Auto-transpose Replication for Parametric Modeling Lists
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Solution Overview
Problem
Parametric modeling systems face challenges in accurately replicating lists of values, leading to undesirable results when input properties expect a single value but receive a list, causing internal component entities to be created incorrectly.
Innovation Solution
The system automatically determines and applies a replication method by creating a rectangularized list, calculating an index trail, and rotating values to correctly replicate geometric entities such as points and curves, using a transpose function to ensure proper replication of one-dimensional and multi-dimensional lists.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a list of values is given to an input property expecting a single value, then replication is triggered, but the internal component entities are created incorrectly
Solution Approach 1:
The system performs preliminary analysis of the list structure (detecting total levels, creating rectangularized copy, calculating index trail) before executing replication. This preliminary preparation ensures that the replication logic understands the nested structure and can correctly map components, preventing incorrect entity creation while maintaining automatic replication.
Solution Approach 2:
The patent introduces an intermediary data structure (rectangularized list with index trail) that mediates between the input list and the replication process. This intermediary structure preserves the nested hierarchy information and enables correct mapping of internal component entities, resolving the contradiction between automation and precision.
2Manufacturing precision
If explicit specification of replication method is required, then replication accuracy improves, but user operation complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing the list structure and determining the appropriate replication method without user intervention. The system detects total levels, creates rectangularized copies, and calculates index trails autonomously, achieving both high precision and ease of operation by eliminating the need for explicit user specification.
Solution Approach 2:
The patent replaces the mechanical approach of explicit user specification with an automated computational system that analyzes list structures and determines replication methods algorithmically. This substitution eliminates manual complexity while maintaining or improving precision through systematic analysis.
3Ease of operation
If the system automatically determines replication method, then ease of operation improves, but handling of multi-dimensional lists becomes complex
Solution Approach 1:
The patent segments the complex multi-dimensional list processing into distinct modular steps: detecting total levels, creating rectangularized copies, calculating index trails, and rotating values. This segmentation breaks down the complexity into manageable components while maintaining automatic operation, resolving the contradiction between ease of use and handling complexity.
Solution Approach 2:
The patent transforms multi-dimensional list processing by introducing a rectangularized representation that preserves hierarchical information in a structured format. This dimensional transformation enables automatic handling of complex structures through systematic index trail calculation and value rotation, maintaining ease of operation while managing complexity.
Data Source
AI summary
A system and method for auto-transpose replication is provided. Auto-transpose replication may be considered the ability to automatically create copies of a given prototype model. Auto-transpose replication may include receiving a first list of data values and determining a total number of levels of the first list. Auto-transpose may also include creating a rectangularized list, where the rectangularized list is a rectangularized copy of the first list based on the determined total number of levels of the first list. Further, auto-transpose may include creating a return list, detecting an item at the deepest level of the rectangularized list, calculating an index trail of the item, rotating the values in the index trail, and storing the item into the return list according to the rotated index trail.