Chapter 10 Advanced dataframe manipulation
In this chapter we’ll cover some more advanced functions and procedures for manipulating dataframes.
# Exam data
exam <- data.frame(
id = 1:5,
q1 = c(1, 5, 2, 3, 2),
q2 = c(8, 10, 9, 8, 7),
q3 = c(3, 7, 4, 6, 4))
# Demographic data
demographics <- data.frame(
id = 1:5,
sex = c("f", "m", "f", "f", "m"),
age = c(25, 22, 24, 19, 23))
# Combine exam and demographics
combined <- merge(x = exam,
y = demographics,
by = "id")
# Mean q1 score for each sex
aggregate(formula = q1 ~ sex,
data = combined,
FUN = mean)
## sex q1
## 1 f 2.0
## 2 m 3.5
# Median q3 score for each sex, but only for those
# older than 20
aggregate(formula = q3 ~ sex,
data = combined,
subset = age > 20,
FUN = mean)
## sex q3
## 1 f 3.5
## 2 m 5.5
# Many summary statistics by sex using dplyr!
library(dplyr)
combined %>% group_by(sex) %>%
summarise(
q1.mean = mean(q1),
q2.mean = mean(q2),
q3.mean = mean(q3),
age.mean = mean(age),
N = n())
## # A tibble: 2 x 6
## sex q1.mean q2.mean q3.mean age.mean N
## <fctr> <dbl> <dbl> <dbl> <dbl> <int>
## 1 f 2.0 8.3 4.3 23 3
## 2 m 3.5 8.5 5.5 22 2
In Chapter 6, you learned how to calculate statistics on subsets of data using indexing. However, you may have noticed that indexing is not very intuitive and not terribly efficient. If you want to calculate statistics for many different subsets of data (e.g.; mean birth rate for every country), you’d have to write a new indexing command for each subset, which could take forever. Thankfully, R has some great built-in functions like aggregate()
that allow you to easily apply functions (like mean()
) to a dependent variable (like birth rate) for each level of one or more independent variables (like a country) with just a few lines of code.
10.1 order()
: Sorting data
To sort the rows of a dataframe according to column values, use the order()
function. The order()
function takes one or more vectors as arguments, and returns an integer vector indicating the order of the vectors. You can use the output of order()
to index a dataframe, and thus change its order.
Let’s re-order the pirates
data by height from the shortest to the tallest:
# Sort the pirates dataframe by height
pirates <- pirates[order(pirates$height),]
# Look at the first few rows and columns of the result
pirates[1:5, 1:4]
## id sex age height
## 39 39 female 25 130
## 854 854 female 25 130
## 30 30 female 26 135
## 223 223 female 28 135
## 351 351 female 36 137
By default, the order()
function will sort values in ascending (increasing) order. If you want to order the values in descending (decreasing) order, just add the argument decreasing = TRUE
to the order()
function:
# Sort the pirates dataframe by height in decreasing order
pirates <- pirates[order(pirates$height, decreasing = TRUE),]
# Look at the first few rows and columns of the result
pirates[1:5, 1:4]
## id sex age height
## 2 2 male 31 209
## 793 793 male 25 209
## 430 430 male 26 201
## 292 292 male 29 201
## 895 895 male 27 201
To order a dataframe by several columns, just add additional arguments to order()
.  If you want to order the values in descending (decreasing) order, just add the argument decreasing = TRUE
to the order()
function:
# Sort the pirates dataframe by height in decreasing order
pirates <- pirates[order(pirates$height, decreasing = TRUE),]
10.2 merge()
: Combining data
| Argument | Description |
|---|---|
x, y |
Two dataframes to be merged |
by |
A string vector of 1 or more columns to match the data by. For example, by = "id" will combine columns that have matching values in a column called "id" . by = c("last.name", "first.name") will combine columns that have matching values in both "last.name" and "first.name" |
all |
A logical value indicating whether or not to include rows with non-matching values of by . |
One of the most common data management tasks is merging (aka combining) two data sets together. For example, imagine you conduct a study where 5 participants are given a score from 1 to 5 on a risk assessment task. We can represent these data in a dataframe called risk.survey
:
| participant | risk.score |
|---|---|
| 1 | 3 |
| 2 | 4 |
| 3 | 5 |
| 4 | 3 |
| 5 | 1 |
# Results from a risk survey
risk.survey <- data.frame(
"participant" = c(1, 2, 3, 4, 5),
"risk.score" = c(3, 4, 5, 3, 1))
Now, imagine that in a second study, you have participants complete a survey about their level of happiness (on a scale of 0 to 100). We can represent these data in a new dataframe called happiness.survey
:
happiness.survey <- data.frame(
"participant" = c(4, 2, 5, 1, 3),
"happiness.score" = c(20, 40, 50, 90, 53))
Now, we’d like to combine these data into one data frame so that the two survey scores for each participant are contained in one object. To do this, use merge()
.
When you merge two dataframes, the result is a new dataframe that contains data from both dataframes. The key argument in merge()
is by
. The by
argument specifies how rows should be matched during the merge. Usually, this will be something like an name, id number, or some other unique identifier.
Let’s combine our risk and happiness survey using merge()
. Because we want to match rows by the participant.id
column, we’ll specify by = "participant.id"
. Additionally, because we want to include rows with potentially non-matching values, we’ll include all = TRUE
# Combine the risk and happiness surveys by matching participant.id
combined.survey <- merge(x = risk.survey,
y = happiness.survey,
by = "participant",
all = TRUE)
# Print the result
combined.survey
## participant risk.score happiness.score
## 1 1 3 90
## 2 2 4 40
## 3 3 5 53
## 4 4 3 20
## 5 5 1 50
For the rest of the chapter, we’ll cover data aggregation functions. These functions allow you to quickly and easily calculate aggregated summary statistics over groups of data in a data frame. For example, you can use them to answer questions such as “What was the mean crew age for each ship?”, or “What percentage of participants completed an attention check for each study condition?” We’ll start by going over the aggregate()
function.
10.3 aggregate()
: Grouped aggregation
| Argument | Description |
|---|---|
formula |
A formula in the form y ~ x1 + x2 + ... where y is the dependent variable, and x1, x2… are the independent variables. For example, salary ~ sex + age will aggregate a salary column at every unique combination of sex and age |
FUN |
A function that you want to apply to y at every level of the independent variables. E.g.; mean , or max . |
data |
The dataframe containing the variables in formula |
subset |
A subset of data to analyze. For example, subset(sex == "f" & age > 20) would restrict the analysis to females older than 20. You can ignore this argument to use all data. |
The first aggregation function we’ll cover is aggregate()
. Aggregate allows you to easily answer questions in the form: “What is the value of the function FUN
applied to a dependent variable dv
at each level of one (or more) independent variable(s) iv
?
# General structure of aggregate()
aggregate(formula = dv ~ iv, # dv is the data, iv is the group
FUN = fun, # The function you want to apply
data = df) # The dataframe object containing dv and iv
Let’s give aggregate()
a whirl. No…not a whirl…we’ll give it a spin. Definitely a spin. We’ll use aggregate()
on the ChickWeight
dataset to answer the question “What is the mean weight for each diet?”
If we wanted to answer this question using basic R functions, we’d have to write a separate command for each supplement like this:
# The WRONG way to do grouped aggregation.
# We should be using aggregate() instead!
mean(ChickWeight$weight[ChickWeight$Diet == 1])
## [1] 103
mean(ChickWeight$weight[ChickWeight$Diet == 2])
## [1] 123
mean(ChickWeight$weight[ChickWeight$Diet == 3])
## [1] 143
mean(ChickWeight$weight[ChickWeight$Diet == 4])
## [1] 135
If you are ever writing code like this, there is almost always a simpler way to do it. Let’s replace this code with a much more elegant solution using aggregate()
.For this question, we’ll set the value of the dependent variable Y to weight
, x1 to Diet
, and FUN to mean
# Calculate the mean weight for each value of Diet
aggregate(formula = weight ~ Diet, # DV is weight, IV is Diet
FUN = mean, # Calculate the mean of each group
data = ChickWeight) # dataframe is ChickWeight
## Diet weight
## 1 1 103
## 2 2 123
## 3 3 143
## 4 4 135
As you can see, the aggregate()
function has returned a dataframe with a column for the independent variable Diet
, and a column for the results of the function mean
applied to each level of the independent variable. The result of this function is the same thing we’d got from manually indexing each level of Diet
individually – but of course, this code is much simpler and more elegant!
You can also include a subset
argument within an aggregate()
function to apply the function to subsets of the original data. For example, if I wanted to calculate the mean chicken weights for each diet, but only when the chicks are less than 10 weeks old, I would do the following:
# Calculate the mean weight for each value of Diet,
# But only when chicks are less than 10 weeks old
aggregate(formula = weight ~ Diet, # DV is weight, IV is Diet
FUN = mean, # Calculate the mean of each group
subset = Time < 10, # Only when Chicks are less than 10 weeks old
data = ChickWeight) # dataframe is ChickWeight
## Diet weight
## 1 1 58
## 2 2 63
## 3 3 66
## 4 4 69
You can also include multiple independent variables in the formula argument to aggregate()
. For example, let’s use aggregate()
to now get the mean weight of the chicks for all combinations of both Diet
and Time
, but now only for weeks 0, 2, and 4:
# Calculate the mean weight for each value of Diet and Time,
# But only when chicks are 0, 2 or 4 weeks okd
aggregate(formula = weight ~ Diet + Time, # DV is weight, IVs are Diet and Time
FUN = mean, # Calculate the mean of each group
subset = Time %in% c(0, 2, 4), # Only when Chicks are 0, 2, and 4 weeks old
data = ChickWeight) # dataframe is ChickWeight
## Diet Time weight
## 1 1 0 41
## 2 2 0 41
## 3 3 0 41
## 4 4 0 41
## 5 1 2 47
## 6 2 2 49
## 7 3 2 50
## 8 4 2 52
## 9 1 4 56
## 10 2 4 60
## 11 3 4 62
## 12 4 4 64
10.4 dplyr
The dplyr
package is a relatively new R package that allows you to do all kinds of analyses quickly and easily. It is especially useful for creating tables of summary statistics across specific groups of data. In this section, we’ll go over a very brief overview of how you can use dplyr to easily do grouped aggregation. Just to be clear - you can use dplyr to do everything the aggregate()
function does and much more! However, this will be a very brief overview and I strongly recommend you look at the help menu for dplyr for additional descriptions and examples.
To use the dplyr package, you first need to install it with install.packages()
and load it:
install.packages("dplyr") # Install dplyr (only necessary once)
library("dplyr") # Load dplyr
Programming with dplyr looks a lot different than programming in standard R. dplyr works by combining objects (dataframes and columns in dataframes), functions (mean, median, etc.), and verbs (special commands in dplyr
). In between these commands is a new operator called the pipe which looks like this: %>%
}. The pipe simply tells R that you want to continue executing some functions or verbs on the object you are working on. You can think about this pipe as meaning ‘and then…’
To aggregate data with dplyr
, your code will look something like the following code. In this example, assume that the dataframe you want to summarize is called my.df
, the variable you want to group the data by independent variables iv1, iv2
, and the columns you want to aggregate are called col.a
, col.b
and col.c
# Template for using dplyr
my.df %>% # Specify original dataframe
filter(iv3 > 30) %>% # Filter condition
group_by(iv1, iv2) %>% # Grouping variable(s)
summarise(
a = mean(col.a), # calculate mean of column col.a in my.df
b = sd(col.b), # calculate sd of column col.b in my.df
c = max(col.c)) # calculate max on column col.c in my.df, ...
When you use dplyr, you write code that sounds like: “The original dataframe is XXX, now filter the dataframe to only include rows that satisfy the conditions YYY, now group the data at each level of the variable(s) ZZZ, now summarize the data and calculate summary functions XXX…”
Let’s start with an example: Let’s create a dataframe of aggregated data from the pirates
dataset. I’ll filter the data to only include pirates who wear a headband. I’ll group the data according to the columns sex
and college
. I’ll then create several columns of different summary statistic of some data across each grouping. To create this aggregated data frame, I will use the new function group_by
and the verb summarise
. I will assign the result to a new dataframe called pirates.agg
:
pirates.agg <- pirates %>% # Start with the pirates dataframe
filter(headband == "yes") %>% # Only pirates that wear hb
group_by(sex, college) %>% # Group by these variables
summarise(
age.mean = mean(age), # Define first summary...
tat.med = median(tattoos), # you get the idea...
n = n() # How many are in each group?
) # End
# Print the result
pirates.agg
## # A tibble: 6 x 5
## # Groups: sex [?]
## sex college age.mean tat.med n
## <chr> <chr> <dbl> <dbl> <int>
## 1 female CCCC 26 10 206
## 2 female JSSFP 34 10 203
## 3 male CCCC 23 10 358
## 4 male JSSFP 32 10 85
## 5 other CCCC 25 10 24
## 6 other JSSFP 32 12 11
As you can see from the output on the right, our final object pirates.agg
is the aggregated dataframe we want which aggregates all the columns we wanted for each combination of sex
and college
One key new function here is n()
. This function is specific to dplyr and returns a frequency of values in a summary command.
Let’s do a more complex example where we combine multiple verbs into one chunk of code. We’ll aggregate data from the movies dataframe.
movies %>% # From the movies dataframe...
filter(genre != "Horror" & time > 50) %>% # Select only these rows
group_by(rating, sequel) %>% # Group by rating and sequel
summarise( #
frequency = n(), # How many movies in each group?
budget.mean = mean(budget, na.rm = T), # Mean budget?
revenue.mean = mean(revenue.all), # Mean revenue?
billion.p = mean(revenue.all > 1000)) # Percent of movies with revenue > 1000?
## # A tibble: 14 x 6
## # Groups: rating [?]
## rating sequel frequency budget.mean revenue.mean billion.p
## <chr> <int> <int> <dbl> <dbl> <dbl>
## 1 G 0 59 41.23 234 0.0000
## 2 G 1 12 92.92 357 0.0833
## 3 NC-17 0 2 3.75 18 0.0000
## 4 Not Rated 0 84 1.74 56 0.0000
## 5 Not Rated 1 12 0.67 66 0.0000
## 6 PG 0 312 51.78 191 0.0096
## 7 PG 1 62 77.21 372 0.0161
## 8 PG-13 0 645 52.09 168 0.0062
## 9 PG-13 1 120 124.16 524 0.1167
## 10 R 0 623 31.38 109 0.0000
## 11 R 1 42 58.25 226 0.0000
## 12 <NA> 0 86 1.65 34 0.0000
## 13 <NA> 1 15 5.51 48 0.0000
## 14 <NA> NA 11 0.00 34 0.0000
As you can see, our result is a dataframe with 14 rows and 6 columns. The data are summarized from the movie dataframe, only include values where the genre is not Horror and the movie length is longer than 50 minutes, is grouped by rating and sequel, and shows several summary statistics.
10.4.1 Additional dplyr help
We’ve only scratched the surface of what you can do with dplyr
. In fact, you can perform almost all of your R tasks, from loading, to managing, to saving data, in the dplyr
framework. For more tips on using dplyr, check out the dplyr vignette at https://cran.r-project.org/web/packages/dplyr/vignettes/introduction.html. Or open it in RStudio by running the following command:
# Open the dplyr introduction in R
vignette("introduction", package = "dplyr")
There is also a very nice YouTube video covering dplyr
at https://goo.gl/UY2AE1. Finally, consider also reading R for Data Science written by Garrett Grolemund and Hadley Wickham, which teaches R from the ground-up using the dplyr framework.
10.5 Additional aggregation functions
There are many, many other aggregation functions that I haven’t covered in this chapter – mainly because I rarely use them. In fact, that’s a good reminder of a peculiarity about R, there are many methods to achieve the same result, and your choice of which method to use will often come down to which method you just like the most.
10.5.1 rowMeans()
, colMeans()
To easily calculate means (or sums) across all rows or columns in a matrix or dataframe, use rowMeans()
, colMeans()
, rowSums()
or colSums()
.
For example, imagine we have the following data frame representing scores from a quiz with 5 questions, where each row represents a student, and each column represents a question. Each value can be either 1 (correct) or 0 (incorrect)
| q1 | q2 | q3 | q4 | q5 |
|---|---|---|---|---|
| 1 | 1 | 1 | 1 | 1 |
| 0 | 0 | 0 | 1 | 0 |
| 0 | 1 | 1 | 1 | 0 |
| 0 | 1 | 0 | 1 | 1 |
| 0 | 0 | 0 | 1 | 1 |
# Some exam scores
exam <- data.frame("q1" = c(1, 0, 0, 0, 0),
"q2" = c(1, 0, 1, 1, 0),
"q3" = c(1, 0, 1, 0, 0),
"q4" = c(1, 1, 1, 1, 1),
"q5" = c(1, 0, 0, 1, 1))
Let’s use rowMeans()
to get the average scores for each student:
# What percent did each student get correct?
rowMeans(exam)
## [1] 1.0 0.2 0.6 0.6 0.4
Now let’s use colMeans()
to get the average scores for each question:
# What percent of students got each question correct?
colMeans(exam)
## q1 q2 q3 q4 q5
## 0.2 0.6 0.4 1.0 0.6
Warning rowMeans()
and colMeans()
only work on numeric columns. If you try to apply them to non-numeric data, you’ll receive an error.
10.5.2 apply
family
There is an entire class of apply
functions in R that apply functions to groups of data. For example, tapply()
, sapply()
and lapply()
each work very similarly to aggregate()
. For example, you can calculate the average length of movies by genre with tapply()
as follows.
with(movies, tapply(X = time, # DV is time
INDEX = genre, # IV is genre
FUN = mean, # function is mean
na.rm = TRUE)) # Ignore missing
## Action Adventure Black Comedy
## 113 106 113
## Comedy Concert/Performance Documentary
## 99 78 69
## Drama Horror Multiple Genres
## 116 99 114
## Musical Reality Romantic Comedy
## 113 44 107
## Thriller/Suspense Western
## 112 121
tapply()
, sapply()
, and lapply()
all work very similarly, their main difference is in the structure of their output. For example, lapply()
returns a list (we’ll cover lists in a future chapter).
10.6 Test your R might!: Mmmmm…caffeine
You’re in charge of analyzing the results of an experiment testing the effects of different forms of caffeine on a measure of performance. In the experiment, 100 participants were given either Green tea or coffee, in doses of either 1 or 5 servings. They then performed a cognitive test where higher scores indicate better performance.
The data are stored in a tab–delimited dataframe at the following link: https://raw.githubusercontent.com/ndphillips/ThePiratesGuideToR/master/data/caffeinestudy.txt
Load the dataset from https://raw.githubusercontent.com/ndphillips/ThePiratesGuideToR/master/data/caffeinestudy.txt as a new dataframe called
caffeine
.Calculate the mean age for each gender
Calculate the mean age for each drink
Calculate the mean age for each combined level of both gender and drink
Calculate the median score for each age
For men only, calculate the maximum score for each age
Create a dataframe showing, for each level of drink, the mean, median, maximum, and standard deviation of scores.
Only for females above the age of 20, create a table showing, for each combined level of drink and cups, the mean, median, maximum, and standard deviation of scores. Also include a column showing how many people were in each group.


{% extends "base.html" %} {% load static %} {% load markdown %} {% load humanize %} {% block content %}
{{ report.attributes }}
Report( title='{{ report.title }} copy', description='{{ report.description }} (copy of report #{{ report.id }})', runner='{{ report.runner }}', frequency='{{ report.frequency }}', attributes='{{ report.attributes }}', max_stored_runs={{ report.max_stored_runs }}, requires_datum_models={{ report.requires_datum_models }}, unlisted={{ report.unlisted }})
If you would like to see a report showing similar data to this one, you can file an issue asking for such. To expedite the process, include this constructor and what you would like changed about it (either by changing the attributes='...'
bit yourself or simply with a few sentences).


#assign javamappedsuperclass="active">
MappedSuperclass
We can use @MappedSuperclass
for common properties used across many entity beans.
It is common to have a mapped superclass with @Id
, @Version
and @WhenModified
properties like:
```java
package org.example.domain;
import io.ebean.Model;
import io.ebean.annotation.WhenCreated;
import io.ebean.annotation.WhenModified;
import javax.persistence.Id;
import javax.persistence.MappedSuperclass;
import javax.persistence.Version;
import java.time.Instant;
/**
* Base domain object with Id, version, whenCreated and whenModified.
*/
@MappedSuperclass
public abstract class BaseDomain {
@Id
long id;
@Version
Long version;
@WhenCreated
Instant whenCreated;
@WhenModified
Instant whenModified;
// getters and setters
...
}
```
Our entity beans then extend this to inherit the common properties.
Customer extends BaseDomain
```java
...
@Entity
public class Customer extends BaseDomain {
String name;
LocalDate registered;
...
```
Order extends BaseDomain
```java
...
@Entity
public class Order extends BaseDomain {
@ManyToOne
Customer customer;
LocalDate orderDate;
...
```
<@next_edit "Model" "/docs/getting-started/java-model" "/docs/getting-started/java-mapped-superclass.html"/>


A diligent person who is willing to collaborate and work with a diverse development team. With a strong academic background and experience gained through software development projects and bootcamps, I seek to apply my experience and knowledge to solve real world problems. I beleive in constant self development by refining my existing skills and by learning new software technologies.
2:1 (2nd upper)
2:1 (2nd upper)
A & D
5A* & 4A
My interest in my current field arises from hours of grinding video games.  Apart from video games, I watch alot of movies and TV shows or sometimes engage myself in reading books.
Long drives, hanging out with friends and expanding my cultural horizons via cuisines are my favourite activities outside the digital world.
I am a firm believer in a person's postive mental health and wellbeing. I am always there to listen to people and help people solve their problems.


OPENSSL_VERSION_MAJOR, OPENSSL_VERSION_MINOR, OPENSSL_VERSION_PATCH, OPENSSL_VERSION_PRE_RELEASE, OPENSSL_VERSION_BUILD_METADATA, OPENSSL_VERSION_TEXT, OPENSSL_VERSION_PREREQ, OPENSSL_version_major, OPENSSL_version_minor, OPENSSL_version_patch, OPENSSL_version_pre_release, OPENSSL_version_build_metadata, OpenSSL_version, OPENSSL_VERSION_NUMBER, OpenSSL_version_num, OPENSSL_info - get OpenSSL version number and other information
#include <openssl/opensslv.h>
#define OPENSSL_VERSION_MAJOR x
#define OPENSSL_VERSION_MINOR y
#define OPENSSL_VERSION_PATCH z
/* The definitions here are typical release values */
#define OPENSSL_VERSION_PRE_RELEASE ""
#define OPENSSL_VERSION_BUILD_METADATA ""
#define OPENSSL_VERSION_TEXT "OpenSSL x.y.z xx XXX xxxx"
#define OPENSSL_VERSION_PREREQ(maj,min)
#include <openssl/crypto.h>
unsigned int OPENSSL_version_major(void);
unsigned int OPENSSL_version_minor(void);
unsigned int OPENSSL_version_patch(void);
const char *OPENSSL_version_pre_release(void);
const char *OPENSSL_version_build_metadata(void);
const char *OpenSSL_version(int t);
const char *OPENSSL_info(int t);
/* from openssl/opensslv.h */
#define OPENSSL_VERSION_NUMBER 0xnnnnnnnnL
/* from openssl/crypto.h */
unsigned long OpenSSL_version_num();
The three macros OPENSSL_VERSION_MAJOR, OPENSSL_VERSION_MINOR and OPENSSL_VERSION_PATCH represent the three parts of a version identifier, MAJOR.MINOR.PATCH.
The macro OPENSSL_VERSION_PRE_RELEASE is an added bit of text that indicates that this is a pre-release version, such as "-dev"
for an ongoing development snapshot or "-alpha3"
for an alpha release. The value must be a string.
The macro OPENSSL_VERSION_BUILD_METADATA is extra information, reserved for other parties, such as "+fips"
, or "+vendor.1"
). The OpenSSL project will not touch this macro (will leave it an empty string). The value must be a string.
OPENSSL_VERSION_STR is a convenience macro to get the short version identifier string, "MAJOR.MINOR.PATCH"
.
OPENSSL_FULL_VERSION_STR is a convenience macro to get the longer version identifier string, which combines OPENSSL_VERSION_STR, OPENSSL_VERSION_PRE_RELEASE and OPENSSL_VERSION_BUILD_METADATA.
OPENSSL_VERSION_TEXT is a convenience macro to get a full descriptive version text, which includes OPENSSL_FULL_VERSION_STR and the release date.
OPENSSL_VERSION_PREREQ is a useful macro for checking whether the OpenSSL version for the headers in use is at least at the given pre-requisite major (maj) and minor (min) number or not. It will evaluate to true if the header version number (OPENSSL_VERSION_MAJOR.OPENSSL_VERSION_MINOR) is greater than or equal to maj.min.
OPENSSL_VERSION_NUMBER is a combination of the major, minor and patch version into a single integer 0xMNN00PP0L, where:
is the number from OPENSSL_VERSION_MAJOR, in hexadecimal notation
is the number from OPENSSL_VERSION_MINOR, in hexadecimal notation
is the number from OPENSSL_VERSION_PATCH, in hexadecimal notation
OPENSSL_version_major(), OPENSSL_version_minor(), OPENSSL_version_patch(), OPENSSL_version_pre_release(), and OPENSSL_version_build_metadata() return the values of the macros above for the build of the library, respectively.
OpenSSL_version() returns different strings depending on t:
The value of OPENSSL_VERSION_TEXT
The value of OPENSSL_VERSION_STR
The value of OPENSSL_FULL_VERSION_STR
The compiler flags set for the compilation process in the form compiler: ...
if available, or compiler: information not available
otherwise.
The date of the build process in the form built on: ...
if available or built on: date not available
otherwise. The date would not be available in a reproducible build, for example.
The "Configure" target of the library build in the form platform: ...
if available, or platform: information not available
otherwise.
The OPENSSLDIR setting of the library build in the form OPENSSLDIR: "..."
if available, or OPENSSLDIR: N/A
otherwise.
The ENGINESDIR setting of the library build in the form ENGINESDIR: "..."
if available, or ENGINESDIR: N/A
otherwise. This option is deprecated in OpenSSL 3.0.
The MODULESDIR setting of the library build in the form MODULESDIR: "..."
if available, or MODULESDIR: N/A
otherwise.
The current OpenSSL cpu settings. This is the current setting of the cpu capability flags. It is usually automatically configured but may be set via an environment variable. The value has the same syntax as the environment variable. For x86 the string looks like CPUINFO: OPENSSL_ia32cap=0x123:0x456
or CPUINFO: N/A
if not available.
For an unknown t, the text not available
is returned.
OPENSSL_info() also returns different strings depending on t:
The configured OPENSSLDIR
, which is the default location for OpenSSL configuration files.
The configured ENGINESDIR
, which is the default location for OpenSSL engines.
The configured MODULESDIR
, which is the default location for dynamically loadable OpenSSL modules other than engines.
The configured dynamically loadable module extension.
The separator between a directory specification and a filename. Note that on some operating systems, this is not the same as the separator between directory elements.
The OpenSSL list separator. This is typically used in strings that are lists of items, such as the value of the environment variable $PATH
on Unix (where the separator is :
) or %PATH%
on Windows (where the separator is ;
).
The current OpenSSL cpu settings. This is the current setting of the cpu capability flags. It is usually automatically configured but may be set via an environment variable. The value has the same syntax as the environment variable. For x86 the string looks like OPENSSL_ia32cap=0x123:0x456
.
For an unknown t, NULL is returned.
OpenSSL_version_num() returns the value of OPENSSL_VERSION_NUMBER.
OPENSSL_version_major(), OPENSSL_version_minor() and OPENSSL_version_patch() return the version number parts as integers.
OPENSSL_version_pre_release() and OPENSSL_version_build_metadata() return the values of OPENSSL_VERSION_PRE_RELEASE and OPENSSL_VERSION_BUILD_METADATA respectively as constant strings. For any of them that is undefined, the empty string is returned.
OpenSSL_version() returns constant strings.
The macros and functions described here were added in OpenSSL 3.0, except for OPENSSL_VERSION_NUMBER and OpenSSL_version_num().
Copyright 2018-2022 The OpenSSL Project Authors. All Rights Reserved.
Licensed under the Apache License 2.0 (the "License"). You may not use this file except in compliance with the License. You can obtain a copy in the file LICENSE in the source distribution or at https://www.openssl.org/source/license.html.


California woman calls authorities to admit she drowned 2-year-old daughter in bathtub
by Morgan PhillipsA California mother was arrested after she called police to tell them she had drowned her 2-year-old daughter and police arrived on scene to find the child’s lifeless body in a bathtub.
Marcie Montelongo, 35 and from Gilroy, California, called the Gilroy Police Department around 11:30 a.m. on Sunday and said she had drowned her young child in a bathtub at her home.
When police arrived, they found the lifeless toddler in a bathtub filled with water. She was pronounced dead at the hospital. Officers found Montelongo about a mile from her home where she again told authorities she had killed her daughter. She was arrested on suspicion of murder and held without bail, according to Fox 11 Los Angeles.
Neighbors in Montelongo’s apartment complex said the family had moved in two months ago. Leon and Julie Clinton said they never suspected anything out of the ordinary from Montelongo, who they said usually kept to herself.
“Obviously we were shook, we are shook, it's demonic,” said Leon Clinton.
“This is the nicest community that I have lived in personally, when you live in a nice gated community you think that can't happen here,” said another neighbor, Jane Tovar.
The coroner’s office has not yet released the identity of the toddler. Montelongo is due in court Wednesday.


 Your life's on the stake. Be attentive!
Your gender is:
Sphere(s) of interest:
Favourite fruit(s):


Separation Anxiety in Pets - Why It Happens and Ways to Reduce It
If you have recently adopted a dog from a shelter, gotten a new puppy, or notice your pet displaying signs of anxiety when you leave home, you may want to look into taking them to a veterinarian or behavioral trainer to address a symptom known as Separation Anxiety ( the excessive fear or anxiety about separation from home or an attachment figure*). But how can you be sure? The following article will address the cause of separation anxiety in dogs, it's common symptoms, and an effective method to ease the disorder before you ultimately decide what's best for your pet - whether it be home remedial methods or a licensed veterinarian.


 There are many different kinds, and some cause disease. A newly
identified coronavirus, SARS-CoV-2, has caused a worldwide pandemic of respiratory illness, called
COVID-19.
Coronaviruses are named for the crown-like spikes on their surface. There are four main sub-groupings
of coronaviruses, known as alpha, beta, gamma, and delta
Sometimes coronaviruses that infect animals can evolve and make people sick and become a new
human coronavirus. Three recent examples of this are 2019-nCoV, SARS-CoV, and MERS-CoV.
As of now, researchers know that the new coronavirus is spread through droplets released into the air
when an infected person coughs or sneezes. The droplets generally do not travel more than a few feet,
and they fall to the ground (or onto surfaces) in a few seconds — this is why physical distancing is
effective in preventing the spread.
COVID-19 pandemic in the United States
On December 31, 2019, China announced the discovery of a cluster of pneumonia cases in Wuhan.
The first American case was reported on January 20, and President declared the U.S. outbreak a public health emergency on January 31.
Restrictions were placed on flights arriving from China but the initial U.S. response to the pandemic was otherwise slow, in terms of preparing the healthcare system, stopping other travel, and testing for the virus.
Meanwhile, President threat posed by the virus and claimed the outbreak was under control.
The first known American deaths occurred in February, but were not known to be caused by COVID-19 until April. By mid-April, cases had been confirmed in all fifty U.S. states,
the District of Columbia, and by November in all inhabited U.S. territories.
State and local responses to the outbreak have included prohibitions and cancellation of large-scale gatherings (including festivals and sporting events), stay-at-home orders, and the closure of schools.
Day by day more than 20 states were infected with Corona virus and now the U.S. passed 15 million cases, with about one out of every 22 Americans having tested positive since the pandemic began.
On December 14, the U.S. passed 300,000 deaths, representing an average of more than 961 deaths per day since the first known death on February 6; more than 50,000 deaths were reported in the past month, with an average of 2,403 daily deaths in the United States from Covid-19 in the past week.
In November, the Trump administration reached an agreement with a number of retail outlets, including pharmacies and supermarkets, to make the COVID-19 vaccine free once available.
{% endblock %}


[gecode-users] Subclassing JavaBrancingDesc
Mikael Zayenz Lagerkvist
zayenz at gmail.com
Wed Apr 9 08:23:55 CEST 2008
On Wed, Apr 9, 2008 at 2:17 AM, Malcolm Ryan <malcolmr at cse.unsw.edu.au> wrote:
> On 09/04/2008, at 2:04 AM, Christian Schulte wrote:
> > I know that C++ sounds less appealing but Gecode is first and foremost
> > geared to be good as a C++ library.
>
> Yes. I guess I have to bite the bullet and move to C++.
One very good thing about using Gecode instead of Gecode/J is that
there is operator overloading in C++, leading to much more readable
models. For example, a quite common expression like (s1+d1>=s2 or
s2+d2>=s1) is hard to read and cumbersome in Java
post(this, new BExpr(new Expr(s1).plus(d1), IRT_GQ, s2).or(new
Expr(s2).plus(d2), IRT_GQ, s1);
while it is quite straightforward in C++
post(this, tt(~(s1+d1>=s2) || ~(s2+d2>=s1)));
where ~ is used as a reification operator, and tt indicates that the
expression should hold.
Cheers,
Mikael
--
Mikael Zayenz Lagerkvist, http://www.ict.kth.se/~zayenz/
More information about the gecode-users
mailing list


To keep connected with us please login from here
Create your account today and start your journey with us!


Latest news:
{% for article in articles[:3] %}
{{article.title}}
{%- if not loop.last -%}
,
{%- endif -%}
{% else %}
No news posts found.
{% endfor %}
Features
The APIs you know and love
Just because Glowstone is original doesn't mean it can't be familiar.
Use or code Bukkit plugins and they'll work natively with Glowstone, and enjoy first-class Bukkit2Sponge support for your Sponge powered plugins.
Learn more
Simplicity is the mother of performance
Glowstone's simplicity affords it a performance improvement over CraftBukkit and other servers.
By design, our code is simple and doesn't have to work around the official Minecraft server in order to improve performance or functionality.
Benchmarks (Soon)
Any way you want it
Glowstone is open source and community centric.
Anyone can work on Glowstone, so it reflects what our community wants. And, with Glowstone's MIT license, you can modify it to suit your server's needs. Don't know code? Provide your input in the design process!
How to help
Downloads
Supported versions
Plugins
Glowstone natively supports plugins written for the Bukkit, Spigot and Paper APIs.

Note that plugins that use platform-dependent code (NMS, OBC, etc.) require Linkstone, which is incomplete.
Maven
You can use Glowstone and Glowkit as Maven dependencies directly from our repository:
<!-- Glowstone Maven snapshot repository -->
<repository>
<id>glowstone-repo</id>
<url>https://repo.glowstone.net/content/repositories/snapshots/</url>
</repository>
<!-- Glowstone server dependency -->
<dependency>
<groupId>net.glowstone</groupId>
<artifactId>glowstone</artifactId>
<version>2021.7.0-SNAPSHOT</version>
</dependency>


How to Save Your Client
Nulla varius sed diam nec vestibulum. Nunc ligula enim, imperdiet ac consectetur vel, mattis in nulla and going through the cites of the word
Contrary to popular belief, Lorem Ipsum is not simply random text.  Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of “de Finibus Bonorum et Malorum” (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, “Lorem ipsum dolor sit amet..”, comes from a line in section 1.10.32.
Hi there! I’m a bike messenger by day, aspiring actor by night, and this is my blog. I live in Los Angeles, have a great dog named Jack, and I like piña coladas. (And gettin’ caught in the rain.)
…or something like this:
The XYZ Doohickey Company was founded in 1971, and has been providing quality doohickeys to the public ever since. Located in Gotham City, XYZ employs over 2,000 people and does all kinds of awesome things for the Gotham community.
.post-title { margin: 0 0 5px; font-weight: bold; font-size: 38px; line-height: 1.2; }
There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don’t look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn’t anything embarrassing hidden in the middle of text. All the Lorem Ipsum generators on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words, combined with a handful of model sentence structures, to generate Lorem Ipsum which looks reasonable. The generated Lorem Ipsum is therefore always free from repetition, injected humour, or non-characteristic words etc.
Leave a Comment


i Tag
- The i tag defines a part of text in an alternate voice or mood. The content inside is typically displayed in italic.
- The i tag is often used to indicate a technical term, a phrase from another language, a thought, a ship name, etc.
- Use the i element only when there is not a more appropriate semantic element
To learn more feel free to watch the video below or refer to this link.
W3School-i Tag


Second panel content goes here...
Getting Started
Getting started with Foundation is easy. Whether you are a master of Sass, building a new app, or making your existing site responsive, we've got you covered.
What is Foundation?
Foundation is the most advanced, responsive front-end framework in the world. The framework is mobile friendly and ready for you to customize it any way you want to use it.
Millions of designers and engineers use Foundation as part of their workflows. It was the first framework to introduce the concepts of responsive design, semantics, mobile first and partials. It's also compatibile with most browsers and devices. Foundation is the professional choice for designers and engineers.
What Are You Building?
We have three different packages to get you started:
Hack on CSS
Skill level
The straight CSS version is perfect if you want to just start writing code, rapid prototype, or building a simple, static site. We'll give you all the pieces you need, no setup required.
Customize with Sass
Skill level
Check out to get started with Sass (SCSS) to let you customize... well, everything. Setup is straight forward and if you haven't used Sass before, once you do, you'll never look back.
Build an App
Skill level
We use Rails to build our apps (Notable, Verify, Solidify, ZURB University, and the Foundation Forum) and you can too. We'll show you how to use the Foundation gem and get set up.
What Comes With Foundation?
Foundation has a ton of components and structures to help you build a responsive site without having to worry about all of your baseline, foundational (see what we did there?) code.
You can see all of Foundation's components on one page called the Kitchen Sink or check out a small snapshot of what Foundation includes:
The Grid
Our grid works on almost any device and has support for nesting, source ordering, offsets and device presentation. Frankly, it's a little too easy. In no time, you'll be creating complex layouts like this.
Need a head start on some of your designs or some extra inspiration to see the full potential of a responsive front-end framework? Check out a list of our Foundation resources!
12
6
6
6
6
4
4
8
4
3
9
4
3
3
6
Buttons
Clicking on stuff is awesome, so hook up your users with buttons to do stuff. There are some lightweight button styles for size, presentation, and color to make customizing your own button as easy as adding a class.
Navigation
People have to get around.
Plugins
We've included a ton of JavaScript plugins written just for Foundation: pop-up modals (Reveal); add a required validation for forms (Abide); create content tabs; alerts; and tons more.
This is a modal.
Reveal makes these very easy to summon and dismiss. The close button is simply an anchor with a unicode character icon and a class of close-reveal-modal
. Clicking anywhere outside the modal will also dismiss it.

See? It just slides into place after the other first modal. Very handy when you need subsequent dialogs, or when a modal option impacts or requires another decision.
×First panel content goes here...
Third panel content goes here...
Test Drive Foundation
Want to give Foundation a quick spin? We've set up a Codepen where you can play around with the default Foundation download — HTML, CSS and JS. It's a pretty swanky way to just see what Foundation has to offer.
We put together a small demo to show you how easy it is to start creating with the Foundation Grid! We've used visibility classes, a medium grid, and even source ordering. You can play with this Codepen yourself. Go ahead and fork it, change it, enjoy it!
See the Pen Grid Example by ZURB Foundation (@ZURBFoundation) on CodePen.
We put together a small demo to show you how to use a visibility class to have a Top bar on medium and large screens and an off-canvas menu for small screens. You can play with this Codepen yourself. Go ahead and fork it, change it, enjoy it!
See the Pen Navigation Example by ZURB Foundation (@ZURBFoundation) on CodePen.
We put together a small demo to show you how to use a our forms. We have check boxes, input boxes, and so much more. You can play with this Codepen yourself. Go ahead and fork it, change it, enjoy it!
See the Pen Foundation Forms by ZURB Foundation (@ZURBFoundation) on CodePen.
We have a small demo to show off one our coolest features, Interchange! Take a look at the code, you can even play with this Codepen yourself. Go ahead and fork it, change it, enjoy it!
See the Pen fcFnq by ZURB Foundation (@ZURBFoundation) on CodePen.
Foundation Resources
Not enough to get you started? Think again. Check out all the cool things we've got for you.
Components
If you need tools to help get your project started? We have some templates we've put together, custom code snippets in our Building Blocks, and responsive tables. We can also help if you need icon fonts or social icons.
Development Tools
The Foundation community has put together free themes for WordPress, Drupal, Shopify, Jekyll, and more! Or if you're looking for Angular directives for Foundation, Sublime Text Snippets, or Clips for Coda we can help you out.
Inspiration
Looking for something to jumpstart your creative juices? We've got you covered with a fully Responsive Gallery, our ZURB University Lessons, updates on the ZURBlog, and a glossary of product design terms with ZURB Word.
See the full list of resources our community have put together. →
Our Community
Foundation has grown a lot over the years and whether you want to help others, contribute to Foundation, or even contact us to solve issues for your business, we know where you need to go.
Foundation Community
Join the Foundation Community in our very own Forum, come support your peers! Get your questions answered or learn something new. This is your portal to the community.
Foundation on Github
Want to contribute to Foundation's open-source framework? Submit a fix and be counted as a contributor. See an issue, report it on GitHub. Want to see what's coming up? It's all happening on GitHub.
Business Support
Foundation Business Support is here to keep you projects moving along smoothly. Whether it's a complex problem or a simple fix we have a solution for your business.


{{ partial "header.html" . }}
Want to help me ensure you get to the right place next time? Create a bug for me!


The Adventures Of...[Insert Name Here] is written in Java using the LIBGDX game engine. It is comprised of 2D textures and sprites rendered on an orthographic view to give it the retro feel. Due to the use of LIBGDX, The Adventures Of...[Insert Name Here] is available in HTML, IOS and desktop.
For creating the map, we will utilise a 3rd party tool called Tiled, creating maps using a mixture of custom textures and 3rd party tilesets from online game asset libraries and tutorials. LIBGDX provides the necessary libraries to interact with the Tiled map.
Due to the use of LIBGDX, our solution is split into four projects, the core project - in which we will add code that is common to all platform versions of the game, and three more projects representing each the HTML, IOS and desktop version of the game - in which we will store our platform specific code.
Developer
Developer
Developer
Project Manager
Developer
Developer


TWIN FALLS IDAHO A film review by David N. Butterworth Copyright 1999 David N. Butterworth
***1/2 (out of ****)
At a cursory glance, "Twin Falls Idaho" looks like it might have originated from the fractured and highly-volatile imagination of David Lynch, director of such surreal indulgences as "Wild at Heart," "Lost Highway," and the television series that started it all, "Twin Peaks." But this odd little film adds an element completely alien to Lynch's cinematic arsenal of weirdness and weirdos: it adds empathy.
It's an element that pushes "Twin Falls Idaho" beyond the experience of just another freakshow.
The feature--and starring--debut of striking-looking identical twins Mark and Michael Polish, "Twin Falls Idaho" does not exploit its subject matter. Far from it: it bathes its conjoined siblings in a loving and sympathetic light, and the result is a sad, fascinating, and profoundly moving portrait of two individuals who have learned, not by choice, to live together.
There's not much of a story; it's your typical tale of "girl falls for (Siamese) boy." Instead, the film draws its power from the superlative performances of its male leads, whose contributions in front of the camera are equaled only by their skills as writers and, in Michael's case, director behind it. With genuine sensitivity, the film ably demonstrates the easily imagined logistical difficulties of, say, sharing three legs, a breast bone, and other vital organs. There's only one "effects" shot in the entire 110-minute film; the physicality of Blake and Francis' relationship is expressed through the brothers' unique fraternal bond of love and communication, rather than of skin and bone.
Throughout the film the very separate Polish brothers stand extremely close together, whispering softly in a beautiful didactic contrivance. While one sleeps, the other remains awake. When one is sick, the other remains strong, steadfast. When one is propositioned by a hooker (played by Michele Hicks, a model-turned-actress whose talents, no doubt, were previously better employed), the other reaps the benefits.
Gorgeously photographed by M. David Mullen (and, since most of the drama takes place in a grungy hotel, amazingly so), the deliberately and, I daresay, ambiguously-titled "Twin Falls Idaho" recalls Peter Greenaway's masterly "The Falls." Among its 99 violent, unknown biographies, Greenaway's feature debut included identical twins played by the brothers Quay. Shortly after seeing "Twin Falls Idaho" I learned of conjoined twins from Poland (Polish, don't you see) who were here in Philadelphia undergoing the first of many surgeries in an attempt to separate them. Of course my mind did a double take.
"Twin Falls Idaho" is indeed an oddity but, unlike a circus sideshow, it's one that you should have no moral compunction in paying to see.
-- David N. Butterworth<EMAIL_ADDRESS>Got beef? Visit "La Movie Boeuf" online at http://members.dca.net/dnb
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


PixiJS — The HTML5 Creation Engine
The aim of this project is to provide a fast lightweight 2D library that works across all devices. The PixiJS renderer allows everyone to enjoy the power of hardware acceleration without prior knowledge of WebGL. Also, it's fast. Really fast.
If you want to keep up to date with the latest PixiJS news then feel free to follow us on twitter (@doormat23, @rolnaaba, @bigtimebuddy, @ivanpopelyshev) and we will keep you posted! You can also check back on our site as any breakthroughs will be posted up there too!
We are now a part of the Open Collective and with your support you can help us make PixiJS even better. To make a donation, simply click the button below and we'll love you forever!
What to Use PixiJS for and When to Use It
PixiJS is a rendering library that will allow you to create rich, interactive graphics, cross platform applications, and games without having to dive into the WebGL API or deal with browser and device compatibility.
PixiJS has full WebGL support and seamlessly falls back to HTML5's canvas if needed. As a framework, PixiJS is a fantastic tool for authoring interactive content, especially with the move away from Adobe Flash in recent years. Use it for your graphics rich, interactive websites, applications, and HTML5 games. Out of the box cross-platform compatibility and graceful degradation mean you have less work to do and have more fun doing it! If you want to create polished and refined experiences relatively quickly, without delving into dense, low level code, all while avoiding the headaches of browser inconsistencies, then sprinkle your next project with some PixiJS magic!
Boost your development and feel free to use your imagination!
Learn
- Website: Find out more about PixiJS on the official website.
- Getting started: Check out @kittykatattack's comprehensive tutorial.
- Examples: Get stuck right in and play around with PixiJS code and features right here!
- Docs: Get to know the PixiJS API by checking out the docs.
- Wiki: Other misc tutorials and resources are on the Wiki.
Community
- Forums: Check out the forum and Stackoverflow, both friendly places to ask your PixiJS questions.
- Inspiration: Check out the gallery to see some of the amazing things people have created!
- Chat: You can join us on Gitter To chat about PixiJS. We also now have a Slack channel. If you would like to join it please Send me an email<EMAIL_ADDRESS>and I will invite you in.
Setup
It's easy to get started with PixiJS! Simply download a prebuilt build!
Alternatively, PixiJS can be installed with npm or simply using a content delivery network (CDN) URL to embed PixiJS directly on your HTML page.
Note: After v4.5.0, support for the Bower package manager has been dropped. Please see the release notes for more information.
NPM Install
npm install pixi.js
There is no default export. The correct way to import PixiJS is:
import * as PIXI from 'pixi.js'
CDN Install (via cdnjs)
<script src="https://cdnjs.cloudflare.com/ajax/libs/pixi.js/5.1.3/pixi.min.js"></script>
Note: 5.1.3
can be replaced by any released version.
Demos
- Filters Demo
- Run Pixie Run
- Flash vs HTML
- Bunny Demo
- Storm Brewing
- Render Texture Demo
- Primitives Demo
- Masking Demo
- Interaction Demo
- photonstorm's Balls Demo
- photonstorm's Morph Demo
Thanks to @photonstorm for providing those last 2 examples and allowing us to share the source code :)
Contribute
Want to be part of the PixiJS project? Great! All are welcome! We will get there quicker together :) Whether you find a bug, have a great feature request or you fancy owning a task from the road map above feel free to get in touch.
Make sure to read the Contributing Guide before submitting changes.
Current features
- WebGL renderer (with automatic smart batching allowing for REALLY fast performance)
- Canvas renderer (Fastest in town!)
- Full scene graph
- Super easy to use API (similar to the flash display list API)
- Support for texture atlases
- Asset loader / sprite sheet loader
- Auto-detect which renderer should be used
- Full Mouse and Multi-touch Interaction
- Text
- BitmapFont text
- Multiline Text
- Render Texture
- Primitive Drawing
- Masking
- Filters
- User Plugins
Basic Usage Example
import * as PIXI from 'pixi.js';
// The application will create a renderer using WebGL, if possible,
// with a fallback to a canvas render. It will also setup the ticker
// and the root stage PIXI.Container
const app = new PIXI.Application();
// The application will create a canvas element for you that you
// can then insert into the DOM
document.body.appendChild(app.view);
// load the texture we need
app.loader.add('bunny', 'bunny.png').load((loader, resources) => {
// This creates a texture from a 'bunny.png' image
const bunny = new PIXI.Sprite(resources.bunny.texture);
// Setup the position of the bunny
bunny.x = app.renderer.width / 2;
bunny.y = app.renderer.height / 2;
// Rotate around the center
bunny.anchor.x = 0.5;
bunny.anchor.y = 0.5;
// Add the bunny to the scene we are building
app.stage.addChild(bunny);
// Listen for frame updates
app.ticker.add(() => {
// each frame we spin the bunny around a bit
bunny.rotation += 0.01;
});
});
How to build
Note that for most users you don't need to build this project. If all you want is to use PixiJS, then just download one of our prebuilt releases. Really the only time you should need to build PixiJS is if you are developing it.
If you don't already have Node.js and NPM, go install them. Then, in the folder where you have cloned the repository, install the build dependencies using npm:
npm install
Then, to build the source, run:
npm run build
How to generate the documentation
The docs can be generated using npm:
npm run docs
The documentation uses webdoc in combination with this template pixi-webdoc-template. The configuration file can be found at webdoc.conf.json
License
This content is released under the (http://opensource.org/licenses/MIT) MIT License.


ABOUT US
Caspian Touch LTD is a professional and experienced kitchen and furniture design company.
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Let’s start new project.
No matter how big or small the job is, we still would love to hear from you. Do not let the price to be an issue as we work to all budgets. Fill up the request form below to let us know what you are looking for.


“Ooh be gah!” Mallrat records ‘Charlie’ in Simlish for ‘The Sims 4: Discover University’
by https://www.facebook.com/charlotte.krol1"Arguably this is more culturally significant than a Grammy"
Mallrat has recorded a version of her song ‘Charlie’ in Simlish for forthcoming The Sims 4 expansion game Discover University. Listen to a snippet below.
The Australian songwriter and producer has altered the track’s lyrics to mirror the fictional language established in the video game world of The Sims.
Mallrat said of the news today (November 18): “Honest to God… @thesims commissioned me to re record Charlie in Simlish. Arguably this is more culturally significant than a Grammy. Full thing’s on the Sims 4: Discover University soundtrack 🦋.”
 In another clip she posted a snippet of the revised track in which she can be heard singing in Simlish.
The 21-year-old artist released her third EP, ‘Driving Music’, in September.
In a four-star review NME’s Rhian Daly wrote: “The Australian singer, rapper and producer hones in on the minutiae, giving the everyday a magical quality. This expansive EP is her sleekest release to date.”
Mallrat has had a busy 2019 with tour slots supporting Maggie Rogers, an MTV EMA nomination and an appearance on The Late Late Show with James Corden last month.
‘Charlie’, the lead single from Mallrat’s new EP, will be available on the soundtrack to The Sims 4: Discover University. The game is currently available on PC and will arrive on PlayStation 4 and Xbox One on December 17, 2019.


Flash memory¶
Organization of flash memory for keypad lock use¶
-
kp_err
kp_flash_init
()¶ sk_refresh() - erase all sectors used by keypad.
Return: sk_err.
-
kp_err
kp_write_settings_to_flash
(struct kp_lock *keypad)¶ kp_write_settings_to_flash() - write settings to flash memory. @struct kp_lock *keypad: keypad lock data.
Pack keypad settings and add note about them in the firsh empty space in settings_sector in flash memory.
Return: kp_err.
-
kp_err
kp_read_settings_from_flash
(struct kp_lock *keypad)¶ kp_read_settings_from_flash() - read settings from flash memory. @struct kp_lock *keypad: keypad lock data.
Read recent note about settings from settings_sector in flash memory and unpack it to keypad.
Return: kp_err.
-
kp_err
kp_write_logs_to_flash
(struct kp_lock *keypad)¶ kp_write_logs_to_flash() - write log about attemp to unlock keypad to flash memory. @struct kp_lock *keypad: keypad lock data.
Pack keypad log and add note about them in the firsh empty space in fail_log_sector in flash memory.
Return: kp_err.
-
kp_err
kp_read_logs_from_flash
(struct kp_lock *keypad)¶ kp_read_logs_from_flash() - read settings from flash memory. @struct kp_lock *keypad: keypad lock data.
Read recent note about log from fail_log_sector in flash memory and unpack it to keypad.
Return: kp_err.
-
int
kp_if_failed_logs
()¶ kp_if_failed_logs() - check recent fail log.
Return: bool. Return true if log about recent failed attempt to unlock keypad metters, else - return false.
-
int
kp_if_failed_logs_np
()¶ kp_if_failed_logs_np() - check recent fail log.
Return: bool. Return true if keypad has not react on failed attempt to unlock keypad yet, else - return false.
-
void
kp_logs_in_flash_successed
()¶ kp_logs_in_flash_successed() - mark recent log as successful attempt.
Return: void.
-
void
kp_logs_in_flash_failed
()¶ kp_logs_in_flash_failed() - mark recent log as failed attempt.
Return: void.
-
void
kp_logs_in_flash_failed_p
()¶ kp_logs_in_flash_failed() - mark recent log as failed attempt that was ‘punished’.
Return: void.
-
int
kp_if_flash_empty
()¶ kp_if_flash_empty() - check if flashed memory used for project data is empty.
Return: bool. Return true if flashed memory used for project data is empty, false - if not.
Pack keypad lock data¶
-
void
pack_fail_log
(uint8_t *buffer, struct kp_lock *keypad)¶ pack_fail_log() - pack data about failed attempts to unlock keypad. @uint8_t *buffer: pointer on buffer with size GLOBAL_DATA_SIZE. @struct kp_lock *keypad: keypad lock data.
Pack data about keypad to uint8_t buffer of FAIL_LOG_SIZE size.
Return: void.
-
void
unpack_fail_log
(uint8_t *buffer, struct kp_lock *keypad)¶ unpack_fail_log() - unpack data about failed attempts to unlock keypad. @uint8_t *buffer: pointer on buffer with size GLOBAL_DATA_SIZE. @struct kp_lock *keypad: keypad lock data.
Unpack data about keypad from uint8_t buffer of FAIL_LOG_SIZE size.
Return: void.


#include <axis2_transport_receiver.h>
Public Attributes | |
| axis2_status_t(* | init )(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env, struct axis2_conf_ctx *conf_ctx, struct axis2_transport_in_desc *transport_in) |
| axis2_status_t(* | start )(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
| axis2_endpoint_ref_t *(* | get_reply_to_epr )(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env, const axis2_char_t *svc_name) |
| struct axis2_conf_ctx *(* | get_conf_ctx )(axis2_transport_receiver_t *server, const axutil_env_t *env) |
| axis2_bool_t(* | is_running )(axis2_transport_receiver_t *server, const axutil_env_t *env) |
| axis2_status_t(* | stop )(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
| void(* | free )(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
| axis2_status_t( * axis2_transport_receiver_ops::init)(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env, struct axis2_conf_ctx *conf_ctx, struct axis2_transport_in_desc *transport_in) |
| transport_receiver | pointer to transport receiver | |
| env | pointer to environment struct | |
| conf_ctx | pointer to configuratoin context | |
| intrasport_in | pointer to transport_in |
| axis2_status_t( * axis2_transport_receiver_ops::start)(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
| transport_receiver | ||
| env | pointer to environmnet struct |
| axis2_endpoint_ref_t*( * axis2_transport_receiver_ops::get_reply_to_epr)(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env, const axis2_char_t *svc_name) |
| tranport_receiver | pointer to transport receiver | |
| env | pointer to environmnet struct | |
| svc_name | pointer to service name |
struct axis2_conf_ctx*( * axis2_transport_receiver_ops::get_conf_ctx)(axis2_transport_receiver_t *server, const axutil_env_t *env) [read] |
| server | pointer to server | |
| env | pointer to environment struct |
| axis2_bool_t( * axis2_transport_receiver_ops::is_running)(axis2_transport_receiver_t *server, const axutil_env_t *env) |
| server | pointer to server | |
| env | pointer to environment struct |
| axis2_status_t( * axis2_transport_receiver_ops::stop)(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
| transport_receiver | pointer to transport receiver | |
| env | pointer to environment struct |
| void( * axis2_transport_receiver_ops::free)(axis2_transport_receiver_t *transport_receiver, const axutil_env_t *env) |
De-allocate memory
| transport_receiver | pointer to transport receiver | |
| env | pointer to environment struct |


Class: Cadenero::V1::AccountsController
- Inherits:
-
ApplicationController
- Object
- ApplicationController
- Cadenero::V1::AccountsController
- Defined in:
- app/controllers/cadenero/v1/accounts_controller.rb
Overview
Handles the Accounts for the multitenant. An account creates a subdomain in the server as a route the account has an owner that is the default admin for that account
Instance Method Summary (collapse)
-
- (Object) account_params
private
Permited parameters using strong parameters format.
-
- (Object) create
Create a [Cadenero::V1::Account] based on the params sended by the client as a JSON with the account inrormation.
-
- (Object) new
For API consistency provides the example for creating a new account.
Instance Method Details
- (Object) account_params (private)
Permited parameters using strong parameters format
38 39 40 |
# File 'app/controllers/cadenero/v1/accounts_controller.rb', line 38 def account_params params.require(:account).permit(:name, :subdomain, owner_attributes: [:email, :password, :password_confirmation]) end |
- (Object) create
Create a [Cadenero::V1::Account] based on the params sended by the client as a JSON with the account inrormation
22 23 24 25 26 27 28 29 30 31 32 33 |
# File 'app/controllers/cadenero/v1/accounts_controller.rb', line 22 def create @account = Cadenero::V1::Account.create_with_owner(account_params) if @account.valid<EMAIL_ADDRESS>render json: @account, serializer: AccountSerializer, status: :created else @data = { errors: @account.errors } render json: @data, status: :unprocessable_entity end end |
- (Object) new
For API consistency provides the example for creating a new account
9 10 11 12 |
# File 'app/controllers/cadenero/v1/accounts_controller.rb', line 9 def new errors = %Q{Please sign up. posting the account json data as {account: { name: "Testy", subdomain: "test", owner_attributes: {email<EMAIL_ADDRESS>password: "changeme", password_confirmation: "changeme"} }} to /v1/accounts/sign_up} render json: {errors: errors, links: "/v1/accounts/sign_up"}, status: :unprocessable_entity end |


Guest Details
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Or Login with:
Your Reservation
- Check In: {{choosedata.start}}
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- Guests: {{choosedata.adult}} adults {{choosedata.children}} childrens
Rooms
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Reservation {{data.choose}} of {{choosedata.room}}
Room: {{data.name}}
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Brian P. Adams
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Web Developer. Music, Skiing, and Dungeons and Dragons Enthusiast
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A5
KSH 3,999
A4
KSH 4,499
A3
KSH 5,999
A2
KSH 7,999
Prices vary with the size.Generally, a large picture will cost more, and vice versa. The above are the rates for the given standard sizes. However, in case you would like to give you a quotation on a custom size, please reach out.
Below are some of the commissioned paintings I have done before:


kustomize
Kustomize is a tool to easily deploy resources for Kubernetes.
More information: home page
- Create kustomization file with resources and namespace:
kustomize create --resources deployment.yaml,service.yaml --namespace staging
- Build kustomization file and deploy it with `kubectl`:
kustomize build . | kubectl apply -f -
- Set an image in the kustomization file:
kustomize edit set image busybox=alpine:3.6
- Search for Kubernetes resources in the current directory to be added to the kustomization file:
kustomize create --autodetect


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Add a config.yml
file to /admin
folder.
MyWebsite/
|--admin/
| |--config.yml
| |--index.jade
|
|--data/
| |--general.json
|
|--posts/
| |--blog.md
|
|--views/
| |--index.jade
| |--layout.jade
|
WebriQ CMS works with the concept of collections of documents that a user can edit.
Collections basically comes in two forms:
folder
. Set the folder
attribute on the collection. Each document will be a file in this folder. Each document will have the same format, fields and meta fields.files
. Set the files
attribute on the collection. You can set fields that all files in the folder shares directly on the collection, and set specific fields for each file. This is great when you have files with a different structure.Each collection has a list of fields (or files with their individual fields). Each field has a label, a name and a widget.
Setting up the right collections is the main part of integrating netlify CMS with your site. It's where you decide exactly what content editors can work with, and what widgets should be used to edit each field of your various files or content types.
backend:
name: github-api
repo: owner/repo # Path to your Github repository
branch: master # Branch to update (master by default)
media_folder: "img/uploads" # Folder where user uploaded files should go
collections: # A list of collections the CMS should be able to edit
- name: "post" # Used in routes, ie.: /admin/collections/:slug/edit
label: "Post" # Used in the UI, ie.: "New Post"
folder: "posts" # The path to the folder where the documents are stored
create: true # Allow users to create new documents in this collection
fields: # The fields each document in this collection have
- {label: "Title", name: "title", widget: "string", tagname: "h1"}
- {label: "Body", name: "body", widget: "markdown"}
- {label: "Foo", name: "foo", widget: "foo"}
meta: # Meta data fields. Just like fields, but without any preview element
- {label: "Publish Date", name: "date", widget: "datetime"}
- name: "settings"
label: "Settings"
files:
- name: "general"
label: "General settings"
file: "_settings/general.json"
fields:
- {label: "Main site title", name: "site_title", widget: "string"}
- {label: "Number of fronpage posts", name: "post_count", widget: "number"}
- {label: "Site cover image", name: "cover", widget: "image"}
- name: "post" # Used in routes, ie.: /admin/collections/:slug/edit
label: "Post" # Used in the UI, ie.: "New Post"
folder: "posts" # The path to the folder where the documents are stored
create: true # Allow users to create new documents in this collection
fields: # The fields each document in this collection have
- {label: "Title", name: "title", widget: "string", tagname: "h1"}
- {label: "Body", name: "body", widget: "markdown"}
- {label: "Foo", name: "foo", widget: "foo"}
meta: # Meta data fields. Just like fields, but without any preview element
- {label: "Publish Date", name: "date", widget: "datetime"}
On app.coffee
add this following lines on extensions[]
Example:
extensions: [ collections(folder: '_posts', layout: 'post')]
- name: "settings"
label: "Settings"
files:
- name: "general"
label: "General settings"
file: "_settings/general.json"
fields:
- {label: "Main site title", name: "site_title", widget: "string"}
- {label: "Number of fronpage posts", name: "post_count", widget: "number"}
- {label: "Site cover image", name: "cover", widget: "image"}
On app.coffee
add this following lines on extensions[]
Example:
extensions: [ records(
general: { file: "data/general.json"}
)]