Note
Since World() is a very special function, I decided not to follow the normal Python convention and have its name start with an uppercase letter.
Choose a world other than Home 1. Then run the following program twice:
World("Home 1")
move()
move()
The first time you run it, you should see Reeborg informing you that the world has changed to Home 1, which you should be able to confirm by looking at the world.
The second time you run it, because Home 1 is already selected, the function World() is effectively ignored, and the rest of the program is executed.

Do this! It’s important.
Select world Storm 1. Write a program that will make Reeborg collect all the leaves and put them in the compost bin. Your program will very likely require you to use carries_object().
Look closely at the world Storm 1, taking note of where leaves are.
Now, at the very top of the program you just wrote to have Reeborg pick up all the leaves in Storm 1, add the following line of code:
World("http://reeborg.ca/worlds/not_storm1.json")
[Note that it is a number “1” at the end of not_storm1, and not the letter “l”.] Run the program once: Reeborg should tell you that the world has been loaded properly. Its appearance should be identical to what it was before.
Note how the world name in the selector at the top is this very long name which was used as an argument to World().
Click on the “World info” button at the top. You will find a brief description of the world, including the fact that you are not supposed to use carries_object(). Ignore that, and run your program. Take note of what happens.
So, your program did not work. We will see how to fix this soon. In the meantime, I want you to try something else. Change the first line of the program to read instead like the following:
World("http://reeborg.ca/worlds/not_storm1.json",
"Not Storm 1")
I have added a second argument to the function World(). So as to avoid having a line of code that would be too long to be seen all at once in the editor, I have put the second argument on a different line. When Python sees an open parentheses ( for a function argument, it continues to read if needed on other lines until it finds a closing ), and treats everything as though it was all on a single line. However, note that I did not split up the strings; I only put things on a new line after a comma, so that each function argument is on its own line.
Now, run this. Again, this will not solve the task at hand. However, if you look at the top, the name that now appears for the world is Not Storm 1 instead of the long address that we had before.
You might want to save your program in a file on your computer by clicking on the “Additional options” button, followed by “Save program to file”. Later, you will be able to retrieve it by clicking on “Import program from file”.


MultiView SPI provides infrastructure for creating components that dock
multiple views into one consistent component. Developers define what
shall be included into the component and are given opportunity to
influence the overall behaviour of the component.
This SPI handles the lifecycle of a multiview component.
Creation
New instance of MultiView TopComponent can be created by calling
MultiViewFactory.createMultiView
The resulting TopComponent can be docked in arbitrary mode at your
convenience. The factory method requires an array of
{@link org.netbeans.core.spi.multiview.MultiViewDescription}s that
describe the content of the view.
Each description in the View shall have a unique display name
and preferredId.
All the descriptions shall be lightweight classes, which create the
actual visual components on demand in
{@link org.netbeans.core.spi.multiview.MultiViewDescription#createElement}
The multiview component is cloneable by default. If any of your
embedded elements cannot be cloned, or you don't intend to allow the
users to clone the component, please use the appropriate factory method
to create a non-cloneable instance.
Lifecycle
Once the multiview component is opened, the element for the default
MultiViewDescription is created. Creation of other Elements is delayed
to the moment these are required.
All created Elements get notified of changes in the lifecycle of the
multiview component and their own. The notification callback method
have the same name and similar semantics as the TopComponent ones.
- When the element is shown for the first time, componentOpened()
is called.
- Everytime the element is selected in the component,
componentShowing() is called on the new selection and componentHidden()
on the one deselected.
- When focusing the whole component, the currently selected element
receives componentActivated(). When switching elements, the element
loosing focus gets called componentDeactivated(), the one gaining focus
is called componentActivated()
- Whenever the multiview component gets notified of it's state
changes (showing/hidden/activate/deactivated) by the window system,
these are propagated to the currently selected element only.
- For all elements that were created during the lifecycle of the
component, componentClosed() is called when the component is about to
be closed. Closing the component is special because the elements can be
in non-deterministic state and a dataloss situation is possible.
Each created MultiViewElement is queried for it's state, the
environment calls
{@link org.netbeans.core.spi.multiview.MultiViewElement#canCloseElement}.
The owner of the multiview component resolves the problems (silently or
by asking the user) in
{@link org.netbeans.core.spi.multiview.CloseOperationHandler#resolveCloseOperation}
Persistence
TopComponents decide about persistence based on the TopComponent.getPersistenceType()
return values. Possible values are:
- TopComponent.PERSISTENCE_ALWAYS,
- TopComponent.PERSISTENCE_NEVER,
- TopComponent.PERSISTENCE_ONLY_OPENED.
The multiview component decides what it's return value is based on the
values returned by MultiViewDescription.getPersistenceType()
of all embedded MultiViewDescriptions.
- When at least one of
them returns PERSISTENCE_ALWAYS, it is returned by
the TopComponent as well.
- If at least one requires
PERSISTENCE_ONLY_OPENED and none needs PERSISTENCE_ALWAYS, the
TopComponent's state will be stored only when it's opened on IDE exit.
- The multiview topcomponent is not persisted if all descriptions
return PERSISTENCE_NEVER, or any of the descriptions are not
serializable.
In other words, ALWAYS has higher priority than ONLY_OPENED and NEVER
has the lowest priority of all.
When the multiview's TopComponent gets persisted, all of it's
{@link org.netbeans.core.spi.multiview.MultiViewDescription} instances
get serialized. Thus they need to implement Serializable. Then
for all MultiViewDescriptions that were opened (created their
{@link org.netbeans.core.spi.multiview.MultiViewElement} instances) and don't
declare PERSISTENCE_NEVER in their getPersistenceType() method, the
MultiViewElement instance gets persisted as well.
Note: If any of the MultiViewDescription instances is not Serializable,
the TopComponent will not get persisted. Please note that even if your
MultiViewDescription returns PERSISTENCE_NEVER, it should be possible
to serialize the Description instance. After restoration the
deserialized instance will create a fresh MultiViewElement instance.
If you define your own {@link org.netbeans.core.spi.multiview.CloseOperationHandler} implementation for the multiview component, then you also ought to define it
Serializable.
When restoring the multiview TopComponent, all the
MultiViewDescriptions are deserialized, also all the stored
MultiViewElements are deserialized. These are kept and the
createElement() method is not called on the matching
MultiViewDescription.
Manipulating the multiview
MultiViewElements get a chance to manipulate the enclosed topcomponent.
Each of them is passed an instance of
{@link org.netbeans.core.spi.multiview.MultiViewElementCallback} on
creation or deserialization. (Please don't serialize with your
element's data, for performance reasons) It can be used during
lifecycle of the element.
- To request activation.
- To request visibility.
- To get the default topcomponent actions (shall be used to
contruct the Element's getActions() array).
- To change the title for the topcomponent.
If your MultiViewElement is a TopComponent or provides a TopComponent
in getVisualRepresentation(), you can manipulate
the activatedNodes of the whole multiview component by setting the
appropriate nodes on your own TopComponent.
when elements are switched, the activated nodes get updated as well
according to the shown element.
Embedding editors
A typical MultiViewElement for embedding editor extends
CloneableEditor
and delegates some of the functionality to the multiview component.
The multiview component implements CloneableEditorSupport.Pane and the
CloneableEditorSupport instance's createPane() method
shall return the overall multiview component, rather than the
MultiViewElement's component. In such case the opening the component
shall be always done using the openCloneableTopComponent() call which
will register the MultiView component as
a holder of the editor pane for that CloneableEditorSupport instance.
The multiview component will always
delegate to the currently selected element when communication with the
editor support classes. Keep that in mind when trying to manipulate
the editor pane. Always switch to the editor's element first.
Please note: The multiview component is just a placeholder for the
enclosed components. Any data related synchronizations are to be
performed in the client code. This is especially important when
multiple elements work over the same data/files.
At
least the requestActive() and requestVisible() methods shall be
overriden to delegate to the MultiViewElementCallback. Sample code:
public void requestActive() {
if
(multiViewCallback != null) {
multiViewCallback.requestActive();
}
else {
super.requestActive();
}
}
Since TopComponent's lifecycle callback methods (componentOpened(),
componentShowing() etc) are defined with protected scope, you will have
to redefine the to be public to be in synch with the MultiViewElement
interface signature. If the lifecycle within the multiview component
differs from the default behaviour, additional handling goes here as
well.
To create the editor's toolbar, the one provided by the
NbDocument.CustomToobar is the obvious choice.
public JComponent
getToolbarRepresentation() {
if
(toolbar == null) {
JEditorPane pane = getEditorPane();
if (pane != null) {
Document doc = pane.getDocument();
if (doc instanceof NbDocument.CustomToolbar) {
toolbar = ((NbDocument.CustomToolbar)doc).createToolbar(pane);
}
}
if (toolbar == null) {
//attempt to create own toolbar?
toolbar = new JPanel();
}
}
return toolbar;
}
The owner/creator of the multiview component is responsible to handle
proper closing of the editor via the
{@link org.netbeans.core.spi.multiview.CloseOperationHandler#resolveCloseOperation}
method implementation.


HOME BEFORE DARK
Reviewed by Harvey Karten, Ph.D. Hazelwood Films-Scout Produciton Director: Maureen Foley Writer: Maureen Foley Cast: Stephanie Castellarin, Brian Delate, Katharine Ross, Patricia Kalember, Helen Lloyd Breed
In this modest film which was introduced at the 1997 Hamptons International Film Festival (where it won the Grand Jury Prize), an 11-year-old girl submits a story to a contest sponsored by "Seventeen" magazine. The story is about her own childhood, about incidents which marred her happiness and caused her single-handedly to seek a resolution to the serious problems her family must bear. That narrative becomes, in effect, the film itself: a tale about a sad but intelligent and sensitive junior-high student at the time of the Kennedy assassination, an era in which bold changes were to occur in American society mirroring the surprises in her own adolescence. While "Home Before Dark" has the look of a TV soap, and one which could use some judicious editing to pick up its sluggigh pace, the film is redeemed by solid acting particularly by young Stephanie Castellarin in her first starring role in a feauture film. It also showcases the talent of Katherine Ross, best known to an American audience for her role in "The Graduate" as Dustin Hoffman's main squeeze and as part of a threesome with Paul Newman and Robert Redford in "Butch Cassidy and the Sundance Kid."
"Home Before Dark" takes place in a Massachusettes suburb which finds Nora (Stephanie Castellarin) attending a strict parochial school in the class of Sister Concilia (Helen Lloyd Breed), her studies hardly motivated by the tragic events in her home. Her mother, Dolores (Patricia Kalember), feels responsible the for automobile deaths of three of her sibs before Nora was born and is institutionalized after a suicide attempt. Forced to grow up before her time, Nora is sent by her stressed-out dad Martin (Brian Delate) to live with her Aunt Rose (Katharine Ross), a cold, prim Jackie-O lookalike who treats the girl as a daughter-substitute but is entirely too rigorous in her demands.
In her script, writer-directed Maureen Foley evokes the usual laughs in dealing with a Catholic education, picturing Sister Concila (Helen Lloyd Breed) as an overbearing disciplinarian who nonetheless has humorous traces of humanity. (In one scene, she catches some 11-year-olds smoking, sends them scurring back to the building, and takes a deep, satisfying breath of their secondhand smoke.)
Foley takes us through a pre-adolescent's usual rites of passage: first period, first kiss, competition with a classmate for the attentions of a cute boy. The year 1963 is perhaps the final year of American innocence, which was lost as a result of the Kennedy assassination, the onset of the Vietnam, and the introduction of the birth control pill. The urge to conform is present in the behavior of the beautician who ruins Nora's free-flowing hair ("they're all wearing it this way"), and the era's obsessiveness is well reflected in the behavior of the priggish Aunt Rose who is "driven crazy" by the way Nora's hair keeps flowing about the girl's face.
Brian Delate turns in a strong and believable performance as a dad who tries his best to pay his bills and bring up four children without the presence of their mother. Without Stephanie Castellarin's laudable dispatch of her sensitive role as an emotionally burdened girl, though, "Home Before Dark" would be quite ordinary, however heartfelt.
Not Rated. Running time: 110 minutes. (C) Harvey Karten 1998
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


On 21st September, Dash, the cryptocurrency ranked 11th on CoinMarketCap made the announcement of its partnership with the India-based cryptocurrency exchange Bitbns. Dash is a relatively new cryptocurrency, founded in 2014 and built on the code of Bitcoin Core. In its offici...
In order to improve the Dash community’s cohesion and discourse experience, and to preserve its decentralization and freedom of speech, several prominent community moderators have created a n…


{% extends 'base.html' %} {% block content %}
RUN NEW JOB for GROUPS
| Platform | City | Status | Action | Results | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| {{ j.provider}} | {{ j.city}} | {% if j.status == 1|string %}Running | Pause | Results | {% elif j.status == 0|string %}Stopped | Run Delete | Results | Stopped | Resume | Results | Finished | Done | Results |


Plugin Information |
|---|
View Tool Labels on the plugin site for more information. |
This plugin allows users to add labels dynamically to every node with a specific tool installation so that a job can restrict the nodes where it runs by their tool locations.
Example use case
Assuming you have nodes A, B, and C, and Java 6 JDK is installed only on A and B for some reasons, you would add JDK Java 6
in the System Configurations and its tool locations in the Node Configurations of A and B.
Then, if you add label jdk1.6
to JDK Java 6
with this plugin in the System Configurations, it will be added dynamically to A and B, and a job can restrict the nodes where it runs to them by using label jdk1.6
.
If you would later remove the tool location of JDK Java 6
from B, label jdk1.6
would disappear from the node, too. You no longer need to manually manage labels for tool installations on your nodes.
Project information
Regardless of the Source Code link above, the source code repository of this plugin is at https://bitbucket.org/kazssym/jenkins-tool-labels-plugin. If you are interested in what will be implemented in future versions, please sign up for a free Bitbucket account (if you have not yet) and watch the repository for notifications.
License
This program is licensed under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
As this program is released under the Affero GPL, if you modify this program and if it can interact with users remotely through a computer network, you must provide access to the source code of your modified version. If you are unwilling to provide access to the source code, you will have to get special permission from the author.
Getting help
Please use an experimental community forum for this plugin.


{tag_addtofavorites,add_Image, remove_Image} | Add FAQ to favorites list. Optionally customize to display your own custom image for adding and removing. Here is an example - {tag_addtofavorites,,} |
{tag_answer} | Answer for frequently asked question (editor content). This outputs the text of the FAQ. |
{tag_button,Your Text} | replace Your Text with your own text. This outputs an anchor that takes the user to the detail view of the FAQ. The anchor's text is in this example "Your Text". |
{tag_counter} | Incremental count of the FAQ on the page. |
{tag_expirydate} | Expiry date of FAQ for example 16-Apr-2014 03:48 AM |
{tag_lastupdatedate} | Last update date of FAQ for example 16-Apr-2014 03:48 AM |
{tag_question_nolink} | Frequently asked question (will not have hyperlink). This outputs the FAQ's title in plain text. |
{tag_question} | Frequently asked question (will have hyperlink). This outputs the FAQ's title as an anchor. When clicked the site visitor is taken to the detail view. The text of the anchor is the FAQ's title. |
{tag_releasedate} | Release date of FAQ in this format - 16-Sep-2014 |
{tag_tellafriend} | Tell a friend about this FAQ. This outputs a link that when clicks opens up a popup that contains the "Tell a Friend" form. |


Google rolls out updated ‘My Devices’ page for G Suite users
Along with the new look, the refreshed 'My Devices' page now supports Chromebooks, laptops and more
by Jonathan LamontGoogle’s little-known G Suite feature, ‘My Devices,’ has received a Material Design makeover.
The search giant announced the changes via a blog post which highlighted changes like the inclusion of “desktop devices,” more detailed device information and more.
For those who aren’t familiar with the My Devices page, it’s a website that acts similarly to the ‘Find My Device’ feature on Android. However, it works with Google-connected devices through G Suite. It allows users to ping their devices, as well as remotely wipe and lock them.
Further, the new layout retains all the previous functionality. In other words, you’ll be able to see all the hardware linked with a G Suite account, as well as extended and detailed device information.
The biggest change is the addition of desktop devices, which means My Devices now shows Chromebooks, laptops and other desktop devices linked to a G Suite account. This will likely prove helpful to IT administrators who need to keep track of and manage hardware utilized by their organization.
Finally, My Devices now exists under a new URL — ‘mydevices.google.com‘ — which should make it easier to get to now. That said, the page isn’t live for everyone yet. When I tried it out, I received a ‘404’ error. Google says it can take around one to three days for it to roll out to all domains.
Once rolled out, the new My Devices page will be the default for all G Suite accounts.
You can learn more about My Devices here.
Source: Google Via: 9to5Google


--- title: Contextual Emotion Detection in Text (DoubleDistilBert Model) keywords: fastai sidebar: home_sidebar summary: "We use the excellent pytorch-lightning, Huggingface transformers, and fast.ai nbdev libraries for a clean and efficient implementation and demonstrate the performance of our model on the SemEval-2019 Task 3 dataset." ---
SemEval-2019 Task 3 description:
"Lack of facial expressions and voice modulations make detecting emotions in text a challenging problem. For instance, as humans, on reading "Why don't you ever text me!" we can either interpret it as a sad or angry emotion and the same ambiguity exists for machines. However, the context of dialogue can prove helpful in detection of the emotion. In this task, given a textual dialogue i.e. an utterance along with two previous turns of context, the goal was to infer the underlying emotion of the utterance by choosing from four emotion classes - Happy, Sad, Angry and Others. To facilitate the participation in this task, textual dialogues from user interaction with a conversational agent were taken and annotated for emotion classes after several data processing steps."
Approach: Pre-Trained DistilBert model for sentence embeddings and contextual information via another Bert model on top
pip install packaging
pip install git+https://github.com/juliusberner/emotion_transformer
Training and testing the default configuration (e.g. on GPU with index 0)
python main.py --mode=test --gpus='0'
Parallel hyperparameter search on 8 GPUs using half-precision (automatically done by test_tube and pytorch_lightning):
python main.py --mode=hparams_search --gpus='0 1 2 3 4 5 6 7' --use_16bit
alternativ: Parallel hyperparameter search on 8 GPUs (2 GPUs with specified indices for each setting):
python main.py --mode=hparams_search --gpus='0,1 2,3 4,5 6,7' --distributed_backend='dp'
(tested with nvidia-docker FROM nvcr.io/nvidia/pytorch:19.02-py3
as specified in requirements.txt
)
automatically created by nbdev: Documentation
Jupyter notebooks explaining the dataloader, the model, and the lightning module:
00_dataloader.ipynb
01_model.ipynb
02_lightning.ipynb
fast.ai nbdev: "nbdev is a library that allows you to fully develop a library in Jupyter Notebooks, putting all your code, tests and documentation in one place."
William Falcon's test tube "Test tube is a python library to track and parallelize hyperparameter search for Deep Learning and ML experiments. It's framework agnostic and built on top of the python argparse API for ease of use."


@() @main("App-Store crawler") {
| Enter app | Possible input |
|---|---|
| Apple App Store | https://itunes.apple.com/de/app/youtube/id544007664 youtube/id544007664 |
| Google Play Store | https://play.google.com/store/apps/details?id=com.google.android.youtube com.google.android.youtube |
Rest call url
Tip: Copy and format result with jsonviewer.stack.hu
You can change the request language by adding an ISO 639-1 conformal language code to the app url. For example
This service is not intended to be called at a high request/s otherwise it will be banned from the app stores. For a more sophisticated iTunes Api visit the iTunes Search API


Purpose
The pgAdmin Development Team exists for 2 reasons:
To manage and maintain the
pgAdmin Project
To ensure that pgAdmin remains
freely available to anyone that wants it.
Structure
The foundation consists of the Project Leader and Members.
Project Leader: The
Project Leader is Dave Page, founder and primary developer of the
software. The Project Leader is also considered a member.
Members: Members can be
any contributor to the project who accepts an invitation from the
existing Development Team.
Division of Responsibilities
Any major decision regarding the Project must be voted on by the
Development Team. Any vote will be made via email through the relevant
mailling list. Responses not received within 2 weeks will be discounted
from the vote.
In the case of a hung vote, the Project Leader shall
cast the deciding vote.
People
The pgAdmin Development Team includes the following people:
- Dave Page (Project Leader): Project founder & primary developer.
- Hiroshi Saito: Produced a Japanese port of pgAdmin II, and countless patches for pgAdmin III.
- Raphaël Enrici: Maintains the Debian port, and helps with numerous other issues.
- Guillaume Lelarge: Manages the pgAdmin application and website translations, and has added a number of enhancements to pgAdmin.
- Erwin Brandstetter: Spends significant amounts of time testing new releases and helping us track down bugs and behavioural issues.
- Magnus Hagander: Has worked on numerous features and project infrastructure.
The following people no longer work on the project, but we remain grateful for their past contributions:
- Mark Yeatman: Works on controls and consults on UI design.
- Frank Lupo: Has made countless improvements to the pgAdmin II code from minor bug fixes to major enhancements.
- Jean-Michel Pouré: translations & web site management.
- Andreas Pflug: Has written vast amounts of pgAdmin III code and is responsible for much of its design.
- Adam H. Pendleton: Developed and maintains the build system, and helps with various porting issues.


{% load static %}
Online E-Learning Portal
{% if user.is_authenticated %}
Learn Naturally
Home
(current)
Dashboard
Log Out
Search
{% else %}
Learn Naturally
Home
(current)
Log In
Sign Up
Search
{% endif %} {% block content %} {% endblock content %}
×
Record Delete Confirmation ?
Do you want to delete the record ?
Delete
Cancel


What is it?
- Yacht sailing race first held in 1851
- No regular schedule
- Currently held by Oracle Team USA
The 2017 America's Cup
- 35th time the contest has been held
- Surrounded in controversy
- Will be held in Bermuda
- Challenger to be decided by qualifying races
The America's Cup World Series
- Race in a smaller AC45
- Chance to gather data
- Held all around the world, next races are in Toulon
Race Format
Fixed Sail Wing and Foiling
Sailing Upwind
Sailing Upwind
Why is the America's Cup Interesting?


| assign.N.sample {pmclust} | R Documentation |
This utility function samples data randomly from X.spmd
to form a relatively small subset of original data. The EM algorithm on the
smaller subset is topically performing fast and capturing rough structures of
entire dataset.
assign.N.sample(total.sample = 5000, N.org.spmd)
total.sample |
a total number of samples which will be selected from
the original data |
N.org.spmd |
the original data size,
i.e. |
This utility function performs simple random sampling without replacement
for the original dataset X.spmd
. Different random seeds should
be set before calling this function.
A list variable will be returned and containing:
N | total sample size across all S processors |
N.spmd | sample size of given processor |
N.allspmds | a collection of sample sizes for all S processors |
ID.spmd | index of selected samples ranged from 1
to N.org.spmd
|
Note that N
and N.allspmds
are the same across all
S processors, but N.spmd
and ID.spmd
are most
likely all distinct. The lengths of these elements are 1 for
N
and N.spmd
, S for N.allspmd
, and
N.spmd
for ID.spmd
.
Wei-Chen Chen<EMAIL_ADDRESS>and George Ostrouchov.
High Performance Statistical Computing (HPSC) Website: http://thirteen-01.stat.iastate.edu/snoweye/hpsc/
Programming with Big Data in R Website: http://r-pbd.org/
## Not run: # Save code in a file "demo.r" and run in 4 processors by # > mpiexec -np 4 Rscript demo.r ### Setup environment. library(pmclust, quiet = TRUE) comm.set.seed(123) ### Generate an example data. N.org.spmd <- 5000 + sample(1:1000, 1) ret.spmd <- assign.N.sample(total.sample = 5000, N.org.spmd) cat("Rank:", comm.rank(), " Size:", ret.spmd$N.spmd, "\n", sep = "") ### Quit. finalize() ## End(Not run)


| defer {withr} | R Documentation |
Similar to on.exit()
, but allows one to attach
an expression to be evaluated when exiting any frame currently
on the stack. This provides a nice mechanism for scoping side
effects for the duration of a function's execution.
defer(expr, envir = parent.frame(), priority = c("first", "last")) defer_parent(expr, priority = c("first", "last")) deferred_run(envir = parent.frame()) deferred_clear(envir = parent.frame())
expr |
|
envir |
|
priority |
|
defer()
works by attaching handlers to the requested environment (as an
attribute called "handlers"
), and registering an exit handler that
executes the registered handler when the function associated with the
requested environment finishes execution.
Deferred events can be set on the global environment, primarily to facilitate
the interactive development of code that is intended to be executed inside a
function or test. A message alerts the user to the fact that an explicit
deferred_run()
is the only way to trigger these deferred events. Use
deferred_clear()
to clear them without evaluation. The global environment
scenario is the main motivation for these functions.
# define a 'local' function that creates a file, and # removes it when the parent function has finished executing local_file <- function(path) { file.create(path) defer_parent(unlink(path)) } # create tempfile path path <- tempfile() # use 'local_file' in a function local({ local_file(path) stopifnot(file.exists(path)) }) # file is deleted as we leave 'local' local stopifnot(!file.exists(path)) # investigate how 'defer' modifies the # executing function's environment local({ local_file(path) print(attributes(environment())) }) # defer and trigger events on the global environment defer(print("one")) defer(print("two")) deferred_run() defer(print("three")) deferred_clear() deferred_run()


PackTravel package¶
Submodules¶
PackTravel.asgi module¶
ASGI config for PackTravel project.
It exposes the ASGI callable as a module-level variable named application
.
For more information on this file, see https://docs.djangoproject.com/en/4.1/howto/deployment/asgi/
PackTravel.settings module¶
Django settings for PackTravel project.
Generated by ‘django-admin startproject’ using Django 4.1.2.
For more information on this file, see https://docs.djangoproject.com/en/4.1/topics/settings/
For the full list of settings and their values, see https://docs.djangoproject.com/en/4.1/ref/settings/
PackTravel.urls module¶
PackTravel URL Configuration
- The urlpatterns list routes URLs to views. For more information please see:
- https://docs.djangoproject.com/en/4.1/topics/http/urls/
Examples: Function views
- Add an import: from my_app import views
- Add a URL to urlpatterns: path(‘’, views.home, name=’home’)
- Class-based views
- Add an import: from other_app.views import Home
- Add a URL to urlpatterns: path(‘’, Home.as_view(), name=’home’)
- Including another URLconf
- Import the include() function: from django.urls import include, path
- Add a URL to urlpatterns: path(‘blog/’, include(‘blog.urls’))
-
PackTravel.urls.
path
(route, view, kwargs=None, name=None, *, Pattern=<class 'django.urls.resolvers.RoutePattern'>)¶
PackTravel.wsgi module¶
WSGI config for PackTravel project.
It exposes the WSGI callable as a module-level variable named application
.
For more information on this file, see https://docs.djangoproject.com/en/4.1/howto/deployment/wsgi/


Dynamic programming approach for finding the longest weighted simple path from s to t .
• Sort the given directed acyclic graph in a topological manner.
• Calculate the longest path to the vertices one by one which should be sorted.
• Initialize the distance of start to zero which comes at first and last node which is named as .
• Pick a vertex at every iteration and compare for every vertex u that is connected to v via an edge and compute the longest path.
• There will be a sub-problem in every iteration that is used to find the simple weighted path which is longest from s to the current node v.
• Calculate all the vertices.
• is (or the maximum distance among all the vertices) is the longest weighted simple path from s to t.
To compute the longest path for every vertex:
• The given algorithm sorts the graph in a topological manner in such a way that it checks all the edges by visiting every vertex.
Efficiency of the algorithm:
• It takes which is the efficiency of the given algorithm.
Let A [1…n] denote the array that has the word “carac”. If a palindrome is a subsequence, it must be divided at any position say j and solve for the longest common subsequence problem A [1…j] which is the first subsequence and A [j+1…. n] which is the second subsequence. Therefore, there are n positions on which there is possibility of splitting input word and the longest common subsequence takes the time . The time for solving palindromes is
Algorithm: Find All Palindrome Subsequences(S)
Input: A string S=
Output: All palindrome subsequences of S.
1. //finding out matched pair
for i=1 to n
2. for j=i+1 to n do
3. if
4. W: = (i, j)
5.
6. //finding all palindrome subsequences of S
for k=2 to n/2
7.
8. for all k-1-pallindrome (…….from
Bitonic euclidean traveling-salesman problem:
In the travelling salesman problem a set of n points is given which represents the cities that are travelled by the salesman to sell his products. For this set of points we find the path which is shortest and connects all the n points. This is the NP-hard problem and so it possesses the polynomial time complexity.
A bitonic tour is a closed polygon chain in the Euclidean plane such that any vertical line will cross the chain at most twice. Open bitonic tour is a bitonic tour which has two end points so bitonic tour is an open bitonic tour with same end points.
For any two vertices in the set n the travelled distance or the length of path between two points is and OPTIMAL-BITONIC-SOLUTION(1, n) is used to calculate the best path with minimum weight for the bitonic tour as it will tell us the shortest open bitonic tour from vertex 1 to vertex n.
The possible cases while we go for calculating the solution for the travelling salesman problem are as:
Case 1:
if
Then the only possible path from i to j will be covering all the points in order. For calculating OPTIMAL-BITONIC-SOLUTION(i, j) we need to have all the points which are at the left of j. So there is only one single way in which this can be done and bitonic property is also maintained at the same time and that way is to take all the vertices in order of their increasing x coordinates.
In order to calculate OPTIMAL-BITONIC-SOLUTION(0, j)we need to calculate OPTIMAL-BITONIC-SOLUTION(0, j-1) which is as:
Case 2:
if
Then in order to reach j you have to come from j-1 so here also the recursion will go the same way as before. If you don't come from j-1 to then either j-1 will be an end point which is not possible because only end points are i and j or it could be connected to some point with less x coordinate which is also not possible because in that case it won't be bitonic any more.
Case 3:
if
In this case we have possible paths or possible vertices from which we can reach to vertex so we will choose that for which total cost is minimum. In other word
The procedure for the logic in case 3 is as:
1. for
2. if
3.
In this algorithm the variable min contains the shortest path.
Optimal Substructure:
The recursive relations are there in all the 3 cases in which the optimal solution to the problem comes from the optimal solution to the sub-problems.
So the problem is exhibiting the optimal substructure property.
Overlapping Sub-problems:
As for calculating the optimal solution to the problem we need to calculate various sub-problems many of the times which show overlapping sub-problems.The procedure for Optimal Bitonic Solution is as in which for all n points in the set,
, the path for will include all the points which are at left of j. Initialize all the elements in array M by
1. if
2. return
3. if or
// recursive calling to the function
4.
5. else
// initial value of shortest path
6.
7. for
8. if
9.
10.
11. return
Here the shortest path is calculated from vertex 1 to vertex n such that the summation of the weight of the edges included in the path is minimum. The number of vertices included are n so this algorithm takes a polynomial time which is.
Dynamic Programming
Dynamic programming is one of the techniques for designing algorithm, for providing the solution to optimization problems. Optimization problems are those in which there is a need to make number of decision. It is applied when sub-problems are dependent upon each other.
Dynamic Algorithm Plan:
The dynamics programming approach is applies to that problem in which there are problems of sub-problem are given. In this approach first the sub-problems are solved and then the results are used to solve the main problem.
If all the words fit in one line, then there is nothing to solve in the printing neatly problem. If the words exceed one line, then an optimal solution for a single line should be found as it is the only line to be filled.
Now, add up these optimal solutions for every line in the complete solution to find an optimum solution to that sub-problem. To print,words of length of characters the total number of characters are as:
Steps of Dynamic Programming: There are different steps which are used for creating algorithm for dynamic programming. These are as follows:
1. Determine the optimal solution’s structure.
2. Define the optimal solution’s value recursively.
3. Apply bottom-up approach for calculating the value of optimal solution.
4. By using calculated values develop an optimal solution.
Printing neatly: Printing neatly describes the rules for printing the paragraph in the formatted way that is all character having same width on a printer. It is required to print the paragraph of words of length characters and characters per line.
Criterion of “neatness” is as: a line contains words through where and only one space can be used between words. The number of spaces which are required additionally at the end of the line is and it must be a positive value.
Based on the above formatting rules; implementinga dynamic programming algorithm which can be used as to print the paragraph of n words and measurement of its running time and space requirement.
Illustration of printing neatly problem by using an example
“ Printing neatly describes the rules for printing the paragraph ”
Consider the above example and width of line M is 16. Optimized solution for the string is as follows:
Line 1: Printing neatly
Line 2: describes the
Line 3: rules for
Line 4: printing the
Line 5: paragraph
Optimized solution of the string comes in 5 lines.
Now, calculate the extra space in all the lines of the optimized arrangements.
Consider the following tabular structure for showing extra space within it corresponding line:
|
Line number |
Extra Space |
|
Line 1 |
1 |
|
Line 2 |
3 |
|
Line 3 |
7 |
|
Line 4 |
4 |
|
Line 5 |
7 |
From the above example, it is clear that all the lines used extra spaces. Due to extra spaces, total cost of all the lines and cost of one line are calculated as shown below:
Here, c is the cost of one line. Hence, cost for the line numbers from 1 to 5 is as below:
Here, T is the Total Cost of all the lines. Now, the total cost is:
From the example, it is clear that extra space consumption is more. So, it is needed to balance the extra spaces this is done with the help of cost function. This there can be represented in another ways by taking two same groups of words.
1. There are 5 lines and there are 5 extra spaces in one line and remaining line have no extra spaces.
Total extra spaces c= 5+0+0+0+0=5.
Total cost of all the line T=53 + 03 + 03 + 03 +03 =125
2. There are 5 lines and there is 1extra space in all the lines.
Total extra spaces c= 1+1+1+1+1=5.
Total cost of all the line T=13 + 13 + 13 + 13 + 13 =5
Thus in both the situations, there are 5 extra spaces, but second situation is preferred as spaces are maintained in consecutive 5 lines. As total cost function of second situation is less in comparison to the first situation.
PRINTING-NEATLY
The algorithm by considering the above dynamic algorithm plan and definition of printing neatly is as:
// checking that all words are filled in one line or more
1. if all words fit in one line
2. return “no need of formatting”
// j can be fit in line starting with word i.
(Now, try to fit all combinations in this line and then solve possible combinations of the remaining words; for finding the optimal layout, summation of minimum cost in first line and the remaining sub-problem is done)
// for words exceeding in more than one lines
3. else
// now taking a variable because space which are additionally needed at the end // of the line is and it must be a positive value
be the largest j for which
4. Fill an array of,
whereis the minimal cost of printing words i through n
// now comparing to number of elements in array of cost c
5 if
6. then
7. else
// now reducing the sum, in all lines leaving the last one, of the cubes of
// number of character of extra spacein the end of lines
Time requirement analysis:
For calculating the running time, consider the following points:
1. For the analysis of time complexity assume that for ,then . So, the length of the characters in the line , can be calculated in time.
2. In the end of each line there are some extra spaces left, which are for the words from i to j. As from the above point can be represented as so, the cost in line 4 of the algorithm can be calculated as:
The values, are already calculated, so it will take only time to calculate the cost of each line.
3. If all the words are comprised in the same line of paragraph then the line cost will be zero. In the line 7 of algorithm the cost is the overall optimal cost of printing the all the words in the paragraph.
4. Now, each line has maximum of M characters and there is one apace between each word then there will be maximum of words. So, the last line will have to j words.
So, the printing cost of a line can be summarized as the printing cost of words and the line cost and is represented as:
.
5. For printing words its cost will bewhich will be for n words.
The total running cost of the printing neatly problem will be the summation of all the costs:
But, M is constant for each line so the total running cost of the printing neatly problem is. Hence, the running time of this algorithm for printing n words in format is
Space requirement analysis: In the algorithm we have to store the values of, length of each word and cost of each lineand each will need space. So, the total required space will be. But, 3 is the constant so, it can be ignored. Hence, the total required space for printing in the format will be.
Edit distance:
Supposed strings are and
The problem of transforming one string into another string, then an intermediate array z, is uses a series of transformation operations.
At the termination of transformation
for.
Here j is the current position in array z and i is the current position in x and we examine each character in the array x so after transformation.
Edit distance problems are one the most famous dynamic programming problems having practical applications in spell checkers and dictionary searching.
Optimal Substructure:
For this problem of string transformation from one string to other using a set of transformation operations a slightly complex but easy to understand recurrence relation holds:
(
,
,
,
,
)
In this problem of finding edit distance the optimal solution for the sub-problems will yield optimal solution for the given problem. Hence the edit distance problem possesses the property of optimal substructure.
Overlapping sub-problems:
As most of the sub-problems will be repeated again and we solve the above recursion so
the problem possessesoverlapping sub-problems property and so it own both the properties that makes it dynamic programming solvable.
The algorithm for edit distance is as:
Initialize all the values for the 2D matrix M
1.
2. return 0
3.
4. return
5. else
6. (
,
,
,
,
)
7. returnThe total time required to run this algorithm in the transformation of anstring of length m to the string length n requires and the space to run this algorithm is required is.
b )
The optimal alignment of an edit distance using the some transformation operations as substitution, insertion, killing and twindle.
The edit distance uses the cost table
|
Operation |
Cost |
|
Copy |
–1 |
|
Replace |
+1 |
|
Delete |
+2 |
|
Insert |
+2 |
|
Twiddle |
|
|
Kill |
The DNA-alignment problem of string x to string y aligns the string sequences from any of the ends that is either it starts from left or from right end and releases the strings x’ and y’ after alignment.
For any alignment the different symbols are used in each process for example a space for the insert and the optimum alignment score is the largest of the minus value of the edit cost.The minus value of minimum edit cost is the negative value of the edit distance in the casting process.
The provided problem can be solved in linear time with the help of dynamic programming.
Suppose is the x employee conviviality and P is the set of employee. The provided problem is to determine the subset of employees whose sum of conviviality is more than any other subset, also subset contain either parent or its child.
Suppose the subset which contains list of these employees is.
In dynamic programming, if one wants optimal solution of a problem then it is required to find the optimal solution of a sub-problem of same form.
Consider the following sub problem:
Suppose is the maximum possible sum of conviviality of employee of x rooted sub-tree when x is also invited. Suppose is the maximum possible sum of conviviality of employee of x rooted sub-tree when x is also not invited.
The first equation contains the conviviality of all parents in x rooted sub-tree whereas the second equation contains the conviviality of all children in x rooted sub-tree.
The following algorithm is used to calculate the conviviality.
CALCULATE
1.
2.
3.
//loop continues iterate y is not null
4. while
5. do CALCULATE
//determine conviviality of presence and absence of y
6.
7.
8.
The above algorithm called with the president of the company. At the termination of the program the conviviality sum of the company get in terms of and . Now call following PARTY-LIST function to determine the list of guest which are called for the company party.
PARTY-LIST
//this part executes when employee get happy in presence of y
1. if
2. Add x in party_list
//check x have grand children or not
3. if x does not have grand children
4. DISPLAY(party_list)
5. EXIT()
6. for all grandchildren of
7. PARTY-LIST
//this part executes when employee get happy in absence of y
8. else
//check x have grand children or not
9. if x does not have children
10. DISPLAY(party_list)
11. EXIT()
12. for all children of
13. PARTY-LIST
The final COMP-PARTY algorithms call both above algorithm to determine list of employee which are called in the company party and where employee conviviality is maximum.
COMP-PARTY
Call CALCULATE
Call PARTY-LIST
Explanation:
• At first call the CALCULATE function to determine the conviviality of each node when it is added in list and when it is not added in the list.
• After that, call PARTY-LIST algorithm to check whether conviviality of adding an x employee in list is more than conviviality of not adding employee in list.
• The employee name stored in the party_list contains the name of the employee which is invited in the party.
Time complexity:
• The CALCULATE procedure traverse the whole set P which contains n employees. A while loop is used in CALCULATE which repeatedly call CALCULATE procedure n times.
Therefore the time complexity of CALCULATE procedure is.
•
When n is too large. Therefore the time complexity of PARTY-LIST procedure is.
Hence, the total complexity of COMP-PARTY is .
Seam Carving
In order to understand image compression by seam carving, it is necessary to know about seam and seam carving.
Seam : Seam is defined as connection of the pixel to form a path which is connected either by going from top to bottom or from left to right.
There are two types of Seam which are as follows:
1. Vertical seam: Vertical seam in an image is defined as a connection of the pixel to form a path by going from top to bottom. From each and every row it selects one pixel.
2. Horizontal seam: Horizontal seam in an image is defined as a connection of the pixel to form a path by going from left to right. From each and every row it selects one pixel.
Seam carving: Seam carving is a method which helps in resizing images and videos. It is a technique which helps in preserving undesirable distortion of the image. In this, remove the pixels which are not so important in order to create an image of the smaller size.
Process of Seam carving
Computation of the energy: Energy of the pixels provides the information about the important of the pixel. Energy function is directly proportional to the important of the pixel. If pixel is of less energy than it is least important otherwise it is of more important.
Energy function is calculated by adding the horizontal and vertical seam value at each and every point with the help of filter of size 3 3.
Here, represents the vertical seam and represents the horizontal seam. In this energy of each pixel is represented by energy matrix.
Dynamic Programming: Dynamic programming helps in finding horizontal or vertical seam which has lesser energy function. Firstly create a matrix M for storing the values of each pixel. After that find the seam which have minimum energy from each row except the first row.
Now, minimum value of the bottom row is extracted from the matrix. Backtrack the traversing of the matrix for finding minimum value of the seam from each and every row.
Making a smaller image: For creating an image of smaller size; least important pixels in values is removed. This helps in maintaining the continuity in the image.
Repeat all the above steps till the images is not compressed into required size.
Image compression by seam carving:
In the Image compression by seam carving there is a color picture of array of pixels and every pixel specifies a triple of RGB (red, blue, and green) intensities. Compressing this picture and removing one pixel from each of m rows, and the picture compressed one pixel narrow.
In this compression process the visual effect is avoided by removing the pixels from the adjacent pixels and those pixels are arranged diagonally or vertically so that they can make a seam.
In this problem, the objective is to prove that in the compression process, the seam grows exponentially.
In order to prove this, find the valid seams from each and every row which is the function of matrix M and establish a recurrence for valid seams.
Here, assume that in the method of seam carving, seam is carved out from each row. Carving of the seam starts from first row and the last pixels which is carved out is
A [i, j]
If the pixel lies on boundary of the column for which of i lies between the ranges from 1 to n. If the value of i is 1, then two choices are there for choosing next pixel are as follows: and.
Otherwise, there are three choices for selecting next pixel which are as follows, and.
Suppose, represents the total number of valid seams from first row to the last row.
Start from first row where value of i=1, When value of i=1 then.
By using direct substitution method it can be proved that in the compression process the seam grows exponentially.
When value of i is greater than 1 then value of is as shown:
By using direct substitution method it can be proved that in the compression process, the seam grows exponentially.
Hence, it is proved that compression process the seam grows exponentially.
b.
The algorithm for finding the seam with lowest measure of disruption in the removal process of pixels from seam: For every pixel in a single row, there are minimum of 2 pixels in the upcoming row; so there will be at least number of seams present.
The value of disruption, the measures of is defined as .
An algorithm to find a seam with the lowest disruption measure is shown below:
In this algorithm the seam array and minimum disruption array B is initialized first as per their pixels using the real valued disruption measure d. So here, two levels of checks are used; first depends upon the seam, and the second depends upon the disruption array B.
Inherently, there will be more similarities with the neighboring pixel if the measure of the disruption of that pixel is lower.
The algorithm for the calculation of minimum disruption seam is shown below:
MINIMUM-DISRUPTION-SEAM
1. S is an array of size m to store the seam
2.
Such that is the minimum of pixels
// accessing each element of seam starting from end in the decreasing order
3. for down to 2
// checking the element of seam array for the value 1
4. if
// comparing two consecutive the elements of disruption array B
5. if
// updating the value of seam array
6.
7. else
// checking if the ith element of seam is n
8. else if
// comparing two consecutive the elements of disruption array B
9. if
// updating the value of seam array
10.
11. else
// finding the new value of j for which B is smallest
12. else
Find j such that with smallest
13.
The above algorithm takes space to run because it needs to maintain array of size and the building of seam in step 4 takes time.
So, the algorithm runs efficiently for finding the minimum disruption seam in time.
Illustration of seam carving with the help of example:
Consider the following diagram.
In the above diagram firstly find the minimum energy pixel in the first row of the matrix. Here, 2 is the minimum energy pixel in the first row.
It lies on the boundary of the column so there are two choices which are 2 and 9 for selecting the next pixel. 2 is the minimum value among the two choices. Compute minimum cost of the seam by using the given formula:
Now move to the next row and select 9. Here, 9 lies on the starting of the column so, there are two choices.
Now, move to the next column and select 1. Here, 1 does not lie on boundary column so it has 3 choices. Compute minimum cost of the seam by using the given formula:
Now, move to the next column and select 2. Here, 2 do not lie on boundary column so it has 3 choices.
Compute minimum cost of the seam by using the given formula:
Similarly, compute minimum cost of all the pixels of the matrix is shown by the diagram:
Now, backtracking mechanism is used to find minimum value of the seam from each and every row.
In the above diagram, backtracking will be started by finding the minimum valued pixel from the last row. Here, 11 is the minimum value in the last row.
Here, 11 lies on the starting of the column so there are two choices which are 11 and 8. Here minimum value is 8 so, select 8 from the third row.
Here, 8 does not lie at the starting of the column so there are three choices which are 13, 5 and 6. Here, minimum value is 5 and thus, select 5 from the second row.
Here, 5 does not lie on the starting of the column so, there are three choices which are 4, 7 and 11. Here, minimum value is 4 and thus, select 4 from the first row.
String breaking problem
Consider S is the string with n characters and is the array that contains the break points. Breaking a string of n characters, the algorithm takes n time.
The below defined recursive algorithm is the string breaking algorithm that computes the lowest cost for a sequence breaks.
Where,
• l and m are the starting and ending indexes of the break points array respectively.
• i and j are the starting and ending indexes of the string S array respectively.
• q is the required least cost.
BREAKING-STRING (L,l,m,i,j)
// Number of characters in the sub string
1 n=j-i+1
2 if i > j or l > m
3 return 0
4 if l= =m
5 if L[l] ≤ i and L[l] ≥ j
6 return 0;
// large positive integers
7 q= + ∞
8 for k= l to m
9 if k = = m
10 q= min(q,n+ BREAKING-STRING(L,l,k-1,i,L[k])
+ BREAKING-STRING(L,m,m,L[k]+1,j));
11 elseif k = = l
12 q= min(q,n+ BREAKING-STRING(L,l,l,i,L[k])
+ BREAKING-STRING(L,k+1,m,L[k]+1,j))
13 else
14 q= min(q,n+ BREAKING-STRING(L,l,k,i,L[k])
+ BREAKING-STRING(L,k+1,m,L[k]+1,j));
15 return q;
The algorithm consists of the basic consideration of recursive calling of the algorithm and the running time of loop used inside the algorithm.
This is the problem of dynamic programming and problem is broken into sub problems so the running time of this algorithm is.
a.
Assume that there exists a solution which is optimal and represented by S, without any loss in generality.
In the solution, within 1 year, assume that dollar is invested for the investment represented by k. And, is invested in the investment represented by m.
Now, suppose that no money is moved for the first j years.
If the following is true, then perform usual cut and paste maneauver and instead invest the sum of the initial dollars for the k investment for j years.
If the investments are same, then it would may result to a strategy which is at-least as profitable as the solution S.
But decrease the number of investments done under the time of 1 year.
Continuously doing this, the chance of considering only a single investment in a year by the optimal strategy will decrease.
b.
For a strategy which is optimal, if an investment is consider for one year then one must solve the following two subproblems.
The two subproblems are as follows:
• Without suffering with the movement of money fee, for one additional year a strategy needs to be maintained.
• The second one is that move the money which is used to resolve the problems where all the information of year 1 is ignored.
Thus, an optimal substructure is exhibited.
c.
The algorithm for optimal investment strategy is as follows:
Initialize the tables I and R with all filled with zero.
//Begin the for loop
for i = 10 downto 1 do
a = 1
for j = 1 to n do
if then
//j contain the investment that is best for the
//given year
a = j
end if
end for
if then
//When the money is not being moved, the
//revenue is higher
else
end if
end for
Return I which is an optimal strategy with return R[1].
The working of the above algorithm is explained below:
Create two tables I and R of size 10 such that the index i of the table I means I[i] represents the investment of the year i, and R[i] represents the overall return in the investment done between the year i to 10.
d.
• The investment strategy that is being taken was not depend on the starting amount.
• The amount which is going to be invest in the next year become relevant, if there is a cap on the investment amount.
• If the year-one-strategy of the optimal strategy is known, and aware about the fact that after one year, one need to move the money, the problem of investing different amount money will be resolved.
• And, hence, for every initial amount of money which is possible one need to solve the subproblems.
Since, there is no bound on the number of subproblems and the returns.
Inventory planning:
The Rinky Dinky Company manufactures machines that resurface the ice rinks and the demand of these machines varies from month to month. So the company wants to create a plan for next n months which can give it the idea that what quantity of machines should be manufactured so that the demand can be fulfilled.
For the month the demand is d which is for next n months.
The company keeps a staff for full time which manufactures m machines in a month and if the company wants to create more than m machines in a month then it hires some more labors and the cost for these is c dollars per machine.
Furthermore, if any machine in a month do not sold then it will be keep in the inventory and the cost of this inventory is paid by the company.
The inventory cost for holding j machines is represented in the form of a functionfor where for and for.
Now developing a procedure plan for the company in the form of algorithm so that company can reduce its costs at the same time fulfills the demand of the machines in next n month and it has polynomial running time in the terms of n and D.
The algorithm for finding the total cost of manufacturing company is designed by using the dynamic programming technique.
The variables used in the algorithm are as:
COST(k)
if
// returns the cost of k machines
return R
return
A tricky recursion in two variables can be developed for the problem which is as:
MIN-COST(i, j)
1.
2.
3.
4. return min
As the optimal solution for the sub-problems yields an optimal solution for the problem, so this cost calculation procedure exhibits the property of optimal substructure. And the above recursion shows that a lot of problems have to solve again and again that is for the company the cost is calculated for each month so the problem also exhibits the property of overlapping sub-problems.This problem of finding cost exhibits both the property of being dynamic programming solvable,
The following is the dynamic programming solution for the problem.
MIN-COST(i, j)
1.
2. return
3. for
4. if
5.
6.
7.
8. return min
This algorithm has a for loop which runs for D on n numbers so the time complexity of this algorithm is and the total space taken used in the memory is also in the form of D which is.
In the problem of signing free-agent baseball players a general manager of team is allowed to spend no more than X dollars to sign some players in the off-season. There are N positions in the team and for each position P players can be signed.
The manager do not want to overload the roster so for each position he signs only one player and if he do not sign any player to a position then he sticks to the old players for that position.
The value of the player for any position is measured by the sabermetric statics which is also known as VORP that is the value of the player which is required to make him safe from replacement and the player with higher VORP is more valuable and he can be less expensive.
For a free agent player the information is as:
1. The post at which the player is signed.
2. The total cost to the signed player.
3. The VORP value of player.
Now, create a procedure for the players of baseball team so that total VORP is maximized for the player within dollars X that are decided to spend by assuming that each signed player costs in the multiple of dollar 1 lacks.
Suppose a 2-D array M having N rows and P columns. Each row of array stores the P player detail that plays at ith position. Each player object contains three attributes which stores VORP, cost and position of player.
Declare another object final which also store three attributes: VORP, Total spend money and a list to store name of employee.
The following algorithm returns the variable final which store maximum VORP, total money spend and the list of signed players:
//check amount exhausted
1. if or
2. return final
3.
4.
//use loop to check VORP of each player
5. for to
//check VORP of jth player who plays at ith position.
6. if
7.
//store the calculated result in final object
8.
9.
10. Add person name in
//Recursive call of function
11.
Space and Time complexity:
• In above algorithm a 2-D array M is used to store player’s details. Therefore the space complexity of above algorithm is
• A for loop is used in above algorithm which iterate P times. At the end of procedure a function call itself.
Therefore the space complexity of above algorithm is


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Port Radio (call sign 60Y) monitors MF 500 KHz and should be contacted to advise a yacht on procedure.


| Library: | Memory |
| Introduced: | 2.3.0 |
| Appearance: |
This component iterates through a pseudorandom sequence of numbers, which steps forward to the following number in the sequence each time the clock is triggered while the component is enabled. Technically speaking, the algorithm used to compute the pseudorandom sequence is a linear congruential generator: Starting from a seed r0, the following number r1 is the number
The next value r2 is computed from r1 using the same computation, and so forth. This sequence is of 48-bit numbers; the value seen from the component is the low-order bits as configured by its Data Bits attribute, after first throwing out the lower 12 bits of the current seed.
Besides the clock input, the component also includes an enable input, which leads the clock input to be ignored when enable is 0, and the reset input, which resets the component's value asynchronously to the initial seed r0.
The initial seed is user-configurable. If it is configured at 0 (which is the default), then the seed is based on the current time; when instructed to reset through the reset input, the component computes a new seed based on the new current time.
When the component is selected or being added,
Alt-0 through Alt-9 alter its Data Bits
attribute.
rising edgeindicates that the component should update its value at the instant when the clock rises from 0 to 1. The
falling edgevalue indicates that it should update at the instant the clock falls from 1 to 0.
None.
Allows the label associated with the component to be edited.


Hi all.
What I would like to do is have to arduino mini's, one with a CT and the other with the AC adapter. Send both values to a Pi and do the calculations there. My meter box does not have and outlet.
Is it possible to do?
Archived Forum |
|
measuring mains voltage and currentSubmitted by vk1em on Mon, 20/04/2015 - 10:48Hi all. What I would like to do is have to arduino mini's, one with a CT and the other with the AC adapter. Send both values to a Pi and do the calculations there. My meter box does not have and outlet. Is it possible to do? » |
Re: measuring mains voltage and current
Yes, but you will measure the voltage and current independently, therefore you will be able to calculate only apparent power (VA), not real power (W). See Building Blocks.
I presume you cannot access voltage and current from the same place - not necessarily at the meter?
Re: measuring mains voltage and current
Not possible as the location of the meter is outside and no where near a power source.
I only have access to the active wire from the meter to the fuse box. The PV active is connected to the fuse box and I cannot get to it either. I am currently collecting the pv output directly from the SMA inverter.
I just need a ct value that can provide me with a positive and negative value.
Re: measuring mains voltage and current
"I just need a ct value that can provide me with a positive and negative value."
By that, do you mean you need to know the direction of power flow? If that's the case, you absolutely need to measure voltage and current in one place using the emonLib real power calculations or an equivalent. If you measure voltage and current independently, you do not know the timing relationship between them and you cannot know their relative phase, which is what tells you the direction of power flow.
What prevents you from installing a power outlet at or within reach of the fuse box? Can you get a thin (3 mm diameter) cable from the fuse box to a place where there is a power outlet?
Re: measuring mains voltage and current
Here in Australia most fuse boxes are installed on an external wall. As for a power point at the fuse box, unlikely to happen either.
To run a 3mm cable from the fuse box to a suitable power source would require something in the order of a 10mtr run of cable. The local power authority here is very particular about who plays in the fuse box. This is why I have asked the question.
The guy who installed my upgrade did not do me any favors when he installed the equipment. I cannot get access to just the house active leads either.
Re: measuring mains voltage and current
I can think of a way, but it'll require some construction and a fairly big battery to get a decent life:
You need a capacitive pickup to detect the voltage - it's been discussed here before, try a search, and a normal emonTx slightly modified to accept the different voltage input. As far as I know, all the parts have worked individually, but never been put together as a system. If that appeals, let me know.
Re: measuring mains voltage and current
Robert.
More than happy to try and build something to give me a result.
Any assistance is appreciated .
Mark
Re: measuring mains voltage and current
As for a power point at the fuse box, unlikely to happen either.
That's a fairly easy problem to solve. I've got a tame sparkie who was out doing other work and added the outdoor GPO pretty much for the price of the weatherproof outlet. Going with the double means I've now got a spare out there for other use. I've also seen quite a few Australian fuse boxes with a low profile outlet installed right on the meter board inside the box.
Re: measuring mains voltage and current
If you don't have a cooperative sparkie, then take a look here for starters.
It assumed that the ADC input was using the internal reference of 1.1 V, not AVcc (3.3 V) as is standard. (That's the reason for the input being biased to around ½ V, not half the supply voltage.) It's worth reading all of that thread.
The op.amp needs to be single rail, with rail-rail input, and low supply current (for best battery life). If you're using the "discrete samples" sketch, you could feed the op.amp from the temperature sensor supply and switch it on only while you're sampling.


REGEX goes here ... <enter> to highlight
Modified regex goes here ...
| Basics | |
|---|---|
| . | Any character except newline |
| a | The character a |
| ab | The string ab |
| a|b | a or b |
| a* | 0 or more a's |
| \ | Escapes a special character |
| Quantifiers | |
|---|---|
| * | 0 or more |
| + | 1 or more |
| ? | 0 or 1 |
| {2} | Exactly 2 |
| {2,5} | Between 2 and 5 |
| {2,} | 2 or more |
| Groups | |
|---|---|
| (...) | Capturing group |
| (?:....) | Non capturing group |
| \Y | Match the Y'th captured group |
| Character classes | |
|---|---|
| [ab-d] | One character of: a,b,c, d |
| [^ab-d] | One character except: a, b, c, d |
| [\b] | Backspace character |
| \d | One digit |
| \D | One non digit |
| \s | One whitespace |
| \S | One non-whitespace |
| \w | One word character |
| \W | One non-word character |
| Assertions | |
|---|---|
| ^ | Start of string |
| $ | End of string |
| \b | Word boundary |
| \B | None word boundary |
| (?=...) | Positive lookahead |
| (!=...) | Negative lookahead |
| Flags | |
|---|---|
| g | Global match |
| ! | Ignore case |
| m | ^ and $ match start and end of line |
| Special Characters | |
|---|---|
| \n | Newline |
| \r | Carriage return |
| \t | Tab |
| \YYY | Octal character YYY |
| \xYY | Hexadecimal character YY |
| \uYYYY | Hexadecimal character YYYY |
| \cY | Control character Y |
| Replacement | |
|---|---|
| $$ | Inserts $ |
| $& | Insert entire match |
| $` | Insert preceding string |
| $' | Insert following string |
| $Y | Insert Y'th captured group |


Purpose
This site is intended for use by software developers looking to build a conformant GP Connect API interface using the FHIR® standard with a focus on general API implementation guidance.
Notational conventions
The keywords ‘MUST’, ‘MUST NOT’, ‘REQUIRED’, ‘SHALL’, ‘SHALL NOT’, ‘SHOULD’, ‘SHOULD NOT’, ‘RECOMMENDED’, ‘MAY’, and ‘OPTIONAL’ on this site are to be interpreted as described in RFC 2119.
General standards
Information on the technical standards that SHALL be conformed to can be found in the sections below and throughout the GP Connect specification.
Internet standards
Clients and servers SHALL be conformant to the following Internet Engineering Task Force (IETF) request for comments (RFCs), which are the principal technical standards that underpin the design and development of the internet and thus FHIR’s APIs.
- transport level integration SHALL be via HTTP as defined in the following RFCs: RFC 7230, RFC 7231, RFC 7232, RFC 7233, RFC 7234 and RFC 7235
- transport level security SHALL be via TLS/HTTPS as defined in RFC 5246 and RFC 6176
- HTTP Strict Transport Security (HSTS) as defined in RFC 6797 SHALL be employed to protect against protocol downgrade attacks and cookie hijacking
RESTful API
The RESTful API described in the FHIR® standard is built on top of the Hypertext Transfer Protocol (HTTP) with the same HTTP verbs (GET
, POST
, PUT
, DELETE
, etc.) commonly used by web browsers. Furthermore, FHIR exposes resources (and operations) as Uniform Resource Identifiers (URIs). For example, a Patient
resource /fhir/Patient/1
, can be operated upon using standard HTTP verbs such as DELETE /fhir/Patient/1
to remove the patient record.
The FHIR RESTful API style guide defines the following URL conventions which are used throughout the remainder of this document:
- URL pattern content surrounded by [ ] are mandatory.
- URL pattern content surrounded by { } are optional.
Service Root URL
The Service Root URL is the address where all of the resources defined by this interface are found.
The Service Root URL is the [base]
portion of all FHIR APIs.
Service Root URL versioning
Service Root URLs SHALL be aligned with the GP Connect specification they were built against, specifically the major version number SHALL be present in the server’s Service Root URL to provide a clear distinction between API versions that are incompatible (i.e. contain breaking changes) vs. backwards-compatible (i.e. contain no breaking changes).
Provider systems SHALL publish Service Root URLs for major versions of FHIR APIs in the Spine Directory Service in the following format:
https://[FQDN of FHIR Server]/[ODS_CODE]/[FHIR_VERSION_NAME]/[GPC_MAJOR_VERSION]/[PROVIDER_ROUTING_SEGMENT]
-
[FQDN_OF_FHIR_SERVER]
is the fully qualified domain name where traffic will be routed to the logical FHIR server for the organisation in question -
[ODS_CODE]
is the Organisation Data Service code which uniquely identifies the GP Practice organisation -
[FHIR_VERSION_NAME]
refers to the textual name identifying the major FHIR version, examples beingDSTU2
andSTU3
. The FHIR Version name SHALL be specified in UPPERCASE characters. -
[GPC_MAJOR_VERSION]
identifies the major version number of the GP Connect specification that the API is built to. -
[PROVIDER_ROUTING_SEGMENT]
enables providers to differentiate between GP Connect and non-GP Connect requests (for example, via a load balancer). If included, this optional provider routing segment SHALL be static across all the provider’s GP Connect API endpoints. -
The Service Root URL SHALL NOT contain a trailing
/
Example Service Root URL
The provider SHALL publish the Service Root URL to Spine Directory Services, for example:
https://provider.nhs.uk/GP0001/STU3/1/gpconnect
Please see Registering GP Connect systems in SDS for more details.
Consumer systems are required to construct a Service Root URL containing the SSP URL followed by the FHIR Server Root URL of the logical practice FHIR server that is suitable for interacting with the SSP service. API provider systems will be unaware of the SSP URL prefix as this will be removed prior to calling the provider API endpoint.
The consumer system would therefore issue a request to the new version of the provider FHIR API to the following URL:
https://[ssp_fqdn]/https://provider.nhs.uk/GP0001/STU3/1/gpconnect/[FHIR request]
Resource URL
The Resource URL will be in the following format:
VERB [base]/[type]/[id] {?_format=[mime-type]}
Clients and servers constructing URLs SHALL conform to RFC 3986 Section 6 Appendix A which requires percent-encoding for a number of characters that occasionally appear in the URLs (mainly in search parameters).
HTTP verbs
The following HTTP verbs SHALL be supported to allow RESTful API interactions with the various FHIR resources:
- GET
- POST
- PUT
- DELETE
Resource types
GP Connect provider systems SHALL support FHIR resource types as detailed within the FHIR Resource Guidance.
Resource ID
This is the logical Id of the resource which is assigned by the server responsible for storing it. The logical identity is unique within the space of all resources of the same type on the same server, is case sensitive and can be up to 64 characters long.
Once assigned, the identity SHALL never change. logical Ids
are always opaque, and external systems need not and should not attempt to determine their internal structure.
logical Ids
are opaque and other systems should not attempt to determine their structure (or rely on this structure for performing interactions). Furthermore, as they are assigned by each server responsible for storing a resource they are usually implementation specific. For example, NoSQL document stores typically preferring a GUID key (for example, 0b28be67-dfce-4bb3-a6df-0d0c7b5ab4) while a relational database stores typically preferring an integer key (for example, 2345).For further background, refer to principles of resource identity as described in the FHIR standard
External resource resolution
In line with work being undertaken in other jurisdictions (see the Argonaut Implementation Guide for details) GP Connect provider systems are not expected to resolve full URLs that are external to their environment.
Content types
- Servers should support both formal MIME-types for FHIR resources:
- Servers SHALL support JSON:
application/fhir+json
- Servers SHOULD support XML:
application/fhir+xml
- Servers SHALL support JSON:
-
Servers SHALL support the optional
_format
parameter in order to allow the client to specify the response format by its MIME-type. If both are present, the_format
parameter overrides theAccept
header value in the request. -
Where no
Accept
header or_format
parameter is sent with a request but there is aContent-Type
header, such as in a POST request, the server SHALL return the response using the format type within theContent-Type
header. - Where no
Accept
header,_format
parameter and noContent-Type
header is present, as is possible within a GET request, the server SHALL default to JSON.
Wire format representations
Servers should support two wire formats as ways to represent resources when they are exchanged:
Consumers SHALL ignore unknown extensions and elements in order to foster forwards compatibility and declare this by setting CapabilityStatement.acceptUnknown to ‘both’ in their capability statement.
Systems SHALL declare which format(s) they support in their CapabilityStatement. If a server receives a request for a format that it does not support, it SHALL return an HTTP status code of 415
indicating an Unsupported Media Type
.
Transfer encoding
Clients and servers SHALL support the HTTP Transfer-Encoding header with a value of chunked
. This indicates that the body of a HTTP response will be returned as an unspecified number of data chunks (without an explicit Content-Length
header).
Character encoding
Clients and servers SHALL support the UTF-8
character encoding as outlined in the FHIR standard.
FHIR uses
UTF-8
for all request and response bodies. Since the HTTP specification (section 3.7.1) defines a default character encoding ofISO-8859-1
, requests and responses SHALL explicitly set the character encoding toUTF-8
using thecharset
parameter of the MIME-type in theContent-Type
header. Requests MAY also specify this charset parameter in theAccept
header and/or use theAccept-Charset
header.
Where the character encoding is included with the “Content-Type” or “Accept” header there should not be a space between the MIME-type and the character encoding, as per the standard for these headers (rfc2616).
Content compression
To improve system performances clients/servers SHALL support GZIP compression.
Compression is requested by setting the Accept-Encoding
header to gzip
.
Inter-version compatibility
Unrecognized search criteria SHALL always be ignored. As search criteria supported in a query are echoed back as part of the search response there is no risk in ignoring unexpected search criteria.
HTTP headers
Proxying headers
Additional HTTP headers SHALL be added into the HTTP request/response for allowing the proxy system to disclose information lost in the proxying process (for example, the originating IP address of a request). Typically, this information is added to proxy forwarding headers as defined in RFC 7239.
Cross-organisation provenance and audit headers
To meet auditing and provenance requirements (which are expected to be closely aligned with the IM1 requirements), clients SHALL provide an oAuth 2.0 Bearer token in the HTTP Authorization header (as outlined in RFC 6749) in the form of a JSON Web Token (JWT) as defined in RFC 7519.
Refer to Integration - cross-organisation audit and provenance for full details of the JWT claims that SHALL be used for passing audit and provenance details between systems.
Clients SHALL add the following Spine proxy headers for audit and security purposes:
Ssp-TraceID
- TraceID (generated per request) which identifies the sender’s message/interaction (for example, a GUID/UUID).Ssp-From
- ASID which identifies the sender’s FHIR endpoint.Ssp-To
- ASID which identifies the recipient’s FHIR endpoint.Ssp-InteractionID
- identifies the FHIR interaction that is being performed 1
1 please refer to the Development - FHIR API guidance - operation guidance for full details.
The SSP SHALL perform the following checks to authenticate client request:
- get the common name (CN) from the TLS session and compare the host name to the declared endpoint
- check that the client/sending endpoint has been registered (and accredited) to initiate the given interaction
- check that the server/receiving endpoint has been registered (and accredited) to receive/process the given interaction
Caching headers
Providers SHALL use the following HTTP header to ensure that no intermediaries cache responses: Cache-Control: no-store
Managing Return Content
Provider SHALL maintain resource state in line with the underlying system, including the state of any associated resources.
For example:
If the practitioner associated with a schedule is changed on the provider’s system, such as when a locum is standing in for a regular doctor, this should be reflected in all associated resources to that schedule. The diagram below shows the expected change to the appointment resources for this scenario.
When the appointment is booked, the appointment resource is associated with a slot resource and references the practitioner resource associated with the schedule in which the slot resides. If the schedule is then updated within the provider system to reflect the change of practitioner from the original doctor to a locum doctor, then the practitioner reference with the schedule will be updated. If a consumer then performs a read of the appointment the returned appointment resource should reflect the updated practitioner on the schedule.
Servers SHALL default to the return=representation
behaviour (that is, returning the entire resource) for interactions that create or update resources.
Servers SHOULD honour a return=minimal
or return=representation
preference indicated in the Prefer
request header, if present.
Demographic cross-checking
Consumer systems SHALL compare the returned structured patient demographic data (supplied by the provider system as structured data) against the demographic data held in the consumer system.
The following data SHALL be cross-checked between consumer and returned provider data. Any differences between these fields SHALL be brought to the attention of the user.
| Item | Resource field |
|---|---|
| Family name | patient.name.family |
| Given name | patient.name.given |
| Gender | patient.gender |
| Birth date | patient.birthDate |
Additionally, the following data MAY be displayed if returned from the provider to assist a visual cross-check and for safe identification, but should not be part of the automatic comparison:
- Address and postcode
- Contact (telephone, mobile, email)
All above may be redacted if patient is flagged on Spine as sensitive demographics.
Managing resource contention
To facilitate the management of resource contention, servers SHALL always return an ETag
header with each resource including the resource’s versionId
:
HTTP 200 OK
Date: Sat, 09 Feb 2013 16:09:50 GMT
Last-Modified: Sat, 02 Feb 2013 12:02:47 GMT
ETag: W/"23"
Content-type: application/json+fhir
ETag
headers which denote resource version Id
s SHALL be prefixed with W/
and enclosed in quotes, for example:
ETag: W/"3141"
Clients SHALL submit update requests with an If-Match
header that quotes the ETag
from the server.
PUT /Patient/347 HTTP/1.1
If-Match: W/"23"
If the version Id
given in the If-Match
header does not match, the server returns a 409
Conflict status code instead of updating the resource.
For servers that don’t persist historical versions of a resource (that is, any resource other than the currently available/latest version) then they SHALL operate in line with the guidance provided in the following Hay on FHIR - FHIR versioning with a non-version capable back-end blog post. This is to ensure that GP Connect servers will be compatible with version-aware clients, even though the server itself doesn’t support the retrieval of historical versions.
Managing return errors
To manage return errors, FHIR defines an OperationOutcome resource that can be used to convey specific detailed processable error information. An OperationOutcome
may be returned with any HTTP 4xx
or 5xx
response, but is not always required.


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The Compiler's Treatment of LINQ Syntax
When LINQ first became available, it was described as having a “lazy evaluation model”, meaning that a query would not actually be executed until you started to look at the result. Iterating through a result, for instance, would finally cause the query to actually run. This gives you the power to piece together a query over multiple statements before letting it execute.
Recently, I found that this abstraction can leak. I had a set of queries that were misbehaving, and it seemed that a bug would be reproducible in one set of queries but not in another, even though they were remarkably similar to each other in structure. The culprit was a big surprise: it turns out that the first ‘from’ clause in a query is treated differently from subsequent ‘from’ clauses. Although my project’s ‘from’ clauses were not implemented with side effects, an example that does use side effects best illustrates what is going on. Consider the following:
If we trusted the explanations of LINQ queries as having a lazy evaluation model, we would expect the output to be:
Before Loop First Clause Side Effect Second Clause Side Effect Third Clause Side Effect 3
We expect this because we’re told that the query doesn’t start doing any work until we start iterating throught the results. Surprisingly, the actual output is:
First Clause Side Effect Before Loop Second Clause Side Effect Third Clause Side Effect 3
Yikes. The SQL-like query syntax is an abstraction over plain old method calls, and that abstraction is leaking. To make sense of what is going on, it is helpful to know what the compiler does every time it encounters query syntax. Before the compiler even bothers to determine whether your query is actually valid, it performs a plain text transformation to a series of specially-nested method calls. Only after that plain text transformation will it actually determine whether the methods being called exist, that the arguments passed to them are of the right type, etc. ReSharper can actually perform that transformation for you. When we do that to the query above, we get the following:
A query with multiple ‘from’ clauses is transformed into a series of nested method calls. Lambda expressions are used to introduce a new local scope for the identifiers x, y, and z. SelectMany is an extension method, so the specific implementation is irrelevant during the plain text transformation. In other words, you can define the query syntax yourself, based on the type of the object you are selecting from (in this case, we’re using the default IEnumerable<T> implementation of SelectMany).
The right hand side of the first from clause is evaluated immediately. Subsequent from clauses are evaluated lazily, because only they appear on the right hand side of a lambda operator =>.
By better-understanding what the compiler is actually doing with our LINQ queries, we can avoid frustrating surprises when the abstraction starts leaking.
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