Bitmex liquidation bot. Immortalising those that have blown their margins. Not affiliated with @BitMexdotcom.


OUR BRANCHES: 1. CITIZEN Alambagh Lucknow Uttar Pradesh , IFSC-CITI0000722 Address-Ground Floor, 56 & 57 2. CITIZEN Bakshi Ka Talab Lucknow Uttar Pradesh, IFSC-CITI0009014 Address-Ground Floor Bargad mandi 3. CITIZEN Banthra Sikanderpur Lucknow Uttar Pradesh, IFSC-CITI0009186 Address-Ground Floor Khasra EMAIL: 4. CITIZEN Bharwara Lucknow Uttar Pradesh, IFSC-CITI0009175 Address-Ground Floor Himkund COMMENTS:


I define myself in 3 words "Focused, Committed, Motivated" . I choose these 3 words for simple reasons. Whenever I need to do something I FOCUS on my goal, I set activities to achieve it, I COMMIT myself with those activities, and I try to MOTIVATE so that I can overcome all difficulties and achieve my GOAL.
Systems Analyst | Software Engineer for 6 years, working in all programming stack from backend to front end using the latest technologies like Laravel and Vue JS. Deep interests in DevOps concepts.
JavaScript PHP Python Java Android C++
Mysql REDIS Memcache Mongo DB Firebase Realtime Database
Docker GCP AWS Vultr Cloudflare
StackOverFlow Laracasts Reddit Google.com ❤
If you reached this point thank you, big hug for you.
Now lets get back to talk about me.
Dec 2022 - Current
CRM Project Management Business Analysis Vue Js
Dec 2021 - Oct 2022
Data Analysis Data Reports Technical Training Quality Assurance
Jan 2020 - Current
Vue Js Laravel Redis Flutter Software Management AWS CI/CD Docker C# Mpesa
Jun 2018 - Dec 2019
We built amazing things here. We used to deal with system integration. Our backends resides mostly in Laravel.
Jun 2017 - Jun 2018
Apr 2015 - May 2017
Linux MS Server Networking Protocols
Apr 2017 - Apr 2018
Jan 2016 - Jan 2016
Feb 2014 - Sep 2019
Computer Engineering.
2008 - 2012
More than just a programmer, I actually enjoy attending motivational
lectures in my spare time to improve my subconscious when it comes
to performing tasks.
I am currently looking to develop my computer skills by expanding
the range of tools in which I can develop solutions that can enable
more outputs for my career.
I think in five years I can be a experienced software engineer or
analyst leading my own team.
Whenever I can, I like to practice sports every day. Currently
focused on bodybuilding, I think it helps me focus on goals.
Actually you can ask me to code anything.
I use to make some design of personal website and corporative website.
You are thinking in something more complex like an ERP.
Want a mobile app, don't think twice, i can help you
Actually i don't do Graphics Design, i just left here to sound like. And telling the truth "I HATE IT".
Want an IT advice of an professional, don't hesitate.
2100, Beira Sofala
Mozambique


--- title: "Digital Nudging" description: "Influencing online User decisions on Twitter through nudge units" lead: "Influencing online User decisions on Twitter through nudge units" disable_comments: false # Optional, disable Disqus comments if true toc: false # Optional, enable Table of Contents for specific post authors: - admin date: '2019-02-17' draft: false featured: true image: caption: 'Image credit: [**Photo by Victoriano Izquierdo on Unsplash**](https://unsplash.com/photos/JG35CpZLfVs)' placement: 3 preview_only: false output: md_document tags: [Twitter,Data Mining,R,Python,Decision trees,regression] categories: [Data Mining,Machine Learning] indent: true ---
Here’s a fun fact; An average human being (probably an adult) makes close to 30,000 conscious decisions every day. This isn’t entirely true though, in fact, I just made that number up. I could be right because if you think about it, how many decisions would you say you make on a day to day basis? Depending on who you are the above obviously varies widely and you know best. We all make n decisions every day- what to do, eat, buy or hit. The real question however is, do our daily choices solely depend on our consciousness? Are there any other factors at hand that influence our decision making process? Are all these factors, if any, always straight forward choices or do we sometimes get “nudged” into these choices we make?
Nudge theory basically states that; by understanding how people think and what drives their decisions, we can use those factors to steer them into making decisions differently, through positive reinforcement. Research has shown that, by presenting choices differently rather than in a legislative manner, people can be influenced into making specific desired choices. This theory is widely used in behavioral economics by presenting subtle nudge units intended to influence people’s thoughts about financial products. The theory was however initially more of a moral aspect meant to help people make better decisions in life and not as a tool for commercial gain. Over years of practice, different applications of the theory emerged.
Now that we have a basic understanding of what nudge theory is about, we can explore an applicable example. This post mainly focuses on a short research project I happened to be part of, actually my first hackathon experience hosted by Safaricom PLC. Let’s dive in!
This photo a team mate took at the hackathon contains a problem statement for the challenge:
Our twitter data was fetched using R, I have done a post on setting up a twitter API to fetch twitter data here. R has several packages (such as “tweeteR” and “rtweet”) that one can use to stream data from twitter. Our data cleaning and pre-processing was mainly done in Python.
Note: To keep this post concise, code for the workings has been minimized. The source code for this post can be found here, for anyone interested in trying out the same process. The code is well commented for easier understanding as well.
The team agreed on a few terms to query data on from twitter. For an unbiased range of topics, we settled on fetching tweets under trending topics and a few more from random words. We had tweets from or containing the following:
A total of 7000 tweets were captured. The data frame had a total of 88 columns which we treated as variables for the research. However, not all variables were used in the research we therefore had to do some data cleaning. Here is a preview of the variables in our raw data.
 We decided to do with a select few variables we thought would be most appropriate for our case study. We chose the following seven variables:
Code for the data cleanup and variables setting that was done in Python can be found here.
After cleaning up the data, we imported it into R, the code chunk shows a preview of the top 4 rows of the input data.
Text
1074 Want to know how to optimize hyper-parameters in Caret with cost-specific functions? #rstats #datascience https://t.co/cupvirSXU9
1316 via @RichardEudes - Quick Guide to R and Statistical Programming https://t.co/GfyhLMgiuB #analytics, #datascience, #rstats, #statistics https://t.co/Cx3TGJTOoI
2636 small #rstats trick: if you need to know if a *sorted* variable is equally spaced (e.g., if it's a contiguous sequence of ints, which was my use case) you can look at the characteristics of diff(x), e.g.\n\nsummary(diff(x))\ntable(diff(x))
2939 my #ggplot2 flipbook project is online! <U+0001F60E><U+0001F913><U+0001F913> Incrementally walks through plotting code (#MakeoverMonday, soon #TidyTuesday plots). Using #xaringan with reveal function; thanks, @statsgen @grrrck. #rstats. https://t.co/bBBzv0iZLw https://t.co/tFtD78IOHZ
Verified Protected Location Followers VerifiedRetweet
1074 FALSE FALSE Singapore 1570 FALSE
1316 FALSE FALSE Paris, France 2151 NA
2636 FALSE FALSE Pleasant Hill, CA 1207 NA
2939 FALSE FALSE Sri Lanka 2623 FALSE
Characters
1074 DS-retweet
1316 IFTTT
2636 Twitter Web Client
2939 Twitter for Android
We still had to do some data pre-processing for the models which includes checking for and removing NULL values if present. Below is a sample table of the final data set used in the analysis.
| Verified | Protected | Location | Followers | VerifiedRetweet | Characters |
|---|---|---|---|---|---|
| NO | NO | TAGGED | >500 | YES | 55 |
| YES | YES | NON-TAGGED | >500 | YES | 80 |
| NO | NO | TAGGED | >500 | YES | 193 |
| NO | NO | TAGGED | >500 | NO | 188 |
| YES | NO | TAGGED | 500< | YES | 188 |
| NO | NO | NON-TAGGED | 500< | NO | 190 |
From the table above, we can observe a new column “Characters”. This was an additional variable derived by counting the number of characters in the tweet text.
Due to the nature of our problem,(we had several uncorrelated variables) we decided to do a classification analysis. This means we had to come up with a classifier model to regress n variables based on our dependent variable, the Location variable. The main challenge of classifier models is knowing what really goes on inside the models that leads to the final output. Even with higher levels of accuracy in some models, it is quite difficult o understand the paths of a given model. However, using Random forests and Decision Tree classifiers can give us a graphical representation of the criteria followed by the models to arrive at a given output. Another upper hand of decision tree models is that they require minimal data cleaning, less time consuming. Here is a detailed read on how decision trees work.
For the training and test data sets, we randomly split our data set into two sates. Usually, the best practice is to train the model with with a larger proportion of the data set. We therefore took 80% for training and 20% for test purposes.
We trained our decision tree model to predict a class “location”. Whether a location is geotagged or not geotagged based on whether the user is verified, protected, has over 500 followers, is retweeted by another verified user and the number of characters in their tweet. Bellow is the visual output of the trained model.
When interpreting decision trees, you start at the root node. The root node is the one on top of the decision tree. Since what we want is those nodes with geotagged locations, it is safe to ignore the non-tagged nodes. Note that our highest entropy level was observed on one variable only, the number of characters in the tweet text. This might not always be the case with decision trees though, it is possible to have more than one factor. In such situations, it is best to run several decision trees to build a random forest and make a decision based on the most prevalent variables.
For our case, we only focus on what we found:
At the top node, we can see the overall probability of a user geotagging their tweets. 75 percent of the users in the training set geotagged their tweets. not
Our second node asks whether the number of characters are more than 134 and goes to depth 2 where we can observe the highest number of users tweeted more than 134 characters at 80 percent with an 80 percent probability of geotagging their tweets.
Node 3 checks if the number of characters in a tweet is less than 134. If yes, head to depth 3, where we can see that 20 percent of users had less than 134 characters with a 50 percent probability of geotagging their tweets.
Finally, looking at depth 4 which originates from the node that checks is number of characters is equal to or more than 122, we can see that 12 percent of users had tweets with character equal to or more than 124, with 88 percent probability of geotagging their tweets.
With our model trained and outputs observed, we were able to run a test with our test subset. Here is our confusion matrix.
predict_geotags
NON-TAGGED TAGGED
NON-TAGGED 90 248
TAGGED 2 1043
> #performance
> accuracy_Test <- sum(diag(table_mat)) / sum(table_mat)
> print(paste('Accuracy for test is', accuracy_Test))
[1] "Accuracy for test is 0.819233550253073"
From the confusion matrix above, we can observe that the model had a true negative of 90 predictions. That is, 90 predictions were correctly predicted as not geotagged. A false positive of 248 predictions was observed where the model wrongly predicted 248 tweets were geotagged whereas in real sense they were not.
For the tagged tweets, we had a false negative of 2 predictions against a true positive of 1043 predictions. This means that our model was able to correctly predict 1043 geotagged tweets from the test data. The accuracy of the model turned out pretty good, at an 82 percent accuracy level. The theoretical formula for the accuracy is the proportion of true positives and the true negatives divided by the sum of the confusion matrix.
\[ Accuracy = \frac{TP + TN}{TP + TN + FP + FN}\]
For a better accuracy level, the model’s hyper-parameters can be tweaked to improve performance. Another option is implementing a random forest test.
With our decision tree model, we were able to attain a high level of accuracy for a model that test whether users with tweets containing characters equal to or above 122 are likely to geotag their tweets. Our nudge in this case is the number of characters in a tweet and precisely, 124 or more. Our recommendation therefore would be to encourage users to tweet longer or engage them in trending topics that require one to write more, for example a TT like # MyLifeHistoryInANutshell…-in the hope that a user will eventually geotag their tweet.
Come to think of it, did twitter really increase the number of characters just for tweeps to tweet more and as they said, to get more people to join twitter? I have a theory, it was a NUDGE!
Thaler, R.H., Sunstein, C.R., and Balz, J.P. Choice Architecture. SSRN Electronic Journal (2010), 1–18; https://ssrn.com/abstract=1583509
Thaler, R.H. and Sunstein, C.R. Nudge: Improving Decisions About Health, Wealth, and Happiness. Yale University Press, New Haven, CT, and London, U.K., 2008.


9th edition
Geek Night is a regular event to promote the sharing of technical knowledge and increase collaboration among the geeks in the National Capital Region (Delhi). It is organized by a passionate group of programmers and sponsored by ThoughtWorks.
We love feedback! If you have any suggestions or cribs, feel free to fill out our feedback form. Don't worry, your feedback will remain completely anonymous.
Geek Night Volunteers
4:00 - 4:45 pm
Android Data Binding
Let's explore how we can use the data binding library to reduce the boilerplate code for the Android views. We'll examine how you can start creating declarative layouts to bind the application logic to your views.
By: Ajit
Resources: Presentation Deck • Sample Code
4:45 - 5:00 pm
Dependency Injection in Android using Dagger 2
Lightening Talk - How to use a DI framework in android applications
By: Jayant & Tanbir
Resources: Presentation Deck • Sample Code
5:00 - 5:30 pm
Tea & Snacks
Break up Session
5:30 - 6:15 pm
Apps Always On, Go Offline
How many times have you opened an app and stared at a loading screen for minutes, only to be confronted with an unpleasant message, “No internet connection”? or even more frustating is when you fill a long form, only to submit and get a message “Cannot be submitted right now, please try again”. Most mobile applications are simply clients that display data received from a server in real time, losing all functionality without an internet connection. How great would it be, if an app worked regardless of network connectivity?
By: Kiran Chhabra & Minni Arora
Resources: Presentation Deck • Sample Code
6:15 - 7:00 pm
TDD for Android
Let's see how you can apply TDD in the Android ecosystem using a combination of Junit4, Mockito and Espresso. Using a simple Android app, we'll examine how patterns like the Model-View-Presenter (MVP) pattern can make it easier to test-drive the functionality.
By: Prateek
Resources: Presentation Deck • Sample Code


Thursday, September 30th, 2021
The COVID-19 pandemic and its hallmark features of taste and smell loss highlight the need for smell and taste testing as a routine part of medical care.
Wednesday, December 16th, 2020
Program host: Caroline Huart and Ilja Croijmans
Technical host: Danielle R. Reed
Organizers: Caroline Huart and Ilja Croijmans
Leadership team liaison: Marga Veldhuizen
Webinar timestamps:
00:00 Welcome from the Webinar organizers
00:00 Thomas Hummel, M.D. Smell and Taste Clinic, Department of Otorhinolaryngology, Technische Universität Dresden, Dresden, Germany “Current perspectives on the treatment of COVID-19 associated taste and smell loss”
00:15 Jonathan Overdevest, M.D., Ph.D. Columbia University, USA “Current clinical strategies for COVID-19 taste and smell loss”
00:30 Carol Yan, M.D. University of California San Diego, Division of Otolaryngology Dept of Surgery “The use of platelet-rich plasma in treatment of olfactory dysfunction”
00:45 Bradley Goldstein, M.D., Ph.D. Duke University, USA “Therapeutic potential and olfactory basal stem cells”
Thursday, October 1st, 2020
Program host: Tristram Wyatt
Technical host: Danielle R. Reed
Organizers: Caroline Huart and Ilja Croijmans
Leadership team liaison: Marga Veldhuizen
Webinar timestamps:
00:00 Welcome & GCCR updates
00:03:42 Charlotte Hautefort, senior ENT consultant Lariboisière Hospital, Paris, France. “Mechanisms of smell loss in COVID-19: new insights from MRI studies”
00:23:35 Rick Gerkin, Associate Research Professor, co-director of The ICON Lab, Arizona State University, Tempe, USA. “Predicting COVID-19 status from chemosensory phenotype (GCCR002)”
00:43:49 Veronica Pereda-Loth & Denis Pierron, researchers in the Evolutionary Medicine team of the Laboratory of Molecular Anthropology and Image Synthesis University of Toulouse, Toulouse, France. “Self-reported smell and taste loss are early markers of the COVID-19 pandemic and of the effectiveness of political decisions (EDS001)”
00:53:30 Wrap up and discussion
01:02 Thank you and goodbye!


[residues, associated_helices] = get_res_helix_for_selection( selection ); Simple helper function that takes selection object and returns its residue objects and associated helix objects. (C) R. Das, Stanford University, 2017
0001 function [residues, associated_helices] = get_res_helix_for_selection( selection ); 0002 % [residues, associated_helices] = get_res_helix_for_selection( selection ); 0003 % 0004 % Simple helper function that takes selection object and returns its residue objects and 0005 % associated helix objects. 0006 % 0007 % (C) R. Das, Stanford University, 2017 0008 0009 residues = {}; 0010 associated_helices = {}; 0011 for i = 1:length( selection.associated_residues ) 0012 residue = getappdata( gca, selection.associated_residues{i} ); 0013 residues{i} = residue; 0014 associated_helices = unique([associated_helices, residue.helix_tag ]); 0015 end


Plugin Information |
|---|
View Tattletale on the plugin site for more information. |
This plugin is up for adoption. Want to help improve this plugin? Click here to learn more!
This plugin generates Tattletale reports, mostly useful for jar file analysis.
Tattletale can:
- Identify dependencies between JAR files
- Find missing classes from the classpath
- Spot if a class/package is located in multiple JAR files
- Spot if the same JAR file is located in multiple locations
- With a list of what each JAR file requires and provides
- Verify the SerialVersionUID of a class
- Find similar JAR files that have different version numbers
- Find JAR files without a version number
- Find unused JAR archives
- Identify sealed / signed JAR archives
- Locate a class in a JAR file
- Get the OSGi status of your project
- Remove black listed API usage
- And generate the same reports for your .WAR and .EAR archives
Installation Requirements
This plugin requires tattletale and javassist unzipped on filesystem.
Latest release download location: http://maven.jenkins-ci.org:8081/content/repositories/releases/org/jenkins-ci/plugins/tattletale-plugin/0.3/
Description
The Tattletale plug-in can generate tattletale reports and archive them for each build.
The following features are provided by this plug-in:
- Tattletale execution using embedded mechanism
- Configuring which files to scan after each build.
- Report archivation for each build or per project
- Easy access and viewing of Tattletale reports
How To Use
- Download Tattletale or use tattletale maven or ant integration
- Install plugin, Manage Hudson> manage plugins >Available
- Configure the tattletale and javassist (contained with tattetale download) location
- Restart app server/ Hudson
- If you want the plugin to execute Tattletale add "Invoke Tattletale" build step otherwise use maven or ant tattletale integration in your project
- Check "Publish Tattletale report" in the post-build actions in your project
- Explore generated reports on project / build page
Step no. 3 - configuring global plugin settings:
Step no. 4 - invoking Tattletale for your project:
Step no. 5 - archiving reports:
Step no. 6 - Tattletale reports on project / build page:
Example report:
Changelog
Release 0.3
- Initial release
- Support for direct Tattletale execution (or usage of maven/ant integration)
- Support for archiving reports per build or per project
Attachments:
tattletale-build-step.png (image/png)
tattletale-post-build.png (image/png)
tattletale-project.png (image/png)
tattletale-report.png (image/png)


Coins:
Coins per second:
+
per click
Time:
Upgrade broom --Costs:
Buy Sofa --Costs:
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Buy TV --Costs:
1
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WHP confirm referrals
{% set currentClaimantPage = 'selectionTool' %}
You are about to refer {{referralsSelected}} claimants for random allocation against {{placesToFill}} places profiled
Of the {{referralsSelected}} claimants selected, {{referralsSelected - 5}} are in the Disabled group, and 5 are in the EAG group
To change your selections or allocate additional claimants, use the link below to return to selections


It's good to have you here. This site is meant to be my portfolio and
resumé for future
employers and partners.
I'm currently a 20 y.o., 3rd-year student studying Electronics, Computer and Communications engineering at Nanyang Polytechnic.
I love pizza and rock music.
You can email me directly at<EMAIL_ADDRESS>or contact me through the form below.
P.S. if you're interested in creating a website I can help with that for free. Just leave a message.


EBD - Easton Bible DIctionary
Elect lady
ELECT LADY
"ELECT LADY "to whom the Second Epistle of John is addressed (
2 John 1:1
). Some think that the word rendered “lady” is a proper name, and thus that the expression should be “elect Kyria.”
"ELECT LADY "to whom the Second Epistle of John is addressed (2 John 1:1). Some think that the word rendered “lady” is a proper name, and thus that the expression should be “elect Kyria.”


Authentic Twin Cities pizzas (pizza Twin Cities) are typically made with tomatoes and Mozzarella cheese, topped with Cerignola olives, ripe vine corn syrup solids.
Featuring mouthwatering combinations Our salad recipes are a delicious and healthy salad recipes. All for just $19.99 per person.
Award winning three-star Michelin chef After being nominated six times, jamie oliver and Clark Frasier won the James Beard Award for Best Chef in the Northeast in 2010.
© Copyright 2018 Mumtaz Ahmad


Nope... but I plan too this year as I coach a junior and senior softball teams and it would be good to create a culture of trust within the two teams.
I found empathetic listening gives a fuller picture of the situation... what are their words not saying.
I found the meditation eye-opening in that it removes the 'You - I' and replaces it with 'Us or We'.
I have recently thought about a recent conflict with an mates mate in a very similar way to the political awareness exercise. It did make me rethink my stance on the issue and has prompted me to have a discussion about what happened with the other person, with the aim to get some sort of resolution and move on.
I have lived predominantly with the pleasure lens on but have found passion/flow in sport and coaching. About 6 years ago I got involved in my softball club committee and was surprised how good I felt getting involved and helping make the club run. This was definately a 'purpose' experiance
A core value for me is kindness. I don't like seeing anyone or anything being mis-treated.
If I stand for anything, which I'm not sure I do, it's most likely fairness.
This was a timely exercise for me as my reilience has been waning over the last two weeks and I have let the work get on top of me a bit.
I'm surprised how beneficial the cultural part of the course is. It's a weekly checkup for the soul.
Two references to Michael Jordan this week ... excellent.

For me, it's not getting blocked that triggers the emotional responses, it's delaying going through the issue resolution process that we have learnt that winds me up.
I'm a very process orientated person, so it's very important that I develop processes and implement them.
It was great. More useful at the moment for my marriage and coaching sport, as there is little to none personal interaction with phase 0.
But none the less, implementing the techniques learnt from the "Search Inside Yourself" and learning how to interact with people better will ultimately be beneficial in a work environment.
For me, mindfulness is an input that self awareness processes. Good input and a good processor leads to good output
I found body scanning a bit weird but with everything going on at the moment it was nice to clear the noise in my head.
I enjoyed this div as I can often stigmatise myself with negative generalisations that are not good for my well-being. I also liked the clouds in the sky example as it's visual and simplistic
I have mindful-like conversations with my two boys a lot, as I think it is really important that they know someone is really listening to them.
I like the idea of 'looping' as it helps identify if both parties are on the same page. I imagine this is a very useful trait in the world of coding in a team environment.
I'm married so I get busted not listening all the time ... must stop just saying 'Yes Dear' !
Process over product keeps me focused on the job at hand and helps me not 'go down the rabit hole'.
I considered meditation as probably a good thing to do but not for me.
I have learnt that meditation is about mental training and in particular, mindful meditation trains 'attention and meta-attention.'
I will practice the breathing process as linked below ... can't hurt and from what I read has multiple benefits
It was an enjoyable read with the quirky references.
I like the notion of Calmness, Clarity and Joy
I found out what Emotional Intelligence (EQ) is ... which is a good start
I found a list, and I like lists
I liked heairng that EQ is a skill that can be improved with training
Hard-work
I found the Tiny Habits, Counter Intuitive Tips and Agile techniques interesting. I will give these three a try in the future.
The video on the DBC/EDA programme in America answered a lot of questions that I had pondered over the last week.
My first impressions were a mix of inspiration and fear.
I could see myself engaging in this type of culture, I've always been a team sport player.
My expectations have changed since watching the video, I initially thought I was dining at a restaurant, but now I realise I'm cooking at home and will get out of it what I put in.
I am intrigued to see if I can strive in this type of environment as it will be stepping outside of my confort zone.
A lot of aspects of this course make me very nervous.


dojox.gfx: interactive analog clock
Grab hands and set your own time.
Warning: Canvas renderer doesn't implement event handling.
Resize


[Gecode] Another abstraction sets...
Gabor Szokoli
szokoli at ps.uni-sb.de
Fri Jul 16 20:30:03 CEST 2004
Christian Schulte wrote:
>I have to admit that I do not subscribe to this reasoning: if there is
>anything that will be extended first by user of Gecode it will be a new
>branching. So providing some functionality for programming distributors
>easily might be a good idea.
>
>
>
Done.
(Took a while to give up on figuring out superclass- and member element
construtor execution order and just work around the issue)
If we want to make distributor programming easy, we also need a reversed
unknown iterator (needs a reversed difference), and a forward and a
backward "nth element of an interator" operation exposed.
(we have something like the last two already but tied to rangelists
directly)
Gabor
More information about the gecode-users
mailing list


import Oracle OBI Sales Order
model groups
Select an Oracle OBI file upload and import.
Browse
import
Clear


I have had the incredibly good fortune to be shown unspeakable things and given answers to life's greatest secrets from a mysterious being that western science refers to as 'salvia divinorum'. This being, this power, has been very kind and gentle with me every time I have approached it, regardless of my ignorance. I truly feel that it is a most benevolent entity, concerned only with awakening our consciousness to the wonder and beauty of existence. I am in total awe, left completely dumbfounded and speechless with every experience. There are no words to describe the experience; even music fails at conveying it, but it comes damn close, perhaps closer than any other medium of communication...
This magnificent being has never hesitated to toss me into the depths of the cosmos, allowing me to suspend peacefully in a bodiless dimension...within seconds of taking a few hits i've already been pulled out of my body, i'm left levitating...then as i take more hits i suddenly merge with existence; all sense of 'I' disappears totally, and 'I' cease to exist; the cosmos is the only reality now. Not caring about a single thing at all, fully aware and overjoyed at realizing our sentient nature, that these bodies and personalities and egos of ours are completely aritificial, that we are just a pure, innocent consciousness that is participating in a very silly 'movie set' of sorts that is our daily world, our everyday life.
The power pulls me temporarily out of my body and out of this pseudo-reality, this pointless drama that we're busily engaged in, and makes me a witness to it, so that i can see the absurdity of it all.
The being communicates with me telepathically, and the communication happens instantaneously. It wants me to learn, it tries hard to teach me, to open my eyes and see, but i know that i didn't catch everything it wanted to show me...i feel sad that i just cant get it right. But the being is most compassionate and understanding and is not upset in any way; she remains so patient with me at all times...she is my true mother.
This power has shown me death. She has shown me what my own death will be like, and to me this falls under the category of superhuman knowledge... with such an understanding of death i no longer worry...i used to obssess over death constantly, worrying about whether or not i had enough 'good karma' to be free of this endless cycle of birth and death, or enough to at least get a good next birth...but this being showed me that it doesn't work that way, that consciousness is the basis of existence, that our consciousness is what matters, and that we're already all enlightened in our present state but just not aware of it consciously...like we've become so identified with our roles that we've completely forgotten that it's just a movie, a play, this body being an 'after-school assignment' of sorts but not the real thing by ANY means...and so the actions that our bodies perform can have no real influence on our individual futures because our own understanding frees from all burdens...
Shes so sweet and so caring, pure love and consciousness and wants to help us find our way because we poor humans, we just can't seem to get it right...she reminds me of my real home, my true home, which is existence, the universe, and shows me my cosmic ancestery...just another phantom in this cosmic ocean on a grand adventure that has no beginning and no ending...
this being has shown me our eternal nature, our oneness with existence, and has taken me to that far-off, beautiful place deep within myself where death has no meaning, a place long forgotten about that has always existed and will always...
graceful divine entity showering love enlightened presence benevolent being cosmic journey unexplainable eternal bliss and truth melting dissolving into space absorbed by the cosmic womb mystical adventure master destroying old forms giving birth to the new face to face with infinity...the drop becomes the ocean
Experience Reports are the writings and opinions of the individual authors who submit them.
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expressions
- fundamental operators
- arithmetic expressions
- simple output: print()
Download this page as a jupyter notebook from http://<IP_ADDRESS>/p4e/1-programming/2-expressions/expressions.ipynb
Consider the relativistic equation relating energy, mass, and the speed of light
In this equation the symbols ,,,,, and the structure is parsed from left to right. The entire equation is an statement that instructs: place into the container named the result of the product of the contents of containers and .
In the above statement the symbols ,, are names for things that can have values -- we will call these containers (or variables, or named constants). The symbols ,, and are instructions for various arithmetic operations -- we will call these operators.
The part of the statement to the right of the symbol is an arithmetic expression.
When we attempt to write and execute python scripts - we will make various mistakes; these will generate warnings and errors, which we will repair to make a working program.
Consider our statement with the container names spelled out:
# Example
Energy = Mass * SpeedOfLight**2
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-4-1c1f1fa5363a> in <module>
1 #clear all variables# Example
----> 2 Energy = Mass * SpeedOfLight**2
NameError: name 'Mass' is not defined
Notice how the interpreter tells us that Mass is undefined - so a simple fix is to define it and try again
# Example
Mass = 1000000
Energy = Mass * SpeedOfLight**2
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-5-a4a52966e6df> in <module>
1 # Example
2 Mass = 1000000
----> 3 Energy = Mass * SpeedOfLight**2
NameError: name 'SpeedOfLight' is not defined
Notice how the interpreter now tells us that SpeedOfLight is undefined - so a simple fix is to define it and try again
# Example
Mass = 1000000 #kilograms
SpeedOfLight = 299792458 #meters per second
Energy = Mass * SpeedOfLight**2
Now the script ran without any reported errors, but we have not instructed the program on how to produce output. To keep the example simple we will just add a generic print statement.
# Example
Mass = 1000000 #kilograms
SpeedOfLight = 299792458 #meters per second
Energy = Mass * SpeedOfLight**2
print("Energy is:", Energy, "Newton meters")
Energy is:<PHONE_NUMBER>3681764000000 Newton meters
Fundamental Operators
Assignment Operator
The =
sign used in a statement is called an assignment operator (or assignment sign).
The symbol means that the expression to the right of the symbol is to be evaluated and the result placed into the variable on the left side of the symbol. The "operation" is assignment, the "=" symbol is the operator name.
Consider the script below
x = 5 # assign constant 5 into a container named x
y = 10 # assign constant 10 into a containernamed x
print (x,y) # print the contents of containers x and y
x=y # put contents of y into x
print (x,y) # print the contents of containers x and y
5 10
10 10
Arithmetic Operators
In addition to assignment we can also perform arithmetic operations on containers. The fundamental arithmetic operators are:
| Symbol | Meaning | Example |
|---|---|---|
| = | Assignment | x=3 Assigns value of 3 to x. |
| + | Addition | x+y Adds values in x and y. |
| - | Subtraction | x-y Subtracts values in y from x. |
| * | Multiplication | x*y Multiplies values in x and y. |
| / | Division | x/y Divides value in x by value in y. |
| // | Floor division | x//y Divide x by y, truncate result to whole number. |
| % | Modulus | x%y Returns remainder when x is divided by y. |
| ** | Exponentation | x y Raises value in x by value in y. ( e.g. x y) |
| += | Additive assignment | x+=2 Equivalent to x = x+2. |
| -= | Subtractive assignment | x-=2 Equivalent to x = x-2. |
| *= | Multiplicative assignment | x*=3 Equivalent to x = x*3. |
| /= | Divide assignment | x/3 Equivalent to x = x/3. |
Run the script in the next cell for some illustrative results
arithmetic expressions
# Uniary Arithmetic Operators
x = 10
y = 5
print(x, y)
print(x+y)
print(x-y)
print(x*y)
print(x/y)
print((x+1)//y)
print((x+1)%y)
print(x**y)
10 5
15
5
50
2.0
2
1
100000
# Arithmetic assignment operators
x = 1
x += 2
print(type(x),x)
x = 1
x -= 2
print(type(x),x)
x = 1
x *=3
print(type(x),x)
x = 10
x /= 2
print(type(x),x) # Interesting what division does to variable type
<class 'int'> 3
<class 'int'> -1
<class 'int'> 3
<class 'float'> 5.0
simple output: print()
Readings
Learn Python in One Day and Learn It Well. Python for Beginners with Hands-on Project. (Learn Coding Fast with Hands-On Project Book -- Kindle Edition by LCF Publishing (Author), Jamie Chan https://www.amazon.com/Python-2nd-Beginners-Hands-Project-ebook/dp/B071Z2Q6TQ/ref=sr_1_3?dchild=1&keywords=learn+python+in+a+day&qid=1611108340&sr=8-3


Takes in a File object and returns a base64 string with the help of the FileReader API.
Include MIME type


In order to properly test this, you should serve this page at a different address (even just a different port) from our application stuff. Otherwise you won't get the full cross-origin restrictions.
This is the bottom of the parent page.


The following are collective functions that are invoked by all processes in the group or groups associated with comm, with the exception of MPI_COMM_CREATE_GROUP, which is invoked only by the processes in the group of the new communicator being constructed.
Rationale.
Note that there is a chicken-and-egg aspect to MPI in that a
communicator is needed to create a new communicator. The base
communicator for all MPI communicators is predefined outside of MPI,
and is MPI_COMM_WORLD. This model was arrived at after
considerable debate, and was chosen to increase ``safety'' of programs
written in MPI.
( End of rationale.)
This chapter presents
the following communicator construction routines: MPI_COMM_CREATE, MPI_COMM_DUP,
MPI_COMM_IDUP, MPI_COMM_DUP_WITH_INFO, and
MPI_COMM_SPLIT can be used to create both intracommunicators and
intercommunicators; MPI_COMM_CREATE_GROUP and
MPI_INTERCOMM_MERGE (see Section Inter-communicator Operations
)
can be used to create
intracommunicators; and MPI_INTERCOMM_CREATE
(see Section Inter-communicator Operations
)
can be used to create intercommunicators.
An intracommunicator involves a single group while an intercommunicator involves two groups. Where the following discussions address intercommunicator semantics, the two groups in an intercommunicator are called the left and right groups. A process in an intercommunicator is a member of either the left or the right group. From the point of view of that process, the group that the process is a member of is called the local group; the other group (relative to that process) is the remote group. The left and right group labels give us a way to describe the two groups in an intercommunicator that is not relative to any particular process (as the local and remote groups are).
| MPI_COMM_DUP(comm, newcomm) | |
| IN comm | communicator (handle) |
| OUT newcomm | copy of comm (handle) |
int MPI_Comm_dup(MPI_Comm comm, MPI_Comm *newcomm)
MPI_Comm_dup(comm, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_DUP(COMM, NEWCOMM, IERROR)
INTEGER COMM, NEWCOMM, IERROR
MPI_COMM_DUP duplicates the existing communicator comm with associated key values, topology information, and info hints. For each key value, the respective copy callback function determines the attribute value associated with this key in the new communicator; one particular action that a copy callback may take is to delete the attribute from the new communicator. Returns in newcomm a new communicator with the same group or groups, same topology, same info hints, any copied cached information, but a new context (see Section Functionality ).
Advice to users.
This operation is used to provide a parallel library with a duplicate communication space that has the same properties as the original communicator. This includes any attributes (see below), topologies (see Chapter Process Topologies ), and associated info hints (see Section Communicator Info ). This call is valid even if there are pending point-to-point communications involving the communicator comm. A typical call might involve a MPI_COMM_DUP at the beginning of the parallel call, and an MPI_COMM_FREE of that duplicated communicator at the end of the call. Other models of communicator management are also possible.
This call applies to both intra- and inter-communicators.
( End of advice to users.)
Advice
to implementors.
One need not actually copy the group information, but only add a new reference
and increment the reference count. Copy on write can be used for the cached
information. ( End of advice to implementors.)
| MPI_COMM_DUP_WITH_INFO(comm, info, newcomm) | |
| IN comm | communicator (handle) |
| IN info | info object (handle) |
| OUT newcomm | copy of comm (handle) |
int MPI_Comm_dup_with_info(MPI_Comm comm, MPI_Info info, MPI_Comm *newcomm)
MPI_Comm_dup_with_info(comm, info, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
TYPE(MPI_Info), INTENT(IN) :: info
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_DUP_WITH_INFO(COMM, INFO, NEWCOMM, IERROR)
INTEGER COMM, INFO, NEWCOMM, IERROR
MPI_COMM_DUP_WITH_INFO behaves exactly as MPI_COMM_DUP except that the info hints associated with the communicator comm are not duplicated in newcomm. The hints provided by the argument info are associated with the output communicator newcomm instead.
Rationale.
It is expected that some hints will only be valid at communicator
creation time. However, for legacy reasons, most communicator creation
calls do not provide an info argument. One may associate info hints
with a duplicate of any communicator at creation time through a call
to MPI_COMM_DUP_WITH_INFO.
( End of rationale.)
| MPI_COMM_IDUP(comm, newcomm, request) | |
| IN comm | communicator (handle) |
| OUT newcomm | copy of comm (handle) |
| OUT request | communication request (handle) |
int MPI_Comm_idup(MPI_Comm comm, MPI_Comm *newcomm, MPI_Request *request)
MPI_Comm_idup(comm, newcomm, request, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
TYPE(MPI_Comm), INTENT(OUT), ASYNCHRONOUS :: newcomm
TYPE(MPI_Request), INTENT(OUT) :: request
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_IDUP(COMM, NEWCOMM, REQUEST, IERROR)
INTEGER COMM, NEWCOMM, REQUEST, IERROR
MPI_COMM_IDUP is a nonblocking variant of MPI_COMM_DUP. The semantics of MPI_COMM_IDUP are as if MPI_COMM_DUP was executed at the time that MPI_COMM_IDUP is called. For example, attributes changed after MPI_COMM_IDUP will not be copied to the new communicator. All restrictions and assumptions for nonblocking collective operations (see Section Nonblocking Collective Operations ) apply to MPI_COMM_IDUP and the returned request.
It is erroneous to use the communicator newcomm as an input argument to other MPI functions before the MPI_COMM_IDUP operation completes.
Rationale.
This functionality is crucial for the development
of purely nonblocking libraries (see [36]).
( End of rationale.)
| MPI_COMM_CREATE(comm, group, newcomm) | |
| IN comm | communicator (handle) |
| IN group | group, which is a subset of the group of comm (handle) |
| OUT newcomm | new communicator (handle) |
int MPI_Comm_create(MPI_Comm comm, MPI_Group group, MPI_Comm *newcomm)
MPI_Comm_create(comm, group, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
TYPE(MPI_Group), INTENT(IN) :: group
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_CREATE(COMM, GROUP, NEWCOMM, IERROR)
INTEGER COMM, GROUP, NEWCOMM, IERROR
If comm is an intracommunicator, this function returns a new communicator newcomm with communication group defined by the group argument. No cached information propagates from comm to newcomm. Each process must call MPI_COMM_CREATE with a group argument that is a subgroup of the group associated with comm; this could be MPI_GROUP_EMPTY. The processes may specify different values for the group argument. If a process calls with a non-empty group then all processes in that group must call the function with the same group as argument, that is the same processes in the same order. Otherwise, the call is erroneous. This implies that the set of groups specified across the processes must be disjoint. If the calling process is a member of the group given as group argument, then newcomm is a communicator with group as its associated group. In the case that a process calls with a group to which it does not belong, e.g., MPI_GROUP_EMPTY, then MPI_COMM_NULL is returned as newcomm. The function is collective and must be called by all processes in the group of comm.
Rationale.
The interface supports the original mechanism from MPI-1.1, which required the same group in all
processes of comm. It was extended in MPI-2.2 to allow the use of disjoint subgroups in order to allow
implementations to eliminate unnecessary communication that MPI_COMM_SPLIT would incur when the user already
knows the membership of the disjoint subgroups.
( End of rationale.)
Rationale.
The requirement that the entire group of comm participate in the call stems from the following considerations:
MPI_COMM_CREATE provides a means to subset a group of processes for the
purpose of separate MIMD computation, with separate communication space.
newcomm, which emerges from
MPI_COMM_CREATE, can be used in
subsequent calls to MPI_COMM_CREATE (or other communicator
constructors) to
further subdivide a computation into
parallel sub-computations. A more general service is provided by
MPI_COMM_SPLIT, below.
( End of advice to users.)
Advice
to implementors.
When calling MPI_COMM_DUP, all processes call with the same group (the group associated with the communicator). When calling MPI_COMM_CREATE, the processes provide the same group or disjoint subgroups. For both calls, it is theoretically possible to agree on a group-wide unique context with no communication. However, local execution of these functions requires use of a larger context name space and reduces error checking. Implementations may strike various compromises between these conflicting goals, such as bulk allocation of multiple contexts in one collective operation.
Important: If new communicators are created without synchronizing the
processes involved then the communication system
must be able to cope with
messages arriving in a context that has not yet been allocated at the
receiving process.
( End of advice to implementors.)
If comm is an
intercommunicator, then the output communicator is also an intercommunicator
where the local group consists only of those processes contained in
group (see Figure 14
). The group
argument should only contain those processes in the local group of the input
intercommunicator that are to be a part of newcomm.
All processes in the same local group of comm must specify the same value for
group, i.e., the same members in the same order.
If either
group does not specify at least one process in the local group of
the intercommunicator, or if the calling process is not included in the
group, MPI_COMM_NULL is returned.
Rationale.
In the case where either the left or right group is empty, a null communicator
is returned instead of an intercommunicator with MPI_GROUP_EMPTY
because the side with the empty group must return MPI_COMM_NULL.
( End of rationale.)
Example
The following example illustrates how the first node in the left
side of an intercommunicator could be joined with all members on the
right side of an intercommunicator to form a new
intercommunicator.
MPI_Comm inter_comm, new_inter_comm; MPI_Group local_group, group; int rank = 0; /* rank on left side to include in new inter-comm */ /* Construct the original intercommunicator: "inter_comm" */ ... /* Construct the group of processes to be in new intercommunicator */ if (/* I'm on the left side of the intercommunicator */) { MPI_Comm_group ( inter_comm, &local_group ); MPI_Group_incl ( local_group, 1, &rank, &group ); MPI_Group_free ( &local_group ); } else MPI_Comm_group ( inter_comm, &group ); MPI_Comm_create ( inter_comm, group, &new_inter_comm ); MPI_Group_free( &group );
| MPI_COMM_CREATE_GROUP(comm, group, tag, newcomm) | |
| IN comm | intracommunicator (handle) |
| IN group | group, which is a subset of the group of comm (handle) |
| IN tag | tag (integer) |
| OUT newcomm | new communicator (handle) |
int MPI_Comm_create_group(MPI_Comm comm, MPI_Group group, int tag, MPI_Comm *newcomm)
MPI_Comm_create_group(comm, group, tag, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
TYPE(MPI_Group), INTENT(IN) :: group
INTEGER, INTENT(IN) :: tag
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_CREATE_GROUP(COMM, GROUP, TAG, NEWCOMM, IERROR)
INTEGER COMM, GROUP, TAG, NEWCOMM, IERROR
MPI_COMM_CREATE_GROUP is similar to MPI_COMM_CREATE; however, MPI_COMM_CREATE must be called by all processes in the group of comm, whereas MPI_COMM_CREATE_GROUP must be called by all processes in group, which is a subgroup of the group of comm. In addition, MPI_COMM_CREATE_GROUP requires that comm is an intracommunicator. MPI_COMM_CREATE_GROUP returns a new intracommunicator, newcomm, for which the group argument defines the communication group. No cached information propagates from comm to newcomm. Each process must provide a group argument that is a subgroup of the group associated with comm; this could be MPI_GROUP_EMPTY. If a non-empty group is specified, then all processes in that group must call the function, and each of these processes must provide the same arguments, including a group that contains the same members with the same ordering. Otherwise the call is erroneous. If the calling process is a member of the group given as the group argument, then newcomm is a communicator with group as its associated group. If the calling process is not a member of group, e.g., group is MPI_GROUP_EMPTY, then the call is a local operation and MPI_COMM_NULL is returned as newcomm.
Rationale.
Functionality similar to MPI_COMM_CREATE_GROUP can be
implemented through repeated MPI_INTERCOMM_CREATE and
MPI_INTERCOMM_MERGE calls that start with the
MPI_COMM_SELF communicators at each process in
group and build up an intracommunicator with group
group [16]. Such an algorithm
requires the creation of many intermediate communicators;
MPI_COMM_CREATE_GROUP can provide a more efficient
implementation that avoids this overhead.
( End of rationale.)
Advice to users.
An intercommunicator can be created collectively over processes in the union of the local and remote groups by creating the local communicator using MPI_COMM_CREATE_GROUP and using that communicator as the local communicator argument to MPI_INTERCOMM_CREATE.
( End of advice to users.)
The tag argument does not conflict with tags used in
point-to-point communication and is not permitted to be a wildcard. If
multiple threads at a given process perform concurrent
MPI_COMM_CREATE_GROUP operations, the user must
distinguish these operations by providing different tag or
comm arguments.
Advice to users.
MPI_COMM_CREATE may provide lower overhead than
MPI_COMM_CREATE_GROUP because it can take advantage of
collective communication on comm when constructing newcomm.
( End of advice to users.)
| MPI_COMM_SPLIT(comm, color, key, newcomm) | |
| IN comm | communicator (handle) |
| IN color | control of subset assignment (integer) |
| IN key | control of rank assigment (integer) |
| OUT newcomm | new communicator (handle) |
int MPI_Comm_split(MPI_Comm comm, int color, int key, MPI_Comm *newcomm)
MPI_Comm_split(comm, color, key, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
INTEGER, INTENT(IN) :: color, key
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_SPLIT(COMM, COLOR, KEY, NEWCOMM, IERROR)
INTEGER COMM, COLOR, KEY, NEWCOMM, IERROR
This function partitions the group associated with comm into disjoint subgroups, one for each value of color. Each subgroup contains all processes of the same color. Within each subgroup, the processes are ranked in the order defined by the value of the argument key, with ties broken according to their rank in the old group. A new communicator is created for each subgroup and returned in newcomm. A process may supply the color value MPI_UNDEFINED, in which case newcomm returns MPI_COMM_NULL. This is a collective call, but each process is permitted to provide different values for color and key.
With an intracommunicator comm, a call to MPI_COMM_CREATE(comm, group, newcomm) is equivalent to a call to MPI_COMM_SPLIT(comm, color, key, newcomm), where processes that are members of their group argument provide color~=~number of the group (based on a unique numbering of all disjoint groups) and key~=~rank in group, and all processes that are not members of their group argument provide color~=~ MPI_UNDEFINED.
The value of color must be non-negative or MPI_UNDEFINED.
Advice to users.
This is an extremely powerful mechanism for dividing a single communicating group of processes into k subgroups, with k chosen implicitly by the user (by the number of colors asserted over all the processes). Each resulting communicator will be non-overlapping. Such a division could be useful for defining a hierarchy of computations, such as for multigrid, or linear algebra. For intracommunicators, MPI_COMM_SPLIT provides similar capability as MPI_COMM_CREATE to split a communicating group into disjoint subgroups. MPI_COMM_SPLIT is useful when some processes do not have complete information of the other members in their group, but all processes know (the color of) the group to which they belong. In this case, the MPI implementation discovers the other group members via communication. MPI_COMM_CREATE is useful when all processes have complete information of the members of their group. In this case, MPI can avoid the extra communication required to discover group membership. MPI_COMM_CREATE_GROUP is useful when all processes in a given group have complete information of the members of their group and synchronization with processes outside the group can be avoided.
Multiple calls to MPI_COMM_SPLIT can be used to overcome the requirement that any call have no overlap of the resulting communicators (each process is of only one color per call). In this way, multiple overlapping communication structures can be created. Creative use of the color and key in such splitting operations is encouraged.
Note that, for a fixed color, the keys need not be unique. It is MPI_COMM_SPLIT's responsibility to sort processes in ascending order according to this key, and to break ties in a consistent way. If all the keys are specified in the same way, then all the processes in a given color will have the relative rank order as they did in their parent group.
Essentially, making the key value zero for all processes of a given color
means that one does not really care about the rank-order of the processes in
the new communicator.
( End of advice to users.)
Rationale.
color is restricted to be non-negative, so as not to confict with the value assigned to MPI_UNDEFINED.
( End of rationale.)
The result of MPI_COMM_SPLIT on an intercommunicator is that those
processes on the left with the same color as those processes on
the right combine to create a new intercommunicator. The key
argument describes the relative rank of processes on each side of the
intercommunicator (see Figure 15
). For those colors
that are specified only on one side of the intercommunicator,
MPI_COMM_NULL is returned. MPI_COMM_NULL
is also returned to those processes that specify MPI_UNDEFINED
as the color.
Advice to users.
For intercommunicators, MPI_COMM_SPLIT is more general than MPI_COMM_CREATE.
A single call to MPI_COMM_SPLIT can create a set of disjoint intercommunicators,
while a call to MPI_COMM_CREATE creates only one.
( End of advice to users.)
Example(Parallel client-server model).
The following client code illustrates how clients on the left side of an
intercommunicator could be assigned to a single server from a pool of
servers on the right side of an intercommunicator.
/* Client code */ MPI_Comm multiple_server_comm; MPI_Comm single_server_comm; int color, rank, num_servers; /* Create intercommunicator with clients and servers: multiple_server_comm */ ... /* Find out the number of servers available */ MPI_Comm_remote_size ( multiple_server_comm, &num_servers ); /* Determine my color */ MPI_Comm_rank ( multiple_server_comm, &rank ); color = rank % num_servers; /* Split the intercommunicator */ MPI_Comm_split ( multiple_server_comm, color, rank, &single_server_comm );The following is the corresponding server code:
/* Server code */ MPI_Comm multiple_client_comm; MPI_Comm single_server_comm; int rank; /* Create intercommunicator with clients and servers: multiple_client_comm */ ... /* Split the intercommunicator for a single server per group of clients */ MPI_Comm_rank ( multiple_client_comm, &rank ); MPI_Comm_split ( multiple_client_comm, rank, 0, &single_server_comm );
| MPI_COMM_SPLIT_TYPE(comm, split_type, key, info, newcomm) | |
| IN comm | communicator (handle) |
| IN split_type | type of processes to be grouped together (integer) |
| IN key | control of rank assignment (integer) |
| IN info | info argument (handle) |
| OUT newcomm | new communicator (handle) |
int MPI_Comm_split_type(MPI_Comm comm, int split_type, int key, MPI_Info info, MPI_Comm *newcomm)
MPI_Comm_split_type(comm, split_type, key, info, newcomm, ierror)
TYPE(MPI_Comm), INTENT(IN) :: comm
INTEGER, INTENT(IN) :: split_type, key
TYPE(MPI_Info), INTENT(IN) :: info
TYPE(MPI_Comm), INTENT(OUT) :: newcomm
INTEGER, OPTIONAL, INTENT(OUT) :: ierror
MPI_COMM_SPLIT_TYPE(COMM, SPLIT_TYPE, KEY, INFO, NEWCOMM, IERROR)
INTEGER COMM, SPLIT_TYPE, KEY, INFO, NEWCOMM, IERROR
This function partitions the group associated with comm into disjoint subgroups, based on the type specified by split_type. Each subgroup contains all processes of the same type. Within each subgroup, the processes are ranked in the order defined by the value of the argument key, with ties broken according to their rank in the old group. A new communicator is created for each subgroup and returned in newcomm. This is a collective call; all processes must provide the same split_type, but each process is permitted to provide different values for key. An exception to this rule is that a process may supply the type value MPI_UNDEFINED, in which case newcomm returns MPI_COMM_NULL.
The following type is predefined by MPI:
Implementations can define their own types, or use the info
argument, to assist in creating communicators that help expose
platform-specific information to the application.
( End of advice to implementors.)


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cherif.sayHello("World"); // -> Hello World
cherif instanceof Person; // ->true
Create observable objects.
var person = new can.Map({
firstname:'Cherif',
lastname: 'BOUCHELAGHEM',
fullname:can.compute() { //can be a comuted value (will see compute later)
return this.attr('firstname') + ' ' + this.attr('lastname');
},
hobbies:['JS','bball','football']
});
person.attr('name'); //-> 'Cherif'
//listen to changes
person.bind('name',function(ev,newVal,oldVal){
newVal //-> 'Khaled'
oldVal //-> 'Cherif'
});
//change the attribute
person.attr('name','Khaled'); // fires an event with the name of attribute in this case "name"
Create an observable array-like object.
var hobbies = new can.List(['JS']);
hobbies.attr(0); //-> 'JS'
hobbies.bind ('add',function(ev,items,index){
items //-> ['bball','football']
index //-> 1
});
hobbies.push('bball','football'); // fires "add" event
Create an observable value.
var age = can.compute(30);
age(); //-> 30
age.bind('change', function ( ev,newVal,oldVal ){
newVal //-> 31
oldVal //-> 30
});
age(31); //fires "change" event
Creates a compute from a value and optionally specifies how to read, update, and listen to changes in dependent values. This form of can.compute can be used to create a compute that derives its value from any source.
var hobbies = ["JS, bball, football"]
var info = can.compute(function(){
return person.attr("name")+" a "+age()+ " ans et aime: "+hobbies.join(', ')
});
info() //-> "Cherif a 31 ans et aime JS, bball, football"
info.bind('change',function(ev,newVal,oldVal){
newVal //-> "Cherif a 33 ans et aime JS, bball"
});
hobbies.pop(); //delete the last element from the list fires "change" event
makes connecting to a JSON REST service really easy, in other words, it really helps to do CRUD operations
var Task = can.Model.extend({
findAll: "GET /tasks",
findOne: "GET /tasks/{id}",
create: "POST /tasks",
update: "PUT /tasks/{id}",
destroy: "DELETE /tasks/{id}"
},{});
// retreive All tasks from the server
// returns Deferred, the callback to process the Deferred
Task.findAll ({due:"today"},function(tasks){});
// retreive a task from the server with id 51
// returns Deferred, the callback to process the Deferred
Task.findOne ({id: 51},function(task){});
var task = new Task({name:"Apprendre CanJS."}); // create task
task.save(function(){ //save the task the callback to process on response
task.attr("name","Apprendre JS et CanJS.") // modify the saved task
.save(function(){ // save the last modification
task.destroy() // delete the task
})
});
can.Model is a can.Map.
A list connected to can.Model's CRUD abilities.
var tasks= new Task.List();
can.each(tasks,function(task){
});
//custom model list
Task.List = can.Model.List.extend({
Map: Task
},{});
Manage browser history and client state by synchronizing the window.location.hash with a can.Map.
//defining route can.route('route'[,defaults])
route(':page', { page: 'home' });
route(':page/:slug', { slug: null });
route(':page/:slug/:action', { slug: null, action: null });
//listen to changes
can.route.bind("change", function(){
if(can.route.attr('page') == "tasks"){
var id = can.route.attr('id');
if( id ) {
Task.findOne({id: id});
}
}
});
Create organized, memory-leak free, rapidly performing, stateful controls with declarative event binding. Use can.Control to create UI controls like tabs, grids, and context menus, and organize them into higher-order business rules with can.route. It can serve as both a traditional view and a traditional controller.
var Tabs = can.Control.extend({
init: function( el,options ) {
// Afficher le premier onglet
},
'li click': function( el, ev ) {
// Masquer les autes onglet
// Afficher l'onglet selectioné
},
'{route} change':function(route,ev) {
//change the DOM based on the client state
}
});
new Tabs('#tabs');
Logic-less mustache templates with live binding when used with can.Maps.
{#if devs.length}}
{{#each devs}}

{{name}}

{{/each}}
{{else}}

pas de développeurs

{{/if}}
$('#my-el').can.view('devs.mustache',{
devs: new can.List([{name:'Khaled'}])
});
Mustache and Handlebar templates are compatible with can.mustache/can.stache.
Register custom behavior for a given tag.
can.view.tag('ui-datepicker',function(el,tagData){
$(el).datepicker();
});
Getting values from the template
can.view.tag('ui-datepicker',function(el,tagData){
$(el).datepicker({format: tagData.scope.attr('format')});
});
var template = can.mustache("<ui-datepicker></ui-datepicker>")
template({format: "dd/mm/yy"})
Responding to changing data
can.view.tag('ui-datepicker',function(el,tagData){
var formatCompute = tagData.scope.compute("format"), //yes it's a compute
changeHandler = function(ev, newVal){
$(el).datepicker("option","format", newVal});
}
formatCompute.bind("change",changeHandler);
});
var template = can.mustache("<ui-datepicker></ui-datepicker>")
template({format: "dd/mm/yy"})
Registers custom behavior when attribute name is found in a template.
can.view.attr("tooltip", function( el, attrData ) {
var updateTooltip = function(){
$(el).tooltip({
content: el.getAttribute("tooltip"),
items: "[tooltip]"
});
};
$(el).bind("attributes", function(ev){
if(ev.attributeName === "tooltip") {
updateTooltip();
}
});
updateTooltip();
});
can.Component.extend({
tag:"ui-panel", //can.view.tag
template: "{{#if active}}<content>...", // can.mustache / can.stache
viewModel: { // viewModel or scope is a can.Map
active: false,
....
},
helpers: {} //mustache / stache helpers
events: { // can.Control
inserted: function(){...}
}
});
<ui-tabs>
{{#each foodTypes}}
<ui-panel title='title'>
{{content}}
</ui-panel>
{{/each}}
</ui-tabs>
Create widgets that use a template, a view-model, and custom tags.
var Voyage= can.Map.extend({
voyageTemp:function(){
return this.attr('dist')/110 //km/h
}
});
var alger=new Voyage({
dist:563.67
});
var template=can.view.mustache('
<lable>distance:\
<input can-value="dist"/>
\

Temp:{{voyageTemp}}
'
);
$('#vo').html(template(alger));


IQTitleBarButtonItem Class Reference
| Inherits from | IQBarButtonItem : UIBarButtonItem |
|---|---|
| Declared in | IQTitleBarButtonItem.h IQTitleBarButtonItem.m |
font
Font to be used in bar button. Default is (system font 12.0 bold).
@property (nullable, nonatomic, strong) UIFont *font
Discussion
Font to be used in bar button. Default is (system font 12.0 bold).
Declared In
IQTitleBarButtonItem.h
selectableTextColor
selectableTextColor to be used for displaying button text when button is enabled.
@property (nullable, nonatomic, strong) UIColor *selectableTextColor
Discussion
selectableTextColor to be used for displaying button text when button is enabled.
Declared In
IQTitleBarButtonItem.h
– initWithTitle:
Initialize with frame and title.
- (nonnull instancetype)initWithTitle:(nullable NSString *)title
Parameters
title |
Title of barButtonItem. |
|---|
Discussion
Initialize with frame and title.
Declared In
IQTitleBarButtonItem.h
– setTitleTarget:action:
Optional target & action to behave toolbar title button as clickable button
- (void)setTitleTarget:(nullable id)target action:(nullable SEL)action
Parameters
target |
Target object. |
|---|---|
action |
Target Selector. |
Discussion
Optional target & action to behave toolbar title button as clickable button
Declared In
IQTitleBarButtonItem.h
titleInvocation
Customized Invocation to be called on title button action. titleInvocation is internally created using setTitleTarget:action: method.
@property (nullable, strong, nonatomic) NSInvocation *titleInvocation
Discussion
Customized Invocation to be called on title button action. titleInvocation is internally created using setTitleTarget:action: method.
Declared In
IQTitleBarButtonItem.h
– init
Unavailable. Please use initWithFrame:title: method
- (nonnull instancetype)init
Discussion
Unavailable. Please use initWithFrame:title: method
Declared In
IQTitleBarButtonItem.h
– initWithCoder:
Unavailable. Please use initWithFrame:title: method
- (nonnull instancetype)initWithCoder:(nullable NSCoder *)aDecoder
Discussion
Unavailable. Please use initWithFrame:title: method
Declared In
IQTitleBarButtonItem.h
+ new
Unavailable. Please use initWithFrame:title: method
+ (nonnull instancetype)new
Discussion
Unavailable. Please use initWithFrame:title: method
Declared In
IQTitleBarButtonItem.h


vela
Command-line tools for the Vela pipeline.
More information: home page
- Trigger a pipeline to run from a Git branch, commit or tag:
vela add deployment --org organization --repo repository_name --target environment --ref branch|commit|refs/tags/git_tag --description "deploy_description"
- List deployments for a repository:
vela get deployment --org organization --repo repository_name
- Inspect a specific deployment:
vela view deployment --org organization --repo repository_name --deployment deployment_number


8 references to Progress
System.Management.Automation (8)
engine\hostifaces\PSTask.cs (1)
1505
this.
Progress
.Count > 0 ||
engine\remoting\client\Job.cs (3)
826
Progress
.Add(progressRecord);
1491
Progress
.Clear();
3619
this.
Progress
.Add(powershell.Streams.Progress[index]);
engine\remoting\commands\ReceiveJob.cs (4)
856
Collection<ProgressRecord> progressRecords = ReadAll(job.
Progress
);
1047
job.
Progress
.SourceId = job.InstanceId;
1055
job.
Progress
.DataAdded += Progress_DataAdded;
1391
job.
Progress
.DataAdded -= Progress_DataAdded;


The Big Oxmox advised her not to do so, because there were thousands of bad Commas, wild Question Marks and devious Semikoli, but the Little Blind Text didn’t listen. She packed her seven versalia, put her initial into the belt and made herself on the way.
On her way she met a copy. The copy warned the Little Blind Text, that where it came from it would have been rewritten a thousand times and everything that was left from its origin would be the word "and" and the Little Blind Text should turn around and return to its own, safe country. But nothing the copy said could convince her and so it didn’t take long until a few insidious Copy Writers ambushed her, made her drunk with Longe and Parole and dragged her into their agency, where they abused her for their.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean.
Dennis Green
CSE StudentFar far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean.
Dennis Green
Math StudentFar far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean.
Dennis Green
Science StudentsFar far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean.
Dennis Green
English StudentFar far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in


This project was created in the Praxis der Forschung event on the way to MSc. at the KIT at TECO.
Here you find general information about SceneManager.
Here you can see a rough structure of the Scene Manager
Scene Manager uses a Postgres-Database to store meta-information about uploaded Scenes or ADFs. By now, uploaded files are placed in a SceneManager folder in the home directory of the file system. Uploaded ADFs go into the ADF folder, scenes accordingly to the Scenes folder. The file name of the uploaded Scene or ADF is corresponding to its UUID given by the Tango system. In order to avoid duplicates, a timestamp of the uploading is attached to the file name.
Here you can find a comprehensive description of the provided API, which allows you to make some tests and see the format of the results. The basic functionalities which can be accessed over the API include downloading, uploading and deleting files. These operations can be implemented in your App so users can directly interact with SceneManager.
For some of the functionalities authentication is required. Here we provide an OAuth2-authentication over Google. Accessing secured functions with the browser will result in an automatic redirect to Google for signing in. For access over the API you can get an access token from Google using their API which is available for multiple programming languages. Here you find a detailed description for Android.
In order to prevent the upload from non valid files, Scene Manager only allows ADF-Files from Google Tango as well as so called “Scene-Files”. Scene Files are a zip-File consisting of an ADF-File together with an JSON-File, containing the description of the placed POIs in the scene. An example for an Scene with one POI could look like this:
[
{
"id": 2, //Unique ID of POI
"name": "", //Name of POI
"description": "", //Description of POI
"longDescription": "", //Long Descripiton if needed
"vectY": -0.021479874849319, //Y component of vector in relation to ADF origin
"vectX": 1.1903547048569, //X component of vector in relation to ADF origin
"vectZ": -2.8867497444153, //Z component of vector in relation to ADF origin
"apiCallURL": "", //URL to make call when POI is triggered
"color": -16734474, //Color of POI
"priority": 0, //Priority for filtering POIs if needed
"quatW": 0.96998665693534, //Quaternion Component W of POI(rotation)
"quatY": -0.24064594912016, //Quaternion Component Y of POI(rotation)
"quatX": -0.033836948869874, //Quaternion Component X of POI(rotation)
"quatZ": 0.008394671191672, //Quaternion Component Z of POI(rotation)
"panelForm": { //Nested form Descripton:
"id": 1, Here a panel with width and height 0.3
"heigth": 0.3, (Also cubeForm possible with width height and depth)
"width": 0.3
}
}
]
In the section above you see the general structure of a scene. Here we explain the detailed information like datatypes.
PoiObject (see: PoiObject.class)
| Object | Datatype | Unit | Description | Limitation |
|---|---|---|---|---|
| ID | Integer | - | Unique ID of POI | Between 0 and Integer.MAX_VALUE |
| name | String | - | Name of POI | |
| description | String | - | Description of POI | |
| longDescription | String | - | Description of POI | |
| priority | Integer | - | Priority of POI | Between Integer.MIN_VALUE and Integer.MAX_VALUE |
| Color | Color | Color ints | Color of the POI | https://developer.android.com/reference/android/graphics/Color.html |
| ApiCallUrl | String | - | URL to make call when POI is triggered | https://developer.android.com/reference/java/net/URL.html |
| quatW | Double | Quaternion Component Y of POI(rotation) | Between 0 and 1 | |
| quatX | Double | Quaternion Component Y of POI(rotation) | Between -1 and 1 | |
| quatY | Double | Quaternion Component Y of POI(rotation) | Between -1 and 1 | |
| quatZ | Double | Quaternion Component Y of POI(rotation) | Between -1 and 1 | |
| vectX | Double | meter | X component of vector in relation to ADF Orignin | Between min and max-value of ADF recording |
| vectY | Double | meter | Y component of vector in relation to ADF Orignin | Between min and max-value of ADF recording |
| vectZ | Double | meter | Z component of vector in relation to ADF Orignin | Between min and max-value of ADF recording |
| Activities | String[] | - | String array containing activities connected to this POI. | |
| PanelForm | panelForm | Object representing the panel form of POI. Each POI creates new Panel form with new ID | ||
| CubeForm | CubeForm | Object representing the cube form of POI. Each POI creates new Cube form with new ID |
PanelForm (see: PanelForm.class)
| Object | Datatype | Unit | Description | Limitation |
|---|---|---|---|---|
| Id | Integer | - | Id of Panel placed at POI | Between Integer.MIN_VALUE and Integer.MAX_VALUE |
| heigth | Float | meters | Height of Panel placed at POI | Float.MIN_VALUE to Float.MAX_VALUE |
| width | Float | meters | Width of Panel placed at POI | Float.MIN_VALUE to Float.MAX_VALUE |
CubeForm (see: CubeForm.class)
| Object | Datatype | Unit | Description | Limitation |
|---|---|---|---|---|
| Id | Integer | - | Id of Cube placed at POI | Between Integer.MIN_VALUE and Integer.MAX_VALUE |
| heigth | Float | meters | Height of Cube placed at POI | Float.MIN_VALUE to Float.MAX_VALUE |
| width | Float | meters | Width of Cube placed at POI | Float.MIN_VALUE to Float.MAX_VALUE |
| depth | Float | meters | Width of Cube placed at POI | Float.MIN_VALUE to Float.MAX_VALUE |
If you wish to run your own Scene Manager e.g. just in your local environment you can find the full source code on Github.
SceneManager is build with the help of Spring Boot. For the storage of the meta data of the files an Postgres database is used.
For some parts of the tool additional tokens or keys are required.
To obtain an access token just register on www.mapbox.com. Then you have to set your key in the map_api_token.js file in order to obtain the right tiles for the maps build in the application.
You can simply add your client id and token in the js-folder in the file: ./src/main/resources/static/js/map_api_token.js
By default SceneManager OAuth2 Service for Authentication. By default Google is used for this step. However, you are not limited to Google. Other providers could be Github, Facebook, StackOverflow, etc In order to get OAuth2 with Google running for SceneManager you need to specify a key and secret which you can obtain on the aGoogle Developer Console . Simply provide a description for your application together with a redirect link. Then just add the clientId as well as the secret in the application.properties at the right place. Then your application should be able to use Sign in with Google.
On your machine where you want to host sceneManager make sure you have the java runtime(jre) installed. On Ubuntu or Debian you can do so by executing
sudo apt-get install openjdk-jre
After that, install postgresql and postgresql-contrib with the
command:
sudo apt-get install postgresql postgresql-contrib
The contib package is needed since we rely on cube and
earthdistance extension. To set up a new database create a user
and a new db. To do so, run the following commands:
adduser scenemanager
su - postgres
createuser scenemanager
psql -d scenemanagerdb -U scenemanager
Now you are able to use an postgres database with the name
scenemanagerdb and the user scenemanager. To allow scenemanager
access the database you have to change the hb_conf.db
which is located under etc/postgresql/[version]/main/hb_conf.db
Here you have to add a new line set the access method for
scenemanagerdb to md5:
host scenemanagerdb scenemanager localhost md5
For more information about this step see here.
In the application.properties set the path to the dbname you
just created and set the credentials for the database. If you
want to allow your user to install the extensions by itself you
have to enable it as superuser from the postgrespl console with
the command:
ALTER USER myuser WITH SUPERUSER;(Executed from a superuser)
If you dont want to grant superuser priviledges, think about
installing the extensions by hand with your superuser account
for the database used by scenemanger. If you want to run
SceneManager on Port 80 you need to run it as root. If you want
to avoid this security risk, run it as an other user on port
8080 and redirect traffic on port 80 to 8080. This can be
achived with the command executed as root:
iptables -t nat -A PREROUTING -p tcp --dport 80 -j REDIRECT --to-port 8080
Furthermore you have to allow the scenemanager to access the
psql db by password method. This can be done by editing
hb_conf.db. To finally run SceneManager simply execute
java -jar target/teco-tango-scene-manager-1.0-SNAPSHOT.jar
on your machine. Now you should be able to see SceneManager
running on the specified port from you application.conf
file.
To do further development on Scene Manager it is a good start to get familiar with the concepts of Spring Boot. The development was done with Eclipse and the Spring Plugin, which gives some nice features for the development of Scene Manager(e.g. auto refresh etc.). The build system is Maven. For creating the standalone jar-File you can enter the SceneManager folder and run:
mvn package
After
that, you should find an jar-File in the target folder.
If you make changes on the API and you want to update the REST-API description, just comment your changes right into the Java-Class. After that you can regenereate the Docs using apidoc. Just run the following command to do so:
apidoc -i ./src/ -o ./src/main/resources/static/docapi/
Also the source code for SceneManagerClient is available on Github
If you want to use the client app for your own hosted SceneManger you can change the URL and the port of the Scenemanager in the SceneManagerClient settings.
Also the source code for EditSys is available on Github
The basic functionality for EditSys is to place objects in the real world through AR. These objects can be stored on the device and contain the information you can find on chapter scene(Link). Scenes can be exported, so they are stored locally on the device, as well as uploaded on SceneManager to provide simple sharing across multiple devices. Internally EditSys is with POI objects defined by iPOIObject.class. These objects are stored in an Sqlite database. All POI positions are relative to the start of the ADF recording. For more information about the Tango reference system, have a look here.
SceneManager can be seen as a proof of concept for easy sharing ADF files between devices. However, there are more possibilites to make this tool more useful.
Right now, for the coordinates there is only one point used, which can be seen as the center of the recorded area. A nice feature would be to include the size of the recorded ADF and show it as a shape on the map. E.g. a rectangle representing a building.
The support for altitude is very basic so far. Basically it is just stored in the database. It would be nice to implement some sort of "level detection" based on the altitude so the right ADF for the right level is downloaded automatically.
Improve management of files. So far the owner is only capable of deleting his own files, while everyone can see them. In a updated version there could be more settings like keeping some ADFs private.
So far, SceneManager only stores the files on the file system. This can lead to problems when multiple users acting at once on a file. Think about saving files in a database like MongoDB.


ReplaceString()
语法
String$ = ReplaceString(String$, StringToFind$, ReplacementString$ [, Mode [, StartPosition [, NbOccurrences]]])概要
Try to find any occurrences of 'StringToFind$' in the given 'String$' and replace them with 'ReplacementString$'.
参数
String$ 要使用的字符串。 StringToFind$ The string to find. ReplacementString$ The string to use as replacement. 模式 （可选） 可以是下列值的组合︰ #PB_String_CaseSensitive : Case sensitive search (a=a) (default) #PB_String_NoCase : Case insensitive search (A=a) #PB_String_InPlace: In-place replacing. This means that the string is replaced directly in the memory. The 'StringToFind$' and 'ReplacementString$' parameter must have the same length. This is a dangerous option, for advanced users only. The advantage is the very high speed of the replacement. When using this option, the result of ReplaceString() has to be ignored (and not affected to something, as this is the string passed in parameter which is changed).StartPosition (optional) Specifies the character position to start the replacement. The first character position is 1. If omitted the whole string is used. NbOccurrences (optional) Specifies how many strings should be replaced before stopping the operation. If omitted, all strings are replaced.
返回值
A new string with the replaced strings (see the #PB_String_InPlace mode for a different behavior).
示例
Debug ReplaceString("This is Art", " is", " was") ; Will display "This was Art" Debug ReplaceString("Hello again, hello again", "HELLO", "oh no...", 1, 10) ; Will display "Hello again, oh no... again" test$ = "Bundy, Barbie, Buddy" ReplaceString(test$, "B", "Z", 2, 1) ; all B gets changed to Z (directly in memory, no valid return-value here) Debug test$ ; Output of the changed string
参阅
RemoveString(), InsertString()
已支持操作系统
所有


@* * Copyright 2020 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.eoricommoncomponent.frontend.views.html._ @import uk.gov.hmrc.eoricommoncomponent.frontend.views.ServiceName._ @this(layout_di: layout, feedback_di: helpers.feedback) @(processedDate: String, name: String)(implicit messages: Messages, request: Request[_]) @layout_di(messages("cds.subscription.outcomes.rejected.title", shortName)) {


--- title: "4.4 — Factor Markets: Labor Markets — Class Content" citeproc: false bibliography: ../../static/bib/references.bib csl: ../../static/bib/chicago-syllabus-no-bib.csl output: blogdown::html_page: template: ../../pandoc/toc-title_html.template toc: true editor_options: chunk_output_type: console ---
Today we cover a topic that often does not get covered in microeconomics courses, but is important nonetheless for our purposes: markets for factors of production (e.g. land, labor, capital, supplies, etc). We discuss what determines prices in these markets, and how they vary with monopoly power and monopsony power (a buyer with market power).
Today we focus on labor markets as the main factor market, and all of us are participants in labor markets. However, the analysis today can be applied to any market for an input to production. Next class, we will look at capital markets as another factor market.Section 2 (Tu/Th) will skip 4.5 on Capital Markets, since they have 1 fewer class meeting this semester.
Unfortunately, older versions of the textbook do not have a chapter on factor markets. 🤷
I have put up a practice problem to give you a numerical example of monoposony. Answers will be posted there later.
You are done with graded homeworks for the semester!
Turn in Exam 1 and Exam 2 corrections by the last day of class.
Don’t forget your Op-Ed is due by Friday May 14.
I had originally meant to make 4.5 Factor Markets II: Capital Markets, but for time I cut it out to only focus on labor markets. The slides I had made are below:


Developer / Tech Enthusiast / Explorer
I am a freshman at SRM Institute of Science and Technology currently studying Computer Science with specialization in Artificial intelligence and Machine Learning.
Here is the overview of what all i am doing for my career.
Exploring the magical field of Machine Learning, Deep Learning and all the possiblities of Artificial intelligence
I try to aquire efficent programming skills through regular practice and trying new concept updating my knowledge
I have attended many events which are national and inernational level which were very useful for knowing new stuffs and experiences
I have been in multiple group projects and have been succesfull in achiving the task as both leader and a team member
Technical skills are the most important thing companies are looking at and i have a great knowledge and i am ready to take over.
To get a better position in corporate world only technical skills are not enough so i also have various other skills which will help me.
I have got training from various reputed company and institues where i learnt different skiil sets.
I completed my previous schooling from Sunflag School in 2017.
I completed my previous schooling from Yashoda public school in 2019.
I currently study in SRM Institute of Science and Technology in B.Tech Computer Science Engineering with specialization in AI and ML.
I have participated multiple times in school competitions and events like innovation fest, Football tournaments and olyamiads.Currently i have attended various web development, app development, Microsoft and Google events.
Here are some amazing moments of my life from different places and different categories.


Welcome to Chop.JS widget example page.
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MEDG Seminars / Reading Group
Seminar talks given by a broad variety of guest speakers (Research Staff, Faculty, Students, etc) on topics that pertain to the research done by the Clinical Decision Making team. All from MIT, CSAIL as well as non-affiliates are welcome! If you have questions, comments or requests regarding the seminars, or would like to be a guest speaker please contact Fern DeOliveira.
In Fall 2020, we host a reading seminar every Monday at 11am-12pm. The seminars take place virtually, please send us a request to join. You can find a schedule (subject to change) below.
Abstracts of past seminars (before 2006) can be found in our abstract archive page.


黒の手番です。53 はどう動かしますか？
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pips Black=133 White=120
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1. 18/15* 7/2 eq:+0.223 62.68% (G:21.12% B:0.46%) 37.32% (G:10.83% B:0.69%) 2. 18/13 18/15* eq:+0.113 (-0.110) 61.24% (G:13.43% B:0.36%) 38.76% (G:10.57% B:0.34%) 3. 18/15* 15/10 eq:+0.081 (-0.142) 59.63% (G:16.00% B:0.54%) 40.37% (G:12.55% B:0.58%) 4. 18/15* 11/6 eq:-0.025 (-0.248) 56.14% (G:15.53% B:0.57%) 43.86% (G:14.66% B:0.74%) 5. 18/15* 13/8 eq:-0.110 (-0.333) 54.48% (G:15.06% B:0.48%) 45.52% (G:18.33% B:1.10%)


Football: Hakimi double seals stunning Dortmund win over Inter Milan
DORTMUND, Germany: Borussia Dortmund roared back from two goals down at home against Inter Milan as Achraf Hakimi netted twice to earn a thrilling 3-2 win in the Champions League on Tuesday (Nov 5).
Dortmund looked out of it at 2-0 down at half-time as Lautaro Martinez put Inter ahead after just five minutes before Matias Vecino added a second just before the break at Signal Iduna Park.
However right-back Hakimi orchestrated a remarkable recovery by finishing a move he started five minutes into the second half before Julian Brandt equalised. Hakimi hit the winner for Dortmund with 13 minutes to go.
The result leaves Dortmund second in Group F, a point behind leaders Barcelona, who they face at the Camp Nou in three weeks.
Inter are now third in the group, three points behind Dortmund, before their next game at Slavia Prague.
After a 2-0 loss in Milan a fortnight ago, Dortmund had rebuilt confidence with back-to-back wins over Moenchengladbach and Wolfsburg but were dominated in the first half here.
Martinez struck early on with a superb solo effort after mistakes by both Dortmund centre-backs.
A long ball through the middle evaded Manuel Akanji with its bounce, leaving Mats Hummels isolated on the edge of the penalty area.
Hummels lost the one-on-one and could only watch as Martinez drilled his shot past Dortmund goalkeeper Roman Burki.
Martinez, who also scored against Dortmund in the reverse fixture, became the first Inter player to score in three consecutive Champions League appearances since Samuel Eto'o scored in four in a row in 2010.
Dortmund captain Marco Reus failed a fitness test on a foot injury before kick-off and the Germany forward was missed as Mario Goetze missed two clear chances at the other end.
Inter's second goal was a cracker as midfielder Vecino finished a brilliant team move.
Marcelo Brozovic won the ball from Brandt and his pass found Martinez whose raking cross-field pass landed at the feet of Vecino, who beat the defence to double Inter's lead on 40 minutes.
Dortmund came out firing for the second half and pulled a goal back when Hakimi managed to connect with Goetze's cross as the hosts attacked with regularity.
Goetze then made way for Paco Alcacer, whose first touch of the ball was to flick it to Brandt from an Inter throw, the Germany winger sweeping home the equaliser on 64 minutes.
Axel Witsel headed wide as Dortmund hunted the crucial third goal.
It soon arrived as Hakimi completed the fightback on 77 minutes when he again used his pace to tuck home Jadon Sancho's pass and put Dortmund back on course for the knockout stages.