Adam Jones (also known as domdomegg) built Who is my MP as a free Alexa skill. Who is my MP is provided by Adam Jones (domdomegg) at no cost and is intended for use as is.
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Information Collection and Use
While using Who is my MP, you will be required to provide your postcode. The information that I request is not stored by me for more than a few seconds, and is used only to provide the service.
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Link to privacy policy of third party service providers used by the app
Changes to This Privacy Policy
I may update our Privacy Policy from time to time. Thus, you are advised to review this page periodically for any changes (Great fun!). I will notify you of any changes by posting the new Privacy Policy on this page. These changes are effective immediately after they are posted on this page.
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javascript or json:
class Test { constructor(name) { this.name = name } } let obj = new Test("hello");
plot!
png
clear
pin all
distance
charge
gravity
arrows 0.1.3
| made with
d3.js


Posted on January 1, 2019 at 12:00 PM
Preparing your home The first thing that you need to take care of, even before you bring your new pet home is to prepare the place for the new member. This includes everything from gathering supplies to putting safety gates above stairs if you’re bringing in a little puppy or a kitten. Get all the food and medicine that the vet suggests for your pet. Put away things that might be dangerous for the pet or things that you don’t want to be chewed away by your little curious friend. Designate a safe place in your house where the new pet can stay when it is not running and jumping around. You could get initially get a crate for the pup or kitten and later replace it with a bigger den. In short, do whatever you can to make your new friend feel welcome and comfortable. Showing around the house Once your newly adopted pet is in the house, let it take some time and explore the house for itself. Do keep an eye though, so that it doesn’t get hurt. Show your pet its bed, its food and toys. Also, start defining its limits gradually from the first day itself. This will help when you begin training it later. You can also let it explore the yard on leash and if there is a designated potty space, lead your pet to it from the very beginning itself. Introducing the family If it is you who brought the pet home, it already sees you as its parent now. But if you are living with your family, it is important that your pet gets comfortable with the other members of the family as well. So, take some time to introduce your new friend to your family. Also, if you already have other pets in the house, acquaint them with the new member too. But make sure that the older pets are on a leash or in their closed spaces so that they can’t harm the new one in any way. Make these introductions slow and subtle so that the new member can have its time to sniff around and feel safe with everyone in the house. Once this basic orientation program for your new pet is done with, you can gradually move on to training it, improving the diet and introducing new activity.


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This is a launcher for OpenOSRS that comes bundled with a java executable. It'll auto update itself when there is a update for the OpenOSRS client available. No further configuration required!
Already have java installed and don't want to have it bundled in a launcher, wanting to have control over your java settings, whatever your motivation is you can also download the jar file!
| Hashing algorithm | Hashing value |
|---|---|
| MD5 | |
| SHA1 |


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Programming Language Suggester
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Answer these questions and you will get a suggestion based on your personality type.
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In the city I am living in, research chemicals such as DOB, DOI, 2c-e, 2c-b etc are fairly easy to get a hold of. Of these, I have only used DOI and only once.
Anyhow, a friend and myself purchased a 30mg liquid bottle. I am not 100% sure about the active dosage because the liquid is not completely DOI. But we mixed a little less than half of the bottle into some juice each. I will continue with a timetable.
6:00pm We both drink it down.
6:30 – 8:00 We make our way to a music store to look at speakers and keyboards. We plug in an iPod and listen to some music in the store. No effects are kicking in yet, the music sounds normal, we feel sober.
8:00-9:00 We walk towards a café, expecting that we will start feeling it soon. We just want to sit down and talk and see what will happen. During the walk we both start to feel anxious and slightly shaky.
9:00-10:00 We are in the café and talking. Effects start to hit in a pretty strong wave. We are having trouble looking at the menu and deciding, our conversation is like weed conversation, and we are laughing a lot. I basically feel like I just smoked a bowl.
10:00 At this point the only visual effect is that things are skewing. What I mean is that when we walk straight down the street, corners and objects appear to jump and angle in different directs. There are no colors and no textural blending.
Now it is probably 11:00 pm, we lose track of time, and keep getting hit in waves. We are laughing a lot, being very cynical of what we observe. More than anything we are shaky and cannot sit still.
 In the span of 30 minutes, we probably eat 5 french fries each. The taste sensation is insanely intense and we basically cant stop laughing or fidgeting. Outside the window, the night sky looks bright, and then inside of the room seems to be broken up into different colors. One side of the room is intensely purple, another green etc.
We take the train at about midnight out to another part of the city. The train ride is about 6 minutes but the feeling of being surrounded by people is uncomfortable and we just want to get off. Once of, we walk towards hidden little bar/café and get some alcohol. We just keep talking enthusiastically about an assortment of topics. There are no “hallucinations”, but sometimes textures blend. Wallpaper with patterns looks like its moving and our minds are pretty slow. The best way to describe it is that our minds are slow, but bodies very fast and fidgety.
At about 1:00 am we head to a new area, in an effort to change our scenery and hopefully our high. The streets are dead (because it is Sunday night). The few drunk college kids look really sloppy to us. We are very content to just sit and talk and observe what is going on around us. Our observations seem very clear, but our perception of it is more detailed than normal.
All in all, we are still cracked out. Walking feels good now, and each time we look at something different a new wave hits us.
At about 2:00 am we start walking home. I wanted to take a taxi but walking sounded more fun. It was about a 2 hour walk but we don't feel tired or sleepy at all. At about 4:00am the sun starts to come up and the sky is impossibly blue. The city looks beautiful and we are still laughing and focused on our conversation topics.
We try to pass out at my apartment, but this is impossible. My friend leaves at about 8:00 am and I cannot go to sleep until about 12:00pm. Even in sleep I still feel very awake and my mind is running fast now.
To conclude DOI is a very “cracky” drug. A higher dosage my increase the visuals, but in general it is an energetic drug, not a visual one. We experienced no nausea except for some caused by hunger. I had fun because our conversation was very focused and funny, and we both made weird new observations that became funny convo topics.
I don't think I will use DOI again anytime soon because more visuals and less energy would be preferable (personally). It was about a 10 hour trip with the after effect lasting for a while after that. With a few hours sleep I felt totally recovered (but really hungry!)
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


- geneSubnets - Variable in class view.GUI
-
- getAddr() - Method in class ISP.IP
-
Returns the IP address in a String form.
- getAddr() - Method in class model.IP
-
Returns the IP address in a String form.
- getBroadcast() - Method in class model.Subnet
-
Return the broadcast Address.
- getCIDR() - Method in class ISP.IP
-
- getFirstIpHost() - Method in class model.Subnet
-
Returns the First Ip usable.
- getHosts() - Method in class ISP.IP
-
Calculate the number of hosts for the network.
- getHosts(int) - Method in class ISP.IP
-
Return the number of hosts possible based on the parameter
- getHosts() - Method in class model.IP
-
Calculate the number of hosts for the network.
- getHosts(int) - Method in class model.IP
-
Returns the number of hosts possible based on a mask
- getHostsUsed() - Method in class model.Network
-
Returns the number of hosts already used in the network
- getLastIpHost() - Method in class model.Subnet
-
Returns the Last Ip usable.
- getMask() - Method in class ISP.IP
-
Returns a String representing the Dotted Decimal Netmask
- getMask() - Method in class model.IP
-
Returns a String representing the Dotted Decimal Netmask
- getNetwork() - Method in class controller.ControllerNetwork
-
Returns the network created by the model.
- getNetwork() - Method in class model.ModelNetwork
-
Returns the network
- getNextSubnetAddr() - Method in class model.Subnet
-
Return the next Subnet address.
- getSubnets() - Method in class model.ModelNetwork
-
Returns the subnets of the network.
- getSubnets() - Method in class model.Network
-
Returns all the subnets the network knows
- gui - Variable in class main.Main
-
- GUI - Class in view
-
- GUI(ModelNetwork, ControllerNetwork, int, int) - Constructor for class view.GUI
-
Constructor of GUI.


Tuscany Samples - Getting Started - SCA C++ Milestone release 1
Tuscany SCA C++ includes a simple technology sample that demonstrates some of the functionality of
the Tuscany SCA C++ runtime. This page describes what is needed to install and run the sample.
Building the samples on Linux
If using the binary distribution the samples are built and installed in
<tuscany_sca_install_dir>/samples - go directly to Running the samples on Linux.
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- Build the source with the following command sequence:
- cd <tuscany_sca_install_dir>/samples
- ./configure
- make
- make install
NOTE: If you don't provide a --prefix configure option, it will by default install into
/usr/local/tuscany/sca/samples/Calculator
Running the samples on Linux
Calculator with basic client
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- Run the sample with the following commands:
- cd <tuscany_sca_install_dir>/samples/Calculator/deploy/bin
- ./runclient.sh
Calculator with Web Service client
- Deploy the Calculator as an Axis2C service:
- Create a new service folder in axis2:
<AXIS2C_HOME>/services/Calculator
- Copy the <TUSCANY_SCACPP>/samples/Calculator/CalculatorModule/services.xml
to <AXIS2C_HOME>/services/Calculator/services.xml
- Edit the <AXIS2C_HOME>/services/Calculator/services.xml file to set the TuscanySystemRoot parameter to
<parameter name="TuscanySystemRoot" locked="xsd:false"><tuscany_sca_install_dir>/samples/Calculator/deploy</parameter>
replacing <tuscany_sca_install_dir> with the install path of Tuscany SCA
- Copy the <TUSCANY_SCACPP>/lib/libtuscany_sca_ws_service.so library into <AXIS2C_HOME>/services/Calculator
- Start the Axis2C simple http server:
- cd <AXIS2C_HOME>/bin
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- Add <TUSCANY_SCACPP>/lib, <TUSCANY_SDOCPP>/lib and <AXIS2C_HOME>/lib
to the LD_LIBRARY_PATH environment variable
- ./axis2_http_server
- Run the client:
- The following environment variable is required:
- AXIS2C_HOME=<path to axis2c version 0.92>
- cd <tuscany_sca_install_dir>/samples/Calculator/deploy/bin
- ./runwsclient.sh
Building the samples on Windows
If using the binary distribution the samples are built and installed in
<tuscany_sca_install_dir>/samples - go directly to Running the samples on Windows.
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- You must have set up the environment for Microsoft Visual C++ tools.
The build command will call vcvars32 to set the environment. Ensure the
directory containing this is on your path. This will be where you
installed the compiler.
- Build the source, either via the Visual Studio 6 or 7 projects under
<tuscany_sca_install_dir>\samples\ides or via the command-line build file
found at <tuscany_sca_install_dir>\samples\ides\devstudio6\projects\Calculator\build.cmd
which will build and deploy the samples.
Running the samples on Windows
Calculator with basic client
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- Run the sample with the following commands:
- cd <tuscany_sca_install_dir>/samples/Calculator/deploy/bin
- runclient add 5 6
(can also use sub, div, mul).
Calculator with Web Service client
- Deploy the Calculator as an Axis2C service:
- Create a new service folder in axis2:
<AXIS2C_HOME>/services/Calculator
- Copy the <TUSCANY_SCACPP>/samples/Calculator/CalculatorModule/services.xml
to <AXIS2C_HOME>/services/Calculator/services.xml
- Edit the <AXIS2C_HOME>/services/Calculator/services.xml file to set the TuscanySystemRoot parameter to
<parameter name="TuscanySystemRoot" locked="xsd:false"><TUSCANY_SCACPP>/samples/Calculator/deploy</parameter>
replacing <TUSCANY_SCACPP> with the install path of Tuscany SCA
- Copy the <TUSCANY_SCACPP>/lib/tuscany_sca_ws_service.dll (and .pdb if debugging) file(s)
into <AXIS2C_HOME>/services/Calculator
- Start the Axis2C simple http server:
- cd <AXIS2C_HOME>/bin
- The following environment variables are required:
- TUSCANY_SCACPP=<path to installed Tuscany SCA>
- TUSCANY_SDOCPP=<path to installed Tuscany SDO>
- AXIS2C_HOME=<path to axis2c version 0.92>
- Add <TUSCANY_SCACPP>\bin, <TUSCANY_SDOCPP>\bin and <AXIS2C_HOME>/lib
to the PATH environment variable
- axis2_http_server
- Run the client:
- The following environment variable is required:
- AXIS2C_HOME=<path to axis2c version 0.92>
- cd <tuscany_sca_install_dir>/samples/Calculator/deploy/bin
- runwsclient


How to Make a Beautifual Website
Good Design Principles
Good design has the following goals:
- To make the most important information the easiest to find.
- To answer your questions in the order you're likely to have them.
- To place more specific information exactly where you'd expect it.
- To make sure you can focus on one thing at a time without being distracted by other information or content.
- To use colors, fonts, and layout to help you focus (not to distract).
Therefore, good design is usually characterized by the following:
- Large text, widely spaced, and condensed down to the most important information. You almost always have to click to learn more.
- Lots of negative space (areas with no content) to direct your focus onto what little is there.
- Pro-tip that the "padding" property is one of the best ways to achieve this.
- Clear design hierarchy (the most important info is up top, in large fonts; more specific info is in smaller fonts, and usually further down)
- Consistency across similar elements.
- Intentional, simplistic font choices. Even though it's tempting to use really bubbly, playful, or decorative fonts, most of the best and most beautiful websites use only two fonts: one for headers, another for body text, and the vast majority of websites use thin and block versions of sans-serif fonts.
History of Design
Over the course of the 2010s, web design trends have been dominated by two major schools of thought:
- Material Design: This particular guide was written by designers at Google, and was the guiding light for a lot of systems you may be used to using, though they're gradually moving away from or at least evolving this school of thought in current updates.
- Flat Design: Microsoft has historically been the largest proponent of flat design (as early as the mid 2000s with many of their products), though Apple has largely shifted their design to Flat Design as well.


How we fell in love with the Philippines?
We started our adventure in Cebu! What a beautiful city, I should say that from the moment we landed we were amazed with how clean it was! Coming from Singapore we had low expectations but Cebu surprised us. Upon arrival, we got our SIM cards with data for a week right outside the airport and it cost us 500 pesos for about 7GB data (this information may be important for those of us who need to make calls home, especially since we were going to the islands with poor connection). But, if you are adventurous and want no connection, by all means do it!
In Cebu, we stayed in an airbnb “Myra’s bedsit” in Horizons 101 condominium for 3 nights. This cost us 47 SGD each person which was really cheap considering it was clean and at a great location! We would definitely recommend it to anyone planning a few nights in Cebu.
Osmena peak and Kawasan falls
We booked our tour about a month earlier just because we were on a tight schedule and wanted to be prepared. We booked with Cebu tours and it cost us 61 SGD each person. This tour included the driver and lunch. The journey to osmena peak took us 3 hours by car depending on traffic as sometimes it could be longer! Osmena peak is worth the journey and money! The view was magnificent! The trek up takes about 20 minutes but be warned it could be slippery with loose rocks. It is considered a beginners route but we did find out that there is a harder route that takes about 2 hours so you may consider that if you like. We had a guide who was very kind and patient! He spent quite some time taking pictures of us and even climbed higher peaks to help us take the perfect picture! Tip here would be remember to bring a jacket, it gets a little cold up at the peak.
After the peak, it takes about an hour to get to Kawasan falls. When you get there you will need to walk for about 15 to 20 minutes to get to the falls. It is required that everyone wears a life jacket as the locals say the water is very deep and can be rough from the falls. When we took our first dip we were freezing! The water was very cold, we could not sit there for long. Maybe it was just the cloudy day? As we know this time of the year it gets chilly and rainy. One tip here would be to know if you take a picture with the “I love kawasan falls” be prepared to pay 50 pesos! There will be an angry guy standing there demanding for the money. Overall, we were underwhelmed with the falls, I would suggest you do canyoneering if you did Kawasan falls!
El nido island hopping
The journey here took us ages! We flew into Puerto Princessa airport from Cebu and had to get a 6 hour van ride to el nido. It costs 450 pesos per person which was a really good price. Despite the time it took us, el nido was our favourite! it was raw and beautiful with very few tourists (but this could be due to the low season). We stayed at spin designer hostel and we gave it a high rating as it was very clean and breakfast was nice! One of the nights there was a black out in el nido but our hostel had a back up generator and we were fine. The only negative would be poor wifi (but you are in paradise, don’t think you will need it!).
Island hopping is a must! We decided to go on a private tour as we read blogs about how crowded the boats get and we wanted to have the freedom over our trip. We booked with el nido paradise tours and it cost us 55 SGD each person with lunch included. We chose tour A which included the small lagoon, big lagoon, secret beach and seven commando beach.
We did some kayaking in the small lagoon, which cost about 400 pesos. It was worth it except be warned that it gets crowded with lots of other boats and people kayaking. The big lagoon is protected so you can only pass through it and they will not allow you to go into the water. The seven commando beach was a a white sand turquoise water beach for swimming and lots of picture spots. Lunch on the boat had a good variety- it included freshly made (they cook it on the boat) BBQ prawns, chicken wings and eggplant salad and lots of fruits. We told our guide that we wished to get down at las cabanas beach to watch the sunset and it was doable! So, we ended our evening with a bottle of wine watching the sunset- perfect end to the day!
Nacpan beach, el nido
You will need to book a shuttle van to take you to the beach. It costs 600 pesos each person. The beach was pretty empty! you will get vouchers for welcome drinks and a free drink at mad monkey hostel. We did try to get a seat there but it was packed and so hot! eventually we paid 200 pesos and rented a bamboo hut from the locals- best decision ever! It was cooling and it fit us all.
The water was clear and wavy! Don’t think it is particularly ideal for swimmers but its great for surfers. We enjoyed jumping around in the waves and we were doing this all day. The only downside at this beach are the stray dogs. There is a pack of them and the moment you take any food out, they will jump at you. It got a little scary at times. One of the dogs jumped at my friends chicken on the table (while she was still eating).
Last night in Puerto Princessa
Our last night was simply for food and karoake! we stayed at the acacia hotel and resort and they served us the best lunch! it was huge with several grilled seafood options not forgetting the eggplant salad we loved. I wish to dedicate a whole post for food in the Philippines! One paragraph is not enough! So stay tuned for my foodie post! For now, our final verdict is we would definitely return to the Philippines! There is so much more to explore!


This is the course website for IS445(AOG) in Fall 2020
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|
In keeping with University and iSchool policy, all students are required to engage in appropriate behavior to protect the health and safety of our community. If you are on campus, this includes wearing a facial covering properly, maintaining social distance (at least 6 feet from others at all times), disinfecting the immediate seating area, and using hand sanitizer.
If you feel ill or are unable to come to class or complete class assignments due to issues related to COVID-19, including but not limited to: testing positive yourself, feeling ill, caring for a family member with COVID-19, or having unexpected child-care obligations, should contact their instructor immediately and cc their advisor.
Additionally, please be aware that there are mental health resources available to students:
Finally, due to the current messiness of the COVID learning environment, we are allowing up to three late homeworks. If you need to “use” one of your late homeworks email the instructor and/or the TA. You do not need to provide any explanation for why you’d like to use one of your late homeworks. You will then have until the end of the week – the Sunday after the homework was due, midnight – to turn in this assignment.
Data visualization is crucial to conveying information drawn from models, observations or investigations. This course will provide an overview of historical and modern techniques for visualizing data, drawing on quantitative, statistical, and network-focused datasets. Topics will include construction of communicative visualizations, the modern software ecosystem of visualization, and techniques for aggregation and interpretation of data through visualization. Particular attention will be paid to the Python ecosystem and multi-dimensional quantitative datasets.
As a land-grant institution, the University of Illinois at Urbana-Champaign has a responsibility to acknowledge the historical context in which it exists. In order to remind ourselves and our community, we will begin this event with the following statement. We are currently on the lands of the Peoria, Kaskaskia, Peankashaw, Wea, Miami, Mascoutin, Odawa, Sauk, Mesquaki, Kickapoo, Potawatomi, Ojibwe, and Chickasaw Nations. It is necessary for us to acknowledge these Native Nations and for us to work with them as we move forward as an institution. Over the next 150 years, we will be a vibrant community inclusive of all our differences, with Native peoples at the core of our efforts.
More information can be found on the Chancellor’s Website.
This course is designed to give practical advice to students on communicating data through visualization. This will involve a considerable amount of programming, and typically this programming will be done in Python. For the most part, our data will be quantitative and multi-dimensional. The course will aim to provide both an understanding of what data visualizations communicate and a set of tools for constructing them yourself.
The course will follow a common pattern within each three-hour instructional session. The first 60-90 minutes will be focused on lecture, where concepts and tools will be introduced; typically, each class will focus on one type of visualization or class of visualization. The remaining time will include exploration of a dataset, which may be independent or in groups, and then a wrap-up session at the end.
Students are expected to have laptops with them, as well as access to Python installations, and will be encouraged to participate in class. Homework will be assigned and collected through other methods specified at time of submission like Moodle.
The central themes of the course are:
None, although basic Python programming experience is assumed. A brief introduction to Python will be presented during the course.
There is no required textbook for this course. All course materials will be posted to the GitHub repository at https://github.com/UIUC-iSchool-DataViz/spring2020 .
A list of Python libraries week-by-week and tips on how to install them can be found by clicking this link.
Optional textbook Visualization Analysis and Design by Tamara Munzner. You can find a lot of the concepts from this textbook on the books webpage and the associated lecture slides.
As the course progresses, a list of recommended readings will be generated for each class. These will be included in the course materials repository, and students are encouraged to fork that repository and issue pull requests to add suggested readings.
The iSchool Writing Resources is the in-house writing support team for graduate students at the iSchool. They are here to help you with your writing and help you feel more comfortable and confident in your skills. The writing consultants are not professors or evaluators. They simply know the struggles of graduate and undergraduate-level writing and want to help you learn how to succeed and improve your writing skills. The iSchool writing consultants can help you with every step of the writing process. For detailed information on our services please visit our website: https://publish.illinois.edu/ischoolwritingresources/
Below is an approximate outline of the course and optional reading for each week. This course is always under development and the course outline below is subject to some flexibility; students will be encouraged to provide feedback on the topics covered, particularly toward the end. Topics that are of particular interest will be emphasized.
Optional texts:
Acronyms for books:
Course Outline and Optional Reading List
| Week | Topic | Reading |
|---|---|---|
| Week 1 | Introduction, syllabus, examples, and some basics | 1. VAD, Ch. 1: What’s Viz, and Why Do It? 2. FDV, Ch. 1: Introduction & FDV, Ch. 17: The principle of proportional ink 3. Same Data, Multiple Perspectives 4. Intro to Jupyter Notebook Video |
| Week 2 | Data storage & Operations; Image data | 1. VAD, Ch. 2: What: Data Abstraction 2. FDV, Ch. 2: Visualizing data: Mapping data onto aesthetics 3. VAD, Ch. 13: Reduce Items and Attributes 4. FDV, Ch. 27: Understanding the most commonly used image file formats 5. IS452’s intro to CSV files (bottom of page) 6. IS452’s Intro to Dictionaries 7. Pandas Docs & NumPy Docs |
| Week 3 | Holiday! | |
| Week 4 | Types of Viz and color, colormaps | 1. VAD, Ch. 10: Map Color and Other Channels 2. FDV, Ch. 4: Color scales 3. VAD, Ch. 5: Marks and Channels 4. Perception in Visualization (pay extra attention to the parts about color) 5. Palettable Docs |
| Week 5 | Beginning Interactivity | 1. Intro to ipywidgets 2. Example Widgets Notebooks 3. VAD Ch. 7: Arrange Tables 4. FDV, Ch. 7: Visualizing distributions: Histograms and density plots |
| Week 6 | Distributions, Engines | 1. Video about bqplot 2. An introduction to Grammar of Graphics 3. ipywidgets Docs; Traitlets Docs; bqplot Docs |
| Week 7 | Dashboards & Maps with bqplot | 1. VAD Ch. 8.1-8.3: Arrange Spatial Data 2. VAD Ch. 11.1-11.5: Manipulate View 3. FDV, Ch. 15: Visualizing geospatial data |
| Week 8 | More with maps - bqplot, cartopy, ipyleaflet, geopandas | 1. VAD Ch. 8.1-8.3: Arrange Spatial Data 2. FDV, Ch. 15: Visualizing geospatial data 3. VAD, Ch. 13.4.2: Reduce Items and Attributes 4. Cartopy docs; ipyleaflet docs; Geopandas Docs |
| Week 9 | Designing for the web with Python & Javascript with Iodide | 1. Iodide Docs - in particular: key concepts & IOMD format 2. Intro to Javascript 3. FDV, Ch. 5: Directory of visualizations |
| Week 10 | Designing for the web with Python & Javascript, Web dev with Iodide; Considering your audience | 1. Same Data, Multiple Perspectives 2. FDV, Ch. 29: Telling a story and making a point 3. Iodide Docs 4. vega-lite docs - in particular: Vega-lite transformations & Vega-lite selections 5. Idyll Docs |
| Week 11 | More javascript & web dev with Idyll | 1. Idyll Docs - in particular: Built in/npm installed components |
| Week 12 | More with Idyll, Publishing Viz | 1. Idyll Docs |
| Week 13 | Idyll + d3.js | 1. d3.js docs |
| Week 14 | Holiday! | |
| Week 15 | Scientific visualization Guest lecture about scientific & cinematic viz from AVL |
1. VAD Ch. 8.4-8.6: Arrange Spatial Data 2. VAD Ch. 11.6: Manipulate View 3. yt docs 4. yt Volume Rendering Tutorial |
| Week 16 | Network Viz & Word cloud Viz; Class summary | 1. VAD Ch. 9: Arrange Networks and Trees 2. VAD, Ch. <IP_ADDRESS>: Reduce Items and Attributes 3. VAD, Ch. 6: Rules of Thumb 4. FDV, Ch. 28: Choosing the right visualization software 5. FDV, Ch. 26: Don’t go 3D 6. FDV, Ch. 25: Avoid line drawings |
Jill Naiman’s background is in theoretical and computational astrophysics with a current research emphasis on scientific data visualization and the digitization of historical scientific images and text. She is currently a Visiting Scholar at the Advanced Visualization Lab at the National Center for Supercomputing Applications. She is currently involved in projects related to increasing access to industry-standard special effects software for scientists - more info can be found here and here. Information about her astrophysical research and outreach efforts can be found here.
| http://www.library.illinois.edu/lis/ |
|<EMAIL_ADDRESS>|
| Phone:<PHONE_NUMBER> |
The campus-wide Writers Workshop provides free consultations. For more information see http://www.cws.illinois.edu/workshop/ The iSchool has a Writing Resources Moodle site https://courses.ischool.illinois.edu/course/view.php?id=1705 and iSchool writing coaches also offer free consultations.
Please review and reflect on the academic integrity policy of the University of Illinois, http://studentcode.illinois.edu/article1_part4_1-401.html, to which we subscribe. By turning in materials for review, you certify that all work presented is your own and has been done by you independently, or as a member of a designated group for group assignments.
If, in the course of your writing, you use the words or ideas of another writer, proper acknowledgement must be given (using APA, Chicago, or MLA style). Not to do so is to commit plagiarism, a form of academic dishonesty. If you are not absolutely clear on what constitutes plagiarism and how to cite sources appropriately, now is the time to learn. Please ask me!
Please be aware that the consequences for plagiarism or other forms of academic dishonesty will be severe. Students who violate university standards of academic integrity are subject to disciplinary action, including a reduced grade, failure in the course, and suspension or dismissal from the University.
Criteria for grading homework assignments include (but are not limited to) creativity and the amount of original work demonstrated in the assignment. However, students are permitted to use and adapt the work of others, provided that the following guidelines are followed:
As the state’s premier public university, the University of Illinois at Urbana-Champaign’s core mission is to serve the interests of the diverse people of the state of Illinois and beyond. The institution thus values inclusion and a pluralistic learning and research environment, one which we respect the varied perspectives and lived experiences of a diverse community and global workforce. We support diversity of worldviews, histories, and cultural knowledge across a range of social groups including race, ethnicity, gender identity, sexual orientation, abilities, economic class, religion, and their intersections.
To obtain accessibility-related academic adjustments and/or auxiliary aids, students with disabilities must contact the course instructor and the Disability Resources and Educational Services (DRES) as soon as possible. To contact DRES you may visit 1207 S. Oak St., Champaign, call 333-4603 (V/TTY), or e-mail a message to<EMAIL_ADDRESS>This syllabus may be obtained in alternative formats upon request. Please contact the instructor.
Students will be graded based on a combination of assignments (70%: 40% standard prose/code assignments and 30% weekly visualization reports) and a final project (30%). The final project will be a capstone to the course, and will have greater flexibility in software packages and data sources. This project will be introduced in Week 8.
In summary, your grades consist of:
| 40% | Standard assignments in prose or code form |
| 30% | Weekly visualization reports |
| 30% | Final project |
Assignments in this course will be a mixture of coding/visualization work and written work. These two may not be distinct assignments; students will be asked to describe their code and justify choices for making decisions with respect to visualizations.
Students are expected, unless otherwise instructed, to be the principal authors of their code. This does not mean they may not investigate resources such as StackOverflow, package documentation, etc; however, they must cite when resources (especially StackOverflow and other “recipe” sites) are utilized.
Assignments will take two forms, and will be given at the end of each class. Students will have until the following class to turn these in; assignments will be collected electronically.
The submission process for homeworks will be described by example during class before any homeworks are to be submitted.
Each assignment will be based on “correctness” and the narrative description of the process. “Correctness” in this case indicates that the code runs without issue, results are produced, and each component of the assignment is completed. The narrative description of the process will be graded on grammar minimally and more so on completeness and thoughtfulness.
All assignments are required for all students, aside from one homework (lowest HW grade will be dropped). Completing all assignments is not a guarantee of a passing grade. You must do homework, visualization reports, and final to receive a passing grade. Late or incomplete assignments will not be given full credit unless the student has contacted the instructor prior to the due date of the assignment (or in the case of emergencies, as soon as practicable).
Grading Scale:
| 94-100 | A |
| 90-93 | A- |
| 87-89 | B+ |
| 83-86 | B |
| 80-82 | B- |
| 77-79 | C+ |
| 73-76 | C |
| 70-72 | C- |
| 67-69 | D+ |
| 63-66 | D |
| 60-62 | D- |
| 59 and below | F |
Students must request an incomplete grade from the instructor. The instructor and student will agree on a due date for completion of coursework and the student must file an Incomplete Form signed by the student, the instructor, and the student’s academic advisor with the School’s records representative. More information on incompletes is available here: http://webdocs.ischool.illinois.edu/registration/incomplete_grade_form.pdf
Students are required to attend each class, and if they are unable to do so must notify the instructor and TA in advance and request an excused absence. Participation in class – in the form of comments, questions, and discussion – is expected.
Emergencies can happen anywhere and at any time. It is important that we take a minute to prepare for a situation in which our safety or even our lives could depend on our ability to react quickly. When we’re faced with any kind of emergency – like fire, severe weather or if someone is trying to hurt you – we have three options: Run, hide or fight.
Leaving the area quickly is the best option if it is safe to do so.
When you can’t or don’t want to run, take shelter indoors.
As a last resort, you may need to fight to increase your chances of survival.
Please be aware of persons with disabilities who may need additional assistance in emergency situations.


Half Guard Hip Clamp (kyotera sweep)
When Ops is sitting up, from Half Guard Knee Shield, slide bottom leg through deep to knee, top leg clamps down on hip/thigh, feet interlock
with top foot at back so bottom foot is stopping it moving towards you or away to the side.
Turn belly down to push up position, get opponents knee off the floor, opens up sweeps and leg attacks.
You end up in a combat base but sitting over ops hips with legs tangled under you.


This is a static web page that contains an embedded Vaadin application. It's here:
Please view the page source to see how embedding works.


MAZE GENERATOR
Created by:
Dylan Roberts
&
Alex Leska
Size
Instant
FPS (30)
Background
Maze
Generate
New Maze
Download


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| Packages that use edu.uci.ics.jung.graph | |
|---|---|
| edu.uci.ics.jung.algorithms.blockmodel | Support for establishing and maintaining graph element equivalence (such as in blockmodeling). |
| edu.uci.ics.jung.algorithms.cluster | Mechanisms for identifying clusters in graphs. |
| edu.uci.ics.jung.algorithms.filters | Filtering mechanisms that produce subgraphs of an original graph. |
| edu.uci.ics.jung.algorithms.flows | Methods for calculating properties relating to network flows (such as max flow/min cut). |
| edu.uci.ics.jung.algorithms.generators | Methods for generating new (often random) graphs with various properties. |
| edu.uci.ics.jung.algorithms.generators.random | Methods for generating random graphs with various properties. |
| edu.uci.ics.jung.algorithms.importance | |
| edu.uci.ics.jung.algorithms.layout | Algorithms for assigning 2D coordinates (typically used for graph visualizations) to vertices. |
| edu.uci.ics.jung.algorithms.matrix | Mechanisms for dealing with graphs as matrices. |
| edu.uci.ics.jung.algorithms.metrics | Specialized measures for graph properties. |
| edu.uci.ics.jung.algorithms.scoring | Mechanisms for assigning values (denoting significance, influence, centrality, etc.) to graph elements based on topological properties. |
| edu.uci.ics.jung.algorithms.scoring.util | Utility functions for assigning scores to graph elements. |
| edu.uci.ics.jung.algorithms.shortestpath | Provides interfaces and classes for calculating (geodesic) distances and shortest paths. |
| edu.uci.ics.jung.algorithms.transformation | Mechanisms for graph transformation. |
| edu.uci.ics.jung.algorithms.util | Provides general algorithmic utilities. |
| edu.uci.ics.jung.graph | Interfaces for the JUNG graph types, and some representative implementations. |
| edu.uci.ics.jung.graph.event | Support for generating events in response to graph actions, especially mutations. |
| edu.uci.ics.jung.graph.util | Utility interfaces and classes for the JUNG API. |
| edu.uci.ics.jung.io | Interfaces and classes for reading and writing graphs in various (file) formats. |
| edu.uci.ics.jung.io.graphml | |
| edu.uci.ics.jung.io.graphml.parser | |
| edu.uci.ics.jung.samples | Sample applications created using JUNG, largely focused on visualization. |
| edu.uci.ics.jung.visualization | Frameworks and mechanisms for visualizing JUNG graphs using Swing/AWT. |
| edu.uci.ics.jung.visualization.decorators | Mechanisms for associating data (shapes, colors, values, strings, etc.) with graph elements. |
| edu.uci.ics.jung.visualization.layout | Visualization mechanisms related to graph layout: caching, persistence, event-emitting, etc. |
| edu.uci.ics.jung.visualization.picking | Visualization mechanisms for supporting the selection of graph elements. |
| edu.uci.ics.jung.visualization.subLayout | Visualization mechanisms relating to grouping or hiding specified element sets. |
| edu.uci.ics.jung.visualization.util | Utilities for graph visualization. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.blockmodel | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.cluster | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.filters | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.flows | |
|---|---|
| DirectedGraph
A tagging interface for implementations of Graph
that accept only directed edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.generators | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.generators.random | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.importance | |
|---|---|
| DirectedGraph
A tagging interface for implementations of Graph
that accept only directed edges. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.layout | |
|---|---|
| Forest
An interface for a graph which consists of a collection of rooted directed acyclic graphs. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.matrix | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.metrics | |
|---|---|
| DirectedGraph
A tagging interface for implementations of Graph
that accept only directed edges. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.scoring | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.scoring.util | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.shortestpath | |
|---|---|
| Forest
An interface for a graph which consists of a collection of rooted directed acyclic graphs. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.transformation | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
|
| KPartiteGraph
An interface for graphs whose vertices are each members of one of 2 or more disjoint sets (partitions), and whose edges connect only vertices in distinct partitions. |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.algorithms.util | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.graph | |
|---|---|
| AbstractGraph
Abstract implementation of the Graph interface. |
|
| AbstractTypedGraph
An abstract class for graphs whose edges all have the same EdgeType . |
|
| DirectedGraph
A tagging interface for implementations of Graph
that accept only directed edges. |
|
| DirectedSparseMultigraph
An implementation of DirectedGraph , suitable for sparse graphs,
that permits parallel edges. |
|
| Forest
An interface for a graph which consists of a collection of rooted directed acyclic graphs. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| GraphDecorator
An implementation of Graph that delegates its method calls to a
constructor-specified Graph instance. |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
|
| MultiGraph
A tagging interface which indicates that the implementing graph accepts parallel edges. |
|
| OrderedKAryTree.VertexData
|
|
| OrderedSparseMultigraph
An implementation of Graph that orders its vertex and edge collections
according to insertion time, is suitable for sparse graphs, and
permits directed, undirected, and parallel edges. |
|
| SparseMultigraph
An implementation of Graph that is suitable for sparse graphs
and permits directed, undirected, and parallel edges. |
|
| Tree
A subtype of Graph which is a (directed, rooted) tree. |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
|
| UndirectedSparseMultigraph
An implementation of UndirectedGraph that is suitable for
sparse graphs and permits parallel edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.graph.event | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.graph.util | |
|---|---|
| DirectedGraph
A tagging interface for implementations of Graph
that accept only directed edges. |
|
| Forest
An interface for a graph which consists of a collection of rooted directed acyclic graphs. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Tree
A subtype of Graph which is a (directed, rooted) tree. |
|
| UndirectedGraph
A tagging interface for extensions of Graph that
accept only undirected edges. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.io | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.io.graphml | |
|---|---|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.io.graphml.parser | |
|---|---|
| Hypergraph
A hypergraph, consisting of a set of vertices of type V
and a set of hyperedges of type E which connect the vertices. |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.samples | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization.decorators | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization.layout | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization.picking | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization.subLayout | |
|---|---|
| Forest
An interface for a graph which consists of a collection of rooted directed acyclic graphs. |
|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
| Classes in edu.uci.ics.jung.graph used by edu.uci.ics.jung.visualization.util | |
|---|---|
| Graph
A graph consisting of a set of vertices of type V
set and a set of edges of type E . |
|
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Step-by-step Illustration¶
In the Quick Start Example section, we have shown the simplest all-in-one command line of
performing the pipeline with a wrapper script imargi_wrapper.sh
. Here we go inside of the quick example to illustrate
the details of iMARGI Pipeline. If you want to customize your pipeline, you can run each step separately with
corresponding tools.
- Step-by-step Illustration
The imargi_wrapper.sh
Running Command¶
In the quick example section, we use the following command of imargi_wrapper.sh
, whose input
are only sequencing read pairs FASTQ files and reference genome sequence FASTA file.
docker run --rm -t -u 1043 -v ~/imargi_example:/imargi zhonglab/imargi \
imargi_wrapper.sh \
-r hg38 \
-N test_sample \
-t 4 \
-g ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta \
-i ./ref/bwa_index/bwa_index_hg38 \
-1 ./data/sample_R1.fastq.gz \
-2 ./data/sample_R2.fastq.gz \
-o ./output
We only set a few arguments in the command which are described below, and use default settings for other arguments.
-r
: Name of reference genome. It will be used in header of .pairs format file and names of new generated reference files.-N
: Name of sample. It will be used in names of final output files.-t
: Maximum CPU cores.-g
: Reference genome sequence FASTA file.-i
: BWA index files.-1
and-2
: Sequencing read pairs FASTQ files.-o
: Output directory
In fact, there are more arguments of imargi_wrapper.sh
can be set, you can check the full arguments in the
Command-line API section. Here we want to remind you the following three arguments of required
reference files, including chromosome sizes file, bwa index and restriction fragments bed format file. Because we didn’t
set these arguments in the command line, imargi_wrapper.sh
automatically generated them. If you have already got these
files, you can use these arguments and it will save you some time and disk space. When the three arguments are all set
correctly, the -g
argument can be ignored.
-i
: BWA index files.-c
: Chromosome sizes file-R
: Restriction fragments bed format file
The following sections are detail illustrations of how imargi_wrapper.sh
works inside of the iMARGI Docker
container.
Generating Required Reference Files¶
As we only input reference genome sequence FASTA file with -g
argument, so imargi_wrapper.sh
will automatically
generate other required reference files, such as chromosome sizes, bwa index and restriction fragments.
Generating Chromosome Sizes File¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | samtools faidx |
<ref_genome_FASTA> |
| Input | ref genome sequence in FASTA | ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta |
| Output | chromosome sizes file | ./ref/chrom.sizes.hg38.txt |
The imargi_wrapper.sh
uses samtools faidx
to generate the chromosome sizes file from reference genome sequence FASTA
file. The command lines used in imargi_wrapper.sh
is:
cd ~/imargi_example/ref
samtools faidx GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta
cat GRCh38_no_alt_analysis_set_GCA_000001405.15.fa.fai |awk 'BEGIN{OFS="\t"}{print $1,$2}' >chrom.sizes.hg38.txt
Building BWA Index¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | bwa index |
-p <idxbase> <ref_genome_FASTA> |
| Input | ref genome sequence in FASTA | ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta |
| Output | a folder of bwa index files | ./ref/bwa_index |
BWA is used to map sequencing reads to reference genome, so we need to construct bwa index for reference genome first.
Here is the command lines used in imargi_wrapper.sh
:
cd ~/imargi_example/refmkdir
bwa index -p ./ref/bwa_index/bwa_index_hg38 ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta
Generating Restriction Fragment File¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | imargi_rsfrags.sh |
- r <ref_genome_FASTA> -c <chromSize_file> -e <enzyme_name> -C <cut_position> |
| Input | ref genome sequence in FASTA | ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta |
| Output | restriction fragment BED file | ./ref/AluI_frags.bed.gz |
AluI enzyme is used to digest genome in iMARGI, whose cutting site is AG^CT. The restriction fragments are used for
filtering out read pairs sequenced from non-RNA-DNA-ligation fragments. The imargi_wrapper.sh
uses imargi_rsfrags.sh
tool to generate the restriction fragment bed (gzip compressed) format file.
imargi_rsfrags.sh \
-r ./ref/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta \
-c ./ref/hg38.chrom.sizes \
-e AluI \
-C 2 \
-o ./ref/iMARGI_AluI_rsfrags.bed.gz
Cleaning: clean read pairs¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | imargi_clean.sh |
-1 <fastq.gz_R1> -2 <fastq.gz_R2> -o <output_dir> -t <threads> |
| Input | raw paired FASTQ files | ./data/sample_R1.fastq.gz ./data/sample_R2.fastq.gz |
| Output | clean paired FASTQ files | ./output/clean_fastq/clean_test_sample_R1.fastq.gz ./output/clean_fastq/clean_test_sample_R2.fastq.gz |
According to the design of iMARGI sequencing library construction, there are two random nucleotides NN
at the 5’ end
of R1 read. It will affect mapping, so we remove those two random bases before mapping.
As the 5’ end of R2 is DNA restriction enzyme digestion site, which is AluI in iMARGI experiment (AG^CT), so the DNA
end should always start with “CT”. Hence, we can use this to filter out non-ligated RNA contaminations.The
imargi_clean.sh
tool has an option -f <filter_CT>
, which can be used to filter read pairs based on the 5’
end sequence of R2 reads as -f CT
. The advantage of of such hard filtering is reduce the computational cost.
But the disadvantage is that it’s not flexible and causes false negative. So we don’t use the filter, and the filter
based on restriction fragments is applied in parsing step within the imargi_parse.sh
tool.
The command of cleaning used in the imargi_wrapper.sh
is:
bash imargi_clean.sh \
-1 ./data/sample_R1.fastq.gz \
-2 ./data/sample_R2.fastq.gz \
-o ./output/clean_fastq/ \
-t 16
Mapping: map reads to genome¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | bwa mem |
-SP5M -t <threads> <idxbase> <in1.fq> <in2.fq> |
| Input | clean paired FASTQ files | ./output/clean_fastq/clean_test_sample_R1.fastq.gz ./output/clean_fastq/clean_test_sample_R2.fastq.gz |
| Output | BAM file | ./output/bwa_output/test_sample.bam |
We use bwa mem with -SP5M
parameters to map cleaned read pairs to reference genome. The -SP5M
options are very
important, which allows split alignments. The output BAM file name is based on the -N
argument of imargi_wrapper.sh
,
and the name will be kept in next step.
# bwa mem mapping
bwa mem -t 16 -SP5M ./ref/bwa_index/bwa_index_GRCh38 \
./clean_fastq/clean_test_sample_R1.fastq.gz \
./clean_fastq/clean_test_sample_R2.fastq.gz |\
samtools view -Shb -@ 7 - >./bwa_output/test_sample.bam
Parsing: parse mapped read pairs to valid RNA-DNA interactions¶
| Type | Description/Tool | Files/Key Parameters |
|---|---|---|
| Tool | imargi_parse.sh |
-r <ref_name> -c <chromSize_file> -R <restrict_frags_file> -b <bam_file> -o <output_dir> -t <threads> |
| Input | BAM file | .output/bwa_output/test_sample.bam |
| Output | .pairs file | ./output/final_test_sample.pairs.gz |
The imargi_parse.sh
is a wrapper script to parse interaction pairs from BAM file, and do de-duplication and filtering,
then output the final .paris file of valid RNA-DNA interaction map, and by default the intermediate files are also kept
in ./output/parse_temp
. There are also some arguments can be used to tweak the thresholds of parsing and filtering.
You can use the default value or customize them.
-Q <min_mapq>
: The minimal MAPQ score to consider a read as uniquely mapped. [default: 1]-G <max_inter_align_gap>
: Read segments that are not covered by any alignment and longer than the specified value are treated as “null” alignments. [default: 20]-O offset_restriction_site
: Offset allowed for restriction fragment filter. [default: 3]-M <max_ligation_size>
: Selected sequencing fragment size. [default: 1000]
The command of parsing used in the imargi_wrapper.sh
is:
imargi_parse.sh \
-r hg38 \
-c ./ref/hg38.chrom.sizes \
-R ./ref/AluI_frags.bed.gz \
-b ./output/bwa_output/test_sample.bam \
-o ./output \
-t 16 \
-Q 1 \
-G 20 \
-O 3 \
-M 1000 \
-d false \
-D $output_dir/parse_temp
The core tool used in imargi_wrapper.sh
is pairtools
. Here are some brief descriptions of the usages of pairtools
in our work. If you want to know more, please check the GitHub repo and
documentation of pairtools
.
pairtools parse
: Parse the types of read pairs based on their mapping results. Output a .pairs file. The parameters--add-columns cigar
,--no-flip
,--walks-policy 5any
are required for iMARGI data, don’t change it unless you know what you want to do.pairtools dedup
: Mark and de-duplications in the.pairs
file.pairtools select
: Filter out those read pairs which are marked as duplications, multiple mappings and 5’ most end was not unique mapped. We used a long filter string designed for iMARGI, don’t change it.
There will be pipelineStats_xx.log
file in the output directory. It reports some basic statistics of the parsing
results, such as total number of read pairs, unique mapped read pairs and valid RNA-DNA interactions.
Filtering strategies
Besides of filtering out unmapped, duplicated and multiple mapped read pairs, we also use restriction fragments information for filtering out those potential un-ligated RNA or DNA fragment contaminations. We check the 5’ end of mapped read pairs R1 (RNA-end) and R2 (DNA-end), there are three cases based on the relative position of 5’ end and the nearest restriction digestion site, which are denoted as dist1 and dist2, and we have a threshold of offset:
- dist2 > offset: R2 (DNA-end) is not sequenced from a proper restriction fragment, so the sequencing fragment might be un-ligated RNA
- dist2 < offset & dist1 < offset: sequencing fragment might be a un-ligated DNA if the distance of R1 and R2 is less than the maximum sequencing fragment size and the strands of R1 and R2 are opposite
- dist2 < offset & dist1 > offset: proper RNA-DNA ligation
The filtering argument used in pairtools is:
"regex_match(pair_type, \"[UuR][UuR]\") and \ dist2_rsite != \"!\" and \ (abs(int(dist2_rsite)) <= "$offset") and \ (not (chrom1 == chrom2 and \ abs(int(dist1_rsite)) <= "$offset" and \ strand1 != strand2 and \ ((strand1 == \"+\" and strand2 == \"-\" and int(frag1_start) <= int(frag2_start) and \ abs(int(frag2_end) - int(frag1_start)) <= "$max_ligation_size") or \ (strand1 == \"-\" and strand2 == \"+\" and int(frag1_start) >= int(frag2_start) and \ abs(int(frag1_end) - int(frag2_start)) <= "$max_ligation_size"))))"
Although we set several filtering strategies, they still cannot filter out all ‘contaminations’. So we use genomic
distance as a final filter. Filtering out those short-range interactions is better for further analysis. We provide a
tool imargi_distfilter.sh
to do genomic distance filter. Please read more in the
further analysis instructions.
Output Files¶
All The Output File List¶
The output files are all in the output directory ~/imargi_example/output
.
The final RNA-DNA interaction map is the final_test_sample.pairs.gz
file, which is in a compressed .pairs
format and
can be used for further analysis. There is a pipeline summary log file, pipelineStats_test_sample.log
in the output
directory, which reports the sequence mapping QC result (pass or failed), total processed read pairs number, BWA mapping
stats and number of valid RNA-DNA interaction in the final .pairs.gz
file. All other intermediate result files are
also kept in several sub-folders of the output directory.
Besides, if we used the minimum input requirements, the pipeline will automatically generated several required reference files in
the same directory of reference genome instead of the output directory, including chromosome sizes, bwa index and AluI
digestion fragments. When processing new dataset, you can reuse these new generated reference files with corresponding
arguments instead of only using -g
argument, which will save you some time and disk space.
The final tree structure of the output directory is shown below.
└── output
├── bwa_output
│ ├── bwa_log_test_sample.txt
│ └── test_sample.bam
├── clean_fastq
│ ├── clean_test_sample_R1.fastq.gz
│ └── clean_test_sample_R2.fastq.gz
├── parse_temp
│ ├── dedup_test_sample.pairs.gz
│ ├── drop_test_sample.pairs.gz
│ ├── duplication_test_sample.pairs.gz
│ ├── sorted_all_test_sample.pairs.gz
│ ├── stats_dedup_test_sample.txt
│ ├── stats_final_test_sample.txt
│ └── unmapped_test_sample.pairs.gz
├── final_test_sample.pairs.gz
└── pipelineStats_test_sample.log
The table below briefly described all the output files.
| Type | Example Items | Directory (relative to output directory) | Format | Description |
|---|---|---|---|---|
| Cleaned FASTQ | clean_test_sample_R1.fastq.gz clean_test_sample_R2.fastq.gz |
./clean_fastq |
paired clean FASTQ | Output of cleaning step, the two random bases at 5' end of R1 were removed |
| Sequencing reads alignments | test_sample.bam |
./bwa_output |
BAM | Output of bwa mapping step |
| BWA mapping log | bwa_log_test_sample.txt |
./bwa_output |
text | BWA mapping log file |
| Intermediate parsing results | sorted_all_test_sample.pairs.gz |
./parse_temp |
.pairs | Sorted all the parsed read pairs |
| Intermediate parsing results | dedup_test_sample.pairs.gz |
./parse_temp |
.pairs | Parsed read pairs after deduplication |
| Intermediate parsing results | duplication_test_sample.pairs.gz |
./parse_temp |
.pairs | Duplicated pairs |
| Intermediate parsing results | unmapped_test_sample.pairs.gz |
./parse_temp |
.pairs | Unmapped pairs (including multiple mapping) |
| Intermediate parsing results | drop_test_sample.pairs.gz |
./parse_temp |
.pairs | Pairs filtered out filtering step |
| Intermediate parsing results | stats_dedup_test_sample.txt stats_final_test_sample.txt |
./parse_temp |
text | pairtools intermediate stats report |
| Final output | final_test_sample.pairs.gz |
./ |
.pairs | Final output of valid RNA-DNA interactions |
| Pipeline stats log | pipelineStats_test_sample.log |
./ |
text | Sequence mapping QC result and stats report |
The iMARGI Pipeline Output .pairs
Format¶
The default final output file is final_test_sample.pairs.gz
which is in .pairs format. .pairs file format is designed
by 4DN DCIC. You can read its
specification document.
In iMARGI Pipeline, we add some more data columns to the default .pairs format files.
The data column descriptions are listed in the table below. (All the genomic coordinates in .pairs file are 1-based.) The first 7 columns are standard information, 8-18 are extra information. All these column names are reserved.
| column order | name | datatype | description |
|---|---|---|---|
| 1 | readID | string | read ID |
| 2 | chrom1 | string | mapping chromosome of R1 (RNA-end) |
| 3 | pos1 | int | 5' end mapping position of R1 (RNA-end) |
| 4 | chrom2 | string | mapping chromosome of R2 (DNA-end) |
| 5 | pos2 | int | 5' end mapping position of R2 (DNA-end) |
| 6 | strand1 | +/- | mapping strand of R1 (RNA-end), the actual cDNA strand is opposite |
| 7 | strand2 | +/- | mapping strand of R2 (DNA-end) |
| 8 | pair_type | string | pairtools defined pair_type |
| 9 | mapq1 | int | bwa MAPQ value of R1 (RNA-end) alignment |
| 10 | mapq2 | int | bwa MAPQ value of R2 (DNA-end) alignment |
| 11 | cigar1 | string | bwa cigar of R1 (RNA-end) alignment |
| 12 | cigar2 | string | bwa cigar of R2 (DNA-end) alignment |
| 13 | frag1_start | int | start position of assigned restriction fragment of R1 (RNA-end) |
| 14 | frag1_end | int | end position of assigned restriction fragment of R1 (RNA-end) |
| 15 | dist1_rsite | int | distance between 5' end mapping position of R1 and the nearest restriction digestion site position |
| 16 | frag2_start | int | start position of assigned restriction fragment of R2 (DNA-end) |
| 17 | frag2_end | int | end position of assigned restriction fragment of R2 (DNA-end) |
| 18 | dist2_rsite | int | distance between 5' end mapping position of R2 and the nearest restriction digestion site position |
The pipeline summary log file¶
When the pipeline finished, it will also generate a simple pipeline summary log file, named as pipelineStats_*.log
. It
reports the sequencing mapping QC result at the first line. If it shows “Sequence mapping QC failed”, your data might
have critical problem for further analysis. The other lines show stats number of total read pairs,
non-dup unique mapping read pairs, final valid read pairs and so on.
Here we describe each line of the log file (TAB separated text file).
Line 1:
Sequence mapping QC
It’s the sequencing mapping QC result, which can be
passed
orfailed
). It’s concluded based on the value of line 2 and 3. Only when both values of line 2 and 3 are greater than threshold 0.5, it can be concluded aspassed
.Line 2:
(#unique_mapped_pairs + #single_side_unique_mapped)/#total_read_pairs
Mapping rate of at least one side of read pairs uniquely mapped to genome. It can be calculated by dividing the sum of line 5 and line 6 by line 4.
Line 3:
#total_valid_interactions/#unique_mapped_pairs
The ratio of retained read pairs of unique mapped read pairs after de-duplication and filtering. It can be calculated by dividing line 8 by line 6.
Line 4:
total_read_pairs
Total number of read pairs in the FASTQ data.
Line 5:
single_side_unique_mapped
Number of single side unique mapped read pairs.
Line 6:
unique_mapped_pairs
Number of unique mapped read pairs (both two side unique mapped).
Line 7:
non_dup_unique_mapped_paris
Number of non-duplicated unique mapped read pairs.
Line 8:
total_valid_interactions
Number of final output valid read pairs (RNA-DNA interactions).
Line 9:
inter_chr
Number of inter-chromosomal interacted read pairs (two ends mapped to different chromosomes).
Line 10:
intra_chr
Number of intra-chromosomal interacted read pairs (two ends mapped to the same chromosome).
Here is the output pipelineStats_test_sample.log
file in our example.
Sequence mapping QC passed
(#unique_mapped_pairs + #single_side_unique_mapped)/#total_read_pairs 0.785859
#total_valid_interactions/#nondup_unique_mapped_pairs 0.768195
total_read_pairs 900000
single_side_unique_mapped 3342
unique_mapped_pairs 703931
nondup_unique_mapped_pairs 694706
total_valid_interactions 533670
inter_chr 244208
intra_chr 289462


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Employment passes 2.3 million for first time
Numbers grow by 2.4% in third quarter
by Eoin Burke-KennedyEmployment in the Irish economy has surpassed 2.3 million for the first time.
According to the Central Statistics Office (CSO), the number of people employed here grew by 53,700 (2.4 per cent) to 2.32 million in the third quarter of 2019.
This is around 80,000 higher than the boom time high of 2.23 million recorded in the fourth quarter of 2007 and reflects the current strength of the economy.
However, the CSO cautioned that the State has a bigger population now and a larger workforce than in 2007 and that the employment rate – the proportion of adults with jobs – is still below the pre-crash level.
Nonetheless the figures, contained in the CSO’s latest Labour Force Survey, show that employment in the economy has risen for 29 consecutive quarters since 2013, the official low point of the crash.
The survey showed employment increased in nine of the 14 economic sectors over the year with largest increase (+12.9 per cent +13,000) recorded in the financial, insurance and real estate sector.
The largest decrease was in agriculture, forestry and fishing, which fell by 5.2 per cent or 5,500.
The headline rate of unemployment for the third quarter was put at 4.9 per cent, equating to 128,000 people.


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DITA Open Toolkit 3.4 Release Notes
DITA Open Toolkit 3.4.1 is a maintenance release that fixes issues reported in DITA-OT 3.4, which includes an official Docker container image, a separate plug-in for PDF indexing, a new option to skip HTML5 cover pages, and initial support for project files that allow you to define multiple deliverables in advance, and publish them all at once.
DITA-OT releases follow
semantic versioning guidelines. Version numbers use the
major.minor.patch
syntax, where
major versions may include incompatible API changes, minor versions add
functionality in a backwards-compatible manner and patch versions are maintenance releases
that include backwards-compatible bug fixes.
Requirements
- You can download the Oracle JRE or JDK from oracle.com/technetwork/java under commercial license.
- OpenJDK is a free open-source implementation of Java available from adoptopenjdk.net.
- Amazon Corretto is an OpenJDK distribution from aws.amazon.com/corretto.
DITA-OT 3.4.1
DITA Open Toolkit 3.4.1 is a maintenance release that includes the following bug fixes.
- Earlier versions of DITA-OT created extra files in the output folder when the DITA 1.3
<dvrResourcePrefix>
or<dvrResourceSuffix>
elements were used to rename filtered topics. When conditions on topic references within a branch filtered out one or more copies of those files, the renamed resources were removed from the ToC, but still copied to the output folder. The branch filtering process has been revised to ensure those filtered copies are no longer created. In some (but not all) cases, this also resolves a related issue where an extra copy of the file was created in the output folder with the original file name. #2980, #3411 - Due to an omission in the DITA 1.3 shell files provided by the OASIS DITA Technical Committee, classification maps based on the XML Schema Definition were considered invalid. The error was reported to the TC and resolved in the official OASIS repository and in the grammar files bundled with DITA-OT. #3202, #3426
- The RELAX NG schema required to validate XML project files was missing in the 3.4 distribution package. The project.rnc file is now provided in the resources folder of the DITA-OT installation. #3409, #3410
- When the bundled Apache™ Formatting Objects Processor (FOP) was upgraded to version 2.4 for DITA-OT 3.4, a required library reference was omitted, which prevented embedded SVG images from appearing in PDF output. The library has been restored to the distribution package to ensure that SVGs are rendered as expected. #3414, #3419
- The bundled Jackson data binding library was updated to version 2.10.1 to resolve several vulnerabilities reported in previous versions. #3420, #3421
- With DITA-OT 3.1.3 or later, generating PDFs from maps with index terms with the RenderX XEP
processor throws “no entries for index key” errors and fails to generate PDF files. Index
processing has been corrected to take the new
@indexid
attribute into account, which resolves the error and allows builds to complete successfully. #3447, #3450, #3455 - The license for the bundled ICU4J library has been updated to the latest version. #3444, #3451, #3454
For additional information on the issues resolved since the previous release, see the 3.4.1 milestone and changelog on GitHub.
DITA-OT 3.4 released November 9, 2019
DITA Open Toolkit Release 3.4 includes an official Docker container image, a separate plug-in for PDF indexing, a new option to skip HTML5 cover pages, and initial support for project files that allow you to define multiple deliverables in advance, and publish them all at once.
Docker container image
Docker is a platform used to build, share, and run portable application containers. As of version 3.4, the DITA-OT project provides an official Docker container image that includes everything you need to run the toolkit and publish DITA content from a containerized environment. #3358
New indexing plug-in
DITA-OT 3.4 extracts the PDF indexing code to a separate org.dita.index plug-in, and
adds a new depend.org.dita.pdf2.index
extension point that can be used to add custom index
processing targets to PDF output.
The built-in index processing has been disabled and deprecated. If you have overridden index processing via
the transform.topic2fo
target in the past, you can set the new
org.dita.index.skip property to yes and re-enable the
transform.topic2fo.index
target with <feature
extension="depend.org.dita.pdf2.index" value="transform.topic2fo.index"/>
in your plug-in
configuration.
Skip HTML5 cover pages
The HTML5 transformation supports a new property that determines whether a table of contents file should be generated to link to the other topics from the input map. The html5.toc.generate parameter is set to yes by default, and creates a cover page named index.html as with previous versions of DITA-OT. If you’re using the nav-toc parameter to embed navigation links in topics, you can set html5.toc.generate to no to stop creating the extra file. #3301
Project files
DITA-OT 3.4 introduces new project files to define publication projects with multiple deliverables. Projects specify a context, output folder, and publication for each deliverable. A re-usable context groups source files and filters, and a publication defines an output format with transformation parameters. You can pass a project file to the dita command to publish multiple deliverables at once.
Project files may be defined in one of three formats: XML, JSON, or YAML. The XML format can be validated with a RELAX NG schema provided in the resources folder of the DITA-OT installation (project.rnc).
#3243, #3256, #3262, #3265, #3268, #3269, #3276, #3298, #3300, #3382, #3388, #3394
Enhancements and changes
In addition to the highlights mentioned above, DITA Open Toolkit Release 3.4 includes the following enhancements and changes to existing features:
- The original preprocessing and map-first preprocessing pipelines have been simplified to process only the merged root map, where previous versions would redundantly process all DITA maps. #3250
- Conref processing has been updated to resolve content references to specializations of the referencing element #3264
- The obsolete build_demo.xml script that was previously used to build Ant samples has been removed from the source code repository. (The file was removed from distribution packages with version 2.1.) #3288
- Ant scripts have been refactored to simplify
<condition>
elements with<isset>
guards to set properties with plain<property>
declarations instead. #3297 - The logging level for Apache HTTP Client libraries has been reduced to
INFO
to quiet the default log output. This information can be displayed if necessary by enabling verbose logging. #3307, #3308 - The
ConrefPushParser
has been converted from a SAX filter to a DOM filter. #3315 - Travis CI build stages are now used to run tests and deployments in parallel to speed up continuous integration builds. #3329
- Several bundled dependencies have been upgraded to the latest versions.
- XSLT error messages now include location information in more cases to make it easier to find the source of the problem. #3334, #3339, #3341
- DITA-OT 3.4 no longer includes the TocJS and troff transformation plug-ins in the default
distribution.
#3363,
#3364
Note: If necessary, legacy plug-ins may be re-installed from earlier DITA-OT distributions, but they are no longer actively maintained or supported by the core toolkit committers. The source code is available on GitHub for anyone interested in maintaining the plug-ins for use with future toolkit versions.
- The LwDITA plug-in has been updated to version 2.3.2, pulling in a number of fixes for Lightweight DITA processing, including support for absolute links and strikethrough in Markdown input, and updated processing for escaped characters and nested blocks in Markdown output. #3371, #3408
- The args.logdir parameter (deprecated since DITA-OT 2.5) has been removed. To write the log to a file, use dita --logfile=file or ant -l file and specify the path to the log file. #3398, #3399
- The source code for the DITA 1.1 and 1.2 plug-ins has been removed from the core repository and extracted to dedicated code repositories. The plug-ins themselves remain available in the DITA-OT 3.4 distribution package. #3401
Bugs
DITA Open Toolkit Release 3.4 provides fixes for the following bugs:
- Several issues have been resolved in the PDF rendering of a generated index:
- To work around an open issue with Apache Formatting Objects Processor
FOP-2520, DITA-OT 3.4 uses
<fo:block>
instead of<fo:wrapper>
to create the destinations for index links. In previous versions of DITA-OT, index terms that appeared in source files between section titles and paragraph content (and several other places) created empty space in PDF output. #2455, #2914, #3381 - When publishing to PDF with Antenna House Formatter, destination anchors for index links now
use
<fo:wrapper>
instead of<fo:inline>
. In previous versions of DITA-OT, index terms that appeared in source files between section titles and other section content created empty space in PDF output. #3042, #3379 - Index links are now created correctly when entries have subterms. In previous versions,
terms with multiple
<index-see-also>
subterms failed to generate links for all but the first reference, and dropped all instances of a term if even one instance had a sub-term, an<index-see>
or<index-see-also>
child. #3314, #3320, #3373 - References to unavailable
<index-see>
terms are filtered from the final index. Previous versions would create invalid links if the target terms were not available in the current publication context. #3391
- To work around an open issue with Apache Formatting Objects Processor
FOP-2520, DITA-OT 3.4 uses
- Cross-reference links to other topics from short descriptions no longer cause build errors. #3078, #3324
- In earlier versions, incorrect parameters passed to the dita command could cause the build to fail with a NullPointerException. The Java code has been updated to issue an appropriate error message in these cases, instead of crashing the build. #3360
Contributors
DITA Open Toolkit Release 3.4 includes code contributions by the following people:
- Jarno Elovirta
- Robert D Anderson
- Roger Sheen
- Radu Coravu
- Eliot Kimber
- Toshihiko Makita
For the complete list of changes since the previous release, see the changelog on GitHub.
Documentation updates
The documentation for DITA Open Toolkit Release 3.4 provides corrections and improvements to existing topics, sample project files in the docsrc/samples/ folder, a Glossary, PDF index, and new information in the following topics:
For additional information on documentation issues resolved in DITA Open Toolkit Release 3.4, see the 3.4 milestone in the documentation repository.
DITA Open Toolkit Release 3.4 includes documentation contributions by the following people:
- Roger Sheen
- Lief Erickson
- Jarno Elovirta
- Robert D Anderson
- Eliot Kimber
- Ursula Kallio
- Jason Fox
- Radu Coravu
For the complete list of documentation changes since the previous release, see the changelog.


Module ringo/buffer
A simple text Buffer class for composing strings.
Buffer (...)
A Buffer class for composing strings. This is implemented as a simple wrapper around a JavaScript array.
Parameters
| ... | initial parts to write to the buffer |
Buffer.prototype.digest (algorithm)
Get a message digest on the content of this buffer.
Parameters
| algorithm | the algorithm to use, defaults to MD5 |
Buffer.prototype.forEach (fn)
Call function fn
with each content part in this buffer.
Parameters
| fn | a function to apply to each buffer part |
Buffer.prototype.length
A read-only property containing the number of characters currently contained by this buffer.
Buffer.prototype.toString ()
Return the content of this buffer as string.
Buffer.prototype.write (...)
Append all arguments to this buffer.
Parameters
| ... | variable arguments to append to the buffer |
Returns
| this buffer object |
Buffer.prototype.writeln (...)
Append all arguments to this buffer terminated by a carriage return/newline sequence.
Parameters
| ... | variable arguments to append to the buffer |
Returns
| this buffer object |


| << Overview << | ^^ Table of Contents ^^ | >> Writing regression tests >> |
Browser bookmarklet: To install the bookmarklet in your browser's Bookmarks toolbar, go to the BidiChecker Bookmarklet Installation Page. You will find two links labeled "BidiChecker LTR" and "BidiChecker RTL". Dragging each of those links to your Bookmarks toolbar will install a button which, when clicked, runs BidiChecker on the page currently in the browser. The LTR bookmarklet expects the page to have a left-to-right UI; the RTL bookmarklet is for pages with a right-to-left UI.
Source code: The BidiChecker source code can be downloaded from http://code.google.com/p/bidichecker using the following command:
svn checkout http://bidichecker.googlecode.com/svn/trunk/ bidichecker
Source code and unit tests can be found in the src/ subdirectory. This user's guide is in the docs/users_guide subdirectory, with the complete API documentation in docs/jsdoc/. A sample application, along with demonstrations of how BidiChecker can be used to check for bidi errors, can be found in samples/reviews/.
The lib/ subdirectory contains a self-contained, deployable installation of BidiChecker. If you copy this directory to a web server, you can easily run BidiChecker either from automated unit tests or via the browser bookmarklet. The directory contains:
BidiChecker source code uses the Closure Library, an open-source library of useful Javascript modules. If you want to run a modified version of BidiChecker or run BidiChecker's own unit tests, you will need to install a copy of the Closure Library on your system. To do that, run the following command from the same working directory as you ran the above command:
svn checkout http://closure-library.googlecode.com/svn/trunk/ bidichecker/third_party/closure-library
BidiChecker does not currently easily support linking with a copy of the Closure Library at a different location. Please note that you do not need to install the Closure Library to use the precompiled version of BidiChecker.
For an example of how to use BidiChecker with the Closure Library, see samples/reviews/reviews_closure_test.html.
The core BidiChecker backend Javascript code is regularly tested on a selection of browsers. The browser bookmarklet has been tested on Firefox and Chrome. It is not currently supported on Internet Explorer prior to version 9.
Regardless, the bidi errors identified by the tool are not platform-specific; the code searches the DOM for errors, and it may find errors which only cause display garbling on browsers other than the one on which it is run. It should not be necessary to run the tool on a particular browser in order to find bidi errors for that browser.
| << Overview << | ^^ Table of Contents ^^ | >> Writing regression tests >> |


Scrollable table
on the
Customers Odata collection
Read more in the
README.md
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Ghana Akan Tribe names are derived from the day of the week and ones gender.
This Javascript application requests for input of birthday and gender and generates the name for the user.


According to the arrest affidavit, the mother of the victim called police to her apartment on Nov.12. She said she saw Darrell Sanders come out of the apartment and her 15-year-old daughter was inside.
She said she walked inside the bathroom and found wet spots on the bed and $25 on the counter. The mother asked her daughter if she had sex with Sanders, and she said yes.
She also said this was the second time she had sex with Sanders. This first time he gave her $90.

Sanders is a police officer for the Veteran's Affairs Hospital. He was being held on $250,000.
He has bonded out of jail the same day he was arrested.
In a statement, The Central Texas Veterans Health Care System called the allegations "abhorrent," and said Sanders has been stripped of his badge.
These allegations are abhorrent, and the Central Texas Veterans Health Care System is taking the appropriate steps to hold this individual accountable.
In the meantime, this individual has been stripped of his badge and is not performing law enforcement duties or interacting with patients.
VA has made clear that it will hold employees accountable when they fail to live up to the high standards Veterans and taxpayers expect, and that's exactly what we're doing in this case.


![](images/8-best-chatbots-2016.PNG)
We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
https://en.wikipedia.org/wiki/Hype_cycle
[![](images/alexa-news-story.png)](http://www.cbs46.com/story/38197149/amazons-alexa-becomes-resource-for-johns-creek)
- 📃 background
- 👋 hello world bot
- 💬 deploy to slack
- ⌨ jSTL bot
- 📲 SMS (twilio)
- 🐞 how to debug
- 💡 advanced calls
# Thank you!
- [gavinr.com](https://gavinr.com)
- [twitter.com/gavinr](https://twitter.com/gavinr)
- [github.com/gavinr/presentations](https://github.com/gavinr/presentations)
# Sources
- https://www.claudiajs.com/
- https://medium.freecodecamp.org/express-js-and-aws-lambda-a-serverless-love-story-7c77ba0eaa35


 Our reconnaissance probes indicate that
5 hostile pigs have entered orbit around our base planet.
Your mission is to destroy them as quickly as possible.
Can you get them before they get you?
If you are ready pressed on GO.
GO
How to Play
You have 3 types of ammunition:-
Bullets:
slow and the least powerful, but you have a lot
and they replenish quickly.
Laser:
very fast and powerful, but replenishes more
slowly.
Missile:
fast and the most powerful, but replenishes very
slowly.
Bullets are set by default.
To select a different one click/touch on the selector panel at
the top left of the screen.
You can control your gun with any combination of mouse,
keyboard or touch.
To review or set keyboard keys go to the keyboard menu.
Press the gun and drag it to the left or the right.
Press anywhere in space and drag left or right;
the gun barrel will follow your mouse or finger.
Let go to fire. The weapon will past through your
release point.
Credits
Game developer:
Brian Akehurst
1 rue BALZAC
91410 DOURDAN, France
Earth image: courtesy NASA
Close
Role of Honnor
GunnerTime
Close
Keyboard Settings
Move Left
ArrowLeft
Move Right
Rotate Left
Rotate Right
Rotate to Center
Fire
Change Weapon
Tab
Press on an item or use the tab key to select, then press any key on
your keyboard to change the value of the selected item.
The Tab key itself is reserved and cannot be used.
Close
Champion Gunner
Congratulations the pigs are repelled.
Close
You Lost
Pigs will invade the planet
Close
The game does not work in portrait mode.
Change orientation to landscape.


-
HTML is a language for describing web pages.
- Stands for Hyper Text Markup Language
- Describes the structure of Web pages using markup
Elements
- Written with a start tag and an end tag, with the content in between:
content
- Elements with no content are called empty elements.
,,
A Simple HTML Document
Attributes
- All HTML elements can have attributes.
- Attributes provide additional information about an element
- Attributes are always specified in the start tag
- Attributes usually come in name/value pairs like: name="value"
This is a link
Attributes used in HTML:
Inline Elements
Normally displayed without line breaks.
  Inline elements are :
content
Italic text
small text
Computer codes
Strong emphasis
Anchor
Line Break
Inline image
Block Elements
Start with a new line, when displayed in a browser.
- The general purpose div container
- Header elements, h1, h2, h3,h4,h5,h6
- Paragraph elements
- Table elements
- Form elements
- List elements(Unordered List and Ordered List)
Headings and Paragraphs
- Six levels of headings
,,
, ,
- "p" tag structure your text into different paragraphs.
Styles
- Every HTML element has a default style
- background color:white
- text color :black
- text-size :12px
- style attribute changes the default style of an HTML element.
- Eg:
Heading
- Result:
Heading
Formatting Elements
- Formatting elements were designed to display special types of text:
-
- Bold
- Strong
- Subscripts
- Superscripts
- Italic
- Emphasis
- Small
- Mark
- Inserted
- Deleted
- Underlined
Comment tags
- Used to insert comments in HTML.
CSS
Cascading Style Sheets
Styling can be in 3 ways:
- Inline - using a style attribute in HTML elements
-
- Internal - using a style element in the HTML head section
-
- External - using one or more external CSS files
-
Hyperlinks
- You can click on a link and jump to another document.
link text
Image
Empty tag
Contains attributes only
Does not have a closing tag
Tables
Lists
- Unordered List
- Ordered List
- Description List
Unordered List
- Apples
- Bananas
- Lemons
- Oranges
Result:
- Apples
- Bananas
- Lemons
- Oranges
Style attribute can be added to an unordered list, to define the style of the marker:
- Apples
- Bananas
- Lemons
- Oranges
Result:
- Apples
- Bananas
- Lemons
- Oranges
Ordered List
- Apples
- Bananas
- Lemons
Result:
- Apples
- Bananas
- Lemons
A type attribute can be added to an ordered list, to define the type of the marker:
- Apples
- Bananas
- Lemons
Result:
- Apples
- Bananas
- Lemons
Description List
List of terms, with a description of each term
- Coffee
- - black hot drink
- Milk
- - white cold drink
Forms
- Used to collect user input.
- Input element is the most important form element.
- It has many variations, depending on the type attribute.
Select Element (Drop-Down List)
- Option elements defines the options to select.
- The list will normally show the first item as selected.
- You can add a selected attribute to define a predefined option.
What is New in HTML5?
Semantic Elements
- header
- footer
- nav
- article
- section
- aside
Form controls
- number
- email
- date
- time
- color
HTML5 comes with a lot of flexibility and supports the following:
- Uppercase tag names.
-
- Quotes are optional for attributes.
- Attribute values are optional.
- Closing empty elements are optional.
HTML 'canvas' and
' SVG' Element
- It is a container for canvas graphics.
- An HTML canvas is a rectangular area on an HTML page.
- Canvas has several methods for drawing paths, boxes, circles, text, and graphic images.
- svg stands for Scalable Vector Graphics
- svg is used to define graphics for the Web
- svg element is a container for SVG graphics.
,


Intana was established as a professional wedding makeup artist in July 2020. but I did makeup since 2017 our business started way back in 2000. We are currently one of the most prominent vendors in our field.
It's a broader card with text below as a natural lead-in to extra content. This content is a little longer.
Last updated 3 mins ago