Chapter 2 Matching
This lecture note will cover the following topics:
- Exact Matching
- Propensity Score Matching
- Multivariate Caliper Matching
- Matching with Multiple Controls
- Full Matching
2.1 What is matching?
In observational study, absent random assignment, treated and control individuals may differ in terms of covariates, so direct comparison of the outcomes of treated individuals and controls may compare individuals who are not comparable - that is, a direct comparison may be biased as an estimate of the effect caused by the treatment.
Pros:
- Simple and intuitive
- Blinding to outcome info
- Diagnostic for overlap is easy
Cons:
- Theory is difficult
- It requires a lot of practice.
2.2 Exact Matching
Idea: Pair people with identical \(X\)s
2.3 Propensity Score Matching
Quick Review on Propensity Score: Propensity score is the conditional probability of exposure to treatment given the observed covariates, \(e(\mathbf{x}) = \mathbb{Pr}(A = 1|\mathbf{x})\), where \(\mathbf{x}\) is the covaraites and \(A\) is the intervention variable. The propensity score is unkown, but it can be estimated from the data. For example, we can use the logistic regression:
\[\log\{\frac{e(\mathbf{x_i})}{1 - e(\mathbf{x_i})}\} = \beta_0 + \mathbf{x_i}^T\mathbf{\beta}\]
Idea: Pair people with similar \(e(X)\). We know \(X \perp A | e(X)\).
Calculate the propensity score for all subjects. Define the distance between subject i in the treatment group and subject j in the control group as:
\[d(\mathbf{x_i}, \mathbf{x_j}) = \big|\text{logit}(e(\mathbf{x_i})) - \text{logit}(e(\mathbf{x_i}))\big|\]
2.4 Multivariate Caliper Matching
Why we need multivariate caliper matching?
In lecture 6, we learned matching with propensity score, which tends to balance all of the covariates used to build that score, but two individuals with the same propensity score may differ in important ways. Also, propensity score matching is a single covariate matching, which ignore the interaction between different covarites.
2.4.1 (a) Mahalanobis Distances
Let \(\mathbf{x}\) be the covariates random vector. Let \(\hat{\Sigma}\) be the sample covariance matrix of \(\mathbf{x}\). Then the estimated Mahalanobis distance between subject \(i\) and \(j\), who has covarates \(\mathbf{x_i}\) and \(\mathbf{x_j}\) repectively, is defined as:
\[d(\mathbf{x_i}, \mathbf{x_j}) = (\mathbf{x_i} - \mathbf{x_j})^T\hat{\Sigma}^{-1}(\mathbf{x_i} - \mathbf{x_j})\]
See the following comments on Mahalanobis distance from Rosenbaum’s book, Design of Observational Studies:
“The Mahalanobis distance was originally developed for use with multivariate Nomal data, and for data of that type it works fine. With data that are not Normal, the Mahalanobis distance can exhibit some rather odd behavior. If one covariate contains extreme outliers of has a long-tailed distribution, its standard deviation will be inflated, and the Mahalanobis distance will tend to ignore that covariate in matching.”
A simple alternative to the Mahalanobis distance is the ‘rank-based Mahalanobis distance’ which replaces each of the covariates by its ranks. Check out Design of Observational Studies, Chapter 8.3 for details.
2.4.2 (b) Penalize large distance
The idea is that two individuals can be close on the propensity score to a degree, once this degree is achieved, covariates \(\mathbf{x}\) may affect the distance. Define \(w\) as the caliper width. With \(w\), if two individuals have propensity scores that differ more than \(w\), we will add a penalty to the ahalanobis distance between subject \(i\) and \(j\). Explicitly,
\[d_{new}(\mathbf{x_i}, \mathbf{x_j})= \begin{cases} d(\mathbf{x_i}, \mathbf{x_j}) + p\times \big|\text{logit}(e(\mathbf{x_i}))-\text{logit}(e(\mathbf{x_j}))\big|,& \text{if } \big|\text{logit}(e(\mathbf{x_i}))-\text{logit}(e(\mathbf{x_j}))\big| \geq w\\ d(\mathbf{x_i}, \mathbf{x_j}), & \text{if } \big|\text{logit}(e(\mathbf{x_i}))-\text{logit}(e(\mathbf{x_j}))\big| < w \end{cases}\]
where \(e(\mathbf{x})\) is the propensity score of covariates \(\mathbf{x}\), \(d(\mathbf{x_i}, \mathbf{x_j})\) is the Mahalanobis distance between individual \(i\) and \(j\) and \(p\) is the penalty term.
In practical, we may want to care about the following things:
What’s the value of \(p\)?
Usually \(p = 1000\). In Paul Rosenbaum’s 2019 review on matching: he used \(d_{new}(\mathbf{x_i}, \mathbf{x_j}) = +\infty\) when \(\big|\text{logit}(e(\mathbf{x_i}))-\text{logit}(e(\mathbf{x_j}))\big| \geq w\).
What’s the value of \(w\)?
People use \(w = 0.5 \times SD(\text{logit}(e(\mathbf{x})))\) or \(w = 0.2 \times SD(\text{logit}(e(\mathbf{x})))\) in practice.
Comments: Use of the Mahalanobis distance inside propensity score calipers will balance covariates and also pair similar individuals. Also, using both Mahalanobis distance and propensity score calipers adds a protection against the failure of a single matching technique.
2.5 Matching with Multiple controls
In previous matching algorithms, we only match one treatment with one control. In matching with multiple controls, each treatment is matched to at least one control. For example if we match 1 treatment with 2 controls, assume we have 10 subjects in treatment group, we will end up with 10 matched sets, which each contains 1 treatment and 2 controls. Note that the 20 controls included in matched sets need to be different.
How many controls?
Let \(m\) be the number of controls to be matched for one treatment. In Paul Rosenbaum’s 2019 review on matching:
“Under a simple, familiar, conventional Gaussian model for matched sets, the variance of the estimator is proportional to 1+1/m, where the omitted constant of proportionality does not depend on m, but depends on all sorts of other things: the sample size, the variance of errors, and so on (see, for instance, Rosenbaum 2010, section 8.7)”
For example, \(m=1\) means paired matching, then \(1+\frac{1}{m} = 2\). If \(m = +\infty\), then \(1+\frac{1}{m} = 1\). Based on Rosenbaum’s comment, \(1+\frac{1}{m}\) represents the variability. By adding controls from 1 to \(+\infty\), the sampling uncertainty from controls reduces but the uncertainty from treatment is unchanged. For example when \(m=10\), \(1+\frac{1}{m} = 1.1\) so almost all the uncertainty come from treatment group. In practice, \(m = 3 \sim 5\).
Pros and cons:
- Pros: Efficiency. More samples are included inside matched sets.
- Cons: Balance becomes terrible.
2.6 Full Matching
In full matching, we can accept one treated matched with multiple controls and many treated matched with one control.
Assessing Balance from Full Matching: Before-matching standardized difference calculation is the same as before. For after matching, we use a weighted harmonic mean. Specifically, let \(s = 1, \cdots, S\) denote the \(S\) matched sets. For each covariate X, the standarized difference after matching is computed as:
\[\Delta_{X}=\frac{\frac{\sum_{s=1}^{s} w_{s}\left(\bar{X}_{s, A=1}-\tilde{X}_{s, A=0}\right)}{\sum_{s=1}^{s} w_{s}}}{\text { SE from before matching }}, \quad w_{s}=\frac{1}{\frac{1}{\text { Number of treated in } s}+\frac{1}{\text { Number of Controls in } s}}\]
A matched pair has weight \(w_s = 1\), so this generalization makes sense.


parul bhattiDesigner . 80's kid . In love with everything Japanese
Designer . 80's kid . In love with everything Japanese


This website template has been designed by Free Website Templates for you, for free. You can replace all this text with your own text. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper
This website template has been designed by Free Website Templates for you, for free. You can replace all this text with your own text.
Click to read moreThis website template has been designed by Free Website Templates for you, for free. You can replace all this text with your own text.
Click to read moreThis website template has been designed by Free Website Templates for you, for free. You can replace all this text with your own text.
Click to read more


Zend\View\Renderer\PhpRenderer composes a plugin manager for managing helpers, specifically an instance of Zend\View\HelperPluginManager, which extends Zend\ServiceManager\AbstractPluginManager, and this extends Zend\ServiceManager\ServiceManager. As you can see, the HelperPluginManager is a specialized service manager, so you can register a helper/plugin like any other service (see the Service Manager documentation for more information).
Programmatically, this is done as follows:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | // $view is an instance of PhpRenderer
$pluginManager = $view->getHelperPluginManager();
// Register as a invokable class:
$pluginManager->setInvokableClass('lowercase', 'MyModule\View\Helper\LowerCase');
// Register as a factory:
$pluginManager->setFactory('lowercase', function ($pluginManager) {
$lowercaseHelper = new MyModule\View\Helper\LowerCase;
// ...do some configuration or dependency injection...
return $lowercaseHelper;
});
|
Within an MVC application, you will typically simply pass a map of plugins to the class via your configuration.
1 2 3 4 5 6 7 8 9 | // From within a configuration file
return array(
'view_helpers' => array(
'invokables' => array(
'lowercase' => 'MyModule\View\Helper\LowerCase',
'uppercase' => 'MyModule\View\Helper\UpperCase',
),
),
);
|
If your module class implements Zend\ModuleManager\Feature\ViewHelperProviderInterface, or just the method getViewHelperConfig(), you could do the following (it’s the same as the previous example).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | namespace MyModule;
class Module
{
public function getAutoloaderConfig(){ /*common code*/ }
public function getConfig(){ /*common code*/ }
public function getViewHelperConfig()
{
return array(
'invokables' => array(
'lowercase' => 'MyModule\View\Helper\LowerCase',
'uppercase' => 'MyModule\View\Helper\UpperCase',
),
);
}
}
|
The two latter examples can be done in each module that needs to register helpers with the PhpRenderer; however, be aware that another module can register helpers with the same name, so order of modules can impact which helper class will actually be registered!
Writing custom helpers is easy. We recommend extending Zend\View\Helper\AbstractHelper, but at the minimum, you need only implement the Zend\View\Helper\HelperInterface interface:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | namespace Zend\View\Helper;
use Zend\View\Renderer\RendererInterface as Renderer;
interface HelperInterface
{
/**
* Set the View object
*
* @param Renderer $view
* @return HelperInterface
*/
public function setView(Renderer $view);
/**
* Get the View object
*
* @return Renderer
*/
public function getView();
}
|
If you want your helper to be capable of being invoked as if it were a method call of the PhpRenderer, you should also implement an __invoke() method within your helper.
As previously noted, we recommend extending Zend\View\Helper\AbstractHelper, as it implements the methods defined in HelperInterface, giving you a headstart in your development.
Once you have defined your helper class, make sure you can autoload it, and then register it with the plugin manager.
Here is an example helper, which we’re titling “SpecialPurpose”
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | // /module/src/MyModule/View/Helper/SpecialPurpose.php
namespace MyModule\View\Helper;
use Zend\View\Helper\AbstractHelper;
class SpecialPurpose extends AbstractHelper
{
protected $count = 0;
public function __invoke()
{
$this->count++;
$output = sprintf("I have seen 'The Jerk' %d time(s).", $this->count);
return htmlspecialchars($output, ENT_QUOTES, 'UTF-8');
}
}
|
Then assume that we register it with the plugin manager, by the name “specialpurpose”.
Within a view script, you can call the SpecialPurpose helper as many times as you like; it will be instantiated once, and then it persists for the life of that PhpRenderer instance.
1 2 3 4 | // remember, in a view script, $this refers to the Zend\View\Renderer\PhpRenderer instance.
echo $this->specialPurpose();
echo $this->specialPurpose();
echo $this->specialPurpose();
|
The output would look something like this:
1 2 3 | I have seen 'The Jerk' 1 time(s).
I have seen 'The Jerk' 2 time(s).
I have seen 'The Jerk' 3 time(s).
|
Sometimes you will need access to the calling PhpRenderer object – for instance, if you need to use the registered encoding, or want to render another view script as part of your helper. This is why we define the setView() and getView() methods. As an example, we could rewrite the SpecialPurpose helper as follows to take advantage of the EscapeHtml helper:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | namespace MyModule\View\Helper;
use Zend\View\Helper\AbstractHelper;
class SpecialPurpose extends AbstractHelper
{
protected $count = 0;
public function __invoke()
{
$this->count++;
$output = sprintf("I have seen 'The Jerk' %d time(s).", $this->count);
$escaper = $this->getView()->plugin('escapehtml');
return $escaper($output);
}
}
|
Sometimes it is convenient to instantiate a view helper, and then register it with the renderer. This can be done by injecting it directly into the plugin manager.
1 2 3 4 5 6 | // $view is a PhpRenderer instance
$helper = new MyModule\View\Helper\LowerCase;
// ...do some configuration or dependency injection...
$view->getHelperPluginManager()->setService('lowercase', $helper);
|
The plugin manager will validate the helper/plugin, and if the validation passes, the helper/plugin will be registered.
The source code of this file is hosted on GitHub. Everyone can update and fix errors in this document with few clicks - no downloads needed.


Please use the form below to submit your job offer to www.JobFluent.com A couple of important things to keep in mind (please don't skip):
- Your ad will not be published if you are a 3rd party recruiter / headhunter
- Cost: 199€ + VAT. Job post will be active for 30 days.
*Obligatorio


I am currently a junior at Rutgers University studying Computer Science with minors in Mathematics and Statistics in the School of Arts and Sciences Honors Program. In addition I am pursuing a Masters in Mathematical Finance concurrently with an expected graduation date in the Fall of 2019. Prior to this, I graduated from West Windsor Plainsboro High School South where I began studying Computer Science and participated in Hack Princeton, Hack Rutgers and several other hackathons.
I love the Hackathon culture and am passionate about getting students excited about computer science and STEM in general.
My professional interests include Big Data Analysis, Machine Learning and Artificial Intelligence with a focus in quantitative finance. In the past I have done contract work for Research Development and Innovation Service a subcontractor for the Defense Advanced Research Projects Agency, several startups. Because of the nature of defense and start up work, I am unable to disclose many details on a public website but I welcome the opportunity to discuss my work further via email or phone correspondence.
My not so professional interests include political activism, nature conservation, hiking, college wrestling and football (Go Pats).
Work ExperenceI have experience working with Java, Python, and C++ and am able to quickly adapt to new languages and technologies.
I prefer to work in Python and have completed several machine learning projects for fun using Scikit-learn, Tensorflow and Pandas, the majority of which are focused in the quantitative finance space.
Familiar with Linux, OS X and Windows.
Experienced with VPN Network Configuration (L2TP/IPSec and SSH).
Working proficiency with Git VCS and Maven.
Very experienced with coffee; french pressed, pour over, Keurig, you name it.


TravelDiary
Share And Store Your Experience
Home
Search Destination
Login
Sign Up
Travel Direction Finder
Origin
Destination


When women are not making the news,
we all lose 50%
of the story
Join the movement
#ChicasPoderosas
What is
Chicas Poderosas is a global community that ignites change by inspiring and developing women in media and creating opportunities for all voices to be heard.
Chicas Poderosas offers professional training to provide women in media with the concrete skills to take their media career to the next level, boost entrepreneurial projects and push forward female leadership in journalism.
Chicas Poderosas believes in a world of informed and equal societies where all voices are heard. We have an engaged and talented network of 5500 women across 18 countries creating content to transform the existing narrative ensuring that women-focused storytelling and editorial workflows affect how we report our world.
Mariana Santos is a visual storyteller, who did groundbreaking work as a member of the interactive team at The Guardian in London. She leads design thinking workshops to increase multidisciplinary approach to storytelling, and she is a leader in community transformation. Leader of Chicas Poderosas together with a team of female leaders in different industries.
LinkedinGia is a Creative Technologist based in Buenos Aires, Argentina. Gia has a degree on Media and Entertainment Management and has a career focused on developing new platforms to tell stories. Nowadays, she is Program Manager for Chicas Poderosas Global for their Mediathons, . She is also part of Chicas Programando, a community of women developers in Argentina. She has been a fellow for Genero e Numero in Brazil and has a scholarship from the National Fine Arts fund of Argentina for developing her first art installation named Low Poly Heart.
LinkedinCo-founder of ADA.vc, journalist, entrepreneur and Master of Digital Media from Goldsmiths University of London. I was elected the most innovative communication and marketing professional in Brazil by PróXXima magazine. I worked for more than 10 years with communication on different platforms such as cinema, television, newspapers, data visualization and magazines, but I discovered my passion for using technology to create and tell good stories in the Internet.
Camila is an avid traveler, multimedia reporter, humanitarian specialist and story-teller for under-represented communities all over the world with a decade of experience at Globo - the biggest Latin America broadcast Company. Focused on data-driven stories about social issues - women's leadership, inclusion, diversity & entrepreneurship, she runs the audiovisual Brazilian company WeTwo Producers and also is the Lead for Inclusion and Diversity at Chicas Poderosas with a focus on new technologies and education.
LinkedinGaby is an international awarded journalist who has worked for 25 years at the biggest publishing groups in Brazil. She is a storyteller, a producer and a content manager in multiple platforms. Gabriela practices and investigate listening processes in communication. Her goal in life is to see listening incorporated in schools and communication projects, newsrooms and other organizations or systems where information can be used to transform intolerable realities.
LinkedinFounder of 50 For Change, that supports organizations to reach their full potential by advancing women in leadership roles. We are working with organizations and individuals to close the gap between women and men at work, achieve sustainable corporate performance and create a more equal society. Aviva is a serial entrepreneur and has been in the startup industry for the last 10 years, supporting +100 founders to grow internationally.
LinkedinNuala Lawlor is a communications graduate-turned-Canadian diplomat with more than 18 years' experience managing public affairs, developing strategic content and advocating for foreign policy priorities with Global Affairs Canada. She has a career focus on Latin America and Sub-Saharan Africa with previous assignments in Venezuela, Sudan, Ghana, Peru and South Africa. Nuala recently enjoyed a sabbatical from government to collaborate with the amazing Chicas Poderosas team and their mission to train and mentor female storytellers towards increasing innovative, women-rights focussed reporting in Latin America.
LinkedinEloiza has 25 years of experience working for and with associations, nonprofit organizations and government agencies. She is currently the Principal Consultant of Mind Redesign Consulting, a business that she founded nineteen years ago to provide Board governance and transition management and organizational development services. Former Executive Director of UNITY: Journalists for Diversity. Recently appointed executive director of JAWS.
Linkedinhow we
A MediaThon is a hack-a-thon for media makers. Over two days, Chicas brings together a talented array of storytellers - from journalists and designers, to coders and technologists - to create and collaborate, developing innovative original content around a specific theme. Boundaries are challenged and networks are expanded. The objective is to disrupt the status quo, inspire new perspectives and promote media that educates on underrepresented issues, changing the narrative and making new headlines.
Know morePower reports (investigaciones poderosas) are deep dive, collaborative special reports involving Chicas journalists from multiple countries that face a similar challenge. Power reports deliver high-quality journalism products on under-represented issues with a regional impact.
Know moreThe New Ventures Lab (NVL) is a 20-week accelerator for independent, women-led media outlets in Latin America. The NVL provides mentorship and training for female media entrepreneurs to build sustainable business models while developing their leadership skills. Previous NVL teams are transforming the Latin American media landscape, generating positive social impact and creating new female-driven leadership models.
Know moreChicas around the world
If you want to know more about Chicas Poderosas, learn about our programs or propose partnerships, email us at:
<EMAIL_ADDRESS>Medium Facebook Twitter Instagram Newsletter


kelp acidification warming microbial effects ocean change changes temperature treatments blistered healthy marine supplementary material, tissue associated figure future {border-style conditions observed px;} using #ffffff;} OTUs microbiomes abundances climate communities disease table Ecklonia effect versus condition habitat-forming (e.g. (electronic bleaching blisters host impacts S). Steinberg affected differences microbiome photosynthetic Ecol. Microbiol. University community experiment interactions mesocosm taxa ./j.-...x Australia New acidification. blistering relative samples significantly water Climate Marzinelli Thomas affect individuals multivariate response structure Biol. Campbell Change Connell DNA Marine Science South [], analysis and/or day electronic microorganisms natural px; studies {font-family ./-. Environ. Microbial Proc. Wales approximately combination differed diseases ecological entire field font-size forests lower number putative seaweed temperate treatment (i.e. Coleman Material abundance affecting bacterial belonging composition different direct distribution double; environmental experiment, global higher kelp, mesocosms model pathogens secondary sequencing similar strong treatments, yield Australian Centre Delisea Glob. Kelaher Kelp Kjelleberg Rev. Sci. acidification, adjacent based biodiversity biological bleached border-color border-width condition, contamination did functional however, identified independent indirect interactive laminae models multiple particularly populations prevalence resilience second sequences significant solid; subsequently time used {font-style {font-weight (day ./pnas. .°C Acad. Alternatively, Anderson Coffs Environmental Harbour, However, LINK Mar. Natl OTU Res. Sb). Supplementary Thus, USA ]). analyses bold checked collected communities. compared coral courier; current data degradation dominant ecosystem ecosystems ecosystems. em; functioning genus haphazardly hosts including influenced kelps lead leading led likely order physiological predicted present processes pt;} quality quantified reduce resulting role seawater seaweeds shifts short-term showed species sterile subtidal suggesting temperatures treatments. understanding


Lightlevel and state of Lights
This represents the logical enable state of the blinker. It it is true as long the blinker is enabled regardless of the physical enabled state of the light (i.e. it does not blink and ignores enable state of electric).
Intensity of the dashboard backlight as factor <0;1>
Is the left blinker enabled?
Is the light in the left blinker currently on?
Is the Right blinker enabled?
Is the light in the Right blinker currently on?
Are the parking lights enabled?
Are the BeamLow lights enabled?
Are the BeamHigh lights enabled?
Are the Beacon lights enabled?
Are the Brake lights enabled?
Are the Reverse lights enabled?


Strangler, mutilator, pedophile, self-described cannibal, Arthur John Shawcross ranks high in the annals of America’s most notorious serial killers.
In 1972, he sexually assaulted and fatally choked a 10-year-old boy and an 8-year-old girl in separate attacks in upstate Watertown.
In 1988 and 1989, he killed 11 upstate women. Most were prostitutes. Most died by battering and strangulation. He cut one corpse open from chest to crotch.

Those evil deeds will not be retold. Instead, this is the story of how Shawcross turned to the Lord in the last months of his life — as told by four men who grew closest to him.
With God as their witness, they say that a man long diagnosed as a sociopath embarked on an intense, genuine, conscience-driven quest for forgiveness.
“He saw himself forgiven by Jesus,” says Father Maduawuchi Stan Ogbonna, a Catholic cleric who has ministered to prisoners at the Sullivan Correctional Facility for almost 22 years.
Shawcross was serving a 250-year sentence at Sullivan. There, murderers, rapists and pedophiles alike scorned him as a monster below even their dignity.
He lived as a pariah until two devout Catholic prisoners and a volunteer Catholic layman encouraged Shawcross to attend Sunday Mass, go to confession and prepare for a Baptism-like ceremony of religious renewal.
In their own words, these men will tell the uplifting story of the serial killer’s final reckoning, along with the meaning they found in his religious awakening.
Felipe Rodriguez served as Shawcross’ primary guide to faith.
Convicted of savagely stabbing a woman to death in 1987, Rodriguez spent 27 years in state prison until Gov. Cuomo granted him clemency last year.
Rodriguez has adamantly protested his innocence. Profiling his case in detail, the Daily News on Sunday raised serious doubts about the finding of guilt, reported that a key witness against Rodriguez appears on the verge of recanting, and chronicled Rodriguez’s transformation from rage-filled inmate to dedicated follower of the teachings of St. Francis of Assisi.
Larry Sieteski gave Shawcross lessons in the ways of St. Francis.
Raised in Buffalo, Sieteski graduated from a Catholic grammar school and a Jesuit high school before earning college and master’s degrees at a Jesuit university. He began his career as a Catholic high school teacher, moved on to pharmaceutical sales and then opened stores selling lottery tickets, cigarettes and alcohol in poor neighborhoods.
Although married and the father of four, Sieteski began an affair with a married woman. There was conflict with her husband. Sieteski hired a tough guy who stabbed the husband to death. Convicted of conspiracy to murder, Sieteski was paroled after 22 years and says he deserved every moment of the time.
Otto Schaefer engaged Shawcross in deep discussions.
A graduate of Aviation High School in Queens and retired IBM executive, Schaefer visits Sullivan once a month to hold group sessions among prisoners studying toward “formation” in the Third Order of Francis, a group dedicated to living by the saint’s precepts.
The prison chaplain — fondly known as Father Stan — sets out every year to save at least one soul among the thousands of hardened cases he has long served.
Here, they speak.
Felipe Rodriguez:
Shawcross was hated in prison. Hated. He was befriended by no one. I was working as a maintenance mechanic. I would walk around the prison fixing things with a shopping cart full of tools.
I was locking in A block, meaning I was living in A block. Shawcross was in A block, too. I was in cell 221 on the second floor. Shawcross was downstairs in the flats. He was so heavy they didn’t put him on top. He was in cell 153.
One day, I went to Shawcross’s cell because his toilet was leaking. He wasn’t there.  I changed the wax seal, the O-ring and fixed the toilet. He came back to the cell and said, “Aw, man, you got water all over my floor.”

After that, we didn’t have yes or no between us for a long time.
Larry Sieteski:
I saw Felipe in the yard playing baseball in almost a Yankee uniform. He is a very good player. I knew that he had identified as a Catholic. So, I talked to him about coming to a three-day program that is a lot of fun and involves outsiders coming into prison. I told him it was called REC. He thought it was a recreation program. Actually, it is Residents Encountering Christ.
Men from the outside lead discussions and activities aimed at leading you back to the Catholic faith. One guy was a fire lieutenant at 9/11 and he talked about how faith got him through.
The speakers affect you. For Felipe, it was a turning point toward truly making faith part of his life.
Father Stan:
Felipe was not attending our church. Lo and behold, he attended our weekend retreat, REC. At the time, in his frustration, he had switched religion. Now he became a Catholic again. He made his mom happy.
I gave him period of grace. He continued to be his old self. Then I tightened the noose by saying, “You’ll never ‘F’ this or ‘F’ that in my office.
He whined to his mother on the phone. He went back to his cell and cried for more than two hours, how to deal with this hard man Father Stan.
Otto Schaefer:
The Franciscans have three orders. The first is brothers and priests. The second is nuns. The third order is lay people, Franciscan seculars, who go through a two-year formation class.
Larry Sieteski sent out 80 letters trying to get a formation class in Sullivan. I couldn’t find anybody willing to work with men in Sullivan. After about a year, I contacted Father Stan. I spent three hours talking with the men. I had no intention of ever visiting a prison. That was about 12 years ago.
Felipe joined the group. Half of the classes should be the men sharing. These men immediately started sharing. That was the most impressive thing.
The lessons are associated with Francis’ 24 rules of life. We would talk about a particular rule. Felipe would talk about the impact on him. I sensed that he was a special person. He became very spiritual. He would write his own rosary meditations and they were like beautiful prayers.
Felipe Rodriguez:
So time went by, and I was locked in the same housing unit as Shawcross. I always noticed that he would sit on the floor. In Sullivan, the housing unit is the mess hall. They’ve got tables with four chairs, and you can only sit at a table if someone lets you. No one would eat with Shawcross, so he ate on the floor.
One day, I came from a Franciscan gathering and we had said the rosary, and I was feeling great. I was just floating with God. And I happened to look at Shawcross on the floor eating his food with his tray on his lap.
 You go to church. You thank God for everything. You ask God to help you. You pray to God every day, but you reach out to nobody. So, I went to Shawcross.”
I said, “Mr. Shawcross, get up from the floor and go sit at the table.”
He looked at me and said, “OK,” and he got up from the floor and he sat at the table, ate his food and said, “Thank you very much.”
The next day, he came out and went to sit on the floor. I looked at him and said, “Shawcross, come here. As long as I’m in this jail, you no longer sit on the floor. You sit at this table. That’s your chair.”
Many people came up to me and asked, “Why are you dealing with that serial killer. He’s an evil motherf----r. If you keep hanging out with him, we’re not gonna talk to you no more.”
I guess Shawcross noticed. Next morning, I came out and Shawcross said, “I don’t want to cause you problems. I’ll go sit on the floor.”
I said, “You stay at that table, and you make sure that you don’t worry about me. Worry about you.”
 All you people have been deemed unworthy of society. So what makes you more worthy than this dude here? You think his crime is worst as well.
“Whether you are here for murder, whether you are here for robbery, whether you are here for rape, whether you are here for pedophilia, you are here for transgressing against another human being.
“So if you really want to make amends with society, then you have to start mending each other. If anybody has a problem with Shawcross, they have a problem with me.”
He sat at my table for another year. Quiet, we never said a word to each other. One day, he came out and said, “I want to thank you for what you did. You are my only friend. I did a lot of wrong things, and you are the only friend I got.”
I said, “You’re so very wrong, Man. Your best friend? His name is Jesus, dude. I’m just a drop in the sea, my man. I’m another man, like you, looking for a little bit of redemption, and looking for God to have mercy on me, and perhaps to give me a second chance to live life.”
We went like that for about six months, not even a word. One day he came out and says, “Tomorrow’s my birthday.”
I said, “Good for you,” and I ate my breakfast.
I had a birthday card in my cell. So, I wrote a few words: “I have neither silver, nor gold, but what I have I give you. May Our Lord and Savior Jesus Christ grant you much life, and may He take your heart and take everything that’s evil from you and replace it with all good. Your brother in Christ,” and I signed it.
That’s the best thing I ever did.
Shawcross found the card amazing. We ate for his birthday. He made some sandwiches, and I brought him a cake. We celebrated his birthday by ourselves.
So, about a week later, Shawcross, says, “Can I make a few drawings for your family?” Shawcross was an artist. He made three beautiful paintings for my sister and her new son.
My sister wrote back a nice letter blessing him. He showed me the letter and he was crying and he said, “You guys have given me a little humanity.”
I said, “No, my friend, you have given us a little bit of humanity,” and I asked, “Why did you do those paintings for my sister?”
He said, “What you did for me. I can never repay you. You were kind to me.”
I said, “All right, you can pay me one way. You can do one thing for me and we are even. You’ll never owe me anything. You’ll never have to feel bound to me in any way.”
He said, “What’s that?”
I said, “Go to church with me one day. Just once. You’ll never have to return. Just once.”
He said, “I’ll think about it.”
I said, “Fair enough.”
He came out one day and put a satanic bible on the table and said, “I worship Satan.”
I said, “Good for you.  Keep practicing what you practice.”
I went and got my Bible and I said, “This is my Bible. That’s what I worship. I’ll tell you what: Let me read yours, and you read mine. If I think yours is better than mine, I’ll convert. If you think mine is better than yours, then you convert. It’s a fair game.”
Shawcross took mine and I took his with two fingers because I didn’t wanna touch that s--t, but I took it because I proposed it. I put it in a paper bag and put it underneath my bed. I lit a white candle and left it there.
About a week later, he came around and said, “I like your book.”
I said, “You like my book?”
He said, “Yeah.”
So I opened it, I took my pen, and dedicated it to him.
I said, “This is my personal Bible. My wife gave it to me a long time ago. It’s yours to keep.”
So he took it.
I loved that Bible.
Shawcross said, “Did you read my Bible?”
I said, “You want me to bulls--t you, or you want me to tell you the truth?”
He said, “I want the truth.”
I said, “Hell no.”
He said, “It’s all right.”
I said, “Can I get rid of it for you?”
He said, “Yeah.” So I took it to Father Stan and I said, “Father, this is Shawcross’ bible. You need to get rid of it.”
The next day, Father Stan said he put some holy water on it, he did a ritual and burned it.
Father Stan:
Artie was a Catholic. I make rounds. I meet people. You see a little spark. I knew that things were taking a different shape, and he would make a few paintings and donate to the church.
I said, “Yeah, Artie, thank you for all those things. They are good. But I want you in the church.”
I go to the visitors’ room every Saturday. I had interactions with Artie and his daughter. I would tell him, “Come to church. Come to church. Just come.”
Larry Sieteski:
We were well into Franciscanism when Arthur’s situation popped up. Father says Shawcross needs instruction in the faith and the sacraments. He volunteers me, even though I didn’t want to be in a room with Arthur Shawcross.
I would have to spend time alone with somebody who did what he did to children.
Father would remind me of my duties and what I professed to.  You have a class of one. You are going to teach him the basics of the faith. You will work with him in the room. Felipe will work with him in the block.”
Arthur had the hardest time believing confession would work for him. I would tell him about my past and that I was in for something I was ashamed of and that I was using the last years of my time to make right.
I would say, “We have to look at your motivations. Are you really, really, sorry? Would you do it again, given who you are today?”
We spent some time in the Bible and some formation reading. If I gave him 60 pages to read, he would read 90 or 100.
He approached it in a very heartfelt way. I would question him on the point of the reading material that I wanted him to remember. He was with it. It wasn't that he memorized things. We engaged in true education. He was sincere. He came around to the Catholic faith and the hope that he wouldn’t go to hell.
It was real that way. Arthur was a basic down-to-earth guy.
Otto Schaefer:
Arthur Shawcross came into three monthly sessions. He made me feel uncomfortable. There was another man in the prison who had killed many people, Mad Dog Sullivan. Quite often, Joe Sullivan sat next to me and my wife in church. I was not afraid of Joe Sullivan. He killed on a contract. That was just his job. Sullivan didn’t kill for enjoyment.
Shawcross was different. He made me feel uncomfortable. It was his mannerism. The way he stared at people. His mannerism and his stare made him a frightening person.
I’ll never know how Felipe was able to turn that man around to want to be baptized. It took three years.
Felipe Rodriguez:
One day, Shawcross said, “I'll go Sunday to church with you. Only one Sunday.”
I said, “OK. Good. Let’s go.”
He asked, “Do you think God can forgive me?”
I said, “His mercy is so majestic that He gave His only begotten Son for you. He loves all his creation and He wants to forgive you. However, forgiveness can only be attained by the desire to be forgiven. Want it, and He will give it to you.”
He said, “People are not going to accept me in church because people hate me.”
I sang in the choir and I told Shawcross that he could sit next to me there. He cried through the entire Mass. His tears flowed and he followed the Mass. But he cried through the entire Mass because he said he was sorry for everything he did.
After Mass on Sunday, Shawcross told Father Stan that he wanted to go to confession. Father gave him a hug. I got Father’s stole, the holy water and Father’s chair. Shawcross looked at me like a lost soul.
I said, “This is where you are going to be free of all your burdens. Let Father hold on to that.”
Shawcross walked into Father’s office. They were inside for more than an hour.
Father walked out of there so tired, exhausted. I had never seen him like that. He went home.
I arranged for Shawcross to go to the chapel from morning to night. He had carte blanche in the sanctuary. I would come sometimes and find Shawcross kneeling before the altar looking at the tabernacle. On many occasions, I caught Shawcross crying in the sanctuary.
One time, Shawcross asked me why I was in prison. I said I was wrongly accused of murdering a lady. Shawcross looked at me and said, “You don’t have it in you.
That was the nicest thing I ever heard. Artie was the only guy who ever came outright and told me, I believe you are innocent.
This monster, this violent guy who everybody despised, and I once despised, a guy who I thought deserved to be hanged, this guy decided to display some mercy and some graciousness upon me and tell me I was innocent.
Father Stan:
I was going to do something special for Shawcross, a reception into the church. To call it baptism, it wasn’t baptism, but I hoped to start giving him communion.
He started coming to church, normal like any other person.
He came to our weekend retreat REC. He was here Friday, Saturday, Sunday.
By Monday, Tuesday, he is dead. He had made his peace with God and passed away.
Felipe Rodriguez:
Shawcross was all in. He asked to be baptized and asked me to be his sponsor. Then he went for gallbladder surgery at a hospital in Albany. He came back in a wheelchair. He came to a REC retreat for two days. The second day, everybody loves this guy. On that second day, something happened. He was supposed to be baptized, but he died.
Arthur John Shawcross passed away Nov. 10, 2008, at the age of 63, from a pulmonary embolism. The New York State Correction Commission later reported that, in his last hours, the Sullivan Correctional Facility gave Shawcross “grossly negligent, incompetent and inadequate medical evaluation and treatment,” helping to cause his death.
Shawcross reported that his leg had become painful and he could not walk. He requested another wheelchair. A nurse refused to send one, saying that regulations called for Shawcross to walk to the infirmary.
A corrections officer pleaded for help. He reported that, returning from a chapel service, two Catholic inmates had helped Shawcross walk into his cell.
Additional reporting by Joe Carmichael
Read the first article, HIS GIFT OF LIFE: Felipe Rodriguez.


Socrata Integration
Socrata provides a large number of government open data repositories. The Socrata RAMADDA plugin allows you to search, access and display data from Socrata.
This is available as a development plugin. You will need to install the
socrataplugin.jar.
The plugin comes with a number of Socrata repositories pre-defined. You can add other repositories by adding a
classes.txt file to your RAMADDA plugins directory. Add any number of lines of the form:
#org.ramadda.plugins.socrata.SocrataSearchProvider;<hostname>;<name>
org.ramadda.plugins.socrata.SocrataSearchProvider;data.cdc.gov;Center for Disease Control and Prevention
org.ramadda.plugins.socrata.SocrataSearchProvider;cdph.data.ca.gov;California Department of Public Health
Socrata maintains a list of
available servers.


Edward Ascan
Fullstack Software Developer
I am a Junior Software Developer based in Toronto, passionate learner with a love for developing interesting and challening applications. Please contact me to learn more!
Fullstack Software Developer
I am a Junior Software Developer based in Toronto, passionate learner with a love for developing interesting and challening applications. Please contact me to learn more!


--- title: About date: 2011-10-01 15:35:50.000000000 +01:00 type: page parent_id: '0' published: true password: '' status: publish categories: [] tags: [] meta: _wp_page_template: default _edit_last: '27605990' _oembed_d84424982e0b11d2e5a444bb8cf4529c: "{{unknown}}" _oembed_c944a7380eee6e8197c89eaa33ac0dcf: "{{unknown}}" author: login: moononthebones email<EMAIL_ADDRESS>display_name: Ben first_name: '' last_name: '' permalink: "/about/" ---
I am a PhD student at the University of Bristol, UK, studying Middle and Late Jurassic ichthyosaurs. I have been a dinosaurs-and-prehistoric-animals nut since at least the age of three and have no wish to stop now! My aim with this blog is to spread the word on ichthyosaurs and how much pleasure I get from them. This will thus revolve around the work that I am doing, my thoughts and progress.
Besides palaeontology, I have a huge love for classical music and listen to, play and compose to my heart's content (which is, cumulatively, quite a lot). My favourite composers are Jean Sibelius, Gustav Mahler and John Adams, and from this some may be able to tell that I am very much a lover of twentieth century music (though haven't really got the hang of post-1980 pop). I play tuba, piano and have been known to try violin and (infrequently) guitar.
Feel free to contact me.


Assembly
| Type | Summary |
|---|---|
| AssetStore | Allows to easyly load assets. |
| BreadcrumbItem | Models the information for a breadcrumd item. |
| BreadcrumbItemCollection | A collection of BreadcrumbItems. |
| ErrorInfo | Models error information to be shown to the user. |
| ForbiddenInfo | Models the information for reporting a forbidden response. |
| ListingViewModel | Implements a view model for pages that list items. |
| MvcButton | Models a button to be used on MVC applications. |
| MvcButtonCollection | A collection of MvcButtons. |
| WebException | Thrown to inform a web user that an error has occured. |
In this document


25th Annivarsary of the department
A demonstration of personal and professional learning of students through outstanding academic and career-focused experiences.
Re-branding an iconic symbol of hospitality
concept, design, development


Hi, I am finishing up my Computer Science and Business Administration studies at UC Berkeley. Past summers, I have interned at ZapLabs and Google. At school, I work with Capital Investments at Berkeley in applying deep and reinforcement learning on finance markets. This semester I teach Efficient Algorithms and Intractable Problems (CS 170) as an undergraduate student instructor. You can find my résumé here and teaching materials below.
| Course | Course Name | Semester | Resource |
|---|---|---|---|
| CS 170 |
Efficient Algorithms and Intractable Problems |
Fall 2017 (Head TA) |
Link |
| CS 170 |
Efficient Algorithms and Intractable Problems |
Spring 2017 | Link |
| CS 61A |
The Structure and Interpretation of Computer Programs |
Fall 2016 |
Link
|
| CS 61A |
The Structure and Interpretation of Computer Programs |
Spring 2016 | Link |


Enter the username "Brian", then input the number of on campus and online courses (priced differently) to view the total cost of tuition for the semester.
Username:


---
layout: post
title: Skype
categories: []
tags: []
status: publish
type: post
published: true
meta:
_original_post_id: ''
_original_import_author: John Duprey
author:
---
Skype is a proprietary VoIP application that provides a free voice call service (to other Skype users) and a prepaid service for dialling out to fixed or mobile phones anywhere on the planet.
It supports all major OS platforms including Linux and OS X. I've created an account: jduprey. I've yet to try it out. If you already know me, give me a ring via Skype so we can both try it out. Its free!


The nannou forum is the home of our community. Please visit feel free to contribute to the discussion if you have any questions, issues, suggestions or anything at all about nannou.
We would love to hear from you!
The nannou Github repository shows our latest development on the coding framework, contributions to the project's code, documentation and website.
If you have any ideas or requests for features you can do so here.


Welcome to EyeOfCharacteristics
Simple tips:
-
Use this path for a POST-Request (image) to EOC /analyze-image
-
curl -i -H "Content-Type: application/json" -X POST -d '{"image":{YOUR-FILE}' https://{THIS-HOST}:443/analyze-image
-
It has to be a .jpg file
-
Use this path for a POST-Request (video) to EOC /analyze-video
-
curl -i -H "Content-Type: application/json" -X POST -d '{"image":{YOUR-FILE}' https://{THIS-HOST}:443/analyze-video
-
It has to be a .mov file
-
It is easier to use the EOC Vue.js Frontend, than the cURL commands
-
For more information: README.md
-
Vue.js Frontend: EyeOfCharacteristics


conpagnon.utils package¶
Submodules¶
conpagnon.utils.array_operation module¶
Created on Thu Sep 28 09:58:24 2017
@author: Dhaif BEKHA
Useful operation on arrays.
-
conpagnon.utils.array_operation.
append_masks
(subjects_connectivity_dictionnary, kinds, discard_diagonal, vectorize)[source]¶ Append a new key called ‘masked_array’ in the subjects connectivity matrices dictionnary and stock as values a boolean mask array accounting for discarded rois.
- Parameters
subjects_connectivity_dictionnary (dict) –
- A multi-levels dictionnary organised as follow :
The first keys levels is the different groupes in the study.
The second keys levels is the subjects IDs
The third levels is the different kind matrices
for each subjects, a ‘discarded_rois’ key for the discarded rois array index.
kinds (list) – List of present kinds in the subjects connectivity matrices dictionnary.
discard_diagonal (bool) – If True, the mask diagonal is discarded in the vectorization process. This argument is passed to masked_void_rois_connectivity_matrix
vectorize (bool) – If True, the returned mask is vectorized. This argument is passed to masked_void_rois_connectivity_matrix
- Returns
output – The modified subjects connectivity matrices with a new key for each subjects containing the boolean mask array for the discarded ROIs. A new keys is added too, which contain the diagonal array of the mask.
- Return type
dict
Notes
If the discarded rois keys do not exist, that is no labels ‘void’ is found in the atlas labels file of each subjects, then all roi are included in the analysis, and we append a boolean mask array of False values.
-
conpagnon.utils.array_operation.
array_rebuilder
(vectorized_array, array_type, diagonal=None)[source]¶ Reconstruct a square array assuming a it is symmetric
- Parameters
vectorized_array (numpy.array) – The one dimensional array you want to rebuild.
diagonal (numpy.array, optional) – The one dimensional array containing the diagonal of the non-vectorized array. If None, we assume that the diagonal was kept in the vectorization process.
array_type (str) – The type of the array. Choices are: numeric, bool.
- Returns
output 1 – The reconstructed array, shape (n_features, n_features).
- Return type
numpy.array
See also
vectorizer()
This function vectorized a two dimensional numeric or boolean array
nilearn.connectome.vec_to_sym_matrix()
This function reconstruct a symmetric array from a one dimensional array.
-
conpagnon.utils.array_operation.
check_2d
(numpy_array)[source]¶ Check if an array is two dimensional.
- Parameters
numpy_array (numpy.array of any shape.) –
:raises ValueError : if the passed array is NOT two dimensional, a Value Error: :raises is raised.:
-
conpagnon.utils.array_operation.
concatenate_imgs_in_order
(imgs_directory, index_roi_number, filename, save_directory)[source]¶ Concatenate 3D NifTi images into a single 4D NifTi files, given a user order.
- Parameters
imgs_directory (string) – The directory containing the list of images. Each file, must contain a number identifying the file.
index_roi_number (list of int) – The list of file number in the order you want to ordered the images before concatenation
filename (string) – The final name of the 4D file containing the images.
save_directory (string) – The directory where to save the 4D generated 4D file.
- Returns
output (list) – Return the list of the pull path to roi files, in the order of concatenation. It should exactly follow the order you provide via the variable index_roi_number.
See Also
——–
nilearn.image.concat_img (This function concatenate a list of 3D NifTi images.) – We use this function to concatenate the images.
Notes
Each file you want to concatenate, must have a pattern to identifying them. Indeed, we use it to search the entire path corresponding to the file, and append it in a list containing all the path to the files in the right order before concatenation. The pattern is simply a number in the file name.
-
conpagnon.utils.array_operation.
mask_array_std
(arrays, masked_array, axis)[source]¶ Compute the standard deviation of a ndimensional numpy array.
- Parameters
arrays (ndimensional numpy.array, shape (number of subjects, number of regions, number of regions)) – The ndimensional array you want to compute the mean.
masked_array (ndimensional numpy.array, shape (.., numbers_of_regions, numbers_of_regions)) – The ndimensional boolean masked accounting for the values you want to discard. True for masked values, False elsewhere.
axis (int) – The direction for computing the standard deviation.
- Returns
output – The standard deviation array excluding some value in the direction along axis.
- Return type
numpy.array shape (number of regions, number of regions)
See also
masked_void_rois_connectivity_matrix()
This function compute the boolean mask for accounting the discarded rois.
-
conpagnon.utils.array_operation.
masked_arrays_mean
(arrays, masked_array, axis)[source]¶ Compute the arithmetic mean of a ndimensional numpy masked array.
- Parameters
arrays (ndimensional numpy.array, shape (.., number of regions, number of regions)) – The ndimensional array you want to compute the mean.
masked_array (ndimensional numpy.array, shape (.., numbers_of_regions, numbers_of_regions)) – The ndimensional boolean masked accounting for the values you want to discard. True for masked values, False elsewhere.
axis (int) – The direction for computing the mean.
- Returns
output – The mean array excluding some value in the direction along axis.
- Return type
numpy.array shape (number of regions, number of regions)
See also
masked_void_rois_connectivity_matrix()
This function compute the boolean mask for accounting the discarded rois.
-
conpagnon.utils.array_operation.
masked_void_rois_connectivity_matrix
(subject_kinds_connectivity, kinds, discard_diagonal=False, vectorize=False)[source]¶ Compute a boolean mask array for discarded rois
- Parameters
subject_kinds_connectivity (dict) –
- The individual subject dictionnary containing as keys:
The different kinds
A keys called ‘discarded_rois’ for ROIs to discard during analysis
kinds (list) – List of present kinds in the subjects connectivity matrices dictionnary.
discard_diagonal (bool, optional) – If True, the diagonal are discarded in the vectorization process. Default is False, the diagonal is kept.
vectorize (bool, optional) – If True, the returned mask is vectorized. Default is False
- Returns
output – A boolean array : True when rois are considered discarded, False elsewhere See notes concerning the discarded roi
- Return type
numpy.array, shape (number of regions, number of regions)
See also
compute_connectivity_matrices.individual_connectivity_matrices()
This is the function which compute the connectivity matrices for the chosen kinds, and return a structured dictionnary containing all the connectivity matrices for each subjects and kinds
Notes
A discarded rois, is a ROI where the corresponding labels is ‘void’ in the individual atlas of a given subject. This information is automatically gathered when you extract time series with an individual atlas for each subjects. We account for discarded rois when computing arithmetic mean, or performing t-test for examples by excluding them during the computation.
Excluding the discarded rois, is possible via the numpy.ma structure which build a numpy masked array that is a couple of a numerical array and a boolean array where True are masked values, and False are un-masked values.
Please refer to the numpy documentation for further details.
-
conpagnon.utils.array_operation.
truncate
(f, n)[source]¶ Truncates/pads a float f to n decimal places without rounding
-
conpagnon.utils.array_operation.
vec_to_matrix_boolean_mask
(vectorized_mask, diagonal=None)[source]¶ Reconstruct a ndim symmetrical boolean mask array giving a boolean vectorized mask.
- Parameters
vectorized_mask (numpy.ndarray, shape(.., number of regions, number of regions)) – The vectorized boolean mask.
- diagonalnumpy.array of shape(number of regions), optional
The diagonal to reconstruct if you discard the diagonal when you first vectorize the ndimensional mask array
- Returns
output – The reconstruct ndimensional array of shape (…, numbers of regions, numbers of regions)
- Return type
numpy.ndarray
See also
nilearn.connectome.sym_matrix_to_vec()
,vec_to_sym_matrix()
vectorize_boolean_mask()
This function flatten a boolean ndimensional array.
-
conpagnon.utils.array_operation.
vectorize_boolean_mask
(symmetric_boolean_mask, discard_diagonal=False)[source]¶ Vectorize the lower part of symmetric boolean mask.
- Parameters
symmetric_boolean_mask (numpy.array, shape(.., numbers of regions, numbers of regions)) – A ndimensional boolean numpy array.
discard_diagonal (bool, optional) – If True, the values of the diagonal are not returned. Default is False.
- Returns
output – The flatten ndimensional boolean mask of shape (…, n_features * (n_features + 1) / 2) if discard_diagonal is False and (…, (n_features - 1) * n_features / 2) otherwise.
- Return type
numpy.ndarray
See also
nilearn.connectome.sym_matrix_to_vec()
,vec_to_sym_matrix()
vec_to_matrix_boolean_mask()
This function reconstruct a flatten boolean ndimensional array.
-
conpagnon.utils.array_operation.
vectorizer
(numpy_array, discard_diagonal=False, array_type='numeric')[source]¶ Vectorize a numerical or boolean numpy array
- Parameters
numpy_array (numpy.array, shape (n_features, n_features)) – A two-dimensional numerical, or boolean data type array.
discard_diagonal (bool, optional) – If True, the lower triangle of the array is flatten without the diagonal. Default is False.
array_type (string, optional) – Precise the array type, choices are {‘numeric’, boolean’}, default is ‘numeric’.
- Returns
output 1 (numpy.array, shape(n_features)) – The diagonal of the entered array.
output 2 (numpy.array, shape( (n_features*(n_features+1))/2 ))
is discard_diagonal is True, (n_features*(n_features-1))/2 else. – The vectorized array.
conpagnon.utils.folders_and_files_management module¶
Created on Thu Sep 21 13:34:12 2017
@author: db242421
Utilitary modules.
-
conpagnon.utils.folders_and_files_management.
append_pdf
(input, output)[source]¶ Append a input pdf file to an output empty pdf file.
-
conpagnon.utils.folders_and_files_management.
check_directories_existence
(root_directory, directories_list)[source]¶ Check if all directories supplied exist, raises an exception if not.
- Parameters
root_directory (str) – The full path to a root directory, containing multiple folders.
directories_list (list) – List of directories you want to check for, in root_directory.
- Raises
Exception – Raise an exception if one of the directories supplied do not exist.
-
conpagnon.utils.folders_and_files_management.
create_directory
(directory, erase_previous=False)[source]¶ Create a directory, erase it and create it if it exist.
-
conpagnon.utils.folders_and_files_management.
load_object
(full_path_to_object)[source]¶ Load a python object saved by a pickler operator.
- Parameters
full_path_to_object (str) – The full path to the saved python object, including the .pkl extension.
- Returns
output – The loaded python object.
- Return type
python object
See also
save_object()
This function save a python object using the pickle module.
-
conpagnon.utils.folders_and_files_management.
merge_pdfs
(pdfs, output_filename)[source]¶ Merge together a list of pdf files.
-
conpagnon.utils.folders_and_files_management.
remove_empty_directories
(root_directory)[source]¶ Erase all empty directory at a root location.
- Parameters
root_directory (str) – The full path to a directory.
-
conpagnon.utils.folders_and_files_management.
save_object
(object_to_save, saving_directory, filename)[source]¶ Save a python object in pickle format.
- Parameters
object_to_save (a Python object structure) – A python that can be pickled : list, dict, integer, tuples, etc…
saving_directory (str) – Full path to a saving directory.
filename (str) – Filename of the saved object, including the extension .pkl.
See also
load_object()
This function load a python object save by this function.
Notes
See the pickle module for python object to see a exhausting list of what object can be saved.
conpagnon.utils.pre_preprocessing module¶
Created on Fri Oct 6 17:04:32 2017
@author: db242421<EMAIL_ADDRESS>Useful pre-processing step before doing statistical test.
-
conpagnon.utils.pre_preprocessing.
fisher_transform
(symmetric_array)[source]¶ Return the Fisher transform of all coefficient in a symmetric array.
- Parameters
symmetric_array (numpy.ndarray, shape(.., number of regions, numbers of regions)) – A symmetric numpy array, typically correlation, or partial correlation subject connectivity matrices.
- Returns
output – The fisher transform of the ndimensional array.
- Return type
numpy.ndarray, shape(.., number of regions, numbers of regions)
Notes
The fisher transform is classically computed according to the formula :
\[z = arctanh(r)\]For r = 1, the Fisher transform is not defined, typically on the diagonal of connectivity matrices. Then we fill diagonal value with np.nan values.
-
conpagnon.utils.pre_preprocessing.
stacked_connectivity_matrices
(subjects_connectivity_matrices, kinds)[source]¶ Stacked the connectivity matrices for each group and for each kinds.
If a masked array exist, i.e a ‘masked_array’ key in each subjects dictionnary, we stacked them too.
- Parameters
subjects_connectivity_matrices (dict) –
- A multi-levels dictionnary organised as follow :
The first keys levels is the different groupes in the study.
The second keys levels is the subjects IDs
The third levels is the different kind matrices
for each subjects, a ‘discarded_rois’ key for the discarded rois array index, a ‘masked_array’ key containing the array of Boolean of True for the discarded_rois index, and False elsewhere.
kinds (list) – List of kinds you are interrested in.
- Returns
ouput – A dictionnary with two keys : kinds and masked_array. The values is respectively the stacked matrices for one kind in a ndimensional array of shape (…, numbers of regions, numbers of regions), and the ndimensional boolean mask array of the same shape (…, numbers of regions, numbers of regions).
- Return type
dict
Module contents¶
Created on Thu Sep 21 14:08:13 2017
@author: db242421


All samples are using Ink.requireModules
, please read how to use it at Ink.requireModules section
This is a awesome set of methods to paint the sky.
| Function name | Description |
|---|---|
| .publicMethod(name, number) | Description of the method |
| Property name | Description |
|---|---|
| .publicProperty |
Description of the method
name
bla ble binumber
blo blu


Product Table
| Product Name |
Processor |
RAM |
ROM |
Battery Type |
Graphic Card |
Screen Size |
Screen Type |
| dell laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |
| asus laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |
| apple laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |
| hp laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |
| dell laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |
| asus laptop |
inter i3- 10 th generation |
4GB |
1TB |
Li-Ion |
Normal |
15 inches |
Normal Screen |


{{ define "title" }}{{ .Title }} - {{ end }} {{ define "main" }}
Nope. Nope. Nope.The page you are looking can't be found.


Form Name
if already registered
Login
Name
Email
OK
Try some different email it exists
Password
Contact no.
Blood Group
Select
A+
B+
AB+
O+
A-
B-
AB-
O-
Country list
City list
Select
Street
Area
District
I agree to conditions
Sign Up
show details
From Knockoutjs
Name:
Email:
Contact:
Bloodgroup:
Country:
City:
Street:
AREA:
District:
From javascript
Your Details
NAME:-
Email:-
Contact:-
Blood group:-
Country list:-
City:-
Street:-
Area:-
District:-


Reach out to us if you have any questions.
If you would like to become a client for DiversaTech, please fill out the client contact form!
If you would like to become a sponsor for DiversaTech, please fill out the sponsor contact form!
Please fill out the berkeley students contact form if you have any questions!
Please fill out the other campuses contact form if you want to start a chapter of DiversaTech at your campus!
Please e-mail<EMAIL_ADDRESS>for any additional inquiries.


External dependencies¶
- Although the nanodiffraction toolbox is almost stand-alone, it uses one dependency that might not be available to the user. This external dependency cannot unfortunately be offered by the authors for licensing reasons. This concerns the following function:
read_pilatus
Other external dependencies include the three colormap packages mentioned in Colormaps. The given licenses allow for distribution of the software within this package as long as it is accompanied by the original license.


--- layout: post title: Defeating Planned Obsolescence date: 2015-07-17 21:34:55.000000000 -04:00 type: post published: true password: '' status: publish categories: [] tags: [] meta: _edit_last: '1' _wpb_vc_js_status: 'false' _wpb_vc_js_interface_version: '2' _nectar_gallery_slider: 'off' _nectar_quote: '' _nectar_link: '' _nectar_video_m4v: '' _nectar_video_ogv: '' _nectar_video_poster: '' _nectar_video_embed: '' _nectar_audio_mp3: '' _nectar_audio_ogg: '' _nectar_header_bg: '' _nectar_header_parallax: 'off' _nectar_header_bg_height: '' _nectar_header_bg_color: '' _nectar_header_font_color: '' _disable_transparent_header: 'off' _nectar_love: '0' _mk_post_love: '1' _vc_post_settings: a:1:{s:7:"vc_grid";a:0:{}} author: Timothy Lock ---
One of the weird things that have been happening over the past few weeks (okay fine - half a year) was that the garage door opener would constantly open halfway or so and then all the power would be cut (and it would stop). I've disregarded it since I could always continue opening it by tapping the machine (and the power would come back) or manually open the door. Today, the machine finally gave out and I decided to take a look at it.
At first, I thought that it was just the trip sensor that was loose, wire was loose, etc. Basically I was hoping that the machine itself wasn't broken. After all of that testing, I concluded that the machine inside was busted. What a bummer. Nobody wants a $300 dead weight.
The electrical engineer inside of me (okay fine I am in computer science but its close enough right?) decided to bust open the machine (after unplugging it of course!) to examine what's wrong. I took out my multimeter and started tracing the power and ground to see where it broke (since I remember that the machine completely lost power rather than parts of it not working). Turns out that the solder on one of the connectors went loose.
All in all, that easy fix costed me absolutely nothing (except for a dab of new solder) and if people knew just to take a look into their broken machines, they can save a lot of money.


API Exceptions¶
-
class
petpy.exceptions.
PetfinderError
(Exception)¶ Base Exception class for Petfinder API Exception definitions.
-
class
petpy.exceptions.
PetfinderInvalidCredentials
(PetfinderError)¶ Exception for handling invalid API and secret keys passed to the Petfinder class.
-
class
petpy.exceptions.
PetfinderInsufficientAccess
(PetfinderError)¶ Exception for handling insufficient access errors when working with the Petfinder API. This exception is typically raised when the credentials supplied to the Petfinder API have expired and the connection to the API needs to be re-authenticated.
-
class
petpy.exceptions.
PetfinderResourceNotFound
(PetfinderError)¶ Exception for handling unknown resource requests.
-
class
petpy.exceptions.
PetfinderUnexpectedError
(PetfinderError)¶ Exception for handling unexpected errors from the Petfinder API. This error is generally the result of an unknown and unexpected error that occurs on the server-side of the Petfinder API when sending a request.
-
class
petpy.exceptions.
PetfinderInvalidParameters
(PetfinderError)¶ Exception for handling invalid values passed to Petfinder API method parameters.