AMERICAN BEAUTY
Reviewed by Harvey Karten DreamWorks Pictures Director: Sam Mendes Writer: Alan Ball Cast: Kevin Spacey, Annette Bening, Thora Birch, Wes Bentley, Mena Suvari, Peter Gallagher, Allison Janney, Chris Cooper, Scott Bakula, Sam Robards
Leo Tolstoy told us that happy families are all alike; every unhappy family is unhappy in its own way. While 90% of us get married, confident that we will be in the former category, statistics prove otherwise. What's unfortunate in that regard is advantageous for art, though. Is "The Brady Bunch" among the world's great contributions? Hardly. Look for dramatic excitement to "Agamemnon," "Medea," "Oedipus," and Hamlet, to cite a few examples. Dysfunctional families make for maximum enjoyment.  Sam Mendes proves this by adapting Alan Ball's alternately funny and poignant story, "American Beauty," to the big screen. Already named by some critics as one of the two Oscar contenders (Tom Hanks's vehicle, "The Green Mile," being the other), "American Beauty" mesmerizes because every moment, however caricatured, hits a nerve in each of us. Don't tell others who have seen this film that you cannot identify with any of the characters. You're likely to get the fortune-cookie reply, "You ought to get out more often."
 In "American Beauty," repressions, anxieties, and hostilities are played out in a suburban neighborhood, but urban landscapes are no strangers to dysfunction. Among well-mown lawns and newly-painted picket fences, though, more pressure is put upon residents to fit in, to appear successful, to have happy marriages, to get with the program. And so suburbanites have been reproached--justifiably or not--for having less tolerance for differences than city people. This notion makes the generic American suburb the consummate setting for "American Beauty," an ideal backdrop for its chiefly sorrowful society which--through nominally tidy lawns and lives and spirits-sodden socials try to imprint their triumphs on their acquaintances.
Foremost among them, Lester Burnham (Kevin Spacey) works in a cubicle as a media writer, but has utter contempt for the hollow mission of his organization and disdain for the company higher-ups and for the people he contacts each day. Nor is his home life the escape-hatch so promoted by the psychological pap that passes for profound professional literature. His wife Carolyn (Annette Bening), an every-hair- in-place real-estate agent, is frustrated to the point of tears because of her inability to sell houses.
Her parents' disappointments are easily perceived by their teen-aged daughter, Jane (Thora Birch), whose best friend Angela (Mena Suvari) considers Jane's father a freak but whose secret admirer Ricky Fitts (Wes Bentley) is so without cynicism that he sees beauty in everything. Though physically and psychologically abused at home by his ex- Marine father, Col. Fitts (Chris Cooper), Ricky is so enthralled by the world's resplendence that he carefully photographs all that he considers divine--people, swirling leaves and papers, even a dead bird, amassing a library of videotapes whose subject could well be American Beauty.
While director Sam Mendes ponders the town's relationships--the colonel with his son and his clinically depressed wife Barbara (Allison Janney); the daughter with her parents, her sexy best friend Angela, and her boy friend Ricky; Carolyn with her husband and her new lover, Buddy-- the focal point is Lester Burnham's connection with himself. And what an awesome job Mendes does with this fellow! Carefully and humorously developing Lester's cynicism, disappointments, and flat-out numbness, Mendes shows what happens when at the age of 42 Lester awakens from his extended coma, laying his eyes on the seductive teen cheerleader, Angela. Lester's rush recalls Dr. Bill Maplewood's attraction to the 11-year-old Billy in Todd Solondz's "Happiness" and Humbert Humbert's for Lolita in the Nabokov novel, brought back to cinematic life last year by Adrian Lyne. With Angela as catalyst for change, Lester determines to shuck off his paunch by working out until he develops awesome abs, to express himself in the most intemperate ways to his boss, his wife and his daughter, and to try at his stage of mid-life to restore the joy and laughter and abandon he experienced in his youth. His resolve, while admirable in some ways, is financially irresponsible and psychologically is little more than important rage. But what is more trenchant is that he is too late. Henri Etienne was on the money when he said in 1594 "Si jeunesse savait, si vieillesse pouvait," or, "If youth but knew, if age but could."
Thrilling acting by Kevin Spacey, one of America's greatest performers, should assure him an Oscar nomination. Unfairly edged out the Tony award competition for his dazzling performance as Hickey in Broadway's "The Iceman Cometh," Spacey sets a new standard here by his facility in switching gears, in turning from a narrator who is alternately side-splitting, self-deprecatory, seething, sexy, and sensitive. Annette Bening in the less-developed and implausibly over- the-top role is a suitable butt for Spacey's rage, Chris Cooper as the stereotypical former Marine who cannot get used to the "ex" in his title, and Wes Bentley as the half-freaky, half- responsive connoisseur of American beauty are all on target. Yet Spacey carries the show. "It's just stuff and it's become more important to you than life," he protests to his materialistic wife, who is more concerned about spilling a drink on the $4000 sofa than showing physical affection for her husband. Lest we get carried away by his newly-found contempt for money, we must realize how much he grooves on the old Pontiac Firebird he has just acquired and how important Ricky's $40,000 is if he is going to continue finding life as beautiful as he has felt it to be in the past.
Most of the world's people do not live in capacious suburban homes with picket fences for decoration and Golden Retrievers to greet them when they get home. Two- thirds of humanity live in the tar-paper shacks, wooden shanties, and the like. Should we dismiss the woes of the comfortably situated as mere bourgeois inconveniences that can be solved by a few affordable sessions on the couch? Of course not.  I've seen dirt-poor, unclad kids in southern India playing on the beaches, sporting broad, authentic smiles that I see less often on the faces of American children. The Greek tragedians, in fact, seemed to believe that only the rich and powerful could truly suffer. I challenge you to see "American Beauty" without feeling great compassion for the anguish of its well-situated people, whose laughter and good times do not always erase their anguish and distress. The performances led by Kevin Spacey, the capable direction by Sam Mendes backed up by Conrad Hall's eye behind the camera, and Thomas Newman's pulsating soundtrack, all position the film for a flurry of year- end awards. I'd be hard-put to recall another movie (certainly not Ang Lee's detached and clinical "The Ice Storm") that has so skillfully integrated exuberant humor with heartbreaking pathos.
Rated R. Running Time: 118 minutes. (C) 1999 Harvey Karten
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|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object com.threed.jpct.util.Overlay
Overlay is a helper class to create opaque or transparent screen overlays
from textures. An overlay is quite similar to scaled blit with the exception
that an overlay has an actual depth and that it takes care of itself, i.e.
once created, it will appear automatically until you dispose it. A scaled
blit has to be applied by the application each frame.
Note: There seems to be some unresolved issue with threaded renderers....
| Constructor Summary | |
Overlay(World world,
FrameBuffer buffer,
java.lang.String textureName)
Creates a new overlay that covers the whole screen. |
|
Overlay(World world,
int upperLeftX,
int upperLeftY,
int lowerRightX,
int lowerRightY,
java.lang.String textureName)
Creates a new overlay of arbritary size. |
| Method Summary | |
void |
dispose()
Disposes the overlay and frees its resources. |
Object3D |
getObject3D()
Returns the internal Object3D that is the actual Overlay. |
void |
setColor(java.awt.Color color)
Sets a new additional color. |
void |
setDepth(float depth)
Sets the depth of the overlay. |
void |
setInitialMatrix(Matrix matrix)
Sets a new initial matrix that will be used instead of the identity matrix when calculating the Overlay's position. |
void |
setNewCoordinates(int upperLeftX,
int upperLeftY,
int lowerRightX,
int lowerRightY)
Sets new coordinates for the overlay. |
void |
setRotation(float angle)
Rotates the Overlay around it's midpoint or it's pivot, if one is set. |
void |
setRotationPivot(int x,
int y)
Sets the pivot point for the rotation in screen coordinates. |
void |
setSelectable(boolean mode)
Sets the object as selectable/unselectable. |
void |
setSourceCoordinates(float upperLeftX,
float upperLeftY,
float lowerRightX,
float lowerRightY)
Sets new source coordinates. |
void |
setTexture(java.lang.String textureName)
Changes the texture of the overlay. |
void |
setTexture(TextureInfo textureInfo)
Changes the texture of the overlay. |
void |
setTransparency(int trans)
Set the transparency of the overlay. |
void |
setTransparencyMode(int mode)
Sets the transparency mode similar to setTransparencyMode() in Object3D. |
void |
setVisibility(boolean visible)
Sets the visibility similar to setVisibility() in Object3D. |
void |
unlink()
Unlinks the overlay. |
void |
update(FrameBuffer buffer)
Updates the overlay. |
| Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
public Overlay(World world, FrameBuffer buffer, java.lang.String textureName)
world
- the worldbuffer
- the current frame buffertextureName
- the name of the texture that should be used as an overlay. The
TextureManager has to know this texture.public Overlay(World world, int upperLeftX, int upperLeftY, int lowerRightX, int lowerRightY, java.lang.String textureName)
world
- the worldupperLeftX
- the upper left corner's x-coordinate in screen coordinatesupperLeftY
- the upper left corner's y-coordinate in screen coordinateslowerRightX
- the lower right corner's x-coordinate in screen coordinateslowerRightY
- the lower right corner's y-coordinate in screen coordinatestextureName
- the name of the texture that should be used as an overlay. The
TextureManager has to know this texture.| Method Detail |
public void setDepth(float depth)
depth
- the new depth (should be positive)public void setSelectable(boolean mode)
mode
- MOUSE_SELECTABLE/MOUSE_UNSELECTABLEObject3D.MOUSE_SELECTABLE
,
Object3D.MOUSE_UNSELECTABLE
public void setTransparency(int trans)
trans
- the transparency valueObject3D.setTransparency(int)
public void setColor(java.awt.Color color)
color
- the new Colorpublic void setTexture(java.lang.String textureName)
textureName
- the new texture's name as the TextureManager knows it.public void setTexture(TextureInfo textureInfo)
textureInfo
- the new TextureInfo.public void setVisibility(boolean visible)
visible
- should it be visible or not?Object3D.setVisibility(boolean)
public void setTransparencyMode(int mode)
mode
- the modeObject3D.setTransparencyMode(int)
,
Object3D.TRANSPARENCY_MODE_DEFAULT
,
Object3D.TRANSPARENCY_MODE_ADD
public void setNewCoordinates(int upperLeftX, int upperLeftY, int lowerRightX, int lowerRightY)
upperLeftX
- the upper left corner's x-coordinate in screen coordinatesupperLeftY
- the upper left corner's y-coordinate in screen coordinateslowerRightX
- the lower right corner's x-coordinate in screen coordinateslowerRightY
- the lower right corner's y-coordinate in screen coordinatespublic void setSourceCoordinates(float upperLeftX, float upperLeftY, float lowerRightX, float lowerRightY)
upperLeftX
- the upper left corner's x-coordinate in texture coordinatesupperLeftY
- the upper left corner's y-coordinate in texture coordinateslowerRightX
- the lower right corner's x-coordinate in texture coordinateslowerRightY
- the lower right corner's y-coordinate in texture coordinatespublic void setRotation(float angle)
angle
- the anglepublic void setInitialMatrix(Matrix matrix)
matrix
- the new initial Matrixpublic void setRotationPivot(int x, int y)
x
- the x positiony
- the y positionpublic Object3D getObject3D()
public void dispose()
public void unlink()
public void update(FrameBuffer buffer)
buffer
-
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This code provides some utility routines for atmospheric tracers in the FMS framework.
fms_mod
time_manager_mod
diag_manager_mod
tracer_manager_mod
field_manager_mod
constants_mod
horiz_interp_mod
use atmos_tracer_utilities_mod [, only: atmos_tracer_utilities_init,
dry_deposition,
wet_deposition,
interp_emiss,
tracer_utilities_end ]
call atmos_tracer_utilities_init (lonb,latb, mass_axes, Time)
| lonb | The longitudes for the local domain. [real, dimension(:)] |
| latb | The latitudes for the local domain. [real, dimension(:)] |
| mass_axes | The axes relating to the tracer array. [integer, dimension(3)] |
| Time | Model time. [type(time_type)] |
call dry_deposition ( n, is, js, u, v, T, pwt, pfull, u_star, landmask, dsinku, tracer, Time)
R = Ra + Rb resisa = aerodynamic resistance resisb = surface resistance (laminar layer + uptake) = 5/u* [s/cm] for neutral stability Vd = 1/RFor the fixed dry deposition velocity, there is no change in the deposition velocity but the variation of the depth of the surface layer implies that there is variation in the amount deposited.
"dry_deposition","wind_driven","surfr=XXX" where XXX is the total resistance defined above. "dry_deposition","fixed","land=XXX, sea=YYY" where XXX is the dry deposition velocity (m/s) over land and YYY is the dry deposition velocity (m/s) over sea.
| n | The tracer number. [integer] |
| is, js | Start indices for array (computational indices). [integer] |
| u | U wind field. [real, dimension(:,:)] |
| v | V wind field. [real, dimension(:,:)] |
| T | Temperature. [real, dimension(:,:)] |
| pwt | Pressure differential of half levels. [real, dimension(:,:)] |
| pfull | Full pressure levels. [real, dimension(:,:)] |
| u_star | Friction velocity. [real, dimension(:,:)] |
| landmask | Land - sea mask. [logical] |
| dsinku | The amount of tracer in the surface layer which is dry deposited per second. [real, dimension(:,:)] |
call wet_deposition (n, T, pfull, phalf, rain, snow, qdt, tracer, tracer_dt, Time, cloud_param, is, js)
"wet_deposition","henry","henry=XXX, dependence=YYY" where XXX is the Henry's constant for the tracer in question and YYY is the temperature dependence of the Henry's Law constant. "wet_deposition","fraction","lslwc=XXX, convlwc=YYY" where XXX is the liquid water content of a standard large scale cloud and YYY is the liquid water content of a standard convective cloud.
| n | Tracer number [integer] |
| is, js | start indices for array (computational indices) [integer] |
| T | Temperature [real, dimension(:,:,:)] |
| pfull | Full level pressure field [real, dimension(:,:,:)] |
| phalf | Half level pressure field [real, dimension(:,:,:)] |
| rain | Precipitation in the form of rain [real, dimension(:,:)] |
| snow | Precipitation in the form of snow [real, dimension(:,:)] |
| qdt | The tendency of the specific humidity due to the cloud parametrization [real, dimension(:,:,:)] |
| tracer | The tracer field [real, dimension(:,:,:)] |
| Time | The time structure for submitting wet deposition as a diagnostic [type(time_type)] |
| cloud_param | Is this a convective (convect) or large scale (lscale) cloud parametrization? [character] |
| tracer_dt | The tendency of the tracer field due to wet deposition. [real, dimension(:,:,:)] |
call interp_emiss (global_source, start_lon, start_lat, & lon_resol, lat_resol, data_out)
| global_source | Global emission field. [real, dimension(:,:)] |
| start_lon | Longitude of starting point of emission field
(in radians). This is the westernmost boundary of the
global field. [real] |
| start_lat | Latitude of starting point of emission field
(in radians). This is the southern boundary of the
global field. [real] |
| lon_resol | Longitudinal resolution of the emission data (in radians). [real] |
| lat_resol | Latitudinal resolution of the emission data (in radians). [real] |
| data_out | Interpolated emission field on the local PE. [real, dimension(:,:)] |


|
Firmware documentation - Master
v. 6.1.5
Centro E.Piaggio
|
Interruptions header file. More...
#include <device.h>
Go to the source code of this file.
Functions | |
Interruptions | |
| CY_ISR_PROTO (ISR_RS485_RX_ExInterrupt) | |
| CY_ISR_PROTO (ISR_WATCHDOG_Handler) | |
General function scheduler | |
| void | function_scheduler (void) |
Encoder reading function | |
| void | encoder_reading (const uint8 index) |
Motor control function | |
| void | motor_control () |
Analog readings | |
| void | analog_read_end () |
Interrupt manager | |
| void | interrupt_manager () |
Utility functions | |
| void | pwm_limit_search () |
| void | overcurrent_control () |
| void | command_slave () |
| void | deactivate_slave () |
Interruptions header file.
| void analog_read_end | ( | ) |
This function executes and terminates the analog readings.
| void command_slave | ( | ) |
This function is used to create a package and send it to another device, only if the actual board is in master mode.
| CY_ISR_PROTO | ( | ISR_RS485_RX_ExInterrupt | ) |
This interruption sets a flag to let the firmware know that a communication interruption is pending and needs to be handled. The interruption will be handled in predefined moments during the firmware execution. When this interruption is handled, it unpacks the package received on the RS485 communication bus.
| CY_ISR_PROTO | ( | ISR_WATCHDOG_Handler | ) |
This interruption sets a flag to let the firmware know that a watchdog interruption is pending and needs to be handled. The interrpution will be handled in predefined moments during the firmware execution. When this interruption is handled, it deactivates the board because the watchdog timer has expired.
| void deactivate_slave | ( | ) |
This function is used to create a package to deactivate motors on another device, only if the actual board is in master mode.
| void encoder_reading | ( | const uint8 | index | ) |
This functions reads the value from the encoder pointed by index.
| index | The number of the encoder that must be read. |
| void function_scheduler | ( | void | ) |
This function schedules the other functions in an order that optimizes the controller usage.
| void interrupt_manager | ( | ) |
This function is called in predefinited moments during firmware execution in order to unpack the received package.
| void motor_control | ( | ) |
This function controls the motor direction and velocity, depending on the input and control modality set.
| void overcurrent_control | ( | ) |
This function increases or decreases the pwm value, depending on the current absorbed by the motor.
| void pwm_limit_search | ( | ) |
This function scales the pwm value of the motor, depending on the power supply voltage, in order to not make the motor wind too fast.


Everytime we log into this blog it will record where we were at the time, the date and the precise GPS coordinates.


Online selling pizza
Serving your daily pizza ! Available through online order only.
Delivery only available by selecting pizza.
pizzaOrder


If you have any questions about what we do or are looking for more information our bees, cafe, shop or home-made honey, fill in the contact form and we’ll get back to you as soon as we can!


{% extends "_post.html" %}
{% hyde
title: "Negative Space in Dancing"
snip: "It’s not just for artsy kids."
created: 2008-08-31 15:33:57
flattr: true
%}
{% block article %}
Last night a few of us from Rochester drove to Buffalo for a swing event.
There were three classes during the afternoon that were pretty fun. There was
a dance in the evening which had a great turnout and plenty of energy. As nice
as all that was, the real highlight of the day/night was the blues party after
the dance. Matt and I ended up DJ'ing it and it was absolutely awesome. I got
to meet and dance with a whole bunch of new people that I hope to dance with
again soon.
One concept I try to use in my blues (and tango) dancing is that of negative
space. I've found that a lot of blues dancers don't really seem to quite get
that idea. I'm not saying that it's the "right" way to blues dance but it's
something that's changed how I dance and I wanted to write something about it
to share it with anyone interested.
What is negative space?
-------------------
Negative space is a term used a lot in painting, photography, graphic design,
etc. It basically means that for a given photo (or painting, whatever) the
whole frame isn't filled with "things." Two examples of this taken from my
flickr favorites are [this photo][1] and [this one][2]. In both of these
images the subject takes up only a small portion of the frame. The expanses of
even texture and tone add certain qualities to the photos that can't be
achieved otherwise.
A photographer that takes this to an extreme is Hiroshi Sugimoto, in his
[Seascape][] series. He uses long exposures and darkroom techniques to produce
images of nothing but negative space. The sea blends into a seamless texture
and the sky becomes a single tone. Even though there isn't a physical object
between the two, the division between them forms a subject of its own.
How does it relate to dancing?
------------------------
Most of the blues dancers I know come from a Lindy Hop background.
When blues dancing I think a lot of Lindy Hoppers never catch on to this idea:
*you don't need to be moving all of the time*. It's alright to slow down and
actually stop for one, two, three, four measures. It gives the dance a chance
to breathe and lets you focus on your connection with your partner without
movement getting in the way.
"Won't that be boring?" No. Absolutely not. Stopping can provide things that
you can't really get while moving. It can add tension, release it, and
completely change the mood of a dance. It really does have a lot in common
with negative space in art, and it adds a lot to a dance.
Negative space does not mean "empty space," although it's often described like
that. In the first photo I linked to the wall is indeed blank, but has color
and texture that can give you plenty to look at. In the second, the expanses
of white are just that: white. They are not empty; they have a distinct tone:
white. If they were black, or even a light grey the photo would be entirely
different.
In dancing, movement is important but not the only thing we think about.
Posture and body positioning is one example. "Feeling" or "mood" is another,
more elusive, one. Just because the movement is gone doesn't mean all these
other things go away automatically; they're still there until you let them go.
Taking it to the extreme like Sugimoto's Seascapes is also emphatically *not*
boring. In some of the best blues dances I've ever had there were parts where
we didn't really move for several measures at a time. When this happens, both
of you create your own negative space through your posture, etc. Neither of
these spaces are empty.
Where these spaces meet is your connection. Like the horizons in Sugimoto's
photographs it becomes the main subject. By eliminating motion you're free to
focus your attention on other aspects of the connection. Sometimes these
aren't obvious at first. One example Mihai likes to talk about is breathing.
Another is understanding where your partner's weight is.
By giving yourself time to really feel the connection with your partner you
have time to examine it much more closely. You can introduce tiny movements
(like the waves that fleck the surface of the water in Sugimito's seas) that
interrupt the absolute flatness of the spaces and let you explore the
interactions between them. Not only does this let you learn about how your
partner is connected to you in a more in-depth way, it's very, very fun.
I don't have a particularly amazing ending for this post. The main points I
wanted to get across are these: Negative space in dancing is removing most or
all of the movement for a longer-than-normal about of time. Negative space is
not empty space unless you ignore all the other aspects of the dance like
posture, mood and connection. Negative space can add things to a dance that
you can't get otherwise.
Try it.
[1]: http://flickr.com/photos/theoperamafia/2790037114/
[2]: http://flickr.com/photos/jodiseva/2385347094/
[Seascape]: http://www.sugimotohiroshi.com/seascape.html
{% endblock %}


Chris Brown Teases Birth Of His First Son
by Shakiel MahjouriIt seems Chris Brown is adding to the family.
The “Kiss Kiss” singer was expecting his second child with his ex Ammika Harris and that time has reportedly come. Brown, 30, published two Instagram posts teasing the arrival of his baby boy. Furthermore, sources close to the singer reportedly confirmed the news to TMZ.
Late Wednesday night, Brown posted a black-and-white photo of himself looking down off-camera. The photo was accompanied with the caption, “11-20-2019.” Soon after, he posted another picture of himself — this time wearing a hoodie adorned with the word “BORN.”
Harris also posted a telling Instagram Story reading, “I was in love when I first saw you.”
This is Brown’s second child and first with Harris. Brown is also father to daughter Royalty, 5, with model Nia Amey.


As the one assistant in the Study Abroad office at Arcadia University, I help students through the process of going abroad, as well as, doing administrative tasks. This entails mentoring, organizing the office, processing paperwork, as well as, helping to plan engaging events which inform students about their options.
Assisted the Alumni Relations office in organizing events by preparing documents, slideshows, and making calls. Handled inquiries from alumni, students, and the local community.
Orientation leader is a voluntary leadership position, that helps the class of 2022 and 2023 to move in, meet classmates, adjust to campus life, and explore the city of Philadephia. This position, while only active during the summer, doesn't end when the semester starts. We instead, aim to be helpful all-year-around and to be mentors and supporters to the future incoming classes.
Participated in the 10 week AMALTHEA REU program at Florida Institute of Technology. Conducted research in machine learning at FIT's Information Characterization & Exploitation (ICE) Laboratory.
GPA: 3.6
Over the course of being a student, I have made time for my many interests. From Traveling the world, babysitting my niece, reading a new book, and also volunteering my time at various places and events.


Your earnings are based on the total order amount in the group and your referrals. More orders in a group gives more earnings


Hello there. Seeing that there is very little info on Kanna (Kagoued to the Dutch) here or anywhere else on the net, I thought I'd share a few things. This is quite an interesting plant with substantial historical use. It also can be grown easily in one's home from cuttings or seeds. It gives a nice, mild buzz. And it's completely legal.
I ordered some dried Sceletium Tortuosum powder on the net a few weeks ago and have enjoyed it on several occasions.  For my first experience I tried all three. First I snuffed about 50 mg, a very small amount. It burns a little, but quickly goes away.
Next I put another 50 mg on top of enough MJ to keep the powder from pulling through my pipe. Different taste, but not bad. For good measure, I also put a pinch under my tongue and swished it around for a couple minutes. Five or ten minutes after this the effects started. It was kinda mild, but nice. It was very similar to the feeling I get right after finishing a fat bowl of MJ, except without the full stone. It was more like the physical effects of MJ with the euphoria but without the hazy feeling. It also made my legs and arms sort of tingly. Very pleasant.
It's definately worth a try. It's even well known in Holland. That says something when the Dutch can get all the best buds around and they still mess with this stuff. Anyway, it's also good on top of MJ. A definate enhancer. Makes the buds go much farther. Dried herb is kind of expensive, but a little goes a long way and it can be grown easily and legally for next to nothing.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Posted: 2017-09-05
, Modified: 2017-09-05
Tags: none
Current projects
- Reinforcement learning
- Next steps with sampling problems, temperature-varying
- Understand AIS/RAISE
- AIS/RAISE estimator - similar criterion?
- See [BGS14] Accurate and Conservative Estimates of MRF Log-likelihood using Reverse Annealing
- “Multiplicative” weights
- Other settings where annealing helps. Analogue on Boolean cube.
- Tensor decomposition.
- Beyond the homotopy method.
- [MR16]
- EGNN
- NLP:
- BoNGs: make recovery work for \(n\)-grams, \(n\ge 2\).
- Treegrams
- cf. Sida Wang
- hyperdim vectors
- document embedding (axioms?)
Sidelined
- Long-term memory (COLT open problem) (Tue)
- For convex optimization
- Tue: this seems difficult because of “bottleneck” of probability \(\ll \rc{\poly(n)}\). Next step: familiarize with lower-bound techniques and try to prove lower bound.
Logic learning (with Kiran)
- Coming up with the objective
- Ex. restrict to separable \(\sum w_i f_i\).
- Learn representations with desired properties by human feedback
- IRL, CIRL. Learn human references, loss function.
- Picking out part of image that matters
- Graphs?
- Recovery as good property to have?
- Learn logic/PCFG over curriculum without supervised data. Language generation.
- Readings (Hrishikesh)
- Probabilistic sentential decision diagrams
- [KVCD14] PSSD
- [D11] SDD
- [N86] Probabilistic logic
- Markov random fields
- Fuzzy logic
- Continuous representations of boolean functions
- Neural tensor machines (matrix product)
- Learning language games through interaction
- Learning grammar: see messenger.
- [TH] Unsupervised learning of probabilistic context-free grammar using iterative biclustering
- [CTC] Automatic Learning of Context-Free Grammar
Code
Misc
Instead of a log-linear model with features from (logical forms, canonical utterances), have something more principled.
Semantic Parsing via Paraphrasing
Agenda-based parsing: reduce from n^3
Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings: certainty
Learning Executable Semantic Parsers for Natural Language Understanding: score derivations with log-linear (survey)
Bringing machine learning and compositional semantics together (survey)
Simpler Context-Dependent Logical Forms via Model Projections: add context dependence.
Inferring Logical Forms From Denotations: getting consistent logical forms
Building a Semantic Parser Overnight: entire pipeline, with crowdsourcing
“To generate candidate logical forms, we use a simple beam search” - it seems better to parse, keep top from beam search, and then convert?
moral: throw in lots of features
Paraphrasing and transformations
The cat was chased by a dog. The cat was bitten.
If CFG doesn’t have too much “latent”, everything is close to surface, then have hope? Prevents combinatorial blowup of possible hidden states/transitions.
Beyond CFGs
Have a superset of the right rules. Now use gradient update to find which best explain it. Also would like to match things that transform, like “You want x.” and “What do you want?”
Neuroscience reading
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021692/ - the brain optimizing cost functions, ie the generalization of gradient descent, as a hypothesis for how local neuron wiring is learned.
- http://www.cell.com/neuron/abstract/S0896-6273(17)30509-3 - this is the one that takes these others and generalizes them to the whole brain, in particular this explains how complicated architectures in deep learning can be used to understand the large scale functional architecture of the brain
- http://physrev.physiology.org/content/physrev/95/3/853.full.pdf - overview of the human reward system
- http://www.nature.com/neuro/journal/v19/n3/abs/nn.4244.html - comparing supervised deep learning to the (unsupervised probably) vision system
- http://rstb.royalsocietypublishing.org/content/371/1705/20160278 - actually physically modeling readings from the brain with the functional statistics from deep learning models trained on the same tasks
AISFP preparation
- Write up AI safety thoughts (from books, etc.)
- Review:
- Lob’s theorem
- Decision theories


26 March 2004
The Ministry of Health has reported a total of 327 cases and 46 deaths in 21 local government areas in Jigwa state.
Samples have been taken to determine the serogroup. The Ministry of Health has provided 150, 000 doses of bivalent (A/C) vaccine and UNICEF has provided oily chloramphenicol.


Example of nested accordions
First tab
Content of 1st tab
Second tab
Content of 2nd tab
First tab
Content of 1st tab
Second tab
Content of 2nd tab
Third tab
Content of 3rd tab
Third tab
Content of 3rd tab
Design pattern
jQuery Accessible tab panel system, using ARIA


Object
Manages the filtering of examples and groups by matching tags declared on the command line or options files, or filters declared via `RSpec.configure`, with hash key/values submitted within example group and/or example declarations. For example, given this declaration:
describe Thing, :awesome => true do it "does something" do # ... end end
That group (or any other with `:awesome => true`) would be filtered in with any of the following commands:
rspec --tag awesome:true rspec --tag awesome rspec -t awesome:true rspec -t awesome
Prefixing the tag names with `~` negates the tags, thus excluding this group with any of:
rspec --tag ~awesome:true rspec --tag ~awesome rspec -t ~awesome:true rspec -t ~awesome
## Options files and command line overrides
Tag declarations can be stored in `.rspec`, `~/.rspec`, or a custom options file. This is useful for storing defaults. For example, let’s say you’ve got some slow specs that you want to suppress most of the time. You can tag them like this:
describe Something, :slow => true do
And then store this in `.rspec`:
--tag ~slow:true
Now when you run `rspec`, that group will be excluded.
## Overriding
Of course, you probably want to run them sometimes, so you can override this tag on the command line like this:
rspec --tag slow:true
You can also store default tags with `RSpec.configure`. We use `tag` on the command line (and in options files like `.rspec`), but for historical reasons we use the term `filter` in `RSpec.configure:
RSpec.configure do |c| c.filter_run_including :foo => :bar c.filter_run_excluding :foo => :bar end
These declarations can also be overridden from the command line.
@see RSpec.configure @see Configuration#filter_run_including @see Configuration#filter_run_excluding
# File lib/rspec/core/filter_manager.rb, line 123 def add_location(file_path, line_numbers) # locations is a hash of expanded paths to arrays of line # numbers to match against. e.g. # { "path/to/file.rb" => [37, 42] } locations = @inclusions.delete(:locations) || Hash.new {|h,k| h[k] = []} locations[File.expand_path(file_path)].push(*line_numbers) @inclusions.replace(:locations => locations) @exclusions.clear end
# File lib/rspec/core/filter_manager.rb, line 133 def empty? inclusions.empty? && exclusions.empty_without_conditional_filters? end
# File lib/rspec/core/filter_manager.rb, line 141 def exclude(*args) merge(@exclusions, @inclusions, *args) end
# File lib/rspec/core/filter_manager.rb, line 145 def exclude!(*args) replace(@exclusions, @inclusions, *args) end
# File lib/rspec/core/filter_manager.rb, line 153 def exclude?(example) @exclusions.empty? ? false : example.any_apply?(@exclusions) end
# File lib/rspec/core/filter_manager.rb, line 149 def exclude_with_low_priority(*args) reverse_merge(@exclusions, @inclusions, *args) end
# File lib/rspec/core/filter_manager.rb, line 157 def include(*args) unless_standalone(*args) { merge(@inclusions, @exclusions, *args) } end
# File lib/rspec/core/filter_manager.rb, line 161 def include!(*args) unless_standalone(*args) { replace(@inclusions, @exclusions, *args) } end
# File lib/rspec/core/filter_manager.rb, line 169 def include?(example) @inclusions.empty? ? true : example.any_apply?(@inclusions) end
Generated with the Darkfish Rdoc Generator 2.


Here is where I list a ton more inforamtion
More informationa bout how much I like to do stuff
Other ways of getting a hold of me include smoke signals and telephones. Or you can check out Twitter


Career Profile
To build a challenging career in the software field by utilizing my skills and contributing towards the goals of the company. To constantly upgrade my knowledge and skills and make difference in whatever I do.
Projects
List of recent projects that i am proud of
An Automated Coin Recognition System Using GLCM - The aim of the project is to build a coin recognition system using Grey Level Cooccurrence Matrix(GLCM). A camera is used to capture the images of the coins. GLCM features are extracted from the captured image and a feature vector is generated. This feature vector is fed as input to an Artificial Neural Network which is trained to recognize the coins.
An Automated Coin Recognition System using Circlet Transform - The main aim of the project was to build a coin recognition system to recognize Indian denomination coins using Circlet transform. The image of the coin was captured using a camera and Circlet transform was applied on these images to identify the circles. From these circles the GLCM features were extracted and a feature vector was generated which was used to train an Artificial Neural Network to recognize the coins.


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Lorem Ipsum is simply dummy text of the printing and typesetting
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Choose from a selection of tastilicious toppings to create your own pizza


Off to see Nutcracker at OBT with tickets gotten in white elephant gift exchange. Thanks Steven!
12/24/2009, 10:40:13 AM
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Off to see Nutcracker at OBT with tickets gotten in white elephant gift exchange. Thanks Steven!
12/24/2009, 10:40:13 AM
Favs: 0
Retweets: 0
link


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#1 of 15


A* Search
Problem Statement
Given
- A map “assets/elevation.data” which provides the elevation of each point on the map at a pixel resolution;
- A set of no-go areas “assets/overrides.data”, i.e., locations which are not driveable such as rivers or marshes;
Three locations on the map:
- Initial location of the vehicle (i.e., Location A);
- First location of interest which the vehicle must drive to (i.e., Location B)
- Second location of interest which the vehicle must drive to from A (i.e., Location C)
- That is: Requested Journey: A → B → C
Find
- The shortest driveable path to go from A → B → C;
- Time required to drive along such a path in nominal time
- Total distance travelled along A → B → C in nominal terms.
Assume:
- The vehicle “rover” can travel 1 unit (specifically, 1 pixel) in 1 unit of time
- The vehicle “rover” can only travel (a) forward (b) reverse (c) along diagnals
- The vehicle’s “rover’s”engine produces constant power.
Optimize:
- Time to search the path;
- Distance travelled and corresponding time required.
Summary of Solution
Algorithm Used: A*
Heuristics: Euclidean Measure
Wallclock Time:~7.16s. Measured only for computing all paths. Details below.
RAM Usage:Depends on the architecture of the target processor.
A summary of computation is provided at the terminal like so:
Note
- The time reported in the summary is the ‘nominal-time’ as mentioned in the problem statement (i.e., reported travel time is normalized to ‘island-time’)
- The distance is reported in terms of ‘nominal-units’ as mentioned in the problem statement.
- The reported computation time is for a tunable parameter “weight” set to 1.0 (from rover’s initial location to the location of the bachelor, and 10.0 for the path between the bachelor’s location to the wedding). See the section of Heuristics for more details. Weights greater than 1.0 leads to increasingly suboptimal paths (i.e., A* optimality guarantee is violated increasingly), but decrease computation time.
- The final path also depends on the regions prohibited from travel, as decided by the masks (e.g., OF_WATER_BASIN) as provided in the setup.
Design Overview
Entry Point for Execution: main.cpp
Step 1
Loading of Elevation and Override data is performed in parallel in order to reduce the overall computation time:
Step 2
The following paths are computed in parallel:
- From Rover’s initial location to the location of the bachelor;
From the location of the bachelor to the location of the wedding
Step 3
The overall time to compute the paths is estimated by a call to chrono library like so:
(before launching the first thread that computes the path from the Rover’s initial location to the location of the bachelor.
The overall time required to compute the paths is then deduced like so:
Detailed Design
Attempt was made to keep the overall solution as modular as possible.
Specifically:
- The call to the solver is made in “main.cpp” by launching the “SearchPath” function with the necessary paramters. See “SearchPath.hpp” for more details about parameters.
- The “SearchPath” itself uses the class “Astar” for computing the paths. See “AStar.hpp” for details about the class.
Therefore, the “SearchPath” function wrapper encapsulates the core A* algorithm, enabling simultaneous searches for multiple paths, as implemented in this project.
Overview of Software Components
- Wrapper “SearchPath” encapsulates the A* path search algorithm, and initializes a Astar object with the necessary parameters. See the “SearchPath.hpp” for details.
- Class AStar: Provides the core functions required to perform path search using A* heuristic. The choice of A* was motivated by Sebastian Thrun’s lecture in the third semester of “Self-Driving Car Nano-Degree Program”, and by the fact that the algorithm was successfully deployed on “Junior” autonomous vehicle from Stanford University in DARPA’s Urban Challenge. See “AStar.hpp” for details on the class itself.
- Class “Node”: Provides a convenient abstraction to express the location on the map. Currently supports only two coordinates <x,y>. Provides necessary operators (e.g., equality) to compare locations, as required by the A* algorithm.
- Class Heuristics: Provides functions that may be used to compute the heuristic (“h”) as required by the A* algorithm. Currently, only Euclidean Distance measure is provided. All algorithms are required to be optimistic (i.e., never overestimate the true distance between two points) by A*. Therefore, it is possible to just recompute paths using a different heuristic cost function without requiring any modifications to either the wrapper “SearchPath”, or the core class “Astar”.
- Class CostGrid: Templated class provding matrix-like abstraction, together with convenient access functions. Used by “Astar” to store various data.
- Various Unit Tests as part of the development process.
Execution
- Parallelism: Search for paths from Rover’s initial position to the location of the bachelor, and from the location of the bachelor to the location of the wedding are computed in parallel.
- Parallelism: Search for all explorable neighbors are also in parallel:
Tunables
Weight: A tunable parameter “weight” is introduced which forces the path-search to possibly select less favorable paths but with reduced computation time. The provided implementation has:
- Weight = 1.0, for estimating the path between Rover’s initial position to the location of the bachelor;
- Weight = 10.0, for estimating the path between the location of the bachelor and the wedding.
- With these weights, the computation time is 65.61 seconds, compared to ~7 seconds when weights are kept as 100.0 for both path searches.
Mask: The choice of regions where the Rover is prohibited can be supplied by setting the mask like so in main.cpp:
Heuristics
- Distance Estimation: Once the final path is computed as a sequence of coordinates, the total distance is estimated by adding the Euclidean distance between two successive coordinates, and accumulating the distance.
Time Estimation:The following heuristic is followed:
- For movement between two points on the map with no net change in elevation: t = d (island-seconds), where d is the island-distance travelled.
- For movement between two points on the map with a net change in elevation of h, t = d/(1-sin(θ)), where θ = tan-1(h/d). This heuristic assumes that the force generated by the Rover’s engine remains constant throughout the journey. The scaling factor of 1-sin(θ) is based on the notion that effective force when going up an elevation with grade θ is F.sin(θ), where F is the constant force generated by the Rover’s engines.
Notes
- By intent,the time required to transform the path computed by AStar class to the format suitable for use with the visualizer is not counted, as this step does not form a core of the path-search. The provided transformation steps in “main.cpp” are mainly done to reduce the overall time to print the final bitmap.
- The A* algorithm is described in Semester 3 of “Self Driving Car Nano-Degree Program”.
Final Result
(Provided for reference. Generated by the executable)
Related Summary:
Trip Distance Time
Rover to Bachelor 2508.59 3240.93
Bachelor to Wedding 1760.88 2287.81
Total Wallclock Time Required for Computation: 221.87 s.
Corresponding weights:
1. weight: 1.0: Rover’s Initial Position to the Bachelor’s Location
2. weight: 10.0: Bachelor’s location to the location of the wedding.


Azure Cloud is a cloud service that allows you to build, run, and manage applications across devices. In this case, Azure Cloud will be hosting the website you are creating.
The only thing you have to do is create an Azure account. The main tutorial will go over the necessary steps needed to deploy your website to the cloud.
Create your Azure account here.Optionally, if you would like to get a feel for working with Azure with Docker, you can complete the tutorials below.


--- date: 2013-11-12 15:00:05 author: Colene Chow title: "PhoneGap Day EU 2013: Tracking Daily App Downloads/Revenues" format: html tags: - PhoneGap Day - Community - Event ---
Thank you to everyone who attended PhoneGap Day EU. We'll be rolling out all the videos over the coming days for those who weren't able to attend.
First up is Vincent Hoogsteder, CEO and co-founder of Distimo, talking about tracking daily downloads and revenues from any app. Vincent shares Distimo's findings, including what is working for top-selling apps.


Hunters kill 10 elk in Wisconsin's second hunt
MADISON, Wis. - Wisconsin wildlife officials say hunters killed 10 elk in Wisconsin's second elk season.
The Department of Natural Resources set a 10-bull limit for the season, which ran from Oct. 12 to Nov. 10 in Ashland, Bayfield, Price and Sawyer counties.
The department says hunters authorized by the state killed five bulls. Ojibwe tribal hunters killed five.
More than 23,000 Wisconsin residents submitted a $10 application in hopes of winning one of four state tags in a drawing. About 2,500 more bought a ticket in hopes of winning the fifth tag in a Rocky Mountain Elk Foundation raffle.
Seven dollars from every application fee as well as raffle proceeds will go to elk management and research in Wisconsin.
The 2020 elk hunt application period is expected to run from March 1 through May 31.


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Welcome to FridgeWords
Unleash your creativity by composing short poems from a limited set of words! Simply drag the magnets around the virtual fridge until you've written something awesome :)
Tips:
Drop magnets onto other magnets to quickly snap them together.
Refresh the page to generate a batch of new words.


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This is your data analytics dashboard. It shows the information of the selected user.
Sum of Created Shootouts
Today's Shootout Participations
Hits Probability


ToMCAT Study
General instructions:
This section of the study has two speech recording tasks. For each recording task, when you are ready, you will need to:
- Add your ID number in the text box provided. Note that the recording will not begin without it. If you are unsure of your ID number, please contact a member of the research team to assist you.
- Press the ‘Start Recording’ button to begin each recording.
- Give permission to the browser to record audio, if prompted.
- Press the ‘Stop Recording’ button to end each task, once you are finished.
Please go ahead and click ‘Next’ to move on to the first task. Next


Open States Documentation: http://docs.openstates.org/en/latest/
Conversion of state legislative scrapers (to a framework called 'pupa') is being tracked here.
Add your GitHub account name to the "Checked Out To" field of this spreadsheet to claim work on a state. (Note: the spreadsheet auto-saves.)
The site uses a Google Sheet for the underlying data and is adapted by Marjorie Roswell from jlord's Fork-n-go site.


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| LuaFunctionArgs Constructor | Constructs a new LuaFunctionArgs object from the given LUA state. You obtain this state via the parameter of your callback routine. |
| ArgumentCount | Returns the number of arguments |
| Arguments | Returns a global array containing all arguments for the function. |
| Item | Retrieves the argument with the given index. |
| ReturnValues | Sets or retrieves a list of objects that can be filled with return values. |
| Stack | Returns the Lua stack associated with the callback. |
| State | Returns the LUA object associated with the callback. |
| EndMethod | Finalizes a LUA callback routine by pushing the return values on the stack and returns the amount of return values. |
| Equals (inherited from Object) | |
| GetArgumentType | Returns the type of the argument specified via the index. |
| GetHashCode (inherited from Object) | |
| GetType (inherited from Object) | |
| ToString (inherited from Object) |


For example, when a client requests a ticket from an ESX Server, the returned ticket
may omit the optional host and port. In such a case, the client establishes an
out-of-band ticketed connection to the same server host and on the same port on
which it made the connection to request the ticket. If this request is
made to the VirtualCenter server, but the server does not provide the required
service directly, then the server provides a hostname and port for a server that
accepts the ticketed connection and provides the service.
|
Name
|
Type
|
Description
|
| host | xsd:string |
The name of the host providing the service for which the ticket applies. If
omitted, then the client uses the host name for the server that issued the ticket.
|
| port | xsd:int |
Access to some services is made possible by connecting to a port on a
server. If the service for which a ticket is issued is available on a
particular port, that port number is specified with this property. If
omitted, except in the case of connecting to CIM interfaces, the port
number for the service that issued the ticket is used. In the case of
connecting to a CIM interface the standard well known port for the
particular service will be used for the connection.
|
| service | xsd:string |
The name of the service to which to connect.
|
| serviceVersion | xsd:string |
A dot-separated string identifying the service protocol version. For example, 1.0
is used for NFC hosted by vpxa on ESX 2.5, and 1.1 is used for
NFC hosted by hostd on ESX 3.0.
|
| sessionId | xsd:string |
An identifying string for the session created for the ticketed connection. This
is used by the host service to identify the operations permitted within the
session.
|
| sslThumbprint | xsd:string |
The expected thumbprint of the SSL cert of the host to which
we are connecting.
Since VI API 2.5
|
|
Properties inherited from DynamicData |
| None |


Luntclipse is Eclipse plugin that provides functionality for working with builds. It is possible to watch status of any build or trigger a build in any build schedule. Luntclipse communicates with Luntbuild through Hessian web service protocol and HTTP (log detail). Luntclipse possibilities are limited by range of APIs exported by Luntbuild . Currently Luntclipse supports all functionality offered by Luntbuild with exception of User management, Luntbuild properties management and Import/Export.


Heading
Select
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Wallaby
Wallaby, again
Paragraph 1
I'm "Paragraph 2"
Paragraph 3
Python Package Index (PyPI)
Python.org
Input 1
Input 2
Label with no input
I've read the "T's & C's"
Nested checkbox
Checkbox with
nested element
in label
Add paragraph
I'm a paragraph adder


Current Legislation
All Legislation
All Sources
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Members
Congressional Record
Committee Reports
Nominations
Treaty Documents
House Communications
Senate Communications
GO
Copied!!!


Given a valid region name, return a boto.sns.connection.SNSConnection.
| Type: | str |
|---|---|
| Parameters: | region_name – The name of the region to connect to. |
| Return type: | boto.sns.connection.SNSConnection or None |
| Returns: | A connection to the given region, or None if an invalid region name is given |
Get all available regions for the SNS service.
| Return type: | list |
|---|---|
| Returns: | A list of boto.regioninfo.RegionInfo instances |
Amazon Simple Notification Service Amazon Simple Notification Service (Amazon SNS) is a web service that enables you to build distributed web-enabled applications. Applications can use Amazon SNS to easily push real-time notification messages to interested subscribers over multiple delivery protocols. For more information about this product see `http://aws.amazon.com/sns`_. For detailed information about Amazon SNS features and their associated API calls, see the `Amazon SNS Developer Guide`_.
We also provide SDKs that enable you to access Amazon SNS from your preferred programming language. The SDKs contain functionality that automatically takes care of tasks such as: cryptographically signing your service requests, retrying requests, and handling error responses. For a list of available SDKs, go to `Tools for Amazon Web Services`_.
Adds a statement to a topic’s access control policy, granting access for the specified AWS accounts to the specified actions.
| Parameters: |
|
|---|
Get properties of a Topic
| Parameters: |
|---|
The CreatePlatformApplication action creates a platform application object for one of the supported push notification services, such as APNS and GCM, to which devices and mobile apps may register. You must specify PlatformPrincipal and PlatformCredential attributes when using the CreatePlatformApplication action. The PlatformPrincipal is received from the notification service. For APNS/APNS_SANDBOX, PlatformPrincipal is “SSL certificate”. For GCM, PlatformPrincipal is not applicable. For ADM, PlatformPrincipal is “client id”. The PlatformCredential is also received from the notification service. For APNS/APNS_SANDBOX, PlatformCredential is “private key”. For GCM, PlatformCredential is “API key”. For ADM, PlatformCredential is “client secret”. The PlatformApplicationArn that is returned when using CreatePlatformApplication is then used as an attribute for the CreatePlatformEndpoint action. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: |
|
|---|
The CreatePlatformEndpoint creates an endpoint for a device and mobile app on one of the supported push notification services, such as GCM and APNS. CreatePlatformEndpoint requires the PlatformApplicationArn that is returned from CreatePlatformApplication. The EndpointArn that is returned when using CreatePlatformEndpoint can then be used by the Publish action to send a message to a mobile app or by the Subscribe action for subscription to a topic. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: |
|
|---|
The DeleteEndpoint action, which is idempotent, deletes the endpoint from SNS. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: | endpoint_arn (string) – EndpointArn of endpoint to delete. |
|---|
The DeletePlatformApplication action deletes a platform application object for one of the supported push notification services, such as APNS and GCM. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: | platform_application_arn (string) – PlatformApplicationArn of platform application object to delete. |
|---|
Get list of all subscriptions.
| Parameters: | next_token (string) – Token returned by the previous call to this method. |
|---|
Get list of all subscriptions to a specific topic.
| Parameters: |
|---|
| Parameters: | next_token (string) – Token returned by the previous call to this method. |
|---|
The GetEndpointAttributes retrieves the endpoint attributes for a device on one of the supported push notification services, such as GCM and APNS. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: | endpoint_arn (string) – EndpointArn for GetEndpointAttributes input. |
|---|
The GetPlatformApplicationAttributes action retrieves the attributes of the platform application object for the supported push notification services, such as APNS and GCM. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: | platform_application_arn (string) – PlatformApplicationArn for GetPlatformApplicationAttributesInput. |
|---|
Get attributes of a Topic
| Parameters: | topic (string) – The ARN of the topic. |
|---|
The ListEndpointsByPlatformApplication action lists the endpoints and endpoint attributes for devices in a supported push notification service, such as GCM and APNS. The results for ListEndpointsByPlatformApplication are paginated and return a limited list of endpoints, up to 100. If additional records are available after the first page results, then a NextToken string will be returned. To receive the next page, you call ListEndpointsByPlatformApplication again using the NextToken string received from the previous call. When there are no more records to return, NextToken will be null. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: |
|---|
The ListPlatformApplications action lists the platform application objects for the supported push notification services, such as APNS and GCM. The results for ListPlatformApplications are paginated and return a limited list of applications, up to 100. If additional records are available after the first page results, then a NextToken string will be returned. To receive the next page, you call ListPlatformApplications using the NextToken string received from the previous call. When there are no more records to return, NextToken will be null. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: | next_token (string) – NextToken string is used when calling ListPlatformApplications action to retrieve additional records that are available after the first page results. |
|---|
Get properties of a Topic
| Parameters: |
|
|---|
Removes a statement from a topic’s access control policy.
| Parameters: |
|---|
The SetEndpointAttributes action sets the attributes for an endpoint for a device on one of the supported push notification services, such as GCM and APNS. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: |
|---|
endpoint. SNS does not use this data. The data must be in UTF-8 format and less than 2KB.
Message Processor will set this to false when a notification service indicates to SNS that the endpoint is invalid. Users can set it back to true, typically after updating Token.
an app and mobile device. This is returned from the notification service when an app and mobile device are registered with the notification service.
The SetPlatformApplicationAttributes action sets the attributes of the platform application object for the supported push notification services, such as APNS and GCM. For more information, see `Using Amazon SNS Mobile Push Notifications`_.
| Parameters: |
|---|
service. For APNS/APNS_SANDBOX, PlatformCredential is “private key”. For GCM, PlatformCredential is “API key”. For ADM, PlatformCredential is “client secret”.
service. For APNS/APNS_SANDBOX, PlatformPrincipal is “SSL certificate”. For GCM, PlatformPrincipal is not applicable. For ADM, PlatformPrincipal is “client id”.
notifications should be sent.
notifications should be sent.
notifications should be sent.
notifications should be sent upon Direct Publish delivery failure (permanent) to one of the application’s endpoints.
Get attributes of a Topic
| Parameters: |
|---|
Subscribe to a Topic.
| Parameters: |
|
|---|
Subscribe an SQS queue to a topic.
This is convenience method that handles most of the complexity involved in using an SQS queue as an endpoint for an SNS topic. To achieve this the following operations are performed:
| Parameters: |
|
|---|


{% extends 'base.html' %} {% block title %}{% endblock %} {% load staticfiles %} {% block body %} Pick Up Home Delivery PICK UP Order online or call us on<PHONE_NUMBER>0 between 10:00AM - 9:00PM. We will send you confirmation as soon as we can. Opening Hours: Lunch : 11:00 AM - 3:30 PM Dinner : 6:30 AM - 10:30 PM HOME DELIVERY Order online or call us on<PHONE_NUMBER>0 between 10:00AM - 9:00PM. We will send you confirmation as soon as we can. MY ORDER 1 × Paneer Tandoori     ₹150 1 × Paneer Tandoori     ₹150 1 × Paneer Tandoori     ₹150 Sub Total: ORDER NOW {% endblock %}


Split text into sentences with a `vanilla` rule based approach (i.e working ~95% of the time).
{{textContent | tokenize | json}}


Evening 10 Series 2019 Event 9
| Sul 4 |
04 June 19 |
|
10 |
miles |
| Name |
Position |
Road bike |
Actual Time |
Avg. mph |
| |
|
|
|
|
| Jordan Peacock |
1 |
|
00:21:24 |
28.04 |
| Matt Plews |
2 |
|
00:24:07 |
24.88 |
| Michael
Burke |
3 |
1 |
00:25:17 |
23.73 |
| Lawrence
Cox |
4 |
|
00:25:21 |
23.67 |
| Adrian
Killworth |
5 |
|
00:25:26 |
23.59 |
| Jonathan
Durnin |
6 |
|
00:25:34 |
23.47 |
| Julian
Middleton |
7 |
|
00:26:36 |
22.56 |
| Linda
Hubbard |
8 |
|
00:26:59 |
22.24 |
| Chris
Dainty |
9 |
|
00:27:14 |
22.03 |
| Matthew
Vallins |
10 |
2 |
00:28:16 |
21.23 |
| Mark
Chapman |
11 |
3 |
00:28:37 |
20.97 |
| Jennifer
Clegg |
12 |
|
00:29:28 |
20.36 |
| Stewart
Holland |
13 |
4 |
00:29:30 |
20.34 |
| Tom Evans |
14 |
|
00:31:34 |
19.01 |
| Debbie
Ward |
15 |
5 |
00:35:46 |
16.78 |
|
|
|
|
|


Wouldn't it be great if...
- The browser requested the optimum-sized image, looking at the width of the container before any image requests are made.
- Retina support is detected before any images are requested, and retina images are loaded where possible.
- As the viewport is resized, the images get replaced with bigger ones suited to the new container width.
Oh yer, well that totally happens!
Small (width 25%)
Medium (width 50%)
Large (width 90%)
For full docs, check out the README


Before Change
while True:
score, qid = next(sys.stdin).split()
features = next(sys.stdin).split()
sys.stdout.write(qid + "\t" + " ".join(features[0:n_features]) + "\n")
except StopIteration:
return
except IOError as e:
After Change
reverse=True,
key=lambda f: abs(f[1])
)[:n_features]
feature_str = " ".join(["{}:{:.2f}".format(name, score) for name, score in features])
sys.stdout.write(qid + "\t" + feature_str + "\n")
except StopIteration:
return
except IOError as e:


| Jump to DART Documentation Main Index |
DART interface module for the Lorenz-05 models II and III. The 16 public interfaces are standardized for all DART compliant models. These interfaces allow DART to advance the model, get the model state and metadata describing this state, find state variables that are close to a given location, and do spatial interpolation for model state variables.
The reference for these models is Lorenz, E.N., 2005: Designing chaotic models. J. Atmos. Sci., 62, 1574-1587.
Model II is a single-scale model, similar to Lorenz 96, but with spatial continuity in the waves. Model III is a two-scale model. It is fundamentally different from the Lorenz 96 two-scale model because of the spatial continuity and the fact that both scales are projected onto a single variable of integration. The scale separation is achived by a spatial filter and is therefore not perfect (i.e. there is leakage). The slow scale in model III is model II, and thus model II is a deficient form of model III. The basic equations are documented in Lorenz (2005) and also in the model_mod.f90 code. The user is free to choose model II or III with a Namelist variable.
This namelist is read from the file input.nml. Namelists start with an ampersand '&' and terminate with a slash '/'. Character strings that contain a '/' must be enclosed in quotes to prevent them from prematurely terminating the namelist.
&model_nml model_size = 960, forcing = 15.00, delta_t = 0.001, space_time_scale = 10.00, coupling = 3.00, K = 32, smooth_steps = 12, time_step_days = 0, time_step_seconds = 3600, model_number = 3 /
| Contents | Type | Description |
|---|---|---|
| model_size | integer | Number of variables in model |
| forcing | real(r8) | Forcing, F, for model |
| delta_t | real(r8) | Non-dimensional timestep |
| space_time_scale | real(r8) | Determines temporal and spatial relationship between fast and slow variables (model III) |
| coupling | real(r8) | Linear coupling between fast and slow variables (model III) |
| K | integer | Determines the wavenumber of the slow variables (K=1, smooth_steps=0 reduces model II to Lorenz 96) |
| smooth_steps | integer | Determines filter length to separate fast and slow scales |
| time_step_days | integer | Arbitrary real time step days |
| time_step_seconds | integer | Arbitrary real time step seconds (could choose this for proper scaling) |
| model_number | integer | 2 = single-scale, 3 = 2-scale. (This follows the notation in the paper.) |
types_mod time_manager_mod oned/location_mod utilities_mod
Optional namelist interface &model_nml may be read from file input.nml.
A note about documentation style. Optional arguments are enclosed in brackets [like this].
integer :: get_model_size
Returns the length of the model state vector as an integer. Settable by namelist, the default is 960.
| model_size | The length of the model state vector. |
real(r8), dimension(:), intent(inout) :: x type(time_type), intent(in) :: time
Advances a model for a single time step using a four-step Runga-Kutta. The time argument is passed in but not used by this model.
| x | State vector of length model_size. |
| time | Specifies time of the initial model state. |
integer, intent(in) :: index_in type(location_type), intent(out) :: location integer, optional, intent(out) :: var_type
Returns metadata about a given element, indexed by index_in, in the model state vector. The location defines where the state variable is located (at present, a variety of simple location models for support of gridpoint models are provided) while the type of the variable (for instance temperature, or u wind component) is returned by var_type. In this model there are no types so it always returns 1.
| index_in | Index of state vector element about which information is requested. |
| location | The location of state variable element. |
| var_type | Returns the type (always 1) of the indexed state variable as an optional argument. |
real(r8), dimension(:), intent(in) :: x type(location_type), intent(in) :: location integer, intent(in) :: itype real(r8), intent(out) :: obs_val integer, intent(out) :: istatus
Given model state, returns the value of variable itype interpolated to a given location.
| x | A model state vector. |
| location | Location to which to interpolate. |
| itype | Integer indexing which type of state variable is to be interpolated. Is ignored for this model since there is only a single type of variable. |
| obs_val | The interpolated value from the model. |
| istatus | Quality control information about the observation of the model state. 0 == successful. |
type(time_type) :: get_model_time_step
Returns the time step (forecast length) of the model; The time step defaults to 1 hour but is settable by namelist.
| var | Smallest time step of model. |
Reads the namelist, allocates space for the state vector, initializes the locations, generates some initial parameters.
A stub routine in this model.
type(time_type), intent(out) :: time
Returns the time at which the model will start if no input initial conditions are to be used. This is used to spin-up the model from rest. Sets time to 0 in this model.
| time | Initial model time. |
real(r8), dimension(:), intent(out) :: x
Sets the entire state variable to the value of the forcing and then slightly perturbs the first element.
| x | Initial conditions for state vector. |
integer :: nc_write_model_atts integer, intent(in) :: ncFileID
Function to write model specific attributes to a netCDF file. At present, DART is using the NetCDF format to output diagnostic information. This is not a requirement, and models could choose to provide output in other formats. This function writes the metadata associated with the model to a NetCDF file opened to a file identified by ncFileID.
| ncFileID | Integer file descriptor to previously-opened netCDF file. |
| ierr | Returns a 0 for successful completion. |
integer :: nc_write_model_vars integer, intent(in) :: ncFileID real(r8), dimension(:), intent(in) :: statevec integer, intent(in) :: copyindex integer, intent(in) :: timeindex
Writes a copy of the state variables to a netCDF file. Multiple copies of the state for a given time are supported, allowing, for instance, a single file to include multiple ensemble estimates of the state.
| ncFileID | file descriptor to previously-opened netCDF file. |
| statevec | A model state vector. |
| copyindex | Integer index of copy to be written. |
| timeindex | The timestep counter for the given state. |
| ierr | Returns 0 for normal completion. |
integer :: ierr integer, intent(in) :: ncFileID real(r8), dimension(:), intent(out) :: statevec integer, intent(in) :: copyindex integer, intent(in) :: timeindex
A general interface routine to read the state vector at a particular time for a particular ensemble member.
| ierr | Returned error code. 0 == normal termination. |
| ncFileID | Integer file descriptor connected to NetCDF file. |
| statevec | State vector. |
| copyindex | Integer index to designate copy to be read. |
| timeindex | Integer index of desired time to be read. |
This interface is essentially untested in the Lorenz 04/05 model. It began life as a stub, but there is so little to it ... TJH 05 Aug 2005.
real(r8), dimension(:), intent(in) :: state real(r8), dimension(:), intent(out) :: pert_state logical, intent(out) :: interf_provided
Given a model state, produces a perturbed model state. This is used to generate initial ensemble conditions perturbed around some control trajectory state when one is preparing to spin-up ensembles. A DART compliant model can choose not to provide an implementation of this algorithm and use the default mechanism in DART by simply returning .false. as a returned value for the interf_provided argument. In this case, DART perturbs the state to generate ensemble members by adding a random sample from a N(0.0, 0.002) distribution independently to each state variable. This model returns .false. for interf_provided and uses the default DART perturbation routine.
| state | State vector to be perturbed |
| pert_state | Perturbed state vector is returned |
| interf_provided | Returns false to have DART perturb state |
The Lorenz 04/05 model relies implicitly on the default DART perturbation mechanism, i.e. this routine always returns .false..
type(get_close_type), intent(inout) :: gc real(r8), intent(in) :: maxdist
Pass-through to the 1-D locations module. See get_close_maxdist_init() for the documentation of this subroutine.
type(get_close_type), intent(inout) :: gc integer, intent(in) :: num type(location_type), intent(in) :: obs(num)
Pass-through to the 1-D locations module. See get_close_obs_init() for the documentation of this subroutine.
type(get_close_type), intent(in) :: gc type(location_type), intent(in) :: base_obs_loc integer, intent(in) :: base_obs_kind type(location_type), intent(in) :: obs(:) integer, intent(in) :: obs_kind(:) integer, intent(out) :: num_close integer, intent(out) :: close_ind(:) real(r8), optional, intent(out) :: dist(:)
Pass-through to the 1-D locations module. See get_close_obs() for the documentation of this subroutine.
real(r8), dimension(:), intent(in) :: ens_mean
A NULL INTERFACE in this model.
| ens_mean | State vector containing the ensemble mean. |
| filename | purpose |
|---|---|
| input.nml | to read the model_mod namelist |
| preassim.nc | the time-history of the model state before assimilation |
| analysis.nc | the time-history of the model state after assimilation |
| dart_log.out [default name] | the run-time diagnostic output |
| dart_log.nml [default name] | the record of all the namelists actually USED - contains the default values |
| Routine | Message | Comment |
|---|---|---|
| nc_write_model_atts nc_write_model_vars |
Various netCDF-f90 interface error messages | From one of the netCDF calls in the named routine |
none at this time
none at this time
DART software - Copyright UCAR. This open source software is provided by UCAR, "as is", without charge, subject to all terms of use at http://www.image.ucar.edu/DAReS/DART/DART_download


The Uttarayani fairs are often used as platforms by social and political workers and the Bageshwar fair specially has played an important role in all the local movements, as also in the freedom movement. In 1921 activists had given a call for the eventual eradication of the system of bonded labour known as coolie begar. In 1929 Gandhi ji came to Bageshwar. Many freedom fighters and folk singers have been closely associated with the Bageshwar fair. Even today the fair attracts a large number of people, who spend the whole night dancing and singing Jhoras, Chancharis and Bairas.


Often a communication with the same argument list is repeatedly executed within the inner loop of a parallel computation. In such a situation, it may be possible to optimize the communication by binding the list of communication arguments to a persistent communication request once and, then, repeatedly using the request to initiate and complete messages. The persistent request thus created can be thought of as a communication port or a ``half-channel.'' It does not provide the full functionality of a conventional channel, since there is no binding of the send port to the receive port. This construct allows reduction of the overhead for communication between the process and communication controller, but not of the overhead for communication between one communication controller and another. It is not necessary that messages sent with a persistent request be received by a receive operation using a persistent request, or vice versa.
A persistent communication request is created using one of the four following calls. These calls involve no communication.
MPI_SEND_INIT(buf, count, datatype, dest, tag,
comm, request)
[ IN buf] initial address of send buffer (choice)
[ IN count] number of elements sent (integer)
[ IN datatype] type of each element (handle)
[ IN dest] rank of destination (integer)
[ IN tag] message tag (integer)
[ IN comm] communicator (handle)
[ OUT request] communication request (handle)
int MPI_Send_init(void* buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm, MPI_Request *request)
MPI_SEND_INIT(BUF, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR)
<type> BUF(*)
INTEGER REQUEST, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR
Creates a persistent communication request for a standard mode send operation, and binds to it all the arguments of a send operation.
MPI_BSEND_INIT(buf, count, datatype, dest, tag,
comm, request)
[ IN buf] initial address of send buffer (choice)
[ IN count] number of elements sent (integer)
[ IN datatype] type of each element (handle)
[ IN dest] rank of destination (integer)
[ IN tag] message tag (integer)
[ IN comm] communicator (handle)
[ OUT request] communication request (handle)
int MPI_Bsend_init(void* buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm, MPI_Request *request)
MPI_BSEND_INIT(BUF, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR)
<type> BUF(*)
INTEGER REQUEST, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR
Creates a persistent communication request for a buffered mode send.
MPI_SSEND_INIT(buf, count, datatype, dest, tag,
comm, request)
[ IN buf] initial address of send buffer (choice)
[ IN count] number of elements sent (integer)
[ IN datatype] type of each element (handle)
[ IN dest] rank of destination (integer)
[ IN tag] message tag (integer)
[ IN comm] communicator (handle)
[ OUT request] communication request (handle)
int MPI_Ssend_init(void* buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm, MPI_Request *request)
MPI_SSEND_INIT(BUF, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR)
<type> BUF(*)
INTEGER COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR
Creates a persistent communication object for a synchronous mode send operation.
MPI_RSEND_INIT(buf, count, datatype, dest, tag,
comm, request)
[ IN buf] initial address of send buffer (choice)
[ IN count] number of elements sent (integer)
[ IN datatype] type of each element (handle)
[ IN dest] rank of destination (integer)
[ IN tag] message tag (integer)
[ IN comm] communicator (handle)
[ OUT request] communication request (handle)
int MPI_Rsend_init(void* buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm, MPI_Request *request)
MPI_RSEND_INIT(BUF, COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR)
<type> BUF(*)
INTEGER COUNT, DATATYPE, DEST, TAG, COMM, REQUEST, IERROR
Creates a persistent communication object for a ready mode send operation.
MPI_RECV_INIT(buf, count, datatype, source, tag,
comm, request)
[ OUT buf] initial address of receive buffer (choice)
[ IN count] number of elements received (integer)
[ IN datatype] type of each element (handle)
[ IN source] rank of source or MPI_ANY_SOURCE (integer)
[ IN tag] message tag or MPI_ANY_TAG (integer)
[ IN comm] communicator (handle)
[ OUT request] communication request (handle)
int MPI_Recv_init(void* buf, int count, MPI_Datatype datatype, int source, int tag, MPI_Comm comm, MPI_Request *request)
MPI_RECV_INIT(BUF, COUNT, DATATYPE, SOURCE, TAG, COMM, REQUEST, IERROR)
<type> BUF(*)
INTEGER COUNT, DATATYPE, SOURCE, TAG, COMM, REQUEST, IERROR
Creates a persistent communication request for a receive operation. The argument buf is marked as OUT because the user gives permission to write on the receive buffer by passing the argument to MPI_RECV_INIT.
A persistent communication request is inactive after it was created --- no active communication is attached to the request.
A communication (send or receive) that uses a persistent request is initiated by the function MPI_START.
MPI_START(request)
[ INOUT request] communication request (handle)
int MPI_Start(MPI_Request *request)
MPI_START(REQUEST, IERROR)
INTEGER REQUEST, IERROR
The argument, request, is a handle returned by one of the previous five calls. The associated request should be inactive. The request becomes active once the call is made.
If the request is for a send with ready mode, then a matching receive should be posted before the call is made. The communication buffer should not be accessed after the call, and until the operation completes.
The call is local, with similar semantics to the nonblocking communication operations described in section Nonblocking communication . That is, a call to MPI_START with a request created by MPI_SEND_INIT starts a communication in the same manner as a call to MPI_ISEND; a call to MPI_START with a request created by MPI_BSEND_INIT starts a communication in the same manner as a call to MPI_IBSEND; and so on.
MPI_STARTALL(count, array_of_requests)
[ IN count] list length (integer)
[ INOUT array_of_requests] array of requests (array of handle)
int MPI_Startall(int count, MPI_Request *array_of_requests)
MPI_STARTALL(COUNT, ARRAY_OF_REQUESTS, IERROR)
INTEGER COUNT, ARRAY_OF_REQUESTS(*), IERROR
Start all communications associated with requests in
array_of_requests. A call to
MPI_STARTALL(count, array_of_requests) has the
same effect as calls to
MPI_START (&array_of_requests[i]),executed for i=0 ,..., count-1, in some arbitrary order.
A communication started with a call to MPI_START or MPI_STARTALL is completed by a call to MPI_WAIT, MPI_TEST, or one of the derived functions described in section Multiple Completions . The request becomes inactive after successful completion of such call. The request is not deallocated and it can be activated anew by an MPI_START or MPI_STARTALL call.
A persistent request is deallocated by a call to MPI_REQUEST_FREE (Section Communication Completion ).
The call to MPI_REQUEST_FREE can occur at any point in the program after the persistent request was created. However, the request will be deallocated only after it becomes inactive. Active receive requests should not be freed. Otherwise, it will not be possible to check that the receive has completed. It is preferable, in general, to free requests when they are inactive. If this rule is followed, then the functions described in this section will be invoked in a sequence of the form,
where * indicates zero or more repetitions. If the same communication object is used in several concurrent threads, it is the user's responsibility to coordinate calls so that the correct sequence is obeyed.
A send operation initiated with MPI_START can be matched with any receive operation and, likewise, a receive operation initiated with MPI_START can receive messages generated by any send operation.


Implements a method for identifying subgroups with superior response relative to the overall sample.
| Version: | 1.0.0 |
| Imports: | methods, mlbench, hash, party, rpart, survival, survRM2, stats, modeltools, utils, parallel |
| Published: | 2018-10-30 |
| Author: | Chakib Battioui, Brian Denton, Lei Shen |
| Maintainer: | Brian Denton <denton_brian_david at lilly.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | ChangeLog |
| CRAN checks: | TSDT results |
| Reference manual: | TSDT.pdf |
| Package source: | TSDT_1.0.0.tar.gz |
| Windows binaries: | r-devel: TSDT_1.0.0.zip, r-release: TSDT_1.0.0.zip, r-oldrel: TSDT_1.0.0.zip |
| OS X binaries: | r-release: TSDT_1.0.0.tgz, r-oldrel: TSDT_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=TSDT to link to this page.


---
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title: Lean Prover Zulip Chat Archive
permalink: 116395maths/85635Bayestheoremfuturedirections.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/116395-maths/topic/Bayes.20theorem.20.2B.20future.20directions.html


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Single place to seek for viz assistance.
Ask your viz query. Get top suggestions.
Answers with image and code snippet if available.
Save users' time and effort to search.


refraction_render.renderers.ray_diagram¶
-
refraction_render.renderers.
ray_diagram
(ax, calc, h_obs, d, angles, heights=None, style='sphere_top', eye_level=True, linewidth_rays=0.2, linewidth_earth=0.2, R0=6371008, h_min=0.01)[source]¶ Side profile view showing the rays trajectories.
Parameters: - ax: matplotlib Axes object
this function plots lines on a graph, you can specify which graph to plot to by passing in the axes object for the graph you want to plot to.
- calc: calcs object
object which can be used to calculate the trajectory of light rays
- h_obs: float
height of renderer in meters
- d: array_like, (N,)
list of values to evaluate ray positions at for ray diagram, must be sorted in ascending order.
- angles: array_like, (M,)
list of initial angles for the rays, in degrees
- heights: array_like, (N,), optional
list of values which represent the elevation profile along ray trajectory
- style: str, optional
style to plot the graph. “flat”: plot rays on flat plane, “sphere_top”: plot rays as if the earth is filling away from the observer, “sphere_side”: plot rays with the ‘bulge’ in the middle.
- eye_level: bool, optional
color the ray which is closest to eye level (0 degrees initial angle) orange.
- linewidth_rays: float, optional
linewidth used for plotting rays in diagram
- linewidth_earth: float, optional
linewidth used for plotting surface of the earth, both water and land.
- h_min: float, optional
minimum values which should count as water when calculating hit locations.


[gecode-users] Debian packages for Gecode
Guido Tack
tack at ps.uni-sb.de
Thu Jan 19 10:44:31 CET 2006
Hi!
We just noticed that Gecode has already appeared in Debian testing. That's
great! Thanks so much for putting the packages together and uploading them to
Debian!
One thing that I would be extremely interested in is whether the test suite
actually passes on the more exotic platforms, like alpha, arm, ia64, sparc,
etc. It would be really cool if you could add a make test and executing
test/test to the build process. This will slow down the build a lot, but I
think it might be a good idea anyway.
I'll put a note on our download pages that Debian packages are available.
Cheers,
Guido
--
Guido Tack
Programming Systems Lab, Saarland University, Saarbrücken
http://www.ps.uni-sb.de/~tack
More information about the gecode-users
mailing list


Gateway
BOT
12-Jun-19 11:37 AM
[dscrd-hush] <dandy_sandy> i try ti close the ./hush-cli stop ___
error: incorrect rpcuser or rpcpassword (authorization failed)
is there any way to close instead of kill {id}
changed the conf without closing the daemon and did not make a copy of the old .conf
[dscrd-hush] <dukeleto> @dandy_sandy if you don't have the old user/pass, I am not sure
[dscrd-hush] <dukeleto> I have CTRL-C'ed/kill'ed many a full node
[dscrd-hush] <dukeleto> usually it is fine
[dscrd-hush] <dukeleto> rarely it might cause you to reindex when you startup
[dscrd-hush] <dandysandy> @dukeleto yes thats the way i wanted to take if there is no other thx
[dscrd-hush] <dukeleto> If you don't know the correct user/pass, your full node will not listen to your RPC commands
[dscrd-hush] <dukeleto> @dandy_sandy i have accidentally done this before too, it happens
[dscrd-hush] <dukeleto> It would not be good if you had a very busy wallet, like an exchange, and you kill it
[dscrd-hush] <dukeleto> But you have a wallet doing nothing, I imagine
[dscrd-hush] <dukeleto> It's not receiving/sending 50 payments a minute/etc
[dscrd-hush] <dukeleto> @dandy_sandy try a kill -15 instead of kill -9
[dscrd-hush] <dukeleto> that asks the process to gracefully seppuku, instead of forcibly killing it, basically
[dscrd-hush] <dandysandy> yes there will be no big trouble
i have also the komodod running and do not find the hushd in the ps -ax
you think this one is the one to kill:
./komodod -ac_name=HUSH3 -ac_sapling=1.....
[dscrd-hush] <dukeleto> @dandy_sandy yes, that is it. hushd is a wrapper for that command
[dscrd-hush] <dukeleto> @dandy_sandy if you cat ./src/hushd you will see all that stuff
[dscrd-hush] <dukeleto> hushd is a bash script around our own custom komodod
[dscrd-hush] <ComputerGenie - MineHush.com> @dukeleto that feken was hideous when they did it and even worse next to the dragon
[dscrd-hush] <dukeleto> @ComputerGenie - MineHush.com glad that you still have opinions
[dscrd-hush] <dukeleto> i was worried for a second
[dscrd-hush] <ComputerGenie - MineHush.com> LOL
[dscrd-hush] <ComputerGenie - MineHush.com> just adding the explanation for the emoji
[dscrd-hush] <ComputerGenie - MineHush.com> imo, it's like making a super hot-rod out of a Dodge Charger, painting it orange, and then putting a giant '10' on the side and a Canadian flag on the roof


Responsive images with Angular
Responsive image sizes
Support for next gen formats
Optional lazy loading using an IntersectionObserver (if supported by
browser)
Universal SSR friendly
Breakpoints
{{ breakpoint.key }}
ngx picture
{{ pictureDetails$ | async }}


GO and KEGG pathway enrichment analyses for DEGs. Notes: ( A) Chord plot of GO enrichment analysis of up-regulated genes. ( B) Chord plot of GO enrichment analysis of down-regulated genes. ( C) Dot plot of KEGG enrichment analysis of up-regulated genes. ( D) Dot plot of KEGG enrichment analysis of down-regulated genes. Abbreviations: GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.


Pope Francis lands in Bangkok for 4-day visit (Photos)
by Coconuts BangkokPope Francis landed just after noon at Don Mueang International Airport as people lined up along his route into town to welcome the 82-year-old pontiff.
The pope was seen waving from a lowered car window to greet the public while he was on his way to the Apostolic Nunciature Embassy of the Holy See on Sathorn Road.
More than 6,500 police officers have been deployed across the capital to ensure security.
It’s the first time a pope has visited the kingdom in 23 years, during which he will meet the king, prime minister, top Buddhist monk and hold two masses.
Related:
6,500+ cops deployed as Pope Francis arrives in Bangkok
Persecuted Catholics ‘honored’ to glimpse Pope Francis in Thailand
Thai convent weaves ‘beautiful’ robes for Pope Francis visit


In this website, I write devlogs and blogs about my projects and technical topics. This website also serves as the place where my projects' developement and release news exist.


#include <Sound.h>
Class diagram for NativeSoundMix:
Public Members | |||
| virtual void | NativeConstruct () | ||
| virtual void | NativeDestruct () | ||
| virtual void | EnterCritical () | ||
| virtual void | LeaveCritical () | ||
| virtual void | BuildAndWrite ( WaveHeader* hdr, BOOL silence ) | ||
| virtual void | GetNativeSoundCap ( S32* format ) | ||
| virtual BOOL | OpenNativeDevice ( CSound* format ) | ||
| virtual void | BuffersReady () | ||
| virtual void | BuffersUpdated () | ||
| virtual void | CloseNativeDevice () | ||
| virtual BOOL | IsDeviceOpen () |
[virtual]
CSoundMix does not use a contructor. For compatibility with CSoundMix, NativeConstruct is called for object "construction."
Reimplemented from CSoundMix.
[virtual]
CSoundMix does not use a destructor. For compatibility with CSoundMix, NativeDestruct is called for object "destruction."
Reimplemented from CSoundMix.
[virtual]
The sound data needs to be protected is multi-threaded systems. Only one thread can have the critical semaphor. This call requests, and blocks, access to the critical sound semaphor.
Reimplemented from CSoundMix.
[virtual]
BuildAndWrite is passed the WaveHeader to an available buffer. It should call BuildBuffer to repack the buffer and then send the buffer to the hardware device. If silence is true, BuildBuffer should not be called, and BuildAndWrite should write silence to the buffer and send it to the hardware.
BuildAndWrite is called from core code when the device is opened, and called by the Native code when a buffer completes playing.
Reimplemented from CSoundMix.
[virtual]
GetNativeSoundCap gets the best native sound format. Called inside a critical section, when the hardware device is closed. This format is OR'd from the following variables:
sndMono, sndStereo
snd8Bit, snd16Bit
snd5K, snd11K, snd22K, snd44K
Reimplemented from CSoundMix.
[virtual]
Opens the hardware device in the given format. This call should not change CSound* format.
Reimplemented from CSoundMix.
[virtual]
BuffersReady is called when the device is open, the buffers are allocated, and the buffers are filled with data. A signal to start playing sound.
Reimplemented from CSoundMix.
[virtual]
When the buffers are allocated or enlarged, BuffersUpdated is called to inform the native code.
Reimplemented from CSoundMix.
[virtual]
[virtual]
Queries the state of the hardware device. Should be a fast call - it may be prudent to buffer the device state rather than actually asking the device.
Reimplemented from CSoundMix.


A package can import modulr for its own usage. There are then essentially two different and complementary ways to exploit all of the modulr features: for the limited scope of the internals of the package itself and/or for an exported usage.
In this use case, modules are defined and used inside the package’s namespace, without interference with any usage that could be made of modulr outside of the package. Something ressembling the following lines of code should then appear in your ./R
package files:
# File: ./R/init.R
#' @import modulr
NULL
my_package_injector <- get_default_injector()
set_verbosity(0L)
Notice that we are using Roxygen2’s @import
tag here to easily populate the NAMESPACE
file of the package with an appropriate import
field (the @importFrom
tag could also import only a selected subset of exported methods from modulr), so that the prefix modulr::
can be omitted in front of modulr methods (in particular for syntactic sugars like %provides%
and %requires%
, see infra).
It is also important to make sure that this portion of code is loaded before defining and using modules, which is guaranteed by the @include
tag (or by manually specifying a collation order in the NAMESPACE
file), as shown in the following example:
# File: ./R/greetings.R
#' @include init.R
NULL
"hello" %provides% "Hello"
"world" %provides% "World"
"greetings" %requires% list(
hello = "hello",
world = "world"
) %provides% {
paste0(hello, ", ", tolower(world), "!")
}
#' @export
say_hello <- function() {
with_injector(my_package_injector, make("greetings"))
}
Notice the with_injector
wrapper around make("greetings")
in the body of the exported say_hello
function: since say_hello
is suscpetible to be called from outside of the package’s namespace, it is important to specify explicitely that the make
call relies on the package’s default injector captured in the ./R/init.R
file.
It is also possible to use the injector’s get
method:
#' @export
say_hello <- function() {
my_package_injector$get("greetings")
}
Notice that none of the modules is directly exposed by the package:
library(my_package)
(modulr::lsmod())
#> NULL
In this situation, the package is intended to provide the user with a predefined set of modules. The following example shows how to use the .onLoad
hook function to define a module, just before sealing the namespace of the package and processing exports:
# File: ./R/zzz.R
.onLoad <- function(libname, pkgname) {
with_injector(get_default_injector(), {
set_verbosity(0L)
"foobar" %provides% "FOOBAR"
})
invisible(NULL)
}
When the package is loaded, the "foobar"
module is defined within the scope of the default modulr injector situated outside of the package’s namespace. It is then accessible by the user of the package:
library(my_package)
modulr::lsmod()
#> name version storage along type weight calls dependencies uses
#> 1 foobar <NA> in-memory <NA> <NA> <NA> 0 0 0
#> size lines modified
#> 1 152 bytes 2 2018-12-02T16:14:51 UTC
inst/modules
Finally, it is possible to define an entire set of on-disk modules at once in the ./inst/modules
directory. For instance:
# File: ./inst/modules/foo.R
library(modulr)
"foo" %provides% "FOO"
In this case, it is necessary to add the path of the modules
sub-directory of the installed package to the modulr’s root paths. The system.file
function is tailored for this kind of situation:
# File: ./R/zzz.R
.onLoad <- function(libname, pkgname) {
# ...
with_injector(get_default_injector(), {
root_config$set(c(
root_config$get_all()[[1L]],
system.file("modules", package = "my_package")))
})
invisible(NULL)
}
Once the package is loaded, the installed modules
directory is then reachable:
library(my_package)
modulr::make("foo")
#> [2018-12-02T16:14:52 UTC] Resetting modulr state ... OK
#> [2018-12-02T16:14:52 UTC] Defining 'foo' ... OK
#> [2018-12-02T16:14:52 UTC] Making 'foo' ...
#> [2018-12-02T16:14:52 UTC] * Visiting and defining dependencies ...
#> [2018-12-02T16:14:52 UTC] * Constructing dependency graph ... OK
#> [2018-12-02T16:14:52 UTC] DONE ('foo' in 0.018 secs)
#> [1] "FOO"


The original polygon and the clip rectangle.
After clipped by the right clip boundary.
After clipped by the right and bottom clip boundaries.
After clipped by the right, bottom, and left clip boundaries.
After clipped by all four boundaries.
Go back to Steps of polygon-clipping algorithm.