--- title: "Week 12 Lab -- Confidence Intervals in (G)LMM" author: "Drew Tyre" date: "2019-02-09" output: html_document: fig_caption: true weight: 803121 ---
This week we’ll continue to look at Linear and Generalized linear mixed effects models, emphasizing how to get confidence intervals on the predictions. We’ll start with something easy - a linear mixed effects model with the sleepstudy data.
library(tidyverse)
library(lme4) ## notice conflicts with tidyr
library(broom)
library(boot)
ssBase <- ggplot(sleepstudy, aes(x = Days, y = Reaction)) + geom_point(aes(color = Subject)) +
scale_color_discrete() + labs(x = "Days with no sleep", y = "Reaction time [ms]")
ssBase + geom_smooth(method = "lm") + facet_wrap(~Subject) + guides(color = FALSE)
So there’s the basic data, and now we fit a mixed model with both the intercept and Days varying across subjects.
# fit a mixed model
summary(ss.mm <- lmer(Reaction ~ Days + (1 + Days | Subject), sleepstudy, REML = FALSE))
Let’s check the profile confidence limits on the estimates before we look at getting confidence limits on predictions.
# remember this is SLOOOOW ss.parms <- tidy(ss.mm, conf.int=TRUE,
# conf.method='profile') unfortunately tidy.merMod doesn't do profile
# intervals
confint(ss.mm, oldNames = FALSE)
So the most interesting thing here is that the confidence limit for the correlation coefficient includes 0. The other thing to recognize is that all of the variance parameters are uncertain as well. Even the residual variance has a range of possible values! This is the uncertainty that is not easy to include in our confidence intervals on predictions.
What I want to do now is get confidence intervals on predicted values so we can add nice confidence polygons to our predicted plots. Unlike glm()
or lm()
objects, the predict function for merMod
objects produced by (g)lmer()
doesn’t give us standard errors or confidence limits. The reason given by the developers is that there isn’t a clear method to account for the variance in the random effects parameters. Recognizing that these parameters are uncertain would increase the width of the confidence intervals on our predictions.
First I want to make a plot that has both the population level fitted values and the subject level lines. This is going to get messy.
# get fitted values
ss.fitted <- augment(ss.mm)
names(ss.fitted)
augment()
gives us a bunch of columns for merMod objects; the one we’re interested in here is .fitted
. There is also a column .mu
that has identical values in it. For a model that has a link function other than the identity link (e.g. the default logit link for the binomial family) .fixed
will be on the link scale, and .mu
will be on the response scale. We’ll come back to that in the next example.
# x is inherited from ssBase if we don't specify color=Subject in
# geom_line() we only get one line ... oh, because I specified color=Subject
# in geom_points() not ggplot()
ssBase + geom_line(aes(y = .fitted, color = Subject), data = ss.fitted) + guides(color = FALSE)
So each line represents the fitted values including the effects of the random perturbations on the intercept and slope. Now get the population level predictions using predict() and a new data.frame.
nd <- data.frame(Days = 0:9)
# re.form tells predict what to do with the random effects ~0 says ignore
# them; population level predictions
nd$PopPred <- predict(ss.mm, newdata = nd, re.form = ~0)
ssBase + geom_line(aes(y = .fitted, color = Subject), data = ss.fitted, alpha = 0.5) +
geom_line(aes(y = PopPred), data = nd, size = 2) + guides(color = FALSE)
OK, but we want to know how much confidence to have in that prediction. Really the only option here is to use bootstrapping. This is slow, but gets all the uncertainty in our prediction. Fortunately lme4
includes a function bootMer
to do bootstrapping by generating a random sample of data and then fitting the model to that new data. Repeat that 1000’s of times and you can get a distribution of possible model fits. Unfortunately we have to write a function to extract the predictions from the random samples the way we want them. Start by getting a single random sample.
# bootMer takes a fitted merMod object then the function that takes a fitted
# merMod object and returns the thing we want as a vector fitted() will give
# us the coefficients from a fit
test <- bootMer(ss.mm, fixef)
# a (fairly) compact look at the *str*ucture of an object
str(test)
There’s alot of stuff in there, most of which relates to internal stuff that would allow us to recreate the simulation. We are mostly interested in t0
and t
. t0
is the result of applying our FUN to the original object. In this case it gives us a vector of the fixed effects coefficients. t
is a matrix of the simulation output. In each row is the result of our FUN applied to a simulated result. By default bootMer
only does one simulation. If we want more:
test <- bootMer(ss.mm, fixef, nsim = 10)
test$t
If we set nsim = 10000
and then took quantiles of the resulting columns, we could get bootstrapped confidence limits on our fixed effects. That’s what is happening when we do confint(ss.mm, method="boot")
. We want a function that makes a prediction from a fitted model. Just using predict()
won’t work, because the function only takes one argument, the fitted model. So we have to make a “wrapper” that will call predict()
with the right arguments.
myFunc <- function(mm) {
# forgot the re.form argument on first try
predict(mm, newdata = nd, re.form = ~0)
}
myFunc(ss.mm) # works
# try with bootMer()
test <- bootMer(ss.mm, myFunc)
test$t #works
OK, this next bit takes a while … about 1 minute on my (old) home computer
bigBoot <- bootMer(ss.mm, myFunc, nsim = 1000)
head(bigBoot$t)
Now we want quantiles of each column of that thing, turned around so the columns are rows like the original nd
.
# apply(xx, MARGIN = 2, FUN, ...) 'applies' FUN to each column (because
# MARGIN = 2). arguments in ... get passed to FUN t() transposes the result
predCL <- t(apply(bigBoot$t, MARGIN = 2, FUN = quantile, probs = c(0.025, 0.975)))
# ggplot only works with data.frames so add to nd '%' in column names is a
# disaster so be explicit
nd$lci <- predCL[, 1]
nd$uci <- predCL[, 2]
ssBase + geom_line(aes(y = .fitted, color = Subject), data = ss.fitted, alpha = 0.5) +
geom_line(aes(y = PopPred), data = nd, size = 2) + geom_ribbon(aes(x = Days,
ymin = lci, ymax = uci), data = nd, inherit.aes = FALSE, alpha = 0.2) +
guides(color = FALSE)
So that’s pretty nice. I can add a geom_smooth() to show how much wider the confidence intervals are compared to ignoring all the extra variability.
ssBase + geom_line(aes(y = .fitted, color = Subject), data = ss.fitted, alpha = 0.5) +
geom_line(aes(y = PopPred), data = nd, size = 2) + # set inherit.aes to FALSE here otherwise geom_ribbon looks for a y
# aesthetic called Reaction
geom_ribbon(aes(x = Days, ymin = lci, ymax = uci), data = nd, inherit.aes = FALSE,
alpha = 0.2) + geom_smooth(method = "lm", alpha = 0.8, color = "black") +
guides(color = FALSE)
It is interesting that there isn’t much difference when Days == 0. Note that you wouldn’t ever do this in practice! However, it might be nice to build a few polygons at different levels of confidence.
predCL <- t(apply(bigBoot$t, MARGIN = 2, FUN = quantile, probs = c(0.05, 0.95,
0.1, 0.9, 0.25, 0.75)))
# try making it into a dataframe
predCL <- data.frame(predCL)
# names(predCL) so puts a X at the front bc can't start with a number, and
# replaces % with . put them into nd
nd <- bind_cols(nd, predCL)
# brute force multi-ribbons:
ssBase + geom_line(aes(y = .fitted, color = Subject), data = ss.fitted, alpha = 0.5) +
geom_line(aes(y = PopPred), data = nd, size = 2) + # set inherit.aes to FALSE here otherwise geom_ribbon looks for a y
# aesthetic called Reaction
geom_ribbon(aes(x = Days, ymin = lci, ymax = uci), data = nd, inherit.aes = FALSE,
alpha = 0.2) + # add 90% ribbon
geom_ribbon(aes(x = Days, ymin = X5., ymax = X95.), data = nd, inherit.aes = FALSE,
alpha = 0.2) + # add 80% ribbon
geom_ribbon(aes(x = Days, ymin = X10., ymax = X90.), data = nd, inherit.aes = FALSE,
alpha = 0.2) + # add 50% ribbon
geom_ribbon(aes(x = Days, ymin = X25., ymax = X75.), data = nd, inherit.aes = FALSE,
alpha = 0.2) +
guides(color = FALSE)
That doesn’t look as good as I’d hoped. The idea here is to draw the eye closer to the expected value rather than the outer edges of the confidence region.
So now we want to redo the deer model from last week.
library(NRES803)
data(ecervi)
ecervi <- ecervi %>% mutate(Ecervi.pa = Ecervi > 0, fSex = factor(Sex, labels = c("Male",
"Female")), cLength = Length - mean(Length), csLength = cLength/sd(Length))
contrasts(ecervi$fSex) <- contr.sum(2)
M0 <- glmer(Ecervi.pa ~ fSex * csLength + (1 + csLength | Farm), data = ecervi,
family = binomial)
lr = range(ecervi$csLength)
nd <- expand.grid(csLength = seq(lr[1], lr[2], length = 20), fSex = factor(levels(ecervi$fSex)))
nd$pp = predict(M0, newdata = nd, type = "response", re.form = ~0)
ggplot(nd, aes(x = csLength, y = pp, col = fSex)) + geom_line(alpha = 0.5) +
ylab("Probability of E. cervi infection") + geom_line(aes(x = csLength,
y = pp, col = fSex), data = nd, inherit.aes = FALSE, size = 2) + geom_rug(aes(x = csLength),
data = filter(ecervi, Ecervi.pa), sides = "t", inherit.aes = FALSE) + geom_rug(aes(x = csLength),
data = filter(ecervi, !Ecervi.pa), sides = "b", inherit.aes = FALSE) + facet_wrap(~fSex) +
guides(color = FALSE)
I like this one with facet_wrap()
better than the one from last week. OK, now we want to do the bootstrap. But fitting this model already is slow, so doing it 1000 times is even slower! Bootstrapping is one of the things that benefits from parallel computing very easily. There are some options to bootMer()
that splits the computation up 4 ways. 4 times faster. Most modern CPU’s have multiple cores that can run independently. In normal operation R uses just one core. My office windows computer has 8 cores, so could speed up this computation by a factor of 8! This seems a bit fussy – use at own risk! You can download a binary file with my bigBoot2 object in it here.
# Don't run this code! takes a loooong time ...
bigBoot2 <- bootMer(M0, myFunc, nsim = 1000, parallel = "multicore", ncpus = 4)
save(bigBoot2, file = "data/bigBoot2.RData")
# remember to download the bigBoot2.RData file
if (!exists("bigBoot2")) {
load("data/bigBoot2.Rdata")
}
# the object returned by bootMer is of type boot and there are some useful
# functions there.
envPred <- envelope(bigBoot2)
str(envPred)
The matrix point
in there is the “pointwise” 95% confidence intervals for each of the 40 rows in nd
. The error rate for those intervals is 5% on each value, which means that 24% of the points will be outside the interval over the entire curve. The matrix overall
expands those limits until the number of points over the entire curve is 5%. Time to add these to a plot. First we have to get them into the nd data.frame.
nd$lower.point <- envPred$point[1, ]
nd$upper.point <- envPred$point[2, ]
ggplot(nd, aes(x = csLength, y = pp, col = fSex)) + geom_line(alpha = 0.5) +
ylab("Probability of E. cervi infection") + geom_line(aes(x = csLength,
y = pp, col = fSex), data = nd, inherit.aes = FALSE, size = 2) + geom_rug(aes(x = csLength),
data = filter(ecervi, Ecervi.pa), sides = "t", inherit.aes = FALSE) + geom_rug(aes(x = csLength),
data = filter(ecervi, !Ecervi.pa), sides = "b", inherit.aes = FALSE) + geom_ribbon(aes(x = csLength,
ymin = lower.point, ymax = upper.point, color = fSex), data = nd, inherit.aes = FALSE) +
facet_wrap(~fSex) + guides(color = FALSE)
OK. That’s not right! I mean, not just the fact that they are completely black. Look at the range, those values go from -5 to nearly 8. They can’t be probabilities.
And in fact they aren’t. Back when we created myFunc()
, we just used predict()
without specifying the argument type
(think back to week 5 & 6 with glm()
fits). By default, predict()
produces values on the link scale, the scale of the linear predictor part of the model. But we want to plot probabilities, so we have two choices.
type="response"
and rerun bootMer()
I’m going with (2), because it took hours to do (1) the first time.
# boot::inv.logit() does the job
nd$lower.point <- inv.logit(envPred$point[1, ])
nd$upper.point <- inv.logit(envPred$point[2, ])
nd$sample.curve <- inv.logit(bigBoot2$t[127, ])
ggplot(nd, aes(x = csLength, y = pp, col = fSex)) + # and don't forget to change alpha
geom_ribbon(aes(x = csLength, ymin = lower.point, ymax = upper.point, fill = fSex),
data = nd, inherit.aes = FALSE, alpha = 0.5) + geom_line(aes(col = fSex),
alpha = 0.5) + ylab("Probability of E. cervi infection") + geom_line(aes(x = csLength,
y = pp, col = fSex), data = nd, inherit.aes = FALSE, size = 2) + geom_rug(aes(x = csLength),
data = filter(ecervi, Ecervi.pa), sides = "t", inherit.aes = FALSE) + geom_rug(aes(x = csLength),
data = filter(ecervi, !Ecervi.pa), sides = "b", inherit.aes = FALSE) + facet_wrap(~fSex) +
guides(color = FALSE, fill = FALSE) + geom_line(aes(y = sample.curve))
Phew! The reason this lab is so late getting up is that I could not get that d#$(*&#) graph to have matching colors on the line and the fill. I spent a couple of hours trying everything I could think of. As it turns out it was failing because I had copied the graph code, but not changed the object names … and because I was working interactively the old objects were still around! I only realized my error after wiping the workspace and running the script from the top. The moral of the story is, when nothing makes sense, take it from the top!


Diabetes Detection
This application aims to detect the presence of diabetes by making use of Machine Learning Technology. We have developed a Web Application for detection of the diabetes based on the parameters that the user enters. It predicts whether it is benign or malignant .by learning from the parameters. We have developed a deep neural network model to classify if the user has diabetes or not. The model is trained based on the PIMA Indian Diabetes dataset from National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney).


All boomerang utility functions are under the BOOMR.utils
namespace.
To access any of the following, dereference the BOOMR.utils object. eg: use BOOMR.utils.getCookie()
to call the getCookie()
method.
Gets the value of the cookie identified by sName
.
sName
. This may be the empty string.null
if the cookie wasn't found or if sName
was empty.
Sets the cookie named sName
to the serialized value of oSubCookies
.
null
, it will
use the value of site_domain
that was configured during the call to BOOMR.init().
You probably want to set this to null
.
Note that the entire cookie name and value needs to be less than 4000 characters.
The BOOMR.plugins.RT
plugin uses this function like this:
if(!BOOMR.utils.setCookie( impl.cookie, { s: t_start, r: url }, impl.cookie_exp, "/", null )) { BOOMR.error("cannot set start cookie", "rt"); return this; }
true
if the cookie was set successfullyfalse
if the cookie was not set successfully
Parse a cookie string returned by getCookie()
and split it into its constituent subcookies.
The BOOMR.plugins.BW
plugin calls this function like this:
var cookies = BOOMR.utils.getSubCookies(BOOMR.utils.getCookie(impl.cookie));
null
if sCookie
was not set or did not contain valid subcookies.
Removes the cookie identified by sName
by nullifying its value, and making it a session cookie.
Nothing useful.
Convenience method that plugins can call to configure themselves with the config object passed in to their init()
method.
init()
method.BOOMR.plugins
object.
The BOOMR.plugins.RT
plugin uses this method like this:
BOOMR.utils.pluginConfig(impl, config, "RT", ["cookie", "cookie_exp", "strict_referrer"]);
true
if at least one property was set.false
if no properties were set or if the oConfig object was not set.The latest code and docs is available on github.com/yahoo/boomerang


--- layout: page title: Keynote and Invited Speakers ---
MD, MPH, MA, Harvey M. Meyerhoff Professor of Bioethics and Medicine, Prof. of Medicine, Prof. of Health Policy and Management, and deputy director for medicine of the Berman Institute of Bioethics at the Johns Hopkins University.
Professor, NTNU, Kavli Institute for Systems Neuroscience, Kentros Research Group, Norway.
Director, Center for Human Disease Modeling, Professor of Cell Biology, Brumley Distinguished Professor of Pediatrics, Duke University
Assistant Professor, Stem Cell Biology and Regenerative Medicine / Broad CIRM Center for Regenerative Medicine and Stem Cell Research at USC
Director - Institute of Mental Health / Head, Division of Psychiatry and Applied Psychology, Faculty of Medicine & Health Sciences
Max Planck Institute for Human Cognitive and Brain Sciences/CBS. Department of Neurology
Professor of Medicine and Electrical Engineering, Chair of Biological Imaging at the Technical University of Munich
Director of the department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics (MPIK), Tübingen, Germany.
Assistant Professor of Neurogenetics Department of Neurology, University of Athens Medical School
FORTH’s Chairman. Director Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas & Professor of Molecular Systems, Biology Medical School, University of Crete
Professor of Pharmaceutical Nanotechnology, Director of the Laboratory of Pharm Technology, Faculty of Pharmacy, University of Athens, Greece.
Assoc. Prof., Medical Education Informatics, Lab of Medical Physics, Medical School, Aristotle University of Thessaloniki
Professor, Laboratory of Neuropathology and Neuroscience, The University of Tokyo
Professor of Pediatrics and Endocrinology and Neurobiology, Chairman of the First Department of Pediatrics at the National and Kapodistrian University of Athens School of Medicine, Athens, Greece. UNESCO Chair on Adolescent Health Care at the University of Athens.
Professor, AO DSc FASSA FAA, NHMRC Australia Fellow, Neuroscience Research Australia, Barker St and Hospital Rd, Randwick, Sydney
Institute of Molecular Biology and Biotechnology (IMBB) Foundation for Research and Technology - Hellas (FORTH)
University of Lausanne, Switzerland. Professor, MD Department of Psychiatry University of Geneva School of Medicine
Professor of Psychiatry, Neuroscience and experimental therapeutics First A.P. Slaner family Professor for Alzheimer disease research. Icahn School of Medicine at Mount Sinai
Professor Department of Physiology at the Medical School, University of Patras, Director Stem Cell Laboratory
Professor of Biology medical School University of Patras
M.Sc., Ph.D., Assistant Professor of Neurology, Johns Hopkins School of Medicine
MD, MHS, Elizabeth Plank Althouse Professor, Director, Memory and Alzheimer’s Treatment Center, Chair, Bayview Department of Psychiatry and Behavioral Sciences, Johns Hopkins Medicine
MD Professor of Pathology at the New York-Presbyterian Hospital at the Columbia University Medical Center
Principal Investigator, International Faculty University of Cologne, Professor of Molecular Genetics at Erasmus University Rotterdam
The Maurice and Ilse Katz Professorial Chair in Neuroimmunology, Department of Neurobiology, Weizmann Institute of Science, Israel
Emeritus Professor, Division of Neuroscience & Experimental Psychology, University of Manchester
Director of Population Health Sciences at the German Center for Neurodegenerative Diseases (DZNE), Professor of Population Health Sciences at the University of Bonn, Adjunct Professor of Epidemiology at the Harvard School of Public Health in Boston
Senior Atlantic Fellow for Equity in Brain Health with the Global Brain Health Institute (GBHI) at UCSF, San Francisco, CA, USA and Trinity College Dublin, Dublin, Ireland. Altoida Inc.,La Jolla, CA, USA, Scripps Memorial Hospital, San Diego, CA, USA
Professor of Applied Mathematics, School of Science and Technology, Hellenic Open University, Greece
Assistant Professor, Department of Informatics, Ionian University, Greece
MD, PhD, FEAN is assistant professor of Neurology in Philipps University, Marburg, Germany; Head of Parkinson's disease and movement disorders Dept. in HYGEIA Hospital, Athens
Research Director, Institute of Nanoscience & Nanotechnology, NCSR “Demokritos”, vice-chairman of the Complex Systems and Applications (COSA) Network
Consultant Neurologist and Lead Clinician at East Sussex NHS Trust
MS Bioinformatics, Sr. Data Architect, Health Catalyst, Salt Lake City, Utah
York University. Department of Dance
Unit Head, Aged Persons Mental Health Service, Monash Health Adjunct Senior Lecturer, Department of Psychiatry, Monash University
Professor, Physics & Computer Science Wilfrid Laurier University, Department of Physics and Computer Science Waterloo, Ontario, Canada
M.D., Clinical Investigator, Laboratory of Neurosciences, National Institute on Aging (NIA/NIH)
PhD, Professor of Neurology, University of California, San Francisco
MD, MS, Associate Professor of Clinical Neurology , Columbia University
Group Leader-Epigenetic mechanism of neurodevelopment and diseases at EMBL Heidelberg


Allan Fong, Ricardo Valerdi, Jayakanth Srinivasan
Department of Defense projects examined. Fun and clear illustrations of exchanges between stakeholders through
"large-scale engineering projects require system integrators
that can manage not only the technical interfaces but also
the organizational ones. This paper proposes a boundary
object framework that can assist in understanding the
role of these systems integrators by observing changes
in organizational interfaces. This framework does so by
monitoring the objects and artifacts used at the interfaces."


| Quick links: |
This is an identification program for trees of Northeastern and Central North America. Fill out the form as best as you can and you'll find which trees match. It's better to start with a few characteristics you are sure about, then add more as needed. Use the "Back" button to go back and add (or subtract) characteristics. If you want to see all the trees in the database, simply hit "Identify" without checking any boxes. Fully identifying the tree is up to you.
Some books that can help include:


--- layout: post esbma_id: 1650 title: Baptists and Boundaries date: 2007-01-19 20:26:53 keywords: mfg_strategy teaser: In the neighborhood where I live, 100% of the people need a well that is at least 300 feet deep. I could extrapolate from this and decide that there is a big market for well drilling in my area. However, the city water system is only three miles away. This example may seem absurd, but at this very moment, there are lots of entrepreneurs writing business plans which use similar logic. ---
A few days ago I noticed that I had moved up to page one.
If you search Google for the word "eric", my blog is usually on the second page of the results. On that day, it was on first page, well ahead of all those poor, unfortunate, lesser-known Erics like Eric Clapton.
At first I thought I might write a blog entry to announce my ascent, but there really isn't much point. The fact that I am ahead of Eric Clapton in Google's page ranking is not interesting.
However, there is a reason why this fact is not interesting, and I think that reason is interesting.
Just inside the gates of heaven, St. Peter sits at a desk checking people in.
Peter: "Welcome to heaven. What religion?"
The man at the front of the line says, "Lutheran."
Glancing at his clipboard, Peter says, "Room 33. Be very quiet as you pass room 6."
The process repeats itself with the next person in line:
Peter: "Welcome to heaven. What religion?"
Person #2: "Catholic."
Peter: "Room 17. Be very quiet as you pass room 6."
The next person moves to the front of the line with a look of curiosity on her face.
Peter: "Welcome to heaven. What religion?"
Person #3: "Methodist."
Peter: "Room 54. Be very quiet as you pass room 6."
Person #3: "Why do you keep telling us to be quiet as we pass room 6?"
Peter: "Because the Baptists are in room 6, and they think they're the only ones here."
Most of us rarely step outside the part of the world which is familiar.
In those rare circumstances when we do step outside our boundaries, we are usually surprised that everything is different. A part of us expects everything outside our boundaries to be just like the stuff we see every day. We are familiar with the very small piece of the world that is nearby. We extrapolate that and assume that the whole world is similar to what we know. But it's not.
Whenever I speak to a bunch of developers, one of my favorite things to do is ask the crowd if they have ever heard of Joel Spolsky. Most of the time, far less than half the crowd raises their hand. Why do I do this? Because it helps me remember that life outside my boundaries is a lot different than life here inside.
In this example, one of my boundaries encircles the community built from a cluster of blogs that I tend to read. If you are reading this article, you are probably a part of that very same community. You probably also read Joel and Mike and Steve and Jeff and Ian and Scott and Roy and Dharmesh and Larry. And you probably know that Joel on Software is the #1 blog for software developers. So does it surprise you that most software developers have never heard of Joel? It always surprises me.
But the fact is that most software developers don't read blogs.
For that matter, most people on this planet are not software developers.
In fact, most people on Earth don't have a computer and don't use the Internet.
On a certain level, we know all these facts and consider them to be obvious.
But on another level, we get surprised every time the reality of one of these facts confronts us.
We don't look outside our boundaries. We think we're the only ones here.
 If you search for the word "Eric" (and ignore the results that are not people), the ranking looks like this:
The order of this list tends to fluctuate a little, but you get the idea.
A similar problem happens when you search for the word "Joel":
Now Google doesn't explicitly say that it sorts people in terms of their world influence or their level of celebrity. But the ordering suggests something, and whatever that something is, it's just gotta be wrong.
Eric Clapton is maybe the greatest guitarist of all time. Billy Joel has sold over 100 million records. These two guys have 16 and 6 Grammy awards, respectively. Eric Clapton is probably the most well known "Eric" since that Viking explorer a thousand years ago. Billy Joel is probably the most well known "Joel" since that guy who wrote a book of the Old Testament. And both of them are languishing down at #5 in Google's rankings for their name.
Any ranking that puts us geek bloggers ahead of these two guys just looks wrong. If it's a ranking of the world's most well-known people, then Spolsky and I don't belong at all. If it's a ranking of the world's most well-known "American geek know-it-alls running small software companies that sell tools to software developers", then these legendary musicians should be booted off the list until they can credibly explain to me what a C pointer is.
My point here is not to gripe about Google's rankings. My point is that extrapolating from very little data can give us a really warped view of the world. In this example, we think of Google as really big, but relative to the whole world, it's really quite small.
It's not just Google. Everything on the Web tends to look a lot bigger than it really is. Amazon is big, right? Sorry -- If you sort all retailers by revenue, Amazon doesn't make the top 25. The gorilla in this market (Wal-Mart) has over 30 times as much revenue as Amazon.
One of my favorite things about the web is all the individual communities that live there in the form of discussion boards. The web connects people in ways that were never possible before. When we find ourselves in a discussion forum with people from five different continents, that forum looks really big. But it's still just five people.
Most of the time, this "web distortion field" doesn't really cause much damage. It's not really a big deal to be somewhat clueless due to a narrow perspective. Eventually we learn the truth. We're surprised. No harm done.
The problem of interest to me is when we wield our cluelessness in making product marketing decisions.
Examples:
So here's my call to action: When you do market research for your product idea, make sure you get outside your boundaries.
I spend time in several web communities, and every one of them looks bigger than it really is:
For every market niche I know, if I made product strategy decisions based on what I see in communities on the Web, I would be extrapolating from far too little data. And my decisions would be wrong.
 The rest of us need to work very hard to fully understand the people we hope will buy our products.


Artificial Gene Regulatory Networks
Resources
- GRGEN: A C++ AGRN implementation featuring a number of different dynamics equations, with usage examples in seacells and LALA.
- pyGRN: A python AGRN implementation, including a GPU-based AGRN and a differentiable AGRN using Tensorflow. The differentiable AGRN is also implemented as a Keras layer for use in deep learning tasks.
- AGRN.jl: A Julia AGRN implementation which is currently under development.


Click to create a new project
A Dynamical Theory of the Electromagnetic Field
Kinetic Theory of Gases
The Rings of Saturn
A Collection


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Pack my box with five dozen liquor jugs.
Pack my box with five dozen liquor jugs.
Global font styles are applied to the a
tag, and other tags, set in _global.scss. You can also directly apply evo-link
to an anchor tag. Styles can be adjusted from _evo_variables.scss.
Pack my box with five dozen liquor jugs.
For inverse styles apply the evo-link-inverse
class to an a
tag. Inverse styles can be adjusted from _evo_variables.scss.
Link Paragraph
Pack my box with five dozen liquor jugs.

Pack my box with five dozen liquor jugs.

Global font styles are applied to a
tags nested within p
tags. You can also directly apply an evo-link
class. Styles can be adjusted from _evo_variables.scss.
Pack my box with five dozen liquor jugs.

Pack my box with five dozen liquor jugs.

For inverse styles apply the evo-link-inverse
class to an a
tag nested within a p
tag. Inverse styles can be adjusted from _evo_variables.scss.
Link States
a-link
Pack my box with five dozen liquor jugs.
a-visited
Pack my box with five dozen liquor jugs.
a-hover
Pack my box with five dozen liquor jugs.
a-active
Pack my box with five dozen liquor jugs.
a-focus
Pack my box with five dozen liquor jugs.
Pack my box with five dozen liquor jugs.
If needed for demonstration purposes, apply a 'link state' class directly to an HTML a
element or text to reveal the a:link
, a:visited
, a:hover
, a:active
, or a:focus
pseudo style. Do not include the 'href='.
Inverse Link States
a-link-inverse
Pack my box with five dozen liquor jugs.
a-visited-inverse
Pack my box with five dozen liquor jugs.
a-hover-inverse
Pack my box with five dozen liquor jugs.
a-active-inverse
Pack my box with five dozen liquor jugs.
a-focus-inverse
Pack my box with five dozen liquor jugs.
Pack my box with five dozen liquor jugs.
If needed for demonstration purposes, apply an 'inverse link state' class directly to an HTML a
element or text to reveal the a:link
, a:visited
, a:hover
, a:active
, or a:focus
pseudo style. Do not include the 'href='.


{% extends 'dashboard/base.html' %} {% load staticfiles %} {% load requested_tags %} {% block title %}Find Company{% endblock title %} {% block content %}
Select Request A Quote on as many retailers as you'd like to submit a quote directly.
{% if company.user.plan == 1 %} {{ company.description|truncatechars:300 }} {% else %} {{ company.description }} {% endif %}
Materials: {{ company.get_material_display }}


Generates a URL to a page on the server. Without parameters, urlMod returns a URL to the current page.
This code will generate a URL that looks something like this:
/o2/System-Documentation-Taglibs/showDocumentation?module=Core&tag=call
If the absoluteURL parameter is set to true (1), the URL would become something like this:
http://www.my-site.com/o2/System-Documentation-Taglibs/showDocumentation?module=Core&tag=call
setClass - the path to the Perl module
setMethod - the method that will be called (in the Perl module)
setParams - all parameters (if there should be no parameters, use removeParams)
setParam - set one parameter (the others will be as in the original URL)
setHash - set the hash part of the url
removeParams - remove all parameters
removeParam - remove the specified parameter
removeHash - remove the hash part of the url
appendParam - add one parameter
toggleParam - toggle one parameter between a set of different values on each page urlMod is called (see example below)
absoluteURL [0]
The URL generated might first look like this:
/o2/System-Documentation-Taglibs/showDocumentation?number=1&character=a
On that page, the link will be
/o2/System-Documentation-Taglibs/showDocumentation?number=2&character=b
After that, number will be 3 and character will be c, then they will 1 and a, and so on.
See also , and .


I am assuming that python is already installed on your system and "pip" command is working. If yes then the following steps should work:
1. Open your command prompt and execute command:
$> pip install django
2. To create rest api we need to install django rest framework.
$> pip install djangorestframework
3. By default the django project comes with a security that blocks request coming from different domains. To disable this lets install django cors headers module.
$> pip install django-cors-headers
4. Now lets create a django project. Open the command prompt in desired folder and type command.
$> django-admin startproject RestProject
After execute above command a folder should create on the same directory names "RestProject"
5. Open that folder in VSCode or code editor of your choice. You will see file structure like following image.
__init__.py is just an empty file that indicates that the given folder is a python project or module
asgi.py is the entry point for the ASGI compatible web servers
settings.py contains all the settings and configurations needed for the project
urls.py contains all the url declarations needed for this project
wsgi.py is the entry point for the WSGI compatible web servers
manage.py is a command line utility that helps intract with django project
6. Now the project is setup, lets run the peoject to see how its look in the browser. Just type following command
$> python manage.py runserver
and you will see the url where you django app is running.
copy that url and paste it to the browser, you will see a default django page like below
Now the django is running successfully on your system. Lets do the further things.
7. Create a app in your django project (The current folder structure which you see is a project but app is different than project. A project may have multiple apps in it). To create an app execute the following command.
$> python manage.py startapp EmployeeApp
8. Let us register the app in the required module in project's settings.py file. In the INSTALLED_APPS section lets add 'rest_framework', 'corsheaders' and 'EmployeeApp.apps.EmployeeappConfig'
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'rest_framework',
'corsheaders',
'EmployeeApp.apps.EmployeeappConfig'
]
MIDDLEWARE section add 'corsheaders.middleware.CorsMiddleware'
MIDDLEWARE = [
'corsheaders.middleware.CorsMiddleware',
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
We will also add instruction to enable all domains to access the API (This is not recommended in production instead just only those domains that need to be whitelisted)
CORS_ORIGIN_ALLOW_ALL = True
9. Lets create models needed for our app. We are creating an EmployeeApp (for an example) for this we need two models: Departments (to store employee's department details) and Employees (to store employee details). Just edit the apps models.py file and insert the following code
from django.db import models
# Create your models here.
class Departments(models.Model):
DepartmentId = models.AutoField(primary_key=True)
DepartmentName = models.CharField(max_length=500)
class Employees(models.Model):
EmployeeId = models.AutoField(primary_key=True)
EmployeeName = models.CharField(max_length=500)
Department = models.CharField(max_length=500)
DateOfJoining = models.DateField()
PhotoFileName = models.CharField(max_length=500)
10. We will be using MySQL as the database to create the table from these models. Open your mysql databse and create a database named "pythonapitest" (you can create any name of your choice).
11. Now to connect MySQL from our django app we need to install database adapter. Lets install it with command:
$> pip install pymysql
12. Let us now add the database connection details in the main settings.py file.
import pymysql
pymysql.install_as_MySQLdb()
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.mysql',
'NAME': 'pythonapitest',
'USER': 'root',
'PASSWORD': '123456',
'HOST': 'localhost',
'PORT': '3306'
}
}
In python3 there is an issue with this mysql client so we have added pymysql.install_as_MySQLdb()
13. Now lets run the command to create migration file from our models
$> python manage.py makemigrations EmployeeApp
after executing this we can see a migration file 0001_initial.py under EmployeeApp -> migrations will be create which tells us that what changes to the database will be done. Once it looks fine we can execute the command to push these changes to the database
$> python manage.py migrate EmployeeApp
after execute the command check the tables created in the mysql database
14. Insert 1-2 records manually in the data tables.
15. Lets create serializers for our models. Serialziers basically help to convert the complex types or model instances into native python data types that can be easily rendered into json or xml or other content types. They also help in serialization which is nothing but converting the past data back to complex types. Add a new file serializers.py and add following code in it
from rest_framework import serializers
from EmployeeApp.models import Departments, Employees
class DepartmentSerializer(serializers.ModelSerializer):
class Meta:
model=Departments
fields=('DepartmentId', 'DepartmentName')
class EmployeeSerializer(serializers.ModelSerializer):
class Meta:
model=Employees
fields=('EmployeeId', 'EmployeeName', 'Department', 'DateOfJoining', 'PhotoFileName')
16. Lets now write the api methods as follows
from django.shortcuts import render
from django.views.decorators.csrf import csrf_exempt
from rest_framework.parsers import JSONParser
from django.http.response import JsonResponse
from EmployeeApp.models import Departments, Employees
from EmployeeApp.serializers import DepartmentSerializer, EmployeeSerializer
# Create your views here.
@csrf_exempt
def departmentAPI(request, id=0):
if request.method=='GET':
departments = Departments.objects.all()
departments_serializer = DepartmentSerializer(departments, many=True)
return JsonResponse(departments_serializer.data, safe=False)
elif request.method=='POST':
department_data = JSONParser().parse(request)
departments_serializer = DepartmentSerializer(data=department_data)
if departments_serializer.is_valid():
departments_serializer.save()
return JsonResponse("Added Successfully", safe=False)
return JsonResponse("Failed to Add", safe=False)
elif request.method=='PUT':
department_data = JSONParser().parse(request)
department=Departments.objects.get(DepartmentId=department_data['DepartmentId'])
departments_serializer=DepartmentSerializer(department, data=department_data)
if departments_serializer.is_valid():
departments_serializer.save()
return JsonResponse("Update Successfully", safe=False)
return JsonResponse("Failed to Update", safe=False)
elif request.method=='DELETE':
department=Departments.objects.get(DepartmentId=id)
department.delete()
return JsonResponse("Deleted Successfully", safe=False)
16. Add the url routes to urls.py
from django.urls import path
from EmployeeApp import views
urlpatterns=[
path('department', views.departmentAPI),
path('department/([0-9]+)', views.departmentAPI)
]
17. Next we need to include these urls into the main urls.py file
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('admin/', admin.site.urls),
path('', include('EmployeeApp.urls')),
]
Now start the server and test the api end points as mentioned below. (You can use postman or any other api client
Request Type: GET, URL: http://<IP_ADDRESS>/department
Response:
[
{
"DepartmentId": 1,
"DepartmentName": "Accounts"
},
{
"DepartmentId": 2,
"DepartmentName": "IT"
}
]
Request Type: POST, URL: http://<IP_ADDRESS>/department
Request Body
{
"DepartmentName": "Sales"
}
Response
"Added Successfully"
Request Type: PUT, URL: http://<IP_ADDRESS>/department
Request Body
{
"DepartmentId": "1",
"DepartmentName": "Accountss"
}
Response
"Update Successfully"


PROJECT
CHECK OUR LATEST PROJECTS
TIMELINE
OUR JOURNEY SO FAR
TEAM
MEET OUR TEAM
GALLERY
CHECK OUR GALLERY
CONTACT
CONTACT US


What is this thing??? How do I use it?
A context-free text generator uses a "grammar" to generate strings. You can use this tool to make your own online context-free text generator—all you need to do is put some rows in a Google spreadsheet.
Probably the best way to show you is by example. Let's say you wanted to make a simple generator, that does: "I am the [adjective] [animal] in the [adjective] [place]." You'd make this spreadsheet:
Each row contains a "rule" and an "expansion." By default, the text generation process starts with the rule "S" (for "sentence"). The process then looks at every word in the expansion for that rule. If there's a rule defined for that word, then it will replace the word with the expansion for the rule. If that expansion contains any words that have rules defined for them, it replaces each of those words with their expansions—and so forth, until the only words left are the words that don't have any rules defined for them.
If there's more than one definition for a rule (as in "ADJ" above), then the generation process selects randomly among the rules.
If you're intrigued but confused about all of this, Daniel Howe's explanation of context-free grammar text generation is worth a read. (Note that in Howe's grammars, you can use | to separate alternate expansions for a rule; with this tool, you need to create an extra spreadsheet row for each alternative.)
There are also three special "rules": if you make a rule called GenTitle, then the "expansion" for that rule will be the name of your generator. (Otherwise, it defaults to "My Generator.") If you make a rule called GenAuthor, then the expansion for the rule will be the byline for the generator. (Otherwise it defaults to "Someone.") Finally, if you make a rule called GenAxiom, the rule named in the expansion will be used as the "starting point" for the text generation process. (As mentioned above, the default axiom is S.)
Then when you're ready, select "File" --> "Publish to the web" and click on the "Start publishing" button. You must do this step, otherwise it won't work.
Then just copy and paste the URL of your spreadsheet into this page, and you've got a generator that you can share with friends!
For a somewhat advanced example, see this Weird Sentence Grammar.


Load
Autolayout
ArtifactId
[[artifactId]]
Theme
light
dark
Connections
[[connections.length]]
Inits
[[inits.length]]
Members
[[members.length]]
Slots
[[slots.length]]
Add Random member from own manifest
Add Random Member
Add member
memberId
artifactId
webpackageId
baseUrl
Add Member


FEZ Cerb Family Developers' Guide
The powerful firmware on a single chip design of the Cerb Family makes this core ideal for many uses. GHI offers the following Cerb Family products that all share the exact same processor (STM32F405RGT6) and firmware:
Memory Constraints
Due to the limited amount of memory on the Cerb Family, the following features are not supported:
- Wi-Fi RS9110
- PPP
- SQLite
- USB Host Webcam and Hub
- USB Client
- Extended Weak References
- InField Update
- Serial debugging
- SSL
- Cryptography
Real Time Clock
To enable the Real Time Clock, you must connect a crystal with frequency 32.768KHz and load capacitance of 6pF between PC14 and PC15. VT200F-6PF20PPM from DigiKey will work. You must also supply the VBAT pin with 3V. The FEZ Cerb40 II already does this. The FEZ Cerbuino Net and Bee expose PC14 and PC15 on pins D3 and D4 respectively on their headers. For the FEZ Cerberus, since PC14 and PC15 are not exposed, you must connect the crystal between C10 and C11 on the board on the side closest to the processor.
Loader Update
The loader on the Cerb Family is updated using ST Microelectronics's STDFU Tester program. This program is installed by default with our SDK. Under STMicroelectronics in the start menu, run the STDFU Tester program. The board must be put in a special mode for the STDFU tool to recognize it. To do so, hold the LDR button on your board, power it, then release LDR. If your board lacks an LDR button, short the two pads labeled either LDR or BOOT (depending on your board) together and then power your board. If you have a FEZ Cerb40 II, hold the LODR pin high and then power the board. Next, you will see "STM Device in DFU Mode" appear under Device in the STDFU tool. Click the Protocol tab. Click the Create from Map button, select the Erase radio button, and then click Go. The program will take a few moments to erase the board. Once it has finished, select the download option on the left before downloading the loader file: Click the Load DFU File button and select the C:\Program Files (x86)\GHI Electronics\NETMF v4.3 SDK\Firmwares\Cerb Family\Loader.dfu file. Click the Download radio button and then click Go. The program will quickly load the new loader onto your board. Reboot your board after it finishes and proceed to update the firmware using FEZ Config as detailed on the Firmware Update page.
Warning
Make sure to follow these steps exactly. You could corrupt the loader file or overwrite certain parts of your device if you are not careful.
PWMs
On the Cerb Family of products, the underlying processor groups PWMs in such a way that a change to the frequency in one PWM affects all PWMs in that group. The below list shows the groups of PWMs:
- PWM_3, PWM_11, PWM_12
- PWM_8, PWM_9, PWM_10, PWM_13
- PWM_4, PWM_5, PWM_6, PWM_7
- PWM_14, PWM_15
- PWM_0, PWM_2
- PWM_1
FEZ Cerbuino Net Ethernet Initialization
The below code shows how to initialize the onboard Ethernet on the FEZ Cerbuino Net from a plain NETMF project. It requires the GHI.Networking, GHI.Pins, and Microsoft.SPOT.Net libraries. If you are using Gadgeteer, you can find the Ethernet object pre-created on the Mainboard.Ethernet object.
using GHI.Networking;
using GHI.Pins;
using Microsoft.SPOT;
using Microsoft.SPOT.Hardware;
using Microsoft.SPOT.Net.NetworkInformation;
public class Program
{
private static EthernetENC28J60 netif;
public static void Main()
{
NetworkChange.NetworkAvailabilityChanged += NetworkChange_NetworkAvailabilityChanged;
NetworkChange.NetworkAddressChanged += NetworkChange_NetworkAddressChanged;
netif = new EthernetENC28J60(SPI.SPI_module.SPI1, Generic.GetPin('A', 13), Generic.GetPin('A', 14), Generic.GetPin('B', 10));
netif.Open();
netif.EnableDhcp();
netif.EnableDynamicDns();
}
private static void NetworkChange_NetworkAddressChanged(object sender, Microsoft.SPOT.EventArgs e)
{
Debug.Print("Network address changed");
if (netif.IPAddress != "<IP_ADDRESS>")
{
//The network is now ready to use.
}
}
private static void NetworkChange_NetworkAvailabilityChanged(object sender, NetworkAvailabilityEventArgs e)
{
Debug.Print("Network availability: " + e.IsAvailable.ToString());
}
}
FEZ Cerbuino Bee and FEZ Cerbuino Net SD Card Detect
To detect whether or not an SD card is inserted in the onboard connector, you can sample pin PC2 with the pull-up resistor enabled. You can also use an interrupt to signal when the insertion state changes. Once you detect the presence of a card, you can create and mount the SDCard object.
Known Issues
Socket 5 and 6 on the FEZ Cerberus are both marked as S and P (among others) and use the same SPI bus. The 3 main SPI pins and the 3 PWM pins both use the physical pins 7, 8, and 9 on a socket. As a result, when you use SPI or PWM on those sockets, neither SPI nor PWM will function on the other socket.


As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus.
In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number ( R 0) from the RP model to assess the transmissibility of the SARS-CoV-2.
The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58.
Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.


Mike Bushell vows to keep dancing after he's given the boot from Strictly
The BBC Breakfast host has finally left Strictly after losing out in his fourth dance-off of the series
by Nicola Methven, https://www.mirror.co.uk/authors/nicola-methven/Mike Bushell was finally given his marching orders on Strictly and immediately vowed to carry on dancing.
The BBC Breakfast sports host lost out to Michelle Visage in his fourth dance-off.

Mike, 53, said: “I’d encourage anyone to take up dancing.
“Emily and I would like to join a salsa class. And my mum and dad are talking about getting some ballroom lessons – she’s 77 and he’s 81.”
Paying tribute, to Katya, 30, he said: “I can’t tell you the dedication she puts in. She’d make the greatest sporting coach ever. She makes you believe anything is possible.
“She hasn’t taken it easy on me. We had difficult routines.”
Judge Craig Revel Horwood, 54, said he saved Michelle, 51, a judge on RuPaul’s Drag Race, despite Mike putting up a “very good fight”.
Motsi Mabusi, 38, said Michelle’s American Smooth with Giovani Pernice, 29, was “the clear winner”.
They scored 36 points, compared to 25 for Mike and Katya’s paso doble.
Mike said that, despite being trolled, and even sent a death threat, by people who wanted him out, he had enjoyed the show. He said: “The positives of this outweigh the negatives by 99/1. I’ve got a thick skin.”
Fellow contestant Alex Scott, 35, denied reports that she had wanted to continue with stand-in Kevin Clifton, 37, as her pro partner.
Alex, an ex-Lioness, was reunited with pro Neil Jones, 37, who missed two live shows with injury.
It was claimed that she was “fuming”, but Alex said: “I started laughing when I read it.”
Saturday’s rating for the BBC1 show topped 10 million, while, over on ITV, X Factor : Celebrity hit a new low of just 2.9 million viewers.


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import config.FrontendAppConfig @import components.view_application @import viewmodels.AnswerSection @import viewmodels.PdfViewModel @import views.html.layouts.FullLayoutMainContent @import viewmodels.ConfirmationUrlViewModel @this( printLink: components.printLink, govukLayoutWrapper: GovukLayoutWrapper, fullLayoutMainContent: FullLayoutMainContent ) @( appConfig: FrontendAppConfig, confirmation: Confirmation, pdfToken: String, pdf: PdfViewModel, getCountryName: String => Option[String], compositeMode: Boolean = false, urlViewModel: ConfirmationUrlViewModel )(implicit request: Request[_], messages: Messages) @createLink(path: String)(implicit req: play.api.mvc.Request[_]) = @{ s"${appConfig.host}${routes.Assets.versioned(path)}" } @additionalCSS = @{ Html(s"""""") Html(s"""""") } @govukLayoutWrapper( pageTitle = messages("confirmation.title"), showBackLink = false, optCustomLayout = Some(fullLayoutMainContent(_)), additionalCSS = Some(additionalCSS) ){
@components.view_application(appConfig, pdf, getCountryName, compositeMode) }


Kekaha man arrested, accused of stealing wallets at Kukui Grove
by Dillon AnchetaLIHUE, Hawaii (HawaiiNewsNow) - A 47-year-old Kekaha man has been arrested, suspected in two wallet snatchings at Kukui Grove.
Kauai officials say Steven Kyle Hookano was arrested late Friday afternoon. He was taken in on suspicion of two counts of fourth-degree theft.
Surveillance footage from Oct. 25 showed a man who officials say was Hookano closely following someone at Times Supermarket before grabbing their wallet and running toward the exit.
About a half an hour later, the same man was seen at Longs Drugs where a second victim reported the same thing happened to them.
Kauai police credit anonymous tips submitted to CrimeStoppers in helping identify and arrest the suspect.
“We appreciate the efforts of our officers, the community, and all involved. We also continue to encourage the community to remain vigilant with your belongings, keeping a close eye on them at all times, and to be aware of any suspicious activity while shopping,” Kauai Police Chief Todd Raybuck said.
Hookano was released on Friday on $1,000 bail for one count of fourth-degree theft. He was released pending investigation on another charge.
The investigation is ongoing.
Copyright 2019 Hawaii News Now. All rights reserved.


| Czech name | Original name | Genres | Count of seasons | Count of episodes | Total length | Picture | Note | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| {{show.show.czechName}} | {{show.show.originalName}} |
|
{{show.seasonsCount}} | {{show.episodesCount}} | {{show.totalLength}} | {{show.show.picture}} | {{show.show.note}} | ČSFD | 0" href="http://www.imdb.com/title/tt{{show.show.imdbCode}}" target="_blank">IMDB | Czech Wikipedia | English Wikipedia | Seasons | 0">Move up | Move down | Duplicate | Edit | Remove |
| Count of shows | Count of seasons | Count of episodes | Total length | ||||
|---|---|---|---|---|---|---|---|
| {{shows.length}} | 0 | {{seasonsCount}} | 0 | {{episodesCount}} | 0 | {{totalLength}} | 0:00:00 |


Sean Kemper is a Computer Science major at Stanford University specializing in Human-Computer Interaction. He is also a member of the Stanford Men's Volleyball team and the Kappa Alpha Order.
John Hennessy is the president of Stanford University. He takes HCI classes in his spare time.


{% extends "turkle/base.html" %} {% load i18n static %} {# This is shown to annotators and for admin site #} {% block body %}
{% trans "Enter your current password and your new password twice for verification." %}


--- layout: post title: Vade Mecum and YanceyWare Reader post_id: 274 categories: - projects date: 2004-05-05 07:40:00.000000000 -06:00 author: Jamis permalink: 2004/5/5/vade-mecum-and-yanceyware-reader.html ---
The weekend brought something of a surprise. I was contacted by Josh Lee, one of the folks working on YanceyWare Reader, and he encouraged me to get involved with the development of YwR. The reason? Bryce Yancey, the creator of YwR, was wanting to use concepts from Vade Mecum (my PPC-based Plucker reader) in an as-yet unborn version of YwR!
I’ve since chatted with Bryce, and he likes many of the features of VM. He also likes the plucker file format, but agrees that trying to do a scripture reader with the plucker format introduces some interesting challenges.
I don’t know that I’ll actually have the time to contribute code to a new YwR version, but it is flattering that my meager attempt at a plucker viewer has come to the attention of such illustrious persons. {:)} I had almost given up on VM, but this kind of has me thinking about it again… if only if only if only it were possible to do PPC development from Linux!


--- title: Helpers stylesheet: /special/styleguide/files/styleguide.css txt: 'in 2019, my dad went to work for the CIA — the Chefs, not the "Spooks." ' num: 5 breakfast: ["eggs", "bacon", "toast", "juice", "coffee", "fruit"] lunch: ["sandwich", "chips", "pickle", "salad", "tea", "cookie"] ---
The helper scripts have been grouped: Strings, Numbers, Dates, Arrays, setVar, Typeof, ifConditionals, URI/URL.
All examples use the following data bits, defined in the frontmatter:
txt: 'in 2019, my dad went to work for the CIA — the chefs, not the "spooks." '
num: 5
breakfast: ["eggs", "bacon", "toast", "juice", "coffee", "fruit"]
lunch: ["sandwich", "chips", "pickle", "salad", "tea", "cookie"]
returns the value as a string
{{#code 'html'}}\{{string "" num }}-\{{string "" breakfast }}
{{/code}}{{string "" num }}-{{string "" breakfast }}
'capitalize' returns the string with first letter capitalized.
{{#code 'html'}}\{{string "capitalize" txt }}
{{/code}}{{string "capitalize" txt }}
'charAt' returns the character in the nth position
{{#code 'html'}}The 3rd character in "txt" is \{{string "charAt" txt 3 }}
{{/code}}The 3rd character in "txt" is {{string "charAt" txt 3 }}
'chop' returns the string with whitespace and non-word characters removed from both ends
{{#code 'html'}}\{{string "chop" txt }}
{{/code}}{{string "chop" txt }}
'ellipsify' returns string with all characters after nth position removed and replaced with ellipsis (use triple-stash so the ellipsis isn't escaped)
{{#code 'html'}}\{{{string "ellipsify" txt 35}}}
{{/code}}{{{string "ellipsify" txt 35}}}
'ellipsifyWords' returns string with all words after nth word removed and replaced with ellipsis (use triple-stash so the ellipsis isn't escaped)
{{#code 'html'}}\{{{string "ellipsifyWords" txt 8}}}
{{/code}}{{{string "ellipsifyWords" txt 8}}}
indexOf' returns the position # of the first instance of the substring within the string
{{#code 'html'}}The first "d" in "txt" is at the index of \{{string "indexOf" txt 'd'}}
{{/code}}The first "d" in "txt" is at the index of {{string "indexOf" txt 'd'}}
'lastIndexOf' returns the position # of the last instance of the substring within the string
{{#code 'html'}}The last "d" in "txt" is at the index of \{{string "lastIndexOf" txt "d"}}
{{/code}}The last "d" in "txt" is at the index of {{string "lastIndexOf" txt "d"}}
'length'returns length of string
{{#code 'html'}}The string "txt" has \{{string "length" txt }} characters
{{/code}}The string "txt" has {{string "length" txt }} characters
'lowercase' returns string with all letters lowercased
{{#code 'html'}}\{{string "lowercase" txt }}
{{/code}}{{string "lowercase" txt }}
'padStart' returns the string with the initial position padded N times with character(s) provided
{{#code 'html'}}\{{string "padStart" num 3 "0"}}
{{/code}}{{string "padStart" num 3 "0"}}
'replace' returns the string with substring replaced with new string, with optional modifiers ("g" is default)
{{#code 'html'}}\{{string "replace" txt "Dad" "Mom" "gi"}}
{{/code}}{{string "replace" txt "Dad" "Mom" "gi"}}
'reverse' returns the string reversed
{{#code 'html'}}\{{string "reverse" txt }}
{{/code}}{{string "reverse" txt }}
'sanitize' returns the string with HTML and special characters removed (we use this for <title> content)
{{#code 'html'}}\{{string "sanitize" txt }}
{{/code}}{{string "sanitize" txt }}
'search' similar to indexOf, but works with regular expressions
{{#code 'html'}}The first non-word, non-space character is at position \{{string "search" txt "[^\w\s]"}}
{{/code}}The first non-word, non-space character is at position {{string "search" txt "[^\w\s]"}}
'slice' returns a portion of the string from after the nth character, up to an optional nth character
{{#code 'html'}}The string after 8th position: \{{string "slice" txt 8}}
The string from 8th - 40th position: \{{string "slice" txt 8 40}}
The string after 8th position: {{string "slice" txt 8}}
The string from 8th - 40th position: {{string "slice" txt 8 40}}
'split' splits the string at specified character(s) and returns an array of N segments
{{#code 'html'}}\{{string "split" txt "—" 1}}
\{{array "join" (string "split" txt " ") "_"}}
{{string "split" txt "—" 1}}
{{array "join" (string "split" txt " ") "_"}}
'test' returns true/false depending on if string contains the substring or expression provided, with optional modifiers ("g" is default)
{{#code 'html'}}The string "txt" contains "Dad" (case-insensitive): \{{string "test" txt "Dad" "gi"}}
The string "txt" contains "Work": \{{string "test" txt "Work"}}
{{/code}}The string "txt" contains "Dad" (case-insensitive): {{string "test" txt "Dad" "gi"}}
The string "txt" contains "Work": {{string "test" txt "Work"}}
'trim' returns the string with whitespace removed from both ends
{{#code 'html'}}\{{string "trim" txt }}
{{/code}}{{string "trim" txt }}
'unquote' returns the string with plaintext double quotes replaced with HTML entity quotes (we use this for most meta tag values, use triple-stash if you don't want entities escaped)
{{#code 'html'}}\{{string "unquote" txt }}
\{{{string "unquote" txt }}}
{{string "unquote" txt }}
{{{string "unquote" txt }}}
'uppercase' returns string with all letters uppercased
{{#code 'html'}}\{{string "uppercase" txt }}
{{/code}}{{string "uppercase" txt }}
'abs' returns absolute value of N1
{{#code 'html'}}\{{number "abs" -21.5}}
{{/code}}{{number "abs" -21.5}}
'add' returns N1 + N2
{{#code 'html'}}\{{number "add" num 10 }}
{{/code}}{{number "add" num 10 }}
'ceiling' returns N1 rounded up to closest integer
{{#code 'html'}}\{{number "ceiling" 3.12}}
{{/code}}{{number "ceiling" 3.12}}
'divide' returns N1 / N2
{{#code 'html'}}\{{number "divide" 34 num}
{{/code}}{{number "divide" 34 num}}
'exponent' returns N1 to the power of N2
{{#code 'html'}}\{{number "exponent" 10 num}}
{{/code}}{{number "exponent" 10 num}}
'fixed' returns N1 formatted with fixed-point notation to N2 decimals
{{#code 'html'}}\{{number "fixed" 3.12654338349 num}}
{{/code}}{{number "fixed" 3.12654338349 num}}
'floor' returns N1 rounded down to closest integer
{{#code 'html'}}\{{number "floor" 6.7}}
{{/code}}{{number "floor" 6.7}}
'isInteger'returns true if N1 is an integer, else returns false
{{#code 'html'}}\{{number "isInteger" -34}
{{/code}}{{number "isInteger" -34}}
'multiply' returns N1 * N2
{{#code 'html'}}\{{number "multiply" num 10}}
{{/code}}{{number "multiply" num 10}}
'negate' returns N1 * -1
{{#code 'html'}}\{{number "negate" num }}
{{/code}}{{number "negate" num }}
'random' returns a random number beteween min: N1 and max: N2
{{#code 'html'}}\{{number "random" 0 num}}
{{/code}}{{number "random" 0 num}}
'remainder' returns the remainder of N1 / N2
{{#code 'html'}}\{{number "remainder" 34 num}}
{{/code}}{{number "remainder" 34 num}}
'round' returns N1 rounded off to closest integer
{{#code 'html'}}\{{number "round" 3.12}}
{{/code}}{{number "round" 3.12}}
'subtract' returns N1 - N2
{{#code 'html'}}\{{number "subtract" num 10}}
{{/code}}{{number "subtract" num 10}}
'USCalendar' returns full US formatted date of today, or optional date provided
{{#code 'html'}}Today is \{{date "USCalendar" }}
{{/code}}Today is {{date "USCalendar" }}
'dateNum' returns the day of the month (1-31) of today, or optional date provided
{{#code 'html'}}Today is day \{{date "dateNum" }} of this month
{{/code}}Today is day {{date "dateNum" }} of this month
'dateStr' similar to dateNum, but formatted to always be 2 characters (01-31)
{{#code 'html'}}\{{date "dateStr" "8/4/1999"}}
{{/code}}{{date "dateStr" "8/4/1999" }}
'USDate' returns a date with US format (MM/DD/YYYY) of today, or optional date provided
{{#code 'html'}}\{{date "USDate" "January 2, 2021 14:23:16 GMT-5"}}
{{/code}}{{date "USDate" "January 2, 2021 14:23:16 GMT-5"}}
'USDateShort' returns a date with US format (m/d/yy) of today, or optional date provided
{{#code 'html'}}\{{date "USDateShort" "January 2, 2021 14:23:16 GMT-5"}}
{{/code}}{{date "USDateShort" "January 2, 2021 14:23:16 GMT-5"}}
'weekdayNum' returns the day of the week (1-7) of today, or optional date provided
{{#code 'html'}}Today is day \{{date "weekdayNum" }} of this week
{{/code}}Today is day {{date "weekdayNum" }} of this week
weekdayStr' returns the day of the week (Sunday - Saturday) of today, or optional date provided
{{#code 'html'}}Christmas 2020 was on a \{{date "weekdayStr" "12/25/2020"}}
{{/code}}Christmas 2020 was on a {{date "weekdayStr" "12/25/2020"}}
'month' returns the month (January - December) of today, or optional date provided
{{#code 'html'}}The month is currently \{{date "month" }}
{{/code}}The month is currently {{date "month" }}
'monthAbr' returns the month abbreviation (Jan - Dec) of today, or optional date provided
{{#code 'html'}}The month is currently \{{date "monthAbr" }}
{{/code}}The month is currently {{date "monthAbr" }}
'monthNum' returns the month number (1-12) of today, or optional date provided
{{#code 'html'}}\{{date "month" }} is month number \{{date "monthNum" }}
{{/code}}{{date "month" }} is month number {{date "monthNum" }}
'monthStr' similar to monthNum but always formatted to be 2 characters (01-12)
{{#code 'html'}}\{{date "month" }} is month number \{{date "monthStr" }}
{{/code}}{{date "month" }} is month number {{date "monthStr" }}
'year' returns the year (4 digits) of today, or optional date provided
{{#code 'html'}}\{{date "year" }}
{{/code}}{{date "year" }}
returns the value as an array (allowing for array functions like each, first, last, etc.)
{{#code 'html'}} \{{#each (array "" num) }}\{{#if @first}}first item: \{{/if}} \{{.}} \{{#if @last}}- also last item\{{/if}}
\{{/each}} {{/code}} {{#each (array "" num) }}{{#if @first}}first item: {{/if}} {{.}} {{#if @last}}- also last item{{/if}}
{{/each}}'concat' returns a new array containing items fromthe 2 arrays passed to it
{{#code 'html'}} \{{#each (array "concat" breakfast lunch)}} \{{this}}, \{{/each}}{{/code}}{{#each (array "concat" breakfast lunch)}} {{this}}, {{/each}}
'inArray' returns true if array contains specified string
{{#code 'html'}} \{{#if (array "inArray" lunch "sandwich")}}The lunch array contains "sandwich".
\{{else}}The lunch array does not contain "sandwich".
\{{/if}}{{/code}} {{#if (array "inArray" lunch "sandwich")}}The lunch array contains "sandwich".
{{else}}The lunch array does not contain "sandwich".
{{/if}}'join' joins elements of an array into a string with specified separators
{{#code 'html'}}\{{array "join" breakfast " & "}}
{{/code}}{{array "join" breakfast " & "}}
'length' returns the length of an array
{{#code 'html'}}I have \{{array "length" breakfast}} items for breakfast
{{/code}}I have {{array "length" breakfast}} items for breakfast
'pop' removes the last item from the array and returns it (permanently modifies the array)
{{#code 'html'}}Last item was \{{array "pop" lunch}}
The rest of lunch is: \{{#each lunch}} \{{.}} \{{/each}}
{{/code}}Last item was {{array "pop" lunch}}
The rest of lunch is: {{#each lunch}} {{.}} {{/each}}
'push' returns the array with the new item added to the end (permanently modifies the array)
{{#code 'html'}}The revised lunch is: \{{#each (array "push" lunch "muffin")}} \{{.}} \{{/each}}
{{/code}}The revised lunch is: {{#each (array "push" lunch "muffin")}} {{.}} {{/each}}
'randomize' returns a copy of the array with the items in random order
{{#code 'html'}}The randomized lunch is: \{{#each (array "randomize" lunch)}} \{{.}} \{{/each}}
{{/code}}The randomized lunch is: {{#each (array "randomize" lunch)}} {{.}} {{/each}}
'reverse' returns a copy of the array with the items in reversed order
{{#code 'html'}}The reversed breakfast is: \{{#each (array "reverse" breakfast)}} \{{.}} \{{/each}}
{{/code}}The reversed breakfast is: {{#each (array "reverse" breakfast)}} {{.}} {{/each}}
'shift' removes the first item from the array and returns it (permanently modifies the array)
{{#code 'html'}}First item was \{{array "shift" breakfast}}
The rest of breakfast is: \{{#each breakfast}} \{{.}} \{{/each}}
{{/code}}First item was {{array "shift" breakfast}}
The rest of breakfast is: {{#each breakfast}} {{.}} {{/each}}
'slice' returns items from within the array, starting at nth item specified, up to an optional nth item
{{#code 'html'}}Items 2-3 of breakfast are: \{{#each (array "slice" breakfast 1 3)}} \{{.}} \{{/each}}
{{/code}}Items 2-3 of breakfast are: {{#each (array "slice" breakfast 1 3)}} {{.}} {{/each}}
'sort' returns the array with the items in alphanumeric order (permanently modifies the array)
{{#code 'html'}}Sorted alphanumerically, lunch is: \{{#each (array "sort" lunch)}} \{{.}} \{{/each}}
{{/code}}Sorted alphanumerically, lunch is: {{#each (array "sort" lunch)}} {{.}} {{/each}}
'unshift' returns the array with the new item added to the start (permanently modifies the array)
{{#code 'html'}}The revised breakfast is: \{{#each (array "unshift" breakfast "muffin")}} \{{.}} \{{/each}}
{{/code}}The revised breakfast is: {{#each (array "unshift" breakfast "muffin")}} {{.}} {{/each}}
'setVar' stores a root level variable that can be retrieved later
{{#code 'html'}} \{{setVar "maximum" num }}The variable 'maximum' equals<EMAIL_ADDRESS>{{/code}} {{setVar "maximum" num }}The variable 'maximum' equals<EMAIL_ADDRESS>'typeof' returns true/false depending on if first item is type of second item
{{#code 'html'}}\{{#if (typeof breakfast "object")}} 'breakfast' has a typeof 'object'.\{{/if}}
>
\{{#unless (typeof breakfast "string")}} 'breakfast' is not typeof 'string'.\{{/unless}}
{{#if (typeof breakfast "object")}} 'breakfast' has a typeof 'object'.{{/if}}
{{#unless (typeof breakfast "string")}} 'breakfast' is not typeof 'string'.{{/unless}}
'==' returns true if (item1 == item2), else false
{{#code 'html'}}value of 'num' \{{#if (ifCond num '==' '5')}} is \{{else}} is not \{{/if}} equal to '5'
{{/code}}value of 'num' {{#if (ifCond num '==' '5')}} is {{else}} is not {{/if}} equal to '5'
'===' returns true if (item1 === item2), else false
{{#code 'html'}}value and type of 'num' \{{#if (ifCond num '===' '5')}} is \{{else}} is not \{{/if}} equal to '5'
{{/code}}value and type of 'num' {{#if (ifCond num '===' '5')}} is {{else}} is not {{/if}} equal to '5'
'!=' returns true if (item1 != item2), else false
{{#code 'html'}}value of 'num' \{{#if (ifCond num '!=' '5')}} is not \{{else}} is \{{/if}} equal to '5'
{{/code}}value of 'num' {{#if (ifCond num '!=' '5')}} is not {{else}} is {{/if}} equal to '5'
'!==' returns true if (item1 !== item2), else false
{{#code 'html'}}value and type of 'num' \{{#if (ifCond num '!==' '5')}} is not \{{else}} is \{{/if}} equal to '5'
{{/code}}value and type of 'num' {{#if (ifCond num '!==' '5')}} is not {{else}} is {{/if}} equal to '5'
'<' returns true if (item1 < item2), else false
{{#code 'html'}}'num' \{{#if (ifCond num '<' 6)}} is \{{else}} is not \{{/if}} less than 6
{{/code}}'num' {{#if (ifCond num '<' 6)}} is {{else}} is not {{/if}} less than 6
'<=' returns true if (item1 <= item2), else false
{{#code 'html'}}'num' \{{#if (ifCond num '<=' 6)}} is \{{else}} is not \{{/if}} less than or equal to 5
{{/code}}'num' {{#if (ifCond num '<=' 6)}} is {{else}} is not {{/if}} less than or equal to 5
'>' returns true if (item1 > item2), else false
{{#code 'html'}}'num' \{{#if (ifCond num '>' 6)}} is \{{else}} is not \{{/if}} greater than 6
{{/code}}'num' {{#if (ifCond num '>' 6)}} is {{else}} is not {{/if}} greater than 6
'>=' returns true if (item1 >= item2), else false
{{#code 'html'}}'num' \{{#if (ifCond num '>=' 6)}} is \{{else}} is not \{{/if}} greater than or equal to 6
{{/code}}'num' {{#if (ifCond num '>=' 6)}} is {{else}} is not {{/if}} greater than or equal to 6
'&&' returns true if both item1 & item2 are true, else false
{{#code 'html'}}\{{#if (ifCond (typeof breakfast "object") '&&' (array "inArray" lunch "sandwich"))}} both conditions are true \{{else}} one or more conditions is false \{{/if}}
{{/code}}{{#if (ifCond (typeof breakfast "object") '&&' (array "inArray" lunch "sandwich"))}} both conditions are true {{else}} one or more conditions is false {{/if}}
'||' returns true if either item1 or item2 is true, else false
{{#code 'html'}}\{{#if (ifCond (typeof breakfast "number") '||' (array "inArray" lunch "sandwich"))}} at least 1 condition is true \{{else}} both conditions are false \{{/if}}
{{/code}}{{#if (ifCond (typeof breakfast "number") '||' (array "inArray" lunch "sandwich"))}} at least 1 condition is true {{else}} both conditions are false {{/if}}
'decodeURI' returns a decoded URI (that was previously encoded)
{{#code 'html'}}\{{uri 'decodeURI' "http://www.freddiemac.com/?str=%5Bhi%20there!%5D"}}
{{/code}}{{uri 'decodeURI' "http://www.freddiemac.com/?str=%5Bhi%20there!%5D"}}
'decodeURIComponent' returns a decoded component URI (that was previously encoded)
{{#code 'html'}}\{{uri 'decodeURI' "http%3A%2F%2Fwww.freddiemac.com%2F%3Fstr%3D%5Bhi%20there!%5D"}}
{{/code}}{{uri 'decodeURI' "http%3A%2F%2Fwww.freddiemac.com%2F%3Fstr%3D%5Bhi%20there!%5D"}}
'encodeURI' returns an URI encoded string
{{#code 'html'}}\{{uri 'encodeURI' "http://www.freddiemac.com/?str=[hi there!]"}}
{{/code}}{{uri 'encodeURI' "http://www.freddiemac.com/?str=[hi there!]"}}
'encodeURIComponent' returns an URI component encoded string
{{#code 'html'}}\{{uri 'encodeURIComponent' "http://www.freddiemac.com/?str=[hi there!]"}}
{{/code}}{{uri 'encodeURIComponent' "http://www.freddiemac.com/?str=[hi there!]"}}
'getHostName' returns hostname of a URL, without query string or protocol
{{#code 'html'}}\{{uri 'getHostName' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
{{/code}}{{uri 'getHostName' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
'getHash' returns hostname of a URL, without query string or protocol
{{#code 'html'}}hash is "\{{uri 'getHash' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}"
{{/code}}hash is "{{uri 'getHash' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}"
'getPageName' returns the pagename of a URL without the query string or hash
{{#code 'html'}}Pagename is "\{{uri 'getPageName' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}"
{{/code}}Pagename is "{{uri 'getPageName' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}"
'getProtocol' returns protocol of a URL
{{#code 'html'}}\{{uri 'getProtocol' "https://myhome.freddiemac.com/page.html?str=[hi there!]"}}
{{/code}}{{uri 'getProtocol' "https://myhome.freddiemac.com/page.html?str=[hi there!]"}}
'getRelativePath' returns path and filename of URL without protocol, domain, query string, or hash
{{#code 'html'}}\{{uri 'getRelativePath' "https://myhome.freddiemac.com/subsection/page.html?a=example&b=sorry#bookmark"}}
{{/code}}{{uri 'getRelativePath' "https://myhome.freddiemac.com/subsection/page.html?a=example&b=sorry#bookmark"}}
'getQueryString' returns Query string of a URL
{{#code 'html'}}\{{uri 'getQueryString' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
{{/code}}{{uri 'getQueryString' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
'stripProtocol' returns a URL without the protocol
{{#code 'html'}}\{{uri 'stripProtocol' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
{{/code}}{{uri 'stripProtocol' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
'stripQueryString' returns a URL without the query string or hash
{{#code 'html'}}\{{uri 'stripQueryString' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}
{{/code}}{{uri 'stripQueryString' "https://myhome.freddiemac.com/page.html?a=example&b=sorry#bookmark"}}


Objects can be filtered quickly using the q
query parameter:
{{ url }}?q=<search terms>
The search terms are split into words, and each word is searched for in the following fields: {% for field in fields %}{{ field.name }}{% if not forloop.last %}, {% endif %}{% endfor %}. Words can be grouped using quotes to prevent them from being split, for example "black dog". You can try simple filtering below:


Vue.js is an MIT-licensed open source project. It’s an independent project with its ongoing development made possible entirely thanks to the support by these awesome backers. If you’d like to join them, please consider:
Funds donated via Patreon goes directly to support Evan You’s full-time work on Vue.js. Funds donated via OpenCollective are managed with transparent expenses and will be used for compensating work and expenses by core team members or sponsoring community events. Your name/logo will receive proper recognition and exposure by donating on either platform.
Vue (pronounced /vjuː/
, like view) is a progressive framework for building user interfaces. It is designed from the ground up to be incrementally adoptable, and can easily scale between a library and a framework depending on different use cases. It consists of an approachable core library that focuses on the view layer only, and an ecosystem of supporting libraries that helps you tackle complexity in large Single-Page Applications.
Vue.js supports all browsers that are ES5-compliant (IE8 and below are not supported).
| Project | Status | Description |
|---|---|---|
| vue-router | Single-page application routing | |
| vuex | Large-scale state management | |
| vue-cli | Project scaffolding | |
| vue-loader | Single File Component (*.vue file) loader for webpack |
|
| vue-server-renderer | Server-side rendering support | |
| vue-class-component | TypeScript decorator for a class-based API | |
| vue-rx | RxJS integration | |
| vue-devtools | Browser DevTools extension |
To check out live examples and docs, visit vuejs.org.
For questions and support please use the the official forum or community chat. The issue list of this repo is exclusively for bug reports and feature requests.
Please make sure to read the Issue Reporting Checklist before opening an issue. Issues not conforming to the guidelines may be closed immediately.
Detailed changes for each release are documented in the release notes.
Please make sure to read the Contributing Guide before making a pull request. If you have a Vue-related project/component/tool, add it with a pull-request to this curated list!
Thank you to all the people who already contributed to Vue!
Copyright (c) 2013-present, Yuxi (Evan) You


{% extends 'admin_base.html' %} {% block title %}Make:good - Admin!{% endblock %} {% block content %}
Cath: You can add a new Category, or delete/edit existing Categories. A Category is just a grouping of Pages. You should aim for about 3 Categories as these are lined up horizontally on the home page. If you want more than that we will have to redesign the homepage to fit. If you delete a Category then the Page will still exist, but will not be linked to on the homepage.


--- layout: post title: "RT: oh boy. Starcraft 2 beta s..." --- RT: oh boy. Starcraft 2 beta signups are available. (via @jakelumetta) (via @xentek)


CONFECTIONERY APPRENTICESHIP AT NESTLE
THE PERFECT OPPORTUNITY
The apprenticeship I’m currently on at Nestle just sounded like one of the best opportunities I had come across. I had no clue what I wanted to do for a job, and I knew further education wasn't for me. As soon as I saw the advert for my apprenticeship, I just knew it was perfect.
THE BEST OF BOTH WORLDS
I'd be working with chocolate and learning skills created hundreds of years ago – with one of the biggest food and drink companies in the world. When I saw that I’d also be working to get a degree, I was over the moon! It seemed to be the best of both worlds – learning while also earning a wage.
LOOKING AHEAD
I am so thankful that I’ve got a degree – but not just that on its own. I also have three years of invaluable hands-on experience working at Nestle. This experience, and the amount I now know about the confectionery industry, gives me a huge advantage for future career options.
I am so thankful that I’ve got a degree – but not just that on its own. I also have three years of invaluable hands-on experience.
Katie Lloyd, 22 Confectionery Apprenticeship
NESTLE


-
hDel
-
Removes the specified fields from the hash stored at key.
-
headerImagem
-
Retorna imagem com seu respectivo cabecalho
-
hExists
-
Determine if a hash field exists
-
hGet
-
Get the value of a hash field
-
hGetAll
-
Get all the fields and values in a hash
-
hIncrBy
-
Increments the number stored at field in the hash stored at key by increment.
-
hKeys
-
Get all the fields in a hash
-
hLen
-
Get the number of fields in a hash
-
hMGet
-
Returns the values associated with the specified fields in the hash stored at key.
-
hMSet
-
Set multiple hash fields to multiple values
-
hSet
-
Set the string value of a hash field
-
hSetNX
-
Set the value of a hash field, only if the field does not exist
-
hVals
-
Get all the values in a hash
-
sAdd
-
Add a member to a set
-
sCard
-
Get the number of members in a set
-
sDiff
-
Returns the members of the set resulting from the difference between the first set and all the successive sets.
-
sDiffStore
-
This command is equal to SDIFF, but instead of returning the resulting set, it is stored in destination.
-
Select
-
Select the DB with having the specified zero-based numeric index. New connections always use DB 0.
-
send_command
-
Execute send_command and return the result
-
Set
-
Set key to hold the string value. If key already holds a value, it is overwritten, regardless of its type.
-
SetBit
-
Sets or clears the bit at offset in the string value stored at key
-
SetEx
-
Set the value and expiration of a key
-
SetNX
-
Set the value of a key, only if the key does not exist
-
SetRange
-
Overwrites part of the string stored at key, starting at the specified offset, for the entire length of value.
-
sInter
-
Returns the members of the set resulting from the intersection of all the given sets.
-
sInterStore
-
Intersect multiple sets and store the resulting set in a key This command is equal to SINTER, but instead of returning the resulting set, it is stored in destination.
-
sIsMember
-
Returns if value is a member of the set.
-
SlaveOf
-
Make the server a slave of another instance, or promote it as master
-
sMembers
-
Returns all the members of the set.
-
sMove
-
Move member from the set at source to the set at destination.
-
Sort
-
Sort the elements in a list, set or sorted set
-
sRem
-
Remove member from the set. If 'value' is not a member of this set, no operation is performed.
-
StrLen
-
Get the length of the value stored in a key
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Subscribe
-
Subscribes the client to the specified channels.
-
sUnion
-
Returns the members of the set resulting from the union of all the given sets.
-
sUnionStore
-
Add multiple sets and store the resulting set in a key
-
zAdd
-
Add a member to a sorted set, or update its score if it already exists
-
zCard
-
Get the number of members in a sorted set
-
zCount
-
Returns the number of elements in the sorted set at key with a score between min and max.
-
zIncrBy
-
Increment the score of a member in a sorted set
-
zInterStore
-
Intersect multiple sorted sets and store the resulting sorted set in a new key
-
zRange
-
-
zRangeByScore
-
Return a range of members in a sorted set, by score
-
zRank
-
Returns the rank of member in the sorted set stored at key, with the scores ordered from low to high.
-
zRem
-
Remove a member from a sorted set
-
zRemRangeByRank
-
Removes all elements in the sorted set stored at key with rank between start and stop.
-
zRemRangeByScore
-
Remove all members in a sorted set within the given scores
-
zRevRange
-
Returns the specified range of elements in the sorted set stored at key.
-
zRevRangeByScore
-
Returns all the elements in the sorted set at key with a score between max and min (including elements with score equal to max or min).
-
zRevRank
-
Returns the rank of member in the sorted set stored at key, with the scores ordered from high to low.
-
zScore
-
Get the score associated with the given member in a sorted set
-
zUnionStore
-
Add multiple sorted sets and store the resulting sorted set in a new key


Looking for a place to board your horse in Central Oregon, but still have questions? Give us a call today and let us win you over with down to earth customer service and professionalism.
Hidden Haven would also like to give a shout out to help promote our quality hay provider, Brian & Emily Lapore with their company Golden Eagle Organics Inc.! Their company has been incredible in keeping a bountiful supply of Central Oregon's best quality hay for us. They also provide organic pasture raised meats. Give their web site a quick look!


This lively and popular tourist city is on the river Elbe, about 60 miles from its entrance.
This is a very busy commercial port with several marinas. There are two marinas for visitors. One is 12 miles from the city and the other (City Sporthafen) is in the city centre.
All the services of a major city are to be found here.
Last updated December 2010.


Available Metrics
For more information about applying metrics, see Caliper.
DIScover offers the following metrics queries:
|
Metric |
Description |
|
Cyclomatic Complexity |
A measure of complexity within a specified function; a higher value means greater complexity |
|
Lines of Code (LOC) |
Number of lines of code contained in a selected function or file |
|
Myer’s Complexity |
Myer’s Complexity for a function or file |
|
Base Classes (fan-in) |
Number of base (super) classes for a selected class |
|
Derived Classes (fan-out) |
Number of derived (sub) classes for a selected class |
|
Size in bytes |
Number of derived (sub) classes for a selected class |
|
Nested Control Structures |
Maximum depth of nested control structures in a file or function |
|
Dangling else-ifs |
Number of dangling else-if statements in a file or function |
|
Defaultless switches |
Number of switches lacking a default clause in a file or function |
|
Starting line number |
Starting line number of a function or class definition |
|
Return statements |
Number of return statements in a file or function |
|
Uncommented lines |
Number of lines of code, excluding comments and empty lines, in a file or function |
|
Executable lines |
For a file or function, number of lines of code, excluding comments, function declarations, lines containing only ‘{ ‘or ‘} ’, and IFDEF ’d regions of code |
|
Number of ifs |
Number of if statements in a file or function |
|
Number of switches |
Number of switch statements in a file or function |
|
Number of loops |
Number of loops in a file or function |
|
Number of defaults |
Number of switch statements with a default in a file or function |


{% extends "base.html" %} {%- block document %}
Pulsar is an event driven framework for the Python programming language


Disaster Response Project 1.0
Data Sources
(current)
Github Repository of this app
Udacity
Disaster Response Project 1.0
Analyzing message data for disaster response
Introduction: This website analyzes disaster data from
Figure Eight
, and try to build a API using machine learning model to classifies disaster messages.
Please input a message with less than 50 words.
Submit
{% block message %} {% endblock %}
{% block content %}
Overview of Training Dataset
{% endblock %}