CN1795429A - Batch-based method and tool for graphical manipulation of workflows - Google Patents
Batch-based method and tool for graphical manipulation of workflows Download PDFInfo
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Abstract
An autofill algorithm provides tools for defining and automatically executing batch based procedures in an adaptive hierarchical workflow environment, and may be suitable for a large variety of applications including laboratory procedure planning, execution, documentation, as wells as driving robotic apparatus.
Description
Technical field
The present invention relates generally to research, exploitation, and the workflow in making are specifically related to be used for robotization and carry out and write down research, the instrument of exploitation and manufacturing activities.
Background technology
A lot of researchists adopt the laboratory notebooks of the Microsoft of Redmond Washington, automatic blank form (spreadsheet) software such as Excel , as be used for carrying out and/or record research the automaticdata bag of exploitation.
In the design of laboratory procedure, be necessary to utilize regularity based on batch processing.The designer can be enough batch operation replace single operation and generating routine allows them to mean the existence of (imply) important fine-grain structure (fine-grained structure).Key based on the batch program design is to limit simple rule, and it is used for obtaining the particulate topological structure from the program (batch level procedure) of the batch processing level that is produced by the user.For the user, this rule, or algorithm can be also measurable by understanding, and provide the ability that produces useful in a large number particulate topological structure for them.
Summary of the invention
The present invention has disclosed and has been used in adaptive hierarchical workflow (adaptive hierarchicalworkflow) environment definition and carries out instrument based on the program of batch processing.Such instrument is suitable for the extensive application program, and these application programs comprise laboratory procedure planning (planning), carries out record, and drive machines people equipment.
Description of drawings
In the accompanying drawing, identical identification number sign analogous element or action.The size of element and relative position needn't draw in proportion in the accompanying drawing.For example, the shape and the angle of different elements are not drawn in proportion, and some element is amplification arbitrarily and locatees to improve the legibility of accompanying drawing.Further, shown in the concrete shape of element be not in order to pass on information about the element-specific true form, and discern accompanying drawing and unique selection in order to be easy to.
Figure 1A is the theory diagram according to the computer system of at least one illustrated embodiment, and this computer system is suitable for operating the adaptive hierarchical workflow tool.
Figure 1B is the synoptic diagram of example flow diagram, and it is used for according to the exemplary process of at least one illustrated embodiment with adaptability workflow model representation.
Fig. 1 C is the synoptic diagram according to a plurality of single node of an illustrated embodiment and border element (edgeelements) and correlation properties, wherein each global unique identification symbol (identifier) and each elements correlation.
Fig. 1 D is according to a plurality of single node of an illustrated embodiment and the synoptic diagram of border element and correlation properties, wherein title respectively technology resolve global not exclusive title with elements correlation uniquely.
Fig. 1 E is the screenshot capture according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it is how related with the sample workflow procedure with value that it illustrates characteristic.
Fig. 1 F is the screenshot capture of the user interface of Fig. 1 E, and it further illustrates name and the searching algorithm that desired value can use here to be instructed and calculates.
Fig. 2 A is a synoptic diagram of representing handle icon in the self-adaptation workflow model according at least one illustrated embodiment.
Fig. 2 B is the synoptic diagram according to batch processing icon in the self-adaptation workflow model of at least one illustrated embodiment.
Fig. 2 C is the synoptic diagram of expression workflow model or program icon.
Fig. 3 is that this exemplary process is by self-adaptation workflow model representation according to the synoptic diagram of the sample process flow diagram that is used for exemplary process of at least one illustrated embodiment.
Fig. 4 is the screenshot capture according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates the characteristic related with the sample batch processing.
Fig. 5 is the sectional drawing according to the user interface of the self-adaptation workflow of at least one illustrated embodiment, the coordinate system that the batch processing of its illustrated example is relevant with this batch processing.
Fig. 6 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates the element of exemplary batch processing and related this batch processing.
Fig. 7 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates exemplary experiment chamber program.
Fig. 8 A is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it is illustrated in the exemplary template before the automatic filling algorithm of operation.
Fig. 8 B is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates exemplary expression formula and how to be used for from the row axle precision of row axle precision (row axis) the derivation dial (plate) of reagent (Reagents).
Fig. 9 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it is illustrated in the exemplary template of operation behind filling algorithm.
Figure 10 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and its exemplary template that interleaving function (cross function) is shown is installed.
Figure 11 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it is illustrated in the exemplary template behind the execution interleaving function.
Figure 12 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and its exemplary template that joint dysfunction (pooling function) is shown is installed.
Figure 13 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it is illustrated in the example behind the execution joint dysfunction.
Figure 14 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates the exemplary template that shows selection function.
Figure 15 is the sectional drawing according to the user interface of the self-adaptation workflow tool of at least one illustrated embodiment, and its exemplary template that transposition function (transpose function) is shown is installed.
Figure 16 is according at least one illustrated embodiment, be used to use the synoptic diagram of self-adaptation workflow model as the sample process flow diagram of the exemplary process of hyperspace complex combination program calculating generation model, this self-adaptation workflow model moves between sample and distribution (dispense) operation and connects.
Figure 17 is the synoptic diagram according to the sample process flow diagram that is used for exemplary process of at least one illustrated embodiment, and this exemplary process is by self-adaptation workflow model representation, and it is similar to the self-adaptation workflow model among Figure 16, yet does not have moving of connection.
Figure 18 is the synoptic diagram that is used for the sample process flow diagram of exemplary process according at least one illustrated embodiment, this exemplary process is by self-adaptation workflow model representation, this self-adaptation workflow model adopts matched rule to transplant primary sample collection and prevent to duplicate pairing simultaneously, produces necessary lower triangular matrix or upper triangular matrix.
Figure 19 is the example view that is used for the process flow diagram of exemplary process sample according to an illustrated embodiment, and this exemplary process connects batch processing X and batch processing Y.
Figure 20 is the example view that is used for the process flow diagram of exemplary process sample according to an illustrated embodiment, this exemplary process illustrates by adding the deletion action of carrying out at disconnected (NoConnect) edge so that revise batch processing X and batch processing Y operation among Figure 19, connection batch processing X and batch processing Y.
Figure 21 is the example view that is used for the process flow diagram of exemplary process sample according to an illustrated embodiment, this exemplary process illustrates the interpolation that manually connects between a pair of element, the icon representation during this is operated by batch processing X shown in Figure 19 and batch processing Y element.
Embodiment
In the following description, provided some detail so that thorough to different embodiments of the invention is provided.Yet, it will be appreciated by those skilled in the art that the present invention can implement without these details.In other example, and be not shown specifically or describe based on the relevant known structure of the program design of batch processing to avoid the explanation of the unnecessary fuzzy embodiment of the invention.
Unless the other requirement of this paper, otherwise in whole instructions and the claim, speech " comprise " and change, as " comprising " and " by ... form " comprise meaning interpretation with opening, as " including, but are not limited to ".
" embodiment " who mentions in the whole instructions or " embodiment " mean the concrete feature of describing in conjunction with the embodiments, and structure or feature are included among at least one embodiment of the present invention.Therefore, different local phrase " in one embodiment " or " in an embodiment " that occur needn't all refer to identical embodiment in the whole instructions.And, concrete feature, structure, or characteristics can be combined among one or more embodiment by any suitable method.
Title provided herein is only in order to explain desired category of the present invention or meaning respectively and not.
Figure 1A and following discussion provide suitable computing environment succinct, the explanation of summary, and the present invention can implement in these suitable computing environment.Though do not require, the embodiment among the present invention will be at computer executable instructions, as the program application module of carrying out by personal computer, and object, or illustrate in the grand general content.It will be appreciated by those skilled in the art that the present invention can use other computer system configurations, comprise hand-held device, the multi-processor system, based on microprocessor or programmable consumer electronics device, network computer, mini-computer, principal computer, or the like carry out.The present invention can carry out in distributed computing environment, and task or module are carried out by the teleprocessing device in this distributed computing environment, and these teleprocessing devices connect by communication network.In distributed computing environment, program module can be arranged in local and remote storage arrangement.
With reference to Figure 1A, the conventional personal computer of mentioning as computing system 10 comprises processor unit 12 here, and system storage 14 and system bus 16, system bus 16 will comprise that system storage 14 different system elements are connected to processing unit 12.Processing unit 12 can be any Logical processing unit, as one or more CPU (central processing unit) (CPUs), or the like.Unless otherwise indicated, the structure of the different masses shown in Figure 1A and operation have traditional design.As a result of, such piece needn't further here describe in detail, because they can be understood by those skilled in the art.
Program module can be stored in this system storage 14, as operating system 34, and one or more application programs 36, other program or module 38 and routine data 40.System storage 14 also comprises browser 41, its be used to allow computing system 10 accesses and with for example internet website, corporate lan, or the Resource Exchange data of other server application on other network and the server computer.Browser 41 is based on SGML, as HTML (Hypertext Markup Language) (" HTML "), and with the SGML operation, this SGML use add to file data according to the sentence structure delimiting character with the expression file structure.
Though conduct is stored in shown in the system storage in Figure 1A, operating system 34, application program 36, other program module 38, routine data 40 and browser 41 can be stored in the hard disk 25 of hard disk drive 24, on the CD 30 of CD drive 26 and/or the disk 32 of disc driver 28.The user can by input media such as keyboard 42 and indicator device such as mouse 44 will be ordered and information is input to computing system 10.Other input media can comprise microphone, operating rod, cribbage-board (game pad) scanner or the like.These and other input media is connected to processing unit 12 through interface 46 as serial port interface, and serial port interface is coupled to bus 16, though other interface such as parallel port, game port or USB (universal serial bus) (" USB ") also can be used.Monitor 48 or other display device can be coupled to bus 16 as video adapter through video interface 50.Computing system 10 can comprise other output unit such as loudspeaker, printer or the like.
In the time of in being used in the lan network environment, computing system 10 is connected to LAN 52 through adapter or network interface 56 (communicating to connect bus 16).In the time of in being used in the WAN network environment, computing system 10 generally includes modulator-demodular unit 57 or other is used for setting up communicating devices on WAN/ the Internet 54.Modulator-demodular unit 57 is shown among Figure 1A, so that communicate to connect at interface 46 and 54 of WAN/ the Internets.In network environment, program module, application program, or data, or part wherein can be stored in the server computer (not shown).Those skilled in the art are easy to recognize that it only is the several examples that establish a communications link that the network among Figure 1A connects between computing machine and/or robot system 60, other connection comprises that wireless connections also can use.
Terminology used here " computer-readable medium " can refer to any medium, and its participation provides instruction for execution to processor unit 12.Such medium can be taked many forms, includes but not limited to non-volatile media, Volatile media, and transmission medium.Non-volatile media comprises, for example, and hard disk, spectrum or disk 25,30,32.Volatile media comprises dynamic storage, as system storage 14.Transmission medium comprises coaxial cable, and copper conductor and fiber optics comprise lead, and this lead comprises system bus 16.Transmission medium also can adopt the form of sound wave or light wave, as the ripple that generates during radiowave and infrared data communication.
The computer-readable medium of common form comprises, for example, and floppy disk, flexible disk, hard disk, tape, or any other magnetic medium, CD-ROM, any other optical medium, punched card, paper tape, any other has the physical medium of sectional hole patterns, RAM, PROM, and EPROM, FLASH-EPROM, any other memory chip or cassette tape, carrier wave as described below, or any other computer-readable medium.
Carrying out one or more one or more sequences of processor unit instruction of issuing so that in carrying out, may relate to multi-form computer-readable medium.For example, can original execution instruction on the disk of remote computer.But the remote computer load instructions sends instruction to its dynamic storage and with modulator-demodular unit by telephone wire.Modulator-demodular unit 57 in computer system 10 parts can receive data and use infrared transmitter so that data are converted to infrared signal on telephone wire.The infrared eye that is coupled to system bus 16 can receive data that infrared signal carries and with data load to system bus 16.System bus 16 carries data to system storage 14, and processor unit 12 recovers from it and executes instruction.The instruction that is received by system storage 14 can be selected in processor unit 12 and be stored on the memory storage before or after carrying out.
Problem-instance
Figure 1B illustrates in the biology laboratory the one group of simple classification workflow diagram 62 that will be executed the task by personnel or robot device.This workflow Figure 62 is classification, and " " 63 node comprises other four nodes to workflow, indicates " sample " 64 respectively, " reagent " 65, " distribution " 66 and " combination " 67 because indicate.(containership) contained in 68 indications of bright rays arrow, and solid arrow 69 indication workflow sequence.
In this example, the target of workflow 63 be with biological sample and some agent combination to reach 50 required ml volumes, wherein cell count is 500 ten thousand.More importantly, the volume of required sample and reagent must calculate based on the quantity (cell density) of the cell and the volume of primary sample.For example, the volume of the primary sample that must distribute is that required counting (5M) multiply by sample volume to sample tale ratio: (volume * tale/required counting).Deduct this volume need to determine how much reagent from volume required (50mL) then.This formula is very similar to the formula type of finding in blank form, but unfortunate, and the no form structure of process flow diagram does not allow the mode of row and column position as reference to variable.
What disclose is that classification name and searching algorithm produce structure to allow the user according to node and characteristic title herein.Use this method, explain in detail that below top formula can be expressed as:
Dispensed volume=(combinatorial enumeration/sample counting) * sample volume
Reagent volume=combined volume-dispensed volume
Problem definition
Given total graph structure (general graph structure) G (E, N), wherein among the figure node and edge available characteristic (field (key): it is right to be worth, as volume: 50mL or counting: 10M), many application programs are arranged, and wherein the best properties value uses the mathematical formulae as adopting in the blank form system to calculate by other characteristic value.
Figure 1B illustrates a solution, and it supposes each node or edge 70a, and 70b has overall unique id (GUID).By this supposition, other characteristic value can be used the GUID.KEY expression formula, refers in the formula as " G1.X ".The sample formula that uses this expression formula can be G1.X+1, and it will be assigned 11, shown in Fig. 1 C.
It is simple and in the value of this node seek characteristic X that this assignment method is searched for the node of its GUID coupling " G1 ".This method is totally independent of rank work so that it can be used for the edge across the rank border.Yet it is right that this method also requires in all formula all variablees to be expressed as GUID.KEY, and they can not be (compact) that compact or human-readable.Practical (real-world) GUIDs is at least 128 string of encryption machine generation normally, and they may increase in time.Human-readable GUIDs is extremely long, makes that the formula of these identifiers of use is not readable.
Name resolution method
Solution is to allow node and edge to have the NAME characteristic, and these characteristics are weak point, human-readable and at user option, but they need not to be unique.The main difference of this method and said method is that NAMEs does not suppose it is unique.As a result of, the name resolving searching algorithm must be used, and its behavior is predictable to the user, and it allows to use simple name in most cases.
The characteristic value identifier is expressed as by the sequence of some separator as the identifier of ". " separation in the formula.Last term is that all aforementioned items are nodenames in characteristics field and the sequence in this sequence.The sequence that algorithm given below has defined nodename is the actual node that how to be mapped in the classification graph structure.The search order of this algorithm can be expressed as " self level " roughly, and its back is " sub level ", and " sub level " back is " female level ".This algorithm at first use-case subsolution is released, and explains with formal definition then.
Example
Fig. 1 D illustrates the example that adopts node 71a-71e, and it illustrates characteristic value and how to be cited in the node hierarchy system.For illustrative purposes, each node has the NAME characteristic, and it needs not to be unique, and all nodes have characteristic in this example, and the field of this characteristic is X.And, node 71a is arranged, its NAME characteristic is " top ", and comprises all other nodes (each rank).
We define initial (originating) node is that the characteristic that comprises this formula is attached to the node on it.In the drawings, start node is 71b, and it has NAME and Y and X characteristic.Be used for some example of formula of Y value and they and be the as described below of assignment how:
The Y:=X assignment is 1, because only the identifier of an item is taken as field, and the characteristic of its matching initial node (self level).
Y:=A.X also assignment is 1, because the title of start node is A and at first search of its quilt (self level).
Y:=A.A.X is assigned 100, because the title of first title " A " matching initial node (self level) in the identifier, and the title of the 2nd NAME " A " matching initial node elements.Notice that start node is at first searched for, and causes the coupling of success.
Y:=TOP.A.A.X also assignment is 100." top " do not match start node title (self level) and its any member (sub level, title child), or their member, so searching algorithm by whole identifier reach start node tundish vessel (container) (female grade, parent).Because toply mate on this level, according to same algorithm, for the remaining member of identifier " A.A.X ", all top members are searched for once more.It is by assignment 100, as mentioned above.
Y:=B.X assignment 1000 is because it is in self level and the inefficacy of sub level place.
Y:=B.A.X assignment 10 is because same reason.
Y:=TOP.A.X is uncertain, assignment 1 or 10000.Actual result be specific execution but not limit by this instructions.
Formal definition
The formal pseudo-code definition of searching algorithm is following recursive definition:
Definition
1. given identifier V as a token of accord with [10 ...., ln] ordered set.
2. if n＞0 and null value Pre (V) assignment are 10.
3.Rem (V) assignment be [11 ..., ln]
4.Key (V) assignment is ln.
Algorithm
match(node，V，src)return a value of the desire property{ if(node＝＝src)return null(base case to prevent infinite loop) if(pre(V)＝＝null)//reference is just a key if (hasProperty(node，key(V))) return getPropertyValue(node，key(V)) if(pre(V)＝＝getPropertyValue(node，NAME)){ //search children with remainder of V for each child of node{ result＝match(child，rem(V)，src) if(result！＝null)return result } }else{//reference does not match this node //search children with all of V for each child of node{ if(child！＝src)result＝match(child，V，src) if(result！＝null)return result } <!-- SIPO <DP n="11"> --> <dp n="d11"/> } //search container with all of V return match(getParent(node)，V，src) }
The permission identifier string is embedded into other identifier string by using bracket or other morphology convention, thereby supports that directly address is useful and strong, as in the following example:
Identifier " n1.n2.n3.[n1.key1] .n4.key2 " be all assignment to be resolved by resolving nested expression formula with the reverse degree of depth first order at start node.Therefore, if match (node, " n1.key1 ") assignment " x ", match () will call behind the identifier that substitutes with " x " in the bracket once more so, as such at match (node, " n1.n2.n3.x.n4.key2 ").
The special application of this technology is to allow the order rank set member's of use node index (index) to quote the member of similar indexing in another level set, as at " n1.n2.[INDEX]+n1.n3[INDEX ", wherein INDEX is the characteristics field of start node, its position in ordered set of this fields specify.Except this example, this method also has several other general application, and this method is supported any level of identifier string indirect.
The edge
The searching algorithm of local edge and node identical, except the pardon relation is defined as the minimum public tundish vessel of two nodes, this edge is connected on these two nodes.Suppose that E is the edge, it is connected to node N1 and N2.As an example, if N1 is included among the N3, and N3 is included among the N4, and N2 directly comprises by N4, and E is directly comprised by N4 so, as the minimum public tundish vessel of E node.The edge does not have the member, so searching algorithm is female rank from self then.Above-mentioned algorithm is applied directly to the edge.
Application example
In Fig. 1 E, be shown in the table 72 on the right with the related characteristic of each node 63-67 among workflow Figure 62, as they appearance before input Sample.Count value." reagent " node has bulk properties, and its value is the formula of expressing according to " Combine.Volume " and " Dispense.Volume ".Wherein " Dispense.Volume " expresses according to " Sample.Count " and " Combine.Count ".Attention is according to this algorithm, and expression formula " Combine.Count " can substitute onto in " Workflow.Combine.Volume ".
Fig. 1 F illustrates how to use above-mentioned name and searching algorithm, and required volume can calculate in Sample.Count value input back in this system, shown in the table 72 that upgrades.
A kind ofly be used to implement mode of the present invention as being stored in the software instruction on the computer-readable medium, it makes computing system carry out above-mentioned algorithm and it can represent the classification graph structure, and wherein node and edge are to explain with characteristic (key.value to).
Fig. 2 A illustrates the icon of operating in the expression self-adaptation workflow tool environment 100.The operation expression is to the action of data or material execution.Input and output are represented that by arc these arcs finish (input) and initialization (output) when operation.Particularly, the icon 100 among Fig. 2 A illustrates expression " combination " operation.
Tundish vessel is the set of operation and other tundish vessel, allows the rank of any level.Two class tundish vessels are arranged, or 1) batch processing or 2) program.Only the subclass of tundish vessel has figure (that is icon) expression.Define two examples below.
Fig. 2 B illustrates icon 102, the batch processing in its expression self-adaptation workflow tool environment.Batch processing is the subclass of tundish vessel, and wherein all members are according to the coordinate system tissue related with batch processing.The size and the dimension of the coordinate system of icon 102 upper left text representation batch processings.Particularly, icon 102 illustrates the one dimension batch processing of three single combination operations among Fig. 2 B.
Fig. 2 C illustrates the icon 102 of program in the expression self-adaptation workflow tool environment.This program is the subclass of tundish vessel, the sequence of operation that its established part is orderly, and it can comprise subroutine and batch processing, for example as shown in following sample flow journey figure (SFG).
Fig. 3 illustrates sample process flow diagram (SFG) 106.SFG is classification sensing figure, its representation program.Node is represented operation or tundish vessel among the SFG.Two types arc is arranged, and it can attended operation and tundish vessel: a) material stream arc 108 (white), and it is from the operation beginning and at EO; Template arc 110 (yellow), it begins and finishes at tundish vessel at tundish vessel.Empty arrow 112 indication " containing " relations.Each green bar 114 that indicates " combination " is diagrammatic representations of single combination operation, and it is the batch processing member who indicates the combination operation of " combination " 102.Their positions (referring to following index) in batch processing of numeral in the single combination operation
Fig. 4 is the sectional drawing according to the user interface 120 of the self-adaptation workflow tool of at least one illustrated embodiment, and it illustrates the characteristic related with the sample batch processing.User interface 120 comprises that a plurality of users can select icon, menu, and palette, button, and/or dialog box to be allowing the user and produce and to revise template, otherwise operation element flow process instrument.Particularly, user interface 120 comprises one or more tool bars 122, and 124 horizontal edge extends along the workspace for it, and has a plurality of users that are used to handle the workflow many aspects of qualification can select icon, as being represented by SFG106.User interface 120 also comprises second tool bar 126, and 124 vertical edge extends along the workspace for it, has a plurality of being used for to produce and limit operation, and the user of batch processing and program can select icon.User interface 120 also comprises a plurality of the text fields 128 with the indication batch processing, some feature of program and/or operation and a plurality ofly be used to indicate batch processing, the check box 130 that some attribute of program and/or operation is provided with.The user can select different user can select icon limiting the workflow module by 106 expressions of SFG in the template, this template by diagrammatic representation in workspace 124.
Fig. 5 illustrate with Fig. 4 in the related characteristic of exemplary sample batch processing.Characteristic is that field-value is right, and it is related with node and arc among the SFG 106.Characteristic is used for the regulation parameter, and this parameter is suitable for the operation and the tundish vessel of each type.This value can be any data type.In this example, the sample batch processing comprises first characteristic, and its value of having is " normally ", and the field " situation " of " cancer " and " diabetes " has value and is " lung ", " liver ", second characteristic of the field of " blood " " tissue ".It should be appreciated by those skilled in the art that this only is the example of batch processing and characteristic, can define the batch processing of the different situations of larger amt or lesser amt.
Attribute is that field-value is right, and its intermediate value is the true or false value always.Attribute and association of characteristics, however characteristic is only related with operation and tundish vessel.The sample attribute that is used for characteristic " title " is shown in Fig. 4 as " necessary " and " visible ".
Fig. 6 illustrates exemplary batch processing 102 and its coordinate system.Batch processing has " coordinate system ", and it is defined by axle descriptor characteristic.The limited discrete domain of axle descriptor properties specify (integer sequence, string, or any other data type).The coordinate system of batch processing can have a plurality of axle, these must have fixed default order (as, axle 1, axle 2, axle 3; Row, OK, dial (Plates); X, Y, Z, etc.).In the example of Fig. 6, one 3 * 3 bidimensional batch processing is stipulated in batch processing 102 on row and row.Simultaneously, their stipulate one 3 * 3 bidimensional coordinate system.Particularly, for example batch processing shown in Fig. 6 102 " sample ", coordinate system has bidimensional: type of animal and types of organization.Each member of batch processing 102 has the index characteristic, its position in the batch processing coordinate system of this index properties specify.
The member of batch processing is the tundish vessel in operation or the batch processing.All members must have " index " characteristic, member's position in its regulation batch processing coordinate system.
Index is batch processing member's a characteristic, and this batch processing member is defined in the member position in the batch processing.The index characteristic is the vector of batch processing coordinate system, so its each axle has digital clauses and subclauses.Here Jiao Dao AutoFill algorithm does not require that all batch processings have identical dimension (dimensionality), but it requires all batch processings to accept default axle ordering so that the index in the different coordinate system can compare.As a result of, the index characteristic can have " sky " clauses and subclauses of the vector representation that is used for axle, and these axles are not included in their batch processing coordinate systems.Following Example is exemplary:
Make X, Y, Z are the orderings that is used for all batch processing axles.
Making A is the one dimension batch processing that only limits on X-axis.
Making B is the one dimension batch processing that only limits on Y-axis.
Making operation L is the member of A.Therefore L must have index characteristic (vector), and it is defined in X but not on Y and the Z axle.This can be expressed as " 1,, ".
Making operation M is the member of B.Therefore M must have index characteristic (vector), and it is defined in Y but not on X and the Z axle.This can be expressed as ", 1, ".
By convention, the comma of magnetic tape trailer crust be omitted in case orderly coordinate system can have uncertain quantity axle (as axle 1, axle 2, spools 3 ..., axle N) and do not require endless index vector.Therefore the index of L is " 1 ", and the index of M be ", 1. ".In a word, if, be empty at the relevant position index not for batch processing definition axle.For the AutoFill algorithm definition that defines below, this definition is important.
Problem-instance
Fig. 7 illustrates the pattern layout for simple experiment chamber program 130, and this laboratory procedure is carried out the sample set of icon 132 expressions.Each sample will with the single agent combination by icon 136 expression, this combination is by icon 134 expressions, ageing then, this ageing is selected by icon 138 expressions, this is selected by icon 140 expressions, and measures, this is measured by icon 142 expressions.The sequence of operation is basic identical, and this sequence of operation is carried out each sample and be basic identical, and for each sample, some parameter is only by minor variations.Therefore, it is favourable allowing the user only once to draft sequence with " batch processing " operated, and input parameter only then is by opening batch processing or in table view, these parameters change one by one.
Large icons 132,134,136,138,140,142 and arrow 144a-144e (yellow) batch processing configuration that is produced by the user is shown.After stipulating that each batch processing is of a size of 3, system is created automatically by small icon 146a, a-146e, c (green) and arrow 148a, a-148e, the fine-grain structure of c (white) expression.Notice that reagent icon 136 is not batch processing.As a result of, reagent icon 136 is connected to each in three " combination " operation, and these " combinations " operation is included in " combination " batch processing of operation.
Fig. 8 A and 8B illustrate the template of being created by the user before operation AutoFill algorithm.Particularly, Fig. 8 A illustrates one dimension batch processing how to want the regulation sample and should be assigned in the two-dimensional array (or dial), so that each sample is assigned in the full line.Fig. 8 B illustrates expression formula and how to be used for from the row axle precision of the row axle precision derivation dial of reagent.Because the row axle is not reagent batch processing definition, so for row 1 and 2, row a, b and c should be connected to row a in the dial, b, and c.Its target is to allow the user to connect and coordinate system on the batch processing level in the mode that the permission system generates correct particulate graph structure.This can adopt and be used to finish or " filling " fine-grain structure, is called " AutoFill " algorithm here.
Fig. 8 A and 9 is illustrated in respectively and carries out before the AutoFill algorithm and the appearance of model afterwards.At next joint, we provide the details of AutoFill algorithm, and it allows the user easily to stipulate multiple useful topological structure.
Particularly, Fig. 9 illustrates the workflow module, as the SFG 106 that obtains from operation AutoFill algorithm.The reagent batch processing is by icon 160 expressions, and batch operation is by icon 162 operations.Vertical bar 164
a-164
bWith 166
1, a-166
2, cBe the batch processing member, and arrow 168 (white) is a material stream arc, they are generated by the AutoFill algorithm.SFG 106 indicators, a is assigned to 1 of dial, and a and 2 is among a.Arrow 170 (empty) the indication containment relationship.
The AutoFill algorithm
Following algorithm generates the graph structure shown in Fig. 9 from the template that the user shown in Fig. 8 A provides:
For?All?nodes?F?and?G?in?the?SFG，such?that：
F?is?a?node?in?Batch?A；and
G?is?a?node?in?Batch?B；and
F！＝G；and
There?exists?a?template?edge?from?A?to?B
Create?a?new?edge?from?F?to?G?if?and?only?if
For?all?i，
F.Index.e
i＝G.Index.e
i“Entry?i?of?F’s?Index＝Entry?i?of?G’s
Index”；or
F.Index.e
i?is?empty；or
G.Index.e
i?is?empty
In other words, the member of the batch processing that algorithm connects, the batch processing of these connections is in each index position coupling, and empty position mates any clauses and subclauses or other sky clauses and subclauses here.This algorithm also works for the operation that is not included in the batch processing, but these algorithms are connected to batch processing by the edge.Because such operation does not have the index characteristic, so all index characteristics of the batch processing member that their couplings connect.This is useful for each member who single operation is connected to batch processing.
Should be simple, general-purpose algorithm can be used for generating many useful graph structures automatically, is assigned to row as reagent, row, or each well (well) of dial; The associating (pooling) (Figure 12 and 13) of the sample of row and column is striden in the generation (Figure 10 and 11) of " the intersection product " of two one dimension batch processings, from the batch processing of operation, selects, and transposition (transposition).
The AutoFill example
How Figure 10-15 and following interpretation describe multiple useful topological structure on the batch processing level, so correct fine-grain structure will be generated by the AutoFill algorithm.This example comprises:
Intersect: create the complete set that between two one dimension batch processing members mode (pair-wise) is concerned.
Associating: by making up the dimension (dimensionality) that all samples reduces batch processing, these samples are striden and are united the dimension coupling.An example will make up all types of organizations for each type of animal in the 2D batch processing among Fig. 6.This will cause eliminating the 1D batch processing of types of organization's dimension.
Select: only allow the part batch processing to be used in the later step of program by the subclass that matches original batch processing coordinate system.
Transposition (transpose): when the AutoFill algorithm moves, the order of the coordinate system by changing batch processing, row can make it possible to create multiple useful experiment structure by transposition for row.Example be single batch processing can with himself intersect to produce all possible combination in the set sample.
Intersect
Figure 10 and 11 illustrates how how to set up " intersection " experiment and " intersections " result of experiment, should " intersections " tests and makes up each medicine in each sample and the dial.Particularly, Figure 10 illustrates the foundation of intersection.As shown in figure 10, arrange as one-dimensional along the row axle by the sample of icon 200 expressions; Following axle by the sample of icon 202 expression arranges as one-dimensional; Dial is restricted to bidimensional, and its row is limited by the medicine batch processing, and its row are limited by the sample batch processing.The AutoFill algorithm is with x on the dial, and y coupling in x and the medicine in y and the sample causes by medicine y and sample x combination in the intersection product of icon 204 expressions.This result is the particulate topological structure that is shown in Figure 11.Notice that the batch processing of combination operation is from the sample precision and from the sample trip axle precision of deriving, so that the user only need stipulate this information in a place of falling out of deriving.
Figure 11 is illustrated in the final particulate graph topological structure that is generated by the AutoFill algorithm into after Samples.Columns and the Drugs.Rows input shaft precision for the intersection example among Figure 10.
Associating (Pooling)
Figure 12 and 13 illustrates how to set up " associating " experiment and " associating " result of experiment.An example of joint objective is that all members of row or column are connected to single combination operation.If one is united across row, so final batch processing will not have the row axle, and the row axle is only arranged.Particularly, Figure 12 illustrates the foundation of associating example." medicine " icon 210 expression samples, " example " icon 212 expression examples, the 214 expression interlace operations of " intersection " icon, and " associating " icon 216 expression joint operations.Icon shown in Figure 12 will make the AutoFill algorithm produce required associating, and it is shown among Figure 13.To mate among the capable x of 2D all members in the batch processing because have the member of the associating batch processing of index x, so it works.Each row of 2D intersection product is associated to single combination operation among Figure 12.Final batch processing will be an one dimension, have as intersection-product batch processing equal number capable.
Figure 13 illustrates the associating example of the final connectedness of operation AutoFill algorithm generation with complete Figure 12.Material stream illustrates decussate texture, is uniting to eliminate row across row thereafter.
Select
Figure 14 illustrates option program.Common requirement is the subclass executive routine to given sample set.This can realize with the AutoFill algorithm by the subclass of regulation axle interested.By keeping identical dimension, just do not unite generation.Example in Figure 14 distributes the dial of batch processing to tie up the subrange (sub-range) that is defined as the dial dimension that is used for the original batch processing of sample.As a result of, the AutoFill algorithm only will distribute the member of batch processing to be connected to the member of original batch processing, and index accurately mates here.
Figure 14 selects.This configuration is selected first dial in 3 dials from 5 * 4 * 3 batch processings.Inset (inset) 220 illustrates the input that was required by the user before operation AutoFill algorithm.Sample icon 222 expression samples, and distribute icon 224 expression batch operations.Dimension " 5 * 4 * 1 " is only indicated the dimension size.Actual dial or dial are by being used to distribute the coordinate system of batch processing to determine that by user's regulation these dials are selected.For example, if dial is defined as " 2,3 " but not " 1 ", tieing up size then is 5 * 4 * 2, and the AutoFill algorithm will mate the second and the 3rd dial, but not first dial.
Transposition
Figure 15 illustrates the transposition program.Sometimes the mode that changes the batch processing arrangement is useful.An example is such situation, wherein people need in single batch processing, make the institute might make up.This can realize that even primary sample can be divided into two batch processings (batch operation), batch processing here follows axle and arranges by above-mentioned interleaved mode, and another is arranged along the row axle.If we can send instruction, for a batch processing, the axle order will change, and the AutoFill algorithm can be used to realize this task.Force the AutoFill algorithm according to the different order coupling that only is used for related batch processing with level features (Rank property).As a result of, member x will mate member x (downwards) in the distribution batch processing of transposition in the primary sample batch processing.Figure 15 illustrates this mode and how to be used for sample batch processing and himself are intersected.
How inset 230 separates if illustrating single one dimension batch processing, transposition is so that it can make up with self in cross program, shown in Figure 10 and 11 then.Sample icon 232 expression samples, " across " icon 234 expressions are across operation, 236 expressions of " downwards " icon are operated downwards, and the 238 expression interlace operations of " intersection " icon.The default ordering of the coordinate system that is used by matching algorithm is rewritten by " rank " characteristic, its regulation new sequences { OK, row, dial }, but not be listed as, OK, dial }.As a result of, the AutoFill algorithm be the row of " sample " batch processing with the row coupling of " downwards " batch processing, so as " downwards " can with " across " intersect with formation the 2-D batch processing that might make up.
Multiple other useful mode can be used the AutoFill algorithm construction, if add other instruction especially, as being offset (offsets) and stepping into (strides) so that matching algorithm can be along different dimensional migration or broadening.
The AutoFill algorithm is promoted
The class of structure is concluded in the popularization of AutoFill algorithm, and this structure can automatically generate with actual and comprise any style, and it can be by mathematical expression.From very succinct, senior standard, the AutoFill algorithm, and can be the calculating generation model in complex combination program and the hyperspace by this popularization.
The member of the batch processing that general AutoFill algorithm discussed above connects, they are in each index position coupling, and empty position mates any clauses and subclauses or other sky clauses and subclauses here.This algorithm also works to other operation, and they are not included in the batch processing, but they are connected to batch processing by the edge.Because such operation does not have the index characteristic, so all index characteristics of the batch processing member that their couplings connect.This is useful for each member who single operation is connected to batch processing.
The conversion that the popularization of this algorithm defined the G.Index.e user application before assignment is so that coupling.Therefore, new algorithm can followingly write out, and wherein the change of the algorithm of Gui Naing is emphasized with runic:
For?All?nodes?F?and?G?in?the?SFG，such?that：
F?is?a?node?in?Batch?A；and
G?is?a?node?in?Batch?B；and
F！＝G；and
There?exists?a?template?edge?from?A?to?B
Create?a?new?edge?from?F?to?G?if?and?only?if
For?all?i，
Index?x＝Transform(G.Index.e)
F.Index.e
i＝x
i“Entry?i?of?F’s?Index＝Entry?i?of?G’s
Transformed?index”；or
F.Index.e
i?is?empty；or
x
i?is?empty
Conversion (transformation) can be the mathematical function of any generation index.This conversion can index and the model name space in the function of any other variable, as the U.S. Provisional Application No.60/454756 of application on March 14th, 2003.Transfer function can be expressed as one group of expression formula by the user, and every dimension is one in the coordinate system.These expression formulas will be called as matched rule, and we claim this AutoFill to be extended to the matched rule popularization.
Figure 16 illustrates the simple case of the SFG 200 that matched rule produces, and this matched rule makes AutoFill algorithm migration sample 302 and distributes connection between 1304.Row matched rule shown in Figure 16 is to each member 304a-304d independence assignment of distributing 1 304 batch processings before using the AutoFill algorithm.Add each member 304a-304d column position to will connect migration left with 1.For example, the 4th member 304d is connected to the fifty percentth Yuan 302e in the sample 302 in the distribution 1304.Note, distribute 1304 only to comprise 4 members.The AutoFill algorithm is eliminated the member who does not have coupling automatically.
Slight modification is shown in the SFG 320 of Figure 17 to matched rule, and it produces 4 similar member results, but need not move.In Figure 17, conditional expression is used for guaranteeing that row 1 do not have coupling in the row matched rule, makes that like this other position is unaffected.Not migration in this case.
Figure 18 represents more complicated example, and its ability that AutoFill algorithm and matched rule popularization are shown is so that useful structure to take place, as SFG 350 expressions.In order to add up purpose, need sometimes all possible combination of a group reagent 354 usefulness is carried out experiment to one group of sample 352.AutoFill algorithm and matched rule are promoted the accurate figure that can be used to easily to generate such experiment and are represented 350.
How simultaneously the example of Figure 18 illustrates matched rule set of transposition primary sample or batch processing 352, to prevent the generation of assignment pairing, causes required lower triangular matrix and upper triangular matrix.This example is similar to shown in Figure 15, because primary sample 352 is claimed two batch processings (batch operation is across 354 and downward 356) by division, batch processing here follows that axle is arranged and another is arranged along the row axle.When row more than or equal to when row, prevent to duplicate pairing and be by preventing any coupling, and before checking coupling, be to realize across coupling 354 by transposition row and column index position.Concealed wire 358 between selected icon is emphasized some connection by the AutoFill generation.Notice that the index of some correctly indicates them how related with primary sample batch processing 352 in the intersection batch processing 360.This is that the AutoFill algorithm is continued to use the natural result that is connected propagation from the batch processing to the batch processing that the family limits with automatic coordinate system on the batch processing level.
The AutoFill algorithm that is used for manually rewriting is promoted
Summarize in the above in the AutoFill algorithm of discussing, all connections in the process flow diagram between the batch processing member are determined by algorithm.These results can be revised after the operation algorithm to obtain the automatic and manual combination that is connected by the user.Yet this method is unsuitable for dynamic execution, and wherein algorithm and the matched rule of carrying out again continuously with the batch processing size is changed.In dynamically carrying out, the result who manually changes AutoFill will carry out next time and eliminate.In order to address this problem, new method of following statement, it is used for to influence the result that the AutoFill algorithm carries out later on the manual editing being kept at model.Modeling is promoted and is as follows to the revised comment of AutoFill algorithm.
In Figure 19, batch processing X is connected to batch processing Y.As a result of, each member of batch processing X connects each member who is connected to batch processing Y according to the AutoFill algorithm automatically by " automatically ".
In primal system, if wanting to eliminate, the user connects, for example, and at 1 of batch processing X, 1 of A and batch processing Y, between the A, " automatically " that the user just just can delete between them connects.Yet, opposite with user's intention, the connection that the execution again of AutoFill algorithm will undelete.
In order to support dynamic user interface, wherein when parameter such as batch processing size and batch processing rule are changed, are dynamically connected certainly and are calculated again, need a kind of method, it is preserved manually and changes.The manual change of two kinds of possibility types is arranged: deletion at " automatically " edge (that is, deletion) and edge add (that is, adding), and they originally to be created by the AutoFill algorithm.
In new execution, the deletion at " automatically " edge is permanent the generation by add " do not have and connect " edge on its position.Should " not have and connect " edge and do not hinder (respected) new automatic filling algorithm, therefore do not create automatic edge.Not having the edge of connection is shown among Figure 20 with white.
Though it is invisible to the user to make this nothing connect the edge, it is visible preferably making nothing connect the edge, if so that the user wishes to recover from being dynamically connected, they know that the deletion nothing connects the edge.
In order to preserve manual connection, only carry out the deletion before of AutoFill algorithm again from being automatically connected in.Figure 21 is illustrated among the X 2, among A and the Y 1, adds the result who manually connects between the A.
Dynamically AutoFill carries out and can be summarised in the following pseudo-code standard:
When?a?change?to?batch?size?or?match?rule?is?detected?do{
Delete?all?connections?marked“automatic”that?involve?the
Changed?batch
Compute?automatic?connection?set?using?the?extended?match
rule?algorithm
Delete?all?automatic?connections?that?conflict?with
NoConnect?edges
Mark?all?automatic?connections?as“automatic”}
An advantage of the enhancing of AutoFill algorithm is based on matched rule and the batch processing syndeton provides dynamically for the user, and the ability of the detailed model of continuous updating also allows user selection ground to rewrite AutoFill result simultaneously.An advantage of AutoFill algorithm is that any mathematics between its actual generation batch processing member can be described connected mode (n ties up array).Though irregular structure can allow the user to draw more effective and direct in conjunction with the AutoFill algorithm simply in the irregular part of this mode with matched rule by discontinuous function (if-then-else expression formula) structure.This is to realize by interpolation and the deletion of supporting connection, and these connections are to preserve in the execution again of AutoFill algorithm.These interpolations and deletion be can be enough same to be connected and disconnection (disconnection) user interface and add and remove, and this user interface is used for all other connections of system.
Other application
Top example illustrates according to laboratory procedure, but can be applied to pure mathematics model and calculating equally.As an example, batch processing and the room and time model that can be used for producing biosystem that is connected that generates automatically.Each element will or concentrate corresponding to the reaction of chemical substance in the batch processing, and the edge flows to reaction and flows out reaction corresponding to chemicals, and reaction causes the change of material concentration.AutoFill algorithm and matched rule are promoted and are made the user generate the complicated finite element model of such system or other computing system fast, and use icon representation.
Those skilled in the art can create fast based on the source of Fig. 2-18 and the detailed description that provides here.
Be used for automatically fill the equipment of workflow model and specific embodiment and the example of method though described for illustrative purposes here, can make different equivalent modifications and not depart from spirit of the present invention and category, for it will be appreciated by those skilled in the art that this point.The instruction that the present invention provides here may be used on the system of other processor control, and needs not to be above-described exemplary computer system.Similarly, the instruction that the present invention provides here may be used on other workflow modeling tool, and needs not to be the workflow modeling tool of summarizing above.
Above-described different embodiment is capable of being combined so that further embodiment to be provided.In this instructions with reference to and/or be listed in all United States Patent (USP)s of request for data list, US patent application publication, U.S. Patent application, foreign patent, foreign patent application and non-patent are announced, including, but not limited to the U.S. Provisional Patent Application sequence number of awarding 14 days March in 2003 application that allows jointly is 60/454756, and its title is " using equation to be used for the method for the graphical manipulation of workflow, equipment and article "; On August 8th, 2003, the sequence number of application was 60/493749, and its title is " Method and kit for based on batch processing that is used for the graphical manipulation of workflow "; On September 22nd, 2003, the sequence number of application was 60/505096, and its title is " Method and kit for based on batch processing that is used for the graphical manipulation of workflow "; On February 11st, 2004, the sequence number of application was 60/543859, and its title is " Method and kit for based on batch processing that is used for the graphical manipulation of workflow "; On August 8th, 2003, the sequence number of application was 60/493748, and its title is " the integrated and physical modeling of closed loop in the silicon "; Their whole contents is all incorporated into herein for your guidance.If necessary, embodiments of the invention can be revised, adopting different patents, and application and the system that announces, thus circuit and notion provide the present invention further embodiment.
Consider top detailed description, can make these and other change the present invention.In a word, in the following claim, used term can not be interpreted as limiting the present invention to disclosed certain embodiments in this instructions and the claim, and should be interpreted as comprising all program designs based on batch processing, and it is operated according to claim.Therefore, the present invention is not limited by the disclosure, and the category that is subjected to be determined by following claim fully limits.
Claims (28)
1. method that adopts the digital model of flow process, this method comprises:
Create the numeral of at least two level node, each level node has each dimension of a plurality of dimensions of related with it each level node of qualification, each dimension of each node has the order that limits relative to each other, and each dimension has qualification, and each ties up the size of a plurality of members' association;
Create the numeral at a plurality of ranks edge, limit the connection between at least some level node, at least the connection between first and second at least two level node of the definition of first in these rank edges; With
Many to level node every pairs that connect for each edge of sharing by the rank edge, to a plurality of matched rules of major general one with this level node to related, each matched rule limits a matrix conversion at least between each is to level node, matrix conversion is applied to each member to level node and goes up the final ancestor node of qualification and the set of original edge, and first in wherein a plurality of matched rules limits first matrix conversion between first and second level node.
2. the method for claim 1 further comprises:
Receive first group of user's input, the selection of first icon representation of first level node of at least two level node of identification expression, and be the dimension of first level node identification indication dimension sum and the size of each dimension; With
Receive second group of user's input, the selection of first icon representation of the second level node of at least two level node of identification expression, and be the dimension of second level node identification indication dimension sum and the size of each dimension;
3. method as claimed in claim 2 further comprises:
Receive the 3rd group of user's input, first icon at identification expression edge, this edge extends to the second level node from first level node.
4. the method for claim 1 further comprises:
Receive first group of user's input, the selection of first icon of first level node of at least two level node of identification expression, the readable title of the people of first level node, and be dimension, the size of each dimension and the readable title of people that is used for each dimension of first level node identification indication dimension sum.
5. the method for claim 1 further comprises:
Receive first group of user's input, the selection of first icon of first level node of at least two level node of identification expression, the readable title of the people of first level node, and be the dimension of first level node identification indication dimension sum, each dimension order relative to each other and the size of each dimension.
6. the method for claim 1 further comprises:
Based on the quantity of dimension and the size of each each dimension of level node, for each level node is created the numeral of a plurality of ancestor nodes automatically to fill each dimension.
7. method as claimed in claim 6 further comprises:
Based on by with each to the matrix conversion that the related matched rule of level node limits, every pair of level node that each rank edge of sharing of serving as reasons connects is created the numeral of the original edge between the ancestor node automatically.
8. method as claimed in claim 7 further comprises:
Detect the change at least one level node or at least one rank edge; With
Respond detected change, based on the quantity of the dimension of each level node and the size of each dimension, the numeral of creating ancestor node quantity for each level node automatically is to fill each dimension.
9. method as claimed in claim 7 further comprises:
Detect the change at least one level node or at least one rank edge; With
The change that response detects, based on the dimension amount of each level node and the size of each dimension, for each level node is created the numeral of ancestor node quantity automatically again, and based on by creating the numeral of the original edge between the ancestor node automatically again with each matrix conversion that the related matched rule of level node is limited.
10. method as claimed in claim 9 further comprises:
Determine that the user points at least one ancestor node or at least one original edge with the inhibition of at least one matched rule application; With
Based on the user at least one ancestor node or at least one original edge are pointed in the inhibition of at least one matched rule, optionally suppress the establishment again of at least one ancestor node or at least one original edge.
11. the method for claim 1 further comprises:
Produce the visual representation of ancestor node and original edge.
12. method as claimed in claim 11 further comprises:
For driving a plurality of sensors, produce a plurality of sensor actuation signals, it is corresponding to some ancestor node at least and some original edge.
13. one kind is used for the system that the modeling highly-parallel is handled, its operative material or data, wherein the parallel route experience again tissue as combination and, or separately, this system comprises:
Be used to create the instrument of the numeral of at least two level node, each level node has each related with it dimension, this dimension limits a plurality of dimensions of each level node, each dimension of each level node has the order that limits relative to each other, and each dimension has related qualification and respectively ties up a plurality of members' size;
Be used to create the instrument of a plurality of ranks edge numeral, the edge limited connection between some level node at least of this rank, first and the connection between second in edge limited at least two level node of at least the first rank; With
Be used to many to every pair in the level node with at least one instrument related in a plurality of matched rules with a pair of level node, these are many to be connected by each rank edge of sharing level node, each matched rule limits each at least one matrix conversion between the level node, matrix conversion is applied to each member to the level node that limits final group ancestor node and original edge, and wherein first of a plurality of matched rules limits first matrix conversion between first and second level node.
14. system as claimed in claim 13 further comprises:
Processor;
Computer-readable memory, the instruction that its storage can be carried out by this processor, the instrument that wherein is used for creating the numeral of at least two level node comprises the first group of instruction that is stored in computer-readable memory; The instrument that is used for creating the numeral at a plurality of ranks edge that qualification connects between some level node at least comprises the second group of instruction that is stored in computer-readable medium, is used to many to level node every pairs that connected by each rank edge of sharing that at least one instrument related with a pair of level node in a plurality of matched rules is comprised the 3rd set of computer readable instructions that is stored in the computer-readable memory.
15. system as claimed in claim 13 further comprises:
Be coupled to the display of this processor, it can operate the demonstration level node, rank edge and ancestor node and original edge.
16. system as claimed in claim 13 further comprises:
The output port that can be coupled and control signal to one or more robot devices to provide.
17. a computer-readable medium, the data structure of its storage representation flow processing, this data structure comprises:
At least two level node, each level node has each related with it dimension, this dimension limits a plurality of dimensions of each level node, and each dimension of each level node has the order relative to each other of qualification, and each dimension has the size that a plurality of members' association is respectively tieed up in qualification;
A plurality of ranks edge, it limits the connection between some level node at least, the connection between first and second level node of edge limited at least two level node of at least the first rank; With
A plurality of matched rules, each matched rule limit connect by a public rank edge each at least one matrix conversion between the level node, matrix conversion is applied to each member to level node and limits final group ancestor node and original edge, and first of a plurality of at least matched rules limits first matrix conversion between first and second level node.
18. computer-readable medium as claimed in claim 17, wherein each member represents primitive operation or original material.
19. computer-readable medium as claimed in claim 17, wherein each member represents raw information.
20. computer-readable medium as claimed in claim 17, wherein each member represents a primitive operation, original material, or another level node.
21. computer-readable medium as claimed in claim 17, wherein each member sorts along described dimension.
22. computer-readable medium as claimed in claim 17, wherein one dimension at least the first and second level node is three-dimensional, and dimension is corresponding to X-axis, perpendicular to the Y-axis of this X-axis with perpendicular to the Z axle of X-axis and Y-axis.
23. computer-readable medium as claimed in claim 17, wherein one dimension at least the first and second level node is a bidimensional, and dimension is corresponding to row with perpendicular to the row of going.
24. method that employing is constructed with the high level of level node and rank boundary form, thereby directly connect between the edge limited level node of this rank and represent the low-level details of technological process with the form of original connection between ancestor node and the ancestor node, this method comprises:
For a plurality of level node each, create a plurality of ancestor nodes automatically so that small part is filled at least one Descartes's dimension of each level node; With
Based on the matched rule of the level node that is connected to being associated, between the ancestor node of automatically creating, create a plurality of original edges automatically and connect, this matched rule limits at least one matrix conversion between the right node of the level node that connects.
25. method as claimed in claim 24 further comprises:
With the characteristic of some ancestor node at least be associated corresponding to the related characteristic of the ancestor node of respectively tieing up characteristic of distributing to this level node, ancestor node limits from this level node by each matched rule.
26. method as claimed in claim 24, wherein first level node is corresponding to first material, the second level node is corresponding to second material, the other node of the third level is corresponding to the operation that will carry out on first and second materials, first edge is connected to the other node of the third level with first level node, and the second level edge is connected to the other node of the third level with the second level node.
27. method as claimed in claim 26, wherein create a plurality of ancestor nodes automatically to fill at least one Descartes's dimension of each level node, this method comprises a plurality of ancestor nodes of creating the expression first level node row, create a plurality of ancestor nodes of expression second level node row, a plurality of row and columns with the ancestor node of creating the other node of the expression third level, the quantity Matching of row in the quantity of the row of the other node of the expression third level and first level node, and the quantity Matching that is listed as in the quantity of the row of the other node of the expression third level and the second level node.
28. method as claimed in claim 27, wherein based on the level node that connects to related matched rule, between the ancestor node of creating automatically, create a plurality of original edges connections automatically and comprise that creating the edge connects, each of a plurality of ancestor nodes that this edge connects each row from represent first level node each of ancestor node in each row of the other node of the third level, and create the edge and connect, this edge connects each each ancestor node in each row of the other node of the third level of a plurality of ancestor nodes of each row from expression second level node.
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US45475603P | 2003-03-14 | 2003-03-14 | |
| US60/454,756 | 2003-03-14 | ||
| US60/493,749 | 2003-08-08 | ||
| US60/505,096 | 2003-09-22 | ||
| US60/543,859 | 2004-02-11 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN1795429A true CN1795429A (en) | 2006-06-28 |
Family
ID=36806169
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200480011361 Pending CN1795429A (en) | 2003-03-14 | 2004-03-11 | Batch-based method and tool for graphical manipulation of workflows |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN1795429A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107463725A (en) * | 2017-06-25 | 2017-12-12 | 浙江大学 | A kind of Parameters design for being applied to simulation and RF IC |
-
2004
- 2004-03-11 CN CN 200480011361 patent/CN1795429A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107463725A (en) * | 2017-06-25 | 2017-12-12 | 浙江大学 | A kind of Parameters design for being applied to simulation and RF IC |
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