Module: ActiveRecord::Transactions
| Child Modules: | |
| Extended by: | |
| Included in: | |
| Defined in: |
Overview
See ClassMethods for documentation.
Constant Summarycollapse
- ACTIONS =
-
[:create, :destroy, :update]
Instance Method Summary collapse
-
#add_to_transaction
Add the record to the current transaction so that the
#after_rollback
and#after_commit
callbacks can be called. - #before_committed!
-
#clear_transaction_record_state
protected
Clear the new record state and id of a record.
-
#committed!(should_run_callbacks: true)
Call the
#after_commit
callbacks. - #destroy
-
#force_clear_transaction_record_state
protected
Force to clear the transaction record state.
- #has_transactional_callbacks? ⇒ Boolean private
-
#remember_transaction_record_state
protected
Save the new record state and id of a record so it can be restored later if a transaction fails.
-
#restore_transaction_record_state(force = false)
protected
Restore the new record state and id of a record that was previously saved by a call to save_record_state.
-
#rollback_active_record_state!
Reset id and @new_record if the transaction rolls back.
-
#rolledback!(force_restore_state: false, should_run_callbacks: true)
Call the
#after_rollback
callbacks. - #save
- #save!
- #set_transaction_state(state) private
-
#sync_with_transaction_state
private
Updates the attributes on this particular Active Record object so that if it's associated with a transaction, then the state of the Active Record object will be updated to reflect the current state of the transaction.
- #touch
-
#transaction(options = {}, &block)
See ClassMethods for detailed documentation.
-
#transaction_include_any_action?(actions) ⇒ Boolean
protected
Determine if a transaction included an action for :create, :update, or :destroy.
-
#transaction_record_state(state)
protected
Determine if a record was created or destroyed in a transaction.
- #update_attributes_from_transaction_state(transaction_state) private
-
#with_transaction_returning_status
Executes
method
within a transaction and captures its return value as a status flag.
Methods included from ActiveSupport::Concern
append_features, class_methods, .extended, included
Instance Method Details
#add_to_transaction
Add the record to the current transaction so that the #after_rollback
and
#after_commit
callbacks can be called.
374 375 376 377 378 379 380 381 382
# File 'activerecord/lib/active_record/transactions.rb', line 374
def add_to_transaction if has_transactional_callbacks? self.class.connection.add_transaction_record(self) else sync_with_transaction_state set_transaction_state(self.class.connection.transaction_state) end remember_transaction_record_state end
#before_committed!
[ GitHub ]342 343 344 345
# File 'activerecord/lib/active_record/transactions.rb', line 342
def before_committed! # :nodoc: _run_before_commit_without_transaction_enrollment_callbacks _run_before_commit_callbacks end
#clear_transaction_record_state (protected)
Clear the new record state and id of a record.
424 425 426 427
# File 'activerecord/lib/active_record/transactions.rb', line 424
def clear_transaction_record_state #:nodoc: @_start_transaction_state[:level] = (@_start_transaction_state[:level] || 0) - 1 force_clear_transaction_record_state if @_start_transaction_state[:level] < 1 end
#committed!(should_run_callbacks: true)
Call the #after_commit
callbacks.
Ensure that it is not called if the object was never persisted (failed create), but call it after the commit of a destroyed object.
351 352 353 354 355 356 357 358
# File 'activerecord/lib/active_record/transactions.rb', line 351
def committed!(should_run_callbacks: true) #:nodoc: if should_run_callbacks && destroyed? || persisted? _run_commit_without_transaction_enrollment_callbacks _run_commit_callbacks end ensure force_clear_transaction_record_state end
#destroy
[ GitHub ]313 314 315
# File 'activerecord/lib/active_record/transactions.rb', line 313
def destroy #:nodoc: with_transaction_returning_status { super } end
#force_clear_transaction_record_state (protected)
Force to clear the transaction record state.
430 431 432
# File 'activerecord/lib/active_record/transactions.rb', line 430
def force_clear_transaction_record_state #:nodoc: @_start_transaction_state.clear end
#has_transactional_callbacks? ⇒ Boolean (private)
477 478 479
# File 'activerecord/lib/active_record/transactions.rb', line 477
def has_transactional_callbacks? # :nodoc: !_rollback_callbacks.empty? || !_commit_callbacks.empty? || !_before_commit_callbacks.empty? end
#remember_transaction_record_state (protected)
Save the new record state and id of a record so it can be restored later if a transaction fails.
413 414 415 416 417 418 419 420 421
# File 'activerecord/lib/active_record/transactions.rb', line 413
def remember_transaction_record_state #:nodoc: @_start_transaction_state[:id] = id @_start_transaction_state.reverse_merge!( new_record: @new_record, destroyed: @destroyed, frozen?: frozen?, ) @_start_transaction_state[:level] = (@_start_transaction_state[:level] || 0) + 1 end
#restore_transaction_record_state(force = false) (protected)
Restore the new record state and id of a record that was previously saved by a call to save_record_state.
435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450
# File 'activerecord/lib/active_record/transactions.rb', line 435
def restore_transaction_record_state(force = false) #:nodoc: unless @_start_transaction_state.empty? transaction_level = (@_start_transaction_state[:level] || 0) - 1 if transaction_level < 1 || force restore_state = @_start_transaction_state thaw @new_record = restore_state[:new_record] @destroyed = restore_state[:destroyed] pk = self.class.primary_key if pk && read_attribute(pk) != restore_state[:id] write_attribute(pk, restore_state[:id]) end freeze if restore_state[:frozen?] end end end
#rollback_active_record_state!
Reset id and @new_record if the transaction rolls back.
332 333 334 335 336 337 338 339 340
# File 'activerecord/lib/active_record/transactions.rb', line 332
def rollback_active_record_state! remember_transaction_record_state yield rescue Exception restore_transaction_record_state raise ensure clear_transaction_record_state end
#rolledback!(force_restore_state: false, should_run_callbacks: true)
Call the #after_rollback
callbacks. The force_restore_state
argument indicates if the record state should be rolled back to the
beginning or just to the last savepoint.
362 363 364 365 366 367 368 369 370
# File 'activerecord/lib/active_record/transactions.rb', line 362
def rolledback!(force_restore_state: false, should_run_callbacks: true) #:nodoc: if should_run_callbacks _run_rollback_callbacks _run_rollback_without_transaction_enrollment_callbacks end ensure restore_transaction_record_state(force_restore_state) clear_transaction_record_state end
#save
[ GitHub ]317 318 319 320 321
# File 'activerecord/lib/active_record/transactions.rb', line 317
def save(*) #:nodoc: rollback_active_record_state! do with_transaction_returning_status { super } end end
#save!
[ GitHub ]323 324 325
# File 'activerecord/lib/active_record/transactions.rb', line 323
def save!(*) #:nodoc: with_transaction_returning_status { super } end
#set_transaction_state(state) (private)
[ GitHub ]473 474 475
# File 'activerecord/lib/active_record/transactions.rb', line 473
def set_transaction_state(state) # :nodoc: @transaction_state = state end
#sync_with_transaction_state (private)
Updates the attributes on this particular Active Record object so that if it's associated with a transaction, then the state of the Active Record object will be updated to reflect the current state of the transaction.
The @transaction_state
variable stores the states of the
associated transaction. This relies on the fact that a transaction can only
be in one rollback or commit (otherwise a list of states would be
required). Each Active Record object inside of a transaction carries that
transaction's TransactionState.
This method checks to see if the ActiveRecord object's state reflects the TransactionState, and rolls back or commits the Active Record object as appropriate.
Since Active Record objects can be inside multiple transactions, this method recursively goes through the parent of the TransactionState and checks if the Active Record object reflects the state of the object.
498 499 500
# File 'activerecord/lib/active_record/transactions.rb', line 498
def sync_with_transaction_state update_attributes_from_transaction_state(@transaction_state) end
#touch
[ GitHub ]327 328 329
# File 'activerecord/lib/active_record/transactions.rb', line 327
def touch(*) #:nodoc: with_transaction_returning_status { super } end
#transaction(options = {}, &block)
See ClassMethods for detailed documentation.
309 310 311
# File 'activerecord/lib/active_record/transactions.rb', line 309
def transaction( = {}, &block) self.class.transaction(, &block) end
#transaction_include_any_action?(actions) ⇒ Boolean (protected)
Determine if a transaction included an action for :create, :update, or :destroy. Used in filtering callbacks.
458 459 460 461 462 463 464 465 466 467 468 469
# File 'activerecord/lib/active_record/transactions.rb', line 458
def transaction_include_any_action?(actions) #:nodoc: actions.any? do |action| case action when :create transaction_record_state(:new_record) when :destroy destroyed? when :update !(transaction_record_state(:new_record) || destroyed?) end end end
#transaction_record_state(state) (protected)
Determine if a record was created or destroyed in a transaction. State should be one of :new_record or :destroyed.
453 454 455
# File 'activerecord/lib/active_record/transactions.rb', line 453
def transaction_record_state(state) #:nodoc: @_start_transaction_state[state] end
#update_attributes_from_transaction_state(transaction_state) (private)
[ GitHub ]502 503 504 505 506 507
# File 'activerecord/lib/active_record/transactions.rb', line 502
def update_attributes_from_transaction_state(transaction_state) if transaction_state && transaction_state.finalized? restore_transaction_record_state if transaction_state.rolledback? clear_transaction_record_state end end
#with_transaction_returning_status
Executes method
within a transaction and captures its return
value as a status flag. If the status is true the transaction is committed,
otherwise a ROLLBACK is issued. In any case the status flag is returned.
This method is available within the context of an Base instance.
390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408
# File 'activerecord/lib/active_record/transactions.rb', line 390
def with_transaction_returning_status status = nil self.class.transaction do add_to_transaction begin status = yield rescue ActiveRecord::Rollback clear_transaction_record_state status = nil end raise ActiveRecord::Rollback unless status end status ensure if @transaction_state && @transaction_state.committed? clear_transaction_record_state end end


--- layout: demos title: Create Auto Scale Group ---
Servers will be created and deleted based on your policies. Use custom saved images that configure your applications on boot.
More about Auto Scale Images »
More about Auto Scale Setup »
View Our FAQs »


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4
Crispy pancakes, but not as you know them. Served with a spicy dipping sauce.
For the dipping sauce, pour 120ml/4fl oz water into a bowl. Add the sugar and whisk until dissolved. Stir in the fish sauce and lime juice.
Using a pestle and mortar, bash the garlic and chilli together until well combined. Mix into the fish sauce and add the julienned carrot. Set aside.
For the banh xeo, mix the rice flour, cornflour and turmeric together. Season with a pinch of salt and pepper. Stir in the coconut milk and 310ml/10½fl oz water to make a thin batter. Set aside.
Heat a little peanut oil in a lidded non-stick frying pan set over a high heat. When hot, add shallot and garlic, and cook until fragrant, but not coloured. Add the sliced pork and fry for a few minutes, until cooked through. Add the prawns and fry until cooked through. Transfer to a bowl.
Add a ladleful of the batter and about an eighth of the filling mixture. Cover the pan with the lid. Cook until golden-brown and crisp on the under-side. Put some beansprouts on one half of the pancake. Replace the lid and cook for another minute. Remove from the heat and fold the pancake in half. Repeat with the remaining batter and filling to make eight pancakes.
To serve, divide the lettuce leaves between serving plates. Top each leaf with some cucumber, mint and coriander. Finely slice the pancakes and divide between the lettuce leaves. Serve with the dipping sauce in a bowl.


class: center, middle, inverse, title-slide # Reproducible computation at scale in R ### Will Landau ---  ## Large statistical computation * [Bayesian data analysis](https://mc-stan.org/) * [Bayesian network meta-analysis](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/bayesian-network-meta-analysis.html) * [Graph-based multiple comparison procedures](https://github.com/kornl/gMCP) * [Subgroup identification](https://cran.r-project.org/web/packages/TSDT/index.html) * [Predictive modeling](http://appliedpredictivemodeling.com/computing) * [Deep neural networks](https://keras.rstudio.com/) * [PK/PD modeling](https://github.com/nlmixrdevelopment/nlmixr) * Clinical trial simulation * Target identification ??? Thank you all for coming, and thank you to R/Pharma for the opportunity to speak today. I come from the life sciences, and we develop ambitious computational workflows for Statistics and data science. There's a lot of Bayesian analysis, machine learning, simulation, and prediction. Other domains have similar workloads, and we need to think about both efficiency and reproducibility right from the start. --- ## Repetition: the overlooked bane of long computation
 ![](./images/reality.png) --- ## Interconnected tasks    ??? A large workflow has a large number of moving parts. We have datasets that we preprocess or simulate, analyses of those datasets, and summaries of the analyses. --- ## Changes    ??? If you change any one of these parts - whether it's a bugfix, a tweak to a model, or some new data - --- ## Consequences    ??? Then everything that depends on it is no longer valid, and you need to rerun the computation to bring the results back up to date. This is seriously frustrating when you're in development and you're still making a constant stream of changes to code and data in real time. If every change means you need to rerun the project, there's no way the results can keep up... --- ## Dilemma: short runtimes or reproducible results? ![](./images/decisions.png) --- ## Let a pipeline tool figure out what to rerun. ![](./images/pipeline_graph.png) * Save time while ensuring computational reproducibility. * Automatic parallel/distributed computing based on the directed acyclic graph. --- ## Pipeline tools    * Existing pipeline tools: https://github.com/pditommaso/awesome-pipeline * Most are language-agnostic or designed for Python or the shell. ## {targets} * Fundamentally designed for R. * Supports a clean, modular, function-oriented programming style. * Abstracts files as R objects and automatically manages data. * Surpasses the permanent limitations of its predecessor, [`drake`](https://github.com/ropensci/drake): <https://books.ropensci.org/targets/drake.html>. * Continuation of the ideas from `remake` by Rich FitzJohn: <https://github.com/richfitz/remake>. --- ## Example targets workflow * Find the model that best predicts which customers will cancel their telecom subscriptions. * IBM Cognos Analytics Telco customer churn dataset (links [here](https://community.ibm.com/community/user/businessanalytics/blogs/steven-macko/2019/07/11/telco-customer-churn-1113) and [here](https://github.com/IBM/telco-customer-churn-on-icp4d/blob/main/data/Telco-Customer-Churn.csv)). * Example from [Matt Dancho's 2018 RStudio AI Blog post](https://blogs.rstudio.com/tensorflow/posts/2018-01-11-keras-customer-churn/). * Workflow principles generalize to the other fields, such as the life sciences. ??? Let's look at an example. We're going to set up a machine learning project to predict customer dropout, or churn, based on the publicly available IBM Watson Telco customer churn dataset. We're going to train a bunch of deep neural nets on the data and pick the one with the best testing accuracy. --- background-image: ./images/not.png ##  Move away from numbered imperative scripts. ```r run_everything.R R/ ├── 01-data.R ├── 02-munge.R ├── 03-model.R ├── 04-results.R └── 05-plot.R data/ └── customer_churn.csv ``` ??? Before we get started, let's talk about the implementation strategy. We're going to move away from numbered scripts and R Markdown as a way to manage the computation end to end. It's an okay strategy for small projects, but it falls apart quickly as a project grows. --- ##  Embrace **functions**. > - Everything that exists is an object. > - Everything that happens is a function call. > > John Chambers ```r add_things <- function(argument1, argument2) { argument1 + argument2 } add_things(1, 2) #> [1] 3 add_things(c(3, 4), c(5, 6)) #> [1] 8 10 ``` ??? Functions scale much better for big stuff. A function is just a reusable set of instructions with multiple inputs and a single return value. Usually those inputs are explicitly defined and easy to create, and usually the function has an informative name. Functions are a fundamental built-in feature of almost every programming language we have, and they are particularly well suited to R, which was designed with formal functional programming principles in mind. The most obvious use for functions is as a way to avoid copies of repeated code scattered throughout your project. So instead of copying and pasting the same code block everywhere, you just call the function. But functions are not just for code you want to reuse, they're for code you want to understand. Functions are custom shorthand. They make your work easier to read, understand, break down into manageable pieces, document, test, and validate for serious research. --- ## Functions for customer churn ```r split_data <- function(churn_file) { read_csv(churn_file, col_types = cols()) %>% initial_split(prop = 0.7) } prepare_recipe <- function(churn_data) { churn_data %>% training() %>% recipe(Churn ~ .) %>% step_rm(customerID) %>% step_naomit(all_outcomes(), all_predictors()) %>% step_discretize(tenure, options = list(cuts = 6)) %>% step_log(TotalCharges) %>% step_mutate(Churn = ifelse(Churn == "Yes", 1, 0)) %>% step_dummy(all_nominal(), -all_outcomes()) %>% step_center(all_predictors(), -all_outcomes()) %>% step_scale(all_predictors(), -all_outcomes()) %>% prep() } ``` ??? Most of your functions revolve around 3 kinds of tasks: preparing datasets, analyzing datasets, and summarizing analyses. These two functions are all about the data. The first one accepts a file path, reads in the data, and splits it into training and test sets. The prepare_recipe() function accepts the return value from split_data() and converts the data into a format that our Keras models can accept in subsequent steps. --- ## Functions for customer churn ```r define_model <- function(churn_recipe, units1, units2, act1, act2, act3) { # ... } train_model <- function(churn_recipe, units1, units2, act1, act2, act3) { # ... } test_accuracy <- function(churn_data, churn_recipe, churn_model) { # ... } test_model <- function(churn_data, churn_recipe, units1, units2, act1, act2, act3) { # ... } retrain_run <- function(churn_run, churn_recipe) { # ... } ``` ??? Similarly, you define functions to define, train, and test the Keras models. --- ## Typical project structure * There are many variations on this theme. ```r _targets.R # Required top-level configuration file. R/ *└── functions.R data/ └── customer_churn.csv ``` ??? You can organize your functions however you want, but it's common practice to put them in scripts inside an R/ folder. Similarly, input datasets can go anywhere, but a data/ folder just helps keep things clean. And at this point, you have a good clean function-oriented project. Even if you decide not to use targets, this function-oriented style still has a lot of value. However, if you're thinking about using targets, then converting to functions is almost all of the work. Once you've done that, you're already almost there. All you need now is to outline the specific steps of the computation in a formal pipeline. And that's where this _targets.R script comes into play. It always lives at the root of the project, and it's always called "_targets.R". --- ## Build up your workflow as a list of targets. ```r # _targets.R library(targets) source("R/functions.R") tar_option_set(packages = c("keras", "tidyverse", "rsample", "recipes", "yardstick")) list( tar_target(churn_file, "data/customer_churn.csv", format = "file"), tar_target(churn_data, split_data(churn_file)), tar_target(churn_recipe, prepare_recipe(churn_data)) ) ``` ??? The purpose of _targets.R is to set up the project at a high level. It loads the packages required to define the pipeline, it loads your custom functions and global objects, it sets high-level options such as the packages the targets are going to need, and it defines the pipeline at the very end. At the bottom of _targets.R, you list out objects called targets. Each target is an individual step in the workflow. It has an informative name like "sim" or "patients", and it has a R command that invokes your custom functions and returns a value.  There are several utility functions that inspect the pipeline for correctness. The tar_manifest() function shows you all the names of the targets and the R commands associated with them. --- ## targets understands code and data dependencies. ```r tar_visnetwork() ```    ??? It's always good practice to visualize the dependency graph of the plan. targets has functions to do this for you, and it really demystifies how the package works. So here you see the flow of the project from left to right. We reproducibly track an input data file, we load that data to split into training and test, and we prepare that data for the models using a Tidymodels recipe. But how does targets deduce this flow? How does it know that the churn_recipe depend on churn_data? The order you write targets in the pipeline does not matter. targets knows that churn_recipe depends on churn_data because the symbol "churn_data" is mentioned in the command for "churn_recipe" in the pipeline. targets scans your commands and functions without actually running them it in order to look for changes and understand dependency relationships. This is called static code analysis. --- ## Build your first targets. ```r tar_make() ``` ``` #> • start target churn_file #> • built target churn_file #> • start target churn_data #> • built target churn_data #> • start target churn_recipe #> • built target churn_recipe #> • end pipeline ``` ??? To actually run the workflow, we use a function called tar_make(). tar_make() creates a clean new reproducible R process, runs _targets.R to populate the new session and define the pipeline, resolves the dependency graph, runs the correct targets in the correct order from the dependency graph, and writes the return values to storage. --- ## Check the targets for problems - `tar_load()` and `tar_read()` get targets from the `_targets/` data store. ```r ncol(training(tar_read(churn_data))) #> [1] 21 tar_load(churn_recipe) ncol(juice(churn_recipe)) #> [1] 36 ``` ??? Afterwards, all the targets are in storage. There's a special key-value store in a hidden _targets/ folder, and targets has functions tar_load() and tar_read() to retrieve data from the store. targets abstracts artifacts as ordinary objects. You don't need to worry about where these files are located, you just need to know the target names. This is the exploratory analysis phase. Always inspect your targets for issues between calls to tar_make(). --- ## Build up the pipeline *gradually*. .large[ 1. Add a couple targets. 2. Run the pipeline with `tar_make()`. 3. Inspect the new targets with `tar_load()` and `tar_read()`. 4. Repeat often. Not very time-consuming because `tar_make()` skips up-to-date targets. ] ??? This is part of an iterative process for building up a pipeline. We add a couple targets, run the pipeline, inspect the new targets, and repeat. We do this early and often. And as you will see, because targets can iterate frequently while still saving you time. --- ## Add some models. ```r # _targets.R library(targets) source("R/functions.R") tar_option_set(packages = c("keras", "tidyverse", "rsample", "recipes", "yardstick")) list( tar_target(churn_file, "data/customer_churn.csv", format = "file"), tar_target(churn_data, split_data(churn_file)), tar_target(churn_recipe, prepare_recipe(churn_data)), * tar_target(run_relu, test_model(act1 = "relu", churn_data, churn_recipe)), * tar_target(run_sigmoid, test_model(act1 = "sigmoid", churn_data, churn_recipe)) ) ``` ??? With the data in place, we are now ready to add some models. We start with two models fit to the same data using different hyperparameters. --- ## Previous work is still up to date. ```r tar_outdated() ``` ``` #> [1] "run_relu" "run_sigmoid" ``` ??? When we inspect the pipeline, we see that some work needs to be done. But all our data processing steps are already up to date. --- ## Previous work is still up to date. ```r tar_visnetwork() ```    ??? We can see this even more clearly in the dependency graph. --- ## Up-to-date targets are skipped. ```r tar_make() ``` ``` #> ✓ skip target churn_file #> ✓ skip target churn_data #> ✓ skip target churn_recipe #> • start target run_relu #> • built target run_relu #> • start target run_sigmoid #> • built target run_sigmoid #> • end pipeline ``` ??? So when we run the pipeline again, only the models run. The tool skips the data targets because they are already up to date. --- ## Inspect the newest targets. ```r tar_read(run_relu) #> # A tibble: 1 × 6 #> accuracy units1 units2 act1 act2 act3 #> <dbl> <dbl> <dbl> <chr> <chr> <chr> #> 1 0.800 16 16 relu relu sigmoid tar_read(run_sigmoid) #> # A tibble: 1 × 6 #> accuracy units1 units2 act1 act2 act3 #> <dbl> <dbl> <dbl> <chr> <chr> <chr> #> 1 0.803 16 16 sigmoid relu sigmoid ``` ??? And as usual, we read our newest targets and verify there are no obvious issues. --- ## Find the best model ```r # _targets.R library(targets) source("R/functions.R") tar_option_set(packages = c("keras", "tidyverse", "rsample", "recipes", "yardstick")) list( ..., tar_target(run_relu, test_model(act1 = "relu", churn_data, churn_recipe)), tar_target(run_sigmoid, test_model(act1 = "sigmoid", churn_data, churn_recipe)), * tar_target( * best_run, * bind_rows(run_relu, run_sigmoid) %>% * top_n(1, accuracy) %>% * head(1) * ), * tar_target( * best_model, * retrain_run(best_run, churn_recipe), * format = "keras" * ) ) ``` ??? And we repeat the process to gradually build up the pipeline. Here, we add new targets to find the model run with the highest accuracy so far and retrain that model to return a fitted model object. For fitted Keras models, we need to write 'format = "keras"' in tar_target() because Keras models cannot be saved with R's ordinary serialization functionality. --- ## Find the best model ```r tar_make() ``` ``` #> ✓ skip target churn_file #> ✓ skip target churn_data #> ✓ skip target churn_recipe #> ✓ skip target run_relu #> ✓ skip target run_sigmoid #> • start target best_run #> • built target best_run #> • start target best_model #> • built target best_model #> • end pipeline ``` ??? As before, only only the new targets run because we didn't change any other code or data, --- ## Find the best model ```r tar_read(best_model) #> Model #> Model: "sequential_2" #> ________________________________________________________________________________ #> Layer (type) Output Shape Param # #> ================================================================================ #> dense_8 (Dense) (None, 16) 576 #> ________________________________________________________________________________ #> dropout_5 (Dropout) (None, 16) 0 #> ________________________________________________________________________________ #> dense_7 (Dense) (None, 16) 272 #> ________________________________________________________________________________ #> dropout_4 (Dropout) (None, 16) 0 #> ________________________________________________________________________________ #> dense_6 (Dense) (None, 1) 17 #> ================================================================================ #> Total params: 865 #> Trainable params: 865 #> Non-trainable params: 0 #> ________________________________________________________________________________ ``` ??? and now one of our targets is actually a trained Keras model. --- ## Try another model. ```r # _targets.R library(targets) source("R/functions.R") tar_option_set(packages = c("keras", "tidyverse", "rsample", "recipes", "yardstick")) list( ..., tar_target(run_relu, test_model(act1 = "relu", churn_data, churn_recipe)), tar_target(run_sigmoid, test_model(act1 = "sigmoid", churn_data, churn_recipe)), * tar_target(run_softmax, test_model(act1 = "softmax", churn_data, churn_recipe)), tar_target( best_run, * bind_rows(run_relu, run_sigmoid, run_softmax) %>% top_n(1, accuracy) %>% head(1) ), ... ) ``` ??? If we try another model, we just need to add another target and reference that new target in any downstream targets that need it. --- ## What gets done stays done. ```r tar_outdated() ``` ``` #> [1] "run_softmax" "best_run" "best_model" ``` ??? Now, not only are the new model and the best_run target outdated, the tool automatically calls everything downstream into question, so best_model is suspect as well. --- ## What gets done stays done. ```r tar_visnetwork() ```    ??? Again, we see this clearly in the dependency graph. run_softmax is new, best_run is outdated because it uses run_softmax, and best_model is suspect because it depends on best_run. --- ## New best model? - Only if the new run beats the old runs, which would invalidate target `best_run`.  When we run the pipeline again, of course run_softmax and best_run both execute. But if best_run doesn't change, we skip best_model. targets looks at the actual fingerprint of the data to make decisions, unlike GNU Make, which just uses timestamps. --- ## What if we need to change a function? ```r define_model <- function(churn_recipe, units1, units2, act1, act2, act3) { input_shape <- ncol( juice(churn_recipe, all_predictors(), composition = "matrix") ) keras_model_sequential() %>% layer_dense( units = units1, kernel_initializer = "uniform", activation = act1, input_shape = input_shape ) %>% * layer_dropout(rate = 0.2) %>% # previously 0.1 layer_dense( units = units2, kernel_initializer = "uniform", activation = act2 ) %>% layer_dropout(rate = 0.1) %>% ... ``` ??? If we change a function in a nontrivial way, targets notices. Let's increase the dropout rate in one of the layers in the neural net. --- ## Show invalidated functions and targets. ```r tar_visnetwork() ```    ??? The define_model() function is no longer up to date. That means neither is train_model() because it calls define_model(), and likewise with downstream functions. That means the targets downstream, which include all our model runs, are also invalidated.  But we can bring everything back up to date without rerunning the data processing.  But the data processing does rerun if we change our data file. This is because in our upstream target churn_file, we selected 'format = "file"' in the tar_target() function. That tells targets to treat the return value of the command as a vector of file and directory paths, and it watches that data for changes.  At the end of the day, targets can tell you if all your targets are up to date. This is tangible evidence that your output matches the code and data it's supposed to come from. It's evidence that someone else running the same code would get the same results. That's reproducibility. It's certainly not the only form of reproducibility, but it does increase the trust we can place in the conclusions of the project. --- ## Evidence of reproducibility ```r tar_outdated() #> character(0) tar_visnetwork() ```    ??? And again, utility functions can confirm the status of targets without needing to run tar_make(). --- ## Resources * Get [`targets`](https://github.com/ropensci/targets): ```r install.packages("remotes") remotes::install_github("ropensci/targets") ``` * Code: <https://github.com/wlandau/targets-keras> * RStudio Cloud workspace: <https://rstudio.cloud/project/1430828/> * These slides: <https://wlandau.github.io/targets-tutorial> * Tutorial materials: <https://github.com/wlandau/targets-tutorial> * Development repository: <https://github.com/ropensci/targets> * Full user manual: <https://books.ropensci.org/targets/> * Reference website: <https://docs.ropensci.org/targets/> ??? There are several resources to learn about targets. There's a reference website, an online user manual, and a repository with the example code from today. targets is nearing the end of its beta phase. I am about to submit it to rOpenSci for peer review, and I hope to have it on CRAN at the end of this year or early next year. Now is a great time for feedback because there is no formal release yet and the interface is not yet set in stone. --- ## The tutorial 1. Sign up for a free account at <https://rstudio.cloud>. 2. Log into <https://rstudio.cloud/project/1699460>. 3. Work through the R notebooks in order. 4. Optional: revisit the material again later at <https://github.com/wlandau/targets-tutorial>. Topic | Notebook ---|--- Functions | [`1-functions.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/1-functions.Rmd) Pipelines | [`2-pipelines.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/2-pipelines.Rmd) Changes | [`3-changes.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/3-changes.Rmd) Debugging | [`4-debugging.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/4-debugging.Rmd) Files | [`5-files.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/5-files.Rmd) Branching | [`6-branching.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/6-branching.Rmd) Challenge | [`7-challenge.Rmd`](https://github.com/wlandau/targets-tutorial/blob/main/7-challenge.Rmd) ??? The workshop is publicly available and deployed to RStudio Cloud. Just sign up for a cloud account and log into a free instance of RStudio Server. We will spend our remaining time working through interactive exercises in the R notebooks here, with some breaks for Q&A and live coding demos to go over the solutions. If you missed part of the exercises or just want to go back and study in your own time, the workshop will still be available. I included the link to both the source and the cloud project here. --- ## References * Dancho. "Deep Learning With Keras To Predict Customer Churn." RStudio AI Blog, 2018-01-11. <https://blogs.rstudio.com/tensorflow/posts/2018-01-11-keras-customer-churn/> * D'Angelo, Scott and Nayak, Sandhya and Martinelli, Steve. "Predict Customer Churn using Watson Machine Learning and Jupyter Notebooks on Cloud Pak for Data." Released to GitHub by IBM under the Apache Software License version 2.0. <https://github.com/IBM/telco-customer-churn-on-icp4d>. Last accessed 2020-08-29. * IBM Cognos Analytics. "Telco customer churn (11.1.3+)." IBM Community, 2019-07-11. <https://community.ibm.com/community/user/businessanalytics/blogs/steven-macko/2019/07/11/telco-customer-churn-1113>


range
(PHP 4, PHP 5, PHP 7)
range — 建立一个包含指定范围单元的数组
说明
array range ( mixed $start , mixed $limit [, number $step = 1 ] )
建立一个包含指定范围单元的数组。
参数
start
序列的第一个值。
limit
序列结束于 limit 的值。
step
如果给出了 step 的值，它将被作为单元之间的步进值。step 应该为正值。如果未指
定，step 则默认为 1。
返回值
返回的数组中从 start 到 limit 的单元，包括它们本身。
更新日志
版本 说明
5.0.0 添加了可选参数 step。
4.1.0 在 PHP 版本 4.1.0 到 4.3.2 中，range() 将数字字符串看作字符串而不是整数
to ，因此将会被作为字符序列使用。例如，"4242" 会被当作 "4" 来对待。
4.3.2
在版本 4.1.0 之前 range() 函数只产生递增的整数数组。对于字符序列和递减
4.1.0 数组的支持是 4.1.0 加入的。字符序列值的长度限定为一。如果输入的长度超过
一，则只使用第一个字符。
范例
Example #1 range() 例子
参见
• shuffle() - 将数组打乱
• array_fill() - 用给定的值填充数组
• foreach
User Contributed Notes 26 notes
===============================================================================
To create a range array like
Array
(
[11] => 1
[12] => 2
[13] => 3
[14] => 4
)
combine two range arrays using array_combine:
array_combine(range(11,14),range(1,4))
===============================================================================
Here is a home rolled range() function that uses the step feature for those
unfortunate souls who cannot use PHP5:
===============================================================================
So, I needed a quick and dirty way to create a dropdown select for hours,
minutes and seconds using 2 digit formatting, and to create those arrays of
data, I combined range with array merge..
Super simple.
===============================================================================
foreach(range()) whilst efficiant in other languages, such as python, it is not
(compared to a for) in php*.
php is a C-inspired language and thus for is entirely in-keeping with the
lanuage aethetic to use it
That the officiant documentation doesnt mention the for loop is strange.
Note however, that in PHP5 foreach is faster than for when iterating without
incrementing a variable.
* My tests using microtime and 100 000 iterations consistently (~10 times) show
that for is 4x faster than foreach(range()).
===============================================================================
The function will generate an array of integers even if your numerical
parameters are enclosed in quotes.
int(1) [1]=> int(2) }
?>
An easy way to get an array of strings is to map strval() to the range:
string(1) "1" [1]=> string(1) "2" }
?>
===============================================================================
if you need zero padding, string prefixes or any other masks, then a simple
combination of array_map, inline functions and sprintf is your friend.
Will result:
Array
(
[0] => sample_050
[1] => sample_051
[2] => sample_052
[3] => sample_053
[4] => sample_054
[5] => sample_055
[6] => sample_056
[7] => sample_057
[8] => sample_058
[9] => sample_059
)
===============================================================================
You might expect range($n, $n-1) to be an empty array (as in e.g. Python) but
actually PHP will assume a step of -1 if start is larger than end.
===============================================================================
I needed a function, that creates a letter range with arbitrary length.
You specify via the $length parameter, how many entries you need.
Logic is analog to the logic of the column-titles in a calc-sheet.
$letter)
{
$position++;
if($position <= $length)
$range[] = ($position > 26 ? $range[$i-1] : '').$letter;
}
}
return $range;
}
?>
===============================================================================
Ever wanted to generate an array with a range of column names for use in Excel
file related parsing?
I've wrote a function that starts at the A column and adds column names up
until the column you specified.
Usage:
===============================================================================
Quick HTML menus with minimum and maximum sets of years:
** @license FREE!
*/
// Years range setup
$year_built_min = 1900;
$year_built_max = date("Y");
?>
===============================================================================
Here's how i use it to check if array is associative or not:
===============================================================================
If you're looking to fill an array to get a hash with 0-9 numerical values,
using
range(0,9);
is a faster solution compared to
array_fill(0, 10, '');
===============================================================================
So with the introduction of single-character ranges to the range() function,
the internal function tries to be "smart", and (I am inferring from behavior
here) apparently checks the type of the incoming values. If one is numeric,
including numeric string, then the other is treated as numeric; if it is a
non-numeric string, it is treated as zero.
But.
If you pass in a numeric string in such a way that is is forced to be
recognized as type string and not type numeric, range() will function quite
differently.
Compare:
?@ABCDEFGHIJKLMNOPQ
echo implode("",range("q","9 "));
// prints qponmlkjihgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;:987654
?>
I wouldn't call this a bug, because IMO it is even more useful than the stock
usage of the function.
===============================================================================
php 5.6.16
'Z',
1 => '[',
2 => '\\',
3 => ']',
4 => '^',
5 => '_',
6 => '`',
7 => 'a',
)
*/
===============================================================================
To create a simple array or a multidimensional array with defined size and null
values, use this expression:
>>$SimpleArray
array(3) {
[0]=> NULL
[1]=> NULL
[2]=> NULL
}
>>$MultiArray
array(3) {
[0]=> array(2) {
[0]=> NULL
[1]=> NULL
}
[1]=> array(2) {
[0]=> NULL
[1]=> NULL
}
[2]=> array(2) {
[0]=> NULL
[1]=> NULL
}
}
?>
===============================================================================
This is a modified version of thomas' range_string() function. It's simpler,
cleaner, and more robust, but it lacks the advanced features his function had,
hopefully it will be of assitance to someone.
Examples:
input: "1, 2, 3, 4, 5, 6" --> output: 1, 2, 3, 4, 5, 6
input: "1-6" --> output: 1, 2, 3, 4, 5, 6
input: "1-6" --> output: 1, 2, 3, 4, 5, 6
input: "1 - -6" --> output: 1, 2, 3, 4, 5, 6
input: "0 - 0" --> output: 0
input: "1, 4-6, 2" --> output: 1, 2, 4, 5, 6
input: "6,3-1" --> output: 1, 2, 3, 6
$end)
{
for($i = $start; $i >= $end; $i -= 1)
{
$range_out[] = (int) $i;
}
}
else
{
for($i = $start; $i <= $end; $i += 1)
{
$range_out[] = (int) $i;
}
}
}
}
switch ($output_type) {
case RANGE_ARRAY_SORT:
$range_out = array_unique($range_out);
sort($range_out);
case RANGE_ARRAY:
return $range_out;
break;
case RANGE_STRING_SORT:
$range_out = array_unique($range_out);
sort($range_out);
case RANGE_STRING:
default:
return implode(", ", $range_out);
break;
}
}
// Sample Usage:
$range = range_string("6, 3-1");
?>
===============================================================================
$v) {
$n = array_merge ($n, range ($v, (empty($a[2][$k])?$v:$a[2][$k])));
}
return ($n);
}
$s = '1-4 6-7 9-10';
print_r(srange($s));
?>
Return:
Array
(
[0] => 1
[1] => 2
[2] => 3
[3] => 4
[4] => 6
[5] => 7
[6] => 9
[7] => 10
)
===============================================================================
A much simpler way of creating a range of even numbers is by starting with an
even number:
===============================================================================
This should emulate range() a little better.
0)?abs($step):1;
$sign = ($low<=$high)?1:-1;
if(is_numeric($low) && is_numeric($high)) {
//numeric sequence
for ($i = (float)$low; $i*$sign <= $high*$sign; $i += $step*$sign)
$arr[] = $i;
} else {
//character sequence
if (is_numeric($low))
return $this->range($low, 0, $step);
if (is_numeric($high))
return $this->range(0, $high, $step);
$low = ord($low);
$high = ord($high);
for ($i = $low; $i*$sign <= $high*$sign; $i += $step*$sign) {
$arr[] = chr($i);
}
}
return $arr;
}
?>
===============================================================================
Interestingly, these two statements produce identical 26-character alphabet
arrays.
';
$o = "";
$time_start = microtime(true);
$a = range(1, 10000);
foreach($a as $val) {
$o .= $val;
}
$time_end = microtime(true);
$time = $time_end - $time_start;
echo 'rangeout: '.$time.' ';
?>
Which gives results:
rangein: 0.0025348663330078
rangeout: 0.0019199848175049
In some cases difference is even bigger and proportional to the range
generated. I suppose that results of range() are cached/hashed.
Note: execution order does affects execution times, but difference still exists
===============================================================================
since its not stated explicitly above, thought id point out that you arent
limited to using integers.
however, be careful when doing so, as you might not get the range you expect!
to illustrate:
print_r($am) yields the expected result:
Array
(
[0] => 500
[1] => 510
[2] => 520
...
[109] => 1590
[110] => 1600
)
print_r($fm), however, falls a bit (1%) short:
Array
(
[0] => 88.1
[1] => 88.3
[2] => 88.5
...
[97] => 107.5
[98] => 107.7
)
so, if you want to use a non-integral step size params for numeric ranges, be
sure to account for fp representation accuracy and error accumulation; a step
size of something like pi or 1/10 could spell disaster for a large range. if in
doubt, use integral steps and divide ... something like might work to recover 107.9, but would not be scalable like, say .
-emory
===============================================================================
Despite the line above that says that the $step value should be "given as a
positive number," the range() function will in fact correctly handle reversed
(decrementing) ranges. For example:
Array
(
[0] => 24
[1] => 23
[2] => 22
[3] => 21
[4] => 20
)
Array
(
[0] => 20
[1] => 17
[2] => 14
[3] => 11
)
It will actually ignore the sign of the $step argument, and determine whether
to increment or decrement based purely on whether $start > $end or $end >
$start. For example:
Array
(
[0] => 20
[1] => 17
[2] => 14
[3] => 11
)
Array
(
[0] => 11
[1] => 14
[2] => 17
[3] => 20
)
===============================================================================
a function to get column index by letter
function getColumnNumber($char){
$alphabet = range('a','z');
$alphabet2 = range('a','z');
$newAlphabet = $alphabet;
foreach($alphabet as $k => $r)
{
foreach($alphabet2 as $row){
$newAlphabet[] = $r.$row;
}
}
$key = array_search($char, $newAlphabet);
return ($key !== false) ? $key : null;
}
===============================================================================
i figured i'd add some more functionality to the myRange() functions below.
now you can, besides giving a $step parameter,
1. count backwards
2. count with letters
3. give whatever parameter you want, there's nothing (i know of) that will
cause an endless loop (try a negative $step for the previous function....)
0 ? abs($step) : 1 ); //make $step positive
$dir = ($num1<=$num2 ? 1 : -1); //get the direction
for($i = (float)$num1; $i*$dir <= $num2*$dir; $i += $step*$dir)
{
$temp[] = $i;
}
}
else
{
//we have a character range
$num1=ord((string)$num1); //convert to ascii value
$num2=ord((string)$num2);
$step = ( abs($step)>0 ? abs($step) : 1 ); //make $step positive
$dir = ($num1<=$num2 ? 1 : -1); //get direction
for($i = $num1; $i*$dir <= $num2*$dir; $i += $step*$dir)
{
$temp[] = chr($i);
}
}
return $temp;
}
print_r(myRange( 1, 3, 0.5 )); //you can use fractional steps
print_r(myRange( "a", "k", 3 )); //or count letters
print_r(myRange( "5", "9" )); //numbers are detected even if hidden in strtings
print_r(myRange( "!", "%", 1/pi() )); //or mess around with senseless
parameters
?>
===============================================================================
Here's a function to generate ranges from strings:
This outputs:
Array
(
[0] => 2
[1] => 3
[2] => 4
)


Powerschool
Once you setup the reports, you can run them to generate the csv files as often as desired.
Setup Reports
Reports
Save each of these to your computer. You may need to right-click on them. You'll need the .rpt files for the setup steps.
Directions
- Login to powerschool admin site.
- Follow the Reports link.
- Click on the Engine tab.
- Folow the Load One Local Report link.
- Press Choose File and select one of the rpt files you saved to your computer.
- Press Import.
- Press Back.
- Repeat steps 4,5,6 with each .rpt file.
Generate Reports
- Login to powerschool admin site.
- Follow the Reports link.
- Click on the Engine tab.
- Click on a report.
- Press Submit (you may have to scroll down.)
- Press Submit in the window or tab that has popped up
- You may close the new window or tab.
- Repeat steps 4,5,6 for each report
- You can now upload the csv files to SIMS (I recommend zipping them together first.)


QTL mapping in a mixed model framework with separate detection and localization stages. The first stage detects the number of QTL on each chromosome based on the genetic variation due to grouped markers on the chromosome; the second stage uses this information to determine the most likely QTL positions. The mixed model can accommodate general fixed and random effects, including spatial effects in field trials and pedigree effects. Applicable to backcrosses, doubled haploids, recombinant inbred lines, F2 intercrosses, and association mapping populations.
| Version: | 1.13 |
| Depends: | qtl, ibdreg, wgaim, nlme, mgcv |
| Suggests: | asreml |
| Published: | 2012-08-09 |
| Author: | Emma Huang and Andrew George |
| Maintainer: | Emma Huang <Emma.Huang at csiro.au> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | dlmap citation info |
| Materials: | NEWS |
| In views: | Genetics |
| CRAN checks: | dlmap results |
| Reference manual: | dlmap.pdf |
| Package source: | dlmap_1.13.tar.gz |
| Windows binaries: | r-devel: dlmap_1.13.zip, r-release: dlmap_1.13.zip, r-oldrel: dlmap_1.13.zip |
| OS X binaries: | r-release: dlmap_1.13.tgz, r-oldrel: dlmap_1.13.tgz |
| Old sources: | dlmap archive |
Please use the canonical form https://CRAN.R-project.org/package=dlmap to link to this page.


@helper.javascriptRouter("jsSuggest")(controllers.search.routes.javascript.ProductSearch.suggest)
Hot Searches
- buy scarves
- buy hats
- 3d nail art
- 50 cent headphones
- airbrush makeup kit
- 3d nail art
- 50 cent headphones
- airbrush makeup kit
@services.base.HtmlUtils.misc().addTailOnce{
}


--- layout: default permalink: /socials.html --- {% include socials-navigation.html %} {% include socials-about.html %} {% include socials-schedule.html %} {% include socials-partners.html %} {% include socials-team.html %}


Predictor
City
Select City
city_103
city_40
city_21
city_115
city_162
city_176
city_160
city_46
city_61
city_114
city_13
city_159
city_102
city_67
city_100
city_16
city_71
city_104
city_64
city_101
city_83
city_105
city_73
city_75
city_41
city_11
city_93
city_90
city_36
city_20
city_57
city_152
city_19
city_65
city_74
city_173
city_136
city_98
city_97
city_50
city_138
city_82
city_157
city_89
city_150
city_70
city_175
city_94
city_28
city_59
city_165
city_145
city_142
city_26
city_12
city_37
city_43
city_116
city_23
city_99
city_149
city_10
city_45
city_80
city_128
city_158
city_123
city_7
city_72
city_106
city_143
city_78
city_109
city_24
city_134
city_48
city_144
city_91
city_146
city_133
city_126
city_118
city_9
city_167
city_27
city_84
city_54
city_39
city_79
city_76
city_77
city_81
city_131
city_44
city_117
city_155
city_33
city_141
city_127
city_62
city_53
city_25
city_2
city_69
city_120
city_111
city_30
city_1
city_140
city_179
city_55
city_14
city_42
city_107
city_18
city_139
city_180
city_166
city_121
city_129
city_8
city_31
city_171
City Development Index
Gender
Select Gender
Male
Female
Other
Relevant Experience
Select Experience
Has relevant experience
No relevant experience
Enrolled University
Select enrollment
no_enrollment
Full time course
Part time course
Education level
Select education level
Graduate
Masters
High School
Phd
Primary School
Major Discipline
Select major discipline
STEM
Business Degree
Arts
Humanities
No Major
Other
Experience
Select Experience
more than 20
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
less than 1
Company Size
Select Company Size
less than 10
10-49
50-99
100-499
500-999
1000-4999
5000-9999
more than 10000
company_type
Select Company type
Do not know
Pvt Ltd
Funded Startup
Early Stage Startup
Public Sector
NGO
Other
Last new job
Select job year difference
more than 4
4
3
2
1
0
Training hours
Predict
{{ prediction }}


Carolina Quiel
Menu
About
Portfolio
Contact
Portfolio
Coraline's Guessing Game
Crystals Collector
Trivia Game
GifTastic The Simpsons
RPS Multiplayer
MusicUp


--- layout: page status: publish published: true title: Health Small Statistical Areas author: display_name: Jessie Pechmann login: jpechmann email<EMAIL_ADDRESS>url: '' author_login: jpechmann author_email<EMAIL_ADDRESS>wordpress_id: 3672 wordpress_url: http://gis.utah.gov/?page_id=3672 date: '2011-11-21 17:25:17 -0700' date_gmt: '2011-11-22 00:25:17 -0700' categories: [] tags: - sgid - Data - utah - gis - map - mapping - dataset - download - agrc - layer - shapefile - geodatabase - metadata - shp - gdb - kml - lyr - digital - geographic - information - database - state - statewide ---
Data Type: GIS Data Layer
Steward(s): AGRC and Utah Department of Health
Abstract:
Small health statistical areas provide a means of geographically analyzing and presenting health statistics at the community level. Producing information at this level provides community planners and others with information that is specific to the populations living in their communities. Small area analysis allows an investigator to explore ecologic relationships between health status, lifestyle, the environment and the health system.
Data Content:
The following data is available for download:
The Area_Code field contains the statistical area code.
The Area_Name field contains the statistical area name.
For questions, contact AGRC.Other Links:
Download 2008 Small Health Statistical areas here.
The Area_Code field contains the statistical area code.
The Area_Name field contains the statistical area name.
For questions, contact AGRC.Other Links:
Download 2008 Small Health Statistical areas here.


Generate a Password
Select your options and click the 'Generate Password' button. Then your password will appear above.
Password Length:
Use Lowercase Characters
Use Uppercase Characters
Use Numbers
Use special characters
Generate Password
Copy to Clipboard


| void WorkerMenu.Awake |
( |
| ) |
|
| void WorkerMenu.OnCreatedRoom |
( |
| ) |
|
| void WorkerMenu.OnDisconnectedFromPhoton |
( |
| ) |
|
| void WorkerMenu.OnFailedToConnectToPhoton |
( |
object |
parameters | ) |
|
| void WorkerMenu.OnGUI |
( |
| ) |
|
| void WorkerMenu.OnJoinedRoom |
( |
| ) |
|
| void WorkerMenu.OnPhotonCreateRoomFailed |
( |
| ) |
|
| void WorkerMenu.OnPhotonJoinRoomFailed |
( |
| ) |
|
| void WorkerMenu.OnPhotonRandomJoinFailed |
( |
| ) |
|
| readonly string WorkerMenu.SceneNameGame = "DemoWorkerGame-Scene" |
|
static |
| readonly string WorkerMenu.SceneNameMenu = "DemoWorker-Scene" |
|
static |
| Vector2 WorkerMenu.WidthAndHeight = new Vector2(600,400) |
| string WorkerMenu.ErrorDialog |
|
get |
The documentation for this class was generated from the following file:
- D:/work/LittleHeroes_Game/Assets/Photon Unity Networking/Demos/DemoWorker/Scripts/WorkerMenu.cs


CompletableFuture
and its quirks
Principal Engineer @ Mi|iM
Async
...but how to get the result back?
Future
Spawn point for results of async operations
Future<Integer> result = someAsyncMethod();
Integer integer = result.get();
Future
Spawn point for results of async operations
Future<Integer> result = someAsyncMethod();
// ...
Integer integer = result.get();
Any method can become async
Future<Integer> result = executor.submit(() -> someSyncMethod());
Integer integer = result.get();
Java Future Implementations:
- java.util.concurrent.Future (JDK 1.5)
- java.util.concurrent.CompletableFuture (JDK 1.8)
Future's Limitations
- Blocking API
- Limited exception handling
- A Future can't be manually completed
- Multiple Futures can't be combined
Future<Integer> result = executor.submit(() -> ...);
try {
Integer integer = result.get(); // blocks
} catch (InterruptedException e) {
// handle
} catch (ExecutionException e) {
// handle
}
Before JDK 8: ListenableFuture
ListenableFuture<Result> future = service.query(name);
future.addListener(new Runnable() {
public void run() {
// ...
}
}, executor);
JDK 8: CompletableFuture
CompletableFuture<Integer> cf = new CompletableFuture<>();
cf.complete(1);
CompletableFuture<Integer> cf1 = ...
CompletableFuture<Integer> cf2 = ...
CompletableFuture<Void> processed = cf1
.thenApply(i -> i + 1)
.thenCombine(cf2, Integer::sum)
.thenRun(() -> { /*...*/});
Cancelling a CompletableFuture
cf.cancel();
CompletableFuture<Void> processed = cf1
.thenApply(i -> i + 1)
.thenCombine(cf2, Integer::sum)
.thenRun(() -> { /*...*/}); // what if I cancel this one?
CompletableFuture<Integer> cf = new CompletableFuture<>();
// ...
cf.cancel();
Cancels a CompletableFuture and not tasks completing it
// @param mayInterruptIfRunning this value has no effect in this
// implementation because interrupts are not used to control
// processing.
Technically, you could hack it...
static final class InterruptibleCompletableFuture<T> extends CompletableFuture<T> {
private volatile FutureTask<?> backingTask;
private void completedBy(FutureTask<Void> task) {
backingTask = task;
}
@Override
public boolean cancel(boolean mayInterruptIfRunning) {
if (backingTask != null) {
backingTask.cancel(mayInterruptIfRunning);
}
return super.cancel(mayInterruptIfRunning);
}
}
Combining Multiple Futures...
CompletableFuture#allOf/anyOf
CompletableFuture<Integer> cf1 = new CompletableFuture<>();
CompletableFuture<Integer> cf2 = new CompletableFuture<>();
CompletableFuture.allOf(cf1, cf2);
CompletableFuture.anyOf(cf1, cf2);
CompletableFuture#allOf
public static CompletableFuture<Void> allOf(
CompletableFuture<?>... cfs) {
return andTree(cfs, 0, cfs.length - 1);
}
- Accepts CompletableFuture<?>... cfs
- Returns CompletableFuture<Void>
- Doesn't shortcircuit on exception
Can you spot the issue?
CompletableFuture#anyOf
public static CompletableFuture<Object> anyOf(
CompletableFuture<?>... cfs) {
return // ...
}
- Accepts CompletableFuture<?>... cfs
- Returns CompletableFuture<Object>
- Doesn't wait for the first successful completion
CompletableFuture vs Threads
Straightforward with JDK 1.5's Future
ExecutorService executor = Executors.newFixedThreadPool(4);
Future<?> future = executor.submit(() -> { /* ... */ });
With CompletableFuture
CompletableFuture<Void> future = CompletableFuture
.runAsync(() -> { /* ... */ }) // 1
.thenRun(() -> { /* ... */ }) // 2
.thenRun(() -> { /* ... */ });
- What thread pool does #1 run on?
- What thread does #2 run on?
Following CompletableFuture#runAsync
ThreadPerTaskExecutor
- ForkJoinPool.commonPool() is not much better either
ForkJoinPool.commonPool()
- Just a single instance
- Good for non-blocking operations
- Used by Stream API
- Used by Arrays.parallel*
- Used by Project Loom
list.stream()
.collect(parallel(i -> foo(i), toList(), executor, parallelism))
.orTimeout(1000, MILLISECONDS)
.thenAcceptAsync(System.out::println, otherExecutor)
.thenRun(() -> System.out.println("Finished!"));
Always provide an Executor instance
CompletableFuture<Void> future = CompletableFuture
.runAsync(() -> { /* ... */ }, executor) // 1
.thenRun(() -> { /* ... */ }) // 2
.thenRun(() -> { /* ... */ });
- What thread does #2 run on?
- Either the same thread as #1 or the calling thread
- Not an issue for simple non-blocking processing
Solution: then***Async
CompletableFuture<Void> future = CompletableFuture
.runAsync(() -> { /* ... */ }, executor)
.thenRunAsync(() -> { /* ... */ }, executor)
.thenRunAsync(() -> { /* ... */ }, executor);
CompletableFuture#applyToEither vs Exceptions
CompletableFuture#applyToEither
CompletableFuture<Integer> cf1 = ...
CompletableFuture<Integer> cf2 = ...
CompletableFuture<Integer> either = cf1.applyToEither(cf2, i -> i);
CompletableFuture#applyToEither
CompletableFuture<Integer> cf1 = completedFuture(42);
CompletableFuture<Integer> cf2 = failedFuture(new NullPointerException());
CompletableFuture<Integer> either = cf1.applyToEither(cf2, i -> i);
CompletableFuture#applyToEither
CompletableFuture<Integer> cf1 = failedFuture(new NullPointerException());
CompletableFuture<Integer> cf2 = completedFuture(42)
CompletableFuture<Integer> either = cf1.applyToEither(cf2, i -> i);
Thank You!


You are looking at a completely new version of Sing App built with brand new Angular 4.0 Final Release!
Made by Flatlogic.
1 656 843
Status: Live
146 Countries, 2759 Cities
Some Cool Text
P. to C. Conversion
Average Bitrate
Tracking: Active
391 elements installed, 84 sets
76.38%
10.38%
3.38%
17% higher than last month
17 567 318
55 120
9 695
8% lower than last month
104.85%
14.29°
7,211M
8 734 higher than last month
Hey! What's up? So many times since we
Good news coming tonight. Seems they agreed to proceed
Check my latest email plz!
What about summer break?
Target $820 day earnings is 96% reached.


An implementation guide may contain one or more categories. These categories, once defined, may be associated with constraints within templates of the implementation guide. Categories may be used to generate different exports, exporting the constraints associated with the selected category.
Create a Category
- Go to the Edit Implementation Guide screen for the implementation guide you want to modify categories for
- Select the Categories tab
- Specify the name of the category in the "NEW CATEGORY" text field
- It is suggested that you choose a short name for the category (example: "CAT1")
- Select the Add button
- Save the implementation guide
Delete a Category
- Go to the Edit Implementation Guide screen for the implementation guide you want to modify categories for
- Select the Categories tab
- Select the Remove button next to the category you want to remove
- Save the implementation guide
Associate the Category to Constraints
See the Template/Profile > Editor > Constraints > Categories section.


A trivial example program.
A trivial example program.
#include <string>
#include <iostream>
#include "caf/actor_ostream.hpp"
#include "caf/actor_system.hpp"
#include "caf/caf_main.hpp"
#include "caf/event_based_actor.hpp"
return {
[=](const std::string& what) -> std::string {
aout(self) << what << std::endl;
return std::string{what.rbegin(), what.rend()};
},
};
}
self->request(buddy, std::chrono::seconds(10), "Hello World!")
.then(
[=](const std::string& what) {
aout(self) << what << std::endl;
});
}
auto mirror_actor = sys.
spawn(mirror);
sys.
spawn(hello_world, mirror_actor);
}
CAF_MAIN()
Actor environment including scheduler, registry, and optional components such as a middleman.
Definition: actor_system.hpp:90
infer_handle_from_class_t< C > spawn(Ts &&... xs)
Returns a new actor of type C using xs... as constructor arguments.
Definition: actor_system.hpp:364
Identifies an untyped actor.
Definition: actor.hpp:29
Describes the behavior of an actor, i.e., provides a message handler and an optional timeout.
Definition: behavior.hpp:25
A cooperatively scheduled, event-based actor implementation.
Definition: event_based_actor.hpp:40
Root namespace of libcaf.
Definition: abstract_actor.hpp:29


"I hired Kevin to help my 9th grade son with his common core math. He is very knowledgeable does a great job of explaining. My son enjoyed working with an older teenager who understood the challenges of high school math. Kevin is very bright and would be a great tutor for elementary school to high school students. He recently worked at a tutoring center where he worked with all levels of math students"
-Meredith G
K-8 Math Tutor, entry level position at local math tutoring center “Mathnasium”
K-12 Math Tutor, promotion from earlier title. First high school student in the history of the franchise to be promoted to full instructor.
Started a successful private tutoring business, JayTutoring.


RT @confreaks: New Video! @mwrc - Code Smells: Your Refactoring Cheat Codes by @jpignata http://www.confreaks.com/videos/2336-mwrc2013-code-smells-your-refactoring-cheat-codes
4/27/2013, 3:46:10 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
RT @confreaks: New Video! @mwrc - Code Smells: Your Refactoring Cheat Codes by @jpignata http://www.confreaks.com/videos/2336-mwrc2013-code-smells-your-refactoring-cheat-codes
4/27/2013, 3:46:10 PM
Favs: 0
Retweets: 0
link


| 3567 | SIGCD429 | The shepherd on the rock |<PHONE_NUMBER>22 | SIGCD429 |
| 3568 | SIGCD430 | Brahms/Bruckner: Motets |<PHONE_NUMBER>28 | SIGCD430 |
| 3569 | SIGCD431 | Bruckner: Symphony No. 9 |<PHONE_NUMBER>27 | SIGCD431 |
| 3570 | SIGCD432 | Szymanowski/Hahn: Violin Sonatas |<PHONE_NUMBER>26 | SIGCD432 |
| 3571 | SIGCD433 | Mozart: Il re pastore |<PHONE_NUMBER>25 | SIGCD433 |
| 3572 | SIGCD434 | Haydn: Symphonies Nos. 52, 53 & 59 |<PHONE_NUMBER>24 | SIGCD434 |
| 3573 | SIGCD435 | Bach/Handel/Mozart: Aksel! – Arias by Bach, Handel & Mozart |<PHONE_NUMBER>23 | SIGCD435 |
| 3574 | SIGCD436 | Invisible Stars – Choral works of Ireland & Scotland |<PHONE_NUMBER>22 | SIGCD436 |
| 3575 | SIGCD437 | Davis/Vivaldi: Seaons |<PHONE_NUMBER>21 | SIGCD437 |
| 3576 | SIGCD438 | Widor: Solo organ works |<PHONE_NUMBER>20 | SIGCD438 |
| 3577 | SIGCD439 | Lullabies for Mila |<PHONE_NUMBER>29 | SIGCD439 |
| 3578 | SIGCD440 | Only a Singing Bird |<PHONE_NUMBER>25 | SIGCD440 |
| 3579 | SIGCD441 | Tchaikovsky: Piano Concerto No. 1 & Nutcracker Suite |<PHONE_NUMBER>24 | SIGCD441 |
| 3580 | SIGCD442 | Tavener: Missa Wellensis & other sacred choral music |<PHONE_NUMBER>23 | SIGCD442 |
| 3581 | SIGCD443 | Songs to the moon |<PHONE_NUMBER>22 | SIGCD443 |
| 3582 | SIGCD444 | Palomo/Rodrigo: Nocturnos de Andalucía |<PHONE_NUMBER>21 | SIGCD444 |
| 3583 | SIGCD445 | Time and its Passing |<PHONE_NUMBER>20 | SIGCD445 |
| 3584 | SIGCD446 | The Evening Hour |<PHONE_NUMBER>29 | SIGCD446 |
| 3585 | SIGCD447 | Greensleeves |<PHONE_NUMBER>28 | SIGCD447 |
| 3586 | SIGCD448 | Brahms/Bruce: Clarinet Quintet & Gumboots |<PHONE_NUMBER>27 | SIGCD448 |
| 3587 | SIGCD449 | Winchester Cathedral 50th Anniversary EP |<PHONE_NUMBER>26 | SIGCD449 |
| 3588 | SIGCD450 | Palestrina: How fair thou art |<PHONE_NUMBER>22 | SIGCD450 |
| 3589 | SIGCD451 | Hughes B: I am the song & other choral works |<PHONE_NUMBER>21 | SIGCD451 |
| 3590 | SIGCD452 | Dove: For an unknown soldier & An airmail letter |<PHONE_NUMBER>20 | SIGCD452 |
| 3591 | SIGCD453 | Gough: The world encompassed |<PHONE_NUMBER>29 | SIGCD453 |
| 3592 | SIGCD454 | L'Estrange: On eagles' wings & other choral works |<PHONE_NUMBER>28 | SIGCD454 |
| 3593 | SIGCD455 | Poulenc: Works for Piano Solo and Duo |<PHONE_NUMBER>27 | SIGCD455 |
| 3594 | SIGCD456 | Harvey: Choral music |<PHONE_NUMBER>26 | SIGCD456 |
| 3595 | SIGCD457 | Where'er you walk - Handel's favourite tenor |<PHONE_NUMBER>25 | SIGCD457 |
| 3596 | SIGCD458 | Christmas with St John's |<PHONE_NUMBER>24 | SIGCD458 |
| 3597 | SIGCD459 | The King's Singers Christmas Songbook |<PHONE_NUMBER>23 | SIGCD459 |
| 3598 | SIGCD460 | Adeste fideles |<PHONE_NUMBER>29 | SIGCD460 |
| 3599 | SIGCD461 | Schubert: Symphony No. 9 |<PHONE_NUMBER>28 | SIGCD461 |
| 3600 | SIGCD462 | Handel: Handel in Italy, Vol. 2 |<PHONE_NUMBER>27 | SIGCD462 |
| 3601 | SIGCD463 | Hakim: Hakim plays Hakim |<PHONE_NUMBER>26 | SIGCD463 |
| 3602 | SIGCD464 | Queen Mary's Big Belly – Prayers for an heir in Catholic England |<PHONE_NUMBER>25 | SIGCD464 |
| 3603 | SIGCD465 | Anthem – Great British Hymns & Choral Works |<PHONE_NUMBER>24 | SIGCD465 |
| 3604 | SIGCD466 | Bartók: The Miraculous Mandarin & other works |<PHONE_NUMBER>23 | SIGCD466 |
| 3605 | SIGCD467 | Mozart/Nielsen: Flute Concertos |<PHONE_NUMBER>22 | SIGCD467 |
| 3606 | SIGCD468 | Adams/Harris: Violin Concertos |<PHONE_NUMBER>21 | SIGCD468 |
| 3607 | SIGCD469 | Davis: Dance |<PHONE_NUMBER>20 | SIGCD469 |
| 3608 | SIGCD470 | Duruflé/Vierne/Briggs: Midnight at St Etienne du Mont |<PHONE_NUMBER>26 | SIGCD470 |
| 3609 | SIGCD471 | Park/Talbot: Footsteps & Path of Miracles |<PHONE_NUMBER>25 | SIGCD471 |
| 3610 | SIGCD472 | Fauré: Songs, Vol. 2 |<PHONE_NUMBER>24 | SIGCD472 |
| 3611 | SIGCD473 | Mozart: Zaide |<PHONE_NUMBER>23 | SIGCD473 |
| 3612 | SIGCD474 | Virgin and Child – Music from the Baldwin Partbooks II |<PHONE_NUMBER>22 | SIGCD474 |
| 3613 | SIGCD475 | A New Heaven |<PHONE_NUMBER>21 | SIGCD475 |
| 3614 | SIGCD476 | Reger: Fantasias & Fugues |<PHONE_NUMBER>20 | SIGCD476 |
| 3615 | SIGCD477 | Nielsen: Flute & Clarinet Concertos |<PHONE_NUMBER>29 | SIGCD477 |
| 3616 | SIGCD478 | Handel: Handel in Ireland, Vol. 1 |<PHONE_NUMBER>28 | SIGCD478 |
| 3617 | SIGCD479 | Handel: Handel at Vauxhall, Vol. 2 |<PHONE_NUMBER>27 | SIGCD479 |
| 3618 | SIGCD480 | Haydn: The Seasons |<PHONE_NUMBER>23 | SIGCD480 |
| 3619 | SIGCD481 | Byrd/Britten: Choral works |<PHONE_NUMBER>22 | SIGCD481 |
| 3620 | SIGCD482 | Chopin: Preludes |<PHONE_NUMBER>21 | SIGCD482 |
| 3621 | SIGCD483 | Fauré: The Complete Songs, Vol. 3 |<PHONE_NUMBER>20 | SIGCD483 |
| 3622 | SIGCD484 | Rachmaninov: Symphony No. 1 |<PHONE_NUMBER>29 | SIGCD484 |
| 3623 | SIGCD485 | Perfido! – Opera arias |<PHONE_NUMBER>28 | SIGCD485 |
| 3624 | SIGCD486 | Grieg/Vaughan Williams: Subito - Violin Sonata & The lark ascending |<PHONE_NUMBER>27 | SIGCD486 |
| 3625 | SIGCD487 | Dove: In Damascus & other works |<PHONE_NUMBER>26 | SIGCD487 |
| 3626 | SIGCD488 | Bach: The complete solo soprano cantatas, Vol. 1 |<PHONE_NUMBER>25 | SIGCD488 |
| 3627 | SIGCD489 | Poulenc/Kodály/Janácek: Kyrie |<PHONE_NUMBER>24 | SIGCD489 |
| 3628 | SIGCD490 | Silence & Music |<PHONE_NUMBER>20 | SIGCD490 |
| 3629 | SIGCD492 | Bernstein/Stravinsky/Schoenberg: Symphonic Psalms & Prayers |<PHONE_NUMBER>28 | SIGCD492 |
| 3630 | SIGCD493 | Shostakovich: Piano Concertos & Sonatas |<PHONE_NUMBER>27 | SIGCD493 |
| 3631 | SIGCD494 | Fire On All Sides |<PHONE_NUMBER>26 | SIGCD494 |
| 3632 | SIGCD495 | Mccarthy/Todd: Codebreaker & Ode to a Nightingale |<PHONE_NUMBER>25 | SIGCD495 |
| 3633 | SIGCD496 | Waley-Cohen: Permutations |<PHONE_NUMBER>24 | SIGCD496 |
| 3634 | SIGCD497 | The King's Singers Christmas Presence |<PHONE_NUMBER>23 | SIGCD497 |
| 3635 | SIGCD498 | Hakim: Phèdre, Caprice, Diptyque & Concerto |<PHONE_NUMBER>22 | SIGCD498 |
| 3636 | SIGCD499 | Mozart: Il sogno di Scipione |<PHONE_NUMBER>21 | SIGCD499 |
| 3637 | SIGCD500 | The King's Singers Gold |<PHONE_NUMBER>26 | SIGCD500 |
| 3638 | SIGCD501 | Tavener: Mother and Child |<PHONE_NUMBER>25 | SIGCD501 |
| 3639 | SIGCD502 | Christmas with The King's Singers |<PHONE_NUMBER>24 | SIGCD502 |
| 3640 | SIGCD506 | Nyman: Music for two pianos |<PHONE_NUMBER>20 | SIGCD506 |
| 3641 | SIGCD509 | Voyages |<PHONE_NUMBER>27 | SIGCD509 |
| 3642 | SIGCD510 | Dvorák/Janácek/Suk: Bohemia - Violin Sonatas |<PHONE_NUMBER>23 | SIGCD510 |
| 3643 | SIGCD511 | Gibbons: In chains of gold |<PHONE_NUMBER>22 | SIGCD511 |
| 3644 | SIGCD512 | Chilcott: In winter's arms |<PHONE_NUMBER>21 | SIGCD512 |
| 3645 | SIGCD513 | The Art of Dancing – Concertos for trumpet, piano & strings |<PHONE_NUMBER>20 | SIGCD513 |
| 3646 | SIGCD514 | Great Cathedral Anthems |<PHONE_NUMBER>29 | SIGCD514 |
| 3647 | SIGCD515 | Dvorák/Sibelius: Symphony No. 9 & Finlandia |<PHONE_NUMBER>28 | SIGCD515 |
| 3648 | SIGCD516 | Wilkinson: The sunlight on the garden & other songs |<PHONE_NUMBER>27 | SIGCD516 |
| 3649 | SIGCD517 | Williams R: Sacred choral works |<PHONE_NUMBER>26 | SIGCD517 |
| 3650 | SIGCD518 | Fitkin: String Quartets |<PHONE_NUMBER>25 | SIGCD518 |
| 3651 | SIGCD519 | Tavener/Panufnik: 99 Words & other choral works |<PHONE_NUMBER>24 | SIGCD519 |
| 3652 | SIGCD522 | Davis: Liberty |<PHONE_NUMBER>28 | SIGCD522 |
| 3653 | SIGCD524 | Kernis: Dreamsongs & other concertos |<PHONE_NUMBER>26 | SIGCD524 |
| 3654 | SIGCD525 | Beethoven: Piano Concerto No. 5 & works for solo piano May 2018 release |<PHONE_NUMBER>25 | SIGCD525 |
| 3655 | SIGCD526 | Light Divine March 2018 release |<PHONE_NUMBER>24 | SIGCD526 |
| 3656 | SIGCD527 | Beethoven: Beethoven Unbound March 2018 release |<PHONE_NUMBER>23 | SIGCD527 |
| 3657 | SIGCD528 | Jenkins: Complete Four-Part Consort Music March 2018 release |<PHONE_NUMBER>22 | SIGCD528 |
| 3658 | SIGCD529 | Wright L: Duets April 2018 release |<PHONE_NUMBER>21 | SIGCD529 |
| 3659 | SIGCD530 | Rachmaninov: Symphony No. 2 April 2018 release |<PHONE_NUMBER>27 | SIGCD530 |
| 3660 | SIGCD531 | Schubert: Winter Journey April 2018 release |<PHONE_NUMBER>26 | SIGCD531 |
| 3661 | SIGCD532 | White Light - the space between April 2018 release |<PHONE_NUMBER>25 | SIGCD532 |
| 3662 | SIGCD533 | Liszt: Piano music April 2018 release |<PHONE_NUMBER>24 | SIGCD533 |
| 3663 | SIGCD534 | Mozart in London May 2018 release |<PHONE_NUMBER>23 | SIGCD534 |
| 3664 | SIGCD536 | A Rose Magnificat May 2018 release |<PHONE_NUMBER>21 | SIGCD536 |
| 3665 | SIGCD541 | Vaughan Williams: Mass in G minor & other choral works May 2018 release |<PHONE_NUMBER>23 | SIGCD541 |
| 3666 | SIGCD542 | Tchaikovsky/Duchen: The Nutcracker and I, by Alexandra Dariescu April 2018 release |<PHONE_NUMBER>22 | SIGCD542 |
| 3667 | SIGCD800 | Bach: The Complete Organ Works, Vol. 1 |<PHONE_NUMBER>23 | SIGCD800 |
| 3668 | SIGCD802 | Bach: The Complete Organ Works, Vol. 2 |<PHONE_NUMBER>21 | SIGCD802 |
| 3669 | SIGCD803 | Bach: The Complete Organ Works, Vol. 3 |<PHONE_NUMBER>20 | SIGCD803 |
| 3670 | SIGCD804 | Bach: The Complete Organ Works, Vol. 4 |<PHONE_NUMBER>29 | SIGCD804 |
| 3671 | SIGCD805 | Bach: The Complete Organ Works, Vol. 5 |<PHONE_NUMBER>28 | SIGCD805 |
| 3672 | SIGCD806 | Bach: The Complete Organ Works, Vol. 6 |<PHONE_NUMBER>27 | SIGCD806 |
| 3673 | SIGCD807 | Bach: The Complete Organ Works, Vol. 7 April 2018 release |<PHONE_NUMBER>26 | SIGCD807 |
| 3674 | SIGCD821 | Hewitt Jones: Christmas Party |<PHONE_NUMBER>26 | SIGCD821 |
| 3675 | SIGCD824 | Schubert/Chopin: Cello Sonatas |<PHONE_NUMBER>23 | SIGCD824 |
| 3676 | SIGCD900 | Russian Treasures |<PHONE_NUMBER>22 | SIGCD900 |
| 3677 | SIGCD901 | Plainchant & Tallis Lamentations |<PHONE_NUMBER>21 | SIGCD901 |
| 3678 | SIGCD902 | A Very English Christmas |<PHONE_NUMBER>20 | SIGCD902 |
| 3679 | SIGCD903 | Chilcott: Sun, Moon, Sea & Stars |<PHONE_NUMBER>29 | SIGCD903 |
| 3680 | SIGCD904 | Partsongs |<PHONE_NUMBER>28 | SIGCD904 |
| 3681 | SPCC2000 | The Music of St Paul's Cathedral |<PHONE_NUMBER>03 | SPCC2000 |
| 3682 | WCC100 | The Music of Westminster Cathedral |<PHONE_NUMBER>10 | WCC100 |


East Is East (1999) 3 stars out of 4. Starring Om Puri, Linda Bassett, Ian Aspinall, Jimi Mistry, Raji James, Emil Marwa, Chris Basson, Archie Panjabi and Jordan Routledge. Directed by Damien O'Donnell. Written by Ayub Khan Din. Music by Deborah Mollison. Rated R.
With a title borrowed from a line in a Rudyard Kipling poem, you are aware beforehand that "East Is East" is going to be a story about a clash of cultures.
And so it is. This 1999 British release is a mixture of comedy and drama, set in the 1970s. The story revolves around the mixed-race Khan family.
As the story opens, George Khan's eldest son, Nazir, has disgraced by father by fleeing from his arranged marriage.
Undeterred, George continues to plow ahead and try to control the lives of his six remaining children.
George, who came to England from Pakistan and married an English woman, tries to run his family as if he were back in the old country. But that type of patriarchal domination doesn't work in swingin' England, and his children continually rebel as their lifestyle of discos and bellbottoms clash with their father's idea of studying the Koran and wearing traditional Pakistani garb.
"East is East" is an interesting movie. As portrayed by Om Puri, George Khan is a character with whom you can empathize and scorn simultaneously.
 But he also is a lovable figure, only wanting the best for his offspring.
He cannot understand them wanting to make life decisions on their own. His attempts to turn his home and family into a little piece of Pakistan are continually thwarted by his free-spirited offspring.
"East Is East," despite its cultural baggage, actually is very universal in theme. Parents, especially those with teen-agers, will be able to identify with George, while young viewers will certainly see parts of themselves in the Khan clan, while recognizing traits of their parents in George.
For those filmgoers who say they want more diversity in their movie selections, "East Is East" fits the bill. At about 96 minutes, it is charming in its own rugged way, a film you can appreciate as well as enjoy.
Bob Bloom is the film critic at the Journal and Courier in Lafayette, IN. He can be reached by e-mail at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>Bloo'm's reviews are posted on the Internet Movie Database at: http://www.imdb.com/M/reviews_by?Bob+Bloom
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


|
GPGPU-Sim
|
#include <XML_Parse.h>
Public Attributes | |
| double | dcache_config [20] |
| int | buffer_sizes [20] |
| int | cache_policy |
| double | total_accesses |
| double | read_accesses |
| double | write_accesses |
| double | total_hits |
| double | total_misses |
| double | read_hits |
| double | write_hits |
| double | read_misses |
| double | write_misses |
| double | replacements |
| double | write_backs |
| double | miss_buffer_access |
| double | fill_buffer_accesses |
| double | prefetch_buffer_accesses |
| double | prefetch_buffer_writes |
| double | prefetch_buffer_reads |
| double | prefetch_buffer_hits |
| double | wbb_writes |
| double | wbb_reads |
| double | conflicts |
Definition at line 161 of file XML_Parse.h.
| int dcache_systemcore::buffer_sizes[20] |
Definition at line 164 of file XML_Parse.h.
| int dcache_systemcore::cache_policy |
Definition at line 165 of file XML_Parse.h.
| double dcache_systemcore::conflicts |
Definition at line 186 of file XML_Parse.h.
| double dcache_systemcore::dcache_config[20] |
Definition at line 163 of file XML_Parse.h.
| double dcache_systemcore::fill_buffer_accesses |
Definition at line 179 of file XML_Parse.h.
| double dcache_systemcore::miss_buffer_access |
Definition at line 178 of file XML_Parse.h.
| double dcache_systemcore::prefetch_buffer_accesses |
Definition at line 180 of file XML_Parse.h.
| double dcache_systemcore::prefetch_buffer_hits |
Definition at line 183 of file XML_Parse.h.
| double dcache_systemcore::prefetch_buffer_reads |
Definition at line 182 of file XML_Parse.h.
| double dcache_systemcore::prefetch_buffer_writes |
Definition at line 181 of file XML_Parse.h.
| double dcache_systemcore::read_accesses |
Definition at line 168 of file XML_Parse.h.
| double dcache_systemcore::read_hits |
Definition at line 172 of file XML_Parse.h.
| double dcache_systemcore::read_misses |
Definition at line 174 of file XML_Parse.h.
| double dcache_systemcore::replacements |
Definition at line 176 of file XML_Parse.h.
| double dcache_systemcore::total_accesses |
Definition at line 167 of file XML_Parse.h.
| double dcache_systemcore::total_hits |
Definition at line 170 of file XML_Parse.h.
| double dcache_systemcore::total_misses |
Definition at line 171 of file XML_Parse.h.
| double dcache_systemcore::wbb_reads |
Definition at line 185 of file XML_Parse.h.
| double dcache_systemcore::wbb_writes |
Definition at line 184 of file XML_Parse.h.
| double dcache_systemcore::write_accesses |
Definition at line 169 of file XML_Parse.h.
| double dcache_systemcore::write_backs |
Definition at line 177 of file XML_Parse.h.
| double dcache_systemcore::write_hits |
Definition at line 173 of file XML_Parse.h.
| double dcache_systemcore::write_misses |
Definition at line 175 of file XML_Parse.h.


|
Bug-reproducer Assistant Python kernel
1.0
Código Python de kernel del Bug-reproducer Assistant
|
Public Member Functions | |
| def | loadProjectsList |
| def | saveProjectsList |
Static Public Attributes | |
| string | NAME = 'name' |
| string | LOCATION = 'location' |
| string | LANGUAGE = 'language' |
| string | SOLUTION_FILE = 'solutionFile' |
| string | MAIN_FILE = 'mainFile' |
| string | MAIN_FUNCTION = 'mainFunction' |
| string | EXE_COMMAND = 'exeCommand' |
| string | TREE_FILES = 'treeFiles' |
| string | COMPILING_COMMAND = 'compilingCommand' |
| string | CPP_PROJECT = 'cppProject' |
| string | FILE_TO_ANNOTATE = 'fileToAnnotate' |
| string | HEADER_TO_INCLUDE = 'headerToInclude' |
| string | PROJECT_SETTINGS_FILE_NAME = 'projectSettings.json' |
| string | INDEX_FILE_NAME = 'projects.json' |
| int | INDENT = 4 |
It loads/stores all the projects in disk, for persistence between runnings.
| def gui::project::ProjectSerializer::loadProjectsList | ( | ) |
Load the projects from disk into memory.
| projectMap | A project represented as a map, to ease Json-serialization. |
| def gui::project::ProjectSerializer::saveProjectsList | ( | allProjects | ) |
| allProjects | All the projects to store. Store all the projects from memory into disk. |


Financial woes will be a thing of the past, says new MUSA president
MELAKA, Nov 2 — The issue of players’ salary arrears will not happen again, said newly appointed Melaka United Soccer Association (MUSA) president Damian Yeo Shen Li.
Yeo has pledged to improve the financial position of the association so that the state teams can be put on a stronger footing.
Chief coach Zainal Abidin Hassan had been asked to prepare a proposal paper on the expenditure for Melaka United’s campaign in the Malaysian League next season, he told a press conference here today.
He said this approach would apply to all state teams to ensure they spend within their means to avoid running into financial problems.
“There are companies and organisations willing to contribute to the development of the state football but surely they want their funds to be managed in a proper and transparent manner,” he added.
“So, we will ensure that the issue of debts and salary arrears will not crop up again as it can affect the team performance and morale of players,” he added.
Yeo believed that all debts and salaries owed to Melaka United players could be settled by November 30.
On the licencing of the club to enable it to compete in the 2020 Super League, he said the association had fulfilled the requirements set by the Football Association of Malaysia (FAM) and a decision is expected on Monday.
He will also reach out to football fans in an effort to strengthen the management and administration of the association and team.
“I will appoint a representative from among them to join the MUSA Exco and share their views on development plans,” he said.
Yeo thanked Melaka Yang di-Pertua Negeri Tun Mohd Khalil Yaakob and Chief Minister Adly Zahari, who is MUSA patron, for placing their trust in him to lead the association. — Bernama


{% extends "general_base.html" %} {% block title %} Dashboard {% endblock %} {% block styles %} {{super()}} {% endblock %} {% block content %}
We are sorry for unable to provide the option of uploading icon right now.
Because this web is running on a free web server, with limited storage space.
List of different category
Note: It might take about 10 seconds to load up the page


I am a Responsive Developer who thrives on visual storytelling and the best user experience. When I'm not working, I can be found in my shop or on an adventure with my family.
I am a Responsive Developer who thrives on visual storytelling and the best user experience. When I'm not working, I can be found in my shop or on an adventure with my family.
December 2019 I propsed to my wife. It was December 22nd to be exact. Every year my wife and daughter makes sugar cookies for christmas and decorate them. This year was just the same except I decorated some to spell out "will you marry me?". It was a very special night for our family. I even had my daughter help with the proposel.
She said yes so the palnning began. Three months into our planning the 2020 pandemic hit and we didnt know if we were even going to be able to get married. We continued to plan in hopes that but the end of 2020 the pandemic would subside enough for some opening of the state. Luckily we caught a window when the governor open things up a bit which allowed us to have our wedding with 50 of our family and friends.
The wedding was beautiful and off we were on our honeymoon. Our original plan was taking us to the Netherlands but as the pandemic would have it we were shut out of other countries. We made the best of the situation and booked a trip to New Orleans. We had a good time in New Orleans, trying the local cusine, walking around the famous French Quarter, and hoping on the Historic St. Charles street car.


The domestic turkey is derived from the native wild turkey of North America. Each year 267 million turkeys are sold in the United States. They're bred for big breasts and their pure white feather. But turkeys weren't always like this and their genes have been manipulated to reach this point. The genetic potential of turkey breeds is constantly improving due to the efforts by the breeding companies and is seen across a wide range of biological traits. Exploitation of genetic potential requires constant evolution of nutrition and management systems to ensure previously accepted methods have not reached a limiting threshold. The genetic improvement in turkey is attributed largely to selective breeding programs that rely on highly heritable phenotypic traits, such as body size and breast muscle development. Also, considerable attention has been done on artificial insemination in recent years to improve their reproductive efficiency and meat production.
Artificial insemination is the process of collecting sperm cells from a male animal and manually depositing them into the reproductive tract of a female. Artificial insemination is commonly used instead of natural mating in many species of animals because of the many benefits it can reap. These benefits include increased safety of the animals and producer, increased production efficiency and better genetics. Artificial insemination centres were founded by the state between early 1950s and the end of the 1970s. The state of artificial insemination in the sheep and goat industries has developed over the last couple of decades. The number of artificial inseminations in the sheep industry and the ratio of inseminated ewes increased sharply. As the consequences of the use of artificial insemination (AI) with semen from imported breeding rams, wool production traits (fibre diameter, shearing, greasy wool weight and staple length among others) have steadily and gradually increased. Also, average milk production per ewe has increased 6 times annually.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque dui elit, lacinia ac efficitur id, laoreet ac augue. Nulla eleifend volutpat massa quis gravida. Ut pellentesque, est ac tincidunt commodo, orci mauris auctor nunc, ac aliquet enim quam malesuada massa.


Home
Projects
Courses
Organizations
Extracurricular Activities
Organizations I Attended
Organizations I Attended


ZwWdP 01-02-2011
|
ZEIT |
INTERPRET |
TITEL |
|
20 h |
T. Rex |
I Love To Boogie |
|
|
Broken Beats |
The Rules |
|
|
Orwell |
A Long Way To The Start |
|
|
David Bowie |
All The Young Dudes |
|
|
The Phoenix Foundation |
Flock Of Hearts |
|
|
Gruff Rhys |
Vitamin K |
|
|
Gruff Rhys |
Shark Ridden Waters |
|
|
The Milk And Honey Band |
Spiral And Arc |
|
|
Jonny |
Candyfloss |
|
|
The High Wire |
Pump Your Little Heart |
|
|
Thirteen Moons |
Origins |
|
|
Tammi Terrell |
All I Do Is Think About You |
|
|
The High Llamas |
Clarion Union Hall |
|
|
Teitur |
Feel Good |
|
|
Remington Super 60 |
Mister Nilsson |
|
21 h |
Duran Duran |
Serious |
|
|
Bart Davenport |
Eye In The Sky |
|
|
Ron Sexsmith |
Miracles |
|
|
Heist |
If |
|
|
The Zombies |
The Look Of Love |
|
|
Budapest Radio Orchestra |
February |
|
|
The Phoenix Foundation |
Bitte Bitte |
|
|
The Loch Ness Mouse |
Jules Verne |
|
|
John Barry |
The Persuaders |
|
|
The Mummers |
Stuck In The Middle |
|
|
Focal Point |
Far Away From Forever |
|
|
The Whitest Boy Alive |
Intentions |
|
|
Duke Special |
You Spin Me Round |
|
22 h |
Joe Egan |
Back On The Road |
|
|
Delay Trees |
In February |
|
|
Racing Cars |
The Shoot Horses Don't They |
|
|
The Phoenix Foundation |
Golden Ship |
|
|
Colin Hay |
Overkill (Acoustic) |
|
|
Undersea Poem |
Ants |
|
|
Thirteen Moons |
Undercurrent |
|
|
The Zombies |
Summertime |
|
|
The Coral |
Walking In The Winter (Acoustic) |
|
|
Tahiti 80 |
4 AM |
|
|
Daniel Carlson |
Gold (Long Version) |
|
|
World Party |
She's The One |
|
|
Duke Special |
You Do Something To Me |
|
|
Louis Armstrong |
We Have All The Time In The World |
|
|
O Morno |
Pinano |


--- layout: page markdown_body: "" --- {% capture changelog_contains %}## {{ page.release.version }}{% endcapture %} {% capture upgrade_contains %}> {{ page.release.version }}{% endcapture %}
| Date | Download | Size | Verification | Description |
|---|---|---|---|---|
| {{ page.release.date }} | {{ asset.name }} | {{ asset.size | filesize }} | [MD5] [SHA1] [SHA256] [SHA512] | {% if asset.name contains '-basic' %}Only Apache, PHP, MySQL services and some tools are included{% elsif asset.name contains '-light' %}Only Apache and PHP services are included{% else %}All modules are included{% endif %} |


Evangelist and Author.
Dr. Sunny Ezhumattoor also known as Dr. John Mathew has been a conservative critique on controversial topics for many decades. He is the author of many award winning books on social and family issues. His literary works display the profound knowledge and erudition he gained in economics, sociology. political science, Philosophy, Scientific Humanism and Jurisprudence. Dr. Sunny uses his mighty talent in writing as a tool for correction and predicting irrational and inexcusable practices among Christians as well as society in general.
From the year 1973, Dr. Sunny resides at Houston, Texas with his wife Annamma and three sons Sunil, Jason and Cyril. Sunil and his wife Jean have two children Lucas and Aubrey. Jason and Shiana have three children Joshua, Nathan and Sophia. Cyril and Megan have two children Caleb and Elizabeth. In 2013 Dr. Sunny retired from JP Morgan Chase Bank in Houston after 40 years of service.
Houston, TX
Email:


--- layout: page title: Github Repositories permalink: /repos/ --- Go ahead and check the other repositories available on Github. {% assign gh = "https://github.com/" %}


Flick the tumblers to record systolic, diastolic, and beats per minute.
Record Your Blood Pressure
Use the tumblers to enter your systolic, diastolic, and beats per minute. Add a note to remind yourself about this particular measurement, and view the plus/minus of each of your measurements on the summary screen before saving.
Trend Line
Inspired by The Hacker's Diet, Goal Blood Pressure implements an Exponentially Smoothed Moving Average Trend Line. The exponentially smoothed moving average trend line is a complicated way of saying, “We are using a line to smooth out measurement to measurement fluctuations.”
 Below, starting blood pressure and goal blood pressure are shown in their default colors, gray for starting blood pressure, green for goal blood pressure.

To combat this embarrassment I’ve added an extra layer of protection to Goal Blood Pressure, under ‘Settings’ click on the ‘Touch ID / Passcode’ to protect Goal Weight from prying eyes. Now anytime someone attempts to open Goal Blood Pressure they will be challenged with providing authentication via Touch ID or the phone’s passcode.
Sharing Progress
There is nothing like sharing your progress with 100s of close friends on Facebook, Twitter, or emailing an update to your mother. With a double tap on any of the graphs you can quickly take a picture of your current progress and post it for all to see.
Settings
Export Blood Pressures – Need to get your blood pressure readings to someone else? Export them to a CSV (comma separated value) file that can be opened in Excel.
Change Graph Colors – Each one of the graph’s colors can be independently changed.
Save your measurements to Apple’s Health app.
Turn on/off recording notes and beats per minute
Add in your historical measurements
View your measurements over five different time periods, three days, one week, two weeks, thirty days, and ninety days


Planning.Solar
Informational site to guide users through greenhouse, conservatory, etc.., purchases and builds
Solar Innovations released the first of a series of sites I built for them. This site focuses on the greenhouse planning, but the framework and theme are highly reusable. They are destined to be used on at least 2 more planning sites such as “Conservatory Planning” or “Skylight Planning”.
The theme was developed with SASS. This allowed me to create a base theme and then apply the various branding styles. For example, if you visit Greenhouse.Planning.Solar and Planning.Solar you can see the difference between two of the four themes.
The sites are built using Jekyll and served up through an NGINX webserver. This allows the site to be extremely performant. This blog post covers the performance and optimizations.
Homepage of Greenhouse Planning


Create a SQL data filter to send filters based on any data stored in ADO.NET-accessible data sources such as relational databases. Whether you let users pick a record set to use in interactive mode, or specify the data row to use directly, the filter value being sent is always the current, live value from the specified data source.
To connect to your data source, you select the data source provider to use and specify a connection string. If unsure, your database administrator can help you with this. The following ADO.NET data source providers can be used out of the box:
Data source providers can be added and removed on the Configuration
page in the FilterZen Studio at
http://farm_url/_layouts/roxority_FilterZen/default.aspx?cfg=cfg.
For the SQL data filter to obtain filter values from your data source, you need to specify, in SQL (or any other query language dialect supported by your data source provider), the query sent to the data source to fetch a result set of filter values. In order for this filter to work as expected, it is mandatory that the result set of filter values is guaranteed by your query to always be returned in a consistent sort order, so in SQL you should add an ORDER BY clause. Per the SQL standard, unless your query specifies the sort order explicitly, the default sort order of data rows is undefined and thus may change randomly at any time.
Your query will need to return a stream of record sets (which your query may also pre-filter and sort as preferred) with at least one data column. The name of the column containing the filter value may be identical to the database column or changed to another name by your query — however, you need to specify the result set column name to be used as the value column, i.e. the name of the column providing the filter value. In interactive mode, if you want to display to the user another column value than the one sent as the filter value, specify the name of the display column.