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YouTube
YouTube 2005
In 2005, YouTube launched. Not many people could upload their videos like today. In fact, people used to simply visit the website and enjoy some short videos.
YouTube website was blank. Not a lot to enjoy or interact. The style was simple to navigate. There was not a lot you could do, but that is because it was in the early years.
YouTube 2020
Today, YouTube is the most used streaming platform. People can use it to upload videos, listen to music. Watch any sort of video or even movies. Anything related to entertainment, YouTube has it. It has taken the Entertainment industry to another level.
Similar too many websites today. The design is to make you interact with
other things. To attract your attention and make you click on a thumbnail.
Before we could not do that. Today everything is based on advertisements.
Anyone can upload a video and make money from it. Of course is not that
simple. Although, by uploading a trending video with an eye-catching thumbnail
you can attract attention.
Anything done in YouTube is free. You do not even need an account to watch
a video. In fact, YouTube is becoming so popular that they implemented
live television. Everything is moving into the internet today. They even
have their own film studio where they make their own shows or movies.


$20.00
$9.99
(Matching cat sweater avalible upon request)
$25.00
$50.00
$30.00
$14.00
$40.00
$15.00
$10.00
$30
$40
$200
.
$5
$75
$14
$10
$45


ExampleStore
You can directly use instance of this class.
exampleStore
Extends:
FrillCore.BaseStore → ExampleStore
Example store
Example:
this.getFrill().store('Example').getCount(); // get count
this.dispatch('COUNT_UP_BY', 15); // count up counter by 15
Test:
Constructor Summary
| Public Constructor | ||
| public |
Constructor |
Member Summary
| Public Members | ||
| public |
Actions to listen |
|
| public get |
Gets current count |
|
| public get |
Gets total count of items |
|
| public get |
Gets items |
|
| public get |
Gets loaded items count |
Method Summary
| Public Methods | ||
| public |
countUp() Count up by 1 |
|
| public |
Count up by a number given |
|
| public |
Load scroll items |
Public Constructors
Public Members
public actions(actions: Object): * source
Actions to listen
Listen:
COUNT_UP |
COUNT_UP_BY |
LOAD_SCROLL_ITEMS |


---
layout: documentation
title: ReactiveX - RefCount operator
id: refcount
---
{% lang_operator RxClojure %}
TBD
{% endlang_operator %}
{% lang_operator RxCpp publish %}
TBD
{% endlang_operator %}
{% lang_operator RxGroovy refCount share %}
RxGroovy implements this operator as refCount
.
There is also a share
operator, which is the equivalent of applying both the
publish
and refCount
operators to an Observable, in that order.
{% endlang_operator %}
{% lang_operator RxJava 1․x refCount share %}
RxJava implements this operator as refCount
.
There is also a share
operator, which is the equivalent of applying both the
publish
and refCount
operators to an Observable, in that order.
{% endlang_operator %}
{% lang_operator RxJava 2․x share %}
TBD
{% endlang_operator %}
{% lang_operator RxJS refCount share shareValue %}
RxJava implements this operator as refCount
.
Sample Code
var interval = Rx.Observable.interval(1000);
var source = interval
.take(2)
.doAction(function (x) { console.log('Side effect'); });
var published = source.publish().refCount();
published.subscribe(createObserver('SourceA'));
published.subscribe(createObserver('SourceB'));
function createObserver(tag) {
return Rx.Observer.create(
function (x) { console.log('Next: ' + tag + x); },
function (err) { console.log('Error: ' + err); },
function () { console.log('Completed'); });
}
Side effect
Next: SourceA0
Next: SourceB0
Side effect
Next: SourceA1
Next: SourceB1
Completed
Completed
refCount
is found in the following distributions:
rx.all.js
rx.all.compat.js
rx.binding.js
(requires rx.js
, rx.compat.js
, rx.lite.js
, or rx.lite.compat.js
)
rx.lite.js
rx.lite.compat.js
There is also a share
operator, which is the equivalent of applying both the
publish
and refCount
operators to an Observable, in that order.
A variant called shareValue
takes as a parameter a single item that it will
emit to any subscribers before beginning to emit items from the source Observable.
Sample Code
var interval = Rx.Observable.interval(1000);
var source = interval
.take(2)
.do(
function (x) { console.log('Side effect'); });
var published = source.share();
// When the number of observers subscribed to published observable goes from
// 0 to 1, we connect to the underlying observable sequence.
published.subscribe(createObserver('SourceA'));
// When the second subscriber is added, no additional subscriptions are added to the
// underlying observable sequence. As a result the operations that result in side
// effects are not repeated per subscriber.
published.subscribe(createObserver('SourceB'));
function createObserver(tag) {
return Rx.Observer.create(
function (x) { console.log('Next: ' + tag + x); },
function (err) { console.log('Error: ' + err); },
function () { console.log('Completed'); });
}
Side effect
Next: SourceA0
Next: SourceB0
Side effect
Next: SourceA1
Next: SourceB1
Completed
share
and shareValue
are found in the following distributions:
rx.all.js
rx.all.compat.js
rx.binding.js
(requires rx.js
or rx.compat.js
)
rx.lite.js
rx.lite.compat.js
{% endlang_operator %}
{% lang_operator RxKotlin refCount share %}
TBD
{% endlang_operator %}
{% lang_operator Rx.NET RefCount %}
TBD
{% endlang_operator %}
{% lang_operator RxPHP share shareValue %}
RxPHP implements this operator as share
.
Returns an observable sequence that shares a single subscription to the underlying sequence. This operator is a specialization of publish which creates a subscription when the number of observers goes from zero to one, then shares that subscription with all subsequent observers until the number of observers returns to zero, at which point the subscription is disposed.
Sample Code
//from https://github.com/ReactiveX/RxPHP/blob/master/demo/share/share.php
$loop = \React\EventLoop\Factory::create();
$scheduler = new \Rx\Scheduler\EventLoopScheduler($loop);
//With Share
$source = \Rx\Observable::interval(1000, $scheduler)
->take(2)
->doOnNext(function ($x) {
echo "Side effect\n";
});
$published = $source->share();
$published->subscribe($createStdoutObserver('SourceA '));
$published->subscribe($createStdoutObserver('SourceB '));
$loop->run();
Side effect
SourceA Next value: 0
SourceB Next value: 0
Side effect
SourceA Next value: 1
SourceB Next value: 1
SourceA Complete!
SourceB Complete!
RxPHP also has an operator shareValue
.
Returns an observable sequence that shares a single subscription to the underlying sequence and starts with an initialValue. This operator is a specialization of publishValue which creates a subscription when the number of observers goes from zero to one, then shares that subscription with all subsequent observers until the number of observers returns to zero, at which point the subscription is disposed.

SourceB Complete!
{% endlang_operator %}
{% lang_operator RxPY ref_count %}
TBD
{% endlang_operator %}
{% lang_operator Rx.rb %}
TBD
{% endlang_operator %}
{% lang_operator RxScala refCount share %}
TBD
{% endlang_operator %}
{% lang_operator RxSwift refCount %}
TBD
{% endlang_operator %}


Tensor Flow is a machine learning toolkit which recently got published by Google. They published it under Apache License 2.0. Looking at the source code overview, it seems to be mainly C++ with a significant bit of Python.
I guess the abstract of the Whitepaper is a good description what TensorFlow is:
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed with little or no change on a wide variety of heterogeneous systems, ranging from mobile devices such as phones and tablets up to large-scale distributed systems of hundreds of machines and thousands of computational devices such as GPU cards. The system is flexible and can be used to express a wide variety of algorithms, including training and inference algorithms for deep neural network models, and it has been used for conducting research and for deploying machine learning systems into production across more than a dozen areas of computer science and other fields, including speech recognition, computer vision, robotics, information retrieval, natural language processing, geographic information extraction, and computational drug discovery. This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google. The TensorFlow API and a reference implementation were released as an open-source package under the Apache 2.0 license in November, 2015 and are available at www.tensorflow.org.
The core seems to be written in C++, but it has a Python front end.
By now, I couldn't test much because I just made my GPU machine unusable (while trying to get the GPU General Computing practical software to run...). I'll try to expand this article as soon as possible, but I guess it might take several weeks until I have enough time. Lets see...
Installation
The documentation about the installation makes a VERY good impression. Better than anything I can write in a few minutes, so ... RTFM 😜
For Linux systems with CUDA and without root privileges, you can install it with:
$ pip install https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl --user
But remember you have to set the environment variable LD_LIBRARY_PATH
and
CUDA_HOME
. For many configurations, adding the following lines to your
.bashrc
will work:
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
export CUDA_HOME=/usr/local/cuda
MNIST
The following code can be used to check if your Tensor Flow installation is
working. You have to have the get_mnist_data_tf.py
in the same directory as the following script. I've - more or less - directly
copied it from the tutorial.
Just execute the script below and see if it finishes without throwing errors.
#!/usr/bin/env python
from get_mnist_data_tf import read_data_sets
mnist = read_data_sets("MNIST_data/", one_hot=True)
import tensorflow as tf
sess = tf.InteractiveSession()
x = tf.placeholder("float", shape=[None, 784])
y_ = tf.placeholder("float", shape=[None, 10])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
sess.run(tf.initialize_all_variables())
y = tf.nn.softmax(tf.matmul(x, W) + b)
cross_entropy = -tf.reduce_sum(y_ * tf.log(y))
train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
for i in range(1000):
batch = mnist.train.next_batch(50)
train_step.run(feed_dict={x: batch[0], y_: batch[1]})
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
print(accuracy.eval(feed_dict={x: mnist.test.images, y_: mnist.test.labels}))
def weight_variable(shape):
initial = tf.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial)
def bias_variable(shape):
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial)
def conv2d(x, W):
return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding="SAME")
def max_pool_2x2(x):
return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding="SAME")
W_conv1 = weight_variable([5, 5, 1, 32])
b_conv1 = bias_variable([32])
x_image = tf.reshape(x, [-1, 28, 28, 1])
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
h_pool1 = max_pool_2x2(h_conv1)
W_conv2 = weight_variable([5, 5, 32, 64])
b_conv2 = bias_variable([64])
h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
h_pool2 = max_pool_2x2(h_conv2)
W_fc1 = weight_variable([7 * 7 * 64, 1024])
b_fc1 = bias_variable([1024])
h_pool2_flat = tf.reshape(h_pool2, [-1, 7 * 7 * 64])
h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)
keep_prob = tf.placeholder("float")
h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)
W_fc2 = weight_variable([1024, 10])
b_fc2 = bias_variable([10])
y_conv = tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2)
cross_entropy = -tf.reduce_sum(y_ * tf.log(y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
sess.run(tf.initialize_all_variables())
for i in range(1000):
batch = mnist.train.next_batch(50)
if i % 100 == 0:
train_accuracy = accuracy.eval(
feed_dict={x: batch[0], y_: batch[1], keep_prob: 1.0}
)
print("step %d, training accuracy %g" % (i, train_accuracy))
train_step.run(feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5})
print(
"test accuracy %g"
% accuracy.eval(
feed_dict={x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}
)
)
Observations
While looking at the MNIST example, I made a couple of observations. Let's begin with the nice parts:
- Tensor Flow has a usable documentation (e.g. The neural network part). Not great, as Lasagne where you have lots of details (e.g. activation functions)
- Seems to be quite easy to use.
- Seems to be well-tested by simply being used in many different projects by Google.
- Just like Theano (and thus Lasagne), Tensor flow has automatic differenciation.
Not sure:
- How easy is it to share trained models? In which format would you do so?
- How easy is it to understand a shared model?
- How easy is it to get something new to Tensor Flow like recurrent layers? (Actually, this seems rather to show that either the Whitepaper is a bit misleading or the documentation / Google search is not that good. In the whitepaper they write something about LTSM models, but I couldn't find any docs about that. Only by manually going through the manual, I found it)
Not so nice:
- Doesn't work with Python 3.
- They don't follow PEP8. I know that there is a Python style guide by Google, but it does not seem to follow that one either. See the next section for some more detailed feedback.
- Just like the other Toolkits, you need CUDA. It doesn't work with OpenCL.
PEP8
- Whitespace
W = tf.Variable(tf.zeros([784, 10]))
should beW = tf.Variable(tf.zeros([784, 10]))
. Missing whitespaces happened quite often.- Indent with 2 spaces instead of 4 spaces. The Google guide seems also to use 4.
- Newlines between functions are missing.
- Print statement instead of a print function was used &rightarrow only Python 2, not Python 3.
- I'm not sure why
y_
has the trailing underscore. According to PEP8, a single trailing underscore is used by convention to avoid conflicts with Python keyword. - A mixture of different styles as pointed out on Credric's Blog
Videos
Starting at 21m 2s:
Alternatives / Similar software
As I don't really know by now what Tensor Flow is doing, I can't pin-point alternatives. But I have some educated guesses:
- Theano has been around for quite a while and seems to have a similar approach with its computational graph. Enhanced by Lasagne, it is a pretty good alternative when it comes to neural networks. Lasagne has an exceptionally good documentation, but parts of the tutorial could still be improved.
- Caffe was something I recently tried. I didn't like it too much due to the lack of documentation, but it certainly is a big project. Especially when it comes to images.
- I haven't tried, but they look promising:
- Chainer
- MXNet
- CGT
- Torch has a very nice example for a character predictor.
See also
- Official Website
- github.com/tensorflow
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
- news.ycombinator.com
- reddit.com/r/programming


--- layout: page title: Projects subtitle: Published projects I have worked on permalink: /projects/ ---


{% load accounting %}
| Date | Amount | Debit Account | Credit Account |
|---|---|---|---|
| {{ transaction.date }} | {% transaction_amount transaction %} | {{ transaction.debit }} | {{ transaction.credit }} |
| No Transactions Added | |||
| {% accounting sheet.transactions.expenses.total.amount__sum %} | Total expense transactions (not transfers) |


The algorithm/drop.h
header defines an algorithm that yields the remainder of a generic data structure after removing a user-specified number of elements.
#include <chaos/preprocessor/algorithm/drop.h>
The CHAOS_PP_DROP
macro removes the number of elements specified by its first argument from the head of its second argument.
CHAOS_PP_DROP
(n, g)
The number of elements to be removed.
Valid values range from 0
to
.
CHAOS_PP_SIZE
(g)
The generic data structure from which elements are to be removed.
This macro expands to a generic data structure of the same type as g containing all but the first n elements of g.
The efficiency of the algorithm's use of the recursion backend can be described in terms of the number of recursion steps required to complete the algorithm. The asymptotic upper and lower bounds are Θ(n+1), where n is n.
This macro uses bypass semantics.
If bypass semantics are already in effect, CHAOS_PP_DROP_BYPASS
must be used instead.
CHAOS_PP_RANGE
CHAOS_PP_SEQ_DROP
CHAOS_PP_SEQ_RANGE
CHAOS_PP_SEQ_TAKE
CHAOS_PP_TAKE
CHAOS_PP_TUPLE_DROP
CHAOS_PP_TUPLE_RANGE
CHAOS_PP_TUPLE_TAKE
#include<chaos/preprocessor/algorithm/drop.h>
#include<chaos/preprocessor/list/core.h>
CHAOS_PP_DROP
( 3, (CHAOS_PP_LIST
) (a, (b, (c, (d, (e, ...))))) ) // (CHAOS_PP_LIST
) (d, (e, ...))
The CHAOS_PP_DROP_ID
macro indirectly expands to CHAOS_PP_DROP
.
CHAOS_PP_DROP_ID
()
This macro effectively allows CHAOS_PP_DROP
to pass through itself without becoming disabled.
The CHAOS_PP_DROP_
macro expands to a λ expression representing CHAOS_PP_DROP
.
CHAOS_PP_DROP_
This macro is a shorthand form of the following λ binding:
The CHAOS_PP_DROP_BYPASS
macro behaves identically to CHAOS_PP_DROP
except that it is parametized by the bypass recursion state.
CHAOS_PP_DROP_BYPASS
(s, n, g)
The current bypass recursion state.
The number of elements to be removed.
Valid values range from 0
to
.
CHAOS_PP_SIZE
(g)
The generic data structure from which elements are to be removed.
If bypass semantics are already in effect, this macro must be used instead of CHAOS_PP_DROP
.
The CHAOS_PP_DROP_BYPASS_ID
macro indirectly expands to CHAOS_PP_DROP_BYPASS
.
CHAOS_PP_DROP_BYPASS_ID
()
This macro effectively allows CHAOS_PP_DROP_BYPASS
to pass through itself without becoming disabled.
The CHAOS_PP_DROP_BYPASS_
macro expands to a λ expression representing CHAOS_PP_DROP_BYPASS
.
CHAOS_PP_DROP_BYPASS_
This macro is a shorthand form of the following λ binding:


{% extends 'logged_base.html' %} {% block detail %}
Create your first Linkcase and start collecting your favorite urls in it!


EcommCo’s Data Lake leverages AWS QuickSight for visualizations of published data. QuickSight presents compelling data stories that are consumable by business users.
The diagram below illustrates QuickSight dashboards, which tell compelling data stories to ECommCo’s business users
When you click this button, the following steps will be performed within your AWS account:
Product category dataset consists of records with columns: product_category, orders_count Use the following procedure to create visualization from it:
Spend distribution dataset consists of records with columns: customer_id, spend, marital_status, education_level Use the following procedure to create visualization from it:
Customer lifetime value dataset consists of records with columns: segment, segment_spend Use the following procedure to create visualization from it:
SKU distribution dataset consists of records with columns: product_category, sku, sku_count Use the following procedure to create visualization from it:
State population dataset consists of records with columns: state, population Use the following procedure to create visualization from it:
Orders by month dataset consists of records with columns: month_date, married_orders, single_orders, total_orders Use the following procedure to create visualization from it:


WITNESS LIST Criminal Justice Committee January 27, 1997-1:30P SB 250 For: Anderson, Ken (self), Georgetown Bible, Lori (PAVC), Austin Clements, Dianne (Justice for All), Houston Cohen, Gary J. (TX Crim. Def. Lawyers), Austin Cotellesse, Suzan (Justice for All, self), Houston Eads, Arthur C. (self), Belton Hamric, Peggy Rep. (Texas House of Rep.), Austin Healey, John (Fam. & Friends of G.E.), Richmond Kelley, Linda (self and children), Houston Palmer, Stephanie (Justice for All), Pearland Parish, Shirley (self), Houston Semander, Harriett (self), Houston Semander, Zahari (self), Houston Tovar, Alida (Justice for All), Katy Wing, Marty (self), Hurst Against: Marin, Linda (TX CURE), Austin On: Fabelo, Tony Dr. (Crim. Just. Policy Coun), Austin Guszak, Garron (Legislative Budget Brd.), Austin Rodriguez, Victor (TX Brd. Pardons&Paroles), Austin Registering, but not testifying: For: Bridgeman, John (self), Humble Carr, Verna Lee (PAVC), Austin Carreiro, Robert G. (Justice for All), Houston Clements, Whitson (Justice for All), Houston Donahue, Sterlene (Justice for All), Houston Dukes, Mark (self), Humble Fuller, Sam (Cut-n-Shoot Hog), Conroe Mason, Mike (self), Houston O'Connell, Tom (Collin Co. Dist. Atty.), McKinney


Pop’s biggest new star is a 17-year-old who rose to fame on her own terms and doesn’t
care what you think — even if she still calls out for her mom after a bad dream Billie Eilish
and the Triumph of the Weird.
Party in the U.K.
Glastonbury is one of the world’s largest music festivals, drawing 200,000 people to a farm in Wales.
Drake
In the past 18 months or so, shorter albums have become a hot trend. Apparently, no one
told Chris Brown, as his ninth LP checks in at 32 songs.
The Eternal Sunshine of Harry Styles
The Eternal Sunshine of Harry Styles
Riding shotgun with the former boy-band hero as he opens up
about sex, psychedelics, and becoming a 21stcentury rock star
BY ROB SHEFFIELD
Greta Thunberg
How a teenage girl’s lone strike against climate change became an international movement


home
teams
format
schedule
fields
party
links
discussions
Questions?
Email us
.
March 30-31, 2013
San Diego, CA


Honzi
/
Personal Bests
/Age of Empires
Statistic (2)
PB
Achievements
5/265 (1.8867925%)
Barbarossa
Joan of Ark
Learn to Play
7/7
Saladin
Genghis Khan


This project was designed to work as a fully functional calender, with a day, week, and month view. It also generates random events from the user-specified category to offer ideas for what to do when you have no clue what could make your boredom go away!
This app was created for a real customer who owns a small local pizza restaraunt. He had issues with his static site and wanted a more heavy-weight application that could be edited and updated from within the site via an owners dashboard. It also contains a user dashboard for restaraunt customers to view menu items and prepare an order.
This project featured local storage, and was designed to display an 9 hr day and have events saveable to the users local system. Then, the user could return to their schedule later to check off or intiate new future plans.


The secret RSA key (N,d) consists of RSA modulus N – the product of two prime numbers p and q – and the secret exponent d. The secret RSA key must not be divulged and must be stored so that it is protected against third party access (for example PIN-protected on a smart card).
Public RSA key and secret RSA key are mathematically related so that with one key it is possible to cancel the function of the other one again.


{lang} Edition Sign up
If you want to stay up to date with the most active articles and discussions, please sign up for future issues.
{?issues}{lang} Archives
{/issues}About
This project retrieves a list of the week's recent changes using Wikimedia Tool Labs, and delivers emails using MailChimp. Code and more information available on GitHub. Built by Stephen LaPorte and Mahmoud Hashemi.


Hi, I got some new SCT-013-000 but when I try the basic Current Sensor circuit and sketch I'm getting almost double measurements.
Thus I had to change the calibration constant to 63.0 instead of 111.1 to get good readings.
Is this correct?
How can I tell if my SCT is doing what it is supposed to do?
I measure the resistance in the SCT-013-000 and I got 100 ohms, is this correct?
Re: SCT-013-000 giving "almost double" measurements
What hardware are you using? Link? What is your ADC reference voltage, what value is your burden resistor? Which sketch are you using?
100 Ω is about right for the resistance of the c.t secondary winding. My first guess would be your burden resistor is missing or the wrong value, but without more details I cannot be certain.
If you connect your multimeter directly to the c.t. (tip & sleeve) on the mA a.c. range, you should read 50 mA per 100 A of primary current. I will be very surprised if that is wrong.
Re: SCT-013-000 giving "almost double" measurements
Do you have a similar CT which gives different readings? If so, you could open each of their cases and check for differences.
The CT is just a coil of wire around a metal core so it's difficult to see why one should give different results than another. I wonder whether the version that you're using has 1000 turns or 2000 turns. I've seen both versions on eBay recently.
Re: SCT-013-000 giving "almost double" measurements
Thanks guys... here is a bit more of details:
I tried that with 3 CTs SCT-013-000 and all have the same issues. Mine are the YHDC ones.
My setup is very simple:
- Arduino UNO
- Burdeen Resistor: 33R
- R1 & R2: 470K
- C1: 10uF
I'm powering the circuit from Arduino's GND and 5V (which is actually measuring 4.89-4.90V).
I'm in Brazil and mains is 127V (actually measuring around 130.4V) at 60Hz.
I build a test rig with a 100W incandescent light bulb that I'm using as load.
Measuring this load and using the 111.1 calibration constant (as suggested in the example) I have:
- Irms: 1.46A
- Apower: ~189-190A
Using an oscilloscope to see what is going on and measuring the signal between GND and the CT output I have:
- Vrms = 2.41V
- Vpp = 180mV
My Sketch is the simplest:
#include <EmonLib.h>
EnergyMonitor emon1;
void setup()
{
Serial.begin(9600);
emon1.current(1, 111.1);
}
void loop()
{
double Irms = emon1.calcIrms(1480);
Serial.print(Irms*130.4);
Serial.print(" ");
Serial.println(Irms);
}
Re: SCT-013-000 giving "almost double" measurements
I cannot see a YHDC SCT-013-100 on the YHDC website. The nearest numbers I can see are the SCT-013-010, the SCT-013-000 and the SCT-013-000V. The first and last have internal burden resistors and do not need an external burden. The first is 1 V out at 10 A, the last is 1 V out at 100 A. The second is the one we recommend, and gives 50 mA out at 100 A. None of these would give you 180 mV pp (64 mV rms) with a 33 Ω external burden that might be in parallel with the internal one. So I don't know which you have.
Let us do the maths:
Load = 100 W
Voltage = 130 V
Load Current (c.t. primary current) = 100 W / 130 V = 770 mA
ct secondary current = 777 mA ÷ 100 A × 50 mA = 0.385 mA
burden voltage = 33 Ω × 0.385 mA = 12.7 mV (rms), or 36 mV pp
That should allow you to check whether the c.t. is giving the correct output, it is also worth checking the value of your burden resistor - is it really 33 Ω? To get 180 mV p-p you would need a 165 Ω burden, or a 100 A : 250 mA c.t.; or some combination of those numbers.
The Arduino voltage disappears from the calculation because it is measured by the emonLib library, and the calibration constant is worked out for you in Building Blocks - Calibration theory, the number you should be using is 60.6. But that does not explain why you see 180 mV where you should have 36 mV.
Re: SCT-013-000 giving "almost double" measurements
Hi Robert,
Thanks for you email.
Actually, my sensor is the YHDC SCT-013-000.
That make things even weirder, since it says on it that it is 100A-50mA. But it is just not actiing like that.
Yes, the resistors are 100% correct, I also measured them to double-check.
Do you believe that these sensors are working with different parameters?
Using 5 loops of the load (to get out of too low readings) I get this:
On the Digital Oscilloscope
- Vrms = 2.42V
- Vpp = 280-300mV
On the Arduino, with the calibration constant in 64:
- Irms = 4.08-4.11A
Does that helps to clarify things?
If you can, I also have another question: how does the Arduino 5V actual value affects the measurements? And what happens if the voltage divider is not perfectly symmetrical? Are those "discrepancies" handled by the emonLib?
I believe this is part of what you mentioned on the last paragraph, but I'm double checking if I understood it correctly.
Thanks in advance!
Re: SCT-013-000 giving "almost double" measurements
The rms voltage measured by your oscilloscope might not be useful unless it can remove the d.c. component. I think it is correctly calculating the voltage with the 2.5 V offset included, and that is not the number we want. That might be confusing you.
When you have a 5 turn primary winding, the c.t. becomes a 20 A : 50 mA one. You still have 770 mA primary current, so now you should have 1.925 mA secondary current, 63.5 mV rms (180 mV pp). And yet you now have 300 mV pp (100 mV rms) across the burden.
With 1 turn, you should have had 36 mV and you got 180 mV.
With 5 turns, you should have had 180 mV and you got 300 mV.
Those numbers are not consistent.
Is it possible to measure the c.t. secondary current directly with a multimeter? That is the certain way to check the ratio. What does your oscilloscope say if you have only the burden resistor and the c.t? (No 2.5 V, no bias resistors, no Arduino.)
To answer the other points, the actual 5 V value does not affect the calibration through emonLib (for the emonTx V2 functions anyway) but the accuracy of the internal 1.1 V reference does. I wrote about that in Calibration. The divider is not in the signal path so it does not affect the calibration, but it does limit the maximum swing of the input voltage - as does a low supply voltage.
Re: SCT-013-000 giving "almost double" measurements
My Sketch is the simplest:
#include <EmonLib.h>
EnergyMonitor emon1;
void setup()
{
Serial.begin(9600);
emon1.current(1, 111.1);
}
void loop()
{
double Irms = emon1.calcIrms(1480);
Serial.print(Irms*130.4);
Serial.print(" ");
Serial.println(Irms);
}
Although this sketch looks simple, a lot of hidden activity is happening within the library routine, calcIrms(). If you want to understand the output signal from the CT, you may be better looking at the raw output values from the ADC.
There are several sketches which do this near the top of my Summary Page, MinAndMaxValues is the simplest one, but you have to specify the analogue inputs correctly. The later version, MinMaxAndRangeChecker, displays the raw ADC values for the first four analogue inputs. RawSamplesTool and RawSamplesTool_4ss_2 rely on an AC voltage source being present. These sketches will display your voltage and current samples in graphical form.
100 Watts is a very small current to be measuring with your CT. Have you tried using a bigger load which will cause a much larger signal to appear at the CT's output? The ADC in the Uno has 1024 steps which are evenly spread over its input range. By using more of the available range, you should get a more reliable result.
Using either of the RawSample tools above, the waveform for current will appear very small when using a load of only 100W. If you can repeat the test using an electric kettle as your load, you should see a much better looking waveform.
Re: SCT-013-000 giving "almost double" measurements
Robin, the sketch is not involved at this point. Manoel is using an oscilloscope and he is measuring the wrong values before it even hits the Arduino. I asked him to measure the burden voltage with only the burden and oscilloscope connected to the current transformer, so that we can positively say that there can be only three possibilities: (1) the c.t. itself, (2) the load current measurement is wrong and (3) the oscilloscope calibration is wrong. The problem might be just one, or could be a combination of all three of these.
What I would like to see is a picture of the current waveform recorded with a real oscilloscope. And as you say, if Manoel can use a much bigger load - say 2 kW which would give a current of 15 A, that would be much more realistic.
Re: SCT-013-000 giving "almost double" measurements
Thanks Gents,
I'll try to work on those measurements.
I have a few doubts on how to evaluate the CT. Maybe I'm to far from my Engineering School times, hehe. I read the Calibration and I have lots of questions. I'll elaborate on that and send another message here (need some spare time).
One thing that intrigues me is the use of the Sound Board Oscilloscope. I understand that it is good to isolate from mains, but I'd prefer to use my DSO (Rigol DS1102E). Is this possible? How?
Any ideas on how to generate a bigger load?
I have a 500VA variac at home, that I was using to calibrate my Voltage Sensors, also I have the DSO and a few multimeters. I'm not sure my multimeters has AC Current capabilities. I have one True RMS clamp multimeter, but I just figure it is almost useless for small loads. ;-)
Also, I'll build some circuit diagrams indicating exactly how my circuit is and where I'm measuring things, to void any misunderstanding.
Anyway, thanks in advance for you priceless help.
PS:. We're having huge geek event in Brazil in the end of the month, it is called Campus Party and my presentation there will be on how to build a connected energy consumption monitor with Arduino. It is inspired and based on the awesome project you guys develop here.
Thanks Again!
Re: SCT-013-000 giving "almost double" measurements
You can read how I test c.t's in the report on the YHDC c.t. As you can see from that, I work at 6.5 V when testing and therefore it is absolutely safe to handle, except the load resistor. Even though it is on a heat sink, gets very warm. If you have a low voltage transformer that is capable of 5 - 10 A secondary current, you could use that but you must be able to insert an ammeter in series so that you can measure the current accurately. Using 5 A and 50 turns of enamelled copper wire, I can test up to 250 A.
From what you wrote, I knew you had an oscilloscope. According to the UK website, it has a USB connection so I would expect you to be able to transfer a captured waveform to your computer. You need to read the manual and experiment. The sound card oscilloscope is good for pictures but it is not calibrated, again you can see how I connected it in the test report. It would be much better to use your Rigol 'scope.
Re: SCT-013-000 giving "almost double" measurements
Robert, ss far as I could see, Manuel was using one of the standard OEM sketches and was surprised that his values were not as expected. You said yourself that "the calibration constant is worked out for you in Building Blocks - Calibration theory, the number you should be using is 60.6."
In order to investigate the signal that a CT is generating, some kind of measurement system is needed. I don't have an oscilloscope or any specialised test equipment, but I have found it very convenient to use the Aurduino's ADC for this purpose. When run at 5V, each ADC level corresponds to approx. 5mV, so the peak-to-peak amplitude of an AC signal can be easily recorded. By displaying such waveforms with my RawSamplesTool, it should be evident how much of the waveform is signal rather than background noise.
Several constructors have found these simple tools to be of use, particularly when burden resistors or divider ratios for the AC voltage source have been incorrectly fitted. But everyone is free to choose how to test their own equipment.
Re: SCT-013-000 giving "almost double" measurements
I
use a digital multimeter to measure the value of SCT 013, it give me voltage AC, not Current AC. the resistor at tip & sleeve) is 100 ohm. So is there any change in the circuit. I leave out the 33 ohm burden resistor. So I can read the value on Arduino , but the result fluctuate so much
Re: SCT-013-000 giving "almost double" measurements
You have a SCT-013. Which one? There are many variants. If you have the SCT-013-000, that gives you a current of 50 mA per 100 A of primary current. If you have one of the other variants, that will give you a voltage of 1 V ac, the current you need to get 1 V depends on which one you have.
If you have the SCT-013-000 and connect a 100 Ω resistor across it, you will measure 5 V at 100 A primary current. That is too big even for an Arduino running from a 5 V power supply, because the voltage swing from peak to peak is 14.14 V, therefore the maximum current that you can measure will be 35 A approximately.
How are you obtaining the value you read in the Arduino?
You must change the input pin in Line 20 to suit how you have wired your Arduino.
That will not give you the correct value of current, but it will give you a steady reading. You can calibrate it by changing the number "111.1" also in line 20. The way to calculate the correct number is in Building Blocks > CT and AC power adaptor installation and calibration theory.
Re: SCT-013-000 giving "almost double" measurements
After, test some circuit, do some measurement with sct 013 only. Finally, I change the calibration in the current function and I get the correct value.Its value is 62.3
Re: SCT-013-000 giving "almost double" measurements
Your calibration constant is correct for a burden resistor value of 32 Ω
Is that the value of your burden resistor?
Re: SCT-013-000 giving "almost double" measurements
yes, i use the burden resistor value of 32 Ω. Now, I want to use 160A Split core current transformer SCT-027H ,http://www.yhdc.com/en/product/356/
is there any change in the hardware and the code
SCT 160A has 40mA @160A, the same to SCT 100A.
Re: SCT-013-000 giving "almost double" measurements
There should be no need to change your burden resistor, but you can move to a slightly higher value if you wish - the objective is to have about 1.6 V at the maximum current that you want to measure. You will also need to change the calibration constant in order to output the correct values. The calibration theory page gives you the details.
I will soon delete your post in the "Simple invasive 3-phase energy monitor" thread. What you are asking/proposing there is completely off-topic (because you are using NON-invasive means). There is already a 3-phase sketch on GitHub, you should start with that and convert the I/O addresses to suit your Arduino.
Re: SCT-013-000 giving "almost double" measurements
I have just test with the same circuit wth 160A non invasive, i change the calibration constant for current. But I have problem with power factor, it has lower value about 10-50% depends on the current value. If current value high @6A, it lower 10%, @ 3A it lower than 12%.@0.2A,it lower than 50-60%
Re: SCT-013-000 giving "almost double" measurements
When I run sct 013-000 (100A) with Mega 2560, the voltage fluctuate around 5V it means that i show the value from 225-230V, but when I run the same sketch with Uno R3, it change only 0.5V. Do I need to change something when run Mega 2560?


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A summary of hacking tools to practice ethical hacking
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Overview
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A
AbstractGameState
- Class in
javalabra.chess.core.impl.state
Abstract game state.
AbstractGameState()
- Constructor for class javalabra.chess.core.impl.state.
AbstractGameState
AbstractMove
- Class in
javalabra.chess.core.impl.move
Abstract skeleton for move objects.
AbstractMove(Piece, Square, Square)
- Constructor for class javalabra.chess.core.impl.move.
AbstractMove
addCaptureMove(int, int)
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Adds only capture move specified by offsets.
addDiagonalMoves()
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Adds diagonal moves to all directions.
added()
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Returns true if last add command added any move.
addMove(int, int)
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Adds any move specified by offsets.
addNormalMove(int, int)
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Adds only normal move specified by offsets.
addStraightMoves()
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Adds straight moves to all directions.
attempt(Move)
- Method in interface javalabra.chess.core.
GameContext
Performs move and returns a new game context to represent new state.
attempt(Move)
- Method in class javalabra.chess.core.impl.
GameContextImpl
B
begin(GameListener)
- Method in interface javalabra.chess.core.
Game
Begin new game and bind it to the specified listener.
begin(GameListener)
- Method in class javalabra.chess.core.impl.
GameImpl
Bishop
- Class in
javalabra.chess.domain
Represents bishop.
Bishop(Color)
- Constructor for class javalabra.chess.domain.
Bishop
Board
- Class in
javalabra.chess.domain
Represents chessboard.
Board()
- Constructor for class javalabra.chess.domain.
Board
Creates empty board.
Board(Board)
- Constructor for class javalabra.chess.domain.
Board
Copy constructor.
BoardBuilder
- Interface in
javalabra.chess.core
Chessboard builder.
BoardBuilderImpl
- Class in
javalabra.chess.core.impl
Implementation of board builder.
BoardBuilderImpl()
- Constructor for class javalabra.chess.core.impl.
BoardBuilderImpl
BoardListener
- Interface in
javalabra.chess.ui
The listener interface for receiving board events.
BoardPanel
- Class in
javalabra.chess.ui
A component that draws board.
BoardPanel()
- Constructor for class javalabra.chess.ui.
BoardPanel
build(PlayerWhite, PlayerBlack)
- Method in interface javalabra.chess.core.
BoardBuilder
Places pieces on the board and returns it.
build(PlayerWhite, PlayerBlack)
- Method in class javalabra.chess.core.impl.
BoardBuilderImpl
C
captured
- Variable in class javalabra.chess.core.impl.move.
CaptureMove
CaptureMove
- Class in
javalabra.chess.core.impl.move
Implementation of the capture move.
CaptureMove(Piece, Square, Square, Piece)
- Constructor for class javalabra.chess.core.impl.move.
CaptureMove
Chess
- Class in
javalabra.chess.ui
Main UI class which is responsible for displaying current game state by reacting to game events.
Chess()
- Constructor for class javalabra.chess.ui.
Chess
Color
- Enum in
javalabra.chess.domain
copy()
- Method in class javalabra.chess.domain.
Board
Returns copy of the board.
D
destination
- Variable in class javalabra.chess.core.impl.move.
AbstractMove
Piece's destination position.
display()
- Method in class javalabra.chess.ui.
Chess
E
equals(Object)
- Method in class javalabra.chess.domain.
Square
G
Game
- Interface in
javalabra.chess.core
Game facade.
gameChanged(GameEvent)
- Method in interface javalabra.chess.core.
GameListener
Triggered when game state is changed.
gameChanged(GameEvent)
- Method in class javalabra.chess.ui.
BoardPanel
gameChanged(GameEvent)
- Method in class javalabra.chess.ui.
Chess
GameContext
- Interface in
javalabra.chess.core
Context object which represents concrete moment in the game.
GameContextImpl
- Class in
javalabra.chess.core.impl
Implementation of game context.
GameContextImpl(Board)
- Constructor for class javalabra.chess.core.impl.
GameContextImpl
GameContextImpl(GameContextImpl)
- Constructor for class javalabra.chess.core.impl.
GameContextImpl
GameEvent
- Interface in
javalabra.chess.core
GameEventEmitter
- Class in
javalabra.chess.core.impl
Utility class for triggering game events.
GameEventEmitter(GameContext, StateAnalyzer)
- Constructor for class javalabra.chess.core.impl.
GameEventEmitter
Constructs new game emitter for concrete context.
GameEventImpl
- Class in
javalabra.chess.core.impl
Implementation of game event.
GameEventImpl(Board, boolean, Square, Collection<Square>, boolean, boolean)
- Constructor for class javalabra.chess.core.impl.
GameEventImpl
GameImpl
- Class in
javalabra.chess.core.impl
Implementation of game facade.
GameImpl()
- Constructor for class javalabra.chess.core.impl.
GameImpl
Prepares new game to begin.
GameListener
- Interface in
javalabra.chess.core
The listener interface for receiving game events.
GameState
- Interface in
javalabra.chess.core.impl
State interface representing game's current state.
getBoard()
- Method in interface javalabra.chess.core.
GameContext
Returns board object.
getBoard()
- Method in interface javalabra.chess.core.
GameEvent
getBoard()
- Method in class javalabra.chess.core.impl.
GameContextImpl
getBoard()
- Method in class javalabra.chess.core.impl.
GameEventImpl
getBoardBuilder()
- Method in class javalabra.chess.core.impl.
GameImpl
getCandidateMoves()
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Returns all the calculated moves at the moment.
getCandidateMoves(King, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(Queen, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(Rook, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(Knight, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(Bishop, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(Pawn, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getCandidateMoves(King, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for king without analyzing them.
getCandidateMoves(Queen, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for queen without analyzing them.
getCandidateMoves(Rook, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for rook without analyzing them.
getCandidateMoves(Knight, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for knight without analyzing them.
getCandidateMoves(Bishop, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for bishop without analyzing them.
getCandidateMoves(Pawn, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates candidate moves for pawn without analyzing them.
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Bishop
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
King
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Knight
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Pawn
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Piece
Returns all candidate moves for piece.
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Queen
getCandidateMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Rook
getCaptured()
- Method in class javalabra.chess.core.impl.move.
CaptureMove
getColor()
- Method in class javalabra.chess.domain.
Piece
Returns color of the piece.
getColumn()
- Method in class javalabra.chess.domain.
Square
getCurrentPiece()
- Method in interface javalabra.chess.core.
GameEvent
getCurrentPiece()
- Method in class javalabra.chess.core.impl.
GameEventImpl
getDestination()
- Method in class javalabra.chess.core.impl.move.
AbstractMove
getDestination()
- Method in interface javalabra.chess.domain.
Move
Returns position to move to.
getFile()
- Method in class javalabra.chess.domain.
Square
Returns human-readable name for the column.
getKingPosition(Color)
- Method in class javalabra.chess.domain.
Board
Finds king's position.
getLegalMoves()
- Method in interface javalabra.chess.core.
GameEvent
getLegalMoves()
- Method in class javalabra.chess.core.impl.
GameEventImpl
getLegalMoves()
- Method in class javalabra.chess.core.impl.
MoveCollectionBuilder
Returns all the legal moves calculated at the moment.
getLegalMoves(King, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(Queen, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(Rook, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(Knight, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(Bishop, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(Pawn, GameContext)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
getLegalMoves(King, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates legals moves for king.
getLegalMoves(Queen, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates legal moves for queen.
getLegalMoves(Rook, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates legal moves for rook.
getLegalMoves(Knight, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates moves for knight.
getLegalMoves(Bishop, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates legal moves for bishop.
getLegalMoves(Pawn, GameContext)
- Method in interface javalabra.chess.core.
MoveDirector
Calculates legal moves for pawn.
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Bishop
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
King
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Knight
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Pawn
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Piece
Returns all legal moves for the piece.
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Queen
getLegalMoves(MoveDirector, GameContext)
- Method in class javalabra.chess.domain.
Rook
getPiece()
- Method in class javalabra.chess.core.impl.move.
AbstractMove
getPiece()
- Method in class javalabra.chess.domain.
Square
getPiecePosition(Piece)
- Method in class javalabra.chess.domain.
Board
Finds concrete piece's position on board.
getPieces(Color)
- Method in class javalabra.chess.domain.
Board
Returns all the pieces on the board.
getPieces()
- Method in class javalabra.chess.domain.
Player
getPreferredSize()
- Method in class javalabra.chess.ui.
BoardPanel
getRank()
- Method in class javalabra.chess.domain.
Square
Returns human-readable name for the row.
getRow()
- Method in class javalabra.chess.domain.
Square
getSource()
- Method in class javalabra.chess.core.impl.move.
AbstractMove
getSource()
- Method in interface javalabra.chess.domain.
Move
Returns position to move from.
getSquare(int, int)
- Method in class javalabra.chess.domain.
Board
Returns square by coordinates.
H
handle(int, int, MoveDirector, GameContext, GameEventEmitter)
- Method in interface javalabra.chess.core.impl.
GameState
Handles square selection.
handle(int, int, MoveDirector, GameContext, GameEventEmitter)
- Method in class javalabra.chess.core.impl.state.
AbstractGameState
handle(Square, MoveDirector, GameContext, GameEventEmitter)
- Method in class javalabra.chess.core.impl.state.
AbstractGameState
Handles square selection and returns next state.
handle(Square, MoveDirector, GameContext, GameEventEmitter)
- Method in class javalabra.chess.core.impl.state.
SelectMoveState
handle(Square, MoveDirector, GameContext, GameEventEmitter)
- Method in class javalabra.chess.core.impl.state.
SelectPieceState
hashCode()
- Method in class javalabra.chess.domain.
Square
I
isCheck()
- Method in interface javalabra.chess.core.
GameEvent
isCheck()
- Method in class javalabra.chess.core.impl.
GameEventImpl
isCheck(GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isCheck(Color, GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isCheck(GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Checks if the any king is in check.
isCheck(Color, GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Checks if the king of specified color is in check.
isCheckmate()
- Method in interface javalabra.chess.core.
GameEvent
isCheckmate()
- Method in class javalabra.chess.core.impl.
GameEventImpl
isCheckmate(GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isCheckmate(Color, GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isCheckmate(GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Checks if the any king is checkmated.
isCheckmate(Color, GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Checks if the king of specified color is checkmated.
isOccupied()
- Method in class javalabra.chess.domain.
Square
isStalemate(GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isStalemate(Color, GameContext)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
isStalemate(GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Check if any king is in stalemate.
isStalemate(Color, GameContext)
- Method in interface javalabra.chess.core.
StateAnalyzer
Check is king of specified color is in stalemate.
isWhite()
- Method in class javalabra.chess.domain.
Piece
Returns true if color of the piece is white.
isWhite()
- Method in class javalabra.chess.domain.
Square
isWhiteTurn()
- Method in interface javalabra.chess.core.
GameEvent
isWhiteTurn()
- Method in class javalabra.chess.core.impl.
GameEventImpl
J
javalabra.chess
- package javalabra.chess
javalabra.chess.core
- package javalabra.chess.core
javalabra.chess.core.impl
- package javalabra.chess.core.impl
javalabra.chess.core.impl.move
- package javalabra.chess.core.impl.move
javalabra.chess.core.impl.state
- package javalabra.chess.core.impl.state
javalabra.chess.domain
- package javalabra.chess.domain
javalabra.chess.ui
- package javalabra.chess.ui
K
King
- Class in
javalabra.chess.domain
Represents king.
King(Color)
- Constructor for class javalabra.chess.domain.
King
Knight
- Class in
javalabra.chess.domain
Represents knight.
Knight(Color)
- Constructor for class javalabra.chess.domain.
Knight
M
Main
- Class in
javalabra.chess
Main()
- Constructor for class javalabra.chess.
Main
main(String[])
- Static method in class javalabra.chess.
Main
Move
- Interface in
javalabra.chess.domain
Represents single player's move, usually known as ply.
MoveCollectionBuilder
- Class in
javalabra.chess.core.impl
Helper class to build moves' collections.
MoveCollectionBuilder(Piece, GameContext, StateAnalyzer)
- Constructor for class javalabra.chess.core.impl.
MoveCollectionBuilder
Constructs builder object for specified piece in given context.
MoveDirector
- Interface in
javalabra.chess.core
Move calculator for pieces.
MoveDirectorImpl
- Class in
javalabra.chess.core.impl
Standard implementation of move director.
MoveDirectorImpl()
- Constructor for class javalabra.chess.core.impl.
MoveDirectorImpl
N
NormalMove
- Class in
javalabra.chess.core.impl.move
Implementation of the normal move.
NormalMove(Piece, Square, Square)
- Constructor for class javalabra.chess.core.impl.move.
NormalMove
O
onSquareSelected(int, int)
- Method in class javalabra.chess.core.impl.
GameImpl
onSquareSelected(int, int)
- Method in interface javalabra.chess.ui.
BoardListener
Triggered when square on the board is selected.
opposite()
- Method in enum javalabra.chess.domain.
Color
Returns opposite color to current one.
P
paint(King)
- Method in interface javalabra.chess.core.
PiecePainter
Paint king.
paint(Queen)
- Method in interface javalabra.chess.core.
PiecePainter
Paint queen.
paint(Rook)
- Method in interface javalabra.chess.core.
PiecePainter
Paint rook.
paint(Knight)
- Method in interface javalabra.chess.core.
PiecePainter
Paint knight.
paint(Bishop)
- Method in interface javalabra.chess.core.
PiecePainter
Paint bishop.
paint(Pawn)
- Method in interface javalabra.chess.core.
PiecePainter
Paint pawn.
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Bishop
paint(PiecePainter)
- Method in class javalabra.chess.domain.
King
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Knight
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Pawn
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Piece
Delegates piece painting to specified painter object.
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Queen
paint(PiecePainter)
- Method in class javalabra.chess.domain.
Rook
paintComponent(Graphics)
- Method in class javalabra.chess.ui.
BoardPanel
Pawn
- Class in
javalabra.chess.domain
Represents pawn.
Pawn(Color)
- Constructor for class javalabra.chess.domain.
Pawn
perform(Board)
- Method in class javalabra.chess.core.impl.move.
AbstractMove
perform(Board)
- Method in class javalabra.chess.core.impl.move.
CaptureMove
Performs capture move on concrete board.
perform(Board)
- Method in class javalabra.chess.core.impl.move.
NormalMove
Performs normal move on concrete board.
perform(Board)
- Method in interface javalabra.chess.domain.
Move
Performs move on specified board.
piece
- Variable in class javalabra.chess.core.impl.move.
AbstractMove
Main piece of the move.
Piece
- Class in
javalabra.chess.domain
Represents abstract piece.
Piece(Color)
- Constructor for class javalabra.chess.domain.
Piece
PiecePainter
- Interface in
javalabra.chess.core
Interface for delegating piece painting.
Player
- Class in
javalabra.chess.domain
Represents abstract player.
Player()
- Constructor for class javalabra.chess.domain.
Player
PlayerBlack
- Class in
javalabra.chess.domain
Black player.
PlayerBlack()
- Constructor for class javalabra.chess.domain.
PlayerBlack
PlayerWhite
- Class in
javalabra.chess.domain
White player.
PlayerWhite()
- Constructor for class javalabra.chess.domain.
PlayerWhite
Q
Queen
- Class in
javalabra.chess.domain
Represents queen.
Queen(Color)
- Constructor for class javalabra.chess.domain.
Queen
R
Rook
- Class in
javalabra.chess.domain
Represents rook.
Rook(Color)
- Constructor for class javalabra.chess.domain.
Rook
S
SelectMoveState
- Class in
javalabra.chess.core.impl.state
State object representing state when piece on the board is selected and game is waiting for a move to be choosen.
SelectMoveState(Piece, Collection<Move>)
- Constructor for class javalabra.chess.core.impl.state.
SelectMoveState
SelectPieceState
- Class in
javalabra.chess.core.impl.state
State object representing state when game is waiting for piece of concrete color to be selected.
SelectPieceState(Color)
- Constructor for class javalabra.chess.core.impl.state.
SelectPieceState
setBoardListener(BoardListener)
- Method in interface javalabra.chess.core.
GameListener
Sets board listener.
setBoardListener(BoardListener)
- Method in class javalabra.chess.ui.
BoardPanel
setBoardListener(BoardListener)
- Method in class javalabra.chess.ui.
Chess
setGameListener(GameListener)
- Method in class javalabra.chess.core.impl.
GameEventEmitter
setMoveDirector(MoveDirector)
- Method in class javalabra.chess.core.impl.
StateAnalyzerImpl
setMoveDirector(MoveDirector)
- Method in interface javalabra.chess.core.
StateAnalyzer
Sets move director responsible for moves calculation.
setPiece(Piece)
- Method in class javalabra.chess.domain.
Square
setPiecePosition(Piece, Square)
- Method in class javalabra.chess.domain.
Board
Deprecated.
setSquare(int, int, Piece)
- Method in class javalabra.chess.domain.
Board
Sets piece on square specified by coordinates, null marks square as empty.
setSquare(Square, Piece)
- Method in class javalabra.chess.domain.
Board
Sets piece on specified square, null marks square as empty.
setStateAnalyzer(StateAnalyzer)
- Method in class javalabra.chess.core.impl.
MoveDirectorImpl
setStateAnalyzer(StateAnalyzer)
- Method in interface javalabra.chess.core.
MoveDirector
Sets state analyzer responsible for state checking.
source
- Variable in class javalabra.chess.core.impl.move.
AbstractMove
Piece's source position.
Square
- Class in
javalabra.chess.domain
Represents one square on the board.
Square(int, int)
- Constructor for class javalabra.chess.domain.
Square
Constructs square for specified column and row.
Square(Square)
- Constructor for class javalabra.chess.domain.
Square
Constructs copy of square.
StateAnalyzer
- Interface in
javalabra.chess.core
Game state analyzer.
StateAnalyzerImpl
- Class in
javalabra.chess.core.impl
Standard implementation of the state analyzer.
StateAnalyzerImpl()
- Constructor for class javalabra.chess.core.impl.
StateAnalyzerImpl
T
toString()
- Method in class javalabra.chess.core.impl.move.
AbstractMove
toString()
- Method in class javalabra.chess.domain.
Square
trigger(Color, Square, Collection<Move>)
- Method in class javalabra.chess.core.impl.
GameEventEmitter
Triggers game event.
trigger(Color)
- Method in class javalabra.chess.core.impl.
GameEventEmitter
Triggers game event with no current piece neither legal moves.
V
valueOf(String)
- Static method in enum javalabra.chess.domain.
Color
Returns the enum constant of this type with the specified name.
values()
- Static method in enum javalabra.chess.domain.
Color
Returns an array containing the constants of this enum type, in the order they are declared.
A
B
C
D
E
G
H
I
J
K
M
N
O
P
Q
R
S
T
V
Overview
Package
Class
Use
Tree
Deprecated
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Copyright © 2013. All Rights Reserved.


Demo Page
Orientation Image
- Install the iOS app
- Choose "Play As Guest"
- Aim device's camera at the orientation image (don't let your finger cover camera at all)
- Tap corresponding buttons to shoot claw at top and bottom rows
- Collect all rupees and bags. Avoid bombs!
- Item points: Green = 2; Blue = 10, Red = 20; Bag = 50; Bomb = -20
- Username is generated for you
- High scores will be displayed in table on full website version
This is a screenshot of what the full website looks like
A demo video of the app running in the Immersion Theater
Pictures of the full website running at Hunt Library


{% extends "layout.html" %} {% block title %}{{title}}{% endblock %} {% block content %}
imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings. Its main feature is the concept of "re-search": results from a search can immediately form the basis of another search. This allows the intuitive exploration of an image corpus, while results are continuously refined.
imgs.ai utilizes modern approximate k-NN algorithms via Spotify's Annoy library to deliver fast search results even for very large datasets in low-resource environments. It is currently in beta and will be made available under an open source license. Sign up for a beta test account here (requires approval).
imgs.ai is developed by Fabian Offert, with contributions by Peter Bell and Oleg Harlamov. Get in touch at hi@imgs.ai


BFO_0000020 - specifically dependent continuant
Label
specifically dependent continuant
Sub class of
Definition
B is a specifically dependent continuant = Def. b is a continuant & there is some independent continuant c which is not a spatial region and which is such that b s-depends_on c at every time t during the course of b’s existence. (axiom label in BFO2 Reference: [050-003]) [has axiom label: http://purl.obolibrary.org/obo/bfo/axiom/050-003]
Imported from


If you want text of different sizes to *feel* like the same weight, make larger text thinner and smaller text bolder. – Steve Schoger · 16 Nov 2017
If you want text of different sizes to *feel* like the same weight, make larger text thinner and smaller text bolder.


class WEBrick::HTTPServer
An HTTP Server
Public Class Methods
Creates a new HTTP server according to config
An HTTP server uses the following attributes:
- :AccessLog
-
An array of access logs. See
WEBrick::AccessLog
- :BindAddress
-
Local address for the server to bind to
- :DocumentRoot
-
Root path to serve files from
- :DocumentRootOptions
-
Options for the default
HTTPServlet::FileHandler
- :HTTPVersion
-
The HTTP version of this server
- :Port
-
Port to listen on
- :RequestCallback
-
Called with a request and response before each request is serviced.
- :RequestTimeout
-
Maximum time to wait between requests
- :ServerAlias
-
Array of alternate names for this server for virtual hosting
- :ServerName
-
Name for this server for virtual hosting
WEBrick::GenericServer::new
# File lib/webrick/httpserver.rb, line 46 def initialize(config={}, default=Config::HTTP) super(config, default) @http_version = HTTPVersion::convert(@config[:HTTPVersion]) @mount_tab = MountTable.new if @config[:DocumentRoot] mount("/", HTTPServlet::FileHandler, @config[:DocumentRoot], @config[:DocumentRootOptions]) end unless @config[:AccessLog] @config[:AccessLog] = [ [ $stderr, AccessLog::COMMON_LOG_FORMAT ], [ $stderr, AccessLog::REFERER_LOG_FORMAT ] ] end @virtual_hosts = Array.new end
Public Instance Methods
Logs req
and res
in the access logs. config
is used for the server name.
# File lib/webrick/httpserver.rb, line 220 def access_log(config, req, res) param = AccessLog::setup_params(config, req, res) @config[:AccessLog].each{|logger, fmt| logger << AccessLog::format(fmt+"\n", param) } end
Creates the HTTPRequest
used when handling the HTTP request. Can be overridden by subclasses.
# File lib/webrick/httpserver.rb, line 230 def create_request(with_webrick_config) HTTPRequest.new(with_webrick_config) end
Creates the HTTPResponse
used when handling the HTTP request. Can be overridden by subclasses.
# File lib/webrick/httpserver.rb, line 237 def create_response(with_webrick_config) HTTPResponse.new(with_webrick_config) end
The default OPTIONS request handler says GET, HEAD, POST and OPTIONS requests are allowed.
# File lib/webrick/httpserver.rb, line 147 def do_OPTIONS(req, res) res["allow"] = "GET,HEAD,POST,OPTIONS" end
Finds the appropriate virtual host to handle req
# File lib/webrick/httpserver.rb, line 207 def lookup_server(req) @virtual_hosts.find{|s| (s[:BindAddress].nil? || req.addr[3] == s[:BindAddress]) && (s[:Port].nil? || req.port == s[:Port]) && ((s[:ServerName].nil? || req.host == s[:ServerName]) || (!s[:ServerAlias].nil? && s[:ServerAlias].find{|h| h === req.host})) } end
Mounts servlet
on dir
passing options
to the servlet at creation time
# File lib/webrick/httpserver.rb, line 155 def mount(dir, servlet, *options) @logger.debug(sprintf("%s is mounted on %s.", servlet.inspect, dir)) @mount_tab[dir] = [ servlet, options ] end
Mounts proc
or block
on dir
and calls it with a WEBrick::HTTPRequest
and WEBrick::HTTPResponse
# File lib/webrick/httpserver.rb, line 164 def mount_proc(dir, proc=nil, &block) proc ||= block raise HTTPServerError, "must pass a proc or block" unless proc mount(dir, HTTPServlet::ProcHandler.new(proc)) end
Processes requests on sock
# File lib/webrick/httpserver.rb, line 69 def run(sock) while true req = create_request(@config) res = create_response(@config) server = self begin timeout = @config[:RequestTimeout] while timeout > 0 break if sock.to_io.wait_readable(0.5) break if @status != :Running timeout -= 0.5 end raise HTTPStatus::EOFError if timeout <= 0 || @status != :Running raise HTTPStatus::EOFError if sock.eof? req.parse(sock) res.request_method = req.request_method res.request_uri = req.request_uri res.request_http_version = req.http_version res.keep_alive = req.keep_alive? server = lookup_server(req) || self if callback = server[:RequestCallback] callback.call(req, res) elsif callback = server[:RequestHandler] msg = ":RequestHandler is deprecated, please use :RequestCallback" @logger.warn(msg) callback.call(req, res) end server.service(req, res) rescue HTTPStatus::EOFError, HTTPStatus::RequestTimeout => ex res.set_error(ex) rescue HTTPStatus::Error => ex @logger.error(ex.message) res.set_error(ex) rescue HTTPStatus::Status => ex res.status = ex.code rescue StandardError => ex @logger.error(ex) res.set_error(ex, true) ensure if req.request_line if req.keep_alive? && res.keep_alive? req.fixup() end res.send_response(sock) server.access_log(@config, req, res) end end break if @http_version < "1.1" break unless req.keep_alive? break unless res.keep_alive? end end
Finds a servlet for path
# File lib/webrick/httpserver.rb, line 182 def search_servlet(path) script_name, path_info = @mount_tab.scan(path) servlet, options = @mount_tab[script_name] if servlet [ servlet, options, script_name, path_info ] end end
Services req
and fills in res
# File lib/webrick/httpserver.rb, line 125 def service(req, res) if req.unparsed_uri == "*" if req.request_method == "OPTIONS" do_OPTIONS(req, res) raise HTTPStatus::OK end raise HTTPStatus::NotFound, "`#{req.unparsed_uri}' not found." end servlet, options, script_name, path_info = search_servlet(req.path) raise HTTPStatus::NotFound, "`#{req.path}' not found." unless servlet req.script_name = script_name req.path_info = path_info si = servlet.get_instance(self, *options) @logger.debug(format("%s is invoked.", si.class.name)) si.service(req, res) end
ServerNameIndication callback
# File lib/webrick/https.rb, line 129 def ssl_servername_callback(sslsocket, hostname = nil) req = SNIRequest.new(sslsocket, hostname) server = lookup_server(req) server ? server.ssl_context : nil end
Unmounts dir
# File lib/webrick/httpserver.rb, line 173 def unmount(dir) @logger.debug(sprintf("unmount %s.", dir)) @mount_tab.delete(dir) end
Adds server
as a virtual host.
# File lib/webrick/httpserver.rb, line 193 def virtual_host(server) @virtual_hosts << server @virtual_hosts = @virtual_hosts.sort_by{|s| num = 0 num -= 4 if s[:BindAddress] num -= 2 if s[:Port] num -= 1 if s[:ServerName] num } end


Form
If you don't know exactly whether you can come, you now have the opportunity to set your status to "Tentative".
From now on you can tell us whether you are arriving by car and how many seats your car has.
Name
Period
From
Till
If you do not specify a time period, we assume that you are present throughout.
Accommodation
Number of Seats


|
<< Click to Display Table of Contents >> Navigation: »No topics above this level« Windows Phone 8.1 Devices |
Key Step: The following steps will need to be performed once on each of the 8-10 client devices. Not all apps will be used in the industry guides, but setting them up on the phone will give you the flexibility to show them during the session.
Setup Tip: If you have previously used the Windows Phone, you will need to first delete the account you used in the past and then proceed with adding an account.
To begin, connect to the WLAN on the device by navigating to Settings.
In the settings screen, select Wi-Fi and look for the name of the WLAN that was setup and configured for CIE.
Select the WLAN and then enter a password, if necessary, before selecting done.
Once connected, start the installation and configuration of the Outlook/Exchange mailbox on the device by completing the following steps.
Still in Settings, select email+accounts and then choose Add an account. Select Exchange as the account type.
Enter the email address of the user you want to configure (e.g., karenb@<yourtenantname>.onmicrosoft.com), followed by that user’s password (in this case, pass@word1), then select sign in and then done. This user’s email, contacts and calendar should begin to sync to the device.
Key step: In order to display all the emails in the persona's inbox, you must configure each of the email accounts (under Settings) that have been setup and choose to Download email from any time. The Windows Phone, by default, will be set to display email from the last seven days so this must be changed to see all.
Tap on the magnifying glass to open Cortana and tap allow so the app will initialize and be ready for use during the session. Perform one search for a local business and open it all the way to the Map App and click allow on any prompts.
In order to download and install apps from the Store (e.g., Skype for Business, Yammer), as well as show a personal calendar, you will need to set up a personal Live ID account in Email & Accounts on the Windows Phone. Once this account has been added, you can create calendar events that conflict with those we have already configured in Outlook/Exchange.
Common Question: Each Live ID will work on up to five devices.
For Skype for Business, navigate to the Store and search for Skype for Business.
Tap Install. Skype for Business will finishing installing from the app list.
Open Skype for Business, tap through several screens prior to signing in for the first time. Enter the credentials for the user persona of this device, by entering the entire email address (e.g<EMAIL_ADDRESS>and pass@word1 before tapping the checkmark icon.
On the screen below, you do not need to enter a valid phone number to proceed. For example, you may enter 1-555-123-4567. Click No, Thanks on the Customer Experience Improvement Program.
Next, you will be prompted to turn on Push Notifications. Swipe to the left to turn off push notifications.
Tap the install button at the bottom of the screen. This will begin the download and installation process, which provides a status bar below the app in the list.
Once the installation has completed, you can launch the app by tapping on it one last time.
Select Log In and provide the credentials for the user persona of this device by entering the entire email address (e.g<EMAIL_ADDRESS>and pass@word1 before tapping Log In and OK.
The device is now fully set up and ready for the CIE session. Repeat the steps in this section on each Windows Phone 8.1.


module EpicGeo::Clustering::KMeans
K-Means Clustering
Allows Tweets to be used as points for x-iterations of k clusters.
Adapted from: gist.github.com/cfdrake/995804 Deprecated as clustering method for Tweets
Constants
- INFINITY
Public Instance Methods
kmeans(tweets, k, iterations=10)
click to toggle source
kmeans algorithm
# File lib/epic_geo/geoprocessing/k-means.rb, line 55 def kmeans(tweets, k, iterations=10) clusters = tweets.sample(k).collect{ |tweet| Cluster.new(tweet)} iterations.times do |index| # Assign points to clusters tweets.each do |tweet| min_dist = +INFINITY min_cluster = nil # Find the closest cluster clusters.each do |cluster| dist = tweet.point.distance(cluster.center) if dist < min_dist min_dist = dist min_cluster = cluster end end # Add to closest cluster min_cluster.tweets << tweet end clusters.each do |cluster| cluster.recenter! end if index < iterations-2 # Reset points for the next iteration clusters.each do |cluster| cluster.tweets = [] end end end to_return = [] clusters.each do |cluster| to_return << cluster.tweets end return to_return end


 He took over the following year and was quickly elected prime minister, a position he held until 1991
The daughter of former Australian prime minister Bob Hawke said he ordered her to keep quiet about her alleged rape by one of his political allies for fear it would damage his career, Australian media has reported.
Rosslyn Dillon alleged she was raped three times by a late Labor member of parliament in the 1980s, The New Daily reported Saturday.
In a court affidavit, Dillon said her father one of Australia's most popular prime ministers told her not to go to the police to avoid controversy ahead of his challenge for the party leadership in 1982.
The allegations were reportedly made as part of her Aus$4 million ($2.73 million) claim to Hawke's estate, which she is disputing after receiving $750,000 in his will.
Hawke was unsuccessful in his 1982 attempt to become a Labor leader. He took over the following year and was quickly elected prime minister, a position he held until 1991.
He died in May aged 89.
According to The New Daily, there are several inconsistencies in Dillon's claims, including the timing of certain documented historical events.
Dillon's sister, Sue Pieters-Hawke, said the family had been aware of the allegations at the time and Hawke found them distressing.
"She did tell people at the time. I believe there was a supportive response but it didn't involve using the legal system," she told The New Daily.
Dillon reportedly said she was "still haunted by the sexual assaults" and may have found closure if she had been able to go to the police.


Adam J Sullivan
Assistant Professor of Biostatistics
Brown University
library(readr)
ree <- read_csv("ree.csv")
ree
## # A tibble: 13 x 2
## CF Healthy
## <dbl> <dbl>
## 1 1153 996
## 2 1132 1080
## 3 1165 1182
## 4 1460 1452
## 5 1634 1162
## 6 1493 1619
## 7 1358 1140
## 8 1453 1123
## 9 1185 1113
## 10 1824 1463
## 11 1793 1632
## 12 1930 1614
## 13 2075 1836
BDSA
PackageSIGN.test(x ,y, md=0, alternative = "two.sidesd",
conf.level=0.95)
x
is a vector of valuesy
is an optional vector of values.md
is median and defaults to 0. alternative
is way to specific type of test.conf.level
specifies \(1-\alpha\).# install.packages("devtools")
# devtools::install_github('alanarnholt/BSDA')
library(BSDA)
attach(ree)
SIGN.test(CF, Healthy)
detach()
##
## Dependent-samples Sign-Test
##
## data: CF and Healthy
## S = 10, p-value = 0.02
## alternative hypothesis: true median difference is not equal to 0
## 95 percent confidence interval:
## 25.4 324.5
## sample estimates:
## median of x-y
## 161
##
## Achieved and Interpolated Confidence Intervals:
##
## Conf.Level L.E.pt U.E.pt
## Lower Achieved CI 0.908 52.0 316
## Interpolated CI 0.950 25.4 324
## Upper Achieved CI 0.978 8.0 330
library(tidyverse)
ree <- ree %>%
mutate(diff = CF - Healthy)
ree
## # A tibble: 13 x 3
## CF Healthy diff
## <dbl> <dbl> <dbl>
## 1 1153 996 157
## 2 1132 1080 52
## 3 1165 1182 -17
## 4 1460 1452 8
## 5 1634 1162 472
## 6 1493 1619 -126
## 7 1358 1140 218
## 8 1453 1123 330
## 9 1185 1113 72
## 10 1824 1463 361
## 11 1793 1632 161
## 12 1930 1614 316
## 13 2075 1836 239
binom.test(2,13)
##
## Exact binomial test
##
## data: 2 and 13
## number of successes = 2, number of trials = 10, p-value = 0.02
## alternative hypothesis: true probability of success is not equal to 0.5
## 95 percent confidence interval:
## 0.0192 0.4545
## sample estimates:
## probability of success
## 0.154
8
-17
52
-76
| Subtraction | Positive Ranks | Negative Ranks |
|---|---|---|
| 8 | 1 | |
| -17 | -2 | |
| 52 | 3 | |
| -76 | -4 | |
| Sum | 4 | -6 |
\[ z =\dfrac{W_{smaller}- \dfrac{n(n+1)}{4}}{\sqrt{\dfrac{n(n+1)(2n+1)}{24}-t^3-\dfrac{t}{48}}}\]
attach(ree)
wilcox.test(CF, Healthy, paired=T)
detach(ree)
##
## Wilcoxon signed rank test
##
## data: CF and Healthy
## V = 80, p-value = 0.005
## alternative hypothesis: true location shift is not equal to 0
\[ z = \dfrac{W_s-\dfrac{n_s(n_s+n_L + 1)}{2}}{\sqrt{\dfrac{n_sn_L(n_s+n_L+1)}{12}}}\]
mtcars
library(tidyverse)
cars <- as_data_frame(mtcars)
cars
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
mpg
and am
mpg
: Miles Per Gallon on Averageam
attach(cars)
wilcox.test(mpg, am)
detach(cars)
##
## Wilcoxon rank sum test with continuity correction
##
## data: mpg and am
## W = 1000, p-value = 3e-12
## alternative hypothesis: true location shift is not equal to 0
kruskal.test(formula, data, subset, ...)
formula
is y~x
or can enter outcome,group
instead.data
is the dataframe of interest.subset
if you wish to test subset of data. BSDA
package. Arthriti
| Variable | Description |
|---|---|
time |
Time in Days until patient felt relief |
treatment |
Factor with three levels A , B , and C |
library(BSDA)
Arthriti
## # A tibble: 51 x 2
## time treatment
## <int> <fct>
## 1 40 A
## 2 35 A
## 3 47 A
## 4 52 A
## 5 31 A
## 6 61 A
## 7 92 A
## 8 46 A
## 9 50 A
## 10 49 A
## # ... with 41 more rows
kruskal.test(time~treatment, data=Arthriti)
##
## Kruskal-Wallis rank sum test
##
## data: time by treatment
## Kruskal-Wallis chi-squared = 2, df = 2, p-value = 0.4
cor()
function. #Pearson from Monotonic Decreasing
cor(x2,y2, method="pearson")
#Spearman from Monotonic Decreasing
cor(x2,y2, method="spearman")
## [1] -0.887
## [1] -0.996
library(tidyverse)
library(dslabs)
data("polls_2008")
qplot(day, margin, data = polls_2008)
resid <- ifelse(lm(margin~day, data = polls_2008)$resid > 0, "+", "-")
polls_2008 %>%
mutate(resid = resid) %>%
ggplot(aes(day, margin)) +
geom_smooth(method = "lm", se = FALSE, color = "black") +
geom_point(aes(color = resid), size = 3)
poll_2008
data is to assume that public opinion remained approximately the same within a week's time. With this assumption in place, we have several data points with the same expected value. span <- 3.5
tmp <- polls_2008 %>%
crossing(center = polls_2008$day) %>%
mutate(dist = abs(day - center)) %>%
filter(dist <= span)
tmp %>% filter(center %in% c(-125, -55)) %>%
ggplot(aes(day, margin)) +
geom_point(data = polls_2008, size = 3, alpha = 0.5, color = "grey") +
geom_point(size = 2) +
geom_smooth(aes(group = center),
method = "lm", formula=y~1, se = FALSE) +
facet_wrap(~center)
span <- 7
fit <- with(polls_2008,
ksmooth(day, margin, x.points = day, kernel="box", bandwidth = span))
polls_2008 %>% mutate(smooth = fit$y) %>%
ggplot(aes(day, margin)) +
geom_point(size = 3, alpha = .5, color = "grey") +
geom_line(aes(day, smooth), color="red")
\[ \hat{f}(x_0) = \sum_{i=1}^N w_0(x_i) Y_i \]
kernel=box
in our call to the function ksmooth
. ksmooth
function provides a "smoother" option which uses the normal density to assign weights:x_0 <- -125
tmp <- with(data.frame(day = seq(min(polls_2008$day), max(polls_2008$day), .25)),
ksmooth(day, 1*I(day == x_0), kernel = "normal", x.points = day, bandwidth = span))
data.frame(x = tmp$x, w_0 = tmp$y) %>%
mutate(w_0 = w_0/sum(w_0)) %>%
ggplot(aes(x, w_0)) +
geom_line()
The final code and resulting plot look like this:
span <- 7
fit <- with(polls_2008,
ksmooth(day, margin, x.points = day, kernel="normal", bandwidth = span))
polls_2008 %>% mutate(smooth = fit$y) %>%
ggplot(aes(day, margin)) +
geom_point(size = 3, alpha = .5, color = "grey") +
geom_line(aes(day, smooth), color="red")
ksmooth
, shown above. library(broom)
fit <- loess(margin ~ day, degree=1, span = span, data=polls_2008)
loess_fit <- augment(fit)
if(!file.exists(file.path("loess-animation.gif"))){
p <- ggplot(tmp, aes(day, margin)) +
scale_size(range = c(0, 3)) +
geom_smooth(aes(group = center, frame = center, weight = weight), method = "lm", se = FALSE) +
geom_point(data = polls_2008, size = 3, alpha = .5, color = "grey") +
geom_point(aes(size = weight, frame = center)) +
geom_line(aes(x=day, y = .fitted, frame = day, cumulative = TRUE),
data = loess_fit, color = "red")
gganimate(p, filename = file.path("loess-animation.gif"), interval= .1)
}
if(knitr::is_html_output()){
knitr::include_graphics(file.path("loess-animation.gif"))
} else{
centers <- quantile(tmp$center, seq(1,6)/6)
tmp_loess_fit <- crossing(center=centers, loess_fit) %>%
group_by(center) %>%
filter(day <= center) %>%
ungroup()
tmp %>% filter(center %in% centers) %>%
ggplot() +
geom_smooth(aes(day, margin), method = "lm", se = FALSE) +
geom_point(aes(day, margin, size = weight), data = polls_2008, size = 3, alpha = .5, color = "grey") +
geom_point(aes(day, margin)) +
geom_line(aes(x=day, y = .fitted), data = tmp_loess_fit, color = "red") +
facet_wrap(~center, nrow = 2)
}
total_days <- diff(range(polls_2008$day))
span <- 21/total_days
fit <- loess(margin ~ day, degree=1, span = span, data=polls_2008)
polls_2008 %>% mutate(smooth = fit$fitted) %>%
ggplot(aes(day, margin)) +
geom_point(size = 3, alpha = .5, color = "grey") +
geom_line(aes(day, smooth), color="red")
spans <- c(.66, 0.25, 0.15, 0.10)
fits <- data_frame(span = spans) %>%
group_by(span) %>%
do(broom::augment(loess(margin ~ day, degree=1, span = .$span, data=polls_2008)))
tmp <- fits %>%
crossing(span = spans, center = polls_2008$day) %>%
mutate(dist = abs(day - center)) %>%
filter(rank(dist) / n() <= span) %>%
mutate(weight = (1 - (dist / max(dist)) ^ 3) ^ 3)
if(!file.exists(file.path( "loess-multi-span-animation.gif"))){
p <- ggplot(tmp, aes(day, margin)) +
scale_size(range = c(0, 2)) +
geom_smooth(aes(group = center, frame = center, weight = weight), method = "lm", se = FALSE) +
geom_point(data = polls_2008, size = 2, alpha = .5, color = "grey") +
geom_line(aes(x=day, y = .fitted, frame = day, cumulative = TRUE),
data = fits, color = "red") +
geom_point(aes(size = weight, frame = center)) +
facet_wrap(~span)
gganimate(p, filename = file.path( "loess-multi-span-animation.gif"), interval= .1)
}
if(knitr::is_html_output()){
knitr::include_graphics(file.path("loess-multi-span-animation.gif"))
} else{
centers <- quantile(tmp$center, seq(1,4)/4)
tmp_fits <- crossing(center=centers, fits) %>%
group_by(center) %>%
filter(day <= center) %>%
ungroup()
tmp %>% filter(center %in% centers) %>%
ggplot() +
geom_smooth(aes(day, margin), method = "lm", se = FALSE) +
geom_point(aes(day, margin, size = weight), data = polls_2008, size = 3, alpha = .5, color = "grey") +
geom_point(aes(day, margin)) +
geom_line(aes(x=day, y = .fitted), data = tmp_fits, color = "red") +
facet_grid(span ~ center)
}
## Error in fortify(data): object 'fits' not found
loess
and the typical bin smoother.
loess
keeps the number of points used in the local fit the same. loess
uses a weighted approach. Basically, instead of using least squares, we minimize a weighted version. loess
has the option of fitting the local model robustly. An iterative algorithm is implemented in which, after fitting a model in one iteration, outliers are detected and down-weighted for the next iteration. To use this option, we use the argument family="symmetric"
.--- .class #id
span
argument, which expects a proportion. N
is the number of data points and span=0.5
, then for a given \(x\), loess
will use the 0.5 * N
closest points to \(x\) for the fit. -- .class #id
\[ \sum_{i=1}^N w_0(x_i) \left[Y_i - \left\{\beta_0 + \beta_1 (x_i-x_0)\right\}\right]^2 \]
-- .class #id
ggplot
uses loess in its geom_smooth
function: polls_2008 %>% ggplot(aes(day, margin)) +
geom_point() +
geom_smooth()
polls_2008 %>% ggplot(aes(day, margin)) +
geom_point() +
geom_smooth(color="red", span = 0.15,
method.args = list(degree=1))


Nacelle Go Service Framework
Nacelle initializes and monitors internal processes, ensuring the application continues to report healthy.
Nacelle populates user-defined configuration structs from the environment and provides basic type conversions and validation logic.
Nacelle injects dependencies into user-defined process structs from an application-level service container.
Nacelle encourages opinionated structured logging to stderr at all layers of the application.
Nacelle provides skeleton processes suitable for HTTP servers, gRPC servers, AWS Lambda servers, and generic worker processes.
Nacelle forms the base for the Chevron HTTP server framework and the Scarf gRPC server framework.
Nacelle is 100% open source and community-driven. All components are available under the MIT License on GitHub.


Rafie aydin ihsan
school in junior high school
Hello, my name is Rafie Aydin Ihsan, I am currently studying at the Depok Bhakti Youth High School, I am 16 years old, I am working in the field of backend developer & game developer.
I am passionate about building excellent software that improves the lives of those around me. specialize in thinking outside the box to find unique solutions to difficult engineering problems.


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| Recovery rate | {{ (report.recoveryRate * 100).toFixed(2) | number }}% |
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