DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Plans for a National Teaching Service to provide elite teachers to struggling areas announced.
Education Secretary Nicky Morgan will announce tomorrow (3 November 2015) the next phase of the government’s education reform programme with a package designed to tackle underperformance and deliver on the government’s commitment to give every child an excellent education.
Thanks to the education reforms of the past 5 years, significant progress has been made in raising standards, with a million more pupils in ‘good’ or ‘outstanding’ schools compared to 2010; but too many places are lagging behind, meaning young people in these areas are not being given a fair shot.
Latest figures show more than 20 local authorities where the majority of pupils are still unable to secure 5 good GCSEs , despite an improving picture across the country.
They include:
In a speech at the Policy Exchange think tank tomorrow, Nicky Morgan will set out details for reforms which will help ensure high standards throughout every child’s education and tackle entrenched underperformance - delivering on the government’s commitment to give every child the security and opportunity of an excellent education.
Education Secretary Nicky Morgan said:
Over the past 5 years we’ve extended opportunity to thousands of young people, through raised standards, heightened expectations and a rigour revolution.
But for all we’ve achieved, too many young people aren’t being given a fair shot to succeed because of where they live. That’s why today I’m announcing the creation of a National Teaching Service - sending some of our best teachers to schools in struggling areas.
At the same time, we’re taking further steps to ensure that every pupil masters the 3Rs in primary school and studies the core academic subjects in secondary school - ensuring that every young person gets the best start in life.
The measures being announced today will include:
Deploying the country’s best teachers and leaders to underperforming schools that struggle to attract and retain the professionals they need, the new service will give teachers that take part fast-track development opportunities, ensuring we get the brightest and best to schools that are struggling.
By 2020, there will be 1,500 outstanding teachers and leaders in the service, deployed across the country to the schools that need them most. The service will offer schools that request help an injection of talent from an NTS teacher or leader who will work with them for a period of up to 3 years to help drive up standards. Outstanding teachers who sign up to the NTS will receive a package of support including a clear path to promotion and leadership roles.
An initial pilot has been launched today in the North West to enlist up to 100 teachers and leaders to start work in primary and secondary schools from September 2016.
Brett Wigdortz OBE, CEO and Founder of Teach First:
We know great teaching and leadership are among the most powerful forces for social change, and for improving children’s life chances.
Yet challenges persist for pupils from low-income communities, especially in coastal and dispersed areas. We therefore warmly welcome the National Teaching Service and hope it will have a clear focus on attracting and developing talented teachers and leaders in areas where there are the greatest challenges, enabling young people from low-income backgrounds to realise their full potential.
Every day, teachers and schools across the country are doing incredible work to support their pupils. We look forward to working with the Department for Education to explore how the National Teaching Service can build on this work further, and give more pupils the fair start in life they deserve.
In her speech on Tuesday, the Education Secretary will underline the government’s commitment to make sure every child masters the basics of literacy and numeracy at primary school - and for those who fail to do so, they must resit tests at secondary school.
This is part of the government’s commitment to making sure that every child get the best start in life and can start secondary ready to succeed.
Schools have already made major improvements in this area, with the number of pupils not reaching the expected level in the 3Rs at the end of primary falling from 1 in 3 in 2010 to 1 in 5 this year.
However, there are still thousands of young people who are at risk of falling behind and evidence shows that pupils leaving primary without a good grasp of English and maths are much less likely to go on and secure good GCSEs . Only 6% of pupils unable to read, write and add up at the expected level subsequently get 5 good GCSEs , compared to 50% of those who achieve the expected level and 90% of those who exceed it.
New, more rigorous standard assessment tests ( SATs ) are already being introduced at the end of primary school, and the new ‘reception baseline’ assessment has been introduced in primary schools this year. But to be really confident that students are progressing well through primary school, the government will be looking at the tests for pupils at age 7 - to make sure they provide a firm basis for calculating progress to key stage 2. The government will be working with headteachers in the coming months on how to get this right, holding schools to account and giving them full credit for the progress they achieve.
In 2010 just 22% of young people were studying the EBacc . Since then, and thanks to the reforms in the last Parliament, that has risen to 39%. Today the Education Secretary will announce a consultation on achieving the government’s goal for 90% of pupils to be studying the vital Ebacc subjects of maths, English, science, a foreign language and either history or geography. She will also announce plans for the proportion of pupils entering the EBacc to become a headline measure used to hold schools to account through Ofsted.
This is part of the government’s aim to ensure every child receives a rigorous education in the core academic subjects that open doors to young people’s futures and are respected by employers and universities alike.
Also today, the Education Secretary will announce the details of 5 academy sponsors that will be tasked with driving up standards in schools across the north of England where historically performance has been poor. Five sponsors have been awarded grants totalling nearly £5 million, to make an impact on improving performance for pupils in some of the most challenging and disadvantaged areas of the county.
They are:
REAch2, who have set up a new entity called ‘REAch4’ to work in the north - REAch2 now sponsors 49 schools across the country
Outwood Grange Academies Trust, a sponsor set up by the ‘outstanding’ Outwood Grange Academy in Outwood, near Wakefield
Wakefield City Academies Trust, which has already successfully opened 16 schools across the northern fund regions
Tauheedul Education Trust, a sponsor with an excellent track record in running schools - all of its schools inspected so far are rated ‘outstanding’ by Ofsted
Bright Tribe, a well established sponsor with a proven track record of successfully managing geographically dispersed academy hubs, making it well-matched to the challenge of working in the north
Minister for the Northern Powerhouse James Wharton said:
A key part of building a Northern Powerhouse is to ensure our schools are performing at the highest level, so children are equipped for the skilled jobs of the future.
This £5 million grant will help some of the best academy sponsors bring in their expertise to help turn around underperforming schools across the north of England.
The sponsors bring with them experience, leadership, and a strong track record of success which will mean these school children have the best possible chance of fulfilling their academic potential.
Pupils in Knowsley were 20 percentage points below the national average for children achieving 5 A* to C GCSEs (including English and maths).
The 5 academy chains are setting up 7 new academy hubs in 5 target areas which regional schools commissioners have identified as being those which stand to gain the most from the additional capacity of high-quality sponsors. Work is underway with an expectation that schools will become sponsored academies and join these hubs over course of the next year.
Read the ‘Implementing the English Baccalaureate’ consultation .
Read about the National Teaching Service: for teachers and middle leaders and the National Teaching Service for schools .
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 2 November 2015


Instagram-famous mummy blogger Caitlin Fladager claims smoking weed makes her a ‘better mum’
An Instagram-famous mummy blogger has been praised online after admitting to smoking weed daily, claiming it makes her a “better mum” and should be “just as acceptable as a glass of wine”.
In a post to her more than 288,000 Instagram followers, Canadian blogger Caitlin Fladager - known for her “mum truth” confessions online - claimed smoking marijuana has helped her, especially in caring for her two children Adriana (six) and Jack (four).
The 23-year-old confessed to smoking weed daily while her children slept, saying it aids her anxiety, allowed her to stop taking antidepressants and has assisted in curbing her dangerous under-eating and alcohol consumption.
“Marijuana is my glass of wine,” the mother-of-two said in the post.
“It’s so funny to me how frowned upon marijuana is.
“No one looks twice when a mum says she enjoys ‘mum juice’, aka wine, after her kids are in bed.
“But when a mum says she smokes weed, it’s a huge shock.”
The post, claiming to “bring awareness” to the the stigma around 420-friendly mums, has drawn massive support online, with more than 25,000 people “liking” it in 48 hours.
“Yes finally someone said it,” a mother-of-three commented on the post.
Another mum agreed with Fladager’s comments about the drug being frowned upon as opposed to drinking.
“It’s crazy how something that’s safer with less negative side effects than alcohol can be so looked down on,” she said.
One mum from Australia said she “felt this in her soul” as marijuana is frowned up for its illegality.
“I wish people would see the benefits rather than just swearing it’s bad because it’s what they’ve been told,” she wrote.
Fladager has been married to her high-school sweetheart Noah for more than a decade and describes herself as a mental health advocate.


Following quiz provides Multiple Choice Questions.You will have to read all the given answers and click over the correct answer


{% extends "student/base.html" %}
{% import 'student/assignment/_formhelpers.html' as forms with context %}
{% block title %} Submit Assignment | Ok {% endblock %}
{% block body %}
{% include 'student/assignment/sidebar.html' %}
{% include 'student/header.html' %}


The extensible link mechanism allows new kinds of record links to be created, using JSON for the link address syntax. The IOC continues to support the older link types that do not use JSON to specify their link addresses.
The following additional link types are available in this release:
When setting a record link field to a JSON link address, the link specification must appear inside a pair of braces {}
expressed as a JSON (JavaScript Object Notation) object, which allows link parameters to be defined as needed by the particular link type. When link fields are set from an IOC database file at initialization time, the field definitions may take advantage of a "relaxed JSON" syntax that reduces the number of double-quote characters required and maintains backwards compatibility with the older database file syntax.
"const"
Constant links are input links that provide literal values at link initalization time, but do not return any data when their getValue()
routine is called. Most record types support the use of constant links on their input links by calling recGblInitConstantLink()
at record initialization, which results in the constant value being loaded into the target field at that time.
Note that for most record types (the printf
and calcout
records are the main exceptions) it is pointless to set an input link to a constant link at runtime since the link initialization that loads the field value usually only happens when a record is initialized. A constant link that is embedded inside another input link type such as a calculation link should be OK though since the link initialization will take place when the record's field gets set.
A const link takes a parameter which may be an integer, double or string, or an array of those types. If an array contains both integers and double values the integers will be promoted to doubles. Mixing strings and numbers in an array results in an error.
{const: 3.14159265358979}
{const: "Pi"}
{const: [1, 2.718281828459, 3.14159265358979]}
{const: ["One", "e", "Pi"]}
The JSON syntax does not support Infinity or NaN values when parsing numbers, but (for scalars) it is possible to provide these in a string which will be converted to the desired double value at initialization, for example:
field(INP, {const:"Inf"})
"calc"
A calculation link is an input link that can evaluate mathematical expressions on scalar (double-precision floating-point) values obtained from up to 12 child input links, and returns a double-precision floating-point result. The expression is evaluated by the EPICS Calc engine, and the result is returned as the value of the link.
Two additional expressions may also be provided and are evaluated to determine whether the record owning the link should be placed in alarm state. In both cases the result of the main calculation is available to these expressions as VAL
(attempts to assign to VAL
inside either expression will have no lasting effect). If the major
expression evaluates to a non-zero value the record will be placed in LINK/MAJOR
alarm. If not and the minor
expression evaluates to non-zero the record will be placed in LINK/MINOR
alarm state.
A calculation link can also be an output link, with the scalar output value being converted to a double and provided to the expression as VAL
. Up to 12 additional input links can also be read and provided to the expression as above. The result of the calculation is forwarded to a child output link specified in the link's out
parameter.
For an output link the main expression is actually optional; if not provided the converted value will be forwarded to the output link unchanged. The two alarm expressions may still be used to put the output link into alarm state as described above.
The link address is a JSON map with the following keys:
The primary expression to be evaluated, given as a string. This is optional for output links, required for input links.
An optional expression that returns non-zero to raise a major alarm.
An optional expression that returns non-zero to raise a minor alarm.
A JSON list of up to 12 input arguments for the expression, which are assigned to the inputs A
, B
, C
, ... L
. Each input argument may be either a numeric literal or an embedded JSON link inside {}
braces. The same input values are provided to the two alarm expressions as to the primary expression.
A JSON link inside {}
braces which specifies the destination of putValue
operations after any expressions have been evaluated. This key is required for output links, not used by input links.
An optional string specifying the engineering units for the result of the expression. Equivalent to the EGU
field of a record.
An optional integer specifying the numeric precision with which the calculation result should be displayed. Equivalent to the PREC
field of a record.
An optional string containing a single upper or lower-case letter A
... L
which must correspond to an input provided in the c<args> parameter. When the record containing such a link has TSEL
set to -2 (epicsTimeEventDeviceTime) the record's timestamp field TIME
will be read from the indicated input link atomically with the value of the input argument.
{calc: {expr:"A*B", args:[{db:"record.VAL"}, 1.5], prec:3}}
"state"
A dbState link is one that gets or puts a boolean value from/to a named global flag as implemented by the dbState facility in dbstate.h
. The link type can invert the sense of the dbState flag during the get or put if desired.
The value of the named flag is read or written at the time of the link I/O operation. When reading a flag, the value returned by the link will be zero or one converted to the requested data type. When writing to a flag the boolean value of the data written is determined in the originating data type. All strings are regarded as true other than ""
and "0"
which are both false.
A link can be configured to invert the sense of the flag data by putting an exclamation mark !
before the first character of the flag's name in the link address.
These dbState flags can be accessed from the IOC Shell with various dbState commands, and are also used by the "sync"
Channel-Access server-side filter mechanism.
The link takes a single parameter which must be a string, providing the name of the dbState object, with an optional leading !
character to indicate that the flag's value should be inverted. The dbState object will be created when the link is initialized if it doesn't already exist.
{state:"redBeam"}
{state:"!simEnable"}
"debug"
The debug link type exists to enable debugging of other link types; it provides no functionality itself other than to turn on the debug flag for the child link that is its only parameter and pass all link operations down to that link.
{debug:{state:"redBeam"}}
"trace"
The trace link type is a relative of the debug link type that also traces the operation of its child link. At creation it turns on the debug flag of its child link, then it prints the method arguments and return values of all link operations before / after passing control down to the child link.
{trace:{state:"redBeam"}}


Neural Monkey
LogBook
configuration
log
↻
⊕
⊖
Start by choosing an experiment from the list on the left.


Please use another device
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Varun Engineering Work
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An ISO 2000:2022 certified company
The Coolant Fluid with iron Dust particles Falling by Gravity to the Inlet of the Separator from the Precision Machine Tools such as Grinders, Milling Machines, Automates etc. The Coolant with Iron impurities come in to contact with Magnetic Drum and extracts all Iron particles. It's Features are : -
Ø Ideal for milling, grinding and general machining
Ø Inlet base in SS
Ø Remove particles from 5 micron upwards
Ø Complete with motor & double reduction gear box.
Ø Operates with soluble or near cutting oils
Ø Efficient pre-filter for high levels of ferrous content
Ø Continuous automatic operation-maintenance free
Ø Rugged design for long-life
Ø Magnetic drum in High Power
Tel. :-<PHONE_NUMBER>1,
Mob. :-<PHONE_NUMBER>5,<PHONE_NUMBER>5


|
Valkyrie Engine Common
|
Column-major 3x3 transformation matrix. More...
#include <Matrix.hpp>
Public Member Functions | |
| Matrix3 () | |
| Creates a 3x3 identity matrix. | |
| Matrix3 (Float x0, Float x1, Float x2, Float y0, Float y1, Float y2, Float z0, Float z1, Float z2) | |
| Initialize individual values of a matrix. More... | |
| Matrix3 (Vector3 v0, Vector3 v1, Vector3 v2) | |
| Initialize a matrix with three Vector3. More... | |
| Matrix3 | operator+ (const Float f) const |
| Performs an addition to every cell of a matrix. More... | |
| Matrix3 | operator- (const Float f) const |
| Performs a subtraction to every cell of a matrix. More... | |
| Matrix3 | operator* (const Float f) const |
| Performs a scalar multiplication to every cell of a matrix. More... | |
| Matrix3 | operator/ (const Float f) const |
| Performs a scalar division to every cell of a matrix. More... | |
| Matrix3 | operator+ (const Matrix3 &rhs) const |
| Adds corresponding cells of two matrices. | |
| Matrix3 | operator- (const Matrix3 &rhs) const |
| Subtracts corresponding cells of two matricies. | |
| Matrix3 & | operator+= (const Float f) |
| Performs an addition to every cell of a matrix. More... | |
| Vector3 | operator* (const Vector3 &rhs) const |
| multiplies a matrix by a vector | |
| Matrix3 | operator* (const Matrix3 &rhs) const |
| multiplies two matricies | |
| Matrix3 | operator! () const |
Returns the inverse of this matrix so that m * !m is an identity matrix. | |
Static Public Member Functions | |
| static Matrix3 | CreateTranslation (const Vector2 &v) |
Creates a matrix equivelant to the translation represented by v . | |
| static Matrix3 | CreateRotation (const Float angle) |
Creates a matrix representing a rotation of angle radians. | |
| static ConstexprWrapper< Matrix3 > | CreateRotation (ConstexprWrapper< Float > angle) |
Creates a matrix representing a rotation of angle radians. More... | |
| static Matrix3 | CreateScale (const Vector2 &v) |
Creates a matrix that scales by the amount specified in v . | |
| static Matrix3 | CreateReflectionX () |
| Creates a matrix that reflects along the X-axis. | |
| static Matrix3 | CreateReflectionY () |
| Creates a matrix that reflects along the Y-axis. | |
Column-major 3x3 transformation matrix.
Used to store and apply transformations in 2d space
|
inline |
Initialize individual values of a matrix.
Initialize a matrix with three Vector3.
| v0 | The first column of the matrix |
| v1 | The second column of the matrix |
| v2 | The third column of the matrix |
|
inlinestatic |
Creates a matrix representing a rotation of angle
radians.
|
inline |
Performs a scalar multiplication to every cell of a matrix.
|
inline |
Performs an addition to every cell of a matrix.
|
inline |
Performs an addition to every cell of a matrix.
|
inline |
Performs a subtraction to every cell of a matrix.
|
inline |
Performs a scalar division to every cell of a matrix.


{% extends 'disturbance/emails/apiary_base_email.html' %} {% block content %} The application {{ proposal.lodgement_number }} is waiting for assessment.
Title: {{proposal.title}}
Activity: {{proposal.activity}}
You can access this application using the following link:
Access application {% endblock %}


MOTSS
`Prev `__
M
`Next `__
--------------
**MOTSS**: /mots/, /M·O·T·S·S/, n.
[from the 1970 U.S. census forms via Usenet] Member Of The Same Sex,
esp. one considered as a possible sexual partner. The gay-issues
newsgroup on Usenet is called ``soc.motss``. See
`*MOTOS* `__ and `*MOTAS* `__, which derive from
it. See also `*SO* <../S/SO.html>`__.
--------------
+--------------------------+----------------------------+--------------------------------+
| `Prev `__ | `Up <../M.html>`__ | `Next `__ |
+--------------------------+----------------------------+--------------------------------+
| MOTOS | `Home <../index.html>`__ | mouse ahead |
+--------------------------+----------------------------+--------------------------------+


UElement
as PsiElement
because of ambiguity of PsiElement
you
get
and several issues in the direct implementation. If you need "physical" PsiElement
please use UElementKt.getSourcePsiElement()
,
if you need PsiElement
that "emulates" behaviour of Java-elements (PsiClass
, PsiMethod
, etc.)
then please use UElementKt.getAsJavaPsiElement()
.


Document customer impact considerations for each change to the software in the cardholder data environment.
Considering the customer impact of each change helps ensure that the customer is satisfied with the results.
Revise the change control documentation and add customer impact considerations to the description of each change that doesn't already have it. Consider and document the customer impact of each change in the future.


{% extends 'apidoc.html' %} {% block title %}Tile5 API Documentation{% endblock %} {% block api %}
The T5.Animation module implements Robert Penner's easing equations and also includes functionality for implementing tweening values and object properties through particular functions and classes.


After completing a BSc in Physics and an MSc in Petroleum Engineering I joined an international oil company working as an engineer. I enjoyed the technical challenge of being an engineer, however always felt that I wanted to widen my opportunities and develop my creativity.
So I decided to invest in becoming a Web Developer ....
After enrolling in a 3 month intensive Web Development course at General Assembly I discovered a passion to create through code. I am excited by the idea of being able to develop concepts and build innovative web applications.
I am currently looking to join a company where I can add value in an exciting environment as well as develop my technical skills.


WiFi options
It can take up to a minute for the change to take effect.
Turn on
Turn off
{%- block message %}{% endblock %}


Hit space to learn about Debtonator's features
View a list of your accounts receivable. Order by Contact Name, Total Due, and number of Invoices
Debtonator supports over 162 currencies (and counting!)
Exchange rates are updated hourly and applied live to your invoices, meaning you will always get an accurate outstanding amount.
With one click, filter any of your views to display...
Add private notes about your Debtors, ensuring that all your credit control operatives have the full story.
Need to ensure that everybody is notified when an invoice is due? Add additional email addresses to any contact.
Want to know when your Debtors were reminded, and what for? Check their history!
Debtors whose email addresses bounce emails can be easily spotted. Might want to give them a call!
Long overdue Debtors are easy to spot with our colour-coded system. Sort by age, amount, or currency.
Long overdue Debtors are easy to spot with our colour-coded system. Sort by age, amount, or currency.
Its in your hands. Remind people about only selected invoices if you choose to.
If your Debtor is more than 90 days overdue, upgrade your reminder to a stern, court-action letter.
Before sending, see how your reminders will look, who they will be sent to, and what PDF invoices will be sent along with them.
Each reminder will have the PDF version of the relevant invoices included along with it in the email.
Select certain contacts to be automatically reminded of their Debts. Leaving you to sit back, and let Debtonator do the work for you.
For automated reminders, you choose when and how often they are sent.
Once you hit send, see realtime feedback of your reminders being sent!
Customise any reminder template used by Debtonator to your needs, using our powerful template editor
You can customise the default templates sent to all Debtors, or just change templates for specific Debtors. Or both!
Debtonator is an Xero Certified Addon and is backed by more than 2,700 automated software tests. So you know your data is safe, secure, and accurate.
Let us know your thoughts!
“We're chatty and love to hear from our users!”
Visit the Debtonator Helpdesk to view FAQs, raise support tickets, and more.


{% load i18n %} {% load static from staticfiles %}
{% if sender_note %}{% blocktrans with sender_note as sender_note %}
{{sender_note}} {% endblocktrans %} {% endif %} {% blocktrans with site.name as sitename and from_user.username|capfirst as from_user %} Congratulations! You have been invited by {{ from_user }} to join
{% endblocktrans %}
{{site.name}}
{% trans "Membership is by invitation only, so click the invitation token below to join us now!" %} {{token|safe}}
{% trans "All the best" %},
{% trans "The" %} {{site.name}} {% trans "team" %} |


My bio and photographs, usable on speaking engagements or articles.
Arlene Andrews is a self-guided learner, moving into the Quality Advocate section of the tech world,
and has been
selected to guest, write and review on podcasts, articles, classes, and proposals for conferences.
Having previously worked
in a wide range of positions including both customer service and HR, she has a worldview of
supporting customers, and is
a fan of learning and applying new things. Moving into technology has been a huge leap, and she has
a passion for
connecting people to resources that will foster improvements, and recently became a pround member of the Agile Alliance for 2020.


|
TLM-2.0
2.0.5
Accellera TLM-2.0 proof-of-concept library
|
#include <tlm_core/tlm_2/tlm_generic_payload/tlm_endian_conv.h>
Public Member Functions | |
| tlm_bool (D &d) | |
| operator bool () const | |
Static Public Member Functions | |
| static D | make_uchar_array (uchar c) |
Static Public Attributes | |
| static D | TLM_TRUE = tlm_bool<D>::make_uchar_array(TLM_BYTE_ENABLED) |
| static D | TLM_FALSE = tlm_bool<D>::make_uchar_array(TLM_BYTE_DISABLED) |
Definition at line 260 of file tlm_endian_conv.h.
|
inline |
Definition at line 272 of file tlm_endian_conv.h.
|
inlinestatic |
Definition at line 264 of file tlm_endian_conv.h.
|
inline |
Definition at line 273 of file tlm_endian_conv.h.
|
static |
Definition at line 263 of file tlm_endian_conv.h.
|
static |
Definition at line 262 of file tlm_endian_conv.h.


%-- Document : Discount Created on : 9 Mar, 2011, 11:10:55 PM Author : VISHAL --%> <%@page contentType="text/html" pageEncoding="UTF-8"%> <% Object obj = session.getAttribute("USERNAME"); if(obj == null) { response.sendRedirect("/MBA/User/Login.jsp"); } %>
|
Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service | Best Quality | Best Price | Best Service |
|


Bye, bye!
Thank you for playing my game!
Created by P.S ❤
Your score:
Robot score:
Please, choose your weapon!


The reopening of borders on June 15 will go ahead as scheduled after the government stated last week that it was still attempting to figure out testing protocols for tourists. Tourists who do not wish to quarantine upon arrival will need to present a negative PCR test from the four days prior to arrival or a positive PCR test that is more than 14 days old. Nurses in Iceland are voting on strike action this week after working without a contract for more than a year. If approved, the strike is scheduled to begin on June 22 and will affect 2500 nurses at all public healthcare clinics just one week after borders to the country reopen.


Statistics: An Introduction Using R
ISBN-13:<PHONE_NUMBER>096
ISBN-10:<PHONE_NUMBER>
Author: Michael J. Crawley
Edition: 2
Binding: Paperback
Publisher: Wiley
Published: November 2014
List Price: $47.00
ISBN-13:<PHONE_NUMBER>096
ISBN-10:<PHONE_NUMBER>
Author: Michael J. Crawley
Edition: 2
Binding: Paperback
Publisher: Wiley
Published: November 2014
List Price: $47.00


Strong wind, sunlight improves air quality in Delhi
Sunlight also helped increase the atmospheric mixing layer height which further helped release pollutants trapped closer to the surface, IMD officials said.
by Express News ServiceStrong, gusty winds coupled with a clear sky and ample sunlight further improved the city’s air quality to the ‘poor’ category Sunday from ‘very poor’ a day earlier. IMD officials said winds as strong as 36 km/hr were recorded in the city Sunday, which dispersed pollutants.
Sunlight also helped increase the atmospheric mixing layer height which further helped release pollutants trapped closer to the surface, IMD officials said.
The 24-hour AQI of Delhi Sunday was 215 (poor). Gurgaon had the lowest AQI of 136 (moderate), Ghaziabad recorded 218 and Noida 203.
A report from the central government’s air quality monitoring system SAFAR said, “High surface winds are forecast to continue for the next 24 hours after which they are likely to decrease slowly.”
Share of stubble burning in Delhi’s air Sunday, as per the SAFAR report, was 2% and is expected to go up to 9% Monday. Air quality is expected to remain ‘poor’ or improve to ‘moderate’ Monday, but may deteriorate from Tuesday and reach the higher end of ‘very poor’ by Wednesday, as per the report.


What is linkedlist ?
Linked List is a sequence of data structures, which are connected together via links. Each struct consists of two parts,
data part which stores the relevant data and link/pointer that stores the refrence to the next data block. Linked list
is second most used data strucutre after array.
You might be thinking if it is just list of data, we already have arrays for that so what is the point of using a
linked list, Right?
Well one disadvantage of using arrays to store data is that arrays are static strcutures and
therefore cannot be easily extended or reduced to fit the data set. Arrays are also expensive to maintain new
insertions and deletions.
Second major disadvantage is that, memory allocation of array is uniform, i.e. knowing address of any one of the
memory block, you can get address of any other memory block of the array. This property helps you to get the
required data from an array in O(1) but restricts the max size of an array to an order of
O(106). Whereas memory allocation in linkedlist is dynamic, this means that each data
block has a randomly allocated memory location. Due to this property of linkedlist, there are no maximum
size constraints. This is very useful when you are working with large amount of data that has to be handled.
Linked List Functionalities
- Appending to Linkedlist
- Inserting to Linkedlist
- Deleting to Linkedlist
Implemetation
#include<stdio.h>
#include<stdlib.h>
struct node{
int data;
struct node* next;
};
void addatbegin(struct node **head,int key)
{
struct node *temp;
temp = (struct node *)malloc(sizeof(struct node));
temp->data = key;
temp->next = (*head);
(*head) = temp;
}
void addatend(struct node *head,int key)
{
struct node *temp;
temp = (struct node *)malloc(sizeof(struct node));
temp->data = key;
while(head->next != NULL)
head = head->next;
head->next = temp;
temp->next = NULL;
}
void addatmiddle(struct node *head,int key,int middata)
{
struct node *temp,*pev;
temp = (struct node *)malloc(sizeof(struct node));
temp->data = key;
while(head->data != middata)
head = head->next;
temp->next = head->next;
head->next = temp;
}
void deleteatbeg(struct node **head)
{
(*head) = (*head)->next;
}
void deleteatend(struct node *head)
{
while((head->next)->next != NULL)
head = head->next;
head->next = NULL;
}
void deleteatmid(struct node *head,int key)
{
struct node *temp;
for(int i=0;i<key;i++)
{
temp = head;
head = head->next;
}
temp->next = head->next;
}
void print(struct node* head)
{
while(head != NULL)
{
printf("%d -> ",head->data);
head = head->next;
}
printf("\n");
}
int main()
{
struct node *head,*a;
a = (struct node *)malloc(sizeof(struct node));
a->data = 1;
a->next = NULL;
head = a;
addatend(head,2);
addatend(head,3);
addatbegin(&head,0);
//deleteatbeg(&head);
deleteatmid(head,2);
print(head);
return 0;
}
Run On IDE


A data service is a component that provides methods to access domain object models from a database by reading them from tables and producing a model or a list of models.
They can also provide methods that produces changes in the database.
Within this framework a data service is a class that implement
Inetdev.Data.IDataServices
or that inherits from
Inetdev.Data.DataServices
, for example:
public class AuditDataServices : DataServices
{
//...
}
A data model will provide the following information related to a database table, this information is provided by their respected properties.
Schema
.Alias
for the table.Table
property.Fields
property.
Table data are filtered from methods within data services, this methods
will use the infrastructure provided by the namespace
Inetdev.Data.Query
to construct query commands in a database
agnostic way.
Usage of this infrastructure can be seen in this sample here.
In this document


Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove
扫一扫二维码，关注我们的微信号，参加更多促销活动！


nips nips2013 nips2013-324 nips2013-324-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund
Abstract: We consider a situation in which we see samples Xn ∈ Rd drawn i.i.d. from some distribution with mean zero and unknown covariance A. We wish to compute the top eigenvector of A in an incremental fashion - with an algorithm that maintains an estimate of the top eigenvector in O(d) space, and incrementally adjusts the estimate with each new data point that arrives. Two classical such schemes are due to Krasulina (1969) and Oja (1983). We give ﬁnite-sample convergence rates for both. 1
[1] A. Agarwal, O. Chapelle, M. Dud´k, and J. Langford. A reliable effective terascale linear ı learning system. CoRR, abs/1110.4198, 2011.
[2] R. Arora, A. Cotter, K. Livescu, and N. Srebro. Stochastic optimization for PCA and PLS. In 50th Annual Allerton Conference on Communication, Control, and Computing, pages 861– 868. 2012.
[3] R. Arora, A. Cotter, and N. Srebro. Stochastic optimization of PCA with capped MSG. In Advances in Neural Information Processing Systems, 2013.
[4] G. Blanchard, O. Bousquet, and L. Zwald. Statistical properties of kernel principal component analysis. Machine Learning, 66(2-3):259–294, 2007.
[5] T. T. Cai, Z. Ma, and Y. Wu. Sparse PCA: Optimal rates and adaptive estimation. CoRR, abs/1211.1309, 2012. 8
[6] R. Durrett. Probability: Theory and Examples. Duxbury, second edition, 1995.
[7] T.P. Krasulina. A method of stochastic approximation for the determination of the least eigenvalue of a symmetrical matrix. USSR Computational Mathematics and Mathematical Physics, 9(6):189–195, 1969.
[8] I. Mitliagkas, C. Caramanis, and P. Jain. Memory limited, streaming PCA. In Advances in Neural Information Processing Systems, 2013.
[9] E. Oja. Subspace Methods of Pattern Recognition. Research Studies Press, 1983.
[10] E. Oja and J. Karhunen. On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix. Journal of Math. Analysis and Applications, 106:69–84, 1985.
[11] A. Rakhlin, O. Shamir, and K. Sridharan. Making gradient descent optimal for strongly convex stochastic optimization. In International Conference on Machine Learning, 2012.
[12] S. Roweis. EM algorithms for PCA and SPCA. In Advances in Neural Information Processing Systems, 1997.
[13] T. Sim, S. Baker, and M. Bsat. The CMU pose, illumination, and expression database. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12):1615–1618, 2003.
[14] V.Q. Vu and J. Lei. Minimax rates of estimation for sparse PCA in high dimensions. Journal of Machine Learning Research - Proceedings Track, 22:1278–1286, 2012.
[15] M.K. Warmuth and D. Kuzmin. Randomized PCA algorithms with regret bounds that are logarithmic in the dimension. In Advances in Neural Information Processing Systems. 2007.
[16] J. Weng, Y. Zhang, and W.-S. Hwang. Candid covariance-free incremental principal component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(8):1034– 1040, 2003.
[17] L. Zwald and G. Blanchard. On the convergence of eigenspaces in kernel principal component analysis. In Advances in Neural Information Processing Systems, 2005. 9


Thieves steal reader’s identity using USPS mail forwarding scam
by John CrudeleDear John: What you wrote about forwarding post office mail was not true for us.
Someone filed a “forwarding address” for our mail, and it was forwarded to a Philadelphia post office address. We live in Florida. They were able to get a password from USPS.
We couldn’t stop the forwarding because we would need the PIN the post office emailed to the thieves.
We received no notification from USPS. Besides, if we did, it would have been forwarded to the bogus address anyway. The thieves got a checking account statement and ordered new checks sent to their address. They applied for credit cards and other charge accounts.
USPS locally was helpful, but the inspector general’s office in Washington, DC, was useless. It had zero interest in investigating, let alone prosecuting.
We, too, were told we couldn’t flag our address to avoid a repeat of this activity. Anyone can file a forwarding order online and you won’t know it until you notice you are not getting mail. F.J.
Dear F.J.: Sorry to hear about your troubles.
So, someone at the post office was either careless or was in on the scheme.
Now everyone is warned. What the post office thinks is going on — and what I put in the Nov. 3 issue of The Post — isn’t necessarily so.
Watch your mail carefully. If you stop getting anything, that’s a sure sign — junk mail never ceases.


# -*- coding: utf-8 -*-
# This file is part of QuTiP: Quantum Toolbox in Python.
#
# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the QuTiP: Quantum Toolbox in Python nor the names
# of its contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
 IN NO EVENT SHALL THE COPYRIGHT
# HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
"""
This module contains a collection of functions for calculating metrics
(distance measures) between states and operators.
"""
__all__ = ['fidelity', 'tracedist', 'bures_dist', 'bures_angle',
'hellinger_dist', 'hilbert_dist', 'average_gate_fidelity',
'process_fidelity', 'unitarity', 'dnorm']
import numpy as np
from scipy import linalg as la
import scipy.sparse as sp
from qutip.sparse import sp_eigs
from qutip.states import ket2dm
from qutip.superop_reps import to_kraus, to_stinespring, to_choi, _super_to_superpauli, to_super
from qutip.superoperator import operator_to_vector, vector_to_operator
from qutip.operators import qeye
from qutip.semidefinite import dnorm_problem
import qutip.settings as settings
import qutip.logging_utils as logging
logger = logging.get_logger()
try:
import cvxpy
except:
cvxpy = None
[docs]def fidelity(A, B):
"""
Calculates the fidelity (pseudo-metric) between two density matrices.
See: Nielsen & Chuang, "Quantum Computation and Quantum Information"
Parameters
----------
A : qobj
Density matrix or state vector.
B : qobj
Density matrix or state vector with same dimensions as A.
Returns
-------
fid : float
Fidelity pseudo-metric between A and B.
Examples
--------
>>> x = fock_dm(5,3)
>>> y = coherent_dm(5,1)
>>> fidelity(x,y)
0.24104350624628332
"""
if A.isket or A.isbra:
# Take advantage of the fact that the density operator for A
# is a projector to avoid a sqrtm call.
sqrtmA = ket2dm(A)
# Check whether we have to turn B into a density operator, too.
if B.isket or B.isbra:
B = ket2dm(B)
else:
if B.isket or B.isbra:
# Swap the order so that we can take a more numerically
# stable square root of B.
return fidelity(B, A)
# If we made it here, both A and B are operators, so
# we have to take the sqrtm of one of them.
sqrtmA = A.sqrtm()
if sqrtmA.dims != B.dims:
raise TypeError('Density matrices do not have same dimensions.')
# We don't actually need the whole matrix here, just the trace
# of its square root, so let's just get its eigenenergies instead.
# We also truncate negative eigenvalues to avoid nan propagation;
# even for positive semidefinite matrices, small negative eigenvalues
# can be reported.
eig_vals = (sqrtmA * B * sqrtmA).eigenenergies()
return float(np.real(np.sqrt(eig_vals[eig_vals > 0]).sum()))
[docs]def process_fidelity(U1, U2, normalize=True):
"""
Calculate the process fidelity given two process operators.
"""
if normalize:
return (U1 * U2).tr() / (U1.tr() * U2.tr())
else:
return (U1 * U2).tr()
[docs]def average_gate_fidelity(oper, target=None):
"""
Given a Qobj representing the supermatrix form of a map, returns the
average gate fidelity (pseudo-metric) of that map.
Parameters
----------
A : Qobj
Quantum object representing a superoperator.
target : Qobj
Quantum object representing the target unitary; the inverse
is applied before evaluating the fidelity.
Returns
-------
fid : float
Fidelity pseudo-metric between A and the identity superoperator,
or between A and the target superunitary.
"""
kraus_form = to_kraus(oper)
d = kraus_form[0].shape[0]
if kraus_form[0].shape[1] != d:
return TypeError("Average gate fidelity only implemented for square "
"superoperators.")
if target is None:
return (d + np.sum([np.abs(A_k.tr())**2
for A_k in kraus_form])) / (d**2 + d)
else:
return (d + np.sum([np.abs((A_k * target.dag()).tr())**2
for A_k in kraus_form])) / (d**2 + d)
[docs]def tracedist(A, B, sparse=False, tol=0):
"""
Calculates the trace distance between two density matrices..
See: Nielsen & Chuang, "Quantum Computation and Quantum Information"
Parameters
----------!=
A : qobj
Density matrix or state vector.
B : qobj
Density matrix or state vector with same dimensions as A.
tol : float
Tolerance used by sparse eigensolver, if used. (0=Machine precision)
sparse : {False, True}
Use sparse eigensolver.
Returns
-------
tracedist : float
Trace distance between A and B.
Examples
--------
>>> x=fock_dm(5,3)
>>> y=coherent_dm(5,1)
>>> tracedist(x,y)
0.9705143161472971
"""
if A.isket or A.isbra:
A = ket2dm(A)
if B.isket or B.isbra:
B = ket2dm(B)
if A.dims != B.dims:
raise TypeError("A and B do not have same dimensions.")
diff = A - B
diff = diff.dag() * diff
vals = sp_eigs(diff.data, diff.isherm, vecs=False, sparse=sparse, tol=tol)
return float(np.real(0.5 * np.sum(np.sqrt(np.abs(vals)))))
[docs]def hilbert_dist(A, B):
"""
Returns the Hilbert-Schmidt distance between two density matrices A & B.
Parameters
----------
A : qobj
Density matrix or state vector.
B : qobj
Density matrix or state vector with same dimensions as A.
Returns
-------
dist : float
Hilbert-Schmidt distance between density matrices.
Notes
-----
See V. Vedral and M. B. Plenio, Phys. Rev. A 57, 1619 (1998).
"""
if A.isket or A.isbra:
A = ket2dm(A)
if B.isket or B.isbra:
B = ket2dm(B)
if A.dims != B.dims:
raise TypeError('A and B do not have same dimensions.')
return ((A - B)**2).tr()
[docs]def bures_dist(A, B):
"""
Returns the Bures distance between two density matrices A & B.
The Bures distance ranges from 0, for states with unit fidelity,
to sqrt(2).
Parameters
----------
A : qobj
Density matrix or state vector.
B : qobj
Density matrix or state vector with same dimensions as A.
Returns
-------
dist : float
Bures distance between density matrices.
"""
if A.isket or A.isbra:
A = ket2dm(A)
if B.isket or B.isbra:
B = ket2dm(B)
if A.dims != B.dims:
raise TypeError('A and B do not have same dimensions.')
dist = np.sqrt(2.0 * (1.0 - fidelity(A, B)))
return dist
[docs]def bures_angle(A, B):
"""
Returns the Bures Angle between two density matrices A & B.
The Bures angle ranges from 0, for states with unit fidelity, to pi/2.
Parameters
----------
A : qobj
Density matrix or state vector.
B : qobj
Density matrix or state vector with same dimensions as A.
Returns
-------
angle : float
Bures angle between density matrices.
"""
if A.isket or A.isbra:
A = ket2dm(A)
if B.isket or B.isbra:
B = ket2dm(B)
if A.dims != B.dims:
raise TypeError('A and B do not have same dimensions.')
return np.arccos(fidelity(A, B))
def hellinger_dist(A, B, sparse=False, tol=0):
"""
Calculates the quantum Hellinger distance between two density matrices.
Formula:
hellinger_dist(A, B) = sqrt(2-2*Tr(sqrt(A)*sqrt(B)))
See: D. Spehner, F. Illuminati, M. Orszag, and W. Roga, "Geometric
measures of quantum correlations with Bures and Hellinger distances"
arXiv:1611.03449
Parameters
----------
A : :class:`qutip.Qobj`
Density matrix or state vector.
B : :class:`qutip.Qobj`
Density matrix or state vector with same dimensions as A.
tol : float
Tolerance used by sparse eigensolver, if used. (0=Machine precision)
sparse : {False, True}
Use sparse eigensolver.
Returns
-------
hellinger_dist : float
Quantum Hellinger distance between A and B. Ranges from 0 to sqrt(2).
Examples
--------
>>> x=fock_dm(5,3)
>>> y=coherent_dm(5,1)
>>> hellinger_dist(x,y)
1.3725145002591095
"""
if A.dims != B.dims:
raise TypeError("A and B do not have same dimensions.")
if A.isket or A.isbra:
sqrtmA = ket2dm(A)
else:
sqrtmA = A.sqrtm(sparse=sparse, tol=tol)
if B.isket or B.isbra:
sqrtmB = ket2dm(B)
else:
sqrtmB = B.sqrtm(sparse=sparse, tol=tol)
product = sqrtmA*sqrtmB
eigs = sp_eigs(product.data,
isherm=product.isherm, vecs=False, sparse=sparse, tol=tol)
#np.maximum() is to avoid nan appearing sometimes due to numerical
#instabilities causing np.sum(eigs) slightly (~1e-8) larger than 1
#when hellinger_dist(A, B) is called for A=B
return np.sqrt(2.0 * np.maximum(0., (1.0 - np.real(np.sum(eigs)))))
def dnorm(A, B=None, solver="CVXOPT", verbose=False, force_solve=False):
"""
Calculates the diamond norm of the quantum map q_oper, using
the simplified semidefinite program of [Wat12]_.
The diamond norm SDP is solved by using CVXPY_.
Parameters
----------
A : Qobj
Quantum map to take the diamond norm of.
B : Qobj or None
If provided, the diamond norm of :math:`A - B` is
taken instead.
solver : str
Solver to use with CVXPY. One of "CVXOPT" (default)
or "SCS". The latter tends to be significantly faster,
but somewhat less accurate.
verbose : bool
If True, prints additional information about the
solution.
force_solve : bool
If True, forces dnorm to solve the associated SDP, even if a special
case is known for the argument.
Returns
-------
dn : float
Diamond norm of q_oper.
Raises
------
ImportError
If CVXPY cannot be imported.
.. _cvxpy: http://www.cvxpy.org/en/latest/
"""
if cvxpy is None: # pragma: no cover
raise ImportError("dnorm() requires CVXPY to be installed.")
# We follow the strategy of using Watrous' simpler semidefinite
# program in its primal form. This is the same strategy used,
# for instance, by both pyGSTi and SchattenNorms.jl. (By contrast,
# QETLAB uses the dual problem.)
# Check if A and B are both unitaries. If so, then we can without
# loss of generality choose B to be the identity by using the
# unitary invariance of the diamond norm,
# || A - B ||_♢ = || A B⁺ - I ||_♢.
# Then, using the technique mentioned by each of Johnston and
# da Silva,
# || A B⁺ - I ||_♢ = max_{i, j} | \lambda_i(A B⁺) - \lambda_j(A B⁺) |,
# where \lambda_i(U) is the ith eigenvalue of U.
if (
# There's a lot of conditions to check for this path.
not force_solve and B is not None and
# Only check if they aren't superoperators.
A.type == "oper" and B.type == "oper" and
# The difference of unitaries optimization is currently
# only implemented for d == 2. Much of the code below is more general,
# though, in anticipation of generalizing the optimization.
A.shape[0] == 2
):
# Make an identity the same size as A and B to
# compare against.
I = qeye(A.dims[0])
# Compare to B first, so that an error is raised
# as soon as possible.
Bd = B.dag()
if (
(B * Bd - I).norm() < 1e-6 and
(A * A.dag() - I).norm() < 1e-6
):
# Now we are on the fast path, so let's compute the
# eigenvalues, then find the diameter of the smallest circle
# containing all of them.
#
# For now, this is only implemented for dim = 2, such that
# generalizing here will allow for generalizing the optimization.
# A reasonable approach would probably be to use Welzl's algorithm
# (https://en.wikipedia.org/wiki/Smallest-circle_problem).
U = A * B.dag()
eigs = U.eigenenergies()
eig_distances = np.abs(eigs[:, None] - eigs[None, :])
return np.max(eig_distances)
# Force the input superoperator to be a Choi matrix.
J = to_choi(A)
if B is not None:
J -= to_choi(B)
# Watrous 2012 also points out that the diamond norm of Lambda
# is the same as the completely-bounded operator-norm (∞-norm)
# of the dual map of Lambda. We can evaluate that norm much more
# easily if Lambda is completely positive, since then the largest
# eigenvalue is the same as the largest singular value.
if not force_solve and J.iscp:
S_dual = to_super(J.dual_chan())
vec_eye = operator_to_vector(qeye(S_dual.dims[1][1]))
op = vector_to_operator(S_dual * vec_eye)
# The 2-norm was not implemented for sparse matrices as of the time
# of this writing. Thus, we must yet again go dense.
return la.norm(op.data.todense(), 2)
# If we're still here, we need to actually solve the problem.
# Assume square...
dim = np.prod(J.dims[0][0])
# The constraints only depend on the dimension, so
# we can cache them efficiently.
problem, Jr, Ji, X, rho0, rho1 = dnorm_problem(dim)
# Load the parameters with the Choi matrix passed in.
J_dat = J.data
Jr.value = sp.csr_matrix((J_dat.data.real, J_dat.indices, J_dat.indptr),
shape=J_dat.shape)
Ji.value = sp.csr_matrix((J_dat.data.imag, J_dat.indices, J_dat.indptr),
shape=J_dat.shape)
# Finally, set up and run the problem.
problem.solve(solver=solver, verbose=verbose)
return problem.value
def unitarity(oper):
"""
Returns the unitarity of a quantum map, defined as the Frobenius norm
of the unital block of that map's superoperator representation.
Parameters
----------
oper : Qobj
Quantum map under consideration.
Returns
-------
u : float
Unitarity of ``oper``.
"""
Eu = _super_to_superpauli(oper).full()[1:, 1:]
#return np.real(np.trace(np.dot(Eu, Eu.conj().T))) / len(Eu)
return np.linalg.norm(Eu, 'fro')**2 / len(Eu)


This is the actual HTML source used to power almost the entire presentation you watched at http://robcolbert.com/#/prototype (watch it again!). When you load this page, it pulls the un-minified/un-uglified source into this editor.


Node overview
Red: active nodes. Blue: old-version nodes. (No number on mouseover for Orange: broken nodes).


{%extends 'mgmt/index.html'%} {% load static%} {% block content %}
Search, Create, Comlete and View Work-orders. View all Tools and Parts associated with a specific Work-order!
| Work Order No | Tail No | Airframe Type | Date Created | LDGS @ open | Hours @ open | |||
|---|---|---|---|---|---|---|---|---|
| {{instance.workorder_number}} | {{instance.tail_number}} | {{instance.type_airframe}} | {{instance.date_added|date:"M d, Y"}} | {{instance.ldgs_at_open}} | {{instance.hours_at_open}} | View | delete | Complete |


# Crichton, Admirable Source Configuration Management # Copyright 2012 British Broadcasting Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # {% extends "admin/base_site.html" %} {% block content %}
There was a problem communicating with Jira so the deployment request couldn't be added / updated. We're very sorry for the inconvenience. If you use your browser's back button the change fields you already filled in should still be there. Once this problem has been fixed then you will be able to re-submit the form. Alternatively if this deployment request is urgent you should create / edit it directly in Jira.
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{% endblock %}


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THE ART OF AMÁLIA A film review by Christopher Null Copyright 2000 filmcritic.com filmcritic.com
I don't know Fado from Fabian, but I do know what makes a good documentary. Regardless of how flattering your opinion is of legendary Portuguese singer Amália Rodrigues, you owe it to yourself to separate her talents from the movie that documents them, because the film clearly doesn't do her justice.
The Art of Amália starts with promise, with ex-Talking Head David Byrne waxing earnestly about when he first heard Rodrigues's music. But the film abruptly detours after that one minute, becoming a strictly linear monologue telling the story her life. The picture is more boring than a history textbook. Why? Because little in Amália's life was or is extraordinary. We wander, year by year, from her early days as a nightclub singer to her career in cinema to more singing to the many awards she's won and finally... to more singing. And poof, the story is over. Ready for The Madonna Story, anyone?
If you think I'm just a naysayer, consider a film like Theremin: An Electronic Odyssey, which documented the life of a musician but did it with style, despite the fact that the audience had never heard of the man. Amália was never kidnapped in her sleep. Amália was not in the KGB. Nothing much happened in her life that's film-worthy at all. Amália sang and she sang a lot. And while she was very good at it, that doesn't mean it makes a great film.
Then again, neither do slow zooms on newspaper clippings, advertisements bearing her name, and still photographs, plus interviews with some of the most poorly-spoken people ever to grace the screen. The production values are nonexistent. The narration is banal and obvious.
Ultimately, even big fans of Amália are going to be disappointed with The Art of Amália, the sole bright spot being her Fado music, which is heartfelt and tears at the soul. Some 60 songs are rendered by her, in whole or in part, throughout the 90-minute film, and they're certainly pleasing to the ears... provided you're tuning out the rest of the picture.

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


{% macro hitsorymodals(from='history') %} {% if from == 'dashboard' %}
Are you sure you want to remove all history?


Chartable is not intended to be feature rich or interactive, there are already libraries for that. Chartable is meant for a project where you only need a static chart or two and don't want to require a download of thousands of lines of JavaScript.
It's a ruby port of chartable by @jxnblk.
This is a work in progress.
The bar chart takes an array of objects with x and y keys. For these examples lets assume the data looks like the following.
[ { x: 0, y: 20 }, { x: 1, y: 40 }, { x: 2, y: 50 }, { x: 3, y: 25 } ]
Rendering a bar chart requires calling Chartable.bar
and passing in the data.
It returns an svg string representation of the bar chart.
Chartable.bar(data, width: 300, height: 150)
You can specify an x axis with the x_axis
.
It's an inline styled border so you can give it a value like 'thin solid #ddd'
.
Chartable.bar(data, x_axis: 'thin solid #ddd')
Similarly to the x_axis
option, you can also specify a y_axis
.
Chartable.bar(data, y_axis: 'thin solid #ddd')


{% extends "base-en.html" %} {% import "blog_macros.html" as blog_macros %} {% block content %}
filed under: {{ blog_macros::category_listing(page=page, language="en", base_url="/category/", none_description="no categories, how unique") }}
It's a bit unfortunate that this sort of metadata cannot easily be rendered under the document heading without falling to the bottom of the page after all content. Not being able to massage the content itself is more pure, but the page title is kind of special. What to do?
{{ content | safe }}This is a blog entry from {{ page.meta.created_at | default(value="sometime") }}. All of them here:
{# the default logic above and in the listing are not very useful because the sort would explode if any page wouldn't have the meta.created_at attribute... #} {%- set blog_entries = site.groups["blog"].pages | filter(attribute="meta.language", value="en") | sort(attribute="title") | sort(attribute="meta.created_at") %}entry before the current one: {% set prev_page = blog_entries | take_until_attr(attribute="url", value=page.url) | last %} {%- if prev_page %}{{ prev_page.title }} {%- else %}(this is the first one) {%- endif %}
entry after the current one: {% set next_page = blog_entries | reverse | take_until_attr(attribute="url", value=page.url) | last %} {%- if next_page %}{{ next_page.title }} {%- else %}(this is the last one) {%- endif %}
{% endblock content %}


Welcome to 🚀 RocketShop
The world's first eva shop where you buy stuff in XLM!!!!
Item Name
Qty
Ajax Cleaner - makes your life cleaner
Checkout


Form Responses Total
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Speedcube competitions is a resource for organizers and competitors to know any information about a speedcube competition.
The primary purpose of this website is to help and give back to the speedcubing community. I have been part of the speedcubing community for many years and have organized a couple of competitions. While organizing competition I've found a lack of tools and resources that would greatly help with the process of organizing a speedcube competition. This website attempts to provide those tools and resources to help organize competitions which will help competitors as well.
My vision for speedcube competitions goes beyond just being a set of helpful tools. The main goal is to be able to sponsor and organize speedcube competitions to make competitions more frequent and available and also to organize and sponsor competitions with FREE registraion.
Currently the website is in a basic version.
Basic version:
Complete version:
This basic version is for organizers. The more complete version will cater to organizers and competitors of speedcube competions.
Speedcubecompetitions.com is created and maintained by Isagani Esteron.
NO... There are no fees or hidden charges involved for this bsaic version and the more complete version.
This website will try to monetize by displaying ads and hopefully through sponsored deals.
The main purpose of this website is to give back to the speedcubing community. There is an opportunity for monetization but it will be to give back as well.. Profits will be used in 2 ways. The 1 item is minimal and item 2 is the most important and exciting part.


{% extends 'base.html' %} {% load staticfiles %} {% block stylesheet %} {% endblock %} {% block title %}Forgot Your Password?{% endblock %} {% block content %}
Enter your email address below, and we'll email instructions for setting a new one.


|
App Engine Python SDK
v1.6.9 rev.445
The Python runtime is available as an experimental Preview feature.
|
Public Member Functions | |
| def | __init__ |
| def | AddPie |
| def | AddSegments |
| def | AddSegment |
| def | AddSeries |
| def | SetColors |
| Public Member Functions inherited from google.appengine._internal.graphy.common.BaseChart | |
| def | __init__ |
| def | AddFormatter |
| def | AddSeries |
| def | GetDependentAxes |
| def | GetIndependentAxes |
| def | GetDependentAxis |
| def | GetIndependentAxis |
| def | GetFormattedChart |
| def | GetMinMaxValues |
| def | AddAxis |
| def | GetAxis |
| def | SetAxis |
Public Attributes | |
| formatters | |
| Public Attributes inherited from google.appengine._internal.graphy.common.BaseChart | |
| data | |
| auto_color | |
| auto_scale | |
| auto_legend | |
| formatters | |
| display | |
Additional Inherited Members | |
| Properties inherited from google.appengine._internal.graphy.common.BaseChart | |
| bottom | |
| left | |
| right | |
| top | |
Represents a pie chart. The pie chart consists of a single "pie" by default, but additional pies may be added using the AddPie method. The Google Chart API will display the pies as concentric circles, with pie #0 on the inside; other backends may display the pies differently.
| def google.appengine._internal.graphy.pie_chart.PieChart.__init__ | ( | self, | |
points = None , |
|||
labels = None , |
|||
colors = None |
|||
| ) |
Constructor for PieChart objects. Creates a pie chart with a single pie. Args: points: A list of data points for the pie chart; i.e., relative sizes of the pie segments labels: A list of labels for the pie segments. TODO: Allow the user to pass in None as one of the labels in order to skip that label. colors: A list of colors for the pie segments, as hex strings (f.ex. '0000ff' for blue). If there are less colors than pie segments, the Google Chart API will attempt to produce a smooth color transition between segments by spreading the colors across them.
| def google.appengine._internal.graphy.pie_chart.PieChart.AddPie | ( | self, | |
| points, | |||
labels = None , |
|||
colors = None |
|||
| ) |
Add a whole pie to the chart. Args: points: A list of pie segment sizes labels: A list of labels for the pie segments colors: A list of colors for the segments. Missing colors will be chosen automatically. Return: The index of the newly added pie.
| def google.appengine._internal.graphy.pie_chart.PieChart.AddSegment | ( | self, | |
| size, | |||
label = None , |
|||
color = None , |
|||
pie_index = 0 |
|||
| ) |
Add a pie segment to this chart, and return the segment. size: The size of the segment. label: The label for the segment. color: The color of the segment, or None to automatically choose the color. pie_index: The index of the pie that will receive the new segment. By default, the chart has one pie (pie #0); use the AddPie method to add more pies.
| def google.appengine._internal.graphy.pie_chart.PieChart.AddSegments | ( | self, | |
| points, | |||
| labels, | |||
| colors | |||
| ) |
DEPRECATED.
| def google.appengine._internal.graphy.pie_chart.PieChart.AddSeries | ( | self, | |
| points, | |||
color = None , |
|||
style = None , |
|||
markers = None , |
|||
label = None |
|||
| ) |
DEPRECATED Add a new segment to the chart and return it. The segment must contain exactly one data point; all parameters other than color and label are ignored.
| def google.appengine._internal.graphy.pie_chart.PieChart.SetColors | ( | self, | |
| colors | |||
| ) |
Change the colors of this chart to the specified list of colors. Note that this will completely override the individual colors specified in the pie segments. Missing colors will be interpolated, so that the list of colors covers all segments in all the pies.


Material Icon picker for MaterializeCSS
Just add the "use-material-icon-picker" class to any input tag to use an interactive icon picker!
Icon picker


"x"
"1" "FERGUSON,LR, DENNY,WA AND O'ROURKE,SM, MUTAGENIC ACTIVITY OFNITRACRINE DERIVATIVES IN SALMONELLA TYPHIMURIUM: RELATIONSHIP TO DRUGPHYSICOCHEMICAL PARAMETERS, AND TO BACTERIAL UVRB AND RECA GENES AND P __ LASMIDPKM101, MUTAT. RES. 223(1):13-22, 1989"


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PHP Expression
PHP expression implies PHP source code written in Seasar2 dicon file. Besides <property> element in a dicon file, PHP expression may be written in <component> element, <initMethod> element, <destroyMethod> element, <arg> element, <meta> element, and <aspect> element. dicon file used in this sample is included in s2container.php5/src/examples/expression.
arg, property, aspect, meta Tag
Return to PHP expression arguments to Constructor and value assigned to a property. <?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE components PUBLIC "-//SEASAR2.1//DTD S2Container//EN"
"http://www.seasar.org/dtd/components21.dtd">
<components>
<component name="sample1" class="ArgExp">
<arg>10</arg>
<property name="message">
file_get_contents(EXAMPLE_DIR . '/dicon/expression/ArgSample.txt')
</property>
</component>
<component name="sample2" class="ArgExp">
<arg>2+3</arg>
<property name="message">
$msg1 = "Hello ";
$msg2 = "World";
return $msg1 . $msg2;
</property>
</component>
</components>
When PHP expression does not include a return, return is automatically inserted. In component sample1,
arugment to a constructor return 10; and message property return file_get_contents(EXAMPLE_DIR . '/dicon/expression/ArgSample.txt'); are processed by a eval function.
PHP expression may also be included in aspect tags and meta tags.
component tag
PHP expression returning an object. <?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE components PUBLIC "-//SEASAR2.1//DTD S2Container//EN"
"http://www.seasar.org/dtd/components21.dtd">
<components>
<component name="hello">
new ComponentExp("Hello")
<property name="messageB">"World"</property>
</component>
<component name="hello2" class="ComponentExp">
hello3
</component>
<component name="hello3" class="ComponentExp"/>
</components>
When there is a class attribute to a component tag, object returned by PHP expression and ReflectionClass#isSubclassOf are compared.
initMethod, destroyMethod tags
Component initialization and exiting processes written in PHP expression. $component variable is used to reference itself. <?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE components PUBLIC "-//SEASAR2.1//DTD S2Container//EN"
"http://www.seasar.org/dtd/components21.dtd">
<components>
<component name="method" class="MethodExp">
<initMethod>
$component->init(10)
</initMethod>
</component>
</components>
|


Class: Sunspot::DSL::FieldQuery
- Inherits:
-
Scope
- Object
- Scope
- Sunspot::DSL::FieldQuery
- Defined in:
- sunspot/lib/sunspot/dsl/field_query.rb
Overview
Provides an API for areas of the query DSL that operate on specific fields. This functionality is provided by the query DSL and the dynamic query DSL.
Direct Known Subclasses
Constant Summary
Constants inherited from Scope
Instance Method Summary (collapse)
- - (Object) dynamic(base_name, &block)
-
- (Object) facet(*field_names, &block)
Request a facet on the search query.
-
- (FieldQuery) initialize(search, query, setup)
constructor
:nodoc:.
-
- (Object) order_by(field_name, direction = nil)
Specify the order that results should be returned in.
-
- (Object) order_by_random
DEPRECATED Use order_by(:random).
Methods inherited from Scope
#all_of, #any_of, #text_fields, #with, #without
Constructor Details
- (FieldQuery) initialize(search, query, setup)
:nodoc:
9 10 11 12 |
# File 'sunspot/lib/sunspot/dsl/field_query.rb', line 9 def initialize(search, query, setup) #:nodoc: @search, @query = search, query super(query.scope, setup) end |
Instance Method Details
- (Object) dynamic(base_name, &block)
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# File 'sunspot/lib/sunspot/dsl/field_query.rb', line 270 def dynamic(base_name, &block) dynamic_field_factory = @setup.dynamic_field_factory(base_name) Sunspot::Util.instance_eval_or_call( FieldQuery.new(@search, @query, dynamic_field_factory), &block ) end |
- (Object) facet(*field_names, &block)
Request a facet on the search query. A facet is a feature of Solr that determines the number of documents that match the existing search and an additional criterion. This allows you to build powerful drill-down interfaces for search, at each step presenting the searcher with a set of refinements that are known to return results.
In Sunspot, each facet returns zero or more rows, each of which represents a particular criterion conjoined with the actual query being performed. For field facets, each row represents a particular value for a given field. For query facets, each row represents an arbitrary scope; the facet itself is just a means of logically grouping the scopes.
Examples
Field Facets
A field facet is specified by passing one or more Symbol arguments to this method:
Sunspot.search(Post) do with(:blog_id, 1) facet(:category_id) end
The facet specified above will have a row for each category_id that is present in a document which also has a blog_id of 1.
Multiselect Facets
In certain circumstances, it is beneficial to exclude certain query scopes from a facet; the most common example is multi-select faceting, where the user has selected a certain value, but the facet should still show all options that would be available if they had not:
Sunspot.search(Post) do with(:blog_id, 1) category_filter = with(:category_id, 2) facet(:category_id, :exclude => category_filter) end
Although the results of the above search will be restricted to those with a category_id of 2, the category_id facet will operate as if a category had not been selected, allowing the user to select additional categories (which will presumably be ORed together).
It possible to exclude multiple filters by passing an array:
Sunspot.search(Post) do with(:blog_id, 1) category_filter = with(:category_id, 2) = with(:author_id, 3) facet(:category_id, :exclude => [category_filter, ].compact) end
You should consider using .compact to ensure that the array does not contain any nil values.
As far as I can tell, Solr only supports multi-select with field facets; if :exclude is passed to a query facet, this method will raise an error. Also, the :only and :extra options use query faceting under the hood, so these can’t be used with :extra either.
Query Facets
A query facet is a collection of arbitrary scopes, each of which represents a row. This is specified by passing a block into the #facet method; the block then contains one or more row blocks, each of which creates a query facet row. The row blocks follow the usual Sunspot scope DSL.
For example, a query facet can be used to facet over a set of ranges:
Sunspot.search(Post) do facet(:average_rating) do row(1.0..2.0) do with(:average_rating, 1.0..2.0) end row(2.0..3.0) do with(:average_rating, 2.0..3.0) end row(3.0..4.0) do with(:average_rating, 3.0..4.0) end row(4.0..5.0) do with(:average_rating, 4.0..5.0) end end end
Note that the arguments to the facet and row methods simply provide labels for the facet and its rows, so that they can be retrieved and identified from the Search object. They are not passed to Solr and no semantic meaning is attached to them. The label for facet should be a symbol; the label for row can be whatever you’d like.
Parameters
| field_names… | fields for which to return field facets |
Options
| :sort | Either :count (values matching the most terms first) or :index (lexical) |
| :limit | The maximum number of facet rows to return |
| :minimum_count | The minimum count a facet row must have to be returned |
| :zeros | Return facet rows for which there are no matches (equivalent to :minimum_count => 0). Default is false. |
| :exclude | Exclude one or more filters when performing the faceting (see Multiselect Faceting above). The object given for this argument should be the return value(s) of a scoping method (with, any_of, all_of, etc.). Only can be used for field facets that do not use the :extra or :only options. |
| :name | Give a custom name to a field facet. The main use case for this option is for requesting the same field facet multiple times, using different filter exclusions (see Multiselect Faceting above). If you pass this option, it is also the argument that should be passed to Search#facet when retrieving the facet result. |
| :only | Only return facet rows for the given values. Useful if you are only interested in faceting on a subset of values for a given field. Only applies to field facets. |
| :extra | One or more of :any and :none. :any returns a facet row with a count of all matching documents that have some value for this field. :none returns a facet row with a count of all matching documents that have no value for this field. The facet row(s) corresponding to the extras have a value of the symbol passed. Only applies to field facets. |
179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 |
# File 'sunspot/lib/sunspot/dsl/field_query.rb', line 179 def facet(*field_names, &block) = Sunspot::Util.(field_names) if block if field_names.length != 1 raise( ArgumentError, "wrong number of arguments (#{field_names.length} for 1)" ) end if .has_key?(:exclude) raise( ArgumentError, "can't use :exclude with query facets" ) end search_facet = @search.add_query_facet(field_names.first, ) Sunspot::Util.instance_eval_or_call( QueryFacet.new(@query, @setup, search_facet), &block ) elsif [:only] if .has_key?(:exclude) raise( ArgumentError, "can't use :exclude with :only (see documentation)" ) end field_names.each do |field_name| field = @setup.field(field_name) search_facet = @search.add_field_facet(field, ) Util.Array([:only]).each do |value| facet = Sunspot::Query::QueryFacet.new facet.add_positive_restriction(field, Sunspot::Query::Restriction::EqualTo, value) @query.add_query_facet(facet) search_facet.add_row(value, facet.to_boolean_phrase) end end else field_names.each do |field_name| search_facet = nil field = @setup.field(field_name) facet = if [:time_range] unless field.type.is_a?(Sunspot::Type::TimeType) raise( ArgumentError, ':time_range can only be specified for Date or Time fields' ) end search_facet = @search.add_date_facet(field, ) Sunspot::Query::DateFieldFacet.new(field, ) else search_facet = @search.add_field_facet(field, ) Sunspot::Query::FieldFacet.new(field, ) end @query.add_field_facet(facet) Util.Array([:extra]).each do |extra| if .has_key?(:exclude) raise( ArgumentError, "can't use :exclude with :extra (see documentation)" ) end extra_facet = Sunspot::Query::QueryFacet.new case extra when :any extra_facet.add_negated_restriction( field, Sunspot::Query::Restriction::EqualTo, nil ) when :none extra_facet.add_positive_restriction( field, Sunspot::Query::Restriction::EqualTo, nil ) else raise( ArgumentError, "Allowed values for :extra are :any and :none" ) end search_facet.add_row(extra, extra_facet.to_boolean_phrase) @query.add_query_facet(extra_facet) end end end end |
- (Object) order_by(field_name, direction = nil)
Specify the order that results should be returned in. This method can be called multiple times; precedence will be in the order given.
Parameters
| field_name | the field to use for ordering |
| direction | :asc or :desc (default :asc) |
22 23 24 25 26 27 28 29 30 31 32 |
# File 'sunspot/lib/sunspot/dsl/field_query.rb', line 22 def order_by(field_name, direction = nil) sort = if special = Sunspot::Query::Sort.special(field_name) special.new(direction) else Sunspot::Query::Sort::FieldSort.new( @setup.field(field_name), direction ) end @query.add_sort(sort) end |
- (Object) order_by_random
DEPRECATED Use order_by(:random)
37 38 39 |
# File 'sunspot/lib/sunspot/dsl/field_query.rb', line 37 def order_by_random order_by(:random) end |


This constructor is an implementation detail. Do not use this.
The delta to show for the segment with the specified index. You may not provide an out of bounds index.
Describes whether a more pronounced separator should be shown in front of the last segment provided.
Returns the amount of icon changes that happened in this state object.
The segment's icon encoded as a Data URL of the icon change with the specified index. The String itself may be empty. This indicates that there is no icon. You may not provide an out of bounds index.
Accesses the index of the segment of the icon change with the specified index. This is based on the index in the run, not on the index of the SplitState in the State object. The corresponding index is the index field of the SplitState object. You may not provide an out of bounds index.
Describes if the segment with the specified index is the segment the active attempt is currently on.
Returns the amount of segments to visualize.
The name of the segment with the specified index. You may not provide an out of bounds index.
The semantic coloring information the delta time carries of the segment with the specified index. You may not provide an out of bounds index.
The split time to show for the segment with the specified index. You may not provide an out of bounds index.
Generated using TypeDoc
The state object that describes a single segment's information to visualize.


Swiper Demos using React-Swiper
For more examples please check Swiper's official demos
page
.
Responsive / Fullscreen + Pagination
Infinite Loop
Slides Per View / Carousel Mode


A video game collection tracker. I built Gamr as part of my personal project at Enspiral Dev Academy. I have recently started adding Redux for state management and am going to be adding Passport.js for authentication - code.
A tool to search cities for upcoming gigs in order to create Spotify playlists. Uses both the Spotify and Songkick APIs. My team are going to get together in the coming weeks to decide on new features to add and to squash some bugs - code.


| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | package org.apache.commons.math3.genetics; | |
| 18 | ||
| 19 | import java.util.ArrayList; | |
| 20 | import java.util.List; | |
| 21 | ||
| 22 | import org.apache.commons.math3.exception.DimensionMismatchException; | |
| 23 | import org.apache.commons.math3.exception.MathIllegalArgumentException; | |
| 24 | import org.apache.commons.math3.exception.util.LocalizedFormats; | |
| 25 | ||
| 26 | ||
| 27 | /** | |
| 28 | * One point crossover policy. A random crossover point is selected and the | |
| 29 | * first part from each parent is copied to the corresponding child, and the | |
| 30 | * second parts are copied crosswise. | |
| 31 | * | |
| 32 | * Example: | |
| 33 | * <pre> | |
| 34 | * -C- denotes a crossover point | |
| 35 | * -C- -C- | |
| 36 | * p1 = (1 0 1 0 0 1 | 0 1 1) X p2 = (0 1 1 0 1 0 | 1 1 1) | |
| 37 | * \------------/ \-----/ \------------/ \-----/ | |
| 38 | * || (*) || (**) | |
| 39 | * VV (**) VV (*) | |
| 40 | * /------------\ /-----\ /------------\ /-----\ | |
| 41 | * c1 = (1 0 1 0 0 1 | 1 1 1) X c2 = (0 1 1 0 1 0 | 0 1 1) | |
| 42 | * </pre> | |
| 43 | * | |
| 44 | * This policy works only on {@link AbstractListChromosome}, and therefore it | |
| 45 | * is parameterized by T. Moreover, the chromosomes must have same lengths. | |
| 46 | * | |
| 47 | * @param <T> generic type of the {@link AbstractListChromosome}s for crossover | |
| 48 | * @since 2.0 | |
| 49 | * @version $Id$ | |
| 50 | * | |
| 51 | */ | |
| 52 | public class OnePointCrossover<T> implements CrossoverPolicy { | |
| 53 | ||
| 54 | /** | |
| 55 | * Performs one point crossover. A random crossover point is selected and the | |
| 56 | * first part from each parent is copied to the corresponding child, and the | |
| 57 | * second parts are copied crosswise. | |
| 58 | * | |
| 59 | * Example: | |
| 60 | * <pre> | |
| 61 | * -C- denotes a crossover point | |
| 62 | * -C- -C- | |
| 63 | * p1 = (1 0 1 0 0 1 | 0 1 1) X p2 = (0 1 1 0 1 0 | 1 1 1) | |
| 64 | * \------------/ \-----/ \------------/ \-----/ | |
| 65 | * || (*) || (**) | |
| 66 | * VV (**) VV (*) | |
| 67 | * /------------\ /-----\ /------------\ /-----\ | |
| 68 | * c1 = (1 0 1 0 0 1 | 1 1 1) X c2 = (0 1 1 0 1 0 | 0 1 1) | |
| 69 | * </pre> | |
| 70 | * | |
| 71 | * @param first first parent (p1) | |
| 72 | * @param second second parent (p2) | |
| 73 | * @return pair of two children (c1,c2) | |
| 74 | * @throws MathIllegalArgumentException iff one of the chromosomes is | |
| 75 | * not an instance of {@link AbstractListChromosome} | |
| 76 | * @throws DimensionMismatchException if the length of the two chromosomes is different | |
| 77 | */ | |
| 78 | @SuppressWarnings("unchecked") // OK because of instanceof checks | |
| 79 | public ChromosomePair crossover(final Chromosome first, final Chromosome second) | |
| 80 | throws DimensionMismatchException, MathIllegalArgumentException { | |
| 81 | ||
| 82 |
2
1. crossover : negated conditional → KILLED 2. crossover : negated conditional → KILLED |
if (! (first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) { |
| 83 | throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME); | |
| 84 | } | |
| 85 |
1
1. crossover : mutated return of Object value for org/apache/commons/math3/genetics/OnePointCrossover::crossover to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return crossover((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second); |
| 86 | } | |
| 87 | ||
| 88 | ||
| 89 | /** | |
| 90 | * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover. | |
| 91 | * | |
| 92 | * @param first the first chromosome. | |
| 93 | * @param second the second chromosome. | |
| 94 | * @return the pair of new chromosomes that resulted from the crossover. | |
| 95 | * @throws DimensionMismatchException if the length of the two chromosomes is different | |
| 96 | */ | |
| 97 | private ChromosomePair crossover(final AbstractListChromosome<T> first, | |
| 98 | final AbstractListChromosome<T> second) throws DimensionMismatchException { | |
| 99 | final int length = first.getLength(); | |
| 100 |
1
1. crossover : negated conditional → KILLED |
if (length != second.getLength()) { |
| 101 | throw new DimensionMismatchException(second.getLength(), length); | |
| 102 | } | |
| 103 | ||
| 104 | // array representations of the parents | |
| 105 | final List<T> parent1Rep = first.getRepresentation(); | |
| 106 | final List<T> parent2Rep = second.getRepresentation(); | |
| 107 | // and of the children | |
| 108 | final ArrayList<T> child1Rep = new ArrayList<T> (first.getLength()); | |
| 109 | final ArrayList<T> child2Rep = new ArrayList<T> (second.getLength()); | |
| 110 | ||
| 111 | // select a crossover point at random (0 and length makes no sense) | |
| 112 |
2
1. crossover : Replaced integer subtraction with addition → KILLED 2. crossover : Replaced integer addition with subtraction → KILLED |
final int crossoverIndex = 1 + (GeneticAlgorithm.getRandomGenerator().nextInt(length-2)); |
| 113 | ||
| 114 | // copy the first part | |
| 115 |
3
1. crossover : changed conditional boundary → KILLED 2. crossover : Changed increment from 1 to -1 → KILLED 3. crossover : negated conditional → KILLED |
for (int i = 0; i < crossoverIndex; i++) { |
| 116 | child1Rep.add(parent1Rep.get(i)); | |
| 117 | child2Rep.add(parent2Rep.get(i)); | |
| 118 | } | |
| 119 | // and switch the second part | |
| 120 |
3
1. crossover : changed conditional boundary → KILLED 2. crossover : Changed increment from 1 to -1 → KILLED 3. crossover : negated conditional → KILLED |
for (int i = crossoverIndex; i < length; i++) { |
| 121 | child1Rep.add(parent2Rep.get(i)); | |
| 122 | child2Rep.add(parent1Rep.get(i)); | |
| 123 | } | |
| 124 | ||
| 125 |
1
1. crossover : mutated return of Object value for org/apache/commons/math3/genetics/OnePointCrossover::crossover to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return new ChromosomePair(first.newFixedLengthChromosome(child1Rep), |
| 126 | second.newFixedLengthChromosome(child2Rep)); | |
| 127 | } | |
| 128 | ||
| 129 | } | |
Mutations | ||
| 82 |
1.1 2.2 |
|
| 85 |
1.1 |
|
| 100 |
1.1 |
|
| 112 |
1.1 2.2 |
|
| 115 |
1.1 2.2 3.3 |
|
| 120 |
1.1 2.2 3.3 |
|
| 125 |
1.1 |


I come from Kerkini Serres, Greece and I'm 29 years old. In 2012 I got in the Aristotle University of Thessaloniki, in the Geology department, which I studied until December 2015, but realizing that it is not an area I am interested in, I made the decision to pause my studies and pursue my favorite subject, computers and programming. In 2018 I got a degree from Institute of Professional Studies "DELTA" in the section of "Computer Applications Technician (Multimedia / Web Designer - Developer / Video Games)".
Experience in building and maintaining websites and e-shops with Wordpress, Joomla and OpenCart. Knowledge of HTML, HTML5, CSS, PHP, Javascript.
Good knowledge & ability in design programs like Photoshop, Illustrator, Affinity Photo, Krita and others.
Internship at OTE SA, as a network technician from 09/2018 to 03/2019. Design, develop and manage websites with Joomla, Wordpress and OpenCart at InfonetGroup Web Services from 04/2019 until 09/2019.
*The website parisrestaurant.gr was created for a customer of InfonetGroup Web Services and under its employment.


I
CW WorkBench
Supervisor
Students
Mentor
{ Left Side Navigation }
System Analysis
Reliability
Robustness
Complexity
Performance
Hardware
Single Unit
Comparative
Components
Memory
Bus
Network
M
1
M
2
IC = 2,487 instr
CPI = 2.6 cyc/instr
Clock = 4.6 GHz
Performance Calculation for M
Time
=
IC
x
CPI
x
Clock Period
=
=
IC = 2,487 instr
CPI = 3.8 cyc/instr
Clock = 2.3 GHz


Uh-Oh! Not Found
You’re in the middle of nowhere. You need to verify your password.
What you can do:
Go back
Home
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to get help with any other error


PEP Draw
In the canvas above, we are drawing squares when the event
pointermove
is triggered.
Original demo code by
Alex Schmitz


Fundamental powershell cmdlets for beginners
October 13th, 2019
Powershell can be confusing for beginners, especially those coming from imperitive, compiled languages like C++ or C#. If you are not used to the command line, not only could you struggle with the syntax of powershell, but also the fundamental question of what you even do with powershell.
Powershell is often advertised as a great tool for network admins who have large clusters of machines to monitor and maintain. Remote computer administration tasks are advanced uses. In my opinion, Powershell is great for beginners (and beyond) who just want to explore and understand their own machine.
In this post I'll explore the top 4 cmdlets a beginner should know when getting started with powershell. You'll end up using these commands even when your an advanced powershell user. Ok, enough said. Lets explore some commands.
- Get-ChildItem
On the surface, the Get-ChildItem cmdlet is essentially getting all the items in a container (e.g. all the files and folders inside your current working directory). This is roughly equivalent to the "dir" command in CMD. In fact powershell automatically aliases dir to Get-ChildItem.
The basic usage will get you the list of files and folders in your current working directory along with some meta information about those items including the length in bytes if the item is a file.
PS /Users/Taylor> Get-ChildItem Mode LastWriteTime Length Name ---- ------------- ------ ---- d----- 2/22/19 10:19 PM Alpha d----- 9/9/19 2:56 PM Beta d----- 9/24/19 9:23 AM 1028 gamma.txt d----- 7/1/19 11:58 AM 2034 delta.txt
You can pass the -Path flag to Get-ChildItem to explore containers outside of your current working directory.
Get-ChildItem -Path ~/path/to/folder
Other notable flags for the Get-ChildItem cmdlet are:
- -Recurse
Get all the items in a container and all the items in all sub-containers.
- -Filter [pattern]
Only those items matching the pattern are returned. Can use * and ? wildcards.
- -Force
Get items that otherwise wouldn't be returned such as hidden files. Doesn't override security restrictions.
- -Recurse
- Get-Content
Get-Content does exactly what it looks like. It retrieves the contents of files. It can do a bit more than that, but for a beginner that is what you'll use it for. In CMD the "type" command will print to the scren that contents of a file. Get-Content can print content to the screen, but often you will want to pipe the contents of a file to another cmdlet.
Lets look at some usages:
PS /Users/Taylor> Get-Content -Path hello.txt Hello, World!
PS /Users/Taylor> Get-Content -Path ~/Logs/ -Filter *2019*.log [Lots of output here]
Other notable flags for the Get-Content cmdlet are:
- -Raw
By default, Get-Content returns an array of strings, one string per line in the file. Using the -Raw flag you can get the entire contents back as a single string.
- -TotalCount
How many lines to read from a file from the start. Useful for checking if the file is what you are looking for.
- -Tail
How many lines from the end to read. Very useful for peeking at recent entries in a log file.
- -Raw
- Select-Object
Select-Object takes an object and returns an object, usually after a bit of transformation. You could take in an array of DirectoryInfo object (produced by Get-ChildItem) and return another array of objects with just "Name" and "Extension" properties. You can also select the first or last item in a collection. Select-Object has a lot of in common with select in linq from C#.
Imagine you want to use the Get-ChildItem cmdlet to get all the files in the current directory. You would use this command:
PS /Users/Taylor> Get-ChildItem -File
Instead of getting all the properties back from this command image you just wanted the Name and Length property. You would pipe that output of that command to a Select-Object with the -Property flag:
PS /Users/Taylor> Get-ChildItem -File | ` Select-Object -Property Name, Length
The -Property parameter specifies which properties from the objects being piped in you want to extract and add to the objects coming out. Also notice you can use the backtick (`) to split commands across lines.
If you want to get the first item in a list use the -First flag.
PS /Users/Taylor> Get-ChildItem -File | ` Select-Object -First 1
Select has a lot of power, and you will use it a lot to transform the output of one cmdlet into the right "shape" for another cmdlet. Other notable parameters for Select-Object are:
- -Last [number]
Get the last X items in a list.
- -Unique
If objects have the same properties and values then only 1 will be added to the output collection.
- -Skip [number]
Skip X items from the start of a collection and return the rest.
- -ExpandProperty [property name]
Return a collection of a specificed property, rather than a collection of objects with that property.
- -Last [number]
- Where-Object
Where-Object is your general-purpose filter: given a collection, filter the objects so that only those meeting a certain condition are returned as output. The simple usage is:
Where-Object Name -eq file.txt
This command is saying only return objects whose name property equals "file.txt". The -eq operator is the powershell equals operator (e.g. == in many other languages).
Where-Object has a lot of power, and is very useful for trimming down the output of one cmdlet before inputing it into another.
A couple of other notable parameters are:
- -Like
If a property value is like rather than equals a certain value. Use wildcards * and ? to match.
Where-Object Name -Like *.txt
- -Not
If a property value is not a value.
- -Like
Powershell is a great tool for exploring and working with your own machine. If you are going to learn powershell I highly recommend focusing on the fundamentals first, because these commands and a few others are really the bread and butter of powershell. Happy scripting!