15 Oct 2018
Determining the price of an Airbnb rental in Chicago and the factors that influence it
Photo from Pexels
Airbnb has been growing in popularity over the years - to a point now - where it has emerged as a viable alternative to hotels. It is especially alluring to travelers who are looking for cheaper yet comfortable accommodations - while looking to experience a distinct local flavor. And the popularity shows.
A quick check of the search trends for the Airbnb website Google Trends shows a steady increase in its popularity over the past five years.
(An aside: watch this space for a companion piece on time-series modeling of the Google trends data using Facebook’s Prophet.)
Google Trends data on the web searches for the Airbnb website for the past five years.
So as a part of the second project in the Metis Data Science Bootcamp, I worked on getting data about Airbnb listings in the Chicago area to try and predict what factors influence their pricing.
Scraping the data
In 2007, three young entrepreneurs started what was at the time called Airbedandbreakfast.com. Since then, Airbnb has not only shortened its name, but has expanded to more than 34,000 cities and as of 2016, had been used by more than 60 million guests. The company is currently the second-highest valued startup in the U.S. at $31 billion.
Business Insider
The $31 billion kitty for Airbnb comes from their commission ranging from 3-12% of the rental price depending on the listings. But, what features of the host’s offering helps set the price of their rentals (and which features dont) was the main aim of my analysis.
To identify some of the features to model the price of the rental, i turned to what the host’s thought were the top selling points of their offering that would entice a potential customer to choose them. I scrapped their descriptions and created a wordcloud to identify the most common features advertised.
The most important features in the host’s own words.
Interestingly, some of the main features that are highlighted here are the bedrooms of the rental offerings, which could be private rooms, apartments or condos, and entire houses. Another key selling points seems to be the location of the property.
Based on this analysis and a study of almost 51 different features offered by the host, I whittled the list down to 10 variables that could best predict the rental price using the Variance Inflation Factor (for an explanation of the VIF and how it was used to select features for predicting how drugs are prices, read the blog by the King of Scraping, Charlie Yaris).
Is the price right?
10 best features used to predict the price of an Airbnb rental.
The features and the price of the rental were fed into a linear regression model to see if they could predict the price of the rental. The resultant model was not one of the best, as the model scores (R^2, for the technical audience) indicated, but there were some interesting takeaways from the analysis.
Firstly, the number of bedrooms and baths clearly had the biggest influence on the price of the rental. For every bedroom offered, the host could charge $23 more per night. So, $46 for two bedrooms, $69 for three and so on. Add to it $10 more per bath added. As a result, entire homes and condos fared better than private rooms.
Entire homes pulled in a bigger share of rental prices compared to private rooms.
Although the location of the rental seems to matter in the preliminary analysis, the model did not corroborate that observation. One possibility the median rental prices in a zipcode I used as a numerical proxy for the role of a location in rental pricing may not have been the best measure. However, I did get some interesting results about rentals along transit routes in Chicago, which will be the subject of another blog! So stay tuned!
The curse of a review?
Superhosts are hosts who have been offering up their homes for a considerable period of time, and have consistently earned good reviews. One would assume that these superhosts could demand a better price for their rental compared to normal hosts. But, that was not the case!
Highly reviewed superhosts do not earn more.
This trend was evident in the correlation plot which also showed that the number of reviews a rental received did not track the price of that rental. However, why that would be the case, is still unclear.
- Python : for most of the cleaning and analysis
- Pandas dataframes
- Beautiful Soup
- Selenium
- Wordcloud
Check out my GitHub repo for more details regarding the project, codes and results!
Next Steps
Off to week four and classification problems with SQL! Keep an eye on this blog for more updates in the coming weeks! I leave you with some interesting quotes from some truly learned people!
Interesting Quotes
“It has become appallingly obvious that our technology has exceeded our humanity.”-  Steve Wozniak
“Simplicity is about subtracting the obvious and adding the meaningful.”- John Maeda
01 Oct 2018
Takaways from Exploratory Data Analysis using NYC MTA Turnstile data
Photo by Jamie McInall from Pexels
Week one of the Metis Data Science Bootcamp saw us wade neck deep into analyzing data - in its full glory, and I kid you not - it was messy! But the final outcome was something, which as a rank newcomer - I was proud of!
This project was designed such that we would face the rigors of understanding the data, clean it and analyze it to come up with recommendations for a fictional client. Women Yes Women Tech (WYWT) International wanted us to analyze the MTA Turnstile data to suggest where to place their street team of volunteers to maximize sign-ups for their cause and increase attendance in their summer gala.
Now, why MTA turnstile data, you may ask.
NYC MTA turnstile data
In 2016, average weekday subway ridership was 5.7 million, the highest since 1948. Annual ridership was 1.757 billion.
MTA info
Given this ridership, it should come as no surprise that the data from the turnstiles - that register the traffic through the New York subway system at each entrance of each station every four hours - would be ideal for our analysis. Given the rather low response rates (10-12%) for external surveys, identifying stations with the highest footfalls could yield a good conversion rate, i.e, more donors to WYWT’s cause.
Given that WYWT would hold their gala in summer, we pulled out the turnstile data for the months preceding it, from March to May and used it for our analysis.
Based on our cleaned-up data (maybe I should go over how we did all that in another blog post?), we came up with a list of top stations with the highest footfalls. We focussed on the number of exits from any given station, as we inferred that people would be more amenable to chatting with volunteers at their destination.
Top MTA stations based on the turnstile Data
The income angle
GPS locations of the top MTA stations that we selected. Larger circles indicate more foot falls.
WYWT is looking to expand on its donor base through the street campaign, so we decided to add income data from Kaggle (household income data), to supplement the footfall data and get more meaning into our analysis.
We identified the zipcodes around our top stations and mapped the income distribution around these locations.
GPS locations of the income distribution. Darker circles indicate higher incomes.
We also devised a simple algorithm that mapped both footfall and income data into a single function, adding weights to each component so that we could tweak the recommendations towards either income heavy stations or footfall heavy stations, based on the client’s preference. For more on that checkout my cohort-mate and project team member Tim Bowlings’s blog here.
GPS map of top ranked MTA Stations based on the combined income and turnstile data.
Our recommendations
-
List of top fifty stations based on our combined income and footfall ranking system.
-
Mondays and Fridays are the best days for positioning street teams at the exits of the stations to maximize their impact as the ridership peaks on those days.
The turnstile data was separated by the days of the week and aggregated over the entire period of 13 weeks to give rise to the distribution of exits over the days of the week for selected stations with the shadow being the 95% confidence interval around each line plot.
Note: Wednesday traffic seem to be fluctuating more than any other day for the period we analyzed.
- Python : for most of the cleaning and analysis
- Pandas dataframes
- Matplotlib
- Seaborn
- Tableau
- GeoPy
Next Steps
Off to week two and web scraping! Keep an eye on this blog for more updates in the coming weeks! I leave you with some interesting quotes on data from some truly learned people!
Interesting Quotes on Data
“It is a capital mistake to theorize before one has data.”- Arthur Conan Doyle, Author of Sherlock Holmes
“Torture the data, and it will confess to anything.” – Ronald Coase, winner of the Nobel Prize in Economics
The world is one big data problem.”- Andrew McAfee, MIT scientist
01 Oct 2018
My personal journey towards Data Science.
A Molecular Biologist and Biochemistry PhD by training, I have over a decade of research experience under my belt.
However, classical molecular biology has, in recent years, evolved technologically, to generate terabytes of digitized data – resulting from genomics and proteomics experiments.
About five years ago, I diversified from my core field into genomics and proteomics, which necessarily involved data analysis. I began learning the R language and using it to analyze data sets. My foray into data analysis led to my appreciation of the appeal and power of using R not just to operate on datasets popularly termed as ‘big data’, but to also extract meaningful, statistically-significant analysis.
I published my research results in the journal Nature, and followed it up with another publication in Nature Communications. These experiences got me interested in learning how to harness the power of data analysis, particularly with the advent of AI techniques in understanding biological data. And this is just data academic research.
Currently, the healthcare industry offers a treasure trove of data in the form of patient database - measurements, images and diagnostic tests - that could amount to 80MB data per person each year. Add to it, fitness data from iPhones and fitbits, government websites (CDC and FDA), insurance claims and other health records – that is a mind-boggling amount of data to sift through, analyze and make sense of.
Expert estimates peg the health data analytics industry to touch $24 billion by the year 2020. And with good reason – such investments in the health care industry will decrease healthcare costs for the patient and improve overall well-being of the population as well! Besides, this will bode well for businesses too.
It is evident from literature survey that supervised and unsupervised machine learning are widely popular and being applied to categorize the vast plethora of viruses and in grading tumors based on their molecular signatures. But this is just the beginning.
This data-driven transformation is not restricted to biology or the health care industry alone. The broad scope of inquiry using data – particularly continuous streams using IOT – will place data analysis as a sought-after skill set.


This test fetches an URL via the plugin, and verifies that the callbacks are expected and that the retrieved content is correct.


Imagine affordable, solar-powered and weather-proof dice that will take a photo every minute, hour or day.
Things happen too fast for us to realize them. Time-lapse enables exciting insights about change over longer periods of time.
Capturing time in a new format.
Not just photos or videos of a party, wedding or day at the office. A time-lapse is a more fun way to document an event from a certain angle over a longer period of time.
Nature & Development
Sure there is many ways to make a time-lapse video. Our approach:
Affordable Gadget
We don't know the final price yet, but our goal is to stay under 100$. Sure you can make awesome stuff with your DSLR, but will you let it sit in your garden for 3 months to capture spring move in?
Smart Design.
Besides being solar-powerd to enable long term projects, we chose a Rhombicuboctahedron for shape, since you then can tilt the camera almost any way you want it. Also each side will have a socket for your favourite tripod.
Easier to use than an actual camera.
Just 3 settings. Taking photos every minute, hour or day. When you are done, connect it to your computer and upload the project folder to our web app. We will let you kick out frames that you don't want in the final version, apply filters and share the outcome with your friends.
Subscribe now to get notified as soon as crowdfunding of this project starts!
Status: Just started prototyping.
We aim for way better quality than you see in the sample gif. It won't be made out of cardboard either.
Encourage us to proceed by sharing / liking this page.
Feel free to contact Michael Schwanzer if you want to help with this project or have questions. Read more on the blog.


' Our Posts '
post title goes here
With over 11,000 employees, University Medical Center Utrecht is one on the biggest public healthcare institutions in the Netherlands and the biggest employer in the region.
post title goes here
With over 11,000 employees, University Medical Center Utrecht is one on the biggest public healthcare institutions in the Netherlands and the biggest employer in the region.
post title goes here
With over 11,000 employees, University Medical Center Utrecht is one on the biggest public healthcare institutions in the Netherlands and the biggest employer in the region.


Small batch shoreditch synth 90's. Adipisicing reprehenderit consectetur et, polaroid jean shorts nihil veniam. Exercitation hella put a bird on it, plaid mollit pinterest magna brunch chillwave meh selfies 90's fixie photo booth. Put a bird on it photo booth farm-to-table, assumenda odd future sapiente ut beard authentic. Delectus accusamus cillum laborum tumblr gluten-free, farm-to-table organic hoodie est yr next level occaecat vice ex. Dolore polaroid master cleanse synth single-origin coffee, high life kale chips portland fap. Trust fund elit placeat velit, iphone ea ut sriracha scenester cosby sweater esse deserunt delectus sunt cray.
Fixie est cillum, you probably haven't heard of them dolore synth ugh jean shorts labore typewriter DIY nesciunt photo booth polaroid ex. Beard irony intelligentsia bicycle rights farm-to-table chillwave. Truffaut forage aliqua neutra leggings. Terry richardson deserunt fashion axe jean shorts 3 wolf moon. Synth pinterest fugiat, fashion axe master cleanse meh pour-over quinoa kale chips selvage. Etsy 90's stumptown consequat mumblecore thundercats, gentrify typewriter. Seitan sartorial ad helvetica proident.
Selvage polaroid 90's, carles authentic bicycle rights nesciunt +1 ea hella consectetur tempor YOLO butcher. Velit raw denim small batch, bicycle rights salvia selvage officia. Artisan vice DIY gluten-free whatever, iphone aliqua. Hoodie ad culpa aute pop-up lomo, organic intelligentsia bespoke biodiesel qui kale chips food truck enim artisan. Williamsburg aliquip salvia, labore disrupt authentic plaid mcsweeney's in et portland ethnic. Aute blog tattooed 90's. Odio irony occupy, veniam cosby sweater kale chips banjo viral freegan thundercats jean shorts non.
Vinyl nulla put a bird on it synth consequat velit, raw denim narwhal. Cray jean shorts ad duis veniam, labore carles mlkshk. Officia odd future umami bushwick, locavore viral 90's eiusmod wayfarers pariatur culpa fingerstache mollit. Farm-to-table placeat artisan, synth 3 wolf moon ugh in small batch fashion axe et pork belly lo-fi locavore vero. Literally lo-fi reprehenderit deep v, artisan hella food truck master cleanse banh mi post-ironic nisi irure. Street art nihil pinterest portland velit qui sapiente, trust fund stumptown organic umami cardigan keytar leggings. Marfa ethnic qui ethical mumblecore.


/**
* Global GAME.
* Reference it via the `GAME` variable.
* @namespace GAME
* @property {GAME#infoObject} [info] - Infos about this game.
*/
const Game = (function() {
//The interval for the tick.
let interval = null;
//Boolean wether or not the game is running.
//Generally the game is on-going. Not indicating wether or not game is paused.
let running = false;
//The function to be called once the game is over.
let gameOverCallback = null;
/**
* @typedef {object} GAME#infoObject
* @property {string} name - Name of this game.
* @property {string} description - Desciption for this game.
* @property {string} imgUrl - URL to a preview image for this game.
* @property {string} manual - Information on how to play this game.
*/
const infoObject = {
name: 'Game',
description: 'basic game template',
shortDescription: 'One sentenceonly',
imgUrl: '',
manual: 'Press buttons to play!',
file: 'standard.js'
}
/**
* Start the game.
* @method GAME#start
*/
function startGame() {
resume();
running = true;
}
/**
* The tick of the game that gets called rappidly.
* @function
* @private
*/
function tick() {
if (!running) {
return false;
}
}
/**
* Pause the game.
* @method GAME#pause
*/
function pause() {
clearInterval(interval);
}
/**
* Resume the game.
* @method GAME#resume
*/
function resume() {
if (!running) {
return;
}
interval = setInterval(tick, 50);
}
/**
* Called when the game is over, the player looses.
* @function
* @private
*/
function gameOver() {
pause();
running = false;
if (gameOverCallback !== null) {
let text = '';
gameOverCallback(text);
}
}
/**
* Set the callback for gameOver.
* @method GAME#setGameOverCallback
*/
function setGameOverCallback(func) {
gameOverCallback = func;
}
/**
* Return an object with all functions that should be publically accessable.
*/
return {
start: startGame,
pause: pause,
resume: resume,
setGameOverCallback: setGameOverCallback,
info: infoObject
};
}());


{% extends "main-no-disqus.html" %} {% block htmltitle %}
We're happy that you're here – not here at this page exactly, but here at Losant's documentation. So let's get you pointed in the right direction.
You can search the documentation to find something specific, or you can read an overview of the Losant Enterprise IoT Platform. Perhaps you want to read about some Losant tutorials and projects, or you want to run through the Losant Walkthrough.
Of course, you can always go start working with the Losant platform directly! Click the links below to start building for free today.


css3 quote
Emily Dickinson
1830-1886
"The fog is rising..."
Oscar Wilde
1854-1900
"And now, I am dying beyond my means."
Thomas Edison
1847-1931
"It is very beautiful over there."


DEEP BLUE SEA (M). (Warner Bros/Village Roadshow) Director: Renny Harlin Stars: Thomas Jane, Saffron Burrows, Samuel L Jackson, L L Cool J, Michael Rapaport, Jacqueline McKenzie, Stellan Skarsgard, Aida Turturro, Ronny Cox (uncredited) Running time: 105 minutes.
Jaws with attitude! There hasn't been a decent shark adventure since the original Jaws (1975), although there have been plenty of imitations and cheap rip-offs. Just when we thought it was safe to venture back into the water, along comes Deep Blue Sea, an undeniably trashy but entertaining big budget B-grade thriller from director Renny Harlin (Die Hard 2, The Long Kiss Goodnight, etc). Deep Blue Sea hits our screens in the wake of other disappointing water-bound stinkers, like Kevin Costner's awful Waterworld and the dire Sphere, but this one works a treat. If nothing else, this enjoyable film will turn a number of people away from the beach this summer.
Scientists at Aquatica, an ocean-based research station that resembles something left over from the disastrous Waterworld, have been tampering with Mako sharks in order to find a cure for degenerative brain diseases, such as Alzheimer's. As a result their genetic tampering has turned a natural killing machine into a highly intelligent, dangerous predator with a thirst for blood. When a savage tropical storm hits Aquatica and wrecks the place, the labs are waterlogged and the sharks get free. They begin hunting the scientists as they desperately try to make their way to the surface.
The international cast includes Thomas Jane (who, from a distance, bears a vague resemblance to Kevin Costner), Aussie actress Jacqueline McKenzie (Angel Baby), Michael Rapaport, Saffron Burrows (currently in Wing Commander, etc), rapper L L Cool J (who adds some humour to the film), and the very busy Samuel L Jackson. Half the fun lies in working out which of these stars will become shark food and who will survive.
The film was shot in the same huge tanks created for Titanic, and delivers plenty of underwater action. Special effects technology and computer generated imaging have advanced since Spielberg's day, allowing Harlin and his special effects crew to create thoroughly menacing sharks that move through the water with awesome fluidity. Harlin is a deft hand at spectacular action sequences, and this fast paced film certainly delivers plenty of thrills.
Deep Blue Sea deftly combines elements of Jaws, Jurassic Park and The Poseidon Adventure, as well as many of the clichés of the popular disaster movie. It is also reminiscent of the series of films from the mid-'70's in which nature sought revenge on man for meddling with the environment. Many of those films took themselves far too seriously, and consequently they were pretty silly. However, the makers of Deep Blue Sea seem aware of its inherent silliness, and the film is all the better for it. The film is cliché- ridden, with lots of unintentionally corny and banal dialogue, but this all somehow adds to the enjoyment of the whole thing. ***1/2 greg king http://www.netau.com.au/gregking
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


{% extends "base_generic_stage.html" %} {% block content %} Oops, no say found here Have your say! {% endblock %} {% block footerstring %} Made with 😺 at 🏡 by hsen. {% endblock %}


Software engineers spend a considerable amount of time on program comprehension. Although vendors of Integrated Development Environments (IDEs) and analysis tools address this challenge, current support for reusing and sharing program com- prehension knowledge is limited. As a consequence, developers have to go through the time-consuming program understanding phase multiple times, instead of recalling knowledge from their past or other's program comprehension activities. In this paper, we present an approach to making the knowledge gained during the program comprehension process accessible, by combining micro-blog messages with interaction data automatically collected from the IDE. We implemented the approach in an Eclipse plugin called James and performed a first evaluation of the underlying approach effectiveness, assessing the nature and usefulness of the collected messages, as well as the added benefit of combining them with interaction data.


{% extends 'main/base.html' %} {% load static %} {% block scripts %} {% endblock %} {% block title %}Education{% endblock %} {% block video %} {% endblock%} {% block videoname %}
We strongly believe in the art of investing and wish to help anyone get started. Time horizon is one of the most important factors that can multiply your money exponentially. Getting started early is extremely important and can be one of the best steps anyone can take to secure their financial future. Here is an infographic that illustrates just how powerful time can be.
By starting early, you automatically have an advantage. At Daedalus
Investments, we don’t believe that investing is an exclusive art. Retail
trading has increased to as much as 20% of all trading on the U.S. equity
market and it is easier than ever to start investing. This course presents
all the information needed for anyone to figure out what type of investor
they are, plus the tools needed to get familiarized with each investing
style. This course is meant to provide a stepping stone into potentially
more education for those who wish and hopefully will kickstart anyone’s
journey with investing!
Investing 101 is suitable for anyone who has a keen interest in learning more about trading the financial markets. Whether you are a complete beginner or a seasoned trader, our courses and trading education materials offer an experience we hope will be beneficial for anyone willing to partake. Our videos are straightforward and give you the opportunity to learn to trade through methodical processes and will serve as the perfect introduction to being able to navigate the complex world of equities. Disclaimer: All costs go towards maintaining the domain and does not serve as direct profit for Daedalus Investments.


- ImageConverter - Class in com.team7.cmput301.android.theirisproject
-
Use this class to encode/decode bitmaps for our app
- ImageConverter() - Constructor for class com.team7.cmput301.android.theirisproject.ImageConverter
-
- imageItem - Variable in class com.team7.cmput301.android.theirisproject.ImageListAdapter.ImageViewHolder
-
- ImageListAdapter<M extends Photo> - Class in com.team7.cmput301.android.theirisproject
-
ImageListAdapter is used to display a gallery of bitmap images on the
activity given its recycler view
- ImageListAdapter(Activity, List<M>, boolean) - Constructor for class com.team7.cmput301.android.theirisproject.ImageListAdapter
-
- ImageListAdapter(Activity, List<M>, boolean, ImageListAdapter.ImageListListener) - Constructor for class com.team7.cmput301.android.theirisproject.ImageListAdapter
-
- ImageListAdapter(Activity, List<M>, int) - Constructor for class com.team7.cmput301.android.theirisproject.ImageListAdapter
-
- ImageListAdapter.ImageListListener - Interface in com.team7.cmput301.android.theirisproject
-
- ImageListAdapter.ImageViewHolder - Class in com.team7.cmput301.android.theirisproject
-
Our View for each item should be able to remove the item by having a
remove button
- ImageSlideAdapter<M extends Photo> - Class in com.team7.cmput301.android.theirisproject
-
Reference: https://www.youtube.com/watch?v=Q2FPDI99-as
- ImageSlideAdapter(Context, List<M>) - Constructor for class com.team7.cmput301.android.theirisproject.ImageSlideAdapter
-
- ImageViewHolder(View) - Constructor for class com.team7.cmput301.android.theirisproject.ImageListAdapter.ImageViewHolder
-
- INDEX - Static variable in class com.team7.cmput301.android.theirisproject.IrisProjectApplication
-
- initBulkUpdater() - Static method in class com.team7.cmput301.android.theirisproject.IrisProjectApplication
-
Prepare for updating in response to internet connection loss.
- instantiateItem(ViewGroup, int) - Method in class com.team7.cmput301.android.theirisproject.ImageSlideAdapter
-
instantiateItem() creates image views from a list of
all record photos associated with the problem
- IrisActivity<M> - Class in com.team7.cmput301.android.theirisproject.activity
-
A type of Activity that uses a IrisController to interact with and update with a Model object,
- IrisActivity() - Constructor for class com.team7.cmput301.android.theirisproject.activity.IrisActivity
-
- IrisController<M> - Class in com.team7.cmput301.android.theirisproject.controller
-
A type of controller that is used by an IrisActivity to manage a Model object.
- IrisController(Intent) - Constructor for class com.team7.cmput301.android.theirisproject.controller.IrisController
-
- IrisProjectApplication - Class in com.team7.cmput301.android.theirisproject
-
IrisProjectApplication is the main class to start our app.
- IrisProjectApplication() - Constructor for class com.team7.cmput301.android.theirisproject.IrisProjectApplication
-
- isAdapterForm() - Method in class com.team7.cmput301.android.theirisproject.ImageListAdapter
-
- isChecked() - Method in class com.team7.cmput301.android.theirisproject.PatientListRecyclerAdapter.ViewHolder
-
- isConnectedToInternet() - Static method in class com.team7.cmput301.android.theirisproject.IrisProjectApplication
-
Determines if currently connected to internet.
- isUser(String) - Method in class com.team7.cmput301.android.theirisproject.model.User
-
- isViewFromObject(View, Object) - Method in class com.team7.cmput301.android.theirisproject.ImageSlideAdapter
-
isViewFromObject() checks if image created is an object
- iterator() - Method in class com.team7.cmput301.android.theirisproject.model.ProblemList
-
- iterator() - Method in class com.team7.cmput301.android.theirisproject.model.RecordList
-


| Package | Description |
|---|---|
| mars | |
| mars.venus | |
| mars.venus.editors.generic | |
| mars.venus.editors.jeditsyntax |
| Class | Description |
|---|---|
| GUI |
Top level container for Venus GUI.
|
| Class | Description |
|---|---|
| ChangeableAction |
parent class for Action subclasses to be defined for every menu/toolbar
option which its state is changeable
|
| Coprocessor0Window |
Sets up a window to display registers in the UI.
|
| Coprocessor1Window |
Sets up a window to display Coprocessor 1 registers in the Registers pane of the UI.
|
| DataSegmentWindow |
Represents the Data Segment window, which is a type of JInternalFrame.
|
| Editor |
Manage the file being edited.
|
| EditPane |
Represents one file opened for editing.
|
| EditRedoAction |
Action for the Edit - Redo menu item
|
| EditTabbedPane |
Tabbed pane for the editor.
|
| EditUndoAction |
Action for the Edit -> Undo menu item
|
| ExecutePane |
Container for the execution-related windows.
|
| GUI |
Top level container for Venus GUI.
|
| GuiAction |
parent class for Action subclasses to be defined for every menu/toolbar
option.
|
| HardcopyWriter.PrintCanceledException |
This is the exception class that the HardcopyWriter constructor
throws when the user clicks "Cancel" in the print dialog box.
|
| LabelsWindow |
Represents the Labels window, which is a type of JInternalFrame.
|
| MainPane |
Creates the tabbed areas in the UI and also created the internal windows that
exist in them.
|
| MessagesPane |
Creates the message window at the bottom of the UI.
|
| NewObservable | |
| NumberDisplayBaseChooser |
Use to select base for displaying numbers.
|
| RegistersPane |
Contains tabbed areas in the UI to display register contents
|
| RegistersWindow |
Sets up a window to display registers in the UI.
|
| RunAction |
parent class for Action subclasses to be defined for every menu/toolbar
run option which its state is changeable
|
| RunSpeedPanel |
Class for the Run speed slider control.
|
| SettingsMemoryConfigurationAction |
Action class for the Settings menu item for text editor settings.
|
| TextSegmentWindow |
Creates the Text Segment window in the Execute tab of the UI
|
| Class | Description |
|---|---|
| EditPane |
Represents one file opened for editing.
|
| Class | Description |
|---|---|
| EditPane |
Represents one file opened for editing.
|


Toggle navigation
MozTW Co-Working Space
Sign in
感謝您的支持！
Thanks for your supporting!
您的贊助紀錄將會於系統確認後列入統計
Back to main page


Ecology is messy. When we work in nature, we are dealing with inherently complex systems. All elements in a natural system are connected, full of dynamic interactions. Interactions among organisms, between organisms and their environment to meet basic needs – these linkages are what makes ecology messy, but also endlessly fascinating.
We can think of humans as just another element in these complex systems. And wildlife conservation and mangement is the task of manipulating or tweaking these linkages to meet societal objectives for natural systems.
This is not a systems ecology class!
BUT, systems ecology provides a great framework for thinking about natural populations, understanding how linkages (abiotic and biotic environments) might affect them, and how to manage natural populations most effectively.
This is one of the most powerful ideas in whole-systems thinking – when you put many interacting, linked parts together, systems often behave in interesting and unexpected ways!
Take a classic predator-prey system…
Insightmaker Lynx-Hare example
This is a classic example in population ecology, which we will revisit in great detail in this course - but for now it serves as an example of an interacting system that exhibits an emergent property – regular oscillations!
And here’s a more abstract example that illustrates some really cool and complex emergent properties.
InsightMaker is a flexible web-based software for defining interacting systems and for modeling the behavior of inter-connected systems.
Both of the above examples were constructed in InsightMaker.
We will make extensive use of InsightMaker, both during class and in lab- this will give you a chance to play around with complex and dynamic systems without needing a background in computer programming!
Modern computers have reduced or eliminated many of the barriers to understanding how complex systems behave, and as a result specialized software and computer programming are a critical component to modern whole-systems analysis, including ecosystems analyses. Armed with basic facility with computer programming, ecologists and natural resource professionals can formalize their understanding of the natural systems in which they work, accounting for complex biological realities that may have been ignored if these tools were not available. In this course, we will learn to harness the power of computer simulations for understanding and managing natural populations.
By the end of this course, students will have the ability to program their own whole-systems models in InsightMaker, and use specialized software for parameterizing these models (e.g., Program MARK, various R packages)
The course motto: Get messy! This might sound funny for a computer-based class. But just as ecological systems are complex and messy, models sometimes get messy. Don’t be afraid to model messy systems. And above all, don’t be afraid to be wrong (especially at first)- that attitude is the enemy of successful computer programming, and of good wildlife management! When we build our own algorithms, we can be entering uncharted territory. And this can be difficult and dangerous, but ultimately rewarding! Keep trying, and stay positive!
Of course, getting messy means not just reading and listening to lectures, it means learning by doing! Instructor-led lectures will be kept short, and we will spend significant class time (and pretty much all of lab time) on our computers, working through problems.
A [Stock] of stuff increases over time via what [Flows] in. Imagine our stock represents Moose! Moose Births would then be the input [Flow] to the population of Moose over time.
A [Stock] of stuff decreases over time via what [Flows] out. For example, Moose Deaths could represent the [Flow] out of the population of Moose.
If the [Flow] in is larger than the [Flow] out then the [Stock] increases over time.
If the [Flow] out is larger than the [Flow] in then the [Stock] decreases over time.
If the [Flow] in equals the [Flow] out then the amount in the [Stock] will not change over time.
The important takeaway is that a [Stock] represents a quantity of something. The [Stock] only changes over time via [Flows In] or [Flows Out]. A [Stock] doesn’t change instantaneously, with hand waving, magic, or smoke and mirrors.
Open up InsightMaker. If you have never used it before you need to sign up first with a username and password. InsightMaker is free!
Create a new Insight (the button to do this should be obvious!) and clear the demo model.
Right click in the center of the screen and select Create Stock from the popup. Notice that the name is New Stock and is selected. Type in a name for what this is an accumulation of. Note the Configuration Panel on the right is now for a [Stock]. In the configuration panel, set the Initial Value to 50. That is, there will be 50 moose at the start of the simulation!
Select [Flow] in the upper left corner of your screen under [Connections]. Now notice that when you mouse over the [Stock] a small right-arrow displays. Click on the right-arrow and drag a couple inches to the left of the [Stock] and release. This is how you create a [Flow] out of a [Stock]. To create a [Flow] into a [Stock] click the Reverse button in the Connections menu. Please do that now. You can name the [Flow] as you wish. Also in the Configuration Panel set Flow Rate = 1.
Now click Run Simulation and you have just finished your first simulation model.
Can you figure out how to change the settings to run the model for 50 years? Try this and click Run Simulation.
Use the same methods as step 4 to create a [Flow Out], representing moose deaths. Re-run the model. Is the population increasing or declining? Why?
Change the Configuration Panel for the [Stock] and for the [Flow In] and [Flow Out] so that “Show Value Slider” is set to “Yes”. You can change the model parameterization easily using these sliders. Try it a couple times, re-running the simulation after each change.
Q: Is this Moose model realistic? What is the first thing you would like to change to make the model more realistic?
Finally, just for fun, here is a cool video of the Lorenz Attractor, which we saw earlier!


@* * This template is called from the `index` template. This template * handles the rendering of the page header and body tags. It takes * two arguments, a `String` for the title of the page and an `Html` * object to insert into the body of the page. *@ @(title: String, scripts: Html = Html(""), includes: Html = Html(""))(body: Html)
@* Here's where we render the page title `String`. *@


|
beginner 1 hour |
Demo | |
|
beginner 2 hours |
Basic Operations - Arithmetic | |
|
intermediate 2 hours |
String Manipulation and Values - Roman Numeral Conversion | |
|
intermediate 2 hours |
Parsing JSON and objects - Student Database | |
|
advanced 2 hours |
Time and Dates | |
|
advanced 2 hours |
Encryption | |
|
advanced 2 hours |
Solve the Maze AI |


{# TODO [DWPF-454] Delete this template #} {% load feedback_tags %}
beta We are continuously improving this service - your feedback will help us improve it.


STATION 5 of 5
Integrating biophilic elements in buildings have positive physiological and physical well-being effects to user in the building. However, there determine the biophilic profile of a building/space have been a challenge, unless design and building process have been carried out. The development of the biophilic analytical tool allow user to assess the biophilic profile in a semi-quantitative manner, providing designers/building owner a mean to determine the biophilic profile of space before construction, saving cost and time.


System Architect Diagram ".Types of Agent"
Sorry, this document will only work on browsers capable of displaying frames (e.g. Netscape Navigator and Internet Explorer).


SM@RT is a great software engineering team of the Reliability of Systems and Software department that specializes in software agility and safety for cyber-physical systems. The team explores new foundations, and develops ground-breaking tools and methods for modeling and software languages (domain-specific languages, specification languages, programming and modeling languages), with a particular focus on the scientific breakthroughs related to socio-technical coordination (heterogeneity of models and execution platforms, final user in the loop, etc.). SM@RT is a leading team in model-driven engineering (MDE) and software language engineering (SLE). The team is highly involved in the international scientific community, and has established strong industrial partnerships (through bilateral and collaborative projects). SM@RT seconds most of the scientific contributions with software developments. The team is also highly involved in various open-source communities (e.g., Eclipse), and contributes to different projects.
You can also access the official list from the lab (up to date, but only related to it).
(and workshops)
(and Habilitations)
Despite the success of Model-Based Systems Engineering adoption, its application at scale and in a continuous approach to ensure the delivery of added value for its adopters is far from straightforward. The inherent complexity in terms of implied domains or of massively heterogeneous and poorly related data is not weaved by the simple use of a formal and disciplined modeling approach. A collaborative and continuous framework and process are required and need to aggregate up-to-date technologies in complementary techniques such as models, ontologies, and complex data management. It is the purpose of this Chair to study and make effective such complementarity.
Collaboration initiated with the Innopolis University on the use of formal methods in Requirements Engineering
Placing the Final User Needs (FUN) at the center of the (modeling) concerns
An integrated model-based early validation approach for Railway Systems
GEMOC is an open and international initiative that aims to coordinate and disseminate the research results regarding the support of the coordinated use of various modeling languages that will lead to the concept of the globalization of modeling languages.
MOdels and Information Sharing for System Engineering in Extended Entreprise


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/autoparam.20in.20instance.html ---
Is it possible to use autoparam in instances? I have a is_add_group_hom
instance that never triggers, probably because is it contains a continuity assumption. The following doesn't seem to help:
instance sep_quot.is_add_group_hom_lift [separated β] (hf : continuous f . tactic.assumption) : is_add_group_hom (sep_quot.lift f) := ...
Isn't this evidence that continuous
should be a class?
Of course this also came to my mind
Here it would clearly help
/me doesn't know why group homs should be a class and continuous maps not...
Is it possible to use autoparam in instances?
No, auto_params are handled by the elaborator. Type class instance synthesis does not know about auto_param (or optional parameters).
Thanks Gabriel
neither should be a class
not group homs. not continuous maps. not linear maps.
So... what should be a class?
groups and topological spaces and modules?
Why???
how is it done in your category theory?
Continuous maps not a class -- Johannes has explained this before on this forum, although I have never really internalised the issue.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Police hunting woman filmed crushing sobbing toddler with her backside
WARNING - UPSETTING CONTENT: Corpus Christi Police launched an investigation after receiving video of a suspected child abuse within the local community - but have now confirmed the incident took place in Mexico
by Tiffany LoA police hunt has been launched to try find a woman who was filmed using her backside to crush and suffocate an inconsolable toddler.
The clip, which has been circulating on social media, shows the woman sitting on a little girl's head to stop her crying.
The child becomes more upset but the woman seems unconcerned as she wraps her legs around the youngster and sits forcefully on her back.
Later, she turns the girl over and locks her movement with her legs.
The video has been widely shared within the community of Corpus Christi, Texas, USA.
Facebook has chosen to leave the disturbing clip online in the hope it helps police track the woman down.
Corpus Christi Police Department shared the clip and stressed that the woman has an easily-identifiable tattoo on her left ankle.
Following an investigation, they posted an update on Monday and found out the incident did not occur in Corpus Christi but in Nuevo Leon, Mexico.
It read: "This video was posted on a local Facebook group and ultimately found its way to us.
"Since then we have actively attempted to identify the suspect, child, and location of the incident so that this incident can be addressed.
"At this time all indications are that the incident did not occur in our jurisdiction and that it occurred in Nuevo Leon, Mexico.
"We have also received information that this incident may have happened over a year ago."
Officers are working to identify the exact location where the assault happened and they have contacted the Child Protection Services equivalent in Mexico to launch an investigation.
They shared photos of suspected women with tattoos on their ankles to help the search.
One said: "I can’t find the post but, on one of the links to this video it was shared from an older woman from Nuevo Leon and she is now living in Corpus!
"Just wondering if anyone seen the link and if she could be related to the family?"
Corpus Christi Police replied in the comment: "The female that shared the video was not the originator of the video and we did contact her that night and ruled her out."


LineVis —
See your files, line-by-line.
Code released under the
Apache v2 License.
Instructions
Use the drag-n-drop box below to generate visualizations of the lines of text in your files.
Drop files here
Your browser doesn't seem to support canvas.


Executing Triana Workflows
A Section
a section with a link
myExperiment
A sub section
Some more content.


The objective of the game is simple. The first player who scores 50 points wins a round. The game ends when a player wins 3 rounds.
Each green sweet gives you one point while each red sweet gives your OPPONENT 5 points (wait whuttt...)
Eating a red sweet makes your opponent longer AND slower (so you can go ahead and eat more green sweets to score points)
Use the W, A, S, D or the directional arrow keys to move the snakes
Avoid hitting yourself or your opponent!


Home
×
Login to Your Account
Register
×
Register
Email:
UserName:
Password:
1-8 Characters
Re-Enter Password:
Sign Up
×
Feedback
Name
Email
Mobile
Ticket No
Feedback
From
Enter City
Enter City
Search Buses
{{ccity.city}}
{{ccity.city}}
×
Bus Details
Name
seats
departure
arrival
Price
Book
{{items.travelName}}
{{items.seats}}
{{items.departure}}
{{items.arrival}}
{{items.price|currency}}
Book
{{errmsg}}


|
Crap Engine 2
|
A red-black tree indexed based implementation. More...
#include <tree.h>
Public Member Functions | |
| CRAP_INLINE | tree (void *memory, uint32_t size) |
| Constructor. More... | |
| CRAP_INLINE | ~tree (void) |
| destructor More... | |
| CRAP_INLINE tree & | operator= (const tree &other) |
| assignment operator More... | |
| CRAP_INLINE uint32_t | find (const T &key) const |
| Finds key and returns index. More... | |
| CRAP_INLINE uint32_t | insert (const T &key) |
| Inserting key if unique and returns index. More... | |
| CRAP_INLINE void | erase_at (uint32_t index) |
| Removes key at given index. More... | |
| CRAP_INLINE void | erase (const T &key) |
| Find key and remove element. More... | |
| CRAP_INLINE uint32_t | begin (void) const |
| Finds the smalles element and returns index. More... | |
| CRAP_INLINE uint32_t | last (void) const |
| Finds the biggest element and returns index. More... | |
| CRAP_INLINE uint32_t | end (void) const |
| Returns invalid element. More... | |
| CRAP_INLINE uint32_t | next (uint32_t index) const |
| get following index More... | |
| CRAP_INLINE uint32_t | previous (uint32_t index) const |
| get previous index More... | |
| CRAP_INLINE T * | get (uint32_t index) |
| returns pointer of given index More... | |
| CRAP_INLINE const T * | get (uint32_t index) const |
| returns pointer of given index More... | |
| CRAP_INLINE T & | operator[] (uint32_t index) |
| index operator More... | |
| CRAP_INLINE const T & | operator[] (uint32_t index) const |
| index operator More... | |
| CRAP_INLINE int32_t | weight (void) const |
| Current weight of the tree. More... | |
| CRAP_INLINE uint32_t | size (void) const |
| Tree number of stored nodes. More... | |
| CRAP_INLINE uint32_t | max_size (void) const |
| Tree number of max stored nodes. More... | |
| CRAP_INLINE pointer_t< void > | memory (void) const |
| returns pointer to memory More... | |
Static Public Member Functions | |
| static CRAP_INLINE uint32_t | size_of_elements (uint32_t number) |
| returns necessary memory for given number of elements More... | |
Static Public Attributes | |
| static const uint32_t | INVALID = UINT32_MAX |
| an invalid key More... | |
A red-black tree indexed based implementation.
The data is kept packed, the tree is connected by using indices.
|
explicit |
| crap::tree< T >::~tree | ( | void | ) |
| uint32_t crap::tree< T >::begin | ( | void | ) | const |
| uint32_t crap::tree< T >::end | ( | void | ) | const |
| void crap::tree< T >::erase | ( | const T & | key | ) |
| void crap::tree< T >::erase_at | ( | uint32_t | index | ) |
| uint32_t crap::tree< T >::find | ( | const T & | key | ) | const |
| T * crap::tree< T >::get | ( | uint32_t | index | ) |
| const T * crap::tree< T >::get | ( | uint32_t | index | ) | const |
| uint32_t crap::tree< T >::insert | ( | const T & | key | ) |
| uint32_t crap::tree< T >::last | ( | void | ) | const |
| uint32_t crap::tree< T >::max_size | ( | void | ) | const |
| pointer_t< void > crap::tree< T >::memory | ( | void | ) | const |
| uint32_t crap::tree< T >::next | ( | uint32_t | index | ) | const |
| tree< T > & crap::tree< T >::operator= | ( | const tree< T > & | other | ) |
| T & crap::tree< T >::operator[] | ( | uint32_t | index | ) |
| const T & crap::tree< T >::operator[] | ( | uint32_t | index | ) | const |
| uint32_t crap::tree< T >::previous | ( | uint32_t | index | ) | const |
| uint32_t crap::tree< T >::size | ( | void | ) | const |
|
static |
| int32_t crap::tree< T >::weight | ( | void | ) | const |
|
static |


You must define latitude, longitude and the content of the map overlay.
Also, you must define a height to the content.
Also, you can define a verticalAlign
, which can be top
, middle
or bottom
, and horizontalAlign
, which can be left
, center
or right
.


C-Suite and managers in financial services are confronted with growing challenges. To streamline operations and deliver the services technically proficient customers expect, decision makers need to keep an eye on the latest IT trends.
Do you know what is currently up in the ERP market? Or how the 2017 IT trends change enterprise resource planning? We rounded it up and made it easier for you to keep up-to-date.
ERP systems collect and organize a great deal of information about business processes and customer behavior. But collecting and organizing information is no longer enough: companies are expected to combine different data sources and improve reporting and analysis activities.
Big data is becoming complementary to ERP systems as it helps to refine the inputs to software. The better the inputs, the more efficient enterprise resource planning installations run.
An intelligent ERP uses new technologies such as artificial intelligence, predictive analytics, and cloud deployment. Intelligent ERPs are the next step in the evolution of the ever-changing IT landscape and will have a great impact on how companies plan, use and expand their resources.
As sales managers and consultants began performing their activities away from the office, using tablets and smartphones, ERPs needed to evolve. Business software now ensures company and customer data are accessible from anywhere.
In the case of Charisma, mobile-ready technology updates company data in real time and allows access to the database via web services. Push notifications make sure users remain on top of their game and are aware of the latest changes.
More and more companies choose to use cloud-based punctual solutions for ERP and CRM systems. Bringing these systems to the cloud eliminates the need for hardware acquisition and maintenance, cuts deployment costs and allows companies scale their IT in fast and reliable ways.
Your employees are already using social media tools to get things done. The next step in ERP development will capitalize on those existing connections. Integrating social media into ERP will open up ways for employees to interact and be more productive.
We expect social media integration will become more and more relevant, allowing organizations to add new elements to ERP applications, such as visitor profiles and conversation feedback.


Everywhere
Quick Acce
D Demo
My Preferences
Logout
View My Shop
Catalog
Products
Categories
Monitoring
Attributes and Values
Orders
Orders
Invoices
Merchandise Returns
Customers
Customers
Addresses
Price Rules
Cart Rules
Catalog Price Rules
Shipping
Shipping
Carriers
Localization
Localization
Languages
Zones
Modules
Modules
Modules & Themes Catalog
Preferences
General
Orders
Advanced Parameters
Configuration Information
Performance
Administration
Preferences
Quick Access
Status
Stats
Catalog
Products
Add New
Filter by category
ID
Photo
Name
Reference
Category
Base Price
Final Price
Quantity
Displayed
Action
-
-
-
1
iPod Nano
iPods
124,58 €
124,58 €
160


RT @aphyr: Equality relations are symmetric, transitive, and reflexive. Delight your users by quietly violating one or more of these invari…
8/1/2013, 1:45:41 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
RT @aphyr: Equality relations are symmetric, transitive, and reflexive. Delight your users by quietly violating one or more of these invari…
8/1/2013, 1:45:41 PM
Favs: 0
Retweets: 0
link


Realm Roller Project
Weather Dashboard Project
Day Planner Project
Playlist Creator Project
DND Character Creator


Mazda RX-Vision GT3 Concept Looks Slick In Official Teaser Sketch
Surely one of the most beautiful race cars to never exist.
by Adrian PadeanuThe Batmobile-ready Lamborghini V12 Vision Gran Turismo wasn’t the only car to be revealed last weekend for Gran Turismo Sport as Mazda also showed the new RX-Vision GT3 concept. The virtual race car was briefly featured in sketch form during the World Final of the FIA World Tour in Gran Turismo Sport event held in Monaco. We’ll have to wait until next year to see it in full as the video game’s developer Polyphony Digital is currently working to model the swoopy race car.
If this gorgeous race car looks familiar, there’s a good reason for that. It’s heavily based on the stunning RX-Vision concept unveiled a little over four years ago at the Tokyo Motor Show. The showcar combined sleek styling with an all-new SkyActiv-R engine, although technical specifications were never released. The rotary engine is indeed making a return, but as you probably know by now, it’s only returning as a range-extending engine per the official word from Mazda. It’s also not known at this point whether the race car designed for Gran Turismo Sport will feature the rotary engine of the 2015 concept.
Gallery: Mazda RX-Vision concept
Getting back to the RX-Vision GT3 at hand, surely the final car for Gran Turismo won’t look as dramatic as this taking into consideration the roof seems unrealistically low and the wheels are rather huge. The aero work with the massive splitter up front and the giant rear wing at the back will likely be toned down a bit, and that should also include the huge vertical planes of the diffuser and the beefy side skirts.
Little else has been revealed about the RX-Vision GT3, although we do know it will have a 48:52 weight distribution with a front mid-mounted engine. The styling is penned Ikuo Maeda, Mazda’s head of global design, who was also responsible for the RX-Vision and the RX-8. Fun fact – his father, Matasaburo Maeda, designed the original RX-7 back in the day.
See Other Spectacular Vision Gran Turismo concepts:
Mazda is signing a partnership with Polyphony Digital to become a partner of Gran Turismo Sport from 2020, after similar deals announced in February by Toyota and in August by Porsche. More Mazdas are to come following the RX-Vision GT3’s debut in the FIA GT Championships next year, and we’d definitely want the wild Mazda3 TCR on that list.


Recipe 6.5. Delegating Automatically as an Alternative to InheritanceCredit: Alex Martelli, Raymond Hettinger ProblemYou'd like to inherit from a class or type, but you need some tweak that inheritance does not provide. For example, you want to selectively hide some of the base class' methods, which inheritance doesn't allow. SolutionInheritance is quite handy, but it's not all-powerful. For example, it doesn't let you hide methods or other attributes supplied by a base class. Containment with automatic delegation is often a good alternative. Say, for example, you need to wrap some objects to make them read-only; thus preventing accidental alterations. Therefore, besides stopping attribute-setting, you also need to hide mutating methods.   In this recipe, we show how to use it to get an effect that is almost indistinguishable from subclassing while hiding some names. In particular, we apply this quasi-subclassing to the task of wrapping objects to make them read-only. Performance isn't quite as good as it might be with real inheritance, but we get better flexibility and finer-grained control as compensation. The fundamental idea is that each instance of our class holds an instance of the type we are wrapping (i.e., extending and/or tweaking). Whenever client code tries to get an attribute from an instance of our class, unless the attribute is specifically defined there (e.g., the mutators dictionary in class Readonly), _ _getattr_ _ TRansparently shunts the request to the wrapped instance after appropriate checks. In Python, methods are also attributes, accessed in just the same way, so we don't need to do anything different to access methods. The _ _getattr_ _ approach used to access data attributes works for methods just as well. This is where the comment in the recipe about there being a specific reason to avoid subclassing object comes in. Our _ _getattr_ _ based approach does work on special methods too, but only for instances of old-style classes. In today's object model, Python operations access special methods on the class, not on the instance. Solutions to this issue are presented next in Recipe 6.6 and in Recipe 20.8. The approach adopted in this recipemaking class Readonly old style, so that the issue can be locally avoided and delegated to other recipesis definitely not recommended for production code. I use it here only to keep this recipe shorter and to avoid duplicating coverage that is already amply given elsewhere in this cookbook. _ _setattr_ _ plays a role similar to _ _getattr_ _, but it gets called when client code sets an instance attribute; in this case, since we want to make a read-only wrapper, we simply forbid the operation. Remember, to avoid triggering _ _setattr_ _ from inside the methods you code, you must never code normal self.n = v statements within the methods of classes that have _ _setattr_ _. The simplest workaround is to delegate the setting to class object, just like our class Readonly does twice in its _ _init_ _ method. Method _ _delattr_ _ completes the picture, dealing with any attempts to delete attributes from an instance. Wrapping by automatic delegation does not work well with client or framework code that, one way or another, does type-testing. In such cases, the client or framework code is breaking polymorphism and should be rewritten. Remember not to use type-tests in your own client code, as you probably do not need them anyway. See Recipe 6.13 for better alternatives. In old versions of Python, automatic delegation was even more prevalent, since you could not subclass built-in types. In modern Python, you can inherit from built-in types, so you'll use automatic delegation less often. However, delegation still has its placeit is just a bit farther from the spotlight. Delegation is more flexible than inheritance, and sometimes such flexibility is invaluable. In addition to the ability to delegate selectively (thus effectively "hiding" some of the attributes), an object can delegate to different subobjects over time, or to multiple subobjects at one time, and inheritance doesn't offer anything comparable. Here is an example of delegating to multiple specific subobjects. Say that you have classes that are chock full of "forwarding methods", such as: class Pricing(object): def _ _init_ _(self, location, event): self.location = location self.event = event def setlocation(self, location): self.location = location def getprice(self): return self.location.getprice( ) def getquantity(self): return self.location.getquantity( ) def getdiscount(self): return self.event.getdiscount( ) and many more such methods Inheritance is clearly not applicable because an instance of Pricing must delegate to specific location and event instances, which get passed at initialization time and may even be changed. Automatic delegation to the rescue: class AutoDelegator(object): delegates = ( ) do_not_delegate = ( ) def _ _getattr_ _(self, key): if key not in do_not_delegate: for d in self.delegates: try: return getattr(d, key) except AttributeError: pass raise AttributeError, key class Pricing(AutoDelegator): def _ _init_ _(self, location, event): self.delegates = [location, event] def setlocation(self, location): self.delegates[0] = location In this case, we do not delegate the setting and deletion of attributes, only the getting of attributes (and nonspecial methods). Of course, this approach is fully applicable only when the methods (and other attributes) of the various objects to which we want to delegate do not interfere with each other; for example, location must not have a getdiscount method; otherwise, it would preempt the delegation of that method, which is intended to go to event. If a class that does lots of delegation has a few such issues to solve, it can do so by explicitly defining the few corresponding methods, since _ _getattr_ _ enters the picture only for attributes and methods that cannot be found otherwise. The ability to hide some attributes and methods that are supplied by a delegate, but the delegator does not want to expose, is supported through attribute do_not_delegate, which any subclass may override. For example, if class Pricing wanted to hide a method setdiscount that is supplied by, say, event, only a tiny change would be required: class Pricing(AutoDelegator): do_not_delegate = ('set_discount',) while all the rest remains as in the previous snippet. See AlsoRecipe 6.13; Recipe 6.6; Recipe 20.8; Python in a Nutshell chapter on OOP; PEP 253 (http://www.python.org/peps/pep-0253.html) for more details about Python's current (new-style) object model. |


This window is designed to help you install and adjust your plunger sensor. It shows the current position reading and the calibration data. If you're using an imaging sensor (such as a TSL1410R), it shows a real-time view of the captured image.
For quadrature sensors (AEDR-8300), the "snapshot" box displays a visualization of the bar scale that the sensor moves across. Quadrature sensors don't take photographic images, so this is just a simulation of what we infer the bar scale to look like - it's not a true photo image. What the sensor actually sees is essentially two side-by-side pixel readings, 1/150 of an inch apart. Given that the white and black bars on the scale are precisely 1/150" wide each (or, at least, they should be, if things are set up properly), we can infer where we must be relative to the nearest two bars. The visualization extrapolates that out to the rest of the nearby bars, but the sensor doesn't actually see those; it only sees the two bars in the center, in the boxes marked "A" and "B". Those boxes represent the actual readings on the sensor's "A" and "B channels.
The VCNL4010 proximity sensor doesn't actually measure distance; it measures the brightness of an infrared light beam reflected from the target (the end of the plunger). The amount of reflected light increases as the target gets closer to the sensor, which allows us to infer the distance from the brightness. To help you see what's really going on at the physical level, the Plunger Viewer displays the brightness level measured on the sensor. The yellow bar shows the brightness reading - this is a number from 0 to 65535, in abstract units, with 0 meaning that the sensor isn't seeing any light at all and 65535 meaning that it's fully saturated (like an overexposed photo). The green bar superimposed over that shows the distance calculation. Remember that the sensor doesn't actually measure distance - it only measures brightness - so the distance calculation is just the result of doing some math on the brightness. This is based on the calibration data, so the distance reading isn't meaningful until you run the calibration procedure. If the green distance bar is missing or erratic, try calibrating. If the yellow brightness bar is missing, or it doesn't respond as you move the plunger, the software probably isn't connected to the sensor properly - make sure the GPIO pin assignments are correct in the Settings, and check the wiring between the KL25Z and the sensor.
For imaging sensors, the "snapshot" box displays the image pixels that your sensor is capturing. This is updated continuously, so that you can immediately see the effects of adjusting the sensor position or the light source.
The pixels are rendered in shades of gray, since the sensors we support are monochromatic. Black pixels correspond to full darkness (or full shadow) on the sensor, and white pixels are fully saturated (maximum brightness at the sensor). Our sensor types are one-dimensional, meaning that the pixel array is one pixel wide. The display stretches out each pixel vertically to make it easier to visualize, so the image might look like a bar code or a series of vertical stripes.
For optimal performance, adjust your sensor and light source as follows:
The statistics shown under the image give you some more information about the sensor scan.
The Min and Max Brightness levels are on a scale from 0 to 255. 0 is full darkness, 255 is fully saturated. If your light source is set up properly, the Max value should be at least 30 or 40 higher than the Min value. This indicates a good level of contrast between the lit areas and the shadows.
For the imaging sensors that take pictures of the plunger (TLS1410/12, TCD1103), you can use the Zoom control to get a closer view of the sensor pixels. This is especially helpful when adjusting the lens focus for sensors where that's a thing, such as the TCD1103.
Use the Zoom combo box to select a zoom factor.
When zoomed in, you can scroll the image snapshot by using the mouse to drag the snapshot area left or right.
If the controller is able to read the plunger position from the sensor, the position will be displayed as a green bar across the bottom of the snapshot box.
If you don't see a green bar, it means that the controller can't read the position. If you're using an imaging sensor, this might be because the image is too dark or too washed out.
The snapshot box draws little arrows to show the current calibration limits. The purple arrows show the park position, where the plunger sits when at rest. The red arrows show the maximum retraction position. If the plunger is calibrated properly, the plunger should settle and stay roughly at the park position when you're not moving it.
Real plungers always have at least a little mechanical play, so your plunger won't come to rest at exactly the same spot every time you fire it. It should be fairly consistent, though. If the park position shown isn't fairly close to the actual resting position, re-run the calibration procedure.
If you just installed the sensor, or you've adjusted its position, you should calibrate it. You can also recalibrate any time if the displayed park position doesn't look right.
To calibrate, make sure the plunger is at rest at its normal park position. Then click the Calibrate button, and follow the on-screen instructions.
Note that the pixel display is disabled during the calibration process. It will resume when the calibration finishes.
The scan time shows you how long it takes, on average, to take one position reading from the sensor. For an imaging sensor, this is the time it takes for the sensor to snap a photo (so to speak) and then transfer the image pixels to the microcontroller. The controller has to read the pixels one by one, so the pixel transfer is usually the bulk of the scan time for an image sensor. For an analog sensor (an LVDT or potentiometer, for example), the "scan time" is simply the time it takes to sample the analog voltage level on the sensor output and turn it into a digital reading.
The capture time for images from the TSL141R should be about 2.5ms with the current controller software. That's about 400 frames per second, which would be considered pretty fast in a regular photography or video context. A high frame rate is good for capturing fast motion, which is exactly the situation we have when you pull back and release the plunger.
For non-imaging sensors, the "scan time" is usually negligible (tens of microseconds), since we only have to wait for the analog voltage sampler to take a reading.
The "processing time" shows how long it took for the software to analyze the raw data for the current frame to determine the current plunger position. For an imaging sensor, this reflects the time it takes for the software to analyze the image pixels. For an analog sensor, this is usually zero (or close enough), since we treat the plunger position as linearly proportional to the voltage level. In other words, the "processing" is simply a multiplication, which takes less than a microsecond on the controller's CPU.
The timing statistics are provided mostly as a sanity check, to help determine if things are working as expected. There isn't anything you can do in the configuration to adjust these directly. If the times displayed aren't in the right ballpark, there might be a problem with the software or with your setup that bears looking into.
A couple of notes on the timing. First, the image update rate that you see in the setup window will be much slower than what you see in the statistics. The USB transfer to send the full image to the PC takes a lot longer than reading the image on the microcontroller. This overhead doesn't apply during normal operations - the controller normally analyzes the pixels all by itself and never sends them to the PC. So the statistics really do reflect what's going on in the controller, even though the viewer window can't display updates at the same speed. Second, for the TSL1410R sensor, the "processing time" and "scan time" happen concurrently, because the sensor is already snapping the next photo and transferring it to the controller while the controller is analyzing the previous one. This means that the true frame rate is basically determined by the longer of the sensor scan time and the processing time.
For a pixel-based sensor, click the "Enhance contrast" checkbox to exaggerate the contrast level in the displayed pixel readout. This makes the display show the bright pixels brighter than they really are, and the dark pixels darker than they really are.
This can be helpful when fine-tuning your sensor installation. The image analysis routines on the KL25Z generally work by finding the dark and light regions in the image, and the edges between regions. Exaggerating the contrast can make this structure more apparent when the physical light level is relatively uniform.
Enhanced contrast is purely a display option. It doesn't in any way affect the way the readings are taken from the sensor, or how the KL25Z processes the readings. In fact, the KL25Z doesn't even know you're using the enhanced contrast; the only effect is on the on-screen display.
If you're using an image sensor, the Full resolution and Low resolution buttons let you select how many pixels you want to view in the dialog. This doesn't affect how the controller reads the sensor; it only affects the visualization in the dialog. The low res mode is offered simply to let you speed up the frame rate displayed in the dialog.
The resolution setting doesn't change anything outside of the dialog. It has absolutely no effect on how the controller reads the sensor or reports the plunger position in normal pinball play. It also has no effect even within the dialog for non-imaging sensors.
No measuring device is perfect, including the plunger sensors. All sensors have some inherent inaccuracies, which means that they won't always get exactly the same reading twice in a row even when the plunger itself is sitting perfectly still.
On a virtual cab, we don't merely have to take two readings in a row: we have to take readings constantly, tens or hundreds of times per second. We want the game to respond immediately when you move the plunger, so we have to know where it is from moment to moment. With such a rapid series of readings, any inaccuracies in the sensor become apparent on-screen as "jitter", meaning that the virtual plunger jiggles around slightly even when the real plunger is sitting perfectly still.
The "jitter filter" is a special feature in the firmware that lets you filter out this type of random motion to make the on-screen animation more stable and realistic. If your on-screen plunger jitters noticeably, you can use the filter to reduce this. Some sensors need this more than others, so you might not need it at all. If your sensor produces stable animation without the filter, you're better off keeping the filter disabled.
The filter works by setting a "window" size for random motion. Any motion within this window is ignored, so the on-screen plunger will remain motionless even if the sensor readings are fluctuating within the boundaries of the window. The window size is set in terms of the native units for the sensor, which are the same units shown in the sensor display in the plunger viewer window.
Larger window sizes produce stronger filtering, but they also reducing the usable precision of the plunger. Use the lowest setting that produces satisfactory results on your machine. You can disable the filter entirely by setting the window size to 0 (zero).
To help you set up the filter, the viewer window provides a visualization of the filter and its effects. When you enable the filter (by setting a non-zero window size), the green bar at the bottom of the sensor window shows the filtered position, which is what Visual Pinball sees. You'll also see a light green box at the end of the bar; this shows you the current bounds of the filter window. And within the box, a red line shows you the raw position reading from the sensor, before the filter was applied.
The goal is to make the filter window just big enough to contain the random motion, if any, of the raw reading, shown by the red line. With the plunger at rest, start with a small filter window setting, and observe the effect for a little while. If the red line jiggles around so much that the window has to keep jumping around to keep up, increase the window size slightly; repeat until you find a window big enough to contain the random noise.


Sandra's Next Generation is a soul food staple in The Hill. Find out why.
Hear from SandraSandra Pittman sold her first meals out of her home on Edgewood Avenue, but it was her mother’s Alabama roots that gave her food soul. As a child, Sandra learned how to make fried chicken, collard greens, and the other staples of a Southern diet. She never thought about opening a restaurant until her husband, Miguel, suggested a spot on Congress Avenue. In 1989, the couple opened Sandra’s in The Hill, just down the street from the current location.
Sandra’s briefly moved downtown from 2000 to 2007, where she served locals as well as visitors from around the world. After closing the restaurant downtown, Sandra retired from the business briefly. In 2010, Sandra, with the help of her husband and all of her children, reopened Sandra’s The Next Generation on Congress Avenue.
The restaurant keeps moving forward, with dreams of inspiring people and providing a little piece of hope for the neighborhood. Sandra’s next venture? She continues to explore all types of food, including vegan soul food.
Watch this documentary to learn more about Sandra's Next Generation from Sandra herself. Bonus: you'll get to watch her prepare her famous fried chicken.
Film edited by Cyrus Duff. Admire more of Cyrus's work at specialoccasionfilms.com
Take a virtual walking tour of The Hill using Google Maps Street View.
Start at Sandra's Next Generation, which is marked with the red marker.
Click and drag the yellow icon to begin.
203-787-4123


The Kronos Messaging Server (Prototype_1)
Host Server
UserName
Password:
Presence with priority
CONNECTED
XMPP Stanza Input:
To


Exodus 28:7
It shall have the two shoulderpieces thereof joined at the two edges thereof; and so it shall be joined together.


See: Description
| Interface | Description |
|---|---|
| FaxClientSpi |
This interface defines the fax client service provider interface.
This is the actual engine behind the fax4j framework. It handles the fax client activities such as sending/suspending fax jobs and so on. The SPI is an internal class that should be used internally only. The configuration of the fax4j framework is made up of 3 layers. The configuration is based on simple properties. Each layer overrides the lower layers by adding/changing the property values. The first layer is the internal fax4j.properties file located in the fax4j jar. This layer contains the preconfigured values for the fax4j framework and can be changed by updating these properties in the higher layers. The second layer is the external fax4j.properties file that is located on the classpath. This file is optional and provides the ability to override the internal configuration for the entire fax4j framework. The top most layer is the optional java.util.Properties object provided by the external classes when creating a new fax client. These properties enable to override the configuration of the lower 2 layers. For SPI specific configuration, see the relevant SPI class javadoc. |
| FaxClientSpiInterceptor |
This interface defines the fax client SPI interceptor which enables to invoke custom logic before and after the fax
client SPI method invocations (such as logging).
|
| FaxClientSpiProxy |
This interface defines the fax client SPI proxy which enables to invoke interceptors before and after the fax client
SPI method invocations.
With this proxy, it is possible to intercept all calls to the fax client SPIs and perform custom logic such as logging. |
| FaxJobMonitor |
This interface defines the fax job monitor capabilities.
|
| Class | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AbstractFax4JClientSpi |
This class provides partial/common functionlity of the internal fax4j fax client service provider interface.
This class should be used only by internal fax4j SPIs, for SPIs written by vendors outside the fax4j, see the org.fax4j.spi.AbstractFaxClientSpi class. This is the actual engine behind the fax4j framework. It handles the fax client activities such as sending/suspending fax jobs and so on. The SPI is an internal class that should be used internally only. The configuration of the fax4j framework is made up of 3 layers. The configuration is based on simple properties. Each layer overrides the lower layers by adding/changing the property values. The first layer is the internal fax4j.properties file located in the fax4j jar. This layer contains the preconfigured values for the fax4j framework and can be changed by updating these properties in the higher layers. The second layer is the external fax4j.properties file that is located on the classpath. This file is optional and provides the ability to override the internal configuration for the entire fax4j framework. The top most layer is the optional java.util.Properties object provided by the external classes when creating a new fax client. These properties enable to override the configuration of the lower 2 layers. For SPI specific configuration, see the relevant SPI class javadoc. |
||||||||||||||||
| AbstractFaxClientSpi |
This class provides partial/common functionlity of the fax client service provider interface.
This is the actual engine behind the fax4j framework. It handles the fax client activities such as sending/suspending fax jobs and so on. The SPI is an internal class that should be used internally only. The configuration of the fax4j framework is made up of 3 layers. The configuration is based on simple properties. Each layer overrides the lower layers by adding/changing the property values. The first layer is the internal fax4j.properties file located in the fax4j jar. This layer contains the preconfigured values for the fax4j framework and can be changed by updating these properties in the higher layers. The second layer is the external fax4j.properties file that is located on the classpath. This file is optional and provides the ability to override the internal configuration for the entire fax4j framework. The top most layer is the optional java.util.Properties object provided by the external classes when creating a new fax client. These properties enable to override the configuration of the lower 2 layers. For SPI specific configuration, see the relevant SPI class javadoc. |
||||||||||||||||
| AbstractFaxClientSpiInterceptor |
This class provides partial implementation of the fax client SPI interceptor which enables to invoke custom logic
before and after the fax client SPI method invocations (such as logging).
|
||||||||||||||||
| AbstractFaxClientSpiProxy |
This class provides partial implementation of the fax client SPI proxy which enables to invoke interceptors before
and after the fax client SPI method invocations.
With this proxy, it is possible to intercept all calls to the fax client SPIs and perform custom logic such as logging. |
||||||||||||||||
| AbstractFaxJob |
This class provides common partial implementation of the fax job.
|
||||||||||||||||
| AbstractFaxJobMonitor |
This class provides partial implementation of the fax job monitor capabilities.
|
||||||||||||||||
| FaxClientSpiFactory |
This is the fax client SPI factory which is used to create new instances of the fax client SPI.
The configuration of the fax4j framework is made up of 3 layers. The configuration is based on simple properties. Each layer overrides the lower layers by adding/changing the property values. The first layer is the internal fax4j.properties file located in the fax4j jar. This layer contains the preconfigured values for the fax4j framework and can be changed by updating these properties in the higher layers. The second layer is the external fax4j.properties file that is located on the classpath. This file is optional and provides the ability to override the internal configuration for the entire fax4j framework. The top most layer is the optional java.util.Properties object provided by the external classes when creating a new fax client. These properties enable to override the configuration of the lower 2 layers. Below table describes the configuration values relevant for this class, for SPI specific configuration, see the relevant SPI class javadoc. Configuration:
Package org.fax4j.spi DescriptionProvides the API classes for the fax client SPI.
The class/interfaces defined in this package should only be used internally by the fax4j library or by classes implemeting a new fax client SPI. Copyright © 2009–2020 fax4j. All rights reserved. |


corda / net.corda.flows / NonValidatingNotaryFlow / receiveAndVerifyTx
receiveAndVerifyTx
@Suspendable fun receiveAndVerifyTx(): TransactionParts
Overrides Service.receiveAndVerifyTx
The received transaction is not checked for contract-validity, as that would require fully
resolving it into a TransactionForVerification, for which the caller would have to reveal the whole transaction
history chain.
As a result, the Notary will commit invalid transactions as well, but as it also records the identity of
the caller, it is possible to raise a dispute and verify the validity of the transaction and subsequently
undo the commit of the input states (the exact mechanism still needs to be worked out).


BlueBottle
Dashboard
Add Dist
Add SubDist
Add Block
Analyse
Rainfall
Town
Toggle Dropdown
HALIYAL
MUTGA
RAMANAGARA
MYSORE
MADIKERI
MANGALORE
HASSAN
BBMP
SARJAPURA
MUTGA
Near by Cities
Red Alerted Cities
Secondary level Cities
Safe cities
Ready to Leave?
×
Select "Logout" below if you are ready to end your current session.


Allows configuration of, participation in, and administration of presenceless Multi-User Chats. Its feature set is a response to mobile XMPP applications needs and specific environment.


| Home | Libraries | People | FAQ | More |
Using floating-point stream operators for input and output has implications for 'round-tripping' and (most commonly, usefully, and significantly) for serialization.
It is usually necessary to use std::numeric_limits<T>::max_digits10
and sometimes also std::ios::scientific
format to ensure that no information is lost on output.
The implication of the current standards (see round-trip details) is that conversion of a decimal digit string to a floating-point type is not guaranteed to be the nearest representable value, but may be, in effect, be one bit 'wrong'.
| Warning | |
|---|---|
This means that any fixed_point values after serialization and de-serialization may not be identical, and that any integrity check based on checksum or hash may fail. |
In practice, as shown in several tests with with zero
integral range bits, for example, negatable<0, -7>
,
round-tripping is correct for all possible values.
But with non-zero range and lower resolution, there are some differences.
Using scientific format:
Range 0, Resolution 7, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 no fails precision =5
Range 1, Resolution 6, all bits 8, 256
signed values, digits10 = 1, max_digits10 = 4 no fails precision =5
Range 2, Resolution 5, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 no fails precision =4
Range 3, Resolution 4, all bits 8, 256
signed values, digits10 = 1, max_digits10 = 4 minimum 2 fails precision
3, 4 and 5
Range 4, Resolution 3, all bits 8, 256 signed values,
digits10 = 1, max_digits10 = 4 Minimum fails 0 for precision 3
Range
5, Resolution 2, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 Minimum fails 0 for precision 2
Range 6, Resolution 1, all bits
8, 256 signed values, digits10 = 1, max_digits10 = 4 Minimum fails 0 for
precision 2
The outlier here is range 3 and resolution 4 which has two failures.
Using fixed format:
Range 0, Resolution 7, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 Minimum fails 31 for precision 3, 32 for fails max_digits10
Range
1, Resolution 6, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 no fails for precision=5, 32 fails for max_digits10
Range 2,
Resolution 5, all bits 8, 256 signed values, digits10 = 1, max_digits10
= 4 no fails for precision= 4 max_digits10
Range 3, Resolution 4,
all bits 8, 256 signed values, digits10 = 1, max_digits10 = 4 no fails
for precision = 3, 2 fails for max_digits10
Range 4, Resolution
3, all bits 8, 256 signed values, digits10 = 1, max_digits10 = 4 no fails
for precision >= 1
Range 5, Resolution 2, all bits 8, 256 signed
values, digits10 = 1, max_digits10 = 4 no fails for precision >= 1
Range 6, Resolution 1, all bits 8, 256 signed values, digits10 =
1, max_digits10 = 4 no fails for precision >= 1
For this limited test, one can conclude that scientific is definitely best, but that, as expected, exact round-tripping is not assured.
For larger, and useful, fixed_point types, it is not possible to test all possible values in a sensible time, (a day for 32-bit and a lifetime for 64-bit!) and a random selection of values is all that we can usefully test.
But we also must expect different results from different compilers and different versions as some are probably are able to guarantee the nearest representable value.
What one can rely on is getting a result that is at most one bit different from the nearest representable value.
A possible alternative that would guarantee round-tripping and serialization
would be to use get
and
set
functions.
Conversion using operator<<
or strtof(), stdtod()...
does not
guarantee the nearest representable
value, (in contrast to the conversion of decimal digit strings by the compiler, which does
guarantee the nearest representable
value).
C++17 draft standard § <IP_ADDRESS> says that we use C0x § <IP_ADDRESS>/3 (floating constants) rules to interpret the literal decimal digit string thus:
" For decimal floating constants, and also for hexadecimal floating constants when FLT_RADIX is not a power of 2, the result is either the nearest representable value, or the larger or smaller representable value immediately adjacent to the nearest representable value, chosen in an implementation-defined manner. "
Some platforms achieve the conversion to the nearest representable value,
(and thus exact 'round-tipping') at least for decimal digits strings of
reasonable lengths (usually std::numeric_limits<T>::max_digits10
).
A popular platform still fails to convert correctly: see Visual C++ strtod() Still Broken.
(The input operator<<
might also be implemented without using floating-point strtod
,
strtof
or strtol
, functions, but this would increase
code size. Such an implementation would probably be faster because the
length and format of the string is already known from the value of std::numeric_limits<>::max_digits10
, and that the format is
also already known.)


Problem : Yet Another Dubhacking contest | Time limit: 0.3secs | Memory: 256MB | Submit code
Dubhacking is planning to conduct a programming contest in the future. Only a team of three students can participate. Assuming there are n students willing to participate (n%3==0) and all students are numbered from 1 to n inclusive. During formation of the teams, some pairs of students wants to be on the same team. Besides, if the i-th student wants to be on the same team with the j-th one, then the j-th student wants to be on the same team with the i-th one. Wasim and Prashanth want good results from the contest. So they put a condition to hold: if the i-th student wants to be on the same team with the j-th, then the i-th and the j-th students must be on the same team. Also, it is obvious that each student must be on exactly one team.
Help them in dividing the teams in the way they want.
Constraints:
3<=n<=47 such that n%3==0 and 0<=m<=1128
1 ≤ ai < bi ≤ n
Input:
The first line of the input contains integers n and m.
Then follow m lines, each contains a pair of integers ai, bi (1 ≤ ai < bi ≤ n) — the pair ai, bi means that students with numbers ai and bi want to be on the same team.
It is guaranteed that n is divisible by 3. It is guaranteed that each pair ai, bi occurs in the input at most once.
Output:
If the required division into teams doesn't exist, print number -1.
Otherwise, print lines. In each line print three integers xi, yi, zi (1 ≤ xi, yi, zi ≤ n) — the i-th team.
There might be multiple answers for few testcases. You can print any of them. Our judging algorithm and server is intelligent enough! :D
3 0
Sample Output:
3 2 1
6 4
1 2
2 3
3 4
5 6
Sample Output:
-1
3 3
1 2
2 3
1 3
Sample Output:
3 2 1