| Opcode/Instruction | Op /En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
| F2 0F 5F /r MAXSD xmm1, xmm2/m64 | RM | V/V | SSE2 | Return the maximum scalar double-precision floating-point value between xmm2/m64 and xmm1. |
| VEX.NDS.128.F2.0F.WIG 5F /r VMAXSD xmm1, xmm2, xmm3/m64 | RVM | V/V | AVX | Return the maximum scalar double-precision floating-point value between xmm3/m64 and xmm2. |
| EVEX.NDS.LIG.F2.0F.W1 5F /r VMAXSD xmm1 {k1}{z}, xmm2, xmm3/m64{sae} | T1S | V/V | AVX512F | Return the maximum scalar double-precision floating-point value between xmm3/m64 and xmm2. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| RM | ModRM:reg (r, w) | ModRM:r/m (r) | NA | NA |
| RVM | ModRM:reg (w) | VEX.vvvv | ModRM:r/m (r) | NA |
| T1S | ModRM:reg (w) | EVEX.vvvv | ModRM:r/m (r) | NA |
Description
Compares the low double-precision floating-point values in the first source operand and second the source operand, and returns the maximum value to the low quadword of the destination operand. The second source operand can be an XMM register or a 64-bit memory location. The first source and destination operands are XMM registers. When the second source operand is a memory operand, only 64 bits are accessed.
If the values being compared are both 0.0s (of either sign), the value in the second source operand is returned. If a value in the second source operand is an SNaN, that SNaN is returned unchanged to the destination (that is, a QNaN version of the SNaN is not returned).
If only one value is a NaN (SNaN or QNaN) for this instruction, the second source operand, either a NaN or a valid floating-point value, is written to the result. If instead of this behavior, it is required that the NaN of either source operand be returned, the action of MAXSD can be emulated using a sequence of instructions, such as, a comparison followed by AND, ANDN and OR.
128-bit Legacy SSE version: The destination and first source operand are the same. Bits (MAX_VL-1:64) of the corresponding destination register remain unchanged.
VEX.128 and EVEX encoded version: Bits (127:64) of the XMM register destination are copied from corresponding bits in the first source operand. Bits (MAX_VL-1:128) of the destination register are zeroed.
EVEX encoded version: The low quadword element of the destination operand is updated according to the writemask.
Software should ensure VMAXSD is encoded with VEX.L=0. Encoding VMAXSD with VEX.L=1 may encounter unpre-dictable behavior across different processor generations.
Operation
MAX(SRC1, SRC2)
{
IF ((SRC1 = 0.0) and (SRC2 = 0.0)) THEN DEST (cid:197)SRC2;
ELSE IF (SRC1 = SNaN) THEN DEST (cid:197)SRC2; FI;
ELSE IF (SRC2 = SNaN) THEN DEST (cid:197)SRC2; FI;
ELSE IF (SRC1 > SRC2) THEN DEST (cid:197)SRC1;
ELSE DEST (cid:197)SRC2;
FI;
}
VMAXSD (EVEX encoded version)
IF k1[0] or *no writemask*
THEN
DEST[63:0] (cid:197) MAX(SRC1[63:0], SRC2[63:0])
ELSE
IF *merging-masking*
; merging-masking
THEN *DEST[63:0] remains unchanged*
ELSE
; zeroing-masking
DEST[63:0] (cid:197) 0
FI;
FI;
DEST[127:64] (cid:197) SRC1[127:64]
DEST[MAX_VL-1:128] (cid:197) 0
VMAXSD (VEX.128 encoded version)
DEST[63:0] (cid:197)MAX(SRC1[63:0], SRC2[63:0])
DEST[127:64] (cid:197)SRC1[127:64]
DEST[MAX_VL-1:128] (cid:197)0
MAXSD (128-bit Legacy SSE version)
DEST[63:0] (cid:197)MAX(DEST[63:0], SRC[63:0])
DEST[MAX_VL-1:64] (Unmodified)
Intel C/C++ Compiler Intrinsic Equivalent
VMAXSD __m128d _mm_max_round_sd( __m128d a, __m128d b, int);
VMAXSD __m128d _mm_mask_max_round_sd(__m128d s, __mmask8 k, __m128d a, __m128d b, int);
VMAXSD __m128d _mm_maskz_max_round_sd( __mmask8 k, __m128d a, __m128d b, int);
MAXSD __m128d _mm_max_sd(__m128d a, __m128d b)
SIMD Floating-Point Exceptions
Invalid (Including QNaN Source Operand), Denormal
Other Exceptions
Non-EVEX-encoded instruction, see Exceptions Type 3.
EVEX-encoded instruction, see Exceptions Type E3.


At Advanced Football Academy our vision is very simple:
“help develop better football players”
The goal at Advanced Football Academy is to provide young players with an environment that is conducive to learning the game of football, encourages fun and provides for player safety.
Our objective is to:
Our coaches are FFA certified and combine extensive playing experience with modern football knowledge and techniques to help deliver effective and enjoyable sessions.
All coaches are WWC approved.


PureScript Spec is a simple testing framework for Purescript, inspired by hspec. Use PureScript Spec to write synchronous and asynchronous tests using a simple DSL, combine with other testing tools, and generate test output in various formats.
Given that you already have a PureScript project setup, the first thing to do is installing purescript-spec
as a development dependency.
bower install --save-dev purescript-spec
The basic building block of spec writing is it
, which creates a spec with a spec body. Spec bodies have the type Aff r Unit
, which is similar to the Eff
type, but with the addition of asynchronicity. When specs are run, they are considered successful, or passing, if the Aff computation does not result in an error. For more information, see purescript-aff.
In the following example we use pure unit
as a body, which does nothing. It will not throw an error, and the spec will always pass.
it "does nothing" $ pure unit
A more interesting test would assert something. Let’s check that addition works!
it "adds 1 and 1" do
1 + 1 `shouldEqual` 2
The shouldEqual
function, here used as an infix operator, takes two values and checks if they are equal. If not, it throws an error in the Aff monad, causing the spec to fail.
Specs can also be pending, which means that they are not testing anything yet - they are like placeholders. We use pending
to write a pending spec.
pending "calculates the answer to Life, the Universe and Everything"
Pending specs can also contain a spec body, just like with it
. The difference is that the body will be ignored. Pending spec bodies are used to give a hint what the spec should assert in the future. Use pending'
(note the '
at the end) to create a pending spec with a body.
pending' "calculates the answer to Life, the Universe and Everything" do
answerTo theUltimateQuestion `shouldBe` 42
To group multiple specs in a logically related group of specs, we use describe
. This creates a new spec which represents the named group.
describe "MyModule" do
it "..." do
...
it "..." do
...
it "..." do
...
Spec groups can be nested in multiple levels, creating a hierarchy of named groups.
describe "MyModule" $
describe "SubModule" $
describe "Database" do
it "..." do
...
it "..." do
...
it "..." do
...
Let’s look at an example of a complete spec program, with the needed imports and a proper main
function. The specs shown in the header image looks like this:
module Main where
import Prelude
import Control.Monad.Aff (later')
import Control.Monad.Eff (Eff)
import Test.Spec (pending, describe, it)
import Test.Spec.Assertions (shouldEqual)
import Test.Spec.Reporter.Console (consoleReporter)
import Test.Spec.Runner (RunnerEffects, run)
main :: Eff (RunnerEffects ()) Unit
main = run [consoleReporter] do
describe "purescript-spec" do
describe "Attributes" do
it "awesome" do
let isAwesome = true
isAwesome `shouldEqual` true
pending "feature complete"
describe "Features" do
it "runs in NodeJS" $ pure unit
it "runs in the browser" $ pure unit
it "supports streaming reporters" $ pure unit
it "supports async specs" do
res <- later' 100 $ pure "Alligator"
res `shouldEqual` "Alligator"
it "is PureScript 0.10.x compatible" $ pure unit
RunnerEffects
is a convenience type alias that includes the effect rows used by the Node runner, meaning you do not have to type them all out if you want to have a type annotation for your main
function. You can pass any extra effect rows used in your own tests:
main :: Eff (RunnerEffects (random :: RANDOM, buffer :: BUFFER)) Unit
You can split specs into multiple files and combine them using regular monadic bind, e.g. with do
expressions.
baseSpecs = do
mathSpec
stringsSpec
arraySpec
...
This is often used to combine all specs into a single spec that can be passed to the test runner, if not using purescript-spec-discovery.
Sometimes you do not wish to run all specs. It might be that you are working on a certain feature, and only want to see the results for the relevant tests. It can also be that some spec takes a lot of time, and you wish to exclude it temporarily. By using itOnly
instead of the regular it
, the test runner includes only that spec.
describe "My API" do
itOnly "does feature X" ... -- only this spec will run
it "does things that takes a lot of time"
Similar to itOnly
, describeOnly
makes the runner include only that group.
describe "Module" do
describeOnly "Sub Module A" -- only this group will run
it "does feature X" ...
describe "Sub Module B"
it "does feature Y" ...
You can use QuickCheck together with the purescript-spec-quickcheck adapter to get nice output formatting for QuickCheck tests.
When you have a spec, you need a runner to actually run it and get the results. PureScript Spec comes with a NodeJS runner, run
, which takes an array of reporters and a spec to run. What you get back is a test-running program of type Eff r ()
. The effect rows in r
depend on what you do in your specs and what reporters you are using. The program can be run using Pulp.
pulp test
If you’re not using pulp, you can compile the test program using psc
. The following command compiles all PureScript modules in test
and src
.
psc -o output/tests 'test/**/*.purs' 'src/**/*.purs'
After that has finished, you can run the test program using NodeJS.
NODE_PATH=output/tests node -e "require('Test.Main').main();"
NOTE: A test program using Test.Spec.Runner.run
cannot be browserified and run in the browser, it requires NodeJS. To run your tests in a browser, see Browser Testing below.
Reporters can be passed to the runner, e.g. run [reporter1, ..., reporterN] spec
. Currently there are these reporters available:
consoleReporter
in Test.Spec.Reporter.Console
dotReporter
in Test.Spec.Reporter.Dot
specReporter
in Test.Spec.Reporter.Spec
tapReporter
in Test.Spec.Reporter.Tap
In addition to the regular run
function, there is also run'
, which takes a Config
record.
main = run' testConfig [consoleReporter] mySpec
where
testConfig = { slow: 5000, timeout: Just 10000 }
The Test.Spec.Runner
module provides a defaultConfig
value which you can use to override only specific values.
main = run' testConfig [consoleReporter] mySpec
where
testConfig = defaultConfig { slow = 100 }
If you are running your specs in an NodeJS environment, e.g. with pulp test
, you can automatically scan for spec modules using purescript-spec-discovery. Then your main
function can be as simple as:
main = discover "My\\.Package\\..*Spec" >>= run [consoleReporter]
All modules matching the pattern, that has a spec :: Spec r ()
definition will be combined into a single large spec by discover
.
You can run tests in a browser environment, instead of NodeJS, using mocha
or karma
. For more information, see purescript-spec-mocha.
purescript-spec on Pursuit features version information and API documentation. For updates on the project, follow @owickstrom at Twitter.
The source code is available on GitHub.
If you have any issues or possible improvements please file them as GitHub Issues. Pull requests are encouraged.


Fast Neural Machine Translation in C++
This tutorial serves as a guide for beginners in neural machine translation (NMT). It should allow you to appreciate the motivation behind the different steps taken in the other examples and tutorials.
We’ll explore a simplified pipeline to produce a translation model consisting of:
Central to producing a machine translation system is the data used to train it. The models rely on large amounts of quality data to perform well. One aspect of this quality is whether your chosen dataset is suited to your desired translation task.
Training data takes the form of equivalent text sequences in the source-language and target-language. You can find examples of such corpora compiled at ELRC, ParaCrawl and OPUS, as well as others. These parallel corpora may be found stored in different formats. Common formats include: TMX, TSV and plain text.
Translation Memory eXchange, or TMX, is an XML formatted standard that encodes parallel data in terms of translation units. A translation unit is a set of aligned sentences across multiple languages. Each variant in the set consists of sentence in a particular language. A minimal translation unit that containing English “Hello world!” and the Italian “Ciao mondo!” would look like
...
<tu>
<tuv xml:lang="en">
<seg>Hello world!</seg>
</tuv>
<tuv xml:lang="it">
<seg>Ciao mondo!</seg>
</tuv>
</tu>
...
and be stored alongside other units in the full TMX file. The complete file may contain additional metadata, such as the origin of each segment or a confidence score for the variants.
TSV and plain text files are somewhat simpler. They maintain association between parallel sentences by aligning them line-by-line. In the case of a tab-separated values (TSV) file the parallel segments from each language are contained on the same line in one file, with each language separated by a tab character, such as:
# $ cat corpus.en-it.tsv
Hello world! Ciao mondo!
Plain text files store associated sentences in different files, one for each language, such that the sentence on a line of one file is parallel to the sentence on the same line in another file. As in:
# $ cat corpus.en.txt
Hello world!
# $ cat corpus.it.txt
Ciao mondo!
Marian natively accepts TSV and plain-text files. For TMX files, you can extract TSV or plain text files using external tools. In the remainder of this example, we’ll consider a pair of plain-text files.
Having obtained a dataset for the languages you want to translate between, there are several preprocessing steps that can impact the quality of the final model.
The first step concerns the quality of the dataset, and filtering out noise present in it. In terms of parallel text data, this noise can be in the form of poor alignment, which results in the incorrect pairing of sentence. Similarly, non-translated source-side sentences may be present on the target-side, or the target-side may be a valid translation but in the wrong language. Inconsistent spelling and punctuation are an additional source of noise. In an attempt to address noise in the data, rule-based cleaning is applied to the data.
Rule-based cleaning is a set of heuristics applied to the corpus to remove low quality data. As an example, such rules may impose limits on:
Deduplication is also commonly applied as part of corpus cleaning.
These rules are motivated from the desire to remove overly long segments that may consist of multiple sentences, with the added benefit that this can reduce the memory required in training; this also includes the removal of empty sentences. The ratio on lengths codifies the idea that the length of the source and target sentences should be positively correlated. The content of the segments can also checked by restricting the presence of non-alphabet characters/words for the language in question. In doing so, we are able to remove sentences consisting of few real words, and sentences with too many characters from a different alphabet. These act as a quick language filter. However, a dedicated filter based on the result of language classification model is a stronger requirement.
Automatic cleaning methods can also be utilised. One such example is filtering based on the dual conditional cross-entropy. By training two rudimentary translation models, one in the desired direction and the other in the reverse, this combined metric scores sentence pairs based the level of agreement between the models with a penalty for sentence pair that both models deem improbable.
Normalisation is may also be applied a pre-processing step. An example of normalisation would be the localisation of punctuation, such as the style of quotation marks, or the radix character
The number is 3.14 # en
Il numero è 3,14 # it
The normalisation of capitalisation, known as Truecasing (see e.g. truecaser from Moses), can also be applied. This method attempts to reconstruct the proper capitalisation for words in the sentence. These casing rules may differ between the source and target language.
As is the case with heuristically motivated techniques, the choice of rules imposed and reasonable values for their thresholds will depend on the languages involved and the domain of interest.
Tokenisation is the process of splitting up text into smaller fragments called tokens. These tokens are associated with some numeric representation, such as an ID, that allows them be used in a machine translation model. The vocabulary is the set of tokens extracted from the corpus, with the number of tokens setting the vocabulary size. Unfortunately, the complexity of training and translating increases with vocabulary size. This leads to a trade
A simple approach is to perform word tokenization, in which each word in the
sentence becomes its own token. However, the size of the vocabulary grows with
each new word, even if the new word is related to an existing one. The words
grow
, grows
and growing
would all get distinct tokens despite sharing a
common stem in grow
. To better handle this we can look at subword units to
model these relationships. We may imagine in the previous example, that our
subword tokens would be ▁grow
, s
and ing
, where ▁
represents the
beginning of a word. From this we can reconstruct the three example words:
▁grow
, ▁grow s
and ▁grow ing
, but may also generalise to new words
▁grown
and ▁grow th
. One approach to discovering these subword
representations is Byte-Pair Encoding, or BPE. This procedure looks through the
corpus starting at the character level and successively joins the most frequent
pairs of symbols until the desired vocabulary size is achieved. Imagining back
to the example, the BPE algorithm would likely see the co-occurrence of i
and
n
, and later the co-occurrence of in
and g
to form ing
as a token. There
are extensions to this idea that take a probabilistic approach to determining
what subwords to build, and even in determining how a particular sentence should
be encoded.
In Marian tutorials and examples we make use of the Moses tokenizer script and BPE. Additionally, we show examples using SentencePiece models that are natively supported. While, another commonly used implementation is subword-nmt.
In many aspects, the process of training a machine translation model is no different than training machine learning systems in other domains. The process starts with the acquisition and preparation of datasets, as described above. We must then select a model type suited to our particular task. For machine translation in Marian, this might be an RNN encoder-decoder (s2s) model or a transformer model. The model type sets the general network architecture, but does not uniquely define it. The size of the network and vocabulary as well as a the choice of training parameters: loss function, optimizer, learning rate schedule and validation metrics, are all important considerations.
There are additional hyperparameters that control model behaviour. The size of
the embedding dimension is an integral part of the model; it directly sets the
size of its internal representation. The mapping from tokens to this internal
representation requires a matrix containing a vector representation for each
token in the vocabulary. A typical vocabulary size of 32000
and an embedding
dimension of 512
requires over 16 million parameters. In general, an separate
embedding matrix is required to map source-side tokens to vectors, target-side
tokens to vectors, and output vectors to target-side tokens. In practice, the
latter two matrices can share the same parameters in a process known as weight
tying. When translating between languages that use the same script its practical
to tie all of the embeddings.
The complexity of the model is also affected by its depth. Marian has separate controls for the depth of the encoder and decoder. Concisely, these control the number of layers of computation with the motivation being that additional layers give the model the capacity to learn more efficient representations. Beyond the number of layers, there are hyperparameters that modify the behaviour of the layers themselves. These range from modifying activation functions, specifying the gating mechanism in RNN cells as well as the intermediate dimensions in feed-forward blocks.
The learning process of the machine learning model is guided by the loss function and the optimizer. The loss function is a function that quantifies the “distance” between the current output and the desired output. It may also be referred to as the cost function, as it is in Marian. The cross-entropy loss is the default cost in Marian.
The optimizer codifies the procedure in which the model moves towards the desired solution. These typically use gradients, computed by the network, to update the parameters in a direction that steps towards a minimum. The size of these steps is mediated by the learning-rate hyper-parameter. At its simplest, the learning-rate is just a fixed quantity, but more advanced schemes can vary the value over time, a so-called learning rate schedule, depending on factors such as amount of data seen, or updates without cost improvement. The inclusion of an initial warmup phase at the start of training is often recommended to stabilise updates.
Beyond this overall rate, different optimization algorithms may employ their own parameters. For instance, the Adam optimization algorithm also computes an separate exponentially decaying average for the first and second moments of parameter gradients; the rate of each exponential decay are user configurable.
During training, the machine translation model processes the parallel corpus. The source input is propagated through the network architecture and compared to the target sentence. The loss is computed, and the optimizer determines the update applied to the models parameters.
For any reasonably sized dataset, memory constraints mean it is not possible to process the entire corpus in a single batch. Instead, the corpus is processed as a sequence of mini-batches, whose size is constrained by the number of sentences, or tokens it contains. In Marian, either of these options may be controlled directly, or alternatively, the mini-batch size can be determined automatically by the workspace memory allocated to the program. Marian also has the concept of a maxi batch which preloads multiple mini-batches. This preloading makes it possible to sort sentences within the maxi batch to regenerate mini-batches that have similar sentence lengths. Constructing mini-batches in this way can reduce the number of padding tokens required increasing the computational efficiency.
This training process repeats until some stopping criteria is met. A practical
criterion is to stop training after a certain amount of data has been seen; this
may be in terms of batches, tokens, or epochs, the number of times the model has
seen the entire dataset. However, this tells us nothing of the resulting models
quality. While the cost does give an indication of model performance, it is
biased by having already seen the data. The solution to this is to periodically
validate the performance of the model against an unseen dataset, or validation
set. Computing a metric from this independent dataset enables one to halt
training before the model is overfit to the training data. A common approach
used in Marian is early-stopping, where training concludes after successive
validation scores fail to improve over some period. As an example, an
early-stopping value of 5
would stop training if the previous five updates did
not yield an improved validation score.
To monitor your model during training, Marian will periodically output a summary of its progress. A typical output is shown below.
Ep. 7 : Up. 36000 : Sen. 948,710 : Cost 3.21035433 : Time 317.61s : 77198.20 words/s : gNorm 0.5012
Here Ep.
refers to the number of epochs and Up.
to the total number of
optimizer updates. Sen.
is the number of sentences seen this epoch. Cost
is
the current value of the loss function. Time
is the time taken to process the
last batch of data, and is followed by the processing speed in words per second.
Finally, gNorm
reports the exponential average for the norms of parameter
gradients. Similarly, the validator will periodically compute and output its
score, such as in
[valid] Ep. 9 : Up. 50000 : bleu : 35.9958 : stalled 2 times (last best: 36.0671)
[valid] Ep. 9 : Up. 50000 : perplexity : 3.74923 : new best
which shows the result of two different validators. They report that after
update 50000
, which occurs in data epoch 9
, the bleu
validator has a score
of 35.9958
having stalled twice, while the perplexity
score has improved to
3.74923
. Marian supports a number of validation metrics while also providing
an option to use a custom validator script.
The evaluation of a machine translation model measures the quality of its output. The final evaluation of a model is made using a test set. This test set should be independent to the training set and also to the validation set, as it is no longer unbiased, having been used to select an optimal set of hyperparameters. It is crucial that any pre-processing (normalisation) that was applied to the training data is applied identically for evaluation.
The natural benchmark to gauge quality is human judgement in which participants score the translated output of a test set given the source input, sometimes with the context of a reference translation. In practice undertaking a statistically robust human assessment is costly, and is only feasible to compare small sets of models.
Automatic evaluation metrics are therefore a desired alternative, provided they reliably correlate with human judgement while also being practical to deploy at scale. Automated metrics are often used in model validation and evaluation. For instance, the validator example of the previous section contains a BLEU score.
The BLEU score is a widely used algorithm, it computes a metric based on a
modified precision score over n-grams (a contiguous sequence of n
words) in
the candidate translation as compared to a reference. It also includes a
“brevity penalty” to prevent candidates much shorter than their references being
too highly scored. An alternate n-gram based metric is chrF, which computes a
character-based n-gram F-score. Another approach is taken by the translation
error rate (TER) which measures the number of corrections required to match the
reference. Each of these implicitly relies on a tokenization method, and so to
compare across models in a consistent manner this should be standardized. Tools
like sacrebleu exist to consistently compare these metrics. In contrast to
these rule-based metrics, it is also possible to build a model to predict the
human judgement for a particular source, candidate and reference sentence. An
example of such a tool is Comet, which provides pre-trained multilingual
scoring models.
Beyond an evaluation of the overall translation quality, the performance against specific tasks can also be considered. Typically, a metric is computed on a challenge set with a focus on a linguistically motivated feature such as negation, punctuation, grammatical gender or verb tense; see ContraPro for such an example. Further measurements may focus on detecting biases present in models. Taken together these offer a more compelling report of the capability and deficiencies of a particular model.
Hopefully this guide serves as solid foundation as you explore the other tutorials and examples related to Marian!


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Are you a new student of programming? Have you found yourself wondering what language you should choose first? Look no farther! The questions below will help determine your personality and what language may best suit your temperament. Choose a selection from each category, then click the button to find out what language you are best suited for.
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Ruby is a language for people who like things to make sense. It uses language very similar to every day usage, rather that adding a ton of punctuation to trip you up! So as you might imagine, a lot of ruby programmers are happy with it and don't want to change. If you want to know more about Ruby straight from the Ruby community, click here.
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|
cds
1.2.0
|
Atomic item counter. More...
#include <cds/cxx11_atomic.h>
Public Types | |
| typedef std::atomic_size_t | atomic_type |
| atomic type used | |
| typedef size_t | counter_type |
| Integral item counter type (size_t) |
Public Member Functions | |
| item_counter () | |
| Default ctor initializes the counter to zero. | |
| counter_type | value (std::memory_order order=std::memory_order_relaxed) const |
| Returns current value of the counter. | |
| operator counter_type () const | |
| Same as value() with relaxed memory ordering. | |
| atomic_type & | getAtomic () |
| Returns underlying atomic interface. | |
| const atomic_type & | getAtomic () const |
| Returns underlying atomic interface (const) | |
| size_t | inc (std::memory_order order=std::memory_order_relaxed) |
| Increments the counter. Semantics: postincrement. | |
| size_t | dec (std::memory_order order=std::memory_order_relaxed) |
| Decrements the counter. Semantics: postdecrement. | |
| size_t | operator++ () |
| Preincrement. | |
| size_t | operator++ (int) |
| Postincrement. | |
| size_t | operator-- () |
| Predecrement. | |
| size_t | operator-- (int) |
| Postdecrement. | |
| void | reset (std::memory_order order=std::memory_order_relaxed) |
| Resets count to 0. |
Atomic item counter.
This class is simplified interface around std::atomic_size_t
. The class supports getting of current value of the counter and increment/decrement its value.


com.phunware.mapping.model
Classes
PwBuilding
PwCoordinateSpace
PwFloor
PwFloorResource
PwMapFloor
PwMarker
PwPoint
PwPointType
PwRoute
PwVenue


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-
Crackmes for lazies: angr demonstration
I have been playing crackmes and CTFs all the time to boost my reverse engineering knowledge and learn new stuff, but there are times that you find some challenges boring or without new unique technics so you develop some automation tools to pass the challenges. So in this blog post, I’m gonna show you my ultimate tool to solve these types of challenges.
-
Frida by example: bypassing IsDebuggerPresent() check
Almost every malware exists out there has a functionally to make the post-detection analysis more difficult. Threat actors use various anti-debugging techniques, one of the more common ones used to check whether a debugger is on via IsDebuggerPresent() Windows API call. In this blog post, we will discuss how to bypass this technique by Frida.


{{#partial "page"}}
{{product.call_for_price}}
That's like paying $7.92 per month!
Pick your plan
{{{product.description}}}


Our Services
Lorem Ipsum is simply dummy Business industry.
Font-Awesome Icons
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer.
Working Contact form
Many desktop publishing packages and web page editors now use Lorem Ipsum as their default model text, and a search for 'lorem ipsum' will uncover many web sites still in their infancy
Friendly Code
Finibus Bonorum et Malorum" by Cicero are also reproduced in their exact original form, accompanied by English versions from the 1914 translation by H. Rackham
Fully Responsive Design
Many desktop publishing packages and web page editors now use Lorem Ipsum as their default model text, and a search for 'lorem ipsum' will uncover many web sites still in their infancy
Retina Ready icons here
There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humouror randomised words which don't look even slightly believable.
Flat trendy landing page Design
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer.
ABout us
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the ore recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum
Read moreChoose your price
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How it works
Lorem Ipsum is simply dummy Business industry
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Happy Clients
We are explain who is using our business solutions
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make.
Darwin Michle, Project manager
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
Madam Elisabath, Creative Director
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make.
Clips arter, Lipsum directer
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
zam cristafr, manager
newsletter
Lorem Ipsum is simply dummy Business industry
Address
Business street
Second north section
Bavani nagar. 88769
Call : +987-9976-999
<EMAIL_ADDRESS>9976 999


Sales Record
Enter new data below to update data table
Location:
Minimum cookies per hour:
Maximum cookies per hour:
Average cookie sold per hour:
Send
back to the face!


Before Change
means = [0.485, 0.456, 0.406]
stds = [0.229, 0.224, 0.225]
preprocessed_img = img.copy()[:, :, ::-1]
for i in range(3):
preprocessed_img[:, :, i] = preprocessed_img[:, :, i] - means[i]
preprocessed_img[:, :, i] = preprocessed_img[:, :, i] / stds[i]
preprocessed_img = \
np.ascontiguousarray(np.transpose(preprocessed_img, (2, 0, 1)))
preprocessed_img = torch.from_numpy(preprocessed_img)
After Change
im_as_arr[channel] -= mean[channel]
im_as_arr[channel] /= std[channel]
// Convert to float tensor
im_as_ten = torch.from_numpy(im_as_arr).float()
// Add one more channel to the beginning. Tensor shape = 1,3,224,224
im_as_ten.unsqueeze_(0)
// Convert to Pytorch variable
im_as_var = Variable(im_as_ten, requires_grad=True)


PE gang member jailed
by Algoa FMA 20-year-old gang member was sentenced in the Port Elizabeth Regional Court to 19 years imprisonment of which he will effectively serve 12 years behind bars.
Police said that Elvis Cedras was sentenced on Wednesday for a shooting incident in March in Kleinskool.
Spokesperson, Colonel Priscilla Naidu, said he was arrested by members of the Provincial Organised Crime Investigation Unit shortly after he and another man fired shots at a house.
She said Unit members who were in the vicinity responded immediately upon hearing the gunfire and chased after the suspects, who had earlier walked past their stationary vehicle.
“One suspect fired at police but the members managed to apprehend the suspect and a stolen 9mm pistol and ammunition was seized. No one was injured,” said Naidu.
She said Cedras was sentenced on two counts of attempted murder and the illegal possession of a firearm and ammunition.


In addition to executing queries against the entire database, Proximity lets you execute queries against existing containers. In such cases, Proximity ignores the container subgraph information and merely limits query matches to the objects and links in the container. Executing a query against a container creates a new container of matching subgraphs at the top level, i.e., directly under the root container. This functionality is available through both the Proximity Database Browser and the command line query interface. You cannot execute a query against a container from the Query Editor.
The following exercise executes a query against the research-clusters2 container created in Exercise 5.3. The research-clusters2 container holds the 1d-star clusters of objects linked to research project pages. The new query searches this data to find pages from Cornell and those pages connected to the Cornell page by “out” links (links pointing from the core page to the linked page).
To execute a query against a container instead of against the full database, you can either navigate to the input container and call the query from the Proximity Database Browser as shown in Exercise 5.9, below, or specify the input container name as an optional argument to the query shell script, as shown above in Exercise 5.8. All queries run from the Query Editor are executed against the complete database.
Exercise 5.9. Querying a container from the Proximity Database Browser:
This exercise requires the container created in Exercise 5.3. You must have completed Exercise 5.3 before running the current exercise.
Before beginning, make sure that you are serving the ProxWebKB database using Mserver. Start the Proximity Database Browser if it is not already running.
Click Home to go to the Proximity Database Browser start page.
Click Containers. Proximity displays the current list of containers in the database.
Click research-clusters2. Proximity displays the research-clusters2 container page.
Click query. Proximity displays the Open dialog.
Navigate to the $PROX_HOME/doc/user/tutorial/examples
directory and
choose the query
cornell-out-clusters.qg2.xml
.
Click Open. Proximity prompts you for a
name for the results container. Enter
cornell-out-clusters
and click
OK.
|
If the database already includes a container with this name, Proximity asks whether you want to delete the existing container. Answering yes lets Proximity overwrite the contents of this container. This also deletes any containers inside the existing container. |
Proximity opens a window to show you a trace of the query execution. The last lines should be similar to the following excerpt (leading information showing elapsed time and execution thread has been omitted from the trace for brevity):
INFO kdl.prox.qgraph2.QueryGraph2CompOp - -> found 99 subgraphs INFO kdl.prox.qgraph2.QueryGraph2CompOp - -> query results saved in container: cornell-out-clusters INFO kdl.prox.qgraph2.QueryGraph2CompOp - * query: done Status: finished running query
Close this window after the query finishes.
Explore the results of the cornell-out-clusters container.
Executing the query creates a new, top-level container of 99 subgraphs using data in the original container of 83 subgraphs. Remember that Proximity uses the input container simply to limit the database items considered in executing the query; it does not use the existing subgraph information as part of this process. Therefore, the subgraphs identified as a result of executing this query are not related to those found by the query that initially created the input container. The new query does not require that its core_page object be a research project page, only that the school attribute have Cornell as a value. Thus the resulting subgraphs may have little resemblance to those in the input container.


A testnet faucet and tools built with the bsv JavaScript library for Bitcoin SV
GitHub Repo
Please return unused tBSV back to this faucet at this address: mgEWZ3FjNvWCswzLikjGMijsdvdV1kxzo6


{% extends "layout.html" %} {% block head %} {{ super() }} {% endblock %} {% block title %}First Login{% endblock %} {% block body %}
This is your first login on this website. You are about to sign in with the following OpenID: {{ openid|displayopenid }}
Before you can use this site we need a name for you. This is what will be displayed next to all of your public contributions to this site. Choose wisely because you cannot change this value later:


As you walk out of the kitchen area you sneakily start looking around to see if anyone saw you.
You like feeling like that.
| Go North | ||
| Go West | Go East | |
| Go South |


A quick {{ color }} {{ animal_one }} jumps over the lazy {{ animal_two }}.
Alice bought {{ orange_amount }} oranges and {{ apple_amount }} apples.
In total she has {{ orange_amount + apple_amount }} fruits.
She gave {{ donate_amount }} fruits to Bob.
Now she has {{ orange_amount + apple_amount - donate_amount }}fruits remaining.
A lot of people think {{ first_name + ' ' + last_name }} is the mostpowerful Marvel character.


Kendo
Kendo clubs
Kendo which means 'the way of the sword' is a form of Japanese martial art that originated from kenjutsu. Kendo makes use of shinai-bamboo swords and boqu-an armour. It is a martial art form that requires rigorous physical activity and ultimate skills which require practice inevitably.
Kendo Description
endo (the way of sword) is a Japanese variation of fencing sport practiced with a bamboo sword. This movement has a centuries-old tradition in Japan. At the beginning of the twentieth century it became well known worldwide thanks to the Japanese emigrants. It became popular in Europe and in Poland in the second half of the twentieth century.
Purpose :
- To mold the mind and body.
- To strive for improvement in the art of Kendo.
- And to forever pursue the cultivation of oneself.
Techniques
Before you start your search for the perfect hike, it’s helpful to think through a few things, such as:
-
Shikake-waza: These attack techniques are used to create an opening in an opponent by initiating an attack, or striking boldly when the opponent has created an opening.
- Hikibana-wazaBody and shinai will lose balance as the initiator strikes or when being attacked. This technique takes advantage of this to help execute a strike. A good example is Hikibana-kote when a strike is made to an opponent's kote as they feel threatened and raise their kensen as the initiator pushes forward.
- Nidan-wazaThere are two types. The first is for moving to the next waza after a failed first strike, and the second holds the opponent's attention and posture to create the opening for a second strike.
- Uchiotoshi-wazaThis waza knocks an opponent's shinai to the right or left. This neutralises a potential strike and gives the ideal chance to strike as an opponent is off-balance.


Also has touch-action:none to test subtle movements (and see how they fire touchmove)
touch-action:none
touchmove


${notification}
${navigation}
Submit
Tasks
Pending
Completed
Deleted
Categories
Add
${category.categoryName}
${category.taskCount}
No categories present!
×
New Task
Add File
File:
Priority:
High
Medium
Low
Hide from timeline
Category:
${ category.categoryName }
Login
Sign up
${task.title}
${task.content}
${task.completedmsg}
${comment.content}
${comment.author} ${comment.created}
Add Comment
Priority: ${task.priority}
${task.created}
${task.category}
No Tasks here
Create new task
here


When people workout they sometimes need motivation so they would listen to music but also sometimes there are headphones that aren’t for working out and I will be able to provide those list of headphones below.
LifeBEAM Vi is a personal coach it also includes a voice like siri but it’s different from siri. It helps monitor the users heart rate, it has a fitness app, and has good sound quality. It tells the user what they have done when the user is exercising. It helps the user lose weight, build an workout routine, prevent injury, and have fun. $149
Jabra Elite Sport is a bluetooth headphones that are comfort, allows people to zone out, and allows people to have a lot more motion because it’s going to be attached to the ear. This type of headphones includes an app which recommend what you should do next time you workout. Also the sound quality is great. $219.99
Jaybird X3 is a bluetooth headphones that allow the user to have a lot movement. The headphones is useful for people that like to work out or go for a run. The headphones are secure and comfort fit for the user ears, it also has 8 hours of battery. Also, music gives the use energy and motivation to keep on going. $129.99
JBL Reflect Contour is a bluetooth headphones that will be attach to the user ear so that user could have movement. The battery life of the headphones is 8 hours and it has uninterrupted listening experience. Lastly the headphones are made out of good quality material which makes the user ear feel comfortable.


This exercise is straightforward. You need to find a user where you can access a resource that you shouldn't be able to access. After a few attempts you will learn that 'Shivam' can access resources of the role 'Account Manager'.


Welcome to the language quiz! Here we are going to take input from you, the user, to determine which language would best fit your preferences. Answer below and hit submit to see your results!
Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.
Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.
Swift coding is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.
Swift coding is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.


"Lazy loading is a design pattern commonly used in computer programming to defer initialization of an object until the point at which it is needed. It can contribute to efficiency in the program's operation if properly and appropriately used. The opposite of lazy loading is eager loading."-- wikipedia
You want to be as lazy as possible, and hope that someone else comes along and does all the work for you.
This dog is doing it right
Lazy loading really means waiting to get data or process an object until you need it; not before. If you get data before and it's never used, the time it took was wasted. Also, getting all your data up front can make the user think the application is slow or unresponsive at first.
There are four common implementations:
Probably the most common implementation
ExampleA virtual proxy object shares an interface with the "real" object. The first time a property of the virtual proxy is accessed, the real object gets initialized. From that point on, accessing properties of the virtual object returns the corresponding property of the real object.
This basically combines the Lazy initialization and Proxy patterns
ExampleThe object is partially loaded, usually only with its identifier. The rest of the data is loaded the first time a property is accessed.
ExampleAnother object handles the lazy loading behavior and is used in the main object's property get accessors.
private ValueHolder<Widget> valueHolder;
public Widget MyWidget
{
get
{
return valueHolder.GetValue();
}
}
.NET 4.0 has a class just for lazy initialization!
MSDNYou specify the type of the object (type parameter) and the initialization function (constructor parameter) and it works like Nullable<T>, giving you IsValueCreated and Value properties.
IQueryable
/IEnumerable
uses a variation of lazy loading called "deferred execution" - it's methods are accessible, but the data is not populated until it's realized by a ToArray()
or other method call.User.Address.City
too bad we're out of time


AFFLICTION (M). (Village Roadshow) Director: Paul Schrader Stars: Nick Nolte, James Coburn, Sissy Spacek, Willem Dafoe, Mary Beth Hurt, Jim True, Homes Osborne, Brigid Tierney, Marian Seldes, Sean McCann, Wayne Robson, Brawley Nolte Running time: 114 minutes.
Adapted from the novel by Russell Banks (The Sweet Hereafter, etc), Affliction is a powerful, dramatic tale that looks at the disturbing pattern of male violence, and explores how this brutal legacy is often passed on from father to son.
The pathology of male violence is a theme common to much of writer/director Paul Schrader's work (Taxi Driver, Raging Bull, Blue Collar, etc), but rarely has it been tackled in such uncompromising and potent style before. Schrader seems to understand these characters and their motivations, and his sympathetic and insightful handling results in a compelling and hauntingly poignant character study, that is both chillingly realistic and deeply disturbing.
Wade Whitehouse (Nick Nolte) is the sheriff of Lawford, a depressed and sleepy New Hampshire hamlet. Reduced to being little more than a glorified traffic cop, he is increasingly frustrated by his demeaning role. He holds the job purely at the whim of the town's corrupt and oily businessman (Homes Osborne). Wade's impending divorce grows ugly and bitter, the relationship between him and his daughter grows more strained and distant, and a massive toothache is causing him pain. Wade turns a hunting accident into a murder investigation, in an attempt to distract his attention away from the real causes of his anger and frustration.
Wade's problems lie in his relationship with his father ('60's action star James Coburn, cast largely against type). For a long time, the young Wade (played by Nolte's own son Brawley) absorbed the full force of the brutal punishment dished out by his drunken, abusive father, to protect his mother and younger siblings. Younger brother Rolph (Willem Dafoe, who provides the voice over narration) escaped this brutal environment, but reluctantly returns home briefly following the death of their mother. The reunion is overshadowed by the intimidating presence of their father and his violent legacy. The emotionally crippled Wade sees himself becoming more and more like his father, and finally takes drastic action to exorcise his personal demons and find salvation.
Affliction unfolds like a low burning fuse as it works its way towards the inevitable explosion. Nolte is superb as the put-upon Wade who is slow to understand the true nature of his affliction. In one of his best, most heartfelt and moving performances in a long time, he brings a sense of sympathy and compassion to his complex character.
In his Oscar winning role, Coburn perfectly nails the abusive, domineering, contemptuous and unforgiving father, who bemoans the loss of real, hard men in a society growing soft. He is a monstrous figure, but somehow Coburn gives the character a surprisingly human dimension and depth. Sissy Spacek makes the most of her smaller role as Wade's waitress girlfriend, who finally decides to leave this volatile relationship before tragedy strikes.
Affliction explores many themes common to Banks' work - dysfunctional families, psychologically damaged men, the tense relationship between fathers and their children, small towns with dark secrets, difficult moral dilemmas - all set against the coldness of an unforgiving, snow covered landscape. The harsh, wintry landscape is almost a character in the story, and somehow adds to the chilling atmosphere that pervades the film.
Like the recent American History X, Affliction is an important film dealing with a serious theme, and deserves to be seen. However, this bleak film has proved difficult for its local distributors, who clearly had no idea how to market it and were going to release it straight to video. ***1/2 greg king http://www.netau.com.au/gregking
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


You can add values not present in autocomplete results by pressing enter or comma. Styled as a list of tags we're adding to. An optional "add" button is also provided to avoid user confusion (in our UX tests this does seem to be important).
You can add values not present in autocomplete results by pressing enter or comma. If you have entered a value but not pressed enter or comma when the save button is clicked, that value is returned too, demonstrating the incomplete option. Styled as a list of tags we're adding to.
You can add values not present in autocomplete results by pressing enter or comma. Styled as a list of tags we're adding to.
Multiple select autocomplete with drag and drop sorting, no duplicate entries, removed entries shown with strikethrough, and checkboxes for propagation to child objects.
Multiple select autocomplete with drag and drop sorting, no duplicate entries, removed entries shown with strikethrough, and a "job title" for each selected employee.
No more than 3 selections permitted.


This second example of Full Meta Jacket expands upon the first by having
_partials
folderThe list of posts to display at the top of this page is taken from the contents of the _posts
directory. The files in any _posts
directory are treated differently from normal files in the following ways:
The publish date of a post is taken from the filename and the title is assumed to be the remaining text. e.g. when the file 2012-06-26-monkeys-in-space.imd
is processed by Full Meta Jacket, amongst it's set of variables there will be a "date" value of "2012-06-26" and a "title" of "monkeys in space".
Any file inside _posts
that doesn't begin with a date is assumed to be a draft copy and won't be converted into a static file (for example see _posts/draft-potential-fourth-post.imd
which doesn't appear in the final output)
The contents of _posts
are "hoisted" up into the parent directory. e.g. a file such as ./foo/_posts/2012-06-26-blog.imd
would result in the static file ./foo/2012-06-26-blog.html
All metadata from the files in _posts
is concatenated into an array and assigned to a variable called posts
Looking at the original index.imd
file for this html page you can see that the list of posts at the top were generated with the line:
{ {=: posts | listWith:'post' }}
This takes the posts
list and passes it into the listWith
function along with another variable called post
which represents the partial file that should be used to render each element of posts
. You can see the post
code in _partials/post.html
:

{{= title }}

This index page uses a layout called listing-page
and each post uses a layout called post
. Both files are located in the _layouts
folder, if you view them in a text editor you can see that they each have a "layout" header value of default
. This nested structure is a good way of sharing common templating code throughout a site.


Drag the shapes around. If they collide they will be moved so that they don't collide. The circle is "heavy" - it will not be moved by other items (but will move other items)
Drag any of the circles and watch them react.


EREBUS Civic Service for 40th anniverary
by Erebus National MemorialEREBUS Civic Service for 40th anniverary with Governor-General Dame Patsy Reddy
40th Anniversary Service of Air New Zealand Flight TE901 28 November 1979 Mt Erebus, Antarctica
A civic service for the 40th anniversary of the accident will be held at Auckland’s Holy Trinity Cathedral, Parnell, at 5pm on Sunday 24th November, in the presence of Her Excellency the Rt Hon Dame Patsy Reddy GNZM, QSO, Governor-General of New Zealand and the Mayor of Auckland Council, Hon. Phil Goff CNZM . The Hon Andrew Little representing the Government will also be in attendance.
The service will feature special music and creative ways of participation. Erebus families are invited, along with interested members of the public. All are welcome.
Rev. Dr Richard Waugh, aviation historian and chaplain of the Hon. Company of Air Pilots (NZ Region), and instigator of the Erebus National Memorial, comments, “The service will be a very special time for Erebus families, and others, to remember and pay tribute to the 257 people who died. There will be special music and creative opportunities for all present to participate. This civic service is another way for New Zealand as a nation to work to care, respect and honour all those who died.”
ends


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Apache License 2.0
A permissive license whose main conditions require preservation of copyright and
license notices. Contributors provide an express grant of patent rights. Licensed works,
modifications, and larger works may be distributed under different terms and without
source code.
| Permissions |
Limitations |
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License and copyright notice |
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Click Me More information about Apache License 2.0
First producer Copyright
Copyright 2017 John Grosh
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and limitations under the License
Go to first producer GitHub site when you click on me
ETC
In accordance with Apache License 2.0, popcon annotated the modifications in the code.
The modifications are annotated as follows, and the newly created code or file has the original mark at the top.
Modified Comment Example : /*modified by devstar1224*/


Matrix Vector
Vector (column or row). Vector is matrix which one dimension equals to 1.
Subclasses
GrowVector
Groups
If true this is row otherwise this is column
See Also
Class Hierarchy


post martial law Ninoy Aquino and the Rise of People Power Oliver Ledbury 2010 | 57 min Nation buildingDocumentarypolitics
post martial law Tu Pug Imatuy (Right to Kill) Arbi Barbarona 2017 | 1 hr 30 min mtrcb family dynamicshuman rightspolitics
post martial law Ninoy Aquino and the Rise of People Power Oliver Ledbury 2010 | 57 min Nation buildingDocumentarypolitics
post martial law Tu Pug Imatuy (Right to Kill) Arbi Barbarona 2017 | 1 hr 30 min mtrcb family dynamicshuman rightspolitics


|
BL3 SDK
0.0.1
Borderlands 3 Class Documentation
|
#include <BL3_WwiseAudio_structs.hpp>
Public Attributes | |
| EWwiseTrackDirectionality | PlaybackDirection |
| unsigned char | UnknownData00 [0x3] |
| unsigned char | UnknownData01 [0x4] |
| class UWwiseEvent * | WwiseEventStart |
| class UWwiseEvent * | WwiseEventStop |
| float | EmitterRadius |
| bool | bAllowPlaythrough |
| bool | bIsLoopingEvent |
| unsigned char | UnknownData02 [0x2] |
| int | RowIdx |
| struct FFrameNumber | SectionStartFrame |
| struct FFrameNumber | SectionEndFrame |
| struct FFrameRate | CachedFrameRate |
| unsigned char | UnknownData03 [0x4] |
| bool bAllowPlaythrough |
| bool bIsLoopingEvent |
| struct FFrameRate CachedFrameRate |
| float EmitterRadius |
| EWwiseTrackDirectionality PlaybackDirection |
| int RowIdx |
| struct FFrameNumber SectionEndFrame |
| struct FFrameNumber SectionStartFrame |
| unsigned char UnknownData00[0x3] |
| unsigned char UnknownData01[0x4] |
| unsigned char UnknownData02[0x2] |
| unsigned char UnknownData03[0x4] |
| class UWwiseEvent* WwiseEventStart |
| class UWwiseEvent* WwiseEventStop |


Tools
- Mandatory
- Source Content Management
- Tickets
- Unit test framework
- Packager
- Nice to have
- Continuous integration automate
- Static analyser
- Runtime analyser
- I18n
- Website
- Documentation tools
Tools
Mandatory
Source Content Management
Why
A good scm allow you to:
- Save your work and rollback easily
- Keep trace of what you did, and how.
- Implement features easily: branch,
so you don't break your project during development, and you can still commit.
- Share, and work together.
What
Tickets
Why
- For bug reports.
- For feature request.
- As a todo list/backlog.
What
- Redmine/chiliproject
- Jira
- Avoid trac if your project contains subprojects
Unit test framework
Why
Unit test are awesome for:
- Debugging.
- Avoid regressions.
- They give nice examples of how to use your code.
Packager
Why
If you want your project to work you need to make it easy to test.
One way is to package it nicely.
What
If your whatever language, framework, does not provide it:
- cpack (which can be used without cmake)
- fpm
- Be a man and right your own rules/specs/ebuild
Nice to have
Continuous integration automate
Why
- It nice that it works on your computer, but it is better if it works on main targets (provides a packages for each target).
- Runs all the tools bellow in background.
What
- Jenkins
- gitlab-ci
- buildbot
Static analyser
Why
Efficient quality checking and nice advice at a low price. What's else?
What
- clang/gcc
- cppcheck/clint
- sonar
Runtime analyser
I18n
Website
Documentation tools


I am starting to learn XNA at the moment, so I am doing what everyone does when they learn a new language - remake their favourite game! I am making a simple remake of the windows version of Chips Challenge using the sprites from the open source clone of the game which can be found here - http://www.muppetlabs.com/~breadbox/software/tworld/ . Although this remake is by no means a full remake or compatible with the original, I am posting the source code so that someone else can learn from this experience. Keep in mind that this is my first game in XNA, so the code is a bit sloppy but it works.
Some of the features that I implemented for this tile based game are level saving and loading, an advanced menu system, power ups, a timer class, event handling and game state management. This remake is a simple one layer approach, as opposed to the original two layer version. I am implementing features as I go along and have finished the first level and I am working on the next levels. Progress might go a bit faster after I create a level editor, because hand coding levels is no fun! The core functionality of this game was completed in a day as a programming challenge that I set myself. The extra features / tiles took an extra day of coding (that I put off for far too long). At the moment, the code is quite messy, there are a few ugly hacks (especially the input detection), but I am working on improving it, adding a full input manager and possibly some enemies that move etc.
In the future I am looking at uploading more games that I can prototype quickly (for programming practice). So look forward to other classic remakes and newer stuff as well.
Here is a screen shot.
For people that are thinking of creating a tile based game, I suggest taking the time to make it work with the Tiled Map Editor level format. The Tiled Map Editor is a quick and easy way for creating tiled based levels (square and isometric). The tiles can have attributes associated with them which makes the code to load and save levels much cleaner. Wish I had used Tiled!
So check out the source code for this game and give it a bit of a play!


Nova Html5-SQLite Demo -- Users Management
Notice: this demo only works in google Chrome.
Add a User
username
birth year
disabled?
no
yes
Database Users
username
birth year
disabled?
created on
last updated
operation
xx
1980
no
2013-12-12
-


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Defines the basic DSL methods availlable in all Cucumber step definitions.
You can, and probably should, extend this DSL with your own methods that make sense in your domain. For more on that, see {Cucumber::RbSupport::RbDsl#World}
@private
@private
@private
@private
# File lib/cucumber/rb_support/rb_world.rb, line 16 def alias_adverb(adverb) alias_method adverb, :__cucumber_invoke end
Call a #Transform with a string from another #Transform definition
# File lib/cucumber/rb_support/rb_world.rb, line 22 def Transform(arg) rb = @__cucumber_runtime.load_programming_language('rb') rb.execute_transforms([arg]).first end
@deprecated Use {puts} instead.
# File lib/cucumber/rb_support/rb_world.rb, line 94 def announce(*messages) STDERR.puts AnsiEscapes.failed + "WARNING: #announce is deprecated. Use #puts instead:" + caller[0] + AnsiEscapes.reset puts(*messages) end
Pause the tests and ask the operator for input
# File lib/cucumber/rb_support/rb_world.rb, line 111 def ask(question, timeout_seconds=60) @__cucumber_runtime.ask(question, timeout_seconds) end
Create an {Cucumber::Ast::DocString} object
Useful in conjunction with the step method, when want to specify a content type. @example Create a multiline string
code = multiline_string(%{ puts "this is ruby code" %}, 'ruby')
# File lib/cucumber/rb_support/rb_world.rb, line 88 def doc_string(string_without_triple_quotes, content_type='', line_offset=0) # TODO: rename this method to multiline_string @__cucumber_runtime.doc_string(string_without_triple_quotes, content_type, line_offset) end
Embed an image in the output
# File lib/cucumber/rb_support/rb_world.rb, line 116 def embed(file, mime_type, label='Screenshot') @__cucumber_runtime.embed(file, mime_type, label) end
Prints the list of modules that are included in the World
# File lib/cucumber/rb_support/rb_world.rb, line 135 def inspect modules = [self.class] (class << self; self; end).instance_eval do modules += included_modules end sprintf("#<%s:0x%x>", modules.join('+'), self.object_id) end
Mark the matched step as pending.
# File lib/cucumber/rb_support/rb_world.rb, line 121 def pending(message = "TODO") if block_given? begin yield rescue Exception raise Pending.new(message) end raise Pending.new("Expected pending '#{message}' to fail. No Error was raised. No longer pending?") else raise Pending.new(message) end end
Print a message to the output.
@note Cucumber might surprise you with the behaviour of this method. Instead
of sending the output directly to STDOUT, Cucumber will intercept and cache the message until the current step has finished, and then display it. If you'd prefer to see the message immediately, call {Kernel#puts} instead.
# File lib/cucumber/rb_support/rb_world.rb, line 106 def puts(*messages) @__cucumber_runtime.puts(*messages) end
Run a single Gherkin step @example Call another step
step "I am logged in"
@example Call a step with quotes in the name
step %{the user "Dave" is logged in}
@example Passing a table
step "the following users exist:", table(%{ | name | email | | Matt |<EMAIL_ADDRESS>| | Aslak |<EMAIL_ADDRESS>| })
@example Passing a multiline string
step "the email should contain:", "Dear sir,\nYou've won a prize!\n"
@param [String] name The name of the step @param [String,Cucumber::Ast::DocString,Cucumber::Ast::Table] multiline_argument
# File lib/cucumber/rb_support/rb_world.rb, line 51 def step(name, multiline_argument=nil) @__cucumber_runtime.invoke(name, multiline_argument) end
Run a snippet of Gherkin @example
steps %{ Given the user "Susan" exists And I am logged in as "Susan" }
@param [String] steps_text The Gherkin snippet to run
# File lib/cucumber/rb_support/rb_world.rb, line 62 def steps(steps_text) @__cucumber_runtime.invoke_steps(steps_text, @__natural_language, caller[0]) end
Parse Gherkin into a {Cucumber::Ast::Table} object.
Useful in conjunction with the step method. @example Create a table
users = table(%{ | name | email | | Matt |<EMAIL_ADDRESS>| | Aslak |<EMAIL_ADDRESS>| })
@param [String] text_or_table The Gherkin string that represents the table
# File lib/cucumber/rb_support/rb_world.rb, line 76 def table(text_or_table, file=nil, line_offset=0) @__cucumber_runtime.table(text_or_table, file, line_offset) end
see {inspect}
# File lib/cucumber/rb_support/rb_world.rb, line 144 def to_s inspect end


Dear {{ user.username }},
Please find attached the archive of your posts that you requested.
DON'T PANIC
Sincerely,
Streamfish Team


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Created by Julie Zelenski, with edits by Jerry Cain, Keith Schwarz, Marty Stepp, Chris Piech and others.
November 7th, 2016
This assignment focuses on implementing a priority queue ("PQ") collection using several internal data structures, using pointers, arrays, dynamic memory allocation, linked lists, and heaps. The starter code for this project is available as a ZIP archive. A demo is availible as a JAR (see handout on how to run a jar):
Turn in the following files:
ArrayPriorityQueue.h / .cpp
, a PQ implementation using an unsorted array as internal storageLinkedPriorityQueue.h / .cpp
, the C++ code for all of your recursion functions.HeapPriorityQueue.h / .cpp
, the C++ code for all of your recursion functions.This is a pair assignment. You may work in a pair or alone. Find a partner in section or use the course message board. If you work as a pair, comment both members' names atop every code file. Only one of you should submit the program; do not turn in two copies. Submit using the Paperless system linked on the class web site.
A priority queue is a collection that is similar to a queue, except that the elements are enqueued with "priority" ratings. Then when the elements are dequeued later, they always come out in increasing order of priority. That is, regardless of the order in which you add (enqueue) the elements, when you remove (dequeue) them, the one with the lowest priority number comes out first, then the second-smallest, and so on, with the largest priority item coming out last. Priority queues are useful for modeling tasks where some jobs are more important to process than others, like the line of patients at an emergency room (a severely injured patient has higher "priority" than one with a cold).
We will use the convention that a smaller priority number means a greater urgency, such that a priority-1 item would take precedence over a priority-2 item. Because terms like "higher priority" can be confusing, since a "higher" priority means a lower integer value, we will follow the convention in this document of referring to a "more urgent" priority for a smaller integer and a "less urgent" priority for a greater integer.
In this assignment, you will be writing three different implementations of a priority queue class that stores strings. If two strings in the queue have the same priority, you will break ties by considering the one that comes first in alphabetical order to come first. Use C++'s built-in relational operators (<, >, <=, etc.) to compare the strings.
For example, if you enqueue these strings into a priority queue:
Then if you were to dequeue the strings, they would be returned in this order:
You could think of a priority queue as a sorted queue where the elements are sorted by priority, breaking ties by comparing the string elements themselves. But internally the priority queue might not actually store its elements in sorted order; all that matters is that when they are dequeued, they come out in sorted order by priority. An actual priority queue implementation is not required to store its internal data in any particular order, so long as it dequeues its elements in increasing order of priority. As we will see, this difference between the external expected behavior of the priority queue and its true internal state can lead to interesting differences in implementation.
1) ArrayPriorityQueue
: The first priority queue implementation you will write uses an unsorted array as its internal data storage. The only private member variables this class is allowed to have inside it are a pointer to your internal array of elements, and integers for the array's capacity and the priority queue's size. The elements of the array are not stored in sorted order internally. As new elements are enqueued, you should simply add them to the end of the array. When dequeuing, you must then search the array to find the smallest element and remove/return it. This implementation is simple to write and optimized for fast enqueuing but has slow dequeue/peeking and poor overall performance. The following is a diagram of the internal array state of an ArrayPriorityQueue
after enqueuing the elements listed on the previous section:
index 0 1 2 3 4 5 6 7 8 9 +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ value | "x":5 | "b":4 | "a":8 | "m":5 | "q":5 | "t":2 | | | | | +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+
We supply you with a PQEntry
structure that is a small object containing a string value and an integer priority. You should use this structure to store the elements of your priority queue along with their priorities in the array.
Remember to include the big-O of enqueue and dequeue in the comments in ArrayPriorityQueue.h
.
2) LinkedPriorityQueue
: The second priority queue implementation you will write uses a sorted linked list as its internal data storage. This class is only allowed to have a single private member variable inside it: a pointer to the front of your list. The elements of the linked list are stored in sorted order internally. As new elements are enqueued, you should add them at the appropriate place in the linked list so as to maintain the sorted order. When dequeuing, you do not need to search the linked list to find the smallest element and remove/return it; it is always at the front of the list. This implementation is harder to write than the array implementation, and enqueuing to it is slower, but it is much faster for dequeue/peeking and has better overall performance. The following is a diagram of the internal linked list state of a LinkedPriorityQueue after enqueuing the elements listed on the previous section:
The hardest part of this implementation is inserting a new node in the proper place when enqueue is called. You must look for the proper insertion point by finding the first element whose priority is at least as large as the new value to insert, breaking ties by comparing the strings. Remember that, as shown in class, you must often stop one node early so that you can adjust the next pointer of the preceding node. For example, if you were going to insert the value "o" with priority 5 into the list shown above , your code should iterate until you have a pointer to the node containing "m", as shown below:
Once the current pointer shown above points to the right location, you can insert the new node as shown below:
We supply you with a ListNode
structure that is a small object representing a single node of the linked list. Each ListNode stores a string value and integer priority in it, and a pointer to a next node. You should use this structure to store the elements of your priority queue along with their priorities.
Remember to include the big-O of enqueue and dequeue in the comments in LinkedPriorityQueue.h
.
3) HeapPriorityQueue
: The third priority queue implementation you will write uses a special array structure called a binary heap as its internal data storage. The only private member variables this class is allowed to have inside it are a pointer to your internal array of elements, and integers for the array's capacity and the priority queue's size.
As discussed in lecture, a binary heap is an unfilled array that maintains a "heap ordering" property where each index i is thought of as having two "child" indexes, i * 2 and i * 2 + 1, and where the elements must be arranged such that "parent" indexes always store more urgent priorities than their "child" indexes. To simplify the index math, we will leave index 0 blank and start the data at an overall parent "root" or "start" index of 1. One very desirable property of a binary heap is that the most urgent-priority element (the one that should be returned from a call to peek or dequeue) is always at the start of the data in index 1. For example, the six elements listed in the previous pages could be put into a binary heap as follows. Notice that the most urgent element, "t":2, is stored at the root index of 1.
index 0 1 2 3 4 5 6 7 8 9 +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ value | | "t":2 | "m":5 | "b":4 | "x":5 | "q":5 | "a":8 | | | | +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ size = 6 capacity = 10
As discussed in lecture, adding (enqueuing) a new element into a heap involves placing it into the first empty index (7, in this case) and then "bubbling up" or "percolating up" by swapping it with its parent index (i/2) so long as it has a more urgent (lower) priority than its parent. We use integer division, so the parent of index 7 = 7/2 = 3. For example, if we added "y" with priority 3, it would first be placed into index 7, then swapped with "b":4 from index 3 because its priority of 3 is less than b's priority of 4. It would not swap any further because its new parent, "t":2 in index 1, has a lower priority than y. So the final heap array contents after adding "y":3 would be:
index 0 1 2 3 4 5 6 7 8 9 +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ value | | "t":2 | "m":5 | "y":3 | "x":5 | "q":5 | "a":8 | "b":4 | | | +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ size = 7 capacity = 10
Removing (dequeuing) the most urgent element from a heap involves moving the element from the last occupied index (7, in this case) all the way up to the "root" or "start" index of 1, replacing the root that was there before; and then "bubbling down" or "percolating down" by swapping it with its more urgent-priority child index (i*2 or i*2+1) so long as it has a less urgent (higher) priority than its child. For example, if we removed "t":2, we would first swap up the element "b":4 from index 7 to index 1, then bubble it down by swapping it with its more urgent child, "y":3 because the child's priority of 3 is less than b's priority of 4. It would not swap any further because its new only child, "a":8 in index 6, has a higher priority than b. So the final heap array contents after removing "t":2 would be:
index 0 1 2 3 4 5 6 7 8 9 +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ value | | "y":3 | "m":5 | "b":4 | "x":5 | "q":5 | "a":8 | | | | +-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+ size = 6 capacity = 10
A key benefit of using a binary heap to represent a priority queue is efficiency. The common operations of enqueue and dequeue take only O(log N) time to perform, since the "bubbling" jumps by powers of 2 every time. The peek operation takes only O(1) time since the most urgent-priority element's location is always at index 1.
If nodes ever have a tie in priority, break ties by comparing the strings themselves, treating strings that come earlier in the alphabet as being more urgent (e.g. "a" before "b"). Compare strings using the standard relational operators like <,<=,>,>=,==,and!=. Donotmakeassumptionsaboutthelengthsofthestrings.
Changing the priority of an existing value involves looping over the heap to find that value, then once you find it, setting its new priority and "bubbling up" that value from its present location, somewhat like an enqueue operation.
For both array and heap PQs, when the array becomes full and has no more available indexes to store data, you must resize it to a larger array. Your larger array should be a multiple of the old array size, such as double the size. You must not leak memory; free all dynamically allocated arrays created by your class.
Remember to include the big-O of enqueue and dequeue in the comments in HeapPriorityQueue.h
.
Each of your three priority queue implementations must support all of the following operations.
| Member | Description |
|---|---|
pq.enqueue(value, priority);
|
In this function you should add the given string value into your priority queue with the given priority. Duplicates are allowed. Any string is a legal value, and any integer is a legal priority; there are no invalid values that can be passed. |
pq.dequeue()
|
In this function you should remove the element with the most urgent priority from your priority queue, and you should also return it. You should throw a string exception if the queue does not contain any elements. |
pq.peek()
|
In this function you should return the string element with the most urgent priority from your priority queue, without removing it or altering the state of the queue. You should throw a string exception if the queue does not contain any elements. |
pq.peekPriority()
|
In this function you should return the integer priority that is most urgent from your priority queue (the priority associated with the string that would be returned by a call to peek), without removing it or altering the state of the queue. You should throw a string exception if the queue does not contain any elements. |
pq.changePriority(value, newPriority);
|
In this function you will modify the priority of a given existing value in the queue. The intent is to change the value's priority to be more urgent (smaller integer) than its current value. If the given value is present in the queue and already has a more urgent priority to the given new priority, or if the given value is not already in the queue, your function should throw a string exception. If the given value occurs multiple times in the priority queue, you should alter the priority of the first occurrence you find when searching your internal data from the start. |
pq.isEmpty()
|
In this function you should return true if your priority queue does not contain any elements and false if it does contain at least one element. |
pq.size()
|
In this function you should return the number of elements in your priority queue. |
pq.clear();
|
In this function you should remove all elements from the priority queue. |
out << pq
|
You should write a << operator for printing your priority queue to the console. The elements can print out in any order and must be in the form of "value":priority with {} braces, suchas {"t":2 , "b":4, "m":5, "q":5, "x":5, "a":8}. The PQEntry and ListNode structures both have >>operators that may be useful. Your formatting and spacing should match exactly. Do not place a \n or endl at the end. |
The headers of every operation must match those specified above. Do not change the parameters or function names.
Constructor/destructor: Each class must also define a parameterless constructor. If the implementation allocates any dynamic memory, you must ensure that there are no memory leaks by freeing any allocated memory at the appropriate time. This will mean that you will need a destructor for classes that dynamically allocate memory.
Helper functions: The members listed on the previous page represent a large fraction of each class's behavior. But you should add other members to help you implement all of the appropriate behavior. Any other member functions you provide must be private. Remember that each member function of your class should have a clear, coherent purpose. You should provide private helper members for common repeated operations. Make a member function and/or parameter const if it does not perform modification of the object's state.
Member variables: We have already specified what member variables you should have. Here are some other constraints:
Here are a few other constraints we expect you to follow that don't fit neatly into any other section.
Thats all! You are done. Consider adding extra features.


- calculateLikelihood(double, double) - Method in class com.mygdx.game.AiPlayer
-
Calculates a value for the likelihood of the AI accepting a trade.
- calculateNewCost(int, String) - Method in class com.mygdx.game.Market
-
A method that calculates cost of market selling and buying prices.
- calculateOpacity() - Method in class io.github.teamfractal.animation.AnimationTileFlash
-
Calculate opacity for rectangle.
- calculateScore() - Method in class com.mygdx.game.Player
-
Calculates the score of the player based on the resources that they own.
- callAnimationFinish() - Method in class io.github.teamfractal.animation.AnimationPlayerWin
-
- callAnimationFinish() - Method in class io.github.teamfractal.animation.AnimationTileFlash
-
- callAnimationFinish() - Method in interface io.github.teamfractal.animation.IAnimation
-
- callback - Variable in class io.github.teamfractal.animation.AnimationPlayerWin
-
- callback - Variable in class io.github.teamfractal.animation.AnimationTileFlash
-
- cancelAnimation() - Method in class io.github.teamfractal.animation.AnimationPlayerWin
-
- cancelAnimation() - Method in class io.github.teamfractal.animation.AnimationTileFlash
-
- cancelAnimation() - Method in interface io.github.teamfractal.animation.IAnimation
-
- cancelTradeButton - Variable in class com.mygdx.game.GameScreen
-
- cardTexture - Static variable in class com.mygdx.game.MiniGameScreen
-
- cardTextureAddMoney - Static variable in class com.mygdx.game.MiniGameScreen
-
- cardTextureAddRoboticon - Static variable in class com.mygdx.game.MiniGameScreen
-
- cardTextureNothing - Static variable in class com.mygdx.game.MiniGameScreen
-
- Chancellor - Class in com.mygdx.game
-
This class is the Chancellor mini game.
- Chancellor(GameEngine) - Constructor for class com.mygdx.game.Chancellor
-
The method that creates the object chancellor
- chancellor() - Method in class com.mygdx.game.GameEngine
-
- chancellor(Tile) - Method in class com.mygdx.game.GameScreen
-
Draws the chancellor is it is set to visible
- chancellorGame - Variable in class com.mygdx.game.GameEngine
-
- chancellorIsVisible() - Method in class com.mygdx.game.Tile
-
- chancellorTexture - Variable in class com.mygdx.game.GameScreen
-
Image of the chancellor
- chancellorTextureVisible - Variable in class com.mygdx.game.Tile
-
- changeEnergyCount(int) - Method in class com.mygdx.game.Tile
-
Setter for the ore count of the tile.
- changeFoodCount(int) - Method in class com.mygdx.game.Tile
-
- changeOreCount(int) - Method in class com.mygdx.game.Tile
-
Setter for the ore count of the tile.
- changeTile() - Method in class com.mygdx.game.Chancellor
-
Method to choose a random tile from the 16 available
- checkEventDurations() - Method in class com.mygdx.game.GameEngine
-
- checkGameEnd() - Method in class com.mygdx.game.GameEngine
-
Returns a value that's true if all tiles have been claimed, and false otherwise
- chooseAffectedTiles() - Method in class com.mygdx.game.Earthquake
-
A method which chooses the tiles to be damaged by the earthquake.
- claimTile() - Method in class com.mygdx.game.GameEngine
-
Claims the last tile to have been selected on the main GameScreen for the active player
This grants them the ability to plant a Roboticon on it and yield resources from it for themselves
Specifically registers the selected tile under the object holding the active player's data, re-colours its
border for owner identification purposes and moves the game on to the next player/phase
- claimTileButton - Variable in class com.mygdx.game.GameScreen
-
Button which allows players to claim selected tiles
- clicked - Variable in class com.mygdx.game.MiniGameScreen
-
- closeEventMessageButton - Variable in class com.mygdx.game.GameScreen
-
- closePriceOverlayButton - Variable in class com.mygdx.game.GameScreen
-
- closeTooExpensiveOverlay() - Method in class com.mygdx.game.GameScreen
-
- closeTrade() - Method in class com.mygdx.game.GameEngine
-
- closeTradeOverlay() - Method in class com.mygdx.game.GameScreen
-
- closeUpgradeOverlay() - Method in class com.mygdx.game.GameScreen
-
Closes the upgrade overlay and restores the functionality of the game's main stage
- closeUpgradeOverlayButton - Variable in class com.mygdx.game.GameScreen
-
Button allowing players to escape from the upgrade overlay if they decide against upgrading roboticons
- College - Class in com.mygdx.game
-
- College(String) - Constructor for class com.mygdx.game.College
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The constructor for the College class
This will assign a name and a logo to the College based on the ID provided
- College - Variable in class com.mygdx.game.Player
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The college that the player is playing as.
- color - Variable in class com.mygdx.game.College
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The color of the College
- com.mygdx.game - package com.mygdx.game
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- confirmButton - Variable in class com.mygdx.game.PlayerSelectScreen
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button to confirm number of players
- confirmSale - Variable in class com.mygdx.game.Market
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button to confirm a trade
- confirmTradeButton - Variable in class com.mygdx.game.GameScreen
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- constructAuctionInterface() - Method in class com.mygdx.game.Market
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Builds the auction's visual interface by populating it with labels and buttons
Once this method has finished executing, the market can be drawn to a stage like any other actor
- constructButtons() - Method in class com.mygdx.game.GameScreen
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Sets up the buttons to be placed onto the interface later by defining their visual representations and their
on-click functions together
- constructButtons() - Method in class com.mygdx.game.Market
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Instantiates the purchase/sale buttons to be placed in the market and sets their on-click functions
Obviously, these buttons enable players to buy and sell resources during certain game-phases
- constructEventMessageOverlay() - Method in class com.mygdx.game.GameScreen
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- constructInterface() - Method in class com.mygdx.game.Market
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Builds the market's visual interface by populating it with labels and buttons
Once this method has finished executing, the market can be drawn to a stage like any other actor
- constructLeftTable() - Method in class com.mygdx.game.GameScreen
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Set up the form and contents of the left-hand table so that they can be rendered later
Specifically defines the left-hand panel's spatial framework (in the form of a table) before populating it with
the game's timer, a phase label, a button for ending turns, the logo of the current player's associated college
and counters visualising the numbers of ore, energy, food and Roboticon stocks (and the money) that the
current player holds
- constructPauseMenu() - Method in class com.mygdx.game.GameScreen
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Set up the pause menu to allow for the game to be successfully paused
- constructRightTable() - Method in class com.mygdx.game.GameScreen
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Set up the form and contents of the right-hand table so that they can be rendered later
Specifically defines the right-hand panel's spatial framework (in the form of a table) before populating it with
the selected tile's name-label and college/roboticon icons, along with buttons to claim and deploy/upgrade
Roboticons on the selected tile and the whole interface for the game's market
- constructTileGrid() - Method in class com.mygdx.game.GameScreen
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Set up the game-screen's central tile-grid so that it can be interacted with
The tiles on this grid take the form of invisible buttons that are directly laid over the map image at the
centre of this screen
- constructTooExpensiveOverlay() - Method in class com.mygdx.game.GameScreen
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- constructTradeOverlay(Trade) - Method in class com.mygdx.game.GameScreen
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- constructUpgradeOverlay() - Method in class com.mygdx.game.GameScreen
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Set up an overlay which shows up when the current player opts to upgrade their roboticon
This will allow them to upgrade its food, energy or ore production stats
- create() - Method in class com.mygdx.game.Main
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Automatically set the game-state to load the splash-screen as soon as the game window opens
- currentPhase - Variable in class io.github.teamfractal.animation.AnimationTileFlash
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- currentPlayer() - Method in class com.mygdx.game.GameEngine
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Returns the data pertaining to the player who is active at the time when this is called
- currentPlayerIcon - Variable in class com.mygdx.game.GameScreen
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Icon representing the currently-active player's chosen college
- currentPlayerIcon() - Method in class com.mygdx.game.GameScreen
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Returns the icon object used to visualise the logo of the current player's associated college
The GameEngine class uses this method to update said logo when it changes the active player
- currentPlayerID - Variable in class com.mygdx.game.GameEngine
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Holds the numeric getID of the player who's currently active in the game
- currentPlayerID() - Method in class com.mygdx.game.GameEngine
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Returns the ID of the player who is active at the time when this is called
- currentPlayerLabel - Variable in class com.mygdx.game.GameScreen
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- currentPlayerMainLabel - Variable in class com.mygdx.game.GameScreen
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- currentTile - Variable in class com.mygdx.game.Chancellor
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- CurrentTile - Variable in class com.mygdx.game.Roboticon
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Variable holding what tile the roboticon is stored on.
- currentTimeOnTile - Variable in class com.mygdx.game.Chancellor
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- currentTrade - Variable in class com.mygdx.game.GameScreen
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- currentTrade - Variable in class com.mygdx.game.Player
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