simulation

r-scripts/data/distribution.R

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+library(tidyverse, warn.conflicts = FALSE)
+library(DBI, warn.conflicts = FALSE)
+library(tidyr, warn.conflicts = FALSE)
+library(dplyr, warn.conflicts = FALSE)
+
+HOME <- Sys.getenv("HOME")
+Sys.setenv(PGHOST = "db.mainscnt.eu",
+           PGDATABASE = "power",
+           PGPORT = 5432,
+           PGUSER = "wn",
+           PGSSLMODE = "verify-ca",
+           PGSSLKEY = paste(HOME, "/keys/psql/wn-postgresql-client-2.key", sep=""),
+           PGSSLCERT = paste(HOME, "/keys/psql/wn-postgresql-client-2.crt", sep=""),
+           PGSSLROOTCERT = paste(HOME, "/keys/psql/postgres-ca.crt", sep=""))
+
+
+con <- dbConnect(RPostgres::Postgres())
+
+YEAR <- 2022
+res <- dbSendQuery(con, "
+  select 
+          date_trunc('day', time)::date as day,
+          avg(temperature) as temperature
+      from room_climate_measurement_t
+      where
+          category = 'Outdoor' and
+          location = 'Outdoor' and
+          extract('hour' from time) = 12 and
+          extract('year' from time) = $1
+      group by day
+      order by day
+")
+dbBind(res, list(YEAR))
+distribution <- dbFetch(res)
+dbClearResult(res)
+
+g <- ggplot(data = distribution, aes(x = temperature)) +
+  geom_histogram(binwidth = 1)
+
+print(g)
+