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

matrixToDataframe <- function(mat) {
    # convert a Ppr/Tpr matrix do a dataframe
    mat <- cbind(as.double(rownames(mat)), mat)  # new column for Tpr
    rownames(mat) <- NULL           # reset row names
    df <- as.data.frame(mat)     # dataframe
    names(df)[1] <- "Tpr"
    df
}

matrixWithCorrelation <- function(ppr_vector, tpr_vector, corr.Function) {
    # create a matrix using a z-factor correlation function and sapply
    corr_matrix <- sapply(ppr_vector, function(x)  
      sapply(tpr_vector, function(y) corr.Function(pres.pr = x, temp.pr = y))) 

    rownames(corr_matrix) <- tpr_vector
    colnames(corr_matrix) <- ppr_vector
    corr_matrix
}

combineCorrWithSK <- function(sk_df, co_df) {
    # combine correlation tidy DF with Standing-Katz tidy DF
    sk_tidy <- tidyr::gather(sk_df, "ppr", "z.chart", 2:ncol(sk_df))
    co_tidy <- tidyr::gather(co_df, "ppr", "z.calcs", 2:ncol(co_df))

    sk_co_tidy <- cbind(sk_tidy, z.calc = co_tidy$z.calcs)
    sk_co_tidy$dif <- sk_co_tidy$z.chart  - sk_co_tidy$z.calc
    colnames(sk_co_tidy)[1:2] <- c("Tpr", "Ppr")
    sk_co_tidy
}

createTidyFromMatrix <- function(ppr_vector, tpr_vector, correlation = "HY") {
    sk_matrix <- getStandingKatzMatrix(ppr_vector = ppr2, tpr_vector = tpr2, 
                                       pprRange = "lp")
    hy_matrix <- matrixWithCorrelation(ppr2, tpr2, corr.Function = z.HallYarborough)

    sk_df <- matrixToDataframe(sk_matrix)
    hy_df <- matrixToDataframe(hy_matrix)

    sk_hy_tidy <- combineCorrWithSK(sk_df, hy_df)
    sk_hy_tidy
}


tpr2 <- c(1.05, 1.1, 1.2, 1.4, 1.5, 1.7, 1.8, 1.9, 2.0) 
ppr2 <- c(0.5, 1.0, 1.5) 

createTidyFromMatrix(ppr2, tpr2)

createTidyFromMatrix2 <- function(ppr_vector, tpr_vector, correlation = "HY") {
    # generic function
    # convert to tidy table for z values calculated by HY and read from SK chart
    corr <- tolower(correlation)

    sk_matrix <- getStandingKatzMatrix(ppr_vector = ppr2, tpr_vector = tpr2, 
                                       pprRange = "lp")

    # create tidy data for z from SK chart
    sk_matrix_t <- cbind(as.double(rownames(sk_matrix)), sk_matrix)  # new column for Tpr
    rownames(sk_matrix_t) <- NULL           # reset row names
    sk_df <- as.data.frame(sk_matrix_t)  # dataframe

    hy_matrix <- sapply(ppr2, function(x)  
        sapply(tpr2, function(y) z.HallYarborough(pres.pr = x, temp.pr = y))) 

    rownames(hy_matrix) <- tpr2
    colnames(hy_matrix) <- ppr2 

    hy_matrix_t <- cbind(as.double(rownames(hy_matrix)), hy_matrix)
    rownames(hy_matrix_t) <- NULL
    hy_df <- as.data.frame(hy_matrix_t)

    sk_tidy <- tidyr::gather(sk_df, "ppr", "z.chart", 2:ncol(sk_df))
    hy_tidy <- tidyr::gather(hy_df, "ppr", "z.calcs", 2:ncol(hy_df))

    sk_hy_tidy <- cbind(sk_tidy, z.calc = hy_tidy$z.calcs)
    sk_hy_tidy$dif <- sk_hy_tidy$z.chart  - sk_hy_tidy$z.calc

    colnames(sk_hy_tidy)[1:2] <- c("Tpr", "Ppr")
    sk_hy_tidy
}


tpr2 <- c(1.05, 1.1, 1.2, 1.4, 1.5, 1.7, 1.8, 1.9, 2.0) 
ppr2 <- c(0.5, 1.0, 1.5) 

createTidyFromMatrix2(ppr2, tpr2)

library(zFactor)



# generic function
# convert to tidy table for z values calculated by HY and read from SK chart
correlation = "HY"
corr <- tolower(correlation)

tpr2 <- c(1.05, 1.1, 1.2, 1.4, 1.5) 
ppr2 <- c(0.5, 1.0, 1.5) 

sk_matrix <- getStandingKatzMatrix(ppr_vector = ppr2, tpr_vector = tpr2, pprRange = "lp")
hy_matrix <- matrixWithCorrelation(ppr2, tpr2, corr.Function = z.HallYarborough)

sk_df <- matrixToDataframe(sk_matrix)
hy_df <- matrixToDataframe(hy_matrix)

sk_hy_tidy <- combineCorrWithSK(sk_df, hy_df)
sk_hy_tidy

sapply(ppr2, function(x)  
    sapply(tpr2, function(y) z.HallYarborough(pres.pr = x, temp.pr = y)))

createTidyFromMatrix0 <- function(correlation = "HY") {
    # generic function
    # convert to tidy table for z values calculated by HY and read from SK chart
    pkg_data_path <- system.file("data", package = "zFactor")

    corr <- tolower(correlation)
    # rda_name <- paste(paste("z", corr, "7p4t", sep = "_"), "rda", sep = ".")
    # ds_name <- paste(pkg_data_path, rda_name, sep = "/")
    # corr_rda_file <- paste(pkg_data_path, rda_name, sep = "/")

    # load both tables (matrices)
    # load(file = "./data/z_sk_chart_7p4t.rda")
    # load(file = corr_rda_file)
    tpr2 <- c(1.05, 1.1, 1.2) 
    ppr2 <- c(0.5, 1.0, 1.5) 

    sk_chart <- getStandingKatzMatrix(ppr_vector = ppr2, tpr_vector = tpr2, pprRange = "lp")

    # create tidy data for z from SK chart
    sk_short <- cbind(as.double(rownames(sk_short)), sk_short)  # new column for Tpr
    rownames(sk_short) <- NULL           # reset row names
    .z_chart <- as.data.frame(sk_short)  # dataframe

    hy_short <- sapply(ppr2, function(x)  
        sapply(tpr2, function(y) z.HallYarborough(pres.pr = x, temp.pr = y))) 

    hy_short <- cbind(as.double(rownames(hy_short)), hy_short)
    rownames(hy_short) <- NULL
    .z_calcs <- as.data.frame(hy_short)

    z_chart <- tidyr::gather(.z_chart, "ppr", "z.chart", 2:8)
    z_calcs <- tidyr::gather(.z_calcs, "ppr", "z.calcs", 2:8)

    hy_dif <- cbind(z_chart, z.calc = z_calcs$z.calcs)
    hy_dif$dif <- hy_dif$z.chart  - hy_dif$z.calc

    colnames(hy_dif)[1:2] <- c("Tpr", "Ppr")

    dif_name <- paste(paste(corr, "dif", sep = "_"), "rda", sep = ".")
    dif_file <- paste(pkg_data_path, dif_name, sep = "/")
    save(hy_dif, file = dif_file)

}


createTidyFromMatrix0()

library(zFactor)

tpr2 <- c(1.05, 1.1, 1.2) 
ppr2 <- c(0.5, 1.0, 1.5) 


sk2 <- getStandingKatzMatrix(ppr_vector = ppr2, tpr_vector = tpr2, pprRange = "lp")
sk2

library(zFactor)

tpr_vec <- c(1.4, 1.5, 1.6, 1.7, 1.8, 1.9)
ppr_vec <- c(0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5)

getStandingKatzMatrix(ppr_vector = ppr_vec, tpr_vector = tpr_vec)

library(zFactor)

tpr_vec <- c(1.4, 1.5, 1.6, 1.7, 1.8, 1.9)
ppr_vec <- c(0.5, 1.0, 2.5, 3.5, 4.5, 5.5, 6.5)

getStandingKatzMatrix(ppr_vector = ppr_vec, tpr_vector = tpr_vec)