| # |
| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| # EMA <- w * EMA + (1 - w) * x |
| # EMS <- sqrt( w * EMS^2 + (1 - w) * (x - EMA)^2 ) |
| # Alarm = abs(x - EMA) > n * EMS |
| |
| ema_global <- function(train_data, test_data, w, n) { |
| |
| # res <- get_data(url) |
| # data <- data.frame(as.numeric(names(res$metrics[[1]]$metrics)), as.numeric(res$metrics[[1]]$metrics)) |
| # names(data) <- c("TS", res$metrics[[1]]$metricname) |
| # train_data <- data[which(data$TS >= train_start & data$TS <= train_end), 2] |
| # test_data <- data[which(data$TS >= test_start & data$TS <= test_end), ] |
| |
| anomalies <- data.frame() |
| ema <- 0 |
| ems <- 0 |
| |
| #Train Step |
| for (x in train_data) { |
| ema <- w*ema + (1-w)*x |
| ems <- sqrt(w* ems^2 + (1 - w)*(x - ema)^2) |
| } |
| |
| for ( i in 1:length(test_data[,1])) { |
| x <- test_data[i,2] |
| if (abs(x - ema) > n*ems) { |
| anomaly <- c(as.numeric(test_data[i,1]), x) |
| # print (anomaly) |
| anomalies <- rbind(anomalies, anomaly) |
| } |
| ema <- w*ema + (1-w)*x |
| ems <- sqrt(w* ems^2 + (1 - w)*(x - ema)^2) |
| } |
| |
| if(length(anomalies) > 0) { |
| names(anomalies) <- c("TS", "Value") |
| } |
| return (anomalies) |
| } |
| |
| ema_daily <- function(train_data, test_data, w, n) { |
| |
| # res <- get_data(url) |
| # data <- data.frame(as.numeric(names(res$metrics[[1]]$metrics)), as.numeric(res$metrics[[1]]$metrics)) |
| # names(data) <- c("TS", res$metrics[[1]]$metricname) |
| # train_data <- data[which(data$TS >= train_start & data$TS <= train_end), ] |
| # test_data <- data[which(data$TS >= test_start & data$TS <= test_end), ] |
| |
| anomalies <- data.frame() |
| ema <- vector("numeric", 7) |
| ems <- vector("numeric", 7) |
| |
| #Train Step |
| for ( i in 1:length(train_data[,1])) { |
| x <- train_data[i,2] |
| time <- as.POSIXlt(as.numeric(train_data[i,1])/1000, origin = "1970-01-01" ,tz = "GMT") |
| index <- time$wday |
| ema[index] <- w*ema[index] + (1-w)*x |
| ems[index] <- sqrt(w* ems[index]^2 + (1 - w)*(x - ema[index])^2) |
| } |
| |
| for ( i in 1:length(test_data[,1])) { |
| x <- test_data[i,2] |
| time <- as.POSIXlt(as.numeric(test_data[i,1])/1000, origin = "1970-01-01" ,tz = "GMT") |
| index <- time$wday |
| |
| if (abs(x - ema[index+1]) > n*ems[index+1]) { |
| anomaly <- c(as.numeric(test_data[i,1]), x) |
| # print (anomaly) |
| anomalies <- rbind(anomalies, anomaly) |
| } |
| ema[index+1] <- w*ema[index+1] + (1-w)*x |
| ems[index+1] <- sqrt(w* ems[index+1]^2 + (1 - w)*(x - ema[index+1])^2) |
| } |
| |
| if(length(anomalies) > 0) { |
| names(anomalies) <- c("TS", "Value") |
| } |
| return(anomalies) |
| } |