This header file defines a minimal console based game of dice written in C programming language
-The game starts with $100
-You choose how many rounds to play
-Then bet with cash on Suits,Jack and Null spaces of the wheel on which the dice will hit
-A dice is thrown
-If the dice hits the betting suit then you earn the betting cash.
-If the dice hits suits other than the betting one then you lose $10
-If it hits any of the Null spaces which is not bet then you lose bet cash
-If it hits the Jack which is bet then you earn the beting cash + $100 otherwise you earn only the bet cash
-Your cash is doubled if you hit the Bull's Eye
#include< ctype.h> #include< cstdio> #include< cmath> #include< cstdlib> int i,j,cash=100; void wheel(); void game(int r); void game_over(); int suit_bet(); int cash_bet(); int roll_wheel(); int roll_dice(); void wheel_count(int c,int h,int s); void dice_count(int d,int h); int w[9][9]={ {32,32,32,32,2,32,32,32,32}, {32,32,32,3,5,4,32,32,32}, {32,32,5,4,3,6,5,32,32}, {32,4,3,6,5,3,4,6,32}, {2,6,5,4,15,5,3,6,2}, {32,3,6,3,4,5,4,3,32}, {32,32,5,6,3,4,5,32,32}, {32,32,32,4,6,6,32,32,32}, {32,32,32,32,2,32,32,32,32} }; void playDice(){ int round; char e; //game intro printf("\t\t\tWelcome to Roullette\n\n"); //game instruction printf("Game Instructions:\n\n"); printf("Diamond(d)=%c Hearts(h)=%c Clubs(c)=%c Spades(s)=%c Jack(j)=%c Bull's Eye=%c \n",4,3,5,6,2,15); printf("\n-The game starts with $100 \n-You chooses how many rounds to play \n-Then bet with cash on Suits,Jack and Null spaces of the wheel on which the dice will hit \n-A dice is thrown \n-If the dice hits the betting suit then you earn the betting cash.\n"); printf("-If the dice hits suits other than the betting one then you lose $10\n"); printf("-If it hits any of the Null spaces which is not bet then you lose bet cash \n"); printf("-If it hits the Jack which is bet then you earn the beting cash + $100 otherwise you earn only the bet cash \n"); printf("-Your cash is doubled if you hit the Bull's Eye \n"); printf("\n\n"); printf("Press Enter to Start Game"); scanf("%c",&e); if(e=='\n'){ printf("\nThe Roullette Wheel: \n\n"); wheel(); printf("\n\nYour Cash: $%d",cash); printf("\n\nHow many rounds you want to play: "); scanf("%d",&round); printf("\n\nYour Cash : $%d \n",cash); game(round); printf("\n\n"); printf("\t %d rounds completed!! \n\n\tYou Earned Total $%d !!\n\n",round,cash); } else{ printf("\nSorry!!\nYou Entered The Wrong Key!!\n"); } } //game on void game(int r){ int count; for(count=1;count<=r;count++){ int suit,ca,hit,dice; fflush(stdin); suit=suit_bet(); ca=cash_bet(); hit=roll_wheel(); dice=roll_dice(); wheel_count(ca,hit,suit); dice_count(dice,hit); printf("\n"); wheel(); printf("\n\nCash: $%d \nSuit Bet: %c \nCash Bet: $%d \nWheel Hit: %c \nDice: %d\n\n\n",cash,suit,ca,hit,dice); } } //show wheel void wheel(){ for(i=0;i< 9;i++){ for(j=0;j< 9;j++){ printf("%c ",w[i][j]); } printf("\n"); } } //betting on suit int suit_bet(){ char s; int k; printf("Suit Bet: "); s=getchar(); s=tolower(s); switch(s){ case 'h': k=3; break; case 'd': k=4; break; case 'c': k=5; break; case 's': k=6; break; case 'j': k=2; break; case 'n': k=32; break; default: k=0; } return k; } //betting on cash int cash_bet(){ int c; printf("Cash Bet: $"); scanf("%d",&c); return c; } //rolling the wheel int roll_wheel(){ float m,n; int wh1,wh2,res; m=rand()/32768.0; n=rand()/32768.0; wh1=(int) (m*9); wh2=(int) (n*9); res=w[wh1][wh2]; w[wh1][wh2]=249; return res; } //rolling the dice int roll_dice(){ float d; int res; d=rand()/32768.0; res=(int) (d*6)+1; return res; } //cash update form wheel hit void wheel_count(int c,int h,int s){ if(h==s){ if(h==2){ cash=cash+c+100; }else{ cash=cash+c; } } else if(h==3 || h==4 || h==5 || h==6){ cash=cash-10; } else if(h==32){ cash=cash-c; } else if(h==2){ cash=cash+c; } if(s==2 && h!=2){ cash=cash-50; } } //cash update from dice throw void dice_count(int d,int h){ if(h==3 || h==4 || h==5 || h==6){ if(d==6){ cash=cash+20; } } else if(h==15){ cash=2*cash; } else if(h==249){ if(d==6){ cash=cash+20; } } } //game end/over


For example, with the below data: label xxxsome valueyyy You can strip out the xxx...yyy and add a label: prefix with: seesv:seesv -change label "xxx(.*)yyy" "label:$1" Which would give: label label:some value You can also specify a file that holds a number of patterns: seesv:seesv -change columns file:file.txt "" The file is of the form:
pattern1::replace_string1 pattern2::replace_string2e.g.:
(?i).*foo.*::foobar .*value.*::new value


Matcha: The Japanese green tea that packs a considerable amount of caffeine and offers a calming sense of ritual. You don't steep this tea—it's gyokuro green tea that's been ground into a fine powder and whisked with hot water to create a full-bodied, verdant elixir. The linchpin of traditional Japanese tea ceremonies, it's celebrated for its nutritional value as well as its deep vegetal flavor (even when used in cooking).
"I once met a neurosurgeon in Geneva who drinks matcha every time he performs surgery," said Ken Kano, president of Ippodo Tea's U.S. division. He and tea consultant Riichiro Kato came to our test kitchen to demonstrate, step-by-step, how to make the perfect cup of matcha—as well as the different ways to make the deep green tea. Click through and meet your possible new morning ritual.
Meet your matcha accessories: a handmade bamboo whisk (called a chasen), a tea bowl (matcha-chawan), a measuring ladle (chashaku), a tea strainer, and—of course—your matcha powder.
To brew a cup, scoop 1½ ladlefuls (about 2 grams, or 1½ teaspoons) matcha powder into your strainer.
Sift your matcha powder into your tea bowl, swirling the powder around the strainer with your ladle. This will ensure there are no clumps so your tea will be smooth.
WATCH
Tumeric Latte
After you've sifted your powder, it should look like this. Pretty, right?
Pour boiling water (about 2 ounces) into a teacup, then let it sit until it cools down to about 180–190 degrees (about a minute). Carefully pour the hot water into the bowl with the matcha powder.
Using your chasen, whisk to combine your tea. Relax your wrist, then whisk in a gentle circular motion for thin, smooth tea, and in a brisk "M" or "W"-shaped motion for foamy tea. (Fun fact: Smooth and foamy tea both have slightly different scents and flavors.) Whisk for about 10–15 seconds until the tea is bright green.
Carefully pour your matcha into a teacup.
Here's the finished foamy matcha tea. Make sure to drink it right after you've prepared it—the powder will settle at the bottom after a while.
To make extra-thick matcha, scoop 3 ladlefuls of high-grade matcha powder into your strainer and sift. Pour boiling water into a teacup (about 2 ounces), then add half of the water to your powder. Circle back and forth with your whisk, carefully combining the powder with the water. Don't add all the water at one time—it will clump.
Then pour the rest of the water into your tea bowl, and whisk in small gentle circles and rainbow-shaped motions. Whisk until your thick tea is completely smooth, then serve in small teacups.
Here's what your thick matcha will look like. Drink up!


class: center, middle, inverse, title-slide # Tidying your model data ## SISBID 2020
https://github.com/dicook/SISBID
### Di Cook (
<EMAIL_ADDRESS>,
@visnut
)
Heike Hofmann (
<EMAIL_ADDRESS>,
@heike_hh
) ### 07/22-24/2020 --- class: inverse middle # Your turn Turn the `french_fries` data from wide format into a long format with variables `type` and `rating`. ``` # A tibble: 6 x 9 time treatment subject rep potato buttery grassy rancid painty <fct> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 1 1 3 1 2.9 0 0 0 5.5 2 1 1 3 2 14 0 0 1.1 0 3 1 1 10 1 11 6.4 0 0 0 4 1 1 10 2 9.9 5.9 2.9 2.2 0 5 1 1 15 1 1.2 0.1 0 1.1 5.1 6 1 1 15 2 8.8 3 3.6 1.5 2.3 ``` What would we like to find out about this data? --- # What would we like to know? - Is the design complete? - Are replicates like each other? - How do the ratings on the different scales differ? - Are raters giving different scores on average? - Do ratings change over the weeks? Each of these questions involves different summaries of the data. --- # Gathering the french fries ```r ff_long <- gather(french_fries, key = type, value = rating, potato:painty) head(ff_long) # A tibble: 6 x 6 time treatment subject rep type rating <fct> <fct> <fct> <dbl> <chr> <dbl> 1 1 1 3 1 potato 2.9 2 1 1 3 2 potato 14 3 1 1 10 1 potato 11 4 1 1 10 2 potato 9.9 5 1 1 15 1 potato 1.2 6 1 1 15 2 potato 8.8 ``` --- # Long to wide In certain applications, we may wish to take a long dataset and convert it to a wide dataset (perhaps displaying in a table). This is called "spreading" the data. --- # Spread We use the **spread** function from `tidyr` to do this: ```r french_fries_weeks <- spread(ff_long, key = time, value = rating) head(french_fries_weeks) # A tibble: 6 x 14 treatment subject rep type `1` `2` `3` `4` `5` `6` `7` `8` <fct> <fct> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 1 3 1 butt… 0 0.3 0.2 0.1 0.3 1.2 0 0.5 2 1 3 1 gras… 0 0.1 0 0 0 0 0 1.3 3 1 3 1 pain… 5.5 0.3 0 0 1.7 9.5 5.5 3.8 4 1 3 1 pota… 2.9 9 11.8 13.6 14 0.4 2.9 3.5 5 1 3 1 ranc… 0 5.8 6 1.7 0 0 0 0 6 1 3 2 butt… 0 0.5 0.5 0 0.8 1.1 0 0.3 # … with 2 more variables: `9` <dbl>, `10` <dbl> ``` Plot Week 1 against Week 9 in a scatterplot: ```r french_fries_weeks %>% ggplot(aes(x = `1`, y = `9`)) + geom_point() ``` --- # Week 1 vs week 9 ```r french_fries_weeks %>% ggplot(aes(x = `1`, y = `9`)) + geom_point() ```  --- class: inverse middle # Your turn: Do the replicates look like each other? Tackle this by plotting the replicates against each other using a scatterplot. You will need to first gather the data into long form, and then get the replicates spread into separate columns by replicate. --- # Are ratings similar on different scales? - Are ratings similar on the different scales: potato'y, buttery, grassy, rancid and painty? - We need to gather the data into long form, and make plots facetted by the scale. --- # Ratings on the different scales ```r ff.m <- french_fries %>% gather(type, rating, -subject, -time, -treatment, -rep) head(ff.m) # A tibble: 6 x 6 time treatment subject rep type rating <fct> <fct> <fct> <dbl> <chr> <dbl> 1 1 1 3 1 potato 2.9 2 1 1 3 2 potato 14 3 1 1 10 1 potato 11 4 1 1 10 2 potato 9.9 5 1 1 15 1 potato 1.2 6 1 1 15 2 potato 8.8 ``` -- ```r ggplot(data=ff.m, aes(x=rating)) + geom_histogram(binwidth=2) + facet_wrap(~type, ncol=5) ```  --- # Side-by-side boxplots ```r ggplot(data=ff.m, aes(x=type, y=rating, fill=type)) + geom_boxplot() ```  --- # Ratings by week How do ratings change over the weeks? Again, we use the long form of the data and plot: ```r ff.m$time <- as.numeric(ff.m$time) ggplot(data=ff.m, aes(x=time, y=rating, colour=type)) + geom_point(size=.75) + geom_smooth() + facet_wrap(~type) ```  --- # Models and model output Functions such as `lm`, `glm`, `lmer`, ... allow us to fit models e.g. fit french fry rating with respect to all designed main effects: ```r ff_long <- gather(french_fries, key = type, value = rating, potato:painty) ff_lm <- lm(rating~type+treatment+time+subject, data=ff_long) ``` --- `summary`, `str`, `resid`, `fitted`, `coef`, ... allow us to extract different parts of a model for a linear model. Other model functions work differently ... major headaches! ```r summary(ff_lm) Call: lm(formula = rating ~ type + treatment + time + subject, data = ff_long) Residuals: Min 1Q Median 3Q Max -7.0729 -1.9674 -0.4644 1.5202 10.2192 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.19851 0.25792 4.647 3.50e-06 *** typegrassy -1.15513 0.15572 -7.418 1.49e-13 *** typepainty 0.70055 0.15577 4.497 7.11e-06 *** typepotato 5.13322 0.15572 32.964 < 2e-16 *** typerancid 2.03293 0.15572 13.055 < 2e-16 *** treatment2 -0.05128 0.12051 -0.426 0.6705 treatment3 -0.04546 0.12056 -0.377 0.7062 time2 0.10194 0.21613 0.472 0.6372 time3 -0.01361 0.21613 -0.063 0.9498 time4 -0.10250 0.21613 -0.474 0.6353 time5 -0.13301 0.21690 -0.613 0.5398 time6 -0.04611 0.21613 -0.213 0.8311 time7 -0.24621 0.21628 -1.138 0.2550 time8 -0.11626 0.21658 -0.537 0.5914 time9 0.13188 0.22783 0.579 0.5627 time10 0.54635 0.22783 2.398 0.0165 * subject10 1.71451 0.24389 7.030 2.48e-12 *** subject15 -0.35911 0.24489 -1.466 0.1426 subject16 0.47519 0.24408 1.947 0.0516 . subject19 2.01651 0.24389 8.268 < 2e-16 *** subject31 1.49284 0.25098 5.948 2.98e-09 *** subject51 1.87284 0.24389 7.679 2.07e-14 *** subject52 0.19484 0.24389 0.799 0.4244 subject63 0.96051 0.24389 3.938 8.37e-05 *** subject78 -0.58283 0.24389 -2.390 0.0169 * subject79 -0.53702 0.25027 -2.146 0.0320 * subject86 0.43543 0.25098 1.735 0.0828 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.9 on 3444 degrees of freedom (9 observations deleted due to missingness) Multiple R-squared: 0.3995, Adjusted R-squared: 0.395 F-statistic: 88.13 on 26 and 3444 DF, p-value: < 2.2e-16 ``` --- # Tidying model output The package `broom` gets model results into a tidy format at different levels One value for each: - model: `broom::glance` - coefficient in the model: `broom::tidy` - value in the dataset: `broom::augment` --- # Goodness of fit statistics: `glance` ```r glance(ff_lm) # A tibble: 1 x 12 r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 0.400 0.395 2.90 88.1 0 26 -8607. 17270. 17442. # … with 3 more variables: deviance <dbl>, df.residual <int>, nobs <int> ``` --- # Model estimates: `tidy` ```r ff_lm_tidy <- tidy(ff_lm) glimpse(ff_lm_tidy) Rows: 27 Columns: 5 $ term <chr> "(Intercept)", "typegrassy", "typepainty", "typepotato", "t… $ estimate <dbl> 1.19851228, -1.15513007, 0.70054547, 5.13321525, 2.03292748… $ std.error <dbl> 0.2579150, 0.1557200, 0.1557749, 0.1557200, 0.1557200, 0.12… $ statistic <dbl> 4.64692727, -7.41799461, 4.49716394, 32.96439433, 13.055019… $ p.value <dbl> 3.495385e-06, 1.489614e-13, 7.113736e-06, 2.275767e-207, 4.… ``` --- # Model diagnostics: `augment` ```r ff_lm_all <- augment(ff_lm) glimpse(ff_lm_all) Rows: 3,471 Columns: 12 $ .rownames <chr> "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "… $ rating <dbl> 2.9, 14.0, 11.0, 9.9, 1.2, 8.8, 9.0, 8.2, 7.0, 13.0, 12.2,… $ type <chr> "potato", "potato", "potato", "potato", "potato", "potato"… $ treatment <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1… $ time <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1… $ subject <fct> 3, 3, 10, 10, 15, 15, 16, 16, 19, 19, 31, 31, 51, 51, 52, … $ .fitted <dbl> 6.331728, 6.331728, 8.046235, 8.046235, 5.972622, 5.972622… $ .resid <dbl> -3.4317275, 7.6682725, 2.9537651, 1.8537651, -4.7726224, 2… $ .std.resid <dbl> -1.1882021, 2.6550643, 1.0225395, 0.6417396, -1.6522266, 0… $ .hat <dbl> 0.007910376, 0.007910376, 0.007575050, 0.007575050, 0.0076… $ .sigma <dbl> 2.899486, 2.897111, 2.899641, 2.899907, 2.898931, 2.899677… $ .cooksd <dbl> 4.169299e-04, 2.081769e-03, 2.955862e-04, 1.164238e-04, 7.… ``` --- # Residual plot ```r ggplot(ff_lm_all, aes(x=.fitted, y=.resid)) + geom_point() ```  --- # Adding random effects Add random intercepts for each subject ```r library(lme4) fries_lmer <- lmer(rating~type+treatment+time+subject + ( 1 | subject ), data = ff_long) ``` --- class: inverse middle # Your turn - Augment the ff_long data with the model diagnostics - Plot the residuals from the (a) fixed, (b) random effects - Plot fitted values against observed values --- # Resources - [RStudio cheatsheets](https://www.rstudio.com/resources/cheatsheets/) - [Wickham (2007) Reshaping data](https://www.jstatsoft.org/article/view/v021i12) - [broom vignettes, David Robinson](https://cran.r-project.org/web/packages/broom/vignettes/broom.html) --- # Share and share alike
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.


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Anse Mitan is the main tourist centre of Martinique and a popular spot with yachts. It is just south of Fort de France.
Position 14° 33'32"N, 61° 03'03"W (entrance to the marina)
See the main Noonsite/Martinique/Formalities page for full details.
Take the dinghy to the dock near the “Pointe du Bout”, walk 50m to the marina office, all you have to do is fill out the form on the dedicated computer, print it, the lady in charge will chop it – done! No Customs officer, no Immigration officer, no fee, nothing. Same for exit.
Last updated October 2015.
Many yachts anchor in the bay but there is also a very small marina east of Pointe du Bout.
This is a nice bay with excellent holding and not too crowded.
The resort complex surrounding this marina offers various repair facilities, chandleries and supermarkets.
There is a small boat pontoon in the NE part of the bay.
Security
An outboard engine, padlocked to the dinghy which was locked to a yacht, was stolen in this bay July 2016. See report adjacent.
Last updated July 2016.


Goal - Redesign
Goal - create mobile app
Goal - create web app
RSSchool mentor (5 students/all is hired)
EPAM js trainings lector (2 lessons)
ITLandia teacher (1 year, 2 students)
Fawaris head of unit (3 subordinates, 2 activities inside of the unit)
REACT mentor at EPAM`s mentoring program (2 students)


How To Watch Or Stream UFC Fight Night 164
by Trent ReinsmithThe UFC visits Brazil for the third and final time in 2019 on Saturday for the ESPN+ streaming UFC Fight Night 164 card. In the main event, Jan Blachowicz welcomes Ronaldo “Jacare” Souza to the light heavyweight division. Blachowicz, who is the No. 6 ranked fighter in the 205-pound division, is coming off a second-round knockout win over Luke Rockhold, while Souza heads into Saturday’s contest with a decision loss to Jack Hermansson in his most recent outing.
In the co-main event, former UFC light heavyweight champion Mauricio Rua looks to continue his resurgent run against Paul Craig. Rua is 4-1 in his past five outings and coming off a third-round TKO win over Tyson Pedro in December 2018. Rua’s recent run is by far the best stretch of fights he has had under the UFC banner. In his first 14 fights with the promotion, Rua never put together two consecutive wins. Craig is 4-4 with the UFC. None of those fights have gone the distance. Craig has earned a post-fight bonus in each of his UFC victories.
Also appearing on the main card is submission ace Charles Oliveira. Oliveira has won five straight fights by stoppage. Four of those victories came via submission. Oliveira faces Jared Gordon in a lightweight bout. Gordon is 3-1 in the UFC and coming off a decision win over Dan Moret.
HOW TO WATCH OR STREAM UFC FIGHT NIGHT 164
UFC Fight Night 164 takes place at Ginasio do Ibirapuera in Sao Paulo, Brazil. The entire card streams on ESPN+. Prelims begin at 5 p.m. ET, followed by the main card at 8 p.m. ET.
UFC Fight Night 164 Prelim Card (ESPN+ 5 p.m. ET)
Sérgio Moraes vs. James Krause
Ricardo Ramos vs. Luiz Eduardo Garagorri
Francisco Trinaldo vs. Bobby Green
Warlley Alves vs. Randy Brown
Douglas Silva de Andrade vs. Renan Barão
Ariane Lipski vs. Veronica Macedon
Vanessa Melo vs. Tracy Cortez
UFC Fight Night 164 Main Card (ESPN+ 8 p.m. ET)
Jan Błachowicz vs. Ronaldo Souza
Maurício Rua vs. Paul Craig
Charles Oliveira vs. Jared Gordon
Antonio Arroyo vs. Andre Muniz
Markus Perez vs. Wellington Turman


Trader Verona:
Welcome, customer! Isn't Innadril a beautiful place? But know that its beauty can disguise its dangers. How can you appreciate a lovely sunset with a man-eating alligator moving towards you? Unless you have solid armor and a stout hammer, of course...
Buy/Sell/Refund.
Ask about the local lord and tax rate.
Quest


Below is the list of teams that are participating in the challenge and the members that attained a particular level.


ARTICLES
his data portal serves two main users
For depositors: The seed portal provides a way to submit inventories of the material they wish to deposit in the Seed Vault - see the Depositor Guidelines tab in the menu above.
For the general public: The seed portal is a way to find basic information about the seed samples conserved in the Seed Vault - see the Information Sharing tab in the menu above.
Seed Portal of the Svalbard Global Seed Vault
Further detailed information on all the germplasm samples in the Svalbard Global Seed Vault (SGSV) Seed Portal will be made available from the new global accession level data portal (GENESYS) under development by Bioversity International and supported by the Global Crop Diversity Trust.
Svalbard Global Seed Vault on the web:
The three partners in the project all have web sites with background information about the Seed Vault. The official website of the project is the one managed by the Ministry in Norway [seedvault.no].
Royal Norwegian Ministry of Agriculture and Food


This is a sub-structure in CSL_Aif2AdDioSetup. This structure is used for configuring the parameters of aif2 dma engine. More...
#include <csl_aif2.h>
Data Fields | |
| CSL_Aif2AdBcnTable | BcnTableSelect |
| CSL_Aif2AdNumQWord | NumQuadWord |
| Uint8 | NumAxC |
| CSL_Aif2AdNumQWord | DmaBurstLen |
| Bool | bEnEgressRsaFormat |
| Bool | bEnIngressRsaFormat |
| Bool | bEnDmaChannel |
| Uint16 | DmaNumBlock |
| Uint32 | DmaBaseAddr |
| Uint16 | DmaBurstAddrStride |
| Uint16 | DmaBlockAddrStride |
| Uint8 | DBCN [64] |
This is a sub-structure in CSL_Aif2AdDioSetup. This structure is used for configuring the parameters of aif2 dma engine.
| CSL_Aif2AdBcnTable CSL_Aif2AdDioEngine::BcnTableSelect |
Selects which buffer channel number table for the DMA engine to use
| Bool CSL_Aif2AdDioEngine::bEnDmaChannel |
enable or disable DIO DMA channel
| Bool CSL_Aif2AdDioEngine::bEnEgressRsaFormat |
enable or disable Egress DIO RSA data type format
| Bool CSL_Aif2AdDioEngine::bEnIngressRsaFormat |
enable or disable Ingress DIO RSA data type format
| Uint8 CSL_Aif2AdDioEngine::DBCN[64] |
Data Buffer Channel Number for total 64 channels
| Uint32 CSL_Aif2AdDioEngine::DmaBaseAddr |
Sets the VBUS destination base address (upper 28 bits of 32 bit data bus).
| Uint16 CSL_Aif2AdDioEngine::DmaBlockAddrStride |
Sets the DMA block address stride (in multiples of 0x10).
| Uint16 CSL_Aif2AdDioEngine::DmaBurstAddrStride |
Sets the DMA burst address stride (in multiples of 0x10). After each DMA burst, the DMA address will increment by this amount
| CSL_Aif2AdNumQWord CSL_Aif2AdDioEngine::DmaBurstLen |
Sets the maximum DMA burst length
| Uint16 CSL_Aif2AdDioEngine::DmaNumBlock |
Set the number of data blocks to transfer before wrapping back to dma_base_addr
| Uint8 CSL_Aif2AdDioEngine::NumAxC |
Sets the number of quad words per AxC
| CSL_Aif2AdNumQWord CSL_Aif2AdDioEngine::NumQuadWord |
Sets the number of quad words per AxC


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Write a script that finds the max and min number from a sequence of numbers
Please use space as separator of the numbers ==> Example: 1 2 3 4 5
Find out


--- ---
January - April 2014
| Course No. | Course Title | Instructor |
| MA 222 | Measure Theory | Harish Seshadri |
| MA 224 | Complex Analysis |
E. K. Narayanan |
| MA 229 | Calculus on Manifolds | A. K. Nandakumaran |
| MA 241 | Ordinary Differential Equations | G. Rangarajan |
| MA 303 | Topics in Operator Theory | Gadadhar Misra |
| MA 304 | Abstract Harmonic Analysis | Lakshmi Lavanya / S. Thangavelu |
| MA 315 | Galois Theory* | D.P. Patil |
| MA 322 | Harmonic Analysis | S. Thangavelu |
| MA 324 | Topics in Complex Analysis | Gautam Bharali |
| MA 332 | Symplectic Geometry | David Farris / Harish Seshadri |
| MA 347 | Advanced PDE and Finite Element Method | Thirupathi Gudi |
| MA 361 | Probability Theory* | Arvind Ayyer Link to course webpage |
| MA 365 | Topics in Gaussian Processes | Manjunath Krishnapur |
* Soft core for Integrated Ph.D. Ist Year students.
|
|
||
| Indian Institute of Science | Contact the Administrator | Disclaimer |


Saint Lucia Labour Party Castries North Constituency Group to host Festival of Ideas
by Saint Lucia Labour Party Castries North Constituency Group(PRESS RELEASE) – The Saint Lucia Labour Party Castries North Constituency Group would like to invite all residents of Castries North to the launch of it Festival of Ideas at the Patricia D James Secondary School La Clery Castries on Sunday, November 24th 2019 from 2pm – 6pm.
The aim of the Festival of Ideas is to share and exchange Ideas for making Real Change in Castries North.
At this initial event presentations will be made by the following individuals, followed by opportunities for discussions, questions, suggestions and comments.
1. Ms. Finola Jennings Clark will present on Art, Culture and Development
2. Mr. Mark Hennecart will present on Housing and Urban Renewal; and
3. Mr. Samuel Bowers will present on the Role of housing association in building Strong, Safe and Resilient Communities.
We live in times of great challenges that include the threats of Climate Change, rising Crime and anti-social behaviour along with a long period of stagnant wages and increasing numbers of the working poor.
We hope to explore ideas that can bring about Real Change. For example, how we can ensure that that children in Castries North can attain a proficiency in the Arts and Culture by age 12. Concerning housing, how we can ensure that the residents of Castries North benefit from the opportunities for renewing the housing stock in Castries and the Renewal of the City of Castries.
The Festival of Ideas will also seek to develop a “bottom up” approach to developing public policy around financing affordable housing and transforming the Nation housing Corporation to make it more relevant to the needs of the residents of Castries Norths and especially given the experience of the former La Clary CDC residents.
For example, in our discussion, we will be exploring the role housing Association can play in building Strong, Safe and Resilient Communities. Participants will consider ideas around the use of Mortgage Repayment Insurance as an approach to providing increase security for home buyers in a flexible labour market and a source for financing affordable housing and urban renewal by reforming the organisations and institution charged with the missions to create affordable housing in Sant Lucia.
The SLP Castries North Constituency Group is a movement for Real Change. All residents are invited, and you don’t have to be a supporter of member of the Saint Lucian Labour Party to attend. The ideas is to bring people together to consider options for Real Change in Castries North and by extension Saint Lucia.
More General Stories
-
Eleven receive OBE honors November 19, 2019
-
Observance of International Men’s Day November 19, 2019
-
Central Statistical Office launches Census 2020 recruitment drive November 18, 2019
-
Tourism ministry spearheads plan to ease traffic congestion in downtown Castries November 12, 2019
-
Bon Nouvel to host traditional Christmas food and beverage competition November 9, 2019
-
Mayor speaks on Castries development projects November 7, 2019
-
Saint Lucia Supreme Court hosts mediation symposium November 7, 2019
-
Saint Lucia works toward gender equality November 6, 2019
-
Transport division experiences challenges in providing drivers licenses November 6, 2019


The FIX is in the Real Virus is Communism! We need to act now declare Martial Law and the Insurrection act and save this country from these communists Democrats and RINOs, China has Declared an act of War against the United States with the corona virus and rigged our election process, for the love of God and this Great country it’s time to act NOW!🇺🇸 God Bless America and our Great President Trump! 👊 #stopthesteal
Q and maga pukes stand down on 1-6-20 These poor folks are too dangerous to not resist anymore. This site is ripe with potential danger of creating more 'lone wolfs' and Timothy mcviegh' types
Q and maga pukes stand down on 1-6-20 These poor folks are too dangerous to not resist anymore. This site is ripe with potential danger of creating more 'lone wolfs' and Timothy mcviegh' types
Time to make it clear to your representatives that our country is ultimately governed by we the people. And we the people are not happy with them conspiring and condoning the fraud to steal this election. Seriously serious. @b753a92e51ac4a9d96c99fb025aa5654 @dcdd1dc516c64d7880a54edb37bdb8ef @senatemajldr
Q and maga pukes stand down on 1-6-20 These poor folks are too dangerous to not resist anymore. This site is ripe with potential danger of creating more 'lone wolfs' and Timothy mcviegh' types
The unanimous Declaration of the thirteen united States of America, When in the Course of human events, it becomes necessary for one people to dissolve the political bands which have connected them with another, and to assume among the powers of the earth, the separate and equal station to which the Laws of Nature and of Nature's God entitle them, a decent respect to the opinions of mankind requires that they should declare the causes which impel them to the separation.
I'm still waiting to see the first governor to send this to Joe Biden & Kamala Harris💔 Red state exit. Defund the Democratic party! #Texit #Redstateexit. America is trending towards socialism. Red states need to divorce blue states; If not then Red states will be dragged along for the ride towards socialism. Let's restore the freedoms that America has lost. And end censorship! #Redstateexit #Texit 💔
This coming year I resolve to encourage my fellow Patriots to be men and women of service. Service to our God, our families, and our beautiful country. I will passionately pursue justice and accountability for those who have betrayed our great nation and seek ways to preserve the protectors of our peace and the the defenders of our constitution. Let my heart guide me, courage propel me, and may my faith be my eyes until truth is revealed.
Q and maga pukes stand down on 1-6-20 These poor folks are too dangerous to not resist anymore. This site is ripe with potential danger of creating more 'lone wolfs' and Timothy mcviegh' types
@2020true Give a example of AJ spreading ‘disinformation’ - if you watch current events, things have turned out ie re deep-state pretty close to what AJ has been talking for years - you didn’t listen though...
The FIX is in the Real Virus is Communism! We need to act now declare Martial Law and the Insurrection act and save this country from these communists Democrats and RINOs, China has Declared an act of War against the United States with the corona virus and rigged our election process, for the love of God and this Great country it’s time to act NOW!🇺🇸 God Bless America and our Great President Trump! 👊 #stopthesteal
I always love to hear Alex tell it like it is. Unafraid to speak the truth! Following back all Patriots!
The only election in my lifetime I truly believe was legitimate in who won was Trump in 2016. Though plenty of BS then just still got the real result.

You’re growing on me Alex!
💕🙏🇺🇲
TRUMP HAS DONE NOTHING ABOUT DEEP STATE CRIMINAL TRAITORS.
STOP THE STEAL!!!!!!
 And we the people are not happy with them conspiring and condoning the fraud to steal this election. Seriously serious. @b753a92e51ac4a9d96c99fb025aa5654 @dcdd1dc516c64d7880a54edb37bdb8ef @senatemajldr
The voting machines are turning thr frogs gay!!! 🐸🌈
In Congress, July 4, 1776
The unanimous Declaration of the thirteen united States of America, When in the Course of human events, it becomes necessary for one people to dissolve the political bands which have connected them with another, and to assume among the powers of the earth, the separate and equal station to which the Laws of Nature and of Nature's God entitle them, a decent respect to the opinions of mankind requires that they should declare the causes which impel them to the separation.
I'm still waiting to see the first governor to send this to Joe Biden & Kamala Harris💔 Red state exit. Defund the Democratic party! #Texit #Redstateexit. America is trending towards socialism. Red states need to divorce blue states; If not then Red states will be dragged along for the ride towards socialism. Let's restore the freedoms that America has lost. And end censorship!
#Redstateexit #Texit 💔
The Patriot’s New Year’s Revolution
This coming year I resolve to encourage my fellow Patriots to be men and women of service. Service to our God, our families, and our beautiful country. I will passionately pursue justice and accountability for those who have betrayed our great nation and seek ways to preserve the protectors of our peace and the the defenders of our constitution. Let my heart guide me, courage propel me, and may my faith be my eyes until truth is revealed.
Im watching him on RSBN, this has been a killer stream
This man is something !!!!
We are hear to finish this fraud the easy right way or blood to a horse's main in the streets...trump won and we will grind them beneath our feet
Damn he is getting more pudgy by the day.  Just get that fat little heart rate up and stroke out already.


As of Fabric 1.1, there are two distinct methods you may use in order to define which objects in your fabfile show up as tasks:
ノート
These two methods are mutually exclusive: if Fabric finds any new-style task objects in your fabfile or in modules it imports, it will assume you’ve committed to this method of task declaration and won’t consider any non-Task callables. If no new-style tasks are found, it reverts to the classic behavior.
The rest of this document explores these two methods in detail.
ノート
To see exactly what tasks in your fabfile may be executed via fab, use fab --list.
Fabric 1.1 introduced the Task class to facilitate new features and enable some programming best practices, specifically:
With the introduction of Task, there are two ways to set up new tasks:
Use of new-style tasks also allows you to set up namespaces.
The quickest way to make use of new-style task features is to wrap basic task functions with @task:
from fabric.api import task, run
@task
def mytask():
run("a command")
When this decorator is used, it signals to Fabric that only functions wrapped in the decorator are to be loaded up as valid tasks. (When not present, classic-style task behavior kicks in.)
@task may also be called with arguments to customize its behavior. Any arguments not documented below are passed into the constructor of the task_class being used, with the function itself as the first argument (see Using custom subclasses with @task for details.)
Here’s a quick example of using the alias keyword argument to facilitate use of both a longer human-readable task name, and a shorter name which is quicker to type:
from fabric.api import task
@task(alias='dwm')
def deploy_with_migrations():
pass
Calling --list on this fabfile would show both the original deploy_with_migrations and its alias dwm:
$ fab --list
Available commands:
deploy_with_migrations
dwm
When more than one alias for the same function is needed, simply swap in the aliases kwarg, which takes an iterable of strings instead of a single string.
In a similar manner to aliases, it’s sometimes useful to designate a given task within a module as the “default” task, which may be called by referencing just the module name. This can save typing and/or allow for neater organization when there’s a single “main” task and a number of related tasks or subroutines.
For example, a deploy submodule might contain tasks for provisioning new servers, pushing code, migrating databases, and so forth – but it’d be very convenient to highlight a task as the default “just deploy” action. Such a deploy.py module might look like this:
from fabric.api import task
@task
def migrate():
pass
@task
def push():
pass
@task
def provision():
pass
@task
def full_deploy():
if not provisioned:
provision()
push()
migrate()
With the following task list (assuming a simple top level fabfile.py that just imports deploy):
$ fab --list
Available commands:
deploy.full_deploy
deploy.migrate
deploy.provision
deploy.push
Calling deploy.full_deploy on every deploy could get kind of old, or somebody new to the team might not be sure if that’s really the right task to run.
Using the default kwarg to @task, we can tag e.g. full_deploy as the default task:
@task(default=True)
def full_deploy():
pass
Doing so updates the task list like so:
$ fab --list
Available commands:
deploy
deploy.full_deploy
deploy.migrate
deploy.provision
deploy.push
Note that full_deploy still exists as its own explicit task – but now deploy shows up as a sort of top level alias for full_deploy.
If multiple tasks within a module have default=True set, the last one to be loaded (typically the one lowest down in the file) will take precedence.
Using @task(default=True) in the top level fabfile will cause the denoted task to execute when a user invokes fab without any task names (similar to e.g. make.) When using this shortcut, it is not possible to specify arguments to the task itself – use a regular invocation of the task if this is necessary.
If you’re used to classic-style tasks, an easy way to think about Task subclasses is that their run method is directly equivalent to a classic task; its arguments are the task arguments (other than self) and its body is what gets executed.
For example, this new-style task:
class MyTask(Task):
name = "deploy"
def run(self, environment, domain="whatever.com"):
run("git clone foo")
sudo("service apache2 restart")
instance = MyTask()
is exactly equivalent to this function-based task:
@task
def deploy(environment, domain="whatever.com"):
run("git clone foo")
sudo("service apache2 restart")
Note how we had to instantiate an instance of our class; that’s simply normal Python object-oriented programming at work. While it’s a small bit of boilerplate right now – for example, Fabric doesn’t care about the name you give the instantiation, only the instance’s name attribute – it’s well worth the benefit of having the power of classes available.
We plan to extend the API in the future to make this experience a bit smoother.
It’s possible to marry custom Task subclasses with @task. This may be useful in cases where your core execution logic doesn’t do anything class/object-specific, but you want to take advantage of class metaprogramming or similar techniques.
Specifically, any Task subclass which is designed to take in a callable as its first constructor argument (as the built-in WrappedCallableTask does) may be specified as the task_class argument to @task.
Fabric will automatically instantiate a copy of the given class, passing in the wrapped function as the first argument. All other args/kwargs given to the decorator (besides the “special” arguments documented in Arguments) are added afterwards.
Here’s a brief and somewhat contrived example to make this obvious:
from fabric.api import task
from fabric.tasks import Task
class CustomTask(Task):
def __init__(self, func, myarg, *args, **kwargs):
super(CustomTask, self).__init__(*args, **kwargs)
self.func = func
self.myarg = myarg
def run(self, *args, **kwargs):
return self.func(*args, **kwargs)
@task(task_class=CustomTask, myarg='value', alias='at')
def actual_task():
pass
When this fabfile is loaded, a copy of CustomTask is instantiated, effectively calling:
task_obj = CustomTask(actual_task, myarg='value')
Note how the alias kwarg is stripped out by the decorator itself and never reaches the class instantiation; this is identical in function to how command-line task arguments work.
With classic tasks, fabfiles were limited to a single, flat set of task names with no real way to organize them. In Fabric 1.1 and newer, if you declare tasks the new way (via @task or your own Task subclass instances) you may take advantage of namespacing:
Let’s build up a fabfile package from simple to complex and see how this works.
We start with a single __init__.py containing a few tasks (the Fabric API import omitted for brevity):
@task
def deploy():
...
@task
def compress():
...
The output of fab --list would look something like this:
deploy
compress
There’s just one namespace here: the “root” or global namespace. Looks simple now, but in a real-world fabfile with dozens of tasks, it can get difficult to manage.
As mentioned above, Fabric will examine any imported module objects for tasks, regardless of where that module exists on your Python import path. For now we just want to include our own, “nearby” tasks, so we’ll make a new submodule in our package for dealing with, say, load balancers – lb.py:
@task
def add_backend():
...
And we’ll add this to the top of __init__.py:
import lb
Now fab --list shows us:
deploy
compress
lb.add_backend
Again, with only one task in its own submodule, it looks kind of silly, but the benefits should be pretty obvious.
Namespacing isn’t limited to just one level. Let’s say we had a larger setup and wanted a namespace for database related tasks, with additional differentiation inside that. We make a sub-package named db/ and inside it, a migrations.py module:
@task
def list():
...
@task
def run():
...
We need to make sure that this module is visible to anybody importing db, so we add it to the sub-package’s __init__.py:
import migrations
As a final step, we import the sub-package into our root-level __init__.py, so now its first few lines look like this:
import lb
import db
After all that, our file tree looks like this:
.
├── __init__.py
├── db
│ ├── __init__.py
│ └── migrations.py
└── lb.py
and fab --list shows:
deploy
compress
lb.add_backend
db.migrations.list
db.migrations.run
We could also have specified (or imported) tasks directly into db/__init__.py, and they would show up as db.<whatever> as you might expect.
You may limit what Fabric “sees” when it examines imported modules, by using the Python convention of a module level __all__ variable (a list of variable names.) If we didn’t want the db.migrations.run task to show up by default for some reason, we could add this to the top of db/migrations.py:
__all__ = ['list']
Note the lack of 'run' there. You could, if needed, import run directly into some other part of the hierarchy, but otherwise it’ll remain hidden.
We’ve been keeping our fabfile package neatly organized and importing it in a straightforward manner, but the filesystem layout doesn’t actually matter here. All Fabric’s loader cares about is the names the modules are given when they’re imported.
For example, if we changed the top of our root __init__.py to look like this:
import db as database
Our task list would change thusly:
deploy
compress
lb.add_backend
database.migrations.list
database.migrations.run
This applies to any other import – you could import third party modules into your own task hierarchy, or grab a deeply nested module and make it appear near the top level.
As a final note, we’ve been using the default Fabric --list output during this section – it makes it more obvious what the actual task names are. However, you can get a more nested or tree-like view by passing nested to the --list-format option:
$ fab --list-format=nested --list
Available commands (remember to call as module.[...].task):
deploy
compress
lb:
add_backend
database:
migrations:
list
run
While it slightly obfuscates the “real” task names, this view provides a handy way of noting the organization of tasks in large namespaces.
When no new-style Task-based tasks are found, Fabric will consider any callable object found in your fabfile, except the following:
Python’s import statement effectively includes the imported objects in your module’s namespace. Since Fabric’s fabfiles are just Python modules, this means that imports are also considered as possible classic-style tasks, alongside anything defined in the fabfile itself.
ノート
This only applies to imported callable objects – not modules. Imported modules only come into play if they contain new-style tasks, at which point this section no longer applies.
Because of this, we strongly recommend that you use the import module form of importing, followed by module.callable(), which will result in a cleaner fabfile API than doing from module import callable.
For example, here’s a sample fabfile which uses urllib.urlopen to get some data out of a webservice:
from urllib import urlopen
from fabric.api import run
def webservice_read():
objects = urlopen('http://my/web/service/?foo=bar').read().split()
print(objects)
This looks simple enough, and will run without error. However, look what happens if we run fab --list on this fabfile:
$ fab --list
Available commands:
webservice_read List some directories.
urlopen urlopen(url [, data]) -> open file-like object
Our fabfile of only one task is showing two “tasks”, which is bad enough, and an unsuspecting user might accidentally try to call fab urlopen, which probably won’t work very well. Imagine any real-world fabfile, which is likely to be much more complex, and hopefully you can see how this could get messy fast.
For reference, here’s the recommended way to do it:
import urllib
from fabric.api import run
def webservice_read():
objects = urllib.urlopen('http://my/web/service/?foo=bar').read().split()
print(objects)
It’s a simple change, but it’ll make anyone using your fabfile a bit happier.


Reports synchronization on a local variable or parameter. It is very difficult to guarantee correctness when such synchronization is used.
It may be possible to improve code like this by controlling access through e.g. a synchronized wrapper class or by synchronizing on a
field.
Example:
void bar() {
final Object lock = new Object();
synchronized (lock) { }
}


public class Shopping
extends java.lang.Object
A namespaced client for the
/v2/travel
endpoints.
Access via the Amadeus client object.
Amadeus amadeus = Amadeus.builder("clientId", "secret").build(); amadeus.travel;
| Modifier and Type | Field and Description |
|---|---|
Activities |
activities
A namespaced client for the
/v1/shopping/activities endpoints. |
Activity |
activity
A namespaced client for the
/v1/shopping/activities endpoints. |
Availability |
availability
A namespaced client for the
/v1/shopping/availability endpoints. |
FlightDates |
flightDates
A namespaced client for the
/v1/shopping/flight-dates endpoints. |
FlightDestinations |
flightDestinations
A namespaced client for the
/v1/shopping/flight-destinations endpoints. |
FlightOffers |
flightOffers
A namespaced client for the
/v1/shopping/flight-offers endpoints. |
FlightOffersSearch |
flightOffersSearch
A namespaced client for the
/v2/shopping/flight-offers endpoints. |
HotelOffers |
hotelOffers
A namespaced client for the
/v2/shopping/hotel-offers endpoints. |
HotelOffersByHotel |
hotelOffersByHotel
A namespaced client for the
/v2/shopping/hotel-offers/by-hotel endpoints. |
HotelOffersSearch |
hotelOffersSearch
A namespaced client for the
/v3/shopping/hotel-offers endpoints. |
SeatMaps |
seatMaps
A namespaced client for the
/v1/shopping/seatmaps endpoints. |
| Modifier and Type | Method and Description |
|---|---|
Activity |
activity(java.lang.String activityId)
A namespaced client for the
/v1/shopping/activities/:activity_id endpoints. |
HotelOffer |
hotelOffer(java.lang.String hotelId)
A namespaced client for the
/v1/shopping/hotel/:hotel_id endpoints. |
HotelOfferSearch |
hotelOfferSearch(java.lang.String offerId)
A namespaced client for the
/v3/shopping/hotel/:hotel_id endpoints. |
public FlightDates flightDates
A namespaced client for the
/v1/shopping/flight-dates
endpoints.
public FlightDestinations flightDestinations
A namespaced client for the
/v1/shopping/flight-destinations
endpoints.
public FlightOffers flightOffers
A namespaced client for the
/v1/shopping/flight-offers
endpoints.
public FlightOffersSearch flightOffersSearch
A namespaced client for the
/v2/shopping/flight-offers
endpoints.
public HotelOffers hotelOffers
A namespaced client for the
/v2/shopping/hotel-offers
endpoints.
public HotelOffersSearch hotelOffersSearch
A namespaced client for the
/v3/shopping/hotel-offers
endpoints.
public HotelOffersByHotel hotelOffersByHotel
A namespaced client for the
/v2/shopping/hotel-offers/by-hotel
endpoints.
public SeatMaps seatMaps
A namespaced client for the
/v1/shopping/seatmaps
endpoints.
public Activity activity
A namespaced client for the
/v1/shopping/activities
endpoints.
public Activities activities
A namespaced client for the
/v1/shopping/activities
endpoints.
public Availability availability
A namespaced client for the
/v1/shopping/availability
endpoints.
public Shopping(Amadeus client)
public HotelOffer hotelOffer(java.lang.String hotelId)
A namespaced client for the
/v1/shopping/hotel/:hotel_id
endpoints.
public HotelOfferSearch hotelOfferSearch(java.lang.String offerId)
A namespaced client for the
/v3/shopping/hotel/:hotel_id
endpoints.
public Activity activity(java.lang.String activityId)
A namespaced client for the
/v1/shopping/activities/:activity_id
endpoints.


Beedrill is extremely territorial, and when threatened, flies at high speeds and attacks with large, venomous stingers.
By soaking up the sun's rays, the seed on Bulbasaur’s back grows progressively larger to power up.
Squirtle’s most powerful asset is his shell, allowing it to swim at high speeds (as it minimizes water resistance), and shielding it from its enemies.
Charizard’s ability to fly and breathe fire is one of the most deadliest of combinations. It's constantly searching for his next opponent to battle, so beware! Its fire can melt anything in its path.
Mewtwo was created by science, capable of telepathy, levitation, and mind control. It is hyper-focused on defeating its foes and is known to have the most savage heart of all Pokémon.
Don’t be fooled by Jigglypuff’s cute and unassuming exterior, for it's more powerful than it seems! Jigglypuff sings its opponents to sleep, and is able to mesmerize its foes with its eyes.


|
SideCar
|
Public Slots | |
| void | shutdown () |
Signals | |
| void | connected () |
| void | incoming (const MessageList &msgs) |
| void | disconnected () |
Public Member Functions | |
| ChannelConnection (const QString &name, QObject *parent=0) | |
| const QString & | getName () const |
| void | useServiceEntry (ServiceEntry *serviceEntry) |
| bool | isConnected () const |
| void | setMinimumSizeHint (const QSize &size) |
| const QSize & | getMinimumSizeHint () const |
| ChannelPlotSettings * | getSettings () const |
Static Public Member Functions | |
| static Logger::Log & | Log () |
Definition at line 20 of file ChannelConnection.h.


| Year | Title | Authors |
|---|---|---|
| 2018 | Large-Scale Analysis of Framework-Specific Exceptions in Android Apps | Lingling Fan, East China Normal University Ting Su, Nanyang Technological University Sen Chen, East China Normal University Guozhu Meng, Chinese Academy of Sciences Yang Liu, Nanyang Technological University Lihua Xu, East China Normal University Geguang Pu, East China Normal University Zhendong Su, University of California |
| 2018 | Generalized Data Structure Synthesis | Calvin Loncaric, University of Washington Michael D. Ernst, University of Washington Emina Torlak, University of Washington |
| 2018 | Static Automated Program Repair for Heap Properties | Rijnard van Tonder & Claire Le Goues, Carnegie Mellon University |
| 2018 | Towards Optimal Concolic Testing | Xinyu Wang, Zhejiang University Jun Sun, Singapore University of Technology and Design Zhenbang Chen, National University of Defense Technology Peixin Zhang, Zhejiang University Jingyi Wang, Singapore University of Technology and Design Yun Lin, National University of Singapore |
| 2018 | Spatio-Temporal Context Reduction: A Pointer-Analysis-Based Static Approach for Detecting Use-After-Free Vulnerabilities | Hua Yan, University of New South Wales Yulei Sui, University of Technology Sydney Shiping Chen, CSIRO Jingling Xue, University of New South Wales |
| 2018 | Identifying Design Problems in the Source Code: A Grounded Theory | Leonardo Sousa, PUC-Rio Anderson Oliveira, PUC-Rio Willian Oizumi, PUC-Rio Simone Barbosa, PUC-Rio Alessandro Garcia, PUC-Rio Jaejoon Lee, Lancaster University Marcos Kalinowski, PUC-Rio Rafael de Mello, PUC-Rio Baldoino Fonseca, UFAL Roberto Oliveira, PUC-Rio Carlos Lucena, PUC-Rio Rodrigo Paes, PUC-Rio |
| 2018 | Traceability in the Wild: Automatically Augmenting Incomplete Trace links | Michael Rath, Technical University Ilmenau Jacob Rendall, University of Notre Dame Jin L. C. Guo, McGill University Jane Cleland-Huang, University of Notre Dame Patrick Mäder, Technical University Ilmenau |
| 2018 | Automated Localization for Unreproducible Builds | Zhilei Ren, Dalian University of Technology He Jiang, Dalian University of Technology Jifeng Xuan, Wuhan University Zijiang Yang, Western Michigan University |
| 2017 | Decoding the representation of code in the brain: An fMRI study of code review and expertise | Benjamin Floyd, University of Virginia Tyler Santander, University of Virginia Westley Weimer, University of Virginia |
| 2017 | Code Defenders: Crowdsourcing Effective Tests and Subtle Mutants with a Mutation Testing Game | José Miguel Rojas, The University of Sheffield Thomas D. White, The University of Sheffield Benjamin S. Clegg, The University of Sheffield Gordon Fraser, The University of Sheffield |
| 2017 | Clone Refactoring with Lambda Expressions | Nikolaos Tsantalis, Concordia University Davood Mazinanian, Concordia University Shahriar Rostami, Concordia University |
| 2017 | Optimizing Test Placement for Module-Level Regression Testing | August Shi, University of Illinois at Urbana-Champaign Suresh Thummalapenta, Microsoft Corporation Shuvendu K. Lahiri, Microsoft Research Nikolaj Bjorner, Microsoft Research Jacek Czerwonka, Microsoft Corporation |
| 2017 | A Grounded Theory of Agile Transitions in Practice | Rashina Hoda, The University of Auckland James Noble Victoria, University of Wellington |
| 2017 | Challenges for Static Analysis of Java Reflection-Literature Review and Empirical Study | Davy Landman, Centrum Wiskunde & Informatica Alexander Serebrenik, Centrum Wiskunde & Informatica Jurgen J. Vinju, Centrum Wiskunde & Informatica |
| 2016 | Feedback-Directed Instrumentation for Deployed JavaScript Applications | Magnus Madsen, University of Waterloo Frank Tip, Samsung Research Esben Andreasen, Aarhus University Koushik Sen, University of California Berkeley Anders Møller, Aarhus University |
| 2016 | From Word Embeddings to Document Similarities for Improved Information Retrieval in Software Engineering | Xin Ye, Ohio University Athens Hui Shen, Ohio University Athens Xiao Ma, Ohio University Athens Razvan Bunescu, Ohio University Athens Chang Liu, Ohio University Athens |
| 2016 | On the Techniques We Create, the Tools We Build, and Their Misalignments: A Study of KLEE | Eric F. Rizzi, Grammatech Sebastian Elbaum, University of Nebraska-Lincoln Matthew B. Dwyer, University of Nebraska-Lincoln |
| 2016 | Work Practices and Challenges in Pull-Based Development: The Contributor’s Perspective | Georgios Gousios, Radboud University Nijmegen Margaret-Anne Storey, University of Victoria Alberto Bacchelli, Delft University of Technology |
| 2016 | Termination-Checking for LLVM Peephole Optimizations | David Menendez & Santosh Nagarakatte, Rutgers University |
| 2016 | Guiding Dynamic Symbolic Execution toward Unverified Program Executions | Maria Christakis, ETH Zurich Peter Müller, ETH Zurich Valentin Wüstholz, ETH Zurich |
| 2016 | Efficient Large-Scale Trace Checking Using MapReduce | Marcello M. Bersani, Politecnico di Milano Domenico Bianculli, University of Luxembourg Carlo Ghezzi, Politecnico di Milano Srđan Krstić, Politecnico di Milano Pierluigi San Pietro, Politecnico di Milano |
| 2016 | VDTest: An Automated Framework to Support Testing for Virtual Devices | Tingting Yu, University of Kentucky Xiao Qu, ABB Corporate Research Myra B. Cohen, University of Nebraska-Lincoln |
| 2016 | Energy Profiles of Java Collections Classes | Samir Hasan, Auburn University Zachary King, Auburn University Munawar Hafiz, Auburn University Mohammed Sayagh, Polytechnique Montréal Bram Adams, Polytechnique Montréal Abram Hindle, University of Alberta |
| 2015 | Alloy*: A General-Purpose Higher-Order Relational Constraint Solver | Aleksandar Milicevic, Massachusetts Institute of Technology Joseph P. Near, Massachusetts Institute of Technology Eunsuk Kang, Massachusetts Institute of Technology Daniel Jackson, Massachusetts Institute of Technology |
| 2015 | How Much Up-Front? A Grounded theory of Agile Architecture | Michael Waterman, Specialised Architecture Services Ltd James Noble, Victoria University of Wellington George Allan, Victoria University of Wellington |
| 2015 | Views on Internal and External Validity in Empirical Software Engineering | Janet Siegmund, University of Passau Norbert Siegmund, University of Passau Sven Apel, University of Passau |
| 2015 | Why Good Developers Write Bad Code: An Observational Case Study of the Impacts of Organizational Factors on Software Quality | Mathieu Lavallée & Pierre N. Robillard, Polytechnique Montréal |
| 2015 | When and Why Your Code Starts to Smell Bad | Michele Tufano, College of William and Mary Fabio Palomba, University of Salerno Gabriele Bavota, Free University of Bozen-Bolzano Rocco Oliveto, University of Molise Massimiliano Di Penta, University of Sannio Andrea De Lucia, University of Salerno Denys Poshyvanyk, College of William and Mary |
| 2015 | CARAMEL: Detecting and Fixing Performance Problems That Have Non-Intrusive Fixes | Adrian Nistor, Chapman University Po-Chun Chang, University of Wisconsin Cosmin Radoi, University of Illinois at Urbana-Champaign Shan Lu, University of Chicago |
| 2014 | Characterizing and Detecting Performance Bugs for Smartphone Applications | Yepang Liu, Hong Kong University of Science and Technology Chang Xu, Nanjing University Shing-Chi Cheung, Hong Kong University of Science and Technology |
| 2014 | Improving Automated Source Code Summarization via an Eye-Tracking Study of Programmers | Paige Rodeghero, University of Notre Dame Collin McMillan, University of Notre Dame Paul W. McBurney, University of Notre Dame Nigel Bosch, University of Notre Dame Sidney D’Mello, University of Notre Dame |
| 2014 | Understanding JavaScript Event-Based Interactions | Saba Alimadadi, University of British Columbia Sheldon Sequeira, University of British Columbia Ali Mesbah, University of British Columbia Karthik Pattabiraman, University of British Columbia |
| 2014 | Coverage Is Not Strongly Correlated with Test Suite Effectiveness | Laura Inozemtseva & Reid Holmes, University of Waterloo |
| 2014 | Cowboys, Ankle Sprains, and Keepers of Quality: How Is Video Game Development Different from Software Development | Emerson Murphy-Hill, North Carolina State University Thomas Zimmermann, Microsoft Research Nachiappan Nagappan, Microsoft Research |
| 2014 | Trading Robustness for Maintainability: An Empirical Study of Evolving C# Programs | Nélio Cacho, Federal University of Rio Grande do Norte Thiago César, Federal University of Rio Grande do Norte Thomas Filipe, Federal University of Rio Grande do Norte Eliezio Soares, Federal University of Rio Grande do Norte Arthur Cassio, Federal University of Rio Grande do Norte Rafael Souza, Federal University of Rio Grande do Norte Israel Garcia, Federal University of Rio Grande do Norte Eiji Adachi Barbosa, Pontifical Catholic University of Rio de Janeiro Alessandro Garcia, Pontifical Catholic University of Rio de Janeiro |
| 2014 | Unit Test Virtualization with VMVM | Jonathan Bell & Gail Kaiser, Columbia University |
| 2014 | Enhancing Symbolic Execution with Veritesting | Thanassis Avgerinos, Carnegie Mellon University Alexandre Rebert, Carnegie Mellon University Sang Kil Cha, Carnegie Mellon University David Brumley, Carnegie Mellon University |
| 2014 | A Study and Toolkit for Asynchronous Programming in C# | Semih Okur, University of Illinois at Urbana-Champaign David L. Hartveld, Delft University of Technology Danny Dig, Oregon State University Arie van Deursen, Delft University of Technology |
| 2013 | Dual Ecological Measures of Focus in Software Development | Daryl Posnett, University of California Davis Raissa D’Souza, University of California Davis Premkumar Devanbu, University of California Davis Vladimir Filkov, University of California Davis |
| 2013 | Data Clone Detection and Visualization in Spreadsheets | Felienne Hermans, Delft University of Technology Ben Sedee, Delft University of Technology Martin Pinzger, Delft University of Technology Arie van Deursen, Delft University of Technology UML in Practice Marian Petre, Open University |
| 2013 | Automatic patch generation learned from human-written patches | Dongsun Kim, Hong Kong University of Science and Technology Jaechang Nam, Hong Kong University of Science and Technology Jaewoo Song, Hong Kong University of Science and Technology Sunghun Kim, Hong Kong University of Science and Technology |
| 2013 | Assisting Developers of Big Data Analytics Applications When Deploying on Hadoop Clouds | Weiyi Shang, Queen’s University Zhen Ming Jiang, Queen’s University Hadi Hemmati, Queen’s University Bram Adams, Polytechnique Montréal Ahmed E. Hassan, Queen’s University Patrick Martin, Queen’s University |
| 2013 | Interaction-Based Test-Suite Minimization | Dale Blue, IBM Itai Segall, IBM Research Rachel Tzoref-Brill, IBM Research Aviad Zlotnick, IBM Research |
| 2012 | Understanding Integer Overflow in C/C++ | Will Dietz, University of Illinois at Urbana-Champaign Peng Li, University of Utah John Regehr, University of Utah Vikram Adve, University of Illinois at Urbana-Champaign |
| 2012 | Using Dynamic Analysis to Discover Polynomial and Array Invariants | ThanhVu Nguyen, University of New Mexico Deepak Kapur, University of New Mexico Westley Weimer, University of New Mexico Stephanie Forrest, University of New Mexico |
| 2012 | Amplifying Tests to Validate Exception Handling Code | Pingyu Zhang & Sebastian Elbaum, University of Nebraska-Lincoln |
| 2012 | Partial Models: Towards Modeling and Reasoning with Uncertainty | Michalis Famelis, University of Toronto Rick Salay, University of Toronto Marsha Chechik, University of Toronto |
| 2012 | How Do Professional Developers Comprehend Software? | Tobias Roehm, Technische Universität München Rebecca Tiarks, University of Bremen Rainer Koschke, University of Bremen Walid Maalej, Technische Universität München |
| 2012 | A Tactic-Centric Approach for Automating Traceability of Quality Concerns | Mehdi Mirakhorli, DePaul University Yonghee Shin, DePaul University Jane Cleland-Huang, DePaul University Murat Cinar, DePaul University |
| 2012 | Automated Detection of Client-State Manipulation Vulnerabilities | Anders Møller & Mathias Schwarz, Aarhus University |
| 2011 | Verifying Multi-threaded Software using SMT-based Context-Bounded Model Checking | Lucas Cordeiro & Bernd Fischer, University of Southampton |
| 2011 | Configuring Global Software Teams: A Multi-Company Analysis of Project Productivity, Quality, and Profits | Narayan Ramasubbu, Singapore Management University Marcelo Cataldo, Carnegie Mellon University Rajesh Krishna Balan, Singapore Management University James D. Herbsleb, Carnegie Mellon University |
| 2011 | Programs, tests, and oracles: the foundations of testing revisited | Matt Staats, University of Minnesota Michael W. Whalen, University of Minnesota Mats P.E. Heimdahl, University of Minnesota |
| 2011 | On-demand Feature Recommendations Derived from Mining Public Product Descriptions | Horatiu Dumitru, DePaul University Marek Gibiec, DePaul University Negar Hariri, DePaul University Jane Cleland-Huang, DePaul University Bamshad Mobasher, DePaul University Carlos Castro-Herrera, DePaul University Mehdi Mirakhorli, DePaul University |
| 2011 | Run-Time Efficient Probabilistic Model Checking | Antonio Filieri, Politecnico di Milano Carlo Ghezzi, Politecnico di Milano Giordano Tamburrelli, Politecnico di Milano |
| 2010 | A Machine Learning Approach for Tracing Regulatory Codes to Product Specific Requirements | Jane Cleland-Huang, DePaul University Adam Czauderna, DePaul University John Emenecker, DePaul University Marek Gibiec, DePaul University |
| 2010 | Collaborative Reliability Prediction of Service-Oriented Systems | Zibin Zheng & Michael R. Lyu, The Chinese University of Hong Kong |
| 2010 | A Cut-off Approach for Bounded Verification of Parameterized Systems | Qiusong Yang & Mingshu Li, Chinese Academy of Sciences |
| 2010 | Test Generation through Programming in UDITA | Milos Gligoric, University of Illinois at Urbana-Champaign Tihomir Gvero, École Polytechnique Fédérale de Lausanne Vilas Jagannath, University of Illinois at Urbana-Champaign Sarfraz Khurshid, University of Texas at Austin Viktor Kuncak, École Polytechnique Fédérale de Lausanne Darko Marinov, University of Illinois at Urbana-Champaign |
| 2010 | A Degree-of-Knowledge Model to Capture Source Code Familiarity | Thomas Fritz, University of British Columbia Jingwen Ou, University of British Columbia Gail C. Murphy, University of British Columbia Emerson Murphy-Hill, University of British Columbia |
| 2009 | How We Refactor, and How We Know It | Emerson Murphy-Hill, Portland State University Chris Parnin, Georgia Institute of Technology Andrew P. Black, Portland State University |
| 2009 | Effective Static Deadlock Detection | Mayur Naik, Intel Research Chang-Seo Park, University of California Berkeley Koushik Sen, University of California Berkeley David Gay, Intel Research |
| 2009 | Invariant-Based Automatic Testing of AJAX User Interfaces | Ali Mesbah & Arie van Deursen, Delft University of Technology |
| 2009 | Does Distributed Development Affect Software Quality? An Empirical Case Study of Windows Vista | Christian Bird, University of California Davis Nachiappan Nagappan, Microsoft Research Premkumar Devanbu, University of California Davis Harald Gall, University of Zurich Brendan Murphy, Microsoft Research |
| 2009 | Automatically finding patches using genetic programming | Westley Weimer, University of Virginia ThanhVu Nguyen, University of New Mexico Claire Le Goues, University of Virginia Stephanie Forrest, University of New Mexico |
| 2008 | Precise memory leak detection for java software using container profiling | Guoqing Xu & Atanas Rountev, Ohio State University |
| 2008 | Debugging reinvented: asking and answering why and why not questions about program behavior | Andrew J. Ko & Brad A. Myers, Carnegie Mellon University |
| 2008 | Recommending adaptive changes for framework evolution | Barthélémy Dagenais & Martin P. Robillard, McGill University |
| 2008 | Predicting Accurate and Actionable Static Analysis Warnings: An Experimental Approach | Joseph Ruthruff, University of Nebraska-Lincoln John Penix, Google J. David Morgenthaler, Google Sebastian Elbaum, University of Nebraska-Lincoln Gregg Rothermel, University of Nebraska-Lincoln |
| 2008 | The effect of program and model structure on mc/dc test adequacy coverage | Ajitha Rajan, University of Minnesota Michael W. Whalen, Rockwell Collins Mats P.E. Heimdahl, University of Minnesota |
| 2007 | Refactoring for Parameterizing Java Classes | Adam Kiezun, Massachusetts Institute of Technology Michael D. Ernst, Massachusetts Institute of Technology Frank Tip, IBM Research Robert M. Fuhrer, IBM Research |
| 2007 | Tracking Code Clones in Evolving Software | Ekwa Duala-Ekoko & Martin P. Robillard, McGill University |
| 2007 | Matching and Merging of Statecharts Specifications | Shiva Nejati, University of Toronto Mehrdad Sabetzadeh, University of Toronto Marsha Chechik, University of Toronto Steve Easterbrook, University of Toronto Pamela Zave, AT&T Laboratories |
| 2007 | Predicting Faults from Cached History | Sunghun Kim, Massachusetts Institute of Technology Thomas Zimmermann, Saarland University E. James Whitehead Jr., University of California Santa Cruz Andreas Zeller, Saarland University |
| 2006 | Model-Based Development of Dynamically Adaptive Software | Ji Zhang & Betty H.C. Cheng, Michigan State University |
| 2006 | Who Should Fix This Bug? | John Anvik, University of British Columbia Lyndon Hiew, University of British Columbia Gail C. Murphy, University of British Columbia |
| 2005 | Eliciting Design Requirements for Maintenance-Oriented IDEs: A Detailed Study of Corrective and Perfective Maintenance Tasks | Andrew Ko, Carnegie Mellon University Htet Htet Aung, Carnegie Mellon University Brad Myers, Carnegie Mellon University |
| 2005 | Is Mutation an Appropriate Tool for Testing Experiments? | James Andrews, University of Western Ontario Lionel Briand, Carleton University Yvan Labiche, Carleton University |
| 2005 | Using Structural Context to Recommend Source Code Examples | Reid Holmes & Gail Murphy, University of British Columbia |
| 2005 | Data Structure Repair Using Goal-Directed Reasoning | Brian Demsky & Martin Rinard, Massachusetts Institute of Technology |
| 2004 | SNIAFL: Towards a Static Non-Interactive Approach to Feature Location | Wei Zhao, Peking University Lu Zhang, Peking University Yin Liu, Peking University Jiasu Sun, Peking University Fuqing Yang, Peking University |
| 2004 | Extending the REpresentational State Transfer (REST) Architectural Style for Decentralized Systems | Rohit Khare & Richard N. Taylor, University of California Irvine |
| 2004 | An Empirical Study of Software Reuse vs. Defect-Density and Stability | Parastoo Mohagheghi, Ericsson Reidar Conradi, Norwegian University of Science and Technology Ole M. Killi, Norwegian University of Science and Technology Henrik Schwarz, Norwegian University of Science and Technology |
| 2004 | A Tool for Writing and Debugging Algebraic Specifications | Johannes Henkel & Amer Diwan, University of Colorado |
| 2004 | Static Checking of Dynamically Generated Queries in Database Applications | Carl Gould, University of California Davis Zhendong Su, University of California Davis Premkumar Devanbu, University of California Davis |
| 2003 | Precise Dynamic Slicing Algorithms | Xiangyu Zhang, University of Arizona Rajiv Gupta, University of Arizona Youtao Zhang, University of Arizona |
| 2003 | Modular Verification of Software Components in C | Sagar Chaki, Carnegie Mellon University Edmund Clarke, Carnegie Mellon University Alex Groce, Carnegie Mellon University Somesh Jha, University of Wisconsin Helmut Veith, Technische Universität Wien |


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{% block content %} {% endblock %}
Copyright © 2019 - All Rights Reserved -
Brybz
Design by
BrybzThickSmoke/Hussein


Assume that x
contains 9 and y
contains 7.
The expression evaluates to False. One way to show this is below.
A truth table is another way to show the evaluation of a boolean expression. Each row of a truth table starts with a selection of truth values for the operands. There is one row for each possible selection of truth values. The columns show the truth value of expressions and subexpressions containing the operands.
| Operands | Boolean Expression | |
|---|---|---|
| x < 12 | y > 10 | x < 12 && y > 10 |
| F | F | F |
| F | T | F |
| T | F | F |
| T | T | T |
The above table has four rows for the truth values,
one row for each of the four possible choices for the two operands.
(The operands are the relational expressions x<12
and y>10
.)
The last column shows the result of the
&&
operator
with those values.
What row of the table is used when x
contains 1 and y
contains 23?


Functions for manipulating mouse inputs
◆ ev_type_t
◆ state_t
| Enumerator |
|---|
| INIT | |
| DRAW | |
| COMPLETE | |
Definition at line 27 of file mouse.h.
◆ isCorrectMovement()
| int isCorrectMovement |
( |
| ) |
|
Checks if the movement of the mouse is overflowed or signed.
- Returns
- 1 on success, 0 otherwise
Definition at line 130 of file mouse.c.
◆ isLeftButtonPressed()
| int isLeftButtonPressed |
( |
| ) |
|
Checks if the mouse left button is pressed.
- Returns
- 1 on true, 0 otherwise
Definition at line 122 of file mouse.c.
◆ isRightButtonPressed()
| int isRightButtonPressed |
( |
| ) |
|
Checks if the mouse right button is pressed.
- Returns
- 1 on true, 0 otherwise
Definition at line 114 of file mouse.c.
◆ mouse_handler()
Reads packets from keyboard controller.
Definition at line 71 of file mouse.c.
◆ mouse_subscribe_int()
| int mouse_subscribe_int |
( |
| ) |
|
Subscribes the mouse interruptions.
- Returns
- 1 on error, 0 on success
Definition at line 145 of file mouse.c.
◆ mouse_unsubscribe_int()
| int mouse_unsubscribe_int |
( |
| ) |
|
Unsubscribes the mouse interruptions.
- Returns
- 1 on error, 0 on success
Definition at line 158 of file mouse.c.
◆ mouseWrite()
| int mouseWrite |
( |
unsigned long |
command | ) |
|
Mix of writes and reads through keybaord controller.
- Returns
- 1 on error, 0 otherwise
Definition at line 227 of file mouse.c.
◆ printPackets()
Prints packets on screen.
Definition at line 271 of file mouse.c.
◆ readInfoThroughKBC()
| int readInfoThroughKBC |
( |
unsigned long * |
data | ) |
|
Reads information through keyboard controller.
- Returns
- 1 on error, 0 success
Definition at line 193 of file mouse.c.
◆ resetPackets()
Resets values from the packets.
Definition at line 107 of file mouse.c.
◆ setMousePackets()
Fills the mouse_t structure with correct values.
Definition at line 12 of file mouse.c.
◆ writeInfoThroughKBC()
| int writeInfoThroughKBC |
( |
unsigned long |
kbd_port, |
|
|
unsigned long |
command |
|
) |
| |
Writes information through keyboard controller.
- Returns
- 1 on error, 0 success
Definition at line 168 of file mouse.c.
◆ distanceY
◆ mouse_t


Low-level conversion functions from R to HDF5 and vice versa
RToH5(Robj, dtype, nelem) H5ToR_Pre(dtype, nelem) H5ToR_Post(Robj, dtype, nelem, flags = getOption("hdf5r.h5tor_default"), id = -1)
| Robj | The R-object to transfer to HDF5 |
|---|---|
| dtype | Datatype of the HDF5 object. Of class |
| nelem | Number of elements to copy |
| flags | Some flags governing edge cases of conversion from HDF5 to R. This is related to how integers are being treated and
the issue of R not being able to natively represent 64bit integers and not at all being able to represent unsigned 64bit integers
(even using add-on packages). The constants governing this are part of |
| id | When creating a reference, an id for the file (or an object in the file) is needed. By default |
The converted object or the buffer into which the object is written.
These are the low-level function that dispatch the R object to HDF5 object conversion to the underlying C code.
None of these should be accessed by the end-user under normal circumstances. See also convertRoundTrip
for an example of how to use them.


Friends
Confirm Group Delete
{if logged_out} {embed="%prefix%inc/login"} {if:else} {embed="%prefix%inc/control_column"}
{exp:friends:groups type="owner" friends_group_id="{segment_3}"}
{/if}
Warning! This action cannot be undone!
Are you sure you'd like to delete the group named:
"{friends_group_title}"


ViIcon
public struct ViIcon
Helper to load icons. As icons might be loaded differently from CocoaPods or from embedded sources This is simplify the process
-
A public reference to the icons bundle, that aims to detect the correct bundle to use i.e. whether loading from Cocoa Pods bundle
Declaration
Swift
public static var bundle: Bundle
-
Get the icon by the image name.
- Parameters:
- name: icon image name
- renderMode: render mode
Returns
UIImageDeclaration
Swift
public static func icon(_ name: String, _ renderMode : UIImageRenderingMode = .alwaysTemplate) -> UIImage?
Parameters
name
icon image name
renderMode
render mode
Return Value
UIImage
- Parameters:
-
Find Similar icon
Declaration
Swift
public static let find_similar = ViIcon.icon("find_similar")
-
Heart icon. Represent default action i.e. add to wishlist
Declaration
Swift
public static let like = ViIcon.icon("heart")
-
Power by Visenze logo
Declaration
Swift
public static let power_visenze = ViIcon.icon("power_visenze", .alwaysOriginal)
-
Back icon
Declaration
Swift
public static let back = ViIcon.icon("back_icon")
-
Filter icon
Declaration
Swift
public static let filter = ViIcon.icon("filter")
-
Color Picker icon . Used in Color Search widget
Declaration
Swift
public static let color_pick = ViIcon.icon("color_pick")
-
Tick icon. Used in color picker to indicate current selected color
Declaration
Swift
public static let tick = ViIcon.icon("tick")
-
image for no result
Declaration
Swift
public static let no_result = ViIcon.icon("no_result" )
-
image for generice error
Declaration
Swift
public static let generic_err = ViIcon.icon("generic_err" , .alwaysOriginal )
-
Undocumented
Declaration
Swift
public struct ViIcon
-
Info icon. Used for taking photo user guide when using camera
Declaration
Swift
public static let info = ViIcon.icon("info" , .alwaysOriginal)
-
Lights icon to indicate flash on/off
Declaration
Swift
public static let lights = ViIcon.icon("lights" , .alwaysOriginal)
-
Lights icon to indicate flash on. Tintable
Declaration
Swift
public static let lights_sel = ViIcon.icon("lights" )
-
For switching between back and front camera icon
Declaration
Swift
public static let reverse = ViIcon.icon("reverse" , .alwaysOriginal)
-
Crop icon
Declaration
Swift
public static let crop = ViIcon.icon("crop")
-
Camera icon. Inititate camera view
Declaration
Swift
public static let camera = ViIcon.icon("camera")
-
Big button for taking photo in camera view
Declaration
Swift
public static let big_camera = ViIcon.icon("big_camera" , .alwaysOriginal)
-
Empty circle button i.e. as OK button to indicate action will be performed
Declaration
Swift
public static let big_camera_empty = ViIcon.icon("big_camera_empty", .alwaysOriginal)
-
Undocumented
Declaration
Swift
public struct ViIcon
-
Permission denied icon when trying to access camera / photo library
Declaration
Swift
public static let permissionsIcon = ViIcon.icon("permissionsIcon" , .alwaysOriginal)


Research Neuroplasticity I value the understanding of Neuroplasticity as a physical representation of the mind responding to a flexible mindset. This understanding I believe is crucial in when we think of the many negative effects one might face either within a stagnent headspace or being observed by one with this particular headspace. In a world of growing acceptance for difference not just in a persons make up from birth but the ever evolving transitions of life this will have to be a widely accepted scientifical understanding. I currently relate to this idea with my predicament as I learn to shift my thought processes to accommodate for this very unique way of thinking in tech. Visualising the neurons making connections with each new lesson is helping to build a physical connection with my learning. Growth mindset is one that I gravitate towards as a new parent. The idea that a simple change in approach, in positive engagement and building a healthy relationship with failure is hugely encouraging to learn of the huge successes associated with this. I like to think about the kindness we have to apply to our minds, the gentle approach that fosters strength rather then fear and fustration. In my learning I hope to remind myself of the changing nature of learning and the positive complications that come with that.


{% extends 'base.html' %} {% block pagetitle %}Brian R. Bondy - Wordpress expected age by tag list{% endblock %} {% block title %} Wordpress expected age by tag list{% endblock %} {% block subtitle %}Calculated by using the expected value for the age each answer comes from{% endblock %} {% block main_content %}
This list contains the expected age per tag from the the Wordpress site, sorted by expected age.
The list was generated with the Wordpress April 2011 data dump on 4/25/2011 10:48:53 PM.
The creator of this list is Brian R. Bondy: Blog, Twitter, StackOverflow.
Please see the following link for other lists.


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Breakfast
Mornings can never be perfect without that triple stacked. Maple glazed, sugar dusted, fruit topped, fluffy mountain of Goodness you call pancakes!
Lunch
Whether they're long or short, thick or thin, asian or european. Noodles are bomb! u toss in butter add some herbs and garlic sprinkle some cheese! them bam you're eating the bomb!
Dinner
They say lobsters are the cockroaches of the sea.Well these are lobster's cheaper yet tastier cousin.Meet the crab!
Dessert
Everyone has space for Dessert! As a matter of fact the stomach is divided into two parts, One of them is reserved for dessert!


In the Eyes of the Aspired, from the View Quite Higher
I wrote this when I was a Teller at Wells Fargo in 2016. I thought I’d share it to inspire other aspired individuals to reach not their dreams, but their goals.
“Setting goals is the first step in turning the invisible into the visible.” — Tony Robbins
My activities in my youth were quite slothful. I would enjoy my time playing action shooter video games online. I recall staying up in the evenings till eleven at night in the same scenario of completing unfulfilling game challenges. Entering junior college in 2010 after high school, I made the decision to quit my lifelong passion of video games to culminate my educational career.
Furthermore, I pondered on the perception of my grandmother consistently seeing me enjoy my time playing video games as she did house chores all while working horrible late evening shifts. Her perception of me hated myself because I didn’t want to be another disappointment in my family.
I needed to change, fast.
I can grandma’s hard work ethic woven into the characteristics I provide for my activities. I have worked consecutively since my sophomore year of high school, in 2007. However, I crippled my grade point average during my attendance at University of California, Davis (UCD). I worked as a Student Housing Logistics member, where I moved incoming freshmen furniture, a Student Housing Janitor in my summers, and then became a cafe manager for one year. These indications displayed my distaste for a languid lifestyle, but should have focused that same attention to my studies.
Furthermore, to properly finance myself during my attendance in college, I needed to maintain my job status to support myself. These actions are not excuses for my average performance in my Mathematics upper division courses, but indicate the level of my productive daily activities.
Standing in the discussion of academia performance, I switched the emphasis of my major from General Mathematics to Applied Mathematics, the second to last year of my stay at UCD. General Mathematics offered simplistic theories and hypotheses with a tremendous amount of abstractive work that had no applications to world scenarios; the degree of application being higher in applied mathematics compared to the general case.
My actual shift from general Mathematics would have been Statistics, but that would have required me to not progress from my undergraduate career until spring of 2017. By graduating in March 2016 at UCD, I realized I was able to perform Statistics and other relatable Data Science applications independent from my attendance at my university.
This past fall, I moved from Davis, Ca to San Francisco to become a data scientist consultant while simultaneously delve into the data science community. However, these initial months of my data scientist goals have been set back. I could not find relatable careers outside my current in-congruent job to hone my technical skills. I am currently a teller at Wells Fargo. The rich time I utilized to financially support myself with my job pauses my technical tools and knowledge for implementing big data analysis.
My vigorous passion to become a data scientist all while being unique stems from my cautious nature to avoid generational repetition of being low income status.
My mother and several older family members never required me to go to high school. I could easily not go to high school, and not graduate from it. I could have continued playing video games and binge watching television shows in my latter part of my teen years.
Furthermore, I didn’t have to waste two to three hours in the hot weather or cold rain for public transportation to get to school. I didn’t have to work a minimum wage job to support myself to get a computer, feed myself properly, or generate funds to help my grandma.
However, my path to not be another low income statistic has lead me to be the first in my family to getting a college degree, and move forward to a progressing technical world of innovation, San Francisco…and become a Data Scientist.


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Halide
12.0.0
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Class that provides a type that implements half precision floating point (IEEE754 2008 binary16) in software. More...
#include <Float16.h>
Public Member Functions | |
| operator float () const | |
| Cast to float. More... | |
| operator double () const | |
| Cast to double. More... | |
| operator int () const | |
| Cast to int. More... | |
| float16_t | operator- () const |
| Return a new float16_t with a negated sign bit. More... | |
| float16_t | operator+ (float16_t rhs) const |
| Arithmetic operators. More... | |
| float16_t | operator- (float16_t rhs) const |
| float16_t | operator* (float16_t rhs) const |
| float16_t | operator/ (float16_t rhs) const |
| float16_t | operator+= (float16_t rhs) |
| float16_t | operator-= (float16_t rhs) |
| float16_t | operator*= (float16_t rhs) |
| float16_t | operator/= (float16_t rhs) |
| bool | operator== (float16_t rhs) const |
| Comparison operators. More... | |
| bool | operator!= (float16_t rhs) const |
| bool | operator> (float16_t rhs) const |
| bool | operator< (float16_t rhs) const |
| bool | operator>= (float16_t rhs) const |
| bool | operator<= (float16_t rhs) const |
| bool | is_nan () const |
| Properties. More... | |
| bool | is_infinity () const |
| bool | is_negative () const |
| bool | is_zero () const |
| uint16_t | to_bits () const |
| Returns the bits that represent this float16_t. More... | |
Constructors | |
| float16_t (float value) | |
| Construct from a float, double, or int using round-to-nearest-ties-to-even. More... | |
| float16_t (double value) | |
| Construct from a float, double, or int using round-to-nearest-ties-to-even. More... | |
| float16_t (int value) | |
| Construct from a float, double, or int using round-to-nearest-ties-to-even. More... | |
| float16_t ()=default | |
| Construct a float16_t with the bits initialised to 0. More... | |
Static Public Member Functions | |
| static float16_t | make_zero () |
| Get a new float16_t that represents a special value. More... | |
| static float16_t | make_negative_zero () |
| static float16_t | make_infinity () |
| static float16_t | make_negative_infinity () |
| static float16_t | make_nan () |
| static float16_t | make_from_bits (uint16_t bits) |
| Get a new float16_t with the given raw bits. More... | |
Static Public Attributes | |
| static const int | mantissa_bits = 10 |
| static const uint16_t | sign_mask = 0x8000 |
| static const uint16_t | exponent_mask = 0x7c00 |
| static const uint16_t | mantissa_mask = 0x03ff |
Class that provides a type that implements half precision floating point (IEEE754 2008 binary16) in software.
This type is enforced to be 16-bits wide and maintains no state other than the raw IEEE754 binary16 bits so that it can passed to code that checks a type's size and used for halide_buffer_t allocation.
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explicit |
Construct from a float, double, or int using round-to-nearest-ties-to-even.
Out-of-range values become +/- infinity.
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explicit |
Construct from a float, double, or int using round-to-nearest-ties-to-even.
Out-of-range values become +/- infinity.
|
explicit |
Construct from a float, double, or int using round-to-nearest-ties-to-even.
Out-of-range values become +/- infinity.
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default |
Construct a float16_t with the bits initialised to 0.
This represents positive zero.
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explicit |
Cast to float.
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explicit |
Cast to double.
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explicit |
Cast to int.
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static |
Get a new float16_t that represents a special value.
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static |
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Get a new float16_t with the given raw bits.
| bits | The bits conformant to IEEE754 binary16 |
| bool Halide::float16_t::operator== | ( | float16_t | rhs | ) | const |
Comparison operators.
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inline |
| bool Halide::float16_t::operator> | ( | float16_t | rhs | ) | const |
| bool Halide::float16_t::operator< | ( | float16_t | rhs | ) | const |
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inline |
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inline |
| bool Halide::float16_t::is_nan | ( | ) | const |
Properties.
| bool Halide::float16_t::is_infinity | ( | ) | const |
| bool Halide::float16_t::is_negative | ( | ) | const |
| bool Halide::float16_t::is_zero | ( | ) | const |
| uint16_t Halide::float16_t::to_bits | ( | ) | const |
Returns the bits that represent this float16_t.
An alternative method to access the bits is to cast a pointer to this instance as a pointer to a uint16_t.
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static |
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