Dual-Axis Graph E-Value Optimization
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Solution Overview
Problem
Conventional graphing tools fail to provide optimal axis boundary settings for comparing two data sets, leading to inaccurate conclusions about correlations between data sets due to arbitrary axis settings that do not consider the relationship between the sets.
Innovation Solution
A machine-implemented method and electronic device that calculates an E-value for each data set, designates one as the first and the other as the second data set based on E-value, and adjusts the axis boundaries to ensure the E-value is consistent across both axes, allowing for accurate comparison and plotting of data points on a dual-axis graph.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the boundaries of the two reference axes are set to be equal to the maximum and minimum values of the respective data sets, then the fluctuations in the resulting curves for the two data sets are clearly visible, but completely erroneous conclusions may be drawn since such an approach is arbitrary and does not take into consideration any relation between the two data sets
Solution Approach 1:
The patent changes the parameters of the axis boundaries from arbitrary max/min values to optimized values determined by an objective function. The system calculates optimal boundaries that maximize the visual separation between curves while maintaining accurate correlation representation, thereby resolving the contradiction between visibility and reliability.
Solution Approach 2:
The patent implements a feedback mechanism where the system evaluates the quality of axis boundary settings using an objective function that considers the relationship between the two data sets. The boundaries are iteratively adjusted based on this feedback until optimal values are achieved, ensuring both visibility and accurate correlation representation.
2Productivity
If conventional graphing tools are used with arbitrary axis boundary settings, then the graph can be generated quickly, but the boundaries are set without taking into consideration any relation between the two data sets, leading to curves that may suggest correlations where there are none or correlations which may be inaccurate
Solution Approach 1:
The patent performs preliminary calculations of optimal axis boundaries using an objective function before generating the graph. This preliminary optimization ensures that the boundaries are scientifically determined rather than arbitrary, improving measurement precision without significantly impacting productivity since the calculation is automated.
3Quantity of substance
If the boundaries of the reference axes are set to maximize the range of values for each data set independently, then each data set can be fully displayed, but the comparison between the two data sets becomes meaningless due to significant difference in scale
Solution Approach 1:
The patent introduces asymmetry in the treatment of the two data sets by applying different scaling approaches. Instead of treating both data sets equally with independent max/min boundaries, the system optimizes boundaries asymmetrically to account for scale differences, enabling meaningful comparison while maintaining full display of value ranges.
Data Source
AI summary
A machine-implemented method for presenting a dual-axis graph for a pair of data sets includes: reading the data sets; setting first and second boundaries of a first reference axis using first coordinates of data points of one data set having maximum and minimum values, respectively; setting first and second boundaries of a second reference axis by adjusting either the first coordinate of one data point of the other data set having a maximum value or the first coordinate of one data point of the other data set having a minimum value, wherein an E-value calculated based on thus-obtained final first and second boundaries of the second reference axis is substantially equal to an E-value of the first data set; and plotting the data points of the data sets. An electronic device capable of presenting a dual-axis graph is also disclosed.