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An example the ais data set in .NET Integrated PDF-417 2d barcode in .NET An example the ais data set




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An example the ais data set using .net toembed pdf417 with asp.net web,windows application GS1 Standards Knowledge Centre Data in the PDF-417 2d barcode for .NET data set ais (DAAG) were shown earlier, in Figure 1.3 in Subsection 1.

5.8. Data were collected with a view to studying possible differences in blood characteristics, between athletes in endurance-related events and those in power-related events.

See the help page for ais for details of the measurements, including a variety of blood cell counts. Here is a breakdown, by sex and sport, of numbers:. B_Ball Graphs in R Swim 4.0 4.5.

Tennis 5.0 5.5.

f Blood cell to plasma ratio (%). Red cell count (1012.L 1). Figure 15.4 Blood cell to plasma ratio (hc) versus red cell count (rcc), by sex (different panels) and sport (distinguished within each panel), for a subset of the ais data. The argument type=c("p", "r") displays both points ("p") and regression lines ("r").

> with(ais, table(sex,sport)) sport sex B_Ball Field Gym Netball Row Swim T_400m T_Sprnt Tennis W_Polo f 13 7 4 23 22 9 11 4 7 0 m 12 12 0 0 15 13 18 11 4 17. There are 20 pdf417 for .NET 2 athletes in total, all from the Australian Institute of Sport. Figure 15.

4 plots blood cell to plasma ratio (%) against red cell count, for three sports only. The three sports are in the one panel, distinguished by different symbols and/or colors. Females and males are in separate panels.

Regression lines have been added. Again, an initial basic plot is updated to give the desired result. Code is:.

basic1 <xyplot(hc rcc sex, groups .NET barcode pdf417 =sport[drop=TRUE], data=subset(ais, sport %in% c("B_Ball", "Swim", "Tennis")), ylab="Blood cell to plasma ratio (%)") parSet <- simpleTheme(pch = c(1:3), lty=1:3, lwd=1.5, col.

line=c("gray40","black","black")) xaxlab <- expression("Red cell count (10" {12}*"."*L {-1}*")") basic2 <- update(basic1, par.settings=parSet, auto.

key=list(columns=3, lines=TRUE), scales=list(tck=0.5), xlab=xaxlab) print(update(basic2, type=c("p", "r"))). Again, there are details that require explanation: r The drop=TRUE in groups=sport[drop=TRUE] ensures that levels that are no longer present in the data (here, sports other than B Ball and Swim) are omitted when the key is drawn. (Subsetting a factor leaves the levels attribute unchanged. Redundant levels must be explicitly removed.

). 15.5 Lattice graphics and the grid package r As in base graphics, graphical annotation (tick labels, axis labels, labels on points, etc.) can be given using the function expression(). r The argument type=c("p","r") gives both points and tted regression lines.

. 15.5.3 Panel functions, strip functions, strip labels, and other annotation Each lattice command that creates a graph has its own panel function. Thus xyplot() has the panel function panel.xyplot().

The following are equivalent:. xyplot(speci .NET PDF-417 2d barcode es length, xlab="", data=cuckoos) xyplot(species length, xlab="", data=cuckoos, panel=panel.xyplot).

The user s o wn function can be substituted for panel.xyplot(). Panel functions that may be used, either in combination with functions such as panel.

xyplot() or separately, include: r panel.points(), panel.lines(), and a number of other such functions that are documented on the same help page as panel.

points(); r panel.abline(), panel.curve(), panel.

rug(), panel.average(), and a number of other functions that are documented on the same help page as panel.abline().

. A panel function that ts and plots parallel lines The followin g updates basic2, used for Figure 15.4 in Subsection 15.5.

2 above, so that the lines for the two sports are parallel. Plate 13 shows the result..

update(basic visual .net pdf417 2d barcode 2, strip=strip.custom(factor.

levels=c("Female","Male")), # In place of level names c("f", "m"), use c("Female", "Male") panel=function(x, y, groups, subscripts, ...

){ panel.superpose(x,y, groups=groups, subscripts=subscripts, ..

.) ## Obtain fitted values for parallel line model parallel.fitted <- fitted(lm(y groups[subscripts] + x)) panel.

superpose(x, parallel.fitted, groups=groups, type="l", subscripts=subscripts, ..

.) }). When a group s argument is supplied, panel.xyplot() calls panel. superpose().

The customized panel function calls panel.superpose() twice, once to plot the paints, and a second time to join the tted values and thus generate the lines. Here is a further example:.

library(grid .net vs 2010 pdf417 2d barcode ) stripplot(species length, xlab="", data=cuckoos, legend=list(top=list(fun=textGrob,. Graphs in R args=list(la .net framework pdf417 bel="Stripplot", x=0, just="left")))) # Here, x=0 is equivalent to x=unit(0,"npc"); the range is (0,1). Modi cation of the strip labels The followin visual .net PDF417 g has modi ed strip labels. It is in the style of Figure 6.

18, but with more elaborate strip labels:. tau <- (0 :5)/2.5; m <- length(tau); n <- 200; SD <- 2 x0 <- rnorm(n, mean=12.5, sd=SD) # Generate x-values df <- data.

frame(sapply(tau, function(s)x0+rnorm(n, sd=2*s))) # Columns after the first are x-values with addedd error df$y = 15+2.5*x0 names(df) <- c(paste("X", tau, sep=""), "y") lab <- c(list("0"), lapply(tau[-1], function(x)substitute(A*s[z], list(A=x)))) form <- formula(paste("y ", paste(paste("X", tau, sep=""), collapse="+"))) xyplot(form, data=df, outer=TRUE, strip=strip.custom(strip.

names=TRUE, var.name="SD(added err)", sep=expression(" = "), factor.levels=as.

expression(lab))). The argument barcode pdf417 for .NET var.name has text that will appear in all strip labels.

See also Subsection 3.3.3, where there was another example of this form of strip labeling.

In the internal code the variables that are printed in parallel become levels of a single factor, as in the following alternative that achieves the same result:. library(resh ape) longdf <- melt(df, measure.vars=1:6, id.vars="y", variable_name="tau") # Columns of "measure" variables are stacked in a column that has # the name "value": column 1, then 2, then 3, .

.. xyplot(y value .

tau, data=l .net vs 2010 PDF 417 ongdf, strip=strip.custom(strip.

names=TRUE, var.name="SD(added err)", sep=expression(" = "), factor.levels=as.

expression(lab))). Annotation using textGrob(). The followin .NET PDF-417 2d barcode g uses the function textGrob() (grid) to create a text object which is then supplied to the lattice function:. library(grid ) stripplot(species length, xlab="", data=cuckoos, legend=list(top=list(fun=textGrob, args=list(label="Stripplot of cuckoo data", x=0)))) # Here, x=0 is equivalent to x=unit(0,"npc"); the range is (0,1). Multiple leg PDF417 for .NET ends, for example a list element bottom as well as a list element top, can be supplied by this means..

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