Returns an Array of all favorited Twitter::Status objects for the logged-in Twig::My user.
If favorites hasn’t been called yet, or if action is :update, :sync, or :refresh, the Array will be cleared and refreshed with the users favorite Twitter::Status objects from the Twitter server.
# File lib/twig/my.rb, line 36 def favorites(action=nil) if @favorites case action when :update, :sync, :refresh @favorites = @client.favorites when nil @favorites else raise ArgumentError, "#{action} is not a valid argument for @favorites." end else @favorites = @client.favorites end end
Returns an Array of all followers for the logged-in Twig::My user as Twitter::User objects.
If followers hasn’t been called yet, or if action is :update, :sync, or :refresh, the Array will be cleared and refreshed with a current list of Twitter::User followers from the Twitter server.
# File lib/twig/my.rb, line 59 def followers(action=nil) if @followers case action when :update @followers = @client.my(:followers) when nil @followers else raise ArgumentError, "#{action} is not a valid argument for @followers." end else @followers = @client.my(:followers) end end
Returns the Twitter::User info object for the logged-in Twig::My user.
If info hasn’t been called yet, or if action is :update, :sync, or :refresh, the Twitter::User object will be cleared and a current one will be fetched from the server.
# File lib/twig/my.rb, line 14 def info(action=nil) if @info case action when :update, :sync, :refresh @info = @client.my(:info) when nil @info else raise ArgumentError, "#{action} is not a valid argument for @info." end else @info = @client.my(:info) end end
Disabled; run with --debug to generate this.
Generated with the Darkfish Rdoc Generator 1.1.6.


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spl
`Prev `__
S
`Next `__
--------------
**spl**: /S·P·L/
[abbrev, from Set Priority Level] The way traditional Unix kernels
implement mutual exclusion by running code at high interrupt levels.
Used in jargon to describe the act of tuning in or tuning out ordinary
communication. Classically, spl levels run from 1 to 7; “Fred's at spl 6
today” would mean that he is very hard to interrupt. “Wait till I finish
this; I'll spl down then.” See also `*interrupts locked
out* <../I/interrupts-locked-out.html>`__.
--------------
+--------------------------------------------+----------------------------+----------------------------------+
| `Prev `__ | `Up <../S.html>`__ | `Next `__ |
+--------------------------------------------+----------------------------+----------------------------------+
| Spinning Pizza of Death | `Home <../index.html>`__ | splash screen |
+--------------------------------------------+----------------------------+----------------------------------+


The file must contain a YVALUE
property and may optionally contain a
URL
property. If present, the URL will be opened when the data point on the plot is clicked.
The specification of this file can use wildcards like build/report/*/report.properties
but only the first file resolved by the wildcard will be used.
See the
@includes of Ant fileset for the exact format.
For example, a properties file might look like:
YVALUE=3.342 URL=http://foo.bar/


These interactive cartograms allow analysts to explore mainland Chinese statistics.
Analysts can better compare regional differences with cartograms, and because most of the indicators have time-series data points that cover many years, analysts can also explore historical changes by choosing different years.
Most of the indicators are downloaded from China’s National Bureau of Statistics (for more details on its effort for “more open and big data”, see my earlier blog post).
The derived indicators of (i) per population and (ii) per GDP are designed for geographic normalization so as to allow analysts to compare per size outcomes, which can be viewed as *density* measurements.
The data of Internet population and Internet penetration rates, are derived from several Statistical Report[s] on Internet Development in China, as part of my DPhil work to understand the "block-then-difussion patterns" . Since such data does not seem to be available openly on the website of China’s National Bureau of Statistics, I have begun to share the data here: http://goo.gl/qzGxWV. Also, my DPhil work includes East Asian data points for further comparisons, as shown by the animated visualization of Internet Penetration Rates in East Asian and Chinese Regions 1995-2012.
The data of Internet International Visits comes from qianzhan.com.
Cartogram.js(designed and built by Shawn Allen at Stamen on the foundation of d3.js) implements an algoritm to construct continuous area cartograms, by James A. Dougenik, Nicholas R. Chrisman and Duane R. Niemeyer, ©1985 by the Association of American Geographers. This example combines TopoJSON-encoded boundaries of the mainland China from Global Administrative Areas.
hanteng June 1, 2014


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/unfolding.20issue.html ---
(presheaf_of_types_pullback_under_open_immersion {F := F, res := res, Hid := Hid, Hcomp := Hcomp} id _).res
Why can't I unfold that?
lam X, presheaf_of_types_pullback_under_open_immersion X f H
is a function from a structure to itself
I explicitly write down the definition, I say what F and res and Hid and Hcomp are
I don't see any reason why Lean can't evaluate that res
My goal is [mess above] == res
and this should just unravel to be, hopefully, something trivial.
This is another one of those insane "trivial in maths, hard in Lean" things
I am trying to prove that if you pull back a sheaf by the identity function, you get the same sheaf
this statement is fraught with difficulties though
and this is definitely not refl
because I am claiming for example that F U = F (id '' U)
What's the definition of presheaf_of_types_pullback_under_open_immersion
? I think the functions like .res
only unfold when applied to something of the form {F := _, ...}.res
and not x.res
for example. Have you tried show
?
Is it because it doesn't know what the underscore is?


Furious Seven
Dominic and his crew thought they'd left the criminal mercenary life behind. They'd defeated international terrorist Owen Shaw and went their separate ways. But now, Shaw's brother, Deckard Shaw, is out killing the crew one by one for revenge. Worse, a Somalian terrorist called Jakarde and a shady government official called "Mr. Nobody" are both competing to steal a computer terrorism program called "God's Eye," that can turn any technological device into a weapon. Torretto must reconvene with his team to stop Shaw and retrieve the God's Eye program while caught in a power struggle between the terrorist and the United States government.


Christmas 1999 - 6,
originally uploaded by jduprey.
The scrawny, pale kid in this picture just turned 21. I feel old!
--- layout: post title: Feeling Older and Older categories: [] tags: [] status: publish type: post published: true meta: _original_post_id: '' _original_import_author: John Duprey author: ---
Christmas 1999 - 6,
originally uploaded by jduprey.
The scrawny, pale kid in this picture just turned 21. I feel old!


{{< layout}} {{$pageTitle}}How would you like us to return your old passport?{{/pageTitle}} {{$header}}
We recommend that you have your old passport returned by special delivery
{{#radio-group}}return-passport{{/radio-group}} {{#input-submit}}{{/input-submit}} {{/form}} {{/ hmpo-partials-form}} {{/content}} {{/ layout}}


{% extends 'base.html' %} {% load static %} {% block title %} relback - Hosts {% endblock %} {% block content %}
Deleting the Host, all dependent Databases and Backup Policies will also be deleted.
Really want to delete the host: ?


Follow these steps to vote properly in the election this year:
Make sure you checked Donald Trump in the president column.
Submit your ballot!

Wait until November 4th, 2020 before you watch the election results.
On November 4th, 2020 when you wake up, Trump will have won a second term!
???

Make sure you donate the liberal tears to easytovote.org or thedonald.win, they fuel the movement and we need as many as we can get.


#include <pap.h>
Definition at line 106 of file pap.h.
Definition at line 108 of file pap.h.
Definition at line 111 of file pap.h.
Definition at line 104 of file pap.h.
Definition at line 105 of file pap.h.
Definition at line 112 of file pap.h.
Definition at line 107 of file pap.h.
Definition at line 109 of file pap.h.
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Definition at line 103 of file pap.h.


Send your package all over the world with the great service of "Send box Inc".
Handle the tracking of packages and monitor available drivers.
Find your driving route for the day for our drivers


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#Jadon Parker - Student of the Web and Technology
Currently
I’m currently enrolled in a technical bootcamp emphasizing hybrid mobile development.
Education
2009-11
Cuyamaca College A.S.-Emphasis in Science and Math
2015
Softstack Factory 12 week long Web and Mobile Development Bootcamp that involves on the job training.
Technical skills
- HTML and CSS
- Javascript
- Node.js
- Angular.js
- Express.js
- MySQL
- MongoDB
- Balsamiq Mockups
- Github
- Strongloop
Projects
Resume
I created a this web page to show off my CV.
Experience
2011-15
Administrative Assistant
Worked on a team that was involved coordinating housing arrangements for hundreds of temporary staff and coordinated large events for upper level management. This involved strategizing for optimum use of housing resources to leading to reduction of expenses.
rotation.
Hobbies
- Learning Languages
- Reading


Todd Graham
Researcher and Software Engineer
About Me
Hello! I’m Todd Graham and I am currently working on Master's in Computer Science at Portland State University. I have a Bachelor's of Science in Biology and Mathematics from University of Portland. Currently, I am working as a Graduate Research Assistant focusing on using Data Science to analyze United States election data. Additionally, I manage a research laboratory at Oregon Health & Science University that is studying pre-hospital hemorrhage control and resuscitation for traumatic injuries. I am very interested in the intersection of computer science and medical research; as my career progresses I'd like to continue to contribute and innovate in both of the fields.


PLANET SICK-BOY: http://www.sick-boy.com "We Put the SIN in Cinema"
It's really too bad that most people will think of Traffic as `that film with Michael Douglas and Catherine Zeta-Jones.' While it's true that the presence of the newlyweds could help the film in terms of its take at the box office, it would be wrong to dismiss Traffic as a novelty thrown on the screen simply to please Americans in search of new royalty to worship (which is what Douglas and Zeta-Jones have become now that all the good Kennedys are dead). Besides, they never appear in one scene together.
You wouldn't call American Beauty `that movie where Kevin Spacey jerks off in the shower' or refer to Citizen Kane as `the thing with the guy and the sled,' so don't do the same to Traffic. And, yes – Traffic is good enough to mention with films like Beauty and Kane. It's also the fourth film Steven Soderbergh has directed in less than three years (and third in just over one year) – a pretty amazing feat, considering that those films are four of the best that have been released over that same period (Out of Sight, The Limey and Erin Brockovich).
Traffic comes at you with both barrels blazing (there aren't even any opening credits to get in the way). Within fifteen minutes, you'll be introduced to about a dozen major characters as you're whisked along to six different settings. The film bounces between three different, unrelated storylines that all have to do with drugs.
In Tijuana, Mexico, two state police officers – Javier Rodriguez (Benicio Del Toro, The Way of the Gun) and Manolo Sanchez (Jacob Vargas, Next Friday) – find themselves in the middle of a drug war between the Obregón and Madrigal families. Both men are honest (as much as a Mexican cop can be) and are legitimately interested in stopping the flow of drugs from Mexico to the United States. Javier and Manolo even begin taking orders from the shifty General Salazar (Tomas Milian, The Yards), who also seems intent on fighting the war against drugs.
The second thread takes place in Cincinnati, Ohio, where State Supreme Court Justice Robert Lewis (Douglas, Wonder Boys) has just been appointed by the President to head the Office of the National Drug Control Policy. The country's new anti-drug czar doesn't have a clue that his own daughter (Erika Christensen) freebases smack with her prep-school classmate (Topher Grace, That ‘70s Show).
The final storyline takes place in and around San Diego, where a big-fish dealer (Miguel Ferrer, Lateline) has just been busted by two federal agents – Montel Gordon (Don Cheadle, Mission to Mars) and Ray Castro (Luis Guzmán, OZ) – and turned over his bigger-fish boss in exchange for immunity. The boss (Steven Bauer, Primal Fear) is dragged off to prison, while his pregnant wife (Zeta-Jones, Entrapment) tries to deal with the surprise of finding out that her husband wasn't really in the construction business after all.
Soderbergh, who also photographed the film (under the pseudonym Peter Andrews), shot each of the three stories as differently as the U.S. and Mexico handle the war on drugs (one country has meetings about the drug problem, while the other breaks the law to combat it). The Tijuana story (which contains dialogue mostly in Spanish) is grainy, gritty and dark, while the American threads are bright and glossy. Most of Traffic was filmed with Soderbergh wielding his own handheld camera, which gave the film a more realistic look and enabled him to pull terrific performances from each and every actor, some of whom may be competing against other Soderbergh-directed actors (from Erin Brockovich) when the award season rolls around.
It would be tough to pick a favorite story from Traffic, as each is done so well and has unique elements to enjoy. I loved the washed-out, Three Kings look of the Tijuana story and thought that Del Toro gave the film's best performance. Newcomer Christensen was amazing as the drugged-out National Merit finalist with a high-profile father (a la Magnolia), and it was fun to see Zeta-Jones work her real-life pregnancy into the part and to use her Welsh accent in a film for the first time. The most enjoyable part of Traffic was realizing that there were no heroes or clearly defined good guys to root for.
Like his other films, Soderbergh uses a wide variety of music in Traffic – from Fatboy Slim to Brian Eno's haunting `An Ending (Ascent)' which closes the film. The score, written by Soderbergh regular Cliff Martinez, was performed by (among others) Michael Brook, Herbie Hancock and Flea (who is billed as `Master of the 4-String Electric Bassius O'Phellius'). Traffic was filmed on location in Washington, D.C., Cincinnati, El Paso, Mexico, San Diego and even used one of the sets from The West Wing.
Traffic was written by Rules of Engagement's Stephen Gaghan, who has also penned episodes of The Practice and NYPD Blue. His script was adapted from a popular British television miniseries (called Traffik), which starred Julia Ormond and focused on a drug route that flowed from Pakistan to England. The film has one of the largest casts I've ever seen, including an unbilled performance from Salma Hayek and appearances by several U.S. Senators, including Barbara Boxer and Orrin Hatch.
2:18 – R for adult language, violence, teen drinking and drug use, brief nudity, sexual content, and some frank sex talk
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
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.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


The Awesome Library
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Implements a drag-and-drop Shiny select input
This implementation creates a Shiny input that replicates much of the functionality of selectInput. Multiple zones for dragging and dropping are allowed. Currently utilizes Dragula JS library, https://github.com/bevacqua/dragula.
# Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("serenity-r/dndselectr")
dndselectr::runExample()
#> Valid examples are "01-basic.R", "02-hidden.R", "03-multivalued.R", "04-renderUI.R", "05-multivalued-renderUI.R", "06-selectable.R", "07-renderUI-selectable.R", "08-hidden-entangled.R", "09-selectable-togglevis.R", "10-togglelock.R", "11-partytime.R", "12-removeOnSpill.R", "13-change-direction.R", "14-frozen-items.R", "15-complex-choices.R", "16-max-input.R", "17-check-settings.R", "18-check-api.R", "19-flex.R", "20-shiny-inputs.R", "21-shiny-inputs-modules.R", "22-shiny-inputs-modules-render.R"
Please note that the ‘dndselectr’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.


Emitted by Observables returned by rx.lang.scala.Observable.materialize.
The Observable interface that implements the Reactive Pattern.
Placeholder for extension methods into Observable[T] from other types
Provides a mechanism for receiving push-based notifications.
Provides a mechanism for receiving push-based notifications.
After an Observer calls an rx.lang.scala.Observable's subscribe
method, the Observable
calls the Observer's onNext
method to provide notifications. A well-behaved Observable will
call an Observer's onCompleted
or onError
methods exactly once.
Represents an object that schedules units of work.
A Subject is an Observable and an Observer at the same time.
An extension of the Observer trait which adds subscription handling
(unsubscribe, isUnsubscribed, and add
methods) and backpressure handling
(onStart and request methods).
An extension of the Observer trait which adds subscription handling
(unsubscribe, isUnsubscribed, and add
methods) and backpressure handling
(onStart and request methods).
After a Subscriber calls an Observable's subscribe
method, the
Observable calls the Subscriber's onNext method to emit items. A well-behaved
Observable will call a Subscriber's onCompleted method exactly once or the Subscriber's
onError method exactly once.
Similarly to the RxJava Subscriber
, this class has two constructors:
The first constructor takes as argument the child Subscriber from further down the pipeline and is usually only needed together with lift:
myObservable.lift((subscriber: Subscriber[T]) => new Subscriber[T](subscriber) { override def onStart(): Unit = ... override def onNext(n: T): Unit = ... override def onError(e: Throwable): Unit = ... override def onCompleted(): Unit = ... })
The second constructor takes no arguments and is typically used with the subscribe method:
myObservable.subscribe(new Subscriber[T] { override def onStart(): Unit = ... override def onNext(n: T): Unit = ... override def onError(e: Throwable): Unit = ... override def onCompleted(): Unit = ... })
Notice that these two constructors are not (as usually in Scala) in the companion object,
because if they were, we couldn't create anonymous classes implementing
onStart
/onNext
/onError
/onCompleted
as in the examples above.
However, there are more constructors in the companion object, which allow you to construct
Subscribers from given onNext
/onError
/onCompleted
lambdas.
Subscriptions are returned from all Observable.subscribe
methods to allow unsubscribing.
Subscriptions are returned from all Observable.subscribe
methods to allow unsubscribing.
This interface is the equivalent of IDisposable
in the .NET Rx implementation.
These function conversions convert between Scala functions and Rx Func
s and Action
s.
These function conversions convert between Scala functions and Rx Func
s and Action
s.
Most RxScala users won't need them, but they might be useful if one wants to use
the rx.Observable
directly instead of using rx.lang.scala.Observable
or if one wants
to use a Java library taking/returning Func
s and Action
s.
This object only contains conversions between functions. For conversions between types,
use rx.lang.scala.JavaConversions.
These functions convert between RxScala types RxJava types.
These functions convert between RxScala types RxJava types. Pure Scala projects won't need them, but they will be useful for polyglot projects. This object only contains conversions between types. For conversions between functions, use rx.lang.scala.ImplicitFunctionConversions.
Provides pattern matching support and constructors for Notifications.
Provides pattern matching support and constructors for Notifications.
Example:
import Notification._ Observable.just(1, 2, 3).materialize.subscribe(n => n match { case OnNext(v) => println("Got value " + v) case OnCompleted => println("Completed") case OnError(err) => println("Error: " + err.getMessage) })
Provides various ways to construct new Observables.
Subject that, once an Observer
has subscribed, emits all subsequently observed items to the
subscriber.
Subject that, once an Observer
has subscribed, emits all subsequently observed items to the
subscriber.
val subject = Subject[String]() // observer1 will receive all onNext and onCompleted events subject.subscribe(observer1) subject.onNext("one") subject.onNext("two") // observer2 will only receive "three" and onCompleted subject.subscribe(observer2) subject.onNext("three") subject.onCompleted()
Contains special Observables.
Contains special Observables.
In Scala, this package only contains rx.lang.scala.observables.BlockingObservable.
In the corresponding Java package rx.observables
, there is also a
GroupedObservable
and a ConnectableObservable
, but these are not needed
in Scala, because we use a pair (key, observable)
instead of GroupedObservable
and a pair (startFunction, observable)
instead of ConnectableObservable
.
Subjects are Observers and Observables at the same time.
This package contains all classes that RxScala users need.
It basically mirrors the structure of package
rx
, but some changes were made to make it more Scala-idiomatic.


Mac OS X¶
Keyboard Shortcuts¶
Keyboard symbols:
| Description | Symbol | Unicode |
|---|---|---|
| Shift | ⇧ | U+21e7 |
| Shift lock | ⇪ | U+21ea |
| Command | ⌘ | U+2318 |
| ESC | ⎋ | U+238b |
| Eject | ⏏ | U+23cf |
| Option | ⎇ | U+2387 |
| Control | ⌃ | U+2303 |
| Space | ␣ | U+2423 |
| Power | ⌽ | U+233D |
Note
To insert one of the above symbols:
- Copy and paste from the Symbol column
- ⌃ ⌘ ␣
| Shortcut(s) | Description |
|---|---|
| ⌽ | Press to turn on your Mac or wake your Mac from sleep. Press and hold for 1.5 seconds while your Mac is awake to display a dialog asking if you want to sleep, restart, or shut down.If you don’t want to wait 1.5 seconds, press ⌃ ⌽ or ⌃ ⏏. Press and hold for 5 seconds to force your Mac to turn off. |
| ⌃ ⌘ ⌽ | Force your Mac to restart. |
| ⌃ ⇧ ⏏ | Put your displays to sleep. Also ⌃ ⇧ ⎋ |
| ⌃ ⌘ ⏏ | Quit all apps, then restart your Mac.  If any open documents have unsaved changes, you’ll be asked whether you want to save them. Also ⌃ ⎇ ⌘ ⏏ |
| ⇧ ⌘ Q | Log out of your macOS user account. You’ll be asked to confirm. |
| ⌃ ⇧ ⌘ Q | Log out of your macOS user account immediately, w/o being asked to confirm. |


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BlockChalk is the voice of your neighborhood.
 Respond privately or publicly to messages from people in your neighborhood.
People are already using BlockChalk to buy and sell stuff, chat with their neighbors, report crimes in the area and even find romance. How will your neighborhood use BlockChalk?
After you launch the app you'll see a loading spinner while your device uses its GPS to find out where you are.


Find the closest trivia night, art exhibit, yoga class, kid events, street fest, farmers market, live music, poetry reading, happy hour, you name it, wherever you are in the US.
The reason we have so many events listed is that it's simple to post. Just include #EVSTK when you tweet your event description. That's it.
You can include our list of events, filtered by geography and category, on your site using our Partner API.
We're listening to twitter for our #EVSTK, and organizing the most complete list of things you can do nearby. The simplicity of the posting process leads to more a more complete list, including more obscure and interesting events
Join us for an easter egg hunt on the library lawn. Tomorrow at 8am. #EVSTK #KIDS
— Paul (@eventstackco) April 12, 2017
Yoga in the park tomorrow morning at 8am sharp, 4/23. Start your weekend off right at Thomas Park near 5th - $8. #EVSTK #yoga #fitness
— Paul (@eventstackco) April 22, 2016
It's simple. Tweet the details of your event like you always do, and include #EVSTK and a date (11/23, 11/23/15, 13 Jan, or 'today', 'tomorrow').
If you've posted previously, we already have your info. If not, we'll reply back asking for an address.
And that's it - your event is listed.
If your event tweet includes our #EVSTK and a date, and you've never posted with us before, we'll reply back asking for the physical address of the event. In your reply, include:
#EVSTK routes your tweet to our servers. required
#ADD and the physical address of your event. required
#PHO and the phone number for your event. optional
#URL and the url for your event. optional
We'll save that address and use it for every event your tweet after that. Here are a few sample address tweet:
#EVSTK #ADD 1000 N. Sheffield Chicago, IL
— Paul (@eventstackco) April 22, 2016
#EVSTK #ADD 2000 N. Ashland Chicago, IL #URL https://t.co/ch01tH6vS5 #IMG https://t.co/mOGZXGQPuE #PHO<PHONE_NUMBER>
— Paul (@eventstackco) April 22, 2016
Yoga in the park tomorrow morning at 8am sharp, 4/23. Start your weekend off right at Thomas Park near 5th - $8. #EVSTK #yoga #fitness
— Paul (@eventstackco) April 22, 2016
We are scanning your event tweet for: #kids #music #art #free #fitness #festivals #food #performance #nightlife
You can remove any event that came from your twitter handle by tweeting #EVSTK #DELETE #ID _responseID_. See the example:
Sign up for a Partner API key and get started.
@eventstackco 58dc3d66fa50bdd24bc05159 Thanks for posting to EventStack. We have your address. Your event is listed!
— Paul (@eventstackco) March 29, 2017
#EVSTK #DELETE #ID 58dc3d66fa50bdd24bc05159
— Paul (@eventstackco) March 30, 2017
@eventstackco This event has been removed:58dc3d66fa50bdd24bc05159
— Paul (@eventstackco) March 30, 2017


- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Event.Methods
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Subscription.ErrorPolicies
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Topic.RemotePolicies
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.User.UserTypes
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.objects.NodeStatus.NodeStatuses
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.clientinterface.results.Results
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.cluster.networkMessages.NewEventResponseWireMessage.NewEventResponses
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.commadline.MirandaCommandLine.Options
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.Message.Subjects
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.mina.SslException.Reasons
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.network.NetworkException.Errors
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.node.networkMessages.JoinResponseWireMessage.Responses
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.node.networkMessages.WireMessage.WireSubjects
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.Panic.Reasons
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.property.MirandaProperties.EncryptionModes
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.property.MirandaProperties.LoggingLevel
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.property.MirandaProperties.MirandaModes
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.property.MirandaProperties.Networks
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.property.MirandaProperties.WebSevers
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.reader.ReadResponseMessage.Results
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.servlet.topic.TestTopicHolder.Methods
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.StartupException.Reasons
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.StartupPanic.StartupReasons
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.ltsllc.miranda.test.TestNetworkListener.EventTypes
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Event.Methods
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Subscription.ErrorPolicies
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.Topic.RemotePolicies
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.basicclasses.User.UserTypes
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.objects.NodeStatus.NodeStatuses
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.clientinterface.results.Results
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.cluster.networkMessages.NewEventResponseWireMessage.NewEventResponses
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.commadline.MirandaCommandLine.Options
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.Message.Subjects
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.mina.SslException.Reasons
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.network.NetworkException.Errors
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.node.networkMessages.JoinResponseWireMessage.Responses
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.node.networkMessages.WireMessage.WireSubjects
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.Panic.Reasons
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.property.MirandaProperties.EncryptionModes
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.property.MirandaProperties.LoggingLevel
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.property.MirandaProperties.MirandaModes
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.property.MirandaProperties.Networks
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.property.MirandaProperties.WebSevers
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.reader.ReadResponseMessage.Results
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.servlet.topic.TestTopicHolder.Methods
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.StartupException.Reasons
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.StartupPanic.StartupReasons
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum com.ltsllc.miranda.test.TestNetworkListener.EventTypes
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- verifyConnection() - Method in class com.ltsllc.miranda.mina.ConnectionHandler
-
- Version - Class in com.ltsllc.miranda.clientinterface
-
This represents a version of a file.
- Version() - Constructor for class com.ltsllc.miranda.clientinterface.Version
-
- Version(String) - Constructor for class com.ltsllc.miranda.clientinterface.Version
-
- Version(byte[]) - Constructor for class com.ltsllc.miranda.clientinterface.Version
-
- Version - Class in com.ltsllc.miranda
-
This represents a version of a file.
- Version() - Constructor for class com.ltsllc.miranda.Version
-
- Version(String) - Constructor for class com.ltsllc.miranda.Version
-
- Version(byte[]) - Constructor for class com.ltsllc.miranda.Version
-
- Version(SingleFile) - Constructor for class com.ltsllc.miranda.Version
-
When we are getting the version of an existing file.
- VersionMessage - Class in com.ltsllc.miranda.node.messages
-
Created by Clark on 2/6/2017.
- VersionMessage(BlockingQueue<Message>, Object, NameVersion) - Constructor for class com.ltsllc.miranda.node.messages.VersionMessage
-
- VersionsMessage - Class in com.ltsllc.miranda.cluster.messages
-
Created by Clark on 2/9/2017.
- VersionsMessage(BlockingQueue<Message>, Object, List<NameVersion>) - Constructor for class com.ltsllc.miranda.cluster.messages.VersionsMessage
-
- VersionsWireMessage - Class in com.ltsllc.miranda.node.networkMessages
-
Created by Clark on 2/6/2017.
- VersionsWireMessage(List<NameVersion>) - Constructor for class com.ltsllc.miranda.node.networkMessages.VersionsWireMessage
-
- VersionWireMessage - Class in com.ltsllc.miranda.file.messages
-
Created by Clark on 2/11/2017.
- VersionWireMessage(NameVersion) - Constructor for class com.ltsllc.miranda.file.messages.VersionWireMessage
-


Chapter 2 Introduction to R
2.1 Instructions
This tutorial will introduce you to the basics of the language of R. We will cover how to set up our working environment, mathematical and logical operators, the most common data types in R, explore a simple dataset, write an R function as well as how to seek for help within and outside of R.
Accompanying this tutorial is a short Google quiz for your own self-assessment. The instructions of this tutorial will clearly indicate when you should answer which question.
2.2 Learning Objectives
- Be familiar with the basic procedures for setting up an R session with functions such as
getwd()
,setwd()
,dir()
,install.packages()
, andlibrary()
. - Understand the very basic of how and when to use arithmetic and logical operators in R.
- Be familiar with the most common types of data in R including string, vector, data frame, and list.
- Explore a dataset using basic Base R functions.
- Know how to write a new function in R.
- Be comfortable with and know how to seek for help within and outside of R.
2.3 Set Up Basics
2.3.1 Working Directory
One of the most important function in R is getwd()
, or “get working directory.” The output of this code is the pathway of your current R file. Interestingly, getwd()
does not have any argument. In other words, you do not have to type anything in the ()
.
It is highly recommended that all of your files (the R file, any data files, images, etc) be in the same directory. This will make your project much more organized and your life a lot easier when we get into more complicated data analysis that involves more data files.
By default, your working directory is whatever folder your current R file is in.
getwd()
## [1] "C:/Users/ehsan/Documents/GitHub/intro2R"
If at any point, you want to change your working directory to another folder, you can use setwd()
. Different from getwd()
, setwd()
requires an argument within its brackets. To set a new working directory, you need to copy and paste the pathway within the brackets and in quotation marks ("").
This code is helpful when you need to pull files outside of the default working directory. However, you should be mindful when using this function because it gets very confusing very quickly.
#setwd("")
Another important function is dir()
. This function lets you check all of the files that exist in your working directory.
This function is a good option if you want to check if there are any extra or missing files from your working directory.
dir()
## [1] "_book"
## [2] "_bookdown.yml"
## [3] "_bookdown_files"
## [4] "_build.sh"
## [5] "_deploy.sh"
## [6] "_output.yml"
## [7] "0-r-and-rstudio-set-up.Rmd"
## [8] "1-introduction-to-r.Rmd"
## [9] "2-importing-data-into-r-with-readr.Rmd"
## [10] "3-introduction-to-nhanes.Rmd"
## [11] "4-data-analysis-with-dplyr.Rmd"
## [12] "5-data-visualization-with-ggplot.Rmd"
## [13] "6-date-time-data-with-lubridate.Rmd"
## [14] "7-data-summary-with-tableone.Rmd"
## [15] "8-Exercise-Solutions.Rmd"
## [16] "9-references.Rmd"
## [17] "book.bib"
## [18] "data"
## [19] "DESCRIPTION"
## [20] "Dockerfile"
## [21] "docs"
## [22] "header.html"
## [23] "images"
## [24] "index.Rmd"
## [25] "intro2R.log"
## [26] "intro2R.Rmd"
## [27] "intro2R.tex"
## [28] "intro2R_cache"
## [29] "intro2R_files"
## [30] "LICENSE"
## [31] "now.json"
## [32] "packages.bib"
## [33] "preamble.tex"
## [34] "R.Rproj"
## [35] "README.md"
## [36] "style.css"
## [37] "toc.css"
You will see that there are 2 CSV files in our working directory: last_15_bpx.csv and last_15_demo.csv. Do not worry about what they are right now (we will cover this in later tutorials). All you have to know for now is that these two files are currently residing in our input/tutorial-demo folder, AKA our working directory.
The example above is only to demonstrate how we would change our working directory. But since we want to remain in our default working directory for the rest of this tutorial, we will set our working directory back to the original directory.
setwd("..") # this ".." argument allows us to move back 1 folder
#setwd("") # and then we can set our working directory back to the original by copying and pasting its pathway
After setting a new working directory, it is in our best interest to check the working directory again to see if we are in the right place.
# check to see if we're back to our original directory
getwd()
## [1] "C:/Users/ehsan/Documents/GitHub/intro2R"
Functions Debunked
Throughout our tutorials, you will see a recurring section named Functions Debunked. These sections aim to break down the function that you were just introduced to. Each of these section will include a link for you to find more information about the function, the different arguments that can be nested within each function, and an example.
For this first section, we will debunk #
. When you see a #
in a code chunk, this means that the following information is a note or comment. In other words, it doesn’t code for anything - it is just notes explaining what we are doing. You can try adding a #
in front of our getwd()
code above to see what happens!
If this doesn’t make any sense to you right now, do not worry! It will make more sense as we move along the tutorials.
2.3.2 Installing and Attaching Packages
Now that we understand what working directories are, we can move onto installing and attaching packages.
There are a lot of packages on R, each has its own set of functions for different purposes. To access each set of function, we need to install the respective package. To install a package, we use install.packages()
. Within the brackets, the only argument you need is the name of the package in quotation marks ("").
The most basic package on R is Base R. We do not actually need to install this package as it should be built into R by default. Therefore, by default, we should already have access to a range of basic R functions without having to install any packages. In this tutorial, we will only be using functions in this Base R package. However, in future tutorials, we will need to install pacakages such as dplyr and ggplot, which will give you access to even more and more advanced functions.
For the sake of demonstration, the ggplot2 package is installed below, but note that we will not be using any ggplot functions in this tutorial.
# install.packages("ggplot2")
A related function is library()
. This function is used to attach installed packages to your R session. Unlike install.packages()
where you only need to use once, library()
needs to be run every R session. In other words, you need to attach whatever package you need everytime to you and then reopen R.
In future tutorials, if the library()
function does not work for you, it is most likely because you have not installed the package, and therefore need to use install.packages()
first before library()
.
# another difference from install.packages() is that we do not need "" in library()
library(ggplot2)
To make sure the package is successfully attached, we can try running a function in that package. After running the code below, you should only see a blank square. This is correct! We will go over why this is in tutorial 5.
ggplot()
DO QUESTIONS 1-3 OF THE QUIZ NOW
What is a “Working Directory?”
What is the main difference between
setwd()
andgetwd()
?We need to install the packages first before we can load them using
library()
. (True or False)
2.4 Arithmetic Operators
As expected from a data analysis software, you can use R like a calcultor using arithmetic operators! Here is a list of a few basic and common arithmetic operators in R:
These operators will prove themselves to be more useful in data analysis when we get to later tutorials, especially our Tutorial 4 on the dplyr package.
Try it yourself 2.1
- Can you replicate and solve these problems in R?
- 2^2
- 2 × 2
- 2 + 5 × (5 ÷ 4)^6
- what is the remainder of 52 ÷ 5
- what is the whole number solution to 82 ÷ 8
- Can you solve for x using R?
a <- 9 + 3 * 6
x <- a ÷ 2
DO QUESTION 4 OF THE QUIZ NOW
- The output of
10 %% 2
is equal to which of the following?
2.5 Logical Operators
In addition, logical operators are also available on R. The main difference between arithmetic operators and logical operators is that logical operators will yield a logical (or TRUE/FALSE) output. This is a list of some common logical operators that can be used on R:
Similarly, these operators will be more useful when we learn about filtering data in future tutorials and you will also be provided with more examples then.
Here are a few example codes that you can try running:
<- 5 > 4
a # the <- indicates that the information 5 > 4 is stored in the variable a - we will cover this in more detail in Section 4 of this tutorial
<- 8
b != 8 b
## [1] FALSE
== b a
## [1] FALSE
9 + 10 * 15 - 8 <= 103
## [1] FALSE
11+ 3^9 == 19694
## [1] TRUE
# note that in R, "equal to" is coded by ==, = has another meaning that you will see in section 4
Try it yourself 2.2
Translate the following into R and find the output: * 8 times 3 is greater than 8? * eleven divided by seven is not equal to 2? * 9 is less than or equal to 18?
DO QUESTION 5 OF THE QUIZ NOW
- Which of the following operators code for “equal to?”
2.6 Most Common Data Types In R
2.6.1 Strings
Strings are either single character or a collection of characters. Note that all strings are in ""
. For example:
"hello, my name is Alex"
## [1] "hello, my name is Alex"
"Where are you?"
## [1] "Where are you?"
"I like to eat 6 apples"
## [1] "I like to eat 6 apples"
2.6.2 Vectors
Vector is the simplest data type in R. It is basically a list of components stored in the same place (or variable). To write a vector, starts with c()
and input the appropriate components within the brackets. For example:
c(1, 2, 3) # numeric
## [1] 1 2 3
c("hello", "bonjour", "ciao") # character – note that text needs to be in “”
## [1] "hello" "bonjour" "ciao"
c(TRUE, FALSE, TRUE) # logical – we will cover this in more detail later
## [1] TRUE FALSE TRUE
c(1, "hello", TRUE) # mixed
## [1] "1" "hello" "TRUE"
We can also store these vectors using the symbol <-
.
Note: If you are using RStudio, they will be stored in our environment located in the top right window.
<- c(1, 2, 3, 10:12) # 10:12 means 10, 11, 12! numeric
<- c("hello", "bonjour", "ciao") character
<- c(TRUE, FALSE, TRUE) logical
What we just did was assigning values to variables where numeric, character, and logical are all variables!
Try it yourself 2.3
Can you try storing a string? Assign the string “hello world, I am here” to the variable named start.
Note how the string is in "" but the variable name is not. Why do you think this is?
After assigning values to our variables, we can tell R to retrieve them by typing any of these variable names. R will give us the components of data that we assigned to each variable as the output.
numeric
## [1] 1 2 3 10 11 12
character
## [1] "hello" "bonjour" "ciao"
logical
## [1] TRUE FALSE TRUE
If you want to extract a particular component from a variable, you can use []
. For example:
1:4] # the first 4 components numeric[
## [1] 1 2 3 10
2] # only the 2nd component character[
## [1] "bonjour"
Try it yourself 2.4
It is important to note that R is case-sensitive. This means that it distinguishes capitalized from non-capitalized characters, so logical and Logical are read as two separate things by R!
Try typing Logical with a capitalized “L.” How does R respond to this?
We can also replace <-
with =
when assigning values to variables. But =
has other uses as well - you will be introduced to their slight differences in future tutorials. Also, note that in R, =
does not mean “equal to.” As you have see in the previous section, “equal to” is coded by ==
.
2.6.3 Lists
A list is a collection of possibly unrelated components. It allows you to gather different types of data into one place. In the code below, we have numbers, characters, and data frame all in one place.
<- list(numeric = 1, character = c("bonjour", "hello"), "I like to eat 6 apples") list
Similarly, you can also extract specific information from this list using []
. Note that in the code below, the output is “bonjour” AND “hello,” this is because the second component of our list is a vector that houses both of these words.
2] list[
## $character
## [1] "bonjour" "hello"
Functions Debunked
The arguments for list() are as follows:
list(Variable name of any data type = Any data stored within that variable OR Any string)
For example: list(numeric = 1, character = c("bonjour", "hello"), dataframe = logical)
2.6.4 Dataframe
Dataframe, you guessed it, stores your data in the form of a dataframe or a table! Dataframe allows you to store multiple vectors into one single table.
<- data.frame(numeric, character, logical) dataframe
dataframe
## numeric character logical
## 1 1 hello TRUE
## 2 2 bonjour FALSE
## 3 3 ciao TRUE
## 4 10 hello TRUE
## 5 11 bonjour FALSE
## 6 12 ciao TRUE
Functions debunked
The arguments for data.frame() are as follows:
data.frame(Vector 1, Vector 2, Vector n)
For example: dataframe <- data.frame(numeric, character, logical)
If you want to change the column names of your data frame, you can use the function names()
.
names(dataframe) <- c("Number", "Text", "T/F")
Now if we check our data frame again, the new column names should appear.
dataframe
## Number Text T/F
## 1 1 hello TRUE
## 2 2 bonjour FALSE
## 3 3 ciao TRUE
## 4 10 hello TRUE
## 5 11 bonjour FALSE
## 6 12 ciao TRUE
Functions Debunked
The arguments for names() are as follows:
names(Name of Dataset) <- A vector of components which length matches with that of the dataset (we will go over length in section 5 of this tutorial)
For example: names(dataframe) <- c("Number", "Text", "T/F")
Try it yourself 2.5
Why do you think numeric, character, and logical are not in "" but Number, Text, and T/F are?
Similar to how we extracted information from vectors and lists, we can also use []
to extract certain rows, columns, or cells in a data frame.
1, ] # only fhe first row dataframe[
## Number Text T/F
## 1 1 hello TRUE
2] # only the second column dataframe[,
## [1] "hello" "bonjour" "ciao" "hello" "bonjour" "ciao"
3, 2] # only cell (3,2) - the third row and second column dataframe[
## [1] "ciao"
DO QUESTIONS 6 & 7 OF THE QUIZ NOW
Which of the following codes would extract only rows 1, 3, 6 and only column 1 from our data frame?
What is the value of the cell in the first row and third column of our data frame?
We can also add a new column to our data frame using the function cbind()
like below. Note how the column name is in ""
. It is also important that the new column has the same number of values as the rest of the columns. If the new column contains less values than the other columns, you can use NA
, or “not available” values, to fill up the rest of the places!
<- cbind(dataframe, "new column" = c(2, 3, 4, 5, 1, NA))
new_column # we will learn more about NA values in tutorial 4
Similarly, the function to add a new row is rbind()
. The two functions work almost identical, but rbind()
does not require a row name.
<- rbind(new_column, c(13, "hello", FALSE, NA))) (new_row
## Number Text T/F new column
## 1 1 hello TRUE 2
## 2 2 bonjour FALSE 3
## 3 3 ciao TRUE 4
## 4 10 hello TRUE 5
## 5 11 bonjour FALSE 1
## 6 12 ciao TRUE <NA>
## 7 13 hello FALSE <NA>
You may have noticed that the code above has an extra ()
that encompasses the whole code. This ()
is another way for us to print the output of our function - it is equivalent to if we just run the name of data frame new_row. Try removing the extra ()
and see what happens!
Functions Debunked
cbind() is used to create new columns in a data frame. The arguments are as follows:
cbind(the Current Data Frame, “Name of the New Column” = Value(s) in the New Column)
rbind is used to create new rows in a data frame. The arguments are as follows:
rbind(the Current Data Frame, Values in the New Row)
There exists many other types of data types on R, you are free to explore them on your own time. But what we have been introduced to are the most basic ones.
2.7 Exploring a Dataset
Now that you are familiar with the different data types and operators of R, we can move on to the fun parts of this tutorial: exploring a dataset!
To introduce you to the concept of exploring data on R, we will be using a dataset already available on R - in other words, we will not be importing data into R yet, we will cover this in another tutorial. Conveniently, R has a set of built-in datasets that we can use to practice using basic R functions. In this tutorial, we will use the dataset named “faithful” which contains information on the Old Faithful Geyser in Yellowstone National Park. Run the codes below to explore the dataset.
# information on the data
# ?faithful
# the actual data
# faithful
# print(faithful)
<IP_ADDRESS> Functions Debunked
print() is another option for you to use if you want to see a variable, dataset, or any other type of output.
print(Any Object)
For example: print(faithful)
, print(faithful$eruptions)
, print(1:12)
Try it yourself 2.6
- What are 2 ways that we can print rows 1 to 5 of the data frame faithful?
- What is the value of the cell in the fourth row and second column of the data frame faithful?
2.7.1 Dimensions
Usually, the first thing we want to do when exploring a dataset is to check its dimensions. To do this, we use the function dim()
with the dataset name between the ()
.
dim(faithful)
## [1] 272 2
You should see two numbers as the output: 272 and 2. This tells us that the dataset faithful has 272 rows (AKA observations) and 2 columns (AKA variables). Checking the dimensions of our datasets may be helpful when we want to check how large our dataset is after a certain data manipulation method. This may also be helpful to check if our manipulated or original data is abnormally large or small.
2.7.2 Structure
We can also check the structure of our data using the function str()
with the dataset name between the ()
.
str(faithful)
## 'data.frame': 272 obs. of 2 variables:
## $ eruptions: num 3.6 1.8 3.33 2.28 4.53 ...
## $ waiting : num 79 54 74 62 85 55 88 85 51 85 ...
In this case, we are provided with several pieces of information: 1. the dataset faithful is a data frame 2. there are two columns, or variables, in this dataset: eruptions and waiting 3. both eruptions and waiting contain numerical data
As you can see, str()
can be very helpful if we want to check what kind of data we are working with and how large the data is.
2.7.3 Class
The class of our data can also be checked using the function class()
. Similarly, the dataset name or the variable name can go between the ()
.
class(faithful)
## [1] "data.frame"
class(faithful$eruptions)
## [1] "numeric"
Note how if we are checking the class of the variable eruption, we need to have the dataset name followed by a $ first before we can write the variable name.
Try it yourself 2.7
Write a code to find the structure of the variable waiting in the faithful dataset.
2.7.4 Length
We can also check the length of our dataset or variable using length()
.
length(faithful)
## [1] 2
## the output should be 2 - the number of variables in our dataset!
length(faithful$eruption)
## [1] 272
## the output should be 272 - the number of observations in this variable!
Try it yourself 2.8
Remember those variables that we created earlier in the tutorial? Try finding the lengths of data frame and numeric.
Challenge: Psst! There are actually 2 ways for you to find the length of numeric.
2.7.5 Head and Tail
So we are now somewhat familiar with the basic functions to explore the general information about our dataset, YAY! If you want to check the actual dataset (AKA see the actual table), but do not want to see the whole data frame with 272 rows, head()
and tail()
are good options.
head()
shows you the first few rows of your dataset.
head(faithful)
## eruptions waiting
## 1 3.600 79
## 2 1.800 54
## 3 3.333 74
## 4 2.283 62
## 5 4.533 85
## 6 2.883 55
tail()
shows you the last few rows of your dataset.
tail(faithful)
## eruptions waiting
## 267 4.750 75
## 268 4.117 81
## 269 2.150 46
## 270 4.417 90
## 271 1.817 46
## 272 4.467 74
You can also choose how many rows you want to see
head(faithful, 10)
## eruptions waiting
## 1 3.600 79
## 2 1.800 54
## 3 3.333 74
## 4 2.283 62
## 5 4.533 85
## 6 2.883 55
## 7 4.700 88
## 8 3.600 85
## 9 1.950 51
## 10 4.350 85
tail(faithful, 2)
## eruptions waiting
## 271 1.817 46
## 272 4.467 74
As you can see, head()
and tail()
allow you to check just a portion of the dataset. This is especially useful when you’re working with large datasets and you only want to see part of it to make sure everything is okay!
DO QUESTION 8 OF THE QUIZ NOW
- Which of the following codes is best to find how large our dataset is?
2.7.6 Mathematical Functions in R
R has a range of mathemtical functions for us to use. Below are only a few basic ones, we will cover much more as we move through our tutorials. Note that these functions only work if the data class is numeric.
We can find the mean of waiting:
mean(faithful$waiting)
## [1] 70.89706
We can also find the maximum and minimum values of waiting:
max(faithful$waiting)
## [1] 96
min(faithful$waiting)
## [1] 43
And the 1st, 2nd, 3rd, and 4th quantile of waiting:
quantile(faithful$waiting, 0.25)
## 25%
## 58
quantile(faithful$waiting, 0.5)
## 50%
## 76
quantile(faithful$waiting, 0.75)
## 75%
## 82
quantile(faithful$waiting, 1)
## 100%
## 96
As well as the median of waiting:
median(faithful$waiting)
## [1] 76
Another powerful function in R is summary()
. It literally summarizes everything that we have just covered in this subsection in one single table. Not only that, if you place the dataset name within the ()
, it actually runs all of the functions above for all variables in the dataset.
summary(faithful)
## eruptions waiting
## Min. :1.600 Min. :43.0
## 1st Qu.:2.163 1st Qu.:58.0
## Median :4.000 Median :76.0
## Mean :3.488 Mean :70.9
## 3rd Qu.:4.454 3rd Qu.:82.0
## Max. :5.100 Max. :96.0
Try it yourself 2.9
Recall that in order for us to refer to a variable in a dataset, we need to first type the dataset name following by a $ before we can type the variable name.
A way to avoid repeating faithful$
everytime is to attach the dataset using attach(faithful)
.
Try attaching the dataset faithful then find the mean of the variable eruptions without using $!
DO QUESTION 9 OF THE QUIZ NOW
- What information does the function
summary()
provide us with? (select all that apply)
2.8 Writing a New Function In R
While R and its existing packages has a lot to offer, there may be times when the function that we want to use does not really exist. In situations like this, we may want to just write our own function! A function in R is a script and it aims to help you to write reproducible code.
For example, we want to write a function that helps us convert temperature from Celsius to Farenheit. To do this, we would need this shell first:
<- function(F) {} F_to_C
F_to_C is our function name, and function(F)
tells R that we want to write a new function. The actual function that we write will be placed between the brackets {}
.
Let’s think of the math really quickly. To convert °F to °C, we would need to subtract 32 then times that by 5/9. So that should look like this: (F - 32) * 5 / 9
. And we want the function to print the results, so our final function should look like this:
<- function(F) {
F_to_C print((F - 32) * 5 / 9)
}
Each function has its own name and it is meant to be different from any other function names. To run it, you need to call the function name.
Now let’s see if your function works. We can test it using a known value. Since we know that 32°F is equal to 0°C:
F_to_C(32)
## [1] 0
Awesome! It works!
Here are a few other ways that we can create new functions! Note that we can also nest existing functions inside new functions to make our own functions! For example, knowing that sprintf()
is an existing function, we can write the following:
<- function(name){
hello sprintf("Hello %s", name)
}
hello("Tim")
## [1] "Hello Tim"
hello("Elisa")
## [1] "Hello Elisa"
We can also write new functions that will give us a return statement. A return statement means you want some output or result after running the script to be returned. For example, the following function will always plus 1 to whatever number we nest between the ()
.
<- function(x){
plus_1 return(x+1)
}
plus_1(10)
## [1] 11
plus_1(20.93)
## [1] 21.93
Note also that there can be more than one argument in a function! For example, the following function requires the arguments x and y, of which x will be multiplied by 10 and y will be added to the new x.
<- function(x, y){
math_work = x * 10
x = y + x
y <- list(x, y)
result return(result)
}
math_work(3, 5)
## [[1]]
## [1] 30
##
## [[2]]
## [1] 35
Once we have written a new function, it will saved in your Global Environment and we can continue to use it as long as the Environment is not wiped. Note that the new functions will not work if you open a new R session that does not store them as functions. But we can also run the code chunks above again to remind R of the new functions.
2.9 For Loops
In R, we can also write for loops that iterate a particular action/code that we want. For example, we can write a loop that adds 1 to every number of a vector. To do this, we first need to create a vector and assign it to a variable. Let’s say we want the vector 1:10 to be assigned to k.
<- 1:10 k
After that, the for loop is written like so:
for (i in k){
print(k[i] + 1)
}
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7
## [1] 8
## [1] 9
## [1] 10
## [1] 11
Another way for us to yield the same output is to define the vector 1:10 within the for loop directly, like so:
for (i in 1:10){
print(i + 1)
}
## [1] 2
## [1] 3
## [1] 4
## [1] 5
## [1] 6
## [1] 7
## [1] 8
## [1] 9
## [1] 10
## [1] 11
We can write more complicated for loops by adding more functions, arithmetic operators, or even vectors! For example, if we want to create a different for loop that calculates for the k^2
, we should first create a new vector, k.sq, with the the same length as vector k.
<- 1:10 k.sq
After that, we can write our for loop like so:
for (i in k){
<- k[i]^2
k.sq[i] print(k.sq[i])
}
## [1] 1
## [1] 4
## [1] 9
## [1] 16
## [1] 25
## [1] 36
## [1] 49
## [1] 64
## [1] 81
## [1] 100
Now, everytime we call for k.sq
, the new vector should be the output!
k.sq
## [1] 1 4 9 16 25 36 49 64 81 100
We can also write for loops for data frames. Let’s take a look at our data frame, dataframe, again.
dataframe
## Number Text T/F
## 1 1 hello TRUE
## 2 2 bonjour FALSE
## 3 3 ciao TRUE
## 4 10 hello TRUE
## 5 11 bonjour FALSE
## 6 12 ciao TRUE
Now, let’s say we want to loop through the entire data frame to find only the values under the “Number” column. To do that, we first need to know the number of rows our data frame has - we can use nrow()
for this. But as we have learned before, we can just define this value directly in our for loop instead of having to do an extra step of finding the number of rows outside of the for loop.
In other words, our code would look like so:
for (i in 1:nrow(dataframe)){
print(dataframe[i,"Number"])
}
## [1] 1
## [1] 2
## [1] 3
## [1] 10
## [1] 11
## [1] 12
We can also add conditions to our for loops by using if
. For instance, we only want to print values under the “T/F” column where i > 3
. To do that, we would need to write the following codes:
for (i in 1:nrow(dataframe)){
if (i > 3) print(dataframe[i,"T/F"])
}
## [1] TRUE
## [1] FALSE
## [1] TRUE
2.10 Help Within and Outside Of R
It gets a while to get used to the language of R and no tutorials can fully explain the complexities and nuances of this language. Therefore, it is important to know how to and where to get help about R! There are so many ways for you to search for help on R, here are only a few methods:
2.10.1 Within R
If you have questions about a function or dataset in R, the easiest way to get help is to type ? before that particular function or dataset - as we have previously seen. Try running the codes below, what do you see?
# ?mean
# ?faithful
If you want to know whether there is a function for a particular action, you can use ?? before the action. If your action is more than one word long (e.g. geometric functions), you can put the entire phrase in quotation marks ("").
# ??"geometic functions"
After running the code above, you should see a list of functions, the package that it belongs to, as well as what it does. For example, the function phil()
in the R package named BAS can be usedd to compound confluent hypergeometric function of two variables.
If you are using RStudio, you can also use the search box in the help window at the bottom right corner of our screen.
2.10.2 Outside of R
Outside of R, there are also plenty of resources for you to tap into R Documentation is a good starting point.
Another resource is Stack Overflow, an online forum where you can ask and answer questions relating to coding!
DO QUESTION 10 OF THE QUIZ NOW
- What are some of the ways that we can find help about R? (select all that apply)
2.11 Summary and Takeaways
In this tutorial, we learned a few basic steps of using R as a data analysis language. Completing this tutorial will prepare you more advanced tutorials in the future. Learning R is like learning another language, so the biggest tip is to practice practice practice!
After this tutorial, you should be familiar with setting up for an R session using basic working directory functions. Additionally, you should also be comfortable with using arithmetic and logical operators and a few common data types of R. You are also introduced with a few basic functions for exploring a dataset as well as several common methods on how to seek help within and outside of R.


--- layout: post status: publish published: true title: "信息过载" author: Leask author_login: leask author_email<EMAIL_ADDRESS>author_url: https://leaskh.com wordpress_id: 232 wordpress_url: http://leaskh.wordpress.com/2009/05/24/%e4%bf%a1%e6%81%af%e8%bf%87%e8%bd%bd date: '2009-05-24 17:56:57 +0800' date_gmt: '2009-05-24 17:56:57 +0800' categories: tags: [] comments: [] ---


| Top |
GIOErrorEnum
g_io_error_from_errno (gint err_no
);
Converts errno.h error codes into GIO error codes. The fallback
value G_IO_ERROR_FAILED
is returned for error codes not currently
handled (but note that future GLib releases may return a more
specific value instead).
GIOErrorEnum
g_io_error_from_win32_error (gint error_code
);
Converts some common error codes (as returned from GetLastError()
or WSAGetLastError()
) into GIO error codes. The fallback value
G_IO_ERROR_FAILED
is returned for error codes not currently
handled (but note that future GLib releases may return a more
specific value instead).
You can use g_win32_error_message()
to get a localized string
corresponding to error_code
. (But note that unlike g_strerror()
,
g_win32_error_message()
returns a string that must be freed.)
Since 2.26
#define G_IO_ERROR g_io_error_quark()
Error domain for GIO. Errors in this domain will be from the GIOErrorEnum enumeration. See GError for more information on error domains.
Error codes returned by GIO functions.
Note that this domain may be extended in future GLib releases. In general, new error codes either only apply to new APIs, or else replace G_IO_ERROR_FAILED in cases that were not explicitly distinguished before. You should therefore avoid writing code like
1 2 3 4 5 |
if (g_error_matches (error, G_IO_ERROR, G_IO_ERROR_FAILED)) { // Assume that this is EPRINTERONFIRE ... } |
but should instead treat all unrecognized error codes the same as G_IO_ERROR_FAILED.
|
Generic error condition for when an operation fails and no more specific GIOErrorEnum value is defined. |
||
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File not found. |
||
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File already exists. |
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File is a directory. |
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File is not a directory. |
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File is a directory that isn't empty. |
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File is not a regular file. |
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File is not a symbolic link. |
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File cannot be mounted. |
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Filename is too many characters. |
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Filename is invalid or contains invalid characters. |
||
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File contains too many symbolic links. |
||
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No space left on drive. |
||
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Invalid argument. |
||
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Permission denied. |
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Operation (or one of its parameters) not supported |
||
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File isn't mounted. |
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File is already mounted. |
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File was closed. |
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Operation was cancelled. See GCancellable. |
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Operations are still pending. |
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File is read only. |
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Backup couldn't be created. |
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File's Entity Tag was incorrect. |
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Operation timed out. |
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Operation would be recursive. |
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File is busy. |
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Operation would block. |
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Host couldn't be found (remote operations). |
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Operation would merge files. |
||
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Operation failed and a helper program has already interacted with the user. Do not display any error dialog. |
||
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The current process has too many files open and can't open any more. Duplicate descriptors do count toward this limit. Since 2.20 |
||
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The object has not been initialized. Since 2.22 |
||
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The requested address is already in use. Since 2.22 |
||
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Need more input to finish operation. Since 2.24 |
||
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The input data was invalid. Since 2.24 |
||
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A remote object generated an error that
doesn't correspond to a locally registered GError error
domain. Use |
||
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Host unreachable. Since 2.26 |
||
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Network unreachable. Since 2.26 |
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Connection refused. Since 2.26 |
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Connection to proxy server failed. Since 2.26 |
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Proxy authentication failed. Since 2.26 |
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Proxy server needs authentication. Since 2.26 |
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Proxy connection is not allowed by ruleset. Since 2.26 |
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Broken pipe. Since 2.36 |


| File | Statements | Branches | Functions | Lines | |||||
|---|---|---|---|---|---|---|---|---|---|
| client.js | 88.7% | 102/115 | 76.09% | 35/46 | 85.71% | 18/21 | 85% | 68/80 | |
| configuration.js | 100% | 25/25 | 90% | 9/10 | 100% | 6/6 | 100% | 10/10 | |
| index.js | 85.71% | 6/7 | 100% | 4/4 | 100% | 1/1 | 50% | 1/2 | |
| logger.js | 88.24% | 15/17 | 100% | 4/4 | 75% | 6/8 | 80% | 8/10 | |
| registrar.connector.js | 81.16% | 112/138 | 63.16% | 24/38 | 84.38% | 27/32 | 75% | 78/104 | |
| registrar.js | 96.3% | 52/54 | 70% | 7/10 | 100% | 11/11 | 90.91% | 20/22 | |
| twilsock.connector.js | 91.67% | 66/72 | 73.68% | 14/19 | 92.31% | 12/13 | 85.37% | 35/41 |


Annotation Property: accrualMethod
http://purl.org/dc/terms/accrualMethod
Annotations (6)
-
hasVersion http://dublincore.org/usage/terms/history/#accrualMethod-003
-
issued "2005-06-13" ()
-
modified "2010-10-11" ()
-
comment "The method by which items are added to a collection." (en-us)
-
isDefinedBy http://purl.org/dc/terms/
-
label "Accrual Method" (en-us)
Domains (1)
-
http://purl.org/dc/dcmitype/Collection
Usage (1)
-
accrualMethod Range (http://purl.org/dc/dcmitype/Collection)


Let me tell you a little about this awesome band toe. They make some music and have a record label. Enemies is a band on their label. Blahblahblahblahblabh blah blahblah blah .
toe has been around for a number of years and are genre-pushing innovators.


You are about to share some or all your contact information with ivan.
Are you sure?
You are about to unfollow yellow.
He will no longer see the changes in your profile (unless it's public). However, Ivan will retain the current snapshot of your profile.
Are you sure?


Registered Users
User data on UseGalaxy.eu (i.e. datasets, histories) will be available as long
as they are not deleted by the user. Once marked as deleted the datasets will
be permanently removed within 14 days. If the user "purges" the dataset in the
Galaxy, it will be removed immediately, permanently.
An extended quota can be requested
for a limited time period in special cases.
Unregistered Users
Processed data will only be accessible during one browser session, using a
cookie to identify your data. This cookie is not used for any other purposes
(e.g. tracking or analytics.)
If UseGalaxy.eu service is not accessed for 90 days, those datasets will be
permanently deleted.
GDPR Compliance
The Galaxy service complies with the EU General Data Protection Regulation
(GDPR). You can read more about this on our
Terms and Conditions.


Your browser doesn't support canvas. Please download a modern browser.
00:00.000
1
00:00.000
2
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gui.control
Classes
FilterPanel
HelpButton
MouseManager
MouseManager.ModeKeyAdapter
PickingPlugin
PopupPlugin
QuadTreeShapePickSupport
ScreenPrint
SearchTool
TranslatingSearchTool
ZoomPanel


Guess the correct letters that spell the picture you see!
When you guess all of the right letters, you earn points!
Points reveal more of the prize puzzle!
Reveal the whole puzzle to move on to the next Level!
Points to See the Puzzle! =


Biographical Sketch of Pearl
L. McCurdy
BATTLE SCARRED WORLD WAR
VETERAN NEW COMMANDER OF PATTERSON TRUE POST VFW
Still carrying bullets and many deep scars received in
France during the World War, Pearl L. McCurdy, Marietta man, is able to be
around and among his friends and has taken on added activities for the current
year as Commander of Patterson True Post No. 128 Veterans of Foreign Wars, an
organization that is carrying out a broad program of patriotic activities. The
post, under his leadership, has outlined an extensive season of work among its
members and with war veterans and their dependents generally.
McCurdy
enlisted when the first call came for troops, was one fo the first Mariettans
to go overseas and nearly all of his service was spent under fire. He saw
service with the old Indian Head Division, the Fighting Second, which was made
up of regular army troops and marines. The Second Division took part in many of
the famous drives in which the A. E. F. participated and among the battles to
its credit are Verdun, Cantigny, Chatteau Theirry, Champaigne, Soissons and
others. McCurdy was over the top seven times and was three times wounded the
last time being shot in 12 different places. He spent many months in hospitals
after that and for months it was feared that he would not survive. He wa
decorated by the French government, every man in his division being cited for
bravery. He likewise was decorated by the American government, this award being
President Wilson's Accolade of the New Chivalry of Humanities certificate.
Provided by Betty Latta Kitchen
-- e-mail: Betty Kitchen
Click here for the Short-Cut Table of Contents


View Location Map
The beach at Le Yaudet is within walking distance from the house.
It is accessed via steps from the headland.
It is very quiet and unspoilt (no shops or bars).
There are many signposted coastal walks and paths to be explored.


{% extends "base.html" %} {% set active_page = "more_info" %} {% block content %}
Step 1 requires biocatalytic retrosynthesis to be employed to work backwards from a target molecule to a suitable starting material. Manually this relies on expert knowledge of what biotransformations are possible. Alternatively, reaction rules can be programmed or extracted from available reaction information and applied iteratively for automated retrosynthesis towards a suitable starting material.
With a number of potential pathways in hand, step 2 requires specific enzymes to be selected to carry out each enzymatic step. In many cases there are a great many potential sequences which could theoretically complete it. Researchers manually selecting enzymes will typically rely on literature searches, or more recently enzyme screening panels, to identify suitable enzymes. For a more automated approach, a database of known biotransformations can be searched for similar substrates which have been tested previously, using molecular similarity.
Often a number of potential pathways are identified. Further evaluation of these pathways in step 3 can provide data-driven analysis of which are the best pathways to take forwards for experimental validation in step 4. This requires the calculation of a number of metrics such as substrate availability, enzyme selectivity, thermodynamics, cofactor usage, substrate solubility ect..
RetroBiocat seeks to offer automated solutions for steps 1-3. Network explorer offers human-led exploration of a network of possible biotransformations, with the option to add custom transformations not currently included in the program (for example chemical transformations). Pathway explorer offers automated pathway generation, with selection based on the weighted average a number available of metrics. These pathways can then be explored one at a time. Both network and pathway explorer identify specific enzymes to complete each step, where data is available.
For a more detailed look at the enzymes available for a particular biotransformation, BiocatDB offers a search portal for investigating substrate specificity for a particular enzyme or reaction.
In a future release we hope to also offer a tool for automated pathway evaluation (step 3), with integration into a complete work flow.


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| Accompanist | Denise Millard | View Teacher | |
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