The Art of Positive Bragging and Why We All Need to Embrace It
The act of disclosing information in a prideful yet sensitive way.
by Dominique Mas“I’m playing too small.”
“I want to push myself and go big.”
“I started feeling invincible but for some reason, I’ve been slowing down and playing smaller”
I’ve heard all these comments in the very first call with various clients I now coach. They are powerful leaders, entrepreneurs, real estate investors… and in response, I ask them to tell me about themselves. They tell me about their life and their previous career and inevitably, they downplay their accomplishments – and I know why.
Being a high performer can be extremely lonely. You gain others’ admiration very quickly but you often refrain from sharing your pride because it might be seen as boastful. You limit yourself so as not to offend or eclipse others. Ultimately, this means you are not living into what you’re capable of living into. This might lead to self-sabotage, downplaying your achievements, playing small or even withdrawal.
Think of the kid at school that’s being made fun of because they always get good grades. Instead of feeling proud of their creativity, their problem solving skills or their analytical thinking, they need to repress their pride, essentially to protect their peers and of course, to protect themselves from mocking comments.
Through my experience working with high performers, I have learned to recognize hidden pride and I now simply ask my clients to “brag”. No holding back! I encourage them to tell me exactly how proud they are of their accomplishments and I repeat those to them out loud. Sometimes, I even retell them their own story in the 3rd person so they can see just how unique and powerful they are and how much impact they can have on the world.
Research and interviews I’ve conducted have shown that whether bragging is considered bragging depends on the context, the environment and the eyes of the beholder so I have decided to encourage positive bragging.
What is Positive Bragging?
“If you done it, it ain’t bragging.” ― Dizzy Dean.
Research suggests that “humans […] willingly self-disclose because doing so represents an event with intrinsic value, in the same way as with primary rewards such as food and sex”. That’s right, it feels good to disclose information about ourselves!
Positive bragging is the act of disclosing information in a prideful yet sensitive way. While positive bragging is evidence-based (you can’t brag about it if you can’t prove you’ve done it), it’s definitely an art and not a science. It takes a strong dose of self-awareness, a clear understanding of your audience and a necessary shot of empathy.
Why would I want to be a bragger?
Because you are AMAZING. That’s why!
Peggy Klaus, author of Brag! The Art of Tooting Your Own Horn Without Blowing It! says that the best way to thrive in the Age of the Entrepreneur is “to start thinking like an entrepreneur and to start bragging about your most valuable product: you!”

And to go back to where we started, if you can’t own your achievements and talk about them, you simply cannot play big.
3 Simple Strategies to Master Positive Bragging
There are plenty of ways to be an artful positive bragger. I’ve chosen to highlight the three most effective.
1) START BEHIND CLOSED DOORS
There’s a ton of research out there showing that bragging makes other people feel uncomfortable, for many different reasons: from the fact that they love you and want to protect you from public opinion to the fact that you remind them of what they are not achieving.
How to brag
Find a community of other high performers that not only will allow you to brag but will actually celebrate you. When I joined Dreamers // Doers, I was delighted to see that we had a place to brag – no reason needed: Just spread joy and pride!
2) OFFER VALUE TO OTHERS
As an educator, I’m a big fan of reflection exercises. When you accomplish something big that you are particularly proud of, it’s often because you have overcome a challenge or pushed yourself to step out of what you know.
How to brag
Can you look back at your accomplishments and extract the lessons you learned along the way? How can you offer those lessons to support, inspire and encourage those around you? Own your achievements, and give back.
3) TELL YOUR STORY
We know that there is much power in storytelling. We start learning through them from the youngest age. When I asked people for input on the word “bragging” on LinkedIn and Facebook and in person, the responses all pointed to stories as a powerful way to share an accomplishment.
How to brag
Look back at how you got to this moment of pride. From the very very very beginning and craft your story, showing the process, emotions you went through as you were creating this outstanding outcome and share it with the world.
Now, as a coach, I wouldn’t be doing my job if I didn’t leave you with some questions to ask yourself! I borrowed a few from Professor Susan Whitbourne and added my own.
For the braggers:
- What are you trying to accomplish? (Remember it’s totally ok to do it because you WANT to! Just make sure it’s with those who appreciate that or you’ll just come off as arrogant!)
- What do you truly want to share? The fact or the lessons?
- How might it be of benefit to others?
For those who are bothered by bragging:
- Why are you affected by others’ bragging?
- Does it make you feel inadequate, insecure or resentful?
- What can you learn about yourself from those reactions?
I also wouldn’t be doing my job if I didn’t leave you with a challenge! Some of you will love this one and some of you will cringe and I hope you take me up on it.
Write a brag in the comments. No story, no lesson, no qualifier.
— Published on November 16, 2019


Optimizing sample sizes in A/B testing, Part II: Expected lift
10 Jan 2020In this blog post (Part II), I describe what I think is an incredibly cool business-focused formula that quantifies how much you can benefit from increasing your sample size. It is, in short, an average of the value of all possible outcomes of the experiment, weighted by their probabilities. This post starts off kind of dry, but if you can make it through the first section, it gets a lot easier.
Outcome probabilities
Imagine you are comparing two versions of a website. You currently are on version A, but you would like to compare it to version B. Imagine you are measuring some random variable \(X\), which might represent something like clicks per user or page views per user. The goal of the experiment is to determine which version of the website has a higher mean value of \(X\).
This blog post aims to quantify the benefit of experimentation as an average of the value of all possible outcomes, weighted by their probabilities. To do that, we first need to describe the probabilities of all the different outcomes. An outcome consists of two parts: A true difference in means, \(\Delta\), defined as
\[\Delta = \mu_B - \mu_A\]and an experimentally observed difference in means \(\delta\), defined as
\[\delta = \overline{X}_B - \overline{X}_A\]Let’s start with \(\Delta\). While you don’t yet know which version of the website is better (that’s what the experiment is for!), you have a sense for how important the product change is. You can therefore create a normally distributed prior on \(\Delta\) with mean zero and variance \(\sigma_\Delta^2\).
Next, let’s consider \(\delta\), your experimentally observed difference in means. It will be a noisy estimate of \(\Delta\). Let’s assume you have previously measured the variance of \(X\) to be \(\sigma_X^2\). It is reasonable to assume that within each group in the experiment, and for any particular \(\Delta\), the variance of \(X\) will still be \(\sigma_X^2\). You should therefore believe that for any particular \(\Delta\), the observed difference in means \(\delta\) will be sampled from a normal distribution \(\mathcal{N}(\Delta, \sigma_c^2)\), where
\[\sigma_c^2 = \frac{2\sigma_X^2}{n}\]and where \(n\) is the sample size in each of the two buckets. If that doesn’t make sense, check out this video.
Collectively, this all forms a bivariate normal distribution of outcomes, shown below.
To gain some more intuition about this, take a look at Figure 3. As sample size increases, \(\sigma^2_c\) decreases.
Outcome lifts
Now that we know the probabilities of all the different outcomes, we next need to estimate how much per-user lift, \(l\), we will gain from each possible outcome, assuming we follow a policy of shipping whichever bucket (A or B) looked better in the experiment.
- In cases where \(\delta > 0\) and \(\Delta > 0\), you would ship B and your post-experiment per-user lift will be positively valued at \(l = \Delta\).
- In cases where \(\delta > 0\) and \(\Delta < 0\), you would ship B, but unfortunately your post-experiment per-user lift will be negatively valued at \(l = \Delta\), since \(\Delta\) is negative.
- In cases where \(\delta < 0\), you would keep A in production, and your post-experiment lift would be zero.
A heatmap of the per-user lifts (\(l\)) for each outcome is shown in the plot below. Good outcomes, where shipping B was the right decision, are shown in blue. Bad outcomes, where shipping B was the wrong decision, are shown in red. There are two main ways to get a neutral outcomes, shown in white. Either you keep A (bottom segment), in which case there is zero lift, or you ship B where B is only negligibly different than A (vertical white stripe).
Probability-weighted Outcome Lifts
At this point, we know the probability of each outcome, and we know the post-experiment per-user lift of each outcome. To determine how much lift we can expect, on average, by shipping the winning bucket of an experiment, we need to compute a probability-weighted average of the outcome lifts. Let’s start by looking at this visually and then later we’ll get into the math.
As shown in Figure 5, if we multiply the bivariate normal distribution (left) by the lift map (center), we can obtain the probability-weighted lift of each outcome (right).
The good outcomes contribute more than the bad outcomes, simply because a good outcome is more likely than a bad outcome. To put it differently, experimentation will on average give you useful information.
To gain some more intuition on this, it is helpful to see this plot for different sample sizes. As sample size increases, the probability-weighted contribution of bad outcomes gets smaller and smaller.
Computing the expected post-experiment per-user lift
We’re almost there! To determine the expected post-experiment lift from shipping the winning bucket, we need to compute a probability-weighted average of all the post-experiment lifts. In other words, we need to sum up all the probability-weighted post-experiment lifts on the right panel of Figure 5. The formula for doing this is shown below. A derivation can be found in the Appendix.
\[\hat{L} = \frac{\sigma_\Delta^2}{\sqrt{2\pi(\sigma_\Delta^2 + \frac{2\sigma_X^2}{n})}}\]There’s three things to notice about this formula.
- As \(n\) increases, \(\hat{L}\) increases. This makes sense. The larger the sample size, the more likely it is that you’ll ship the winning bucket.
- As the within-group variance \(\sigma_X^2\) increases, \(\hat{L}\) decreases. That’s because a high within-group variance makes experiments less informative – they’re more likely to give you the wrong answer.
- As the variance prior on \(\Delta\) increases, \(\hat{L}\) increases. This also make sense. The more impactful (positive or negative) you think the product change might be, the more value you will get from experimentation.
You can try this out using the get_lift_via_closed_form
formula in the Notebook.
Demonstration via simulation
In the previous section, we derived a formula for \(\hat{L}\). Should you trust a formula you found on a random internet blog? Yes! Let’s put the formula to the test, by comparing its predictions to actual simulations.
First, let’s consider the case where the outcome is a continuous variable, such as the number of clicks. Let’s set \(\sigma_D^2 = 2\) and \(\sigma_X^2 = 100\). We then measure \(\hat{L}\) for a range of sample sizes, using both the closed-form solution and simulations. To see how we determine \(\hat{L}\) for simulations, refer to the box below.
Procedure for finding \(\hat{L}\) with simulations
Loop through thousands of simulated experiments. On each each experiment doing the following:
- Sample a true group difference \(\Delta\) from \(\mathcal{N}(0, \sigma_D^2)\)
- Sample an \(X\) for each of the \(n\) users in each bucket A and B, using Normal distributions \(\mathcal{N}(\frac{\Delta}{2}, \sigma_X^2)\) and \(\mathcal{N}(-\frac{\Delta}{2}, \sigma_X^2)\), respectively.
- Compute \(\delta = \overline{X}_B - \overline{X}_A\).
- If \(\delta <= 0\), stick with A and accrue zero lift.
- If \(\delta > 0\), ship B and accrue the per-user lift of \(\Delta\), which will probably, but not necessarily, be positive.
We run these experiments thousands of times, each time computing the per-user lift. Finally, we average all the per-user lifts together to get \(\hat{L}\). See the get_lift_via_simulations_continuous function in the notebook for an implementation.
As seen in Figure 7, below, the results of the simulation closely match the closed-form solution.
Second, let’s consider the case where the variable is binary, as in conversion rates. For reasonably large values of \(n\), we can safely assume that the error variance is normally distributed with variance \(\sigma_X^2 = p(1-p)\), where \(p\) is the baseline conversion rate. For this example, let’s set the baseline conversion rate \(p = 0.1\), and let’s set \(\sigma_\Delta^2 = 0.01^2\). The results of the simulation closely match the closed-form solution.
Thinking about costs, and a preview of Part III
In this blog post, we saw how increasing the sample size improves the expected post-experiment per-user lift, \(\hat{L}\). But to determine the optimal sample size, we need to think about costs.
The cost in dollars of an experiment can be described as \(f + vn\), where \(f\) is a fixed cost and \(v\) is the variable cost per participant. If you already know these costs, and if you already know the revenue increase \(u\) from each unit increase in lift, you can calculate the net revenue \(R\) as
\[R = u\hat{L} - f - vn\]and then find the sample size \(n\) that maximizes \(R\).
Unfortunately, these costs aren’t always readily available. The good news is that there is a really nice way to calculate the most important cost: the forfeited benefit that comes from prolonging your experiment. To read about that, and about how to optimize your sample size, please continue to Part III.
Appendix
To determine \(\hat{L}\), we start with the probability-weighted lifts on the right panel of Figure 5. This is a bivariate normal distribution over \(\Delta\) and \(\delta\), multiplied by \(\Delta\).
\[f(\Delta, \delta) = \frac{\Delta}{2 \pi \sigma_\Delta \sigma_\delta \sqrt{1-\rho^2}} e^{-\frac{ \frac{\Delta^2}{\sigma_\Delta^2} - \frac{2 \rho \Delta \delta}{\sigma_\Delta \sigma_\delta} + \frac{\delta^2}{\sigma_\delta^2} }{2(1-\rho^2)} }\]where the correlation coefficient \(\rho\), is defined as:
\[\rho = \sqrt{1 - \frac{\sigma_c^2}{\sigma_\Delta^2 + \sigma_c^2}}\]and \(\sigma_\delta^2\) is the variance on \(\delta\). By the variance addition rules, \(\sigma_\delta^2\) is defined as
\[\sigma_\delta^2 = \sigma_\Delta^2 + \sigma_c^2\]We next need to sum up the probability-weighted values in \(f(\Delta, \delta)\). To obtain a closed form solution, we can use integration.
\[\hat{L} = \int_{0}^{\infty} \int_{-\infty}^{\infty} {\frac{\Delta}{2 \pi \sigma_\Delta \sigma_\delta \sqrt{1-\rho^2}} e^{-\frac{ \frac{\Delta^2}{\sigma_\Delta^2} - \frac{2 \rho \Delta \delta}{\sigma_\Delta \sigma_\delta} + \frac{\delta^2}{\sigma_\delta^2} }{2(1-\rho^2)} } \,d\Delta\,d\delta }\]The integration limits on \(\delta\) start at zero because the lift will always be zero if \(\delta < 0\) (i.e if the status quo bucket A wins the experiment).
Thanks to my 15-day free trial of Mathematica, I determined that this integral comes out to the surprisingly simple
\[\hat{L} = \rho \frac{\sigma_\Delta}{\sqrt{2\pi}}\]The command I used was:
Integrate[(t / (2*\[Pi]*s1*s2*Sqrt[1 - p^2]))*Exp[-((t^2/s1^2 - \
(2*p*t*d)/(s1*s2) + d^2/s2^2)/(2*(1 - p^2)))], {d, 0, \[Infinity]}, \
{t, -\[Infinity], \[Infinity]}, Assumptions -> p > 0 && p < 1 && s1 > \
0 && s2 > 0]
If we then substitute in previously defined formulas for \(\rho\) and \(\sigma_c^2\), we can produce a formula that accepts more readily-available inputs.
\[\hat{L} = \frac{\sigma_\Delta^2}{\sqrt{2\pi(\sigma_\Delta^2 + \frac{2\sigma_X^2}{n})}}\]Continue to Part III.


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What is Purrfect Match?
Our job here on Purrfect Match is to find you a pet that perfectly matches your character. At first you will take a test which will make is easier for us, to find you the perfect little friend. Your test will be analyzed from our specialist, which then will choose the perfect pet for you based on your results. You will then (in the following weeks) get diffrent pictures and descriptions from diffrent animals. After you decided what animal it should be, you can come and pick it up in the Purrfect Match center that is closest to you.


|
libpqxx
4.0.1
|
Classes | |
| class | pqxx::connect_direct |
| Connection policy; creates an immediate connection to a database. More... | |
| class | pqxx::connect_lazy |
| Lazy connection policy; causes connection to be deferred until first use. More... | |
| class | pqxx::connect_async |
| Asynchronous connection policy; connects "in the background". More... | |
| class | pqxx::connect_null |
| Nonfunctional, always-down connection policy for testing/debugging purposes. More... | |
| class | pqxx::connectionpolicy |
Typedefs | |
| typedef basic_connection < connect_direct > | pqxx::connection |
| The "standard" connection type: connect to database right now. | |
| typedef basic_connection < connect_lazy > | pqxx::lazyconnection |
| A "lazy" connection type: connect to database only when needed. | |
| typedef basic_connection < connect_async > | pqxx::asyncconnection |
| "Asynchronous" connection type: start connecting, but don't wait for it | |
| typedef basic_connection < connect_null > | pqxx::nullconnection |
| A "dummy" connection type: don't connect to any database at all. |
The connection classes are where the use of a database begins. You must connect to a database in order to access it. Your connection represents a session with the database. In the context of that connection you can create transactions, which in turn you can use to execute SQL. A connection can have only one regular transaction open at a time, but you can break your work down into any number of consecutive transactions and there is also some support for transaction nesting (using the subtransaction class).
Many things come together in the connection classes. Handling of error and warning messages, for example, is defined by errorhandlers in the context of a connection. Prepared statements are also defined here.
Several types of connections are available, including plain connection and lazyconnection. These types are typedefs combining a derivative of the connection_base class (where essentially all connection-related functionality is defined) with a policy class which governs how the connection is to be established. You pass details such as the database you wish to connect to, username and password, and so on as as PostgreSQL "connection string" and certain environment variables that you can learn more about from the core postgres documentation.
See the connection_base documentation for a full list of features inherited by all connection classes. Connections can be deactivated and reactivated if needed (within reason, of course–you can't do this in the middle of a transaction), and where possible, disabled or broken connections are transparently re-enabled when you use them again. This is called "reactivation," and you may need to understand it because you'll want it disabled in certain situations.
You can also set certain variables defined by the backend to influence its behaviour for the duration of your session, such as the applicable text encoding. You can query the connection's capabilities (because some features will depend on the versions of libpq and of the server backend that you're using) and parameters that you set in your connection string and/or environment variables.
| typedef basic_connection<connect_async> pqxx::asyncconnection |
"Asynchronous" connection type: start connecting, but don't wait for it
| typedef basic_connection<connect_direct> pqxx::connection |
The "standard" connection type: connect to database right now.
| typedef basic_connection<connect_lazy> pqxx::lazyconnection |
A "lazy" connection type: connect to database only when needed.
| typedef basic_connection<connect_null> pqxx::nullconnection |
A "dummy" connection type: don't connect to any database at all.


--- layout: post date: 2010-06-10 time: "11:00:00" authors: ["Greg Wilson"] title: The Big Picture (version 3) tags: ["Content"] ---
Version 3 of the concept map describing what we mean by "computational thinking" incorporates feedback from several people—thanks for sending it. Please let us know what you think...


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Issue 3042: Show syntax error position like in error console of Firefox
Steps to reproduce
- Open Firebug
- Enable and switch to the Console panel
- Reload the page
Expected result
- A syntax error should be listed inside the console having an indicator for the column where the error occurred


An R package to generate palettes based on famous paintings from the Rijksmuseum, using the fantastic Rijksmuseum API.
# Install the development version:
devtools::install_github("vankesteren/rijkspalette")
Let’s make a barplot using a palette based on Vermeer’s famous painting of a woman reading a letter. The rijksPalette()
function queries the collection of paintings of the Rijksmuseum in Amsterdam.
library(rijkspalette)
letter <- rijksPalette("Vermeer Letter")
letter
A 16-bit impression of the palette is shown in the R
console.
Let’s look at the palette a bit better:
plot(letter)
Now we can make a plot using the palette from these colours.
barplot(iris$Sepal.Length,
col = letter$palette(3)[iris$Species],
border = NA, space = 0,
main = "Sepal length of 3 iris species")
Note that the palette()
function performs interpolation: you can generate any number of colours!
barplot(rep(1, 1500),
col = letter$palette(1500),
border = NA, space = 0,
axes = FALSE, asp = 1)
Try it out for yourself! Post your palette on twitter with the #rijkspalette
hashtag 👍
The palette works well for the above image. However, when a painter uses many colours, some prominent colours may be skipped:
appel5 <- rijksPalette("Karel Appel")
plot(appel5)
Here, the quite prominent red colour is skipped. Luckily, we can tune both the number of colours and the brightness of those colours:
appel7 <- tune(appel5, brightness = 0.85, k = 7)
plot(appel7)
That’s better. But why? The explore()
function can give us more detail:
explore(appel)
Here, we see the colours in the image plotted on the a*b*
space. The white squares are the cluster centroids used to generate the palette. Note that the two quite distinct arms in the top of the plot belong to the same cluster. By increasing the number of clusters (the number of colours in the palette), we can fix this issue:
The better coverage of the colour space indicates that 7 clusters is better than 5. The k
argument in the tune()
function takes care of that.
To access the individual colours, use the cols
slot:
appel$cols
[1] "#A8402D" "#969D4C" "#B5BDAC" "#7D817A" "#336D7F" "#235B6D" "#303344"
As before, the palette
slot is a colorRampPalette
function to be used in plots:
barplot(1/sqrt(1:15), col = appel$palette(15))


Recent projects:
I. Machine Learning
Interest rates predictions
This project aims to predict the base interest rates in Australia, US, and UK in the coming months. I demonstrate a complete cycle in Machine Learning and Data Engineering project, including an ETL process to collect and transform data from different data sources. The data is then stored in Azure Storage and is used for model development. The model is then deployed and served as a web service, which pushes the prediction results onto a Github page for visualization.
Data pipelines and architecture
Modelling baseball players’s performance
This work is supported by Google Summer of Code project, which adds support for Multi-output Gaussian processes in PyMC.
We model the performances of different sport players by leveraging Multi-output Gaussian processes (MOGPs), which can simultaneously learn and infer many outputs with the same source of uncertainty. The following picture shows the estimated sprin rates of three top pitchers in different game dates. Please check the PyMC example for further details.
Aussie Social Sentiment Analysis
This project collects data from Twitter’s APIs, then cleans and stores in a sql database. The data is then used for model training and prediction of sentiment analysis for other tweets. The webapp uses Dash visualisations and is deployed on Herokuapp.
II. MLOps & Data Engineering
Accelerating testing CI pipelines
Continuous Integration - Continuous Development (CI/CD) plays an essential role in MLOps and DataOps. One of the popular CI/CD tools is GitHub Actions. To enhance CI/CD pipelines, we can use the matrix strategy in GitHub Actions to run parallel tasks.
For example, I have recently leveraged the strategy.matrix
feature to significantly accelerate the testing CI pipelines for PyTensor from 75 mins to around 26 mins (a 65% reduction in running time). Please check this pull request for further details.
Building Docker images for PyMC
I have built a docker file for PyMC v4, which support both GPUs and CPUs version. The dockerfile has been merged into PyMC project’s code base in this pull request.
The docker image is then published on Docker Hub, so users can easily pull the image and set up their environment.
III. Data Science
Data Visualisation: Melbournian Daily Activities
This project visualises the daily activities of Melbournians in different areas.
Domain Scenery Views - Telegram Bot
A Telegram bot in Python, which will automatically push the top listings into the Domain channel on Telegram each day. The top listings show properties with the most beautiful views like beaches, lakes, and city views in Australia cities. Customers can join Domain Scenery Views channel on Telegram to receive the news.
For more projects, please check my github@danhphan.


My Shop Lot, Shopping Mall, Post Code, City
Thank you! See you again.
Please don't forget to disble the header and footer in browser print settings.
Firefox: File > Print Setup > Margin & Header/Footer Make all --blank--
Chrome: Menu > Print > Disable Header/Footer in Option & Set Margins to None


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import config.ApplicationConfig @this(govukErrorSummary : GovukErrorSummary, govukDetails : GovukDetails, govukRadios : GovukRadios, govukButton : GovukButton, mainLayout: views.html.mainLayout, formWithCSRF: FormWithCSRF, govukInsetText: GovukInsetText, govukWarningText: GovukWarningText) @(agentName: String, agentCode: Long, chosenListYear: String, backLink: String)(implicit request: Request[_], messages: Messages, config: ApplicationConfig) @invalidListYear = @{if (chosenListYear.equals("2023")) "2017" else "2023"} @mainLayout( backUri = Some(backLink), pageTitle = messages("ratingsListConfirmation.header", agentName, chosenListYear)) {
@messages("ratingsListConfirmation.thisAgentWill", chosenListYear)
@messages("ratingsListConfirmation.theyWillNot", invalidListYear)
@govukWarningText(WarningText( iconFallbackText = messages("warning.text"), content = Text(messages("ratingsListConfirmation.restricting")))) @formWithCSRF(action = controllers.manageAgent.routes.AreYouSureController.submitRatingListYears(chosenListYear)) { } }


'Various failures' in Bolivian election: incoming EU diplomacy chief
MADRID (Reuters) - The European Union’s incoming foreign policy chief, Josep Borrell, said on Monday that Bolivia’s Oct. 20 election results could not be validated, citing a report that pointed to various failures amounting to more than just “simple irregularities.”
Violent clashes erupted in the Bolivian capital of La Paz after Evo Morales, the country’s president since 2006, resigned on Sunday under pressure over a disputed election last month.
A report from the Organization of American States (OAS) released early on Sunday said the Oct. 20 election should be annulled and a new vote held after it had found “clear manipulations” of the voting system that called into question the win by Morales.


Krept & Konan discuss dealing with trauma: “These things affect us but we act like it’s normal”
“Where we’re from, we’re meant to just get on with things”
Krept & Conan have opened up about dealing with depression, trauma and suicidal thoughts in a new interview.
Alongside Ramz, who also features on the duo’s new album ‘Revenge Is Sweet’, the group spoke to The Guardian about their own battles with mental health and the impact they’ve seen it have on people close to them.
“Our friend did actually kill himself, and it affected us seriously,” Konan said. “Ramz is our peoples and he’s going through the same situation, and we don’t want him to go down that path. He’s getting help now.”
Ramz claims he had never suffered from mental health problems before last year.
Krept
“People were saying stuff online… I couldn’t even write. So I stopped making music, didn’t go to the studio any more. I was just staying at home, not doing anything.” Krept says that he and Konan have also struggled to deal with negativity on the internet: “People not giving us the dues, people cussing us online, people giving us hate. It’s affecting our mental health.”
Ramz also spoke about the day he seriously considered suicide, posting a hangman image on Instagram and running into the road. “On the day when I posted the picture I was in my car,” he said. “I turned off my phone and everything so no one could get a hold. I said to myself: ‘If no one comes in a certain time I’m going to kill myself.’ I’m not even lying. The ambulance came, the police came.”
The rapper said he’s now receiving therapy, but still finds it difficult to return to: “I don’t even want to be there, it just brings back bad memories. I just feel like I’m a different person.”
In a four-star review of Revenge Is Sweet, NME said: “These two rap entrepreneurs have proven that it was worth the wait for another studio album. The years between ‘Revenge Is Sweet’ and their debut ‘Long Way Home’ have been fruitful for the duo, but – for all their dabbling – this is a welcome return to their roots.”


About Me
My name is William Molhoek. I am a student at the Coding Bootcamp through the U of M. Some of my hobbies include hiking, hammocking and listening to music. I love the outdoors and take any chance I get to be outside.
I love working with Habitat for Humanity, I have done two trips to North Carolina and Colorado to help build houses and any other projects they need help with.


MA in Computational Linguistics
The Graduate Center, CUNY New York, NYThesis: Infixer: A Method for Segmenting Non-Concatenative Morphology in Tagalog
Coursework in natural language processing, statistics, and theoretical linguistics. Areas of interest include morphological segmentation, low-resource languages, machine learning, and language modeling.


IN THE HIGH COURT OF PUNJAB AND HARYANA AT CHANDIGARH. CWP No. 5915 of 2011 Date of Decision: January 10, 2012 M/s East India Cotton Manufacturing Company Limited ...Petitioner Versus State of Haryana and others ...Respondents CORAM: HON'BLE MR. JUSTICE M.M. KUMAR KUMAR HON'BLE MR. JUSTICE AJAY KUMAR MITTAL Present: Ms. Bhavna Joshi, Advocate, for the petitioner. Mr. Kuldeep Singh, Advocate, for Mr. Gaurav Singh Hooda, Advocate, for respondent Nos. 2 and 3. 1. To be referred to the Reporters or not? 2. Whether the judgment should be YES reported in the Digest? M.M. KUMAR, J.
1. This petition filed under Article 226 of the Constitution prays for issuance of direction to the respondents to implement the rehabilitation scheme, dated 10.1.2007 (P-5), which has been sanctioned by the Board for Industrial and Financial Reconstruction (for brevity, 'BIFR'). The petitioner Company has also challenged order dated 13.9.2000 (P-1), passed by the Assessing Authority for Cess-cum-Member Secretary, Haryana State Board for Prevention and Control of Water Pollution, under Section 11 of the Water (Prevention and Control of Pollution) Cess Act, 1977 (for brevity, 'the Cess Act') raising the demand of `8,16,851/- on account of Water Cess payable by the petitioner, imposing the penalty of CWP No. 5915 of 2011 2 equivalent amount as well as interest of `7,49,418/-, total of which comes to `23,82,120/-. The order dated 15.3.2011 (P-4), passed by the Appellate Authority, dismissing the appeal preferred by the petitioner Company under Section 13 of the Cess Act against the order dated 13.9.2000, has also been challenged. Still further, the communication dated 20.4.2010 (P-8) has also been challenged whereby it has been asked to make payment of the outstanding amount of `23,83,120/- before the sale of surplus assets of the petitioner Company and to avoid action under the Cess Act.
2. The undisputed facts of the case are that the petitioner Company is engaged in the business of processing of textiles, having its processing unit at Faridabad. Due to recession in the international market, it started incurring losses and in the year 1996 an application under Section 25-N of the Industrial Disputes Act, 1947, was filed before the Specified Authority-cum-Joint Labour Commissioner, Haryana, seeking permission to retrench surplus 991 workmen out of 2163 workmen, which was allowed. Another application under Section 15(1) of the Sick Industrial Companies (Special Provisions) act, 1985 (for brevity, 'SICA') was filed before the BIFR. On 4.10.1996, the petitioner Company was declared as a sick industrial company in terms of Section 3(1)(o) of SICA.
3. It has been claimed that despite the complete lock out in the factory and the fact that w.e.f. 12.9.1996 the workers' union took forceful possession of the plant, machinery and office of the petitioner Company, it continued to pay water cess from 1993 to 1996 at the rate of `85,000/- on actual consumption basis. However, on 13.9.2000, the Assessing Authority of the respondent Haryana State Pollution Control Board-respondent No. 2, exercising CWP No. 5915 of 2011 3 the powers under Sections 10 and 11 of the Cess Act, raised the total demand of `23,83,120/-, which includes Water Cess, penalty and interest (P-1). Feeling aggrieved, the petitioner Company filed an appeal on 11.10.2000 under Section 13 of the Cess Act, for setting aside the order dated 13.9.2000. It was specifically highlighted in the appeal that since the petitioner Company has been declared as a sick company by the BIFR on 4.10.1996, therefore, as per Section 22 of the SICA no recovery could be effected from it without seeking prior permission from BIFR. It was further stated that even the assets of the Company could not be disposed of or alienated without the permission of the BIFR (P-2). The Appellate Authority, however, dismissed the appeal on merit, vide order dated 15.3.2001 (P-4). With regard to the fact that the matter was pending before BIFR and that the petitioner Company has been declared as a sick company, the Appellate Authority in the concluding para of its order made the following observations:-
" However, the point raised by the company, that the dues are not recoverable after their cases has been registered with BIFR, may be examined by the Assessing Authority. The appellant also raised the issue, that when the case is registered with BIFR, it is wrong to impose penalty or charge interest and also the lodge proceedings under Land revenue Act for recovery of dues. The Assessing Authority will look into the matters at his own level and take suitable action. The appeal does not lie in this case."
4. It is, thus, evident that the Appellate Authority under the Cess Act has left it open for the Assessing Authority to apply his CWP No. 5915 of 2011 4 mind on the aforementioned issue and take a decision by examining the issue at his own level.
5. On 10.1.2007, the matter before BIFR came up for consideration and after considering the suggestions and rival contentions of the parties, a rehabilitation scheme under the provisions of Section 19(3) read with Section 18(4) of the SICA was finalised, which has been placed on record (P-5). The respondent Nos. 2 Board was a party before the BIFR. The representative of the respondent No. 2 Board, namely, Shri P.K. Sharma, was present during the proceedings. In para 12 of the order dated 10.1.2007, it has been specifically directed that the various Government and statutory authorities including Haryana State Pollution Control Board would reassess their demands after taking into account the period for which the petitioner Company had remained closed.
6. In para 13 of the petition, the petitioner Company has given the details of debts/liabilities which have been discharged by it when the proceedings were pending before the BIFR and even thereafter. The respondents, however, did not accept in principle that the rehabilitation scheme prepared by the BIFR was the rehabilitation scheme finalised by the BIFR (P-6 Colly). The petitioner Company also applied under the Right to Information Act, 2005 for supplying the reasons for not implementing the directions of the BIFR (P-7). On 20.4.2010, a reply has been sent by respondent No. 3 stating that there is no provision to waive the interest/penal charges for default or non-payment of any dues under the Cess Act (P-8). Faced with the action of the respondents, the petitioner Company has filed the instant petition.
7. In the written statement filed on behalf of respondent CWP No. 5915 of 2011 5 Nos. 2 and 2 there is no denial of the factual position. It has been reiterated that there is no provision in the Cess Act for waiving off the water cess as claimed by the petitioner Company. The BIFR has made only a recommendation which is not binding upon them. It has been specifically admitted that no appeal against the order dated 10.1.2007 (P-5), passed by the BIFR has been filed by respondent Nos. 2 and 3.
8. We have heard learned counsel for the parties at length and perused the paper book with their able assistance. It is a conceded position that the petitioner Company has been declared as a sick company by BIFR on 4.10.1996 under the provisions of Section 3(1)(o) of SICA. Eventually, vide order dated 10.1.2007, the BIFR has also formulated a rehabilitation scheme for revival of the petitioner company, which has been duly approved in the presence of representatives of various parties including the respondent Pollution Control Board. In para 12 of the order dated 10.1.2007, BIFR has specifically issued directions to various Government and statutory authorities including the respondent Pollution Control Board that they would reassess their demands after taking into account the period for which the petitioner Company had remained closed. In para 7(B)(x) of the rehabilitation scheme, in respect of the dues of the State Government of Haryana and its agencies, the following proposal has been approved by BIFR:-
"x) STATE GOVERNMENT OF HARYANA
a) To declare the company as a "Relief Undertaking" and grant all benefits and concessions as per the State Government's policy guidelines for sick industrial units.
b) To accept the payment of power charges based on CWP No. 5915 of 2011 6 actual consumption of power for August & September, 1996 i.e. till the company was in operation, after adjustment of the security deposit lying with them. The payment shall be made over a period of twelve months from the date of sanction of scheme on interest free basis and to waive the entire minimum demand charges, slow meter charges, late payment surcharge, interest, penalty meter rent, meter charge or any other charges etc.
c) To accept the payment of water cess as based on actual discharge till the company was in operation, as per past average. The payment shall be made over a period of twelve months from the date of sanction of the scheme and to waive the entire interest, penalty etc.
d) To waive interest/penal interest/penalty/damages etc. for the defaults or for non-payment or for delayed payment of any dues payable to the State Govt." (emphasis added)
9. Once the rehabilitation scheme has been approved by BIFR in the presence of the representative of the respondent Pollution Control Board and it is their own admitted case that no appeal against the order dated 10.1.2007 passed by BIFR has been filed before the Appellate Authority for Industrial and Financial Reconstruction (for brevity, 'AAIFR') by the respondent Pollution Control Board, then the rehabilitation scheme would be binding on all the parties before the BIFR. We find no force in the argument raised on behalf of the respondent Pollution Control Board that the rehabilitation scheme is not binding on them and there is no CWP No. 5915 of 2011 7 provision in the Cess Act for waiving off the penalty and interest.
10. Even otherwise once a company is before the BIFR, Section 22 of SICA would come in operation. It would be profitable to reproduce the relevant part of Section 22 of SICA, which reads thus:-
"22.
22. Suspension of legal proceedings, contract, etc.-
etc.
(1) Where in respect of an industrial company, an inquiry under Section 16 is pending or any scheme referred to under Section 17 is under preparation or consideration or a sanctioned scheme is under implementation or where an appeal under Section 25 relating to an industrial company is pending, then, notwithstanding anything contained in the Companies Act, 1956 (1 of 1956), or any other law or the Memorandum and Articles of Association of the industrial company or any other instrument having effect under the said Act or other law, no proceedings for the winding up of the industrial company or for execution, distress or the like against any of the properties of the industrial company or for the appointment of a Receiver in respect thereof and no suit for the recovery of money or for the enforcement of any security against the industrial company or of any guarantee in respect of any loans or advances granted to the industrial company shall lie or be proceeded with further, except with the consent of the Board or, as the case may be, the Appellate Authority." (emphasis added)
11. A perusal of the aforesaid provision would show that CWP No. 5915 of 2011 8 where in respect of an industrial company, amongst other things, a sanctioned scheme is under implementation then notwithstanding anything contained in any other law, no proceedings for execution, distress or the like against any of the properties of the industrial company or for the appointment of a Receiver in respect thereof and no suit for the recovery of money or for the enforcement of any security against or of any guarantee in respect of any loans or advances granted to the industrial company is to lie or be proceeded with further except with the express permission of the BIFR or AAIFR as the case may be. The aforesaid provision came up for consideration before Hon'ble the Supreme Court in the case of Rishabh Agro Industries Ltd. v. P.N.B. Capital Services Ltd., Ltd., (2000) 5 SCC 515.
515 It was held that for successfully invoking the applicability of Section 22 of SICA, it has to be established that a sanctioned scheme is under implementation and it could not be said that despite the aforesaid situation the provisions of Section 22 would not be attracted (See para 9). Therefore, it is evident that the BIFR has permitted respondent Nos. 2 and 3 to accept the payment of water cess as based on actual discharge till the company was in operation as per past average. The payment has to be made over a period of 12 months from the date of sanction of the scheme and to waive the entire interest, penalty etc. This aspect has also been highlighted by the Appellate Authority in its order dated 15.3.2011 (P-4) although it has been left to the wisdom of the Assessing Authority. Accordingly, we find that the relief claimed by the petitioner is meritorious and deserves to be accepted even on this additional ground.
12. As a sequel to the above discussion, this petition CWP No. 5915 of 2011 9 succeeds. The impugned order dated 13.9.2000 (P-1) passed by the Assessing Authority is set aside. The respondents are directed to implement the rehabilitation scheme in so far it concerns them and, as approved by the BIFR, vide order dated 10.1.2007 (P-5). The needful shall be done within a period of one month from the date of receipt of a copy of this order.
(M.M. KUMAR) JUDGE (AJAY KUMAR MITTAL) January 10, 10, 2012 JUDGE PKapoor


| DOSE: |
150 ug |
oral |
LSD |
(blotter / tab) |
| |
0.2 g |
smoked |
Cannabis |
(plant material) |
I was prompted to submit this report after reading of an experience which seemed similar in some respects, pertaining to the fractal patterns.
I had obtained a tab of LSD from a friend of a flatmate, and I was able to choose from which part of the sheet my tab would be cut.
The picture printed on the sheet was of a Dali painting, 'Torero Alucinogeno', or 'Hallucinogenic Bullfighters', and the sheet seemed to have been unevenly scored, so that a lot of the squares were of an uneven size. Thus I chose one of the largest available squares, which happened to coincide with the part of the picture where a uniform field of flies disappears into perspective. This was the first time I had taken LSD from this batch, although I had taken acid from other manufacturers on 6 other occasions.
I should note that I had been smoking hydroponic skunk fairly regularly (1g per day average), and I could feel the effects of the various cannabinoids near constantly, although I had not smoked that day.
I put the tab under my tongue, and sat on the front porch of my flat, talking with two other flatmates for about 20 minutes, until I decided I would like to go for a skate. I'm careful to avoid planning out a night using psychedelics, I like to be free to follow ideas as they come to me. I retrieved my camera bag (I've found that it's best to keep things like keys, change, stash, lighter etc all together, and my ABC is to Always Bear a Camera!) and skateboard and skated off down the road.
I found immediately that my balance was slightly better than normal, and I could adjust my weight distribution very exactly, close enough to almost ride on the back two wheels (a manual). This may not sound amazing, but I skate only for travel and adrenaline, and I skate very basically, one foot on the board all the time, and the other pushes now and again. I enjoyed the ride until I got into the inner city, and the smell of cars became stronger. There were drifts of fast food wrappers everywhere, and I knew that I had to keep moving and get past the city centre, as I felt rising disgust at the drunken hordes, shambling animals looking for food/a fight/a root. Each to their own, I thought as I dodged a drifting Coke cup.
I threw my skateboard over the Botanic Gardens fence, and immediately regretted making so much noise. I jumped the fence and wandered slowly towards the trees, marvelling at their size and complexity, and the strength of their frames.
I began to notice more and more hallucinations very soon, some of the trees appeared to me as groups of bearded dog-like creatures, leaning down towards me. I found concrete to be too harsh on my bare feet (I had stashed my skateboard and shoes safely, as I had done in the past) and I moved from the path to the grass of the archery lawn. As I walked between the two rows of tall trees I felt coldness lapping at my feet, and I became convinced that I was walking in two inches of water. I looked at my feet for a minute, and they seemed to be covered in darkness up to the ankles. I had to put my hands down into the shadow to realise that it was only shadow, not water.
I kept moving through the gardens, without direction, idly observing the forms and hallucinations, until I realised that I hadn't had a drink all day, and I was becoming somewhat dehydrated. I started searching in vain for a drinking fountain, slowly getting more and more agitated when one wasn't right around the corner. I felt worried, as some part of me knew that there were at least six drinking fountains spread throughout this half of the gardens (which span about 10 acres), and yet I couldn't find one!
I began to feel despair, and sat down. Then I noticed a light far away, and felt compelled to walk towards it. It was very dark, but I could see better as I walked onwards, until I started to recognise parts of the gardens I had been through earlier. I skirted the archery lawn and continued towards the light.
I stopped some distance from the light, and looked around. As my eyes adjusted and chased away the retinal ghosting I realised that I could hear water running . . . I looked to my right and saw a drinking fountain, continually running. Christchurch is built on a series of artesian wells, and if you dig and hit a spring the cleanest water in the world flows continually out.
I knelt down by the stone fountain and drank deeply.
From there I moved to a small hill in the centre of a ring of very tall pine trees, and lay between a two large oblong plates set in the ground, one white, one black.  As I smoked it I felt a bubble expanding in my lungs, pressing upon my throat, sliding into my head.
The bubble grew, spreading through my limbs, and slowly through my brain. It seemed to stop, completely filling me with gentle pressure, until I felt what seemed like a drop of water on the very top of my head. It was almost like there was suddenly a hole on my 7th chakra, and what had just filled my body was flowing out, running over my skin, spreading to envelope the grass, trees and bushes until it was an even field which was still a part of me.
I lay back, and watched the stars slowly circle and the trees sway. After a time it seemed as though the trees were fractal generations, a single line splitting and multiplying until it merges with the air, taking air and water and spreading to continue the formula. The stars also seemed to be carefully arranged in patterns spelling out the flow of gravity and expansion. I was still hallucinating myriad faces in the clouds, and they started to become larger and talk more actively, smiling and communicating with each other, although I was unclear as to what they were saying. They seemed to merge until there was just one face, as large as one a few feet away from me. She (I'm very sure that the face was feminine) laughed once, before I looked too closely in wonder and the clouds were clouds again.
Many other visions came to me during that time, many of which I can't recount with language written or spoken. However, one thing that really stood out was a the feeling that light was hitting me with energy that I could perceive as groups of particles. I could see the grain of light, except on sources of light or direct reflections where it blended into the image. I felt at the time that this was more than a visual illusion, as I know that the human eye is sensitive enough to register single photons.
Particles moving in waves, the theory actually meant something!
My photography has since come a long way, I can now explore optical oddities and tools with a greater understanding of the underlying physics. This experience and the mental exploration over the next few days gave me insight into things I would otherwise have never found. I'm now studying for a degree in Physics, and I hope to follow on with String theory study.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


'Mark my words' - Newcastle United fans make Aston Villa claim
Aston Villa v Newcastle United | Magpies fans have been discussing the Premier League meeting between the two sides on Monday night as they prepare to do battle in B6
by Richard CusackNewcastle United fans have revealed who they want to see in defence for Monday night's Premier League clash with Aston Villa.
Fabian Schar and Florian Lejeune are both back available for selection and could start the match, with Jamaal Lascelles and former Villan Ciaran Clark both out injured.
Matt Ritchie will miss the game as he continues his recovery from an injury picked up in the Carabao Cup clash with Leicester City earlier this season.
French defender Lejeune is on the comeback trail from a knee injury suffered in April 2019 and he could make his first appearance of the season at Villa Park while Schar has missed the last three League games.
Aston Villa latest
This is your round up of all things Villa; the one-stop shop that will keep you updated on the latest goings on at the club and beyond.
Transfers, injuries, match-days and managers, we’ve got you covered.
We’ll be bringing the very latest on the Villains throughout the week and around the clock.
Make sure you keep yourself updated with our handy daily catch up...
Must reads...
- Director reveals John McGinn's reaction to failed transfer
- Martin Keown fires puzzling criticism at Tyrone Mings
- What Jarrad Branthwaite has said about Villa interest
- Dean Smith urged to have a 'quiet word' with Frederic Guilbert
For all your latest AVFC news, opinion, analysis and transfer gossip, click here
You can follow our Villa reporter Ashley Preece on Twitter, and his email address is<EMAIL_ADDRESS>And Newcastle fans have had their say on how they would line up the defence for the trip to the West Midlands .
Here's the pick of the reaction on social media...
Danzo Sean Johnston : Yes! Good news! Solid big CB not scared of challenge either and very good in the air him Clark schar back since lacsclles is out
Leigh Bendelow : Schar lascelles lejeune our best 3 personally
Mattie Jeffels : Glad to see him back. Him, Schar and Fernandez at the back and we’re sorted.
Josh Tambakis-Brown : Have Schar and Lejeune played together? That has the makings of a really good CB partnership.
David Milburn : Has to be the best defender on the books its just been so unfortunate that he has been dogged with injuries & some have been caused by bad tackles from apposing players which makes it all the worse for the lad but it will be great to see him back has to make the defence even stronger.
Daniel Edwards: Better than lascelles imo. Solid addition.
Alex Jennings : Lascelles ain’t getting his place back, mark my words


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Clinical Assistant Professor of Computer Science at the Courant Institute of Mathematical Sciences at New York University.
Junior studying Math and CS at Courant. Having started to code only after she arrived at NYU, she's is excited to mentor new members that may not know how to make their ideas translate into tangible code based projects!
Senior studying Computer Science in CAS. Originally from Tanzania, Nadira loves travelling, scuba diving and wildlife. She's excited to learn and teach open source principles and in turn make exciting and impactful contributions.
Californian studying Biology on the pre-med track, with three minors, and loves both carbon based life and silicon based life to equal extents.
Sophomore from Singapore majoring in Computer Science and Business. He likes reading, writing, coding, and gaming.
Junior from Woodmere, New York studying Computer Science with interests in sports and traveling
Freshman studying Computer Science in CAS. She loves to talk about code with other people. In her free time, Veena goes to the gym, makes jewelry, and plays card games.
Freshman from California studying Computer Science and Economics. In her free time, she loves spending time with family, running, and of course, coding!


Data sources: Associated Press, Minnesota Secretary of State, Star Tribune analysis. Winner calls made by the Associated Press and the Star Tribune.
Credits: Alan Palazzolo, C.J. Sinner, Chase Davis


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Beautiful moments in Minamiuonuma,Japan.
It's just amazing.
We are part of nature.
The more we live in harmony with nature, The better we live well.
And we have the power of choise for our lifestyle.
Nature gives humans creativity.
In history, humans got ideas from nature, accumulated knowledge, and developed technology.
Technology is essential to establish this modern civilization.
Humans get inspired art and design of nature. Nature gives us the sense of beauty, this is amazing.
It's always nice to enjoy the gift from nature. Color, patterns, space, moves, any aspects of nature
gives us ideas and makes us think richer.
Nature also might be helped to reduce humans stress and helps to think creative. Nature is essential
for human being to think well.
There are so much information anywhere.
On our smartphone, TV, Advertisement on buildings, there are so much.
We might even miss opportunities that look closely at our emotion
because of processing information from outside too much.
Nature gives opportunities to let people look at themselves and recognize
what is really important in our life.
Nature also helps us to improve wellbeing in terms of emotion and physical condition.
It reduces anxiey and stress. Also people can improve their health through nature activities.
Even people can spend great time with others, so it's important to build strong connection with others too.
What's futures lifestyle? the world moves on so fast and sometimes people felt like left behind and gets streesed.
It might be needed to be in nature to look deeply into the world and yourself.
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This page ensures that WebKit can render unicode variation selector correctly. On platforms which support UVSes, the glyphs of U+845B should be different. On platforms which don't support UVSes, they should be identical. In addition, any glyphs (including the last resort glyph) should not appear after the U+845B on all platforms.


2. Getting a MicroPython REPL prompt¶
REPL stands for Read Evaluate Print Loop, and is the name given to the interactive MicroPython prompt that you can access on the ESP8266. Using the REPL is by far the easiest way to test out your code and run commands.
There are two ways to access the REPL: either via a wired connection through the UART serial port, or via WiFi.
2.1. REPL over the serial port¶
The REPL is always available on the UART0 serial peripheral, which is connected to the pins GPIO1 for TX and GPIO3 for RX. The baudrate of the REPL is 115200. If your board has a USB-serial convertor on it then you should be able to access the REPL directly from your PC. Otherwise you will need to have a way of communicating with the UART.
To access the prompt over USB-serial you need to use a terminal emulator program. On Windows TeraTerm is a good choice, on Mac you can use the built-in screen program, and Linux has picocom and minicom. Of course, there are many other terminal programs that will work, so pick your favourite!
For example, on Linux you can try running:
picocom /dev/ttyUSB0 -b115200
Once you have made the connection over the serial port you can test if it is
working by hitting enter a few times. You should see the Python REPL prompt,
indicated by >>>
.
2.2. WebREPL - a prompt over WiFi¶
WebREPL allows you to use the Python prompt over WiFi, connecting through a browser. The latest versions of Firefox and Chrome are supported.
For your convenience, WebREPL client is hosted at http://micropython.org/webrepl . Alternatively, you can install it locally from the the GitHub repository https://github.com/micropython/webrepl .
Before connecting to WebREPL, you should set a password and enable it via a normal serial connection. Initial versions of MicroPython for ESP8266 came with WebREPL automatically enabled on the boot and with the ability to set a password via WiFi on the first connection, but as WebREPL was becoming more widely known and popular, the initial setup has switched to a wired connection for improved security:
import webrepl_setup
Follow the on-screen instructions and prompts. To make any changes active, you will need to reboot your device.
To use WebREPL connect your computer to the ESP8266’s access point (MicroPython-xxxxxx, see the previous section about this). If you have already reconfigured your ESP8266 to connect to a router then you can skip this part.
Once you are on the same network as the ESP8266 you click the “Connect” button (if you are connecting via a router then you may need to change the IP address, by default the IP address is correct when connected to the ESP8266’s access point). If the connection succeeds then you should see a password prompt.
Once you type the password configured at the setup step above, press Enter once
more and you should get a prompt looking like >>>
. You can now start
typing Python commands!
2.3. Using the REPL¶
Once you have a prompt you can start experimenting! Anything you type at the prompt will be executed after you press the Enter key. MicroPython will run the code that you enter and print the result (if there is one). If there is an error with the text that you enter then an error message is printed.
Try typing the following at the prompt:
>>> print('hello esp8266!')
hello esp8266!
Note that you shouldn’t type the >>>
arrows, they are there to indicate that
you should type the text after it at the prompt. And then the line following is
what the device should respond with. In the end, once you have entered the text
print("hello esp8266!")
and pressed the Enter key, the output on your screen
should look exactly like it does above.
If you already know some python you can now try some basic commands here. For example:
>>> 1 + 2
3
>>> 1 / 2
0.5
>>> 12**34
4922235242952026704037113243122008064
If your board has an LED attached to GPIO2 (the ESP-12 modules do) then you can turn it on and off using the following code:
>>> import machine
>>> pin = machine.Pin(2, machine.Pin.OUT)
>>> pin.on()
>>> pin.off()
Note that on
method of a Pin might turn the LED off and off
might
turn it on (or vice versa), depending on how the LED is wired on your board.
To resolve this, machine.Signal class is provided.
2.3.1. Line editing¶
You can edit the current line that you are entering using the left and right arrow keys to move the cursor, as well as the delete and backspace keys. Also, pressing Home or ctrl-A moves the cursor to the start of the line, and pressing End or ctrl-E moves to the end of the line.
2.3.2. Input history¶
The REPL remembers a certain number of previous lines of text that you entered (up to 8 on the ESP8266). To recall previous lines use the up and down arrow keys.
2.3.3. Tab completion¶
Pressing the Tab key will do an auto-completion of the current word that you are entering. This can be very useful to find out functions and methods that a module or object has. Try it out by typing “ma” and then pressing Tab. It should complete to “machine” (assuming you imported machine in the above example). Then type “.” and press Tab again to see a list of all the functions that the machine module has.
2.3.4. Line continuation and auto-indent¶
Certain things that you type will need “continuing”, that is, will need more
lines of text to make a proper Python statement. In this case the prompt will
change to ...
and the cursor will auto-indent the correct amount so you can
start typing the next line straight away. Try this by defining the following
function:
>>> def toggle(p):
... p.value(not p.value())
...
...
...
>>>
In the above, you needed to press the Enter key three times in a row to finish the compound statement (that’s the three lines with just dots on them). The other way to finish a compound statement is to press backspace to get to the start of the line, then press the Enter key. (If you did something wrong and want to escape the continuation mode then press ctrl-C; all lines will be ignored.)
The function you just defined allows you to toggle a pin. The pin object you created earlier should still exist (recreate it if it doesn’t) and you can toggle the LED using:
>>> toggle(pin)
Let’s now toggle the LED in a loop (if you don’t have an LED then you can just print some text instead of calling toggle, to see the effect):
>>> import time
>>> while True:
... toggle(pin)
... time.sleep_ms(500)
...
...
...
>>>
This will toggle the LED at 1Hz (half a second on, half a second off). To stop the toggling press ctrl-C, which will raise a KeyboardInterrupt exception and break out of the loop.
The time module provides some useful functions for making delays and doing timing. Use tab completion to find out what they are and play around with them!
2.3.5. Paste mode¶
Pressing ctrl-E will enter a special paste mode. This allows you to copy and paste a chunk of text into the REPL. If you press ctrl-E you will see the paste-mode prompt:
paste mode; Ctrl-C to cancel, Ctrl-D to finish
===
You can then paste (or type) your text in. Note that none of the special keys or commands work in paste mode (eg Tab or backspace), they are just accepted as-is. Press ctrl-D to finish entering the text and execute it.
2.3.6. Other control commands¶
There are four other control commands:
Ctrl-A on a blank line will enter raw REPL mode. This is like a permanent paste mode, except that characters are not echoed back.
Ctrl-B on a blank like goes to normal REPL mode.
Ctrl-C cancels any input, or interrupts the currently running code.
Ctrl-D on a blank line will do a soft reset.
Note that ctrl-A and ctrl-D do not work with WebREPL.


|
Pebble Foundation Classes
0.2.0
C++ for Pebble
|
An unowned bitmap. More...
#include <pebble_graphics_types.hpp>
Public Member Functions | |
| GBitmap (::GBitmap *gbitmap) | |
| Wrap a Pebble bitmap. | |
| GBitmap (const GBitmapBase &that) | |
| Copy bitmap reference. | |
| GBitmap & | operator= (const GBitmapBase &that) |
| Assign the bitmap. | |
| GBitmap & | operator= (::GBitmap *gbitmap) |
| Assign the bitmap. | |
| bool | IsValid () |
| Returns true if the bitmap is valid and can be used. | |
| Public Member Functions inherited from Pebble::GBitmapBase | |
| operator::GBitmap * () const | |
| Instances of this class can be automatically converted to Pebble gbitmap pointer. | |
| virtual | ~GBitmapBase () |
| Destructor. | |
| uint16_t | GetBytesPerRow () const |
| GBitmapFormat | GetFormat () const |
| uint8_t * | GetData () const |
| GRect | GetBounds () const |
| GColor * | GetPalette () const |
Additional Inherited Members | |
| Protected Member Functions inherited from Pebble::GBitmapBase | |
| GBitmapBase () | |
| Cannot construct. | |
| GBitmapBase (::GBitmap *gbitmap) | |
| Wrap a Pebble bitmap. | |
| Protected Attributes inherited from Pebble::GBitmapBase | |
| ::GBitmap * | gbitmap_ |
An unowned bitmap.


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"Winnie" projects gallery
Some example of what kind of applications can be created using "Winnie":
A project of
Moscow region culture heritage
- using Leaflet clusters and LayerTree Widget
A project of
WWF social map
- using GeoMixer bookmarks and Leaflet clusters
A
"Crisismap"
project


Evaluating Climate Policy Options, Costs and Benefits
On This Page
- Common-sense Approaches Through the Clean Air Act
- Analysis of Proposed Climate Legislation
- Understanding Benefits
- Research Underlying EPA Economic Modeling of Climate Policies
EPA analyzes the anticipated economic effects of proposed standards and policies to reduce greenhouse gas emissions. These analyses have shown that there are a variety of cost-effective policies available to reduce greenhouse gas emissions.
Policy options range from comprehensive market-based legislation to targeted regulations to reduce emissions and improve the efficiency of vehicles, power plants and large industrial sources. Underlying these analyses are economic models and detailed studies of technologies to reduce emissions.
Common-sense Approaches Through the Clean Air Act
EPA is taking action under the Clean Air Act to reduce greenhouse gas emissions from the largest sources by increasing the efficiency of our power plants, cars, and trucks. Our analyses show that these regulations will save consumers money at the pump, improve the air we breathe, promote jobs in the green technology sector, and cut millions of tons of harmful greenhouse gas emissions.
- EPA's regulatory initiatives for greenhouse gases under the Clean Air Act
- Historical economic benefits from taking action under the Clean Air Act
Analysis of Proposed Climate Legislation
Congress periodically proposes legislation to lower greenhouse gas emissions, and EPA economists analyze these bills as part of the legislative process. EPA analyses have shown that comprehensive, market-based climate legislation can transform the U.S. energy system and reduce greenhouse gas emissions, all at relatively low cost.
Understanding Benefits
Taking actions to reduce greenhouse gas emissions yields important economic benefits. These benefits are from the reduced risk to human health and welfare that results from lower emissions of greenhouse gases and less global warming and climate change. EPA and other federal agencies have developed Social Cost of Carbon (SC-CO2) estimates to assess the economic benefits of rulemakings that reduce carbon dioxide (CO2) emissions. When agencies prepare to issue regulations implementing the laws enacted by Congress, they must justify proposed regulations by assessing their cost and benefits to the economy and society. The SC-CO2 is typically used in the benefits part of the cost-benefit analysis. For a regulation that decreases emissions, the SC-CO2 represents the damage avoided--or the benefit of the regulation--for marginal reductions of CO2.
As discussed in the supporting technical documentation, (PDF, 21pp, 1.4MB) however, these benefit estimates are not complete because current models do not yet capture all of the important physical, ecological, and economic impacts of rising levels of CO2 in the atmosphere that are recognized in the literature. Nonetheless, these estimates and the discussion of their limitations in the supporting technical documentation represent the best available information about the social benefits of CO2 reductions to inform benefit-cost analysis.
EPA is exploring approaches to further understand the benefits of CO2 reductions that complement the analysis conducted with the SC-CO2. While the SC-CO2 is a useful metric to assess marginal changes in CO2 emissions in the context of cost-benefit analysis, bottom-up approaches, such as the Climate Change Impacts and Risks Analysis (CIRA) project, may offer additional insights about the impact of significant global action.
CIRA is a peer-reviewed study comparing impacts in a future with significant global action on climate change to a future in which current greenhouse gas emissions continue to rise.
In 2015, EPA released a report, Climate Change in the United States: Benefits of Global Action, estimating the physical and monetary benefits to the U.S. of reducing global greenhouse gas emissions. This report summarizes results from the CIRA. Although no specific mitigation policies were analyzed, the report shows that global action on climate change will significantly benefit Americans by saving lives and avoiding costly damages across the U.S. economy.
Research Underlying EPA Economic Modeling of Climate Policies:
Climate Economic Modeling
EPA uses a variety of economic models and analytical tools when conducting climate economic analyses of climate legislation or policy. These models help researchers estimate the future effects of proposed policies on energy production, the economy, emissions of CO2, and land use trends in agriculture and forestry.
Air Quality and Climate Modeling
EPA is creating decision support tools to evaluate policy options for both air quality and climate change
Transportation Sector Analyses
EPA conducts modeling and feasibility analyses to understand the potential of technologies and strategies to reduce greenhouse gas emissions from the transportation sector.
International Emissions Projections for Non CO2 Gases
EPA conducts studies of projected global emissions of the methane, nitrous oxide, and fluorinated greenhouse gases which account for about 30 percent of human-caused warming. Projected emissions studies for the non-CO2 gases provide a benchmark that can be used to measure the potential environmental and economic impact of proposed climate policies across all relevant gases.
International Mitigation Technologies to Reduce Emissions of Non CO2 Gases
Numerous technologies are available to reduce emissions of methane, nitrous oxide, and fluorinated greenhouse gases. EPA develops reports that evaluate the costs of various technologies to reduce non-CO2 greenhouse gas emissions. These reports also provide cumulative marginal abatement cost curves which are used by researchers to represent mitigation costs in their models.


(a -> b) & a & -bor a dimacs version of the clause normal form syntax like
-1 2 1 -2which is a conjunction of disjunction lines with numbers standing for variables: the last example means simply (-x1 v x2) & x1 & -x2
For conventional formula syntax:
For dimacs you may use or skip the initial comment lines starting with c, the special p line and the final 0 symbols at the end of each disjunct. We allow the trailing 0-s only at the end of a line.
I.e. you may use the full dimacs version like
c comment p cnf 2 3 -1 2 0 1 0 -2 0or just
-1 2 1 -2hide syntax
You can select and try out several solver algorithms: the "DPLL better" is the best solver amongst the options. Read from here about the differences between algorithms.
One single suitable set of values is enough as a solution: the solver algorithms stop and do not try to find additional solutions. Some of the solver algorithms output the suitable values, but some do not, or output a partial set.
It may also happen that the formula is false for all possible values of variables: if so, the solver algorithms report that after exhausting the search options. For example, (a -> b) & a & -b is always false.
Notice that you can check whether some formula F is always true by trying to solve the negated formula -F: in case -F is always false, F must be always true.
The algorithms may optionally output a trace of the search process. Select "html trace" to see the search process: again, read from here about the search methods used by the algorithms.
For formula-syntax input the solvers first convert the formula to a clause normal form: for certain kinds of formulas this conversion step may create a huge output, but in most cases it is a sensible simplification before actual search.
The options for the type of a problem are:
For DPLL try out 200 variables or more. Truth table solvers start running into trouble with more than 20 variables. The resolution provers are a bit better than the truth table solvers, yet much worse than the DPLL solvers.
You can also browse and read the contents of a file into the input area: essentially copy-paste from a file.


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[CHAPTER 429]
UNIFORM UNINCORPORATED NONPROFIT ASSOCIATION ACT
Section
429-1 Definitions
429-2 Supplementary general principles of law and equity
429-3 Territorial application
429-4 Real and personal property; nonprofit association as
legatee, devisee, or beneficiary
429-5 Statement of authority as to real property
429-6 Liability in contract and tort
429-7 Capacity to assert and defend; standing
429-8 Effect of judgment or order
429-9 Disposition of personal property of inactive nonprofit
association
429-10 Appointment of agent to receive service of process
429-11 Claim not abated by change
429-12 Venue
429-13 Summons and complaint; service on whom


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SoS can be easily extended with new actions, targets, converters, file previewers. To make the extension available to other users, you can either create and distribute a separate package, or extend SoS and send us a pull request.
entry_points
¶SoS makes extensive use of entry points, which allows external modules to register their features in the file system to make them available to other modules. It can be confusing initially but this stack overflow ticket explains it quite well.
To register additional feature with SoS, you either need to extend entry_points
of the setup.py
script of SoS, or create your own package with these entry_points
. Option extras_require
can be used to specify additional dependent packages for these features. For example, you can create a package with the following entry_points to provide support for ruby.
entry_points='''
[sos-language]
ruby = sos-ruby.kernel:sos_ruby
[sos-targets]
Ruby_Library = sos-ruby.target:Ruby-Library
'''
With the installation of this package, sos
would be able to obtain a class sos_ruby
from module sos-ruby.kernel
, and use it to work with the ruby
language.
Under the hood an action is a normal Python function that is decorated as SoS_Action
. The decorator
defines the common interface of actions and calls the actual function. To define your own action, you generally need to
from sos.actions import SoS_Action
@SoS_Action()
def my_action(*args, **kwargs):
pass
The decorator accepts two optional parameters:
run_mode=['interactive', 'run']
meaning the action will be executable in batch and interactive (Jupyter kernel) mode, and not in dryrun
mode. An action usually behave the same in both modes but can be tailered for the environment in which it runs. acceptable_args=['*']
which can be used to specify a list of acceptable parameter (*
matches all keyword args). An exception will be raised if an action is defined with a list of acceptable_args
and is called with an unrecognized argument.You then need to add an entry to entry_points
as
[sos-actions]
my_action = mypackage.mymodule:my_action
If the execution of action depends on some other targets, you can raise an UnknownTarget
with the target so that the target can be obtained. For example, if your action depends on a particular R_library
, you can test the existence of the target as follows:
from sos.target import UnknownTarget
from sos.R.target import R_library
@SoS_Action()
def my_action(script, *args, **kwargs):
if not R_library('somelib').exists():
raise UnknownTarget(R_library('somelib'))
# ...
Adding additional target is similar with a class derived from BaseTarget
.
from sos.target import BaseTarget
class my_target(BaseTarget):
def __init__(self, *args, **kwargs):
pass
You will need to define several member functions for this class, most notably exists
that checks the existence of the target. This function accept a parameter mode
, which can be target
, signature
, or any
. Like a file target, a target can be considered exist as long as its signature exists, and if the real target is not needed for the execution of the workflow.
The details of this class can be found at the source code of BaseTarget
. The R_Library
provides a good example of a virtual target that do not have a fixed corresponding file, can be checked for existence, and actually attempts to obtain (install a R library) the target when it is checked.
After you defined your target, you can make it available to SOS by adding an appropriate entry point
[sos-targets]
my_target = mypackage.mymodule:my_target
To convert between sos and another file format, you would need to define two function, one returnning an argparse.ArgumentParser
that parse converter arguments, and one performing real file conversion.
Suppose you would like to convert .sos
to a .xp
format, you can define these two functions as follows
import argparse
from sos.sos_script import SoS_Script
def get_my_converter_parser():
parser = argparse.ArgumentParser('sos_xp')
parser.add_argument('--theme',
help='Style of output format')
return parser
def my_converter(source_file, dest_file, args=None, unknown_args=[]):
# parse additional_args to obtain converter-specific options
# then convert from source_file to dest_file
script = SoS_Script(source_file)
for section in script.sections:
# do something
if __name__ == '__main__':
parser = get_my_converter_parser()
args, unknown_args = parser.parse_known_args(sys.argv[3:])
my_converter(sys.argv[1], sys.argv[2], args, unknown_args)
You can then register the converter in setup.py
as
[sos-converters]
fromExt-toExt.parser: mypackage.mymodule:get_my_converter_parser
fromExt-toExt.func: mypackage.mymodule:my_converter
Here fromExt
is file extension without leading dot, toExt
is destination file extension without leading dot, or a format specified by the --to
parameter of command sos convert
. If dest_file
is unspecified, the output should be written to standard output.
This example uses if __name__ == '__main__'
section so that the converter can be used as a standandalone program, which is not needed but a great way for testing purposes. Note that the input and output files are handled by sos convert
so the parser only needs to parse converter-specific options.
Adding a preview function is very simple. All you need to is to define a function that returns preview information, and add an entry point to link the function to certain file format.
More specifically, a previewer should be specified as
pattern,priority = preview_module:func
or
module:func,priority = preview_module:func
where
pattern
is a pattern that matches incoming filename (see module fnmatch.fnmatch for details)module:func
specifies a function in module that detects the type of input file.priority
is an integer number that indicates the priority of previewer in case multiple pattern or function matches the same file. Developers of third-party previewer can override an existing previewer by specifying a higher priority number.preview_module:func
points to a function in a module. The function should accept a filename as the only parameter, and returns either
data
field of display_data
(see Jupyter documentation for details). The dictionary typically has text/html
for HTML output, "text/plain" for plain text, and "text/png" for image presentation of the file.If you would like to add a complete subcommand as an addon to SoS, you will need to define two functions and add them to setup.py
as two entry points, one with suffix .args
and one with suffix .func
.
[sos_addons]
myaddon.args = yourpackage.module:addon_parser
myaddon.func = yourpackage.module:addon_func
The addon_parser
function should use module argparse
to return an ArgumentParser
object. SoS would obtain this parser and add it as a subparse of the SoS main parser so that the options can be parsed as
sos myaddon options
The addon_func
should be defined as
def addon_func(args, unknown_args)
with args
being the parsed known arguments, and unknown_args
being a list of unknown arguments that you can process by youself.


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| 1 | /* =========================================================== | |
| 2 | * JFreeChart : a free chart library for the Java(tm) platform | |
| 3 | * =========================================================== | |
| 4 | * | |
| 5 | * (C) Copyright 2000-2008, by Object Refinery Limited and Contributors. | |
| 6 | * | |
| 7 | * Project Info: http://www.jfree.org/jfreechart/index.html | |
| 8 | * | |
| 9 | * This library is free software; you can redistribute it and/or modify it | |
| 10 | * under the terms of the GNU Lesser General Public License as published by | |
| 11 | * the Free Software Foundation; either version 2.1 of the License, or | |
| 12 | * (at your option) any later version. | |
| 13 | * | |
| 14 | * This library is distributed in the hope that it will be useful, but | |
| 15 | * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY | |
| 16 | * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public | |
| 17 | * License for more details. | |
| 18 | * | |
| 19 | * You should have received a copy of the GNU Lesser General Public | |
| 20 | * License along with this library; if not, write to the Free Software | |
| 21 | * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, | |
| 22 | * USA. | |
| 23 | * | |
| 24 | * [Java is a trademark or registered trademark of Sun Microsystems, Inc. | |
| 25 | * in the United States and other countries.] | |
| 26 | * | |
| 27 | * --------------------- | |
| 28 | * LegendItemEntity.java | |
| 29 | * --------------------- | |
| 30 | * (C) Copyright 2003-2008, by Object Refinery Limited and Contributors. | |
| 31 | * | |
| 32 | * Original Author: David Gilbert (for Object Refinery Limited); | |
| 33 | * Contributor(s): -; | |
| 34 | * | |
| 35 | * Changes: | |
| 36 | * -------- | |
| 37 | * 05-Jun-2003 : Version 1 (DG); | |
| 38 | * 20-May-2004 : Added equals() method and implemented Cloneable and | |
| 39 | * Serializable (DG); | |
| 40 | * ------------- JFREECHART 1.0.x --------------------------------------------- | |
| 41 | * 18-May-2007 : Added dataset and seriesKey fields (DG); | |
| 42 | * 21-Jun-2007 : Removed JCommon dependencies (DG); | |
| 43 | * | |
| 44 | */ | |
| 45 | ||
| 46 | package org.jfree.chart.entity; | |
| 47 | ||
| 48 | import java.awt.Shape; | |
| 49 | import java.io.Serializable; | |
| 50 | ||
| 51 | import org.jfree.chart.util.ObjectUtilities; | |
| 52 | import org.jfree.data.general.Dataset; | |
| 53 | ||
| 54 | /** | |
| 55 | * An entity that represents an item within a legend. | |
| 56 | */ | |
| 57 | public class LegendItemEntity extends ChartEntity | |
| 58 | implements Cloneable, Serializable { | |
| 59 | ||
| 60 | /** For serialization. */ | |
| 61 | private static final long serialVersionUID = -7435683933545666702L; | |
| 62 | ||
| 63 | /** | |
| 64 | * The dataset. | |
| 65 | * | |
| 66 | * @since 1.0.6 | |
| 67 | */ | |
| 68 | private Dataset dataset; | |
| 69 | ||
| 70 | /** | |
| 71 | * The series key. | |
| 72 | * | |
| 73 | * @since 1.0.6 | |
| 74 | */ | |
| 75 | private Comparable seriesKey; | |
| 76 | ||
| 77 | /** | |
| 78 | * Creates a legend item entity. | |
| 79 | * | |
| 80 | * @param area the area. | |
| 81 | */ | |
| 82 | public LegendItemEntity(Shape area) { | |
| 83 | super(area); | |
| 84 | } | |
| 85 | ||
| 86 | /** | |
| 87 | * Returns a reference to the dataset that this legend item is derived | |
| 88 | * from. | |
| 89 | * | |
| 90 | * @return The dataset. | |
| 91 | * | |
| 92 | * @since 1.0.6 | |
| 93 | * | |
| 94 | * @see #setDataset(Dataset) | |
| 95 | */ | |
| 96 | public Dataset getDataset() { | |
| 97 |
1
1. getDataset : mutated return of Object value for org/jfree/chart/entity/LegendItemEntity::getDataset to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return this.dataset; |
| 98 | } | |
| 99 | ||
| 100 | /** | |
| 101 | * Sets a reference to the dataset that this legend item is derived from. | |
| 102 | * | |
| 103 | * @param dataset the dataset. | |
| 104 | * | |
| 105 | * @since 1.0.6 | |
| 106 | */ | |
| 107 | public void setDataset(Dataset dataset) { | |
| 108 | this.dataset = dataset; | |
| 109 | } | |
| 110 | ||
| 111 | /** | |
| 112 | * Returns the series key that identifies the legend item. | |
| 113 | * | |
| 114 | * @return The series key. | |
| 115 | * | |
| 116 | * @since 1.0.6 | |
| 117 | * | |
| 118 | * @see #setSeriesKey(Comparable) | |
| 119 | */ | |
| 120 | public Comparable getSeriesKey() { | |
| 121 |
1
1. getSeriesKey : mutated return of Object value for org/jfree/chart/entity/LegendItemEntity::getSeriesKey to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return this.seriesKey; |
| 122 | } | |
| 123 | ||
| 124 | /** | |
| 125 | * Sets the key for the series. | |
| 126 | * | |
| 127 | * @param key the key. | |
| 128 | * | |
| 129 | * @since 1.0.6 | |
| 130 | * | |
| 131 | * @see #getSeriesKey() | |
| 132 | */ | |
| 133 | public void setSeriesKey(Comparable key) { | |
| 134 | this.seriesKey = key; | |
| 135 | } | |
| 136 | ||
| 137 | /** | |
| 138 | * Tests this object for equality with an arbitrary object. | |
| 139 | * | |
| 140 | * @param obj the object (null permitted). | |
| 141 | * | |
| 142 | * @return A boolean. | |
| 143 | */ | |
| 144 | public boolean equals(Object obj) { | |
| 145 |
1
1. equals : negated conditional → KILLED |
if (obj == this) { |
| 146 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE |
return true; |
| 147 | } | |
| 148 |
1
1. equals : negated conditional → KILLED |
if (!(obj instanceof LegendItemEntity)) { |
| 149 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → NO_COVERAGE |
return false; |
| 150 | } | |
| 151 | LegendItemEntity that = (LegendItemEntity) obj; | |
| 152 |
1
1. equals : negated conditional → KILLED |
if (!ObjectUtilities.equal(this.seriesKey, that.seriesKey)) { |
| 153 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED |
return false; |
| 154 | } | |
| 155 |
1
1. equals : negated conditional → KILLED |
if (!ObjectUtilities.equal(this.dataset, that.dataset)) { |
| 156 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED |
return false; |
| 157 | } | |
| 158 |
1
1. equals : replaced return of integer sized value with (x == 0 ? 1 : 0) → KILLED |
return super.equals(obj); |
| 159 | } | |
| 160 | ||
| 161 | /** | |
| 162 | * Returns a clone of the entity. | |
| 163 | * | |
| 164 | * @return A clone. | |
| 165 | * | |
| 166 | * @throws CloneNotSupportedException if there is a problem cloning the | |
| 167 | * object. | |
| 168 | */ | |
| 169 | public Object clone() throws CloneNotSupportedException { | |
| 170 |
1
1. clone : mutated return of Object value for org/jfree/chart/entity/LegendItemEntity::clone to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return super.clone(); |
| 171 | } | |
| 172 | ||
| 173 | /** | |
| 174 | * Returns a string representing this object (useful for debugging | |
| 175 | * purposes). | |
| 176 | * | |
| 177 | * @return A string (never null). | |
| 178 | */ | |
| 179 | public String toString() { | |
| 180 |
1
1. toString : mutated return of Object value for org/jfree/chart/entity/LegendItemEntity::toString to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return "LegendItemEntity: seriesKey=" + this.seriesKey |
| 181 | + ", dataset=" + this.dataset; | |
| 182 | } | |
| 183 | ||
| 184 | } | |
Mutations | ||
| 97 |
1.1 |
|
| 121 |
1.1 |
|
| 145 |
1.1 |
|
| 146 |
1.1 |
|
| 148 |
1.1 |
|
| 149 |
1.1 |
|
| 152 |
1.1 |
|
| 153 |
1.1 |
|
| 155 |
1.1 |
|
| 156 |
1.1 |
|
| 158 |
1.1 |
|
| 170 |
1.1 |
|
| 180 |
1.1 |


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