FREDDY'S DEAD: THE FINAL NIGHTMARE A review in the public domain by The Phantom<EMAIL_ADDRESS>The Phantom feels good about this review, because with it he can help nearly all of his readers. All except those who have already seen FREDDY'S DEAD: THE FINAL NIGHTMARE, that is. There's not much that can be done for those unfortunate few who bolted from the comfort and safety of their homes to see Freddy's latest (and purportedly, his last) ELM STREET film this past weekend. Perhaps they were disappointed by CHILD'S PLAY 3 the week before and figured that at the very least, nothing could be worse. Perhaps they were enticed by the prospect of great special effects -- after all, as the print ads read, "they saved the best for last." Perhaps the rare opportunity of seeing another film in 3-D did it. Or perhaps it was just their self-appointed job, as it was for the Phantom, Janet Maslin of the New York Times, and what appeared to be most of the employees of New Line Cinema's New York office (New Line has been the distributor of all of the ELM STREET films).
That in and of itself should have told the Phantom something. The premiere of TERMINATOR 2 was also filled with industry people (rows 10 through 14 were filled with nothing but ILM weenies), but that seemed easy to understand. After all, T2 was destined to be the summer's blockbuster film, and if it weren't for the dedicated effort made by the folks who work at the special effects houses, the film wouldn't be nearly the success it is. Why not go see it with a packed house of eager movie-goers the night before opening day and see how your efforts -- or those of your coworkers -- paid off?
But it's hard to understand what those folks from New Line were doing at the National Theater last Friday, except perhaps looking for an excuse to cut out of work early. Surely they couldn't have expected people to stand up and cheer (as they did at the end of T2). Or stay seated and applaud (as they did at the end of DANCES WITH WOLVES). Or even keep their dissatisfaction to themselves (as they do at the end of most films which fail to live up to their expectations)? Given the general grumbling heard by the Phantom on the way out, the last place he would expect a New Line employee would want to be last Friday afternoon is anywhere within range of rotten fruit. (Alas, the Phantom forgot to pick some up on the way in, so his preferred form of film criticism was denied him.)
So the Phantom can come to no other conclusion than that these poor folks weren't going to get paid last week unless they attended the 4:00 show in an attempt to help fill what would otherwise be a rather empty auditorium. Additional confirmation for this theory was provided outside the theater, where the Phantom looked on in amusement as the New Line folks were told that even with their industry passes it would still cost them $1 each to get in. Since New Line at this point has more unopened, returned copies of TEENAGE MUTANT NINJA TURTLES II than it has dollar bills, the Phantom wasn't at all surprised to see that the National's steep cover charge might prove their undoing. Yet by the time the film was over, even they did little more than provide what the Phantom's believes was the very definition of a "smattering" of applause. They may not be hard workers; they may not be well-paid; but they are loyal.
Yet even a full refund wouldn't have kept the Phantom from wishing that he had bought some popcorn at the concession stand. How frustrating it was to have to leave the theater without being able to fully express his feelings about the nightmare that had just unfolded before him. And if some of the buttered kernels happened to fall on the heads of the New Liners, it probably wouldn't have surprised them, knowing as they did that at least one critic was in the audience -- Ms. Maslin, like other film critics, wasn't allowed to see and review the film before opening day because New Line didn't screen it before opening day. (As an aside, when a studio or distributor doesn't screen a film before opening day, you can be fairly sure that there's a reason for it; one can't pan a film one hasn't seen yet, can one?)
Well, one has now seen this film, and one is therefore now quite well prepared to pan it. As was obvious to every phan unfortunate enough to see Freddy in his last outing (THE DREAM CHILD), the ELM STREET series has really been on the skids for a few years now. The first ELM STREET film was a certified original, a unique twist on the by then standard slasher genre that allowed horror auteur Wes Craven to transcend the limitations of ordinary horror villains in a more-or-less plausible way. Freddy was a little more scary and a little less funny back in those days, and the sequels never really matched the original. On the other hand, the first two sequels were well made and very entertaining in their own right, and by the fourth (THE DREAM MASTER), Freddy had turned into a veritable cottage industry, spawning a television series and a line of Halloween makeup that made everyone involved an awful lot of money. In short, Freddy achieved the celebrity status that had always eluded Michael and Jason -- the serial killers from the HALLOWEEN and FRIDAY THE 13TH serials respectively -- and it quickly became apparent that New Line had the cinematic equivalent of the Golden Goose on its hands. Freddy's films were relatively inexpensive to make, and people apparently couldn't get enough of him.
That is until DREAM CHILD, when someone decided that people really *would* see anything with Freddy in it, regardless of how good -- or, in this case, bad -- it was. That's always a mistake, and in this case it left the Goose's neck on the chopping block, anxiously awaiting a reprieve from the farmers at New Line -- and more importantly, from Freddy's still-loyal phans. After DREAM CHILD, there were two ways to go. Either New Line could find a writer and a director who would breathe some life back into the series, or they could drop the axe and make whatever money they could as quickly as they could and kill the series once and for all. After leaving FREDDY'S DEAD, the Phantom should have asked the folks from New Line what they were having for dinner later that night, but he suspected that at least for some of them, roast goose was on the menu.
The problem with DREAM CHILD was that despite all the money spent on special effects (which were an increasingly costly and escalating proposition since THE DREAM WARRIORS), it was a fairly boring film. Not bad, really, but not interesting either, and shortly after it opened, word of mouth saw it to a speedy closing. All of a sudden, it seemed that Freddy wasn't perhaps the drawing card that New Line thought he was; after the smoke cleared, it wasn't clear whether there would even *be* another sequel.
But another sequel there is: FREDDY'S DEAD, the first of the ELM STREET films not to use the words "A NIGHTMARE ON ELM STREET" in its title. That now seems strangely appropriate to the Phantom, for FREDDY'S DEAD is less like an honest sequel to the original 1984 horror classic than a big joke played on everyone who has the misfortune of seeing it. From the jokey title (a play on the early 70s Curtis Mayfield hit); to the 3-D glasses (which are in fact good for nothing but making you feel like a complete fool until the last 15 minutes of the film -- the first 115 are in two dimensions, though of course the characters are only drawn in one); to the throwaway special effects (which are not very especially special); FREDDY'S DEAD provides ELM STREET phans with a very sad, very tawdry sendoff for one of our favorite horror personalities. Romero did better by his DEAD; it's too bad that New Line couldn't have done better by Wes' Freddy.
What can be said of an ELM STREET film in which only three people die (four, including Freddy)? Such a film simply doesn't have its heart in the right place. Or what of a film that's advertised as being in "3-D FreddyVision" and yet has no 3-D effects until the last 15 minutes? (By the way, the joke was certainly on the Phantom and his fellow audience members at the National last Friday. We all dutifully put on our vintage 50s red/blue 3-D glasses right at the start of the film -- and then spent the next 10 to 30 minutes peering over them, under them, and around them in vain search of any effect that could even be construed as being in three dimensions. "There ain't a *damn* thing 3-D about this!" was the most apt summary overheard by the Phantom during the film's exceedingly flat beginning.) Still not convinced? Okay, how about Roseanne and her husband Tom Arnold as deranged residents of the now-childless Springfield? See, it's a joke, son! Laugh it up, why don't you!
The Phantom did indeed come close to doubling up once or twice, but it most assuredly wasn't from laughter. Rather it was from watching the most lackluster and uninteresting ELM STREET film ever. The characters were dull; the special effects were.... Oh, the Phantom went through this once already, didn't he? Comes from trying to write too many sequels to his own reviews, perhaps. Got your magic 3-D reviewing glasses on, phans?
The plot might have been interesting, but the idea -- discovering how Freddy became the oh-so-unneighborly guy he is by looking at scenes from his tortured past -- is almost completely wasted. Robert Englund does what he can out of makeup, but oh how the Phantom longed for Terry O'Quinn and a performance even half as good -- and half as scary -- as the one he turned in for THE STEPFATHER. The rest of the cast is uniformly uninteresting; character development has been rolling steadly downhill since DREAM WARRIORS.
We learn that Freddy has a child that was taken from him, and that he has been seeking revenge on everyone else's children since he was burned alive by the angry townsfolk of Springfield. It might have been possible to explore in some depth Freddy's relationship to his son or daughter (the Phantom's not telling which, though it hardly matters in the scheme of things), and that might have made FREDDY'S DEAD much more interesting than it is. Something along these lines was attempted in ELM STREET 2, and because of that it remains the most intelligent and interesting of the sequels (though perhaps not the crowd-pleaser that later sequels were). But such discussion and exposition is postponed until the "final confrontation", and by then it is much too late.
We do, however, get to see -- in 3-D, no less -- those spirits of the underworld with which Freddy Krueger makes his fateful pact. As the flames surge around him, these dream agents offer Freddy immortality as long as he spends it collecting children's souls, television residuals, and product endorsements. They may come from the depths of hell, but agents are, after all, agents. It wasn't clear to the Phantom whether these dream agents get 10% of the souls that Freddy collects, but he suspects that some arrangement along those lines was worked out. (Naturally the agents looked like flying skulls with short spinal cord tails -- all mouth and no heart, you might say.)
Alas, the dream agents have let Freddy down; with FREDDY'S DEAD, the Golden Goose has been cooked, and the series ends not with a bang but a smirk. Though the 3-D at the end is fun (the Phantom's always had a soft spot for 3-D, ever since it was revived in the 1981 spaghetti western COMIN' AT YA), it's a shame that it was implemented with red/blue glasses rather than polarized glasses -- the result is not nearly as good as it could have been, and so those phans who go in expecting something similar to FRIDAY THE 13TH PART 3 are going to be doubly disappointed.
It was kind of sad watching FREDDY'S DEAD and seeing what had become of the premiere horror series of the eighties. Though it concentrated less on horror than on crowd-pleasing special effects and humor in its later sequels, the ELM STREET series was like a favorite pair of jeans -- something you could slip into and feel comfortable with no matter how torn up it got. But Hollywood never seems to learn the lesson that last summer's season of dud sequels brought home with a vengeance: that although audiences may not always be as discerning as we critics would like them to be, and though they may not always know quality when they see it, they certainly have no trouble perceiving a lack quality and effort, and they'll stay away in droves from films that don't at least make an honest attempt to entertain, if nothing else.
About the only people who might enjoy FREDDY'S DEAD are those who will see *anything at all* in 3-D -- the Phantom isn't sure whether the video release will also be in "FreddyVision"; on the other hand, given the bad word of mouth that this last ELM STREET film is generating, it's likely that we'll all find out quite soon.
: The Phantom<EMAIL_ADDRESS>: {cmcl2,uunet}!esquire!baumgart
.
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


Namespace Echosign
| Echosign\Abstracts |
| Echosign\Creators |
| Echosign\Exceptions |
| Echosign\Interfaces |
| Echosign\RequestBuilders |
| Echosign\Requests |
| Echosign\Responses |
| Echosign\Transports |
| Agreements | Class Agreements |
| BaseUris | Class BaseUris |
| LibraryDocuments | Class LibraryDocuments |
| Reminders | Class Reminders |
| Search | Class Search |
| TransientDocuments | Class TransientDocuments |
| Users | Class Users |
| Util | |
| Views | Class Views |
| Widgets | Class Widgets |


| About Dailyrotten |
|
Feedback
If you like this page, hate it, or would like to suggest changes,
<EMAIL_ADDRESS>is listening. This page
is experimental and somewhat different from what we usually offer, so please
do send your feedback.
Adding Stories
If you are a rotten newshound and you would like to suggest a story,
visit our submit page to
send us the URL. Stories that are accepted will have your name credited.
Posting Comments
In order to post comments to stories, you will have to
create an account.
Accounts will generally be validated within 24 hours, and of
course will be disabled if there is abuse.
Viewership
On the first full day this page went live, 100,000 people visited this Rotten
News page. Of course that was the day after the WTC attacks, so that number is
somewhat distorted. Right now this page gets between 50,000 and 75,000 people
every day.
Linking
We encourage everyone to link to this page; if you like it, others probably
will as well.
Other Rotten
Rotten
Gaping Maw
Celebrity Morgue
Mugshots
Rotten Store
Rate My Poo
Rate My Kitten
Rate My Finger
Penny Postcards
Phallic
Boners
Home
Make Dailyrotten your start page
|
|
|
August 25, 2002
Poo in the post
Melbourne Herald Sun | Submitted by: Vesney
Under a federal government plan, 50,000 Australians aged between 55 and 74
would be asked to smear samples of faeces on cards and mail them to
pathologists to test for bowel cancer. But nobody told the postal service.
|
|
Read article...
|
|
Rabbi arrested for DUI while on way to bris
WKMG-TV 6 Orlando | Submitted by: Kat
Not sure which part is more distressing... that he was driving drunk, or
that the mohel was going to perform the circumcision while drunk.
"West Bloomfield, Mich., police said that Greenbaum failed a breathalyzer
test after he was spotted driving erratically."
|
|
Read article...
|
|
Holy crap I just gave birth
News Corporation | Submitted by: gogoBOi
"A territory woman who did not know she was pregnant got a shock when she
gave birth at home, suddenly and without warning. Rebecca Pierce, 22, was
yesterday coming to grips with the surprise arrival of 3.3kg baby Grace."
|
|
Read article...
|
|
Is the world ready for Di's death photos?
Independent | Submitted by: n. gibbons
"On the night of the crash, the News of the World and other newspapers were
offered, and saw on their screens in London, pictures taken by Laurent Sola's
agency. The shots showed Dodi dead in the back seat of the Mercedes and
Diana's body lying between the two front seats. They were syndicated by Big
Pictures, an agency in London, and negotiations were under way for the
rights to publish them when news broke at about 3.30am London time
that Diana had died."
|
|
Read article...
|
|
Exploiting hippies for fun and profit
Court TV | Submitted by: Son of Benway
"Voyeur Video, which O'Brian founded in 1989, currently offers 12 Burning Man
videos at $29.95 each. The tapes, sold on Voyeur's Web site alongside such
titles as "Kinky Nude Beach Day" and "Springbreak Stripoffs", show naked women
being painted, dancing and taking group showers, while the cameramen make
comments like "Man, this is like Playboy."
|
|
Read article...
|
|
Yucca crater: Nuclear waste on the moon?
MSNBC | Submitted by: Son of Benway
"As the debate rages over using the Yucca Mountain as a burial ground for
thousands of tons of radioactive material, a better site for unwanted nuclear
waste holds its mute vigil in the skies above the Nevada desert: the
moon... even the highest reliability attained by a space booster also comes
with catastrophic launch failure probabilities. Then itís a matter of
acceptable risk of how much nuclear material might come back at Earth."
|
|
Read article...
|
|
Woman dies in Disney stadium promotion
ESPN | Submitted by: anonymous
"A woman taking part in a minor-league baseball promotion collapsed and died
as she ran across the baseball field in search of a hidden diamond.
Lampe appeared to suffer a seizure in the infield of the Disney's Wide World
of Sports stadium."
|
|
Read article...
|
|
And call me in the morning
Sun | Submitted by: col klink
A chemist's shop worker has been sacked for putting an obscene message on
a womanís pills. He printed out a prescription label that read: "Insert ONE
into PUSSY when pleasure is required". Photo of label!
|
|
Read article...
|
|
Animal rights group responsible for mink massacre
AZ Central | Submitted by: Col. Klink
"Members of an animal-rights group cut fences and broke open pens at an
Iowa mink farm over the weekend, releasing hundreds of the cat-sized animals
prized for their fur. Becky Demuth, who owns the farm with her husband,
Nick, said about 1,200 mink escaped and half had been recovered by Monday.

|
|
Read article...
|
|
Christians attempt mass snail theft
Charlotte Observer | Submitted by: wingnut
"The great Pismo Beach snail caper began about 3:40 p.m. Monday when a
caller told the police that a large group of people was harvesting snails by
gallon buckets on the beach at the end of Cuyama Avenue... When the police
arrived, the gallon buckets were empty, but the police kept searching and
found 200 pounds of black turban snails in an ice chest, he said. 'We had
a discussion with them about lying', Martin said about the church members."
|
|
Read article...
|
|
|
|
|


"Blast From The Past" (1999) - Brendan Fraser, Alicia Silverstone, ...
Last year's underrated "Pleasantville" tossed a couple of modern teens into the 1950s, and occasionally went so far as to touch on social issues. This year's "Blast From The Past" is its conceptual opposite, launching a young man from the early 1960s into the eerie modern world with a much lighter touch.
The story is one that could only happen in the movies. Convinced that the Cold War is about to turn hot, Calvin and Helen Webber (Christopher Walken and Sissy Spacek) lock themselves up in their bomb shelter. 35 years later, they send their son, optimistically named Adam, to the dreaded outside world for much-needed supplies. Adam (Brendan Fraser) has never seen the sun, or wacky religious cults, or public transportation, and so promptly gets lost.
Enter Eve (Alicia Silverstone), the consummate 90s girl from L.A. Adam needs a guide to this post-Apocalyptic wasteland. She knows what a liquor store is, and she even knows how to drive. Over the next hour and a half, Adam gets a practical education in the modern world... and, of course, in love, while Eve realizes this may be the one man left who won't try to ruin her life.
Yes, it's a romantic comedy, and it's utterly predictable. So what? Fraser, with goofy charm, is already well-versed at the "fish out of water" routine, having done it before in "Encino Man" and "George Of The Jungle." Once again, he pulls it off with subdued flair. The always-lovely Silverstone, complete with puppy-dog eyes, is equally charming in her role. And Dave Foley, in the cliched role of the gay best friend (as Eve's brother Troy), steals a few scenes too.
Back in the 1960s, Walken and Spacek do their jobs as well. Christopher Walken has always been good at doing "spooky-cool," but like Spacek, rarely gets a chance to do pure comedy. While Walken raises his son as a Renaissance man, Spacek goes stir crazy, and they generate more than a few chuckles in the process.
Visually, "Blast From The Past" is serviceable. Aurally, though, it's outstanding. The soundtrack is nearly a copy of the Billboard charts, if you splice together this week's chart with one from 1964. And those tunes are used to good effect, but rarely over-used. Pardon the pun, but musically it hits almost all the right notes.
There's only one major flaw in this otherwise sparkling romantic comedy. The first half-hour is spent underground, showing Adam's childhood; while it may help build the character, it waffles between almost-funny and almost-tedious. But that's what the fast-forward button is for, right? Blast through the first few minutes of "Blast From The Past" and what's left is thoroughly charming.
(This review was originally published in The Capaha Arrow, the student newspaper of Southeast Missouri State University.)
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


Upload an XML file for META-SHARE validation:
Or supply a URL to an XML file for META-SHARE validation:
{% extends "layout.html" %} {% block body %}
Upload an XML file for META-SHARE validation:
Or supply a URL to an XML file for META-SHARE validation:


slycat.web.server.remote¶
Functions for managing cached remote ssh sessions.
Slycat makes extensive use of ssh and the Slycat Agent to access remote resources located on the high performance computing platforms used to generate ensembles. This module provides functionality to create cached remote ssh / agent sessions that can be used to retrieve data from remote hosts. This functionality is used in a variety of ways:
Web clients can browse the filesystem of a remote host.
Web clients can create a Slycat model using data stored on a remote host.
Web clients can retrieve images on a remote host (an essential part of the parameter-image-model).
Web clients can retrieve video compressed from still images on a remote host.
When a remote session is created, a connection to the remote host over ssh is created, an agent is started (only if the required configuration is present), and a unique session identifier is returned. Callers use the session id to retrieve the cached session and communicate with the remote host / agent. A “last access” time for each session is maintained and updated whenever the cached session is accessed. If a session times-out (a threshold amount of time has elapsed since the last access) it is automatically deleted, and subsequent use of the expired session id will fail.
Each session is bound to the IP address of the client that created it - only the same client IP address is allowed to access the session.
-
class
slycat.web.server.remote.
Session
(sid, client, username, hostname, ssh, sftp, agent=None)[source]¶ Bases:
object
Encapsulates an open session connected to a remote host.
Examples
Calling threads must serialize access to the Session object. To facilitate this, a Session is a context manager - callers should always use a with statement when accessing a session:
>>> with slycat.web.server.remote.get_session(sid) as session: ... print session.username
-
property
accessed
¶ Return the time the session was last accessed.
-
cancel_job
(jid)[source]¶ Submits a command to the slycat-agent to cancel a running job on a cluster running SLURM.
- Parameters
jid (int) – Job ID
- Returns
response – A dictionary with the following keys: jid, output, errors
- Return type
dict
-
checkjob
(jid)[source]¶ Submits a command to the slycat-agent to check the status of a submitted job to a cluster running SLURM.
- Parameters
jid (int) – Job ID
- Returns
response – A dictionary with the following keys: jid, status, errors
- Return type
dict
-
property
client
¶ Return the IP address of the client that created the session.
-
get_job_output
(jid, path)[source]¶ Submits a command to the slycat-agent to fetch the content of the a job’s output file from a cluster running SLURM.
Note that the expected format for the output file is slurm-[jid].out.
- Parameters
jid (int) – Job ID
- Returns
response – A dictionary with the following keys: jid, output, errors
- Return type
dict
-
get_remote_job_status
(jid)[source]¶ check of the status of a job running on an agent with a hostanemd session :param jid: job id :return:
-
get_user_config
()[source]¶ Submits a command to the slycat-agent to fetch the content of a user’s .slycatrc file in their home directory.
- Returns
response – A dictionary with the configuration values
- Return type
dict
-
property
hostname
¶ Return the remote hostname accessed by the session.
-
launch
(command)[source]¶ Submits a single command to a remote location via the slycat-agent or SSH.
- Parameters
command (string) – Command
- Returns
response – A dictionary with the following keys: command, output, errors
- Return type
dict
-
run_remote_command
(command)[source]¶ run a remote command from an HPC source running a slycat agent. the command could be things such as starting an hpc script or batch job or something as simple as moving files. the only requirement is that the script is in our list of trusted scripts. this_func()->calls agent_command_func()->which runs_shell_command() -> which launches_script()-> sends_response_to_agent()->sends_response_to_server() ->sends_status_response_to_client()
- Parameters
command (json) –
of a command to be run (form) –
{ –
"scripts" (//pre defined scripts that are registerd with the server) –
[{ –
"script_name" ("script_name", // key for the script lookup) –
"parameters" ([{key:value},..] // things such as number of nodes) –
} –
..] –
"hpc" (// these are the hpc commands that may be add for thing such as slurm) –
{ –
"is_hpc_job" (bol, // determins if this should be run as an hpc job) –
"parameters" –
} –
} –
- Returns
obj
{“msg” (“message from the agent”, “error”: boolean})
-
set_user_config
(config)[source]¶ Submits a command to the slycat-agent to set the content of a user’s .slycatrc file in their home directory.
- Returns
response
- Return type
dict
-
property
sftp
¶
-
submit_batch
(filename)[source]¶ Submits a command to the slycat-agent to start an input batch file on a cluster running SLURM.
- Parameters
filename (string) – Name of the batch file
- Returns
response – A dictionary with the following keys: filename, jid, errors
- Return type
dict
-
property
username
¶ Return the username used to create the session.
-
property
-
slycat.web.server.remote.
check_session
(sid)[source]¶ Return a true if session is active
If the session has timed-out or doesn’t exist, returns false
- Parameters
sid (string) – Unique session identifier returned by
slycat.web.server.remote.create_session()
.- Returns
- Return type
boolean
-
slycat.web.server.remote.
create_session
(hostname, username, password, agent)[source]¶ Create a cached remote session for the given host.
- Parameters
hostname (string) – Name of the remote host to connect via ssh.
username (string) – Username for ssh authentication.
password (string) – Password for ssh authentication.
agent (bool) – Used to require / prevent agent startup.
- Returns
sid – A unique session identifier.
- Return type
string
-
slycat.web.server.remote.
delete_session
(sid)[source]¶ Delete a cached remote session.
- Parameters
sid (string, required) – Unique session identifier returned by
slycat.web.server.remote.create_session()
.
-
slycat.web.server.remote.
get_session
(sid, calling_client=None)[source]¶ Return a cached remote session.
If the session has timed-out or doesn’t exist, raises a 404 exception.
- Parameters
sid (string) – Unique session identifier returned by
slycat.web.server.remote.create_session()
.- Returns
session – Session object that encapsulates the connection to a remote host.
- Return type
-
slycat.web.server.remote.
get_session_server
(client, sid)[source]¶ Return a cached remote session.
If the session has timed-out or doesn’t exist, raises a 404 exception.
- Parameters
sid (string) – Unique session identifier returned by
slycat.web.server.remote.create_session()
.- Returns
session – Session object that encapsulates the connection to a remote host. :param client:
- Return type


Motivation
The InjectCircularSources
component allows to inject a behaviour source (or simply behaviour)
and/or an event source into children components, both of which can be instrumented through
processing commands received through the relevant sinks.
The InjectCircularSources
responds to the need to have encapsulated components, which holds and
manage their own state independently, and are able to interact with the external world with the
help of a command processor, which receives, interprets, executes and returns the results of
incoming commands. The command processor being external to the component, from the point of view
of the application using the component, the component acts very much as an automata (more
specifically a class of automata termed state transducers), which produces an output on
reception of an input. The component, encapsulating a set of functionalities realized by its
children, can also be seen as a web-component
of sorts.
A typical example would be a calendar component, which can receive new calendar entries as
inputs, and update its internal state to display the updated calendar visualization. That
calendar component might also need to query other calendars to synchronize entries. Such
components with internal state and interaction with the exterior world, can be implemented in an
encapsulated way with the InjectCircularSources
component.
API
InjectCircularSources :: InjectCircularSourcesSettings -> ComponentTree -> InjectCircularSourcesComponent
Description
Creates an encapsulated component whose behaviour is parameterized via
InjectCircularSourcesSettings
.
The parametrization is as follows :
behaviour
: an object specifying the encapsulated piece of state for the component tree as a behaviour. In particular, are detailed here the behaviour source name; the initial value for the behaviour; the function processing behaviour update commands ; and optionally a function called when the behaviour is terminated, which can be used to release any used resources – resources could be used when computing the initial value for the behaviour.event
: an object specifying the interface by which the component will communicate with the outside world. In particular, are detailed here the event source name by which results from command execution will be received; the command processor, which executes the commands; optionally a function called when the event source is terminated.
The behaviour of the component is as follows :
- behaviour source and event source are created (technically speaking, they are subjects)
- behaviour source is initialized with the initial state
- the initial state is taken as is if it is an object, or computed if it is a function. In the latter case, that funcion returns a constructor, which executed returns the desired initial state
- event source and behaviour source are passed down the component tree and are hence visible by all components
- behaviour sink receives update commands describing how to update the behaviour
- event sink receives commands describing an operation to execute. Such commands are executed and the result of such is passed back to the eponym source
- any error occurring during the processing of the commands leads to the partial termination of the component tree (namely the portion of the tree which depends on the terminated source)
- THERE IS NO SEQUENTIALITY GUARANTEE, i.e. two executed commands might see their results received in an order different of that of the execution
- order of subscription
- the behaviour source is subscribed first
- the event source is subscribed second
- the remainder of upper-stream sources are subscribed after
- computing of update/results
- the command processor takes a command and returns a stream of results
- the behaviour updates takes the current value of the behaviour, the update command ; and returns an updated behaviour value. That value is cached prior to scheduling its emission
- this allows in particular to have commands whose semantics include operations on a delta vs. the current behaviour value. That is, instead of computing the new value entirely from scratch, it can be computed as an update of a portion of the current value.
- More prosaically, the behavior updating function can be seen as a reducer
- scheduling of update/results
- behaviour value updates and command execution results are passed from the relevant sink to
the eponym source asynchronously, always. However they are passed as soon as possible, via
use of the
currentThread
scheduler
- behaviour value updates and command execution results are passed from the relevant sink to
the eponym source asynchronously, always. However they are passed as soon as possible, via
use of the
- sinks filtering
- behaviour and event sinks are not passed or visible upstream. They stop at the
InjectCircularSources
level. - The remainder of sinks are merged as usual.
- behaviour and event sinks are not passed or visible upstream. They stop at the
Types
InjectCircularSourcesComponent :: Component
ComponentTree :: ChildrenComponents | [ParentComponent, ChildrenComponents]
ParentComponent :: Component
ChildrenComponents :: Array<Component>
InjectCircularSourcesSettings :: Record {
behaviour :: BehaviourConfig
event :: EventConfig
}
BehaviourConfig :: Record {
behaviourSourceName :: SourceName
processingBehaviourFn :: Command -> BehaviourValue -> BehaviourValue
initialBehaviorValue :: BehaviourValue
finalizeBehaviourSource :: BehaviourCache -> ()
}
EventConfig :: Record {
eventSourceName :: SourceName
processingEventFn :: Command -> Stream<CommandResult>
finalizeEventSource :: () -> ()
}
Contracts
- At least one of the
behaviour
orevent
property must be set in the
InjectCircularSourcesSettings
object. - the behaviour update function must not mutate the behaviour value passed in parameter
Example
Cf. Tree
component source code and tests.
TODO : add url when merged in master


| 0 |
enlist, korea, north, america, patriot, patriots, china, stand, surprise, freedom |
national, persian, potus, heavy, security, director, clean, storm, bunch, denounce |
trump, racist, venezuela, amaze, women, crazy, court, imagine, doubt, maduro |
| 1 |
nation, father, tough, disgust, explain, responsible, chicken, collusion, price, image |
president, twitter, speech, trump, racism, impeach, liberty, boycott, press, front |
clinton, hillary, party, change, politics, democrats, trump, health, email, democratic |
| 2 |
mccain, traitor, mcmaster, setup, trump, market, stock, speech, flake, ryanjensen |
white, country, supremacists, terror, project, nature, single, reach, speak, stupid |
fight, human, heart, resign, embarrass, trump, opposite, congressman, millions, official |
| 3 |
pardon, sheriff, arpaio, terrorist, trump, obama, major, worse, break, crime |
weapons, international, night, trade, company, reopen, grand, shell, billion, probe |
trump, white, president, supremacists, birthday, supremacist, nazis, charlottesville, condemn, denounce |
| 4 |
narrative, prisonplanet, resistance, manafort, defend, islam, guilty, lrihendry, flashback, white |
continue, administration, political, mother, music, arrive, store, achieve, phone, paris |
korea, learn, north, unite, trump, violence, teach, state, people, idiot |
| 5 |
wasserman, schultz, scandal, trust, point, establishment, check, debbie, stonewall_, hillaryclinton |
bannon, power, support, silence, steve, racists, saudi, immigration, message, liberation |
trump, retweet, maganda, disgust, mexico, nuclear, social, media, favor, presidency |
| 6 |
trumptrain, draintheswamp, corruptcongress, potus, photo, kaepernick, durham, houston, historic, longer |
charlottesville, women, service, summer, police, secret, market, point, militarize, front |
pardon, impeachtrump, arpaio, impeach, trump, daughter, instagram, sheriff, queen, donald |
| 7 |
matter, stupid, black, soros, chrisbragdon, guess, group, media, administration, prepare |
claim, change, policy, afghanistan, responsibility, germany, mosque, mutzenich, troop, answer |
color, religion, background, statues, trump, popular, remove, confederate, folks, remind |
| 8 |
susan, kwilli, millions, alozrast, trump, made__usa, leadership, denounce, support, senatemajldr |
business, campaign, fight, trump, lovelylandscape, giant, government, threat, school, fundraiser |
obama, tweet, president, trump, twitter, donald, barack, block, number, trust |
| 9 |
ignore, archive, media, pjnet, approval, hedgebz, bless, crimes, woman, trigger |
update, official, complete, technology, scaramucci, stephen, politicians, bless, spend, remind |
happen, trump, putin, tower, president, russian, video, russia, country, shock |
| 10 |
retweet, rt_america, worst, investigation, sanctuary, benghazi, cities, accuser, bolling, search |
saudiarabia, shiraz, racist, reveal, truth, injure, latest, funny, graham, attack |
vacation, trump, katrina, obama, supporters, bitch, pathetic, council, manufacture, president |
| 11 |
republicans, thegreatfeather, agenda, officials, realdonaldtrump, politician, picture, arrest, trump, veteran |
rally, border, father, protesters, boston, economy, march, celebrate, block, fascist |
trump, sound, friends, finally, mention, notice, update, online, senators, girls |
| 12 |
security, politicalhedge, national, georgiadirtroad, federal, count, official, business, troll, investigate |
murder, share, break, militants, officer, praise, david, security, rohingya, punch |
obama, stand, victims, trump, barcelona, michelle, families, promise, daughter, shoot |
| 13 |
night, orphaned_annie, culture, thomaswictor, femalesfortrump, kayhair, clean, jimlibertarian, movie, brain |
northkorea, report, breakingnews, brother, saudi, salman, mohamed, appoint, years, wahhabism |
donald, trump, trumprussia, resist, theresistance, approval, office, president, leave, shame |
| 14 |
corruption, congress, raise, credibility, amaze, unpunished, return, global, politicize, realize |
cartoon, earth, respect, washington, russian, criticize, mccain, trump, airforce, indian |
mueller, america, afghanistan, trump, interest, stupid, security, grand, phoenix |
| 15 |
hannity, break, steve, bannon, folks, trump, terrorists, update, resign, assassination |
politics, facebook, peace, neonazis, region, usledcoalition, throw, special, syria, conflict |
bannon, trump, congress, steve, surprise, facts, gorka, truth, miller, picture |
| 16 |
chelsea, handler, christiec, presidenttrump, trump, general, street, charlottesville, veterans, sharia |
freepalestine, sanaa, airstrikes, congress, include, relations, apartheid, trump, israel, blame |
people, texas, trump, trumpresign, americans, mcconnell, harvey, hurricane, support, transgender |
| 17 |
block, learn, train, gregoriodownlow, friends, drive, excuse, blasio, children, senate |
realiran, iranian, zionism, train, province, small, record, syria, barack, hospital |
magazine, cover, eclipse, obamacare, trump, directly, repeal, correct, photo, fakenews |
| 18 |
miller, remember, senator, stephen, service, thomaspaine, ms_erika, company, gorka, election |
center, honor, kennedy, spray, yemeni, attend, question, fighters, flood, protesters |
- |
| 19 |
debalwaystrump, corrupt, russia, congress, trump, proof, dossier, thugs, mueller, human |
zionist, regime, children, space, yemen, followers, members, village, saudi, ambassador |
- |
| 20 |
trump, cernovich, attorney, loser, tucker, celebrity, globalist, workers, hrtablaze, source |
eclipse, tehran, tweet, media, people, science, interest, solareclipse, birthday, solar |
- |
| 21 |
emmss, interest, russian, conservatives, blast, party, perfect, democratic, ajaforcongress, waynedupreeshow |
korea, north, china, nuclear, explain, clothe, unite, prison, moment, thenatural |
- |
| 22 |
lynch, clinton, comey, tarmac, loretta, criminal, happen, justice, debesstrs, tragedy |
trump, press, front, liberty, arpaio, pardon, sanction, putin, russia, sessions |
- |
| 23 |
office, impeach, zakzale, trump, scaramucci, crazy, disavow, worry, slave, the_trump_train |
animals, forget, human, stand, shoot, return, accuse, blackandwhite, close, victory |
- |
| 24 |
lissla, mueller, follow, robert, terrebehlog, dirty, donate, voiceshumanity, break, decision |
leaders, protest, democratic, thousands, shutdown, trump, pence, phoenix, tower, liberty |
- |
| 25 |
white, charlottesville, supremacists, kelly, trump, michael, fakenews, police, americanvoterus, moore |
reason, fakenews, general, visit, heart, nicholson, supporters, trump, australia, roboinsta |
- |
| 26 |
theresistance, special, potus, understand, trumptrain, eissolomon, chron, stacylstiles, spend, youtube |
liberate, iraqi, learn, jason, impact, massive, postcard, force, friends, soldier |
- |
| 27 |
share, illegals, firemcmaster, liberal, collude, melania, abuse, funny, lawyer, pathetic |
black, wildlife, picture, august, palestinians, paint, friday, create, favorite, woman |
- |
| 28 |
fraud, texas, sessions, voter, tweet, twitter, judge, monuments, refuse, virginia |
prince, crown, mohammed, saudi, commander, dance, chief, release, sleep, salman |
- |
| 29 |
trump, president, video, antifa, water, supporter, maxine, statement, charlottesville, break |
arrest, follow, force, refugees, offer, turkish, minutes, station, afghanistan, pakistan |
- |
| 30 |
acosta, illegal, harvey, hurricane, followers, rubysayzz, stockmonsterusa, nowplaying, trump, throw |
leave, climatechange, yemenis, britain, press, massacre, resistance, front, liberty, write |
- |
| 31 |
press, supremacy, respect, unmask, white, erase, compare, elections, emerge, close |
amaze, infect, short, memory, press, liberty, front, young, cholera, americans |
- |
| 32 |
governor, respond, months, murder, trump, outrage, switch, movement, korea, energy |
early, donald, palestine, happen, dementia, navarro, opinion, abuse, trump, press |
- |
| 33 |
disgraceful, politicians, terrorism, foreign, congratulations, weekend, ridiculous, policy, michelle, reason |
assad, america, control, countries, leader, domestic, holiday, agreement, afghanistan, mutual |
- |
| 34 |
obamacare, repeal, agree, cadens, canden, statues, mcconnell, confederate, trump, americans |
raqqa, syria, coalition, hurricane, civilians, strike, major, whitehouse, harvey, press |
- |
| 35 |
nuclear, message, swamp, music, obama, trump, north, korea, northkorea, mattis |
yemen, humanitarian, saudi, demand, cholera, arabia, officials, rouhani, coast, inauguration |
- |


STEP COACHING CLASS
BIOLOGY YOUTUBE VIDEOS
Human Eye
Animal Cell
Animal Tissue
Balancing of Inner Ear
How the Sodium Potassium Pump Works
Nitrogen Cycle
Osmosis
Plant Tissues
Tooth Structure
Nitrogen Cycle
Nitrogen Cycle
Nitrogen Cycle
Nitrogen Cycle
Nitrogen Cycle
Nitrogen Cycle


about me
My name is David Mathaga and I am tech enthusiast and an avid lover of the arts and history.
I went to school in Alliance Highschool and went on to graduate in Mechanical Engineering from the University of Nairobi.
I decided to take a class in programming to link my love for computers and tech with my career path of engineering hoping something good will come out of it,something beneficial to both my community and myself.
projects
- Project cookie
- Hotel dummy
- My first website
This was a practice project where i was learning some html and css elements.It used html and css
This was a project where i was practicing hover and transition additions to css.It used html and css
This was a project where i was able to impliment everything I had learnt on html and css.It used html and css


Hello everyone, let me quick introduce myself.
My name is Kate, I'm 25 years old, originally I'm from Ukraine (if someone doesn't know Ukraine it's a huge country
in Europe :).
I moved to US 3 years ago. First I came to Alaska and after few month I moved to Seattle.
In Ukraine I finished Banking University, but actually never worked at the bank. After University because of war I was forced to move, but this is not sad story of my life. I love US and happy to be here..I love traveling and if you too, GO do it together!!!
Regarding work experience, I started working as a student. And during all this years I tried myself in different spaces. First job I got in jewelry company, first as a seller and after as Customer relations manager. When I came to US I use to work at fish company, few schools, retailers and also Blueprint which is Technology company.
After years jumping from one space to another I decided that I want to do something cool. I here I am.


Hitachi understands the importance of standardization to make the world seamlessly connected, and strongly supports W3C's activities.
Hitachi expects that standardization of Web of Things enables easy integration across various Things and IoT platforms. We create a tool for rapid application development using Node-RED, called Node generator.
Node generator is command line tool to generate Node-RED node modules from several various sources including Thing Description of Web of Things. Using this tool, node developers can dramatically reduce their time to implement Node-RED node modules.


Text Conversion
Text:
Used text:
Character values:
Sum of values:
Cross sum of values:
Iterated cross sum of values:
Coordinate Conversion and Projection
Start:
Distance:
meters
Direction:
°
Target:
Summary:
Start:
Target:


HARRIET THE SPY
A film review by L. O'Connor
Copyright 1996 L. O'Connor
I had high expectations of director Bronwen Hughes, having read Louise Fitzhugh's quirky, insightful children's book no fewer than twenty-six times since the age of eight. The book, published in 1964, bears these irresistible words: "The zany adventures of a child spy." Director Hughes, producer Marykay Powell, and the screen writers do not disappoint: the film is refreshingly imaginative and sensitive, from casting to sound- track to characterisation. Just as author Fitzhugh credits her young readers with intelligence, Hughes presents us with a fully believable Harriet. Eleven-year-old Michelle Trachtenberg is an intense, bright-eyed, intelligent young actor with a wide experssive range and an arresting credibility.
Harriet is in Grade 5 or 6 and lives in New York City, the only child of uninvolved parents, whose true caregiver is her nanny, Golly (Rosie O'Donnell). Golly's function is more that of a mentor, and behind her stern exterior we know immediately that she takes Harriet's individuality and ambition to become a writer seriously.
Nothing Harriet sees goes unnoticed -- or unrecorded in her spy notebook, marked "PRIVATE" -- from thoughtful musings on the characters and antics of her New York neighbourhood (the movie was filmed in Toronto, quite convincingly) to scathingly accurate commentaries on her classmates, friends, family, neighbours and teachers. The singular child spy has two remarkable friends: Sport (Gregory Smith), who at age eleven is the capable caretaker of his "starving artist" writer father, and Janie (Vanessa Lee Chester), a young Marie Curie. But the most influential person in Harriet's life -- and Harriet knows it -- is certainly Golly, who sees to it that Harriet is given ample opportunity to explore, observe, and record. Golly is Harriet's source of wisdom and encouragement, and delivers pithy one-liners: "A good spy never gets caught." "You're an individual, and that makes people nervous." When Harriet's parents fire Golly, Harriet is on her own, and pursues her "spy route" with redoubled energy.
Harriet's spy route continues to our delight (with an unforgettable cameo appearance by Eartha Kitt) until, one day, Harriet's secret notebook is found by the hateful Marion Hawthorne, and each classmate finds himself or herself skewered in writing by Harriet's "dossiers", even Sport and Janie, who too turn against Harriet in an affecting scene. Even the quality of light in the film changes as Harriet's life is turned upside down. Harriet, always an outsider, now finds herself completely shunned. She turns inward again; What would Golly say?
Harriet's classmates form a "Spy Catchers' Club" to torment Harriet and follow her on her spy route, and Harriet finally retaliates by targeting each classmate and exposing or using a conceit or a vulnerability: she knows all, because she has observed them all. Hostilities escalate -- director Hughes "tells it like it is" in the often-ruthless world of children -- and Harriet's frantic parents finally take her to a psychologist (whom Harriet is forced to admire because he, too, keeps copious notes!), and her notebook is taken away.
Just as Harriet declares "I have nothing left to lose," Golly reappears for a visit and solemnly tells Harriet what she must do: apologise, and lie! Harriet's strong character is revealed as she sincerely attempts to tell her friends she is sorry. "Good friends", in Golly's words, "are one of life's blessings. Don't give them up without a fight."
Sport and Janie soon lose interest in the petty hierarchies of the Spy Catchers' Club, and events finally turn around when class elections are held for the position of class newspaper editor, for which Harriet, despite the still-hostile environment, is nominated.  Harriet is able to conclude: "The truth is important, and so are your friends... if you can have both, it's a good life."
The film has captured the atmosphere and the wisdom of the book, of equal charm for child and adult viewers. It is a delight to see a film about individuality and integrity which never misses a beat in telling, with humour and depth, a story of an exceptional girl. The casting is faithful to the spirit of the book, and the soundtrack is energetic and upbeat.
I would recommend "Harriet the Spy" to viewers of all ages.
reviewed by L. O'Connor
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


I'm web designer & front-end developer with 6 years of professional experience. I'm interested in all kinds of visual communication, but my major focus is on designing web, mobile & tablet interfaces. I also have skills in other fields like branding, icon design or web development.
There are tough coding problems to be solved everywhere. I look forward to any challenge within the developer community. It is my goal to work along side passionate and brilliant individuals bringing solutions to many problems.
In regards to experience, I have worked with a variety of technologies but my background also includes IT, public safety, business administration, agriculture business, and project management.
I strongly believe in building exceptional projects and ensuring that my work is truly something of value. More than just code.
In regards to experience, I have worked with e-commerce based websites for five years.
To prevent cyber based threats I constantly research and remain in tune with todays standards.


Publishing
We are a registered publisher that actively places music into film and tv spots.
Artist development requires providing artists many avenues to expose their art and so we are always looking to expand our library to service licensing opportunities.
So take a listen to our current talent, or apply to become part of our team!
Recording
The key factor in attracting fans and licensing to your music is the sound! The song has to sound like it deserves attention. A lot of that sound has to do with the way its recorded.
Everybody has gear, but not everybody has the right gear for the right moment, nor do they really understand how to use it.
Live The Dream
Artist Portal
Introducing FANCATCHER - the true tool for Artist Development! A teaching platform that also provides you tools to attract and engage your customer - the fan!
We have built a complete end-to-end tool that will not only show you HOW to get new fans, but WHERE to find them and WHAT to do to keep them.
And finally, we will show you WHEN its time to consistently keep your fans hearing from you! You said you want to put your music "out there" -- are you ready?
Samples & Loops
If you're a producer looking for new sounds for your productions, we are constantly coming up with fresh ideas to keep you sounding amazing and creative.
We are always expanding our library with fresh material from our staff producers around the globe. Take a listen!
Mixing & Mastering
A good song is made great with a great mix. For us, the mixing process is more than just EQ and balancing. You have to know the genre and what is expected in that genre to make a "radio-ready" mix! Our expertise will provide new life to your masterpiece! And for these prices, you really cannot beat the value!


A SMS containing a confirmation code was sent to your phone.
Please, enter the code below
Bitcoins will be immediately sent from your wallet to Glidera. Fiat will be deposited in your bank account in 4-6 business days.
A transfer has been initiated to your bank account and should arrive in 4-6 business days.


extlinux(1) extlinux(1) NAME extlinux - install the SYSLINUX bootloader on a ext2/ext3 filesystem SYNOPSIS extlinux [options] directory DESCRIPTION EXTLINUX is a new syslinux derivative, which boots from a Linux ext2/ext3 filesystem. It works the same way as SYSLINUX, with a few slight modifi‐ cations. It is intended to simplify first-time installation of Linux, and for creation of rescue and other special-purpose boot disks. The installer is designed to be run on a mounted directory. For example, if you have an ext2 or ext3 usb key mounted on /mnt, you can run the fol‐ lowing command: extlinux --install /mnt OPTIONS -H, --heads=# Force the number of heads. -i, --install Install over the current bootsector. -O, --clear-once Clear the boot-once command. -o, --once=command Execute a command once upon boot. -M, --menu-save=label Set the label to select as default on the next boot -r, --raid Fall back to the next device on boot failure. --reset-adv Reset auxiliary data. -S, --sectors=# Force the number of sectors per track. -U, --update Updates a previous EXTLINUX installation. -z, --zip Force zipdrive geometry (-H 64 -S 32). FILES The extlinux configuration file needs to be named extlinux.conf and needs to be stored in the extlinux installation directory. For more information about the contents of extlinux.conf, see syslinux(1) manpage, section files. BUGS I would appreciate hearing of any problems you have with SYSLINUX. I would also like to hear from you if you have successfully used SYSLINUX, especially if you are using it for a distribution. If you are reporting problems, please include all possible information about your system and your BIOS; the vast majority of all problems reported turn out to be BIOS or hardware bugs, and I need as much infor‐ mation as possible in order to diagnose the problems. There is a mailing list for discussion among SYSLINUX users and for announcements of new and test versions. To join, send a message to major‐<EMAIL_ADDRESS>with the line: SEE ALSO syslinux(1) SYSLINUX for ext2/ext3 filesyste18 December 2007 extlinux(1)


Welcome to Dynamic IPython’s documentation!¶
- date
September 14, 2020
Startup Scripts¶
This repository hosts startup scripts that can be used during IPython’s startup.
The scripts add well over 1000 aliases to the namespace, import commonly used
modules, instantiate exception hooks from cgitb
, format a traceback
,
import readline to add additional keybindings as well as checking for pyreadline
for Windows users, lex documents with the pygments
library and stylize the
REPL as a result, add multiple application specific loggers, and more.
Heavy use of prompt_toolkit
and Jedi’s respective APIs are utilized here.
As both libraries as well as pygments are explicit dependencies of IPython, no additional installation is required for those features.
Specifically, new completers are added to the shell to handle fuzzy completion as well as autocompletion of paths and executables.
Portability¶
Portability was a major factor while writing these scripts.
Therefore, any script should work on:
Ubuntu
Android
Windows 10
On Windows 10, the scripts have been primarily tested in powershell windows or in a shell with either ConEmu or Cmder.
As a result, there may be unexpected behavior that arises when running the following scripts while within in an unmodified cmd shell.
Motivation¶
The intent was to create a system that worked on any relatively modern platform.
I regularly use IPython
as a system shell in comparison to the
typical Bash shell that Unix OSes provide. While a terminal provides a
huge number of powerful commands and the ability to pipe them together,
Bash still has a number of inconsistencies and oddities in its behavior.
Installation¶
This repository can be installed in the following manner.:
python setup.py build
pip install -U -e .
However, that unfortunately assumes one has admin access to wherever pip installs files globally, and that the python command points to python3.7. In most cases it does not.
If one has pipenv installed, an easier installation could be
pipenv install -e .
If a non-pipenv installation is desired for some reason, a fully specified installation could look like.
python3 setup.py build
python3 -m pip install -U --user pip -e .
As one can see this gets complicated very quickly, and as a result, installation via pipenv is the recommended method.
See Also¶
For commands that are more related to the interactive aspect of the shell, see the following.
In [1]: from IPython import get_ipython
In [2]: _ip = get_ipython()
In [3]: help(_ip) # doctest: +SKIP
In [4]: dir(_ip): # doctest: +SKIP
Which features descriptions of functions relevant to startup such as
IPython.core.interactiveshell.register_magic_function()
and literally
every option available through the %config
magic.
In addition, there’s an abundance of documentation online in the form of rst docs and ipynb notebooks.
Table of Contents¶
Startup¶
The first script to run invokes %rehashx
which initializes
IPython
with all of the commands that the system shell knows.
By invoking %rehashx
at the beginning of startup, all system commands
are added as well, which regularly adds well over 1000 commands to the shell.
The IPython team cleverly remembers to also check the environment variable
PATHEXT
on Windows devices as it indicates to the system which
files are executable without requiring the typical Unix file permissions
system.
Before delving into the startup files, the API for the main IPython config file will be discussed.
This is simply a heavily configured version of the file that’s generated when
ipython --generate-config
is run on the command line.
As a result, it heavily utilizes the traitlets
module.
IPython Config API¶
-
exception
NotInIPythonError
(*args, **kwargs)[source][source]¶ Bases:
default_profile.ipython_config.UsageError
Error raised when a magic is invoked outside of IPython.
-
conditional_editing_mode
()[source][source]¶ Execute this function to enable the emacs editing mode on Windows and vi only in tmux.
IPython-specific Sphinx extensions.¶
The default_profile.sphinxext
package.
Imports the modules found in the current directory and utilizes
pkgutil
and pkgutil.extend_path()
to extend the packages __path__
parameter.
It only imports the modules below if this repository has been installed.
If this weren’t true, then starting IPython without this package installed
would emit ImportError
on startup, which would be frustrating for
users.
Extensions¶
In addition this repository handles a growing number of IPython extensions.
Some of the bundled extensions provide a more usable PAGER
for users on
Window than the one provided by pydoc
.
Here are the varying %magic
extensions that are bundled with this
portion of the repository.
Continue reading with the pandas extension at Pandas CSV.
Utilities¶
The modules contained in this package are, generally speaking, a collection of scripts that I’ve found useful while working with IPython, but that unfortunately haven’t been fleshed out enough.
They’re still all useful in their current state and when the user is running IPython interactively, but none of the scripts haven’t been fleshed out to the extent that they could be easily changed to IPython extensions.
Goals¶
Currently the module aims to:
Create consistent
logging.Logger
objectsMake a better pager on Windows
Create a collection of classes that can more easily remove platform-specific issues that continue to arise.
In addition, configure a module-wide logger by equating logging.BASIC_FORMAT
with a pre-determined template string like so:
>>> logging.BASIC_FORMAT = '%(asctime)s : %(levelname)s : %(message)s'
>>> UTIL_LOGGER = logging.getLogger('default_profile.util')
>>> UTIL_LOGGER.setLevel(logging.WARNING)
The submodules contained in this package are as follows:


The Markdown Abbreviation Extension adds the ability to define abbreviations.
Specifically, any defined abbreviation is wrapped in an
tag.
The Abbreviation extension is included in the standard Markdown library.
Abbreviations are defined using the syntax established in PHP Markdown Extra.
Thus, the following text (taken from the above referenced PHP documentation):
The HTML specification
is maintained by the W3C.
*[HTML]: Hyper Text Markup Language
*[W3C]: World Wide Web Consortium
will be rendered like so:

The HTML specification
is maintained by the W3C.

From the Python interpreter:
>>> import markdown
>>> text = """
... Some text with an ABBR.
...
... *[ABBR]: Abbreviation
... """
>>> html = markdown.markdown(text, ['abbr'])
To use with other extensions, just add them to the list, like this:
>>> html = markdown.markdown(text, ['abbr', 'footnotes'])
Abbreviations can also be called from the command line using Markdown's -x
parameter, like so:
markdown.py -x abbr source.txt > output.html


Protesters March Against Islamophobia in Paris - Video
Activists are holding a rally against Islamophobia in Paris, following a call from the Collective Contre l’Islamophobie in France (CCIF), in the wake of the attack against a mosque in Bayonne on 28 October.
On 28 October, an 84-year-old man identified as Claude Sinke tried to set the mosque's doors on fire and shot two people who tried to stop him.
He was arrested by police while attempting to flee. In 2015, Sinke was a candidate for the right-wing National Rally political party — previously known as the National Front — in a regional election.
Follow Sputnik feed to find out more.


Tyler Wians
CSC 317: Computer Networks
Home → Graded Exercise #1
Wireshark Lab Report
Book Questions
Question
Answer
Question
Answer
Questions
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer
Question
Answer


Chapter 11 Binary Dependent Variable Models
11.1 Seminar
11.1.1 Required Packages
Let’s start by loading the required packages:
library(foreign)
library(texreg)
library(lmtest)
library(sandwich)
Clear the environment
rm(list = ls())
11.1.2 Loading Data
We will be using data from the Afrobarometer (a public attitude survey on democracy and governance in more than 35 countries in Africa) to investigate whether a political candidate can utilize his wife’s ethnicity to garner coethnic support. This is linked to a broad research theory which implies that voters in Africa prefer to vote for candidates of their own ethnic group, and that if a presidential candidate marries a non-coethnic wife, this may broaden their electoral appeal to other ethnic groups.
We will focus only African democracies where the president and wife are not of the same ethnicity are considered (i.e., the president and wife are not coethnic with one another). We will investigate whether voters are more likely to vote for the a president when the voter shares the same ethnicity as the president’s wife.
First, let’s load the data directly from GitHub:
afb <- read.csv("https://raw.githubusercontent.com/UCLSPP/datasets/master/data/afb_class.csv")
The table below gives an overview of the variables included in the data.
| Variable | Description |
|---|---|
country |
A character variable indicating the country of the respondent |
wifecoethnic |
1 if respondent is same ethnicity as president’s wife, and 0 otherwise |
oppcoethnic |
1 if respondent is same ethnicity as main presidential opponent, and 0 otherwise |
ethnicpercent |
Respondent’s ethnic group fraction in respondent country |
distance |
Distance between respondent’s home and the home city of the president (measured in hundreds of miles) |
vote |
1 if respondent would vote for the president, 0 otherwise |
Now take a look at the first few observations to see what the dataset looks like
head(afb)
country wifecoethnic oppcoethnic ethnicpercent vote distance
1 benin 1 1 0.4173623 1 5.449764
2 benin 1 1 0.4173623 0 18.510687
3 benin 1 1 0.4173623 0 26.370297
4 benin 1 1 0.4173623 0 21.012341
5 benin 1 1 0.4173623 0 22.238316
6 benin 1 1 0.4173623 1 1.822167
11.1.3 Linear regression with a Binary Dependent Variable
Before moving on to the new model, we can illustrate some of the shortcomings of the linear regression model when working with binary outcome variables.
Let’s run a linear regression (here, a linear probability model) where vote
is our dependent variable, and distance
is our independent variable. Try doing this yourself before revealing the solution code below.
linear_mod <- lm(vote ~ distance, data = afb)
screenreg(linear_mod)
========================
Model 1
------------------------
(Intercept) 1.33 ***
(0.01)
distance -0.06 ***
(0.00)
------------------------
R^2 0.70
Adj. R^2 0.70
Num. obs. 4552
RMSE 0.27
========================
*** p < 0.001, ** p < 0.01, * p < 0.05
The model shows that there is a strong and significant bivariate relationship between distance and vote choice for the president. Specifically, the model suggest that increasing the distance between the respondent and the president’s home city by 100 miles decreases the probability that the respondent will vote for the president by 6 percentage points on average.
As we discussed in lecture, however, the linear probability model can lead to some odd conclusions with regard to fitted values. Let’s plot the two variables above, and include the estimated regression line.
plot(
x = afb$distance,
y = afb$vote,
pch = 19,
col = "grey",
xlab = "Distance",
ylab = "Vote for the president",
ylim = c(-.5, 1.5),
frame.plot = F)
abline(linear_mod, lwd = 3)
As we can see from the plot, because the functional form of the linear probability model is linear, the estimated relationship suggests that for respondents with a distance
value greater than about 23 have a negative probability of voting for the president, and respondents with a distance
value less than about 5 have a probability of voting for the president that is greater than 1.
<IP_ADDRESS> Adjusted Standard Errors in the Linear Probability Model
Now create a plot of the residuals from the model on the Y-axis, and the distance
variable on the X-axis. Try this yourself before revealing the code below.
plot(
x = afb$distance,
y = residuals(linear_mod),
pch = 19,
col = "grey",
xlab = "Distance",
ylab = "Residuals",
frame.plot = F)
abline(h = 0, lwd = 3)
We can see from this plot that the linear probability model is always heteroskedastic – the errors are not evenly distributed around zero for all values of distance
.
Because of this problem, we now adjust the standard errors to be heteroskedasticity robust.
corrected_errors <- coeftest(linear_mod, vcov = vcovHC(linear_mod))
screenreg(list(linear_mod,corrected_errors))
===================================
Model 1 Model 2
-----------------------------------
(Intercept) 1.33 *** 1.33 ***
(0.01) (0.01)
distance -0.06 *** -0.06 ***
(0.00) (0.00)
-----------------------------------
R^2 0.70
Adj. R^2 0.70
Num. obs. 4552
RMSE 0.27
===================================
*** p < 0.001, ** p < 0.01, * p < 0.05
In this instance, the adjustment did not change our substantial conclusion. However, we still always need to adjust standard errors when we estimate the linear probability model.
<IP_ADDRESS> Classification
Our binary variable is either 0 or 1. With the linear probability model, we predict the underlying (and fundamentally unobserved) probability that the outcome is 0 or 1. In order to decide whether an outcome is 0 or 1, we follow a simple rule: Every outcome with a probability of greater or equal 0.5 is assigned a 1 and a 0 otherwise. First, we create a new variable called lm_yhats
. Those are our model predictions or fitted values. They are predicted probabilities that the outcome is 1 - with the downside that we can get predictions outside the 0 to 1 interval.
# predicted probabilities
afb$lm_yhats <- linear_mod$fitted.values
summary(afb$lm_yhats)
Min. 1st Qu. Median Mean 3rd Qu. Max.
-0.8084 0.1974 0.5875 0.5464 0.8928 1.3344
Let’s turn our predictions into outcomes of either 0 or 1 using the ifelse()
function. The first argument of the function is a logical condition that is true or false for every observation that is evaluated. The second argument specifies what to do if the condition is true and third argument specifies what to do if the condition is not met (false).
# expected values
afb$exp.vals <- ifelse( afb$lm_yhats >= 0.5, yes = 1, no = 0 )
table(afb$exp.vals)
0 1
2066 2486
We predict 2066 zeroes and 2486 ones. How good is this. We cannot use R^2 as a model fit statistic for models with binary dependent variables. It is impossible that all values are on the regression line. Let’s examine the outcome variable vote
first.
summary(afb$vote)
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000 0.0000 1.0000 0.5464 1.0000 1.0000
The mean is ~0.55. Therefore, 55 per cent of the respondents would vote for the president. It also means that a classification model must be better than predicting 55 per cent of the outcomes correctly. Otherwise, it is no better than the naive guess.
What is the naive guess? It is simply the modal category. In our case, it is 1 because 55 per cent of the respondents would vote for the president and 45 would not.
If our model does not predict more than 55 per cent of outcomes correctly, it makes no contribution. We must always pass this minimum test. Let’s compare actual outcomes to our expected values (the predictions from our model).
out.table <- table(prediction = afb$exp.vals, truth = afb$vote)
out.table
truth
prediction 0 1
0 1922 144
1 143 2343
On the diagonal, we see the correct predictions and on the off-diagonal, we see the errors. If we sum up the diagonal and divide by the total, we get the per cent correctly classified. Recall, it must be larger than 55 per cent.
# per cent correctly classified
cc.lm <- sum(diag(out.table)) / sum(out.table)
cc.lm
[1] 0.9369508
The model does extremely well. We correctly classify 94 of all cases. A substantial improvement on the naive guess. Let’s move on and compare our linear model to the logistic regression approach.
11.1.4 Logistic Regression Model
We use the generalized linear model function glm()
to estimate a logistic regression. The syntax is very similar to the lm
regression function that we are already familiar with, but there is an additional argument that we need to specify (the family
argument) in order to tell R that we would like to estimate a logistic regression model.
| Argument | Description |
|---|---|
formula |
As before, the formula describes the relationship between the dependent and independent variables, for example dependent.variable ~ independent.variable In our case, we will use the formula: vote ~ wifecoethnic + distance |
data |
Again as before, this is simply the name of the dataset that contains the variable of interest. In our case, this is the dataset called afb . |
family |
The family argument provides a description of the error distribution and link function to be used in the model. For our purposes, we would like to estimate a binary logistic regression model and so we set family = binomial(link = "logit") |
We tell glm()
that we’ve binary dependent variable and we want to use the logistic link function using the family = binomial(link = "logit")
argument:
logit_model_1 <- glm(vote ~ wifecoethnic + distance,
family = binomial(link = "logit"), data = afb)
screenreg(logit_model_1)
===========================
Model 1
---------------------------
(Intercept) 11.66 ***
(0.42)
wifecoethnic -1.36 ***
(0.17)
distance -0.79 ***
(0.03)
---------------------------
AIC 1364.65
BIC 1383.92
Log Likelihood -679.33
Deviance 1358.65
Num. obs. 4552
===========================
*** p < 0.001, ** p < 0.01, * p < 0.05
Interpreting the output of a logistic regression model is less straightforward than for the linear model, because the coefficients no longer describe the effect of a unit change in X on Y. Instead, the direct interpretation of the coefficient is: a one unit change in X is associated with a \(\hat{\beta}\) change in the log-odds of Y, holding constant other variables. Here, the coefficient on wifecoethnic
is equal to -1.36, implying that the log-odds of voting for the president are 1.36 lower when the respondent has the same ethnicity as the president’s wife, holding constant distance.
The interpretation of the significance of the coefficients remains unchanged from the linear regression model. For example, the standard error for the coefficient on wifecoethnic
is 0.17, and the test statistic is therefore -1.36/0.17 = -8. This is much greater than the critical value of any conventionally used \(\alpha\)-level and so we can be sure that this result is statistically significant. We will speak more about statistical inference for logit coefficients next week.
11.1.5 Odds-ratios
Differences in the log-odds, however, are difficult to interpret substantively. There are two main approaches to describing the substantive relationships that emerge from a logistic regression model. 1) odds-ratios, and 2) predicted probabilities.
Converting log-odds differences to odds-ratios is very straightforward. As the log function is the inverse of the exponential function, we can simply exponentiate the coefficient associated with wifecoethnic
:
beta_wifecoethnic <- coef(logit_model_1)[["wifecoethnic"]]
exp(beta_wifecoethnic)
[1] 0.2556929
And we can do the same for the coefficient associated with distance
:
beta_distance <- coef(logit_model_1)[["distance"]]
exp(beta_distance)
[1] 0.4539435
We can then interpret the odds-ratios as follows:
- When the respondent shares the same ethnicity as the president’s wife the odds of voting for the president are multiplied by 0.26, holding constant the distance between the respondent and the president’s home city (i.e. they decrease by 74%)
- Increasing the distance between the respondent and the president’s home city by 100 miles, holding constant whether the respondent shares the same ethnicity as the president’s wife, multiplies the odds of voting for the president by 0.45, (i.e. the odds decrease by 55%)
- In general, when X increases by one unit, the odds of the outcome \(Y = 1\) are multiplied by \(exp(\hat{\beta})\), holding other factors constant
11.1.6 Predicted probabilities
Thinking in terms of odds may not be much better than thinking in terms of log-odds, and so often the most useful discussion of the substantive effect sizes is in terms of predicted probabilities.
We can use the predict()
function to calculate fitted values for the logistic regression model, just as we did for the linear model. Here, however, we need to take into account the fact that we model the log-odds that \(Y = 1\), rather than the probability that \(Y=1\). The predict()
function will therefore, by default, give us predictions for Y on the log-odds scale. To get predictions on the probability scale, we need to add an additional argument to predict()
: we set the type
argument to type = "response"
.
For example, if we would like to calculate the predicted probability of voting for the president for a respondent who shares the same ethnicity as the president’s wife, and lives 1000 miles from the president’s home city, we could use:
pred_prob_1 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 1, distance = 10), type = "response")
pred_prob_1
1
0.91698
The tells us that the probability of a respondent with these covariate values voting for the president (\(Y=1\)) is 0.92, based on this model.
At home, we want you to estimate the predicted probability for this scenario by doing the transformation yourself. You can compare your results with the code below
# get fitted values using predict function - not transformed back to probabilities
pred_prob_1a <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 1, distance = 10))
pred_prob_1a
1
2.402004
# send the fitted values through the link function
exp(pred_prob_1a) / (1 + exp(pred_prob_1a))
1
0.91698
# get fitted values by hand
pred_prob_1b <- coef(logit_model_1)[1] + coef(logit_model_1)[2] * 1 + coef(logit_model_1)[3] * 10
# below we use as.numeric() only because otherwise R labels the result intercept which it is not
pred_prob_1b <- as.numeric(pred_prob_1b)
pred_prob_1b
[1] 2.402004
## send fitted values through the link function
exp(pred_prob_1b) / (1 + exp(pred_prob_1b))
[1] 0.91698
How does this predicted probability compare to the predicted probability of voting for the president for a respondent who is not coethnic with the president’s wife, and lives 1000 miles from the president’s home city? We can just use the predict()
function again, but specify a different value for wifecoethnic
to use for the prediction:
pred_prob_2 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 0, distance = 10), type = "response")
pred_prob_2
1
0.9773743
Comparing the two predicted probabilities, the model tells us that for respondents who live 100 miles from the president’s home city, sharing the ethnicity of the president’s wife decreases the probability of voting for the president by about 6 points:
pred_prob_1 - pred_prob_2
1
-0.0603943
Notice that this “finding” is the opposite of the prediction from the theory: respondents do not seem to be more likely to vote for the president if they share the same ethnicity as the president’s wife. Of course, here we are dealing with a very simple model with many possible confounding variables that we have not included in the model!
As discussed in lecture, the logistic model implies a non-linear relationship between the X variables and the outcome. To see this more clearly, we can calculate the probability of voting for the president over the entire range of the distance
variable.
## Set the values for the explanatory variables
data_for_predicted_prob <- data.frame(distance = seq(from = 0, to = 34, by = .5),
wifecoethnic = 1
)
Here, we have set the distance
variable to vary between 0 and 34, with increments of .5 units and we have set wifecoethnic
to be equal to 1. We have then put all of these values into a new data.frame
called data_for_predicted_prob
which we will pass to the predict()
function.
# Calculate the fitted values
predicted_probs <- predict(logit_model_1, newdata = data_for_predicted_prob, type = "response")
## Save the fitted values as a new variable in the data_for_fitted_values object
data_for_predicted_prob$predicted_probs <- predicted_probs
Finally, we can plot these values:
plot(
predicted_probs ~ distance, # Specify the formula for the plot (dependent.variable ~ independent.variable)
data = data_for_predicted_prob, # Specify the data to use for the plot
xlab = "Distance", # Specify the X-axis title
ylab = "Probability of voting for the president", # Specify the Y-axis title
frame.plot = FALSE, # The frame.plot = FALSE argument removes the box from around the plot
col = "grey", # The col argument specifies the color
type = "l", # type = "l" will produce a line plot, rather than the default scatter plot
lwd = 3 # lwd = 3 will increase the thinkness of the line on the plot
)
The plot nicely illustrates the non-linear functional form of the logistic regression model. As desired, all of the predicted probabilities now vary between 0 and 1, as the line takes on a distinctive “S” shape. It is clear from this plot that X (distance
) is non-linearly related to the probability that \(Y=1\) (\(P(Y = 1) = \pi\)): the same change in X results in difference changes in \(\pi\) depending on which values of X we consider. For example:
- Increasing
distance
from 5 to 10 leads to a decrease in \(\pi\) of only a very small amount - Increasing
distance
from 10 to 15 leads to a decrease in \(\pi\) of a very large amount
This is why we are unable to interpret the \(\beta\) coefficients from the logistic model as constant increases or decreases in \(\pi\) given a change in X. For any given change in X, the amount that \(\pi\) will change will depend on the starting value of X that we are considering.
Finally, we can also see the non-linearity inherent in the logistic model by calculating the difference in predicted probability between respondents who share the ethnic group of the president’s wife and respondents who come from different ethnic groups than the president’s wife, at different values of the distance
variable. Let’s calculate this difference for distance = 10
and distance = 12
:
prob_coethnic_dist10 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 1, distance = 10), type = "response")
prob_not_coethnic_dist10 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 0, distance = 10), type = "response")
prob_coethnic_dist10 - prob_not_coethnic_dist10
1
-0.0603943
prob_coethnic_dist12 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 1, distance = 12), type = "response")
prob_not_coethnic_dist12 <- predict(logit_model_1, newdata = data.frame(wifecoethnic = 0, distance = 12), type = "response")
prob_coethnic_dist12 - prob_not_coethnic_dist12
1
-0.2042512
The results indicating that, when comparing respondents with values of 10 on the district variable, coethnics of the president’s wife are 6 points less likely to vote for the president than non-coethnics. However, when comparing respondents with values of 12 on the distance variable, coethnics are 20 points less likely to vote for the president. Therefore, this illustrates that in a multiple logistic regression model the change in \(\pi\) in response to even exactly the same change in one X variable depends on the values at which the other X variables are fixed.
11.1.7 Exercises
We will be using some data from a post-referendum survey among people living in Switzerland. The survey was carried out right after the vote on an initiative whether to ban military assault rifles in private households or not. If you would like to get some more background you may consult the wikipedia article on the referendum, here.
You can load the data from GitHub by running the following code
library(foreign)
swiss <- read.dta("https://raw.githubusercontent.com/UCLSPP/datasets/master/data/SwissData2011.dta")
We have access to the following variables:
| Variable | Description |
|---|---|
| VoteYes | 1 if someone voted yes and is 0 if someone voted no. |
| participation | 1 for people that voted and 0 otherwise. |
| male | 1 for men and 0 for women. |
| age | Age in years. |
| LeftRight | Left-Right self placement where low values indicate that a respondent is more to the left. |
| GovTrust | Trust in government. Little or no trust is -1, neither YES nor NO is 0, and +1 if somebody trusts the government. |
| ReligFreq | How frequently does a respondent attend a religious service? Never (0), only on special occasions (1), several times a year (2), once a month (3), and once a week (4). |
| university | Binary indicator (dummy) whether respondent has a university degree (1) or not (0). |
| party | Indicates which party a respondent supports. Liberals (1), Christian Democrats (2), Social Democrats (3), Conservative Right (4), and Greens (5). |
| income | Income measured in ten different brackets (higher values indicate higher income). You may assume that this variable is an interval type measure. |
| german | Binary indicator (dummy) whether respondent’s mother tongue is German (1) or not (0) |
| suburb | Binary indicator (dummy) whether respondent lives in a suburban neighborhood (1) or not (0) |
| urban | Binary indicator (dummy) whether respondent lives in a city (1) or not (0) |
| cars | Number of cars the respondent’s household owns. |
| old voter | Variable indicating whether a respondent is older than 60 years (1) or not (0). |
| cantonnr | Variable indicating in which of the 26 Swiss cantons a respondent lives. |
| nodenomination | Share of citizens in a canton that do not have a denomination. |
| urbanization | Share of citizens in a canton that live in urban areas. |
- Create plots of
age
vsVoteYes
andLeftRight
vsVoteYes
. Add a regression line (from a linear probability model) to the plots - Estimate a model which includes
age
andLeftRight
as predictors, andVoteYes
as the dependent variable - What is the effect of a one-unit increase in
LeftRight
onVoteYes
? Discuss in terms of odds-ratios - What is the effect of a one-unit increase in
age
onVoteYes
? Discuss in terms of odds-ratios - What is the effect on the probability of a “yes” vote of moving from a left-right self placement of 5 to a self placement of 6 for an individual who is 44 years old?
- Calculate and plot the predicted probability of voting yes across the range of the
age
variable for individuals who have a left-right self placement of 5. Do the same across the range of theLeftRight
variable for individuals with an age of 50. - Looking at the other variables in the
swiss
data, which do you think might be important determinants of a “yes” vote in the referendum? Write a short paragraph justifying the importance of 3 of the predictors in theoretical terms. Include the additional explanatory variables you have selected in a new model that also includesage
andLeftRight
. - Provide some predicted probabilities from the model that illustrate the substantive importance of the new variables that you have added


List of Publications
Articles in Conference Proceedings
Funnelselect: Cache-oblivious multiple selection
Gerth Stølting Brodal and Sebastian Wild, Sep 2023
ESA 2023RNA secondary structures: from ab initio prediction to better compression, and back
Eva Onokpasa, Sebastian Wild, and Prudence Wong, Mar 2023
DCC 2023-
William Cawley Gelling, Markus E. Nebel, Benjamin Smith, and Sebastian Wild, Jan 2023
ALENEX 2023 Randomized Communication and Implicit Graph Representations
Nathaniel Harms, Sebastian Wild, and Viktor Zamaraev, Jun 2022
STOC 2022Towards the 5/6-Density Conjecture of Pinwheel Scheduling
Leszek Gąsieniec, Benjamin Smith, and Sebastian Wild, Jan 2022
ALENEX 2022-
Travis Gagie and Sebastian Wild, Jun 2021
CCCG 2021 -
J. Ian Munro, Patrick K. Nicholson, Louisa Seelbach Benkner, and Sebastian Wild, Apr 2021
ESA 2021 -
Bryce Sandlund and Sebastian Wild, Dec 2020
FOCS 2020 Distance Oracles for Interval Graphs via Breadth-First Rank/Select in Succinct Trees
Meng He, J. Ian Munro, Yakov Nekrich, Sebastian Wild, and Kaiyu Wu, May 2020
ISAAC 2020Efficient Second-Order Shape-Constrained Function Fitting
David Durfee, Yu Gao, Anup B. Rao, and Sebastian Wild, Aug 2019
WADS 2019Median-of-k Jumplists and Dangling-Min BSTs
Markus E. Nebel, Elisabeth Neumann, and Sebastian Wild, Jan 2019
ANALCO 2019Sesquickselect: One and a half pivots for cache-efficient selection
Conrado Martínez, Markus Nebel, and Sebastian Wild, Jan 2019
ANALCO 2019Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs
J. Ian Munro and Sebastian Wild, May 2018
ESA 2018Average Cost of QuickXsort with Pivot Sampling
Sebastian Wild, Mar 2018
AofA 2018Quicksort Is Optimal for Many Equal Keys
Sebastian Wild, Jan 2018
ANALCO 2018Analysis of Branch Misses in Quicksort
Conrado Martínez, Markus Nebel, Sebastian Wild, Jan 2015
ANALCO 2015Pivot Sampling in Dual-Pivot Quicksort—Exploiting Asymmetries in Yaroslavskiy’s Partitioning Scheme
Markus Nebel and Sebastian Wild, Jun 2014
AofA 2014Engineering Java 7’s Dual-Pivot Quicksort Using MaLiJAn
Sebastian Wild, Markus Nebel, Raphael Reitzig, and Ulrich Laube, Jan 2013
ALENEX 2013Average-Case Analysis of Java 7’s Dual-Pivot Quicksort
Sebastian Wild and Markus Nebel, Sep 2012
ESA 2012
2023
2022
2021
2020
2019
2018
2015
2014
2013
2012
Journal Articles
A Simple and Fast Linear-Time Algorithm for Divisor Methods of Apportionment
Raphael Reitzig, Sebastian Wild, Feb 2023
Mathematical Programming-
Konstantinos Tsakalidis, Sebastian Wild, and Viktor Zamaraev, Sep 2022
Algorithmica QuickXsort – A Fast Sorting Scheme in Theory and Practice
Stefan Edelkamp, Armin Weiß, and Sebastian Wild, Feb 2020
Algorithmica (2020)Dual-pivot and beyond: The potential of multiway partitioning in quicksort
Sebastian Wild, Jun 2018
it – Information Technology (invited article)-
Raphael Reitzig, Sebastian Wild, Nov 2017
Algorithmica (2018) -
Markus Nebel, Sebastian Wild, and Conrado Martínez, Aug 2016
Algorithmica (2016) Average Case and Distributional Analysis of Dual-Pivot Quicksort
Sebastian Wild, Markus Nebel, and Ralph Neininger, Jan 2015
TALG 11(3), art. 22 (2015)Analysis of Quickselect under Yaroslavskiy’s Dual-Pivoting Algorithm
Sebastian Wild, Markus Nebel and Hosam Mahmoud, Nov 2014
AlgorithmicaJAguc – A Software Package for Environmental Diversity Analyses
Sebastian Wild, Markus Nebel, Michael Holzhauser, Lars Hüttenberger, Raphael Reitzig, Matthias Sperber, and Thorsten Stoeck, Dec 2011
J. of Bioinformatics and Comp. Biology
2023
2022
2020
2018
2017
2016
2015
2014
2011
Books
Entwurf und Analyse von Algorithmen
Markus Nebel, Sebastian Wild, Apr 2018
Springer Vieweg
Theses
Dual-Pivot Quicksort and Beyond: Analysis of Multiway Partitioning and Its Practical Potential
Sebastian Wild, Oct 2016
Ph.D. Thesis-
Sebastian Wild, Aug 2012
Master's Thesis An Earley-style Parser for Solving the RNA-RNA Interaction Problem
Sebastian Wild, Jun 2010
Bachelor's Thesis
Others
A House Divided: Cooperation, Polarization, and the Power of Reputation
Sebastian Wild, Phillip Keldenich, Jann Spiess, Maximilian Schlund, Jano Costard, Jonas Radbruch, Paul Stursberg, and Sándor Fekete, Jul 2023
Research SquareDynamic Optimality Refuted – For Tournament Heaps
J. Ian Munro, Richard Peng, Sebastian Wild, and Lingyi Zhang, Aug 2019
arxivEntropy Trees and Range-Minimum Queries In Optimal Average-Case Space
J. Ian Munro, and Sebastian Wild, Mar 2019
arxivA Practical and Worst-Case Efficient Algorithm for Divisor Methods of Apportionment
Raphael Reitzig, Sebastian Wild, Mar 2017
arxiv


{% extends 'base.html' %} {% block content %}
It looks like you don't have any notifications right now. Please check later.
You currently have {{count}} notification(s). Check them below.
{{ mention.tweet }}


Githawk is the simplest way to read and respond to your GitHub notifications on iOS.
Free Download View Source


White to play 43
pips White=183 Black=112
(CorrectAnswer= 0/0, ErrorScore= 0)
1. Bar/21 18/15* eq: -0.525 30.33% (G: 5.00% B:0.17%) 69.67% (G:28.41% B:0.79%) 2. Bar/18 eq: -0.645 (-0.120) 24.36% (G: 2.65% B:0.08%) 75.64% (G:24.23% B:0.29%) 3. Bar/21 8/5 eq: -0.658 (-0.133) 24.18% (G: 2.71% B:0.08%) 75.82% (G:25.18% B:0.38%) 4. Bar/21 6/3 eq: -0.670 (-0.145) 24.04% (G: 2.61% B:0.08%) 75.96% (G:25.92% B:0.35%) 5. Bar/21 13/10 eq: -0.768 (-0.243) 22.02% (G: 2.37% B:0.08%) 77.98% (G:30.54% B:0.54%)


Calculates auto- and cross-correlation functions and plots an actogram and a smoothing function from a time series to identify and visualize periodic components. Tests presence of anticipated rhythm and estimates rhythm parameters; fits model consisting of multiple rhythmic components to data; performs least squares spectral analysis and other cosinor-based analyses, including population-mean cosinor (PMC) and population-mean cosinor parameter tests (PMCtest).
| Version: | 3.3.3 |
| Imports: | MASS, png, rtf, season, magic, stats, graphics, utils, grDevices, signal, assertr, CombMSC, Hmisc |
| Published: | 2018-07-17 |
| Author: | Cathy Lee Gierke, Ruth Helget, Germaine Cornelissen-Guillaume |
| Maintainer: | Cathy Lee Gierke <leegi001 at umn.edu> |
| License: | GPL-2 |
| URL: | http://z.umn.edu/CATkit, http://www.tandfonline.com/doi/full/10.1080/09291016.2015.1094965 |
| NeedsCompilation: | no |
| CRAN checks: | CATkit results |
| Reference manual: | CATkit.pdf |
| Package source: | CATkit_3.3.3.tar.gz |
| Windows binaries: | r-devel: CATkit_3.3.3.zip, r-release: CATkit_3.3.3.zip, r-oldrel: CATkit_3.3.3.zip |
| OS X binaries: | r-release: CATkit_3.3.3.tgz, r-oldrel: CATkit_3.3.3.tgz |
| Old sources: | CATkit archive |
Please use the canonical form https://CRAN.R-project.org/package=CATkit to link to this page.


Vector is a list, but each item in list defines a different axis. For ex in 2D plain, [x,y] there are two axis x and y. Talking about living being, eyes, nose, ….legs . There are many attribute/dimension. human has 2 legs but cow has 4 in leg axis. Vector has magnitude and direction - If we take only 1 vector a time, i. We can define magnitude by number. But the direction is always relative so the direction will only be shown when there is another vector. Such 3i+4j. 3 x and 4y, x and y are different direction and forms a plain. so 3i+4y gives resulting vector of 3i and 4j vectors.
Axis is called basis vector for ex. 3i+4j is give points in space x to 3 and y to 4 and i,j are axis or basis vector.
3i+4j is Linearly dependent to 6i-9j, they both lie same dimension so linearly dependent. 3i+4j ne to 7w. Here w is different dimension.
AX = Y it tells matrix A is combination of rotation and then sheer stacked in matrix A column which transform X to Y.
Give the factor by which area has changed after transformation. AX=Y. |A| gives factor by which area change in X to Y coordinate system.
AX=Y, How much inverse of A you should apply to get X. It can be negative as well. But what is |A| is 0. This mean, A has linearly dependent columns which reduces the rank of matrix, for example 3d to 2d or 1d, or 2d to 1d etc. After transforming 3d to 2d or 1d it is difficult reshape it original shape.
x.y is x projection over y, which x.ycosθ, magnitude of x projection over y multiplied by y magnitude. a · b = ax X bx + ay X by + az X bz


Our concept is revolutionizing the dust suppression industry using science and innovative technology to improve decision making and effectiveness of product in increasingly unpredictable climatic patterns. Through the current issues that are prevalent in the mining industry, in the context of dust suppression and road stabilization, Ihobe has undertaken an alternative approach in comparison to traditional dust palliatives.
We have identified the core issues from mining corporations and dust suppression companies and integrated these concerns to create a simplistic, cost effective product, called Profit Science Liquid. Dust suppression companies have been viewed as:
To eradicate these issues, a Family of Profit Science Liquid (PSL) was developed around a concept of simplicity and cost efficiency. Our latest technology is a member of our polymer family that has been designed with ultra-hydrophobicity. The suitability and effectiveness of the product allows mine corporations to improve decision making and overall productivity of their operation.