ben/laundry_status
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

edited recent times

Browse Source
This commit is contained in:
Ben Varick 2023-11-07 14:37:02 -06:00
parent aaaa55186c
commit 6284a05f47
Signed by: ben
SSH Key Fingerprint: SHA256:jWnpFDAcacYM5aPFpYRqlsamlDyKNpSj3jj+k4ojtUo
3 changed files with 403 additions and 403 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

776
.Rhistory
View File

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

22
html/index.html
View File

File diff suppressed because one or more lines are too long

8
laundry_status.R
View File

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