Uses of Class
ltl.Formula
-
Uses of Formula in ltl
Subclasses of Formula in ltl Modifier and Type Class Description class
And
This class represents an LTL formula that is a conjuction (and) of two formulas.class
AtomicProposition
This class represents the LTL formula consisting of an atomic proposition.class
BinaryFormula
This class represents a generic binary LTL formula type consisting of two sub formulas.class
ConstantFormula
This class represents a generic constant LTL formula type consisting of some value.class
False
This class represents the LTL state formula false.class
Next
This class represents an LTL formula that is a next formula.class
Not
This class represents an LTL formula that is the negation (not) of a formula.class
Or
This class represents an LTL formula that is an Or formula.class
True
This class represents the LTL state formula true.class
UnaryFormula
This class represents a generic unary LTL formula type consisting of one sub formula.class
Until
This class represents an LTL formula that is an until formula.class
WeakUntil
This class represents an LTL formula that is a weak until formula.Methods in ltl that return Formula Modifier and Type Method Description Formula
BinaryFormula. accept(Visitor visitor)
Accepts a formula visitorFormula
ConstantFormula. accept(Visitor visitor)
Accepts a formula visitorabstract Formula
Formula. accept(Visitor visitor)
Formula
UnaryFormula. accept(Visitor visitor)
Accepts a formula visitorFormula
And. dual()
Returns the dual of this formula (And) In general, the dual of And is represented by the following transformation: (f1 && f2) -> (!f1 || !f2)Formula
BinaryFormula. dual()
Returns the dual of this binary formula.Formula
ConstantFormula. dual()
Returns the dual of this constant formula.Formula
False. dual()
Returns the dual of this formula (False) In general, the dual of false is represented by the following transformation: !false -> trueabstract Formula
Formula. dual()
Formula
Next. dual()
Returns the dual of this formula (Next) In general, the dual of next is represented by the following transformation: !Xf -> X!fFormula
Not. dual()
Returns the dual of this formula (Not) In general, the dual of not is the dual of it's subformulaFormula
Or. dual()
Returns the dual of this formula (Or) In general, the dual of Or is represented by the following transformation: (f1 || f2) -> (!f1 && !f2)Formula
True. dual()
Returns the dual of this formula (True) In general, the dual of true is represented by the following transformation: !true -> falseFormula
UnaryFormula. dual()
Formula
Until. dual()
Returns the dual of this formula (Until) In general, the dual of until is represented by the following transformation: !(f1 U f2) -> ((f1 && !f2) W (!f1 && !f2))Formula
WeakUntil. dual()
Returns the dual of this formula (Weak Until) In general, the dual of weak until is represented by the following transformation: !(f1 W f2) -> ((f1 && !f2) U (!f1 && !f2))Formula
UnaryFormula. getFormula()
Gets the subformula of this unary formulaFormula
BinaryFormula. getLeft()
Gets the left subformula of this binary formulaFormula
BinaryFormula. getRight()
Gets the right subformula of this binary formulaMethods in ltl with parameters of type Formula Modifier and Type Method Description void
UnaryFormula. setFormula(Formula formula)
Sets the subformula of this unary formulavoid
BinaryFormula. setLeft(Formula left)
Sets the left subformula of this binary formulavoid
BinaryFormula. setRight(Formula right)
Sets the left subformula of this binary formulaConstructors in ltl with parameters of type Formula Constructor Description And(Formula left, Formula right)
Initializes this LTL formula as the conjunction (and) of the given left and right subformulas.Next(Formula formula)
Initializes this LTL formula as the next of the given formula.Not(Formula formula)
Initializes this LTL formula as the negation of the given formula.Or(Formula left, Formula right)
Initializes this LTL formula as the disjunction (or) of the given left and right subformulas.Until(Formula left, Formula right)
Initializes this LTL formula as the until of the given left and right subformulas.WeakUntil(Formula left, Formula right)
Initializes this LTL formula as the weak until of the given left and right subformulas. -
Uses of Formula in v
Methods in v that return Formula Modifier and Type Method Description Formula
FormulaVisitor. visit(BinaryFormula binaryFormula)
Visits a Binary LTL formula Firstly, the left and right subformulas are visited and then on the traversal back up a new Formula is generated consisting of the type of Binary formula this formula is and it's left and right subformulasFormula
FormulaVisitor. visit(ConstantFormula constantFormula)
Visits a constant LTL formula Generally, a constant is a leaf in an expression tree and this signifies the end of a particular branch of the formula.Formula
FormulaVisitor. visit(Formula formula)
Visits a generic LTL formulaFormula
FormulaVisitor. visit(UnaryFormula unaryFormula)
Visits a unary LTL formula Firstly, it is determined whether the unary formula is of type Not and if so, distributes the Not into the subformula by applying the correct dual transformation.Formula
Visitor. visit(BinaryFormula binaryFormula)
Visits a generic binary LTL formulaFormula
Visitor. visit(ConstantFormula constantFormula)
Visits a generic constant LTL formulaFormula
Visitor. visit(Formula formula)
Visits a generic LTL formulaFormula
Visitor. visit(UnaryFormula unaryFormula)
Visits a generic unary LTL formula


AWS::Lambda::Version
The AWS::Lambda::Version
resource publishes a specified version of an AWS Lambda (Lambda) function. When publishing
a new version of your function, Lambda copies the latest version of your function.
For more information, see Introduction to AWS Lambda Versioning in the AWS Lambda Developer Guide.
Topics
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::Lambda::Version", "Properties" : { "CodeSha256" :
String
, "Description" :String
, "FunctionName" :String
} }
YAML
Type: AWS::Lambda::Version Properties: CodeSha256 :
String
Description :String
FunctionName :String
Properties
CodeSha256
-
The SHA-256 hash of the deployment package that you want to publish. This value must match the SHA-256 hash of the
$LATEST
version of the function. Specify this property to validate that you are publishing the correct package.Required: No
Type: String
Update requires: Updates are not supported.
Description
-
A description of the version you are publishing. If you don't specify a value, Lambda copies the description from the
$LATEST
version of the function.Required: No
Type: String
Update requires: Updates are not supported.
FunctionName
-
The Lambda function for which you want to publish a version. You can specify the function's name or its Amazon Resource Name (ARN).
Required: Yes
Type: String
Update requires: Replacement
Return Values
Ref
When the logical ID of this resource is provided to the Ref
intrinsic function, Ref
returns the ARN of the Lambda version, such as arn:aws:lambda:us-west-2:123456789012:function:helloworld:1
.
For more information about using the Ref
function, see Ref.
Fn::GetAtt
Fn::GetAtt
returns a value for a specified attribute of the specified resource type.
Version
-
The published version of a Lambda version, such as
1
.
For more information about using Fn::GetAtt
, see Fn::GetAtt.
Example
The following example publishes a new version of the MyFunction
Lambda function.
JSON
"TestingNewFeature" : { "Type" : "AWS::Lambda::Version", "Properties" : { "FunctionName" : { "Ref" : "MyFunction" }, "Description" : "A test version of MyFunction" } }
YAML
TestingNewFeature: Type: AWS::Lambda::Version Properties: FunctionName: Ref: "MyFunction" Description: "A test version of MyFunction"


A self-motivated and responsible individual, possessing well-honed skills of languages and development tools, seeking a position in a growth-oriented company where I can dedicate my knowledge to the advantage of the company, as well as exercising self-discipline to aid my personal growth. Furthermore, with M.E. in Computer Engineering, I will contribute my skills in researching and analyzing cutting-edge technologies to the advancement of the company and its goals.
Coursework: Introduction to Computing, Algorithms, Flow Charts and Problem Solving, Java (Introduction to Object Oriented Programming), Android App Development, Swift Programming (Algorithms & Data Structures), Objective-C Programming, iOS Application Development
Preliminary research for User-centric MIMO (multi-input & multi-output) Human-Computer Interface project.
Designed the experiment for recognizing conscious/unconscious user's intent.
Extracted electroencephalogram data and analyzed the results by Support Vector Machine.
Developed indoor and outdoor guidance system for visually impaired persons.
[The indoor system] Developed by detecting markers and lines using Hough Transform algorithm and template matching.
[The outdoor system] Estimated user's position by Zigbee RSSI using trilateration and guided directions
by predefined scenarios from a guidance planning program.
Implemented the engine to recognize Korean ID and Driver's license to conceal personal information.
Discriminated private forms from degraded images, such as transferred by fax,
by noise filtering, K-means clustering and NCC template matching.
Researched on a quantificational algorithm of Visually Induced Motion Sickness factors.
Designed and experimented to obtain a correlation between the factors and the reaction of test subjects.
Implemented tools for creating unstable videos from monotonous movies or text images by optical flow features from hand-held videos.
Implemented the object recognition engine using Speeded Up Robust Features.
Enhanced performance by RANSAC to eliminate outliers and Kalman filter to tracking objects.


{% extends "horizon/common/_modal_form.html" %} {% load i18n %} {% load static %} {% block form_id %}import_bundle{% endblock %} {% block form_action %}{% url 'horizon:app-catalog:packages:import_bundle' %}{% endblock %} {% block modal_id %}upload_bundle_modal{% endblock %} {% block modal-header %}{% trans 'Import Bundle' %}{% endblock %} {% block modal-body %}
{% trans "Bundle Name" %}: {% trans "Bundle's full name."%}
{% blocktrans trimmed %}The bundle is going to be installed from {{murano_repo_url}} repository.{% endblocktrans %}
{% trans "Bundle URL" %}: {% trans "HTTP/HTTPS URL of the bundle file."%}
{% trans "Note" %}: {% trans "You'll have to configure each package installed from this bundle separately." %}
{% trans "If packages depend upon other packages and/or require specific glance images, those are going to be installed with them from murano repository." %}


Contract
| Vendor Name | ALTIS HUMAN RESOURCES (OTTAWA) |
|---|---|
| Description of Work | ATIP Analyst Temporary Help |
| Comments | ATIP Analyst Temporary Help. This contract includes an amendment in the amount of $45,703.56 which extends the contract until February 24, 2017, bringing the total contract value to $86,233.13. This competitive contract was awarded under a Public Services and Procurement Canada (PSPC) supply arrangement. |
| Reference Number | 4507274 |
| Contract Date | 2016-12-02 |
| Contract Period | 2016-09-27 to 2017-02-24 |
| Contract Value | $ 45,703.56 |
* Use either Contract Period or Delivery Date.


+++ title = "AWS Copilot CLI" linkTitle = "AWS Copilot CLI" +++
Develop, release, and operate containerized applications on Amazon ECS and AWS Fargate.
}}"> Learn More }}"> DownloadModel and provision application architectures from a Dockerfile.
Run $ copilot init
to setup a Load Balanced Web Service or Backend Service.
Create and deploy to multiple environments with a CI/CD pipeline.
Run $ copilot env init
to create new environments and $ copilot pipeline init
to setup a pipeline.
Monitor the health of your services without leaving the terminal.
Run $ copilot svc status
to check your service's status.


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This is summary of goals, actions and ideas added by you and your achievement rate.
The last 3 goals added in application or those with nearest deadline.


I make things work on front and back-end. I am passionate about web-development and coding in general. I have been interested in programming since I was 14. I have used different programming languages for my projects. I code web-apps most of my spare time.


Gateway
BOT
13-Aug-18 07:52 PM
[dscrdeql] <NWhiskeyTango> Can i ask a sincere question?
[dscrdeql] <Llama-Admin> yes
(edited)
[dscrdeql] <NWhiskeyTango> Would a pool for mining EQLI be a positive thing for the project?
[dscrdeql] <Llama-Admin> I don't know how that would affect it. The mining reward is super small, and we are implementing masternodes soon.
[dscrdeql] <NWhiskeyTango> True. I mean a pool won't take over the network with dPOW. I am just trying to figure what the positives would be and I find none
[dscrdeql] <NWhiskeyTango> Things i see...
[dscrdeql] <NWhiskeyTango> -pool would have a "fee"
[dscrdeql] <NWhiskeyTango> -pool would earn most of the block rewards
[dscrdeql] <NWhiskeyTango> - people would spend more on electricity trying to fight for the highest share % on pool
[dscrdeql] <NWhiskeyTango> -other "solo" miners would be EVEN less "profitable"
[dscrdeql] <Biomech-Founder> the block reward, currently, is .0001 EQL per block. This is going to go away. It was an error in the code. We MIGHT keep it, but probably not. By running a full node with gen=true in your EQL.conf, you ARE mining and you will get the transaction fees.
[dscrdeql] <Biomech-Founder> In our design, we deliberately wanted to avoid the problems associated with pools.
[dscrdeql] <Biomech-Founder> You can set one up, easily, but it's not going to be profitable, unless you and your friends wanted to form a private one to pool cheap hardware. Even then, I don't see it being worthwhile.
[dscrdeql] <Biomech-Founder> I could be wrong, as things progress, but I'm thinking smart contracts will be where the profit lies
[dscrdeql] <NWhiskeyTango> With all these facts i just see it hurting to have a pool more then helping. Do you all agree?
[dscrdeql] <Biomech-Founder> Yeah. I see exactly one exception, and it's only personal use.
[dscrdeql] <Biomech-Founder> If you got a bunch of computers or old equipment that can mine, making your own pool might help your chances of processing transactions.
[dscrdeql] <Biomech-Founder> But outside of that, I really don't see a use case. Especially for a public pool.
[dscrdeql] <Biomech-Founder> I've run several pools. Hell, I'm running one now But I don't see the point for this one.
[dscrdeql] <Catalyst> hey everyone
[dscrdeql] <c2k> hi @Catalyst
[dscrdeql] <Catalyst> Yo surprised Hilary
[dscrdeql] <Jellysmash> Hi @Faisal
[dscrdeql] <Catalyst> hey Jelly
[dscrdeql] <Jellysmash> EQLI price is holding nicely...
[dscrdeql] <Jellysmash> I kinda miss the dumper now I'd like to buy more cheap EQLI
[dscrdeql] <Jellysmash> Haha...that's some cool jelly
[dscrdeql] <Biomech-Founder> yeah, got a few more people interested Good support starting to build. Dumper is still there, he's just contained
[dscrdeql] <Biomech-Founder> Next major goal, 100 satoshis.
[dscrdeql] <Jellysmash> He must be doing smaller dumps
[dscrdeql] <Biomech-Founder> yup.
[dscrdeql] <Biomech-Founder> He tried earlier today, and got shot down. Got bought out every time he lowballed, and it went back up higher, and with higher buy support. and this time, I didn't do it
[dscrdeql] <Jellysmash> Haven't noticed him the last day or so....looks like no one wants to sell under 10sats since Saturday
[dscrdeql] <Biomech-Founder>
[dscrdeql] <Biomech-Founder> Wouldn't be any buy support there or anything...
[dscrdeql] <Jellysmash> @Biomech I was wondering if you were buying up all those low sell orders about a week ago...
[dscrdeql] <Jellysmash> It pushed the price up a lot
[dscrdeql] <Biomech-Founder> Not all of 'em. Didn't have the money.
[dscrdeql] <Biomech-Founder> But some of 'em.
[dscrdeql] <Biomech-Founder> I been fightin' this son of a bitch hard.
[dscrdeql] <c2k> if he does have more, wondering if he knows we are all waiting for below 10sats to buy 7figs therefore hes tryig to be higher
[dscrdeql] <Biomech-Founder> I can't take him out all at once, but I can do the death of a thousand cuts.
[dscrdeql] <Jellysmash> I thought it was going to keep going up and bought at 46 sats...urrgh
[dscrdeql] <Biomech-Founder> probably
[dscrdeql] <Jellysmash> @c2k Haha...that's me...waiting below 10 sats...just on case
[dscrdeql] <c2k> ive been there too
[dscrdeql] <c2k> he must sense some big size waiting
[dscrdeql] <Biomech-Founder> I got peeps helping. I wouldn't try for below 10 sats too hard at this point.
[dscrdeql] <Biomech-Founder> Never hurts to have a low ball order in though. Just in case...
[dscrdeql] <Jellysmash> Yes that's what it's looking like
[dscrdeql] <c2k> im not really trying. bag already big. but if he gets stupid im willing to clean him out
[dscrdeql] <Biomech-Founder>
[dscrdeql] <Jellysmash> Same...my bag is big-ish....but I don't want to miss out on a good opportunity
[dscrdeql] <c2k> for sure
[dscrdeql] <Biomech-Founder> I just want to get it back to the low end of the dICO price. If you guys make a killing on the way, all the better
[dscrdeql] <Biomech-Founder> Nothing like a bonus to keep people interested.
[dscrdeql] <c2k> absolutely. that would be nice. also would be nice to buy a dome home with some of my bag
[dscrdeql] <c2k> nice plot in PR
[dscrdeql] <c2k> no federal taxes
[dscrdeql] <c2k> you know...good stuff
[dscrdeql] <Llama-Admin> If i get a dome I'm renting it out until i need a house
[dscrdeql] <Llama-Admin> if possible lol
[dscrdeql] <Biomech-Founder> If we're half as successful as we're aiming for, and caught the low end of the dumps... you might be sitting on a resort
[dscrdeql] <Llama-Admin> better get back to PR
[dscrdeql] <c2k> ha, sounds like a nice plan. ive been to some half deserted islands in the bahamas that would be a nice place to lay down a resort
[dscrdeql] <c2k> what are your thoughts on PR @Llama-Admin ?
[dscrdeql] <Biomech-Founder> I'd like to build on an uninhabited island in the future. Planned community, fully self sustaining
[dscrdeql] <Biomech-Founder> But that's down the road a ways.
[dscrdeql] <Llama-Admin> we should get some houses down
[dscrdeql] <Biomech-Founder> Yeah, we got to get one or two up, approved, and where everyone can see and touch them. From there, there's no stopping us
[dscrdeql] <Biomech-Founder> If Barterdex and the market had cooperated, we'd already be there. But, ambitious projects always get derailed. The only think we didn't seriously expect was homey the dumper. And he's an irritant. We're just delayed a bit.  Probably pretty wealthy out of it, damn it, but done.
[dscrdeql] <Biomech-Founder> I basically see the scenarios playing out like this:
[dscrdeql] <Biomech-Founder> One, prices stay low for a while. We build small, get interest up, it takes a while, but we get it rolling.
[dscrdeql] <Biomech-Founder> two, he gets stuffed, gives up, or gets eaten by a whale. Time is shortened.
[dscrdeql] <Biomech-Founder> Three, (and this is in the works) we get listed on a couple more exchanges. Homey can't crash most of 'em to the insane lows because unlike exrates, most exchanges have limits on the lower size of orders. He has to play in his sandbox, and become irrelevant.  Don't care if it's him or somebody(ies) else.
[dscrdeql] <Biomech-Founder> Which reminds me, I need to see if they got komodo ocean up to the current standard yet Also, the issues with the electrum servers have been solved. I'd like to claim full credit for that....
[dscrdeql] <Biomech-Founder> But since I'm not a liar, it was Siu at chainmakers.
[dscrdeql] <Biomech-Founder> And I was the cause of the error, dammit.
[dscrdeql] <Biomech-Founder> Missed a configuration setting on the update, and screwed up one of them real bad.
[dscrdeql] <Biomech-Founder> Luckily, Chainmakers are badasses, and they got it sorted quick. Any of you guys considering a crypto project, go there
[dscrdeql] <Biomech-Founder> We got massive value out of what we paid. They're seriously good people to work with for development.


On the campaign trail on Thursday
Labour will launch its manifesto while the PM is heading to Bedfordshire.
Labour is set to unveil its manifesto on Thursday – hailed by Jeremy Corbyn as the most radical in the UK’s history.
The party leader will visit Birmingham in the morning, where he will tell supporters that the “manifesto of hope” for the December 12 election is full of policies “that the political establishment has blocked for a generation”.
The proposals are expected to include renationalisation plans for key utilities, following a pledge to take part of BT into public ownership to deliver free full-fibre broadband for all, as well as promises to significantly boost NHS spending, create a £10 minimum hourly wage for all and tackle climate change and create jobs in a “green industrial revolution”.
It comes after the Liberal Democrats revealed details of their manifesto, entitled Stop Brexit, Build A Brighter Future, on Wednesday.
Also on Thursday, Prime Minister Boris Johnson is expected to continue his campaigning in the Bedfordshire area.
The Conservatives have yet to officially unveil their manifesto, but Mr Johnson said on Wednesday that it would include a commitment to raise the threshold at which workers start paying National Insurance contributions (NICs) from £8,628 a year to £9,500 – eventually rising to £12,500.
The party will on Thursday divulge plans to build one million extra homes over the next five years, as well as outline measures to make it easier for renters to buy, while providing more security for the 4.5 million people in the private rented market.
Elsewhere, Scottish Greens co-leader Patrick Harvie is due to join Edinburgh West candidate Elaine Gunn for a bike ride, before talking about the party’s policies to radically transform Scotland’s transport network.
There is currently nothing scheduled on Thursday for the Liberal Democrats, SNP or the Brexit Party.


| Table 1 |
Statistics of climate variables used for GCM performance ass ... |
| Table 2 |
Changes of the mean annual precipitation and air temperature ... |
| Table 3 |
Decadal changes of the maize yield in the Gaotai area under ... |
| Table 4 |
Decadal changes of the maize CWC in the Gaotai area under th ... |
| Table 5 |
Decadal changes of the maize yield in the Ganzhou area under ... |
| Table 6 |
Decadal changes of the maize CWC in the Ganzhou area under t ... |


Meeting Attendance
Attendance Sheet Legend
| Absent | Attended | Participant Type |
|---|---|---|
| Face-to-Face | ||
| Online | ||
| Waitlisted |
There are no past attendance sheets for you to view and no open attendance sheets.
Please note that attendance sheets for a meeting are only opened the day of the meeting.


Hi, my name is Homam Almofty and this is my first website created using Django. The website simply counts the words for whatever you put inside the box and then it tells you the most repeated words in the text.
Copyright 2021


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FF Match
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Contributing to Appium
There are a lot of different ways to contribute to Appium. See below for everything you can do and the processes to follow for each contribution method. Note that no matter how you contribute, your participation is governed by our Code of Conduct.
Make changes to the Appium code or docs
Fork the project, make a change, and send a pull request! Please have a look at our Style Guide before getting to work. Please make sure the unit and functional tests pass before sending a pull request; for more information on how to run tests, keep reading!
Make sure you read and follow the setup instructions in the README first. And note that all participation in the Appium community (including code submissions) is governed by our Code of Conduct. Then, have a look at our running from source doc for more information on how to get set up to run tests and start slinging code.
You will probably also want to have a look at this more in-depth Developer’s Overview of the Appium project, how Appium is architected, how to make changes to modules, and so on.
Finally, before we accept your code, you will need to have signed our Contributor License Agreement.
Become an Appium Triager
You can help us manage our issue tracker! All you need is enough familiarity with Appium to try and reproduce bugs. We triage issues by having conversations with the issue creator and then either closing the issue or moving it into the Bugs or Features milestone. We use these buckets as the backlogs for our upcoming releases.
We use this “algorithm” for triaging issues, which anyone can jump in and follow:
- If issue is a feature request, discuss amongst Appium devs.
- If we decide to build it, add to the Features milestone.
- If we decide not to build it, just close.
- If issue is a bug report, attempt to verify
- If it’s a duplicate, close with link to bug already reported.
- If it ultimately can’t be verified, close until we have enough information to verify (e.g., in most cases we need a full set of Appium logs to help diagnose an issue).
- If the user hasn’t provided enough information, keep asking for enough information to verify.
- If it’s a verified new bug, add it to the Bugs milestone.
- If we have been waiting for a reply from the user for over 3 weeks, close.
If you’re interested in joining our triage rotation, contact @jlipps or @imurchie.
Help out on our forums
We can always use help on our forums at discuss.appium.io! Hop on over and see if there are any questions that you can answer.
Submit bug reports or feature requests
Just use the GitHub issue tracker to submit your bug reports and feature requests. If you are submitting a bug report, please follow the issue template.


{% extends 'indexbase.html' %} {% load staticfiles %} {% block content %}
The Student Welfare Division at BITS Pilani, K.K. Birla Goa Campus shall
always strive to provide the most conducive environment to bring out the best out of every student. It is our
endeavor to do anything and everything possible to make the student's stay in the campus the most memorable
one.
Our division cares for every student and shall always look into their needs that may arise from time to time.


Geospecific Network Information for Spatial Analytic (GeISA) is an integrated web application for reporting, visualizing, and monitoring KPI achievement for Network Directorate in Telkomsel. Current project has been successfully delivering valuable information to support monitoring of Network KPI achievement. Based on further review and evaluation of this application, there are several capabilities that should be embedded to this application.
GeISA is now used by many entities in Telkomsel, with main Objective such as :
As an integrated web application for reporting, visualizing, and monitoring KPI achievement for network directorate in Telkomsel. There are 5 Main Features on GeISA
Data source of GeISA is consist of 5 important elements such as Network OSS for network traffic, utililzation, and performance, Teradata for revenue, Lacima for BTS coordinates, Planet for BTS beamwidth and azimuth, Bakosurtanal for border map in any geographical levels, and Marketing data for recharge share and sales share. Those whole data are compiled using cron job with ETL process and stored in the database automatically. Finally, all necessary information from database are presented in both map-based application and dashboard one.


|
PortAudio
2.0
|
PortAudio V19 adds a huge advance over previous versions with a feature called Blocking I/O. Although it may have lower performance that the callback method described earlier in this tutorial, blocking I/O is easier to understand and is, in some cases, more compatible with third party systems than the callback method. Most people starting audio programming also find Blocking I/O easier to learn.
Blocking I/O works in much the same way as the callback method except that instead of providing a function to provide (or consume) audio data, you must feed data to (or consume data from) PortAudio at regular intervals, usually inside a loop. The example below, excepted from patest_read_write_wire.c, shows how to open the default device, and pass data from its input to its output for a set period of time. Note that we use the default high latency values to help avoid underruns since we are usually reading and writing audio data from a relatively low priority thread, and there is usually extra buffering required to make blocking I/O work.
Note that not all API's implement Blocking I/O at this point, so for maximum portability or performance, you'll still want to use callbacks.
Previous: Enumerating and Querying PortAudio Devices | Next: Exploring PortAudio


--- layout: example.html title: Draw Features shortdesc: Example of using the ol.interaction.Draw interaction. docs: > Example of using the Draw interaction. Select a geometry type from the dropdown above to start drawing. To finish drawing, click the last point. To activate freehand drawing for lines and polygons, hold the `Shift` key. Square drawing is achieved by using Circle mode with a `geometryFunction` that creates a 4-sided regular polygon instead of a circle. Box drawing uses a custom `geometryFunction` that takes start and end point of a line with 2 points and creates a rectangular box. tags: "draw, edit, freehand, vector" ---


Martell, Helvetia. "About the Bibliography." Hispanic Periodicals in the United States: Origins to 1960 A Brief History and Comprehensive Bibliography. Eds. Nicolás Kanellos and Helvetia Martell, Arte Público Press, 2000, pp. 137-8.
Objectives
Identifying, locating, and making accessible the publications of a people whose intellectual production was ignored by most institutions responsible for bibliographic control (publication, preservation, and access) are very large and at times frustrating tasks. Nevertheless, we took on the compilation of this bibliography as part of Recovering the US Hispanic Literary Heritage to support reconstituting the documentary legacy of Hispanics in the United States. The present bibliography offers a list of periodical publications whose pages have survived in some form, or whose existence is remembered only through bibliographic documentation, because to date no vestiges of the original serial have been recovered.
Our list contains some 1,700 records, of which only some 900 titles are accessible in one form or another. All of those serials that are missing bear the annotation "No extant issues located." [...]
The criteria used for inclusion of records in this list were: (1) all known serials published in the Spanish language in the United States; and (2) all known serials published in the United States, whether English or bilingually (Spanish-English), that were produced by or that served US Hispanic communities.
Sources
The titles included were located in various electronic and print sources, as well as through direct contact with individuals and by research in various institutions. In some cases, the Recovery Program itself discovered the serials, microfilmed them, and is now making them universally accessible for the first time since the publications' demise. The electronic sources most relied upon were the public catalogs of the Library of Congress (LOCIS-LOC), WorldCat (the OCLC Online Union Catalog), and catalogs of individual libraries....For any title that can be found only in print catalogs, and for which we found no repository, we have reproduced the catalog entry as cited in the particular source....[See Repositories section below for more information.]
Bibliographic Information
Each entry contains information on the title, place of publication, publisher, and dates of publication. When these data do not appear in the serial itself, external sources have been used to provide the information. Because not all of the issues of these publications have survived, and because even the publications often do not provide clear bibliographic information, determining actual dates of origin and demise has been an arduous task. When the dates cannot be verifies, we substitute for the missing dates a lower-case "u".... Any approximate date offered is always accompanied by a question mark: "(?)." A dash immediately after the beginning date indicates that the serial is still publishing, or that we do not know of its demise. ....
Our bibliography does not pretend to be exhaustive, nor is it definitive. We hope that by making the results of our reserach available, other titles not on our list will surface, and that some of our "non-extant" titles will also come to light. We invite our readers to provide us with additional information, sources, and titles.
The map visualization on this site was created using Leaflet, with the Google Sheets template created by Ilya Ilyankou and Jack Dougherty, included in the book Data Visualization for All (https://datavizforall.org/). Coordinates were automatically generated using Google geocoder using the city and state for each periodical. Thumbnail images were produced from the image of the first page of extant periodicals. In the case of non-extant periodicals, a placeholder appears that indicates that there is no image available.
Many of the periodicals included in this project are available in our databases available through Newsbank-Readex and EBSCO.
Dataset
View the periodicals dataset on Google Docs by clicking here. If you use this dataset, please cite Recovering the US Hispanic Literary Heritage.
The newspaper titles included in this map can be found in various repositories, including Recovering the US Hispanic Literary Heritage's databases (listed below), in-house microfilm collections and in the University of Houston's Special Collections. Please verify with the listed repository regarding which newspaper(s) they hold in their collections. Collection and repository details are also available on WorldCat.
Newsbank-Readex
Hispanic American Newspapers (1808-1980) contains the single largest compilation of Spanish-language newspapers printed in the United States during the 19th and 20th centuries. This distinctive collection features hundreds of titles, including many published bilingually in Spanish and English. This collection draws from archival work done at Recovering the US Hispanic Literary Heritage. For more information, visit www.readex.com.
EBSCO
Arte Público Press Historical Collection: Series 1 is an archive of publications focused exclusively on US Hispanic history, literature and culture from colonial times until 1960. This series focuses on the creative life of US Latinos and Hispanics. Context is written, indexed and searchable in Spanish and English. For more information, visit www.ebscohost.com.
Alabama
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
New Hampshire
New Jersey
New Mexico
New York
Nevada
North Carolina
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Texas
Tennessee
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
D.C.
Puerto Rico
Australia
Canada
Chile
Colombia
France
Germany
Israel
Netherlands
Mexico
New Zealand
Peru
Philippines
Spain
South Africa
Switzerland
Taipei
United Kingdom


dials.index¶
Introduction¶
This program attempts to perform autoindexing on strong spots output by the program dials.find_spots. The program is called with a “datablock.json” file (as generated by dials.import) and a “strong.pickle” file (as generated by dials.find_spots). If one or more lattices are identified given the input list of strong spots, then the crystal orientation and experimental geometry are refined to minimise the differences between the observed and predicted spot centroids. The program will output an “experiments.json” file which is similar to the input “datablock.json” file, but with the addition of the crystal model(s), and an “indexed.pickle” file which is similar to the input “strong.pickle” file, but with the addition of miller indices and predicted spot centroids.
dials.index provides both one-dimensional and three-dimensional fast Fourier transform (FFT) based methods. These can be chosen by setting the parameters indexing.method=fft1d or indexing.method=fft3d. By default the program searches for a primitive lattice, and then proceeds with refinement in space group P1. If the unit_cell and space_group parameters are set, then the program will only accept solutions which are consistent with these parameters. Space group constraints will be enforced in refinement as appropriate.
Examples:
dials.index datablock.json strong.pickle
dials.index datablock.json strong.pickle unit_cell=37,79,79,90,90,90 space_group=P43212
dials.index datablock.json strong.pickle indexing.method=fft1d
Basic parameters¶
indexing { nproc = 1 fft3d { reciprocal_space_grid { d_min = Auto } } scan_range = None known_symmetry { space_group = None unit_cell = None } index_assignment { simple { hkl_tolerance = 0.3 } } check_misindexing { grid_search_scope = 0 } refinement_protocol { n_macro_cycles = Auto d_min_step = Auto d_min_start = None d_min_final = None verbosity = 1 } method = *fft3d fft1d real_space_grid_search stills { ewald_proximity_resolution_cutoff = 2.0 refine_all_candidates = True rmsd_min_px = 2 ewald_proximal_volume_max = 0.0025 isoforms { name = None cell = None lookup_symbol = None rmsd_target_mm = None beam_restraint = None } } } refinement { verbosity = 0 parameterisation { auto_reduction { min_nref_per_parameter = 5 action = *fail fix remove } scan_varying = False beam { fix = all *in_spindle_plane out_spindle_plane *wavelength } crystal { fix = all cell orientation } detector { fix = all position orientation } goniometer { fix = *all in_beam_plane out_beam_plane } } reflections { reflections_per_degree = 100 minimum_sample_size = 1000 maximum_sample_size = None outlier { algorithm = null *auto mcd tukey sauter_poon minimum_number_of_reflections = 20 separate_experiments = True separate_panels = Auto separate_blocks = True block_width = Auto } } } output { experiments = experiments.json split_experiments = False reflections = indexed.pickle unindexed_reflections = None log = dials.index.log debug_log = dials.index.debug.log } verbosity = 1
Full parameter definitions¶
indexing { nproc = 1 .help = "The number of processes to use." .type = int(value_min=1) mm_search_scope = 4.0 .help = "Global radius of origin offset search." .type = float(value_min=0) .expert_level = 1 wide_search_binning = 2 .help = "Modify the coarseness of the wide grid search for the beam" "centre." .type = float(value_min=0) .expert_level = 1 min_cell_volume = 25 .help = "Minimum unit cell volume (in Angstrom^3)." .type = float(value_min=0) .expert_level = 1 min_cell = 3 .help = "Minimum length of candidate unit cell basis vectors (in" "Angstrom)." .type = float(value_min=0) .expert_level = 1 max_cell = Auto .help = "Maximum length of candidate unit cell basis vectors (in" "Angstrom)." .type = float(value_min=0) .expert_level = 1 max_cell_estimation .expert_level = 1 { filter_ice = True .help = "Filter out reflections at typical ice ring resolutions before" "max_cell estimation." .type = bool filter_overlaps = True .help = "Filter out reflections with overlapping bounding boxes before" "max_cell estimation." .type = bool overlaps_border = 0 .help = "Optionally add a border around the bounding boxes before" "finding overlaps." .type = int(value_min=0) multiplier = 1.3 .help = "Multiply the estimated maximum basis vector length by this" "value." .type = float(value_min=0) .expert_level = 2 step_size = 45 .help = "Step size, in degrees, of the blocks used to peform the" "max_cell estimation." .type = float(value_min=0) .expert_level = 2 nearest_neighbor_percentile = None .help = "Percentile of NN histogram to use for max cell determination." .type = float(value_min=0, value_max=1) .expert_level = 2 histogram_binning = linear *log .help = "Choose between linear or logarithmic bins for nearest neighbour" "histogram analysis." .type = choice nn_per_bin = 5 .help = "Target number of nearest neighbours per histogram bin." .type = int(value_min=1) max_height_fraction = 0.25 .type = float(value_min=0, value_max=1) .expert_level = 2 } fft3d { peak_search = *flood_fill clean .type = choice .expert_level = 2 peak_volume_cutoff = 0.15 .type = float .expert_level = 2 reciprocal_space_grid { n_points = 256 .type = int(value_min=0) .expert_level = 1 d_min = Auto .help = "The high resolution limit in Angstrom for spots to include in" " the initial indexing." .type = float(value_min=0) } } sigma_phi_deg = None .help = "Override the phi sigmas for refinement. Mainly intended for" "single-shot rotation images where the phi sigma is almost" "certainly incorrect." .type = float(value_min=0) .expert_level = 2 b_iso = Auto .type = float(value_min=0) .expert_level = 2 rmsd_cutoff = 15 .type = float(value_min=0) .expert_level = 1 scan_range = None .help = "The range of images to use in indexing. Number of arguments must" "be a factor of two. Specifying 0 0" will use all images" by" "default. The given range follows C conventions (e.g. j0 <= j <" "j1)." .type = ints(size=2) .multiple = True known_symmetry { space_group = None .help = "Target space group for indexing." .type = space_group unit_cell = None .help = "Target unit cell for indexing." .type = unit_cell relative_length_tolerance = 0.1 .help = "Relative tolerance for unit cell lengths in unit cell" "comparision." .type = float .expert_level = 1 absolute_angle_tolerance = 5 .help = "Angular tolerance (in degrees) in unit cell comparison." .type = float .expert_level = 1 max_delta = 5 .help = "Maximum allowed Le Page delta used in searching for basis" "vector combinations that are consistent with the given" "symmetry." .type = float(value_min=0) .expert_level = 1 } basis_vector_combinations .expert_level = 1 { max_combinations = None .help = "Maximum number of basis vector combinations to test for" "agreement with input symmetry." .type = int(value_min=1) max_refine = Auto .help = "Maximum number of putative crystal models to test. Default for" "rotation sweeps: 50, for still images: 5" .type = int(value_min=1) .expert_level = 1 sys_absent_threshold = 0.9 .type = float(value_min=0, value_max=1) solution_scorer = filter *weighted .type = choice .expert_level = 1 filter .expert_level = 1 { check_doubled_cell = True .type = bool likelihood_cutoff = 0.8 .type = float(value_min=0, value_max=1) volume_cutoff = 1.25 .type = float(value_min=1) n_indexed_cutoff = 0.9 .type = float(value_min=0, value_max=1) } weighted .expert_level = 1 { power = 1 .type = int(value_min=1) volume_weight = 1 .type = float(value_min=0) n_indexed_weight = 1 .type = float(value_min=0) rmsd_weight = 1 .type = float(value_min=0) } } index_assignment { method = *simple local .help = "Choose between simple 'global' index assignment and xds-style " "'local' index assignment." .type = choice .expert_level = 1 simple { hkl_tolerance = 0.3 .help = "Maximum allowable deviation from integer-ness for assigning " "a miller index to a reciprocal lattice vector." .type = float(value_min=0, value_max=0.5) } local .expert_level = 1 { epsilon = 0.05 .help = "This corresponds to the xds parameter INDEX_ERROR=" .type = float delta = 8 .help = "This corresponds to the xds parameter INDEX_MAGNITUDE=" .type = int l_min = 0.8 .help = "This corresponds to the xds parameter INDEX_QUALITY=" .type = float nearest_neighbours = 20 .type = int(value_min=1) } } check_misindexing { grid_search_scope = 0 .help = "Search scope for testing misindexing on h, k, l." .type = int } optimise_initial_basis_vectors = False .type = bool .expert_level = 2 debug = False .type = bool .expert_level = 1 debug_plots = False .help = "Requires matplotlib" .type = bool .expert_level = 1 combine_scans = False .type = bool .expert_level = 1 refinement_protocol { mode = *refine_shells repredict_only .help = "refine_shells: refine in increasing resolution cutoffs after" "indexing. repredict_only: do not refine after indexing, just" "update spot predictions." .type = choice .expert_level = 1 n_macro_cycles = Auto .type = int(value_min=1) d_min_step = Auto .help = "Reduction per step in d_min for reflections to include in" "refinement." .type = float(value_min=0) d_min_start = None .type = float(value_min=0) d_min_final = None .help = "Do not ever include reflections below this value in refinement." .type = float(value_min=0) verbosity = 1 .type = int(value_min=0) disable_unit_cell_volume_sanity_check = False .help = "Disable sanity check on unrealistic increases in unit cell" "volume during refinement." .type = bool .expert_level = 1 } method = *fft3d fft1d real_space_grid_search .type = choice multiple_lattice_search .expert_level = 1 { cluster_analysis_search = False .help = "Perform cluster analysis search for multiple lattices." .type = bool recycle_unindexed_reflections_cutoff = 0.1 .help = "Attempt another cycle of indexing on the unindexed reflections " "if more than the fraction of input reflections are unindexed." .type = float(value_min=0, value_max=1) minimum_angular_separation = 5 .help = "The minimum angular separation (in degrees) between two" "lattices." .type = float(value_min=0) max_lattices = 1 .type = int cluster_analysis { method = *dbscan hcluster .type = choice hcluster { linkage { method = *ward .type = choice metric = *euclidean .type = choice } cutoff = 15 .type = float(value_min=0) cutoff_criterion = *distance inconsistent .type = choice } dbscan { eps = 0.05 .type = float(value_min=0) min_samples = 30 .type = int(value_min=1) } min_cluster_size = 20 .type = int(value_min=0) intersection_union_ratio_cutoff = 0.4 .type = float(value_min=0, value_max=1) } } real_space_grid_search .expert_level = 1 { characteristic_grid = 0.02 .type = float(value_min=0) } stills { indexer = *Auto stills sweeps .help = "Use the stills or sweeps indexer. Auto: choose based on the" "input imagesets (stills or sweeps)." .type = choice .expert_level = 1 ewald_proximity_resolution_cutoff = 2.0 .help = "the acceptable volume of reciprocal space for spot prediction" .type = float refine_all_candidates = True .help = "If False, no attempt is made to refine the model from initial" "basis vector selection. The indexing solution with the best" "RMSD is chosen." .type = bool candidate_outlier_rejection = True .help = "If True, while refining candiate basis solutions, also apply" "Sauter/ Poon (2010) outlier rejection" .type = bool .expert_level = 1 refine_candidates_with_known_symmetry = False .help = "If False, when choosing the best set of candidate basis" "solutions, refine the candidates in the P1 setting. If True," "after indexing in P1, convert the candidates to the known" "symmetry and apply the corresponding change of basis to the" "indexed reflections." .type = bool .expert_level = 2 rmsd_min_px = 2 .help = "Minimum acceptable RMSD for choosing candidate basis solutions" "(in pixels)" .type = float ewald_proximal_volume_max = 0.0025 .help = "Maximum acceptable ewald proximal volume when choosing" "candidate basis solutions" .type = float isoforms .help = "Constrain the unit cell to specific values during refinement" "after initial indexing." .multiple = True { name = None .type = str cell = None .type = unit_cell lookup_symbol = None .help = "The sgtbx lookup symbol of the reflections pointgroup" .type = str rmsd_target_mm = None .help = "Maximum acceptable DIALS positional rmsd, in mm" .type = float beam_restraint = None .help = "to assure that no images are accepted where the lattice is" "misindexed by a unit shift." .type = floats(size=2) } } } refinement .help = "Parameters to configure the refinement" { mp .expert_level = 2 { nproc = 1 .help = "The number of processes to use. Not all choices of refinement" "engine support nproc > 1. Where multiprocessing is possible, it" "is helpful only in certain circumstances, so this is not" "recommended for typical use." .type = int(value_min=1) } verbosity = 0 .help = "verbosity level" .type = int(value_min=0) parameterisation .help = "Parameters to control the parameterisation of experimental models" { auto_reduction .help = "determine behaviour when there are too few reflections to" "reasonably produce a full parameterisation of the experiment" "list" { min_nref_per_parameter = 5 .help = "the smallest number of reflections per parameter for a model" "parameterisation below which the parameterisation will not be" "made in full, but the action described below will be" "triggered." .type = int(value_min=1) action = *fail fix remove .help = "action to take if there are too few reflections across the" "experiments related to a particular model parameterisation." "If fail, an exception will be raised and refinement will not" "proceed. If fix, refinement will continue but with the" "parameters relating to that model remaining fixed at their" "initial values. If remove, parameters relating to that model" "will be fixed, and in addition all reflections related to" "that parameterisation will be removed. This will therefore" "remove this reflections from other parameterisations of the" "global model too. For example, if a crystal model could not" "be parameterised it will be excised completely and not" "contribute to the joint refinement of the detector and beam." "In the fix mode, reflections emanating from that crystal will" "still form residuals and will contribute to detector and beam" "refinement." .type = choice detector_reduce = False .help = "Special case designed for detector metrology refinement" "(particularly of the CSPAD). See detector_reduce_list for" "details." .type = bool .expert_level = 1 detector_reduce_list = Dist Tau2 Tau3 .help = "Partial names to match to detector parameters to try fixing." "If there are still not enough parameters for refinement after" "fixing these, then fail. This is to ensure that metrology" "refinement never completes if it is not able to refine some" "panels. The default is to try fixing the distance as well as" "Tau2 and Tau3 rotations of detector panel, leaving the" "in-plane shifts and the rotation around the detector normal" "for refinement. groups only." .type = strings .expert_level = 1 } scan_varying = False .help = "Allow models that are not forced to be static to vary during" "the scan" .type = bool compose_model_per = image *block .help = "For scan-varying parameterisations, compose a new model either" "every image or within blocks of a width specified in the" "reflections parameters. When this block width is larger than" "the image width the result is faster, with a trade-off in" "accuracy" .type = choice .expert_level = 1 debug_centroid_analysis = False .help = "Set True to write out a file containing the reflections used" "for centroid analysis for automatic setting of the " "scan-varying interval width. This can then be analysed with" "dev.dials.plot_centroid_analysis" .type = bool .expert_level = 2 beam .help = "beam parameters" { fix = all *in_spindle_plane out_spindle_plane *wavelength .help = "Whether to fix beam parameters. By default, in_spindle_plane" "is selected, and one of the two parameters is fixed. If a" "goniometer is present this leads to the beam orientation" "being restricted to a direction in the initial spindle-beam" "plane. Wavelength is also fixed by default, to allow" "refinement of the unit cell volume." .type = choice(multi=True) fix_list = None .help = "Fix specified parameters by a list of 0-based indices or" "partial names to match" .type = strings .expert_level = 1 constraints .help = "Parameter equal shift constraints to use in refinement." .multiple = True .expert_level = 2 { id = None .help = "Select only the specified experiments when looking up which" "parameterisations to apply the constraint to. If an" "identified parameterisation affects multiple experiments" "then the index of any one of those experiments suffices to" "identify that parameterisation. If None (the default) then" "constraints will be applied to all parameterisations of" "this type." .type = ints(value_min=0) parameter = None .help = "Identify which parameter of each parameterisation to" "constrain by a (partial) parameter name to match. Model" "name prefixes such as 'Detector1' will be ignored as" "parameterisations are already identified by experiment id" .type = str } force_static = True .help = "Force a static parameterisation for the beam when doing" "scan-varying refinement" .type = bool .expert_level = 1 smoother .help = "Options that affect scan-varying parameterisation" .expert_level = 1 { interval_width_degrees = 36.0 .help = "Width of scan between checkpoints in degrees. Can be set to" "Auto." .type = float(value_min=0) absolute_num_intervals = None .help = "Number of intervals between checkpoints if scan_varying" "refinement is requested. If set, this overrides" "interval_width_degrees" .type = int(value_min=1) } } crystal .help = "crystal parameters" { fix = all cell orientation .help = "Fix crystal parameters" .type = choice unit_cell .expert_level = 1 { fix_list = None .help = "Fix specified parameters by a list of 0-based indices or" "partial names to match" .type = strings .expert_level = 1 restraints .help = "Least squares unit cell restraints to use in refinement." .expert_level = 1 { tie_to_target .multiple = True { values = None .help = "Target unit cell parameters for the restraint for this" "parameterisation" .type = floats(size=6) sigmas = None .help = "The unit cell target values are associated with sigmas" "which are used to determine the weight of each" "restraint. A sigma of zero will remove the restraint at" "that position. If symmetry constrains two cell" "dimensions to be equal then only the smaller of the two" "sigmas will be kept" .type = floats(size=6, value_min=0) id = None .help = "Select only the specified experiments when looking up" "which parameterisations to apply these restraints to." "If an identified parameterisation affects multiple" "experiments then the index of any one of those" "experiments suffices to restrain that parameterisation." "If None (the default) then the restraints will be" "applied to all experiments." .type = ints(value_min=0) } tie_to_group .multiple = True { target = *mean low_memory_mean median .help = "Function to tie group parameter values to" .type = choice sigmas = None .help = "The unit cell parameters are associated with sigmas" "which are used to determine the weight of each" "restraint. A sigma of zero will remove the restraint at" "that position." .type = floats(size=6, value_min=0) id = None .help = "Select only the specified experiments when looking up" "which parameterisations to apply these restraints to." "For every parameterisation that requires a restraint at" "least one experiment index must be supplied. If None" "(the default) the restraints will be applied to all" "experiments." .type = ints(value_min=0) } } constraints .help = "Parameter equal shift constraints to use in refinement." .multiple = True .expert_level = 2 { id = None .help = "Select only the specified experiments when looking up" "which parameterisations to apply the constraint to. If an" "identified parameterisation affects multiple experiments" "then the index of any one of those experiments suffices" "to identify that parameterisation. If None (the default)" "then constraints will be applied to all parameterisations" "of this type." .type = ints(value_min=0) parameter = None .help = "Identify which parameter of each parameterisation to" "constrain by a (partial) parameter name to match. Model" "name prefixes such as 'Detector1' will be ignored as" "parameterisations are already identified by experiment id" .type = str } force_static = False .help = "Force a static parameterisation for the crystal unit cell" "when doing scan-varying refinement" .type = bool .expert_level = 1 smoother .help = "Options that affect scan-varying parameterisation" .expert_level = 1 { interval_width_degrees = 36.0 .help = "Width of scan between checkpoints in degrees. Can be set" "to Auto." .type = float(value_min=0) absolute_num_intervals = None .help = "Number of intervals between checkpoints if scan_varying" "refinement is requested. If set, this overrides" "interval_width_degrees" .type = int(value_min=1) } } orientation .expert_level = 1 { fix_list = None .help = "Fix specified parameters by a list of 0-based indices or" "partial names to match" .type = strings .expert_level = 1 constraints .help = "Parameter equal shift constraints to use in refinement." .multiple = True .expert_level = 2 { id = None .help = "Select only the specified experiments when looking up" "which parameterisations to apply the constraint to. If an" "identified parameterisation affects multiple experiments" "then the index of any one of those experiments suffices" "to identify that parameterisation. If None (the default)" "then constraints will be applied to all parameterisations" "of this type." .type = ints(value_min=0) parameter = None .help = "Identify which parameter of each parameterisation to" "constrain by a (partial) parameter name to match. Model" "name prefixes such as 'Detector1' will be ignored as" "parameterisations are already identified by experiment id" .type = str } force_static = False .help = "Force a static parameterisation for the crystal orientation" "when doing scan-varying refinement" .type = bool .expert_level = 1 smoother .help = "Options that affect scan-varying parameterisation" .expert_level = 1 { interval_width_degrees = 36.0 .help = "Width of scan between checkpoints in degrees. Can be set" "to Auto." .type = float(value_min=0) absolute_num_intervals = None .help = "Number of intervals between checkpoints if scan_varying" "refinement is requested. If set, this overrides" "interval_width_degrees" .type = int(value_min=1) } } } detector .help = "detector parameters" { panels = *automatic single multiple hierarchical .help = "Select appropriate detector parameterisation. Both the single" "and multiple panel detector options treat the whole detector" "as a rigid body. The hierarchical parameterisation treats" "groups of panels as separate rigid bodies." .type = choice .expert_level = 1 hierarchy_level = 0 .help = "Level of the detector hierarchy (starting from the root at 0)" "at which to determine panel groups to parameterise" "independently" .type = int(value_min=0) .expert_level = 1 fix = all position orientation .help = "Fix detector parameters. The translational parameters" "(position) may be set separately to the orientation." .type = choice fix_list = None .help = "Fix specified parameters by a list of 0-based indices or" "partial names to match" .type = strings .expert_level = 1 constraints .help = "Parameter equal shift constraints to use in refinement." .multiple = True .expert_level = 2 { id = None .help = "Select only the specified experiments when looking up which" "parameterisations to apply the constraint to. If an" "identified parameterisation affects multiple experiments" "then the index of any one of those experiments suffices to" "identify that parameterisation. If None (the default) then" "constraints will be applied to all parameterisations of" "this type." .type = ints(value_min=0) parameter = None .help = "Identify which parameter of each parameterisation to" "constrain by a (partial) parameter name to match. Model" "name prefixes such as 'Detector1' will be ignored as" "parameterisations are already identified by experiment id" .type = str } force_static = True .help = "Force a static parameterisation for the detector when doing" "scan-varying refinement" .type = bool .expert_level = 1 smoother .help = "Options that affect scan-varying parameterisation" .expert_level = 1 { interval_width_degrees = 36.0 .help = "Width of scan between checkpoints in degrees. Can be set to" "Auto." .type = float(value_min=0) absolute_num_intervals = None .help = "Number of intervals between checkpoints if scan_varying" "refinement is requested. If set, this overrides" "interval_width_degrees" .type = int(value_min=1) } } goniometer .help = "goniometer setting matrix parameters" { fix = *all in_beam_plane out_beam_plane .help = "Whether to fix goniometer parameters. By default, fix all." "Alternatively the setting matrix can be constrained to allow" "rotation only within the spindle-beam plane or to allow" "rotation only around an axis that lies in that plane. Set to" "None to refine the in two orthogonal directions." .type = choice(multi=True) fix_list = None .help = "Fix specified parameters by a list of 0-based indices or" "partial names to match" .type = strings .expert_level = 1 constraints .help = "Parameter equal shift constraints to use in refinement." .multiple = True .expert_level = 2 { id = None .help = "Select only the specified experiments when looking up which" "parameterisations to apply the constraint to. If an" "identified parameterisation affects multiple experiments" "then the index of any one of those experiments suffices to" "identify that parameterisation. If None (the default) then" "constraints will be applied to all parameterisations of" "this type." .type = ints(value_min=0) parameter = None .help = "Identify which parameter of each parameterisation to" "constrain by a (partial) parameter name to match. Model" "name prefixes such as 'Detector1' will be ignored as" "parameterisations are already identified by experiment id" .type = str } force_static = True .help = "Force a static parameterisation for the goniometer when doing" "scan-varying refinement" .type = bool .expert_level = 1 smoother .help = "Options that affect scan-varying parameterisation" .expert_level = 1 { interval_width_degrees = 36.0 .help = "Width of scan between checkpoints in degrees. Can be set to" "Auto." .type = float(value_min=0) absolute_num_intervals = None .help = "Number of intervals between checkpoints if scan_varying" "refinement is requested. If set, this overrides" "interval_width_degrees" .type = int(value_min=1) } } sparse = Auto .help = "Calculate gradients using sparse data structures." .type = bool .expert_level = 1 treat_single_image_as_still = False .help = "Set this to True to treat a single image scan with a non zero" "oscillation width as a still" .type = bool .expert_level = 1 spherical_relp_model = False .help = "For stills refinement, set true to use the spherical relp model" "for prediction and gradients." .type = bool .expert_level = 1 } refinery .help = "Parameters to configure the refinery" .expert_level = 1 { engine = SimpleLBFGS LBFGScurvs GaussNewton *LevMar SparseLevMar .help = "The minimisation engine to use" .type = choice max_iterations = None .help = "Maximum number of iterations in refinement before termination." "None implies the engine supplies its own default." .type = int(value_min=1) log = None .help = "Filename for an optional log that a minimisation engine may use" "to write additional information" .type = path journal .help = "Extra items to track in the refinement history" { track_step = False .help = "Record parameter shifts history in the refinement journal, if" "the engine supports it." .type = bool track_gradient = False .help = "Record parameter gradients history in the refinement journal," "if the engine supports it." .type = bool track_parameter_correlation = False .help = "Record correlation matrix between columns of the Jacobian for" "each step of refinement." .type = bool track_condition_number = False .help = "Record condition number of the Jacobian for each step of " "refinement." .type = bool track_out_of_sample_rmsd = False .help = "Record RMSDs calculated using the refined experiments with" "reflections not used in refinement at each step. Only valid" "if a subset of input reflections was taken for refinement" .type = bool } } target .help = "Parameters to configure the target function" .expert_level = 1 { rmsd_cutoff = *fraction_of_bin_size absolute .help = "Method to choose rmsd cutoffs. This is currently either as a" "fraction of the discrete units of the spot positional data," "i.e. (pixel width, pixel height, image thickness in phi), or a" "tuple of absolute values to use as the cutoffs" .type = choice bin_size_fraction = 0.0 .help = "Set this to a fractional value, say 0.2, to make a cut off in" "the natural discrete units of positional data, viz., (pixel" "width, pixel height, image thickness in phi). This would then" "determine when the RMSD target is achieved. Only used if" "rmsd_cutoff = fraction_of_bin_size." .type = float(value_min=0) absolute_cutoffs = None .help = "Absolute Values for the RMSD target achieved cutoffs in X, Y" "and Phi. The units are (mm, mm, rad)." .type = floats(size=3, value_min=0) gradient_calculation_blocksize = None .help = "Maximum number of reflections to use for gradient calculation." "If there are more reflections than this in the manager then the" "minimiser must do the full calculation in blocks." .type = int(value_min=1) } reflections .help = "Parameters used by the reflection manager" { reflections_per_degree = 100 .help = "The number of centroids per degree of the sweep to use in" "refinement. Set to None to use all suitable reflections." .type = float(value_min=0) minimum_sample_size = 1000 .help = "cutoff that determines whether subsetting of the input" "reflection list is done" .type = int maximum_sample_size = None .help = "The maximum number of reflections to use in refinement." "Overrides reflections_per_degree if that produces a larger" "sample size." .type = int(value_min=1) random_seed = 42 .help = "Random seed to use when sampling to create a working set of" "reflections. May be int or None." .type = int .expert_level = 1 close_to_spindle_cutoff = 0.02 .help = "The inclusion criterion currently uses the volume of the" "parallelepiped formed by the spindle axis, the incident beam" "and the scattered beam. If this is lower than some value then" "the reflection is excluded from refinement. In detector space," "these are the reflections located close to the rotation axis." .type = float(value_min=0) .expert_level = 1 block_width = 1.0 .help = "Width of a reflection 'block' (in degrees) determining how" "fine- grained the model used for scan-varying prediction during" "refinement is. Currently only has any effect if the crystal" "parameterisation is set to use compose_model_per=block" .type = float(value_min=0) .expert_level = 1 weighting_strategy .help = "Parameters to configure weighting strategy overrides" .expert_level = 1 { override = statistical stills constant external_deltapsi .help = "selection of a strategy to override default weighting" "behaviour" .type = choice delpsi_constant = 1000000 .help = "used by the stills strategy to choose absolute weight value" "for the angular distance from Ewald sphere term of the target" "function, whilst the X and Y parts use statistical weights" .type = float(value_min=0) constants = 1.0 1.0 1.0 .help = "constant weights for three parts of the target function," "whether the case is for stills or scans. The default gives" "unit weighting." .type = floats(size=3, value_min=0) } outlier .help = "Outlier rejection after initial reflection prediction." { algorithm = null *auto mcd tukey sauter_poon .help = "Outlier rejection algorithm. If auto is selected, the" "algorithm is chosen automatically" .type = choice minimum_number_of_reflections = 20 .help = "The minimum number of input observations per outlier" "rejection job below which all reflections in the job will be" "rejected as potential outliers." .type = int(value_min=0) separate_experiments = True .help = "If true, outlier rejection will be performed on each" "experiment separately. Otherwise, the data from all" "experiments will be combined for outlier rejection." .type = bool separate_panels = Auto .help = "If true, outlier rejection will be performed separately for" "each panel of a multi-panel detector model. Otherwise data" "from across all panels will be combined for outlier" "rejection." .type = bool separate_blocks = True .help = "If true, for scans outlier rejection will be performed" "separately in equal-width blocks of phi, controlled by the" "parameter outlier.block_width." .type = bool block_width = Auto .help = "If separate_blocks, a scan will be divided into equal-sized" "blocks with width (in degrees) close to this value for" "outlier rejection. If Auto, a width of at least 18 degrees" "will be determined, such that each block contains enough" "reflections to perform outlier rejection." .type = float(value_min=1) tukey .help = "Options for the tukey outlier rejector" .expert_level = 1 { iqr_multiplier = 1.5 .help = "The IQR multiplier used to detect outliers. A value of 1.5" "gives Tukey's rule for outlier detection" .type = float(value_min=0) } mcd .help = "Options for the mcd outlier rejector, which uses an algorithm" "based on FAST-MCD by Rousseeuw and van Driessen. See" "doi.org/10.1080/00401706.1999.10485670." .expert_level = 1 { alpha = 0.5 .help = "Decimal fraction controlling the size of subsets over which" "the covariance matrix determinant is minimised." .type = float(value_min=0, value_max=1) max_n_groups = 5 .help = "The maximum number of groups to split the dataset into if" "the dataset is 'large' (more observations than twice the" "min_group_size)." .type = int(value_min=1) min_group_size = 300 .help = "The smallest sub-dataset size when splitting the dataset" "into a number of groups, maximally max_n_groups." .type = int(value_min=100) n_trials = 500 .help = "The number of samples used for initial estimates to seed" "the search within each sub-dataset." .type = int(value_min=1) k1 = 2 .help = "The number of concentration steps to take after initial" "estimates." .type = int(value_min=1) k2 = 2 .help = "If the dataset is 'large', the number of concentration" "steps to take after applying the best subset estimates to" "the merged group." .type = int(value_min=1) k3 = 100 .help = "If the dataset is 'small', the number of concentration" "steps to take after selecting the best of the initial" "estimates, applied to the whole dataset." .type = int(value_min=1) threshold_probability = 0.975 .help = "Quantile probability from the Chi-squared distribution with" "number of degrees of freedom equal to the number of" "dimensions of the data data (e.g. 3 for X, Y and Phi" "residuals). Observations whose robust Mahalanobis distances" "are larger than the obtained quantile will be flagged as" "outliers." .type = float(value_min=0, value_max=1) } sauter_poon .help = "Options for the outlier rejector described in Sauter & Poon" "(2010) (http://dx.doi.org/10.1107/S0021889810010782)" .expert_level = 1 { px_sz = Auto .help = "X, Y pixel size in mm. If Auto, this will be taken from the" "first panel of the first experiment." .type = floats(size=2, value_min=0.001) verbose = False .help = "Verbose output." .type = bool .multiple = False pdf = None .help = "Output file name for making graphs of |dr| vs spot number" "and dy vs dx." .type = str .multiple = False } } } } output { experiments = experiments.json .type = path split_experiments = False .type = bool reflections = indexed.pickle .type = path unindexed_reflections = None .type = path log = dials.index.log .type = str debug_log = dials.index.debug.log .type = str } verbosity = 1 .help = "The verbosity level" .type = int(value_min=0)


This example starts with a playlist of video ids and loads them one after the other. It doesn't use the player.cuePlaylist or player.loadPlaylist methods. Instead, it listens for player state changes and checks if they're "ended" events.


New in 1.3.0
Edit (pull request)TOSCA editor
Alien 4 Cloud 1.3.0 introduce a brand new version of the editor that now allows to edit a full archive, including topology yaml, scripts and any other files while still providing the topology and workflow edition views.
The core of the editor has been rewritten to allow support for undo/redo and user-triggered save (rather than automatic save on every operation) allowing to update the topology only when your changes are consistent.
To ease usage we now includes basic keyboard shortcuts in the editor and plan to improve their support with new ones. If you have a wish-list join our slack and share with us and the community!
The editor is now fully integrated with git, providing a local history through commits (performed automatically on a save) and allowing to push and/or pull from a remote repository.
Workspaces
TOSCA archives are now uploaded within workspaces. OpenSource support allow better isolation of application workspace. Premium support includes user workspaces and promotion mechanisms to allow archive sharing.
TOSCA conformance improvements
Complex inputs
Alien 4 Cloud now supports complex data types (including lists and maps) for topology inputs. Remember that you can access your complex properties using the get_property input in TOSCA
Repositories support
Alien 4 Cloud now support artifact repositories definition and parsing. See more in Artifact repositories support section below.
Artifact repositories support
Ability to define artifact repositories to override url and credential based on artifact id (usefull when behind proxy).
Support of various repository types:
- Http
- Maven/Nexus (
Premium
) - Git (
Premium
)
API improvements
Support for single call topology update or git pull making it easy to update your topology before deployment.
Alien4Cloud High Availability - Premium
HA support allowing a 24/7 availability of Alien4Cloud, using a primary / backup system.
Cloudify 3.4 support
Alien4Cloud 1.3 officially supports cloudify 3.4 that bring support for scalability groups. We now removed our custom OpenStack plugin that worked-around scalability issues in cloudify 3 to leverage scalability groups.
As Scalability Groups have limitations for block storage scalability we include custom wrappers that enable full Block Storage scalability and all that fully transparent for the user!
Docker support
Support for docker deployment using our Marathon plugin (beta state) and experimental support for Kubernetes through cloudify
Edit (pull request)


{{welcome}}
Welcome! For instructions, refer to FAQ.
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count down: Time Up
Price Center
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Additional style for the .box where the object is rendered.
String, default = ''
You need to call .render() method to re-render the object if
you changed this property during run-time. The .style property can be set during object creation.
It is not recommended to change it during run-time as it requires complete re-render.


Dependenciesedit
The low-level Java REST client internally uses the Apache Http Async Client to send http requests. It depends on the following artifacts, namely the async http client and its own transitive dependencies:
- org.apache.httpcomponents:httpasyncclient
- org.apache.httpcomponents:httpcore-nio
- org.apache.httpcomponents:httpclient
- org.apache.httpcomponents:httpcore
- commons-codec:commons-codec
- commons-logging:commons-logging


The specific UI handles most of the manipulation of the target hierarchy. Most specific UIs interpret keyboard and mouse events and know when to switch the target from one object to another. For example, in OSF/Motif, clicking on a window will switch the target to that window from the previous target window. Before the mouse is clicked, however, the target exclusive of that window will not change. In other specific UIs which incorporate real-estate cursor behavior, merely moving the cursor over a window will transfer the target to that window.
By default, an application will come up with certain objects having the target exclusive within their target levels. This allows the user to immediately begin typing or operating on data. For an object to grab the default exclusive, it must first be targetable. A targetable object can be any child of a valid target node. Valid nodes for the target hierarchy are:
In addition, however, a generic object must be set GA_TARGETABLE in its
GI_attrs
field to become a valid target object. This bit is set by default for the following classes:
If you wish a generic object to be targetable and it does not appear in this list, set it GA_TARGETABLE. If the object does not by default appear as a valid node in the Target hierarchy (such as for a custom gadget), you must subclass the object and add target instance fields and message handlers.
For all targetable objects within a target exclusive level, the target will be granted to the object with
HINT_DEFAULT_TARGET
in its instance data. If no object has this hint at a particular target level, then the target will be granted to the first targetable object at that level.
To grab the target exclusive in its level, a node should send itself
MSG_META_GRAB_TARGET_EXCL
. The default handler for this message grabs the target exclusive for the object from its parent and forces any other object on the caller's level to give the target up. The active exclusive will not be granted unless the caller is part of the active path after the grab.
When another node grabs the target exclusive, the node currently having the exclusive on that level must give it up.
MSG_META_RELEASE_TARGET_EXCL
releases the target exclusive for the other node.
Note that these messages only modify the exclusive at a single level. Therefore, they only affect the target optr of the parent's node; further up the target hierarchy there is no effect. Changing the target exclusive of an object will only change the direction of the target path if all parents of the new exclusive are also target exclusives.
MSG_META_GET_TARGET_EXCL
may be sent to any targetable composite node to get the optr of the node's child having the exclusive. This message may be used even on nodes in the inactive path.
When an object gains the active target exclusive and is a node in the active path, it receives
MSG_META_GAINED_TARGET_EXCL
. This indicates to the object that it will receive all keyboard input as the active keyboard object.
At some point later, when the object has lost the target exclusive, it will receive
MSG_META_LOST_TARGET_EXCL
.
Frequently, you may wish to send messages to objects in the active Target path. The easiest way to deliver a message to an object in the target hierarchy is to use
MSG_META_SEND_CLASSED_EVENT
with the
TravelOption
TO_TARGET. To send a message to the leaf node of the active path, send this message with a null class. The message will be sent down the hierarchy until it reaches the leaf object, where it will be processed. (See Delivering Messages to the Target
.)
This approach is desirable over using
MSG_META_GET_TARGET_EXCL
to return an optr for later use, as the system may have corrupted the optr in the meantime.
Code Display 11-3 Delivering Messages to the Target
@method MyProcessClass, MSG_SEND_MESSAGE_TO_TARGET_INTERACTION { EventHandle event;
/* The classed event is recorded to be handled by the first object of class * GenInteractionClass. */ event = @record GenTextClass::MSG_TEST_MESSAGE();
/* This message is then sent to the GenApplication object, from which it * will travel down the target hierarchy until handled at the * GenInteraction level. */ @call MyApplication::MSG_META_SEND_CLASSED_EVENT(event, TO_TARGET); }
/* You may also declare an object with the TravelOption TO_APP_TARGET. This will * send the message to the application object and then down the target hierarchy. */
@object GenTriggerClass MyTargetTrigger = { GI_visMoniker = "Send test message to the target"; GTI_actionMsg = MSG_TEST_MESSAGE; GTI_destination = (TO_APP_TARGET); ATTR_GEN_DESTINATION_CLASS = { (ClassStruc *)&GenTextClass }; }
/* To send a message to the target leaf node, use a null class. */
@method MyProcessClass, MSG_SEND_TEST_TO_TARGET_LEAF { EventHandle event;
/* A classed event with the class of null is recorded. */ event = @record null::MSG_TEST_MESSAGE();
/* This event is sent to the GenApplication, where it will travel down the * target hierarchy to the leaf object, where it will be handled. */ @call MyApplication::MSG_META_SEND_CLASSED_EVENT(event, TO_TARGET); }
/* As an alternative, an object could be set to deliver its message to the * leaf target node of the application. */ @object GenTriggerClass MyTargetLeafTrigger = { GI_visMoniker = "Send test message to the target leaf object"; GTI_actionMsg = MSG_TEST_MESSAGE; GTI_destination = (TO_APP_TARGET); /* An ATTR_GEN_DESTINATION_CLASS of zero specifies a null class. */ ATTR_GEN_DESTINATION_CLASS = 0; }


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As someone who knows barely anything privacy related if we are talking about the web. I thought it would be a good opportunity to take a deep dive in this particularly matter. Especially for a project which concerns the use of medications. Which could be described as sensitive data.
So first and foremost what is a “cookie”?
A cookie is a small bit of textual information that is stored on a device’s hard-drive by a web server, which is sent again with each future request to that website. — dbswebsite
What kinds of cookies are there?
According to the GDPR there are three different ways to classify cookies: what purpose they serve, how long they endure, and their provenance.
Duration
- Session cookies
- Persistent cookies
Provenance
- First-party cookies
- Third-party cookies
Purpose
- Strictly necessary cookies
- Preferences cookies
- Statistics cookies
- Marketing cookies
While there are a lot of different kinds of cookies, it all comes down to these four:
session cookies
Session cookies are cookies who are temporary and will expire once a user closes his/her browser. And fall under the category strictly necessary cookies according to GDPR website. Which means it’s not required to ask users for their consent, but what they do and why they are necessary should be explained to the user.
They are also known as functional cookies and a consent is not required.
It is required to inform the user about those cookies. Informing about that can be done with the Privacy page via the “Your privacy” link. — uxdesign
personalization cookies
Are cookies who remember personalizing information, for example carts. Also known as the preferences cookies.
anonymous tracking cookies
These are cookies used by websites like Google Analytics, to gather anonymous information about how user interacts on the website. Also known as the statistic cookies.
third-party cookies
These cookies usually come from ad-related content and are usually not anonymous either. They serve as a way to serve user even more relevant ads (also the ads that follow you around).
Privacy
Why do users consider cookies as a privacy invasion?
There are people who consider cookies as a form of privacy invasion. While cookies can’t obtain personal information from your computer, some cookies are used to gather information from users without their consent. It’s also seen as a form of tracking. Which is why they consider it as privacy invasion.
Conclusion
From a privacy standpoint, the best option would be to use session cookies. Session cookies are temporary and will not be saved on a server or anywhere else besides the users device but only temporary. On the other hand it would be nice to give users the option to choose between either sessions cookies or cookies. In order to give them the control over what they would like to be saved and why.
At the end of the day I do believe that the voices of users are the key behind changing the web and the more noise there is the better. However I also believe that we as designers/developers have a role in this too, it’s not just them or us, because for what it’s worth all they know or see is an annoying popup. It’s our job to educate those who maybe aren’t as tech savy as us or have any knowledge about privacy or about laws. So we can not protect only those close to us, but also others.


Certain servers may not have mod_rewrite (basic rewriting) enabled by default. To ensure mod_rewrite is enabled throughout your site, add the following line once to your site’s root .htaccess file (located before any rewrite rules):
# enable mod_rewrite
RewriteEngine on


A Pizza Pablo
Y'all want summa this?
Build a Pizza
What size pizza would you like?
Small
Medium
Large
Would you like cheese?
Yes
No
What meats would you like?
Pepperoni
Anchovy
Any veggies with that?
Mushrooms
Pineapple
Add to Order
Thanks for your order!
Here's what you got:
Toppings:
Total: $


This project is a demonstration of how to migrate an AngularJS app from a hand-spun build process to webpack.
The JavaScript is bundled using a gulp task. The task searches for files matching the following patterns:
node_modules/jquery/dist/jquery.js
node_modules/boostrap/dist/js/bootstrap.js
node_modules/angular/angular.js
src/app.js
src/**/*.js
Files matching those patterns are concatenated, minified, then bundled into
a single file named bundle.js
.
The order of those files matters; Bootstrap cannot load
until jQuery does, and none of the components can load until
app.js
does, since that's where our AngularJS module is
declared.
The AngularJS templates are compiled and added to the template cache by the
npm package gulp-angular-templatecache
. The output of that
plugin is concatenated with the rest of the JavaScript before minification.
Any files matching the following patterns are fed to
gulp-sass
:
node_modules/boostrap/dist/css/bootstrap.min.css
src/**/*.scss
The output of gulp-sass
is concatenated and saved to
bundle.css
.
Again, the order of bundling matters. Styles defined in later stylesheets override those in previous ones. If we had many SCSS files, we could run into issues where they don't get concatenated in the order we expect.
The development server is Browsersync. Once all the JavaScript, CSS, and
other assets are bundled and placed in ./dist
,
Browsersync serves files out of that directory.
A gulp watch is placed on the input files. If any change, the appropriate gulp task is executed, then Browsersync reloads the page in the browser.