Created
April 7, 2020 06:46
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# Rolling Average | |
# Moving window week | |
mw = df[df$Date >= "2009-11-01" & df$Date <= "2009-11-07",] | |
# MW days | |
mw_sat <- subset(mw, wday(mw$Date) == 2) | |
mw_mon <- subset(mw, wday(mw$Date) == 7) | |
# MW time | |
mw_sat_window <- mw_sat[mw_sat$Time >= '07:00:00' & mw_sat$Time <= "09:00:00",] | |
mw_mon_window <- mw_mon[mw_mon$Time >= '07:00:00' & mw_mon$Time <= "09:00:00",] | |
# Plot the unsmoothed data (gray) | |
x <- (strptime(mw_sat_window$Time, '%H:%M:%S')) | |
y <- mw_sat_window$Global_active_power | |
plot(x, y, type="l", col=grey(.5), main="Global_active_power MA from 7am-9am, 2009-11-02",sub = "(2 sided MA, 10 levels)", xlab="Time", ylab="Global_active_power",) | |
f20 <- rep(1/10,10) | |
f20 | |
y_sym <- stats::filter(y, f20, sides=2) | |
lines(x, y_sym, col="blue") | |
legend("topleft", inset=.01, | |
c("Moving Average","Original Data"), fill=c("blue","grey"), horiz=FALSE) | |
legend("topright", inset=.01, | |
c("Minor Anomaly","Major Anomaly", "Extreme Anomaly"), fill=c("yellow","orange","red"), horiz=FALSE) | |
stddev <- sd(y_sym, na.rm = TRUE) | |
threshold_minor <- 1*stddev | |
threshold_major <- 2*stddev | |
threshold_extreme <- 4*stddev | |
minor_occurances <- 0 | |
major_occurances <- 0 | |
extreme_occurances <- 0 | |
for(i in 1:length(y_sym)) { | |
if (is.na(y_sym[i])) { | |
# print("na") | |
} else { | |
difference <- abs(y[i] - y_sym[i]) | |
if (difference >= threshold_minor) { | |
if (difference >= threshold_major) { | |
if (difference >= threshold_extreme) { | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "red", pch = 19) | |
extreme_occurances = extreme_occurances + 1; | |
next | |
} | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "orange", pch = 19) | |
major_occurances = major_occurances + 1; | |
next | |
} | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "yellow", pch = 19) | |
minor_occurances = minor_occurances + 1; | |
next | |
} | |
next | |
} | |
} | |
print(minor_occurances) | |
print(major_occurances) | |
print(extreme_occurances) | |
# ======= | |
# Plot the unsmoothed data (gray) | |
x <- (strptime(mw_mon_window$Time, '%H:%M:%S')) | |
y <- mw_mon_window$Global_active_power | |
plot(x, y, type="l", col=grey(.5), main="Global_active_power MA from 7am-9am, 2009-11-07",sub = "(2 sided MA, 10 levels)", xlab="Time", ylab="Global_active_power",) | |
f20 <- rep(1/10,10) | |
f20 | |
y_sym <- stats::filter(y, f20, sides=2) | |
lines(x, y_sym, col="blue") | |
legend("topleft", inset=.01, | |
c("Moving Average","Original Data"), fill=c("blue","grey"), horiz=FALSE) | |
legend("topright", inset=.01, | |
c("Minor Anomaly","Major Anomaly", "Extreme Anomaly"), fill=c("yellow","orange","red"), horiz=FALSE) | |
stddev <- sd(y_sym, na.rm = TRUE) | |
threshold_minor <- 1*stddev | |
threshold_major <- 2*stddev | |
threshold_extreme <- 4*stddev | |
minor_occurances <- 0 | |
major_occurances <- 0 | |
extreme_occurances <- 0 | |
for(i in 1:length(y_sym)) { | |
if (is.na(y_sym[i])) { | |
# print("na") | |
} else { | |
difference <- abs(y[i] - y_sym[i]) | |
if (difference >= threshold_minor) { | |
if (difference >= threshold_major) { | |
if (difference >= threshold_extreme) { | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "red", pch = 19) | |
extreme_occurances = extreme_occurances + 1; | |
next | |
} | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "orange", pch = 19) | |
major_occurances = major_occurances + 1; | |
next | |
} | |
points(strptime(mw_sat_window[i, "Time"], '%H:%M:%S'), y[i], col = "yellow", pch = 19) | |
minor_occurances = minor_occurances + 1; | |
next | |
} | |
next | |
} | |
} | |
print(minor_occurances) | |
print(major_occurances) | |
print(extreme_occurances) |
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