Hello, and welcome to my online portfolio. My name is Rachel Broering and I'm currently a first-year student at the School of Advertising Art in Kettering, where I am studying to become a hybrid designer.
I have experience with the Adobe Creative Suite, web development, digital media, photography, graphic design, digital illustration, 3D modeling and video editing thanks to all of my schooling. My main focus is web design/development and I love to further my knowledge on this ever evolving industry.


| Date | Ticket No. | Unload Time | Commodity | Name/Farm | Contract # | Gross | Tare | Unload | Net Weight | Action | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| {{result.date | date}} | RI-{{result.ticketNumber}} | {{result.unloadTime}} | {{result.commodityId.commodityName}} | {{result.growerFullName}} | {{result.contractNumber}} | {{result.grossWeight| number:3}} | {{result.tareWeight| number:3}} | {{result.unloadWeidht | number:3}} | {{result.netWeight | number:3}} |
| This document is | SPECIAL BIN ELEVATOR RECEIPT |
INTERIM PRIMARY ELEVATOR RECEIPT (subject to grade and dockage) |
PRIMARY ELEVATOR RECEIPT | Non CGA Grain | Non Producer Purchase |
| Scale Record in Metric Tonnes | Received this day for storage from | |
|---|---|---|
|
GROSS
WEIGHT
{{scaleTicketDetails.grossWeightMT}}
|
Producer’s Name and Address (surname first) |
CONTRACT #
{{scaleTicketDetails.contractNumber}}
|
|
TARE
WEIGHT
{{scaleTicketDetails.tareWeightMT}}
|
{{scaleTicketDetails.growerFullName}} |
STATION NAME
RUDY AGRO
|
|
UNLOAD WEIGHT
{{scaleTicketDetails.unloadWeidhtMT}}
|
{{scaleTicketDetails.growerId.addresses[0].street}}
|
STATION NO.
|
|
|
{{(scaleTicketDetails.growerId.addresses[0].town+' '+scaleTicketDetails.growerId.addresses[0].country+' '+scaleTicketDetails.growerId.addresses[0].province+' '+scaleTicketDetails.growerId.addresses[0].postal)}}
|
BIN NO.
{{scaleTicketDetails.binNumber}}
|
|
{{result.analysisId.analysisName}}
{{result.value | number:3}}%
{{result.weightMT | number:3}}
|
|
|
|
|
Grain
{{scaleTicketDetails.commodityId.commodityName}}
|
SAMPLE TICKET
|
|
INTERIM GRADE
{{scaleTicketDetails.delGrade}}
|
MOISTURE
{{scaleTicketDetails.moisture}}
|
| Size 7 | {{scaleTicketDetails.sizeKabuli[0]["size7"]}} |
| Size 8 | {{scaleTicketDetails.sizeKabuli[0]["size8"]}} |
| Size 9 | {{scaleTicketDetails.sizeKabuli[0]["size9"]}} |
| Size 10 | {{scaleTicketDetails.sizeKabuli[0]["size10"]}} |
On surrender of this receipt and the payment or tender of all lawful charges in respect of the grain described. The identical grain will be delivered either
(a) by the discharge of the grain into a railway car or other conveyance made available for loading at this elevator or
(b) by the substitution for this and like receipts, together covering a quantity not less than a carload lot, of an elevator receipt for grain of the identical quantity and grade, and subject only to the dockage above specified, issued in the prescribed form by a terminal, process or transfer elevator to which shipment of the said grain, upon notice or otherwise, is authorized by the Canada Grain Act.
Upon the surrender of this receipt after delivery of the Commission report as to the grade and dockage of the above sample, there shall be issued in lieu ofthis receipt a Primary Elevator Receipt or Cash Purchase Ticket for grain of the grade reported by the inspecting officer, subject to the dockage specified.
Upon surrender of this receipt and the payment or tender of all lawf ul charges in respect of the grain described, either a cash purchase ticket shall be issuedfor the net weight of grain of the grade specified or like grain described on this receipt will be delivered to the holder of this receipt
(a) by the discharge of the grain into a railway car or other conveyance made available for loading at this elevator, or
(b) by the substitution for this and like receipts, together covering a quantity not less than a carload lot, of an elevator receipt for grain of the same quantity and grade, and subject only to the dockage above specified, issued in the prescribed form by a terminal, process or transfer elevator to whichshipment of the grain, upon notice or otherwise, is authorized by the Canada Grain Acl.


→
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Class: {{selectedStudent.classroomName}}
Grade: {{selectedStudent.gradeLevel}}
Age: {{selectedStudent.age}}
Parent First Name: {{selectedStudent.parentFirst}}
Parent Last Name: {{selectedStudent.parentLast}}
Parent Email: {{selectedStudent.parentEmail}}
Emergency Contact: {{selectedStudent.emergencyNumber}}
Student Address: {{selectedStudent.address}}
Student Allergies: {{selectedStudent.allergies}}
Student Emotion Total Score: {{selectedStudent.totalScore}}


The Trailer For Ian Somerhalder’s New Netflix Series Is Here & Consider My Pickle Tickled
by By Steffanie TanSomewhere out there Damon Salvatore is quaking, because Ian Somerhalder is back baby but he’s no longer a vampire. He’s a vampire, uh, curer / maybe-killer.
Netflix has released the trailer for its new series V Wars, based on the comics of the same name by Jonathan Maberry and Alan Robinson. Somerhalder plays Dr Luther Swann – a human – whose entire world goes to shits when a mysterious disease transforms his best friend, Michael Fayne (Adrian Holmes) into a murderous predator who feeds on humans. As the disease spreads, society fractures, and Swann must race against time to find a cure while his best mate rises to become the powerful underground leader of the vampires. Dun-dun-DUNNNN.
“My people and I are not terrorist, and have as much right to live as anybody else. As horrible as it will be, this war is also necessary. Blood nation will prevail,” Fayne says in the trailer.
The trailer starts off as incredibly moody and dark, and then it just gets plain saucy. And Somerhalder? The man apparently does not age.
Netflix has ordered 10 episodes for season 1 so that’s a solid amount of binge material you have there.
V Wars will premiere December 5 on Netflix.
Surely, surely, Dr Swann will become a vampire at some point. SURELY.
And, if you’re interested in true crime, Netflix will release its latest documentary based on a serial killer on December 6. The content, it never ends.
The Confession Killer is a five-part series based on infamous American serial killer Henry Lee Lucas, who confessed to hundreds of unsolved murder cases during the ’80s. The thing is, he was only ever convicted of murdering three people, including his mother.
You can read more about the new docuseries below.
Image: Netflix / V Wars


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Here are a few ways to give back this Thanksgiving
by Kyle HicksGluttony and greed are typically the main hallmarks of Thanksgiving and Black Friday, but they certainly don’t have to be.
While devouring a plate full of hot food and shopping for the hottest items can provide a dose of satisfaction, nothing compares to giving back.
There are endless ways to volunteer or donate your time around Thanksgiving. Here are a few ideas:
Run in a Turkey Trot race
It has become a tradition for some in the United States to participate in Turkey Trot races around Thanksgiving. Not only do they help you burn off the calories from all the food, the proceeds from many races are donated to local organizations to help those in need.
These types of races vary in names and length. They’ve also been called things like “Drumstick Dash” or “Mashed Potato Mile." Most Turkey Trots are in the 3-to 5-mile distance category, but some are longer or shorter.
Volunteer your time
If running’s not your thing, there are other ways to get out and help your community. The amount of opportunities can be overwhelming, but resources like VolunteerMatch.org can help match you with an opportunity near you that matches your skills and interests.
Deliver meals
Everyone deserves a hot meal on Thanksgiving. Sadly, not everyone has family to celebrate with or can get out of the house to cook a meal themselves. That’s where organizations like Meals on Wheels come in. In addition to donating your time, you can also contribute food to your community’s branch as well.
Donate to local food banks
Donating to food banks is a great way to give back any time of the year, but especially around Thanksgiving. Organizations like Feeding America make it super easy to find a food bank near you to donate to. The Feeding America network secures and distributes 4.3 billion meals each year through food pantries and meal programs in the U.S.
Make a monetary donation
If you can’t make time to volunteer with an organization in person, you can make a donation. But before you donate though, make sure the charity you choose is legit by verifying it through online vetting tools, like the Better Business Bureau’s Give.org.
Help military families
Unfortunately, military families can struggle to make ends meet. That’s where Operation Homefront steps in. Its annual Holiday Meals for Military program began on Nov. 14.
“The program provides lower- and mid-grade ranking military families with all the grocery items necessary for a full holiday meal, helping to ease a widely felt financial burden and to make the holiday season brighter for those who sacrifice so much.”
Since the program began in 2009, more than 100,000 meals have been provided to military families across the country. Click here to learn about how to donate or volunteer with the organization.


This section is used to define which scopes can be selected by third parties when they register a client through the Openid Connect Dynamic Client Registration endpoint.
On the client registration process, access management will only retain the allowed scopes (if enabled).


You can manage your favorite points of interest around Tokyo. Feel free to order your favorite places and plan a personal trip for yourself! Note that changes won't be saved unless you click the "Save Changes" button.
| Name | Image | Category | Views | Rating | Order | Remove |
|---|---|---|---|---|---|---|
| {{poi.Name}} | {{poi.CategoryName}} | {{poi.Views}} | {{(100 * poi.Rating/5).toFixed(2)}}% |
|
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LEAVE IT TO BEAVER
A Film Review by James Berardinelli
RATING (0 TO 10): 3.5 Alternative Scale: *1/2 out of ****
United States, 1997 U.S. Release Date: 8/22/97 (wide) Running Length: 1:30 MPAA Classification: PG (Mature themes) Theatrical Aspect Ratio: 1.85:1
Cast: Cameron Finley, Christopher McDonald, Janine Turner, Erik von Detten, Grace Phillips, Adam Zolotin Director: Andy Cadiff Producers: Brian Levant and Robert Simonds Screenplay: Brian Levant & Lon Diamond Cinematography: Thomas Del Ruth Music: Randy Edelman U.S. Distributor: Universal Pictures
Why? That's the question foremost in my mind when I consider this latest motion picture retread of a defunct television series. Why was this movie made in the first place? If it had to be made, why didn't it take the BRADY BUNCH MOVIE's satirical approach? And why didn't the film makers consider that there might be someone in the audience over the age of 10? Most importantly, why did I bother seeing this film in the first place?
Let me preface this review by stating that I am not a fan of the television series LEAVE IT TO BEAVER, nor have I ever been. I have seen no more than a handful of episodes, and was neither impressed nor enchanted. This new motion picture, which attempts to modernize the Cleavers by placing them in the 1990s, affected me in the same way.
Perhaps the powers that be should have taken a lesson from how THE BRADY BUNCH made their small-to-big screen transformation. Turning this into a straightforward satire might have gone a long way towards reducing the level of tediousness in LEAVE IT TO BEAVER. Alas, with the exception of an occasional sly aside, this film plays it mostly straight. The one advantage of this approach is that the movie illustrates just how embarrassingly bad the original sit-com is by today's entertainment standards, especially with all the nostalgia stripped away.
The story plays like a very looooooong episode of the TV series (updated to the '90s, of course -- now June can say "crap"). 8-year old Beaver Cleaver (Cameron Finley) has his brand new bicycle stolen by a local hoodlum while big brother Wally (Erik von Detten), who is supposed to be watching out for him, is busy making goo-goo eyes at a girl. Dad (Christopher McDonald) yells at both of them, then softens up when his wife, June (Janine Turner), makes him realize that he's being too domineering. Meanwhile, the neighborhood conniver, Eddie Haskell (Adam Zolotin), is mad at Wally for stealing "his girl," and enjoys seeing his rival lose her to a roughneck who happens to be friends with the bike thief.
Ho hum. To be fair, LEAVE IT TO BEAVER has its moments, the best of which is an off-the-wall family therapy session during which Wally lets out some unexpected truths. Considering how good this scene is, I can't determine why first-time feature director Andy Cadiff didn't opt for the same irreverent tone throughout. Likewise, some of the modern characteristics of the Cleaver parents hold a promise that isn't developed. June shows a few sexpot tendencies and there are times when Ward appears close to grabbing the nearest sharp object and slicing his family to pieces. Unfortunately, rather than being accentuated, these aspects are underplayed, causing me to wonder if there might have been some more openly campy elements in an earlier version of the script.
The acting is hodgepodge of mediocre performances, with only Christopher McDonald doing anything interesting with his character (he opts for playing Ward tongue-in-cheek as often as he can). Janine Turner, best known for her recurring role as Maggie in NORTHERN EXPOSURE, is as stiff as a board. Teen actors Erik von Detten and Adam Zolotin are largely unconvincing. And young Cameron Finley, who plays the title character, gets high marks for cuteness, but isn't a particularly strong actor. LEAVE IT TO BEAVER is light on cameos, with brief appearances by Barbara Billingsley (June) and Ken Osmond (Eddie) being the most notable. The absence of several key original cast members, particularly Jerry Mathers (Beaver) and Tony Dow (Wally), is curious, to say the least.
Fans of LEAVE IT TO BEAVER will undoubtedly enjoy this movie more than I did. To me, however, this seems like a wasted opportunity to do something inventive -- perhaps to improve upon what was done with THE BRADY BUNCH. About the best thing I can say about LEAVE IT TO BEAVER is that it's innocuous. Some people find that to be a positive quality. Personally, it's about the last thing I look for in a movie. And, while LEAVE IT TO BEAVER may not be one of the worst films of the year, I certainly won't be recommending it to anyone. It's just another television series that is diminished by the transition to the big screen.
Copyright 1997 James Berardinelli
- James Berardinelli e-mail<EMAIL_ADDRESS>ReelViews web site: http://www.cybernex.net/~berardin
"A film is a petrified fountain of thought." - Jean Cocteau
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


About Me
The name is Davis, Bradley L. Davis. I like building satellites and robots, watching movies, playing boards games, and cooking. I sometimes take photos and videos, as well.
Currently at Washington State University, Go Cougs!, I am studying Electrical Engineering. My portfolio contains many circuit boards mainly for CougSat-1. It is a nanosatellite I am leading the engineering efforts for in WSU’s Cougs in Space. The electronics work is mainly embedded microcontroller systems with occasional radio frequency components. Part of my role in the club is providing systems engineering to manage the vast complexities that is a satellite.
I am also a software engineer. With building microcontroller systems, comes the obligatory software. I often help design, implement, test, and review this code. The most exciting software I have written (and still am writing) for Cougs in Space is the software defined radio. At my internship at Schweitzer Engineering Laboratories, I created gigabit ethernet burden software as well as many automation scripts.
Many years ago, I participated in FIRST Robotics Challenge in which I led a team of mechanical designers and CADers to create a human-sized robot in less than six weeks. The programmers, electricians, machinist, and fabricators wanted to have a couple weeks to do their thing; furthermore, high school has a thing called “homework” and “sleep”, so actual design duration was much shorter. If you want to check out my professional work or club contributions, head over to my portfolio. For my personal projects, visit my laboratories.
Outside of class, work, and projects, I enjoy spending time with my friends. With that comes watching countless movies, binging series, baking and indulging in chocolaty goods, and playing games. Ooh, and cooking. From tator tot casserole to smoked salmon to mac and cheese with Cougar Gold, I make it all. When I have time, traveling is fun too.
My main drive for life is my continued exploration of valuable knowledge, exciting experiences, and innovative ideas. In every activity, I push the boundaries of myself and the topic.


CustomerDisputes
public final class CustomerDisputes: PayPalController
Occasionally, something goes wrong with a customer’s order. To dispute a charge, a customer can create a dispute with PayPal. PayPal merchants, partners, and external developers can use the PayPal Customer Disputes API to manage customer disputes.
Note
Merchants cannot create disputes but can only respond to customer-created disputes.A customer can also ask his or her bank or credit card company to dispute and reverse a charge, which is known as a chargeback. For more information, see Disputes, claims, chargebacks, and bank reversals.
When a customer disputes a charge, you can use this API to provide evidence that the charge is legitimate. To provide evidence or appeal a dispute, you submit a proof of delivery or proof of refund document or notes, which can include logs.
Normally, an agent at PayPal updates the status of disputes and settles them, but now you can run test cases in the sandbox that complete these operations.
For details, see Customer Disputes Integration Guide and the Marketplace Disputes Integration Guide.
Use the /customer/disputes/
resource to list disputes, show dispute details, send a message to the other party, make an offer to resolve a dispute,
escalate a dispute to a claim, provide evidence, accept a claim, and appeal a dispute. Normally, an agent at PayPal updates the status of disputes and
settles them, but now you can run test cases in the sandbox that update the dispute status and settle disputes.
-
Declaration
Swift
public let container: Container
-
Value is
"customer/disputes"
.See
PayPalController.resource
for more information.Declaration
Swift
public let resource: String
-
Declaration
Swift
public init(container: Container)
-
Lists disputes with a full or summary set of details. Default is a summary set of details, which shows the
dispute_id
,reason
,status
,dispute_amount
,create_time
, andupdate_time fields
.To filter the disputes in the response, specify one or more optional query parameters. To limit the number of disputes in the response, specify the
page_size
query parameter.To list multiple disputes, set these query parameters in the request:
page_size=2
start_time
instead ofdisputed_transaction_id
If the response contains more than two disputes, it lists two disputes and includes a HATEOAS link to the next page of results.
The querystring parameters that this endpoint can use are
startTime
,pageSize
, andpage
. Along with these standard querystrings, there are two parameters that are endpoint specific:disputed_transaction_id
: Filters the disputes in the response by a transaction, by ID. You can specify either but not both the start_time and disputed_transaction_id query parameter.dispute_state
: Filters the disputes in the response by a state. The allowed values are:REQUIRED_ACTION
: Filters the disputes in the response in REQUIRED_ACTION dispute_stateREQUIRED_OTHER_PARTY_ACTION
: Filters the disputes in the response in REQUIRED_OTHER_PARTY_ACTION stateUNDER_PAYPAL_REVIEW
: Filters the disputes in the response in UNDER_PAYPAL_REVIEW stateRESOLVED
: Filters the disputes in the response in RESOLVED stateOPEN_INQUIRIES
: Filters the disputes in the response in OPEN_INQUIRIES state
A successful request returns the HTTP
200 OK
status code and a JSON response body that lists disputes with a full or summary set of details. Default is a summary set of details, which shows thedispute_id
,reason
,status
,dispute_amount
,create_time
, andupdate_time
fields for each dispute.Declaration
Swift
public func list(parameters: QueryParamaters = QueryParamaters()) -> Future<CustomerDisputeList>
Parameters
parameters
The querystring paramaters sent with the request.
Return Value
A list of customer disputes wrapped in a future. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Shows details for a dispute, by ID.
Note
The fields that appear in the response depend on whether you access this call through first- or third-party access. For example, if the merchant shows dispute details through third-party access, the customer’s email ID does not appear.A successful request returns the HTTP
200 OK
status code and a JSON response body with dispute details.Declaration
Swift
public func details(for disputeID: String) -> Future<CustomerDispute>
Return Value
A customer dispute wrapped in a future. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Accepts liability for a claim, by ID, which closes the dispute in the customer’s favor. PayPal automatically refunds money to the customer from the merchant’s account.
A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func accept(claim disputeID: String, with body: AcceptDisputeBody) -> Future<[LinkDescription]>
Parameters
disputeID
The ID of the dispute for which to accept a claim.
body
The body of the request.
Return Value
An array containing a link to the dispute wrapped in a future. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Sandbox only. Settles a dispute in either the customer’s or merchant’s favor. Merchants can make this call in the sandbox to complete end-to-end dispute resolution testing, which mimics the dispute resolution that PayPal agents normally complete. To make this call, the dispute
status
must beUNDER_REVIEW
.A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Throws
A
500 Internal Server Error
if you call this method in a production environment.Declaration
Swift
public func settle(dispute id: String, outcome: AdjudicationOutcome)throws -> Future<[LinkDescription]>
Parameters
id
The ID of the dispute to settle.
outcome
The outcome of the settled dispute.
Return Value
An array containing a link to the dispute wrapped in a future. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Appeals a dispute, by ID. To appeal a dispute, use the
appeal
link in the HATEOAS links from the show dispute details response. If this link does not appear, you cannot appeal the dispute. Submit new evidence as a document or notes in the JSON request body. For information about dispute reasons, see dispute reasons.A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func appeal(dispute id: String, evidence: [Evidence]) -> Future<[LinkDescription]>
Parameters
id
The PayPal dispute ID.
evidences
An array of evidences for the dispute.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Escalates the dispute, by ID, to a PayPal claim. To make this call, the stage in the dispute lifecycle must be
INQUIRY
.A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func escalate(dispute id: String, note: String) -> Future<[LinkDescription]>
Parameters
id
The PayPal dispute ID.
note
The notes about the escalation of the dispute to a claim. Length must be between 1 and 2,000.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Makes an offer to the other party to resolve a dispute, by ID. To make this call, the stage in the dispute lifecycle must be
INQUIRY
. If the customer accepts the offer, PayPal automatically makes a refund.A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func offerResolution(for disputeID: String, offer: CustomerDispute.ResolutionOffer) -> Future<[LinkDescription]>
Parameters
disputeID
The ID of the dispute to make the resoultion offer on.
offer
The specific information about the offer. This is the body of the request sent to the PayPal API.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Provides evidence for a dispute, by ID. A merchant can provide evidence for disputes with the
WAITING_FOR_SELLER_RESPONSE
status while customers can provide evidence for disputes with theWAITING_FOR_BUYER_RESPONSE
status. Evidence can be a proof of delivery or proof of refund document or notes, which can include logs. A proof of delivery document includes a tracking number while a proof of refund document includes a refund ID.The following rules apply to document file types and sizes:
- The merchant can upload up to 10 MB of files for a case.
- Individual files must be smaller than 5 MB.
- The supported file formats are JPG, GIF, PNG, and PDF.
To make this request, specify the dispute ID in the URI and specify the evidence in the JSON request body. For information about dispute reasons, see dispute reasons.
A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func evidence(for disputeID: String, file: File, evidences: [Evidence]) -> Future<[LinkDescription]>
Parameters
disputeID
The ID of the dispute for which to submit evidence.
file
The name of a file with evidence.
evidences
An array of evidences for the dispute.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Sandbox only. Updates the status of a dispute, by ID, from UNDER_REVIEW to either
WAITING_FOR_BUYER_RESPONSE
orWAITING_FOR_SELLER_RESPONSE
.This status change enables either the customer or merchant to submit evidence for the dispute. To make this call, the dispute
status
must beUNDER_REVIEW
. Specify anaction
value in the JSON request body to indicate whether the status change enables the customer or merchant to submit evidence.If the
action
isBUYER_EVIDENCE
, Thestatus
updates toWAITING_FOR_BUYER_RESPONSE
. If theaction
isSELLER_EVIDENCE
, Thestatus
updates toWAITING_FOR_SELLER_RESPONSE
.Declaration
Swift
public func updateStatus(of disputeID: String, with action: UpdateAction)throws -> Future<[LinkDescription]>
Parameters
disputeID
The ID of the dispute that requires evidence.
action
The action. Indicates whether the state change enables the customer or merchant to submit evidence.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.
-
Sends a message to the other party in the dispute, by ID.
A successful request returns the HTTP
200 OK
status code and a JSON response body that includes a link to the dispute.Declaration
Swift
public func message(dispute id: String, content: String) -> Future<[LinkDescription]>
Parameters
id
The ID of the dispute for which to send a message.
content
The message sent by the merchant to the other party.
Return Value
An array of request-related HATEOAS links. If an error response was sent back instead, it gets converted to a Swift error and the future wraps that instead.


tspsolver.ga package¶
Subpackages¶
Submodules¶
tspsolver.ga.crossover module¶
-
class
tspsolver.ga.crossover.
AbstractCrossoverOperator
(pcross=0.6, use_rog=False)[source]¶ Bases:
object
-
class
tspsolver.ga.crossover.
OnePointPMX
(pcross=0.6, use_rog=False)[source]¶ Bases:
tspsolver.ga.crossover.AbstractCrossoverOperator
Create a new population using one point PMX crossover. The pivot location of the split is determined uniformly at random.
-
class
tspsolver.ga.crossover.
OrderCrossover
(pcross=0.6, use_rog=False)[source]¶ Bases:
tspsolver.ga.crossover.AbstractCrossoverOperator
Create a new population by keeping a subtour of the chromosome and then copying from the other parent.
-
class
tspsolver.ga.crossover.
TwoPointPMX
(pcross=0.6, use_rog=False)[source]¶ Bases:
tspsolver.ga.crossover.AbstractCrossoverOperator
Create a new population using one point PMX crossover. The pivot location of the split is determined uniformly at random.
tspsolver.ga.mutation module¶
-
class
tspsolver.ga.mutation.
DisplacementMutation
(pmutate=0.5)[source]¶ Bases:
tspsolver.ga.mutation.AbstractMutationOperator
Mutate indivudals in a population by randomly moving a subtour in the chromosome.
-
class
tspsolver.ga.mutation.
InsertionMutation
(pmutate=0.5)[source]¶ Bases:
tspsolver.ga.mutation.AbstractMutationOperator
Mutate indivduals in a population by randomly removing and reinserting a gene in a different part of the chromosome.
-
class
tspsolver.ga.mutation.
InversionMutation
(pmutate=0.5)[source]¶ Bases:
tspsolver.ga.mutation.AbstractMutationOperator
Mutate indivudals in a population by randomly moving a subtour in the chromosome then reversing it.
-
class
tspsolver.ga.mutation.
SwapCityMutation
(pmutate=0.5)[source]¶ Bases:
tspsolver.ga.mutation.AbstractMutationOperator
Mutate indivudals in a population by randomly swapping two genes.
tspsolver.ga.population_generation module¶
-
class
tspsolver.ga.population_generation.
AbstractPopulationGenerator
(population_size, **kwargs)[source]¶ Bases:
object
-
class
tspsolver.ga.population_generation.
KNNPopulationGenerator
(*args, **kwargs)[source]¶ Bases:
tspsolver.ga.population_generation.AbstractPopulationGenerator
Generate a population based using the k nearest neighbours for each city.
-
class
tspsolver.ga.population_generation.
SimplePopulationGenerator
(population_size, **kwargs)[source]¶ Bases:
tspsolver.ga.population_generation.AbstractPopulationGenerator
Generate a population based on randomly shuffling 1D array of the indicies of every data point. This makes no attempt to consider any heuristic.
tspsolver.ga.selection module¶
-
class
tspsolver.ga.selection.
AbstractSelectionOperator
(**kwargs)[source]¶ Bases:
object
-
fitness
(population)[source]¶ Evaluate the fitness of a population
Parameters: population – 2D array representing the population of solutions. Returns: array of total distances representing the fitness of each solution Return type: ndarray
-
get_fitness
()[source]¶ Get the cached fitness of the most recent population.
Returns: the fitness for a population
-
selection
(population, distance_matrix)[source]¶ Choose a subset of a population to breed from.
Parameters: - population – 2D array representing the population of solutions.
- distance_matrix – the distance matrix of points in the dataset
Returns: a subset of the population which are the fittest
Return type: ndarray
-
-
class
tspsolver.ga.selection.
RouletteWheelSelection
(**kwargs)[source]¶ Bases:
tspsolver.ga.selection.AbstractSelectionOperator
Roulette Wheel Selection
Implements fitness propotionate or “roulette wheel” selection. Individuals are selected with probability that is directly proportional to their fitness
tspsolver.ga.simulator module¶
-
class
tspsolver.ga.simulator.
Simulator
(**params)[source]¶ -
evolve
(data)[source]¶ Evolve a solution to the TSP problem.
Parameters: distance_matrix – a distance matrix for the points in the dataset Returns: chromosome representing the best solution found. Return type: 1Darray
-
get_averge_fitness
()[source]¶ Get the averge fitness of over all iterations
Returns: list of the average fitness over all iterations Return type: 1Darray
-
get_max_fitness
()[source]¶ Get the maximum fitness of over all iterations
Returns: list of the maximum fitness over all iterations Return type: 1Darray
-
get_min_fitness
()[source]¶ Get the minimum fitness of over all iterations
Returns: list of the minimum fitness over all iterations Return type: 1Darray
-
initilize_population
(data)[source]¶ Initilize the first population to a random set fo solutions
Parameters: distance_matrix – distance matrix for points in the dataset Returns: a random population of solutions Return type: 2Darray
-
load_component
(name, params, module_name)[source]¶ Loads a sub component of the GA.
This method dynamically sets up an instance of a class defined by the parameters passed to the system.
Parameters: - name – the name of the type of component to load
- params – the parameter dictionary defining the algorithm
- module_name – the name of the python module to load from
Returns: a new instance of the component with it’s paramters set
Return type: Object
-
perform_crossover
(population)[source]¶ Apply the crossover operator to a population
Parameters: population – the population to apply the operator too
-
perform_mutation
(population)[source]¶ Apply the mutation operator to a population
Parameters: population – the population to apply the operator too
-
perform_selection
(population, distance_matrix)[source]¶ Apply the selection operator to a population
Parameters: - population – the population to apply the operator too
- distance_matrix – distance matrix for points in the dataset
-
score
(X)[source]¶ Score function runs the genetic algorithm and returns the best fitness achieved.
This is useful in parameter tuning to evaluate the settings of the GA.
Parameters: X – the data to run the GA with Returns: an integer representing the best fitness achieved by this GA Return type: Int
-
set_params
(**parameters)[source]¶ Set the parameters of the GA
This takes a flat dictionary of keyword arguments for each of the components of the GA. Parameters must be named according to the convention ‘<component>_<param name>’. E.g. ‘crossover_pcross’.
This format is require for integration with scikit-learn tools, such as the ParameterGrid function.
Parameters: parameters – dictionary of parameters for the GA.
-


Let’s try the query-first approach to start designing the data model for a hotel application. The user interface design for the application is often a great artifact to use to begin identifying queries. Let’s assume that you’ve talked with the project stakeholders and your UX designers have produced user interface designs or wireframes for the key use cases. You’ll likely have a list of shopping queries like the following:
It is often helpful to be able to refer to queries by a shorthand number rather that explaining them in full. The queries listed here are numbered Q1, Q2, and so on, which is how they are referenced in diagrams throughout the example.
Now if the application is to be a success, you’ll certainly want customers to be able to book reservations at hotels. This includes steps such as selecting an available room and entering their guest information. So clearly you will also need some queries that address the reservation and guest entities from the conceptual data model. Even here, however, you’ll want to think not only from the customer perspective in terms of how the data is written, but also in terms of how the data will be queried by downstream use cases.
You natural tendency as might be to focus first on designing the tables to store reservation and guest records, and only then start thinking about the queries that would access them. You may have felt a similar tension already when discussing the shopping queries before, thinking “but where did the hotel and point of interest data come from?” Don’t worry, you will see soon enough. Here are some queries that describe how users will access reservations:
All of the queries are shown in the context of the workflow of the application in the figure below. Each box on the diagram represents a step in the application workflow, with arrows indicating the flows between steps and the associated query. If you’ve modeled the application well, each step of the workflow accomplishes a task that “unlocks” subsequent steps. For example, the “View hotels near POI” task helps the application learn about several hotels, including their unique keys. The key for a selected hotel may be used as part of Q2, in order to obtain detailed description of the hotel. The act of booking a room creates a reservation record that may be accessed by the guest and hotel staff at a later time through various additional queries.
Material adapted from Cassandra, The Definitive Guide. Published by O’Reilly Media, Inc. Copyright © 2020 Jeff Carpenter, Eben Hewitt. All rights reserved. Used with permission.


Boston, MA
Location:
3rd floor Atrium
McGovern Institute for Brain Research [Directions]
Massachusetts Institute of Technology
Registration:
Sign up online. When you register please provide us with your lunch choices along with whether or not you plan to attend the organized dinner on Saturday Night (attendees pay for their own dinner). If you do not provide us with your lunch choices, you will not get free lunch. In addition, please indicate whether you are interested in working with/on the Neuroelectrics headset.
Other Information:
- The doors will be locked on the day of the event. When you get to the door, please call 4-3544 or<PHONE_NUMBER>) or post a chat message to: https://gitter.im/satra/brainhackEDT and someone will come let you in.
- Amazon is providing credits for cloud computing ($100 per person): register here.
- NeuroElectrics will be bringing a couple of their Enobio wireless EEG headsets for interested parties to hack on. Please indicate on your registration if you are interested in working with one of these devices.
- If you have a project idea for Brainhack EDT Boston, we would like to hear about it. Please add it to: http://goo.gl/fSMgc3
- Project proposal introductions will be 1 minute. If you want to use a slide to introduce your project, please send the powerpoint slide to<EMAIL_ADDRESS>Schedule:
| Saturday, October 18, 2014 | |
| 08:30 | Attendee Arrival (with coffee) |
| 09:00 | Welcome reception |
| 09:15 | Ignite Talk with icebreaker |
| 09:45 | Project Pitch |
| 10:00 | Open Hacking |
| 12:00 | Onsite Lunch (Mexicali) |
| 13:00 | Crowd Annotation Projects (Dolphin Brain) |
| 13:45 | Unconference Session, click here to tune in. |
| 15:00 | Coffee Break |
| 15:30 | Open Hacking |
| 18:30 | Organized dinner (pay your own way) |
| 20:30 | Open Hacking |
| Sunday, October 19, 2014 | |
| 08:30 | Attendee Arrival |
| 09:00 | Ignite Session #2 click here to tune in. |
| 09:30 | Unconference Session, click here to tune in. |
| 10:30 | Open Hacking |
| 12:30 | Onsite Lunch (Mexicali) |
| 13:30 | Open Hacking |
| 15:00 | Coffee Break |
| 15:30 | Open Hacking |
| 17:00 | Project Summaries and Wrap-up, click here to tune in. |
| 18:30 | Adjournment |
| 19:00 | Optional Dinner or Open Hacking |
Organizers:
- Satra Gosh, PhD, Research Scientist, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Boston, MA
- Matt Hutchison, PhD, Postdoctoral Fellow, Center for Brain Science, Harvard University, Boston, MA
- Donald McLaren, PhD, Research Fellow, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA and Postdoctoral Research Fellow, GRECC, Bedford VA


--- layout: post status: publish published: true title: Take-Two Interactive shatters Wall St. estimates, GTA V hits 29 million copies sold author: display_name: mvukas login: mvukas email<EMAIL_ADDRESS>url: '' author_login: mvukas author_email<EMAIL_ADDRESS>wordpress_id: 336 wordpress_url: http://mattvukas.com/?p=336 ---
Take-Two Interactive (NASDAQ: TTWO) is the publisher behind various big name video game franchises, such as Bioshock, NBA 2K, and others. But their most lucrative series is without a doubt Grand Theft Auto, and their earnings release today clearly demonstrates that.
Take-Two Interactive shattered Wall Street's consensus estimate of $1.48 EPS for Q2 and instead reported earnings of $2.49 per share around 4pm EST today. Also of note is that Grand Theft Auto V has also sold around 29 MILLION copies, after being out for only six weeks.
Despite some concerns from investors over the past year about demand going soft, it seems that the video game industry is still rip roaring and making profits like never before. Electronic Arts (NASDAQ: EA) also reported earnings today, beating Wall Street estimates and rising in after-hours trading. With the launch of the new Xbox One and PlayStation 4 consoles coming later this year, in addition to brisk sales of current-generation games, it seems that competition from mobile gaming and the more "casual" social gaming scene has done nothing to impede the success of the traditional video game industry.


There are numbers, syllables, alphabet, various characters, but the character used by the computer is only two "0" and "1".
Usually, if you add 1 in 9, it will be 10 and 2 characters, but because there is only 0 and 1, only 1 will be added to 1, so it will be 10 (one zero) and 2 characters.
This is a binary number.
"BIN$" command that change the number to binary number.
The symbol "` "(shift + "@" or left of "1") converts a binary number to a number.
0, 1, 2, 3, 4 ... count it with binary number.
Binary numbers count with "bit".
3 is 2 bits with "11", 8 is 4 bits with "1000".
Try it!
1. Let's make "16" a binary number
2. Let' make the binary numbers "101", "1010", "10100" a number
3. Let's make "40" to binary number
4. What is the maximum number that can be represented by 5 bits?
5. Let's make "-1" a binary number


Feature List
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Question 4 Rationale:
- Cephalexin (KEFLEX).[CORRECT. Cephalexin (KEFLEX) is a 1st-generation cephalosporin. People with a penicillin allergy may cross-react with cephalosporins. Therefore, a patient with a severe penicillin allergy should not taking Cephalexin (KEFLEX).]
- Kanamycin Sulfate (KANAMYCIN). [Kanamycin sulfate (KANAMYCIN) is an aminoglycoside antibacterial that does not cross-react with penicillins.]
- Ciprofloxacin (CIPRO). [Ciprofloxacin (CIPRO) is a quinolone antibacterial tht does not cross-react with penicillins.]
- Clarithromycin (BIAXIN). [Clarithromycin (BIAXIN) is a macrolide antibacterial tht does not cross-react with penicillins.]
Click here to go back to the quiz


Foolscap comes with an advanced event-logging package. This package is used internally to record connection establishment, remote message delivery, and errors. It can also be used by applications built on top of Foolscap for their own needs.
This logging package includes a viewer application that processes locally saved log data or data retrieved over a foolscap connection, and displays a selected subset of the events. It also includes code to create a web page inside your application that presents the same kind of log view.
My background is in embedded systems, specifically routers, in which bugs and unexpected operations happen from time to time, causing problems. In this environment, storage space is at a premium (most routers do not have hard drives, and only a limited amount of RAM and non-volatile flash memory), and devices are often deployed at remote sites with no operator at the console. Embedded devices are expected to function properly without human intervention, and crashes or other malfunctions are rare compared to interactive applications.
In this environment, when an error occurs, it is a good idea to record as much information as possible, because asking the operator to turn on extra event logging and then try to re-create the failure is only going to make the customer more angry ("my network has already broken once today, you want me to intentionally break it again?"). That one crash is the only chance you have to learn about the cause.
In addition, as new features are being developed (or completed ones are being debugged), it is important to have visibility into certain internal state. Extra logging messages are added to illuminate this state, sometimes resulting in hundreds of messages per second. These messages are useful only while the problem is being investigated. Since most log formats involve flat text files, lots of additional log messages tend to obscure important things like unhandled exceptions and assertion failures, so once the messages have outlived their usefulness they are just getting in the way. Each message costs a certain amount of human attention, so we are motiviated to minimize that cost by removing the unhelpful messages.
Logging also gets removed because it consumes CPU time, disk IO, disk space, or memory space. Many operations that can be done in linear time can expand to super-linear time if additional work is required to log the actions taking place, or the current state of the program.
As a result, many formerly-useful log messages are commented out once they have served their purpose. Having been disabled, the cost to re-enable them if the bug should resurface is fairly high: at the very least it requires modifying the source code and restarting the program, and for some languages requires a complete recompile/rebuild. Even worse, to keep the source code readable, disabled log messages are frequently deleted altogether. After many months it may not be obvious where the log messages should be put back, and developers will need to re-acquaint themselves with the code base to find suitable places for those messages.
To balance these costs, developers try to leave enough log messages in place that unexpected events will be captured with enough detail to start debugging, but not so many that it impacts performance or a human's ability to spot problems while scanning the logs. But it would be nice if certain log messages could be disabled or disregarded in a way that didn't abandon all of the work that went into developing and placing them.
Each potential log message could be described (to a human) as being useful in a particular set of circumstances. For example, if the program tried to read from a file and got a permission-denied error, it would be useful to know which file it was trying to read from, and how it came to decide upon that particular filename, and what user command was responsible for triggering this action. If a protocol parser which implements a state machine finds itself in an invalid state, it would be useful to know what series of input messages had arrived recently, to work backwards to the place where things started to go awry.
Flip this around and you can phrase it as: the filename we compute will be interesting only if we get an error when we finally try to access it. Likewise, the series of input messages would be interesting to know if, at some point in the near future, an invalid protocol state is reached.
The thing to note about these patterns is that an event at time T causes events before time T to become interesting. Interesting messages are worth keeping (and storing, and examining). Non-interesting messages are not worth as much, but there are different kinds of costs, and as the message becomes less interesting (or loses the potential to become interesting), we want to lower our costs. Displaying a message to a human is pretty expensive, since it tends to obscure other, more important messages. Storing messages is less expensive, depending upon how long we expect to store them (and how much storage space is available). Generating messages may be expensive or cheap, depending upon their frequency and complexity.
Foolscap's logging library seeks to capture this ex-post-facto interestingness by categorizing messages into "severity levels", recording each level into a separate size-limited circular buffer, and provoking a dump of all buffers when an "Incident" occurs. An "Incident Qualifier" is used to classify certain higher-severity events as worthy of triggering the log dump. The idea is that, at any given time, we have a record (in memory) of a lot of low-frequency important things (like program startup, user actions, and unhandled exceptions), and only the most recent high-frequency events (verbose debugging data). But, if something strange happens, we dump everything we've got to disk, because it is likely that some of these noisy high-frequency not-normally-interesting events will be helpful to track down the cause of the unusual event. The viewing tools then rearrange all of these events into a linear order, and make it easy to filter out events by severity level or origin.
Each severity level is (roughly) inversely proportional to a message rate. Assertion checks in code are in the "this should never happen" category, and their resulting low expected rate puts them in a high-severity level. Routine actions are expected to happen all the time, which puts them into a low-severity level.
(you might think of severity as a separate axis than frequency. Severity would mean "how much damage will this cause". Frequency equals cost, controlling how long we keep the message around in the hopes of it becoming interesting. But things which cause a lot of damage should not be happening very frequently, and things which happen frequently must not cause a lot of damage. So these axes are sufficiently aligned for us to use just a single parameter for now.)
The usual approach to event logging involves a single file with a sequence of lines of text, new events being continually appended at the end, perhaps with the files being rotated once they become too large or old. Typically the source code is peppered with lines like:
log.msg(text) Log.Log(source, facility, severity, text) log.log_stacktrace() log.err(failure)
Each such function call adds some more text to the logfile, encoding the various parameters into a new line.
Using a text-based file format enables the use of certain unix tools like 'grep' and 'wc' to analyze the log entries, but frequently inhbits the use of more complex tools because they must first parse the human-readable lines back into the structured arguments that were originally passed to the log() call. Frequently, the free-form text portion of the log cannot be reliably distinguished from the stringified metadata (the quoting issue), making analysis tools more difficult to write. In addition, the desire to make both logfiles and the generating source code more greppable is occasionally at odds with clean code structure (putting everything on a single line) or refactoring goals (sending all logging for a given module through a common function).
The Foolscap log system uses binary logfiles that accurately and reversibly serialize all the metadata associated with a given event. Tools are provided to turn this data into a human-readable greppable form, but better tools are provided to perform many of the same tasks that 'grep' is typically used for. For example, a log viewer can apply a python expression to each event as a filter, and the expression can do arbitrary comparison of event parameters (e.g. "show me all events related to failing uploads of files larger than 20MB").
To accomplish this, all unrecognized keyword arguments to the
log.msg
call are recorded as additional keys in the log event.
To encourage structured usage, the message string be provided as a format
specifier instead of a pre-interpolated string, using the keyword args as a
formatting dictionary. Any time the string is displayed to a human, the
keyword args are interpolated into the format string first.
(in compiled languages, it would be useful and cheap to embed the source file and line number of the log() call inside the log event. Unfortunately, in Python, this would require expensive stack crawling, so developers are generally stuck with grepping for the log message in their source tree to backtrack from a log message to the code that generated it)
Code is provided to allow a Foolscap-based application to easily publish a
'logport': an object which providers remote callers with access to that
application's accumulated log data. Events are delivered over a secure
Foolscap connection, to prevent eavesdroppers from seeing sensitive data
inside the log messages themselves. This can be useful for a developer who
wants to find out what just happened inside a given application, or who is
about to do something to the application and wants to see how it responds
from the inside. The flogtool tail
tool is provided for this
job.
Each Tub always activates a logport, and a Tub option makes it possible to use a persistent FURL for remote access.
(TODO: really?) The log-viewer application can either read log data from a local log directory, or it can connect to the logport on a remote host.
A centralized "log gatherer" program can connect to multiple logports and aggregate all the logs collected from each, similar to the unix 'syslog' facility. This is most useful when the gatherer is configured to store more messages than the applications (perhaps it stores all of them), since it allows the costs to be shifted to a secondary machine with extra disk and fewer CPU-intensive responsibilities.
To facilitate this, each Tub can either be given the FURL of a Log Gatherer, or the name of a file that might contain this FURL. This makes deployment easier: just copy the FURL of your central gatherer into this file in each of your application's working directories.
A basic log gatherer is created by running flogtool
create-gatherer
and giving it a storage directory: this emits a
gatherer FURL that can be used in the app configuration, and saves all
incoming log events to disk.
Log messages correspond to events. Events are triggered by other events. Sometimes the relationship between events is visible to the local programmer, sometimes it involves external hosts that can confuse the relationships.
For local "application-level" causality, Foolscap's logging system makes
it possible to define hierarchies of log events. Each call to
log.msg
returns an identifier (really just a number). If you
pass this same identifier into a later log.msg
call as the
parent=
parameter, that second message is said to be a "child"
of the first. This creates multiple trees of log events, in which the tree
tops are the parentless messages. For example, a user command like "copy this
file" could be a top-level event, while the various steps involved in copying
the file (compute source filename, open source file, compute target filename,
open target file, read data, write data, close) would be children of that
top-level event.
The viewer application has a way to hide or expand the nodes of these trees, to make it easy to look at just the messages that are related to a specific action. This lets you prioritize events along both severity (is this a common event?) and relevance (is this event related to the one of interest?)
In the future, Foolscap's logging system will be enhanced to offer tools for analyzing causality relationships between multiple systems, taking inspiration from the E Causeway debugger. In this system, when one Tub sends a message to another, enough data is logged to enable a third party (with access to all the logs) to figure out the set of operations that were caused by the first message. Each message send is recorded, with an index that includes the TubID, current event number, and stack trace. Event A on tub 1 triggers event B on tub 2, along with certain operations and log messages. Event B triggers further operations, etc.
The viewer application will offer a causality-oriented view in addition to the temporal one.
The majority of your application's interaction with the Foolscap logging
system will be in the form of calls to its log.msg
function.
To emit log messages from application code, just use the
foolscap.log.msg
function:
from foolscap.logging import log log.msg("hello world")
You can add arguments that will be lazily evaluated and stringified by treating the log message as a normal format string:
log.msg("queue depth %d exceeds limit %d", current_depth, limit)
Or you can use keyword arguments instead. The format string can use positional parameters, or keyword arguments, but not both.
log.msg(format="Danger %(name)s %(surname)s", name="Will", surname="Robinson")
Passing arguments as separate parameters (instead of interpolating them
before calling log.msg
has the benefit of preserving more
information: later, when you view the log messages, you can apply python
filter expressions that use these parameters as search criteria.
Regardless of how you format the main log message, you can always pass additional keyword arguments, and their values will be serialized into the log event. This will not be automatically stringified into a printed form of the message, but it will be available to other tools (either to filter upon or to display):
log.msg("state changed", previous=states[now-1], current=stats[now])
There are a number of arguments you can add to the log.msg
call that foolscap will treat specially:
parent = log.msg(facility="app.initialization", level=log.INFREQUENT, msg="hello world", stacktrace=False) log.msg(facility="app.storage", level=log.OPERATIONAL, msg="init storage", stacktrace=False, parent=parent)
The level
argument is how you specify a severity level, and
takes a constant from the list defined in foolscap/log.py
:
BAD
: something which significantly breaks functionality.
Unhandled exceptions and broken invariants fall into this category.SCARY
: something which is a problem, and shouldn't happen
in normal operation, but which causes minimal functional impact, or from
which the application can somehow recover.WEIRD
: not as much of a problem as SCARY, but still not
right.CURIOUS
INFREQUENT
: messages which are emitted as a normal course
of operation, but which happen infrequently, perhaps once every ten to one
hundred seconds. User actions like triggering an upload or sending a
message fall into this category.UNUSUAL
: messages which indicate events that are not
normal, but not particularly fatal. Examples include excessive memory or
CPU usage, minor errors which can be corrected by fallback code. OPERATIONAL
: messages which are emitted as a normal course
of operation, like all the steps involved in uploading a file, potentially
one to ten per second..NOISY
: verbose debugging about small operations,
potentially emitting tens or hundreds per secondThe stacktrace
argument controls whether or not a stack trace
is recorded along with the rest of the log message.
The parent
argument allows messages to be related to earlier
messages.
Each Tub offers a log method: this is just like the process-wide
log.msg
described above, but it adds an additional parameter
named tubid
. This is convenient during analysis, to identify
which messages came from which applications.
class Example: def __init__(self): self.tub = Tub() ... def query(self, args): self.tub.log("about to send query to server") self.server.callRemote("query", args).addCallback(self._query_done)
Facility names are up to the application: the viewer app will show a list
of checkboxes, one for each facility name discovered in the logged data.
Facility names should be divided along functional boundaries, so that
developers who do not care about, say, UI events can turn all of them off
with a single click. Related facilities can be given names separated with
dots, for example "ui.internationalization" and "ui.toolkit", and the
viewer app may make it easy to enable or disable entire groups at once.
Facilities can also be associated with more descriptive strings by calling
log.explain_facility
at least once:
log.explain_facility("ui.web", "rendering pages for the web UI")
Sometimes it is the user of your application who is in the best position to decide that something weird has taken place. Internal consistency checks are useful, but the user is the final judge of what meets their needs. So if they were expecting one thing to happen and something else happened instead, they should be able to declare that an Incident has taken place, perhaps by pushing a special "That Was Weird" button in your UI.
To implement this sort of button for your user, just take the user's reason string and log it in an event at level WEIRD or higher. Since events at this level trigger Incidents by default, Foolscap's normal incident-handling behavior will take care of the rest for you.
def that_was_weird_button_pushed(reason): log.msg(format="The user said that was weird: %(reason)s", reason=reason, level=log.WEIRD)
Foolscap's logging system is always enabled, but the unconfigured initial state is lacking a number of useful features. By configuring the logging system at application startup, you can enable these features.
The first missing piece is that it does not have a place to save log events in the event of something strange happening, so the short-term circular buffers are the only source of historical log events.
To give the logging system some disk space to work with, just give it a logdir. The logging system will dump the circular buffers into this directory any time something strange happens, and both the in-memory buffers and the on-disk records are made available to viewing applications:
from foolscap.logging import log log.setLogDir("~/saved-log-events") # == log.theLogger.setLogDir
The foolscap logging code does not delete files from this directory. Applications which set up a logdir should arrange to delete old files once storage space becomes a problem. TODO: we could provide a maximum size for the logdir and have Foolscap automatically delete the oldest logfiles to stay under the size limit: this would make the disk-based logdir an extension of the memory-based circular buffers.
Foolscap's logging subsystem uses the term "Incident" to describe the
"something strange" that causes the buffered log events to be dumped. The
logger has an "Incident Qualifier" that controls what counts as an incident.
The default qualifier simply fires on events at severity level
log.WEIRD
or higher. You can override the qualifier by
subclassing foolscap.logging.incident.IncidentQualifier
and
calling log.setIncidentQualifier
with an instance of your new
class. For example, certain facilities might be more important than others,
and you might want to declare an Incident for unusual but relatively
low-severity events in those facilities:
from foolscap.logging import log, incident class BetterQualifier(incident.IncidentQualifier): def check_event(self, ev): if ev.get('facility',"").startswith("lifesupport"): if ev['level'] > log.UNUSUAL: return True return incident.IncidentQualifier.check_event(self, ev) log.setIncidentQualifier(BetterQualifier())
The qualifier could also keep track of how many events of a given type had occurred, and trigger an incident if too many UNUSUAL events happen in rapid succession, or if too many recoverable errors are observed within a single operation.
Once the Incident has been declared, the "Incident Reporter" is
responsible for recording the recent events to the file on disk. The default
reporter copies everything from the circular buffers into the logfiles, then
waits an additional 5 seconds or 100 events (whichever comes first),
recording any trailing events into the logfile too. The idea is to capture
the application's error-recovery behavior: if the application experiences a
problem, it should log something at the log.WEIRD
level (or
similar), then attempt to fix the problem. The post-trigger trailing event
logging code should capture the otherwise-ordinary events performed by this
recovery code.
Overlapping incidents will be combined: if an incident reporter is already active when the qualifier sees a new triggering event, that event is just added to the existing reporter.
The incident reporter can be overridden as well, by calling
log.setIncidentReporterFactory
with a class that will
produce reporter instances. For example, if you wanted to increase the
post-trigger event recording to 1000 events or 10 seconds, then you could do
something like this:
from foolscap.logging import log, incident class MoreRecoveryIncidentReporter(incident.IncidentReporter): TRAILING_DELAY = 10.0 TRAILING_EVENT_LIMIT = 1000 log.setIncidentReporterFactory(MoreRecoveryIncidentReporter)
Recorded Incidents will be saved in the logdir with filenames like
incident-2008-05-02--01-12-35Z-w2qn32q.flog.bz2
, containing both
a (UTC) timestamp and a random/unique suffix. These can be read with tools
like flogtool dump
and flogtool web-viewer
.
The logport
is a foolscap.Referenceable
object
which provides access to all available log events. Viewer applications can
either retrieve old events (buffered in RAM or on disk), or subscribe to hear
about new events that occur later. The logport implements the
foolscap.logging.interfaces.RILogPublisher
interface, which
defines the methods that can be called on it. Each Tub automatically creates
and registers a logport: the tub.getLogPort()
and
tub.getLogPortFURL()
methods make it possible to grant access to
others:
t = Tub() ... # usual Tub setup: startService, listenOn, setLocation logport_furl = t.getLogPortFURL() # this is how you learn the logport furl print "please point your log viewer at: %s" % logport_furl logport = t.getLogPort() # a Referenceable you can pass over the wire rref.callRemote("please_use_my_logport", logport)
The default behavior is register the logport object with an ephemeral
name, and therefore its FURL will change from one run of the program to the
next. This can be an operational nuisance, since the external log viewing
program you're running (flogtool tail LOGPORT
) would need a new
FURL each time the target program is restarted. By giving the logport a place
to store its FURL between program runs, the logport gets a persistent name.
The logport-furlfile
option is used to identify this file. If
the file exists, the desired FURL will be read out of it. If it does not, the
newly-generated FURL will be written into it.
If you use logport-furlfile
, it must be set before you call
getLogPortFURL
(and also before you pass the result of
getLogPort
over the wire), otherwise an ephemeral name will have
already been registered and the persistent one will be ignored. The call to
setOption
can take place before setLocation
, and
the logport-furlfile will be created as soon as both the filename and the
location hints are known. However, note that the logport will not be
available until after setLocation
is called:
getLogPortFURL
and getLogPort
will raise
exceptions.
tub.setOption("logport-furlfile", "~/logport.furl") print "please point your log viewer at: %s" % tub.getLogPortFURL()
This logport.furl
file can be read directly by other tools if
you want to point them at an operating directory rather than the actual
logport FURL. For example, the flogtool tail
command (described
below) can accept either an actual FURL, or the directory in which a file
named logport.furl
can be located, making it easier to examine
the logs of a local application. Note that the logport-furlfile
is chmod'ed go-r
, since it is a secret: the idea is that only
people with access to the application's working directory (and presumeably to
the application itself) should get access to the logs.
The third feature that requires special setup is the log gatherer. You can either tell the Tub a specific gatherer to use, or give it a filename where the FURL of a log gatherer is stored.
The tub.setOption("log-gatherer-furl", gatherer_FURL)
call
can be used to have the Tub automatically connect to one or more log
gatherers and offer its logport. The Tub uses a Reconnector to make sure the
gatherer connection is reestablished each time it gets dropped.
t = Tub() t.setOption("log-gatherer-furl", gatherer_FURL)or
t = Tub() t.setOption("log-gatherer-furl", gatherer_FURLs)
Alternatively, you can use the
tub.setOption("log-gatherer-furlfile", "~/gatherer.furl")
call
to tell the Tub about a file where a gatherer FURL might be found. If that
file exists, the Tub will read a FURL from it, otherwise the Tub will not use
a gatherer. The file can contain multiple log-gatherer FURLs, one per line.
This is probably the easiest deployment mode:
t = Tub() t.setOption("log-gatherer-furlfile", "~/gatherer.furl")
In both cases, the gatherer FURL is expected to point to a remote object
which implements the foolscap.logging.RILogGatherer
interface
(such as the service created by flogtool create-gatherer
). The
Tub will connect to the gatherer and offer it the logport.
The log-gatherer-furl
and log-gatherer-furlfile
options can be set at any time, however the connection to the gatherer will
not be initiated until setLocation
is called.
There are two other logging systems that the Foolscap logging code knows
how to handle: twisted.python.log
and the stdlib
logging
system.
First, a brief discussion of the single-instance nature of Foolscap's
logging is in order. Each process that uses Foolscap gets a single instance
of the Foolscap logging code (named theLogger
and defined at
module level in foolscap.logging.log
). This maintains a single
logdir. Each time a process is started it gets a new "incarnation record",
which consists of a randomly generated (unique) number, and (if a logdir is
available) (TODO) a continuously incrementing sequence number. All log events
are tagged with this incarnation record: it is used to distinguish between
event#23 in one process versus the same event number from a different
process.
Each Tub has a distinct TubID, and all log events that go through the Tub
(via tub.log
) are tagged with this TubID. Each Tub maintains its
own logport (specifically there is a single LogPublisher
object,
but like all Referenceables it can be registered in multiple Tubs and gets a
distinct FURL for each one).
Twisted's logging mechanism is used by importing
twisted.python.log
and invoking its log.msg()
and
log.err
methods. This mechanism is used extensively by Twisted
itself; the most important messages are those concerning "Unhandled Error in
Deferred" and other exceptions in processing received data and timed calls.
The normal destination for Twisted log messages depends upon how the
application is run: the twistd
daemonization tool sends the log
messages to a file named twistd.log
, the trial
unit-test tool puts them in _trial_temp/test.log
, and standalone
scripts discard these logs by default (unless you use something like
log.startLogging(sys.stderr)
).
To capture these log messages, you need a "bridge", which will add a Twisted log observer and copy each Twisted log message into Foolscap. There can be at most one such bridge per python process. Either you will use a generic bridge (which tags each message with the incarnation record), or you will use a Tub as a bridge (which additionally tags each message with the TubID). Each time you set the twisted log bridge, any previous bridge is discarded.
When you have only one Tub in an application, use the Tub bridge. Likewise if you have multiple Tubs but there is one that is long-lived, use that Tub for the bridge. If you have mutiple Tubs with no real primary one, use the generic bridge. Using a Tub bridge adds slightly more information to the log events, and may make it a bit easier to correlate Twisted log messages with actions of your application code, especially when you're combining events from several applications together for analysis.
To set up the generic bridge, use the following code:
from foolcap.logging import log log.bridgeTwistedLogs()
To set up a Tub bridge, use this instead:
t = Tub() t.setOption("bridge-twisted-logs", True)
Note that for Tub bridges, the Twisted log messages will only be delivered while the Tub is running (specifically from the time its startService() method is until its stopService() method is called). TODO: review this behavior, we want earlier messages to be bridged too.
To bridge log events in the other direction (i.e. taking foolscap log
messages and copying them into twisted), use the
log.bridgeLogsToTwisted()
call, or the
FLOGTOTWISTED
environment variable. This is useful to get
foolscap.logging.log.msg() events copied into twistd.log
. The
default filter only bridges non-noisy events (i.e. those at level OPERATIONAL
or higher), and does not bridge foolscal internal events.
You might use this if you don't buy into the foolscap logging philosophy and really want log events to be continually written out to disk. You might also use it if you want a long-term record of operationally-significant events, or a record that will survive application crashes which don't get handled by the existing Incident-recording mechanism.
from foolscap.logging import log log.bridgeLogsToTwisted()
stdlib logging
messages must be bridged in the same way. TODO:
define and implement the bridge setup
To take advantage of the parent/child causality mechanism, you must use
Foolscap's native API. (to be precise, you can pass in parent=
to either Twisted's log.msg
or stdlib's
logging.log
, but to get a handle to use as a value to
parent=
you must use foolscap.log.msg
, because
neither stdlib's nor Twisted's log calls provide a return value)
There is a separate circular buffer (with some maximum size) for each combination of level and facility. After each message is added, the size of the buffer is checked and enough old messages are discarded to bring the size back down to the limit. Each facility uses a separate set of buffers, so that e.g. the NOISY messages from the "ui" facility do not evict the NOISY messages from the "upload" facility.
The sizes of these buffers can be controlled with the
log.set_buffer_size
function, which is called with the severity
level, the facility name, and the desired buffer size (maximum number of
messages). If set_buffer_size
is called without a facility name,
then it will set the default size that will be used when a log.msg call
references an as-yet-unknown facility).
log.set_buffer_size(log.NOISY, 10000) log.set_buffer_size(level=log.NOISY, facility="upload", size=10000) log.allocate_facility_buffers("web") print log.get_buffer_size(log.NOISY, facility="upload")
If the message to be logged is below some threshold, it will not even be generated. This makes it easy to leave the log line in the source code, but not consume CPU time or memory space by actually using it. Such messages must be enabled before use (either through the logport (TODO) or by restarting the application with different log settings(TODO)), but at least developers will not have to re-learn the source code to figure out where it might be useful to add some messages. This threshold can be configured for all facilities at the same time, or on a facility-by-facility basis.
log.set_generation_threshold(log.NOISY) log.set_generation_threshold(level=log.OPERATIONAL, facility="web") print log.get_generation_threshold() print log.get_generation_threshold(facility="web")
There are a variety of ways for humans (and their tools) to read and
analyze log messages. The flogtool
program, provided with
Foolscap, provides access to many of them.
flogtool dump
: look at the saved log events (in a logdir)
and display their contents to stdout. Options are provided to specify the
log source, the facilities and severity levels to display, and grep-like
filters on the messages to emit. flogtool tail
: connect to a logport and display new log
events to stdout. The --catchup
option will also display old
events.flogtool gtk-viewer
: a Gtk-based graphical tool to examine
log messages.flogtool web-viewer
: runs a local web server, through
which log events can be examined.This tool uses a log-viewing API defined in
foolscap/logging/interfaces.py
. (TODO) Application code can use
the same API to get access to log messages from inside a python program.
(NOTE: this section is incomplete and has not been implemented)
Many of these tools share the concept of "Log Views". This is a particular set of filters which can be applied to the overall log event stream. For example, one view might show all events that are UNUSUAL or worse. Another view might show NOISY messages for the "ui" facility but nothing else.
Each view is described by a set of thresholds: each facility gets a severity threshold, and all messages at or above the threshold will be included in the view. While in principle there is a threshold for each facility, this may be expressed as a single generic threshold combined with overrides for a few specific facilities.
A "Log Observer" can be attached to a foolscap-using program (either internally or by subscribing through the flogport). Once attached, this observer will receive a stream of log messages, which the observer is then free to format, store, or ignore as it sees fit.
Each log message is a dictionary, as defined in specifications/logfiles.
def observe(event): print strftime(fmt, event.timestamp) print event["level"] # a number print event.get("facility" # a string like "ui" print event["message"] # a unicode object with the actual event text log.theLogger.addObserver(observe)
A "Log Gatherer" is a python server to which the process under examination sends some or all of its log messages. These messages are saved to a file as they arrive, so they can be examined later. The resulting logfiles can be compressed, and they can be automatically rotated (saved, rename, reopened) on a periodic interval. In addition, sending a SIGHUP to the gatherer will cause it to rotate the logfiles.
To create one, choose a new directory for it to live in, and run
"flogtool create-gatherer
". You can then start it with "twistd",
and stop it by using the twistd.pid
file:
% flogtool create-gatherer lg Gatherer created in directory lg Now run '(cd lg && twistd -y gatherer.tac)' to launch the daemon % cd lg % ls gatherer.tac % twistd -y gatherer.tac % ls from-2008-07-28--13-30-34Z--to-present.flog log_gatherer.furl twistd.pid gatherer.pem portnum gatherer.tac twistd.log % cat log_gatherer.furl pb://g7yntwfu24w2hhb54oniqowfgizpk73d@<IP_ADDRESS>:54611,<IP_ADDRESS>:54611/z4ntcdg4jpdg3pnabhmyu3qvi3a7mdp3 % kill `cat twistd.pid` %
The log_gatherer.furl
string is the one that should be
provided to all applications whose logs should be gathered here. By using
tub.setOption("log-gatherer-furlfile", "log_gatherer.furl")
in
the application, you can just copy this .furl file into the application's
working directory.
An "Incident Gatherer" is like a Log Gatherer, but it only gathers weirdness-triggered Incidents. It records these incidents into files on the local disk, and provides access to them through a web server. The Incident Gatherer can also be configured to classify the incidents into various categories (perhaps expressions of a specific bug), to facilitate analysis by separating known problems from new ones.
To create one, choose a new directory for it to live in, and run
"flogtool create-incident-gatherer
", just like the log
gatherer:
% flogtool create-incident-gatherer ig Gatherer created in directory ig Now run '(cd ig && twistd -y gatherer.tac)' to launch the daemon % cd ig % ls gatherer.tac % twistd -y gatherer.tac %
Inside the gatherer's base directory (which we refer to as BASEDIR here),
the incidents/
directory will contain a subdirectory for each
tub that connects to the gatherer. Each subdir will contain the incident
files, named incident-TIMESTAMP-UNIQUE.flog.bz2
.
A simple unix command like find BASEDIR/incidents -name
'incident-*.flog.bz2'
will locate all incident files. Each incident
file can be examined with a tool like flogtool dump
. The format
is described in the Logfiles
specification docs.
The Incident Gatherer uses a collection of user-supplied classification
functions to analyze each Incident and place it into one or more categories.
To add a classification function, create a file with a name like
"classify_*.py
" (such as classify_foolscap.py
or
classify_db.py
), and define a function in it named
"classify_incident()
". Place this file in the gatherer's
directory. All such files will be loaded and evaluated when the gatherer
starts.
The classify_incident()
function will accept a single
triggering event (a regular log Event dictionary, see logfiles.xhtml for
details, which can be examined as follows:
def classify_incident(trigger): m = trigger.get('message', '') if "Tub.connectorFinished:" in m: return 'foolscap-tubconnector'
The function should return a list (or set) of categories, or a single category string, or None. Each incident can wind up in multiple categories. If no function finds a category for the incident, it will be added to the "unknown" category. All incidents are added to the "all" category.
The classified/
directory will contain a file for each
defined classification. This file will contain one line for each incident
that falls into that category, containing the BASEDIR-relative pathname of
the incident file (i.e. each line will look like
incidents/TUBID/incident-TIMESTAMP-UNIQUE.flog.bz2
). The
classified/all
file will contain the same filenames as the
find
command described earlier.
If the classified/
directory does not exist when the gatherer
is started, all stored Incidents will be re-classified. After modifying or
adding classification functions, you should delete the
classified/
directory and restart the gatherer.
The Incident Gatherer can run a small webserver, to publish information
about the incidents it collects. The plan is to have it publish an RSS feed
of incidents by category, and to serve incidents as HTML just like the
foolscap web-viewer
command. This code is not yet written.
The Incident Gatherer can also be configured to send email with a description of the incident for various categories. The incident report will be included as an attachment for further analysis. This code is not yet written.


Digital Jam 2.0
Mobile Application Development Workshop
Workshop #2: Friday May 25 to May 29
Held at the University of the West Indies, Mona, St. Andrew
Math Lecture Hall and Lab
Two lecture and Lab sessions per day: 1pm-4pm, 6pm -9pm (or later)
Workshop #1: Monday April 30th, 2012 to Friday May 4
Held at the University of the West Indies, Mona, St. Andrew
Math Lecture Hall and Lab
Three lecture and Lab sessions per day: 10am-1pm, 2pm-5pm, 6pm -9pm (or later)
This workshop is free of charge
The Digital Jam 2.0 Mobile Applications Development workshop will help young developers move ahead of the technical curve by specializing in cutting edge technologies that let developers build effective native mobile applications (e.g. for the iPhone and Android or Blackberry phones) using cross-platform tools that deliver greater flexibility and speed to market.
The five days of intensive development support will focus on two key objectives:
1. Support development of skills of all participants – from beginners to advanced programmers – as needed for to work as a team to implement commercial-strength mobile application.
2. Establish the partnerships between creative/art practitioners and engineering/programming specialist as needed to deliver uniquely exciting offerings.
Mobile application development requires programming and art skills and course work typically programing covered a by 12 week course at college level. The 5 day workshop can only give a taste and provide assistance to people already along this path.
The approach will be open and dynamic, with the activities of each day depending of the progress made on the previous day and the needs of the participants. After the first day of team and individual assessments, sessions will be structured to meet the differing needs of beginning, intermediate and advanced programmers. One will not need to attend all sessions for the workshop to meet your needs.
REGISTER FOR WORKSHOP ONLINE
Please provide IMPORTANT REGISTRATION INFORMATION by filling out the REGISTRATION FORM on the Digital Jam 2.0 App Community Forum main page to help us structure the workshop to best meet your needs.
www.digijam.biz
BRING A LAPTOP to the workshop if you have one.


Components
ScriptableObjects
Plain C# Classes
AgentEventType : EntityType : ScriptableObject
What is an Agent Event Type?
An Agent Event Type contains the main configuration for an Agent Event. It inherits from Entity Type which
is also the base class for Agent Type and World Object Type.
See Agent Event for more info.
Agent Event Type Custom Inspector
Entity Type Fields
See Entity Type for info on Entity Type Info, Prefab Variants, Placement Info, Tags, Inventory, and Entity Triggers.
Timing
| How long to wait for min number of attendees? If this time is exceeded the Agent Event will terminate. | |
| Time To Wait After Min | Once the min number of attendees is reached, how long to wait for more Agents to join? |
| Include Go To Agents | Should Agents that are currently going to the Agent Event be counted? Check this to avoid Agent Events from being cancelled when Max Time To Wait is reached but enough Agents are going to the event. |
| Running Time Limit | Max time for event to run for. Leave at None for no limit. The length of a game hour is set in the Scene's TimeManager. |
| End When Creator Quits | If the creator quits should the event end? Agents can quit Agent Events at any time. |
| End When Less Than Min | If a running event goes below min number of attendees should it end? Agents can quit Agent Events at any time. |
Attendees
| Only Faction Members | A Bool indicating if the attendees must be in the same Faction as the creator. |
| R Level Min | What relationship level (R Level) must the attendee have with the Creator? This R Level comes from the Creator's memory. (Creator's view of the attendee.) |
| Min Attendees | Minimum number of attendees for this Agent Event to run. |
| Maximum number of attendees for this Agent Event. |
Sound
| Will play the selected Audio Clip while the Agent Event is in the Waiting state. | |
| Loop | Should this sound loop? |
Role Types
Assign role types to the attendees. Role Types can completely change an Agent's Drives and Actions. When the Agent Event is over the Role Types are removed, unless the Role Type was active before the Event.
| Role Mapping Type | Creator Attendee, Join Order, or Has Role Type: What criteria type to use to assign role types to attendees? |
| How many criteria to Role Types mappings are there? | |
| For Creator | Is this for the creator or the attendee? |
| Mapping Join Orders | A list of join order positions that get these Role Types. |
| Mapping Role Types | List of Role Types. If any match the Agent will get these role types. |
| Role Types | All of these will be added to the Agent if they match the above criteria. |


{% extends 'base.html' %} {% load percentage %} {% load humanize %} {% block main_content %}
HAWC is a collaboration of several individuals and organizations who create, maintain, and enhance the functionalities of this tool. The lead developer of the project is Andy Shapiro, who created the prototype in partial fulfillment of the requirements for the degree of Masters of Science in Public Health in the Department of Environmental Sciences and Engineering at the University of North Carolina at Chapel Hill under direction of Dr. Ivan Rusyn. Overall guidance on HAWC development is provided by a steering committee with representation from the National Toxicology Program at the National Institute of Environmental Health Sciences (NIEHS/NTP), Texas A&M University, and the National Center for Computational Toxicology of the Environmental Protection Agency (EPA/NCCT).
The HAWC database is changing daily as users add more data to assessments. Below is a list of the current counts for different types of data captured in the database. Note that in most cases, these data are available in assessments which may not be publicly accessible (yet):
Last updated: {{counts.updated}}
| File | Download |
|---|---|
| Data extraction fields | Spreadsheet |
| Presentation title | Audience | Link (and format) |
|---|---|---|
| HAWC: current capabilities and uses at the US National Toxicology Program (NIH/NIEHS/NTP) | 2015 National Toxicology Program (NTP) Board of Scientific Counselors | Slides |
| HAWC: A Modular Web-based Interface to Facilitate Development of Human Health Assessments of Chemicals | 2014 Society of Toxicology (SOT) | Poster |
| HAWC presentation overview and tutorial of key functionality including literature search, animal bioassay data extraction, and BMD modeling. | 2014 Webinar |
Slides
Video |
| HAWC: A Modular Web-based Interface to Facilitate Development of Human Health Assessments of Chemicals | 2013 OpenTox USA | Poster |
| Web-based Benchmark Dose Modeling Module as a Prototype Component of an Informatics-based System for Human Health Assessments of Chemicals | 2013 Society of Toxicology (SOT) | Poster |
Current version: {{GIT_COMMIT}}
HAWC: Health Assessment Workplace Collaborative [Computer software]. (2013).
URL: https://hawcproject.org. [Month, year of date use].
This project is supported, in part, by funding from the following sources:
The contents of HAWC are solely the responsibility of the users and developers, and do not necessarily represent the official views of EPA, NIH, NTP, or WHO. Further, EPA, NIH, NTP, and WHO do not endorse the purchase or use of any commercial or open-source products or services that were used in the development of HAWC.


--- layout: default title: "Anshul Samar" ---
April 2023: 3 year anniversary of Meditation Mondays which has now grown to a community of students, alumni, and community members across the country. See my post on wellness/mental health events we have been organizing at Stanford. Hope you all can join! Mailing list here.
Nov 2022: Our blog post on sparse GPT-3 style models via iterative magnitude pruning.
Nov 2021: It's a wrap! Thanks to the more than 350 attendees who came out to support for our sketch comedy shows! See reviews here. Was so much fun writing and producing this show and thanks to the entire cast!
May 2021: Started a "Name the Variants" petition to change the way news outlets refer to variants, see here.
Feb 2021: Performed at You & Me play reading hosted by CaLAA (California Arts Association) and directed by Richa Wadekar. Thanks for the great experience!
{{ item.title }} {{ item.mydate }}
{% endfor %}{{ item.title }} {{ item.mydate }}
{% endfor %}{{ item.title }} {{ item.mydate }}
{% endfor %}


Use this page to configure cloud providers: user account info and related settings.
To add a configuration, create a cloud user account and install the corresponding plugin. For more information, see Enable cloud support.


Retrying jobs without clearing them will create a confusing situation.
The job will get retried, but will still be in the failed queue. It will not be clear to anyone else if the job needs attention.
In general, always “Retry & Clear”, which will remove the job from the failed queue and then retry it.


| 016:075 Khan | : |
Allah puts forward the example (of two men a believer and a disbeliever); a slave (disbeliever) under the possession of another, he has no power of any sort, and (the other), a man (believer) on whom We have bestowed a good provision from Us, and He spends thereof secretly and openly. Can they be equal? (By no means, not). All the praises and thanks be to Allah. Nay! (But) most of them know not. |
| 016:075 Maulana | : |
Allah sets forth a parable: There is a slave, the property of another, controlling naught, and there is one to whom we have granted from ourselves goodly provisions, so he spends from it secretly and openly. Are the two alike? Praise be to Allah! Nay, most of them know not. |
| 016:075 Pickthal | : |
Allah coineth a similitude: (on the one hand) a (mere) chattel slave, who hath control of nothing, and (on the other hand) one on whom we have bestowed a fair provision from Us, and he spendeth thereof secretly and openly. Are they equal? Praise be to Allah! But most of them know not. |
| 016:075 Rashad | : |
GOD cites the example of a slave who is owned, and is totally powerless, compared to one whom we blessed with good provisions, from which he gives to charity secretly and publicly. Are they equal? Praise be to GOD, most of them do not know. |
| 016:075 Sarwar | : |
God tells a parable about a helpless servant and one to whom He has given honorable provisions and who has spent for the cause of God privately and in public. Can these two people be considered equal? It is only God who deserves all praise, but most people do not know. |
| 016:075 Shakir | : |
Allah sets forth a parable: (consider) a slave, the property of another, (who) has no power over anything, and one whom We have granted from Ourselves a goodly sustenance so he spends from it secretly and openly; are the two alike? (All) praise is due to Allah! Nay, most of them do not know. |
| 016:075 Sherali | : |
ALLAH sets forth for you the parable of a slave who is owned, having no power over anything; and a free man whom WE have provided with a fair provision from US and he spends thereof secretly and openly. Are they equal? Praise be to ALLAH. But most of them know not. |
| 016:075 Yusufali | : |
Allah sets forth the Parable (of two men: one) a slave under the dominion of another; He has no power of any sort; and (the other) a man on whom We have bestowed goodly favours from Ourselves, and he spends thereof (freely), privately and publicly: are the two equal? (By no means;) praise be to Allah. But most of them understand not. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > الشرك والمشركون > تنزيه الله جلّ جلاله عن الشريك Pillars of Islam> Islamic> Polytheism and the Polytheists> Allah's Freedom from Partnership الإنسان والعلاقات الاجتماعية > المجتمعات > التفاضل بينها Man and The Social Relations>The Societies>Preference Among them تنظيم العلاقات المالية > إنفاقها Organizing Financial Relationships>Its Expenditure
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Ehler angles. Angles of rotation along all three axes.
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#include <euler_angles.h>
Ehler angles. Angles of rotation along all three axes.
Definition at line 22 of file euler_angles.h.
| gbmath::euler_angles::euler_angles |
( |
) | |
|
|
inline |
| gbmath::euler_angles::euler_angles |
( |
const euler_angles & |
ea) | |
|
|
inline |
| gbmath::euler_angles::euler_angles |
( |
float |
_yaw, |
|
|
float |
_pitch, |
|
|
float |
_roll |
|
) |
| |
|
inline |
| gbmath::euler_angles::operator std::string |
( |
) | |
const |
|
inline |
| void gbmath::euler_angles::operator= |
( |
const std::string & |
str) | |
|
| throw | ( | std::invalid_argument |
| ) | | |
|
inline |
| std::ostream& operator<< |
( |
std::ostream & |
stream, |
|
|
const euler_angles & |
ea |
|
) |
| |
|
friend |
| float gbmath::euler_angles::pitch |
Pitch around the x-axis, in radians.
Definition at line 27 of file euler_angles.h.
| float gbmath::euler_angles::roll |
Roll around the z-axis, in radians.
Definition at line 28 of file euler_angles.h.
| float gbmath::euler_angles::yaw |
Yaw around the y-axis, in radians.
Definition at line 26 of file euler_angles.h.
The documentation for this class was generated from the following file:


Testdata10000.nsf
Testdata100000.nsf
Testdata1000000.nsf
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