R/Dranchuk-Purvis-Robinson.R
Dranchuk-Purvis-Robinson.RdDranchuk-Purvis-Robinson correlation
z.DranchukPurvisRobinson(pres.pr, temp.pr, tolerance = 1e-13, verbose = FALSE)
| pres.pr | pseudo-reduced pressure |
|---|---|
| temp.pr | pseudo-reduced temperature |
| tolerance | controls the iteration accuracy |
| verbose | print internal |
## calculate for one Tpr curve at a Ppr z.DranchukPurvisRobinson(pres.pr = 1.5, temp.pr = 2.0)#> [1] 0.9546382## For vectors of Ppr and Tpr: ppr <- c(0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5) tpr <- c(1.3, 1.5, 1.7, 2) z.DranchukPurvisRobinson(pres.pr = ppr, temp.pr = tpr)#> 0.5 1.5 2.5 3.5 4.5 5.5 6.5 #> 1.3 0.9197157 0.7525940 0.6366665 0.6337883 0.6891997 0.7650171 0.8480804 #> 1.5 0.9504834 0.8583491 0.7926325 0.7720713 0.7914322 0.8348883 0.8915239 #> 1.7 0.9677844 0.9121791 0.8752677 0.8630002 0.8743271 0.9033216 0.9440582 #> 2 0.9822021 0.9546382 0.9399310 0.9391490 0.9512966 0.9740256 1.0047347## create a matrix of z values tpr2 <- c(1.05, 1.1, 1.2, 1.3) ppr2 <- c(0.5, 1.0, 1.5, 2, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5) sk_corr_2 <- createTidyFromMatrix(ppr2, tpr2, correlation = "DPR") tibble::as_tibble(sk_corr_2)#> # A tibble: 52 x 5 #> Tpr Ppr z.chart z.calc dif #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 1.05 0.5 0.829 0.830 -0.000976 #> 2 1.1 0.5 0.854 0.857 -0.00264 #> 3 1.2 0.5 0.893 0.894 -0.00146 #> 4 1.3 0.5 0.916 0.920 -0.00372 #> 5 1.05 1 0.589 0.586 0.00333 #> 6 1.1 1 0.669 0.676 -0.00689 #> 7 1.2 1 0.779 0.777 0.00205 #> 8 1.3 1 0.835 0.836 -0.000989 #> 9 1.05 1.5 0.253 0.285 -0.0320 #> 10 1.1 1.5 0.426 0.443 -0.0169 #> # … with 42 more rows