iccsa-21-wind

Wind Simulation Using High-Frequency Velocity Component Measurements
git clone https://git.igankevich.com/iccsa-21-wind.git
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daily-stats.R (1439B)

      1 library(DBI)
      2 
      3 source("R/common.R")
      4 
      5 db <- dbConnect(RSQLite::SQLite(), "samples/load-cell.sqlite3")
      6 RSQLite::initExtension(db)
      7 
      8 velocity = dbGetQuery(db,
      9                       "SELECT timestamp/(60*60*2) AS interval,
     10                       --STRFTIME('%Y-%m-%dT%H', DATETIME(timestamp, 'unixepoch')) AS timestamp,
     11                       timestamp,
     12                       t, x, y, z
     13                       FROM samples
     14                       ORDER BY timestamp")
     15 
     16 i <- 0
     17 result <- data.frame(interval=numeric(0),timestamp=numeric(0),
     18                      x_sd=numeric(0),y_sd=numeric(0),z_sd=numeric(0),
     19                      speed=numeric(0))
     20 c <- calibration_coefficients()
     21 unique_intervals <- unique(velocity$interval)
     22 pb <- txtProgressBar(min = 0, max = length(unique_intervals), style = 3)
     23 for (interval in unique_intervals) {
     24   v <- (velocity[velocity$interval==interval, ])
     25   v$x <- sample_to_speed(v$x, c$x1, c$x2)
     26   v$y <- sample_to_speed(v$y, c$y1, c$y2)
     27   v$z <- sample_to_speed(v$z, c$z1, c$z2)
     28   new_row = nrow(result)+1
     29   result[new_row, "interval"] <- interval
     30   result[new_row, "timestamp"] <- min(v$timestamp)
     31   result[new_row, "x_sd"] <- sd(v$x)
     32   result[new_row, "y_sd"] <- sd(v$y)
     33   result[new_row, "z_sd"] <- sd(v$z)
     34   result[new_row, "speed"] <- sqrt(var(v$x) + var(v$y) + var(v$z))
     35   i <- i + 1
     36   setTxtProgressBar(pb, i)
     37 }
     38 close(pb)
     39 write.table(result, "build/daily-stats", row.names=FALSE, quote=FALSE)
     40 
     41 dbDisconnect(db)