IT-4 batch is the most energetic , enthusiastic,fadoo,dramebaaaz,studious,friendly batch among all the cse batches. We are the group of engineers at pursuing our under-graduate degree from walchand college of engineering .Members of our batch possess a unique and different quality which makes our bond much stronger.We do live in unity .
Batch Representative[BR]
Most active member from boys.always ready for celebrating birthdays."#coder".Loves playing Pubg .#punctual #sincere
Animal Lover
The boy with a kind heart for girls.choclate boy of our batch,Also a great lover of dogs and animals too.
Studious
Dashing most handsome boy of the college.A cricket player.very studious
Editor
#Pj jokes #comments #gadi wala ladka Exactyl at 11:00am in class-"Rahul bhuk lagi yaar kahi khayal aahee ka and class sutyla kiti time aahe"
Nustya chengdya
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTIIIIIIIIIIIIMMMMMEEEEPPPPPPPASSSSSSSSSSSSSSSSSSSSSS
Don manus
#hacker #photographer #dosti nibhanewala Dosti ke liye kuch bhi(Bhai ke har ghoot me swag hai)
Exterme Sahbhya
Most studious one #assignment writer #studios(MECH+CSE+IT)
Foodie
" aee Rahulya paanii de mala mahit aahe tuzya kde pani aahe and eea challa bhuk lagli lipton la jau"
Damn Sincere
#busy #atttiiii... #silent #Studious #Hidden Photographer #picnic Boleto pura mahol karne ka par padhai bhi karni chahiye
Open Minded
# Kind hearted abhysu #pillu lover
Silent
NO COMMENTS
Hava Karnara
#friendly but jabse ladki mili dosti badme #bhai mera only Family planning
Studious
#merko kuch aata nahi re mera hua nahi yaar
Topper
#dictator in studies-word is enough "studious"
Helping Hands
Always ready for scholarship forms and caring towards everyone
Party Wala Bhai
Busy in his own world dragon ballzwee ka bhooooot bada fan
Studious
#studios #allrounder #dancer #lipton #bat bat pe party
Studious
#studios #allrounder #singer
IT-4 batch is the most energetic , enthusiastic,fadoo,dramebaaaz,studious,friendly batch among all the cse batches. We are the group of engineers at pursuing our under-graduate degree from walchand college of engineering .Members of our batch possess a unique and different quality which makes our bond much stronger.We do live in unity .
IT-4 batch is the most energetic , enthusiastic,fadoo,dramebaaaz,studious,friendly batch among all the cse batches. We are the group of engineers at pursuing our under-graduate degree from walchand college of engineering .Members of our batch possess a unique and different quality which makes our bond much stronger.We do live in unity .
IT-4 batch is the most energetic , enthusiastic,fadoo,dramebaaaz,studious,friendly batch among all the cse batches. We are the group of engineers at pursuing our under-graduate degree from walchand college of engineering .Members of our batch possess a unique and different quality which makes our bond much stronger.We do live in unity


| Total net profit | 5.25 | Gross profit | 13.9 | Gross loss | -8.65 |
| Profit factor | 1.61 | Expected payoff | 0.29 | ||
| Absolute drawdown | -2.98 | Maximal drawdown (%) | 3.57 (89.92%) | ||
| Total trades | 18 | Profit trades (% of total) | 14 (77.78%) | Loss trades (% of total) | 4 (22.22%) |
| Long positions (won %) | 9 (66.67%) | Short positions (won %) | 9 (88.89%) | ||
| Largest | profit trade | 1.63 | loss trade | -3.29 | |
| Average | profit trade | 0.99 | loss trade | -2.16 | |
| Minimum | profit trade | 0.31 | loss trade | -0.76 | |
| Maximum | take profit in pips | 15.7 | stop loss in pips | -33.7 | |
| Average | take profit in pips | 9.1 | stop loss in pips | -26.6 | |
| Minimum | take profit in pips | 3.1 | stop loss in pips | -7.1 | |
| Maximum | Reward-Risk | 1.7 | Duration in minutes | 4071 | |
| Average | Reward-Risk | 0.4 | Duration in minutes | 859.3 | |
| Minimum | Reward-Risk | 0.1 | Duration in minutes | 14 | |
| Maximum | consecutive wins (profit in money) | 7.0 (6.95) | consecutive losses (loss in money) | 2.0 (-3.57) | |
| Average | consecutive wins | 4.0 | consecutive losses | 1.0 |
| Total net profit | -1.6 | Gross profit | 6.29 | Gross loss | -7.89 |
| Profit factor | 0.8 | Expected payoff | -0.18 | ||
| Absolute drawdown | -3.29 | Maximal drawdown (%) | 2.97 (761.54%) | ||
| Total trades | 9 | Profit trades (% of total) | 6 (66.67%) | Loss trades (% of total) | 3 (33.33%) |
| Largest | profit trade | 1.63 | loss trade | -3.29 | |
| Average | profit trade | 1.05 | loss trade | -2.63 | |
| Minimum | profit trade | 0.71 | loss trade | -1.79 | |
| Maximum | take profit in pips | 15.7 | stop loss in pips | -33.7 | |
| Average | take profit in pips | 8.7 | stop loss in pips | -28.9 | |
| Minimum | take profit in pips | 4.5 | stop loss in pips | -17.2 | |
| Maximum | Reward-Risk | 0.6 | Duration in minutes | 4071.0 | |
| Average | Reward-Risk | 0.3 | Duration in minutes | 1169.7 | |
| Minimum | Reward-Risk | 0.2 | Duration in minutes | 33.0 | |
| Maximum | consecutive wins (profit in money) | 4.0 (3.68) | consecutive losses (loss in money) | 1.0 (-3.29) | |
| Average | consecutive wins | 2.0 | consecutive losses | 1.0 |
| Total net profit | 6.85 | Gross profit | 7.61 | Gross loss | -0.76 |
| Profit factor | 10.01 | Expected payoff | 0.76 | ||
| Absolute drawdown | 0.31 | Maximal drawdown (%) | 0.76 (21.23%) | ||
| Total trades | 9 | Profit trades (% of total) | 8 (88.89%) | Loss trades (% of total) | 1 (11.11%) |
| Largest | profit trade | 1.56 | loss trade | -0.76 | |
| Average | profit trade | 0.95 | loss trade | -0.76 | |
| Minimum | profit trade | 0.31 | loss trade | -0.76 | |
| Maximum | take profit in pips | 15.2 | stop loss in pips | -32.8 | |
| Average | take profit in pips | 9.5 | stop loss in pips | -24.4 | |
| Minimum | take profit in pips | 3.1 | stop loss in pips | -7.1 | |
| Maximum | Reward-Risk | 1.7 | Duration in minutes | 1308.0 | |
| Average | Reward-Risk | 0.5 | Duration in minutes | 548.9 | |
| Minimum | Reward-Risk | Duration in minutes | 14.0 | ||
| Maximum | consecutive wins (profit in money) | 4.0 (3.58) | consecutive losses (loss in money) | 1.0 (-0.76) | |
| Average | consecutive wins | 4.0 | consecutive losses | 1.0 |


See: Description
| Class | Description |
|---|---|
| AreaEffectCloudApplyEvent |
Called when a lingering potion applies it's effects.
|
| ArrowBodyCountChangeEvent |
Called when an arrow enters or exists an entity's body.
|
| BatToggleSleepEvent |
Called when a bat attempts to sleep or wake up from its slumber.
|
| CreatureSpawnEvent |
Called when a creature is spawned into a world.
|
| CreeperPowerEvent |
Called when a Creeper is struck by lightning.
|
| EnderDragonChangePhaseEvent |
Called when an EnderDragon switches controller phase.
|
| EntityAirChangeEvent |
Called when the amount of air an entity has remaining changes.
|
| EntityBreakDoorEvent |
Called when an
Entity breaks a door |
| EntityBreedEvent |
Called when one Entity breeds with another Entity.
|
| EntityChangeBlockEvent |
Called when any Entity changes a block and a more specific event is not available.
|
| EntityCombustByBlockEvent |
Called when a block causes an entity to combust.
|
| EntityCombustByEntityEvent |
Called when an entity causes another entity to combust.
|
| EntityCombustEvent |
Called when an entity combusts.
|
| EntityCreatePortalEvent | Deprecated |
| EntityDamageByBlockEvent |
Called when an entity is damaged by a block
|
| EntityDamageByEntityEvent |
Called when an entity is damaged by an entity
|
| EntityDamageEvent |
Stores data for damage events
|
| EntityDeathEvent |
Thrown whenever a LivingEntity dies
|
| EntityDropItemEvent |
Thrown when an entity creates an item drop.
|
| EntityEnterBlockEvent |
Called when an
Entity enters a block and is stored in that block. |
| EntityEnterLoveModeEvent |
Called when an entity enters love mode.
|
| EntityEvent |
Represents an Entity-related event
|
| EntityExhaustionEvent |
Called when a human entity experiences exhaustion.
|
| EntityExplodeEvent |
Called when an entity explodes
|
| EntityInteractEvent |
Called when an entity interacts with an object
|
| EntityPickupItemEvent |
Thrown when a entity picks an item up from the ground
|
| EntityPlaceEvent |
Triggered when a entity is created in the world by a player "placing" an item
on a block.
|
| EntityPortalEnterEvent |
Called when an entity comes into contact with a portal
|
| EntityPortalEvent |
Called when a non-player entity is about to teleport because it is in
contact with a portal.
|
| EntityPortalExitEvent |
Called before an entity exits a portal.
|
| EntityPoseChangeEvent |
Called when an entity changes its pose.
|
| EntityPotionEffectEvent |
Called when a potion effect is modified on an entity.
|
| EntityRegainHealthEvent |
Stores data for health-regain events
|
| EntityResurrectEvent |
Called when an entity dies and may have the opportunity to be resurrected.
|
| EntityShootBowEvent |
Called when a LivingEntity shoots a bow firing an arrow
|
| EntitySpawnEvent |
Called when an entity is spawned into a world.
|
| EntitySpellCastEvent |
Called when a
Spellcaster casts a spell. |
| EntityTameEvent |
Thrown when a LivingEntity is tamed
|
| EntityTargetEvent |
Called when a creature targets or untargets another entity
|
| EntityTargetLivingEntityEvent |
Called when an Entity targets a
LivingEntity and can only target
LivingEntity's. |
| EntityTeleportEvent |
Thrown when a non-player entity is teleported from one location to another.
|
| EntityToggleGlideEvent |
Sent when an entity's gliding status is toggled with an Elytra.
|
| EntityToggleSwimEvent |
Sent when an entity's swimming status is toggled.
|
| EntityTransformEvent |
Called when an entity is about to be replaced by another entity.
|
| EntityUnleashEvent |
Called immediately prior to an entity being unleashed.
|
| ExpBottleEvent |
Called when a ThrownExpBottle hits and releases experience.
|
| ExplosionPrimeEvent |
Called when an entity has made a decision to explode.
|
| FireworkExplodeEvent |
Called when a firework explodes.
|
| FoodLevelChangeEvent |
Called when a human entity's food level changes
|
| HorseJumpEvent |
Called when a horse jumps.
|
| ItemDespawnEvent |
This event is called when a
Item is removed from
the world because it has existed for 5 minutes. |
| ItemMergeEvent | |
| ItemSpawnEvent |
Called when an item is spawned into a world
|
| LingeringPotionSplashEvent |
Called when a splash potion hits an area
|
| PigZapEvent |
Stores data for pigs being zapped
|
| PigZombieAngerEvent |
Called when a Pig Zombie is angered by another entity.
|
| PlayerDeathEvent |
Thrown whenever a
Player dies |
| PlayerLeashEntityEvent |
Called immediately prior to a creature being leashed by a player.
|
| PotionSplashEvent |
Called when a splash potion hits an area
|
| ProjectileHitEvent |
Called when a projectile hits an object
|
| ProjectileLaunchEvent |
Called when a projectile is launched.
|
| SheepDyeWoolEvent |
Called when a sheep's wool is dyed
|
| SheepRegrowWoolEvent |
Called when a sheep regrows its wool
|
| SlimeSplitEvent |
Called when a Slime splits into smaller Slimes upon death
|
| SpawnerSpawnEvent |
Called when an entity is spawned into a world by a spawner.
|
| StriderTemperatureChangeEvent |
Called when a
Strider 's temperature has changed as a result of
entering or existing blocks it considers warm. |
| VillagerAcquireTradeEvent |
Called whenever a villager acquires a new trade.
|
| VillagerCareerChangeEvent | |
| VillagerReplenishTradeEvent |
Called when a villager's trade's maximum uses is increased, due to a player's
trade.
|
| Enum | Description |
|---|---|
| CreatureSpawnEvent.SpawnReason |
An enum to specify the type of spawning
|
| CreeperPowerEvent.PowerCause |
An enum to specify the cause of the change in power
|
| EntityDamageEvent.DamageCause |
An enum to specify the cause of the damage
|
| EntityDamageEvent.DamageModifier | Deprecated
This API is responsible for a large number of implementation
problems and is in general unsustainable to maintain.
|
| EntityExhaustionEvent.ExhaustionReason |
The reason for why a PlayerExhaustionEvent takes place
|
| EntityPotionEffectEvent.Action |
An enum to specify the action to be performed.
|
| EntityPotionEffectEvent.Cause |
An enum to specify the cause why an effect was changed.
|
| EntityRegainHealthEvent.RegainReason |
An enum to specify the type of health regaining that is occurring
|
| EntityTargetEvent.TargetReason |
An enum to specify the reason for the targeting
|
| EntityTransformEvent.TransformReason | |
| EntityUnleashEvent.UnleashReason | |
| VillagerCareerChangeEvent.ChangeReason |
Reasons for the villager's profession changing.
|
Copyright © 2021. All rights reserved.


--- layout: post title: 'Google''s Eric Schmidt on mobile' date: 2006-05-26 00:00:00 category: mobile ---
Google's Eric Schmidt: "Mobile phones are cheaper than PCs, there are three times more of them, growing at twice the speed, and they increasingly have internet access. What is more, the World Bank estimates that more than two-thirds of the world’s population lives within range of a mobile phone network. Mobile is going to be the next big internet phenomenon. It holds the key to greater access for everyone – with all the benefits that entails."


Rice holds off North Texas 20-14
HOUSTON (AP) - Charlie Booker and Aston Walter had touchdown runs in the first half and Rice held off North Texas for a 20-14 victory on Saturday.
The Owls (2-9, 2-5 Conference USA) led 20-0 at halftime.
North Texas (4-7, 3-4) capped the scoring on Tre Siggers’ 1-yard touchdown run with 7:32 to play. Larry Nixon III forced a fumble on the ensuing kickoff and Evan Johnson recovered the ball at the Rice 23. But the Mean Green couldn’t capitalize on the turnover when Mason Fine threw an incomplete pass on fourth-and-12 at the Owls 15.
Walter bulled into the end zone from the 1, Booker scored on an 8-yard run, and Chris Barnes kicked two field goals for Rice. Booker finished with 78 yards rushing on 22 carries.
Fine was 17 of 32 for 163 yards passing and had a 10-yard touchdown run in the third quarter for the Mean Green.
Sign up for Daily Newsletters
Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


No Description
No Dependencies
NettoRanking: A ranking variant which sorts players by wins and netto points, in this order.
simply return the stored size
Returns: the size
resize the internal arrays
Argument: size
new size
Returns: {Netto} this
return an object with ranking-specific data.
Returns: {Object} the return object
Add the result of a game to the ranking table.
Argument: result
the result
Returns: {Netto} this
remove the result of a game from the ranking table
Argument: result
the result
Returns: {Netto} this
Correct the result of a game.
Argument: correction
the correction
Returns: {Netto} this
get a copy of the applied corrections
Returns: copy of the array of corrections
whether the game took place
Argument: game
the game in question
Returns: {Boolean} true if the game is likely to have been added, false otherwise
stores the current state in a blob
Returns: the blob


A driver creates a ride offer on the application for a particular destination.
A passenger request for a available ride offers to a destination, and waits for the driver to either accept or reject the offer.
After successful request has been accepted. You can enjoy the ride with a new company and save money.


{% extends "layout.html" %}
{% block content %}
Statistics for {{ data.username }}
When playing white:
| Opening |
Played (%) |
{% for item in data.white.win %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
| Opening |
Played (%) |
{% for item in data.white.lost %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
| Opening |
Played (%) |
{% for item in data.white.draw %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
When playing black:
| Opening |
Played (%) |
{% for item in data.black.win %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
| Opening |
Played (%) |
{% for item in data.black.lost %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
| Opening |
Played (%) |
{% for item in data.black.draw %}
|
{{item[0]}}
|
{{item[1]}}
|
{% endfor %}
{% endblock content %}


msgpack.download(), msgpack.upload()
Last downloaded data length:
0
bytes
add decode log
Test1 (without WebWorkers)
Choose Download data
Upload Last data
Download Last data
->
->
Test2 (with WebWorkers)
Choose Download data
Upload Last data
Download Last data
->
->


| Modifier and Type | Method | Description |
|---|---|---|
CertifiedDecision |
ApplicationState.getCertifiedDecision(ServerViewController controller) |
Retrieves the certified decision for the last das present in this object
|
| Modifier and Type | Field | Description |
|---|---|---|
protected java.util.HashMap<java.lang.Integer,CertifiedDecision> |
BaseStateManager.senderProofs |
| Modifier and Type | Method | Description |
|---|---|---|
CertifiedDecision |
CSTState.getCertifiedDecision(ServerViewController controller) |
Retrieves the certified decision for the last das present in this object
|
| Modifier and Type | Method | Description |
|---|---|---|
void |
ServiceReplica.receiveMessages(int[] consId,
int[] regencies,
int[] leaders,
CertifiedDecision[] cDecs,
TOMMessage[][] requests) |
| Modifier and Type | Method | Description |
|---|---|---|
CertifiedDecision |
LCManager.getHighestLastCID(int ts) |
Gets the highest valid last CID related to the given timestamp
|
| Modifier and Type | Method | Description |
|---|---|---|
java.util.HashSet<CertifiedDecision> |
LCManager.getLastCIDs(int regency) |
Get the set of last CIDs related to a regency
|
| Modifier and Type | Method | Description |
|---|---|---|
void |
LCManager.addLastCID(int regency,
CertifiedDecision lastCID) |
Keep last CID from an incoming SYNC message
|
boolean |
LCManager.hasValidProof(CertifiedDecision cDec) |
| Modifier and Type | Method | Description |
|---|---|---|
void |
LCManager.setLastCIDs(int regency,
java.util.HashSet<CertifiedDecision> lasts) |
Defines the set of last CIDs related to a regency
|
| Modifier and Type | Method | Description |
|---|---|---|
CertifiedDecision |
DefaultApplicationState.getCertifiedDecision(ServerViewController controller) |
Retrieves the certified decision for the last das present in this object
|
Copyright © 2018. All rights reserved.


| Package | Description |
|---|---|
| adept.kbapi |
This package consists of all classes and interfaces related to the Adept Knowledge Base v3.
|
| adept.kbapi.sparql |
Contains utility classes required to generate SPARQL queries to access and modify the KB triple store.
|
| adept.kbapi.sql |
Contains utility classes required to generate SQL queries to access and modify the KB metadata store.
|
| adept.utilities |
General KB utility classes.
|
| Class and Description |
|---|
| KB
The most important class for using the KB API is
adept.kbapi.KB.
|
| KBBelief
The class KBBelief represents a Belief relation within the KB.
|
| KBBelief.InsertionBuilder
Class for inserting a KBBelief into the KB.
|
| KBBelief.UpdateBuilder
Class for updating the provenances or confidence of this belief.
|
| KBConfigurationException |
| KBDate
Class for representing Dates in the KB.
|
| KBDate.InsertionBuilder
Class for inserting KBDates into the KB.
|
| KBDate.UpdateBuilder
Class for updating a KBDate.
|
| KBEntity
The Class KBEntity represents an entity saved in the knowledge base.
|
| KBEntity.InsertionBuilder |
| KBEntity.UpdateBuilder
Builder for updating the KBEntity.
|
| KBEntityMentionProvenance
A subclass of
KBTextProvenance for entity-mention type provenances. |
| KBEntityMentionProvenance.InsertionBuilder |
| KBEvent
Class KBEvent represents Events that have been saved in the KB.
|
| KBEvent.InsertionBuilder
The InsertionBuilder class for Events.
|
| KBEvent.UpdateBuilder
The UpdateBuilder class for events.
|
| KBGenericThing
Class for representing KB things which are mainly represented by a class and
a string reference, i.e, Crimes, Sentences, Weapons, etc.
|
| KBGenericThing.InsertionBuilder
InsertionBuilder class for inserting a
KBGenericThing |
| KBGenericThing.UpdateBuilder |
| KBMentalState |
| KBMentalState.InsertionBuilder |
| KBMentalState.UpdateBuilder |
| KBNumber
This class represents numbers in the KB.
|
| KBNumber.InsertionBuilder
Class defines the InsertionBuilder for a KBNumber object.
|
| KBNumber.UpdateBuilder
Update builder for KBNumber objects.
|
| KBObjectBuilder |
| KBOntologyMap
A simple mapping between one ontology and another.
|
| KBOntologyModel
Contains information about the current ontology for use in validation.
|
| KBOpenIEArgument
The Class KBOpenIERelation represents a fully loaded, immutable OpenIE relation.
|
| KBOpenIEArgument.InsertionBuilder
Class defines the InsertionBuilder for a KBOpenIEArgument object.
|
| KBOpenIERelation
The Class KBOpenIERelation represents a fully loaded, immutable OpenIE relation.
|
| KBOpenIERelation.InsertionBuilder
Class defines the InsertionBuilder for a KBOpenIERelation object.
|
| KBParameters
Reads the KBParameters.xml configuration file, and sets all KB parameters at
the outset.
|
| KBPredicateArgument
Superclass for all KB types which can be the argument of any predicate.
|
| KBPredicateArgument.InsertionBuilder
Default InsertionBuilder class, which holds provenances that will be
inserted when the object is inserted.
|
| KBPredicateArgument.InsertionBuilderWithConfidence
Extension to default InsertionBuilder for objects which include a
confidence value.
|
| KBPredicateArgument.UpdateBuilder
Default UpdateBuilder class, allows the addition and removal of
provenances.
|
| KBPredicateArgument.UpdateBuilderWithConfidence
UpdateBuilder class which additionally allows the updating of the
confidence value.
|
| KBProvenance |
| KBProvenance.InsertionBuilder |
| KBProvenance.UpdateBuilder |
| KBQueryException |
| KBRelation
The Class KBRelation represents a fully loaded, immutable relation.
|
| KBRelation.AbstractInsertionBuilder
Class InsertionBuilder for assembling the data required to insert a new
KBRelation object. |
| KBRelation.AbstractUpdateBuilder |
| KBRelation.InsertionBuilder |
| KBRelation.UpdateBuilder |
| KBRelationArgument
This class represents the link between a KBRelation and one of its arguments.
|
| KBRelationArgument.InsertionBuilder
Class for creating a new KBRelationArgument.
|
| KBRelationArgument.UpdateBuilder
UpdateBuilder class for Relation Arguments.
|
| KBSentiment
The Class KBSentiment represents a pointer to a Knowledge Base Entity
uniquely identified by KB URI and source KB type.
|
| KBSentiment.InsertionBuilder
Class for inserting a KBSentiment into the KB.
|
| KBSentiment.UpdateBuilder
Class for updating the provenances or confidence of this sentiment.
|
| KBTemporalSpan |
| KBTemporalSpan.InsertionBuilder |
| KBTemporalSpan.UpdateBuilder |
| KBTextProvenance
A textual provenance for a KB Object.
|
| KBTextProvenance.InsertionBuilder |
| KBTextProvenance.UpdateBuilder
Allows only the update of the KBID of the parent Entity of this KBTextProvenance.
|
| KBThing |
| KBUpdateException |
| LRUCache |
| SPARQLService |
| Class and Description |
|---|
| KBEntity.InsertionBuilder |
| KBEntity.UpdateBuilder
Builder for updating the KBEntity.
|
| KBGenericThing.InsertionBuilder
InsertionBuilder class for inserting a
KBGenericThing |
| KBGenericThing.UpdateBuilder |
| KBQueryException |
| Class and Description |
|---|
| KBConfigurationException |
| KBOpenIEArgument.InsertionBuilder
Class defines the InsertionBuilder for a KBOpenIEArgument object.
|
| KBOpenIERelation.InsertionBuilder
Class defines the InsertionBuilder for a KBOpenIERelation object.
|
| KBParameters
Reads the KBParameters.xml configuration file, and sets all KB parameters at
the outset.
|
| KBProvenance |
| Class and Description |
|---|
| KB
The most important class for using the KB API is
adept.kbapi.KB.
|
| KBConfigurationException |
| KBEntity
The Class KBEntity represents an entity saved in the knowledge base.
|
| KBOntologyMap
A simple mapping between one ontology and another.
|
| KBParameters
Reads the KBParameters.xml configuration file, and sets all KB parameters at
the outset.
|
| KBPredicateArgument
Superclass for all KB types which can be the argument of any predicate.
|
| KBQueryException |
| KBRelation
The Class KBRelation represents a fully loaded, immutable relation.
|
| KBRelationArgument
This class represents the link between a KBRelation and one of its arguments.
|
| KBThing |
| KBUpdateException |
| RemoteSPARQLService |
Copyright © 2012–2017 Raytheon BBN Technologies Corp.. All rights reserved.


To this point we have discussed how to scan covert lines and curves. Suppose that we want to do more than just draw outline figures. We could fill the interior of objects with lines using our line drawing algorithm, or we could draw concentric circles or ellipses with increasingly smaller radii until it appeared to be solid. But this approach is wasteful.
The next class of scan conversion algorithms that we will discuss are the
area-filling algorithms. These algorithms operate on a raster while
completely unaware of any other primatives previously drawn.
The first algorithm, called the parity-fill algorithm, is very simple.
The parity fill algorithm has some notable disadvantages.
Despite all its problems the parity fill algorithm is very popular is some applications, such as fonting and simple polygon drawing. Some reasons are
The first such method that we will discuss is called the boundary-fill algorithm. The boundary-fill method requires the coordinate of a starting point, a fill color, and a background color as arguments.
public void boundaryFill(int x, int y, int fill, int boundary) { if ((x < 0) || (x >= raster.width)) return; if ((y < 0) || (y >= raster.height)) return; int current = raster.getPixel(x, y); if ((current != boundary) & (current != fill)) { raster.setPixel(fill, x, y); boundaryFill(x+1, y, fill, boundary); boundaryFill(x, y+1, fill, boundary); boundaryFill(x-1, y, fill, boundary); boundaryFill(x, y-1, fill, boundary); } }Note: that this is a recusive routine. Each invocation of boundaryFill( ) may call itself four more times.
The logic of this routine is very simple. If we are not either on a boundary
or already filled we first fill our point, and then tell our neighbors to fill
themselves.
Left-button click inside one of the regions to start the fill process. I might suggest a starting with a small region. Click the right button to reset the image to its original state
What has happened here? Why is the drawing happening in the order shown? (Hint: consider the algorithm as a tree, with the current pixel as a node and neighoring pixels as ancestors).
Here's the algorithm at full speed.
Left-button click inside one of the regions to start the fill process. Click the right button to reset the image to its original state
public void floodFill(int x, int y, int fill, int old) { if ((x < 0) || (x >= raster.width)) return; if ((y < 0) || (y >= raster.height)) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); floodFill(x+1, y, fill, old); floodFill(x, y+1, fill, old); floodFill(x-1, y, fill, old); floodFill(x, y-1, fill, old); } }
Here's the algorithm in action
Left-button click inside one of the regions to start the fill process. Click the right button to reset the image to its original state
public void fillFast(int x, int y, int fill) { if ((x < 0) || (x >= raster.width)) return; if ((y < 0) || (y >= raster.height)) return; int old = raster.getPixel(x, y); if (old == fill) return; raster.setPixel(fill, x, y); fillEast(x+1, y, fill, old); fillSouth(x, y+1, fill, old); fillWest(x-1, y, fill, old); fillNorth(x, y-1, fill, old); } private void fillEast(int x, int y, int fill, int old) { if (x >= raster.width) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); fillEast(x+1, y, fill, old); fillSouth(x, y+1, fill, old); fillNorth(x, y-1, fill, old); } } private void fillSouth(int x, int y, int fill, int old) { if (y >= raster.height) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); fillEast(x+1, y, fill, old); fillSouth(x, y+1, fill, old); fillWest(x-1, y, fill, old); } } private void fillWest(int x, int y, int fill, int old) { if (x < 0) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); fillSouth(x, y+1, fill, old); fillWest(x-1, y, fill, old); fillNorth(x, y-1, fill, old); } } private void fillNorth(int x, int y, int fill, int old) { if (y < 0) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); fillEast(x+1, y, fill, old); fillWest(x-1, y, fill, old); fillNorth(x, y-1, fill, old); } }And here is the working algorithm.
Left-button click inside one of the regions to start the fill process. Click the right button to reset the image to its original state
Here's the code for an eight-connected flood fill.
public void floodFill8(int x, int y, int fill, int old) { if ((x < 0) || (x >= raster.width)) return; if ((y < 0) || (y >= raster.height)) return; if (raster.getPixel(x, y) == old) { raster.setPixel(fill, x, y); floodFill8(x+1, y, fill, old); floodFill8(x, y+1, fill, old); floodFill8(x-1, y, fill, old); floodFill8(x, y-1, fill, old); floodFill8(x+1, y+1, fill, old); floodFill8(x-1, y+1, fill, old); floodFill8(x-1, y-1, fill, old); floodFill8(x+1, y-1, fill, old); } }Sometimes the eight-connected algorithm gives you exactly what you want. In the following example try a 8-way connected flood-fill of the antelope.
Left-button click inside one of the regions to start the fill process. Click the right button to reset the image to its original state
Left-button click inside one of the regions to start the fill process. Click the right button to reset the image to its original state


Rooms oh fully taken by worse do. Points afraid but may end law lasted. Was out laughter raptures returned outweigh. Luckily cheered colonel me do we attacks on highest enabled. Tried law yet style child. Bore of true of no be deal. Frequently sufficient in be unaffected. The furnished she concluded depending procuring concealed.
He as compliment unreserved projecting. Between had observe pretend delight for believe. Do newspaper questions consulted sweetness do. Our sportsman his unwilling fulfilled departure law. Now world own total saved above her cause table. Wicket myself her square remark the should far secure sex. Smiling cousins warrant law explain for whether.


mntyjs Moving Ball Demo
Ball count:
Control
Activate Collision
(Experimental - tested in Firefox and IE 11 - does not work in Chrome)
Size
Age
Speed
Color
red
green
blue
orange
silver
purple
fuchsia
bisque
brown
Add
Demonstrated Features
Using multiple clones of same plugin (every ball is using the same plugin)
Inheritance: The BallCollide plugin extends the Ball plugin with the collision detection
Create and Destroy process of plugins
Configuration due the data-attribute
Communication between Plugins about the system message bus


Package it.polimi.ingsw.model.soloMode
Class LorenzoIlMagnifico
java.lang.Object
public class LorenzoIlMagnifico extends Observable<GameEvent>
-
Field Summary
Fields Modifier and Type Field Description private int
blackCross
The marker of Lorenzo's position on the Faith Track.private FaithTrack
faithTrack
The player'sFaithTrack
instance.private int
passedSection
The index of the last Vatican Report section passed by Lorenzo.private SoloMode
soloGame
The instance of the ongoing game. -
Constructor Summary
Constructors Constructor Description LorenzoIlMagnifico(FaithTrack faithTrack, SoloMode soloGame)
Constructs an instance of Lorenzo il Magnifico from the given parameters. -
Method Summary
Modifier and Type Method Description int
getBlackCross()
int
getPassedSection()
void
moveAndShuffle()
Moves black cross forward by one position, then refresh the stack of tokens.boolean
moveBlackCross(int pos)
Moves Lorenzo's cross forward on player's Faith Track.void
throwDevCards(ColorCard color)
Perform Lorenzo's action of discarding two development cards from decks.Methods inherited from class it.polimi.ingsw.Observable
addObserver, notify, removeObserver
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Field Details
-
blackCross
private int blackCrossThe marker of Lorenzo's position on the Faith Track. -
passedSection
private int passedSectionThe index of the last Vatican Report section passed by Lorenzo. -
faithTrack
The player'sFaithTrack
instance. -
soloGame
The instance of the ongoing game.
-
-
Constructor Details
-
LorenzoIlMagnifico
Constructs an instance of Lorenzo il Magnifico from the given parameters.- Parameters:
faithTrack
- the faith track of the player.soloGame
- the instance of the ongoing game.
-
-
Method Details
-
moveBlackCross
public boolean moveBlackCross(int pos)Moves Lorenzo's cross forward on player's Faith Track.- Parameters:
pos
- indicates number of cells that has been covered.- Returns:
- whether Lorenzo has activated a Vatican Report.
-
throwDevCards
Perform Lorenzo's action of discarding two development cards from decks. Player loses the possibility to buy them, If cards of a certain color finish, notifies Game instance that the event occurred.- Parameters:
color
- represents color of the cards to be discarded.
-
moveAndShuffle
public void moveAndShuffle()Moves black cross forward by one position, then refresh the stack of tokens. -
getBlackCross
public int getBlackCross()- Returns:
- Lorenzo's position on the faith track.
-
getPassedSection
public int getPassedSection()- Returns:
- the index of the last Vatican Report section passed by Lorenzo.
-


Bosnian police arrest at least 8 in soccer match-fixing case
by The Associated PressSARAJEVO, Bosnia-Herzegovina (AP) — Referees and soccer officials were among those arrested in Bosnia on Monday in a match-fixing investigation into the country’s second division, prosecutors said.
Suspects are facing charges of organized crime, bribery and abuse of position, the Bosnian Prosecutor’s Office said in a statement.
The suspects have been implicated in “demanding and receiving gifts and other benefits” to fix the outcome of matches during the 2018-19 season, the statement added.
Police searched several locations throughout the country as part of the ongoing operation. Bosnian media say at least eight people have been detained, including prominent referees, club managers and other officials.
The Bosnian soccer federation said it fully supports the investigation and is ready to help any way it can, adding the damage made is “immeasurable.”
The arrests come while UEFA is looking to create a multi-national agency that would help coordinate match-fixing investigations.
___
More AP soccer https://apnews.com/Soccer and https://twitter.com/AP_Sports
The Associated Press


Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Click Link and open another page in a modal window


CHAPTER 2.3: File Transfer: FTP
In a typical FTP session:
- The user interacts with FTP through an FTP user agent.
- The user provides the hostname of the remote host, causing the FTP client process in the local host to establish a TCP connection with the FTP server process in the remote host.
- The user then provides the user identification and password, which are sent over the TCP connection as part of FTP commands
- Once the server has authorized the user, the user copies one or more files stored in the local file system into the remote file system (or vice versa).
TCP uses two parallel TCP connections to transfer a file, a control connection and a data connection.
- The control connection (port 21) is used for sending control information between the two hosts - information such as user indetification, password, commands to change remote directory, and commands to "put" and "get" files.
- The data connection (port 20) is used to actually send a file
Because FTP uses a separate control connection, FTP is said to send its control information out-of-band. Unlike FTP, HTTP sends request and response header lines into the same TCP connection that carries the transferred file itself. For this reason, HTTP is said to send its control information in-band.
The control connection remains open throughout the duration of the user session, but a new data connection is created for each file transferred within a session.
Throughout a session, the FTP server must maintain state about the user. Keeping track of this state information for each ongoing user session significantly constrains the total number of sessions that FTP can maintain simultaneously.
The commands, from client to server, and replies, from server to client, are sent across the control connection in 7-bit ASCII format. Some of the more common commands are given below:
- USER username: Used to send the user identification to the server.
- PASS password: Used to send the user password to the server.
- LIST: Used to ask the server to send back a list of all the files in the current remote directory. The list of files is sent over a (new and non-persistent) data connection rather than the control TCP connection.
- RETR filename: Used to retrieve (that is, get) a file from the current directory of the remote host. This command causes the remote host to initiate a data connection and to send the requested file over the data connection.
- STOR filename: Used to store (that is, put) a file into the current directory of the remote host.
Each command is followed by a reply, sent from server to client. The replies are three-digit numbers, with an optional message following the number. Some typical replies, along with their possible messages, are as follows:
- 331 Username OK, password required
- 125 Data connection already open; transfer starting
- 425 Can’t open data connection
- 452 Error writing file


Compare GitHub contributions, visually
Track your teammates' contributions for the project
Check coding activities of your friends


HANGMAN
Japan Style
Press Any To Begin!
Current Word:
Number Of Guesses Remaining:
5
Guessed Letters:
Wins:
0


Google Earth Enterprise Documentation Home | Troubleshooting and error messages
Unable to find a suitable resource provider
Error message
Unable to find a suitable resource provider: no CPU(s) is available to start the task <task_name>
Description
This error typically occurs when the system is building and no more CPUs are available for the build task. This error can also occur if there are fewer CPUs (maximum number of concurrent tasks/jobs) assigned to Fusion (specifically, to a Fusion machine, also called a geresourceprovider
) than the minimum CPU setting for a task rule.
Resolution
In response to the error, you can do one of the following:
- Wait for the other build or task to finish.
- Assign more CPUs (maximum number of concurrent tasks/jobs) to Fusion.
You can use the tool
geselectassetroot --assetroot path --numcpus
to assign more CPUs. For example:geselectassetroot --assetroot /gevol/assets --numcpus 8
- If the task can complete with fewer CPUs, decrease the minimum CPU setting for the task rule.


Memory
This tests that we can inspect the Wasm memory in the linear memory inspector.
Steps
- Open DevTools
- Locate the Wasm function
get
from the memory.wasm
module and set a breakpoint on the i32.load
line
- Reload the page
- Breakpoint should hit the new breakpoint
- Now look at the Scope in the DevTools and right click on the
imports.memory
- Select "Reveal in Memory Inspector panel"
- The linear memory inspector should open
- Inspect memory and navigate


Teacher suspended for caning students
At Alangariyur village in Bhavani
by Staff ReporterA mathematics teacher at the Panchayat Union Middle School at Alangariyur village in Ammapettai block in Bhavani Taluk was placed under suspension on Tuesday, after parents staged a protest accusing him of caning students.
S. Selvaraj (35) of Bhavani worked as a BT Assistant in the school and handled Classes VII to VIII. It is alleged that Selvaraj caned 12 students of Class VII for not doing their homework. After the students started crying, people in the nearby area gathered at the school. The students complained to their parents, following which they were taken to a hospital. Later, the parents staged a protest demanding action against the teacher.
Bhavani District Education Officer K. Palani and Ammapettai Police arrived at the school and held talks with the parents who wanted the teacher to be suspended. Later, the DEO held inquiries with the teacher and the headmaster and issued an order placing Mr. Selvaraj under suspension.


Increase temperature
Decrease temperature
Power save on
Power save off
Reset temperature
Energy usage
Temperature
Power save


Alberta RCMP remind drivers to not leave vehicle idling and unoccupied
RCMP have estimated about 33 per cent of all vehicle thefts occurred while the vehicle was idling
Alberta RCMP remind drivers not to leave their vehicles idling while unoccupied. When the temperature drops, police see an increase in stolen vehicle incidents while leaving them unoccupied.
RCMP have estimated that about 33 per cent of all vehicle thefts occurred while the vehicle was idling and unoccupied. Vehicle thefts of this kind are crimes of opportunity and are completely preventable.
RCMP have the following safety tips to keep your vehicle secure, not only in the winter but the warmer months as well:
· never leave an idling vehicle unoccupied, even when it is locked.
· use a remote starter whenever possible and keep your vehicle locked.
· use a steering wheel lock to deter thieves.
· never leave spare keys or garage door openers in or around your vehicle.
· never leave children or pets in an idling vehicle.
· report suspicious activity to police immediately by calling your local police detachment.
Many people believe that their vehicle isn’t going to be stolen because they live on a quiet street or are only leaving it unattended for a minute.
In reality, it only takes second for someone to get into the vehicle and drive away. Stolen vehicles pose a significant risk to public safety and we need the community’s help to prevent these easy thefts.
-Submitted


There is a dilemma nowadays for developers where they have to chose to design an own application for mobile use, or stick to the earlier design but just design it responsive.
Pros and cons with responsive websites:
Pros:
It takes less time to just implement a responsive design to your website than developing an app for it.
It’s very much cheaper, because you just have to implement something into your existing design, rather than creating something new.
Cons:
There are cons however, and these cons sets up the plan for your design entirely. When it comes to the user experience, hosting a responsive website instead of a mobile app can be very slow, not user friendly and be hard to navigate.
Pros and cons with mobile applications:
Pros:
It’s usually way more faster to navigate an application than a website, at least when you’re on your handheld device.
The functionality is usually way more fitting in application format than website format.
Cons:
The cons are the counterpart of responsive website’s pros. It takes more time, usually more manpower (because another set of skills is required), and a bigger wallet.
So what to choose?
This all depends on what you want to do. Mobile applications are not coded using HTML and CSS usually, and it requires another sets of skills from the developer. Are you developing something for a bigger company that has an idea where mobile use is very important, then I suggest that you would get into mobile application development and use those skills to do that. Are you designing an informational platform that can be read on a handheld device? Then you probably need to just be sure the website is readable on a phone.


| Field | Required | Type | Description |
|---|---|---|---|
elevation |
required | number |
The elevation of the location in meters. |
location |
required | LatLngLiteral |
A location element of the position for which elevation data is being computed. Note that for path requests, the set of location elements will contain the sampled points along the path. See LatLngLiteral for more information. |
resolution |
optional | number |
The value indicating the maximum distance between data points from which the elevation was interpolated, in meters. This property will be missing if the resolution is not known. Note that elevation data becomes more coarse (larger resolution values) when multiple points are passed. To obtain the most accurate elevation value for a point, it should be queried independently. |
Generated from the OpenAPI specification. Edit Report bug


Gateway
BOT
22-Sep-19 12:28 PM
[dscrd-hush] <Privatoshi²> Same here
[dscrd-hush] <denio> So why worry
[dscrd-hush] <Privatoshi²> Germany is a good test for how all of Europe is
[dscrd-hush] <Privatoshi²> That's all... Only reason I asked
[dscrd-hush] <denio> If a Muslim party become majority they have rules to follow
[dscrd-hush] <Privatoshi²> This is a good thing
[dscrd-hush] <denio> Like every other Party
[dscrd-hush] <Privatoshi²> To embrace everyone.. it really is
"Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, ...
[dscrd-hush] <denio> I know is maybe some kind of romantic... But we believe in democratic system nowadays
[dscrd-hush] <Privatoshi²> I do to. It's hard to set the rules tho
[dscrd-hush] <denio> Concerned me a little that other big states goes the opposite direction
[dscrd-hush] <Privatoshi²> Not everyone has to oppose the US Military, if they protest
[dscrd-hush] <Privatoshi²> And local police department
[dscrd-hush] <Privatoshi²> And swat
[dscrd-hush] <Privatoshi²> It's unfathomable
[dscrd-hush] <Privatoshi²> What they do in France, you couldn't do here for a day
[dscrd-hush] <Privatoshi²> What they do in HK, nope
[dscrd-hush] <Privatoshi²> Did u know that local US police depts, spend millions on privacy breaking tech each year?
[dscrd-hush] <Privatoshi²> Stingrays
[dscrd-hush] <Privatoshi²> Finding a role for Hush in all of this, would be nice
[dscrd-hush] <denio> That's crazy... After 9/11 a lot went crazy from a outside view in the US
[dscrd-hush] <Privatoshi²> Not really
[dscrd-hush] <Privatoshi²> Intelligence operations worldwide, yeah
[dscrd-hush] <Privatoshi²> Domestic, yeah
[dscrd-hush] <Privatoshi²> The citizens, the same as before
[dscrd-hush] <denio> That's not crazy?
[dscrd-hush] <Privatoshi²> Well there was a major attack
[dscrd-hush] <Privatoshi²> In the world's biggest city
[dscrd-hush] <Privatoshi²> And it killed and even caused a lot of victims to get cancer
[dscrd-hush] <Privatoshi²> From the smoke
[dscrd-hush] <Privatoshi²> What would you do?
[dscrd-hush] <Privatoshi²> Take it
[dscrd-hush] <denio> Puuhh not a easy question... But spy and bomb the world would maybe not my answer
[dscrd-hush] <Privatoshi²> Well if the US didn't have to take the world's stage post world war 2, which we shouldn't be in that position politically, then we aren't policing the world like we have to
[dscrd-hush] <Privatoshi²> US is isolated. We are better off focusing on us.
[dscrd-hush] <Privatoshi²> But it is what it is
[dscrd-hush] <Privatoshi²> Bc everyone has an opinion on how we should do it
[dscrd-hush] <Privatoshi²> It's probably not easy
[dscrd-hush] <denio> No it's hard to answer. But why are the US isolated? You have more friends in Europe then you know. Sometimes it's just hard to understand your goals
[dscrd-hush] <Privatoshi²> We are isolated geographically
[dscrd-hush] <Privatoshi²> And Europeans like to deal with other Europeans
[dscrd-hush] <denio> Canada?
[dscrd-hush] <denio> Mexiko?
[dscrd-hush] <Privatoshi²> What about them
[dscrd-hush] <Privatoshi²> Our goal is to have a war-free Europe
(edited)
[dscrd-hush] <Privatoshi²> We also focus on Latin America & Mexico and Canada
[dscrd-hush] <Privatoshi²> And we don't want the Chinese building man made islands in the South Pacific
[dscrd-hush] <denio>
[dscrd-hush] <Privatoshi²> Has Europe had a major war in 75 years?
[dscrd-hush] <denio> Kosovo was the last
[dscrd-hush] <Privatoshi²> Sure. But I mean a large conflict spread throughout Europe
[dscrd-hush] <Privatoshi²> You guys have had stability
[dscrd-hush] <Privatoshi²> To grow and do whatever
[dscrd-hush] <Privatoshi²> Who else in the World has had that
[dscrd-hush] <Privatoshi²> Asia? Not really
[dscrd-hush] <Privatoshi²> Latin America? No
[dscrd-hush] <Privatoshi²> Africa? No
[dscrd-hush] <Privatoshi²> Middle East? No
[dscrd-hush] <Privatoshi²> US cares about Europe
[dscrd-hush] <Privatoshi²> I know Europe caress about the US
[dscrd-hush] <Privatoshi²> Vietnam
[dscrd-hush] <Privatoshi²> Congo
[dscrd-hush] <Privatoshi²> Kosovo
[dscrd-hush] <Privatoshi²> Serbia
[dscrd-hush] <Privatoshi²> No, I read. I don't pay attention to the media
[dscrd-hush] <Privatoshi²> So there was a major conflict spread throughout Europe, at one time, in a 2-5 year period?
[dscrd-hush] <Privatoshi²> I meant it prevented another world war.. another devestating conflict
[dscrd-hush] <Privatoshi²> Maybe I'm wrong
[dscrd-hush] <denio> No you are not wrong
[dscrd-hush] <Privatoshi²> Yeah, it's ashamed
[dscrd-hush] <Privatoshi²> Conflict is not the way
[dscrd-hush] <Privatoshi²> That's why I haven't minded trump
[dscrd-hush] <Privatoshi²> Bc the drones have stopped for the most part
[dscrd-hush] <Privatoshi²> And no new major war
[dscrd-hush] <Privatoshi²> Who was that guy?
[dscrd-hush] <Privatoshi²> I haven't met him. I should say hi
[dscrd-hush] <denio> Don't know but the Krim was conquer by Russia... They have not free anything there
[dscrd-hush] <Privatoshi²> Yeah I know
[dscrd-hush] <Privatoshi²> They stick to their style
[dscrd-hush] <Privatoshi²> You don't judge the way other cultures live.
[dscrd-hush] <Privatoshi²> It's hard to not do, but it is fair, to an extent
[dscrd-hush] <Privatoshi²> Maybe that works for them
[dscrd-hush] <Privatoshi²> I'm not saying it's right.
[dscrd-hush] <Privatoshi²> Ukraine, that's crazy too
[dscrd-hush] <Privatoshi²> Which part of Germany are u from?
[dscrd-hush] <denio> Western near cologne
[dscrd-hush] <Privatoshi²> It's kind of slower type of life?
[dscrd-hush] <denio> 10 min away from Belgium and Netherlands
[dscrd-hush] <Privatoshi²> 10min ,m
[dscrd-hush] <Privatoshi²> Wtf
[dscrd-hush] <denio> Yes this is Rly nice
[dscrd-hush] <denio> That's maybe why I see me as European
[dscrd-hush] <denio> Not so much as german
[dscrd-hush] <Privatoshi²> Te parle frances?
[dscrd-hush] <denio> Just un peu
[dscrd-hush] <Privatoshi²> Dios mio
[dscrd-hush] <Privatoshi²> Italiano?
[dscrd-hush] <denio> No


Oops, something went wrong, please try again
You have been signed out
Signin with Facebook
Login
Email
Password
Signin
Reset password


GAME DESCRIPTION
This is simple game designed using HTML and JavaScript.
Use the Buttons Up,Down,Right,Left to move the car.
Dodge the walls using these buttons.
If you collide with the wall,your game will be over.
ENJOY PLAYING!!!!


Raw freaking BVH numbers!
Note the faster searches after re-insertion of the same elements that were deleted.


Putting Together the Mathematics So Far
We’ve established the relationship:
We also saw earlier that eccentricity can be defined as:
This gives us enough to interrelate the four quantities:
- a — semi-major axis
- b — semi-minor axis
- c — focal distance
- e — eccentricity
and, given any two, calculate the other two.
In particular, we can square the second equation, rearrange it to get c2 by itself and then substitute into the first equation to get:
This can be rearranged to get eccentricity as a function of the ratio of semi-minor axis to semi-major axis:
or the semi-minor axis as a function of the semi-major axis and the eccentricity:
These equations are used at various points in the code behind all these visualisations.
It is common for the semi-major axis and eccentricity to be given for an orbital body and the other two values calculated from them.


Welcome to My Web Page!
This is H1
This is a paragraph
I have learned
HTML
I have learned
CSS
My Skill
My Level
Python
Basic
Machine Learning
Basic
One item
Another item
First item
Second item


Created: 30/09/2011
By: Your Inspiration Web
Email<EMAIL_ADDRESS>Thank you for purchasing our theme. If you have any questions that are beyond the scope of this help file, please feel free to email via my user page contact form here. Thanks so much!
The navigation is in located on header (#header) and have the ID "#nav". Here the structure:
This theme is a fixed layout with two columns. All of the information within the main content area is nested within a div with an id of "content". The sidebar's (column #2) content is within a div with an id of "sidebar". The general template structure is the same throughout the template. Here is the general structure.
If you would like to edit the color, font, or style of any elements in one of these columns, you would do the following:
#content a { color: #someColor; }
If you find that your new style is not overriding, it is most likely because of a specificity problem. Scroll down in your CSS file and make sure that there isn't a similar style that has more weight.
I.E.
#content a { color: #someColor !important; }
So, to ensure that your new styles are applied, make sure that they carry enough "weight" and that there isn't a style lower in the CSS file that is being applied after yours.
Each page can be easily changed in its layout, replacing a class, that define the layout of the page:
You need to define this class in the ".inner" div, inside the main content wrapper. Here an example:

 content and sidebar

We're using one main CSS file in this theme, located in the root of the theme and called "style.css". It contains the general reset and all style of the theme. The other two are
The stylesheet is organizzed and compact, to easily find the roles. Each section of this file is delimited by some comments line. Here an example:
/* === HEADER === */ some code /* === END HEADER === */ /* === CONTENT === */ some code /* === END CONTENT === */ /* === SIDEBAR === */ some code /* === END SIDEBAR === */ /* === FOOTER === */ some code /* === END FOOTER === */ etc, etc.
Other CSS files are located in the "css" folder and they are for specif jQuery library.
If you would like to edit a specific section of the site, simply find the appropriate label in the CSS file, and then scroll down until you find the appropriate style that needs to be edited.
This theme imports three Javascript files.
To change the logo image url, you must edit header of each HTML file:
The special font is provided by Google Fonts
Then set the specific font, by google fonts, you need to edit style.css file:
You can also set a font, choose one of the fonts saved in "Fonts" folder.
There are four sliders available in this theme:
This theme have a contact form already working, by the file called sendmail.php. The script is written with PHP language and work both in client-side, that server-side. The ajax request and real-time validation is on js/contact.js file.
In the file sendmail.php, there is some configuration, for the sending of the contact form.
With this, you can configure to send emails from, and where to send the name that will appear in the email client:
// email define('TO_EMAIL', 'your@email.com'); define('FROM_EMAIL', 'info@test.it'); define('FROM_NAME', 'Your Name');
Then, the contact form is already dynamic and works with infinity combination of inputs on contact form.
That is, you can add also more input fields, without change the script of sendmail.php file.
Also, you can configure the body of the email and add inside the information added by the user in the contact form.
You can configure the body with this constant, that you find on top of the file:
define( 'BODY', '%message%

email inviata da %name%, email %email%.' );
The string between the percentual symbol (%), is the name of the field. For example, if I add this field in the contact page:
<input type="text" name="name" id="name-form" class="required" value="" />
by the string %name% (that is the same of name="name") I can replace it with the name added by the user in the contact form.
In addition, you can configure the real time validation, by adding some classes on the input fields. For example:
<input type="text" name="email" id="email-form" class="required email-validate" value="" />
with the classes "required" and "email-validate", you can say respectively that this field is required and must be a valid email.
We've included the psd of the home.
If you'd like to change the main image in the header, open "home.psd", make the necessary adjustments, and then save the file with the right image name and replace the existing file. Do the same for other part of the theme.
Fonts
Icons
I’ve used “Basic icon set” pack, you can find it here:
http://pixel-mixer.com/basic_set/
and another icons with shadow effect:
http://www.dezinerfolio.com/freebie/30-free-vector-icons
Social network icons are taken here:
http://www.nouveller.com/general/free-social-media-bookmark-icon-pack-the-ever-growing-icon-set/
and some free stock
Once again, thank you so much for purchasing this theme. As I said at the beginning, We'd be glad to help you if you have any questions relating to this theme. No guarantees, but I'll do my best to assist. If you have a more general question relating to the themes on ThemeForest, you might consider visiting our forum.
Your Inspiration Web


Response
The response class helps you build a HTTP response.
An instance of the response class is always avaiable in all controller classes. It is also easily made avaiable in route closures.
Basics
The body
method allows you to set the response body. This is not normally needed as the framework automatically sets the response body to the return value of your controller/route action. It can however be useful if you want to alter the response body in an after filter.
public function afterFilter()
{
$this->response->body(strtoupper($this->response->getBody()));
}
The getBody
method returns the response body.
$responseBody = $this->response->getBody();
The type
method lets you define the response type as well as the response charset. The default response type is text/html
and the default charset is UTF-8
. The default charset is defined in your app\config\application.php
config file.
$this->response->type('application/json');
// You can also override the default charset
$this->response->type('application/json', 'iso-8859-1');
The getType
method returns the current response type.
$responseType = $this->response->getType();
The charset
method lets you set the response charset. The default charset is UTF-8
and it is defined in your app\config\application.php
config file.
$this->response->charset('iso-8859-1');
The getCharset
returns the current response charset.
$responseCharset = $this->response->getCharset();
The status
method lets you set the response status.
$this->response->status(404); // Sends the 404 "Not Found" header.
The getStatus
method returns the current status code.
$responseStatus = $this->response->getStatus();
The back
method will redirect the user back to the previous page.
return $this->response->back();
// You also specify the status header (default is 302)
return $this->response->back(301);
Setting cookies
The cookie
method adds a cookie to the response.
// Sets a cookie that expires when the browser closes
$this->response->cookie('name', 'value');
// Sets a cookie that expires after 1 hour
$this->response->cookie('name', 'value', 3600);
// You can also set the path, domain, secure and httponly options using the fourth parameter
$this->response->cookie('name', 'value', 3600, ['path' => '/mydir', 'domain' => '.example.org']);
The signedCookie
method has the same method signature as the cookie
method. The difference is that the cookie will be signed using the application secret defined in the app/config/application.php
config file.
$this->response->signedCookie('name', 'value');
The benefit of using signed cookies over regular cookies is that their values can not be tampered with on the client site.
The deleteCookie
method deletes a cookie from the browser. It can be used to delete both normal and signed cookies.
$this->response->deleteCooke('name');
// You can also set the path, domain, secure and httponly options using the second parameter
$this->response->deleteCookie('name', ['path' => '/mydir', 'domain' => '.example.org']);
The getCookies
method returns an array of all the cookies that have been set.
$responseCookies = $this->response->getCookies();
The clearCookies
method will clear all cookies that have been set.
$this->response->clearCookies();
Setting headers
The header
method adds a header to your response. The first parameter is the header field while the second is the header value.
$this->response->header('access-control-allow-origin', '*');
The removeHeader
method allows you to remove a previously set header from the response.
$this->response->removeHeader('access-control-allow-origin');
The getHeaders
method will return an array of all the response headers that have been set.
$responseHeaders = $this->response->getHeaders();
The clearHeaders
method will clear all response headers that have been set
$this->response->clearHeaders();
Response filters
The filter
methods allows you to add a response filter that the response body will be passed through before being sent to the browser. You can define multiple filters and they will be executed in the order that they were defined.
$this->response->filter(function($responseBody)
{
return strtoupper($responseBody);
});
The getFilters
method will return an array containing all the defined response filters.
$responseFilters = $this->response->getFilters();
The clearFilters
method will clear all the defined response filters.
$this->response->clearFilters();
Caching and compression
You can enable ETag
caching using the cache
method. Doing so can save bandwidth as the response body will only be sent if it has been modified since the last request.
$this->response->cache();
The disableCaching
method disables ETag
caching if it has been enabled.
$this->response->disableCaching();
The compress
method enables output compression. This will save you bandwidh in excahge for a slight bump in CPU usage.
$this->response->compress();
The disableCompression
method disables output compression if it has been enabled.
$this->response->disableCompression();
Special responses
Redirecting
The redirect
method returns a redirect response container.
return $this->response->redirect($urlBuilder->toRoute('home'));
You can also set the status header (default is 302) by chaining the status method.
return $this->response->redirect($urlBuilder->toRoute())->status(301);
Files
The file
method returns a file response container. The file download will be resumable, something that can be very useful when downloading large files.
return $this->response->file('/path/to/file.ext');
You can set a custom file name, content type, content disposition and a callback to be executed after a completed download using the second parameter.
return $this->response->file('/path/to/file.ext', ['file_name' => 'foo.ext']);
| Option key | Description |
|---|---|
| file_name | The file name sent to the client |
| disposition | Content-disposition (default is attachment) |
| content_type | The framework will try to detect the content type for you but you can override it using this option |
| callback | Closure that will be executed after a completed download |
Note that any errors in the callback will not be displayed as it happens after the output has been sent. You'll have to check your logs for errors.
Streams
The stream
method returns a stream response container. They can be usefull when sending large ammounts data as the data will be flushed to the client in chunks, thus minimizing your application memory usage. It also allows you to begin transmitting dynamically-generated content before knowing the total size of the content.
$this->response->type('text/plain');
return $this->response->stream(function($stream)
{
$stream->flush('Hello, world!');
sleep(2);
$stream->flush('Hello, world!');
});
This might not work as expected as some webservers and reverse proxies will buffer the output before sending it.


{% extends "base.html" %} {% block content %} create a new organization {% if org_list %}
It doesn't look like there are any organizations yet. You could create an organization if you want to.


If a regular 2D photograph is the amount of light that runs into each pixel on an image plane, then the analogous 4D light field is the amount of light traveling along each ray that runs into the image plane. In other words, it captures the direction of the light values as well as the light values themselves. As Ng. et al. describe in this paper, we can use the additional information to enable countless post-processing effects such as refocusing and aperture resizing. (As a result, having light field data is useful for photographers since it means they no longer have to decide between controlling motion blur and controlling depth of field!)
In this project, we focus (through alignment and averaging, haha) on the two light field applications mentioned a few seconds ago: depth refocusing and aperture adjustment. Without a Lytro camera, we turn to the Stanford Light Field Archive for photographic data to process.
Each light field in the Stanford dataset is represented as a collection of 289 sub-aperture images taken over a 17 x 17 grid (/captured over a plane orthogonal to the optical axis). Each sub-aperture image can be thought of as the light that comes through a different part of some universal aperture, or effectively just the same "back of the lens" picture taken a bunch of times from slightly different positions. (As a side note, this means that it's theoretically possible to record light field data with a conventional camera just by snapping many variations on the same shot. We could do that as a bells and whistles option for this project, actually, but ain't nobody got time for that.)
In our minds, we can turn such images into light rays because each \((x, y)\) position on the image plane and each \((u, v)\) position on the aperture plane uniquely define a ray. In this way, the parameters \((x, y, u, v)\) make up the four dimensions of our plenoptic function. With the Stanford data, we maintain a fixed \((x, y)\)-plane – the output image itself – while varying \((u, v)\) over the positions specified in the image names. Thus we can consider ourselves to have the set of rays that will be integrated by a single pixel, for every pixel on the image plane.
Then what? Well, we can create our output photograph by performing that integration process – i.e. adding up and averaging the light from all those rays. But perhaps we don't want just any output photograph; perhaps we want our image to be focused on a specific point of interest. For this we introduce shifting. With the Stanford dataset in hand, all we have to do to focus on some element is shift-align the sub-aperture images so that our element is at the same position in every image... and then average the lot of them. Of course this means we need an image of reference (the image whose content all of the other images will be shifted toward), and here we choose the central sub-aperture image for that role: the one corresponding to point \((8, 8)\) if we're still speaking of our 17 x 17 grid.
Unfortunately, it turns out that to focus on a certain element it's necessary to run extra processing (in order to compute those tailored shifts). Accordingly, for the time being we remain lazy and deign merely to shift the image based on some arbitrary constant \(C\). With this, we arrive at our refocusing algorithm, where actually the pseudocode below was straight ripped from Prof. Ng's lecture slides:
for every sub-aperture image I(x, y): compute the (u, v) coordinates corresponding to that image shift by Δ(x, y) = C * (u, v) average the shifted image into an output image
We compute \((u, v)\) by utilizing the absolute coordinates given in the image filenames.
Chess; C = 0 |
Truck; C = 0 |
Chess; C = -0.3 to 0.8 |
Truck; C = -0.2 to 0.6 |
Tarot; C = -0.5 to 0.6 |
We can also post-process the images in order to virtually modify the size of the aperture. To do this, we fix our \(C\) (if only so we can highlight aperture adjustment instead of depth refocusing) and simply include more or less sub-aperture images in our average. If wanted the smallest possible aperture, we wouldn't average anything at all – instead we'd just return a single one of our sub-aperture images. In our case, we'll again base our photographs around the central \((8, 8)\) image, so we'd actually return that.
Then, to increase the aperture size, we'd average more images in the space around the central image. We step over radius lengths here (although technically we average over a box, not a circle). For radius 0, we return the central image; for radius 1, we average the 3 x 3 box of sub-aperture images around the central image; for radius 2, we average the 5 x 5 box... and so on so forth. By the end of it, we're averaging the entire collection of sub-aperture images again.
Intuitively, this represents a larger aperture because we're expanding the space (the grid) around the center of the aperture that we're letting light pass through. If we think of each sub-aperture image as the light that passes through a certain portion of the aperture, then obviously taking into account more sub-aperture images will take into account a bigger portion of the aperture. (We get more light rays – more pixel values – due to a larger aperture!)
Below are examples of aperture adjustment in action. In each, we set \(C = 0.1\) (which seems to focus around the middle) and run Part 1's depth refocusing algorithm on varying numbers of images around the \((8, 8)\) photograph.
Chess; C = 0.1 |
Truck; C = 0.1 |
Tarot; C = 0.1 |
About a year ago, I found Lytro's living picture demonstrations and they became a nontrivial motivator for my enrollment in Ren Ng's graphics class / interest in comp. photo-esque material in general. I remember being blown away by the idea of refocusing images and seemingly moving the viewpoint after taking a picture. Thus, through this project I'm excited to have been able to implement a refocusing algorithm via light field data at last.
Also, I found it interesting that light fields would be given in the form of sub-aperture images (I previously thought it would be more of a primitive "directional rays with light values" kind of deal), but in hindsight it makes a lot of sense and was very straightforward to work with. On the whole, it was pretty eye-opening to experience how simple and effective these light field methods can be – because really all this project came down to was shifting and averaging, and through that I was able to recreate the type of post-processing that so amazed me one year ago...


We now support uploading your own themes in the same way as we integrated it for plugins.
The gallery is currently only available on getbblog.com - The integration in BBLog is in progress.
To all theme creators - Upload your theme to the new theme gallery.
The old theme administration tool will be removed in the future.


"NICOPOLIS "city of victory, where Paul intended to winter (Titus 3:12). There were several cities of this name. The one here referred to was most probably that in Epirus, which was built by Augustus Caesar to commemorate his victory at the battle of Actium (B.C. 31). It is the modern Paleoprevesa, i.e., “Old Prevesa.” The subscription to the epistle to Titus calls it “Nicopolis of Macedonia”, i.e., of Thrace. This is, however, probably incorrect.
"NICOPOLIS "city of victory, where Paul intended to winter (Titus 3:12).
There were several cities of this name. The one here referred to was most probably that in Epirus, which was built by Augustus Caesar to commemorate his victory at the battle of Actium (B.C. 31). It is the modern Paleoprevesa, i.e., “Old Prevesa.” The subscription to the epistle to Titus calls it “Nicopolis of Macedonia”, i.e., of Thrace. This is, however, probably incorrect.


Product 01
Product 02
Product 03
Product 04
Product 05
Product 06
Product 07
Product 08
Product 09
Product 10
Product 11
Product 12
Product 13
Product 14
Product 15
Product 16


PySpark Usage Guide for Pandas with Apache Arrow
- Apache Arrow in PySpark
- Enabling for Conversion to/from Pandas
- Pandas UDFs (a.k.a. Vectorized UDFs)
- Pandas Function APIs
- Usage Notes
Apache Arrow in PySpark
Apache Arrow is an in-memory columnar data format that is used in Spark to efficiently transfer data between JVM and Python processes. This currently is most beneficial to Python users that work with Pandas/NumPy data. Its usage is not automatic and might require some minor changes to configuration or code to take full advantage and ensure compatibility. This guide will give a high-level description of how to use Arrow in Spark and highlight any differences when working with Arrow-enabled data.
Ensure PyArrow Installed
To use Apache Arrow in PySpark, the recommended version of PyArrow
should be installed.
If you install PySpark using pip, then PyArrow can be brought in as an extra dependency of the
SQL module with the command pip install pyspark[sql]
. Otherwise, you must ensure that PyArrow
is installed and available on all cluster nodes.
You can install using pip or conda from the conda-forge channel. See PyArrow
installation for details.
Enabling for Conversion to/from Pandas
Arrow is available as an optimization when converting a Spark DataFrame to a Pandas DataFrame
using the call toPandas()
and when creating a Spark DataFrame from a Pandas DataFrame with
createDataFrame(pandas_df)
. To use Arrow when executing these calls, users need to first set
the Spark configuration spark.sql.execution.arrow.pyspark.enabled
to true
. This is disabled by default.
In addition, optimizations enabled by spark.sql.execution.arrow.pyspark.enabled
could fallback automatically
to non-Arrow optimization implementation if an error occurs before the actual computation within Spark.
This can be controlled by spark.sql.execution.arrow.pyspark.fallback.enabled
.
import numpy as np
import pandas as pd
# Enable Arrow-based columnar data transfers
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "true")
# Generate a Pandas DataFrame
pdf = pd.DataFrame(np.random.rand(100, 3))
# Create a Spark DataFrame from a Pandas DataFrame using Arrow
df = spark.createDataFrame(pdf)
# Convert the Spark DataFrame back to a Pandas DataFrame using Arrow
result_pdf = df.select("*").toPandas()
Using the above optimizations with Arrow will produce the same results as when Arrow is not
enabled. Note that even with Arrow, toPandas()
results in the collection of all records in the
DataFrame to the driver program and should be done on a small subset of the data. Not all Spark
data types are currently supported and an error can be raised if a column has an unsupported type,
see Supported SQL Types. If an error occurs during createDataFrame()
,
Spark will fall back to create the DataFrame without Arrow.
Pandas UDFs (a.k.a. Vectorized UDFs)
Pandas UDFs are user defined functions that are executed by Spark using
Arrow to transfer data and Pandas to work with the data, which allows vectorized operations. A Pandas
UDF is defined using the pandas_udf
as a decorator or to wrap the function, and no additional
configuration is required. A Pandas UDF behaves as a regular PySpark function API in general.
Before Spark 3.0, Pandas UDFs used to be defined with PandasUDFType
. From Spark 3.0
with Python 3.6+, you can also use Python type hints.
Using Python type hints are preferred and using PandasUDFType
will be deprecated in
the future release.
Note that the type hint should use pandas.Series
in all cases but there is one variant
that pandas.DataFrame
should be used for its input or output type hint instead when the input
or output column is of StructType
. The following example shows a Pandas UDF which takes long
column, string column and struct column, and outputs a struct column. It requires the function to
specify the type hints of pandas.Series
and pandas.DataFrame
as below:
import pandas as pd
from pyspark.sql.functions import pandas_udf
@pandas_udf("col1 string, col2 long")
def func(s1: pd.Series, s2: pd.Series, s3: pd.DataFrame) -> pd.DataFrame:
s3['col2'] = s1 + s2.str.len()
return s3
# Create a Spark DataFrame that has three columns including a sturct column.
df = spark.createDataFrame(
[[1, "a string", ("a nested string",)]],
"long_col long, string_col string, struct_col struct<col1:string>")
df.printSchema()
# root
# |-- long_column: long (nullable = true)
# |-- string_column: string (nullable = true)
# |-- struct_column: struct (nullable = true)
# | |-- col1: string (nullable = true)
df.select(func("long_col", "string_col", "struct_col")).printSchema()
# |-- func(long_col, string_col, struct_col): struct (nullable = true)
# | |-- col1: string (nullable = true)
# | |-- col2: long (nullable = true)
In the following sections, it describes the combinations of the supported type hints. For simplicity,
pandas.DataFrame
variant is omitted.
Series to Series
The type hint can be expressed as pandas.Series
, … -> pandas.Series
.
By using pandas_udf
with the function having such type hints above, it creates a Pandas UDF where the given
function takes one or more pandas.Series
and outputs one pandas.Series
. The output of the function should
always be of the same length as the input. Internally, PySpark will execute a Pandas UDF by splitting
columns into batches and calling the function for each batch as a subset of the data, then concatenating
the results together.
The following example shows how to create this Pandas UDF that computes the product of 2 columns.
import pandas as pd
from pyspark.sql.functions import col, pandas_udf
from pyspark.sql.types import LongType
# Declare the function and create the UDF
def multiply_func(a: pd.Series, b: pd.Series) -> pd.Series:
return a * b
multiply = pandas_udf(multiply_func, returnType=LongType())
# The function for a pandas_udf should be able to execute with local Pandas data
x = pd.Series([1, 2, 3])
print(multiply_func(x, x))
# 0 1
# 1 4
# 2 9
# dtype: int64
# Create a Spark DataFrame, 'spark' is an existing SparkSession
df = spark.createDataFrame(pd.DataFrame(x, columns=["x"]))
# Execute function as a Spark vectorized UDF
df.select(multiply(col("x"), col("x"))).show()
# +-------------------+
# |multiply_func(x, x)|
# +-------------------+
# | 1|
# | 4|
# | 9|
# +-------------------+
For detailed usage, please see pyspark.sql.functions.pandas_udf
Iterator of Series to Iterator of Series
The type hint can be expressed as Iterator[pandas.Series]
-> Iterator[pandas.Series]
.
By using pandas_udf
with the function having such type hints above, it creates a Pandas UDF where the given
function takes an iterator of pandas.Series
and outputs an iterator of pandas.Series
. The
length of the entire output from the function should be the same length of the entire input; therefore, it can
prefetch the data from the input iterator as long as the lengths are the same.
In this case, the created Pandas UDF requires one input column when the Pandas UDF is called. To use
multiple input columns, a different type hint is required. See Iterator of Multiple Series to Iterator
of Series.
It is also useful when the UDF execution requires initializing some states although internally it works identically as Series to Series case. The pseudocode below illustrates the example.
The following example shows how to create this Pandas UDF:
from typing import Iterator
import pandas as pd
from pyspark.sql.functions import pandas_udf
pdf = pd.DataFrame([1, 2, 3], columns=["x"])
df = spark.createDataFrame(pdf)
# Declare the function and create the UDF
@pandas_udf("long")
def plus_one(iterator: Iterator[pd.Series]) -> Iterator[pd.Series]:
for x in iterator:
yield x + 1
df.select(plus_one("x")).show()
# +-----------+
# |plus_one(x)|
# +-----------+
# | 2|
# | 3|
# | 4|
# +-----------+
For detailed usage, please see pyspark.sql.functions.pandas_udf
Iterator of Multiple Series to Iterator of Series
The type hint can be expressed as Iterator[Tuple[pandas.Series, ...]]
-> Iterator[pandas.Series]
.
By using pandas_udf
with the function having such type hints above, it creates a Pandas UDF where the
given function takes an iterator of a tuple of multiple pandas.Series
and outputs an iterator of pandas.Series
.
In this case, the created pandas UDF requires multiple input columns as many as the series in the tuple
when the Pandas UDF is called. Otherwise, it has the same characteristics and restrictions as Iterator of Series
to Iterator of Series case.
The following example shows how to create this Pandas UDF:
from typing import Iterator, Tuple
import pandas as pd
from pyspark.sql.functions import pandas_udf
pdf = pd.DataFrame([1, 2, 3], columns=["x"])
df = spark.createDataFrame(pdf)
# Declare the function and create the UDF
@pandas_udf("long")
def multiply_two_cols(
iterator: Iterator[Tuple[pd.Series, pd.Series]]) -> Iterator[pd.Series]:
for a, b in iterator:
yield a * b
df.select(multiply_two_cols("x", "x")).show()
# +-----------------------+
# |multiply_two_cols(x, x)|
# +-----------------------+
# | 1|
# | 4|
# | 9|
# +-----------------------+
For detailed usage, please see pyspark.sql.functions.pandas_udf
Series to Scalar
The type hint can be expressed as pandas.Series
, … -> Any
.
By using pandas_udf
with the function having such type hints above, it creates a Pandas UDF similar
to PySpark’s aggregate functions. The given function takes pandas.Series
and returns a scalar value.
The return type should be a primitive data type, and the returned scalar can be either a python
primitive type, e.g., int
or float
or a numpy data type, e.g., numpy.int64
or numpy.float64
.
Any
should ideally be a specific scalar type accordingly.
This UDF can be also used with groupBy().agg()
and pyspark.sql.Window
.
It defines an aggregation from one or more pandas.Series
to a scalar value, where each pandas.Series
represents a column within the group or window.
Note that this type of UDF does not support partial aggregation and all data for a group or window will be loaded into memory. Also, only unbounded window is supported with Grouped aggregate Pandas UDFs currently. The following example shows how to use this type of UDF to compute mean with a group-by and window operations:
import pandas as pd
from pyspark.sql.functions import pandas_udf
from pyspark.sql import Window
df = spark.createDataFrame(
[(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)],
("id", "v"))
# Declare the function and create the UDF
@pandas_udf("double")
def mean_udf(v: pd.Series) -> float:
return v.mean()
df.select(mean_udf(df['v'])).show()
# +-----------+
# |mean_udf(v)|
# +-----------+
# | 4.2|
# +-----------+
df.groupby("id").agg(mean_udf(df['v'])).show()
# +---+-----------+
# | id|mean_udf(v)|
# +---+-----------+
# | 1| 1.5|
# | 2| 6.0|
# +---+-----------+
w = Window \
.partitionBy('id') \
.rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing)
df.withColumn('mean_v', mean_udf(df['v']).over(w)).show()
# +---+----+------+
# | id| v|mean_v|
# +---+----+------+
# | 1| 1.0| 1.5|
# | 1| 2.0| 1.5|
# | 2| 3.0| 6.0|
# | 2| 5.0| 6.0|
# | 2|10.0| 6.0|
# +---+----+------+
For detailed usage, please see pyspark.sql.functions.pandas_udf
Pandas Function APIs
Pandas Function APIs can directly apply a Python native function against the whole DataFrame
by
using Pandas instances. Internally it works similarly with Pandas UDFs by using Arrow to transfer
data and Pandas to work with the data, which allows vectorized operations. However, A Pandas Function
API behaves as a regular API under PySpark DataFrame
instead of Column
, and Python type hints in Pandas
Functions APIs are optional and do not affect how it works internally at this moment although they
might be required in the future.
From Spark 3.0, grouped map pandas UDF is now categorized as a separate Pandas Function API,
DataFrame.groupby().applyInPandas()
. It is still possible to use it with PandasUDFType
and DataFrame.groupby().apply()
as it was; however, it is preferred to use
DataFrame.groupby().applyInPandas()
directly. Using PandasUDFType
will be deprecated
in the future.
Grouped Map
Grouped map operations with Pandas instances are supported by DataFrame.groupby().applyInPandas()
which requires a Python function that takes a pandas.DataFrame
and return another pandas.DataFrame
.
It maps each group to each pandas.DataFrame
in the Python function.
This API implements the “split-apply-combine” pattern which consists of three steps:
- Split the data into groups by using
DataFrame.groupBy
. - Apply a function on each group. The input and output of the function are both
pandas.DataFrame
. The input data contains all the rows and columns for each group. - Combine the results into a new PySpark
DataFrame
.
To use groupBy().applyInPandas()
, the user needs to define the following:
- A Python function that defines the computation for each group.
- A
StructType
object or a string that defines the schema of the output PySparkDataFrame
.
The column labels of the returned pandas.DataFrame
must either match the field names in the
defined output schema if specified as strings, or match the field data types by position if not
strings, e.g. integer indices. See pandas.DataFrame
on how to label columns when constructing a pandas.DataFrame
.
Note that all data for a group will be loaded into memory before the function is applied. This can lead to out of memory exceptions, especially if the group sizes are skewed. The configuration for maxRecordsPerBatch is not applied on groups and it is up to the user to ensure that the grouped data will fit into the available memory.
The following example shows how to use groupby().applyInPandas()
to subtract the mean from each value
in the group.
df = spark.createDataFrame(
[(1, 1.0), (1, 2.0), (2, 3.0), (2, 5.0), (2, 10.0)],
("id", "v"))
def subtract_mean(pdf):
# pdf is a pandas.DataFrame
v = pdf.v
return pdf.assign(v=v - v.mean())
df.groupby("id").applyInPandas(subtract_mean, schema="id long, v double").show()
# +---+----+
# | id| v|
# +---+----+
# | 1|-0.5|
# | 1| 0.5|
# | 2|-3.0|
# | 2|-1.0|
# | 2| 4.0|
# +---+----+
For detailed usage, please see pyspark.sql.GroupedData.applyInPandas
.
Map
Map operations with Pandas instances are supported by DataFrame.mapInPandas()
which maps an iterator
of pandas.DataFrame
s to another iterator of pandas.DataFrame
s that represents the current
PySpark DataFrame
and returns the result as a PySpark DataFrame
. The functions takes and outputs
an iterator of pandas.DataFrame
. It can return the output of arbitrary length in contrast to some
Pandas UDFs although internally it works similarly with Series to Series Pandas UDF.
The following example shows how to use mapInPandas()
:
df = spark.createDataFrame([(1, 21), (2, 30)], ("id", "age"))
def filter_func(iterator):
for pdf in iterator:
yield pdf[pdf.id == 1]
df.mapInPandas(filter_func, schema=df.schema).show()
# +---+---+
# | id|age|
# +---+---+
# | 1| 21|
# +---+---+
For detailed usage, please see pyspark.sql.DataFrame.mapsInPandas
.
Co-grouped Map
Co-grouped map operations with Pandas instances are supported by DataFrame.groupby().cogroup().applyInPandas()
which
allows two PySpark DataFrame
s to be cogrouped by a common key and then a Python function applied to each
cogroup. It consists of the following steps:
- Shuffle the data such that the groups of each dataframe which share a key are cogrouped together.
- Apply a function to each cogroup. The input of the function is two
pandas.DataFrame
(with an optional tuple representing the key). The output of the function is apandas.DataFrame
. - Combine the
pandas.DataFrame
s from all groups into a new PySparkDataFrame
.
To use groupBy().cogroup().applyInPandas()
, the user needs to define the following:
- A Python function that defines the computation for each cogroup.
- A
StructType
object or a string that defines the schema of the output PySparkDataFrame
.
The column labels of the returned pandas.DataFrame
must either match the field names in the
defined output schema if specified as strings, or match the field data types by position if not
strings, e.g. integer indices. See pandas.DataFrame
on how to label columns when constructing a pandas.DataFrame
.
Note that all data for a cogroup will be loaded into memory before the function is applied. This can lead to out of memory exceptions, especially if the group sizes are skewed. The configuration for maxRecordsPerBatch is not applied and it is up to the user to ensure that the cogrouped data will fit into the available memory.
The following example shows how to use groupby().cogroup().applyInPandas()
to perform an asof join between two datasets.
import pandas as pd
df1 = spark.createDataFrame(
[(20000101, 1, 1.0), (20000101, 2, 2.0), (20000102, 1, 3.0), (20000102, 2, 4.0)],
("time", "id", "v1"))
df2 = spark.createDataFrame(
[(20000101, 1, "x"), (20000101, 2, "y")],
("time", "id", "v2"))
def asof_join(l, r):
return pd.merge_asof(l, r, on="time", by="id")
df1.groupby("id").cogroup(df2.groupby("id")).applyInPandas(
asof_join, schema="time int, id int, v1 double, v2 string").show()
# +--------+---+---+---+
# | time| id| v1| v2|
# +--------+---+---+---+
# |20000101| 1|1.0| x|
# |20000102| 1|3.0| x|
# |20000101| 2|2.0| y|
# |20000102| 2|4.0| y|
# +--------+---+---+---+
For detailed usage, please see pyspark.sql.PandasCogroupedOps.applyInPandas()
.
Usage Notes
Supported SQL Types
Currently, all Spark SQL data types are supported by Arrow-based conversion except MapType
,
ArrayType
of TimestampType
, and nested StructType
.
Setting Arrow Batch Size
Data partitions in Spark are converted into Arrow record batches, which can temporarily lead to high memory usage in the JVM. To avoid possible out of memory exceptions, the size of the Arrow record batches can be adjusted by setting the conf “spark.sql.execution.arrow.maxRecordsPerBatch” to an integer that will determine the maximum number of rows for each batch. The default value is 10,000 records per batch. If the number of columns is large, the value should be adjusted accordingly. Using this limit, each data partition will be made into 1 or more record batches for processing.
Timestamp with Time Zone Semantics
Spark internally stores timestamps as UTC values, and timestamp data that is brought in without
a specified time zone is converted as local time to UTC with microsecond resolution. When timestamp
data is exported or displayed in Spark, the session time zone is used to localize the timestamp
values. The session time zone is set with the configuration ‘spark.sql.session.timeZone’ and will
default to the JVM system local time zone if not set. Pandas uses a datetime64
type with nanosecond
resolution, datetime64[ns]
, with optional time zone on a per-column basis.
When timestamp data is transferred from Spark to Pandas it will be converted to nanoseconds
and each column will be converted to the Spark session time zone then localized to that time
zone, which removes the time zone and displays values as local time. This will occur
when calling toPandas()
or pandas_udf
with timestamp columns.
When timestamp data is transferred from Pandas to Spark, it will be converted to UTC microseconds. This
occurs when calling createDataFrame
with a Pandas DataFrame or when returning a timestamp from a
pandas_udf
. These conversions are done automatically to ensure Spark will have data in the
expected format, so it is not necessary to do any of these conversions yourself. Any nanosecond
values will be truncated.
Note that a standard UDF (non-Pandas) will load timestamp data as Python datetime objects, which is
different than a Pandas timestamp. It is recommended to use Pandas time series functionality when
working with timestamps in pandas_udf
s to get the best performance, see
here for details.
Recommended Pandas and PyArrow Versions
For usage with pyspark.sql, the supported versions of Pandas is 0.24.2 and PyArrow is 0.15.1. Higher versions may be used, however, compatibility and data correctness can not be guaranteed and should be verified by the user.
Compatibility Setting for PyArrow >= 0.15.0 and Spark 2.3.x, 2.4.x
Since Arrow 0.15.0, a change in the binary IPC format requires an environment variable to be
compatible with previous versions of Arrow <= 0.14.1. This is only necessary to do for PySpark
users with versions 2.3.x and 2.4.x that have manually upgraded PyArrow to 0.15.0. The following
can be added to conf/spark-env.sh
to use the legacy Arrow IPC format:
ARROW_PRE_0_15_IPC_FORMAT=1
This will instruct PyArrow >= 0.15.0 to use the legacy IPC format with the older Arrow Java that
is in Spark 2.3.x and 2.4.x. Not setting this environment variable will lead to a similar error as
described in SPARK-29367 when running
pandas_udf
s or toPandas()
with Arrow enabled. More information about the Arrow IPC change can
be read on the Arrow 0.15.0 release blog.


The best technical fest ever
Crescendo brings to you an exciting and mindblowing platform where you sure can flaunt your Techxiness. This is where fun meets technology and gives rise to the exceptional ideas . Each year Crescendo sees a new face of technology. Improvising is what we believe in and that's what we do in our tech fest . We improvise with technology. From technical competitions to FIFA , from workshops to counterstrike, from guest lectures to laser tag . Crescendo always has something techxy for everyone. Over the years Crescendo has given the minds a chance to take their take on technology and showcase what they believe in.
AT CRESCENDO THE FUN JUST BEGINS.. ..NEVER ENDS.. ..
 So here are the people behind the scene this crescendo.
CREDITSOur College
Fr. Conceicao Rodrigues College of Engineering
Fr. Conceicao Rodrigues College of Engineering (CRCE), popularly known as Fr. Agnel Bandra, is an un-aided, minority, non-autonomous institute affiliated to the University of Mumbai offering B.E. degrees in Computers, Electronics, Production and Information Technology branches.
CHECK US OUT


ContentList.Rd
R6Class
for storing content in a list. Note that
this$container()
and this$set_session(session)
must be called
in order for the content list to work properly.
content_list <- ContentList$new("content")
new(id, sortable = FALSE)
Initialize the content list.
id | Character . The id of the
content list's container. If the session associated with the content
list is a session proxy (session inside of a module), the id gets
namespaced. |
sortable | Currently defunct. |
container()
Call this function in the UI definition. This function returns the div-element containing the content list.
set_session(session)
Call this function in the server function to connect the content list with a session.
session | A shiny session object. |
add_element(content_element)
Add a content element to the content list. If this particular element has already been added and it is currently hidden, it gets shown.
content_element | A content element object. |
add_element_actionButton(content_element, actionButton_id,
actionButton_session)
Add a content element to the content list, that gets
displayed after an actionButton
has been
clicked.
content_element | A content element object. |
actionButton_id | The inputId associated with the
actionButton . |
actionButton_session | The shiny session
object that the actionButton belongs
to. |
add_element_by_id(content_element_id)
Show the content element
with id == content_element_id
.
append_tab(content_element_id, tab, select = FALSE)
Append a
tab to the content element with id == content_element_id
.
content_element_id | Character .
The id of the content element. |
tab | The item to be added (must be created with
tabPanel ). |
select | If TRUE tab gets
selected upon being inserted. |
get_content_element_by_id(content_element_id)
Get the content
element with id == content_element_id
.
get_content_element_ids()
Get the ids of the content elements
as a character
vector.
hide_content_element_by_id(content_element_id)
Hide the content
element with id == content_element_id
.
update_tab(content_element_id, selected)
Update the selected
tab of the content element with id == content_element_id