diff --git a/Notebooks/Baseline - Guichaoua - database.ipynb b/Notebooks/Baseline - Guichaoua - database.ipynb
deleted file mode 100644
index ee2a2b7a55b39f4974a662c9ae005f3086dc894f..0000000000000000000000000000000000000000
--- a/Notebooks/Baseline - Guichaoua - database.ipynb
+++ /dev/null
@@ -1,565 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T16:52:48.152364Z",
- "start_time": "2021-01-21T16:52:46.526078Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T16:52:48.162337Z",
- "start_time": "2021-01-21T16:52:48.154360Z"
- }
- },
- "outputs": [],
- "source": [
- "# Subset \n",
- "#database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\subset_analysis\\\\\"\n",
- "\n",
- "# Database\n",
- "database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\final_bimbot_al\\\\\"\n",
- "\n",
- "max_size = 10\n",
- "\n",
- "manual = []\n",
- "\n",
- "for file in os.listdir(database_path):\n",
- " bag_of_words = file.split(\".\")\n",
- " if bag_of_words[-1] == \"seq\":\n",
- " if bag_of_words[-3] == \"manual\":\n",
- " manual.append(file)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# My Code"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Direct antecedents"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T16:54:17.981841Z",
- "start_time": "2021-01-21T16:52:48.165331Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Prec: 0.2166, rap: 0.789, F measure: 0.3394\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1080x360 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "persisted_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\data_persisted\"\n",
- "flow_folder = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "\n",
- "all_res = []\n",
- "all_res_one = []\n",
- "distrib_segments = []\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " with open(\"{}\\\\{}.flow_simple\".format(flow_folder, song_number),'r') as obj:\n",
- " bag_of_chords = obj.read().split(\"\\n\")\n",
- " while '' in bag_of_chords:\n",
- " bag_of_chords.remove('')\n",
- " \"\"\"bag_of_chords = dm.flowify_song(database_path + song)\n",
- " for couple in zip(bag_of_chords, a):\n",
- " if couple[0].triad != couple[1]:\n",
- " print(couple)\"\"\"\n",
- "\n",
- " frontiers, _ = algos.dynamic_minimization_guichaoua(bag_of_chords, \n",
- " positive_segment_size_penalty = 0, negative_segment_size_penalty = 0.125, \n",
- " min_size = 8, max_size = max_size, target_size = 32, \n",
- " positive_penalty = 2.25, negative_penalty = 3,\n",
- " global_antecedents = False)\n",
- "\n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " distrib_segments.append(snd - fst)\n",
- "\n",
- " \"\"\"\n",
- " # Scores, computed on time\n",
- " song_number = song.split(\".\")[0]\n",
- " this_song_ann = dm.get_annotation_name_from_song(song_number, \"MIREX10\")\n",
- " annotation_path = \"{}\\\\{}\".format(annotations_folder_path, this_song_ann)\n",
- " annotations = dm.get_segmentation_from_txt(annotation_path, \"MIREX10\")\n",
- " references_segments = np.array(annotations)[:, 0:2]\n",
- " beats = np.load(\"{}\\\\beats\\\\{}.npy\".format(persisted_path, int(song_number)), allow_pickle=True) \n",
- "\n",
- " estimation = []\n",
- " for f in frontiers:\n",
- " if f < len(beats):\n",
- " estimation.append(beats[f])\n",
- " else:\n",
- " estimation.append(beats[-1])\n",
- " estimated_seg = dm.frontiers_to_segments(estimation)\n",
- "\n",
- " prec, rec, fmes = dm.compute_score_of_segmentation(references_segments, estimated_seg, window_length = 0.5)\"\"\"\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " song_number = song.split(\".\")[0]\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " p, r, f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, window_length = 0.5)\n",
- " all_res.append([p, r, f])\n",
- "\n",
- "results = np.array(all_res)\n",
- "prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- "print(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Global antecedents"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T16:55:39.626755Z",
- "start_time": "2021-01-21T16:54:17.988820Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Prec: 0.2166, rap: 0.789, F measure: 0.3394\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1080x360 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "persisted_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\data_persisted\"\n",
- "flow_folder = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "\n",
- "all_res = []\n",
- "all_res_one = []\n",
- "distrib_segments = []\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " with open(\"{}\\\\{}.flow_simple\".format(flow_folder, song_number),'r') as obj:\n",
- " bag_of_chords = obj.read().split(\"\\n\")\n",
- " while '' in bag_of_chords:\n",
- " bag_of_chords.remove('')\n",
- " \"\"\"bag_of_chords = dm.flowify_song(database_path + song)\n",
- " for couple in zip(bag_of_chords, a):\n",
- " if couple[0].triad != couple[1]:\n",
- " print(couple)\"\"\"\n",
- "\n",
- " frontiers, _ = algos.dynamic_minimization_guichaoua(bag_of_chords, \n",
- " positive_segment_size_penalty = 0, negative_segment_size_penalty = 0.125, \n",
- " min_size = 8, max_size = max_size, target_size = 32, \n",
- " positive_penalty = 2.25, negative_penalty = 3,\n",
- " global_antecedents = True)\n",
- "\n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " distrib_segments.append(snd - fst)\n",
- "\n",
- " \"\"\"\n",
- " # Scores, computed on time\n",
- " song_number = song.split(\".\")[0]\n",
- " this_song_ann = dm.get_annotation_name_from_song(song_number, \"MIREX10\")\n",
- " annotation_path = \"{}\\\\{}\".format(annotations_folder_path, this_song_ann)\n",
- " annotations = dm.get_segmentation_from_txt(annotation_path, \"MIREX10\")\n",
- " references_segments = np.array(annotations)[:, 0:2]\n",
- " beats = np.load(\"{}\\\\beats\\\\{}.npy\".format(persisted_path, int(song_number)), allow_pickle=True) \n",
- "\n",
- " estimation = []\n",
- " for f in frontiers:\n",
- " if f < len(beats):\n",
- " estimation.append(beats[f])\n",
- " else:\n",
- " estimation.append(beats[-1])\n",
- " estimated_seg = dm.frontiers_to_segments(estimation)\n",
- "\n",
- " prec, rec, fmes = dm.compute_score_of_segmentation(references_segments, estimated_seg, window_length = 0.5)\"\"\"\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " song_number = song.split(\".\")[0]\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " p, r, f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, window_length = 0.5)\n",
- " all_res.append([p, r, f])\n",
- "\n",
- "results = np.array(all_res)\n",
- "prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- "print(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Auto DB"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:02:50.877186Z",
- "start_time": "2021-01-21T17:02:50.870179Z"
- }
- },
- "outputs": [],
- "source": [
- "# Subset \n",
- "#database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\subset_analysis\\\\\"\n",
- "\n",
- "# Database\n",
- "database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\final_bimbot_al\\\\\"\n",
- "\n",
- "max_size = 10\n",
- "\n",
- "auto = []\n",
- "\n",
- "for file in os.listdir(database_path):\n",
- " bag_of_words = file.split(\".\")\n",
- " if bag_of_words[-1] == \"seq\":\n",
- " if bag_of_words[-3] == \"auto\":\n",
- " auto.append(file)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:02:57.745449Z",
- "start_time": "2021-01-21T17:02:51.072639Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "001.auto.simple.seq\n",
- "002.auto.simple.seq\n",
- "003.auto.simple.seq\n",
- "004.auto.simple.seq\n",
- "005.auto.simple.seq\n",
- "006.auto.simple.seq\n",
- "007.auto.simple.seq\n",
- "008.auto.simple.seq\n",
- "009.auto.simple.seq\n"
- ]
- },
- {
- "ename": "InvalidChordNotesException",
- "evalue": "Empty list of notes: a Chord must admit notes.",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mInvalidChordNotesException\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-8-13a94a056f18>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0msong\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mauto\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msong\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[0mauto_bag_of_chords\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflowify_song\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdatabase_path\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0msong\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m auto_frontiers, _ = algos.dynamic_minimization_guichaoua(auto_bag_of_chords, \n",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\data_manipulation.py\u001b[0m in \u001b[0;36mflowify_song\u001b[1;34m(path)\u001b[0m\n\u001b[0;32m 471\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mchords\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 472\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m\"N\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 473\u001b[1;33m \u001b[0mbag_of_chords\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mChord\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 474\u001b[0m \u001b[1;32mbreak\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 475\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mbag_of_chords\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, a_chord, redundancy)\u001b[0m\n\u001b[0;32m 71\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_notes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlocal_notes\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 72\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_notes\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 73\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidChordNotesException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Empty list of notes: a Chord must admit notes.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 74\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_triad\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtriad_from_notes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 75\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtriad\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mcst\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAMBIGUOUS\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# A redundant chord shouldn't be reordered as it corresponds to permutated chord (#TODO: rename the parameter ?)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mInvalidChordNotesException\u001b[0m: Empty list of notes: a Chord must admit notes."
- ]
- }
- ],
- "source": [
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "persisted_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\data_persisted\"\n",
- "auto_res = []\n",
- "auto_distrib_segments = []\n",
- "\n",
- "for song in auto:\n",
- " print(song)\n",
- " auto_bag_of_chords = dm.flowify_song(database_path + song)\n",
- "\n",
- " auto_frontiers, _ = algos.dynamic_minimization_guichaoua(auto_bag_of_chords, \n",
- " positive_segment_size_penalty = 0, negative_segment_size_penalty = 0.125, \n",
- " min_size = 8, max_size = max_size, target_size = 32, \n",
- " positive_penalty = 2.25, negative_penalty = 3)\n",
- "\n",
- " for fst, snd in zip(auto_frontiers[:-1], auto_frontiers[1:]):\n",
- " auto_distrib_segments.append(snd - fst)\n",
- "\n",
- " \"\"\"\n",
- " # Scores, computed on time\n",
- " song_number = song.split(\".\")[0]\n",
- " this_song_ann = dm.get_annotation_name_from_song(song_number, \"MIREX10\")\n",
- " annotation_path = \"{}\\\\{}\".format(annotations_folder_path, this_song_ann)\n",
- " annotations = dm.get_segmentation_from_txt(annotation_path, \"MIREX10\")\n",
- " references_segments = np.array(annotations)[:, 0:2]\n",
- " beats = np.load(\"{}\\\\beats\\\\{}.npy\".format(persisted_path, int(song_number)), allow_pickle=True) \n",
- "\n",
- " estimation = []\n",
- " for f in frontiers:\n",
- " if f < len(beats):\n",
- " estimation.append(beats[f])\n",
- " else:\n",
- " estimation.append(beats[-1])\n",
- " estimated_seg = dm.frontiers_to_segments(estimation)\n",
- "\n",
- " prec, rec, fmes = dm.compute_score_of_segmentation(references_segments, estimated_seg, window_length = 0.5)\"\"\"\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " auto_beat_indexed_segments = dm.frontiers_to_segments(auto_frontiers)\n",
- "\n",
- " song_number = song.split(\".\")[0]\n",
- " annot_name = \"{:03d}.auto.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation if x !=''])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " p, r, f = dm.compute_score_of_segmentation(beat_indexed_annotation, auto_beat_indexed_segments, window_length = 0.5)\n",
- " auto_res.append([p, r, f])\n",
- "\n",
- "results = np.array(auto_res)\n",
- "prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- "print(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(auto_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# His outputs"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:02:49.838365Z",
- "start_time": "2021-01-21T16:52:46.524Z"
- }
- },
- "outputs": [],
- "source": [
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "all_res = []\n",
- "g_distrib_segments = []\n",
- "for song in manual:\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- " song_number = song.split(\".\")[0]\n",
- " guichaoua_estimates = open(flow_file_path + \"Guichaoua Estimates\\\\Experiments\\\\{:03d}_0penalties.frontiers_estimated\".format(int(song_number)), \"r\")\n",
- " tab = guichaoua_estimates.read().split(\" \")\n",
- " guichaoua_frontiers = [int(i) - 1 for i in tab if i != \"\\n\"]\n",
- " if guichaoua_frontiers[-1] < len(bag_of_chords)-1:\n",
- " guichaoua_frontiers.append(len(bag_of_chords)-1)\n",
- " \n",
- " for fst, snd in zip(guichaoua_frontiers[:-1], guichaoua_frontiers[1:]):\n",
- " g_distrib_segments.append(snd - fst)\n",
- "\n",
- " beat_indexed_segments = dm.frontiers_to_segments(guichaoua_frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " p, r, f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, window_length = 0.2)\n",
- " all_res.append([p, r, f])\n",
- "\n",
- "results = np.array(all_res)\n",
- "prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- "print(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(g_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Baseline - Guichaoua - on song.ipynb b/Notebooks/Baseline - Guichaoua - on song.ipynb
deleted file mode 100644
index 1ae901c3c7155773bc2fde4d92afd853b388e369..0000000000000000000000000000000000000000
--- a/Notebooks/Baseline - Guichaoua - on song.ipynb
+++ /dev/null
@@ -1,439 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:24:43.535284Z",
- "start_time": "2021-01-21T17:24:42.354227Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.segmentation_helper as sh\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:24:43.541244Z",
- "start_time": "2021-01-21T17:24:43.536292Z"
- }
- },
- "outputs": [],
- "source": [
- "# Hyperparams\n",
- "max_size = 47\n",
- "min_size = 8\n",
- "positive_segment_size_penalty = 0\n",
- "negative_segment_size_penalty = 0.125\n",
- "target_size = 32\n",
- "positive_penalty = 2.25\n",
- "negative_penalty = 3"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# On a song"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:24:43.550219Z",
- "start_time": "2021-01-21T17:24:43.544234Z"
- }
- },
- "outputs": [],
- "source": [
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "song = \"001\"\n",
- "bag_of_chords = []\n",
- "file = open(flow_file_path + song + \".flow\", \"r\") \n",
- "for chord in file.readlines():\n",
- " bag_of_chords.append(chord.split(\"\\n\")[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:36.388412Z",
- "start_time": "2021-01-21T17:24:43.552214Z"
- }
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\segmentation_algorithms.py:398: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "My frontiers: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "My frontiers, but global: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "Cost: 113.25, and global: 113.25\n",
- "Guichaoua's frontiers: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "Equality ? True\n",
- "\n"
- ]
- }
- ],
- "source": [
- "frontiers_global, cost_global = algos.dynamic_minimization_guichaoua(bag_of_chords, global_antecedents = True)\n",
- "frontiers, cost = algos.dynamic_minimization_guichaoua(bag_of_chords, global_antecedents = False)\n",
- "\n",
- "print(\"My frontiers: {}\".format(frontiers))\n",
- "print(\"My frontiers, but global: {}\".format(frontiers_global))\n",
- "print(\"Cost: {}, and global: {}\".format(cost, cost_global))\n",
- "\n",
- "guichaoua_estimates = open(flow_file_path + \"Guichaoua Estimates\\\\Experiments\\\\\" + song + \".frontiers_estimated\", \"r\")\n",
- "tab = guichaoua_estimates.read().split(\" \")\n",
- "guichaoua_frontiers = [int(i) - 1 for i in tab if i != \"\\n\"]\n",
- "guichaoua_frontiers.append(frontiers[-1])\n",
- "print(\"Guichaoua's frontiers: {}\".format(guichaoua_frontiers))\n",
- "print(\"Equality ? {}\\n\".format(guichaoua_frontiers == frontiers))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:36.398384Z",
- "start_time": "2021-01-21T17:29:36.391403Z"
- }
- },
- "outputs": [],
- "source": [
- "string = \"\"\n",
- "for i in frontiers:\n",
- " string += str(i + 1) + \" \"\n",
- "file = open(flow_file_path + \"Marmoret Estimates\\\\\" + song + \".frontiers_estimated\", \"w\")\n",
- "file.write(string)\n",
- "file.close()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:53.555232Z",
- "start_time": "2021-01-21T17:29:36.401377Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 7.75 at (0, 20)\n",
- "Cost: 6 at (20, 52)\n",
- "Cost: 5 at (52, 84)\n",
- "Cost: 8.5 at (84, 112)\n",
- "Cost: 4 at (112, 144)\n",
- "Cost: 6 at (144, 176)\n",
- "Cost: 7.0 at (176, 192)\n",
- "Cost: 8.5 at (192, 220)\n",
- "Cost: 4 at (220, 252)\n",
- "Cost: 6 at (252, 284)\n",
- "Cost: 6.0 at (284, 292)\n",
- "Cost: 13.25 at (292, 332)\n",
- "Cost: 7 at (332, 364)\n",
- "Cost: 6 at (364, 396)\n",
- "Cost: 8 at (396, 428)\n",
- "Cost: 10.25 at (428, 462)\n",
- "Ze sum:113.25\n"
- ]
- }
- ],
- "source": [
- "#frontiers = [0, 20,52,84,112,144,176,192,220,252,284, 292, 332,364,396, 428, 462]\n",
- "the_sum = 0\n",
- "for start, end in zip(frontiers[:-1], frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " #print(segment)\n",
- " size = len(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_global_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " cost = pc.guichaoua_cost_global_antecedents_successors(segment, a_pattern[0], a_pattern[3], a_pattern[4], a_pattern[5])\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " #print(best_pattern)\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " #print(pm.recursive_chords_on_pattern(best_pattern[0],segment))\n",
- " print(\"Cost: {} at {}\".format(the_min, (start, end)))#, pm.recursive_chords_on_pattern(best_pattern[0],segment)))\n",
- " #print(\"local_cost: {}\\n\".format(local_costs[end - 1]))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:54.956883Z",
- "start_time": "2021-01-21T17:29:53.560219Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'Eb', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ab', 'Ebm', 'Ebm', 'Ebm', 'Ebm']\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['Abm', 'Abm'], ['E', 'Eb']]], [[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [[('Ebm', 'Ebm'), ('Ebm', 'Ab')], [('Ebm', 'Ebm'), ('Ebm', 'Ebm')]]]]]\n",
- "Cost: 15\n"
- ]
- }
- ],
- "source": [
- "segment = bag_of_chords[268:304]\n",
- "print(segment)\n",
- "size = len(segment)\n",
- "bag_of_patterns = sh.compute_patterns_with_global_antecedents_for_size(size)\n",
- "the_min = math.inf\n",
- "best_pattern = None\n",
- "for a_pattern in bag_of_patterns[0:1]:\n",
- " cost = pc.guichaoua_cost_global_antecedents_successors(segment, a_pattern[0], a_pattern[3], a_pattern[4], a_pattern[5])\n",
- " #cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- "print(pf.apply_chords_on_pattern(best_pattern[0],segment))\n",
- "print(\"Cost: {}\".format(cost))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:30:04.595293Z",
- "start_time": "2021-01-21T17:29:54.960875Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 7.75 at (0, 20)\n",
- "Cost: 6 at (20, 52)\n",
- "Cost: 5 at (52, 84)\n",
- "Cost: 8.5 at (84, 112)\n",
- "Cost: 4 at (112, 144)\n",
- "Cost: 6 at (144, 176)\n",
- "Cost: 7.0 at (176, 192)\n",
- "Cost: 8.5 at (192, 220)\n",
- "Cost: 4 at (220, 252)\n",
- "Cost: 6 at (252, 284)\n",
- "Cost: 6.0 at (284, 292)\n",
- "Cost: 13.25 at (292, 332)\n",
- "Cost: 7 at (332, 364)\n",
- "Cost: 6 at (364, 396)\n",
- "Cost: 8 at (396, 428)\n",
- "Cost: 10.25 at (428, 462)\n",
- "Ze sum:113.25\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(guichaoua_frontiers[:-1], guichaoua_frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " size = len(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " cost = pc.guichaoua_cost(segment, a_pattern[0], a_pattern[3], a_pattern[4], a_pattern[5])\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " #print(pm.recursive_chords_on_pattern(best_pattern[0],segment))\n",
- " print(\"Cost: {} at {}\".format(the_min, (start, end)))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:30:04.926356Z",
- "start_time": "2021-01-21T17:30:04.597287Z"
- },
- "scrolled": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[[('E', 'E'), ('E', 'E')], [('F#', 'F#'), ('Eb', 'Eb')]], [[('Abm', 'Abm'), ('Abm', 'Abm')], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 10\n",
- "Cost irreg': 12.25\n",
- "Cost penalty: 12.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [[('Abm', 'Abm'), ('Abm', 'Abm')], [('E', 'E'), ('E', 'E')]]], [[['F#', 'F#'], ['Eb', 'Eb']], [[('Abm', 'Abm'), ('Abm', 'Abm')], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 11\n",
- "Cost irreg': 13.25\n",
- "Cost penalty: 13.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], [('Eb', 'Eb'), ('Abm', 'Abm')]], [['Abm', 'Abm'], [('E', 'E'), ('E', 'E')]]], [[['F#', 'F#'], [('Eb', 'Eb'), ('Abm', 'Abm')]], [['Abm', 'Abm'], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 14\n",
- "Cost irreg': 16.25\n",
- "Cost penalty: 16.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', ('Eb', 'Eb')], ['Eb', ('Abm', 'Abm')]], [['Abm', ('Abm', 'E')], ['E', ('E', 'E')]]], [[['F#', ('F#', 'Eb')], ['Eb', ('Abm', 'Abm')]], [['Abm', ('Abm', 'Abm')], ['Abm', ('E', 'Eb')]]]]]\n",
- "Cost: 19\n",
- "Cost irreg': 21.25\n",
- "Cost penalty: 21.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [[('B', 'B'), ('B', 'B')], [('Eb', 'Eb'), ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#'], ['Eb', 'Eb']], [[('Abm', 'Abm'), ('Abm', 'Abm')], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 13\n",
- "Cost irreg': 15.25\n",
- "Cost penalty: 15.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], [('E', 'E'), ('B', 'B')]], [['B', 'B'], [('Eb', 'Eb'), ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#'], [('Eb', 'Eb'), ('Abm', 'Abm')]], [['Abm', 'Abm'], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 16\n",
- "Cost irreg': 18.25\n",
- "Cost penalty: 18.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', ('E', 'E')], ['E', ('B', 'B')]], [['B', ('B', 'Eb')], ['Eb', ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', ('F#', 'Eb')], ['Eb', ('Abm', 'Abm')]], [['Abm', ('Abm', 'Abm')], ['Abm', ('E', 'Eb')]]]]]\n",
- "Cost: 21\n",
- "Cost irreg': 23.25\n",
- "Cost penalty: 23.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], [('Abm', 'Abm'), ('E', 'E')]]], [[['E', 'E'], ['B', 'B']], [['B', 'B'], [('Eb', 'Eb'), ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], [('E', 'E'), ('F#', 'F#')]]], [[['Eb', 'Eb'], ['Abm', 'Abm']], [['Abm', 'Abm'], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "Cost: 17\n",
- "Cost irreg': 19.25\n",
- "Cost penalty: 19.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', ('Abm', 'Abm')], ['Abm', ('E', 'E')]]], [[['E', 'E'], ['B', 'B']], [['B', ('B', 'Eb')], ['Eb', ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', ('E', 'E')], ['E', ('F#', 'F#')]]], [[['Eb', 'Eb'], ['Abm', 'Abm']], [['Abm', ('Abm', 'Abm')], ['Abm', ('E', 'Eb')]]]]]\n",
- "Cost: 19\n",
- "Cost irreg': 21.25\n",
- "Cost penalty: 21.25\n",
- "[[[[['Eb', 'Eb'], ['Eb', ('Eb', 'Abm')]], [['Abm', 'Abm'], ['Abm', ('E', 'E')]]], [[['E', 'E'], ['B', ('B', 'B')]], [['B', 'Eb'], ['Eb', ('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', ('Abm', 'E')]], [['E', 'E'], ['E', ('F#', 'F#')]]], [[['Eb', 'Eb'], ['Abm', ('Abm', 'Abm')]], [['Abm', 'Abm'], ['Abm', ('E', 'Eb')]]]]]\n",
- "Cost: 26\n",
- "Cost irreg': 28.25\n",
- "Cost penalty: 28.25\n"
- ]
- }
- ],
- "source": [
- "segment = bag_of_chords[252:292]\n",
- "#print(segment)\n",
- "size = len(segment)\n",
- "bag_of_patterns = sh.compute_patterns_with_antecedents_for_size(size)\n",
- "the_min = math.inf\n",
- "best_pattern = None\n",
- "for a_pattern in bag_of_patterns:\n",
- " print(pf.recursive_chords_on_pattern(a_pattern[0],segment))\n",
- " cost = pc.guichaoua_cost(segment, a_pattern[0], a_pattern[3], a_pattern[4], a_pattern[5])\n",
- " print(\"Cost: {}\".format(cost))#, pm.recursive_chords_on_pattern(best_pattern[0],segment)))\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " print(\"Cost irreg': {}\".format(cost))#, pm.recursive_chords_on_pattern(best_pattern[0],segment)))\n",
- " cost += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " print(\"Cost penalty: {}\".format(cost))#, pm.recursive_chords_on_pattern(best_pattern[0],segment)))\n"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Baseline - Louboutin - on database.ipynb b/Notebooks/Baseline - Louboutin - on database.ipynb
deleted file mode 100644
index 1cc3a9fe441251b13b960ed1e92cf9243c60aba9..0000000000000000000000000000000000000000
--- a/Notebooks/Baseline - Louboutin - on database.ipynb
+++ /dev/null
@@ -1,238 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:06:55.721737Z",
- "start_time": "2021-01-21T17:06:53.345094Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:06:55.740687Z",
- "start_time": "2021-01-21T17:06:55.726725Z"
- }
- },
- "outputs": [],
- "source": [
- "# Subset \n",
- "#database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\subset_analysis\\\\\"\n",
- "\n",
- "# Database\n",
- "database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\final_bimbot_al\\\\\"\n",
- "\n",
- "max_size = 10\n",
- "\n",
- "manual = []\n",
- "\n",
- "for file in os.listdir(database_path):\n",
- " bag_of_words = file.split(\".\")\n",
- " if bag_of_words[-1] == \"seq\":\n",
- " if bag_of_words[-3] == \"manual\":\n",
- " manual.append(file)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# My Code"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:10:19.258790Z",
- "start_time": "2021-01-21T17:06:55.748666Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\segmentation_algorithms.py:522: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Prec: 0.1969, rap: 0.7022, F measure: 0.307\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
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\n",
- "text/plain": [
- "<Figure size 1080x360 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "persisted_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\data_persisted\"\n",
- "\n",
- "all_res = []\n",
- "all_res_one = []\n",
- "distrib_segments = []\n",
- "for song in manual:\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- "\n",
- " frontiers, _ = algos.dynamic_minimization_louboutin(bag_of_chords, segment_size_penalty = 0.125, min_size = 8, max_size = max_size, target_size = 32, irregularity_penalty = 1)\n",
- "\n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " distrib_segments.append(snd - fst)\n",
- "\n",
- " \"\"\"\n",
- " # Scores, computed on time\n",
- " song_number = song.split(\".\")[0]\n",
- " this_song_ann = dm.get_annotation_name_from_song(song_number, \"MIREX10\")\n",
- " annotation_path = \"{}\\\\{}\".format(annotations_folder_path, this_song_ann)\n",
- " annotations = dm.get_segmentation_from_txt(annotation_path, \"MIREX10\")\n",
- " references_segments = np.array(annotations)[:, 0:2]\n",
- " beats = np.load(\"{}\\\\beats\\\\{}.npy\".format(persisted_path, int(song_number)), allow_pickle=True) \n",
- "\n",
- " estimation = []\n",
- " for f in frontiers:\n",
- " if f < len(beats):\n",
- " estimation.append(beats[f])\n",
- " else:\n",
- " estimation.append(beats[-1])\n",
- " estimated_seg = dm.frontiers_to_segments(estimation)\n",
- "\n",
- " prec, rec, fmes = dm.compute_score_of_segmentation(references_segments, estimated_seg, window_length = 0.5)\"\"\"\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " song_number = song.split(\".\")[0]\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " p, r, f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, window_length = 0.5)\n",
- " all_res.append([p, r, f])\n",
- "\n",
- "results = np.array(all_res)\n",
- "prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- "print(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
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- "window_display": false
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- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Baseline - Louboutin - on song.ipynb b/Notebooks/Baseline - Louboutin - on song.ipynb
deleted file mode 100644
index cd1d5d82bc0b18b4c6d2d49ab818f9e49af5fa5e..0000000000000000000000000000000000000000
--- a/Notebooks/Baseline - Louboutin - on song.ipynb
+++ /dev/null
@@ -1,309 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T12:49:08.668545Z",
- "start_time": "2021-01-04T12:49:07.252923Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T12:49:08.674521Z",
- "start_time": "2021-01-04T12:49:08.670531Z"
- }
- },
- "outputs": [],
- "source": [
- "# Hyperparams\n",
- "max_size = 47\n",
- "min_size = 8\n",
- "positive_segment_size_penalty = 0\n",
- "negative_segment_size_penalty = 0.125\n",
- "target_size = 32\n",
- "positive_penalty = 2.25\n",
- "negative_penalty = 3"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# On a song"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T12:49:08.683498Z",
- "start_time": "2021-01-04T12:49:08.676516Z"
- }
- },
- "outputs": [],
- "source": [
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "song = \"001\"\n",
- "bag_of_chords = []\n",
- "file = open(flow_file_path + song + \".flow\", \"r\") \n",
- "for chord in file.readlines():\n",
- " bag_of_chords.append(chord.split(\"\\n\")[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T13:18:19.928387Z",
- "start_time": "2021-01-04T12:49:08.685493Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\baselines.py:643: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "My frontiers: [0, 24, 52, 84, 116, 148, 176, 196, 228, 256, 284, 316, 340, 368, 396, 428, 462]\n",
- "Guichaoua's frontiers: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "Equality ? False\n",
- "\n"
- ]
- }
- ],
- "source": [
- "frontiers, costs = baselines.dynamic_minimization_louboutin_ppp(bag_of_chords)\n",
- "\n",
- "print(\"My frontiers: {}\".format(frontiers))\n",
- "#print(\"Costs: {}\".format(costs))\n",
- "\n",
- "guichaoua_estimates = open(flow_file_path + song + \".frontiers_estimated\", \"r\")\n",
- "tab = guichaoua_estimates.read().split(\" \")\n",
- "guichaoua_frontiers = [int(i) - 1 for i in tab if i != \"\\n\"]\n",
- "guichaoua_frontiers.append(frontiers[-1])\n",
- "print(\"Guichaoua's frontiers: {}\".format(guichaoua_frontiers))\n",
- "print(\"Equality ? {}\\n\".format(guichaoua_frontiers == frontiers))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T13:18:30.780002Z",
- "start_time": "2021-01-04T13:18:19.934454Z"
- },
- "scrolled": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 17.0 at size 24\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 18 at size 32\n",
- "Cost: 15 at size 32\n",
- "Cost: 23 at size 32\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 21.75 at size 20\n",
- "Cost: 17 at size 32\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 27 at size 32\n",
- "Cost: 26.0 at size 24\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 23 at size 32\n",
- "Cost: 20.25 at size 34\n",
- "Ze sum:301.0\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(frontiers[:-1], frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " #print(segment)\n",
- " size = len(segment)\n",
- " bag_of_patterns = baselines.compute_ppp_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = baselines.louboutin_cost(segment, a_pattern[0][i], a_pattern[3][i], a_pattern[4][i])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += baselines.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " the_min += baselines.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-04T13:18:40.297340Z",
- "start_time": "2021-01-04T13:18:30.785260Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 8.75 at size 20\n",
- "Cost: 31 at size 32\n",
- "Cost: 18 at size 32\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 10 at size 32\n",
- "Cost: 31 at size 32\n",
- "Cost: 18.25 at size 16\n",
- "Cost: 15.5 at size 28\n",
- "Cost: 10 at size 32\n",
- "Cost: 31 at size 32\n",
- "Cost: 13.0 at size 8\n",
- "Cost: 35.25 at size 40\n",
- "Cost: 12 at size 32\n",
- "Cost: 31 at size 32\n",
- "Cost: 23 at size 32\n",
- "Cost: 20.25 at size 34\n",
- "Ze sum:323.5\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(guichaoua_frontiers[:-1], guichaoua_frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " size = len(segment)\n",
- " bag_of_patterns = baselines.compute_ppp_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = baselines.louboutin_cost(segment, a_pattern[0][i], a_pattern[3][i], a_pattern[4][i])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += baselines.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " the_min += baselines.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Cohen Marmoret - on song.ipynb b/Notebooks/Cohen Marmoret - on song.ipynb
deleted file mode 100644
index 041c5c77cde6568f6bc8561225395fa1989b1986..0000000000000000000000000000000000000000
--- a/Notebooks/Cohen Marmoret - on song.ipynb
+++ /dev/null
@@ -1,373 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:39:46.629984Z",
- "start_time": "2021-01-21T17:39:45.120964Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "import polytopes.segmentation_helper as sh\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:39:46.637927Z",
- "start_time": "2021-01-21T17:39:46.631940Z"
- }
- },
- "outputs": [],
- "source": [
- "# Hyperparams\n",
- "max_size = 47\n",
- "min_size = 8\n",
- "positive_segment_size_penalty = 0\n",
- "negative_segment_size_penalty = 0#.125\n",
- "target_size = 32\n",
- "positive_penalty = 0#2.25\n",
- "negative_penalty = 0#3"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# On a song"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:39:46.647900Z",
- "start_time": "2021-01-21T17:39:46.640917Z"
- }
- },
- "outputs": [],
- "source": [
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "song = \"001\"\n",
- "bag_of_chords = []\n",
- "file = open(flow_file_path + song + \".flow\", \"r\") \n",
- "for chord in file.readlines():\n",
- " bag_of_chords.append(chord.split(\"\\n\")[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:44:58.341425Z",
- "start_time": "2021-01-21T17:39:46.649893Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\segmentation_algorithms.py:239: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "My frontiers: [0, 24, 52, 84, 116, 148, 180, 192, 224, 256, 284, 315, 336, 368, 396, 428, 462]\n",
- "Costs: 425\n",
- "Guichaoua's frontiers: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "Equality ? False\n",
- "\n"
- ]
- }
- ],
- "source": [
- "frontiers, costs = algos.dynamic_minimization_cohen_marmoret(bag_of_chords)\n",
- "\n",
- "print(\"My frontiers: {}\".format(frontiers))\n",
- "print(\"Costs: {}\".format(costs))\n",
- "\n",
- "guichaoua_estimates = open(flow_file_path + \"Guichaoua Estimates\\\\Experiments\\\\\" + song + \".frontiers_estimated\", \"r\")\n",
- "tab = guichaoua_estimates.read().split(\" \")\n",
- "guichaoua_frontiers = [int(i) - 1 for i in tab if i != \"\\n\"]\n",
- "guichaoua_frontiers.append(frontiers[-1])\n",
- "print(\"Guichaoua's frontiers: {}\".format(guichaoua_frontiers))\n",
- "print(\"Equality ? {}\\n\".format(guichaoua_frontiers == frontiers))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:47:02.961257Z",
- "start_time": "2021-01-21T17:46:56.267145Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'E', 'E', 'E', 'E', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#', 'Eb', 'Eb', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['F#', 'F#']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['Eb', 'Eb'], ['Eb', 'Eb']]]]]\n",
- "Cost: 16 at size 24\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['B', 'B'], ['B', 'B']], [['Eb', 'Eb'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#']], [['Eb', 'Eb']]]]]\n",
- "Cost: 23 at size 28\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#', 'Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]]]\n",
- "Cost: 20 at size 32\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Ab', 'Ab', 'Bb', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']], [[('Cm', 'Cm'), ('Cm', 'Cm')]]]]]\n",
- "Cost: 14 at size 32\n",
- "['Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Eb', 'Eb', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Ab', 'Ab'], ['Ab', 'Ab']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['G', 'G'], ['G', 'G']], [['Cm', 'Cm'], [('Cm', 'Cm')]]]], [[[['Ab', 'Ab'], ['Ab', 'Ab']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['G', 'G'], ['G', 'G']], [['Eb', 'Eb'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 25 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['B', 'B'], ['B', 'B']], [['Eb', 'Eb'], [('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#'], ['Eb', 'Eb']], [['Abm', 'Abm'], [('Abm', 'Abm')]]]]]\n",
- "Cost: 29 at size 32\n",
- "['F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#']\n",
- "Sequence: [[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E']], [['F#', 'F#']]]]\n",
- "Cost: 9 at size 12\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Ab', 'Ab', 'Bb', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']], [[('Cm', 'Cm'), ('Cm', 'Cm')]]]]]\n",
- "Cost: 14 at size 32\n",
- "['Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Eb', 'Eb', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Ab', 'Ab'], ['Ab', 'Ab']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['G', 'G'], ['G', 'G']], [['Cm', 'Cm'], [('Cm', 'Cm')]]]], [[[['Ab', 'Ab'], ['Ab', 'Ab']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['G', 'G'], ['G', 'G']], [['Eb', 'Eb'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 25 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['B', 'B'], ['B', 'B']], [['Eb', 'Eb'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#']], [['Eb', 'Eb']]]]]\n",
- "Cost: 23 at size 28\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'Eb', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ab', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'C#', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['Abm', 'Abm'], ['E', 'Eb']]], [[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ab']]]], [[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm']]], [[['C#', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], [('Ebm', 'Ebm')]]]]]\n",
- "Cost: 32 at size 31\n",
- "['Ab', 'C#', 'C#', 'F#', 'F#', 'B', 'B', 'E', 'E', 'A', 'A', 'D', 'D', 'Eb', 'Eb', 'Eb', 'Eb', 'Eb', 'Eb', 'Eb', 'Eb']\n",
- "Sequential cost\n",
- "Ze sum:230\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(frontiers[:-1], frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " #print(segment)\n",
- " size = len(segment)\n",
- " print(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = pc.cohen_marmoret_cost(segment, a_pattern[0], a_pattern[3])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " if bag_of_patterns == []:\n",
- " print(\"Sequential cost\")\n",
- " break\n",
- " print(\"Sequence: {}\".format(pf.apply_chords_on_pattern(best_pattern[0],segment)))\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:48:21.919557Z",
- "start_time": "2021-01-21T17:48:12.829436Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "['Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'E', 'E', 'E', 'E', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#', 'F#']\n",
- "Sequence: [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['E', 'E'], ['E', 'E']], [[('F#', 'F#'), ('F#', 'F#')], [('F#', 'F#'), ('F#', 'F#')]]]]\n",
- "Cost: 7 at size 20\n",
- "['Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], [('B', 'B')]]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 39 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#', 'Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]]]\n",
- "Cost: 20 at size 32\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Ab', 'Ab', 'Bb', 'Bb']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']]]]]\n",
- "Cost: 13 at size 28\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], [('G', 'G')]]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], [('G', 'G')]]]]]\n",
- "Cost: 12 at size 32\n",
- "['Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], [('B', 'B')]]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 39 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#']\n",
- "Sequence: [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]]\n",
- "Cost: 20 at size 16\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Bb', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'Cm', 'F', 'Ab', 'Ab', 'Bb', 'Bb']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']]]]]\n",
- "Cost: 13 at size 28\n",
- "['Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G']\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], [('G', 'G')]]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], [('G', 'G')]]]]]\n",
- "Cost: 12 at size 32\n",
- "['Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], [('B', 'B')]]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 39 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'Eb']\n",
- "Sequence: [[['Abm', 'Abm'], ['Abm', 'Abm']], [['Abm', ('Abm', 'E')], ['Eb']]]\n",
- "Cost: 11 at size 8\n",
- "['Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ab', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'C#', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ebm', 'Ab', 'C#', 'C#', 'F#', 'F#', 'B', 'B', 'E', 'E', 'A', 'A', 'D', 'D', 'Eb', 'Eb', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ab']]], [[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'C#']]]], [[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ab']]], [[[('C#', 'C#'), ('F#', 'F#')], [('B', 'B'), ('E', 'E')]], [[('A', 'A'), ('D', 'D')], [('Eb', 'Eb'), ('Eb', 'Eb')]]]]]\n",
- "Cost: 41 at size 40\n",
- "['Eb', 'Eb', 'Eb', 'Eb', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G', 'Cm', 'Cm', 'Cm', 'Cm', 'Ab', 'Ab', 'Ab', 'Ab', 'Eb', 'Eb', 'Eb', 'Eb', 'G', 'G', 'G', 'G']\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], [('Eb', 'Eb')]], [['G', 'G'], [('G', 'G')]]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], [('Eb', 'Eb')]], [['G', 'G'], [('G', 'G')]]]]]\n",
- "Cost: 18 at size 32\n",
- "['Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb']\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], [('B', 'B')]]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], [('Eb', 'Eb')]]]]]\n",
- "Cost: 39 at size 32\n",
- "['Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'B', 'B', 'B', 'B', 'Eb', 'Eb', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm', 'E', 'E', 'E', 'E', 'F#', 'F#', 'Eb', 'Eb', 'Abm', 'Abm', 'Abm', 'Abm']\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['B', 'B'], ['B', 'B']], [['Eb', 'Eb'], [('Eb', 'Eb')]]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['E', 'E'], ['E', 'E']]], [[['F#', 'F#'], ['Eb', 'Eb']], [['Abm', 'Abm'], [('Abm', 'Abm')]]]]]\n",
- "Cost: 29 at size 32\n",
- "['F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#', 'Abm', 'Abm', 'Abm', 'Abm', 'F#', 'F#', 'F#', 'F#', 'C#', 'C#', 'C#', 'C#', 'E', 'E', 'F#', 'F#', 'F#', 'F#', 'Abm', 'Abm', 'Abm', 'Abm']\n",
- "Sequence: [[[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], ['F#', 'F#']], [['Abm', 'Abm'], ['Abm', 'Abm']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], [('F#', 'F#'), ('F#', 'F#')]], [['Abm', 'Abm'], [('Abm', 'Abm')]]]]]\n",
- "Cost: 17 at size 34\n",
- "Ze sum:369\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(guichaoua_frontiers[:-1], guichaoua_frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " #print(segment)\n",
- " size = len(segment)\n",
- " print(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = pc.cohen_marmoret_cost(segment, a_pattern[0], a_pattern[3])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_pattern = a_pattern\n",
- " the_min = cost\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " if bag_of_patterns == []:\n",
- " print(\"Sequential cost\")\n",
- " break\n",
- " print(\"Sequence: {}\".format(pf.apply_chords_on_pattern(best_pattern[0],segment)))\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Comparing Louboutin & Guichaoua.ipynb b/Notebooks/Comparing Louboutin & Guichaoua.ipynb
deleted file mode 100644
index 3f78b92168365e00afe0a71715484e7ed94c4543..0000000000000000000000000000000000000000
--- a/Notebooks/Comparing Louboutin & Guichaoua.ipynb
+++ /dev/null
@@ -1,583 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Disclaimer: for fair comparison, penalties MUST be always null, to check everytime it is launched."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T17:44:55.613067Z",
- "start_time": "2021-01-22T17:44:54.268957Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.segmentation_helper as sh\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T17:44:55.624850Z",
- "start_time": "2021-01-22T17:44:55.614876Z"
- }
- },
- "outputs": [],
- "source": [
- "database_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\RWC_annotations\\\\final_bimbot_al\\\\\"\n",
- "annotations_folder_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Audio samples\\\\RWC Pop\\\\annotations\\\\final_bimbot\\\\\"\n",
- "persisted_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\data_persisted\"\n",
- "\n",
- "max_size = 42\n",
- "\n",
- "manual = []\n",
- "\n",
- "for file in os.listdir(database_path):\n",
- " bag_of_words = file.split(\".\")\n",
- " if bag_of_words[-1] == \"seq\":\n",
- " if bag_of_words[-3] == \"manual\":\n",
- " manual.append(file)\n",
- "\n",
- "CURR_DIR = os.path.dirname(os.path.realpath(\"__file__\"))\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T17:44:55.633827Z",
- "start_time": "2021-01-22T17:44:55.627843Z"
- }
- },
- "outputs": [],
- "source": [
- "def print_res_for_songs_range(all_res, context = \"\"):\n",
- " results = np.array(all_res)\n",
- " prec, rap, fmes = round(np.mean(results[:,0]),4), round(np.mean(results[:,1]),4), round(np.mean(results[:,2]),4)\n",
- " print(\"Context: {}, prec: {}, rap: {}, F measure: {}\".format(context, prec, rap, fmes))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Marmoret"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Marmoret-Cohen cost"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:01.881581Z",
- "start_time": "2021-01-22T17:44:55.635823Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\segmentation_algorithms.py:239: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Context: Zero Tolerance, prec: 0.3721, rap: 0.5916, F measure: 0.4505\n",
- "Context: Three Tolerance, prec: 0.4198, rap: 0.6688, F measure: 0.5086\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1080x360 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "mc_all_res_zero_tol = []\n",
- "mc_all_res_three_tol = []\n",
- "mc_all_frontiers = []\n",
- "mc_distrib_segments = []\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- "\n",
- " try:\n",
- " frontiers = np.load(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\marmoret_cohen_song{}_penalties{}_maxsize{}.npy\".format(CURR_DIR, song_number, (0,0), max_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " frontiers, cost = algos.dynamic_minimization_cohen_marmoret(bag_of_chords, segment_size_penalty = 0, min_size = 8, max_size = max_size, target_size = 32, irregularity_penalty = 0)\n",
- " fro = np.array(frontiers, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\marmoret_cohen_song{}_penalties{}_maxsize{}\".format(CURR_DIR, song_number, (0,0), max_size), fro)\n",
- "\n",
- " mc_all_frontiers.append(frontiers)\n",
- " \n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " mc_distrib_segments.append(snd - fst)\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " \n",
- " p,r,f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 0.2)\n",
- " mc_all_res_zero_tol.append([p,r,f])\n",
- " \n",
- " p_3,r_3,f_3 = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 3)\n",
- " mc_all_res_three_tol.append([p_3,r_3,f_3])\n",
- "\n",
- "print_res_for_songs_range(mc_all_res_zero_tol, context = \"Zero Tolerance\")\n",
- "print_res_for_songs_range(mc_all_res_three_tol, context = \"Three Tolerance\")\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(mc_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:02.095017Z",
- "start_time": "2021-01-22T22:25:01.883574Z"
- }
- },
- "outputs": [
- {
- "ename": "NameError",
- "evalue": "name 'stop' is not defined",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-5-4f76a9dad686>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mstop\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;31mNameError\u001b[0m: name 'stop' is not defined"
- ]
- }
- ],
- "source": [
- "stop"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Louboutaoua cost"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:02.107974Z",
- "start_time": "2021-01-22T17:44:54.272Z"
- }
- },
- "outputs": [],
- "source": [
- "m_all_res_zero_tol = []\n",
- "m_all_res_three_tol = []\n",
- "m_all_frontiers = []\n",
- "m_distrib_segments = []\n",
- "m_cost_sum = 0\n",
- "m_cost_nb = 0\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- "\n",
- " try:\n",
- " frontiers = np.load(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\marmoret_louboutaoua_song{}_penalties{}_maxsize{}.npy\".format(CURR_DIR, song_number, (0,0), max_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " frontiers, cost = algos.dynamic_minimization_louboutaoua(bag_of_chords, segment_size_penalty = 0, min_size = 8, max_size = max_size, target_size = 32, irregularity_penalty = 0)\n",
- " fro = np.array(frontiers, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\marmoret_louboutaoua_song{}_penalties{}_maxsize{}\".format(CURR_DIR, song_number, (0,0), max_size), fro)\n",
- "\n",
- " m_all_frontiers.append(frontiers)\n",
- " #m_cost_sum += cost\n",
- " #m_cost_nb += len(frontiers) - 1\n",
- " \n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " m_distrib_segments.append(snd - fst)\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " \n",
- " p,r,f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 0.2)\n",
- " m_all_res_zero_tol.append([p,r,f])\n",
- " \n",
- " p_3,r_3,f_3 = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 3)\n",
- " m_all_res_three_tol.append([p_3,r_3,f_3])\n",
- "\n",
- "print_res_for_songs_range(m_all_res_zero_tol, context = \"Zero Tolerance\")\n",
- "print_res_for_songs_range(m_all_res_three_tol, context = \"Three Tolerance\")\n",
- "#print(\"Averaged cost for a polytope: {}\".format(m_cost_sum/m_cost_nb))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(m_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Guichaoua"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Local"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:02.110967Z",
- "start_time": "2021-01-22T17:44:54.274Z"
- }
- },
- "outputs": [],
- "source": [
- "g_all_res_zero_tol = []\n",
- "g_all_res_three_tol = []\n",
- "g_all_frontiers = []\n",
- "g_distrib_segments = []\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- " try:\n",
- " frontiers = np.load(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\guichaoua_song{}_penalties{}_maxsize{}.npy\".format(CURR_DIR, song_number, (0,0), max_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " frontiers, cost = algos.dynamic_minimization_guichaoua(bag_of_chords, \n",
- " positive_segment_size_penalty = 0, negative_segment_size_penalty = 0,\n",
- " min_size = 8, max_size = max_size, target_size = 32, \n",
- " positive_penalty = 0, negative_penalty = 0,\n",
- " global_antecedents = False)\n",
- " fro = np.array(frontiers, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\guichaoua_song{}_penalties{}_maxsize{}\".format(CURR_DIR, song_number, (0,0), max_size), fro)\n",
- "\n",
- " g_all_frontiers.append(frontiers)\n",
- " \n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " g_distrib_segments.append(snd - fst)\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " \n",
- " p,r,f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 0.2)\n",
- " g_all_res_zero_tol.append([p,r,f])\n",
- " \n",
- " p_3,r_3,f_3 = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 3)\n",
- " g_all_res_three_tol.append([p_3,r_3,f_3])\n",
- "\n",
- "print_res_for_songs_range(g_all_res_zero_tol, context = \"Zero Tolerance\")\n",
- "print_res_for_songs_range(g_all_res_three_tol, context = \"Three Tolerance\")\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(g_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Global"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:02.112962Z",
- "start_time": "2021-01-22T17:44:54.278Z"
- }
- },
- "outputs": [],
- "source": [
- "g_all_res_zero_tol = []\n",
- "g_all_res_three_tol = []\n",
- "g_all_frontiers = []\n",
- "g_distrib_segments = []\n",
- "#g_cost_sum = 0\n",
- "#g_cost_nb = 0\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- " try:\n",
- " frontiers = np.load(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\guichaoua_global_song{}_penalties{}_maxsize{}.npy\".format(CURR_DIR, song_number, (0,0), max_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " frontiers, cost = algos.dynamic_minimization_guichaoua(bag_of_chords,\n",
- " positive_segment_size_penalty = 0, negative_segment_size_penalty = 0,\n",
- " min_size = 8, max_size = max_size, target_size = 32, \n",
- " positive_penalty = 0, negative_penalty = 0,\n",
- " global_antecedents = True)\n",
- " fro = np.array(frontiers, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\guichaoua_global_song{}_penalties{}_maxsize{}\".format(CURR_DIR, song_number, (0,0), max_size), fro)\n",
- "\n",
- " g_all_frontiers.append(frontiers)\n",
- " #g_cost_sum += cost\n",
- " #g_cost_nb += len(frontiers) - 1\n",
- " \n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " g_distrib_segments.append(snd - fst)\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " \n",
- " p,r,f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 0.2)\n",
- " g_all_res_zero_tol.append([p,r,f])\n",
- " \n",
- " p_3,r_3,f_3 = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 3)\n",
- " g_all_res_three_tol.append([p_3,r_3,f_3])\n",
- "\n",
- "print_res_for_songs_range(g_all_res_zero_tol, context = \"Zero Tolerance\")\n",
- "print_res_for_songs_range(g_all_res_three_tol, context = \"Three Tolerance\")\n",
- "#print(\"Averaged cost for a polytope: {}\".format(g_cost_sum/g_cost_nb))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(g_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Louboutin"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-22T22:25:02.114955Z",
- "start_time": "2021-01-22T17:44:54.281Z"
- }
- },
- "outputs": [],
- "source": [
- "l_all_res_zero_tol = []\n",
- "l_all_res_three_tol = []\n",
- "l_all_frontiers = []\n",
- "l_distrib_segments = []\n",
- "l_cost_sum = 0\n",
- "l_cost_nb = 0\n",
- "\n",
- "for song in manual:\n",
- " song_number = song.split(\".\")[0]\n",
- "\n",
- " bag_of_chords = dm.flowify_song(database_path + song)\n",
- "\n",
- " try:\n",
- " fro = np.load(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\louboutin_song{}_penalties{}_maxsize{}.npy\".format(CURR_DIR, song_number, (0,0), max_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " frontiers, cost = algos.dynamic_minimization_louboutin(bag_of_chords, segment_size_penalty = 0, min_size = 8, max_size = max_size, target_size = 32, irregularity_penalty = 0)\n",
- " fro = np.array(frontiers, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\estimated_frontiers\\\\louboutin_song{}_penalties{}_maxsize{}\".format(CURR_DIR, song_number, (0,0), max_size), fro)\n",
- "\n",
- " l_cost_sum += cost\n",
- " l_cost_nb += len(frontiers) - 1\n",
- "\n",
- " l_all_frontiers.append(frontiers)\n",
- " \n",
- " for fst, snd in zip(frontiers[:-1], frontiers[1:]):\n",
- " l_distrib_segments.append(snd - fst)\n",
- "\n",
- " #Scores, computed on the beat annotation\n",
- " beat_indexed_segments = dm.frontiers_to_segments(frontiers)\n",
- "\n",
- " annot_name = \"{:03d}.manual.seg\".format(int(song_number))\n",
- " annotation_file = open(annotations_folder_path + annot_name,'r')\n",
- " annotation = annotation_file.read().replace(\"\\n\", \"\").split(\" \")\n",
- " annotation = np.array([int(x) - 1 for x in annotation])\n",
- " beat_indexed_annotation = np.array(dm.frontiers_to_segments(annotation))\n",
- " \n",
- " p,r,f = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 0.2)\n",
- " l_all_res_zero_tol.append([p,r,f])\n",
- " \n",
- " p_3,r_3,f_3 = dm.compute_score_of_segmentation(beat_indexed_annotation, beat_indexed_segments, \n",
- " window_length = 3)\n",
- " l_all_res_three_tol.append([p_3,r_3,f_3])\n",
- "\n",
- "print_res_for_songs_range(l_all_res_zero_tol, context = \"Zero Tolerance\")\n",
- "print_res_for_songs_range(l_all_res_three_tol, context = \"Three Tolerance\")\n",
- "print(\"Averaged cost for a polytope: {}\".format(l_cost_sum/l_cost_nb))\n",
- "plt.figure(figsize=(15,5))\n",
- "plt.hist(l_distrib_segments, bins = range(max_size))\n",
- "plt.xlabel(\"Segment's size (in nb of beats)\")\n",
- "#plt.title(\"Prec: {}, rap: {}, F measure: {}\".format(prec, rap, fmes))\n",
- "plt.plot()"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
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- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
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- "window_display": false
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- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Comparing direct and global.ipynb b/Notebooks/Comparing direct and global.ipynb
deleted file mode 100644
index a78fa8985ebcc6e7c577b39bb8c5119e7b2fa6e3..0000000000000000000000000000000000000000
--- a/Notebooks/Comparing direct and global.ipynb
+++ /dev/null
@@ -1,217 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:55.265096Z",
- "start_time": "2021-01-21T17:29:53.064544Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.baselines as baselines\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.chord_movement as mvt\n",
- "import polytopes.pattern_manipulation as pm\n",
- "import polytopes.sequence_segmentation as seq_seg\n",
- "\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:29:55.279060Z",
- "start_time": "2021-01-21T17:29:55.268089Z"
- }
- },
- "outputs": [],
- "source": [
- "pattern_persist_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Projects\\\\PhD main projects\\\\On Git\\\\Code\\\\Polytopes and relation\\\\polytopes\"\n",
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "song = \"002\"\n",
- "bag_of_chords = []\n",
- "max_size = 48\n",
- "file = open(flow_file_path + song + \".flow\", \"r\") \n",
- "for chord in file.readlines():\n",
- " bag_of_chords.append(chord.split(\"\\n\")[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:34:18.787824Z",
- "start_time": "2021-01-21T17:29:55.282052Z"
- }
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\amarmore\\AppData\\Local\\Continuum\\anaconda3\\envs\\s_and_c\\lib\\site-packages\\ipykernel_launcher.py:27: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.\n",
- "C:\\Users\\amarmore\\AppData\\Local\\Continuum\\anaconda3\\envs\\s_and_c\\lib\\site-packages\\ipykernel_launcher.py:27: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n"
- ]
- },
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "cnt_equal = []\n",
- "cnt_diff = []\n",
- "for current_idx in range(2, len(bag_of_chords)):\n",
- " if current_idx < 8:\n",
- " possible_starts = [0]\n",
- " elif current_idx == len(bag_of_chords) - 1:\n",
- " possible_starts = sh.possible_segment_start(current_idx, min_size = 2, max_size = max_size)\n",
- " else:\n",
- " possible_starts = sh.possible_segment_start(current_idx, min_size = 8, max_size = max_size)\n",
- " for possible_start_idx in possible_starts:\n",
- " if possible_start_idx < 0:\n",
- " raise err.ToDebugException(\"Invalid value of start index.\")\n",
- " segment = [bag_of_chords[k] for k in range(possible_start_idx, current_idx + 1)]\n",
- " segment_size = len(segment)\n",
- " \n",
- " try:\n",
- " this_bag_direct = np.load(\"{}\\\\persisted_content\\\\compute_patterns_with_antecedents_for_size_{}.npy\".format(pattern_persist_path, segment_size), allow_pickle = True)\n",
- " this_bag_global = np.load(\"{}\\\\persisted_content\\\\compute_patterns_with_global_antecedents_for_size_{}.npy\".format(pattern_persist_path, segment_size), allow_pickle = True)\n",
- " except FileNotFoundError:\n",
- " this_bag_direct = sh.compute_patterns_with_antecedents_for_size(segment_size)\n",
- " arr = np.array(this_bag_direct, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\compute_patterns_with_antecedents_for_size_{}\".format(pattern_persist_path, segment_size), arr)\n",
- " this_bag_global = sh.compute_patterns_with_global_antecedents_for_size(segment_size)\n",
- " arr_glob = np.array(this_bag_global, dtype=object)\n",
- " np.save(\"{}\\\\persisted_content\\\\compute_patterns_with_global_antecedents_for_size_{}\".format(pattern_persist_path, segment_size), arr_glob)\n",
- "\n",
- " if this_bag_direct != []:\n",
- " this_segment_cost = math.inf\n",
- " \n",
- " if len(this_bag_direct) != len(this_bag_global):\n",
- " raise NotImplementedError(\"Chelou\")\n",
- "\n",
- " for i in range(len(this_bag_direct)):\n",
- " a_pattern_direct = this_bag_direct[i]\n",
- " a_pattern_global = this_bag_global[i]\n",
- " if not np.array(a_pattern_direct[0] == a_pattern_global[0]): \n",
- " raise NotImplementedError(\"Aussi chelou\")\n",
- "\n",
- " this_polytope_cost_direct = pc.guichaoua_cost(segment, a_pattern_direct[0], a_pattern_direct[3], a_pattern_direct[4], a_pattern_direct[5])\n",
- " this_polytope_cost_global = pc.guichaoua_cost_global_antecedents_successors(segment, a_pattern_global[0], a_pattern_global[3], a_pattern_global[4], a_pattern_global[5])\n",
- " if this_polytope_cost_direct != this_polytope_cost_global:\n",
- " cnt_diff.append(segment_size)\n",
- " #print(\"la\")\n",
- " else:\n",
- " cnt_equal.append(segment_size)\n",
- " \n",
- "plt.hist(cnt_diff)\n",
- "plt.show()\n",
- "plt.hist(cnt_equal)\n",
- "plt.show()"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Notebooks/Louboutaoua - on song.ipynb b/Notebooks/Louboutaoua - on song.ipynb
deleted file mode 100644
index ca19baaa1053695f9ad5fee3f8b3552da15cb2ed..0000000000000000000000000000000000000000
--- a/Notebooks/Louboutaoua - on song.ipynb
+++ /dev/null
@@ -1,378 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:25:28.291265Z",
- "start_time": "2021-01-21T17:25:26.703476Z"
- }
- },
- "outputs": [],
- "source": [
- "import os\n",
- "import time\n",
- "\n",
- "# Self-code imports\n",
- "import polytopes.segmentation_algorithms as algos\n",
- "from polytopes.model.note import Note\n",
- "from polytopes.model.chord import Chord\n",
- "import polytopes.polytopical_costs as pc\n",
- "import polytopes.data_manipulation as dm\n",
- "import polytopes.pattern_manip as pm\n",
- "import polytopes.pattern_factory as pf\n",
- "import polytopes.segmentation_helper as sh\n",
- "\n",
- "#Generic imports\n",
- "import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import math\n",
- "import copy"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:25:28.303197Z",
- "start_time": "2021-01-21T17:25:28.296232Z"
- }
- },
- "outputs": [],
- "source": [
- "# Hyperparams\n",
- "max_size = 47\n",
- "min_size = 8\n",
- "positive_segment_size_penalty = 0\n",
- "negative_segment_size_penalty = 0#.125\n",
- "target_size = 32\n",
- "positive_penalty = 0#2.25\n",
- "negative_penalty = 0#3"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# On a song"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:25:28.320154Z",
- "start_time": "2021-01-21T17:25:28.306191Z"
- }
- },
- "outputs": [],
- "source": [
- "flow_file_path = \"C:\\\\Users\\\\amarmore\\\\Desktop\\\\Annotations MIREX Quaero\\\\annotations_as_flow\\\\\"\n",
- "song = \"001\"\n",
- "bag_of_chords = []\n",
- "file = open(flow_file_path + song + \".flow\", \"r\") \n",
- "for chord in file.readlines():\n",
- " bag_of_chords.append(chord.split(\"\\n\")[0])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:58:19.456535Z",
- "start_time": "2021-01-21T17:25:28.323147Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "c:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\segmentation_algorithms.py:119: UserWarning: No Polytope is available for this size of segment. Trying sequential cost instead.\n",
- " warnings.warn(\"No Polytope is available for this size of segment. Trying sequential cost instead.\")\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "My frontiers: [0, 24, 56, 84, 112, 148, 176, 184, 192, 220, 256, 284, 292, 317, 328, 356, 368, 396, 428, 462]\n",
- "Cost: 237\n",
- "Guichaoua's frontiers: [0, 20, 52, 84, 112, 144, 176, 192, 220, 252, 284, 292, 332, 364, 396, 428, 462]\n",
- "Equality ? False\n",
- "\n"
- ]
- }
- ],
- "source": [
- "frontiers, costs = algos.dynamic_minimization_louboutaoua(bag_of_chords, segment_size_penalty = 0, irregularity_penalty = 0)\n",
- "\n",
- "print(\"My frontiers: {}\".format(frontiers))\n",
- "print(\"Cost: {}\".format(costs))\n",
- "\n",
- "guichaoua_estimates = open(flow_file_path + \"Guichaoua Estimates\\\\Experiments\\\\\" + song + \".frontiers_estimated\", \"r\")\n",
- "tab = guichaoua_estimates.read().split(\" \")\n",
- "guichaoua_frontiers = [int(i) - 1 for i in tab if i != \"\\n\"]\n",
- "guichaoua_frontiers.append(frontiers[-1])\n",
- "print(\"Guichaoua's frontiers: {}\".format(guichaoua_frontiers))\n",
- "print(\"Equality ? {}\\n\".format(guichaoua_frontiers == frontiers))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:58:19.462481Z",
- "start_time": "2021-01-21T17:58:19.457493Z"
- }
- },
- "outputs": [],
- "source": [
- "frontiers = [0, 24, 56, 84, 112, 148, 180, 220, 256, 292, 328, 368, 396, 428, 462] # this_poltyope_cost, 23min\n",
- "#333, [0, 24, 56, 84, 112, 148, 180, 220, 256, 292, 328, 368, 396, 428, 462] #this_segment_cost, 23min34\n",
- "#333, [0, 24, 56, 84, 112, 148, 180, 220, 256, 292, 328, 368, 396, 428, 462] #Nothing, 24 min24"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:58:43.325834Z",
- "start_time": "2021-01-21T17:58:19.463478Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 12 at size 24\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['F#', 'F#']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['Eb', 'Eb'], ['Eb', 'Eb']]]]]\n",
- "0\n",
- "Cost: 21 at size 32\n",
- "Sequence: [[[[['Abm', 'Abm'], ['B', 'B']], [['Abm', 'Abm'], ['B', 'B']]], [[['E', 'E'], ['Eb', 'Eb']], [['E', 'E'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['F#', 'Eb']], [['Abm', 'Abm'], ['F#', 'Eb']]], [[['E', 'E'], ['Abm', 'Abm']], [['E', 'E'], ['Abm', 'Abm']]]]]\n",
- "5\n",
- "Cost: 12 at size 28\n",
- "Sequence: [[[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], ['F#', 'F#']], [['Abm', 'Abm'], ['Abm', 'Abm']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], ['F#', 'F#']]]]]\n",
- "4\n",
- "Cost: 13 at size 28\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']]]]]\n",
- "5\n",
- "Cost: 12 at size 36\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Ab', 'Ab']], [['Cm', 'Cm'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['G', 'G']], [['Eb', 'Eb'], ['G', 'G']]]], [[[['Cm', 'Cm'], ['Ab', 'Ab']], [['Cm', 'Cm'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], [('G', 'G'), ('G', 'G')]], [['Eb', 'Eb'], [('Eb', 'Eb'), ('Eb', 'Eb')]]]]]\n",
- "9\n",
- "Cost: 21 at size 32\n",
- "Sequence: [[[[['Abm', 'Abm'], ['B', 'B']], [['Abm', 'Abm'], ['B', 'B']]], [[['E', 'E'], ['Eb', 'Eb']], [['E', 'E'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['F#', 'Eb']], [['Abm', 'Abm'], ['F#', 'Eb']]], [[['E', 'E'], ['Abm', 'Abm']], [['E', 'E'], ['Abm', 'Abm']]]]]\n",
- "5\n",
- "Cost: 38 at size 40\n",
- "Sequence: [[[[['F#', 'F#'], ['E', 'F#']], [['F#', 'F#'], ['E', 'F#']]], [[['C#', 'C#'], [('Cm', 'Cm'), ('Cm', 'Cm')]], [['C#', 'C#'], [('Cm', 'Cm'), ('Cm', 'F')]]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Cm']]], [[['Cm', 'Cm'], [('Cm', 'Cm'), ('Ab', 'Ab')]], [['Cm', 'Bb'], [('Cm', 'F'), ('Bb', 'Bb')]]]]]\n",
- "8\n",
- "Cost: 12 at size 36\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Ab', 'Ab']], [['Cm', 'Cm'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['G', 'G']], [['Eb', 'Eb'], ['G', 'G']]]], [[[['Cm', 'Cm'], ['Ab', 'Ab']], [['Cm', 'Cm'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], [('G', 'G'), ('G', 'G')]], [['Eb', 'Eb'], [('Eb', 'Eb'), ('Eb', 'Eb')]]]]]\n",
- "9\n",
- "Cost: 32 at size 36\n",
- "Sequence: [[[[['Abm', 'Abm'], ['B', 'B']], [['Abm', 'Abm'], ['B', 'B']]], [[['E', 'E'], ['Eb', 'Eb']], [['E', 'E'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['F#', 'Eb']], [['Abm', 'Abm'], ['F#', 'Eb']]], [[['E', 'E'], [('Abm', 'Abm'), ('Abm', 'Abm')]], [['E', 'E'], [('Abm', 'Abm'), ('E', 'Eb')]]]]]\n",
- "2\n",
- "Cost: 21 at size 36\n",
- "Sequence: [[[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ab']]], [[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'C#']]]], [[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ab']]], [[['C#', ('F#', 'F#')], ['E', ('A', 'A')]], [['C#', ('B', 'B')], ['E', ('D', 'D')]]]]]\n",
- "1\n",
- "Cost: 26 at size 40\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['Ab', 'Ab'], [('Eb', 'Eb'), ('Eb', 'Eb')]], [['Ab', 'Ab'], [('G', 'G'), ('G', 'G')]]]], [[[['Cm', 'Cm'], ['Ab', 'Ab']], [['Cm', 'Cm'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], [('G', 'G'), ('G', 'G')]], [['Eb', 'Eb'], [('Eb', 'Eb'), ('Eb', 'Eb')]]]]]\n",
- "3\n",
- "Cost: 14 at size 28\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['E', 'E'], ['E', 'E']]]], [[[['B', 'B'], ['F#', 'F#']], [['B', 'B']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['Eb', 'Eb']]]]]\n",
- "6\n",
- "Cost: 21 at size 32\n",
- "Sequence: [[[[['Abm', 'Abm'], ['B', 'B']], [['Abm', 'Abm'], ['B', 'B']]], [[['E', 'E'], ['Eb', 'Eb']], [['E', 'E'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['F#', 'Eb']], [['Abm', 'Abm'], ['F#', 'Eb']]], [[['E', 'E'], ['Abm', 'Abm']], [['E', 'E'], ['Abm', 'Abm']]]]]\n",
- "5\n",
- "Cost: 12 at size 34\n",
- "Sequence: [[[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], ['F#', 'F#']], [['Abm', 'Abm'], ['Abm', 'Abm']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], [('F#', 'F#'), ('F#', 'F#')]], [['Abm', 'Abm'], [('Abm', 'Abm')]]]]]\n",
- "0\n",
- "Ze sum:267\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(frontiers[:-1], frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " #print(segment)\n",
- " size = len(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_ppp_and_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " best_ppp_idx = None\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = pc.louboutaoua_cost(segment, a_pattern[0][i], a_pattern[3], a_pattern[4], a_pattern[5], a_pattern[6][i])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " best_ppp_idx = i\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_ppp = a_pattern[0][best_ppp_idx]\n",
- " the_min = cost\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " if the_min != math.inf:\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " print(\"Sequence: {}\".format(pf.apply_chords_on_pattern(best_ppp,segment)))\n",
- " print(best_ppp_idx)\n",
- " the_sum += the_min\n",
- " else:\n",
- " print(\"Sequential cost at size {}, not computed\".format(end-start))\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2021-01-21T17:59:14.568432Z",
- "start_time": "2021-01-21T17:58:43.329792Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Cost: 6 at size 20\n",
- "Sequence: [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['E', 'E'], ['E', 'E']], [[('F#', 'F#'), ('F#', 'F#')], [('F#', 'F#'), ('F#', 'F#')]]]]\n",
- "Cost: 39 at size 32\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['Eb', 'Eb']]]]]\n",
- "Cost: 20 at size 32\n",
- "Sequence: [[[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]], [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]]]\n",
- "Cost: 13 at size 28\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']]]]]\n",
- "Cost: 12 at size 32\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], ['G', 'G']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], ['G', 'G']]]]]\n",
- "Cost: 39 at size 32\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['Eb', 'Eb']]]]]\n",
- "Cost: 20 at size 16\n",
- "Sequence: [[[['Abm', 'Abm'], ['Abm', 'Abm']], [['F#', 'F#'], ['F#', 'F#']]], [[['C#', 'C#'], [('C#', 'C#'), ('E', 'E')]], [['F#', 'F#']]]]\n",
- "Cost: 13 at size 28\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'Bb']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Cm', 'Cm'], ['Cm', 'F']]], [[['Ab', 'Ab'], ['Bb', 'Bb']]]]]\n",
- "Cost: 12 at size 32\n",
- "Sequence: [[[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], ['G', 'G']]]], [[[['Cm', 'Cm'], ['Cm', 'Cm']], [['Ab', 'Ab'], ['Ab', 'Ab']]], [[['Eb', 'Eb'], ['Eb', 'Eb']], [['G', 'G'], ['G', 'G']]]]]\n",
- "Cost: 39 at size 32\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['Eb', 'Eb']]]]]\n",
- "Cost: 11 at size 8\n",
- "Sequence: [[['Abm', 'Abm'], ['Abm', 'Abm']], [['Abm', ('Abm', 'E')], ['Eb']]]\n",
- "Cost: 33 at size 40\n",
- "Sequence: [[[[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ebm'], ['Ebm', 'Ebm']]], [[['Ebm', 'Ebm'], ['Ebm', 'Ebm']], [['Ebm', 'Ab'], ['Ebm', 'C#']]]], [[[['Ebm', 'Ebm'], ['B', 'B']], [['Ebm', 'Ebm'], ['E', 'E']]], [[[('Ebm', 'Ebm'), ('Ebm', 'Ab')], [('A', 'A'), ('D', 'D')]], [[('C#', 'C#'), ('F#', 'F#')], [('Eb', 'Eb'), ('Eb', 'Eb')]]]]]\n",
- "Cost: 16 at size 32\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Cm', 'Cm']], [['Eb', 'Eb'], ['Cm', 'Cm']]], [[['Ab', 'Ab'], ['Ab', 'Ab']], [['Ab', 'Ab'], ['Ab', 'Ab']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Eb', 'Eb'], ['Eb', 'Eb']]], [[['G', 'G'], ['G', 'G']], [['G', 'G'], ['G', 'G']]]]]\n",
- "Cost: 39 at size 32\n",
- "Sequence: [[[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['B', 'B'], ['B', 'B']]]], [[[['Eb', 'Eb'], ['Eb', 'Eb']], [['Abm', 'Abm'], ['Abm', 'Abm']]], [[['E', 'E'], ['E', 'E']], [['F#', 'F#'], ['Eb', 'Eb']]]]]\n",
- "Cost: 21 at size 32\n",
- "Sequence: [[[[['Abm', 'Abm'], ['B', 'B']], [['Abm', 'Abm'], ['B', 'B']]], [[['E', 'E'], ['Eb', 'Eb']], [['E', 'E'], ['Eb', 'Eb']]]], [[[['Abm', 'Abm'], ['F#', 'Eb']], [['Abm', 'Abm'], ['F#', 'Eb']]], [[['E', 'E'], ['Abm', 'Abm']], [['E', 'E'], ['Abm', 'Abm']]]]]\n",
- "Cost: 12 at size 34\n",
- "Sequence: [[[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], ['F#', 'F#']], [['Abm', 'Abm'], ['Abm', 'Abm']]]], [[[['F#', 'F#'], ['F#', 'F#']], [['C#', 'C#'], ['C#', 'C#']]], [[['E', 'E'], [('F#', 'F#'), ('F#', 'F#')]], [['Abm', 'Abm'], [('Abm', 'Abm')]]]]]\n",
- "Ze sum:345\n"
- ]
- }
- ],
- "source": [
- "the_sum = 0\n",
- "for start, end in zip(guichaoua_frontiers[:-1], guichaoua_frontiers[1:]):\n",
- " segment = bag_of_chords[start:end]\n",
- " size = len(segment)\n",
- " bag_of_patterns = sh.compute_patterns_with_ppp_and_antecedents_for_size(size)\n",
- " the_min = math.inf\n",
- " best_pattern = None\n",
- " for a_pattern in bag_of_patterns:\n",
- " this_polytope_cost = math.inf\n",
- " for i in range(len(a_pattern[0])):\n",
- " this_ppp_cost = pc.louboutaoua_cost(segment, a_pattern[0][i], a_pattern[3], a_pattern[4], a_pattern[5], a_pattern[6][i])\n",
- " if this_ppp_cost < this_polytope_cost:\n",
- " best_ppp_idx = i\n",
- " this_polytope_cost = this_ppp_cost\n",
- " cost = this_polytope_cost\n",
- " cost += pc.irregularities_penalty_guichaoua(adding_code = a_pattern[1], deleting_code = a_pattern[2], positive_penalty = positive_penalty, negative_penalty = negative_penalty)\n",
- " if cost < the_min:\n",
- " best_ppp = a_pattern[0][best_ppp_idx]\n",
- " the_min = cost\n",
- " the_min += sh.penalty_cost_guichaoua(size, target_size = 32, positive_segment_size_penalty = positive_segment_size_penalty, negative_segment_size_penalty = negative_segment_size_penalty)\n",
- " print(\"Cost: {} at size {}\".format(the_min, end-start))\n",
- " print(\"Sequence: {}\".format(pf.apply_chords_on_pattern(best_ppp,segment)))\n",
- " the_sum += the_min\n",
- "print(\"Ze sum:{}\".format(the_sum))"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
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- "varRefreshCmd": "print(var_dic_list())"
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- "varRefreshCmd": "cat(var_dic_list()) "
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diff --git a/Notebooks/Tutorial - model classes.ipynb b/Notebooks/Tutorial - model classes.ipynb
deleted file mode 100644
index c8fc8565cc2fb698645f3a5fcabe60046bc7201e..0000000000000000000000000000000000000000
--- a/Notebooks/Tutorial - model classes.ipynb
+++ /dev/null
@@ -1,2184 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Tutorial for the model classes."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "This notebook will briefly present some functionnalities implemented to cope with symbolic representation of music, as an upgrade of C. Louboutin's code."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It contains 2 files: note.py, chord.py.\n",
- "All these files represent different objects, used to handle musical information at different levels.\n",
- "\n",
- "A note is the most basic element, a chord is an aggregation of notes."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## note.py"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:39.980475Z",
- "start_time": "2020-10-30T15:35:39.976485Z"
- },
- "scrolled": true
- },
- "outputs": [],
- "source": [
- "from polytopes.model.note import Note"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Let's start with the Note object, which is the lowest-level object in music.\n",
- "\n",
- "The interest of defining such an object is that it allows us to control what is an acceptable note, and what isn't."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Initialization"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Particularily, a Note contains two attributes:\n",
- " - a number: between 0 and 11, which corresponds to the pitch classe of the note. 0 represent the C pitch class, and 11 the B pitch class. \n",
- " - a symbol: the classical representation of a note as a letter, with flat (\"b\") or sharp(\"#\") suffixes."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:41.270648Z",
- "start_time": "2020-10-30T15:35:41.258680Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "\"<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9)\""
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "note_a = Note('A')\n",
- "repr(note_a)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "We can access to these attributes directly on the object:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:42.215995Z",
- "start_time": "2020-10-30T15:35:42.211006Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'A'"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "note_a.symbol"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:42.708684Z",
- "start_time": "2020-10-30T15:35:42.702692Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "9"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "note_a.number"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A note can be defined by it's symbol or it's number."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:43.666480Z",
- "start_time": "2020-10-30T15:35:43.660496Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9)"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note('9')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:44.156913Z",
- "start_time": "2020-10-30T15:35:44.151926Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9)"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note('A')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:44.724397Z",
- "start_time": "2020-10-30T15:35:44.718413Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note('9') == Note('A')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Modification"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A Note object can also be modified.\n",
- "\n",
- "Modifying the number of a note will also modify it's symbol, and vice-versa, as both are linked."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:47.003807Z",
- "start_time": "2020-10-30T15:35:46.998822Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Before modification: <class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11)\n",
- "After modification: <class 'polytopes.model.note.Note'>(Symbol: 'D', Number: 2)\n",
- "After modifying its number: <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)\n"
- ]
- }
- ],
- "source": [
- "a_note = Note('B')\n",
- "print(\"Before modification: \" + str(a_note))\n",
- "\n",
- "a_note.symbol = 'D'\n",
- "print(\"After modification: \" + str(a_note))\n",
- "\n",
- "a_note.number = 7\n",
- "print(\"After modifying its number: \" + str(a_note))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Still, not every symbol or every number is acceptable. Hence, modifying or initializing a Note with a wrong number should not be tolerated."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:50.898336Z",
- "start_time": "2020-10-30T15:35:50.763098Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "ename": "InvalidNoteNumberException",
- "evalue": "The desired new number is too large to be a valid note.",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mInvalidNoteNumberException\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-10-8a3266453d6f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma_note\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnumber\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m15\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\note.py\u001b[0m in \u001b[0;36m_set_number\u001b[1;34m(self, number)\u001b[0m\n\u001b[0;32m 122\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidNoteNumberException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"The desired new number is not an integer, and is not valid.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 123\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 124\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidNoteNumberException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"The desired new number is too large to be a valid note.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 125\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 126\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mInvalidNoteNumberException\u001b[0m: The desired new number is too large to be a valid note."
- ]
- }
- ],
- "source": [
- "a_note.number = 15"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:52.920685Z",
- "start_time": "2020-10-30T15:35:52.908717Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "ename": "InvalidNoteSymbolException",
- "evalue": "This symbol is not a correct note symbol.",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mInvalidNoteSymbolException\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-11-20488d99cd64>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma_note\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msymbol\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'K'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\note.py\u001b[0m in \u001b[0;36m_set_symbol\u001b[1;34m(self, symbol)\u001b[0m\n\u001b[0;32m 87\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_number\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnumber_from_symbol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 88\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 89\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidNoteSymbolException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"This symbol is not a correct note symbol.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 90\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 91\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_get_number\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mInvalidNoteSymbolException\u001b[0m: This symbol is not a correct note symbol."
- ]
- }
- ],
- "source": [
- "a_note.symbol = 'K'"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Finally, sharp and flat symbols should both exist but shouldn't invalid tests, as they represent the same note.\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:55.400706Z",
- "start_time": "2020-10-30T15:35:55.396706Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note('A#') == Note(\"Bb\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "By default, a note symbol is set in flat convention. Still, it can be set to sharp with an argument in the constructor."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:35:57.297625Z",
- "start_time": "2020-10-30T15:35:57.293373Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Default: <class 'polytopes.model.note.Note'>(Symbol: 'Bb', Number: 10)\n",
- "In sharp: <class 'polytopes.model.note.Note'>(Symbol: 'A#', Number: 10)\n"
- ]
- }
- ],
- "source": [
- "a_note = Note(\"A#\")\n",
- "print(\"Default: \" + repr(a_note))\n",
- "a_note = Note(\"A#\", flat = False)\n",
- "print(\"In sharp: \" + repr(a_note))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Additionally, one can modify a note to be in the sharp or in the flat system."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:01.128721Z",
- "start_time": "2020-10-30T15:36:01.123584Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "In flat: <class 'polytopes.model.note.Note'>(Symbol: 'Bb', Number: 10)\n",
- "In sharp: <class 'polytopes.model.note.Note'>(Symbol: 'A#', Number: 10)\n"
- ]
- }
- ],
- "source": [
- "a_note = Note(\"Bb\")\n",
- "print(\"In flat: \" + repr(a_note))\n",
- "a_note.to_sharp()\n",
- "print(\"In sharp: \" + repr(a_note))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:02.901568Z",
- "start_time": "2020-10-30T15:36:02.896604Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "In sharp: <class 'polytopes.model.note.Note'>(Symbol: 'A#', Number: 10)\n",
- "In flat: <class 'polytopes.model.note.Note'>(Symbol: 'Bb', Number: 10)\n"
- ]
- }
- ],
- "source": [
- "a_note = Note(\"A#\", flat = False)\n",
- "print(\"In sharp: \" + repr(a_note))\n",
- "a_note.to_flat()\n",
- "print(\"In flat: \" + repr(a_note))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### chord.py"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:07.685939Z",
- "start_time": "2020-10-30T15:36:07.681950Z"
- },
- "scrolled": true
- },
- "outputs": [],
- "source": [
- "from polytopes.model.chord import Chord"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A chord is a set of mulitple pitches. Hence, a chord is defined from notes."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Initialization"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:10.163397Z",
- "start_time": "2020-10-30T15:36:10.158409Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.chord.Chord'>(Symbol: 'Am', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9), <class 'polytopes.model.note.Note'>(Symbol: 'C', Number: 0), <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4)])"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a = Note('A')\n",
- "c = Note('C')\n",
- "e = Note('E')\n",
- "Chord([a,c,e])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A chord must contain at least one note."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:12.076386Z",
- "start_time": "2020-10-30T15:36:12.061393Z"
- }
- },
- "outputs": [
- {
- "ename": "InvalidChordNotesException",
- "evalue": "Empty list of notes: a Chord must admit notes.",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mInvalidChordNotesException\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-18-bf07a16d637a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mChord\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, a_chord, redundancy)\u001b[0m\n\u001b[0;32m 71\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_notes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlocal_notes\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 72\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_notes\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 73\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidChordNotesException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Empty list of notes: a Chord must admit notes.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 74\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_triad\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtriad_from_notes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 75\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtriad\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mcst\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAMBIGUOUS\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# A redundant chord shouldn't be reordered as it corresponds to permutated chord (#TODO: rename the parameter ?)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mInvalidChordNotesException\u001b[0m: Empty list of notes: a Chord must admit notes."
- ]
- }
- ],
- "source": [
- "Chord([])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It can be directly defined by a list of numbers."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:14.333701Z",
- "start_time": "2020-10-30T15:36:14.325723Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.chord.Chord'>(Symbol: 'Am', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9), <class 'polytopes.model.note.Note'>(Symbol: 'C', Number: 0), <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4)])"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord([9, 0, 4])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "!!!!!!!!!!!! A chord **can't** be defined by a list of note symbols (at least not yet)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:17.596300Z",
- "start_time": "2020-10-30T15:36:17.581336Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "ename": "TypeError",
- "evalue": "int() argument must be a string, a bytes-like object or a number, not 'list'",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, a_chord, redundancy)\u001b[0m\n\u001b[0;32m 67\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 68\u001b[1;33m \u001b[0mnote_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNote\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma_note\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 69\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mnote_obj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_in_list_of_notes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlocal_notes\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_redundant\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mValueError\u001b[0m: invalid literal for int() with base 10: 'A'",
- "\nDuring handling of the above exception, another exception occurred:\n",
- "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-20-6a8e4e2a89cb>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mChord\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'A'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'C'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'E'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, a_chord, redundancy)\u001b[0m\n\u001b[0;32m 80\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# If it's a symbol\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 81\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 82\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_symbol\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mformat_symbol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma_chord\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 83\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_root\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mroot_from_symbol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 84\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_triad\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtriad_from_symbol\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36mformat_symbol\u001b[1;34m(symbol)\u001b[0m\n\u001b[0;32m 693\u001b[0m \"\"\"\n\u001b[0;32m 694\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 695\u001b[1;33m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msymbol\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 696\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidChordSymbolException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"The symbol isn't valid.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 697\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mTypeError\u001b[0m: int() argument must be a string, a bytes-like object or a number, not 'list'"
- ]
- }
- ],
- "source": [
- "Chord(['A', 'C', 'E'])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "However, a Chord can be defined by its symbol."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:21.550969Z",
- "start_time": "2020-10-30T15:36:21.545981Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.chord.Chord'>(Symbol: 'Abm', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8), <class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11), <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3)])"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord('Abmin')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Defining a Chord by its symbol or by its notes doesn't change the value of its attributes."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:23.347691Z",
- "start_time": "2020-10-30T15:36:23.342704Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord('Abmin') == Chord([8, 11, 3])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When instanciated, a Chord has several attributes:\n",
- " - notes: the list of notes of the Chord. These are Note objects.\n",
- " - symbol: the symbol of the Chord.\n",
- " - root: the root of the Chord.\n",
- " - triad: the type of triad of the Chord (maj or min) if it's a triad."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:25.458179Z",
- "start_time": "2020-10-30T15:36:25.453190Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4)]"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord = Chord('A')\n",
- "chord.notes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:27.419601Z",
- "start_time": "2020-10-30T15:36:27.414602Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'A'"
- ]
- },
- "execution_count": 24,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord.symbol"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:27.944160Z",
- "start_time": "2020-10-30T15:36:27.940510Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9)"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord.root"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:28.472353Z",
- "start_time": "2020-10-30T15:36:28.467367Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'A'"
- ]
- },
- "execution_count": 26,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord.triad"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Still, defined by its notes, a chord symbol can be ambiguous (ex: A6 (A with a sixth) is also F#m7)\n",
- "\n",
- "In that sense, a chord defined by its notes, when not a triad (perfect major or minor), will have its root and its symbol labelled as \"Ambiguous\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:30.499972Z",
- "start_time": "2020-10-30T15:36:30.495979Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.chord.Chord'>(Symbol: 'Ambiguous', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9), <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1), <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4), <class 'polytopes.model.note.Note'>(Symbol: 'Gb', Number: 6)])"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord([9, 1, 4, 6])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:32.195767Z",
- "start_time": "2020-10-30T15:36:32.187788Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "('Ambiguous', 'Ambiguous', 'Ambiguous')"
- ]
- },
- "execution_count": 28,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord([9, 1, 4, 6]).symbol, Chord([9, 1, 4, 6]).root, Chord([9, 1, 4, 6]).triad"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Modification"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "As for a Note, a Chord symbol or notes of a Chord can be directly modified."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:41.627387Z",
- "start_time": "2020-10-30T15:36:41.621403Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Before modif: <class 'polytopes.model.chord.Chord'>(Symbol: 'B', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11), <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3), <class 'polytopes.model.note.Note'>(Symbol: 'Gb', Number: 6)])\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Gb', Number: 6)]"
- ]
- },
- "execution_count": 29,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord = Chord('B')\n",
- "print(\"Before modif: %r\" % (a_chord))\n",
- "a_chord.notes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:43.296242Z",
- "start_time": "2020-10-30T15:36:43.289260Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "After modif: <class 'polytopes.model.chord.Chord'>(Symbol: 'Ab', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8), <class 'polytopes.model.note.Note'>(Symbol: 'C', Number: 0), <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3)])\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'C', Number: 0),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3)]"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord.notes = [8, 0, 3]\n",
- "print(\"After modif: %r\" % (a_chord))\n",
- "a_chord.notes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:45.000201Z",
- "start_time": "2020-10-30T15:36:44.994248Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "After 2nd modif: <class 'polytopes.model.chord.Chord'>(Symbol: 'A7', Notes: [<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9), <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1), <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4), <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)])\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)]"
- ]
- },
- "execution_count": 31,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord.symbol = 'A7'\n",
- "print(\"After 2nd modif: %r\" % (a_chord))\n",
- "a_chord.notes"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Still, the other attributes can't, as they do not hold enough information on the new Chord to re-instanciate it."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:47.441333Z",
- "start_time": "2020-10-30T15:36:47.427369Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "ename": "CantModifyAttribute",
- "evalue": "Not on my watch: you can't modify this attribute alone, you can only modify the notes or the symbol.",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mCantModifyAttribute\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-32-2efe97ae21f2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ma_chord\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mroot\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'B'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;32mc:\\users\\amarmore\\desktop\\projects\\phd main projects\\on git\\code\\polytopes and relation\\polytopes\\model\\chord.py\u001b[0m in \u001b[0;36m_not_on_my_watch\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 197\u001b[0m \u001b[0mRaises\u001b[0m \u001b[0man\u001b[0m \u001b[0merror\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mthese\u001b[0m \u001b[0mattributes\u001b[0m \u001b[0mmust\u001b[0m \u001b[0mbe\u001b[0m \u001b[0mfound\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0meither\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mnotes\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mthe\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mset\u001b[0m \u001b[0mindependantly\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mthey\u001b[0m \u001b[0mdon\u001b[0m\u001b[0;31m'\u001b[0m\u001b[0mt\u001b[0m \u001b[0mcontain\u001b[0m \u001b[0menough\u001b[0m \u001b[0minformation\u001b[0m \u001b[0mon\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mchord\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 198\u001b[0m \"\"\"\n\u001b[1;32m--> 199\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCantModifyAttribute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Not on my watch: you can't modify this attribute alone, you can only modify the notes or the symbol.\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 200\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 201\u001b[0m \u001b[0mroot\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mproperty\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_get_chord_root\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_not_on_my_watch\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mCantModifyAttribute\u001b[0m: Not on my watch: you can't modify this attribute alone, you can only modify the notes or the symbol."
- ]
- }
- ],
- "source": [
- "a_chord.root = 'B'"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Adding a note"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A note can be added to a Chord, which will modify all of its attributes accordingly."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:50.653614Z",
- "start_time": "2020-10-30T15:36:50.648627Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)]"
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord = Chord('A')\n",
- "chord.add_note(7)\n",
- "chord.notes"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Still, the added Note is already in the Chord, it won't be redundant."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:52.466659Z",
- "start_time": "2020-10-30T15:36:52.461672Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)]"
- ]
- },
- "execution_count": 34,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord.notes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:53.563757Z",
- "start_time": "2020-10-30T15:36:53.557773Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'A', Number: 9),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Db', Number: 1),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'E', Number: 4),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'G', Number: 7)]"
- ]
- },
- "execution_count": 35,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "chord.add_note(9)\n",
- "chord.notes"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:53.874511Z",
- "start_time": "2020-10-30T15:36:53.865535Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 36,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord([8, 11, 3, 11]) == Chord([8, 11, 3, 11, 11, 11, 11])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Notes in the chord"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The attributes \"notes\" of a chord is a list, and so, an individual Note can be retrieved from this list."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:57.674854Z",
- "start_time": "2020-10-30T15:36:57.667871Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8)"
- ]
- },
- "execution_count": 37,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord = Chord([8, 0, 3])\n",
- "a_chord.notes[0]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "For convenience though, the i-th element of the .notes attribute can be accessed directly by indexing the Chord, as in:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:36:58.339461Z",
- "start_time": "2020-10-30T15:36:58.334474Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8)"
- ]
- },
- "execution_count": 38,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord[0]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Inversely, the presence of a note in the chord can be tested as any element in a list:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:00.560917Z",
- "start_time": "2020-10-30T15:37:00.554933Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(True, False)"
- ]
- },
- "execution_count": 39,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note(8) in a_chord.notes, Note(7) in a_chord.notes"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Or, more simply, by testing if the Chord contains this note:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:02.719718Z",
- "start_time": "2020-10-30T15:37:02.714733Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(True, False)"
- ]
- },
- "execution_count": 40,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Note(8) in a_chord, Note(7) in a_chord"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "To know the number of notes in a chord, one can use the method get_nb_notes():"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:05.609149Z",
- "start_time": "2020-10-30T15:37:05.603649Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "3"
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord.get_nb_notes()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:08.439380Z",
- "start_time": "2020-10-30T15:37:08.434394Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "4"
- ]
- },
- "execution_count": 42,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord.add_note(7)\n",
- "a_chord.get_nb_notes()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Finally, one can want to access to the notes as numbers, and there's a function for that:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:10.143551Z",
- "start_time": "2020-10-30T15:37:10.138568Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 7]"
- ]
- },
- "execution_count": 43,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Chord with redundancy"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Defined that way, chords doesn't allow repetitions in its notes (which is logical since notes are expressed in pitch classes).\n",
- "\n",
- "This could become a problem when manipulating theoretical objects, for example in a context of optimal transport between chords.\n",
- "\n",
- "To solve this problem, a parameter of the constructor can allow redundancy in the notes of a chord.\n",
- "\n",
- "It is called redundancy and is a boolean."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:12.084047Z",
- "start_time": "2020-10-30T15:37:12.077072Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'Eb', Number: 3),\n",
- " <class 'polytopes.model.note.Note'>(Symbol: 'B', Number: 11)]"
- ]
- },
- "execution_count": 44,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "Chord([8, 11, 3, 11], redundancy = True).notes"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "When the object is created redundant, it remains redundant when its notes are modified."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:14.444702Z",
- "start_time": "2020-10-30T15:37:14.439716Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 8]"
- ]
- },
- "execution_count": 45,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "redundant_chord = Chord([8, 0, 3], redundancy = True)\n",
- "redundant_chord.add_note(8)\n",
- "redundant_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:15.852253Z",
- "start_time": "2020-10-30T15:37:15.844280Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 4, 3]"
- ]
- },
- "execution_count": 46,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "redundant_chord = Chord([8, 0, 3], redundancy = True)\n",
- "redundant_chord.notes = [8, 0, 3, 4, 3]\n",
- "redundant_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Conversely, a chord created without redundancy (default behavior) cannot be modified into a redundant chord."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 47,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:16.964692Z",
- "start_time": "2020-10-30T15:37:16.958700Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 4]"
- ]
- },
- "execution_count": 47,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "default_chord = Chord([8, 0, 3], redundancy = False) # or simply Chord([8, 0, 3])\n",
- "default_chord.notes = [8, 0, 3, 4, 3]\n",
- "default_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It also works when defined by its symbol."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 48,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:18.561793Z",
- "start_time": "2020-10-30T15:37:18.555808Z"
- },
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 4]"
- ]
- },
- "execution_count": 48,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "default_chord = Chord('A')\n",
- "default_chord.notes = [8, 0, 3, 4, 3]\n",
- "default_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 49,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:19.882635Z",
- "start_time": "2020-10-30T15:37:19.875653Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[8, 0, 3, 4, 3]"
- ]
- },
- "execution_count": 49,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "redundant_chord = Chord('A', redundancy = True)\n",
- "redundant_chord.notes = [8, 0, 3, 4, 3]\n",
- "redundant_chord.get_numbers()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It should be noted that the notes of a triad are ordered when the chord is not redundant, and aren't ordered when the chord is.\n",
- "\n",
- "This is made to allow permutations when the chord is redundant, and to be more consistent with the real chord when it's not."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 50,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:20.603827Z",
- "start_time": "2020-10-30T15:37:20.597844Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "([8, 0, 3], <class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8))"
- ]
- },
- "execution_count": 50,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "default_chord = Chord('A')\n",
- "default_chord.notes = [3, 8, 0]\n",
- "default_chord.get_numbers(), default_chord.root"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T15:37:22.478662Z",
- "start_time": "2020-10-30T15:37:22.470683Z"
- }
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "([3, 8, 0], <class 'polytopes.model.note.Note'>(Symbol: 'Ab', Number: 8))"
- ]
- },
- "execution_count": 51,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "redundant_chord = Chord('A', redundancy = True)\n",
- "redundant_chord.notes = [3, 8, 0]\n",
- "redundant_chord.get_numbers(), redundant_chord.root"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## polytope.py"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "ExecuteTime": {
- "end_time": "2020-10-30T10:55:12.222629Z",
- "start_time": "2020-10-30T10:55:12.139304Z"
- }
- },
- "outputs": [
- {
- "ename": "NameError",
- "evalue": "name 'anymore' is not defined",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m<ipython-input-1-8e7a5bdb8a47>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mEDIT\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0manymore\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
- "\u001b[1;31mNameError\u001b[0m: name 'anymore' is not defined"
- ]
- }
- ],
- "source": [
- "EDIT: not anymore"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {},
- "outputs": [],
- "source": [
- "from polytope import Polytope"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "A Polytope is an object defined to represent one or several musical bars, in the context of structural segmentation.\n",
- "\n",
- "Hence, it is defined by several chords."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 52,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Gm', Notes: [<class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'D', Number: 2)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Gm', Notes: [<class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'D', Number: 2)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Gm', Notes: [<class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'D', Number: 2)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Gm', Notes: [<class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'D', Number: 2)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Ab', Notes: [<class 'note.Note'>(Symbol: 'Ab', Number: 8), <class 'note.Note'>(Symbol: 'C', Number: 0), <class 'note.Note'>(Symbol: 'Eb', Number: 3)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Bbm', Notes: [<class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'Db', Number: 1), <class 'note.Note'>(Symbol: 'F', Number: 5)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Bbm', Notes: [<class 'note.Note'>(Symbol: 'Bb', Number: 10), <class 'note.Note'>(Symbol: 'Db', Number: 1), <class 'note.Note'>(Symbol: 'F', Number: 5)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Eb', Notes: [<class 'note.Note'>(Symbol: 'Eb', Number: 3), <class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10)]),\n",
- " <class 'chord.Chord'>(Symbol: 'Eb', Notes: [<class 'note.Note'>(Symbol: 'Eb', Number: 3), <class 'note.Note'>(Symbol: 'G', Number: 7), <class 'note.Note'>(Symbol: 'Bb', Number: 10)])]"
- ]
- },
- "execution_count": 52,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "some_chords = [[8, 0, 3], [8, 0, 3], [8, 0, 3], [8, 0, 3], [7, 10, 2], [7, 10, 2], [7, 10, 2], [7, 10, 2], [8, 0, 3], [8, 0, 3], [8, 0, 3], [8, 0, 3], [10, 1, 5], [10, 1, 5], [3, 7, 10], [3, 7, 10]]\n",
- "polytope = Polytope(some_chords)\n",
- "polytope.chords"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "To facilitates the visualization of polytopes, when they contain 16 elements, a 4 by 4 visualization function has been implemented."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 53,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "16"
- ]
- },
- "execution_count": 53,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_length()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 54,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0 [8, 0, 3] 1 [8, 0, 3] \n",
- "2 [8, 0, 3] 3 [8, 0, 3] \n",
- "\n",
- "4 [7, 10, 2] 5 [7, 10, 2] \n",
- "6 [7, 10, 2] 7 [7, 10, 2] \n",
- "\n",
- "8 [8, 0, 3] 9 [8, 0, 3] \n",
- "10 [8, 0, 3] 11 [8, 0, 3] \n",
- "\n",
- "12 [10, 1, 5] 13 [10, 1, 5] \n",
- "14 [3, 7, 10] 15 [3, 7, 10] \n",
- "\n"
- ]
- }
- ],
- "source": [
- "polytope.pretty_print()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 55,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0 Ab 1 Ab \n",
- "2 Ab 3 Ab \n",
- "\n",
- "4 Gm 5 Gm \n",
- "6 Gm 7 Gm \n",
- "\n",
- "8 Ab 9 Ab \n",
- "10 Ab 11 Ab \n",
- "\n",
- "12 Bbm 13 Bbm \n",
- "14 Eb 15 Eb \n",
- "\n"
- ]
- }
- ],
- "source": [
- "polytope.pretty_print(symbols = True)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "It is also possible to access to the chords of a polytope as a list of Chord symbols or by lists of the note numbers:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 56,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Gm',\n",
- " 'Gm',\n",
- " 'Gm',\n",
- " 'Gm',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Bbm',\n",
- " 'Bbm',\n",
- " 'Eb',\n",
- " 'Eb']"
- ]
- },
- "execution_count": 56,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_list_of_symbols()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 57,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[[8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [10, 1, 5],\n",
- " [10, 1, 5],\n",
- " [3, 7, 10],\n",
- " [3, 7, 10]]"
- ]
- },
- "execution_count": 57,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_list_of_numbers()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "One of the interest of the polytopical paradigm is to reorder the elements in a non sequential way.\n",
- "\n",
- "In that context, a promising framework, developed in [Louboutin 2017], is the \"Primer Preseving Permutation\" system, or PPP. Here, it is possible to obtain the ppp of a polytope with the methods:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 58,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[[8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [10, 1, 5],\n",
- " [10, 1, 5],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [3, 7, 10],\n",
- " [3, 7, 10]]"
- ]
- },
- "execution_count": 58,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_ppp(1).get_list_of_numbers() # The argument is the index of the desired ppp."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 59,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[<polytop.Polytop at 0x23b26514808>,\n",
- " <polytop.Polytop at 0x23b26514908>,\n",
- " <polytop.Polytop at 0x23b26514f08>,\n",
- " <polytop.Polytop at 0x23b26514608>,\n",
- " <polytop.Polytop at 0x23b26514548>,\n",
- " <polytop.Polytop at 0x23b26514208>]"
- ]
- },
- "execution_count": 59,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_all_ppps()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 60,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Ab',\n",
- " 'Gm',\n",
- " 'Gm',\n",
- " 'Bbm',\n",
- " 'Bbm',\n",
- " 'Gm',\n",
- " 'Gm',\n",
- " 'Eb',\n",
- " 'Eb']"
- ]
- },
- "execution_count": 60,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_all_ppps()[3].get_list_of_symbols()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Finally, it is also possible to add a Chord to a polytope."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 61,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "17"
- ]
- },
- "execution_count": 61,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.add_chord('Abmin')\n",
- "polytope.get_length()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 62,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[[8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [7, 10, 2],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [8, 0, 3],\n",
- " [10, 1, 5],\n",
- " [10, 1, 5],\n",
- " [3, 7, 10],\n",
- " [3, 7, 10],\n",
- " [8, 11, 3]]"
- ]
- },
- "execution_count": 62,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "polytope.get_list_of_numbers()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.7.5"
- },
- "toc": {
- "base_numbering": 1,
- "nav_menu": {},
- "number_sections": true,
- "sideBar": true,
- "skip_h1_title": false,
- "title_cell": "Table of Contents",
- "title_sidebar": "Contents",
- "toc_cell": false,
- "toc_position": {},
- "toc_section_display": true,
- "toc_window_display": false
- },
- "varInspector": {
- "cols": {
- "lenName": 16,
- "lenType": 16,
- "lenVar": 40
- },
- "kernels_config": {
- "python": {
- "delete_cmd_postfix": "",
- "delete_cmd_prefix": "del ",
- "library": "var_list.py",
- "varRefreshCmd": "print(var_dic_list())"
- },
- "r": {
- "delete_cmd_postfix": ") ",
- "delete_cmd_prefix": "rm(",
- "library": "var_list.r",
- "varRefreshCmd": "cat(var_dic_list()) "
- }
- },
- "types_to_exclude": [
- "module",
- "function",
- "builtin_function_or_method",
- "instance",
- "_Feature"
- ],
- "window_display": false
- }
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- "nbformat": 4,
- "nbformat_minor": 2
-}