b[33m'\u001b[39m)\n",
"\u001b[31mValueError\u001b[39m: Total of weights must be greater than zero"
]
}
],
"source": [
"seed(8729743) \n",
"path = stochastic_hamiltonian(graph, root)\n",
"#for edge in path:\n",
"# print(edge)\n",
"write_chord_sequence(path, \"sirens.txt\")"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "215266dd-643d-4c2b-af7d-a8f8d6875c10",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(list(chord_set))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "29877cb1-c9ae-4e3c-b492-b7e8646fed2d",
"metadata": {},
"outputs": [],
"source": [
"from random import choice, choices, seed\n",
"\n",
"def stochastic_hamiltonian(chord_set, start_root, min_symdiff, max_symdiff, max_chord_size):\n",
" \n",
" def movement_size_weights(edges):\n",
" \n",
" def max_cent_diff(edge):\n",
" res = max([abs(v) for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None])\n",
" return res\n",
" \n",
" def min_cent_diff(edge):\n",
" res = [abs(v) for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None]\n",
" res.remove(0)\n",
" return min(res)\n",
" \n",
" for e in edges:\n",
" if ((max_cent_diff(e) < 100) and (min_cent_diff(e)) >= 0):\n",
" yield 1000\n",
" elif ((max_cent_diff(e) < 200) and (min_cent_diff(e)) >= 0):\n",
" yield 10\n",
" else:\n",
" yield 0\n",
"\n",
" def hamiltonian_weights(edges):\n",
" for e in edges:\n",
" yield 10 if e[1] not in [path_edge[0] for path_edge in path] else 1 #/ graph.nodes[e[1]]['count']\n",
" \n",
" def contrary_motion_weights(edges):\n",
"\n",
" def is_contrary(edge):\n",
" cent_diffs = [v for val in edge[2]['movements'].values() if (v:=val['cent_difference']) is not None]\n",
" cent_diffs.sort()\n",
" return (cent_diffs[0] < 0) and (cent_diffs[1] == 0) and (cent_diffs[2] > 0)\n",
" #return (cent_diffs[0] < 0) and (cent_diffs[1] == 0) and (cent_diffs[2] == 0) and (cent_diffs[3] > 0)\n",
"\n",
" for e in edges:\n",
" yield 100 if is_contrary(e) else 0\n",
" \n",
" def is_directly_tunable_weights(edges):\n",
" for e in edges:\n",
" yield 10 if e[2]['is_directly_tunable'] else 0\n",
"\n",
" def transposition_weight(edges):\n",
" for e in edges:\n",
" yield 1000 if 0 <= hs_array_to_cents(e[2]['transposition']) < 100 else 0\n",
"\n",
" def is_sustained_voice(edges, voice):\n",
" \n",
" def is_sustained(edge):\n",
" source = list(edge[0])\n",
" ordered_source = sorted(source, key=hs_array_to_fr) \n",
" destination = [transpose_pitch(edge[2]['movements'][p]['destination'], edge[2]['transposition']) for p in source]\n",
" ordered_destination = sorted(destination, key=hs_array_to_fr)\n",
" return ordered_source[voice] == ordered_destination[voice]\n",
"\n",
" for e in edges:\n",
" yield 10 if is_sustained(e) else 0\n",
"\n",
" def is_sustained_voice_alt(edges, voice, current_root):\n",
" \n",
" def is_sustained(edge):\n",
"\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" tmp_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, tmp_root) for pitch in next_ref_chord)\n",
" return chords[-1][1][voice] == next_transposed_chord[voice]\n",
"\n",
" for e in edges:\n",
" yield 10 if is_sustained(e) else 1\n",
"\n",
" def is_connected_to(edges, chordrefs):\n",
" \n",
" def is_connected(edge, chordrefs):\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" tmp_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, tmp_root) for pitch in next_ref_chord)\n",
" #return min([min([sum(abs(d) for d in collapse_pitch(pitch_difference(c, p))) for p in next_transposed_chord]) for c in chordrefs]) == 0\n",
" return min([min([sum(abs(d) for d in pitch_difference(c, p)) for p in next_transposed_chord]) for c in chordrefs]) == 0\n",
"\n",
" \n",
" for e in edges:\n",
" yield 10 if is_connected(e, chordrefs) else 0\n",
"\n",
" def voice_crossing_weights(edges):\n",
" \n",
" def has_voice_crossing(edge):\n",
" source = list(edge[0])\n",
" ordered_source = sorted(source, key=hs_array_to_fr) \n",
" source_order = [ordered_source.index(p) for p in source]\n",
" destination = [transpose_pitch(edge[2]['movements'][p]['destination'], edge[2]['transposition']) for p in source]\n",
" ordered_destination = sorted(destination, key=hs_array_to_fr)\n",
" destination_order = [ordered_destination.index(p) for p in destination]\n",
" return source_order != destination_order\n",
"\n",
" for e in edges:\n",
" yield 10 if not has_voice_crossing(e) else 0\n",
"\n",
" def dca_weight(edges, last_chords):\n",
" for edge in edges:\n",
" source = list(edge[0])\n",
" ordered_source = sorted(source, key=hs_array_to_fr) \n",
" source_order = [ordered_source.index(p) for p in source]\n",
" destination = [transpose_pitch(edge[2]['movements'][p]['destination'], edge[2]['transposition']) for p in source]\n",
" ordered_destination = tuple(sorted(destination, key=hs_array_to_fr))\n",
" test_sequence = tuple(zip(*(last_chords + (ordered_destination, ))))\n",
" #print('here')\n",
" #print(test_sequence)\n",
" if len(test_sequence[0]) < 4:\n",
" yield 10\n",
" else:\n",
" if len(set(test_sequence[0][-2:])) == 1 or len(set(test_sequence[1][-2:])) == 1 or len(set(test_sequence[2][-2:])) == 1:\n",
" yield 0\n",
" else:\n",
" yield 10\n",
"\n",
" def is_bass_rooted(chord):\n",
" return max([sum(abs(p) for p in collapse_pitch(pitch_difference(chord[0], p))) for p in chord[1:]]) == 1\n",
"\n",
" def is_directly_tunable(intersection, diff):\n",
" # this only works for now when intersection if one element - need to fix that\n",
" return max([sum(abs(p) for p in collapse_pitch(pitch_difference(d, list(intersection)[0]))) for d in diff]) == 1\n",
"\n",
" def gen_edges(source, candidates, min_symdiff, max_symdiff, max_chord_size, ostinato_ref):\n",
" for target in candidates:\n",
" [expanded_source, expanded_target] = [expand_chord(chord) for chord in [source, target]]\n",
" edges = []\n",
" expanded_source_with_ostinato_ref = expanded_source + ostinato_ref\n",
" #print(expanded_source + ostinato_ref)\n",
" transpositions = set(pitch_difference(pair[0], pair[1]) for pair in set(product(expanded_source, expanded_target)))\n",
" #print(transpositions)\n",
" for trans in transpositions:\n",
" expanded_target_transposed = transpose_chord(expanded_target, trans)\n",
" intersection = set(expanded_source) & set(expanded_target_transposed)\n",
" symdiff_len = sum([len(chord) - len(intersection) for chord in [expanded_source, expanded_target_transposed]])\n",
" if (min_symdiff <= symdiff_len <= max_symdiff):\n",
" rev_trans = tuple(t * -1 for t in trans)\n",
" [diff1, diff2] = [list(set(chord) - intersection) for chord in [expanded_source, expanded_target_transposed]]\n",
" base_map = {val: {'destination':transpose_pitch(val, rev_trans), 'cent_difference': 0} for val in intersection}\n",
" #base_map_rev = reverse_movements(base_map)\n",
" maps = []\n",
" diff1 += [None] * (max_chord_size - len(diff1) - len(intersection))\n",
" perms = [list(perm) + [None] * (max_chord_size - len(perm) - len(intersection)) for perm in set(permutations(diff2))]\n",
" for p in perms:\n",
" appended_map = {\n",
" diff1[index]:\n",
" {\n",
" 'destination': transpose_pitch(val, rev_trans) if val != None else None, \n",
" 'cent_difference': cent_difference(diff1[index], val) if None not in [diff1[index], val] else None\n",
" } for index, val in enumerate(p)}\n",
" yield (tuple(expanded_source), tuple(expanded_target), {\n",
" 'transposition': trans,\n",
" 'symmetric_difference': symdiff_len, \n",
" 'is_directly_tunable': is_directly_tunable(intersection, diff2),\n",
" 'movements': base_map | appended_map\n",
" },)\n",
"\n",
" current_root = start_root\n",
" #weighted_chord_set = {\n",
" # chord:\n",
" # {\n",
" # 'weight': 10\n",
" # } for index, chord in enumerate(chord_set)}\n",
" next_chord = tuple(sorted(expand_chord(choice(chord_set)), key=hs_array_to_fr))\n",
" #tuple(sorted(next_node, key=hs_array_to_fr))\n",
" print(next_chord)\n",
" #weighted_chord_set[next_chord]['weight'] = 1;\n",
" chords = ((next_chord, next_chord,),)\n",
" last_chords = (next_chord,)\n",
" path = []\n",
" index = 0\n",
" pathRefChords = ((0, 0, 0, 0, 0, 0, 0), (-2, 0, 1, 0, 0, 0, 0), (-3, 0, 0, 0, 1, 0, 0), (-1, 1, 0, 0, 0, 0, 0), (-3, 0, 0, 0, 0, 1, 0), (-2, 0, 0, 1, 0, 0, 0))\n",
" #pathRefChords = ((0, 0, 0, 0, 0, 0), (-1, 1, 0, 0, 0, 0), (-2, 0, 1, 0, 0, 0), (-2, 0, 0, 1, 0, 0), (-3, 0, 0, 0, 1, 0), (-3, 0, 0, 0, 0, 1))\n",
" while (len(path) < 100):\n",
" ostinato_ref = (pathRefChords[len(path)%6],)\n",
" edges = list(gen_edges(next_chord, chord_set, min_symdiff, max_symdiff, max_chord_size, ostinato_ref))\n",
" #print(edges)\n",
" factors = [\n",
" movement_size_weights(edges), \n",
" hamiltonian_weights(edges), \n",
" #contrary_motion_weights(edges), \n",
" is_directly_tunable_weights(edges),\n",
" voice_crossing_weights(edges),\n",
" #dca_weight(edges, last_chords),\n",
" is_sustained_voice_alt(edges, choice([0, 1, 2]), current_root),\n",
" #is_connected_to(edges, (pathRefChords[len(path)%6],))\n",
" #is_connected_to(edges, (pathRefChords[(len(path) + index) % 6], pathRefChords[(len(path) + index + 1) % 6], pathRefChords[(len(path) + index + 2) % 6]))\n",
" #is_connected_to(edges, pathRefChords)\n",
" ]\n",
" index += 1\n",
" weights = [prod(a) for a in zip(*factors)]\n",
" edge = choices(edges, weights=weights)[0]\n",
" #edge = random.choice(out_edges)\n",
" #print(edge)\n",
"\n",
" trans = edge[2]['transposition']\n",
" movements = edge[2]['movements']\n",
" current_root = transpose_pitch(current_root, trans)\n",
" current_ref_chord = chords[-1][0]\n",
" next_ref_chord = tuple(movements[pitch]['destination'] for pitch in current_ref_chord)\n",
" next_transposed_chord = tuple(transpose_pitch(pitch, current_root) for pitch in next_ref_chord)\n",
" chords += ((next_ref_chord, next_transposed_chord,),)\n",
" \n",
" next_chord = edge[1]\n",
" #node[1]['count'] += 1\n",
"\n",
" last_chords = last_chords + (next_chord,)\n",
" if len(last_chords) > 2:\n",
" last_chords = last_chords[-2:]\n",
" #print(last_chords)\n",
" \n",
" path.append(edge)\n",
" #if next_node in check_graph.nodes:\n",
" # check_graph.remove_node(next_node)\n",
" return tuple(chord[1] for chord in chords)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "84095118-af45-49c8-8b5c-6b51d9432edc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"((0, 0, 0, 0, 0, 0, 0), (-2, 0, 1, 0, 0, 0, 0), (-3, 1, 1, 0, 0, 0, 0))\n"
]
}
],
"source": [
"seed(872984353450043) \n",
"dims = (2, 3, 5, 7, 11, 13, 17)\n",
"root = (0, 0, 0, 0, 0, 0, 0)\n",
"chord = (root,)\n",
"chord_set = compact_sets(root, 3, 3)\n",
"path = stochastic_hamiltonian(list(chord_set), root, 4, 4, 3)\n",
"#for edge in path:\n",
"# print(edge)\n",
"write_chord_sequence(path, \"sirens.txt\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "1123dc10-17a4-449f-bb97-d959b1a2ee0c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"((0, 0, 0, 0), (4, -1, -1, 0), (7, -1, -1, -1), (6, -2, -1, 0), (3, 0, -1, 0))\n"
]
}
],
"source": [
"seed(872984353450043) \n",
"dims = (2, 3, 5, 7)\n",
"root = (0, 0, 0, 0)\n",
"chord = (root,)\n",
"chord_set = compact_sets(root, 5, 5)\n",
"path = stochastic_hamiltonian(list(chord_set), root, 4, 4, 5)\n",
"#for edge in path:\n",
"# print(edge)\n",
"write_chord_sequence(path, \"sirens.txt\")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "e16fc2f3-d8f4-4d70-9f33-403f9639f4df",
"metadata": {},
"source": [
"dims = (2, 3, 5, 7, 11, 13, 17)\n",
"root = (0, 0, 0, 0, 0, 0, 0)\n",
"chord = (root,)\n",
"chord_set = compact_sets(root, 3, 3)\n",
"#print(len(list(chord_set)))\n",
"reduced_chord_set = tuple()\n",
"for chord in chord_set:\n",
" c_flag = False\n",
" for p1, p2 in combinations(collapse_chord(chord), 2):\n",
" diff = pitch_difference(p1, p2)\n",
" print(diff)\n",
" if diff in ((0, 1, 0, 0, 0, 0, 0), (0, 0, 1, 0, 0, 0, 0), (0, 0, 0, 1, 0, 0, 0), (0, -1, 0, 0, 0, 0, 0), (0, 0, -1, 0, 0, 0, 0), (0, 0, 0, -1, 0, 0, 0)) and not c_flag:\n",
" #if (abs(p1[1] - p2[1]) == 1 or abs(p1[2] - p2[2]) == 1 or abs(p1[3] - p2[3]) == 1) and not c_flag:\n",
" c_flag = True\n",
" #break\n",
" if c_flag:\n",
" reduced_chord_set += (chord,)\n",
" \n",
"\n",
"len(reduced_chord_set)\n",
"\n",
"pitch_difference("
]
}
],
"metadata": {
"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": "3.14.3"
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},
"nbformat": 4,
"nbformat_minor": 5
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