Coal: Is this the beginning of the end?
by Justin RowlattThe fuel that powered the industrial revolution may be in decline at last.
This year looks set to see the largest fall in electricity production from coal on record, according to a new report.
The reduction is estimated to be more than the power generated from coal in Germany, Spain and the UK combined.
It is projected to drop by 3% - which is a fall of 300 terawatt hours.
The report by three energy experts - published in the online journal Carbon Brief - draws on energy sector data from around the world for the first seven to 10 months of the year.
The record drop raises the prospect of a slowing of global CO2 emissions growth in 2019.
But the authors warn that, even with this decline, coal use and emissions remain far higher than the level required to keep the global temperature rise below 2C.
Record decline
Coal has been the mainstay of electricity generation for over a century and has seen decades of near-uninterrupted growth.
Yet this report finds that record reductions in coal use in developed countries, including the US, European Union, and South Korea, could signal the beginning of the end of the industry.
These reductions in use are not being matched by increases elsewhere.
The decline suggests that coal plants will take a significant blow to revenues as average running hours look set to reach an all-time low.
"It is clear that the economics of coal production no longer make sense in many parts of the world where it is simply cheaper to generate electricity from natural gas and renewables," said Bob Ward, policy director at the Grantham Research Institute on climate change and the environment at the London School of Economics.
However, he also warned that is too early to tell whether the global downturn in coal consumption in 2019 is the start of a declining trend.
Rise of renewables
The report suggests that the reasons for the drop in coal-fired generation vary from country to country, but include increased electricity generation from renewables, nuclear and gas, as well as slowing or negative demand for electricity.
In previous years the reductions in coal generation in the US and EU have been offset by increases elsewhere, particularly China.
This year, however, the fall in developed economies is accelerating, while coal generation in India and China is slowing sharply
The Chinese situation is complex.
A recent report showed a surge in new coal-fired plants in China.
However, this new analysis shows that electricity demand growth in China this year slowed to 3%, down from 6.7% over the last two years.
It finds that non-fossil energy sources - nuclear, wind and hydro generation - have met almost all of this demand.
As a result, coal-fired power plants are being used less intensively.
The report estimates that this year utilisation rates will be below 49% - a record low.
It says 2019 has also seen the first Chinese contracts for wind and solar plants that will generate power at the same price as coal power plants.
The authors say this could threaten the long-term viability of coal in China and put it on a path to renewable energy "grid parity" as those projects come online in 2020.
US bankruptcies
Meanwhile, the US has seen the largest reductions in coal-fired power generation.
This comes despite US President Donald Trump's vigorous efforts to revive the US coal industry.
Eight US coal companies have filed for bankruptcy this year, including Murray Energy, the largest privately held coal company in the country.
At the same time, the report finds there has been a sharp turnaround in India, where coal power output is on track to fall for the first time in at least three decades.
Only south-east Asia has seen significant increases in coal generation, but demand here is relatively small relative to the global total.


System.out.println()
with an exception as an argument.
Using print statements for logging exceptions hides the stack trace from you, which is important when you need to investigate what happened.
It is recommended to use logger instead.
Calls to System.out.print()
, System.err.println()
and System.err.print()
with an exception argument will also be
reported.
It is better to use logger to log exceptions instead.
For example, instead of:
try {
foo();
} catch (Exception e) {
System.out.println(e);
}
use the following code:
try {
foo();
} catch (Exception e) {
logger.warn(e); // logger call may be different
}


{% extends "layout_unbranded.html" %} {% block page_title %} Tax Tribunals Prototype {% endblock %} {% block body_classes %}index clear-session{% endblock %} {% block content %} Tax Tribunals Prototypes Main application Start at a mocked-up GOV.UK start page: With Tribunal Fees Fee-Free Service Validation Error messages for required fields On Off Testing Dummy email - case saved (opens in new tab) {% endblock %}
Start at a mocked-up GOV.UK start page:
Error messages for required fields


< < < Index > > >
Image source: /Users/rjl/git/clawpack/new_features_for_v5.7.0/examples/geoclaw_test1/_plots_1/frame0003fig0.png
Other figures at this time: Computational domain coastal area All Figures
Other frames: 0 1 2 3 4 5 All Frames


Yao Peisen (姚培森)
- Email:
- rainoftime - at - gmail - dot- com
- pyao - at - connect - dot- ust - dot - hk
Research Interests
I am broadly interested in topics related to programming languages, software engineering, and cybersecurity, with an emphasis on using program reasoning techniques to ensure software reliability, e.g.,- Program Analysis and Verification
Value-flow analysis, numerical domains, fuzzing - Automated Reasoning
Symbolic abstraction, deductive synthesis
News
- I am currenctly a postdoc research associate in HKUST, and will be joining Zhejiang University as an Assistant Professor this year. 欢迎校内外感兴趣的同学联系...
- 浙江大学计算机科学与技术学院关于接收2023级推荐免试研究生工作安排的通知...
- I am currently on the program committee of PLDI 2023. Please consider submitting a paper!
Dissertation
- Solidifying and Scaling SMT-based Program Analysis.
Ph.D. Dissertation. 2022.
Committee members: Charles Zhang, Shing-Chi Cheung, Fangzhen Lin, Hongce Zhang, and Darko Marinov (External committee)
Publications
- [TOSEM] Anchor: Fast and Precise Value-Flow Analysis for Containers via Memory Orientation. Chengpeng Wang, Wenyang Wang, Peisen Yao*, Qingkai Shi, Jinguo Zhou, Xiao Xiao, and Charles Zhang. ACM Transactions on Software Engineering and Methodology (CCF Rank A)
- [OOPSLA 2022] Indexing the Extended Dyck-CFL Reachability for Context-Sensitive Program Analysis. Qingkai Shi, Yongchao Wang, Peisen Yao, and Charles Zhang. The 37th ACM SIGPLAN Conference on Objected Oriented Programming, Systems, Languages, and Applications (CCF Rank A) [pdf] [tool]
- [OOPSLA 2022] Complexity-Guided Container Replacement Synthesis. Chengpeng Wang, Peisen Yao*, Wensheng Tang, Qingkai Shi, and Charles Zhang. The 37th ACM SIGPLAN Conference on Objected Oriented Programming, Systems, Languages, and Applications (CCF Rank A) [pdf]
- [ICSE 2022] Precise Divide-By-Zero Detection with Affirmative Evidence. Yiyuan Guo, Jinguo Zhou, Peisen Yao*, Qingkai Shi, and Charles Zhang. The 2022 IEEE/ACM International Conference on Software Engineering (CCF Rank A) [study data and bug reports] [pdf]
- [S&P 2022] BEACON: Directed Grey-Box Fuzzing with Provable Path Pruning. Heqing Huang, Yiyuan Guo, Qingkai Shi, Peisen Yao, Rongxin Wu, and Charles Zhang. The 43rd IEEE Symposium on Security and Privacy (CCF Rank A) [pdf]
- [OOPSLA 2021] Program Analysis via Efficient Symbolic Abstraction. Peisen Yao, Qingkai Shi, Heqing Huang, and Charles Zhang. The 36th ACM SIGPLAN Conference on Objected Oriented Programming, Systems, Languages, and Applications (CCF Rank A) [pdf]
- [ASE 2021] Transcode: Detecting Status Code Mapping Errors in Large-Scale Systems. Wensheng Tang, Yikun Hu*, Gang Fan, Peisen Yao*, Rongxin Wu, Guangyuan Bai, Pengcheng Wang, and Charles Zhang. The 2021 IEEE/ACM Automated Software Engineering Conference (CCF Rank A)[pdf]
- [ESEC/FSE 2021] Skeletal Approximation Enumeration for SMT Solver Testing. Peisen Yao, Heqing Huang, Wensheng Tang, Qingkai Shi, Rongxin Wu, and Charles Zhang. The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (CCF Rank A)
[pdf]
- [ISSTA 2021] Fuzzing SMT Solvers via Two-Dimensional Input Space Exploration. Peisen Yao, Heqing Huang, Wensheng Tang, Qingkai Shi, Rongxin Wu, and Charles Zhang. The 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (CCF Rank A)
[pdf]
- [PLDI 2021] Path-Sensitive Sparse Analysis without Path Conditions. Qingkai Shi, Peisen Yao*, Rongxin Wu, and Charles Zhang. The 42nd ACM SIGPLAN Conference on Programming Language Design and Implementation (CCF Rank A)
[pdf]
- [PLDI 2021] Canary: Practical Static Detection of Inter-Thread Value-Flow Bugs. Yuandao Cai, Peisen Yao*, and Charles Zhang. The 42nd ACM SIGPLAN Conference on Programming Language Design and Implementation (CCF Rank A)
[pdf]
- [ISSTA 2020] Fast Bit-Vector Satisfiability. Peisen Yao, Qingkai Shi, Heqing Huang, and Charles Zhang. The 29th ACM SIGSOFT International Symposium on Software Testing and Analysis (CCF Rank A)
[pdf]
- [S&P 2020] Pangolin: Incremental Hybrid Fuzzing with Polyhedral Path Abstraction. Heqing Huang, Peisen Yao, Rongxin Wu, Qingkai Shi, and Charles Zhang. The 41st IEEE Symposium on Security and Privacy (CCF Rank A) [pdf]
* means corresponding author.
Drafts/Technical Reports
- Efficient Path-Sensitive Data-Dependence Analysis. Peisen Yao, Jinguo Zhou, Xiao Xiao, Qingkai Shi, Rongxin Wu, and Charles Zhang.
- Duplicate-sensitivity Guided Transformation Synthesis for DBMS Correctness Bug Detection. Yushan Zhang, Peisen Yao, Rongxin Wu, and Charles Zhang.
Projects
- Static Analysis, Static Vulnerability Detection
Pinpoint/Fusion is an industrial-strength next-generation automated bug finding tool through static analysis (PLDI'21a, PLDI'21b, ASE'21, ICSE'22, OOPSLA'22). It has found 500+ bugs in many mature and fundamental open-source projects, including Linux Kernal, MySQL, Firefox, HBase, Apache, Git, Python, Memcached, OpenSSL, Redis, Tmux, Vim, Mariadb, and many others.
- Dynamic Vulnerability Analysis, Fuzz Testing
Fuzz testing is an automated software testing technique that is conducted to reveal coding errors and security loopholes. We are interested in leveraging our static analysis knowledge to optimize fuzz testers (S&P'20, S&P'22) (a partial of vulnerabilities can be found here), and applying fuzz testers to domain-specific application scenarios. Specificaly, the SMTFuzz framework (ESEC/FSE'21, ISSTA'21) has found 1000+ bugs in several state-of-the-art SMT solvers and first-order theorem provers, such as Z3, CVC5, Yices2, STP, Boolector, MathSAT5, SMTInterpol, OpenSMT, SMT-RAT, DReal, SPASS, and Vampire.
- Automated Program Verification, Model Checking
To appear...
Service
- Program Committee: PLDI'23, ATC'22 (artifact evaluation), OSDI'22 (artifact evaluation), ChinaSoft'22
- Conference Reviewer/Sub-/Co-reviewer: ATVA'22, ISSRE'21, ESEC/FSE'19, ISSTA'19, ASE'18, VMCAI'17
- Journal Reviewer: Journal of Software(软件学报)
Teaching
- COMP4632: Practicing CyberSecurity: Attacks and Counter-measures
- COMP3021: Java Programming
- COMP3511: Operating System
Invited Talks
- Introduction to Metamorphic Testing (蜕变测试导引), System Security Summer School, Zhejiang University
- Solidifying and Scaling SMT-based Program Analysis, Nanjing Univeristy
- Scaling and Solidifying SMT-based Program Analysis, Shanghai Jiao Tong University
Misc
- Some interesting papers
- Writing a technical paper by Michael Ernst
- Tips on writing a research paper by Tom Reps


--- layout: post title: Global Warming Report date: '2010-01-13 22:48:56 -0700' mt_id: 1426 blog_id: 1 post_id: 1426 basename: global-warming-report categories: - essays ---
If you read only the major newspapers and watched only the network news, you would believe that global warming is unquestioned and as certain as any other scientific conclusion. Do a little probing and you quickly discover the wealth of contrarian views available. There are web sites devoted to debunking the mainstream media's sacred cow, respectable books by prominent authors, and scholarly articles chock full of doubts. This would all be interesting diversion and debate were it not for the policy implications present. If the federal government believes the global warming hype, actions could be taken that would cripple the economy and lower our standard of living. It is thus important to discover which side is right.
The basic claim by proponents of global warming is that greenhouse gases like carbon dioxide and methane are building up in the atmosphere. This buildup, called the greenhouse effect, traps ultraviolet radiation and its consequent heat in the lower reaches of the atmosphere, causing the global temperatures to rise. This rising temperature leads to desertification, food shortages, and melting of the polar ice caps. Millions of people die from starvation and drowning. Supporters of this scenario call for government-mandated carbon dioxide emission reduction. They believe that reducing the amount of carbon dioxide produced will stem the greenhouse effect and save humanity.
They have held international conferences that have resulted in global accords like the Montreal Protocol—which banned chlorofluorocarbons—and the Kyoto Protocol—which seeks a hefty reduction in carbon dioxide emissions by the economic superpowers. Debate is squelched by cries of impending doom and universal consensus. "We must act now before it is too late," they clamor. Or they say, "No one questions the validity of global warming." A more careful investigation reveals just how wrong they are.
Global warming predictions are based on global climate models that are run on supercomputers. The advantage of computer modelling is that it allows a climatologist to tweak variables and see possible outcomes. The disadvantage of computer modelling is that it is far from clear whether a simulation can ever take account of all of the variables that make up our climate. In other words, the knowledge required to accurately portray the global climate approaches omniscience. For example, no one can accurately determine the effect of the earth's oceans and sea currents on the climate. Nor can they accurately estimate the effect of clouds or cataclysmic events like volcanic eruptions. The sun's role in the earth's climate is largely mysterious. And these are just the natural influences. Human influences, such as pollution and carbon dioxide production, have been quantified, but their causative relationship with climate is indeterminate. This is not to say that climate is unknowable, just currently unknown.
Due to the presently impossible incorporation of these variables into a computer model, researchers are left to guessing at impacts and hypothesizing causal relationships. The models are so rough that they entirely miss the effect of mountains1 and they treat the climate of heavily-forested Oregon and the Nevada desert the same.2 The output of the models they build become foregone conclusions because they are built on certain suppositions assumed by the author. Given that these models are used to predict climate in the near-future (within the next hundred years), they should be able to provide accurate predictors of the past. However, they cannot. Projections by computer models show that there should have been a 0.4°C rise in temperature over the last twenty years due to large increases in CO2 and other greenhouse gases, but satellite measurements for the years 1978-97 show no temperature rise at all. In fact, no reliable global temperature records show the rise predicted by the computer models.3 Also, when supplied with the relevant variables for the Pleistocene era, advanced computer models fail to predict glaciers.4 As James Hansen (the NASA scientist who started the global warming debate in 1988) said in the October 1998 issue of Proceedings of the National Academy of Sciences, "the forcings that drove long-term climate change are not known with an accuracy sufficient to define future climate change."5 With the current uncertainty of weather forecasts of weeks into the future, it is sheer folly to presume that we can understand (at present) weather patterns decades and centuries from now.
Another problem the global warming advocates face is the troublesome climate record. Satellite measuring only came into widespread use in 1978. Ground-based temperature measurement extends back about one hundred years. These ground-based readings show a global rise of 1°F this century, with a surge in the eighties. Satellite readings do not show this, however. Which set of data should one believe? The ground-based readings—though accurate—have been collected mostly in the Northern Hemisphere around urban centers. They don't record ocean temperatures—a particularly startling fact given that three-quarters of the earth's surface is ocean—and urban centers are prone to the heat-island effect.  Unfortunately, as noted earlier, they only date from the late 70s—too soon for real impact. With an imperfect dataset it is difficult to make accurate assessments.
Finally, by being quick to blame man and specifically the "developed" nations, global warming supporters cast a blind eye to other plausible explanations for temperature fluctuations. Serious research is underway into the strong correlation between the sun's 11-year sunspot cycle and global temperature changes. When plotted side by side, the graphs for temperature change and solar magnetic cycle appear very similar.6 In fact, the Maunder Minimum—a century-long period when the sun "dropped to very low levels of magnetism."7 This Maunder Minimum occurred at the same time as the Little Ice Age. While the causal relationship has not been established, it seems certain that the sun must have considerable influence on the earth's climate.
Even if the global warming advocates were correct and the global temperature was going to rise as much as their ever-revising-downward temperature predictions indicate, there is much to lead one to doubt their prophecies of global catastrophe. There are several scientists who believe that rising levels of carbon dioxide would be beneficial to plant growth and would herald an agricultural time of plenty.8 Also, a recent study indicates that "warming may actually increase the volume of ice stored in the large Antarctic ice sheets."9 The melting of ice sheets due to warmer sea surface temperatures would result in a net increase in ice accumulation due to increased precipitation. Finally, S. Fred Singer states that "any future moderate warming, from whatever cause, will slow down the ongoing sea-level rise, rather than speed it up."10 In short, the dire predictions of the global warming proponents would not necessarily be the end of the world—no pun intended—even if they were true.
1 Sanera, Michael and Jane Shaw. Facts Not Fear. (Washington: Regnery Publishing, 1996), 155.
2 Jastrow, Robert, William Nierenberg, and Frederick Seitz. "An Overview." Scientific Perspectives on the Greenhouse Problem. (San Francisco: Pacific Research Institute, 1992), 23, quoted in Sanera, 155.
3 http://www.marshall.org/globalfax.html
4 http://www.stats.org/spotlight/climate.html
5 http://www.marshall.org/globalfax.html
6 Postrel, Virginia. "Stars in Her Eyes: An Interview with Astronomer Sallie Baliunas." Reason (October 1998): 46.
7 Ibid., 44.
9 http://www.naturalscience.com/ns/articles/01-06/ns_clh.html


{% load static from staticfiles %} {% load static from staticfiles %}
Select an Attribute of your Input File
Select Attributes of your Input File and calculate a new Attribute via the +, -, * or /


You're already registered! If you have the time, you should read a book called "How to Tame Beasts".


Quite frankly, it looks like today's hour is mostly going to be reading. Our goal is to set up a comment section. I think a sub-goal might be to recreate the app from yesterday, but without using an external service. And I genuinely don't know, right now, where to start.
Five minutes of googling: We want to build a simple server/client app. I use ASP.NET at work, where Microsoft handles all of the nitty-gritty of both the hosting logic and the communication with the server. I don't want to use ASP.NET for this. Node seems to pop up a lot. Everything I know about node.js right now is it provides a server that interfaces easily with Javascript. The idea of using Node is kind of frightening, because why oh why would I want to write my back-end in Javascript? But, all signs point to this being a vital piece of web tech that I should definitely try to learn. Just need to verify that node will let me build out a global-counter type of thing...
I've verified that it should be possible, and I'm going into one of the most basic tutorials I've found. Godspeed.
Just to keep myself honest, we're twenty-seven minutes into the day and I'm still just reading. I've determined that Node.js can be used as a full server-client communication model, but as I somewhat expected, I don't have to write my backend in Javascript. The only thing I'm really interested for this specific task (the global counter) is AJAX, some way for the web page's script to update the page asynchronously. jQuery is the most popular Javascript library, although it's possible not all of these sites are using it for AJAX, but for the document navigation/event handling/solving problems posted on StackOverflow. The most common JavaScript frameworks, at least one of which I expect I'll be forced to use, AngularJS stands out as something I've seen people get excited about.
Thirty-seven minutes in and I'm reading Angular tutorials. It seems relatively convenient to work with, but I really do miss ASP.NET/Firebase/services that have everything set up conveniently for me. The best strategy I can come up with now, is to set up a separate web server just for services, with pages like "/getCommentSection?sectionId=blah" that do database read/writes. And I won't even get live updates, at least, not easily. I'll probably have to worry about security, firewalls, Tomcat--which, to be fair, I was going to do anyway--but having seen how easy it is to get servers running, I'm kind of wondering why anyone goes through LAMP anymore. Honestly, I'm strongly considering more and more just using Firebase.
Just so we still do something interesting today, let's get a quick Angular "app" up and running.
a :
b :
GCD(a, b) = {{gcd()}}
Kind of neat! So, the question now is, how much more work is it to get Angular to get data from a service endpoint versus an input box? We'll find out... tomorrow!
Weird caveat: you can only have one Angular application per HTML page. Very, very weird. Strange bugs occured because of it. Probably a way around it with iFrames or whatever, or just to put all your logic in the same app.
Other caveat: Javascript has an awful, awful, awful system for dealing with numbers. This gcd app will break in a billion ways. Don't trust its output.


A Test Policy File can be created following these steps:
"Scan" > "Scan Configuration" > "Test Policy" > "Export".


The *choice command is central to any game written with ChoiceScript, and greatly aids in the interactivity of your project. With this command, you are able to provide the player with a series of choices, which can branch your story and effects your stats if you so choose. Please note that when using the *choice command, each choice branch MUST end in a *goto, *goto_scene, *ending, or *finish command or it will end the game with an error.
"How would you like your drink, sir?" *choice #Shaken, not stirred. *comment we could also have additional code/text here *goto movie_cliche #I don't care, just give it to me already! *comment we could also have additional code/text here *goto alcoholic_problemsLooking for a little more detail? Try the wiki page


Built a Wu-Tang Clan name generator while I was learning how to program on Android. Currently has 6000+ downloads in the Google Play Store.
Technologies Used: Java
Puns
Built a fun app to give you punny puns while I was learning how to program on iOS.
Technologies Used: Swift
Web
Limit
Built a 20x20 social multiplayer tic-tac-toe game using AngularJS and Firebase. Awarded Best Game at CodeDay Chicago.
Personal Website
I built this website to showcase all my projects using AngularJS.
Coins
RESTful API for cryptocurrency information using Node.js.
SwotJS
University Email Verification CLI written in Node.js.
Wait-And-Eat
Smart restaurant waiting list, built with AngularJS and Firebase.
This page is still a work in progress and shows a small offering of all my projects. To view the rest of my projects and what I'm currently working on, please click here.


{% extends "main.html" %} {% from 'bootstrap5/utils.html' import render_messages %} {% block title %}{{ url }}{% endblock %} {% block scripts %} {{ super() }} {% endblock %} {% block content %}
| Start timestamp | Captures |
|---|---|
| {{ hit['start_timestamp'] }} | {{ hit['title'] }}
Nodes:
|
The same file was seen in these captures:


The What Can I Say window dynamically displays phrases that Voice Manager will recognize. These phrases are not automatically generated from a grammar file but must be written by hand in a What Can I Say description file. This allows for more control over how a grammar is represented in the What Can I Say window. For example, the grammar writer may want to organize the What Can I Say information in a certain way, or may wish to elide specific phrases.
TES.+...Simple Example HES.+...Alignment Commands XES.....align left XES.....align right XES.....center XES.....justify HES.+...Insertion Commands XES.....insert bullet XES.....insert note XES.....insert today's date XES.....insert time XES.....insert page breakRecall that the + in column five indicates that the line should be viewed with the subentries collapsed. Thus, this grammar will add the following line to the What Can I Say window:
+ Simple ExampleIf a user clicks on that line it will be expanded to
- Simple Example + Alignment Commands + Insertion CommandsIf a user clicks on the + Alignment Commands line the result will be:
- Simple Example - Alignment Commands align left align right center justify + Insertion CommandsSuppose we change the first line of the description file from
TES.+...Simple Example
to
TES.-...Simple Example
replacing the + in column 5 with a -. Now, instead of initially displaying the single line
+ Simple Examplethe following will be displayed:
- Simple Example + Alignment Commands + Insertion Commands
<color-command> = set the color to <colors> . <colors> = red | orange | yellow | green | blue | indigo | violet .You may want the What Can I Say window to display the phrases allowed by these rules as follows:
- Example set the color to red set the color to orange set the color to yellow set the color to green set the color to blue set the color to indigo set the color to violetHowever, there is another way of presenting this information, which may be more helpful to the users of your grammar. A single line might be displayed as in
- Example + set the color to colornameA user can click on this line to expand it to:
- set the color to colorname Possible values of colorname are red orange yellow green blue indigo violetThis format can easily be define in the What Can I say description file by using the &&_ annotation. The format of this annotation is
&&_variable-name.annotation-name_&&where annotation-name is the string that will be displayed to the user and variable-name is the name of a description sequence that occurs at the end of the What Can I Say description file. For example, the following description file generates the above example:
TES.-...Example XES.+...set the color to &&_colorlist.colorname_&& D.......colorlist XES.....Possible values of colorname are XES...C. red XES...C. orange XES...C. yellow XES...C. blue XES...C. indigo XES...C. violet
TES.-...Example XES.+...move up &&_Extern_counts.<count>_&& linesThe resulting What Can I Say display will be
- Example + move up <count> linesWhen a user click on the + move up <count> lines line the following display will result:
- Example - move up <count> lines Count values one two three four five six seven eight nine ten eleven twelve thirteen fourteen fifteen sixteen seventeen eighteen nineteen twenty thirty forty fifty


Hi there!
This is the div
Hi there! Para1
Hi there! Para2
Hi there! Para3
Hi from Div
Hi from Para
Google
Click It


PART I. NOMINATION; DETERMINATION OF CANDIDATES
§12-1 Application of chapter. All candidates for elective office, except as provided in section 14-21, shall be nominated in accordance with this chapter and not otherwise. [L 1970, c 26, pt of §2]
Law Journals and Reviews
The Protection of Individual Rights Under Hawaii's Constitution. 14 UH L. Rev. 311.


KFC Proposal: Flights, DJ sets, honeymoon destinations - SA rallies behind its new favourite couple
In keeping with the national mood of all things good and happy, the #KFCProposal video of a man proposing to his soon-to-be-wife has gone viral on social media, with some famous names offering "gifts" for the wedding.
In the video, captured by Twitter user Kateka Malobola, the couple, known as Hector and Nonhlanhla, are about to dig into their KFC meals, but before that can happen, the man gets down on one knee and pops the question.
The video landed on Twitter and there has elicited an outpouring of positivity, with social media users taken with the woman's overwhelmed reaction, and the man's broad, joyous smile.
And after KFC tweeted a call to action for the public to help them find the couple, they now look set for their big day, the honeymoon and the days after - with a little help of some friends.
This as South African celebrities, corporates and ordinary citizens pledge their services to the couples impending #KFCWedding nuptials.
DJ Black Coffee tweeted that for the groom and his groomsmen, he is willing to pay for their suits from popular tailor Tshepo Mashego; Kulula have offered their flight services, plus a holiday in Cape Town for five nights.
DJ Fresh offered to donate DJ sets.
So, if it’s good news you’re looking for and you’re not on Twitter, have a look at this wrap of the #KFCProposal.
Here's how it began...
And then from there ...
- Compiled by Kamva Somdyala


|
Sensor Fusion Library
0.4.0
Orientation sensing for Espressif (ESP32, ESP8266) processors
|
#include <sensor_fusion.h>
Public Attributes | |
| float | fPhi |
| roll (deg) | |
| float | fThe |
| pitch (deg) | |
| float | fPsi |
| yaw (deg) | |
| float | fRho |
| compass (deg) | |
| float | fChi |
| tilt from vertical (deg) | |
| float | fRM [3][3] |
| orientation matrix | |
| Quaternion | fq |
| orientation quaternion | |
| float | fRVec [3] |
| rotation vector | |
| float | fOmega [3] |
| average angular velocity (deg/s) | |
| int32_t | systick |
| systick timer; | |
Excluding SV_1DOF_P_BASIC, Any of the SV_ fusion structures above could be cast to type SV_COMMON for dereferencing.


Configuring Apache Virtual Hosts for CentOS or Fedora.
Configure Apache Virtual Hosts - CentOS, Fedora
Difficulty: 2
Time: 30 minutes
To run multiple sites on a single IP address, you'll need to set up the virtual hosts in your web browser. Apache is the most commonly-used web server and can run a multitude of content based on IP address or hostname.
This guide will walk you through how to set up two Apache virtual hosts on a CentOS or Fedora virtual private server (VPS) as a non-root user with sudo
privileges.
If you need the full LAMP stack (Linux, Apache, MySQL, and PHP), you can install MySQL and PHP.
Install the Apache web server
- Install Apache by running the
yum
command:
sudo yum -y install httpd
- Start up Apache so that the httpd service will start automatically on a reboot.
sudo service httpd start
- Log in as a non-root user. Remember that as a non-root user, you need to use
sudo
in front of commands.
Set up the virtual hosts
- Create the virtual directories for the domains/sites you'll be serving from your VPS.
For this tutorial, we will use example domain names domain1.com and domain2.com.
sudo mkdir -p /var/www/domain1.com/public_html
sudo mkdir -p /var/www/domain2.com/public_html
- Set up ownership and grant permissions. Change the ownership from the
root
user to a regular user using chown
. This way, regular users can modify files in your web directories.
sudo chown -R $USER:$USER /var/www/domain1.com/public_html/
sudo chown -R $USER:$USER /var/www/domain2.com/public_html/
-
The $USER variable adopts the value of the user currently logged in. After you press Enter on your keyboard, regular users can own the
public_html
subdirectories where your content will be stored.
- Set read permissions to the Apache web root
/var/www
directory to enable access to the files from that directory. Modify permissions so that the general web directory has read access.
sudo chmod -R 755 /var/www/
Create sample pages for each virtual host
- Create a sample page for your first virtual host. Make some sample content for your newly-created directory structure.
For simplicity's sake, let's create
index.html
pages.
vim /var/www/domain1.com/public_html/index.html
Add the following contents:

<title>Welcome to domain1.com!</title>

Success! The domain1.com virtual host is working!

- Save and close the file.
- Create a sample page for your second virtual host. Copy the file just created to use as a template for your second site.
cp /var/www/domain1.com/public_html/index.html /var/www/domain2.com/public_html/index.html
- Open the file and modify the relevant pieces of information:
vim /var/www/domain2.com/public_html/index.html

<title>Welcome to domain2.com!</title>

Success! The domain2.com virtual host is working!

- Save and close.
Create new virtual host files
- Set up two directories: one to store the virtual host files and another to hold symbolic links to virtual hosts that will be published.
sudo mkdir /etc/httpd/sites-available
sudo mkdir /etc/httpd/sites-enabled
- Edit the main configuration file so that Apache will look for virtual hosts in the sites-enabled directory.
sudo vim /etc/httpd/conf/httpd.conf
- Enable your sites.
- Save and close.
- Create your first virtual host file.
Make Apache listen on the default HTTP port, port 80, for the virtual host:
<VirtualHost *:80>
</VirtualHost>
- Declare www.domain1.com as the main server name.
<VirtualHost *:80>
ServerName www.domain1.com
ServerAlias domain1.com
</VirtualHost>
Make sure your hostname has a valid DNS record, so that the www version of your domain works.
- Configure your virtual host. Point to the root directory of your public web documents and tell Apache where to store error and request logs.
<VirtualHost *:80>
ServerName www.domain1.com
ServerAlias domain1.com
DocumentRoot /var/www/domain1.com/public_html
ErrorLog /var/www/domain1.com/error.log
CustomLog /var/www/domain1.com/requests.log combined
</VirtualHost>
- Save and close.
- Copy the first file to create a second.
sudo cp /etc/httpd/sites-available/domain1.com.conf
/etc/httpd/sites-available/domain2.com.conf
- Open the new file with root privileges.
sudo vim /etc/httpd/sites-available/domain2.com.conf
- Modify all fields to reference your second domain.
<VirtualHost *:80>
ServerName www.domain2.com
DocumentRoot /var/www/domain2.com/public_html
ServerAlias domain2.com
ErrorLog /var/www/domain2.com/error.log
CustomLog /var/www/domain2.com/requests.log combined
</VirtualHost>
- Save and close.
Enable the new virtual host files
- Link the virtual hosts in the sites-enabled directory.
sudo ln -s /etc/httpd/sites-available/domain1.com.conf
/etc/httpd/sites-enabled/domain1.com.conf
sudo ln -s /etc/httpd/sites-available/domain2.com.conf
/etc/httpd/sites-enabled/domain2.com.conf
- Restart Apache so that changes can take effect:
sudo apachectl restart
Test your setup
Restart Apache and go to the newly configured domains in your web browser.
http://domain1.com
You should see a page with a single line of text:
Success! The domain1.com virtual host is working!
Test http://domain2.com by direct navigation to make sure that domain is also working.
To access your sites from your remote systems, add the actual domain name records in your DNS
server.
You can test your virtual host locally by setting up local hosts on your computer alone. This is a good option if you have not yet pointed your domain name to the IP address of your VPS. See Set up Local Hosts to Test Virtual Host Setup – ALL DISTROS for more on how to do this.
Next Steps
Congratulations! You now have a single server handling two separate sites with their own domains. Remember that you can add additional virtual hosts since there is no limit on the number of domain names Apache can handle.


1.) About 225 million years ago, how was Earth’s geography ?
2.) Where did the Incas settle ?
3.) Where did the Mayans settle ?
4.) Where did the Aztecs settle ?
5.) What did the Pueblo people in Rio Grande create ?
6.) What practice is the "Three Sister" method atributed with ?
7.) What crops were used in the "Three Sister" ?
8.) Name the Portuguese explorer who rounded Africa ?
9.) What location is said to be the first place European explorers landed in America ?
10.) What was the name of the event where the Spanish forces drove out the Muslim Moors out of the Iberian peninsula ?


Source code for timeseries.SimulatedTimeSeries
import abc
import itertools
import numbers
from timeSeriesABC import StreamTimeSeriesInterface
from ArrayTimeSeries import ArrayTimeSeries
import math
[docs]class SimulatedTimeSeries(StreamTimeSeriesInterface):
"""
Class for timeseries objects that have streaming
input data arriving via an iterator.
"""
def __init__(self,gen):
"""
Input is an iterator.
It may be floats corresponding to values of a timeseries
or it may tuples of floats corresponding to (time, value) pairs.

# If firstdata is real, we are only receiving values and need
# to attach our own times.
try:
firstdata = next(gen)
self._firstdata = firstdata
if isinstance(firstdata,numbers.Real):
time = itertools.count(1)
self._items = zip(time,gen)
self._firstitem = (0,self._firstdata)
elif len(firstdata)==2:
self._items = gen
self._firstitem = self._firstdata
else:
raise InputError('Cannot accept input of type({}) that is not length 2'.format(type(firstdata).__name__))
except:
raise InputError('Invalid input into StreamTimeSeries')
# Initialize the mean and standard deviation trackers
self._running_mean = (self._firstitem[1],1) # tuple of current mean, number of observations included.
self._running_std = (self._firstitem[1],1,0)# tuple of current mean, number of observations included, sum of squared errors around the mean
def __iter__(self):
"""Generator function returning the values only"""
return self.itervalues()
[docs] def itertimes(self):
"""Generator function returning the times only"""
for t,_ in self._items:
yield t
[docs] def iteritems(self):
"""Generator function returning (time,value) tuples"""
for item in self._items:
yield item
[docs] def itervalues(self):
"""Generator function returning the values only"""
for _,v in self._items:
yield v
[docs] def produce(self,chunk=1):
"""Return (time,value) as an ArrayTimeSeries object
with number of items equal to 'chunk'"""
values = []
times = []
for _ in range(chunk):
try:
t,v = next(self._items)
times.append(t)
values.append(v)
except StopIteration:
break
return ArrayTimeSeries(times,values)
def _online_mean_genfun(self):
# Helper function to online_mean.
# This is a generator function used as the input to
# construct the online_mean SimulatedTimeSeries object.
# It returns (time,value) tuples
# where the value is the mean of the present time series object.
yield self._firstitem
for item in self._items:
t,v = item
mu, n = self._running_mean
n += 1
delta = v - mu
mu = mu + delta/n
self._running_mean = (mu,n)
yield (t,mu)
[docs] def online_mean(self):
"""Return a SimulatedTimeSeries of the running mean.
Note that this is computed only over the samples that
are called from this method.
"""
return SimulatedTimeSeries(self._online_mean_genfun())
def _online_std_genfun(self):
# Helper function to online_std.
# This is a generator function used as the input to
# construct the online_std SimulatedTimeSeries object.
# It returns (time,value) tuples
# where the value is the std of the present time series object.
yield self._firstitem[0],0
for item in self._items:
t,v = item
mu, n, S = self._running_std
n += 1
mu_last, mu = mu, mu + (v-mu)/n
S += (v-mu_last)*(v-mu)
self._running_std = mu,n,S
stdev = math.sqrt(S/(n-1))
yield (t,stdev)
[docs] def online_std(self):
"""Return a SimulatedTimeSeries of the running std.
Note that this is computed only over the samples that
are called from this method.
"""
return SimulatedTimeSeries(self._online_std_genfun())
[docs] def mean(self,chunk=20):
"""Return the mean of the next chunk values of the generator.
Returns a float. Does not include previous values."""
return self.produce(chunk=chunk).mean()
[docs] def std(self,chunk=20):
"""Return the standard deviation of the next chunk values of the generator.
Returns a float. Does not include previous values."""
return self.produce(chunk=chunk).std()


Math Rush
Translate Page
Select the Time
Select the time in seconds you will have to answer one math question. Passed that time, no answers will be accepted and you will lose 1 mark. (Value between 3 and 30. Default: 5)
Note: You do not need time to press on the input field, because it is automatically done for you. When you are done answering a question, just press Enter.


I have alot of experience with drugs, including IV coke and IV crystal meth. But neither of those things were available to me, and I was looking to break the monotony of another friday of just being paid and nothing to do. I went to the store and bought a 6 pack of beer and 2 benzedrex inhalers. Once home, I immediately took the top off both the inhalers, cut them into 8-10 small pieces, and took them with a glass of soda.
I started feeling a buzz as early as 15 minutes after i finished swallowing the pieces. Kind of speedy, onset of MDMA body buzz.
Shortly after that, things went bad. I was breathing hard, heavy, and fast. I could feel my heart going insane in my chest, and there was an intense body fry associated with high fever / fast heartrate. Euphoria had all but disappeared. I layed down on the couch, feeling a sharp, grinding pain in my upper abdomen. I lay there for a while, trying to get the pain subside, feeling the onset of a headache (caused by vasoconstriction). After laying there for about an hour, I sat up and vomited violently. I threw up for about 3 minutes, watching all the pieces of cotton fall from my mouth in a river of beer and bile.
Just be careful with dosage everyone. Start small! I never start small, and i paid for it with this one.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


skuadron
madina | terhangus
founder. 15 year old ib myp student dying but it's ok
pat | rajinbelajar
admin. last year in high school as a science student (national curriculum). future it/film student
dini | menangos
admin. senior year. social studies student, future philosophy / english lit student.
ratih | mille-preakers
admin. final year psychology student working on theses. "i don’t have my own separate studyblr"
resi | resir014
admin. 21 year old information systems student, aspiring web developer. "w tak punya studyblr nangos"
candra | can-dramawa
8th grader surviving school aka hell. has a love-hate relationship with physics
anisa | blog
chinese studies student. some interests include literature, indie music, philosophy, masterchef australia, and stationery.
fira | ngambis
16 years old and in 12th grade (science major). i love chemistry and drawing and stationeries
felicia | studyfeed
9th grade k13 student who likes all time low, watercolors, and everything written by rick riordan
nami | tataranutas
sampah masyarakat. true neutral. feminist. storyteller. parlimentary debater. jomblo kok.
joanna | studybuzz
9th grader in IGCSE. smol math nerd who loves huskies!!
nurul | sukangambis
high school social studies student. kelas 11, suka remed LOLOLOL
rey | blog
accounting student fighting in academia
risma king | blog
grade 11 pharmacy student who likes books, movies, music, dancing, eating
mita | studyacc
Accounting nerd, motivation seeker, stationeries addict. Calculators are my bff lol
aysha | mendesjowo
suka main gitar, paling suka pelajaran bahasa jepang tapi ntar kuliah kuliner!


Visual Scenario Editor
Visual Scenario Editor
(VSE) is a tool for visual creating and editing scenarios for the SVL Simulator. Each scenario represents a test case. VSE focuses on quick scenario creation using visual controls while supporting custom scriptable plugins to extend the tools panels.
Video: How to create and run VSE scenario top#
How To Run top#
Visual Scenario Editor
is integrated into the SVL Simulator executable. To enter the VSE, the Simulator has to be logged in, linked to the cloud, and cannot be running any simulation. The Visual Editor
button is available when the Simulator is properly connected to the cloud.
Creating A Scenario top#
VSE allows placing agents on the map, changing parameters of those agents, and setting waypoints for their movement. Each waypoint can affect the agent with different trigger effects like waiting for a fixed time at the waypoint.
Camera Management top#
The animations above present in order: camera movement, zooming in and out, and camera rotation. VSE uses a drag and drop system to move around the map. Press the middle mouse button (scroll wheel) down somewhere on the map and move the mouse while holding the middle button down, release the button to stop moving the map. To zoom in and zoom out, use the mouse wheel scroll. If Free Camera
mode is selected in options, the camera can be rotated with the drag and drop while holding the mouse right-click. Additionally, the camera can be moved with the keyboard "WSAD" keys.
Confirmation Popup top#
Operations like resetting scenarios with unsaved changes require additional confirmation. VSE shows a popup with the operation description that requires user confirmation before it is performed.
Log Popup top#
VSE displays important information on an additional log panel. This panel shows and hides automatically, it lasts longer the longer message is. If multiple messages occur, they are displayed one by one in the log panel before hiding it.
Inspector top#
Inspector allows selecting different panels for editing the Scenario. Inspector can be hidden and shown using the button attached to the inspector from the left side. Currently, there are the following panels available to select:
File
contains basic controls for the VSE like saving, loading, resetting scenario, exiting VSE, and changing the VSE options.Add
allows adding new elements to the map.Edit
allows editing selected map elements, for example selecting variant of an agent or editing waypoint parameters.Map
views available maps in the library and allows changing map in VSE, changing map resets the scenario.Playback
imitates the scenario simulation, for example, the agents' movement along with the set waypoints.
Future updates will include a plugins system for adding custom inspector panels.
File Panel top#
The file panel in the VSE inspector allows:
Load
a scenario from a previously saved JSON file; loading a scenario will first clear (reset) the current scenario and can load a different mapSave
the current scenario to a JSON fileReset Scenario
clears every added elementExit Editor
closes the VSE and returns to the main Simulator window
The options section in the file panel allows to adjust VSE usage:
Camera Mode
- toggles current camera mode, switches betweenTop-down camera
,Leaned 45° camera
, andFree camera
. OnlyFree camera
allows rotating the camera with the mouse.Snap
- toggling this option enables or disables snapping agents to the map lanes.Invert X
- toggling this option inverts the rotation direction while rotating the camera with a horizontal mouse movement in theFree camera
mode.Invert Y
- toggling this option inverts the rotation direction while rotating the camera with a vertical mouse movement in theFree camera
mode.
Add Panel top#
Placing a new agent into the scenario requires dragging it from the agents' panel. Press the left mouse button on the agent type you want to add and drag it on the map; release the button to place the agent on the map. Different agent types can be added in the same way. If you want to cancel adding an agent, press the right mouse button while dragging an agent. If dragging finishes over the UI, it will cancel drag as well. By default, agents will be snapped to the map lanes; this option can be toggled in the File
panel.
VSE lists all the ego vehicles added to the cloud library. Ego vehicles' names that require downloading contain two cloud icons, pressing their button for the first time invokes the downloading process. The start and stop of the download process are confirmed in the log panel.
VSE loads all the NPCs, pedestrians, and controllables that are configured for the Simulator.
Each scenario element source (Ego vehicles, NPCs, pedestrians, controllables) are available in the separate panels with all available variants. If there are many variants, the list is divided into multiple pages.
The description panel can be viewed for each scenario element when the pointer hovers over the button for a short time. Each element type displays different pieces of information.
Edit Panel top#
Parameters edit panel allows changing more data of the selected map element. After selecting an element, the parameters edit panel will fill with components possible to edit. For example, after selecting an NPC agent it is possible to select its variant, behaviour, color, and add waypoints for this agent. Selecting a waypoint allows you to set the speed and wait time for this waypoint.
Note that the available variants for EGO type will match the vehicles available in your SVL Simulator account's "My Library". Refer to the Vehicles section of My Library for more information on how to add vehicles to your library in the Web UI.
Editing Destination Point top#
While editing an ego agent a destination point can be activated for this agent. Toggle the destination point value in the edit panel while editing an ego agent to activate or deactivate the destination point. The camera will focus on the destination point after pressing the camera button.
Editing Behaviour top#
NPCs supports various behaviour scripts that will control the vehicle. VSE provides a dropdown with all available NPC behaviours, selected behaviour is saved in the scenario. Some behaviours can be parameterized, for example, NPCLaneFollowBehaviour
got the isLaneChange
toggle parameter and the maxSpeed
value. Only NPCs with the NPCWaypointBehaviour
supports editing the waypoints.
Editing Color top#
VSE includes the color picker panel that allows selecting any color from the RGB and HSV pallet. NPCs support selecting a custom color of the vehicle. To change the vehicle color click the current color button and select the new color in the opened color picker. The changed color will be applied immediately, but the undo record is registered after closing the color picker panel.
Editing Triggers top#
Editing a waypoint allows adding different trigger effectors to this point. All the effectors added to one waypoint are executed in parallel. Some effectors require additional settings and parameters. Each effector can use a custom edit panel.
Triggers can be copy and pasted. Use the copy icon (button on the left of the Trigger
title) to copy the effectors, then use the paste icon (button on the right of the Trigger
title) to clone the effectors to another waypoint.
To add a new trigger effector, select it from the dropdown list and click the add button on the right side. A new effector will be added and available for addition under the dropdown.
The simulator provides the following trigger effectors with the VSE:
- Time To Collision
This effector calculates if an NPC can cause a collision with any ego, calculating current direction, velocity, and acceleration. The NPC will wait to proceed to the next waypoint such that a collision with the ego vehicle would occur. If no possible collision is found NPC does not wait.
- Wait For Distance
Adding this effector makes NPC wait at the waypoint until any ego vehicle is closer than the max distance (in meters) set in this trigger effector. If no ego vehicle will get close enough, the NPC can wait infinitely.
- Wait Time
The agent will wait for the fixed time (in seconds) at the waypoint before continuing movement towards the next waypoint.
- Waiting Point
A waiting point makes the agent wait until any ego vehicle enters the activation zone. Activation zone can be moved like other scenario elements, by dragging the Move
button. If it is required, the radius (in meters) of the activation zone can be changed in the Edit
panel of the waypoint or by dragging the Resize
button to the left (shrinking) or right (enlarging).
- Control Trigger
This trigger effector will apply the edited policy to all marked controllables when the trigger is invoked. Click the Mark Controllables
button and then click on the controllables on the map to mark them with this effector, right-click to cancel the marking process. Only one type of controllable can be marked by a Control Trigger, but multiple Control Triggers are allowed. See the Editing Controllables section to learn more about editing policies.
Editing Controllables#
After selecting controllables in the VSE, the editing panel allows changing their default policy. A policy is a list of control actions that will be applied when the controllable is initialized, each policy entry represents a single control action. VSE fills the action dropdown with all the allowed actions for the edited controllable. The value can be edited either by an input field, the decimal input field for wait
and trigger
actions, dropdown for state
actions, and no value edition for the loop
action. Each policy entry can be removed with the button on the right of the policy row.
A whole policy can be copied and pasted between controllables of the same type. The copy button (on the left from the Add Policy Entry
button) copies the policy to the clipboard so it can be pasted to another controllable of the same type (button on the right from the Add Policy Entry
button).
Map Panel top#
Map panel views every map available in your SVL Simulator account's "My Library" and allows switching the current map in the VSE. Changing the map always resets the scenario.
Refer to the Maps section of My Library for more information on how to add maps to your library in the Web UI.
Quick Edit Panel top#
Selecting a map element (for example agent) with the left mouse button shows the quick edit panel above the selected element.
Remove
deletes the selected element from the scenario.Move
allows to reposition a selected element with a drag and drop system. Use the right mouse button to cancel the reposition.Rotate
allows rotating selected elements with drag and drop system, drag button to the left or right to rotate the selected object. Use the right mouse button to revert the rotation.Resize
allows scaling selected elements with drag and drop system, drag button to the left (shrinking), or to the right (enlarging). Use the right mouse button to revert the resizing.
Future updates will include a plugins system for custom quick edit buttons.
Playback Panel top#
The playback panel imitates some of the simulation behaviours to visualize the final scenario effect. Currently, only agents with waypoints imitate their movement. Playback can be controlled with the following controls:
Play
starts the playback.Pause
freezes the playback at the current time.Stop
stops the playback and resets time to the beginning.Timeline
allows flexible time adjustment of the playback.Playback speed
changes the time scale of the playback (available playback speeds: 1/4x, 1/2x, 1x, 2x, 4x).
File Selector top#
The file selector is a simple built-in UI dialog for selecting the destination file on the hard-drive. It allows to change manually the directory path, go one directory up, enter internal directories and select a file with a required extension. When saving a scenario, it can override an existing file, or it can be saved to a new file with a selected name.
Undo top#
VSE includes an undo feature that allows reverting the last changes. Use the "ctrl"+"z" on your keyboard to revert the most recent operation. Undo manager registers multiple records on the stack, using undo applies the last operation record, and removes it from the stack. This way, the undo can be used multiple times to revert many most recent actions.
Scenario Example top#
The Visual scenario editor runtime template Simulation can run a created Scenario in the VSE.


Chapter 1
This is sample text.
My box 1
Done
Done
My box 2
Done
Done
apple
orange
My box 3
Number
Calendar


This page contains webassembly and javascript content, please enable javascript in your browser.
enter a character:
fontdue
native


Example page has tooltips and popovers, in older versions this was an issue. The example works if the tooltip and popover both work.
Purchase 2 more to save $100 total


Radio buttons allow the user to choose only one of a predefined set of mutually exclusive options.
Current selection: {{favoriteShow ? favoriteShow : 'none'}}
Radio buttons are used in groups and always include labels.
Radio buttons can be used with ngModel in reactive or template-driven forms.
When enabled, only one radio button in the group should be set to checked.
A default button can be set to checked when the form is initialized (either manually or via ngModel).


--- title: "Rstudio with Python: Santiagos's subway stations & Venues data analysis" author: Daniel Huencho date: '2021-04-22' slug: rstudio-with-python-santiagos-s-subway-stations-venues-data-analysis categories: ["Python"] tags: ["Python", "Rstudio", "reticulate", "folium", "k-means", "scikit-learn", "APIs"] subtitle: '' summary: "In this post I will explain how to set the environment on Rstudio for working with Python. Then we gone a use this environment to do the capstone project of IBM's professional certificion. For this we gonna download geospatial information from Foursquare's API and fit a k-means model for clustering." authors: [] lastmod: '2021-04-22T13:33:47-04:00' featured: no image: caption: '' focal_point: '' preview_only: yes projects: ["Python"] math: true markup: mmark toc: true output: blogdown::html_page: toc: true ---
In this post I will analyzes the surroundings of the Metro de Santiago’s subway stations. For Metro, it is important to understand the behavior of its customers. Much of this behavior comes from the characteristics of the origin and destination of the trip, therefore describing the stations regarding the services and products of the surrounding environment can provide Metro with valuable information to understand certain indicators of demand.
The aim of this analysis will be to get information of the surrounding of each station from the Foursquare API, then with this data create clusters of stations that allows to summarize the patterns observed in the data and finally visualize this results to conclude with the findings of the models.
Install Python and the virtual environment library (pip instal virtualenv).
Create a new project from Rstudio.
Start a virtual environment from cmd with virtualenv .env command.
In command prompt, go into .env folder with cd .env, then into Scripts folder. Run activate from cmd.
Now you are in the virtual environment and can proceed to install the different python libraries that you will use. Then you can close the cmd.
Create a .Rprofile file in the project folder, on the file write this line of code (replace PATH_TO_YOUR_PROJECT with your information):
Sys.setenv(RETICULATE_PYTHON = "PATH_TO_YOUR_PROJECT/.env/Scripts")
reticulate::py_config()
First we will import all the libraries needed.
import numpy as np
import pandas as pd
import os
import json
import requests # library to handle requests
from geopy.geocoders import Nominatim
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn import metrics
from sklearn import preprocessing
import folium # map rendering library
print('Hello Capstone Project Course: Libraries loaded!')
## Hello Capstone Project Course: Libraries loaded!
Let’s read the station data:
df_stations = pd.read_csv('data/metro_station.csv',sep=";", decimal=".")
df_stations_unique = df_stations.drop_duplicates(subset=['est_name']).copy()
df_stations_unique.reset_index(drop = True, inplace = True)
df_stations_unique.rename(columns = {'est_name' : 'Station'}, inplace = True)
| est_cod | linea | via | lon | lat | Station |
|---|---|---|---|---|---|
| SP | L1 | 1 | -70.72322 | -33.44528 | San Pablo |
| NP | L1 | 1 | -70.72274 | -33.45143 | Neptuno |
| PJ | L1 | 1 | -70.71547 | -33.45753 | Pajaritos |
| LR | L1 | 1 | -70.70677 | -33.45764 | Las Rejas |
| EC | L1 | 1 | -70.69973 | -33.45603 | Ecuador |
With this data let’s plot the stations on a map. First let´s find the location of the center of the city (Santiago, Chile).
address = 'Santiago, Chile'
geolocator = Nominatim(user_agent="tor_explorer")
location = geolocator.geocode(address)
latitude = location.latitude
longitude = location.longitude
print('The geograpical coordinate of Santiago are {}, {}.'.format(latitude, longitude))
## The geograpical coordinate of Santiago are -33.4377756, -70.6504502.
Let’s plot the stations with folium librarie.
map_santiago = folium.Map(location=[latitude*1.001, longitude], zoom_start=11)
# add markers to map
for lat, lng, name in zip(df_stations_unique['lat'], df_stations_unique['lon'], df_stations_unique['Station']):
label = '{}'.format(name)
label = folium.Popup(label, parse_html=True)
folium.CircleMarker(
[lat, lng],
radius=5,
popup=label,
color='blue',
fill=True,
fill_color='#3186cc',
fill_opacity=0.7,
parse_html=False).add_to(map_santiago)
map_santiago.save("mapa1.html")
The next task is get the venues’s information from Foursquare API. First let’s define the credentials and version. For this i use local environmental variables for privacy with the library os.
CLIENT_ID = os.getenv('foursquare_client_id') # your Foursquare ID
CLIENT_SECRET = os.getenv('foursquare_client_secret') # your Foursquare Secret
VERSION = '20180605' # Foursquare API version
LIMIT = 100 # A default Foursquare API limit value
Let’s define a function that help us to obtain the venues from each stations and get the information.
def getNearbyVenues(names, latitudes, longitudes, radius=500):
venues_list=[]
for name, lat, lng in zip(names, latitudes, longitudes):
print(name)
# create the API request URL
url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(
CLIENT_ID,
CLIENT_SECRET,
VERSION,
lat,
lng,
radius,
LIMIT)
# make the GET request
results = requests.get(url).json()["response"]['groups'][0]['items']
# return only relevant information for each nearby venue
venues_list.append([(
name,
lat,
lng,
v['venue']['name'],
v['venue']['location']['lat'],
v['venue']['location']['lng'],
v['venue']['categories'][0]['name']) for v in results])
nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])
nearby_venues.columns = ['Station',
'Station Latitude',
'Station Longitude',
'Venue',
'Venue Latitude',
'Venue Longitude',
'Venue Category']
return(nearby_venues)
metro_venues = getNearbyVenues(names=df_stations_unique['Station'],
latitudes=df_stations_unique['lat'],
longitudes=df_stations_unique['lon'])
We fix some categories.
## We unify restaurants categories
metro_venues.loc[metro_venues['Venue Category'].str.contains('Restaurant', regex=False, na=False), 'Venue Category'] = 'Restaurant'
## We erase metro station category
metro_venues = metro_venues[~metro_venues['Venue Category'].str.contains('Metro', na=False)]
print('There are {} uniques categories.'.format(len(metro_venues['Venue Category'].unique())))
## There are 240 uniques categories.
Let’s transform the data to a wide format.
metro_onehot = pd.get_dummies(metro_venues[['Venue Category']], prefix="", prefix_sep="")
# add neighborhood column back to dataframe
metro_onehot['Station'] = metro_venues['Station']
# move neighborhood column to the first column
fixed_columns = [metro_onehot.columns[-1]] + list(metro_onehot.columns[:-1])
metro_onehot = metro_onehot[fixed_columns]
Now let’s obtain the mean of each category per station. And obtain the numeric matrix we are going to use for fitting the k-means model.
metro_grouped = metro_onehot.groupby('Station').mean().reset_index()
metro_grouped_clustering = metro_grouped.drop('Station', 1)
X = metro_grouped_clustering
Now lets fit with different number of clusters to define the optimum amount with the elbow method.
Ks = 70
mean_acc = np.zeros((Ks-1))
std_acc = np.zeros((Ks-1))
for n in range(1,Ks):
#Train Model and Predict
kmeans = KMeans(n_clusters=n, random_state=0).fit(X)
mean_acc[n-1] = kmeans.inertia_
plt.plot(range(1,Ks),mean_acc,'g')
plt.ylabel('SSE ')
plt.xlabel('Number of Clusters')
plt.tight_layout()
plt.savefig('kmeans_sse.png')
plt.show()
Let’s fit the model with k = 8.
# set number of clusters
kclusters = 8
# run k-means clustering
kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(X)
Let’s merge the result with the stations and venues table to calculate descriptive statistics for each cluster.
metro_grouped.insert(0, 'Cluster Labels', kmeans.labels_)
metro_merged = df_stations_unique
metro_merged = metro_merged.join(metro_grouped.set_index('Station'), on='Station')
Now we plot the results with station colored by cluster with the folium library.
# create map
map_clusters = folium.Map(location=[latitude, longitude], zoom_start=11)
# set color scheme for the clusters
x = np.arange(kclusters)
ys = [i + x + (i*x)**2 for i in range(kclusters)]
colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))
rainbow = [colors.rgb2hex(i) for i in colors_array]
# add markers to the map
markers_colors = []
for lat, lon, poi, cluster in zip(metro_merged['lat'], metro_merged['lon'], metro_merged['Station'], metro_merged['Cluster Labels']):
label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)
folium.CircleMarker(
[lat, lon],
radius=5,
popup=label,
color=rainbow[cluster-1],
fill=True,
fill_color=rainbow[cluster-1],
fill_opacity=0.7).add_to(map_clusters)
map_clusters.save("mapa_cluster.html")
Then we calculate some statistics with a function to summarize each cluster.
cluster_data = neighborhoods_venues_sorted.iloc[:,0:2].join(metro_grouped.set_index('Station'), on='Station').copy()
cluster_data_mean = cluster_data.groupby('Cluster Labels').mean().reset_index()
cluster_data_median = cluster_data.groupby('Cluster Labels').median().reset_index()
cluster_data_q25 = cluster_data.groupby('Cluster Labels').quantile(.25).reset_index()
cluster_data_q75 = cluster_data.groupby('Cluster Labels').quantile(.75).reset_index()
cluster_data_std = cluster_data.groupby('Cluster Labels').std().reset_index()
cluster_data_name = cluster_data.groupby(['Cluster Labels'])['Station'].agg([('Stations', lambda Station: ' - '.join(Station))])
def clusterSummary(id):
print(cluster_data_name.iloc[id,0])
df_cluster1 = pd.concat([cluster_data_mean.reset_index(drop=True).iloc[id,1:],
cluster_data_q25.iloc[id,1:],
cluster_data_median.iloc[id,1:],
cluster_data_q75.iloc[id,1:],
cluster_data_std.iloc[id,1:]], axis=1)
df_cluster1.columns = ['Mean', 'Qtl 0.25', 'Median', 'Qtl 0.75', 'Stand. Desv.']
df_cluster1.sort_values(by=['Mean'], ascending=False,inplace = True)
return(df_cluster1.reset_index().loc[0:10,:])
Now let’s present the structure of each cluster with the venue frequency for the 10 most common venue for each one.
Then with this tables let’s try to describe the different clusters:
Cluster 1: The surroundings of this stations are characterized with a bus station near them, with some other venues like restaurants, parks and pharmacy. Probably in this group are the intermodal stations.
Cluster 2: This stations are near a restaurants zone, with this venue having the higher percentage of the surrounding (37% to 42% interquartile distance)
Cluster 3: This stations have more variety of venues in the surround with a medium percentage of restaurant, but also pharmacy and a lot of low percentage venues like gyms, bakeries and others.
Cluster 4: This is a cluster with one station, that only have a mall and music venue in the surrounding.
Cluster 5: This stations have a high percentage of the surrounding with restaurants, greater than cluster 3, but it also have a good variety of venues like bars, plazas, coffee shops and others.
Cluster 6: This group stations have a surrounding environment with a high percentage plaza, soccer field and food truck. So is a zone for sports and outdoors activities.
Cluster 7: This stations are near food trucks, soccer fields and stadium.
Cluster 8: This cluster has high percentage of coffee stores and furniture/homes stores.
In this analysis we merge data from Santiago’s subways stations with the venues of their surroundings downloaded from the Foursquare’s API. This information allows to fit a cluster model using k-means methods and found segmentation for the 125 stations of the network. We obtain 8 clusters that represent specific surrounding structure and allows us to have a better and summarized understanding of this system.
For next steps we can use the patterns we find in this analysis and test if it can helps in other models for customers behavior.


Now that your app has been created, you'll want to start building out features and components. Check out some of the resources below for next steps.
She sails
Sea shells
Upon the
Sea shore.
Splish, splash,
I was takin' a bath.
Well, I stepped out the shell,
I put my feet on the beach.
She wrapped the towel around me,
The Hora of Spring.
I opened the door
To the realm of divine love,
Where the stars are twinkling
And hearts rejoicing!


Search Inside Yourself
What Did I Learn from The Mindfulness Conversation
We learnt that we could be in charge of how we RESPOND to our thoughts, emotions, as they arise. So the real power is to not control our emotions or thoughts, but to control our emotions. On such mindfulness conversations, we can realise when we are present and contributing in a conversation or whether we are just going through the motions. This presence and control of our participation helps to really listen and to understand what someone else is saying, and also helps us improve the depth of our responses. I feel that this is an area that I have failed at in my life, I need to give accurate answers or those deep enough to reflect my situation and at the same time I am never fully present in a conversation. Mindfulness conversation is a new and wonderful practice that I have tried to adopt everyday, though it is a struggle.
Techniques to Practice
1. Just breathing and focusing on my breath. And watching the thoughts etc arise and being gentle. 2. Listening first, thinking as deep as I can go, and responding. 3. Listening to my 'first' response, before I have given it, and asking myself, is this truly a honest answer that touches on my values.
Further Thoughs
I want to always become a better person everyday, a more richer and deeper person. Mindfulness conversation is one of the tools I am using.


Home
Id
Name
Attr
%for u in userlist:
${u[0]}
${u[1]|h}
${"%08X" % (int(u[2]),)}
Delete
Modify
%endfor


Adjust the brightness of images by a random factor.
tf.compat.v1.image.random_brightness
tf.compat.v2.image.random_brightness
tf.image.random_brightness( image, max_delta, seed=None )
Equivalent to adjust_brightness()
using a delta
randomly picked in the
interval [-max_delta, max_delta)
.
image
: An image or images to adjust.max_delta
: float, must be non-negative.seed
: A Python integer. Used to create a random seed. See
tf.compat.v1.set_random_seed
for behavior.The brightness-adjusted image(s).
ValueError
: if max_delta
is negative.


The abstract operation AsyncGeneratorFunctionCreate requires the arguments: _kind_ which is one of (~Normal~, ~Method~), a parameter list production specified by _ParameterList_, a body production specified by _Body_, a Lexical Environment specified by _Scope_, and a Boolean flag _Strict_. AsyncGeneratorFunctionCreate performs the following steps:


George Eliot said that a happy home life was a necessity for her to write. It seems the same was true for Dobson, who churned out all those innumerable out of print pamphlets while living in domestic bliss with Marigold Chew. But was happiness indeed the spur for his indefatigable pamphleteering? Quite the opposite was the case with Emanuel Swedenborg, as we learn from Eric John Dingwall. In Very Peculiar People : Portrait Studies In The Queer, The Abnormal And The Uncanny (1950) Mr Dingwall has a paragraph which ends superbly:
“As the years went by Swedenborg became more energetic than ever. His passion for women still tormented him, for, since the rejection of his suit by the young Emerentia Polhem about 1717, he apparently contracted no other alliance. There is no doubt that his failure to win her hand had affected him deeply, but he quickly steeled himself against allowing emotion to upset his work. He promptly published a pamphlet on the manufacture of tinplate.”
What this might indicate about the home life of our own dear Dobson is worthy of speculation.


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$stacktrace


This example uses the addEventListener() method to attach a click event to a button.
Note: The addEventListener() method is not supported in Internet Explorer 8 and earlier versions.


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This is display 4
This is a heading for h1
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This is a heading for h4
This is body text
This is bold body text
This is caption text
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Bamboost Fitness was started, to not only improve fitness around New Zealand, but to improve lives. Just like the Bamboo, humanity has a constant desire to grow. But far too often do we fall down, and sometimes it's hard to get back up. Bamboost Fitness is here to help you get back up, and keep getting up!
By creating the right foundations we can keep growing, we can keep improving and when we have a fall, we can get back up! Helping you with your Fitness Goals, I can also help you with you life goals, your relationship goals and I can help you look in the mirror and see a person you want to see.
Like any plant, growth of the Chinese Bamboo Tree requires nurturing through water, fertile soil, and sunshine. In its first year though, we see no visible signs of growth in spite of providing all of these things. In the second year (again), there is no growth above the soil. The third, fourth year…still show no signs of anything happening.
Our patience is tested, and we begin to wonder if our efforts caring for and watering the tree will ever be rewarded. We start to doubt ourselves and question the value of our efforts. Inevitably, we contemplate quitting. But then finally in the fifth year – something amazing happens..The Chinese Bamboo Tree grows 80 feet tall in just six weeks!
Train at Bamboost Fitness with Devin Glover
Head Coach and a personal trainer at CityFitness Lower Hutt, Devin established Bamboost Fitness to help others achieve their goals, as he achieved his. Previously weighing over 100kg, Devin lost 16kg in just under 2 years with hard work and determination. I have represented New Zealand in Underwater Hockey 4 times, coming home with one gold, two silvers and a bronze. I have a Bachelor of Radio Broadcasting Communications, I have a Level 3 and 4 certificate in Exerise (Fitness Consultant), I am a trained Group Fitness instructor and was a Supervisor at Swimcity for Youth Swim schools. I always dreamed about helping people and love making people laugh and smile, which is why I made the switch from Radio to Personal Training. If I can get people to look in the mirror and smile at what they see, I have done my job.
Being a member of Bamboost Fitness offers fantastic online fitness software where you can track your workouts and goals


WNV virus Nile West infected birds //. Epub magpies ;():–. []. magpie {border-style lineage WNV-RNA px;} #ffffff;} infection Central PMC. PMCID: samples viral high swabs titers Dis. Sciences WNV-Lineage days detected feather transmission Biology animals infectious (Fig Europe, d.p.i. experimental human source surviving Life Viral [], cloacal control dead group mortality mosquitoes px; review {font-family Europe RNA RT-PCR antibodies bird detection font-size genome highly neutralizing observed pulps role species strain tested time (Pica American European Fig birds. considered cycle double; hearts host hosts infections lineages original strains survival using weight (represented Antibodies Birds Emerg Europe. Immune Infect Medicine [pii]. abundant border-color border-width circulating clinical d.p.i., described different draftWriting important infection. isolated lower migratory pathogens significant solid; susceptibility vector viremia virus, wild {font-style {font-weight (A) (WNV) ./eid. ./vbz.. Borne Culex Detection Flaviviruses: Health Investigación Magpies MonacoF, Mosquitoes North Organisms SaviniG, Southern Vector Zoonotic accession analysis assay. bold brains courier; data differences em; end equivalents euthanized experiment feeding life line magpie, negative no. oral oropharyngeal pica) plaque play positive post previously pt;} rates respectively. results sciences susceptible virus. weighed


ACT police appeal for information to find missing man Damian Brown
ACT police have appealed for information to help find a man who has been missing for more than a month.
Damian Brown, 46, was last seen in the Woden area on October 17.
Mr Brown has been described as Caucasian, about 180 centimetres tall, with short brown hair and a slim build.
He also has a distinctive skull tattoo on his inner-left forearm.
While photos released by ACT police show Mr Brown with long hair, an ACT police spokesman said police believe he has cut his hair since the photos were taken.
Mr Brown's family and police said they held concerns for his welfare and have called for help from the public to help find him.
Anyone with information on Mr Brown's whereabouts has been urged to contact ACT police on 131 444.


You can alter the appearance of the calendar in several ways:
| cell_border | boolean | Set a cell-border around the calendar itself, the days-of-week header and the individual days. Otherwise only a line is displayed. |
|---|---|---|
| today | boolean | Display today with a special badge. |
| show_days | boolean | Show the days-of-week header. |
| weekstartson | integer | Start the week on Sunday (0) or Monday (1). |
| nav_icon | object | Override 'prev' and/or 'next' icon html |
override other styling elements with your own css.
Font Awesome was added to this page to show an alternative icon example:
<link href="//netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.min.css" rel="stylesheet">


naive_reg()
is a way to generate a specification of an NAIVE or SNAIVE model
before fitting and allows the model to be created using
different packages.
naive_reg(mode = "regression", id = NULL, seasonal_period = NULL)
| mode | A single character string for the type of model. The only possible value for this model is "regression". |
|---|---|
| id | An optional quoted column name (e.g. "id") for identifying multiple time series (i.e. panel data). |
| seasonal_period | SNAIVE only. A seasonal frequency. Uses "auto" by default. A character phrase of "auto" or time-based phrase of "2 weeks" can be used if a date or date-time variable is provided. See Fit Details below. |
The data given to the function are not saved and are only used
to determine the mode of the model. For naive_reg()
, the
mode will always be "regression".
The model can be created using the fit()
function using the
following engines:
"naive" (default) - Performs a NAIVE forecast
"snaive" - Performs a Seasonal NAIVE forecast
naive (default engine)
The engine uses naive_fit_impl()
The NAIVE implementation uses the last observation and forecasts this value forward.
The id
can be used to distinguish multiple time series contained in
the data
The seasonal_period
is not used but provided for consistency with the SNAIVE
implementation
snaive (default engine)
The engine uses snaive_fit_impl()
The SNAIVE implementation uses the last seasonal series in the data and forecasts this sequence of observations forward
The id
can be used to distinguish multiple time series contained in
the data
The seasonal_period
is used to determine how far back to define the repeated
series. This can be a numeric value (e.g. 28) or a period (e.g. "1 month")
Date and Date-Time Variable
It's a requirement to have a date or date-time variable as a predictor.
The fit()
interface accepts date and date-time features and handles them internally.
ID features (Multiple Time Series, Panel Data)
The id
parameter is populated using the fit()
or fit_xy()
function:
ID Example: Suppose you have 3 features:
y
(target)
date
(time stamp),
series_id
(a unique identifer that identifies each time series in your data).
The series_id
can be passed to the naive_reg()
using
fit()
:
naive_reg(id = "series_id")
specifes that the series_id
column should be used
to identify each time series.
fit(y ~ date + series_id)
will pass series_id
on to the underlying
naive or snaive functions.
Seasonal Period Specification (snaive)
The period can be non-seasonal (seasonal_period = 1 or "none"
) or
yearly seasonal (e.g. For monthly time stamps, seasonal_period = 12
, seasonal_period = "12 months"
, or seasonal_period = "yearly"
).
There are 3 ways to specify:
seasonal_period = "auto"
: A seasonal period is selected based on the periodicity of the data (e.g. 12 if monthly)
seasonal_period = 12
: A numeric frequency. For example, 12 is common for monthly data
seasonal_period = "1 year"
: A time-based phrase. For example, "1 year" would convert to 12 for monthly data.
External Regressors (Xregs)
These models are univariate. No xregs are used in the modeling process.
library(dplyr) library(parsnip) library(rsample) library(timetk) library(modeltime) # Data m750 <- m4_monthly %>% filter(id == "M750") m750#> # A tibble: 306 × 3 #> id date value #> <fct> <date> <dbl> #> 1 M750 1990-01-01 6370 #> 2 M750 1990-02-01 6430 #> 3 M750 1990-03-01 6520 #> 4 M750 1990-04-01 6580 #> 5 M750 1990-05-01 6620 #> 6 M750 1990-06-01 6690 #> 7 M750 1990-07-01 6000 #> 8 M750 1990-08-01 5450 #> 9 M750 1990-09-01 6480 #> 10 M750 1990-10-01 6820 #> # … with 296 more rows# Split Data 80/20 splits <- initial_time_split(m750, prop = 0.8) # ---- NAIVE ---- # Model Spec model_spec <- naive_reg() %>% set_engine("naive") # Fit Spec model_fit <- model_spec %>% fit(log(value) ~ date, data = training(splits)) model_fit#> parsnip model object #> #> Fit time: 9ms #> NAIVE #> -------- #> Model: #> # A tibble: 1 × 2 #> date value #> <date> <dbl> #> 1 2010-04-01 9.29# ---- SEASONAL NAIVE ---- # Model Spec model_spec <- naive_reg( id = "id", seasonal_period = 12 ) %>% set_engine("snaive") # Fit Spec model_fit <- model_spec %>% fit(log(value) ~ date + id, data = training(splits)) model_fit#> parsnip model object #> #> Fit time: 13ms #> SNAIVE [12] #> -------- #> Model: #> # A tibble: 12 × 3 #> id date value #> <fct> <date> <dbl> #> 1 M750 2009-05-01 9.27 #> 2 M750 2009-06-01 9.27 #> 3 M750 2009-07-01 9.15 #> 4 M750 2009-08-01 9.19 #> 5 M750 2009-09-01 9.18 #> 6 M750 2009-10-01 9.25 #> 7 M750 2009-11-01 9.26 #> 8 M750 2009-12-01 9.27 #> 9 M750 2010-01-01 9.26 #> 10 M750 2010-02-01 9.26 #> 11 M750 2010-03-01 9.29 #> 12 M750 2010-04-01 9.29


Hello World API documentation version 1.0
https://helloworld.service.hmrc.gov.uk/
Overview
Add overview documentation here
Versioning
When an API changes in a way that is backwards-incompatible, we increase the version number of the API. See our reference guide for more on versioning.
Errors
We use standard HTTP status codes to show whether an API request succeeded or not. They are usually in the range:
- 200 to 299 if it succeeded, including code 202 if it was accepted by an API that needs to wait for further action
- 400 to 499 if it failed because of a client error by your application
- 500 to 599 if it failed because of an error on our server
Errors specific to each API are shown in the Endpoints section, under Response. See our reference guide for more on errors.
/insert/context
This endpoint allows a user to see an example endpoint.


It keeps your content up to date.
On every device you use.
Send unlimited messages to iPhone, iPad,
iPod touch, or Mac. From your Mac.
Mail, messages, reminders, alerts, and more.
See what’s new with you. All in one place.
Post to Facebook, Twitter, Flickr, and Vimeo.
Right from the app you’re in.
Facebook integration coming this fall.


Types in nCompiler
must be static. These include nClass
fields and nFunction
variables. To accomplish static typing, the programmer must declare types of arguments, return objects, and Cpublic (compilable) fields in an nClass
. The same variable cannot be used for more than one type.
These represent three core types of scalar and hence elements of non-scalars (vectors, matrices, arrays).
Note that in R, “numeric” sometimes means “double or integer” [e.g., is.numeric
] and sometimes means “double” [e.g. as.numeric
]. In nCompiler
, “numeric” means “double”.
There are several ways to declare these three core types. We use numeric as an example:
numericScalar()
numericVector()
numericMatrix()
numericArray(nDim = 3)
## nCompiler will also provides some alternatives and ways to
## control sizes and values in type declarations.
In these formats, the “numeric
” prefix can be replaced with “integer
” or “logical
”.
Say we want to do compiled vector addition:
library(nCompiler)
addVectors <- nFunction(
fun <- function(x, y) {
ans <- x + y
return(ans)
},
argTypes = list(x = 'numericVector()',
y = 'numericVector()'),
returnType = 'numericVector()'
)
# We could compile like this:
# test <- nCompile(addVectors)
When using character-string type declarations, the ()
is optional if no arguments are needed. Simply 'numericVector'
would work above.
As an alternative, types can be declared directly in code. The following is an equivalent way to write addVectors
:
addVectors <- nFunction(
fun <- function(x = numericVector(),
y = numericVector()) {
ans <- x + y
return(ans)
returnType(numericVector())
})
nCompiler also provides backward-compatibility support for nimble-style type declarations such as double(1)
for a numeric vector.
nimble
).nimble
).In nimble
, arguments are passed by value in uncompiled execution and by reference in compiled execution. This is internally inconsistent, and the compiled behavior is efficient but not R-like.
In nCompiler
, we aim to support consistent type behavior and let the user declare what they need. Three options are:
X
. X
could be resized in the called function.X[2:5, 3:6]
.Note that pass-by-reference is desirable for efficient C++, and after all a goal of C++ is efficiency. However, it is very un-R-like. To achieve consistent uncompiled and compiled behavior for debugging purposes, we programmatically modify the R function body.
Currently, a system for passing entire objects by reference in both uncompiled (R) and compiled (C++) code has been implemented. (It remains to implement pass-by-reference semantics when calling C++ from R.)
There are two ways to declare pass-by-reference: the refArgs
argument, and wrapping the type declaration in ref()
.
Note that this represents un-R-like behavior and has been implemented to support matching uncompiled and compiled behavior.
library(nCompiler)
f1 <- nFunction(
fun = function(x = 'numericVector',
y = 'numericVector') {
x <- x + 1
ans <- x + y
return(ans)
},
refArgs = 'x',
returnType = 'numericVector'
)
x <- 1:3
f1(x, 11:13)
## [1] 13 15 17
x # x was modified by f1, because it was passed by reference
## [1] 2 3 4
To see pass-by-reference work in compiled code, we need a second function to call the first.
f2 <- nFunction(
fun = function(x = 'numericVector',
y = 'numericVector') {
f1(x, y) # We are not interested in the returned value.
return(x) # We are interested in seeing that x was modified.
},
returnType = 'numericVector'
)
compiled <- nCompile(f2, f1)
x <- 1:3
compiled$f2(x, 11:3) # We see the modified x returned.
## [1] 2 3 4
nCompiler supports the use of many Rcpp types. Rcpp’s types are designed for easy integration with R objects, and they include types like DataFrame
, List
, and S4
, as well as a variety of typed matrices and vectors.
In nCompiler, these types are prefixed with Rcpp, such as RcppDataFrame
and RcppNumericMatrix
. This is to differentiate between certain Rcpp and nCompiler types with similar names and functions but which are fundamentally different types under the hood.
The following Rcpp types are supported:
| Rcpp.Type | Equivalent nCompiler type |
|---|---|
| NumericVector | RcppNumericVector |
| NumericMatrix | RcppNumericMatrix |
| IntegerVector | RcppIntegerVector |
| IntegerMatrix | RcppIntegerMatrix |
| LogicalVector | RcppLogicalVector |
| LogicalMatrix | RcppLogicalMatrix |
| CharacterVector | RcppCharacterVector |
| CharacterMatrix | RcppCharacterMatrix |
| ComplexVector | RcppComplexVector |
| ComplexMatrix | RcppComplexMatrix |
| DateVector | RcppDateVector |
| DatetimeVector | RcppDatetimeVector |
| RawVector | RcppRawVector |
| DataFrame | RcppDataFrame |
| S4 | RcppS4 |
| Function | RcppFunction |
nCompiler also supports the direct use of the following RcppEigen types:
| RcppEigen.Type | Equivalent nCompiler type |
|---|---|
| MatrixXd | RcppEigenMatrixXd |
| MatrixXi | RcppEigenMatrixXi |
| MatrixXcd | RcppEigenMatrixXcd |
| VectorXd | RcppEigenVectorXd |
| VectorXi | RcppEigenVectorXi |
| VectorXcd | RcppEigenVectorXcd |
The following example shows how one might want an Rcpp type in an nFunction.
nf <- nFunction(
fun = function(x = "RcppIntegerVector",
y = 'RcppIntegerVector') {
cppLiteral(
'ans = x + y;
return ans;',
types = list(ans = "RcppIntegerVector()")
)
returnType("RcppIntegerVector()")
}
)
nfC <- nCompile_nFunction(nf)
x <- c(1, 2)
y <- c(100, 200)
nfC(x, y)
## [1] 101 202
You may also want an nClass with a public field of an Rcpp type, for example:
nc <- nClass(
classname = "demo_RcppNumericMatrix",
Cpublic = list(
x = "RcppNumericMatrix",
invert_x = nFunction(fun = function(new_x = "RcppNumericMatrix") {
x <<- new_x
cppLiteral("return transpose(x);")
}, returnType = "RcppNumericMatrix()"
)
)
)
ncC <- nCompile(nc)
my_nc <- ncC$new()
test_x1 <- matrix(c(1000, 100, 0, 0), nrow = 2)
my_nc$invert_x(test_x1)
## [,1] [,2]
## [1,] 1000 100
## [2,] 0 0
my_nc$x
## [,1] [,2]
## [1,] 1000 0
## [2,] 100 0
class(my_nc$x) # Return type corresponds to that of a numeric matrix in R
## [1] "matrix" "array"


Across: 1. Osbert turns out flashing light (6) 4. In two seconds, tablet falls out (6) 9. Liquid Gold carried back by horse (4) 10. Initially Carol's Mum mixed cockney woman's cake with Penny in a sash (10) 11. In Lent I like finding food (6) 12. Orders us to Burt for tirade! (8) 13. Most powerful man, for example, reels from street to street (9) 15. Old jokers could be at this end (4) 16. Shades reported as belonging to TV's Scully (4) 17. I bore a gin for native (9) 21. Bury Mr Doonican in gap? (8) 22. Must he always win? (6) 24. Speaker swallows a drink so he can get things moving (10) 25. Hit around the middle (4) 26. Bob tried out the worst! (6) 27. Chops always carried by boat? (6) Down: 1. Snake quietly let out after directions (7) 2. Is girth correct? (5) 3. Support record accumulation (7) 5. I, out of pity, embrace Len more than enough (6) 6. Having babies may be hard work! (9) 7. Part of changes in us especially affect our cranial cavities (7) 8. Is it Limbo I spy? This cannot be true! (13) 14. Too keen to be finished and sort of agree! (9) 16. German comes to dread losing a ton (7) 18. Dream of one in love (7) 19. Idiots on pot could be unwholesome! (7) 20. Meetings in smooth back street (6) 23. 16 down skilled in making rope (5)


UpdateWorld [anim_speed#]
Parameters:
| anim_speed# (optional) - a master control for animation speed. Defaults to 1. |
Description:
| Animates all entities in the world, and performs collision checking. The optional anim_speed# parameter allows you affect the animation speed of all entities at once. A value of 1 will animate entities at their usual animation speed, a value of 2 will animate entities at double their animation speed, and so on. For best results use this command once per main loop, just before calling RenderWorld. |
| None. |


{% include 'nav.html' %}
With the spread of COVID-19 many things have swapped over to the digital world. Have swapped their main operations to online retail. However, an area that is lacking in this department is the agriculture sector of Kuwait. With the aid of this project, we would be able to provide farmers of Kuwait access to a website that would allow them to check weather patterns to better know upcoming weather. Allow them a place to show their farm and products to be able to better network and find people interested in their farm and their products. We believe that pushing farmers to the digital age would only add benefits to their work.
Worked mainly on the back-end using Python Language in addition to the Flask framework and SQLite3 to handle the databases
Assisted on Back-End and Front-End. Lead in Research & Report Editing.
Worked mainly on the front-end using HTML, CSS and BOOTSTRAP, in order to ensure easy portablity on all devices


Construct a new OPRF instance
the libsodium wrappers sumo instance desired (version > 0.7.6)
Promise that is resolved when the libsodium wrappers have been loaded It is unsafe to use OPRF before this promise is resolved
Exposes sodium wrappers sumo
Adds pointA and pointB together on an elliptic curve and returns the sum
sum of pointA and pointB
Decodes elliptic curve point from a string
the encoding of a point
the point
Encodes a point representation to a string with either 'ASCII' or 'UTF-8' encoding
the point to encode
a compact string representing the point
Generates a random number uniform in [1, ORDER OF CURVE).
Hash to point
array of numbers representing a point on the curve ed25519
Returns whether the given point exists on the elliptic curve
true if the point is a valid point, false otherwise
Hashes input as a point on an elliptic curve and applies a random mask to it
a masked point and the mask
Masks a point with a random mask and returns both masked point and mask
a masked point and the mask
Salts a point using a key as a scalar
a point (usually masked)
a scalar (usually PRF key)
salted point
Subtracts pointB from pointA and returns the difference
difference between pointA and pointB
Applies the multiplicative inverse of the mask to the masked point
a masked point
the original mask that was applied to the masked point
the resulting unmasked value
Generated using TypeDoc
Main entry point for using slim OPRF.
This is not exposed directly in node.js or bundled OPRF. Look at OPRF instead, which has identical API.