public class Animation extends java.lang.Object implements Renderable
| Constructor and Description |
|---|
Animation()
Create an empty animation
|
Animation(boolean autoUpdate)
Create an empty animation
|
Animation(SpriteSheet frames,
int duration)
Create a new animation based on the sprite from a sheet.
|
Animation(SpriteSheet ss,
int[] frames,
int[] duration)
Creates a new Animation where each frame is a sub-image of SpriteSheet ss.
|
Animation(SpriteSheet frames,
int x1,
int y1,
int x2,
int y2,
boolean horizontalScan,
int duration,
boolean autoUpdate)
Create a new animation based on a selection of sprites from a sheet
|
| Modifier and Type | Method and Description |
|---|---|
void |
addFrame(Image frame,
int duration)
Add animation frame to the animation
|
void |
addFrame(int duration,
int x,
int y)
Add animation frame to the animation.
|
Animation |
copy()
Create a copy of this animation.
|
void |
draw()
Draw the animation to the screen
|
void |
draw(float x,
float y)
Draw the animation at a specific location
|
void |
draw(float x,
float y,
Color filter)
Draw the animation at a specific location
|
void |
draw(float x,
float y,
float width,
float height)
Draw the animation
|
void |
draw(float x,
float y,
float width,
float height,
Color col)
Draw the animation
|
void |
drawFlash(float x,
float y,
float width,
float height)
Draw the animation
|
void |
drawFlash(float x,
float y,
float width,
float height,
Color col)
Draw the animation
|
Image |
getCurrentImage()
Get the image associated with the current animation frame
|
int |
getDuration(int index)
Get the duration of a particular frame
|
int[] |
getDurations()
Get the durations of all the frames in this animation
|
int |
getFrame()
Get the index of the current frame
|
int |
getFrameCount()
Get the number of frames that are in the animation
|
int |
getHeight()
Get the height of the current frame
|
Image |
getImage(int index)
Get the image assocaited with a given frame index
|
float |
getSpeed()
Returns the current speed of the animation.
|
int |
getWidth()
Get the width of the current frame
|
boolean |
isStopped()
Check if this animation has stopped (either explictly or because it's reached its target frame)
|
void |
renderInUse(int x,
int y)
Render the appropriate frame when the spriteSheet backing this Animation is in use.
|
void |
restart()
Restart the animation from the beginning
|
void |
setAutoUpdate(boolean auto)
Indicate if this animation should automatically update based on the
time between renders or if it should need updating via the update()
method.
|
void |
setCurrentFrame(int index)
Set the current frame to be rendered
|
void |
setDuration(int index,
int duration)
Set the duration of the given frame
|
void |
setLooping(boolean loop)
Indicate if this animation should loop or stop at the last frame
|
void |
setPingPong(boolean pingPong)
Indicate if this animation should ping pong back and forth
|
void |
setSpeed(float spd)
Adjust the overall speed of the animation.
|
void |
start()
Start the animation playing again
|
void |
stop()
Stop the animation
|
void |
stopAt(int frameIndex)
Indicate the animation should stop when it reaches the specified
frame index (note, not frame number but index in the animation
|
java.lang.String |
toString() |
void |
update(long delta)
Update the animation, note that this will have odd effects if auto update
is also turned on
|
public Animation()
public Animation(boolean autoUpdate)
autoUpdate
- True if this animation should automatically update. This means that the
current frame will be caculated based on the time between renderspublic Animation(SpriteSheet frames, int duration)
frames
- The sprite sheet containing the framesduration
- The duration each frame should be displayed forpublic Animation(SpriteSheet frames, int x1, int y1, int x2, int y2, boolean horizontalScan, int duration, boolean autoUpdate)
frames
- The sprite sheet containing the framesx1
- The x coordinate of the first sprite from the sheet to appear in the animationy1
- The y coordinate of the first sprite from the sheet to appear in the animationx2
- The x coordinate of the last sprite from the sheet to appear in the animationy2
- The y coordinate of the last sprite from the sheet to appear in the animationhorizontalScan
- True if the sprites are arranged in hoizontal scan lines. Otherwise
vertical is assumedduration
- The duration each frame should be displayed forautoUpdate
- True if this animation should automatically update based on the render timespublic Animation(SpriteSheet ss, int[] frames, int[] duration)
ss
- The SpriteSheet backing this animationframes
- An array of coordinates of sub-image locations for each frameduration
- The duration each frame should be displayed forpublic void addFrame(int duration, int x, int y)
duration
- The duration to display the frame forx
- The x location of the frame on the SpriteSheety
- The y location of the frame on the spriteSheetpublic void setAutoUpdate(boolean auto)
auto
- True if this animation should automatically updatepublic void setPingPong(boolean pingPong)
pingPong
- True if the animation should ping pongpublic boolean isStopped()
stopAt
public void setSpeed(float spd)
spd
- The speed to run the animation. Default: 1.0public float getSpeed()
public void stop()
public void start()
public void restart()
public void addFrame(Image frame, int duration)
frame
- The image to display for the frameduration
- The duration to display the frame forpublic void draw()
public void draw(float x, float y)
draw
in interface Renderable
x
- The x position to draw the animation aty
- The y position to draw the animation atpublic void draw(float x, float y, Color filter)
draw
in interface Renderable
x
- The x position to draw the animation aty
- The y position to draw the animation atfilter
- The filter to applypublic void draw(float x, float y, float width, float height)
draw
in interface Renderable
x
- The x position to draw the animation aty
- The y position to draw the animation atwidth
- The width to draw the animation atheight
- The height to draw the animation atpublic void draw(float x, float y, float width, float height, Color col)
draw
in interface Renderable
x
- The x position to draw the animation aty
- The y position to draw the animation atwidth
- The width to draw the animation atheight
- The height to draw the animation atcol
- The colour filter to usepublic void renderInUse(int x, int y)
x
- The x position to draw the animation aty
- The y position to draw the animation atpublic int getWidth()
public int getHeight()
public void drawFlash(float x, float y, float width, float height)
x
- The x position to draw the animation aty
- The y position to draw the animation atwidth
- The width to draw the animation atheight
- The height to draw the animation atpublic void drawFlash(float x, float y, float width, float height, Color col)
x
- The x position to draw the animation aty
- The y position to draw the animation atwidth
- The width to draw the animation atheight
- The height to draw the animation atcol
- The colour for the flashpublic void update(long delta)
delta
- The amount of time thats passed since last updateautoUpdate
public int getFrame()
public void setCurrentFrame(int index)
index
- The index of the frame to renderedpublic Image getImage(int index)
index
- The index of the frame image to retrievepublic int getFrameCount()
public Image getCurrentImage()
public void setLooping(boolean loop)
loop
- True if this animation should loop (true = default)public void stopAt(int frameIndex)
frameIndex
- The index of the frame to stop atpublic int getDuration(int index)
index
- The index of the given framepublic void setDuration(int index, int duration)
index
- The index of the given frameduration
- The duration in (ms) for the given framepublic int[] getDurations()
public java.lang.String toString()
toString
in class java.lang.Object
Object.toString()
public Animation copy()


| EP2112164 |
lipid attachment signals or GPI |
Antiviral peptides linked to a lipid attachment signals or GPI against enveloped virus such as HIV, avian flu, SARS or Ebola virus |
Institute Pasteur of Shanghai |
20080229 |
| WO2009128963 |
spike protein |
Cross-neutralizing human monoclonal antibodies to SARS-CoV and methods of use thereof |
Institute for Research In Biomedicine |
20080117 |
| WO2009128963 |
spike protein |
Cross-neutralizing human monoclonal antibodies to spike protein of SARS coronavirus and methods of use thereof |
Humab, LLC |
20080117 |
| WO2008035894 |
viral infection |
Preparation of antiviral antibody 3D8 fragments and their use in treatment of viral infection |
Sung Kyun Kwan University; Ajou University; Invitroplant Co., Ltd. |
20060919 |
| WO2008060331 |
spike protein |
Antibodies to SARS coronavirus |
Amgen Inc. |
20060519 |
| WO2007044695 |
spike protein |
Neutralizing monoclonal anti-spike protein antibodies for diagnosis and treatment of SARS-coronavirus-associated disease and screening of vaccine or anti-SARS agent |
Dana-Farber Cancer Institute |
20051007 |
| CN1911963 |
RBD of S protein |
Method for preparing neutralizing monoclonal antibody against severe acute respiratory syndrome coronavirus and its application |
Chinese Academy of Sciences |
20050810 |
| CN1903878 |
spike protein |
Fab fragment of human antibody IgG against SARS coronavirus |
Fudan University |
20050726 |
| WO2006095180 |
S2 protein |
Human monoclonal antibodies against SARS-associated coronavirus and treatment of patients with SARS |
Ultra Biotech Ltd.; University of California |
20050310 |
| WO2006086561 |
spike protein |
Neutralizing monoclonal antibodies against severe acute respiratory syndrome-associated coronavirus |
New York Blood Center, Inc. |
20050208 |
| CN1664100 |
spike protein |
Preparation of heavy chain and light chain variable regions of anti-SARS coronavirus antigen antibodies and their diagnostic and therapeutic uses thereof |
Chen Zhinan |
20050204 |
| CN1660912 |
IL-8 |
Sequences of monoclonal antibodies against human interleukin 8 and therapeutic use |
Ye Qingwei |
20041208 |
| WO2006051091 |
spike protein |
Compositions against SARS-coronavirus and uses thereof |
Crucell Holland BV |
20041111 |
| WO2006051091 |
spike protein |
Compositions against SARS-coronavirus comprising at least two immunoglobulins reacting with non-competing epitopes, and therapeutic and diagnostic uses thereof |
Crucell Holland BV |
20041111 |
| CN1673231 |
spike protein |
Monoclonal antibody of SARS coronavirus N protein and its use in treatment of SARS virus infections |
Chinese Academy of Sciences |
20040715 |
| US20060240551 |
spike protein |
Neutralizing monoclonal antibodies against severe acute respiratory syndrome-associated coronavirus |
New York Blood Center, Inc. |
20040602 |
| WO2005054469 |
spike protein |
Anti-SARS-coronavirus monoclonal antibodies, and diagnostic, therapeutic and vaccine preparation uses |
Health Canada |
20031205 |
| WO2005060520 |
spike protein |
Antibodies specific to SARS-CoV spike protein for diagnosis and therapy of SARS and for screening of epitopic vaccines or anti-SARS therapeutics |
Dana-Farber Cancer Institute, Inc. |
20031125 |
| US20050106563 |
spike protein |
Epitope profiles of SARS coronavirus for use in antigen detection, antibody production, and defense against infection |
Genesis Biotech Inc. |
20030908 |
| US20050069869 |
spike protein |
SARS coronavirus codon-optimized sequences for spike (S) protein expression, anti-S human monoclonal antibodies, and therapeutic and diagnostic uses thereof |
University of Massachusetts |
20030804 |
| WO2005012360 |
S and N proteins |
Antibody binding molecules specific for SARS coronavirus |
Crucell Holland BV |
20030722 |
| CN1566155 |
S, N, and M proteins |
Antibody library-derived human monoclonal anti-SARS virus antibodies for treating severe acute respiratory syndrome |
Igcon Therapeutics Co., Ltd.; Genetastix Corporation |
20030710 |
| WO2005007671 |
spike protein |
Compositions and methods for treating SARS using peptides derived from SARS virus E2 N-terminal-alpha helix or C-terminal-alpha helix and related monoclonal antibody |
Epitomics, Inc. |
20030429 |


by Matthew Beedham 1 hour ago5
by Matthew Beedham1 hour ago5
Destruction AllStars goes from PS5 launch title to free PS Plus game
David Canellis · 17 hours ago


Mothers remembered in fundraising
by Sue AustinTwo mothers from St Martins near Oswestry who died in their 40s are being remembered in a fundraising evening.
Wendy Newell was just 46 when she lost her life to cancer while Trudie Fell, 47, died from sepsis.
Their daughters are now organising an evening, not only to raise funds for charities close to their hearts but to do something in their memory.
The event will be held in the Ifton Miners Institute on December 14 and will include bingo, a raffle and face painting for children young and old.
Wendy Newell's daughters, Chloe Pitcher and Jemma Edwards say their mother's death left the family in turmoil.
"She was nursed at Nightingale House Hospice which also gave support to our family at such a sad time, something that we are so grateful for.
"We would like to raise money for Nightingale to enable them to continue to be able to offer their services and support to other families in their time of need."
Trudie Fell thought she had flu when she fell in in February 2007.
Her symptoms worsened with a chest infection diagnosed. But daughters Rhian Traquair and Adele Jebb said their mother in fact had sepsis from a urinary infection.
Rhian, who was just 17 when her mother died, said: "She was our best friend and we were devastated by her death, which was such a shock.
"We want to raise awareness of sepsis as although we didn't know it, she had many of the symptoms. But at the time people were not tuned into to it. We want to make people aware of what the symptoms are as it could save more lives and mean people won't loose the special people in their lives."
She said the two families also wanted to ensure their mothers were remembered.


Making A Chaturaji Set
Chaturaji literally means “4 Kings”. It is a 4 handed Indian chess variant with written sources dating back to 1030 A.D. Like many of the ancient chess variants, sets can be hard to find. In true maker fashion, I found some STL’s of the Nishapur Chess pieces and had a friend 3D print them for me. The King and Queen pieces look similar enough where you can make the 4 sets of pieces needed for Chaturaji. With the help of my 3 and 5 year old daughters, we painted the pieces different colors. Painting chess pieces with children is….interesting. Let’s just say many layers of colors (including some very muddy ones) were involved.
The board is an 8x8 inch red oak plywood which was originally the start for another game. I played around with the grid and it ended up with this imprecise and rustic look. In the end, I felt like the set came together and it was a fun way to spend some time with my kids.


Better Professor is an app that takes the stress out of mentoring your graduate students. Designed and built with higher education in mind, Better Professor gives you the tools to simplify your day-to-day tasks as a mentor. With Better Professor, you can guide students to academic success by staying on track with their projects and feedback requests.
Forgetting about deadlines is a thing of the past. Better Professor makes staying up to date with your students easy, giving you the freedom to concentrate on your own academic work.


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E Source Lighting Technology Atlas
This Atlas is a comprehensive guild to energy efficient lighting,
converting both design and technology fundamentals. It presents
a "system approach" to lighting design, and characterizes the existing
stock of lighting technology, with description of available and
emerging energy efficient alternatives.
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 Note that this only makes 8 cookies, which is a good idea for those who are watching their weight (not too many cookies lying around )Nutritional information included below. This recipe has been featured in a post on The Recipe Girl blog: Agave and Honey Oatmeal M&M Cookies.
AGAVE & HONEY OATMEAL M&M COOKIES
www.RecipeGirl.com
2 Tbsp lightly beaten egg
3 Tbsp agave nectar
1 Tbsp honey
2 Tbsp vegetable or canola oil
1 tsp vanilla extract
½ cup whole wheat pastry flour
1 Tbs ground flaxseed (or wheat germ)
1/8 tsp baking soda
1/8 tsp baking powder
¼ tsp salt
¼ tsp (heaping) ground cinnamon
¾ cup old fashioned oats
M&M’s or raisins
1. Preheat oven to 375°F.
2. Mix egg, agave, honey, oil and vanilla together in a bowl. Stir very well.
3. Combine flour, flaxseed, baking powder, baking soda, salt and cinnamon in a bowl. Stir very well, then add to agave mixture and stir until blended. Stir in oats and desired amount of M&M’s (or raisins). Let batter sit for about 5 minutes.
4. Scoop Tablespoonfuls of dough onto a parchment lined baking sheet. You should be able to fit 8 cookies on one sheet.
5. Bake for 10 to 11 minutes, until set and golden. Cool completely. Store in covered container.
Servings: 8
Yield: 8 cookies
Nutritional information per cookie (M&M’s or raisins are not included in nutritional info.): calories 132, fat 5g (sat fat .5g), cholesterol 16.06mg, sodium 106.94mg, carbohydrates 20g, fiber 2.14g, protein 3.05g
WW Points: Points Plus 4 Old WW Program 3.5
Cooking Tips
*Agave nectar can be found at Trader Joe’s and other specialty markets & health food stores.
Recipe Source: Adapted from Cookie Madness
4 Comments
Hi – I am a HUGE fan of agave and cook/bake with it all the time – the same with flax seed. I just made oatmeal chocolate chunk cookies, and while they are good, they are very soft. Curious, what is the texture of these?
Have a good weekend!
Lily (thequeenoftarts)
[Reply]
RecipeGirl Reply:
May 1st, 2009 at 4:48 PM
They’re not soft… and not crispy… somewhere in the middle.
[Reply]
Recipe for the agave & Honey oatmeal looks great. I have been developing a few agave recipes for my business. The question I have for you is what software or formula do you use to create the nutrition labels for your recipes?
[Reply]
Lori Lange Reply:
July 20th, 2010 at 4:45 AM
@mike, Living Cookbook is the program I use.
[Reply]
Being that I am sensitive to wheat, rice & rye I substituted for 1//4cup oat flour & 1/4 cup masa(corn flour) 1/2 tsp xanthan gum. I was worried but surprisingly they turned out very good. Very good flavor and they held together well. I am a happy baker now!
[Reply]
I just made these and they were amazing. They came out just smooshy but not falling apart. I changed it up a bit for the pretzel M&Ms though. Amazing recipe. Thanks for sharing.
[Reply]


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@Cryptoon Yeah, tried calling. It goes straight to voicemail, never got a call back even when I pretended to want to place a new order. I don't speak Dutch, but the one-star speaks for itself... They seem Dutch, cause the address on the invoice in in Holland, and their domain is registered to a residential address like 2km away form the place of business, as listed on the invoice...
I am thinking small claims court will be my way forward, trouble is the EU one only goes up to 5k EUR, I think my local UK one would cover my (at this point) loss.


|
QuantLib: a free/open-source library for quantitative finance
Fully annotated sources - version 1.30
|
Inverse cumulative normal distribution function. More...
#include <ql/math/distributions/normaldistribution.hpp>
Public Member Functions | |
| InverseCumulativeNormal (Real average=0.0, Real sigma=1.0) | |
| Real | operator() (Real x) const |
Static Public Member Functions | |
| static Real | standard_value (Real x) |
Public Attributes | |
| QL_DEPRECATED typedef Real | argument_type |
| QL_DEPRECATED typedef Real | result_type |
Static Private Member Functions | |
| static Real | tail_value (Real x) |
Private Attributes | |
| Real | average_ |
| Real | sigma_ |
Static Private Attributes | |
| static const CumulativeNormalDistribution | f_ |
| static const Real | a1_ = -3.969683028665376e+01 |
| static const Real | a2_ = 2.209460984245205e+02 |
| static const Real | a3_ = -2.759285104469687e+02 |
| static const Real | a4_ = 1.383577518672690e+02 |
| static const Real | a5_ = -3.066479806614716e+01 |
| static const Real | a6_ = 2.506628277459239e+00 |
| static const Real | b1_ = -5.447609879822406e+01 |
| static const Real | b2_ = 1.615858368580409e+02 |
| static const Real | b3_ = -1.556989798598866e+02 |
| static const Real | b4_ = 6.680131188771972e+01 |
| static const Real | b5_ = -1.328068155288572e+01 |
| static const Real | c1_ = -7.784894002430293e-03 |
| static const Real | c2_ = -3.223964580411365e-01 |
| static const Real | c3_ = -2.400758277161838e+00 |
| static const Real | c4_ = -2.549732539343734e+00 |
| static const Real | c5_ = 4.374664141464968e+00 |
| static const Real | c6_ = 2.938163982698783e+00 |
| static const Real | d1_ = 7.784695709041462e-03 |
| static const Real | d2_ = 3.224671290700398e-01 |
| static const Real | d3_ = 2.445134137142996e+00 |
| static const Real | d4_ = 3.754408661907416e+00 |
| static const Real | x_low_ = 0.02425 |
| static const Real | x_high_ = 1.0 - x_low_ |
Inverse cumulative normal distribution function.
Given x between zero and one as the integral value of a gaussian normal distribution this class provides the value y such that formula here ...
It use Acklam's approximation: by Peter J. Acklam, University of Oslo, Statistics Division. URL: http://home.online.no/~pjacklam/notes/invnorm/index.html
This class can also be used to generate a gaussian normal distribution from a uniform distribution. This is especially useful when a gaussian normal distribution is generated from a low discrepancy uniform distribution: in this case the traditional Box-Muller approach and its variants would not preserve the sequence's low-discrepancy.
Definition at line 124 of file normaldistribution.hpp.
| InverseCumulativeNormal | ( | Real | average = 0.0 , |
| Real | sigma = 1.0 |
||
| ) |
Definition at line 373 of file normaldistribution.hpp.
Definition at line 149 of file normaldistribution.hpp.
Definition at line 91 of file normaldistribution.cpp.
| QL_DEPRECATED typedef Real argument_type |
auto
or decltype
instead. Deprecated in version 1.29. Definition at line 130 of file normaldistribution.hpp.
| QL_DEPRECATED typedef Real result_type |
auto
or decltype
instead. Deprecated in version 1.29. Definition at line 136 of file normaldistribution.hpp.
|
staticprivate |
Definition at line 183 of file normaldistribution.hpp.
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private |
Definition at line 185 of file normaldistribution.hpp.
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private |
Definition at line 185 of file normaldistribution.hpp.
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staticprivate |
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staticprivate |
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Definition at line 208 of file normaldistribution.hpp.


Select the times you would like to book the room and enter your email address below (the email address is used to notify you if changes occur in the booking availabilities)
{% if errorMessage %} {{ errorMessage }} Back to index Back to {{room.name}} {% endif %} {% if booking_timeslots %}


class: mainpage name: accueil # # Community dynamics analysis ## Lab-STICC (CNRS, UMR 6285) ### Cécile Bothorel, Laurent Brisson --- layout:true .footer[ # Community dynamics analysis ## [DECIDE](https://labsticc.fr/en/teams/decide) TEAM, [Lab-STICC](https://labsticc.fr/en) Laboratory (CRNS, UMR 6285) ## [Cécile Bothorel](https://www.imt-atlantique.fr/fr/personne/cecile-bothorel), [Laurent Brisson](http://www.laurent-brisson.fr/) .logo-labsticc[] ] --- name: grid-layout .header[ # Community Definition ] The term community is used here in the sense used in the field of **social network analysis**. ## Definition It is a grouping of individuals created by applying a clustering algorithm that maximizes interactions within groups and minimizes interactions between groups.
--- name: grid-layout .header[ # Analysis Process ]
Business
Tasks and
Data Scientist
Tasks
Discussion Threads
Interactions Graphs
Evolving Communities
Metrics Computation
Business Interpretation
--- name: grid-layout .header[ # Metrics and analysis levels ] ## Differents kinds of metrics
Use metrics
Context-dependant metrics
Topological metrics
Number of members, messages
Answer time, duration of threads
Toxicity levels
Topics
Static: hub dominance, clustering coefficiant
Dynamic: events, communities evolutions
## Different levels of analysis - static communities (over a given period) - evolving communities (over time) - platform --- name: grid-layout .header[ # Focus on Topological metrics ] .left-column50[ ## Community structures ### (On one period) ![Community structures](images/community_internal_structure_dark.png)
Vinh-Loc Dao. Characterizing community detection algorithms and detected modules in large-scale complex networks. Data Structures and Algorithms. Ecole nationale supérieure Mines-Télécom Atlantique, 2018.
https://tel.archives-ouvertes.fr/tel-02121358
] .right-column50[ ## Community evolution forms ### (Between two periods) ![Community evolution forms](images/evolutions_dark.png)
Palla, G., Barabási, AL. & Vicsek, T. Quantifying social group evolution. Nature 446, 664–667, 2007.
https://doi.org/10.1038/nature05670
] --- name: grid-layout .header[ # Some of our Applications ] ## Backer profiles on the Ulule crowdfunding platform Analysis of the static structure of the platform's community to detect different profiles of backers: sponsors, pre-cursors, experts, followers, etc.
Inna Lyubareva, Laurent Brisson, Cécile Bothorel, Romain Billot. Une plateforme de crowdfunding et son réseau social : L'exemple Ulule. Revue Française de Gestion, Lavoisier, 2020, Les mutations de l’accompagnement entrepreneurial, 1 (286), pp.135--151.
https://dx.doi.org/10.3166/rfg.2019.00402
## Learner profiles on the squily e-learning platform Detection of student behavioral profiles and analysis of posture changes to understand community dynamics in peer review.
Raphaël Charbey, Laurent Brisson, Cécile Bothorel, Philippe Ruffieux, Serge Garlatti, et al.. Roles in social interactions: graphlets in temporal networks applied to learning analytics. COMPLEX NETWORKS 2019 : 8th International Conference on Complex Networks and their Applications, Dec 2019, Lisbon, Portugal.
https://dx.doi.org/10.1007/978-3-030-36683-4_41
## Detection of echo chambers on YouTube media channels Dynamic analysis of community structures to detect inward-looking communities by excluding members with differing opinions.
Project funded by the French National Research Agency.
http://www.anr-pil.org/
MathJax.Hub.Configured();


PySpark uses Spark as an engine. PySpark uses Py4J to leverage Spark to submit and computes the jobs.
On the driver side, PySpark communicates with the driver on JVM by using Py4J. When pyspark.sql.SparkSession or pyspark.SparkContext is created and initialized, PySpark launches a JVM to communicate.
pyspark.sql.SparkSession
pyspark.SparkContext
On the executor side, Python workers execute and handle Python native functions or data. They are not launched if a PySpark application does not require interaction between Python workers and JVMs. They are lazily launched only when Python native functions or data have to be handled, for example, when you execute pandas UDFs or PySpark RDD APIs.
This page focuses on debugging Python side of PySpark on both driver and executor sides instead of focusing on debugging with JVM. Profiling and debugging JVM is described at Useful Developer Tools.
Note that,
If you are running locally, you can directly debug the driver side via using your IDE without the remote debug feature. Setting PySpark with IDEs is documented here.
There are many other ways of debugging PySpark applications. For example, you can remotely debug by using the open source Remote Debugger instead of using PyCharm Professional documented here.
This section describes remote debugging on both driver and executor sides within a single machine to demonstrate easily. The ways of debugging PySpark on the executor side is different from doing in the driver. Therefore, they will be demonstrated respectively. In order to debug PySpark applications on other machines, please refer to the full instructions that are specific to PyCharm, documented here.
Firstly, choose Edit Configuration… from the Run menu. It opens the Run/Debug Configurations dialog. You have to click + configuration on the toolbar, and from the list of available configurations, select Python Debug Server. Enter the name of this new configuration, for example, MyRemoteDebugger and also specify the port number, for example 12345.
+
MyRemoteDebugger
12345
pydevd-pycharm
pip install pydevd-pycharm~=<version of PyCharm on the local machine>
To debug on the driver side, your application should be able to connect to the debugging server. Copy and paste the codes with pydevd_pycharm.settrace to the top of your PySpark script. Suppose the script name is app.py:
pydevd_pycharm.settrace
app.py
echo "#======================Copy and paste from the previous dialog=========================== import pydevd_pycharm pydevd_pycharm.settrace('localhost', port=12345, stdoutToServer=True, stderrToServer=True) #======================================================================================== # Your PySpark application codes: from pyspark.sql import SparkSession spark = SparkSession.builder.getOrCreate() spark.range(10).show()" > app.py
Start to debug with your MyRemoteDebugger.
spark-submit app.py
To debug on the executor side, prepare a Python file as below in your current working directory.
echo "from pyspark import daemon, worker def remote_debug_wrapped(*args, **kwargs): #======================Copy and paste from the previous dialog=========================== import pydevd_pycharm pydevd_pycharm.settrace('localhost', port=12345, stdoutToServer=True, stderrToServer=True) #======================================================================================== worker.main(*args, **kwargs) daemon.worker_main = remote_debug_wrapped if __name__ == '__main__': daemon.manager()" > remote_debug.py
You will use this file as the Python worker in your PySpark applications by using the spark.python.daemon.module configuration. Run the pyspark shell with the configuration below:
spark.python.daemon.module
pyspark
pyspark --conf spark.python.daemon.module=remote_debug
Now you’re ready to remotely debug. Start to debug with your MyRemoteDebugger.
spark.range(10).repartition(1).rdd.map(lambda x: x).collect()
top
ps
The Python processes on the driver and executor can be checked via typical ways such as top and ps commands.
On the driver side, you can get the process id from your PySpark shell easily as below to know the process id and resources.
>>> import os; os.getpid() 18482
ps -fe 18482
UID PID PPID C STIME TTY TIME CMD 000 18482 12345 0 0:00PM ttys001 0:00.00 /.../python
To check on the executor side, you can simply grep them to figure out the process ids and relevant resources because Python workers are forked from pyspark.daemon.
grep
pyspark.daemon
ps -fe | grep pyspark.daemon
000 12345 1 0 0:00PM ttys000 0:00.00 /.../python -m pyspark.daemon 000 12345 1 0 0:00PM ttys000 0:00.00 /.../python -m pyspark.daemon 000 12345 1 0 0:00PM ttys000 0:00.00 /.../python -m pyspark.daemon 000 12345 1 0 0:00PM ttys000 0:00.00 /.../python -m pyspark.daemon ...
memory_profiler is one of the profilers that allow you to check the memory usage line by line. This method documented here only works for the driver side.
Unless you are running your driver program in another machine (e.g., YARN cluster mode), this useful tool can be used to debug the memory usage on driver side easily. Suppose your PySpark script name is profile_memory.py. You can profile it as below.
profile_memory.py
echo "from pyspark.sql import SparkSession #===Your function should be decorated with @profile=== from memory_profiler import profile @profile #===================================================== def my_func(): session = SparkSession.builder.getOrCreate() df = session.range(10000) return df.collect() if __name__ == '__main__': my_func()" > profile_memory.py
python -m memory_profiler profile_memory.py
Filename: profile_memory.py Line # Mem usage Increment Line Contents ================================================ ... 6 def my_func(): 7 51.5 MiB 0.6 MiB session = SparkSession.builder.getOrCreate() 8 51.5 MiB 0.0 MiB df = session.range(10000) 9 54.4 MiB 2.8 MiB return df.collect()
Python Profilers are useful built-in features in Python itself. These provide deterministic profiling of Python programs with a lot of useful statistics. This section describes how to use it on both driver and executor sides in order to identify expensive or hot code paths.
To use this on driver side, you can use it as you would do for regular Python programs because PySpark on driver side is a regular Python process unless you are running your driver program in another machine (e.g., YARN cluster mode).
echo "from pyspark.sql import SparkSession spark = SparkSession.builder.getOrCreate() spark.range(10).show()" > app.py
python -m cProfile app.py
... 129215 function calls (125446 primitive calls) in 5.926 seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1198/405 0.001 0.000 0.083 0.000 <frozen importlib._bootstrap>:1009(_handle_fromlist) 561 0.001 0.000 0.001 0.000 <frozen importlib._bootstrap>:103(release) 276 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:143(__init__) 276 0.000 0.000 0.002 0.000 <frozen importlib._bootstrap>:147(__enter__) ...
To use this on executor side, PySpark provides remote Python Profilers for executor side, which can be enabled by setting spark.python.profile configuration to true.
spark.python.profile
true
pyspark --conf spark.python.profile=true
>>> rdd = sc.parallelize(range(100)).map(str) >>> rdd.count() 100 >>> sc.show_profiles() ============================================================ Profile of RDD<id=1> ============================================================ 728 function calls (692 primitive calls) in 0.004 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 12 0.001 0.000 0.001 0.000 serializers.py:210(load_stream) 12 0.000 0.000 0.000 0.000 {built-in method _pickle.dumps} 12 0.000 0.000 0.001 0.000 serializers.py:252(dump_stream) 12 0.000 0.000 0.001 0.000 context.py:506(f) ...
To use this on Python/Pandas UDFs, PySpark provides remote Python Profilers for Python/Pandas UDFs, which can be enabled by setting spark.python.profile configuration to true.
>>> from pyspark.sql.functions import pandas_udf >>> df = spark.range(10) >>> @pandas_udf("long") ... def add1(x): ... return x + 1 ... >>> added = df.select(add1("id")) >>> added.show() +--------+ |add1(id)| +--------+ ... +--------+ >>> sc.show_profiles() ============================================================ Profile of UDF<id=2> ============================================================ 2300 function calls (2270 primitive calls) in 0.006 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 10 0.001 0.000 0.005 0.001 series.py:5515(_arith_method) 10 0.001 0.000 0.001 0.000 _ufunc_config.py:425(__init__) 10 0.000 0.000 0.000 0.000 {built-in method _operator.add} 10 0.000 0.000 0.002 0.000 series.py:315(__init__) ...
The UDF IDs can be seen in the query plan, for example, add1(...)#2L in ArrowEvalPython below.
add1(...)#2L
ArrowEvalPython
>>> added.explain() == Physical Plan == *(2) Project [pythonUDF0#11L AS add1(id)#3L] +- ArrowEvalPython [add1(id#0L)#2L], [pythonUDF0#11L], 200 +- *(1) Range (0, 10, step=1, splits=16)
This feature is not supported with registered UDFs.
AnalysisException
AnalysisException is raised when failing to analyze a SQL query plan.
Example:
>>> df = spark.range(1) >>> df['bad_key'] Traceback (most recent call last): ... pyspark.sql.utils.AnalysisException: Cannot resolve column name "bad_key" among (id)
Solution:
>>> df['id'] Column<'id'>
ParseException
ParseException is raised when failing to parse a SQL command.
>>> spark.sql("select * 1") Traceback (most recent call last): ... pyspark.sql.utils.ParseException: Syntax error at or near '1': extra input '1'(line 1, pos 9) == SQL == select * 1 ---------^^^
>>> spark.sql("select *") DataFrame[]
IllegalArgumentException
IllegalArgumentException is raised when passing an illegal or inappropriate argument.
>>> spark.range(1).sample(-1.0) Traceback (most recent call last): ... pyspark.sql.utils.IllegalArgumentException: requirement failed: Sampling fraction (-1.0) must be on interval [0, 1] without replacement
>>> spark.range(1).sample(1.0) DataFrame[id: bigint]
PythonException
PythonException is thrown from Python workers.
You can see the type of exception that was thrown from the Python worker and its stack trace, as TypeError below.
TypeError
>>> from pyspark.sql.functions import udf >>> def f(x): ... return F.abs(x) ... >>> spark.range(-1, 1).withColumn("abs", udf(f)("id")).collect() 22/04/12 14:52:31 ERROR Executor: Exception in task 7.0 in stage 37.0 (TID 232) org.apache.spark.api.python.PythonException: Traceback (most recent call last): ... TypeError: Invalid argument, not a string or column: -1 of type <class 'int'>. For column literals, use 'lit', 'array', 'struct' or 'create_map' function.
>>> def f(x): ... return abs(x) ... >>> spark.range(-1, 1).withColumn("abs", udf(f)("id")).collect() [Row(id=-1, abs='1'), Row(id=0, abs='0')]
StreamingQueryException
StreamingQueryException is raised when failing a StreamingQuery. Most often, it is thrown from Python workers, that wrap it as a PythonException.
>>> sdf = spark.readStream.format("text").load("python/test_support/sql/streaming") >>> from pyspark.sql.functions import col, udf >>> bad_udf = udf(lambda x: 1 / 0) >>> (sdf.select(bad_udf(col("value"))).writeStream.format("memory").queryName("q1").start()).processAllAvailable() Traceback (most recent call last): ... org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "<stdin>", line 1, in <lambda> ZeroDivisionError: division by zero ... pyspark.sql.utils.StreamingQueryException: Query q1 [id = ced5797c-74e2-4079-825b-f3316b327c7d, runId = 65bacaf3-9d51-476a-80ce-0ac388d4906a] terminated with exception: Writing job aborted
Fix the StreamingQuery and re-execute the workflow.
SparkUpgradeException
SparkUpgradeException is thrown because of Spark upgrade.
>>> from pyspark.sql.functions import to_date, unix_timestamp, from_unixtime >>> df = spark.createDataFrame([("2014-31-12",)], ["date_str"]) >>> df2 = df.select("date_str", to_date(from_unixtime(unix_timestamp("date_str", "yyyy-dd-aa")))) >>> df2.collect() Traceback (most recent call last): ... pyspark.sql.utils.SparkUpgradeException: You may get a different result due to the upgrading to Spark >= 3.0: Fail to recognize 'yyyy-dd-aa' pattern in the DateTimeFormatter. 1) You can set spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before Spark 3.0. 2) You can form a valid datetime pattern with the guide from https://spark.apache.org/docs/latest/sql-ref-datetime-pattern.html
>>> spark.conf.set("spark.sql.legacy.timeParserPolicy", "LEGACY") >>> df2 = df.select("date_str", to_date(from_unixtime(unix_timestamp("date_str", "yyyy-dd-aa")))) >>> df2.collect() [Row(date_str='2014-31-12', to_date(from_unixtime(unix_timestamp(date_str, yyyy-dd-aa), yyyy-MM-dd HH:mm:ss))=None)]
There are specific common exceptions / errors in pandas API on Spark.
ValueError: Cannot combine the series or dataframe because it comes from a different dataframe
Operations involving more than one series or dataframes raises a ValueError if compute.ops_on_diff_frames is disabled (disabled by default). Such operations may be expensive due to joining of underlying Spark frames. So users should be aware of the cost and enable that flag only when necessary.
ValueError
compute.ops_on_diff_frames
Exception:
>>> ps.Series([1, 2]) + ps.Series([3, 4]) Traceback (most recent call last): ... ValueError: Cannot combine the series or dataframe because it comes from a different dataframe. In order to allow this operation, enable 'compute.ops_on_diff_frames' option.
>>> with ps.option_context('compute.ops_on_diff_frames', True): ... ps.Series([1, 2]) + ps.Series([3, 4]) ... 0 4 1 6 dtype: int64
RuntimeError: Result vector from pandas_udf was not the required length
>>> def f(x) -> ps.Series[np.int32]: ... return x[:-1] ... >>> ps.DataFrame({"x":[1, 2], "y":[3, 4]}).transform(f) 22/04/12 13:46:39 ERROR Executor: Exception in task 2.0 in stage 16.0 (TID 88) org.apache.spark.api.python.PythonException: Traceback (most recent call last): ... RuntimeError: Result vector from pandas_udf was not the required length: expected 1, got 0
>>> def f(x) -> ps.Series[np.int32]: ... return x ... >>> ps.DataFrame({"x":[1, 2], "y":[3, 4]}).transform(f) x y 0 1 3 1 2 4
Py4JJavaError
Py4JJavaError is raised when an exception occurs in the Java client code. You can see the type of exception that was thrown on the Java side and its stack trace, as java.lang.NullPointerException below.
java.lang.NullPointerException
>>> spark.sparkContext._jvm.java.lang.String(None) Traceback (most recent call last): ... py4j.protocol.Py4JJavaError: An error occurred while calling None.java.lang.String. : java.lang.NullPointerException ..
>>> spark.sparkContext._jvm.java.lang.String("x") 'x'
Py4JError
Py4JError is raised when any other error occurs such as when the Python client program tries to access an object that no longer exists on the Java side.
>>> from pyspark.ml.linalg import Vectors >>> from pyspark.ml.regression import LinearRegression >>> df = spark.createDataFrame( ... [(1.0, 2.0, Vectors.dense(1.0)), (0.0, 2.0, Vectors.sparse(1, [], []))], ... ["label", "weight", "features"], ... ) >>> lr = LinearRegression( ... maxIter=1, regParam=0.0, solver="normal", weightCol="weight", fitIntercept=False ... ) >>> model = lr.fit(df) >>> model LinearRegressionModel: uid=LinearRegression_eb7bc1d4bf25, numFeatures=1 >>> model.__del__() >>> model Traceback (most recent call last): ... py4j.protocol.Py4JError: An error occurred while calling o531.toString. Trace: py4j.Py4JException: Target Object ID does not exist for this gateway :o531 ...
Access an object that exists on the Java side.
Py4JNetworkError
Py4JNetworkError is raised when a problem occurs during network transfer (e.g., connection lost). In this case, we shall debug the network and rebuild the connection.
There are Spark configurations to control stack traces:
spark.sql.execution.pyspark.udf.simplifiedTraceback.enabled is true by default to simplify traceback from Python UDFs.
spark.sql.execution.pyspark.udf.simplifiedTraceback.enabled
spark.sql.pyspark.jvmStacktrace.enabled is false by default to hide JVM stacktrace and to show a Python-friendly exception only.
spark.sql.pyspark.jvmStacktrace.enabled
Spark configurations above are independent from log level settings. Control log levels through pyspark.SparkContext.setLogLevel().
pyspark.SparkContext.setLogLevel()


This is test post 1
The title is This is test post 1 and this is an example blog post number 1.
newer post
Some comments belong here


The value of "title" parameter in query string is "' OR 'a'='a" Code: qry = "SELECT * FROM books_book WHERE title=%s" book = Book.objects.raw(qry, [title]) Now %s will automatically escape
Code: qry = "SELECT * FROM books_book WHERE title=%s" book = Book.objects.raw(qry, [title])
Click here to see how SQL Injection works
Click here to see how SQL Injection works HTML file


class RefreshResult
Result object of a call to OnlineRepository.refresh. Understand if a refresh call was successful, not successful, or skipped for some reason.
enum class SkippedReason
If a OnlineRepository.refresh task was skipped, compare the skipped property with the enum cases below to determine why the refresh task was skipped. |
|
object Testing
Used for testing purposes to create instances of OnlineCacheState. |
val failedError: Throwable? |
|
val skipped: SkippedReason? |
|
val successful: Boolean |
fun didFail(): Boolean |
|
fun didSkip(): Boolean |
|
fun didSucceed(): Boolean |
|
fun equals(other: Any?): Boolean |
|
fun hashCode(): Int |


My projects
Sysadmin
- Sysadmin stuff: as a sysadmin, I've a collection of scripts of my own, written either in Bash or Python and that I share on one of my repos.
Python
I have a couple of Python pet-projects hosted on GitHub. The following, are the most significant ones to me:
- Tiny LDAP Manager: a CLI utility that's aimed to ease the task of performing different LDAP operations, such as adding, deleting or changing the attributes of an LDAP entry. It also allows you to add or delete LDAP entries as well.
- LDAP Attributes Selector: a CLI utility that allows you to get a CSV formatted list, based on a custom set of LDAP attributes.
- SSH Commander: it allows you to execute commands on several remote hosts, using the SSH protocol!.
- Zimbra Permissions Inspector: a CLI tool to query sending permissions on a Zimbra server. You can retrieve sending permissions for a particular Zimbra Distribution List (ZDL) or get a complete list of "Send as" permissions.
- Quackmyip: a small CLI utility to keep your public IP address updated with the DuckDNS service!.
Please, see the link on each project for more details.
Web stuff
Even though I know enough HTML, CSS and Javascript to build some stuff, I'm certainly not an expert web programmer nor a designer. Sometimes, I just simply enjoy fiddling around some web technologies (Python microframeworks, websockets, SocketIO, SSE, etc)
If you take a look at some of my repos, you'll see that I've played around with the Python Bottle microframework and some websockets stuff.
To sum up, I don't have any serious web related stuff yet and I'm not sure if I ever will!.
Electronics
As part of my incursion in electronics, I built a small robot based on the NodeMCU board, using MicroPython on it and programmed a small web interface to control the former!. Project details can be found here!
I also like to fiddle around with Raspberry Pis!. Related projects of mine, can be found here!.


What do you want to optimize for?
Not important
Important
Not important
Important
Not important
Important
Helper tool to pick a Google Cloud region, taking into accout carbon footprint (before offset), price and latency.


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Home
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Run History
Manager Suppliers
Past Runs
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Accessibility E2E Tests
Note: Spartacus 2.x is no longer maintained. Please upgrade to the latest version.
Accessibility in Spartacus has its own set of end-to-end tests, which are located in projects/storefrontapp-e2e-cypress/cypress/integration/accessibility/tabbing-order.e2e-spec.ts
.
These include tests that require a user to be logged in (for the My Account pages and the cart, for example), as well as tests that do not require a user to be logged in (for the Home page and Login page, for example).
Currently, the tests cover tabbing through the application. For every new feature, a new test should be written manually that checks how the tabbing is intended to work. If some aspect of the tabbing does not work properly (for example, the tabbing order is not as intended, or an interactable element cannot be reached by tabbing), the test should fail.
To run a new test that you have added to tabbing-order.e2e-spec.ts
, choose the tabbing-order
test when you run Cypress.
Implementing a New A11y E2E Test
You can create a new a11y e2e test by updating the existing set of tests, as described in the following procedure.
-
Add a a new property to the config object in
projects/storefrontapp-e2e-cypress/cypress/helpers/accessibility/tabbing-order.config.ts
.The name should be short and descriptive. The following is an example:
login: [ { value: 'userId', type: TabbingOrderTypes.FORM_FIELD }, { value: 'password', type: TabbingOrderTypes.FORM_FIELD }, { value: 'Forgot password?', type: TabbingOrderTypes.LINK }, { value: 'Sign In', type: TabbingOrderTypes.BUTTON }, { value: 'Register', type: TabbingOrderTypes.BUTTON }, ]
The following are some details about the above example:
-
The
login
is of typeTabElement[]
. -
The
type
is aTabbingOrderTypes
enum, which supports many types of elements. You can see all the supported types by looking up the definition of theTabbingOrderTypes
enum in the Spartacus source code.
-
-
Add a new helper file to
projects/storefrontapp-e2e-cypress/cypress/helpers/accessibility/tabbing-order/
.The following is an example of the
login.ts
helper file:import { verifyTabbingOrder } from '../tabbing-order'; import { fillLoginForm } from '../../auth-forms'; import { user } from '../../../sample-data/checkout-flow'; import { TabElement } from '../tabbing-order.model'; const containerSelector = '.LoginPageTemplate'; export function loginTabbingOrder( config: TabElement[], prefillForm: boolean = false ) { cy.visit('/login'); if (prefillForm) { const { email: username, password } = user; fillLoginForm({ username, password }); } verifyTabbingOrder(containerSelector, config); }
Some pages or views might require additional steps, and the helper file may be bigger or more complex than the example shown above. You can see other examples by looking at existing helper files in
projects/storefrontapp-e2e-cypress/cypress/helpers/accessibility/tabbing-order/
.The following are some details about the above example:
- With
const containerSelector
, you create a variable for holding your feature using a CSS-like selector. - Exported functions, such as the
loginTabbingOrder
function in this example, should always have theTabbingOrder
suffix, and should always takeconfig
as a parameter. cy.visit
is an example of Cyprus functionality. In this example, it tells Cyprus to access a page where your feature is located.- Your exported function should always use the predefined
verifyTabbingOrder(containerSelector, config)
function.
- With
-
In
projects/storefrontapp-e2e-cypress/cypress/integration/accessibility/tabbing-order.e2e-spec.ts
, import theTabbingOrder
function from the helper file you created in the previous step.The following is an example:
import { loginTabbingOrder } from '../../helpers/accessibility/tabbing-order/login';
-
In the same file (
tabbing-order.e2e-spec.ts
), add the test.The following is an example:
context('Login page', () => { it('should allow to navigate with tab key (empty form)', () => { loginTabbingOrder(config.login); }); it('should allow to navigate with tab key (filled out form)', () => { loginTabbingOrder(config.login, true); }); });
The following are some details about the above example:
- The
context
should point to the page you want to test. - The string
'should allow to navigate with tab key'
is used in every test and should be included in all new tests. - The
loginTabbingOrder
is the function you created in yourlogin.ts
helper file, and(config.login)
refers to thelogin
property you added to the config object inprojects/storefrontapp-e2e-cypress/cypress/helpers/accessibility/tabbing-order.config.ts
(in step 1 of this procedure).
- The
Group Skipping
If your feature uses a unique route and also uses group skipping to improve the user experience on the keyboard, you need to implement a test configuration for this aspect of your feature.
The approach is similar to how you verify the tabbing order. In projects/storefrontapp-e2e-cypress/cypress/helpers/accessibility/group-skipping/group-skipping.config.ts
, you add the GroupSkippingPageConfig
to the relevant GroupSkippingConfig
, as shown in the following example:
export interface GroupSkippingPageConfig {
pageUrl: string;
expectedSkipperCount: number;
}
export interface GroupSkippingConfig {
[name: string]: GroupSkippingPageConfig;
}
export const groupSkippingConfigNotLoggedIn: GroupSkippingConfig = {
home: { pageUrl: '/', expectedSkipperCount: 3 },
login: { pageUrl: '/login', expectedSkipperCount: 3 },
register: { pageUrl: '/login/register', expectedSkipperCount: 3 },
/* ... */
};
The following are some details about the above example:
- The
pageUrl
is the route of the page where your feature is implemented. - The
expectedSkipperCount
is the number of skip links expected to be generated on the page.
Fixes
If your tests fail, create a new GitHub issue with details about the error, and use the feature/accessibility
label.


Order Id:{{viewOrder._id}} |
Order Name:{{viewOrder.name}} |
Product Name:{{viewOrder.productName}} |
Description:{{viewOrder.productDescription}} |
Order Cost:Rs.{{viewOrder.orderValue}}/- |
Quantity:{{viewOrder.quantity}} |
Order Complete:{{viewOrder.complete}} |
Received Payment:{{viewOrder.receivedPayment}} |
Delivery Address: |
Comments: |


מחשבון
מחשבון הצמדה למדד
מחשבון NOI
four
five
six
Welcome!
This changing effect is done by ...
... having
<div>
s with
id
s ...
... that have the style
display: none
and the style
:target { display: block; }
so that these messages appear when there is a hash tag like
#three
(look at the address bar!)
Look at the source of this page ...
... to see how the circular menu works.
By Shaquin Trifonoff


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Asking good questions is a skill everyone needs to have. In the tech world, a good question has been attempted to answer for at least 30 minutes, googled, documentation read, and then fully formed with relevant information when posed. Good questions are appreciated on Stackoverflow, in DBCs Google+ communities and in person. Even the most basic question can be a good question, if posed correctly.
While good questions are appreciated, bad questions are not. The statement "There's no such thing as a bad question" assumes the person asking has put effort into their question. While beginner questions are appreciated, beginner questions asked before any research or effort to answer the questions is attempted, are not appreciated. I've seen this on Stackoverflow questions closed because they are duplicates of other postings or in questions and rants about how the question is answered in the language's documentation.
If the person answering the question can google it, it was a lazy question.
If you google your question, still don't understand the answer found and fully communicate your question, the information found and the parts still needing an explanation, it's a good question.
So ask your question, just be respectful of the people answering and make it a good question. At some point in time, a beginner learns enough to start answering back and that's when they really start to value the good question.


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Source code for mbmp.server.util
## Python implementation of MBMA (Van den Bosch & Daelemans 1999)
## Copyright (C) 2011 Institute for Dutch Lexicology (INL)
## Author: Folgert Karsdorp, INL<EMAIL_ADDRESS>## URL: <http://www.inl.nl/>
## For licence information, see LICENCE.TXT
import os
import tempfile
import socket
import subprocess
[docs]def pid_file(server):
"""
Return the path to the file holding the pid for a given instance
of TimblServer.
Args:
- server: an instance of Timblserver that needs to be started
Returns:
str -- the path to the file containing the pid for this server.
"""
return os.path.join(
tempfile.gettempdir(),
'mbmp.%s_%s_%s.pid' % (server.classifier, server.port, server.host))
[docs]def remove_pid_file(server):
"""
Remove the file holding the pid for a given instance of TimblServer.
Args:
- server: an instance of Timblserver that needs to be started
Returns:
boolean
"""
try:
os.remove(pid_file(server))
except OSError:
pass
[docs]def free_port(server):
"""
Utility function to check whether a given port is free.
Args:
- server: an instance of Timblserver that needs to be started
Returns:
boolean
"""
try:
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((server.host, server.port))
s.close()
return False
except socket.error, e:
return True
[docs]def server_in_use(serverinstance):
"""
Check if there are any other connections with the timblserver. If so,
return True, else return False.
Args:
- server: an instance of Timblserver that needs to be started
Returns:
boolean
"""
command = 'netstat -an | grep :%s' % serverinstance.port
p = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE,
stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
close_fds=True)
# count how many established connections there are
established = sum(1 for line in p.stdout if 'ESTABLISHED' in line)
if established > 1:
return True
return False


Enforcement Directorate grills P. Chidambaram in INX Media case
New Delhi: A team of Enforcement Directorate (ED) officials on Friday visited Tihar Jail here to interrogate former Finance Minister and senior Congress leader P. Chidambaram in connection with INX Media money laundering case.
A senior Enforcement Directorate official said that a team has gone there to question Chidambaram and also to confront him with some documents.
The financial probe agency’s action comes a day after a Special CBI Court allowed ED to interrogate Chidambaram for two days in connection with the money laundering case in INX Media deal.
Special CBI Judge Ajay Kumar Kuhar allowed the agency to confront Chidambaram on November 22 and 23 during office hours. Chidambaram was arrested on August 21 by the CBI but was granted bail later. The ED later arrested Chidambaram in the INX media money laundering case. (IANS)
Also Read: Delhi court allows ED to quiz P. Chidambaram in Tihar
Also Watch: AGP leadership has not been vocal against the CAB: Prafulla Kumar Mahanta


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Winter Weather Advisory issued November 18 at 3:08AM EST until November 18 at 11:00AM EST by NWS Binghamton NY
Winter Weather Advisory: Northern Wayne, Otsego, Southern Wayne and 3 more areas until 11:00 AM
* WHAT…Pockets of freezing rain or freezing drizzle is
expected. Total ice accumulations of a light glaze.
* WHERE…In Pennsylvania, Northern Wayne, Pike and Southern
Wayne counties. In New York, Otsego, Delaware and Sullivan
counties.
* WHEN…From 4 AM to 11 AM EST Monday.
* IMPACTS…Very slippery sidewalks, roads and bridges are
possible. The hazardous conditions could impact the morning
commute.
Slow down and use caution while traveling. Prepare for possible
power outages.
The latest road conditions for the state you are calling from can
be obtained by calling 5 1 1.
The Pennsylvania Department of Transportation and Pennsylvania
Turnpike Commission remind motorist to adjust speeds based on
driving conditions as winter weather impacts Pennsylvania
roadways. Visit www.511pa.com for the latest travel, roadways,
and traffic conditions.


So this is one of those really cool things that passed through my mind when I was a kid. Luckily, it is a dream I can remove from the checklist! So I appeared on a documentary on biological anthropology, more specifically about a recently discovered archaeological skeletal collection from Lagos, Portugal. This collection is unique, worldwide, in how much it can tell us about slavery related to the Age of Discovery.
Die Sklaven von Lagos
The documentary is split into 6 episodes:
The skeletons from Algarve
Bioarchaeology: working with the bones
History meets CSI
What the teeth tell us
A piece of history for the nameless
The general interview with Maria Teresa Ferreira
All very interesting and available in german and english, my 15 seconds of fame are mostly on the fifth one, but best is to watch all of them!
I have finally finished a full tree of knowledge in Duolingo. This means there are not any new games for me to try, with this language in specific, in the platform. Yet, Danish sure is a difficult language, while I can somewhat read it now, it’s still really hard to understand by listening. I’ve watched a few series and listened to a few audiobooks to improve that, yet…
Well, just wanted to share this little achievement. By the way, you can add me as your friend and check my general scores in all languages:
Today I was trying to update myself on the state of the art of deep learning, a paradigm of machine learning that is exploding in popularity. In very few words, it grows artificial neural networks with very deep architectures (i.e. hundreds of hidden layers, thousands or millions of neurons) in an attempt to simulate or even beat human performance in a variety of tasks, for example, recognizing objects in pictures. And somehow I ended up watching this video:
It is a work from the Evolving AI Lab, with Jeff Clune giving the lecture. But as he notices, most of the work presented, was done by his student, Anh Nguyen, who has some awesome publications in the field of deep learning.
Now the coolest thing, is that near the end of the video, Clune starts talking about how deep learning can be used in a generative sense. For example, you can give hundreds of pictures of a flower or a bus to your model, and then use your model to create new, never seen before, pictures of what the model understands as a flower, or a bus. Then he shows some images of the results, and its very interesting.
Now the crazy thing. When I think about machine learning in general is hard not to see connections on how these abstract algorithms work and how we humans - a big-brain ape - think. With most algorithms, it is kind of a stretch really! Ultimately, it is hard to conceive of concepts like creativity, coming from the side of computers. But deep neural networks are a really strange metaphor for “understanding” in its general sense, and if you go too deep in the rabbit hole, the experience of thinking about all this stuff gets a bit psychedelic.
What showed up in the video you can see here: evolvingai.org/synthesizing. Near the bottom there are some examples with ladybugs, cardoon flowers, fountains and other objects. I was not looking specifically at anything, but for a few seconds I got this very paranoid feeling of “something is really wrong!”. It took me a few minutes to realize what it was. But then it hit me… there was a picture taken by me there!
So it seems I had this picture on my old Flickr account. And somehow, as they explain “we show the top 9 validation set images that highest activate a given neuron (left) and 9 synthetic images produced by our method (right)”, this makes my picture a very ladybug-ish picture to “ladybug neurons” that were trained with thousands of ladybug pictures, or so I guess. That’s so strange and hard to gasp.
Around the end of last year I wrote a research proposal for a DPhil in Anthropology at Oxford University. Last week I was delighted to get an offer letter from their School of Anthropology. My research will be in the area of Geospatial Paleoanthropology, meaning using remote sensing to discover potential hot spots of fossil human ancestors. Plus, I got an excellent supporting team as well! Professor Susana Carvalho as my supervisor and Professor Robert Anemone and Professor Eugénia Cunha as my co-supervisors.
This week the official results of the Fundação para a Ciência e a Tecnologia grants also come out. For me, it was positive! Which was awesome, unexpected good news. This scholarship will help me pay my studies and my life for the next 3 or 4 years in England.
Recently I launched in collaboration with a few friends the jest.pt website. JEST promotes a startup-like environment for young academics, mainly from the Life Sciences Department at the University of Coimbra. We are a junior association that develops data science solutions in bioinformatics, forensic, and health sciences. We are committed to learn by doing and as a team.
Our first project is R Attack, a workshop about the R Statistical Language that we will be giving during 4 days. You can read more about it here: R Attack. It goes from completely beginner’s material to very advanced topics, such as optimization of written functions. However, we will try to keep things simple, so that all the course is accessible even for people with no background whatsoever in programming.
DAY 1 - R for dummies
Intro to R and R Studio
Importing data
Basic operations and loops
Descriptive and Inferential stats
DAY 2 - R for data nerds
From raw data to tidy data (tidyr and dplyr)
Exploring: base plot vs. ggplot2
Intro to Machine Learning with caret
Open data, online collaboration and sharing
DAY 3 - R for hackers
Reporting with R Markdown
Intro to Shiny: Web-app development
Interactive plotting
Intro to R efficiency
DAY 4 - R for programmers
The apply family
Function writing
Advanced R programming
Data science workflow
There will be a different speaker each day and I will be responsible for the 3rd day. My current role in JEST is as head of design, webmaster and workshop speaker.
Don’t forget to follow us on facebook to keep up with the news!


|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object GameObject.GameObject
public class GameObject
Parent class to every object present in the game. Defines fundamental attributes present in every object that is rendered on the game grid. Namely, position on the grid, visibility, the image object associated, and the dimensions of the object.
| Field Summary | |
|---|---|
protected int |
height
|
protected java.awt.Image |
image
|
protected java.lang.String |
imagePath
|
protected int |
posX
|
protected int |
posY
|
protected int |
previousX
|
protected int |
previousY
|
protected boolean |
visible
|
protected int |
width
|
| Constructor Summary | |
|---|---|
GameObject()
|
| Method Summary | |
|---|---|
void |
draw(java.awt.Graphics2D g)
Draws the GameObject instance on the Game Grid. |
java.awt.Rectangle |
getBounds()
Get the bounds of the image that represents the Game Object. |
int |
getHeight()
Returns the height of the Image used to represent the Game Object on the game grid. |
java.awt.Image |
getImage()
Get the Image object used to contain the image associated with the Game Object. |
Coordinate |
getPositionAsCoordinate()
Get the position of the object as an instance of Coordinate |
int |
getPosX()
Get the x position of the Game Object on the grid. |
int |
getPosY()
Get the y position of the Game Object on the grid. |
int |
getPreviousX()
Get the previous x coordinate where the object was rendered in the last frame. |
int |
getPreviousY()
Get the previous y coordinate where the object was rendered in the last frame. |
int |
getWidth()
Returns the width of the Image used to represent the Game Object on the game grid. |
boolean |
isVisible()
Gets the visibility status of the Game Object. |
void |
setHeight(int height)
|
void |
setImage(java.awt.Image image)
Set the Image object that will be rendered when the object is drawn. |
void |
setPosX(int posX)
Set the x position of the object on the grid. |
void |
setPosY(int posY)
Set the y position of the object on the grid. |
void |
setPreviousX(int previousX)
Set the previous x coordinate where the object was rendered in the last frame. |
void |
setPreviousY(int previousY)
Set the previous y coordinate where the object was rendered in the last frame. |
void |
setVisible(boolean visible)
Set the visibility status of the Game Object. |
void |
setWidth(int width)
|
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
protected java.lang.String imagePath
protected int posX
protected int posY
protected int previousX
protected int previousY
protected int width
protected int height
protected transient java.awt.Image image
protected boolean visible
| Constructor Detail |
|---|
public GameObject()
| Method Detail |
|---|
public void draw(java.awt.Graphics2D g)
g
- Graphics object corresponding to the JPanel where the game play state is rendered.public java.awt.Rectangle getBounds()
public int getPosX()
public void setPosX(int posX)
posX
- An integer representing the x position where the object will be rendered on the Game Grid.public int getPosY()
public void setPosY(int posY)
posY
- An integer representing the y position where the object will be rendered on the Game Grid.public int getPreviousX()
public void setPreviousX(int previousX)
previousX
- The previous x coordinate where the object was rendered in the previous frame.public int getPreviousY()
public void setPreviousY(int previousY)
previousY
- The previous y coordinate where the object was rendered in the previous frame.public int getWidth()
public void setWidth(int width)
public int getHeight()
public void setHeight(int height)
public java.awt.Image getImage()
public void setImage(java.awt.Image image)
image
- The Image object used to represent the GameObject on the Game Grid.public boolean isVisible()
public void setVisible(boolean visible)
visible
- A boolean representing whether the Game Object is visible on the grid or not.public Coordinate getPositionAsCoordinate()
|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


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| PREV NEXT | FRAMES NO FRAMES |
| Packages that use Piece | |
|---|---|
| javalabra.chess.core.impl | |
| javalabra.chess.core.impl.move | |
| javalabra.chess.core.impl.state | |
| javalabra.chess.domain |
| Uses of Piece in javalabra.chess.core.impl |
|---|
| Constructors in javalabra.chess.core.impl with parameters of type Piece | |
|---|---|
MoveCollectionBuilder(Piece piece,
GameContext context,
StateAnalyzer analyzer)
Constructs builder object for specified piece in given context. |
| Uses of Piece in javalabra.chess.core.impl.move |
|---|
| Fields in javalabra.chess.core.impl.move declared as Piece | |
|---|---|
protected Piece |
CaptureMove.captured
|
protected Piece |
AbstractMove.piece
Main piece of the move. |
| Methods in javalabra.chess.core.impl.move that return Piece | |
|---|---|
Piece |
CaptureMove.getCaptured()
|
Piece |
AbstractMove.getPiece()
|
| Constructors in javalabra.chess.core.impl.move with parameters of type Piece | |
|---|---|
AbstractMove(Piece piece,
Square source,
Square destination)
|
|
CaptureMove(Piece piece,
Square source,
Square destination,
Piece captured)
|
|
NormalMove(Piece piece,
Square source,
Square destination)
|
| Uses of Piece in javalabra.chess.core.impl.state |
|---|
| Constructors in javalabra.chess.core.impl.state with parameters of type Piece | |
|---|---|
SelectMoveState(Piece piece,
java.util.Collection<Move> moves)
|
| Uses of Piece in javalabra.chess.domain |
|---|
| Subclasses of Piece in javalabra.chess.domain | |
|---|---|
class |
Bishop
Represents bishop. |
class |
King
Represents king. |
class |
Knight
Represents knight. |
class |
Pawn
Represents pawn. |
class |
Queen
Represents queen. |
class |
Rook
Represents rook. |
| Methods in javalabra.chess.domain that return Piece | |
|---|---|
Piece |
Square.getPiece()
|
| Methods in javalabra.chess.domain that return types with arguments of type Piece | |
|---|---|
java.util.List<Piece> |
Player.getPieces()
|
java.util.Collection<Piece> |
Board.getPieces(Color color)
Returns all the pieces on the board. |
| Methods in javalabra.chess.domain with parameters of type Piece | |
|---|---|
Square |
Board.getPiecePosition(Piece piece)
Finds concrete piece's position on board. |
void |
Square.setPiece(Piece piece)
|
void |
Board.setPiecePosition(Piece piece,
Square square)
Deprecated. |
void |
Board.setSquare(int column,
int row,
Piece piece)
Sets piece on square specified by coordinates, null marks square as empty. |
void |
Board.setSquare(Square square,
Piece piece)
Sets piece on specified square, null marks square as empty. |
|
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| PREV NEXT | FRAMES NO FRAMES |


{% extends 'base.html' %} {% block title %}Donations{% endblock %} {% block content %}
Since 1994, ${{ totals[0][0]|format_large_number }} has been donated to political campaigns in the State of Illinois. Browse the {{ totals[0][1] | format_number }} individual donations below.
| {% if donation.first_name %}{{ donation.first_name }}{% endif %} {{ donation.last_name }} | donated {{ donation.amount|format_money }} to | {{ donation.committee.name }} | on {{ donation.received_date.strftime('%b %d, %Y') }} |


| MPI_WIN_CREATE_ERRHANDLER(function, errhandler) | |
| IN function | user defined error handling procedure (function) |
| OUT errhandler | MPI error handler (handle) |
2.2 int MPI_Win_create_errhandler(MPI_Win_errhandler_function *function, MPI_Errhandler *errhandler)
2.2 { static MPI::Errhandler MPI::Win::Create_errhandler(MPI::Win::Errhandler_function* function) (binding deprecated, see Section Deprecated since MPI-2.2
) }
Creates an error handler that can be attached to a window object.
The user routine should be, in C, a
function of type
MPI_Win_errhandler_function
which is defined as
2.2 typedef void MPI_Win_errhandler_function(MPI_Win *, int *, ...);
In Fortran, the user routine should be of the form:
2.2 SUBROUTINE WIN_ERRHANDLER_FUNCTION(WIN, ERROR_CODE)
In C++, the user routine should be of the form:
2.2 { typedef void MPI::Win::Errhandler_function(MPI::Win &, int *, ... ); (binding deprecated, see Section Deprecated since MPI-2.2
) }
int MPI_Win_set_errhandler(MPI_Win win, MPI_Errhandler errhandler)
MPI_WIN_SET_ERRHANDLER(WIN, ERRHANDLER, IERROR)
{ void MPI::Win::Set_errhandler(const MPI::Errhandler& errhandler) (binding deprecated, see Section Deprecated since MPI-2.2
) }
Attaches a new error handler to a window. The error handler must be
either a predefined error
handler, or an error handler created by a call to
MPI_WIN_CREATE_ERRHANDLER.
int MPI_Win_get_errhandler(MPI_Win win, MPI_Errhandler *errhandler)
MPI_WIN_GET_ERRHANDLER(WIN, ERRHANDLER, IERROR)
{ MPI::Errhandler MPI::Win::Get_errhandler() const (binding deprecated, see Section Deprecated since MPI-2.2
) }
Retrieves the error handler currently associated with a window.
MPI_WIN_CREATE_ERRHANDLER(FUNCTION, ERRHANDLER, IERROR)
EXTERNAL FUNCTION
INTEGER ERRHANDLER, IERROR
The first argument is the window in use, the second
is the error code to be returned.
INTEGER WIN, ERROR_CODE
MPI_WIN_SET_ERRHANDLER(win, errhandler) INOUT win window (handle) IN errhandler new error handler for window (handle)
INTEGER WIN, ERRHANDLER, IERROR
MPI_WIN_GET_ERRHANDLER(win, errhandler) IN win window (handle) OUT errhandler error handler currently associated with window
(handle)
INTEGER WIN, ERRHANDLER, IERROR
Up: Error Handling
Next: Error Handlers for Files
Previous: Error Handlers for Communicators
Return to MPI-2.2 Standard Index
Return to MPI Forum Home Page
(Unofficial) MPI-2.2 of September 4, 2009
HTML Generated on September 10, 2009


--- layout: default format: blog-index # Don't index these pages dear Google. noindex: true comments: true ---


Debut: {{song.performances[0].date | date:'MM/dd/yyyy'}}
Last Played: {{song.performances[song.performances.length - 1].date | date:'MM/dd/yyyy'}} ({{lastShow.show_number - song.performances[song.performances.length - 1].show_number}} shows since)
Biggest Gap: {{biggestGap.gap}} shows ({{biggestGap.from.date | date:'MM/dd/yyyy'}} arrow_forward {{biggestGap.to.date | date:'MM/dd/yyyy'}})
{{performance.date | date:'MM/dd/yyyy'}}
{{performance.venue_name}}
{{performance.location}}


User Devices
Device Name
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Room
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Device Room
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Select a deviceType:
Add Device


--- layout: default ref: AboutUs lang: en title: About us materialicon: accessibility ---
This is the OpenData.cz team
Martin Nečaský (@martinnec) is an associate professor at the Charles University in Prague.
Jakub Klímek (@jakubklimek) is a researcher at the Charles University in Prague.
Dušan Chlapek is an assistant professor at the University of Economics, Prague.
Jan Kučera is a researcher at the University of Economics, Prague.
Jindřich Mynarz (@jindrichmynarz) is a researcher at the University of Economics, Prague.
Martin Nečaský (@martinnec) is an associate professor at the Charles University in Prague.
Vojtěch Svátek is an associate professor at the University of Economics, Prague.


README.html
Introduction
This directory contains the Csharp code to implement the
Distributed
Interactive Simulation (DIS) IEEE-1278 standard, which is often used in
military simulations.
The code consists of two portions. The protocol
code itself consists of classes that represent Protocol Data Units
(PDUs). These classes have fields, getters, and setters, and are able
to marshal and unmarshal themselves to and from the DIS binary format.
This code was automatically generated via XMLPG,
a tool that generates
code automatically from an XML description. The
code is in the java and cpp directories.
The second portion of the code is supporting classes that read and
write PDUs from the network, log PDUs to a file, and more. These are
utility and example files that demonstrate the use of the generated DIS
code.
XML Description File
An XML file that is an abstract description of the protocol classes is
in DIS1998.xml. This file is used by XML Multi-Language Protocol
Generator
(XMLPG), which is available at the sourceforge site for download.
The XML file is processed by XMLPG and writes the Java, CSharp, and C++
protocol code. The idea is to use the XMLPG tool to get the final
product "close", and then manually modify the source code in subversion
to tweak the last bit.
The CSharp generator has been provided by Peter Smith. It is very
similar to the Java and C++ code.
* CSharp implementation from Peter Smith. He wrote a new xmlpg class to
generate CSharp code.


Scraping the declassified documents of CIA with python and serving in a web
Web App See RepositoryPlatzigram is a basic clone of instagram allocate on Google Cloud
Check it out Web AppThis web application predict how much is the cost of a house with a little database and a basic algorithm of ML
Check it out Web AppThis web application is a Ecommerce with prodcuts, multilevel, and panel for publish, with Stripe pay tech
Check it out Web AppInnovation Student is a Content Manager System(CMS). This is intended for students who want to learn in practice html and css, through posts and how to structure them.
Check it out"No te vares" is the application(apk) where you can have a map and geo-referencing to find your sites of interest thanks to open street map, responsive design
Check it outPlatziVideo is a web app for videos, similar to Youtube.
Check it out Web App


The Haunting (1999)
A Film Review by Mark O'Hara
Visit Online Film Critics Society at http://www.ofcs.org
If you've read Shirley Jackson's short story "The Lottery," you know the woman can spin a tale. Her 1959 novel THE HAUNTING OF HILL HOUSE is the basis for Jan De Bont's film, a mostly successful adaptation with state-of-the-art special effects and even some of the psychology handed down from Jackson's disturbing narrative.
The opening sequence brings us into the apartment and the life of Eleanor Vance (Lili Taylor), an early middle-aged woman whose mother has just died. Eleanor had cared for the woman for the last several years, and Eleanor's sister, her husband and bratty son are now making sure Eleanor gets the short end of the stick. She will inherit her mother's old Gremlin automobile, and get evicted from the apartment. Because she has not much to lose, Eleanor decides to take a break of sorts, and after a telephone solicitation, decides to take part in a study of sleep disorders.
Dr. Jeffrey Marrow - an excellent name - is running the study. Marrow (Liam Neeson) is in fact a behavioral scientist seeking to assemble a controlled study group, for the purpose of examining his subjects' reactions to fear. That his actions are unethical doesn't motivate him to inform the sleep deprived trio of the true nature of the study. He says, "You don't tell the rats they're really in a maze."
Thus we sit through the convention of the group assembling at a remote country house - Hill House - the estate of the textile magnate Hugh Crane. The three insomniacs arrive separately, a nice way for director De Bont to characterize them. After Eleanor is shown to her room by the mysterious, taciturn wife of the caretaker, we meet the second of the group, Theo (Catherine Zeta-Jones). Then Luke Sanderson (Owen Wilson) comes in, and we get to see more of the house. Although this exposition goes rather slowly for modern audiences, it is backed up well by the old house itself. In reality a school in England, the mansion seems to be overdecorated in every room, gothic touches and rococo flares everywhere. Eleanor's bedroom has the feel of a deconsecrated chapel, filigreed trim leaking from the ceilings and walls. A definite motif is the statues of children, their carved likenesses covering mantels throughout the house. Marrow later explains that the builder of the house was childless, his wife having had many stillborn children before her suicide.
Where does the haunting come in? Well, the interesting premise is that Dr. Marrow believes he is witnessing fictions and myths latent in the imaginations of his subjects. Let their minds work in the night, he figures, and they will fall victim to fears they themselves haven woven. So it is not until far into Eleanor's ordeals with the supernatural that Marrow begins to lend any credence to her behaviors.
It turns out of course that the long-dead Crane took a terrible secret to his grave, a secret still kept prisoner in the house. The rest of the narrative follows Eleanor's quest to expose the momentous truth and to free the restless souls held captive.
The biggest performance here is Lili Taylor's. This actress casts an amazing emotive truth upon her expressions, shedding tears or grimacing or acting blankly shocked, just this side of insanity. An Academy Award nomination for Best Supporting Actress might be in order here.
Catherine Zeta-Jones does a nice job in a rather different role for her. Here Theodora is full of zest and guts, a switch-hitting and aggressive female who dares you to tell her she dresses sluttishly. (At only one point does Zeta-Jones' Scottish accent, unfamiliar to most American movie-goers, slip through, when she shouts in anger at Dr. Marrow for his scientific remoteness.) Theo makes for a nice contrast with the plainer Eleanor, without seeming superior. And she's a great foil for Owen Wilson's fast-talking, rather hypochondriacal Luke. Wilson lends the most comic relief to the story, appearing sometimes like a spacey clown; nevertheless, he is protective of Eleanor when she begins to make claims about the horrendous history of the house.
Always reliable, Liam Neeson has a way in this film of making his presence strong yet quiet. He's the doctor in charge of the study, watching from the background and recording his observations on a mini-recorder that Eleanor actually finds and plays once. But Neeson is also careful not to overact, especially during one sequence in which he convinces his superior that it is necessary to set up the study by keeping the subjects in ignorance. After a few more movies, Neeson will have the reputation of being as consistent and reliable as the best actors in the history of film. Traces of slight brogue are just enough to fascinate American fans, giving the big man an edge over actors with more familiar dialects.
The bottom line is that "The Haunting" is solid but not outstanding. Three stars out of four, a B+ -- whatever your rating, the film will supply you with some nifty visual thrills, and best of all, some delicious psychological ones. Long after her death, Shirley Jackson is still an American writer with a talent for the fright-tale.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
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Related links: index of all rec.arts.movies.reviews reviews


|
Ocular Engine
|
#include <FloatProperty.hpp>
Public Member Functions | |
| FloatProperty (QWidget *parent=nullptr) | |
| virtual bool | updateProperties () override |
| virtual void | setValue (void *value, uint32_t size) override |
| virtual std::string | getValue () const override |
| LineEdit * | getLineEdit () |
| Public Member Functions inherited from Ocular::Editor::PropertyWidget | |
| PropertyWidget (std::string const &type, QWidget *parent=nullptr) | |
| virtual QSize | sizeHint () const override |
| std::string | getType () const |
| void | setVariable (Core::ExposedVariable &variable) |
| void | setDisplayName (std::string const &name) |
| std::string const & | getDisplayName () const |
| std::string const & | getVariableName () const |
| void | addWidgetLeftSide (QWidget *widget) |
| void | addWidgetRightSide (QWidget *widget) |
Additional Inherited Members | |
| Protected Attributes inherited from Ocular::Editor::PropertyWidget | |
| QHBoxLayout * | m_LayoutRight |
| Layout for the right-side frame. | |
| Core::ExposedVariable | m_Variable |
| The variable this widget is responsible for displaying and modifying. | |
Pre-built property display for 32-bit floating point value.
|
overridevirtual |
Reimplemented from Ocular::Editor::PropertyWidget.
|
overridevirtual |
Sets the value of the variable and/or widget.
Reimplemented from Ocular::Editor::PropertyWidget.
|
overridevirtual |
Update method that is called up to once a frame so that changes to the tracked variable may be checked for, and displayed.
Reimplemented from Ocular::Editor::PropertyWidget.


Instarecipes
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These notes concern the object HoTT, which has the core implementation of homotopy type theory.
The major components of homotopy type theory implemented in the object HoTT are
Inductive types, induction and recursion are in different objects as they are rather subtle. The other major way (also not in the HoTT object) of constructing non-composite types is to wrap scala types, possibly including symbolic algebra.
The core project contains code that is agnostic to how it is run. In particular this also compiles to scala-js.
We have a family of universes, but mostly use the first one denoted by Type. Given a type, we can construct symbolic objects of that type. We construct such a type A.
scala>
scala> import provingground._
import provingground._
scala> import HoTT._
import HoTT._
scala> val A = "A" :: Type
A: Typ[Term] with Subs[Typ[Term]] = A
scala> A == Type.::("A")
res9: Boolean = true
We consider a symbolic object of the type A
scala> val a = "a" :: A
a: Term with Subs[Term] = a
Given types A and B, we have the function type A → B. An element of this is a function from A to B.
We can construct functions using λ's. Here, for the type A, we construct the identity on A using a lambda. We can then view this as a dependent function of A, giving the identity function.
In this definition, two λ's are used, with the method lmbda telling the TypecompilerType that the result is a (non-dependent) function.
scala> val id = lambda(A)(lmbda(a)(a))
id: FuncLike[Typ[Term] with Subs[Typ[Term]], Func[Term with Subs[Term], Term with Subs[Term]]] = (A : 𝒰 _0) ↦ ((a : A) ↦ (a))
The type of the identity function is a mixture of Pi-types and function types. Which of these to use is determined by checking dependence of the type of the value on the varaible in a λ-definition.
scala> id.typ
res12: Typ[FuncLike[Typ[Term] with Subs[Typ[Term]], Func[Term with Subs[Term], Term with Subs[Term]]]] = (A : 𝒰 _0 ) ~> ((A) → (A))
scala> lmbda(a)(a).typ
res13: Typ[Func[Term with Subs[Term], Term with Subs[Term]]] = (A) → (A)
scala> lmbda(a)(a).typ.dependsOn(A)
res14: Boolean = true
The lambdas have the same effect at runtime. It is checked if the type of the value depends on the variable. The result is either LambdaFixed or Lambda accordingly.
scala> val indep = lmbda(a)(a)
indep: Func[Term with Subs[Term], Term with Subs[Term]] = (a : A) ↦ (a)
scala> val dep = lambda(a)(a)
dep: FuncLike[Term with Subs[Term], Term with Subs[Term]] = (a : A) ↦ (a)
scala> indep == dep
res17: Boolean = true
Note that we have alternative notation for lambdas, the maps to methods :->
and :~>
.
For instance, we can define the identity using these.
scala> assert(id == A :~> (a :-> a))
A new variable object, which has the same toString, is created in making lambdas. This is to avoid name clashes.
scala> val l = dep.asInstanceOf[LambdaFixed[Term, Term]]
l: LambdaFixed[Term, Term] = (a : A) ↦ (a)
scala> l.variable
res20: Term = a
scala> l.variable == a
res21: Boolean = false
We construct Modus Ponens, as an object in Homotopy Type theory. Note that A ->: B is the function type A → B.
scala> val B = "B" :: Type
B: Typ[Term] with Subs[Typ[Term]] = B
scala>
scala> val f = "f" :: (A ->: B)
f: Func[Term, Term] with Subs[Func[Term, Term]] = f
scala>
scala> val mp = lambda(A)(lambda(B)(lmbda(a)(lmbda(f)(f(a)))))
mp: FuncLike[Typ[Term] with Subs[Typ[Term]], FuncLike[Typ[Term] with Subs[Typ[Term]], Func[Term with Subs[Term], Func[Func[Term, Term] with Subs[Func[Term, Term]], Term]]]] = (A : 𝒰 _0) ↦ ((B : 𝒰 _0) ↦ ((a : A) ↦ ((f : (A) → (B)) ↦ ((f) (a)))))
The type of Modus Ponens is again a mixture of Pi-types and function types.
scala> mp.typ
res25: Typ[FuncLike[Typ[Term] with Subs[Typ[Term]], FuncLike[Typ[Term] with Subs[Typ[Term]], Func[Term with Subs[Term], Func[Func[Term, Term] with Subs[Func[Term, Term]], Term]]]]] = (A : 𝒰 _0 ) ~> ((B : 𝒰 _0 ) ~> ((A) → (((A) → (B)) → (B))))
We can apply modus ponens with the roles of A and B reversed. This still works because variable clashes are avoided.
scala> val mpBA = mp(B)(A)
mpBA: Func[Term with Subs[Term], Func[Func[Term, Term] with Subs[Func[Term, Term]], Term]] = (a : B) ↦ ((f : (B) → (A)) ↦ ((f) (a)))
scala> mpBA.typ == B ->: (B ->: A) ->: A
res27: Boolean = true
Lambdas do not depend on the name of the variable.
scala> val aa = "aa" :: A
aa: Term with Subs[Term] = aa
scala> lmbda(aa)(aa) == lmbda(a)(a)
res29: Boolean = true
scala> (lmbda(aa)(aa))(a) == a
res30: Boolean = true
Given a type family, we can construct the corresponding Pi-types and Sigma-types. We start with a formal type family, which is just a symbolic object of the appropriate type.
scala> val Bs = "B(_ : A)" :: (A ->: Type)
Bs: Func[Term, Typ[Term]] with Subs[Func[Term, Typ[Term]]] = B(_ : A)
In addition to the case class constructor, there is an agda/shapeless-like convenience method for constructing Pi-types. Namely, given a type expression that depends on a varaible a : A, we can construct the Pi-type correspoding to the obtained λ-expression.
Note that the !: method just claims and checks a type, and is useful (e.g. here) for documentation.
scala> val fmly = (a !: A) ~>: (Bs(a) ->: A)
fmly: GenFuncTyp[Term, Func[Term, Term]] = (a : A ) ~> (((B(_ : A)) (a)) → (A))
There is also a convenience method for defining Sigma types using λs.
scala> Sgma(a !: A, Bs(a))
res33: SigmaTyp[Term, Term] = ∑((a : A) ↦ ((B(_ : A)) (a)))
scala> Sgma(a !: A, Bs(a) ->: Bs(a) ->: A)
res34: SigmaTyp[Term, Func[Term, Func[Term, Term]]] = ∑((a : A) ↦ (((B(_ : A)) (a)) → (((B(_ : A)) (a)) → (A))))
Like functions and dependent functions, pairs and dependent pairs can be handled together. The mkPair function assignes the right type after checking dependence, choosing between pair types, pairs and dependent pairs.
scala> val ba = "b(a)" :: Bs(a)
ba: Term with Subs[Term] = b(a)
scala> val b = "b" :: B
b: Term with Subs[Term] = b
scala> mkPair(A, B)
res37: AbsPair[Term, Term] = ((A) , (B))
scala> mkPair(a, b)
res38: AbsPair[Term, Term] = ((a) , (b))
scala> mkPair(a, b).typ
res39: Typ[U] = ((A) , (B))
scala> mkPair(a, ba).typ
res40: Typ[U] = ∑((a : A) ↦ ((B(_ : A)) (a)))
scala> mkPair(A, B).asInstanceOf[ProdTyp[Term, Term]]
res41: ProdTyp[Term, Term] = ((A) , (B))
We can also construct the plus type A plus B, which comes with two inclusion functions.
scala> val AplusB = PlusTyp(A, B)
AplusB: PlusTyp[Term, Term] = PlusTyp(A,B)
scala> AplusB.incl1(a)
res43: PlusTyp.FirstIncl[Term, Term] = FirstIncl(PlusTyp(A,B),a)
scala> AplusB.incl2
res44: Func[Term with Subs[Term], PlusTyp.ScndIncl[Term, Term]] = ($cn : B) ↦ (ScndIncl(PlusTyp(A,B),$cn))
In the above, a λ was used, with a variable automatically generated. These have names starting with $ to avoid collision with user defined ones.
We have an identity type associated to a type A, with reflexivity giving terms of this type.
scala> val eqAa = IdentityTyp(A, a, a)
eqAa: IdentityTyp[Term with Subs[Term]] = a = a
scala> val ref = Refl(A, a)
ref: Refl[Term with Subs[Term]] = Refl(A,a)
scala> ref.typ == eqAa
res47: Boolean = true
Finally, we have the types corresponding to True and False
scala> Unit
res48: Unit.type = Unit
scala> Zero
res49: Zero.type = Zero
scala> Star !: Unit
res50: Term = Star
commit a83fc238eaaa2f98d8ea8f6e9cbc94aa157f2e41
Author: Siddhartha Gadgil<EMAIL_ADDRESS>Date: Mon Sep 17 15:43:03 2018 +0530
better logging auto search; fails but not serious
relevant lemmas are discovered, its a matter of spawning with lemmas
together or some such tuning.


- Go Vanity Server - Decouple SCM repository path from Go import path.
- Simple Proxy Server - Hosted applications on the same box then simply proxy it behind.
{{- end }}


Prescribing Dashboard
Prescribed items per Primary Care Trust (PCT)
Infection treatment drug as % of all infection treatments
{{infection_drug_bars[1][0][0]}} {{infection_drug_bars[0][0][0]}}%
{{infection_drug_bars[1][1][0]}} {{infection_drug_bars[0][1][0]}}%
{{infection_drug_bars[1][2][0]}} {{infection_drug_bars[0][2][0]}}%
{{infection_drug_bars[1][3][0]}} {{infection_drug_bars[0][3][0]}}%
{{infection_drug_bars[1][4][0]}} {{infection_drug_bars[0][4][0]}}%
BNF data per PCT
| Practice | BNF code | BNF name | Items | {% for row in pct_data %}
| {{ row.practice }} | {{ row.BNF_code }} | {{ row.BNF_name }} | {{ row.items }} |
Creatinine clearance calculator
About the dashboard
This dashboard was created by Trainee Clinical Scientists as part of a Clinical Science MSc. It displays data extracted from the Open Prescribing Dataset which contains practice level prescribing data. Its intended users are CCGs, practice managers, clinicians and pharmacists.