projects / epclust.git / blame
| Commit | Line | Data |
|---|---|---|
| ad642dc6 BA |
1 | # File: descriptive-32K.r |
| 2 | ||
| 3 | rm(list = ls()) | |
| 4 | #library(dplyr) | |
| 5 | ||
| 6 | ## Following lines allow to construct the data file | |
| 7 | ## totconso-par-indiv.txt. | |
| 8 | ## They are very time&memory-consumming | |
| 9 | #library(data.table) | |
| 10 | #d10 <- fread("~/tmp/data/2010.csv") | |
| 11 | #tot <- d10[, list(tot= sum(CPP_PUISSANCE_BRUTE), | |
| 12 | # min= min(CPP_PUISSANCE_BRUTE), | |
| 13 | # max= max(CPP_PUISSANCE_BRUTE), | |
| 14 | # sd = sd( CPP_PUISSANCE_BRUTE)), | |
| 15 | # by = FK_CCU_ID] | |
| 16 | # write.table(file = "~/tmp/data/totconso-par-indiv.txt", tot) | |
| 17 | ||
| 18 | tot <- read.table("~/tmp/data/totconso-par-indiv.txt") | |
| 19 | synchro <- read.table("~/tmp/data/syncrone2010.txt") | |
| 20 | mat_synchro <- matrix(c(synchro$V1[1:2], synchro$V1) / 1e6, | |
| 21 | ncol = 48, | |
| 22 | byrow = TRUE) | |
| 23 | ||
| 24 | xHour <- seq(1/2, 24, length.out = 48) | |
| 25 | xDate <- seq.Date(from = as.Date("2010/1/1"), | |
| 26 | to = as.Date("2011/1/1"), | |
| 27 | length.out = 365 * 48 - 2) | |
| 28 | ||
| 29 | # Filter infra daily | |
| 30 | plot(xDate, filter(synchro$V1 / 1e6, rep(1 / 48, 48)), | |
| 31 | type = 'l', | |
| 32 | main = 'Synchrone 2010', | |
| 33 | ylab = 'Charge (en Mwh)', | |
| 34 | xlab = 'Time') | |
| 35 | ||
| 36 | # Daily | |
| 37 | matplot(xHour, scale(t(mat_synchro)), type = 'l', lty = 1, | |
| 38 | col = rgb(0, 0, 0, .25), | |
| 39 | main = 'Synchrone jounalière (norm.)', | |
| 40 | xlab = 'Heures', ylab = 'Charge (en Mwh)') | |
| 41 | ||
| 42 | ||
| 43 | tot_order <- tot[order(tot$tot), ] | |
| 44 | max_order <- tot[order(tot$max), ] | |
| 45 | ||
| 46 | ## Mesures aberrantes ? | |
| 47 | tail(cbind(max_order[,1], max_order[,-1] / 1e3)) | |
| 48 | ||
| 49 | ||
| 50 | ## I want to recuperate ids: 186733, 191819, 193174 | |
| 51 | ## which corresponds to places 1, 2481, 3478 | |
| 52 | # identiants <- read.table('~/tmp/data/identifs.txt') | |
| 53 | # match(c(186733, 191819, 193174), identiants$V1) | |
| 54 | ||
| 55 | #c186733 <- d10[, FK_CCU_ID == 186733] | |
| 56 | #c191819 <- d10[, FK_CCU_ID == 191819] | |
| 57 | #c193174 <- d10[, FK_CCU_ID == 193174] | |
| 58 | ||
| 59 | c186733 <- read.csv("~/tmp/data/c186733.csv")[, 4] / 1e3 | |
| 60 | ||
| 61 | mat_186733 <- matrix(c(c186733[1:2], c186733), | |
| 62 | ncol = 48, | |
| 63 | byrow = TRUE) | |
| 64 | ||
| 65 | # Filter infra daily | |
| 66 | plot(xDate, filter(c186733, rep(1 / 48, 48)), | |
| 67 | type = 'l', | |
| 68 | main = "Consommation individuelle (2010)", | |
| 69 | ylab = 'Charge (en Mwh)', | |
| 70 | xlab = 'Temps') | |
| 71 | ||
| 72 | # Daily (raw) | |
| 73 | matplot(xHour, t(mat_186733), type = 'l', lty = 1, | |
| 74 | col = rgb(0, 0, 0, .25), | |
| 75 | #main = "Consommation individuelle journalière " | |
| 76 | xlab = 'Heures', ylab = 'Charge (en Mwh)') | |
| 77 | ||
| 78 | # Daily (standarized) | |
| 79 | matplot(xHour, scale(t(mat_186733)), type = 'l', lty = 1, | |
| 80 | col = rgb(0, 0, 0, .25), | |
| 81 | xlab = 'Heures', ylab = 'Charge (en Mwh)') |