Civil Rights
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In 1968 Shirley Chisholm became the first Black woman elected to the United States Congress. In 1972 she launched a campaign for the Democratic presidential nomination, breaking another political barrier.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
In computer science, partial application (or partial function application) refers to the process of fixing a number of arguments of a function, producing another function of smaller arity. Given a function , we might fix (or 'bind') the first argument, producing a function of type . Evaluation of this function might be represented as . Note that the result of partial function application in this case is a function that takes two arguments. Partial application is sometimes incorrectly called currying, which is a related, but distinct concept.
Intuitively, partial function application says "if you fix the first arguments of the function, you get a function of the remaining arguments". For example, if function div(x,y) = x/y, then div with the parameter x fixed at 1 is another function: div1(y) = div(1,y) = 1/y. This is the same as the function inv that returns the multiplicative inverse of its argument, defined by inv(y) = 1/y.
The practical motivation for partial application is that very often the functions obtained by supplying some but not all of the arguments to a function are useful; for example, many languages have a function or operator similar to plus_one. Partial application makes it easy to define these functions, for example by creating a function that represents the addition operator with 1 bound as its first argument.
In languages such as ML, Haskell and F#, functions are defined in curried form by default. Supplying fewer than the total number of arguments is referred to as partial application.
In languages with first-class functions, one can define curry, uncurry and papply to perform currying and partial application explicitly. This might incur a greater run-time overhead due to the creation of additional closures, while Haskell can use more efficient techniques.[1]
Scala implements optional partial application with placeholder, e.g. def add(x: Int, y: Int) = {x+y}; add(1, _: Int) returns an incrementing function. Scala also supports multiple parameter lists as currying, e.g. def add(x: Int)(y: Int) = {x+y}; add(1) _.
Clojure implements partial application using the partial function defined in its core library.[2]
The C++ standard library provides bind(function, args..) to return a function object that is the result of partial application of the given arguments to the given function. Since C++20 the function bind_front(function, args...) is also provided which binds the first sizeof...(args) arguments of the function to the args. In contrast, bind allows binding any of the arguments of the function passed to it, not just the first ones. Alternatively, lambda expressions can be used:
int f(int a, int b);
auto f_partial = [](int a) { return f(a, 123); };
assert(f_partial(456) == f(456, 123) );
In Java, MethodHandle.bindTo partially applies a function to its first argument.[3]
Alternatively, since Java 8, lambdas can be used:
public static <A, B, R> Function<B, R> partialApply(BiFunction<A, B, R> biFunc, A value) {
return b -> biFunc.apply(value, b);
}
In Raku, the assuming method creates a new function with fewer parameters.[4]
The Python standard library module functools includes the partial function, allowing positional and named argument bindings, returning a new function.[5]
In XQuery, an argument placeholder (?) is used for each non-fixed argument in a partial function application.[6]
In the simply typed lambda calculus with function and product types (λ→,×) partial application, currying and uncurrying can be defined as
papplycurryuncurryNote that curry papply = curry.
Partial application can be a useful way to define several useful notions in mathematics.
Given sets and , and a function , one can define the function
where is the set of functions . The image of under this map is . This is the function which sends to . There are often structures on which mean that the image of restricts to some subset of functions , as illustrated in the following examples.
A group action can be understood as a function . The partial evaluation restricts to the group of bijections from to itself. The group action axioms further ensure is a group homomorphism.
An inner-product on a vector space over a field is a map . The partial evaluation provides a canonical map to the dual vector space, . If this is the inner-product of a Hilbert space, the Riesz representation theorem ensures this is an isomorphism.
The partial application of the cross product on is . The image of the vector is a linear map such that . The components of can be found to be .
This is closely related to the adjoint map for Lie algebras. Lie algebras are equipped with a bracket . The partial application gives a map . The axioms for the bracket ensure this map is a homomorphism of Lie algebras.
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In computer science, partial application (or partial function application) refers to the process of fixing a number of arguments of a function, producing another function of smaller arity. Given a function f : ( X × Y × Z ) → N {\displaystyle f\colon (X\times Y\times Z)\to N} , we might fix (or 'bind') the first argument, producing a function of type partial ( f ) : ( Y × Z ) → N {\displaystyle {\text{partial}}(f)\colon (Y\times Z)\to N} . Evaluation of this function might be represented as f partial ( 2 , 3 ) {\displaystyle f_{\text{partial}}(2,3)} . Note that the result of partial function application in this case is a function that takes two arguments. Partial application is sometimes incorrectly called currying, which is a related, but distinct concept.
In mathematics and computer science, currying (named after Haskell Curry) is the technique of translating a function that takes multiple arguments into a sequence of families of functions, each taking a single argument. In the prototypical example, one begins with a function f : ( X × Y ) → Z {\displaystyle f:(X\times Y)\to Z} that takes two arguments, one from X {\displaystyle X} and one from Y , {\displaystyle Y,} and produces objects in Z . {\displaystyle Z.} The curried form of this function treats the first argument as a parameter, so as to create a family of functions f x : Y → Z . {\displaystyle f_{x}:Y\to Z.} The family is arranged so that for each object x {\displaystyle x} in X , {\displaystyle X,} there is exactly one function f x {\displaystyle f_{x}} , such that for any y {\displaystyle y} in Y {\displaystyle Y} , f x ( y ) = f ( x , y ) {\displaystyle f_{x}(y)=f(x,y)} . In this example, curry {\displaystyle {\mbox{curry}}} itself becomes a function that takes f {\displaystyle f} as an argument, and returns a function that maps each x {\displaystyle x} to f x . {\displaystyle f_{x}.} The proper notation for expressing this is verbose. The function f {\displaystyle f} belongs to the set of functions ( X × Y ) → Z . {\displaystyle (X\times Y)\to Z.} Meanwhile, f x {\displaystyle f_{x}} belongs to the set of functions Y → Z . {\displaystyle Y\to Z.} Thus, something that maps x {\displaystyle x} to f x {\displaystyle f_{x}} will be of the type X → [ Y → Z ] . {\displaystyle X\to [Y\to Z].} With this notation, curry {\displaystyle {\mbox{curry}}} is a function that takes objects from the first set, and returns objects in the second set, and so one writes curry : [ ( X × Y ) → Z ] → ( X → [ Y → Z ] ) . {\displaystyle {\mbox{curry}}:[(X\times Y)\to Z]\to (X\to [Y\to Z]).} This is a somewhat informal example; more precise definitions of what is meant by "object" and "function" are given below. These definitions vary from context to context, and take different forms, depending on the theory that one is working in. Currying is related to, but not the same as, partial application. The example above can be used to illustrate partial application; it is quite similar. Partial application is the function apply {\displaystyle {\mbox{apply}}} that takes the pair f {\displaystyle f} and x {\displaystyle x} together as arguments, and returns f x . {\displaystyle f_{x}.} Using the same notation as above, partial application has the signature apply : ( [ ( X × Y ) → Z ] × X ) → [ Y → Z ] . {\displaystyle {\mbox{apply}}:([(X\times Y)\to Z]\times X)\to [Y\to Z].} Written this way, application can be seen to be adjoint to currying. The currying of a function with more than two arguments can be defined by induction. Currying is useful in both practical and theoretical settings. In functional programming languages, and many others, it provides a way of automatically managing how arguments are passed to functions and exceptions. In theoretical computer science, it provides a way to study functions with multiple arguments in simpler theoretical models which provide only one argument. The most general setting for the strict notion of currying and uncurrying is in the closed monoidal categories, which underpins a vast generalization of the Curry–Howard correspondence of proofs and programs to a correspondence with many other structures, including quantum mechanics, cobordisms, and string theory. The concept of currying was introduced by Gottlob Frege, developed by Moses Schönfinkel, and further developed by Haskell Curry. Uncurrying is the dual transformation to currying, and can be seen as a form of defunctionalization. It takes a function f {\displaystyle f} whose return value is another function g {\displaystyle g} , and yields a new function f ′ {\displaystyle f'} that takes as parameters the arguments for both f {\displaystyle f} and g {\displaystyle g} , and returns, as a result, the application of f {\displaystyle f} and subsequently, g {\displaystyle g} , to those arguments. The process can be iterated.
In computing, partial evaluation is a technique for several different types of program optimization by specialization. The most straightforward application is to produce new programs that run faster than the originals while being guaranteed to behave in the same way. A computer program prog {\displaystyle {\texttt {prog}}} is seen as a mapping of input data into output data: prog : I static × I dynamic → O , {\displaystyle {\texttt {prog}}:I_{\text{static}}\times I_{\text{dynamic}}\to O,} where I static {\displaystyle I_{\text{static}}} , the static data, is the part of the input data known at compile time. The partial evaluator transforms ⟨ prog , I static ⟩ {\displaystyle \langle {\texttt {prog}},I_{\text{static}}\rangle } into prog ∗ : I dynamic → O {\displaystyle {\texttt {prog}}^{*}:I_{\text{dynamic}}\to O} by precomputing all static input at compile time. prog ∗ {\displaystyle {\texttt {prog}}^{*}} is called the "residual program" and should run more efficiently than the original program. The act of partial evaluation is said to "residualize" prog {\displaystyle {\texttt {prog}}} to prog ∗ {\displaystyle {\texttt {prog}}^{*}} .
In mathematics, a partial differential equation (PDE) is an equation which involves a multivariable function and one or more of its partial derivatives. The function is often thought of as an "unknown" that solves the equation. However, it is often impossible to write down explicit formulas for solutions of partial differential equations. Hence there is a vast amount of modern mathematical and scientific research on methods to numerically approximate solutions of partial differential equations using computers. Partial differential equations also occupy a large sector of pure mathematical research, where the focus is on the qualitative features of solutions of various partial differential equations, such as existence, uniqueness, regularity and stability. Among the many open questions are the existence and smoothness of solutions to the Navier–Stokes equations, named as one of the Millennium Prize Problems in 2000. Partial differential equations occur very widely in mathematically oriented scientific fields, such as physics and engineering. For instance, they are foundational in the modern scientific understanding of sound, heat, diffusion, electrostatics, electrodynamics, thermodynamics, fluid dynamics, elasticity, general relativity, and quantum mechanics (Schrödinger equation, Pauli equation etc.). They also arise from many purely mathematical considerations, such as differential geometry and the calculus of variations; among other notable applications, they are the fundamental tool in the proof of the Poincaré conjecture from geometric topology. Partly due to this variety of sources, there is a wide spectrum of types of partial differential equations. Many different methods have been developed for dealing with the individual equations which arise. As such, there is no "universal theory" of partial differential equations, with specialist knowledge being divided between several distinct subfields. Ordinary differential equations can be viewed as a subclass of partial differential equations, corresponding to functions of a single variable. Stochastic partial differential equations and nonlocal equations are widely studied extensions of the "PDE" notion. More classical topics, on which there is still much active research, include elliptic and parabolic partial differential equations, fluid mechanics, Boltzmann equations, and dispersive partial differential equations.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →The Greenwood District.