|
| Local Methods | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |
Properties
| Name | Type | Description |
|---|---|---|
| None |
Methods
| Methods defined in this Managed Object |
|---|
| VsanVibInstall_Task, VsanVibInstallPreflightCheck, VsanVibScan |
| Privileges | Required on |
|---|---|
| Host.Config.Storage Host.Config.Settings | ClusterComputeResource |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the VsanUpdateManager used to make the method call. |
| cluster* | ManagedObjectReference
to a ComputeResource |
Optional cluster this scan is happening in reference to.
Since vSAN API 6.6 |
| vibSpecs* | VsanVibSpec[] |
List of VIB specs to installed (context is always a single host)
Since vSAN API 6.6 |
| scanResults* | VsanVibScanResult[] |
List of VIB scan results obtained from VsanVibScan()
Since vSAN API 6.6 |
| firmwareSpecs* | VsanHclFirmwareUpdateSpec[] |
List of Firmware spec to be installed (context is always
a single host and vmhba)
Since vSAN API 6.6 |
| maintenanceSpec* | HostMaintenanceSpec |
Maintenance spec to pass to EnterMaintenanceMode_Task()
In case of non-rolling installs, no other vSAN action
than 'noAction' is allowed.
Since vSAN API 6.6 |
| rolling* | xsd:boolean |
True (default) means a 1-host-at-a-time rolling install
will be performed.
Since vSAN API 6.6 |
| noSigCheck* | xsd:boolean |
Skip signature checking, should not be used outside of
fully trusted test environments. Default: False
Since vSAN API 6.6 |
Return Value
| Type | Description |
|---|---|
| ManagedObjectReference
to a Task | A task |
Faults
| Type | Description |
|---|---|
| NotFound | |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
| VsanFault |
Events
| Type | |
|---|---|
| None |
| Privileges | Required on |
|---|---|
| System.Read | ClusterComputeResource |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the VsanUpdateManager used to make the method call. |
| cluster* | ManagedObjectReference
to a ComputeResource |
Cluster for which to perform preflight check
Since vSAN API 6.6 |
Return Value
| Type | Description |
|---|---|
| VsanVibInstallPreflightStatus | Preflight check results |
Faults
| Type | Description |
|---|---|
| NotFound | |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
| VsanFault |
Events
| Type | |
|---|---|
| None |
| Privileges | Required on |
|---|---|
| System.Read | ClusterComputeResource |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the VsanUpdateManager used to make the method call. |
| cluster* | ManagedObjectReference
to a ComputeResource |
Optional cluster this scan is happening in reference to.
Since vSAN API 6.6 |
| vibSpecs | VsanVibSpec[] |
List of VIB specs to check (one entry per host)
|
Return Value
| Type | Description |
|---|---|
| VsanVibScanResult[] | List of VIBs that would be installed. Each such result is for a single host, single VIB. |
Faults
| Type | Description |
|---|---|
| NotFound | |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
| VsanFault |
Events
| Type | |
|---|---|
| None |
| Top of page | Local Methods | ||
| Managed Object Types | Data Object Types | All Properties | All Methods |


|
gLogger Mini
1.6
A simple and small GPS logging device
|
Library for handling the GPS-module. More...
#include "modules/gps.h"
Functions | |
| void | gps_init (uint8_t pFrequency, uint8_t pMessages) |
| Initializes the GPS-module. Locks the processor in case of error. | |
| void | gps_highspeed () |
| Prompts the GPS to send data with a higher baudrate and reinitializes the UART port. | |
| unsigned char | gps_calculateCS (const unsigned char *pPayload, uint16_t pLength) |
| unsigned char | gps_setParam (unsigned char pCommand, unsigned char *pData, uint16_t pLength) |
| Sets a parameter of the GPS-module to a given value. | |
| uint8_t | gps_checkNMEA (const char *pSentence, uint8_t pMessageType, char *pPrefix, uint8_t pValidityToken, char *pValidityCheck, uint8_t pCheckEquality) |
| Checks if the given sentence meets the criteria for a valid message. | |
| uint8_t | gps_getNMEA (char *pOutput, uint8_t pMaxLength) |
| Writes a NMEA-String into the given output buffer and returns its type. |
Library for handling the GPS-module.
| unsigned char gps_calculateCS | ( | const unsigned char * | pPayload, |
| uint16_t | pLength | ||
| ) |
| uint8_t gps_checkNMEA | ( | const char * | pSentence, |
| uint8_t | pMessageType, | ||
| char * | pPrefix, | ||
| uint8_t | pValidityToken, | ||
| char * | pValidityCheck, | ||
| uint8_t | pCheckEquality | ||
| ) |
Checks if the given sentence meets the criteria for a valid message.
This method checks several properties, some of them will only indicate if the message can be considered as "valid" or not, others will say more generally if the given message is in a correct format.
In detail, the method sweeps through the sentence once, while:
| pSentence | The sentence which shall be checked |
| pMessageType | The message type which is expected |
| pPrefix | The prefix (== message type) that the sentence is supposed to have |
| pValidityToken | The index of a token (a token is delimited by commas) in which a validity information can be found. Set to 0 if no validity check should be performed. Token 1 begins after the first comma (i.e. the first data after the "$GP..." type string) |
| pValidityCheck | A string to which the validityToken should be compared |
| pCheckEquality | If TRUE, the sentence is considered valid if the validityToken equals the validityCheck string, otherwise if they are unequal |
| uint8_t gps_getNMEA | ( | char * | pOutput, |
| uint8_t | pMaxLength | ||
| ) |
Writes a NMEA-String into the given output buffer and returns its type.
| pOutput | The buffer in which the NMEA string shall be written |
| pMaxLength | The buffer's maximal length |
| void gps_highspeed | ( | ) |
Prompts the GPS to send data with a higher baudrate and reinitializes the UART port.
| void gps_init | ( | uint8_t | pFrequency, |
| uint8_t | pMessages | ||
| ) |
Initializes the GPS-module. Locks the processor in case of error.
The parameters can be used to configure the output produced by the GPS. Please note that certain limitations exist for the parameters values.
| pFrequency | The frequency (in Hertz) in which NMEA-sentences should be returned. The module supports only a value of the set {1,2,4,5,8,10}. Only the values {1,2} are supported by the gLogger-Firmware right now! Higher frequencies may or may not work. |
| pMessages | A bitset containing the messages which should be returned in each message block. Multiple messages can be selected by using the OR-operator on the constant values. Possible constant values are {GPS_NMEA_GGA, GPS_NMEA_RMC, GPS_NMEA_GSA, GPS_NMEA_GSV, GPS_NMEA_GLL, GPS_NMEA_VTG, GPS_NMEA_ZDA}. |
| unsigned char gps_setParam | ( | unsigned char | pCommand, |
| unsigned char * | pData, | ||
| uint16_t | pLength | ||
| ) |
Sets a parameter of the GPS-module to a given value.
| pCommand | The parameter which should be set (see constants) |
| pData | The data which should be written for this parameter |


Kozhikode Beach or Calicut Beach is a beach on the western side of Kozhikode, situated on the Malabar Coast of India. The beach is accessible through four road overbridges in the city. The beach has paved stones and illumination. There is one Lions Park for the children and an aquarium. Kozhikode beach has always been a prominent place for conducting public meetings. The beach road was renamed 'Gandhi Road' in 1934 after Gandhi visited Calicut in 1934.
Regional Science Centre & Planetarium Calicut functioning under NCSM (Govt.of India) shoulders the leading role in propelling science dissemination activities in Kerala, especially in the Malabar region. Calicut, the capital of Malabar right from the time of the Zamorin’s dynasty is now a fascinating place with unparalleled attractions including historic monuments, works of art and cultural contributions. The cityattracts and accommodates visitors by outstretched red carpet of its enticing natural beauty. Situated in this land of distinct heritage RSC & Planetarium engages itself in dissemination of science through interactive exhibitions.
Sarovaram Bio Park is an eco-friendly development near Kottooly in Kozhikode city in India. The park is situated adjacent to Canoly Canal. The project has been developed with an eco-friendly theme and is located in an ecosystem consisting of wetlands and mangrove forests containing bird habitats.This park is a protected place to conserve mangrove species and other flora. This park is identified as one of the 27 wetlands of India. There are 7 mangrove species and 29 associated species. This park is the habitat for 34 types of birds. The canal is eleven kilometres long and connects the Korapuzha and Kallayi rivers. The park contains boating facilities, musical fountain and an open-air theatre. Of late the park has gained a reputation as a popular hangout of college couples.


Devices > Clock
See also: Timer
A clock:
::
--
,
HTML:
Javascript:
A clock with a lag of 3 hours:
::
--


{% extends "free_software.html" %} {% block logo %} {% endblock %} {% block software %}
AWS offers server hosting and high-powered tools to deploy and scale a successful project. AWS has donated credits to CfA which we are happy to share with your Brigade to get your projects hosted.
Please note: AWS credits is a pilot program for Brigades, and we might have to end this program at the end of 2018 depending on the continued availability of donated credits.
If approved, CfA will give your brigade a $100 budget to spend on whatever it needs. We know this doesn’t go very far, so, above this threshold, we are happy to support promising projects on a case-by-case basis. To request a higher budget, reach out as described in "Any project-specific requests" below.
Create an account on the AWS site named after your brigade. (To simplify record-keeping on our end, we require that your Brigade only have a single AWS account.)
If you have an existing account, make sure the Account Name is the name of your brigade.
This is what the account details should look like. Finally, send the Account ID number to<EMAIL_ADDRESS>along with the following information:
No catches! But there are a couple things to be aware of.
AWS payments are in a pilot stage of CfA. We will update you with information about the duration of the pilot when you send your request to<EMAIL_ADDRESS>Your AWS account will be added as a sub-account of Code for America’s main account, which means that CfA will be on the hook for any bills that you create. To make sure we are able to distribute the credits fairly across all the brigades and prevent accidental billing issues, we will require the ability to audit your AWS account and set up billing alerts.
If your account goes over its agreed budget, we reserve the right to request that you pay back the difference, or to deduct it from your brigade account at CfA.
{% endblock %}


@* * Copyright 2018 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.apidocumentation.config._ @import uk.gov.hmrc.apidocumentation.models._ @import uk.gov.hmrc.apidocumentation.controllers @import include._ @(pageAttributes: PageAttributes)(implicit request: play.api.mvc.Request[Any], applicationConfig: ApplicationConfig, messages: Messages) @apiMain(pageAttributes) {
Some APIs on the sandbox are stateless - they return hard-coded happy path responses.
However, many APIs on the sandbox are stateful - they let you send test data through create (POST) or update (PUT) requests (or through an accompanying Test Support API) and then read back that same data through retrieval (GET) requests.
For stateful APIs where there is no way to clear down test data, the best way to start anew is to create a new test user.
}


Home
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Name
Date
Introduction
Music Light
2016.12
An interactive installation which
can produce music using light.
Name
Date
Introduction
Boyfri Camera
2016.10
A camera re-design to free people’s hands
Game
Product
Graphic


I recently purchased some Iboga root bark from Holland, with the intention of taking small amounts, as an antidote to OCD. I'd had some experience with mescaline, but had read that Iboga would be more effective for my purposes. I decided to take 2 grams at about midday, thinking this would be a good test dose that wouldn't interfere with my day to day activities. I was quite wrong.
Firstly, a note on its taste. It came ready ground so I mixed it with water and downed it. It is without doubt the foulest tasting thing I have ever known. Peruvian Torch tastes like Chocolate Haagen Daaz in comparison.
Within half an hour I begin to be much more aware of the sounds around me and from outside. However I was having trouble in distinguishing exactly where they were coming from. It seemed as though the volumes of the individual sounds were out of whack and what was far was near and vice versa.
  I lost my appetite, and my ability to speak became weakened to a croak. This was a little difficult as I was at my parents' house and so had to maintain a semblance of normality. I hadn't expected the impact to be this strong.
I was content to lie there, but had moments of panic, fearing I would 'trip out' and end up in hospital, bringing aggravation all round. I guess this emphasizes the usefulness of being in a completely safe setting. I began to feel like I'd made a terrible mistake taking this drug, and would soon be paying a terrible price for it. I was also having quite strong trails around movement and flashes of light in my peripheral vision. My heart rate at times raised up to about 120.
However I also began to have moments of clarity that I haven't had in a long time. I became introspective and more self-aware. I became clearer about things that had been troubling me, including a serious relationship split. I began to see that much of what had occurred to me had actually been caused by me, and my own foolishness. This was painful but also relieving, as I was coming to terms with the truth of matters, and so seeing the solution to behaviours that had brought me despair.
I felt the iboga was pulling me towards some sort of precipice, which I had to cross, some truth to face. I presume it was the truth of my own self, but the dose wasn't strong enough to take me in that direction and I was resistant to it.
Iboga is a very long experience. Late at night I was still buzzing (not tripping, it was too small a dose). The tracers and flashes were still there as well as the ataxia. I was able to get to sleep, but on waking the next day the iboga was still in effect, replete with the traces and flashing. I began to worry it was permanent, and called in sick to work.
For the next two days I felt pretty ill, and didn't get out of bed, slowly recovering my appetite. I also experienced constipation, which may be consistent with iboga working on opioid receptors in the brain, as heroin addicts also experience this same problem. I did however feel more centered, and more at peace. I'd gained a lot from the insight this small amount had given me.
I'd also found my OCD had decreased, I was less neurotic, less irrationally worried. This effect has continued, and in a small way I feel changed, altered, and in a good way. Iboga is used as an anti-addiction treatment and I certainly felt less compulsive in the days after use. I also could sleep more easily, felt less physically active, sweated more, and felt colder at night. This drug really affected homeostasis.
This wasn't a pleasant experience. To quote Shulgin, 'There is no question but that ibogaine is a rough trip, physically as well as mentally'. But I feel like the benefits are very worthwhile. I would do it again, but only as a form of medicine. If there was an easier way to attain these affects I would take it. I would never consider this to be a recreational experience, and its use should be very carefully considered.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Mackerel
Mackerel is a minimal static site generator written in typed Python 3.6+.
Installation
This part of the documentation covers the installation of Mackerel.
pip install
To install Mackerel, simply run this command in your terminal of choice:
$ pip install mackerel
If you don't have pip installed, this pip installation guide can guide you through the process.
Get the Source Code
Mackerel is developed on GitHub, where the source code is available.
You can clone the public repository:
$ git clone git@github.com:pkolios/mackerel.git
Once you have a copy of the repository you can install it:
$ cd mackerel
$ pip install -e .
Basic Usage
After succesfully installing mackerel you can use the mackerel cli to initialize a new site or build an existing one.
Start a new site
Mackerel's cli provides with an init
command that generates a new site under the given directory name.
$ mackerel init ~/my_site
The mackerel directory structure looks like this:
.
├── .mackerelconfig # The configuration file of this site
├── content # The site's content
└── template # The site's template
You can have a look at the generated .mackerelconfig
file and content
directory and alter them to your liking.
For further documentation regarding the template development see the Template development section.
Build your site
The new site already contains some demo content and a template. The build
command will build the site.
$ mackerel build ~/my_site
The static site will be generated inside the _build
directory of the site.
You can use mackerel's development server to host the site.
$ mackerel develop ~/my_site
The development server automatically detects changes in the content
and template
folders and rebuilds the site.
Create a new page or post
Using your favorite editor, create a new .md
file anywhere in the site's content
directory.
Make sure the new file has the .md
file extension. The content file has two sections.
The top section that contains metadata keys and values related to this document.
Title: New page
Author: John Doe
Date: December 31, 2099
Template: page.html
Custom_meta: Nyancat
...
And the main section that contains the actual content.
...
This is the main content of this document written in Markdown.
Configuration
The .mackerelconfig
file contains the configuration for the site
[mackerel]
OUTPUT_PATH = _build # Sets the build output directory
CONTENT_PATH = content # Specifies the site's content directory
TEMPLATE_PATH = template # Specifies the site's template directory
[navigation] # This section is used to define navigation menus for the template
main = index.md, about.md # The main navigation consists of the index and the about documents
[user] # This section contains all the user / template site-wide settings
title = Mackerel Example Site # The site's title
description = A beautiful narrative written with Mackerel. The story begins here. # The site's description
logo = img/logo.svg # The path to the site's logo inside the content directory
url = http://localhost:8000/ # The site's url (supports sub directories ex. /blog/)
copyright = 2017 Paris Kolios # Site-wide copyright string
powered = https://github.com/pkolios/mackerel # Site-wide powered-by string
Template development
Currently the chosen template engine is Jinja2. When rendering the content files, Mackerel passes the following objects to the template:
document
- the document that is currently being generatedctx
- the context object that contains the navigation & config objectsctx.nav
- the navigation objectctx.cfg
- the config parser object
Built With
- Python 3
- mypy Static type checker
- Jinja2 Template engine
- Markdown Python implementation of Markdown
- mistune Markdown parser in pure Python
Changelog
Version 0.2
Bugfixes
- Fix an error in the packaging that caused
mackerel init
command to fail due to the lack ofconfig.ini
.
Improvements
- Rework the
setup.py
script to increase release automation.
Version 0.1
First preview release.
License
See the LICENSE file for details.


# Examples of HTML *tables* written in Markdown
> This *StrapDown*-flavored HTML page is a demo of *how to write a table with Markdown*, and how a table will be (nicely) rendered by StrapDown.js.
> ### (Why this demo?)
> Someone asked me (01-2015) about that feature, so, *here is the demo!*
---
### How to enable the *tables* rendering?
In order for StrapDown.js to be able to read and render HTML **tables** (the [``]() tag),
**no need to ask any special option** (as opposed to [the MathJax feature allowing you to embed LaTeX equations](example5.html)).
#### Some help? (about the `` HTML tag)
> More documentation about that `` tag can be found on these sites: [www.htmlquick.com/reference/tags/table.html](http://www.htmlquick.com/reference/tags/table.html), [www.html.am/tags/html-table-tag.cfm](http://www.html.am/tags/html-table-tag.cfm), [www.w3ctutorial.com/html5-tags/tag-table](http://www.w3ctutorial.com/html5-tags/tag-table), and the famous [w3schools.com/html/html_tables.asp](http://w3schools.com/html/html_tables.asp) or [w3schools.com/tags/tag_table.asp](http://w3schools.com/tags/tag_table.asp).
---
## How to write a Markdown table ?
> More details about the syntax for Markdown tables can be found on the **GitHub Flavored Markdown** document : [help.github.com/articles/github-flavored-markdown/#tables](https://help.github.com/articles/github-flavored-markdown/#tables).
### First example
The basic syntax to have in mind is the following :
First Header | Second Header
------------- | -------------
Content Cell | Content Cell
Content Cell | Content Cell
> The previous table corresponds to the following *Markdown* code:
>
> First Header | Second Header
> ------------- | -------------
> Content Cell | Content Cell
> Content Cell | Content Cell
### Second example
> I follow the examples from [GitHub's help page about tables in Markdown](https://help.github.com/articles/github-flavored-markdown/#tables).
| Name | Description |
| ------------- | ----------- |
| Help | Display the help window.|
| Close | Closes a window |
> The previous table corresponds to the following *Markdown* code:
>
> | Name | Description |
> | ------------- | ----------- |
> | Help | Display the help window.|
> | Close | Closes a window |
### Third example
> That example is also **extremely satisfying**, because StrapDown.js *does* support the alignment custom syntax (from [GFM](https://help.github.com/articles/github-flavored-markdown/#tables)):
| Left-Aligned | Center Aligned | Right Aligned |
| :------------ |:---------------:| -----:|
| col 3 is | some wordy text | $1600 |
| col 2 is | centered | $12 |
| zebra stripes | are neat | $1 |
> The previous table corresponds to the following *Markdown* code:
>
> | Left-Aligned | Center Aligned | Right Aligned |
> | :------------ |:---------------:| -----:|
> | col 3 is | some wordy text | $1600 |
> | col 2 is | centered | $12 |
> | zebra stripes | are neat | $1 |
#### Hoho, a small trap:
> At first, I thought that this feature was not available, but it was my fault, as I use an old version of the [united](http://bootswatch.com/united) BootStrap theme.
>
> Hence I modified one line, which was forcing the table content to be left-aligned, and removed the `text-align:left` element:
> ```css
> .table th,.table td { [.. stuff]; text-align:left; } -----> .table th,.table td { [.. stuff]; }
> ```
> Now, this [has been fixed](https://bitbucket.org/lbesson/lbesson.bitbucket.org/commits/fba4d321b4445e2e2ed7e8762a4a89cf8a673238) (the 22-01-2015).
---
---
## A partial list of the [Justice League of America](https://en.wikipedia.org/wiki/Justice_League)
[StrapDown.js](//lbesson.bitbucket.io/md/index.html) supports *really well* these Markdown tables, and the [GFM extension](https://help.github.com/articles/github-flavored-markdown) for alignment.
Here is a last example, displaying some *super heroes* ^^:
| Number | Name | Secret Name! | Super Hero Group | Gender | Email Address | Photo |
| :----- |:----:|:------------:|:----------------:|:------:|:-------------:| -----:|
| 01 | **Superman** | *Clark Kent* | JLoA | Male | [superman<EMAIL_ADDRESS>| ![Picture for hero #01](https://randomuser.me/api/portraits/med/men/72.jpg "Picture for super-hero #01")|
| 02 | **Batman** | *Bruce Wayne* | JLoA | Male | [batman<EMAIL_ADDRESS>| ![Picture for hero #02](https://randomuser.me/api/portraits/med/men/45.jpg "Picture for super-hero #02")|
| 03 | **Green Lantern** | *Secret!* | JLoA | Male | [Green.Lantern<EMAIL_ADDRESS>| ![Picture for hero #03](https://randomuser.me/api/portraits/med/men/51.jpg "Picture for super-hero #03")|
| 04 | **Wonder Woman** | *Secret!* | JLoA | Female | [Wonder.Woman<EMAIL_ADDRESS>| ![Picture for hero #04](https://randomuser.me/api/portraits/med/women/25.jpg "Picture for super-hero #04")|
| 05 | **AwkGirl** | *Too lazy to look for it* | JLoA | Female | [AwkGirl<EMAIL_ADDRESS>| ![Picture for hero #05](https://randomuser.me/api/portraits/med/women/88.jpg "Picture for super-hero #05")|
> *Hint:* these emails addresses are really secret, keep they from yourself, and especially from super villains! (Seriously: **they are fake!**)
> Thanks to the *awesome* [RandomUser.me](https://randomuser.me/) for providing **fake** profile pictures for our super-heroes!
---
## [A personal example](../cv/)
And if you may, I will conclude these examples with a more personal one:
| *Scholar* Year | My age
(when started/when finishing) | Scholar level | City, *Country* |
| :----------- | :----: | :-----------: | --: |
| 2015 ~ 2016 | 22 → 23 | [Another 2nd Year M.Sc. (Maths and CS)](http://www.cmla.ens-cachan.fr/version-anglaise/academics/mva-master-degree-227777.kjsp) | Cachan (Paris), *France* |
| 2014 ~ 2015 | 21 → 22 | [Assistant professor](http://web.archive.org/web/20141103063707/http://www.mahindraecolecentrale.edu.in/faculties.html), Maths and CS | Hyderabad, *India* |
| 2013 ~ 2014 | 20 → 21 | 2nd Year M.Sc. (Maths, CS)
and ranked 23rd at the French Agrégation | Cachan (Paris), *France* |
| 2012 ~ 2013 | 19 → 20 | 1st Year M.Sc. (Maths, CS) | Cachan (Paris), *France* |
| 2011 ~ 2012 | 18 → 19 | 3rd Year B.Sc. (Maths, CS) | Cachan (Paris), *France* |
| 2010 ~ 2012 | 17 → 18 | 2nd Year B.Sc. (Maths and Physics) | Marseille, *France* |
| 2009 ~ 2010 | 16 → 17 | 1st Year B.Sc. (*MPSI*) | Marseille, *France* |
| 2008 ~ 2009 | 15 → 16 | Scientific *"Baccalauréat"* | Briançon, *France* |
> ... But that was just a short overview of my academic education and [my curriculum](http://perso.crans.org/besson/cv.en.pdf).
---
## One more example: how to easily add a search input button for a table?
→ [Go read the next example please](example7.html) to know more about that.
It's pretty easy, and works extremely well :) !
---
### End of the examples
That's all for today! [Go back to StrapDown.js main page](index.html)?
---


Sliding Puzzle
needs JavaScript
Activate JavaScript and reload the page
Play
Options
You won
of the
Games you played ~
%.
Sliding Puzzle
Sides
Time
Stop After Timeout
Sliding Puzzle
Time:
Quit
Restart
Done


IIT Guwahati Model United Nations brings to you, for the very first
time, a two-day MUN workshop! This unprecented opportunity is the
perfect place for amateurs as well as seasoned delegates to groom
themselves for the upcoming flagship conference. Whether yor are
just looking for the hang of an MUN, to refine your debating skills,
or to explore your potential in an extemporary environment, this workshop
is one initiative that caters to all these needs and aspires to give
you personalised guidance. This is your one chance to participate
and learn from the best. Highly experienced executive board
members of distinguised MUNs shall serve as your mentors. So, do join
us on the first and second of this September to aquire your
cutting edge as a delegate!


--- layout: archive title: Zulip Chat Archive permalink: /stream/141825-kbb/topic/fourier.20series.html ---
I think one of the foundational things about modular forms is their Fourier series. Do people think it is reasonable to attack this is the coming week?
I don't see how we could get series expansion for holomorphic functions so quickly (unless Kenny really wants it)
(deleted)
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Class VisualNumerics.math.ComplexVector
All Packages Class Hierarchy This Package Previous Next Index
Class VisualNumerics.math.ComplexVector
java.lang.Object
|
+----VisualNumerics.math.ComplexVector
- public final class ComplexVector
- extends Object
Complex vector manipulation functions.
This class cannot be instantiated.
-
add(Complex, Complex[])
- Add a Complex scalar to each element of the vector, zi + b for all values of the index i.
-
add(Complex[], Complex[])
- Add a Complex vector to a Complex vector.
-
add(double, Complex[])
- Add a scalar of type double to each element of the vector, z
i + b for all values of the index i.
-
add(double[], Complex[])
- Add a double vector to a Complex vector.
-
conjugate(Complex[])
-
Return the complex conjugate of each Complex object in the array.
-
imag(Complex[])
- Return the imaginary part of each Complex element of the array.
-
infinityNorm(Complex[])
-
Calculate the infinity norm of a vector.
-
innerProduct(Complex[], Complex[])
-
Calculate the dot product of two vectors.
-
multiply(Complex, Complex[])
-
Multiply a Complex vector by a Complex scalar, z
i * b for all values of the index i.
-
multiply(Complex[], Complex[])
- Multiply a Complex vector by a Complex vector.
-
multiply(double, Complex[])
-
Multiply a Complex vector by a scalar of type double, z
i * b for all values of the index i.
-
multiply(double[], Complex[])
- Multiply a Complex vector by a double vector.
-
oneNorm(Complex[])
- Calculate the one norm of a vector.
-
product(Complex[])
-
Calculate the product of the array elements.
-
real(Complex[])
-
Return the real part of each Complex element of the array.
-
subtract(Complex[], Complex)
- Subtract a Complex scalar from a Complex vector, z
i - b, for all values of the index i.
-
subtract(Complex[], Complex[])
- Subtract a Complex vector from a Complex vector, b - z.
-
subtract(Complex[], double)
-
Subtract a scalar of type double from a Complex vector, z
i - b for all values of the index i.
-
subtract(Complex[], double[])
- Subtract a double vector from a Complex vector, z - b.
-
subtract(double[], Complex[])
- Subtract a Complex vector from a double vector, b - z.
-
sum(Complex[])
- Calculate the sum of the array elements.
-
twoNorm(Complex[])
- Calculate the Euclidean or two norm of a vector.
ComplexVector
public ComplexVector()
conjugate
public static Complex[] conjugate(Complex z[])
- Return the complex conjugate of each Complex object in the array.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A vector whose elements are complex conjugates of
corresponding elements in the input vector.
sum
public static Complex sum(Complex z[])
- Calculate the sum of the array elements.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A Complex object equal to the sum of the array elements.
product
public static Complex product(Complex z[])
- Calculate the product of the array elements.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A Complex object equal to the product of the array elements.
innerProduct
public static Complex innerProduct(Complex x[],
Complex y[])
- Calculate the dot product of two vectors.
- Parameters:
- x - A vector with Complex elements.
- y - A vector with Complex elements.
- Returns:
- A Complex object equal to the dot product of the two vectors.
oneNorm
public static double oneNorm(Complex z[])
- Calculate the one norm of a vector.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A double value equal to the sum of the absolute values
of the elements.
twoNorm
public static double twoNorm(Complex z[])
- Calculate the Euclidean or two norm of a vector.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A double value equal to its Euclidean norm.
infinityNorm
public static double infinityNorm(Complex z[])
- Calculate the infinity norm of a vector.
- Parameters:
- z - A vector with elements of type Complex.
- Returns:
- A double value equal to the maximum of the absolute
values of the elements of the array.
real
public static double[] real(Complex z[])
- Return the real part of each Complex element of the array.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A vector whose elements are the real parts of corresponding
elements in the input vector.
imag
public static double[] imag(Complex z[])
- Return the imaginary part of each Complex element of the array.
- Parameters:
- z - A vector with Complex elements.
- Returns:
- A vector whose elements are the imaginary parts of corresponding
elements in the input vector.
add
public static Complex[] add(double b,
Complex z[])
- Add a scalar of type double to each element of the vector, zi + b for all values of the index i.
- Parameters:
- b - A double value.
- z - A vector with Complex elements.
- Returns:
- A Complex vector where each element is the sum of the corresponding element in z and the input scalar b.
add
public static Complex[] add(Complex b,
Complex z[])
- Add a Complex scalar to each element of the vector, zi + b for all values of the index i.
- Parameters:
- b - A Complex object.
- z - A vector with Complex elements.
- Returns:
- A Complex vector where each element is the sum of the corresponding element in z and the input scalar b.
add
public static Complex[] add(double b[],
Complex z[])
- Add a double vector to a Complex vector.
- Parameters:
- b - A vector with elements of type double.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise sum of b and z.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
add
public static Complex[] add(Complex b[],
Complex z[])
- Add a Complex vector to a Complex vector.
- Parameters:
- b - A vector with Complex elements.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise sum of b and z.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
subtract
public static Complex[] subtract(Complex z[],
double b)
- Subtract a scalar of type double from a Complex vector, zi - b for all values of the index i.
- Parameters:
- z - A vector with Complex elements.
- b - A double value.
- Returns:
- A Complex vector where each element is the difference between the corresponding element of
z and the input scalar b.
subtract
public static Complex[] subtract(Complex z[],
Complex b)
- Subtract a Complex scalar from a Complex vector, zi - b, for all values of the index i.
- Parameters:
- z - A vector with Complex elements.
- b - A Complex object.
- Returns:
- A Complex vector where each element is the difference between the corresponding element in z
and the input scalar b.
subtract
public static Complex[] subtract(double b[],
Complex z[])
- Subtract a Complex vector from a double vector, b - z.
- Parameters:
- b - A vector with elements of type double.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise difference between the input vectors.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
subtract
public static Complex[] subtract(Complex z[],
double b[])
- Subtract a double vector from a Complex vector, z - b.
- Parameters:
- z - A vector with Complex elements.
- b - A vector with elements of type double.
- Returns:
- A Complex vector containing the elementwise difference between the input vectors.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
subtract
public static Complex[] subtract(Complex b[],
Complex z[])
- Subtract a Complex vector from a Complex vector, b - z.
- Parameters:
- b - A vector with Complex elements.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise difference between the input vectors.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
multiply
public static Complex[] multiply(double b,
Complex z[])
- Multiply a Complex vector by a scalar of type double, zi * b for all values of the index i.
- Parameters:
- b - A double value.
- z - A vector with Complex elements.
- Returns:
- A Complex vector where each element is the product of the corresponding element in the input vector and the input scalar b.
multiply
public static Complex[] multiply(Complex b,
Complex z[])
- Multiply a Complex vector by a Complex scalar, zi * b for all values of the index i.
- Parameters:
- b - A Complex object.
- z - A vector with Complex elements.
- Returns:
- A Complex vector where each element is the product of the corresponding element in the input vector and the input scalar b.
multiply
public static Complex[] multiply(double b[],
Complex z[])
- Multiply a Complex vector by a double vector.
- Parameters:
- b - A vector with elements of type double.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise product of the input vectors.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
multiply
public static Complex[] multiply(Complex b[],
Complex z[])
- Multiply a Complex vector by a Complex vector.
- Parameters:
- b - A vector with Complex elements.
- z - A vector with Complex elements.
- Returns:
- A Complex vector containing the elementwise product of the input vectors.
- Throws: IllegalArgumentException
- This exception is thrown when the input vectors
do not have the same length.
All Packages Class Hierarchy This Package Previous Next Index


OmniROM is our Android custom ROM variant, feature-packed but always with stability as #1 priority in mind.
Based on the Android Open Source Project (AOSP) and enriched by our developers with lots of custom enhancements, OmniROM has set out to give you a great Android experience on your mobile.
We do custom ROMs since 2013 CyanogenMod is history - we are still here
It’s another option for the billion Android users out there. Android (vs. iOS and every other mobile OS) has thrived on options as well as the gigantic, talented development community that has emerged to build those options. That’s the beauty of Android – that you can pick and choose from a smorgasbord of devices with varying features and functionality.
Omni is a chance to get involved, no matter who you are.
Developers, whether you’ve been developing apps for a week, or ROM features for 3 years, you’re welcome. Users, we know you want to help out, and now you can - we encourage all levels of contribution, from code to reporting bugs to squashing bugs to (what developer's tend to hate) documentation.


World Anti-Doping Agency suspends Bangkok laboratory
MONTREAL, Canada: The National Doping Control Centre in Bangkok has been suspended for six months due to non-conformities, the World Anti-Doping Agency (WADA) said on Wednesday (Nov 20).
The suspension, which took effect on Nov 18, prohibits the laboratory from carrying out any anti-doping activities, including all analyses of urine and blood samples.
WADA said the suspension was the result of a site visit that found non-conformities with the International Standard for Laboratories (ISL).
The laboratory was given six months to address the issues otherwise WADA said it may extend the suspension for another six months.
During the suspension sample testing will be moved to another WADA accredited laboratory.


HOYEAH WEDDING eagers to provide personalized wedding planing services by integrating customized strategies and updated resources.
HOYEAH WEDDING eagers to provide personalized wedding planing services by integrating customized strategies and updated resources.


Skynet
gem¶ ↑
Library for integrating Skynet
into Ruby applications
Getting started¶ ↑
Gem¶ ↑
gem install ruby-skynet
Bundle¶ ↑
bundle add ruby-skynet
Gemfile¶ ↑
gem 'ruby-skynet', '~> 1.3'
Examples¶ ↑
require 'skynet' # Upload upload = Skynet.upload_file('src.jpg') puts upload #=> Upload successful, skylink: ABC123 # Download download = Skynet.download_file("test/src.jpg", skylink) puts download #=> Download successful!
For more see examples.md


| Name: mr. praksh | Reg No: 5-12smhc17 |
|---|---|
| Age / Sex:36y/m | Contact No:9535197501 |
| Marital Status:ml- 4 years | Date:20/12/17 |
| Occupation:driver since 10 years | Dr. pjfp |
Address: Native mangaluru. In blore since 2 years. |
DIAGNOSIS- |
Left year pain since yesterd. Frm 4 days feels ear blocked. Vertigo in the night. Pain in the whole left region. In closed area feels tinnitus n open area feels popping sound.
3-4 times coffee.
Lot of wax .
Rx:
Conium 200 – 4-4-4-4
Causticum 1m – 9 doses. 1-1-1
cham 200+spigelia200+hyp 200 – 4 pills 2 hourly.


Metapackage for implementing a variety of event-based models, with a focus on spatially explicit models. These include raster-based, event-based, and agent-based models. The core simulation components (provided by 'SpaDES.core') are built upon a discrete event simulation (DES; see Matloff (2011) ch 7.8.3 <https://nostarch.com/artofr.htm>) framework that facilitates modularity, and easily enables the user to include additional functionality by running user-built simulation modules (see also 'SpaDES.tools'). Included are numerous tools to visualize rasters and other maps (via 'quickPlot'), and caching methods for reproducible simulations (via 'reproducible'). Additional functionality is provided by the 'SpaDES.addins' and 'SpaDES.shiny' packages.
| Version: | 2.0.2 |
| Depends: | R (≥ 3.3.0) |
| Imports: | methods, quickPlot, reproducible, SpaDES.addins, SpaDES.core, SpaDES.tools, utils |
| Suggests: | archivist, devtools, hunspell, igraph, knitr, raster, rmarkdown, testthat, tkrplot |
| Published: | 2018-06-15 |
| Author: | Alex M Chubaty [aut, cre], Eliot J B McIntire [aut], Yong Luo [ctb], Steve Cumming [ctb], Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph] |
| Maintainer: | Alex M Chubaty <alex.chubaty at gmail.com> |
| BugReports: | https://github.com/PredictiveEcology/SpaDES/issues |
| License: | GPL-3 |
| URL: | http://spades.predictiveecology.org, https://github.com/PredictiveEcology/SpaDES |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | SpaDES results |
| Reference manual: | SpaDES.pdf |
| Vignettes: |
03 Caching SpaDES simulations |
| Package source: | SpaDES_2.0.2.tar.gz |
| Windows binaries: | r-devel: SpaDES_2.0.2.zip, r-release: SpaDES_2.0.2.zip, r-oldrel: SpaDES_2.0.2.zip |
| OS X binaries: | r-release: SpaDES_2.0.2.tgz, r-oldrel: SpaDES_2.0.2.tgz |
| Old sources: | SpaDES archive |
Please use the canonical form https://CRAN.R-project.org/package=SpaDES to link to this page.


This includes the 'IVA 1C basic category A,C,S application'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.
This includes the 'IVA 1C basic category L,M,N,P,T application'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.
This includes the 'IVA 1C normal category R application'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.
This includes the 'IVA 1C mutual recognition category E application'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.
This includes the 'IVA 1C application for IVA in Northern Ireland only'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.
This includes the 'IVA 5 request for replacement certificate'.
Expected processing time from date of submission: 5 days
This includes the 'IVA 9 application for a model report or TILT at a non DVSA site'.
Expected processing time from date of submission: 10 days
Before you continue, ensure you have read the guidance documentation (opens in new tab) for this test type.


This research project develops signal processing, image processing, and machine learning technology ingesting multi-dimensional datasets acquired on paintings to unveil distributions of materials within artwork
Abstract: X-ray images of polyptych wings, or other artworks painted on both sides of their support, contain in one image content from both paintings, making them difficult for experts to “read.” To improve the utility of these x-ray images in studying these artworks, it is desirable to separate the content into two images, each pertaining to only one side. This is a difficult task for which previous approaches have been only partially successful. Deep neural network algorithms have recently achieved remarkable progress in a wide range of image analysis and other challenging tasks. We, therefore, propose a new self-supervised approach to this x-ray separation, leveraging an available convolutional neural network architecture; results obtained for details from the Adam and Eve panels of the Ghent Altarpiece spectacularly improve on previous attempts.
Link


public interface Cookie
A cookie has a name, a single value, and optional attributes such as a comment, path and domain qualifiers, a maximum age, and a version number.
The server sends cookies to the browser by using the Response.cookie(Cookie)
method, which adds fields to HTTP response headers to send cookies to the browser, one at a time. The browser is expected to support 20 cookies for each Web server, 300 cookies total, and may limit cookie size to 4 KB each.
The browser returns cookies to the server by adding fields to HTTP request headers. Cookies can be retrieved from a request by using the Request.cookie(String)
method. Several cookies might have the same name but different path attributes.
This class supports both the Version 0 (by Netscape) and Version 1 (by RFC 2109) cookie specifications. By default, cookies are created using Version 0 to ensure the best interoperability.
| Modifier and Type | Interface and Description |
|---|---|
static class |
Cookie.Definition
Build a Cookie .
|
static class |
Cookie.Signature
Sign cookies using a HMAC algorithm plus SHA-256 hash.
|
| Modifier and Type | Field and Description |
|---|---|
static Function<String,Map<String,String>> |
URL_DECODER
Decode a cookie value using, like: k=v , multiple k=v pair are separated by & .
|
static Function<Map<String,String>,String> |
URL_ENCODER
Encode a hash into cookie value, like: k1=v1&...&kn=vn .
|
| Modifier and Type | Method and Description |
|---|---|
Optional<String> |
comment() |
Optional<String> |
domain() |
String |
encode() |
boolean |
httpOnly() |
int |
maxAge()
Gets the maximum age of this cookie (in seconds).
|
String |
name() |
Optional<String> |
path() |
boolean |
secure()
Returns true if the browser is sending cookies only over a secure protocol, or false if the browser can send cookies using any protocol.
|
Optional<String> |
value() |
static final Function<String,Map<String,String>> URL_DECODER
k=v
, multiple k=v
pair are separated by &
. Also, k
and v
are decoded using URLDecoder
.
int maxAge()
By default, -1
is returned, which indicates that the cookie will persist until browser shutdown.
boolean secure()
true
if the browser is sending cookies only over a secure protocol, or false
if the browser can send cookies using any protocol.
true
if the browser uses a secure protocol, false
otherwise.
boolean httpOnly()
Copyright © 2019. All rights reserved.


Classic stylesheets for web applications
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Tabs
First tab panel
Second tab panel
Third tab panel
Lists
Green
Orange
Yellow
Blue
Violet
Detailed lists
|
My Documents
|
File Folder | 2020-07-14 20:28 | |
|
Program Files
|
File Folder | 2020-07-14 20:28 | |
|
autoexec.bat
|
0KB | MS-DOS Batch File | 2020-07-14 20:28 |
|
Command.com
|
92KB | MS-DOS Application | 1999-04-23 22:22 |
| Name | Size | Type | Modified |
|---|---|---|---|
|
My Documents
|
File Folder | 2020-07-14 20:28 | |
|
Program Files
|
File Folder | 2020-07-14 20:28 | |
|
autoexec.bat
|
0KB | MS-DOS Batch File | 2020-07-14 20:28 |
|
Command.com
|
92KB | MS-DOS Application | 1999-04-23 22:22 |
Icon grids
Network Neighborhood
My Documents
New Text Document.txt
New Text Document (2).txt
New Text Document (3).txt
New Bitmap Image.bmp
New Bitmap Image (2).bmp
New Bitmap Image (3).bmp
Recycle Bin
Menus
- Open
- Edit
-
Send To
- Compressed Folder
- Desktop
- Properties
-
File
- Save
- Save As…
-
Another Submenu
- Foo
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- Quit
-
Edit
- Undo
- Cut
- Copy
- Paste
Windows
-
File
- Save
- Save As…
-
Another Submenu
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Do you want to delete everything?
Do you want to delete everything?


# Allen Institute Software License - This software license is the 2-clause BSD
# license plus a third clause that prohibits redistribution for commercial
# purposes without further permission.
#
# Copyright 2017-2019. Allen Institute. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Redistributions for commercial purposes are not permitted without the
# Allen Institute's written permission.
# For purposes of this license, commercial purposes is the incorporation of the
# Allen Institute's software into anything for which you will charge fees or
# other compensation. Contact<EMAIL_ADDRESS>for commercial licensing
# opportunities.
 IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
from django.db import models
from workflow_engine.mixins import (
Archivable,
Configurable,
Runnable,
Timestamped
)
import logging
[docs]class SafeWorkflowNodeManager(models.Manager):
[docs] def get_queryset(self):
return super(SafeWorkflowNodeManager, self).get_queryset().filter(
workflow__archived=False,
archived=False
)
[docs]class WorkflowNode(Archivable, Configurable, Timestamped, models.Model):
_log = logging.getLogger('workflow_engine.models.workflow_node')
job_queue = models.ForeignKey(
'workflow_engine.JobQueue',
on_delete=models.CASCADE
)
'''Defines strategy code and a queue of object to be run'''
parent = models.ForeignKey(
'workflow_engine.WorkflowNode',
null=True,
blank=True,
on_delete=models.CASCADE
)
'''Deprecated field from when workflows were implemented as trees.'''
sinks = models.ManyToManyField(
'self', through='workflow_engine.WorkflowEdge',
related_name='sources',
symmetrical=False,
through_fields=('source', 'sink')
)
'''Accessor to immediately downstream nodes'''
is_head = models.BooleanField(default=False)
'''Deprecated field from when workflows were implemented as trees.'''
workflow = models.ForeignKey(
'workflow_engine.Workflow',
on_delete=models.CASCADE
)
'''Accessor to the workflow collection of nodes and edges'''
disabled = models.BooleanField(default=False)
'''Used to temporarily turn off the node.'''
batch_size = models.IntegerField(default=50)
'''How many enqueued objects to submit to the compute cluster at a time.'''
priority = models.IntegerField(default=50)
'''Integer value to provide to the compute cluster (lower number is higher priority)'''
overwrite_previous_job = models.BooleanField(default=True)
'''Whether to reuse a job records or archive them'''
max_retries = models.IntegerField(default=3)
'''How many times to resubmit failed jobs automatically.'''
safe_objects = SafeWorkflowNodeManager()
'''Used to filter archived workflow objects out of queries'''
def __str__(self):
'''default human readable representation'''
return self.get_node_short_name()
[docs] def get_node_short_name(self):
'''Node name is defined by the job queue name'''
return self.job_queue.name # TODO: this interacts poorly w/ unique restriction.
[docs] def get_node_name(self):
'''Node name for use in the
:class:`WorkflowView <workflow_engine.views.workflow_view.WorkflowView>`
'''
return self.job_queue.name + '(' + str(self.get_total_number_of_jobs()) + ') ' + str(self.get_number_of_queued_and_running_jobs()) + ' / '+ str(self.batch_size)
[docs] def get_workflow_name(self):
'''Helper for the collection name'''
return self.workflow.name
[docs] def get_strategy(self):
'''Helper for accessing the implementation'''
return self.job_queue.get_strategy()
[docs] def get_children(self):
'''Access following nodes.
Returns
-------
QuerySet
nodes immediately downstream in priority order
'''
return self.sinks.all().order_by('sinks') # TODO: priority order?
[docs] def get_total_number_of_jobs(self):
'''Count all associated jobs regardless of state.
Returns
-------
Integer
number of unarchived jobs associated with the node
'''
return self.job_set.count()
[docs] def get_number_of_queued_and_running_jobs(self):
'''Count jobs that are queued or running.
Returns
-------
Integer
number of unarchived jobs associated with the node
'''
return self.get_queued_and_running_jobs().count()
[docs] def get_queued_and_running_jobs(self):
return self.job_set.filter(
running_state__in=[
Runnable.STATE.QUEUED,
Runnable.STATE.RUNNING
]
)
[docs] def get_n_pending_jobs(self, number_jobs_to_run):
return self.job_set.filter(
running_state=Runnable.STATE.PENDING,
).order_by(
'priority',
'-updated_at'
)[:number_jobs_to_run]
[docs] def update(self,
current_disabled,
overwrite_previous_job,
max_retries,
batch_size,
priority):
prev_disabled = self.disabled
self.disabled = current_disabled
self.overwrite_previous_job = overwrite_previous_job
self.max_retries = int(max_retries)
self.batch_size = int(batch_size)
self.priority = int(priority)
self.save()
return prev_disabled
[docs] def get_job_states(self):
result = {}
node_jobs = self.job_set.all()
success_count = node_jobs.filter(
running_state=Runnable.STATE.SUCCESS).count()
failed_count = node_jobs.filter(
running_state__in=[
Runnable.STATE.FAILED_EXECUTION,
Runnable.STATE.FAILED,
Runnable.STATE.PROCESS_KILLED
]).count()
running_count = node_jobs.filter(
running_state__in=[
Runnable.STATE.RUNNING,
Runnable.STATE.PENDING,
Runnable.STATE.QUEUED,
Runnable.STATE.FINISHED_EXECUTION
]).count()
if success_count > 0:
result[Runnable.STATE.SUCCESS] = success_count
if failed_count > 0:
result[Runnable.STATE.FAILED] = failed_count
if running_count > 0:
result[Runnable.STATE.RUNNING] = running_count
return result
[docs] def short_enqueued_object_class_name(self):
try:
return self.job_queue.enqueued_object_type.model_class().__name__
except:
return '-'


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Highlighting
Highlighters enable you to get highlighted snippets from one or more fields
in your search results so you can show users where the query matches are.
When you request highlights, the response contains an additional highlight
element for each search hit that includes the highlighted fields and the
highlighted fragments.
|
Note
|
Highlighters don’t reflect the boolean logic of a query when extracting
terms to highlight. Thus, for some complex boolean queries (e.g nested boolean
queries, queries using minimum_should_match etc.), parts of documents may be
highlighted that don’t correspond to query matches.
|
Highlighting requires the actual content of a field. If the field is not
stored (the mapping does not set store
to true
), the actual _source
is
loaded and the relevant field is extracted from _source
.
For example, to get highlights for the content
field in each search hit
using the default highlighter, include a highlight
object in
the request body that specifies the content
field:
GET /_search
{
"query": {
"match": { "content": "bilbo" }
},
"highlight": {
"fields": {
"content": {}
}
}
}
OpenSearch supports three highlighters: unified
, plain
, and fvh
(fast vector
highlighter). You can specify the highlighter type
you want to use
for each field.
Unified highlighter
The unified
highlighter uses the Lucene Unified Highlighter. This
highlighter breaks the text into sentences and uses the BM25 algorithm to score
individual sentences as if they were documents in the corpus. It also supports
accurate phrase and multi-term (fuzzy, prefix, regex) highlighting. This is the
default highlighter.
Plain highlighter
The plain
highlighter uses the standard Lucene highlighter. It attempts to
reflect the query matching logic in terms of understanding word importance and
any word positioning criteria in phrase queries.
|
Warning
|
The plain highlighter works best for highlighting simple query matches in a
single field. To accurately reflect query logic, it creates a tiny in-memory
index and re-runs the original query criteria through Lucene’s query execution
planner to get access to low-level match information for the current document.
This is repeated for every field and every document that needs to be highlighted.
If you want to highlight a lot of fields in a lot of documents with complex
queries, we recommend using the unified highlighter on postings or term_vector fields.
|
Fast vector highlighter
The fvh
highlighter uses the Lucene Fast Vector highlighter.
This highlighter can be used on fields with term_vector
set to
with_positions_offsets
in the mapping. The fast vector highlighter:
-
Can be customized with a
boundary_scanner
. -
Requires setting
term_vector
towith_positions_offsets
which increases the size of the index -
Can combine matches from multiple fields into one result. See
matched_fields
-
Can assign different weights to matches at different positions allowing for things like phrase matches being sorted above term matches when highlighting a Boosting Query that boosts phrase matches over term matches
|
Warning
|
The fvh highlighter does not support span queries. If you need support for
span queries, try an alternative highlighter, such as the unified highlighter.
|
Offsets strategy
To create meaningful search snippets from the terms being queried, the highlighter needs to know the start and end character offsets of each word in the original text. These offsets can be obtained from:
-
The postings list. If
index_options
is set tooffsets
in the mapping, theunified
highlighter uses this information to highlight documents without re-analyzing the text. It re-runs the original query directly on the postings and extracts the matching offsets from the index, limiting the collection to the highlighted documents. This is important if you have large fields because it doesn’t require reanalyzing the text to be highlighted. It also requires less disk space than usingterm_vectors
. -
Term vectors. If
term_vector
information is provided by settingterm_vector
towith_positions_offsets
in the mapping, theunified
highlighter automatically uses theterm_vector
to highlight the field. It’s fast especially for large fields (>1MB
) and for highlighting multi-term queries likeprefix
orwildcard
because it can access the dictionary of terms for each document. Thefvh
highlighter always uses term vectors. -
Plain highlighting. This mode is used by the
unified
when there is no other alternative. It creates a tiny in-memory index and re-runs the original query criteria through Lucene’s query execution planner to get access to low-level match information on the current document. This is repeated for every field and every document that needs highlighting. Theplain
highlighter always uses plain highlighting.
|
Warning
|
Plain highlighting for large texts may require substantial amount of time and memory.
To protect against this, the maximum number of text characters that will be analyzed has been
limited to 1000000. This default limit can be changed
for a particular index with the index setting index.highlight.max_analyzed_offset .
|
Highlighting settings
Highlighting settings can be set on a global level and overridden at the field level.
- boundary_chars
-
A string that contains each boundary character. Defaults to
.,!? \t\n
. - boundary_max_scan
-
How far to scan for boundary characters. Defaults to
20
.
- boundary_scanner
-
Specifies how to break the highlighted fragments:
chars
,sentence
, orword
. Only valid for theunified
andfvh
highlighters. Defaults tosentence
for theunified
highlighter. Defaults tochars
for thefvh
highlighter.chars
-
Use the characters specified by
boundary_chars
as highlighting boundaries. Theboundary_max_scan
setting controls how far to scan for boundary characters. Only valid for thefvh
highlighter. sentence
-
Break highlighted fragments at the next sentence boundary, as determined by Java’s BreakIterator. You can specify the locale to use with
boundary_scanner_locale
.NoteWhen used with the unified
highlighter, thesentence
scanner splits sentences bigger thanfragment_size
at the first word boundary next tofragment_size
. You can setfragment_size
to 0 to never split any sentence. word
-
Break highlighted fragments at the next word boundary, as determined by Java’s BreakIterator. You can specify the locale to use with
boundary_scanner_locale
.
- boundary_scanner_locale
-
Controls which locale is used to search for sentence and word boundaries. This parameter takes a form of a language tag, e.g.
"en-US"
,"fr-FR"
,"ja-JP"
. More info can be found in the Locale Language Tag documentation. The default value is Locale.ROOT. - encoder
-
Indicates if the snippet should be HTML encoded:
default
(no encoding) orhtml
(HTML-escape the snippet text and then insert the highlighting tags) - fields
-
Specifies the fields to retrieve highlights for. You can use wildcards to specify fields. For example, you could specify
comment_*
to get highlights for all text and keyword fields that start withcomment_
.NoteOnly text and keyword fields are highlighted when you use wildcards. If you use a custom mapper and want to highlight on a field anyway, you must explicitly specify that field name. - force_source
-
Highlight based on the source even if the field is stored separately. Defaults to
false
. - fragmenter
-
Specifies how text should be broken up in highlight snippets:
simple
orspan
. Only valid for theplain
highlighter. Defaults tospan
.simple
-
Breaks up text into same-sized fragments.
span
-
Breaks up text into same-sized fragments, but tries to avoid breaking up text between highlighted terms. This is helpful when you’re querying for phrases. Default.
- fragment_offset
-
Controls the margin from which you want to start highlighting. Only valid when using the
fvh
highlighter. - fragment_size
-
The size of the highlighted fragment in characters. Defaults to 100.
- highlight_query
-
Highlight matches for a query other than the search query. This is especially useful if you use a rescore query because those are not taken into account by highlighting by default.
ImportantOpenSearch does not validate that highlight_query
contains the search query in any way so it is possible to define it so legitimate query results are not highlighted. Generally, you should include the search query as part of thehighlight_query
. - matched_fields
-
Combine matches on multiple fields to highlight a single field. This is most intuitive for multifields that analyze the same string in different ways. All
matched_fields
must haveterm_vector
set towith_positions_offsets
, but only the field to which the matches are combined is loaded so only that field benefits from havingstore
set toyes
. Only valid for thefvh
highlighter. - no_match_size
-
The amount of text you want to return from the beginning of the field if there are no matching fragments to highlight. Defaults to 0 (nothing is returned).
- number_of_fragments
-
The maximum number of fragments to return. If the number of fragments is set to 0, no fragments are returned. Instead, the entire field contents are highlighted and returned. This can be handy when you need to highlight short texts such as a title or address, but fragmentation is not required. If
number_of_fragments
is 0,fragment_size
is ignored. Defaults to 5. - order
-
Sorts highlighted fragments by score when set to
score
. By default, fragments will be output in the order they appear in the field (order:none
). Setting this option toscore
will output the most relevant fragments first. Each highlighter applies its own logic to compute relevancy scores. See the document How highlighters work internally for more details how different highlighters find the best fragments. - phrase_limit
-
Controls the number of matching phrases in a document that are considered. Prevents the
fvh
highlighter from analyzing too many phrases and consuming too much memory. When usingmatched_fields
,phrase_limit
phrases per matched field are considered. Raising the limit increases query time and consumes more memory. Only supported by thefvh
highlighter. Defaults to 256. - pre_tags
-
Use in conjunction with
post_tags
to define the HTML tags to use for the highlighted text. By default, highlighted text is wrapped in
and
tags. Specify as an array of strings. - post_tags
-
Use in conjunction with
pre_tags
to define the HTML tags to use for the highlighted text. By default, highlighted text is wrapped in
and
tags. Specify as an array of strings. - require_field_match
-
By default, only fields that contains a query match are highlighted. Set
require_field_match
tofalse
to highlight all fields. Defaults totrue
. - tags_schema
-
Set to
styled
to use the built-in tag schema. Thestyled
schema defines the followingpre_tags
and definespost_tags
as
., , , , , , , , ,
- type
-
The highlighter to use:
unified
,plain
, orfvh
. Defaults tounified
.
Highlighting examples
Override global settings
You can specify highlighter settings globally and selectively override them for individual fields.
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"number_of_fragments" : 3,
"fragment_size" : 150,
"fields" : {
"body" : { "pre_tags" : [""], "post_tags" : [""] },
"blog.title" : { "number_of_fragments" : 0 },
"blog.author" : { "number_of_fragments" : 0 },
"blog.comment" : { "number_of_fragments" : 5, "order" : "score" }
}
}
}
Specify a highlight query
You can specify a highlight_query
to take additional information into account
when highlighting. For example, the following query includes both the search
query and rescore query in the highlight_query
. Without the highlight_query
,
highlighting would only take the search query into account.
GET /_search
{
"query": {
"match": {
"comment": {
"query": "foo bar"
}
}
},
"rescore": {
"window_size": 50,
"query": {
"rescore_query": {
"match_phrase": {
"comment": {
"query": "foo bar",
"slop": 1
}
}
},
"rescore_query_weight": 10
}
},
"_source": false,
"highlight": {
"order": "score",
"fields": {
"comment": {
"fragment_size": 150,
"number_of_fragments": 3,
"highlight_query": {
"bool": {
"must": {
"match": {
"comment": {
"query": "foo bar"
}
}
},
"should": {
"match_phrase": {
"comment": {
"query": "foo bar",
"slop": 1,
"boost": 10.0
}
}
},
"minimum_should_match": 0
}
}
}
}
}
}
Set highlighter type
The type
field allows to force a specific highlighter type.
The allowed values are: unified
, plain
and fvh
.
The following is an example that forces the use of the plain highlighter:
GET /_search
{
"query": {
"match": { "user.id": "bilbo" }
},
"highlight": {
"fields": {
"comment": { "type": "plain" }
}
}
}
Configure highlighting tags
By default, the highlighting will wrap highlighted text in
and

. This can be controlled by setting pre_tags
and post_tags
,
for example:
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"pre_tags" : ["<tag1>"],
"post_tags" : ["</tag1>"],
"fields" : {
"body" : {}
}
}
}
When using the fast vector highlighter, you can specify additional tags and the "importance" is ordered.
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"pre_tags" : ["<tag1>", "<tag2>"],
"post_tags" : ["</tag1>", "</tag2>"],
"fields" : {
"body" : {}
}
}
}
You can also use the built-in styled
tag schema:
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"tags_schema" : "styled",
"fields" : {
"comment" : {}
}
}
}
Highlight on source
Forces the highlighting to highlight fields based on the source even if fields
are stored separately. Defaults to false
.
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"fields" : {
"comment" : {"force_source" : true}
}
}
}
Highlight in all fields
By default, only fields that contains a query match are highlighted. Set
require_field_match
to false
to highlight all fields.
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"require_field_match": false,
"fields": {
"body" : { "pre_tags" : [""], "post_tags" : [""] }
}
}
}
Combine matches on multiple fields
|
Warning
|
This is only supported by the fvh highlighter
|
The Fast Vector Highlighter can combine matches on multiple fields to
highlight a single field. This is most intuitive for multifields that
analyze the same string in different ways. All matched_fields
must have
term_vector
set to with_positions_offsets
but only the field to which
the matches are combined is loaded so only that field would benefit from having
store
set to yes
.
In the following examples, comment
is analyzed by the english
analyzer and comment.plain
is analyzed by the standard
analyzer.
GET /_search
{
"query": {
"query_string": {
"query": "comment.plain:running scissors",
"fields": [ "comment" ]
}
},
"highlight": {
"order": "score",
"fields": {
"comment": {
"matched_fields": [ "comment", "comment.plain" ],
"type": "fvh"
}
}
}
}
The above matches both "run with scissors" and "running with scissors" and would highlight "running" and "scissors" but not "run". If both phrases appear in a large document then "running with scissors" is sorted above "run with scissors" in the fragments list because there are more matches in that fragment.
GET /_search
{
"query": {
"query_string": {
"query": "running scissors",
"fields": ["comment", "comment.plain^10"]
}
},
"highlight": {
"order": "score",
"fields": {
"comment": {
"matched_fields": ["comment", "comment.plain"],
"type" : "fvh"
}
}
}
}
The above highlights "run" as well as "running" and "scissors" but still sorts "running with scissors" above "run with scissors" because the plain match ("running") is boosted.
GET /_search
{
"query": {
"query_string": {
"query": "running scissors",
"fields": [ "comment", "comment.plain^10" ]
}
},
"highlight": {
"order": "score",
"fields": {
"comment": {
"matched_fields": [ "comment.plain" ],
"type": "fvh"
}
}
}
}
The above query wouldn’t highlight "run" or "scissor" but shows that
it is just fine not to list the field to which the matches are combined
(comment
) in the matched fields.
|
Note
|
Technically it is also fine to add fields to matched_fields that
don’t share the same underlying string as the field to which the matches
are combined. The results might not make much sense and if one of the
matches is off the end of the text then the whole query will fail.
|
|
Note
|
There is a small amount of overhead involved with setting
to
|
Explicitly order highlighted fields
OpenSearch highlights the fields in the order that they are sent, but per the
JSON spec, objects are unordered. If you need to be explicit about the order
in which fields are highlighted specify the fields
as an array:
GET /_search
{
"highlight": {
"fields": [
{ "title": {} },
{ "text": {} }
]
}
}
None of the highlighters built into OpenSearch care about the order that the fields are highlighted but a plugin might.
Control highlighted fragments
Each field highlighted can control the size of the highlighted fragment
in characters (defaults to 100
), and the maximum number of fragments
to return (defaults to 5
).
For example:
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"fields" : {
"comment" : {"fragment_size" : 150, "number_of_fragments" : 3}
}
}
}
On top of this it is possible to specify that highlighted fragments need to be sorted by score:
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"order" : "score",
"fields" : {
"comment" : {"fragment_size" : 150, "number_of_fragments" : 3}
}
}
}
If the number_of_fragments
value is set to 0
then no fragments are
produced, instead the whole content of the field is returned, and of
course it is highlighted. This can be very handy if short texts (like
document title or address) need to be highlighted but no fragmentation
is required. Note that fragment_size
is ignored in this case.
GET /_search
{
"query" : {
"match": { "user.id": "bilbo" }
},
"highlight" : {
"fields" : {
"body" : {},
"blog.title" : {"number_of_fragments" : 0}
}
}
}
When using fvh
one can use fragment_offset
parameter to control the margin to start highlighting from.
In the case where there is no matching fragment to highlight, the default is
to not return anything. Instead, we can return a snippet of text from the
beginning of the field by setting no_match_size
(default 0
) to the length
of the text that you want returned. The actual length may be shorter or longer than
specified as it tries to break on a word boundary.
GET /_search
{
"query": {
"match": { "user.id": "bilbo" }
},
"highlight": {
"fields": {
"comment": {
"fragment_size": 150,
"number_of_fragments": 3,
"no_match_size": 150
}
}
}
}
Highlight using the postings list
Here is an example of setting the comment
field in the index mapping to
allow for highlighting using the postings:
PUT /example
{
"mappings": {
"properties": {
"comment" : {
"type": "text",
"index_options" : "offsets"
}
}
}
}
Here is an example of setting the comment
field to allow for
highlighting using the term_vectors
(this will cause the index to be bigger):
PUT /example
{
"mappings": {
"properties": {
"comment" : {
"type": "text",
"term_vector" : "with_positions_offsets"
}
}
}
}
Specify a fragmenter for the plain highlighter
When using the plain
highlighter, you can choose between the simple
and
span
fragmenters:
GET my-index-000001/_search
{
"query": {
"match_phrase": { "message": "number 1" }
},
"highlight": {
"fields": {
"message": {
"type": "plain",
"fragment_size": 15,
"number_of_fragments": 3,
"fragmenter": "simple"
}
}
}
}
Response:
{
...
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.6011951,
"hits": [
{
"_index": "my-index-000001",
"_type": "_doc",
"_id": "1",
"_score": 1.6011951,
"_source": {
"message": "some message with the number 1"
},
"highlight": {
"message": [
" with the number",
" 1"
]
}
}
]
}
}
GET my-index-000001/_search
{
"query": {
"match_phrase": { "message": "number 1" }
},
"highlight": {
"fields": {
"message": {
"type": "plain",
"fragment_size": 15,
"number_of_fragments": 3,
"fragmenter": "span"
}
}
}
}
Response:
{
...
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1.6011951,
"hits": [
{
"_index": "my-index-000001",
"_type": "_doc",
"_id": "1",
"_score": 1.6011951,
"_source": {
"message": "some message with the number 1"
},
"highlight": {
"message": [
" with the number 1"
]
}
}
]
}
}
If the number_of_fragments
option is set to 0
,
NullFragmenter
is used which does not fragment the text at all.
This is useful for highlighting the entire contents of a document or field.
How highlighters work internally
Given a query and a text (the content of a document field), the goal of a highlighter is to find the best text fragments for the query, and highlight the query terms in the found fragments. For this, a highlighter needs to address several questions:
-
How break a text into fragments?
-
How to find the best fragments among all fragments?
-
How to highlight the query terms in a fragment?
How to break a text into fragments?
Relevant settings: fragment_size
, fragmenter
, type
of highlighter,
boundary_chars
, boundary_max_scan
, boundary_scanner
, boundary_scanner_locale
.
Plain highlighter begins with analyzing the text using the given analyzer,
and creating a token stream from it. Plain highlighter uses a very simple
algorithm to break the token stream into fragments. It loops through terms in the token stream,
and every time the current term’s end_offset exceeds fragment_size
multiplied by the number of
created fragments, a new fragment is created. A little more computation is done with using span
fragmenter to avoid breaking up text between highlighted terms. But overall, since the breaking is
done only by fragment_size
, some fragments can be quite odd, e.g. beginning
with a punctuation mark.
Unified or FVH highlighters do a better job of breaking up a text into
fragments by utilizing Java’s BreakIterator
. This ensures that a fragment
is a valid sentence as long as fragment_size
allows for this.
How to find the best fragments?
Relevant settings: number_of_fragments
.
To find the best, most relevant, fragments, a highlighter needs to score each fragment in respect to the given query. The goal is to score only those terms that participated in generating the 'hit' on the document. For some complex queries, this is still work in progress.
The plain highlighter creates an in-memory index from the current token stream, and re-runs the original query criteria through Lucene’s query execution planner to get access to low-level match information for the current text. For more complex queries the original query could be converted to a span query, as span queries can handle phrases more accurately. Then this obtained low-level match information is used to score each individual fragment. The scoring method of the plain highlighter is quite simple. Each fragment is scored by the number of unique query terms found in this fragment. The score of individual term is equal to its boost, which is by default is 1. Thus, by default, a fragment that contains one unique query term, will get a score of 1; and a fragment that contains two unique query terms, will get a score of 2 and so on. The fragments are then sorted by their scores, so the highest scored fragments will be output first.
FVH doesn’t need to analyze the text and build an in-memory index, as it uses pre-indexed document term vectors, and finds among them terms that correspond to the query. FVH scores each fragment by the number of query terms found in this fragment. Similarly to plain highlighter, score of individual term is equal to its boost value. In contrast to plain highlighter, all query terms are counted, not only unique terms.
Unified highlighter can use pre-indexed term vectors or pre-indexed terms offsets, if they are available. Otherwise, similar to Plain Highlighter, it has to create an in-memory index from the text. Unified highlighter uses the BM25 scoring model to score fragments.
How to highlight the query terms in a fragment?
Relevant settings: pre-tags
, post-tags
.
The goal is to highlight only those terms that participated in generating the 'hit' on the document. For some complex boolean queries, this is still work in progress, as highlighters don’t reflect the boolean logic of a query and only extract leaf (terms, phrases, prefix etc) queries.
Plain highlighter given the token stream and the original text, recomposes the original text to highlight only terms from the token stream that are contained in the low-level match information structure from the previous step.
FVH and unified highlighter use intermediate data structures to represent fragments in some raw form, and then populate them with actual text.
A highlighter uses pre-tags
, post-tags
to encode highlighted terms.
An example of the work of the unified highlighter
Let’s look in more details how unified highlighter works.
First, we create a index with a text field content
, that will be indexed
using english
analyzer, and will be indexed without offsets or term vectors.
PUT test_index
{
"mappings": {
"properties": {
"content": {
"type": "text",
"analyzer": "english"
}
}
}
}
We put the following document into the index:
PUT test_index/_doc/doc1
{
"content" : "For you I'm only a fox like a hundred thousand other foxes. But if you tame me, we'll need each other. You'll be the only boy in the world for me. I'll be the only fox in the world for you."
}
And we ran the following query with a highlight request:
GET test_index/_search
{
"query": {
"match_phrase" : {"content" : "only fox"}
},
"highlight": {
"type" : "unified",
"number_of_fragments" : 3,
"fields": {
"content": {}
}
}
}
After doc1
is found as a hit for this query, this hit will be passed to the
unified highlighter for highlighting the field content
of the document.
Since the field content
was not indexed either with offsets or term vectors,
its raw field value will be analyzed, and in-memory index will be built from
the terms that match the query:
{"token":"onli","start_offset":12,"end_offset":16,"position":3}, {"token":"fox","start_offset":19,"end_offset":22,"position":5}, {"token":"fox","start_offset":53,"end_offset":58,"position":11}, {"token":"onli","start_offset":117,"end_offset":121,"position":24}, {"token":"onli","start_offset":159,"end_offset":163,"position":34}, {"token":"fox","start_offset":164,"end_offset":167,"position":35}
Our complex phrase query will be converted to the span query:
spanNear([text:onli, text:fox], 0, true)
, meaning that we are looking for
terms "onli: and "fox" within 0 distance from each other, and in the given
order. The span query will be run against the created before in-memory index,
to find the following match:
{"term":"onli", "start_offset":159, "end_offset":163}, {"term":"fox", "start_offset":164, "end_offset":167}
In our example, we have got a single match, but there could be several matches.
Given the matches, the unified highlighter breaks the text of the field into
so called "passages". Each passage must contain at least one match.
The unified highlighter with the use of Java’s BreakIterator
ensures that each
passage represents a full sentence as long as it doesn’t exceed fragment_size
.
For our example, we have got a single passage with the following properties
(showing only a subset of the properties here):
Passage: startOffset: 147 endOffset: 189 score: 3.7158387 matchStarts: [159, 164] matchEnds: [163, 167] numMatches: 2
Notice how a passage has a score, calculated using the BM25 scoring formula
adapted for passages. Scores allow us to choose the best scoring
passages if there are more passages available than the requested
by the user number_of_fragments
. Scores also let us to sort passages by
order: "score"
if requested by the user.
As the final step, the unified highlighter will extract from the field’s text a string corresponding to each passage:
"I'll be the only fox in the world for you."
and will format with the tags  and  all matches in this string
using the passages’s matchStarts
and matchEnds
information:
I'll be the only fox in the world for you.
This kind of formatted strings are the final result of the highlighter returned to the user.


@* * Copyright 2021 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.helptosavefrontend.models.HtsContext @import uk.gov.hmrc.helptosavefrontend.config.FrontendAppConfig @this(main: uk.gov.hmrc.helptosavefrontend.views.html.main_template) @()(implicit htsContext: HtsContext, request: Request[_], messages: Messages, appConfig: FrontendAppConfig) @title = @{ Messages("hts.we-cannot-check-details.title.h1") } @main( title = title, bodyClasses = None){
@Html(Messages("hts.we-cannot-check-details.title.p1"))
@Html(Messages("hts.we-cannot-check-details.title.p2"))
@Messages("hts.we-cannot-check-details.create-gg-account")@Html(Messages("hts.we-cannot-check-details.title.p3"))
@Messages("hts.sign-in") }


@(playerName : String, crew : String) @import helper._
You reach Valyria and load up on dragons. When you get back to Westeros the Queen rewards you with a monopoly on importing them. You rule happily ever after. The end for @playerName.


|
CAT GYAN
FAQs About CAT
- What is the weightage given to CAT scores, GD and
PI?
No one knows for sure, except of course the
professors themselves. You have enough to worry about as it
is, so leave weightages alone. Just put in your best at
every stage.
- Does work experience make a difference?
Letís
put it this way. Work Ex. is not a negative. Depending on
the profile the profs are looking for, it could be a
positive. Only the preparation will differ slightly. Check
the Interview tips.
- Do I have to indicate an area of specialization?
Not really. Do so if you are really keen on a particular
area and then be prepared to answer a few basic questions
regarding that area. Most people decide only after getting
here, so itís okay to say that youíre keeping options open.
- What if I have no extra-curricular activities to talk
about?
Come on, you must have taken part in some
race, some small elocution in the ninth standard, or in the
very least played cricket with friends from the colony! You
donít have to be a stud player (that helps though), but you
need to come across as a person with diverse interests.
INTERVIEW GYAN
An interview is a selection method unlike CAT, which is an
elimination method. So, prepare on several levels -
- General Knowledge - have an opinion about thingsÖ
you donít have to be an expert but 'awareness' is the key.
It could be about anything - from Presidents to polls to the
budget to the population of your native place
- Academics - if youíve got work ex, you might not
be grilled too much on your grad fundas, but in any case,
youíll have to dust your textbooks and read up on the
basics. If you are a fresher, then chances are you might
have to take a lot of acad related questions.
 However much you try and cram in,
thereíd always be things you canít cover in the given amount
of time. The best way to get a hold on things is to get your
grounding firm. Revise your core courses and do the basics -
the stuff thatís elementary but important in your line of
specialization. Concentrate on application, rather than pure
theory. For IIMC in particular, do a bit of Math Ė
probability, differential calculus, trigonometry, etc.
(prove a triangle sum of angles is 180!) Example: For an
Electronics and Telecomm. Engineer: 555 timer circuit, how
does a fan/circonditioner work, latest in telecom industry,
WAP, M-commerce, etc
- Work Experience - be prepared to answer any
question regarding your work. Prepare to talk about your
projects, your major achievements, failures and learnings.
Also find out about your company statistics (size, profits,
market share) vis-ŗ-vis your competitors
- Personal - the general load of questions about
why you did xyz and not abc in life... why MBA... describe
yourself in a sentence, a wordÖ please think about these
questions carefully in advance. Donít make up answers on the
spot!
- Stress - be prepared to handle stress.  Get them
to take your trip on different levels Ė fundas, stress, GK,
etc. It helps.
GROUP DISCUSSION It is
not about airtime. Speak confidently and speak well. Do NOT
speak rubbish just for the sake of getting yourself heard - in
that case, any amount of airtime wonít do.
Talk sense, whatever be the amount of airtime. Donít try to
hog the limelight by uttering things like "I agree with my
friend here" or "Thatís a good point", unless you are going to
add something that is cogent and that hasnít been said before.
At the same time, donít remain too quiet and passive, donít
keep the interviewer in doubt, chances are that he wonít look
at it too well.
You can also try bringing in a different point of view - a
different definition of the topic given, that could show your
creativity. But again, let it be realistic so that you wonít
be wasting anyone's time. Again, prior practice
helps. |


{% extends "layouts/base.html" %} {% block title %} Profile {% endblock %} {% block stylesheets %}{% endblock stylesheets %} {% block content %}
CEO / Co-Founder
Hi, I’m Alec Thompson, Decisions: If you can’t decide, the answer is no. If two equally difficult paths, choose the one more painful in the short term (pain avoidance is creating an illusion of equality).
Architects design houses
Project #1
Music is something that every person has his or her own specific opinion about.