I like watching movies and listening to music when I have free time.
The movie genre that I love is action and fantasy so, my favorite movie is “Along with the gods” which is a South Korean fantasy action movie.
Also, I always listen to music whenever I do something boring.
I love listening to EDM, Pop, and rap music.
When I was young, I wanted to go and live in other countries to experience a variety of cultures and meet various people.
Also, I wanted to learn both design and coding skills.
I realized that I could do everything I wanted at Fanshawe College, so I decided to study abroad.
Every study that I’m learning here is new for me, so I may not keep up well, but I still want to do my best to learn.
So basically I am From India and I Love playing cricket i am some what weak at coding but since my school days i find
coding very intresting so i am trying best to learn all this and practice as much as i can because I Can't wait to be pro at something which is very intresting to me.
With anime, being more specific I love Isekai's, what that means is going to different worlds and having an exploration in said world. Having an absolute blast in there. For Manga, I love following the roles of villains and villianess as they try to reclaim their honor, try to live a subtle life after doing such horrific acts as the baddie. The video games I love to play would be Battle Royales such as Apex Legends, Bloodhunt and Hunt: Showdown currently, moving into Moba's such as SMITE and mobile games like Raid: Shadow Legends.
 I am what some people call a weeb or an otaku. I used to play ESports but quickly got burnt out when it was day-in day-out work due to the pandemic. Just the same games over and over again. I am proud about being Ojib-cree. I am the 7th oldest out of 15 children. All the same mom but different dads. I used to live in North Western Ontario so I know cold, coldest it has ever been up there was -55c. I wish it got as much snow down here and it does up there. I love Halloween because it would be my birthday and then 6 days later I get a ton of candy.


Mountain Spokes
Owner Operated.
Diamondback Mission 1.0 Bike 2017
Grade Aluminum w/ Hydroformed Top Tube, Butted/Formed Down Tube/ Seatstays durable, lightweight and reliable performance.
Fox Shox front and rear suspension for a superior feel and ride.
SRAM Level T Hydraulic Disc brakes for steadfast braking ability.
1x11spd SRAM drivetain Smooth and reliable shifting
RaceFace Ride 1x crankset with 30t Narrow Wide charinring. Never drop a chain!


The world is full of fascinating places. Planning the perfect vacation involves packing up, leaving home, and experiencing something new.


by ipedrazas 2013-02-21 stats
78 visits to the app page (78.71% from Twitter, 8.17% from Facebook, 0% from G+)
And this, my friends, it’s why you all should have the best communicators driving your corporate twitter accounts.
Ok, let’s be honest here. I really thought that Facebook would be 0 and that Google Plus would be closer to twitter… and I was wrong. Very wrong.
Google must be doing something very wrong to not driving traffic like that. 0%? that’s absolute rubbish!
Bear in mind that I posted to different G+ circles with, in total, thousands of people. Result: 0
I use Facebook ONLY for family and close friends… so, don’t get offended if I don’t know you very well and I don’t accept your facebook request… and now remember that me being Spanish and spaniards not mastering English it’s kind of foreseeable that not much traffic will come from Facebook… still, almost a 10% came from it.
Let me remind you that Thousands in G+ were trumped by a handful of Facebook friends, and completely smashed by Twitter. Google, you’re doing something very wrong.
Did we say Twitter? well, I have less than 400 followers, but I managed to get 78 clicks. 72 of which came from Twitter… So, 1 in 5 of my followers clicked my link. Will be good to know if this percentage scale but I’m afraid it will not, still 20% of my followers visiting the app page is awesome!
Thanks guys!
What can we learn from this? Twitter is a wicked for promotion. Forget Facebook, Ignore Google Plus. Tweet, Tweet, Tweet!
Anyone in the room fancy sharing their experiences?


This person was actually standing at where I stood to take a picture of another person through the same window, 10 seconds before she became captured in my version of the flattened view. The contrast between the vivid, on-going space she is in, and the flat embedded frame from which I perceive her might be analogous of the flattening processing we apply to other humans.


--- title: 1.7.9 Version layout: post published: true ---
Hello all,
We've juste publish Kevoree 1.7.9 version.
Severals bug improve the stability, especially for android runtime.
We also add severals cool feature in KevEditor like save model as KevScript or load from ArduinoNode.


--- layout: default title: For Nonprofits permalink: /for-nonprofits nav_highlight: /for-nonprofits --- {% assign charities_text = site.data.for_charities_text %}
Get in touch


Just send us a text message, we'll record it, and reply back with a random response emoji.
We are currently invite only, please send a message with your phone number to be invited.


Data Analyst, excited by the insight found when exploring data coupled with the beauty and clarity of visualizations.
Find Out MoreA former finance professional with new found passion for coding and data analytics looking to make a career change from operations to tech.
Being a visual person and a firm believer that data can create meaningful stories that can help companies improve their business intelligence and process has driven me into the world of data analytics.
I wish to utilize my keen analytical and problem-solving skills to identify and solve business problems through a multidisciplinary approach.
If I'm not anylyzing data then I'm probably exploring new places to eat and trying out new food.
ResumePython, Numpy, Pandas, Matplotlib, API Interactions, Social Media Mining, Vader Sentiment Analysis
MySQL, MongoDB, Sqlite3, NoSql
HTML, CSS, Bootstrap, JavaScript, D3.js, Dashboarding, Plotly
Tableau, Machine Learning, Big Data with Hadoop


An OutputStream
handles byte data.
OutputStream is an abstract class from which all
byte-oriented output streams are derived.
Its descendant classes are used for general-purpose
(non-character output).
These streams are aimed at
writing groups of 8-bit bytes to output destinations.
The bytes are in the same format as Java primitive types.
For example,
4-byte groups corresponding to type int
can
be written to a disk file.
We will mostly be interested in FileOutputStream
and DataOutputStream
.
We have used PrintStream
many times already,
because System.out
is an object of that type.


When you get assistance you go to a doctor or health care provider and ask for help with quitting smoking.
This could involve:
Health
If you quit,
You will have lower risk of serious diseases, such as cancer, heart disease, and stroke.
You can add years to your life.
This option is recommended by doctors
Cost
If you quit,
Withdrawal Symptoms
If you quit using nicotine replacement product or prescription medicines, your nicotine cravings and withdrawal symptoms may be reduced.
Support
Chances for Success
You are more likely to quit with assistance from a health care provider than by going it alone
# out of 100 people successfully quit with counseling from a physician
# out of 100 people successfully quit using a combination of counseling and medication
# our of 100 people quit using a combination of counseling and NRT
Health
Your appetite may increase
Cost
You may have to pay for things such as nicotine replacement products out of pocket
Side Effects
If you quit using prescription medicines, side effects vary depending on the product. They may include:
Withdrawal Symptoms
If you quit only using counseling you may experience nicotine cravings or withdrawal symptoms.


Find Your Brew
Brew result [1]
Bars with this brew on tap
Bar 1
.5 miles
Bar info
[Bar name]
[Address]
This bar currently [has your brew on tap]


--- layout: default carousel: - img: MyImages/ResearchProject/Headslides.001.gif text: Big Data Inference caption: - img: MyImages/ResearchProject/Headslides.002.gif text: Network Models caption: - img: MyImages/ResearchProject/Headslides.003.gif text: Predictive Systems caption: - img: MyImages/ResearchProject/Headslides.004.gif text: Optimization caption: - img: MyImages/ResearchProject/Headslides.005.gif text: Method and Theory caption: portfolio: heading: Research Projects items: - link: /dimensional_inferencing.html img: MyImages/research/dimensional.jpg alt: High Dimensional Inference/Big Data Analytics - link: /casual_inference.html img: MyImages/research/brain.jpg alt: Casual Inference script: | $('.carousel').carousel({ interval: 5000 //changes the speed }) ---


India fastest growing economy among G20: Sitharaman
by DH Web DeskFinance Minister Nirmala Sitharaman said on Monday that India's economic growth has decelerated but it is still the fastest-growing among the G20 nations. She also assured that the goal of $5 trillion economy will be achieved by 2025.
In a question raised by NK Premachandran, an MP from Kerala, Sitharaman replied that though India is seeing a deceleration in growth recently, its economy is being projected as the fastest-growing among G-20 countries in 2019-20.
"The government has been taking several measures to address moderate levels of fixed investment rate in the economy, plateauing of private consumption rate and modest export performance, with a view to increasing the GDP growth," said Sitharaman.
Sitharaman also said that the 15 per cent corporate tax rate for new domestic manufacturing companies announced in September was "amongst the lowest in the world".


Shadow Demon
Tips
- If you select your Disruption illusions you can see how the enemy is skilling themselves since your
illusions' skill points will mirror the enemy's. For example, since Shadow Demon is a popular pick
against Anti-Mage (because the illusions will Mana Break AM), you can use this to see how AM is skilling
himself (maxing Mana Break, maxing Blink, or taking stats).
- There are pretty much only two reasons why you should ever Disrupt an ally to save them.  For slows, blinds, silences, or disarms, unless you're communicating with your allies,
avoid Disrupting them. 9 times out of 10, people will get mad at you even if they were dead anyway.
- However, there are tons of great situations to use Disruption on allies in other situations. During
tower pushes, make more Lunas for maximum glaives. During defenses, make fake Batriders and send one in.
When warding, make more yous to bait a gank attempt.
- Disruption banishes a target for 2.5 seconds. Blink Dagger's damage cooldown is 3 seconds. Cast a Shadow
Poison while a target is Disrupted to keep their Blink Dagger on cooldown. You don't even need to use
the Detonate because the impact damage from the Shadow Poison will disable Blink Dagger and then they'll
immediately take damage from the illusions afterwards.
- Early game, try fishing for Disruptions on enemies when they're 'cornered' against the map, then stand near
the Disruption. There's a chance they'll be fully body-block-locked between you and the two illusions when they
come out.
- With some practice, you don't even need to corner an enemy. If you plant an Iron Branch and stand on a Disruption,
enemies will be blocked on all 4 sides (2 illusions, your hero, a tree). This probably won't work early game when
everyone has tangoes, but there's something to be said for a 15-30 minute GG branch on SD.
- Shadow Poison is a great spell to use to stack camps because of its ludicrous range and cheap mana cost.
For maximum supportage, angle yourself so you can stack two camps with one Shadow Poison.
- With practice,
you can even stack three camps (this is on the pre-6.86 map, but it gives you a good idea).
- Stacking camps is useful with Shadow Demon because he's actually great at taking stacks himself with
Shadow Poison. Once maxed, it takes 6 stacks of Shadow Poison to kill any camp, or 7 if you want to play it safe with
magic resistance aura creeps.
- Shadow Poison is another great spell to draw creep aggro off a tower during defenses.
- Shadow Poison's projectile gives flying vision as it travels.
- Demonic Purge is essentially a Diffusal Blade purge that can go through spell immunity. This includes
the ability to remove runes.
- Demonic Purge can damage and slow enemy couriers.
- Agh upgraded Demonic Purge Breaks passive abilities (like Agh Doom and Silver Edge).
Counters
- Get a Magic Stick if he's spamming Shadow Poison.
- The only reason Shadow Poison is balanced is because the projectile is very easy to dodge. Don't get
lazy.  If you've bumbled your way into 3 stacks, back off.
- The only reason Soul Catcher is balanced is because it's extremely hard to land, especially in the
laning phase. Being a ranged hero will actually work against you when laning against SD because your
natural positioning makes you easy pickings for a Soul Catchin'.


ML models are ubiquitous -- from transportation (self-driving cars) to finance (credit card or mortgage applications) and careers (company hiring). ML, however, does not come without its risks. Some important risks involve model understanding and accountability: models created by machine learning are largely black boxes that are hard for us to peer into and understand; they are susceptible to unforeseen faults, to adversarial manipulation, and to violations of ethical norms in privacy and fairness.
This course will provide an introduction to state-of-the-art ML methods designed to make AI more trustworthy. The course focuses on four concepts: explanations, fairness, privacy, and robustness. We first discuss how to explain and interpret ML model outputs and inner workings. Then, we examine how bias and unfairness can arise in ML models and learn strategies to mitigate this problem. Next, we look at differential privacy and membership inference in the context of models leaking sensitive information when they are not supposed to. Finally, we look at adversarial attacks and methods for imparting robustness against adversarial manipulation.
Students will gain understanding of a set of methods and tools for deploying transparent, ethically sound, and robust machine learning solutions. Students will complete labs, homework assignments, and discuss weekly readings.
Students are expected to have the following background:
Permissive but strict. If unsure, please ask the course staff!
We’re generally open to auditing requests by all Stanford affiliates. External requests will be determined on a case by case basis, mostly because the course is hosted on Canvas and we’re not sure how non-Stanford affiliates access Canvas.
You will be able to attend all the lectures, but we won't be able to grade your homework or give advice on final projects. Our human resources are limited. There are only four of us and on top of teaching, we also have full-time jobs or are full-time students.
Even if you’re not auditing, you can still access all the slides, notes, assignments, and final repot instructions. These are posted on the Syllabus page.
To audit the class, please send<EMAIL_ADDRESS>an email with the subject title "CS329T: Audit Request" with a few sentences introducing yourself and your relevant background.
We’ll add you as an observer on Canvas -- you need to create an account on Canvas first. You can attend all lectures scheduled there.
There's no textbook. The course relies on lecture slides and accompanying readings.


Interactive Merge Sort 2.0 [WIP]
1
2
3
4
5
6
Welcome to Merge Sort Interactive
This is a tutorial for understanding the concept behind the merge sort algorithm.
Use the carousel slider or arrow keys to navigate.


Godzilla (PG-13) ** (out of ****)
Reviewing a much-ballyhooed "event" movie like _Godzilla_ is a pointless task. No matter what I or any critic might say about it, everyone and their mother will still rush out to the theatre to see the movie just to say that they did. But in the event that anyone out there is listening, be forewarned that this lavish take on the classic Japanese monster movies is a technically superb but flavorless piece of sci-fi hackwork.
_Godzilla_'s mediocrity should not come as a surprise to anyone familiar with the work of the "brains" behind the project, the team of co-writer/producer Dean Devlin and co-writer/director Roland Emmerich. As the film's many trailers so bombastically boast, they are the creators of that overhyped sci-fi phenomenon of a couple year's back, _Independence_Day_ (they were also behind another inexplicable success, 1994's ridiculous _StarGate_, as well as 1992's unspeakably horrid Jean-Claude Van Damme-Dolph Lundgren battle royale _Universal_Soldier_). I was lukewarm on _ID4_ (it earned a fairly charitable ** 1/2 on my scale--which elicited a rather snottily sarcastic e-mail from Devlin himself), which had top-flight effects, a charismatic lead (the incomparable Will Smith), but a sloppy script populated by poorly drawn characters with vapid individual storylines.
_ID4_'s "human dimension" (which a lot of people actually bought into) is as profound as _Schindler's List_'s in comparison to what is on display in _Godzilla_--or, rather, what _isn't_ on display. Our primary human guide throughout the giant lizard mayhem is Dr. Niko Tatopoulos (Matthew Broderick), a nuclear scientist who is enlisted by the military to investigate the origins and analyze the behavior of the behemoth reptile that is destroying New York City. There, he is reunited with his college sweetheart, aspiring reporter Audrey Timmonds (Maria Pitillo, sporting wild Sarah Jessica Parker-ish locks--a coincidence?). Their love story is supposed to be the emotional hook, but Devlin and Emmerich scarcely bother to give them any quiet scenes alone together, so what's the point? Broderick and Pitillo appear to not see one either, woodenly playing their already-plywood roles and failing to generate any romantic spark whatsoever.
But the flat lead characters are the least of _Godzilla_'s problems. The film's fundamental flaw can best be summed up in the scene where the creature's appearance is fully revealed. The work of creature designer and supervisor Patrick Tatopoulos does not disappoint; sort of a mix between a T-rex, stegosaurus, and velociraptor with a little iguana thrown in, Godzilla's look is truly menacing, and the big visual revelation should be a moment of genuine fright and tension, much like the grand T-rex entrance in _Jurassic_Park_. But Emmerich completely misdirects the moment. The audience's first, uninterrupted glimpse is scored with some uplifting, awe-inspiring music not unlike _Jurassic_'s main theme, and Niko's aghast look is one more of wonder than fear, which is what I'm sure any person, scientist or not, would feel in the presence of a giant, hungry lizard.
This is but the first instance in Emmerich's complete botching of what should be a key element in _Godzilla_--terror. For all the destruction Godzilla causes, and the threat he poses to everyone's lives, the purported "thrill ride" feels safe and is not scary in the slightest. This is especially the case in an extended sequence set in the destroyed Madison Square Garden. Without giving away a key plot "surprise," the sequence's obvious model is the showcase raptor sequence in _Jurassic_ (in fact, so much of _Godzilla_ is derivative of _Jurassic_ it might as well have been called _Godzilla_Park_), but Emmerich and Devlin mistake quantity for quality. If you see the film, you'll know what I mean--the threat to the "heroes" is considerably larger, but I never once felt that they were in any danger.
The always-visually exciting (as opposed to just plain exciting) _Godzilla_ would have gone down a bit easier if there was a greater dose of humor. Unlike _ID4_, which had a comic firecracker at its center in Smith, Godzilla's stabs at humor are few and, frankly, not terribly funny. Hank Azaria, as news cameraman Victor "Animal" Palotti, tries to make the most of the blah wisecracks he's assigned to deliver. A running dig at Roger Ebert--the stocky, silver-haired, bespackled mayor (Michael Lerner) is also named Ebert, and an upturned thumb is his big campaign gesture--grows old quickly. An injokey dig at Warner Bros. and Disney, numerous lame verbal gags involving Niko's Greek surname, Harry Shearer's pompous news anchor (who is not too far from one of his _Simpsons_ roles, newsman Kent Brockman), and some comic stoicism by Jean Reno (playing--what else?--a shady Frenchman) round out the film's light touches. As a whole, the film takes itself much too seriously--much like Devlin and Emmerich themselves.
The terrible twosome have proclaimed themselves the Lucas and Spielberg of this generation (a sad testimony), which could not be farther from the truth. While they are adept at handling the technical aspects of effects-laden extravaganzas (_Godzilla_ is, if anything, a superlative technical achievement, terrifically designed by Oliver Scholl and shot by Ueli Steiger), they have yet to display any of the imagination, creativity, or solid ideas of George and Steven. What ideas they do have only work within the confines of two-minute trailers, which are always far superior to the full films themselves. The fact that hype-brainwashed moviegoers don't ever appear to care--and pre-sold _Godzilla_ certainly won't break the mass hypnosis--shows that their true calling lies within the offices of a studio's marketing department and _not_ on the creative end of the film business.
Michael Dequina Chat Forum Host, The Official Michael Jordan Web Site http://jordan.sportsline.com
<EMAIL_ADDRESS><EMAIL_ADDRESS>|<EMAIL_ADDRESS>>My personal WWW sites< Mr. Brown's Movie Site: http://welcome.to/mrbrown Michael Jordan Beyond the Court: http://fly.to/michaeljordan A Michael Jordan Fan's Heartbreak: http://fly.to/mj23 Personal Page: http://welcome.to/w3md >Other WWW sites I work on< CompuServe Hollywood Hotline: http://www.HollywoodHotline.com Albany Online: http://www.AlbanyOnline.com Eyepiece Network: http://www.eyepiece.com
"I didn't know what to expect. It's like something you chase for so long, but then you don't know how to react when you get it. I still don't know how to react." --Michael Jordan, on winning his first NBA championship in 1991 ...or, my thoughts after meeting him on November 21, 1997
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


| AmbientLight |
An ambient light adds a constant color to the scene.
|
| BasicProbeBlendingStrategy |
This strategy returns the closest probe from the rendered object.
|
| DefaultLightFilter |
|
| DirectionalLight |
DirectionalLight is a light coming from a certain direction in world space.
|
| Light |
Abstract class for representing a light source.
|
| LightList |
LightList is used internally by Spatial s to manage
lights that are attached to them.
|
| LightProbe |
A LightProbe is not exactly a light.
|
| OrientedBoxProbeArea |
|
| PointLight |
Represents a point light.
|
| SphereProbeArea |
|
| SpotLight |
Represents a spot light.
|
| WeightedProbeBlendingStrategy |
This strategy returns the 3 closest probe from the rendered object.
|


alasql("SELECT * INTO HTML('#result',{headers:true}) FROM cities;")
alasql("SELECT * INTO HTML('#result',{headers:true}) FROM cities WHERE population > 3000000 ORDER BY population DESC;")


Examples using the figure module
Here is the table of content for the example programs.
Figure with and without figcaption.
Align images to center using css-class
.center
.
Align images to left using css-class
.left
.
Align images to right using css-class
.right
.
Responsive using css-class
.w25
.
Responsive using css-class
.w33
.
Responsive using css-class
.w40
.
Responsive using css-class
.w50
.
Responsive using css-class
.w67
.


Advice Giver
Home
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Project JXTA will be offering a tutorial for developers just starting out with JXTA technology and for those who are already using JXTA for development. Come learn about Project JXTA technology and our community when we get together on January 8, 2004. The tutorial is offered as part of the IEEE Consumer Communications and Networking Conference.
Start out the year on the right foot. Come join in the fun!
Project JXTA is an open network programming platform to enable peer-to-peer (P2P) services and applications. Developers and software vendors can freely use the JXTA Open Source technology to build secure, interoperable P2P applications that can run on any connected device from servers to hand-held devices.
The Project JXTA Tutorial will guide the participants through a complete JXTA overview including project history, problem domain, feature set and available resources. Subsequently, the various JXTA projects will be touched upon with an emphasis on the core projects, namely Platform and Shell. As a result, the class participant will be able to obtain and run the specified core projects. Lastly, a number of developer focused exercises will be explained touching upon JXTA Peer configuration, initialization, queries, etc.
Attendees will develop a clear understanding of programming distributed systems, the status, available resources, and future direction of JXTA technology, as well as information about the jxta.org Open Source community. Project JXTA technology is both language and protocol agnostic. Our reference implementation is written in Java(TM), so we will be covering both Java 2 Platform, Standard Edition (J2SE)(TM) for desktops and servers and Java 2 Platform, Micro Edition (J2ME)(TM) for smaller devices such as PDAs and cell phones.
Benefits:
Tutorial Fees:
Conference registration fee depends on whether the student registers for one day or the full conference.
| On or before December 5, 2003 | After December 5, 2003 | |
| IEEE member with registration | $300 | $350 |
| IEEE member without conf. registration | $350 | $400 |
| Non-member with conf. registration | $350 | $400 |
| Non-member without conf. registration | $400 | $450 |
Schedule notes:
This tutorial is tentatively scheduled for the morning of January 8th, Las Vegas, NV. For more information or to register:


Derek Nimmo (born 1930-09-19[ref]) has appeared in 309 episodes between 1967-2007. Derek Nimmo on IMDB. Derek Nimmo on Wikipedia.
| 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 |


Create a new repository on GitHub and clone it to your local computer
On GitHub choose "Create New Repository"
Name the repository
Make it public or private
Choose whether to auto-include a README file
Choose a license (for DBC we've been using MIT License)
Click "Create"
Copy the URL for cloning
On your local computer, navigate to the directory in which you want the repository directory to be created. To be clear, whatever directory you are in, Git will be creating a subdirectory with the name of the repository, and the files for that repository will be inside the Git-created subdirectory.
At the command line enter
git clone
then paste the URL after and enter.
Create a new branch and move into it to start work in it
Make sure you are in the branch you want to branch off of. Often, you want to branch off of master. To make sure you are in master:
git checkout master
Create and move into the new branch, let's call the new branch awesome-feature-branch:
git checkout -b awesome-feature-branch
Stage (add) files that you've edited in the current branch
Before adding (staging) your files prior to a commit, you can double-check the status of files that have had changes to them:
git status
Add (stage) the files:
git add <filename>
Or, to add all the changed files at once:
git add .
Optionally check the status again to ensure that they were actually added:
git status


properties¶
Tools to manage the properties of a feature
Classes¶
- Property
The class Property, which represents the values of a property of a feature. A Property be: * A constant (initialization with, e.g., a number, a tuple) * A sequence of variables (initialization with, e.g., an iterator) * A random variable (initialization with, e.g., a function)
- SequentialProperty
The class SequentialProperty, which extends Property to sample one value for each step in a sequence.
- PropertyDict
The class PropertyDict, which is a dictionary with each element a Property. The class provides utility functions to update, sample, clear and retrieve properties.
Module classes¶
Property¶
-
class
deeptrack.properties.
Property
(sampling_rule)¶ Represents a property of a feature
The class Property` wraps an input, which is treated internally as a sampling rule. This sampling rule is used to update the value of the property. The sampling rule can be, for example: * A constant (initialization with, e.g., a number, a tuple) * A sequence of variables (initialization with, e.g., a generator) * A discrete random variable (initialization with, e.g., a list, a dictionary) * A continuous random variable (initialization with, e.g., a function)
- Parameters
- sampling_ruleany
Defines the sampling rule to update the value of the feature property. See method sample() for how different sampling rules are sampled.
- Attributes
- sampling_ruleany
The sampling rule to update the value of the feature property.
- current_valueany
The current value obtained from the last call to the sampling rule.
Methods
sample
(sampling_rule, **kwargs)Samples the sampling rule
update
(**kwargs)Updates the current value
-
sample
(sampling_rule, **kwargs)¶ Samples the sampling rule
Returns a sampled instance of the sampling_rule field. The logic behind the sampling depends on the type of sampling_rule. These are checked in the following order of priority:
- Any object with a callable sample() method has this
method called and returned.
- If the rule is a
dict
, sample each value and combine the result into a new
dict
using the original keys.
- If the rule is a
- If the rule is a
list
, sample each element of the list and combine the result into a ne
list
.
- If the rule is a
If the rule is an
iterable
, return the next output.- If the rule is callable, call it with its accepted arguments.
Example arguments can be the value of some other property.
If none of the above apply, return the rule itself.
- Parameters
- sampling_ruleany
The rule to sample values from.
- **kwargs
Arguments that will be passed on to functions that accepts them.
- Returns
- any
A sampled instance of the sampling_rule.
-
update
(**kwargs)¶ Updates the current value
The method update() sets the property current_value as the output of the method sample(). Will only update once per resolve.
Any object that implements the method update() will have it called.
- Returns
- Property
Returns itself.
PropertyDict¶
-
class
deeptrack.properties.
PropertyDict
(*args, **kwargs)¶ Dictionary with Property elements
A dictionary of properties. It provides utility functions to update, sample, reset and retrieve properties.
- Parameters
- *args, **kwargs
Arguments used to initialize a dict
Methods
clear
()copy
()current_value_dict
(**kwargs)Retrieves the current value of all properties as a dictionary
fromkeys
(/, iterable[, value])Create a new ordered dictionary with keys from iterable and values set to value.
items
()keys
()move_to_end
(/, key[, last])Move an existing element to the end (or beginning if last is false).
pop
(k[,d])value.
popitem
(/[, last])Remove and return a (key, value) pair from the dictionary.
sample
(**kwargs)Samples all properties
setdefault
(/, key[, default])Insert key with a value of default if key is not in the dictionary.
update
(**kwargs)Updates all properties
update_item
(item, **kwargs)Updates a single property.
values
()-
current_value_dict
(**kwargs)¶ Retrieves the current value of all properties as a dictionary
- Returns
- dict
A dictionary with the current value of all properties
-
sample
(**kwargs)¶ Samples all properties
- Returns
- dict
A dictionary with each key-value pair the result of a sample() call on the property with the same key.
-
update
(**kwargs)¶ Updates all properties
Calls the method update() on each property in the dictionary.
- Returns
- Properties
Returns itself
-
update_item
(item, **kwargs)¶ Updates a single property.
- Parameters
- item: Property
The item to update.
- Returns
- self
SequentialProperty¶
-
class
deeptrack.properties.
SequentialProperty
(sampling_rule, initializer=None)¶ Property that has multiple sequential values
Extends standard Property to resolve one value for each step in a sequence of images. This is often used when creating movies.
- Parameters
- initializerany
Sampling rule for the first step of the sequence.
- sampling_ruleany
Sampling rule for each step after the first.
- Attributes
- initializerany
Sampling rule for the first step of the sequence.
- sampling_ruleany
Sampling rule for each step after the first.
- has_updated_since_last_resolvebool
Whether the property has been updated since the last resolve.
Methods
sample
(sampling_rule, **kwargs)Samples the sampling rule
update
([sequence_length])Updates current_value
-
update
(sequence_length=0, **kwargs)¶ Updates current_value
For each step in the sequence, sample self.sampling_rule. self.initializer is used for the first step. These rules should output one value per step. Sampling rules that are functions can optionally accept the following keyword arguments:
sequence_step : the current position in the sequence.
sequence_length : the length of the sequence.
previous_value : the value of the property at the previous step in the sequence.
previous_values : the value of the property at all previous steps in the sequence.
- Parameters
- sequence_lengthint, optional
length of the sequence
- Returns
- self
returns self


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Try it


The Session object that you can get from the Request.getSession() provides some additional methods:
| Method | description |
|---|---|
| getID() | the session ID (string). This is a rather long id that is cryptographically (i.e. very) hard to guess (it is constructed from several variables and then fed through SHA-1, a secure hash. The variables are the remote client address, the current time in string format and numerical format, and a random number). |
| isNew() | if the session is brand new (this means that only the server knows about it, it has not been synchronised with the client yet). |
| loginUser(user) | set logged in user object - this must be an instance of snakeserver.user.LoginUser . This class stores userid, password(hash), a user name and a set of privileges. Often this is enough. If you need more, you have to create your own subclass (don't forget to call __init__ ). For more information about the built-in LoginUser class, see authentication. |
| logoutUser() | Logs out the current user. The session remains alive. Usually you also want to clear the session: see Request.deleteSession() |
| getLoggedInUser() | get logged in user object (an instance of snakeserver.user.LoginUser , or a subclass thereof), or None . For more information about the built-in LoginUser class, see authentication. |
| getContext() | the session context (ContextContainer object). Scope: session (Request.getSessionContext() is a shortcut for this) unique per user, shared for all requests of this user |
For correct session management, the web browser must allow session cookies from the website. If cookies are not allowed, and the web browser accesses a page that uses a session, every request from the browser will cause a new session to be created on the server (to a certain limit that Snakelets enforces).
Test if cookies are enabled: There are various was to test if the web browser accepts cookies. The 'test' webapp that comes with Snakelets contains three examples that show how you can check for correct session-cookie acceptance (in a snakelet, in an Ypage, and using Javascript). The basic trick is to send a http refresh back to the browser, and when the next request comes in, the code checks for the existance of a "valid" session.
The session cookie that is used is called SNSESSID
, and has its path set to /webapp/ (the name of the webapp that is accessed) on the server from your URL. In case of shared sessions, the session cookie that is used is called SNSESSIDSHR
, and has its path set to / (the root) on the server from your URL. The contents of the cookie is just the session id.


HTTPS, Live Search, and a new blog
After a few years on the backburner, we’re finally moving Chowdown up to a low simmer. We’re back with a slew of updates like HTTPS, live search, our first pull request, and this blog!
A quick runthough the new goodness:
- HTTPS for chowdown.io is now enabled by default, thanks to recent changes by Github Pages. If you’re hosting with Github, enabling it for your own site is as simple as using the correct A/CNAME/DNS records.
- A simple live search is now available at /search. It indexes the recipe title and the ingredients (so you could find stuffed peppers by searching either “pepper” or “goat cheese”).
- This may seem ordinary elsewhere, but I wanted to take a quick minute to celebrate Chowdown’s first pull request. We’ve had a few forks and comments over the years, but I wasn’t really watching the project like I should, and now that we’re back on track, it’s time to celebrate 🎉🙌. You can see it here, where @maartenpaauw submitted a little fix that enabled component recipes to have ingredients of their own. Nice!
- A new readme is up in the root of the repo, (read it here). Moving forward, I’ll keep updating it and plan to keep an eye on the beginner use-case (which is me, I’m still new to Jekyll).
- Changed the default typeface to Inter UI, from Rasmus Andersson. Previously we were using Karla.
- Last but not least, I’ve added a simple blog template (this one!). That means I’ll be posting some updates here on chowdown.io, but also that you can use the blogging template in your own install (if you’re into that).
New features hopefully coming in the next few weeks:
- Reworked templates, including some design tweaks and a swap to the latest version of BassCSS.
- PWA stuffs, like more “add to homescreen” and offline caching.
I’ll try to post some updates on new projects soon, and I’m always looking for feedback (and recipes! submit via pull request!). Until then, happy cooking!
Posted by @clarklab on Sep 9, 2018


XPathResult
public enum XPathResult
This enum represents a result of a search by an XPath.
- none: The result value is undefined
- nodeSet: The result value is a node set
- bool: The result value is a boolean
- number: The result value is a number
- string: The result value is a string
-
The result value is undefined
Declaration
Swift
case none
-
The result value is a node set
Declaration
Swift
case nodeSet(XMLNodeSet)
-
The result value is a boolean
Declaration
Swift
case bool(Bool)
-
The result value is a number
Declaration
Swift
case number(Double)
-
The result value is a string
Declaration
Swift
case string(String)
-
The position of the first element in a nonempty collection.
If the collection is empty,
startIndex
is equal toendIndex
.Declaration
Swift
public var startIndex: Int
-
Accesses the element at the specified position.
The following example accesses an element of an array through its subscript to print its value:
var streets = ["Adams", "Bryant", "Channing", "Douglas", "Evarts"] print(streets[1]) // Prints "Bryant"
You can subscript a collection with any valid index other than the collection’s end index. The end index refers to the position one past the last element of a collection, so it doesn’t correspond with an element.
Parameter
Parameter position: The position of the element to access.position
must be a valid index of the collection that is not equal to theendIndex
property.Declaration
Swift
public subscript(index: Int) -> XMLElement
Parameters
position
The position of the element to access.
position
must be a valid index of the collection that is not equal to theendIndex
property. -
The collection’s
past the end
position—that is, the position one greater than the last valid subscript argument.When you need a range that includes the last element of a collection, use the half-open range operator (
..<
) withendIndex
. The..<
operator creates a range that doesn’t include the upper bound, so it’s always safe to use withendIndex
. For example:let numbers = [10, 20, 30, 40, 50] if let index = numbers.index(of: 30) { print(numbers[index ..< numbers.endIndex]) } // Prints "[30, 40, 50]"
If the collection is empty,
endIndex
is equal tostartIndex
.Declaration
Swift
public var endIndex: Int
-
Returns the position immediately after the given index.
Returns
The index value immediately afteri
.Declaration
Swift
public func index(after i: Int) -> Int
Parameters
i
A valid index of the collection.
i
must be less thanendIndex
.Return Value
The index value immediately after
i
.
-
Returns a Boolean value indicating whether two values are equal.
Equality is the inverse of inequality. For any values
a
andb
,a == b
implies thata != b
isfalse
.- Parameters:
- lhs: A value to compare.
- rhs: Another value to compare.
Declaration
Swift
public static func ==(lhs: XPathResult, rhs: XPathResult) -> Bool
Parameters
lhs
A value to compare.
rhs
Another value to compare.
- Parameters:


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JS Debounce
2019-05-09 11:02:00
These days, i have created a scheduler for my school management system project, i have met the problem that evert time i click the next button to turn to next page, so the frontend will send AJAX r ......
2019-05-09 11:02:00
These days, i have created a scheduler for my school management system project, i have met the problem that evert time i click the next button to turn to next page, so the frontend will send AJAX r ......
2019-04-25 20:45:00
Here are a few concepts introduced firstly.
To understand the callback function, first understand the rules of the funct ......
2019-04-06 11:13:00
Getting Started with my own blog.
From now on, I will continue to update my own code and share my coding problem with you.


--- layout: post title: Oasis concept date: '2015-09-22T18:30:46+02:00' categories: - Concept Art picture_url: https://film-Storyboards.tumblr.com/post/129671901608/desert-solar-city-oasis-concept ---
Desert solar city / oasis concept.


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In this chapter, the syntax of SIF is presented using a modified BNF notation. All nonterminals and BNF punctuation are written in boldface, while characters in SIF are expressed in plain font. The notation {x1,...,xn} means the set of terminals x1,...,xn. The notation [nonterminal] means zero or one instances of nonterminal; nonterminal* means zero or more occurrences; nonterminal+ means one or more occurrences; nonterminal^n means n occurrences. The notation nonterminal1 - nonterminal2 refers to all of the members of nonterminal1 except for those in nonterminal2. The notation int(n) denotes the decimal representation of integer n. The nonterminals space, tab, return, linefeed, and page refer to the characters corresponding to ascii codes 32, 9, 13, 10, and 12, respectively. The nonterminal character denotes the set of all 128 ascii characters. The nonterminal empty denotes the empty string.
SIF characters are classified as upper case letters, lower case letters, digits, alpha characters (non-alphabetic characters that are used in the same way that letters are used), special characters, white space, and other characters (every ascii character that is not in one of the other categories).
upper ::= A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z lower ::= a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | p | q | r | s | t | u | v | w | x | y | z digit ::= 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 alpha ::= ! | $ | % | & | * | + | - | . | / | < | = | > | ? | @ | _ | ~ | special ::= " | # | ' | ( | ) | , | \ | ^ | ` white ::= space | tab | return | linefeed | pageA normal character is either an upper case, a lower case character, a digit, or an alpha character.
normal ::= upper | lower | digit | alpha
The function of a lexical analyzer is cyclic. It reads characters from the input string until it encounters a character that cannot be combined with previous characters to form a legal lexeme. When this happens, it outputs the lexeme corresponding to the previously read characters. It then starts the process over again with the new character. Whitespace causes a break in the lexical analysis process but otherwise is discarded unless it occurs within a string or is preceded by a suitable escape character.
There are five types of lexemes in SIF -- special lexemes, words, character references, character strings, and character blocks.
Each special character forms its own lexeme. It cannot be combined with other characters to form more complex lexemes, except through the ``escape'' syntax described below.
A word is a contiguous sequence of (1) normal characters or (2) other characters preceded by the escape character \.
word ::= normal | word normal | word\character
Except for characters following \, the lexical analysis of words is case insensitive. The output lexeme for any word corresponds to the lexeme obtained by converting all letters not following \ to their upper case equivalents. For example, the word abc and the word ABC map into the same lexeme. The word a\bc maps into the same lexeme as the word A\bC, which is not the same as the lexeme for the word ABC.
A character reference consists of the characters #, \, and any character. Character references allow us to refer to characters as characters and differentiate them from one-character symbols, which may refer to other objects.
charref ::= #\characterA character string is a series of characters enclosed in quotation marks. The escape character \ is used to permit the inclusion of quotation marks and the \ character itself within such strings.
string ::= "quotable" quotable ::= empty | quotable strchar | quotable\character strchar ::= character - {",\}Sometimes it is desirable to group together a sequence of arbitrary bits or characters without imposing escape characters, e.g. to encode images, audio, or video in special formats. Character blocks permit this sort of grouping through the use of a prefix that specifies how many of the following characters are to grouped together in this way. A character block consists of the character # followed by the decimal encoding of a positive integer n, the character q or Q, and then n arbitrary characters.
block ::= # int(n) q character^n | # int(n) Q character^nFor the purpose of grammatical analysis, it is useful to subdivide the class of words a little further, viz. as variables, operators, and constants.
A variable is a word in which the first character is ? or @. A variable that begins with ? is called an individual variable. A variable that begins with an @ is called a sequence variable.
variable ::= indvar | seqvar indvar ::= ?word seqvar ::= @wordOperators are used in forming complex expressions of various sorts.
operator ::= unprovable | not | and | or | => | <=All other words are called constants.
constant ::= word - variable - operatorSemantically, there are four categories of constants in SIF -- object constants, function constants, relation constants, and logical constants. Object constants are used to denote individual objects. Function constants denote functions on those objects. Relation constants denote relations. Logical constants express conditions about the world and are either true or false. SIF is unusual among logical languages in that there is no syntactic distinction among these four types of constants; any constant can be used where any other constant can be used. The differences between these categories of constants is entirely semantic.
There are six types of terms in SIF -- individual variables, constants, character references, character strings, character blocks, and list expressions. Individual variables, constants, character references, strings, and blocks were discussed earlier.
term ::= indvar | constant | charref | string | block | listexprA list expression is either an atom or a sequence of list expressions surrounded by parentheses. An atom is either a word or a character reference or a character string or a character block.
listexpr ::= atom | (listexpr*) atom ::= word | charref | string | blockThe following BNF defines the set of legal sentences in SIF. There are three types of sentences. We have already mentioned logical constants.
sentence ::= constant | relsent | quantsent | logsentA relational sentence consists of a relation constant and an arbitrary number of argument terms, terminated by an optional sequence variable. As with functional terms, there is no syntactic restriction on the number of argument terms in a relation sentence -- the same relation constant can be applied to any finite number of arguments.
relsent ::= (constant term* [seqvar])
It is noteworthy that the syntax of relational sentences is the same as that of functional terms. On the other hand, their meanings are different. Fortunately, the context of each such expression determines its type (as an embedded term in one case or as a top-level sentence or argument to some sentential operator in the other case); and so this slight ambiguity causes no problems.
The syntax of quantified sentences takes the form shown below.
quantsent ::= (bagofall term sentence term)
The syntax of logical sentences depends on the logical operator involved. A sentence involving the not operator is called a negation. A sentence involving the and operator is called a conjunction, and the arguments are called conjuncts. A sentence involving the or operator is called a disjunction, and the arguments are called disjuncts.
logsent ::= (not sentence) | (and sentence*) | (or sentence*)
As with sentences, the syntax of a form depends on the logical operator involved. A form involving the => operator is called an implication; all of its arguments but the last are called antecedents; and the last argument is called the consequent. A sentence involving the <= operator is called a reverse implication; its first argument is called the consequent; and the remaining arguments are called the antecedents.
form ::= sentence | (=> sentence* sentence) | (<= sentence sentence*)
A knowledge base is a finite sequence of forms. It is defined as a sequence because the order of forms in a knowledge base may have affect the way the knowledge base is processed by interpreters.


Stack Overflow is a question and answer site for professional and enthusiast programmers.
Since launching in 2008, Stack Overflow has become the primary destination for support in the developer community. Along with the proliferation of the tech industry, there has been an increasing demand for developers, many of whom have chosen to fast-track their career path with online self-help in lieu of traditional computer science degrees. This is evident in Stack Overflow's Growth
Stack Overflow is a community of users who post questions and answers spanning various programming topics. Ultimately, both groups are vetted through a communal system of qualification: users accumulate reputation and posts are voted up or down. Hover over the below components to learn more:


Player banned for one year for age fraud in DR Congo
DR Congo Football Federation have banned striker Meschack Elia for twelve months falsifying his age in an attempt to join another club without the knowledge of his parent club.
Elia who has contract with giants TP Mazembe disappeared with no trace after having trials with Belgium top-flight side RSC Anderlecht in the summer.
An investigation conducted by the Congolese football authorities revealed Elia has been dealing with some crooked agents with the view of joining Young Boys FC in Switzerland.
The investigation also revealed that the striker changed his year of birth in a new passport from 1996 to 1997 to enable him to join the Swiss club without the knowledge and consent of TP Mazembe.
Elia has then been banned from football activities for the next one year.


networkx.algorithms.community.community_generators.LFR_benchmark_graph¶
-
LFR_benchmark_graph
(n, tau1, tau2, mu, average_degree=None, min_degree=None, max_degree=None, min_community=None, max_community=None, tol=1e-07, max_iters=500, seed=None)[source]¶ Returns the LFR benchmark graph for testing community-finding algorithms.
This algorithm proceeds as follows:
Find a degree sequence with a power law distribution, and minimum value
min_degree
, which has approximate average degreeaverage_degree
. This is accomplished by either- specifying
min_degree
and notaverage_degree
, - specifying
average_degree
and notmin_degree
, in which case a suitable minimum degree will be found.
max_degree
can also be specified, otherwise it will be set ton
. Each node u will havemu mathrm{deg}(u)
edges joining it to nodes in communities other than its own and(1 - mu) mathrm{deg}(u)
edges joining it to nodes in its own community.- specifying
Generate community sizes according to a power law distribution with exponent
tau2
. Ifmin_community
andmax_community
are not specified they will be selected to bemin_degree
andmax_degree
, respectively. Community sizes are generated until the sum of their sizes equalsn
.Each node will be randomly assigned a community with the condition that the community is large enough for the node’s intra-community degree,
(1 - mu) mathrm{deg}(u)
as described in step 2. If a community grows too large, a random node will be selected for reassignment to a new community, until all nodes have been assigned a community.Each node u then adds
(1 - mu) mathrm{deg}(u)
intra-community edges andmu mathrm{deg}(u)
inter-community edges.
Parameters: - n (int) – Number of nodes in the created graph.
- tau1 (float) – Power law exponent for the degree distribution of the created graph. This value must be strictly greater than one.
- tau2 (float) – Power law exponent for the community size distribution in the created graph. This value must be strictly greater than one.
- mu (float) – Fraction of intra-community edges incident to each node. This value must be in the interval [0, 1].
- average_degree (float) – Desired average degree of nodes in the created graph. This value
must be in the interval [0, n]. Exactly one of this and
min_degree
must be specified, otherwise aNetworkXError
is raised. - min_degree (int) – Minimum degree of nodes in the created graph. This value must be
in the interval [0, n]. Exactly one of this and
average_degree
must be specified, otherwise aNetworkXError
is raised. - max_degree (int) – Maximum degree of nodes in the created graph. If not specified,
this is set to
n
, the total number of nodes in the graph. - min_community (int) – Minimum size of communities in the graph. If not specified, this
is set to
min_degree
. - max_community (int) – Maximum size of communities in the graph. If not specified, this
is set to
n
, the total number of nodes in the graph. - tol (float) – Tolerance when comparing floats, specifically when comparing average degree values.
- max_iters (int) – Maximum number of iterations to try to create the community sizes, degree distribution, and community affiliations.
- seed (integer, random_state, or None (default)) – Indicator of random number generation state. See Randomness.
Returns: G – The LFR benchmark graph generated according to the specified parameters.
Each node in the graph has a node attribute
'community'
that stores the community (that is, the set of nodes) that includes it.Return type: NetworkX graph
Raises: NetworkXError
– If any of the parameters do not meet their upper and lower bounds:tau1
andtau2
must be strictly greater than 1.mu
must be in [0, 1].max_degree
must be in {1, …, n}.min_community
andmax_community
must be in {0, …, n}.
If not exactly one of
average_degree
andmin_degree
is specified.If
min_degree
is not specified and a suitablemin_degree
cannot be found.ExceededMaxIterations
– If a valid degree sequence cannot be created withinmax_iters
number of iterations.If a valid set of community sizes cannot be created within
max_iters
number of iterations.If a valid community assignment cannot be created within
10 * n * max_iters
number of iterations.
Examples
Basic usage:
>>> from networkx.algorithms.community import LFR_benchmark_graph >>> n = 250 >>> tau1 = 3 >>> tau2 = 1.5 >>> mu = 0.1 >>> G = LFR_benchmark_graph(n, tau1, tau2, mu, average_degree=5, ... min_community=20, seed=10)
Continuing the example above, you can get the communities from the node attributes of the graph:
>>> communities = {frozenset(G.nodes[v]['community']) for v in G}
Notes
This algorithm differs slightly from the original way it was presented in [1].
- Rather than connecting the graph via a configuration model then rewiring to match the intra-community and inter-community degrees, we do this wiring explicitly at the end, which should be equivalent.
- The code posted on the author’s website [2] calculates the random power law distributed variables and their average using continuous approximations, whereas we use the discrete distributions here as both degree and community size are discrete.
Though the authors describe the algorithm as quite robust, testing during development indicates that a somewhat narrower parameter set is likely to successfully produce a graph. Some suggestions have been provided in the event of exceptions.
References
[1] “Benchmark graphs for testing community detection algorithms”, Andrea Lancichinetti, Santo Fortunato, and Filippo Radicchi, Phys. Rev. E 78,<PHONE_NUMBER> [2] http://santo.fortunato.googlepages.com/inthepress2


The "quality" parameter may be set to one of the following values:-
Low - No smoothing is performed but the image is produced very quickly
Medium - Some smoothing is performed giving a reasonable appearance in a time only slightly slowly
than the low setting.
High - A higher level of smoothing is performed giving a very good quality result but the time taken
to produce the image is about double that of the low setting.
Very High - A very level of smoothing is performed to give the best possible result. The time taken
is around 4 times that of the low setting.
| Low |
Medium |
| |
|
| High |
Very High |
| |
|
One of the big factors which effect the time taken to perform the image smoothing is the size of each pie.
The larger the pie the more pixels there are to process and hence the more processing time is required.
| Is the Quality parameter supported on your installation of PHP
? |
|
The smoothing algorithm requires that PHP is running with a graphics environment of GD 2 or higher.
If your PHP environment is running with GD 1.x then the chart will automatically set the quality parameter
to low regardless of the specification in the property file.
For more information on the PHP GD environment click
here »
|


The link below provides access to the entire table of mapped activities. All mappings are ultimately integrated into the ChEMBL database - you can read about ways to query them here - but you might want to work with mappings that have only been assigned in the current round of curations. If that is the case you can download the pfam_maps table using the link provided below.
download expand table legend| Col name | explained |
|---|---|
| map_id | unique identifier for each row |
| activity_id | activity_id as in the ChEMBL activities table |
| compd_id | unique identifier of the domain as defined in the component_domains table in ChEMBL |
| domain_name | name of the Pfam-A domain |
| category_flag | Constellation in the protein: 0 - no conflict; 1 - ambiguous map; 2 - conflicting map |
| status_flag | Status of the domain: 0 - activity mapped to domain; 1 - activities not currently mapped to domain |
| manual_flag | 0 - activity uncurated; 1 -activity curated; |
| comment | Curation comment |
| timestamp | time of last curation |
| submitter | user who submitted last curation decision |


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Kalman filter (accel + gyro)


Chief Investigator Johnny:
Yeah, whatever dude. Everyone's got their limits, and clearly you don't have what it takes. Later.


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