├── funding.yml ├── chord.3rdL.csv ├── chord.4thL.csv ├── chord.prog.sankey.PNG ├── Musical-chord-progressions.Rproj ├── .gitattributes ├── .gitignore ├── README.md ├── chord.1stL.csv ├── Chord progression probability.R ├── LICENSE.txt └── chord.2ndL.csv /funding.yml: -------------------------------------------------------------------------------- 1 | patreon: amitkohli -------------------------------------------------------------------------------- /chord.3rdL.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataStrategist/Musical-chord-progressions/HEAD/chord.3rdL.csv -------------------------------------------------------------------------------- /chord.4thL.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataStrategist/Musical-chord-progressions/HEAD/chord.4thL.csv -------------------------------------------------------------------------------- /chord.prog.sankey.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/DataStrategist/Musical-chord-progressions/HEAD/chord.prog.sankey.PNG -------------------------------------------------------------------------------- /Musical-chord-progressions.Rproj: -------------------------------------------------------------------------------- 1 | Version: 1.0 2 | 3 | RestoreWorkspace: Default 4 | SaveWorkspace: Default 5 | AlwaysSaveHistory: Default 6 | 7 | EnableCodeIndexing: Yes 8 | UseSpacesForTab: Yes 9 | NumSpacesForTab: 2 10 | Encoding: UTF-8 11 | 12 | RnwWeave: knitr 13 | LaTeX: pdfLaTeX 14 | -------------------------------------------------------------------------------- /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | 4 | # Custom for Visual Studio 5 | *.cs diff=csharp 6 | *.sln merge=union 7 | *.csproj merge=union 8 | *.vbproj merge=union 9 | *.fsproj merge=union 10 | *.dbproj merge=union 11 | 12 | # Standard to msysgit 13 | *.doc diff=astextplain 14 | *.DOC diff=astextplain 15 | *.docx diff=astextplain 16 | *.DOCX diff=astextplain 17 | *.dot diff=astextplain 18 | *.DOT diff=astextplain 19 | *.pdf diff=astextplain 20 | *.PDF diff=astextplain 21 | *.rtf diff=astextplain 22 | *.RTF diff=astextplain 23 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Windows image file caches 2 | Thumbs.db 3 | ehthumbs.db 4 | 5 | # Folder config file 6 | Desktop.ini 7 | 8 | # Recycle Bin used on file shares 9 | $RECYCLE.BIN/ 10 | 11 | # Windows Installer files 12 | *.cab 13 | *.msi 14 | *.msm 15 | *.msp 16 | 17 | # ========================= 18 | # Operating System Files 19 | # ========================= 20 | 21 | # OSX 22 | # ========================= 23 | 24 | .DS_Store 25 | .AppleDouble 26 | .LSOverride 27 | 28 | # Icon must end with two \r 29 | Icon 30 | 31 | # Thumbnails 32 | ._* 33 | 34 | # Files that might appear on external disk 35 | .Spotlight-V100 36 | .Trashes 37 | 38 | # Directories potentially created on remote AFP share 39 | .AppleDB 40 | .AppleDesktop 41 | Network Trash Folder 42 | Temporary Items 43 | .apdisk 44 | .Rproj.user 45 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Musical-chord-progressions 2 | ========================== 3 | 4 | An analysis of hooktheory's db, represented as a sankey plot 5 |

This represents an visualization of all normalized chord progressions in the 6 | hooktheory database. The scales are normalized so that for example C -> G -> Am is the same as A -> E -> Fm 7 | (what's important for this is the progression not the key.

8 |

Notes: The database 'starts' with 29 chords. For every subsequent step the number of chords transitioned into 9 | keeps growing (which is expected), but for the purpose of this visualization, I only keep the original 29 chords. Also, 10 | since the thickness of the lines I'm plotting are in and of themselves probabilities, it's not fully correct to treat 11 | them the same. Very lazily, I just normalized all probabilities across each level so that it adds up to 1, I'm sure 12 | there's a better way. Community is invited to improve! 13 | 14 | Check writeup here 15 | -------------------------------------------------------------------------------- /chord.1stL.csv: -------------------------------------------------------------------------------- 1 | "L1","child_path","chord_HTML","chord_ID","probability" 2 | "1","","","","","" 3 | "2","1","1","I","1","0.154" 4 | "3","2","4","IV","4","0.148" 5 | "4","3","5","V","5","0.14" 6 | "5","4","6","vi","6","0.138" 7 | "6","5","2","ii","2","0.047" 8 | "7","6","3","iii","3","0.033" 9 | "8","7","27","ii⁷","27","0.02" 10 | "9","8","47","IV⁷","47","0.017" 11 | "10","9","16","I⁶","16","0.017" 12 | "11","10","67","vi⁷","67","0.016" 13 | "12","11","56","V⁶","56","0.015" 14 | "13","12","5/6","V/vi","5/6","0.013" 15 | "14","13","b7","♭VII","b7","0.012" 16 | "15","14","164","I⁶₄","164","0.012" 17 | "16","15","57","V⁷","57","0.011" 18 | "17","16","37","iii⁷","37","0.011" 19 | "18","17","5/5","V/V","5/5","0.007" 20 | "19","18","464","IV⁶₄","464","0.006" 21 | "20","19","17","I⁷","17","0.006" 22 | "21","20","664","vi⁶₄","664","0.006" 23 | "22","21","564","V⁶₄","564","0.006" 24 | "23","22","46","IV⁶","46","0.006" 25 | "24","23","57/6","V⁷/vi","57/6","0.006" 26 | "25","24","642","vi⁴₂","642","0.004" 27 | "26","25","36","iii⁶","36","0.004" 28 | "27","26","66","vi⁶","66","0.004" 29 | "28","27","b6","♭VI","b6","0.004" 30 | "29","28","b3","♭III","b3","0.004" 31 | -------------------------------------------------------------------------------- /Chord progression probability.R: -------------------------------------------------------------------------------- 1 | library(rjson) 2 | library(reshape2) 3 | library(googleVis) 4 | 5 | 6 | chords <- c("1", "4", "5", "6", "2", "3", "27", "47", "16", "67", "56", "5/6", "b7", "164", "57", "37", "5/5", "464", "17", "664", "564", "46", "57/6", "642", "36", "66", "b6", "b3") 7 | 8 | # test 9 | # Url <- "http://www.hooktheory.com/api/trends/stats?cp=1,1" 10 | # document <- fromJSON(file=Url, method='C') 11 | # doc.melt <- melt(document) 12 | # doc.df <- dcast(doc.melt, L1 ~ L2, value.var='value') 13 | 14 | 15 | # get data ---------------------- 16 | 17 | # STEP 1 get starting probabilities: 18 | 19 | # (For all these following sections tho... first see if the files were already 20 | # written... no need to hit the API unneccessarily, no? :) ) 21 | if (file.exists("chord.1stL.csv")){ 22 | all.df <- read.csv("chord.1stL.csv") 23 | } else { 24 | Url <- "http://www.hooktheory.com/api/trends/stats" 25 | document <- fromJSON(file=Url, method='C') 26 | doc.melt <- melt(document) 27 | doc.df <- dcast(doc.melt, L1 ~ L2, value.var='value') 28 | 29 | all.df <- "" 30 | all.df <- rbind(all.df,doc.df) 31 | 32 | all.df[,c(2,5)] 33 | write.table(all.df, file="chord.1stL.csv",sep=",") 34 | } 35 | 36 | # STEP 2 get chord 1 -> 2 37 | 38 | if (file.exists("chord.2ndtL.csv")){ 39 | all2.df <- read.csv("chord.2ndtL.csv") 40 | } else { 41 | all2.df <- "" 42 | for (i in 1:length(chords)){ 43 | q <- chords[i] 44 | Url <- paste("http://www.hooktheory.com/api/trends/stats?cp=",q,sep="") 45 | document <- fromJSON(file=Url, method='C') 46 | if(length(document)!=0){ 47 | doc.melt <- melt(document) 48 | doc.df <- dcast(doc.melt, L1 ~ L2, value.var='value') 49 | all2.df <- rbind(all2.df,doc.df) 50 | Sys.sleep(.1) 51 | } 52 | } 53 | all2.df[,c(2,5)] 54 | write.table(all2.df, file="chord.2ndL.csv",sep=",") 55 | } 56 | 57 | # STEP 3 get chord 2 -> 3 58 | 59 | if (file.exists("chord.3rdL.csv")){ 60 | all3.df <- read.csv("chord.3rdL.csv") 61 | } else { 62 | all3.df <- "" 63 | for (i in 1:length(chords)){ 64 | for (j in 1:length(chords)){ 65 | q <- paste(chords[i],chords[j],sep=",") 66 | Url <- paste("http://www.hooktheory.com/api/trends/stats?cp=",q,sep="") 67 | document <- fromJSON(file=Url, method='C') 68 | if(length(document)!=0){ 69 | doc.melt <- melt(document) 70 | doc.df <- dcast(doc.melt, L1 ~ L2, value.var='value') 71 | all3.df <- rbind(all3.df,doc.df) 72 | Sys.sleep(.1) 73 | } 74 | } 75 | } 76 | all3.df[,c(2,5)] 77 | write.table(all3.df, file="chord.3rdL.csv",sep=",") 78 | } 79 | 80 | # STEP 4 get chord 3 -> 4 81 | all4.df <- "" 82 | 83 | if (file.exists("chord.4thL.csv")){ 84 | all4.df <- read.csv("chord.4thL.csv") 85 | } else { 86 | for (i in 1:length(chords)){ 87 | for (j in 1:length(chords)){ 88 | for (k in 1:length(chords)){ 89 | q <- paste(chords[i], chords[j], chords[k],sep=",") 90 | Url <- paste("http://www.hooktheory.com/api/trends/stats?cp=",q,sep="") 91 | document <- fromJSON(file=Url, method='C') 92 | if(length(document)!=0){ 93 | doc.melt <- melt(document) 94 | doc.df <- dcast(doc.melt, L1 ~ L2, value.var='value') 95 | all4.df <- rbind(all4.df,doc.df) 96 | Sys.sleep(.1) 97 | } 98 | } 99 | } 100 | } 101 | all4.df[,c(2,5)] 102 | write.table(all4.df, file="chord.4thL.csv",sep=",") 103 | } 104 | 105 | ### OK, Now build sankeys! ========================================= 106 | 107 | # Drop first rows, which are always empty: 108 | all2.df <- all2.df[2:nrow(all2.df),] 109 | all3.df <- all3.df[2:nrow(all3.df),] 110 | all4.df <- all4.df[2:nrow(all4.df),] 111 | 112 | # um... not sure why this is contaminated... but: 113 | all4.df <- all4.df[9:nrow(all4.df),] 114 | 115 | ## First level 116 | d <- data.frame(FROM=rep("start",29), TO=all.df[1:29,2], 117 | PROB=as.numeric(all.df[1:29,5])) 118 | 119 | ## Second level 120 | all2.df <- all2.df[2:nrow(all2.df),] 121 | d2 <- as.data.frame(matrix(unlist(strsplit(all2.df[,2], ",")), 122 | ncol=2,byrow=TRUE)) 123 | names(d2) <- c("FROM", "TO") 124 | d2$PROB <- as.numeric(all2.df[,5]) 125 | 126 | #This is how many choords are at this level! 127 | length(unique(d2[,2])) 128 | 129 | # In order to identify different levels, keep adding stars to new 130 | # levels (otherwise it wouldn't even draw due to suspected cyclicity) 131 | d2[,2] <- paste(d2[,2]," ",sep="") 132 | 133 | # Problem! There's 128 chords at level 3! so let's be a bit picky 134 | # d2 <- d2[d2[,3]>.06,] # where the cutoff is kinda guessed 135 | # or simply restrict d2 to original list of chords 136 | d2 <- d2[gsub("\\ ","",d2[,2]) %in% chords,] 137 | 138 | 139 | ## Third level 140 | # first simplify for subsequent splitting: 141 | all3.df.clean <- as.character(all3.df[,2]) 142 | 143 | d3 <- as.data.frame(matrix(unlist(strsplit(all3.df.clean, ",")), 144 | ncol=3,byrow=TRUE)) 145 | 146 | #Drop first level chords for now since I don't care (and anyway can't use em) 147 | d3 <- d3[,c(2,3)] 148 | names(d3) <- c("FROM", "TO") 149 | d3$PROB <- as.numeric(all3.df[,5]) 150 | 151 | #This is how many choords are at this level! 152 | length(unique(d3[,2])) 153 | 154 | d3[,1] <- paste(d3[,1]," ",sep="") 155 | d3[,2] <- paste(d3[,2]," ",sep="") 156 | 157 | d3 <- d3[gsub("\\ ","",d3[,1]) %in% chords,] 158 | d3 <- d3[gsub("\\ \\ ","",d3[,2]) %in% chords,] 159 | 160 | 161 | ## Forf level 162 | all4.df.clean <- as.character(all4.df[,2]) 163 | 164 | d4 <- as.data.frame(matrix(unlist(strsplit(all4.df.clean, ",")), 165 | ncol=4,byrow=TRUE)) 166 | 167 | #Drop first and second levels for now since I don't care 168 | d4 <- d4[,c(3, 4)] 169 | names(d4) <- c("FROM", "TO") 170 | d4$PROB <- as.numeric(all4.df[,5]) 171 | 172 | #This is how many choords are at this level! 173 | length(unique(d4[,2])) 174 | 175 | d4[,1] <- paste(d4[,1]," ",sep="") 176 | d4[,2] <- paste(d4[,2]," ",sep="") 177 | 178 | d4 <- d4[gsub("\\ \\ ","",d4[,1]) %in% chords,] 179 | d4 <- d4[gsub("\\ \\ \\ ","",d4[,2]) %in% chords,] 180 | 181 | 182 | # ok, so far we're good... BUT: since we're dealing with probabilities, we 183 | # probably need to somehow normalize the columns... if anything, for 184 | # presentation purposes. So, I don't know how... propose to kinda normalize 185 | # totals to 1 186 | 187 | sum(d[,3], na.rm=T); sum(d2[,3], na.rm=T); sum(d3[,3], na.rm=T); sum(d4[,3], na.rm=T) 188 | 189 | d[,3] <- d[,3] / 0.867 190 | d2[,3] <- d2[,3] / 22.71 191 | d3[,3] <- d3[,3] / 478.685 192 | d4[,3] <- d4[,3] / 1308.849 193 | 194 | d.all <- rbind(d, d2, d3, d4) 195 | d.plot <- gvisSankey(d.all, from="FROM", to="TO", weight="PROB", 196 | options=list( 197 | width=1000, height=1050, 198 | sankey="{link: {color: { fill: '#d799ae' } }, 199 | node: { width: 15, 200 | color: { fill: '#a61d4c' }, 201 | label: { fontName: 'Garamond', 202 | fontSize: 20, 203 | bold: true} }}")) 204 | plot(d.plot) 205 | 206 | ########################################################## 207 | 208 | 209 | 210 | 211 | 212 | # ==============================For song stuff ------------ 213 | 214 | # get ratings 215 | allScores <-"" 216 | fileUrl <-c("http://www.metrolyrics.com/rolling-stone-top500-1.html", 217 | "http://www.metrolyrics.com/rolling-stone-top500-2.html", 218 | "http://www.metrolyrics.com/rolling-stone-top500-3.html", 219 | "http://www.metrolyrics.com/rolling-stone-top500-4.html", 220 | "http://www.metrolyrics.com/rolling-stone-top500.html") 221 | 222 | # fileUrl <- "http://www.metrolyrics.com/rolling-stone-top500-1.html" 223 | # fileUrl <- "http://www.metrolyrics.com/rolling-stone-top500-2.html" 224 | # fileUrl <- "http://www.metrolyrics.com/rolling-stone-top500-3.html" 225 | # fileUrl <- "http://www.metrolyrics.com/rolling-stone-top500-4.html" 226 | # fileUrl <- "http://www.metrolyrics.com/rolling-stone-top500.html" 227 | 228 | 229 | for (i in 1:5){ 230 | doc <- htmlTreeParse(fileUrl[i],useInternal=TRUE) 231 | # doc <- htmlTreeParse(fileUrl,useInternal=TRUE) 232 | scores <- xpathSApply(doc,"//li",xmlValue) 233 | scores <- gsub("\n","ƒ", scores) 234 | scores <- gsub(" Lyrics","", scores) 235 | scores <- gsub("\t","ƒ", scores) 236 | scores <- gsub("ƒƒƒ","ƒ", scores) 237 | scores <- scores[10:109] 238 | scores <- substring(scores, 2, nchar(scores)-1) 239 | scores.parsed <- strsplit(scores,"ƒ") 240 | 241 | scores.melt <- melt(scores.parsed) 242 | scores.m <- matrix(scores.melt$value,ncol=3,byrow=T) 243 | scores.df <- data.frame(scores.m) 244 | head(scores.df) 245 | allScores <- rbind(allScores,scores.df) 246 | } 247 | 248 | colnames(allScores) <- c("Rank", "Song", "Author") 249 | sort.df <- with(allScores, allScores[order(as.numeric(allScores$Rank)) , ]) 250 | head(sort.df) 251 | 252 | head(allScores) 253 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 1 | License for data unknown. 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If you wish to incorporate parts of the Program into other free 256 | programs whose distribution conditions are different, write to the author 257 | to ask for permission. For software which is copyrighted by the Free 258 | Software Foundation, write to the Free Software Foundation; we sometimes 259 | make exceptions for this. Our decision will be guided by the two goals 260 | of preserving the free status of all derivatives of our free software and 261 | of promoting the sharing and reuse of software generally. 262 | 263 | NO WARRANTY 264 | 265 | 11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY 266 | FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN 267 | OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES 268 | PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED 269 | OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF 270 | MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS 271 | TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE 272 | PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, 273 | REPAIR OR CORRECTION. 274 | 275 | 12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 276 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR 277 | REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, 278 | INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING 279 | OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED 280 | TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY 281 | YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER 282 | PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE 283 | POSSIBILITY OF SUCH DAMAGES. 284 | 285 | END OF TERMS AND CONDITIONS 286 | 287 | How to Apply These Terms to Your New Programs 288 | 289 | If you develop a new program, and you want it to be of the greatest 290 | possible use to the public, the best way to achieve this is to make it 291 | free software which everyone can redistribute and change under these terms. 292 | 293 | To do so, attach the following notices to the program. It is safest 294 | to attach them to the start of each source file to most effectively 295 | convey the exclusion of warranty; and each file should have at least 296 | the "copyright" line and a pointer to where the full notice is found. 297 | 298 | {description} 299 | Copyright (C) {year} {fullname} 300 | 301 | This program is free software; you can redistribute it and/or modify 302 | it under the terms of the GNU General Public License as published by 303 | the Free Software Foundation; either version 2 of the License, or 304 | (at your option) any later version. 305 | 306 | This program is distributed in the hope that it will be useful, 307 | but WITHOUT ANY WARRANTY; without even the implied warranty of 308 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 309 | GNU General Public License for more details. 310 | 311 | You should have received a copy of the GNU General Public License along 312 | with this program; if not, write to the Free Software Foundation, Inc., 313 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. 314 | 315 | Also add information on how to contact you by electronic and paper mail. 316 | 317 | If the program is interactive, make it output a short notice like this 318 | when it starts in an interactive mode: 319 | 320 | Gnomovision version 69, Copyright (C) year name of author 321 | Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 322 | This is free software, and you are welcome to redistribute it 323 | under certain conditions; type `show c' for details. 324 | 325 | The hypothetical commands `show w' and `show c' should show the appropriate 326 | parts of the General Public License. Of course, the commands you use may 327 | be called something other than `show w' and `show c'; they could even be 328 | mouse-clicks or menu items--whatever suits your program. 329 | 330 | You should also get your employer (if you work as a programmer) or your 331 | school, if any, to sign a "copyright disclaimer" for the program, if 332 | necessary. Here is a sample; alter the names: 333 | 334 | Yoyodyne, Inc., hereby disclaims all copyright interest in the program 335 | `Gnomovision' (which makes passes at compilers) written by James Hacker. 336 | 337 | {signature of Ty Coon}, 1 April 1989 338 | Ty Coon, President of Vice 339 | 340 | This General Public License does not permit incorporating your program into 341 | proprietary programs. If your program is a subroutine library, you may 342 | consider it more useful to permit linking proprietary applications with the 343 | library. If this is what you want to do, use the GNU Lesser General 344 | Public License instead of this License. 345 | 346 | -------------------------------------------------------------------------------- /chord.2ndL.csv: -------------------------------------------------------------------------------- 1 | "L1","child_path","chord_HTML","chord_ID","probability" 2 | "1","","","","","" 3 | "2","1","1,5","V","5","0.265" 4 | "3","2","1,4","IV","4","0.184" 5 | "4","3","1,6","vi","6","0.1" 6 | "5","4","1,2","ii","2","0.052" 7 | "6","5","1,56","V⁶","56","0.052" 8 | "7","6","1,3","iii","3","0.035" 9 | "8","7","1,b7","♭VII","b7","0.021" 10 | "9","8","1,16","I⁶","16","0.018" 11 | "10","9","1,164","I⁶₄","164","0.017" 12 | "11","10","1,464","IV⁶₄","464","0.016" 13 | "12","11","1,5/6","V/vi","5/6","0.015" 14 | "13","12","1,27","ii⁷","27","0.012" 15 | "14","13","1,47","IV⁷","47","0.011" 16 | "15","14","1,364","iii⁶₄","364","0.01" 17 | "16","15","1,5/5","V/V","5/5","0.01" 18 | 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"248","3","67,4","IV","4","0.1" 250 | "249","4","67,37","iii⁷","37","0.059" 251 | "250","5","67,47","IV⁷","47","0.043" 252 | "251","6","67,164","I⁶₄","164","0.037" 253 | "252","7","67,1","I","1","0.034" 254 | "253","8","67,6","vi","6","0.032" 255 | "254","9","67,2","ii","2","0.032" 256 | "255","10","67,3","iii","3","0.025" 257 | "256","11","67,57/5","V⁷/V","57/5","0.02" 258 | "257","12","67,642","vi⁴₂","642","0.019" 259 | "258","13","67,56","V⁶","56","0.016" 260 | "259","14","67,46","IV⁶","46","0.013" 261 | "260","15","67,17","I⁷","17","0.013" 262 | "261","16","67,5/5","V/V","5/5","0.012" 263 | "262","17","67,142","I⁴₂","142","0.009" 264 | "263","18","67,57","V⁷","57","0.008" 265 | "264","19","67,16","I⁶","16","0.007" 266 | "265","20","67,643","vi⁴₃","643","0.007" 267 | "266","21","67,b57","v⁷","b57","0.006" 268 | "267","22","67,665","vi⁶₅","665","0.006" 269 | "268","23","67,4/2","IV/ii","4/2","0.006" 270 | "269","24","67,M17","Ib7","M17","0.006" 271 | "270","1","56,6","vi","6","0.287" 272 | "271","2","56,1","I","1","0.274" 273 | "272","3","56,4","IV","4","0.063" 274 | "273","4","56,5","V","5","0.055" 275 | "274","5","56,46","IV⁶","46","0.049" 276 | "275","6","56,67","vi⁷","67","0.047" 277 | "276","7","56,2","ii","2","0.031" 278 | "277","8","56,b7","♭VII","b7","0.016" 279 | "278","9","56,66","vi⁶","66","0.016" 280 | "279","10","56,564","V⁶₄","564","0.014" 281 | "280","11","56,464","IV⁶₄","464","0.013" 282 | "281","12","56,164","I⁶₄","164","0.01" 283 | "282","13","56,3","iii","3","0.007" 284 | "283","14","56,26","ii⁶","26","0.007" 285 | "284","15","56,5/5","V/V","5/5","0.006" 286 | "285","16","56,M77","♭VII⁷","M77","0.006" 287 | "286","17","56,17","I⁷","17","0.005" 288 | "287","18","56,47","IV⁷","47","0.005" 289 | "288","19","56,27","ii⁷","27","0.005" 290 | "289","20","56,37","iii⁷","37","0.005" 291 | "290","21","56,664","vi⁶₄","664","0.004" 292 | "291","22","56,16","I⁶","16","0.004" 293 | "292","23","56,M56","v⁶","M56","0.004" 294 | "293","24","56,b1","i","b1","0.003" 295 | "294","25","56,5/6","V/vi","5/6","0.003" 296 | "295","26","56,564/5","V⁶₄/V","564/5","0.002" 297 | "296","1","5/6,6","vi","6","0.497" 298 | "297","2","5/6,4","IV","4","0.165" 299 | "298","3","5/6,2","ii","2","0.042" 300 | "299","4","5/6,57/6","V⁷/vi","57/6","0.032" 301 | "300","5","5/6,564/6","V⁶₄/vi","564/6","0.026" 302 | "301","6","5/6,664","vi⁶₄","664","0.022" 303 | "302","7","5/6,56/6","V⁶/vi","56/6","0.022" 304 | "303","8","5/6,66","vi⁶","66","0.021" 305 | "304","9","5/6,1","I","1","0.02" 306 | "305","10","5/6,27","ii⁷","27","0.016" 307 | "306","11","5/6,47","IV⁷","47","0.012" 308 | "307","12","5/6,67","vi⁷","67","0.011" 309 | "308","13","5/6,5","V","5","0.011" 310 | "309","14","5/6,3","iii","3","0.009" 311 | "310","15","5/6,5/2","V/ii","5/2","0.006" 312 | "311","16","5/6,17","I⁷","17","0.005" 313 | "312","17","5/6,542/6","V⁴₂/vi","542/6","0.004" 314 | "313","18","5/6,M5","v","M5","0.004" 315 | "314","19","5/6,5/3","V/iii","5/3","0.004" 316 | "315","20","5/6,46","IV⁶","46","0.003" 317 | "316","21","5/6,57/2","V⁷/ii","57/2","0.003" 318 | "317","22","5/6,7/2","vii°/ii","7/2","0.002" 319 | "318","23","5/6,26","ii⁶","26","0.002" 320 | "319","24","5/6,b2","ii°","b2","0.002" 321 | "320","25","5/6,642","vi⁴₂","642","0.002" 322 | "321","26","5/6,L765","vii⁶₅","L765","0.002" 323 | "322","1","b7,4","IV","4","0.237" 324 | "323","2","b7,1","I","1","0.203" 325 | "324","3","b7,6","vi","6","0.137" 326 | "325","4","b7,5","V","5","0.059" 327 | "326","5","b7,46","IV⁶","46","0.046" 328 | "327","6","b7,b3","♭III","b3","0.033" 329 | "328","7","b7,7","vii°","7","0.018" 330 | "329","8","b7,b6","♭VI","b6","0.018" 331 | "330","9","b7,2","ii","2","0.017" 332 | "331","10","b7,5/2","V/ii","5/2","0.012" 333 | "332","11","b7,b1","i","b1","0.011" 334 | "333","12","b7,5/3","V/iii","5/3","0.009" 335 | "334","13","b7,5/6","V/vi","5/6","0.008" 336 | "335","14","b7,L7","vii","L7","0.008" 337 | "336","15","b7,264","ii⁶₄","264","0.007" 338 | "337","16","b7,27","ii⁷","27","0.006" 339 | "338","17","b7,57","V⁷","57","0.006" 340 | "339","18","b7,57/2","V⁷/ii","57/2","0.005" 341 | "340","19","b7,56/6","V⁶/vi","56/6","0.005" 342 | "341","20","b7,57/6","V⁷/vi","57/6","0.005" 343 | "342","21","b7,D4","IV","D4","0.005" 344 | "343","22","b7,D3","♭III","D3","0.005" 345 | "344","23","b7,Y5","v°","Y5","0.005" 346 | "345","24","b7,M17","Ib7","M17","0.004" 347 | "346","25","b7,3","iii","3","0.004" 348 | "347","26","b7,67","vi⁷","67","0.004" 349 | "348","1","164,4","IV","4","0.166" 350 | "349","2","164,5","V","5","0.134" 351 | "350","3","164,1","I","1","0.131" 352 | "351","4","164,6","vi","6","0.073" 353 | "352","5","164,57","V⁷","57","0.042" 354 | "353","6","164,16","I⁶","16","0.035" 355 | "354","7","164,47","IV⁷","47","0.032" 356 | "355","8","164,27","ii⁷","27","0.024" 357 | "356","9","164,46","IV⁶","46","0.022" 358 | "357","10","164,67","vi⁷","67","0.021" 359 | "358","11","164,56","V⁶","56","0.019" 360 | "359","12","164,L26","II⁶","L26","0.018" 361 | "360","13","164,b6","♭VI","b6","0.012" 362 | "361","14","164,57/2","V⁷/ii","57/2","0.011" 363 | "362","15","164,2","ii","2","0.011" 364 | "363","16","164,37","iii⁷","37","0.01" 365 | "364","17","164,56/5","V⁶/V","56/5","0.01" 366 | "365","18","164,L4","♯iv°","L4","0.009" 367 | "366","19","164,464","IV⁶₄","464","0.007" 368 | "367","20","164,264","ii⁶₄","264","0.007" 369 | "368","21","164,142","I⁴₂","142","0.007" 370 | "369","22","164,7/5","vii°/V","7/5","0.006" 371 | "370","23","164,642","vi⁴₂","642","0.006" 372 | "371","24","164,542/4","V⁴₂/IV","542/4","0.006" 373 | "372","25","164,5/5","V/V","5/5","0.006" 374 | "373","26","164,265","ii⁶₅","265","0.006" 375 | "374","27","164,C164","i°⁶₄","C164","0.005" 376 | "375","28","164,564","V⁶₄","564","0.005" 377 | "376","29","164,3","iii","3","0.005" 378 | "377","1","57,1","I","1","0.395" 379 | "378","2","57,5","V","5","0.07" 380 | "379","3","57,17","I⁷","17","0.045" 381 | "380","4","57,6","vi","6","0.045" 382 | "381","5","57,164","I⁶₄","164","0.038" 383 | "382","6","57,27","ii⁷","27","0.037" 384 | "383","7","57,4","IV","4","0.037" 385 | "384","8","57,67","vi⁷","67","0.033" 386 | "385","9","57,37","iii⁷","37","0.023" 387 | "386","10","57,2","ii","2","0.022" 388 | "387","11","57,642","vi⁴₂","642","0.019" 389 | "388","12","57,665","vi⁶₅","665","0.017" 390 | "389","13","57,542","V⁴₂","542","0.013" 391 | "390","14","57,57/4","V⁷/IV","57/4","0.013" 392 | "391","15","57,47","IV⁷","47","0.011" 393 | "392","16","57,Y57","v^??⁷","Y57","0.01" 394 | "393","17","57,543","V⁴₃","543","0.009" 395 | "394","18","57,56/6","V⁶/vi","56/6","0.009" 396 | "395","19","57,16","I⁶","16","0.008" 397 | "396","20","57,b7","♭VII","b7","0.008" 398 | "397","21","57,57/6","V⁷/vi","57/6","0.008" 399 | "398","22","57,565","V⁶₅","565","0.007" 400 | "399","23","57,M17","Ib7","M17","0.007" 401 | "400","24","57,365","iii⁶₅","365","0.007" 402 | "401","25","57,D47","IVb7","D47","0.007" 403 | "402","26","57,7/6","vii°/vi","7/6","0.006" 404 | "403","27","57,3","iii","3","0.005" 405 | "404","28","57,b3","♭III","b3","0.005" 406 | "405","29","57,77","vii^??⁷","77","0.003" 407 | "406","1","37,6","vi","6","0.17" 408 | "407","2","37,67","vi⁷","67","0.14" 409 | "408","3","37,47","IV⁷","47","0.117" 410 | "409","4","37,4","IV","4","0.112" 411 | "410","5","37,27","ii⁷","27","0.106" 412 | "411","6","37,3","iii","3","0.036" 413 | "412","7","37,5","V","5","0.022" 414 | "413","8","37,1","I","1","0.02" 415 | "414","9","37,57/2","V⁷/ii","57/2","0.018" 416 | "415","10","37,2","ii","2","0.016" 417 | "416","11","37,164","I⁶₄","164","0.012" 418 | "417","12","37,66","vi⁶","66","0.009" 419 | "418","13","37,Y37","♭IIIb7","Y37","0.008" 420 | "419","14","37,343","iii⁴₃","343","0.007" 421 | "420","15","37,5/2","V/ii","5/2","0.007" 422 | "421","16","37,565/5","V⁶₅/V","565/5","0.007" 423 | "422","17","37,265","ii⁶₅","265","0.006" 424 | "423","18","37,664","vi⁶₄","664","0.006" 425 | "424","19","37,564","V⁶₄","564","0.006" 426 | "425","20","37,D37","♭III⁷","D37","0.005" 427 | "426","21","37,17","I⁷","17","0.005" 428 | "427","22","37,16","I⁶","16","0.005" 429 | "428","23","37,b57","v⁷","b57","0.005" 430 | "429","24","37,M57","v⁷","M57","0.005" 431 | "430","25","37,M47","IV⁷","M47","0.004" 432 | "431","26","37,365","iii⁶₅","365","0.004" 433 | "432","1","5/5,4","IV","4","0.204" 434 | "433","2","5/5,5","V","5","0.189" 435 | "434","3","5/5,6","vi","6","0.115" 436 | "435","4","5/5,1","I","1","0.095" 437 | "436","5","5/5,3","iii","3","0.039" 438 | "437","6","5/5,2","ii","2","0.029" 439 | "438","7","5/5,27","ii⁷","27","0.024" 440 | "439","8","5/5,67","vi⁷","67","0.023" 441 | "440","9","5/5,5/6","V/vi","5/6","0.021" 442 | "441","10","5/5,5/2","V/ii","5/2","0.019" 443 | "442","11","5/5,b4","iv","b4","0.016" 444 | "443","12","5/5,47","IV⁷","47","0.016" 445 | "444","13","5/5,57","V⁷","57","0.015" 446 | "445","14","5/5,36","iii⁶","36","0.013" 447 | "446","15","5/5,L27","II⁷","L27","0.012" 448 | "447","16","5/5,b3","♭III","b3","0.011" 449 | "448","17","5/5,56/5","V⁶/V","56/5","0.01" 450 | "449","18","5/5,57/5","V⁷/V","57/5","0.009" 451 | "450","19","5/5,56","V⁶","56","0.008" 452 | "451","20","5/5,L7","vii","L7","0.008" 453 | "452","21","5/5,66","vi⁶","66","0.007" 454 | "453","22","5/5,564","V⁶₄","564","0.007" 455 | "454","23","5/5,5/3","V/iii","5/3","0.006" 456 | "455","24","5/5,b7","♭VII","b7","0.006" 457 | "456","25","5/5,b6","♭VI","b6","0.006" 458 | "457","26","5/5,664","vi⁶₄","664","0.006" 459 | "458","27","5/5,D47","IVb7","D47","0.006" 460 | "459","28","5/5,164","I⁶₄","164","0.006" 461 | "460","29","5/5,L5","V","L5","0.005" 462 | "461","1","464,1","I","1","0.397" 463 | "462","2","464,564","V⁶₄","564","0.059" 464 | "463","3","464,4","IV","4","0.053" 465 | "464","4","464,2","ii","2","0.043" 466 | "465","5","464,5","V","5","0.041" 467 | "466","6","464,6","vi","6","0.039" 468 | "467","7","464,17","I⁷","17","0.038" 469 | "468","8","464,56","V⁶","56","0.026" 470 | "469","9","464,565","V⁶₅","565","0.023" 471 | "470","10","464,3","iii","3","0.021" 472 | "471","11","464,27","ii⁷","27","0.019" 473 | "472","12","464,b464","iv⁶₄","b464","0.016" 474 | "473","13","464,164","I⁶₄","164","0.014" 475 | "474","14","464,M17","Ib7","M17","0.013" 476 | "475","15","464,46","IV⁶","46","0.012" 477 | "476","16","464,364","iii⁶₄","364","0.011" 478 | "477","17","464,564/6","V⁶₄/vi","564/6","0.01" 479 | "478","18","464,16","I⁶","16","0.009" 480 | "479","19","464,66","vi⁶","66","0.008" 481 | "480","20","464,57/4","V⁷/IV","57/4","0.008" 482 | "481","21","464,b7","♭VII","b7","0.008" 483 | "482","22","464,C464","iv⁶₄","C464","0.008" 484 | "483","23","464,b4","iv","b4","0.008" 485 | "484","24","464,5/6","V/vi","5/6","0.008" 486 | "485","25","464,77","vii^??⁷","77","0.007" 487 | "486","26","464,57","V⁷","57","0.007" 488 | "487","27","464,47","IV⁷","47","0.006" 489 | "488","28","464,7","vii°","7","0.006" 490 | "489","29","464,264","ii⁶₄","264","0.005" 491 | "490","1","17,47","IV⁷","47","0.126" 492 | "491","2","17,1","I","1","0.079" 493 | "492","3","17,4","IV","4","0.076" 494 | "493","4","17,67","vi⁷","67","0.062" 495 | "494","5","17,27","ii⁷","27","0.053" 496 | "495","6","17,6","vi","6","0.049" 497 | "496","7","17,464","IV⁶₄","464","0.043" 498 | "497","8","17,57/4","V⁷/IV","57/4","0.037" 499 | "498","9","17,5","V","5","0.028" 500 | "499","10","17,37","iii⁷","37","0.026" 501 | "500","11","17,47/4","IV⁷/IV","47/4","0.021" 502 | "501","12","17,2","ii","2","0.02" 503 | "502","13","17,b77","♭VIIb7","b77","0.02" 504 | "503","14","17,77","vii^??⁷","77","0.016" 505 | "504","15","17,143","I⁴₃","143","0.015" 506 | "505","16","17,57/3","V⁷/iii","57/3","0.015" 507 | "506","17","17,642","vi⁴₂","642","0.013" 508 | "507","18","17,3","iii","3","0.013" 509 | "508","19","17,M17","Ib7","M17","0.011" 510 | "509","20","17,564","V⁶₄","564","0.011" 511 | "510","21","17,5/5","V/V","5/5","0.011" 512 | "511","22","17,b57","v⁷","b57","0.01" 513 | "512","23","17,D17","i⁷","D17","0.01" 514 | "513","24","17,M77","♭VII⁷","M77","0.009" 515 | "514","25","17,164","I⁶₄","164","0.008" 516 | "515","1","664,6","vi","6","0.27" 517 | "516","2","664,4","IV","4","0.131" 518 | "517","3","664,5/6","V/vi","5/6","0.086" 519 | "518","4","664,2","ii","2","0.062" 520 | "519","5","664,5","V","5","0.039" 521 | "520","6","664,642","vi⁴₂","642","0.038" 522 | "521","7","664,26","ii⁶","26","0.031" 523 | "522","8","664,1","I","1","0.024" 524 | "523","9","664,27","ii⁷","27","0.023" 525 | "524","10","664,57/6","V⁷/vi","57/6","0.023" 526 | "525","11","664,564","V⁶₄","564","0.021" 527 | "526","12","664,16","I⁶","16","0.019" 528 | "527","13","664,66","vi⁶","66","0.018" 529 | "528","14","664,47","IV⁷","47","0.016" 530 | "529","15","664,36","iii⁶","36","0.016" 531 | "530","16","664,3","iii","3","0.012" 532 | "531","17","664,7/3","vii°/iii","7/3","0.011" 533 | "532","18","664,464","IV⁶₄","464","0.01" 534 | "533","19","664,365","iii⁶₅","365","0.009" 535 | "534","20","664,37","iii⁷","37","0.007" 536 | "535","21","664,56/3","V⁶/iii","56/3","0.005" 537 | "536","22","664,265","ii⁶₅","265","0.005" 538 | "537","23","664,5/5","V/V","5/5","0.005" 539 | "538","24","664,56/5","V⁶/V","56/5","0.005" 540 | "539","25","664,56/6","V⁶/vi","56/6","0.005" 541 | "540","26","664,77","vii^??⁷","77","0.005" 542 | "541","27","664,D6","vi°","D6","0.004" 543 | "542","1","564,1","I","1","0.142" 544 | "543","2","564,5","V","5","0.135" 545 | "544","3","564,6","vi","6","0.101" 546 | "545","4","564,2","ii","2","0.095" 547 | "546","5","564,4","IV","4","0.077" 548 | "547","6","564,16","I⁶","16","0.064" 549 | "548","7","564,664","vi⁶₄","664","0.062" 550 | "549","8","564,27","ii⁷","27","0.041" 551 | "550","9","564,56","V⁶","56","0.03" 552 | "551","10","564,464","IV⁶₄","464","0.025" 553 | "552","11","564,3","iii","3","0.023" 554 | "553","12","564,37","iii⁷","37","0.022" 555 | "554","13","564,564/6","V⁶₄/vi","564/6","0.018" 556 | "555","14","564,Y564","v°⁶₄","Y564","0.016" 557 | "556","15","564,542","V⁴₂","542","0.015" 558 | "557","16","564,164","I⁶₄","164","0.012" 559 | "558","17","564,47","IV⁷","47","0.012" 560 | "559","18","564,364","iii⁶₄","364","0.011" 561 | "560","19","564,67","vi⁷","67","0.008" 562 | "561","20","564,66","vi⁶","66","0.008" 563 | "562","21","564,57/5","V⁷/V","57/5","0.008" 564 | "563","22","564,5/6","V/vi","5/6","0.007" 565 | "564","23","564,b3","♭III","b3","0.005" 566 | "565","24","564,77","vii^??⁷","77","0.005" 567 | "566","25","564,543","V⁴₃","543","0.004" 568 | "567","26","564,46","IV⁶","46","0.004" 569 | "568","27","564,L264","II⁶₄","L264","0.003" 570 | "569","28","564,5/2","V/ii","5/2","0.003" 571 | "570","29","564,17","I⁷","17","0.003" 572 | "571","1","46,164","I⁶₄","164","0.13" 573 | "572","2","46,1","I","1","0.12" 574 | "573","3","46,6","vi","6","0.093" 575 | "574","4","46,56","V⁶","56","0.091" 576 | "575","5","46,4","IV","4","0.08" 577 | "576","6","46,5","V","5","0.078" 578 | "577","7","46,b46","iv⁶","b46","0.067" 579 | "578","8","46,b7","♭VII","b7","0.037" 580 | "579","9","46,464","IV⁶₄","464","0.036" 581 | "580","10","46,16","I⁶","16","0.023" 582 | "581","11","46,L46","♯iv°⁶","L46","0.022" 583 | "582","12","46,264","ii⁶₄","264","0.02" 584 | "583","13","46,36","iii⁶","36","0.018" 585 | "584","14","46,b6","♭VI","b6","0.018" 586 | "585","15","46,2","ii","2","0.016" 587 | "586","16","46,57","V⁷","57","0.014" 588 | "587","17","46,27","ii⁷","27","0.014" 589 | "588","18","46,L264","II⁶₄","L264","0.012" 590 | "589","19","46,67","vi⁷","67","0.008" 591 | "590","20","46,b5","v","b5","0.008" 592 | "591","21","46,564","V⁶₄","564","0.008" 593 | "592","22","46,47","IV⁷","47","0.008" 594 | "593","23","46,66","vi⁶","66","0.007" 595 | "594","24","46,C67","♭VIb7","C67","0.007" 596 | "595","25","46,b465","iv⁶₅","b465","0.006" 597 | "596","26","46,5/6","V/vi","5/6","0.006" 598 | "597","27","46,542/3","V⁴₂/iii","542/3","0.005" 599 | "598","28","46,542/2","V⁴₂/ii","542/2","0.005" 600 | "599","29","46,565","V⁶₅","565","0.005" 601 | "600","1","57/6,6","vi","6","0.483" 602 | "601","2","57/6,67","vi⁷","67","0.113" 603 | "602","3","57/6,4","IV","4","0.102" 604 | "603","4","57/6,664","vi⁶₄","664","0.026" 605 | "604","5","57/6,2","ii","2","0.025" 606 | "605","6","57/6,D47","IVb7","D47","0.025" 607 | "606","7","57/6,57/2","V⁷/ii","57/2","0.024" 608 | "607","8","57/6,47","IV⁷","47","0.024" 609 | "608","9","57/6,565/6","V⁶₅/vi","565/6","0.021" 610 | "609","10","57/6,27","ii⁷","27","0.021" 611 | "610","11","57/6,D26","ii⁶","D26","0.013" 612 | "611","12","57/6,5/6","V/vi","5/6","0.011" 613 | "612","13","57/6,1","I","1","0.01" 614 | "613","14","57/6,542/6","V⁴₂/vi","542/6","0.009" 615 | "614","15","57/6,56/6","V⁶/vi","56/6","0.008" 616 | "615","16","57/6,37","iii⁷","37","0.007" 617 | "616","17","57/6,M3","iii°","M3","0.006" 618 | "617","18","57/6,b77","♭VIIb7","b77","0.005" 619 | "618","19","57/6,b7","♭VII","b7","0.005" 620 | "619","20","57/6,57/5","V⁷/V","57/5","0.003" 621 | "620","21","57/6,D67","vi^??⁷","D67","0.003" 622 | "621","22","57/6,565/3","V⁶₅/iii","565/3","0.003" 623 | "622","23","57/6,26","ii⁶","26","0.003" 624 | "623","24","57/6,M37","iii^??⁷","M37","0.003" 625 | "624","25","57/6,77","vii^??⁷","77","0.003" 626 | "625","26","57/6,M56","v⁶","M56","0.003" 627 | "626","27","57/6,543/6","V⁴₃/vi","543/6","0.003" 628 | "627","28","57/6,Y37","♭IIIb7","Y37","0.002" 629 | "628","1","642,4","IV","4","0.204" 630 | "629","2","642,6","vi","6","0.199" 631 | "630","3","642,47","IV⁷","47","0.056" 632 | "631","4","642,5","V","5","0.048" 633 | "632","5","642,664","vi⁶₄","664","0.041" 634 | "633","6","642,57","V⁷","57","0.034" 635 | "634","7","642,56/5","V⁶/V","56/5","0.031" 636 | "635","8","642,67","vi⁷","67","0.023" 637 | "636","9","642,1","I","1","0.021" 638 | "637","10","642,665","vi⁶₅","665","0.019" 639 | "638","11","642,164","I⁶₄","164","0.019" 640 | "639","12","642,L4","♯iv°","L4","0.017" 641 | "640","13","642,27","ii⁷","27","0.014" 642 | "641","14","642,36","iii⁶","36","0.014" 643 | "642","15","642,37","iii⁷","37","0.014" 644 | "643","16","642,46/6","IV⁶/vi","46/6","0.014" 645 | "644","17","642,2","ii","2","0.012" 646 | "645","18","642,543","V⁴₃","543","0.011" 647 | "646","19","642,365","iii⁶₅","365","0.01" 648 | "647","20","642,L265","II⁶₅","L265","0.01" 649 | "648","21","642,77/5","vii^??⁷/V","77/5","0.01" 650 | "649","22","642,643","vi⁴₃","643","0.009" 651 | "650","23","642,17","I⁷","17","0.008" 652 | "651","24","642,26","ii⁶","26","0.008" 653 | "652","25","642,542/2","V⁴₂/ii","542/2","0.008" 654 | "653","26","642,3","iii","3","0.008" 655 | "654","1","36,4","IV","4","0.186" 656 | "655","2","36,6","vi","6","0.128" 657 | "656","3","36,47","IV⁷","47","0.121" 658 | "657","4","36,5","V","5","0.072" 659 | "658","5","36,2","ii","2","0.062" 660 | "659","6","36,L26","II⁶","L26","0.042" 661 | "660","7","36,3","iii","3","0.04" 662 | "661","8","36,26","ii⁶","26","0.031" 663 | "662","9","36,L764","vii⁶₄","L764","0.029" 664 | "663","10","36,1","I","1","0.025" 665 | "664","11","36,46","IV⁶","46","0.024" 666 | "665","12","36,27","ii⁷","27","0.021" 667 | "666","13","36,57","V⁷","57","0.015" 668 | "667","14","36,66","vi⁶","66","0.013" 669 | "668","15","36,564","V⁶₄","564","0.012" 670 | "669","16","36,37","iii⁷","37","0.012" 671 | "670","17","36,5/5","V/V","5/5","0.011" 672 | "671","18","36,364","iii⁶₄","364","0.01" 673 | "672","19","36,5/6","V/vi","5/6","0.01" 674 | "673","20","36,67","vi⁷","67","0.009" 675 | "674","21","36,542/3","V⁴₂/iii","542/3","0.007" 676 | "675","22","36,17","I⁷","17","0.006" 677 | "676","23","36,665","vi⁶₅","665","0.004" 678 | "677","24","36,56/3","V⁶/iii","56/3","0.004" 679 | "678","25","36,C1","i°","C1","0.004" 680 | "679","26","36,543","V⁴₃","543","0.004" 681 | "680","27","36,7/6","vii°/vi","7/6","0.004" 682 | "681","1","66,6","vi","6","0.124" 683 | "682","2","66,4","IV","4","0.096" 684 | "683","3","66,2","ii","2","0.059" 685 | "684","4","66,1","I","1","0.057" 686 | "685","5","66,364","iii⁶₄","364","0.055" 687 | "686","6","66,3","iii","3","0.041" 688 | "687","7","66,56","V⁶","56","0.039" 689 | "688","8","66,564/6","V⁶₄/vi","564/6","0.035" 690 | "689","9","66,664","vi⁶₄","664","0.033" 691 | "690","10","66,564","V⁶₄","564","0.023" 692 | "691","11","66,56/6","V⁶/vi","56/6","0.023" 693 | "692","12","66,M76","♭VII⁶","M76","0.021" 694 | "693","13","66,7","vii°","7","0.021" 695 | "694","14","66,36","iii⁶","36","0.021" 696 | "695","15","66,5","V","5","0.021" 697 | "696","16","66,5/5","V/V","5/5","0.02" 698 | "697","17","66,164","I⁶₄","164","0.019" 699 | "698","18","66,5/6","V/vi","5/6","0.019" 700 | "699","19","66,26","ii⁶","26","0.018" 701 | "700","20","66,77","vii^??⁷","77","0.018" 702 | "701","21","66,464","IV⁶₄","464","0.016" 703 | "702","22","66,47","IV⁷","47","0.014" 704 | "703","23","66,16","I⁶","16","0.011" 705 | "704","24","66,17","I⁷","17","0.011" 706 | "705","25","66,643","vi⁴₃","643","0.009" 707 | "706","26","66,67","vi⁷","67","0.008" 708 | "707","27","66,56/2","V⁶/ii","56/2","0.008" 709 | "708","28","66,665","vi⁶₅","665","0.008" 710 | "709","29","66,57/3","V⁷/iii","57/3","0.008" 711 | "710","30","66,b7","♭VII","b7","0.008" 712 | "711","1","b6,b7","♭VII","b7","0.286" 713 | "712","2","b6,1","I","1","0.166" 714 | "713","3","b6,5","V","5","0.136" 715 | "714","4","b6,6","vi","6","0.061" 716 | "715","5","b6,b3","♭III","b3","0.058" 717 | "716","6","b6,4","IV","4","0.048" 718 | "717","7","b6,b4","iv","b4","0.031" 719 | "718","8","b6,164","I⁶₄","164","0.027" 720 | "719","9","b6,b5","v","b5","0.015" 721 | "720","10","b6,Y2","♭II","Y2","0.014" 722 | "721","11","b6,D3","♭III","D3","0.012" 723 | "722","12","b6,5/2","V/ii","5/2","0.012" 724 | "723","13","b6,5/5","V/V","5/5","0.01" 725 | "724","14","b6,16","I⁶","16","0.009" 726 | "725","15","b6,5/3","V/iii","5/3","0.008" 727 | "726","16","b6,b56","v⁶","b56","0.006" 728 | "727","17","b6,57","V⁷","57","0.004" 729 | "728","18","b6,b67","♭VI⁷","b67","0.004" 730 | "729","19","b6,b1","i","b1","0.004" 731 | "730","20","b6,b565","v⁶₅","b565","0.004" 732 | "731","21","b6,642","vi⁴₂","642","0.004" 733 | "732","22","b6,67","vi⁷","67","0.004" 734 | "733","23","b6,b26","ii°⁶","b26","0.004" 735 | "734","24","b6,D6","vi°","D6","0.002" 736 | "735","1","b3,4","IV","4","0.24" 737 | "736","2","b3,1","I","1","0.141" 738 | "737","3","b3,b7","♭VII","b7","0.102" 739 | "738","4","b3,b6","♭VI","b6","0.057" 740 | "739","5","b3,5/5","V/V","5/5","0.051" 741 | "740","6","b3,2","ii","2","0.045" 742 | "741","7","b3,Y2","♭II","Y2","0.043" 743 | "742","8","b3,5","V","5","0.041" 744 | "743","9","b3,b76","♭VII⁶","b76","0.04" 745 | "744","10","b3,b4","iv","b4","0.023" 746 | "745","11","b3,Y76","♭vii⁶","Y76","0.018" 747 | "746","12","b3,b5","v","b5","0.017" 748 | "747","13","b3,27","ii⁷","27","0.015" 749 | "748","14","b3,57/6","V⁷/vi","57/6","0.013" 750 | "749","15","b3,16","I⁶","16","0.012" 751 | "750","16","b3,b37","♭III⁷","b37","0.012" 752 | "751","17","b3,C27","♭II⁷","C27","0.01" 753 | "752","18","b3,57","V⁷","57","0.009" 754 | "753","19","b3,C5","♭V","C5","0.009" 755 | "754","20","b3,D4","IV","D4","0.009" 756 | "755","21","b3,3","iii","3","0.006" 757 | "756","22","b3,564","V⁶₄","564","0.006" 758 | "757","23","b3,M3","iii°","M3","0.005" 759 | "758","24","b3,543","V⁴₃","543","0.005" 760 | "759","25","b3,56/3","V⁶/iii","56/3","0.005" 761 | --------------------------------------------------------------------------------