Chapter 10 Customizing Plots
10.1 Key Concepts
We can create almost any customized visualization using a small number of functions from the Core R graphics engine:
points(
x=x, y=y, # plots points at the x,y positions
pch=19, # the type of point to plot
cex=2, # aspect ratio of point size
col="red", # color of points
bg="green" # fill color for open symbols
)
text(
x=x, y=y, # draws a line by connecting points
labels=some.text, # vector of labels to plot on the graph
pos=3, # position: 1=below, 2=left, 3=above, 4=right
cex=2, # aspect ratio of text size
col="red" # color of text
)
lines(
x=x, y=y, # draws a line by connecting points
lty="l", # type of lines, same as above
lwd=0.5, # line thickness
)
segments(
x0=x0, y0=y0, # starting points of the segments (usually a vector)
x1=x1, y1=y1, # end points of the segments (usually a vector)
... # other arguments from lines()
)
title(
main="Plot Title", # text for the plot title
xlab="x variable", # text for the x-axis label
ylab="y variable", # text for the y-axis label
line= -1 # move the title closer / further
)
axis(
side=1 # 1=below, 2=left, 3=above, 4=right
at=c(10,20,30), # position of tick marks
labels=c("S","M","L") # labels for tick marks
)
10.2 Packages Used in This Chapter
We will use some data from the Lahman baseball data package for examples in this chapter.
The Master data frame contains information about professional baseball players. We will focus on the relationship between height and weight of the players.
| nameFirst | nameLast | weight | height | bats | throws | birthYear |
|---|---|---|---|---|---|---|
| David | Aardsma | 215 | 75 | R | R | 1981 |
| Hank | Aaron | 180 | 72 | R | R | 1934 |
| Tommie | Aaron | 190 | 75 | R | R | 1939 |
| Don | Aase | 190 | 75 | R | R | 1954 |
| Andy | Abad | 184 | 73 | L | L | 1972 |
| Fernando | Abad | 220 | 73 | L | L | 1985 |
10.3 Layering Approach
Graphs in R are created by layering elements on top of each other. The easiest way to understand this is to build a plot from the ground up.
The following graph is comprised of six components:
- points
- plot box
- x-axis
- y-axis
- x-label
- y-label
Many other elements can be added to the plot, but this is a good start.
# remove players with no height or weight measures
Master <- select( Master, height, weight )
Master <- na.omit( Master )
# find max and min values for each
xmin <- min(Master$height)
xmax <- max(Master$height)
ymin <- min(Master$weight)
ymax <- max(Master$weight)
# empty plot
plot.new()
plot.window( xlim=c(xmin,xmax), ylim=c(ymin,ymax) )
box( col="gray" )
text( 64, 200, "(Empty Plot Window)", cex=2 )
# add points
plot.new()
plot.window( xlim=c(xmin,xmax), ylim=c(ymin,ymax) )
box( col="gray" )
points( Master$height, Master$weight, pch=19 )
# add an x-axis and y-axis
plot.new()
plot.window( xlim=c(xmin,xmax), ylim=c(ymin,ymax) )
box( col="gray" )
points( Master$height, Master$weight, pch=19 )
axis( side=1 )
axis( side=2, las=1 )
# add axis labels
plot.new()
plot.window( xlim=c(xmin,xmax), ylim=c(ymin,ymax) )
box( col="gray" )
points( Master$height, Master$weight, pch=19 )
axis( side=1 )
axis( side=2, las=1 )
title( xlab="Height (inches)", ylab="Weight (lbs)" )
title( main="Relationship Between Height and Weight of MLB Players" )
Now let’s see if we can improve the aestetics a bit. This is pretty dense data, so let’s see if we can use some color transparency to get a sense of typical players versus outliers.
Let’s adjust the xlim and ylim arguments so we don’t show the empty bottom left quadrant, and let’s use the gray() color function to add some transparency to the over-plotted data points. The first argument is a value between 0 and 1 specifying how dark you want the gray (0 being white, 1 being black, and any value in-between being a shade of gray). The second argument is another value between 0 and 1 specifying the transparency of the points, 0 being invisible and 1 being no transparency.
We can also jitter them a bit (a tiny amount of random error to each data point) so they are not all plotted on top of each other since height and weight only take integer values.
height.jitter <- Master$height + rnorm( nrow(Master) )
weight.jitter <- Master$weight + rnorm( nrow(Master) )
plot.new()
plot.window( xlim=c(60,xmax), ylim=c(110,ymax) )
points( height.jitter, weight.jitter,
pch=19, cex=1.2, col=gray(0.5,0.02) )
axis( side=1 )
axis( side=2 )
title( xlab="Height (inches)", ylab="Weight (lbs)",
main="Relationship Between Height and Weight of MLB Players" )
This is helpful, but maybe we want to highlight the data core some more. Let’s add another layer with only that data that falls within the 25th to 75th percentiles of height and weight.
| 0% | 25% | 50% | 75% | 100% |
|---|---|---|---|---|
| 43 | 71 | 72 | 74 | 83 |
| 0% | 25% | 50% | 75% | 100% |
|---|---|---|---|---|
| 65 | 170 | 185 | 200 | 320 |
height.jitter <- Master$height + rnorm( nrow(Master) )
weight.jitter <- Master$weight + rnorm( nrow(Master) )
height.25th <- quantile( Master$height, 0.25, na.rm=T )
height.75th <- quantile( Master$height, 0.75, na.rm=T )
these.height.25th.to.75th <- Master$height > height.25th & Master$height < height.75th
weight.25th <- quantile( Master$weight, 0.25, na.rm=T )
weight.75th <- quantile( Master$weight, 0.75, na.rm=T )
these.weight.25th.to.75th <- Master$weight > weight.25th & Master$weight < weight.75th
these.both.25th.to.75th <- these.height.25th.to.75th & these.weight.25th.to.75th
plot.new()
plot.window( xlim=c(60,xmax), ylim=c(110,ymax) )
axis( side=1 )
axis( side=2 )
title( xlab="Height (inches)", ylab="Weight (lbs)",
main="Relationship Between Height and Weight of MLB Players" )
points( height.jitter, weight.jitter,
pch=19, cex=1.2, col=gray(0.5,0.02) )
points( height.jitter[ these.both.25th.to.75th ],
weight.jitter[ these.both.25th.to.75th ],
pch=19, cex=0.3, col="firebrick3" )
That didn’t quite work out because a player might be “average” height (height between 25th and 75th percentile), but be heavier or lighter than normal. The criteria we applied basically draws a box and finds data within the box.
Let’s rethink this a bit, and select players with “average” size using ratios between height and weight, often expressed as Body Mass Index (BMI). This selection criteria will not limit us to a square.
bmi <- (Master$weight * 0.45359237) / (Master$height / 39.370)^2
bmi.25th <- quantile( bmi, 0.25, na.rm=T )
bmi.75th <- quantile( bmi, 0.75, na.rm=T )
these.bmi.25th.to.75th <- bmi > bmi.25th & bmi < bmi.75th
plot.new()
plot.window( xlim=c(60,xmax), ylim=c(110,ymax) )
axis( side=1 )
axis( side=2 )
title( xlab="Height (inches)", ylab="Weight (lbs)",
main="Relationship Between Height and Weight of MLB Players" )
points( height.jitter, weight.jitter,
pch=19, cex=2, col=gray(0.5,0.02) )
points( height.jitter[ these.bmi.25th.to.75th ],
weight.jitter[ these.bmi.25th.to.75th ],
pch=19, cex=0.1, col="firebrick3" )
10.4 Highlighting Cases
Let’s look back at the original plot. Do you see anything strange?
The smallest data point in the dataset seems to represent a baseball player that is 40 inches tall and weighs 80 pounds. That must be some sort of data entry error, right?
| nameFirst | nameLast | weight | height | bats | throws | birthYear | |
|---|---|---|---|---|---|---|---|
| 5839 | Eddie | Gaedel | 65 | 43 | R | L | 1925 |
It turns out that Eddie Gaedel, at 3 foot 7 inches, was the shortest man to ever play on a professional team. He was hired by the owner of the St. Louis Browns as a publicity stunt. He was so short that his strike zone, which goes form the knee to mid-chest, was too small for most pitchers. Crowds would cheer as he would quickly accumulate walks.
Perhaps it would be useful to annotate some of the outliers on our graph. To do this, we can use the text() function.
text(
x=x, y=y, # draws a line by connecting points
labels=some.text, # vector of labels to plot on the graph
pos=3, # position: 1=below, 2=left, 3=above, 4=right
cex=2, # aspect ratio of text size
col="red" # color of text
)
Let’s start by circling some data points. We do this by plotting a slightly larger point around the originals for the tallest, shortest, and heaviest players.
plot.new()
plot.window( xlim=c(0,1), ylim=c(0,1) )
points( 0.5, 0.5, pch=19, col="gray", cex=3 )
points( 0.5, 0.5, pch=1, cex=5, col="firebrick" )
title( main="Large Hollow Point Plotted \nOver Solid Point" )
this.shortest <- which.min(Master$height)
this.tallest <- which.max(Master$height)
this.heaviest <- which.max(Master$weight)
Master[ c(this.shortest,this.tallest,this.heaviest), c(14,15,17:20,2) ] %>% pander()
| nameFirst | nameLast | weight | height | bats | throws | birthYear | |
|---|---|---|---|---|---|---|---|
| 5839 | Eddie | Gaedel | 65 | 43 | R | L | 1925 |
| 14139 | Jon | Rauch | 290 | 83 | R | R | 1978 |
| 19008 | Walter | Young | 320 | 77 | L | R | 1980 |
Let’s highlight the three outliers in our dataset.
plot( Master$height, Master$weight,
pch=19, col="gray",
frame.plot=FALSE,
xlab="Height (inches)",
ylab="Weight (lbs)",
main="Relationship Between Height and Weight of MLB Players" )
points( Master$height[ this.shortest ],
Master$weight[ this.shortest ],
col="firebrick", cex=2, lwd=2 )
points( Master$height[ this.tallest ],
Master$weight[ this.tallest ],
col="firebrick", cex=2, lwd=2 )
points( Master$height[ this.heaviest ],
Master$weight[ this.heaviest],
col="firebrick", cex=2, lwd=2 )
text( Master$height[ this.shortest ],
Master$weight[ this.shortest ],
"Some Text Here", col="firebrick", pos=3 )
We add text to the graph through the x,y coordinate for the text, the text itself, and the pos= argument is used to specify where the text should go.
- pos=1: below
- pos=2: left
- pos=3: top
- pos=4: right
- no pos: on the point
You can see that we have a problem above. Our text above Eddie Gaedel is lopped off because it wanders outside of the plot window. We can add additional real estate by expanding plot window with the xlim= and ylim= arguments.
You can add a line break to a string by including the carriage return symbol “”.
data( Master)
plot( Master$height, Master$weight,
pch=19, col="gray", cex=0.8,
xlim=c(30,100), ylim=c(50,450),
frame.plot=FALSE,
xlab="Height (inches)",
ylab="Weight (lbs)",
main="Relationship Between Height and Weight of MLB Players" )
d.small <- Master[ c(this.shortest,this.tallest,this.heaviest), c(14,15,17:20,2) ]
points( d.small$height,
d.small$weight,
col="firebrick", cex=2, lwd=2 )
text( Master$height[ this.shortest ],
Master$weight[ this.shortest ],
"Eddie Gaedel \nHeight: 43 Inches \nWeight: 65 Lbs",
col="firebrick", cex=0.8, pos=3, offset=1 )
text( Master$height[ this.tallest ],
Master$weight[ this.tallest ],
"Jon Rauch \nHeight: 83 Inches \nWeight: 290 Lbs",
col="firebrick", cex=0.8, pos=4, offset=1 )
text( Master$height[ this.heaviest ],
Master$weight[ this.heaviest ],
"Walter Young \nHeight: 77 Inches \nWeight: 320 Lbs",
col="firebrick", cex=0.8, pos=3, offset=1 )
10.5 Visual Hypothesis Testing
As you can see, the text() function can be used to add narrative to a graphic. It can also be used in place of plotting points.
Let’s think about testing the hypothesis that players have gotten larger over time. When we look at the basic relationship between height and weight we see the distribution of player sizes, but this plot has no information about the time-periods in which they played so we can’t tell if they are growing larger over time. What if we replace the plotting points with birth years?
plot.new()
plot.window( xlim=c(60,xmax), ylim=c(110,ymax) )
text( x=Master$height,
y=Master$weight,
labels=Master$birthYear )
This is too dense to be meaningful. Maybe we can try to make the text smaller?
plot.new()
plot.window( xlim=c(60,xmax), ylim=c(110,ymax) )
text( x=Master$height,
y=Master$weight,
labels=Master$birthYear, cex=0.5 )
Still not very insightful. We have over 19,000 players in the database, which appears to be too many for this graphic. Let’s thin the data out by taking a random sample of the full dataset.
par( mar=c(0,0,0,0) )
m.sample <- sample_n( Master, 100 )
plot.new()
plot.window( xlim=c(65,78), ylim=c(130,280) )
text( x=m.sample$height,
y=m.sample$weight,
labels=m.sample$birthYear, cex=0.8 )
axis( side=1, line=-2 )
axis( side=2, line=-2 )
This is a big improvement. We can eyeball the data and start to pull out some trends. The people born in the 1800’s tend to be near the bottom of each pile of years, for example.
Perhaps we can improve our visual hypothesis testing if we add some color coding. Let’s identify all of the individuals born since 1980 and color their birth years red to highlight the youngest cohort in the data. If people have gotten larger over time, we would expect this group to cluster near the top of the distribution.
red.gray <- ifelse( m.sample$birthYear >= 1980, "firebrick", "gray" )
text( x=m.sample$height,
y=m.sample$weight,
labels=m.sample$birthYear,
col=red.gray )
And we in fact see the pattern emerge. The youngest cohort, highlighted in red, seems to cluster near the top right, which suggests they have grown both taller and heavier over time.
This hypothesis can be test more rigorously in other ways, but the demonstration at least gives an idea about how we might explore the data efficiently using flexible R graphing functions.
10.6 Additional Parameters
The small number of functions introduced here in these chapters on data visualization can be used to make highly-customizable graphics that help you discover important patterns in the data and share the story with others.
We are only scratching the surface on the options available within plotting functions. To see the default list of parameter settings in the R plot() function, type:
These chapters show how core R graphics can be used to create highly-customized graphics. You can see that you have fine-tuned access to all aspects of the figures you create. You don’t have to become familiar with all of the options to develop solid visualization skills. Rather, you will likely focus on a few specific functions. A little time invested in learning the arguments for plot(), points(), lines(), text(), title(), and axis() goes a long way.


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Virgin Atlantic to codeshare with Canada’s Westjet
by Jenni ReidVirgin Atlantic has announced a codeshare partnership with Westjet that will see it sell the Canadian carrier’s flights.
Westjet flies year-round from Gatwick to Calgary and Toronto and from Gatwick to Halifax and Vancouver in the summer season. It then offers domestic and regional connections including Montreal, Quebec, Edmonton and Deer Lake.
Formerly a low-cost carrier, Calgary-based Westjet has rebranded as a full-service airline in recent years. In 2019 it took delivery of three B787-9 Dreamliners featuring business and premium economy cabins and it will open a flagship lounge in Calgary next year.
Westjet already has a joint venture partnership with Delta, which owns 49 per cent of Virgin.
Virgin does not currently have any nonstop routes to Canada. For passengers, the main benefit is the accrual of Virgin loyalty points when booking through its website instead of Westjet’s.
“WestJet welcomes Virgin Atlantic guests on board our flights to and from London, Gatwick and throughout our Canadian network,” said Brian Znotins, Westjet’s head of network planning and alliances.
“Canada is a desirable tourism destination with thriving business centres and vast scenic wilderness. We believe the Virgin Atlantic codeshare, offering seamless connections, one itinerary, and Westjet’s caring onboard experience, will inspire global travellers to choose Canada.”
Juha Jarvinen, Virgin’s head of commercial, commented: “This new partnership will open up a plethora of Canadian destinations to our customers and offer more choice for those looking to fly directly to Canada.
“Customers will have the security and ease of booking through a codeshare and we are sure our customers will enjoy flying with Westjet.”
Virgin Atlantic will put its code on the following services from Thursday November 21:
| Transatlantic codeshare destinations *summer only |
|
| YYC | Calgary |
|---|---|
| YYZ | Toronto |
| YHZ | Halifax* |
| YVR | Vancouver* |
| Domestic codeshare destinations | |
| YCD | Nanaimo |
|---|---|
| YDF | Deer Lake |
| YEG | Edmonton |
| YFC | Fredericton |
| YHZ | Halifax |
| YKA | Kamloops |
| YLW | Kelowna |
| YMM | Fort McMurray |
| YOW | Ottawa |
| YQB | Quebec |
| YQM | Greater Moncton |
| YQQ | Comox |
| YQR | Regina |
| YQT | Thunder Bay |
| YQU | Grande Prairie |
| YQY | Sydney |
| YUL | Montreal |
| YWG | Winnipeg |
| YXE | Saskatoon |
| YXJ | Fort St John |
| YXS | Prince George |
| YXT | Terrace |
| YXU | London |
| YXX | Abbotsford |
| YYC | Calgary |
| YYF | Penticton |
| YYG | Charlottetown |
| YYJ | Victoria |
| YYT | St Johns |
| YYZ (YTO) | Toronto |
| YVR | Vancouver |
| YZF | Yellowknife |
virginatlantic.com, westjet.com


The standard types defined by the specification.
More...
Typedefs |
| typedef detail::tvec2< bool > | bvec2 |
| typedef detail::tvec3< bool > | bvec3 |
| typedef detail::tvec4< bool > | bvec4 |
| typedef detail::tmat2x2< double > | dmat2 |
| typedef detail::tmat2x2< double > | dmat2x2 |
| typedef detail::tmat2x3< double > | dmat2x3 |
| typedef detail::tmat2x4< double > | dmat2x4 |
| typedef detail::tmat3x3< double > | dmat3 |
| typedef detail::tmat3x2< double > | dmat3x2 |
| typedef detail::tmat3x3< double > | dmat3x3 |
| typedef detail::tmat3x4< double > | dmat3x4 |
| typedef detail::tmat4x4< double > | dmat4 |
| typedef detail::tmat4x2< double > | dmat4x2 |
| typedef detail::tmat4x3< double > | dmat4x3 |
| typedef detail::tmat4x4< double > | dmat4x4 |
| typedef detail::tvec2< double > | dvec2 |
| typedef detail::tvec3< double > | dvec3 |
| typedef detail::tvec4< double > | dvec4 |
| typedef precision::mediump_ivec2 | ivec2 |
| typedef precision::mediump_ivec3 | ivec3 |
| typedef precision::mediump_ivec4 | ivec4 |
| typedef mat2x2 | mat2 |
| typedef precision::mediump_mat2x2 | mat2x2 |
| typedef precision::mediump_mat2x3 | mat2x3 |
| typedef precision::mediump_mat2x4 | mat2x4 |
| typedef mat3x3 | mat3 |
| typedef precision::mediump_mat3x2 | mat3x2 |
| typedef precision::mediump_mat3x3 | mat3x3 |
| typedef precision::mediump_mat3x4 | mat3x4 |
| typedef mat4x4 | mat4 |
| typedef precision::mediump_mat4x2 | mat4x2 |
| typedef precision::mediump_mat4x3 | mat4x3 |
| typedef precision::mediump_mat4x4 | mat4x4 |
| typedef precision::mediump_uvec2 | uvec2 |
| typedef precision::mediump_uvec3 | uvec3 |
| typedef precision::mediump_uvec4 | uvec4 |
| typedef precision::mediump_vec3 | vec3 |
| typedef precision::mediump_vec4 | vec4 |
Detailed Description
The standard types defined by the specification.
These types are all typedefs of more generalized, template types. To see the definiton of these template types, go to Template types.
Typedef Documentation
| typedef detail::tvec2<bool> bvec2 |
2 components vector of boolean.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 245 of file type.hpp.
| typedef detail::tvec3<bool> bvec3 |
3 components vector of boolean.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 250 of file type.hpp.
| typedef detail::tvec4<bool> bvec4 |
4 components vector of boolean.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 255 of file type.hpp.
| typedef detail::tmat2x2<double> dmat2 |
2 * 2 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 278 of file type.hpp.
| typedef detail::tmat2x2<double> dmat2x2 |
2 * 2 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 293 of file type.hpp.
| typedef detail::tmat2x3<double> dmat2x3 |
2 * 3 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 298 of file type.hpp.
| typedef detail::tmat2x4<double> dmat2x4 |
2 * 4 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 303 of file type.hpp.
| typedef detail::tmat3x3<double> dmat3 |
3 * 3 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 283 of file type.hpp.
| typedef detail::tmat3x2<double> dmat3x2 |
3 * 2 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 308 of file type.hpp.
| typedef detail::tmat3x3<double> dmat3x3 |
3 * 3 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 313 of file type.hpp.
| typedef detail::tmat3x4<double> dmat3x4 |
3 * 4 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 318 of file type.hpp.
| typedef detail::tmat4x4<double> dmat4 |
4 * 4 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 288 of file type.hpp.
| typedef detail::tmat4x2<double> dmat4x2 |
4 * 2 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 323 of file type.hpp.
| typedef detail::tmat4x3<double> dmat4x3 |
4 * 3 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 328 of file type.hpp.
| typedef detail::tmat4x4<double> dmat4x4 |
4 * 4 matrix of double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 333 of file type.hpp.
| typedef detail::tvec2<double> dvec2 |
Vector of 2 double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 263 of file type.hpp.
| typedef detail::tvec3<double> dvec3 |
Vector of 3 double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 268 of file type.hpp.
| typedef detail::tvec4<double> dvec4 |
Vector of 4 double-precision floating-point numbers.
From GLSL 4.00.8 specification, section 4.1 Basic Types.
Definition at line 273 of file type.hpp.
| typedef precision::mediump_ivec2 ivec2 |
2 components vector of signed integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 194 of file type.hpp.
| typedef precision::mediump_ivec3 ivec3 |
3 components vector of signed integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 199 of file type.hpp.
| typedef precision::mediump_ivec4 ivec4 |
4 components vector of signed integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 204 of file type.hpp.
2 columns of 2 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 163 of file type.hpp.
| typedef precision::mediump_mat2x2 mat2x2 |
2 columns of 2 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 116 of file type.hpp.
| typedef precision::mediump_mat2x3 mat2x3 |
2 columns of 3 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 121 of file type.hpp.
| typedef precision::mediump_mat2x4 mat2x4 |
2 columns of 4 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 126 of file type.hpp.
3 columns of 3 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 168 of file type.hpp.
| typedef precision::mediump_mat3x2 mat3x2 |
3 columns of 2 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 131 of file type.hpp.
| typedef precision::mediump_mat3x3 mat3x3 |
3 columns of 3 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 136 of file type.hpp.
| typedef precision::mediump_mat3x4 mat3x4 |
3 columns of 4 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 141 of file type.hpp.
4 columns of 4 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 173 of file type.hpp.
| typedef precision::mediump_mat4x2 mat4x2 |
4 columns of 2 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 146 of file type.hpp.
| typedef precision::mediump_mat4x3 mat4x3 |
4 columns of 3 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 151 of file type.hpp.
| typedef precision::mediump_mat4x4 mat4x4 |
4 columns of 4 components matrix of floating-point numbers.
(From GLSL 1.30.8 specification, section 4.1.6 Matrices)
Definition at line 156 of file type.hpp.
| typedef precision::mediump_uvec2 uvec2 |
2 components vector of unsigned integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 226 of file type.hpp.
| typedef precision::mediump_uvec3 uvec3 |
3 components vector of unsigned integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 231 of file type.hpp.
| typedef precision::mediump_uvec4 uvec4 |
4 components vector of unsigned integer numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 236 of file type.hpp.
| typedef precision::mediump_vec3 vec3 |
3 components vector of floating-point numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 106 of file type.hpp.
| typedef precision::mediump_vec4 vec4 |
4 components vector of floating-point numbers.
From GLSL 1.30.8 specification, section 4.1.5 Vectors.
Definition at line 111 of file type.hpp.


I am extremely honored and ecstatic to be associated with a subject that has made significant inroads and contributions to the human life in the past 30 years. I believe that the rise of computers and computer-based services are akin to the Industrial Revolution in their own right.
I am learning new things about the subject every day, but these are the topics (in no particular order) I care most about, and follow very closely.
The following links will shed more light about my academic interests and achievements:
During my Master studies, I took a diverse selection of subjects, ranging from Virtual Reality to Satisfiability Checking. To follow the details about my coursework, please visit my repository on Github.


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Hardcore porn retweeted from Welsh Office Twitter account
They say the account was hacked
by Katie-Ann GupwellHardcore porn has been tweeted from a Welsh Office Twitter account.
An extremely graphic screenshot was shared on social media after being re-tweeted on Monday afternoon from the UK Government in Wales Twitter account.
The message was quickly deleted and a spokesman has since alleged that the account had been the victim of a "cyber-attack".
Stace Williams Tweeted: "That awkward moment when the UK Government in Wales account tweets porn into your timeline."
Another social media user posted: "Biggest faux pas of the day goes to whomever is running the UK Government in Wales @UKGovWales Twitter account who r/ted this."
Following the incident, UK Government in Wales posted on Twitter: "We are aware that our account was subject to a cyber-attack earlier.
"We apologise for any offence caused by the material shared.
"We are confident the issue has now been resolved.
"If you find yourself in a similar situation please see: https://ncsc.gov.uk/section/information-for/individuals-families "


Root application controller. This provides a number of useful functions that’re common to all controllers.
Methods
Attributes
| [RW] | meta_description | |
| [RW] | og_image |
Instance Public methods
after_sign_in_path_for(user)
Link
Utility function that overrides devise’s default functionality after a user logs in. In this case, if it’s the user’s first time, they are bounced to a first-time log in page (see Admin::PasswordController#first_time)
Source: show
# File app/controllers/application_controller.rb, line 27 def after_sign_in_path_for user if user.first_time? flash[:alert] = "Because this is your first time here, you'll need to change your password" admin_first_login_path else admin_root_path end end
after_sign_out_path_for(user)
Link
Utility function that overrides devise’s default functionality after a user logs out.
Source: show
# File app/controllers/application_controller.rb, line 37 def after_sign_out_path_for user new_user_session_path end
forbidden()
Link
Convenience function that renders a 403 page
Source: show
# File app/controllers/application_controller.rb, line 11 def forbidden render_error 403, :forbidden end


{% extends "app/layout.html" %} {% block content %} {% csrf_token %}
Answer the following questions and we will tell you what analysis to perform:
1. What is the approximate number of observations you have in your data?
2. Is your output categorical?
3. Are your outputs labelled?
4. If your data is just a bunch of observations that you want to cluster, do you know the number of clusters?
Submit


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Individuals who are more prone to allergies or who have a family member who has had a life-threatening reaction to an allergen are more likely to go into anaphylactic shock when they come into contact with certain substances.
The most common causes are:
The individual may have a flushed or pale appearance. They may first experience a burning of the lips followed within minutes by a puffy face and neck, as well as breathing difficulties. They may complain of itching or belly pain, begin to vomit, and/or develop a blotchy, raised red rash or hives. Call an ambulance immediately (911 in most locations).
 If your child is old enough, teach him or her how to self-administer the injection. Get him or her an identity bracelet, clearly showing the medical details of his/her allergies and the necessary treatment. An allergist should also be consulted, as he or she may be able to reduce the severity of your child’s reactions with appropriate treatment, often including a series of shots. (See Tip 169 for more information on allergies.)


Internet of Things Simulator that takes care of the hassle of choosing the right devices in order to get a working networking and interoperability between devices. Not all the devices available on the market are compatible Google Assistant and Alexa. Some of them may require proprietary hubs in order to get connect to the local network.


When you design interfaces, you need to consider graphic design, user experience and implementation all at the same time. To simplify this very complex issue and have a document on which people with those three specialities, I very often use my more complex projects with an initial wireframe prototype, which is either done with mockup tools or directly in code.
The main issue with wireframe prototyping is that people tend to consider visual aspects of the definitive. One nice trick is to use hand drawn theme so it is very clear to all viewer that it is not the definitive appearance of the site.
Handdrawn.css is a plug and play library that turn your proptotype into handrawn theme and can be used with bootstrap.


jhat(1) jhat(1) Name jhat - Java Heap Analysis Tool SYNOPSIS jhat [ options ] <heap-dump-file> PARAMETERS options Options, if used, should follow immediately after the command name. heap-dump-file Java binary heap dump file to be browsed. For a dump file that con‐ tains multiple heap dumps, you may specify which dump in the file by appending "#<number> to the file name, i.e. "foo.hprof#3". DESCRIPTION The jhat command parses a java heap dump file and launches a webserver. jhat enables you to browse heap dumps using your favorite webbrowser. jhat supports pre-designed queries (such as 'show all instances of a known class "Foo"') as well as OQL (Object Query Language) - a SQL-like query language to query heap dumps. Help on OQL is available from the OQL help page shown by jhat. With the default port, OQL help is available at http://localhost:7000/oqlhelp/ There are several ways to generate a java heap dump: o Use jmap(1) -dump option to obtain a heap dump at runtime; o Use jconsole(1) option to obtain a heap dump via HotSpotDiagnos‐ ticMXBean @ http://docs.oracle.com/javase/7/docs/jre/api/management/exten‐ sion/com/sun/management/HotSpotDiagnosticMXBean.html at runtime; o Heap dump will be generated when OutOfMemoryError is thrown by spec‐ ifying -XX:+HeapDumpOnOutOfMemoryError VM option; o Use hprof @ http://java.sun.com/developer/technicalArticles/Program‐ ming/HPROF.html. NOTE: This tool is experimental and may not be available in future ver‐ sions of the JDK.  Note that if allo‐ cation site information is not available in the heap dump, you have to set this flag to false. Default is true. -refs false/true Turn off tracking of references to objects. Default is true. By default, back pointers (objects pointing to a given object a.k.a referrers or in-coming references) are calculated for all objects in the heap. -port port-number Set the port for the jhat's HTTP server. Default is 7000. -exclude exclude-file Specify a file that lists data members that should be excluded from the "reachable objects" query. For example, if the file lists java.lang.String.value, then, whenever list of objects reachable from a specific object "o" are calculated, reference paths involv‐ ing java.lang.String.value field will not considered. -baseline baseline-dump-file Specify a baseline heap dump. Objects in both heap dumps with the same object ID will be marked as not being "new". Other objects will be marked as "new". This is useful while comparing two differ‐ ent heap dumps. -debug int Set debug level for this tool. 0 means no debug output. Set higher values for more verbose modes. -version Report version number and exit. -h Output help message and exit. -help Output help message and exit. -J<flag> Pass <flag> to the Java virtual machine on which jhat is run. For example, -J-Xmx512m to use a maximum heap size of 512MB. SEE ALSO o jmap(1) o jconsole(1) o hprof - Heap and CPU profiling tool @ http://java.sun.com/developer/technicalArticles/Program‐ ming/HPROF.html 16 Mar 2012 jhat(1)


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Simon Cowell's girlfriend appears to 'ask who Mark Wright is' live on X Factor
Some X Factor viewers were convinced that Simon Cowell's girlfriend Lauren Silverman did not know who the former TOWIE star was while he spoke to Dermott O'Leary
by Kyle O'Sullivan, https://www.mirror.co.uk/authors/kyle-osullivan/X Factor viewers were surprised to see Mark Wright sat in the audience tonight - and it seemed to confuse Simon Cowell's girlfriend.
Lauren Silverman was sat on the table next to the former The Only Way Is Essex star during the semi-final.
Radio host Mark spoke to X Factor presenter Dermot O'Leary about his favourite performers, including his pal Thom Evans and fellow Essex resident Megan McKenna.
However, some viewers tried to lip read Lauren as she spoke to her friend and were convinced she had no idea who mark was.
One viewer asked: "Did Simons partner just ask who @MarkWright_ was live on tv directly in front on the camera?!?!? Love the lady answering clarified he was on Towie"
Lauren started listening to Mark as he spoke to Dermot but had a baffled look on her face.
Simon's girlfriend, who is mum to their son Eric, then leaned across the table to seemingly ask her friend a question.
After getting a response, Lauren then sat back in her chair and clapped Mark while looking towards the camera.
When Dermot asked who Mark was cheering for, he said: "It's a tough one. Thom Evans is my boy so I obviously want him to win.
"Megan is an Essex girl who's repping the Essex.
"And Vinnie is one of my all time heroes. It's tough."
Dermot pointed out that he had chosen "pretty much the whole semi-final line-up" to support.
Giggling Mark admitted he was a big fan of the show before finally choosing his favourite to win.
He added: "I think with what just happened it's got to be Megan. She was phenomenal. [Louis] Walshy's got to win."
X Factor viewers took to Twitter after spotting Mark in the audience.
One viewer asked: "Was that Mark Wright cheering Meghan?"
"Wtf is @MarkWright_ doing there?," added another.
A third said: "Mark Wright’s teeth are keeping the whole audience lit up in the background"
*The X Factor airs Saturdays on ITV


iPhenoGram - Getting Started
iPhenoGram is a jQuery widget that utilizes D3.js to create chomosomal ideograms annotated with lines in color at specific base-pair locations or colored base-pair to base-pair regions.
The code below loads a JSON file and creates a new widget using the data and specifying various options.
$(document).ready(function() { var data; d3.json("example_data.json", function(error, json) { if (error) return console.warn(error); data = json; visualizeit(); }); function visualizeit(){ var chromplot = $("#basic").iphenogram({chroms: data.chromsDefault, phenos: data.phenos, cytoBands: data.cytoDefault, zoom_map: false, chromsOnly: false, chromwidth: 64, circlesize: 28, height: 368, width: 340}); } });
Displaying only some chromosomes
iPhenoGram has an option to display only some of the chromosomes in the set as below. The chromosomes are drawn to take advantage of the additional space available.
var showChroms = ["7", "10", "11", "12", "18", "21", "X", "Y"]; var fileredPlot = $("#filtered").iphenogram({chroms: data.chromsDefault, phenos: data.phenos, cytoBands: data.cytoDefault, includedChroms: showChroms, chromwidth: 64, circlesize: 28, height: 368, width: 340});
Altering circle size
iPhenoGram has an option to change the size of the phenotypic circles and an option to control the display of the cytogenetic bands (turned off in the example below).
var showChroms = ["7", "10", "11", "12", "18", "21", "X", "Y"]; var fileredPlot = $("#filtered").iphenogram({chroms: data.chromsDefault, phenos: data.phenos, cytoBands: data.cytoDefault, includedChroms: showChroms, drawCyto: false, chromwidth: 64, circlesize: 56, height: 368, width: 340});
Change plot dimensions
iPhenoGram will draw the plot to fill the dimensions given it. Below is the same plot as above but with twice the width given to iPhenoGram.
var showChroms = ["7", "10", "11", "12", "18", "21", "X", "Y"]; var fileredPlot = $("#filtered").iphenogram({chroms: data.chromsDefault, phenos: data.phenos, cytoBands: data.cytoDefault, includedChroms: showChroms, drawCyto: false, chromwidth: 64, circlesize: 56, height: 368, width: 680});


Defense attorneys for the Guantanamo Bay detainees charged with plotting the September 11, 2001 terrorist attacks told the court this week that the Wi-Fi connection at Starbucks was more secure than the Pentagon’s own system.
Lawyers for the accused terrorists said in pretrial hearings previously that they often relied on the wireless Internet provided at coffee shops to conduct work over the Web, but on Thursday the attorneys went as far as to say that the Starbucks’ Wi-Fi was significantly the most secure connection available.
Air Force Colonel Karen Mayberry, the chief defense counsel for the war crimes tribunal, told the judge that the Starbucks Wi-Fi was “the best bad option that we had,” Jane Sutton reported for Reuters.
Lawyers for the accused 9/11 masterminds asked the court before for more time to prepare their case, citing an inability to work efficiently on the Defense Department’s computer system.
"We're basically put back in the 19th century," Army Major Jason Wright, the attorney for Khalid Sheik Mohammed, said last month. "It takes about five to 10 times what it would normally take to do defense functions.”
Army Colonel James Pohl said at the time, "I understand the serious nature of being able to communicate as a defense counsel," and announced he would decide this week if hearings set for later this year should be postponed to provide attorneys more time.
On Thursday, the lawyers said things haven’t improved with regards to their computer issues.
Mayberry acknowledged that the Starbucks Wi-Fi might be unsecure but, according to Reuters, said she was certain the DoD network had been compromised.
"It's not speculative or hypothetical. It happened," she said.
A day earlier, another attorney for Mohammed said he was questioned by the government about visiting terrorism-related websites. Mayberry said that the pages lawyer David Nevin and other members of the defense team visited were relevant to their work. On their part, the Defense Department said it has systems in place to flag suspicious activity on the Pentagon’s systems.
Given the issues that have plagued the attorney’s ability to access the Internet so far, though, Mayberry said the problems created “an extremely difficult work environment,” and that “it has become a cumbersome process to complete even the most simple of tasks.”
Nevin, Washington Post’s Billy Keber reported from Gitmo, said US intelligence services “have an extreme interest in information in relation to the men who are the accused in this case.” It was previously reported that fake smoke detectors at Guantanamo had been equipped with eavesdropping devices and that defense emails were handed over to the prosecution.
According to Reuters, a logistic overseer said it could take over three months to fix the Pentagon’s system and was a matter of money. Internet technology supervisor Paul Scott Parr testified that the problems may have occurred due to a switch in the email system used by attorneys, or perhaps an attempt to replicate their work on two computers networks — one based near Washington and another near the Cuban prison. Pohl said funding for the issues could be discussed in court in around two weeks.
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When a Date object is created, a number of methods allow you to operate on it.
Date methods allow you to get and set the year, month, day, hour, minute, second, and millisecond of objects, using either local time or UTC (universal, or GMT) time.
When you display a date object in HTML, it is automatically converted to a string, with the toString() method.
The toUTCString() method converts a date to a UTC string (date display standard):
The toDateString() method converts a date to a more readable format:


Revisiting Learning Style
Date: June 20th, 2014
From the pre-prep work, I found out I have an abstract random learning style based on the evaluation we took. This means I tend to be people-oriented, my thinking process is based more on feelings and intuition, and I would rather be in a cooperative environment rather than working alone. At DBC, with pairing sessions, this sounds great because I think what my learning style says is I'll be empathetic and enjoy working with others.
The downsides are finding it hard to take criticism, working in a restrictive environment, and focusing on one thing at a time. At DBC, we have already been training with feedback, so I will possibly struggle more with that. I don't mind creating an MVP for programming because it's the most practical and pragmatic solution we can come up with, although I may need reminders later. I found that I focus better in chunks of time, which is why I've been using things like the Pomodoro technique.
From the looks of it, my plan of action is not to take much action and go out of feeling because that's what most comfortable for me. That means the constant feedback I get will be internalized and tried to be understood more. With a growth mindset, I'm trying to go more for a learning conversation and a learning attitude with the things I do at DBC, and embrace what's going to come to me rather than have an instant rejection. Try once and evaluate. I'm looking forward to DBC next week!


http://www.speakers-podium.com/susangranger.
Susan Granger's review of "LIMBO" (Columbia Pictures)
John Sayles makes movies the way James Michener wrote books, traveling to fascinating places and placing imaginary characters amidst very real situations. Think of the intelligence and creativity of Sayles' "Secret of Roan Inish," "Lone Star," "Matewan," "Passion Fish," and "Men with Guns."
Alaska is America's last frontier. Its vast expanse of rugged, untamed wilderness is both setting and antagonist in "Limbo," the story of three isolated people who come together to face their own demons and to explore the very nature of emotional and physical risk Mary Elizabeth Mastrantonio plays a tough, frustrated bar singer with a troubled, strong-willed teenage daughter, Vanessa Martinez. David Strathairn is a quiet, traumatized ex-fisherman-turned-handyman who invites them to join him for a weekend cruise which goes sour when his half-brother (Casey Siemaszko), who owns the boat, reveals he's being pursued by killers after a drug deal went bad. Their lives, past and present, form the crux of the superbly crafted drama which places them in a life-threatening survival situation from which they may not successfully emerge, depending on the whim of a quixotic bush pilot (Kris Kristofferson). "Limbo" is John Sayles' most unflinching, daringly original, and powerfully disturbing film, and Mary Elizabeth Mastrantonio's performance of bruising, heart-wrenching intensity is definitely Oscar-caliber. On the Granger Movie Gauge of 1 to 10, "Limbo" is a piercing, suspenseful 8. The ambiguity of its ending may be frustrating, but your reaction and subsequent conclusion reveal more about you than about the characters in the film. Remember, "limbo" is defined as "a condition of unknowable outcome."
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


New studio flats to be built in Bolton town centre
Nine new apartments will be built at the site of an empty warehouse
by Joseph Timan, Local Democracy ReporterNew studio flats are set to be built in Bolton town centre after the developer reached a compromise with the town council.
An empty warehouse in Bark Street East can now be demolished to make way for nine apartments which were granted planning permission by a committee of councillors last Thursday, after the landowner was told the previous plans for 12 flats were not big enough.
Councillors deferred the application in September because the proposed one-bedroom apartments were only 39 square metres, the minimum required to meet national standards.
Town hall planners told the committee that the unit sizes have increased “modestly” to 46 square metres and “suburban” features were removed to match the Georgian properties opposites.
Crompton councillor Hanif Darvesh said these revised plans were “much more in-keeping” with the conservation area it sits in.
Cllr Elaine Sherrington thanked the applicant for “taking notice” of the committee’s comments.
She added: “I welcome this and I think they look brilliant.”


Apache Flink® — Stateful Computations over Data Streams
In the last two months since our initial preview release the community has been hard at work to stabilize and improve the core Flink Kubernetes Operator logic. We are now proud to announce the first production ready release of the operator project.


The World Through My Lens
Traveling the world
Fill free to contact me and please check out my other pages.


4011
2016
7239
1586
Card Holder
Zara Lynch
Expires
11/28
CVV
239
Using this card to purchase goods and services whenever you see the VISA symbol. Your use of this card is acceptance to your issuer's arragements including amendments.


On January 21, 2010, the United States Supreme Court ruled that the government cannot restrict the amount a for-profit corporation corporation, labor union or voluntary association donates to a Political Action Committee (PAC), as doing so would restrict free speech. Even though the court held that any individual or organization could not make direct contributions to a candidate running for office, many were concerned with whether donations to a candidate's political action committee would affect a candidates policy decisions when in office. PACs provide most of the logistical support for candidates running for office (running advertisements, organizing trips, planning speeches, etc.), so if a politician votes against the interest of an organization providing donations, that candidate would risk losing those PAC donations in the next election cycle.
Our website examines if campaign finances influence how a politican makes decisions by examining the top contributors to a politican's campaign and their voting records.


{% extends "education/ministry/ministry_dashboard.html" %} {% block content %}
Report based on 22% of Total Reporters (Schools)


First, download the plug-in and unzip to a location that can be found by the DB2 Command Window.
Note: These installation and set-up steps were written based on the README documentation that was originally supplied with the plug-in package.
Click here to download the plug-in


Strictly: Kelvin Fletcher's wife addresses his sexy routines with Oti ahead of final
He's in the final this weekend…
by Nancy BrownThe wife of Strictly Come Dancing star Kelvin Fletcher has spoken out about her husband's sexy routines with professional partner Oti Mabuse.
Former Emmerdale star Kelvin has been married to Elizabeth Marsland for four years.
The pair share two children – daughter Marnie, three, and son Milo, one.
And Liz has revealed just how she feels to see her husband slow dancing alongside Oti on the BBC dance show, which reaches its climax this weekend.
Speaking to Hello!, it appears the show's so-called curse isn't a worry for the stunning brunette.
Read more: NHS employees will get £20 off Uber this Christmas
She said: "It doesn't bother me. I'm used to seeing him kiss Britain's sexiest females on Emmerdale."
 I understand it's a performance."
However, Liz did say she can understand why people who aren't in the industry are worried about their partner taking part.
Read more: Kate Garraway reveals her shock at losing a stone in the jungle
The mum of two is a singer and actress.
She added: "I can imagine it's difficult for people who aren't in this industry."
Kelvin is due to face Emma Barton and Karim Zeroual in Saturday night's live grand final.
Last week, Oti shut down rumours of a rift between herself and Kelvin when he was forced to miss his fourth wedding anniversary due to training.
Head to our Facebook page @EntertainmentDailyFix and let us know what you think of our story.


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Pre-requested R packages
R version >= 3.6.0
Following is the description for dependent R packages, mainly for developers to better understand the code in NetBID2.
Users do not need to digest the information below.
| R package | Functions1 | Category | Purpose |
|---|---|---|---|
| Biobase | - | Data processing | ExpressionSet class |
| GEOquery | getGEO | Data processing | Get expression dataset from GEO database |
| limma | - | Data processing | Expression data normalization |
| impute | impute.knn | Data processing | Data imputation |
| tximport | Data processing | Data import | |
| DESeq2 | DESeqDataSetFromTximport,DESeq | Data processing | Data import from txi and normalization for RNASeq data |
| ConsensusClusterPlus | - | Clustering | Get consensus clustering results |
| aricode | clustComp | Clustering | For cluster comparison statistic calculation |
| igraph | - | Visualization | Igraph class and basic network-based calculation |
| RColorBrewer | brewer.pal | Visualization | Get color bar |
| plot3D | scatter3D | Visualization | 3D plot |
| plotrix | draw.ellipse | Visualization | drawing ellipse |
| umap | umap | Visualization | data dimension reduction and visualization |
| ComplexHeatmap | Heatmap | Visualization | heatmap drawing |
| plotly | - | Visualization | For interactive plot |
| ordinal | clm,clmm | bid | Cumulative Link Mixed Models |
| MCMCglmm | MCMCglmm | bid | Multivariate Generalized Linear Mixed Models |
| arm | bayesglm | bid | Bayesian generalized linear models |
| reshape | melt | bid | Melt an object into a form suitable for easy casting |
| biomaRt | - | ID conversion | ID conversion |
| GSVA | gsva | Gene Set | gene set activity calculation |
| msigdbr | - | Gene Set | MSigDB database |
| openxlsx | - | IO | Output into excel file (master table) |
| rhdf5 | H5Fopen,H5Fclose | IO | For hd5 formation data processing (MICA) |
| rmarkdown | render | Report | For generating html report file |
| kableExtra | - | Report | For table layout in the report file |
-
’-‘ in the Function column represents multiple functions in the package were used in NetBID2. ↩


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M. Allman, V. Paxson and W. Stevens, TCP Congestion Control, RFC 2581, Proposed Standard, April 1999.
The latest standard on TCP Congestion Control. Required reading.
V. Jacobson, Congestion Avoidance and Control. Proceedings of SIGCOMM '88 (Palo Alto, CA, Aug. 1988) Available from: ee.lbl.gov/nrg-papers.html
The classic TCP congestion control paper. Describes the slow start, implicit loss detection, congestion avoidance, and RTT filtering algorithms. Papers on TCP improvements. Great archive of TCP-related Papers. IETF Groups: TCPSAT , TCPIMPL , PILC (drafts and RFCs can be found here).
The paper describing the RED buffer management/packet drop algorithm. This work complements end-to-end TCP control, by using a simple, stateless, randomized packet dropping algorithm to avoid TCP synchronization effects. Latest RED page
Describes the use of Selective Acknowledgements in TCP. Note that SACK refers to the capability to specify selective retransmission of blocks of data, not just one segment (as opposed to Selective Reject). This feature can improve TCP performance considerably, especially in the presence of bursty packet drops. The SACK page also describes other related enhancements including Forward Acks etc.
This RFC describes TCP-ECN, an experimental proposal in the Internet. This scheme uses one-bit feedback from routers in a manner similar to the Decbit scheme (see elsewhere in this page), but adapts its use for TCP. Latest ECN page .
Floyd, S., and Henderson, T., The NewReno Modification to TCP's Fast Recovery Algorithm, RFC 2582, Experimental, April 1999. Available from: Sally Floyd's page
These papers describe the proposed NewReno enhancements to TCP.
Describes another technique to refine congestion control.
This paper describes TCP Vegas, a new version of TCP which uses an estimate of the bandwidth-delay product of the pipe to perform better congestion avoidance. Though very popular in academic and research circles, this work has not won the favor of implementors and standards bodies. Additional Vegas Page (USC).
This paper proposes a simple, but powerful stochastic model for steady state TCP throughput and shows it to be inversely proportional to the RTT, p^0.5 and timeout intervals. It started off work in TCP-friendly congestion control protocols, which is now influencing work in UDP and multicast congestion control.
Related work by INRIA folks: INRIA TCP modeling work
Describes the ack compression problem in TCP.
Describes TCP traffic synchronization problems. RED was later designed to tackle this issue.
Interesting analysis of TCP performance, including effects of asymmetry.
Congestion control issues relating to TCP over wireless and asymmetric media. Includes a discussion of the Berkeley "snoop" protocol. Won the ACM best dissertation award.
Researchers in this area:
This paper uses explicit rate-based congestion control for the ABR service in ATM. Conceptually, explicit rate-based schemes involve more participation by interior nodes (routers/switches) and involve the exchange of more information than implicit congestion indication (like TCP Reno), or bit-based feedback schemes (Decbit, TCP-ECN). The payoff is the achieving of properties such as efficiency, fairness, controlled queueing delays, and fast transient response while being robust to measurement errors. Explicit, transparent window-based control has been used by Packeteer Inc.
Postscript (1.29 MB | Gzip Compressed Postscript (200 KB)
This is the classic MS thesis that introduced the explicit rate control idea upon which ABR explicit rate schemes have been based.
This paper studies the use of transparent explicit window control of TCP using a rate-control scheme, followed by rate-to-window translation and acknowledgement pacing. Comparative performance analysis with RED and ECN shows improvements in fairness, efficiency etc.
Postscript (474KB) | gzip Compressed Postscript (108KB) | PDF (254KB)
Related paper dealing with basic explicit rate-to-window conversion
techniques: Postscript
(1960KB).
Packeteer, a company that
makes TCP rate-control products
This paper describes the credit-based approach to flow-control in ATM Networks. This is a hop-by-hop window (credit) based scheme. It lost out in the great rate-vs-credit debate in the ATM Forum, but nevertheless has very influential ideas. Can achieve tight queue bounds, fairness, efficiency etc, but required mandatory per-flow queueing support.
This paper describes the classic Decbit scheme which introduces the use of 1-bit feedback, additive-increase-multiplicative-decrease policy (AIMD), and associated filtering schemes. Later schemes such as TCP-ECN, OSI, frame-relay and ATM ABR 1-bit feedback schemes were motivated by this work.
This paper analyzes the additive increase/multiplicative decrease policy for dynamic window adjustment, and shows it to be superior in terms of stability and fairness properties over other alternatives.
This paper describes the use of round-trip delay in estimating congestion epoch lengths. Delay is highly variable, and hence the scheme is a study in the use of advanced filtering techniques to obtain the required congestion information.
This paper, a precursor of Jacobson's TCP congestion control paper, describes the use of timeout and packet loss as an implicit indicator of congestion. It also describes the method of starting the dynamic window from one segment.
This paper describes the classic Decbit scheme which introduces the use of 1-bit feedback, additive-increase-multiplicative-decrease policy (AIMD), and associated filtering schemes. Later schemes such as TCP-ECN, OSI, frame-relay and ATM ABR 1-bit feedback schemes were motivated by this work.
Proposes a new end-system architecture to aggregate congestion control actions for UDP, TCP and other unicast transports into a single "congestion manager." This proposal is being discussed for standardization in the IETF. Latest CM page. Related Work on Multiplexing TCP, UDP sessions .
The paper describing need for end-to-end congestion control even for non-TCP applications. Related work on Global Optimization using End-to-End Congestion Control.
Describes how the IP multicast signaling and routing mechanisms to develop a congestion control algorithm for layered video. Later papers by others have used similar techniques using layered FEC, or every layered data multicast transmission.
Latest work on congestion control for reliable multicast transport (RMT) protocols. Additional (better) RMT page.
Researchers in this area:
This paper describes the basis for the famous CBQ (class based queueing) scheduler. Note that schedulers are open-loop components which can control the parameters of the "virtual link" offered to each contending traffic class or aggregate. Latest CBQ page .
Diff-serv is a new IETF standard that allows simple and coarse methods of providing differentiated classes of service for Internet traffic, to support various types of applications, and specific business requirements.
A.Demers, S.Keshav, and S.J. Shenker. ``Analysis and Simulation of a Fair Queueing Algorithm''. Proc. of ACM SIGCOMM '89, pages 1-12, Sep. 1989.
The paper on Weighted Fair Queueing (WFQ).
I. Stoica, S. Shenker, and H. Zhang. ``Core-Stateless Fair Queueing: Achieving Approximately Fair Bandwidth Allocations in High Speed Networks'' Proc. of ACM SIGCOMM '98, pages 118-130, Sep. 1998.
Per-flow state in packet headers rather than in routers. Follow up paper in SIGCOMM'99: "Providing Guaranteed Services Without Per Flow Management" .
Precursor to the int-serv work.
Describes a new approach to admission control - measurement based. The shorter version of this paper won the SIGCOMM best paper award in 1995.
Researchers in this area:
S. Keshav, Packet-Pair Flow Control, Tech-report, Cornell Univ. Available from: http://www.cs.cornell.edu/skeshav/papers.html .
This paper proposes the use of rate-based flow control, combined with a per-flow round-robin scheduler at bottlenecks and a packet-pair based bandwidth probing technique. Good discussion of filters, control-theoretic and scheduling issues. Also check out Keshav's PhD thesis and SIGCOMM'91 paper. Recent work on bandwidth measurement by Allman, Paxson (SIGCOMM'99) , Lai/Baker (Nettimer/Mosquitonet project, Infocom'99) has been based upon this.
This document is a description of and a specification for the NETBLT protocol. It is a revision of the specification published in RFC-969. NETBLT (NETwork BLock Transfer) is a transport level protocol intended for the rapid transfer of a large quantity of data between computers. It provides a transfer that is reliable and flow controlled, and is designed to provide maximum throughput over a wide variety of networks. Although NETBLT currently runs on top of the Internet Protocol (IP), it should be able to operate on top of any datagram protocol similar in function to IP. This document is published for discussion and comment, and does not constitute a standard. The proposal may change and certain parts of the protocol have not yet been specified; implementation of this document is therefore not advised.
Design of a robust control-theoretic flow-control scheme based upon H-infinity theory. Also contains pointers to other control-theoretic work.
Postscript (459496 bytes) | PKzip Compressed Postscript (97220 bytes) | PDF
Other researchers in this area:
Pricing. Links.
Pricing as a tool for economic efficiency, as well as traffic management in the Internet.
Abstract: We study the role of pricing policies in multiple service class networks. We argue that some form of graduated prices are required in order for any multiclass service discipline to have the desired effect. Moreover, we demonstrate through simulation that it is possible to set the prices so that every user is more satisfied with the combined cost and performance of a network with graduated prices. For some users the performance penalty received for requesting a less-than-optimal service class is offset by the reduced price of the service. For the other users the monetary penalty incurred by using the more expensive, higher quality service classes is offset by the improved performance they receive. Thus, prices allow us to spread the benefits of multiple service classes around to all users, rather than just having these benefits remain exclusively with users who are performance sensitive.
[KP91] P. Karn and C. Partridge, Improving Round-Trip Time Estimates in Reliable Transport Protocol. ACM Transactions on Computer Systems (TOCS), Vol. 9, No. 4, pp. 364-373, November 1991.
This paper describes a new filtering technique for estimating RTT.
This paper discusses techniques for measuring bandwidth of a connection. Builds upon earlier work in Vern Paxson's dissertation , Keshav's packet pair scheme . TCP Vegas (reference elsewhere) estimates bandwidth-delay product, a random variable with higher variance than each of the two random variables (RTT and bandwidth) of which it is a product.
New paper which talks about filtering RTT, RTO and bandwidth information.
Abstract: Congestion is a longstanding problem in datagram networks. One congestion avoidance technique is feedback flow control, in which sources adjust their transmission rate in response to congestion signals sent (implicitly or explicitly) by network gateways. The goal is to design flow control algorithms which provide time-scale invariant, fair, stable, and robust performance. In this paper we introduce a simple model of feedback flow control, in which sources make synchronous rate adjustments based on the congestion signals and other local information, and apply it to a network of Poisson sources and exponential servers. We investigate two different styles of feedback, aggregate and individual, and two different gateway service disciplines, FIFO and Fair Share. The purpose of this paper is to identify, in the context of our simple model, which flow control design choices allow us to achieve our performance goals. Aggregate feedback flow control, in which congestion signals reflect only the aggregate congestion at the gateways, can provide time-scale invariant and stable performance, but not fair or robust performance. The properties of individual feedback flow control, in which the congestion signals reflect the congestion caused by the individual source, depend on the service discipline used in the gateways. Individual feedback with FIFO gateways can provide time-scale invariant, fair, and stable performance, but not robust performance. Individual feedback with Fair Share gateways can achieve all four performance goals. Furthermore, its stability properties are superior to those of the other two design choices. By making robust and more stable performance possible, gateway service disciplines play a crucial role in realizing effective flow control.


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{% extends 'Blog/base.html' %} {% block title %}Disclaimer{% endblock %} {% block description %}Content disclaimer for Corkran.{% endblock %} {% block content %}
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As an Admin, you can evalute new items to add to the bibliography and keep track of bibcode lists sent to ADS.
This website was designed to have two functions:
to search the bibliogrpahy, and
to evalute new items to add to the bibliography.
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CfA Bibliography
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Project: Cisco IOS 2
Description: Collection of QuickCalls and response maps for Cisco IOS devices
Category: library
Class: Community
2 QuickCall Libraries in project://di_cisco_ios_com
getInterfaceStates
This will the interface states on the system for a quick status check
login
Automatically login to cisco device - privileged mode
Return value = prompt respose
e.g.
Bad login:
Password Status: % Login invalid
Enable Password Status: % Login invalid
or
Good login:
Password Status:
Enable Password Status:
| Argument |
Description |
| username |
Valid username |
| password |
valid password |
| enablePassword |
Leave blank if the same as password |
getVersion
checkCounters
This procedure is used to clear counters for Ethernet interface.
| Argument |
Description |
| ifc |
Enter a valid interface value.
e.g. - fastEthernet 6/0 |
| clearCounters |
Clear counter is if set to 1 (true). Default value is 0 (false). Acceptable values: 0|1 |
saveRunningConfigTftp
Save running config to TFTP server
| Argument |
Description |
| tftpServerIp |
Valid IP address |
| filename |
Valid config file name |
restoreRunningConfigTftp
Restore running config to TFTP server
| Argument |
Description |
| tftpServerIp |
Valid IP address |
| filename |
Valid config file name |
graphProcesses
This is intended to run as a background process throughout the entire test. By default we capture stats every 30 seconds.
| Argument |
Description |
| delaySec |
Number of seconds to wait before checking process info. |
queryIfcStates
This procedure will query all the interface states and return a summary view of the system.
showVersion2
| Argument |
Description |
| fwVersion |
Expected FW version |


{% extends "/site/home_base.html" %}
{% block head %}
{{ super() }}
{% endblock %}
{% block page_content %}
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We now come to the decisive step of mathematical abstraction: we forget about what the symbols stand for. … [The mathematician] need not be idle; there are many operations which he may carry out with these symbols, without ever having to look at the things they stand for.Hermann Weyl The Mathematical Way of Thinking
We concentrated in chapter 1 on computational processes and on the role of functions in program design. We saw how to use primitive data (numbers) and primitive operations (arithmetic operations), how to combine functions to form compound functions through composition, conditionals, and the use of parameters, and how to abstract processes by using function declarations. We saw that a function can be regarded as a pattern for the local evolution of a process, and we classified, reasoned about, and performed simple algorithmic analyses of some common patterns for processes as embodied in functions. We also saw that higher-order functions enhance the power of our language by enabling us to manipulate, and thereby to reason in terms of, general methods of computation. This is much of the essence of programming.
In this chapter we are going to look at more complex data. All the functions in chapter 1 operate on simple numerical data, and simple data are not sufficient for many of the problems we wish to address using computation. Programs are typically designed to model complex phenomena, and more often than not one must construct computational objects that have several parts in order to model real-world phenomena that have several aspects. Thus, whereas our focus in chapter 1 was on building abstractions by combining functions to form compound functions, we turn in this chapter to another key aspect of any programming language: the means it provides for building abstractions by combining data objects to form compound data.
Why do we want compound data in a programming language? For the same reasons that we want compound functions: to elevate the conceptual level at which we can design our programs, to increase the modularity of our designs, and to enhance the expressive power of our language. Just as the ability to declare functions enables us to deal with processes at a higher conceptual level than that of the primitive operations of the language, the ability to construct compound data objects enables us to deal with data at a higher conceptual level than that of the primitive data objects of the language.
Consider the task of designing a system to perform arithmetic with
rational numbers. We could imagine an operation add_rat that takes
two rational numbers and produces their sum. In terms of
simple data, a rational number can be thought of as two integers: a
numerator and a denominator. Thus, we could design a program in which
each rational number would be represented by two integers (a numerator
and a denominator) and where
add_rat
would be implemented by two
functions
(one producing the numerator of the sum and one producing
the denominator). But this would be awkward, because we would then
need to explicitly keep track of which numerators corresponded to
which denominators. In a system intended to perform many operations
on many rational numbers, such bookkeeping details would clutter the
programs substantially, to say nothing of what they would do to our
minds. It would be much better if we could glue together
a
numerator and denominator to form a pair—a compound data
object—that our programs could manipulate in a way that would be
consistent with regarding a rational number as a single conceptual
unit.
The use of compound data also enables us to increase the modularity of our programs. If we can manipulate rational numbers directly as objects in their own right, then we can separate the part of our program that deals with rational numbers per se from the details of how rational numbers may be represented as pairs of integers. The general technique of isolating the parts of a program that deal with how data objects are represented from the parts of a program that deal with how data objects are used is a powerful design methodology called data abstraction. We will see how data abstraction makes programs much easier to design, maintain, and modify.
The use of compound data leads to a real increase in the expressive
power of our programming language. Consider the idea of forming a
linear combination
$ax+by$. We might like to write a
function
that would accept $a$, $b$, $x$, and $y$ as arguments and return the
value of $ax+by$. This presents no difficulty if the arguments are to
be numbers, because we can readily
declare the function
But suppose we are not concerned only with numbers. Suppose we would like to describe a process that forms linear combinations whenever addition and multiplication are defined—for rational numbers, complex numbers, polynomials, or whatever. We could express this as a function of the form
function linear_combination(a, b, x, y) { return add(mul(a, x), mul(b, y)); }
We begin this chapter by implementing the rational-number arithmetic system mentioned above. This will form the background for our discussion of compound data and data abstraction. As with compound functions, the main issue to be addressed is that of abstraction as a technique for coping with complexity, and we will see how data abstraction enables us to erect suitable abstraction barriers between different parts of a program.
We will see that the key to forming compound data is that a
programming language should provide some kind of glue
so that data
objects can be combined to form more complex data objects. There are
many possible kinds of glue. Indeed, we will discover how to form
compound data using no special data
operations at all, only
functions. This will further blur the distinction between
function
and data,
which was already becoming tenuous toward
the end of chapter 1. We will also explore some conventional
techniques for representing sequences and trees. One key idea in
dealing with compound data is the notion of
closure—that the
glue we use for combining data objects should allow us to combine not
only primitive data objects, but compound data objects as well.
Another key idea is that compound data objects can serve as
conventional interfaces for combining program modules in
mix-and-match ways. We illustrate some of these ideas by presenting a
simple graphics language that exploits closure.
We will then augment the representational power of our language by introducing symbolic expressions—data whose elementary parts can be arbitrary symbols rather than only numbers. We explore various alternatives for representing sets of objects. We will find that, just as a given numerical function can be computed by many different computational processes, there are many ways in which a given data structure can be represented in terms of simpler objects, and the choice of representation can have significant impact on the time and space requirements of processes that manipulate the data. We will investigate these ideas in the context of symbolic differentiation, the representation of sets, and the encoding of information.
Next we will take up the problem of working with data that may be represented differently by different parts of a program. This leads to the need to implement generic operations, which must handle many different types of data. Maintaining modularity in the presence of generic operations requires more powerful abstraction barriers than can be erected with simple data abstraction alone. In particular, we introduce data-directed programming as a technique that allows individual data representations to be designed in isolation and then combined additively (i.e., without modification). To illustrate the power of this approach to system design, we close the chapter by applying what we have learned to the implementation of a package for performing symbolic arithmetic on polynomials, in which the coefficients of the polynomials can be integers, rational numbers, complex numbers, and even other polynomials.
a function,it is doubtful that we would ever even think of the possibility of defining an operation such as sum. Moreover, insofar as performing the summation is concerned, the details of how term may be constructed from more primitive operations are irrelevant.


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PRG155NGH Lab 1
/*
Course: PRG155NGH: Programming Fundamentals Using "C"
Program: Lab1.c
Author: Ping Zhang
Date: 09/04/2019
Purpose: Write an algorithm in pseudocode and draw a flowchart
*/
/* Problem #1:Design an algorithm that calculates the average of 3 input numbers. The program then displays the result. */
/* Pseudocode */
START
READ numberOne, numberTwo, numberThree
Sum = numberOne + numberTwo + numberThree
Average = Sum / 3
WRITE Average
END
/* Flowchart */
/* Source code for Problem #1 */
#include <stdio.h>
int main()
{
int numberOne, numberTwo, numberThree, sum;
float average;
/* prompt user to input three numbers */
printf("Please enter three numbers as following\n");
printf("Enter Number One: ");
scanf("%d", &numberOne);
printf("\nEnter Number Two: ");
scanf("%d", &numberTwo);
printf("\nEnter Number Three: ");
scanf("%d", &numberThree);
/* Calculate the sum of three numbers */
sum = numberOne + numberTwo + numberThree;
/* Calculate the average of three numbers */
average = sum / 3.0; /* Set the denominator to 3.0 to covert average value float type */
/* Output the average value on the screen*/
printf("\nYou entered the numbers: %d, %d, %d", numberOne, numberTwo, numberThree);
printf("\nThe average of three numbers: %.2f", average); /* set the value has two decimals */
getchar();/* Keep the screen pause, enter any key to exit */
getchar();
return 0;
}


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This page explains how to follow the Rest.li Test Suite Specification to validate a new Rest.li client binding. This guide is based on experience with Python, and your language implementation may diverge from this guide.
For a broader overview of code structure and test coverage, refer to test suite overview. For Java client binding example, please refer to the provided Java TestNG suite, which follows the Rest.li Test Suite Specification to validate a Java Rest.li client implementation.
To use the Rest.li Test Suite Specification for a new language implementation of Rest.li, you must set up code generation within the project so you can test Rest.li client’s code generation. You must also write methods in the new language so you can use the language-independent data included in the Rest.li Test Suite Specification.
Here is a step-by-step guide on how to set up a test suite for a new language implementation of Rest.li:
In client-testsuite’s build.gradle
, apply the plugin for your new implementation of Rest.li to enable code generation.
apply plugin: 'li-python-restli'
Run the Rest.li code generators against all the files in the schemas/
directory (for data
bindings) and/or the restspecs/
directory (for rest client bindings).
For Python and Java, this means running a gradle build
. In Java, the code is generated in src/
. In Python,
the code is generated in build/
The generated code will be tested later in the testsuite.
Select a test framework. You should use the same test framework you usually use for the language your Rest.li client is written in. For the Python test suite, we use pytest.
In your test framework, load the manifest.json
file into a convenient in-memory representation before running the tests.
In Python, a Manifest class is generated from the .pdsc
provided by the test suite.
The manifest.json
file is loaded into a Manifest representation that is used by the Python test suite.
Based on your test framework, decide how you want to use your Manifest representation to drive your automated tests.
For example, consider json tests in the Python test suite, shown below. We get the list of manifest tests from the Manifest representation in json_test_data(). Then we use the pytest @parametrize decorator to pass the test names and data files into the function test_json(), which contains the testing logic.
def json_test_data():
"""Data provider for json_test"""
results = []
for test in manifest.get_json_test_data():
results.append(test)
return results
json_data = json_test_data()
@pytest.mark.parametrize("json_test", json_test_data(), ids=[test.data_ for test in json_data])
def test_json(json_test):
"""Tests for correct serialization/deserialization of provided 'data' files"""
...
Set up utility methods in your new language. These methods should provide a way to read in the files referenced by
manifest.json
. You also need methods to compare and load flat HTTP requests and responses from the test suite’s
provided test data.
In the Java TestNG suite, these utility methods are part of a test suite base class that is extended by the classes containing actual tests. The Python pytest suite has no subclass/superclass structure because it makes pytest harder to use.
Now your test suite is set up to generate code and read language-independent files from the Rest.li Test Suite Specification.
The next step is to implement tests using the spec’s guidelines and provided test data.
This will be a combination of manual assertions and data driven tests specified by manifest.json
.
The tests are driven by manifest.json
and cover three main categories:
Json tests ensure that Rest.li correctly serializes/deserializes all the provided data/
files.
These files include corner cases to check that they are supported.
One possible approach, which is used by the Java and Python test suites:
def test_json(json_test):
"""Tests for correct serialization/deserialization of provided 'data' files"""
deserialized = load_json_file(os.path.join(*json_test.get_data_().split("/")))
serialized = JSONRestliCodec.encode(deserialized)
twice_deserialized = JSONRestliCodec.decode(serialized)
for field in deserialized.keys():
assert deserialized[field] == twice_deserialized[field]
assert len(deserialized) == len(twice_deserialized)
Schema tests ensure that Rest.li correctly generates language-specific data templates from language-independent data schemas.
For implementations that use data schemas to provide convenience data bindings from data schemas (either dynamically or via code generation):
gradle build
to construct data bindings for all the schema/
files.manifest.json
.For implementations that provide validation:
When testing wire protocol, we want to ensure that the generated request builders can build correct HTTP responses. We also want to ensure that the Rest.li client can correctly create a Rest.li Response representation from an HTTP response.
To test requests and responses, flat files containing HTTP requests and responses are provided in
Rest.li Test Suite Specification’s requests/
and responses/
folders, which are for Rest.li protocol 1.0.0.
These flat files have counterparts in requests-v2/
and responses-v2/
that use Rest.li protocol version 2.0.0.
but are otherwise identical.
A few possible approaches one might take to use these test files:
The Java and Python test suites use approach 1.
For Rest.li implementations that use restspecs to provide convenience rest client bindings from restspecs (either dynamically or via code generation):
restspecs/
files.Use the constructed rest client bindings to produce HTTP requests. Do this for all the ‘restspecs.operations.request’
entries in manifest.json
. Instead of sending the requests, keep the request in an in-memory representation (a string,
or basic HTTP representation) or write it to a file.
In Python, the logic for this is as follows:
Verify the HTTP request created by the rest client bindings matches the expected HTTP as found in the ‘restspecs.operations.request’ files. This may require writing a routine to compare HTTP requests that ignores header order, and does not fail for optional headers. For instance, Python includes an optional “User-Agent” header, which the flat requests do not include. You may want to ignore such differences in wire protocol.
For implementations that do not provide convenience rest client bindings:
.req
files can be produced correctly using these utilities.Some tests cannot be easily automated. For instance, if you want to check the correct value of a field of an in-memory representation, you do not want to validate it against another in-memory representation. Instead, you can use manual assertions.
Examples of test cases for manual assertions:
data/
,
so assert that the accessors return the correct test data.


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Populate a given annotation container group
<g class='{in|out}-annotations'></g>
with annotation group of the following structure:
selection of the container.
node.{in|out}Annotations
node to build group for.
selection of appended objects
Adjust annotation's position.
selection of a 'g.annotation' element.
Host node data.
annotation node data.
Generated using TypeDoc
Maps an annotation enum to a class name used in css rules.


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I am an Assistant Professor at the Department of Political Science at Florida State University. I received my PhD in Political Science from the University of Rochester and held a Postdoctoral Fellow position at the Data Sciece Lab at Hertie School, working with the SCRIPTS Cluster of Excellence and CATALYSE EU Horizon Project.
My research lies in the fields of comparative political economy, public policy, and visual studies, and is conducted with an application of causal inference and machine learning and deep learning models.
I am a member of the Lancet Countdown team, where I contribute by computationally analyzing climate change rhetoric of the public, media, and international organizations.


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@(playerName : String)(crewCount : Int)(crewNames : List[String])(avatar : Int) @import helper._
You reach China and load up on fidget spinners. When you get back to England the Queen rewards you with a monopoly on importing them. You spin happily ever after. The end for @playerName and the @crewCount crew members left.
Remaining Crew Members: