Machine Learning Library (MLlib)
MLlib is a Spark implementation of some common machine learning (ML) functionality, as well associated tests and data generators. MLlib currently supports four common types of machine learning problem settings, namely, binary classification, regression, clustering and collaborative filtering, as well as an underlying gradient descent optimization primitive. This guide will outline the functionality supported in MLlib and also provides an example of invoking MLlib.
Dependencies
MLlib uses the jblas linear algebra library, which itself depends on native Fortran routines. You may need to install the gfortran runtime library if it is not already present on your nodes. MLlib will throw a linking error if it cannot detect these libraries automatically.
Binary Classification
Binary classification is a supervised learning problem in which we want to classify entities into one of two distinct categories or labels, e.g., predicting whether or not emails are spam. This problem involves executing a learning Algorithm on a set of labeled examples, i.e., a set of entities represented via (numerical) features along with underlying category labels. The algorithm returns a trained Model that can predict the label for new entities for which the underlying label is unknown.
MLlib currently supports two standard model families for binary classification, namely Linear Support Vector Machines (SVMs) and Logistic Regression, along with L1 and L2 regularized variants of each model family. The training algorithms all leverage an underlying gradient descent primitive (described below), and take as input a regularization parameter (regParam) along with various parameters associated with gradient descent (stepSize, numIterations, miniBatchFraction).
The following code snippet illustrates how to load a sample dataset, execute a training algorithm on this training data using a static method in the algorithm object, and make predictions with the resulting model to compute the training error.
import org.apache.spark.SparkContext
import org.apache.spark.mllib.classification.SVMWithSGD
import org.apache.spark.mllib.regression.LabeledPoint
// Load and parse the data file
val data = sc.textFile("mllib/data/sample_svm_data.txt")
val parsedData = data.map { line =>
val parts = line.split(' ')
LabeledPoint(parts(0).toDouble, parts.tail.map(x => x.toDouble).toArray)
}
// Run training algorithm
val numIterations = 20
val model = SVMWithSGD.train(parsedData, numIterations)
// Evaluate model on training examples and compute training error
val labelAndPreds = parsedData.map { point =>
val prediction = model.predict(point.features)
(point.label, prediction)
}
val trainErr = labelAndPreds.filter(r => r._1 != r._2).count.toDouble / parsedData.count
println("trainError = " + trainErr)
The SVMWithSGD.train()
method by default performs L2 regularization with the
regularization parameter set to 1.0. If we want to configure this algorithm, we
can customize SVMWithSGD
further by creating a new object directly and
calling setter methods. All other MLlib algorithms support customization in
this way as well. For example, the following code produces an L1 regularized
variant of SVMs with regularization parameter set to 0.1, and runs the training
algorithm for 200 iterations.
import org.apache.spark.mllib.optimization.L1Updater
val svmAlg = new SVMWithSGD()
svmAlg.optimizer.setNumIterations(200)
.setRegParam(0.1)
.setUpdater(new L1Updater)
val modelL1 = svmAlg.run(parsedData)
Both of the code snippets above can be executed in spark-shell
to generate a
classifier for the provided dataset.
Available algorithms for binary classification:
Linear Regression
Linear regression is another classical supervised learning setting. In this problem, each entity is associated with a real-valued label (as opposed to a binary label as in binary classification), and we want to predict labels as closely as possible given numerical features representing entities. MLlib supports linear regression as well as L1 (lasso) and L2 (ridge) regularized variants. The regression algorithms in MLlib also leverage the underlying gradient descent primitive (described below), and have the same parameters as the binary classification algorithms described above.
Available algorithms for linear regression:
Clustering
Clustering is an unsupervised learning problem whereby we aim to group subsets of entities with one another based on some notion of similarity. Clustering is often used for exploratory analysis and/or as a component of a hierarchical supervised learning pipeline (in which distinct classifiers or regression models are trained for each cluster). MLlib supports k-means clustering, arguably the most commonly used clustering approach that clusters the data points into k clusters. The MLlib implementation includes a parallelized variant of the k-means++ method called kmeans||. The implementation in MLlib has the following parameters:
- k is the number of clusters.
- maxIterations is the maximum number of iterations to run.
- initializationMode specifies either random initialization or initialization via k-means||.
- runs is the number of times to run the k-means algorithm (k-means is not guaranteed to find a globally optimal solution, and when run multiple times on a given dataset, the algorithm returns the best clustering result).
- initializiationSteps determines the number of steps in the k-means|| algorithm.
- epsilon determines the distance threshold within which we consider k-means to have converged.
Available algorithms for clustering:
Collaborative Filtering
Collaborative filtering is commonly used for recommender systems. These techniques aim to fill in the missing entries of a user-item association matrix. MLlib currently supports model-based collaborative filtering, in which users and products are described by a small set of latent factors that can be used to predict missing entries. In particular, we implement the alternating least squares (ALS) algorithm to learn these latent factors. The implementation in MLlib has the following parameters:
- numBlocks is the number of blacks used to parallelize computation (set to -1 to auto-configure).
- rank is the number of latent factors in our model.
- iterations is the number of iterations to run.
- lambda specifies the regularization parameter in ALS.
- implicitPrefs specifies whether to use the explicit feedback ALS variant or one adapted for implicit feedback data
- alpha is a parameter applicable to the implicit feedback variant of ALS that governs the baseline confidence in preference observations
Explicit vs Implicit Feedback
The standard approach to matrix factorization based collaborative filtering treats the entries in the user-item matrix as explicit preferences given by the user to the item.
It is common in many real-world use cases to only have access to implicit feedback (e.g. views, clicks, purchases, likes, shares etc.). The approach used in MLlib to deal with such data is taken from Collaborative Filtering for Implicit Feedback Datasets. Essentially instead of trying to model the matrix of ratings directly, this approach treats the data as a combination of binary preferences and confidence values. The ratings are then related to the level of confidence in observed user preferences, rather than explicit ratings given to items. The model then tries to find latent factors that can be used to predict the expected preference of a user for an item.
Available algorithms for collaborative filtering:
Gradient Descent Primitive
Gradient descent (along with stochastic variants thereof) are first-order optimization methods that are well-suited for large-scale and distributed computation. Gradient descent methods aim to find a local minimum of a function by iteratively taking steps in the direction of the negative gradient of the function at the current point, i.e., the current parameter value. Gradient descent is included as a low-level primitive in MLlib, upon which various ML algorithms are developed, and has the following parameters:
- gradient is a class that computes the stochastic gradient of the function being optimized, i.e., with respect to a single training example, at the current parameter value. MLlib includes gradient classes for common loss functions, e.g., hinge, logistic, least-squares. The gradient class takes as input a training example, its label, and the current parameter value.
- updater is a class that updates weights in each iteration of gradient descent. MLlib includes updaters for cases without regularization, as well as L1 and L2 regularizers.
- stepSize is a scalar value denoting the initial step size for gradient descent. All updaters in MLlib use a step size at the t-th step equal to stepSize / sqrt(t).
- numIterations is the number of iterations to run.
- regParam is the regularization parameter when using L1 or L2 regularization.
- miniBatchFraction is the fraction of the data used to compute the gradient at each iteration.
Available algorithms for gradient descent:


Climate change: Sea level rise to affect 'three times more people'
From Antarctica to the Oceans, Climate Change Damage Is About to Get a Lot Worse, IPCC Warns
UN calls for shipping ‘propulsion revolution’ to avoid ‘environmental disaster’
California's new normal: How the climate crisis is fueling wildfires and changing life in the Golden State
Human Disruption of Earth's Oceans and Ice is 'Unprecedented,' Says 'Chilling and Compelling' Climate Report
Global climate conference in limbo after Chile cancels plans to host
NOAA's 2019-20 winter outlook for temperature, precipitation, and drought
EU Commissioner for Climate Action and Energy Miguel Arias Cañete and China’s Special Representative on Climate Change Xie Zhenhua


Sex For Grades: Prof Gyampo ‘breached’ UG code of conduct
The Committee set up to probe Prof. Ransford Gyampo and Paul Butakor, over their alleged involvement in the BBC Sex For Grades Documentary, has found prima facie evidence of breaches of the University of Ghana (UG) code of conduct by the two lecturers.
The two senior lecturers were interdicted in October 2019, after they were captured in the BBC’s African Eye documentary which sought to expose sexual misconduct in universities across West Africa.
The Committee has therefore recommended that the matter be brought before the University’s Disciplinary Committee.
This was contained in a statement issued by Stella A. Amoa, Director of Public Affairs, UG.
According to the statement, the Committee chaired by Justice Vida Akoto-Bamfo, a retired Supreme Court judge, noted in its report to the Vice Chancellor that there was prima facie evidence of misconduct against Prof. Gyampo and Dr. Butakor, contrary to paragraph 6.4 of the Code of Conduct for Academic Staff of the University of Ghana, which stipulates that Academic Staff shall at all times comport themselves in ways that will enhance their image and that of the University.
It added that the Committee further found prima facie evidence of misconduct contrary to Statute 42(1) (e) (ii) of the University of Ghana which states that “no member of the University shall engage in a course of vexatious conduct that is directed at one or more specific individuals, and that is known to be unwelcome.”
It noted that the Vice Chancellor has accepted the Committee’s findings and forwarded to the Disciplinary Committee.


Dear User 2,
You have been invited to join the project My Project as a named finance contact.
You will be providing finance details on behalf of Invite Organisation Name
The project is being led by Lead Organisation 123
Please sign in to accept this invitation. If you haven't used this service before you must create an account.
Yours sincerely,
Innovate UK, part of UK Research and Innovation
Tel: 0300 321 4357
Email: competitions@iuk.ukri.org


new Timeline()
Use the Timeline object to create a schedule of transitions to occur at specified points in time.
To create a new Timeline, create a new variable that is equal to a "new Timeline()". After that, call the addKeyframe() method on that variable to add a keyframe to the timeline. The next step is to call the addStyleChange() method, passing in the target HTML element that needs a change made to, the duration of the CSS transition, the style that should be changed, and the new value of the style. The addStyleChange() can be called any number of times to make multiple style changes to the same target HTML element or different targets.
Once all the styles for that keyframe have been set, you can call the addKeyframe() method again for a different point in time and have that method call followed by addStyleChange(). After all the keyframes and style changes have been added, call the play() method to kick off the playback of the timeline of animations.
To create a new Timeline, create a new variable that is equal to a "new Timeline()". After that, call the addKeyframe() method on that variable to add a keyframe to the timeline. The next step is to call the addStyleChange() method, passing in the target HTML element that needs a change made to, the duration of the CSS transition, the style that should be changed, and the new value of the style. The addStyleChange() can be called any number of times to make multiple style changes to the same target HTML element or different targets.
Once all the styles for that keyframe have been set, you can call the addKeyframe() method again for a different point in time and have that method call followed by addStyleChange(). After all the keyframes and style changes have been added, call the play() method to kick off the playback of the timeline of animations.
- Source:
Example
<!DOCTYPE html>

<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<title>banner example</title>


Register Early Bird NowClick here for hotel information
Early Bird Registration is now open!
The importance of registering early
The FOSS4G event is presented by the non-profit OSGeo Foundation and is organized by a volunteer Local Organizing Committee. Your early bird registration is the largest funding source for this conference. It is vitally important to have early registration to build momentum and to properly plan for the event. Early information on how many people will be attending will help us put together the best possible conference. We have put together a very attractive early bird package that
will save you money and provide other benefits.
Boston is a fabulous and busy place to visit in the Summer time. If you know you’re coming you’ll be well served by registering early and making travel and lodging reservations as early as possible. We expect that our conference hotel block at the
Seaport Hotel - with a fantastic location and very competitive rate - will fill up early. Check out the details below.
The Benefits of Early Bird - Register before May 16, 2017
- Save $150 off the registration price, bringing down the price to attend to $650 from $800. Registration includes: 3 days of conference, conference meals & coffee breaks, Weds evening social, T-shirt and gift bag.
- Get a free ticket to the Thursday evening Gala at the New England Aquarium (a $50 value). Non-early bird registrants will need to purchase a Gala ticket in addition to registration
- Be among the first to have a chance to get a ticket to the Tuesday evening “Ice Breaker” at the Harpoon Brewery. This special brew hall event is "first-come, first-served" as capacity at this venue is limited.
- Take advantage of significant discounts for workshops. The earlier you purchase and the more you purchase the better the deal.
Multiple Events Covered by Registration
During the registration process you will have the opportunity to sign up for several important events that will be happening in parallel and in Boston alongside the main FOSS4G Conference.
- Workshops
- Over 40 hands-on workshops will be held at Harvard University covering a wide variety FOSS4G software and technology topics.
- Workshops will be held on Monday & Tuesday atThe Harvard CGIS
- Co-Located JS.Geo Conference
- JS.Geo is a gathering for those with an enthusiasm for code and maps. In previous gatherings speakers included devs from organizations you know (Carto, Mapbox, Mapzen, ESRI, Cesium, IBM, etc.) as well as indie coders doing creative work
outside the traditional geospatial industry. It's a single day, single track event that moves fast so as to maximize the number of interesting people and ideas.
- JS.Geo registration is exclusive to FOSS4G attendees until July 15th.
- JS.Geo will be held on Tuesday near our conference venue atDistrict Hall
- For more details, please visit the JS.Geo Website
- FOSS4G B2B
- Come see how a variety of businesses and sponsors are leveraging FOSS4G software while also giving back to the FOSS4G community.
- The Business-to-Business session wil be held on Tuesday at our conference venueThe Seaport Hotel & World Trade Center
Costs Table
| Item |
Thru May 16 Early Bird |
After May 16 Full Cost |
| Main Conference Events |
| Full 3 day registration |
$650 |
$800 |
| Single day registration |
$295 |
$350 |
| Thursday night Gala at Aquarium |
Included |
$50 |
| Optional Workshops & Co-located Events |
| Workshop package of 4 |
$250 |
$350 |
| Workshop package of 2 |
$150 |
$200 |
| Single Workshop |
$100 |
$125 |
| JS.Geo conference |
$50 |
| Business to Business event |
$40 |
| Additional Aquarium Gala tickets |
$50 |
Register Early Bird NowClick here for hotel information


SideWall
can connect people already in a community who need jobs and can't afford cars/transit with other members of that community who can rideshare on their way to jobs at similar locations. More people get jobs because more people can commute to the areas that are experiencing economic growth regardless of where they originally live in that city. People find jobs on our job board and can make "connections" with registered profiles/routes on a map that match their job criteria. They then can message other users profiles and work out details.
Jane Doe
Registered Driver
2011 Honda Prius
Home
1234 Lane LN
Detroit, MI, 00000
Work
1234 Street ST
Detroit, MI, 00000


We Are Always Here For You
At JR Techy we value your opinion please do not hesitate to contact us with any questions concerns or comments. They are welcomed and will be handled promptly and with the courteous, and professional customer service that you deserve and expect from us.


| OLD line(s): 69,70
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| OLD line(s): 73
<Description>Qualified capital costs limitation (see instructions)</Description> | NEW line(s): 73
<Description>Qualified costs limitation (see instructions)</Description> |


{% extends "layout_unbranded.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %} Back Calculate State Pension age for QQ123456C State Pension date 8 November 2028 Enter date of birth Day Month Year Calculate Calculate State Pension age for QQ123456C State Pension date 8 November 2028 State Pension age 67 years, 3 months and 2 days Start again Back {% endblock %}
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Microsoft release Windows 10 20H1 Insider Preview Build 19028 to the Fast Ring (changelog)
by SururToday Microsoft released Windows 10 Insider Preview Build 19028 (20H1) to Windows Insiders in the Fast ring.
As Microsoft approaches the end of the testing of the OS update the latest build includes mainly fixes and no new features.
The Windows 10 Build 19028 changelog includes:
General changes, improvements, and fixes for PC
- Microsoft fixed a recent issue that could result in Settings crashing when docking/undocking your device. This issue may have also impacted Action Center launch performance.
- Microsoft fixed an issue impacting the performance of the Printers & Scanners section of Settings loading.
- Microsoft fixed an issue resulting in the Other People section under Storage Settings not displaying the correct size used.
- Microsoft fixed an issue that could result in Windows Update history in Settings saying a Cumulative Update required a reboot, despite it already being installed. This occurred when a Feature on Demand had installed while the cumulative update was originally pending reboot.
- Microsoft fixed an issue that could result in the Photos app crashing when interacting with HEVC images.
Knowns issues
- BattlEye and Microsoft have found incompatibility issues due to changes in the operating system between some Insider Preview builds and certain versions of BattlEye anti-cheat software. To safeguard Insiders who might have these versions installed on their PC, Microsoft have applied a compatibility hold on these devices from being offered affected builds of Windows Insider Preview. See this article for details.
- Microsoft has looking into reports of the update process hanging for extended periods of time when attempting to install a new build.
- Microsoft has heard that Settings still isn’t available outside of launching via the URI (ms-settings:) for some Insiders and are investigating.
- Some Insiders are reporting that after successfully installing printer drivers from the Optional Updates section, the same driver is still showing as available for install. Microsoft has looking into the issue.
- Microsoft has looking into reports of certain external USB 3.0 drives not responding with Start Code 10 or 38 after they’re attached.
Windows 10 Insiders in the Fast Ring can download the update by Checking for Updates in Settings.


Spaces and tabs can not mixed in front of line.
good:
→ →
········
bad:
→····
···· →
Note: in the examples above, spaces and tabs are represented by ·
and →
, respectively, to make the difference visible.
config value:


TeeChart for JavaScript
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SPAWN A Film Review By Jesse A. Kaplan Cast: Michael Jai White, John Leguizamo, Martin Sheen, Theresa Randle, Mindy Clarke Directed By mark A.Z. Dippe
So many movies are coming out now from former comic books and change much so they can appeal to the general public who are not as familiar with the stories. SPAWN is no exception to this, the problem here is that the plot, the directing, the effects, and the acting are so poor that anyone even remotely interested in the movie will lose that slight bit of interest 25 minutes into it. The plot deals with an assassinated hitman Al Simmons, (White) who dies, makes a deal with the devil to lead his armies to taking over the world in exchange for seeing his fiancee Wanda (Randle). Violator (Leguizamo), who looks like a cross between a constipated Danny Devito and Chris Farley on a bad hair day, is there to make sure Simmons, now called Spawn, lives up to his end of the deal, which includes killing global kingpin Jason Wynn (Sheen) who is going to blow up the world if he dies by a deal made with the Violator. Yawn!! Who cares. Leguizamo gives a horrendous and annoying performance here, Sheen looks bored even though he couldn't be in a better picture, and White doesn't have much to do as Spawn, as the costume and effects on him steal the spotlight.  This is another movie, such as TWISTER and INDEPENDENCE DAY, where the plot and storyline are simply there to back up the Special Effects, which can not and will not make a movie. The only positives I enjoyed from SPAWN are Mindy Clarke, not for her acting but for some other features (nice rubber) and the special effects on Spawn himself.
I give this movie a single star * and do not recommend it to anyone, there are much better movies out worth seeing. AIR FORCE ONE, anyone?
**** Excellent (Air Force One, The Rock) *** Good (Face/Off, Mission Impossible) ** Fair (Con Air, The Devil's Own) * Poor (Twister, Spawn) 0 Horrible (Batman and Robin, Congo)
Copyright 1997<EMAIL_ADDRESS>Jesse A. Kaplan
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
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Related links: index of all rec.arts.movies.reviews reviews


Overview
Simple Instagram Video is a premium Instagram plugin that uses the power of HTML5 Video to showcase the latest functionality of the Instagram API. We know you will love it as much as we do because we've designed it to be as beautiful as it is useful. Give it a try, have some fun, and share you moments with the world!
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- Popular Instagram Feed Mode - This feed mode pulls in the photos from the Instagram popular feed.
- Tag Instagram Feed Mode - This feed mode allows you to specify a tag to search from the Instagram API.
- User Instagram Feed Mode - This feed mode allows you to specify a user id to pull in photos from a specific user.
- Multiuser Instagram Feed Mode - This feed mode allows you to specify multiple user id's to pull in photos from specific users. Note, this feature does NOT allow load more functionality.


The primary focus of the EWB at USC chapter is on our international project. However, we also volunteer in our local community in a variety of ways!
We are partnering with three local schools in the Irmo, SC area (northwest of Columbia). Engineering students from USC volunteer once a week to work with fifth-grade LEGO FIRST teams, helping them with design, programming, and presentation for the regional competition in December.
The USC Honors Dorm garden grows herbs and vegetables to use in the dormitory kitchen.


GROSSE POINTE BLANK A film review by Steve Kong Copyright 1997 Steve Kong
I saw the trailers for Grosse Pointe Blank and wondered what this movie could possible be about. And I think most people felt the same. The trailer does the movie no good. Grosse Pointe Blank is a movie that cannot be easily categorized. There is no a single genre that can describe Grosse Pointe Blank.
Martin Q. Blank (John Cusack) is a professional hitman. He is going through a life crisis. He is tired of his profession and is unsure of what he really is. By coincident, his next hit job is in his hometown and this tenth high school reunion also being held. Blank insists that he not go to the reunion. But with a little convincing from his office manager (Joan Cusack) and his fearful therapist (Alan Arkin), he agrees to do the hit job and to attend the reunion. Blank's hesitation to go to the reunion stems from what happened ten years ago during his senior prom. He left his girlfriend, Debi stranded, and unable to go go to the prom. Debi is played by the beautiful Minnie Driver. A funny subplot about a competing hitman trying to start a Union for hitmen unfolds during the movie.
The meat of Grosse Pointe Blank is a love story, and to a point, redemption story. Blank wants to get redemption from that one night when he stood Debi up. But she wants him to earn it. Along with this love story is a comedy that includes Dan Aykroyd as the opposing hitman trying to start the Hitmen's Union, two FBI guys, a therapist who feels threatened by Blank, and all of the people of Grosse Pointe. At one point Blank tells Debi's father that he is a professional hitman, the reply he gets is, "Good for you, growth industry." Then there is the action, and at times highly violent, portion of the film. I found this portion to be as well done as the previous two, but some may find this portion to be a turn off. With all of these different genres in the same film, the obvious question would be: Do the work together well? Yes, they work really well.
John Cusack, who is one of the four writers of this movie, gives a good performance of Martin Q Blank. Blank, who is the only sane character in this movie. Minnie Driver, although good in the movie, gives a flat dull performance as Debi. I enjoyed the performances of Dan Aykroyd as the opposing hitman, and Alan Arkin as the threatened therapist. Dan Aykroyd looks to be having the time of his life in this movie. Arkin gives a wonderfully off-beat performance.
A special mention for Grosse Pointe Blank is it's soundtrack. The soundtrack is filled with 80's music and is a real joy. The soundtrack fits in well with the movie.
Grosse Pointe Blank is a quirky movie the defies categorization. It has a great mix of attitude and quirky dialog. This makes for a fun movie that is enjoyable and well worth the money to see.
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


Digital way of securing your home from unauthorised visitors. This app is developed as a part of Silicon Valley Challenge Program of Whitehat Junior.
Every visitor's information is sent to the specified owner or tenant for verification and approval. Upon owner's approval only the visitor will be let to enter the building to avoid any criminal activity.
Whеn іt’ѕ іmроrtаnt tо hаvе unіfоrmеd ѕесurіtу оffісеrѕ оnѕіtе tо ѕесurе уоur рrореrtу, уоu саn rеlу оn Elegant Suraksha.
All your data are safe and secured in our system. Elegant Suraksha's main motto is security and protection.


pyglet_helper.objects package¶
Submodules¶
pyglet_helper.objects.arrow module¶
-
class
pyglet_helper.objects.arrow.
Arrow
(fixed_width=False, head_width=0.0, head_length=0.0, shaft_width=0.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0), axis=(1, 0, 0))¶ Bases:
pyglet_helper.objects.primitive.Primitive
A 3D 4-sided arrow, with adjustable head and shaft. By default, pointing along +x, unit length.
Parameters: - fixed_width (bool) – if True, the arrow’s head width and length will not be scaled in proportion to its length.
- head_width (float) – The width of the arrow’s head section.
- head_length (float) – The length of the arrow’s length section
- shaft_width (float) – The length of the arrow’s shaft section
- color (pyglet_helper.util.Rgb) – The arrow’s color.
- pos (pyglet_helper.util.pos) – The arrow’s position
- axis (pyglet_helper.util.Vector) – The arrow’s axis direction
-
center
¶ Calculates the center of the arrow by subtracting the axis off of the position
Returns: The arrow’s center (position+axis)/2 Return type: float
-
degenerate
¶ Returns: True if the arrow has an effective length of 0 Return type: bool
-
effective_geometry
(gcf)¶ Initializes these four variables with the effective geometry for the arrow. The resulting geometry is scaled to view space, but oriented and positioned in model space. The only required transforms are reorientation and translation.
Parameters: gcf (float) – The scaling factor
-
fixed_width
¶
-
head_length
¶
-
head_width
¶
-
init_model
(scene)¶ Add the arrow head and shaft to the scene.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into.
-
length
¶
-
render
(scene)¶ Render the arrow on the current view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into.
-
shaft_width
¶
pyglet_helper.objects.axial module¶
-
class
pyglet_helper.objects.axial.
Axial
(axis=Vector(1, 0, 0), radius=1.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0), material=<pyglet_helper.objects.material.Material object>, other=None)¶ Bases:
pyglet_helper.objects.primitive.Primitive
A subclass for all shapes with some radial symmetry around an axis (spheres, cones, etc., ).
Parameters: - other (pyglet_helper.objects.Axial) – another axial object to copy properties from (optional)
- axis (pyglet_helper.util.Vector) – The axis for the orientation of the object.
- radius (float) – The object’s radius.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- material (pyglet_helper.util.Material) – The object’s material
-
material_matrix
¶
-
radius
¶
pyglet_helper.objects.box module¶
-
class
pyglet_helper.objects.box.
Box
(width=1.0, height=1.0, length=1.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0))¶ Bases:
pyglet_helper.objects.rectangular.Rectangular
A box object.
Parameters: - width (float) – The box’s width.
- height (float) – The box’s height.
- length (float) – The box’s length.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
-
init_model
(scene, skip_right_face=False)¶ Add the Vertexes and Normals to the compile list.
Parameters: - scene (pyglet_helper.objects.View) – The view to render the model to.
- skip_right_face (bool) – If True, the right face will not be rendered.
-
render
(scene)¶ Render the box in the view
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
pyglet_helper.objects.cone module¶
-
class
pyglet_helper.objects.cone.
Cone
(radius=1.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0), axis=Vector(1, 0, 0))¶ Bases:
pyglet_helper.objects.axial.Axial
A Cone object
Parameters: - radius (float) – The cone’s bottom radius.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- axis (pyglet_helper.util.Vector) – The cone points from the base to the point along the axis.
Returns: -
center
¶ Get the center of the object.
Returns: position + axis/2 Return type: float
-
degenerate
¶ Returns: True if radius == 0 or the length is 0 Return type: bool
-
init_model
(scene)¶ Add the cone quadrics to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model to.
-
length
¶
-
render
(scene)¶ Add the cone to the scene.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
pyglet_helper.objects.cylinder module¶
-
class
pyglet_helper.objects.cylinder.
Cylinder
(pos=Vector(0, 0, 0), axis=Vector(1, 0, 0), radius=1.0, color=<pyglet_helper.util.rgba.Rgb instance>)¶ Bases:
pyglet_helper.objects.axial.Axial
A Cylinder object.
Parameters: - radius (float) – The cylinder’s radius.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- axis (pyglet_helper.util.Vector) – The cone points from the base to the point along the axis.
-
center
¶ Returns: Position + axis/2 Return type: float
-
degenerate
¶
-
init_model
(scene)¶ Add the cylinder quadrics to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model to.
-
length
¶
-
render
(scene)¶ Add the cylinder to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
pyglet_helper.objects.ellipsoid module¶
-
class
pyglet_helper.objects.ellipsoid.
Ellipsoid
(height=1.0, width=1.0, length=1.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0))¶ Bases:
pyglet_helper.objects.sphere.Sphere
An Ellipsoid object
Parameters: - width (float) – The ellipsoid’s width.
- height (float) – The ellipsoid’s height.
- length (float) – The ellipsoid’s length.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
-
degenerate
()¶
-
height
¶
-
length
¶
-
scale
¶
-
size
¶
-
width
¶
pyglet_helper.objects.light module¶
-
class
pyglet_helper.objects.light.
Light
(color=<pyglet_helper.util.rgba.Rgb instance>, specular=(0.5, 0.5, 1, 0.5), diffuse=(1, 1, 1, 1), position=(1, 0.5, 1, 0))¶ Bases:
pyglet_helper.objects.renderable.Renderable
A light object
Parameters: - color (pyglet_helper.util.Rgb) – The object’s color.
- specular (array_like) – The color of the specular reflections on the objects in the scene.
- diffuse – The color of the diffuse reflections of the objects in the scene.
- position (array_like) – The object’s position.
-
center
¶
-
get_vertex
(gcf)¶
-
is_light
¶
-
material
¶
-
render
(v)¶ Add the light to the scene. :param scene: The view to render the model into :type scene: pyglet_helper.objects.View
-
rgb
¶
pyglet_helper.objects.material module¶
-
class
pyglet_helper.objects.material.
Material
(translucent=False, shader_program=None)¶ Bases:
object
A Material object, used for storing and handling shader programs.
Parameters: - translucent (bool) –
- shader_program (str) – The GLSL (Graphics library shader language) code to be executed).
Returns: -
get_shader_program
()¶
-
shader
¶
-
textures
¶
-
translucent
¶
pyglet_helper.objects.primitive module¶
-
class
pyglet_helper.objects.primitive.
Primitive
(axis=Vector(1, 0, 0), up=Vector(0, 1, 0), pos=Vector(0, 0, 0), make_trail=False, trail_initialized=False, obj_initialized=False, color=<pyglet_helper.util.rgba.Rgb instance>, material=<pyglet_helper.objects.material.Material object>, other=None)¶ Bases:
pyglet_helper.objects.renderable.Renderable
A base class for all geometric shapes.
Parameters: - axis (pyglet_helper.util.Vector) – The orientation to use when drawing.
- up (pyglet_helper.util.Vector) – A vector that points to the current up direction in the view.
- pos (pyglet_helper.util.Vector) – The object’s position.
- make_trail (bool) – If True, the position of the primitive object will be tracked over time.
- trail_initialized (bool) – If True, the trail, meaning the list of tracked positions over time, has been initialized
- obj_initialized (bool) – If True, the object has been initialized
- color (pyglet_helper.util.Rgb) – The object’s color.
- material (pyglet_helper.util.Material) – The object’s material
- other (pyglet_helper.objects.Primitive) – another object to copy properties from (optional)
-
axis
¶
-
blue
¶
-
center
¶
-
green
¶
-
is_light
¶
-
make_trail
¶
-
model_world_transform
(world_scale=0.0, object_scale=Vector(1, 1, 1))¶ Performs scale, rotation, translation, and world scale (gcf) transforms in that order.
Parameters: - world_scale (float) – The global scaling factor.
- object_scale (pyglet_helper.util.Vector) – The scaling to applied to this specific object
Return type: pyglet_helper.util.Tmatrix
Returns: Returns a tmatrix that performs reorientation of the object from model orientation to world (and view) orientation.
-
pos
¶
-
primitive_object
¶
-
red
¶
-
rotate
(angle, axis, origin)¶ Rotate the primitive’s axis by angle about a specified axis at a specified origin.
Parameters: - angle (float) – the angle to rotate by, in radians
- axis (pyglet_helper.util.Vector) – The axis to rotate around.
- origin (pyglet_helper.util.Vector) – The center of the axis of rotation.
-
typeid
¶
-
up
¶
-
x
¶
-
y
¶
-
z
¶
-
pyglet_helper.objects.primitive.
trail_update
(obj)¶ A function for keeping track of the change in a primitive object’s position.
Parameters: obj (pyglet_helper.objects.Primitive) – the primitive object to track.
pyglet_helper.objects.pyramid module¶
-
class
pyglet_helper.objects.pyramid.
Pyramid
(pos=Vector(0, 0, 0), width=1.0, height=1.0, length=1.0, color=<pyglet_helper.util.rgba.Rgb instance>)¶ Bases:
pyglet_helper.objects.rectangular.Rectangular
A Pyramid Object
Parameters: - color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- width (float) – The pyramid’s width.
- height (float) – The pyramid’s height.
- length (float) – The pyramid’s length.
Returns: -
center
¶
-
init_model
(scene)¶ Add the pyramid normals and vertices to the View
Parameters: scene (pyglet_helper.objects.View) – The view to render the model to.
-
material_matrix
¶
-
render
(scene)¶ Add a pyramid to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
pyglet_helper.objects.rectangular module¶
-
class
pyglet_helper.objects.rectangular.
Rectangular
(other=None, pos=Vector(0, 0, 0), width=1.0, height=1.0, length=1.0, color=<pyglet_helper.util.rgba.Rgb instance>)¶ Bases:
pyglet_helper.objects.primitive.Primitive
A base class for rectangular-like objects (such as the box or pyramid)
Parameters: - color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- width (float) – The object’s width.
- height (float) – The object’s height.
- length (float) – The object’s length.
-
apply_transform
(scene)¶ Scale the object to the correct height, width and length
Parameters: scene (pyglet_helper.objects.View) – the object’s current view
-
height
¶
-
length
¶
-
size
¶
-
width
¶
pyglet_helper.objects.renderable module¶
-
class
pyglet_helper.objects.renderable.
Renderable
(color=<pyglet_helper.util.rgba.Rgb instance>, mat=<pyglet_helper.objects.material.Material object>, opacity=1.0, visible=False)¶ Bases:
object
A base class for all geometric shapes and lights.
Parameters: - color (pyglet_helper.util.Rgb) – The object’s color.
- material (pyglet_helper.util.Material) – The object’s material
- opacity (float) – The transparency value of the object
- visible (bool) – If True, the object will be rendered on the screen
-
material
¶
-
translucent
¶
-
class
pyglet_helper.objects.renderable.
View
(gcf=1.0, view_width=800, view_height=600, anaglyph=False, coloranaglyph=False, forward_changed=False, gcf_changed=False, lod_adjust=0, tan_hfov_x=0, tan_hfov_y=0, enable_shaders=True, background_color=<pyglet_helper.util.rgba.Rgb instance>)¶ Bases:
object
A class for handling the environment in which all objects are rendered
Parameters: - gcf (float) – The global scaling factor, a coefficient applied to all objects in the view
- view_width (int) – The width of the viewport in pixels.
- view_height (int) – The height of the viewport in pixels.
- anaglyph (bool) – If True, the scene will be rendered in anaglyph stereo mode.
- coloranaglyph (bool) – If True, the scene will be rendered in coloranaglyph stereo mode.
- forward_changed (bool) – True if the forward vector changed since the last rending operation.
- gcf_changed (bool) – True if the global scaling factor changed since the last render cycle.
- lod_adjust (int) – The level-of-detail.
- tan_hfov_x (int) – The tangent of half the horizontal field of view.
- tan_hfov_y (int) – The tangent of half the vertical field of view.
- enable_shaders (bool) – If True, shader programs will be allowed
- background_color (pyglet_helper.util.Rgb) – The scene’s background color
-
draw_lights
()¶ Render the lights in the scene
-
pixel_coverage
(pos, radius)¶ Compute the apparent diameter, in pixels, of a circle that is parallel to the screen, with a center at pos, and some radius. If pos is behind the camera, it will return negative.
Parameters: - pos (pyglet_helper.util.Vector) – The position in the view to examine
- radius (float) – The radius of coverage to examine
Returns: The diameter in pixels.
Return type: float
-
setup
()¶ Does some one-time OpenGL setup.
pyglet_helper.objects.ring module¶
-
class
pyglet_helper.objects.ring.
Ring
(thickness=0.0, radius=1.0, color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0), axis=Vector(1, 0, 0))¶ Bases:
pyglet_helper.objects.axial.Axial
A Ring object
Parameters: - thickness (float) – The ring’s thickness.
- radius (float) – The ring’s radius.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- axis (pyglet_helper.util.Vector) – The cone points from the base to the point along the axis.
-
degenerate
¶
-
material_matrix
¶
-
render
(scene)¶ Add a ring to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
-
thickness
¶
-
pyglet_helper.objects.ring.
clamp
(lower, value, upper)¶ Restrict a value to be between a lower value and upper value. Used to restrict the number of polygons in the ring object
Parameters: - lower (float or int) – the lowest possible value of value
- value (float or int) – the value to check
- upper (float or int) – the largest possible value of value
Return type: float or int
Returns: the restricted value
pyglet_helper.objects.sphere module¶
-
class
pyglet_helper.objects.sphere.
Sphere
(color=<pyglet_helper.util.rgba.Rgb instance>, pos=Vector(0, 0, 0), radius=1.0, material=<pyglet_helper.objects.material.Material object>, other=None)¶ Bases:
pyglet_helper.objects.axial.Axial
A Sphere object
Parameters: - radius (float) – The sphere’s radius.
- color (pyglet_helper.util.Rgb) – The object’s color.
- pos (pyglet_helper.util.Vector) – The object’s position.
- axis (pyglet_helper.util.Vector) – The cone points from the base to the point along the axis.
- material (pyglet_helper.util.Material) – The object’s material
- other (pyglet_helper.objects.Sphere) – another sphere object to copy properties from (optional)
-
degenerate
¶ Returns true if this object should not be drawn. Conditions are: zero radius, or visible is false. (overridden by the ellipsoid class).
-
init_model
(scene)¶ Add the sphere quadrics to the View
Parameters: scene (pyglet_helper.objects.View) – The view to render the model to.
-
material_matrix
¶
-
render
(geometry)¶ Add the sphere to the view.
Parameters: scene (pyglet_helper.objects.View) – The view to render the model into
-
scale
¶ Exposed for the benefit of the ellipsoid object, which overrides it. The default is to use <radius, radius, radius> for the scale.


Preparation time
less than 30 mins
Cooking time
over 2 hours
Serves
Serves 4-6
Fancy something a bit special for dinner this Sunday? This slow roasted lamb is wonderfully tender, serve with minted Jersey Royals and you're on to a winner.
Preheat the oven to 170C/150C Fan/Gas 3.
Rub the shoulder of lamb all over with the olive oil. Season with salt and pepper. Arrange the rosemary, garlic and onion in the bottom of a deep sided roasting tin and pour in 200ml/7fl oz water. Put the lamb on top and cover with aluminium foil.
Roast the lamb for 3-4 hours, basting every hour or so with the juices in the roasting tray. After two hours, remove the aluminium foil and continue to cook until the meat is very tender and falling off of the bone. Remove the lamb from the tray and set aside to rest.
Put the Jersey Royals and the mint in a saucepan, cover with water and bring to the boil. Cook for 10-15 minutes and then drain.
To make the wild garlic butter, put the butter in a mixing bowl and add the wild garlic. Season with salt and pepper, then set aside.
For the mint sauce, put the mint, sugar and vinegar in a bowl and mix.
Just before serving add a little of the garlic butter to the warm Jersey Royals.
Shred the lamb on a serving plate and pour over the gravy, serve the Jersey Royals alongside and the mint sauce in a small serving dish.


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Open this application in multiple browser window. For each instance of app separate sessionid and transactioid will be generated.
SessionId is used by backend service to send message to specific instance of application.
Transaction id is some transaction processed by distributed system. Ideally when job is submitted, system will return transactionID. So when updates are received for the transaction this service will lookup session/app instance which started the transaction and send updates only to that app instance over websocket
Application should call register endpoint by passing the session and transaction id.
Application should call unregister endpoint by passing the session and transaction id when application is closed.
Session ID for this instance of App :
Transaction ID for demo:
Notifications received on the web socket channel will be displayed below:
To avoind complexity, for this demo, transaction id is generated by front end application only. Assume that this transactionId is generated by backend system. Use RabbitMQ management console to sned message. Use the transactionId displayed on page Notice that every instance of page has different transactioid and sessioid. When message is sent to RabbitMQ queue, it will be displayed on the correct page.


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This is the documentation for yweather. yweather is a Python module that provides an interface to the Yahoo! Weather RSS feed
There are multiple ways to install yweather. If you are unsure about which method to use, try pip.
pip is a tool for installing and managing Python packages. To install yweather, run:
$ pip install yweather
This will download yweather from the Python Package Index and install it in your Python’s site-packages directory.
This will install yweather in your Python’s site-packages directory.
yweather’s code is hosted at GitHub. To install the development version, do the following:
This will link the yweather directory into your site-packages directory. You can find out where your site-packages directory is by running:
python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())"
>>> import yweather
>>> client = yweather.Client()
>>> client.fetch_woeid("Oslo, Norway")
'862592'
>>> oslo_weather = client.fetch_weather("862592")
>>> oslo_weather["atmosphere"]["pressure"]
'30.24'
>>> oslo_weather["condition"]["text"]
'Mostly Cloudy'
This code creates a yweather.Client instance that allows you to fetch a location’s WOEID and weather. The weather data is returned as a dict.


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Build trigger that polls one or more directories and starts a build if certain files are found within those directories.
Plugin Information |
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View Files Found Trigger on the plugin site for more information. |
Compatible with Java 7 and above.
Instructions
Enable the trigger within the "Build Environment" section of the build's configuration page.
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Features
- Detect files on the master or on a Jenkins slave.
- Specify the files with Ant-style includes and excludes patterns.
- Multiple directories can be specified.
- Can specify the minimum number of found files to trigger the build.
- Able to test the trigger before saving the settings.
- Environment variables and global variables can be entered as $var or ${var}.
- During the build, the settings can be accessed as environment variables.
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New releases may take a few hours to appear in the update center.
1.5 (Mar 14, 2017)
- Can now specify the minimum number of found files to trigger the build. (pull request #2)
Contributed by lyenliang - Improved diagnostic logging.
- Now requires at least Jenkins 1.580.1 and Java 7.
1.4 (Aug 15, 2015)
- Can now look for files on Jenkins slaves.
1.3.1 (Feb 25, 2015)
- When the directory is not found, display a hint about file permissions.
- Now requires at least Jenkins 1.520.
1.3 (Aug 17, 2011)
- The trigger settings are available to the build scripts as environment variables.
- When testing the configuration, the number of files found is displayed.
- Environment variables, provided by the global properties or the operating system, can be entered into the configuration page as $var or ${var}.
- Now requires at least Jenkins 1.399.
1.2 (Mar 06, 2011)
- Multiple directories can be specified.
- Now requires at least Jenkins/Hudson 1.377.
1.1.4 (Feb 07, 2011)
- Built from github repository with new Jenkins infrastructure. No behavioural changes.
1.1.3 (Jul 18, 2010)
- Removed dependency on Java 6, specifically the String.isEmpty() method.
1.1.2 (Jun 20, 2010)
- Now requires at least Jenkins/Hudson 1.301, rather than 1.349.
1.1.1 (Jun 4, 2010)
- Fixed the broken Ant documentation links within the help messages.
1.1 (Apr 25, 2010)
- Added a button to test the entered configuration before saving.
- The
Files to find
field now defaults to**
. - By default, no files are ignored. Previous releases ignored all files in the Ant default excludes.
1.0.1 (Apr 23, 2010)
- An exception no longer appears in the console when the entered directory does not exist.
1.0 (Mar 16, 2010)
- Initial release.
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In this time of crisis, all coders should do their part in contributing to the society in this fight against this alien virus.Therefore, I am currently working on a COVID prediction model with my brother Kartikeya Bector .
- Conics with Matpoltlib
Owing to my love for graphs I was introduced to this amazing world of Conic Sections, commonly known Conics. As I explored, pondered and discovered new and quite exciting stuff in maths, I eventually decided to take a very bold step and Extrapolate this interest of mine, in my CS project.
- Ultimate Matplotlib
Riding the wave of my previous project I decided to expand my domain and add more options, making a GUI to help navigate the programme better and including straight lines, trigonometry graphs with integration with MySQL to save our data.
- Authentication Programme
As I was preparing my matplotlib project for using it in my school, I decided to build an Authentication Programme to go alongside it. I made a basic template in tkinter and used this as the basis of many of my GUI, saving time and resources. You’ll see a reflection of this programme in many of my other projects as well. This was the first time I got acquainted with tkinter and os modules. I used this experience in building the Ultimate Matplotlib project
- OBS Clone
COVID 19 shifted our schools online, this was also accompanied by a need for a screen recorder. I am a huge fan of the OBS Studio, though it has a steep learning curve, the amount of flexibility it provides in recording the video, audio and our computer screen. So I made an elementary application which can record your screen, audio and webcam. For doing this I had to learn many new modules like cv2, sound device, soundfile, scipy and got to know how numpy can be used to make an array of photos, which when stitched together forms a video.
- Password Manager
Constantly making new passwords and memorising is a difficult job, no carter to this issue we have many password managers in the market, however I decided to make one of my own as a side project.
- IELTS Test taker
IELTS is compulsory for all the students applying in the international universities. Not only is it a life changing exam but also very expensive. In order to put my best foot forward and to get used to the Computer Based IELTS exam, I made a project to help me with the same.
- PyElections
During the pandemic we had to conduct elections in our vidyalaya. Since it involved participation of a lot of students from various age groups, the student council had to come up with a solution that could be easily used by all and difficult to cheat. We decided to have the elections on zoom, to cater to the above mentioned problems. The students were required to turn on their videos and cast a vote in the chat box(privately messaging to the host). These chats could then be saved as text files and the programme to transverse through it count the occurrence of a particular name and save it in a dictionary, in the format {key= name: value = votes}.


|
| PathTheme | | Portability | portable | | Stability | experimental | | Maintainer | Ralf Laemmel, Joost Visser |
|
|
|
|
|
| Description |
| This module is part of StrategyLib, a library of functional strategy
combinators, including combinators for generic traversal. In this module, we
define path combinator to constrain selection and transformation of nodes or
subtrees by path conditions. |
|
| Synopsis |
|
|
|
|
| Below |
|
| Strictly below |
|
| belowS :: (MonadPlus m, Strategy s m, StrategyPlus s m) => s m -> TU () m -> s m |
| Select or transform a node below a node where a condition holds.
We find the top-most node which admits selection or transformation
below the top-most node which meets the condition. Thus, the
distance between guard and application node is minimized. |
|
| Below or at the same height |
|
| beloweqS :: (MonadPlus m, Strategy s m, StrategyPlus s m) => s m -> TU () m -> s m |
| Select or transform a node below or at a node where a condition holds. |
|
| Type-specialised versions |
|
| belowTP :: MonadPlus m => TP m -> TU () m -> TP m |
| Apply a transformation strictly below a node where a condition holds. |
|
| beloweqTP :: MonadPlus m => TP m -> TU () m -> TP m |
| Apply a transformation below or at a node where a condition holds. |
|
| Above |
|
| Strictly above |
|
| aboveS :: (MonadPlus m, Strategy s m, StrategyPlus s m) => s m -> TU () m -> s m |
| Select or transform a node above a node where a condition holds. The
distance between guard and application node is minimized. |
|
| Above or at the same height |
|
| aboveeqS :: (MonadPlus m, Strategy s m, StrategyPlus s m) => s m -> TU () m -> s m |
| Select or transform a node above or at a node where a condition holds. |
|
| Type-specialised versions |
|
| aboveTP :: MonadPlus m => TP m -> TU () m -> TP m |
| Apply a transformation strictly above a node where a condition holds. |
|
| aboveeqTP :: MonadPlus m => TP m -> TU () m -> TP m |
| Apply a transformation above or at a node where a condition holds. |
|
| Produced by Haddock version 0.6 |


The kaidez JavaScript Conference Tour: Leg 1: Fluent 2012/San Francisco
byI was hoping to attend at least one JavaScript conference this year…luckily, I’m going to two! First up is O’Reilly’s three-day Fluent Conference in San Francisco (with June’s TXJS 2012 in Austin being the second one). Conference dates are May 29th through the 31st: premium training sessions on the first day, keynotes and public sessions during the other two days.
My Goals
Like I said in my last post, I’ve realized that I understand JavaScript a hell of a lot better than I give myself credit for. While I’m not a guru, I’m well past trying to figure out how it works. The time has come for me to understand the best case scenarios of “when “and “why” to use it, along with some top-notch implementation techniques.
Fluent’s first day training sessions and subsequent public ones should help me in meeting these goals…the full list of courses and sessions is here.
Premium Sessions I’ll Be Taking
The premium training day offers a morning and an afternoon block of sessions, allowing attendees to pick one from each block.
Here’s the full list of premium training sessions: I’ll be attending “Breaking HTML5 limits on mobile JavaScript” with Maximiliano Firtman in the morning and “Writing robust Node.js applications” with Tom Hughes-Croucher in the afternoon.
I’m a big fan of Maximiliano (AKA Max). He’s been developing for and writing about the mobile web well before the iPhone pushed it to critical mass so he knows his stuff. Plus, Max curates the excellent mobile web reference, mobilehtml5.org…should be a good session.
As for the Node course, I also mentioned in my last post that Node is starting to creep into the day job. I’m taking this session to better prepare myself in case I’m asked to support it.
Free Sessions & Keynotes
Keynotes are short and will be coming from some of the big names in web development: Brendan Eich, Lea Verou, Paul Irish, Steve Souders and many others.
Here are the sessions I’m plan on attend, all of which are subject to change:
Wednesday Sessions
Q&A with Brendan Eich »
He invented JavaScript which created an environment inside which all web developers can prosper and has earned respect as an elder in the developer community. I’m not thrilled about a specific political contribution that Eich made a few years back, but I have the chance to hear JavaScript’s inventor actually talk about JavaScript…OK?!?!
High Performance Snippets with Steve Souders »
Souders is an expert in the field of creating efficient, high-performance code. HTML5 Boilerplate, its build script, YSlow and PageSpeed were created using many of the techniques he writes about on his blog and in his books.
Jasmine: An Introduction with Davis W. Frank »
As implied earlier, I know how to write JavaScript, I just have to embed the best practices in my brain. Reviewing Jasmine, a behavior-driven development (BDD) framework for JavaScript testing is a good start.
There’s a SLIGHT chance that I’ll pass on this session and go to the Bootstrap one…will probably be a last minute decision.
These next two sessions are also happening at the same time, meaning I’ll have to make a choice…
Choice 1:
What Modernizr Teaches Us About Design & Development with Faruk Ateş »
Modernizr is a kick-ass feature detection library that appears in practically every web dev stack nowadays. The guy that created it talks about it.
Choice 2:
/Reg(exp){2}lained/: Demystifying Regular Expressions with Lea Verou »
It’s an opportunity to hear a well-known, well-respected web developer talk about something that many web developers ignore.
No idea what to do here…
Maintainable JavaScript with Nicholas Zakas »
I want to write JavaScript at work, knowing I can document it well enough so that others can fix it while off on vacation and drunk on a beach. Factor in that I’m a Zakas fan and I’m definitely going to this session.
Thursday Sessions
Here’s another case of two great sessions happening at the same time…
Choice 1:
SpineJS – Moving State to the Client with Alex MacCaw »
I’ve peeked at JavaScript MVC frameworks like Spine and Backbone for a while but haven’t really used them. I may check this session out.
Choice 2:
Sharing Code Between Client and Server with Node.js with Chris Powers »
Again, I have the Node bug so this may be the session for me.
Since I’m already doing the Node premium session and I’ll be attending a Node session after this one, I’m leaning towards the Spine session here…not sure yet.
How to Deploy a Node.js App to Production (And Not Get Fired) with Sean Hess »
All the Node I’ve done up to this point has been on my laptop running off of localhost, not a production site. Hoping to get a better understanding of production-based Node with this session.
Hybrid Web-Mobile Applications with PhoneGap and jQuery Mobile with Ryan Stewart »
I don’t see myself using PhoneGap to create native mobile apps…not that I dislike PhoneGap, I’m just not a native app guy. But I am curious about how it works with jQuery Mobile. I think this session will be a “cool kids” one, which is absolutely fine with me.
JS HTML5 Video Canvas = WOAH! with Wes Bos »
I was really pumped about HTML5 Video at one point, but severely lost interested in it. I have seen some cool demos on how it works with Canvas so I’ll check it out.
Ember.js: An MVC framework for ambitious web applications with Bruce Williams »
I’ve heard nothing but good things about Ember so I’ll be at this one.
Follow Me While I’m There!!!
As I did with MIX11, I probably won’t live blog during Fluent but will be tweeting it against the #FluentConf hash-tag. Follow me there and let me know if you’re going!


Power Inside
Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature
Read More➜Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature
Read More➜Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature
Read More➜Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature
Read More➜by cmsmasters Comments (6)
Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature Contrary to popular belief, Lorem Ipsum is not simply random text.
by cmsmasters Comments (3)
Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature Contrary to popular belief, Lorem Ipsum is not simply random text.


title = "Page not found (404)" url = "/404" layout = "default" is_hidden = 0 enabled_in_sitemap = 0 use_updated_at = 0 changefreq = "always" priority = 0.1 ==
Hmmm.... Looks like something went wrong. :(


For more complex headers, which can span over columns and/or rows use a
<f:facet name="header">
in the sheet.
The facet could be filled with <tc:out/>
tags
to set the names of the header.
Such an output field tag may also contain
<tc:gridLayoutConstraint columnSpan="..."/>
or
<tc:gridLayoutConstraint rowSpan="..."/>
to set a span over columns or rows.
Tag Library Documentation:
For multi-header sheets, you should consider to use markup="bordered"
for better appearance.


The HMS group has diverse chemical interests ranging from electronic structure
of solid-state and non-equilibrium materials to catalysis. We don't 'touch chemicals' in this lab (besides coffee and water), all our work is performed on super computers.
We are fortunate to have support from the NSF and the University of Oregon, providing access to state-of-the-art computational
facilities. Our primary goal is to perform valuable computational experiments that compliment and guide experimental studies
by providing atomic resolution of properties that are beyond the reach of conventional experimental chemistry.
Chemistry of metal-organic frameworks
Metal-organic frameworks (MOFs) are a class of solid-state porous materials composed of inorganic clusters spatially supported by organic ligands.
Their porosity gives rise to extremely high surface area.
Furthermore the combination of compositional and topological diversity enables unprecedented access to physical properties only arising from the unique MOF composition-function relationship.
As a result these hybrid materials have garnered increased interest over the past two decades dueto their potential applications in gas storage and separation, catalysis, sensors, and as battery materials.
The realization of electrically conductive MOFs would make them attractive targets for implementation in sensors, as capacitor matrices, and as electrocatalysts.
Yet, despite the potential for compositional diversity only a subset of ligands and metals yield electrically conductive MOFs, some representative ligands are shown.
Similar increases in conductivity have also been noted for MOFs constructed with Fe
2+. In all cases, the ligand and/or metal feature accessible redox states. Perhaps this is critical in the design of electrically conductive MOFs?
One objective of the HMS group is to use electronic structure calculations to determine design principles that underpin the development of future electrically conductive MOFs.
We are also interested in how MOFs can be harnessed as spatially separated single-site catalysts, either in thermal– or photocatalysis.
In this case we require localized electronic states as catalytically active sites, as opposite to a delocalized electronic structure required for electrically conductive MOFs.
A recent overview of MOF chemistry:
ACS. Cent. Sci., 2017
Harnessing Ti-localized conduction band minima for Ti
3+-catalyzed reactions:
Sci. Rep., 2016
Amorphous materials
Electronic and physical properties of liquid- and solid-state materials with no crystallographic order are of interest due to their cheap processing, overcoming the requirement for crystallization.
The challenge is rather to discover amorphous materials that feature similar chemical properties to their parent crystalline structures.
One successful example is SiO
2: both quartz and amorphous silicates (i.e. glass) are transparent and insulating.
Experimentally, the characterization of non-crystalline solids is extremely complex, because conventional X-ray techniques are not applicable.
Quantum chemistry compliments experiment to provide insights into chemical and physical properties that may persist or emerge upon amorphization.
We are interested in the prediction of chemical properties arising from diminishing symmetry and increased disorder in solid-state and glassy materials.
Emergence of new reactivity in amorphous NiS electrocatalysis:
Joule, 2017
Electrical conductivity in amorphous SnO
2:
Chem. Mater., 2016
Surface structures and properties
All materials have surfaces, if we define the surface as the boundary between two materials (we liberally include the vacuum as a 'material', too!).
It is the chemistry at the interfaces that determines the materials' catalytic activity.
Unlike thet static description of a surface recovered from cleaving crystallographic planes, a more realistic description allows for dynamic restructuring.
Yet, conventional DFT is often applied to the static picture, and hence there arrises a disparity between our models and reality.
TiWC coated in Pt is an example where conventional static models fail to describe the surface:
J. Phys. Chem. Lett., 2017
We are able to recover more representative surface descriptions using ab initio molecular dynamics, an approach which uses DFT and kinetic energy to allow atoms to move, making and breaking bonds dynamically.
The HMS group is interested in the discovery of non-equilibrium surface structure and its impact on the chemical properties arising at the interface.
The same approach can be applied to examine lattice dynamics of crystalline materials, too.


{% extends "layout.html" %} {% block title %}Index{% endblock %} {% block content %}
{% trans trimmed %} This tool, called Signatures, is designed to find technical issues in custom user signatures. It was written in Python by User:AntiCompositeNumber. {% endtrans %}
{% trans trimmed proposal=''|safe, close=""|safe %} MediaWiki has never imposed technical restrictions on fancy signatures other than maximum length. This allowed editors to create complex signatures that are hard for machines to parse. Complex signatures sometimes contained mistakes that would affect other text. A {{proposal}}proposal{{close}} was created for technical requirements that would fix these issues. {% endtrans %}
{% trans trimmed %} This tool was created as a result of that proposal so that editors discussing the proposal could make informed comments. It may also be useful in notifying users about their problematic signatures. {% endtrans %}
{% trans trimmed %} As this tool was built to collect data about the proposed new requirements, it checks for signatures that would violate those requirements. {% endtrans %}
{% trans %}The following problems are detected:{%endtrans%}
{% trans trimmed %} Some lint errors reported by the tool may not currently affect the rendered output of the page. Some are deprecated tags that may not be supported by browsers in the future, while others are silently fixed by the wikitext rendering system. There is no way to guarentee that these lint errors will continue to work over time. {% endtrans %}
{% trans trimmed %} Other reported errors are a result of requirements that don't target the rendered version of a page. These requirements are designed to make it easier for machines to find and parse signatures. If these problems are not fixed, tools, scripts, and bots may not work correctly with your signature. {% endtrans %}
{% trans trimmed talkopen=''|safe, ghopen=''|safe, close=""|safe %} Some reported issues are false positives caused by bugs in the detection code. You should report these bugs to AntiCompositeNumber on {{talkopen}}their talk page{{close}} or on {{ghopen}}GitHub{{close}}. {% endtrans %}
{% trans trimmed%} Unfortunately, site-level reports usually take too long to be able to generate them on the fly. The single user tool works for all Wikimedia wikis though. If you would like the report for a wiki to be created, please contact AntiCompositeNumber. {% endtrans %}
{% trans trimmed apiopen=''|safe, close=('')|safe %} The tool has a basic REST API, documented {{apiopen}}here{{close}}. It should not be considered especially stable. {% endtrans %}
{% endblock %}


public class RangeSearch<D extends DataObject>
extends java.lang.Object
| Modifier and Type | Class and Description |
|---|---|
static class |
RangeSearch.Info |
class |
RangeSearch.InfoFinder |
class |
RangeSearch.InfoMapper |
| Constructor and Description |
|---|
RangeSearch(DataObjectFactory<D> fac,
java.lang.String field) |
| Modifier and Type | Method and Description |
|---|---|
long |
search(long min,
long max)
search for a positive id value not used by any record in the
repository
|
public RangeSearch(DataObjectFactory<D> fac, java.lang.String field)
public long search(long min, long max) throws DataException
min
- minimum legal value (inclusive)max
- maximum legal value (inclusive)DataException


--- layout: post title: Relative Copy in vim tags: - vim ---
It surprises me that I’ve not found or used this before!
In vim, you can use relative line numbers to copy and paste code(it can actually be used for other commands as well but I stick to one command at a time). Using this command:
:-5t.
Will copy the line of code that is 5 lines above your current cursor to your current position.
This line:
:-10, -8 t.
Will copy from 10 lines above your cursor to 8 lines above your cursor and put it to your current position.
This is incredibly handy when trying to rearrange text and prevents you from needing to move to the line you need to copy, only to move back to where you need to paste it.


Andrew Legaspi is an undergrad senior of Computer Engineering at University of California, San Diego. His interests are Networking, Android development and Embedded Systems. He is planning on moving to Hawaii once he graduates.


The American Legion Auxiliary celebrates a century of service
by Cal DymowskiBINGHAMTON (WBNG) — The American Legion Auxiliary (ALA) celebrated 100 years today, holding a ham dinner for members of the community and veterans to attend.
The ALA was founded back on November 10, 1919, and has been helping support veterans, active military and their families ever since.
The American Legion Post 1194 held the dinner, which was made extra special thanks to a donation for Floyd’s Rent-All in Endwell, who donated the linens used for the tables.
To Legion members and officials, knowing the community support still remains after a century of service means the world.
“It was very nice to know that there are people out there to support the women veterans and all veterans, not just the American Legion,” said former president Cheryl Miller. “It’s very important. Let the community know that we are all here and we are doing things for our veterans, not only are men veterans, but our women veterans, and for our community.”
The dinner took six weeks to plan. Miller told 12 News she was expecting around 150 people to show up throughout the course of the meal.
All proceeds for the event will go to women veterans at the Oxford Veterans Home.


Now that we know reduce
is in some sense "universal" among functions that process arrays we can try unifying all of our array processing under reduce
and see if that aids in composition. To get to that point we are going to define some more things. First a term: given data types A
and C
we call a function of the form (C, A) -> C
a reducer on A
. These are precisely the kinds of functions we could feed into reduce
. The first argument is called the accumulation and the second element is just the element of the array being inspected. A function that takes a reducer on A
and returns a reducer on B
is called a transducer. A simple example would be the following:


The easiest way to stay up to date with all ShefFood activities is to sign up to our newsletter. You can also follow us on social media.


|
xpcc
|
Lightweight, stackless threads. More...
Classes | |
| class | xpcc::pt::Protothread |
| A very lightweight, stackless thread. More... | |
| class | xpcc::pt::Semaphore |
| Counting semaphore. More... | |
Macros | |
| #define | PT_BEGIN() |
| Declare start of protothread. More... | |
| #define | PT_END() |
| Stop protothread and end it. More... | |
| #define | PT_YIELD() |
| Yield protothread till next call to its run(). | |
| #define | PT_WAIT_WHILE(condition) |
| Cause protothread to wait while given condition is true. | |
| #define | PT_WAIT_UNTIL(condition) |
| Cause protothread to wait until given condition is true. | |
| #define | PT_WAIT_THREAD(child) |
| Cause protothread to wait until given child protothread completes. | |
| #define | PT_SPAWN(child) |
| Restart and spawn given child protothread and wait until it completes. | |
| #define | PT_CALL(resumable) |
| Calls a given resumable function and returns whether it completed successfully or not. | |
| #define | PT_RESTART() |
| Reset protothread to start from the beginning. More... | |
| #define | PT_EXIT() |
| Stop and exit from protothread. | |
Protothreads are extremely lightweight stackless threads designed for severely memory constrained systems, such as small embedded systems or wireless sensor network nodes. Protothreads provide linear code execution for event-driven systems implemented in C. Protothreads can be used with or without an underlying operating system to provide blocking event-handlers.
Protothreads provide sequential flow of control without complex state machines or full multi-threading.
As they implement some kind of cooperative multithreading Protothreads are non-preemptable. Therefore, a context switch can only take place on blocking operations. Therefore you don't need complex synchronisation. Protothreads are also stackless, which means member variables of the xpcc::Protothread subclasses are needed for preserving variables across context switches.
A protothread runs within a single function (xpcc::Protothread::run()) and cannot span over other functions. A protothread may call normal functions, but cannot block inside a called function. Blocking inside nested function calls is instead made by spawning a separate protothread for each potentially blocking function.
The protothread concept was developed by Adam Dunkels and Oliver Schmidt.
Originally ported to C++ for use by Hamilton Jet (www.hamiltonjet.co.nz) by Ben Hoyt, but stripped down for public release. See his blog entry about it for more information: http://blog.micropledge.com/2008/07/protothreads/
| #define PT_BEGIN | ( | ) |
| #define PT_END | ( | ) |
| #define PT_RESTART | ( | ) |
In the next executing cycle the protothread will restart its execution at its PT_BEGIN.


C-Programming
C - Basic Introduction
C is a general-purpose high level language that was originally developed by Dennis Ritchie for the UNIX operating system. It was first implemented on the Digital Equipment Corporation PDP-11 computer in 1972. The UNIX operating system and virtually all UNIX applications are written in the C language. C has now become a widely used professional language for various reasons. Easy to learn
Structured language
It produces efficient programs.
It can handle low-level activities.
It can be compiled on a variety of computers.
Facts about C
C was invented to write an operating system called UNIX.
C is a successor of B language which was introduced around 1970
The language was formalized in 1988 by the American National Standard Institute (ANSI).
By 1973 UNIX OS was almost totally written in C.
Today C is the most widely used System Programming Language.
Most of the state of the art software have been implemented using C
C was initially used for system development work, in particular the programs that make-up the operating system. C was adopted as a system development language because it produces code that runs nearly as fast as code written in assembly language. Some examples of the use of C might be:
Operating Systems
Language Compilers
Assemblers
Text Editors
Print Spoolers
Network Drivers
Modern Programs
Data Bases
Language Interpreters
Utilities
C Compilers
When you write any program in C language then to run that program you need to compile that program using a C Compiler which converts your program into a language understandable by a computer. This is called machine language (i.e. binary format). So before proceeding, make sure you have C Compiler available at your computer. Some examples of C compilers are Turbo C and Borland C.
C - Program Structure
A C program basically has the following form:
Preprocessor Commands
Functions
Variables
Statements & Expressions
Comments
Preprocessor Commands: This command tells the compiler to do preprocessing before doing actual compilation. Like;
- #include stdio.h
The C Programming language provides a set of built-in functions. printf() is a C built-in function which is used to print anything on the screen.
Variables: Variables are used to hold numbers, strings and complex data for manipulation. Statements & Expressions: Expressions combine variables and constants to create new values. Statements are expressions, assignments, function calls, or control flow statements which make up C programs.
Comments: are used to give additional useful information inside a C Program. All the comments will be put inside /*...*/ as given in the example above. A comment can span through multiple lines.
Note the followings
C is a case sensitive programming language. It means in C printf and Printf will have different meanings.
C has a free-form line structure. End of each C statement must be marked with a semicolon.
Multiple statements can be one the same line.
White Spaces (ie tab space and space bar ) are ignored.
Statements can continue over multiple lines.
Data Types in C
A C language programmer has to tell the system before-hand, the type of numbers or characters he is using in his program. These are data types. There are many data types in C language. A C programmer has to use appropriate data type as per his requirement in the program he is going to do.


Issue page
Author: {{issue.Author.Username}}
Project: {{issue.Project.Name}}
Statut: {{issue.Status.Name}}
Labels: {{AllLabels}}
Avaiable Statuses:
-----Closed Change
-----StoppedProgress Change
-----InProgress Change
{{comment.Author.Username}} ---- {{comment.CreatedOn}}
{{comment.Text}}
{{comment.Author.Username}} ---- {{comment.CreatedOn}}
{{comment.Text}}


Library Fsub_LetSum_Soundness
Type-safety proofs for Fsub.
Authors: Brian Aydemir and Arthur Chargu\'eraud, with help from Aaron Bohannon, Jeffrey Vaughan, and Dimitrios Vytiniotis.
In parentheses are given the label of the corresponding lemma in the appendix (informal proofs) of the POPLmark Challenge.
Table of contents:
Authors: Brian Aydemir and Arthur Chargu\'eraud, with help from Aaron Bohannon, Jeffrey Vaughan, and Dimitrios Vytiniotis.
In parentheses are given the label of the corresponding lemma in the appendix (informal proofs) of the POPLmark Challenge.

We provide detailed comments for the following proof, mainly to
point out several useful tactics and proof techniques.
Starting a proof with "Proof with <some tactic>" allows us to specify a default tactic that should be used to solve goals. To invoke this default tactic at the end of a proof step, we signal the end of the step with three periods instead of a single one, e.g., "apply typing_weakening...".
Starting a proof with "Proof with <some tactic>" allows us to specify a default tactic that should be used to solve goals. To invoke this default tactic at the end of a proof step, we signal the end of the step with three periods instead of a single one, e.g., "apply typing_weakening...".
The proof proceeds by induction on the given typing derivation
for e. We use the remember tactic, along with generalize
dependent, to ensure that the goal is properly strengthened
before we use induction.
intros U E F x T e u TypT TypU.
remember (F ++ x ~ bind_typ U ++ E) as E'.
generalize dependent F.
induction TypT; intros F EQ; subst; simpl subst_ee...
The typing_var case involves a case analysis on whether the
variable is the same as the one being substituted for.
Case "typing_var".
destruct (x0 == x); try subst x0.
In the case where x0=x, we first observe that hypothesis
H0 implies that T=U, since x can only be bound once in
the environment. The conclusion then follows from hypothesis
TypU and weakening. We can use the analyze_binds_uniq
tactic, described in the MetatheoryEnv library, with H0 to
obtain the fact that T=U.
SCase "x0 = x".
analyze_binds_uniq H0.
injection BindsTacVal; intros; subst.
In order to apply typing_weakening, we need to rewrite
the environment so that it has the right shape. (We could
also prove a corollary of typing_weakening.) The
rewrite_env tactic, described in the Environment
library, is one way to perform this rewriting.
In the case where x0<>x, the result follows by an exhaustive
case analysis on exactly where x0 is bound in the
environment. We perform this case analysis by using the
analyze_binds tactic, described in the MetatheoryEnv
library.
SCase "x0 <> x".
analyze_binds H0.
eauto using wf_env_strengthening.
eauto using wf_env_strengthening.
Informally, the typing_abs case is a straightforward
application of the induction hypothesis, which is called H0
here.
Case "typing_abs".
We use the "pick fresh and apply" tactic to apply the rule
typing_abs without having to calculate the appropriate
finite set of atoms.
We cannot apply H0 directly here. The first problem is that
the induction hypothesis has (subst_ee open_ee), whereas in
the goal we have (open_ee subst_ee). The lemma
subst_ee_open_ee_var lets us swap the order of these two
operations.
The second problem is how the concatenations are associated in
the environments. In the goal, we currently have
where concatenation associates to the right. In order to apply the induction hypothesis, we need
We can use the rewrite_env tactic to perform this rewriting, or we can rewrite directly with an appropriate lemma from the MetatheoryEnv library.
(y ~ bind_typ V ++ F ++ E),
where concatenation associates to the right. In order to apply the induction hypothesis, we need
((y ~ bind_typ V ++ F) ++ E).
We can use the rewrite_env tactic to perform this rewriting, or we can rewrite directly with an appropriate lemma from the MetatheoryEnv library.
Now we can apply the induction hypothesis.
apply H0...
The remaining cases in this proof are straightforward, given
everything that we have pointed out above.
Case "typing_tabs".
pick fresh Y and apply typing_tabs.
rewrite subst_ee_open_te_var...
rewrite <- app_assoc.
apply H0...
Case "typing_let".
pick fresh y and apply typing_let...
rewrite subst_ee_open_ee_var...
rewrite <- app_assoc.
apply H0...
Case "typing_case".
pick fresh y and apply typing_case...
rewrite subst_ee_open_ee_var...
rewrite <- app_assoc.
apply H0...
rewrite subst_ee_open_ee_var...
rewrite <- app_assoc.
apply H2...
Qed.

Lemma typing_inv_abs : forall E S1 e1 T,
typing E (exp_abs S1 e1) T ->
forall U1 U2, sub E T (typ_arrow U1 U2) ->
sub E U1 S1
/\ exists S2, exists L, forall x, x `notin` L ->
typing (x ~ bind_typ S1 ++ E) (open_ee e1 x) S2 /\ sub E S2 U2.
Lemma typing_inv_tabs : forall E S1 e1 T,
typing E (exp_tabs S1 e1) T ->
forall U1 U2, sub E T (typ_all U1 U2) ->
sub E U1 S1
/\ exists S2, exists L, forall X, X `notin` L ->
typing (X ~ bind_sub U1 ++ E) (open_te e1 X) (open_tt S2 X)
/\ sub (X ~ bind_sub U1 ++ E) (open_tt S2 X) (open_tt U2 X).
Lemma typing_inv_inl : forall E e1 T,
typing E (exp_inl e1) T ->
forall U1 U2, sub E T (typ_sum U1 U2) ->
exists S1, typing E e1 S1 /\ sub E S1 U1.
Lemma typing_inv_inr : forall E e1 T,
typing E (exp_inr e1) T ->
forall U1 U2, sub E T (typ_sum U1 U2) ->
exists S1, typing E e1 S1 /\ sub E S1 U2.
Lemma canonical_form_abs : forall e U1 U2,
value e ->
typing empty e (typ_arrow U1 U2) ->
exists V, exists e1, e = exp_abs V e1.
Lemma canonical_form_tabs : forall e U1 U2,
value e ->
typing empty e (typ_all U1 U2) ->
exists V, exists e1, e = exp_tabs V e1.
Lemma canonical_form_sum : forall e T1 T2,
value e ->
typing empty e (typ_sum T1 T2) ->
exists e1, e = exp_inl e1 \/ e = exp_inr e1.
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Armed police called to Newcastle's West End after officer is assaulted
A large-scale response was spotted on Grainger Park Road following the assault of an officer on Thursday evening
by Kieran MurrayArmed police were called in as back-up after an officer was assaulted in the West End of Newcastle last night.
Officers were in attendance at an address on Grainger Park Road at around 4.35pm on Thursday to assist mental health services with an assessment of a patient.
During the assessment, a 54-year-old man became aggressive and assaulted a police officer.
Armed police were among the units drafted in as part of a large-scale response to descend on the scene.
A witness told ChronicleLive they saw at least five vehicles at the scene, including a police dogs unit.
The man was arrested by police and was later released into the care of mental health professionals.
Northumbria Police confirmed no officers were seriously injured during the altercation and stated there was never any risk to the wider public.
A spokesman also said there will be no further criminal action taken against the man.


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MIRAGE(1) MIRAGE(1) NAME mirage - A fast and simple GTK+ Image Viewer SYNOPSIS mirage [OPTION]... [FILES|FOLDERS]... DESCRIPTION Mirage is a fast and simple GTK+ Image Viewer. OPTIONS -h, --help Show this help and exit -v, --version Show version information and exit -V, --verbose Show more detailed information -R, --recursive Recursively include all images found in subdirectories of FOLDERS -s, --slideshow Start in slideshow mode -f, --fullscreen Start in fullscreen mode -o, --onload 'cmd' Execute 'cmd' when an image is loaded (uses same syntax as custom actions, i.e. mirage -o 'echo file is %F') SEE ALSO Website: http://mirageiv.berlios.de AUTHOR Mirage was written by Scott Horowitz<EMAIL_ADDRESS>This manual page was written by Mike Massonnet<EMAIL_ADDRESS>for the Debian project (but may be used by others). January 15, 2007 MIRAGE(1)