In f0nzie/zFactor: Calculate the Compressibility Factor 'z' for Hydrocarbon Gases

Boxplots of MPE for selected correlations

library(zFactor)
qcorrs <- z.stats_quantile("MPE")
scorrs <- qcorrs[, c("HY", "DAK", "DPR", "N10")]

par(mfrow = c(1,2))
boxplot(scorrs,  ylim= c(-2, 25), cex = 1.5, las=2, main = "MPE, y = (-2, 25)")
grid()

boxplot(scorrs,  ylim= c(-2, 2), cex = 1.5, las=2, main = "MPE, y = (-2, 2)")
grid()

MPE with with free y scale for all correlations

library(zFactor)
qcorrs <- z.stats_quantile("MPE")

boxplot(qcorrs,  cex = 1.5, las=2, main = "MPE")
grid()

Boxplots for MAE at different `y` scale

library(zFactor)
qcorrs <- z.stats_quantile("MPE")

par(mfrow = c(1,3))
boxplot(qcorrs,  ylim= c(-600, 100), cex = 1.5, las=2, main = "MPE, y = (-4, 100)")
grid()
boxplot(qcorrs,  ylim= c(-4, 30), cex = 1.5, las=2, main = "MPE, y = (-4, 30)")
grid()
boxplot(qcorrs,  ylim= c(-4, 6), cex = 1.5, las=2, main = "MPE, y = (-4, 6)")
grid()

Boxplots for four statistical indicators for all correlations

library(zFactor)

qcorrs <- z.stats_quantile("RMSE")
par(mfrow = c(2,2))
boxplot(qcorrs, log = "y", ylim =  c(1e-6, 1e3), las=2, main = "RMSE")
grid()

qcorrs <- z.stats_quantile("MAPE")
boxplot(qcorrs, log = "y", ylim =  c(1e-6, 1e3), las=2, main = "MAPE")
grid()

qcorrs <- z.stats_quantile("MSE")
boxplot(qcorrs, log = "y", ylim = c(1e-12, 1e3), las=2, main = "MSE")
grid()

qcorrs <- z.stats_quantile("RSS")
boxplot(qcorrs, log = "y", ylim = c(1e-12, 1e3), las=2, main = "RSS")
grid()

Using `z.stats_quantile` to all correlations

library(zFactor)
qcorrs <- z.stats_quantile("RMSE")

boxplot(qcorrs, log = "y", ylim =  c(1e-6, 1e3), main = "RMSE")
grid()

# MAPE
boxplot(qcorrs, log = "y", ylim =  c(1e-5, 1e3), main = "MAPE")
grid()

# MSE
boxplot(qcorrs, log = "y", ylim = c(1e-6, 1e3), main = "MSE")
grid()

# RSE
boxplot(qcorrs, log = "y", ylim = c(1e-6, 1e3), main = "RSE")
grid()

# MAE
boxplot(qcorrs, log = "y", ylim = c(1e-6, 1e3), main = "MAE")
grid()

library(zFactor)

z.stats()

z.stats_quantile <- function(stat = "MAPE", ylim, ...) {
    cols <- ncol(z.stats())
    z.stats_stats <- names(z.stats())[3:cols]
    corrs <- zFactor:::z_correlations$short

    qcorrs <- sapply(corrs, function(corr) quantile(z.stats(corr)[[stat]] ))

    boxplot(qcorrs, log = "y", ylim = ylim)
    grid()
    # boxplot(qcorrs, log = "y")
    # abline(h=0.1, col = "blue")
}

z.stats_quantile("RMSE", c(1e-6, 1000))
# z.stats_quantile("MPE", c(1e-1, 100))
z.stats_quantile("MAPE", c(1e-4, 1000))
z.stats_quantile("MSE", c(1e-12, 1e3))
z.stats_quantile("RSS", ylim = c(1e-12, 1e4))
z.stats_quantile("MAE", c(1e-6, 1000))

library(zFactor)
# quantile for MAPE all correlations
stat = "RMSLE"
cols <- ncol(z.stats())
z.stats_stats <- names(z.stats())[3:cols]
corrs <- zFactor:::z_correlations$short

qcorrs <- sapply(corrs, function(corr) quantile(z.stats(corr)[[stat]] ))
qcorrs

boxplot(qcorrs, log = "y", ylim = c(1e-12, 1e12))
# abline(h=0.1, col = "blue")

library(zFactor)
# quantile for MAPE all correlations
stat = "MPE"
cols <- ncol(z.stats())
z.stats_stats <- names(z.stats())[3:cols]
corrs <- zFactor:::z_correlations$short


qcorrs <- sapply(corrs, function(corr) quantile(z.stats(corr)[[stat]] ))
qcorrs
par(mfrow = c(1,3))
boxplot(qcorrs,  ylim= c(-4, 100), cex = 1.5, las=2)
grid()
boxplot(qcorrs,  ylim= c(-4, 10), cex = 1.5, las=2)
grid()
boxplot(qcorrs,  ylim= c(-4, 6), cex = 1.5, las=2)
grid()
# abline(h=5, col = "gray")
# abline(h=0, col = "red")
# abline(h=-0.5, col = "gray")
# abline(h=-1, col = "gray")

op <- par(mfcol = 1:2)
with(iris,
     {
     plot(Sepal.Length, Sepal.Width, col = as.integer(Species),
          xlim = c(4, 8), ylim = c(2, 4.5), panel.first = grid(),
          main = "with(iris,  plot(...., panel.first = grid(), ..) )")

     plot(Sepal.Length, Sepal.Width, col = as.integer(Species),
          panel.first = grid(3, lty = 1, lwd = 2),
          main = "... panel.first = grid(3, lty = 1, lwd = 2), ..")
     }
    )
par(op)

library(zFactor)
# quantile for MAPE all correlations
stat = "MAPE"
cols <- ncol(z.stats())
z.stats_stats <- names(z.stats())[3:cols]
corrs <- zFactor:::z_correlations$short


qcorrs <- sapply(corrs, function(corr) quantile(z.stats(corr)[[stat]] ))
qcorrs

boxplot(qcorrs, log = "y", ylim = c(1e-4, 1000))
abline(h=0.1, col = "blue")

boxplot(qcorrs, log = "y", ylim = c(1e-4, 1000))
abline(h=0.1, col = "blue")

library(zFactor)
zbb <- z.stats("BB")
zbb

max(zbb$MAPE)

quantile(zbb$MAPE)

# MAPE of one correlation
stat = "MAPE"
cols <- ncol(z.stats())
z.stats_stats <- names(z.stats())[3:cols]
corrs <- zFactor:::z_correlations$short

custom_functions <- c("mean", "max", "min", "median", "Mode")

sapply(corrs, function(corr)
            sapply(custom_functions, function(f) get(f)( z.stats(corr)[[stat]] )))

# quantile for MAPE all correlations
stat = "MAPE"
cols <- ncol(z.stats())
z.stats_stats <- names(z.stats())[3:cols]
corrs <- zFactor:::z_correlations$short


qcorrs <- sapply(corrs, function(corr) quantile(z.stats(corr)[[stat]] ))
qcorrs

boxplot(qcorrs, log = "y", ylim = c(1e-4, 1000))
abline(h=0.1, col = "blue")

boxplot(qcorrs[, "BB"], log = "y", ylim = c(1e-3, 1000))

boxplot(qcorrs[,2], log = "y")

boxplot(qcorrs[,3], log = "y")

boxplot(qcorrs[, "DPR"], log = "y")

boxplot(qcorrs[, "SH"], log = "y")

boxplot(qcorrs[, "N10"], log = "y")

boxplot(qcorrs[, "PP"], log = "y", ylim = c(1e-3, 1000))

boxplot(qcorrs, log = "y", ylim = c(1e-4, 1000))
abline(h=0.1, col = "blue")

## maybe change the desired number of tick marks:  par(lab = c(mx, my, 7))
op <- par(mfcol = 1:2)
with(iris,
     {
     plot(Sepal.Length, Sepal.Width, col = as.integer(Species),
          xlim = c(4, 8), ylim = c(2, 4.5), panel.first = grid(),
          main = "with(iris,  plot(...., panel.first = grid(), ..) )")
     plot(Sepal.Length, Sepal.Width, col = as.integer(Species),
          panel.first = grid(3, lty = 1, lwd = 2),
          main = "... panel.first = grid(3, lty = 1, lwd = 2), ..")
     }
    )
par(op)