Jewish_Art_Will_Deutsch_Judaism_Jews_Scribe_Sofer_Torah.jpg
My preschool teacher was concerned that I had developmental disabilities.
So concerned in fact that she called my Mother into the school to discuss it.
My Mother thanked her and asked what behavior I was displaying that would denote any sort of issue.
At this point my teacher filled up a pitcher with water, gave me a cup and asked me to pour.
I spilled the contents everywhere.
‘Use your left hand William’ my Mother said.
Problem solved.
It hasn’t been easy growing up as a southpaw in a right handed world.
The worst was learning to cut paper.
Thats when they really separate the righties from the lefties.
While everybody else got beautifully pointed, stainless steel blades with bright red handles I was forced to make do with the rounded off, puke green shears left rusting in an old Yuban coffee can branded with a giant ‘L’.
Naturally, this was par for the course.
Right handed desks.
Right handed baseball mitts.
Right handed guitars and can openers.
Even the cords on credit card machines are on the right hand side so you have to stretch them awkwardly at an angle just to sign with your left hand.
I’m reminded that about 90 percent of the world is right handed every time I go to shake somebody’s hand.
But by and far the bane of my existence has been the fact that I cannot write more than a sentence without completely smudging the writing and discoloring the side of my palm as I drag it across the paper from left to right.
And to top it off studies show that my lifespan is almost a decade shorter than the rest of you.
On the other hand (pun so very much intended) if I were a more pious man, its for this very reason that I’d probably make an excellent sofer.


/* Copyright (c) 2009... All rights reserved. */
/* Copyright (c) 2009... All rights reserved. */
/* Copyright (c) 2009... All rights reserved. */
/* Copyright (c) 2009... All rights reserved. */


--- layout: page header-img: img/img1.png header-credit: Jeff Lichtman/Harvard University ---
FISSEQ · MERFISH · Seq-FISH · ExM · IHC · brDNA · MIPs · Oligopaints · DNA Paint · smFISH · HCR · Padlock Probes · Microscopy
We will not sell your email or use it for any purpose other than for precipiate.bio launch notifications!


Namespace McMaster.Extensions.CommandLineUtils.Conventions
Classes
AppNameFromEntryAssemblyConvention
Sets Name using the name of the entry assembly to the current application. It is only applied if the name is null.
ArgumentAttributeConvention
Adds a CommandArgument for each ArgumentAttribute on the model type for CommandLineApplication<TModel>.
CommandAttributeConvention
Adds settings from CommandAttribute set on the model type for CommandLineApplication<TModel>.
ConstructorInjectionConvention
Uses an instance of System.IServiceProvider to call constructors when creating models.
ConventionContext
The context in which a convention is applied.
ExecuteMethodConvention
Sets Invoke to call a method named
OnExecute
or OnExecuteAsync
on the model type
of CommandLineApplication<TModel>.
HelpOptionAttributeConvention
Sets OptionHelp based on the usage of HelpOptionAttribute.
OptionAttributeConvention
Adds an CommandOption to match each usage of OptionAttribute on the model type of CommandLineApplication<TModel>.
OptionAttributeConventionBase<TAttribute>
Shared implementation for adding conventions based on OptionAttributeBase.
ParentPropertyConvention
Sets a property named Parent
on the model type to the value
of the model of the parent command.
RemainingArgsPropertyConvention
Sets a property named RemainingArguments
or RemainingArgs
on the model type on CommandLineApplication<TModel>
to the value of RemainingArguments.
SubcommandAttributeConvention
Creates a subcommand for each SubcommandAttribute on the model type of CommandLineApplication<TModel>.
SubcommandPropertyConvention
Sets a property named Subcommand
to the value of the selected subcommand
model type of CommandLineApplication<TModel>.
ValidationErrorMethodConvention
Invokes a method named OnValidationError
on the model type of CommandLineApplication<TModel>
to handle validation errors.
VersionOptionAttributeConvention
Sets OptionVersion using settings from VersionOptionAttribute on the model type of CommandLineApplication<TModel>.
VersionOptionFromMemberAttributeConvention
Sets OptionVersion using settings from VersionOptionFromMemberAttribute on the model type of CommandLineApplication<TModel>.
Interfaces
IConvention
Defines a convention for an instance of CommandLineApplication<TModel>.
IConventionBuilder
Builds a collection of conventions.


{# jQuery #} {# Bootstrap Core CSS and JavaScript #} {# LeafletJS Core CSS and JavaScript #} {# Custom CSS #} {# Custom JavaScript #} {# Page Title #}
Mailgun is a set of powerful APIs that allows sending, receiving and tracking email effortlessly. Try it out! Read more
Mailgun, as any other API, provides a range of methods with different functionality, such as allowing to send emails to one vs. multiple email addresses. Read more
Simulating a login/signup or even subscribing to an email list is as easy as opening a new page. Flask, a Python web framework, makes this easy through routing. Read more
Tweepy integrates Twitter within websites. It can provide trending topic information in relation to a specific hashtag. Read more
The OpenWeather API provides weather data, including historical and current data, as well as forecasts. The API documentation details the functionality and usage of the different features. Read more
FoursquareAPI helps you find the perfect places for food and entertainment in your area and see information about specific venues. Read more
Uber for developers allows integrating Uber services in the code. One example would be getting the type of available services based on a location's latitude and longitude. Read more
LeafletJS is a user-friendly and interactive mapping platform for developers that allows displaying maps and building applications using JavaScript. Read more
AfterShip is a shipment tracking application and API that allows, among others, viewing delivery status by entering a tracking number. Read more


Base of all operators implementation considering the definitions of AStrAL. As a reminder, the operator definitions can
be found here.
This package gives the minimum framework to write quickly any type of operators. With the abstract classes like
{@link fr.lig.sigma.astral.operators.RelationOperator} or {@link fr.lig.sigma.astral.operators.StreamOperator},
implementing an operator can be nearly reduced to it's core algorithm.
Common rules to define an operator
Each operator, are classes that implements the interface {@link fr.lig.sigma.astral.operators.Operator} as well as their
right output entity type. An interface must be defined for that, like {@link fr.lig.sigma.astral.operators.pi.Pi} for
example with an unique function that will initialize the operator with its input and parameters.
The implementation must follow very simple rules to define a good operators.
- Extends on of the two abstract operators that extends {@link fr.lig.sigma.astral.common.structure.EntityContainer}
- Do a setOutput as soon as enough details about the attributes and names are gathered
- Then only, do a addInput to indicate to the scheduler the dependencies of the operator, and if it is the case,
to be registered as an input listener.
- Implement your algorithm inside the processEvent of {@link fr.lig.sigma.astral.common.event.EventProcessor}
If your operator is a composite and needs to create other operators, just extends the interface with
{@link fr.lig.sigma.astral.operators.OperatorFactory}. The core will detect it at the instanciation and will attach the
right one to this component.


complex-priors.Rmd
This vignette demonstrates the use of more complex priors, which can add realism to the model but also tend to slow down the MCMC. It covers:
This vignette follows on from the previous tutorial - or you can pick up here by running these lines of code:
# load output of previous tutorial
mysim <- malecot_file("tutorial1_mysim.rds")
myproj <- malecot_file("tutorial1_myproj.rds")
In the previous tutorial we assumed a uniform prior on COI. This tends to be too permissive for real data as it gives considerable weight to high COIs and can therefore lead to over-estimation. There are two alternative priors implemented in MALECOT - the Poisson distribution and the negative binomial distribution.
The Poisson distribution assumes that COIs are clustered around a mean value. It is what we would expect if all individuals in the population were becoming infected and clearing infections at the same constant rate. The negative binomial distribution can be thought of as an over-dispersed form of Poisson distribution, i.e. it allows for a greater spread of values around the mean. It more closely reflects a situation where there is heterogeneity in exposure, meaning some individuals tend to be heavily infected while some are only lightly infected. We can use the parameter COI_dispersion
to set the level of over-dispersion - for example, a value of 2 means the prior variance will be twice as large as the prior mean. Note that whatever prior we choose, COIs will still be truncated at COI_max
.
We can explore different shapes of prior using the plot_prior_COI()
function:
plot_prior_COI(COI_model = "uniform")
plot_prior_COI(COI_model = "poisson", COI_mean = 3)
plot_prior_COI(COI_model = "nb", COI_mean = 3, COI_dispersion = 2)
The simulated data in the previous tutorial were generated from a Poisson distribution, and so we could use this prior to exactly match the inference model to the simulated data. However, in reality we will not have the luxury of knowing the true COI distribution, and so for this example we will use a negative binomial prior. Rather than using a set value for the prior mean we will use the argument estimate_COI_mean = TRUE
to tell the model that we want to estimate the mean COI for each subpopulation.
In some cases we may want to specify the COI of certain samples manually - for example if we have already used other programs to estimate the COI and we want to insert these values. This can be accommodated using the COI_manual
argument, which takes a vector of length equal to the number of samples. Values of -1 indicate that the COI should be estimated, while positive values indicate that the COI should be fixed at that value. In this example we will assume that we know the true COIs of the last 10 samples.
# define some COIs manually
known_COI <- rep(-1,100)
known_COI[91:100] <- mysim$true_m[91:100]
# create new parameter set
myproj <- new_set(myproj, name = "nb model", COI_model = "nb", COI_max = 20,
COI_manual = known_COI, estimate_COI_mean = TRUE, COI_dispersion = 2)
myproj
## DATA:
## data format = biallelic
## samples = 100
## loci = 24
## pops = 3
## missing data = 0 of 2400 gene copies (0%)
##
## PARAMETER SETS:
## SET1: uniform model
## * SET2: nb model
##
## ACTIVE SET: SET2
## lambda = 1
## COI model = nb
## COI max = 20
## COI specified manually for 10 samples
## estimate COI mean = TRUE
## COI dispersion = 2
## estimate error = FALSE
## e1 = 0
## e2 = 0
We will keep things simple here by only running the MCMC for \(K = 3\):
# run MCMC
myproj <- run_mcmc(myproj, K = 3, burnin = 1e4, converge_test = 1e2,
samples = 1e4, pb_markdown = TRUE)
## Running MCMC for K = 3
## Burn-in phase
##
|
|=================================================================| 100%
## converged within 200 iterations
## Sampling phase
##
|
|=================================================================| 100%
## completed in 3.32222 seconds
##
## Processing results
## Total run-time: 3.86 seconds
As before, we need to check that we are happy with the behaviour of our MCMC by looking at trace plots and other diagnostics. Assuming everything looks OK, we can go ahead and produce the posterior allocation and and posterior COI plots:
# structure plot
plot_structure(myproj, K = 3, divide_ind_on = TRUE)
# load ggplot2 package
library(ggplot2)
# produce plot of posterior COIs
posterior_COI <- plot_COI(myproj, K = 3)
# overlay true COI values
posterior_COI <- posterior_COI + geom_point(aes(x = 1:100, y = mysim$true_m), col = "red", shape = 4)
posterior_COI
Notice that the 95% credible intervals in the COI plot are tighter than the equivalent plot of the previous tutorial. This is because our prior now assumes that COIs are clustered around a mean value. Notice also that the final ten samples have their COI fixed at the correct value due to our use of the COI_manual
argument.
Next we can look at the estimated mean COI for each of the subpopulations:
plot_COI_mean(myproj, K = 3)
Recall that the data were simulated from three subpopulations with true mean COIs of 1.2, 2, and 3 respectively. The model appears to have estimated the correct values, but in the wrong order. The seemingly incorrect order of these estimates goes back to the issue of labelling subpopulations mentioned in the previous tutorial. When lined up against the three groups in the structure plot above (which go group3 then group2 then group1) we can see that mean COI estimates do in fact go from lowest on the left to highest on the right. We can also specify the deme order in this plot using the deme_order
argument:
plot_COI_mean(myproj, K = 3, deme_order = c(3,2,1))
The distribution of allele frequencies can be an important factor in determining how much signal there is in the data. If allele frequencies have a narrow range then even subpopulations that are evolutionarily well separated might look similar, and so it becomes difficult to detect population structure. Similarly, if our model expects subpopulations to have very different allele frequencies then it might ignore more subtle differences, tending instead to lump subpopulations together.
MALECOT assumes a beta prior on allele frequencies with shape parameter lambda
. We have three options when specifying lambda
:
lambda
can be a single value. In this case the same shape parameter is used for all alleles and all loci, making the prior symmetric and identical over all loci.
lambda
can be a vector of shape parameters - one for each allele. In this case the prior will usually be asymmetric and skewed in favour of one allele. The same prior is still applied over all loci, meaning this option can only be used if there are the same number of alleles at every locus (this is always true for bi-allelic data).
lambda
can be a list with as many elements as there are loci, and each element consisting of a vector with as many elements as there are alleles at that locus. This makes it possible to specify a different prior at every locus.
By default, lambda
is defined using the first method with a value of 1. This places equal weight on every allele frequency in the interval \([0,1]\) at every locus, i.e. the Beta distribution simplifies to the uniform distribution. We can visualise different priors using the plot_prior_p()
function:
# (the default prior)
plot_prior_p(lambda = 1)
plot_prior_p(lambda = 0.5)
plot_prior_p(lambda = c(7,1))
We will use the last of these distributions, which makes it more likely a priori that the reference allele will be common and the alternative allele will be rare. We can simulate some new data under this prior and load it into a new project:
# simulate new data with skewed allele frequency distribution
mysim_skew <- sim_data(n = 100, L = 24, K = 3, lambda = c(7,1))
# bind data to new project
myproj_skew <- malecot_project()
myproj_skew <- bind_data_biallelic(myproj_skew, df = mysim_skew$data, ID_col = 1, pop_col = 2)
Next we need a parameter set. When defining the prior on allele frequencies we will use the same skewed distribution that we used when generating the data. We then run the MCMC as normal:
# define parameter set with skewed prior
myproj_skew <- new_set(myproj_skew, name = "skew allele freqs", COI_model = "poisson",
COI_max = 20, estimate_COI_mean = TRUE, lambda = c(7,1))
# run the MCMC
myproj_skew <- run_mcmc(myproj_skew, K = 3, burnin = 1e4, converge_test = 1e2,
samples = 1e4, pb_markdown = TRUE)
## Running MCMC for K = 3
## Burn-in phase
##
|
|=================================================================| 100%
## converged within 100 iterations
## Sampling phase
##
|
|=================================================================| 100%
## completed in 2.19839 seconds
##
## Processing results
## Total run-time: 2.54 seconds
After checking that our MCMC has behaved as expected, we can look at the posterior allocation plot:
# structure plot
plot_structure(myproj_skew, K = 3, divide_ind_on = TRUE)
We can see that the model has struggled slightly to pull apart the population structure. This is due to there being less information in 24 loci with skewed allele frequencies than in 24 loci with evenly spread allele frequencies.
Plotting credible intervals of posterior allele frequencies and overlaying the true simulated values, as demonstrated in the previous tutorial, we see that the model has done a good job of estimating the allele frequencies:
# get group order
group_order_k3 <- get_group_order(myproj_skew, K = 3, target_group = mysim_skew$true_group)
# loop through subpopulations
for (i in 1:3) {
# produce plot of posterior allele frequencies for this subpopulation
posterior_p <- plot_p(myproj_skew, K = 3, deme = i)
# get true simulated allele frequencies for this subpopulation
sim_p <- mapply(function(x){x[group_order_k3[i],1]}, mysim_skew$true_p)
# overlay true allele frequencies onto plot
posterior_p <- posterior_p + geom_point(aes(x = 1:24, y = sim_p), col = "red", shape = 4)
print(posterior_p)
}
If we had used a uniform prior then the posterior allele frequencies would have been slightly biased towards the middle, although the overall inferred population structure would probably have been similar.
Real data is rarely without errors. Often true homozygotes will be miscalled as heterozygotes (error 1), and true heterozygotes will be miscalled as homozygotes (error 2). The probabilities of these two types of error can be specified in MALECOT using the arguments e1
and e2
. We can either use fixed values, or these error probabilities can be estimated by setting estimate_error = TRUE
, in which case a uniform prior is assumed ranging from 0 to e1_max
for e1
, and 0 to e2_max
for e2
.
Let us simulate some new data containing errors to test the model in a more challenging setting. We will assume that artificial heterozygotes occur with probability 0.1, and artificial homozygotes with probability 0.05. We will also assume that 20% of the data is missing, and hence encoded as -9
.
# simulate data
mysim_errors <- sim_data(n = 100, L = 24, K = 3, e1 = 0.1, e2 = 0.05, prop_missing = 0.2)
head(mysim_errors$data)
## sample_ID pop locus1 locus2 locus3 locus4 locus5 locus6 locus7 locus8
## 1 samp001 1 1.0 1.0 1.0 1.0 0.5 0.5 0.0 0.5
## 2 samp002 1 1.0 1.0 1.0 0.5 0.5 0.5 0.5 0.0
## 3 samp003 1 0.5 1.0 0.5 1.0 -9.0 0.0 1.0 1.0
## 4 samp004 1 0.5 0.5 1.0 0.5 0.5 1.0 -9.0 0.5
## 5 samp005 1 1.0 0.5 -9.0 0.5 -9.0 1.0 0.5 0.0
## 6 samp006 1 1.0 0.5 1.0 0.5 0.5 0.5 0.5 -9.0
## locus9 locus10 locus11 locus12 locus13 locus14 locus15 locus16 locus17
## 1 0.5 1.0 0.0 0.5 1.0 0.0 -9 0.5 0.0
## 2 0.0 -9.0 -9.0 0.0 1.0 0.5 1 0.0 -9.0
## 3 0.0 0.5 -9.0 1.0 -9.0 0.0 1 0.0 0.0
## 4 0.5 0.5 0.5 0.5 0.5 0.5 1 -9.0 -9.0
## 5 0.5 1.0 0.5 0.5 0.5 -9.0 1 0.5 0.5
## 6 0.5 1.0 -9.0 -9.0 1.0 0.0 1 -9.0 0.0
## locus18 locus19 locus20 locus21 locus22 locus23 locus24
## 1 0.0 0.5 1.0 0 1.0 0.5 1.0
## 2 -9.0 -9.0 1.0 0 1.0 1.0 0.0
## 3 1.0 1.0 0.5 -9 1.0 1.0 0.0
## 4 0.5 0.5 0.5 0 -9.0 0.5 -9.0
## 5 0.0 0.0 0.5 -9 0.5 0.0 0.5
## 6 0.5 0.5 -9.0 0 0.5 -9.0 0.5
Next we will create a new project and bind the new data:
# bind data to new project
myproj_errors <- malecot_project()
myproj_errors <- bind_data_biallelic(myproj_errors, mysim_errors$data, ID_col = 1, pop_col = 2)
myproj_errors
## DATA:
## data format = biallelic
## samples = 100
## loci = 24
## pops = 3
## missing data = 480 of 2400 gene copies (20%)
##
## PARAMETER SETS:
## (none defined)
Looking at this output we can see that the project has correctly registered 20% of the data as missing.
For the model, we will assume a maximum value of 0.2 for both e1
and e2
. It is recommended to use sensible values for e1_max
and e2_max
, for example values of 1.0
are usually inappropriate as we (hopefully) do not expect all of our data to be mistakes! We then run the MCMC as usual:
# create new parameter set
myproj_errors <- new_set(myproj_errors, name = "error model", COI_model = "poisson",
COI_max = 20, estimate_COI_mean = TRUE,
estimate_error = TRUE, e1_max = 0.2, e2_max = 0.2)
# run the MCMC
myproj_errors <- run_mcmc(myproj_errors, K = 3, burnin = 1e4, converge_test = 1e2,
samples = 1e4, pb_markdown = TRUE)
## Running MCMC for K = 3
## Burn-in phase
##
|
|=================================================================| 100%
## converged within 200 iterations
## Sampling phase
##
|
|=================================================================| 100%
## completed in 3.48164 seconds
##
## Processing results
## Total run-time: 3.82 seconds
After checking the behaviour of our MCMC we can plot the posterior 95% credible intervals of e1
and e2
:
plot_e(myproj_errors)
## using K = 3 by default
In this example the model has been able to correctly infer the error rates of around 0.1 and 0.05 from the data. To help get an intuition as to how the model is able to do this, imagine a situation where every locus in a given sample is homozygous apart from one which is heterozygous. There are two possibilities here: 1) the heterozygous locus is due to that sample having COI of 2 and being homozygous everywhere else by chance, 2) the heterozygous call is an error and the sample actually has COI of 1. The probability of being homozygous at every other locus by chance may be very small if the allele frequencies are intermediate, in which case the weight of evidence is in favour of this one heterozygous call being an error. The MCMC considers all possibilities in proportion to their likelihood, and weighted by our prior beliefs, to arrive at the posterior distributions above.
The next tutorial explores how the analysis pipeline differs when using multi-allelic data.


---
layout: post
date: 2008-04-02
time: "09:00:00"
authors: ["Greg Wilson"]
title: Summer Plans for Software Carpentry
tags: ["Content"]
---
The Software Carpentry site is still getting a lot of traffic, despite my neglect:
This summer, I'd like to:
- Convert the site from static HTML pages to a wiki to make it easier for people to contribute content and fix bugs.
- Translate the examples into MATLAB to make them accessible to a larger audience. (Yes, Python is still my favorite language, and yes, the Python versions will remain—I just want it to be possible for the average mechanical engineer to follow the discussion of testing without first having to learn a new programming language).
- Add some of the material that I developed for CSC301: Introduction to Software Engineering, and some of what Titus Brown wrote for Intermediate and Advanced Software Carpentry.
The odds of all three happening are close to zero: my grad students are going to be in the middle of real research, we're hoping to have half a dozen or ten undergraduate interns as well, we have a "CS-1 in Python" book to finish for Pragmatic, and oh yeah, I'm getting married twice. If you want to help out, now would be a good time to raise your hand... :-)


29 May 2009 - As of 06:00 GMT, 29 May 2009, 53 countries have officially reported 15,510 cases of influenza A(H1N1) infection, including 99 deaths.
The breakdown of the number of laboratory-confirmed cases by country is given in the following table.
| Country | Cumulative total | Newly confirmed since the last reporting period | ||
| Cases | Deaths | Cases | Deaths | |
| Argentina | 37 | 0 | 18 | 0 |
| Australia | 147 | 0 | 108 | 0 |
| Austria | 1 | 0 | 0 | 0 |
| Bahrain | 1 | 0 | 0 | 0 |
| Belgium | 8 | 0 | 1 | 0 |
| Brazil | 10 | 0 | 1 | 0 |
| Canada | 1118 | 2 | 197 | 1 |
| Chile | 165 | 0 | 79 | 0 |
| China | 30 | 0 | 8 | 0 |
| Colombia | 17 | 0 | 1 | 0 |
| Costa Rica | 33 | 1 | 0 | 0 |
| Cuba | 4 | 0 | 0 | 0 |
| Czech Republic | 1 | 0 | 1 | 0 |
| Denmark | 1 | 0 | 0 | 0 |
| Dominican Republic | 2 | 0 | 2 | 0 |
| Ecuador | 32 | 0 | 4 | 0 |
| El Salvador | 11 | 0 | 0 | 0 |
| Finland | 3 | 0 | 1 | 0 |
| France | 21 | 0 | 5 | 0 |
| Germany | 19 | 0 | 2 | 0 |
| Greece | 3 | 0 | 2 | 0 |
| Guatemala | 5 | 0 | 0 | 0 |
| Honduras | 1 | 0 | 0 | 0 |
| Iceland | 1 | 0 | 0 | 0 |
| India | 1 | 0 | 0 | 0 |
| Ireland | 3 | 0 | 2 | 0 |
| Israel | 11 | 0 | 2 | 0 |
| Italy | 26 | 0 | 3 | 0 |
| Japan | 364 | 0 | 4 | 0 |
| Korea, Republic of | 33 | 0 | 12 | 0 |
| Kuwait | 18 | 0 | 0 | 0 |
| Malaysia | 2 | 0 | 0 | 0 |
| Mexico | 4910 | 85 | 369 | 2 |
| Netherlands | 3 | 0 | 0 | 0 |
| New Zealand | 9 | 0 | 0 | 0 |
| Norway | 4 | 0 | 0 | 0 |
| Panama | 107 | 0 | 31 | 0 |
| Peru | 31 | 0 | 4 | 0 |
| Philippines | 6 | 0 | 4 | 0 |
| Poland | 4 | 0 | 1 | 0 |
| Portugal | 1 | 0 | 0 | 0 |
| Romania | 3 | 0 | 3 | 0 |
| Russia | 2 | 0 | 0 | 0 |
| Singapore | 4 | 0 | 3 | 0 |
| Slovakia | 1 | 0 | 1 | 0 |
| Spain | 143 | 0 | 5 | 0 |
| Sweden | 4 | 0 | 1 | 0 |
| Switzerland | 4 | 0 | 1 | 0 |
| Thailand | 2 | 0 | 0 | 0 |
| Turkey | 2 | 0 | 0 | 0 |
| United Kingdom | 203 | 0 | 66 | 0 |
| United States of America | 7927 | 11 | 1163 | 1 |
| Uruguay | 2 | 0 | 2 | 0 |
| Grand Total | 15510 | 99 | 2112 | 4 |


25 May 2001
Disease Outbreak Reported
The Bangladesh Ministry of Health has reported 28 cases in adult males, including 9 deaths betwen 26 April and 12 May in the Meherpur district, in the western part of the country near the border with India. Symptoms include progressive fever, malaise, headache, coma and death.
A team from the Bangladesh Ministry of Health has investigated the outbreak and collected samples from survivors and contacts. WHO and its partners are providing technical experts to assist the Ministry of Health in evaluating the information from the investigation and to carry out further investigations as needed.


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Gets a single code scanning alert. You must use an access token with the
security_events
scope to use this endpoint. GitHub Apps must have
the security_events
read permission to use this endpoint.
The security alert_id
is found at the end of the security
alert's URL. For example, the security alert ID for
https://github.com/Octo-org/octo-repo/security/code-scanning/88
is 88
.
GET /repos/:owner/:repo/code-scanning/alerts/:alert_id
Status: 200 OK
{
"rule_id": "js/useless-expression",
"rule_severity": "warning",
"rule_description": "Expression has no effect",
"tool": "CodeQL",
"created_at": "2020-05-06T12:00:00Z",
"open": true,
"closed_by": null,
"closed_at": null,
"url": "https://api.github.com/repos/Octo-org/octo-repo/code-scanning/alerts/88",
"html_url": "https://github.com/Octo-org/octo-repo/security/code-scanning/88"
}


You have 0 antimatter.
|
|
| 1 Eternity: | 2 Eternities: |
| 3 Eternities: | 4 Eternities: |
| 5 Eternities: | 7 Eternities: |
| 9 Eternities: | 10 Eternities: |
| 11 Eternities: | 12 Eternities: |
| 13 Eternities: | 14 Eternities: |
| 15 Eternities: | 16 Eternities: |
| 17 Eternities: | 18 Eternities: |
| 20 Eternities: | 25 Eternities: |
| 30 Eternities: | 40 Eternities: |
| 50 Eternities: | 60 Eternities: |
| 80 Eternities: | 100 Eternities: |
You have 0 tachyon particles.
You have 0 ex-dilation,
You have 0 dilated time 0
Next at 1000 dilated time, gained total of 0
|
|
You have 0 black hole power, translated to 0x multiplier on Dilated Time gain, and 0x multiplier on banked Infinity gain and Replicanti speed.
| Dimension Shift: requires 20 Fourth Dimension | |
| Tickspeed Boost (0): requires 10 Fifth Dimensions | |
| Antimatter Galaxies: requires 80 Eight Dimension | |
| The Singularity: ^10 Galaxy Power |
You have 0 Infinity Power, ranslated to 0x multiplier on all Normal Dimensions
You've gained 0 tickspeed upgrades.
You have 0 Time Shards. The next tickspeed upgrade is at 0 Time Shards.
You have 0 meta-antimatter.
was 0, which is raised by , and then translated to 0x .
| First Meta Dimension |
0 (0)
|
||
| Second Meta Dimension |
0 (0)
|
||
| Third Meta Dimension |
0 (0)
|
||
| Fourth Meta Dimension |
0 (0)
|
||
| Fifth Meta Dimension |
0 (0)
|
||
| Sixth Meta Dimension |
0 (0)
|
||
| Seventh Meta Dimension |
0 (0)
|
||
| Eighth Meta Dimension |
0 (0)
|
| Meta-Dimension Shift: requires 20 Fourth Meta Dimensions | |
| First Fluctuant Dimension x1.00 |
0
|
|
| Second Fluctuant Dimension x1.00 |
0
|
|
| Third Fluctuant Dimension x1.00 |
0
|
|
| Fourth Fluctuant Dimension x1.00 |
0
|
|
| Fifth Fluctuant Dimension x1.00 |
0
|
|
| Sixth Fluctuant Dimension x1.00 |
0
|
|
| Seventh Fluctuant Dimension x1.00 |
0
|
|
| Eighth Fluctuant Dimension x1.00 |
0
|
Auto-save interval: 30s |
|||
Render rate: 1 tick |
||
Update Rate: 50ms |
||
|
Game speed: 1.00x
|
Replicate speed: 1.00x
|
|
DT production: 1.00x
|
TT production: 1.00x
|
|
Nanospeed: 1.00x
|
Branch speed: 1.00x
|
|
Photonic Flow: 1.00x
|
Bosonic Speed: 1.00x
|
Created by Aarex.

Reward: Second Dimension autobuyer |
|
The First Dimension is heavily weakened, but gets an exponentially increasing bonus that resets on a reset.
Reward: Third Dimension autobuyer |
Buying a dimension automatically erases all lower tier dimensions, like a sacrifice without the boost.
Reward: Fourth Dimension autobuyer |
|
Reward: Fifth Dimension autobuyer |
Each Normal Dimension costs the Dimension 2 tiers before it (excluding the 1st and 2nd Dimensions), with modified prices.
Reward: Sixth Dimension autobuyer |
|
The multiplier per 10 dimensions is random for each per-10 purchase, varying from 0.30x to 10x.
Reward: Seventh Dimension autobuyer |
Dimension Boosts and Galaxies have no effect. Sacrifice will act similarly to a Dimension Boost, but its effect is immensely more powerful.
Reward: Eighth Dimension autobuyer |
|
Reward: Tickspeed autobuyer |
Reward: Automated Dimension Boosts |
|
There's normal matter which rises. If it exceeds your antimatter, it will act as an Dimension Boost without the bonus.
Reward: Automated Galaxies |
Reward: Automated Big Crunches |
|
Reward: Automated Dimensional Sacrifice |
Reward: Automated Galactic Sacrifice |
|
Reward: Automated Tickspeed Boosts |
The Tickspeed Multiplier boost to Time Dimensions is weaker.
Reward: Automated Time Dimension Boosts |
|
Dimension boosts are disabled.
Reward: Automated Dimensional Sacrifice |
|
There are no reductions on Galaxy and Dimension Boost cost increases, but Infinity Upgrades based on time or Infinities are applied post-dilation.
Goal: 1e550 |
Dimension and Tickspeed cost multiplier increases start immediately, but are reduced.
Goal: 1e950 Reward: Cost multiplier increases are reduced, and tickspeed cost multiplier increase is further decreased based on galaxies. |
||
|
|
All Normal Dimension multipliers are disabled except for Infinity Power, but the Galaxy boost on Infinity Power is stronger.
Reward: Dimension & tickspeed boosts also boost infinity power. |
||
|
The Tickspeed multiplier to dimensions is always at 1x, but every tickspeed purchase decreases tickspeed based on galaxies.
Goal: 1e1200 Reward: Every tickspeed purchase decreases tickspeed based on galaxies |
Goal: 1e850 |
Goal: 1e10500 Reward: Get the sacrifice autobuyer, and sacrifice is more powerful. |
|
|
Tickspeed interval decrease is always at 0%, but for every tickspeed purchase you get a static multiplier on all Normal Dimensions, which increases with galaxies.
Goal: 1e5000 Reward: Gain a static multiplier on every tickspeed purchase. |
Goal: 1e13000 Reward: All Normal Dimension multipliers are raised by ^1.05. |
The Tickspeed Autobuyer Challenge, Automated Big Crunches Challenge, Automated Galactic Sacrifice Challenge, and Automated Tickspeed Boosts Challenge are all applied at once.
Reward: Galaxy points boost Tickspeed Boosts. |
|
|
The Galaxy exponent boost to Galaxy points gain is buffed, but all Galaxy upgrades that are based on Galaxy points are disabled.
Reward: The Galaxy exponent boost to Galaxy points gain is buffed. |
|||
|
Goal: 1e11111 Reward: Galaxies are 10% more powerful, and reduce the requirements for Galaxies and Dimension Boosts by 1. |
There's an exponentially rising matter that divides the multiplier on all of your Dimensions.
Goal: 2e22222 |
||
|
Goal: 1e10000 |
Your production is at 100% after purchasing anything, after that it rapidly drops down.
Goal: 1e27000 Reward: You get a multiplier to Normal Dimensions 2-7 based on the 1st and 8th Normal Dimension multipliers. |
||
|
Condensers & Infinity Condensers do nothing.
Reward: Infinity Condensers are stronger based on your Condensers. |
Condensers & Infinity Condensers are the only source of production for their respective dimensions.
Reward: Condensers & Infinity Condensers are 15% stronger, and the Tickspeed softcap is 10% weaker. |
|
Time Dimensions are disabled.
Completed 0 Times. Goal: 1e2000 IP Reward: Xx on all Time Dimensions (based on time spent this Eternity) |
Infinity Dimensions are disabled.
Completed 0 Times. Goal: 1e1000 IP Reward: idk lol |
|
Dimensions 5-8 don't produce anything. Dimensional Sacrifice is disabled.
Completed 0 Times. Goal: 1e750 IP Reward: idk lol |
All infinitied stat multipliers and generators are disabled.  If you exceed the restraint, you fail the challenge.
Completed 0 Times. Goal: 1e4250 IP in 20 infinities Reward: Infinity Dimension multiplier from unspent IP |
|
Galaxy cost increase scaling starts instantly (Normally at 100 galaxies). Dimension Boost cost scaling is massively increased.
Completed 0 Times. Goal: 1e3000 IP Reward: Galaxy cost scaling starts 10 galaxies later |
You can't gain galaxies normally, but the cost of upgrading your max Replicated Galaxies is massively reduced.
Completed 0 Times. Goal: 1e1500 Reward: Further reduction dimension cost multiplier increase, Current: 3x |
|
The First Time Dimension produces Eighth Infinity Dimensions, and the First Infinity Dimension produces Seventh Dimensions. Tickspeed .
Completed 0 Times. Goal: 1e2700 IP Reward: Infinity Dimension multiplier based on time shards, Current: 0x |
You can only upgrade Infinity Dimensions 50 times, and upgrade Replicanti 40 times. The autobuyers of these features are disabled.
Completed 0 Times. Goal: 1e1150 Reward: dunno |
|
You can't buy tickspeed upgrades, but Infinity Power instead gives a greatly reduced multiplier to Time Dimensions.
Completed 0 Times. Goal: 1e400 IP Reward: something good I hope |
Time Dimensions and Infinity Dimensions are disabled, but you gain an immense boost from your Infinities to Normal Dimensions.
(infinities^1000) Currently: xX Completed 0 Times. Goal: 1e1500 Reward: dunno |
|
All prior multipliers to Dimensions are disabled, except for the multipliers from Infinity Power and Dimension Boosts to Normal Dimensions.
Completed 0 Times. Goal: 1e400 IP Reward: something good I hope |
The game runs 1,000x slower, however you have a time limit to beat the challenge. Exceeding the time limit results in failing the challenge.
Completed 0 Times. Goal: 1e110000 in 0.5 seconds or less. Reward: Infinity Dimension cost multipliers are reduced. (x^1) |
|
Dimension Boosts and total Galaxies boost each other, but square root their powers.
|
The Replicanti amount is always 1.
|
| Perk #1 | Perk #2 | Perk #3 | Perk #4 |
| Perk #5 | Perk #6 | Perk #7 | Perk #8 |
| Infinity | Eternity | Quantum |
| Coming soon... | Coming soon... | Coming soon... |
| Ghostify | ||
| Coming soon... |
| 1 Sacrifice: | 2 Sacrifices: |
| 5 Sacrifices: | 10 Sacrifices: |
| 25 Sacrifcies: | 50 Sacrifices: |
Automatic Dilation
Dilate for every X eternities:
Auto-dilate after TP upgrade or quantum: Is active |
Automatic Eternity
Amount of EP to wait until reset:
Is active |
Automatic Quantum
Is active
Disable at times quantumed stat:
(0 = always) |
|
Automatic Dimension Boosts
Current interval: 30 seconds
Max 8ths used on reset:
Galaxies required to always Dimboost:
Bulk DimBoost amount:
Is active |
Automatic Galaxies
Current interval: 30 seconds
Max Galaxies:
Buy max galaxies every X seconds (0 to always buy):
Is active |
Automatic Big Crunch
Current interval: 60 seconds
Amount of IP to wait until reset:
Require max replicanti:
Require IP from crunch at peak:
Is active
|
|
1st Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
2nd Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
3rd Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
|
4th Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
5th Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
6th Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
|
7th Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
8th Dimension Autobuyer
Current interval: 5 seconds
Priority:
Is active |
Tickspeed Autobuyer
Current interval: 5 seconds
Priority:
Is active |
|
Automatic Tickspeed Boosts
Max 8ths used on reset:
Galaxies required to always tickspeed boost:
Bulk Tickspeed Boost amount:
Is active
|
Automatic Sacrifice
Current interval: 0.10 seconds
Sacrifice when the multiplier is over:
Is active |
Automatic Galactic Sacrifice
Galactic sacrifice when GP gain is over:
Is active |
|
Automatic Time Dimension Boosts
Max 8ths used on reset:
Galaxies required to always Time Dimension Boost: Is active |
You have 0 replicanti, which is translated to 0 .
You have 0 Replicanti Compressors, which boosts the exponent of Replicantis by ^1.00, x1.00.
You have 0 Replicanti Dilaters, which cheapens Replicanti upgrades by 1.00 efficiency.
Replicantis have generated 0 energy1 in total, which translated to 0x Quantum Energy and Positronic Charge.
For next eternity:
Galaxy strength:You have 0 singularity power.
You have 0.0 dark matter, translated to 1.0x faster tickspeed.
You are getting 0 dark matter per second.You have 0.0 dark matter. The next discount upgrade is at 0.0.
|
First Dimension Dim-tech First Dimension discount: 1x |
Second Dimension Dim-tech Second Dimension discount: 1x |
Third Dimension Dim-tech Third Dimension discount: 1x |
|
Fourth Dimension Dim-tech Fourth Dimension discount: 1x |
Fifth Dimension Dim-tech Fifth Dimension discount: 1x |
Sixth Dimension Dim-tech Sixth Dimension discount: 1x |
|
Seventh Dimension Dim-tech Seventh Dimension discount: 1x |
Tickspeed Dim-tech Tickspeed discount: 1x |
Eighth Dimension Dim-tech Eighth Dimension discount: 1x |
|
(translated to ) |
(translated to ) |
|
|
0 red
On next quantum: 0 (+0 green-antired gluons) |
0.0 red power | Translated to stronger galaxies. |
| Ratio: | ||
|
0 green
On next quantum: 0 (+0 blue-antigreen gluons) |
0.0 green power | Translated to slower replicanti interval scaling. |
| Ratio: | ||
|
0 blue
On next quantum: 0 (+0 red-antiblue gluons) |
0.0 blue power |
Translated to more Tachyon particles. |
| Ratio: | ||
| Your Quantum Energy is giving 0.0 more color powers and 0.0 total extra color powers. | ||
|
You will get colored anti-Quarks when you assort anti-Quarks
|
% |
|
|
0 green-antired
(translated to 1.00x to red power, 0.00 to green power) |
0 blue-antigreen
(translated to 1.00x to green power, 0.00 to blue power) |
0 red-antiblue
(translated to 1.00x to blue power, 0.00 to red power) |
|
|
||
| Some Entangled Boosts only work on and based on which kind you choose. | ||
|
Gain more Quantum Energy. |
Gain more extra Replicated Galaxies. |
3x TP upgrade scales slower after e100 DT. |
|
Meta-antimatter boosts dilated time by . (from ^0.003) |
|
|
|
TP formula upgrade scales at after e100 DT. |
Dilated time boosts Meta Dimensions by . |
Meta Accelerator accelerates faster. |
|
Multiply the blue power base by . |
Raise the blue power effect by . |
(at anti-Quarks tab) |
| 0 Milestone Points | |||
|
Speedrun
(Your best quantum time is 0 seconds) 0 |
Energetic
(Your best Quantum Energy is 0) 0 |
Relativistic
(You got a best of 0 Tachyon Particles) 0 |
Challenging
(You have completed a total of 0 unique paired challenges) 0 |
|
Fluctuant
(You have 0 Fluctuant Energy) 0 |
Achievement |
|
0 Positrons |
0.0 Positronic Charge |
|
|
Quantum efficiency is based on Replicantis , but the denominator is decreased to 1. |
Unlock Meta-Accelerator. (with a base multiplier of , based on time since quantum) (at Meta Dimensions tab) |
Galaxies raise the per-10 multiplier by . |
|
Quantum requires instead. |
Reduce the gluon penalties by . |
Raise all Time Dimensions by . |
Tachyon particles speed up production by . |
EC14 reward is closer to ^1. |
Meta Accelerator slowdown starts later, but also slows down the acceleration. |
|
Infinitied stat raises itself by . |
Eternity Points boost Anti-Quarks by . |
Replicantis add to cap. |
Complete 8 PC completions to unlock String.
| Alpha: 0.00 | Beta: 0.00 | Gamma: 0.00 | |
|
|
| You have 0 positron neutrinos. | You have 0 Muon neutrinos. | You have 0 Tau neutrinos. |
| They boost something by 1.0x. | They boost something by 1.0x. | They boost something by 1.0x. |
| They boost something by 1.0x. | They boost something by 1.0x. | They slow down Distant Antimatter Galaxies by 0.0%. (Nerfed in Big Rip runs) |
| They boost something by 1.0x. | They strengthen the first Big Rip upgrade by 0.0%. | In Big Rips, they multiply the IC3 reward for each tickspeed purchase by 1.00x. |
| They decrease free tickspeed upgrade threshold by -. | They boost the production and cap of Ghostly Rays by 1.00x. | They raise the Eternal Matter gain by 1.00. |
| You have 1 Automator Ghosts. Next Automator Ghost at ?.?. |
You have 0.0 Automator Charge. | You have 0.0 Automator Power. Automator Ghosts are using 0.0 Automator Power. WARNING: NOT ENOUGH POWER TO AUTOMATE! |
Auto-Red Unstabilize Ghost (unstabilizes when you have no red unstable quarks, up to 10 times per second) Power usage: bug Is active: |
Auto-Green Unstabilize Ghost (unstabilizes when you have no green unstable quarks, up to 10 times per second) Power usage: bug Is active: |
Auto-Blue Unstabilize Ghost (unstabilizes when you have no blue unstable quarks, up to 10 times per second) Power usage: bug Is active: |
Auto-Rotate Ghost Power usage: 1 Auto-rotate unstabilize ghosts: Direction: Is active: |
Auto-Branch Upgrade Ghost (buys if possible) Power usage: bug Is active: |
Auto-Tree Upgrade Ghost (buys if possible) Power usage: bug Is active: |
Auto-Quantum Boost Ghost (buys Entangled & Positronic Boosters if possible) Power usage: bug Is active: |
Auto-Food Ghost (buys if possible) Power usage: bug Is active: |
Auto-Worker Replicant Ghost (feeds if possible) Power usage: bug Is active: |
Auto-Worker Limit Ghost (buys if possible) Power usage: bug Is active: |
Auto-Nanoreward Ghost Power usage: bug Every seconds, producing preon charge for seconds. Is active: |
Auto-Radioactive Decay Ghost (buys if possible) Power usage: bug Is active: |
Auto-Big Rip Ghost Power usage: bug Big Rip in seconds and undo after seconds. Stop after times. (0 = always) Is active: |
Auto-BE Multi Upgrade Ghost Power usage: bug Is active: |
Auto-Ghostify Ghost Power usage: bug Amount of GhP to wait until reset: Is active: |
Auto-Neutrino Cycler Ghost Power usage: bug Is active: |
Auto-Extractor Ghost Power usage: bug This also changes runes at a complete extraction on 1s after last change or change immediately at X seconds remaining for extracting: Is active: |
Anti-??? Ghost Power usage: bug Is active: |
Auto-Enchanter Ghost (doesn't consume your Bosonic Runes, enchant every 2 seconds) Power usage: bug Is active: |
Auto-Bosonic Upgrader Ghost Power usage: bug Is active: |
Auto-W & Z Boson Ghost Power usage: bug Is active: |
Auto-Challenge Sweeper Ghost (not implemented) Power usage: bug Seconds per 1 Paired Challenge: Is active: |
Auto-Light Ghost (automatically get Light Empowerments every second) Power usage: bug Is active: |
Auto-Higgs Ghost (automatically get Higgs Bosons every second) Power usage: bug Wait until Higgs gain: Or gain multiplier: Is active: |
Auto-Shifter Ghost (automatically get Gravity Dimension Shifts / Boosts every second) Power usage: bug Is active: |
|
You have Ghostly Photons. They increase your Ghostly Rays production to per second. |
You have Ghostly Rays. |
You have Dark Matter. They increase your limit amount of Ghostly Rays to . |
|
You have red Light. You have made a best amount of red Light. |
You have orange Light. | You have yellow Light. | You have green Light. |
| Next Light at Ghostly Rays. | Next Light at Ghostly Rays. | Next Light at Ghostly Rays. | Next Light at Ghostly Rays. |
| They boost something by 1.00x. | They boost red Light strength by x. | They boost orange Light strength by x. | They boost yellow Light strength by x. |
| They boost something by 1.00x. | They boost something by 1.00x. | They boost something by 1.00x. | |
| You have blue Light. | You have indigo Light. | You have violet Light. | You have ultraviolet Light. |
| Next Light at Ghostly Rays. | Next Light at Ghostly Rays. | Next Light at Ghostly Rays. | Next Light at Ghostly Rays. |
| They boost green Light strength by x. | They boost blue Light strength by x and increase your Neutrino gain by x. |
They boost indigo Light strength by x and in Big Rips, your tickspeed multiplier boosts sixth Time Dimensions by x. (Your tickspeed multiplier boosts more if you have more violet Light.) |
Violet Light strength is currently x. Sharing with the power of Light Empowerments, they boost Violet Light. |
| In Big Rips, they slow down Ghostly Galaxies scaling by %. | They boost Neutrino Boosts 1, 6, and 9 by %. | They make Infinite Time reward % stronger. | |
| You have 0 . | |||
| Translated to +x multiplier to all Light strength boosts. | They make that all Lights boost other Lights from (x+1)^0.5 to . |
|
You have Bosonic Watts. Bosonic Speed: x Bosonic Lab is currently running at x. You have played Bosonic Lab for ticks. |
You have Bosonic Antimatter. (reduced) |
You have Bosonic Battery. Overdrive Speed: |
|
You have W+ Bosons and W- Bosons. Translated to x faster extracting time, x faster oscillate progression gain, x Bosonic Antimatter production speed. |
You have Z Bosons. Translated to x faster decay speed of W Boson and faster conversion speed of W- to W+. |
|
|
You have Anti-Preons. | ||
|
W Boson is currently . |
Z Boson is currently positron. |
Note: Auto-Presets get automatically assigned on buying a preset!
Note 2: Respeccing turns the Auto-Presets off.
Assigning updates the preset you are choosing.
Eternity (Normal)
Dilation
Quantum Challenge 1
Quantum Challenge 7
You have 0 Time Theorems.


Enter your domain (e.g. foo.com) to check whether your apple-app-site-association is properly hosted. Optionally, provide a Bundle identifier to validate the correct values from your project are present. For more accuracy, additionally provide your Team Identifier.
Currently Apple requires the AASA be signed.
Alternatively, provide an archived app .ipa file, and we'll check that it contains the proper entitlements and validate any listed domains.
Ensure sure your app name is correct
Disclaimer: This product is in no way affiliated with Apple, and the results you see here do not guarantee that your setup will work with the actual Apple scraper. This is all my personal best guess at how things work, and things that have worked for me. None of the files or domains you use are stored on disk, they are deleted after the request completes.
- {{ appname }} wasn't able to be loaded
- Must be able to extract application (should be of IPA format)
- Must be able to find entitlements (looking in {{appname}}/Payload/{{appname}}.app/archived-expanded-entitlements.xcent)
- Must have domains listed in com.apple.developer.associated-domains
{{ appname }} was successfully loaded
{{ domain }} -- This domain validates, JSON format is valid, and Bundle / Team Identifiers match (if provided)
{{ prettyPrintAASA(results.aasa) }}
{{ domain }} -- This domain has a valid AASA, but does not contain provided Bundle / Team Identifiers
{{ prettyPrintAASA(results.aasa) }}
{{ domain }} -- This domain AASA was pulled, but the JSON format is Invalid
{{ prettyPrintAASA(results.aasa) }}
- {{ domain }} -- This domain has some validation issues
- Your domain is valid (valid DNS)
- Your file must be served over HTTPS
- Your server shouldn't return an error status code (>= 400)
- Your file cannot be behind redirects
- Your file must be served with content type "application/pkcs7-mime"
- Your file should validate and return its contents with `openssl smime -verify -inform DER -noverify`
- Your file should contain valid JSON (using simple JSON.parse). This can be tripped by things like having an extraneous NULL at the end of your string.


Created: 11/01/2015
By: demonisblack
Email<EMAIL_ADDRESS>Thank you for purchasing my game. If you have any questions that are beyond the scope of this help file, please feel free to email via my user page contact form here. Thanks so much!
The Boiled Eggs is a HTML5 game where you have to boiled different types of eggs with simple steps and controls!.
The ZIP package contains the game with 1024x768 resolution that scales proportionally to fit current screen device.
How To Play:
1. Use finger or mouse to tap to start cooking
2. Pressing the burn button to maintain the heat meter in greenzone
3. Successfully maintain the heat meter in time will score
To install the game just upload folder 'game' to your server. The game won't run locally with some browser like Chrome due to some security mode.
You need a website that runs PHP to make facebook share button work, and make sure to change Facebook Open Graph meta and Twitter meta in index.html, just replace [GAME_URL] to your game URL.
 <meta property="og:image" content="[GAME_URL]/share.jpg" /> <meta property="og:url" content="[GAME_URL]" />  <meta name="twitter:image" content="[GAME_URL]/share.jpg" />
You can easily customize game text and settings in game.js file
//Game Text var bgColour = '#f4eee0'; var playBackgroundMusic = true; //toggle background music var cookButtonText = 'COOK'; //gameplay cook text button var heatButtonText = 'BURN'; //gameplay burn text button var mistakeText = 'MISTAKE :'; //text for gameplay mistake, [NUMBER] will replace with value var scoreText = 'SCORE : [NUMBER]'; //text for gameplay score, [NUMBER] will replace with value var resultTitleText = 'GAME OVER!'; //text for result page title var resultScoreText = 'Your best score is [NUMBER]'; //text for result page score var totalMistake = 3; //total mistakes var gameScore = 100; //game score var targetScore = 100; //score target to increase game speed, it will multiplied for next speed eg.(100, 200, 400, 800...) var burnerIncreaseSpeed = .005; //burn meter speed to increase game speed var burnerButtonSpeed = .8; //burn meter button speed var startCookCountdown = 5; //countdown for auto start cook var waterBoilTime = 6000; //total boil time 6 sec var waterStartBoilTime = 5000; //water start boil animation time 5 sec (note timer must set lower than waterBoilTime); var potWidth = 150; //pot width var potWaterHeight = 40; //pot water height var eggDropHeight = 60; //total height for egg drop aniamtion //types of eggs name and cook time var eggTypes_arr = [{name:'Soft Boiled Eggs', time:60000}, {name:'Half Boiled Eggs', time:120000}, {name:'Boiled Eggs', time:180000}]; var eggAdditionalRandomTimer = 6000; //total random timer to plus var boilingText = 'Boiling water...'; //boiling water text var gameScoreText = 'Good!'; //score text var failedScoreText = 'Overcooked!'; //fail text //Social share, [SCORE] will replace with game score var shareOption = true; //toggle share option var shareText ='SHARE NOW...'; //text for share instruction var shareTitle = 'Highscore on The Boiled Eggs is [SCORE]';//social share score title var shareMessage = '[SCORE] is mine new highscore on The Boiled Eggs! Try it now!'; //social share score message
The sound can be easily disabled to avoid compatibility issues in sound.js file:
var enableMobileSound = true;
The page start with the loader wrapper that covering the whole screen in the body. It shows loader progress when calls the function initPreload()

0

This section is for browser not support page when calls the function checkBrowser(). It shows error message when detect the browser does not support canvas.

YOUR BROWSER ISN'T SUPPORTED.
PLEASE UPDATE YOUR BROWSER IN ORDER TO RUN THE GAME

Device rotate instruction page when calls the function checkMobileOrientation(). It shows rotate instruction when device is in portrait view.

Rotate your device
to landscape

Follow by one canvas tag in the body. The game start initiatie by calls the main function of the game initMain().

 <canvas id="gameCanvas" width="1024" height="768"></canvas>

I'm using two CSS files in this game. The first one is a generic reset file. Many browser interpret the default behavior of html elements differently. By using a general reset CSS file, we can work round this. This file also contains some general styling, such as anchor tag colors, font-sizes, etc. Keep in mind, that these values might be overridden somewhere else in the file.
The second file contains all of the specific stylings for the page.
This game using Javascript files below.
Complete game flow:
The most important functions used for page.
The most important functions used for game.
The game contain 'design' folder which include following:
And 'animations' folder which include following:
You can generate PNG spritesheet file from a SWF using SwfSpriteSheet 1.7
The folder 'assets' in 'game' folder contains all the images of the game that can be replaced. Is better to have the same size of the old ones if you want to reskin the game graphic without coding.
This game is build for Desktop browsers that support HTML5 canvas. Any mobile/tablet should work in landscape view, but they are not officially supported.
I've used the following font and sound files as listed.
Once again, thank you so much for purchasing this game. As I said at the beginning, I'd be glad to help you if you have any questions relating to this game. No guarantees, but I'll do my best to assist. If you have a more general question relating to the games on CodeCanyon, you might consider visiting the forums and asking your question in the "Item Discussion" section.
If you like my game, please take a moment to rate it. Thanks!
demonisblack


$220/NIGHT
Guests staying in our 22 sqm (237 sq ft) Standard Twin Rooms enjoy an elegant and modern design providing a comfortable living throughout your stay whether you are on business or leisure. Relax in our fresh, stylish, air conditioned Guest Rooms, where you can enjoy a restful night's sleep and work in comfort at the spacious desk.
Relax and Watch movies on the 32-inch LCD TV and surf the web with WiFi access. These rooms also feature a mini-fridge, hair dryer and an iron/ironing board on request to make you feel at home.
Adults: 2
Size: 29.68m2
Categories: Double
Children:2
Bed type: One Twin
View: Sea Side
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Student:
Grade:
[.5em]School:
TSVI:
[.5em] Prompt Hierarchy / Scoring
I = Independent
FP = Full Physical
PP = Partial Physical
VP = Verbal Prompt
VC = Verbal Cue
Table
2.16.1
.
in-context


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Here we present an OpenCAL-OMP implementation of SciddicaT, which takes advantage of the built-in unsafe operations. They belong to the eXtended CA definition and allow for further computational optimizations. You can find the complete source code of SciddicaT implemented as an eXtended CA in Listing [lst:calomp_SciddicaT-unsafe], while the corresponding serial implementation can be found in Section [sec:sciddicaT_extended], Listing [lst:cal_sciddicaT-unsafe].
First of all - from a XCA modeling point of view - note that only the topographic altitude and the debris thickness are now considered as model’s substates (lines 25-28, 147-148), as the four outflows substates are no longer needed. Moreover, the number of elementary process now considered is two (lines 143-144), instead of three for the previous versions of SciddicaT.
The call to the calSetUnsafe2D()
function (line 139)
places OpenCAL-OMP in unsafe mode, allowing to lock memory locations
(i.e. cells) that can be simultaneously accessed by more threads. In
order properly exploit the OpenCAL-OMP’s built in lock feature, you
have to use specific functions, which are provided by the
OpenCAL-OMP/cal2DUnsafe.h
header file (line 6). In the specific
case, besides the already discussed calAddActiveCellX2D()
function, the calAddNext2Dr()
and calAddNextX2Dr()
functions are employed (lines 88-89), in place of the combination of
get-set operations, as done in the corresponding serial implementation
(Listing [lst:cal_sciddicaT-unsafe], lines 84-85). In fact, consider
the source code snippet in Listing [lst:get-set] (checked out by
Listing [lst:cal_sciddicaT-unsafe]). As you can see, for each
not-eliminated cell, the algorithm computes a flow,
\(f\) (line 5) and then subtracts it from the central cell (line 6),
adding it to the corresponding neighbour (line 7), in order to
accomplish mass balance. In both cases (flow subtraction and adding), a
flavor of calGet
function is called to read the current
value of the
\(Q_h\) substate from the next working plane. Subsequently, a flavor of
the calSet
function is used to update the previously read
value. When a single thread is used to perform such operations, no race
conditions can obviously occur. At the contrary, even in the case of
two concurrent threads, different undesirable situations can take
place, which give rise to a race condition and therefore to a wrong
result. For instance, let’s suppose both threads read the value
first, and then write their updated values; in this case, the resulting
value will correspond to the one written by the thread that writes the
value for last, and the contribution of the other thread will be lost.
// <snip>
for (n=1; n<sciddicaT->sizeof_X; n++)
if (!eliminated_cells[n])
{
f = (average-u[n])*P.r;
calSet2Dr (sciddicaT,Q.h,i,j, calGetNext2Dr (sciddicaT,Q.h,i,j) -f);
calSetX2Dr(sciddicaT,Q.h,i,j,n,calGetNextX2Dr(sciddicaT,Q.h,i,j,n)+f);
// <snip>
}
// <snip>
In order to avoid such kind of problems when dealing with more
threads, the above mentioned calAddNext2Dr()
and
calAddNextX2Dr()
functions lock the cell under consideration and
then perform the get-set operations without the risk other threads can
interfere. In this way, no race conditions can be triggered. Obviously,
there is a side-effect in terms of computational performance. In fact,
as expected, locks can slow down threads execution and therefore the
entire simulation.


greengrasssdk.stream_manager.data package¶
-
class
greengrasssdk.stream_manager.data.
VersionInfo
[source]¶ Bases:
enum.Enum
(Internal Only) Version information.
-
PROTOCOL_VERSION
= '1.1.0'¶
-
-
class
greengrasssdk.stream_manager.data.
ConnectRequest
(request_id: str = None, protocol_version: str = None, other_supported_protocol_versions: List[str] = None, sdk_version: str = None, auth_token: str = None)[source]¶ Bases:
object
(Internal Only) Request object to connect to the service.
-
request_id
¶
-
protocol_version
¶
-
other_supported_protocol_versions
¶
-
sdk_version
¶
-
auth_token
¶
-
-
class
greengrasssdk.stream_manager.data.
ResponseStatusCode
[source]¶ Bases:
enum.Enum
(Internal Only) Enum defining possible response status codes from StreamManager server. Success: Request succeeded. UnknownFailure: Encountered unknown StreamManager server failure. Unauthorized: Client is not authorized to perform this request. InvalidRequest: Client request is invalid. RequestPayloadTooLarge: Request payload is too large. ResourceNotFound: The requested resource does not exist. ServerTimeout: Server took too long and timed out. ResponsePayloadTooLarge: Server response exceeded the max allowed response payload size by the protocol. UnsupportedConnectVersion: Server does not support the Connect version presented by the Client. UnexpectedOperation: Operation presented was not expected by the Server. UnsupportedProtocolVersion: Protocol version presented by the Client is not compatible with the Server. InvalidProtocolVersion: Protocol version presented by the Client is not valid. FailedToConnect: Client failed to connect to the Server. NotEnoughMessages: There is not enough messages to return. MessageStoreReadError: Read messages encountered an error. OutOfMemoryError: Server ran out of memory. UpdateFailed: Update operation failed. UpdateNotAllowed: One or more fields are not allowed to be updated. UnknownOperation: Client request is not recognized by the server.
-
Success
= 0¶
-
UnknownFailure
= 1¶
-
InvalidRequest
= 3¶
-
RequestPayloadTooLarge
= 4¶
-
ResourceNotFound
= 5¶
-
ServerTimeout
= 6¶
-
ResponsePayloadTooLarge
= 7¶
-
UnsupportedConnectVersion
= 8¶
-
UnexpectedOperation
= 9¶
-
UnsupportedProtocolVersion
= 10¶
-
InvalidProtocolVersion
= 11¶
-
FailedToConnect
= 12¶
-
NotEnoughMessages
= 13¶
-
MessageStoreReadError
= 14¶
-
OutOfMemoryError
= 15¶
-
UpdateFailed
= 16¶
-
UpdateNotAllowed
= 17¶
-
UnknownOperation
= 18¶
-
-
class
greengrasssdk.stream_manager.data.
ConnectResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None, protocol_version: str = None, supported_protocol_versions: List[str] = None, server_version: str = None, client_identifier: str = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
status
¶
-
error_message
¶
-
protocol_version
¶
-
supported_protocol_versions
¶
-
server_version
¶
-
client_identifier
¶
-
-
class
greengrasssdk.stream_manager.data.
Operation
[source]¶ Bases:
enum.Enum
Internal Only.
-
Unknown
= 0¶
-
Connect
= 1¶
-
CreateMessageStream
= 2¶
-
DeleteMessageStream
= 3¶
-
AppendMessage
= 4¶
-
ReadMessages
= 5¶
-
ConnectResponse
= 6¶
-
CreateMessageStreamResponse
= 7¶
-
DeleteMessageStreamResponse
= 8¶
-
AppendMessageResponse
= 9¶
-
ReadMessagesResponse
= 10¶
-
ListStreams
= 11¶
-
ListStreamsResponse
= 12¶
-
DescribeMessageStream
= 13¶
-
DescribeMessageStreamResponse
= 14¶
-
UpdateMessageStream
= 15¶
-
UpdateMessageStreamResponse
= 16¶
-
UnknownOperationError
= 17¶
-
-
class
greengrasssdk.stream_manager.data.
MessageFrame
(operation: greengrasssdk.stream_manager.data.Operation = None, payload: bytes = None)[source]¶ Bases:
object
Internal Only.
-
operation
¶
-
payload
¶
-
-
class
greengrasssdk.stream_manager.data.
Status
[source]¶ Bases:
enum.Enum
The status of the event.
-
Success
= 0¶
-
Failure
= 1¶
-
InProgress
= 2¶
-
Warning
= 3¶
-
Canceled
= 4¶
-
-
class
greengrasssdk.stream_manager.data.
StatusLevel
[source]¶ Bases:
enum.Enum
Defines the verbosity of status messages in a status-stream.
-
ERROR
= 0¶
-
WARN
= 1¶
-
INFO
= 2¶
-
DEBUG
= 3¶
-
TRACE
= 4¶
-
-
class
greengrasssdk.stream_manager.data.
S3ExportTaskDefinition
(input_url: str = None, bucket: str = None, key: str = None, user_metadata: dict = None)[source]¶ Bases:
object
S3 Task definition containing all the information necessary to export the data to S3. This will contain the S3 bucket and key as well as the file’s URL where the data is stored.
-
input_url
¶ The URL of the file that contains the data to upload. The file should be local on the disk.
-
bucket
¶ The name of the S3 bucket that this file should be uploaded to.
-
key
¶ The key for the S3 object that this file should be uploaded to. The string can have placeholder expressions which are resolved at upload time. Valid expressions are strings that are valid Java DateTimeFormatter strings. See https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html Example: myKeyNamePrefix/!{timestamp:yyyy/MM/dd}/myKeyNameSuffix.
-
user_metadata
¶ User metadata. For key of a user metadata, callers should not include the internal “x-amz-meta-” prefix. Keys are case insensitive and will appear as lowercase strings on S3, even if they were originally specified with uppercase strings. Reserved key names start with “$aws-gg-” prefix.
-
-
class
greengrasssdk.stream_manager.data.
StatusContext
(s3_export_task_definition: greengrasssdk.stream_manager.data.S3ExportTaskDefinition = None, export_identifier: str = None, stream_name: str = None, sequence_number: int = None)[source]¶ Bases:
object
Context associated with a status message. Describes which stream, export config, message, the status is associated with.
-
s3_export_task_definition
¶ The task definition of an S3 upload task if the status is associated with it, ie, if the eventType = S3Task.
-
export_identifier
¶ The export identifier the status is associated with.
-
stream_name
¶ The name of the stream the status is associated with.
-
sequence_number
¶ The sequence number of the message the status is associated with.
-
-
class
greengrasssdk.stream_manager.data.
EventType
[source]¶ Bases:
enum.Enum
The type of event, which determines how to interpret the status payload.
-
S3Task
= 0¶
-
-
class
greengrasssdk.stream_manager.data.
StatusMessage
(event_type: greengrasssdk.stream_manager.data.EventType = None, status_level: greengrasssdk.stream_manager.data.StatusLevel = None, status: greengrasssdk.stream_manager.data.Status = None, status_context: greengrasssdk.stream_manager.data.StatusContext = None, message: str = None, timestamp_epoch_ms: int = None)[source]¶ Bases:
object
Status object appended to a status-stream.
-
event_type
¶
-
status_level
¶
-
status
¶
-
status_context
¶
-
message
¶ String describing the status message.
-
timestamp_epoch_ms
¶ The time this status was added to the status-stream (in milliseconds since epoch).
-
-
class
greengrasssdk.stream_manager.data.
TraceableRequest
(request_id: str = None)[source]¶ Bases:
object
(Internal Only) TraceableRequest that contains only requestId.
-
request_id
¶
-
-
class
greengrasssdk.stream_manager.data.
UnknownOperationError
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None)[source]¶ Bases:
object
(Internal Only) Response for UnknownOperationError.
-
request_id
¶
-
status
¶
-
error_message
¶
-
-
class
greengrasssdk.stream_manager.data.
KinesisConfig
(identifier: str = None, kinesis_stream_name: str = None, batch_size: int = None, batch_interval_millis: int = None, priority: int = None, start_sequence_number: int = None, disabled: bool = None)[source]¶ Bases:
object
Configuration object for Kinesis data streams export destination.
-
identifier
¶ A unique identifier to identify this individual upload stream. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
kinesis_stream_name
¶ The name of the Kinesis data stream that this exporter should upload to.
-
batch_size
¶ The maximum size of a batch to send to Kinesis. Messages will be queued until the batch size is reached, after which they will then be uploaded. If unspecified the default will be 500. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The batch size must be between 1 and 500.
-
batch_interval_millis
¶ The time in milliseconds between the earliest un-uploaded message and the current time. If this time is exceeded, messages will be uploaded in the next batch. If unspecified messages will be eligible for upload immediately. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum value is 60000 milliseconds and the maximum is<PHONE_NUMBER>854 milliseconds.
-
priority
¶ Priority for this upload stream. Lower values are higher priority. If not specified it will have the lowest priority.
-
start_sequence_number
¶ The sequence number of the message to use as the starting message in the export. Default is 0. The sequence number provided should be less than the newest sequence number in the stream, i.e., sequence number of the last messaged appended. To find the newest sequence number, describe the stream and then check the storage status of the returned MessageStreamInfo object.
-
disabled
¶ Enable or disable this export. Default is false.
-
-
class
greengrasssdk.stream_manager.data.
IoTSiteWiseConfig
(identifier: str = None, batch_size: int = None, batch_interval_millis: int = None, priority: int = None, start_sequence_number: int = None, disabled: bool = None)[source]¶ Bases:
object
Configuration object for IotSiteWise data streams export destination. Minimum version requirements: StreamManager server version 1.1 (or AWS IoT Greengrass Core 1.11.0)
-
identifier
¶ A unique identifier to identify this individual upload stream. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
batch_size
¶ The maximum size of a batch to send to the destination. Messages will be queued until the batch size is reached, after which they will then be uploaded. If unspecified the default will be 10. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum batch size is 1 and the maximum is 10.
-
batch_interval_millis
¶ The time in milliseconds between the earliest un-uploaded message and the current time. If this time is exceeded, messages will be uploaded in the next batch. If unspecified messages will be eligible for upload immediately. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum value is 60000 milliseconds and the maximum is<PHONE_NUMBER>854 milliseconds.
-
priority
¶ Priority for this upload stream. Lower values are higher priority. If not specified it will have the lowest priority.
-
start_sequence_number
¶ The sequence number of the message to use as the starting message in the export. Default is 0. The sequence number provided should be less than the newest sequence number in the stream, i.e., sequence number of the last messaged appended. To find the newest sequence number, describe the stream and then check the storage status of the returned MessageStreamInfo object.
-
disabled
¶ Enable or disable this export. Default is false.
-
-
class
greengrasssdk.stream_manager.data.
ExportFormat
[source]¶ Bases:
enum.Enum
ExportFormat is used to define how messages are batched and formatted in the export payload. RAW_NOT_BATCHED: Each message in a batch will be sent as an individual HTTP POST with the payload as the body (even if batchSize is set). JSON_BATCHED: Each batch of messages will be sent as a JSON list of Message objects as the body.
-
RAW_NOT_BATCHED
= 0¶
-
JSON_BATCHED
= 1¶
-
-
class
greengrasssdk.stream_manager.data.
HTTPConfig
(identifier: str = None, uri: str = None, batch_size: int = None, batch_interval_millis: int = None, priority: int = None, start_sequence_number: int = None, disabled: bool = None, export_format: greengrasssdk.stream_manager.data.ExportFormat = None)[source]¶ Bases:
object
This export destination is not supported! The interface may change at any time without notice and should not be relied on for any production use. There are no guarantees around its correctness. This configures an HTTP endpoint which sends a POST request to the provided URI. Each request contains a single message in the body of the request.
-
identifier
¶ A unique identifier to identify this individual upload stream. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
uri
¶ URL for HTTP endpoint which should receive the POST requests for export.
-
batch_size
¶ The maximum size of a batch to send to the destination. Messages will be queued until the batch size is reached, after which they will then be uploaded. If unspecified the default will be 500. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum batch size is 1 and the maximum is 500.
-
batch_interval_millis
¶ The time in milliseconds between the earliest un-uploaded message and the current time. If this time is exceeded, messages will be uploaded in the next batch. If unspecified messages will be eligible for upload immediately. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum value is 60000 milliseconds and the maximum is<PHONE_NUMBER>854 milliseconds.
-
priority
¶ Priority for this upload stream. Lower values are higher priority. If not specified it will have the lowest priority.
-
start_sequence_number
¶ The sequence number of the message to use as the starting message in the export. Default is 0. The sequence number provided should be less than the newest sequence number in the stream, i.e., sequence number of the last messaged appended. To find the newest sequence number, describe the stream and then check the storage status of the returned MessageStreamInfo object.
-
disabled
¶ Enable or disable this export. Default is false.
-
export_format
¶ Defines how messages are batched and formatted in the export payload.
-
-
class
greengrasssdk.stream_manager.data.
StatusConfig
(status_level: greengrasssdk.stream_manager.data.StatusLevel = None, status_stream_name: str = None)[source]¶ Bases:
object
Configuration for status in a status-stream.
-
status_level
¶ Defines the verbosity of status messages in a status-stream.
-
status_stream_name
¶ The name of the stream to which status messages are appended. The status-stream should be created before associating it with another stream.
-
-
class
greengrasssdk.stream_manager.data.
S3ExportTaskExecutorConfig
(identifier: str = None, size_threshold_for_multipart_upload_bytes: int = None, priority: int = None, disabled: bool = None, status_config: greengrasssdk.stream_manager.data.StatusConfig = None)[source]¶ Bases:
object
Configuration object for S3 export tasks executor. Minimum version requirements: StreamManager server version 1.1 (or AWS IoT Greengrass Core 1.11.0)
-
identifier
¶ A unique identifier to identify this individual upload task. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
size_threshold_for_multipart_upload_bytes
¶ The size threshold in bytes for when to use multipart uploads. Uploads over this size will automatically use a multipart upload strategy, while uploads equal or smaller than this threshold will use a single connection to upload the whole object.
-
priority
¶ Priority for this upload task. Lower values are higher priority. If not specified it will have the lowest priority.
-
disabled
¶ Enable or disable this export. Default is false.
-
status_config
¶ Event status configuration that specifies the target status stream and verbosity.
-
-
class
greengrasssdk.stream_manager.data.
IoTAnalyticsConfig
(identifier: str = None, iot_channel: str = None, iot_msg_id_prefix: str = None, batch_size: int = None, batch_interval_millis: int = None, priority: int = None, start_sequence_number: int = None, disabled: bool = None)[source]¶ Bases:
object
Configuration object for IoT Analytics export destination.
-
identifier
¶ A unique identifier to identify this individual upload stream. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
iot_channel
¶ The name of the IoT Analytics Channel that this exporter should upload to.
-
iot_msg_id_prefix
¶ A string prefixed to each unique message id. After this prefix, StreamManager may append more data to make the message ID unique. This prefix must be less than 32 characters.
-
batch_size
¶ The maximum size of a batch to send to IoT Analytics. Messages will be queued until the batch size is reached, after which they will then be uploaded. If unspecified the default will be 100. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The batch size must be between 1 and 100.
-
batch_interval_millis
¶ The time in milliseconds between the earliest un-uploaded message and the current time. If this time is exceeded, messages will be uploaded in the next batch. If unspecified messages will be eligible for upload immediately. If both batchSize and batchIntervalMillis are specified, then messages will be eligible for upload when either condition is met. The minimum value is 60000 milliseconds and the maximum is<PHONE_NUMBER>854 milliseconds.
-
priority
¶ Priority for this upload stream. Lower values are higher priority. If not specified it will have the lowest priority.
-
start_sequence_number
¶ The sequence number of the message to use as the starting message in the export. Default is 0. The sequence number provided should be less than the newest sequence number in the stream, i.e., sequence number of the last messaged appended. To find the newest sequence number, describe the stream and then check the storage status of the returned MessageStreamInfo object.
-
disabled
¶ Enable or disable this export. Default is false.
-
-
class
greengrasssdk.stream_manager.data.
ExportDefinition
(http: List[greengrasssdk.stream_manager.data.HTTPConfig] = None, iot_analytics: List[greengrasssdk.stream_manager.data.IoTAnalyticsConfig] = None, kinesis: List[greengrasssdk.stream_manager.data.KinesisConfig] = None, iot_sitewise: List[greengrasssdk.stream_manager.data.IoTSiteWiseConfig] = None, s3_task_executor: List[greengrasssdk.stream_manager.data.S3ExportTaskExecutorConfig] = None)[source]¶ Bases:
object
Defines how and where the stream is uploaded.
-
http
¶ Defines how the stream is uploaded to an HTTP endpoint.
-
iot_analytics
¶ Defines how the stream is uploaded to IoT Analytics.
-
kinesis
¶ Defines how the stream is uploaded to Kinesis.
-
iot_sitewise
¶ Defines how the stream is uploaded to IoT SiteWise.
-
s3_task_executor
¶ Defines the list of configs for S3 task executors.
-
-
class
greengrasssdk.stream_manager.data.
StrategyOnFull
[source]¶ Bases:
enum.Enum
StrategyOnFull is used in the MessageStreamDefinition when creating a stream. It defines the behavior when the stream has reached the maximum size. RejectNewData: any append message request after the stream is full will be rejected with an exception. OverwriteOldestData: the oldest stream segments will be deleted until there is room for the new message.
-
RejectNewData
= 0¶
-
OverwriteOldestData
= 1¶
-
-
class
greengrasssdk.stream_manager.data.
Persistence
[source]¶ Bases:
enum.Enum
Stream persistence. If set to File, the file system will be used to persist messages long-term and is resilient to restarts. Memory should be used when performance matters more than durability as it only stores the stream in memory and never writes to the disk.
-
File
= 0¶
-
Memory
= 1¶
-
-
class
greengrasssdk.stream_manager.data.
MessageStreamDefinition
(name: str = None, max_size: int = 268435456, stream_segment_size: int = 16777216, time_to_live_millis: int = None, strategy_on_full: greengrasssdk.stream_manager.data.StrategyOnFull = None, persistence: greengrasssdk.stream_manager.data.Persistence = None, flush_on_write: bool = None, export_definition: greengrasssdk.stream_manager.data.ExportDefinition = None)[source]¶ Bases:
object
Object defining a message stream used in the CreateMessageStream and UpdateMessageStream API.
-
name
¶ The unique name of the stream. Must be an alphanumeric string including spaces, commas, periods, hyphens, and underscores with length between 1 and 255.
-
max_size
¶ The maximum size in bytes for the entire stream. Set to 256MB by default with a minimum of 1KB and a maximum of 8192PB.
-
stream_segment_size
¶ The size of each segment of the stream. Set to 16MB by default with a minimum of 1KB and a maximum of 2GB. Data is only deleted segment by segment, so the segment size is the smallest amount of data which can be deleted.
-
time_to_live_millis
¶ Time to live for each message in milliseconds. Data may be deleted at any time after the TTL expires; deletion is not guaranteed to occur immediately when the TTL expires. The minimum value is 60000 milliseconds and the maximum is<PHONE_NUMBER>854 milliseconds.
-
strategy_on_full
¶ What to do when the maximum size of the stream is reached. RejectNewData: any append message request after the stream is full will be rejected with an exception. OverwriteOldestData: the oldest stream segments will be deleted until there is room for the new message.
-
persistence
¶ Stream persistence. If set to File, the file system will be used to persist messages long-term and is resilient to restarts. Memory should be used when performance matters more than durability as it only stores the stream in memory and never writes to the disk.
-
flush_on_write
¶ This only applies when Persistence is set to File mode. Waits for the filesystem to complete the write for every message. This is safer, but slower. Default is false.
-
export_definition
¶ Defines how and where the stream is uploaded. See the definition of the ExportDefinition object for more detail.
-
-
class
greengrasssdk.stream_manager.data.
CreateMessageStreamRequest
(request_id: str = None, definition: greengrasssdk.stream_manager.data.MessageStreamDefinition = None)[source]¶ Bases:
object
(Internal Only) Request object for creating a message stream.
-
request_id
¶
-
definition
¶
-
-
class
greengrasssdk.stream_manager.data.
CreateMessageStreamResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
status
¶
-
error_message
¶
-
-
class
greengrasssdk.stream_manager.data.
UpdateMessageStreamRequest
(request_id: str = None, definition: greengrasssdk.stream_manager.data.MessageStreamDefinition = None)[source]¶ Bases:
object
(Internal Only) Request object for updating a message stream.
-
request_id
¶
-
definition
¶
-
-
class
greengrasssdk.stream_manager.data.
UpdateMessageStreamResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None)[source]¶ Bases:
object
(Internal Only) Response for UpdateMessageStreamRequest.
-
request_id
¶
-
status
¶
-
error_message
¶
-
-
class
greengrasssdk.stream_manager.data.
DeleteMessageStreamRequest
(request_id: str = None, name: str = None)[source]¶ Bases:
object
(Internal Only) Request object for deleting a message stream.
-
request_id
¶
-
name
¶
-
-
class
greengrasssdk.stream_manager.data.
DeleteMessageStreamResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
status
¶
-
error_message
¶
-
-
class
greengrasssdk.stream_manager.data.
DescribeMessageStreamRequest
(request_id: str = None, name: str = None)[source]¶ Bases:
object
(Internal Only) Request object for describing a message stream.
-
request_id
¶
-
name
¶
-
-
class
greengrasssdk.stream_manager.data.
MessageStreamInfo
(definition: greengrasssdk.stream_manager.data.MessageStreamDefinition = None, storage_status: greengrasssdk.stream_manager.data.MessageStreamInfo.storageStatus = None, export_statuses: List[greengrasssdk.stream_manager.data.MessageStreamInfo.exportStatuses] = None)[source]¶ Bases:
object
Message stream information including its definition, storage status and export status.
-
class
storageStatus
(oldest_sequence_number: int = None, newest_sequence_number: int = None, total_bytes: int = None)[source]¶ Bases:
object
Stream status including oldest/newest sequence number and total bytes.
-
oldest_sequence_number
¶ The sequence number of the first message which is still accessible in the stream.
-
newest_sequence_number
¶ The sequence number of the last appended message.
-
total_bytes
¶ The current total size of the stream in bytes.
-
-
class
exportStatuses
(export_config_identifier: str = None, last_exported_sequence_number: int = None, last_export_time: int = None, error_message: str = None, exported_bytes_from_stream: int = None, exported_messages_count: int = None)[source]¶ Bases:
object
Export status including the export identifier and the last exported sequence number for that export task.
-
export_config_identifier
¶ The unique export identifier.
-
last_exported_sequence_number
¶ The sequence number of the last message which was successfully exported.
-
last_export_time
¶ The last time an export was attempted. Data is Unix epoch time in milliseconds.
-
error_message
¶ Error message from the last export attempt if it failed.
-
exported_bytes_from_stream
¶ Total bytes exported from the stream for this Export Config. It does not include the failed export attempts or messages which are skipped because of some non-retryable error.
-
exported_messages_count
¶ Total messages exported/processed.
-
-
definition
¶
-
storage_status
¶ Stream status including oldest/newest sequence number and total bytes.
-
export_statuses
¶
-
class
-
class
greengrasssdk.stream_manager.data.
DescribeMessageStreamResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None, message_stream_info: greengrasssdk.stream_manager.data.MessageStreamInfo = None)[source]¶ Bases:
object
(Internal Only) Response object for describing a message stream.
-
request_id
¶
-
status
¶
-
error_message
¶
-
message_stream_info
¶
-
-
class
greengrasssdk.stream_manager.data.
AppendMessageRequest
(request_id: str = None, name: str = None, payload: bytes = None)[source]¶ Bases:
object
(Internal Only) Request object for appending to a message stream.
-
request_id
¶
-
name
¶
-
payload
¶
-
-
class
greengrasssdk.stream_manager.data.
AppendMessageResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None, sequence_number: int = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
status
¶
-
error_message
¶
-
sequence_number
¶
-
-
class
greengrasssdk.stream_manager.data.
ReadMessagesOptions
(desired_start_sequence_number: int = None, min_message_count: int = 1, max_message_count: int = None, read_timeout_millis: int = 0)[source]¶ Bases:
object
Options for the ReadMessages API. All fields are optional.
-
desired_start_sequence_number
¶ The desired beginning sequence number to start reading from. If the desired sequence number is less than the current minimum of the stream, then it will instead start reading from the current minimum.
-
min_message_count
¶ The minimum number of messages that will be returned. If not enough messages are available for reading, then NotEnoughMessages exception will be thrown. The minimum values is 1 and the maximum value is<PHONE_NUMBER>.
-
max_message_count
¶ The maximum number of messages that will be returned. The minimum values is the value of the minimum message count and the maximum value is<PHONE_NUMBER>.
-
read_timeout_millis
¶ The time to wait for messages in milliseconds. Default is 0, meaning that the server will not wait for messages. If it can fulfill the minimum messages it will return them, but otherwise NotEnoughMessages exception will be thrown. If the timeout is greater than zero, then the server will wait up to that time for more messages to be appended to the stream, waiting until the minimum number of messages is reached. The maximum value is the value of the client timeout.
-
-
class
greengrasssdk.stream_manager.data.
ReadMessagesRequest
(request_id: str = None, stream_name: str = None, read_messages_options: greengrasssdk.stream_manager.data.ReadMessagesOptions = None)[source]¶ Bases:
object
(Internal Only) Request object for reading from a message stream. readMessagesOptions is optional.
-
request_id
¶
-
stream_name
¶
-
read_messages_options
¶
-
-
class
greengrasssdk.stream_manager.data.
Message
(stream_name: str = None, sequence_number: int = None, ingest_time: int = None, payload: bytes = None)[source]¶ Bases:
object
Message object containing metadata and the user’s payload.
-
stream_name
¶ The name of the stream which this message is in.
-
sequence_number
¶ The sequence number of this message within the stream.
-
ingest_time
¶ The time that the message was ingested to Stream Manager. Data is Unix epoch time in milliseconds.
-
payload
¶ The binary message data.
-
-
class
greengrasssdk.stream_manager.data.
ReadMessagesResponse
(request_id: str = None, messages: List[greengrasssdk.stream_manager.data.Message] = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
messages
¶
-
status
¶
-
error_message
¶
-
-
class
greengrasssdk.stream_manager.data.
ListStreamsRequest
(request_id: str = None)[source]¶ Bases:
object
(Internal Only) Request object to list all available streams. There are no options.
-
request_id
¶
-
-
class
greengrasssdk.stream_manager.data.
ListStreamsResponse
(request_id: str = None, status: greengrasssdk.stream_manager.data.ResponseStatusCode = None, error_message: str = None, streams: List[str] = None)[source]¶ Bases:
object
Internal Only.
-
request_id
¶
-
status
¶
-
error_message
¶
-
streams
¶
-
-
class
greengrasssdk.stream_manager.data.
TimeInNanos
(time_in_seconds: int = None, offset_in_nanos: int = None)[source]¶ Bases:
object
Contains a timestamp with optional nanosecond granularity.
-
time_in_seconds
¶ The timestamp date, in seconds, in the Unix epoch format. Fractional nanosecond data is provided by offsetInNanos.
-
offset_in_nanos
¶ The nanosecond offset from timeInSeconds.
-
-
class
greengrasssdk.stream_manager.data.
Quality
[source]¶ Bases:
enum.Enum
An enumeration.
-
GOOD
= 'GOOD'¶
-
BAD
= 'BAD'¶
-
UNCERTAIN
= 'UNCERTAIN'¶
-
-
class
greengrasssdk.stream_manager.data.
Variant
(string_value: str = None, integer_value: int = None, double_value: float = None, boolean_value: bool = None)[source]¶ Bases:
object
Contains an asset property value (of a single type only).
-
string_value
¶ Asset property data of type string (sequence of characters).
-
integer_value
¶ Asset property data of type integer (whole number).
-
double_value
¶ Asset property data of type double (floating point number).
-
boolean_value
¶ Asset property data of type Boolean (true or false).
-
-
class
greengrasssdk.stream_manager.data.
AssetPropertyValue
(value: greengrasssdk.stream_manager.data.Variant = None, timestamp: greengrasssdk.stream_manager.data.TimeInNanos = None, quality: greengrasssdk.stream_manager.data.Quality = None)[source]¶ Bases:
object
Contains asset property value information.
-
value
¶ The value of the asset property.
-
timestamp
¶ The timestamp of the asset property value.
-
quality
¶ The quality of the asset property value.
-
-
class
greengrasssdk.stream_manager.data.
PutAssetPropertyValueEntry
(entry_id: str = None, asset_id: str = None, property_id: str = None, property_alias: str = None, property_values: List[greengrasssdk.stream_manager.data.AssetPropertyValue] = None)[source]¶ Bases:
object
Contains a list of value updates for a IoTSiteWise asset property in the list of asset entries consumed by the BatchPutAssetPropertyValue API. See https://docs.aws.amazon.com/iot-sitewise/latest/APIReference/API_BatchPutAssetPropertyValue.html.
-
entry_id
¶ The user specified ID for the entry. You can use this ID to identify which entries failed.
-
asset_id
¶ The ID of the asset to update.
-
property_id
¶ The ID of the asset property for this entry.
-
property_alias
¶ //docs.aws.amazon.com/iot-sitewise/latest/userguide/connect-data-streams.html.
Type: The property alias that identifies the property, such as an OPC-UA server data stream path (for example, /company/windfarm/3/turbine/7/temperature) For more information, see https
-
property_values
¶ The list of property values to upload. You can specify up to 10 values.
-


4 references to SafeNativeMethods
Microsoft.PowerShell.Commands.Management (4)
commands\management\Process.cs (4)
2454
SafeNativeMethods
.PROCESS_INFORMATION lpProcessInformation = new();
2746
SafeNativeMethods
.PROCESS_INFORMATION lpProcessInformation);
2759
SafeNativeMethods
.PROCESS_INFORMATION lpProcessInformation);
2955
return
SafeNativeMethods
.CloseHandle(base.handle);


|
Genetic Drone Evolution
|
#include <Network.h>
Public Member Functions | |
| Network () | |
| void | forward (const std::vector< float > &input, std::vector< float > &output) const noexcept |
| void | update () noexcept |
A Neural Network consisting of an input layer, multiple hidden layers and an output layer.
| SIZE_IN | Input dimensions |
| SIZE_HIDDEN | Hidden layer dimensions |
| SIZE_OUT | Output dimensions |
| NUM_HIDDEN | Number of hidden layers |
|
inlinenoexcept |
Feed forward the input through the Network.
| input[in] | Input vector of size SIZE_IN |
| output[out] | Preallocated vector of size SIZE_OUT to store the result in |
|
inlinenoexcept |
Modify/Overwrite the weights