calculateRefinedCriticalDiameter: Calculate several versions of critical diameter: ltest,...
In jasonelaw/nrsa: Calculate metrics for NRSA protocol data.
Description
Usage
Arguments
Details
Value
References
Examples
View source: R/calculateRelativeBedStability.R
Description
These functions can be used to calculate several versions of the critical particle
diameter:
a crude estimate via calculateCrudeCriticalDiameter
several more refined ones via calculateRefinedCriticalDiameter
a research based one due to Kauffman 2007 via calculateCriticalDiameterKaufmann
Usage
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calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq,
old.version = F, xbkf_w = NULL, xwidth = NULL)
calculateCrudeCriticalDiameter(xdepth, xslope)
calculateCriticalDiameterKaufmann(xdepth, xslope, rp100, xbkf_h, v1w_msq,
lsub_dmm)
Arguments
xdepth
average depth in centimeters
xslope
average slope in percent
rp100
average residual depth in centimeters
xbkf_h
average bankfull height in meters
v1w_msq
volume lwd in cubic meters / 100 square meeters
old.version
Calculate old version of logged critical diameter that were based on the
wood density when it accidentally used the wetted widths instead of the
bankfull widths.
xbkf_w
average bankfull width in meters; must be supplied when old.version = T.
xwidth
average width in meters; must be supplied when old.version = T.
lsub_dmm
mean log10(substrate diameter) in millimeters
Details
calculateRefinedCriticalDiameter is used to calculate the metrics
ldmb_bw4 (with old.version = T), ldmb_bw5, and s_ldmb_bw5 (when the rp100
argument is as returned by calculateS_RP100).
Value
the log10(critical diameter)
References
Kaufmann, P.R. et al., A roughness-corrected index of relative bed stability
for regional stream surveys. Geomorphology (2007)
Examples
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library(reshape2)
x <- structure(list(UID = c("1", "10", "11", "2", "3", "4", "5", "6", "7", "8", "9"),
lsub_dmm = c(1, -1.31451, 1.18991, 1, 1, 1, 0.5408, 3.204, 0.75694, 0.37664, 0.31911),
lsub2dmm = c(2, -1.31451, NA, 2, 2, 2, 0.5408, 3.19253, 0.7244, 0.37664, 0.29885),
rp100 = c(1, 10.3489, 112.73, 1, 1, 1, 19.0993, 28.3768, 6.4191, 27.2566, 22.2393),
sddepth = c(3.95494014, 8.8661, 1.69386, 3.95494014, 3.95494014,
3.95494014, 27.7557, 44.2636, 10.4878, 22.6112, 28.7622),
v1w_msq = c(1, NA, 0.005818, NA, NA, 0.3, 4e-05, 0.01461, 0.37977, 0.00015, NA),
xbkf_h = c(1, 0.33636, 1.47273, 1, 1, 1, 0.75545, 0.61818, 0.3, 0.4, 0),
xbkf_w = c(1, 3.718, 255.273, 1, 1, 1, 21.818, 6.673, 2.927, 3.4818, 8.745),
xdepth = c(1, 42.67, 3.29555, 1, 1, 1, 51.16, 71.19, 24.007, 31.033, 66.51),
xfc_lwd = c(1, 0.00455, 0.00455, 1, 0, NA, 0, 0.01364, 0.11818, 0, 0),
xslope = c(1, 0.775, 0.036, 1, 1, 1, 1.22, 9.75, 8.05, 0, 1.57),
xwidth = c(1, 3.085, 163.364, 1, 1, 1, 10.0105, 5.255, 2.445, 2.385, 9.1474),
PROTOCOL = c("WADEABLE", "WADEABLE", "BOATABLE", "WADEABLE",
"WADEABLE", "WADEABLE", "WADEABLE",
"WADEABLE", "WADEABLE", "WADEABLE", "WADEABLE")),
.Names = c("UID", "lsub_dmm", "lsub2dmm", "rp100", "sddepth", "v1w_msq", "xbkf_h",
"xbkf_w", "xdepth", "xfc_lwd", "xslope", "xwidth", "PROTOCOL"),
row.names = c(NA, -11L),
class = "data.frame")
x$xslope <- forceSlopeGt0(x$xslope)
x$xdepth <- fixBoatableDepthUnits(x$xdepth, x$PROTOCOL == 'WADEABLE')
x$sddepth <- fixBoatableDepthUnits(x$sddepth, x$PROTOCOL == 'WADEABLE')
x$s_rp100 <- calculateS_RP100(x$xslope, x$sddepth)
x$v1w_msq <- fillMissingLWD(x$v1w_msq, x$xfc_lwd)
x$ltest <- with(x, calculateCrudeCriticalDiameter(xdepth, xslope))
x$ldmb_bw5 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq))
x$s_ldmb_bw5 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, s_rp100, xbkf_h, v1w_msq))
x$ldmb_bw4 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq, T, xbkf_w, xwidth))
x <- cbind(x, with(x, calculateCriticalDiameterKaufmann(xdepth, xslope, rp100, xbkf_h, v1w_msq, lsub_dmm)))
x <- cbind(x, with(x, calculateRelativeBedStability(lsub_dmm, lsub2dmm, ltest, ldmb_bw4, ldmb_bw5, s_ldmb_bw5, ldcbf_g08)))
metsExpected <-
structure(list(UID = c("1", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2",
"2", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3",
"3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", "4", "4",
"4", "4", "4", "4", "4", "4", "4", "4", "4", "5", "5", "5", "5",
"5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "6", "6", "6",
"6", "6", "6", "6", "6", "6", "6", "6", "6", "6", "6", "7", "7",
"7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "8",
"8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8",
"9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9",
"9", "10", "10", "10", "10", "10", "10", "10", "10", "10", "10",
"10", "10", "10", "10", "11", "11", "11", "11", "11", "11", "11",
"11", "11", "11", "11", "11", "11", "11"),
METRIC = c("ltest",
"lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5",
"s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5",
"lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08",
"s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4",
"lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6",
"Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst",
"ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5",
"s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08",
"lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5",
"ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6",
"s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100",
"ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5",
"s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5",
"lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08",
"s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4",
"lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6",
"Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst",
"ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5",
"s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08",
"lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5",
"ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6",
"s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100",
"ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100"),
RESULT = c(-0.164309429,
1.164309429, 0.835690571, 0.831325766, -0.164309429, 1.164309429,
0.164309429, 0.168674234, 1.164309429, 1.168674234, 113.9277151,
2.056629387, -1.056629387, 2, -0.164309429, 1.164309429, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, -0.164309429, 1.164309429,
1.835690571, 1.831325766, 1.835690571, -0.835690571, -0.835690571,
-0.831325766, 0.164309429, 0.168674234, NA, NA, NA, 2, -0.164309429,
1.164309429, 1.437750563, 1.426755179, 0.437750563, 0.562249437,
-0.437750563, -0.426755179, 0.562249437, 0.573244821, 146.4599268,
2.165718813, -1.165718813, 2, 1.630980938, -1.090180938, 1.95385339,
1.941619453, 1.953783007, -1.412983007, -1.41305339, -1.400819453,
-1.41305339, -1.400819453, 105.9303106, 2.025020246, -1.484220246,
22.08840009, 2.67711418, 0.52688582, 2.832055426, 2.842904539,
2.815915646, 0.388084354, 0.371944574, 0.361095461, 0.360474574,
0.349625461, 1588.155449, 3.200893009, 0.003106991, 25.80377156,
2.121824344, -1.364884344, 1.418982992, 1.436906832, 0.418982992,
0.337957008, -0.662042992, -0.679966832, -0.694582992, -0.712506832,
148.8617733, 2.172783188, -1.415843188, 4.41366392, -0.672485667,
1.049125667, -0.523367109, -0.768424143, -0.523802116, 0.900442116,
0.900007109, 1.145064143, 0.900007109, 1.145064143, 0.32636017,
-0.486302849, 0.862942849, 46.120606, 1.854477172, -1.535367172,
1.677706613, 1.680788736, 1.677706613, -1.358596613, -1.358596613,
-1.361678736, -1.378856613, -1.381938736, NA, NA, NA, 21.92365464,
1.355114917, -2.669624917, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 5.80084933, 0.909920977, 0.279989023, 0.951821206, -0.080588008,
0.949639991, 0.240270009, 0.238088794, 1.2704980082, NA, NA,
17.97017283, 1.254552254, -0.064642254, 441.9807675)),
.Names = c("UID", "METRIC", "RESULT"), row.names = c(NA, 154L), class = "data.frame")
mets <- melt(subset(x, select = -PROTOCOL), id.var = 'UID', variable.name = 'METRIC', value.name = 'RESULT')
res <- merge(metsExpected, mets, by = c('UID', 'METRIC'), all.x = T)
res$diff <- abs(res$RESULT.x - res$RESULT.y)
res
jasonelaw/nrsa documentation built on Nov. 8, 2019, 11:34 a.m.
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Description Usage Arguments Details Value References Examples
View source: R/calculateRelativeBedStability.R
Description
These functions can be used to calculate several versions of the critical particle diameter:
a crude estimate via
calculateCrudeCriticalDiameterseveral more refined ones via
calculateRefinedCriticalDiametera research based one due to Kauffman 2007 via
calculateCriticalDiameterKaufmann
Usage
1 2 3 4 5 6 7 | calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq,
old.version = F, xbkf_w = NULL, xwidth = NULL)
calculateCrudeCriticalDiameter(xdepth, xslope)
calculateCriticalDiameterKaufmann(xdepth, xslope, rp100, xbkf_h, v1w_msq,
lsub_dmm)
|
Arguments
xdepth |
average depth in centimeters |
xslope |
average slope in percent |
rp100 |
average residual depth in centimeters |
xbkf_h |
average bankfull height in meters |
v1w_msq |
volume lwd in cubic meters / 100 square meeters |
old.version |
Calculate old version of logged critical diameter that were based on the wood density when it accidentally used the wetted widths instead of the bankfull widths. |
xbkf_w |
average bankfull width in meters; must be supplied when old.version = T. |
xwidth |
average width in meters; must be supplied when old.version = T. |
lsub_dmm |
mean log10(substrate diameter) in millimeters |
Details
calculateRefinedCriticalDiameter is used to calculate the metrics
ldmb_bw4 (with old.version = T), ldmb_bw5, and s_ldmb_bw5 (when the rp100
argument is as returned by calculateS_RP100).
Value
the log10(critical diameter)
References
Kaufmann, P.R. et al., A roughness-corrected index of relative bed stability for regional stream surveys. Geomorphology (2007)
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | library(reshape2)
x <- structure(list(UID = c("1", "10", "11", "2", "3", "4", "5", "6", "7", "8", "9"),
lsub_dmm = c(1, -1.31451, 1.18991, 1, 1, 1, 0.5408, 3.204, 0.75694, 0.37664, 0.31911),
lsub2dmm = c(2, -1.31451, NA, 2, 2, 2, 0.5408, 3.19253, 0.7244, 0.37664, 0.29885),
rp100 = c(1, 10.3489, 112.73, 1, 1, 1, 19.0993, 28.3768, 6.4191, 27.2566, 22.2393),
sddepth = c(3.95494014, 8.8661, 1.69386, 3.95494014, 3.95494014,
3.95494014, 27.7557, 44.2636, 10.4878, 22.6112, 28.7622),
v1w_msq = c(1, NA, 0.005818, NA, NA, 0.3, 4e-05, 0.01461, 0.37977, 0.00015, NA),
xbkf_h = c(1, 0.33636, 1.47273, 1, 1, 1, 0.75545, 0.61818, 0.3, 0.4, 0),
xbkf_w = c(1, 3.718, 255.273, 1, 1, 1, 21.818, 6.673, 2.927, 3.4818, 8.745),
xdepth = c(1, 42.67, 3.29555, 1, 1, 1, 51.16, 71.19, 24.007, 31.033, 66.51),
xfc_lwd = c(1, 0.00455, 0.00455, 1, 0, NA, 0, 0.01364, 0.11818, 0, 0),
xslope = c(1, 0.775, 0.036, 1, 1, 1, 1.22, 9.75, 8.05, 0, 1.57),
xwidth = c(1, 3.085, 163.364, 1, 1, 1, 10.0105, 5.255, 2.445, 2.385, 9.1474),
PROTOCOL = c("WADEABLE", "WADEABLE", "BOATABLE", "WADEABLE",
"WADEABLE", "WADEABLE", "WADEABLE",
"WADEABLE", "WADEABLE", "WADEABLE", "WADEABLE")),
.Names = c("UID", "lsub_dmm", "lsub2dmm", "rp100", "sddepth", "v1w_msq", "xbkf_h",
"xbkf_w", "xdepth", "xfc_lwd", "xslope", "xwidth", "PROTOCOL"),
row.names = c(NA, -11L),
class = "data.frame")
x$xslope <- forceSlopeGt0(x$xslope)
x$xdepth <- fixBoatableDepthUnits(x$xdepth, x$PROTOCOL == 'WADEABLE')
x$sddepth <- fixBoatableDepthUnits(x$sddepth, x$PROTOCOL == 'WADEABLE')
x$s_rp100 <- calculateS_RP100(x$xslope, x$sddepth)
x$v1w_msq <- fillMissingLWD(x$v1w_msq, x$xfc_lwd)
x$ltest <- with(x, calculateCrudeCriticalDiameter(xdepth, xslope))
x$ldmb_bw5 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq))
x$s_ldmb_bw5 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, s_rp100, xbkf_h, v1w_msq))
x$ldmb_bw4 <- with(x, calculateRefinedCriticalDiameter(xdepth, xslope, rp100, xbkf_h, v1w_msq, T, xbkf_w, xwidth))
x <- cbind(x, with(x, calculateCriticalDiameterKaufmann(xdepth, xslope, rp100, xbkf_h, v1w_msq, lsub_dmm)))
x <- cbind(x, with(x, calculateRelativeBedStability(lsub_dmm, lsub2dmm, ltest, ldmb_bw4, ldmb_bw5, s_ldmb_bw5, ldcbf_g08)))
metsExpected <-
structure(list(UID = c("1", "1", "1", "1", "1", "1", "1", "1",
"1", "1", "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2",
"2", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3",
"3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", "4", "4",
"4", "4", "4", "4", "4", "4", "4", "4", "4", "5", "5", "5", "5",
"5", "5", "5", "5", "5", "5", "5", "5", "5", "5", "6", "6", "6",
"6", "6", "6", "6", "6", "6", "6", "6", "6", "6", "6", "7", "7",
"7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "7", "8",
"8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8", "8",
"9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9", "9",
"9", "10", "10", "10", "10", "10", "10", "10", "10", "10", "10",
"10", "10", "10", "10", "11", "11", "11", "11", "11", "11", "11",
"11", "11", "11", "11", "11", "11", "11"),
METRIC = c("ltest",
"lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5",
"s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5",
"lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08",
"s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4",
"lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6",
"Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst",
"ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5",
"s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08",
"lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5",
"ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6",
"s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100",
"ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5",
"s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5",
"lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08",
"s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4",
"lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6",
"Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100", "ltest", "lrbs_tst",
"ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4", "lrbs_bw5",
"s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08",
"lrbs_g08", "s_rp100", "ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5",
"ldmb_bw4", "lrbs_bw4", "lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6",
"s_lrbs_bw6", "Dcbf_g08", "ldcbf_g08", "lrbs_g08", "s_rp100",
"ltest", "lrbs_tst", "ldmb_bw5", "s_ldmb_bw5", "ldmb_bw4", "lrbs_bw4",
"lrbs_bw5", "s_lrbs_bw5", "lrbs_bw6", "s_lrbs_bw6", "Dcbf_g08",
"ldcbf_g08", "lrbs_g08", "s_rp100"),
RESULT = c(-0.164309429,
1.164309429, 0.835690571, 0.831325766, -0.164309429, 1.164309429,
0.164309429, 0.168674234, 1.164309429, 1.168674234, 113.9277151,
2.056629387, -1.056629387, 2, -0.164309429, 1.164309429, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, -0.164309429, 1.164309429,
1.835690571, 1.831325766, 1.835690571, -0.835690571, -0.835690571,
-0.831325766, 0.164309429, 0.168674234, NA, NA, NA, 2, -0.164309429,
1.164309429, 1.437750563, 1.426755179, 0.437750563, 0.562249437,
-0.437750563, -0.426755179, 0.562249437, 0.573244821, 146.4599268,
2.165718813, -1.165718813, 2, 1.630980938, -1.090180938, 1.95385339,
1.941619453, 1.953783007, -1.412983007, -1.41305339, -1.400819453,
-1.41305339, -1.400819453, 105.9303106, 2.025020246, -1.484220246,
22.08840009, 2.67711418, 0.52688582, 2.832055426, 2.842904539,
2.815915646, 0.388084354, 0.371944574, 0.361095461, 0.360474574,
0.349625461, 1588.155449, 3.200893009, 0.003106991, 25.80377156,
2.121824344, -1.364884344, 1.418982992, 1.436906832, 0.418982992,
0.337957008, -0.662042992, -0.679966832, -0.694582992, -0.712506832,
148.8617733, 2.172783188, -1.415843188, 4.41366392, -0.672485667,
1.049125667, -0.523367109, -0.768424143, -0.523802116, 0.900442116,
0.900007109, 1.145064143, 0.900007109, 1.145064143, 0.32636017,
-0.486302849, 0.862942849, 46.120606, 1.854477172, -1.535367172,
1.677706613, 1.680788736, 1.677706613, -1.358596613, -1.358596613,
-1.361678736, -1.378856613, -1.381938736, NA, NA, NA, 21.92365464,
1.355114917, -2.669624917, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 5.80084933, 0.909920977, 0.279989023, 0.951821206, -0.080588008,
0.949639991, 0.240270009, 0.238088794, 1.2704980082, NA, NA,
17.97017283, 1.254552254, -0.064642254, 441.9807675)),
.Names = c("UID", "METRIC", "RESULT"), row.names = c(NA, 154L), class = "data.frame")
mets <- melt(subset(x, select = -PROTOCOL), id.var = 'UID', variable.name = 'METRIC', value.name = 'RESULT')
res <- merge(metsExpected, mets, by = c('UID', 'METRIC'), all.x = T)
res$diff <- abs(res$RESULT.x - res$RESULT.y)
res
|
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