Thai cave reopens for visitors after Wild Boars rescue
BANGKOK: Thailand has reopened the cave where 12 young footballers and their coach were trapped last year in a saga that captivated the world.
The Tham Luang cave has been closed to visitors since the Wild Boars football team were rescued alive after nearly three weeks inside the grotto's waterlogged corridors.
But the world-famous cave in northern Chiang Rai province was re-opened Friday (Nov 1), drawing some 2,000 tourists in a single day, a local conservation official told AFP.
"We have allowed visitors to see the mouth of the cave," said Kamolchai Kotcha, director of the local conservation office that overseas the cave.
Guests are not allowed beyond the entrance for now, where they can peer into the cave opening, but officials said they were considering allowing people deeper inside after surveying the safety of the route.
READ: 'Wild Boars' deal with fame one year after Thai cave rescue
READ: Miracle of 'Wild Boars' rescue transforms Thai cave into tourist draw
Some of the rescue equipment left behind - including telephone wires, hoses and zip lines - could be exhibited inside the cave for visitors to view in the future, Kotcha said.
Photos from the opening on Friday showed tourists at the site's entry, where last year the boys' bikes and backpacks were found - alerting local police they were likely inside.
The Wild Boars went into Tham Luang in June 2018 for a routine hike after a football practice, but became trapped after heavy rains blocked the only route out.
Hundreds of people descended on the remote site to help save the boys, who were found - emaciated but alive - on a muddy perch deep inside the cave after nine excruciating days of searching.
INTERACTIVE SPECIAL: A closer look at the unprecedented rescue operation
The boys were sedated and fitted out in full-face breathing masks before being pulled to safety through a hazardous underwater labyrinth.
Several books deals about the drama have been inked, and the first film about the rescue premiered this month at the Busan International Film Festival in South Korea.


Form elements
Buttons
button default as link
Button selection
When there is more than one button, there is a space between
Table
| # | First | Last | Handle |
|---|---|---|---|
| 1 | Mark | Otto | @mdo |
| 2 | Jacob | Thornton | @fat |
| 3 | Larry the Bird |
Typography
This section has the class flow
to set the baseline.
Lorem ipsum dolor sit amet consectetur adipisicing elit. Nam ipsa rem, excepturi labore iusto perferendis, eum neque necessitatibus magni eveniet quibusdam tempora quae optio mollitia ducimus soluta aliquid accusamus voluptates.
“The only way to get rid of a temptation is to yield to it. Resist it, and your soul grows sick with longing for the things it has forbidden to itself, with desire for what its monstrous laws have made monstrous and unlawful.”
"Lorem"
Oscar Wilde, The Picture of Dorian Gray
Lorem ipsum dolor sit amet consectetur adipisicing elit. Exercitationem corrupti quis optio omnis. Repudiandae ducimus, eum perspiciatis dolores adipisci sed obcaecati voluptas quo, libero labore amet quod corrupti necessitatibus possimus?
[b bold] [strong bold] abbr [mark] [ins] [small] [dfn] [cite] [em] [i][code]
[kbd]
[var]
Pre tag: "Courier 10 Pitch", courier, monospaceAddress: 10 Point street
this is a link without class, with hover effect properties.
this is a external link, with an icon
Align full
Lorem, ipsum dolor sit amet consectetur adipisicing elit. Praesentium omnis quia impedit laudantium facere quod nostrum, natus hic adipisci sint ex, dolor perspiciatis dolores, libero illo accusamus. Accusantium, non dicta!


A typical class consists of gentle warm-ups and stretches, falling and rolling (ukemi) practice, Ki exercises and then technique practice.
Aikido movements often result in an attacker being thrown to the floor or pinned using joint locks. To enable safe and continued practice, we practice falling and rolling safely. These can seem intimidating at first to the beginner, since we have been conditioned to be afraid of falling. However, if you look at a toddler, there is no fear of falling. Learning the techniques to safely fall and roll will help you overcome this conditioned fear. In fact, when you start aikido, learning to fall safely is the most valuable and applicable skill you learn. It has certainly saved me (Abhijit) on the road many times.
Ki exercises can be thought of as elements of aikido movement that have been extracted out and are practiced separately as building blocks of aikido technique. We usually practice these to a count of five, and use this opportunity to understand how to make these foundational elements more correct.
Technique practice usually starts with more basic movements from a particular attack to practice fundamentals, and then progresses to more involved techniques or particular applications. We practice as partners, taking turns attacking (as uke) and defending (as nage). We emphasize a relaxed flow that allows the defender to diffuse an attack, while maintaining the basic principles himself. This practice cannot really be described in words, and must be experienced kinesthetically to begin to understand and absorb it.
One of the most common questions we get is, how long does it take to get to black belt? There are many philosophic, and many tongue-in-cheek, answers to this question. However, we think that it is best not to focus on this question but to start your journey and learn. Even after many years of training, we (the instructors) are still learning.
The black belt is certainly a milestone in a martial artist’s path, but it is a beginning, not the end. To us, it signifies the end of the beginning part of our training, when one has a reasonable grasp of the fundamentals and is ready to move on to deeper understanding of the art. Some have compared the black belt to a Bachelor’s degree, where you know the basics pretty well but aren’t really an expert. We would strongly recommend that you focus not on the goal of a black belt but learn, absorb and understand the art through regular practice. Ranks and belts will come along the way.
Aikido is typically practiced using Judo gi. We find that a single weave Judo gi or a heavy Karate gi tends to be the most comfortable. Hakama, or divided skirts, are worn by black belt practitioners. Belts are colored by rank, from white (beginner) through orange, blue and brown, to black.
Beginners : When you are first starting aikido practice with us, we encourage you to wear long-sleeved clothes like long-sleeved t-shirts, sweatshirts without hoods and sweatpants. Jewellery like necklaces or dangling earrings are prohibited, and taking off all jewellery may be the most comfortable. Stone-less rings like some wedding bands and stud earrings may be acceptable; ask your instructor what he or she would allow on the mat. Please ensure that your clothing is clean and your nails are trimmed and filed. Cover any cuts you may have with band-aids or bandages, and let the instructor know if you have any active injuries; we can work around those.
Aikido is a martial art. Though our practice is safe and relatively injury-free, the practice does have the potential to cause injury or harm to the practitioner if he is not careful. It requires attention and concentration to practice safely, absorb and understand. When you get on the mat, try and leave all other concerns off the mat and give your practice your undivided attention. This is your time, in your laboratory, to learn and practice this amazing martial art.


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| Package | Description |
|---|---|
| org.plasma.query.model |
Copyright 2017 TerraMeta Software, Inc.
|
| org.plasma.query.visitor | |
| org.plasma.sdo.access.provider.common | |
| org.plasma.sdo.jdbc.filter |
| Modifier and Type | Field and Description |
|---|---|
protected Property |
Variable.property |
protected Property |
Term.property |
| Modifier and Type | Field and Description |
|---|---|
protected java.util.List<Property> |
OrderBy.properties |
protected java.util.List<Property> |
GroupBy.properties |
| Modifier and Type | Method and Description |
|---|---|
Property |
ObjectFactory.createProperty()
Create an instance of
Property |
static Property |
Property.forName(java.lang.String name)
Factory method returning a property for the given name.
|
static Property |
Property.forName(java.lang.String name,
Path path)
Factory method returning a property for the given name and path.
|
Property |
Term.getProperty()
Gets the value of the property property.
|
| Modifier and Type | Method and Description |
|---|---|
java.util.List<Property> |
OrderBy.getProperties() |
java.util.List<Property> |
GroupBy.getProperties()
Gets the value of the properties property.
|
| Modifier and Type | Method and Description |
|---|---|
void |
OrderBy.addProperty(Property property) |
void |
GroupBy.addProperty(Property property) |
static Expression |
Expression.between(Property prop,
Literal min,
Literal max)
Returns a 6 term expression, where the given property is greater than or
equal to the given 'min' literal, and is less than or equal
tothe given 'max' literal.
|
static Expression |
Expression.between(Property prop,
java.lang.Object min,
java.lang.Object max)
Returns a 6 term expression, where the given property is greater than or
equal to the given 'min' literal, and is less than or equal
tothe given 'max' literal.
|
static Expression |
Expression.eq(Property prop,
Literal literal)
Returns an expression where the given property is equal to to the
given literal.
|
static Expression |
Expression.eq(Property prop,
NullLiteral literal)
Returns an expression where the given property is equal to to the
given null-literal.
|
static Expression |
Expression.eq(Property prop,
java.lang.Object literal)
Returns an expression where the given property is equal to to the
given literal.
|
static Expression |
Expression.exists(Property prop,
Query subquery) |
static Expression |
Expression.ge(Property prop,
Literal literal)
Returns an expression where the given property is greater than or equal
to to the given literal.
|
static Expression |
Expression.ge(Property prop,
java.lang.Object literal)
Returns an expression where the given property is greater than or equal
to to the given literal.
|
static Expression |
Expression.gt(Property prop,
Literal literal)
Returns an expression where the given property is greater than to
the given literal.
|
static Expression |
Expression.gt(Property prop,
java.lang.Object literal)
Returns an expression where the given property is greated than to
the given literal.
|
static Expression |
Expression.in(Property prop,
Query subquery)
Returns a subquery expression, where the given property is found
within the given subquery results collection.
|
static Expression |
Expression.le(Property prop,
Literal literal)
Returns an expression where the given property is less than or equal
to to the given literal.
|
static Expression |
Expression.le(Property prop,
java.lang.Object literal)
Returns an expression where the given property is less than or equal
to to the given literal.
|
static Expression |
Expression.like(Property prop,
Literal literal)
Returns a wildcard expression "triad", where the given property is
like the given literal, and the literal may contain any number of
wildcards, the wildcard character being '*'
|
static Expression |
Expression.like(Property prop,
java.lang.Object literal)
Returns a wildcard expression "triad", where the given property is
like the given literal, and the literal may contain any number of
wildcards, the wildcard character being '*'
|
static Expression |
Expression.lt(Property prop,
Literal literal)
Returns an expression where the given property is less than to the
given literal.
|
static Expression |
Expression.lt(Property prop,
java.lang.Object literal)
Returns an expression where the given property is less than to the
given literal.
|
static Expression |
Expression.ne(Property prop,
Literal literal)
Returns an expression where the given property is not equal to to
the given literal.
|
static Expression |
Expression.ne(Property prop,
NullLiteral literal)
Returns an expression where the given property is not equal to to
the given null-literal.
|
static Expression |
Expression.ne(Property prop,
java.lang.Object literal)
Returns an expression where the given property is not equal to to
the given literal.
|
static Expression |
Expression.notIn(Property prop,
Query subquery)
Returns a subquery expression, where the given property is not found
within the given subquery results collection.
|
void |
Variable.setProperty(Property value)
Sets the value of the property property.
|
void |
Term.setProperty(Property value)
Sets the value of the property property.
|
void |
QueryValidator.start(Property property) |
void |
AbstractQueryValidator.start(Property property) |
| Modifier and Type | Method and Description |
|---|---|
void |
QueryVisitor.end(Property property) |
void |
DefaultQueryVisitor.end(Property property) |
void |
QueryVisitor.start(Property property) |
void |
DefaultQueryVisitor.start(Property property) |
| Modifier and Type | Field and Description |
|---|---|
Property |
DataComparator.PathInfo.property |
| Modifier and Type | Method and Description |
|---|---|
void |
DataComparator.addAscending(Property property) |
void |
DataComparator.addDescending(Property property) |
protected abstract void |
TextQueryFilterAssembler.assembleSubquery(Property property,
PredicateOperator oper,
Query query) |
protected java.lang.Object |
DataComparator.findEndpoint(commonj.sdo.DataObject targetObject,
Property property,
Path path,
int pathIndex) |
protected abstract void |
TextQueryFilterAssembler.processWildcardExpression(Property property,
PredicateOperator oper,
Literal literal) |
void |
DataObjectHashKeyAssembler.start(Property property) |
void |
DataComparatorAssembler.start(Property property) |
| Constructor and Description |
|---|
DataComparator.PathInfo(Property property,
int direction) |
| Modifier and Type | Method and Description |
|---|---|
protected void |
SubqueryFilterAssembler.assembleSubquery(Property property,
PredicateOperator oper,
Query query) |
protected void |
FilterAssembler.assembleSubquery(Property property,
PredicateOperator oper,
Query query) |
protected void |
SubqueryFilterAssembler.processWildcardExpression(Property property,
PredicateOperator oper,
Literal literal) |
protected void |
FilterAssembler.processWildcardExpression(Property property,
PredicateOperator oper,
Literal literal) |
void |
SubqueryFilterAssembler.start(Property property) |
void |
OrderingDeclarationAssembler.start(Property property) |
void |
GroupingDeclarationAssembler.start(Property property) |
void |
FilterAssembler.start(Property property)
Handles a property query node, traversing the property path appending SQL
'AND' expressions based on key relationships until the property endpoint is
reached.
|
PlasmaSDO™ and PlasmaQuery™ are trademarks of TerraMeta Software, Inc. Copyright © 2011 - All Rights Reserved.


I am currently pursuing a B.E degree in Information Technology. I am learning software development and computer programming and have an avid interest in Data Structures, Algorithms and Optimization. As a core programmer, I love taking challenges and love being part of the solution.
I am exploring several areas of computer science, some of them are: Fullstack Web and Mobile development, Data Science, Machine Learning, Computer Vision, Cyber-security, Networking and related technologies.
As a freelance developer I usually analyze user requirements, create innovative, scalable, fault-tolerant software solutions for clients and customer base. Currently working on two projects, a e-commerce website with MongoDB, Express, React and Node.js and a social media cum calling app with React-native.
Researched industry-related topics (combining online sources, interviews and studies), wrote clear marketing copy to promote products/services, prepared well-structured drafts using Content Management Systems, actively engaged customers/stakeholders and maintained a cohesive brand voice.
Managed Switches, Routers and Routing protocols; and network peripherals, analyzed network protocols including http, ftp, ssh, tcp, udp, ip, arp, Ethernet, and 802.11 technologies
I am currently studying courses like Computer Networks, Operating Systems, Compiler Design, Computer Organization, Modern Cryptology, Data Structures and Algos, Distributed Systems, Analysis and Design of Algorithms, Theory Of Computation, Parallel Programming, Computer Architecture, Computer Systems Security, Probability and Statistics, Differential Equations, Linear Algebra, Matrix Theory.
Enrolled in various online courses across different platforms for learning recent trends in the world like: "CS50's Introduction to Computer Science by Harvard University", "UCSanDiegoX: DSE200x Python for Data Science", "Algorithms, Part I and Part II by Princeton University ", etc..
Completed High school with Physics, Chemistry, Maths as majors..

Linus Torvalds
"Success is a lousy teacher. It seduces smart people into thinking they can't lose."
Bill Gates.
"If you're changing the world, you're working on important things. You're excited to get up in the morning."
Larry Page.
I am always excited to work on some awesome projects, message me and let's discuss over a cup of coffee.


--- layout: default date: 08/10/2019 ---
Covers races from 22nd August — 10th Ocotober.
Last updated: {{ page.date | date: "%A, %B %e" }}
{% include standings.html riders=site.data.2019.series_5.crit teams=site.data.2019.series_5.critteam %} {% include datetime.html %}


--- layout: default hero-image: url(/assets/images/stock-images/robotics_competition_sp17.jpg) hero-message: PiE Robotics Competition ---
Download Dawn and Runtime software, view documents and guides, and check for updates.
Visit software hub Visit kit hubAsk questions and get answers! Discuss various competition aspects or just come chat. Access code: pie
Visit the forumsSign up for worksessions 24 hours in advance! Having debug issues? Need some more build time or tools? Come on out!
Sign up for worksession


| MPI_TYPE_DUP(type, newtype) | |
| IN type | datatype (handle) |
| OUT newtype | copy of type (handle) |
int MPI_Type_dup(MPI_Datatype type, MPI_Datatype *newtype)
MPI_TYPE_DUP(TYPE, NEWTYPE, IERROR)
INTEGER TYPE, NEWTYPE, IERROR
{ MPI::Datatype MPI::Datatype::Dup() const (binding deprecated, see Section Deprecated since MPI-2.2
) }
MPI_TYPE_DUP is
a type constructor
which duplicates the existing type
with associated key values.
For each key value, the respective copy
callback function determines the attribute value associated with this
key in the new communicator; one particular action that a copy
callback may take is to delete the attribute from the new datatype.
Returns in newtype a new datatype with exactly the same
properties as type and any copied cached
information, see Section Datatypes
on page Datatypes
.
The new datatype has identical
upper bound and lower bound and yields the same net result when fully
decoded with the functions in Section Decoding a Datatype
.
The
newtype has the same committed state as the old
type.
Up: Derived Datatypes
Next: Use of General Datatypes in Communication
Previous: Commit and Free
Return to MPI-2.2 Standard Index
Return to MPI Forum Home Page
(Unofficial) MPI-2.2 of September 4, 2009
HTML Generated on September 10, 2009


Neural Steganography: Text-in-Picture
Video-in-Video
Picture-in-Picture
Text-in-Picture
Enter a secret to send:
Processed text: {{ secret }}
Choose a cover to hide the secret in:
Here is the hidden secret to send:
Here is the revealed secret:
{{ revealed }}


Bold
Italics
H1
H3
H5
check out this cool website!
A
B
C
This is the first paragraph
This is the second paragraph


This extension searches and returns pages based on the query entered in the browser's address bar.
For the extension to recognize a query, it must start with the 'h ' string (an 'h' letter followed by a whitespace)
General query form:
h searchTerms... tags... dates... afterFilters... sortingRules...
| Arguments | Meaning |
|---|---|
searchTerms | Strings which must exist within a page's title or URL |
tags | User-defined and assigned to pages tags |
dates | Date arguments of special format specifying search timeframes |
afterFilters | Filters removing unwanted entries from the resulting set |
sortRules | Sorting rules to be applied on the resulting set |
Any number of arguments of any type can be included in a query, or none at all. The only important thing is their order if they are present.
String, words, letters that must exist within a page's title or URL
| Example query | Explanation |
|---|---|
| h word | Find any pages containing 'word' in either URL or title |
| h word1 word2 | Find any pages containing 'word1' AND 'word2' in either URL or title |
Tags are special entities assignable by the user to pages for easiness of later finding those pages.
After a tag is assigned to a page through the extensions' popup, pages with such a tag can be found using a tag argument in a query.
Tagged pages will be found through a tag even if they are deleted from history.
Tag argument form:
!tagName
Tag word must be prefixed with the exclamation mark (!)
| Example query | Explanation |
|---|---|
| h !tagWord | Find any pages having 'tagWord' assigned to them |
| h !tag1 !tag2 | Find any pages having 'tag1' AND 'tag2' tags assigned to them |
Dates limit resulting set to desired time borders.
General date argument form:
[+-=]dd/mm/yyyy/hh:mm
where one of -, +, = signs must be included at the start of the date argument depending on the desired result:
| Sign | Explanation |
|---|---|
+ | after and including date |
- | before and including date |
= | exact date |
then the sign is followed by one or more date segments specifying the necessary precision of a time frame:
| Segment | Description | Explanation |
|---|---|---|
dd/ | one or two digits followed by a slash | a number of the month |
/mm/ | a slash followed by one or two digits followed by another slash | a number of the month |
/yyyy/ | a slash followed by four digits followed by another slash | a year |
hh: | two digits followed by a colon | hours |
:mm | a colon followed by two digits | minutes |
Omitted date segments will be assumed to be of the current time (the current year, the current month, etc.).
Multiple date options can be added and combined to specify multiple time spans.
| Example query | Explanation |
|---|---|
| h =/2018/ | Find pages that were visited in 2018 |
| h =/4/2018/ | Find pages that were visited in April 2018 |
| h +3/ | Find pages that were visited from 3th of the current month up to now |
| h +3/ -10/ | Find pages that were visited from 3th and before 10th of the current month |
| h +/6/ | Find pages that were visited from June of the current year up to now |
| h =/5/ =/9/ | Find pages that were visited in May or September of the current year |
| h +6: -12: | Find pages that were visited today from 6 am to 12 pm |
Filters that will remove unwanted entries from the resulting set
| Form | Explanation |
|---|---|
+url terms... | include only pages with a URL that contain such terms |
-url terms... | exclude pages that contain a URL with such terms |
+title terms... | include only pages with a title that contain such terms |
-title terms... | exclude pages that contain a title with such terms |
| Example query | Explanation |
|---|---|
| h word -title word | Find pages containing 'word' only in URL |
| h word1 +url word2 word3 | Find pages containing 'word1' in either URL or title AND ALSO have 'word2' AND 'word3' in their URL |
| Form | Explanation |
|---|---|
>u terms... >url terms... | sort result by url in ascending order |
<u terms... <url terms... | sort result by url in descending order |
>t terms... >title terms... | sort result by title in ascending order |
<t terms... <title terms... | sort result by title in descending order |
>d terms... >date terms... | sort result by date in ascending order |
<d terms... <date terms... | sort result by date in descending order |
>v terms... >visit terms... | sort result by visit count in ascending order |
<v terms... <visit terms... | sort result by visit count in descending order |
| Example query | Explanation |
|---|---|
| h word !tag | Find pages containing 'word' in either URL or title and having 'tag' tag |
| h !tag1 !tag2 =/7/ | Find pages having 'tag1' and 'tag2' tags visited in July |
| h word +title word >url | Find pages containing 'word' in title and sort them by URL |
| h word1 word2 !tag1 !tag2 >t | Find pages containing 'word1' and 'word2' in either URL or title, and having 'tag1' and 'tag2' tags, and then sort them by title |
| h word =1/ =8/ =15/ | Find pages containing 'word' in either URL or title that were visited on 1th, 8th or 15th of the current month |


All numbers that contain a 3 or are a multiple of 3 are Fizz! All numbers that contain a 5 or are a multiple of 5 are Buzz! Any numbers that fit both of the above criteria are Fizz Buzz!


Preparation time
over 2 hours
Cooking time
10 to 30 mins
Serves
Serves 4
The Hairy Bikers serve up this creamy chicken liver pâté as part of an Eastern European smorgasboard, it also makes wonderful party food or a tasty starter if you have friends over for dinner.
Melt the butter in a frying pan. When it is just foaming, add the onion and thyme. Sauté until the onion is soft and translucent, then add the chicken livers and spices.
Turn up the heat and fry until the livers are just cooked through, this should take about 3-5 minutes.  Transfer the mixture to a bowl and leave to cool.
Return the frying pan to the heat, pour in the sherry. Allow to bubble and reduce by half, stirring and scraping up any sediment from the bottom of the frying pan as you go, remove from the heat and leave to cool.
Put the chicken mixture in a food processor. Pour in the reduced sherry. Pulse the food processor until the pâté is smooth. To make the pâté extra smooth pass it through a coarse sieve. Season with salt to taste.
Put the pâté in a terrine dish or pot and chill in the fridge for about 2 hours. If you want to keep the pâté for a few days, cover it with clarified butter.


This was pesky enough that I thought it merited a small post. I recently ran out of media on my Ubuntu VM on my ESXi v6.5 homelab. And went on a small adventure trying to figure out what to slap in the terminal to get more space. So hopefully this might save someone else more time.
First, go to the VM whose HDD you’d like to expand and click edit settings. Then click the Hard disk option and enter your desired HDD size (make sure the VM is shut down for this).
Then boot your VM and click the GUI option or ssh in. Make sure GParted is installed with:
~ sudo apt install gparted
Start GParted and click the /dev/sda1 partition then click the Resize/Move button. Drag the partition to the right to consume the unallocated partition.
Normally, this is all you’d have to do for a regular linux machine, however, it uses logical volumes that have to be extended as well.
Run
~ sudo fdisk -l
It should display something like this:
The second entry, ubuntu–vg-root, is the volume we’re concerned with. The name will vary from machine to machine but it should still something like name–vg-root at end. You can ignore the swap partition.
Next run:
~ sudo lvresize /dev/mapper/ubuntu--vg-root -L +100g
~ sudo resize2fs /dev/mapper/vg0-slash
Be sure to modify /dev/mapper/ubuntu–vg-root to match your fdisk -l output. This extends your partition by 100g, insert however much you need. You can use 100%FREE instead of +100g and it should consume all available space; however, I couldn’t get it working for me.
That’s it!


EventsSet¶
Contains a class that represent a set of DYNAP-se events
-
class
classes.EventsSet.
EventsSet
(ts, chip_id, core_id, neuron_id)[source]¶ Bases:
object
A set of DYNAP-se events
Return a new EventsSet object
Parameters: - ts (array, float) – Times of events
- chip_id (array, int) – Chip number of events
- core_id (array, int) – Core number of events
- neuron_id (array, int) – Neuron number of events
Note
The event set contains only normal events, not special ones.
Events has the following structure:
Vect Event 0 Event 1 Event 2 Event … chip_id 0 1 3 … core_id 0 3 1 … neuron_id 1 100 255 … ts<PHONE_NUMBER>64 150128 … Accessing directly events from an .aedat is very simple, after having imported them:
set = import_events("recording.aedat") # event set of the recording chip_id = set.chip_id core_id = set.core_id neuron_id = set.neuron_id ts = set.ts
We can now access every event:
>>> chip_id[0] 0 >>> core_id[0] 0 >>> neuron_id[1] 100 >>> ts[2] 150128
-
__getitem__
(key)[source]¶ Return a time filtered EventsSet object
Parameters: key (tuple, ints) – a tuple containing an init and an end index Note
This attribute is very useful when you want to isolate some events for which you know the indexes.
Example
Isolate first 10 events:
set = import_events("recording.aedat") # event set of the recording filteredSet = set[0:10]
-
calculate_firing_rate_matrix
(totNeurons, numBins=10, timeBin=None)[source]¶ Derive a firing rate matrix starting from the current EventSet
Parameters: - totNeurons (int) – Maximum number of neurons for which firing rate is calculated (from id = 0 to totNeuron number)
- numBins (int) – Default parameter. Number of intervals in which firing rate must be evaluated
- tBin (int, [s], optional) – Amplitude of each interval in which firing rate must be evaluated
Returns: tuple containing:
- timeSteps (array, float): Time steps in which firing rate has been calculated
- neuronsFireRate (2D array, float): Contain firing rate for every neuron and for every time step
Return type: (tuple)
Note
To evaluate the firing rate the average of the spikes is made over a certain time step. The rate value is then associated to the first time in the time bin, as here below:
timeSteps -> [t0 t0+tBin t0+2tBin ... tn-tBin]
where tBin is the temporal step in which firing rate is evaluated (tBin = (tn - t0) / numBins)) or directly the specified tBin
The firing rate is calculated for every specified neuron, obtaining the following matrix (number are expressed in Hz):
neuron id fr at t0 fr at t0+tBin … fr at t0+ntBin neuron 0 5 0 … 0 neuron 1 0 10 … 10 … 2 2 … 2 neuron n 20 10 … 10 Examples
# Initialize set importing all events set = import_events("recording.aedat") # event set of the recording # obtain firing rate from number of bins timeSteps, neuronsFireRate = set.calculate_firing_rate_matrix(totNeurons = 1024, numBins = 100) # obtain firing rate from bin size timeSteps, neuronsFireRate = set.calculate_firing_rate_matrix(totNeurons = 1024, timeBin = 0.02)
-
filter_events
(chip_id, core_id, neuron_id)[source]¶ Return a EventsSet containing only the wanted events
Parameters: - chip_id (int) – id of the chip you want to take events from (for now is only possible to filter one chip events)
- core_id (list, int; int) – id of the cores you want to take event from
- neuron_id (2D list, int; list, int; int) – id of the neurons you want to take events from
Returns: A set containing the events resulting from the filtering
Return type: obj EventsSet
Note
Filter is specified selecting certain chip_id, core_id and neuron_id. It supports only one chip at a time (so chip_id must be a integer from 0 to 3), so you cannot take, for example, events from core 0 of chip 0 and core 1 of chip 1.
After selecting the chip_id you have two alternatives: Or don’t apply filters to the cores, by leaving core_id as None. In this way the events of all cores can be potentially taken, if no neuron_id is specified. The other alternative is to specify the cores you want to take events from, filtering the ones not specified by you. You can at this point define:
- a single core id, between 0 and 3.
- list of cores id, for example [0, 2].
At this point you have two alternatives: Or don’t apply a filter to the neurons inside a core, by neuron_id as None. In this way you will take all the events from the 256 neuron per core (only the one specified in the core filter, of course). The other alternative is to specify the neurons you want to take events from, filtering the ones that are not specified by you. If this is the case, you must define something for all cores selected in the previous point. You can define:
- a single neuron id, between 0 and 255
- a list of neurons id, for example [1, 5, 22, 128, …]
The types can be mixed, so you can take a single neuron from one core and a list from another, indipendently.
Examples
Initialize set importing all events:
set = import_events("recording.aedat") # event set of the recording
Take events from chip 0, neuron from 0 to 99 of core 0 and neurons from 100 to 199 on core 1:
filterCore0 = list(range(0, 100)) filterCore1 = list(range(100, 199)) neuronIdFilter = [filterCore0, filterCore1] filteredSet = set.filter_events(chip_id = 0, core_id = [0, 1], neuron_id = neuronIdFilter)
Take all events from chip 1:
filteredSet = set.filter_events(chip_id = 1, core_id = None, neuron_id = None)
Take all events from core 0 and 1 of chip 2:
filteredSet = set.filter_events(chip_id = 2, core_id = [0, 1], neuron_id = None)
Take only events from neuron 3 of core 0 and chip 3:
filteredSet = set.filter_events(chip_id = 3, core_id = 0, neuron_id = 3)
Take events from chip 0, neuron 20 of core 0 and neuron 127 of core 1:
filteredSet = set.filter_events(chip_id = 0, core_id = [0, 1], neuron_id = [20, 127])
-
isolate_events_sets
(startTriggerNeuron, stopTriggerNeuron, maxNumber=None)[source]¶ Returns a list of Event sets each one containing an experiment.
Parameters: - startTriggerNeuron (tuple, int (chip id, core id, neuron id)) – Neuron which events triggers the start of the experiment
- stopTriggerNeuron (tuple, int (chip id, core id, neuron id)) –
- maxNumber (int) – max number of experiments that can be extracted from the Set of events
Returns: a list of Event sets each one containing an experiment
Return type: list, obj EventsSet
Note
When dealing with Dynap-se output recordings, one of the main problems is “how get only events that are associated only with my input?” You can, of course, filter events manually using custom functions, but this is expensive in terms of time. An automatic solution, however, can be to use two Dynap-se neurons to trigger the start and the end of the events correlated to my input.
The experiment would be constructed in this way:
- send a spike to a neuron that will represent my starting trigger
- send the experiment input spikes after small delay, negligible with respect to the delays involved in the input stream
- send a spike to a neuron that will represent my ending trigger, with a small delay, as for the input
So each experiment is the repetition of these 3 passages. Make sure there is enough delay between the stop trigger event and the start of the new one. You should avoid overlapping of them, because this can create confusion while extracting events. The code is able to handle multiple spikes of start and trigger neurons for the same experiment, so don’t much worry about that.
This function should be applied to the output recording in order to filter all events but for the ones that are between the start and stop neurons. In this way you can automatically synchronize your analysis with the events generated only by your input.
It is possible to specify also a maximum number of experiments that are extracted from the set using maxNumber parameter.
Examples
# Initialize set importing all events set = import_events("recording.aedat") # event set of the recording
startTriggerNeuron neuron 64 of core 2 of chip 0, stopTriggerNeuron is neuron 128 of core 2 of chip 0. Take all experiments (no maxNumber specified) included between these two neurons:
startTriggerNeuron = (0, 2, 64) stopTriggerNeuron = (0, 2, 128) extractedEvents = set.isolate_events_sets(startTriggerNeuron = startTriggerNeuron, stopTriggerNeuron = stopTriggerNeuron, maxNumber = None)
startTriggerNeuron neuron 64 of core 2 of chip 0, stopTriggerNeuron neuron 128 of core 2 of chip 0. Take UP TO 5 experiments between these two neurons:
startTriggerNeuron = (0, 2, 64) stopTriggerNeuron = (0, 2, 128) extractedEvents = set.isolate_events_sets(startTriggerNeuron = startTriggerNeuron, stopTriggerNeuron = stopTriggerNeuron, maxNumber = 5)
-
normalize
()[source]¶ Normalize the time of the current EventSet
Returns: A new normalized EventSet Return type: obj EventsSet Note
The time of the first event is set to 0. The subsequent are changed accordingly
-
plot_events
(ax=None)[source]¶ Raster plot of events included in the current EventsSet
Parameters: ax (ax handle, optional) – Plot graph on this handle, otherwise a new figure will be created Returns: tuple containing: - fig (fig handles): To modify properties of the figure
- ax (ax handles): To modify properties of the plot
- handles (lines handles): To create custom legends
Return type: (tuple) Note
Colors has been chosen to be clearly visible and to match the DYNAP-se core color enconding:
- core 0: green - core 1: magenta - core 2: red - core 3: yellow
With this classification there there is no distinguish between different chips events. It is much better to filter them and display them separately.
The input ax value can be used to make it plot over a pre-created figure. Fig, ax and handles can be used instead by the user to specify in detail the properties of the graph (see Example for how to do it)
Examples
# Initialize set importing all events set = import_events("recording.aedat") # event set of the recording figList, ax, handles = set.plot_events() # plot events ax.set_title("Raster plot Recording") ax.set_xlabel('time [us]') ax.set_ylabel('Neuron id')


| Home | Tutorials | Loading Information | The Entity Class | Class and Message Basics |
All sample PMA Tutorials are based on the data described in this section. Several sample data files have been supplied in addition to sample Vision code which can be executed to read these files and create the database.
By default, all files referenced are in the directory /localvision/samples/pma/. Check with your Vision Administrator if you do not see the following files in the directory:
| File Name | Function | Reference |
| Currency.pma | Tab-delimited file containing currency identifiers and names. | CurrencyMaster |
| Country.pma | Tab-delimited file containing country identifiers and names and a currency identifier. | CountryMaster |
| Sector.pma | Tab-delimited file containing sector identifiers and names. | SectorMaster |
| Industry.pma | Tab-delimited file containing industry identifiers and names and a sector identifier. | IndustryMaster |
| Company.pma | Tab-delimited file containing basic company information: id, name, country, industry id, and fiscalYearEnd. | CountryMaster |
| SecType.pma | Tab-delimited file containing basic SecurityType information: id, name, unitcalc, assetcategory | SecurityTypeMaster |
| Security.pma | Tab-delimited file containing security information: id, name, currency, cusip, ticker, companyId, security type, and latestMarketCapUS. | SecurityMaster |
| Portfolio.pma | Tab-delimited file containing additional portfolio information: id, name | SecurityMaster |
| Price.pma | Tab-delimited file containing price information for different time points. | PriceFeed |
| Holdings.pma | Tab-delimited file containing holdings information for portfolios over time. | HoldingsFeed |
| sample.pma | File containing Vision code that loads the .pma files. |
You can read the sample.load file into your favorite Vision Editor or you can execute the code in this file using the asFileContents evaluate expression:
"/localvision/samples/pma/sample.load" asFileContents evaluate ;
Note: The sample.load file runs by default on a Unix environment. If you are using a Windows NT platform, this location may be prefixed by a drive and optional path (e.g., d:/visiondb/localvision/samples/pma/sample.load). In additition, the sample.load file must be edited by your Vision Administrator to reflect the correct locations.
The file Currency.pma contains one line per currency. Each line contains a currency identifier and a currency name. The first few lines of this file are displayed below:
id name ADP Andorran Peseta AED UAE Dirham ...
CurrencyMaster is the name of the feed that is used to create and refresh basic information for Currency instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"CurrencyMaster" usingFile: "/localvision/samples/pma/Currency.pma";
The output buffer will display the total number of currencies loaded.
The file Country.pma contains one line per country. Each line contains a country identifier and a country name. The first few lines of this file are displayed below:
id name currency AD Andorra ADP AE United Arab Emirates AED ...
CountryMaster is the name of the feed that is used to create and refresh basic information for Country instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"CountryMaster" usingFile: "/localvision/samples/pma/Country.pma";
The output buffer will display the total number of countries loaded.
The file Sector.pma contains one line per sector. Each line contains a sector identifier and a sector name. The first few lines of this file are displayed below:
id name NONDUR Non-durables DUR Durables ...
SectorMaster is the name of the feed that is used to create and refresh basic information for Sector instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"SectorMaster" usingFile: "/localvision/samples/pma/Sector.pma";
The output buffer will display the total number of sectors loaded.
The file Industry.pma contains one line per industry. Each line contains an industry identifier, industry name, and a sector identifier.The first few lines of this file are displayed below:
id name sector 110 Beverages NOND 120 Cosmetics NOND ...IndustryMaster is the name of the feed that is used to create and refresh basic information for Industry instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"IndustryMaster" usingFile: "/localvision/samples/pma/Industry.pma";
The output buffer will display the total number of industries loaded.
The file Company.pma contains one line per company. Each line contains a company identifier, company name, country identifier, identifier, industry identifier, and a fiscalYearEnd date. The first few lines of this file are displayed below:
id name Country Currency Industry fiscalYearEnd 02364J10 AMERICA ONLINE INC US USD 390 6 37044210 GENERAL MOTORS CORP US USD 210 12 45920010 INTL BUSINESS MACHINES CORP US USD 530 12 ...CompanyMaster is the name of the feed that is used to create and refresh basic information for Company instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"CompanyMaster" usingFile: "/localvision/samples/pma/Company.pma";
The output buffer will display the total number of companies loaded.
The file SecType.pma contains one line per security type. Each line contains a security type identifier, security type name, UnitCalc, and an AssetCategory. The first few lines of this file are displayed below:
id name unitcalc assetcategory 0 Cash & Equiv 1.00 Cash 1 Common Stock 1.00 Equity 2 Preferred Stock 1.00 Equity ...
SecutityTypeMaster is the name of the feed that is used to create and refresh basic information for SecurityType instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"SecurityTypeMaster" usingFile: "/localvision/samples/pma/SecType.pma";
The output buffer will display the total number of security types loaded.
The file Security.pma contains one line per security. Each line contains a security identifier, security name, currency identifier, cusip, ticker, company identifier, security type identifier, and latestMarketCapUS. The first few lines of this file are displayed below:
id name currency cusip ticker companyId type latestMarketCapUS 02364J10 AMERICA ONLINE INC DEL COM USD 02364J10 AOL 02364J10 1 4792900.00 37044210 GENERAL MTRS CORP COM USD 37044210 GM 37044210 1 42734805.00 45920010 INTERNATIONAL BUSINESS MACH COM USD 45920010 IBM 45920010 1 88261698.75 ...SecurityMaster is the name of the feed that is used to create and refresh basic information for Security instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"SecurityMaster" usingFile: "/localvision/samples/pma/Security.pma";
The output buffer will display the total number of securities loaded.
The file Portfolio.pma contains one line per portfolio. Each line contains a portfolio identifier and a portfolio name. The first few lines of this file are displayed below:
id name 102 INSYTE GROWTH FUND 232 INSYTE INCOME FUND 332 INSYTE GROWTH & INCOME FUND ...PortfolioMaster is the name of the feed that is used to create and refresh basic information for Portfolio instances.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"PortfolioMaster" usingFile: "/localvision/samples/pma/Portfolio.pma";
The output buffer will display the total number of portfolios loaded.
The file Price.pma contains multiple dates per security. Each line represents a specific security identifier, date, currency identifier, adjustmentDate closing, price, and volume. The first few lines of this file are displayed below:
id date currency adjustmentDate close volume 02364J10 11/06/1997 USD 12/18/1997 79.38 2.55 02364J10 11/07/1997 USD 12/18/1997 79.25 4.85 02364J10 11/10/1997 USD 12/18/1997 76.06 1.75 ...PriceFeed is the name of the feed that is used to create and refresh basic information for security prices.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"PriceFeed" usingFile: "/localvision/samples/pma/Price.pma";
The output buffer will display the total number of prices loaded.
The file Holdings.pma contains a line for each security held in a portfolio on a date. Multiple dates of holdings for a portfolio are involved. Each line contains a date, an account identifier, and security identifier. The first few lines of this file are displayed below:
date acctId secId shares mval 19971215<PHONE_NUMBER>0 7800 497741.40 19971215 102 00949T10 15200 589000.00 19971215 102 02364J10 8200 695975.00 ...HoldingsFeed is the name of the feed that is used to create and refresh basic information for Account holdings.
To manually load the file, execute the following:
Interface ExternalFeedManager upload:"HoldingsFeed" usingFile: "/localvision/samples/pma/Holdings.pma";
The output buffer will display the total number of holdings loaded.
| Copyright © 1999 Innovative Systems Techniques, Inc. | Created January 28, 1999 |


Turn on/off lights
Understanding Booth's Algorithm
Booth's algorithm is a non conventional approach to multiplication. Though the implementation is non challenging, I found the underlying concept a bit tricky. Here I would like to share a detailed analysis of it's working.
Multiplication is all about adding a value 'a', 'b' times.
Here 'a' is called a multiplier, and 'b' is multiplicand.
Example:
Let multiplicand be 3, multiplier be 15, then
3*15 = 15 + 15 + 15 = 45
Binary multiplication can be approached in a similar fashion. We can take multiplicand as a counter and can add multiplier to the accumulator, decrementing the counter at each addition. The process will stop when the counter reaches zero and the accumulator will store the result.
If you are not familiar with accumulator, think of it as a data cell initialized to 0.
Unfortunately, the above approach trades efficiency for simplicity. When we deal with low-level architecture, the no. of additions and subtractions increase the time complexity. For large numbers, the no. of additions increases drastically.
Try multiplying 253614*727128 !
To combat that, we go back to 1
st grade. The algorithm taught to us to multiply two numbers is surprisingly more efficient than the one stated above.
Let's start with an example:
Assume : multiplicand = 42, multiplier = 19
[1]
4 2
X 1 9
------------
3 7 8
+ 4 2
------------
7 9 8
------------
The above example as we will observe trades inefficient additions for bitwise operations. First let us understand why this basic method works.
The principle used is distributive property:
( a + b ) * ( c + d ) = a*b + a*d + b*c + b*d
( 40 + 2 ) * ( 10 + 9 ) = 40*10 + 40*9 + 2*10 + 2*9 = 798
We first divide the multiplicand and multiplier according to their place value, multiply each individual component and finally add them all. By shedding the zeros and replacing them with shift operations, we start seeing a noticeable difference in terms of no. of addition operations. Here is an excellent link to better visualize this process : [
lattice multiplication ].
By now the reader should realize that implementing this in computers will be a performance-boost as we only deal with binary digits ( 0's and 1's ). We can skip an entire row where multiplier's digit is 0. Though we would have to do more shift operations every subsequent digit, this is not a major concern as most modern processors can perform this in O(1) time. See the following SO question for more detail : [
Is bit shifting O(1) or O(n)? ]. Carry look ahead adders can be used to reduce the propagation delay in addition operations.
But can we perform better ?
How ?
A careful reader would have realized by now that this game is all about minimizing the number of addition operations. In enters the Booth's algorithm. It works on the principle that by simplifying addition operations, we can reduce the no. of 1's and in turn reduce the no. of additions. We start with accumulator initialized to 0, multiplier ( m ) with its initial value and m
-1 to 0.
With the goal of multiplying multiplier( m ) * multiplicand( n ), all we do is check m
0 and m
-1 bits at each step, where m
0 is the leftmost bit of multiplier. We then follow a simple check: ( m
-1 - m
0 ).
We can observe from the above check:
| m-1 |
m0 |
m-1 - m0 |
| 1 |
1 |
0 |
| 0 |
0 |
0 |
| 1 |
0 |
1 |
| 0 |
1 |
-1 |
All we do now is multiply 'check' value with multiplicand and 2
a. Where 'a' is counter from 0 to no. of bits in m or n. If multiplicand and multiplier doesn't have the same number of bits, padding is required. Think of padding this way: when m : 11, n : 1010 --> m will become 0011 and no. of bits will be 4. After each step, we perform arithmetic right shift, just like we did in lattice multiplication.
Ok, so with all in place, let's try and see the final equation :
∑ ARS [ (m
k-1 - m
k) * n * 2
k ]
Where ARS is arithmetic right shift, n is multiplicand and m is the multiplier. The ARS outside square brackets indicates that arithmetic right shift has to be performed at each step.
NOTE: This equation is NOT in accordance with the mathematical convention, and I use it as a remembering technique.
You would observe that that the above equation will be equal to m*n, our result to be determined.
Helpful resources:
[1]
Wikipedia
[2]
https://bit.ly/2TvfUqF
Update (28/04/19): The [2] link is dead. Luckily I have a copy of the PDF file with me. If anyone is interested, I can mail it to them.
←


Transfer statistics
| |
Since startup |
Recent history |
| Data fetched: |
${dataInHuman} |
${dataHistInHuman} |
| Data served: |
${dataOutHuman} |
${dataHistOutHuman} |
Log analysis
| Period |
Cache efficiency |
| |
Requests |
|
Data |
| |
Hits |
Misses |
Total |
|
Hits |
Misses |
Total |
${statsRow}
Note: data table is created based on the current log file. Deviation from real request count is possible due to previous log file optimization.
Configuration instructions
Please visit any invalid download URL to see
configuration
instructions for users. For system administrators, read the
manual (or see system
documentation
online
resp. in the
local
filesystem).
File Type Pattern Tracing
This section provides a simple tool useful to identify new file name patterns which might be needed to configuration in order to handle new file types correctly. Please provide your findings to apt-cacher-ng author if they might be useful for other users.
Current value of pattern extensions:
SPfilePatternEx: ${cfg:SPfilePatternEx}
VfilePatternEx: ${cfg:VfilePatternEx}
PfilePatternEx: ${cfg:PfilePatternEx}
${footer}


|
PMSIS API
|
The PMSIS API is a set of low-level drivers which any operating system can implement to provide a common layer to upper layers. Together with the PMSIS BSP, it provides a full stack of drivers, allowing the development of applications portable across a wide range of operating systems.
All functions prefixed by pi_
can only be called from fabric-controller side while the ones prefixed by pi_cl_
can only be called from cluster side. Any exception to these rules is documented where it applies.
All functions on fabric-controller side are by default synchronous and are blocking the caller until the operation is done. All the functions suffixed by _async
are asynchronous and are not blocking the caller. The termination of such operations is managed with a pi_task_t
object, see PMSIS API documentation for more information.
Functions on cluster-side are by default synchronous but can also be asynchronous if the documentation of the function mentions it.


Today, it was the last day of the 19th Panhellenic Conference on Informatics (PCI 2015), which was held in Athens from 1-3 October 2015. In this conference we had the chance to discuss some initial results of our work in progress and especially some of the problems that we are facing, as (as announced in a previous post) we were presenting a short paper entitled “Automated Analysis of Greek Legislative Texts for Version Control: Limitations, Caveats and Challenges”.
The audience seemed to be as excited as we are on this work, which we believe it is an encouraging indicator of the importance of this project not only for the scientific community, but also for the general public.
The short paper as printed in the conference proceedings is available here.
Finally, the presentation can be downloaded from here.


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*************CHOOSE YOUR MEAL*************
BREAKFAST
LUNCH
SNACKS
DINNER
BILLING AMOUNT-:
BREAKFAST=RS 50
LUNCH=RS 60
SNACKS=RS 30
DINNER=RS 50
*****************************************


Here's a short list of commands you can invoke to interact with the Bunch SDK.
Sending over a message with the SDK and receive the message back from the SDK. An alert is displayed by default for now.
Switch the video layout to the default HUD template.
Switch to the fill layout where the video feeds will take up as much space in the most optimial way.
Region support to put the video in the top half of the screen.
Region support to put the video in the bottom half of the screen.
This allows the javascript to define the layout, customizing the video feed placement however the developer see fit. This is using the relative layout schema.
This allows the javascript to define the layout, customizing the video feed placement however the developer see fit. This is using the absolute layout schema.
SDK supports simple blank view and text view injectiongs on top of the video feed. This one injects 3 views: green bar, red bar, and a text view.


Shopping Zone
iBall Soundwave2 2.0 Multimedia Speakers
iBall Soundwave2 2.0 Multimedia Speakers, Black
Captcha Mini Mushroom Portable Bluetooth Mobile/Tablet Speaker
Captcha Mini Mushroom Portable Bluetooth Mobile/Tablet Speaker (Assorted Color)
Philips BT50B Wireless Portable Bluetooth Speaker
Philips BT50B Wireless Portable Bluetooth Speaker
Intex IT-850U 2.1 Channel Multimedia Speakers
Intex IT-850U 2.1 Channel Multimedia Speakers
Philips SPA-502.0 speaker with USB Plug
Philips SPA-502.0 speaker with USB Plug (Blue)
JBL Flip 2 Portable wireless speaker
JBL Flip 2 Portable wireless speaker with 5-hour battery and speakerphone technology, Black
boAt Stone 600
boAt Stone 600 Water Proof and Shock Proof Wireless Speaker (Black)


Bases: PyQt4.QtCore.QObject
Class that holds a value, using change() emits a signal.
There is no mandatory naming for instances of this Class, however ARTview components name variable according to the following table, using it is recommended:
| Name | Function | Valid values |
|---|---|---|
| Vradar | Hold radar open with pyart | pyart.core.Radar instance |
| Vgrid | Hold grid open or generated with pyart | pyart.core.Grid instance |
| Vcontainer | Alias to Vradar or Vgrid | Radar, Grid or None |
| Vfield | Name of a Field in radar file | string, preferencialy in radar.fields.keys(), but there is no garanty |
| Vtilt | Tilt (sweep) of a radar file | int between 0 and (number of sweeps) - 1 |
| VlevelZ | Vertical level of a grid file | int between 0 and nz - 1 |
| VlevelY | Latitudinal level of a grid file | int between 0 and ny - 1 |
| VlevelX | Longitudinal level of a grid file | int between 0 and nx - 1 |
| Vlevel | Alias to Vtilt, VlevelZ, VlevelY or VlevelX | positive integer |
| Vlims | Limits of display | dict containing keys: ‘xmin’, ‘xmax’, ‘ymin’, ‘ymax’ and holding float values |
| Vcmap | Colormap | dict containing keys: ‘vmin’ and ‘vmax’ holding float values and key ‘cmap’ holding colormap string name |
| Vgatefilter | Hold pyart GateFilter | pyart.filters.GateFilter instance or None |
| VplotAxes | Hold axes of Matplotlib figure | matplotlib.axes.Axes instance or None |
| VPathInteriorFunc | Hold auxiliar function | function like getPathInteriorValues or None |
Methods
| Variable.change(value[, strong]) | Change the Variable value and emit ‘ValueChanged’ signal. |
| Variable.update([strong]) | Emits the ‘ValueChanged’ signal without changings value. This is |
Attributes
Value of the Variable


{% extends 'base.html' %} {% block content %}
This is the best blog in town. See different categories or different posts by clicking the links below.


Salsa Dancing Dogs love Cats on Turtles
No animals where hurt in the making of this page.
And yes, IT WAS EASY !
Meaowwwwwwwwwwww
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Rufffffffffffffff
Barkkkkkkkkkkkkkk
Moooooooooooooooo
Bahahhahahahahaha
What does the fox say??
Ring ning ning ning ning n-ning!


| < Day Day Up > |
Working with NULLsWriting queries against tables that can contain nulls can be a confusing endeavor. Nulls represent missing or unknown information at the column level. If a column "value" can be null, it can mean one of two things: The attribute is not applicable for certain occurrences of the entity, or the attribute applies to all entity occurrences, but the information may not always be known. Of course, it could be a combination of these two situations, too. Nulls sometimes are inappropriately referred to as null "values." Using the term value to describe a null is inaccurate because the term null implies the lack of a value. Nulls would be better referred to as null "lack of values." Problems with NullsGiven that nulls are possible in DB2 tables, SQL must support three-valued logic (3VL) in order to retrieve data. To understand 3VL let's first define two-valued logic (2VL). With 2VL there are two possible answers to a query: true or false. Either the data was found or it was not found. However, if nulls exist, then there is a third possible answer: unknown. Most of us are not accustomed to working with 3VL, and so handling nulls in DB2 queries can be difficult to master. Here are some basic rules to remember:
The bottom line is that 3VL is hard to understand and hard to implement properly. NULL GuidelinesThe following guidelines are helpful to keep in mind as you design, build, and test your DB2 SQL statements. Use the Special NULL PredicateTo test for the existence of nulls, use the special predicate IS NULL in the WHERE clause of the SELECT statement. For example, the following is not a valid SQL predicate:
WHERE column = NULL
Instead, you must code this as WHERE column IS NULL. Furthermore, it is not valid to test whether a column is < NULL, <= NULL, > NULL, or >= NULL. These are all meaningless because null is the absence of a value. Do Not Try to Design Away the Null IssueBecause of the possible problems associated with nulls, it can be enticing to simply avoid using them. This simplistic thinking goes something like this: "If I create a database without using nulls then I do not need to worry about nulls in my queries." This is not true, though. It is possible to code a statement against tables with no nullable columns and return NULL as a result. For example, consider the following query: SELECT SUM(SALARY) FROM DSN8810.EMP WHERE LASTNAME = 'RAINES'; What will be returned by this query if there are no employees with the last name of RAINES? The answer is NULL. The impact of applying a column function (other than COUNT) to no data is not zero, but NULL. This is true even if the column upon which the function is operating is not-nullable (as is the case with the SALARY column of the EMP sample table). Understand Nulls and CollatingWhen a nullable column participates in an ORDER BY or GROUP BY clause, the returned nulls are grouped at the high end of the sort order. Nulls are considered to be equal when duplicates are eliminated by SELECT DISTINCT or COUNT (DISTINCT column). A unique index considers nulls to be equivalent and disallows duplicate entries because of the existence of nulls, unless the WHERE NOT NULL clause is specified in the index. Consider Using IS NOT DISTINCT FROMTwo columns, each set to NULL, are not considered equivalent when compared in a predicate. In other words, as stated previously, a NULL does not equal another NULL. When a nullable column participates in a predicate in the WHERE or HAVING clause, the nulls encountered cause the comparison to evaluate to unknown.
WHERE COL IS NOT DISTINCT FROM :HOSTVAR The predicate will be true when both COL and HOSTVAR are NULL, or when both COL and HOSTVAR are set to the same non-NULL value. When only COL or only HOSTVAR is NULL, but the other is set to a value, the result is false. Of course, the result is false when both COL and HOSTVAR are set to different values. Consider Nulls in Your Database DesignWhen you build your DB2 databases be sure to consider nulls and how they are used before setting any column as nullable. Keep in mind, too, that the default if nothing is specified is a nullable column. More information on defining and using nulls in DB2 tables is provided in Chapter 5. |
| < Day Day Up > |


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- p - Variable in class ml.regression.Regression
-
Number of independent variables.
- p - Variable in class ml.temporal.SurvivalScoreModel
-
- Pair<A extends java.lang.Comparable<? super A>,B extends java.lang.Comparable<? super B>> - Class in ml.utils
-
- Pair(Pair<A, B>) - Constructor for class ml.utils.Pair
-
- Pair(A, B) - Constructor for class ml.utils.Pair
-
- parentIdx - Variable in class ml.recommendation.util.Node
-
- pause(double) - Static method in class ml.utils.Time
-
PAUSE(n) pauses for n seconds before continuing, where n can also be a
fraction.
- PCA - Class in ml.subspace
-
Principal Component Analysis (PCA).
- PCA(int) - Constructor for class ml.subspace.PCA
-
Constructor.
- Pe - Variable in class ml.recommendation.util.Data
-
Event feature size.
- peek() - Method in class ml.utils.PriorityQueue
-
Returns the top element on the priority queue.
- phaseI(Matrix, Matrix, Matrix, Matrix) - Static method in class ml.optimization.GeneralQP
-
We demonstrate the implementation of phase I via primal-dual interior
point method to test whether the following problem is feasible:
- phaseII(Matrix, Matrix, Matrix, Matrix, Matrix, Matrix, Matrix) - Static method in class ml.optimization.GeneralQP
-
Phase II for solving a general quadratic programming problem formulated as
- PhaseIResult - Class in ml.optimization
-
- PhaseIResult(Matrix, double) - Constructor for class ml.optimization.PhaseIResult
-
- PhaseIResult(boolean, Matrix, double) - Constructor for class ml.optimization.PhaseIResult
-
- plus(Matrix) - Method in class la.matrix.DenseMatrix
-
- plus(double) - Method in class la.matrix.DenseMatrix
-
- plus(Matrix) - Method in interface la.matrix.Matrix
-
This + A.
- plus(double) - Method in interface la.matrix.Matrix
-
This + v.
- plus(Matrix) - Method in class la.matrix.SparseMatrix
-
- plus(double) - Method in class la.matrix.SparseMatrix
-
- plus(Vector) - Method in class la.vector.DenseVector
-
- plus(Vector) - Method in class la.vector.SparseVector
-
- plus(Vector) - Method in interface la.vector.Vector
-
Vector addition, i.e.
- plus(double[], double[]) - Static method in class ml.utils.ArrayOperator
-
Element-wise addition.
- plus(Vector, Vector, Vector) - Static method in class ml.utils.InPlaceOperator
-
res = V + U.
- plus(double[], double[], double[]) - Static method in class ml.utils.InPlaceOperator
-
res = V1 + V2.
- plus(Vector, Vector, double) - Static method in class ml.utils.InPlaceOperator
-
res = V + v.
- plus(Vector, double, Vector) - Static method in class ml.utils.InPlaceOperator
-
res = v + V.
- plus(Matrix, Matrix, Matrix) - Static method in class ml.utils.InPlaceOperator
-
res = A + B
- plus(Matrix, Matrix, double) - Static method in class ml.utils.InPlaceOperator
-
res = A + v;
- plus(Vector, Vector) - Static method in class ml.utils.Matlab
-
- plus(Matrix, Matrix) - Static method in class ml.utils.Matlab
-
- plus(Matrix, double) - Static method in class ml.utils.Matlab
-
- plus(double, Matrix) - Static method in class ml.utils.Matlab
-
- plusAssign(double[], double) - Static method in class ml.utils.ArrayOperator
-
Element-wise addition and assignment operation.
- plusAssign(double[], double, double[]) - Static method in class ml.utils.ArrayOperator
-
res += a * V.
- plusAssign(double[], double[]) - Static method in class ml.utils.ArrayOperator
-
Element-wise addition and assignment operation.
- plusAssign(double[][], double) - Static method in class ml.utils.ArrayOperator
-
res = res + v.
- plusAssign(Vector, double) - Static method in class ml.utils.InPlaceOperator
-
res += v.
- plusAssign(Vector, Vector) - Static method in class ml.utils.InPlaceOperator
-
res += V
- plusAssign(Vector, double, Vector) - Static method in class ml.utils.InPlaceOperator
-
res += a * V.
- plusAssign(Matrix, Matrix) - Static method in class ml.utils.InPlaceOperator
-
res = res + A
- plusAssign(Matrix, double) - Static method in class ml.utils.InPlaceOperator
-
res = res + v
- plusAssign(Matrix, double, Matrix) - Static method in class ml.utils.InPlaceOperator
-
res += a * A.
- poll() - Method in class ml.utils.PriorityQueue
-
Removes and returns the top element on the priority queue.
- postTraverse(Node, HashMap<Pair<Integer, Integer>, Integer>, TreeMap<Integer, Pair<Integer, Integer>>) - Static method in class ml.recommendation.util.Utility
-
Traverse and build indices for all the edges (pIdx, idx) on all the nodes
in the subtree rooted by parent node in post-order.
- pow(Matrix, double) - Static method in class ml.utils.Matlab
-
Compute element-wise exponentiation of a vector.
- pow(Vector, double) - Static method in class ml.utils.Matlab
-
Compute element-wise exponentiation of a vector.
- predict(Matrix) - Method in class ml.classification.Classifier
-
Predict the labels for the test data formated as an original data matrix.
- predict(double[][]) - Method in class ml.classification.Classifier
-
Predict the labels for the test data formated as an original 2D
double
array.
- predict(double[][][]) - Method in class ml.classification.MaxEnt
-
Predict labels for the test data formated as a 3D
double
array.
- predict(Matrix[]) - Method in class ml.classification.MaxEnt
-
Predict labels for the test data formated as a 1D
Matrix
array.
- predict(Matrix, String) - Static method in class ml.recommendation.FM
-
- predict(Matrix) - Static method in class ml.recommendation.FM
-
- predict(Vector[], String) - Static method in class ml.recommendation.STSR
-
- predict(Vector[]) - Static method in class ml.recommendation.STSR
-
- predict(Matrix, String) - Static method in class ml.recommendation.STSR
-
- predict(Matrix) - Static method in class ml.recommendation.STSR
-
- predict(Data, double[], TreeMap<Integer, Integer>, TreeMap<Integer, Integer>) - Static method in class ml.recommendation.util.Utility
-
- predict(int[], double[], HashMap<Integer, LinkedList<Integer>>) - Static method in class ml.recommendation.util.Utility
-
- predict(Matrix) - Method in class ml.regression.Regression
-
Predict the dependent variables for test data Xt.
- predict(double[][]) - Method in class ml.regression.Regression
-
Predict the dependent variables for test data Xt.
- predict(Matrix[][]) - Method in class ml.sequence.CRF
-
Predict the single best label sequence given the features for an
observation sequence by Viterbi algorithm.
- predict(int[]) - Method in class ml.sequence.HMM
-
Predict the best single state path for a given observation sequence
using Viterbi algorithm with logarithms.
- predict(Matrix, Matrix) - Method in class ml.temporal.ReflectedLogisticRegression
-
- predict(Matrix, Matrix) - Method in class ml.temporal.SurvivalScoreModel
-
- predict(Matrix, Matrix) - Method in class ml.temporal.TemporalLASSO
-
- predict(Matrix, Matrix) - Method in class ml.temporal.TemporalLogisticRegression
-
- predict2(int[]) - Method in class ml.sequence.HMM
-
Predict the best single state path for a given observation sequence
using Viterbi algorithm.
- predictColdStart(Data, double[], TreeMap<Integer, Integer>, TreeMap<Integer, Integer>) - Static method in class ml.recommendation.util.Utility
-
- predictColdStart(int[], double[], int[], HashMap<Integer, LinkedList<Integer>>, TreeMap<Integer, Integer>, TreeMap<Integer, Integer>) - Static method in class ml.recommendation.util.Utility
-
- predictLabelMatrix(Matrix) - Method in class ml.classification.AdaBoost
-
- predictLabelMatrix(Matrix) - Method in class ml.classification.Classifier
-
Predict the label matrix given test data formated as an
original data matrix.
- predictLabelMatrix(double[][]) - Method in class ml.classification.Classifier
-
Predict the label matrix given test data formated as an
original 2D double
array.
- predictLabelMatrix(Matrix[]) - Method in class ml.classification.MaxEnt
-
Predict the label matrix given test data formated as a 1D
Matrix
array.
- predictLabelMatrix(double[][][]) - Method in class ml.classification.MaxEnt
-
Predict the label matrix given test data formated as a
3D double
array.
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.AdaBoost
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.Classifier
-
Predict the label score matrix given test data formated as an
original data matrix.
- predictLabelScoreMatrix(double[][]) - Method in class ml.classification.Classifier
-
Predict the label score matrix given test data formated as an
original data matrix.
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LinearBinarySVM
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LinearMCSVM
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LogisticRegression
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LogisticRegressionByBoundConstrainedPLBFGS
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LogisticRegressionByNonlinearConjugateGradient
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.LogisticRegressionByNonnegativePLBFGS
-
- predictLabelScoreMatrix(Matrix) - Method in class ml.classification.MaxEnt
-
- predictLabelScoreMatrix(Matrix[]) - Method in class ml.classification.MaxEnt
-
Predict the label score matrix given test data formated as a
Matrix
array.
- predictLabelScoreMatrix(double[][][]) - Method in class ml.classification.MaxEnt
-
Predict the label score matrix given test data formated as a
3D double
array.
- preTraverse(Node, HashMap<Pair<Integer, Integer>, Integer>, TreeMap<Integer, Pair<Integer, Integer>>) - Static method in class ml.recommendation.util.Utility
-
Traverse and build indices for all the edges (pIdx, idx) on all the nodes
in the subtree rooted by parent node in pre-order.
- PrimalDualInteriorPoint - Class in ml.optimization
-
A Java implementation for the Primal-dual Interior-point
method.
- PrimalDualInteriorPoint() - Constructor for class ml.optimization.PrimalDualInteriorPoint
-
- print() - Method in class ml.recommendation.util.Tree
-
- print(String, String) - Method in class ml.recommendation.util.Tree
-
- print(Node, String, String, int) - Method in class ml.recommendation.util.Tree
-
- print(String) - Static method in class ml.utils.Printer
-
Print a string to the standard output (the screen).
- print(char) - Static method in class ml.utils.Printer
-
Print a character to the standard output (the screen).
- print(char[]) - Static method in class ml.utils.Printer
-
Print an array of characters to the standard output (the screen).
- print(int[]) - Static method in class ml.utils.Printer
-
Print an array of integers to the standard output (the screen).
- print(Object) - Static method in class ml.utils.Printer
-
Print an object to the standard output (the screen).
- printDenseMatrix(Matrix, int) - Static method in class ml.utils.Printer
-
Print a dense matrix with specified precision.
- printDenseMatrix(Matrix) - Static method in class ml.utils.Printer
-
Print a dense matrix.
- printDenseVector(Vector, int) - Static method in class ml.utils.Printer
-
Print a dense vector with specified precision.
- printDenseVector(Vector) - Static method in class ml.utils.Printer
-
Print a dense vector.
- Printer - Class in ml.utils
-
- Printer() - Constructor for class ml.utils.Printer
-
- printf(String, Object...) - Static method in class ml.utils.Printer
-
Write a formatted string to the standard output (the screen).
- println(String) - Static method in class ml.utils.Printer
-
Print a string to the standard output (the screen)
and then terminate the line.
- println(char[]) - Static method in class ml.utils.Printer
-
Print an array of characters to the standard output (the screen)
and then terminate the line.
- println(int[]) - Static method in class ml.utils.Printer
-
Print an array of integers to the standard output (the screen)
and then terminate the line.
- println(Object) - Static method in class ml.utils.Printer
-
Print an object and then terminate the line.
- println() - Static method in class ml.utils.Printer
-
- printMatrix(Matrix, int) - Static method in class ml.utils.Printer
-
Print a matrix with specified precision.
- printMatrix(Matrix) - Static method in class ml.utils.Printer
-
Print a matrix.
- printMatrix(double[], int) - Static method in class ml.utils.Printer
-
Print a column matrix with specified precision.
- printMatrix(double[]) - Static method in class ml.utils.Printer
-
Print a column matrix.
- printSparseMatrix(Matrix, int) - Static method in class ml.utils.Printer
-
Print a sparse matrix with specified precision.
- printSparseMatrix(Matrix) - Static method in class ml.utils.Printer
-
Print a sparse matrix.
- printSparseVector(Vector, int) - Static method in class ml.utils.Printer
-
Print a sparse vector with specified precision.
- printSparseVector(Vector) - Static method in class ml.utils.Printer
-
Print a sparse vector.
- printVector(double[], int) - Static method in class ml.utils.Printer
-
Print a row vector with specified precision.
- printVector(double[]) - Static method in class ml.utils.Printer
-
Print a row vector.
- printVector(Vector, int) - Static method in class ml.utils.Printer
-
Print a row vector with specified precision.
- printVector(Vector) - Static method in class ml.utils.Printer
-
Print a row vector.
- PriorityQueue<E> - Class in ml.utils
-
The PriorityQueue class represents a priority queue of generic elements.
- PriorityQueue(int, Comparator<E>) - Constructor for class ml.utils.PriorityQueue
-
Initializes an empty priority queue with the given initial capacity and
comparator.
- PriorityQueue(int) - Constructor for class ml.utils.PriorityQueue
-
Initializes an empty priority queue with the given initial capacity.
- PriorityQueue() - Constructor for class ml.utils.PriorityQueue
-
Initializes an empty priority queue.
- PriorityQueue(E[]) - Constructor for class ml.utils.PriorityQueue
-
Initializes a priority queue from the array of elements.
- Projection - Interface in ml.optimization
-
Compute proj_tC(X), which is defined by
proj_tC(x) := argmin_{u \in tC} 1/2 * || u - x ||^2.
- ProjL1 - Class in ml.optimization
-
Compute proj_tC(X) where C = {X: || X ||_1 <= 1}.
- ProjL1() - Constructor for class ml.optimization.ProjL1
-
- ProjL2 - Class in ml.optimization
-
Compute proj_tC(X) where C = {X: || X ||_2 <= 1}.
- ProjL2() - Constructor for class ml.optimization.ProjL2
-
- ProjLInfinity - Class in ml.optimization
-
Compute proj_tC(X) where C = {X: || X ||_{\infty} <= 1}.
- ProjLInfinity() - Constructor for class ml.optimization.ProjLInfinity
-
- prox - Static variable in class ml.optimization.AcceleratedProximalGradient
-
Proximity operator: prox_th(X).
- Prox - Class in ml.optimization
-
Compute prox_th(X) where h = 0.
- Prox() - Constructor for class ml.optimization.Prox
-
- ProximalMapping - Interface in ml.optimization
-
Compute prox_th(X), which is defined by
prox_th(x) := argmin_u 1/2 * || u - x ||^2 + t * h(u).
- ProxL1 - Class in ml.optimization
-
Compute prox_th(X) where h = lambda * || X ||_1.
- ProxL1(double) - Constructor for class ml.optimization.ProxL1
-
- ProxL2 - Class in ml.optimization
-
Compute prox_th(X) where h = lambda * || X ||_F.
- ProxL2(double) - Constructor for class ml.optimization.ProxL2
-
- ProxL2Square - Class in ml.optimization
-
Compute prox_th(X) where h = lambda * || X ||_F^2.
- ProxL2Square(double) - Constructor for class ml.optimization.ProxL2Square
-
- ProxLInfinity - Class in ml.optimization
-
Compute prox_th(X) where h = lambda * || X ||_{\infty}.
- ProxLInfinity(double) - Constructor for class ml.optimization.ProxLInfinity
-
- ProxPlus - Class in ml.optimization
-
Compute prox_th(X) where h = I_+(X).
- ProxPlus() - Constructor for class ml.optimization.ProxPlus
-
- Pu - Variable in class ml.recommendation.util.Data
-
User feature size.
- Pv - Variable in class ml.recommendation.util.Data
-
Item feature size.


All members of the research group, along with visitors, are required to agree with the following code of conduct. Additionally, we collectively agree to enforce this code. We expect cooperation from all members to help ensuring a safe environment for everybody.
The Quick Version
This research group is dedicated to providing a harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of group members or other colleagues in any form. Sexual language and imagery is not appropriate for any professional setting, including talks, workshops, parties, Twitter and other online media. Research group members violating these rules may be sanctioned or expelled from the group at the discretion of Kyle Niemeyer.

Group members asked to stop any harassing behavior are expected to comply immediately.
If a member engages in harassing behavior, other group members and Kyle Niemeyer may take any action they deem appropriate to stop this behavior, including warning the offender or expulsion from the group and sanctioning through official Oregon State University channels.
If you are being harassed, notice that someone else is being harassed, or have any other concerns, please contact Kyle Niemeyer immediately. Kyle is available to help group members contact security or local law enforcement, navigate official University reporting channels, or otherwise assist those experiencing harassment to feel safe in the research environment.
If Kyle is the cause of the concern or you would prefer he not be involved, official concerns can be addressed by contacting Nicole Thompson or Harriet Nembhard in the School of MIME, or the Oregon State University Equal Opportunity and Access office.
We expect research group members to follow these rules in all professional settings including the office, conferences, workshop venues, and group-related social events. We additionally expect members to treat each other professionally with respect to their work and workspaces, with constructive criticism, without dismissive behavior, and without disruption of shared working spaces.
Original source and credit
http://2012.jsconf.us/#/about & The Ada Initiative. Please help by translating or improving: http://github.com/leftlogic/confcodeofconduct.com. This work is licensed under a Creative Commons Attribution 4.0 International License. This text was adapted from that used in the Advanced Reactors And Fuel Cycles group led by Katy Huff, originally based on that used in the Data Intensive Biology Lab, developed by C. Titus Brown.


An Exception Has Occurred
Python Traceback
Traceback (most recent call last):
File "/usr/local/viewvc-install/viewvc-trunk-r2530/lib/viewvc.py", line 4531, in main
request.run_viewvc()
File "/usr/local/viewvc-install/viewvc-trunk-r2530/lib/viewvc.py", line 393, in run_viewvc
self.view_func(self)
File "/usr/local/viewvc-install/viewvc-trunk-r2530/lib/viewvc.py", line 2677, in view_checkout
fp, revision = request.repos.openfile(path, rev)
File "/usr/local/viewvc-install/viewvc-trunk-r2530/lib/vclib/svn/svn_repos.py", line 392, in openfile
raise vclib.Error("Path '%s' is not a file." % path)
Error: Path 'jakarta/ecs/tags/V1_0/src/java/org/apache/ecs' is not a file.


Class: kb.Factory
| Defined in: | src/knockback-core/knockback-factory.coffee |
Overview
Used to share the hierachy of constructors and create functions by path to allow for custom creation per Model attribute.
Examples:
Create an instance by path.
var factory = new kb.Factory();
factory.addPathMapping('bob.the.builder', kb.ViewModel);
view_model = factory.createForPath(new Backbone.Model({name: 'Bob'}), 'bob.the.builder'); // creates kb.ViewModel
Class Method Summary
- + (void) useOptionsOrCreate(options, obj, owner_path) Used to either register yourself with the existing factory or to create a new factory.
Instance Method Summary
- - (void) constructor(parent_factory) Constructor
- - (void) hasPath(path)
- - (void) addPathMapping(path, create_info)
- - (void) addPathMappings(factories, owner_path)
- - (void) creatorForPath(obj, path) If possible, creates an observable for an object using a dot-deliminated path.
Class Method Details
+ (void) useOptionsOrCreate(options, obj, owner_path)
Used to either register yourself with the existing factory or to create a new factory.
Constructor Details
- (void) constructor(parent_factory)
Instance Method Details
- (void) hasPath(path)
- (void) addPathMapping(path, create_info)
- (void) addPathMappings(factories, owner_path)
- (void) creatorForPath(obj, path)
If possible, creates an observable for an object using a dot-deliminated path.
Examples:
Create an instance by path.
var factory = new kb.Factory();
factory.addPathMapping('bob.the.builder', kb.ViewModel);
view_model = factory.createForPath(new Backbone.Model({name: 'Bob'}), 'bob.the.builder'); // creates kb.ViewModel


The agile movement attempts to move software development away from large presriptive processes and towards processes that are more responsive to change. Change is a fact of life and a realiy of modern business. We might as well embrace it. A number of methodologies have sprung up, each with their own characteristics.
The agile movement is defined in the Agile Manifesto. They promote short and frequent iterations for rapid feedback and responsiveness. Two techniques in particular have emerged from the agile movement. Refactoring applies successive transformations to the code to keep it as simple as possible while maintaining behavior. Test-Driven Development makes you write a test before the code which it verifies. Together, they have defined a new coding cycle for agile developers:
- write a test
- write just enough code to make the test pass
- refactor all the code and tests mercilessly
- repeat
In recent years, a movement for Software Craftsmanship has emerged, with a large intersection with the people in the agile movement.
Here are some of the more widely known methodologies:
- eXtreme Programming (XP)
- The one that started it all. It takes practices that make sense at first glance, an pushes them to their extreme. Highly controversial, many say that it is only glorified hacking.
- Lean Programming
- What modern manufacturing can teach software developers. Focus on activities that produce value and aggressively cut down on things that don't add value.
- I attended a presentation by lean programming proponent Mary Poppendieck.
- Scrum
- List features for roughly one month's worth of work, an run with it. For one month, the development team cannot be distracted and works in virtual isolation. Someone called it the planning game from XP without all the other, code-related practices.
- Agile Modeling
- Agile programming ideas applied to software modeling.


Have you ever wanted to surround a block of HTML with an a tag, for example a group of images. It is possible to do this because takes a block. According to apidock the syntax is:
link_to(url, html_options = {}) do
# name
end
In my idea situation i need to get the images for all the books in a certain genre and have them surrounded by one a tag. Reason I need this is because they are forming a slideshow. My code came out to be:
<% link_to(genre_path(genre)) do %>
<div class="home_gallery_images">
<% books = books.shuffle %>
<% for book in books %>
<%= image_tag(book.cover.url(:medium)) %>
<% end %>
<% end %>


CS 107 - Introduction to Scientific Computation
Spring 2018
Course Information
Course Information Page
Syllabus
Guide to CS1 Success
Homework Assignments
Readings
Moodle
site for homework submission
Homework #1
Homework #2
Homework #3
Homework #4
Homework #5
Homework #6
Homework #7
Homework #8
Homework #9
Homework #10
Homework #11
Homework #12
Homework #13
Online Resources
Matlab:
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Math majors: Don't Skip the Code


{% extends 'base.html' %} {% block content %} {% include 'navbars/navbar_measurement.html' %}
When we perform a measurement in a classical LC system, the probability distributions on the flux and on the charge collapse into dirac delta distributions. A classical measurement provides full certainty both in the measured domain and the domain coupled to it. Measuring the flux alone, gives all the information about the charge. After the measurement, the state of the L-C system is fully known for all time.
! insert classical simulation with measurements !
When we perform a measurement on a quantum system, we change the probability density and its corresponding wavefunction to reflect our new knowledge of the system. Here, we notice 2 very interesting effects:
You probably heard that in quantum mechanics, a measurement collapses a wavefunction. But what does that actually mean? Let's imagine a measurement instrument which is rated to measure current between -1 mA and 1 mA and gives a reading with 2 decimal numbers (i.e. accuracy 0.01 mA). If the device gives us a reading of 0.34 mA, we know that the true current value is somewhere between 0.335 mA and 0.345 mA. For the sake of simplicity, let's assume that there's a uniform probability distrubution for the true value of the current in that region. This means that every time we perform a measurement, we recieve a narrow probability distribution that looks like a square pulse. We can use this probability distribution to write down a collapsed wavefunction. Our code collapses the wavefunction as follows:
def simple_measure_1d(self, M: int, seed: int = 0):
np.random.seed(seed)
# initiate a table of probabilities to store the probability of the flux being found in each region
probability_table = []
# get del x
for xmin, xmax, N in self.ranges:
delx = (xmax - xmin)/(N-1)
# for every region:
for i in range(M):
inds = [j for j in range(round(i*len(self)/M), round((i+1)*len(self)/M))]
exclude_inds = list(set(range(len(self))) - set(inds))
# create a projection matrix x:
x = np.identity(len(self), dtype=np.float32)*delx
x[exclude_inds, exclude_inds] = 0
# find probability of flux being in that region by taking (phi^* | x | phi) and store in the probability table
prob = np.real(np.transpose(np.conjugate(self)) @ x @ self)
probability_table.append(prob)
# Use multinomial RV to get the resul of throwing a weighted cube.
# Multinomial returns an array of size p.size where the entry in each index is the number of times
# the cube landed on that face
probability_table = np.array(probability_table)/np.sum(probability_table) # normalize probabilities in case wavevctor isn't normalized
cube_throw = np.random.multinomial(1, probability_table)
region_number = int((np.where(cube_throw ==1)[0][0]))
# for some odd reason numpy returns the array index s a float which needs to be converted to an int for indexing
inds = [j for j in range(round(region_number*len(self)/M), round((region_number+1)*len(self)/M))]
exclude_inds = list(set(range(len(self))) - set(inds))
# collaps the wavefunction
self[inds] = 1
self[exclude_inds] = 0
# normalize it
self /= np.sqrt(np.sum(np.power(np.absolute(self), 2)*delx))
return self


Data sets from the book Generalized Linear Models with Examples in R by Dunn and Smyth.
| Version: | 1.0.0 |
| Published: | 2018-04-10 |
| Author: | Peter K. Dunn [cre,aut], Gordon K. Smyth [aut] |
| Maintainer: | Peter K. Dunn <pdunn2 at usc.edu.au> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | GLMsData results |
| Reference manual: | GLMsData.pdf |
| Package source: | GLMsData_1.0.0.tar.gz |
| Windows binaries: | r-devel: GLMsData_1.0.0.zip, r-release: GLMsData_1.0.0.zip, r-oldrel: GLMsData_1.0.0.zip |
| OS X binaries: | r-release: GLMsData_1.0.0.tgz, r-oldrel: GLMsData_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=GLMsData to link to this page.


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Welcome to BoilerPlate Generator
You are ready to start making your awesome looking websites


And He said to them, “Go into all the world and preach the gospel to every creature.
Whoever believes and is baptized will be saved, but whoever does not believe will be condemned.…
Every Sunday 10am at google meet (online)
Powerful Praise and worship
Real Word Of God with translations
Large Community and fellowship
Reaching the pershing souls


Please contact Colon on Twitter or Discord if you are interested in adding your private server to this list.
Please note that I am only adding relatively popular servers at this time. Servers which are inactive or have few levels/members will not be accepted.


Hey there, we are a full party planning company based off of This City, Ca. We have the pleasure of bringing you the best entertainment and event planning this side of Cali!
Whenever you need it, no matter the day, year round event planning around your schedule.
Whether it be kid's parties, quinceneras, birthday parties, or just any party type you can think of, we will help you throw it!
We do our best in accomedating to your schedule at a fast and Effecient rate!
Whenever you need it, no matter the day, year round event planning around your schedule.


Summary
Little engineering goes into the design and construction of ski and snowboard jumps in terrain parks at publicly accessible ski resorts. Catastrophic injuries and even deaths occur during skiing and snowboarding at these resorts. It is possible to design the landing surfaces of jumps such that the normal impact velocity on landing is capped at a safer value regardless of the jumper's takeoff speed and jump launch speed. These jump designs can still provide large maximum heights and flight durations for participant fun. We have designed a web application that laypeople can use to design and analyze ski jumps with specified equivalent fall height in mind.
| Theme | Sports Engineering | Current Researchers | |
| Last Worked On | August 2020 | Past Researchers | Bryn Cloud, Britt Tarien |
| Collaborators | Bryn Cloud, Mont Hubbard, Chris Brown |
Associated Research Products
Journal Articles:
- J. K. Moore and M. Hubbard, "skijumpdesign: A Ski Jump Design Tool for Specified Equivalent Fall Height," The Journal of Open Source Software, vol. 3, no. 28, p. 818, Aug. 2018, doi: 10.21105/joss.00818.
Conference Presentations:
- B. Cloud, B. Tarien, J. K. Moore, and M. Hubbard, "Accessible, Open-source Computational Analysis and Design of Terrain Park Ski Jumps," presented at the 23rd International Congress on Snow Sports Trauma and Safety, Squaw Valley, California, USA, Apr. 2019.
Software:
- Web application: http://www.skijumpdesign.info
- Ski jump simluation library and web application source code: https://gitlab.com/moorepants/skijumpdesign


Use the following input to query a Job. A successful query will return the job information for the given job ID.
{{job | json}}


Usage of the OpenUI5 name and icon
Feel free to spread the word about OpenUI5 and use our icon.
Please follow these few guidelines when doing so:
Name
The official name is OpenUI5 - capital O, capital UI, no spaces between Open and UI5.
If you use the correct name you help people recognize it and e.g. avoid the impression that we are building "Openui"
in version 5.
The short name UI5 is also fine, in particular when you explain something that is not specific to the Open Source
version, but also applies to SAPUI5.
Flavors: Fire and Water
The OpenUI5 icon comes in 2 flavors: Fire and Water.
The orange icon sits on black background, blue stands on white.
Colors: 2 Color Tracks
Main and Secondary colors are mostly meant for additional elements (e.g. header in a presentation, sticker on an image).
You can use them as background colors only if the icon is single colored (black for orange and white for blue).
Both tracks could be combined with neutral greys.
Layout: Horizontal and Vertical
Depending on the context, you have two layout options - horizontal and vertical.
Download the different versions in the Assets section below.
Assets
Web:
The .ZIP contains PNG files with transparent background in RGB color mode.
Those work best on screens, but they're okay for A4 print.
Print:
The .ZIP contains EPS files in CMYK color mode.
Use those if you're printing a shirt, mug or an umbrella.
Wallpapers:
Team Orange or Blue? Get your UI5 Wallpaper here.
Download WallpapersFormer Icon:
You can find the files for the former UI5 Icon here.
Please do not use it further for official purposes.
How to use?
DO:
- Use our icon for visual purposes (presentations, products, websites, merchandise...)
- Show a clear differentiation between your initiative/service/product and the OpenUI5 brand
- Clearly state that you are a partner or community project and link to our official website
DON'T:
- Pretend to be officially affiliated with OpenUI5 unless authorized by the OpenUI5 Team
- Publish and replicate content from our official website. Link to us instead if possible.
- Change the icon in any way (e.g. colors, shadow, glow, stretching)
- Register and operate official looking accounts or websites (e.g. registering the "OpenUI5" account in a social network)
- Mix it with other content.
3D Icon Model
Here you can download STL model files for use with 3D printers:
- Freestanding (flat bottom)
- Round
- Keychain (with hole in the top)
For any other legal or organizational questions please contact us at Please do NOT use this mail address for any technical questions.


The following is a number of interesting / useful solutions to problems, or recipes, written in Moya code.
The following one liner will retrieve the current price of Bitcoin (in USD) from https://www.bitstamp.net:
<echo>${(fromjson:get:"https://www.bitstamp.net/api/ticker/")['ask']}</echo>
How does this work? Well, the URL https://www.bitstamp.net/api/ticker/ contains a JSON object with the current Bitcoin prices. The get: modifier reads that request from the internet, and the fromjson: modifier converts the text in to a dictionary with a number of values. Finally the index operator ['ask']
looks up the value of 'ask'
which is the current asking price.