Twisted is a framework designed to be very flexible, and let you write powerful clients. The cost of this flexibility is a few layers in the way to writing your client. This document covers creating clients that can be used for TCP, SSL and Unix sockets, UDP is covered in a different document.
At the base, the place where you actually implement the protocol parsing
and handling, is the Protocol class. This class will usually be decended
from twisted.internet.protocol.Protocol
. Most
protocol handlers inherit either from this class or from one of its
convenience children. An instance of the protocol class will be
instantiated when you connect to the server, and will go away when the
connection is finished. This means that persistent configuration is not
saved in the Protocol.
The persistent configuration is kept in a Factory class, which usually
inherits from twisted.internet.protocol.ClientFactory
. The default
factory class just instantiate the Protocol, and then sets on it an
attribute called factory
which points to itself. This let
the Protocol access, and possibly modify, the persistent
configuration.
As mentioned above, this, and auxiliary classes and functions, is where most of the code is. A Twisted protocol handles data in an asynchronous manner. What this means is that the protocol never waits for an event, but rather responds to events as they arrive from the network.
Here is a simple example:
from twisted.internet.protocol import Protocol from sys import stdout class Echo(Protocol): def dataReceived(self, data): stdout.write(data)
This is one of the simplest protocols. It simply writes to standard output whatever it reads from the connection. There are many events it does not respond to. Here is an example of a Protocol responding to another event.
from twisted.internet.protocol import Protocol class WelcomeMessage(Protocol): def connectionMade(self): self.transport.write("Hello server, I am the client!\r\n") self.transport.loseConnection()
This protocol connects to the server, sends it a welcome message, and then terminates the connection.
The connectionMade event is usually where set up of the Protocol object happens, as well as any initial greetings (as in the WelcomeMessage protocol above). Any tearing down of Protocol-specific objects is done in connectionLost.
In many cases, the protocol only needs to connect to the server once,
and the code just wants to get a connected instance of the protocol. In
those cases twisted.internet.protocol.ClientCreator
provides the
appropriate API.
from twisted.internet import reactor from twisted.internet.protocol import Protocol, ClientCreator class Greeter(Protocol): def sendMessage(self, msg): self.transport.write("MESSAGE %s\n" % msg) def gotProtocol(p): p.sendMessage("Hello") reactor.callLater(1, p.sendMessage, "This is sent in a second") reactor.callLater(2, p.transport.loseConnection) c = ClientCreator(reactor, Greeter) c.connectTCP("localhost", 1234).addCallback(gotProtocol)
We use reactor.connect* and a ClientFactory. The ClientFactory is in charge of creating the Protocol, and also receives events relating to the connection state. This allows it to do things like reconnect on the event of a connection error. Here is an example of a simple ClientFactory that uses the Echo protocol (above) and also prints what state the connection is in.
from twisted.internet.protocol import Protocol, ClientFactory from sys import stdout class Echo(Protocol): def dataReceived(self, data): stdout.write(data) class EchoClientFactory(ClientFactory): def startedConnecting(self, connector): print 'Started to connect.' def buildProtocol(self, addr): print 'Connected.' return Echo() def clientConnectionLost(self, connector, reason): print 'Lost connection. Reason:', reason def clientConnectionFailed(self, connector, reason): print 'Connection failed. Reason:', reason
To connect this EchoClientFactory to a server, you could use this code:
from twisted.internet import reactor reactor.connectTCP(host, port, EchoClientFactory()) reactor.run()
Note that clientConnectionFailed
is called when a connection could not be established, and that clientConnectionLost
is called when a connection was made and then disconnected.
Many times, the connection of a client will be lost unintentionally due
to network errors. One way to reconnect after a disconnection would be to
call connector.connect()
when the
connection is lost:
from twisted.internet.protocol import ClientFactory class EchoClientFactory(ClientFactory): def clientConnectionLost(self, connector, reason): connector.connect()
The connector passed as the first argument is the interface between a
connection and a protocol. When the connection fails and the factory
receives the clientConnectionLost event, the factory can call connector.connect()
to start the connection over
again from scratch.
However, most programs that want this functionality should implement ReconnectingClientFactory
instead,
which tries to reconnect if a connection is lost or fails, and which
exponentially delays repeated reconnect attempts.
Here is the Echo protocol implemented with a ReconnectingClientFactory:
from twisted.internet.protocol import Protocol, ReconnectingClientFactory from sys import stdout class Echo(Protocol): def dataReceived(self, data): stdout.write(data) class EchoClientFactory(ReconnectingClientFactory): def startedConnecting(self, connector): print 'Started to connect.' def buildProtocol(self, addr): print 'Connected.' print 'Resetting reconnection delay' self.resetDelay() return Echo() def clientConnectionLost(self, connector, reason): print 'Lost connection. Reason:', reason ReconnectingClientFactory.clientConnectionLost(self, connector, reason) def clientConnectionFailed(self, connector, reason): print 'Connection failed. Reason:', reason ReconnectingClientFactory.clientConnectionFailed(self, connector, reason)
The clients so far have been fairly simple. A more complicated example comes with Twisted Words in the doc/examples directory.
ircLogBot.pyircLogBot.py connects to an IRC server, joins a channel, and logs all traffic on it to a file. It demonstrates some of the connection-level logic of reconnecting on a lost connection, as well as storing persistent data in the Factory.
Since the Protocol instance is recreated each time the connection is made, the client needs some way to keep track of data that should be persisted. In the case of the logging bot, it needs to know which channel it is logging, and where to log it to.
from twisted.internet import protocol from twisted.protocols import irc class LogBot(irc.IRCClient): def connectionMade(self): irc.IRCClient.connectionMade(self) self.logger = MessageLogger(open(self.factory.filename, "a")) self.logger.log("[connected at %s]" % time.asctime(time.localtime(time.time()))) def signedOn(self): self.join(self.factory.channel) class LogBotFactory(protocol.ClientFactory): protocol = LogBot def __init__(self, channel, filename): self.channel = channel self.filename = filename
When the protocol is created, it gets a reference to the factory as self.factory. It can then access attributes of the factory in its logic. In the case of LogBot, it opens the file and connects to the channel stored in the factory.
The Protocol
class used throughout this document is a base implementation of IProtocol
used in
most Twisted applications for convenience. To learn about the
completeIProtocol
interface, see the API documentation for
IProtocol
.
The transport
attribute used in some examples in this
document provides the
ITCPTransport
interface. To learn about the complete interface, see
the API documentation for ITCPTransport
.
Interface classes are a way of specifying what methods and attributes an object has and how they behave. See the Components: Interfaces and Adapters document.


{% extends 'layouts/layout.html' %} {% from 'button/macro.njk' import button %} {% from 'back-link/macro.njk' import backLink %} {% block pageTitle %} The security code has expired {% endblock %} {% block content %}
This is because it has been more than 5 minutes since it has been sent.


Bending the rules of Bandit
Bandit is more what you'd call
"guidelines" than actual rules
- Captain Hector Barbossa
Don't sweat it
Use Bandit to model your own methodology
- Selectors performance is a game to win 50ms, top.
- Don't mess files up just because you can.
- Try to forget that !important exists
- Write code that the next dev can understand.
- Solve your problems.


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SwiftSeq can perform variant calling on exomes in minutes and genomes in hours.
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Across: 1. Moving track - English move, as he moved! (3'1 7 4) 9. Severely macerates the squads that put cars on the track (4 5) 10. Prostrate misrepresentation (5) 11. Question report of generation of track (3) 12. "Him" a cleric? Ridiculous fantasy! (10) 14. Tom and Ben stitched up and put away for a long time (6) 15. see 4dn 18. Whole mob returns in human resources comeback (7) 20. You bunt unless provided familiar distribution (6) 23. "Mom" a cleric? Bizarre promotion! (10) 25. Maiden volume (3) 27. 24dn a cleric chooses? Maidenhead's lost it's earliest point! (5) 28. Mad dance is spasmodic movement (9) 29. Then see more such material on track (4 5 3 3) Down: 1,22. Weird barfly rests fitfully... this forever will be an odd track (10 6) 2. Put into the code of 14 perhaps (7) 3. Cremate ol' crazy... maybe he was retarded? (9) 4,15ac. Final idea they experimented with on track (1 3 2 3 4) 5. Checks with those such as fly about quietly (8) 6. Mongol gimmick provides complex name for Italian bioligist (5) 7. It's enthusiasts always come back to the fold (7) 8. Nervous but making progress (4) 13. Grand old party animal to rub pelican the wrong way (10) 16. In uncharacteritic blemish, the Spanish apply decoration (9) 17. Winged creatures in pastiche rub implausibly (8) 19. Iron Man bread (7) 21. Makes opposite: sane get insane (7) 22. see 1 24. Mauls Vince oddly with sonic stimulation (5) 26. Chief of Middle East hash production (4)


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The American Medical Association calls for ban on gay conversion thera
by Christopher VondracekThe American Medical Association will begin developing legislation to ban so-called reparative, or conversion, therapy for LGBTQ individuals, characterizing the practice as harmful and scientifically unfounded.
The AMA’s policy-making committee in San Diego on Tuesday called for banning conversion therapy for minors and adults, saying the therapy’s practice opens the door to fraud.
“It is clear to the AMA that the conversion therapy needs to end in the United States, given the risk of deliberate harm to LGBTQ people,” said Dr. William E. Kobler, an AMA board member. “Conversion therapy has no foundation as scientifically valid medical care and lacks credible evidence to support its efficacy or safety.”
Eighteen states and the District of Columbia have banned conversion therapy for people under age 18. No state has banned conversion therapy for adults.
Earlier this fall, New York City repealed a ban on conversion therapy for adults after the Alliance Defending Freedom sued the city, alleging the ban violated the religious freedom of an Orthodox Jewish counselor.
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First post, first meeting, and a preview of what's ahead
Welcome to the new 2013 UAARG blog! Last Tuesday, we had our first meeting of the new year, in which we discussed work that went on over the holiday break and looked ahead at the final months of work before competition in May.
We reached one of our major goals over the holiday season: completing the Competition Paper for the Unmanned Systems Canada Unmanned Air Vehicle Student Competition, the first of our two major competitions this year. This paper is meant to be a document that outlines the design process of the aircraft and describes its major components and systems, from physical construction and flight to communications and imaging. The paper is also judged toward our final score in the competition, so finishing it was a very large milestone, as well as a large relief, for the team.
The second major goal reached over the holidays was the completion of the range testing for the communications systems of the aircraft. Several different wireless links are required for both controlled and autonomous flight, as well as transmission of images from the aircraft. The entire system was taken outdoors under conditions similar to those at competition, and the range and capacity of each of the wireless links were tested. Though there are still some problems with communications, the majority of the systems are performing as expected.
Some photos from the outdoor range testing, including a graph of successful signal transmission
There is still, however, quite a list of items to be completed in the weeks ahead, one of which is flight testing of foam model airplanes so that R/C pilots can be trained for competition. This is a priority at present because of the lack of flight training that the pilots have received so far (flight simulators are fun but no substitute), and we’re going to find an indoor flying field appropriate for this purpose next. We are also working towards having a functional, testable version of the ground station imaging system in a few weeks’ time.
A few shots of the foam airplanes under construction for pilot training
To stay on track in the meantime, we have set several internal deadlines for the completion and testing of major systems before competition. We are also piloting the idea of short presentations by one of the subgroups (airframe, autopilot, imaging, etc.) at the beginning of each meeting; these are meant to familiarize members with all aspects of the plane and its systems, as well as update on progress in subgroups. Stay tuned for updates on the blog as we gear up for the competition season!


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public class SubdivisionSearch
extends java.lang.Object
Subdivision
.
Creates a search structure that achieves a query time of O(log n) for point location
in a planar Subdivision
with n full edges. However, the search structure itself
occupies O(n) fairly big objects which require O(n log n) steps to construct, and must
be recreated whenever the underlying Subdivision
changes.
Moreover, SubdivisionSearch
requires a minimum epsilon of 1e-10 for coordinate
comparisons to reliably construct its search structure, and must use the construction
epsilon for all point location queries. Use the brute force Subdivision.find(org.kynosarges.tektosyne.geometry.PointD, double)
algorithm to avoid construction costs or perform searches with a different epsilon.
The algorithm to incrementally construct a search structure for the trapezoidal map of a
planar subdivision was adapted from Mark de Berg et al., Computational Geometry
(3rd ed.), Springer-Verlag 2008, p.122-137. This implementation uses null half-edges and
Double.POSITIVE_INFINITY
to indicate the unbounded face, rather than placing an
actual bounding rectangle around the Subdivision
.
| Modifier and Type | Field and Description |
|---|---|
double |
epsilon
The maximum absolute difference at which two coordinates should be considered equal.
|
Subdivision |
source
The
Subdivision for which the SubdivisionSearch graph was created. |
| Constructor and Description |
|---|
SubdivisionSearch(Subdivision source,
boolean ordered)
Creates a
SubdivisionSearch graph for the specified Subdivision . |
| Modifier and Type | Method and Description |
|---|---|
SubdivisionElement |
find(PointD q)
|
java.lang.String |
format()
Returns a
String that represents the entire SubdivisionSearch graph. |
void |
validate()
Validates the structure of the
SubdivisionSearch graph. |
public final double epsilon
Subdivision.epsilon
of the associated
source
, whichever is greater.
The SubdivisionSearch
algorithm always uses a positive epsilon
to
guard against Subdivision.vertices()
with infinitesimal coordinate differences
that might corrupt the search structure. If you encounter exceptions or incorrect
search results for a given Subdivision
, try using a greater comparison
Subdivision.epsilon
in its creation.
public final Subdivision source
Subdivision
for which the SubdivisionSearch
graph was created.
Never null
. The SubdivisionSearch
graph is not updated to reflect
structural changes in the associated Subdivision
. You must create a new
SubdivisionSearch
to receive correct results for a changed source
.public SubdivisionSearch(Subdivision source, boolean ordered)
SubdivisionSearch
graph for the specified Subdivision
.
The ordered
parameter is intended for tests that require a known edge
insertion order. A random permutation is usually preferable, as the original
Subdivision.edges()
order can result in worst-case performance for the
SubdivisionSearch
algorithm.source
- the Subdivision
to searchordered
- true
to insert the Subdivision.edges()
of source
in their original order, false
to apply a random permutationjava.lang.NullPointerException
- if source
is null
public SubdivisionElement find(PointD q)
SubdivisionElement
at the specified PointD
coordinates within the associated source
.
Returns SubdivisionElement.NULL_FACE
if q
lies within the unbounded face
of the associated source
.
If q
coincides with a SubdivisionEdge
, find
always returns the twin
SubdivisionEdge
whose SubdivisionEdge.origin()
is lexicographically smaller
than its SubdivisionEdge.destination()
, according to PointDComparatorX
.
find
always uses the default epsilon
to determine whether q
coincides with an SubdivisionElement.edge()
or SubdivisionElement.vertex()
.
The SubdivisionSearch
algorithm does not support a comparison epsilon that is
significantly different from that which was used to construct the search structure.
q
- the PointD
coordinates to examineSubdivisionElement
that coincides with q
java.lang.NullPointerException
- if q
is null
public java.lang.String format()
String
that represents the entire SubdivisionSearch
graph.
Implemented as a new method, rather than overriding Object.toString()
,
because the returned String
may be hundreds or thousands of lines long.String
containing the Object.toString()
results for all nodes
in the SubdivisionSearch
graph, traversed in breadth-first orderpublic void validate()
SubdivisionSearch
graph.
Uses assert
statements to verify the structural invariants of the SubdivisionSearch
graph. Assertions must be enabled at runtime for validate()
to have any effect.java.lang.AssertionError
- if the structure of the SubdivisionSearch
graph is invalid


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Generative adversarial networks (GANs) are algorithmic architectures that use two neural networks, pitting one against the other (thus the “adversarial”) in order to generate new, synthetic instances of data that can pass for real data. They are used widely in image generation, video generation and voice generation.
To understand GANs, you should know how generative algorithms work, and for that, contrasting them with discriminative algorithms is instructive. Discriminative algorithms try to classify input data; that is, given the features of an instance of data, they predict a label or category to which that data belongs.
For example, given all the words in an email (the data instance), a discriminative algorithm could predict whether the message is spam or not_spam. spam is one of the labels, and the bag of words gathered from the email are the features that constitute the input data. When this problem is expressed mathematically, the label is called y and the features are called x. The formulation p(y|x) is used to mean “the probability of y given x”, which in this case would translate to “the probability that an email is spam given the words it contains.”
So discriminative algorithms map features to labels. They are concerned solely with that correlation. One way to think about generative algorithms is that they do the opposite. Instead of predicting a label given certain features, they attempt to predict features given a certain label.
The question a generative algorithm tries to answer is: Assuming this email is spam, how likely are these features? While discriminative models care about the relation between y and x, generative models care about “how you get x.” They allow you to capture p(x|y), the probability of x given y, or the probability of features given a label or category. (That said, generative algorithms can also be used as classifiers. It just so happens that they can do more than categorize input data.)
One neural network, called the generator, generates new data instances, while the other, the discriminator, evaluates them for authenticity; i.e. the discriminator decides whether each instance of data that it reviews belongs to the actual training dataset or not.
The goal of the discriminator, when shown an instance from the true dataset, is to recognize those that are authentic. Meanwhile, the generator is creating new, synthetic images that it passes to the discriminator. It does so in the hopes that they, too, will be deemed authentic, even though they are fake. The goal of the generator is to generate passable images: to lie without being caught. The goal of the discriminator is to identify images coming from the generator as fake.
Here are the steps a GAN takes:
So you have a double feedback loop:
The discriminator in a GAN is simply a classifier. It tries to distinguish real data from the data created by the generator. It could use any network architecture appropriate to the type of data it's classifying.
The discriminator's training data comes from two sources:
In Figure, the two "Sample" boxes represent these two data sources feeding into the discriminator. During discriminator training the generator does not train. Its weights remain constant while it produces examples for the discriminator to train on.
The discriminator connects to two loss functions. During discriminator training, the discriminator ignores the generator loss and just uses the discriminator loss. We use the generator loss during generator During the discriminator training:
The generator part of a GAN learns to create fake data by incorporating feedback from the discriminator. It learns to make the discriminator classify its output as real.
Generator training requires tighter integration between the generator and the discriminator than discriminator training requires. The portion of the GAN that trains the generator includes:
Neural networks need some form of input. Normally we input data that we want to do something with, like an instance that we want to classify or make a prediction about. But what do we use as input for a network that outputs entirely new data instances?
In its most basic form, a GAN takes random noise as its input. The generator then transforms this noise into a meaningful output. By introducing noise, we can get the GAN to produce a wide variety of data, sampling from different places in the target distribution.
Experiments suggest that the distribution of the noise doesn't matter much, so we can choose something that's easy to sample from, like a uniform distribution. For convenience the space from which the noise is sampled is usually of smaller dimension than the dimensionality of the output space.
To train a neural net, we alter the net's weights to reduce the error or loss of its output. In our GAN, however, the generator is not directly connected to the loss that we're trying to affect. The generator feeds into the discriminator net, and the discriminator produces the output we're trying to affect. The generator loss penalizes the generator for producing a sample that the discriminator network classifies as fake.
This extra chunk of network must be included in backpropagation. Backpropagation adjusts each weight in the right direction by calculating the weight's impact on the output — how the output would change if you changed the weight. But the impact of a generator weight depends on the impact of the discriminator weights it feeds into. So backpropagation starts at the output and flows back through the discriminator into the generator.
At the same time, we don't want the discriminator to change during generator training. Trying to hit a moving target would make a hard problem even harder for the generator.
So we train the generator with the following procedure each generation:
Because a GAN contains two separately trained networks, its training algorithm must address two complications:
The generator and the discriminator have different training processes. GAN training proceeds in alternating periods:
We keep the generator constant during the discriminator training phase. As discriminator training tries to figure out how to distinguish real data from fake, it has to learn how to recognize the generator's flaws. That's a different problem for a thoroughly trained generator than it is for an untrained generator that produces random output.
Similarly, we keep the discriminator constant during the generator training phase. Otherwise the generator would be trying to hit a moving target and might never converge.
It's this back and forth that allows GANs to tackle otherwise intractable generative problems. We get a toehold in the difficult generative problem by starting with a much simpler classification problem. Conversely, if you can't train a classifier to tell the difference between real and generated data even for the initial random generator output, you can't get the GAN training started.
As the generator improves with training, the discriminator performance gets worse because the discriminator can't easily tell the difference between real and fake. If the generator succeeds perfectly, then the discriminator has a 50% accuracy. In effect, the discriminator flips a coin to make its prediction.
This progression poses a problem for convergence of the GAN as a whole: the discriminator feedback gets less meaningful over time. If the GAN continues training past the point when the discriminator is giving completely random feedback, then the generator starts to train on junk feedback, and its own quality may collapse.
For a GAN, convergence is often a fleeting, rather than stable, state.
For better understanding of GANs and the Math behind it along eith the code, check out the jupyter notebook here.


/**
* Populate the current user associated with the JWT
*/
const defaults = {
userEndpoint: '/users',
idField: '_id'
};
export default function (options = {}) {
return function (hook) {
let id;
options = Object.assign({}, defaults, hook.app.get('auth'), options);
// If it's an after hook grab the id from the result
if (hook.type === 'after') {
id = hook.result[options.idField];
// Check to see if we have an id from a decoded JWT
} else Iif (hook.params.payload) {
id = hook.params.payload[options.idField];
}
// If we didn't find an id then just pass through
if (id === undefined) {
return Promise.resolve(hook);
}
return new Promise(function (resolve, reject) {
hook.app.service(options.userEndpoint).get(id, {}).then(user => {
// attach the user to the hook for use in other hooks or services
hook.params.user = user;
// If it's an after hook attach the user to the response
Eif (hook.result) {
hook.result.data = Object.assign({}, user = !user.toJSON ? user : user.toJSON());
// remove the id field from the root, it already exists inside the user object
delete hook.result[options.idField];
}
return resolve(hook);
}).catch(reject);
});
};
}
|


{% extends 'blocks/base.html' %} {% block content %}
Product requires V3 machine
Yes
1st production line has < 50,000 skates for that month
Allocate production line
No
2nd production line has < 50,000 skates for that month
...


Exception Assertions
These methods allow you to assert the throwing of an exception.
ShouldThrowException
Asserts that the Action should throw an exception.
Usage
Where
TExceptionType is an Exception
public static TExceptionType ShouldThrowException<TExceptionType>(Action action)
public static TExceptionType ShouldThrowException<TExceptionType>(Action action, string message)
public static TExceptionType ShouldThrowException<TExceptionType>(Action action, string message, params object[] parameters)
Remarks
This method is contained in the
Testing static class of the library.
Unlike the default Exception testing in Visual Studio, you can test multiple Exceptions within the same test method.
Example
[TestMethod]
public void Test()
{
int zero = 0;
Testing.ShouldThrowException<DivideByZeroException>( () => int x = 12 / zero );
}
[TestMethod]
public void Test()
{
// Multiple expected exceptions can be tested in the same test method
int zero = 0;
Testing.ShouldThrowException<DivideByZeroException>( () => int x = 12 / zero );
Testing.ShouldThrowException<InvalidCastException>( () => bool x = (bool)DateTime.Now );
}
Supported Releases: All


{{ define "main" }} {{partial "nav_regular.html" .}} {{if not (.Parent).IsHome}} {{partial "breadcrumb.html" .}} {{end}}
{{.Description}}
Back to Home
Back to {{(.Parent).Name}}


Website
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Originally from Chino Hills, California, Tiffany Walker is a choral conductor in Seattle, Washington. She is currently in her first year pursuing a Doctor of Musical Arts in Choral Conducting at the University of Washington. At the UW, Tiffany is the co-director of the Collegiate Treble Choir. Performances include UW Sings and Carolfest. She has also led an orchestral rehearsal with choir for the UW Campus Philharmonia Orchestras concert performance of The Pirates of Penzance.
Tiffany completed a Master of Arts in Teaching and Single-Subject Credential in K-12 music at the University of Southern California, studying under Dr. John Whitener, Christine DeMore, and Lisa Smith. Tiffany received a Bachelor of Arts degree in Music from the University of California, Berkeley, where her focus was vocal performance. She sang in the University Chorus and Chamber Singers under the direction of Dr. Marika Kuzma. She studied voice with Deborah Benedict, and with Melissa Landis as a post-graduate.
From 2007-2012, Tiffany taught private voice lessons and was an assistant director in the choral music department at Ruben S. Ayala High School in Chino Hills. As an assistant director, she conducted the Women’s Ensemble in a concert tour to Puerto Rico in 2011. In 2009, she helped prepare rehearsals and sang with the Vocal Ensemble at the Third International Choral Festival in Lima, Peru.
After completing her Master of Arts in Teaching degree and attaining her K-12 music credential, Tiffany taught as a high school choral director at San Clemente High School from 2012-2013, then at Ruben S. Ayala High School from 2013-2017. At Ayala HS, she had produced and directed an annual madrigal dinner, entitled Madrigal Feaste. She was also a member of the Southern California Vocal Association, and took her choirs to perform in numerous festivals. Her auditioned groups travelled for Spring tour, and won gold ratings at Heritage Festivals in San Francisco, Chicago, Seattle, and Washington, D.C.
Tiffany was a member of the Pacific Chorale under the direction of Dr. John Alexander and Dr. Rob Istad from 2008-2017. Some of her accomplishments with Pacific Chorale included performing at the Hollywood Bowl, being a chorister for Andrea Bocelli’s performance tour, singing world premieres commissioned by the Pacific Symphony, and participating in many live concerts and CD recordings at the Segerstrom Center for the Arts in Orange County.
The University of Washington Collegiate Treble Choir is currently performing
See the calendarA day long workshop focusing on choral technique
Festival adjudication comments and ratings
Guest conductor for regional and state conferences
Private Lessons
Together we'll make music that moves the soul


WITNESS LIST Licensing & Administrative Procedures Committee March 23, 2005-8:00A HB 1357 For: Atkins, Winnfield (DIAGEO) HB 1549 On: Coffey, Jan (Texas Dept. of Public Safety) HB 1817 - Committee Substitute (Hamilton/CSHB 1817) For: Schulle, Jr., Gerhardt (Texas Society of Professional Engineers) Stagner, Steve (Texas Council of Engineering Companies) On: Farrow, Dale Beebe (Texas Board of Professional Engineers)


| Package | Description |
|---|---|
| edu.wpi.first.wpilibj.image |
Provides classes to access National Instrument's nivison library for machine vision enables
automated image processing for color identification, tracking and analysis.
|
| edu.wpi.first.wpilibj.vision |
| Modifier and Type | Method and Description |
|---|---|
ColorImage |
ColorImage.colorEqualize()
Calculates the histogram of each plane of a color image and redistributes pixel values across
the desired range while maintaining pixel value groupings.
|
BinaryImage |
BinaryImage.convexHull(boolean connectivity8) |
NIVision.DetectEllipsesResult |
MonoImage.detectEllipses(NIVision.EllipseDescriptor ellipseDescriptor) |
NIVision.DetectEllipsesResult |
MonoImage.detectEllipses(NIVision.EllipseDescriptor ellipseDescriptor,
NIVision.CurveOptions curveOptions,
NIVision.ShapeDetectionOptions shapeDetectionOptions,
NIVision.ROI roi) |
void |
ImageBase.free()
Release the memory associated with an image.
|
MonoImage |
ColorImage.getBluePlane()
Get the blue color plane from the image when represented in RGB color space.
|
MonoImage |
ColorImage.getGreenPlane()
Get the green color plane from the image when represented in RGB color space.
|
int |
ImageBase.getHeight()
Get the height of the image in pixels.
|
MonoImage |
ColorImage.getHSIHuePlane()
Get the hue color plane from the image when represented in HSI color space.
|
MonoImage |
ColorImage.getHSISaturationPlane()
Get the saturation color plane from the image when represented in HSI color space.
|
MonoImage |
ColorImage.getHSLHuePlane()
Get the hue color plane from the image when represented in HSL color space.
|
MonoImage |
ColorImage.getHSLSaturationPlane()
Get the saturation color plane from the image when represented in HSL color space.
|
MonoImage |
ColorImage.getHSVHuePlane()
Get the hue color plane from the image when represented in HSV color space.
|
MonoImage |
ColorImage.getHSVSaturationPlane()
Get the saturation color plane from the image when represented in HSV color space.
|
MonoImage |
ColorImage.getIntensityPlane()
Get the intensity color plane from the image when represented in HSI color space.
|
MonoImage |
ColorImage.getLuminancePlane()
Get the luminance color plane from the image when represented in HSL color space.
|
int |
BinaryImage.getNumberParticles()
Returns the number of particles.
|
ParticleAnalysisReport[] |
BinaryImage.getOrderedParticleAnalysisReports()
Gets all the particle analysis reports ordered from largest area to smallest.
|
ParticleAnalysisReport[] |
BinaryImage.getOrderedParticleAnalysisReports(int size)
Gets all the particle analysis reports ordered from largest area to smallest.
|
ParticleAnalysisReport |
BinaryImage.getParticleAnalysisReport(int index)
Get a particle analysis report for the particle at the given index.
|
MonoImage |
ColorImage.getRedPlane()
Get the red color plane from the image when represented in RGB color space.
|
MonoImage |
ColorImage.getValuePlane()
Get the value color plane from the image when represented in HSV color space.
|
int |
ImageBase.getWidth()
Get the width of the image in pixels.
|
ColorImage |
ColorImage.luminanceEqualize()
Calculates the histogram of each plane of a color image and redistributes pixel values across
the desired range while maintaining pixel value groupings for the Luminance plane only.
|
BinaryImage |
BinaryImage.particleFilter(NIVision.ParticleFilterCriteria2[] criteria) |
BinaryImage |
BinaryImage.removeLargeObjects(boolean connectivity8,
int erosions)
removeLargeObjects filters particles based on their m_size.
|
BinaryImage |
BinaryImage.removeSmallObjects(boolean connectivity8,
int erosions)
removeSmallObjects filters particles based on their m_size.
|
ColorImage |
ColorImage.replaceBluePlane(MonoImage plane)
Set the blue color plane from the image when represented in RGB color space.
|
ColorImage |
ColorImage.replaceGreenPlane(MonoImage plane)
Set the green color plane from the image when represented in RGB color space.
|
ColorImage |
ColorImage.replaceHSIHuePlane(MonoImage plane)
Set the hue color plane from the image when represented in HSI color space.
|
ColorImage |
ColorImage.replaceHSISaturationPlane(MonoImage plane)
Set the saturation color plane from the image when represented in HSI color space.
|
ColorImage |
ColorImage.replaceHSLHuePlane(MonoImage plane)
Set the hue color plane from the image when represented in HSL color space.
|
ColorImage |
ColorImage.replaceHSLSaturationPlane(MonoImage plane)
Set the saturation color plane from the image when represented in HSL color space.
|
ColorImage |
ColorImage.replaceHSVHuePlane(MonoImage plane)
Set the hue color plane from the image when represented in HSV color space.
|
ColorImage |
ColorImage.replaceHSVSaturationPlane(MonoImage plane)
Set the saturation color plane from the image when represented in HSV color space.
|
ColorImage |
ColorImage.replaceIntensityPlane(MonoImage plane)
Set the intensity color plane from the image when represented in HSI color space.
|
ColorImage |
ColorImage.replaceLuminancePlane(MonoImage plane)
Set the luminance color plane from the image when represented in HSL color space.
|
ColorImage |
ColorImage.replaceRedPlane(MonoImage plane)
Set the red color plane from the image when represented in RGB color space.
|
ColorImage |
ColorImage.replaceValuePlane(MonoImage plane)
Set the value color plane from the image when represented in HSV color space.
|
BinaryImage |
ColorImage.thresholdHSI(int hueLow,
int hueHigh,
int saturationLow,
int saturationHigh,
int intansityLow,
int intensityHigh)
Return a mask of the areas of the image that fall within the given ranges for color values
|
BinaryImage |
ColorImage.thresholdHSL(int hueLow,
int hueHigh,
int saturationLow,
int saturationHigh,
int luminenceLow,
int luminenceHigh)
Return a mask of the areas of the image that fall within the given ranges for color values
|
BinaryImage |
ColorImage.thresholdHSV(int hueLow,
int hueHigh,
int saturationLow,
int saturationHigh,
int valueLow,
int valueHigh)
Return a mask of the areas of the image that fall within the given ranges for color values
|
BinaryImage |
ColorImage.thresholdRGB(int redLow,
int redHigh,
int greenLow,
int greenHigh,
int blueLow,
int blueHigh)
Return a mask of the areas of the image that fall within the given ranges for color values
|
void |
ImageBase.write(String fileName)
Write the image to a file.
|
void |
BinaryImage.write(String fileName) |
| Constructor and Description |
|---|
HSLImage()
Create a new 0x0 image.
|
HSLImage(String fileName)
Create a new image by loading a file.
|
MonoImage()
Create a new 0x0 image.
|
RGBImage()
Create a new 0x0 image.
|
RGBImage(String fileName)
Create a new image by loading a file.
|
| Modifier and Type | Method and Description |
|---|---|
HSLImage |
AxisCamera.getImage()
Instantiate a new image object and fill it with the latest image from the camera.
|


Discoverthreejs.com
Ch 7.1 Working with Lights: Spotlight.target
Spotlight target controls
Show Helper
Default Target (0,0,0)
Target Duck
Target Head
Target Horse


Vinibar |
69 € |
Recharges |
{{gift.order.credits}} € |
Livraison |
{{gift.order.delivery_cost}} € |
Réduction |
- {{gift.order.coupon_value}} € |
Total |
{{69 + gift.order.delivery_cost + gift.order.credits - gift.order.coupon_value | number:1}} € |
{{gift.order.receiver_address.first_name}} {{gift.order.receiver_address.last_name}}
{{gift.order.receiver_email}}
{{gift.order.receiver_address.street}}
{{gift.order.receiver_address.zipcode}} {{gift.order.receiver_address.city}}
SSL Secure


FROM: Jordan hamson ABIDJAN COTE D�IVOIRE WEST AFRICA ATTN: President Dear sir, It is my pleasure to write you, pending on this business proposal. It may be strange to you of whom I am and how I got your contact. However, I am Mr jordan Hamson a citizen of republic of Sierra- Leone. Also I am the accountant general / treasurer of the then republic of Sierra- Leone I am 33 years old of age and happily married. I got your contact through a reliable and a confident source with pleasant motives which I shall reveal to you as soon as you are interested to know. As you must have heard about my country (Sierra-Leone) and the serious suffering for humanity and the national unrest killing and hostility in the hands of the rebels this event have caused much more death and destruction of properties in the country. As a matter of fact my people have become emergency refugees in other Africa countries. Consequently I am badly affected because the rebels needed my assistance and co-operation by releasing the national treasury department to them which I Strictly refused their entry. Therefore out of my four children two was kidnapped including my father and they were eventually killed by the rebels. Further more, all my investments and other asst were burst to pieces. Even my life and my wife and rest of my family are in danger. But it was not only me in the government facing this hard time, all top the government official were also maltreated after all these, I patiently continued but I now see it necessary to quit Africa with my family since the trouble never make any step of reconciliation and Africa continent is very unreliable now as there�s political and ethnic war in every part. Presently, I am taking refugee with my family in Abidjan Côte d�Ivoire under the United Nations refugee umbrella. Unfortunately Côte d�Ivoire is Having political unrest and many equally burst to pieces soonest, so I am tired and sincerely need your support and assurance to invest wisely and relocate to your country through your productive ideas and qualities. I have $18.5 million US dollar to be invested in your country though your support and this existing amount is right safe and presently not in SIERRA LEONE but lodge in the custody of a security and finance company some where around west Africa region which I may disclosed to you as soon as I receive your complacence. I would be contented to have your private contact for security reasons and I am very optimistic to release a reasonable percentage of this amount to you for your assistance. I anticipate your speedy response remain. Please kindly contact me immediately you receive this message through my telephone number or my electronic box . Yours sincerely. Jordan Hamson _________________________________________________________________ Do You Yahoo!? -- Une adresse @yahoo.fr gratuite et en français ! Yahoo! Mail : http://fr.mail.yahoo.com


My Work
Blocipedia
Build a production quality SaaS app that allows users to create their own wikis.
Blocmetrics
An analytics and reporting tool that captures event data for registered users.
I'm a kickass developer specializing in Rails, AngularJS, and MongoDB.
Build a production quality SaaS app that allows users to create their own wikis.
An analytics and reporting tool that captures event data for registered users.


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Korea National University of Transportation
korea national university of transportation
Korea National University of Transportation
Korea National University of Transportation


So I was looking up the Trac instance for pudge (which is here). All of the lesscode Trac instances are styled to go with the rest of the site. Slick?
Now, I swear this is not just laziness speaking, but I think I prefer it without the template. Keeping the navigation wrapper from the site is nice (like Django does), but when I'm in a bug tracker I like to know my way around. To some degree I've started to feel comfortable in Trac (simply because it's become very common). I want consistency with other Trac instances, not with the site or project the tracker is attached to. The way I interact with a tracker has little or nothing to do with the project that uses it, and everything to do with the software behind the tracker.
I feel like there's some important user interface lesson here, but I don't think it's actually important enough for me to try to extract it. Plus that'd be pretentious. I'll say only this: hobgoblins!
I've felt the same way. The navigation in and out of trac instances, to the project pages, to the weblog is just wrong. I had a plan for that but... well... you know.


{include file="common/top"}
{volist name="banner" id="banner"}
{$banner.name}
{/volist}
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| Star | Watch | Fork |
| Home |
|---|
| User Guide |
| Examples |
| About |
RSOME (Robust Stochastic Optimization Made Easy) is an open-source Python package for modeling generic optimization problems. Models in RSOME are constructed by variables, constraints, and expressions that are formatted as N-dimensional arrays. These arrays are consistent with the NumPy library in terms of syntax and operations, including broadcasting, indexing, slicing, element-wise operations, and matrix calculation rules, among others. In short, RSOME provides a convenient platform to facilitate developments of optimization models and their applications.
The RSOME package can be installed with the pip
command:
pip install rsome
The current version of RSOME supports deterministic, robust optimization and distributionally robust optimization problems. In the default configuration, linear programming problems are solved by the open-source solver linprog()
imported from the scipy.optimize
package. Details of this solver interface, together with interfaces of other open-source and commercial solvers are presented in the following table.
| Solver | License type | RSOME interface | Integer variables | Second-order cone constraints |
|---|---|---|---|---|
| scipy.optimize | Open-source | lpg_solver |
No | No |
| CyLP | Open-source | clp_solver |
Yes | No |
| OR-Tools | Open-source | ort_solver |
Yes | No |
| Gurobi | Commercial | grb_solver |
Yes | Yes |
| MOSEK | Commercial | msk_solver |
Yes | Yes |
| CPLEX | Commercial | cpx_solver |
Yes | Yes |
The RSOME package supports specifying models using highly readable algebraic expressions that are consistent with NumPy syntax. A very simple linear program example is provided below,
\[\begin{align} \max ~&3x + 4y \\ \text{s.t.}~&2.5x + y \leq 20 \\ &5x + 3y \leq 30 \\ &x + 2y \leq 16 \\ &|y| \leq 2, \end{align}\]and it is used to illustrate the steps of solving optimization models.
from rsome import ro # import the ro modeling tool
model = ro.Model('LP model') # create a Model object
x = model.dvar() # define a decision variable x
y = model.dvar() # define a decision variable y
model.max(3*x + 4*y) # maximize the objective function
model.st(2.5*x + y <= 20) # specify the 1st constraints
model.st(5*x + 3*y <= 30) # specify the 2nd constraints
model.st(x + 2*y <= 16) # specify the 3rd constraints
model.st(abs(y) <= 2) # specify the 4th constraints
model.solve() # solve the model by the default solver
Being solved by the default LP solver...
Solution status: 0
Running time: 0.0426s
In this sample code, a model object is created by calling the constructor Model()
imported from the rsome.ro
toolbox. Based on the model object, decision variables x
and y
are created by the method dvar()
. These variables are then used in specifying the objective function and model constraints. The last step is calling the solve()
method to solve the problem. Once the solution completes, a message showing the solution status and running time will be printed.
You may find the interpretation of the solution status code of linprog()
from the website scipy.optimize.linprog
. The status code 0
suggests that the problem was solved to optimality (subject to tolerances), and an optimal solution is available. The optimal solution and the corresponding objective value can be attained by the get()
method.
print('x:', x.get())
print('y:', y.get())
print('Objective:', round(model.get(), 2))
x: [4.8]
y: [2.]
Objective: 22.4
The example above shows that RSOME models can be formulated via straightforward and highly readable algebraic expressions, and the formulated model can be transformed into a standard form, which is then solved by the integrated solver. The basic information of the standard form can be retrieved by calling the do_math()
method of the RSOME model object.
formula = model.do_math()
print(formula)
Second order cone program object:
=============================================
Number of variables: 3
Continuous/binaries/integers: 3/0/0
---------------------------------------------
Number of linear constraints: 6
Inequalities/equalities: 6/0
Number of coefficients: 11
---------------------------------------------
Number of SOC constraints: 0


3
Pray for Us
1 Finally, brothers, pray for us, that the word of the Lord may speed ahead and be honored, as happened among you,
2 and that we may be delivered from wicked and evil men. For not all have faith.
3 But the Lord is faithful. He will establish you and guard you against the evil one.
4 And we have confidence in the Lord about you, that you are doing and will do the things that we command.
5 May the Lord direct your hearts to the love of God and to the steadfastness of Christ.
Warning Against Idleness
6 Now we command you, brothers, in the name of our Lord Jesus Christ, that you keep away from any brother who is walking in idleness and not in accord with the tradition that you received from us.
7 For you yourselves know how you ought to imitate us, because we were not idle when we were with you,
8 nor did we eat anyone's bread without paying for it, but with toil and labor we worked night and day, that we might not be a burden to any of you.
9 It was not because we do not have that right, but to give you in ourselves an example to imitate.
10 For even when we were with you, we would give you this command: If anyone is not willing to work, let him not eat.
11 For we hear that some among you walk in idleness, not busy at work, but busybodies.
12 Now such persons we command and encourage in the Lord Jesus Christ to do their work quietly and to earn their own living.
13 As for you, brothers, do not grow weary in doing good.
14 If anyone does not obey what we say in this letter, take note of that person, and have nothing to do with him, that he may be ashamed.
15 Do not regard him as an enemy, but warn him as a brother.
Benediction
16 Now may the Lord of peace himself give you peace at all times in every way. The Lord be with you all.
17 I, Paul, write this greeting with my own hand. This is the sign of genuineness in every letter of mine; it is the way I write.
18 The grace of our Lord Jesus Christ be with you all.


| SV Producer | |
| Description | A generic producer parameterized on transaction type. |
A generic producer parameterized on transaction type. Used to illustrate different converter options using the same producer class. Doesn’t do anything functionally useful. Sends a transaction out a out put port and receives the same packet via its in_ap analysis imp. The write function compares to make sure the conversion happened properly in both directions.
class producer #(type T=int) extends ovm_component; ovm_blocking_put_port #(T) out; ovm_analysis_imp #(T,producer#(T)) ap_in; int num_pkts; packet expected_pkt; `ovm_component_param_utils(producer #(T)) function new(string name, ovm_component parent=null); super.new(name,parent); out = new("out", this); ap_in = new("ap_in", this); num_pkts = 10; endfunction : new virtual task run(); ovm_test_done.raise_objection(this); for (int i = 1; i <= num_pkts; i++) begin int unsigned exp_addr; byte exp_data[$]; T pkt = new(); assert(pkt.randomize()); exp_addr = ~pkt.addr; foreach (pkt.data[i]) exp_data[i] = ~pkt.data[i]; `ovm_info("PRODUCER/PKT/SEND_REQ", $sformatf("SV producer request:\n %s", pkt.convert2string()), OVM_MEDIUM) expected_pkt = pkt; out.put(pkt); end `ovm_info("PRODUCER/END_TEST","Dropping objection to ending the test",OVM_LOW) ovm_test_done.drop_objection(this); endtask virtual function void write(packet t); `ovm_info("PRODUCER/PKT/RECV_RSP", $sformatf("SV producer response:\n %s\n", t.convert2string()), OVM_MEDIUM) if (t.addr != expected_pkt.addr) `ovm_error("PRODUCER/PKT/ADDR_MISCOMPARE", $sformatf("Expected address to be %h, got back %h", expected_pkt.addr,t.addr)) if (t.data != expected_pkt.data) `ovm_error("PRODUCER/PKT/DATA_MISCOMPARE", $sformatf("Expected data to be %p, got back %p", expected_pkt.data,t.data)) expected_pkt = null; endfunction endclass


This is Ruba Banat . I'm 24 years old , I studied Economic of finance and business in Yarmouk University and I graduated in 2018 , I had a great volunteer work experience with an international organization that gave me a lot , but I don't have any professional work experience yet so I decided to try something new something I aspire to do so I found this chance , and I believe it is the way to fulfill my ambition. The best is coming .


Cumberland leads Cincinnati over Illinois St. 66-65
by EndPlayST. THOMAS, U.S. VIRGIN ISLANDS (AP) - Jarron Cumberland scored 23 points, including the game-winner with eight seconds left as Cincinnati rallied to defeat Illinois State 66-65 in the U.S. Virgin Islands Paradise Jam on Friday night.
Chris Vogt had 13 points and 13 rebounds for Cincinnati (3-1). Tre Scott added 14 points and Keith Williams 12 for Cincinnati.
Dedric Boyd scored 18 points for the Redbirds (2-2), Zach Copeland added 12 points.
Illinois State slowly widened a 33-30 halftime lead to 10 points midway through the second half when Boyd buried a jumper to make it 57-47. Cincinnati, which was 21 of 28 at the foul line to the Redbirds' 5 of 9, used free throws to nibble away at the lead.
Cumberland hit a 3 that cut the gap to 63-60 with just under three minutes to go, and Williams drove for a layup, making it a one-point game, 63-62.
With 34 seconds remaining, Williams fed to Scott for a dunk and the Cincinnati lead, 64-63. Illinois State answered with a dunk, but Cumberland scored the winner with a layup and Illinois State missed a 3-point try with two seconds left.
Cincinnati plays UNLV at home next Saturday. Illinois State plays Illinois-Springfield at home next Friday.
___
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
___
Elements of this story were generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com


Plot of Small Circles:
This program draws small circles with the projections used in Fabric7. Only manual data input is possible. In the menu 'angle' the scaling (1..360° or 1..400gon) must be chosen.


My last stab at mincemeat models wasn’t very pretty – wrapping different method sets in blocks and folding them.
This is what I’ve been doing lately instead, to keep fat Rails models manageable.
Background
In Ruby, there is the concept of the load path. Basically, if you require "foo"
, Ruby will first look for “foo.rb” in your current directory, then in each of the directories in the load path.
Rails adds several directories to your load path, such as "#{RAILS_ROOT}/lib"
and "#{RAILS_ROOT}/app/models"
.
Furthermore, Rails does some magic with Module#const_missing
: if you use a module (classes are modules, too, by inheritance) that isn’t known, Rails will automatically try to require
a file.
The filename is assumed to be the name of the module. If the module is nested in other modules, any but the right-most module are assumed to be directories. CamelCase is converted to snake_case. So FooBar::Baz
translates to foo_bar/baz.rb
.
This is why you don’t have to explicitly require your models or controllers: their directories are in the load path, and their files follow this naming convention.
Extensions
To break some code out of a model, create a directory under app/models
with the same name as the model, then put your extension files in this directory, and name them according to the convention.
So to extend the User
model, you could create app/models/user/authentication_extension.rb
:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 |
|
Though this file is automatically loaded when you refer to the module, you still have to refer to it, and explicitly include it in the model class. Like so:
1 2 3 |
|
The module we defined is User::AuthenticationExtension
, but within the User
class you don’t have to fully qualify the name. Note that this means you have to be careful what names you use: if you define a User::Forum
module for code related to a forum system, and also have a Forum
model, you will have to use ::Forum
to refer to the latter from within the User
model.
I use the FooExtension
naming scheme to avoid these conflicts.
Constant repositories
In addition to including modules, you can also use the same idea to e.g. store a bunch of related constants.
If you, say, find yourself using a lot of raw SQL in a model, you could create a class
1 2 3 4 5 6 7 8 |
|
and then refer to the constants as e.g. User::SQL::SOME_QUERY
, or just SQL::SOME_QUERY
from within the model.
The same caveat about class name conflicts applies.
In closing
As was brought up in comments on my last post on this subject, keep in mind that it is sometimes better to create more models, rather than fattening the ones you have. But if they must be fat, cut them up.


Installation¶
Elle’s installation is quite straightforward if all you want to do is use the FourL frontend as described in Usage of the LLL Frontend, and somewhat more involved if you want to be able to generate, build, check, or modify the implementation and proofs of Elle.
Getting Elle¶
In the rest of this file, let >
stand for a bash-compatible shell
prompt (that is, lines starting with >
are to be understood as input)
Clone Elle from the Github repo as follows:
> git clone https://github.com/mmalvarez/eth-isabelle
Later in this file, we assume that Elle is checked out into
a directory called eth-isabelle
. (This repository has this name because
it is a fork of Yoichi Hirai’s eth-isabelle <https://github.com/pirapira/eth-isabelle>
project specifying EVM in the Isabelle proof assistant.)
Since Elle is no longer under active development, the master
branch should
be stable enough to build reliably. For a version of Elle that is more guaranteed
to build successfully, try the ITP2019
branch, which contains an artifact
submission for the 2019 edition of the Interactive Theorem Proving conference:
> cd eth-isabelle
> git checkout ITP2019
Installation as an End-User of Elle¶
The following dependencies are required to build llllc
, the
FourL command-line interface to the FourL compiler frontend that makes
use of Elle’s verified compiler.
- Ocaml (tested with v4.05.0)
- OcamlBuild
- OCaml Zarith
On an Ubuntu-like system, these can be installed as follows:
> apt-get install ocaml ocamlbuild libzarith-ocaml libzarith-ocaml-dev
Once these dependencies are installed, navigate to eth-isabelle/elle/generated
and run make
. This should succeed and generate a file called llllc
.
When run on an lll file, it will print (to standard output) a hexadecimal
representation of the bytecode produced by the compiler for that smart contract
(similar to Solidity LLL’s command-line tool, but with fewer options and error
messages). Files to run llllc
on can be found in the eth-isabelle/elle/tests
directory.
For example:
> cd eth-isabelle/elle/generated
# output snipped
> make
# output snipped
> ./llllc ../tests/if.lll
6001600a576003600d565b60025b
Usage of llllc
is described further in Usage of the LLL Frontend
To help inspect the output of llllc
, you may find it useful to use the
EVM bytecode parser contained in eth-isabelle:
eth-isabelle/parser/hexparser.rb <https://github.com/mmalvarez/eth-isabelle/blob/master/parser/hexparser.rb>
You’ll need an installation of Ruby (tested with 2.5.1p57) to use this tool. It takes hex bytecodes like those
output by llllc
(or other compilers for Ethereum, such as Solidity LLL) on standard input and outputs
(on standard output)
a series of mnemonics describing the opcodes in the input.
Installation for Modifying and Examining Elle¶
The Elle git repository includes the file eth-isabelle/elle/generated/FourL.ml <https://github.com/mmalvarez/eth-isabelle/blob/master/elle/generated/FourL.ml>. This file is generated from the formal Isabelle model contained in the rest of the Elle repository, and is all that is needed to build a working executable version of Elle/FourL as described in end-user-installation.
In order to work with the formal model directly, Isabelle itself is needed as a dependency. Elle requires Isabelle 2018, which can be downloaded here<https://isabelle.in.tum.de/website-Isabelle2018/index.html> (binaries for Linux, MacOS, and Windows are provided).
Once Isabelle is installed, the user will need to set up Lem, a framework used to generate the some of the Isabelle specifications used by Elle. In order to do this, first run the following, to update the Lem submodule contained in Elle’s git repository:
> cd eth-isabelle
> git submodule init
# output snipped
> git submodule update lem-installation
# output snipped
we have tested with the version of Lem having the Git hash of 0927743c1bd31d7bba20a54260ba4c4dd3ce49e9
.
Newer versions should also work. Older versions may not support generating code compatible with Isabelle2018.
In order to build Lem, run the following:
> cd lem-installation
> make
# output snipped
If this succeeds, it will generate an executable called lem
. Add it to your path, and ensure the
it will look for its libraries in the correct place, by running the following:
> `export PATH=$PWD/lem-installation/bin:$PATH`
> `export LEMLIB=$PWD/lem-installation/library`
Finally, navigate back to the root of the repository (eth-isabelle
), and run the following to
build the .thy
files that Elle depends on of from their Lem sources:
> make lem-thy
Examining Elle Sources¶
Isabelle allows .thy
files representing formal models and
proofs to be grouped together into sessions. Sessions make it easier
to automate the process of compiling Isabelle developments, as well
as allowing for caching the results of compilation and proof-checking
so that work does not need to be repeated each time Isabelle is
re-opened. Elle contains a session called ElleCorrect
, which
packs together all the files containing Elle’s correctness proofs into
a single session file.
However, in order to be able to
step through the proofs contained in the ElleCorrect
session,
it’s better not to run the ElleCorrect
session, since. Therefore,
to examine Elle’s proofs,
run Isabelle-Jedit, with the HOL
session
isabelle jedit -d ./lem -l HOL
For some proofs (particularly the more complex ones in elle/ElleCorrect
)
you will need to increase the editor’s limit on the number of allowed tracing
messages (or else the proofs will pause and appear to get stuck). To do this,
navigate through the Isabelle/JEdit menus as follows
Plugins > Plugin Options > Isabelle > General > Editor Tracing Messages
Increase this value to 30000.
The most interesting proofs are in eth-isabelle/elle/ElleCorrect
. The final
correctness theorems for the compiler are elle_alt_correct*
in eth-isabelle/elle/ElleCorrect/ElleAltSemantics.thy
For more details on the structure of Elle, see Implementation.
Recreating FourL.ml¶
The command-line binary version of the Elle-based FourL compiler depends on
FourL.ml
, an Ocaml file that is produced from a formal Isabelle model
via Isabelle’s built-in extraction mechanism. As such, FourL.ml can be regenerated
from Elle’s sources, provided Isabelle is installed. This can be done as follows:
> isabelle jedit -d ./lem -d ./elle -l ElleCorrect
This will open the ElleCorrect
session (building this session for the first time
can take some time - as much as a couple of hours on a 16Gb machine). Once this session
is done being processed, open the file eth-isabelle/elle/ElleCorrect/FourLExtract.thy
.
If that file is processed to the end (which can be forced by moving the cursor to the end of the file)
it will create a new version of eth-isabelle/elle/generated/FourL.ml
, which can then be built as
described in end-user-installation.


| 1 | package fr.sii.ogham.assertion.internal; | |
| 2 | ||
| 3 | import static fr.sii.ogham.assertion.AssertionHelper.assertThat; | |
| 4 | ||
| 5 | import java.util.Set; | |
| 6 | ||
| 7 | import org.apache.commons.lang3.reflect.FieldUtils; | |
| 8 | import org.hamcrest.Matcher; | |
| 9 | import org.thymeleaf.TemplateEngine; | |
| 10 | ||
| 11 | import fr.sii.ogham.assertion.HasParent; | |
| 12 | import fr.sii.ogham.template.thymeleaf.common.ThymeleafParser; | |
| 13 | ||
| 14 | /** | |
| 15 | * Helper class to make assertions on {@link ThymeleafParser} instance created | |
| 16 | * by Ogham. | |
| 17 | * | |
| 18 | * @author Aurélien Baudet | |
| 19 | * | |
| 20 | */ | |
| 21 | public class ThymeleafParserAssertions extends HasParent<ThymeleafAssertions> { | |
| 22 | private final Set<ThymeleafParser> parsers; | |
| 23 | ||
| 24 | public ThymeleafParserAssertions(ThymeleafAssertions parent, Set<ThymeleafParser> parsers) { | |
| 25 | super(parent); | |
| 26 | this.parsers = parsers; | |
| 27 | } | |
| 28 | ||
| 29 | /** | |
| 30 | * Ensures that {@link TemplateEngine} is configured as expected. | |
| 31 | * | |
| 32 | * @param <T> | |
| 33 | * the type of expected object | |
| 34 | * @param matcher | |
| 35 | * the matcher to ensure that engine is configured as expected. | |
| 36 | * @return this instance for fluent chaining | |
| 37 | */ | |
| 38 | public <T extends TemplateEngine> ThymeleafParserAssertions engine(Matcher<? super TemplateEngine> matcher) { | |
| 39 |
2
1. engine : All methods instructions replaced by: return null; → KILLED 2. engine : All methods instructions replaced by: return null; → KILLED |
for (ThymeleafParser thymeleafParser : parsers) { |
| 40 | assertThat(getEngine(thymeleafParser), matcher); | |
| 41 | } | |
| 42 | return this; | |
| 43 | } | |
| 44 | ||
| 45 | private TemplateEngine getEngine(ThymeleafParser parser) { | |
| 46 | try { | |
| 47 |
2
1. getEngine : All methods instructions replaced by: return null; → KILLED 2. getEngine : All methods instructions replaced by: return null; → KILLED |
return (TemplateEngine) FieldUtils.readField(parser, "engine", true); |
| 48 | } catch (IllegalAccessException e) { | |
| 49 | throw new IllegalArgumentException("Failed to get 'engine' field of ThymeleafParser", e); | |
| 50 | } | |
| 51 | } | |
| 52 | } | |
Mutations | ||
| 39 |
1.1 2.2 |
|
| 47 |
1.1 2.2 |


| Binance | BitMax | sum | |
|---|---|---|---|
| BNB | N/A | N/A | N/A |
| USDT | N/A | N/A | N/A |
| N/A | N/A |
| Binance | diff/max profit | BitMax |
|---|---|---|
| N/A | N/A | N/A |
| N/A | N/A (N/A) |
N/A |
| N/A | N/A | |
| N/A | N/A |
WHITE: Close, last trading price
GREEN: Bid, people would buy at this price
RED: Ask, people would sell at this price
We want to buy from RED and sell to GREEN with profits.
| Time | Exchange | Side | Order | Fill | Status |
|---|
| Time | Binance | BitMax | Profit |
|---|


What is MagiWord?
Our Team
Install
Quit
Installation manual
1. Download .zip file with extension via this
link
.
2. Open the file and copy magiword folder to some path on your PC.
3. Open the browser and click options button in the top right corner.
4.
5. Turn on Developer mode in the top right corner.
6. Press "Load unpacked" and choose path to magiword folder. Make shure to choose FOLDER, not some other file.
7. Turn the extension on and enjoy learning new words with MagiWord!


Creates an empty tag file. Use tag files for creating custom JSP tags.
This is a JSP 2.0 facility that allows you to write tags using JSP syntax.
Tag file authors are not required to know how write Java classes. Tag
files should be placed under the /WEB-INF/tags
directory of the web application.


Experience
Summary
- 6+ years experience in Developer Relations/Developer Advocacy/Developer Evangelism
- 10+ years experience as a Developer
- Open source contributor
- Docs update lover
Skills
- Programming
- HTML/CSS/JS (ES2015+) or "frontend web development"
- WebAssembly
- JS Web APIs
- WebRTC
- JS frameworks
- Node.js/Deno
- "backend web development"
- Rust
- Python
- Databases (SQL and noSQL)
- Marketing
- Creating content campaigns
- Using analytics to determine KPIs/success
- Multi-channel marketing campaigns
- Developer-centric marketing
- Community Building
- Twitter/Dev.to/Discord/GitHub
- Creating champion or MVP programs
- Interacting with users with problems
- Engaging with community
- Content Creation
- Written content
- Book-writing
- Product-oriented blog posts
- Mentor other team members to write content
- Video content
- Product and concept videos
- Webinars
- Basic video editing
- Public Speaking
- Speaking at developer conferences
- Speaking at events with less technical people
- Communication
- Direct communication
- Takes constructive feedback well
- "Works out loud"
- General
- Mentoring
- Early management skills
- Fast learner
Work History
This can be located on
my LinkedIn Page.