edited recent times

.Rhistory

@@ -1,68 +1,26 @@
-values <- values %>%
-mutate(
-time = as.POSIXct(time, tz = "America/Chicago"),
-status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
 labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
+View(values)
+ggplot(data = values) +
+geom_tile(aes(x = time,
+y = entity_id,
+fill = status))
+ggplot(data = values) +
+geom_tile(aes(x = time,
+y = entity_id,
+width = 1,
+height = 1
 fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
+ggplot(data = values) +
+geom_tile(aes(x = time,
+y = entity_id,
+width = 1,
+height = 1,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-difftime(Sys.time(), washer_last_on, units = "mins")
-difftime(Sys.time(), washer_last_off, units = "mins")
-difftime(Sys.time(), washer_last_off)
-difftime(Sys.time(), washer_last_on, units = "mins")
-difftime(Sys.time(), washer_last_on)
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+labs(title = "The past week")
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -73,62 +31,7 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+mutate(end_time = values$time[-1])
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -139,62 +42,8 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+mutate(end_time = c(values$time[-1], NA))
+View(values)
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -205,62 +54,8 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+mutate(end_time = c(values$time[-1], Sys.time()))
+run_time <- Sys.time()
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -271,62 +66,20 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+mutate(end_time = c(values$time[-1], run_time))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > 1, "on", "off"))
+c(values$time[-1], run_time)
+run_time <- Sys.time()
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -337,62 +90,8 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-# ---- generate html
-current_status <- as.list(NULL)
-for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
-}
-plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
-fill = status)) +
-scale_y_continuous()  +
-scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
-theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-#setup ----
-library(tidyverse)
-library(influxdbclient)
-library(rmarkdown)
-if(test) {
-setwd("~/Documents/dataProjects/laundry_status")
-} else {
-setwd("/laundry_status")
-}
-Sys.setenv(TZ='America/Chicago')
-# parameters needed to make connection to Database
-token <- substr(read_file("data/api_key"), 1, 88)
-org = "home_assistant"
-bucket = "home_assistant"
-## make connection to the influxDB bucket
-home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
-token = token,
-org = org)
-update_interval <- 5
-# ---- set variables
-entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
-update_data <- function(){
+mutate(end_time = c(values$time[-1], run_time))
+run_time <- Sys.time()
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -403,45 +102,241 @@ values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
 status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > 5) %>% tail(1) %>% pull(time)
-dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < 5) %>% tail(1) %>% pull(time)
+mutate(end_time = c(values$time[-1], as.POSIXct(run_time)))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off")) %>%
+mutate(end_time = c(values$time[-1], c(run_time)))
+power_threshhold <- 5
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off")) %>%
+mutate(end_time = c(values$time[-1], c(run_time)))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+values <- values %>%
+mutate(end_time = c(values$time[-1], run_time))
+ggplot(data = values) +
+geom_tile(aes(x = time + minutes(as.numerica(difftime(time, endtime, unit = "mins")))/2,
+y = entity_id,
+width = minutes(as.numerica(difftime(time, endtime, unit = "mins"))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+ggplot(data = values) +
+geom_tile(aes(x = time + minutes(as.numeric(difftime(time, endtime, unit = "mins")))/2,
+y = entity_id,
+width = minutes(as.numeric(difftime(time, endtime, unit = "mins"))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+ggplot(data = values) +
+geom_tile(aes(x = time + minutes(as.numeric(difftime(time, end_time, unit = "mins")))/2,
+y = entity_id,
+width = minutes(as.numeric(difftime(time, end_time, unit = "mins"))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+ggplot(data = values) +
+geom_tile(aes(x = time + minutes(as.numeric(difftime(time, end_time, unit = "mins"))/2),
+y = entity_id,
+width = minutes(as.numeric(difftime(time, end_time, unit = "mins"))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+values$time + minutes(as.numeric(difftime(values$time, values$end_time, unit = "mins"))/2)
+difftime(values$time, values$end_time, unit = "mins")
+as.numeric(difftime(values$time, values$end_time, unit = "mins"))
+ggplot(data = values) +
+geom_tile(aes(x = time + minutes(as.numeric(difftime(end_time, time, unit = "mins"))/2),
+y = entity_id,
+width = minutes(as.numeric(difftime(end_time, time, unit = "mins"))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+ggplot(data = values) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+values <- values %>%
+group_by(entity_id) %>%
+arrange(time) %>%
+mutate(end_time = c(values$time[-1], run_time))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+values <- values %>%
+group_by(entity_id) %>%
+mutate(end_time = c(values$time[-1], run_time))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+for(entity in entities$entity_id) {
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(values$time[-1], run_time))
+}
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+for(entity in entities$entity_id) {
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(time[-1], run_time))
+}
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(time[-1], run_time))
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+values_by_entity <- as.list(NULL)
+for(entity in entities$entity_id) {
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(time[-1], run_time))
+}
+values <- bind_rows(values_by_entity)
+View(values)
+washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > power_threshhold) %>% tail(1) %>% pull(time)
+washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < power_threshhold) %>% tail(1) %>% pull(time)
 # ---- generate html
 current_status <- as.list(NULL)
 for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
+current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > power_threshhold, "on", "off")
 }
 plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
 fill = status)) +
-scale_y_continuous()  +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
 scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
-plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
+labs(title = "The past week")
+ggplot(data = values) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
 fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week")
+ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
 scale_y_continuous()  +
 scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
 labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
-}
-for(i in 1:8640){
-update_data()
-Sys.sleep(60*update_interval)
-}
-Sys.info()
-Sys.info()[4]
-Sys.info()[4] == "pseudotsuga"
+ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "Last 24 hours")
 #setup ----
 library(tidyverse)
 library(influxdbclient)
@@ -461,9 +356,12 @@ home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
 token = token,
 org = org)
 update_interval <- 5
+cronjob_interval <- 60
+power_threshhold <- 5
 # ---- set variables
 entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
 update_data <- function(){
+run_time <- Sys.time()
 values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
 POSIXctCol = NULL)
 values <- bind_rows(values)
@@ -473,40 +371,142 @@ time = "_time")
 values <- values %>%
 mutate(
 time = as.POSIXct(time, tz = "America/Chicago"),
-status = ifelse(value > 1, "on", "off")) %>%
-mutate(end_time = time + minutes(1))
-washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > 5) %>% tail(1) %>% pull(time)
-washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < 5) %>% tail(1) %>% pull(time)
-dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > 5) %>% tail(1) %>% pull(time)
-dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < 5) %>% tail(1) %>% pull(time)
+status = ifelse(value > power_threshhold, "on", "off"))
+values_by_entity <- as.list(NULL)
+for(entity in entities$entity_id) {
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(time[-1], run_time))
+}
+values <- bind_rows(values_by_entity)
+washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > power_threshhold) %>% tail(1) %>% pull(time)
+washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < power_threshhold) %>% tail(1) %>% pull(time)
 # ---- generate html
 current_status <- as.list(NULL)
 for (entity in entities$entity_id){
-current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > 5, "on", "off")
+current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > power_threshhold, "on", "off")
 }
 plot_1week <- ggplot(data = values) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
 fill = status)) +
-scale_y_continuous()  +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
 scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last week")
+labs(title = "The past week",
+x = NULL,
+y = NULL,
+fill = NULL)
 plot_1day <- ggplot(data = values %>% filter(time >= max(values$time) - hours(24))) +
-geom_rect(aes(xmin = end_time,
-xmax = time,
-ymin = ifelse(entity_id == "lamp_a_power", 0, 2) + 0.5,
-ymax = ifelse(entity_id == "lamp_a_power", 0, 2) + 1.5,
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
 fill = status)) +
-scale_y_continuous()  +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
 scale_x_datetime(breaks = seq(round_date(max(values$time), "4 hours") - hours(24), round_date(max(values$time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
 theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
-labs(title = "Last 24 hours")
-render("laundry_status.Rmd")
+labs(title = "Last 24 hours",
+x = NULL,
+y = NULL,
+fill = NULL)
+render("laundry_status.Rmd",
+output_dir = "html",
+output_file = "index.html")
 }
-for(i in 1:8640){
+for(i in 1:(cronjob_interval/update_interval)){
+message(Sys.time())
+update_data()
+Sys.sleep(60*update_interval)
+}
+round_date(max(values$time), "4 hours")
+#setup ----
+library(tidyverse)
+library(influxdbclient)
+library(rmarkdown)
+if(Sys.info()[4] == "pseudotsuga") {
+setwd("~/Documents/dataProjects/laundry_status")
+} else {
+setwd("/laundry_status")
+}
+Sys.setenv(TZ='America/Chicago')
+# parameters needed to make connection to Database
+token <- substr(read_file("data/api_key"), 1, 88)
+org = "home_assistant"
+bucket = "home_assistant"
+## make connection to the influxDB bucket
+home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
+token = token,
+org = org)
+update_interval <- 5
+cronjob_interval <- 60
+power_threshhold <- 5
+# ---- set variables
+entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
+update_data <- function(){
+run_time <- Sys.time()
+values <- home_assistant$query('from(bucket: "home_assistant") |> range(start: -7d) |> filter(fn: (r) => r["entity_id"] == "lamp_b_power" or r["entity_id"] == "lamp_a_power") |> filter(fn: (r) => r["_field"] == "value") |> filter(fn: (r) => r["_measurement"] == "W")',
+POSIXctCol = NULL)
+values <- bind_rows(values)
+values <- values %>%
+rename(value = "_value",
+time = "_time")
+values <- values %>%
+mutate(
+time = as.POSIXct(time, tz = "America/Chicago"),
+status = ifelse(value > power_threshhold, "on", "off"))
+values_by_entity <- as.list(NULL)
+for(entity in entities$entity_id) {
+values_by_entity[[entity]] <- values %>%
+filter(entity_id %in% entity) %>%
+mutate(end_time = c(time[-1], run_time))
+}
+values <- bind_rows(values_by_entity)
+washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > power_threshhold) %>% tail(1) %>% pull(time)
+washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > power_threshhold) %>% tail(1) %>% pull(time)
+dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < power_threshhold) %>% tail(1) %>% pull(time)
+# ---- generate html
+current_status <- as.list(NULL)
+for (entity in entities$entity_id){
+current_status[[entity]] <- ifelse(values %>% filter(entity_id %in% entity) %>% tail(1) %>% pull(value) > power_threshhold, "on", "off")
+}
+plot_1week <- ggplot(data = values) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(date_breaks = "24 hours", date_labels = '%A', date_minor_breaks = "6 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "The past week",
+x = NULL,
+y = NULL,
+fill = NULL)
+plot_1day <- ggplot(data = values %>% filter(time >= max(values$end_time) - hours(24))) +
+geom_tile(aes(x = time + seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))/2),
+y = entity_id,
+width = seconds(round(as.numeric(difftime(end_time, time, unit = "secs")))),
+height = 0.5,
+fill = status)) +
+scale_y_discrete(breaks = entities$entity_id, labels = entities$name) +
+scale_x_datetime(breaks = seq(round_date(max(values$end_time), "4 hours") - hours(24), round_date(max(values$end_time), "4 hours"), by = "4 hours"), date_labels = '%I:%M %p', date_minor_breaks = "1 hours") +
+theme(axis.text.x = element_text(angle = 30, vjust = 0.5)) +
+labs(title = "Last 24 hours",
+x = NULL,
+y = NULL,
+fill = NULL)
+render("laundry_status.Rmd",
+output_dir = "html",
+output_file = "index.html")
+}
+for(i in 1:(cronjob_interval/update_interval)){
+message(Sys.time())
 update_data()
 Sys.sleep(60*update_interval)
 }

laundry_status.R

@@ -45,11 +45,11 @@ update_data <- function(){
   }
   values <- bind_rows(values_by_entity)
   
-  washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > power_threshhold) %>% tail(1) %>% pull(time)
-  washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < power_threshhold) %>% tail(1) %>% pull(time)
+  washer_last_on <- values %>% filter(entity_id == entities$entity_id[1], value > power_threshhold) %>% tail(1) %>% pull(end_time)
+  washer_last_off <- values %>% filter(entity_id == entities$entity_id[1], value < power_threshhold) %>% tail(1) %>% pull(end_time)
   
-  dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > power_threshhold) %>% tail(1) %>% pull(time)
-  dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < power_threshhold) %>% tail(1) %>% pull(time)
+  dryer_last_on <- values %>% filter(entity_id == entities$entity_id[2], value > power_threshhold) %>% tail(1) %>% pull(end_time)
+  dryer_last_off <- values %>% filter(entity_id == entities$entity_id[2], value < power_threshhold) %>% tail(1) %>% pull(end_time)
   # ---- generate html
   current_status <- as.list(NULL)
   for (entity in entities$entity_id){