"Some treasures aren't worth finding, let alone stealing."
Dack Fayden is a human mage from Drakeston, a village on the plane of Fiora. As a youth, Dack and his friend Marsh were adept mages who excelled at their abilities but lacked judgment. One night, their genius got the best of them and they picked a fight with brutes, resulting in the death of Marsh. In that moment, Dack’s spark ignited and he became a Planeswalker.
Dack soon found he could walk the planes and sought out challenges that could both test his abilities and line his pockets. On the plane of Alkabah, Dack got his hands on a cursed artifact, which resulted in his arrest. By the law of that society, his right hand was stained red, forever branding him a thief. He was eventually able to return to Fiora, but in his absence, another Planeswalker named Sifa Grent had massacred Drakeston and all those Dack cared for.
Dack then turned to use psychometry—the ability to absorb the magic, memories, and uses of an artifact—to track Sifa. His psychometry allowed him to follow her trail from plane to plane, even through the Blind Eternities. He survived his final encounter with Sifa on Ravnica, and was forced to realize that as a Planeswalker, he could help or hurt more than an average person should be able. Although Dack now considers Ravnica home, he will never forget what happened to his people on Fiora.


A good friend of mine had taken morning glory seeds for the first time (about 25 or so seeds) and highly suggested it to me. He said that it was a very pleasant experience on that low dosage, and I decided to try it. He later suggested taking a low dosage before going to a higher dosage in order to get myself accustomed to it.
The seeds were easy enough to obtain, I found them at the local grocery store in the floral department. The first time I took them was during the day, I chewed up 25 seeds. After about an hour, I experienced a pleasant warm feeling, curiosity about things that I am not usually curious about (such as the grass, the feeling of my own body, etc). I also had some increased perception, etc. Patterns and textures, for example, were very pronounced, and almost took on a sort of 'character.'
About 2 weeks later (two nights ago), I had the chance to try a higher dosage. I counted out 25 seeds at a time and chewed them up until I had ingested 100 seeds. The taste became unpleasant after about the second handful, but I never had any feelings of nausea. About a half hour after I chewed them, I began feeling that warmth from before, as well as an increased sense of touch. My hands felt soft to the touch. About fifteen minutes later that nice warmth intensified, and was accompanied by a very calm feeling that pervaded me, all of life's pressures began to fade away. I began to see a sort of flashing light effect in everything around me, and everything seemed brighter than usual. I decided to lie down on my bed, I felt like I was floating, detached from the surface of the bed. I closed my eyes and saw some lights dancing around, sort of beckoning me toward them.
About an hour and a half after I had first taken the seeds, I got up to go outside. I didn't have much trouble walking, but I felt like I was in no rush, I just drifted along down the hallway, through the kitchen, and out into the backyard. It was dark, with the clouds in the sky illuminated by the moon and the streetlights. Everything looked so beautiful and serene. I looked up at the branches of the leafless tree (it was early springtime, before the leaves began to bud), the branches seemed to point to all of the universe. The entirety of existence seemed to all connect to that tree. I walked through the grass, and felt like I was part of all of the life in it. Walking over some gravel, I felt like they were alive, sort of moving beneath me. This sounds unnerving, but it was actually very pleasant, and made me feel sort of like I was a part of it all.
I went inside, put on some Shpongle and lay down on my bed. Once again I felt like I was floating. I closed my eyes again, no lights this time, but it drew me into a strong sense of calm. A friend called me, and I talked to her with not much of a problem. My speech came out a bit funny, and she seemed to think I was completely gone. But I wasn't completely gone, I was more 'with it' than I had ever been in my life.
(About 3 hours into my trip): I went outside again and leaned against the aforementioned tree. I moved my hands along the trunk and along the branches. I began to feel almost as if I were part of the tree. I was in a position that would have normally felt uncomfortable, completely connected to the tree, but it felt completely natural. I closed my eyes and my consciousness began to 'meld' with this tree which was a part of the entirety of existence and life in the universe. My self became part of the tree, and it became part of my self. I imagine that I stood there for a half hour or so, my spirit in union with that of the tree.
I'm not quite sure how I regained my self from there, but I wound up going back inside. At this point the feelings of warmth were starting to fade, and I knew that I was on my way back to reality. I turned out the lights in my bedroom and put on Pink Floyd's Dark Side of the Moon, one of my favorite albums, then laid down and let myself sink into the pleasure of the music, it seemed to speak to me in ways that it never had before. I was very serene. Once the cd was over, I stood up. The feelings of warmth were gone, everything was 'normal' again. My trip was over.
This trip gave me some great insight into my place in the universe. I feel like I am part of all of the life around me, a feeling that I had never truly felt before. The experience opened my mind to new thoughts, new perspectives, and new insight. I have read reports that show significantly less power in their LSA experience. I'd imagine my weight and the potency of the seeds that I had may have had something to do with it. This was my first experience with psychoactives. It has definately changed my perspective on them, and I do plan on trying different things in the future.
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.


Across: 1. Little person has no time for little creature (5) 4. State shares heart with another state (8) 8,23 Dn. See if TV guru has hole constructed for writing of 5 21 (14 4) 10. Thank you! Some idea about writing! (8) 11. Procurer accepts hollow lure - a superficial prominence (6) 12. Limited amateur actors on the first tentative step of the ladder (9) 15. Vegetation seen at front of house by boundary (5) 17. On one occasion, University was included in measure (5) 18. Refuses to eat, embracing crazy core prophecies (9) 19. Selected, perhaps, to be locked up (6) 21. see 5 Down 24. Boss stunned Peter in dancing (14) 25. Banner made with mad haste (8) 26. Shots fired - ones of vital concern to parasites (5) Down: 1. Terrible harm in topics framing people in a bad light (12) 2. They help 16 with figures and are spoken of as potential kings (9) 3. The 'G is animated about third of third, with 23 more than 3 (5) 4. Bad start - four fake blades (9) 5,21 Ac. Hoosier who wrote letters to TV guru? Not Ken! (4 8) 6. Blasted Chile into distant past (9) 7. Maker stomps out odd characters, as he tells cautionary tales (5) 9. Set since East deployed forces (12) 13. "As hot as it gets" trial draws in crazy diner (9) 14. Choked on return of old cloth, decomposed (9) 16. Creative types who make bills disappear perhaps? (9) 20. A place to let off steam, such as a U.N. building? (5) 22. Third of third, it follows number 3 (5) 23. see 8 Across


{% if registeredOfficeAddress is defined %}
|
Delivery Address {% if 'addressChanged' in registeredOfficeAddress.deliveryAddress.actions %}{{ labelNew() }}{% endif %}
{{ registeredOfficeAddress.deliveryAddress.streetAddress }}
{{ registeredOfficeAddress.deliveryAddress.streetAddressAdditional }}
{{ registeredOfficeAddress.deliveryAddress.addressCity }}
{{ registeredOfficeAddress.deliveryAddress.addressRegion }}
{{ registeredOfficeAddress.deliveryAddress.postalCode }}
{{ registeredOfficeAddress.deliveryAddress.addressCountry }}
{{ registeredOfficeAddress.deliveryAddress.deliveryInstructions }}
|
Mailing Address {% if 'addressChanged' in registeredOfficeAddress.mailingAddress.actions %}{{ labelNew() }}{% endif %}
{{ registeredOfficeAddress.mailingAddress.streetAddress }}
{{ registeredOfficeAddress.mailingAddress.streetAddressAdditional }}
{{ registeredOfficeAddress.mailingAddress.addressCity }}
{{ registeredOfficeAddress.mailingAddress.addressRegion }}
{{ registeredOfficeAddress.mailingAddress.postalCode }}
{{ registeredOfficeAddress.mailingAddress.addressCountry }}
{{ registeredOfficeAddress.mailingAddress.deliveryInstructions }}
|


Teachers and parents can create their own Augmented Reality experience with little to no programming knowledge. It's as simple as creating a slide show presentation!
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AR Experience.
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This is a holiday town close to the border with Croatia. Whilst the town itself is nothing special, there are good marina and repair facilities here. In fact Marina Portoroz was the first marina built in Slovenia back in 1974. It is very large, with more than 1000 berths.
Position 45°30.5'N, 13°35.7'E.
There are customs and immigration in Piran.
The marina for visiting yachts is to sta'bd as you come through the entrance. Not an easy place for a multihull to fit in. Berthing is stern-to with a pile for the bow-line set off the dock. Careful manoevuring is required.
Anchoring is not permitted here.
This is a well-sheltered spot and a safe place to leave a boat during the winter.
Last updated May 2016.


Shows multi-line text and text wrapping with Text elements. It also uses DisplayObject.getBounds() to draw a background for the text.
Text
DisplayObject.getBounds()


A number is rational if it can be written as the ratio of two whole numbers.
eg 2/5 is rational but e is not.
We use the symbol Q for the set $ \{ \frac{\mathrm{n}}{\mathrm{m}} | \mathrm{n} \in \mathbb{Z} , \mathrm{m} \in \mathbb{Z} \; \mathrm{and} \; \mathrm{m} \neq 0 \} . $


Growthed black Gram
Harvest
5000 kg
Jan 01
3000 kg Black gram divided
stone removed
packing
JAN 05
2600 Kg checking and divide the quality wise
skin removed
Kg
black gram
kg
broken gram
Transport
Broken gram
1 Kg


Click the Play/Pause Button
Hover Over any Country to check the number of Cases at that Date
Select Country To View Historical Time Series of Cases/Deaths/Recovered
Choose your country
World
Submit


|
ReactESP 2.1.0
Asynchronous programming for the ESP microcontrollers
|
TimedReactions are called based on elapsing of time. More...
#include <ReactESP.h>
Public Member Functions | |
| TimedReaction (const uint32_t interval, const react_callback callback) | |
| Construct a new Timed Reaction object. More... | |
| TimedReaction (const uint64_t interval, const react_callback callback) | |
| Construct a new Timed Reaction object. More... | |
| virtual | ~TimedReaction () |
| bool | operator< (const TimedReaction &other) |
| Return the current time since the device restart in microseconds. More... | |
| void | add (ReactESP *app=nullptr) override |
| void | remove (ReactESP *app=nullptr) override |
| uint32_t | getTriggerTime () |
| uint64_t | getTriggerTimeMicros () |
| bool | isEnabled () |
| virtual void | tick ()=0 |
| Public Member Functions inherited from reactesp::Reaction | |
| Reaction (react_callback callback) | |
| Construct a new Reaction object. More... | |
Protected Attributes | |
| const uint64_t | interval |
| uint64_t | last_trigger_time |
| bool | enabled |
| ReactESP * | app_context = nullptr |
| Protected Attributes inherited from reactesp::Reaction | |
| const react_callback | callback |
TimedReactions are called based on elapsing of time.
Definition at line 47 of file ReactESP.h.
|
inline |
Construct a new Timed Reaction object.
| interval | Interval or delay for the reaction, in milliseconds |
| callback | Function to be called when the reaction is triggered |
Definition at line 62 of file ReactESP.h.
|
inline |
Construct a new Timed Reaction object.
| interval | Interval, in microseconds |
| callback | Function to be called when the reaction is triggered |
Definition at line 73 of file ReactESP.h.
|
inlinevirtual |
Definition at line 79 of file ReactESP.h.
|
overridevirtual |
Implements reactesp::Reaction.
Definition at line 28 of file ReactESP.cpp.
|
inline |
Definition at line 83 of file ReactESP.h.
|
inline |
Definition at line 84 of file ReactESP.h.
|
inline |
Definition at line 85 of file ReactESP.h.
| bool reactesp::TimedReaction::operator< | ( | const TimedReaction & | other | ) |
Return the current time since the device restart in microseconds.
Returns the time since the device restart. Even though the time is in microseconds, a 64-bit integer is all but guaranteed not to rewrap, ever.
Definition at line 23 of file ReactESP.cpp.
|
overridevirtual |
Implements reactesp::Reaction.
Definition at line 37 of file ReactESP.cpp.
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pure virtual |
Implements reactesp::Reaction.
Implemented in reactesp::DelayReaction, and reactesp::RepeatReaction.
|
protected |
Definition at line 53 of file ReactESP.h.
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protected |
Definition at line 51 of file ReactESP.h.
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protected |
Definition at line 49 of file ReactESP.h.
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protected |
Definition at line 50 of file ReactESP.h.


Enter the managed identity Client ID.
You can get this information from the Azure portal.
This is only needed if there are multiple identities assigned to the resource this is running on.


{% endblock %}
{% block main_content %}
{% with tutorial_content_type as node_content_type %}
{% with tutorial_model as model %}
{% with tutorial as node %}
{% with "standard" as vote_class %}
{% include "django_multivoting/standard_vote.html" %}
{% endwith %}


A sweet and refreshing milkshake that barely requires any effort to make. You’re not required to make it and drink it on Sunday, it was just almost a tradition in my family to make it on the weekends, and it somehow does taste better on a Saturday or Sunday morning.
These are for about 4 glasses or 1 liter:
Basically anything is better consumed fresh, but it is especially the case for this milkshake recipe. If you leave it sitting for more than 10-15 minutes it won’t be so delicious anymore.
Originally published at https://www.yaroslavps.com/food/sunday-morning-milkshake/
Recipe tags: sweet breakfast drink cheesefare


You can find your API key here: https://real-debrid.com/apitoken.
Recommended level is Warning, set to Debug to get the most info.
Path in the docker container to download files to (i.e. /data/downloads).
Path where files are downloaded to on your host (i.e. D:\Downloads). This path is used for Radarr and Sonarr to find your downloads.
Maximum amount of downloads that get unpacked on your host at the same time.
Select which download client to use, see the README for the various options.
Path in the docker container to temporarily download to (i.e. /data/temp). Make sure the docker container has enough disk space if using a path inside the container.
Maximum amount of torrents that get downloaded to your host at the same time.
Maximum amount of parallel threads that are used to download a single torrent to your host. If set to 1 no parallel downloading will be done.
Maximum download speed in Megabytes per second. When set to 0 unlimited speed is used.
Address of a proxy server.
This is the URL to your Aria2c instance. It must end in /jsonrpc. A common URL is http://<IP_ADDRESS>:6800/jsonrpc.
The secret of your Aria2c instance. Optional.


I have considered a career in programming off and on for several years now, one of my best friends went through the Epicodus program, and four years removed is very succesful. There were many ups and downs in his journey the past four years, but one thing he does not regret in his life is going to a code school. I'm hoping to feel the same way in four years.
I have an internship lined up after the intership that epicodus provides us, and my short term goal is to get hired after my intership is up. I would love to land a junior developer job within a year of graduating from epicodus and a senior developer job within 5 years.
I love asking for help in this environment, sometimes I feel like I ask for help too quickly when the answer might be a quick google search and some elbow grease away.
I feel the only time I have a hard time asking for help is when my ego gets in the way, which is not beneficial for anyone.
Once I learn something, it is very beneficial for me to teach it to someone else a few times. It really helps reinforce the information into my head. Plus no matter how time consuming it is, I really benefit from just coding. coding. coding. More time spent doing it, the better I get. My problem solving process is still under progress, I am trying to obtain some more patience, and building the skill of a google search.
It is certainly more along the lines of okay, I need to learn more about this. But sometimes when you know you have learned something, but it isn't sticking or being applied succesfully in the code editor. It is hard not to get too down on yourself.
If i'm being honest, I would say I praise myself for knowning stuff innately, but I don't like this aspect of myself.
I am interested in applying some fun and unique HTML and CSS to the codebase. But I know my weakness is complex algorithms and looping, so I would like to be CC'd on those topics as we build them out.
I do believe that I get overly frustrated by bugs and it makes me lose focus and possibly become a distraction. Maybe that is something I should keep an eye on.
I think working through my bugs step by step isn't something that I have done a great job of so far. Also using the debugging tools we have learned in the program are going to be key for me going forward.
That being present for as much of a team project is very crucial, I was a part of a good part of it (as much as I could be with power issues) and I still only felt I had a 50-75% understanding of what was going on.
My biggest strengths are css, and objects. My biggest weakness is looping.
I really need extra practice looping, testing, and also, I just don't think like a developer yet. I am nearly fluent at reading javascript at this point, but not at writing logic and functions from scratch.
Being more versed on the topic I choose to participate in for team week. I didn't have a passion for the subject, just signed up because I liked some of the people in the group. I didn't feel as invested in the result as I would of liked to.


Light weight data table with smooth virtual scrolling.
Title: {{value}}]]> {{row?._id}}
{{row?._label}}
;
private rowDataStream: Observable<{rows: any[], offset: number, limit: number}>;
onRowCountRequest() {
console.log("on row count request");
this.rowCountStream = this.requestRowCount();
}
onRowDataRequest(request) {
console.log("on row data request");
this.rowDataStream = this.requestRowData(request.offset, request.limit);
}
onSort(data) {
console.log("sort data:", data);
}
onRowClick(event) {
console.log("on row click", event);
}
onListItemClick(event) {
console.log("on list item click", event);
}
onRowSelectionChange(event) {
console.log("change row selection", event);
}
requestRowCount() {
return Observable.of(500).delay(1000);;
}
requestRowData(offset, limit) {
let rows = [];
for(var i = offset; i < (offset + limit); i++) {
rows.push({_id: i, _label: 'Test ' + i});
}
return Observable.of({rows, offset, limit}).delay(1000);
}
}
]]>
Just add the option row-selection-enabled to your column. Optional you can also add select-all-enabled if you want a select all checkbox on the column header.
You receive each change on the row-selection-change-Event.
The data you receive is selection and rejection with list of selected rows and also the rows
that are not selected. If the selection list contains a element __all__ the user has selected
all rows, expect the list from rejection!
This is because normal you could only select rows that
are visible and already rendered, but in case of the select all option you don't want do
load your complete table to know the selected row items.


This form is for creating a new, empty table. You must enter a table
name and one or more fields. For each field, you must enter a name, select a
data type and enter the type width (if appropriate for the data type).
You can also choose if the field is an multi-value array, if it allows null,
if it is the primary key for indexing, and if the values it in must be unique.
When done, click on the Create button to have the table immediately
created.


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface HostAuthenticationToken
A HostAuthenticationToken
retains the host information from where
an authentication attempt originates.
| Method Summary | |
|---|---|
String |
getHost()
Returns the host name of the client from where the authentication attempt originates or if the Shiro environment cannot or chooses not to resolve the hostname to improve performance, this method returns the String representation of the client's IP address. |
| Methods inherited from interface org.apache.shiro.authc.AuthenticationToken |
|---|
getCredentials, getPrincipal |
| Method Detail |
|---|
String getHost()
ServletRequest.getRemoteHost()
value.
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Silva is a powerful CMS for organizations that manage multiple or complex websites. Content is stored independent of layout and presentation. Silva also provides an easy solution to make complex page layouts. Many large organizations and universities use Silva, which is released under a BSD license.
Download Silva Try the demoKey feature
This is a short discription of a great feature of Silva. This is a short discription of a great feature of Silva.
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What are three new things you have learned about yourself and your ego as a result of the core learning?
1 - After a decade in aviation pushing to achieve a life long dream I reached a point where I was happy and thought that I would retire another overweight pilot that got what I set out to achieve. But I learnt that the end goal was not what I was actually looking for, at times the journey felt too slow or had last time but I always made it through and yes, making it was great but the stories of how I got into my dream job are far better than the job itself. Embarking on this journey has reawakened the passion for learning something new again and being curious which I thought I had lost after so long. The core learning has helped me focus on being thankful for this opportunity to learn and grow again.
2 - My ego…is a hard thing to talk about, sometimes it comes on strong and makes me feel confident in my knowledge and place in the world. It gives me the drive to never give up and know that my opinions are worth listening to. Sometimes it disappears and I feel like I have taken a huge gamble with my families time and that I really don’t know what I am doing. The core learning has highlighted that not only is this completely normal and that everyone is going through their own battles but that having the self awareness to understand these emotions is a strength not a weakness. Everyone has taken on a huge challenge and even walking in the front door is an achievement.
3 - That I have some of the core skills and knowledge to be successful in the tech industry. I know that as long as I keep true to myself and apply the lessons I have learnt over the years I will succeed.
What are the role of values, empathy and self awareness in learning and programming?
Programming and the tech industry are huge. There is so much to learn about so many different moving or updating parts. At the start you cannot be expected to know them all and I feel that in 10 or 20 years you may have a really good grasp on your chosen area of expertise and parts of programming that are associated with this but you will still be a beginner in other areas. This makes a persons values extremely important, why? Because we are all learning, even those experienced web developers that have been in the industry for years won’t have all the answers to how ‘everything’ works.
It is up to us to take responsibility for our learning. This is where self awareness really shows itself, how long do I stick at a challenge before asking google, a work colleague or friend?  Being honest with yourself and your abilities is hard skill to master but with great self awareness comes a great opportunity to learn and grow. Making those once hard challenges not so big after all.
And lastly but most importantly, empathy will play a huge part in any industry where teamwork and shared knowledge are key. No one wants to work with the mad scientist that knows all the answers (or where to get them) and rubs your face in how smart they are. Teamwork, sharing and helping others will be major skills for us moving forward in the industry and how good you are at these skills depends on how empathetic you are towards others. Taking time to listen, share and adapt to colleagues and clients will help you complete projects that everyone is proud of and ultimately win business for you.
What has surprised you the most about the core learning?
The amount of similarities between the core learning and what aviation refers to as human factors. There is a huge amount of cross over between the two and having done human factors training every year for the last decade I feel confident I understand the basics regarding the core syllabus.
What were the most challenging aspects of the core learning?
Sharing personal information with others and opening out. While I may have been given and done similar things with aviation I never had to talk about them or open out to share what I have learn with other people. Up until now it has been, here is the information, take it home, have a read. Getting me to think back on information and share my personal experiences has been different…I might be guilty of over sharing, I get carried away sometimes once I start.
Why do you think we, a programming school, are spending so much time focusing on core learning in a web development bootcamp course?
There are certain behaviours and skills potential employers and going to be looking for in everyone. Things like the drive to keep learning (growth mindset), the ability to work well in a team, even if the team is you and your clients in a small firm, and how well you communicate (listening and looping) and get along with others.
The core content is highlighting the fact that these skills are just as important for us getting our first job as our coding abilities may be. In fact, if the tech industry is anything like the aviation industry, I am sure that hiring will be done on the core skill firstly with the knowledge that if they find the right candidate they will train that person up to be the coder they want in due course.
Does the time you spent studying core learning here feel like a waste of time?
No, it feels like a refresher and also more in-depth look at some of the knowledge I already have. It also serves as a reminder that some of the skills from my past will be very useful moving forward.
Should you have just used that time to practicing programming instead? Justify your answer
I was wondering that at the start especially when I knew how challenging weeks 3 and 5 were going to be but I have found there is only so much coding I can do before my head starts to explode and I need a break. The coding will come with time and practice and doing a little bit every day rather than having to climb a huge wall of coding every has been a good learning curve.
What is your long term goal and/or career pathway?
The skills I am really hoping to attain are a good base level understanding of Javascript and knowledge of ‘how’ web development teams (or individuals) work to produce their results. This is a completely different environment to what I have been used to in the past , I am nervous and excited to see how it works.
As I have mentioned previously, I would love to become a full stack web developer over time as I feel a good grounding in the whole process will set me up for the future if I manage to make it to the dizzy heights of self-employment. In the short term, learning as much as possible everyday and then gaining a first start to keep building my skills is the aim.
Long term I want to be able to use my knowledge to help those that may not be able to afford a web page at market rates and keep developing skills to explore new options such as making games etc.
What do you think your biggest strengths and limitations will be in Bootcamp?
My impatience with computers is definitely being softened as I learn to live and deal with the blocks that pop up while working. I have found understanding what is going on by use of console.log and reading error messages has help tremendously. Getting stuck and not knowing what just happened is very frustrating and these skills along with a bit of patience have helped me find the challenge of finding a solution rewarding.
I do still believe that my strengths of communication, reliable and being a team player will be my biggest strengths going into bootcamp. I know when to ask for help and have been getting better at ‘knowing’ what is going on which should make the transition into bootcamp easier than it would have been five weeks ago. In saying that I do need to be careful that I do not go asking for help every ten seconds…
I understand I am new to web development and I am going to have to listen and learn not just from facilitators but also my fellow students as well. The opportunity to learn is going to be great I just need to make sure I am soaking everything so I can keep improving.
What do you think your biggest non-technical challenge at Bootcamp will be?
I think for me it will be the balance between home and bootcamp life. My wife and I have a four month old (at the start of bootcamp) and I am sure this is going to make juggling the course load more difficult than it would have been a little while ago. In the short time we have had a baby we have learnt that any schedule or structure for your day or week is hard to maintain as there is always a curve ball being thrown into the mix. This could make finishing projects hard as I may need time away to deal with home life.
What non-technical skills - human skills - would you like to see developed in yourself while at EDA?
I am really interested in developing a structured approach to how projects are attempted. My personal style has been just to choose a point to go in on and start working. This works okay for someone who is working on something by themselves but I want my developing technique to be understandable and relatable for other people that I am working with. By working in a structured manner I will lay a strong foundation for others to understand where I am up to and pick up my work if I am not available to complete it.
What are your expectations of yourself on Bootcamp?
From the foundations material I know that uncle google is always available and there are many other problem solving techniques at my disposal. Based on the amount of time I have been given for a task and how big the task is will inform how soon I go looking for help. I am confident enough not to whittle away precious time if swallowing my pride and getting assistance is going to get the ball moving in the right direction.
While on bootcamp I know I will not only have my fellow cohort members to discuss course material, but there will also be access to facilitators to assist with any areas I am coming stuck on.
To work productively and safely with all other members in the dev academy environment I will follow staff member instructions (as long as they don’t cause harm physical or mental) and listen to and work in collaboration with my cohort members. Taking time to see how team members are feeling and any issues that we have as a group will help me work with team members productively.
Workload management should hopefully not be an issue for me. I am invested in the course and will happily work weekends and overtime to make sure I am where I need to be.


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Two counsels of Abrar’s father will be in prosecution team, law minister says
by bdnews24.comLaw Minister Anisul Huq has said two counsels chosen by slain BUET student Abrar Fahad’s father Barkatullah will also be in the team of public prosecutors.
Barkatullah, the plaintiff, had provided a list of lawyers of his choice and the government picked two of them as per his wish ahead of the trial, Anisul told reporters after a meeting with Abrar’s father at the minister’s home in Dhaka on Thursday.
“They are happy with the pace of trial proceedings. They want the trial to end quickly at the Speedy Trial Tribunal,” the minister said.
Barkatullah told bdnews24.com that the law minister assured him of having the trial held at the speedy tribunal.
Police charged 25 students of the Bangladesh University of Engineering and Technology or BUET earlier this month with torturing Abrar to death on Oct 6.
Anisul has already confirmed that the 25 accused, mostly members of the ruling Awami League’s student wing Bangladesh Chhatra League, will be tried in the Speedy Trial Tribunal, which can take additional 45 working days if a trial does not end within 90 working days.


{{quote.description}}
This quote was published on {{quote.completeDate|date}}
Published: {{quote. completeDate| dateAgo}}


That it was called a contract, Gavin mused, was no coincidence. As he thought of it, beyond the piece of paper lying inert in his filing upstairs to the thing in itself, he saw the agreement as something tightening around him, first a starched collar, then manacles, then stocks, then a noose. On the phone to Eleanor, friend since school, he made the mistake of confiding a fraction of this, and she replied:
"Gavin, come on. That's pathetic."


What's on TV: Friday, November 29
by Ben PobjieCharles: Fifty Years a Prince
7TWO, 7.30pm
This celebratory documentary marks 50 years since Prince Charles was formally invested with the title of Prince of Wales. Which was 11 years after he actually became Prince of Wales, at the age of nine. Of course, he had been a prince since birth, being the son of the Queen, so "50 Years a Prince" is something of what some might call "a lie", but I guess any excuse for a party. And this doco is, essentially, a party: a deep investigation of the heir apparent to the English throne that ends up concluding – spoiler alert! – that this prince fellow is an absolutely super chap. Bombshell revelations include: the prince loves his country; the country loves the prince; his wife is rather fond of him; he lives in a castle. If you're a fan of Prince Charles, this will really satisfy your urge to revel in royalty. If you're not a fan of Prince Charles, it'll just raise your blood pressure to dangerous levels.


Derek Eder
@derekeder
UPDATE: The City has restored access to the CPD arrest data!
Anonymized arrests data published here: https://data.cityofchicago.org/Public-Safety/Arrests/dpt3-jri9
Detailed arrests data available to reporters by request (similar to the previous API). Email<EMAIL_ADDRESS>for access https://twitter.com/derekeder/status/1281288802015772674
7/11/2020, 1:51:25 PM
Favs: 50
Retweets: 28
link


Definition: A Privately Held Company is one owned by a relatively small number of shareholders, where the stock is not available to the general public on a stock exchange market.
Definition: A Public Company offers its securities (stock, bonds, etc.) for sale to the general public, typically through a stock exchange, or through market makers operating in over the counter markets.


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'Bachelorette' alum J.P. Rosenbaum diagnosed with rare autoimmune disorder
by Annie MartinDec. 9 (UPI) -- Former Bachelorette contestant J.P. Rosenbaum has been diagnosed with a rare autoimmune disorder.
Rosenbaum, 42, and his wife, Bachelorette Season 7 star Ashley Hebert, shared Rosenbaum's diagnosis with Guillain-Barré syndrome Sunday on Instagram Stories.
Rosenbaum posted photos and videos from a hospital, where he is undergoing immunoglobulin therapy. He described Guillain-Barré syndrome as "a very surreal, and humbling, and crazy, rare" disorder.
"Just can't really believe it," Rosenbaum said. "Next steps are figure out if I've plateaued, which I think I have, in my symptoms. Definitely staying another night in the hospital."
Guillain-Barré syndrome is a rare autoimmune disorder that causes a person's own immune system to damage the nerves, according to the CDC. The disorder can cause muscle weakness and sometimes paralysis.
Hebert also shared photos and videos with Rosenbaum from the hospital.
"Jp was diagnosed with Guillain-Barré syndrome yesterday. He is in treatment and doing well," Hebert wrote. "It may be a long road to full recovery, but we are so grateful to everyone that has helped us get to a speedy diagnosis and treatment."
"Bachelorette" couple J.P. Rosenbaum and Ashley Hebert shared Rosenbaum's diagnosis with Guillain-Barré syndrome. Photo via ashleylynnrosenbaum/Instagram Stories
Hebert thanked supporters in another post.
"Thank you to everyone that has reached out," she said.
"Bachelorette" couple J.P. Rosenbaum and Ashley Hebert shared Rosenbaum's diagnosis with Guillain-Barré syndrome. Photo via ashleylynnrosenbaum/Instagram Stories
Rosenbaum and Hebert met and got engaged during The Bachelorette Season 7, which aired in 2011. The couple married in December 2012 and have two children, son Fordham Rhys and daughter Essex Reese.
Rosenbaum shared a family photo Dec. 1 on his seven-year wedding anniversary with Hebert.
"7 years down, probably about 3-4 more to go. Happy anniversary to the woman responsible for all the love and happiness in this picture (and basically all my pictures for the last 7 years). [Love] u @ashleylynnrosenbaum," he wrote.
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pips Red=5 White=12
(CorrectAnswer= 0/0, ErrorScore= 0)
If you wait long enough backgammon positions do repeat.
Nearly thirty years ago in the first ever World Cup Final Joe Sylvester (Black), at that time the strongest player in the world, trailed Ray Glazer (White) 15-23 in a match to 41 points (time was not a pressing issue in 1988!) when this position arose. Sylvester studied and analysed for eight minutes before redoubling to 8, much to the surprise of the crowd.
Sylvester rolled a non-double, Glazer rolled 43, both sides then rolled non-doubles, Joe had won 8 points and the match was tied at 23-23. From there Joe moved steadily ahead and won the match 41-31. After this game the players took a break and Joe arrived breathlessly at the commentary position to explain that while he would not redouble in a money game it was correct to double at this match score because Glazer could never redouble. Was he correct?
On one thing they were all agreed, if this was a money game this was no double because of the huge redouble vigorish that White has in the sequences where Black does not roll a double and then White bears off two men. Having decided this, the consensus of opinion on the question posed above was that Black should wait and redouble White out if he rolled a 1 or a 3 (except 33 of course, after 11 White still has a take).
In an article “Backgammon – An Independent View”, written long ago, I analysed the match position and determined that Sylvester was both correct to redouble and in analysing that Glazer should not redouble in the scenario outlined above.
Moving on the present day I was watching a late-night match on GridGammon when this identical position occurred in a money game. Coincidentally the cube was once more on 4. Black paused for about two seconds before rolling. He rolled a non-double, his opponent rolled 31 and Black then cashed his four points. Should he have redoubled? This is easy to solve with modern technology. Both XG and Sconyers’ bear-off database give this as a clear redouble. It is an error but not a blunder to hold on to the cube.
So, Sylvester was wrong about the money game action in 1988 and the modern-day player also failed to redouble. Why does nobody get this right? I think it comes down to too much analysis being subjective, rather than objective, plus a little bit of fear of staring down the barrel of a 16 cube! Having got the result from Sconyers I did a little objective analysis.
Firstly, how often will Black lose his market in the original position? There are two possibilities: he rolls a set of doubles and White doesn’t roll 44 or better, or he rolls a non-set and White rolls a 1 or a 3 (except 33). 11 can be viewed as a market loser as it is right on the borderline of pass/take. This happens a whopping 59% of the time. Definitely volatile! Definitely a good time to double.
Secondly, how often will White redouble? This now requires a triple parlay. Black doesn’t roll a set, White rolls one of the 13 numbers (54, 45, 64, 46, 65, 56, 42, 24, 52, 25, 62, 26, 22) which leave him with two checkers, Black doesn’t roll a set. This works out to 25%. It is great for White when it happens but it only happens a quarter of the time.
Having removed the emotion it becomes clear why this is a redouble - Black loses his market far too often to be able to afford to wait.  So, think objectively, not subjectively.
A little objective analysis in the eight minutes available to the commentary team in 1988 might have produced the right answer at the time, but somehow I doubt it. We are used to using computers to help solve problems like this and then we learn for the analysis. That technique was not available in 1988 and the commentators were trapped in the type of thinking that predominated in that era.
Never forget how much the game has changed since the advent of neural net computers.
Nearly thirty years ago in the first ever World Cup Final Joe Sylvester (Black), at that time the strongest player in the world, trailed Ray Glazer (White) 15-23 in a match to 41 points (time was not a pressing issue in 1988!) when this position arose. Sylvester studied and analysed for eight minutes before redoubling to 8, much to the surprise of the crowd.
Sylvester rolled a non-double, Glazer rolled 43, both sides then rolled non-doubles, Joe had won 8 points and the match was tied at 23-23. From there Joe moved steadily ahead and won the match 41-31. After this game the players took a break and Joe arrived breathlessly at the commentary position to explain that while he would not redouble in a money game it was correct to double at this match score because Glazer could never redouble. Was he correct?
On one thing they were all agreed, if this was a money game this was no double because of the huge redouble vigorish that White has in the sequences where Black does not roll a double and then White bears off two men. Having decided this, the consensus of opinion on the question posed above was that Black should wait and redouble White out if he rolled a 1 or a 3 (except 33 of course, after 11 White still has a take).
In an article “Backgammon – An Independent View”, written long ago, I analysed the match position and determined that Sylvester was both correct to redouble and in analysing that Glazer should not redouble in the scenario outlined above.
Moving on the present day I was watching a late-night match on GridGammon when this identical position occurred in a money game. Coincidentally the cube was once more on 4. Black paused for about two seconds before rolling. He rolled a non-double, his opponent rolled 31 and Black then cashed his four points. Should he have redoubled? This is easy to solve with modern technology. Both XG and Sconyers’ bear-off database give this as a clear redouble. It is an error but not a blunder to hold on to the cube.
So, Sylvester was wrong about the money game action in 1988 and the modern-day player also failed to redouble. Why does nobody get this right? I think it comes down to too much analysis being subjective, rather than objective, plus a little bit of fear of staring down the barrel of a 16 cube! Having got the result from Sconyers I did a little objective analysis.
Firstly, how often will Black lose his market in the original position? There are two possibilities: he rolls a set of doubles and White doesn’t roll 44 or better, or he rolls a non-set and White rolls a 1 or a 3 (except 33). 11 can be viewed as a market loser as it is right on the borderline of pass/take. This happens a whopping 59% of the time. Definitely volatile! Definitely a good time to double.
Secondly, how often will White redouble? This now requires a triple parlay. Black doesn’t roll a set, White rolls one of the 13 numbers (54, 45, 64, 46, 65, 56, 42, 24, 52, 25, 62, 26, 22) which leave him with two checkers, Black doesn’t roll a set. This works out to 25%. It is great for White when it happens but it only happens a quarter of the time.
Having removed the emotion it becomes clear why this is a redouble - Black loses his market far too often to be able to afford to wait.  So, think objectively, not subjectively.
A little objective analysis in the eight minutes available to the commentary team in 1988 might have produced the right answer at the time, but somehow I doubt it. We are used to using computers to help solve problems like this and then we learn for the analysis. That technique was not available in 1988 and the commentators were trapped in the type of thinking that predominated in that era.
Never forget how much the game has changed since the advent of neural net computers.
Cube analysis 2-ply cubeless equity +0.337 0.669 0.000 0.000 - 0.331 0.000 0.000 Cubeful equities: 1. Double, take +0.503 2. Double, pass +1.000 (+0.497) 3. No double +0.443 (-0.060) Proper cube action: Redouble, take


{% load markup %} {% if polls %} {% for poll in polls %}
{{ poll.question }} (results) - by {{ poll.author }} on {{ poll.date_published|date:"DATETIME_FORMAT" }} ({{ poll.get_total_vote_count }} votes)
{% endfor %} {% else %}Currently, there are no polls :-(
Please come back again later or help using make our site better by joining our team.


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---
layout: post
title: september 1877 shooting rifles from behind rocks
date: '2016-02-22T14:28:02+01:00'
categories:
- Sketches
- Horses
- Storyboards
picture_url: https://film-Storyboards.tumblr.com/post/139805490251/september-1877-shooting-rifles-from-behind-rocks
---
September 1877. Shooting rifles from behind rocks, Nez Percé warriors hold the advance of Major Lewis Merrill’s battalion at Canyon Creek, Montana.


{% load filters %}
Here you are welcome to register the actions you take to fight COVID-19 today.
Did you go out more than 15 minutes today? :
If yes:
Did you wash your hands when comming back home:
Why did you go out? {{ form.reason }}
Did you spend time in a crowded place? :
How frequently do you wash your hands? :


pyitm: Longley-Rice Irregular Terrain Model
This is a pure python implementation of the NTIA Longley-Rice Irregular Terrain Model. This model is a port from the C++ [1] model which itself was a port from the original FORTRAN implementation. pyitm only supports the area-prediction mode of the original model and has been validated against the example data sets from NTIA report 82-100 [2].
Installation
pyitm is available on PyPI and can be installed using pip:
pip install pyitm
Original NTIA Disclaimer:
The ITM software was developed by NTIA. NTIA does not make any warranty of any kind, express, implied or statutory, including, without limitation, the implied warranty of merchantability, fitness for a particular purpose, non-infringement and data accuracy. NTIA does not warrant or make any representations regarding the use of the software or the results thereof, including but not limited to the correctness, accuracy, reliability or usefulness of the software or the results. You can use, copy, modify, and redistribute the NTIA-developed software upon your acceptance of these terms and conditions and upon your express agreement to provide appropriate acknowledgments of NTIA’s ownership of and development of the software by keeping this exact text present in any copied or derivative works. By clicking the links on this page to download the software, you acknowledge that you have read this disclaimer.
Sources


Implements a predictive model of community assembly called 'Traitspace' (Laughlin et al. 2012, Ecology Letters). Traitspace is a hierarchical Bayesian model that translates the theory of trait-based environmental filtering into a statistical model that incorporates intraspecific trait variation to predict the relative abundances and the distributions of species. The package includes functions to plot the predicted and the observed values. It also includes functions to compare the predicted values against the observed values using a variety of different distance measures and to implement permutation tests to test their statistical significance.
| Version: | 1.1 |
| Depends: | permute, mclust, graphics, grDevices, stats, utils |
| Published: | 2015-11-18 |
| Author: | Chaitanya Joshi, Xin Li, Daniel Laughlin |
| Maintainer: | Chaitanya Joshi <cjoshi at waikato.ac.nz> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | Traitspace results |
| Reference manual: | Traitspace.pdf |
| Package source: | Traitspace_1.1.tar.gz |
| Windows binaries: | r-devel: Traitspace_1.1.zip, r-release: Traitspace_1.1.zip, r-oldrel: Traitspace_1.1.zip |
| OS X binaries: | r-release: Traitspace_1.1.tgz, r-oldrel: Traitspace_1.1.tgz |
| Old sources: | Traitspace archive |
Please use the canonical form https://CRAN.R-project.org/package=Traitspace to link to this page.


Seeta High School is located in mukono district and has three campuses in mukono distrct, the main campus is located in mukono town
the next is in mbalala of mukono.
We welcome all regions at Seeta,the schools are mixed boys and girls but is only bording section students are allowed.
VERSE I
Seeta High School raise your banners,
Lift your vision above all,
You the model, you the fountain,
The core of morals and talents.
Responsible leaders for our nation,
Rise to excel and prosper,
Seeta High School, raise your banners,
Lift your plight above all.
VERSE II
Seeta High School ever shining
You are the helm morning star
Serve the church and serve the nation
Producing soldiers of Christ.
Education for our great future
Uganda will rise and shine.
Seeta High School, raise your banners,
Lift your plight above all
The school was started in 2006 with only one compus and that was mukono
at first the school had 40 staff members.
The founders of this school were;
MR Aloysious Musiime, MR Abitegeka Jackson, MR Mukisa Adrian, MR Kakooza Azizi,MS Dorothy Lunkuse
Mr. Kakooza Azizi
He holds a bachelors degree in law , PHD in arts with education
from makerere University.He sits on the schools board of governors he is responsible
for approval of policies made at school by the head teacher and his team. He
carries responsibility of ensuring students wel fare at the school.
Mr. Mukisa Adrian
He holds a bachelors degree in civil engneering , a PHD in science
with Education from makerere University and the University of Manchester in U.K
He is the head of the school, meaning that he undertakes the overall responsibility
in decision making and policy making at the school. he also takes part in the
approval of new teachers .
Mr. Jinno jackson Abitegeka.
He holds a masters degree in public Administration, PHD in science
with education. He is responsible for admitting new students to the school on
behalf of the head teacher.He is tasked to undertake collective responsibility at
school on behalf of the head teacher. The school bursar , the director of
studies report to him in case of any need to change the school pplicies and rules.
He also approves the teachers being employed at school.He is a cardinal
pillar in the policy making at the school.
Mr. Aloysious Musiime
He holds a masters degree in Education and a bachelors degree in law from makerere
university. He is responsible for all academic issues at the school, he manages
all the school teaching staff plus the sports master. He is also responsible for designing class
time tables, cordinates the heads of departments and the class teachers
for the sake of excellence of students.
Ms Dorothy Lunkuse.
She holds a masters degree in planning and management, and a PHD in business
administration from the miami University of Ohio in America. She is responsible for all finances
of a school, She handles the withdraw and deposit of school funds in banks.


Using k-Nearest Neighbors (k-NN) to Predict Car Prices.
Car Prices: K-Nearest Neighbors
Using k-Nearest Neighbors (k-NN) to Predict Car Prices.
1. The Data
The data that we will be using is compiled from the University of California Irvine’s Website and contains the following car attributes:
| Columns | Description |
|---|---|
| symboling | -3, -2, -1, 0, 1, 2, 3 |
| normalized-losses | continuous from 65 to 256 |
| make | alfa-romero, audi, bmw, chevrolet, dodge, honda, isuzu, jaguar, mazda, mercedes-benz, mercury, mitsubishi, nissan, peugot, plymouth, porsche, renault, saab, subaru, toyota, volkswagen, volvo |
| fuel-type | diesel, gas |
| aspiration | std, turbo |
| num-of-doors | four, two |
| body-style | hardtop, wagon, sedan, hatchback, convertible |
| drive-wheels | 4wd, fwd, rwd |
| engine-location | front, rear |
| wheel-base | continuous from 86.6 120.9 |
| length | continuous from 141.1 to 208.1 |
| width | continuous from 60.3 to 72.3 |
| height | continuous from 47.8 to 59.8 |
| curb-weight | continuous from 1488 to 4066 |
| engine-type | dohc, dohcv, l, ohc, ohcf, ohcv, rotor |
| num-of-cylinders | eight, five, four, six, three, twelve, two |
| engine-size | continuous from 61 to 326 |
| fuel-system | 1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfi |
| bore | continuous from 2.54 to 3.94 |
| stroke | continuous from 2.07 to 4.17 |
| compression-ratio | continuous from 7 to 23 |
| horsepower | continuous from 48 to 288 |
| peak-rpm | continuous from 4150 to 6600 |
| city-mpg | continuous from 13 to 49 |
| highway-mpg | continuous from 16 to 54 |
| price | continuous from 5118 to 45400 |
The imports-85.data
data set columns do not match the columns from our Dataset’s Documentation and we will need to provide additional parameters to effectively work with our data.
import numpy as np
import pandas as pd
pd.options.display.max_columns = 99
cols = ['symboling', 'normalized-losses', 'make', 'fuel-type', 'aspiration', 'num-of-doors', 'body-style',
'drive-wheels', 'engine-location', 'wheel-base', 'length', 'width', 'height', 'curb-weight', 'engine-type',
'num-of-cylinders', 'engine-size', 'fuel-system', 'bore', 'stroke', 'compression-rate', 'horsepower', 'peak-rpm', 'city-mpg', 'highway-mpg', 'price']
cars = pd.read_csv('imports-85.data', names=cols)
cars.head()
| symboling | normalized-losses | make | fuel-type | aspiration | num-of-doors | body-style | drive-wheels | engine-location | wheel-base | length | width | height | curb-weight | engine-type | num-of-cylinders | engine-size | fuel-system | bore | stroke | compression-rate | horsepower | peak-rpm | city-mpg | highway-mpg | price | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 3 | ? | alfa-romero | gas | std | two | convertible | rwd | front | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | dohc | four | 130 | mpfi | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 13495 |
| 1 | 3 | ? | alfa-romero | gas | std | two | convertible | rwd | front | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | dohc | four | 130 | mpfi | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 16500 |
| 2 | 1 | ? | alfa-romero | gas | std | two | hatchback | rwd | front | 94.5 | 171.2 | 65.5 | 52.4 | 2823 | ohcv | six | 152 | mpfi | 2.68 | 3.47 | 9.0 | 154 | 5000 | 19 | 26 | 16500 |
| 3 | 2 | 164 | audi | gas | std | four | sedan | fwd | front | 99.8 | 176.6 | 66.2 | 54.3 | 2337 | ohc | four | 109 | mpfi | 3.19 | 3.40 | 10.0 | 102 | 5500 | 24 | 30 | 13950 |
| 4 | 2 | 164 | audi | gas | std | four | sedan | 4wd | front | 99.4 | 176.6 | 66.4 | 54.3 | 2824 | ohc | five | 136 | mpfi | 3.19 | 3.40 | 8.0 | 115 | 5500 | 18 | 22 | 17450 |
2. Data Cleaning
After observing the data set above we can see that the normalized-losses
column contains missing values that are represented by ?
. Let’s replace these values and look for the presence of missing values in other numeric columns. We will also need to normalize the values in all numeric columns if we want to use them for predicitive modeling.
2.1 Selecting Continuous Values
We will select only the columns with continuous values based off of our Dataset’s Documentation
continuous_values_cols = ['normalized-losses', 'wheel-base', 'length', 'width', 'height', 'curb-weight', 'bore', 'stroke', 'compression-rate', 'horsepower', 'peak-rpm', 'city-mpg', 'highway-mpg', 'price']
numeric_cars = cars[continuous_values_cols]
numeric_cars.head(5)
| normalized-losses | wheel-base | length | width | height | curb-weight | bore | stroke | compression-rate | horsepower | peak-rpm | city-mpg | highway-mpg | price | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | ? | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 13495 |
| 1 | ? | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 16500 |
| 2 | ? | 94.5 | 171.2 | 65.5 | 52.4 | 2823 | 2.68 | 3.47 | 9.0 | 154 | 5000 | 19 | 26 | 16500 |
| 3 | 164 | 99.8 | 176.6 | 66.2 | 54.3 | 2337 | 3.19 | 3.40 | 10.0 | 102 | 5500 | 24 | 30 | 13950 |
| 4 | 164 | 99.4 | 176.6 | 66.4 | 54.3 | 2824 | 3.19 | 3.40 | 8.0 | 115 | 5500 | 18 | 22 | 17450 |
2.2 Replacing Values
Using the DataFrame.replace() method we can replace all of the ?
values with the numpy.nan
missing value:
numeric_cars = numeric_cars.replace('?', np.nan)
numeric_cars.head()
| normalized-losses | wheel-base | length | width | height | curb-weight | bore | stroke | compression-rate | horsepower | peak-rpm | city-mpg | highway-mpg | price | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | NaN | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 13495 |
| 1 | NaN | 88.6 | 168.8 | 64.1 | 48.8 | 2548 | 3.47 | 2.68 | 9.0 | 111 | 5000 | 21 | 27 | 16500 |
| 2 | NaN | 94.5 | 171.2 | 65.5 | 52.4 | 2823 | 2.68 | 3.47 | 9.0 | 154 | 5000 | 19 | 26 | 16500 |
| 3 | 164 | 99.8 | 176.6 | 66.2 | 54.3 | 2337 | 3.19 | 3.40 | 10.0 | 102 | 5500 | 24 | 30 | 13950 |
| 4 | 164 | 99.4 | 176.6 | 66.4 | 54.3 | 2824 | 3.19 | 3.40 | 8.0 | 115 | 5500 | 18 | 22 | 17450 |
After replacing the ?
values, we need to determine the columns that need to be converted to numeric types. We will then use the DataFrame.astype() method to convert the column types:
2.3 Converting Values
numeric_cars = numeric_cars.astype('float')
numeric_cars.isnull().sum()
normalized-losses 41
wheel-base 0
length 0
width 0
height 0
curb-weight 0
bore 4
stroke 4
compression-rate 0
horsepower 2
peak-rpm 2
city-mpg 0
highway-mpg 0
price 4
dtype: int64
2.4 Columns with Missing Values
We observe that the following columns have missing values:
41
rows have a missing value for thenormalized-losses
column4
rows have a missing value for thebore
column4
rows have a missing value for thestroke
column2
rows have a missing value for thehorsepower
column2
rows have a missing value for thepeak-rpm
column4
rows have a missing value for theprice
column
We need to determine the correct approach to handling these missing values so that we don’t interfer with the integrity of the data.
2.5 Identifying the Target Column and Handling Missing Values
Because the price
column is what we want to predict, let’s remove any rows with missing price
values:
numeric_cars = numeric_cars.dropna(subset=['price'])
numeric_cars.isnull().sum()
normalized-losses 37
wheel-base 0
length 0
width 0
height 0
curb-weight 0
bore 4
stroke 4
compression-rate 0
horsepower 2
peak-rpm 2
city-mpg 0
highway-mpg 0
price 0
dtype: int64
We will replace missing values in the other columns using the column’s mean (average) value:
numeric_cars = numeric_cars.fillna(numeric_cars.mean())
Let’s confirm that there are no more missing values:
numeric_cars.isnull().sum()
normalized-losses 0
wheel-base 0
length 0
width 0
height 0
curb-weight 0
bore 0
stroke 0
compression-rate 0
horsepower 0
peak-rpm 0
city-mpg 0
highway-mpg 0
price 0
dtype: int64
2.6 Normalizing Columns
Finally, we can normalize all columnns to range from 0
to 1
except our target column (price
).
price_col = numeric_cars['price']
numeric_cars = (numeric_cars.max() - numeric_cars)/(numeric_cars.max())
numeric_cars['price'] = price_col
3. Univariate Model
We will start with some univariate k-nearest neighbors models and move to more complex ones to help us structure our code workflow and better understand the features.
We will create a function named knn_train_test()
that encapsulates the traing and simple validation process. The function will:
- Split the data set into a training and test set
- Instantiate the KNeighborsRegressor class, fit the model on the training set, and make predictions on the test set
- Calculate the RMSE and return that value
def knn_train_test(train_col, target_col, df):
np.random.seed(1)
# Randomize order of rows in DataFrame
shuffled_index = np.random.permutation(df.index)
rand_df = df.reindex(shuffled_index)
# Divide number of rows in half and round
last_train_row = int(len(rand_df) / 2)
# Select the first half and set as training set
train_df = rand_df.iloc[0:last_train_row]
# Select the second half and set as test set
test_df = rand_df.iloc[last_train_row:]
# train, and test a univariate model using the following k values (1, 3, 5, 7, 9)
k_values = [1,3,5,7,9]
k_rmses = {}
for k in k_values:
# Fit model using k nearest neighbors
knn = KNeighborsRegressor(n_neighbors=k)
knn.fit(train_df[[train_col]], train_df[target_col])
# Make predictions using model
predicted_labels = knn.predict(test_df[[train_col]])
# Calculate and return RMSE.
mse = mean_squared_error(test_df[target_col], predicted_labels)
rmse = np.sqrt(mse)
k_rmses[k] = rmse
return k_rmses
k_rmse_results = {}
# For each column (minus `price`), train a model, return RMSE value and add to the dictionary `rmse_results`
train_cols = numeric_cars.columns.drop('price')
for col in train_cols:
rmse_val = knn_train_test(col, 'price', numeric_cars)
k_rmse_results[col] = rmse_val
k_rmse_results
{'bore': {1: 7496.1492312406444,
3: 6936.9888741632003,
5: 6816.8537123691885,
7: 7062.0613050538341,
9: 6869.7274373649016},
'city-mpg': {1: 4540.3610032247389,
3: 4662.4683767438482,
5: 4729.6734209992692,
7: 5099.2742894698586,
9: 4999.2917237740958},
'compression-rate': {1: 9024.9026779536325,
3: 7033.5529229950389,
5: 6736.676353123451,
7: 7459.1131944220724,
9: 7219.385481303907},
'curb-weight': {1: 5518.8832374058084,
3: 5048.6077260366692,
5: 4437.9343946355393,
7: 4369.3490898512136,
9: 4632.2055452210743},
'height': {1: 9108.4718365936551,
3: 8049.9871472883196,
5: 7487.6525188849646,
7: 7753.7974180840583,
9: 7695.632426557866},
'highway-mpg': {1: 5270.360471073066,
3: 4618.1866223408379,
5: 4579.0372499290315,
7: 4914.2600028726101,
9: 5181.9124189636359},
'horsepower': {1: 3749.5962185254293,
3: 3964.9503610053594,
5: 4007.4723516831596,
7: 4391.4816735297054,
9: 4505.1886320053109},
'length': {1: 5291.7851645472883,
3: 5267.2167776785409,
5: 5382.6711551381659,
7: 5396.362242025737,
9: 5420.5479164322587},
'normalized-losses': {1: 7906.5941410250143,
3: 6712.8733553798356,
5: 7635.1704160923791,
7: 7870.6510032392407,
9: 8221.5784655443185},
'peak-rpm': {1: 9825.559283202294,
3: 8025.1729800507092,
5: 7498.7464749413657,
7: 7296.5172664110205,
9: 7239.4781688794701},
'stroke': {1: 7282.3488587810798,
3: 7664.9840308065386,
5: 8078.4912887356768,
7: 7754.4838594616886,
9: 7723.9131538450647},
'wheel-base': {1: 5964.6822353178914,
3: 5246.472910232148,
5: 5527.6824887322919,
7: 5485.6830335257237,
9: 5734.4339857054465},
'width': {1: 4453.161424568767,
3: 4697.2871145506588,
5: 4644.8984285434217,
7: 4562.1341847495605,
9: 4643.8823393933362}}
Below we will visualize the results using a line plot:
import matplotlib.pyplot as plt
%matplotlib inline
for k,v in k_rmse_results.items():
x = list(v.keys())
y = list(v.values())
plt.plot(x,y)
plt.xlabel('k value')
plt.ylabel('RMSE')
4. Multivariate Model
Compute average RMSE across different k
values for each feature:
feature_avg_rmse = {}
for k,v in k_rmse_results.items():
avg_rmse = np.mean(list(v.values()))
feature_avg_rmse[k] = avg_rmse
series_avg_rmse = pd.Series(feature_avg_rmse)
series_avg_rmse.sort_values()
horsepower 4123.737847
width 4600.272698
curb-weight 4801.395999
city-mpg 4806.213763
highway-mpg 4912.751353
length 5351.716651
wheel-base 5591.790931
bore 7036.356112
compression-rate 7494.726126
normalized-losses 7669.373476
stroke 7700.844238
peak-rpm 7977.094835
height 8019.108269
dtype: float64
We can now modify the knn_train_test()
function to work with multiple columns:
def knn_train_test(train_cols, target_col, df):
np.random.seed(1)
# Randomize order of rows in DataFrame
shuffled_index = np.random.permutation(df.index)
rand_df = df.reindex(shuffled_index)
# Divide number of rows in half and round
last_train_row = int(len(rand_df) / 2)
# Select the first half and set as training set
train_df = rand_df.iloc[0:last_train_row]
# Select the second half and set as test set
test_df = rand_df.iloc[last_train_row:]
k_values = [5]
k_rmses = {}
for k in k_values:
# Fit model using k nearest neighbors
knn = KNeighborsRegressor(n_neighbors=k)
knn.fit(train_df[train_cols], train_df[target_col])
# Make predictions using model
predicted_labels = knn.predict(test_df[train_cols])
# Calculate and return RMSE
mse = mean_squared_error(test_df[target_col], predicted_labels)
rmse = np.sqrt(mse)
k_rmses[k] = rmse
return k_rmses
k_rmse_results = {}
# Use the best 2 features to train and test a multivariate k-nearest neighbors model using the default `k` value
two_best_features = ['horsepower', 'width']
rmse_val = knn_train_test(two_best_features, 'price', numeric_cars)
k_rmse_results["two best features"] = rmse_val
# Use the best 3 features to train and test a multivariate k-nearest neighbors model using the default `k` value
three_best_features = ['horsepower', 'width', 'curb-weight']
rmse_val = knn_train_test(three_best_features, 'price', numeric_cars)
k_rmse_results["three best features"] = rmse_val
# Use the best 4 features to train and test a multivariate k-nearest neighbors model using the default `k` value
four_best_features = ['horsepower', 'width', 'curb-weight', 'city-mpg']
rmse_val = knn_train_test(four_best_features, 'price', numeric_cars)
k_rmse_results["four best features"] = rmse_val
# Use the best 5 features to train and test a multivariate k-nearest neighbors model using the default `k` value
five_best_features = ['horsepower', 'width', 'curb-weight' , 'city-mpg' , 'highway-mpg']
rmse_val = knn_train_test(five_best_features, 'price', numeric_cars)
k_rmse_results["five best features"] = rmse_val
# Use the best 6 features to train and test a multivariate k-nearest neighbors model using the default `k` value
six_best_features = ['horsepower', 'width', 'curb-weight' , 'city-mpg' , 'highway-mpg', 'length']
rmse_val = knn_train_test(six_best_features, 'price', numeric_cars)
k_rmse_results["six best features"] = rmse_val
# Display all of the RMSE values
k_rmse_results
{'five best features': {5: 3346.6737097607775},
'four best features': {5: 3232.1036292326721},
'six best features': {5: 3398.1290113563641},
'three best features': {5: 3212.5596306057919},
'two best features': {5: 3681.3980922556266}}
5. Hyperparameter Tuning
We will now optimize the top three models that performed the best, varying the hyperparameter value from 1
to 25
.
def knn_train_test(train_cols, target_col, df):
np.random.seed(1)
# Randomize order of rows in DataFrame
shuffled_index = np.random.permutation(df.index)
rand_df = df.reindex(shuffled_index)
# Divide number of rows in half and round
last_train_row = int(len(rand_df) / 2)
# Select the first half and set as training set
train_df = rand_df.iloc[0:last_train_row]
# Select the second half and set as test set
test_df = rand_df.iloc[last_train_row:]
k_values = [i for i in range(1, 25)]
k_rmses = {}
for k in k_values:
# Fit model using k nearest neighbors
knn = KNeighborsRegressor(n_neighbors=k)
knn.fit(train_df[train_cols], train_df[target_col])
# Make predictions using model
predicted_labels = knn.predict(test_df[train_cols])
# Calculate and return RMSE
mse = mean_squared_error(test_df[target_col], predicted_labels)
rmse = np.sqrt(mse)
k_rmses[k] = rmse
return k_rmses
k_rmse_results = {}
three_best_features = ['horsepower', 'width', 'curb-weight']
rmse_val = knn_train_test(three_best_features, 'price', numeric_cars)
k_rmse_results["three best features"] = rmse_val
four_best_features = ['horsepower', 'width', 'curb-weight', 'city-mpg']
rmse_val = knn_train_test(four_best_features, 'price', numeric_cars)
k_rmse_results["four best features"] = rmse_val
five_best_features = ['horsepower', 'width', 'curb-weight' , 'city-mpg' , 'highway-mpg']
rmse_val = knn_train_test(five_best_features, 'price', numeric_cars)
k_rmse_results["five best features"] = rmse_val
k_rmse_results
{'five best features': {1: 2561.7319037195625,
2: 2567.2749455482176,
3: 2949.9007889192553,
4: 3074.6091106298891,
5: 3346.6737097607775,
6: 3686.4646211770864,
7: 3907.1959982578019,
8: 4104.0339873177718,
9: 4335.7141974258602,
10: 4463.6007084810435,
11: 4444.0259889090448,
12: 4534.547516044051,
13: 4638.5257014541967,
14: 4686.7680627393893,
15: 4676.6172318274348,
16: 4706.4889916373404,
17: 4714.757468354599,
18: 4724.0179262108768,
19: 4780.0364569672583,
20: 4790.8654014852591,
21: 4788.4429142051176,
22: 4820.2560355653704,
23: 4823.6246116515467,
24: 4830.7715122893824},
'four best features': {1: 3135.5489073677436,
2: 2514.1812009849527,
3: 2788.5519417420178,
4: 2917.4679936225316,
5: 3232.1036292326721,
6: 3566.725419074407,
7: 3834.9804809872821,
8: 3927.3952487590609,
9: 4078.9765839753827,
10: 4199.8376270003955,
11: 4345.0069904611819,
12: 4451.3870113027624,
13: 4550.1634683008278,
14: 4591.5340160428832,
15: 4630.3996426828098,
16: 4711.9117982858279,
17: 4692.3372730081592,
18: 4709.1872236435829,
19: 4698.1962740829795,
20: 4738.5487814580347,
21: 4727.3518464816807,
22: 4719.3369599341022,
23: 4707.9563401268824,
24: 4753.4193738950999},
'three best features': {1: 3308.7499419294022,
2: 3044.812909435545,
3: 3042.2117028741623,
4: 2958.964739955848,
5: 3212.5596306057919,
6: 3542.3007736748041,
7: 3801.5597829031262,
8: 4007.7501484785639,
9: 4074.3452185932656,
10: 4225.0494506919176,
11: 4338.8991649386644,
12: 4428.0841388589351,
13: 4496.3621365502913,
14: 4540.1357252028592,
15: 4614.0272979737174,
16: 4654.474275823789,
17: 4714.0580949648638,
18: 4645.9886513064885,
19: 4628.211244787356,
20: 4665.0992005704829,
21: 4648.5009310888045,
22: 4610.0134050293573,
23: 4642.8367354686252,
24: 4669.5676777327653}}
Let’s plot the resulting RMSE values:
for k,v in k_rmse_results.items():
x = list(v.keys())
y = list(v.values())
plt.plot(x,y)
plt.xlabel('k value')
plt.ylabel('RMSE')
6. Recommendations
- Modify the
knn_train_test()
function to use k-fold cross validation instead of test/train validation - Modify the
knn_train_test()
function to perform the data cleaning as well


Why it is important for everyone to consider having a flu jab
Health experts say more people taking up the vaccine option will pay dividends in the long run
by Chris PeregrineIt may start with a sniffle and then you think ‘here we go’.
Is that cold on its way, or, even worse, is flu about to make its unwelcome presence felt?
Well, now with the spectre of winter upon us, what do you expect? You are probably going to get something - the question is what?
There is a lot of confusion about what people may succumb to over the long months ahead.
Why, it could even be ‘man flu’, that strain which can afflict members of the male species who normally still manage, despite their condition, to tell anyone who is prepared to listen all about it.
Dr Jo Longstaffe is a director at Wales’ first private general practice, known as the Independent General Practice. Clinics are held at HMT Sancta Maria Hospital in Swansea.
Here, she dispels some myths about flu and the flu vaccine and offers some helpful advice on avoiding catching flu this winter.
Give yourself the best chance of avoiding flu
“At this time of year I see many patients with a similar set of symptoms with varying degrees of severity," she said. "While some people pick up colds and upper respiratory infections that can cause coughs and runny noses, others will have a more serious set of symptoms that are more associated with the flu virus.
"Flu can cause a high fever and body aches, severe fatigue and coughing for up to two weeks or more. In some cases it can be fatal and so I encourage my patients to do everything they can to avoid catching flu, especially at this time of year."
One of the best ways to avoid flu is to have the flu vaccine. While it is offered to high risk groups, including older people and young children on the NHS, vaccine is available to others through the Independent GP Practice at Sancta Maria Hospital. Even if you feel that you are fit and healthy, you may be helping the spread of flu to other, more vulnerable people around you if you do not have the flu jab.
"There are some common misconceptions about the flu jab that I hear frequently," said Dr Longstaffe. "Many people are concerned that the vaccine will give them the flu or cause other nasty side effects. In fact, the flu viruses contained within the vaccine are either weakened or have been killed and are therefore inactive.
"It takes around two weeks to kick in, so there is a possibility of picking up the flu virus within that time but it’s not caused by the jab. For most people, there will be no side effects from the vaccine but others will feel weak for a day or two with fever and muscle pain but it’s a lot less severe than flu. I recommend getting the flu vaccine every year if you want to give yourself the best chance of avoiding the virus."
Common sense measures will help pay dividends
"As well as the jab, you can give yourself the best chance of avoiding the flu if you wash your hands regularly and keep surfaces that come in contact with people clean," said Dr Longstaffe. "Other immune system boosting lifestyle factors such as a balanced diet, getting enough sleep and exercising frequently will also help to ward off the virus.
"If you are unfortunate enough to have flu this winter then rest as much as you can. Keep warm and drink plenty of fluids to avoid dehydration. Take paracetamol or ibuprofen for aches, pains and fever."
How the Independent General Practice can help
The Independent General Practice operates clinics on Tuesday and Wednesday at HMT Sancta Maria Hospital, Ffynone Road, Swansea, SA1 6DF. The service provides private GP appointments, vaccinations, medicals, tests and screens.
To book an appointment call 03456 252 252. For more information about HMT Sancta Maria Hospital visit www.hmtsanctamaria.org .


KNOW YOUR FOOD !
Retailer Name
Retailer Pincode
Item
Wheat
Rice
Tomato
Potato
Apple
Banana
Submit
KNOW YOUR FOOD !
Pincode
Retailer
Item
Fertilizer Grade
Seed Grade
Day
EC Value
Average


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OPNAVINST 5530.14E, Navy Physical Security and Law Enforcement Program
OPNAVINST 5530.13C, Department of the Navy Physical Security Instruction for Conventional Arms, Ammunition, and Explosives (AA&E)
SECNAVINST 5500.29C, Use of Deadly Force and the Carrying of Firearms by Personnel of the Department of the Navy in Conjunction with Law Enforcement, Security Duties and Personal Protection


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Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4
Preheat the oven to 190C/375F/Gas 5.
Place the aubergine halves into a roasting tin. Roast in the oven for 30-45 minutes, or until tender, then set aside.
Heat a frying pan over a medium heat until hot. Add the duck breasts, skin-side down, and fry for 6-8 minutes until the skin is crisp and most of the fat has melted (rendered).
Turn the duck breasts over and continue to fry on the other side for 2-3 minutes, or until cooked to your liking. Remove from the pan and set aside on a warm plate to rest.
Line a lidded wok with a double layer of aluminium foil. Sprinkle the wood chips into the bottom of the wok, then cover the wok with a lid and heat over a low heat, until the wood chips start to smoke. (CAUTION: Food-smoking generates a great deal of smoke. Cook in a well-ventilated place and open the windows. Open the wok outdoors.)
Add the aubergine halves to the wok, then quickly replace the lid and smoke for 3-4 minutes.
Remove the smoked aubergine halves from the wok outdoors.
Transfer the smoked aubergines to a food processor, then add 50g/2oz of the butter and all of the lemon juice and blend to a purée. Season, to taste, with salt and freshly ground black pepper.
Heat the remaining butter in a separate frying pan over a medium heat. When the butter is foaming, add the spinach leaves and fry for 1-2 minutes, stirring regularly.
Add the water and continue to cook for 1-2 minutes, or until the spinach has wilted.
To serve, carve the duck breasts into thin slices. Place one sliced duck breast onto each of four serving plates. Spoon a little of the smoked aubergine purée and the sautéed spinach alongside.


Simple man with simple ideas. It turns out that these ideas are always well received. What are these ideas? These ideas are ideas for giving gifts to people, family, friends, girlfriend, co-workers, whomever you want. Sometimes even my friends and family come and ask me for advice.
I am proud owner of a 3D printer wich helps a lot to design my own gifts and turn the ideia in reality, but before the printer I already had the "gift" for choosing gifts, pun not intended. Of course knowing the person, what she does, her passions, hobbies and how her brain works is half the work done. The other half is more difficult, so I created this blog to help you choose and get some ideias.
If you want to know more about the gifts I bought or have made for my friends and family check my posts, I have a new one every month with new gifts and the reasons. It the studies and work it's difficult to post every week. But if you have a story about a gift and want to share it or you want advice send me a message in the contact form, I will reply as soon as possible.


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Imported paint from Finland. Over 256 colors available in-store, varying in quantity (1 oz. to 8 oz.). Clean Finnish paint microbinds to canvas, increasing the finish and longevity of any artwork. Starting at $5.00 / tube.


{% extends "admin/base_site.html" %} {% load i18n %} {% block bodyclass %}grp-doc{% endblock %} {% block content-class %}{% endblock %} {% block title %}Grappelli Documentation » Modules{% endblock %} {% block extrahead %} {% endblock %} {% block breadcrumbs %}
The most essential component of Grappelli is a .grp-module, wrapping pieces of related content. The horizontal layout within a module is structured by one ore more .grp-row. A row stretches over the full width of the parent module and represents one piece of content or contains multiple pieces of content which belong together. Additionally, there might be a description for a module. In that case, just put a p.grp-description in a .grp-row.
Some text describing the module
Row
Row
Row
{% filter force_escape %}
Module
Some text describing the module
Row
Row
Row
{% endfilter %}
Rows might be split into two or more cells. To do so assign .grp-cells to the .grp-row you want to carry the cells. Each cell within that row is a .grp-cell then.
Cell
Cell
Cell
{% filter force_escape %}
Module
Cell
Cell
Cell
{% endfilter %}
Modules may be nested up to three levels.
Row
Row
Row
Row
Row
Row
{% filter force_escape %}
Parent Module
Child Module
Row
Row
Child Module
Grandchild Module
Row
Row
Grandchild Module
Row
Row
{% endfilter %}
A module usually contains a heading. Although that heading is optional, modules without it do not appear in document outlines — besides, the heading is required if your module is collapsible.
Row
Row
Row
Row
Row
{% filter force_escape %}
Heading 2
Row
Row
{% endfilter %}
{% filter force_escape %}
Row
Row
Row
{% endfilter %}
To make a module collapsible, just add .grp-collapse. With adding .grp-open or .grp-closed you define whether the collapsible module is opened or closed by default. Moreover, you need to define a .grp-collapse-handler which is usually the heading, but you may assign that class to other elements as well. Finally, you have to use some javascript code (see source code below).
Row
Row
Row
Row
{% filter force_escape %}
Parent Module
Child Module
Row
Row
Child Module
Row
Row
{% endfilter %}
{% filter force_escape %}
(function($) {
$(document).ready(function() {
$("#grp-content-container .grp-collapse").grp_collapsible();
});
})(grp.jQuery);
{% endfilter %}
Find out how you may nest modules in stacked & tabular groups.


Gecode::Int::Extensional::Incremental< View >::SupportEntry Class Reference
#include <extensional.hh>
Inherits Gecode::FreeList.
Detailed Description
template<class View>
class Gecode::Int::Extensional::Incremental< View >::SupportEntry
Entry for storing support.
Definition at line 289 of file extensional.hh.
Constructors | |
| SupportEntry (void) | |
| Default constructor (noop). | |
| SupportEntry (Tuple t0, SupportEntry *n0=NULL) | |
| Initialize with Tuple and next (defaulting to NULL). | |
Memory management | |
| void | dispose (Space *home, SupportEntry *l) |
| Free memory for all elements between this and l (inclusive). | |
| void | dispose (Space *home) |
| Free memory for this element. | |
| static void * | operator new (size_t s, Space *home) |
| Allocate memory from space. | |
| static void | operator delete (void *) |
| No-op (for exceptions). | |
| static void | operator delete (void *, Space *) |
| No-op (use dispose instead). | |
Public Attributes | |
| Tuple | t |
| Supporting Tuple. | |
| SupportEntry * | next |
| Next support. |
Constructor & Destructor Documentation
template<class View>
| Gecode::Int::Extensional::Incremental< View >::SupportEntry::SupportEntry | ( | void | ) | [inline] |
template<class View>
| Gecode::Int::Extensional::Incremental< View >::SupportEntry::SupportEntry | ( | Tuple | t0, | |
| SupportEntry * | n0 = NULL | |||
| ) | [inline] |
Member Function Documentation
template<class View>
| void Gecode::Int::Extensional::Incremental< View >::SupportEntry::dispose | ( | Space * | home, | |
| SupportEntry * | l | |||
| ) | [inline] |
Free memory for all elements between this and l (inclusive).
This routine assumes that the list has already been fixed.
Definition at line 72 of file incremental.icc.
template<class View>
| void Gecode::Int::Extensional::Incremental< View >::SupportEntry::dispose | ( | Space * | home | ) | [inline] |
template<class View>
| void * Gecode::Int::Extensional::Incremental< View >::SupportEntry::operator new | ( | size_t | s, | |
| Space * | home | |||
| ) | [inline, static] |
template<class View>
| void Gecode::Int::Extensional::Incremental< View >::SupportEntry::operator delete | ( | void * | ) | [inline, static] |
template<class View>
| void Gecode::Int::Extensional::Incremental< View >::SupportEntry::operator delete | ( | void * | , | |
| Space * | ||||
| ) | [inline, static] |
Member Data Documentation
template<class View>
| Tuple Gecode::Int::Extensional::Incremental< View >::SupportEntry::t |
template<class View>
| SupportEntry* Gecode::Int::Extensional::Incremental< View >::SupportEntry::next |
The documentation for this class was generated from the following files:
- gecode/int/extensional.hh (Revision: 7285)
- gecode/int/extensional/incremental.icc (Revision: 6017)


1. Write a program disyntax1 that takes the most common elements of Stata
syntax and displays the contents of each macro created by the syntax
command. For example, you might use the auto
dataset.
. disyntax1 mpg price = 1 using some_file if rep78!=. & make=="AMC Concord" in 1/25
varlist contains |mpg price|
exp contains |= 1 |
using contains |using `"some_file"'|
if contains |if rep78!=. & make=="AMC Concord" |
in contains |in 1/25|
| ADO-FILE: disyntax1.ado |
|---|
|
2. Modify the above program to also display the the following types of options,
by()
, detail
, and offset()
. Here by()
should require
a variable list, and offset
should accept only a
number. For example, you might use the auto dataset.
. disyntax2 mpg, by(foreign) detail offset(10)
varlist contains |mpg|
exp contains ||
using contains ||
if contains ||
in contains ||
by contains |foreign|
detail contains |detail|
offset contains |10|
| ADO-FILE: disyntax2.ado |
|---|
|
3. Write a program myci1
that uses the returned values
of summarize
to construct and display the limits of a
95% CI for the mean. For example, you might use the auto dataset.
. summ mpg
(output). myci1
ll = 19.979121 ul = 22.615473
| ADO-FILE: myci1.ado |
|---|
|
4. Modify the previous program so that it gives a meaningful error message if
r(mean)
or r(sd)
is missing.
| ADO-FILE: myci2.ado |
|---|
|


The MIT License has been chosen to be used with this project.
It does not matter if you are a student, a hobbyist, or even a gaming industry company.
This project is truly open source.
MIT License
Copyright (c) 2018 Pantelis Andrianakis
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
 IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*Mind that the date must not change, since it indicates the effective creation date of the project, which affects the time window of this copyright.
**Also changing the copyright holder is a violation of the license.


Research & Development (R&D) is a well known driver of economic progress. This is true in most advanced countries like the US, Japan, and Germany, where the intensity of R&D expenditure has been relatively high and stable for many years. Unfortunately in the Philippines, R&D has been left behind in both scope and pace.
Tuklas brings researchers and funders together to collaborate. By leveraging the collective power of the people (through crowd-funding), meaningful and high-impact research and inventions come to life, may it be in the areas of science, engineering, medicine, or governance.
Explore new knowledge, discover breakthroughs, and bring ideas to life.
Support researchers, scholars, and inventors. Collectively fund research projects and help change the world.
Follow bleeding-edge projects by connecting with researchers and funders.


Welcome to Stickle, the consensual calling app.
Stickle lets you call and be called when it's convenient for you. It's that simple.
- Invite your friends by tapping the icon
- Find who you want to talk to and tap their toggle
- They'll be notified you want to talk
- When they're ready, they'll tap "Ready"
- Your phone will prompt you to call them, just by pressing the green telephone button
End voicemail tennis. Stickle lets you speak when you're both ready.


{% extends "account/base.html" %} {% load staticfiles i18n %} {% load url from future %} {% block head_title %}Sign up for account{% endblock %} {% block header_title %}Signup{% endblock %} {% block breadcrumb_title %}Signup{% endblock %} {% block content %} Sign Up {% csrf_token %} Name E-mail Address Password Password Confirmation I agree with terms of use Sign Up Sign Up or Connect with Connect with Already have an account? Sign In! © Copyright 2015. All Rights Reserved. {% endblock %}
Already have an account? Sign In!
© Copyright 2015. All Rights Reserved.


Developers
Srishti Sharma
I am a developer. It was really worth to make such an efficient and time saving software.I learned a lot.Great experience.
Connect
Shubam Walia
I am also a developer .I leaded the project. It was a great teamwork and I really hope for good future results.
Connect


Preparation time
less than 30 mins
Cooking time
over 2 hours
Serves
Serves 6
This slow-cooked stew of wild boar with juniper berries and black olives is great served with freshly cooked pappardelle pasta and shavings of parmesan.
Cut the boar into chunky pieces, each around 2.5cm/1in.  Season the meat really well with salt and pepper. Heat two tablespoons of the oil in a large frying pan.
Fry the boar in two batches over a medium-high heat until nicely browned on all sides, turning every now and then and adding more oil if necessary. As soon as the boar is browned, transfer to a large flameproof casserole or large saucepan.
Pour a little more oil into the pan in which the boar was browned and fry the bacon for 2-3 minutes, or until the fat crisps and browns. Scatter over the meat. Add a touch more oil to the frying pan and fry the chopped onion over a low heat for five minutes, stirring often until beginning to soften.
Stir the garlic, olives and crushed juniper berries into the pan and cook for two minutes more, stirring. Add to the flame-proof casserole with the meat and pour over the wine.
Stir in the tomatoes, tomato purée and 500ml/18fl oz cold water. Crumble over the stock cube, add all the herbs and the sugar and bring to a simmer.
Stir well, cover loosely with a lid, reduce the heat to low and leave to simmer very gently for 2½ hours, or until the boar is completely tender and falling apart.
Remove the lid every now and then and stir. If the liquid reduces too much, add a little extra water. The sauce should be fairly thick when you are finished, but not at all dry. Remove the thyme and rosemary stalks and bay leaves. Season to taste with salt and pepper.
Toss the ragù with freshly cooked pappardelle pasta and sprinkle with a few parmesan shavings to serve.


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How To Gain Weight In A Healthy Way?
Protein Supplements: Do You Really Need Them?
6 Amazing Health Benefits Of Mulethi Or Licorice
Back to Home


Dots: 3D cube with CSS animation
step-1
step-2
step-3
auto
inspired by
Dots by Mark Pearson @ dribble


Front-End Project | Basic TO-DO List CSS
The Web Developer Bootcamp
Instructor - Colt Steele
Walk Rusty
Buy Groceries
Finish Recording CSS Videos
F1 Wireframe
Back to Course projects


WebXR Demo
Customize a WebXR Augmented Reality session with HTML, CSS, and JS in Chrome 83+ on Android.
This demonstrates the use of slots, as well as shared and unshared DOM between the 3D and AR modes.
A slot is used here for replacing the default AR button with a custom one - in this case the one recommended by SceneViewer. This is not the default only because this way localization of the text is left to whatever system you prefer to use. Note the AR button will only be visible on AR-capable devices.
By styling based on the ar-status
attribute, you can add DOM that only shows up in certain modes.
In this case a CSS animation has been added to prompt the user to move their phone around to help ARCore find
their floor so that the object can be placed. User studies show a prompt like this is an important part of
guiding users to a good AR experience.
Finally, even complex DOM can easily function in both 3D and AR modes, including interactions via script. In this case a simple carousel of models is demonstrated. Unfortunately none of this DOM content can flow into SceneViewer or QuickLook, as these are native apps. Only through WebXR, now our default AR mode, can this be achieved, as the AR session is still inside of the browser. This also removes the need to redownload the model.
Note that by not specifying an ios-src
,
the USDZ will instead be auto-generated when the user clicks the
AR button on iOS to launch Quick Look.


{{chip}}
Tip: Press Enter
to accept a value.
A list of the protocols this Route should allow. By default it is ["http", "https"]
,
which means that the Route accepts both. When set to ["https"]
,
HTTP requests are answered with a request to upgrade to HTTPS.