12.3. Class ScopeEvery class defines its own new scope and a unique type. The declarations of the class members within the class body introduce the member names into the scope of their class. Two different classes have two different class scopes.
class First {
public:
int memi;
double memd;
};
class Second {
public:
int memi;
double memd;
};
First obj1;
Second obj2 = obj1; // error: obj1 and obj2 have different types
Using a Class MemberOutside the class scope, members may be accessed only through an object or a pointer using member access operators dot or arrow, respectively. The left-hand operand to these operators is a class object or a pointer to a class object, respectively. The member name that follows the operator must be declared in the scope of the associated class: Class obj; // Class is some class type Class *ptr = &obj; // member is a data member of that class ptr->member; // fetches member from the object to which ptr points obj.member; // fetches member from the object named obj // memfcn is a function member of that class ptr->memfcn(); // runs memfcn on the object to which ptr points obj.memfcn(); // runs memfcn on the object named obj Some members are accessed using the member access operators; others are accessed directly from the class using the scope operator, (::). Ordinary data or function members must be accessed through an object. Members that define types, such as Screen::index, are accessed using the scope operator. Scope and Member DefinitionsMember definitions behave as if they are in the scope of the class, even if the member is defined outside the class body. Recall that member definitions that appear outside the class body must indicate the class in which the member appears: double Sales_item::avg_price() const { if (units_sold) return revenue/units_sold; else return 0; } Here we use the fully qualified name Sales_item::avg_price to indicate that the definition is for the avg_price member in the scope of the Sales_item class. Once the fully qualified name of the member is seen, the definition is known to be in class scope. Because the definition is in class scope, we can refer to revenue and units_sold without having to write this->revenue or this->units_sold. Parameter Lists and Function Bodies Are in Class ScopeIn a member function defined outside the class, the parameter list and member-function body both appear after the member name. These are defined inside the class scope and so may refer to other class members without qualificationfor example, the definition of the two-parameter version of get in class Screen: char Screen::get(index r, index c) const { index row = r * width; // compute the row location return contents[row + c]; // offset by c to fetch specified character } This function uses the type name index defined inside Screen to name the types of its parameters. Because the parameter list is inside the scope of class Screen, there is no need to specify that we want Screen::index. It is implicit that the one we want is the one defined in the current class scope. Similarly, the uses of index, width, and contents all refer to names declared inside class Screen. Function Return Types Aren't Always in Class ScopeIn contrast to the parameter types, the return type appears before the member name. If the function is defined outside the class body, then the name used for the return type is outside the class scope. If the return type uses a type defined by the class, it must use the fully qualified name. For example, consider the get_cursor function: class Screen { public: typedef std::string::size_type index; index get_cursor() const; }; inline Screen::index Screen::get_cursor() const { return cursor; } The return type of this function is index, which is a type name defined inside the Screen class. If we define get_cursor outside the class body, the code is not in the class scope until the function name has been processed. When the return type is seen, its name is used outside of the class scope. We must use the fully qualified type name, Screen::index to specify that we want the name index that is defined inside class Screen.
12.3.1. Name Lookup in Class ScopeIn the programs we've written so far, name lookup (the process of finding which declaration is matched to a given use of a name) has been relatively straightforward:
If no declaration is found, then the program is in error. In C++ programs, all names must be declared before they are used. Class scopes may seem to behave a bit differently, but in reality they obey this same rule. Confusion can arise due to the way names are resolved inside a function defined within the class body itself.
Of course, the names used in class scope do not always have to be class member names. Name lookup in class scope finds names declared in other scopes as well. During name lookup, if a name used in class scope does not resolve to a class member name, the scopes surrounding the class or member definition are searched to find a declaration for the name. Name Lookup for Class Member DeclarationsNames used in the declarations of a class member are resolved as follows:
typedef double Money; class Account { public: Money balance() { return bal; } private: Money bal; // ... }; When processing the declaration of the balance function, the compiler first looks for a declaration of Money in the scope of the class Account. The compiler considers only declarations that appear before the use of Money. Because no member declaration is found, the compiler then looks for a declaration of Money in global scope. Only the declarations located before the definition of the class Account are considered. The declaration for the global typedef Money is found and is used for the return type of the function balance and the data member bal.
The compiler handles member declarations in the order in which they appear in the class. As usual, a name must be defined before it can be used. Moreover, once a name has been used as the name of a type, that name may not be redefined: typedef double Money; class Account { public: Money balance() { return bal; } // uses global definition of Money private: // error: cannot change meaning of Money typedef long double Money; Money bal; // ... }; Name Lookup in Class Member DefinitionsA name used in the body of a member function is resolved as follows:
Class Members Follow Normal Block-Scope Name Lookup
The following function uses the same name for a parameter and a member, which normally should be avoided. We do so here to show how names are resolved: // Note: This code is for illustration purposes only and reflects bad practice // It is a bad idea to use the same name for a parameter and a member int height; class Screen { public: void dummy_fcn(index height) { cursor = width * height; // which height? The parameter } private: index cursor; index height, width; }; When looking for a declaration for the name height used in the definition of dummy_fcn, the compiler first looks in the local scope of that function. A function parameter is declared in the local scope of its function. The name height used in the body of dummy_fcn refers to this parameter declaration. In this case, the height parameter hides the member named height.
If we wanted to override the normal lookup rules, we could do so: // bad practice: Names local to member functions shouldn't hide member names void dummy_fcn(index height) { cursor = width * this->height; // member height // alternative way to indicate the member cursor = width * Screen::height; // member height } After Function Scope, Look in Class ScopeIf we wanted to use the member named height, a much better way to do so would be to give the parameter a different name: // good practice: Don't use member name for a parameter or other local variable void dummy_fcn(index ht) { cursor = width * height; // member height } Now when the compiler looks for the name height, it will not find that name in the function. The compiler next looks in the Screen class. Because height is used inside a member function, the compiler looks at all the member declarations. Even though the declaration of height appears after its use inside dummy_fcn, the compiler resolves this use to the data member named height. After Class Scope, Look in the Surrounding ScopeIf the compiler doesn't find the name in function or class scope, it looks for the name in the surrounding scope. In our example, declarations in global scope that appear before the definition of the Screen include a global object named height. However, that object is hidden.
// bad practice: Don't hide names that are needed from surrounding scopes void dummy_fcn(index height) { cursor = width * ::height;// which height? The global one } Names Are Resolved Where They Appear within the FileWhen a member is defined outside the class definition, the third step of name lookup not only considers the declarations in global scope that appear before the definition of class Screen, but also considers the global scope declarations that appear before the member function definitionfor example: class Screen { public: // ... void setHeight(index); private: index height; }; Screen::index verify(Screen::index); void Screen::setHeight(index var) { // var: refers to the parameter // height: refers to the class member // verify: refers to the global function height = verify(var); } Notice that the declaration of the global function verify is not visible before the definition of the class Screen. However, the third step of name lookup considers the surrounding scope declarations that appear before the member definition, and the declaration for the global function verify is found. |


WQMY
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|


Aliases for integer constraints
[Direct modelling]
Detailed Description
Contains definitions of common constraints which have different names in Gecode.
Functions | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, int n, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, IntVar y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, const IntArgs &y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, int n, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, IntVar y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atmost (Space *home, const IntVarArgs &x, const IntArgs &y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, int n, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, IntVar y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, const IntArgs &y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, int n, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, IntVar y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::atleast (Space *home, const IntVarArgs &x, const IntArgs &y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, int n, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, IntVar y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, const IntArgs &y, int m, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, int n, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, IntVar y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::exactly (Space *home, const IntVarArgs &x, const IntArgs &y, IntVar z, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for . | |
| void | Gecode::lex (Space *home, const IntVarArgs &x, IntRelType r, const IntVarArgs &y, IntConLevel icl=ICL_DEF, PropKind pk=PK_DEF) |
| Post propagator for lexical order between x and y. |
Function Documentation
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 872 of file minimodel.hh.
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 881 of file minimodel.hh.
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 893 of file minimodel.hh.
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 902 of file minimodel.hh.
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 911 of file minimodel.hh.
| void Gecode::atmost | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 923 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 933 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 942 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 954 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 963 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 972 of file minimodel.hh.
| void Gecode::atleast | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 984 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 994 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 1003 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| int | m, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 1015 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| int | n, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 1024 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntVar | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Definition at line 1033 of file minimodel.hh.
| void Gecode::exactly | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| const IntArgs & | y, | |||
| IntVar | z, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for .
Supports domain consistent propagation only.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 1045 of file minimodel.hh.
| void Gecode::lex | ( | Space * | home, | |
| const IntVarArgs & | x, | |||
| IntRelType | r, | |||
| const IntVarArgs & | y, | |||
| IntConLevel | icl = ICL_DEF , |
|||
| PropKind | pk = PK_DEF | |||
| ) | [inline] |
Post propagator for lexical order between x and y.
Throws an exception of type Int::ArgumentSizeMismatch, if x and y are of different size.
Definition at line 1055 of file minimodel.hh.


Source files weaved in this document
Welcome to this tutorial, whose objective is to guide you through the features of the Catala language and teach you how to annotate a legislative text using the language. This document is addressed primarily to developers or people that have a programming background, though tech-savvy lawyers will probably figure things out.
To begin writing a Catala program, you must start from the text of the
legislative source that will justify the code that you will write. Concretely,
that means copy-pasting the text of the law into a Catala source file and
formatting it according so that Catala can understand it. Catala source files
have the ".catala_en" extension. If you were to write a Catala program for a
French law, you would use the ".catala_fr" extension.
You can write any kind of plain text in Catala, and it will be printed as is
in PDF or HTML output. You can split your text into short lines, those
will appear as a single paragraph in the output. If you want to create a
new paragrah, you have to leave a blank line in the source.
Catala allows you to declare section or subsection headers as it is done
here, with the "at" symbol repeated twice. You can define heading of lower
importance by adding increasing numbers of "+" after the title of the heading.
The fundamental division unit is the article, introduced by a single "at".
Let's analyse a fictional example that defines an income tax.
The income tax for an individual is defined as a fixed percentage of the individual's income over a year.
To do that, we will intertwine short snippets of code between the sentences of the legislative text. Each snippet of code should be as short as possible and as close as possible to the actual sentence that justifies the code. This style is called literate programming, a programming paradigm invented by the famous computer scientist Donald Knuth in the 70s.
The content of article 1 uses a lot of implicit context: there exists an
individual with an income, as well as an income tax that the individual has
to pay each year. Even if this implicit context is not verbatim in the law,
we have to explicit it for programming purposes. Concretely, we need a
"metadata" section that defines the shape and types of the data used
inside the law.
Let's start our metadata section by declaring the type information for the
individual:
This structure contains two data fields, "income" and "number_of_children". Structures are
useful to group together data that goes together. Usually, you
get one structure per concrete object on which the law applies (like the
individual). It is up to you to decide how to group the data together,
but you should aim to optimize code readability.
Sometimes, the law gives an enumeration of different situations. These
enumerations are modeled in Catala using an enumeration type, like:
In computer science terms, such an enumeration is called a "sum type" or simply
an enum. The combination of structures and enumerations allow the Catala
programmer to declare all possible shapes of data, as they are equivalent to
the powerful notion of "algebraic datatypes".
We've defined and typed the data that the program will manipulate. Now we have
to define the logical context in which these data will evolve. This is done in
Catala using "scopes". Scopes are close to functions in terms of traditional
programming. Scopes also have to be declared in metadata, so here we go:
We now have everything to annotate the contents of article 1, which is copied over below.
The income tax for an individual is defined as a fixed percentage of the individual's income over a year.
In the code, we are defining inside our scope the amount of the income tax
according to the formula described in the article. When defining formulae,
you have access to all the usual arithmetic operators: addition "+",
substraction "-", multiplication "*" and division (slash).
However, in the Catala code, you can see that we use "*$" to multiply the
individual income by the fixed percentage. The $ suffix indicates that we
are performing a multiplication on an amount of money. Indeed, in Catala,
you have to keep track of what you are dealing with: is it money ? Is it
an integer? Using just "+" or "*" can be ambiguous in terms of rounding,
since money is usually rounded at the cent. So to disambiguate, we suffix these
operations with something that indicates the type of what we manipulate.
The suffixes are "$" for money "." for decimals, "at" (like in email adresses)
for dates and the hat symbol for durations. If you forget the suffix, the Catala type
checker will display an error message that will help you put it where it
belongs.
But inside article 1, one question remains unknown: what is the value of
of the fixed percentage? Often, precise values are defined elsewhere in the
legislative source. Here, let's suppose we have:
The fixed percentage mentionned at article 1 is equal to 20 %.
You can see here that Catala allows definitions to be scattered throughout the annotation of the legislative text, so that each definition is as close as possible to its location in the text.
So far so good, but now the legislative text introduces some trickiness. Let us suppose the third article says:
If the individual is in charge of 2 or more children, then the fixed percentage mentionned at article 1 is equal to 15 %.
This article actually gives another definition for the fixed percentage, which was already defined in article 2. However, article 3 defines the percentage conditionnally to the individual having more than 2 children. Catala allows you precisely to redefine a variable under a condition:
When the Catala program will execute, the right definition will be dynamically chosen by looking at which condition is true. A correctly drafted legislative source should always ensure that at most one condition is true at all times. However, if it is not the case, Catala will let you define a precedence on the conditions, which has to be justified by the law.
Catala lets you define functions anywhere in your data. Here's what it looks like in the metadata definition when we want to define a two-brackets tax computation:
And in the code:
The tax amount for a two-brackets computation is equal to the amount of income in each bracket multiplied by the rate of each bracket.
Now that we've defined our helper scope for computing a two-brackets tax, we want to use it in our main tax computation scope.
For individuals whose income is greater than $100,000, the income tax of article 1 is 40% of the income above $100,000. Below $100,000, the income tax is 20% of the income.
Individuals earning less than $10,000 are exempted of the income tax mentionned at article 1.
That's it! We've defined a two-brackets tax computation simply by annotating
legislative article by snippets of Catala code. However, attentive readers
may have caught something weird in articles 5 and 6. What happens when the
income of the individual is between $10,000 and $100,000 ?
The law leaves it unspecified ; our dummy articles are clearly badly drafted.
But Catala can help you find this sort of errors via simple testing or
even formal verification. Let's start with the testing.
Testing Catala programs can be done directly into Catala. Indeed, writing test cases for each Catala scope that you define is a good practice called "unit testing" in the software engineering community. A test case is defined as another scope:
This test should pass. Let us now consider a failing test case:
This test case should compute a $0 income tax because of Article 6. But instead, execution will yield an error saying that there is a conflict between rules.
Indeed, the definition of the income tax in article 6 conflicts with the definition of income tax in article 5. But actually, article 6 is just an exception of article 5. In the law, it is implicit that if article 6 is applicable, then it takes precedence over article 5.
This implicit precedence has to be explicitely declared in Catala. Here is a fixed version of the NewIncomeTaxComputation scope:
And the test that should now work:
This tutorial presents the basic concepts and syntax of the Catala language
features. It is then up to you use them to annotate legislative texts
with their algorithmic translation.
There is no single way to write Catala programs, as the program style should be
adapted to the legislation it annotates. However, Catala is a functional
language at heart, so following standard functional programming design patterns
should help achieve concise and readable code.


{% extends "partials/_layout.html" %} {% load static %} {% block title %} Sign Up Closed {% endblock title %} {% block body %} Sign Up Closed We are sorry, but the sign up is currently closed. Please contact us if you have any problems.
We are sorry, but the sign up is currently closed.


{% extends "help/base.html" %} {% load i18n %} {% block help_con %}
{% trans "Usually Syncwerk client automatically detects changes on local folder and upload the changes to server. However, if the local folder is in a Windows network share drive, Syncwerk client cannot detect changes reliably. In this case, you can ask Syncwerk client to periodically checks for changes in the local folder. You can set the interval of this periodic sync. The interval is set in the unit of seconds." %}
{% endblock %}


Pig Cookbook
- Overview
-
Performance Enhancers
- Use Optimization
- Use Types
- Project Early and Often
- Filter Early and Often
- Reduce Your Operator Pipeline
- Make Your UDFs Algebraic
- Implement the Aggregator Interface
- Drop Nulls Before a Join
- Take Advantage of Join Optimizations
- Use the PARALLEL Clause
- Use the LIMIT Operator
- Prefer DISTINCT over GROUP BY - GENERATE
Overview
This document provides hints and tips for pig users.
Performance Enhancers
Use Optimization
Pig supports various optimization rules which are turned on by default. Become familiar with these rules.
Use Types
If types are not specified in the load statement, Pig assumes the type of =double= for numeric computations. A lot of the time, your data would be much smaller, maybe, integer or long. Specifying the real type will help with speed of arithmetic computation. It has an additional advantage of early error detection.
--Query 1 A = load 'myfile' as (t, u, v); B = foreach A generate t + u; --Query 2 A = load 'myfile' as (t: int, u: int, v); B = foreach A generate t + u;
The second query will run more efficiently than the first. In some of our queries with see 2x speedup.
Project Early and Often
Pig does not (yet) determine when a field is no longer needed and drop the field from the row. For example, say you have a query like:
A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); C = join A by t, B by x; D = group C by u; E = foreach D generate group, COUNT($1);
There is no need for v, y, or z to participate in this query. And there is no need to carry both t and x past the join, just one will suffice. Changing the query above to the query below will greatly reduce the amount of data being carried through the map and reduce phases by pig.
A = load 'myfile' as (t, u, v); A1 = foreach A generate t, u; B = load 'myotherfile' as (x, y, z); B1 = foreach B generate x; C = join A1 by t, B1 by x; C1 = foreach C generate t, u; D = group C1 by u; E = foreach D generate group, COUNT($1);
Depending on your data, this can produce significant time savings. In queries similar to the example shown here we have seen total time drop by 50%.
Filter Early and Often
As with early projection, in most cases it is beneficial to apply filters as early as possible to reduce the amount of data flowing through the pipeline.
-- Query 1 A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); C = filter A by t == 1; D = join C by t, B by x; E = group D by u; F = foreach E generate group, COUNT($1); -- Query 2 A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); C = join A by t, B by x; D = group C by u; E = foreach D generate group, COUNT($1); F = filter E by C.t == 1;
The first query is clearly more efficient than the second one because it reduces the amount of data going into the join.
One case where pushing filters up might not be a good idea is if the cost of applying filter is very high and only a small amount of data is filtered out.
Reduce Your Operator Pipeline
For clarity of your script, you might choose to split your projects into several steps for instance:
A = load 'data' as (in: map[]); -- get key out of the map B = foreach A generate in#k1 as k1, in#k2 as k2; -- concatenate the keys C = foreach B generate CONCAT(k1, k2); .......
While the example above is easier to read, you might want to consider combining the two foreach statements to improve your query performance:
A = load 'data' as (in: map[]); -- concatenate the keys from the map B = foreach A generate CONCAT(in#k1, in#k2); ....
The same goes for filters.
Make Your UDFs Algebraic
Queries that can take advantage of the combiner generally ran much faster (sometimes several times faster) than the versions that don't. The latest code significantly improves combiner usage; however, you need to make sure you do your part. If you have a UDF that works on grouped data and is, by nature, algebraic (meaning their computation can be decomposed into multiple steps) make sure you implement it as such. For details on how to write algebraic UDFs, see the Pig UDF Manual and Aggregate Functions.
A = load 'data' as (x, y, z) B = group A by x; C = foreach B generate group, MyUDF(A); ....
If MyUDF is algebraic, the query will use combiner and run much faster. You can run explain command on your query to make sure that combiner is used.
Implement the Aggregator Interface
If your UDF can't be made Algebraic but is able to deal with getting input in chunks rather than all at once, consider implementing the Aggregator interface to reduce the amount of memory used by your script. If your function is Algebraic and can be used on conjunction with Accumulator functions, you will need to implement the Accumulator interface as well as the Algebraic interface. For more information, see the Pig UDF Manual and Accumulator Interface.
Drop Nulls Before a Join
With the introduction of nulls, join and cogroup semantics were altered to work with nulls. The semantic for cogrouping with nulls is that nulls from a given input are grouped together, but nulls across inputs are not grouped together. This preserves the semantics of grouping (nulls are collected together from a single input to be passed to aggregate functions like COUNT) and the semantics of join (nulls are not joined across inputs). Since flattening an empty bag results in an empty row, in a standard join the rows with a null key will always be dropped. The join:
A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); C = join A by t, B by x;
is rewritten by pig to
A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); C1 = cogroup A by t INNER, B by x INNER; C = foreach C1 generate flatten(A), flatten(B);
Since the nulls from A and B won't be collected together, when the nulls are flattened we're guaranteed to have an empty bag, which will result in no output. So the null keys will be dropped. But they will not be dropped until the last possible moment. If the query is rewritten to
A = load 'myfile' as (t, u, v); B = load 'myotherfile' as (x, y, z); A1 = filter A by t is not null; B1 = filter B by x is not null; C = join A1 by t, B1 by x;
then the nulls will be dropped before the join. Since all null keys go to a single reducer, if your key is null even a small percentage of the time the gain can be significant. In one test where the key was null 7% of the time and the data was spread across 200 reducers, we saw a about a 10x speed up in the query by adding the early filters.
Take Advantage of Join Optimizations
Regular Join Optimizations
Optimization for regular joins ensures that the last table in the join is not brought into memory but streamed through instead. Optimization reduces the amount of memory used which means you can avoid spilling the data and also should be able to scale your query to larger data volumes.
To take advantage of this optimization, make sure that the table with the largest number of tuples per key is the last table in your query. In some of our tests we saw 10x performance improvement as the result of this optimization.
small = load 'small_file' as (t, u, v); large = load 'large_file' as (x, y, z); C = join small by t, large by x;
Specialized Join Optimizations
Optimization can also be achieved using fragment replicate joins, skewed joins, and merge joins. For more information see Specialized Joins.
Use the PARALLEL Clause
Use the PARALLEL clause to increase the parallelism of a job:
- PARALLEL sets the number of reduce tasks for the MapReduce jobs generated by Pig. The default value is 1 (one reduce task).
- PARALLEL only affects the number of reduce tasks. Map parallelism is determined by the input file, one map for each HDFS block.
- If you don’t specify PARALLEL, you still get the same map parallelism but only one reduce task.
As noted, the default value for PARALLEL is 1 (one reduce task). However, the number of reducers you need for a particular construct in Pig that forms a MapReduce boundary depends entirely on (1) your data and the number of intermediate keys you are generating in your mappers and (2) the partitioner and distribution of map (combiner) output keys. In the best cases we have seen that a reducer processing about 500 MB of data behaves efficiently.
You can include the PARALLEL clause with any operator that starts a reduce phase (see the example below). This includes COGROUP, CROSS, DISTINCT, GROUP, JOIN (inner), JOIN (outer), and ORDER.
You can also set the value of PARALLEL for all Pig scripts using the set default parallel command.
In this example PARALLEL is used with the GROUP operator.
A = LOAD 'myfile' AS (t, u, v); B = GROUP A BY t PARALLEL 18; .....
In this example all the MapReduce jobs that get launched use 20 reducers.
SET DEFAULT_PARALLEL 20; A = LOAD ‘myfile.txt’ USING PigStorage() AS (t, u, v); B = GROUP A BY t; C = FOREACH B GENERATE group, COUNT(A.t) as mycount; D = ORDER C BY mycount; STORE D INTO ‘mysortedcount’ USING PigStorage();
Use the LIMIT Operator
Often you are not interested in the entire output but rather a sample or top results. In such cases, using LIMIT can yield a much better performance as we push the limit as high as possible to minimize the amount of data travelling through the pipeline.
Sample:
A = load 'myfile' as (t, u, v); B = limit A 500;
Top results:
A = load 'myfile' as (t, u, v); B = order A by t; C = limit B 500;
Prefer DISTINCT over GROUP BY - GENERATE
When it comes to extracting the unique values from a column in a relation, one of two approaches can be used:
Example Using GROUP BY - GENERATE
A = load 'myfile' as (t, u, v); B = foreach A generate u; C = group B by u; D = foreach C generate group as uniquekey; dump D;
Example Using DISTINCT
A = load 'myfile' as (t, u, v); B = foreach A generate u; C = distinct B; dump C;
In pig 0.1.x, DISTINCT is just GROUP BY/PROJECT under the hood. In pig 0.2.0 it is not, and it is much faster and more efficient (depending on your key cardinality, up to 20x faster in pig team's tests). Therefore, the use of DISTINCT is recommended over GROUP BY - GENERATE.


NHL notebook: Blues' Blais (wrist surgery) out 10 weeks
St. Louis Blues forward Sammy Blais will undergo surgery on his right wrist and be sidelined at least 10 weeks, the team announced Thursday.
Blais was injured during the Blues’ 3-1 victory over the Tampa Bay Lightning on Tuesday.
The 23-year-old has collected five goals, three assists and 10 penalty minutes in 20 games this season.
Blais, who scored a goal and set up two others in the playoffs in the spring, has recorded 15 points (eight goals, seven assists) in 63 career games since being selected by St. Louis in the sixth round of the 2014 NHL Draft.
—Tampa Bay Lightning star forward Nikita Kucherov sat out the road game against the Chicago Blackhawks, coach Jon Cooper announced.
Kucherov, who is the reigning Hart Trophy recipient, sustained an upper-body injury following a hit from St. Louis forward Brayden Schenn in the second period of Tuesday’s 3-1 setback to the Blues.
Cooper said he wasn’t certain if Kucherov would be available to play in Tampa Bay’s game against the visiting Anaheim Ducks on Saturday. Kucherov, 26, has recorded six goals and 12 assists in 18 games this season for the Lightning.
—Veteran NHL player and coach Paul MacLean was added the Columbus Blue Jackets’ coaching staff as an assistant with emphasis on special teams.
MacLean was expected to be on the bench for the Blue Jackets’ home game against the Detroit Red Wings on Thursday, according the Columbus Dispatch.
MacLean, 61, was head coach for the Ottawa Senators from 2011-14, compiling a 114-90-35 record with the club and two playoff appearances. He was fired 27 games into the 2014 season, with his dismissal coming just 18 months after winning NHL Coach of the Year honors.
—The Pittsburgh Penguins recalled defenseman Zach Trotman from Wilkes-Barre/Scranton of the American Hockey League in advance of their road game against the New York Islanders.
Trotman, 29, had two goals and three assists over eight games in the AHL.
Trotman has three career NHL goals and 10 assists over 83 games with the Boston Bruins and Penguins. Trotman appeared in 13 games with the Penguins last season, recording one assist.
—Field Level Media


{% extends 'logged_in_base.html' %} {% load static %} {# Load the tag library #} {% load bootstrap3 %} {% block css_imports %} {% endblock %} {% block main %}
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ArcticConnect is a network-enabled platform for realizing geospatial referencing of information about the arctic system derived from research, education, and private sector activities in the arctic and subarctic. This project is maintained by the Arctic Institute of North America, the GeoSensorWeb Lab at the University of Calgary, Cybera, Inc, and CANARIE.
Our public services include Arctic Web Map and Arctic Sensor Web.
© Arctic Connect 2014–2021


Query:
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Shared Queries/Current Sprint/Work in Progress
hared Queries/Current Sprint/Test Cases
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INSPECTOR LAVARDIN (Inspecteur Lavardin) (director: Claude Chabrol; screenwriter: Dominique Roulet; cinematographer: Jean Rabier; editor: Monique Fardoulis/Angela Braga-Mermet; cast: Jean Poiret (Inspecteur Jean Lavardin), Jean-Claude Brialy (Claude Alvarez), Bernadette Lafont (Hélène Mons), Jean-Luc Bideau (Max Charnet), Jacques Dacqmine (Raoul Mons), Hermine Clair (Véronique Manguin), Pierre-François Dumeniaud (Marcel Vigouroux), Florent Gibassier (Francis), 1986-France)
Reviewed by Dennis Schwartz
A thoroughly enjoyable Claude Chabrol detective story, covering ground the director is very familiar with from his previous successes with this kind of a mystery story.
The director is in a playful mood and builds a crime scene around kinky characters, hypocrites, lowlifes, and druggies, as he parodies bourgeois life. This is Poiret's second venture into police investigation, he also did it in Chabrol's 1984 Cop au Vin. The film starts with a surprise and ends with a debatable moral ending to the murder case, which is geared to be pleasing to the audience's sense of what is right rather than one that follows the law or the integrity of the inspector's profession. The inspector will deem it necessary for himself to become personally involved in the case and to act as judge and jury as well as cop.
The inspector is given a local policeman to escort him around and assist when needed, Vigouroux (Dumeniaud), who is affectionately called Watson by Poiret. The inspector is the focal point of the film and the way he operates is a rough imitation of Sherlock Holmes. His reactions to what occurs is how we are led to believe we should see the film. Poiret is superb, his dry wit and the persistent way he carries out the investigation, sets the film's laconic tone, setting up the bizarre turn of events in a magnificently comic fashion.
His first surprise is when he comes to the wealthy home of the widow, Hélène Mons (Bernadette Lafont), and discovers that she is an old flame of his from some twenty years ago, when he was a hoodlum and she refused to marry him. He first views her when she is behind the glass partition of the house, which gives his recognition of her a more descriptive but also a more aloof impression. This meeting gives him a chance to look through the mirror of his life again and see what happened with a clarity that mirrors a murder investigation. He uses the excuse that he is here on police business to ask the questions and not answer anything about his private life, while he diligently probes the life of the love he still cannot forget.
Also living at the house, are her brother Claude (Brialy) and 13-year-old daughter Véronique (Clair). She tells the inspector that this is the second husband of hers that got killed; the first, Pierre, she loved dearly, and that he died in a boating accident. Her current husband Raoul Mons (Dacqmine), she detests. She married him because of debts that Pierre incurred and that Raoul paid off when she made an arrangement with the priggish and Bible quoting zealous Catholic, one in which they sleep in separate bedrooms, but their outward appearances give others the impression that they are a perfect couple.  It turns out that he means gay, in the literal vernacular sense, that he now likes only men. His hobby is creating painted sculptures of eyes. While Véronique, the same name Lavardin would have chosen for a daughter if he had one with Hélène, is a spirited young girl who is very close with Uncle Claude. Uncle covers for her, while she goes out night clubbing, hanging out with druggies, and having a secret boyfriend. Her regal mother is very protective of her and blindly trusts Claude to look out for her.
The initial suspicion for who did the murder falls on a theater group putting on a blasphemous play entitled "Our Father Which Farts in Heaven."Their play was banned when a group of concerned citizens asked Raoul to go to his friends on the town council. But the inspector picks up a hotter lead for the murder and goes on the trail of Max Charnet (Bideau), who owns a nightclub where drug pushers carry on business and underaged teens are allowed in and are served alcohol drinks because he has paid off the police and the town council to look the other way. Max's favorite expression is, "That life is absurd."The inspector also discovers that Raoul is a hypocrite, leading a double-life, as he regularly attends Max's club and is involved in a drug ring and in procuring girls. When the inspector finds that Max rented Raoul a secret apartment, he begins to focus primarily on Raoul's activities in the apartment.
Another suspicious guy in the hunt, is a weird disheveled young man always hanging around Claude, Francis (Gibassier). He, it will turn out later, is not a "faggot" but a blackmailer, which adds to the many twists in the story, as Chabrol loves to surprise and tell about the secret lives his suspects are living.
Chabrol's use of eyes as a motif could be construed to mean how narrowly each character sees himself, as everyone who is a suspect seems self-absorbed.
This is a purely entertaining film, with no great insights into life to be discovered but, with some great looks at how absurd life really is. The joy in the film is expressed best through the following actors: the dreamy and soft performance of Lafont, the spry and eccentric performance from Brialy, who was in a Chabrol film some thirty years ago, and from Poiret's strongly understated performance, holding back his feelings by letting his action do the talking. This is Chabrol at his most playful, which offers some surprises, shocks, and amusement.
REVIEWED ON 5/22/99 GRADE: B+
http://www.sover.net/~ozus
<EMAIL_ADDRESS>Dennis Schwartz: "Ozus' World Movie Reviews"
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making madeincluj
madeincluj is built by:
danburzo adriana-saroz cronco..with a bit of help from our friends.
Watch this space: we'll write about what we've learned in the process and oh boy do we have things to share.
xoxo,
#mic
madeincluj is built by:
danburzo adriana-saroz cronco..with a bit of help from our friends.
Watch this space: we'll write about what we've learned in the process and oh boy do we have things to share.
xoxo,
#mic


get pods
and docker ps
don’t show it.Not running Linux? Consider running Linux in a local virtual machine with Vagrant, or on a cloud provider like Google Compute Engine
At least Docker
1.3+. Ensure the Docker daemon is running and can be contacted (try docker
ps
). Some of the Kubernetes components need to run as root, which normally
works fine with docker.
You need an etcd in your path, please make sure it is installed and in your $PATH
.
You need go at least 1.3+ in your path, please make sure it is installed and in your $PATH
.
In a separate tab of your terminal, run the following (since one needs sudo access to start/stop Kubernetes daemons, it is easier to run the entire script as root):
cd kubernetes
hack/local-up-cluster.sh
This will build and start a lightweight local cluster, consisting of a master and a single node. Type Control-C to shut it down.
You can use the cluster/kubectl.sh script to interact with the local cluster. hack/local-up-cluster.sh will print the commands to run to point kubectl at the local cluster.
Your cluster is running, and you want to start running containers!
You can now use any of the cluster/kubectl.sh commands to interact with your local setup.
cluster/kubectl.sh get pods
cluster/kubectl.sh get services
cluster/kubectl.sh get replicationcontrollers
cluster/kubectl.sh run my-nginx --image=nginx --replicas=2 --port=80
## begin wait for provision to complete, you can monitor the docker pull by opening a new terminal
sudo docker images
## you should see it pulling the nginx image, once the above command returns it
sudo docker ps
## you should see your container running!
exit
## end wait
## introspect Kubernetes!
cluster/kubectl.sh get pods
cluster/kubectl.sh get services
cluster/kubectl.sh get replicationcontrollers
Note the difference between a container
and a pod. Since you only asked for the former, Kubernetes will create a wrapper pod for you.
However you cannot view the nginx start page on localhost. To verify that nginx is running you need to run curl
within the docker container (try docker exec
).
You can control the specifications of a pod via a user defined manifest, and reach nginx through your browser on the port specified therein:
cluster/kubectl.sh create -f docs/user-guide/pod.yaml
Congratulations!
Some firewall software that uses iptables may not interact well with
kubernetes. If you have trouble around networking, try disabling any
firewall or other iptables-using systems, first. Also, you can check
if SELinux is blocking anything by running a command such as journalctl --since yesterday | grep avc
.
By default the IP range for service cluster IPs is 10.0.. - depending on your docker installation, this may conflict with IPs for containers. If you find containers running with IPs in this range, edit hack/local-cluster-up.sh and change the service-cluster-ip-range flag to something else.
You are running a single node setup. This has the limitation of only supporting a single replica of a given pod. If you are interested in running with larger replica sizes, we encourage you to try the local vagrant setup or one of the cloud providers.
cd kubernetes
hack/build-go.sh
hack/local-up-cluster.sh
get pods
and docker ps
don’t show it.One or more of the KUbernetes daemons might’ve crashed. Tail the logs of each in /tmp.
The local-up-cluster.sh script doesn’t start a DNS service. Similar situation can be found here. You can start a manually. Related documents can be found here


smoot(3f) - [M_calcomp:scientific] draw a polyline using modified spline-fitting technique (LICENSE:PD)
Synopsis
Description
Options
Description
Comments
Example
License
subroutine smoot(xpage,ypage,ipen)
SMOOT is a FORTRAN subroutine which draws a smooth curve through a set of data points. It accomplishes this by using a modified spline-fitting technique. The subroutine receives a single coordinate pair on each call and accumulates the points until it has received a sufficient number to compute a pair of cubic parametric equations for a smooth curve. This accumulation method requires the user to specify an initial and a terminal call to the subroutine.
The SMOOT subroutine operates in either of two modes: Smooth Mode and Plot Mode.
XPAGE,YPAGE are the coordinates, in inches, of a single point through which the pen moves. IPEN determines the mode and action of the SMOOT subroutine.
The first call to SMOOT must use an IPEN value of 0 or -1 to put SMOOT in the Smooth Mode.
if IPEN = 0, XPAGE,YPAGE define the initial point (P(1)) on the curve. The smoothing function ends at the last point (P(n)). An open curve is produced.SMOOTH MODE:if IPEN = -1, XPAGE,YPAGE are used to define the initial point (P(1)) on the curve. The smoothing function continues from the last point (P(n)) back to the initial point (P(1)). A closed curve is produced.
When SMOOT is in the Smooth Mode, IPEN performs the following functions:PLOT MODE:IPEN = -2 XPAGE,YPAGE are used to define points P(2), P(3),..., P(N-1), and a smoothed curve is drawn through the points on the curve.
IPEN = -3 XPAGE,YPAGE are used to define points P(2), P(3), ...,P(N-1), and the pen, in the up position, is moved through these points. The smoothing function is maintained.
IPEN = 2 or 3 The call is treated as a normal CALL PLOT (XPAGE,YPAGE,IPEN), and the point is not considered a point on the curve. The point of departure from the curve is the next-to-last point received by SMOOT, not the last point.
When the next call to SMOOT with IPEN = -2 or -3 is received, the pen is repositioned to the point where it left the smooth curve. The smooth curve is then continued as though the calls with IPEN = 2 or 3 had not occurred.
IPEN <=(-24) is used for the terminal call while SMOOT is in the Smooth Mode. XPAGE,YPAGE represent P(N). The curve is finished, and the subroutine returns to the Plot Mode.
SMOOT is in the Plot Mode after receiving a terminal call.
IF IPEN = +-2 or +-3, the call is treated as a normal CALL PLOT (XPAGE,YPAGE,IPEN).
When SMOOT is called while it is in the Smooth Mode, the pen is not moved until three points on an open curve or four points on a closed curve have been received. For subsequent calls to SMOOT, the actual pen position is the next-to-last point received.
Calls to other plotting subroutines may be intermixed with calls to SMOOT. Point-of-departure restrictions are the same as noted in the Smooth Mode description above.
The first call to SMOOT must be with IPEN = 0 or -1 .
Sample program
program demo_smoot use M_calcomp implicit none ! based on concepts of CALIFORNIA COMPUTER PRODUCTS, 1968 real :: xar(10)=[0.75,1.75,2.25,2.75,3.25,4.25,4.75,5.75,0.0,1.0] real :: yar(10)=[3.25,2.00,5.25,6.50,6.75,6.25,3.25,4.25,0.0,1.0] character(len=50) :: ibcd integer :: inteq call plots(0.0,10.0,0.0,10.0) !     FLINE IS USED call plot(0.75,3.25,3) call fline(xar, yar, -8,1,1,1) call nframe() end program demo_smoot
Public Domain
| Nemo Release 3.1 | smoot (3) | July 22, 2023 |


Blog (#til)
2023
📝 PostgreSQL: Mark a column non-nullable after creating it
TIL: How to add a not null constraint to an existing column in a PostgreSQL table
📝 PostgreSQL: Make a column unique after creating it
TIL: How to add unique constraint to an existing column in a PostgreSQL table
📝 Avoid .DS_Store files on removable media
TIL: Settings change on Mac to avoid having .DS_Store files being created on USB and Network shares
📝 Recursively remove .DS_Store files
TIL: Shell command to recursively remove .DS_Store files
📝 Custom 404 in Express
TIL: How to return custom response for a 404 in Express on NodeJS
📝 Using emoji as a favicon
TIL: How to write a simple SVG which renders an emoji as a favicon
📝 Save dependency list of your python project to a file
TIL: How to do for python what we get with `dependencies` in npm `package.json`
📝 Map an array of ids in postgres to matching data from another table
TIL: How to map an array in postgres to other data
📝 Counting days between 2 dates in PostgreSQL
TIL: You can use the extract function to find difference in days between 2 dates
📝 Find the first entry in each group
TIL: How to get the first entry from each group given a sort order
📝 Navigate to a path in Mac Finder
TIL: How to navigate to a given system path without clicking through folders
📝 Most used commands
TIL: How to view your most used terminal commands on a Mac
📝 wget with custom filename
TIL: How to download a file with wget to a custom filename
📝 Taking a heap-dump from a running JVM process
TIL: How to take heap-dump from a running JVM process
2022
📝 Figma styles not present in the API response
TIL: Why Figma returns empty styles in API and how to fix it
📝 Authentication with wget
TIL: How to provide username and password for simple authentication when downloading files using wget
📝 How to make non-capturing groups in RegEx
TIL: What are non-capturing groups and how we can use them
📝 India's national aquatic animal
TIL: India has a species of dolphin as its national aquatic animal.
2021
📝 List files updated in a git commit
TIL: How to see a list of files updated in a git commit
📝 Centering elements with CSS
TIL: How to center (horizontally and vertically) elements with CSS.
📝 Resizing images from command-line
TIL: Resizing images from command-line while centering them and adding a transparent background.
📝 Comparing two BigDecimal instances
TIL: Turns out that 7.5.toBigDecimal() and 7.50.toBigDecimal() are not equal
📝 Castle Under Threat
TIL: You cannot castle your king in chess if king's path is under threat
📝 Ugh fields
TIL: What are "ugh fields" and why everyone should atleast know about them.
📝 Opening current terminal command in $EDITOR
TIL: Ctrl+X followed by Ctrl+E opens the command you are currently editing in your $EDITOR program
📝 Google gives refresh token only once
TIL: Google doesn't return refresh token on subsequent authentication after the first one.
📝 JavaScript can "throw" the table
TIL: JavaScript can throw anything
📝 CSS support for browser dark-mode preference
TIL: How to support dark-mode preference of browser via CSS


ID: 1
Office Number: 1
ID: 2
Office Number: 2
ID: 3
GitHub: princesscbh
ID: 4
School: Lincoln High School
ID: 5
ID: 6


| AIC-method | Log likelihoods and model selection for mle2 objects |
| AIC-methods | Log likelihoods and model selection for mle2 objects |
| AICc | Log likelihoods and model selection for mle2 objects |
| AICc-method | Log likelihoods and model selection for mle2 objects |
| AICc-methods | Log likelihoods and model selection for mle2 objects |
| AICctab | Compute table of information criteria and auxiliary info |
| AICtab | Compute table of information criteria and auxiliary info |
| anova-method | Log likelihoods and model selection for mle2 objects |
| as.data.frame.profile.mle2 | convert profile to data frame |
| BIC-methods | Log likelihoods and model selection for mle2 objects |
| BICtab | Compute table of information criteria and auxiliary info |
| calc_mle2_function | Maximum Likelihood Estimation |
| call.to.char | Convert calls to character |
| coef-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| coef-method | Class "summary.mle2", summary of "mle2" objects |
| coerce-method | convert profile to data frame |
| coerce-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| confint-method | Methods for likelihood profiles |
| confint.mle2 | Methods for likelihood profiles |
| deviance-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| dnorm_n | Normal distribution with profiled-out standard deviation |
| formula-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| get.mnames | extract model names |
| gfun | Predicted values from an mle2 fit |
| ICtab | Compute table of information criteria and auxiliary info |
| logLik-method | Log likelihoods and model selection for mle2 objects |
| logLik-methods | Log likelihoods and model selection for mle2 objects |
| mle | Maximum Likelihood Estimation |
| mle2 | Maximum Likelihood Estimation |
| mle2-class | Class "mle2". Result of Maximum Likelihood Estimation. |
| mle2.options | Options for maximum likelihood estimation |
| namedrop | drop unneeded names from list elements |
| parnames | get and set parameter names |
| parnames<- | get and set parameter names |
| plot-method | Methods for likelihood profiles |
| plot.profile.mle2 | Methods for likelihood profiles |
| pop_pred_samp | generate population prediction sample from parameters |
| predict-method | Predicted values from an mle2 fit |
| predict-methods | Predicted values from an mle2 fit |
| print.ICtab | Compute table of information criteria and auxiliary info |
| proffun | Likelihood profiles |
| profile-method | Likelihood profiles |
| profile-methods | Likelihood profiles |
| profile.mle2 | Likelihood profiles |
| profile.mle2-class | Methods for likelihood profiles |
| qAIC | Log likelihoods and model selection for mle2 objects |
| qAIC-method | Log likelihoods and model selection for mle2 objects |
| qAIC-methods | Log likelihoods and model selection for mle2 objects |
| qAICc | Log likelihoods and model selection for mle2 objects |
| qAICc-method | Log likelihoods and model selection for mle2 objects |
| qAICc-methods | Log likelihoods and model selection for mle2 objects |
| relist2 | reconstruct the structure of a list |
| residuals-method | Predicted values from an mle2 fit |
| sbeta | Abstract definitions of distributions |
| sbetabinom | Abstract definitions of distributions |
| sbinom | Abstract definitions of distributions |
| show-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| show-method | Methods for likelihood profiles |
| show-method | Class "summary.mle2", summary of "mle2" objects |
| simulate-method | Predicted values from an mle2 fit |
| slice | Calculate likelihood "slices" |
| slice-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| slice.mle2-class | likelihood-surface slices |
| slice1D | Calculate likelihood "slices" |
| slice2D | Calculate likelihood "slices" |
| sliceOld | Calculate likelihood "slices" |
| slicetrans | Calculate likelihood "slices" |
| slnorm | Abstract definitions of distributions |
| snbinom | Abstract definitions of distributions |
| snorm | Abstract definitions of distributions |
| spois | Abstract definitions of distributions |
| stdEr | Class "mle2". Result of Maximum Likelihood Estimation. |
| stdEr-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| strwrapx | Wrap strings at white space and + symbols |
| summary-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| summary.mle2-class | Class "summary.mle2", summary of "mle2" objects |
| update-method | Class "mle2". Result of Maximum Likelihood Estimation. |
| vcov-method | Class "mle2". Result of Maximum Likelihood Estimation. |


News story
Perceptions of A levels and GCSEs in England: wave 14
The results of Ofqual's annual survey on perceptions of A levels, GCSEs and other qualifications. Conducted 19 January to 27 February 2016.
In general, this year’s results are very similar to previous waves.
Highlights from the survey
Perceptions of GCSEs and A levels
-
GCSEs and A levels continue to be seen as trusted qualifications by headteachers (GCSE +43 percentage points (pp); A level +82pp), young people (+61pp; +76pp) and parents (+58pp; +74pp).
-
Overall, A levels are seen as good preparation for further study by those involved in higher education (+40pp), teachers (+78pp) and employers (+80pp), but their views are more broadly balanced with respect to work. GCSEs are seen by all groups to develop a broad range of skills for students and are good preparation for further study.
-
Head teachers and teachers (+22pp) are more likely to agree than disagree that A level standards are maintained year on year. Overall, more young people than not have confidence that GCSE standards (+8pp) and A level standards (+3pp) are maintained year on year.
-
More HE providers and employers than not believe the marking of GCSEs (+12pp & +7pp respectively) and A levels (+23pp & +20pp) is accurate. More teachers than not (+7pp) believe the marking of A levels is accurate. Slightly fewer teachers agree than disagree that the marking of GCSEs is accurate (-4pp).
-
Overall, those involved in higher education (+30pp) and employers (+15pp) believe GCSEs provide a reliable measure by which applicants can be fairly compared to one another.
-
Those involved in higher education are more likely to say than not (+30pp) that A levels provide a good indicator of the overall ability of an applicant. And employers are more likely to say than not (+32pp) that A levels provide a reliable measure by which candidates’ suitability for employment can be fairly compared to one another.
-
Overall, more parents (+8pp), teachers (+15pp) and those in higher education than not (+17pp) agree that GCSEs needed reform. Employers (+19pp) and those involved in higher education (+25pp) are more likely to say than not that A levels needed reform, but head teachers (-5pp) are more likely to think the opposite.
-
The vast majority of head teachers (90%) understand that grade 9 is the best grade that students can get on the new 9 to 1 grading scale to be used for reformed GCSEs. Knowledge and understanding of the new system is much lower among the general teaching population young people, parents and employers.
 Understanding is lower among young people (32%), parents (23%) and employers (16%).
Enquiries about results and appeals
-
Awareness of the systems available for enquiring about and appealing GCSE and A level results is lower among groups outside the teaching profession, including young people and parents (32%).
-
Young people (+5pp) and teachers (+4pp) are more likely than not to say that the enquiries about results and appeals systems are fair. Head teachers are less likely to agree (-13pp).
Commenting on today’s release, Sally Collier, Chief Regulator Ofqual, said:
In general, these data show patterns similar to previous years. It is reassuring that GCSEs and A levels continue to be trusted qualifications, and that employers and those in higher education believe students’ results are reliable measures of ability. These qualifications are, however, going through a period of reform and it is apparent that we need to do more to build awareness and understanding of some of the changes today in order to maintain those perceptions into the future.
For the full Official Statistics,
please click here
.


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Some Cheese Nips Snacks Pulled From Retail Shelves Nationwide Over Plastic Concerns
The recall exclusively applies to Cheese Nips 11 oz. boxes with "best used by" dates of May 18, 2020, May 19, 2020 and May 20, 2020
A limited quantity of Cheese Nips (11 oz. boxes) are being yanked from United States grocery shelves because of the potential presence of small pieces of plastic, the FDA announced Wednesday.
The company that makes them, Mondelez Global LLC, issued the voluntary recall because small food-grade yellow plastic pieces from a dough scraper may have gotten into the production process of a limited amount of the favored snacks.
Mondelez learned of the issue when yellow plastic pieces were spotted on the manufacturing equipment.
The recall exclusively applies to Cheese Nips 11 oz. boxes with "best used by" dates of May 18, 2020, May 19, 2020 and May 20, 2020 (retail UPC 0 44000 03453 5). The snacks were sold at retail stores nationwide.
There have been no reports of injury or illness to date because of the issue.
Anyone who has purchased the product is advised to throw it away. People with questions can contact the company at 1-844-366-1171 24 hours a day for more information or view the full recall notice here.


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E-learning Profile JavaScript Library
This xAPI code library provides developers with existing JavaScript functions that meets the E-learning Profile requirements for xAPI Statements.
Code libraries are reusable JavaScript wrappers for developers to reuse when building content that meets the Navy's xAPI Profiles. Each of the xAPI code libraries below are intended to be used when building custom content.
This xAPI code library provides developers with existing JavaScript functions that meets the E-learning Profile requirements for xAPI Statements.
This xAPI code library provides developers with existing JavaScript functions that meets the Performance Support Profile requirements for xAPI Statements.
This xAPI code library provides developers with existing JavaScript functions that meets the Navy Common Reference Profile and the xAPI Video Profile requirements for xAPI Statements.
This xAPI code library provides developers with an existing code library that meets the Navy Simbulation Base Profile requirements for xAPI Statements.
This xAPI code library provides developers with an existing code library that meets the Navy Task Trainer Simbulation Profile requirements for xAPI Statements.
Content examples are fully functional demonstrations of content that meets Navy's xAPI requirements. Each of the examples below were created with the xAPI Code Libraries are intended to be downloaded and evaluated by content developers.
This xAPI content example demonstrates how an e-learning course implements xAPI to track lesson attempts, assessment interactions, and results.
This xAPI content example demonstrates how a performance support application implements xAPI to track page views, checklists, searches & other interactions.
This xAPI content example demonstrates how a HTML5 video implements xAPI to track video interactions.
This xAPI content example demonstrates how a Unity-based simulation implements the Navy Task the base Simulation Profile requirements for xAPI Statements.
This xAPI content example demonstrates how a Unity-based simulation implements the Navy Task Trainer Simulation Profile requirements for xAPI Statements.


The following expeditions belong to
{{ $ctrl.currentUser.username }}
and may not represent a comprehensive list of expeditions for this project, which can be found
under
You do not have any expeditions in {{$ctrl.currentProject.projectTitle}} yet


When does the money come and go?
The total amount borrowed from Lending Club is $200,000. Monthly payment will be made, and the entire loan including accrued interest will be paid back in 5 years after the loan was taken out. Equal payments will be made each month. 5 years is chosen as it is the longest term offered. Though it increases the amount of interest accrued, we would rather have positive net funds at the end of each year in case any accidents occur that require liquid assets. Loan interest is negotiated as 12% annually. Given this is a market interest rate, we deflate this value as to deal with real interest rates. Deflating the 12% market rate with our 1.5% inflation rate yields a loan interest rate of 10.34%. The annual interest rate is converted to a monthly interest rate of 0.824% to calculate our monthly payment schedule.
CCA depreciation is used for the vehicles, office equipment, and walk in freezers. Both the cars and equipment fall under CCA class 10 which includes “general purpose electronic data equipment and motor vehicles” at a depreciation rate of 30%. The refrigeration unit falls under CCA class 8 which includes refrigeration equipment. Equipment follows open book depreciation until sold. The refrigeration units are sold after 10 years for $2,000 each and new versions purchased. Ten years is determined for these units because we deemed it necessary to buy a third fridge as our customer base continues to increase. As most refrigeration units have a mean lifetime of 14 years, it is decided to replace the existing fridges, so they all have the same age. The cars are sold after 12 years for $5,000 each. The lifetime of the Toyota Prius C is determined from a used car site that has a depreciation schedule for each year of car. They estimate the mean lifetime to be 12 years, so we set that as our economic lifetime. After the sale of all 5 cars in year 12, 5 more cars of the same make and model are purchased (this assumes that the new cars have a 12-year life time) for the same price as we are considering all cash flows in real dollars. In Year 20, we plan to sell all our assets including the fridges, vehicles, and office equipment. The fridges will again be sold off for $2,000, like the last pair. The cars and office equipment are anticipated to sell for $60,000 and $2,500 respectively. Due to this being closed books, we investigate the book value of each class and see if any more taxes need to be paid. Since both classes are sold for more than their book value, this results in recaptured CCA. After paying these taxes, a net salvage for all our assets comes out to $50,939.
The yearly breakdowns can be seen in an excel document here. This sheet breaks down the various expenses and profits made in each year and the corresponding net profits and after-tax cash flows. As seen, World of BeerCraft never profits more than $500,000 in a single year, so it classifies as a small business. This means provincial and federal tax are only 2% and 10% respectively. After paying taxes, there are various other payments that are made. These include loan repayment (interest and principle repayment) and charitable donations. As mentioned in our About Us section, World of BeerCraft donates $3 from every monthly subscription to Alcoholics Anonymous. After these payments are made, a retained value can be seen that is used to calculate our rate of return for this project.


Finds the next and previous cells on the worksheet, as specified in the Find dialog box, and returns TRUE. (To see the Find dialog box, click Find on the Edit menu.) If a matching cell is not found, the functions return FALSE. For more information see FORMULA.FIND.
Syntax
FORMULA.FIND.NEXT( )
FORMULA.FIND.PREV( )
Related Functions
DATA.FIND Selects records in a database that match the specified criteria
FORMULA.FIND Finds text in a workbook
Return to index


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Student Course Evaluations Get An 'F'
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Tony Stewart -- CLEARED Of Criminal Charges ... Kevin Ward Was High On Weed
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Amber Rose Files for Divorce from Wiz Khalifa
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Kerry: 'Baghdad could well have fallen'
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Rare Photos From the Early Days of Blondie
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A new book celebrates the photography of Blondie co-founder and guitarist Chris Stein.
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Coke and Pepsi concede that maybe soda is bad for you
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If you can't beat them, join them.
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Isro's Mars mission successful, India makes history - The Times of India
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Note to moderator: Please credit this review to Brian Matherly at<EMAIL_ADDRESS>Thanks!
Cannibal! The Musical (1996) Rating: 4.0 stars out of 5.0 stars
Cast: Trey Parker (billed as "Juan Schwartz"), Matt Stone, Dian Bachar, Jason McHugh, Ian Hardin, Jon Hegel, Toddy Walters, Andy Kemler Written and Directed by: Trey Parker (billed as "Trey Parker") Running Time: 90 minutes
Insane (but inspired) musical about Alferd Packer, the first man ever tried for cannibalism in America. As the story unfolds we learn what events led to Packer (Trey Parker) supposedly killing and eating the five men who got lost while accompanying him through the mountains of Colorado in search of gold. Throughout, Packer must contend with evil trappers bent on stealing his prized horse, a tribe of `Ute' Indians that doesn't seem quite on the mark, and a terrible winter storm that leads to the eventual cannibalism. Parker obviously knows his musicals very well, because the viewer is also treated to some of the most maddeningly catchy songs to appear in a film (he would accomplish this again in his post-Cannibal! musical motion picture, South Park: Bigger, Longer, and Uncut).
Apart from the inherent interest of seeing a pre-"South Park" Parker and Stone in their first effort, Cannibal! also offers up some pretty decent laughs. The aforementioned `Ute' Indian tribe that Packer's group encounters is a definite highlight, as are two rousing musical numbers about snowmen (one of which ends on a comedically deadly note). Stone's Humphrey character steals the show, especially when complaining about the prospect of having to `eat butt' or revealing what's underneath his muff cap. Jason McHugh's character of Mr. Miller is the stand out performance though, as he offers a hilarious dissenting voice to the proceedings.
As I mentioned before, Parker's songs are very catchy. You'll be hard pressed to get `It's a Shpadoinkle Day' out of your head once you've heard it (incidentally, the Braniff logo that appears at the end of every "South Park" episode is scored with a few notes from this song). Other songs you'll find yourself humming include `When I Was On Top of You' (a love ballad), `The Trapper's Song' (the villains leit motif), and `Hang the Bastard' (the rousing finale). Thankfully, none of these songs are quite as embarrassing to find yourself singing in public as South Park:Bigger, Longer & Uncut's songs are.
Released as a pick-up through Troma Studios, the film is available on videocassette and DVD. The videocassette includes an intro by the beautiful Jane Jensen and an interview segment with Lloyd Kaufman, discussing his admiration for Parker and Stone and the fact that they had been hired for a Zucker brothers film (which turned out to be the hilarious BASEketball). There are also multiple trailers for upcoming Troma films.
As for the DVD... well, that's a different story. Probably one of the best DVD packages of the year (and potentially of all time), Cannibal! The Musical! the DVD is a massive achievement. Presented in 1.33:1 (full frame) only, the disc has the usual Troma inclusions: the Tour of Troma, the Troma Intelligence Test 2, trailers for upcoming releases, but where the disc truly shines is in its Cannibal! specific extras. The first thing I must note is, the transfer is about as beautiful as any I've ever seen on any disc. The picture is crisp, clear, and free from any noticeable artifacts. Add to that one of the funniest commentary tracks I have ever heard, featuring Trey Parker, Matt Stone, Jason McHugh, Dian Bachar, and Andy Kemler getting drunker and drunker as the track continues and you still haven't scratched the surface of the extras. There's also behind the scenes footage of the shooting of the film, a clip with Trey, Matt, and Lemmy (of the band Motorhead) from the film Terror Firmer, an index for easy location of all of the songs in the film, and finally, an index of all the songs as performed by the cast of a stage production of Cannibal!.
It's good to see this film finally get the treatment it deserves. Kudos to the entire production staff at Troma and AIX for making one of the most entertaining DVDs I have seen in a very long time.
Reviewed by Brian Matherly -<EMAIL_ADDRESS>The Jacksonville Film Journal - http://www.jaxfilmjournal.com/
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