Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security.The growing role of data and machine learning cuts across domains and industries. Companies continue to use data to improve decision-making (business intelligence and analytics) and for automation (machine learning and AI). At the Strata Data Conference in London, we’ve assembled a program that introduces technologies and techniques, showcases use cases across many industries, and highlights the importance of ethics, privacy, and security. We are bringing back the Strata Business Summit, and this year, we have two days of executive briefings. Data Science and Machine Learning sessions will cover tools, techniques, and case studies. This year, we have many sessions on managing and deploying models to production, and applications of deep learning in enterprise applications. This year’s sessions on Data Engineering and Architecture showcases streaming and real-time applications, along with the data platforms used at several leading companies. Privacy and security The enforcement date for the General Data Protection Regulation (GDPR) is the day after the end of the conference (May 25, 2018) and for the past few months, companies have been scrambling to learn this new set of regulations. We have a tutorial and sessions to help companies learn how to comply with GDPR. Implementing data security and privacy remain foundational, but one of the key changes advanced by GDPR—“privacy-by-design”—will require companies to reassess how they design and architect products. Security and Privacy sessions Visualization, Design, and UX sessions Unlocking popular data types: Text, temporal data, and graphs The need for scaleout and streaming infrastructure can often be traced back to the importance of text, temporal data, and graphs. After one sets up infrastructure for collecting, storing, and querying these data types, the next step is to uncover interesting patterns or to use them to make predictions. Over the past year, companies have been turning to machine learning, in many cases to deep learning, when faced with large amounts of text, graphs, or temporal data. On the infrastructure side, we have sessions from members of some of the leading stream processing and storage communities. Text and Natural Language sessions Time-series and Graphs sessions Stream Processing and Real-time Applications sessions Data platforms How do some of the best companies architect and develop data platforms that help accelerate innovation and digital transformation? In a series of sessions, companies will share their internal platforms for business intelligence and machine learning. These are battle-tested platforms used in production, some at extremely large scale. Many of these data platforms encourage collaboration and sharing of data, features, and models. In addition, since we’re very much in an empirical era for machine learning, tools for running and reproducing experiments, and for exploring the space of algorithms, are essential. Security and privacy become even more critical in light of the upcoming enforcement date for GDPR. Data Platforms sessions Machine learning: From data preparation and integration, to model deployment and management Media articles on machine learning over emphasize algorithms and models. The reality is that model building is just one aspect of building products that rely on machine learning. In a vast majority of cases, machine learning applications require training data (“labeled data is the new, new oil”). To that end, the first step is to bring together existing data sources and when appropriate, enrich them with other data sets. In most cases, data needs to be refined and prepared before it’s ready for analytic applications. While prototypes are easy to cook up, building production-grade applications requires serious engineering. Companies have come to realize that deploying, monitoring, and managing models in production requires different skills and a different mindset. So much so that a new breed of workers, machine learning engineers, was recently forecasted to be the fastest growing, emerging job in 2018. Managing and Deploying Machine Learning sessions Data Integration and Data Pipelines sessions Industry- and domain-specific tools, methods, and use cases The best way to understand the potential of data technologies and machine learning is to see how companies are using them in real-world applications. One of the great things about Strata Data London is that one gets to hear case studies from many different industries and countries. You will learn how a variety of companies from across the globe have designed their data infrastructures; how they are incorporating machine learning; and how they’re approaching data privacy, security, and ethics. This year, we have keynotes and sessions on important topics in public policy, health care, manufacturing, and many other sectors of the economy. Here are some examples: Data Case Studies (12 presentations) Findata Day and Financial Services sessions Media and Advertising sessions E-commerce, and Transportation and Logistics sessions Telecom sessions The Strata Data Conference is happening in London from May 21-24, 2018—best price ends April 6. Continue reading How companies around the world apply machine learning.


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--- layout: post title: MUA Nail Varnish - Bright Coral, Amaretto Crush, Pistachio Icecream Swatches tags: - Make Up Academy(MUA) status: publish type: post published: true meta: _edit_last: '2' _aioseop_title: MUA Nail Varnish - Bright Coral, Amaretto Crush, Pistachio Icecream Swatches _aioseop_keywords: MUA Nail Varnish - Bright Coral, Amaretto Crush, Pistachio Icecream Swatches _yoast_wpseo_linkdex: '0' _thumbnail_id: '5201' _yoast_wpseo_focuskw: '' _yoast_wpseo_title: '' _yoast_wpseo_metadesc: '' _yoast_wpseo_metakeywords: '' _yoast_wpseo_meta-robots-noindex: '0' _yoast_wpseo_meta-robots-nofollow: '0' _yoast_wpseo_meta-robots-adv: none _yoast_wpseo_sitemap-include: ! '-' _yoast_wpseo_sitemap-prio: ! '-' _yoast_wpseo_canonical: '' _yoast_wpseo_redirect: '' --- Its been a busy weekend, spent few hours at office and then my besties spending this weekend with me...I had a gala time.. painted their nails last evening and they loved it. We all got our hair cut... from none other than Sudeep Grover.. its been a really lovely and lucky week. In recent MUA Haul, I picked up three shades from their Nail Varnish Collection. These are richly pigmented, fast drying varnish. But the Brush is a problem, it gives a very streaky finish.. and I keep on layering the color like 3-4 times to get a smooth coat. Price: £1 available online on http://www.muastore.co.uk/
MUA Nail Varnish-Bright Coral
MUA Nail Varnish-Pistachio Icecream
MUA Nail Varnish-Amaretto Crush
No doubt these awesome really trendy colors, dry up really fast. I would definitely pick up shades not available here. Wont say these are must picks, but for fun you can pick up some really nice shades for just £1 These are my BFF's and a very important part of my life.... Love you guys :-* Did you like the shades ? How was your weekend ?


Sabah MACC says yet to receive report on pygmy elephant killings
KOTA KINABALU, Nov 22 — The Malaysian Anti-Corruption Commission (MACC) has yet to receive a report on any corruption case involving several Pygmy elephant killings in the state.
Sabah MACC director Karunanithy Y. Subbiah said if a report was received, it would conduct an investigation to see if there were any elements of corruption in the case.
“If a report is received, we will also look at the form of the report. If the report contains elements of corruption, we will investigate immediately as it has to do with the scope of MACC duties.
“But what we do know is that this is a criminal case,” he said when contacted by Bernama here today.
Four incidents of elephant carcasses were found in the east of the state from September to this month.
The first case was on September 25 when a group of anglers found a dead body of a pygmy elephant with 70 gunshot wounds on its body in Sungai Udin, Dumpas, Kalabakan, Tawau.
This was followed on October 19, when another pygmy elephant was found shot dead in an oil palm plantation in Beluran and investigations revealed five wounds on the elephant with its tusks missing.
On November 3, the dead body of a Borneo pygmy elephant was found floating in Sungai Kinabatangan River and an autopsy revealed that both of the elephant’s hind legs had been cut off with a sharp object.
On November 16, another elephant was found dead in Kampung Sukau Kinabatangan, believed to be caused by toxaemia poisoning, causing the elephant’s internal organs to fail. — Bernama


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Attention: TESTED only on 5.4.x. Please give me info if it works correctly on 5.0 too.
Template to monitor Synology Hyperbackup status.
Create a zabbix user in your DSM. The user should be in the administrator group as it must be able to ssh to the DSM. You can disable access to all folders and to all programs/functions. Login on DSM with administrative/root account and create /etc/sudoers.d/zabbix with this inside: zabbix ALL = NOPASSWD: /bin/more /var/log/messages, /bin/grep This tells the system that the user zabbix can run as root only this 2 commands without the root password.
Assign the template to the synology. Pay attention to: the template uses the Dns name of the synology to do the discovery and other stuff.
In the assigned machine you must define two macros: {$SSH_USERNAME} {$SSH_PASSWORD}
with this template you can monitor the status of the Hyperbackup on your synology with zabbix.
The template comes with a discovery rule to get all configured backup on the NAS.
Tested on Zabbix version 5.4.1
You can write questions also to<EMAIL_ADDRESS>Gianluca Romito
{$SSH_USERNAME} {$SSH_PASSWORD}
None
Attention: TESTED only on 5.4.x. Please give me info if it works correctly on 5.0 too.
Template to monitor Synology Hyperbackup status.
Create a zabbix user in your DSM. The user should be in the administrator group as it must be able to ssh to the DSM. You can disable access to all folders and to all programs/functions. Login on DSM with administrative/root account and create /etc/sudoers.d/zabbix with this inside: zabbix ALL = NOPASSWD: /bin/more /var/log/messages, /bin/grep This tells the system that the user zabbix can run as root only this 2 commands without the root password.
Assign the template to the synology. Pay attention to: the template uses the Dns name of the synology to do the discovery and other stuff.
In the assigned machine you must define two macros: {$SSH_USERNAME} {$SSH_PASSWORD}
with this template you can monitor the status of the Hyperbackup on your synology with zabbix.
The template comes with a discovery rule to get all configured backup on the NAS.
Tested on Zabbix version 5.4.1
You can write questions also to<EMAIL_ADDRESS>Gianluca Romito
{$SSH_USERNAME} {$SSH_PASSWORD}
None


Colubrina (Colubrina hondurensis)
| Kingdom | Plantae |
|---|---|
| Phylum | Tracheophyta |
| Class | Magnoliopsida |
| Order | Rhamnales |
| Family | Rhamnaceae |
| Genus | Colubrina (1) |
Colubrina hondurensis is classified as Critically Endangered (CR) on the IUCN Red List (1).
Information on Colubrina hondurensis is being researched and written and will appear here shortly.
This information is awaiting authentication by a species expert, and will be updated as soon as possible. If you are able to help please contact:
<EMAIL_ADDRESS>-
IUCN Red List (January, 2012)
http://www.iucnredlist.org


{% set current_page='Media' %} {% extends 'base.html' %} {% block body %}
All video and audio that teacher provided are collected here.
{{ row.name}}
If there is no material you need, please contact your teacher.


ReHabit is the platform for tracing your habits which you want to change.And also connect with people around.
Login to your account to Track bad habits and get notified to Unhabit yourself.


WITNESS LIST Education Reform & Public School Finance, Sel Committee February 6, 2006 -10:00A Governor's Educator Excellence Award Program ON: Gelinas, Robin Program Manager (TEA Education Initiatives), Austin, TX Martin, Christi Senior Advisor for Education Initiatives (Texas Education Agency), Austin, TX Panel 1: Efficiency ON: Anderson, David General Counsel (Texas Education Agency), Austin, TX Cloudt, Criss Associate Commissioner, Accountability & Data Quality (Texas Education Agency), Austin, TX Dougherty, Ph.D., Chrys Director of Research (National Center for Educational Accountability), Austin, TX Kress, Sandy (Self), Austin, TX Riley, Jay Director (Deloitte Consulting), Austin, TX Panel 2: Post-Secondary Success ON: Friou, Eileen AVID District Director (Richardson Independent School District), Dallas, TX Hayes, Patricia V. Associate Commissioner-Educator Quality & P16 Initiatives (Texas Education Agency), Austin, TX Israel, Cary A. President- Collin County Community College District (Collin County CCD), Plano, TX Pennell, Karen L. Assistant Vice President and Southwest Regional Manager (ACT, Inc.), Austin, TX Wright, B. Ann Vice President, Southwest (College Board), Austin, TX Panel 3: High School Reform ON: Boyd, Charles B. Director-Secondary School Leadership (Fort Worth Independent School District), Fort Worth, TX Ewing, Kent Director, Blue Print High Schools, High School Redesign (Austin I.S.D.), Austin, TX Fitzpatrick, John Executive Director (Texas High School Project), Dallas, TX Hernandez, Dr. Rosalinda Associate Supt. for High Schools (Austin ISD), Austin, TX Martin, Christi Senior Advisor for Education Initiatives (Texas Education Agency), Austin, TX McClellan, Anne Founding Principal (HISD), Houston, TX Public Testimony ON: Eaton, Holly Director of Professional Development & Advocacy (Tx Classroom Teachers Association), Austin, TX Resource Witnesses Registering, but not testifying: On: Barron, Dr. Glenda Associate Commissioner for Participation & Success (Tx Higher Education Coordinating Board), Austin, TX Gardner, Dr. David Associate Commissioner for Academic Excellence & Research (Tx Higher Education Coordinating Board), Austin, TX


C# is most popular among bigger established businesses, often for building internal software.
Java has been very popular for a very long time and is used in so many applications, it is also a very high-demand language.
Great for building mobile applications.
Ruby is a favorite language of developers building interactive web applications.
Making things beautiful and more appealing is designing.


The goal of {fivestars} is to generate star ratings with HTML and CSS.
Install the development version from GitHub with:
install.packages("fivestars", repos = "https://tanho63.r-universe.dev")
# or use remotes/devtools
# install.packages("remotes")
remotes::install_github("tanho63/fivestars")
use_fivestars()
adds the appropriate CSS and allows for some configuration of defaults (star size, colour, and background).
use_fivestars(
star_size = "20px", # default is "larger"
star_color = "#fc0", # default
star_background = "#999" # default
)
Minimal usage of the fivestar
function looks like this:
fivestars(rating = 3.5)
3.5
The output can be further customized with some arguments, e.g.
fivestars(rating = 1.2,
label = "Poor",
label_pos = "right",
aria_label = "This item is rated 'Poor'",
star_color = "#d13",
star_background = "#000")
Poor


Monopoly 1 - Click to transform
source
Monopoly 2 - Simple 1
source
Monopoly 3 - Simple 2
source
Monopoly 4 - Simple 3
source
Monopoly 5 - Detailed 1
source
Monopoly 6 - Flex Grid
source
Monopoly 7 - Detailed 2
source
Monopoly 8 - Transform 2
source
Monopoly 9 - Transform 3
source
Other 1 - Property Cards 1
source
Other 2 - Choose your character
source
Other 3 - Property Cards 2
source
Other 4 -
source
Other 5 -
source
Other 6 -
source


GPU-accelerated model checking
Bringing GPU acceleration to statistical model checking.
PRISM is a state-of-the-art and well-known probabilistic model checker. The core idea of model checking is to describe a complex system with an abstract mathematical model, define its properties in a formal logic language, and verify the properties automatically. PRISM uses probabilistic models such as discrete-time and continuous-time Markov chains (DTMC, CTMC), Markov decision process (MDP), and probabilistic timed automata (PTA).
The classical approach of PMC is to use the linear algebra methods, such as represent the model and properties as a system of linear equations and solve them in an iterative fashion. While this method has been applied successfully in many cases, it does suffer from the well-known problem of state space explosion. Furthermore, a wrong selection of termination conditions might lead to incorrect results, as we will show later.
Another approach is to analyze the properties statistically: use the Monte Carlo method to generate many random walks through the model and average the results of property verification. It’s not a perfect method, the number of samples limits its precision, and it cannot easily verify some qualitative properties. Nevertheless, a model checker will benefit from a fast and easy-to-use statistical simulator.
The example presented above is a DTMC model written in the PRISM language (see PRISM website for full discussion).
It simulates throwing a 6-side dice by using only coin throw with 50% probability.
In the end, reaching each value of d
has exactly one chance in 6.
The state of the model is a composition of all variables, and the commands describe transitions.
Each transition includes a guard specifying when this transition can be taken, followed by the
multiple possible transition results with corresponding probability rates.
Finally, the transitions can be synchronized, and PRISM models can include multiple modules that are executed in parallel. If we have many models with a huge number of possible states in each of them, we will end up with the state space explosion problem - there are too many states to handle when computing a solution.
Clearly, this model is not very difficult to simulate - we need to encode transition guards as
if
conditions, compute the probability distribution of all available transitions, and randomize
the selection while verifying properties in each step.
Unfortunately, PRISM includes only a limited simulator that is quite sequential and implemented
entirely in Java, reinterpreting the model above in every transition.
The simulator is sufficient for debugging purposes, but it’s not fast enough for statistical computations.
We created prism-faststim, an OpenCL-based fast and heterogeneous simulator for PRISM. We created a high-level Java library for the generation of OpenCL kernels, and we used it to build a just-in-time source-to-source translation of the PRISM model and properties to a dedicated compute kernel. The kernel is a program executing the model on many GPU and CPU threads, using the single-instruction-multiple-data paradigm. The implementation had to be specially adapted for GPU devices, leading to low-level optimizations. For example, when simulating independent paths, they will diverge at some point which is not ideal on a GPU device with limited ability to handle diverging control flow. We compress variables sizes as much as possible to save the register and local memory space. We want to perform synchronized transitions in a single step to keep for performance reasons, but this might require multiple copies of the state vector because of Read-After-Write race conditions. To keep the high efficiency and decrease memory consumption, we use a single copy of the vector and analyze transitions to detect variables affected by a race condition and make copies of only those memory locations.
The simulation algorithm presents a single OpenCL thread executing a single path through the model. The second loop (lines 8-27) generates the path until any of the following happens: its maximum length is reached (line 8), a deadlock (line 14) or a self-loop (line 18) occurs, or all properties are verified precisely enough (line 24). The last loop (lines 29–31) copies the collected data into the global memory, which will be collected later by the host simulator.
We demonstrated the usability of our tool on an example of computing an instantaneous reward in a CTMC. PRISM performs discretization and performs an iterative process to approximate the probabilities. When executing that operation, Prism also tests if a steady state has been reached by checking the difference between elements in solution vectors from two successive steps. If the difference is smaller than a constant threshold, the process is terminated early as such a state has been reached. However, in some models, detecting a steady state is premature if the default termination criterion is used. This can lead to incorrect results (plot above, on the left). Therefore, the fast statistical model checking is used to verify with a high degree of certainty if the analytical result is correct, helping users discover incorrect results.
Furthermore, we compared the performance of our simulator on an AMD R9 Nano, a modern mid-range GPU with 4096 stream processors, and on two Intel Xeon E5-2630 v3 CPUs with clock frequency 2.40GHz, each of them providing eight cores with HyperThreading, resulting in 32 threads for OpenCL. The results (plot above, right) show that two CPUs are several times slower than a GPU. This shows the advantage of streams processors in the case of a large number of parallel tasks.
The results from the PRISM simulator are not shown on the plot, as it is not optimized for speed.
At t = 2000
, where long paths make it especially advantageous to use the on-the-fly compilation,
it took the PRISM simulator over 130 minutes to evaluate the same reward property on the same CPU,
thousands of times slower comparing a respective simulation on a GPU.
This work is a result of my Bachelor’s thesis conducted at the Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, under the supervision of Dr. Artur Rataj, Dr. Mateusz Nowak, and Prof. Tadeusz Czachórski. We presented the paper at the 25th International Workshop on Concurrency, Specification and Programming.


FOUR ROOMS A film review by Ted Prigge Copyright 1997 Ted Prigge
When respecting a director, you must also respect the fact that they are not perfect. Woody Allen has made a couple less-than good films, and he's my favorite. Even Martin Scorsese hasn't had a perfect track record. Kevin Smith, after a smashing debut with the classic "Clerks" stooped as low to sell-out and make the dreadful "Mallrats." I mean, so far the only director who's made several films, none of which have been bad is Richard Linklater ("Slacker," "Dazed and Confused," "Before Sunrise," and "SubUrbia"...all which were great).
Now, I ADORE Quentin Tarantino. His first two films were classic films, the second one being one of the greatest films of all time. But 1995 just wasn't that good of a year for him. He made way too many TV appearances. He mispronounced Jackie Chan's name on the MTV Movie Awards. And he made this film. (He was also awarded an Oscar, so I guess that would be a grand exception). Robert Rodriguez is also a great director; not a brilliant one, but a cool one. I've never seen an Alexandre Rockwell or Allison Anders film, so I can't comment on them.  Pitiful for any director, too.
Now in all fairness, ensemble director pieces never really work out. I've never seen all of "New York Stories," but have heard the first two films, by Scorsese and Francis Ford Coppola are crap (I saw Woody's one, which was hilarious but not totally up to par). But I will rate each film individually and then report back to you on the overal average score of the film.
EXPOSITION: A simple one - a bellhop, Ted (the totally overdone Tim Roth, who's a god and all, but not in this one, though he has a couple good moments) is working on New Year's Eve for his first shift (!!!) in an old fancy hotel. He's the only one there (again: !!!) and he only has a couple rooms (yet again: !!!). The old bellhop (the seemingly immortal Marc Lawrence - who hated Pulp Fiction actually) hands over his cap to Ted and he goes to his job happily. As the night goes on, he becomes increasingly annoyed and hostile. Yea.
 The situation is so terrible that it's physically painful to watch. The plot has something to do with a coven of witches needing sperm to bring back a godess who is (GASP!) stuck inside some object in their hotel room. The witch that was supposed to bring it (Ione Skye) calls up Ted and asks him if she can perform Fellatio on him to get it. Yeah, that's what I said. Stupid plot, inane characters who aren't interesting at all, etc, etc, etc. The only good thing about this is it has a good cast which, in turn, it wastes pitifully. Not even actually funny for a second.
MY RATING (out of 5): NO STARS!!!!
 Ted stumbles into the wrong room or something and gets in the middle of a couple (David Proval and Jennifer Beals in her attempt at "coming back") who are playing sex games. Ted tries to escape and we cheer him on so it will end soon. But at least this has a bit of comedy in it, just not that much. And David Proval has never overacted as much. And it's "Pulp Fiction" producer Laurence Bender who gets to puke from a window. A masterpiece compared to the first one, but still...
MY RATING (out of 5): 1/2
THE MISBEHAVERS Writer/Director: Robert Rodriguez Starring: Antonio Banderes, Tamlyn Tomita, Lana McKissack, Danny Verduzco, Salma Hayek
Would a Robert Rodriguez film be the same without Salma Hayek's navel? Nope. Luckily she's on the TV dancing so we get to see her. Surprisingly enough, when I read the screenplay (about a year before actually seeing it), this one seemed to have the most potential. It was fast-paced, funny, and well, funny. But when I watched it, it seemed anti-climactic and only seemed to gain any momentum towards the end when everything happened at once. Antonio overacts nicely and the two kids (Lana and Danny) are funny. But, as I said, it moves slowly and in that way, it's more painful than funny.  Oh! The plot: Antonio is a supposed gangster (assumed, really) who leaves his two troubling kids home while he and his wife (Tomita) go out to get drunk at a New Year's Party. Antonio hires Ted for a couple bucks to watch his kids all night long, but things go wrong...it was okay.
MY RATING (out of 5): **
THE MAN FROM HOLLYWOOD Writer/Director: Quentin Tarantino Starring: Quentin Tarantino, Bruce Willis, Paul Calderon and Jennifer Beals (again)
Ironically, this one could be considered the best for a bad reason: it best represents what Quentin has done with this film. He plays Chester, a spoiled brat actor or something who has just had a huge box-office hit on his hands and is living it up by playing an anti-climactic game from a Hitchcock TV episode starring Steve McQueen and Peter Lorre where they gamble to see if one of them can get light from his lighter ten times in a row. They're drunk and need sober but nervous Ted to hold the cleaver and bring it down if the lighter doesn't light. They also pay him a lot of cash. This is so much exactly what this little film is about that it's campy.  It took Quentin to realize that. But the thing is, it doesn't seem like he realizes that. If he did, I'd give this a good 3 stars. But this sucked. It was anti-climactic and the dialogue wasn't very good. He starts off with a very long steadicam shot then goes to flashes. That makes no sense. It's cool for a while, then he makes it uneven. It's long and it's just not very good. Hopefully Quentin never repeats what he did with this one.
MY RATING (out of 5): *1/2
CONCLUSION: What's the moral here? If you've made celebrated films, don't do an ensemble piece. They should have re-watched "New York Stories" and then stopped in their tracks.  But I will forgive everyone involved and I especially look forward to Quentin's next directing job (even though he and Rodriguez jumped back to the top immeadiately with the cool "From Dusk Till Dawn," which I found exhilerating). I love Quentin and I suppose it's good he made "The Man from Hollywood" because it makes him seem more realistic and not some "God of Cinema." I seem to respect directors if they aren't "Gods" and are actually human beings who make mistakes. "The Man from Hollywood" is his big mistake and let's hope he doesn't return her continuously.
OVERALL AVERAGE RATING (out of 5): *
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


|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object java.awt.image.ColorModel java.awt.image.ComponentColorModel edu.cmu.cs.stage3.image.codec.FloatDoubleColorModel
public class FloatDoubleColorModel
A ColorModel
class that works with pixel values that
represent color and alpha information as separate samples, using
float or double elements. This class can be used with an arbitrary
ColorSpace
. The number of color samples in the pixel
values must be same as the number of color components in the
ColorSpace
. There may be a single alpha sample.
Sample values are taken as ranging from 0.0 to 1.0; that is, when converting to 8-bit RGB, a multiplication by 255 is performed and values outside of the range 0-255 are clamped at the closest endpoint.
For maximum efficiency, pixel data being interpreted by this class should be in the sRGB color space. This will result in only the trivial conversion (scaling by 255 and dividing by any premultiplied alpha) to be performed. Other color spaces require more general conversions.
For those methods that use a primitive array pixel
representation of type transferType
, the array length
is the same as the number of color and alpha samples. Color
samples are stored first in the array followed by the alpha sample,
if present. The order of the color samples is specified by the
ColorSpace
. Typically, this order reflects the name
of the color space type. For example, for TYPE_RGB
,
index 0 corresponds to red, index 1 to green, and index 2 to blue.
The transfer types supported are
DataBuffer.TYPE_FLOAT
,
DataBuffer.TYPE_DOUBLE
.
The translation from pixel values to color/alpha components for display or processing purposes is a one-to-one correspondence of samples to components.
Methods that use a single int pixel representation throw an
IllegalArgumentException
.
A FloatDoubleColorModel
can be used in
conjunction with a ComponentSampleModelJAI
.
ColorModel
,
ColorSpace
,
ComponentSampleModel
,
ComponentSampleModelJAI
| Field Summary |
|---|
| Fields inherited from interface java.awt.Transparency |
|---|
BITMASK, OPAQUE, TRANSLUCENT |
| Constructor Summary | |
|---|---|
FloatDoubleColorModel(java.awt.color.ColorSpace colorSpace,
boolean hasAlpha,
boolean isAlphaPremultiplied,
int transparency,
int transferType)
Constructs a ComponentColorModel from the
specified parameters. |
| Method Summary | |
|---|---|
java.awt.image.ColorModel |
coerceData(java.awt.image.WritableRaster raster,
boolean isAlphaPremultiplied)
Forces the raster data to match the state specified in the isAlphaPremultiplied variable, assuming the data
is currently correctly described by this ColorModel . |
java.awt.image.SampleModel |
createCompatibleSampleModel(int w,
int h)
Creates a SampleModel with the specified width and
height that has a data layout compatible with this
ColorModel . |
java.awt.image.WritableRaster |
createCompatibleWritableRaster(int w,
int h)
Creates a WritableRaster with the specified width
and height, that has a data layout (SampleModel )
compatible with this ColorModel . |
int |
getAlpha(int pixel)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int |
getAlpha(java.lang.Object inData)
Returns the alpha component for the specified pixel, scaled from 0 to 255. |
int |
getBlue(int pixel)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int |
getBlue(java.lang.Object inData)
Returns the blue color component for the specified pixel, scaled from 0 to 255 in the default RGB ColorSpace, sRGB. |
int[] |
getComponents(int pixel,
int[] components,
int offset)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int[] |
getComponents(java.lang.Object pixel,
int[] components,
int offset)
Throws an IllegalArgumentException since
the pixel values cannot be placed into an int array. |
int |
getDataElement(int[] components,
int offset)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
java.lang.Object |
getDataElements(int[] components,
int offset,
java.lang.Object obj)
Returns a data element array representation of a pixel in this ColorModel , given an array of unnormalized
color/alpha components. |
java.lang.Object |
getDataElements(int rgb,
java.lang.Object pixel)
Returns a data element array representation of a pixel in this ColorModel , given an integer pixel representation
in the default RGB color model. |
int |
getGreen(int pixel)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int |
getGreen(java.lang.Object inData)
Returns the green color component for the specified pixel, scaled from 0 to 255 in the default RGB ColorSpace, sRGB. |
int |
getRed(int pixel)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int |
getRed(java.lang.Object inData)
Returns the red color component for the specified pixel, scaled from 0 to 255 in the default RGB ColorSpace, sRGB. |
int |
getRGB(int pixel)
Throws an IllegalArgumentException , since pixel
values for this ColorModel are not conveniently
representable as a single int . |
int |
getRGB(java.lang.Object inData)
Returns the color/alpha components for the specified pixel in the default RGB color model format. |
boolean |
isCompatibleRaster(java.awt.image.Raster raster)
Returns true if the supplied Raster 's
SampleModel is compatible with this
FloatDoubleColorModel . |
boolean |
isCompatibleSampleModel(java.awt.image.SampleModel sm)
Checks whether or not the specified SampleModel is
compatible with this ColorModel . |
java.lang.String |
toString()
Returns a String containing the values of all valid fields. |
| Methods inherited from class java.awt.image.ComponentColorModel |
|---|
equals, getAlphaRaster, getDataElement, getDataElements, getNormalizedComponents, getNormalizedComponents, getUnnormalizedComponents |
| Methods inherited from class java.awt.image.ColorModel |
|---|
finalize, getColorSpace, getComponentSize, getComponentSize, getNumColorComponents, getNumComponents, getPixelSize, getRGBdefault, getTransferType, getTransparency, hasAlpha, hashCode, isAlphaPremultiplied |
| Methods inherited from class java.lang.Object |
|---|
getClass, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public FloatDoubleColorModel(java.awt.color.ColorSpace colorSpace, boolean hasAlpha, boolean isAlphaPremultiplied, int transparency, int transferType)
ComponentColorModel
from the
specified parameters. Color components will be in the specified
ColorSpace
. hasAlpha
indicates
whether alpha information is present. If hasAlpha
is true, then the boolean isAlphaPremultiplied
specifies how to interpret color and alpha samples in pixel
values. If the boolean is true
, color samples are
assumed to have been multiplied by the alpha sample. The
transparency
specifies what alpha values can be
represented by this color model. The transferType
is the type of primitive array used to represent pixel values.
colorSpace
- The ColorSpace
associated with
this color model.hasAlpha
- If true, this color model supports alpha.isAlphaPremultiplied
- If true, alpha is premultiplied.transparency
- Specifies what alpha values can be represented
by this color model.transferType
- Specifies the type of primitive array used to
represent pixel values, one of
DataBuffer.TYPE_FLOAT or TYPE_DOUBLE.
java.lang.IllegalArgumentException
- If the transfer type is not
DataBuffer.TYPE_FLOAT or TYPE_DOUBLE.ColorSpace
,
Transparency
| Method Detail |
|---|
public int getRed(int pixel)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getRed
in class java.awt.image.ComponentColorModel
public int getGreen(int pixel)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getGreen
in class java.awt.image.ComponentColorModel
public int getBlue(int pixel)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getBlue
in class java.awt.image.ComponentColorModel
public int getAlpha(int pixel)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getAlpha
in class java.awt.image.ComponentColorModel
public int getRGB(int pixel)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getRGB
in class java.awt.image.ComponentColorModel
public int getRed(java.lang.Object inData)
pixel
value
is specified by an array of data elements of type
transferType
passed in as an object reference. The
returned value will be a non pre-multiplied value. If the alpha
is premultiplied, this method divides it out before returning
the value (if the alpha value is 0, the red value will be 0).
getRed
in class java.awt.image.ComponentColorModel
inData
- The pixel from which you want to get the red
color component, specified by an array of data elements of type
transferType
.
java.lang.ClassCastException
- If inData
is not a
primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- if inData
is not large enough to hold a pixel value for this
ColorModel
.public int getGreen(java.lang.Object inData)
pixel
value
is specified by an array of data elements of type
transferType
passed in as an object reference. The
returned value will be a non pre-multiplied value. If the alpha
is premultiplied, this method divides it out before returning
the value (if the alpha value is 0, the green value will be 0).
getGreen
in class java.awt.image.ComponentColorModel
inData
- The pixel from which you want to get the green
color component, specified by an array of data elements of type
transferType
.
java.lang.ClassCastException
- If inData
is not a
primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- if inData
is not large enough to hold a pixel value for this
ColorModel
.public int getBlue(java.lang.Object inData)
pixel
value
is specified by an array of data elements of type
transferType
passed in as an object reference. The
returned value will be a non pre-multiplied value. If the alpha
is premultiplied, this method divides it out before returning
the value (if the alpha value is 0, the blue value will be 0).
getBlue
in class java.awt.image.ComponentColorModel
inData
- The pixel from which you want to get the blue
color component, specified by an array of data elements of type
transferType
.
java.lang.ClassCastException
- If inData
is not a
primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- if inData
is not large enough to hold a pixel value for this
ColorModel
.public int getAlpha(java.lang.Object inData)
transferType
passed in as an
object reference. If the ColorModel
does not have
alpha, 255 is returned.
getAlpha
in class java.awt.image.ComponentColorModel
inData
- The pixel from which you want to get the alpha
component, specified by an array of data elements of type
transferType
.
java.lang.NullPointerException
- if inData
is
null
and the colorModel
has alpha.
java.lang.ClassCastException
- If inData
is not a
primitive array of type transferType
and the
ColorModel
has alpha.
java.lang.ArrayIndexOutOfBoundsException
- if inData
is not large enough to hold a pixel value for this
ColorModel
and the ColorModel
has
alpha.public int getRGB(java.lang.Object inData)
transferType
passed in as an
object reference. The returned value is in a non
pre-multiplied format. If the alpha is premultiplied, this
method divides it out of the color components (if the alpha
value is 0, the color values will be 0).
getRGB
in class java.awt.image.ComponentColorModel
inData
- The pixel from which you want to get the
color/alpha components, specified by an array of data elements
of type transferType
.
java.lang.ClassCastException
- If inData
is not a
primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- if inData
is not large enough to hold a pixel value for this
ColorModel
.public java.lang.Object getDataElements(int rgb, java.lang.Object pixel)
ColorModel
, given an integer pixel representation
in the default RGB color model. This array can then be passed
to the setDataElements
method of a
WritableRaster
object. If the pixel
parameter is null, a new array is allocated.
getDataElements
in class java.awt.image.ComponentColorModel
rgb
- An ARGB value packed into an int.pixel
- The float or double array representation of the pixel.
java.lang.ClassCastException
- If pixel
is not null and
is not a primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- If pixel
is
not large enough to hold a pixel value for this
ColorModel
.public int[] getComponents(int pixel, int[] components, int offset)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getComponents
in class java.awt.image.ComponentColorModel
public int[] getComponents(java.lang.Object pixel, int[] components, int offset)
IllegalArgumentException
since
the pixel values cannot be placed into an int
array.
getComponents
in class java.awt.image.ComponentColorModel
public int getDataElement(int[] components, int offset)
IllegalArgumentException
, since pixel
values for this ColorModel
are not conveniently
representable as a single int
.
getDataElement
in class java.awt.image.ComponentColorModel
public java.lang.Object getDataElements(int[] components, int offset, java.lang.Object obj)
ColorModel
, given an array of unnormalized
color/alpha components. This array can then be passed to the
setDataElements
method of a
WritableRaster
object.
getDataElements
in class java.awt.image.ComponentColorModel
components
- An array of unnormalized color/alpha
components.offset
- The integer offset into the
components
array.obj
- The object in which to store the data element array
representation of the pixel. If obj
variable is
null, a new array is allocated. If obj
is not
null, it must be a primitive array of type
transferType
. An
ArrayIndexOutOfBoundsException
is thrown if
obj
is not large enough to hold a pixel value for
this ColorModel
.
ColorModel
.
java.lang.IllegalArgumentException
- If the components array
is not large enough to hold all the color and alpha components
(starting at offset).
java.lang.ClassCastException
- If obj
is not null and
is not a primitive array of type transferType
.
java.lang.ArrayIndexOutOfBoundsException
- If obj
is
not large enough to hold a pixel value for this
ColorModel
.public java.awt.image.ColorModel coerceData(java.awt.image.WritableRaster raster, boolean isAlphaPremultiplied)
isAlphaPremultiplied
variable, assuming the data
is currently correctly described by this ColorModel
.
It may multiply or divide the color raster data by alpha, or
do nothing if the data is in the correct state. If the data needs
to be coerced, this method also returns an instance of
FloatDoubleColorModel
with
the isAlphaPremultiplied
flag set appropriately.
coerceData
in class java.awt.image.ComponentColorModel
java.lang.IllegalArgumentException
- if transfer type of
raster
is not the same as that of this
FloatDoubleColorModel
.public boolean isCompatibleRaster(java.awt.image.Raster raster)
true
if the supplied Raster
's
SampleModel
is compatible with this
FloatDoubleColorModel
.
isCompatibleRaster
in class java.awt.image.ComponentColorModel
raster
- a Raster
to be checked for compatibility.public java.awt.image.WritableRaster createCompatibleWritableRaster(int w, int h)
WritableRaster
with the specified width
and height, that has a data layout (SampleModel
)
compatible with this ColorModel
. The returned
WritableRaster
's SampleModel
will be
an instance of ComponentSampleModel
.
createCompatibleWritableRaster
in class java.awt.image.ComponentColorModel
w
- The width of the WritableRaster
you want
to create.h
- The height of the WritableRaster
you want
to create.
WritableRaster
that is compatible with
this ColorModel
.WritableRaster
,
SampleModel
public java.awt.image.SampleModel createCompatibleSampleModel(int w, int h)
SampleModel
with the specified width and
height that has a data layout compatible with this
ColorModel
. The returned SampleModel
will be an instance of ComponentSampleModel
.
createCompatibleSampleModel
in class java.awt.image.ComponentColorModel
w
- The width of the SampleModel
you want to create.h
- The height of the SampleModel
you want to create.
SampleModel
that is compatible with this
ColorModel
.SampleModel
,
ComponentSampleModel
public boolean isCompatibleSampleModel(java.awt.image.SampleModel sm)
SampleModel
is
compatible with this ColorModel
. A
SampleModel
is compatible if it is an instance of
ComponentSampleModel
, has the sample number of
bands as the total nomber of components (including alpha) in
the ColorSpace
used by this
ColorModel
, and has the same data type (float or
double) as this ColorModel
.
isCompatibleSampleModel
in class java.awt.image.ComponentColorModel
sm
- The SampleModel
to test for compatibility.
true
if the SampleModel
is
compatible with this ColorModel
,
false
if it is not.SampleModel
,
ComponentSampleModel
public java.lang.String toString()
toString
in class java.awt.image.ColorModel
|
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Rangers vs Celtic Betfred Cup Final ticket prices revealed as prices rise
It's the first time the teams have met in the cup final since 2011.
by Gabriel McKayAdult ticket prices for the Betfred Cup final between Rangers and Celtic will start at £35, the SPFL has announced.
The first cup final meeting between the two Glasgow giants since 2011 takes place next month after both sides cruised through their semi-finals.
Celtic despatched Hibs 5-2 on Saturday, before Steven Gerrard 's side eased to a 3-0 win over Hearts the following day.
Adult tickets for the Final will start at £35, with those tickets situated in the West Stand for Rangers supporters and £35 for Celtic .
The most expensive adult tickets are for the lower section of the South Stand, priced at £45 each.
That's a £5 increase on last season's Betfred Cup final between Celtic and Aberdeen, where the most expensive adult ticket was £40 and the cheapest £30.
Betfred Cup final ticket prices:
Rangers support
South Stand Lower section O2: adults £45
South Stand Lower section P: adults £40
South Stand Upper section Q: adults £40
North Stand section C: adults £40, over 65/under-16 £22
West Stand sections A & B: adults £35, over 65/under-16 £18
North Stand accessible seating: adults £22, over 65/under-16 £6
South Stand accessible seating: adults £18, over 65/under-16 £6
West Stand accessible seating: adults £12, over 65/under-16 £6
Celtic support
South Stand Lower section J1: adults £45
South Stand Lower section I: adults £40
South Stand Upper section H: adults £40
North Stand section D: adults £40, over 65/under-16 £22
East Stand sections F & G: adults £35, over 65/under-16 £18
North Stand accessible seating: adults £22, over 65/under-16 £6
South Stand accessible seating: adults £18, over 65/under-16 £6
East Stand accessible seating: adults £12, over 65/under-16 £6


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Open stats system
"Dark Souls doesn't force the player to play the game in any particular way.  Sure thing. The game lets you use the style of hero that you feel most comfortable with." (Boyd, 2012)
If Dark Souls were a university, the player's major would be undeclared. Sure you pick a few stats (or courses) at the beginning, but those choices act as
trial periods. Over time, as you try different play styles, you are able to commit to the ones you like best.
Dark Souls relies heavily on the mechanic of souls. You gain souls by killing enemies, with larger payouts for bigger baddies. You can spend them in a
variety of ways - to purchase new items and gear, to upgrade existing gear, or to level up your character. Purchasing a level grants one stat point
that you can put into any of the base stats. Rolling a Priest? Upgrade your faith. Playing a Tank? You’ll want some strength. Want to play a Paladin?
Then go half and half. Any character can upgrade any stat without limitation. But stats don’t merely improve your character’s attributes, they also
increase the scale with which weapons deal damage.
The weapon system
Dark Souls' weapon system is unique and peculiar. For starters, each class of weapon comes with different attack patterns, animations, and attack speeds.
Each weapon class feels different; each has a different weight. Sword swings may bounce off the narrow sewer walls, but a thrusting weapon with minimal
horizontal movement (a spear) is perfect for the occasion. Weapon damage scales with stat points. In each weapon class, you'll usually find at least one
weapon for each stat. And to add fuel to the complexity fire, you can upgrade weapons to scale with a different stat entirely. Dark Souls is able to put
all of this together to form one of the deepest and most engaging sets of fighting mechanics ever devised.
 This is a hard game, after all. There are bonfires scattered throughout the different areas. Bonfires
are safe-havens. They serve as respawn points, level up vendors, and reset buttons. That last item might sound a bit odd, but bear with me. When you
rest, every enemy in the game (except bosses) resets health, location, and aggro status. This affords ample opportunity to learn how the surrounding area
works.  To get far in Dark Souls, you must understand your enemies. This is daunting
at first because every enemy type (and there are hundreds) have different attack patterns, different animations, and different AI. There is no "One Size
Fits All" solution to this game. An attack style might absolutely decimate rabid dogs but be worthless against crystalline giants. Each area has a spattering
of different enemies which keeps the game feeling alive and compelling.