2023-11-06 16:18:30 -06:00
|
|
|
#setup ----
|
|
|
|
library(tidyverse)
|
|
|
|
library(influxdbclient)
|
|
|
|
library(rmarkdown)
|
|
|
|
|
2023-11-06 17:09:10 -06:00
|
|
|
setwd("/laundry_status")
|
2023-11-06 16:18:30 -06:00
|
|
|
|
|
|
|
# parameters needed to make connection to Database
|
2023-11-06 17:08:05 -06:00
|
|
|
token <- substr(read_file("data/api_key"), 1, 88)
|
2023-11-06 16:18:30 -06:00
|
|
|
org = "home_assistant"
|
|
|
|
bucket = "home_assistant"
|
|
|
|
## make connection to the influxDB bucket
|
|
|
|
home_assistant <- InfluxDBClient$new(url = "https://influxdb.dendroalsia.net",
|
|
|
|
token = token,
|
|
|
|
org = org)
|
|
|
|
|
|
|
|
|
|
|
|
values <- home_assistant$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 <- bind_rows(values)
|
|
|
|
values <- values %>%
|
|
|
|
rename(value = "_value")
|
|
|
|
values <- values %>%
|
|
|
|
mutate(status = ifelse(value > 1, "on", "off"),
|
|
|
|
end_time = c(values$time + minutes(1)))
|
|
|
|
|
|
|
|
# ---- set variables
|
|
|
|
entities <- data.frame(name = c("washing machine", "dryer"), entity_id = c("lamp_a_power", "lamp_b_power"))
|
|
|
|
|
|
|
|
# ---- generate html
|
|
|
|
current_status <- as.list(NULL)
|
|
|
|
for (entity in entities$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(date_breaks = "4 hours", date_labels = '%I:%M %p', 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")
|