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The memo contains many of the same types of information: a date, telephone number, email address and an "importance" value from an enumerated list, such as "low", "medium" or "high". Applications which process invoices and memos need to raise exceptions if something that was supposed to be a date or telephone number does not conform to the rules for valid dates or telephone numbers.

In both cases, validity constraints exist on the content of the instances that are not expressible in XML DTDs. The limited datatyping facilities in XML have prevented validating XML processors from supplying the rigorous type checking required in these situations. The result has been that individual applications writers have had to implement type checking in an ad hoc manner. This specification addresses the need of both document authors and applications writers for a robust, extensible datatype system for XML which could be incorporated into XML processors.

As discussed below, these datatypes could be used in other XML-related standards as well. The [XML Schema Requirements] document spells out concrete requirements to be fulfilled by this specification, which state that the XML Schema Language must:. This portion of the XML Schema Language discusses datatypes that can be used in an XML Schema. These datatypes can be specified for element content that would be specified as PCDATA and attribute values of various types in a DTD.

It is the intention of this specification that it be usable outside of the context of XML Schemas for a wide range of other XML-related activities such as [XSL] and [RDF Schema]. The terminology used to describe XML Schema Datatypes is defined in the body of this specification. The terms defined in the following list are used in building those definitions and in describing the actions of a datatype processor:. This specification provides three different kinds of normative statements about schema components, their representations in XML and their contribution to the schema-validation of information items:.

This section describes the conceptual framework behind the type system defined in this specification. The framework has been influenced by the [ISO ] standard on language-independent datatypes as well as the datatypes for [SQL] and for programming languages such as Java.

The datatypes discussed in this specification are computer representations of well known abstract concepts such as integer and date. It is not the place of this specification to define these abstract concepts; many other publications provide excellent definitions.

Each value in the value space of a datatype is denoted by one or more literals in its · lexical space ·. The · value space · of a given datatype can be defined in one of the following ways:. For example, they always have the property of · cardinality · , some definition of equality and might be · ordered · , by which individual values within the · value space · can be compared to one another.

The properties of · value space · s that are recognized by this specification are defined in Fundamental facets §2. In addition to its · value space · , each datatype also has a lexical space. For example, "" and "1. The type system defined in this specification provides a mechanism for schema designers to control the set of values and the corresponding set of acceptable literals of those values for a datatype.

While the datatypes defined in this specification have, for the most part, a single lexical representation i. each value in the datatype's · value space · is denoted by a single literal in its · lexical space · , this is not always the case.

The example in the previous section showed two literals for the datatype float which denote the same value. Similarly, there · may · be several literals for one of the date or time datatypes that denote the same value using different timezone indicators. Generally speaking, each facet characterizes a · value space · along independent axes or dimensions. The facets of a datatype serve to distinguish those aspects of one datatype which differ from other datatypes.

Rather than being defined solely in terms of a prose description the datatypes in this specification are defined in terms of the synthesis of facet values which together determine the · value space · and properties of the datatype.

Facets are of two types: fundamental facets that define the datatype and non-fundamental or constraining facets that constrain the permitted values of a datatype. All fundamental facets are fully described in Fundamental Facets §4. Constraining the · value space · consequently constrains the · lexical space ·.

Adding · constraining facet · s to a · base type · is described in Derivation by restriction §4. All constraining facets are fully described in Constraining Facets §4.

It is useful to categorize the datatypes defined in this specification along various dimensions, forming a set of characterization dichotomies. The first distinction to be made is that between · atomic · , · list · and · union · datatypes. For example, a single token which · match · es Nmtoken from [XML 1. The · value space · of an · atomic · datatype is a set of "atomic" values, which for the purposes of this specification, are not further decomposable.

The · lexical space · of an · atomic · datatype is a set of literals whose internal structure is specific to the datatype in question. Several type systems such as the one described in [ISO ] treat · list · datatypes as special cases of the more general notions of aggregate or collection datatypes. The · value space · of a · list · datatype is a set of finite-length sequences of · atomic · values. The · lexical space · of a · list · datatype is a set of literals whose internal structure is a space-separated sequence of literals of the · atomic · datatype of the items in the · list ·.

A · list · datatype can be · derived · from an · atomic · datatype whose · lexical space · allows space such as string or anyURI or a · union · datatype any of whose {member type definitions} 's · lexical space · allows space. In such a case, regardless of the input, list items will be separated at space boundaries. When a datatype is · derived · from a · list · datatype, the following · constraining facet · s apply:.

For each of · length · , · maxLength · and · minLength · , the unit of length is measured in number of list items. The value of · whiteSpace · is fixed to the value collapse. For · list · datatypes the · lexical space · is composed of space-separated literals of its · itemType ·. Hence, any · pattern · specified when a new datatype is · derived · from a · list · datatype is matched against each literal of the · list · datatype and not against the literals of the datatype that serves as its · itemType ·.

The canonical-lexical-representation for the · list · datatype is defined as the lexical form in which each item in the · list · has the canonical lexical representation of its · itemType ·. The · value space · and · lexical space · of a · union · datatype are the union of the · value space · s and · lexical space · s of its · memberTypes ·. Currently, there are no · built-in · · union · datatypes. Any number greater than 1 of · atomic · or · list · · datatype · s can participate in a · union · type.

During validation, an element or attribute's value is validated against the · memberTypes · in the order in which they appear in the definition until a match is found. The evaluation order can be overridden with the use of xsi:type.

The canonical-lexical-representation for a · union · datatype is defined as the lexical form in which the values have the canonical lexical representation of the appropriate · memberTypes ·. Next, we distinguish between · primitive · and · derived · datatypes. For example, in this specification, float is a well-defined mathematical concept that cannot be defined in terms of other datatypes, while a integer is a special case of the more general datatype decimal.

anySimpleType can be considered as the · base type · of all · primitive · datatypes. anySimpleType is considered to have an unconstrained lexical space and a · value space · consisting of the union of the · value space · s of all the · primitive · datatypes and the set of all lists of all members of the · value space · s of all the · primitive · datatypes.

The datatypes defined by this specification fall into both the · primitive · and · derived · categories. It is felt that a judiciously chosen set of · primitive · datatypes will serve the widest possible audience by providing a set of convenient datatypes that can be used as is, as well as providing a rich enough base from which the variety of datatypes needed by schema designers can be · derived ·.

In the example above, integer is · derived · from decimal. As described in more detail in XML Representation of Simple Type Definition Schema Components §4.

base type s can be either · primitive · or · derived ·. A · list · datatype can be · derived · from another datatype its · itemType · by creating a · value space · that consists of a finite-length sequence of values of its · itemType ·. One datatype can be · derived · from one or more datatypes by · union · ing their · value space · s and, consequently, their · lexical space · s. Conceptually there is no difference between the · built-in · · derived · datatypes included in this specification and the · user-derived · datatypes which will be created by individual schema designers.

The · built-in · · derived · datatypes are those which are believed to be so common that if they were not defined in this specification many schema designers would end up "reinventing" them.

Furthermore, including these · derived · datatypes in this specification serves to demonstrate the mechanics and utility of the datatype generation facilities of this specification. Each built-in datatype in this specification both · primitive · and · derived · can be uniquely addressed via a URI Reference constructed as follows:. Additionally, each facet definition element can be uniquely addressed via a URI constructed as follows:.

Additionally, each facet usage in a built-in datatype definition can be uniquely addressed via a URI constructed as follows:. For example, to address the usage of the maxInclusive facet in the definition of int, the URI is:. The · built-in · datatypes defined by this specification are designed to be used with the XML Schema definition language as well as other XML specifications. To facilitate usage within the XML Schema definition language, the · built-in · datatypes in this specification have the namespace name:.

To facilitate usage in specifications other than the XML Schema definition language, such as those that do not want to know anything about aspects of the XML Schema definition language other than the datatypes, each · built-in · datatype is also defined in the namespace whose URI is:. This applies to both · built-in · · primitive · and · built-in · · derived · datatypes.

Each · user-derived · datatype is also associated with a unique namespace. However, · user-derived · datatypes do not come from the namespace defined by this specification; rather, they come from the namespace of the schema in which they are defined see XML Representation of Schemas in [XML Schema Part 1: Structures].

The · primitive · datatypes defined by this specification are described below. For each datatype, the · value space · and · lexical space · are defined, · constraining facet · s which apply to the datatype are listed and any datatypes · derived · from this datatype are specified.

The · value space · of string is the set of finite-length sequences of character s as defined in [XML 1. A character is an atomic unit of communication; it is not further specified except to note that every character has a corresponding Universal Character Set code point, which is an integer.

string has the following · constraining facets · :. The following · built-in · datatypes are · derived · from string :. An instance of a datatype that is defined as · boolean · can have the following legal literals {true, false, 1, 0}. boolean has the following · constraining facets · :. The · value space · of decimal is the set of numbers that can be obtained by multiplying an integer by a non-positive power of ten, i.

Precision is not reflected in this value space; the number 2. The · order-relation · on decimal is the order relation on real numbers, restricted to this subset.

decimal has a lexical representation consisting of a finite-length sequence of decimal digits x x39 separated by a period as a decimal indicator. An optional leading sign is allowed.

Leading and trailing zeroes are optional. If the fractional part is zero, the period and following zero es can be omitted. For example: The canonical representation for decimal is defined by prohibiting certain options from the Lexical representation §3. The decimal point is required. Leading and trailing zeroes are prohibited subject to the following: there must be at least one digit to the right and to the left of the decimal point which may be a zero.

decimal has the following · constraining facets · :. The following · built-in · datatypes are · derived · from decimal :. In addition to the basic · value space · described above, the · value space · of float also contains the following three special values : positive and negative infinity and not-a-number NaN.

Positive infinity is greater than all other non-NaN values. NaN equals itself but is · incomparable · with neither greater than nor less than any other value in the · value space ·. A literal in the · lexical space · representing a decimal number d maps to the normalized value in the · value space · of float that is closest to d in the sense defined by [Clinger, WD ] ; if d is exactly halfway between two such values then the even value is chosen.

float values have a lexical representation consisting of a mantissa followed, optionally, by the character "E" or "e", followed by an exponent.

The exponent · must · be an integer. The mantissa must be a decimal number. The representations for exponent and mantissa must follow the lexical rules for integer and decimal. If the "E" or "e" and the following exponent are omitted, an exponent value of 0 is assumed.

The special values positive and negative infinity and not-a-number have lexical representations INF , -INF and NaN , respectively. Lexical representations for zero may take a positive or negative sign.

For example, -1E4, The canonical representation for float is defined by prohibiting certain options from the Lexical representation §3. Specifically, the exponent must be indicated by "E". If the exponent is zero, it must be indicated by "E0". Leading and trailing zeroes are prohibited subject to the following: number representations must be normalized such that there is a single digit which is non-zero to the left of the decimal point and at least a single digit to the right of the decimal point unless the value being represented is zero.

The canonical representation for zero is 0. float has the following · constraining facets · :. In addition to the basic · value space · described above, the · value space · of double also contains the following three special values : positive and negative infinity and not-a-number NaN. A literal in the · lexical space · representing a decimal number d maps to the normalized value in the · value space · of double that is closest to d ; if d is exactly halfway between two such values then the even value is chosen.

This is the best approximation of d [Clinger, WD ] , [Gay, DM ] , which is more accurate than the mapping required by [IEEE ]. double values have a lexical representation consisting of a mantissa followed, optionally, by the character "E" or "e", followed by an exponent.

The canonical representation for double is defined by prohibiting certain options from the Lexical representation §3. double has the following · constraining facets · :. The · value space · of duration is a six-dimensional space where the coordinates designate the Gregorian year, month, day, hour, minute, and second components defined in § 5.

These components are ordered in their significance by their order of appearance i. as year, month, day, hour, minute, and second. The number of seconds can include decimal digits to arbitrary precision. The values of the Year, Month, Day, Hour and Minutes components are not restricted but allow an arbitrary unsigned integer, i.

Similarly, the value of the Seconds component allows an arbitrary unsigned decimal. Following [ISO ] , at least one digit must follow the decimal point if it appears. Thus, the lexical representation of duration does not follow the alternative format of § 5. An optional preceding minus sign '-' is allowed, to indicate a negative duration. If the sign is omitted a positive duration is indicated.

See also ISO Date and Time Formats §D. For example, to indicate a duration of 1 year, 2 months, 3 days, 10 hours, and 30 minutes, one would write: P1Y2M3DT10H30M. One could also indicate a duration of minus days as: -PD. Reduced precision and truncated representations of this format are allowed provided they conform to the following:. For example, PY, PM and P1Y2MT2H are all allowed; P0YM and P0YM0D are allowed.

PM is not allowed although -PM is allowed. P1Y2MT is not allowed. In general, the · order-relation · on duration is a partial order since there is no determinate relationship between certain durations such as one month P1M and 30 days P30D. These values for s cause the greatest deviations in the addition of dateTimes and durations. Addition of durations to time instants is defined in Adding durations to dateTimes §E. The following table shows the strongest relationship that can be determined between example durations.

Note that because of leap-seconds, a seconds field can vary from 59 to However, because of the way that addition is defined in Adding durations to dateTimes §E , they are still totally ordered. Implementations are free to optimize the computation of the ordering relationship.

For example, the following table can be used to compare durations of a small number of months against days. In comparing duration values with minInclusive , minExclusive , maxInclusive and maxExclusive facet values indeterminate comparisons should be considered as "false". Certain derived datatypes of durations can be guaranteed have a total order. For this, they must have fields from only one row in the list below and the time zone must either be required or prohibited.

For example, a datatype could be defined to correspond to the [SQL] datatype Year-Month interval that required a four digit year field and a two digit month field but required all other fields to be unspecified. This datatype could be defined as below and would have a total order.

duration has the following · constraining facets · :. Each such object also has one decimal-valued method or computed property, timeOnTimeline, whose value is always a decimal number; the values are dimensioned in seconds, the integer 0 is T and the value of timeOnTimeline for other dateTime values is computed using the Gregorian algorithm as modified for leap-seconds.

The timeOnTimeline values form two related "timelines", one for timezoned values and one for non-timezoned values. Each timeline is a copy of the · value space · of decimal , with integers given units of seconds.

The · value space · of dateTime is closely related to the dates and times described in ISO For clarity, the text above specifies a particular origin point for the timeline. It should be noted, however, that schema processors need not expose the timeOnTimeline value to schema users, and there is no requirement that a timeline-based implementation use the particular origin described here in its internal representation.

Other interpretations of the · value space · which lead to the same results i. All timezoned times are Coordinated Universal Time UTC, sometimes called "Greenwich Mean Time".

Other timezones indicated in lexical representations are converted to UTC during conversion of literals to values. The value of each numeric-valued property other than timeOnTimeline is limited to the maximum value within the interval determined by the next-higher property.

For example, the day value can never be 32, and cannot even be 29 for month 02 and year February The · lexical space · of dateTime consists of finite-length sequences of characters of the form: '-'? yyyy '-' mm '-' dd 'T' hh ':' mm ':' ss '. For example, T noon on 10 October , Central Daylight Savings Time as well as Eastern Standard Time in the U. is TZ, five hours later than TZ. For further guidance on arithmetic with dateTime s and durations, see Adding durations to dateTimes §E.

Except for trailing fractional zero digits in the seconds representation, '' time representations, and timezone for timezoned values , the mapping from literals to values is one-to-one. Where there is more than one possible representation, the canonical representation is as follows:. Timezones are durations with integer-valued hour and minute properties with the hour magnitude limited to at most 14, and the minute magnitude limited to at most 59, except that if the hour magnitude is 14, the minute value must be 0 ; they may be both positive or both negative.

When a timezone is added to a UTC dateTime , the result is the date and time "in that timezone". dateTime value objects on either timeline are totally ordered by their timeOnTimeline values; between the two timelines, dateTime value objects are ordered by their timeOnTimeline values when their timeOnTimeline values differ by more than fourteen hours, with those whose difference is a duration of 14 hours or less being · incomparable ·.

In general, the · order-relation · on dateTime is a partial order since there is no determinate relationship between certain instants. For example, there is no determinate ordering between a T and b T Z. It is, however, possible for this range to expand or contract in the future, based on local laws.

The following definition uses the notation S[year] to represent the year field of S, S[month] to represent the month field, and so on. This is a logical explanation of the process. Actual implementations are free to optimize as long as they produce the same results.

Normalize P and Q. That is, if there is a timezone present, but it is not Z, convert it to Z using the addition operation defined in Adding durations to dateTimes §E.

If P and Q either both have a time zone or both do not have a time zone, compare P and Q field by field from the year field down to the second field, and return a result as soon as it can be determined.

That is:. Certain derived types from dateTime can be guaranteed have a total order. To do so, they must require that a specific set of fields are always specified, and that remaining fields if any are always unspecified. For example, the date datatype without time zone is defined to contain exactly year, month, and day. Thus dates without time zone have a total order among themselves. dateTime has the following · constraining facets · :.

The · value space · of time is the space of time of day values as defined in § 5. Specifically, it is a set of zero-duration daily time instances. Since the lexical representation allows an optional time zone indicator, time values are partially ordered because it may not be able to determine the order of two values one of which has a time zone and the other does not.

The order relation on time values is the Order relation on dateTime §3. See also Adding durations to dateTimes §E. Pairs of time values with or without time zone indicators are totally ordered. The lexical representation for time is the left truncated lexical representation for dateTime : hh:mm:ss. sss with optional following time zone indicator.

For example, to indicate pm for Eastern Standard Time which is 5 hours behind Coordinated Universal Time UTC , one would write: The canonical representation for time is defined by prohibiting certain options from the Lexical representation §3. Specifically, either the time zone must be omitted or, if present, the time zone must be Coordinated Universal Time UTC indicated by a "Z".

Additionally, the canonical representation for midnight is time has the following · constraining facets · :. For nontimezoned values, the top-open intervals disjointly cover the nontimezoned timeline, one per day. For timezoned values, the intervals begin at every minute and therefore overlap. A "date object" is an object with year, month, and day properties just like those of dateTime objects, plus an optional timezone-valued timezone property.

As with values of dateTime timezones are a special case of durations. Just as a dateTime object corresponds to a point on one of the timelines, a date object corresponds to an interval on one of the two timelines as just described.

Timezoned date values track the starting moment of their day, as determined by their timezone; said timezone is generally recoverable for canonical representations. This "timezone normalization" which follows automatically from the definition of the date · value space · is explained more in Lexical representation §3. For the following discussion, let the "date portion" of a dateTime or date object be an object similar to a dateTime or date object, with similar year, month, and day properties, but no others, having the same value for these properties as the original dateTime or date object.

The · lexical space · of date consists of finite-length sequences of characters of the form: '-'? yyyy '-' mm '-' dd zzzzzz? where the date and optional timezone are represented exactly the same way as they are for dateTime. The first moment of the interval is that represented by: '-' yyyy '-' mm '-' dd 'T' zzzzzz? and the least upper bound of the interval is the timeline point represented noncanonically by: '-' yyyy '-' mm '-' dd 'T' zzzzzz? Given a member of the date · value space · , the date portion of the canonical representation the entire representation for nontimezoned values, and all but the timezone representation for timezoned values is always the date portion of the dateTime canonical representation of the interval midpoint the dateTime representation, truncated on the right to eliminate 'T' and all following characters.

For timezoned values, append the canonical representation of the · recoverable timezone ·. The · value space · of gYearMonth is the set of Gregorian calendar months as defined in § 5. Specifically, it is a set of one-month long, non-periodic instances e. Since the lexical representation allows an optional time zone indicator, gYearMonth values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gYearMonth values are considered as periods of time, the order relation on gYearMonth values is the order relation on their starting instants. This is discussed in Order relation on dateTime §3. Pairs of gYearMonth values with or without time zone indicators are totally ordered. The lexical representation for gYearMonth is the reduced right truncated lexical representation for dateTime : CCYY-MM.

No left truncation is allowed. An optional following time zone qualifier is allowed. To accommodate year values outside the range from to , additional digits can be added to the left of this representation and a preceding "-" sign is allowed.

For example, to indicate the month of May , one would write: gYearMonth has the following · constraining facets · :. The · value space · of gYear is the set of Gregorian calendar years as defined in § 5. Specifically, it is a set of one-year long, non-periodic instances e. lexical to represent the whole year , independent of how many months and days this year has. Since the lexical representation allows an optional time zone indicator, gYear values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gYear values are considered as periods of time, the order relation on gYear values is the order relation on their starting instants. Pairs of gYear values with or without time zone indicators are totally ordered.

The lexical representation for gYear is the reduced right truncated lexical representation for dateTime : CCYY. An optional following time zone qualifier is allowed as for dateTime. For example, to indicate , one would write: gYear has the following · constraining facets · :. Arbitrary recurring dates are not supported by this datatype. The · value space · of gMonthDay is the set of calendar dates , as defined in § 3 of [ISO ]. Specifically, it is a set of one-day long, annually periodic instances.

Since the lexical representation allows an optional time zone indicator, gMonthDay values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not. If gMonthDay values are considered as periods of time, in an arbitrary leap year, the order relation on gMonthDay values is the order relation on their starting instants.

Pairs of gMonthDay values with or without time zone indicators are totally ordered. The lexical representation for gMonthDay is the left truncated lexical representation for date : --MM-DD. An optional following time zone qualifier is allowed as for date. No preceding sign is allowed. No other formats are allowed.

This datatype can be used to represent a specific day in a month. To say, for example, that my birthday occurs on the 14th of September ever year. gMonthDay has the following · constraining facets · :. Arbitrary recurring days are not supported by this datatype. The · value space · of gDay is the space of a set of calendar dates as defined in § 3 of [ISO ].

Specifically, it is a set of one-day long, monthly periodic instances. This datatype can be used to represent a specific day of the month. To say, for example, that I get my paycheck on the 15th of each month. Since the lexical representation allows an optional time zone indicator, gDay values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not. If gDay values are considered as periods of time, in an arbitrary month that has 31 days, the order relation on gDay values is the order relation on their starting instants.

Pairs of gDay values with or without time zone indicators are totally ordered. The lexical representation for gDay is the left truncated lexical representation for date : DD.

gDay has the following · constraining facets · :. The · value space · of gMonth is the space of a set of calendar months as defined in § 3 of [ISO ]. Specifically, it is a set of one-month long, yearly periodic instances.

This datatype can be used to represent a specific month. To say, for example, that Thanksgiving falls in the month of November. Since the lexical representation allows an optional time zone indicator, gMonth values are partially ordered because it may not be possible to unequivocally determine the order of two values one of which has a time zone and the other does not.

If gMonth values are considered as periods of time, the order relation on gMonth is the order relation on their starting instants.

Pairs of gMonth values with or without time zone indicators are totally ordered. The lexical representation for gMonth is the left and right truncated lexical representation for date : --MM. gMonth has the following · constraining facets · :. The · value space · of hexBinary is the set of finite-length sequences of binary octets. hexBinary has a lexical representation where each binary octet is encoded as a character tuple, consisting of two hexadecimal digits [a-fA-F] representing the octet code.

For example, "0FB7" is a hex encoding for the bit integer whose binary representation is The canonical representation for hexBinary is defined by prohibiting certain options from the Lexical Representation §3. Specifically, the lower case hexadecimal digits [a-f] are not allowed.

hexBinary has the following · constraining facets · :. The · value space · of base64Binary is the set of finite-length sequences of binary octets. For base64Binary data the entire binary stream is encoded using the Base64 Alphabet in [RFC ]. The lexical forms of base64Binary values are limited to the 65 characters of the Base64 Alphabet defined in [RFC ] , i.

No other characters are allowed. For compatibility with older mail gateways, [RFC ] suggests that base64 data should have lines limited to at most 76 characters in length.

This line-length limitation is not mandated in the lexical forms of base64Binary data and must not be enforced by XML Schema processors. The lexical space of base64Binary is given by the following grammar the notation is that used in [XML 1. Note that this grammar requires the number of non-whitespace characters in the lexical form to be a multiple of four, and for equals signs to appear only at the end of the lexical form; strings which do not meet these constraints are not legal lexical forms of base64Binary because they cannot successfully be decoded by base64 decoders.

The canonical lexical form of a base64Binary data value is the base64 encoding of the value which matches the Canonical-base64Binary production in the following grammar:. The length of a base64Binary value is the number of octets it contains.

This may be calculated from the lexical form by removing whitespace and padding characters and performing the calculation shown in the pseudo-code below:.

Note on encoding: [RFC ] explicitly references US-ASCII encoding. However, decoding of base64Binary data in an XML entity is to be performed on the Unicode characters obtained after character encoding processing as specified by [XML 1.

base64Binary has the following · constraining facets · :. An anyURI value can be absolute or relative, and may have an optional fragment identifier i. This type should be used to specify the intention that the value fulfills the role of a URI as defined by [RFC ] , as amended by [RFC ]. The mapping from anyURI values to URIs is as defined by the URI reference escaping procedure defined in Section 5. This means that a wide range of internationalized resource identifiers can be specified when an anyURI is called for, and still be understood as URIs per [RFC ] , as amended by [RFC ] , where appropriate to identify resources.

The · lexical space · of anyURI is finite-length character sequences which, when the algorithm defined in Section 5. anyURI has the following · constraining facets · :. The · value space · of QName is the set of tuples { namespace name , local part }, where namespace name is an anyURI and local part is an NCName. The · lexical space · of QName is the set of strings that · match · the QName production of [Namespaces in XML]. QName has the following · constraining facets · :.

The use of · length · , · minLength · and · maxLength · on datatypes · derived · from QName is deprecated. Future versions of this specification may remove these facets for this datatype. The · value space · of NOTATION is the set of QName s of notations declared in the current schema. The · lexical space · of NOTATION is the set of all names of notations declared in the current schema in the form of QName s. For compatibility see Terminology §1.

NOTATION has the following · constraining facets · :. The use of · length · , · minLength · and · maxLength · on datatypes · derived · from NOTATION is deprecated. This section gives conceptual definitions for all · built-in · · derived · datatypes defined by this specification. The XML representation used to define · derived · datatypes whether · built-in · or · user-derived · is given in section XML Representation of Simple Type Definition Schema Components §4.

The · value space · of normalizedString is the set of strings that do not contain the carriage return xD , line feed xA nor tab x9 characters. The · lexical space · of normalizedString is the set of strings that do not contain the carriage return xD , line feed xA nor tab x9 characters. The · base type · of normalizedString is string.

normalizedString has the following · constraining facets · :. The following · built-in · datatypes are · derived · from normalizedString :. The · value space · of token is the set of strings that do not contain the carriage return xD , line feed xA nor tab x9 characters, that have no leading or trailing spaces x20 and that have no internal sequences of two or more spaces. The · lexical space · of token is the set of strings that do not contain the carriage return xD , line feed xA nor tab x9 characters, that have no leading or trailing spaces x20 and that have no internal sequences of two or more spaces.

The · base type · of token is normalizedString. token has the following · constraining facets · :. The following · built-in · datatypes are · derived · from token :. The · value space · of language is the set of all strings that are valid language identifiers as defined [RFC ]. The · base type · of language is token. language has the following · constraining facets · :. The · value space · of NMTOKEN is the set of tokens that · match · the Nmtoken production in [XML 1.

The · lexical space · of NMTOKEN is the set of strings that · match · the Nmtoken production in [XML 1. The · base type · of NMTOKEN is token. NMTOKEN has the following · constraining facets · :. The following · built-in · datatypes are · derived · from NMTOKEN :.

The · value space · of NMTOKENS is the set of finite, non-zero-length sequences of · NMTOKEN · s. The · lexical space · of NMTOKENS is the set of space-separated lists of tokens, of which each token is in the · lexical space · of NMTOKEN. The · itemType · of NMTOKENS is NMTOKEN. NMTOKENS has the following · constraining facets · :. The · value space · of Name is the set of all strings which · match · the Name production of [XML 1. The · lexical space · of Name is the set of all strings which · match · the Name production of [XML 1.

The · base type · of Name is token. Name has the following · constraining facets · :. The following · built-in · datatypes are · derived · from Name :. The · value space · of NCName is the set of all strings which · match · the NCName production of [Namespaces in XML]. The · lexical space · of NCName is the set of all strings which · match · the NCName production of [Namespaces in XML]. The · base type · of NCName is Name.

NCName has the following · constraining facets · :. The following · built-in · datatypes are · derived · from NCName :. The · value space · of ID is the set of all strings that · match · the NCName production in [Namespaces in XML]. The · lexical space · of ID is the set of all strings that · match · the NCName production in [Namespaces in XML].

The · base type · of ID is NCName. ID has the following · constraining facets · :. The · value space · of IDREF is the set of all strings that · match · the NCName production in [Namespaces in XML]. The · lexical space · of IDREF is the set of strings that · match · the NCName production in [Namespaces in XML]. The · base type · of IDREF is NCName. IDREF has the following · constraining facets · :.

The following · built-in · datatypes are · derived · from IDREF :. The · value space · of IDREFS is the set of finite, non-zero-length sequences of IDREF s. The · lexical space · of IDREFS is the set of space-separated lists of tokens, of which each token is in the · lexical space · of IDREF. The · itemType · of IDREFS is IDREF. IDREFS has the following · constraining facets · :.

The · value space · of ENTITY is the set of all strings that · match · the NCName production in [Namespaces in XML] and have been declared as an unparsed entity in a document type definition. The · lexical space · of ENTITY is the set of all strings that · match · the NCName production in [Namespaces in XML]. The · base type · of ENTITY is NCName.

ENTITY has the following · constraining facets · :. The following · built-in · datatypes are · derived · from ENTITY :. The · value space · of ENTITIES is the set of finite, non-zero-length sequences of · ENTITY · s that have been declared as unparsed entities in a document type definition. The · lexical space · of ENTITIES is the set of space-separated lists of tokens, of which each token is in the · lexical space · of ENTITY. The · itemType · of ENTITIES is ENTITY.

ENTITIES has the following · constraining facets · :. This results in the standard mathematical concept of the integer numbers. The · value space · of integer is the infinite set { The · base type · of integer is decimal. integer has a lexical representation consisting of a finite-length sequence of decimal digits x x39 with an optional leading sign. The canonical representation for integer is defined by prohibiting certain options from the Lexical representation §3.

integer has the following · constraining facets · :. The following · built-in · datatypes are · derived · from integer :. This results in the standard mathematical concept of the non-positive integers. The · value space · of nonPositiveInteger is the infinite set { The · base type · of nonPositiveInteger is integer. nonPositiveInteger has a lexical representation consisting of an optional preceding sign followed by a finite-length sequence of decimal digits x x For example: -1, 0, , The canonical representation for nonPositiveInteger is defined by prohibiting certain options from the Lexical representation §3.

In the canonical form for zero, the sign must be omitted. Leading zeroes are prohibited. nonPositiveInteger has the following · constraining facets · :. The following · built-in · datatypes are · derived · from nonPositiveInteger :.

This results in the standard mathematical concept of the negative integers. The · value space · of negativeInteger is the infinite set { The · base type · of negativeInteger is nonPositiveInteger.

negativeInteger has a lexical representation consisting of a negative sign "-" followed by a finite-length sequence of decimal digits x x For example: -1, , The canonical representation for negativeInteger is defined by prohibiting certain options from the Lexical representation §3.

Specifically, leading zeroes are prohibited. negativeInteger has the following · constraining facets · :. The · base type · of long is integer. long has a lexical representation consisting of an optional sign followed by a finite-length sequence of decimal digits x x The canonical representation for long is defined by prohibiting certain options from the Lexical representation §3.

long has the following · constraining facets · :. The following · built-in · datatypes are · derived · from long :. The · base type · of int is long. int has a lexical representation consisting of an optional sign followed by a finite-length sequence of decimal digits x x The canonical representation for int is defined by prohibiting certain options from the Lexical representation §3.

int has the following · constraining facets · :. The following · built-in · datatypes are · derived · from int :. The · base type · of short is int.

short has a lexical representation consisting of an optional sign followed by a finite-length sequence of decimal digits x x The canonical representation for short is defined by prohibiting certain options from the Lexical representation §3. short has the following · constraining facets · :. The following · built-in · datatypes are · derived · from short :. The · base type · of byte is short. byte has a lexical representation consisting of an optional sign followed by a finite-length sequence of decimal digits x x The canonical representation for byte is defined by prohibiting certain options from the Lexical representation §3.

byte has the following · constraining facets · :. This results in the standard mathematical concept of the non-negative integers. The · value space · of nonNegativeInteger is the infinite set {0,1,2, The · base type · of nonNegativeInteger is integer. nonNegativeInteger has a lexical representation consisting of an optional sign followed by a finite-length sequence of decimal digits x x The canonical representation for nonNegativeInteger is defined by prohibiting certain options from the Lexical representation §3.

nonNegativeInteger has the following · constraining facets · :. The following · built-in · datatypes are · derived · from nonNegativeInteger :. The · base type · of unsignedLong is nonNegativeInteger. unsignedLong has a lexical representation consisting of a finite-length sequence of decimal digits x x For example: 0, , The canonical representation for unsignedLong is defined by prohibiting certain options from the Lexical representation §3.

unsignedLong has the following · constraining facets · :. The following · built-in · datatypes are · derived · from unsignedLong :. The · base type · of unsignedInt is unsignedLong. unsignedInt has a lexical representation consisting of a finite-length sequence of decimal digits x x The canonical representation for unsignedInt is defined by prohibiting certain options from the Lexical representation §3. unsignedInt has the following · constraining facets · :.

The following · built-in · datatypes are · derived · from unsignedInt :. The · base type · of unsignedShort is unsignedInt. unsignedShort has a lexical representation consisting of a finite-length sequence of decimal digits x x The canonical representation for unsignedShort is defined by prohibiting certain options from the Lexical representation §3.

Specifically, the leading zeroes are prohibited. unsignedShort has the following · constraining facets · :.

Below is list of command-line options recognized by the ImageMagick command-line tools. If you want a description of a particular option, click on the option name in the navigation bar above and you will go right to it. Unless otherwise noted, each option is recognized by the commands: convert and mogrify. A Gaussian operator of the given radius and standard deviation sigma is used. If sigma is not given it defaults to 1. The sigma value is the important argument, and determines the actual amount of blurring that will take place.

The radius is only used to determine the size of the array which holds the calculated Gaussian distribution. It should be an integer. If not given, or set to zero, IM will calculate the largest possible radius that will provide meaningful results for the Gaussian distribution.

See Image Geometry for complete details about the geometry argument. The -adaptive-resize option defaults to data-dependent triangulation. Use the -filter to choose a different resampling algorithm. Offsets, if present in the geometry string, are ignored, and the -gravity option has no effect.

This option is enabled by default. An attempt is made to save all images of an image sequence into the given output file. However, some formats, such as JPEG and PNG, do not support more than one image per file, and in that case ImageMagick is forced to write each image as a separate file. As such, if more than one image needs to be written, the filename given is modified by adding a -scene number before the suffix, in order to make distinct names for each image.

As an example, the command. will create a sequence of 17 images the two given plus 15 more created by -morph , named: my00morph. jpg, my01morph. jpg, my02morph. In summary, ImageMagick tries to write all images to one file, but will save to multiple files, if any of the following conditions exist Set the drawing transformation matrix for combined rotating and scaling.

This option sets a transformation matrix, for use by subsequent -draw or -transform options. The matrix entries are entered as comma-separated numeric values either in quotes or without spaces. Internally, the transformation matrix has 3x3 elements, but three of them are omitted from the input because they are constant. The new transformed coordinates x' , y' of a pixel at position x , y in the original image are calculated using the following matrix equation. The size of the resulting image is that of the smallest rectangle that contains the transformed source image.

The parameters t x and t y subsequently shift the image pixels so that those that are moved out of the image area are cut off. The transformation matrix complies with the left-handed pixel coordinate system: positive x and y directions are rightward and downward, resp.

If the translation coefficients t x and t y are omitted they default to 0,0. Therefore, four parameters suffice for rotation and scaling without translation. Scaling by the factors s x and s y in the x and y directions, respectively, is accomplished with the following.

See -transform , and the -distort method ' Affineprojection for more information. Translation by a displacement t x , t y is accomplished like so:. The cumulative effect of a sequence of -affine transformations can be accomplished by instead by a single -affine operation using the matrix equal to the product of the matrices of the individual transformations. An attempt is made to detect near-singular transformation matrices.

If the matrix determinant has a sufficiently small absolute value it is rejected. Used to set a flag on an image indicating whether or not to use existing alpha channel data, to create an alpha channel, or to perform other operations on the alpha channel. Choose the argument type from the list below.

This is a convenience for annotating an image with text. For more precise control over text annotations, use -draw.

The values Xdegrees and Ydegrees control the shears applied to the text, while t x and t y are offsets that give the location of the text relative any -gravity setting and defaults to the upper left corner of the image. Using -annotate degrees or -annotate degrees x degrees produces an unsheared rotation of the text. The direction of the rotation is positive, which means a clockwise rotation if degrees is positive.

This conforms to the usual mathematical convention once it is realized that the positive y —direction is conventionally considered to be downward for images.

The new transformed coordinates x' , y' of a pixel at position x , y in the image are calculated using the following matrix equation. If t x and t y are omitted, they default to 0.

This makes the bottom-left of the text becomes the upper-left corner of the image, which is probably undesirable. Adding a -gravity option in this case leads to nice results. Text is any UTF-8 encoded character sequence. If text is of the form ' mytext.

txt', the text is read from the file mytext. Text in a file is taken literally; no embedded formatting characters are recognized. By default, objects e. text, lines, polygons, etc. are antialiased when drawn. This will then reduce the number of colors added to an image to just the colors being directly drawn. That is, no mixed colors are added when drawing such objects.

This option creates a single longer image, by joining all the current images in sequence top-to-bottom. If they are not of the same width, narrower images are padded with the current -background color setting, and their position relative to each other can be controlled by the current -gravity setting. For more flexible options, including the ability to add space between images, use -smush. Use this option to supply a password for decrypting a PDF that has been encrypted using Microsoft Crypto API MSC API.

The encrypting using the MSC API is not supported. For a different encryption method, see -encipher and -decipher. This works well for real-life images with little or no extreme dark and light areas, but tend to fail for images with large amounts of bright sky or dark shadows. It also does not work well for diagrams or cartoon like images.

It uses the -channel setting, including the ' sync ' flag for channel synchronization , to determine which color values is used and modified. As the default -channel setting is ' RGB,sync ', channels are modified together by the same gamma value, preserving colors.

This is a 'perfect' image normalization operator. It finds the exact minimum and maximum color values in the image and then applies a -level operator to stretch the values to the full range of values. On the other hand it is the right operator to use for color stretching gradient images being used to generate Color lookup tables, distortion maps, or other 'mathematically' defined images.

The operator is very similar to the -normalize , -contrast-stretch , and -linear-stretch operators, but without 'histogram binning' or 'clipping' problems that these operators may have. That is -auto-level is the perfect or ideal version these operators. It uses the -channel setting, including the special ' sync ' flag for channel synchronization , to determine which color values are used and modified.

Adjusts an image so that its orientation is suitable for viewing i. top-left orientation. This operator reads and resets the EXIF image profile setting 'Orientation' and then performs the appropriate 90 degree rotation on the image to orient the image, for correct viewing.

This EXIF profile setting is usually set using a gravity sensor in digital camera, however photos taken directly downward or upward may not have an appropriate value. Also images that have been orientation 'corrected' without reseting this setting, may be 'corrected' again resulting in a incorrect result.

If the EXIF profile was previously stripped, the -auto-orient operator will do nothing. The computed threshold is returned as the auto-threshold:verbose image property. This backdrop covers the entire workstation screen and is useful for hiding other X window activity while viewing the image.

The color of the backdrop is specified as the background color. The color is specified using the format described under the -fill option. The default background color if none is specified or found in the image is white. Repeat the entire command for the given number of iterations and report the user-time and elapsed time. For instance, consider the following command and its output. Modify the benchmark with the -duration to run the benchmark for a fixed number of seconds and -concurrent to run the benchmark in parallel requires the OpenMP feature.

In this example, 5 iterations were completed at 2. This option shifts the output of -convolve so that positive and negative results are relative to the specified bias value. This is important for non-HDRI compilations of ImageMagick when dealing with convolutions that contain negative as well as positive values. This is especially the case with convolutions involving high pass filters or edge detection. Without an output bias, the negative values are clipped at zero.

See the discussion on HDRI implementations of ImageMagick on the page High Dynamic-Range Images. For more about HDRI go the ImageMagick Usage pages or this Wikipedia entry. A non-linear, edge-preserving, and noise-reducing smoothing filter for images.

It replaces the intensity of each pixel with a weighted average of intensity values from nearby pixels. This weight is based on a Gaussian distribution.

This section specifies functions and operators on the [XML Schema Part 2: Datatypes Second Edition] xs:string datatype and the datatypes derived from it. As such some colors may be merged together when they originally fell into the same 'bin'. 爆款少儿青少年scratch编程第1课：四合一游戏机（上） 可以直接运行。A53课程制作 爆款爆款少儿青少年scratch编程是包括教程制作完整课程，里面包括教学步骤，教学视频，教学素材，教学课件pdf，教学课件word，课程源码。课程内容大致如下所示：资源:. As it involves only a single pixel, a point primitive is not affected by -stroke or -strokewidth. Every node has a string value, even an element with element-only content which has no typed value.

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