## Animations generated in R version 4.4.1 (2024-06-14) using the package animation
library(animation)
library(RColorBrewer)
library(onlineforecast)
library(quantreg)
library(SparseM)
library(testthat)
library(devtools)
library(usethis)
for (i in k:(60)) {
    par(mfrow = c(2, 1))
    par(mar = c(2, 4, 2, 2))
    with(Pred_model, {
        plot(Dtrain$t[(i - 10):(i + k)], Dtrain$Ps[(i - 10):(i + 
            k)], bty = "l", lwd = 2, col = "black", pch = 19, 
            cex = 0.5, axes = FALSE, xaxt = "n", type = "n", 
            ylim = range(Dtrain$Ps[(i - 10):(i + k)], q0.5[i, 
              ], q0.95[i, ], q0.05[i, ], na.rm = T), main = "TimeAdaptive with Weights", 
            xlab = "Time", ylab = "Ps")
        axis(2)
        polygon(c(Dtrain$t[(i + 1):(i + k)], rev(Dtrain$t[(i + 
            1):(i + k)])), c(Pred_model$q0.05[i, ], rev(Pred_model$q0.2[i, 
            ])), col = colSeq[3], border = NA)
        polygon(c(Dtrain$t[(i + 1):(i + k)], rev(Dtrain$t[(i + 
            1):(i + k)])), c(Pred_model$q0.8[i, ], rev(Pred_model$q0.95[i, 
            ])), col = colSeq[3], border = NA)
        polygon(c(Dtrain$t[(i + 1):(i + k)], rev(Dtrain$t[(i + 
            1):(i + k)])), c(Pred_model$q0.2[i, ], rev(Pred_model$q0.5[i, 
            ])), col = colSeq[4], border = NA)
        polygon(c(Dtrain$t[(i + 1):(i + k)], rev(Dtrain$t[(i + 
            1):(i + k)])), c(Pred_model$q0.5[i, ], rev(Pred_model$q0.8[i, 
            ])), col = colSeq[4], border = NA)
        lines(Dtrain$t[(i - 10):(i + k)], Dtrain$Ps[(i - 
            10):(i + k)], col = "black", type = "b", lwd = 2)
        lines(Dtrain$t[(i + 1):(i + k)], q0.5[i, ], type = "b", 
            col = "grey", lwd = 2)
        axis.POSIXct(side = 1, x = Dtrain$t[(i - 10):(i + 
            k)], at = seq(from = Dtrain$t[(i - 10):(i + k)][1], 
            to = Dtrain$t[(i - 10):(i + k)][length(Dtrain$t[(i - 
              10):(i + k)])], by = "1 hour"), format = "%Y/%m/%d %H:%M \n %a", 
            las = 1, cex.axis = 1, srt = 45)
        plot(Dtrain$t[(i - 10):(i + k)], c(rep(NA, 11), as.numeric(Dtrain$I[i, 
            1:k])), type = "b", col = "steelblue", axes = FALSE, 
            xlab = "Time", ylab = "Temp", lwd = 2, ylim = range(Dtrain$I[i, 
              1:k], Dtrain$Iobs[(i + 1):(i + k)]))
        lines(Dtrain$t[(i + 1):(i + k)], Dtrain$Iobs[(i + 
            1):(i + k)], type = "b", col = "red", lwd = 2)
        axis(2)
        abline(h = 0, v = Dtrain$t[i], lty = 2, col = "lightgrey", 
            lwd = 2)
        legend("topleft", legend = c("Ta Obs", "Ta Pred"), 
            col = c("red", "steelblue"), lty = 1, cex = 1, 
            lwd = 2)
        i
        axis.POSIXct(side = 1, x = Dtrain$t[(i - 10):(i + 
            k)], at = seq(from = Dtrain$t[(i - 10):(i + k)][1], 
            to = Dtrain$t[(i - 10):(i + k)][length(Dtrain$t[(i - 
              10):(i + k)])], by = "1 hour"), format = "%Y/%m/%d %H:%M \n %a", 
            las = 1, cex.axis = 1, srt = 45)
    })
}
## R version 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Other packages: animation 2.7, RColorBrewer 1.1-3, onlineforecast
## 1.0.2, quantreg 5.99, SparseM 1.84-2, testthat 3.2.1.1, devtools 2.4.5,
## usethis 3.0.0