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1 library(tidyverse)
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2
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3 feats_mode <- 'original'
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4 feats_lev <- 'f'
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5
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6 feats_path <- paste0('~/Repositories/research/datasets/features/gtzan/',
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7 feats_mode, '/scattering/')
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8
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9 feats <- read.csv(file = paste0(feats_path, feats_lev, '.csv'))
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10
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11 feats_desc <-
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12 feats %>%
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13 group_by(ex_id, gt) %>%
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14 summarise_all(funs(mean, median, var, min, max,
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15 skew = psych::skew,
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16 kurt = psych::kurtosi)) %>%
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17 ungroup()
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18
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19 dif <- function(x) x - lag(x)
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20
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21 feats_dif <-
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22 feats %>%
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23 group_by(ex_id, gt) %>%
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24 mutate_all(funs(dif)) %>%
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25 na.omit() %>%
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26 ungroup()
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27 names(feats_dif) <- c(names(feats_dif)[1:2],
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28 paste0(names(feats_dif)[3:length(names(feats_dif))],
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29 "_dif"))
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30
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31 feats_dif2 <-
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32 feats_dif %>%
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33 group_by(ex_id, gt) %>%
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34 mutate_all(funs(dif)) %>%
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35 na.omit() %>%
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36 ungroup()
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37 names(feats_dif2) <- c(names(feats_dif2)[1:2],
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38 paste0(names(feats_dif2)[3:length(names(feats_dif2))],
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39 "2"))
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40
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41 feats_desc <-
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42 cbind(feats_desc,
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43 feats_dif %>%
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44 group_by(ex_id, gt) %>%
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45 summarise_all(funs(mean, var)) %>%
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46 ungroup() %>%
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47 select(-ex_id, -gt),
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48 feats_dif2 %>%
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49 group_by(ex_id, gt) %>%
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50 summarise_all(funs(mean, var)) %>%
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51 ungroup() %>%
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52 select(-ex_id, -gt)
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53 )
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54
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55
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56 file_name <- paste0(feats_path, feats_lev, '_desc.csv')
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57 write.csv(x = feats_desc, file = file_name, row.names = F)
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58
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