$$ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Self-defined math definitions %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Math symbol commands \newcommand{\intd}{\,{\rm d}} % Symbol 'd' used in integration, such as 'dx' \newcommand{\diff}{{\rm d}} % Symbol 'd' used in differentiation \newcommand{\Diff}{{\rm D}} % Symbol 'D' used in differentiation \newcommand{\pdiff}{\partial} % Partial derivative \newcommand{DD}[2]{\frac{\diff}{\diff #2}\left( #1 \right)} \newcommand{Dd}[2]{\frac{\diff #1}{\diff #2}} \newcommand{PD}[2]{\frac{\pdiff}{\pdiff #2}\left( #1 \right)} \newcommand{Pd}[2]{\frac{\pdiff #1}{\pdiff #2}} \newcommand{\rme}{{\rm e}} % Exponential e \newcommand{\rmi}{{\rm i}} % Imaginary unit i \newcommand{\rmj}{{\rm j}} % Imaginary unit j \newcommand{\vect}[1]{\boldsymbol{#1}} % Vector typeset in bold and italic \newcommand{\phs}[1]{\dot{#1}} % Scalar phasor \newcommand{\phsvect}[1]{\boldsymbol{\dot{#1}}} % Vector phasor \newcommand{\normvect}{\vect{n}} % Normal vector: n \newcommand{\dform}[1]{\overset{\rightharpoonup}{\boldsymbol{#1}}} % Vector for differential form \newcommand{\cochain}[1]{\overset{\rightharpoonup}{#1}} % Vector for cochain \newcommand{\bigabs}[1]{\bigg\lvert#1\bigg\rvert} % Absolute value (single big vertical bar) \newcommand{\Abs}[1]{\big\lvert#1\big\rvert} % Absolute value (single big vertical bar) \newcommand{\abs}[1]{\lvert#1\rvert} % Absolute value (single vertical bar) \newcommand{\bignorm}[1]{\bigg\lVert#1\bigg\rVert} % Norm (double big vertical bar) \newcommand{\Norm}[1]{\big\lVert#1\big\rVert} % Norm (double big vertical bar) \newcommand{\norm}[1]{\lVert#1\rVert} % Norm (double vertical bar) \newcommand{\ouset}[3]{\overset{#3}{\underset{#2}{#1}}} % over and under set % Super/subscript for column index of a matrix, which is used in tensor analysis. \newcommand{\cscript}[1]{\;\; #1} % Star symbol used as prefix in front of a paragraph with no indent \newcommand{\prefstar}{\noindent$\ast$ } % Big vertical line restricting the function. % Example: $u(x)\restrict_{\Omega_0}$ \newcommand{\restrict}{\big\vert} % Math operators which are typeset in Roman font \DeclareMathOperator{\sgn}{sgn} % Sign function \DeclareMathOperator{\erf}{erf} % Error function \DeclareMathOperator{\Bd}{Bd} % Boundary of a set, used in topology \DeclareMathOperator{\Int}{Int} % Interior of a set, used in topology \DeclareMathOperator{\rank}{rank} % Rank of a matrix \DeclareMathOperator{\divergence}{div} % Curl \DeclareMathOperator{\curl}{curl} % Curl \DeclareMathOperator{\grad}{grad} % Gradient \DeclareMathOperator{\tr}{tr} % Trace \DeclareMathOperator{\span}{span} % Span $$

止于至善

As regards numerical analysis and mathematical electromagnetism

A tuple is defined as a function

In James Munkres “Topology”, the concept for a tuple, which can be \(m\)-tuple, \(\omega\)-tuple or \(J\)-tuple, is defined from a function point of view as below.

Let \(X\) be a set.

  • Let \(m\) be a positive integer and \(\{ 1, \cdots, m \}\) be an index set. An \(m\)-tuple of elements in \(X\) is a function

    \[
    \vect{x}: \{ 1, \cdots, m \} \rightarrow X.
    \]

  • Let \(\mathbb{Z}_+\) be the index set comprised of all positive integers. An \(\omega\)-tuple of elements in \(X\) is a function

    \[
    \vect{x}: \mathbb{Z}_+ \rightarrow X.
    \]

  • Let \(J\) be an index set, whose cardinality is not limited to be finite or infinite, countable or uncountable. A \(J\)-tuple of elements in \(X\) is a function

    \[
    \vect{x}: J \rightarrow X.
    \]

For all these types of tuples, if \(\alpha\) is an index belongs to the index set, the corresponding coordinate component of the tuple is \(\vect{x}(\alpha)\). It is written as \(x_{\alpha}\), which is the form we often use.

From the above it can be seen that a tuple of elements, which are literally tangible data, are viewed as the rule of assignment for a function, which is more abstract. In addition, while we have already been given to the stereotype of a tuple, which is a container holding a list of ordered elements, the function mapping version of a tuple does not require any order relation prescribed for the tuple’s index set.

Considering these concepts in computer programming, a tuple of values or objects can be either stored in an ordered array as in procedural programming. Or the tuple can be stored within a function as in functional programming. Without loss of generality, this functional perspective can be further applied to matrix and tensor, which eliminates or mingles the boundary between data and operation.

posted @ 2018-12-23 16:15  皮波迪博士  阅读(200)  评论(0编辑  收藏  举报