| 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)') |