In

_{''p''} × T_{''p''} → R on the tangent space T_{''p''} at ''p'', doing so in a smooth manner. This form determines the length of any tangent vector v on the manifold, via the definition $\backslash ,\; v\backslash ,\; =\; \backslash sqrt$. Then for any differentiable path on the manifold, its length is defined as the integral of the length of the tangent vector to the path at any point, where the integration is done with respect to the path parameter. Finally, to get a metric defined on any pair of points of the manifold, one takes the infimum, over all paths from ''x'' to ''y'', of the set of path lengths. A smooth manifold equipped with a Riemannian metric is called a Riemannian manifold.
* The Fubini–Study metric on complex projective space. This is an example of a Riemannian metric.
* String metrics, such as Levenshtein distance and other Edit distance, string edit distances, define a metric over String (computer science), strings.
* Graph edit distance defines a distance function between Graph (discrete mathematics), graphs.
* The Wasserstein metric is a distance function defined between two probability distributions.
* The Finsler metric is a continuous nonnegative function defined on the tangent bundle.

_{1} and ''d''_{2} are called ''topologically equivalent'' (''uniformly equivalent'') if the identity mapping
is a homeomorphism (uniform isomorphism).
For example, if $d$ is a metric, then $\backslash min\; (d,\; 1)$ and $\backslash frac$ are metrics equivalent to $d.$

topology
s, which have only one surface and one edge, are a kind of object studied in topology.
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structu ...

(such as continuous function (topology), continuity or limit (mathematics), convergence) are concerned. This can be done using a Subadditive function, subadditive monotonically increasing bounded function which is zero at zero, e.g. ''d''′(''x'', ''y'') = ''d''(''x'', ''y'') / (1 + ''d''(''x'', ''y'')) or ''d''″(''x'', ''y'') = min(1, ''d''(''x'', ''y'')).
The requirement that the metric take values in can even be relaxed to consider metrics with values in other directed sets. The reformulation of the axioms in this case leads to the construction of uniform spaces: topological spaces with an abstract structure enabling one to compare the local topologies of different points.

~~''d''(''x'', ''y'') = ''d''(''y'', ''x'')~~ (''symmetry'', dropped)
# ''d''(''x'', ''z'') ≤ ''d''(''x'', ''y'') + ''d''(''y'', ''z'') (''triangle inequality'')
Quasimetrics are common in real life. For example, given a set ''X'' of mountain villages, the typical walking times between elements of ''X'' form a quasimetric because travel up hill takes longer than travel down hill. Another example is a taxicab geometry topology having one-way streets, where a path from point ''A'' to point ''B'' comprises a different set of streets than a path from ''B'' to ''A''.
A quasimetric on the reals can be defined by setting
:''d''(''x'', ''y'') = ''x'' − ''y'' if ''x'' ≥ ''y'', and
:''d''(''x'', ''y'') = 1 otherwise. The 1 may be replaced by infinity or by $1\; +\; 10^$.
The topological space underlying this quasimetric space is the Sorgenfrey line. This space describes the process of Filing (metalworking), filing down a metal stick: it is easy to reduce its size, but it is difficult or impossible to grow it.
If ''d'' is a quasimetric on ''X'', a metric ''d' '' on ''X'' can be formed by taking
:''d' ''(''x'', ''y'') = (''d''(''x'', ''y'') + ''d''(''y'', ''x'')).

_{r}''(''p'') = .
A set is called ''open'' if for any point ''p'' in the set there is an ''r''-ball centered at ''p'' which is contained in the set. Every premetric space is a topological space, and in fact a sequential space.
In general, the ''r''-balls themselves need not be open sets with respect to this topology.
As for metrics, the distance between two sets ''A'' and ''B'', is defined as
:''d''(''A'', ''B'') = inf_{''x''∊''A'', ''y''∊''B''} ''d''(''x'', ''y'').
This defines a premetric on the power set of a premetric space. If we start with a (pseudosemi-)metric space, we get a pseudosemimetric, i.e. a symmetric premetric.
Any premetric gives rise to a preclosure operator ''cl'' as follows:
:''cl''(''A'') = .

mathematics
Mathematics (from Greek: ) includes the study of such topics as numbers ( and ), formulas and related structures (), shapes and spaces in which they are contained (), and quantities and their changes ( and ). There is no general consensus abo ...

, a metric or distance function is a function
Function or functionality may refer to:
Computing
* Function key
A function key is a key on a computer
A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations automatically. Modern comp ...

that gives a distance
Distance is a numerical measurement
'
Measurement is the number, numerical quantification (science), quantification of the variable and attribute (research), attributes of an object or event, which can be used to compare with other objects or eve ...

between each pair of point elements of a set. A set with a metric is called a metric space
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structure (algebra), space (geometry), and calculus, change (mathematical analysis, analysis). It ...

. A metric induces a topology
s, which have only one surface and one edge, are a kind of object studied in topology.
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structu ...

on a set, but not all topologies can be generated by a metric. A topological space
In mathematics, a topological space is, roughly speaking, a Geometry, geometrical space in which Closeness (mathematics), ''closeness'' is defined but cannot necessarily be measured by a numeric distance. More specifically, a topological space is a ...

whose topology can be described by a metric is called metrizable
In topology
s, which have only one surface and one edge, are a kind of object studied in topology.
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical struct ...

.
One important source of metrics in differential geometry
Differential geometry is a mathematical
Mathematics (from Greek
Greek may refer to:
Greece
Anything of, from, or related to Greece
Greece ( el, Ελλάδα, , ), officially the Hellenic Republic, is a country located in Southeast E ...

are metric tensor
In the mathematics, mathematical field of differential geometry, one definition of a metric tensor is a type of function which takes as input a pair of tangent vectors and at a point of a surface (or higher dimensional differentiable manifold) an ...

s, bilinear form
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structure (algebra), space (geometry), and calculus, change (mathematical analysis, analysis). It h ...

s that may be defined from the tangent vector
:''For a more general — but much more technical — treatment of tangent vectors, see tangent space.''
In mathematics, a tangent vector is a Vector (geometry), vector that is tangent to a curve or Surface (mathematics), surface at a given point. T ...

s of a differentiable manifold
In mathematics, a differentiable manifold (also differential manifold) is a type of manifold
The real projective plane is a two-dimensional manifold that cannot be realized in three dimensions without self-intersection, shown here as Boy's surfa ...

onto a scalar. A metric tensor allows distances along curves to be determined through integration, and thus determines a metric.
Definition

A metric on a set is afunction
Function or functionality may refer to:
Computing
* Function key
A function key is a key on a computer
A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations automatically. Modern comp ...

(called ''distance function'' or simply ''distance'')
:$d\; :\; X\; \backslash times\; X\; \backslash to;\; href="/html/ALL/s/,\backslash infty),$
where $[0,\backslash infty)$ is the set of non-negative real numbers and for all $x,\; y,\; z\; \backslash in\; X$, the following three axioms are satisfied:
:
A metric (as defined) is a non-negative real-valued function. This, together with axiom 1, provides a ''separation condition'', where distinct or separate points are precisely those that have a positive distance between them.
The requirement that $d$ have codomain of $[0,\backslash infty)$ is a clarifying (but unnecessary) restriction in the definition, for if we had any function $d\; :\; X\; \backslash times\; X\; \backslash to\; \backslash R$ that satisfied the same three axioms, the function could be proven to still be non-negative as follows (using axioms 1, 3, and 2 in that order):
$0\; =\; d(x,\; x)\; \backslash le\; d(x,\; y)\; +\; d(y,\; x)\; =\; d(x,\; y)\; +\; d(x,\; y)\; =\; 2\; d(x,\; y)$ which implies $0\; \backslash le\; d(x,\; y)$.
A metric is called an ultrametric
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structure (algebra), space (geometry), and calculus, change (mathematical analysis, analysis). It h ...

if it satisfies the following stronger version of the ''triangle inequality'' where points can never fall 'between' other points:
: $d(x,\; y)\; \backslash leq\; \backslash max(d(x,\; z),\; d(y,\; z))$
for all $x,\; y,\; z\; \backslash in\; X$
A metric on is called Intrinsic metric, intrinsic if any two points and in can be joined by a curve with Curve#Lengths of curves, length arbitrarily close to .
A metric ''d'' on a group ''G'' (written multiplicatively) is said to be (resp. ) if we have
:$d(zx,\; zy)\; =\; d(x,\; y)$ [resp. $d(xz,yz)=d(x,y)$]
for all ''x'', ''y'', and ''z'' in ''G''.
A metric $D$ on a commutative additive group $X$ is said to be if $D(x,\; y)\; =\; D(x\; +\; z,\; y\; +\; z)$ for all $x,\; y,\; z\; \backslash in\; X,$ or equivalently, if $D(x,\; y)\; =\; D(x\; -\; y,\; 0)$ for all $x,\; y\; \backslash in\; X.$ Every vector space is also a commutative additive group and a metric on a real or complex vector space that is induced by a Norm (mathematics), norm is always translation invariant. A metric $D$ on a real or complex vector space $X$ is induced by a norm if and only if it is translation invariant and , where the latter means that $D(sx,\; sy)\; =\; ,\; s,\; D(x,\; y)$ for all scalars $s$ and all $x,\; y\; \backslash in\; X,$ in which case the function $\backslash ,\; x\; \backslash ,\; :=\; D(x,\; 0)$ defines a norm on $X$ and the canonical metric induced by $\backslash ,\; \backslash cdot\; \backslash ,$ is equal to $D.$
Notes

These conditions express intuitive notions about the concept ofdistance
Distance is a numerical measurement
'
Measurement is the number, numerical quantification (science), quantification of the variable and attribute (research), attributes of an object or event, which can be used to compare with other objects or eve ...

. For example, that the distance between distinct points is positive and the distance from ''x'' to ''y'' is the same as the distance from ''y'' to ''x''. The triangle inequality means that the distance from ''x'' to ''z'' via ''y'' is at least as great as from ''x'' to ''z'' directly. Euclid in his Euclidean geometry, work stated that the shortest distance between two points is a line; that was the triangle inequality for his geometry.
Examples

* The discrete space, discrete metric: if ''x'' = ''y'' then ''d''(''x'',''y'') = 0. Otherwise, ''d''(''x'',''y'') = 1. * The Euclidean metric is translation and rotation invariant. * The Taxicab geometry, taxicab metric is translation invariant. * More generally, any metric induced by a norm (mathematics), norm is translation invariant. * If $(p\_n)\_$ is a sequence of seminorms defining a (locally convex) topological vector space ''E'', then $$d(x,y)=\backslash sum\_^\backslash infty\; \backslash frac\; \backslash frac$$ is a metric defining the sametopology
s, which have only one surface and one edge, are a kind of object studied in topology.
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structu ...

. (One can replace $\backslash frac$ by any absolute convergence, summable sequence $(a\_n)$ of strictly positive numbers.)
* The normed space $(\backslash R,\; ,\; \backslash cdot\; ,\; )$ is a Banach space where the absolute value is a Norm (mathematics), norm on the real line $\backslash R$ that induces the usual Euclidean topology on $\backslash R.$ Define a metric $D\; :\; \backslash R\; \backslash times\; \backslash R\; \backslash to\; \backslash R$ on $\backslash R$ by $D(x,\; y)\; =\; ,\; \backslash arctan(x)\; -\; \backslash arctan(y),$ for all $x,\; y\; \backslash in\; \backslash R.$ Just like induced metric, the metric $D$ also induces the usual Euclidean topology on . However, $D$ is not a complete metric because the sequence $x\_\; =\; \backslash left(x\_i\backslash right)\_^$ defined by $x\_i\; :=\; i$ is a Cauchy sequence, sequence but it does not converge to any point of . As a consequence of not converging, this sequence cannot be a Cauchy sequence in $(\backslash R,\; ,\; \backslash cdot\; ,\; )$ (i.e. it is not a Cauchy sequence with respect to the norm $\backslash ,\; \backslash cdot\; \backslash ,$) because if it was then the fact that $(\backslash R,\; ,\; \backslash cdot\; ,\; )$ is a Banach space would imply that it converges (a contradiction).
* Graph metric, a metric defined in terms of distances in a certain graph.
* The Hamming distance in coding theory.
* Riemannian metric, a type of metric function that is appropriate to impose on any differentiable manifold
In mathematics, a differentiable manifold (also differential manifold) is a type of manifold
The real projective plane is a two-dimensional manifold that cannot be realized in three dimensions without self-intersection, shown here as Boy's surfa ...

. For any such manifold, one chooses at each point ''p'' a symmetric, positive definite, bilinear form ''L'': TEquivalence of metrics

For a given set ''X'', two metrics ''d''Norm induced metric

Norms on vector spaces are equivalent to certain metrics, namely homogeneous, translation-invariant ones. In other words, every norm determines a metric, and some metrics determine a norm. Given a normed vector space $(X,\; \backslash ,\; \backslash cdot\backslash ,\; )$ we can define a metric $d$ on $X,$ called the or simply the , by :$d(x,y)\; :=\; \backslash ,\; x-y\backslash ,\; .$ The metric $d$ is said to be the norm $\backslash ,\; \backslash cdot\backslash ,\; .$ Conversely if a metric $d$ on a vector space $X$ satisfies the properties * Translation invariance: $d(x,y)\; =\; d(x+a,y+a)$; * Absolute homogeneity: $d(\backslash alpha\; x,\; \backslash alpha\; y)\; =\; ,\; \backslash alpha,\; d(x,y)$; then a norm (mathematics), norm on $X$ may be defined by :$\backslash ,\; x\backslash ,\; :=\; d(x,0)$ where the metric induced by this norm is the original given metric $d.$ Similarly, a seminorm induces a pseudometric (see below), and a homogeneous, translation invariant pseudometric induces a seminorm.Metrics on multisets

We can generalize the notion of a metric from a distance between two elements to a distance between two nonempty finite multisets of elements. A multiset is a generalization of the notion of a set (mathematics), set such that an element can occur more than once. Define $Z=XY$ if $Z$ is the multiset consisting of the elements of the multisets $X$ and $Y$, that is, if $x$ occurs once in $X$ and once in $Y$ then it occurs twice in $Z$. A distance function $d$ on the set of nonempty finite multisets is a metric if # $d(X)=0$ if all elements of $X$ are equal and $d(X)\; >\; 0$ otherwise (positive definiteness), that is, (Non-negative, non-negativity plus identity of indiscernibles) # $d(X)$ is invariant under all permutations of $X$ (symmetry) # $d(XY)\; \backslash leq\; d(XZ)+d(ZY)$ (triangle inequality) Note that the familiar metric between two elements results if the multiset $X$ has two elements in 1 and 2 and the multisets $X,Y,Z$ have one element each in 3. For instance if $X$ consists of two occurrences of $x$, then $d(X)=0$ according to 1. A simple example is the set of all nonempty finite multisets $X$ of integers with $d(X)=\backslash max\backslash -\; \backslash min\backslash $. More complex examples are information distance in multisets; and normalized compression distance (NCD) in multisets.Generalized metrics

There are numerous ways of relaxing the axioms of metrics, giving rise to various notions of generalized metric spaces. These generalizations can also be combined. The terminology used to describe them is not completely standardized. Most notably, in functional analysis pseudometrics often come from seminorms on vector spaces, and so it is natural to call them "semimetrics". This conflicts with the use of the term intopology
s, which have only one surface and one edge, are a kind of object studied in topology.
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structu ...

.
Extended metrics

Some authors allow the distance function ''d'' to attain the value ∞, i.e. distances are non-negative numbers on the extended real number line. Such a function is called an ''extended metric'' or "∞-metric". Every extended metric can be transformed to a finite metric such that the metric spaces are equivalent as far as notions ofPseudometrics

A ''pseudometric'' on ''X'' is a function $d:\; X\; \backslash times\; X\; \backslash to\; \backslash R$ which satisfies the axioms for a metric, except that instead of the second (identity of indiscernibles) only for all ''x'' is required. In other words, the axioms for a pseudometric are: # ''d''(''x'', ''y'') ≥ 0 # ''d''(''x'', ''x'') = 0 (but possibly ''d''(''x'', ''y'') = 0 for some distinct values ''x'' ≠ ''y''.) # ''d''(''x'', ''y'') = ''d''(''y'', ''x'') # ''d''(''x'', ''z'') ≤ ''d''(''x'', ''y'') + ''d''(''y'', ''z''). In some contexts, pseudometrics are referred to as ''semimetrics'' because of their relation to seminorms.Quasimetrics

Occasionally, a quasimetric is defined as a function that satisfies all axioms for a metric with the possible exception of symmetry. The name of this generalisation is not entirely standardized. # ''d''(''x'', ''y'') ≥ 0 (''positivity'') # ''d''(''x'', ''y'') = 0 if and only if ''x'' = ''y'' (''positive definiteness'') #Metametrics

In a ''metametric'', all the axioms of a metric are satisfied except that the distance between identical points is not necessarily zero. In other words, the axioms for a metametric are: # ''d''(''x'', ''y'') ≥ 0 # ''d''(''x'', ''y'') = 0 implies ''x'' = ''y'' (but not vice versa.) # ''d''(''x'', ''y'') = ''d''(''y'', ''x'') # ''d''(''x'', ''z'') ≤ ''d''(''x'', ''y'') + ''d''(''y'', ''z''). Metametrics appear in the study of Δ-hyperbolic space, Gromov hyperbolic metric spaces and their boundaries. The ''visual metametric'' on such a space satisfies ''d''(''x'', ''x'') = 0 for points ''x'' on the boundary, but otherwise ''d''(''x'', ''x'') is approximately the distance from ''x'' to the boundary. Metametrics were first defined by Jussi Väisälä.Semimetrics

A semimetric on ''X'' is a function $d:\; X\; \backslash times\; X\; \backslash to\; \backslash R$ that satisfies the first three axioms, but not necessarily the triangle inequality: # ''d''(''x'', ''y'') ≥ 0 # ''d''(''x'', ''y'') = 0 if and only if ''x'' = ''y'' # ''d''(''x'', ''y'') = ''d''(''y'', ''x'') Some authors work with a weaker form of the triangle inequality, such as: : ''d''(''x'', ''z'') ≤ ρ (''d''(''x'', ''y'') + ''d''(''y'', ''z'')) (ρ-relaxed triangle inequality) : ''d''(''x'', ''z'') ≤ ρ max(''d''(''x'', ''y''), ''d''(''y'', ''z'')) (ρ-inframetric inequality). The ρ-inframetric inequality implies the ρ-relaxed triangle inequality (assuming the first axiom), and the ρ-relaxed triangle inequality implies the 2ρ-inframetric inequality. Semimetrics satisfying these equivalent conditions have sometimes been referred to as "quasimetrics", "nearmetrics" or inframetrics. The ρ-inframetric inequalities were introduced to model round-trip delay times in the internet. The triangle inequality implies the 2-inframetric inequality, and the ultrametric inequality is exactly the 1-inframetric inequality.Premetrics

Relaxing the last three axioms leads to the notion of a premetric, i.e. a function satisfying the following conditions: # ''d''(''x'', ''y'') ≥ 0 # ''d''(''x'', ''x'') = 0 This is not a standard term. Sometimes it is used to refer to other generalizations of metrics such as pseudosemimetrics or pseudometrics; in translations of Russian books it sometimes appears as "prametric". A premetric that satisfies symmetry, i.e. a pseudosemimetric, is also called a distance. Any premetric gives rise to a topology as follows. For a positive real ''r'', the ''r''-ball centered at a point ''p'' is defined as :''BPseudoquasimetrics

The prefixes ''pseudo-'', ''quasi-'' and ''semi-'' can also be combined, e.g., a pseudoquasimetric (sometimes called hemimetric) relaxes both the indiscernibility axiom and the symmetry axiom and is simply a premetric satisfying the triangle inequality. For pseudoquasimetric spaces the open ''r''-balls form a basis of open sets. A very basic example of a pseudoquasimetric space is the set with the premetric given by ''d''(0,1) = 1 and ''d''(1,0) = 0. The associated topological space is the Sierpiński space. Sets equipped with an extended pseudoquasimetric were studied by William Lawvere as "generalized metric spaces". From a Category theory, categorical point of view, the extended pseudometric spaces and the extended pseudoquasimetric spaces, along with their corresponding nonexpansive maps, are the best behaved of the metric space categories. One can take arbitrary products and coproducts and form quotient objects within the given category. If one drops "extended", one can only take finite products and coproducts. If one drops "pseudo", one cannot take quotients. Approach spaces are a generalization of metric spaces that maintains these good categorical properties.Łukaszyk-Karmowski distance

Łukaszyk–Karmowski metric, Łukaszyk-Karmowski distance is afunction
Function or functionality may refer to:
Computing
* Function key
A function key is a key on a computer
A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations automatically. Modern comp ...

defining a metric space, distance between two random variables or two random vectors. The axioms of this function are:
# ''d''(''x'', ''y'') > 0
# ''d''(''x'', ''y'') = ''d''(''y'', ''x'')
# ''d''(''x'', ''z'') ≤ ''d''(''x'', ''y'') + ''d''(''y'', ''z'').
This distance function satisfies the identity of indiscernibles condition if and only if both arguments are described by idealized Dirac delta density Probability density function, probability distribution functions.
Important cases of generalized metrics

Indifferential geometry
Differential geometry is a mathematical
Mathematics (from Greek
Greek may refer to:
Greece
Anything of, from, or related to Greece
Greece ( el, Ελλάδα, , ), officially the Hellenic Republic, is a country located in Southeast E ...

, one considers a metric tensor
In the mathematics, mathematical field of differential geometry, one definition of a metric tensor is a type of function which takes as input a pair of tangent vectors and at a point of a surface (or higher dimensional differentiable manifold) an ...

, which can be thought of as an "infinitesimal" quadratic metric function. This is defined as a nondegenerate symmetric bilinear form
In mathematics
Mathematics (from Ancient Greek, Greek: ) includes the study of such topics as quantity (number theory), mathematical structure, structure (algebra), space (geometry), and calculus, change (mathematical analysis, analysis). It h ...

on the tangent space of a manifold with an appropriate differentiability requirement. While these are not metric functions as defined in this article, they induce what is called a pseudo-semimetric function by Antiderivative, integration of its square root along a path through the manifold. If one imposes the positive-definiteness requirement of an inner product on the metric tensor, this restricts to the case of a Riemannian manifold, and the path integration yields a metric.
In general relativity the related concept is a metric tensor (general relativity) which expresses the structure of a pseudo-Riemannian manifold. Though the term "metric" is used, the fundamental idea is different because there are non-zero null vectors in the tangent space of these manifolds, and vectors can have negative squared norms. This generalized view of "metrics", in which zero distance does ''not'' imply identity, has crept into some mathematical writing too:: "This bilinear form is variously called the ''Lorentz metric'', or ''Minkowski metric'' or ''metric tensor''"; : "We call this scalar product the ''Lorentz metric''"
See also

*Acoustic metric *Complete metric *Similarity measure *Signed distance functionNotes

References

* * * * * * * * * *; reprinted with added commentary from * * * * * * * * * * de:Metrik (Mathematik) {{DEFAULTSORT:Metric (Mathematics) Metric geometry Topology Distance