Slycat Ensemble Analysis of Electrical Circuit Simulations

Enhancements to the RAVEN code in FY16

“…Persistence simplification can be used in this context to smooth the patches and thus the data can still be treated as being well approximated as a monotonic region. The algorithm used by Gerber et al [27] can be used to approximate this structure in aribtrary dimensional domains. In fact, Gerber et al [29] demonstrated the effectiveness of the Morse-Smale complex in fitting simple and intuitive local models to data.…”

“…Automated techniques systematically partition the domain, typically in a greedy fashion, by splitting the data along either an original axis-aligned dimension or a reduced axis after performing dimensionality reduction. The criterion for splitting the data varies from minimizing numerical error [2,10,13,17,27] to more geometry and topology-based criteria [29,38].…”

“…HDViz [27] and its extensions [42,43,44] encode sensitivity and density information into a skeleton of the topology and provide auxillary views for more refined analysis. The work of Maljovec et al [45] more explicitly encodes the sensitivity and fitness of the partitioned data into bar charts.…”

“…The topology map encodes the locations of local extrema defined by their persistence and function values, as well as their connectivity (i.e., curves describing flow from a local minimum to a local maximum). Such visualization is, in spirit, similar to the topological skeleton proposed by Gerber et al [27] and applied to nuclear probabilistic risk assessment [43,44]. However, based on the new requirements outlined in Section 4.1.2, we have completely redesigned such a visual encoding to provide a topological summary that omits geometric information but preserves the underlying structure essential to understanding the data partitioning, thereby greatly improving its usability and scalability.…”

“…MSR builds upon a domain partitioning of a dataset induced by the Morse-Smale complex (MSC) and employs a linear regression fit within each partition, thereby exploiting its monotonicity. The MSC itself has been successfully utilized in visual exploration of simulation data modeled as high-dimensional scalar functions [14,22,27,28]. Figure 2a shows the MSC of a 2D test function with four maxima and nine minima.…”