1 Help zone is a community of people willing and able to help people. We have a common goal of helping humanity. it is not a bank, it is not a corporative society, it is just a meeting point for well-meaning individuals expressing their willingness to help other people. We have no central account, so participant pays directly into other participant’s bank account without any conditions, Promises or guarantees.
No Lender, No investor and no Guaranty, your money is not growing because we are not investing your money, rather your money qualifies you to get help from other people in a multiples of your donated help.
This community is not made up of houses, cars and businesses or legal entities rather it is made up of ordinary people loving and caring for each other. Therefore, the survival of this community is on your hand. You may say I have seen many of such systems, yes, but we are with a difference, the lifespan of this system remains as long as you continue to perform your obligation faitfully.
If you know you are willing to help someone, then create and Account by clicking on “Create account” link on the main page. After signing up, then login into your dashboard and click on “Account” and update your bank account information. After that you are good to go.
We have a single regime of N25, 000.00 meaning we only accept one amount which is 25k. Click on “Provide help” and accept terms and conditions, after that wait for you to be matched to another participant which you will pay. When you are matched, Click on the Participant’s name to reveal his/her bank details, make payment by Paying directly to the participant’s account using Mobile or Online transfer. Then upload your proof of payment contact the participant to let him/her know that you have paid money to his/her account.
After the payment has been confirmed, you will then be eligible to get help. To get help, Click on “Get Help” link on your dashboard, and accept the terms and condition, then wait for other 2 participants to be matched to pay you N25,000.00 each making it a total of N50,000.00. Make sure you confirm the receipt of the payments as soon as the payment is made.
NOTE: you are expected to make payment within 24hrs after you have been paired to provide help.
We believe in reward for labour that is why we set a reward mechanism for those that really work and make sure that this community continues to grow. For every participant you referred to the community, you are entitled to a one-time N5, 000.00 when the person provides help and pays his pledge. This referrals bonuses is withdrawable in multiple of 5. That is you can only withdraw your bonuses when you have 5 people under you that have provided help and payed their pledges.
NOTE: You cannot withdraw referral bonuses alone, you must withdraw it along with you get help amount. Meaning that when withdrawing referral bonuses, you will get help of N75, 000.00. instead of N50,000.00.
1.
2. If you upload fake Proof of Payment, Your account will be deleted from our system.


PROCEDURE IN THE CASE OF A COMPLAINT OF MISCONDUCT
1. NOTIFICATION OF MISCONDUCT
A student will not be formally charged with misconduct until a written
and signed statement containing an accusation, complaint or allegation made
against the student has been submitted to the Registrar or a person authorised by
him/her to receive such complaint, provided that nothing contained herein will
prpromotion the Registrar from laying a complaint of misconduct against a student.
2. PRELIMINARY INVESTIGATION
2.1 The Registrar appoints one or more persons to conduct a preliminary investigation
into an accusation, complaint or allegation brought to his/her attention. The Registrar may,
at his/her discretion, conduct the investigation him/herself.
2.2 Such person(s) so appointed submits a written report and/or charge sheet to the
Registrar.
2.3 The person(s) appointed to conduct the preliminary investigation may consult with or
obtain information from any person, including the student against whom the accusation, complaint
or allegation has been made.
3. REFERRAL TO THE STUDENT DISCIPLINARY COMMITTEE (SDC)
3.1 If the Registrar is of the opinion that there is a prima
facie case and that there are reasonable grounds for a charge of
misconduct and that the misconduct is of a
serious nature, he/she drafts a written charge or has
such charge drawn up to be heard by the SDC.
3.2 If the Registrar is of the opinion that
an alleged misconduct of a student constitutes a minor
contravention of the Code, the Registrar may exercise his/her
discretion to decide what further steps should be taken in
response to the alleged misconduct.
4. NOTICE TO THE ACCUSED STUDENT
4.1 When proceedings against a student are instituted in terms of paragraph 3 above
, the Registrar will give the student concerned not less than fourteen calendar days’ notice
in writing of the date, time and place of the hearing by the SDC.
4.2 The Notice under this rule will inform the student:
4.2.1 that proceedings under the Students’ Disciplinary Code are to be instituted against him/her
and that a copy of the Code is available for inspection in the Office of the Registrar or on the University
student website,
4.2.2 of the Rule that the student is alleged to have breached and/or the act(s) of misconduct that the student
is alleged to have committed. The Notice must set out the charge with sufficient particularity to enable the student
to prepare for his/her defence,
4.2.3 of his/her right to answer the charge in writing at least four calendar days before the hearing,
4.2.4 of his/her right to attend the hearing to present his/her case, or to be represented at the hearing
by another student, member of the Student Representative Council or an employee of the University, and
4.2.5 of his/her right if he/she is a minor to be assisted by his/her parent or guardian or,
at the discretion of the SDC, to be assisted by any other person appointed by such parent
or guardian, provided that nothing contained in this Rule renders the conduct of the SDC void
if the student is not so assisted on the date set for the hearing.
5. SERVICE OF NOTICE
5.1 Service of any written notice and the furnishing of
particulars in terms of this Code will be by prepaid, registered post
to the residential address provided either on the most recent application
form completed by the student for the purpose of registration or on any later
written notice submitted by the student to the University of a change of address.
5.2 In the case of such service the student will be deemed to have received the Notice
and particulars within five calendar days of the date of posting thereof.
6. SUSPENSION
6.1 No student will be suspended from the University before a hearing is held. However,
the Registrar may use an abridged service of Notice to convene an emergency SDC that will determine
the need for a temporary suspension which will serve to prohibit such student from:
6.1.1 entering onto the premises of the University, or any part thereof, and/or
6.1.2 using an opportunity resulting from his/her enrolment as a student.
6.2 A temporary suspension in terms of paragraph 6.1 remains in force for the period not exceeding
thirty calendar days or until the disciplinary proceedings in terms of this Code have been completed,
whichever instance may first occur.
6.3 The suspended student may make written representations to the Principal and Vice Chancellor
within five calendar days of receipt of written notice of his/her suspension, advancing reasons why
he/she should not be suspended.
6.3.1 The Principal and Vice Chancellor may at his/her discretion revoke a suspension at any time,
provided that, notwithstanding such revocation, further steps may be taken to proceed with the disciplinary
hearing on the charge of misconduct against the student.
6.3.2 The Principal and Vice Chancellor may, at his/her discretion, also confirm the suspension.


Transform XML Document
Document to transform
Display output as
xalanApplets.xml
foo-s1.xml
HTML
HTML Source


UTT’s Bond Fund IPO raises over 15.9bn/- in a month
by Beatrice PhilemonUTT Asset Management and Investor Services’ Bond Fund has raised 15.9bn/- during a month long initial public offer period which ended mid October this year.
UTT AMIS’ Senior Public Relations and Marketing Manager, Rahim Mwanga said in Dar es Salaam this week that after the IPO period, the Bond Fund has now entered the secondary market and will sell at 101/- from 100/- which was the IPO price.
“We would like to invite prospective investors to come forward and by some part of the bond and earn some dividend in future,” said Mwanga who stated that 1,400 investors took part during the IPO which started mid September this year.
He said the bond which interest pegged at seven year Treasury Bond is a lucrative vehicle fir any investors to put their money in with as little as 50,000/- of purchase. “All funds are accessible after three months of lock in period with payment being made within 10 days,” he noted while pointing out that investors can buy their stake using any mobile money platform.
Speaking during the IPO launch, UTT-AMIS Managing Director, Simon Migangala said the bond fund was aimed at ensuring that more Tanzanians including those in rural areas take part in collective investment schemes.
“UTT-AMIS is looking to widen the participation of all Tanzanians by putting initial investment to as low as 50,000/- where bond fund offers annual, semiannual and monthly income distribution,” Migangala said.
He said those investing 10m/-will be eligible for monthly income distribution while the 5m/-investors will receive semiannual earnings but for investors who part with 50,000/-, they benefiting from capital appreciation.
The UTT-AMIS CEO further said rural folks are targeted investors by the bond because they can use mobile phones to buy their stake without the need to visit physical agents or brokers most of who are urban based.


Having got Odio to a reasonable state, the next step is to incorporate a RELAX NG validator into it, to make sure the output of Odio is always a valid ODF document. I couldn't find a Python RELAX NG validator, so I've embarked on Prang.
Armed with the RELAX NG specification, tutorial and suggested algorithm, I'm tackling this daunting task. Actually, dear reader, I'm finding it tough going. I haven't given up though...


Timestamp Logger
User Stories
- I can pass a string as a parameter, and it will check to see whether that string contains either a unix timestamp or a natural language date (example: January 1, 2016)
- If it does, it returns both the Unix timestamp and the natural language form of that date.
- If it does not contain a date or Unix timestamp, it returns null for those properties.
Example Usage
https://timestamp-logger.glitch.me/December%2015,%202015
https://https://timestamp-logger.glitch.me/1450137600
Example Output
{ "unix":<PHONE_NUMBER>, "natural": "December 15, 2015" }


|
Class Summary |
| BatchQueryUtils |
Collection of utility methods to work with BatchQueries. |
| ConnectionEventLogger |
|
| ContextCommitObserver |
ContextCommitObserver is used as an observer for DataContext
commit operations. |
| ContextSelectObserver |
Deprecated. Since 1.1 Cayenne internally uses a superclass SelectObserver that
has all needed functionality to convert rows to objects. |
| DataNodeCommitHelper |
|
| DefaultOperationObserver |
Simple implementation of OperationObserver interface. |
| DefaultSorter |
Deprecated. Since 1.1 use EntitySorter |
| IteratedSelectObserver |
OperationObserver that is used to track the execution
of SelectQueries with results returned as ResultIterator. |
| NullSorter |
Deprecated. Since 1.1 NullSorter is an inner class of DataNode. |
| PrefetchHelper |
A helper class to resolve relationships in batches for the lists of objects. |
| PrimaryKeyHelper |
PrimaryKeyHelper resolves primary key dependencies for entities
related to the supported query engine via topological sorting. |
| QueryUtils |
Implements helper methods that perform different query-related operations. |
| RelationshipFault |
Deprecated. Since 1.1 Fault is used in Cayenne as a stateless
flyweight for all kinds of relationships. |
| ResultDescriptor |
Contains information about the ResultSet used to process fetched rows. |
| SelectObserver |
OperationObserver that accumulates select query results provided
by callback methods. |


Making HTML slides & handout notes
by Eric J. Ma (MIT)
14 December 2016
introduction
In this tutorial, I will show you how you can use a single Markdown source file to create HTML notes and Reveal.js versions of your slides.
versions
why? (philosophical)
- I've grown frustrated with the opacity of Keynote and PowerPoint files
- I've come to like having more granular control over my presentations
why? (practical)
- It's useful to have a single-page HTML version of your slide to make things easier for your listeners to follow along.
- Write once, output everywhere.
- Markdown + Reveal.js + Pandoc = full, version-controlled, source for multiple outputs.
prerequisite knowledge
I'm assuming that you:
- know how to use
git
,
- are comfortable working at the command line,
- can grasp simple HTML, CSS, Bash and Python.
what you'll be able to do by the end
- Create a markdown file and convert it to Reveal.js slides and a single-page HTML notes version.
- Create a custom CSS file for styling the slides and HTML notes.
- Modify the template to add in elements that you decide are necessary.
how?
Let's get setup!
install
git clone
prepare
- Create new repository (hereby called
repo
) to hold slides (distinct from hakimel/reveal.js
)
- Copy from
hakimel/reveal.js
into repo
:
make slides source
- create a file called
slides.md
$ touch slides.md
Use standard Markdown.
---
title: My Title Goes Here
author:
- name: My Name Here
affiliation: My Affiliation Here
---
fill in content
# slide 1 title
- Bullet point 1
- Bullet point 2
- Bullet point 3
# sub-slide title
1. Numbered point.
1. Numbered point.
# slide 2 title
Some text. A [url] to somewhere.
[url]: http://myfavoritewebsite.com/
create your build script (ver.1)
write your build script (ver.1)
write your pandoc commands into the build script
# Make revealjs version of slides
pandoc slides.md -o slides.html \
--section-divs \
-t revealjs \
-s \
--template template.revealjs
open and view your slides!


Toggle navigation
Track G - Oakland's Measure G
About
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Explore
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Ophelia's Oasis is a 45-room hotel situated on the top of a mountain overlooking the most beautiful part of the Amlet Desert in Australia. Every room has an uninterrupted view of the desert sketching to the horizon some 15 or 20 miles away.
Start Date
End Date
Number of rooms
Save 25%. Pay full amount at least 90 days prior reservation start date. The reservation can be changed (subject to avaibility).
Save 15%. Pay full amount 30 days prior reservation start date. The reservation can be changed (subject to avaibility).
Pay full amount after your stay. No show and cancellation penalties may apply.


|
DESERT
3.0
|
#include <packer-common.h>
Public Member Functions | |
| packerCOMMON () | |
| ~packerCOMMON () | |
| Public Member Functions inherited from packer | |
| packer (bool) | |
| ~packer () | |
| int | command (int, const char *const *) |
| size_t | getPayloadBytesLength () |
| size_t | getHdrBytesLength () |
| size_t | getPayloadBinLength () |
| size_t | getHdrBinLength () |
| std::string | packPayload (Packet *) |
| std::string | packHdr (Packet *) |
| Packet * | unpackPayload (Packet *) |
| Packet * | unpackHdr (Packet *) |
| void | printMap () |
Private Types | |
| enum | nbits_index { PTYPE = 0, SIZE, UID, ERROR, TIMESTAMP, DIRECTION, PREV_HOP, NEXT_HOP, ADDR_TYPE, LAST_HOP, TXTIME, errbitcnt_, fecsize_, iface_, src_rt_valid, ts_arr_, aomdv_salvage_count_, xmit_failure_, xmit_failure_data_, xmit_reason_, num_forwards_, opt_num_forwards_ } |
Private Member Functions | |
| void | init () |
| size_t | packMyHdr (Packet *, unsigned char *, size_t) |
| size_t | unpackMyHdr (unsigned char *, size_t, Packet *) |
| void | printMyHdrMap () |
| void | printMyHdrFields (Packet *) |
Private Attributes | |
| size_t | PTYPE_Bits |
| size_t | SIZE_Bits |
| size_t | UID_Bits |
| size_t | ERROR_Bits |
| size_t | TIMESTAMP_Bits |
| size_t | DIRECTION_Bits |
| size_t | PREV_HOP_Bits |
| size_t | NEXT_HOP_Bits |
| size_t | ADDR_TYPE_Bits |
| size_t | LAST_HOP_Bits |
| size_t | TXTIME_Bits |
| size_t | errbitcnt_Bits |
| size_t | fecsize_Bits |
| size_t | iface_Bits |
| size_t | src_rt_valid_Bits |
| size_t | ts_arr_Bits |
| size_t | aomdv_salvage_count_Bits |
| size_t | xmit_failure_Bits |
| size_t | xmit_failure_data_Bits |
| size_t | xmit_reason_Bits |
| size_t | num_forwards_Bits |
| size_t | opt_num_forwards_Bits |
Additional Inherited Members | |
| Static Public Member Functions inherited from packer | |
| template<typename T > | |
| static T | restoreSignedValue (T _header_field, const uint32_t &_num_compressed_bits) |
| static std::string | hexdump_nice (std::string) |
| static std::string | hexdump_nice (const char *, size_t) |
| static std::string | hexdump (std::string) |
| static std::string | hex_bytes (float) |
| static std::string | hex_bytes (double) |
| static std::string | hex_bytes (const char &, const uint32_t &) |
| static std::string | hex_bytes (const int8_t &, const uint32_t &) |
| static std::string | hex_bytes (const int16_t &, const uint32_t &) |
| static std::string | hex_bytes (const int32_t &, const uint32_t &) |
| static std::string | hex_bytes (const int64_t &, const uint32_t &) |
| static std::string | hex_bytes (const uint8_t &, const uint32_t &) |
| static std::string | hex_bytes (const uint16_t &, const uint32_t &) |
| static std::string | hex_bytes (const uint32_t &, const uint32_t &) |
| static std::string | hex_bytes (const uint64_t &, const uint32_t &) |
| static std::string | hexdump (const char *, size_t) |
| static std::string | bindump (std::string) |
| static std::string | bindump (const char *, size_t) |
| Protected Member Functions inherited from packer | |
| virtual void | printMyHdrField (Packet *, int) |
| size_t | getMyHdrBinLength () |
| size_t | get (unsigned char *buffer, size_t offset, void *val, size_t h) |
| size_t | put (unsigned char *buffer, size_t offset, void *val, size_t h) |
| Protected Attributes inherited from packer | |
| std::vector< size_t > | n_bits |
| int | debug_ |
Class to map a ns2 mac header into a bit stream, and vice-versa.
Definition at line 52 of file packer-common.h.
|
private |
Definition at line 68 of file packer-common.h.
| packerCOMMON::packerCOMMON | ( | ) |
Class constructor.
Definition at line 60 of file packer-common.cpp.
| packerCOMMON::~packerCOMMON | ( | ) |
Class destructor.
Definition at line 145 of file packer-common.cpp.
|
privatevirtual |
|
privatevirtual |
Method to transform the headers into a stream of bits.
| Pointer | to the packet to serialize |
| Pointer | to the buffer |
| Offset | from the begin of the buffer |
Reimplemented from packer.
Definition at line 185 of file packer-common.cpp.
|
privatevirtual |
Method used for debug purposes.
It prints the value of the headers of a packet
| Pointer | of the packet |
Reimplemented from packer.
Definition at line 454 of file packer-common.cpp.
|
privatevirtual |
Method used for debug purposes.
It prints the number of bits for each header serialized
Reimplemented from packer.
Definition at line 375 of file packer-common.cpp.
|
privatevirtual |
Method responsible to take the informations from the received buffer and store it into the headers of the packet.
| Pointer | to the buffer received |
| Offset | from the begin of the buffer |
| Pointer | to the new packet |
Reimplemented from packer.
Definition at line 251 of file packer-common.cpp.
|
private |
Bit length of the next_hop_ field to be put in the header stream of bits.
Definition at line 144 of file packer-common.h.
|
private |
Bit length of the ts_arr_ field to be put in the header stream of bits.
Definition at line 163 of file packer-common.h.
|
private |
Bit length of the ts_ field to be put in the header stream of bits.
Definition at line 136 of file packer-common.h.
|
private |
Bit length of the txtime_ field to be put in the header stream of bits.
Definition at line 153 of file packer-common.h.
|
private |
Bit length of the uid_ field to be put in the header stream of bits.
Definition at line 132 of file packer-common.h.
|
private |
Bit length of the errbitcnt_ field to be put in the header stream of bits.
Definition at line 155 of file packer-common.h.
|
private |
Bit length of the fecsize_ field to be put in the header stream of bits.
Definition at line 157 of file packer-common.h.
|
private |
Bit length of the addr_type_ field to be put in the header stream of bits.
Definition at line 147 of file packer-common.h.
|
private |
Bit length of the prev_hop_ field to be put in the header stream of bits.
Definition at line 142 of file packer-common.h.
|
private |
Bit length of the xmit_reason_ field to be put in the header stream of bits.
Definition at line 173 of file packer-common.h.
|
private |
Bit length of the num_forwards_ field to be put in the header stream of bits.
Definition at line 175 of file packer-common.h.
|
private |
Bit length of the direction_ field to be put in the header stream of bits.
Definition at line 139 of file packer-common.h.
|
private |
Definition at line 126 of file packer-common.h.
|
private |
Bit length of the ptype_ field to be put in the header stream of bits.
Definition at line 128 of file packer-common.h.
|
private |
Bit length of the iface_ field to be put in the header stream of bits.
Definition at line 159 of file packer-common.h.
|
private |
Bit length of the error_ field to be put in the header stream of bits.
Definition at line 134 of file packer-common.h.
|
private |
Bit length of the src_rt_valid_ field to be put in the header stream of bits.
Definition at line 161 of file packer-common.h.
|
private |
Bit length of the last_hop_ field to be put in the header stream of bits.
Definition at line 149 of file packer-common.h.
|
private |
Bit length of the size_ field to be put in the header stream of bits.
Definition at line 130 of file packer-common.h.
|
private |
Bit length of the aomdv_salvage_count_ field to be put in the header stream of bits.
Definition at line 166 of file packer-common.h.
|
private |
Bit length of the xmit_failure_ field to be put in the header stream of bits.
Definition at line 168 of file packer-common.h.
|
private |
Bit length of the xmit_failure_data_ field to be put in the header stream of bits.
Definition at line 171 of file packer-common.h.


See: Description
| Class | Description |
|---|---|
| AddAudienceRestrictionToAssertions |
Action adds an audience restriction condition to every assertion contained in a SAML 1/2
response, with the audiences obtained from a lookup function.
|
| AddInResponseToToResponse |
Action that adds the
InResponseTo attribute to a response message if a SAML message ID is set on
the inbound message context. |
| AddInResponseToToResponse.DefaultRequestIdLookupStrategy |
Default lookup of request ID from inbound message context, suppressing lookup for bindings
known to be supplying artificial IDs.
|
| AddNotBeforeConditionToAssertions |
Action that adds the
NotBefore attribute to every assertion in a SAML 1/2
response message. |
| AddNotOnOrAfterConditionToAssertions |
Action that adds the
NotBefore attribute to every assertion in a SAML 1/2
response message. |
| ChainingNameIdentifierGenerator<NameIdType extends SAMLObject> |
A compound implementation of the
NameIdentifierGenerator interface that wraps a sequence of
candidate generators along with a default to try if no format-specific options are available. |
| PopulateSignatureSigningParameters |
Action that resolves and populates
SignatureSigningParameters on a SecurityParametersContext
created/accessed via a lookup function, by default on the outbound message context. |
| SignAssertions |
Action that signs assertions in a SAML 1/2 Response returned by a lookup strategy,
by default the message returned by
InOutOperationContext.getOutboundMessageContext() . |
| VerifyChannelBindings |
Action that verifies two sets of
ChannelBindings from two different ChannelBindingsContext
objects obtained via lookup functions, by default from below the inbound message context and from below
a SOAP11Context below the inbound message context. |
Copyright © 1999–2016 Shibboleth Consortium. All rights reserved.


iBelong
SubCategory
By Category
Category where SubCategory resides:
---
{{range .}}
{{.Category}}
{{end}}
SubCategory to be removed:
Remove
Go Back


Connect with Cambuzz,explore
opportunities with our campus networking tool
Interact with other people,
ask your questions and get answers
Update yourself with upcoming
events or track your faculty outside the class
Missing out events you like? Don't you worry, because Cambuzz has the "BUZZ" feature which has the updates of the latest events also the upcoming ones. Now you won't miss any event!
Finding difficult to locate your teacher? Cambuzz will help you track the teacher on just a click! Now you can track a teacher outside the class without any difficulties.
Missing out events you like? Don't you worry, because Cambuzz has the "BUZZ" feature which has the updates of the latest events also the upcoming ones. Now you won't miss any event!


@(form: Form[Application.Login])
@form.globalError.message
@flash.get("success")
Login
You don't have an account? Register here.


| AutotunerPID Toolkit |
The ISA-PID Regulator
Several PID structure are available in literature: the regulator used in this application is the so called "ISA PID", that is widely accepted in the industrial domain. The ISA PID control law is expressed as
where Y0(s), Ym(s) and U(s) are, respectively, the Laplace transforms of the set-point (SP), the (measurement of the) controlled variable or process value (PV), and the control signal or control variable (CV), K is the PID gain, Ti the integral time, and Td the derivative time. The ISA PID encompasses the set-point weights b and c in the proportional and derivative actions.
Traditionally, b is thought to have the role to limit the control step that may arise as a consequence of an error step, while c has to limit the control spike that may arise as a consequence of an error step, also with a proper controller. In the autotuning context, b and c can have a more extensive and flexible role, however. The derivative part is made proper by adding a pole with time constant proportional to Td via parameter N.
| Introduction to PID Autotuning | Process Identification |


Hijacking SSH Agents
If you see SSH agents running on a pentest (process called “ssh-agent”), you might be able to use it to authenticate you to other hosts – or other accounts on that host. Check out ~/.ssh/known_hosts for some ideas of where you might be able to connect to.
You can use any agents running under the account you compromised. If you’re root you can use any SSH agent.
SSH agents listen on a unix socket. You need to figure where this is for each agent (e.g. /tmp/ssh-tqiEl28473/agent.28473). You can then use the agent like this:
export SSH_AUTH_SOCK=/tmp/ssh-tqiEl28473/agent.28473
ssh-add -l # lists the keys loaded into the agent
ssh user@host # will authenticate you if server trusts key in agent
This command illustrates how you could inspect the environment of every ssh-agent process on a Linux system. It should yield a list of unix sockets for SSH agents.
ps auxeww | grep ssh-agent | grep SSH_AUTH_SOCK | sed 's/.*SSH_AUTH_SOCK=//' | cut -f 1 -d ' '


Counter: Number
Description
Main clas used to replace origial number like
int
,
float
etc.
Operators
All possible operator are tracked.
Functions
Tracked functions: cos, sin, tan, acos, asin, atan, cosh, sinh, tanh, acosh, asinh, atanh.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/wf.20recursion.20after.20mathlib.20update.html ---
i updated mathlib and now some of my recursions are broken with the error message mentioned at the end of https://github.com/leanprover-community/mathlib/blob/master/src/tactic/well_founded_tactics.lean.
using the suggested fix in the link above works.
however, before updating mathlib, it worked as well.
was it intended for https://github.com/leanprover-community/mathlib/commit/140a606a461aa066927ba3a2d8e5c3976a2f7367 to break existing code that worked fine beforehand?
i can provide a code example if necessary.
actually, looking at the commit in more detail, it seems to apply the fix to a bunch of other places in mathlib as well, so i presume that it was intended.
Yes, the problem was that we wanted to add a few more @[simp] lemmas, which turned out to be so useful that the built in proving-that-the-recursion-is-decreasing tactics were succeeding before "they were expected too", and hence actually failing! That commit modified those tactics so they "weren't suprised" when the goal was discharged by simp
early in the process.
ah, alright. thanks!
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Use this list to choose the strategy to synchronize your local repository with the remote storage. The selected
method will be used when the
push
operation is rejected (if the Auto-updated if push of the current branch was rejected
option is enabled), or when you invoke the Update Project operation. The following
options are available:
git fetch
and then git merge
, or git pull
--no-rebase
.
git fetch
and then git rebase
, or git pull
--rebase
(all local commits will be put on top of the updated upstream head).


I am a full stack software engineer with a strong Javascript background. My experiences include technologies such as Node.js, Express, Socket.IO, AngularJS, MongoDB, Redis, LevelDB, Jade, EJS, D3.js, Gulp, Grunt, Drupal, Convio / Blackbaud, as well as developing Chrome Extensions, RESTful API endpoints and scalable backends. I am also experienced in Linux server administration, DNS, Load balancer configuration as well as executing load and stress testing of server infrastructures and application performance. I have a passion for thinking outside the box and love to tackle challenges together with other talented and enthusiastic engineers. Nothing is more inspiring and satisfying than seeing ideas become reality.
NPR: Ted radio hour The History of Rome
Revolutions
This American Life
Radiolab
Planet Money
Intelligence Squared
The Moth
Sci Fri
Freakonomics Radio
Note to Self
Invisibilia


|
CodeAFriend
A website for submitting and voting on code samples that solve user submitted problems. Will only support python at first.
|
Api Methods dealing with Problems. More...
Public Member Functions | |
| ProblemController (ICodeAFriendFacade facade) | |
| async Task< IActionResult > | AddProblemForUser (User.AddProblemCommand command) |
| Create the specified Problem. More... | |
| async Task< IActionResult > | UpdateProblem (User.UpdateProblemCommand command) |
| Update the specified Problem. More... | |
| async Task< IActionResult > | DeleteProblem (User.DeleteProblemCommand command) |
| async Task< IActionResult > | GetProblem (string problemName) |
| Get a specified problem. More... | |
| async Task< IActionResult > | TestScript (string problemName, Guid scriptId) |
| Submit a Script to be considered a ProblemSolution. More... | |
| async Task< IActionResult > | Vote (string problemName, Vote vote) |
| IEnumerable< ProblemSolution > | GetSolutions (string problemName) |
Additional Inherited Members | |
| Protected Member Functions inherited from CodeAFriend.ApiService.Controllers.CodaAFriendController | |
| CodaAFriendController (ICodeAFriendFacade facade) | |
| DI constructor. More... | |
| Protected Attributes inherited from CodeAFriend.ApiService.Controllers.CodaAFriendController | |
| ICodeAFriendFacade | Facade |
| ICodeAFriendFacade where all CodAFriend objects are stored. More... | |
Api Methods dealing with Problems.
| CodeAFriend.ApiService.Controllers.ProblemController.ProblemController | ( | ICodeAFriendFacade | facade | ) |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.AddProblemForUser | ( | User.AddProblemCommand | command | ) |
Create the specified Problem.
| command | Properties for the Problem. |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.DeleteProblem | ( | User.DeleteProblemCommand | command | ) |
| problemName | Name of problem to delete. |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.GetProblem | ( | string | problemName | ) |
Get a specified problem.
| problemName | Name of problem to retrieve. |
| IEnumerable<ProblemSolution> CodeAFriend.ApiService.Controllers.ProblemController.GetSolutions | ( | string | problemName | ) |
| problemName |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.TestScript | ( | string | problemName, |
| Guid | scriptId | ||
| ) |
Submit a Script to be considered a ProblemSolution.
| script | |
| problemName |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.UpdateProblem | ( | User.UpdateProblemCommand | command | ) |
Update the specified Problem.
| problemName | Name of problem to update. |
| problem | New Properties for problem. |
| async Task<IActionResult> CodeAFriend.ApiService.Controllers.ProblemController.Vote | ( | string | problemName, |
| Vote | vote | ||
| ) |
| vote | |
| solution |


Preparation time
1-2 hours
Cooking time
30 mins to 1 hour
Serves
Makes 12 éclairs
Dietary
Chocolate choux pastry filled with peanut butter cream and strawberry jam - a Franco-American fusion that's sure to make an impact.
Equipment and preparation: for this recipe you will need, four piping bags, 15mm plain and star nozzle, a 5mm round nozzle, a 15mm wide ribbon nozzle and a cook's thermometer.
For the crème pâtissière, place the eggs, egg yolks and sugar in a large bowl and whisk until pale and smooth. Add the cornflour and whisk until incorporated and smooth.
Place the milk and vanilla paste in a large saucepan and bring just to the boil. Pour over the egg mixture slowly whisking all the time until smooth.
Place all the mixture back in the pan and bring to a simmer. Cook for three minutes, whisking all the time. Pour into a large bowl and mix in in the peanut butter until well incorporated.
Cover with cling film touching the mixture to prevent a skin forming. Set aside to cool.
For the chocolate choux pastry, preheat the oven to 190C/375F/Gas 5.
In a bowl, combine the flour and cocoa powder. Place the eggs in another bowl and whisk.
Put 110ml/4fl oz water, the milk, butter and salt in a large saucepan and bring to the boil. Remove from the heat and quickly stir in the flour mixture until well combined.
Place back on a medium heat and cook for two minutes, stirring all the time. Remove from heat and whisk in the eggs a little at a time until the mixture reaches a thick dropping consistency.
Spoon the mixture in a large piping fitted with a 15mm nozzle and set aside to cool slightly.
Cut two pieces of non-stick baking parchment to line baking trays. Mark each piece of baking parchment with six 15cm/6in long lines, spaced apart to allow for the pastry to expand as it cooks. Turn the paper over so you can see the lines through the parchment.
Dab a small spots of the choux mixture into each corner of the baking trays and stick the baking parchment to it. Pipe 12 éclairs on the lines and spray lightly with sunflower oil. Place in the centre of the oven for 25-30 minutes, or until well risen, golden-brown and crisp. You may need to swap the trays around to ensure the éclairs cook evenly.
For the strawberry jam, place the strawberries in a small food processor and blend to a purée. Transfer to a large saucepan with the lemon juice and jam sugar. Bring to the boil stirring all the time. Add a knob of butter and boil for four minutes. Pour into a heatproof bowl and set aside to cool.
For the salted peanut brittle, place the sugar in a saucepan over a medium heat and cook until it forms a caramel. Stir in the salted peanuts and pour out the mixture onto a large piece of non-stick baking parchment and allow to cool and set. (CAUTION: sugar gets very hot.
To assemble, cut the chocolate éclairs neatly in half lengthways. Pour the strawberry jam into a piping bag fitted with a 5mm round nozzle and pipe a line of jam in the base of each éclair.
Spoon the crème pâtissière into a piping bag fitted with a 15mm star nozzle and fill each éclair base over the top of the jam.
For the topping, place slices of strawberries in a row on top of the filling and put the tops on the éclairs.
Put the fondant in a large saucepan with four teaspoons of water and enough red food paste colouring to make it a deep red colour (you will only need a tiny amount). Gently heat until it reaches 38C/100F on a cook’s thermometer, stirring all the time.
Place the icing in a large piping bag fitted with a 15mm wide ribbon nozzle and pipe a line of fondant over the top of each éclair. Break the salted peanut brittle into small pieces using a rolling pin and scatter pieces on top of each éclair while the fondant is still wet.
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How to make choux pastry
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Using piping bags


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
# but I hear, nchw have best performance!
# image = tf.placeholder(tf.float32, shape=[None, image_channels,
# image_height, image_width])
image = tf.placeholder(tf.float32, shape=[None, image_width, image_height, image_channels])
z = tf.placeholder(tf.float32, shape=[None, z_dim])
lr = tf.placeholder(tf.float32)
return image, z, lr
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the generator, tensor logits of the generator).
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
alpha = 0.2
with tf.variable_scope("discriminator", reuse=reuse) as scope:
initer = tf.truncated_normal_initializer(stddev=0.02)
net = tf.layers.conv2d(images, 64, 5, strides=2, padding='same',
kernel_initializer=initer)
relu1 = tf.maximum(alpha * net, net)
# 14x14x64
net = tf.layers.conv2d(net, 128, 5, strides=2, padding='same',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=True)
net = tf.maximum(alpha * net, net)
# 7x7x128
net = tf.layers.conv2d(net, 256, 5, strides=2, padding='same',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=True)
net = tf.maximum(alpha * net, net)
# 4x4x256
net = tf.layers.conv2d(net, 512, 5, strides=2, padding='same',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=True)
net = tf.maximum(alpha * net, net)
# 2x2x512
# Flatten it
shape = net.get_shape().as_list()
net = tf.reshape(net, (-1, shape[1] * shape[2] * shape[3]))
logits = tf.layers.dense(net, 1, kernel_initializer=initer)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
alpha = 0.2
with tf.variable_scope("generator", reuse=not is_train) as scope:
initer = tf.truncated_normal_initializer(stddev=0.02)
# First fully connected layer
net = tf.layers.dense(z, 2 * 2 * 512)
# Reshape it to start the convolutional stack
net = tf.reshape(net, (-1, 2, 2, 512))
net = tf.layers.batch_normalization(net, training=is_train)
net = tf.maximum(alpha * net, net)
# 2x2x512 now
net = tf.layers.conv2d_transpose(net, 256, 5, strides=2, padding='same',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=is_train)
net = tf.maximum(alpha * net, net)
# 4x4x256 now
net = tf.layers.conv2d_transpose(net, 128, 4, strides=1, padding='valid',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=is_train)
net = tf.maximum(alpha * net, net)
# 7x7x128 now
net = tf.layers.conv2d_transpose(net, 64, 5, strides=2, padding='same',
kernel_initializer=initer)
net = tf.layers.batch_normalization(net, training=is_train)
net = tf.maximum(alpha * net, net)
# 14x14x64 now
# Output layer
net = tf.layers.conv2d_transpose(net, out_channel_dim, 5, strides=2,
padding='same', kernel_initializer=initer)
# 28x28x3 now
out = tf.tanh(net)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)*0.9))
d_loss_fake = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
# Optimize
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
out_channel_dim = (data_image_mode == 'L') and 1 or 3
image, z, lr = model_inputs(*data_shape[1:], z_dim)
d_loss, g_loss = model_loss(image, z, out_channel_dim)
d_train_opt, g_train_opt = model_opt(d_loss, g_loss, lr, beta1)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
steps = 0
for batch_images in get_batches(batch_size):
# TODO: Train Model
steps += 1
batch_images *= 2
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
_ = sess.run(d_train_opt, feed_dict={image: batch_images, z: batch_z, lr: learning_rate})
_ = sess.run(g_train_opt, feed_dict={image: batch_images, z: batch_z, lr: learning_rate})
if steps % 20 == 0:
# At the end of each epoch, get the losses and print them out
train_loss_d = d_loss.eval({image: batch_images, z: batch_z})
train_loss_g = g_loss.eval({z: batch_z})
print("Epoch {}/{} {:.0f}%...".format(epoch_i+1, epochs, steps*batch_size/data_shape[0]*100),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
if steps % 100 == 0:
show_generator_output(sess, show_n_images, z,
out_channel_dim, data_image_mode)
show_generator_output(sess, show_n_images, z, out_channel_dim, data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.0004
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0004
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


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Handed out: October 2, 2017
Due: October 16 at 11:59pm
The input consists of a set S
of N
two-dimensional records of integers,
each of which consists of a pair of coordinates (x[i],y[i])
for 0 ≤ i ≤ N-1
, where the x[i]
are distinct
(i.e., no two are equal) and the y[i]
are also distinct.
Intuitively, the x coordinates represent one desirable attribute of each record, whereas the y coordinates represent another (different) desirable attribute of the record.
Write a program that eliminates from S
every record
(x[i],y[i])
for which
there exists another record (x[j],y[j])
having both
x[j] > x[i]
and y[j] > y[i]
.
Intuitively, we want to eliminate all records that are doubly inferior to at least one other record, where "doubly" means in terms of both x coordinate and in terms of y coordinate.
Output the surviving ("filtered") records in S
sorted according
to increasing order of their x coordinates.
Note: You are allowed to use existing sorts (no need to write your own).
Create a class Filter.java
to perform the task described above.
Your program should process input using StdIn.java
in the
following format.
The first line consists of a single integer N
, the number
of records to read.
This is followed by a list of N
records, one per line,
each consisting of two integers x
and y
separated by a space. The records do not appear in any specific order.
Your program should output the filtered, sorted records using
StdOut.java
. Write
one record per line, x
followed by y
separated
by a space.
We have provided example input / output files in the archive linked at
the beginning of the handout. Use filter1.txt
,
filter2.txt
, and filter3.txt
as input, and
filter1out.txt
, filter2out.txt
, and
filter3out.txt
as output to test your program.
Put the sorted input N
records (unfiltered) into an array,
sorted by their x coordinates in increasing order. That array can be
viewed as representing a complete binary tree T
. For every
node v
of T
, create an array L[v]
that contains the records in the subtree of v
in
T
, sorted according to their y coordinates. Note that this
creates multiple copies of a record (as many as ther record's ancestors
in T
).
Hint: Create the L[v]
's in bottom-up order, so that you can
obtain the L[v]
of a v
whose children are
u
and w
by merging the already-computed
L[u]
with the already-computed L[w]
and with
v
.
Use the tree T
and the L[v]
lists to efficiently
process queries of the type Q(a,b)
that outputs the records
whose x coordinate is greater than a
AND y coordinate is
greater than b
. The records output from each query should be
sorted by their x coordinates in increasing order.
Performance for each such query should be
O((log N
)2 + m
log m
)
time where m
is the number of output records.
Note: O(log N
+ m
log m
)
time performance is possible, but not required.
Create a class Query.java
to perform the task described
above. Your program should process input using StdIn.java
in the following format.
The first part of the input is the same as for part 1: the first line
has a single integer N
, followed by N
records,
one record per line, each consisting of two integers x
and
y
separated by a space. As in part 1, the records do not
appear in any specific order.
The line following the last record
contains a single integer Q
, the number of queries to process.
This is followed by Q
lines, one query per line, consisting
of two integers a
and b
separated by a space.
Your program should process and output each query in the order it appears.
Your program should print the records output from each query to
StdOut.java
. For each query, output m
records,
one per line, each consisting of two integers x
and
y
separated by a space, where m
is the number of
records returned by that query. If a query returns zero records, output
a single line with the string "none
" (without quotes).
As with part 1, we've included example input / output files in the
archive linked at the top of the handout. Use query1.txt
,
query2.txt
, and query3.txt
as input, and
query1out.txt
, query2out.txt
, and
query3out.txt
as output to test your program.
Note: since we require each query to have a specific complexity, your code will be timed to ensure this requirement is met. Specific time limits are yet to be determined.
Submit your solution on or before Monday, October 16, 11:59pm.
The submission procedure is the same as for previous projects. Inside your
working directory for this project on data
(e.g. ~/cs251/project3
), create a folder in which you will
include all source code used and libraries needed to compile and run your
code. Specifically, your submission must include the following files:
Filter.java
Query.java
readme.txt
(if needed)
DO NOT use absolute paths in your files since they will become invalid once submitted. Optionally, you can include a README file to let us know about any known issues with your code (like errors, special conditions, etc).
After logging into data.cs.purdue.edu
, please follow these
steps to submit your assignment:
%cd ~/cs251/project3
<your_first_name>_<your_last_name>
and copy
all the files needed to compile and run your code there.
~/cs251/project3
) execute the following turnin command:
%turnin -c cs251 -p project3 <your_first_name>_<your_last_name>
%turnin -v -c cs251 -p project3
-v
flag here, as otherwise your submission
would be replaced with an empty one.


Here we put things together showing how to use the ETL tools to clean up and normalize an example CSV data file, how to ingest that file and create a display of the data.
The overall flow is to -
- Upload the raw data file to RAMADDA
- Clean it up and convert it using the ETL tools
- Add the converted file back to RAMADDA as a special "Text Point Data" entry type
- Create a plot using RAMADDA's wiki facility
The example we are using is data from the City of Boulder's Open Data Repository that shows greenhouse gas emissions and looks like -
Year,Category,Sub-Category,Emissions per Sub-Category (MTCO2e)
2005,Source,Electricity,"1,014,560"
2005,Source,Stationary Fuels,"274,089"
...
2014,Source,Transportation Fuels, Not Available
2014,Source,Other, Not Available
...
- First download the GHGI_Community_Emissions_Source.csv file.
- Assuming you are logged in to RAMADDA you will upload the file to RAMADDA.
- Navigate to some folder
- Click on the menu and select "New File" -
- Upload the file in the Add Entry form -
- Once you upload the raw CSV file RAMADDA automatically creates a "CSV File" entry type.
Next, the data needs to be cleaned up, reformatting the numeric values, removing the missing years and transforming the data to group the fields by year to be able to create time series displays.
From the menu choose "Convert Data" -
This takes us to the interactive ETL conversion form (view it
here).
RAMADDA's ETL facility provides a large number of operations (documented
here) for transforming the CSV file. One adds any number of conversion commands in the main input area. The buttons along the bottom (e.g., Table, Records) allow for the results to be viewed in different ways.
The below commands are used to convert the raw data. This changes the commas in the
value field (column 3 in the raw data), groups the different values by year, removes the years that have no values then adds RAMADDA's point data header to the result file.
Once all is good use the "Make Files" button to process the entire raw file. This provides a link to download the temporary processed file.
Once you download the file you can then upload it back to RAMADDA to the folder of your choice.
Instead of adding it as a regular CSV file you need to specify a "Text Point Data" entry type. Go to the folder's menu and choose "Pick a Type" -
Since RAMADDA supports a huge number of entry types this next page can be daunting but fear not. Just scroll down or search in the page for "Text Point Data" and select the link -
This takes you to an Add Entry form. Upload the converted file.
You have now created a new entry with the structured data. You can view information about the entry including
its file format with the entry menu "Information" link (example
here).
The default display of the new entry does not show any plots of data. To define a new display RAMADDA's wiki facility is used. From the entry's menu go to "Edit Entry". You will need to change the description. To specify that
this is wiki text add a "<wiki>" tag to the beginning of the description (documented
here).
The
example entry
on the Boulder Data Hub has some descriptive information and shows 4 time series plots -
The above page also shows the wiki text. The wiki text facility is very powerful and provides
numerous display types available - line charts, bar charts, dot plots, etc. There are a number of examples
shown
here. Here is further documentation -
You can change the default display of your new data entry by changing its description. Copy and paste the
example entry's wiki text.
Alternately you can create other wiki pages that import and display data from other entries. Simple go to
some folder in RAMADDA and choose "Pick a Type" from the Folder's menu. The Wiki Page type is listed under the "Information" category (search for "wiki" in the web page. Create the wiki page - specifying a name and the wiki text. To display data from other entries you use the same wiki text as described above but you also specify an
entry-
{{display type="linechart" layoutHere="true" fields="#1" entry="becb663b-d464-451a-a3c6-3ec8a4816515"}}
{{display type="linechart" layoutHere="true" fields="#1" entry="some other entry id"}}
Using the ETL tools one can also create searchable databases from CSV files. To do this the user needs to be a site administrator since a plugin is
created and installed as part of this process.
We're going to use the City of Boulder
employee salaries data.
Like the example above one first uploads the CSV file to RAMADDA.
Here is the salaries file.
Defining a database is a 2 step process. You define operations to clean up and convert the CSV file. Then, there is a special command (-db) that creates the database plugin. The -db command (documentation here) takes a number of name/value properties as shown. When you press "Run" the database schema is shown. The links will popup a menu that allows you to define various properties of the different columns (e.g., label, type, etc). If you set "install true" then when you run "Make Files" RAMADDA will generate the database plugin and install it.
Once you have defined and installed the database you need to comment out the -db command (or add a -quit command before it) and then press "Make Files" again to create the processed CSV data file. Download this file. Next, you need to create the actual database entry. Navigate to some folder and select "Pick a Type". Look for the database name that you specified and select that link to add the new database entry (note - you can have multiple different database entries based on the same database schema). Once you create the database entry got the "New" link, select the Bulk Upload tab and upload the processed CSV file. If you want to redo everything you can add a "nukedb true" property to the -db command. This, when run, will drop the previous database table and recreate it.


Marvel Explorer
Wandering aimlessly from character to
character through the Marvel Comics data,
sometimes getting stuck in an X-Men gravity well. Updated every
{{ site.data.config.interval | divided_by: 60}} minutes
(unless we hit the Marvel rate-limit)


JavaScript Diagram Builder - Introduction |
|
The JavaScript Diagram Builder v. 3.3 is a library of some objects and functions, which can help you to display
a coordinate diagram (resp. a chart or graph) in your webpage in an easy way. The file 'diagram.js' contains all the necessary objects and functions.
This file must be included in the header of your webpage: <SCRIPT Language="JavaScript" src="diagram.js"></SCRIPT> The script will best work with Microsoft Internet Explorer 5.x, Netscape 6.x, Opera 7.x or Konqueror 3.x under Windows and Linux, but it will also work with Netscape 4.x and Opera 5.x under Windows and Linux with some restrictions. The JavaScript Diagram Builder is especially useful, if you want to display a coordinate diagram (chart or graph) which depends on the client's input parameter or from data of a database. The JavaScript Diagram Builder v. 3.3 is copyrighted freeware. It is provided "as is", without a warranty of any kind. If you encounter any bugs, or if you have any suggestions for further versions, then send me an email. Here is the history of new features:
|
| Lutz Tautenhahn © 2001-2005 |
The Diagram object » |


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Socks Proxy
Free Socks Proxy List
Here are some free socks proxies that are just checked and added into our proxy list. We update the socks proxy list every 10 minutes to keep them fresh. These free socks proxies are public socks proxy. Please check the proxies by our free Socks Proxy Checker before using them. If you need stable proxy, please try our Multi-IP free Web Proxy or proxy software My IP Hide.
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| <IP_ADDRESS> | 52538 | FR | France | Socks5 | Anonymous | Yes | 16 seconds ago |
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| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
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| <IP_ADDRESS> | 3130 | RU | Russian Federation | Socks5 | Anonymous | Yes | 16 seconds ago |
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| <IP_ADDRESS> | 27992 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 808 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 29689 | RU | Russian Federation | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | GE | Georgia | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 18628 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 12345 | UA | Ukraine | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 19628 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 48804 | UA | Ukraine | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 9000 | VE | Venezuela | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 8080 | TW | Taiwan | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 10200 | SE | Sweden | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | TW | Taiwan | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 64101 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 18628 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | BR | Brazil | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 3128 | CN | China | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | ID | Indonesia | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 3129 | TW | Taiwan | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 10200 | SE | Sweden | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | IQ | Iraq | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | AL | Albania | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 23071 | FR | France | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 29930 | US | United States | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 22446 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | EG | Egypt | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 54321 | CN | China | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 443 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 16 seconds ago |
| <IP_ADDRESS> | 31448 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | BD | Bangladesh | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | BR | Brazil | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | IQ | Iraq | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | ID | Indonesia | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | AR | Argentina | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | US | United States | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | ID | Indonesia | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | ID | Indonesia | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CO | Colombia | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | PY | Paraguay | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | SE | Sweden | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | SE | Sweden | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 8020 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | ID | Indonesia | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 4567 | US | United States | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | RU | Russian Federation | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 8020 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 18628 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 10200 | US | United States | Socks5 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 1080 | CN | China | Socks4 | Anonymous | Yes | 17 seconds ago |
| <IP_ADDRESS> | 60088 | SG | Singapore | Socks5 | Anonymous | Yes | 17 seconds ago |
What is socks proxy?
Socks proxy is versatile proxy for all usage while the http proxy can only be used for surfing. You can use socks proxy to send email, transfer file, chat online, play game as well as surf website. Here is an article about socks proxy and http proxy.
How to use the socks proxy?
Many programs (such as Firefox, IE, Skype, mIRC) support the socks proxy option. When you enable socks proxy in the program, the proxy will fetch the traffic data for the program. The server will regard the IP of socks proxy as your IP so it cannot trace your real IP. We recommend using Socks Proxy Checker to check socks proxies.
What is the version of socks proxy?
There are two versions of socks proxy: version 4 and 5, as known as Socks4 and Socks5. Socks5 supports UDP (Skype needs it), name resolution and authentication while Socks4 not. However in most cases either Socks4 or Socks5 is OK.
What is the proxy anonymity?
All the socks proxies are highly anonymous. The server does not know you are using a proxy. Http proxies are different. They can be anonymous or transparent.
How to check the proxy speed?
You can use our free software Socks Proxy Checker to test the proxy speed. We don't show the speed in the proxy list. It's because one proxy may have different speed for different users. For example, a proxy which is fast for USA users may be slow for European users. So check it by yourself.
What is HTTPS / SSL proxy?
Secure websites whose url starts with https:// instead of http:// (ex. https://www.paypal.com) use the encrypted (SSL/HTTPS) connections between its web server and the visitors. All socks proxies support SSL/HTTPS.


| Property starting with A |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
AmountCentral
|
|
|
Number
|
|
AmountCentral
|
|
|
|
|
|
AmountDivision
|
|
|
Number
|
|
AmountDivision
|
|
|
|
|
|
AmountDivisionDefault
|
|
|
Number
|
|
AmountDivisionDefault
|
|
|
|
|
| Property starting with B |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
BatchNumber
|
|
|
String
|
|
BatchNumber
|
|
|
|
|
| Property starting with C |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
CompanyAccountCode
|
|
|
String
|
|
CompanyAccountCode
|
|
|
|
|
|
CompanyCode
|
|
|
String
|
|
CompanyCode
|
|
|
|
|
|
CompanyName
|
|
|
String
|
|
CompanyName
|
|
|
|
|
|
CostCenterCode
|
|
|
String
|
|
CostCenterCode
|
|
|
|
|
|
CostcenterDescription
|
|
|
String
|
|
CostcenterDescription
|
|
|
|
|
|
CostUnitCode
|
|
|
String
|
|
CostUnitCode
|
|
|
|
|
|
CostUnitDescription
|
|
|
String
|
|
CostUnitDescription
|
|
|
|
|
|
CreatedDate
|
|
|
Date
|
|
CreatedDate
|
|
|
|
|
|
Creator
|
|
|
Number
|
|
Creator
|
|
|
|
|
|
CreditorCode
|
|
|
String
|
|
CreditorCode
|
|
|
|
|
|
CurrencyAliasForeignExchange
|
|
|
String
|
|
CurrencyAliasForeignExchange
|
|
|
|
|
|
CurrencyCentral
|
|
|
String
|
|
CurrencyCentral
|
|
|
|
|
|
CurrencyCentralName
|
|
|
String
|
|
CurrencyCentralName
|
|
|
|
|
|
CurrencyDivision
|
|
|
String
|
|
CurrencyDivision
|
|
|
|
|
|
CurrencyDivisionName
|
|
|
String
|
|
CurrencyDivisionName
|
|
|
|
|
|
CustomerIDName
|
|
|
String
|
|
CustomerIDName
|
|
|
|
|
| Property starting with D |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
Date
|
|
|
Date
|
|
Date
|
|
|
|
|
|
DebtorCode
|
|
|
String
|
|
DebtorCode
|
|
|
|
|
|
Description
|
|
|
String
|
|
Description
|
|
|
|
|
|
DocDate
|
|
|
Date
|
|
DocDate
|
|
|
|
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|
DocumentCreatedBy
|
|
|
String
|
|
DocumentCreatedBy
|
|
|
|
|
|
DocumentCreatedDate
|
|
|
Date
|
|
DocumentCreatedDate
|
|
|
|
|
|
DocumentID
|
|
|
GUID
|
|
DocumentID
|
|
|
|
|
|
DocumentSubject
|
|
|
String
|
|
DocumentSubject
|
|
|
|
|
| Property starting with E |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
EmployeeID
|
|
|
Number
|
|
EmployeeID
|
|
|
|
|
|
EmployeeName
|
|
|
String
|
|
EmployeeName
|
|
|
|
|
|
EntryGuid
|
|
|
GUID
|
|
EntryGuid
|
|
|
|
|
|
EntryOrigin
|
|
|
String
|
|
EntryOrigin
|
|
|
|
|
|
ExtraCurrencyCode
|
Extra currency code
|
Extra currency code
|
String
|
|
ExtraCurrencyCode
|
|
|
|
|
| Property starting with F |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
FinPeriod
|
|
|
String
|
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FinPeriod
|
|
|
|
|
|
FinYear
|
|
|
Number
|
|
FinYear
|
|
|
|
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| Property starting with I |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
ID
|
|
|
Number
|
|
ID
|
|
|
|
|
|
InvoiceNumber
|
Our ref
|
Our ref
|
String
|
|
InvoiceNumber
|
|
|
|
|
|
ItemCode
|
|
|
String
|
|
ItemCode
|
|
|
|
|
|
ItemDescription
|
|
|
String
|
|
ItemDescription
|
|
|
|
|
| Property starting with L |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
LineCode
|
|
|
String
|
|
LineCode
|
|
|
|
|
| Property starting with M |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
ModifiedDate
|
|
|
Date
|
|
ModifiedDate
|
|
|
|
|
|
Modifier
|
|
|
Number
|
|
Modifier
|
|
|
|
|
| Property starting with P |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
PaymentMethod
|
Payment method
|
Payment method
|
String
|
|
PaymentMethod
|
|
|
|
|
|
PaymentReference
|
|
|
String
|
|
PaymentReference
|
|
|
|
|
|
ProjectCode
|
|
|
String
|
|
ProjectCode
|
|
|
|
|
|
ProjectDescription
|
|
|
String
|
|
ProjectDescription
|
|
|
|
|
| Property starting with Q |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
Quantity
|
|
|
Number
|
|
Quantity
|
|
|
|
|
| Property starting with R |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
RateCentral
|
|
|
Number
|
|
RateCentral
|
|
|
|
|
|
RateForeignCurrency
|
|
|
Number
|
|
RateForeignCurrency
|
|
|
|
|
| Property starting with S |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
Scenario
|
|
|
String
|
|
Scenario
|
|
|
|
|
|
ScenarioDescription
|
|
|
String
|
|
ScenarioDescription
|
|
|
|
|
|
ScenarioPeriodFrom
|
|
|
String
|
|
ScenarioPeriodFrom
|
|
|
|
|
|
ScenarioPeriodTo
|
|
|
String
|
|
ScenarioPeriodTo
|
|
|
|
|
|
ScenarioStatus
|
|
|
String
|
|
ScenarioStatus
|
|
|
|
|
|
ScenarioYearFrom
|
|
|
Number
|
|
ScenarioYearFrom
|
|
|
|
|
|
ScenarioYearTo
|
|
|
Number
|
|
ScenarioYearTo
|
|
|
|
|
|
SerialNumber
|
|
|
String
|
|
SerialNumber
|
|
|
|
|
| Property starting with T |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
TextFreeField1
|
|
|
String
|
|
TextFreeField1
|
|
|
|
|
|
TextFreeField2
|
|
|
String
|
|
TextFreeField2
|
|
|
|
|
|
TextFreeField3
|
|
|
String
|
|
TextFreeField3
|
|
|
|
|
|
TextFreeField4
|
|
|
String
|
|
TextFreeField4
|
|
|
|
|
|
TextFreeField5
|
|
|
String
|
|
TextFreeField5
|
|
|
|
|
|
TransactionGuid
|
|
|
GUID
|
|
TransactionGuid
|
|
|
|
|
|
TransactionLineOriginates
|
|
|
String
|
|
TransactionLineOriginates
|
|
|
|
|
|
TransactionType
|
Transaction type
|
Transaction type
|
Number
|
|
TransactionType
|
|
|
|
|
|
TransactionTypeDescription
|
|
|
String
|
|
TransactionTypeDescription
|
|
|
|
|
|
TransactionTypeValid
|
|
|
Boolean
|
|
TransactionTypeValid
|
|
|
|
|
|
TransSubType
|
|
|
String
|
|
TransSubType
|
|
|
|
|
|
TransType
|
|
|
String
|
|
TransType
|
|
|
|
|
| Property starting with V |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
VATAmountCentral
|
VAT amount in default currency
|
VAT amount in default currency
|
Number
|
|
VATAmountCentral
|
|
|
|
|
|
VatCode
|
|
|
String
|
|
VatCode
|
|
|
|
|
| Property starting with W |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
Warehouse
|
|
|
String
|
|
Warehouse
|
|
|
|
|
| Property starting with Y |
| Name |
Caption |
Description |
Type |
Mandatory |
Name (known in REST) |
Available since release |
Introduced by which team |
Introduced for which project |
Additional remarks |
|
YourReference
|
Your reference
|
Your reference
|
String
|
|
YourReference
|
|
|
|
|
| Property starting with A |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
AmountCentral
|
AmountCentral
|
Number
|
|
16
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
AmountDivision
|
AmountDivision
|
Number
|
|
16
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
AmountDivisionDefault
|
bdr_val
|
Number
|
|
16
|
4
|
AmountDivision
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with B |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
BatchNumber
|
BatchNumber
|
String
|
|
8
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with C |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
CompanyAccountCode
|
CompanyAccountCode
|
String
|
|
9
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CompanyCode
|
CompanyCode
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CompanyName
|
CompanyName
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CostCenterCode
|
CostCenterCode
|
String
|
|
8
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CostcenterDescription
|
CostcenterDescription
|
String
|
|
50
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CostUnitCode
|
CostUnitCode
|
String
|
|
8
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CostUnitDescription
|
CostUnitDescription
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CreatedDate
|
Created
|
Date
|
|
0
|
0
|
NOW
|
|
|
|
|
|
|
|
|
|
|
|
|
Creator
|
Creator
|
Number
|
|
10
|
0
|
HUMRESID
|
|
|
|
|
|
|
|
|
|
|
|
|
CreditorCode
|
CreditorCode
|
String
|
|
6
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CurrencyAliasForeignExchange
|
CurrencyAliasFC
|
String
|
|
3
|
0
|
CurrencyDivision
|
|
|
|
|
|
|
|
|
|
|
|
|
CurrencyCentral
|
CurrencyCentral
|
String
|
|
3
|
0
|
DefaultCurrency
|
|
|
|
|
|
|
|
|
|
|
|
|
CurrencyCentralName
|
CurrencyCentralName
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CurrencyDivision
|
CurrencyDivision
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CurrencyDivisionName
|
CurrencyDivisionName
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CustomerIDName
|
CustomerIDName
|
String
|
|
50
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with D |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
Date
|
Date
|
Date
|
|
8
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DebtorCode
|
DebtorCode
|
String
|
|
6
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Description
|
Description
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DocDate
|
DocDate
|
Date
|
|
8
|
0
|
NOW
|
|
|
|
|
|
|
|
|
|
|
|
|
DocumentCreatedBy
|
DocumentCreatedBy
|
String
|
|
64
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DocumentCreatedDate
|
DocumentCreatedDate
|
Date
|
|
0
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DocumentID
|
DocID
|
GUID
|
|
16
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
DocumentSubject
|
DocumentSubject
|
String
|
|
255
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with E |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
EmployeeID
|
EmployeeID
|
Number
|
|
10
|
0
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
EmployeeName
|
EmployeeName
|
String
|
|
64
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
EntryGuid
|
EntryGuid
|
GUID
|
|
16
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
EntryOrigin
|
EntryOrigin
|
String
|
|
1
|
0
|
U
|
|
|
|
|
|
|
|
|
|
|
|
|
ExtraCurrencyCode
|
ExCurrencyCode
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with F |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
FinPeriod
|
FinPeriod
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
FinYear
|
FinYear
|
Number
|
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with I |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
ID
|
ID
|
Number
|
|
10
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
InvoiceNumber
|
InvoiceNumber
|
String
|
|
8
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ItemCode
|
ItemCode
|
String
|
|
30
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ItemDescription
|
ItemDescription
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with L |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
LineCode
|
regelcode
|
String
|
|
1
|
0
|
U
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with M |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
ModifiedDate
|
Modified
|
Date
|
|
0
|
0
|
now
|
|
|
|
|
|
|
|
|
|
|
|
|
Modifier
|
Modifier
|
Number
|
|
10
|
0
|
HUMRESID
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with P |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
PaymentMethod
|
PaymentMethod
|
String
|
|
1
|
0
|
|
|
|
|
|
|
|
|
|
|
|
| I,8664,Input | | G,14015,Generated | | E,18224,Entered |
|
|
PaymentReference
|
PaymentReference
|
String
|
|
20
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ProjectCode
|
ProjectCode
|
String
|
|
20
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ProjectDescription
|
ProjectDescription
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with Q |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
Quantity
|
Quantity
|
Number
|
|
16
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with R |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
RateCentral
|
RateCentral
|
Number
|
|
12
|
4
|
1
|
|
|
|
|
|
|
|
|
|
|
|
|
RateForeignCurrency
|
RateFC
|
Number
|
|
12
|
4
|
1
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with S |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
Scenario
|
Scenario
|
String
|
|
30
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioDescription
|
ScenarioDescription
|
String
|
|
30
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioPeriodFrom
|
ScenarioPeriodFrom
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioPeriodTo
|
ScenarioPeriodTo
|
String
|
|
3
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioStatus
|
ScenarioStatus
|
String
|
|
1
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioYearFrom
|
ScenarioYearFrom
|
Number
|
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
ScenarioYearTo
|
ScenarioYearTo
|
Number
|
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
SerialNumber
|
SerialNumber
|
String
|
|
20
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with T |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
TextFreeField1
|
Freefield1
|
String
|
|
75
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TextFreeField2
|
Freefield2
|
String
|
|
75
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TextFreeField3
|
Freefield3
|
String
|
|
75
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TextFreeField4
|
Freefield4
|
String
|
|
75
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TextFreeField5
|
Freefield5
|
String
|
|
75
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TransactionGuid
|
TransactionGuid
|
GUID
|
|
16
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TransactionLineOriginates
|
oorsprong
|
String
|
|
1
|
0
|
Z
|
|
|
|
|
|
|
|
|
|
|
|
|
TransactionType
|
TransactionType
|
Number
|
|
4
|
0
|
100
|
|
|
|
|
|
|
|
|
|
|
| 310,1625,Budgets | | 320,1625,Budgets | | 340,1625,Budgets |
|
|
TransactionTypeDescription
|
TransactionTypeDescription
|
String
|
|
60
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
TransactionTypeValid
|
TransactionTypeValid
|
Boolean
|
|
1
|
0
|
0
|
0
|
1
|
|
|
|
|
|
|
|
|
|
|
TransSubType
|
TransSubType
|
String
|
|
1
|
0
|
N
|
|
|
|
|
|
|
|
|
|
|
|
|
TransType
|
TransType
|
String
|
|
1
|
0
|
B
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with V |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
VATAmountCentral
|
VATAmountCentral
|
Number
|
|
16
|
4
|
|
|
|
|
|
|
|
|
|
|
|
|
|
VatCode
|
VatCode
|
String
|
|
3
|
0
|
0
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with W |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
Warehouse
|
Warehouse
|
String
|
|
4
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|
| Property starting with Y |
| Name |
Source name |
Type |
Mandatory |
Length |
Scale |
Default value |
Lower range |
Upper range |
Allowed characters |
Auto increment |
Numeric string |
Right aligned |
Unsigned |
Upper case |
Zero equals null |
Zero fill |
Selection values |
|
YourReference
|
YourRef
|
String
|
|
30
|
0
|
|
|
|
|
|
|
|
|
|
|
|
|


Alphabet:
Consonants:
Vowels:
Pattern:
is always onset
add
is always coda
add
When
is vowel,
is onset
add
When
is vowel,
is coda
add
Exclude these words:
add
Lines:
Generate


I've been very happy to be able to start migrating from Incanica's ITP
to Watir at work, but I've run into my first real problem. I have a
select box defined thus:
and I'm trying to choose the ">=" option via the following code:
and our WebSiteTester Ruby class translates that into
Watir calls.)
and the output I get from Watir is:
Setting box op_numhits to >= String
comparing >= to á=áá
comparing >= to á<>á
comparing >= to á>=á
comparing >= to á<=á
While I just realized I could enhance our WebSiteTester class to be
able to pass Regexp's as well as Strings to the select() method, it
would also be nice to be able to specify the desired select option by
value (in my example, the value is "3").
Is it even possible for Watir to select something based on an attribute
that's empty, like the first option of the select box below? I know I
also have an issue given that I'm translating from an XML representation
to a Ruby Watir call, and I'm probably getting a nil back from REXML
when I ask for the value of an attribute that has nothing between the
quotes....