Nokogiri builder can be used for building XML and HTML documents.
builder = Nokogiri::XML::Builder.new do |xml| xml.root { xml.products { xml.widget { xml.id_ "10" xml.name "Awesome widget" } } } end puts builder.to_xml
Will output:
<?xml version="1.0"?> <root> <products> <widget> <id>10</id> <name>Awesome widget</name> </widget> </products> </root>
The builder allows two forms. When the builder is supplied with a block that has a parameter, the outside scope is maintained. This means you can access variables that are outside your builder. If you don’t need outside scope, you can use the builder without the “xml” prefix like this:
builder = Nokogiri::XML::Builder.new do root { products { widget { id_ "10" name "Awesome widget" } } } end
The builder works by taking advantage of method_missing. Unfortunately some methods are defined in ruby that are difficult or dangerous to remove. You may want to create tags with the name “type”, “class”, and “id” for example. In that case, you can use an underscore to disambiguate your tag name from the method call.
Here is an example of using the underscore to disambiguate tag names from ruby methods:
@objects = [Object.new, Object.new, Object.new] builder = Nokogiri::XML::Builder.new do |xml| xml.root { xml.objects { @objects.each do |o| xml.object { xml.type_ o.type xml.class_ o.class.name xml.id_ o.id } end } } end puts builder.to_xml
The underscore may be used with any tag name, and the last underscore will just be removed. This code will output the following XML:
<?xml version="1.0"?> <root> <objects> <object> <type>Object</type> <class>Object</class> <id>48390</id> </object> <object> <type>Object</type> <class>Object</class> <id>48380</id> </object> <object> <type>Object</type> <class>Object</class> <id>48370</id> </object> </objects> </root>
Tag attributes may be supplied as method arguments. Here is our previous example, but using attributes rather than tags:
@objects = [Object.new, Object.new, Object.new] builder = Nokogiri::XML::Builder.new do |xml| xml.root { xml.objects { @objects.each do |o| xml.object(:type => o.type, :class => o.class, :id => o.id) end } } end puts builder.to_xml
A couple attribute short cuts are available when building tags. The short cuts are available by special method calls when building a tag.
This example builds an “object” tag with the class attribute “classy” and the id of “thing”:
builder = Nokogiri::XML::Builder.new do |xml| xml.root { xml.objects { xml.object.classy.thing! } } end puts builder.to_xml
Which will output:
<?xml version="1.0"?> <root> <objects> <object class="classy" id="thing"/> </objects> </root>
All other options are still supported with this syntax, including blocks and extra tag attributes.
Namespaces are added similarly to attributes. Nokogiri::XML::Builder assumes that when an attribute starts with “xmlns”, it is meant to be a namespace:
builder = Nokogiri::XML::Builder.new { |xml| xml.root('xmlns' => 'default', 'xmlns:foo' => 'bar') do xml.tenderlove end } puts builder.to_xml
Will output XML like this:
<?xml version="1.0"?> <root xmlns:foo="bar" xmlns="default"> <tenderlove/> </root>
Tags that reference non-default namespaces (i.e. a tag “foo:bar”) can be built by using the Nokogiri::XML::Builder#[] method.
For example:
builder = Nokogiri::XML::Builder.new do |xml| xml.root('xmlns:foo' => 'bar') { xml.objects { xml['foo'].object.classy.thing! } } end puts builder.to_xml
Will output this XML:
<?xml version="1.0"?> <root xmlns:foo="bar"> <objects> <foo:object class="classy" id="thing"/> </objects> </root>
Note the “foo:object” tag.
To create a document type (DTD), access use the Builder#doc method to get the current context document. Then call Node#create_internal_subset to create the DTD node.
For example, this Ruby:
builder = Nokogiri::XML::Builder.new do |xml| xml.doc.create_internal_subset( 'html', "-//W3C//DTD HTML 4.01 Transitional//EN", "http://www.w3.org/TR/html4/loose.dtd" ) xml.root do xml.foo end end puts builder.to_xml
Will output this xml:
<?xml version="1.0"?> <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> <root> <foo/> </root>
Create a new Builder object. options are sent to the top level Document that is being built.
Building a document with a particular encoding for example:
Nokogiri::XML::Builder.new(:encoding => 'UTF-8') do |xml| ... end
# File lib/nokogiri/xml/builder.rb, line 266 def initialize options = {}, root = nil, &block if root @doc = root.document @parent = root else namespace = self.class.name.split('::') namespace[-1] = 'Document' @doc = eval(namespace.join('::')).new @parent = @doc end @context = nil @arity = nil @ns = nil options.each do |k,v| @doc.send(:"#{k}=", v) end return unless block_given? @arity = block.arity if @arity <= 0 @context = eval('self', block.binding) instance_eval(&block) else yield self end @parent = @doc end
Create a builder with an existing root object. This is for use when you have an existing document that you would like to augment with builder methods. The builder context created will start with the given root node.
For example:
doc = Nokogiri::XML(open('somedoc.xml')) Nokogiri::XML::Builder.with(doc.at('some_tag')) do |xml| # ... Use normal builder methods here ... xml.awesome # add the "awesome" tag below "some_tag" end
# File lib/nokogiri/xml/builder.rb, line 253 def self.with root, &block new({}, root, &block) end
Append the given raw XML string to the document
# File lib/nokogiri/xml/builder.rb, line 342 def << string @doc.fragment(string).children.each { |x| insert(x) } end
Build a tag that is associated with namespace ns. Raises an ArgumentError if ns has not been defined higher in the tree.
# File lib/nokogiri/xml/builder.rb, line 314 def [] ns @ns = @parent.namespace_definitions.find { |x| x.prefix == ns.to_s } return self if @ns @parent.ancestors.each do |a| next if a == doc @ns = a.namespace_definitions.find { |x| x.prefix == ns.to_s } return self if @ns end raise ArgumentError, "Namespace #{ns} has not been defined" end
Generated with the Darkfish Rdoc Generator 2.


{% extends "base.html" %} {% load bootstrap4 %} {% block content %}
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I have been experimenting with Yerba Mate as a mind altering herb in various dosages and methods. This is a synthesis of what I observed. The results might be different from person to person so just keep that into consideration if you try it for yourself.
Drinking Mate tea is so far the best usage method I know of. I don't own a gourd and bombilla so I made use of a coffeemaker for heating the water and keeping it at a sub-boiling temperature. I put 8 table spoons of yerba tea and a table spoon of honey in the pot (not in the filter because I need to reuse the plant over and over again and keep it in contact with the water all the time). I pour a little cold water to wet the mate leaves and homogenize with the honey. The honey leaves a great aroma into the leaves and the end result is better in my opinion than mixing it later, after the tea is made (I don't use sugar because it is not as healthy and in my opinion the taste is not as good). Then I pour 2 cups (about 400-500ml) of water in the other compartment of the coffeemaker and let it do its thing for 10-15 minutes. In this time the hot water extracts an amazingly strong first cup of tea.
I drink the tea by sipping it little by little. It can be drank hot or cold, but the point is to sip it instead of just gulping it down the throat - that way you can absorb sublingually some of the mate goodness and it directly enters the bloodstream and goes right into the brain. When I do that I can feel a sudden rush through my brain, like a pleasant tingling sensation going up from the back of the head towards the top of the head - this is the best part.
After 15-30 minutes the tea makes its way into the bloodstream and I get a second rush, a little different from the first. It is slower and envelops the whole body. I start getting this wonderful tingling sensation all over the body (it seems mate opens the capillaries and enhances the peripheral circulation - which stimulates the skin which is connected to millions of tactile nerves - that is in my opinion the physical explanation of this tactile stimulation). I get the same tactile sensations from cannabis too, but it is much more intense. Mate on the other hand is very manageable yet powerful enough to entice me to do it almost daily, as it is also completely legal, inexpensive and easy to procure.
The sensation lasts anywhere from 1 hour to 4-5 hours. Sometimes after 1 liter of mate tea brewed from 8 tablespoons of dry tea I can have the effects for 3-4 hours before going to bed and another 2-3 hours after waking up! I might be more sensitive than the average person as I have been practicing yoga meditation for years so I guess everyone is probably experiencing somewhat different effects and for a different length of time.
The second method I tried is smoking dry leaf. I used the filter from a normal cigarette. The smoke is acceptable, I could even get myself to like it. The effects are very subtle and more cerebral. The same tingling in the brain and body, the same etheric sensation. I combined with drinking the mate tea and the final effect was one of the best I've had.  Anyway, I can say it's not mind blowing like salvia or even remotely close as intense as cannabis can be. It's just a subtle sensation that might add up to the sensation you get from drinking the tea. I would say, drinking the tea makes 80% of the sensations and smoking just 20% at most.
Another method of usage I tried was to make a concentrate of yerba mate. For this I made 2 liters of tea out of 100g of leaf. I put 4 times 2 cups of water in the coffeemaker. This guaranteed after the 4th hand that the leaves were almost 'completely washed'. So I had 2 liters of mate goodness. Then I put this in a pot on the fire and boiled it for 1-2 hours until it reduced to the volume of a small espresso coffee (it is usually not recommended to boil mate so I might try to let it evaporate naturally, next time, but that will take even more time).
It looked like a black syrup - that is thicker than normal tea and very dark. Before I drunk it I added some honey to make it more palatable. The effects came on after 10 minutes and lasted for more than 5 hours. I consider 100g of leaves too much to use at once (I got a nauseating sensation in the stomach after 2 hours - yet bearable). Maybe half the quantity should be better, or just to drink only half the concentrate at one time. The whole body was tingling with a superb sensation. I was focused and calm, yet intense. The heart might have been beating stronger than normal. I wasn't 'high' per se, but I had a subtle sensation of floating and my body felt like it was made of something wonderful and different from normal.
For those that know a little about yoga, I will try to describe the sensations in a technical language. The mate tea activates a subtle purification in the etheric body. It gives an intense sattvic resonance, yet it is also resonating with apas and also gives a warm sensation (heat). The tea stimulates Ajna chakra and the whole brain. It can lead to a sensation of purity and a feeling of astral floating. The etheric body can be clearly perceived as a lot of energy is attracted into it by resonance. Mate tea gives a type of resonance with Ananda, the energy of happiness and beatitude. It also removes some psychic blocks and makes introverts and shy people more extrovert and voluble in conversation.
As negative effects: nausea at high dosages - a sensation that passes in a few hours and is bearable for me, especially the second time and later on as I knew what it was and I wasn't scared like the first time. It can overstimulate the mind creating a sensation of mental rush. Might reduce the equilibrium - again, only at high dosages. Also, in high dosages might put a strain on the heart.
Overall I think mate is amazing - a legal high that is manageable, healthy and also reduces appetite and helps with mental and physical effort.
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.


Welcome to the home page for
the summoner
Frosty
.
chat_time
chat_message
chat_date
chat_user
send
to start chatting.
All Chat
expand_less


Menu Items that Perform Actions Prior to Loading the Page
Now that you know about actions, we can put some in our menu item, to perform some checks prior to loading the page.
We will have the menu item perform two checks:
- Check the number of stored procedures there are under the 'DB2AUTH' schema (the db2auth plug-in creates 7)
- Check the existance of the DB2AUTH.USERS table
If either of these two checks fail, we will configure the menu to pop up an error message.
Color scheme reminder:
- Indicated text has been removed
- Indicated text has been edited
- Indicated text has been added
- Indicated text is the source of a copy


This is Contact List page.
Back to Home page
Add new contact item
Name
Phone
Delete
@Each.Contacts
@Current.Name
@Current.Phone
Delete
@EndEach


We
make
robots.
Team 4814 is a part of the FIRST Robotics Competition (FRC). FRC is an international competition of high-school students, each year a challenge is given out and teams have 6 weeks to build a robot weighing up to 120 pounds.
We are based in London, Ontario. Now in our second year of competition, we have been working hard to prepare for regionals.
Last year, we were Curie Division Finalists at the World Championship, where we won the Rookie Inspiration Award.
At Team 4814, we seek to inspire youth across the globe with science and technology. We strive to create sustainable FRC teams and provide them with the facilities and resources they require to succeed. In London and beyond,
We
are
laying
the
tracks
for
success
Team 4814 was first established during the 2012-2013 school year, when students from London Central Secondary School and Oakridge Secondary School joined forces to create a single FRC Team. With the joint assistance of Eugen Porter, Founder of the WE FIRST Club at Western University, and university student mentors, we successfully built our team’s first robot and started competing.


We will be going over the syllabus today. Afterwards, a quick demo will be shown on how setup your files. Follow along in class and submit your work.


Max's grandfather Frans Verstappen dies
Brazil GP winner Max Verstappen's grandfather has died.
by GMM F11Limburg, as well as other Dutch news sources, are confirming that Frans Verstappen, who is Jos Verstappen's father, died of cancer in a hospice at the age of 72.
Frans was reportedly admitted earlier in November.
Jos, Max and Frans had a difficult relationship. In 2016, Frans even accused Jos, a former Formula 1 driver, of assault.
However, Frans remained a strong supporter of his grandson, telling 1Limburg earlier this year that the Red Bull-Honda driver's success gives him "goosebumps".
His death comes just days after Verstappen, 22, won at Interlagos.
"Joy and sorrow are often close together," Max said in a brief statement read out by the broadcaster Ziggo Sport.
Jos cancelled a scheduled appearance on the same network on Monday.
Frans Verstappen reportedly owned an ice-cream parlour in Montfort, where he lived and where Jos was born. He regularly organised parties at a local club with a big screen to watch Max's races.
A source said Frans Verstappen will be cremated on Saturday.
Jos' ex-wife Kelly van der Waal said: "After a fantastic F1 weekend, the world pauses for the death of grandpa Verstappen."
body check tags ::


Each point displayed represents a parcel centroid, shaded by one of the Zoning Types shown below.
Click on each parcel point to view information about that parcel.
- B1-1 Commercial
- B3-3 Commercial
- B4-2 Commercial
- B4-5 Commercial
- M1-5 Industrial
- MPD Residential
- R-0.5 Residential
- R-1-5 Residential
- R-2.5 Residential
- UR


{% extends "base.html" %} {% block title %}Basic Formset (Table layout){% endblock %} {% block extrahead %} {% endblock %} {% block content %}
Django 1.7 added a "MIN_NUM_FORMS" field to the management form; its value maps to the value passed in "min_num" to the formset factory function.
If you're running Django 1.7+, you will be required to have at least 2 forms in this formset.
{% endblock %}


Help: multimedia icons
|
Like |
|
|
Messages |
|
|
Post photo |
|
|
Notifications |
|
|
Profile |
Help: health icons
|
Steps |
|
|
Calories |
|
|
Heart rate |
|
|
Distance |
|
|
Sleep time |
|
|
Glucose Level |
Help: posting photo
If you want to add a description to your photo say it out loud while pressing/holding the button that looks like this:
Help: editing profile
If you want to change your profile name or description say it out loud while pressing/holding the
button that looks like this:
If you want to change your profile name or description say it out loud while pressing/holding the button that looks like this:
Help: sending message
If you want to write a message say it out loud while pressing/holding the button that looks like this:
After that, press the button that looks like this to send the message:
map icons
map idk
|
Current Position |
|
|
Park |
|
|
Metro |
|
|
Restaurant |
|
|
Museum |
|
|
Hotel |
|
Search place |
|
|
Points of interest |
|
|
Search friend |
|
|
Center on position |
Help: searching place
If you want to search a place by its name say it out loud while pressing/holding the button that
looks like this:
If you want to search a place by its name say it out loud while pressing/holding the button that looks like this:
Help: searching place
If you want to search a friend by its name say it out loud while pressing/holding the button that
looks like this:
If you want to search a friend by its name say it out loud while pressing/holding the button that looks like this:
Sejam bem vindos ao meu pântano #meme
Press a photo to publish:
min ( m)
EMERGENCY MODE
CALLING...
911
Activity
Profile
NAME |
| > Gato das botas |
GENDER |
| > Male |
DATE OF BIRTH |
| > 22/04/2001 |
HEIGHT |
| > 1.05m |
WEIGHT |
| > 12kg |
BLOOD TYPE |
| > A+ |
DISEASES |
| > Diabetes |
ALERGIES |
| > Dog fur |
Loading...please wait
Steps
12345 STEPS TO YOUR GOAL
Loading...please wait
Calories
126KCAL TO YOUR GOAL
Loading...please wait
Heart rate:
85 BPM
Loading...please wait
Distance
2.3KM TO YOUR GOAL
Loading...please wait
Average sleep time:
8:10h
Sleep time:
8:27h
Loading...please wait
Glucose level:
4.2mmol/L
Change the goal of steps you want to do daily:
Change the goal of calories you want to burn daily:
Change the goal of the distance you want to walk/run daily
Settings
Bluetooth |
|
GPS |
|
Health profile |
Bluetooth
|
Bluetooth |
Choose the phone to connect:
|
Phone 1 |
|
Phone 2 |
|
Phone 3 |
GPS
|
GPS |
Choose friends to share location with:
|
Shrek |
|
|
Bart |
|
|
Buzz |
Notifications
Edit your profile:
Choose a filter:
Description:
Messages
Turn on bluetooth
Turn on bluetooth
Allow health profile syncronization
Turn on the GPS
Search a place:
Search a friend:
Points of Interest
Increase or decrease the radius in meters to know the points of interest around you:
END
SHARE
Shrek
Location Sharing


Oh dear, it appears we aren't quite ready for you.
Perhaps you could try just making a map? (Hint: click on the yellow tab on the left of the map.)


How to use the Feathers PageIndicator
component
The PageIndicator
component displays a series of symbols, with one being highlighted, to show the user which index among a limited set is selected. Typically, it is paired with a List
or a similar component that supports scrolling and paging. The user can tap the PageIndicator
to either side of the selected symbol to navigate forward or backward.
The Basics
First, let's create a PageIndicator
control, give it a number of pages, and add it to the display list.
var pages:PageIndicator = new PageIndicator();
pages.pageCount = 5;
this.addChild( pages );
The number of symbols that a page indicator displays is controlled by the pageCount
property. You'll see that the first symbol is automatically selected. If you tap the page indicator on the right side, it will advance to the next index.
If we want to react to the selected index changing, we can add a listener for Event.CHANGE
:
pages.addEventListener( Event.CHANGE, pageIndicator_changeHandler );
The listener might look something like this:
function pageIndicator_changeHandler( event:Event ):void
{
var pages:PageIndicator = PageIndicator( event.currentTarget );
trace( "selected index:", pages.selectedIndex );
}
Skinning a PageIndicator
You can customize the layout of a page indicator, and you can customize the appearance of a its "normal" and "selected" symbols. For full details about which properties are available, see the PageIndicator
API reference. We'll look at a few of the most common ways of styling a list below.
Layout
You may set the direction
of a page indicator to Direction.HORIZONTAL
or Direction.VERTICAL
. The default layout direction is horizontal. Below, we change it to vertical:
pages.direction = Direction.VERTICAL;
We can set other layout properies, such as the gap
between symbols, the padding around the edges, and the alignment, both horizontalAlign
and verticalAlign
:
pages.gap = 4;
pages.paddingTop = 4;
pages.paddingRight = 4;
pages.paddingBottom = 4;
pages.paddingLeft = 10;
pages.horizontalAlign = HorizontalAlign.CENTER;
pages.verticalAlign = VerticalAlign.MIDDLE;
Symbol Skins
The symbols may be created using the normalSymbolFactory
and selectedSymbolFactory
for normal and selected symbols, respectively. These functions may return any type of Starling display object. Below, we return Starling Images with different textures for normal and selected states:
pages.normalSymbolFactory = function():DisplayObject
{
return new Image( normalSymbolTexture );
};
pages.selectedSymbolFactory = function():DisplayObject
{
return new Image( selectedSymbolTexture );
};
The page indicator will automatically reuse symbols if the page count or the selected index changes.


Test Task Submission Form
User:
Pass:
log in
App key:
Lookup tasks
Task ID (leave blank for all tasks):
Lookup
Task Submission
Load Task Information


Taiga UI uses
tui-svg
component to display SVG icons. It can show icons by name, link or
source code. Several icon names are hardcoded into kit components so if
you want to switch to a different icon set you would need to provide a
mapping.
{{name}}
These are keys of following dictionaries: tuiCoreIcons
and
tuiKitIcons
. It is not required to provide all those icons,
you can gradually add the ones you need depending on components you use.
There are two ways to add icons: bundled and as assets. Bundled icons
have the benefit of immediate display but increase your app size. Assets
work like regular
img src="xxx"
with all the benefits of caching. In both
cases you can control color with CSS color
style.
fill="currentColor"
or stroke="currentColor"
.
If you want to bundle your icons, you need to provide
TUI_ICONS
token with a dictionary of name to source code.
If you want to move your icons to assets you need to process them with
this script. Drop it to the folder with your icons and run
node process-icons.js
. Then move your icons to the assets
folder and provide TUI_ICONS_PATH
as seen in example below:
If you use unsafe icons or
Editor component you
need to provide TUI_SANITIZER
token, which is
responsible for removing malicious code from the svg. We recommend
to use
NgDompurify
as a sanitizer. This library implements
DOMPurify
as Angular Sanitizer or Pipe. It delegates sanitizing to DOMPurify
and supports the same configuration.


An input stream that always returns the same RDD on each time step.
An input stream that always returns the same RDD on each time step. Useful for testing.
A Discretized Stream (DStream), the basic abstraction in Spark Streaming, is a continuous sequence of RDDs (of the same type) representing a continuous stream of data (see org.apache.spark.rdd.RDD in the Spark core documentation for more details on RDDs).
A Discretized Stream (DStream), the basic abstraction in Spark Streaming, is a continuous
sequence of RDDs (of the same type) representing a continuous stream of data (see
org.apache.spark.rdd.RDD in the Spark core documentation for more details on RDDs).
DStreams can either be created from live data (such as, data from TCP sockets, Kafka, Flume,
etc.) using a org.apache.spark.streaming.StreamingContext or it can be generated by
transforming existing DStreams using operations such as map
,
window
and reduceByKeyAndWindow
. While a Spark Streaming program is running, each DStream
periodically generates a RDD, either from live data or by transforming the RDD generated by a
parent DStream.
This class contains the basic operations available on all DStreams, such as map
, filter
and
window
. In addition, org.apache.spark.streaming.dstream.PairDStreamFunctions contains
operations available only on DStreams of key-value pairs, such as groupByKeyAndWindow
and
join
. These operations are automatically available on any DStream of pairs
(e.g., DStream[(Int, Int)] through implicit conversions.
A DStream internally is characterized by a few basic properties:
This is the abstract base class for all input streams.
This is the abstract base class for all input streams. This class provides methods start() and stop() which are called by Spark Streaming system to start and stop receiving data, respectively. Input streams that can generate RDDs from new data by running a service/thread only on the driver node (that is, without running a receiver on worker nodes), can be implemented by directly inheriting this InputDStream. For example, FileInputDStream, a subclass of InputDStream, monitors a HDFS directory from the driver for new files and generates RDDs with the new files. For implementing input streams that requires running a receiver on the worker nodes, use org.apache.spark.streaming.dstream.ReceiverInputDStream as the parent class.
:: Experimental ::
DStream representing the stream of data generated by mapWithState
operation on a
pair DStream.
:: Experimental ::
DStream representing the stream of data generated by mapWithState
operation on a
pair DStream.
Additionally, it also gives access to the stream of state snapshots, that is, the state data of
all keys after a batch has updated them.
Class of the key
Class of the value
Class of the state data
Class of the mapped data
Extra functions available on DStream of (key, value) pairs through an implicit conversion.
Abstract class for defining any org.apache.spark.streaming.dstream.InputDStream that has to start a receiver on worker nodes to receive external data.
Abstract class for defining any org.apache.spark.streaming.dstream.InputDStream that has to start a receiver on worker nodes to receive external data. Specific implementations of ReceiverInputDStream must define getReceiver function that gets the receiver object of type org.apache.spark.streaming.receiver.Receiver that will be sent to the workers to receive data.
Class type of the object of this stream
Various implementations of DStream's.
org.apache.spark.streaming.dstream.DStream


Miscellaneous R functions for calculating and decomposing multiple hierarchical diversity metrics, including hierarchical allele richness (q=1), hierarchical exponential Shannon entropy (q=1), hierarchical heterozygosity (q=2) and genetic differentiation (Fst and Delta D). This package allows you to analyse spatial structured genetic data or species data under a unifying framework (Gaggiotti, O. E. et al, 2018, Evol Appl, 11:1176-1193; <doi:10.1111/eva.12593>), which partitions diversity and differentiation into any hierarchical levels. It helps you easily structure and format your data. It produces diversity profiles (q=0,1,2), hierarchical diversities and differentiation, as well as the the correlation between geographic distance and genetic differentiation.
| Version: | 0.1.2 |
| Depends: | R (≥ 3.0) |
| Imports: | GGally, adegenet, diveRsity, dplyr, entropart, ggplot2, hierfstat, reshape2, tibble |
| Suggests: | knitr, testthat, rmarkdown |
| Published: | 2018-10-26 |
| Author: | Xinghu Qin |
| Maintainer: | Xinghu Qin <qinxinghu at gmail.com> |
| BugReports: | https://github.com/xinghuq/HierDpart/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/xinghuq/HierDpart |
| NeedsCompilation: | no |
| SystemRequirements: | GNU make |
| Materials: | README |
| CRAN checks: | HierDpart results |
| Reference manual: | HierDpart.pdf |
| Vignettes: |
Instruction to pPackage HierDpart |
| Package source: | HierDpart_0.1.2.tar.gz |
| Windows binaries: | r-devel: HierDpart_0.1.2.zip, r-release: HierDpart_0.1.2.zip, r-oldrel: HierDpart_0.1.2.zip |
| OS X binaries: | r-release: HierDpart_0.1.2.tgz, r-oldrel: HierDpart_0.1.2.tgz |
Please use the canonical form https://CRAN.R-project.org/package=HierDpart to link to this page.


Gujarat High Court Case Information System Print CR.A/196/2008 8/ 8 JUDGMENT IN THE HIGH COURT OF GUJARAT AT AHMEDABAD CRIMINAL APPEAL No. 196 of 2008 For Approval and Signature: HONOURABLE MR.JUSTICE Z.K.SAIYED ========================================================= 1 Whether Reporters of Local Papers may be allowed to see the judgment ? 2 To be referred to the Reporter or not ? 3 Whether their Lordships wish to see the fair copy of the judgment ? 4 Whether this case involves a substantial question of law as to the interpretation of the constitution of India, 1950 or any order made thereunder ? 5 Whether it is to be circulated to the civil judge ? ========================================================= SHRI HARKISHAN RAMNIKLAL JOSHI(ASST.LAW OFFICER) - Appellant(s) Versus M/S.KRISHANKANT CHEMICALS IND. & 3 - Opponent(s) ========================================================= Appearance : MR SUNIL L MEHTA for Appellant(s) : 1, MR RR TRIVEDI for Opponent(s) : 1 - 3. MR BHAVESH P TRIVEDI for Opponent(s) : 1 - 3. MR HL JANI, APP for Opponent(s) : 4, ========================================================= CORAM : HONOURABLE MR.JUSTICE Z.K.SAIYED Date : 27/01/2010 ORAL JUDGMENT
The present appeal, under section 378(4) of the Code of Criminal Procedure, 1973, is directed against the judgment and order of acquittal dated 08.09.2006 passed by the learned Judicial Magistrate, First Class, Junagadh, in Criminal Case No. 7380 of 1993, whereby the learned Magistrate has acquitted the respondents accused from the charges levelled against them.
The brief facts of the prosecution case is that the respondent No. 1 is the company and respondents No.2 & 3 are the Partners of the said respondent No.1 Company. It is alleged that in the said company is engaged in doing the business of chemical and discharging the effluent water without purifying the same. It is alleged that on 27.5.1993 Shri K.C. Pancholi, Assistant Engineer, Shri J.D. Kalyani and Shri B.R. Kochara, of the office of the Board at Rajkot, have visited the factory of respondent No.1 for inspection, after issuing the notice. They have taken the sample water from the said company. It is alleged that after sealing the sample the same was sent to the Public Analyst for analysis. It is alleged that the Public Analyst submitted the Report on 17.7.1993 and as per the said Report it was found that the accused have committed the breach of Section 24 & 25 of the Water Act and, therefore, they are responsible for the offences under Sections 43, 44 and 47 of the Water Act. Thereafter, after obtaining sanction complaint has been filed against the respondents accused. Thereafter, the trial was conducted against the respondents accused. The trial Court examined the witnesses and also considered the documentary evidence led before it and after considering the documentary as well as oral evidence has acquitted the respondents accused from the charges levelled against them.
It was contended by learned Advocate Mr. Sunil Mehta for the appellant that the judgment and order of the learned Magistrate is not proper, legal and it is erroneous. He has also contended that the learned Magistrate has not considered the evidence of the witnesses. He has contended that the Board Officers have followed the rules prescribed by law and the Officer of the Board have also followed the procedure of taking the sample. The sample was seized and sealed properly. Yet, the learned Magistrate has not considered the evidence of prosecution. Therefore, the order impugned in this appeal passed by the learned Magistrate requires to be quashed and set aside.
Learned Advocate, appearing for the respondents original accused, have supported the judgment and order of acquittal passed by the trial Court and contended that the trial Court has rightly acquitted the respondents accused.
It is a settled legal position that in acquittal appeal, the Appellate Court is not required to re-write the judgment or to give fresh reasonings when the Appellate Court is in agreement with the reasons assigned by the trial court acquitting the accused. In the instant case, this Court is in full agreement with the reasons given and findings recorded by the trial Court while acquitting the respondents- accused and adopting the said reasons and for the reasons aforesaid, in my view, the impugned judgment is just, legal and proper and requires no interference by this Court at this stage. From the perusal of record it appears that the prosecution has not followed Rule 27, which is mandatory and, therefore, there is no question to entertain this Appeal. Hence, this appeal requires to be dismissed.
Even in a recent decision of the Apex Court in the case of State of Goa V. Sanjay Thakran & Anr. Reported in (2007)3 SCC 75, the Court has reiterated the powers of the High Court in such cases. In para 16 of the said decision the Court has observed as under:
16. From the aforesaid decisions, it is apparent that while exercising the powers in appeal against the order of acquittal the Court of appeal would not ordinarily interfere with the order of acquittal unless the approach of the lower Court is vitiated by some manifest illegality and the conclusion arrived at would not be arrived at by any reasonable person and, therefore, the decision is to be characterized as perverse. Merely because two views are possible, the Court of appeal would not take the view which would upset the judgment delivered by the Court below. However, the appellate court has a power to review the evidence if it is of the view that the conclusion arrived at by the Court below is perverse and the Court has committed a manifest error of law and ignored the material evidence on record. A duty is cast upon the appellate court, in such circumstances, to re-appreciate the evidence to arrive to a just decision on the basis of material placed on record to find out whether any of the accused is connected with the commission of the crime he is charged with.
Similar principle has been laid down by the Apex Court in the cases of State of Uttar Pradesh Vs. Ram Veer Singh & Ors, reported in 2007 AIR SCW 5553 and in Girja Prasad (Dead) by LRs Vs. state of MP, reported in 2007 AIR SCW 5589. Thus, the powers which this Court may exercise against an order of acquittal are well settled.
It is also a settled legal position that in acquittal appeal, the appellate court is not required to re-write the judgment or to give fresh reasonings, when the reasons assigned by the Court below are found to be just and proper. Such principle is laid down by the Apex Court in the case of State of Karnataka Vs. Hemareddy, reported in AIR 1981 SC 1417, wherein, it is held as under:
& This court has observed in Girija Nandini Devi V.
Bigendra Nandini Chaudhary (1967)1 SCR 93: (AIR 1967 SC 1124) that it is not the duty of the appellate court when it agrees with the view of the trial court on the evidence to repeat the narration of the evidence or to reiterate the reasons given by the trial court expression of general agreement with the reasons given by the Court the decision of which is under appeal, will ordinarily suffice.
Thus, in case the appellate court agrees with the reasons and the opinion given by the lower court, then the discussion of evidence is not necessary.
I have gone through the judgment and order passed by the trial court. I have also perused the oral as well as documentary evidence led by the trial court and also considered the submissions made by learned Advocate for the appellant. The trial Court has found that in Exh.43 there is no signature of the accused. The trial Court has also found that in Exh.46 signature of the accused is not obtained and the copy of the same is also not provided to the accused. The trial Court has also observed that panchas have not been examined. The trial Court has found that from the deposition of the witnesses and perusing the record it is clearly established that the prosecution has failed to prove its case beyond reasonable doubt. The trial court while considering the oral as well as documentary evidence has clearly observed that the prosecution has not followed the mandatory provision of the Act and the Rules. The trial Court has clearly found that the prosecution has failed to prove its case beyond reasonable doubt. Even in the present appeal, nothing is produced or pointed out to rebut the conclusion of the trial Court. Thus, from the evidence itself it is established that the prosecution has not proved its case beyond reasonable doubt.
Mr Sunil Mehta learned Advocate for the appellant is not in a position to show any evidence to take a contrary view of the matter or that the approach of the trial court is vitiated by some manifest illegality or that the decision is perverse or that the trial court has ignored the material evidence on record.
In the above view of the matter, I am of the considered opinion that the trial court was completely justified in acquitting the respondent of the charges leveled against him.
I find that the findings recorded by the trial court are absolutely just and proper and in recording the said findings, no illegality or infirmity has been committed by it.
I am, therefore, in complete agreement with the findings, ultimate conclusion and the resultant order of acquittal recorded by the court below and hence find no reasons to interfere with the same. Hence the appeal is hereby dismissed. R & P to be sent back to the trial Court, forthwith. Bail bond, if any, stands cancelled.
(Z.K.
SAIYED, J.) sas Top


I am a passionate person in software engineering who has ability to work as an individual or as a team and deliver quality software products.
Involved in developing following features User security, agent information and management, levies returns, levies payments and payment history, return history, APIs and service interfaces. Some of the notable projects include Levies Online (https://leviesonline.agriculture.gov.au), Phoenix, Levy Receipient Portal, IFresh
Work collaboratively with the business to develop following functionalities Vacancy, Vacancy Notice board, Vacancy applications, Roles and Positions, Screening templates, Screening Criteria and ConnX Automated Process etc. Notable projects ConnX (www.connx.com.au), ConnXCareers (https://connx.connxcareers.com/)
Engaged in designing and developing ConnX Roster modeling which is designed to create work pattern models. The module provide the ability to create models using current work pattern or from other existing patterns.
Major roles and resposilities included developing Inter Dealer Broker which is an intermediary that facilitates transactions between broker and dealers.
I am trained Carnatic Vocalist who had participated in various music competitions.
Cuurently learning Ukelele.


Thanks for coming to our conference. It wouldn't have been the same without you!
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Political activism is at the heart of any democracy and your voice needs to be heard. Please consider reaching out to your representatives:
| You can find your representatives by visiting www.commoncause.org/take-action/find-elected-officials |


Deafness
Hearing disability is divided into two categories: “deafness” and “hard of hearing”.
Deafness involves “a substantial uncorrectable impairment of hearing in both ears”. “Some deaf individuals' first language is a sign language, and they may or may not be fluent readers of a written language.
To use the Web, people who are deaf may rely on captions for audio content.” (Brewer, 1999)
Barriers that deaf people may encounter online include:
Hard of hearing
“A person with a mild to moderate hearing impairment may be considered hard of hearing.” (Brewer, 1999)
People with impaired hearing may rely on subtitles and audio amplification of audio content when using the Internet. The obstacles encountered on the Internet include:
“lack of captions or transcripts for audio content.” (Brewer, 1999)
According to data collected by the World Federation of the Deaf (WFD), about 80% of the deaf people in the world have insufficient education and/or literacy skills, low language skills and chaotic living conditions. (Debevc, 2009)
People with impaired hearing or deaf disorder will counter a series of troubles when they surf the Internet. In most cases, people with deaf have difficulties when they read text element, as the text is designed based on oral language . Oral languages are strange to the deaf as their first language is sign language (Jensen, 2016). Hence, it is necessary for us to develop tools to solve their problems on the Internet.
In Center for Deaf blindness and Hearing Loss in Aalborg, Denmark, they conducted requisitions of deaf subjects and made the observation. The center has drawn following conclusions:
Useful toolkits
1. Sign Language Interpreter Module:
Debevc (2009) introduces a Sign Language Interpreter Module (SLIM), and this module can offer so sign language video to users.
The function of this tool is 'provides the translation of a specific word, text, image, photo, animation and any other video on the Web.' (Debevc, 2009)
2. Sign language dictionary embedded in browsers:
Center for Deaf blindness and Hearing Loss in Aalborg, Denmark has developed a prototype of a website, which has embedded sign language dictionary and it can translate keywords to sign language. (Jensen, 2016)


This code is beta, so your comments and suggestions would be very helpful. I know that there are bugs. That is why it is beta. Please take the time to fill out a detailed bug report when you find one. First person to report a bug gets full versions of all future versions of this software for free. I will create a site for this software shortly.
Geoff Granum,
<EMAIL_ADDRESS>Purdue University
Aeronautical & Astronautical Engineering


- Cras justo odio
- Dapibus ac facilisis in
- Morbi leo risus
- Porta ac consectetur ac
- Vestibulum at eros
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Lorem ipsum dolor sit amet, consectetur.
150.000.000$
"...the location is one of the most beautiful to be found, holy and unapproachable, a worthy temple for the divine friend who has brought salvation and true blessing to the world." - King Ludwig II of Bavaria
"Schonbrunn wasn't just a palace, it was a tone that either one carries forever in one's soul or one does not. It was the most beautiful thing in my life. The allés in Schönbrunn. The blue light in the dormitory at the academy, the great white stairwell with the baroque statue."


Working with over 3,000 technology experts, Mapt provides you with a reference library of eBooks and videos that keeps your skills up-to-date and provides you with practical solutions. No matter what situation you face, one of our authors has been there before. Whether they work for IBM or PayPal, our authors are from all over the world, and each one brings their own unique style to help you learn. What unites them is a passion for helping you put your learning into practice, as quickly as possible.


WITNESS LIST State Affairs Committee February 22, 1999-1:30P HB 156 For: Larson, Dohn (Texas Classroom Teachers Association) Miller, Karen (Self and Texas Parent Teacher Association) Oppel, Rich (Self and Texas Daily Newspaper Association; Texas Press Association) Raab, Ted Melina (Texas State Employees) Schneider, Rob (Consumers Union) Smith, Tom "Smitty" (Public Citizens Member) Woodford, Suzy (Common Cause Texas) Against: Shields, Brad (Self) Sullivan, Mike (Self and Texas Association of School Boards) On: Horton, Susan (Texas Municipal League) Millsap, Michael (Self and UT System) Registering, but not testifying: For: Allison, Jim (County Judges and Commissioners Association of Texas) Schneider, Michael (Texas Association of Broadcasters) Zucker, Charles (Texas Faculty Association) HB 304 Registering, but not testifying: For: Smith, Tom "Smitty" (Public Citizens Member) Woodford, Suzy (Common Cause Texas) HB 432 For: Joiner, Gary (Texas Farm Bureau) Pinkus, David (Small Business United of Texas) Pollard, Mike (Texas Association of Life and Health Insurers) Against: James, Reggie (Consumers Union SW Regional Office) Registering, but not testifying: Against: Smith, Tom "Smitty" (Public Citizens Member) HB 471 Registering, but not testifying: For: McDonald, Carol (Independent Colleges and Universities of Texas, Inc.) Wood, Karen (Baylor University) HB 595 For: Smith, Tom "Smitty" (Public Citizens Member) HB 596 For: Hagert, Celia (Center for Public Policy Priorities) Hinojosa, Walter (Texas AFL-CIO) Oppel, Rich (Self and Texas Daily Newspaper Association; Texas Press Association) Raab, Ted Melina (Texas State Employees Union) Schneider, Rob (Consumers Union) Smith, Tom "Smitty" (Public Citizens Member) Wilson, Nanci (Self and The Texas Network) Woodford, Suzy (Common Cause Texas) On: Miller, Karen (Self) Registering, but not testifying: For: Dieter, Alison (Gray Panthers non-profit organization) Schneider, Michael (Texas Association of Broadcasters) Simpson, Dee (American Federation of State County and Municipal Employees) Willis, D.L. Dally (Communications Workers of America) HB 599 For: Borges, Walt (Court Watch; Texas Watch) Raab, Ted Melina (Texas State Employees Union) Schneider, Rob (Consumers Union) Smith, Tom "Smitty" (Public Citizens Member) Woodford, Suzy (Common Cause Texas) On: Brown, Harvey (District Court Judges of Harris County) Registering, but not testifying: On: Davis, Denise (Texas Judicial Council) Electric Restructuring For: Kroger, Stephanie (Self and Texas Coalition for Competetive Electricity) Selig, Clyde (Self) On: Williams, Mike (Texas Electric Cooperatives)


Editing Mode
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Joint Match
Joint Oppose
Rotation
Translation
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Animation
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Slider Ranges
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frequency
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Node.js v0.10.35 Manual & Documentation
Table of Contents
Timers#
Stability: 5 - Locked
All of the timer functions are globals. You do not need to require()
this module in order to use them.
setTimeout(callback, delay, [arg], [...])#
To schedule execution of a one-time callback
after delay
milliseconds. Returns a
timeoutObject
for possible use with clearTimeout()
. Optionally you can
also pass arguments to the callback.
It is important to note that your callback will probably not be called in exactly
delay
milliseconds - Node.js makes no guarantees about the exact timing of when
the callback will fire, nor of the ordering things will fire in. The callback will
be called as close as possible to the time specified.
clearTimeout(timeoutObject)#
Prevents a timeout from triggering.
setInterval(callback, delay, [arg], [...])#
To schedule the repeated execution of callback
every delay
milliseconds.
Returns a intervalObject
for possible use with clearInterval()
. Optionally
you can also pass arguments to the callback.
clearInterval(intervalObject)#
Stops an interval from triggering.
unref()#
The opaque value returned by setTimeout
and setInterval
also has the method
timer.unref()
which will allow you to create a timer that is active but if
it is the only item left in the event loop won't keep the program running.
If the timer is already unref
d calling unref
again will have no effect.
In the case of setTimeout
when you unref
you create a separate timer that
will wakeup the event loop, creating too many of these may adversely effect
event loop performance -- use wisely.
ref()#
If you had previously unref()
d a timer you can call ref()
to explicitly
request the timer hold the program open. If the timer is already ref
d calling
ref
again will have no effect.
setImmediate(callback, [arg], [...])#
To schedule the "immediate" execution of callback
after I/O events
callbacks and before setTimeout
and setInterval
. Returns an
immediateObject
for possible use with clearImmediate()
. Optionally you
can also pass arguments to the callback.
Immediates are queued in the order created, and are popped off the queue once
per loop iteration. This is different from process.nextTick
which will
execute process.maxTickDepth
queued callbacks per iteration. setImmediate
will yield to the event loop after firing a queued callback to make sure I/O is
not being starved. While order is preserved for execution, other I/O events may
fire between any two scheduled immediate callbacks.
clearImmediate(immediateObject)#
Stops an immediate from triggering.


HAL-SET-PROPERTY(1) HAL-SET-PROPERTY(1) NAME hal-set-property - set a property on a device object SYNOPSIS hal-set-property [options] DESCRIPTION hal-set-property sets a property on a device object in the HAL device database. For more information about both the big picture and specific HAL properties, refer to the HAL spec which can be found in /usr/share/doc/hal-doc/spec/hal-spec.html depending on the distribution. OPTIONS The following options are supported: --udi The UDI (Unique Device Identifier) of the device object. --key The name of the property. --int Set value property of the property to a 32-bit signed integer. The value passed is assumed to be decimal unless it's prefixed with 0x or x for hexadecimal values. --uint64 Set value property of the property to a 64-bit unsigned integer. The value passed is assumed to be decimal unless it's prefixed with 0x or x for hexadecimal values. --string Set value property of the property to a string. --double Set value property of the property to a floating point number. --bool Set value property of the property to boolean, e.g. true or false. --strlist-pre Prepend an item to a string list. --strlist-post Append an item to a string list. --strlist-rem Remove an item from a string list. --remove Remove a property. --help Print out usage. --version Print the version. RETURN VALUE If setting the property succeeds, this program will exit with exit code 0. On errors a non-zero the program will exit with a non-zero exit code. Note that setting properties on the HAL device database usually requires super user privileges. BUGS Please send bug reports to either the distribution or the HAL mailing list, see http://lists.freedesktop.org/mailman/listinfo/hal on how to subscribe. SEE ALSO hald(8), lshal(1), hal-get-property(1), hal-find-by-property(1), hal- find-by-capability(1) AUTHOR Written by David Zeuthen<EMAIL_ADDRESS>with a lot of help from many others. HAL-SET-PROPERTY(1)


A young boy learns that he has powers and is not of this Earth.
The story revolves around United Nations employee Gerry Lane (Pitt).
Mike Wazowski and James P. Sullivan are an inseparable pair, but that wasn't always the case.


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Please email us with the email address you used to log in and we'll investigate.
In the mean time, you can email the export from your EMS to the same address and we'll manually process your data.
{% endif %} {% endblock council_content %}


About Me
As a child I was offered so many opportunities, I did not even recognize them as such. I was afforded the ability to fail, and did so, over and over again. In my late twenties I found coding, and started to develop success. Building code also helped me to build power, and altered the way in which I interact with our world and within my community. I know now that opportunity is far more rare and special than I understood as a child. I have spent the last 7 years of my professional life understanding the challenges faced by underrepresented communities in the technology development space and working to recreate the kind of opportunities I was given.
In my extended college years, I studied philosophy, religion, astronomy, physics, and engineering. But it was my childhood exposure to computer programming from which I forged a career. That skill, latent for over a decade, awoke and gave me power and opened opportunities.
The skills I learned running programs on our Apple IIe as a child led to further chances to grow, learn, and connect. I got to work with the top scientists in their respective fields, devising cutting edge solutions at Lawrence Berkley National Lab. I had the privilege to leave that dream job to seek another; creating my own technology and developing an online platform to connect employees with training.
Programming skills have placed me in the decision-making team within every organization with which I have worked. I skipped the years of paying dues in every industry - from healthcare to education, and technology to politics - and had the opportunity to see my work directly and immediately impact the mission.
By 2012, when a company I helped to form was sold, those skills had also given me financial power. It was then that I started Code for Progress, an organization designed to assist others in building the same types of power I found in coding. I designed that program to address some of the imbalance in opportunity, and help individuals build power for themselves and within their communities.
I have had many successes, and a good deal more challenges in the 5 years I've run Code for Progress, but the experience and understanding I've gained, I consider some of my most valuable assets. I am now eager to place the full body of that experience, all of my energy, and my hopeful spirit into bringing the program to Philadelphia.
Code for Progress Philadelphia's intent to provide exposure, guidance, and a runway clear of obstacles - will help to supply some of the elements necessary to build opportunity. It is clear that where these elements come together, power is built.


"Light Makes Right"
March 1, 1988
Volume 1, Number 3
Compiled by
All contents are copyright (c) 1988, all rights reserved by the individual authors
Archive locations: anonymous FTP at
ftp://ftp-graphics.stanford.edu/pub/Graphics/RTNews/,
wuarchive.wustl.edu:/graphics/graphics/RTNews, and many others.
You may also want to check out the Ray Tracing News issue guide and the ray tracing FAQ.
- Eric
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'I'm currently hanging out at Apple thinking about "3D graphics for the rest of us" and how to keep the jaggies away from personal computers. (But there is this Cray sitting about 50 feet away. Hmmm...)'
# # John Peterson - bicubic splines, texturing # Apple Computer (graduated University of Utah, 1988) alias john_peterson<EMAIL_ADDRESS>asked him for ray tracers at the University of Utah. So, Tom Malley and Rod Bogart (whose initials are 'RGB') are now subscribers.
From Tom: My thesis research was similar to what John Wallace described, being a two pass approach to radiosity to include specular reflection and transparency. Form factors were all calculated via ray tracing, however. I did some brief examination of different ray intersection methods along the way (Rubin-Whitted, Kay-Kajiya, and Glassner).
# # Tom Malley - blending ray tracing and radiosity # Evans & Sutherland (graduated University of Utah, 1988) #<EMAIL_ADDRESS>cs.utah.edu!esunix!tmalley) alias tom_malley<EMAIL_ADDRESS>To quote John Peterson about Rod Bogart: Rod developed a really neat method for using ray tracing to integrate computer generated pictures with real world images (coming soon to a SIGGRAPH near you...).
# # Rod Bogart - blending ray tracing and images # University of Utah alias rod_bogart<EMAIL_ADDRESS>back to contents
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Just a quick response to your football stadium/teapot example. When you subdivide a node, look at its children. If only one child is non-empty, replace the original node with its non-null child. Do this recursively until the subdivision criterion is satisfied. I do this in my spacetime ray tracer, and the results can be big. The ray propagation can get just a bit more complex, but there are clever rays to keep it simple (see John Amanatide's article in Eurographics '87, plus I have a scheme that hope to write up soon...).
Better yet, go with a hybrid space subdivision/bounding volume scheme, such as the one described in my spacetime paper (poorly described in the ntro to RT notes, but better described in the version slated for the March issue of CG&A; I'd be happy to mail you a preprint). I think this hybrid scheme gives the best of both worlds, and you can use whatever space subdivision and bounding volume techniques that you like in the two distinct phases of the algorithm. I use adaptive space subdivision and Kay's bounding slabs, and that combination seems to work pretty well.
And now I have to get back to moving into my office!
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From: Eric Haines (with a few extra comments than my original letter to Jim)
Your article on efficiency is fascinating. I hope to read it more carefully tonight and (eventually--we just came under a crunch of work) comment on it. Sounds like you've done a lot of serious thought and speculation on the possibilities. I agree with the philosophy of objects each having their own private hierarchies, and having the ability to hook these hierarchies up however you want. We've done that on a small scale with our tesselated spline surfaces: automatic hierarchy a la Goldsmith & Salmon (IEEE CG&A, May 1987) for everything, but then octrees for the spline surfaces themselves. A nice feature of Goldsmith is that you can weight the cost of each primitive into the algorithm: multiply its area by some intersection cost (which you'll probably have to figure out through experimentation) to give it a weighting. In this way a torus surface which has the same size bounding volume as a quadrilateral can be given a higher weighting factor. A higher cost has the effect of making the hierarchical tree less horizontal near the complicated object, i.e. there are more bounding volumes overall, with a few complicated objects in each. This is what you want, since you'd rather spend a little extra time on intersecting bounding volumes than wasting a lot of time intersecting the empty space around costly objects.
____
Response from: Jim Arvo
I'm glad you found my article interesting. All your interesting mail finally motivated me to contribute to the discussion. I thought I would toss out a pet idea of mine and see if it sparked any debate. It turns out that Jeff Goldsmith also looked at simulated annealing for bounding box hierarchies. One day one of us will get some results. Hopefully not negative results!
With all the talk about octrees and such, it's clear that there are a number of potential papers "waiting in the wings". I've been thinking that by getting the right collaborations going, we (the ray tracing group) could easily "hand" IEEE several related papers, effectively defining a theme issue. What do you think?
____
My reply:
The efficiency article collection sounds possible. Another idea which someone (Mike Kaplan, maybe? I forget) mentioned at last SIGGRAPH was "A Characterization of Ten Ray Tracing Efficiency Algorithms". If well done, this would be a classic. There are probably entirely new schemes still to be found, and certainly trying to optimize and figure out good hybrid methods is an area ripe for development. But right now many of the structures and algorithms are in place, and still have not been fully compared. Timings are unconvincing, and statistics are worthwhile but don't tell the whole story. An in-depth comparison of the major algorithms and techniques to improve these would be wonderful. Someday, someday ... well, my hope is that a few of us could do some writing along these lines, even if it's just brainstorming on how to compare particular algorithms in a rigorous fashion (e.g. How can we simulate a scene mathematically? OK, idealize each object as a box or sphere for simplicity. Now, how do we distribute the points to get realistic clustering? Once we have a "scene generator" which could create various typical distributions of objects in a scene, then we have to analyze how this generator would interact with each algorithm, and be able to predict how each efficiency scheme deals with the scenes generated. Or there might be simpler ways to isolate and analyze each factor which affects the efficiency of a scheme. Anyway, whatever, but this stuff looks fun!). Understanding the strengths of the various techniques seems vital to being able to do any kind of "annealing" process for optimization.
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The obvious corollary to that idea has a little more reach to it. Since illumination rays form the bulk of the rays we trace, getting the nearest intersection is of limited value. In addition, if CSG is used, more times occur when the nearest intersection is of less value. This seems to indicate that space tracing techniques are doing some amount of needless work. Since it doesn't really cost that much, perhaps it is not a flaw, but maybe space tracers should consider approaches that don't worry about where along the path we are and optimize that problem instead.
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I agree completely with your comment about libraries. Mine is a crucial resource for me. Here are some of my favorite books that are in my office:
Geometry:
Computational Geometry for Design and Manufacture Faux & Pratt --an early CAD text. It has lots of good stuff on splines and 3D math.
Differential Geometry of Curves and Surfaces DoCarmo --A super text on classical differential geometry. (Not quite the same as analytic geometry.)
CRC Standard Math Tables --This has an awesome section on analytic geometry. Calculus, too. Can't live without it. It is not the same as the first part of the Chemistry and Physics one.
Analytic Geometry Steen and Ballou --Once was the standard college text on the subject. That was a long time ago, but it is very easy to read and it covers the fundamentals.
Computing:
Data Structures and Algorithms --Aho, Hopcroft and Ullman Read anything by these guys.
Data Structure Techniques --Standish More How-to than AHU's tome.
Numerical Analysis --Burden, Faires, and Reynolds I have the other two, as well. This is the least complete of the three, but the algorithms inside are childishly easy to implement. They always seem to work, too. Best of all, for many cases, they have test data and solutions.
Software Tools --Kernighan and Plauger How to write command line interpreters, editors, macro expanders, the works. Great reading.
Fundamentals of Computer Algorithms --Horowitz and Sahni Less technical than AHU, but pretty technical. Thicker. It may very well answer the problem you can't figure out straight off.
The Art of Computer Programming --Knuth The "Encyclopedia"
Physics: (Seem awfully useful sometimes)
Gravitation --Misner, Thorne, and Wheeler The thickest book on my shelf. It's a paperback, too. (It's bent three bookends permanently. Cheap JPL ones.) Truly a tome on modern physics.
Modern Physics --Tippler Much easier to read than MTW. Has lots of good appendices.
University Astronomy --Pasachoff and Kuttner I read this book for fun. I wonder why I didn't read it while I was taking Kuttner's course?
The Feynman Lectures on Physics Awesome first course. Most of my needs are problems in the text.
Graphics, etc:
Raster Graphics Handbook --Conrac All about fundamentals of the craft.
Light and Color in Nature and Art --Williamson and Cummings Much easier to read than Hall's thesis, but less technical as well.
Etc, Etc:
The Random House Dictionary of the English Language, College Edition The best collegiate sized dictionary around. By far.
The Chicago Manual of Style Has most of the answers. Did you know that to recreate is to have fun, but to re-create is computer graphics?
The Elements of Style The one that came before computers.
back to contents
This bug was one I had when implementing octree subdivision for ray tracing. The basic algorithm used was Glassner's: once you intersect the octree structure, move the intersection point in one half of the smallest cube's dimension in the direction normal to the wall hit. In other words, find out what cube is the next cube by finding a point that should be well inside of it, then translating this point into integer octree coordinates and traversing the octree downwards until a leaf node is found.
However, there are some subtle errors that can occur with moving to the next octree cube. My favorite is almost hitting the edge of a cube, moving into the next cube, then getting caught moving to the cube diagonal to this cube, i.e. moving from cube 1 to 2 to 3 ...
X--> +---+---+ ^ | 2 | $ | Numbers are the order of cubes moved through. | +---#---+ Y | 1 | 3 | +---+---+ ^________ray started here, and hit almost at the "#". (ray is in +X, +Y direction)
This went into an infinite loop, going between 2 and 3 forever. The reason was that when I hit the boundary 1&2 I would add a Y increment (half minimum box size) to the intersection point, then convert this to find that I was now in box 2. I would then shoot the ray again and it would hit the wall at 2&$. To this intersection point I would add an X increment. However, what would happen is that the Y intersection point would actually be ever so slightly low - earlier when I hit the 1&2 wall adding the increment pushed us into box 2. But now when the Y intersection point was converted it would put us in the 1+3 boxes, and X would then put us in box 3. Basically, the precision of the machine made the mapping between world space and octree space be ever so slightly off.
The infinite loop occurred when we shot the ray again at box 3. It would hit the 3/$ wall, get Y incremented, and because X was ever so slightly less than what was truly needed to put the intersection point in the 3+$ boxes, we would go back to box 2, ad infinitum. Another way to look at this is that when we would intersect the ray against any of the walls near the "#" point, the intersection point (due to roundoff) was always mapping to box 1 if not incremented. Incrementing in Y would move it to box 2, and in X would move it to box 3, but then the next intersection test would yield another point that would be in box 1. Since we couldn't increment in both directions at once, we could never get past 2 and 3 simultaneously.
This bug occurs very rarely because of this: the intersection points all have to be such that they are very near a corner, and the mapping of the points must all land within box 1. This problem occurred for me once in a few million rays, which of course made it all that much more fun to search for it.
My solution was to check the distance of the intersections generated each time: if the closest intersection was a smaller distance from the origin than the closest distance for the previous cube move, then this intersection point would not be used, but rather the next higher would be. In this way forward progress along the ray would always be made.
By the way, I found that it was worthwhile to always use the original ray origin for testing ray/cube intersections - doing this avoids any cumulative precision errors which could occur by successively starting from each new intersection point. To simulate the origin starting within the cube would simply test only the 3 cube faces which faced away from the ray direction (this was also faster to test).
Anyway, hope this made sense - has anyone else run into this bug? Any other solutions?
back to contents
[I agree: my problem now is that Y=0 is the bottom edge of the screen when dealing with the graphics package (HP's Starbase), and Y=0 is the top when directly accessing the frame buffer (HP's SRX). -- EAH]
back to contents
All for now,
Eric
back to contents


Lisk Swift
Lisk Swift is a Swift 4 library for Lisk - the cryptocurrency and blockchain application platform. It allows developers to create offline transactions and broadcast them onto the network. It also allows developers to interact with the core Lisk API, for retrieval of collections and single records of data located on the Lisk blockchain. Its main benefit is that it does not require a locally installed Lisk node, and instead utilizes the existing peers on the network. It can be used on any environment that runs Swift 4, including iOS, tvOS, macOS, watchOS.
Lisk Swift is heavily inspired by Lisk JS
Features
- [x] Local Signing for maximum security
- [x] Targets Lisk 1.0.0 API
- [x] Directly based on lisk-js
- [x] Swift 4.0
- [x] Unit Tests (87% coverage)
- [x] Documentation
API
Documentation
https://andrewbarba.github.io/lisk-swift/
Usage
Import Framework
import Lisk
Send LSK
let address = ...
let secret = ...
// Send LSK on the Mainnet
Transactions().transfer(lsk: 1.12, to: address, secret: secret) { response in
switch response {
case .success(let result):
print(result.transactionId)
case .error(let error):
print(error.message)
}
}
Send LSK on Testnet
let address = ...
let secret = ...
// Send LSK on the Testnet
Transactions(client: .testnet).transfer(lsk: 1.12, to: address, secret: secret) { response in
switch response {
case .success(let result):
print(result.transactionId)
case .error(let error):
print(error.message)
}
}
Testnet
By default, all modules are initialized with an APIClient
pointing to the Lisk Mainnet. You can optionally pass in a specific client to any modules constructor:
let mainTransactions = Transactions()
let testTransactions = Transactions(client: .testnet)
To default all modules to a specific client you can set the shared client:
APIClient.shared = .testnet
And then all modules initialized will default to Testnet:
// This will connect to Testnet
let transactions = Transactions()
Requirements
- iOS 10.0+ / macOS 10.12+ / tvOS 10.0+ / watchOS 3.0+
- Xcode 9.0+
- Swift 4.0+
Installation
Swift Package Manager
// swift-tools-version:4.0
import PackageDescription
let package = Package(
name: "My Lisk App",
dependencies: [
.package(url: "https://github.com/AndrewBarba/lisk-swift.git", from: "1.0.0-beta")
]
)
CocoaPods
CocoaPods 1.1.0+ is required to build lisk-swift
pod 'Lisk', '~> 1.0.0-beta'
Carthage
github "AndrewBarba/lisk-swift" ~> 1.0.0-beta
Thank You
To show support for continued development feel free to vote for my delegate: andrew
Or donate LSK to<PHONE_NUMBER>5736502769L


CHAPTER THREE. PARSING
a
:=
7
Old
num
10
Stack
:=
6
id
4
↓
;
b
:=
c
+
(
±
²³
´
6-token queue
Current
(
8
Stack
+
16
E
11
:=
6
id
4
;
3
S
2
↓
d
:=
5
+
6
,
d
)
$
FIGURE 3.38.
Burke-Fisher parsing, with an error-repair queue.
Figure 3.18
shows the complete parse of this string according to
Table 3.19
.
Generally, if a repair carries the parser
R
=
4 tokens beyond where it origi-
nally got stuck, this is “good enough.”
The advantage of this technique is that the LL(
k
) or LR(
k
) (or LALR, etc.)
grammar is not modiﬁed at all (no
error
productions), nor are the parsing
tables modiﬁed. Only the parsing engine, which interprets the parsing tables,
is modiﬁed.
The parsing engine must be able to back up
K
tokens and reparse. To do
this, it needs to remember what the parse stack looked like
K
tokens ago.
Therefore, the algorithm maintains
two
parse stacks: the
current
stack and
the
old
stack. A queue of
K
tokens is kept; as each new token is shifted, it
is pushed on the
current
stack and also put onto the tail of the queue; simul-
taneously, the head of the queue is removed and shifted onto the
old
stack.
With each
shift
onto the old or current stack, the appropriate reduce actions
are also performed.
Figure 3.38
illustrates the two stacks and queue.
Now suppose a syntax error is detected at the
current
token. For each possi-
ble insertion, deletion, or substitution of a token at any position of the queue,
the Burke-Fisher error repairer makes that change to within (a copy of) the
queue, then attempts to reparse from the
old
stack. The success of a modiﬁ-
cation is in how many tokens past the
current
token can be parsed; generally,
if three or four new tokens can be parsed, this is considered a completely
successful repair.
In a language with
N
kinds of tokens, there are
K
+
K
·
N
+
K
·
N
possible
deletions, insertions, and substitutions within the
K
-token window. Trying
80


Coding Quiz Challenge
Try to answer the following code-related questions within the time limit. Keep in mind that incorrect answers will penalize your score/time by ten seconds!
View highscores
Try to answer the following code-related questions within the time limit. Keep in mind that incorrect answers will penalize your score/time by ten seconds!


AmazeRec : You'll want to buy these!
Introduction and Motivation
- The recommendations which use metrics like rmse are based on explicit ratings which are not always reliable in
figuring out what the user really wants. We want to make use of product reviews, in particular the sentiments in the
reviews left by the users. The choice of words by a user is indicative of her preference/dislike towards a certain type
of product. By combining this insight with traditional algorithms like collaborative filtering/Matrix Factorization,
we create a recommender system that is more personalized to the user.
- Another improvement our recommender provides is the inclusion of standard reviews of recommended item from reputed sources rather than from other users.
Collaborative filtering does a good job at identifying the user interest but the actual reviews from other users provide little
information about the item. Instead, reading a review of recommended book in our case by New York times will provide a lot more relevant information to
the user.
Related Work
There are various approaches for recommenders that incorporate the reviews information to provide better recommendation e.g. HFT (Hidden Factors and Hidden Topics) which combine latent rating dimensions (such as those of latent-factor recommender systems) with latent review topics (such as those learned by topic models like LDA) . We were inspired by this idea and wanted to incorporate the simple sentiment information of the reviews in light weight.collaborative filtering models that does not add much of learning time and verify their performance on this new added feature.
Proposed solution
Our approach was to the get the sentiment score of the review on a scale of -1 to 1(-1= very bad, 1=very good) and then augment the actual rating with the sentiment score.
We tried various approaches to mix them
- Scaling the sentiment score from 1-5 and averaging it with actual rating
- Adding the sentiment score directly to the rating
- Suppressing the less signinficant reviews i.e. sentiment score between -0.5 to 0.5, and considering only the impact of only the stronger reviews.
- Just using the sentiment scores to get the recommendations
We found the best results for third approach opf supressing the less significant reviews.
Our Recommendation system invlolves following steps:
- Get sentiment scores
- Add the sentiment scores(suppresses) with rating to generate new ratings on a scale of 5.5 to 0.5
- Get the recommendation based on chosen algorithm
- Extract the actual standand reviews of the books obtained via NYT API
We tried this approach across various recommendation algorithms viz. simple Collaborative Filtering, Collaborative filtering with biases, Latent factors model,
implicit factorization model. Although implicit feedback model does not consider ratings we used this to compare the MRR(Mean Reciprocal rating)
with explicit factorization model.
Recommender Demo : For demo we have our recommender running in backend which writes the recommendations for a user in .json file.
It is then loaded from the server when the user logs in. Then, website dynamically loads the book details and also its
reviews though the Google API to
provide the user with our recommendations for her.
Evaluation and analysis of results
We have used RMSE and MAE as a metric to compare the performance of the recommender. Additionally we have extracted the top-k recommendations for a few users and compared the ranks of recommended items.
As we found it would be inefficient to find the recommendation for all the items for a user we considered only the items which close by users have rated.
Also, we compared the MRR scores to evaluate the performance of various approaches.
Collaborative Filtering: MAE: 0.67 , RMSE: 0.99
Collaborative filtering with sentiment scores: MAE: 0.842, RMSE: 1.19
SVD without sentiment scores: RMSE: 0.7432 MAE: 0.5305
SVD with sentiment scores: RMSE: 0.7873 MAE: 0.4928
MRR for Implicit and ecplicit factorization: 0.01 & 0.02
MRR for Implicit and ecplicit factorization(with sentiment): 0.01 & 0.02 (MRR score did not change)
Even Though RMSE Increased after adding sentiment scores, we observed that the for users with many neighbors ranks for top 50 items did not change much but he corresponding rating scale of prediction now varied from (0.5 to 5.5) providing more distinctions in top recommendations based on user review.
For users users with few neighbours it will be a good idea as we he will get the recommendation of neighbor with strong review than of equidistant neighbor with lighter reviews.
Also, we felt that mse might not always be the best way to compare a system that uses sentiment scores with one that uses ratings. So we used NDCG to calculate the effectiveness and found that the systems were almost equivalent in performance (0.923 vs 0.936)
Discussion
Providing the user with our recommendations in an effective manner proved to be challenging. There were several issues to consider :
- The biggest challenge was to decide the approach on using the review information to power the recommender. Even for calculating the sentiment score, a naive approach that assigns a score for each word and then aggregating the scores wouldn’t have worked well. We had to find a parser that calculated sentiment scores more intelligently. We used 'valence aware sentimet dictionary and sentiment reasoner (VADER)'
- Since we tried many approaches many of which yielded comparable results, we couldn’t decide how to better the accuracies even further. Our models include collaborative, SVD and BPR with ratings and/or sentiment scores.
- We found that user review could not be discarded and managed to get good results from the reviews. However a more complex model akin to HFT would probably give better results.
- How to provide useful information to the user regarding the product?
We use the Google API to obtain reviews from reputed sources like nytimes.com, npr.org, washingtonpost.com etc.
We would like to deploy our system and try to get feedback from actual users, we believe that this is the best way to evaluate our system.
Right now, our system relies on the user's caching to get the item details which is not realistic. In a practical system,
we would need to have a database of all the item details from which the details can be queried dynamically.
Project Demo :
https://vorzawk.github.io/irProjectWebsite/
2 minute Video :
https://www.youtube.com/watch?v=Mqql19gBgRk
Dataset :
http://jmcauley.ucsd.edu/data/amazon/
Repo for backend :
https://github.com/habib-baig/IR-project
Repo for frontend :
https://github.com/vorzawk/irProjectWebsite


You can edit the configuration here. Note that this will be effective on the next restart of the radio.


User Statistics
Full Name
user
User ID / Email
user
Creation Date
today
Total Logins
0
Session Creation Date
today


Catalog interface for Spark.
A column in Spark, as returned by listColumns
method in Catalog.
A column in Spark, as returned by listColumns
method in Catalog.
2.0.0
A database in Spark, as returned by the listDatabases
method defined in Catalog.
A database in Spark, as returned by the listDatabases
method defined in Catalog.
2.0.0
A user-defined function in Spark, as returned by listFunctions
method in Catalog.
A user-defined function in Spark, as returned by listFunctions
method in Catalog.
2.0.0
A table in Spark, as returned by the listTables
method in Catalog.
A table in Spark, as returned by the listTables
method in Catalog.
2.0.0
Catalog interface for Spark. To access this, use
SparkSession.catalog
.2.0.0


Website still in development phase. Site hosted on Site primarily for desktop Some mobile features may not work now.


Chester Bennington
#RIP Chester
- Early life -- Chester Charles Bennington was born on March 20, 1976, in Phoenix, Arizona.  Music career
- Early acts - Bennington first began singing with a band called Sean Dowdell and His Friends? They released an eponymous three-track cassette in 1993. Later, Dowdell and Bennington moved on to form a new band, Grey Daze, a post-grunge band from Phoenix, Arizona. The band recorded three albums: Demo in 1993, Wake/Me in 1994, and ...no sun today in 1997. Bennington left Grey Daze in 1998, but struggled to find another band.
- Linkin Park - Bennington was frustrated and almost ready to quit his musical career altogether when Jeff Blue, the vice president of artists and repertoire at Zomba Music in Los Angeles, offered him an audition with the future members of Linkin Park. Bennington quit his day job at a digital services firm[6] and took his family to California, where he had a successful audition with Linkin Park, who were then called Xero. He managed to record the song for his audition in a day, missing his own birthday celebration in the process. Bennington and Mike Shinoda, the band's other vocalist, made significant progress together, but failed to find a record deal. After facing numerous rejections, Blue, now a vice president of artists and repertoire at Warner Bros., intervened again to help the band sign with Warner Bros. Records.
- Dead by Sunrise - Bennington co-founded Dead by Sunrise, an electronic rock band from Los Angeles, California, with Orgy and Julien-K members Amir Derakh and Ryan Shuck in 2005.[19][20] Dead by Sunrise made their live debut in May 2008, performing four songs at the 13th anniversary party for Club Tattoo in Tempe, Arizona. The band released their debut album Out of Ashes on October 13, 2009.
- Stone Temple Pilots - In February 2013, Stone Temple Pilots parted ways with long-time lead singer Scott Weiland. The band recruited Bennington to replace Weiland in May 2013. On May 18, 2013, Bennington took the stage at KROQ's Weenie Roast with the band. The setlist included original Stone Temple Pilots songs, as well as their first single with Bennington on vocals called "Out of Time", which debuted on May 19 and was available for free download via their official website. It was later announced by Chester and the band in an exclusive KROQ interview that he was officially the new frontman of Stone Temple Pilots and discussed the possibility of a new album and tour. The song "Out of Time" is featured on their EP High Rise, which was released on October 8, 2013 Personal life
- Relationshops and children - Bennington had a child, Jaime (born May 12, 1996), from his relationship with Elka Brand.[25] In 2006, he adopted Brand's other son, Isaiah[25] (born November 8, 1997). He married his first wife, Samantha Marie Olit, on October 31, 1996.[26] They had one child together, Draven Sebastian (born April 19, 2002).[25] Bennington's relationship with his first wife declined during his early years with Linkin Park, and they divorced in 2005. In 2006, he married Talinda Ann Bentley, a former Playboy model with whom he had three children: Tyler Lee Bennington (born March 16, 2006) and twins Lilly and Lila (born November 6, 2011).[28]
- Interests - Bennington was a tattoo enthusiast.[30] He had done work and promotions with Club Tattoo, a tattoo parlor in Tempe, Arizona. Club Tattoo is owned by Sean Dowdell, Bennington's friend since high school with whom he played in two bands. Bennington was a fan of the Phoenix Suns, Arizona Cardinals, Arizona Diamondbacks, and Arizona Coyotes.[35] Death
- Suicide - Bennington was found dead at his home in Palos Verdes Estates, California; his housekeeper discovered his body around 9:00 a.m. PDT on July 20, 2017.His death was ruled a suicide. Mike Shinoda confirmed his death on Twitter, writing, "Shocked and heartbroken, but it's true. An official statement will come out as soon as we have one". On July 21, Brian Elias, the chief of operations for the office of the medical examiner-coroner, confirmed that a half-empty bottle of alcohol was found at the scene, but no other drugs were present. The band announced that they had canceled the North American leg of their One More Light Tour following Bennington's death and that tickets would be refunded.
- Funeral - Bennington's funeral was held at South Coast Botanic Garden in Palos Verdes, California, on July 29. In addition to his family members and close friends, many musicians who toured or played with Linkin Park were also in attendance. The service also included a full stage for musical tributes. Bennington was cremated.
Chester Bennington life summary:
"Who cares when someone's time runs out? If a moment is all we are We're quicker, quicker Who cares if one more light goes out? Well I do"
-- Chester Bennington


In the previous post we promised to provide a new release every 2 weeks and we are already breaking this promise as it’s been 3 weeks since then. We decided to wait with the release to merge several pull requests related to source-git support.
Now the good news. You can find a complete list of new features and improvements of version 0.3.0 in the changelog.
Features
- You can now specify your own hooks or actions to replace default packit behaviour. (More information can be found in the documentation).
- Packit supports pagure.io-based upstream projects.
- Commands
propose-update
andsync-from-downstream
supports copying directories. - A new command
status
! It displays useful upstream/downstream info. - Packit now supports Source-git. The functionality is not available, yet - we will add a CLI interface for it in the next release.
- You can now have a config file for packit in your home directory(
~/.config/packit.yaml
). - Packit installed from an RPM now has manpages.
packit status
example
$ packit status
Cloning repo: https://src.fedoraproject.org/rpms/packit.git -> /tmp/tmp84we_6n8
Downstream PRs: No open PRs.
f29: 0.2.0
f30: 0.2.0
master: 0.2.0


9.14.1. sklearn.grid_search.GridSearchCV¶
- class sklearn.grid_search.GridSearchCV(estimator, param_grid, loss_func=None, score_func=None, fit_params=None, n_jobs=1, iid=True, refit=True, cv=None, verbose=0, pre_dispatch='2*n_jobs')¶
Grid search on the parameters of a classifier
Important members are fit, predict.
GridSearchCV implements a “fit” method and a “predict” method like any classifier except that the parameters of the classifier used to predict is optimized by cross-validation.
Parameters : estimator: object type that implements the “fit” and “predict” methods :
A object of that type is instantiated for each grid point.
param_grid: dict :
Dictionary with parameters names (string) as keys and lists of parameter settings to try as values.
loss_func: callable, optional :
function that takes 2 arguments and compares them in order to evaluate the performance of prediciton (small is good) if None is passed, the score of the estimator is maximized
score_func: callable, optional :
A function that takes 2 arguments and compares them in order to evaluate the performance of prediction (high is good). If None is passed, the score of the estimator is maximized.
fit_params : dict, optional
parameters to pass to the fit method
n_jobs: int, optional :
number of jobs to run in parallel (default 1)
pre_dispatch: int, or string, optional :
Controls the number of jobs that get dispatched during parallel execution. Reducing this number can be useful to avoid an explosion of memory consumption when more jobs get dispatched than CPUs can process. This parameter can be:
- None, in which case all the jobs are immediatly created and spawned. Use this for lightweight and fast-running jobs, to avoid delays due to on-demand spawning of the jobs
- An int, giving the exact number of total jobs that are spawned
- A string, giving an expression as a function of n_jobs, as in ‘2*n_jobs’
iid: boolean, optional :
If True, the data is assumed to be identically distributed across the folds, and the loss minimized is the total loss per sample, and not the mean loss across the folds.
cv : integer or crossvalidation generator, optional
If an integer is passed, it is the number of fold (default 3). Specific crossvalidation objects can be passed, see sklearn.cross_validation module for the list of possible objects
refit: boolean :
refit the best estimator with the entire dataset
verbose: integer :
Controls the verbosity: the higher, the more messages.
Notes
The parameters selected are those that maximize the score of the left out data, unless an explicit score_func is passed in which case it is used instead. If a loss function loss_func is passed, it overrides the score functions and is minimized.
Examples
>>> from sklearn import svm, grid_search, datasets >>> iris = datasets.load_iris() >>> parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]} >>> svr = svm.SVR() >>> clf = grid_search.GridSearchCV(svr, parameters) >>> clf.fit(iris.data, iris.target) GridSearchCV(cv=None, estimator=SVR(C=1.0, coef0=..., degree=..., epsilon=..., gamma=..., kernel='rbf', probability=False, shrinking=True, tol=...), fit_params={}, iid=True, loss_func=None, n_jobs=1, param_grid=..., ...)
Methods
fit(X[, y]) Run fit with all sets of parameters score(X[, y]) set_params(**params) Set the parameters of the estimator. - __init__(estimator, param_grid, loss_func=None, score_func=None, fit_params=None, n_jobs=1, iid=True, refit=True, cv=None, verbose=0, pre_dispatch='2*n_jobs')¶
- fit(X, y=None, **params)¶
Run fit with all sets of parameters
Returns the best classifier
Parameters : X: array, [n_samples, n_features] :
Training vector, where n_samples in the number of samples and n_features is the number of features.
y: array, [n_samples] or None :
Target vector relative to X, None for unsupervised problems
- set_params(**params)¶
Set the parameters of the estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The former have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.
Returns : self :


Hi Edo.
I named my installation script as "install" and it was located in my $home/bin so, when I was trying to compile the program, the make process was not calling the system install located in /usr/bin but the one located in my $home/bin/. I corrected that and the NWChem installation was completely fine, but, when I execute the program it runs OK on a single core but the parallel does not, this is the tail of the .out file.
The calculation does not go any further of the last line " Singularity in Pulay matrix. Error and Fock matrices removed"
(Hope I made myself clear)
Thank you so much.
Grid_pts file = ./scan.tmp.gridpts.0
Record size in doubles = 12289 No. of grid_pts per rec = 3070
Max. records in memory = 4 Max. recs in file = 231234
Memory utilization after 1st SCF pass:
Heap Space remaining (MW): 65.49 65486212
Stack Space remaining (MW): 65.54 65535716
convergence iter energy DeltaE RMS-Dens Diis-err time
---------------- ----- ----------------- --------- --------- --------- ------
d= 0,ls=0.0,diis 1 -14.9106132446 -1.56D+01 9.98D-03 5.97D-03 0.2
Singularity in Pulay matrix. Error and Fock matrices removed.
|