Smoothing of Scatterplots
Explore the source record for details and available documents.
Friedman, J.↗
SEARCH · Search NASA
Results for “SCATTERPLOTS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The Monotone Smoothing of Scatterplots
Explore the source record for details and available documents.
Friedman, J.↗
Structure Perception in 3D Point Clouds
Understanding human perception is critical to the design of effective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the literature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projections of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rotation, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under rotation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns perceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
data analysis↗
Structure Perception in 3D Point Clouds: Preprint
Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.
data analysis↗
A multiscale landscape approach for prioritizing river and stream protection and restoration actions
River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.
54 ENVIRONMENTAL SCIENCES↗
Caerbannog Point Clouds
The Caerbannog Point Clouds provide point-sampled 3D models occluded in clouds of points. We synthesized the 3D point clouds from polygonal models, point-sampling the models and surrounding them in a point cloud such that the shape of the model is occluded in any 2D projection. We obscure our model-of-interest by repeatedly surrounding it with an amorphous cloud of points, giving the overall point cloud a structure of organic nature, like that of shrubbery. In a user study, participants were significantly better at identifying the models when visualized as 3D scatterplots under rotation than in axis-aligned 2D scatterplots. We provide three point-clouds, both occluded and unoccluded: the Stanford bunny, Utah Teapot, and OSG Cow.
97 MATHEMATICS AND COMPUTING↗
Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data
An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.
97 MATHEMATICS AND COMPUTING↗
Evaluation of passive microwave precipitation algorithms in wintertime midlatitude situations
The second intercomparison project of the Global Precipitation Climatology Project (GPCP) examined the estimation of midlatitude, cool-season precipitation. As part of that effort, the authors report here on the results of two microwave techniques, the Goddard scattering algorithm and the physical retrieval algorithm of Kummerow. Results from the estimation of instantaneous rain rate for five overpasses of the Special Sensor Microwave/Imager (SSM/I) are presented in a case study mode to illustrate both the strong and weak points of each technique. These five cases represent a sampling of the various types of precipitating systems observed. Results for the complete set of 20 swaths chosen by the United Kingdom Meteorological Office (UKMO) are then categorized by scatterplots and statistics of instantaneous radar versus microwave-estimated rain rate, rain no-rain contingency tables, and scatterplots of areal coverage of rainfall. Neither algorithm produced a good statistical correlation with the radar data, yet in general, both did well at determining rainy areas. Two reasons are suggested for the low correlation coefficients between both algorithms and the radar data. Time differences between the SSM/I overpass and the radar observations can occasionally account for some of the differences. The primary reason for the low correlations, however, appears to be the predominance of very light rain in the area of interest during the winter. Both algorithms are in good spatial agreement with the radar when the radar data are restricted to rates above 1 mm/h. When all radar rain rates are included, the radar areal coverage increases by as much as a factor of 10 in some cases. Because the Kummerow algorithm does not handle such low rain rates over land very well, and because the Goddard scattering algorithm uses 1 mm/h as the minimum reliably detectable rain rate, regimes that contain large areas of very light rain present inherent difficulties for these retrieval methods. Therefore, the proliferation of low rain rates observed during the experiment is the main contributor to low correlation coefficients and high root-mean-square differences. Mididentification of cold surface (e.g., snow cover) as precipitation was also a problem in several instances.
Negri, Andrew J.↗
Foreshock Langmuir Waves for Unusually Constant Solar Wind Conditions: Data and Implications for Foreshock Structure
Plasma wave data are compared with ISEE 1's position in the electron foreshock for an interval with unusually constant (but otherwise typical) solar wind magnetic field and plasma characteristics. For this period, temporal variations in the wave characteristics can be confidently separated from sweeping of the spatially varying foreshock back and forth across the spacecraft. The spacecraft's location, particularly the coordinate D(sub f) downstream from the foreshock boundary (often termed DIFF), is calculated by using three shock models and the observed solar wind magnetometer and plasma data. Scatterplots of the wave field versus D(sub f) are used to constrain viable shock models, to investigate the observed scatter in the wave fields at constant D(sub f), and to test the theoretical predictions of linear instability theory. The scatterplots confirm the abrupt onset of the foreshock waves near the upstream boundary, the narrow width in D(sub f) of the region with high fields, and the relatively slow falloff of the fields at large D(sub f), as seen in earlier studies, but with much smaller statistical scatter. The plots also show an offset of the high-field region from the foreshock boundary. It is shown that an adaptive, time-varying shock model with no free parameters, determined by the observed solar wind data and published shock crossings, is viable but that two alternative models are not. Foreshock wave studies can therefore remotely constrain the bow shock's location. The observed scatter in wave field at constant D(sub f) is shown to be real and to correspond to real temporal variations, not to unresolved changes in D(sub f). By comparing the wave data with a linear instability theory based on a published model for the electron beam it is found that the theory can account qualitatively and semiquantitatively for the abrupt onset of the waves near D(sub f) = 0, for the narrow width and offset of the high-field region, and for the decrease in wave intensity with increasing D(sub f). Quantitative differences between observations and theory remain, including large overprediction of the wave fields and the slower than predicted falloff at large D(sub f) of the wave fields. These differences, as well as the unresolved issue of the electron beam speed in the high-field region of the foreshock, are discussed. The intrinsic temporal variability of the wave fields, as well as their overprediction based on homogeneous plasma theory, are indicative of stochastic growth physics, which causes wave growth to be random and varying in sign, rather than secular.
Cairns, Iver H.↗
Interactive Visualization of High-Dimensional Petascale Ocean Data
We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48- degree “lat-lon cap” configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model’s floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/ vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.
Interactive↗
Microsegregation Measurement: Methods and Applications
Microsegregation is chemical variation at the microstructural level in a solidified ingot, which can cause undesirable effects on material properties. Its formation is driven by different levels of solute elemental solubility between solid and liquid phases, resulting in solute buildup or depletion in the liquid phase during solidification. Characterization of microsegregation can be essential for understanding its formation and removing it through heat treatment. Measurement is frequently carried out via scanning electron microscope (SEM), though metallographic analysis, mechanical testing and optical radiography have been used. SEM analysis can consist of point measurements on single dendrites, line scans across or along dendrites, elemental maps, and extended line-based or grid-based analyses extending over many dendrites, which can generate large amounts of data. Line-based or grid-based data can be analyzed using scatterplots of element concentrations to visualize segregation behavior and sorting/ranking of data by a single element or a combination of elements, to give compositional profiles as a function of extent of solidification. For both qualitative and quantitative analyses, effects of phase transformations and secondary phases need to be considered as well as sorting of measurement errors when generating compositional profiles. Applications of analysis include determination of partition ratios, examination of solute–element interactions, determination of effects of cooling rate and back diffusion, applications to freckling studies, validations of modeling, and development of heat-treatment profiles.
36 MATERIALS SCIENCE↗
Shortwave absorptance in a tropical cloudy atmosphere: Reconciling calculations and observations
The absorption of shortwave (SW) by clouds is a topic surrounded by contradictory reports and controversy. Some studies have shown large discrepancies between observed SW absorption and absorption predicted by models, while others have found no significant dfference. In this study, values of column SW absorptance obtained by combining collocated top-of atmosphere (TOA) and surface observations at an island site in the Tropical Western Pacific are compared to radiative transfer model (RTM) output. To compensate for the field of view difference between satellite and surface instruments, the surface data are averaged over time. Scatterplots and statistical measures show that there is a signficant discrepancy between models and observations with the RTMs apparently underestimating SW absorptance. In previous observational studies showing highly enhanced absorption compared to models, the slope of a linear fit to d*TOA/dT (the derivative of TOA albedo with respect to transmittance) was used to quantify cloud SW absorption while non-linearity of d*TOA/dT was interpreted as a sign of sampling issues. Here, the models produce a steeper slope (about -0.9) than observations (-0.6 to -0.8), indicating that models predict too little cloud SW absorption. However, when the surface observations are averaged over a longer period, their slope grows steeper and the root mean square di*erence between linear and quadratic fits to d*TOA/dT is reduced. This implies that insufficient averaging of surface data contributes to the observed SW absorption discrepancy. Reexamination of the observational data using the difference between cloud fraction estimated from satellite and surface measurements as an estimate of field of view mismatch supports this hypothesis. High mea sured absorptance values are shown to correspond to occasions of large field of view mismatch. When such data are excluded, the difference between the linear and quadratic fits is reduced and the slope of the best fit line becomes steeper. We conclude that averaging surface data over three hours or less is not always sufficient to eliminate sampling issues. However, the possibility that shortcomings of the RTMs contribute to the discrepancy in SW absorption values cannot be excluded.
58 GEOSCIENCES↗
Brightness of Solar Magnetic Elements As a Function of Magnetic Flux at High Spatial Resolution
We investigate the relationship between the photospheric magnetic field of small-scale magnetic elements in the quiet-Sun (QS) at disk center and the brightness at 214, 300, 313, 388, 397, and 525.02 nm. To this end, we analyzed spectropolarimetric and imaging time series acquired simultaneously by the Imaging Magnetograph eXperiment magnetograph and the SuFI filter imager on board the balloon-borne observatory SUNRISE during its first science flight in 2009, with high spatial and temporal resolution. We find a clear dependence of the contrast in the near ultraviolet and the visible on the line-of-sight component of the magnetic field, B {sub LOS}, which is best described by a logarithmic model. This function effectively represents the relationship between the Ca ii H-line emission and B {sub LOS} and works better than the power-law fit adopted by previous studies. This, along with the high contrast reached at these wavelengths, will help with determining the contribution of small-scale elements in the QS to the irradiance changes for wavelengths below 388 nm. At all wavelengths, including the continuum at 525.40 nm, the intensity contrast does not decrease with increasing B {sub LOS}. This result also strongly supports the fact that SUNRISE has resolved small strong magnetic field elements in the internetwork, resulting in constant contrasts for large magnetic fields in our continuum contrast at 525.40 nm versus the B {sub LOS} scatterplot, unlike the turnover obtained in previous observational studies. This turnover is due to the intermixing of the bright magnetic features with the dark intergranular lanes surrounding them.
79 ASTRONOMY AND ASTROPHYSICS↗
Evaluation of Visualization Heuristics
Heuristics have been used since the early 1990's in the Human Computer Interaction (HCI) domain, for evaluating user interfaces. Most notably, heuristics developed by Nielsen and Molich (1990) have been used by the HCI community. Forsell and Johansson (2010) used the same methodology as Nielsen and Molich and developed a set of 10 heuristics for information visualization. Currently, neither the information visualization or the visual analytics community has adopted these heuristics. However, several studies have been conducted using heuristics. Hearst et al. (2015) found that using the heuristics for visualizations along with asking questions about the data resulted in complementary results as the questions about the data could compensate for heuristics that were difficult to understand and apply. Heli Väätäjä et al. (2016) found that heuristics related to interaction, veracity, and aesthetics needed to be added to the Forsell and Johansson (2010) set. They also noted that a lack of domain knowledge caused the evaluators issues in conducting a heuristic evaluation. We conducted a controlled experiment to determine what factors might impact the expert evaluators' capability to conduct a heuristic evaluation of a static information visualization. In particular, we wanted to understand how their familiarity with the visualizations and their experience in conducting heuristic evaluations impacted their evaluations of visualizations. We recruited 10 participants who were domain experts in the visualization field each having experience with one of more of the following: user experience design or research, user interface development, and human computer interaction research. We used a heuristic set proposed by Forsell and Johansson. Participants were also asked to complete a demographic survey in which they rated their experience with each visualization type generally, their experience conducting heuristic evaluations, their experience using each visualization type to extract information, and their experience developing and creating each visualization type. The participants were shown a series of 5 common visualizations (Scatterplots, Sunbursts, Tree Maps, Parallel Sets, and Area Graphs) all displaying the VAST 2008 Mini Challenge Two- Migrant Boats data . Participants were given a suggested analytical question related to each visualization to keep in mind as they applied the 10 heuristics to each visualization. They were asked if they could find any usability problems in the visualizations and which heuristic(s) helped them to identify these problems. The participants were asked to rate how relevant each heuristic was for evaluating each visualization along with rating how confident they felt in their ability to apply the heuristic to evaluate each visualization. At the conclusion of the study, participants provided qualitative feedback on the usability issues of each visualization. Additionally, we collected eye tracking data on 6 of the 10 participants. We will be using this data to determine how long participants looked at the various visualizations and what parts of the visualizations they focused on. We had two hypotheses for this empirical evaluation: 1.The Forsell and Johansson heuristics of Orientation and help, Data set reduction, and Prompting are less useful for static visualizations because they require some interaction in order to test completely. 2.Participants that do not have experience with heuristic evaluation will provide lower evaluation scores for the heuristics compared to those that have experience. Related to hypothesis 1, as our study used only static visualizations, interaction-related usability challenges should be harder to identify. This should result in lower usefulness ratings for those heuristics. Preliminary results indicate that participants found it more difficult to apply heuristics to unfamiliar visualizations.
Williams, Ryan G.↗
Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets
Introduction Data normalization is crucial for multi-omics integration, reducing systematic errors and maximizing the likelihood of discovering true biological variation. Most studies assess normalization for a single omics type or use datasets from separate experiments. Few address time-course data, where normalization might bias temporal differentiation. In this study, we compared common normalization methods and a machine learning approach, Systematical Error Removal using Random Forest (SERRF), using multi-omics datasets generated from the same experiment—even from the same cell lysate. Objectives To develop a straightforward process to assess normalization effects and identify the most robust methods across multi-omics datasets. Methods We analyzed metabolomics, lipidomics, and proteomics datasets from primary human cardiomyocytes and motor neurons exposed to acetylcholine-active compounds over time. Normalization effectiveness was evaluated based on improvement in QC features consistency and observing the change in treatment and time-related variance. Results Probabilistic Quotient Normalization (PQN) and Locally Estimated Scatterplot Smoothing (LOESS) QC were identified as optimal for metabolomics and lipidomics, while PQN, Median, and LOESS normalization excelled for proteomics. These methods consistently enhanced QC feature consistency in metabolomics and lipidomics, and preserved time-related variance or treatment-related variance in proteomics, demonstrating their effectiveness and robustness. SERRF normalization, applied only to metabolomics in this study, outperformed other methods in some datasets but inadvertently masked treatment-related variance in others. Conclusion Our evaluation identified PQN and LoessQC as the top methods for metabolomics and lipidomics, and PQN, Median, and Loess normalization for proteomics, in multi-omics integration in a temporal study.
60 APPLIED LIFE SCIENCES↗
Characterizing forecastability of wind sites in the United States
With the rapid growth of wind power, managing its uncertainty and variability becomes critical in power system operations. Wind forecasting is one of the enablers to partially tackle challenges associated with wind power uncertainty. To improve the 'forecasting ability', defined as forecastability, different forecasting methods have been developed to assist grid integration of wind energy. However, forecasting performance not only relies on the power of forecasting models, but is also related to local weather conditions and (known as wind characteristics) wind farm properties. In this study, geospatial and instance spatial distributions of six wind characteristics and two forecasting error metrics are first analyzed based on 126,000 + wind sites in the United States. Forecasts in different look-ahead times are generated by using a machine learning based multi-model forecasting framework model and the Weather Research and Forecasting model. A forecastability quantification method is developed by characterizing the relationship between forecastability and wind series entropy using three regression methods, i.e., linear approximation, locally weighted scatterplot smoother nonlinear nonparametric regression, and quantile regression. It is found that the forecastability of a wind site can be successfully characterized by wind series characteristics, thereby providing valuable information at different stages of wind energy projects.
17 WIND ENERGY↗
ColorMap ND : A Data-Driven Approach and Tool for Mapping Multivariate Data to Color
A wide variety of color schemes have been devised for mapping scalar data to color. We address the challenge of color-mapping multivariate data. While a number of methods can map low-dimensional data to color, for example, using bilinear or barycentric interpolation for two or three variables, these methods do not scale to higher data dimensions. Likewise, schemes that take a more artistic approach through color mixing and the like also face limits when it comes to the number of variables they can encode. Our approach does not have these limitations. It is data driven in that it determines a proper and consistent color map from first embedding the data samples into a circular interactive multivariate color mapping display (ICD) and then fusing this display with a convex (CIE HCL) color space. The variables (data attributes) are arranged in terms of their similarity and mapped to the ICD’s boundary to control the embedding. Using this layout, the color of a multivariate data sample is then obtained via modified generalized barycentric coordinate interpolation of the map. In conclusion, the system we devised has facilities for contrast and feature enhancement, supports both regular and irregular grids, can deal with multi-field as well as multispectral data, and can produce heat maps, choropleth maps, and diagrams such as scatterplots.
97 MATHEMATICS AND COMPUTING↗
WE-FG-206-12: Enhanced Laws Textures: A Potential MRI Surrogate Marker of Hepatic Fibrosis in a Murine Model
Purpose: To compare enhanced Laws texture derived from parametric proton density (PD) maps to other MRI-based surrogate markers (T2, PD, ADC) in assessing degrees of liver fibrosis in a murine model of hepatic fibrosis using 11.7T scanner. Methods: This animal study was IACUC approved. Fourteen mice were divided into control (n=1) and experimental (n=13). The latter were fed a DDC-supplemented diet to induce hepatic fibrosis. Liver specimens were imaged using an 11.7T scanner; the parametric PD, T2, and ADC maps were generated from spin-echo pulsed field gradient and multi-echo spin-echo acquisitions. Enhanced Laws texture analysis was applied to the PD maps: first, hepatic blood vessels and liver margins were segmented/removed using an automated dual-clustering algorithm; secondly, an optimal thresholding algorithm was applied to reduce the partial volume artifact; next, mean and stdev were corrected to minimize grayscale variation across images; finally, Laws texture was extracted. Degrees of fibrosis was assessed by an experienced pathologist and digital image analysis (%Area Fibrosis). Scatterplots comparing enhanced Laws texture, T2, PD, and ADC values to degrees of fibrosis were generated and correlation coefficients were calculated. Unenhanced Laws texture was also compared to assess the effectiveness of the proposed enhancements. Results: Hepatic fibrosis and the enhanced Laws texture were strongly correlated with higher %Area Fibrosis associated with higher Laws texture (r=0.89). Only a moderate correlation was detected between %Area Fibrosis and unenhanced Laws texture (r=0.70). Strong correlation also existed between ADC and %Area Fibrosis (r=0.86). Moderate correlations were seen between %Area Fibrosis and PD (r=0.65) and T2 (r=0.66). Conclusions: Higher degrees of hepatic fibrosis are associated with increased Laws texture. The proposed enhancements improve the accuracy of Laws texture. Enhanced Laws texture features are more accurate than PD and T2 in assessing fibrosis, and can potentially serve as an accurate surrogate marker for hepatic fibrosis.
60 APPLIED LIFE SCIENCES↗