CN117371393A - Feature marking method for EDA model data Boolean operation - Google Patents
Feature marking method for EDA model data Boolean operation Download PDFInfo
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- CN117371393A CN117371393A CN202311347295.5A CN202311347295A CN117371393A CN 117371393 A CN117371393 A CN 117371393A CN 202311347295 A CN202311347295 A CN 202311347295A CN 117371393 A CN117371393 A CN 117371393A
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000012163 sequencing technique Methods 0.000 claims abstract description 11
- 239000013598 vector Substances 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 8
- 230000009466 transformation Effects 0.000 claims description 8
- 230000001131 transforming effect Effects 0.000 claims description 3
- 238000004088 simulation Methods 0.000 abstract description 2
- 238000002372 labelling Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
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- 238000005457 optimization Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/39—Circuit design at the physical level
- G06F30/398—Design verification or optimisation, e.g. using design rule check [DRC], layout versus schematics [LVS] or finite element methods [FEM]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The invention relates to the technical field of EDA model layout simulation, and discloses a feature marking method for EDA model data Boolean operation, which comprises the following steps: determining data of a Boolean operation; traversing all the faces in the Result model data in sequence, summarizing the faces with the same Feature Name to form a data set ListSameNameFace, and sequencing according to the Feature Name; sequentially processing Face data in the data set, and renaming the Face data according to rules; judging the associated edge list while processing the Face; and (5) checking all the Face and Edge in the traversal Result model, and marking the missed unlabeled data. The invention solves the problems of sequencing, marking and tracing of newly added Face and Edge in the EDA model Boolean operation process.
Description
Technical Field
The invention relates to the technical field of EDA model layout simulation, in particular to a feature marking method for EDA model data Boolean operation.
Background
The feature tag of EDA model data is a basic function of model data operation, and is characterized in that all Vertex, edge, face in the model are uniquely identified, and Vertex, edge, face data in the model can be quickly located through the identification. Common Boolean operations include Unite, subtract, intersect, imprint, split; because of the model Boolean operation, new Vertex, edge, face data are generated, which are arbitrary and have no obvious rule, and the feature labeling method is always a special research subject in the industry, and no perfect solution exists at present, and only iterative optimization is performed continuously.
In the prior art, the label of the newly added Vertex, edge, face is marked in an ID mode, after command parameters are changed, the number and the positions of the newly added surfaces are changed, the positions of the labels before and after the modification are inconsistent, and the problems of difficult tracing of the model label and difficult maintenance of the label ID exist.
Disclosure of Invention
The invention provides a feature marking method for EDA model data Boolean operation, which solves the problems of sequencing, marking and tracing of newly added Face and Edge in the EDA model Boolean operation process.
The invention provides a feature labeling method for EDA model data Boolean operation, which comprises the following steps:
s1, determining data of Boolean operation, wherein the data comprise Blank model data, tools model data and Result model data;
s2, traversing all the faces in the Result model data in sequence, and summarizing the faces with the same Feature Name to form a data set ListSameNameFace;
s3, sorting the data set ListSameNameFace according to FeatureName;
s4, sequentially processing the Face data in the ListSameNameface, and renaming the Face data according to rules;
s5, judging edges edge list associated with the Face while processing the Face, renaming if the edges edge list are the same, and marking if the edges edge list are not marked;
s6, checking all the Face and Edge in the traversal Result model, marking the missed unmarked data, and performing unique index positioning through Edge marking information associated with the Vertex when the method is used, wherein the Vertex is not used for marking alone.
Further, in step S1, the Blank model data is a target object for performing a Boolean operation, the Tools model data is data for performing an operation on the target object, and the Result model data is a Result after the Boolean operation;
after Boolean operation, the surface area newly generated by Result model will multiplex the original feature label information if it is attached to the Blank, tools model.
Further, the step S5 specifically includes:
s5.1, processing the two identical faces Face01 and Face02 with the characteristic marked as FeatureName 01;
s5.2, searching for a Face00 corresponding to the FeatureName01 in a Blank or Tools model;
s5.3, constructing a space transformation matrix based on the Face00, wherein the normal vector of the Face00 is taken as a z-axis, and Edge center points with the minimum feature marks in all edges of the Face00 are taken as one point on an x-axis;
s5.4, spatially changing the center points of the faces of the Face01 and the Face02, forming vectors Vector01 and Vector02 with the original points, and calculating the included angles of the vectors and the x axis;
s5.5, sorting the Face01 and the Face02 according to the included angles, and sorting again according to the area of the reference surface if the included angles are the same;
s5.6, traversing edges edge List01 and edge List02 corresponding to the edges Face01 and Face02, renaming edges with the same name, and naming if unnamed edges exist;
s5.7, sequencing the Edge list01 and the Edge list02 respectively based on the Face01 and the Face02, constructing a space transformation matrix, transforming the Edge center point, and then solving the included angles for sequencing;
s5.8, a new feature mark is that mark information is continuously added behind FeatureName01, and the mark rule is letter+ID+underline+serial number; if the Face is renamed, the letter is F, if Edge is marked, the letter is E.
The beneficial effects of the invention are as follows:
according to the feature marking method for the EDA model data Boolean operation, provided by the invention, the new unique identification is added on the feature marking of the original model by searching the mapping relation between the newly generated surface and the original Entity, meanwhile, the associated edge construction space transformation matrix is subjected to sequencing traversal, the unique feature identification is carried out in sequence, the whole marking process is simple and quick, traceability is achieved, and the EDA model data modeling operation requirement is met.
Drawings
FIG. 1 is a flow chart of a method of characterizing EDA model data Boolean operations of the present invention.
FIG. 2 is a schematic diagram of a process flow for characterizing the same Face in the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the present invention provides a feature labeling method for EDA model data Boolean operation, comprising:
s1, determining data of Boolean operation, wherein the data comprise Blank model data, tools model data and Result model data;
the Blank model data is a target object for Boolean operation, the Tools model data is data for operating on the target object, and the Result model data is a Result after Boolean operation;
after Boolean operation, the surface area newly generated by Result model will multiplex the original feature label information if it is attached to the Blank, tools model.
S2, traversing all the faces in the Result model data in sequence, and summarizing the faces with the same Feature Name to form a data set ListSameNameFace;
s3, sorting the data set ListSameNameFace according to FeatureName;
s4, sequentially processing the Face data in the ListSameNameface, and renaming the Face data according to rules;
s5, judging edges edge list associated with the Face while processing the Face, renaming if the edges edge list are the same, and marking if the edges edge list are not marked; as shown in fig. 2, the method specifically includes:
s5.1, processing the two identical faces Face01 and Face02 with the characteristic marked as FeatureName 01;
s5.2, searching for a Face00 corresponding to the FeatureName01 in a Blank or Tools model;
s5.3, constructing a space transformation matrix based on the Face00, wherein the normal vector of the Face00 is taken as a z-axis, and Edge center points with the minimum feature marks in all edges of the Face00 are taken as one point on an x-axis;
s5.4, spatially changing the center points of the faces of the Face01 and the Face02, forming vectors Vector01 and Vector02 with the original points, and calculating the included angles of the vectors and the x axis;
s5.5, sorting the Face01 and the Face02 according to the included angles, and sorting again according to the area of the reference surface if the included angles are the same;
s5.6, traversing edges edge List01 and edge List02 corresponding to the edges Face01 and Face02, renaming edges with the same name, and naming if unnamed edges exist;
s5.7, sequencing the Edge list01 and the Edge list02 respectively based on the Face01 and the Face02, constructing a space transformation matrix, transforming the Edge center point, and then solving the included angles for sequencing;
s5.8, a new feature mark is that mark information is continuously added behind FeatureName01, and the mark rule is letter+ID+underline+serial number; if the Face is renamed, the letter is F, if Edge is marked, the letter is E.
S6, checking all the Face and Edge in the traversal Result model, marking the missed unmarked data, and performing unique index positioning through Edge marking information associated with the Vertex when the method is used, wherein the Vertex is not used for marking alone.
After the EDA model Boolean operation, the Face and Edge are newly added, and the Face/Edge is ordered and marked by constructing a space transformation matrix for a plurality of times. Based on the local features of the model data, the newly added Face/Edge is subjected to sequencing marking, so that the data marking traceability requirement is met, the newly added marking information is based on the expansion of the original marking information no matter how the model changes, and the consistency of main data marking information after multiple parameter modification is ensured.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes using the descriptions and drawings of the present invention or directly or indirectly applied to other related technical fields are included in the scope of the invention.
Claims (3)
1. A method for characterizing EDA model data Boolean operations, comprising:
s1, determining data of Boolean operation, wherein the data comprise Blank model data, tools model data and Result model data;
s2, traversing all the faces in the Result model data in sequence, and summarizing the faces with the same Feature Name to form a data set ListSameNameFace;
s3, sorting the data set ListSameNameFace according to FeatureName;
s4, sequentially processing the Face data in the ListSameNameface, and renaming the Face data according to rules;
s5, judging edges edge list associated with the Face while processing the Face, renaming if the edges edge list are the same, and marking if the edges edge list are not marked;
s6, checking all the Face and Edge in the traversal Result model, marking the missed unmarked data, and performing unique index positioning through Edge marking information associated with the Vertex when the method is used, wherein the Vertex is not used for marking alone.
2. The method for marking characteristics of a Boolean operation according to the EDA model data of claim 1, wherein in step S1, said Blank model data is a target object for performing a Boolean operation, said Tools model data is data for performing an operation on the target object, and said Result model data is a Result after the Boolean operation;
after Boolean operation, the surface area newly generated by Result model will multiplex the original feature label information if it is attached to the Blank, tools model.
3. The method for characterizing an EDA model data Boolean operation according to claim 1, characterized in that step S5 comprises in particular:
s5.1, processing the two identical faces Face01 and Face02 with the characteristic marked as FeatureName 01;
s5.2, searching for a Face00 corresponding to the FeatureName01 in a Blank or Tools model;
s5.3, constructing a space transformation matrix based on the Face00, wherein the normal vector of the Face00 is taken as a z-axis, and Edge center points with the minimum feature marks in all edges of the Face00 are taken as one point on an x-axis;
s5.4, spatially changing the center points of the faces of the Face01 and the Face02, forming vectors Vector01 and Vector02 with the original points, and calculating the included angles of the vectors and the x axis;
s5.5, sorting the Face01 and the Face02 according to the included angles, and sorting again according to the area of the reference surface if the included angles are the same;
s5.6, traversing edges edge List01 and edge List02 corresponding to the edges Face01 and Face02, renaming edges with the same name, and naming if unnamed edges exist;
s5.7, sequencing the Edge list01 and the Edge list02 respectively based on the Face01 and the Face02, constructing a space transformation matrix, transforming the Edge center point, and then solving the included angles for sequencing;
s5.8, a new feature mark is that mark information is continuously added behind FeatureName01, and the mark rule is letter+ID+underline+serial number; if the Face is renamed, the letter is F, if Edge is marked, the letter is E.
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| CN202311347295.5A CN117371393A (en) | 2023-10-17 | 2023-10-17 | Feature marking method for EDA model data Boolean operation |
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| CN202311347295.5A CN117371393A (en) | 2023-10-17 | 2023-10-17 | Feature marking method for EDA model data Boolean operation |
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