Dynamic Scaling Graphical User Interface Easing Functions
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Solution Overview
Problem
Existing graphical user interface technologies lack dynamic scaling capabilities, particularly in data visualization, where users struggle to understand and configure easing functions, and existing functions often fail to preserve monotonicity and can return undefined results or skew output domains.
Innovation Solution
The implementation of parameterizable easing functions that allow users to configure styling parameters such as hue and size through a manipulatable interface, ensuring monotonicity between input and output data, and automatic synchronization of styling parameters across multiple layers when a common metric is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If parameterizable easing functions are implemented with configurable styling parameters, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system automatically detects common metrics across multiple layers and performs automatic synchronization of styling parameters without requiring manual user intervention. This self-service capability reduces the operational burden on users while managing the underlying complexity automatically.
Solution Approach 2:
A graphical user interface serves as an intermediary between the user and the complex easing function parameters. The UI provides visual controls that simplify the configuration process, allowing users to adjust easing parameters without directly dealing with the mathematical complexity of the underlying functions.
2Productivity
If real-time dynamic scaling is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The system applies easing functions selectively to styling parameters rather than transforming all data representations. By applying the easing function only to visual styling attributes (color, size, shape) rather than the underlying data structures, the system achieves real-time visual feedback with reduced computational overhead.
Solution Approach 2:
The easing function parameters are pre-configured and validated before real-time processing. The system prepares the easing function mappings and styling parameter relationships in advance, allowing for efficient real-time application without extensive computation during the visualization update phase.
3Ease of operation
If automatic synchronization across multiple layers is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system automatically detects common metrics across multiple layers and performs automatic synchronization of styling parameters without requiring manual user intervention. This self-service capability reduces the operational burden on users while managing the underlying complexity automatically.
Solution Approach 2:
The easing function configuration system serves multiple layers simultaneously with a single set of parameters. Once an easing function is configured for one layer, the same configuration can be automatically applied to other layers sharing common metrics, making the system work efficiently across multiple data representations without requiring separate configurations for each layer.
Data Source
AI summary
Systems and methods for dynamic scaling in graphical user interfaces are described herein. According to some embodiments, an example method includes receiving input data to be graphically displayed on a graphical user interface, generating an interface that includes a control icon that can be translated within a grid so as to define an easing curve and to select at least two easing function parameters for a parameterizable easing function, and generating, in real-time as the least two easing function parameters are received, the graphical user interface which includes output representations of the input data which have one or more styling parameters that are selected based on the parameterizable easing function such that monotonicity is maintained between the input data and the output representations.